The Northern Transport Axis The Northern Transport Axis

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					                        European Commission
                       European Commission
              Directorate-General Energy and Transport
             Directorate-General Energy and Transport


   The Northern Transport Axis
   The Northern Transport Axis
       for for analytical support framework to monitor the implementation
 PilotPilotthe the analytical support framework to monitorthe implementation
    of the infrastructure and “soft” measures proposed by the High Level Group
of the infrastructure and “soft” measures proposed by the High Level Group
                               Final Report
                             Draft Final Report
                             December 2007
                                26.10.2007




                                                                 WSP Finland Ltd
                                                                 WSP Finland Ltd
                     European Commission
           Directorate-General Energy and Transport




     The Northern Transport Axis
    Pilot for the analytical support framework to monitor the
implementation of the infrastructure and “soft” measures proposed
                     by the High Level Group




                        Final Report

                        December 2007




                          WSP Finland
  The Northern Transport Axis - Pilot for the analytical support framework to monitor the implementation
                           of the infrastructure and “soft” measures proposed by the High Level Group
                                                                                                Preface




Preface

The project “Analytical support framework to monitor the implementation of the
infrastructure and “soft” measures proposed by the High Level Group” started in
October 2006.

This Report summarises the results of the project. The results include data collection
regarding the axis infrastructure and the related investments in Northern European
countries including also Germany and Poland as well as in Russia and Belarus.
“Exogenous Scenarios” estimating world trade trends were produced and used as
background when making transport forecasts. The forecasts were followed by a
bottleneck analysis and prioritisation of infrastructure projects in the study area. Also
a plan for the “Analytical Support Framework” to be piloted in monitoring the
development of the Northern Axis was prepared. Part of the collected data and results
is stored in the Commission’s TEN databases.

Another study “Implementation of TEN-T Guidelines 2004-2005” has been
simultaneously ongoing. It covers part of the specified data collection needs in EU
countries. These two projects have been coordinated because they feed data into the
same database.

The geographical scope of this study was extended to Russia. Data was collected in
Norway, Russia and Belarus in the same standard format that was applied in EU
countries. However, all such data did not exist or was not available although major
part of the data was successfully collected.

The study has been supervised by Mr. Francois Begeot, Ms. Catharina Sikow and Mr.
Gilles Carabin from DG TREN. The lead consultant for the project has been WSP
Finland Oy, where the project has been managed by Kari Lautso and Martti Miettinen.
WSP Finland has been assisted by a number of subconsultants and country experts to
whom we would also like to express our gratitude.




Helsinki, December 2007

Kari Lautso

Project Manager, WSP Finland Oy




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    The Northern Transport Axis - Pilot for the analytical support framework to monitor the implementation
                             of the infrastructure and “soft” measures proposed by the High Level Group
                                                                                         Table of Contents



TABLE OF CONTENTS
PREFACE............................................................................................................................................... 3
ABSTRACT ............................................................................................................................................ 7
SUMMARY, CONCLUSIONS AND RECOMMENDATIONS ........................................................ 8
1  THE TRANSPORT PROBLEM OF THE NORTHERN TRANSPORT AXIS –
UNDERSTANDING OF THE REQUIREMENTS ........................................................................... 22
    1.1          INTRODUCTION .................................................................................................................... 22
    1.2          DEVELOPMENT OF THE EUROPEAN TRANSPORT SYSTEM ..................................................... 22
    1.3          TRANSPORT STRATEGY OF THE RUSSIAN FEDERATION ........................................................ 24
    1.4          TRADE AND TRAFFIC FLOWS................................................................................................ 25
    1.5          INFRASTRUCTURE ................................................................................................................ 26
2       THE APPROACH ...................................................................................................................... 28
    2.1          INTRODUCTION AND OBJECTIVES......................................................................................... 28
    2.2          THE SCOPE ........................................................................................................................... 28
    2.3          METHODOLOGICAL ASPECTS ................................................................................................ 30
    2.4          WORK PROGRAMME ............................................................................................................ 32
    2.5          OUTPUT ............................................................................................................................... 33
    2.6          TIME SCHEDULE................................................................................................................... 33
    2.7          PROJECT STRUCTURE AND DISTRIBUTION OF RESPONSIBILITIES .......................................... 34
3       THE ANALYTICAL SUPPORT FRAMEWORK .................................................................. 35
    3.1          OBJECTIVES ......................................................................................................................... 35
    3.2          METHODS............................................................................................................................. 35
    3.3          ORGANISATION AND MANAGEMENT..................................................................................... 38
    3.4          RESOURCES .......................................................................................................................... 45
4   ANALYSIS OF INFRASTRUCTURE ALONG THE NORTHERN AXIS -
INFRASTRUCTURE........................................................................................................................... 47
    4.1          DATA COLLECTION .............................................................................................................. 47
    4.2          ANALYSIS OF INFRASTRUCTURE........................................................................................... 52
5   ANALYSIS OF INFRASTRUCTURE ALONG THE NORTHERN AXIS –
INVESTMENTS AND FINANCIAL COMMITMENTS ................................................................. 78
    5.1          DATA COLLECTION .............................................................................................................. 78
    5.2          INVESTMENTS IN THE NORTHERN AXIS INFRASTRUCTURE ................................................... 79
    5.3          INVESTMENTS RELATIVE TO GDP ........................................................................................ 81
6       TRANSPORT DEMAND – EXOGENOUS SCENARIOS ..................................................... 83
    6.1          RESEARCH FRAMEWORK ...................................................................................................... 83
    6.2          GROWTH PROSPECTS OF THE WORLD.................................................................................... 85
    6.3          GROWTH PROSPECTS OF THE RESEARCH AREA ..................................................................... 89
    6.4          RISKS ................................................................................................................................... 94
    6.5          NOMINAL AND REAL GDP FORECASTS ................................................................................. 95
    6.6          EXPORT FORECASTS ............................................................................................................. 98
    6.7          RUSSIAN SCENARIOS .......................................................................................................... 101
    6.8          RUSSIAN TRADE MODELLING IN DIFFERENT SCENARIOS ..................................................... 103
7       TRANSPORT MODELLING ................................................................................................. 105
    7.1          SCOPE AND OBJECTIVES OF THE MODELS ........................................................................... 105
    7.2          FREIGHT ............................................................................................................................. 106
    7.3          PASSENGER TRANSPORT .................................................................................................... 127
8       THE BOTTLENECK ANALYSIS.......................................................................................... 146
    8.1          PRINCIPLES OF THE SYSTEM EVALUATION .......................................................................... 146


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                            of the infrastructure and “soft” measures proposed by the High Level Group
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    8.2          ANALYSIS PROCESS ............................................................................................................ 152
    8.3          ROAD SYSTEM .................................................................................................................... 153
    8.4          RAILWAY SYSTEM .............................................................................................................. 159
    8.5          BORDER CROSSINGS (ROAD AND RAIL)............................................................................... 166
    8.6          PRIORITY PROJECTS............................................................................................................ 172
    8.7          SYSTEMIC EFFECTS ............................................................................................................ 180
9  MAJOR ENVIRONMENTAL ISSUES RELATED TO THE DEVELOPMENT OF THE
NORTHERN AXIS ............................................................................................................................ 183
    9.1          EMISSIONS ......................................................................................................................... 183
    9.2          NATURA 2000 NETWORK................................................................................................. 184
    9.3          URBAN AREAS .................................................................................................................... 185
APPENDICES .................................................................................................................................... 187
APPENDIX 1: COUNTRY REPORTS ............................................................................................ 189
APPENDIX 2: BASIC ROAD AND RAIL PARAMETER AND PERFORMANCE DATA...... 241
    ROADS ........................................................................................................................................... 241
APPENDIX 3: DATABASE REPORT............................................................................................. 256
    OVERVIEW ....................................................................................................................................... 256
    THE TEN-NORTH DATABASE ........................................................................................................... 256
    THE DATABASE MODEL .................................................................................................................... 256
    DATA VALIDATION ........................................................................................................................... 275
APPENDIX 4: EVALUATION SYSTEM OF ROADS AND RAILWAYS.................................. 277
    ROADS ........................................................................................................................................... 277
    RAILWAYS .................................................................................................................................... 281
APPENDIX 5: TRANSPORT MODELLING ................................................................................. 283
    FREIGHT TRANSPORT ................................................................................................................ 283
    PASSENGER TRANSPORT .......................................................................................................... 287




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  The Northern Transport Axis - Pilot for the analytical support framework to monitor the implementation
                           of the infrastructure and “soft” measures proposed by the High Level Group
                                                                                                Abstract




Abstract
The Northern Axis is one of the five Trans-European transport Axes defined by the
“High Level Group” in 2005 and presented in the report “Network for Peace and
Development”. The Axis is the main trade and transport connection between Russia
and the EU countries. The Axis consists of main rail and road corridors starting with
the Berlin Moscow corridor in the south and ending with St. Petersburg – Narvik
corridor in the north.

The aim of this study has been to set up – as a pilot for the Northern Axis – the
analytical support framework that would enable monitoring the implementation of the
measures proposed by the High Level Group. The methodology and principles of the
analytical framework should be easily extendable to the other Axes.

To do this the project has:
   • Collected data on infrastructure, traffic, transport regulations, operations etc.
   • Analysed the current condition of the infrastructure
   • Analysed investments and financial commitments
   • Built long term exogenous scenarios describing future trade demand
   • Modelled the current and future transport demand
   • Analysed current and future physical and non-physical bottlenecks
   • Defined priority projects
   • Made plans and recommendations for the organisation, management and tasks
       for establishing the Northern Axis cooperation
   • Developed and piloted standard methods that could be used in other Axes for
       collecting and analysing data, assessing bottlenecks and defining priority
       projects in order to produce comparable results for other axes

Part of the collected data is stored in the Commission’s TEN-T database.

The work has had an exploratory nature with an emphasis in developing the system
for the Analytical Framework. The priority lists made for individual projects are
subject for negotiation process after the project.

The analyses show that the transport demand will roughly double by 2020 between
the EU and Russia in all studied scenarios creating increasing pressure for the
infrastructure development. However, even after implementation of the current
extensive infrastructure plans, bottlenecks will remain on the transport networks.
Clearly the most severe problems are concentrated on border operations resulting to
long waiting times. This is due to differences in administrative and technical systems
of neighbouring countries.

Thus, there is an interest and challenge for both non - EU and EU countries along the
Northern Axis to improve their transport connections. The report recommends the
dialogue for establishing the Northern Axis cooperation be started along the lines
drafted in the report.


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  The Northern Transport Axis - Pilot for the analytical support framework to monitor the implementation
                           of the infrastructure and “soft” measures proposed by the High Level Group
                                                           Summary, Conclusions and Recommendations




Summary, Conclusions and Recommendations
Summary and conclusions
The scope and objectives of the study

The Northern Axis is one of the five Trans-European transport Axes defined by the
“High Level Group” in 2005 and presented in the report “Network for Peace and
Development”. The Northern Axis consists of the following road and rail corridors
which are directly linked to the TEN-T networks:
   1. Narvik-Haparanda/Tornio-St. Petersburg
   2. Helsinki-St. Petersburg-Moscow
   3. Tallinn-St. Petersburg
   4. Ventspils-Riga-Moscow
   5. Klaipeda-Vilnius-Minsk
   6. Kaliningrad-Vilnius
   7. Berlin-Warsaw-Minsk-Moscow
   8. Oslo- Swedish Border (direction Gothenburg)
   9. Oslo- Swedish Border (direction Stockholm)

Accordingly, the geographical scope of the project has covered the following EU
countries: Sweden, Finland, Estonia, Latvia, Lithuania, Poland and Germany and the
following non-EU countries: Norway, Russia, Belarus.




Transport corridors passing the Northern Axis area



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  The Northern Transport Axis - Pilot for the analytical support framework to monitor the implementation
                           of the infrastructure and “soft” measures proposed by the High Level Group
                                                           Summary, Conclusions and Recommendations




The aim of this study was to set up – as a pilot for the Northern Axis – the analytical
support framework that would enable monitoring the implementation of the measures
proposed by the High Level Group.

In brief the project has:
    • Collected data on infrastructure, traffic, transport regulations, operations etc.
    • Analysed the current condition of the infrastructure
    • Analysed investments and financial commitments
    • Built long term exogenous scenarios describing future trade demand
    • Modelled the current and future transport demand
    • Analysed current and future physical and non-physical bottlenecks
    • Defined priority projects
    • Made plans and recommendations for the organisation, management and tasks
        for establishing the Northern Axis cooperation
    • Developed and piloted standard methods that could be used in other Axes for
        collecting and analysing data, assessing bottlenecks and defining priority
        projects in order to produce comparable results for other axes

The above listed issues are briefly discussed below.


The Analytical Support Framework

The Analytical Support Framework (ASF) is defined as a system that enables the
monitoring of the implementation of the measures proposed by the High Level Group.
The methodology and principles of the analytical framework should be easily
extendable to the other Axes identified by the Group.

The Northern Axis has some specific characteristics, which must also affect the
design of its framework. One such fundamental feature is the Axis’ all-encompassing
objective to serve passenger and goods transport between Russia and the EU. Another
one is the fact that only one non-EU country, namely Russia, account for roughly half
of the network length and investments. Thus, the establishment of an ASF becomes a
multifaceted problem. The process must address in a balanced way the following
questions:
    • What are the working methods that can be sustained in the long-term
    • What kinds of resources (financial and human) will be made available
    • How to organise the axis cooperation and management functions so that the
        necessary activities can be carried out within the available resources

The working methods comprise several tasks that are shown in the table below.




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  The Northern Transport Axis - Pilot for the analytical support framework to monitor the implementation
                           of the infrastructure and “soft” measures proposed by the High Level Group
                                                           Summary, Conclusions and Recommendations




                                        DATA COLLECTION
    EU-Member states                    Non-EU countries                    International traffic
    TEN-T:                              Infrastructure                      Transport models
    •     Infrastructure                Investment programs
    •     Investments                   Domestic traffic
    Traffic forecasts                   Safety
                                        Environment
                                        Regulations


                                 TRANSPORT AXIS DATABASE
                                      Links and nodes
                                   Infrastructure (roads, rail, borders)
                           Current and forecast traffic (road, rail, international)
                                       Planned investment projects
                                    Environmentally sensitive areas
                                               Safety data


                                       TRAFFIC FORECASTS
                               International traffic (passengers and freight)
                                 Domestic traffic (passengers and freight)


                                       ANALYSIS METHODS
                                  Criteria for evaluations and selections
                                                   Models
                                                Comparisons


                                       REPORTING SYSTEM
                                                  Reports
                                                Action plans
                                                  Projects


Analysis and monitoring tasks of the Analytical Support Framework (ASF)

Resources. Methods and organisation cannot be selected without considering to some
degree the financial resources that are made available for the cooperation. The natural
solution to the financial problem is that the partners, mainly the axis country
ministries of transport, allocate the needed financial resources for the use of the
cooperation framework. In reality, any agreement on this matter may be difficult to
reach. For guaranteeing for the Axis cooperation a quick and strong start the best
option is that the Commission would cover the costs for the first years.

Organisation. One of the main considerations in setting up an ASF management
system revolves around the split of responsibilities between the three main parties: (i)
the Commission, (ii) Axis Steering Committee/Secretariat, and (iii) transport
ministries and authorities of the axis countries. It is clear that the responsibilities
should not overlap and the parties should see them in a similar way. Thus, the core
questions that affect the effectiveness of the axis cooperation in the long run are:
    • the degree to which each party is willing to yield authority to an international
        cooperation framework.
    • resources that each party wants to devote to the axis cooperation.




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  The Northern Transport Axis - Pilot for the analytical support framework to monitor the implementation
                           of the infrastructure and “soft” measures proposed by the High Level Group
                                                           Summary, Conclusions and Recommendations




The study proposes three possible models for the axis management building mainly
on the experience of the Pan-European Transport Corridors and Areas:
        Option 1 – light organisation concentrating on general axis cooperation. The
        nature of cooperation resembles that of the current Pan-European Transport
        Corridors and Areas.
        Option 2 – strong organisation focused on results. In this option the axis
        management exerts leadership and it has a mandate to accomplish the axis
        development.
        Option 3 – two-tiered organisation. This option is a combination of the two
        options above. The option provides a two-tiered approach: (i) light management
        organisation for addressing general objectives and policy issues, and (ii) strong
        resources to employ adequate human resources and expertise for each task and
        project when they are ready.

The axis cooperation should not be a closed entity and an end in itself, but it rather
should be open to other either already existing or new cooperation frameworks, which
have the same goals, such as:
   • Regional cooperation forums
   • Cooperation between national transport authorities across the borders
   • Cooperation between transport operating companies utilising the Axis roads
       and railways
   • The Commission’s cooperation with the Russian authorities, namely the EU-
       Russia transport dialogue and its permanent working groups
   • International Financial Institutions

The secretariat is an important entity of the axis framework, which is tasked to keep
the momentum in the cooperation. Therefore, setting up the secretariat deserves
specific attention.

Lastly, after the Axis cooperation framework has been established, the main areas
needing joint actions are the following:
   • Rapprochement in the general understanding of the Axis objectives between
        the parties
   • Border crossings for road transport of freight
   • Harmonisation of heavy goods vehicle standards and improving road safety,
        bearing capacity and maintenance
   • Railway harmonisation and improving competitiveness of rail transport


Data collection and analysis of infrastructure

The Commission launched two studies: the Analytical framework pilot study and the
TEN-T implementation guidelines study for the period 2004-2000, approximately at
the same time. The latter study has collected basic infrastructure data of the TEN-T
network in the current EU member states, while the analytical framework pilot study
collected data, which the TEN-T implementation study did not cover, namely:
     • Additional data needed for identifying bottlenecks and analysing projects


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  The Northern Transport Axis - Pilot for the analytical support framework to monitor the implementation
                           of the infrastructure and “soft” measures proposed by the High Level Group
                                                           Summary, Conclusions and Recommendations




    •    All necessary information about border crossings
    •    Domestic traffic volumes in each of the axis countries (current and forecast)
    •    TEN-T type data of the non-EU Axis countries (Belarus, Russia and Norway)




Road (left) and railway (right) branches of the Northern Axis included in this study

The basic characteristics of the road and rail networks of the Northern Axis are:
   o The Northern Axis comprises about 7 000 km of roads and another 7 300 km
       of railways. The majority of the network length (55%) is located outside the
       EU, 40% in Russia alone.
   o The railway system is composed of two more or less incompatible systems:
       one having the wide track gauge (76% of length) of the Russian origin
       (1520mm), and another having the standard European track gauge (1435mm)
       (24% of length).
   o The biggest legacy problem of railway transport on the Axis is the two
       different track gauges. Other problems arise from different power and
       signalling systems.
   o The road network is divided as well, but not as clearly as the railways. In
       general, the roads in the west have been built to a higher standard as in the
       east. Also, the traffic flows are heavier there. However, this is changing fast
       with the rapid motorisation and the very large new investments in roads,
       particularly in Russia and Poland.
   o Problems of road traffic are fewer than those of the railways. Some problems
       arise from vehicle weights, which are less in Russia (38 tons) than in the EU
       (44 tons).

New borders rose in the region early 1990s, which more recently have again been
eradicated. Tight borders with full controls are still at the external border of the EU
with Belarus and Russia.




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  The Northern Transport Axis - Pilot for the analytical support framework to monitor the implementation
                           of the infrastructure and “soft” measures proposed by the High Level Group
                                                           Summary, Conclusions and Recommendations




Investments

The Northern Axis roads and railways belong to the trunk system of each country.
They are important both for domestic and international traffic. Therefore, the
countries invest heavily in this portion of their transport infrastructure. The major
projects on the Axis exceeding €1 billion are:
    • Construction of motorway between Moscow and St. Petersburg in Russia, €6,9
        billion
    • Construction of A2/E30 motorway in Poland, €1,9 billion
    • Upgrading the entire railway in Latvia, €1,7 billion
    • Modernization of the railway in Poland, €1,1 billion

By the year 2020, the total identified expenditures amount to €21,2 billion, all
countries combined. Two big investor countries are Russia (46%) and Poland (28%).
In this period, the level of investments is typically less than 0,3%of the GDP of an
Axis country. Highest shares are for Latvia 1,7% and Lithuania 0,7%.

86% of the identified investments are planned for implementation in the period 2007-
2013. 65% of them are allocated for the roads, 35% for the railways.

The Axis Branch 2 (Helsinki-Moscow) in Russia and Branch 7 (Berlin-Moscow) in
Poland get by far the biggest share of the total investments, 42% and 34%
respectively.

 Investments by Country (MEURO)   Investments by Branch (MEUR)

                                                BR9              BRANCH                          Total     Share
            BY EE                               0%               Br 1 Narvik-St. Petersburg      1259,2      5,8 %
         SE 2 % 1 % FI                    BR8
         1%         4 %DE                 2%       BR1           Br 2 Helsinki-Moscow            9165,3     42,1 %
                       2%                          6%
                                                                 Br 3 Tallinn-St. Petersburg      300,3      1,4 %
                             LV
                             9%    BR7                           Br 4 Ventspils/Riga-Moscow      1853,7      8,5 %
                             LT    34 %                          Br 5 Klaipeda/Vilnius-Moscow     853,0      3,9 %
  RU                         5%                          BR2     Br 6 Kaliningrad-Kaunas          377,5      1,7 %
 46 %                        NO                          42 %    Br 7 Berlin-Warsaw-Moscow       7442,0     34,2 %
                             2%
                                    BR6                          Br 8 Olso-Stockholm              530,0      2,4 %
                                    2%                           Br 9 Oslo-Copenhagen                0,0     0,0 %
                                      BR5 BR4 BR3                TOTAL                          21781,0    100,0 %
                       PL
                                      4% 9% 1%
                      28 %


Investments by country and by branch in the Northern Axis 2007-2020



Exogenous scenarios, development of GDP and trade

Transport demand can be explained by economic factors. Exogenous scenarios were
made to describe the political and economic development.

Economic growth has been divided into two components: productivity growth and
growth of labour input measured by employed people or population. Growth rate is
estimated at a little bit over three percent per year in the world level. Two thirds of
this is explained by productivity growth and one third by population growth.
Population growth will decrease in the future and the growth in GDP, accordingly.



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  The Northern Transport Axis - Pilot for the analytical support framework to monitor the implementation
                           of the infrastructure and “soft” measures proposed by the High Level Group
                                                           Summary, Conclusions and Recommendations




The growth rates and growth prospects of the study area of Central, Northern and
Eastern Europe differ considerable between countries and groups of countries. In most
of the old EU-countries the problem is low productivity growth. In EU-15
productivity has increased only by 1.1 percent annually in 2000-2007. In the new EU-
countries and other Eastern European countries the problem is low fertility. Fertility is
lower than anywhere in the world.

Forecasts for the two components of growth, productivity and employed people, were
made separately. According to the prognosis, the growth rates in new EU-countries
are about two percentage points higher than in old EU-countries. It follows that the
new EU-countries almost reach the level of living of old EU-countries by 2030. Baltic
countries may even exceed it. Many risks, which may prevent the implementation of
the forecasts, were analysed. Assuming risks materialize we obtain many alternative
scenarios for the main forecast. Some of them have been quantified.

Export forecasts were derived from GDP forecasts by taking into account the change
in export rates (exports as a percentage of GDP). Generally export rates are increasing
because of technology change and globalisation. Correspondingly, exports grow more
than GDP in most cases. Exports grow 1.5 fold in the old EU-countries and 2.4 fold in
the new EU-countries by 2030. At the same time GDP grows 2.1 fold in new EU-
countries and 1.3 fold in the old EU-countries. Country specific export/import
forecasts were also made.

Three possible scenarios were presented for Russia, from which the most probable
was utilised in calculations. In Russia export rate is increasing only in the minimum
scenario. Despite this, exports grow considerably more in the maximum scenario. In
the minimum scenario Russia exports mainly energy and raw materials. In the
maximum scenario export is many-sided and Russia achieves good competitive
position in several fields. In the most probable scenario Russian exports grow 2.4 fold
by 2030.

Finally the growth rates for different commodity groups have been estimated. These
serve as the basis for transport forecasts. Strong increase in international trade
presupposes corresponding increase in performance of the transport system in the
research area.


Transport forecasts

The main focus of the study was on the international freight transport, although
passenger transport was examined through model-based databases where feasible. The
time span of the modelling study covered forecasts to 2010 and 2020.

The freight transport volumes will rapidly increase within EU and between EU,
Russia and other continents. The growth is estimated at 82% from 2000 to 2020. In
tonkilometers the growth is even bigger, 94%. The system wide transportation costs
will increase 108% between 2000 and 2020. This growth will be a big challenge also



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  The Northern Transport Axis - Pilot for the analytical support framework to monitor the implementation
                           of the infrastructure and “soft” measures proposed by the High Level Group
                                                           Summary, Conclusions and Recommendations




to the present infrastructure and its capacity. Increasing Russian freight will affect
every available border station in the Northern Axis countries also in the future.




Assigned international transport volumes on rail network in 2000 and 2020
(1000 tons/a, <0.5 million tons/a not shown)




Assigned international transport volumes on road network in 2000 and 2020
(1000 tons/a, <0.5 million tons/a not shown)


Also the sea transports increase heavily: in the Southern Baltic there will be ca. 135
million tons/a bulk more in 2020 than in 2000. This is mainly due to Russian traffic


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  The Northern Transport Axis - Pilot for the analytical support framework to monitor the implementation
                           of the infrastructure and “soft” measures proposed by the High Level Group
                                                           Summary, Conclusions and Recommendations




from the bottom of Gulf of Finland (ca. 90 million tons bulk/a). Liner transport will
add to the figure some tens of million tons/a more. The sea transport in Baltic will
double in volumes. Because most of the bulk transport is oil, this increases also the
environmental risks. In this respect, the Motorways of Seas in the Baltic is an
important initiative if it can help avoiding accidents, providing safety for freight and
protect the environment more efficiently.

An economic recession in Russia would not necessarily decrease the freight flows in
the Northern Axis area: Russia would transport more oil and raw materials to support
its economy. The transport problems might be even more challenging in this case to
solve.

Rail transport’s share of mileage is 1/3. It produces only 10% of emissions. Sea
transport, which produces most emissions, has slightly bigger share of emissions than
of mileage, ca 50%. Road transport’s share is ca 17% of mileage but 35% of
emissions. Even if freight grows rapidly the relative shares by mode remain about the
same during the forecast period.

The used approach in freight demand modelling and analysis produced viable results,
which correspond on the system (macro) level to the observed values (volumes, costs,
route/mode choice and changes and interactions) and also the official statistics. The
approach is applicable for system wide, EU-level evaluations and assessments (policy
and infrastructure changes, scenarios, sensitivities, environmental impacts etc.) The
system now serves the Northern Axis area. It could be adapted for other European
areas, as well.

Passenger travel forecasting has focused on international passenger flows on the
Northern Axis corridors. The approach to estimate the current and the future travel
demand was adapted to cope with the current deficiencies in the data. Passenger
demand forecasting first examined passenger travel growth at the country level, then
at country to country level, and finally at the key corridor level based on all the
information assembled during the study.

Passenger traffic including business, tourism, personal visits and leisure has been
gradually increasing in many Northern Axis corridors, notably between Russia and
the EU Member States. Business travel is expected to grow as trade links between
these countries are further strengthened. Employment of the population from the
Baltic countries as well as Poland in the other EU countries is increasing steadily,
which would also lead to growth in travel.

The SCENES-based passenger travel demand forecast suggests fast passenger demand
increase in the EU10 New Member States, in particular in Baltic States where the total
passenger travel demand (in passenger km) will grow by around 44% by 2020. Train,
bus/coach passenger journeys are expected to decline in the Baltic States, whilst
having a moderate growth in Sweden, Finland and Germany. On the other hand, car
journeys will rise sharply in the Baltic States. Over the forecasting period, the
population is stable in EU15 and slightly declining in some EU10 countries, so the



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  The Northern Transport Axis - Pilot for the analytical support framework to monitor the implementation
                           of the infrastructure and “soft” measures proposed by the High Level Group
                                                           Summary, Conclusions and Recommendations




growth of passenger demand stems mainly from the increasing mobility of the
individuals.

Forecasts on long distance cross border journeys (based on ETIS dataset) indicate a
continuous growth of air passenger demand in the Northern Axis area with the highest
rate of growth in demand being from the Baltic States and Belarus. On road there is a
moderate increase in longer road journeys between Sweden-Russia as well as
Germany-Belarus-Russia. Scandinavian countries will generate a higher amount of
long distance travel towards Poland and Germany.

Road traffic forecasts on key Northern Axis corridors and borders were developed
based on data from national road authorities. The growth of passenger related traffic is
predicted to be moderate to high on corridors in Latvia and Russia. It will be lower on
the corridors between Scandinavian countries, and moderate to high between
Scandinavian countries and Russia.

In terms of the rail travel, the Helsinki-Moscow corridor is the most important link of
the Northern Axis. There have been 267,000 passengers travelling between Finland
and Russia in the year 2005. Lithuania is becoming an important transit corridor for
the rail passenger flows from Kaliningrad to Russia, with the percentage of
international journeys ending or originating in the country reducing from 49% in 1995
to 14% in 2001. As the share of car travel is becoming more dominant in the Baltic
countries, the scope may be limited for future rail passenger demand growth.

Main passenger flows between Russia, Germany, Poland, and Baltic States use air
connections. The main international air hubs in the Northern Axis are in Helsinki, St.
Petersburg and Stockholm. Low-cost carriers have entered the Baltic aviation market.
The passenger numbers have almost doubled since these states became members of
the EU. Once the current aviation bilateral agreements are renegotiated, new access to
other Russian cities than Moscow could widen the scope for competition in air travel
in these areas.

Maritime transport has not been the main focus of the study. Nevertheless it is
important to mention that the passenger route Tallinn to Helsinki has developed into
one of the major sea corridors in the study area.

Whilst the approach chosen to forecast passenger demand is appropriate given the
information currently available, the study also highlights the importance in enhancing
passenger data collection and monitoring in the future.


Bottleneck analysis and project prioritisation

The basic rationale for analysing the Northern Axis roads and railways is that the Axis
network should be able to carry, at a reasonable speed, freight trains and heavy
commercial vehicles that utilize standard technologies and meet vehicle dimensions
and weights adopted in the EU. Secondly, the primary focus of the future



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development of the transport axes should be on international trade flows and
international business related travel.

From the above it follows that the analysis of the Northern Axis deficiencies and
bottlenecks focuses on the performance of road and railway links and border
crossings, which is measured using the following evaluation criteria:
    • Level of regulatory harmonisation
    • Mobility and/or line speeds
    • Capacity utilisation
    • Road safety
    • Environment

A very robust system for identifying bottlenecks has been developed. It showed to
work well with the Northern Axis data. Three different evaluation methods have been
developed due to differences in data availability: (1) border crossings, which have the
best data available, (2) roads for which the indicators are either available or can be
estimated, and (3) railways which have the poorest data and only the locations of
capacity constraints can be identified. These methods have been used to identify
infrastructure development needs in addition to those already identified by national
authorities.

By far the biggest bottlenecks of road transport are the border crossings. It can be
estimated that 98% of the total delay to international heavy goods transport occur at
the Northern Axis borders. By a great margin the most constrained are road borders,
particularly those that have had an average waiting times this year either near or often
well above 24h. Those borders are:
    • Narva-Ivangorod (EE-RU)
    • Vaalimaa-Torfjanovka (FI-RU)

Other high delay borders are those that have waiting times of close to 10h:
   • Terehovo-Burachi (LV-RU) and
   • Kybartai-Chernyshevskoe (LT-Kaliningrad/RU)

Road congestion, excepting the borders, is not generally a big problem, particularly
after the already started and planned major motorway projects have been completed in
Russia and Poland. Remaining problems of congestion and substantial traffic delay
occur only on the approach roads to major metropolitan areas, such as Moscow. There
are also some other congested areas, where a heavy commercial traffic runs through a
small town town, such as Narva, Estonia. These locations are obvious candidates for
additional improvement projects that were not listed by the transport authorities of the
Axis countries.

On the Axis railway system there are a number of capacity constraints, which
however, will largely be improved with the identified investment programs already by
2013. In addition, there exist one missing link (Ledmozero-Kotchkoma, RU), where
the construction needs to be completed.



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By 2020, new railway capacity problems appear to arise due to traffic growth, but
even more so due to Russia’s intention to channel more traffic through its own ports.
Potentially congested sections will include St. Petersburg-Ust Luga port, Moscow-
Velikie Luki-Ust Luga port, and the railway Minsk-Kaliningrad, all in Russia.




ROADS: Current bottlenecks, programmed projects and bottlenecks in 2020 after
implementation of the programmed projects




RAILWAYS: Current bottlenecks, programmed projects and bottlenecks in 2020 after
implementation of the programmed projects




Situation of Road and Rail border stations




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Environmental issues

The emissions of the transport system will grow together with growing volumes.
Additionally, the growing average distances and congestion add to the increase of
emissions. The emissions of international transports in the system will almost double
by 2020. The emissions/tonkm are biggest in road transport mode. Increase of the
road transport operation costs would rapidly shift transports to other modes assuming
that there were enough capacity.
Railways and roads are in many places at or near NATURA sites and the growing
traffic will negatively affect these sites. In some cases the new alignments of roads or
railways are in potential conflict with NATURA sites. These cases have to be studied
in detail locally.

Noise, emission, safety etc. problems are likely to emerge and grow especially in
urban areas. Growing traffic together with growing urban areas will clearly increase
the number of people exposed to these problems. The share of urban areas has been
separately analysed in the Northern Axis transport network.

Finally, the rapidly increasing sea traffic and oil export in Gulf of Finland and the
Baltic Sea is experienced as a big and growing environmental threath.

Recommendations
The recommendations for setting up the Northern Axis Analytical Framework are as
follows:

Methods
Project evaluation, selection and ranking can well be carried out using the methods
developed in this study. Due to differences in data availability between the main
infrastructure systems the report presents three analysis methods, one for each: (1)
border crossings, (2) roads, and (3) railways. These methods are proven very robust
and they produced credible results when using the Northern axis data.

Organisation
It is proposed that Option 3 described above will be selected as the basic model for
organising the Northern Transport Axis cooperation. The reasons are obvious. The
Northern Axis development is likely to require considerable freedom and flexibility
with regard to time and approaches that will eventually be adopted in the Action Plan.
Specifically, many of the Northern Axis policy objectives should be developed further
and political disputes resolved so that there will be a common approach, which is
acceptable to all parties. On the other hand, Option 3 allows starting the more
concrete work in areas that are already mature and generally accepted. These areas,
however, must first be jointly verified.

One important additional feature of Option 3 is that all other existing cross-border
cooperation working groups and task forces are brought under the axis umbrella. This
concerns first of all the existing Steering Committees of the Pan-European Transport
Corridors and Areas (Corridors 2, 9 and BEATA). Secondly, the permanent working

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groups of the EU-Russia transport dialogue should be brought to bear in the Axis
cooperation.

The advantage of these and other groups is that they are already set up and have
invariably good contacts and ways of cooperation. What they often lack, and what the
axis framework should offer to them, are high-level support as well as financial and
technical assistance.

Resources
The Axis partners must see to it that the axis cooperation is funded properly, which
concerns both the management costs as well as the variable study and project
preparation costs. In this important respect it is recommended that the Commission
would cover the cost of the establishment of Axis cooperation for the first
development period.

In addition, it is advisable to explore the potential of the new ENPI instrument of the
Commission when it comes to other supporting transport studies and project
development phases in the region.

How to proceed
After the parties and the Commission have agreed to establish the Northern Axis
cooperation, signed an agreement of cooperation, and set up the organisation,
guidance for further activities are obtained from several Chapters of this report. They
include, among others, but are not limited to the following:
    1. The Steering Committee should start the process of general rapprochement
       among the parties, which includes the clarification of specific Axis
       development objectives that have been identified in this report. This phase
       should lead to an Action Plan of the Axis
    2. Start of the dialogue with other and parallel transport forums and working
       groups in the region
    3. With the help of the above forums/working groups setting up specific working
       groups for conducting highly practical cooperation in the following fields:
           • Road border crossings, which constitute the most pressing problem for
               the Axis transport system. As there are existing working groups on
               regulatory and legal side of this problem, the new axis cooperation
               might concentrate more on technical and managerial improvements of
               road borders at a very concrete level.
           • Railway transport with focus on harmonising operations and
               terminal/border crossing functions so that the railways can maintain
               and increase their competitiveness against road transport over time. An
               important element in this is the establishment of unit trains between
               main destinations.
           • Road transport, which should focus on harmonising vehicle standards
               on one hand and on strengthening the roads on the other. Related
               matters concerns reliability of road transport which can be achieved
               with better road maintenance and information. Other areas that need
               attention are road safety and protection of the environment.



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1 The Transport Problem of the Northern Transport Axis –
  Understanding of the Requirements

1.1   Introduction
The Northern Transport Axis is, first of all, the trade and transport connection
between Russia and the EU countries. In addition, trade flows to/from Far East using
the Trans-Siberian land-bridge play an increasing role, but in terms of volume and
value the Russian flows dominate the transport market by a large margin.

Not to be overlooked, the Axis serves also the EU trade with Belarus, but the
generated flows are of minor importance when considering any transport investment
needs on the EU side.

The Axis covers also the EU trade and traffic with Norway, which is not insignificant.
In terms of improvement measures and investments the connections with Norway are
in a different category and may not merit alone the study in question.

All in all, the passenger and freight flows using the Northern Transport Axis are
largely determined by the development of trade and social contacts between the EU
Member States and Russia, and the political decisions and transport policies that are
applied at any given time by these two parties.

1.2   Development of the European Transport System
In the past decade or so, the EU has defined and developed both its internal (TEN-T)
and external transport corridors (Pan-European Transport Corridors and Areas). After
the enlargement of May 2004, most of the Pan-European system fell inside the
Community and became integrated into the TEN-T system.

The most recent guidelines for the development of the trans-European transport
network (TEN-T) were adopted by the Council and the European Parliament at the
end of April 2004. The new Guidelines revise and modernize the plans from the
1990’s by concentrating investment priorities on a limited core network - major trans-
European axes - that primarily serve long-distance and international traffic and by
integrating the networks of the new Member States. A list of 30 priority projects is
also included - located on these major axes - and covers the territory of the enlarged
EU as well as Bulgaria and Romania.

In 2004, the European Commission decided to establish a High Level Group (the
Group) on the “extension of the major trans-European transport axes to the
neighbouring countries and regions”. This was to extend the concept of European
Neighbourhood Policy into the transport field and to find ways to better connect the
European Union with the neighbouring countries and regions. The work comprised 26
neighbouring countries, the 25 EU States plus Bulgaria and Romania, and the
international financial institutions. The Group completed its work in December 2005



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and produced its final report “Network for Peace and Development”, in November
2005.

The Group identified five major trans-national axes that extend and complement the
major axes of the trans-European transport network by interconnecting them with the
networks of the neighbouring countries. One of these axes is the Northern Transport
Axis.

The Group put also forward a preliminary list of infrastructure projects, for which,
however, further studies and analyses are necessary in terms of their economic
viability, technical specification, environmental impact and financing mechanisms,
before they can be considered for implementation. On the Northern Axis the Group
identified the following short and medium term projects:
   • Norway: Road and railway upgrading on the Nordic Triangle
   • Belarus: Railway line section Brest-Osinovka

The Group put a considerable emphasis on so-called horizontal measures that aim at
making transport along the axes more rapid and effective. These measures concern all
transport modes with a particular focus on the five axes proposed. The measures
include, among others:
   • Technical and administrative interoperability as regards e.g. railway networks
      and signalling systems.
   • Speeding up border crossing procedures by implementing without delay and
      fully the relevant international conventions, by introducing “one-stop” offices
      through shared facilities.
   • Simplification and harmonisation of trade and transport related documentation.
   • Implementation of new technologies, like traffic management and information
      systems, including satellite navigation (Galileo) that are effective and
      compatible with those implemented in the EU territory.
   • Measures to improve safety and security in all transport modes, e.g. through
      harmonising controls of vessels in the various sea areas at the highest level of
      performance.
   • The Group also emphasised that strong and effective coordination frameworks
      should be put in place to ensure synchronised and timely implementation of the
      proposed measures.

In 2006, the Commission organised a public consultation of the Group’s
recommendations, which ended with the public hearing in March 28, 2006. In January
2007, the EU Commission published its communication on the HLG proposals. The
communication adopted the main conclusions of the Group: (i) to extend the Pa-
European corridors so as (ii) to facilitate trade and transport flows along the axes, and
(iii) to strengthen the axes coordination and monitoring frameworks. The Commission
particularly approved the four land axes identified in the Group’s final report along with
the extended concept of the motorways of the seas.




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In autumn 2006, the Commission launched the study on the implementation of TEN-T
guidelines 2004-2005, which aims at updating infrastructure and project information
on the axes within EU territory.

This project of developing an analytical framework to monitor the implementation of
the infrastructure and soft measures is part of the further elaboration related to the
Transport Axes and the above list of horizontal measures. It is also closely related to
the 2004-2005 TEN-T guidelines implementation study.

1.3   Transport Strategy of the Russian Federation
In Russia, the transport policy work has intensified after 2000. The strategy work has
been partly driven by the increasing needs of foreign trade, which has also resulted in
the provision of better resources for transport system improvements.

The Ministry of Transport of the Russian Federation had worked on a transport
strategy for several years, which finally resulted in the approval of the Strategy by the
Russian Government, April 28, 2005.

In the Strategy the Ministry recognizes the absence of coordination between transport
modes, which has lead to low effectiveness and poorly linked projects, imbalanced
transport development, and bottlenecks in the national transport network in general.
This has consequences like:
    • Poor fluency of transport flows
    • High national costs, both for transport system users (time losses, operational
        costs) and more generally for the entire society (congestion, accidents,
        environmental stress)
    • Inability to realize potential geopolitical advantages

The main objective of the new Transport Strategy is to move from narrow modal
approach to the development of transport infrastructure with a focus on maximizing
system and macroeconomic effects, and on integration of Russia with the world
transport market.

The Strategy has the time horizon until 2020 with these objectives:
   1. Development of transport infrastructure to facilitate traffic flows and to reduce
       transport costs
   2. Improvement of competitiveness of the Russian transport system and
       realization of its transit potential
   3. Improvement of safety and sustainability of the transport operations
   4. Attracting investments to transport sector

The State support is intended particularly to:
   • attract investments for implementing projects that eliminate bottlenecks and
       missing links from the national transport system
   • integrate with the international transport system




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The Transport Strategy defines the priorities of the European part of Russia as
follows:
    • Modernization and integration of the development of the transport network,
       particularly along the main international transport corridors II and IX
    • Improvement of road network capacity, and elimination of bottlenecks on the
       accesses to big cities and major transport nodes,
    • Modernization of the sea ports and their land access

As a conclusion it can be stated that the interests of both the EU and the Russian
Federation are very similar.

1.4   Trade and Traffic Flows
The Northern Transport Axis comprises the main trade and transport connections
between Russia and the EU. Over 40% of the Russian foreign trade and the majority
of its trade with the EU Member States use the roads, railways and seaports of the
Northern Axis. On top of that, small but increasingly important EU trade flows with
Far East countries use the Trans-Siberian railway and the Northern Axis. Details of
the development of the trade including trade forecasts are presented in chapter 6.
“Exogenous scenarios”.

In the past decade, the EU-Russian trade flows have increased steadily and a certain
degree of concentration of the flows has occurred. Particularly the Gulf of Finland
ports have become the hubs of trade and transport after the completion of major port
construction projects near St. Petersburg.

There still is a fair degree of instability in route selection within the Northern
Transport Axis, which has been recently evidenced in the drop of Far East container
traffic possibly due to doubling of transport fees by the Russian railways. An
alternative is the sea route through the Suez Canal. Other routes that may have some
impact on the route selection from time to time are the rapidly growing ports of the
Barents Sea, and the more stable Black Sea, which both are the prime oil and gas
exporting areas.

The composition of the Russian trade with the EU is very imbalanced. The Russian
exports to the EU area comprise mostly energy (oil, gas, oil products) and raw
materials (ores, metals, coal and timber). Increasingly these types of exports, high
volumes in terms of tonnage and sensitive to transport costs, are concentrating in
special ports in the Gulf of Finland, the Barents Sea and the Black Sea. The Russian
imports from the EU consist mainly of consumer goods and investment products and
are in terms of tonnage much smaller than the Russian exports. These flows use
mainly the Gulf of Finland ports and to a lesser degree the other Baltic ports and the
Berlin-Moscow corridor.

The volume and routes of the Russian trade flows have fluctuated with political
upheavals and the often quick changes of trade regulations, laws, and peculiar
applications of a variety of export and import charges and taxes. With the increasing
volume going through the Russian own ports, the routes can be expected to stabilise.


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Also the Russian membership in the WTO will make rule changes more predictable in
the near future.

The passenger flows between the EU area and Russia are of three kinds. Main
passenger flows to/from Central Europe use air connections. Train connections exist
from Vilnius and Riga to Moscow. Tallinn has a connection to St. Petersburg and
from Helsinki there exist a good passenger train service both to St. Petersburg and
Moscow. The third category is private cars, which are used all along the border
mostly for shorter cross-border trips. Bus service is often in good order, but the
volumes are significant only in certain routes.

Route selection of passenger transport is not nearly so sensitive to changes than that
of freight transport. The obstacles to development are of different kind, such as low
volumes in most links excepting only a few like Helsinki – St. Petersburg and the air
connections between Moscow and St. Petersburg with the major European hub
airports. A special consideration in cross-border passenger traffic is small-scale
trading practiced in border regions, which has increased and distorted passenger
volumes at several borders.

The trade flows between Belarus and the EU are of much smaller significance. On the
EU side they concern mainly Poland, Lithuania and a bit of Latvia.

The trade flows between Norway and the EU are fairly large but much less
problematic and very stable due to close integration of Norway with the EU structures
and long established trade relations. As Norway is a very long country the flows are
thin and dispersed along the border with Sweden and Finland. By far the highest
volumes are in southeast Norway that use the road and rail connections of the Nordic
Triangle.

As discussed later in this report, considerable changes will take place in future
regarding trade between different economic powers affecting, correspondingly, the
trade flows and traffic volumes.

1.5   Infrastructure
The Northern Transport Axis has in principle three different transport infrastructure
regimes, and the most severe barriers to international trade and transport are typically
manifested at the regime borders.

Firstly, there are the old EU Member States (GER, SWE, FIN) and Norway, which
have very modern transport infrastructures comprising all transport modes (road, rail,
sea, air). No major problems of cross-border transport can be expected at these
borders apart from potential deficiencies resulting from their aging and congested
transport infrastructure, such as the Nordic Triangle road and railway sections in
Norway.

Secondly, there are Russia and Belarus, which have a considerable need for
expanding and modernising their transport infrastructures. The most severe


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bottlenecks are experienced at their borders with the EU, which today often result
from operational problems rather than physical ones. The conditions inside Russia
impact trade flows and their routes also on the EU side.

Thirdly, there are the new member states (POL, LIT, LAT, EST), which may have
more severe legacy problems as a result of different histories of infrastructure
development and subsequent neglect in maintenance. The most obvious such problem
concern railway gauges in some countries, which are very difficult or impossible to
eliminate. However, the situation is improving rapidly due to extensive investment
programs launched at and after the accession of these countries to the EU.




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                                                                                           The Approach




2 The Approach

2.1     Introduction and Objectives
The aim of this study is to set up – as a pilot for the Northern Axis – the analytical
support framework that would enable monitoring the implementation of the measures
proposed by the High Level Group. The methodology and principles of the analytical
framework should be easily extendable to the other Axes identified by the Group.

The analytical framework builds on the analysis of the infrastructure along the
Northern Axis including
   • Analysis of the current condition of the infrastructure
   • Investments and financial commitments
   • Analysis of physical and non-physical bottlenecks
   • Modelling the transport demand

This study also builds on completed and on-going studies and exercises aiming at
identifying bottlenecks and defining priority infrastructure in different neighbouring
regions and countries to the European Union.

The Analytical Framework is designed and documented bearing in mind that it can be
transferred to studies on other Axes to produce comparable data and analyses. The
Framework especially consist of the methodology of how to obtain and store the
required data and how to assess the current and expected bottlenecks. The framework
introduces a performance based planning system, which will be generally applicable.

The work has an exploratory nature with an emphasis in developing the system for the
Analytical Framework. The recommendations made for individual projects are subject
for negotiation process after the project. The priority order of different parts is thus
the following: The Analytical Framework, Data collection and analysis, modelling (as
it is likely that special modelling projects will start later). In modelling, freight is
more important than passenger traffic.

2.2     The scope

2.2.1    Geographical scope
The modelling part covers the whole world in the Exogenous Scenario Phase and
Northern Europe in the demand modelling phase including both EU and non-EU
countries relevant for the axis.




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The principal interest of the study lies in the major transport corridors passing through
the Northern Axis area. The analysis of infrastructure covers the following sections of
the Northern Axis:

    10. Narvik-Haparanda/Tornio-St. Peterburg
    11. Helsinki-St. Petersburg-Moscow
    12. Tallinn-St. Petersburg
    13. Ventspils-Riga-Moscow
    14. Klaipeda-Vilnius-Minsk
    15. Kaliningrad-Vilnius
    16. Berlin-Warsaw-Minsk-Moscow
    17. Oslo- Swedish Border (direction Gothenburg)
    18. Oslo- Swedish Border (direction Stockholm)

The above listed corridors are illustrated in Figure 2.1. The main emphasis of the
analysis is on the parts outside EU territory and on the parts in new EU countries and
secondly in old EU countries.




Figure 2.1 Transport corridors passing the Northern Axis area.


The modelling part of the study covers all transport networks as they are defined in
the latest version of TEN-T Guidelines: road network; rail network; combined
transport networks and terminals, inland waterways and ports, seaports and
motorways of the sea, airports. The main emphasis is on roads, railways and border
crossings.



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Regarding data collection for the Commission GIS database the scope is limited to
those parts of networks that are included in the Northern axis and situated outside EU
territory. This limitation is made because the 2004-2005 TEN-T guidelines
implementation study takes care of the data collection on EU side. Data collection
covers roads, railways and border stations.

The project has also collected such additional data from relevant EU countries and
non-EU countries that are not included in the Commission GIS database but are
relevant for the analysis purposes (current traffic volumes, traffic forecasts and
capacities etc. for roads, railways and border stations).

Data for harbours, airports etc has been collected for modelling purposes only as such
terminals are not nominated, yet, as parts of the Northern axis.

Some data gaps occur due to non-existence of data or data availability but major part
of the relevant data has been successfully collected and stored.

2.2.2    Time horizon
Time horizon will be 2020 except for the Exogenous Scenario phase where also 2030
is included. 2010 will be an intermediate year.

2.3     Methodological aspects
The main methodological aspects used are summarised below.

2.3.1    Definition of detailed objectives
The project started with a kick-off meeting with the Commission representatives
where the detailed objectives of the project were discussed together with
methodological, co-ordination etc. issues. The results of these discussions were fed
into the work programme.

2.3.2    Data collection and use of GIS
Data collection included a systematic approach and procedure that is updatable and
extendable to other Axes. It involved definitions and classifications that comply with
the requirements of the Commission’s database. It also included a procedure for data
quality assurance.

Data collection was coordinated with the study “Implementation Report on the TEN-
T Guidelines for the Period 2004-2005” co-ordinated by TINA Vienna. The new
definitions to be proposed by TINA Vienna were followed as far as possible.
However, the data collection started before the new definitions were ready.

Data was collected through the national contact points and network of experts for
which special guidelines and questionnaires have been designed. The data collection
procedure was designed to minimize the efforts of local authorities by using existing



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data as far as possible. The collection procedure is documented including definitions
and classifications used.

All required data for all countries does not exist or is not made available. In some
cases lack of data could be compensated with qualitative descriptions and expert
opinions.

Collection of data and data definition was designed to be compatible with the
Commission’s GIS system.

2.3.3   Building Scenarios
Trade and transport flows on the Northern Axis will be radically changed as a result
of globalisation. They are also very much dependent on the political and economic
development of Russia. Trade and transport flows between the main economic powers
of the world were estimated including sensitivity analyses for different political
scenarios. The study then focused on the trade between the Northern axis countries.

2.3.4   Modelling
The modelling part of the work took the above scenarios as an exogenous input. The
main models used were the SCENES and the STAN based FRISBEE model for
detailed assignment of freight flows. The models already had the majority of data of
networks, terminals, current flows etc. available. The main emphasis was on freight
flows and traffic crossing the borders.

2.3.5   The Analytical Framework
The study for the Northern Axis also serves as a pilot for other axes. In addition, the
study for the Northern Axis may have later to be updated or complemented. This is
why the methodologies were designed and documented so as to allow future updates
to be made easily and bearing in mind the requirements of transferability.

2.3.6   Quality
The Quality management procedures of the WSP LT Consultants’ certified quality
and environmental system were followed. In addition special quality management
procedures were designed for the data collection and the reporting tasks.

2.3.7   Dissemination & Internet
An internet site is established for the project (www.TEN-naxis.info). The site serves
as storage of all relevant data in an organised form.




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                                                                                           The Approach




2.4                               Work Programme
The work was carried out in Tasks as outlined in the Invitation to Tender, Purpose of
the contract:

              Part 1 – Analysis of the infrastructure along the Northern Axis
              Task 1. Analysis of the infrastructure and its current condition
              Task 2. Investments and Financial Commitments
              Task 3. Analysis of Physical and Non-Physical Bottlenecks
                 Task 3A The Analytical Framework
                 Task 3B Bottleneck Analysis

              Part 2 – Modelling Transport Demand
              Task 4. Trade and Traffic Flows
                 Task 4A Building exogenous scenarios
                 Task 4B Transport modelling

                                                                                             OUTPUTS

                                                              Kick – off                        Detailed objectives
                                                              meeting                           for the work



                                                              Inception                         1st Interim report
                                                                phase
                                                                                                Detailed work plan
   Analytical Support Framework




                                                            Investments           Building
                                         Analyses of                                            Country Reports,
                                                           and financial        Exogenous
                                        infrastructure                                          Technical Notes
                                                           commitments           scenarios



                                                              Transport                         2nd Interim Report
                                                              modelling



                                                             Analyses of
                                                         physical constraints                   Draft Final Report
                                                               - current
                                                                     - future


                                                                                                Final Report
                                                             Final report

                                                              GIS database



Figure 2.2 Relationships between the tasks.




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2.5     Output
The main outputs of the study are:

      Interim Report I
      Detailed work plan

      Country Reports, Technical Notes
      Country reports summarise the quantitative and qualitative data for each country.
      Technical notes cover specific issues of the project, such as the planned electronic
      questionnaire etc.

      Interim Report II
      The Interim Report summarises the tasks 1., 2. and 4., and forms the basis for
      analyses and recommendations (Task 3.). The Interim Report was approved on
      3.7.2007.

      Draft Final Report
      Draft of the Final Report including draft recommendations for comments by the
      Commission and the local authorities.

      GIS Database and database report
      A GIS database with the collected data and analysis results integrated, as far as
      possible, compatible with the Commission current GIS database.

      Final Report
      A Final Report including aggregated and detailed data, analysis of results, the
      analytical framework, illustrations and recommendations etc.

2.6     Time Schedule
The study was planned to be completed in 12 moths after its inception in October
2006. The project is completed a few weeks behind the schedule because of the
coordination needs with the “2004-2005 Implementation Study” that delayed the start
of the data collection.




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      2.7        Project Structure and Distribution of Responsibilities
      The structure of the project organisation is presented in the figure below.


                   CLIENT                              European Commission

                                                      Steering Committee
                                               DG TREN, RELEX, ENV, REGIO, ECFIN

                                                               F.Begeot




                   CONSULTANT                                Lead Partner
                                                               WSP LT
                                                              K.Lautso
                                                             M.Miettinen


                               TRT                  WSP UK                  MATREX                ANSERI
                            A. Martino              Jin Ying                T. Särkkä          W. Segercrantz



                   NATIONAL NETWORKS
Consortium         Norway     Sweden     Finland   Estonia   Latvia    Lithuania   Poland   Germany   Belarus   Russia
responsibility     WSP LT WSP LT         WSP LT    ANSERI    ANSERI       ANSERI   WSP LT   WSP LT    ANSERI    ANSERI



      Figure 2.3 Project organisation.




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                                                                        The Analytical Support Framework




3      The Analytical Support Framework

3.1     Objectives
The Terms of Reference (ToR) define the Analytical Support Framework (ASF) as a
system that enables the monitoring of the implementation of the measures proposed
by the High Level Group. The ToR specifies further that the methodology and
principles of the analytical framework should be easily extended to the other Axes
identified by the Group. The analytical framework should also provide the basis for
defining an action plan for the implementation of the measures along the pilot axis.
This would include the necessary data and detailed analysis of the selected trans-
national transport axes in view of more detailed planning of the implementation of the
axes, better synchronisation of investments along the axes and linking the axes
development within national master plans.

Based on the point of departure outlined in the ToR, the establishment of an ASF
becomes a multifaceted problem. Quite obviously the process must address in a
balanced way the following questions:
    • What are the methods of data collection, analysis, and monitoring of the
       progress that can be sustained in the long-term
    • What kinds of resources (financial and human) can be anticipated to be
       available both in the short and long-term
    • How to organise the axis cooperation and management functions so that the
       necessary activities can be carried out within the available resources

When it comes to the Northern Axis, it has some specific characteristics, which must
be reflected in the design of the Axis framework. One such fundamental feature is the
Axis’ all-encompassing objective to serve passenger and goods transport between
Russia and the EU. Another one is the fact that only one non-EU country, namely
Russia, account for roughly half of the network length and investments. Third
consideration is that the later sections of this report show that the main areas needing
joint actions in the Axis are the following:
    • Rapprochement in the general understanding of the Axis objectives between
        the parties
    • Border crossings for road transport of freight
    • Harmonisation of heavy goods vehicle standards
    • Railway harmonisation and improving competitiveness of rail transport

Rest of this Chapter discusses first the analysis methodology, which is then followed
by presentations of organisational options. Detailed descriptions of the methodology
can be found in other Chapters of this report, particularly Chapter 8.

3.2     Methods
In broad terms the methodological side of an ASF should be able to:
    • Collect, store and update traffic, infrastructure and other pertinent data on a
       continuous basis

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    •    Allow synthesis of large volumes of data
    •    Identify bottlenecks and deficiencies along the axis
    •    Evaluate identified improvement projects and prioritise among them
    •    Demonstrate progress toward the Axis goals and objectives
    •    Support effective decision-making

In order to fulfil the above needs the consideration of several practical questions are
required as to how to accomplish all this with the means and resources that are
available, namely
    • Where and how to obtain relevant data
    • How to forecast into the future
    • How to store data and information
    • How to do data updating and monitoring the progress

Once these questions are resolved and data and information are available, several
methods can be used for analysing and assessing the axis, as well as for doing
representations of the axis status and progress over time. The methodological process
is shown in Figure 3.1.


                                        DATA COLLECTION
    EU-Member states                    Non-EU countries                    International traffic
    TEN-T:                              Infrastructure                      Transport models
    •     Infrastructure                Investment programs
    •     Investments                   Domestic traffic
    Traffic forecasts                   Safety
                                        Environment
                                        Regulations


                                 TRANSPORT AXIS DATABASE
                                      Links and nodes
                                   Infrastructure (roads, rail, borders)
                           Current and forecast traffic (road, rail, international)
                                       Planned investment projects
                                    Environmentally sensitive areas
                                               Safety data


                                       TRAFFIC FORECASTS
                               International traffic (passengers and freight)
                                 Domestic traffic (passengers and freight)


                                       ANALYSIS METHODS
                                  Criteria for evaluations and selections
                                                   Models
                                                Comparisons


                                       REPORTING SYSTEM
                                                  Reports
                                                Action plans
                                                  Projects



Figure 3.1 Analysis and monitoring tasks of the ASF




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Data and data collection. All efforts of establishing the ASF for a system as large as a
transport axis tend to be data intensive. Requirements for data can easily become
daunting. As data and information collection risks to become a major undertaking, it
is highly recommended that a conscious effort will be launched for setting up a
reasonable system to collect, generate and store data on a continuous basis, but within
the available resources. Judgement must be exercised and priority given to those kinds
of data and information that support portraying and monitoring of the Axis status and
development in terms of their fundamental objectives.

There are different ways of organising the above functions, but the starting points are
various existing databases. Most parties of the axis cooperation have infrastructure
and traffic databases of various kinds. Currently, the Commission maintains the TEN-
T database, which contains the basic data of the TEN-T infrastructure. The database is
updated at certain intervals through specific consultancy assignments, such as the
TEN-T implementation studies. The Commission has also put a considerable effort
into modelling and forecasting traffic on the TEN-T system.

Unfortunately, the future axis cooperation can draw on the Commission’s data
resources only limitedly due to its current focus. Other problems arise from the
geographical coverage, lacking data types and the level of detail of the TEN-T
database:
    • TEN-T database covers only the transport infrastructure of the EU member
       states, while the axes comprise links and nodes that are largely outside the EU
    • TEN-T data is too general and the links are long. The relatively rough data do not
       support well the identification and analyses of concrete bottlenecks at a more
       refined level which often is needed, e.g. in case of weak bridges or small town
       thoroughfares.
    • The database does not have any information about border crossings
    • TEN-T database does not contain any traffic information
    • Traffic models used in the evaluation of the TEN-T system may not be extensive
       enough for forecasting traffic in the non-EU countries.

When it comes to data collection and monitoring, the basic option is that these
activities are carried out as now. With regard the TEN-T data this requires that the
Commission will continue to let consultancy contracts for data updating at regular
intervals. The difference in the future work is that the contracts are extended to cover
also the non-EU axes countries. Alternatively, the axis steering committee could do
the same if it has adequate resources to do so.

Organising data collection on a continuous basis is not an easy task, which is also
likely to require some sorts of agreements with the database owners and managers. In
the long-term, it is important that the external databases support data exchange
interfaces that allow easy retrieval of data and help in updating the Axis database at
regular intervals. With time, data and information should be received more directly
and without any specific effort from the sources that are directly responsible for the
relevant data and its updating in each country.




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The axis database. Any analysis of the axis infrastructure and its traffic, as well as
planning future measures, requires a well-structured and accessible database. If the
TEN-T database will not be expanded to cover the entire Northern Axis; that is also
the non-EU countries, it is obvious that the axis database must be set up separately.
The axis database could technically be located anywhere. Important, however, is that
the parties and individuals directly responsible for managing the axis development
and joint planning processes have an unobstructed access to the database. In the end,
it is likely that it is up to the axis management who must see to it that the axis
database is in order, accessible and contains the most recent information.

Traffic forecasts. Models, each separately for freight transport and passenger travel,
are needed for forecasting future traffic flows and link-specific traffic volumes. The
axis analysis needs both domestic flows as well as international (cross-border) flows.
They need to be developed and maintained for each transport axis in some way. In the
axis context it seems that only models for international transport and travel need to be
developed specifically by the Axis management. Maintaining domestic transport and
travel information as well as their forecasts in each country should be the
responsibility of national transport authorities.

Analyses. Analyses such as corridor performance, identification of bottlenecks and
viability of projects can be done within the joint working groups or by each of the
parties separately for their own projects. In principle, the axis level analyses can best
be done by some kind of a Steering Committee/Secretariat, while the national
transport authorities – the project owners – are best suited to carry out project level
studies. However, the Axis management will have the final responsibility of
coordinating and assisting the various analyses.

For the general axis level analyses, concerning performance and emerging
bottlenecks, specific tools and models must be developed so that the results are
consistent and comparable between the axes, their branches, and over time. Much of
the method development and harmonising could conceivably fall on the Commission.
Such methods are first developed in this study.

3.3     Organisation and management

3.3.1    General considerations
One of the main considerations in setting up an ASF management system revolve
around the split of responsibilities between the three main parties: (i) the Commission,
(ii) Axis Steering Committee/Secretariat, and (iii) transport ministries and authorities
of the axis countries. There is likely to be some ambiguity regarding this matter. It is
clear that the responsibilities should not overlap and the parties should see them in a
similar way. How potential conflicts are overcome, influences the design of the ASF
management structure. The core questions that affect the effectiveness of the axis
cooperation in the long run are:
     • the degree to which each party is willing to yield authority to a international
        cooperation framework. This may be difficult to measure first, but it eventually



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                                                                      The Analytical Support Framework




        shows up in the commitments to implement jointly prepared development plans
        and recommendations.
   •    resources that each party wants to devote to axis cooperation. Resources can be
        of different kinds such as financial and human. Particularly important is political
        urgency, which shows e.g. in the authority and seniority of the individuals
        designated to the process.

There are no simple answers to these basic questions. Rather, these answers become
matters of choice that must be debated and solved in each case separately.
Furthermore, it must be recognized that these issues and countries’ commitments are not
uniform and constant over time but vary between the partners reflecting political realities
in each axis country at any given time.

3.3.2   Models for organisation
There are no obvious models for organising the axis cooperation, because there has
not been any similar international joint effort in this scale before. However, in the
following, three possible models for the axis management are presented building
mainly on the practices used in the context of the Pan-European Corridors.

Option 1 – light organisation concentrating on general axis cooperation

The nature of cooperation resembles that of the current Pan-European transport
corridors. Main characteristics are:
    • The axis management is light consisting of (i) an international steering
       committee, (ii) its chairman, which rotates between the involved countries, and
       (iii) a secretariat, which will be responsible for running the routines of axis
       cooperation. The secretariat, consisting typically of a single person, works often
       on part-time basis only.
    • The axis management has no or very limited financial resources available
       beyond what is needed for the routine activities of the secretariat and steering
       committee meetings.
    • All inputs for developing and monitoring the axis progress come from the
       countries concerned, namely from the transport ministries and road, rail, border
       and other relevant authorities.

Option 2 – strong organisation focused on results

In this option the axis management is independent and exerts leadership. The
management has also a mandate to accomplish the axis development. Main
characteristics are:
   • The axis management consists of (i) an international steering committee, (ii) its
       permanent chairman, who is a prominent figure, and (iii) a secretariat, which has
       adequate human and financial resources to carry out all the functions that are
       necessary for running the axis development and cooperation on the daily basis.
       The secretariat consists of several experts that may work full or part time.
   • The axis management has adequate financial resources, which can cover
       practically all the functions that the axis development needs, excepting


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                                                                      The Analytical Support Framework




        construction. They include planning, traffic modelling, setting up and
        maintaining the axis database and launching project studies.
   •    Input for monitoring the axis progress comes from the countries concerned under
        the strong guidance of the chairman and secretariat.

Option 3 – two-tiered organisation

This option is a sort of combination of the two options above. The two tiers are:
• Tier 1: Axis steering committee and its secretariat are set up very much like the
   organisation in Option 1. The Steering Committee should have preferably a
   permanent chairman as in Option 2.
• Tier 2: Framework of working groups and regional coordination groups for specific
   projects and tasks. They are composed of relevant authorities. In addition,
   international financing institutions should be invited in the groups that prepare
   investment decisions. These groups should take full responsibility of the practical
   preparation of the selected projects, where the process should follow the guidelines
   agreed in the Axis Steering Committee.

   In the case of the Northern Axis the above could be achieved in practice by
   incorporating the existing steering committees and other transport working groups in
   the Axis process. A very potential tool in this respect could be the envisioned
   transport and logistics partnership of the Northern Dimension initiative. The
   intention is that the partnership would provide International Financial Institution led
   working groups for each transport investment project in the region. As of now, the
   transport and logistics partnership has not been established.

   Financing for the working groups and task forces should come from the axis budget
   overseen by the secretariat and the Steering Committee chairman. Adequate financial
   provisions should be secured for this purpose.

All the organisations outlined above have their merits and applications. Option 1 may
be a good way of starting the process and getting a feel of possible directions and
limits of the Axis cooperation. A practical foundation for the long-term axis
development could be built this way. However, Option 1 has often proved inefficient
as a long-term cooperation model, because it is difficult to maintain momentum in this
more or less loose framework without a strong leadership.

Option 2 has the benefit of providing a strong support framework for the axis
cooperation. Such a framework is typically well suited for processes, which are
relatively mature for implementation. Thus, the drawback if Option 2 is that it is
doubtful whether a single development unit, a secretariat, is adequate to handle such a
wide geographic area as the Northern Axis. Furthermore so, as the circumstances
differ from region to region and possible solutions are often not very clear, are subject
to changes and are politically contested. Invariably, unspecified time is needed to
reach agreements in any given issue. In these cases Option 2 may not be any better
and more efficient than Option 1. Lack of firm commitments and not being able to
proceed is also likely to lead to frustration and inefficient use of resources affecting
particularly Option 2.

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Option 3 merges the “good” parts of Option 1 and 2. In this option the lighter Steering
Committee structure (tier 1) is employed for developing general development
objectives for the Northern Axis. Tier 1 should particularly focus on harmonising the
thinking and finding solutions to political disputes and other contested issues. At the
second tier, as the projects become mature, specific working groups should be set up
with proper financial and human resources for preparing and implementing those
projects and tasks, which can proceed.

An advantage of Option 3 is that it provides a structured two-prong approach, which
works better than Option 2 in politically contested situations, but also provides
adequate resources for the work when needed. Different from Option 2, which
envisions a strong in-house staff, Option 3 has a relatively light organisation, which
will employ external experts for various tasks on a contract basis. This helps in
keeping the size of the secretariat at a modest level. An important strength of the
model is that the already existing regional working groups (e.g. current Pan-European
Corridor Steering Committees) can readily be incorporated in the framework.

It should be pointed out that the current BEATA cooperation (Barents Euro-Arctic
Transport Area) is organised like Option 3 in several important respects. As BEATA
covers several of the Axis countries, it can be relatively easily envisioned that the
same approach could be workable also in the Northern Axis cooperation framework
as well.

In the end, the “best” organisation will depend largely on the resources that are made
available for the axis cooperation. Over time, also on the maturity of the axis
cooperation can influence the organisation, which may even fluctuate between the
above-described models.

3.3.3   External frameworks of cooperation
The axis cooperation should not be a closed entity and an end in itself, but it rather
should be very open to other either already existing or new cooperation frameworks
that have same or parallel interests. Every effort should be made that these
cooperation frameworks become partners in the larger axis cooperation. Examples of
other such cooperation frameworks are:
• Regional cooperation, such as between the border regions of Finland and Russia.
    This can be an important contributor at the grass-root level. They also have
    financial resources for implementing small-scale investments in border regions.
• Cooperation between national border and transport authorities across the borders.
    An example is the customs cooperation between the Nordic and Russian customs
    officials, which would be an effective tool in tackling the border problems.
• Cooperation between transport operating companies, particularly the national
    railways. Examples of this are the existing cooperation agreements and joint
    ventures between the Russian Railways and German Railways (DB) as well as
    with the Finnish Railways (VR).
• The Commission’s cooperation with the Russian authorities. Relevant in this case
    are the EU-Russia transport dialogue and its permanent working groups, and the


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     customs cooperation and task force(s) such as the Ad-Hoc Group on Transport
     Logistics Problems. They all should be drawn to contribute more directly to the
     axis level cooperation as well.
•    Cooperation with the International Financial Institutions

3.3.4     Secretariat
Secretariat is an important entity of the axis framework, which is tasked to keep the
momentum in the cooperation. Therefore, the work of the secretariat deserves specific
attention. In Table 3.1 an attempt is made to draw up a tentative outline for the
secretarial responsibilities using the organisational Options 1 and 2 as a base.

Table 3.1 Setting up the secretarial functions
1. Axis database
Option 1 – light organisation                         Option 2 – strong organisation
TEN-T database and/or several dispersed               A specific axis database will be set up for the
national databases will be used as the axis           axis
database
Database manager/owner:                               Database manager/owner:
EU/DG TREN                                            Steering Committee/Secretariat of an axis
Each authority/country for its own data

2. Updating the axis database
Option 1 – light organisation                         Option 2 – strong organisation
Responsibility:                                       Responsibility:
EU/DG TREN                                            Steering Committee/Secretary with the help of
Each authority/country for its own data               dedicated national transport authorities
Data sources:                                         Data sources:
Studies and data collection efforts of EU/DG          National databases with their updates
TREN                                                  Data collection through specific studies
National data updates                                 Country reports which will be updated by each
                                                      country/transport authority separately
                                                      Project data
                                                      Relevant data and studies from other sources
Frequency:                                            Frequency:
When new data is available                            Continuous (minimum annual)

3. Updating domestic traffic data
Option 1 – light organisation                          Option 2 – strong organisation
Responsibility:                                        Responsibility:
Transport authorities in each country                  Dedicated national transport authorities in each
                                                       axis country
Database:                                              Database:
Dispersed databases with the              transport    Axis database
authorities of the axis countries
Analysis tools:                                        Analysis tools:
National practices                                     National traffic counts and forecasts
                                                       Project data
Frequency:                                             Frequency:
National practices                                     Annual




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4. Updating international traffic data
Option 1 – light organisation          Option 2 – strong organisation
Responsibility:                                     Responsibility:
Transport authorities in each axis country          Axis Steering Committee/Secretariat            with
EU/DG TREN                                          dedicated transport authorities
Database:                                           Database:
Dispersed databases                                 Axis database
Analysis tools:                                     Analysis tools:
National practices                                  Transport models
EU/DG TREN studies                                  Specific studies
Frequency:                                          Frequency:
National practices                                  Once in 3-5 years
When specific studies are available

5. Axis performance and project/bottleneck identification
Option 1 – light organisation         Option 2 – strong organisation
Responsibility:                                     Responsibility:
Transport authorities in each axis country          Axis Steering Committee/Secretary
Data sources:                                       Data source:
Dispersed databases in each country or              Axis database
corridor
Analysis tools:                                     Analysis tools:
National practices                                  Performance indicators
                                                    Analysis models
Results:                                            Results:
List of transport projects that have been           Locations of
identified nationally or locally                    • Capacity constraints/bottlenecks
                                                    • Delays
                                                    • Black spots
Frequency:                                          Frequency:
National practices                                  Annual
When new projects are proposed

6. Project evaluation and program development
Option 1 – light organisation        Option 2 – strong organisation
Responsibility:                                      Responsibility:
National transport authorities (project owners)      Axis Steering Committee/Secretariat
                                                     National transport authorities (project owners)
Analysis tools:                                      Analysis tools:
Evaluations and studies performed by national        Cost-Benefit analyses
transport authorities, national practices            Tentative EIA or SEA
                                                     Economic and social impacts
Results:                                             Results:
List of national priority projects                   Feasibility of a project
                                                     Project list by priority
Frequency:                                           Frequency:
When a new programs are being prepared in            Annual
each country




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7. Monitoring national investment programs
Option 1 – light organisation         Option 2 – strong organisation
Responsibility:                                      Responsibility:
Axis Steering Committee/Secretariat                  Axis Steering Committee/Secretariat
Data sources:                                        Data source:
Transport ministries and transport authorities in    Specific country reports from transport
the axis countries                                   ministries and authorities
Analysis tools:                                      Analysis tools:
None                                                 Evaluation
                                                     • Whether identified projects are in program
                                                     • Adequacy of financing
                                                     • Delays in implementation
Results:                                             Results:
Report based on information from the                 Status report, including evaluation of
ministries                                           compatibility between the national programs
                                                     and the objectives of the axis
Frequency:                                           Frequency:
When the Steering Committee considers this           Annual
necessary

8. Monitoring progress of national transport legislation and regulations
Option 1 – light organisation          Option 2 – strong organisation
Responsibility:                                      Responsibility:
Axis Steering Committee/Secretariat                  Axis Steering Committee/Secretariat
Data sources:                                        Data source:
Transport ministries and transport authorities in    Specific country reports from transport
the axis countries                                   ministries
Tools:                                               Analysis tools:
None                                                 Evaluation
                                                     • Remaining differences with EU regulations
                                                     • Planned legislation and regulations
                                                     • Timetables of implementation
Results:                                             Results:
Report based on information from the                 Status report about the level of harmonisation
ministries                                           and compliance
Frequency:                                           Frequency:
When the Steering Committee considers this           Annual
necessary




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9. Reporting on the Axis cooperation
Option 1 – light organisation        Option 2 – strong organisation
Responsibility:                                      Responsibility:
Axis Steering Committee/Secretariat                  Axis Steering Committee/Secretariat
Data sources:                                        Data source:
All the above                                        All the above

Reporting tools:                                     Reporting tools:
Steering Committee:                                  Steering Committee:
• Annual activity reports                            • Annual status and progress reports
                                                     • Country reports
                                                     • General public: newsletters, internet site
Results:                                             Results:
General information about the axis cooperation       Information about the status and progress of
                                                     the axis development and regulatory
                                                     harmonisation
                                                     Action plans and their updates
Frequency:                                           Frequency:
Annual                                               Annual


3.4   Resources
Analysis methods, the organisation, and financial resources are intertwined in many
respects. An important notion is that the methodology adopted for the analytical
support framework cannot be selected without considering to some degree the
resources that are made available for this activity. The available resources also
determine the size of organisation and the type of management that must apply the
methods.

There are in principle two types of funding needs, which must eventually be covered:
• Management of cooperation: chairman, secretariat and other expenses such as
   meetings, seminars, translations, interpretations, and dissemination of information
   (reporting, newsletters etc). These are more or less permanent costs and must be
   covered as soon as the cooperation is set up.
• Studies and project preparation, which are needed for making concrete progress in
   the cooperation. These are, however, variable costs where flexibility in spending
   can be exercised.

The question of financial resources, which will be made available for the axis
cooperation, is always a difficult one. As the experience of the Pan-European Corridor
cooperation highlights, the provision of financial resources is invariably an
overlooked issue, which is detrimental to timely progress as well as the final success
of cooperation. It is paramount that the parties setting up the ASF consider this
question along with other organisational questions.

The natural solution to the financial problem is that the partners, mainly the axis
country ministries of transport, allocate the needed financial resources for the use of
the cooperation framework. Often this is easier to say than carry out, because the
capacity or will to provide funding will differ among the ministries. A difficult issue
always is that the perceptions of the potential benefits of such cooperation differ and
may not rank high among the priorities of some countries. This leads to widely

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                                                                      The Analytical Support Framework




differing views of justified payment shares for each country, which takes lengthy
periods of time to resolve and the end result more often than not will be a
considerably reduced budget.

An optional solution to the above problem is that only few or a single source will
provide financing for the Axis cooperation, preferably on a long-term basis. As a
single source may be difficult to find among the Axis countries, the option is that the
Commission will cover the cooperation costs fully or at least for its permanent share.

One more financial solution could, for instance, be the new ENPI (European New
Partnership Initiative) mechanism, which can provide substantial and long-term
financing for the axis cooperation in the period 2007-2013. The ENPI mechanism is
quite fair, as each party pays a certain share of the costs and commits itself by doing
so, while the ENPI covers the vast majority of the project budget. Drawbacks of this
approach are that the ENPI funding must be applied for separately, which is a tedious
process and there is no certainty that funds will be granted. Also, the use of funds
must be carried out under the ENPI rules, which have been somewhat restrictive when
it comes to carrying out joint projects across the Russian-EU border. However, the
rule problem may have been improved in the new program 2007-2013.




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                           of the infrastructure and “soft” measures proposed by the High Level Group
                                        Analysis of infrastructure along the Northern Axis - Infrastructure




4 Analysis of infrastructure along the Northern Axis -
  Infrastructure

4.1     Data collection

4.1.1    Background
Analysis of infrastructure and its current condition needs good information about the
transport system comprising the axis. The Analytical support framework pilot study
has an extensive work phase for this purpose. It consists mainly of data collection
about international traffic flows as well as about railway and road infrastructure and
border crossings facilities of the Northern Transport Axis as defined by the High
Level Group in 2005.

Approximately at the same time, the Commission has launched the TEN-T
implementation guidelines study for the period 2004-2005, which collects basic
infrastructure data of the TEN-T network in the current EU member states. Due to the
two parallel efforts it has been decided that the analytical framework pilot study
collects only data, which the TEN-T implementation study does not cover, such as:
     • Additional data needed for identifying bottlenecks and analysing projects
     • All necessary information about border crossings
     • Domestic traffic volumes in each of the axis countries (current and forecast)
     • TEN-T type data of the non-EU Axis countries (Belarus, Russia and Norway)

Categories of data that need to be collected are generally selected based on the
analysis needs of the axes, namely:
   • National transport laws and regulations (only selected information)
   • Transport infrastructure (roads and rails)
   • Border crossings (roads and rails)
   • Investments (past and planned)
   • Domestic traffic

Both the studies, the TEN-T implementation study and the Analytical support
framework study, have employed an extensive network of local experts in the
countries in question. In the end, the Northern Axis database will comprise all the
collected data of these two studies.

4.1.2    National transport laws and regulations
The point of departure for data collection has been the expediency of international
freight transport along the Northern Axis. In the axis countries slowing of traffic and
delays to transport operators and the travelling public can occur due to several
reasons. At present, the most severe obstacles to smooth flow of passengers and
freight are experienced at the international border crossings. This is largely due to
differing transport laws and regulations and the way they are administered in each
country and border. As the EU has enlarged, the sites of border delays are less


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                                        Analysis of infrastructure along the Northern Axis - Infrastructure




frequent due to progression of legal and regulatory harmonisation and improved
management of borders. Yet, considerable problems persist at the external borders of
the EU that need continuous attention. The focus of this data collection phase has
been to reveal the regulatory differences that may limit access and cause delays
primarily at the external borders.

Table 4.1 Collected data on national regulations by study
TEN-T implementation study 2004-2005,                   Analytical support framework study, additional data
basic data collection                                   collection
Road:                                                   Road:
   Max HGV weight                                           Max HGV height
   Max. axle load for HGVs                                  Max HGV length
                                                            Max HGV width
                                                            Max HGV speed limit

Rail:                                                   Rail:
    Max load gauge                                        Railway gauge
    Max axle load
    Voltage on electrified tracks


The collected data consists of allowable vehicle dimensions, which present mainly an
access to market problem but have also some cost implications. There are also other
constraints of general type that have not been covered by the data collection. They
typically include horizontal measures that the HLG has listed in its final report of
November 2005, such as:
    • customs controls (conventions adopted and languages used in documentation)
    • border procedures (cooperation and “one-stop offices”)
    • transport and trade documentation with a specific introduction of electronic
        data-interchange (EDI) at borders
    • common procedures for rolling stock acceptance
    • international conventions such as COTIF and OSJD for railways
    • labour and visa regulations for professional drivers
    • coordination between enforcement authorities in security issues

First, it is well known that these kinds of regulatory and procedural constraints exist,
particularly between the EU and Russia/Belarus, which derive from different histories
of and approaches to border controls. However, going beyond that recognition it is
somewhat difficult to factor the above listed types of constraints into transport
operations so that they would manifest themselves in transport bottlenecks needing
infrastructure or operational improvements at the axis borders. When they exist, they
are undoubtedly matters that cause excessive effort and increase cost, but are typically
solved and accounted for prior to any shipment of goods across such borders.
Secondly, it can be well argued that these constraints go beyond the mere axis
development and cannot be solved within the cooperation framework of a given axis
alone. By and large they belong to the bilateral talks between the Commission and the
member states on one hand and Russia and Belarus on the other.

4.1.3     Transport infrastructure
As mentioned above, data of transport infrastructure in the EU countries have been
collected in the TEN-T implementation study. The analytical framework study


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                                         Analysis of infrastructure along the Northern Axis - Infrastructure




extends this data collection into the neighbouring countries of the EU, namely
Belarus, Russia and Norway. Thus, a similar data collection has been performed in all
of these countries allowing the compilation of a homogenous database for the entire
Northern Axis area.

In addition to the TEN-T specified data, this study has collected also other
information about the axis for the purpose that the performance of the axis roads and
rails can be determined and analysed properly.

Table 4.2 Collected data on transport infrastructure by study
TEN-T implementation study 2004-2005,                  Analytical support framework study, additional data
basic data collection                                  collection
Road:                                                  Road:
   Road type                                               Road width
   Number of lanes                                         Pavement type
   Design speed                                            Urban areas (distance)
   Max gradient                                            Number of accidents
   Tolled                                                  Speed limit
                                                           Responsibility

Rail:                                                  Rail:
    Category of high speed                                 Max train weight
    Activity (freight, passenger or both)                  Max train length
    Number of tracks                                       Capacity for freight
    Traction power                                         Degree of capacity utilization
    Min radius                                             Punctuality data
    Design speed                                           Accidents or events causing delay
    Max gradient
    ERTMS readiness and level
    Signalling system in use


4.1.4     Border crossings
Border crossings are very unique features of any transport system, because most of
the difficulties of international trade and transport will be revealed at the borders. The
root causes are always the national laws and regulations and how they are
administered and managed at the border. There are undoubtedly also capacity issues at
the borders, but the capacities are always defined within the prevailing regulatory and
procedural framework of a country. Border capacities will change, when regulations
and field practices change. If regulations are simplified and harmonised, procedural
adjustments most likely will follow that reduce delays and make them also less
frequent.

In this phase the physical features of border crossings were collected. Collected
information is selected so that it assists in estimating the capacities and analysing any
bottleneck situations that may occur now or arise in the future.




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Table 4.3 Collected data on border crossings by study
TEN-T implementation study 2004-2005,                 Analytical support framework study, additional data
basic data collection                                 collection
   No border data collected.                          Road borders:
                                                          Year of construction
                                                          Number of approach lanes
                                                          Number of lanes between the posts
                                                          Number of service points
                                                          Opening hours
                                                          Capacity for motor vehicles (entering and exiting the
                                                          country)
                                                          Capacity for trucks (entering and exiting the country)

                                                      Railway borders:
                                                          Year of construction
                                                          Number of approach tracks
                                                          Number of tracks between the posts
                                                          Railway yard, number of tracks
                                                          Number of tracks for inspection
                                                          Passenger trains, formalities in the train
                                                          Opening hours
                                                          Reloading at border (freight)
                                                          Axle change facilities at border
                                                          Capacity for freight trains (entering and exiting the
                                                          country)
                                                          Capacity for passenger trains (entering and exiting
                                                          the country)


4.1.5   Domestic traffic
In the analytical framework study, only international freight and passenger traffic is
studied and forecasts are made. There has not been any attempt made to estimate and
forecast national and local traffic in the axis countries. Here, this kind of national
traffic is called domestic traffic. Domestic traffic studies and forecasts made by
national transport authorities provide the underlying local traffic data for road and rail
links. These data have been collected, if available. It must be pointed out that
domestic traffic by and large constitute most of the traffic flows on the axis.

Thus, a distinction must be made between the domestic/internal and international
traffic. Traffic analyses and forecasts of this study concern international traffic only.
These data are used to indicate the branches and infrastructure that are important for
international trade. On the other hand, domestic traffic gives the basic (total) traffic
data for bottleneck analyses.

Forecast years of domestic traffic are those that are available in each segment of the
axis by country. The typical forecast horizons are 2010, 2015 and 2020.




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                                        Analysis of infrastructure along the Northern Axis - Infrastructure




Table 4.4 Collected data on domestic traffic by study
TEN-T implementation study 2004-2005,                   Analytical support framework study, additional data
basic data collection                                   collection
   No traffic data collected.                           Existing and forecast traffic on road links:
                                                            Number of vehicles per day
                                                            Share of HGVs per day

                                                        Existing and forecast traffic on rail links:
                                                            Number of passenger and freight trains per day
                                                            Freight tonnes per year
                                                            Number of containers (TEU) per year

                                                        Existing and forecast traffic at road border crossings:
                                                            Existing traffic (cars, buses, trucks) per day
                                                            Tons of goods exported and imported per year
                                                            Number of passengers per year

                                                        Existing and forecasts traffic at rail border crossings:
                                                            Number of passenger trains per year
                                                            Number of freight trains per year
                                                            Tons of goods imported and exported per year
                                                            Number of passengers per year


4.1.6   Problems with data
Collected data and information for both the TEN-T implementation study and the
Analysis Support Framework pilot study are rather basic and relatively easy to obtain
at least in principle, if not always in practice. Some comments with regard the data is,
however, warranted:
    • There is some variance with data definitions. However, harmonizing of
        collected data to a reasonable degree can be done.
    • Existing traffic is based on counts and estimates from different years. Also,
        national transport authorities have different practices as to how to update count
        data. Some countries carry national surveys every so many years, and some
        others have continuous counting on main roads. That does not, however,
        present major problems for estimating current traffic.
    • There is a recent problem with commercialised national railway companies.
        They do not, as a rule, provide freely obtainable transport flow data to the
        national authorities. These data are now considered confidential. The same
        affects also any railway traffic forecasts which are difficult to get or do not
        exist any more.
    • Domestic traffic forecasts are also from different base years and made for
        differing purposes. It is believed that these data can be used reasonably.
        Difficulties arise when these domestic forecasts must be extended longer into
        the future, such as the years 2020 and 2030. In the study, extrapolation of
        forecasts has been done using the factors that are considered best for each case.
        A bigger problem is that in several cases there are no basic traffic forecasts.
    • A specific problem concerns some border crossings, typically between the
        Nordic Countries, where normally no traffic count data are available any more.
    • The biggest problem concerns all kinds of travel time and delay data. For
        roads, normal travel times can be calculated with reasonable certainty, but
        delays due to traffic events and road condition are more difficult to estimate. In
        this study phase these have not been done.



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                                        Analysis of infrastructure along the Northern Axis - Infrastructure




   •    For railways there are two distinctly different operational regimes. First,
        passenger trains run typically on schedule and their delays are small and also
        recorded in some way. Second, for railway freight the question of delays is a
        much more complex issue. Freight train delays are not uncommon, but they are
        hidden in waiting times on line and at railway junctions that are poorly or not at
        all recoded.
   •    Border delays are the most notorious delays. Even if their existence is well
        known, often only anecdotal information is available. In addition, variance of
        border delays is very high between days and the seasons. As a rule, long-term
        and continuous recordings of border delays are scarce.

4.2     Analysis of infrastructure

4.2.1    Elements of the Northern Axis
For the purposes of analysing and portraying the Northern Axis and its many
characteristics, it is important to code the elements in a structured way. In Table 4.5 a
proposal of such a coding system is presented. The coding system in the Table is
generic so as to allow its use also in other axes in a harmonised way.

Table 4.5 Proposed coding of branches of the Northern Axis
Element
                                                                 Code            Affected countries
Northern Axis
                                                                 Naxis
Branches:
  Narvik-St.Petersburg                                             1         NOR, SWE, FIN or RUS
  Helsinki-Moscow                                                  2         FIN or RUS
  Tallin-St.Petersburg                                             3         EST or RUS
  Ventspils-Riga-Moscow                                            4         LAT or RUS
  Klaipeda-Vlnius-Minsk                                            5         LIT or BLR
  Kaliningrad-Kaunas                                               6         LIT or RUS
  Berlin-Warsaw-Minsk-Moscow                                       7         GER, POL, BLR or RUS
  Oslo-Stockholm                                                   8         NOR or SWE
  Oslo-Copenhagen                                                  9         NOR or SWE
Road branches (code 1):
  Narvik-Kiruna-Haparanda/Tornio-Vartius-St.Petersburg             11        NOR, SWE, FIN or RUS
  Helsinki-St.Petersburg-Moscow                                    21        FIN or RUS
  Tallinn-St.Petersburg                                            31        EST or RUS
  Ventspils-Riga.Moscow                                            41        LAT or RUS
  Klaipeda-Kaunas-Vilnius-Minsk                                    51        LIT or BLR
  Kaliningrad-Kaunas                                               61        LIT or RUS
  Berlin-Warsaw-Minsk-Moscow                                       71        GER, POL, BLR or RUS
  Oslo-Stockholm                                                   81        NOR or SWE
  Oslo-Gothenburg-Copenhagen                                       91        NOR or SWE




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                                        Analysis of infrastructure along the Northern Axis - Infrastructure




Railway branches (code 2):
  Narvik-Kiruna-Haparanda/Tornio-Vartius-St.Petersburg             12        NOR, SWE, FIN or RUS
  Helsinki-St.Petersburg-Moscow                                    22        FIN or RUS
  Tallinn-St.Petersburg                                            32        EST or RUS
  Ventspils-Jelgava.Moscow                                         42        LAT or RUS
  Klaipeda—Siauliai-Vilna-Minsk                                    52        LIT or BLR
  Kaliningrad-Vilnius                                              62        LIT or RUS
  Berlin-(Warsaw)-Minsk-Moscow                                     72        GER, POL, BLR or RUS
  Oslo-Stockholm                                                   82        NOR or SWE
  Oslo-Gothenburg-Copenhagen                                       92        NOR or SWE
Motorways of the seas (code 3)                                    13...      Not in Naxis
Inland waterways (code 4)                                         14…        Not in Naxis
Seaports (code 5)                                                 15…        Not in Naxis
Airports (code 6)                                                 16…        Not in Naxis
Border crossings (code 7):
Road borders:
  Narvik-Kiruna-Haparanda/Tornio-Vartius-St.Petersburg         1171-1173     NOR, SWE, FIN and RUS
  Helsinki-St.Petersburg-Moscow                                   2171       FIN and RUS
  Tallinn-St.Petersburg                                           3171       EST and RUS
  Ventspils-Riga.Moscow                                           4171       LAT and RUS
  Klaipeda-Kaunas-Vilnius-Minsk                                   5171       LIT and BLR
  Kaliningrad-Kaunas                                              6171       LIT and RUS
  Berlin-Warsaw-Minsk-Moscow                                   7171-7173     GER, POL, BLR and RUS
  Oslo-Stockholm                                                  8171       NOR and SWE
  Oslo-Gothenburg-Copenhagen                                      9171       NOR and SWE
Railway borders:
  Narvik-Kiruna-Haparanda/Tornio-Vartius-St.Petersburg         1271-1273     NOR, SWE, FIN and RUS
  Helsinki-St.Petersburg-Moscow                                   2271       FIN and RUS
  Tallinn-St.Petersburg                                           3271       EST and RUS
  Ventspils-Jelgava.Moscow                                        4271       LAT and RUS
  Klaipeda—Siauliai-Vilna-Minsk                                   5271       LIT and BLR
  Kaliningrad-Vilnius                                             6271       LIT and RUS
  Berlin-(Warsaw)-Minsk-Moscow                                 7271-7273     GER, POL, BLR and RUS
  Oslo-Stockholm                                                  8271       NOR and SWE
  Oslo-Gothenburg-Copenhagen                                      9271       NOR and SWE
Seaport borders                                                  1571…       Not in Naxis
Airport borders                                                  1671…       Not in Naxis
Other facility (code 8)
Other facility (code 9)



4.2.2     Road transport
When it comes to road transport along the Northern Axis, two different types of
regimes need attention: (1) operations, which are affected by the regulations, and (2)
infrastructure. With regard the operational side of road transport, the paramount
consideration is regulatory harmonisation, such as heavy goods vehicle (HGV) sizes
and weights across the borders. Differences in HGV regulations invariably increase
the cost of international road transport, as well as may present obstacles to access to
some markets. For these reasons the Commission has been vigilant in harmonising
commercial vehicle regulations across the EU, and today, the Community has the

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                                           Analysis of infrastructure along the Northern Axis - Infrastructure




benchmark values for vehicle sizes and weights that need to be obeyed. Also the new
member states are bound to meet these HGV regulations in their accession
agreements. In Table 4.6 both the EU and national regulations are shown. The table is
simplified and represents only the requirements for the heaviest articulated trailer
trucks.

At present, the countries in the Northern Axis area can be divided into five categories
when it comes to vehicle sizes and weights:
   • Old EU member countries that have applied fully the EU regulations.
       Currently they include Germany, Sweden and Finland
   • Sweden and Finland, which actually exceed the maximum requirements in two
       important respects: HGV gross weight (60 tons) and length (25,25 m) allowing
       a much higher efficiency of road transport in these sparsely populated
       countries.
   • New member states, which in principle adhere to the EU regulations. Their
       biggest remaining problem is the weak roads that do not allow the required
       11,5 ton axle weights yet on the entire network.
   • Non-EU countries of Russia and Belarus, which have the axle weight
       constraint of 10 tons on their main roads. Besides, their secondary road
       network has been built primarily for 6-ton axles. In addition, the gross HGV
       weight is relatively low (38 tons).
   • Norway meets the EU regulations in most respects, except in axle weights.
       Currently there are preparations underway to allow vehicle sizes and weights
       close to Sweden/Finland on selected routes.

Table 4.6 National regulations on Heavy Good Vehicle sizes and weights (A simplified table
representing only the requirements for the heaviest articulated trailer trucks)

             Unit        BY      EE       FI      DE      LV      LT       PL        NO      RU      SE      EU
Max    axle
weight      tonnes      10,00   11,501   11,50   11,50   10,00   11,50    11,50     10,00   10,00   11,50   11,50
Max    HGV
weight      tonnes      38,00   44,00    60,00   44,00   44,00   44,00    44,00     50,00   38,00   60,00   44,00
Max    HGV
height        m         4,00    4,00     4,20    4,00     4,00   4,00      4,00     4,00    4,00    4,50    4,00
Max    HGV
length        m         20,00   18,75    25,25   18,75   18,75   18,75   18,75/22   18,75   20,00   25,25   18,75
Max    HGV
width         m          n.a.   2,55     2,55    2,55     2,55   2,55      2,60     2,55    n.a.    2,60    2,55
HGV speed
limits       km/h        n.a.   90,00    90,00   80,00   80,00   90,00    80,00     80,00   n.a.    80,00   n.a.


The discrepancies of regulations, presented in Table 4.6, pose some restrictions to
businesses using the road branches of the Northern Axis. Most significant are the low
axle and gross vehicle weights of Russia and Belarus, which is a frequent problem to
EU-registered vehicles, particularly in the northern branches to/from Finland and
Sweden. Heavier loads can be used with a special permit, but the permit carries a
considerable cost and delay to obtain. The situation can be corrected fully only with a
large road network strengthening program in Russia, Belarus and some parts of the

1
    Max HGV weight on secondary roads with not rehabilitated pavements my be 10 tonnes



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                           of the infrastructure and “soft” measures proposed by the High Level Group
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new member states. However, these programs take considerable expense and time.
While heavier axle weights can invariably be used in these countries, quick
restrictions on HGV travel can be imposed e.g. during hot summer days or during
spring thaw.

Map of road branches is shown in Figure 4.1. Additional characteristics of each road
branch are shown in graphs a-h Table 4.7. The graphs include also generalised traffic
volumes of the branch.




Figure 4.1 Map of road branches of the Northern Axis and their codes




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                                        of the infrastructure and “soft” measures proposed by the High Level Group
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4.2.3                       Road branches


Table 4.7 a-i Characteristics of road branches of the Northern Axis

                                                                  11                 21              31                41                      51            61               71              81              91          Total
 Road length, km                                                1758                867             320               1121                     461          247            1745               91            122            6732
 4-lane share (incl.
 motorways)                                                     7%                 59 %           19 %                13 %                    80 %          5%             78 %             24 %          100 %            41 %
 Paved with asphalt                                           100 %                100 %         100 %                100 %                   100 %       100 %           100 %             100 %         100 %          100 %
 Urban areas
 w/restrictions                                                 4%                 20 %           13 %                4%                      3%            9%              4%              27 %           10 %             7%
 Speed limit 100 km/h or
 more                                                          21 %                20 %           19 %                0%                      74 %         42 %            78 %             24 %           73 %            38 %
 Speed limit 80 km/h or
 less                                                           3%                  0%              1%                0%                      0%            0%              0%              60 %            8%              2%
a.

   Country borders                                                                                                            Road type
                Norway
               1     Sweden              Finland                              Russia                                                      1
               Narvik                                                                          St. Petersburg                             Narvik                                                                   St. Petersburg

               2                                            Finland                Russia                                                 2
                                                            Helsinki St. Petersburg                Moscow                                                                          Helsinki St. Petersburg            Moscow

               3                                            Estonia Russia                                                                3
                                                            Tallinn       St. Petersburg                                                                                          Tallinn    St. Petersburg
                                                                                                                            B R A N C H
B R A N C H




               4                                                      Latvia               Russia                                         4
                                                     Ventspils Riga                               Moscow                                                                     VentspilsRiga                           Moscow

               5                                Lithuania Belarus                                                                         5
                                        Klaipeda                      Minsk                                                                                         Klaipeda                Minsk

               6                        Russia Lithuania                                                                                  6
                                      Kaliningrad Kaunas                                                                                                          Kaliningrad Kaunas
                   Germany
               7                 Poland                        Belarus                        Russia                                      7
                   Berlin               Warsaw                             Minsk                         Moscow                                Berlin               Warsaw                    Minsk                       Moscow

               8            Norway                                    9             Norway                                                8                                             9
               Oslo Swedish border    (dir. G othenbur g)                 Oslo Swedish border     (dir. Stock holm)                       Oslo Swedish border (dir. Goth en b urg )          Oslo Swedish border (d ir. Stock holm )
                                                                                                                                                1 Motorway
b.                                                                                                                                              2 High quality road
                                                                                                                                                3 Ordinary road

                                                                                                                            c.
   Number of lanes                                                                                                            Speed limit
               1                                                                                                                          1
               Narvik                                                                          St. Petersburg                             Narvik                                                                   St. Petersburg

               2                                                                                                                          2
                                                            Helsinki St. Petersburg                Moscow                                                                          Helsinki St. Petersburg            Moscow

               3                                                                                                                          3
                                                            Tallinn       St. Petersburg                                                                                          Tallinn    St. Petersburg
 B R A N C H




                                                                                                                            B R A N C H




               4                                                                                                                          4
                                                     VentspilsRiga                                Moscow                                                                     VentspilsRiga                           Moscow

               5                                                                                                                          5
                                        Klaipeda                      Minsk                                                                                         Klaipeda                Minsk

               6                                                                                                                          6
                                      Kaliningrad Kaunas                                                                                                          Kaliningrad Kaunas

               7                                                                                                                          7
                   Berlin               Warsaw                             Minsk                         Moscow                                Berlin               Warsaw                    Minsk                       Moscow

               8                                                  9                                                                       8                                             9
               Oslo Swedish border (dir. Gothen b urg )                   Oslo Swedish border (d ir. Stock holm )                         Oslo Swedish border (dir. Goth en b urg )          Oslo Swedish border (d ir. Stock holm )
                    2 lanes                                                                                                                     < 80 km/h
                    3 lanes                                                                                                                     80-100 km/h
                    4 lanes or more                                                                                                             > 100 km/h

d.                                                                                                                          e.




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  Current traffic                                                                                                 HGV, % of current traffic
              1                                                                                                               1
              Narvik                                                                  St. Petersburg                          Narvik                                                                  St. Petersburg

              2                                                                                                               2
                                                      Helsinki St. Petersburg             Moscow                                                                      Helsinki St. Petersburg             Moscow

              3                                                                                                               3
                                                      Tallinn    St. Petersburg                                                                                       Tallinn    St. Petersburg




                                                                                                                B R A N C H
B R A N C H




              4                                                                                                               4
                                                 VentspilsRiga                           Moscow                                                                  VentspilsRiga                           Moscow

              5                                                                                                               5
                                        Klaipeda                Minsk                                                                                   Klaipeda                Minsk

              6                                                                                                               6
                                      Kaliningrad Kaunas                                                                                              Kaliningrad Kaunas

              7                                                                                                               7
                  Berlin                Warsaw                    Minsk                       Moscow                              Berlin                Warsaw                    Minsk                       Moscow

              8                                             9                                                                 8                                             9
              Oslo Swedish border (dir. Goth en b urg )          Oslo Swedish border (d ir. Stock holm )                      Oslo Swedish border (dir. Goth en b urg )          Oslo Swedish border (d ir. Stock holm )
                   < 6000 vehicles per day                                                                                          < 10 %
                   6000-19999 vehicles per day                                                                                     10-20 %
                   20000-60000 vehicles per day                                                                                    > 20 %
                   > 60000 vehicles per day                                                                                        No information

f.                                                                                                          g.
  Forecast traffic 2020                                                                                           Accidents
              1                                                                                                               1
              Narvik                                                                  St. Petersburg                          Narvik                                                                  St. Petersburg

              2                                                                                                               2
                                                      Helsinki St. Petersburg             Moscow                                                                      Helsinki St. Petersburg             Moscow

              3                                                                                                               3
                                                      Tallinn    St. Petersburg                                                                                       Tallinn    St. Petersburg
                                                                                                                B R A N C H
B R A N C H




              4                                                                                                               4
                                                 VentspilsRiga                           Moscow                                                                  VentspilsRiga                           Moscow

              5                                                                                                               5
                                        Klaipeda                Minsk                                                                                   Klaipeda                Minsk

              6                                                                                                               6
                                      Kaliningrad Kaunas                                                                                              Kaliningrad Kaunas

              7                                                                                                               7
                  Berlin                Warsaw                    Minsk                       Moscow                              Berlin                Warsaw                    Minsk                       Moscow

              8                                             9                                                                 8                                             9
              Oslo Swedish border (dir. Goth en b urg )          Oslo Swedish border (d ir. Stock holm )                      Oslo Swedish border (dir. Goth en b urg )          Oslo Swedish border (d ir. Stock holm )
                   < 6000 vehicles per day                                                                      Number of accidents per million vehicle km per year
                   6000-19999 vehicles per day                                                                       < 0,2
                   20000-60000 vehicles per day                                                                      0,2 - 0,5
                   > 60000 vehicles per day                                                                          > 0,5
                                                                                                                     No information
h.
                                                                                                            i.


Branch 11. The Narvik – St.Petersburg road branch is the longest and the least
uniform of all branches. Being 1 760 km long it caters to very different types of
traffic, often of local or regional nature. Traffic volumes are typically low (< 6 000
vehicles/day). At the borders, excepting Sweden/Finland, traffic flows are quite low,
at or below 1 000 vehicles/day. However, in a few urban areas (Haparanda/Tornio,
Kemi, Oulu and St. Petersburg) traffic can be in the range of 10 000 – 15 000
vehicles/day.

HGV share is often high, at around 15% in Finland and Sweden. In Russia, the HGV
traffic is normally very high. On this route it is anywhere between 20-40%.

Growth of traffic is forecast to be moderate in all the countries. In Russia it is even
high.

The road is mostly an ordinary 2-lane road. There are, however, short motorway or 4-
lane sections in the busiest urban areas. Their length amounts to some 120 km.

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Table 4.8 Traffic on road branch 11, Narvik – St.Petersburg

             Current                   Traffic growth   2020
                          HGVs per
 Country     Traffic
                            day
              ADT
                                        Cars        HGVs
Norway
Min                n.a.         n.a.         n.a.         n.a.
Max                n.a.         n.a.         n.a.         n.a.
Sweden
Min              1 300          200         1,20         1,23
Max             11 400          570         1,32         1,33
Finland
Min                500           50         1,13         1,13
Max             15 000        1 100         1,40         1,40
Russia
Min              2 300          480         1,24         1,18
Max              6 700        1 700         1,99         2,94


Branch 21. Helsinki-Moscow. The road between Moscow and St. Petersburg is the
one of the most important and busy road branches of the Northern Axis with the direct
continuation to Helsinki, Finland. The branch caters to intercity traffic between
Moscow and St. Petersburg, as well as Southern Finland (Helsinki). Throughout the
traffic volumes are moderate or high (> 10 000 vehicles/day). In the large
metropolitan areas (Helsinki, St. Petersburg and Moscow) traffic can be quite high
reaching up to 100 000 vehicles/day. Even near the Finnish-Russian border the traffic
flow is still moderately high (5 000 – 10 000 vehicles/day).

The HGV flow is very high, because the road serves as Russia’s main route for
imports. HGV share is high ranging between 12-24% in Finland and anywhere
between 20-60% in Russia.

Growth of traffic is assumed moderate in Finland, and moderate to high in Russia. It
should be noted that the Russians are predicting the HGV traffic to go down in many
sections, most notably at the Finnish border.

Considerable stretches (60%) of the road are either motorways or 4-lane high quality
roads.

Table 4.9 Traffic on road branch 21, Helsinki-Moscow

             Current                   Traffic growth   2020
                          HGVs per
Country      Traffic
                            day
              ADT
                                        Cars        HGVs
Finland
Min              5 000        1 200         1,33         1,33
Max             18 300        2 750         1,33         1,33
Russia
Min              7 500        1 900         1,29         0,73
Max             95 000       28 000         2,56         1,20




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Branch 31. The Tallinn-St.Petersburg road is another important and fairly busy road
branch. The branch caters to intercity traffic between Tallinn and St. Petersburg and
smaller towns in between, such as the two borders towns of Narva (EE) and
Ivangorod (RU). Traffic flows are low and moderate (4 000 - 10 000 vehicles/day),
somewhat higher on the Estonian side. In the large urban areas (Tallinn,
Narva/Ivangorod and St. Petersburg) traffic volumes are high, 10 000 – 30 000
vehicles/day. Flows are the lowest near the Estonian-Russian border (4 000
vehicles/day).

HGV share is high ranging between 10-28% in Estonia and 30-40% in Russia. The
Estonians are predicting the HGV traffic to go down considerably, in some sections
by nearly one half. Also, in Russia the growth of HGVs is between none to moderate.

A considerable portion of the road in Estonia is motorway (60 km). In Russia, the
road is an ordinary 2-lane road.

Table 4.10 Traffic on road branch 31, Tallinn-St.Petersburg

             Current                  Traffic growth   2020
                         HGVs per
 Country     Traffic
                           day
              ADT
                                        Cars        HGVs

Estonia
Min              4 600        1 200        1,00         0,45
Max             28 700        4 600        1,58         0,79
Russia
Min              4 000        1 600        1,79         1,02
Max              9 000        3 200        1,96         1,22


Branch 41. The Ventspils-Riga-Moscow is similar to the Tallinn-St. Petersburg route
catering to intercity traffic between the two capitals (Riga and Moscow) and the
Latvian port city of Ventspils, as well as destinations between them. Traffic flows are
between low and moderate (2 000 - 10 000 vehicles/day). In the large urban areas
(Riga and its surroundings and Moscow) traffic volumes can be quite high, 35 000 –
70 000 vehicles/day. Flows are the lowest near the border (2 200-4 000 vehicles/day).
HGV share is high ranging between 10-30% in Latvia and 20-40% in Russia.

The Latvians are predicting a relatively brisk growth of HGV traffic, while the
Russians see a considerable drop on the entire route.

A large portion of the road in Latvia is a motorway or a high quality 4-lane road. In
Russia the road is mostly an ordinary 2-lane road. Near Moscow the number of lanes
increases to 4 and eventually to 6.




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Table 4.11 Traffic on road branch 41, Ventspils-Riga-Moscow

             Current                   Traffic growth   2020
                          HGVs per
 Country     Traffic
                            day
              ADT
                                        Cars        HGVs

Latvia
Min              2 200          610         1,80         1,60
Max             35 000        3 000         3,20         4,50
Russia
Min              4 000        1 600         1,20         0,70
Max             70 000       20 000         1,40         0,78


Branch 51. Klaipeda-Vilnius-Minsk is the main route between Lithuanian and
Belarusian capitals Vilnius and Minsk and the Baltic Sea port of Klaipeda. In
Lithuania the entire length of the route is a motorway and also some 30 km into
Belarus. The rest of the road in Belarus is an ordinary 2-lane road.

Traffic flows are quite high in Lithuania (up to 30 000 vehicles/day). In Belarus,
traffic is more moderate at 6 000 vehicles/day. HGV share is high ranging between
20-30%.

In Belarus, traffic is forecast to grow moderately.

Table 4.12 Traffic on road branch 51, Klaipeda-Vilnius-Minsk

             Current                   Traffic growth   2020
                          HGVs per
 Country     Traffic
                            day
              ADT
                                        Cars        HGVs

Lithuania
Min                n.a.         n.a.         n.a.        n.a.
                                n.a.         n.a.        n.a.
Max             29 000
Belarus
Avg.             6 000        1 400         1,35         1,66


Branch 61. The Kaliningrad (Russia)-Kaunas line is the branch of Branch 5. The road
connection is important for trade between Lithuania and Kaliningrad. It also provides
the road connection between Kaliningrad and the mainland Russia. The road is
primarily a 2-lane ordinary road, but has a short 4-lane section (13 km) in
Kaliningrad.

Traffic flows are moderate at 6 000 vehicles/day. Near Kaunas (LT) the traffic
volume is higher (13 000 vehicles/day). In Kaliningrad, traffic is seen to grow fast,
particularly as it concerns HGVs.




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Table 4.13 Traffic on road branch 61, Kaliningrad (RU)-Kaunas (LT)

             Current                       Traffic growth     2020
                            HGVs per
 Country     Traffic
                              day
              ADT
                                             Cars        HGVs

Lithuania
Min          n.a            n.a            n.a          n.a
                            n.a            n.a          n.a
Max                13 100
Kaliningrad/Russia
Min                 6 400          1 200         1,50          1,95
Max                 7 700          1 850         1,70          2,30


Branch 71. The Berlin-Warsaw-Minsk-Moscow road is the major branch between
Russia and Central Europe. The route is composed of variable, but mostly high quality
road sections. In Germany the route is motorway fully. Also in Russia and Belarus the
road has four lanes. Poland is busy implementing its motorway program, but still
several stretches of the route are ordinary 2-lane roads.

On this route traffic flows are high. In Germany the volumes are at 30 000 – 40 000
vehicles/day. Only at the border the flow drops below 20 000 vehicles per day. Also
in Russia the volumes are above 10 000. The Belarusian sections are moderate with
6 000 vehicles/day.

HVG flows are very high. The shares range throughout the road between 25-50%. At
borders the share can be as high as 60%.

In Germany, the anticipated growth of traffic comes entirely from HGVs. However,
there is no growth foreseen in HGV traffic in Belarus, which also is true for some
sections in Russia. It is seen in these countries that largely passenger car traffic is
growing.

Table 4.14 Traffic on road branch 71, Berlin-Warsaw-Minsk-Moscow

             Current                       Traffic growth     2020
                            HGVs per
 Country     Traffic
                              day
              ADT
                                             Cars        HGVs

Germany
Min                17 000          7 000         0,70          1,80
Max                44 000         10 500         1,24          2,60
Poland
Min                 9 440          2 549         n.a.          n.a.
                                                 n.a.          n.a.
Max                25 400          6 858
Belarus
Min                  n.a.           n.a.         n.a.          n.a.

Max                 6 100          2 100         1,36          1,00
Russia
Min                12 000          4 700         1,10          0,77
Max                83 000         17 000         2,00          1,33



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Branches 81 and 91. The Oslo-Stockholm and Oslo-Copenhagen branches are parts of
the Nordic Triangle TEN –T priority project. In this study only the sections that are in
Norway are considered.

The Norwegian part of the route Oslo-Copenhagen is being built into a motorway.
The last section will be completed in 2009. A similar but slower construction program
is also underway on route Oslo-Stockholm. This program will be completed only after
2015.

Traffic in the branches leading the Norwegian-Swedish border is moderate to high.
Branch 9 has high traffic over a considerable length (> 20 000 vehicles per day). The
sections near Oslo have the highest volumes.

Table 4.15 Traffic on road branches 81 (Oslo-Stockholm) and 91 (Oslo-Copenhagen)

             Current                  Traffic growth   2020
                         HGVs per
 Country     Traffic
                           day
              ADT
                                        Cars         HGVs

Norway - Branch 8
Min              5 400          810         n.a.          n.a
                                            n.a           n.a
Max             29 000        2 900
Norway - Branch 9
Min              9 000        1 620            n.a        n.a
                                               n.a        n.a
Max             49 000        4 900


4.2.4   Railway network
The Northern Transport Axis has two primary railway operation regimes that are quite
distinct. They can be called (1) European and (2) Russian due to their historical
backgrounds. They comprise respectively about 24% and 76% of the Northern Axis
railway network length of over 7 300 km. Most obvious difference between the two
regimes lies in the track gauges that quite effectively prevent direct train runs across
the borderline of the two systems.

Countries that use the European standard gauge of 1 435 mm are Germany, Sweden,
Norway and Poland. Also in many other ways the railways of these countries are quite
similar. Only Poland differs from the others in some important respects, such as
traction power, signalling system and maximum allowable axle weight.

The countries having their railway systems originating from Russia comprise the
majority of the railway network of the Axis: Belarus, Estonia, Finland, Latvia,
Lithuania and Russia. Track gauge is 1 520 mm, even if in Finland it is a bit wider
(1524). With the exception of Finland, the railway systems of these countries are
practically identical due to their long common history. Crossing the national borders
by train does not present any physical obstacles particularly between Russia, Belarus,
Estonia, Latvia and Lithuania. The border between Russia and Finland is not quite so
easy. Different systems of traction power and signalling necessitate always the change



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of locomotive at the border. Alternatively specific dual-system locomotives must be
used.

It should be added that the European Railway Agency (ERA) has analysed the
relationship between the 1435 mm and the 1520/1524 mm railway systems as far as
technical and operational aspects and the possible convergence of the two systems
(keeping apart the gauge differences) are concerned. The Agency is also currently
assessing the technical and economical feasibility of specific Technical Specifications
for Interoperability (TSI) valid for the 1520/1524-mm railway system. In this, it
cooperates with the OSJD ("Organization for the Cooperation of Railways") in order
to gather information on the existing technical standards and specifications of the
broad gauge system.

Table 4.16 Characteristics of the Northern Axis railway network by country
            Unit     BY        EE       FI      DE       LV      LT      PL      NO        RU             SE      EU
Railway
length      km      766       210      657      85      456     537     723      350      2936           604      n.a.
Track
gauge       mm      1520      1520     1524    1435     1520    1520    1435     1435     1520           1435     n.a.
Max axle                               22,5-                            22,1-   22,5-                     25-
load        ton     22,5      32,0      30      22,5    23,0    22,5    21,6      30       22,5           30      n.a.
Max train           800-                                                         500-      800-
length       m      1 000     800      925      750     850     850     600       600     1 000           750     n.a.
Max train                                                                       4 000-    2 600-         up to
load        ton     5 000     5 500 2 700      <3 000   5 500   5 500   3 000   6 000     6 000          8 500    n.a.
Loading      UIC 1T             T                        GB
gauge       class (nat.)      (nat.)   >GC      GB      (nat)    GC      GB      nat.    1T (nat.)        GC      n.a.
Signalling                                     ERTMS
system     Type  DSS          DSS      DSS       3      DSS     DSS     WSS     DSS       DSS            CSS     ERTMS
Traction                                                                                 Dsl/AC2/
power      Type AC2/Dsl        Dsl     AC2      AC1      Dsl    AC2     DC3     AC1       DC3            AC1      n.a.

Notes:      WSS -           Warning stop                        AC1 -    15kV/16Hz              nat. -     national
                            system
            DSS -           Discrete speed                      AC2 -    25 kV/50 Hz            n.a. -     not applicaple
                            supervision
            CSS -           Continuous speed                    DC3 -    3000 V
                            supervision
            ERTMS -         European Railway Traffic            DSL -    Diesel
                            Management System

In addition to track gauge, the following track characteristics are important from
operational point of view:

   Maximum axle load seems to be fairly uniform of 22,5 tons (225 kN) throughout
   the Northern Axis railway network. Some 28% of the Axis network allows also
   higher than 22.5-ton axles, but about 10% has a lower limit (Poland). Estonia has
   the highest axle loads of 32 tons. High axle loads can be found also in Sweden and
   Norway on the ore line from the mining region in Northern Sweden to the Narvik
   and Luleå ports. In Finland upgrading to 30-ton axles is underway on mainlines.

   Maximum train length is dictated by the length of platforms and passing sidings for
   freight trains. The UIC considers 750 m as an unofficial desired standard in


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 Europe. The Axis railways meet generally this requirement. Only in Norway the
 train length is restricted to 500-600 m; that is less than 5% of the Axis network.

 Maximum trainload is another characteristic that determines the capacity of a
 railway. In the EU member states the typical limit is 3 000 tons, prevailing over
 some 80% of the total line length. Largely due to the legacy of the Soviet Union
 allowable trainloads are much greater on most of the Axis network, up to 5 000 –
 6 000 tons. Another area of high trainloads is again the mine region in Northern
 Sweden and its railway connections to the seaports. Only the Axis railways in
 Finland, Germany and also in some links in Russia are somewhat below the 3 000-
 ton limit.

 Loading gauge determines the maximum heights and widths of locomotives and
 wagons. There is a plethora of loading gauges around that have been developed
 solely for national purposes. The UIC has defined a harmonised system of loading
 gauges, which can be used as a standard and a guide for classifying the railway
 lines. In Europe, the UIC class GB is a dominant one accounting for nearly 50% of
 the track length. GC is a better class allowing higher loads. In the Russian system
 class T is a standard and is close to UIC’s class GC. Thus, it is believed that
 loading gauge does not present a constraint to international trains.

 Signalling systems have typically been developed using some national and track
 specific technologies that have evolved in different directions in the axis countries
 over time. At present, Europe has nearly two dozens of different signalling designs,
 which present a major problem to cross-border railway traffic on the EU-wide
 railway network. To overcome this problem the EU has developed the European
 Rail Traffic Management System (ERTMS) based on the European Train Control
 System (ETCS). It appears that the ETCS will eventually become the standard on
 main railway lines within the EU.

 The second component of ERTMS is GSM-R, which is a specific GSM-based
 communication technology for the railways. As of now, only Germany has adopted
 the full ERTMS/ETCS/GSM-R on its part of the Northern Axis railways. Other EU
 member states have currently different degrees of continuous or discrete speed
 supervision systems in use. It can be assumed that they will eventually migrate
 towards full ERTMS/ETCS/GSM-R capacities.

 Traction power is another feature of the railway systems that has been developed
 nationally, although there is already considerable homogeneity in this respect. At
 present, 2/3 of the Northern Axis railway network has been electrified. In the
 European network, 15kV/16Hz is the dominant technology, while in the network
 based on the Russian legacy the electrification is typically 25kV/50Hz. In Russia,
 Estonia, Latvia and particularly in Poland there are sections using still the old DC
 3 000 V system. However, diesel locomotives are used in Estonia and Latvia to
 pull freight trains on to/from Russia. The electrified railways (DC3000) are used
 mainly for commuter traffic near Tallinn and Riga.




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There are nine distinct branches in the Northern Axis railway network that are
described in Table 4.17 and in following Chapter 4.2.5. Figure 4.2 shows a map of the
railway branches. The graphs a-l of Table 4.18 present characteristics of each of the
Northern Axis railway branch.

Table 4.17 Rail branches of the Northern Axis

                    12       22       32     42     52     62     72      82      92     Total    Share
Railway lenght     1938     1026     321    1036    569   276    1846     143     169    7324    100,0 %
Double track       353       766      89    375     569   276    1846     21      60     4355    59,5 %
Diesel             410        0      335    935     412   276      0       0       0     2368    32,3 %
Electrification    1528     1026     -14    101     157     0    1846     143     169    4956    67,7 %
Axle load > 22,5   482       212     224      0      0      0    1123      0       0     2041    27,9 %
Axle load < 22,5    0         0       0       0      0      0     723      0       0      723     9,9 %
European track
gauge 1435         642        0       0       0      0      0     808     143     169    1762    24,1 %
Russian/Finnish
gauge
1520/1524          1296     1026     321    1036    569   276    1038      0       0     5562    75,9 %




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Figure 4.2 Map of railway branches of the Northern Axis and their codes




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Table 4.18 a-l Characteristics of railway branches of the Northern Axis
  Country borders                                                                                                         Railway Type
              Norway
              1                 Sweden                 Finland                        Russia                                          1
              Narvik                                                                                St. Petersburg                    Narvik                                                                      St. Petersburg

              2                                                Finland                 Russia                                         2
                                                                                                                                                                            Helsinki      St. Petersburg             Moscow
                                                            Helsinki        St. Petersburg             Moscow

              3                                                  Estonia Russia                                                       3
                                                                                                                                                                                 Tallinn St. Petersburg




                                                                                                                        B R A N C H
                                                                 Tallinn St. Petersburg
B R A N C H




                                                                                                                                      4
              4                                                      Latvia                Russia
                                                                                                                                                                          Ventspils                                  Moscow
                                                        Ventspils                                      Moscow
                                                                                                                                      5
              5                                     Lithuania Belarus                                                                                          Klaipeda                 Minsk
                                             Klaipeda                      Minsk
                                                                                                                                      6
              6                             Russia Lithuania                                                                                                 Kaliningrad Kaunas
                                          Kaliningrad Kaunas
                  Germany                                                                                                             7
              7                       Poland                   Belarus                       Russia                                       Berlin               Warsaw                   Minsk                       Moscow
                    Berlin                  Warsaw                        Minsk                       Moscow
                                                                                                                                      8                                            9
              8              Norway                                  9              Norway                                            Oslo Swedish border (dir. Gothen burg)           Oslo Swedish border (d ir. Stock holm )
                  Oslo Swedish border (d ir. Go th enb ur g)             Oslo Swedish border (d ir. Stoc khol m)                           Conventional
                                                                                                                                           High speed

a.                                                                                                                      b.
  Max axle load                                                                                                           Number of tracks
              1                                                                                                                       1
              Narvik                                                                                St. Petersburg                    Narvik                                                                     St. Petersburg

              2                                                                                                                       2
                                                                                                                                                                            Helsinki      St. Petersburg             Moscow
                                                            Helsinki        St. Petersburg             Moscow

              3                                                                                                                       3
                                                                                                                                                                                 Tallinn St. Petersburg
                                                                                                                        B R A N C H




                                                                Tallinn St. Petersburg
B R A N C H




                                                                                                                                      4
              4                                                                                                                                                           Ventspils                                  Moscow
                                                        Ventspils                                      Moscow
                                                                                                                                      5
              5                                                                                                                                                Klaipeda                 Minsk
                                             Klaipeda                     Minsk
                                                                                                                                      6
              6                                                                                                                                              Kaliningrad Kaunas
                                          Kaliningrad Kaunas
                                                                                                                                      7
              7                                                                                                                           Berlin               Warsaw                   Minsk                       Moscow
                    Berlin                  Warsaw                        Minsk                       Moscow                          8                                            9
              8                                                      9                                                                Oslo Swedish border (dir. Goth en b urg)         Oslo Swedish border (dir. Stock ho lm )
                  Oslo Swedish border (d ir. Goth e nb ur g)             Oslo Swedish border (dir. Stoc kho l m)                           1
                      < 22,5 t                                                                                                             2
                                                                                                                                           >2
                      22,5 t
                                                                                                                                           No information
                      > 22,5 t
                                                                                                                        d.
c.
  Track Gauge                                                                                                             Max speed
              1                                                                                                                       1
              Narvik                                                                            St. Petersburg                        Narvik                                                                      St. Petersburg

              2                                                                                                                       2
                                                        Helsinki          St. Petersburg           Moscow                                                                   Helsinki      St. Petersburg             Moscow

              3                                                                                                                       3
                                                               Tallinn St. Petersburg                                                                                            Tallinn St. Petersburg
                                                                                                                        B R A N C H
B R A N C H




              4                                                                                                                       4
                                                      Ventspils                                    Moscow                                                                 Ventspils                                  Moscow

              5                                                                                                                       5
                                           Klaipeda                      Minsk                                                                                 Klaipeda                 Minsk

              6                                                                                                                       6
                                         Kaliningrad Kaunas                                                                                                  Kaliningrad Kaunas

              7                                                                                                                       7
                    Berlin                 Warsaw                      Minsk                       Moscow                                 Berlin               Warsaw                   Minsk                       Moscow

              8                                                  9                                                                    8                                            9
              Oslo Swedish border (d ir. Go th e nb ur g)            Oslo Swedish border (d ir. Stoc kho lm)                          Oslo Swedish border (d ir. Gothen burg)          Oslo Swedish border (d ir. Stock holm )

                      1      1435 mm                                                                                                        < 80km/h
                      2      1520 mm                                                                                                        80-90 km/h
                      4      1524 mm                                                                                                        100-160 km/h
                                                                                                                                            > 160 km/h

e.                                                                                                                      f.




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  Traction power                                                                                                            Signalling system
              1                                                                                                                         1
              Narvik                                                                              St. Petersburg                        Narvik                                                                            St. Petersburg

              2                                                                                                                         2
                                                         Helsinki         St. Petersburg             Moscow                                                                       Helsinki         St. Petersburg            Moscow

              3                                                                                                                         3
                                                               Tallinn St. Petersburg                                                                                                    Tallinn St. Petersburg




                                                                                                                          B R A N C H
B R A N C H




              4                                                                                                                         4
                                                       Ventspils                                     Moscow                                                                      Ventspils                                   Moscow

              5                                                                                                                         5
                                            Klaipeda                    Minsk                                                                                         Klaipeda                   Minsk

              6                                                                                                                         6
                                          Kaliningrad Kaunas                                                                                                       Kaliningrad Kaunas

              7                                                                                                                         7
                    Berlin                  Warsaw                      Minsk                        Moscow                                   Berlin                 Warsaw                      Minsk                       Moscow

              8                                                  9                                                                      8                                                  9
              Oslo Swedish border (d ir. Goth enb urg )                Oslo Swedish border (d ir. Stock ho lm )                         Oslo Swedish border (d ir. Gothen b urg )              Oslo Swedish border (d ir. Stock ho lm )

                      Electrified AC 15kV/16Hz                                                                                                  Warning stop system
                      Electrified AC 25kV/50Hz                                                                                                  Discrete speed supervision
                      Electrified DC 3000V                                                                                                      Continuous speed supervision
                      Diesel                                                                                                                    European railway traffic manageme nt system


g.                                                                                                                        h.
 Current number of trains per day                                                                                           Current capacity utilisation, %
 (passanger trains + freight trains)
                                                                                                                                        1
              1                                                                                                                         Narvik                                                                                St. Petersburg
              Narvik                                                                              St. Petersburg
                                                                                                                                        2
              2                                                                                                                                                                      Helsinki         St. Petersburg              Moscow
                                                         Helsinki         St. Petersburg             Moscow
                                                                                                                                        3
              3                                                                                                                                                                            Tallinn St. Petersburg
                                                                                                                          B R A N C H




                                                               Tallinn St. Petersburg
B R A N C H




                                                                                                                                        4
              4
                                                                                                                                                                                   Ventspils                                      Moscow
                                                       Ventspils                                     Moscow

              5                                                                                                                         5
                                                                                                                                                                       Klaipeda                     Minsk
                                            Klaipeda                    Minsk

              6                                                                                                                         6
                                          Kaliningrad Kaunas                                                                                                         Kaliningrad Kaunas

              7                                                                                                                         7
                    Berlin                  Warsaw                      Minsk                        Moscow                                   Berlin                   Warsaw                       Minsk                        Moscow

              8                                                  9                                                                      8                                                      9
              Oslo Swedish border (dir. Gothenburg)                  Oslo Swedish border (dir. Stockholm)                                   Oslo Swedish border (d ir. Go the nbur g)              Oslo Swedish border (dir. Stoc kholm )
                      < 50 trains / day                                                                                                          < 70 %
                      50 - 100 trains / day                                                                                                      70-84 %
                      > 100 trains / day                                                                                                         85-99 %
                      No information                                                                                                             100 % or over

i.                                                                                                                                               No information

                                                                                                                          j.
  Current freight volume (per year)                                                                                         Forecast freight volume 2020 (per year)
              1                                                                                                                         1
              Narvik                                                                                St. Petersburg                      Narvik                                                                              St. Petersburg
              2                                                                                                                         2
                                                          Helsinki         St. Petersburg              Moscow                                                                       Helsinki         St. Petersburg             Moscow
              3                                                                                                                         3
                                                               Tallinn St. Petersburg                                                                                                     Tallinn St. Petersburg
B R A N C H




                                                                                                                          B R A N C H




              4                                                                                                                         4
                                                        Ventspils                                      Moscow                                                                     Ventspils                                     Moscow
              5                                                                                                                         5
                                             Klaipeda                    Minsk                                                                                         Klaipeda                    Minsk
              6                                                                                                                         6
                                          Kaliningrad Kaunas                                                                                                        Kaliningrad Kaunas
              7                                                                                                                         7
                    Berlin                  Warsaw                       Minsk                        Moscow                                  Berlin                  Warsaw                       Minsk                       Moscow
              8                                                    9                                                                    8                                                    9
                  Oslo Swedish border (d ir. Goth en b urg )           Oslo Swedish border (d ir. Stock ho lm )                             Oslo Swedish border (d ir. Goth en b urg )           Oslo Swedish border (d ir. Stock ho lm )
                      < 5 million tons                                                                                                          < 5 million tons
                      5 - 10 million tons                                                                                                       5 - 10 million tons
                      10,1 - 20 million tons                                                                                                    10,1 - 20 million tons
                      20,1 - 50 million tons                                                                                                    20,1 - 50 million tons
                      > 50 million tons                                                                                                         > 50 million tons
                      No information                                                                                                            No information

k.                                                                                                                        l.




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4.2.5     Rail branches
Branch 12. The Narvik – St.Petersburg rail branch is the longest and the least uniform
of all branches. Being nearly 2 000 km long the branch caters to very different types
of traffic. For most parts it is a freight railway. Very heavy freight flows (>20 million
tons) are found in the section St. Petersburg – Murmansk. High freight volumes are
also in Northern Sweden and Norway. Real high freight and passenger flows are in
the St. Petersburg region. Flows in Finland are moderate.

The rail branch has been largely electrified. Diesel driven sections are located at the
two borders: the Russian section leading to the Finnish border, and the Swedish
section leading also to the Finnish border. The biggest obstacle to any potential
through traffic is the change of track gauge at the border between Finland and
Sweden. Locomotives need to be changed at these two borders also for different
traction systems.

Table 4.19 Traffic on rail branch 12, Narvik – St.Petersburg
 Country    Passenger      Freight       Freight     Growth of
            trains/ day    trains/       volume,      freight
                             day         tonnes        2020




Norway
Min                 n.a.        n.a.          n.a.         n.a.
                    n.a.        n.a.
Max                                         16,00          n.a.

Sweden
Min                 n.a.        n.a.          1,0          n.a.
                    n.a.        n.a.                       n.a.
Max                                          16,0
Finland
Min                 n.a.        n.a.          0,8          n.a.
                    n.a.        n.a.                       n.a.
Max                                           4,9

Russia
Min                   0              8        6,2          n.a.
                                                           n.a.
Max                  37          60          76,0


Branch 22. Helsinki-Moscow. The railway between Moscow and St. Petersburg is one
of the most important and busy railways of the Northern Axis. It has the direct
continuation to Helsinki, Finland. This rail branch is predominantly a passenger
railway, but has considerable freight traffic in section St. Petersburg-Vyborg. Also the
sections close to the Russian-Finnish border on both sides have high freight flows.

There is currently a high-speed train service between St. Petersburg and Moscow,
which will be extended to Helsinki in the coming years, starting possibly in 2008. The
entire railway on the Russian side will be gradually converted into a high-speed
passenger railway. Freight trains are diverted to parallel routes. Therefore, over the
entire length of the railway in Russia freight traffic is forecast to decrease
dramatically. Only at the Finnish-Russian border considerable growth is expected.



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At present, locomotive change is necessary at the Russian-Finnish border due to
different electric systems in Finland and Russia. The new high-speed trains will have
dual-power systems so that they can cross the border without locomotive change.

Table 4.20 Traffic on rail branch 22, Helsinki-Moscow
 Country    Passenger      Freight       Freight    Growth of
            trains/ day    trains/       volume,     freight
                             day         tonnes       2020




Finland
Min                   8           4           0,3         0,84
Max                 200          61          10,1         8,33
Russia
Min                  10          10           4,6         0,11
Max                 114          34          34,5         1,95


Branch 32. The Tallinn-St.Petersburg railway is predominantly a freight line even if
some long-distance passenger trains are serving the line. The railway has very high
freight flows (over 20 million tons) from Russia to the Estonian ports and inside
Estonia due to transport of oil shale (40 million tons). This railway is electrified in
Estonia but only for the use of commuter trains. Diesel traction is used for freight
trains in this branch. Therefore, crossing the Russian-Estonian border does not present
any technical problems.

In the near future, the Russians anticipate transit freight trough Estonia to decrease
considerably, to more than half. However, the Estonians have assumed traffic to grow
slightly. On the other hand, the Russians see freight flows to increase greatly to the
new port of Ust-Luga near the Estonian border in Russia.

Table 4.21 Traffic on rail branch 32, Tallinn-St.Petersburg
 Country    Passenger      Freight       Freight    Growth of
            trains/ day    trains/       volume,     freight
                             day         tonnes       2020




Estonia
Min                   3              6        6,1          n.a.
Max                  18          32          38,0          n,a.
Russia
Min                   4          19          22,0         0,46
Max                   5          20          24,0         1,53


Branch 42. The Ventspils-Riga-Moscow is also predominantly a freight line with some
long-distance passenger service. However, commuter traffic is heavy in Moscow and
Riga. Freight volumes are about half of those on the Tallinn line (less than 10 million
tons).


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This railway is largely diesel powered; only the section near Moscow has been
electrified. Also near Riga there are electrified stretches (DC3000) for commuter
traffic. Crossing the Russian-Latvian border does not present any technical problems.

In the future, the Russians see freight traffic to Latvia to stabilise at 8-9 million tonnes
or slightly reduced. High traffic growth is, instead, forecast in section Moscow-
Velikie Luki, which is the second alternative route for diverting freight traffic away
from the Moscow-St. Petersburg high-speed line. In Latvia a growth of freight traffic
from Russia is still assumed.

Table 4.22 Traffic on rail branch 42, Ventspils-Riga-Moscow
 Country    Passenger      Freight       Freight     Growth of
            trains/ day    trains/       volume,      freight
                             day         tonnes        2020




Latvia
Min                   0              1        n.a.         1,20
Max                  38          19           n.a.         2,00
Russia
Min                   4          13          10,0          0,95
Max                  54          21          17,0          1,57


Branch 52. Klaipeda-Vilnius-Minsk is the third main freight route from the Russian
and Belarusian hinterlands to the Baltic Sea ports. The two others are Branches 3 and
4 above. Freight volumes are high (15-20 million tons) throughout the line. Also this
line is diesel-powered in Belarus, but Lithuania has electrified this railway. Crossing
the Belarus-Lithuania border does not present any technical problems.

About 20 million tonnes of freight uses this railway, normally crossing from Belarus
to Lithuania. A modest growth of traffic is predicted in the future. Both countries
seem to share largely the same view of the future traffic.

Table 4.23 Traffic on rail branch 52, Klaipeda-Vilnius-Minsk
 Country    Passenger      Freight       Freight     Growth of
            trains/ day    trains/       volume,      freight
                             day         tonnes        2020




Lithuania
Min                 n.a.        n.a.         15,7          n.a.
Max                 n.a.         55          20,0          1,28

Belarus
Min                  17          30          19,2          1,22
Max                  61          32          20,5          1,28




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Branch 62. The Kaliningrad (Russia)-Kaunas line is a branch of Branch 5. It is an
important supply and export route to and through Kaliningrad from the mainland
Russia. Freight is the dominant use of the route, but it also has a fair volume of
passenger traffic. The railway is not electrified and there are no technical problems
with crossing the Lithuanian-Russian (Kaliningrad) border.

About 17 million tons of freight is transported on this line. The Russians see a higher
growth of freight traffic than the Lithuanians do.
Table 4.24 Traffic on rail branch 62, Kaliningrad (Russia)-Kaunas
 Country    Passenger        Freight         Freight      Growth of
            trains/ day      trains/         volume,       freight
                               day           tonnes         2020




Lithuania
Min                  n.a.         n.a.            n.a.           n.a.
Max                  n.a.          28            17,3           1,18
Kaliningrad/Russia
Min                    9           17            16,6           1,60
Max                   13           17            16,8           1,66


Branch 72. The Berlin-Warsaw-Minsk-Moscow railway is the major branch between
Russia and Central Europe, as well as the EU. The route has high volumes of both
passenger and freight traffic (15-40 million tons), but mainly within each country.
Freight flows drop considerably at the Belarus-Polish border, where the European
standard gauge and the Russian standard gauge meet. At present, reloading of cargo
and change of trains for passengers are necessary at the border.

Growth of freight traffic is expected to be small or none in Russia and Belarus.
Table 4.25 Traffic on rail branch 72, Berlin-Warsaw-Minsk-Moscow
 Country     Passenger        Freight         Freight       Growth
             trains/ day      trains/         volume,      of freight
                                day           tonnes         2020




Germany
Min                   n.a.         n.a.            n.a.          n.a.
Max                   n.a.         117             n.a.          n.a.
Poland
Min                    25           14             n.a.          n.a.
Max                    85              48          n.a.          n.a.
Belarus
Min                    10                6          6,5         1,10
Max                    58              31         27,6          1,12
Russia
Min                    26              19         23,3          0,97
Max                    52              32         44,5          1,59




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Branches 82 and 92. The Oslo-Stockholm and Oslo-Copenhagen branches in Norway
are parts of the Nordic Triangle TEN –T priority project. In this study only the
sections that are in Norway are considered. Both railways are for passengers and
freight, but the Oslo-Stockholm line is more geared to freight. Near Oslo there is
heavy commuter traffic on both lines. Crossing the Swedish-Norwegian border does
not present any technical or regulatory problems.

Table 4.26 Traffic on rail branches 82 (Oslo-Stockholm) and 92 (Oslo-Copenhagen)
 Country    Passenger      Freight       Freight     Growth of
            trains/ day    trains/       volume,      freight
                             day         tonnes        2020




Norway/Branch 8
Min                  52              0        n.a.         n.a.
Max                 400          18           0,4          n.a.
Norway/Branch 9
Min                   6              6        n.a.         n.a.
Max                 210          16           n.a.         n.a.



4.2.6   Border crossings
With the break-up of the Soviet Union in early 1990s, new borders were drawn within
the previous socialistic block and even inside the old Soviet Union. As a result, new
borders emerged and new border crossings were built, which presented significant
delay to travellers. Since then, the situation has changed with the enlargement of the
EU, which impacted international borders possibly the most. At present, there are in
principle four kinds of border crossings between the Northern Axis countries:
    1. Free borders without any border formalities. They include traditionally the
        borders between Norway, Sweden and Finland, which have enjoyed free
        access for decades even before joining the EU.
    2. New borders between the old and new EU member states have become nearly
        free, such as the German-Polish border. Currently only quick checks of
        passenger passports are needed. With the enlargement of the Schengen area in
        2008, also these border formalities will be eliminated.
    3. The border between Russia and Belarus resembles the current border between
        old and new EU member states. Only quick personal checks are carried out.
    4. The EU external borders with Belarus and Russia are still old-fashioned, tight
        borders where full checks of personal travel and goods transport are carried
        out.

With the erection of new borders in the 1990s also new border stations with all
facilities were built at every border crossing of the Northern Axis. This was done
often with the financial assistance from the Community. As a consequence, the border
facilities are largely modern and often less than ten years old. All this time, however,
border problems at the external borders of the EU have received considerable
attention. One recent effort has been the EU-Russia Ad-Hoc Group on Transport
Logistics Problems, which has recently identified procedural and infrastructure

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problems of the road and rail border crossings between Russia and the neighbouring
EU countries. The group issued concrete recommendations and mandated the
permanent groups of the EU-Russia Transport Dialogue to implement its conclusions.

Road border traffic

There seems to be a shortage of traffic information of the road borders. Often data is
also conflicting and forecasts are typically non-existent. The tables below show the
combined data that have been available for the study about the EU-Russia/Belarus
borders.

Table 4.27 Traffic at road border stations
BRANCH 1                          VARTIUS (FI) – LYTTA (RU)
    daily traffic, annual average                                              annual     freight annual
    (AADT)                                                                     volume             passengers
                                                                    total
                                                          truck or number tons of tons of
                                                          van > 3.5 of       goods    goods    total
year   passenger car                  bus or coach        t         vehicles imported exported passengers
2006                           600                   3           73     676        n.a.     n.a.         n.a.
2010                           n.a.              n.a.           n.a.    n.a.       n.a.     n.a.         n.a.
2020                           n.a.              n.a.           n.a.    n.a.       n.a.     n.a.         n.a.
BRANCH 21                          VAALIMAA (FI) - TORFJANOVKA (RU)
     daily traffic, annual average                                    annual     freight           annual
     (AADT)                                                           volume                       passengers
                                                             total
                                                   truck or number tons of tons of
                                                   van > 3.5 of       goods    goods               total
year passenger car                 bus or coach    t         vehicles imported exported            passengers
                                                                                  2 416
2006                          2170              45      1200    3415      n.a.      801             2 645 636
2015                         2 840                   60        2 300   5 200       n.a.     n.a.    3 300 000
2030                         4 100               100           4 000   8 200       n.a.     n.a.    5 000 000
BRANCH 31                          NARVA (EE) - IVANGOROD (RU)
     daily traffic, annual average                                             annual     freight annual
     (AADT)                                                                    volume             passengers
                                                            total
                                                  truck or number              tons of tons of
                                                  van > 3.5 of                 goods    goods    total
year passenger car                 bus or coach   t         vehicles           imported exported passengers
2006                           888                   12         255    1155        n.a.     n.a.         n.a.
2010                           n.a.              n.a.           n.a.    n.a.       n.a.     n.a.         n.a.
2020                           n.a.              n.a.           n.a.    n.a.       n.a.     n.a.         n.a.
BRANCH 41                          TEREHOVO (LV) - BURACHKI (RU)
     daily traffic, annual average                                             annual     freight annual
     (AADT)                                                                    volume             passengers
                                                          total
                                                truck or number                tons of tons of
                                                van > 3.5 of                   goods    goods    total
year passenger car                 bus or coach t         vehicles             imported exported passengers
2005                           n.a.              n.a.           380     n.a.       n.a.     n.a.         n.a.
2010                           n.a.              n.a.           n.a.    n.a.       n.a.     n.a.         n.a.
2020                           n.a.              n.a.           n.a.    n.a.       n.a.     n.a.         n.a.




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BRANCH 51                          MEDININKAI (LT) - KAMENNY LOG (BY)
     daily traffic, annual average                                  annual     freight        annual
     (AADT)                                                         volume                    passengers
                                                           total
                                                 truck or number tons of tons of
                                                 van > 3.5 of       goods    goods            total
year passenger car                 bus or coach  t         vehicles imported exported         passengers
2006                           710              74         693     1477      0,48      1,29         n.a.
2010                           n.a.            n.a.        n.a.     n.a.      n.a.     n.a.         n.a.
2020                           n.a.            n.a.        n.a.     n.a.      n.a.     n.a.         n.a.
BRANCH 61                          KYBARTAI (LT) - CHERNYSHEVSKOE (RU)
     daily traffic, annual average                                   annual     freight       annual
     (AADT)                                                          volume                   passengers
                                                            total
                                                  truck or number tons of tons of
                                                  van > 3.5 of       goods    goods           total
year passenger car                 bus or coach   t         vehicles imported exported        passengers
2006                           576              24         238      839      0,02      0,02         n.a.
2010                           n.a.            n.a.        n.a.     n.a.      n.a.     n.a.         n.a.
2020                           n.a.            n.a.        n.a.     n.a.      n.a.     n.a.         n.a.
BRANCH 71                          KUKYRYKI/TERESOPOL (PL) - BREST (BY)
     daily traffic, annual average                                 annual     freight         annual
     (AADT)                                                        volume                     passengers
                                                          total
                                                truck or number tons of tons of
                                                van > 3.5 of       goods    goods             total
year passenger car                 bus or coach t         vehicles imported exported          passengers
2006                           n.a.            n.a.        n.a.     n.a.      n.a.     n.a.         n.a.
2010                           n.a.            n.a.        n.a.     n.a.      n.a.     n.a.         n.a.
2020                           n.a.            n.a.        n.a.     n.a.      n.a.     n.a.         n.a.


The tables above show that there are three basic categories of borders as follows:

   High volume border(s):
      1. Vaalimaa (FI)-Torfjanovka (RU) on Branch 21 is quite clearly the busiest
          border in terms of all vehicle categories.
   Moderate volume borders (over 1000 vehicles per day):
      2. Medininkai (LT)-Kamenny Log (BY), Branch 51
      3. Narva (EE)-Ivangorod (RU), which has a fair amount of local traffic. Branch
          31
   Low volume borders (less than 1000 vehicles per day):
      4. Terehovo (LV)-Burachki (RU) has a considerable HVG traffic, Branch 41
      5. Kybartai (LT)-Chernyshevskoe (RU), Branch 61
      6. Vartius (FI)-Lytta (RU), Branch 11

Railway border traffic

The lack of data harmonisation shows well at the railway border stations. First, in
many cases data is missing and, second, there are discrepancies in the data received
from different railway administrations. At the Russian border with Estonia there are
further difficulties with traffic forecasting after the abrupt reduction of freight flows
due to the dispute between Russia and Estonia in May 2007. In general, the most
complete border traffic data is available from the Russian and Belarusian borders.
This helps, because the traffic originating from and ending in these countries


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dominates the Northern Axis railway freight flows. Railway traffic at the EU external
borders with Belarus and Russia is shown in Table 4.28.

The Northern Axis has three categories of railway borders:
• High volume borders (over 15 million tons of freight per year), which serve
   Russian exports (Narva-Ivangorod, EE-RU), or primary traffic needs between
   mainland Russia and Kaliningrad (Kena-Gudogay, BY-LT and Kybartai-Nesterov,
   LT-RU).
• Medium volume borders (over 5 million tons of freight per year), which also serve
   Russian export. They are Vainikkala-Buslovskaya (FI-RU), Zilupe-Posin (LV-
   RU) and Brest (PL-BY).
• Low volume borders (less than 5 million tons of freight per year) are Vartius-
   Kivijärvi and Haparanda-Tornio, which specialise mainly in raw materials such as
   timber.

Table 4.28 Traffic at railway border stations

                                          BRANCH 1
                     Finland (Vartius)                        Russia (Kivijarvi)
           Passengers         Freight      Growth    Passengers         Freight     Growth
Current                 0,0         5,3         na                0,0         2,2        na
Yr 2020                 0,0         na          na                0,0         2,6        1,2



                                          BRANCH 2
                   Finland (Vainikkala)                     Russia (Buslovskaya)
           Passengers         Freight      Growth    Passengers         Freight     Growth
Current                 0,3         6,9         na                na          7,7        na
Yr 2020                 na          na          na                na        15,0         2,0



                                          BRANCH 3
                     Estonia (Narva)                         Russia (Ivangorod)
           Passengers         Freight      Growth    Passengers         Freight     Growth
Current                 0,2       22,8          na                na        21,3         na
Yr 2020                 na          na          na                na          9,2        0,4


                                          BRANCH 4
                      Latvia (Zilupe)                          Russia (Posin)
           Passengers         Freight      Growth    Passengers         Freight     Growth
Current                 na          na          na                na          9,1        na
Yr 2020                 na          na          na                na          8,6        1,0


                                          BRANCH 5
                     Lithuania (Kena)                        Belarus (Gudogay)
           Passengers         Freight      Growth    Passengers         Freight     Growth
Current                 na          na          na                na        19,2         na
Yr 2020                 na          na          na                na        24,5         1,3




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                                          BRANCH 6
              Kaliningrad/Russia (Nesterov)                  Lithuania (Kybartai)
           Passengers        Freight       Growth     Passengers        Freight     Growth
Current                 na       16,6           na                 na         na         na
Yr 2020                 na       27,3           1,8                na         na         na



                                          BRANCH 7
                        Poland ( )                             Belarus (Brest)
           Passengers        Freight       Growth     Passengers        Freight     Growth
Current                 na           na         na                 na         6,5        na
Yr 2020                 na           na         na                 na         8,0        1,2


The following conclusions can be drawn from the available data above:
• The Russians expect their trade flows to use largely their existing and new ports in
   the future. The outcome is that they do not see much of growth, rather a decline, in
   cross-border railway freight to Estonia and Latvia. For their part, the Estonians
   expect a modest growth until year 2011 and the Latvians have seen a brisk growth
   until this year.
• Basically there are two directions where the Russians see their freight flows by rail
   to grow: Finland and Kaliningrad.
• In addition, Belarus sees a moderate growth in the direction of Lithuania and
   Poland.




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           Analysis of infrastructure along the Northern Axis – Investments and financial commitments




5 Analysis of infrastructure along the Northern Axis –
  Investments and financial commitments

5.1   Data collection

Collection of investment information was performed at the same time than the
collection of data for transport infrastructure. The two parallel studies, the TEN-T
implementation study for the EU member states and the analysis framework study for
non-EU countries, carried out the investment data collection separately

Data collection has aimed at obtaining investment information, which deals with
already identified and prepared projects; that is, the projects that have been already
completed, programmed for investments or planned sufficiently so that their
implementation can realistically be seen in the timeframe of the study; that is by 2013
and 2020.

It has to be pointed out, however, that the received information is heterogeneous,
because in most countries only the projects that have been decided or programmed
have been reported. Mostly this covers the next few years with a time horizon until
2010 or 2013. The projects that are more distant in time have usually not been
reported or they are reported only occasionally. This is quite understandable from the
transport authorities’ point of view, but is not very conductive to the axis evaluation
process, particularly in the years after 2013. Conversely, it can be said that the
investment program will eventually be bigger than now presented. On the other hand,
it is not uncommon that even near-term projects need to be postponed for reasons that
crop up prior to or even during implementation years, such as lack of public financing
or public opposition. Thus, the volume of implemented investments until 2013 are
probably smaller than now reported.

Table 5.1 Collected investments data by study
TEN-T implementation study 2004-2005, Analytical support framework study,
basic data collection                 additional data collection
Project description                                    Measure types are more detailed
Total project cost
Measure type                                           Project card with more descriptive
Length of project                                      information:
Start/End years                                            Project name
Stage     of    project    (completed,  under              Project owner
construction, under study, planned)                        Project description – free format
If under study, what type of study                         Reason for project/problem
Expenditure/investment until 2003, 2004-2013,              Socio-economic impacts
or 2014-2020                                               Benefits/costs
Source of funding                                          Environmental Impacts
                                                           Availability of project reports over
                                                           internet




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5.2     Investments in the Northern Axis infrastructure

The investments based on the collected information are as follows:

Total investments in the Northern Axis                      21,8 billion euros

of which
• share of investments in roads                             14,2 billion euros (65%)
• share of investments in railways                           7,6 billion euros (35%)
• investments in the period 2007-2013                       18,8 billion euros (86%)
• investments in the period 2014-2020                        3,0 billion euros (14%)

Table 5.2. Summary of investments in the Northern Axis 2007-2020

                                                     SUMMARY
                              Road                                   Rail                   TOTAL           Share %
                 2007-2013   2014-2020      Total    2007-2013     2014-2020       Total    2007-2014
New
construction       11499,3      1239,0     12738,3        324,4             30,0    354,4       13092,7       60,1 %
Rehabilitation       121,1           0,0     121,1          50,2             0,0     50,2           171,3      0,8 %
Upgrade             1153,0       191,0      1344,0       5681,0        1491,3      7172,3        8516,3       39,1 %
Total              12773,4      1430,0     14203,4       6055,5        1521,3      7576,8       21780,3      100,0 %
Share %             58,6 %       6,6 %     65,2 %        27,8 %         7,0 %      34,8 %       100,0 %



Table 5.3 Investments by country in the Northern Axis 2007-2020


                      Investments by Country (MEURO)


                                         BY EE
                                      SE 2 % 1 % FI
                                      1%         4 %DE
                                                    2%
                                                       LV
                                                       9%
                                                                     LT
                        RU                                           5%
                       46 %                                          NO
                                                                     2%



                                                              PL
                                                             28 %




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The summary of investments in Table 5.3 indicates that Russia and Poland are the
largest investors in the Northern Axis transport system accounting for 46% and 24%
of the total program, respectively. Latvia has the third largest program with a 9%
share. The rest of the countries have shares at 5% or less.

Two-thirds of all the axis investments are allocated to roads, which is largely due to
the very large motorway investments programs of Russia and Poland. Also Estonia
and Finland have bigger road than railway programs. On the other hand, there are
several countries where investments in railways dominate such as Germany, Sweden,
Belarus, Latvia and Lithuania. Norway is the only country, which has not reported
any railway investments, see Table 5.4.

Table 5.4 Investments by country and mode in the Northern Axis 2007-2020

Country          Road       Rail
BY                9,0 %     91,0 %
EE               76,6 %     23,4 %
FI               73,4 %     26,6 %
DE                0,0 %    100,0 %
LV                4,3 %     95,7 %
LT               38,6 %     61,4 %
NO              100,0 %      0,0 %
PL               70,7 %     29,3 %
RU               81,9 %     18,1 %
SE                0,0 %    100,0 %

There are two branches of the Northern Axis which receive most of the investments
by a large margin:
• Branch 2, Helsinki-St. Petersburg-Moscow, which receives 42% of all
    investments in the Northern Axis. Russia accounts for more than 90% of the
    Branch 2 investments. Also about 90% go to motorway projects.
• Branch 7, Berlin-Warsaw-Minsk-Moscow, which receives about a third of all
    investments. Polish investments dominate in Branch 7 accounting for about 75%
    of all expenditures. The rest of the expenditures are nearly evenly divided between
    Germany, Belarus and Russia. Almost two-thirds go to motorway projects.

Table 5.5 Investments by branch in the Northern Axis 2007-2020
 Investments by Branch (MEUR)

                  BR9             BRANCH                            Total     Share
                  0%              Br 1 Narvik-St. Petersburg        1259,2      5,8 %
          BR8
          2%         BR1          Br 2 Helsinki-Moscow              9165,3     42,1 %
                     6%
                                  Br 3 Tallinn-St. Petersburg        300,3      1,4 %
  BR7                             Br 4 Ventspils/Riga-Moscow        1853,7      8,5 %
  34 %                            Br 5 Klaipeda/Vilnius-Moscow       853,0      3,9 %
                           BR2    Br 6 Kaliningrad-Kaunas            377,5      1,7 %
                           42 %   Br 7 Berlin-Warsaw-Moscow         7442,0     34,2 %
    BR6                           Br 8 Olso-Stockholm                530,0      2,4 %
    2%                            Br 9 Oslo-Copenhagen                  0,0     0,0 %
     BR5 BR4 BR3                  TOTAL                            21781,0    100,0 %
     4% 9% 1%



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5.3   Investments relative to GDP
As shown in Table 5.3 and Table 5.6 two countries out of ten plan to make 72% of all
reported investments in the Northern Axis in the period until 2020. The countries are
Russia and Poland. Latvia (9%) is a distant third followed by Lithuania, Finland,
Belarus, Germany and Norway with shares between 2,5%-5,6%.

Table 5.6 Investments by country, 2007-2020

   TOTAL INVESTMENTS
Country    Total  Share
BY          536,9   2,5 %
EE          274,2   1,3 %
FI          958,0   4,4 %
DE          500,0   2,3 %
LV         1838,2   8,4 %
LT         1180,0   5,4 %
NO          530,0   2,4 %
PL         5811,0  26,7 %
RU         9847,0  45,2 %
SE          305,0   1,4 %
Total     21780,3 100,0 %


Table 5.7 Investments as a share of GDP, 2007-2020

 SHARE OF GDP 2007-2013

BELARUS                   0,27 %
ESTONIA                   0,30 %
FINLAND                   0,09 %
GERMANY                   0,00 %
LATVIA                    1,70 %
LITHUANIA                 0,71 %
NORWAY                    0,03 %
POLAND                    0,33 %
RUSSIA                    0,19 %
SWEDEN                    0,02 %

Latvia’s axis investments appear very large when compared to the country’s GDP.
The Latvian investments are meant for upgrading and modernising the existing
railway between the Russian border, Riga and the Port of Ventspils. As there has not
been given any timetable for the investments, they have been assumed to take place in
the first planning period of 2007-2013. With this assumption they account for 1.7% of
the Latvian GDP in those years. The EU member state average for transport
investments is now slightly below 1% of GDP, which however represents a low level
by common understanding. Even if it is likely that the investments of this magnitude
in Latvia take longer and extending beyond 2013, they seem large for the country.




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The declared investments in Lithuania (0,71%), and possibly also in Estonia (0,30%),
Belarus (0,27%) and Poland (33%), seem relatively large for the countries. This may
not be excessive, if it is remembered that the road and railway links that constitute the
axis in these countries are also important national transport routes and are likely to
take a considerable share of transport investments in any given time.




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                                                              Transport Demand – exogenous scenarios




6 Transport Demand – exogenous scenarios

6.1   Research framework
The aim of building exogenous scenarios is to develop a base for forecasting future
trade and transport flows which are very much dependent on the development of the
population, GDP, export rates, productivity etc.

The research framework of this study is presented in the Figure 6.1. Forecasts are
based on available knowledge of history and current situation. In the research area the
growth rates of GDP (gross domestic product), employed people (labour input) and
productivity (GDP/employed people) are estimated from time series. These growth
rates are projected to the future by taking into account available forecasts and “soft”
information of risks, possibilities etc. In addition, population factors are taken into
account. In the long run, population forecasts are the most reliable sources of
information. Especially fertility and age structure data is utilised in this case. Exports
are forecasted by using growth estimates of GDP and forecasts of export rates. Export
rates are predicted by taking into account trends of export rates and probable changes
in technology – especially transport technology and logistics. If export rates are
constant, growth rates of GDP and exports are the same. The same proportion is
always exported from output.

The research area covers Northern Axis countries Norway, Sweden, Finland, Baltic
countries, Poland, Germany, Russia and Belarus. For comparison also United States,
Japan and China are included in the research area.

As an introduction an analysis on the world level is presented. Instead of “employed
people”, “population” is now used. In many developing countries the unofficial sector
is very large. Official employment data is often unreliable or it is not available.
Instead of productivity, GDP per capita is now used. This is an indicator of
productivity and level of living.

Formally the analysis is the same in these two cases. The output indicator is gross
domestic product (GDP). In the research area analysis productivity = GDP/employed,
from which GDP = productivity*employed. By taking logarithms we have: ln GDP =
ln productivity + ln employed. This is the same as: growth rate of GDP = growth rate
of productivity + growth rate of employed. On the world level analysis, accordingly,
GDP per capita = GDP/population, from which GDP = GDP per capita*population,
and so on.

The method divides GDP growth into two components: growth of productivity (or
GDP per capita in world level analysis) and growth of employed people/labour input
(or population in world level analysis). This distinction is very important for
understanding the history and the future prospects of economic growth. Distinction
also enhances the reliability of long run forecasts because it is easier to predict
population and labour factors than growth of productivity.



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           World                               Research area
         Time series of                        Time series of
         Output (GDP) and                      Output (GDP) and
         Population                            employed people
                                               (labour input)



         Estimation   of                       Estimation       of
         growth rates of                       growth rates of
         population,                           labour input, GDP
         GDP and GDP                           and productivity
         per capita


                                                                             Trends
                                                                             of export
                      Available information of trends,                       rates,
                      risks and possibilities of national                    change     of
                      economies                                              technology

                       Fertility and age structure data



         Forecasts of the                  Forecasts of the                   Forecasts
         growth rates of                   growth rates of                    of export
         population, GDP                   employed people,                   rates
         and GDP per                       GDP and
         capita                            productivity


                                         Export forecasts




     •      GDP (gross domestic product) per capita = GDP/population
     •      Productivity = GDP/employed people
     •      Growth rate of GDP = growth rate of population plus growth rate of GDP per
           capita
     •      Growth rate of GDP = growth rate of employed people plus growth rate of
           productivity
     •      Export rate = Export as a percentage of GDP

Figure 6.1 Research framework.




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6.2             Growth prospects of the world
The world is divided into the following seven regions according to Angus
Maddison/OECD.

Four countries belong to the group of Western Offshoots; Australia, Canada, New
Zealand, and United States.

To Eastern Europe: Albania, Bulgaria, Czech Republic, Slovakia, Hungary, Poland,
Romania, Bosnia, Croatia, Macedonia, Slovenia, and Serbia/Montenegro.

To Former USSR: Armenia, Azerbaijan, Belarus, Estonia, Georgia, Kazakhstan,
Kyrgyzstan, Latvia, Lithuania, Moldova, Russian Federation, Tajikistan,
Turkmenistan, Ukraine, and Uzbekistan.

Mexico and other Central American countries are part of Latin America in this
classification.

Growth rates of population, GDP per capita and GDP are presented in Table 6.1 for
different regions of the world. Growth rates of the years 1950–2000 have been
estimated from the annual data (source: Maddison/OECD pp. 232–234) by semi
logarithmic models. Curves of the variables and absolute numbers from some years
are in Figure 6.2 – Figure 6.4. Population forecasts are in accordance with the medium
variant forecast of the United Nations.

                                5000
                                4500
                                4000
                                3500
                                3000
   (millions)




                                2500
                                2000
                                1500
                                1000
                                    500
                                      0
                                          1950   1960   1970   1980   1990   2000   2010   2020   2030
                   Wes tern Europe        305    326    352    367    378    391    393    389    382
                   Wes tern Offs hoots    176    212    242    270    298    337    367    397    425
                   Eas tern Europe         88     99    108    117    122    121    120    114    109
                   Form er USSR           180    214    242    266    289    291    265    251    234
                   Latin Am erica         166    218    286    362    443    524    600    670    730
                    As ia                 1382   1687   2093   2580   3103   3605   4077   4500   4861
                   Africa                 227    283    361    473    627    803    1009   1246   1507
                   World                  2524   3039   3685   4436   5260   6071   6826   7579   8270


Figure 6.2 Population by region.


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                                                         45000

                                                         40000
  GDP per capita (1990 dollars)




                                                         35000

                                                         30000

                                                         25000

                                                         20000

                                                         15000

                                                         10000

                                                          5000

                                                              0
                                                                  1950   1960    1970    1980    1990    2000    2010    2020    2030

                                             Western Europe       4579   6896    10195   13197   15966   19002   22170   25467   28962
                                             Western Off shoots   9268   10961   14560   18060   22345   27065   32088   37237   41987
                                             Eastern Europe       2111   3070    4315    5786    5450    5804    8678    12842   18133
                                             Former USSR          2841   3945    5575    6426    6878    4351    7787    12171   18348
                                             Latin America        2506   3133    3986    5412    5053    5838    7401    9438    11985
                                             A sia                712    1029    1530    2034    2781    3817    5242    7099    9541
                                             A frica              894    1066    1357    1536    1444    1464    1536    1772    2127
                                             World                2111   2777    3736    4520    5157    6012    7463    9193    11306


Figure 6.3 World GDP per capita by region.



                                                        10000
                                                         9000
                                                         8000
             GDP (10 billion 1990 dollars)




                                                         7000
                                                         6000
                                                         5000
                                                         4000
                                                         3000
                                                         2000
                                                         1000
                                                              0   1950   1960    1970    1980    1990    2000    2010    2020    2030

                                             Western Europe       140     225     359     485     603     743     871     991    1105
                                             Western Off shoots   164     232     353     488     667     911    1178    1478    1784
                                             Eastern Europe        19     30      47      68      66      70      104     147     197
                                             Former USSR           51     84      135     171     199     126     206     305     430
                                             Latin A merica        42     68      114     196     224     306     444     632     875
                                             A sia                 98     174     320     525     863    1376    2137    3194    4638
                                             A f rica              20     30      49      73      90      118     155     221     321
                                             World                533     844    1377    2005    2712    3650    5094    6968    9350


Figure 6.4 World GDP by region.


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The figures highlight the increasing role of Asia. In 1950 the GDP of Asia accounted
for 18 % of the GDP of the world. In 2000 the share was 38 %, and according to the
prognosis it will be 50 % in 2030. The historical GDP data in the analysis has been
corrected by purchasing power parities (PPP). Generally GDPs of developing
countries have been corrected upwards because of lower price levels. From this
follows that long run forecasts may slightly exaggerate the levels of currently poor
countries’ GDPs: price levels become more even in the long run. Asia’s share of the
GDP of the world may be under 50 % in 2030 even if growth rates were right. Next,
the analysis of Table 6.1 is continued.

Table 6.1 Growth of world population, GDP per capita and GDP by region in 1900 – 2030,
percent per year.

                               1900-      1950-        1980-    1990-     2000-      2010-      2020-
                               1950       1980         1990     2000      2010       2020       2030
Western   Population            0.53       0.67         0.25     0.33       0.0       -0.1       -0.2
Europe    GDP pc                0.92       3.62         2.16     1.72       1.6       1.4        1.3
          GDP                   1.45       4.29         2.41     2.05       1.6       1.3        1.1
Western   Population            1.45       1.40         0.97     1.20       0.9       0.8        0.7
Offshoots GDP pc                1.70       2.33         2.52     2.13       1.7       1.5        1.2
          GDP                   3.15       3.73         3.49     3.33       2.6       2.3        1.9
Eastern   Population            0.42       0.93         0.41    -0.09      -0.1       -0.5       -0.5
Europe    GDP pc                0.77       3.65         0.09     1.68       4.1       4.0        3.5
          GDP                   1.19       4.58         0.50     1.59       4.0       3.5        3.0
Former    Population            0.74       1.31         0.85     0.01      -0.9       -0.6       -0.7
USSR      GDP pc                1.68       3.07         0.97    -5.19       5.9       4.6        4.2
          GDP                   2.42       4.38         1.82    -5.18       5.0       4.0        3.5
Latin     Population            1.90       2.65         2.02     1.67       1.4       1.1        0.9
America GDP pc                  1.65       2.58        -0.32     1.49       2.4       2.5        2.4
          GDP                   3.55       5.23         1.70     3.16       3.8       3.6        3.3
Asia      Population            0.92       2.12         1.86     1.51       1.3       1.0        0.8
          GDP pc                0.22       3.55         3.19     3.25       3.2       3.1        3.0
          GDP                   1.14       5.67         5.05     4.76       4.5       4.1        3.8
Africa    Population            1.46       2.44         2.83     2.46       2.3       2.1        1.9
          GDP pc                0.80       1.90        -0.54     0.37       0.5       1.5        1.9
          GDP                   2.26       4.34         2.29     2.83       2.8       3.6        3.8
World     Population            0.97       1.91         1.71     1.44       1.2       1.1        0.9
          GDP pc                1.03       2.63         1.56     1.64       2.2       2.1        2.1
          GDP                   2.00       4.54         3.27     3.08       3.4       3.2        3.0

Source (years 1900 – 2000): The World Economy: Historical Statistics. Angus Maddison, OECD
Development Centre Studies. Paris 2003.
World Population Prospects. The 2000 Revision. Volume III: Analytical Report. United Nations. New
York 2002, p. 171.
Global Economic Prospects. The World Bank 2004. Washington DC 2003.




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Growth rate was at its highest in the world after the Second World War during 1950–
1980. Both population growth and productivity growth (measured by GDP per capita)
contributed to it. Population growth explained 42 % (= 100*1.91/4.63) and
productivity growth 58 % of the growth. After that population growth has decreased
and will keep on decreasing in the future. In 2020–2030 population will still
contribute to 30 % (= 100*0.9/3.0) of the growth in world level. Population decrease
is strong especially in the former USSR countries and in Eastern Europe. Population
growth is turning negative also in Western Europe. In the future the growth of the
whole research area will strongly depend on the productivity growth. It must also
compensate negative population growth which is not the case in any other parts of the
world. – Slowdown of the population growth is very good in world scale because
population growth increases demand for non-renewable raw materials and energy,
which decreases productivity growth in the long run.

In Africa population growth currently (2000 – 2010) explains 82 % of the economic
growth (= 100*2.3/2.8) and according to the forecast, in 2020–2030 still 50 %. In the
case of Africa, forecast is somehow target-oriented. It is assumed that strong obstacles
of growth such as corruption, political instability, low know how and education levels,
work motivation etc., will ease gradually. For Europe growth in Africa should offer
new bilateral long run possibilities in the spirit of win-win situations (which is
opposite to former colonial spirit; compare Asian “tigers” now). China is already
active in Africa.

Productivity growth has been negative only in three cases in Table 6.1: during 1980’s
in Africa and Latin America and during 1990’ss in former USSR just after the
collapse of the Soviet empire. Corresponding exceptional situations may take place
occasionally also in the future.

Productivity growth will decrease in old industrialised parts of the world. In post
industrial economies only small fraction of the labour force is employed in
manufacturing industries where productivity growth is highest. Most people are
working in service sectors where productivity growth is slow. Also prices of non-
renewable raw materials and energy will rise, which slows down the growth rate of
productivity. In newly industrialised parts or just industrialising parts of the world
decrease of productivity growth is smaller or productivity growth will remain
constant. In Africa where the take off phase of industrialisation is still ahead,
productivity will grow until 2030. Net effect of this to the whole world is that
productivity growth will be almost constant until 2030. The research area belongs
mainly to the first group where productivity growth will decrease.

Small decrease of growth rates in the world level in the forecasting period is the result
of the decrease of the growth rate of population, and not yet of productivity growth
slowing down. After 2030, productivity growth will decrease unless new
technological breakthroughs like information technology in past ten - twenty years
will emerge. Note also the remarkable increase of productivity growth from 1.6 in
1990–2000 to 2.2 in 2000–2010 on the world level. However, major part of this
increase is explained by the collapse of the Soviet Empire and globalisation.



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6.3     Growth prospects of the research area
In the following analysis “number of employed people” is used instead of
“population”. Accordingly, “productivity” substitutes “GDP per capita”. The two
methods give exactly the same results if number of employed people/population is
constant. The ratio is constant if employment rate, unemployment rate and age
structure are constants. Often they are not.

Statistical sources are Maddison/OECD, Statistical Annex of European economy by
European Commission, Statistical Central Offices (non EU-countries) and forecasts of
research institutes.

Historical trends behind the growth prospects is analysed in the Table 6.2. Growth is
divided into two components: growth of labour input which is measured by number of
employed people, and labour productivity which is output/labour input. Equation
holds if growth rates are estimated from the same periods as they are in all cases in
last period 2000−2007. Growth rates are estimated from time series by semi
logarithmic models.

Table 6.2 Growth rates of GDP, employed people and productivity, %/year 1980-2007 by ten
year periods and total fertility rates 2000-2005.

                                          GDP           Employed Produc- Total    fertility
                                                                 tivity  rate 2000-2005
EU-25               1980-1989
                    1990-1999              2.551          1.272       1.362
                    2000-2007              1.91           0.68        1.23               1.5
      EU-15         1980-1989              2.45           0.58        1.87
                    1990-1999              1.95           0.30        1.65
                    2000-2007              1.74           0.69        1.05               1.5
      EU-10         1980-1989
                    1990-1999              4.461          1.082       3.462
                    2000-2007               5.54          0.64        4.90               1.3
US                  1980-1989               3.59          1.91        1.68
                    1990-1999               3.24          1.67        1.57
                    2000-2007               2.65          0.89        1.76               2.1
Japan               1980-1989               3.74          0.75        2.99
                    1990-1999               1.34          0.37        0.97
                    2000-2007               1.66          0.03        1.63               1.3
China               1980-1989               8.09
                    1990-1999               7.66          1.10         6.56
                    2000-2007               8.47          1.38         7.09              1.7
Russia              1980-1989               2.72
                    1990-1999              -6.31          -1.99       -4.33
                    2000-2007               6.06           0.50        5.56              1.3




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Belarus               1980-1989               4.24
                      1990-1999              -2.56        -1.91         -0.65
                      2000-2007               7.45        -0.16          7.61              1.2
Germany               1980-1989               1.90         0.81          1.09
                      1990-1999               1.52        -0.00          1.53
                      2000-2007               0.85        -0.12          0.97              1.3
Poland                1980-1989               1.32
                      1990-1999               4.45        -0.003        5.413
                      2000-2007               3.82         0.32         3.50               1.3
Baltic                1980-1989               3.90
countries             1990-1999              -3.54        -3.25         -0.29
                      2000-2007               8.22         1.28          6.94              1.3
      Lithuania       1980-1989               4.56
                      1990-1999              -4.27        -1.78         -2.48
                      2000-2007               8.10         1.27          6.83              1.3
      Latvia          1980-1989               3.91
                      1990-1999              -4.43        -4.76          0.33
                      2000-2007               8.23         1.38          6.85              1.3
      Estonia         1980-1989               2.94
                      1990-1999              -0.69        -4.03          3.34
                      2000-2007               8.42         1.15          7.27              1.4
Finland               1980-1989               3.30         0.51          2.79
                      1990-1999               2.38        -0.81          3.19
                      2000-2007               2.90         0.86          2.04              1.7
Sweden                1980-1989               2.25         0.69          1.56
                      1990-1999               1.65         1.48          0.17
                      2000-2007               2.72         0.47          2.25              1.6
Norway                1980-1989               2.92         1.01          1.91
                      1990-1999               3.74         1.25          2.49
                      2000-2007               2.58         0.67          1.91              1.8
1
  1993-1999, 2 1995-1999, 3 1992-1999
Growth rates are estimated from annual time series by semi logarithmic models.
Total fertility rate (TFR) of a population is the average number of children that would be born to a
woman over her lifetime if she were to experience the current age-specific fertility rates through her
lifetime. It is obtained by summing the age-specific rates for a given time-point. The TFR required for
a population to reach equilibrium in size is about 2.1 (assuming infant mortality rates are not unusually
high).

Sources: The World Economy: Historical Statistics. Angus Maddison, OECD Development Centre
Studies. Paris 2003.
European Commission: Statistical Annex of European Economy. Spring 2006.
OECD Economic Outlook No. 81, 24-May-2007 http://www.oecd.org/dataoecd/18/26/271384.xls
Statistical Central Offices on non-EU-countries.
Statistical Central Office of Finland: World in Figures

To understand growth prospects, it is important to divide growth into two
components: productivity growth and chance of labour input (employed). In
2000−2007 in EU-15 productivity has explained from 1.74 %/year growth 60 % (=

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100*1.05/1.74) and employment growth 40 % (= 100*0.69/1.74). During the 1990’s
the growth of employed people explained 15 % of the total growth and 24 % during
the 1980s. In the future, change of employed will partly have even dramatic negative
effects on growth because of the ageing population and low fertility rates. This will be
seen from the forecasts presented in the following tables.

There seems to be a general trend that growth rates are declining as they do in “old”
EU countries (EU-15) including Germany, US and Japan. However, there are
exceptions to this rule. For instance, strong growth continues in emerging markets.
Take off phase in growth process has already taken place in former Soviet Union
countries after the collapse of the Soviet empire. Growth rates were negative in the
1990s but they have become very high after that. In China take off phase took place
already in 1980s without any changes in the political system but after some
liberalisation and reforms in the economy. Change towards capitalism has been
controlled unlike in former Soviet Union countries, in which it was partly hasty and
chaotic. This explains decreases both in productivities and employment in many
eastern European countries during 1990s. Growth presupposes certain sustainability
and predictability.

From the old EU countries, growth rates have been comparatively high in Ireland
(which does not belong to this study) and Nordic countries. These smaller countries
have been not as rigid as the bigger central and southern European countries. One to
two years ago growth prospects of these bigger countries seemed very inadequate.
This reflects the low growth rate of 1.05 %/year of productivity in EU-15 during
2000−2007. Present outlooks seem to be a little bit better. This holds especially to
Germany which has succeeded to perform some structural changes necessary for
growth. It is possible that Germany takes its position as the engine for European
growth which it missed after the unification of Eastern Germany to West Germany.

Fertility has strong lagged impact on employment. In all countries of Table 6.2,
except US, the impact will be negative. Population will be constant only if total
fertility rate is more than about 2.1. In former Soviet Union countries fertility is very
low, which has a very negative impact on long run growth prospects.

Growth forecasts of Table 6.3 are loosely based on Table 6.2. First growth rates of
employed and productivities are assessed separately. Then growth rates of GDP are
calculated as a sum of these. Generally growth rates of productivities are decreasing
in a very long run. Behind this trend there are certain reasons. Supply of non-
renewable raw materials is decreasing at the same time when their demand is strongly
increasing because of growth in many newly industrialised countries. Production costs
of many raw materials and energies will grow.




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Table 6.3 Growth rates of GDP, productivity and employed people, percent/year in 2000−2030.

                                             2000-2007            2007-2020             2020-2030
EU-15            Employed                       0.69                 0.0                   -0.3
”old”         EU Productivity                   1.05                 1.3                   1.4
countries        GDP                            1.74                 1.3                   1.1
EU-10            Employed                       0.64                 0.0                   -0.5
”new”         EU Productivity                   4.90                 3.7                   3.4
countries        GDP                            5.54                 3.7                   2.9
US               Employed                       0.89                 0.7                   0.5
                 Productivity                   1.76                 1.6                   1.4
                 GDP                            2.65                 2.3                   1.9
Japan            Employed                       0.03                 -0.1                  -0.5
                 Productivity                   1.63                 1.3                   1.3
                 GDP                            1.66                 1.2                   0.8
China            Employed                       1.38                 0.7                   0.3
                 Productivity                   7.09                 6.1                   4.2
                 GDP                            8.47                 6.8                   4.5
Russia           Employed                       0.50                 -0.4                  -0.5
                 Productivity                   5.56                 5.3                   4.3
                 GDP                            6.06                 4.9                   3.8
Belarus          Employed                      -0.16                 -0.2                  -0.7
                 Productivity                   7.61                 5.0                   3.7
                 GDP                            7.45                 4.8                   3.0
Germany          Employed                      -0.12                 -0.1                  -0.4
                 Productivity                   0.97                 1.4                   1.5
                 GDP                            0.84                 1.3                   1.1
Poland           Employed                       0.32                 -0.1                  -0.5
                 Productivity                   3.50                 3.5                   3.3
                 GDP                            3.82                 3.4                   2.8
Baltic           Employed                       1.28                 -0.1                  -0.5
countries        Productivity                   6.94                 4.5                   3.4
                 GDP                            8.22                 4.4                   2.9
Finland          Employed                       0.86                 -0.2                  -0.3
                 Productivity                   2.04                 2.1                   1.8
                 GDP                            2.90                 1.9                   1.5
Sweden           Employed                       0.47                 0.1                   -0.1
                 Productivity                   2.25                 2.1                   1.8
                 GDP                            2.72                 2.2                   1.7
Norway           Employed                       0.67                 0.2                   0.0
                 Productivity                   1.91                 1.9                   1.7
                 GDP                            2.58                 2.1                   1.7

Growth rate of gross domestic product (GDP) = growth rate of productivity + growth rate of employed.




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Focus of growth is changing from manufacturing industry to service industry where
the productivity growth is slower. In take off phase of economic growth more people
are working in manufacturing industries and productivity growth is very high. After
some point when productivity and income levels have grown enough, fewer and fewer
people are working in manufacturing; working places are going to less developed
countries which in turn reach take off phase in long run growth process. This old
process goes forward quickly now because of developed information and transport
technologies and it is called globalisation. One consequence is that export (and
import) rates are increasing substantially as shown in Table 6.6.

Productivity growth in some emerging markets will slow down also because incoming
flow of direct investments decreases when the country gradually achieves the wage
and productivity levels of developed countries. (Wages are determined by
productivities.)

Old EU countries (excluding Nordic countries) are an exception of the macro trend of
decreasing productivities. In the forecast it is assumed that these countries succeed to
go to the level of productivity growth where they should be taking into account their
level of development. Germany has shown clear signs of this but for example Italy
and Portugal have not yet shown any signs. Forecast is objective-oriented from this
part. Without structural changes EU-15 will be nearer to the productivity growth level
of 1.05 (fulfilled level in 2000−2007) than target-oriented forecasted level of 1.3–1.4
in 2007–2030. In best case EU-15 will reach the productivity growth level of US.
This is assumed to happen in 2020−2030. Despite of the same productivity growth
speed, growth rate is going to be even 73 percent higher (100*1.9/1.1) in US than in
EU-15 because of fertility, immigration and labour market factors.

In the period 2007−2020 population factors have greatest negative effect on growth in
Finland and in Belarus. In Belarus fertility is very low, only 57 % (= 100*1.2/2.1) of
the level where population renews itself. In Finland population is ageing more quickly
than in other countries because of the retirement of great age classes born after the
Second World War. (Ageing is fast also in Japan). – Population factors have superior
positive effect on economic growth only in US.

In the former Soviet Union countries fertility levels collapsed in insecure
circumstances of the collapse of the empire. This will have very big negative effect on
growth in the future especially if the country has low income level (as a consequence
of low productivity) which does not attract immigrants. Shortage of labour will be an
acute problem in many countries also in 2007−2010. The labour supply gap, produced
by the low fertility rate, can only partly be filled by immigration. This can be seen
from the case of an old immigration country Germany. First signs of labour shortages
can currently already be seen in Estonia. For Europe a real problem in the long run is
not the working places moving to China and India in connection with globalisation
but too slow productivity growth (especially EU-15) and too small birth rate
(especially EU-10 and eastern European non-EU countries). It is worth to notice that
leading global economic powers of future, US and China, do not have these problems.




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6.4   Risks
There are certain risks, which may decrease the forecasted growth rates substantially.
In EU-15 the risk is that countries do not perform the required structural reforms. In
that case productivity growth would in 2007–2020 be perhaps 1 %/year and in 2020–
2030 0.9 %/year. (General trend is that speed of productivity growth will decline in
developed countries). In this scenario Europe is degenerating to the second order
economic block, from which there are numerous examples in the history of the world.

The US has short run risks which are connected to incurring of a debt. However,
during last months outlook of “soft landing” has gained ground. Possible collapse of
the US economy would take place very quickly. China and other financiers would
withdraw their investments back. Stock prices would fall down some tens of percents
in some days all over the world. This is not an advantage to almost anybody. This risk
would materialise in some days and weeks when European risk of low productivity
growth materialises during tens of years, which is such a long time span that nobody
even realises it.

In the long run US economy is very strong, much stronger than the European
economy. The US produce innovations and commercialises them more effectively
than any other country. Majority of Nobel Prise winners are from the US – not
necessarily US citizens. Both finance systems and entrepreneur climates favour quick
commercialisation of innovations – which is not the case in Europe. Reaching the
productivity growth of the US presupposes structural changes from Europe also in this
respect.

The risk of the new EU-countries is that they remain economies of subsidiary
companies. Now they have direct investments but when the advantage of lower wages
gradually disappears because of the high productivity growth, the incoming flow of
direct investment will substantially decrease. The first signs of this can already be
seen. E.g. the direct investments from Finland are turning from Estonia to Russia and
China. The important reason for this is, in addition to lower wages, also the bigger
size of home markets of those countries. If EU-10 countries do not reach the path of
self sufficient growth e.g. by investing more in R&D, the productivity growth would
in 2007−2020 be perhaps 2.7 %/year and in 2020−2030 2 %/year (instead of 3.7 and
3.4 respectively).

Main risks in China and Russia are connected to politics. The development has been
stable in both countries in recent years. Markets have been opened restrictedly.
Reforms in legislation and WTO membership bring predictability. But behind there
are still political risks connected to change of power, deficiencies in democracy,
unstable regional development, very unequal distribution of the income and wealth,
low productivity of state-owned companies, too strong ambitions to the status of
superpower, isolationistic tendencies, corruption and organized crime. Especially
problems in China would have immediate big effects on world economy. It is
assumed that risks do not materialise and both countries go towards self sufficient
growth when they learn to produce also more demanding competitive industrial
products to the world markets, such as cars and electronics equipment as an example.
Correspondingly, exports diversify. Russians and Chinese buy noteworthy part of the

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productive means of western countries and Chinese also of the sources of raw
materials in developing countries. Russians have wealth because of oil and Chinese
because of frugality, the high savings rate.

In addition to economic and political risks also the environmental risks have to be
mentioned. They may directly affect the population and its living conditions and this
way also the growth rates discussed above. Especially counter measures against
global climate change may affect the GDP figures.

6.5   Nominal and real GDP forecasts
GDP numbers from year 2005 in Table 6.4 and Table 6.5 are from International
Monetary Fund (IMF). Numbers have been taken from Wikipedia. The forecasts of
the nominal and real (PPP) GDP in Table 6.4 are based on GDP growth rates
presented in Table 6.3. The forecasts of real GDP per capita (PPP) in Table 6.5 are
based on productivity growth rates presented in Table 6.3. The forecasts during the
years 2005−2010 are based partly on the observed growth rates in 2000−2007. In
cases where recent development differs from the period’s observed development,
numbers have been corrected. This is especially the case in Germany.

Index numbers of Table 6.4 can be changed to absolute numbers (millions US dollars
in 2005 prices) simply by multiplying nominal GDP index numbers by 13,070 and
multiplying real (PPP) GDP index numbers by 11,500.

It is important to note that in nominal and real forecasts growth rates are exactly the
same. Only difference is in starting levels. For example China’s GDP is in 2030 4.5
times higher than in year 2005 both in nominal and in real terms. China’s 4.8 times
higher real GDP in 2030 is explained completely by 4.8 times higher starting level in
2005. So, when looking at growth rates in Table 6.1, Table 6.2 and Table 6.3 they
apply as well to nominal and real purposes. In fact both EU and OECD publish
nowadays mainly only annual growth rates, when you avoid difficult questions of
what is the starting level and if it is real, who’s definition of PPP is used.




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Table 6.4 Nominal and purchasing power parity (PPP) GDP in 2005–2030 when EU-15 = 1000 in
2005.
Nominal GDP based on exchange rates
                       2005                        2010                2020                 2030
EU-25                    1033.0                      1130.0              1298.0               1461.0
    EU-15                1000.0                      1088.0              1238.0               1381.0
    EU-10                   33.0                        42.0                60.0                 80.0
US                        953.0                      1086.0              1363.0               1645.0
Japan                     349.0                       379.0               427.0                462.0
China                     171.0                       256.0               494.0                767.0
Russia                      58.0                        77.6              125.2                182.0
Belarus                      2.3                         3.3                 5.3                  7.0
Germany                   214.0                       234.7               267.0                298.0
Poland                      23.0                        27.7                38.7                 51.0
Baltic countries             4.2                         6.1                 9.4                 12.5
    Lithuania                2.0                         2.8                 4.3                  5.7
    Latvia                   1.2                         1.8                 2.8                  3.7
    Estonia                  1.0                         1.5                 2.3                  3.1
Finland                     15.0                        17.3                20.9                 22.5
Sweden                      27.0                        30.9                38.4                 45.5
Norway                      22.6                        25.7                31.6                 37.4

GDP (PPP): price level of the countries is controlled
                         2005               2010                       2020                 2030
EU-25                        1082.0           1183.6                     1359.6               1530.0
    EU-15                    1000.0           1088.0                     1238.0               1381.0
    EU-10                      82.0             104.4                     149.1                199.0
US                           1069.0           1218.0                     1528.7               1845.0
Japan                         340.0             369.2                     416.0                450.0
China                         820.0           1227.6                     2359.3               3663.0
Russia                        137.0             183.3                     295.7                430.0
Belarus                         6.5               9.3                       14.9                 19.8
Germany                       220.0             241.3                     274.5                306.4
Poland                         43.0              51.8                       72.4                 95.4
Baltic countries                8.6              12.5                       19.3                 26.0
    Lithuania                   4.2               5.9                        9.1                 12.1
    Latvia                      2.5               3.8                        5.8                  7.7
    Estonia                     1.9               2.8                        4.4                  6.2
Finland                        14.0              16.1                       19.5                 21.0
Sweden                         23.6              27.0                       33.6                 39.8
Norway                         17.0              19.3                       23.7                 28.1
Source for 2005 numbers: IMF/Wikipedia

In 2005 Chinese economy was only 18 % of the US economy (100*171/953) but after
price level correction it is 77 % (100*820/1069) of the GDP of US. Prices are much
lower in China than in US. The use of purchasing power parities (PPP) corrects


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differences in price levels. This is especially important when using GDP per capita
numbers as the indicator of differences in the level of living between countries (Table
6.5). In 2005 the level of living in China was ¼ (24/100) from the level of living in
EU-15. In 2030 it will be 2/3 (92/138). – In 2030 new member countries (EU-10)
almost reach the level of living of the old member countries (EU-15); Baltic States
even exceed it. However it is possible that realisation of any of the above-mentioned
risks will change growth prospects considerably.

Table 6.5 Gross domestic product (GDP) at purchasing power parity (PPP) per capita 2005 –
2030. Indexes where EU-15 (“old EU countries”) = 100 in 2005.
                               2005                2010                2020                 2030
EU-25                                92.3                99.1             115.9                137.0
    EU-15                           100.0               105.4             119.9                137.8
    EU-10                            52.0                66.0               94.9               132.6
US                                  138.0               152.3             178.5                205.0
Japan                               102.0               110.6             125.8                143.0
China                                24.0                33.7               60.9                 92.0
Russia                               36.8                48.2               78.5               118.4
Belarus                              25.7                37.1               47.4                 68.2
Germany                             101.8               110.8             127.3                147.7
Poland                               43.3                51.4               72.5               101.4
Baltic countries                     47.5                68.7             106.7                142.0
    Lithuania                        47.1                65.5             101.7                135.4
    Latvia                           42.2                62.7               97.4               129.6
    Estonia                          54.6                81.8             127.0                169.0
Finland                             104.0               115.0             141.6                169.0
Sweden                               99.6               111.3             137.0                163.7
Norway                              141.0               154.9             187.0                221.0

In Figure 6.5 GDP forecasts based on nominal and real differences between countries
have been presented. Growth rates are the same but starting levels differ. Two
methods give an especially big difference in the case of China. China does not reach
the GDP of EU -15 or US by 2030 if nominal differences (exchange rates) are used.
But after price level correction, by using real differences based on PPPs, China has a
double GDP compared to the US in 2030. Before 2030 China would lose the biggest
part of its price competitiveness because wages will grow, which also increases
product prices. Real starting level gives therefore exaggerated forecast to China. (See
also discussion after Figure 6.5).

Index numbers of Table 6.5 can be changed to absolute numbers (USD in 2005 prices)
simply by multiplying index numbers by 300.




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                                          4000
      GDP index (EU-15 in 2005 = 1000)


                                          3500

                                          3000

                                          2500                                                 Nominal
                                                                                               PPP
                                          2000

                                          1500

                                          1000

                                           500

                                             0




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Figure 6.5 Nominal and real GDP in 2030.


6.6                                      Export forecasts
The export forecasts in Table 6.6 are calculated from GDP forecasts by taking into
account probable changes in export rates. Generally export rates will grow because of
globalisation, and better and cheaper transport connections. In Russia the export rate
will probably decrease as a consequence of economic growth. The country is so huge
that economic growth will further more internal trade inside the country and in
addition export rates are very low in all developed big countries. Despite the decrease
of export rate, the exports will grow in Russia 2.4 fold in 2007−2030 as they do also
in new EU-countries. In the old EU countries exports grow 1.5 fold according to the
prognosis. Strong increase of the international trade presupposes corresponding
increase of the performance of the transport system.




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Table 6.6 Export forecasts.

                                    1990          2000          2007          2020          2030
EU-15         Export rate           28.0          36.1          41.6            45            48
”old” EU      Export index                                      100           128.0         150.7
countries     GDP index                                          100          118.3         130.6
EU-10         Export rate             31            55           63             67            70
”new” EU      Export index                                      100           170.6         237.2
count         GDP index                                          100          160.4         213.5
US            Export rate             9.6          11.2         11.6           12.5          13.0
              Export index                                      100           144.8         181.8
              GDP index                                          100          134.4         162.2
Japan         Export rate            10.4          11.0         17.5            23            25
              Export index                                      100           153.5         180.7
              GDP index                                          100          116.8         126.5
China         Export rate                          23.3         35*             40            40
              Export index                                      100           268.8         417.5
              GDP index                                          100          235.2         365.3
Russia        Export rate                          44.1         40*             37            36
              Export index                                      100           172.2         243.4
              GDP index                                          100          186.2         270.4
Belarus       Export rate                                       40*             45            50
              Export index                                      100           206.9         308.9
              GDP index                                          100          183.9         247.1
Germany       Export rate            24.2          33.4         46.9            53            55
              Export index                                      100           133.7         160.0
              GDP index                                          100          118.3         136.4
Poland        Export rate            26.2          27.1         42.9            47            50
              Export index                                      100           169.2         237.2
              GDP index                                          100          154.4         203.5
Baltic        Export rate                          54.8         65.1            69            72
countries     Export index                                      100           197.4         274.1
              GDP index                                          100          186.2         247.8
Finland       Export rate            22.5          43.5         45.4            48            52
              Export index                                      100           135.0         169.7
              GDP index                                          100          127.7         148.2
Sweden        Export rate            29.7          45.9         52.0            54            56
              Export index                                      100           137.8         169.2
              GDP index                                          100          132.7         157.1
Norway        Export rate                          46.7         43*             45            47
              Export index                                      100           137.1         169.5
              GDP index                                          100          131.0         155.1
* = estimate
Export rate = Exports of goods and services as a percentage of gross domestic product (GDP) at market
prices.
Export and GDP indexes = Export and GDP at constant prices when 2007 = 100.

Sources:
European Commission: Statistical Annex of European Economy. Spring 2006.
World Economic Factbook 2005/2006. Euromonitor International 2005.
Statistical Central Offices on non-EU-countries.


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                                   450

                                   400
    Export index when 2007 = 100




                                   350

                                   300
                                                                                              2020
                                                                                              2030
                                   250

                                   200

                                   150

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Figure 6.6. Export forecasts.


In Table 6.7, export forecasts are allocated to different countries in the research area.
Trade of Baltic countries is the weighted average of the three countries – not the trade
of the whole area. – If the value of trade index is the same as the value of the index of
the whole export, then country’s share of whole exports remains the same. Poland’s
share of Finnish exports remains the same. Both grow 1.7 fold by 2030. However,
Finland’s share of Poland’s exports grows a little bit (from 0.8 % to 1 %).
Correspondingly export from Poland to Finland grows 3 fold when whole export
grows 2.37 fold according to the forecast.

Pronounced decrease will take place in the shares of the trade between Russia and
Belarus. In 2005 Russia’s share of Belarus’ trade (exports and imports) was 48 %.
This share will decrease to 25 % if Belarus opens and reaches the path of strong
growth – as we assume in the prognosis. This happens in the long term forecast. In the
short and medium run the trade between Russia and Belarus still grows considerably.
Low wage levels and location close to the EU-15 countries – especially Germany –
attracts direct investments to Belarus. Relatively biggest increase of trade flows occur
in the exports from Belarus to Germany. Germany’s share of Belarus trade (exports
and imports) will grow from 5.6 % in 2005 to 9 % in 2030. German firms
manufacture in Belarus and export to Germany and other countries. Similar
globalisation in the close by regions will continue. This also reflects the trade flows
between the developed countries (Germany and the Nordic countries) and the
developing or newly industrialised countries (other countries in Table 6.7).

Russia’s share of Finland’s exports grows from 9 % in 2005 to 14 % in 2030. Long
border between countries is at the same time the biggest level of living difference in
the world. This opens also business opportunities. – Germany’s share of Poland’s


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exports decreases from very high 30 % level to 23 %. Russia’s share of Poland’s
exports increases from 3.8 % to 4.5 % as implied by trade index 280.

Table 6.7 Trade indexes between research area countries in 2030, when 2007 = 100.

Exporting Export destinations
Country   Russ Bela Germ                     Pola      Balti     Finl      Swed      Norw      Whole
                                                                                               export
Russia                    140       280       280       180       260       200       180        243
Belarus         160                 500       250       350       450       350       350        309
Germany         180       250                 160       170       160       150       150        160
Poland          280       270       180                 300       300       220       200        237
Baltic c        200       280       300       220                 200       180       150        274
Finland         260       300       180       170       150                 150       150        170
Sweden          200       250       170       190       180       150                 150        169
Norway          190       200       170       180       190       170       150                  170

6.7   Russian scenarios
Maximum and minimum scenarios of Russia are presented in Table 6.8.
Probable/medium scenario is the same as in Table 6.3 – Table 6.6. Russia is a member
of WTO in all scenarios. In the maximum scenario, Russia develops to pluralistic
democracy where many industries develop to high level and participate in
international division of labour. Examples of this are forest industry and ICT.
Entrepreneurship flourishes and growth rate is high. Structure of exports is many-
sided (Table 6.8:C). Middle class becomes wealthier and gains much more political
power. Freedom and wellbeing also reflect the development of population, which is
positive as the birth rates increase. In maximum scenario WTO membership is a
possibility, which offers many options that are fully utilised.

Table 6.8 Russian scenarios.
A Growth rates of employed people, productivity and GDP percent/year
                                               2007-2020           2020-2030
Maximum scenario Employment                       -0.3                -0.3
                    Productivity                  6.3                 5.3
                    GDP                           6.0                 5.0
Probable/medium     Employment                    -0.4                -0.5
scenario            Productivity                  5.3                 4.3
                    GDP                           4.9                 3.8
Minimum scenario Employment                       -0.5                -0.7
                    Productivity                  3.9                 3.6
                    GDP                           3.4                 2.9




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B Export forecasts
                                                 2007                  2020                 2030
Maximum             Export rate                    40                   39                   35
scenario            Export index                  100                  208.0                352.0
                    GDP index                     100                  213.3                402.2
Probable/           Export rate                    40                   37                   36
medium              Export index                  100                  172.2                243.4
scenario            GDP index                     100                  186.2                270.4
Minimum             Export rate                    40                   45                   50
scenario            Export index                  100                  173.7                279.9
                    GDP index                     100                  154.4                223.9

C Content of the value of Russian exports to EU-25: percentage distribution and index
(2005 = 100)
                                        2005             2020              2030
                                          %          Index     %          Index      %         Index
Maximum             Energy                  66          100       35        110        20        107
scenario            Raw materials           4           100        2        104         1         88
                    Industrial prod         30          100       63        437        79        927
Probable/           Energy                  66          100       50        130        48        177
medium              Raw materials           4           100        3        129         2        122
scenario            Industrial prod         30          100       47        270        50        406
Minimum             Energy                  66          100       72        189        77        327
scenario            Raw materials           4           100        5        217         5        350
                    Industrial prod         30          100       23        133        18        168

In the minimum scenario Russia is ruled by force and fear and the only developed
sector is the energy sector. Leaders of the energy sector, security sector and
administration, form the political elite, which does not have the courage to give
people real political freedom. Political parties are established and closed down by
appropriateness reasons by Kremlin in this ‘guided’ democracy. Policies are very
conservative and for the elite to maintain its power external and internal threats are
raised. Many minorities are seen as threats, even as terrorists in this scenario when
they are richness in the maximum scenario. Innovativeness is suppressed and growth
rate remains low. Middle class is poor and distribution of income is very uneven. Elite
needs money for itself, for wars against minorities, for bolstering fictional superpower
position and for keeping masses satisfied. Because of this exports of energy and raw
materials grow and export rate grows when it in the other scenarios diminishes.
Structure of exports is very one-sided. In the maximum scenario energy reserves are
partly saved for the future. In the minimum scenario the value of exports is bigger
than in the probable scenario but clearly smaller than in the maximum scenario. At an
individual level this situation is difficult and fertility remains very low. WTO
membership is nominal just as a democracy. De facto superpower position is weak in
the minimum scenario (despite of strong pursuit of it) but strong in the maximum



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scenario. In a modern world, power and influence come only via economic growth,
especially via productivity growth.

Most probable scenario is between these two extreme scenarios. – Selection between
scenarios is first of all a political question. Much depends on presidential election in
2008.

6.8      Russian trade modelling in different scenarios
The freight transport modelling in the next chapter 7 is based on tonnes instead of
monetary values. Hence the monetary scenarios produced above have to be adjusted
to reflect the essential future changes in the volumes of commodity types in
international trade. Splitting the Russian export to different categories - energy, raw
materials and industrial products - serves this purpose.

Assuming that the average unit prices of the 12 commodity groups used in the freight
model do not relatively change during the study period (the total change of trade
consists of quantity changes or general common price level changes), the indices in
the Table 6.8 C can be used as change rates for the matrixes by demand segments.
Segments 1-3 are counted as raw materials, segment 4 as energy and the rest as
industrial products.

The base year for transport modelling is year 2000 while here the base year has been
2005. For this reason additional factors were calculated for the years 2000 – 2005 by
interpolating the earlier modelled 2000 -2010 period (k2000-2005=sqrt(k2000-2010)).

An exception for the energy segment 4 has to be made. Natural gas is not included in
the transport flow matrixes. According to several estimations, gas is beside coal the
main source of the Russian energy export growth after 20102. The production and
own consumption make the oil export growth stagnate. This is why the growth rate of
energy products has been reduced by 50% compared to the index of the whole energy
sector in the Table 6.8 C.




2
    E.g. World Energy Outlook, 2004. EIA.



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Table 6.9 Russian trade indexes 2000 - 2010 and 2000 - 2020 by demand segment and Russian
scenario (2000 = 1,0).
                                                          Rate 2000-2010           Rate 2000-2020


                                                        Max Prob Min Max Prob Min
Demand segment                                          Scen Scen Scen Scen Scen Scen
1 – Food and Live Animals                                1.13 1.26 1.63 1.28 1.58 2.66
2 – Beverages and Tobacco                                1.13 1.26 1.63 1.28 1.58 2.66
3 – Raw materials, inedible, except fuels                1.13 1.26 1.63 1.28 1.58 2.66
4 – Mineral fuels, lubricants and related materials*     1.10 1.10 1.22 1.10 1.21 1.53
5 – Animal and vegetable oils, fats, waxes               2.20 1.73 1.22 4.85 3.00 1.48
6 - Chemicals and related products                       2.20 1.73 1.22 4.85 3.00 1.48
7 - Paper, paper board, paper pulp                       2.20 1.73 1.22 4.85 3.00 1.48
8 - Metal products                                       2.20 1.73 1.22 4.85 3.00 1.48
9 - Manufactured goods                                   2.20 1.73 1.22 4.85 3.00 1.48
10 – Machinery                                           2.20 1.73 1.22 4.85 3.00 1.48
11 - Miscellaneous manufactured items                    2.20 1.73 1.22 4.85 3.00 1.48
12 - Valuable machinery, manufactured articles           2.20 1.73 1.22 4.85 3.00 1.48
Total                                                    1.54 1.40 1.40 2.37 1.97 1.97
* Without Natural Gas


The above indexes by demand segment were used for estimating Russian export
figures. Total rates in the Table 6.9 were used for Russian import calculations,
because Russian import quantities are generally very small compared to export
quantities and there was no justified reason for commodity itemisation.




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7 Transport Modelling

7.1   Scope and objectives of the models
The main goal of the study is to set up an analytical framework to monitor the
implementation of the measures proposed by the High Level Group. The Northern
Axis is used as a pilot for the study. The study is built on available data from previous
and on-going studies and models as much as possible. Thus, the task of estimating
trade and traffic flows cannot contain development of completely new demand
models. The focus of the study is clearly on the international freight transport.
Passenger transport is a concern usually only at borders or terminals.

The approach to estimate the demand has been to use the Scenes models,
methodology (and results) for the general, European wide demand estimation both for
freight and passenger transports. It has been complemented with other data, e.g. from
ETIS-database and data gathered in non-EU countries, especially in Russia and
Belarus.

For the pilot study covering the Northern Axis the Frisbee database has been
available. It has very good data of freight networks and movements in Nordic and
Baltic countries, Russia, Poland and Germany, including all European countries and
the other continents as external zones. Frisbee database, Scenes and other data has
been integrated in the study.

For passenger modelling, Scenes is used with additional data e.g. from ETIS-database.
The focus of passenger travel forecasting is on the connections between Russia and
the EU countries. In addition, depending on available data, attention has been given
to international passenger travel elsewhere in the TEN-Naxis corridors. The time span
of the modelling study covers years 2010 and 2020.

The aim of this task is to provide estimations for current and future flows (2000, 2010
and 2020) using the exogenous scenarios (Chapter 6.) regarding the underlying
variables like population and economic development.

The underlying data covers the trade and traffic flows between EU and the relevant
neighbouring countries of EU. The main emphasis is on the flows to/from and through
the Northern Axis area.

Central development strategies regarding new infrastructure, pricing alternatives etc.
are tested in order to serve the analysis of bottlenecks and prioritising of the measures
on the axis.




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7.2      Freight

7.2.1      Methods and Data
The starting point for the modelling of the freight transport is the estimation of the
freight demand flows between the regions of the study area. The method used for the
estimation is based on different sources, including the outcome of the trade forecasts.
Two main steps can be identified for the estimation of the freight matrix:

      1. Estimation of a base year matrix;
      2. Estimation of the matrix for the forecasting years. As far as the base year
         matrix is concerned, the procedure used for its appraisal made use of the
         following main inputs:
             a. The EUROSTAT COMEXT data concerning the external trade
                between/to/from the EU25 countries;
             b. The ETIS-BASE freight matrix for the year 2000;
             c. The SCENES model freight matrix for the year 2000;
             d. The original matrix of the FRISBEE freight system model;
             e. The available data concerning the trade of non-EU countries in the area
                with non-European regions.

ETIS-BASE is an information system of integrated policy tools to support policy
analysis and policy making3. With ETIS, ETIS-BASE has developed a reference
database, covering the EU25 and Eastern Europe countries, with the aim of making it
the reference database for European strategic modelling and focuses on TEN-T policy
issues.

COMEXT is the database of EUROSTAT dedicated to the external trade of EU
countries. Data is provided in both monetary and quantitative (tonnes) terms for a
very detailed classification of commodities. COMEXT provided the base figures for
the import and export of freight of EU countries.

The SCENES model is a European Transport model developed in different European
projects since the mid 1990’s. In SCENES a freight matrix is computed
endogenously thanks to a Regional-Economic Model (REM). The REM is based upon
a spatial adaptation of the Leontief input-output framework4 and uses Eurostat I-O
tables’ data5. The REM computes matrices in monetary values for 24 commodity
groups between more than 250 zones covering EU25 plus Switzerland and Norway at
the NUTS2 level and neighbouring regions at a coarser geographical detail. Then,
matrices in value are translated in matrices of tonnes for 13 different freight segments

3
    See ETIS website: http://www.etis-eu.org/index.html
4
    See SCENES (2001) Transport Forecasting Model: Calibration and Forecast Results. Deliverable D7
      of the SCENES project, funded by the European Commission (DG TREN). Cambridge, 2001.
      http://www.iww.uni-karlsruhe.de/SCENES/download.html
5
    I-O tables data has been recently updated for the Mid-term assessment of the White Paper on the
       European Transport Policy (ASSESS project)



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based on the NST/R classification. From SCENES, the domestic traffic has been
drawn to complete the foreign trade data taken from COMEXT. In addition, the
SCENES REM module provides a consistent mechanism for representing the
development of trade matrices according to the trend of different sectors of an
economy and between different economies. For that reason it represents a key input
for developing the freight matrices of the future years (2010 and 2020) starting from
the base year matrix.

FRISBEE is a multi-modal freight transportation model, the emphasis on (Northern)
Europe, Russia and Baltic states. It is based on the system originally developed for
STEMM-project and it consists of descriptions of transport networks and terminals,
flows of 12 commodities and detailed cost functions. The Finnish Ministry of
Transport and Communications updates it continuously. Because there are in Frisbee
good descriptions of available infrastructure and costs of freight, it has bee used as a
tool to simulate flows of goods for testing of transport scenarios.

7.2.2      Demand in 2000 (the base year), 2010 and 2020
Table 7.1 shows in commodity level the base year (2000) system wide total demand
and forecasts for 2010 and 2020. Also the growth rates are shown in the table. 61 % of
all the freight transported to, from or between the Northern Axis countries is raw
materials and oil.

The freight volumes will increase from the base year (2000) to 2010 31% and to 2020
82%.

Table 7.1 Base year (2000) total freight flows, forecasts 2010 and 2020 and growth rates by
commodity (million tons/a)6
Demand segment                                    2 000      2 010     2 020    Rate      Rate     Rate
                                                                                2000-     2000-    2010-
                                                                                2010      2020     2020
1 - Food and Live Animals                           340        492       772      1,45      2,27     1,57
2 - Beverages and Tobacco                            29         38        55      1,29      1,88     1,46
3 - Raw materials, inedible, except fuels           601        916     1 358      1,52      2,26     1,48
4 - Mineral fuels, lubricants and related         1 257      1 495     1 835      1,19      1,46     1,23
materials
5 - Animal and vegetable oils, fats, waxes           14         20        29      1,38      2,00      1,45
6 - Chemicals and related products                  257        318       422      1,24      1,64      1,32
7 - Paper, paper board, paper pulp                   70         90       141      1,30      2,03      1,57
8 - Metal products                                  254        317       422      1,25      1,66      1,33
9 - Manufactured goods                              104        142       240      1,36      2,30      1,69
10 - Machinery                                       86        100       152      1,17      1,77      1,52
11 - Miscellaneous manufactured items                28         46       100      1,68      3,62      2,15
12 - Valuable machinery, manufactured                21         26        40      1,21      1,86      1,54
articles
Total                                             3 061      3 996     5 561      1,31      1,82      1,39




6
    The flows consist of freight inside Europe and between Europe and other continents.



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The demand by commodity for the base year (2000), 2010 and 2020 in (from/to) the
Northern Axis countries is shown in the Table 7.2.

The freight volumes in, to and within the Northern Axis countries were in 2000 ca.
1520 million tons, which is 50% of the total system volumes (equal roughly the EU-
25 and Russian, Ukrainian and Belarusian flows combined). The share will be 48% in
2010 and 45% in 2020 (Table 7.1 and Table 7.2).

Table 7.2. The base year 2000 and forecasts 2010 and 2020 of freight flows to/from/between the
Northern Axis countries by demand segment (million tons/a)
Demand segment          Intra-Northern axis   In to Northern axis    Out from Northern                Total
                               Area                  Area                 axis Area
                        -00     -10     -20   -00     -10     -20   -00      -10    -20       2000    2010    2020
1 - Food and Live         8      10      15   114     158     224    37      44       55       159     212     294
Animals
2 - Beverages and         0       1       1     4       6       8     2       3           3      6       10     12
Tobacco
3 - Raw materials,       67      92     125   127     179     249   118     148     185        312     419     559
inedible, except
fuels
4 - Mineral fuels,      126     176     251   128     147     168   358     408     464        612     731     883
lubricants and
related materials
5 - Animal and            1       1       1     3       4       6     2       2           2      6        7      9
vegetable oils, fats,
waxes
6 - Chemicals and        17      24      34    41      51      63    61      71       92       119     146     189
related products
7 - Paper, paper          8      10      15    10      13      17    28      35       51        46       58     83
board, paper pulp
8 - Metal products       16      22      29    38      48      58    87     116     171        141     186     258
9 - Manufactured          9      12      17    21      29      46    27      29       40        57       70    103
goods
10 - Machinery            4       7       9    17      23      34    21      19       22        42       49     65
11 - Miscellaneous        3       4       5     5       9      18     5       5        7        13       18     30
manufactured items
12 - Valuable             1       1       1     4       5       7     4       3           4      9        9     12
machinery,
manufactured
articles
Total                   259     359     453   512     672     898   750     883    1 096      1 521   1 914   2 497



The base year total imports and exports by the European countries (in 1000 tons/a) are
shown in the Figure 7.1. The figure shows also the forecasted demand for 2010 and
2020.

The major importers (in volumes in 2000) are Germany (434 million tons/a),
Netherlands (269), France (326), Great Britain (199), Belgium (226), Italy (274),
Spain (208), Russia (109), Poland (70) and Sweden (69). Of these, Germany, Russia,
Poland and Sweden belong to Northern Axis. Volumes to other continents (from EU-
25 and Russia) are rather small, Northern America 104 million tons/a (2000), Middle
East 129, Far East 112, South America 41; Oceania only 4 million tons/a.




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                                                 import, million tons                                                                            export, million tons
Russia                                                               216 |||||| 153 |||| 109 |||||||||| ||||||||||||||||||||||||||||||||||||||||||| 433 ||||||||||||||| 586 ||||||||||||||||||||| 797
S America                                                                               36 29 41 |||| |||||||||||||||| 163 ||||||||||||| 302 ||||||||||||||||||||| 521
Afrca                                                                                 74 | 61 53 ||||| ||||||||||||||||||||||||| 252 ||||||||||| 367 |||||||||||||| 508
M East                                                                198 |||| 157 || 129 |||||||||||| ||||||||||||||||||||||||| 250 ||||||||||| 361 |||||||||||||| 507
Far East                                                                176 ||| 138 || 112 ||||||||||| ||||||||| 96 |||||||| 180 ||||||||||||||||| 356
N America                                                                        28 23 104 |||||||||| ||||||||||| 112 |||||||| 199 |||||||||||||| 343
Germany                  736 |||||||||||||||||| 553 ||||||||||| 434 ||||||||||||||||||||||||||||||||||||||||||| |||||||||||||||||||||||| 245 | 264 ||||| 313
Netherlands                              534 |||||||||||||||| 372 |||||||||| 269 |||||||||||||||||||||||||| ||||||||||||||||||||||| 239 | 248 || 277
France                               586 ||||||||||||||| 430 |||||||||| 326 |||||||||||||||||||||||||||||||| |||||||||||||||| 167 176 ||| 208
Great Britain                                      426 |||||||||||||| 279 |||||||| 199 ||||||||||||||||||| ||||||||||||||||| 172 152 || 176
Norway                                                                                    23 20 18 | |||||||||||||| 145 | 157 | 171
Oceania                                                                                          7 5 4 ||||| 58 |||| 101 |||||| 161
Belgium                                               389 ||||||||| 291 |||||| 226 |||||||||||||||||||||| ||||||||||||| 130 134 | 150
Italy                                    530 |||||||||||||||| 369 ||||||||| 274 ||||||||||||||||||||||||||| |||||||| 89 90 || 113
Poland                                                                     160 ||||| 109 ||| 70 ||||||| ||||| 58 | 77 || 100
Spain                                         484 |||||||||||||||| 318 ||||||||||| 208 |||||||||||||||||||| ||||||| 74 75 || 95
Sweden                                                                           121 || 92 || 69 |||||| ||||| 59 69 | 87
Ukraine                                                                                          0 0 0 || 29 || 55 ||| 85
Czech                                                                             105 ||| 74 || 46 |||| ||| 33 | 50 | 70
Finland                                                                             97 || 69 || 49 |||| ||| 34 42 | 60
Turkey                                                                                           0 0 0 | 16 | 29 || 53
Central Asia                                                                              27 22 19 | | 10 | 22 || 47
Switzerland                                                                                      0 0 0 | 16 | 28 | 43
Denmark                                                                              74 || 54 | 41 |||| ||| 32 33 38
Slovakia                                                                             70 || 49 || 30 ||| | 15 | 26 | 38
Austria                                                                              88 || 66 | 47 |||| || 29 30 34
Hungary                                                                                 61 | 43 | 27 || | 12 20 | 30
Latvia                                                                                         10 7 4 9 14 20
Portugal                                                                            95 ||| 62 | 49 |||| | 13 15 19
Estonia                                                                                        10 7 5 9 13 19
Greece                                                                              95 ||| 65 || 41 |||| | 15 14 18
Lithuania                                                                                 25 18 13 | 7 12 17
Serbia ja Montenegro                                                                             9 7 6 7 11 17
Romania                                                                                          0 0 0 5 10 16
Belarussia                                                                                       4 3 2 5 9 15
Ireland                                                                                 55 | 39 | 25 || | 10 11 13
Bulgaria                                                                                         0 0 0 4 7 11
Kroatia                                                                                   17 13 10 | 5 7 10
Iceland                                                                                          0 0 0 1 2 5
Slovenia                                                                                         0 0 0 1 2 3
Malta                                                                                            2 2 2 0 1 1
Bosnia ja Hertsegovina                                                                           0 0 0 0 0 1
Albania                                                                                          0 0 0 0 0 0

Figure 7.1 Total imports (blue) and exports (green) (million tons/a) in European countries. The
other continents: import and export from/to EU-25 and Russia. Base year (2000) and forecasts
2010 and 2020. Values of the base year (2000) are nearest of the centre line, the ones of 2020 the
farthest. Values of 2010 are in the middle; Values are total for the year. The red colour indicates
negative growth



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One has to note that the forecasted volumes to North and South America might be
erroneous, because the emphasis of the model is on the Northern Axis countries and
the model is rather aggregated for those volumes. However, possible errors do not
remarkably affect the values (and analysis of the derived results) of Northern Axis
countries.

The biggest exporter in the system (EU-25 and Russia) is Russia, 433 million tons/a
in the base year 2000. Then come Germany (245), Netherlands (239), Great Britain
(172), France (167), Norway (145), Belgium (130), Italy (89), Poland (58), Spain (74)
and Sweden (59). Smaller exporters are Ukraine (29), Czech (33), Denmark (32) and
Finland (34).

Unlike in import, the other continents are big exporters to EU-25 and Russia: South
America 163 million tons/a, Africa (252), Middle East (250), Far East (98), Northern
America (112) and Oceania (58).

Table 7.3. Base year (2000) freight flows between Northern axis countries (1000 tons/a)
Country      Bel    Est      FIN      Ger       Lat     Lit     Nor     Pol      Rus     Swe     Sum
from/to
Belarus       -     136      29       666       632     1 113    -      1 231    -       22      3 830
Estonia       17    -        1 586    604       400     170     716     124      111     2 513   6 241
Finland       7     764      -         4 990    266     101      539    597      3 271   3 937   14 472
Germany      342    284      2 323     -        175     448     2126    8 386    1 932   7 181   23 197
Latvia        25    175      494       1 026    -       210     50      108      140     4 086   6 313
Lithuania     173   101      99        894      585     -       172     984      467     860     4 334
Norway        -     48       4 169    27 853    52      43       -      888      -       14104   47 157
Poland       275    76       2 400     22 375   150     270      730    -        816     1 831   28 923
Russia        -     2 850    19 794   36 030    1 291   8 289    -      26 834   -       5 788   100875
Sweden        9     191      5 160    11 101    244     136     5290    1475     308     -       23 913
Sum          847    4 624    36 052   105538    3 796   10781   9622    40628    4 045   40322   259254


The major exporter in trade in tons between the Northern axis countries is Russia with
its 100 million tons/a (mostly oil), second Norway (47 mil tons/a) and then Poland,
Sweden and Germany (29, 24 and 23 mil tons/a, respectively), see Table 7.3.

Germany is the biggest importer from the Northern axis countries, 106 million tons/a;
the other big importers are Poland, Sweden and Finland (41, 40 and 36 mil tons/a,
resp.).

The biggest flows are from Russia to Germany, Poland and Finland and to Germany
from Norway, Poland and Sweden. There are also rather big flows between Sweden
and Norway and between Germany and Poland. One can note that the flows between
Norway and Russia are negligible.

Russian freight flows play an important role in the Northern Axis countries, either in
terms of bilateral trade or transit freight. Figure 7.2 shows all the major directions of
these flows: for Russian exports Finland, Germany, Poland and also Northern and
Southern America are important destinations; for imports, Germany and Finland stand
up.



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                                   Russian import, 1000 tons                                                  Russian export, 1000 tons
 M East                                            125791 89394 63855 96761 119228 152815
 Far East                                           58466 41549 29679 75181 94373 122184
 Germany                                                3220 2494 1932 | |||||||||||||||||||||||||||||||||||| 36030 |||||||||||||||||||| 56371 ||||||||||||||||||||||||||||||| 88203
 Poland                                                   1997 1276 816 |||||||||||||||||||||||||| 26834 ||||||||||||||| 41984 ||||||||||||||||||||||| 65692
 Finland                                            7477 || 4944 | 3271 ||| ||||||||||||||||||| 19794 |||||||||| 29987 ||||||||||||||| 45432
 Slovakia                                                      244 165 87 |||||||||||||| 14097 ||||||||||| 25961 ||||||||||| 37817
 Czech                                                       456 309 163 |||||||||||||| 14066 ||||||||||| 25776 ||||||||||| 37510
 Hungary                                                     971 716 466 ||||||||||| 11952 ||||||||| 21788 ||||||||| 31647
 S America                                              2140 1521 1087 | ||||||||||||||||||||| 21869 ||| 25641 ||||| 30904
 Italy                                                      1141 808 580 ||||||||||||||||||| 19376 |||| 23467 ||||| 29435
 France                                                   1403 1002 722 ||||||||||||||||| 17753 || 20583 ||| 24197
 Central Asia                                                283 201 144 |||||||||| 10880 || 13538 |||| 17550
 Spain                                                       681 481 344 |||||||||| 10856 || 13518 ||| 17396
 Lithuania                                                   853 631 467 |||||||| 8289 || 10701 ||| 13818
 Netherlands                                              1843 1317 950 |||||||| 8313 | 10272 || 13093
 N America                                                   633 450 322 ||||||| 7344 | 8732 | 10710
 Sweden                                                      563 417 308 ||||| 5788 || 7823 || 10574
 Great Britain                                               546 389 279 |||||| 6170 | 7881 || 10436
 Belgium                                                    1082 774 559 |||| 4970 | 6715 || 9415
 Greece                                                     1010 719 515 |||| 4640 5631 | 6992
 Afrca                                                  2926 2080 1486 | || 2968 3733 | 4772
 Estonia                                                     204 151 111 || 2850 3679 | 4750
 Denmark                                                     625 447 322 || 2233 2786 3561
 Latvia                                                      256 190 140 | 1291 1667 2152
 Austria                                                     419 299 216 | 1169 1460 1887
 Kroatia                                                         122 79 37 573 1029 1490
 Portugal                                                             12 9 6 736 967 1332
 Oceania                                                           33 23 17 463 579 757
 Ireland                                                       163 117 84 48 83 142
 Malta                                                                  0 0 0 8 11 14

Figure 7.2 The Russian freight flows (import blue and export green) in the base year 2000 and
forecasts 2010 and 2020 (1000 tons/a). The values for Middle East and Far East are shown only in
numbers. Values of the base year (2000) are nearest of the centre line, the ones of 2020 the
farthest. Values of 2010 are in the middle; Values are total for the year


The biggest exporter in 2020 (the Base forecast) in the trade between Northern axis
countries will be still Russia (231 mil tons/a), next Norway (73 mil tons/a) and Poland
(52 mil tons/a) (Table 7.4).

Table 7.4. Freight flow forecast 2020 between Northern axis countries (1000 tons/a)
Country     Bel     Est      FIN       Ger        Lat          Lit                Nor            Pol             Rus              Swe            Sum
Belarus        -       405      108       2 698    1 880            3 309             -            2 731               -              65          11 196
Estonia       41         -    2 897       1 571    1 138              495         1 019              247             204           4 189          11 799
Finland       17     1 087        -       8 318      379              143           767              948           7 477           5 602         24 737
Germany     1385       844    3 495           -      278              711          3024           18 603           3 220          10216           41 777
Latvia        61       500      902       2 666        -              667            71              214             256           6 811          12 148
Lithuania    424       290      181       2 323    1 579                -           245            1 952             853           1 433           9 279
Norway         -        83    6 613     44 183        91               76             -            1 481               -          20065           72 592
Poland       652       197    6 238     37 301       389              703          1333                -           1 997           3 634          52 445
Russia         -     4 750   45 432      88 203    2 152           13 818             -           65 692               -          10574          230622
Sweden        19       318    7 341     17 609       406              226          7526            2 577             563               -          36 585
Sum         2599     8 474   73 206     204871     8 292           20 148         13984           94 445          14 571          62590          503180



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The biggest importer will be Germany (205 mil tons/a), Poland (94 mil tons/a) and
Finland (73 mil tons/a) next.

The major freight flows will be from Russia (to other countries) and to Germany from
others). Interesting are also rather big flows from the Baltic States to Sweden.

The biggest growth (2020 – 2000) in Russian exports is to Germany, Poland and
Finland. The same applies also to Russian imports.

Russian growth scenarios
In addition to the basic forecasts, two scenarios forecasts were run: minimum and
maximum. They are correlated to the development of Russian economy; the other
areas are kept constant.


           RUSSIAN EXPORT FORECASTS TO NORTHERN AXIS COUNTRIES
                       AND NORTH AND SOUTH AMERICA

    350


    300
                                                                                              South Am
    250                                                                                       North Am
                                                                                              Sweden
    200                                                                                       Poland
                                                                                              Lithuania
    150                                                                                       Latvia
                                                                                              Germany
    100                                                                                       Finland
                                                                                              Estonia
      50


       0
           Base 2000   Base 2010   Min 2010    Max 2010     Base 2020   Min 2020   Max 2020
                                              FROM RUSSIA
                                              SCENARIOS



Figure 7.3. Russian export forecasts from Northern Axis countries and North and South
America, economic development scenarios 2010 and 2020


One can notice that paradoxically, minimum growth in Russia will increase the freight
volumes in tons (Figure 7.3). This is due to increased oil exports and less domestic
consumption.




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               RUSSIAN IMPORT FORECASTS FROM NORTHERN AXIS COUNTRIES
                            AND NORTH AND SOUTH AMERICA

    16

    14

    12                                                                                       South Am.
                                                                                             North Am.
    10                                                                                       Sweden
                                                                                             Poland
        8                                                                                    Lithuania
                                                                                             Latvia
        6                                                                                    Germany
                                                                                             Finland
        4                                                                                    Estonia

        2

        0
            Base 2000   Base 2010   Min 2010    Max 2010   Base 2020   Min 2020   Max 2020
                                               TO RUSSIA
                                               SCENARIOS



Figure 7.4. Russian import forecasts from Northern Axis countries and North and South
America, economic development scenarios 2010 and 2020


7.2.3       Freight system analysis
Assumptions
The FRISBEE freight transport model was used to simulate interaction between the
transport infrastructure, costs and demand. The system was calibrated to correspond to
the observed flows at the main borders and ports and on main corridors. The
commodities were assigned on the networks and the results analyzed (costs, ton
mileage, bottlenecks, impacts of possible policies etc.).

Frisbee has descriptions of supply, demand and costs. The supply consists of all the
modes of interest (truck, train, liner ships, tramp ships, oil pipes etc) and respective
networks (by mode) and terminals (ports, borders stations etc.). Demand is in matrices
of 12 commodities between 250 areas. Usually the matrices are not mode based, they
have the total flows for any commodity. Cost functions for links and terminals
(transfer points) have operation and level of service elements, like transport time,
risks, value of goods, headways in line transport. The idea of assignment of Frisbee
(STAN) is to get system optimum by simultaneous mode and route choice (“chain of
transport”).

Several assumptions were made before assignments:
   • The costs are average unit prices by mode, commodity and country.
   • The unit prices are kept constant, except for truck in sensitivity analysis.
   • There are no changes in the infrastructure (supply), like new connections or
       changes in level of service.
   • There are no new sea connections or new ports.
   • Only the demand changes (matrices 2010, 2020)
   • The demand doesn’t contain possible new production, like coal and oil
       through the Murmansk port.

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      •     Airfreight is not considered due to lacking unit prices and networks. Also the
            flows are not very big (in tons) compared with the rest of the system.
      •     The oil pipes included in the system are in Russia to Primorsk port and from
            Russia to Poland.
      •     The Finnish inland waterways and the Russian inland waterway to St.
            Petersburg are included accurately in the system. The waterways in the Middle
            Europe are there, but they are not in the calibration process.
      •     The other continents are in the system, but their transport is dealt with only as
            feeder traffic to Europe (near Great Britain).
      •     There are no political changes assumed in the relations between Russia and the
            Baltic countries.

Total volumes
At present (2000…2003), all commodities together, there are 3 060 million tons in
matrices. The volumes will increase 31% in 2010 and 82% in 2020. This is quite well
in line with the economic forecasts (see Table 7.5).

Table 7.5. Total freight volumes in matrices (million tons/a)
                                      2000                       2010                       2020
          Million ton                 3 060                      4 000                      5 565
            Index                      100                        131                        182

Assigning all the commodities on to freight network yields the ton mileage of 5 635
billion tonkilometers. The corresponding figure for EU-25 countries is 3 900 billion
tonkilometers7. The TEN-NAxis figures include Russia, Ukraine and Belarus. Thus,
we can assume that the system contains all the major flows and networks.

Table 7.6. Ton mileage by modes in the system, 1000 million tonkm/a
            Mode                      2000                       2010                       2020
                   Road                851                       1 125                      1 562
                     Rail             1 361                      1 845                      2 559
            Liner traffic              138                        190                        272
     Tramp Traffic (inc.              3 218                      4 424                      6 349
      inland waterways)
        Pipe (oil/Russia)               67                        103                       163
                   Total              5 635                      7 687                     10 906
                   Index               100                        136                       194

The average distance transported in the model is currently ca. 1840 km, in 2010 1920
km and in 2020 1960 km (dividing the values in Table 7.5 and Table 7.6).

The freight volumes will increase 39 % between 2010 and 2020. In tonkilometres the
corresponding growth is 42%. At the same time the GDP was estimated to grow
14 % in the EU-15 countries and 61% in Russia .


7
    Energy & Transport in Figures 2006, Directorate-General for Energy and Transport



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The ton mileage by road and rail without Russia, Ukraine and Belarus is presented in
the Table 7.7. The modal shares (road and rail) in the EU-25 area are 60% (road) and
40% (rail). In the whole system (including Russia, Ukraine and Belarus) the shares are
the other way around, 40% road and 60% rail. The numbers for 2010 and 2020 are
about the same.

Table 7.7. Ton mileage (1000 million tonkm/a) in road and rail transport, excl. Russia, Ukraine
and Belarus
                                                  2000                   2010               2020
Road
 Ton mileage (1000 million tonkm/a)                751                   986                1358
 Index                                             100                   131                181
Rail
 Ton mileage (1000 million tonkm/a)                521                   656                 897
 Index                                             100                   126                 172


Total costs
The transport costs in the whole system will increase relatively more than tons and ton
mileage. This is due to capacity constraints at some points.

Table 7.8.Total system transportation costs, billion euros/a
                                         2000                     2010                    2020
    Costs (billion euros/a)              172                      234                     357
            Index                         100                     136                     208

The costs consist of operating costs and level of service costs, which are ca 25% of
the total in the model.

Value of goods
The average value of goods exported and imported was calculated by weighing the
value with the volumes of commodity for values of 2010. The next figures show that
if Russia is a very big exporter, the value of its goods is relatively low compared to
other Northern Axis countries, even the Baltic countries.

The average value of import by country is much more homogenous than the one of
export.




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                                                    average value of goods, eur/kg
                                       import                                                            export
Malta                                                      0,74 ||||||| |||||||||||||||||||||||||||||||||||||||||||||||||||||||| 5,63
Far East                                               1,19 ||||||||||| |||||||||||||||||||||||||||||||||||||||| 4,04
Kroatia                                           1,76 ||||||||||||||||| ||||||||||||||||||||||||||||||||||||| 3,74
Italy                                                   1,01 |||||||||| ||||||||||||||||||||||||||||||| 3,1
Romania                                                               0 ||||||||||||||||||||||||||||| 2,97
Albania                                                               0 ||||||||||||||||||||||||||||| 2,9
Hungary                                               1,33 ||||||||||||| |||||||||||||||||||||||||||| 2,84
Portugal                                              1,24 |||||||||||| |||||||||||||||||||||||||| 2,6
Switzerland                                                           0 ||||||||||||||||||||||||| 2,51
Spain                                                  1,14 ||||||||||| |||||||||||||||||||||||| 2,43
Central Asia                                           1,16 ||||||||||| ||||||||||||||||||||||| 2,36
Bosnia ja Hertsegovina                                                0 ||||||||||||||||||||||| 2,3
Germany                                               1,35 ||||||||||||| |||||||||||||||||||||| 2,25
Austria                                          1,88 |||||||||||||||||| |||||||||||||||||||||| 2,24
Ireland                                              1,49 |||||||||||||| |||||||||||||||||||||| 2,21
Slovenia                                                              0 ||||||||||||||||||||| 2,14
France                                                1,28 |||||||||||| |||||||||||||||||||| 2,09
Czech                                                   1,02 |||||||||| |||||||||||||||||||| 2,08
Turkey                                                                0 ||||||||||||||||||| 1,96
Bulgaria                                                              0 ||||||||||||||||| 1,79
Slovakia                                                  0,84 |||||||| ||||||||||||||||| 1,77
Finland                                                   0,87 |||||||| ||||||||||||||||| 1,7
Poland                                                 1,18 ||||||||||| |||||||||||||||| 1,6
Belgium                                               1,23 |||||||||||| ||||||||||||||| 1,54
Lithuania                                              1,18 ||||||||||| ||||||||||||||| 1,51
Sweden                                                1,28 |||||||||||| |||||||||||||| 1,48
Denmark                                           1,74 ||||||||||||||||| |||||||||||||| 1,48
Great Britain                                   1,98 ||||||||||||||||||| |||||||||||||| 1,45
Iceland                                                               0 ||||||||||||| 1,37
N America                                             1,26 |||||||||||| |||||||||||| 1,25
Belarussia                                   2,37 ||||||||||||||||||||||| |||||||||||| 1,2
Netherlands                                              0,96 ||||||||| ||||||||||| 1,16
Greece                                                 1,12 ||||||||||| |||||||||| 1,09
Estonia                                             1,51 ||||||||||||||| |||||||||| 1,05
Latvia                                             1,65 |||||||||||||||| ||||||||| 0,97
Serbia ja Montenegro                     2,85 |||||||||||||||||||||||||||| ||||||||| 0,9
S America                                                   0,64 |||||| ||||||| 0,72
M East                                                   0,97 ||||||||| |||||| 0,64
Ukraine                                     2,46 |||||||||||||||||||||||| |||||| 0,62
Russia                                               1,6 |||||||||||||||| |||| 0,48
Afrca                                            1,86 |||||||||||||||||| |||| 0,44
Oceania                             3,46 |||||||||||||||||||||||||||||||||| ||| 0,39
Norway                                          1,92 ||||||||||||||||||| ||| 0,38

Figure 7.5. Average values (weighted by volumes) of goods exported and imported by country in
2010


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                                                 Finnish export

        20 000


        15 000


        10 000


         5 000


               0
                    1       2      3      4        5        6        7          8    9       10     11      12

    1000 t         827     53    6 158   3 342    55      2 662    12 079 3 618     2 389   1 094   799     484
    million EUR    1 147   195   1 709   618      65      3 743    16 760 5 288     5 923   12 753 7 691   12 270

                                                        1000 t    million EUR



                                                 Finnish import

        20 000


        15 000


        10 000


         5 000


               0
                     1      2      3       4       5         6        7         8     9       10    11       12
    1000 ton       1 603   86    19 419 18 497     67     4 234     432    2 555     850     754    190     217
    million EUR 2 224      318   5 389   3 422     79     5 953     600    3 734    2 107   8 785 1 830    5 508

                                                       1000 ton    million EUR


Figure 7.6. The Finnish export and import in volumes and value by commodity. The export is
above the import. Numbers 1,2…12 refer the classification as in Table 7.1.




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                                                     Russian export

         325 000
         275 000
         225 000
         175 000
         125 000
           75 000
           25 000
          -25 000
                      1       2       3      4         5        6         7          8    9       10     11      12

       1000 t        712      21    61 904 312 500     1      11 208    2 416 41 949     1 871    627    91      35
       million EUR   988      78    17 179 57 815      1      15 759    3 352 61 311     4 638   7 302   872     883

                                                            1000 t     million EUR




                                                     Russian import

          125 000

          100 000

           75 000

           50 000

           25 000

                0
                       1       2      3       4         5       6         7          8    9       10     11      12

       1000 t        73 171   162   20 399   200      450     1 644     3 152   3 523    1 372   3 728   792     374
       million EUR 101 528    599   5 661    37       532     2 312     4 374   5 149    3 401   43 451 7 618   9 467

                                                            1000 t     million EUR


Figure 7.7. The Russian export and import in volumes and value by commodity. The export is
above the import. Numbers 1,2…12 refer the classification as in Table 7.1.


Freight flows at borders and ports
The freight transport system model was calibrated to observed flows in the Northern
Axis area.

Table 7.9. Freight flows at border stations and ports (million tons/a)
Border stations                                                  2000                    2010                   2020
Murmansk route                                                   14                      17                     19
Finland/Russia                                                   26                      36                     55
Finnish ports                                                    65                      83                     126
Russian ports (Baltic sea)                                       126                     180                    273
Ports of Baltic Countries                                        51                      80                     109
Poland/Belarus border8                                           62                      79                     98
8
    Includes transport by oil pipe, ca. 50 million tons/a.


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The model assigns much more volumes to the border stations and to ports than the
volumes revealed in the query. E.g. at the Poland/Belarusian border the local forecast
for rail is 8 million tons/a (2020 from current, 6.5 million tons/a) and the road freight
is expected to grow at similar rates. However, the model assigns (road + rail) over 2.5
times the present volume (from 14 to 40 million tons/a). There is great growth also at
other stations, Corridor 7 (Moscow – Minks – Warszawa – Berlin). The corridor is a
clear bottleneck in Northern Axis.


                350


                300


                250
   index (% )




                200


                150


                100


                50


                 0
                      Muurmansk   Finland Russia   Finnish ports   Russian ports in   Ports of Baltic        Poland            Poland
                        route         border                        the Baltic Sea      Countries         Belorussia        Belorussia
                                                                                                        border, road +     border, road +
                                                                                                         rail + oil pipe         rail

                                                              Current       2010         2020


Figure 7.8. Index of total volumes at certain borders (stations) in Northern Axis area


The Figure 7.9 shows the relative growth of volumes at certain border stations,
regarding Northern Axis and Russia. It can be noted, that Narvik doesn’t have the
mineral transport included. At Murmansk harbour ca. 14 million tons/a (79%) is coal,
the rest apatite enrichment, containers and metals. According to the Russian forecasts
the volumes at Murmansk harbour will increase by 2015 to 69 million tons/a (of
which 20 million tons coal and 20 million tons oil). These forecasts are not included
in the TEN-Naxis forecasts.

The capacity of the oil pipe in from Russia to Poland is ca. 50 million tons/a (Corridor
7). It is clear that higher level of service in the corridor would bring there more goods
of higher value.




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        Norway/Sweden (Narvik), road + rail                Norway/Sweden (Oslo), road + rail                              Muurmansk route                          Vartius, Finland/Russia, road + rail

  300                                                300                                                 300                                                 300
  250                                                250                                                 250                                                 250
  200                                                200                                                 200                                                 200
  150                                                150                                                 150                                                 150
  100                                                100                                                 100                                                 100
   50                                                50                                                   50                                                  50
                 1           2               3                   1            2              3                        1            2               3                     1             2            3



            Vaalimaa, Finland/Russia, road                   Vainikkala, Finland/Russia, rail                   Narva, Estonia/Russia, road + rail                     Latvia/Russia, road + rail

  300                                                300                                                  300                                                300
  250                                                250                                                  250                                                250
  200                                                200                                                  200                                                200
  150                                                150                                                  150                                                150
  100                                                100                                                  100                                                100
   50                                                 50                                                   50                                                 50
                1            2               3                   1             2             3                        1            2               3                     1            2             3



            Poland/Belorussia, road + rail                     Poland/Belorussia, oil pipe                        Lithuania/Belarus, road + rail               Lithuania/Russia, Kaliningrad, road +
                                                                                                                                                                               rail
  300                                                300                                                  300
  250                                                                                                                                                        300
                                                     250                                                  250
                                                                                                                                                             250
  200                                                200                                                  200
                                                                                                                                                             200
  150                                                150                                                  150
                                                                                                                                                             150
  100                                                100                                                  100                                                100
  50                                                  50                                                   50                                                 50
                1            2               3                   1             2             3                        1            2               3                     1            2             3




Figure 7.9. Relative growth of freight volumes at border stations (Narvik, Oslo, Murmansk,
Vartius, Vaalimaa, Vainikkala, Narva, Latvia/Russia, Poland/Belarus, Lithuania/Belarus,
Kaliningrad. (1 = year 2000, 2 = 2010 and 3 = 2020)


Freight volumes and values at border stations and some major Baltic ports 2010
Although the volumes at the Russian ports are big, the value of those goods is small
compared to the other ports. It is less than e.g. at Finnish ports. However, at the
Russian/Finnish border station relatively cheap raw materials are transported. See
Figure 7.10 .

  200
  180
  160
  140
  120
  100
   80
   60
   40
   20
        0
                     Muurmans k              Finland Russia          Finnish ports                Russian ports             Ports of Baltic                Poland                  Poland
                       route                      border                                         in the Baltic sea           Countries                   Belorussia              Beloruss ia
                                                                                                                                                       border, road +           border, road +
                                                                                                                                                        rail + oil pipe              rail

                                                                                   million tons         1000 million euros


Figure 7.10 Volumes and value of the goods at border stations of Northern Axis (2010)


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Russian freight volumes and values at border stations 2000 and 2020
The figures next show the Russian export and import in 1000 tons and values in
million euros in 2000 and 2020. The Russian ports are left out, because their volumes
would dominate the figures too much. The Russian ports in the Baltic Sea, excl.
Kaliningrad, exported in 2000 106 million tons and in 2020 the forecast is 215 million
tons. The respective figures for Russian import are 6 million tons (2000) and 12
million tons (2020).


                                                    Russian export via Northern Axis
                                                              1000 tons/a

  40 000




  30 000




  20 000




  10 000




       0
           1) Muurm ans k 2) Vartius (FI) -    3) Finland     4) Narva (EE) -   5) Latvia -   6) Lithuania - 7) Lithuania -   8) Poland -
               route         Lytta (RU)          Rus s ia        Ivangorod       Rus s ia     Belarus , note: Kaliningrad       Belarus
                                              border, other         (RU)                      incl. part of 6     (RU)
                                                 than 2                                       (Kaliningrad)
                                                (Vartius )

                                                                  2000 tons     2020 tons

Figure 7.11. Russian export via Northern Axis area (1000 tons/a) in 2000 and 2020



                                                    Russian import via Northern Axis
                                                              1000 tons/a

  40 000




  30 000




  20 000




  10 000




       0
           1) Muurm ans k 2) Vartius (FI) -    3) Finland   4) Narva (EE) -     5) Latvia -   6) Lithuania - 7) Lithuania -   8) Poland -
               route         Lytta (RU)          Rus s ia      Ivangorod         Rus s ia     Belarus , note: Kaliningrad       Belarus
                                              border, other       (RU)                        incl. part of 6     (RU)
                                                 than 2                                       (Kaliningrad)
                                                (Vartius )

                                                                       2000     2020

Figure 7.12. Russian import via Northern Axis (1000 tons/a, 2000, 2020)


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The value of Russian export through Russian ports in the Baltic Sea, excl. Kaliningrad
was in 2000 35 billion euros and the forecast for 2020 is 103 billion euros. The
respective value for Russian import was in 2000 3 billion euros and the forecast for
2020 is 5.5 billion euros.

The importance of the Finnish-Russian border is emphasized in the value of Russian
import (Figure 7.14). It represents about 25…30% of the total Russian import value.

                                                Russian export via Northern Axis
                                                        million euros/a


  40 000



  30 000



  20 000



  10 000



       0
                1)    2) Vartius (FI) 3) Finland 4) Narva (EE)           5) Latvia -   6) Lithuania - 7) Lithuania -   8) Poland -
            Muurmansk - Lytta (RU)       Russia     - Ivangorod           Russia       Belarus, note: Kaliningrad        Belarus
              route                   border, other     (RU)                           incl. part of 6     (RU)
                                         than 2                                         (Kaliningrad)
                                        (Vartius)

                                                           2000 value    2020 value

Figure 7.13. Russian export via Northern Axis area (million euros/a) in 2000 and 2020



                                                 Russian import via Northern Axis
                                                          million euros/a


  40 000




  30 000




  20 000




  10 000




      0
           1) Muurmansk 2) Vartius (FI) -  3) Finland  4) Narva (EE) -   5) Latvia -   6) Lithuania - 7) Lithuania -   8) Poland -
               route       Lytta (RU) Russia border, Ivangorod            Russia       Belarus, note: Kaliningrad       Belarus
                                          other than 2      (RU)                       incl. part of 6     (RU)
                                            (Vartius)                                  (Kaliningrad)

                                                           2000 value    2020 value


Figure 7.14 Russian import via Northern Axis (million euros/a, 2000, 2020)


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Volumes assigned on the networks
All the results (costs, mileage, values, volumes at borders and ports etc) are based on
the assignments of the freight demand matrices (12 commodities, 2000, 2010, 2020)
on the transportation networks (road, rail, oil pipe and sea networks, altogether 9
modes). The next figures show the volumes in 1000 tons/a by main modes, road, rail
and tramp traffic (sea) in the Northern Axis area. Oil pipes, line traffic and in-land
waterways are left out and as well as flows less than 0.5 million tons/a. The scale is of
tramp traffic differs from the other modes.




Figure 7.15. Assigned international transport volumes on rail network in 2000 and 2020 (1000
tons/a, <0.5 million tons not shown)
The Russian large volumes in freight dominate the overall picture of rail transport,
especially between Moscow and St. Petersburg.




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Figure 7.16. Assigned international transport volumes on road network in 2000 and 2020 (1000
tons/a, <0.5 million tons not shown)




Figure 7.17. Assigned international transport volumes on sea network (tramp traffic) in 2000 and
2020 (1000 tons/a, <0.5 million tons not shown)
Sensitivity analyses
Increasing truck transport’s operation costs
The idea has been to find out, how the increase in truck transport’s operation cost in
the system affects the transportation mode choice (road or rail transportation). The
operation cost has been increased gradually first by 2.5%, then by 5.0%, 7.5%, and
finally by 10.0%. This corresponds to the increase of fuel price ca. 7.5%, 15%, 20%
and 30%.

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The flows of the year 2010 were used. The following figures show what will happen
to ton mileage by mode if the operating costs in road transport would rise. The results
are without the Russian, Ukrainian and Belarusian mileage (Only EU-25 countries +
Norway and Switzerland) because those flows would give bias for rail.

       100


       80


       60
   %
       40


       20


        0
               + 0%          + 2,5%         + 5,0%           + 7,5%      + 10,0%

                                          Road        Rail


Figure 7.18. The share of ton mileage by road and rail for all products at different operation cost
level


Even 2.5% increase in operation costs (equals 7.5% increase in fuel price) will yield
equal share in ton mileage for all the products. The road transport transfers to rail and
the impacts on total mileage are negligible. The share of road and rail together of the
total mileage (including sea transport and oil pipes) stays about the same, 39%, even
if operation costs of road transport increase.


       100

        80

        60
   %
        40

        20

         0
                + 0%          + 2,5%         + 5,0%             + 7,5%     + 10,0%

                                           Road          Rail


Figure 7.19. Product A (Food and Live Animals): share of ton mileage byroad and rail


Food and live animals are also sensitive for the price increase. For metal products the
results are even more sensitive.




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          100

           80

           60
      %
           40

           20

           0
                   + 0%          + 2,5%         + 5,0%            + 7,5%      + 10,0%

                                              Road         Rail


Figure 7.20. Product H (metal products): share of ton mileage by road and rail


Total volumes at border stations of Northern Axis countries stay quite stable even if
the operation costs for the road mode increase. Thus the use (the volumes) of
corridors stays also stable, even if the mode changes, the routes do not change so
easily.

The Russian Baltic Sea ports take the major share freight volumes and increase in
operations costs (road) yields only small impacts on the flows.


                                                     9
Increase of Level of Service at the Corridor 7
There is a great pressure to get more freight through the Corridor 7 (Moscow – Minsk
– Warszawa – Berlin). The impact of increasing the level of service (motorways and
high quality rail) on that corridor had been studied earlier with the same Frisbee
system in two cases: with costs (in that corridor) corresponding to German prices (A)
and to Russian prices (B).




9
    Source: Transport Connections between the EU and Russia, Current status and outlook for the future.
      Publications 10/2005, Ministry of Transport and Communication Finland, 2005



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       %
      5,0

               Route through Finland   Route through the Russian      Route through
                                              Baltic ports            the Baltic ports
      0,0



      -5,0



   -10,0
                         Germany - Poland -route, A      Germany - Poland -route, B


Figure 7.21. Decrease of transport volumes on other routes as a result of a more efficient level of
service on the Germany–Poland-route. (Unit costs on the Germany–Poland-route between
Moscow–the Polish border A: at the EU-level B: at the Russian level)


Changes on the route through Finland would be relatively small, total freight volumes
would decrease by a share of 1–2 % from the current level at the border between
Finland and Russia. This would indicate a decrease of about 0.2–0.4 million tonnes in
the transit traffic through Finland. Freight volumes through the Baltic ports would
decrease by an average share of 6–8 % and the transport volumes at the Baltic ports of
Russia would decrease by a share of 1–5 %.

Freight transport volumes on the Germany–Poland-route would more than double as a
result of a more efficient level of service. Other than so-called bulk cargo would
consist of the potential freight transport flows, which could shift to this route. A total
of about 210 million tonnes of freight was transported through the Baltic ports of
Russia and the Baltic countries in the year 2003. About 55 million tonnes of this
volume was other than bulk cargo.

Current transport times on the Germany–Poland-route are longer than on the other
routes. If border crossing operations and speed of transport on this route were at the
average EU-level, this would be clearly the fastest route in freight transport between
Germany and Moscow. Unlike the other routes, there are no port operations, but only
ground transport operations on this route.

7.3          Passenger Transport

7.3.1        Method and data
The focus of the passenger travel forecasting is in passenger flows between Russia
and EU countries, and international passenger flows elsewhere in the Northern Axis.
In this study the scope for the passenger travel demand forecasting is confined by the
relatively poor data availability.

Main passenger flows between Russia and Baltic States as well as Germany use air
connections. The train service between Moscow and St. Petersburg is heavily used


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and represents an important passenger corridor in the Northern Axis with the direct
continuation to Helsinki. Car journeys are also important in particular for short cross-
border traffic between Russia, Finland and Baltic states as well as between Norway
and Sweden, and Sweden and Finland. The main modes considered are air, rail, as
well as the car and bus journeys.

The approach to estimate the current and the future travel demand has been adapted to
the current lack of the data. It is a top-down approach that first provides the country
level forecast. A broad comparison of the country, and country to country level
forecasts is then made in order to determine validity of the data projections. Finally,
the key corridor forecasts are developed based on the available data sources.

Main steps for the estimation of the passenger matrix are:

           a. Estimation of the base year matrix based on the available data.
           b. Estimation of the matrix for the forecasting years. A broad, trend forecast
              of passenger travel demand was made, based on the SCENES European
              Transport Model Database and up-to-date socioeconomic data collected
              for the study. The forecast is at the country level, given the poor data
              availability at the sub-national level. This provides the most likely growth
              trajectory in terms of the overall passenger travel demand, and the context
              for the analyses at the corridor level.
           c. Comparison of the SCENES forecasts at the country level with the existing
              projections. This examines possible variations in existing forecasts. This
              includes the ETIS10 database. Also, as part of the data collection and
              consultation, the Country Experts have been asked to comment on the
              trend forecasts produced in the first stream of work. The feedback to a
              certain degree has been received, and this takes into account existing
              forecasts which have been made at the various levels of detail.
           d. Estimation and analysis of the key corridor forecasts based on a range of
              data sources and projections.

The main data sources used are the SCENES European Transport Model Database
that gives the total distance travelled by mode of transport on a country level; the
ETIS database that gives the origin destination matrix of the passenger trips by main
modes (air, rail, and private car), and the corridor traffic data where available. The
ETIS database has gaps and inconsistencies11. Comparison to other observed data
10
     ETIS (received from TNO, 2007)
11
   D5 Annex report WP 4: ETIS-Database methodology development and database user manual –
passenger demand V3.1. (NEA Transport Research and Training BV, 2004); “While some matrices
reflect all kind of transport from urban to long distance others just monitor the long distance cross
border trips above 100 km”. The source for the passenger data is VACLAV transport model which
does not simulate local NUTS3 level demand (for some metropolitan areas NUTS3 traffic share may be
relevant). The ETIS estimates were calibrated based on the survey focused on long distance trips. All
journeys are assigned to three main modes: air, rail and road. “Air includes access and egress by rail
and road. Rail includes ferries due to services offered. Road includes ferries due to services offered.
E.g. passengers using a rail connection where the train will be picked up by a ferry will be assigned to
the rail mode”.


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confirms that the rail and car matrices are likely to represent long distance cross-
border trips. Section Passenger Transport in Appendix 5: Transport Modelling gives
detailed representation of the data sources used, and how they compare to each other.

7.3.2   Base year demand
The section below first gives an introduction of the passenger demand in the Northern
Axis Area. It then uses the main data sources to estimate the passenger demand for the
base year. The base year demand is first given on a broad country level. The
passenger flows are then represented between the Northern Axis country pairs.

Passenger traffic has been gradually increasing between Russia and the old/new EU
Member States. The growth is expected to continue in the future, provided that no
major political upheavals take place. The trips can be categorized as follows:
   • Business (private companies and public sector),
   • Tourism and personal visits including long distance shopping,
   • Work and students trips across the border,
   • Small-scale trading and shopping across the borders, and
   • Other (social, sports, cultural events etc.)

The profile of the trips between the country pairs differs in some respects. Germany,
Norway and Sweden are more distantly located from Russia, which is reflected in the
trip profiles: number of tourism and personal visits may be smaller in volume than for
the other countries, but the trade value and travel budget associated with each trip is
likely to be higher than average. As Germany and Finland have the biggest trade share
with Russia, business trips are an important category for them. On the other hand, the
Russians have considerable business interest in the Baltic countries, which naturally
contributes to business travel demand to those countries.

Russian tourism is a very strong factor in Finland and the Baltic countries, not so
much in the other direction. In recent years, however, St. Petersburg is emerging as a
tourist attraction. Outside St. Petersburg and Moscow, the volume of tourists is
currently small.

Personal visits and visiting friends and relatives are important for Estonia and Latvia,
which have large Russian populations. There is also limited Latvian and Estonian
population on the Russian side, which means that this kind of travel will continue
long into the future and expand as income rises.

Employment of the population from the Baltic countries as well as Poland in the EU
countries is increasing steadily. It is a recent development and as such may not yet be
reflected in official statistics. The Baltic countries are expected to join the Schengen
Agreement in December 2007 alongside with the other new EU members. According
to the Schengen Agreement, systematic border controls between the old and the new
EU member states (within the Norther Axis those are: Estonia, Latvia, Lithuania and
Poland) will no longer be active. The border control is expected to remain only for sea
and air transport in airports.



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All modes of travel are used: air, train, bus and private car. Private car is used mainly
in shorter trips near the border. Bus and train dominates longer trips of low and
medium budget travellers. Air is clearly for business travel, tourists, and passengers in
transit, and generally for longer trips, such as between Germany and Russia. The
following table considers the drivers of growth by trip purpose and mode.

Table 7.10 Modes and drivers of growth by trip purpose
 Trip           Main travel mode                             Drivers of growth
 Purpose        Air      Train       Bus       Private car
 Business       EU       EU                    RU            RU and EU: Trade growth and GDP
                RU       RU
                Transit
 Tourism and    Transit EU           EU        RU            RU: Personal income in Russia and
 personal                RU          RU                      decrease of regulatory restrictions
                         Transit     Transit                 (visas) in EU
                                                             EU: Increase of wealth, better tourism
                                                             infrastructure,    and     decrease of
                                                             regulatory restrictions (visas) in Russia
 Employment,    EU        RU         RU        EU            RU: Decrease of regulatory restrictions
 students                                      RU            (visas and work/study permits)
 across the                                                  EU: trade growth
 border
 Small-scale                                   EU            EU and RU: price differences
 trading                                       RU
 across the
 border
 Other          EU        EU         EU                      RU: Personal income in Russia and
 (mainly        Transit   RU         RU                      decrease of regulatory restrictions
 seasonal                 Transit    Transit                 (visas) in EU
 events)                                                     EU: increase of wealth and decrease of
                                                             regulatory restrictions (visas) in Russia

EU: EU citizens to Russia
RU: Russian citizens to EU
Transit: Businessmen and tourists in transit

A broad indicator of the base year total passenger travel on an overall country level is
shown in Table 7.11. Given travel demand is by mode of travelling for the EU
Member States within the Northern Axis. The table gives no information for Russia
and Belarus. However, the study later analyses and estimates the passenger flows on
the major corridors to and from Northern Axis; the most important being to and from
Russia.




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Table 7.11 Passenger demand by country, base year 2000

                                                   Passenger Kilometres (billion) in 2000
                                                                                                                                 Grand
 Country             Air              Car           Bus/Coach                Slow                Train           All             Total
 Germany             38.3             871.8         69                       54.5                82.3            1115.9          2231.8
 Estonia             0.2              4.3           2.6                      0.1                 0.3             7.5             15
 Finland             5.7              56.6          7.7                      3.3                 3.9             77.2            154.4
 Latvia              0.2              6.6           2.3                      0.2                 1.3             10.6            21.2
 Lithuania           0.2              14.3          2.2                      0.1                 0.6             17.4            34.8
 Norway              0                47.9          4.1                      2.5                 2.9             57.3            114.7
 Poland              1.7              149.7         31.7                     9.4                 19.7            212.2           424.4
 Sweden      12.6      91.9      9.3           5.8          10.4        130        260
 Grand
 Total       58.9      1243.1 128.9            75.9         121.4       1628.1     3256.3
Sources: SCENES, 2005 (data on the country level is not available for Russia and Belarus)
The main generators and attractors of the passenger demand within the Northern Axis
are Germany, Poland, and Scandinavian countries. The corridor analysis will further
investigate the travel demand assignment on the mayor corridors to and from
Northern Axis.

The ETIS data source is now used to give an overview of the origin-destination
passenger demand travelling between the Northern Axis countries, including flows to
and from Russia and Belarus (Ukraine and Moldova also included). Table 7.12, Table
7.13, and Table 7.14 show the base year passenger demand by main modes, i.e.
private car, rail and air, (see footnote 11) between the Northern Axis countries. The
data is missing for some of the country pairs. The ETIS data for rail and car
passenger journeys is likely to represent long distance cross border movement, and
underestimates local cross border traffic and NUTS3 local traffic.

Table 7.12 Passenger car demand between Northern Axis countries; ETIS Base year 2000
 Private car
 passengers
 (thousand),
 2000          Fin             Nor          Swe           Est          Lat          Lit            Ger           Rus     Ukr      Pol           Mol    Bel
 Finland       139333.0           30.5         792.8       1927.4            33.2          4.8           131.8   79.8      2.3          176.7    0.1     0.4
 Norway               30.5     91134.5         217.0             6.8          5.0          1.2           307.0    2.9      4.0           54.0    0.1     0.4
 Sweden              792.8       217.0      263081.7            90.8         29.5          5.3          1091.3   36.3      8.7          183.8    0.4     0.5
 Estonia         1927.4              6.8          90.8    21102.5        336.1            15.1            23.3            21.1          104.0            4.7
 Latvia               33.2           5.0          29.5      336.1      25187.7        389.3               12.5            25.0           83.6    3.3    97.3
 Lithuania               4.8         1.2           5.3          15.1     389.3      36564.8               49.0            13.7          547.3    1.1   438.9
 Germany             131.8       307.0        1091.3            23.3         12.5         49.0     3019046.5     53.9     78.0        21057.1   10.6   229.9
 Russia               79.8           2.9          36.3                                                    53.9
 Ukraine                 2.3         4.0           8.7          21.1         25.0         13.7            78.0                          679.1
 Poland              176.7        54.0         183.8        104.0            83.6     547.3            21057.1           679.1    420824.1              98.8
 Moldova                 0.1         0.1           0.4                        3.3          1.1            10.6
 Belarus                 0.4         0.4           0.5           4.7         97.3     438.9              229.9                           98.8
Note: Base year data does not reflect short cross border traffic and NUTS3 local traffic




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Table 7.13 Rail passenger demand between Northern Axis countries; ETIS Base year 2000
 Rail
 passengers
 (thousand),
 2000           Fin           Nor          Swe          Est          Lat         Lit         Ger          Rus      Ukr          Pol               Mol     Bel
 Finland        11817.5             2.5          84.8     89.4          0.3            0.1          3.6   100.0                         2.9
 Norway                2.5    5839.5             25.7         0.9       0.1            0.0         19.3     0.2     0.0                 1.1
 Sweden               84.8         25.7    22343.1            9.9       0.3            0.1         96.0     0.1     0.0                 3.7
 Estonia              89.4          0.9           9.9   3550.1        127.5            4.8          0.6             0.6                35.2                 0.1
 Latvia                0.3          0.1           0.3    127.5       5576.6       130.9             0.8            10.0                43.8       0.0      51.9
 Lithuania             0.1          0.0           0.1         4.8     130.9      6732.2             1.6   17.9      0.9               203.7                29.4
 Germany               3.6         19.3          96.0         0.6       0.8            1.6   246024.0      30.4     0.0               509.0       0.1     288.9
 Russia              100.0          0.2           0.1                            17.9              30.4
 Ukraine                            0.0           0.0         0.6      10.0            0.9          0.0                                74.2
 Poland                2.9          1.1           3.7     35.2         43.8       203.7         509.0              74.2          41194.2                  422.5
 Moldova                                                                0.0                         0.1
 Belarus                                                      0.1      51.9        29.4         288.9                                 422.5
Note: Base year data does not reflect short cross border traffic and NUTS3 local traffic

Table 7.14 Air passenger demand between Northern Axis countries; ETIS Base year 2000
 Air
 passengers
 (thousand)
 2000          Fin           Nor           Swe          Est           Lat        Lit         Ger          Rus       Ukr               Pol         Mol      Bel
 Finland        3105.9              68.9     648.2            78.7     32.9        20.3         339.6       97.9          3.9           43.3        0.0         0.0
 Norway              68.9      9529.1            46.3         14.7         9.8         3.2      230.3       18.2          9.8           30.0        1.1         1.6
 Sweden          648.2              46.3    4698.1        115.6        38.4        18.8         484.5       10.8          4.1           35.9        0.6         0.5
 Estonia             78.7           14.7     115.6                         7.1         9.9         25.7                   5.8               4.2                 0.9
 Latvia              32.9            9.8         38.4          7.1                     3.5         28.5                   5.7               5.2     0.0         0.1
 Lithuania           20.3            3.2         18.8          9.9         3.5         0.7         43.6                   2.1           13.9                    5.4
 Germany         339.6             230.3     484.5            25.7     28.5        43.6       17935.7      544.8      76.5             270.5       11.3     22.8
 Russia              97.9           18.2         10.8                                           544.8
 Ukraine              3.9            9.8          4.1          5.8         5.7         2.1         76.5                                 57.6
 Poland              43.3           30.0         35.9          4.2         5.2     13.9         270.5                 57.6             697.4                    0.8
 Moldova              0.0            1.1          0.6                      0.0                     11.3
 Belarus              0.0            1.6          0.5          0.9         0.1         5.4         22.8                                     0.8
Note: Base year data does not reflect short cross border traffic and NUTS3 local traffic

The country to country data demonstrates that the passenger flows between more
distantly located countries to Russia such as Germany, and Norway mainly use air
connections. The passenger flows between Finland and Russia are equally distributed
between rail and air with the long distance car journeys being below rail and air. The
train service between Helsinki, St. Petersburg and Moscow is one of the major
passenger connections in the study area. Rail is also important between Germany and
Belarus, Poland and Belarus compared to the air passenger demand.

Passenger flows from Germany to Russia by car are moderate to low. The data shows
that Estonia has strong links with Finland, whereas Lithuania and Latvia have stronger
connections to the other Baltic countries as well as to Belarus and Poland. Short cross-
border car traffic in particularly between Russia and Finland is likely to be
underestimated.



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7.3.3      Demand Forecasts
Available forecasts on passenger travel in the Northern Axis area have been reviewed.
There is a significant lack of existing data and the available forecasts are largely poor
and inconsistent at the corridor level analysis.
The approach to estimate the future travel demand has been adapted to the current
lack of the data. The approach first provides the country level forecast. This is then
followed by a broad comparison of the country level forecasts against the available
country to country level forecasts, in order to determine consistency of the travel
demand projections. The key corridor forecasts are later developed based on the
analysis of the available data.

There are only few existing forecasts in the Northern Axis area specifically dealing
with international and cross-border passenger traffic. National road authorities usually
maintain forecasts of road traffic on the national network, typically for some 20 years
into the future. These forecasts are not strong in cross-border traffic and are based on
less robust data than for heavy goods vehicles. With some limitations, they will be
used to get at least a general estimate of the passenger traffic along the key corridors
and borders in the Northern Axis countries.

The total passenger demand percentage change between the 2000 and 2010, and 2000
and 2020, for the Northern Axis countries (Russia and Belarus not included) is
represented in the following Table 7.15. This represents the SCENES12 European
Transport Model forecast corrected for the socio-economic assumptions as developed
for this study (see Appendix 5 on the difference in GDP growth assumptions).

The study later analyses and estimates major passenger flows on the corridors to and
from Northern Axis, the most important being to and from Russia. The ASSESS
Partial scenario, as indicated in the table, represents perhaps the most likely outcome
of the implementation of the main White Paper measures.




12
  ASSESS, “Assessment of the contribution of the TEN and other transport policy measures to the
midterm implementation of the White Paper on the European Transport Policy for 2010”, Final Report,
European Commission, DG TREN, 2005.
SCENES provides transport demand forecast for 2010 and 2020, having the 2000 as a base year, based
on a set of macro-economic and trade assumptions derived from DG TRENs.




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Table 7.15 Medium term passenger demand forecast on a country level
              Partial scenario:
              passenger kilometre                              Bus/      Walk/
 State        % change over period       Air        Car        Coach     Cycle      Train      All
 Estonia      2000-2010                  98.1       36.9       -6.8      14.6       -5.8      21.4
              2000-2020                  206.2      82.1       -15.0     24.0       -4.0      47.1
 Finland      2000-2010                  50.0       11.5       -3.1      4.2        11.5      12.5
              2000-2020                  107.8      32.5       -7.3      12.6       19.9      32.5
 Germany      2000-2010                  50.8       18.6       22.3      13.6       5.0       18.6
              2000-2020                  108.7      40.6       28.7      20.3       19.1      39.4
 Latvia       2000-2010                  22.8       38.5       -7.9      11.8       -4.7      22.0
              2000-2020                  29.7       73.5       -11.9     17.8       -8.2      43.1
 Lithuania    2000-2010                  23.3       32.9       -5.6      12.8       -2.4      26.5
              2000-2020                  40.0       57.0       -12.3     20.0       -4.6      46.2
 Poland       2000-2010                  72.2       47.9       -5.2      20.0       0.0       33.9
              2000-2020                  154.8      84.9       -10.3     24.6       -4.8      60.3
 Sweden       2000-2010                  53.4       14.9       2.1       5.3        24.5      18.1
              2000-2020                  95.1       34.9       3.2       18.0       25.4      37.0
Source: ASSESS Partial scenario forecasts (ASSESS, 2005) corrected for the difference in GDP.


The SCENES based forecast suggests that, in Baltic countries, the total passenger
travel demand (in passenger km) will grow by around 23% by 2010 and 44% by 2020.
There is in general much faster passenger demand increase in the EU10 New Member
States, in particular in Baltic States. Train, bus and coach passenger journeys are
expected to decline in the Baltic States, and have a moderate growth in Sweden,
Finland and Germany. On the other side, car journeys will rise sharply in the Baltic
States.

Over the forecasting period, the population is stable in EU15 and slightly declining in
some EU10 countries, so the growth of passenger demand stems mainly from the
increasing mobility of the individuals. The ASSESS study has shown that the long
distance travel is growing more strongly than the shorter distance travel like
commuting, education and personal business.

The given country level forecasts now provide the most likely growth trajectory in
terms of the overall passenger travel demand, and the context for analyses at the
corridor level. Note that the country level forecasts in the majority of cases would
indicate the minimum level of growth that can be expected at the corridor level
(because long distance traffic is likely to growth more quickly than short distance,
local traffic).

The ETIS forecast is available for the period between 2000 and 2020 (see Table 7.16,
Table 7.17 and Table 7.18 for passenger growth rates by main mode11). The ETIS
forecast figures are not available for all of the country pairs. Forecasts for private car
and rail passengers do not reflect short cross border traffic and NUTS3 local traffic
growth.




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Table 7.16 ETIS Private Car passenger percentage change over period 2000 – 2020 for Northern
axis countries
Northern Axis
Private car pax growth
2000-2020                  Fin          Nor          Swe            Est               Lat            Lit          Ger           Rus       Ukr         Pol         Mol      Bel
Finland                     24.0           16.5        14.4           27.6            -16.9           -11.5          4.8           3.7         -4.6     29.3       63.1     26.4
Norway                      16.4           39.4        38.6          -15.2            -25.1           -18.7         30.2          -8.9         29.0     15.5       30.1     20.8
Sweden                      14.4           38.6        22.9           10.6            -21.5           -16.0         24.9          18.5         17.1     25.7       40.3     10.5
Estonia                     27.9           -15.2       10.6           43.2             49.5           58.2           -0.5                       3.3     62.3                14.7
Latvia                      -15.6          -25.4       -21.3          48.4               0.0          44.3          11.3                       -2.9     34.3       75.0     35.3
Lithuania                   -11.5          -18.7       -16.0          58.2             44.3           70.0          12.4                       -0.2     71.2       68.9     21.0
Germany                      4.8           30.2        24.9           -0.5             11.3           12.4          15.4          26.2         19.3     27.0       78.0     63.1
Russia                       3.7            -8.9       18.5                                                         26.2
Ukraine                      -4.6          29.0        17.1               3.3          -2.9            -0.2         19.3                                    9.2
Poland                      30.6           15.6        25.7           62.2             36.7           71.2          27.0                        9.2     73.0                25.5
Moldova                     63.1           30.1        40.3                            75.0           68.9          78.0
Belarus                     26.4           20.8        10.5           14.7             35.3           21.0          63.1                                25.5
Note: (blank cell) indicates that the data is not available. Forecasts do not reflect short cross border
traffic and NUTS3 local traffic growth
Table 7.17 ETIS Rail passenger demand percentage change over period 2000 - 2020 for Northern
axis countries

Northern Axis
rail pax growth
2000-2020         Fin        Nor              Swe             Est               Lat            Lit            Ger           Rus          Ukr          Pol         Mol      Bel
Finland             13.4           11.3              0.0           30.8          -20.5             -14.3           2.4          -4.1                    32.5
Norway              11.3           83.9             64.0       -17.2             -17.2             -20.0          37.8          -2.1      150.0         32.6
Sweden               0.0           64.0             12.5            0.0          -17.9               1.4          25.8           3.4      300.0         55.2
Estonia             31.3          -17.2              0.0            2.4          11.5              18.2           16.1                         8.8      34.6                12.9
Latvia             -19.0          -17.2            -17.9           12.5           0.0                9.4          10.9                     20.8         18.1       50.0     45.5
Lithuania          -14.3          -20.0              1.4           18.2           9.4              25.2           30.3                         3.8      28.5                25.5
Germany              2.4           37.8             25.8           16.1          10.9              30.3           10.4          17.6       55.6         26.5       52.5     62.9
Russia              -4.1            -2.1             3.4                                                          17.6
Ukraine                           150.0            300.0            8.8          20.8                3.8          55.6                                      7.8
Poland              32.8           32.1             53.8           35.0          19.6              28.5           26.5                         7.8      22.1                48.4
Moldova                                                                          50.0                             52.5
Belarus                                                            12.9          45.5              25.5           62.9                                  48.4
Note: (blank cell) indicates that the data is not available. Forecasts do not reflect short cross border
traffic and NUTS3 local traffic growth
Table 7.18 ETIS Air passenger demand percentage change over period 2000 - 2020 for Northern
axis countries
Northern Axis
Air pax growth
2000-2020                   Fin            Nor         Swe            Est              Lat            Lit           Ger           Rus      Ukr        Pol         Mol      Bel
Finland                          50.2        60.5           51.2      143.6                 70.3           70.4          55.9     44.5         44.6    198.2       310.0    142.9
Norway                           60.5        67.1           77.0          87.1              87.2           92.6          91.1     40.1         90.5    144.7       119.9     85.7
Sweden                           51.2        77.0           68.2          93.6              88.4           76.3          83.9     47.3         90.1    143.7       155.2     78.6
Estonia                      142.8           87.1           93.6                            61.1           64.2      116.7                 161.4       474.2                202.9
Latvia                           69.6        86.7           88.5          59.9                             58.9          48.6              179.3       414.3       300.0     64.2
Lithuania                        70.4        92.6           76.3          64.2              58.9           87.8      115.1                 171.7       167.3                228.7
Germany                          55.9        91.1           83.9      116.7                 48.6       115.1             59.5     53.8         46.2    154.9       176.3    100.3
Russia                           44.5        40.1           47.3                                                         53.8
Ukraine                          44.6        90.5           90.1      161.4             179.3          171.7             46.2                          185.2
Poland                       193.0          144.9          143.5      482.9             401.2          167.3         154.9                 185.2       250.6                255.8
Moldova                      310.0          119.9          155.2                        300.0                        176.3
Belarus                      142.9           85.7           78.6      202.9                 64.2       228.7         100.3                             255.8
Note: (blank cell) indicates that the data is not available


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The ETIS air passenger forecast indicates a continuous growth of air passenger
demand in the Northern Axis area with the highest growth of demand being from the
Baltic States, plus Belarus and Moldova. The road forecast indicates a moderate
increase in longer road journeys between Sweden and Russia as well as Germany,
Belarus and Russia. Scandinavian countries may have a smaller demand for the rail
services towards Baltic countries notably Latvia and Lithuania, but will generate
higher long distance travel growth towards Poland and Germany. A moderate
passenger growth is predicted between Russia and Germany. Rail passenger demand
between Finland and Russia is likely to be underestimated (see footnote 11).

The ASSESS (corrected for the socio-economic assumptions) and the ETIS
projections are not directly comparable due to the data definitions. They should
however have a broad agreement on the future year travel demand trends. See
Appendix 5 for more details on the two projections.

The two although different forecast are broadly consistent and indicating a stronger
growth of car passenger traffic in the Baltic States as well as in Poland. The ASSESS
most likely scenario for the total distance travelled by air gives higher growth rates
than in the ETIS for Finland, Sweden, and Germany. This is probably due to higher
rise of long distance journeys in these countries. This is contrary to the rail journeys in
the Baltic countries. It is also likely that the 2020 air passenger demand projections
for the Baltic countries rather represent lower growth scenario.

The available projections provide the most likely growth trajectory in terms of overall
passenger travel demand, and the context for the analyses at the corridor level.

7.3.4   Passenger demand analysis


Assumptions
The passenger flows by mode is first analysed and estimated on the main corridors
and borders in the Northern Axis area, based on the observed flows.

Expected growth rates at the specific corridor locations were developed based on the
available forecasts and in consultation with the Country Expert Group. The given data
and forecasts are subject to lot of uncertainly. The given base line figures and
projections should be considered as indicative only.

The corridor level forecast segmented by the border and non-border cross-country
traffic is then analysed and discussed in the context of the broad country level
passenger travel forecast. The country level forecasts in the majority of cases would
indicate the minimum level of growth that can be expected at the corridor level.

National road authorities’ forecasts on the road traffic are used to get a general
estimate of the passenger traffic along the key corridors and borders in the Northern
Axis countries. In general, passenger traffic forecasts are based on less robust data
than heavy goods vehicles.



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The below section summarises the “current” and the future travel demand on the key
corridors first for road, rail and finally for air travel. The “current” data represent a
combination of data collections in the last 5 years.In addition, it analyses the border
crossing traffic for the road transport.


Road Passenger Flows at Corridors/Borders
Section 4.2.3 describes each of the key corridors. In terms of the road travel, it focuses
mainly on the HGV traffic. The available data source provides information on the
HGV share in the total traffic. It has been assumed that the rest of the road traffic is
made of passenger cars, small vans or buses, with the van share being inconsiderable.
Figure 7.22 gives an indication of the passenger related traffic change along the key
study corridors between the current year (2002-2006) and 2020. The figures give the
minimum and maximum percentage change expected on different road sections along
the corridors (Section 4.2.3 gives more details for the traffic on the corridors). The
traffic includes both domestic and international.




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Figure 7.22 Forecast of average annual daily passenger related traffic (passenger car, bus and LGV)
between the current (2002-2006) and Future year (2020) on Northern Axis corridors
Source: National road authorities interviewed
Note: It is not possible to separate cars, buses and light good vehicles (LGV) in the data available. The
LGV share is likely to be small and they are often used for passenger as well as freight transport.
The “current” data represent a combination of data collections in the last 5 years.
At the time of writing this report, no data is available for the road sections in Norway, Lithuania and
Poland.

In general, car share in the total road traffic is high in Scandinavian Countries (80 to
90%), lower in the Baltic Countries (around 70% or higher), and is the lowest on the
Russian side of the corridors (around 50% or higher).

The growth is predicted to be high on the corridors between Latvia, Lithuania,
Belarus, and Russia. Passenger traffic growth will be lower on the corridors between


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Scandinavian countries, and moderate to high between Scandinavian countries and
Russia.

On the Narvik-St.Petersburg corridor, traffic volume is the highest at the Haparanda
border (11000 non-HGV per day). Elsewhere traffic level is lower. The country level
forecasts are slightly above the given forecast, and below the border traffic forecast.

The Helsinki-St Petersburg-Moscow corridor is the busiest corridor of the Northern
Axis. The non-HGV traffic volumes between Moscow and St. Petersburg are very
high (from 10000 to 20000) as well as around Helsinki. Vaalimaa border has a
moderate traffic with around 4000 non HGV traffic; nevertheless with the growth of 2
to 3% per year it may become one of the bottlenecks. The model forecast for Finland
is broadly matching the corridor forecast. The forecast of the traffic is from moderate
to high in particular for the traffic in Russia, with the higher forecasts along the whole
corridor in Russia. The traffic from Finland to Russia on the Vaalimaa border has a
moderate traffic growth.

The Tallinn-St. Petersburg corridor is another important road corridor with the high
traffic flows in the large urban areas such as Tallinn, Narva/Ivangorod and St.
Petersburg. Traffic is envisaged to grow strongly around St. Petersburg and along the
corridor from Russian border, and moderate in Estonia. The country level forecast is
higher than the given forecast along the Estonian part of the corridor. It is likely that
the corridor data underestimates growth of traffic in Estonia.

The Ventspils-Riga-Moscow corridor is similar to the Tallinn-St. Petersburg route
catering to intercity traffic between the two capitals (Riga and Moscow) and the
Latvian port city of Ventspils, as well as destinations between them. Flows are the
lowest near the border (2200-3500 non-HGV per day). HGV share in Latvia is
predicted to have a high growth. Although both the Latvian and Russian border traffic
is not very high at the moment, with the traffic growth in the future, these have a
potential to become the corridor bottlenecks. The country level forecast is lower that
the given corridor forecast.

The Klaipeda-Vilnius-Minsk corridor traffic flows are quite high in Lithuania (up to
25000 non-HGV per day). In Belarus, traffic is more moderate at 4500 of non-HGV
per day. The given forecast for the traffic in Belarus is moderate.

The Kaliningrad-Kaunas corridor is a very short corridor but an important road
connection between Lithuania and Kaliningrad. Near Kaunas the traffic volume is
higher (13000 all vehicles per day). Kaliningrad has a moderate level of non HGV
traffic or around 4500 per day. In Kaliningrad, Russian side of the corridor, the traffic
is predicted to have a high grow. The country level forecast predicts similar trend
around Kaunas.

The Berlin-Warsaw-Minsk-Moscow corridor is the major corridor between Russia and
Central Europe. The HGV share ranges along the corridor are high, around 25 to 50%,
which indicates importance of the corridor for the freight traffic. At borders the HGV
share can be as high as 60%. The corridor is still used for shorter passenger journeys.


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Traffic volume in Germany is high, with sections with around 30000 to 40000 of non-
HGV per day. The border traffic is lower in general with around 7000 vehicles per
day. The Belarusian sections are moderate with 4000 non-HGV per day. The given
forecast implies a small growth of non-HGV traffic in Germany, moderate in Belarus
and Russia, and very high on the Belarus-Russian border. HGV share on some parts
along the corridor in Germany will have a high growth from 23% to around 40%.

The Oslo-Stockholm and Oslo-Copenhagen corridors are parts of the Nordic Triangle
TEN –T priority project. The forecast data is not available for this corridor. However
it is known that in particular the Corridor 9 has high level of total traffic over a
considerable length (more than 20000 vehicles per day). The sections near Oslo have
the highest volumes. The ASSESS is predicting a moderate growth in road passenger
demand in Sweden (around 30% over the period from 2000 to 2020), and low in
Denmark (around 10% over the period from 2000 to 2020).

Summary of the analysis of the cross-border traffic is presented on the following
figure.


                          PASSENGER CAR, BUS AND LGV ON NORTHERN AXIS BORDERS

                         18000
                                                                                         289%
                         16000
                         14000
  Vehicles per day




                                         36%
                         12000
                         10000
                          8000
                          6000
                                                       34%         96%    44%   36%
                          4000
                                                 20%
                          2000
                                 0
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                                                        Current    2020

Figure 7.23 Passenger car, bus and LGV travel demand percentage change between the “current”
(2002-2006) and Future year (2020) on Northern Axis borders.
Source: National road authorities interviewed.
Note: It is not possible to separate cars, buses and light good vehicles (LGV) in the data available. The
LGV share is likely to be small and they are often used for passenger as well as freight transport.
The “current” data represent a combination of data collections in the last 5 years.

Most of the borders are either already having a high level of traffic congestion, or are
predicted to have a high traffic growth.




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Rail Passenger Flows at Corridors
The Chapter 4.2.5 describes each of the key rail corridors. The available data is given
mainly for the freight rail traffic, and it does not exist for the rail passenger demand.
This makes it difficult to analyse rail passenger demand along the key corridors. Rail
travel demand will require further research.

This section describes the general situation on the passenger rail services in the
Northern Axis, summarises information on the corridor traffic, and recommends
further action.

Currently there are no direct trains that can run across the borderline of the “Russian”
and “European” rail systems. However there are no physical obstacles in crossing the
border between Russia, Belarus, Estonia, Latvia and Lithuania. Finland and Russia
have different systems of traction power and signalling that makes it necessary to
change the locomotive at the border. The EU external borders with Belarus and
Russia are still old-fashioned where full checks of personal travel are carried out.

In the Baltic States, rail has been mainly used for the freight transport. There are 71
freight railway stations in Estonia and 43 passenger stations. In Lithuania the
corresponding numbers are 118 (freight) and 76 (passenger). In Latvia there are 169
freight stations but only 1 railway station (Riga) is registered as a passenger station.
(The World Bank, 2007). Particularly in Latvia and Estonia, the market share of the
rail mode is at a very low level.

The Rail Baltica between the Baltic States and Poland will connect Warsaw and
Tallinn via Kaunas and Riga by a western gauge rail line. Improved rail lines will
result in more efficient land-bound connections between the Baltic and the Nordic
countries (particularly Finland) and in the long run potentially further to Central Asia.
International rail passenger transport flows along the Rail Baltica corridor are
currently negligible and road transport is predominant. Congestion in north-western
Germany can be bypassed.

One of the major passenger corridors in the study area is Helsinki – St Petersburg
corridor. The St Petersburg railway bypass has enabled passengers to travel by high-
speed train from Turku or Helsinki to Moscow without changing trains. Stockholm
offers high-speed services via the Ostlanken line to continental Europe.

The Narvik – St.Petersburg corridor is the longest rail corridor where the most parts
are for freight only traffic. High passenger flows are in the St. Petersburg region. The
peak day have 37 passenger trains serving the St. Petersburg region. The country level
forecast predicts moderate growth of rail passenger traffic in Sweden and Finland.

The Helsinki-Moscow corridor is the most important and busy railway of the
Northern Axis. There have been 267000 passengers travelling between Finland and
Russia in the year 2005. This rail corridor is predominantly a passenger corridor. Rail
passenger demand between Helsinki and St Petersburg will have a high growth if a
railway line between the two cities is to be upgraded into a high speed railway.
Maximum country level forecasts for Finland are around 25% for the rail traffic.

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The Tallinn-St.Petersburg corridor is predominantly a freight line even if some long-
distance passenger trains are serving the line. Crossing the Russian-Estonian border
does not present any technical problems and it may have potential for better passenger
service. There are two pairs of international trains; one daily connection Tallin-St.
Petersburg and one daily connection Tallin-Moscow. On Estonian side, there are also
nine pairs of commuting trains in Tallin-Tapa section (five trains continue towards
Tartu and South East Estonia and two continue towards Narva). The country level
forecast for the rail traffic in Estonia is from a slight drop to a small growth of 4%.
With the Rail Baltica project (Tallin-Tartu-Valga line will be the basis for Rail Baltica
phase I development in Estonia) it is likely that the rail passenger demand in Estonia
will have a positive growth.

The Ventspils-Riga-Moscow corridor is predominantly a freight line with some long-
distance passenger service. However, commuter traffic is heavy in Moscow and Riga.
There are 38 trains per day running on Latvian side and up to 54 on Russian side.

The Klaipeda-Vilnius-Minsk corridor is also one of the main freight routes from the
Russian and Belarusian hinterlands to the Baltic Sea ports. There is no direct
passenger service connecting Klaipeda and Minsk. There are from 17 to 61 trains
running from Minsk to Vilnius. The model predicts small drop in passenger traffic in
Lithuania.

Lithuania is a transit corridor for the rail passenger flows from Kaliningrad to Russia.
In 1995, 48.9% of all the international railway passengers flows were ending or
originating in the country, whereas in 2001 their share decreased to 14.4%. Car has
become a dominant transport mode in the Baltic countries; over 76.4% of passengers
go by car from Vilnius to Kaunas, 84.6% between Vilnius and Klaipeda (The research
into the development of passenger transport by land, Jonas Butkevicius, Vilnius
Technical University, 2004).

The Kaliningrad (Russia)-Kaunas is an important supply and export route to and
through Kaliningrad from the mainland Russia. Freight is the dominant user of the
route, but it also has a fair volume of passenger traffic. The railway is not electrified
and there are no technical problems with crossing the Lithuanian-Russian
(Kaliningrad) border.

The Berlin-Warsaw-Minsk-Moscow corridor is the major corridor between Russia and
Central Europe, as well as the EU. The route has high volumes of both passenger and
freight traffic, but mainly within each country. Belarus-Polish border is an obstacle to
the cross country movement. The country forecasts for Germany and Poland is from
15 to 20% in Germany and a slight decline in passenger demand in Poland.

The Oslo-Stockholm and Oslo-Copenhagen corridors are part of the Nordic Triangle
TEN –T priority project. Both railways are for passengers and freight, but the Oslo-
Stockholm line is more geared to freight. Near Oslo there is heavy commuter traffic
on both lines. The country level forecast predicts moderate increase in rail share for



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Sweden of up to 26%. Both corridors have strong prospects of attracting bigger share
of passengers.


Air Passenger Flows at Corridors


Main passenger flows between Russia, Germany and Poland, and Baltic States use air
connections.

The past decades have seen a rise in the importance of regional airports but also large
airports. A few large international airports in Helsinki, St. Petersburg and Stockholm
are still the Northern Axis main international hubs. Rapid rises in income in Estonia,
Latvia and Russia have increased tourist travel from St. Petersburg, Riga and Tallinn,
and business travel has increased throughout the region. Many regional airports are
still subsidised, mostly to allow them to maintain high environmental standards and
improve links to TEN road and rail systems and the Helsinki corridors.

Low-cost carriers, notably Ryanair and EasyJet have entered the Baltic aviation
market in 2004 operating flights to Tallinn and Riga. As a result, the passenger
numbers have almost doubled after the EU membership.

The ICAO data is the only data source that shows on an aggregate basis the number of
passengers between all international city-pairs on scheduled services. The figure
below indicates the base year (2005) and growth in passenger demand over the period
of 2005 and 2020 on the key city pairs in the Northern Axis area (see Appendix 5 for
details on the air traffic data between the 2000 and 2005). The ETIS country to
country annual growth rates were used in order to extrapolate the numbers into the
future. The ETIS projections are broadly in line with the ASSESS partial scenario,
and EUROCONTROL’s forecasts of IFR, apart for the Baltic States that are likely to
have a higher passenger growth.

Helsinki-Stockholm is one of the busiest city pair corridors in Europe although it has
seen a drop in traffic in the last two years. However the trend is now reversing and it
is likely that the city pair will remain one of the busiest in the future. Helsinki
(Vantaa) airport is within the top 50 most affected departure and arrival airports in
Europe with the average delay per departure and arrivals of 10 to 9 minutes
respectively.

The airports in the region are growing fairly fast. International passenger travel
to/from Russia, that basically is Moscow and to a lesser degree St. Petersburg has
grown rapidly, for instance by 21% between 2003 and 2004. The passenger demand
towards Moscow has been increasing on all of the major corridors.




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Figure 7.24 Air passenger traffic percentage change on the key corridors in Northern Axis area
between the 2005 and 2020
Source: ICAO, 2007; ETIS, 2007
Note: Helsinki - St. Petersburg and Berlin - Helsinki base year value represents extrapolation of the
past trend.

Oslo airport is one of the busiest airports in the Northern Axis. It has seen traffic
growth of 3% per year over the last 7 years. The city pairs not represented in the
above table that are within the busiest in Europe are Oslo-Bergen, Oslo-Trondheim
and Oslo-Stavanger with the increase in number of flight of 3, 5, and 8% respectively.

The effects of the expansion of the EU in 2004 have increased traffic to Poland.
Poland in particular has sustained around 20% growth through 2006, adding around
100 flights per day to the European network. Ukraine has signed the Open Skies
agreements that may explain a strong growth trend of air passenger transport.

The air passenger demand will have a moderate to strong growth in the Northern Axis
countries, in particular between Baltic States and Russia.


Sea passenger transport
Sea transport has not been the main focus of the study. However, it is important to
mention main past trends. The figure below shows the sea passenger transport
between Finland and other bordering Northern Axis countries in the past 25 years.

Sea passenger transport demand between Sweden and Finland has been growing at a
high rate over the last 25 years. Travel to and from Estonia had a sharp increase
between the 1995 and 2000, followed by a small decline in the following three years,
with the demand having an increasing trend again from the 2003 onwards.




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                                   W ATER TRANSPORT - PASSENGER DEMAND BETW EEN FINLAND AND OTHER
                                                       NORTHERN AXIS COUNTRIES


                           10000
   Passengers (thousand)




                            8000

                            6000

                            4000

                            2000

                               0
                                     Sweden          Rus s ia            Es tonia            Latvia           Germ any

                                      1980    1985   1990       1995   2000    2001   2002      2003   2004     2005


Figure 7.25 Passenger transport by sea from and to Finland
Source: Finnish Maritime Administration, 2007

It is important to mention that the port of Tallinn has significant international
passenger movements. There are no other ports in the Baltic States area, which
operate more than 300,000 passengers in the international traffic per year (The World
Bank, 2005). In the 2004 summer months, there were over 65 passenger ferry
departures a day, and around 30 in the wintertime along the passenger shipping route
Tallinn – Helsinki, one of the major sea corridors in the study area.


Summary of major international passenger flows
The major international passenger flows by all modes (road, rail, air, sea) on the
Northern Axis are presented in the same scale in the figure below. Where applicable,
also growth estimates are indicated.




Figure 7.26 Major international passenger flows in different modes
Source: National road authorities interviewed, Finnish Maritime Administration (2007), ICAO (2007),
ETIS (2007).
Note: Current year for air, rail and sea transport is 2005; and for road it is combination of data
collections in the last 5 years
Figure 7.22 shows the borders for which the road traffic data is estimated.


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8 The Bottleneck Analysis

8.1     Principles of the system evaluation

8.1.1     Method selection
A transport system can be analysed and its deficiencies (e.g. bottlenecks) identified
from three fundamentally different perspectives:

a. A pre-selected design standard. A standard-based analysis is rather
   straightforward if all the necessary information is available. For instance, if it is
   decided that all axis roads must be motorways then all ordinary 2-lane roads of the
   network are deficient and need upgrading. Or, if a railway system must to carry
   25-ton axles, all railway sections not meeting this standard are deficient.

      The standard-based method is very common and it has been used widely in most
      countries in the past. It has certain advantages such as simplicity, and it also
      promotes the systemic view of the design. The drawback is that a road or railway
      design based on a uniform standard is not likely to be always cost-effective and
      invariably provides excessive standard (i.e. capacity) on much of the system. In
      recent years, the standards-based design has run into very difficult conflicts with
      increasing environmental concerns and restrictions. As a result, it has become the
      embodiment of the “engineering approach” to transportation problem.

b. Capacity analysis compares traffic volume (transport demand) to a link or node
   capacity (infrastructure supply) in current or some future situation. As this method
   is specifically sensitive to the transport demand, its application should result in a
   cost-effective system of transport infrastructure. Capacity-based analyses are also
   nowadays very common and relatively easy ways of making estimates of the
   status and development needs of any infrastructure system. Results of such
   analyses are also quite adequate for many purposes, typically in national, regional
   and project-level analyses. The capacity-based analysis has, however, some
   inherent problems particularly when it comes to international transport:
   • a capacity analysis is not sensitive to the needs of the international trade and
       traffic other than possibly in the vicinity of borders. Domestic traffic
       dominates the flows elsewhere and determines the improvement needs.
   • analyses are location and mode-specific and typically result in lists of isolated
       measures. A wider view with well-understood systemic effects is difficult to
       devise.
   • any identified lack of capacity calls mainly for new infrastructure investments,
       as the basic remedy of a capacity deficiency will invariably be capacity
       increase using investments
   • capacity analysis can handle poorly or not at all the “softer” policy objectives
       (i.e. maintenance, safety, environment)

c. Outcome-based analysis where only the system performance, with regard selected
   objectives, matters. This is done by describing the current and future performance

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   of the system in terms of selected indicators, which should depict the service that
   the system users enjoy at any given time. Typical performance indicators include
   travel speeds or times on a link, or hours of delay at a border crossing.
   Deficiencies are identified when revealed outcomes (e.g. travel times over a road
   section) are compared with policy objectives. Outcome-based approach tries
   expressly to evaluate the system from the users’ point of view, whereas the
   standard-based approach and even the capacity-based approach are more or less
   driven by the system owner’s views.

    The outcome-based analysis using performance indicators can to a large extent
    avoid the problems of capacity analysis. This presupposes that indicators are
    selected so that they are responsive to policy targets.

   Performance is also inherently scalable and can be used to evaluate both specific
   locations as well as the entire infrastructure system using same measures. Also,
   very different elements of the transport chain, not only infrastructure links, can be
   evaluated and compared using the same measures, such as road/rail sections,
   terminals, borders etc. This can lead to a much wider variety of improvement
   measures than a simple capacity analysis might suggest. For instance, in the case
   of transport axes, a transport delay indicator can be used to compare the ease of
   the international goods and passenger transport over a range of links, nodes,
   terminals and even regulatory practices. A set of best measures that eliminate
   delays the most and at a least cost is then rather straightforward to select.

The High Level Group report stated in a very concise way that the overall objective of
the Group’s work has been the facilitation of (international) trade and economic
development in the EU and its neighbouring countries. Consequently, they are also
the fundamental reasons for establishing the major trans-European transport axes in
the first place. From this it follows that the primary focus of the future development of
the transport axes should be on:
    • international trade flows, and
    • international business related travel.

As international trade flows and business travel are only a fraction of all traffic on
roads and railways constituting the axes, it is somewhat difficult to see other than the
outcome-based method that can be considered for the axis analyses and long-term
monitoring purposes. The tools for doing this are performance indicators, which will
be selected so that they describe the condition of trade flows and business travel in the
system properly. In the following chapters the concept of performance indicators is
developed further, now mainly from the perspective of international freight transport.

8.1.2   Performance indicators
The key to the outcome-based approach is the selection of performance indicators,
which must be, among others:
   • responsive to selected policies
   • easy to understand
   • measurable at a reasonable cost and effort


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In recent years, a large number of different performance indicators have been devised
and used in transport organisations throughout the world. Typically the indicators
address certain key issues that are important to transport profession in general or to a
given situation or a particular goal. Most commonly used indicators can be
categorised into a smaller number of generalized groups as shown below (please note
that the groups below are often defined differently in different contexts):
    • Accessibility, which refers to geographical coverage of the transport network
        enabling us to reach our destinations
    • Mobility that represents the relative ease or difficulty with which trips are
        made in the transport system. Typically, congestion or other delays impede the
        mobility of transport system users, who nonetheless may enjoy excellent
        accessibility. Mobility is measured e.g. in travel speeds, travel times and
        delays.
    • Economic development is the fundamental objective of the transport system
        development. However, economic development is mostly difficult to discern
        and measure based on typical project data. Invariably a specific study is
        needed.
    • Environmental protection and resource conservation are increasingly
        important considerations of transport system use and development. Indicators
        of environmental and resource conservation can be given in a numerous ways,
        such as in terms of resources saved (e.g. fuel conserved) or the environment
        damaged (pollution emitted or land taken).
    • Safety is an indicator that always has great importance in the development of
        transport systems and operations.
    • Security deals with unauthorised transport of dangerous goods (e.g.
        smuggling) and limitations of access to restricted areas. Security is the key
        consideration at borders and increasingly in terminals.
    • System quality has to do with the physical condition of transport infrastructure
        (such as pavement roughness and possible weight limits on bridges) and
        equipment. Deterioration of the system quality is the main cause of revolving
        and capital maintenance measures and programs.

When recalling the intention of the High Level Group to promote international trade
flows across the borders and on existing links, it becomes quite clear that the main
performance indicator of the ASF will be the mobility with its several indicators.
Improvement of mobility is the driver of any axis development, while we must also
ensure that the environment and safety are not compromised in the process.

Of the other common performance indicators we can say that accessibility may not
feature high on the performance of the axes. This is due to the fact that the road and
railway links of the axes have already been selected and by doing so the system
accessibility is fixed to a high degree. Only if we at some time ask the question
whether our axis comprises the “best” set of links and nodes, there is a need to include
accessibility in the performance indicators.

System quality is an important objective impacting e.g. resources of maintenance. In
the case of axes, maintenance of current infrastructure can be considered

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fundamentally a national and local responsibility, not a priority of any international
cooperation. However, there may arise cases that this assumption must be revisited.
Examples are excessively poor roads and railways and weak bridges, which may slow
down, reduce loads, lengthen travel distance due to detours, or prevent entirely some
types of international shipments.

Security has become an important consideration of international trade. However, it is
recommended that security is not included among the performance indicators for the
time being due to the fact that today security can only be assessed using expert
evaluations of selected sites.

Economic development is one of the main objectives of the High Level Group. Later
in this chapter it is shown that the proposed indicators can be used to estimate also
these impacts. Therefore, no specific economic development indicator is proposed.

Based on the above discussion the performance indicators that seem to suit best for
the axis analyses and monitoring are the following:
    • Mobility
           − Travel time (speed) measured in hours (or km/h) on road and rail links.
               Alternatively also travel delay in hours can be used to describe the
               link. Delay is obtained by comparing the link travel time against some
               desired travel time, such as that of the free flow speed.
           − Delay measured in hours at node points (e.g. borders and terminals)
           − Travel time reliability measured in buffer time (hours) needed for an
               end-to-end journey. The concept of travel time reliability (buffer time)
               is shown in Figure 8.1.
    • Traffic safety
    • Environmental protection




Figure 8.1 Concept of travel time reliability (buffer time) Source: US Federal Highway Administration



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Often the level of travel cost is also considered as a measure of performance. Travel
cost is, however, a rather difficult indicator in practice. It should be noted first that the
societal part of travel costs can be derived from travel time and delay information to a
considerable degree. On the other hand, the true operation costs and their changes for
commercial road hauliers and railway companies are difficult to obtain, because they
are considered proprietary information. In addition, there are considerable cost
components that specifically are designed to alter transport patterns (e,g. fuel and
vehicle taxes) which also play a role in the choices of transport modes and routes.
International cross-border operations complicate the matters even further. Thus, when
it comes to the axis analyses it can be concluded that (i) the travel cost is a difficult
issue and (ii) much of data will not be available or monitorable over time. For these
practical reasons travel cost is not recommended among the performance indicators of
the axes for now.

8.1.3   Why are the proposed indicators relevant?
There are many advantages if the analysis and monitoring of axis development can be
performed reasonable directly in terms of travel time, delays and reliability of
journeys along the axis. When we consider also travel cost components including
safety, they all represent transaction costs of international trade that accrue to a
country, region or a business from trips across the borders. Economic theory tells that
savings in transaction costs with regard transport, among others, improve:
    • economic competitiveness
    • business productivity
    • market area
    • access to labour and other business inputs

If the conditions of international trade flows and business travel can be improved in
terms of the above mentioned performance indicators, the result will be economic
development in the countries, regions and businesses concerned. In addition, quality of
life of the general public improves. Needless to say that these outcomes link directly
with the fundamental objectives of the axis development as defined by the High Level
Group.

Today, there exist also econometric models, which allow quantification of macro-
economic benefits based on the observed or predicted changes in these specific
performance indicators. It should be added here that, if we accomplish to do this, no
specific economic development indicators are needed in the analysis.

8.1.4   Evaluation of projects
The proposed time-based performance indicators allow us to analyse and compare
different types of constraints, ”soft” and ”hard” measures (projects), and prioritise
among them using the same yardstick.

Using the delays in travel time on a link it is possible to develop comparisons and
rankings among improvement projects, such as:
   • ton-hours saved for international freight flows by the project


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     •    euro-hours saved for international trade by the project
     •    ton-hours saved per euro spent in the project
     •    euro-hours saved per euro spent in the project


It must be noted that these changes in travel times and costs can be used as direct
inputs to transport models and obtain estimates of traffic rerouting effects due to any
project or program implementation.

8.1.5     Regulatory and legacy constraints of performance
There are some transport system characteristics that cannot be readily described in
terms of performance indicators. Nevertheless, they are important and influence
greatly how people travel and goods are being transported across the borders. They
mainly consist of the horizontal issues that the High Level Group has identified in its
report. Following considerations can be included in the axes analysis:

•    Regulatory and legacy constraints to transport that are due to different
     development histories of national transport systems. At the moment, they persist
     due to inadequate and often slow harmonisation processes. They typically consist
     of different vehicle standards (e.g. weights, widths and lengths), which probably
     will be eliminated over time. There are also more fundamental physical
     characteristics of the transport system, such as railway gauge widths, which can be
     standardised only with great difficulty and cost, if at all.

•    Administrative and institutional restrictions of transport manifest themselves
     typically at border crossings in the form of differing requirements for
     documentation, or the number of authorities present and their responsibilities at
     the border.

The analysis must take account of the regulatory and legacy indicators as well.
However, using the logic presented here, the constraints that do not cause any delays
or specific cost to transport can be ignored – they are not relevant from the strict
analysis point of view.

8.1.6     Problems with the application of performance indicators
Even if the above-described approach seems quite simple and straightforward, its
immediate application faces a single but considerable problem. That is that the TEN-T
database is not particularly useful in finding values for the proposed performance
indicators. The biggest lacks of data concern time delays on railway links and
junctions, particularly those that the freight trains are exposed to.

In the following sections of this chapter the above-described principles of analyses can
be applied nearly fully only for the road borders, where there are the right kind of
information available. Also on road links delays can be estimated using the available
speed-flow models. The results are, however, less accurate than for the road borders
where direct observations can be used.


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The available information is the worst with the railways, where the above kind of
analyses cannot be performed due to complete lack of data and models, which would
provide time-measures for railway operations on links and at nodes. However, an
evaluation method can be developed also for the railways, which prioritise investments
with regard the likelihood of congestion.

Lastly, it should be pointed out that there are currently methods under development,
which allow us to monitor the time-based indicators relatively easily and at a
reasonable cost over time.

8.2   Analysis process
As presented in previous chapters, the analysis phase of the ASF brings together
various physical data of the system, traffic forecasts, planned projects, and regulatory
information. The analysis phase is meant to synthesise these data and make portrayals
of the system condition, and present these data and analysis results in a meaningful
way. The phase is particularly designed for identification of bottlenecks and provision
of information for evaluations and priority settings among potential improvement
projects.

The steps that are employed in the analysis process are as follows:

Step 1a, Collection of basic regulatory data
Regulatory data can be national, regional or specific to some road or railway section
such as axle weight restrictions. Collected regulatory data must have relevance to the
performance of the transport system.

Step 1b, Collection of basic infrastructure data
Transport system data consists of physical infrastructure and operational information
of the roads, railways and border crossings belonging to the Northern Axis. Ideally
these data, including the no-EU countries, should be collected and maintained in axis-
specific datasets.

Step 2, Traffic and traffic forecast data
Traffic data and forecasts must also be included in the axis-specific datasets. The
traffic dataset contains the following traffic data of the axes links and nodes:
    • Current traffic on roads, railways and borders obtained from national
         authorities (domestic traffic)
    • International passenger and freight traffic based on separate studies
    • Forecasts of domestic traffic flows, obtained from national authorities
    • Forecasts of international passenger and freight flows (2010 and 2020) based
         on specific studies

Step 3, Analysis phase
In the analysis phase all the collected data and information will be used representing
either current situation (infrastructure and traffic) and relevant future points in time,
such as 2010 and 2020. The analysis consists of several separate analyses:



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               a. Operational incompatibility. Identification and analyses of differing
               regulatory practices, typically at and across the borders showing lack of
               interoperability.
               b. Capacity. Identify links and nodes where capacity will be exceeded.
               c. System performance. Evaluating the system performance using
               selected performance indicators. Delays and loss of time over links and
               at node points is used as the main indicator.
               d. Safety. Only the road safety is evaluated in the study.
               e. Environment. The affected Natura areas and built-up areas along the
               road are used as the primary measures of environmental impacts.

Step 4, Reporting
Reporting presents synthesised information of the overall axis system. Such
information includes characteristics of the current transport system, existing or
emerging bottlenecks due to traffic growth, and regulatory environments and their
changes.

8.3     Road system

8.3.1    Performance indicators
In previous chapters it has been proposed that the performance indicators used in the
analysis phase are selected from these categories:
    • regulatory and legacy restrictions
    • mobility (travel time, delay and travel time reliability)
    • road safety
    • environmental protection

It was also mentioned that, due to lack of data, any full-fledged performance analysis
is not possible. However, a practical method for evaluating the Northern Axis
transport operations and infrastructure is possible to make, which emulates the more
ideal performance based approach.

The above performance indicators must be modified slightly for the roads so that they
can be used with the available information. The are:
       • Bearing capacity of roads
       • Vehicle dimensions
       • HGV travel speed on a road link (km/h)
       • Reliability of travel (can be estimated with some assumptions)
       • Road safety
       • Environment

8.3.2    Classification of performance indicators
The basic rationale for analysing the Northern Axis roads is that the all the roads of
the system should be able to carry, at a reasonable speed, heavy commercial vehicles
(HGV) that are within the EU standardised dimensions and weights.



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The operational requirements are as follows:
      • Bearing capacity of roads should allow:
          − maximum axle weight – 11.5 tons
          − maximum vehicle weight – 44 tons

        •   Vehicle dimensions should allow HGVs the following:
            − Length – 18,75 m
            − Height – 4,00 m
            − Width – 2,55 m

The most common speed limit for HGVs in Europe is 80 km/h. Thus, it is assumed
that the desired HGV speed limit is 80 km/h or greater in the entire system.
Converting this into travel speed, it will be approximately 75 km/h over a given
(rural) link. It should be noted that the end-to-end travel speed is much less, as it also
includes several other factors, most notably stops for rest and vehicle maintenance. 75
km/h is used as a threshold value for road links in the following analyses.

Operational requirements for HGV speeds:
      • Good link:           - travel speed for HGVs 75 km/h or higher
      • Insufficient link: - travel speed for HGVs 50 - 75 km/h
      • Congested link:       - speed limit for HGVs less than 50 km/h

Reliability of travel:
       • Reliability of travel is to be assessed mechanically by assuming a 100%
           surplus to congestion-related, recurring delay. The surplus is meant to
           account for non-recurring delays such as accidents, vehicle breakdowns,
           weather conditions, work zones and other similar unpredictable events. The
           100% surplus is a rough estimate, which is adopted so that this important
           factor is not forgotten. The assumption is supported by recent studies in the
           USA.

Road safety:
      • Road safety of international traffic will be assessed based on expert
          judgement. The criteria will be whether the level of accidents is at par or
          not with the EU averages on similar roads.

Environment:
      • Expert assessment concerning possible impacts on the Natura areas.
      • Data about the length of urbanised area along the road link has also been
         collected. This information can be used as a rough measure to identify
         sections with moderate or high impact on population.

8.3.3   Road system performance
Operational incompatibility

Chapter 4 presents the regulations for heavy goods vehicles by country (see Table
4.6). The main deficiencies concern Russia and Belarus where the axle weights (10 t),

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but more importantly the total vehicle weight (38 t), fall short of the current EU
requirements.

Similar vehicle weight restrictions may still prevail also in Estonia, Latvia, Lithuania
and Poland to some degree. However, these countries are well on their way of
upgrading their roads for heavier vehicles. In Russia a similar progress is slower and
present a prolonged constraint to certain vehicles and shipment types.

Table 4.6 reveal also other minor discrepancies with regard vehicle dimensions. They
cannot, however, be considered major obstacles to commercial transport across the
borders.

Capacity

Even if the road capacity is not a primary measure of performance in the analysis, it is
always of interest to an analyst. Therefore, road capacity is dealt with here to some
length. The sections, where the road capacity has been or will be exceeded in the
planning period, are shown in Table 8.1. Criteria for capacity are the volume/capacity
(v/c) rates. Capacity is exceeded when v/c is 1,0 or greater.

By and large, the capacity of the Northern Axis roads seems to be quite adequate into
the year 2020. In general, the calculated shortage of capacity can be found on the
approach roads of a few major cities: Moscow, St. Petersburg, Riga and Oslo. There
are also a few sections where capacity is exceeded in and around some medium size
towns: Vyborg (Russia) and Jekabpils (Latvia). Their specific problem is that they
both have a considerable through traffic of HGVs between the EU and Russia.




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Table 8.1 Capacity constraints
                                                  TRAFFIC         DATA         AND
                                                  FORECAST
Section     Start       End node Length                                   of which       V/C
ID          node                 km                                       %     of
                                                  year        AADT        HGV

BRANCH 2                RUSSIA
  9h            City of Vyborg           11         2002        13 789        64           1,17
                                         11         2010        15 000        48           1,15
                                         11         2020        18 000        36           1,26
    9e       Southern access to          31         2002        10 857        67           0,94
               St. Petersburg            31         2010        13 500        54           1,08
                                         31         2020        15 000        42           1,10
    9a         NW approach to            21         2002        91 755        31           1,54
                 Moscow                  21         2010        98 500        26           1,58
                                         21         2020       105 000        22           1,63
BRANCH 4          LATVIA
  A95   Western approach to              15            2005      33145         9           0,46
               Riga                     15             2025      87389         9           1,20
   I    Eastern approach to              9             2005      11380        24           0,72
               Riga                      9             2025      27605        29           1,82
   AS4         City of Jekabpils        109            2005      10230        18           0,61
                                        109            2025      19086        29           1,26
BRANCH 7        RUSSIA
  2a     SW approach to                  21            2002      81953        22           1,27
            Moscow                       21            2010      84000        18           1,26
                                         21            2020      86500        16           1,27
BRANCH 8         NORWAY
  2-6   NE approach to Oslo               6            2005      12600        14           0,73
                                          6            2010      14607        14           0,84
                                          6            2020      19631        14           1,13
   2-8      NE approach to Oslo          8,6           2005      19000        10           1,05
                                         8,6           2010      22027        10           1,22
                                         8,6           2020      29602        10           1,64
   2-9              Near Oslo            8,9           2005      29000        10           1,61
                                         8,9           2010      33620        10           1,87
                                         8,9           2020      45182        10           2,51
BRANCH 9         NORWAY
  1-8   SE approach to Oslo          18          2005     49000      10          0,68
                                     18          2010     56806      10          0,79
                                     18          2020     76342      10          1,06
Notes: Traffic forecast are based on national estimates (shown in black). Red figures
are estimated in the study based on 3% annual growth.




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Loss of time

In Appendix 2: Basic Road and Rail Parameter and Performance Data the loss of time
(or delay) by road link is presented. The loss is the difference between actual speed
and the desirable speed of 75 km/h. Travel speeds higher than 75 km/h are ignored.
This time loss is called recurring delay and points to a potential bottleneck situation.

In addition, it is assumed that further delays due to accidents, weather conditions,
construction etc. double the congestion related delay. That is called incident-related
loss of time. Indicator for the total time loss is then the sum of recurring and incident-
related delays.




Figure 8.2 Current Road Bottlenecks


Figure 8.2 shows the compilation of the road sections, which experience some delay
due to reduced speeds during congestion period (for details see Appendix 2: Basic
Road and Rail Parameter and Performance Data). These sections represent about 10%
of the total system length. As the used link lengths are quite long, the congested share
is probably an overestimation.

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The total time loss per a road link is typically quite short, less than 10 min. Only in
three sections the total delay currently is 20 min or more. They both are on the
approaches to Moscow (branches 2 and 7). Significant delays are experienced also in
the City of Narva (EE), where heavy HVG traffic mixes with urban traffic.

At around 2020, new delays will appear also in some additional locations, namely on
one approach to Oslo (branch 8), and in a few locations on branch 4 in Latvia, on
approaches to Ventspils and City of Jekabpils. This is the case, if no road
improvement measures are taken by then.

It should be pointed out, however, there are differences how far into the urban
road/street network the Axis links reach. In some cities they stop at the end of
motorways, while in others they extend into the street-like environment. Therefore,
the congestion situations near urban centres cannot be compared well without more
detailed knowledge of the nature of the network.

Road Safety

Road accident data of the Northern Axis has been collected from each country, even if
these data were not available for all road links and countries. The data is shown in
Table 8.2.

Table 8.2 The Axis road safety data by country (recorded accidents per 100 million vehicle-km
per year)
Country                  Min            Max
Norway                    1               35
Sweden                    12              21
Finland                    4              22
Russia                    7               92
Estonia                    9              69
Latvia                   N.A.            N.A.
Lithuania                N.A.            N.A.
Belarus                  N.A.            N.A.
Poland                   N.A.            N.A.
Germany                  N.A.            N.A.

Only very general conclusions can be drawn from the accident data, because the
different accident recording practices of the Axis countries are probably reflected in
the figures. More importantly, road accidents tend to concentrate in certain locations,
“black spots”, and they cannot be identified using only the available road link-based
data. The TEN-T road links are long, often tens of kilometres, which hide effectively
the potential high-risk sites.

It can, however, be said that in the Nordic countries accident rates on two-lane roads
are typically well below 20 accidents/100 million vehicle-km. Only few sites exceed
that rate. On the other hand, in Russia several road stretches exceed 20 accidents/100
million vehicle-km, in many cases by a wide margin. Also Estonia has a high-risk



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road link, but also a section of 4-lane motorway with low accident rate. No relevant
data were obtained from the other Axis countries.

Accident rates of each road link are shown in tables of Appendix 2.

8.4     Railway system

8.4.1    Performance indicators
In principle, also the railway performance should be measured by the speed and/or
delay of trains on the axis railways. However, the speed/delay indicator is not nearly
so straightforward and handy as it is in road transport, because the causes of railway
speed and delay are much more complex. Furthermore, railway traffic is highly
controlled, often by schedules, ensuring rather steady line speeds. Instead, end-to-end
travel speeds can be quite different from line speeds. Travel speeds over a chain of
railway links and nodes are strongly influenced by the operational capacity of
intermediate node points, terminals and railway junctions. They invariably reduce
overall travel speeds, typically with a considerable amount. Freight trains can
experience delays also on links due to stops for passing or overtaking passenger
trains, which have given priority. A good example of these factors is shown in the box
below.

 A direct container train between Kouvola (Finland) and Moscow
 There is a considerable flow of containers from Finland to Russia, which nowadays all
 are practically shipped by trucks. In spring 2007, the Russian Railways and the Finnish
 Railways established a joint stock company TransContainer Scandinavia for this
 container business. In April, a container train made a pilot run between Kouvola (a
 railway hub in Finland) and Moscow. The total trip took 34 hours including building the
 train in Kouvola. (As travel distance is 850 km, the average travel speed is 25 km/h even
 if the allowable line speeds are as high as 200 km/h)

 A shipment of a single container by an ordinary freight train between the same
 destinations is reported to take 5-6 days.

 Source: Delevoi Peterburg 17.4.2007, Kommersant 18.4.2007


Railway line speeds for freight trains are often inconsequential. They are also very
difficult to observe and are not well recorded. More often than not, these kinds of
data, if they exist, are proprietary information. Also for this study no travel time
information has been available and there is no reasonable way of estimating it either.
Therefore, it is proposed that train travel speed is left out of the analysis for the time
being. Freight train speed is recorded only as the maximum allowable line speed on a
given railway section. As such, it represents the general physical quality of the given
railway section. Potential for congestion and delay can be observed and monitored in
the axis analysis only descriptively through the use of the capacity utilisation concept.

In recent years, cross-border requirements for railway infrastructure and operations
arise from the need of harmonising railway transport across the EU. The European
Railway Agency has put a lot of effort to harmonising railway transport on the all-


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European level. One of the ERA’s main achievements is recommendation to the
railway administrators to adopt the European Railway Traffic management System,
ERTMS. Additional work has been carried out in elaborating and
adopting Technical Specifications for Interoperability (TSI) covering six subsystems
of the trans-European high-speed rail system (maintenance, control and command,
infrastructure, energy, rolling stock and operation) and five subsystems of the
conventional trans-European rail system (rolling stock – noise, telematic applications
for freight, control-command and signalling, rolling stock - freight wagons and traffic
operation and management). In the near future, the third group of TSI for
conventional rail (infrastructure, traction units and locomotives, energy, passenger
carriages and telematic applications for passenger services) will be drafted by the
European Railway Agency.

Significant preparatory work towards railway harmonising has also been carried out in
other quarters, which includes the recent study “European Rail Infrastructure
Masterplan (ERIM, 2006) by the UIC proposing harmonisation parameters for the
international railways within the EU. The threshold values used here are derived
mostly from the ERIM study.

Based on the general performance requirements, described above, it is proposed to use
the following performance indicators for railways:
        • Level of operational and technical harmonisation (current legacy
           restrictions)
        • Line speed of freight trains on a rail link (km/h)
        • Capacity utilisation of a rail link

8.4.2   Classification of performance indicators
Level of harmonisation of operational requirements (trains) with regard of:
       • Train weight, maximum – 3 000 tons
       • Train length, allowable – 750 m

Level of harmonisation of technical requirements (tracks) with regard of:
       • Load gauge – GC
       • Axle load, maximum – 25 tons
       • Signalling system – ERTMS (European Railway Traffic Management
           System)

Two more issues are still remaining: railway gauge and type of power supply for
electrification, which are much more difficult to harmonise and are not normally done
so. Typically these differences are bridged with special measures such as provision of
reloading facilities, changeable axles and dual-powered locomotives.

Line speed on a link (freight trains):
   • Insufficient link – line speed is less than 100 km/h
   • Normal link – line speed is 100 km/h or higher




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Basic railway capacity:
In this study the capacities that have been received from the national railway
authorities are used as the basis for estimating the railway performance.

In the absence of line-specific capacity information, selected default values can be
used. The basic Western European railway capacities have been presented in the UIC
study, European Rail Infrastructure Master Plan (ERIM). Others are those that have
been recommended by the UN/ECE.

The ERIM default values for theoretical railway capacities:
                    Single track Double track
Below average line <74              <270        trains per day, total in both directions
Above average line 74-150           270-400
Excellent line      >150            >400

The above theoretical capacities are different from practical capacities. Theoretical
values must be used with the rates of capacity utilisation on a link:
    • Good –         <70% of theoretical capacity (Free flow)
    • Normal –       70%-85% (Normal flow which can be susceptible to delay)
    • Capacity –     85%-100% (Approaching capacity with regular delay in peak
       periods)
    • Congested – >100% (long and difficult to predict delays during an average
       day)

The UN/ECE values for practical capacity are:
Single track       60-80 trains/day
Double track       100-200 trains/day

8.4.3   Railway system performance
Operational and technical incompatibility

The railway regulations and their differences have already been discussed in Chapter
4 Analysis of infrastructure along the Northern Axis – Infrastructure. Table 4.16 shows
the differences between the countries with regard operational requirements for trains
and technical requirements for tracks.

There exist principally two types of performance indicators when it comes to
harmonisation:
   (1) convention-based standards, such as track gauge, where the main issue is
       harmonisation. No axle gauge is better than another.
   (2) capacity-related standards, such as axle weight, where the objective is to provide
       certain minimum level, carrying capacity, for a track . Higher levels are always
       better.




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Convention-based standards:
   • The main incompatibility by far is the track gauge between the European
      (1435mm) and Russian (1520mm) gauges, which is almost impossible to
      overcome in large scale due to the huge extent of the existing networks.
   • Signalling system, where the standard is ERTMS. However, none of the railways
      of the Northern axis is applying ERTMS fully.
   • Traction power, where both electric and diesel locomotives are common. At the
      interfaces, typically international borders, locomotive change is necessary if the
      traction system changes. In addition, there are different electrical power systems
      in use, but they are not always major problems, as the locomotive must be
      changed due to track gauge differences anyhow. Alternatively, the problem can
      to be solved with dual powered locomotives.

Capacity-related standards:
   • The ERIM proposes 25-ton axle weights for the European railways. Only
       Sweden and Estonia meet currently this standard fully. There are also some
       railways of high bearing capacity in Norway and Finland.
   • Maximum trainload is related to axle weight. The ERIM recommendation is
       3 000 tons. This requirement is mostly met excepting Finland and Germany
       and some railways in Russia. Some railways in Sweden and Russia can carry
       double or even higher loads, but they are designated for specific hauls, mainly
       iron ore, and not for general cargo.
   • Railways should allow train lengths up to 750 m. This requirement is largely
       met.
   • Loading gauge specifies the height and width of loads (wagons). The ERIM
       recommendation is GC. However, practically all countries have their own
       historical systems, but by and large they are close or meet the ERIM
       requirement.

Line speeds

Line speeds on the Northern Axis railway network are generally good. The dominant
allowable speed range is 100-120 km/h. Almost half of the railway length belongs to
this group. About 18% (1 300 km) of the network has less than a 100 km/h speed
limit. Those links are listed in Table 8.3.




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Table 8.3 Rail links with speed limits of less than a 100 km/h
RAILPARAMETER                                                               Max
Section Start node       End node                                   Length speed
ID
                                                                    km         km/h
BRANCH 1        NORWAY
                Swedish Border
   3  Narvik    Bjørnfjell/(Vassijaure)                               38,2      50
BRANCH 1        SWEDEN
  30  Boden     Haparanda                                             160       70
BRANCH 1        RUSSIA
 8.1  Kivijarvi Ledmozero                                             123       80
 8.2  Ledmozero Kochkoma                                              127       80
BRANCH 3        ESTONIA
      Kopli     Lagedi                                                 15       70
      Lagedi    Tapa                                                   63       90
      Tapa      Narva                                                 132       90
BRANCH 4        LATVIA
   1  VENTSPILS TUKUMS                                                108       80
   2  TUKUMS    JELGAVA                                                56       80
   3  JELGAVA   KRUSTPILS                                             138       80
  18  TUKUMS    RIGA                                                   33       80
   6  RIGA      KRUSTPILS                                             129       80
   7  KRUSTPILS REZEKNE                                                95       80
   8  REZEKNE   ZILUPE-State border                                   59        80

Line capacities

The line capacity on railways depends on several factors that are not recorded in the
Axis database. Therefore, the capacities given by each railway have been used in the
analysis. In some cases, it has only been possible to estimate the capacities based on
other available information. For some lines no capacity information has been
available, nor has it been possible to estimate them either. Then, the default values
recommended by the UN/ECE have been adopted, as they appear to be the most
appropriate for the Northern Axis railways.

The difficult question of line capacity is highlighted in Table 8.4, which shows the
distribution of existing railway capacities in the Northern Axis links. Table shows
separately the capacities for old and new EU member states, as well as for Russia and
Belarus. This is necessary because the “standard” capacities in these three groups
seem to differ. Particularly in Russia there are remote or outdated railways that have
quite low capacities, apparently due to long blocks and infrequent passing sites. In
addition, train control systems seem not to allow high capacities even on some double
track sections to the extent that is possible in the EU member states. Just to make it
clear, however, despite of low train frequencies the Russian railways can carry
nevertheless high freight flows, mostly raw materials, due to high trainloads.




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It is somewhat remarkable that the UN/ECE capacity values for single track (60-80
trains/day) are met only by less than 10% of the system. They are all in Norway. The
dominant capacity of single track sections in new member states is 40-60 trains/day
and in Russia/Belarus 20-40 trains/day.

Table 8.4 Summary table of line capacities
        SUMMARY TABLE OF LINE CAPACITIES (Lengths in km)
           Trains/day Old EU New EU   RU/BY Total
          <20                             250      250 14,6 %
          20-40                    59     948    1007 58,7 %
          40-60            149    227              376 21,9 %
 1- track 60-80            114                     114   6,6 %
          80-100                                     0   0,0 %
          100-120                                    0   0,0 %
          Total          262,8    286   1198 1746,8

            <40                                302        151       453      12,1 %
            40-60                                                     0       0,0 %
            60-80                              177        160       337       9,0 %
            80-100                                                    0       0,0 %
 2-track    100-120              85,2        537,5      1386     2008,7      53,6 %
            120-140                             63       698        761      20,3 %
            140-160                                      109        109       2,9 %
            >160               280,2                              280,2       7,5 %
            Total              365,4       1079,5       2504     3948,9

For double tracks the dominant capacities fall in the range of 100-140 trains/day, even
if there are a group of tracks that have considerable lower capacities. In Norway,
Finland, Germany and Poland capacities above 200 trains/day can be reached, which
meet also the ERIM requirements well.

Capacity constraints

The railway constraint indicators adopted in this study are descriptive but aim still to
measure the susceptibility to delays. They are based on chapter 8.4.2 Classification of
performance indicators for capacity utilisation on a link:
    • Good line with free flow and with no or rare delay. Capacity utilisation is less
       than 70%
    • Normal flow, which is to some degree susceptible to delay, particularly during
       unexpected events such as inclement weather and system breakdowns.
       Capacity utilisation is 70%-85%
    • Capacity is reached at 85%-100% of utilisation rate. This means frequent
       delays in peak periods due congestion and unexpected events.
    • Congested – >100%. Long and difficult to predict delays during an average
       day, particularly for traffic without priority.



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Figure 8.3 presents the railway links that show some capacity constraint either now or
in the future years without any improvement measures. The links that are indicated
cover about 45% of the total system length.




Figure 8.3 Current Railway Bottlenecks


Some observations about capacities and bottlenecks by branch of the Northern Axis:

Branch 1, Narvik-St.Petersburg
• The Norwegian section of the ore line is nearing its capacity and can currently
   take new traffic only limitedly.
• The section in Russia from the Finnish border to St. Petersburg-Murmansk line is
   practically a missing link. It has currently very low capacity, because the
   construction of this new railway has not yet been completed. However, there is
   some ore traffic on the line (This line is not shown on Table 8.6)
• The St. Petersburg-Murmansk line has severe capacity problems over a 300 km
   section to the north of Petrozavodsk. This is due to low line capacity. High
   capacity utilization rates are expected also near St. Petersburg in 2010 and
   onward.

Branch 2, Helsinki-Moscow
• The existing capacity constraints are located in the approaches of Moscow. The
   future constraints are avoided by diverting freight trains to parallel railways in

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   sections: Vyborg-St. Petersburg and St. Petersburg-Moscow. In the future, only
   passenger and fast container trains are allowed to use this high-speed railway.
• In Finland, the capacity of the 1-track section to the Russian border is reaching its
   capacity by 2025.
Branch 3, Tallinn-St. Petersburg
• On the Estonian side, capacity utilization is expected to grow modestly. However,
   in Russia, traffic to Estonia is expected to drop down leaving ample capacity on
   the railway. Instead, freight transport to the new Russian Port of Ust-Luga is
   predicted to grow so much that the rail capacity from St. Petersburg to the Ust-
   Luga port (Veimarn station) will be exceeded very quickly, by 2010.

Branch 4, Ventspils-Riga-Moscow
• In Latvia, there is a growing lack of capacity in the section east of Riga, which has
   relatively heavy commuter traffic.
• As with Estonia, the Russians predict freight traffic to go down between Russia
   and Latvia, which leaves free capacity on the existing track in the years until
   2010. However, traffic between Moscow and the Ust-Luga Port impacts also this
   railway. Its capacity will be used fully in the section Moscow-Velikie Luki by
   2020. Already now there is a growing lack of the railway capacity in the single-
   track section near Moscow. The current capacity of the line in Russia is low.

Branch 5, Klaipeda-Vilnius-Minsk
• Capacity of the about 80 km section to the west of Minsk is nearly congested
   because of quite high commuter train traffic. The line carries also heavy freight
   traffic from Russia to Lithuania.

Branch 6, Kaliningrad-Kaunas
• The entire 150 km railway in Kaliningrad has capacity problems due to the low
   basic capacity. Quite quickly (2010-2020) the current capacity will be exceeded.

Branch 7, Berlin-Warsaw-Minsk-Moscow
• In Germany, the current railway from Berlin to the Polish border runs today at
   capacity.
• In Belarus, the over 200 km section east of Minsk is approaching its capacity due
   to heavy passenger train and freight train traffic.

Branches 8and 9, Oslo-Stockholm and Oslo-Copenhagen
• The approaches to Oslo have very high capacities and are running under good
   conditions. The only problem is a 40 km section near Oslo on Branch 8 (Oslo-
   Stockholm), which has 2 tracks and is reaching its capacity already today.

8.5     Border crossings (road and rail)

8.5.1    Performance indicators
The practical performance of road and rail border crossings could be described in
terms of capacity and its rate of utilisation, and the time it takes to process each
vehicle. However, these kinds of data are not directly available. In fact, the

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performance of borders seems to be uneven over time and it has been quite difficult
even to determine it reliably, not to speak about monitoring it on the permanent basis.

Over the years, however, there have been off-and-on monitoring efforts set up, e.g. by
the IRU at several of the EU’s external road borders and by the Finnish Road
Administration at the Finnish borders with Russia. These data have been proved very
valuable and makes it possible to evaluate the Axis road borders quite well after all.
Using these data it has been possible to calculate the mean waiting times (delays) and
their variance (buffer index) for each road border very much like the above described
theory calls for.

Because the border delays can vary a lot during a relatively short time like a month or
a year, the study adopts very general and robust indicators for road borders as follows:

1. Border delay. Over the years, in several seminars and reports the experts have
   claimed that waiting time at the borders around the Baltic Sea should be reduced
   to two hours in the maximum. Based on that more or less general goal the border
   delay indicator can be expressed as:
       a. Good border - Delay less than 2 hours
       b. Delayed border – Delay more than 2 hours, up to 12 hours
       c. Poor or congested border – Delay generally more than 12 hours

2. Incompatibility at border. This concerns mainly the railway borders, such as
   where some technical incompatibility prevents a train crossing the border. A
   typical case is a gauge difference at border. For roads, a similar issue might be
   vehicle and axle weight limits, which may prevent certain vehicles from crossing
   the border.

8.5.2   Performance of road borders
In this study the internal borders of the EU will not be considered, because they meet
easily or at least are on the way of meeting the above-mentioned performance
requirements. Any further analysis of them would require the development of more
refined indicators. The same is true for the EU borders with Norway as well.
Therefore, the considered borders consist only of those located on the EU external
border with Russia and Belarus. There are seven such borders, as shown in Figure 8.4
and Table 8.5.




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Figure 8.4 Road Borders


Table 8.5 Delays at road borders
Branch         From          To border        HVG        Delay (hours)      Buffer Incompa- Notes
              border          station         ADT                           index tibilities
              station                         2006      Median       95 %
                                                                                      HGV and
    1      Vartius (FI)     Lytta (RU)          73          <2        <2     n.a.   axle weights
                            Torfjanovka                                               HGV and
    2      Vaalimaa (FI)    (RU)               1200         19        38     2,0    axle weights    Source 1
                                                                                     (HGV and
    3      Narva (EE)       Ivangorod (RU)      255         50       100     2,0    axle weights)   Source 2
                                                                                     (HGV and
    4      Terehovo (LV)    Burachki (RU)       380         8         18     2,3    axle weights)   Source 3
           Medininkai       Kamenny Log                                              (HGV and
    5      (LT)             (BY)                693         2         4      2,0    axle weights)   Source 3
                            Chernyshevsko                                            (HGV and
    6      Kybartai (LT)    e (RU)              238         9         19     2,1    axle weights)   Source 2
                                                                                     (HGV and
   7       Kukuryki (PL)  Brest (BY)          n.a.          2         21     10,5   axle weights)   Source 4
Source 1: Finnish Road Administration December 2006-
June 007
Source 2: International Road Transport Union IRU April-August 2007
Source 3: International Road Transport Union IRU May 2007
Source 4: International Road Transport IRU Union May-June2007




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  Explanation of Delay Definitions in Table 8.5

  Median delay is defined so that half the trips faces less waiting time than indicated and another
  half faces more.

  95% delay is defined as the waiting time that is exceeded only by 5% of trips. At probability of
  95%, one trip out of twenty will be delayed more than the value shown; in other words one daily
  trip in an average month assuming 20 working days.

  Buffer index is (95% delay) / (Median delay) and it indicates how much more additional time one
  must reserve for the trip in order to reach destination with 95% certainty. At the road borders the
  index seems to be 2.0 even if very disparate sets of data have been used.


Based on the available field data from spring and summer of year 2007, the Northern
Axis road borders fall into three distinct categories as follows:

1. Very poorly operating and/or congested borders with high delays:
    • Narva (EE) – Ivangorod (RU) has been extremely slow during summer 2007
       even if HGV volumes have not been excessively high.
    • Vaalimaa (FI) – Torjanovka (RU) has been very congested through 2007 due
       to very heavy HGV flows into Russia. This border has by far the highest HGV
       flows of all the Axis borders.

2. Borders with marked delay:
    • Terehovo (LV) – Burachki (RU) has been congested due to rapidly growing
       HGV traffic. Unfortunately the available data is limited
    • Kybartai (LT) – Chernyshevskoe (Kaliningrad, RU) appears also to experience
       delays, even if the HGV volume is not excessive.

3. Borders with no excessive delays (2 h or less):
    • Vartius (FI) – Lytta (RU) has no problems due to low HGV traffic
    • Medininkai (LT) – Kamenny Log (BY) appears to be without major problems
       even if the HGV volumes are relatively high. Also the predictability of waiting
       times is fairly good.
    • Kukuryki (PL) – Brest (BY) shows high delay variability at border, even if the
       median delay is modest. Unfortunately road delay data is scarce here.

The IRU delay data are mostly reported in the direction from EU to the neighbouring
countries. In the other direction data are very scarce and random. However, based on
the data that have been obtained the entry into the EU takes less time that the exit.

In this chapter above, some incompatibility with HGV regulations between the EU
and the neighbouring countries have been identified. This has at times been an issue at
the Finnish-Russian border, but possibly less so on other borders.

8.5.3   Performance of railway borders
Performance of railway borders could and should be measured in a similar way than
that of road borders. However, evaluation of railway border delays is more difficult

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for the reason that there are not much hard data available for determining the severity
of experienced delays at any given location and over time.

As with road borders the internal rail borders of the EU function quite decently and
need not be considered here any further. This includes also the three Norwegian
borders with Sweden, which present no problems to traffic. The only exception is the
Haparanda (SE) – Tornio (FI) border where the European standard and the wide
Finnish gauge meet. At present, there are no passenger trains at this border.

There are seven railway borders between the EU member states and the eastern
neighbouring countries, Figure 8.5 and Table 8.6. Additionally, the Haparanda/Tornio
border is shown. These borders can be divided into three railway border categories:
• High volume borders (over 15 million tons/yr), which serve Russian exports
    (Narva-Ivangorod) or primarily traffic needs between mainland Russia and
    Kaliningrad (Kena-Gudogay and Kybartai-Nesterov).
• Medium volume borders (over 5 million tons/year) which also serve Russian
    export or trade between Russia and the EU. They are Vainikkala-Buslovskaya,
    Zilupe-Posin and Brest.
• Low volume borders (less than 5 million tons/yr) such as Vartius-Kivijärvi and
    Haparanda-Tornio, which specialise mainly in raw materials such as timber.




Figure 8.5 Railway Borders




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Table 8.6 Railway borders
                                                Volumes 2005
          From border        To border                               Track    Traction
Branch                                                                                    Signalling
             station          station        Passenger Freight       gauge     power

   1     Haparanda        Tornio (FI)                                          change
                                                                    change
         (SE)                                                                               change
   2     Vartius (FI)    Kivijarvi (RU)           0         2,2        no      change       change
                         Buslovskaya
   3     Vainikkala (FI) (RU)                 340000        7,0        no      change       change
   4     Narva (EE)       Ivangorod (RU)      160000        22,8       no        no           no
   5     Zilupe (LV)      Posin (RU)           n.a.         9,1        no        no           no
   6     Kena (LT)        Gudogay (BY)         n.a.         19,2       no      change         no
                          Nesterov
   7     Kybartai (LT)    (RU/Kaliningrad)      n.a.        16,6       no      change         no
   8     Brest (PL)       Brest (BY)            n.a.        6,5     change     change       change

When it comes to performance of railway borders three different cases can be
distinguished:

Borders with fundamental technical incompatibility. They include the two borders
with gauge change between the European standard and Russian wide railway gauges.
They are Haparanda (SE)-Tornio (FI) and Brest (PL-BY) borders, where reloading of
freight and reboarding of passengers will take a considerable time. At Haparanda-
Tornio reloading from one train to another will take 6-8 hours, some times up to 24
hours, to perform.

In addition, locomotive changes are necessary at several borders due to changes in
traction power and signalling systems. Locomotive changes are typically short in
duration.

Freight borders within the Russian gauge standard. There are no technical problems,
but shunting, locomotive changes, border formalities and general waiting between
work phases will take considerable time. At Vartius-Kivijarvi minimums of 4-5 hours
have been reported, while at other borders time delay can be up to 15-20 hours. These
borders include the other six borders than those necessitating the railway gauge
change.

Passenger train borders. As passenger trains run according to timetables and are
given priority, delays at the borders are the shortest, typically much less than 2 hours.
At the busiest borders like Vainikkala-Buslovskaya, border formalities are carried out
in a moving train. At the border, a stop is necessary for locomotive change only.

It can be concluded that all the eight freight borders are bottlenecks to some degree.
Special cases are the two borders with railway gauge difference, which definitely are
bottlenecks. With the available data and information no further conclusions can be
made.




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8.6     Priority projects

8.6.1     Programmed projects
As it has been shown in Chapter 5, “Analysis of infrastructure – Investments and
financial commitments”, the governments have launched major improvement
programs in several important sections of the Northern Axis road and railway
network. Table 8.7 and Figure 8.6 show the main projects that are included in the
current improvement programs.




Figure 8.6 Main road projects until 2020


Table 8.7 Main road projects programmed for completion by 2020 (over €100 million)
                                                                            Cost      Cost
 Branch                   Project                      Type       Country                       Total
                                                                            -2013     -2020

   2      Moscow-St. Petersburg motorway             New const      RU      6 857,1             6 857,1
   7      Motorway A2 (E30), completion of project   New const      PL      1 916,0   1 985,0   3 901,0
   2      St. Petersburg southern bypass             New const      RU       676,2               676,2
          Motorway construction E18 remaining
   2      sections                                   New const      FI       260,0     300,0     560,0
   8      Motorway Oslo-(Stockholm) E18              New constr     NO       170,0     360,0     530,0
   7      Moscow-Minsk road                          upgrade        RU       217,0               217,0
   2      Moscow-St. Petersburg road                 upgrade        RU       149,3               149,3
          Upgrading bridges and intersections
   1      Kemi-Oulu                                  upgrade        FI       143,0               143,0
   3      4-lane road Valgajõe-Rõmeda                New const      EE       130,0               130,0
   5      Development of road Vilnius-Klaipeda       upgrade        LT       113,0               113,0
   1      St. Petersburg - Murmansk road             upgrade        RU       107,6               107,6


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Figure 8.7 Main Railway Projects until 2020


Table 8.8 Main railway projects programmed for completion by 2020 (over €100 million)

                                                                             Cost -    Cost -
 Branch                     Project                       Type     Country                       Total
                                                                             2013      2020

   4      Double-tracking, electrification, signalling   upgrade     LV      1760,0              1760,0
          Modernization of E20 railway from border
   7      to border                                      upgrade     PL      1097,4              1097,4
   7      Railway upgading and speed increase            upgrade     DE        500,0              500,0
          Increasing pass train speeds to 140 and
   7      160 km/h                                       upgrade     BY         17,1    471,4     488,6
   1      Double-tracking the Murmansk line              upgrade     RU        149,7    275,6     425,3
          Moscow-St. Petersburg
   2                                                     upgrade     RU        417,0              417,0
          Increasing pass train speed from 140 to
   7      160 km/h                                       upgrade     RU         15,3    361,9     377,1
          New railway Boden-Haparanda (SE-FI -           New
   1      border)                                        const       SE        305,0              305,0
          Finnish border-St. Petersburg
   2                                                     upgrade     RU        265,0              265,0
          Stations and marshalling yards
   1                                                     upgrade     RU        213,5      44,8    258,3
   2      Upgrading section Lahti-Luumäki                upgrade     FI        150,0      85,0    235,0
          Upgrading Vilnius-Kaunas for speed 160
  5&6     km/h                                           upgrade     LT        207,2              207,2




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Table 8.7 and Table 8.8 indicate that a vast majority of new investments will be carried
out by year 2013. This obviously is an underestimation, because the available investment
information tends to include mainly the “decided” projects. The projects, which are more
long term and possibly contested have not, as a rule, been reported by the Transport
Ministries. Therefore, it is likely that more projects will eventually be launched in the
years after 2013. For the purposes of this study the investments that have been identified
by the national transport authorities are considered more or less certain for
implementation and are not studied any further in the subsequent project analysis and
priority setting. It is further assumed that these projects are completed according to the
given timetables.

8.6.2   Non-programmed road improvement projects
The above listed major road projects (Table 8.7) will address the main infrastructure
bottlenecks that have been identified also in this study until 2020. Several of the projects
are upgrading projects and are not considered to add significant capacity on the existing
road. Invariably much of the project details are not known making it somewhat difficult
to estimate the effects of planned improvements. There are, however, a group of projects
that clearly increases the road capacity in the most constrained locations. They include:
    • Construction of a new motorway between Moscow and St. Petersburg
    • Construction of a ring road around St. Petersburg. In St. Petersburg, additional
        capacity will be available before 2015, when the Western High Speed Diameter
        Road will be opened to traffic.
    • Completing the motorway construction program in Poland by 2020, which
        converts E30 into a motorway through the entire country, from the German
        border to the Belarus border.
    • Construction of the remaining E18 sections into a motorway in Finland by 2020
    • Construction of motorways from Oslo to the Swedish border on routes E6 and
        E18.

In addition to the above-mentioned projects there are only a limited number of potential
bottlenecks on the road network that need to be addressed. They are shown in Figure
8.8. These bottlenecks are potentially new investment projects. In Table 8.9 the priority
of the projects is determined by using the time loss per ton of transported international
freight as an indicator. Time losses on a road section are then weighted (multiplied) by
the forecasted international freight volume. The derived value of time loss in ton-
hours/day gives a good indication of the importance of the identified bottleneck to
international trade.




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Table 8.9 Road bottlenecks after programmed improvements
ROADPARAMETER                                 TRAFFIC DATA AND
                                                 FORECAST
Secti    Start node   End node       Length                          V/C     Share of Interna-    Travel   Inci-   Total
on ID                                km                              with    delayed tional        time    dent    time
                                                                    impro-   traffic % freight     loss    time    loss
                                                                      ve-              1000t/yr    1000    loss    1000
                                                                    ments                          ton-    1000    ton-
                                                                                                  hrs/yr   ton-    hrs/yr
                                                             HGV-                                          hrs/
                                              year   AADT     %                                            yr


BRANCH 1          SWEDEN
                  Haparanda
    150 Haparanda border               1      2006   11400    5     0,60      50 %       1 285        1       1        2
                                       1      2010   15000    5     0,79      50 %         883        1       1        2
                                       1      2025   16000    6     0,85      50 %       1 251        2       2        4
BRANCH 2              RUSSIA
                                                        13
    9h   km 138       km 149          11      2002     789    64    1,17      35 %       5 358        0       0        0
                                                        15
         Vyborg bypass                11      2010     000    48    1,15      35 %       5 394        0       0        0
                                                        18
                                      11      2020     000    36    1,26      35 %       9 513        5       5        9
BRANCH 3              ESTONIA
612a     NARVA                        3,5     2006    8000    20    street    50 %        1684       41      41       82
                                      3,5     2010    8000    20    street    50 %        2178       53      53      106
                                      3,5     2020    8000    20    street    50 %        3269       80      80      159
BRANCH 4              LATVIA
A95      Babite       Riga            15      2005   33145    9     0,46      50 %          22        0       0        0
                                              2010                            50 %          29        0       0        0
                                      15      2025   87389    9     1,20      50 %          37        2       2        4
I        Salaspils    Kekava           9      2005   11380    24    0,72      50 %         742        0       0        0
                                              2010                            50 %       1 007        0       0        0
                                       9      2025   27605    29    1,82      50 %       1 901       13      13       26
AS4      Ogre         Jekabpils       109     2005   10230    18    0,61      35 %         742        0       0        0
                                              2010                            35 %       1 007        0       0        0
                                      109     2025   19086    29    1,26      35 %       1 901       10      10       19
BRANCH 7              RUSSIA
     MOSCOW
2a   km 16            km 37           21      2002   81953    22    1,27      50 %       6 356      627     627    1254
                                      21      2010   84000    18    1,26      50 %       7 061      666     666    1332
                                      21      2020   86500    16    1,27      50 %      17 554     1728 1728       3455
BRANCH 8              NORWAY
                      Oslo
2-8      Vinterbro    grense          8,6     2005   19000    10    0,70      50 %          88        0       0        1
                                      8,6     2010   22027    10    0,81      50 %         114        1       1        1
                                      8,6     2020   29602    10    1,10      50 %         160        2       2        3
         Akershus     Bispelokke
2-9      grense       t (x rv 190)    8,9     2005   29000    10    1,07      50 %          88        1       1        2
                                      8,9     2010   33620    10    1,24      50 %         114        2       2        3
                                      8,9     2020   45182    10    1,67      50 %         160        3       3        7
BRANCH 9              NORWAY
     Akershus
1-8  grense           Alnabru         18      2005   49000    10    0,68      50 %         544        0       0        0
                                      18      2010   56806    10    0,79      50 %         631        0       0        0
                                      18      2020   76342    10    1,06      50 %         734        7       7       14




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 How to read Table 8.9
 • Travel time loss in 1000 ton-hrs/day is the main indicator of a bottleneck situation. This
    is the product of time loss (see Appendix 2) and international freight flow on a road link
    (1000t/yr). The indicator reflects the effects of congestion on a given road section. It is
    called recurrent delay.
 • International freight, 1000t/yr, is obtained from the forecast of international freight
    transport prepared in this study
 • Share of delayed traffic is the heavy traffic that is subject to the estimated delay. In major
    urban areas the share assumed at 50% and in smaller urban areas, excepting streets, the
    share is 35%
 • Incident time loss or the non-recurring loss is due to weather, accidents etc.
 •   Total time loss is the sum of recurrent and non-recurrent delay. This value is indicative
     only and is not used in prioritisation




Figure 8.8 Road Bottlenecks after main investments in 2020


The first observation from Table 8.9 and Figure 8.8 is that the remaining bottlenecks are
all in the vicinities of urban centres. No capacity bottlenecks are located in rural road
sections. The second observation is that the used method reveals the remaining
bottlenecks and their priorities very clearly. Thus, an additional improvement program
can be compiled without any further analyses. The program has three categories:
     1. Capacity improvement projects, which are not included in the already approved
         programs, Table 8.10
     2. Road sections that need monitoring in the planning period until 2020, Table 8.11
     3. Other projects that do not affect capacity but are structurally important, Table
         8.12

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Table 8.10 Recommended additional improvement projects
      Proposed project                                         Remarks
1. Capacity increase (from 4 to    There is an upgrading project on the Moscow-Minsk road (217
6-8 lanes) on the approach to      Meuro) by 2013. However, it appears not to increase
Moscow (21km), Branch 7 in         specifically the road capacity.
Russia
2. Bypass of the City of Narva,    The Narva bypass is closely linked with the relocation of the
Branch 3 in Estonia                Narva/Ivangorod border station outside the city centre. The
                                   border is currently highly congested.


Table 8.11 Road sections that need monitoring up to 2020
      Proposed project                                      Remarks
3. Road branch 4 in Latvia,        The road is approaching its capacity by 2020 and becomes
Riga-Jelgava-Russian border        an eventual bottleneck.
4. Vyborg bypass, Branch 2         The new bypass of Vyborg needs to be widened into a 4-
in Russia                          lane road
5. E 6 in Norway, Branch 9         There is a new motorway between Oslo and the Swedish
                                   border on E6 towards Gothenburg and Copenhagen.
                                   However, the 4-lane section near Oslo may become
                                   congested by 2020
6. E 18 in Norway, Branch 8        New motorway is being constructed on E18. However, not
                                   much additional capacity will be provided on the approach to
                                   Oslo. This section may become congested by 2020.


Table 8.12 Road sections that need other measures
             Proposed project                                            Remarks
Strengthening of roads to meet 11,5 ton axle         Limitations of axle and vehicle weights are
weights in Russia:                                   significant impediments to international HGV
• Branch 2, Finnish border-Vyborg-St.                traffic. They also have cost implications
    Petersburg
• Branch 3, Estonian border-St. Petersburg
• Branch 4, Latvian border-Moscow
• Branch 6 in Kaliningrad
• Branch 7, Belarus border-Moscow

Table 8.9 refers also to an additional “bottleneck”, namely Haparanda/Tornio in Sweden
and Finland (Branch 1), where the road runs along the city streets. This location,
however, is not listed as a bottleneck due to its relatively minor impact on through
traffic. The existing border does not present any delay to traffic. Furthermore, there are
no proposals of relocating this road outside the two cities, because any new alignment
will involve expensive bridge construction.

There are a number of small urban centres and villages on the Northern Axis roads, even
if they are being bypassed with the new road construction. Unfortunately the collected
data is not refined enough to pick up those situations. These built-up sections
nevertheless present bottlenecks for heavy goods vehicles, should be identified in the
further analysis and eliminated over time.




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8.6.3    Non-programmed railway improvement projects
Table 8.8 shows the main railway projects, which the countries have identified and
largely programmed at the moment. When it comes to railway improvements and
without very detailed information, it is often difficult to determine how much these
investments can improve the capacity, particularly for freight. Typical such projects
are those that are intended for speed increases, which clearly favour passenger trains.
Among the identified projects the obvious ones that improve the capacity are:
• Double-tracking of the railway Riga-Russian border in Latvia, which includes also
    a complete modernisation of the line
• Double tracking the St. Petersburg-Murmansk railway in Russia on its most
    congested sections
• Rerouting freight traffic to parallel lines in sections Moscow-St. Petersburg and
    St. Petersburg-Vyborg in Russia. These moves leave considerable capacity for
    high-speed passenger trains and some container trains on the line.

Considering that the above programmed projects will be implemented, and many of
them are already underway, it leaves still a number of obvious and potential
bottlenecks unaddressed. Based on Figure 8.3 showing the links with capacity
constraints in the railway network a number of additional improvement needs have
been identified and are shown in Table 8.13 in more detail.

Table 8.13 Improvement needs that are not addressed in current investment programs
                                                                              TRAFFIC              Capa     Interna-
             RAILPARAMETER                                                    FORECAST             city     tional
Branch       Sectio  Start node         End node           Length   Country           freigth Capa utili-   freight
              n ID                                                                  volume city satio       flow
                                                                                                   n%
                                                                                                            1000
                                                              km              year   Mton/a                 ton/a
1 Priority
                                    Saint-Petersburg
   3          3.2   Veimarn         (Gatchina)                74      RU      2010     32,1   32     100      32000
   6          6.1   Kaliningrad     Chernyakhovsk             90      RU      2010     23,8   34     109       17229
                                                                                                            Missing
   1          8.2   Ledmozero       Kotchkoma                127      RU                                    link
2a Priority
                                    Saint-Petersburg
   1          8.8   Volkhovstroy    (Mga)                     75      RU      2010     98,3   125    91       20284
   4          4.5   Shakhovskaya    Volokolamsk               28      RU      2010       16   28     89       15900
   5                Molodechno      Minsk                     77      BY      2010     22,7   100    97       22700
   6          6.2   Chernyakhovsk   Nesterov                  61      RU      2010     23,4   35     94       17229
   7          7.3   Minsk           Orsha                    216      BY      2010     30,5   100    94       25700
3a Priority
                                    Swedish Border
                                    Bjørnfjell/(Vassijau
   1           3    Narvik          re)                      38,2    NO       2005     16,0          80       16000
   2          2.2   Vyborg          Saint-Petersburg         143      RU      2010     55,4   137    78       33118
   3                Tapa            Narva                    132      EE      2010     25,9   44     80       25900
   7          7.2   Baranovichi     Minsk                    139      BY      2010     17,5   100    80       17500
   7          7.3   Vyazma          Mozhaisk                 133      RU      2010     39,2   100    71       25700
   7          7.4   Mozhaisk        Moskow (Kubinka)          47      RU      2010     40,5   115    72       25700




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3b Priority
   2          196     Luumäki          Vainikkala                 32         FI          2010          8,7    50         91 %        8700
   8         B 2-2    Lillestrøm       Årnes                     37,5    NO              2007       0,435     72          95         6792
4b Priority
                                       Moscow
   2          2.5     Bologoe          (Povarovo)                279     RU              2010          1,3    137         88         1300
5 Priority
   8         B 2-1    Oslo S           Lillestrøm                 21     NO              2007       0,435     571         70          435
   9         A 1-1    Oslo S           Ski                       24,3    NO              2007                 301         75         1194


Priority of projects
The priority of a project is determined by using two indicators: (1) the rate of capacity
utilisation (%), and (2) the volume of international freight that is using the given railway
link.
At 70% and below of theoretical capacity the railway has free flow. As capacity
utilisation reaches 85% and above, it begins to run at its practical capacity and
congested situations occur and delays grow. At 100% the railway has reached its
theoretical capacity, but can often operate by delaying trains and making selected
operational changes.
At higher flow rates of international freight investments may become justified also at
lower than 100% level of capacity utilisation. The chart below follows this logic of
priority, which is applied in Table 8.13 and Table 8.14.
                                                         (1) Capacity utilisation
                                                      <70%     70-85%        >100%
              (2) International
              freight (mill. tons)           >15       3a               2a                  1
                                             5-15      4a               3b                 2b
                                              <5        5               4b                 3c



By 2020 and with growing traffic some new sections begin to show strain. They are
shown in Table 8.14 and in Figure 8.9.

Table 8.14 Improvement needs that must be monitored until 2020
             RAILPARAMETER                                                    TRAFFIC                  Capa- Capa-             Interna-
                                                                              FORECAST                  city city utili-         tional
 Branch       Secti     Start node      End node      Length      Country            freigth                  sation            freight
              on ID                                                                 volume                       %                flow

                                                       km                         year     Mton/a                              1000ton
                                                                                                                                 /a
2a Priority
   4           4.2    Novosokolniki   Velikie Luki          29      RU            2020           23     35          94          23000
   4           4.3    Velikie Luki    Rzhev              241        RU            2020          22,5    32          94          23000
3a Priority
   2           2.1    Buslovskaya     Vyborg                28      RU            2020           15     38          79          15000
   4           4.4    Rzhev           Shakhovskaya          83      RU            2020           23     40          75          23000
                                      Moskow
   4           4.6    Volokolamsk     (Manihino)            73      RU            2020          25,5    111         74          23000
   7        7.4       Orsha           Osinovka              48      BY            2020           30     100         71          30000
3b Priority
   1           8.5    Petrozavodsk    Svir               115        RU            2020          52,8    71          85            5078
   1           8.6    Svir            Lodeinoe Pole         45      RU            2020          52,8    71          85            5078



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On the Northern Axis railway network there is only one link that can be considered as
missing, see Table 8.13. That is the Lemozero-Kotchkoma stretch of Branch 1 in
Russia. This railway link has for most parts been built, but is still not complete
enough so that it could be opened to normal international traffic.




Figure 8.9 Railway Bottlenecks 2020


8.7     Systemic effects
The above analysis of roads and road borders allows us to go further in our analysis
and make some system level estimates, such as the total delays in the system and
fathom even their cost implications. The same is not possible for the railways. Lack of
railway data lets us only identify those locations where the railway capacity is or will
become insufficient.

8.7.1    Time loss on roads and road borders
Time loss has been estimated for each road link and road border crossing. The system
level loss of time can be obtained by summing them all up, which yields the total
delay of international freight transport in million ton-hours. The following estimate
represents the current situation and can also be seen as an avoidable delay on the
Northern Axis road network:




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Table 8.15 Total time loss on roads and road borders
                     Ton-hrs, in million        Share, %
Roads                5,4                        2%
Borders              242,1                      98%
Total                247,5

Even if the estimate is rough, the split of delay sends a quite strong message: road
borders cause practically all the delay, while even the most congested road sections do
not matter so much.

The above estimate is based on some assumptions of which the most important is the
delay in the direction from Russia/Belarus into the EU area. Here it is assumed that
this delay is half of that estimated for traffic from the EU to Russia/Belarus.

8.7.2     Cost implications
The above total delay estimation can be continued by applying some unit cost value to
the derived ton-hour delays. The cost estimate requires further assumptions and,
therefore, the values given below should be considered only indicative. However,
such an estimate can be useful as it gives some kind of measure of the system level
costs.

Table 8.16 Total monetary loss on roads and road borders
                                                             Million euros/yr
Alternative 1.                             Roads                    10
Only loaded HGVs are considered            Borders                 440
                                           Total                   450
Alternative 2.                             Roads                    20
Both loaded and empty HGVs are             Borders                 880
considered                                 Total                   900
Assumptions:
• An average HGV crossing the border carries 5,5 tons of goods based on border statistics.
    Assuming half of the HGVs empty, the average full load is 11 tons.
• Cost of time delay of a Finnish HGV is 20 euros/hr, which takes into consideration only
    the cost of the driver.

With the assumptions mentioned in the table, the total monetary cost of delays amount
to 450 – 900 million euros per year.

Lower total costs can be obtained by using the true split of HGV origins and
respective unit costs for vehicles. If also the time value of a vehicle and the load is
considered, the total cost will be higher. Thus, alternative ways of estimating are
many. The above calculation should suffice for now, as it indicates that the potential
monetary savings are quite high. Furthermore, it clearly states that practically all
expenditures at the road borders will be justified, if they bring about significant
shortening of waiting times. On the other hand, potential savings of international
freight on road links are quite small and can hardly be used to justify any major road
investments other than in some specific locations, such as those improving the border
stations.



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8.7.3   Logistics chains
The estimated time loss data on road links and at road borders can also be used when
estimating bottlenecks of a given logistics chain. Table 8.17 shows a schematic
presentation of avoidable delays during a delivery from a port or terminal in Helsinki
to a customs terminal in Moscow. The Table shows clearly that delays can be reduced
firstly at the border and secondly in terminals. Achieving any significant time savings
on the road are next to impossible unless the allowable HGV speeds are considerably
increased.

Table 8.17 Avoidable delays of a logistic chain: Helsinki = > Moscow

                                      Time Loss: Helsinki-Moscow




            Roads                                                                    Roads
            Finland                                                                  Russia




   Port/Terminal                                Border                                 Customs terminal




   0%       10 %      20 %     30 %      40 %     50 %     60 %      70 %     80 %       90 %    100 %


Notes: Time delays in port/terminal in Helsinki and in customs terminal in Moscow are
indicative only. They have not been quantified in this study.

It should be noted that the selected terminal delays in Helsinki and Moscow are
indicative only, as they have not bee the subject of this study. In further analyses these
delays should deserve full attention so that the improvement measures can be directed
and judged properly. Similar logistics chains analyses can also be prepared for all the
main routes of international freight transport of the Northern Axis.




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                             Major environmental issues related to the development of the Northern Axis




9 Major environmental issues related to the development of
  the Northern Axis

9.1                   Emissions
The used transport model allows the estimation of environmental impacts when mode
specific mileage (ton-km) and emission coefficients (e.g. CO2/tkm, train) are known.
In the analysis the emissions are calculated only for the transport of foreign trade in
the Northern Axis area. Thus, the derived values do not represent the total emissions
on the Axis.

The used emission coefficients13 by mode and ton-km values are from the VTT (CO,
HC, NOx, SO2, PM and CO2). In the analysis it is assumed that these coefficients do
not change with time.


                                   Fre ig h t e m i s sions in the Northern Axis area


                      60

                      50

                      40
     million tons/a




                      30

                      20

                      10

                       0
                                  2000                        2010                      2020

                                                      Sea      Road      Rail


Figure 9.1 Total emissions by mode by freight transport (export and import) in the Northern
Axis area (million tons/a)


The transport of foreign trade on the Axis road and rail network causes emissions ca.
30 million tons in 2000. The main part of emissions is CO2, ca. 98%. Most of the
emissions are from sea transport, 16 million tons in 2000, which will with the growth
of transport almost double to 29 million tons by 2020.

1/3 of the emissions are from road transport, 10 million tons in 2000 and 18 million
tons in 2020. Rail transport’s share of the emissions is only ca. 10%, 3 million tons in
2000 and 5 million tons in 2020. The marshalling yard locomotives at the railway

13
     VTT Technical Research Centre of Finland, http://lipasto.vtt.fi/indexe.htm.



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yards are assumed to have diesel engines. The respective emissions are included in
rail figures and are assumed to be 15% (of rail mode).


                    Share o f m ile a g es and em issions by mode


         100 %

           80 %

           60 %
   %
           40 %

           20 %

            0%
                              mile age                          emissions

                                         Sea     Road    Rail


Figure 9.2 Comparison of shares of mileage (tonkm’s) and total emissions (tons/a) by sea, road
and water transport of the foreign trade transport in the Northern Axis area


Regarding transport work (mileage, ton-km), rail transport’s share of is 1/3. It appears
to be “clean”, producing only 10% of emissions. Sea transport, which produces most
emissions, has slightly bigger share of emissions than of mileage, ca 50%. Road
transport’s share is ca 17% of mileage, but 35% of emissions (double). Even if freight
transport grows rapidly, the shares remain stable (about the same), because no
assumptions were made of the development of new “clean” vehicles.

9.2    NATURA 2000 network
In several locations the Northern Axis roads and railways run through or near the
specific environmental protection and biodiversity sites, the Natura 2000 network,
defined by the EU member states. Such situations can be found in all EU member
states. However, as the current axis roads and railways are, as a rule, much older than
the relatively recently defined Natura sites, a conclusion is made here that only those
Natura areas should be highlighted where new transport facilities are planned or built.
Such locations can be found in Estonia and particularly in Poland. These countries
have plans for major road construction projects. With regard the railways no such
sites can be clearly determined, even if in Latvia attention must be paid to potential
conflicts during the country’s major railway improvement program.

It should be pointed out that no information about the nature protection areas has been
available from Russia.

Figure 9.3 shows the identified sites for potential conflicts between the planned
Northern Axis infrastructure and the Natura network. These sites are only indicative,


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as the exact alignments of the planned new infrastructure with regard the Natura areas
are not studied in detail here.




Figure 9.3 Indicative sites for potential conflict between new Northern Axis infrastructure and
the NATURA sites


9.3   Urban areas
The Northern Axis roads and railways pass through urban areas in many occasions.
These sections are potential areas for excessive noise in addition to emissions and
increased safety risk, among others. Tables in Appendix 2 show the length of urban
areas along each road link based on the information from the national experts. This
information is only indicative, because the exact relationship between the road and
residential land-use in each case is not known.




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Appendices

APPENDIX 1: COUNTRY REPORTS …………………………………………189
APPENDIX 2: BASIC ROAD AND RAIL PARAMETER AND
            PERFORMANCE DATA ……………………………………… 241
      ROADS ………………..……………………………………….….. 241
      RAILWAYS ………………..……………………………………...…249
APPENDIX 3: DATABASE REPORT ……………………………..…………. 256
     OVERVIEW ………………………….……………………………… 256
     THE TEN-NORTH DATABASE …..…………………………………… 256
     THE DATABASE MODEL……………………………………….       256
APPENDIX 4: EVALUATION SYSTEM OF ROADS AND RAILWAYS ..……….. 277
     ROADS .……………………………..…………………….……….. 277
     RAILWAYS …………………………………………………………. 281
APPENDIX 5: TRANSPORT MODELLING
     FREIGHT TRANSPORT ….………………………………………….. 283
     PASSENGER TRANSPORT …………………………………………. 287




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Appendix 1: Country Reports

BELARUS …...………………………………………190
ESTONIA ...………………………………………….195
FINLAND ...……………………….………………… 198
GERMANY …………………………………………. 203
LATVIA …………………………………………….. 206
LITHUANIA ………………………………………… 209
NORWAY ……………………………………………214
POLAND …………………………………………… 221
RUSSIA ……………………………………………. 225
SWEDEN …………………………………………… 238




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COUNTRY REPORT                                                COUNTRY     BELARUS
Branches   5 and 7
Version                                   Date                                     Name of preparer
1                                         22 August 2007                           B.Karimov, E.Mahlin,
                                                                                   A.Strijevsky, W.Segercrantz




National regulations

Heavy Goods Vehicles                                          Max speed   100 km/h and 70 km/h1
Max weight              Max axle weight          Max height                Max length                 Max width
18/44        and 115 kN3                         4.0 m                     12 / 20 m4
           2
18/38 tons
Railways                                                      Railway gauge
                                                                              1 520 mm
General comments
1
  100 km/h for Brest-Minsk-Russia road and 70 km/h for Minsk – Lithuania road
2
  max weight 18 tons for single vehicle and 44/38 tons for trailer (Higher weight of trailer
   possible for Brest – Minsk – Russia road and lower for Minsk – Lithuania road
3
  In spring time special restriction might be in use on most of the network
4
  max length 12m for single vehicle and 20 m for trailer



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BRANCH                                  Branch   71                        ROAD
Route                                                        Route Nos
Brest-Minsk-Belarusian/Russian border                        E-30, Bearus national M1
Version                                 Date                               Name of preparer
1                                       22 August 2007                     W. Segercrantz,
                                                                           A. Strijevsky, B. Karimov
Infrastructure
Length 610 km            Road type: High quality road                                     km/h
                                                                           Design speed: 120
Tolled Yes               Responsibility National                           Width 15/22 m (2+2 lanes)
Pavement Asphalt 566 km, Urban areas                                       Accidents

concrete 44 km           12,6 km                                           190 with injuries

Traffic
Existing, Yr 2006              Avg 6090                      Max                       Min
                               HGV 35%
Forecast 2010                  Avg 6050                      Max                       Min
                               HGV 33%
Forecast 2020                  Avg 7500                      Max                       Min
                               HGV 28%
Internat’l HGV in %            Avg                           Max                       Min


Investments (MEURO) Not defined
New construction                        2006-2013                          2014-2020
Rehabilitation                          2007-2013     47,5                 2014-2020
Upgrade                                 2007-2013                          2014-2020


Comments

The road starting from Brest at the Polish border and bisecting the entire country of
Belarus is the main east-west road between Central Europe, Belarus and Russia
(Moscow).

The road is principally of high quality having 4-lanes over its entire length.

Traffic volumes are modest at 6 000 vehicles/day.

The road is scheduled for rehabilitation in years 2006-2010.




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BRANCH                                72  Branch                                     RAILWAY
Route Brest – Baranovichi – Minsk – Orsha – Osinovka                         Route Nos:
Version                                   Date                                       Name of preparer   W. Segercrantz,
1                                         22 August 2007                             E. Mahlin
Infrastructure
Length 609   km                           Rail type Conventional                     Activity Passenger        and freight
Number of tracks 2                        Traction Electrified                       Voltage 25 kV
Load gauge                                Signalling standard:                       Degree of capacity utilisation:
1T                                        Automatic block                            No data
                                                                     1
Max axle load 22,5 T                      Max train length 800-1000m                 Max train weight 4500      – 5100 t2
Speed: (1) Design (2) Max (3) Min   (4) Freight
120 km/h
Traffic3
Existing, Yr                  Trains/d   16-89                  Tons/yr   6,5-23,4               TEU/yr no data

Forecast 2010                 Trains/d   18-94                  Tons/yr   7,2-30,5               TEU/yr no data

Forecast 2020                 Trains/d   20-100                 Tons/yr 8,0-34,0                 TEU/yr no data

Forecast 2030                 Trains/d   22-106                 Tons/yr   9,0-37,0               TEU/yr no data



Investments (MEURO)
New construction                          2007-2015                                  2014-2020
Rehabilitation                            2007-2013                                  2014-2020
Upgrade4                                  2002-2009:   17,1                          2010-2015: 471,4


Comments:

Notes:
1
  Train length 800m is possible in sections Brest – Baranovichi and Orsha - Osinovka. Train
   length 1000m is possible in section Baranovichi – Minsk – Orsha;
2
  Max train weight 5100t is possible from Brest to Baranovichi, max weight 5000t from Orsha
   to Osinovka, and 4500t on the section Baranovichi – Minsk – Orsha;
3
  Smaller traffic and freight volumes are related to the section from Brest to Baranovich
4
  Increasing the speed of passenger the trains: Phase 1: maximum speed 140 km/h; Phase
   2: maximum speed 160 km/h.




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BRANCH                               Branch   51                        ROAD
Route     Lithuanian border-Minsk                       Route Nos
Version                              Date                               Name of preparer
1                                    22 August 2007                     W. Segercrantz,
                                                                        E. Mahlin, A. Strijevsky.
Infrastructure
Length90 km                          Road type: High quality road                       km/h
                                                                        Design speed: 120
Tolled No                                         National
                                     Responsibility                     Width 1+1 / 2+2 lanes
Pavement Asphalt                     Urban areas 13 km                  Accidents No data


Traffic
Existing, Yr 2006           Avg                         Max 5970                 Min 3780
                                                        HGV 24%                  HGV 46%
Forecast 2010               Avg                         Max 7000                 Min 5000
                                                        HGV 26%                  HGV 34%
Forecast 2020               Avg                         Max 8500                 Min 7500
                                                        HGV 28 %                 HGV 28%
Internat’l HGV in %         Avg                         Max                      Min


Investments (MEURO)
New construction                     2006-2013                          2014-2020
Rehabilitation                       2007-2013                          2014-2020
Upgrade                              2007-2013    0,7                   2014-2020


Comments:

     1. From Minsk in direction of Lithuania for 58 km there is a 2-lane road. The rest
        of branch to the Lithuanian border has 2+2 lanes
     2. Higher traffic volumes take place nearer to Minsk




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BRANCH                                      Branch   52                                 RAILWAY
Route Lithuanian      border-Minsk                                 Route Nos:
Version                                     Date                                        Name of preparer
1                                           22 August 2007                              W. Segercrantz, E. Mahlin
Infrastructure
Length 157   km                             Rail type Conventional                      Activity Freight     +passenger
Number of tracks 2   (Double)               Traction Diesel                             Voltage

Load gauge 1T                               Signalling standard Automatic       block   Degree of capacity utilisation
Max axle load 22,5                          Max train length 800   m                    Max train weight 5000     T
Speed: (1) Design (2) Max (3) Min     (4) Freight
Max speed 120 km/h
Traffic
Existing, Yr 2005               Trains/d   47-931                  Tons/yr   19,2 – 20,5            TEU/yr   a)
Forecast 2010                   Trains/d 52-97                     Tons/yr   22-22,7                TEU/yr

2020                            56 - 101                           24,5 – 25,0
2030                            59 - 104                           26,9 – 27,2


Investments (MEURO)
New construction                            2007-2015                                   2014-2020
Rehabilitation                              2007-2013                                   2014-2020
Upgrade                                     2007-2013                                   2014-2020


Comments

The railway is the main connection form Belarus to the Lithuanian and Kaliningrad ports.

It has heavy freight traffic over the entire line. The number of passenger trains is higher in
the section from Minsk to Lithuanian border

No investments are foreseen




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COUNTRY REPORT                                                  COUNTRY     ESTONIA
Branchs:   3
Version                                     Date                                     Name of preparer  A. Kaldas,
1                                           8 October 2007                           W. Segercrantz, R. Uukkivi




National regulations

Heavy Goods Vehicles                                            Max speed   90 km/h, in built-up areas 60 km/h
Max weight                Max axle weight          Max height                Max length                 Max width
44 ton                    11,5 (10) ton            4.0 m                     12 / 18,75m*               2.55 m
Railways                                                        Railway gauge
                                                                                1 520 mm
General comments
Estonia has largely harmonized its vehicle standards with those of the EU. The only major
difference is the maximum axle weight of 10 tons, which can still be found on road sections
that have not yet been upgraded to 11,5 tons. Upgrading is being carried out in new projects.
HGV speed of 90 km/h is somewhat higher than 80 km/h allowed in some other axis
countries.
Estonia has the wide railway gauge as inheritance from Russia/Soviet Union. That does not
present a problem, because the only railway border crossing in the branch is with Russia.

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BRANCH                                  Branch ID   31                             ROAD
Route Tallinn   – Narva                                        Route Nos   E20, National road nro 1
Version                                 Date                                      Name of preparer A. Kaldas,
1                                       8 October 2007                            W. Segercrantz
Infrastructure
Length     202 km                       Road type High quality road from           Design speed
                                        which 60,6 km is motorway,
                                        and 3,5 km urban street
Tolled   No                             Responsibility. National                   No of lanes: Motorway 4 lanes,
                                                                                   and road 2 lanes
Pavement   Asphalt concrete             Urban areas   3,5 km                       Accidents 99 with injuries


Traffic
Existing, Yr                   Avg   6 584                     Max35 186                       Min 3 720
Forecast 2020                  Avg                             Max35 720                       Min 4 360
Share of HGVs in %             Avg                             Max 17                          Min 9
Internat’l HGV in %            Avg                             Max                             Min


Investments (MEURO)
New construction                        2007-2013: 130 milj €                      2014-2020 none
Rehabilitation                          2007-2013: none                            2014-2020 none
Upgrade                                 2007-2013: 80 milj €                       2014-2020 none



Comments

Road E20/National route 1 is the main road between Tallinn and Northeast Estonia, and
particularly between Estonia and St. Petersburg.

The road comprises three different stretches: (1) after the Tallinn street system (10,4 km) a
4-lane motorway extends 61 km to the east of Tallinn, (2) a high quality 2-lane road (137
km), and (3) the city streets in Narva (3,5 km) at the Russian border.

The biggest bottleneck is the City of Narva with its street section, border crossing in the City
centre and the old bridge over the Narva River to Russia.

In the two lane section there are small settlements (Viitna, Aseri, Kukruse, Jõhvi, Sillamäe),
which can also be defined as bottlenecks.

Traffic volume ranges between 35 000 near Tallinn to 3 700 in most rural section. The
average volume of 6600 vehicles per day is moderate. Traffic growth has been rapid.

The main road improvements are: 1) Väo-Maardu (4-lane to 6-lane) 2)Kukruse-Jõhvi (2-
lane to 4-lane) 3) Valgejõe-Rõmeda (new 4-lane road). The launch of these road works are
planned for the last years of this decade.




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BRANCH                                     Branch ID    32                             RAILWAY
Route: Kopli / Maardu-Muuga-Tapa-Narva                            Route Nos:
Version                                    Date                                        Name of preparer R Uukkivi,
1                                          8 October 2007                              W. Segercrantz
Infrastructure
Length:224 km                              Rail type: Conventional                                  and freight
                                                                                       Activity: Passenger
Number of tracks 2 and 1              Traction : Diesel (electric for Voltage 3000 DC for commuter
                                      commuter trains)                  trains only
Load gauge T                          Signalling    standard: Automatic Degree of capacity utilisation :
                                      blocking                          Tapa – Narva 70%, Tapa –Lagedi
                                                                        40%, access Port Muuga 75%
Max axle load: 32 tons                Max train length 798 m            Max train weight 5500
Speed: Passenger 120 Freight 90; Lagedi – Kopli section 90/70; temporary speed limits on other sections
possible

Traffic
Existing, Yr 2006              Trains/d:                          M. Tons/yr   25-38               TEU/yr   2200-10500
                               Passenger trains : 3
                               Commuter trains : 5
                               Freight trains: 22-29
Forecast 2011                  Trains/d Long distance             Tons/yr   26,2-44,9              TEU/yr   10000-48000
                               pass 5
                               Freight 30-38


Investments (MEURO)
New construction                           2007-2013                                   2012-2016      30
Rehabilitation                             2007-2013:        30,2                      2014-2020
Upgrade                                    2007-2013          4                        201 2020


Comments

The railway is the main line between Estonia and Russia. It connects Tallinn with St. Petersburg
and Moscow, as well as provides the rail connection from Russia to the Estonian ports: Sillamäe,
Muuga, Tallinn, Paldiski.

In Tapa there is a branch south to Tartu and Pechory (Russia), as well as to Valga (border with
Latvia) The line Tallinn-Tartu-Valga will be the basis for Rail Baltica development in Estonia.

The railway is structurally of high quality with its 32 ton allowable axle weight and 5 500 ton train
weight. Nearly half of the railway length has 2 tracks. Trains are diesel driven. There are
electrical commuter trains near Tallinn.

The railway is primarily a freight line with 22-29 freight trains per day (38 million tonnes in 2006).
Long-distance passenger trains are 3 per day and short-distance commuter trains 15 to/from
Tallinn. Capacity utilisation is high (70%) on the single-track section Tapa – Narva. Considerable
traffic growth is expected by 2020.

Train controls are compatible with those of the Russian railways (RZD).

The only capacity improvement project is double-tracking the railway leading to Muuga Port by
2015.




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COUNTRY REPORT                                                  COUNTRY     FINLAND
Corridors:   1 and 2
Version                1.0                  Date      18 June 2007                   Name of preparer   T. Kärkinen




National regulations

Heavy Goods Vehicles                                            Max speed   90 km/h
Max weight                Max axle weight          Max height                Max length                 Max width
60 tons                   11,5 tons                4,2 m                     25,25 m                    2,55 m
Railways                                                        Railway gauge
                                                                                1524 mm
General comments

HGV sizes and weights are the same or exceed those of the EU.

Track gauge of the Finnish railways is principally that of Russia. Other characteristics of the
Finnish railways differ from those of Russia, such as traction power, signalling and rolling
stock standards.

The gauge difference is at the border with Sweden, which uses the European standard
gauge.


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CORRIDOR                               Corridor ID   1                        ROAD
Route  Tornio-Oulu-Vartius                                  Route Nos   E8, E75
Version 1.0                            Date   18 June 2007                    Name of preparer Timo   Kärkinen
Infrastructure
Length 385 km                          Road type  Ordinary road               Design speed

Tolled No                              Responsibility National                No of lanes:4 and 2
Pavement Asphalt                       Urban areas 0 km                       Accidents 0 … >20


Traffic (vehicles per day, AADT)
Existing, Yr 2006           Avg: 2 000 – 8 000              Max 42 700                    Min 350
Forecast 2020               Avg:    2 500 – 9 000           Max 48 000                    Min 420
Share of HGVs in %          Avg    10                       Max 15                        Min 7
Internat’l HGV in %         Avg                             Max                           Min


Investments (MEURO)
New construction                       2007-2013                              2014-2020
Rehabilitation                         2007-2013                              2014-2020
Upgrade                                2007-2013   143 M€                     2014-2020




Comments

The road corridor Tornio-Oulu-Vartius consists of four roads of differing functional classes
and standards: (1) Rt. 29 / E8 from Tornio (Swedish border) to Kemi, (2) Rt. 4 / E75 from
Kemi to Oulu, (3) Rt. 22 from Oulu to Paltamo and (4) Rt. 89 from Paltamo to Vartius border
station at the Russian border. All the roads are designed for long distance traffic and the
road connection has no street sections other than in Tornio/Haparanda at the border of
Finland-Sweden.

Rt. 29 is a 4-lane motorway connection between Tornio and Kemi. The average traffic
volume is 8 000 vehicles / day.

Rt. 4 is the main north-south road in Finland. It has a motorway section in Oulu, elsewhere it
is an ordinary 2-lane road. The biggest traffic volumes are in Oulu, about 32 000 vehicles /
day.

Rt. 22 is a connection from Oulu to Kajaani in Eastern Finland. The road is an ordinary 2-
lane main road. AADT on this road in 2 000 vehicles / day.

Rt. 89 from Paltamo to Vartius at the Finnish-Russian border has a little lower standard than
the other roads, but it is also designed for long-distance traffic with a certain volume of
HGV’s.

Traffic volumes are estimated to grow 10 – 30 % by the year 2020. The biggest growth is in
the Oulu region and the peak volume is close to the Oulu City centre.

Finnish Road Administration has a development programme for the road section Kemi –
Oulu. It contains e.g. upgrading of bridges on Rt 4 in Kemi and building of three new
intersections. There are also plans to upgrade the road leading to the Vartius border station.
The cost estimate of all these projects is 143 million Euros.




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CORRIDOR                             Corridor ID   2                        ROAD
Route  Helsinki-Vaalimaa(-St.Petersburg)         Route Nos E18
Version 1.0                      Date 18 June 2007                          Name of preparer Timo   Kärkinen
Infrastructure
Length 167 km                        Road type  Motorway/Ordinary           Design speed
Tolled No                            Responsibility National                No of lanes: 4 and 2
Pavement Asphalt                     Urban areas 5 km                       Accidents   13 … >20

Traffic (vehicles per day, AADT)
Existing, Yr 2006           Avg 8 000 – 17 000            Max 24 000                    Min 5 000
Forecast 2020               Avg 11 000 – 9 000            Max 31 900                    Min 6 700
Share of HGVs in %          Avg 15                        Max   24                      Min 12
Internat’l HGV in %         Avg                           Max                           Min


Investments (MEURO)
New construction                     2007-2013   260 M€                     2014-2020   300 M€
Rehabilitation                       2007-2013                              2014-2020
Upgrade                              2007-2013                              2014-2020



Comments

The E18 road between Helsinki – Vaalimaa is the main road connecting Southern Finland
(Helsinki) with Russia (St. Petersburg and Moscow).

The route has varying standards: the sections Helsinki –Porvoo - Koskenkylä and Kotka –
Hamina are 4-lane motorways and the sections Koskenkylä – Kotka and Hamina – Vaalimaa
are ordinary roads. In Hamina, the E18 traffic uses the street network through the town.

The biggest traffic volumes are in the western end of the road section, close to Helsinki
region, about 24 000 vehicles / day. Volumes lessen closer to the border and the number of
vehicles crossing the border is about 5 000.

E18 is part of TEN priory project Nordic Triangle, and plans call for building it into a motorway
by the year 2015. The motorway construction consists of three projects, which will start in the
year 2011. The total cost of these projects is 560 million Euros.




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CORRIDOR                                   Corridor ID   1                            RAILWAY
Route    Tornio – Oulu – Vartius                                   Route Nos:

      1.0
Version                                    Date   18 June 2007                        Name of preparer   Timo Kärkinen
Infrastructure
Length391 km                               Rail type   Conventional                   Activity Partly    freight only
Number of tracks 1                         Traction    Electric                       Voltage   25 kV
Load gauge                                 Signalling standard                        Degree of capacity utilisation 14-70%
Max axle load 22,5 kN                     Max train length   925 m                    Max train weight   2 700 tons
Speed: (1) Design (2) Max (3) Min   (4) Freight


Traffic
Existing, Yr 2006             Trains/d 7   - 35                    Tons/yr   0,8M – 4,9M          TEU/yr

Forecast 2020                 Trains/d                             Tons/yr   2,2M – 4,6 M         TEU/yr



Investments (MEURO)
New construction                           2007-2013                                  2014-2020
Rehabilitation                             2007-2013    (250 M€)                      2014-2020
Upgrade                                    2007-2013                                  2014-2020


Comments

The railway corridor consists of four sections, which differ operationally and technically from
each other.

Section Tornio – Kemi is for freight traffic only.

Section Kemi – Oulu is a part of the main north-south railway of Finland. It serves both
passenger and freight traffic.

Section Oulu – Kontiomäki serves both passenger and freight traffic and is also a trunk
railway of the national railway network.

Section Kontiomäki – Vartius serves freight trains only. The rail traffic on this rail section
contains a significant amount of transit traffic from Russia to the Finnish port of Kokkola on
the Gulf of Bothnia.

The Finnish Rail Administration has one major project planned for this rail corridor. That
contains the upgrading of the transit traffic rail connection from Vartius border station to the
port of Kokkola. The section Vartius – Oulu of that project belongs to the corridor in study. It
is more than half of the whole project. The cost estimate of the entire project is 250 million
Euros.




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CORRIDOR                                  Corridor ID   2                         RAILWAY
Route  Helsinki – Lahti - Vainikkala               Route Nos:

Version 1.0                        Date 18 June 2007                              Name of preparer   Timo Kärkinen
Infrastructure
Length   212 km                           Rail type   Conventional                Activity Passengers         and freight
Number of tracks 2   /1                   Traction Electric                       Voltage   25 kV
Load gauge                                Signalling standard                                                28-72 %
                                                                                  Degree of capacity utilisation
Max axle load 22,5 kN                     Max train length   925 m                Max train weight   2 700 tons
Speed: (1) Design (2) Max (3) Min   (4) Freight


Traffic
Existing, Yr 2006             Trains/d   35 - 216               Tons/yr   0,3M – 10,1M        TEU/yr

Forecast 2025                 Trains/d                          Tons/yr   1,9M – 11,5M        TEU/yr



Investments (MEURO)
New construction                          2007-2013                               2014-2020
Rehabilitation                            2007-2013                               2014-2020
Upgrade                                   2007-2013   150 M€                      2014-2020   85 M€

Comments

The Helsinki-Vainikkala railway corridor is the main railway connection between Finland and
Russia. It consists of two parts, of which the first is the main railway connection from Helsinki
to the eastern border (Helsinki – Kerava - Lahti – Kouvola – Luumäki – Vainikkala) and the
second is railway connection to the ports of Kotka and Hamina (Kotka – Kouvola) on the Gulf
of Finland.

The railway section Helsinki – Kerava is a conventional rail line. The Kerava – Lahti direct
line opened to traffic in 2006 and is designed for high-speed trains. Lahti – Kouvola –
Luumäki is an old railway line which needs upgrading. The rail section Luumäki – Vainikkala
border station at the Russian border has only one track.

The Finnish Rail Administration has planned the upgrading of the rail section Lahti –
Luumäki. The cost of the upgrading is 150 million Euros. Adding second track from Luumäki
to Vainikkala border station will cost 85 million Euros.




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COUNTRY REPORT                                                    COUNTRY   FEDERAL REPUBLIC OF GERMANY
Corridors:   7
Version                 1                     Date      18 June 2007                 Name of preparer Ralf   Fiedler




National regulations

Heavy Goods Vehicles                                              Max speed 80km/h
Max weight                  Max axle weight          Max height              Max length              Max width
 40    /      44 10 (single) /11,5 4 m                                        18,75m                 2,55
(combination)    (double tires)
Railways                                                          Railway gauge
                                                                  1435mm
General comments

Germany has fully harmonized its vehicle standards with those of the EU.

Germany has the European standard track gauge. It is compatible with those of its
neighbours.




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CORRIDOR                   Corridor ID 71                                   ROAD
Route Berlin Dreieck Spreeau – Border                    Route Nos

Germany-Poland at Frankfurt/Oder             E30 (National A12)
Version 1                    Date 18 June 2007              Name of preparer: Ralf Fiedler
Infrastructure
Length 58,2 km                 Road type Motorway                           Design speed   130 km/h
Tolled for trucks heavier than Responsibility                               No of lanes:
12 tonnes                      National                                     4
Pavement     concrete,   some Urban areas                                   Accidents
asphalt elements               0 km                                         104 (2006)

Traffic (vehicles per day, AADT)
Existing, Yr 2005           Avg 29.900-43.600            Max 43.600                     Min 16.500
Forecast 2015               Avg 37.000-45.000            Max 45.000                     Min 19.000
Share of HGVs in %          Avg 31%                      Max 40,9%                      Min 23%
Internat’l HGV in %         Avg



Investments (MEURO)
New construction                     2007-2013                              2014-2020
Rehabilitation                       2007-2013                              2014-2020
Upgrade                              2007-2013                              2014-2020



Comments

The road corridor is the main connection between Germany (Berlin) and Central Poland
(Warsaw), as well as Belarus and Russia to further east.

The road has high traffic volumes near Berlin, but it declines towards the Polish border. The
road has a very high number of HGVs. The lowest share of HGVs is near Berlin and the
highest in the border section to/from Poland. HGV flows are forecast to increase very rapidly
accounting nearly all the traffic growth in the road corridor.

Accidents are mostly occurring at the border crossing, where the traffic is the slowest and the
traffic density is also the lowest on this corridor.

No major investments are planned for the road.




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CORRIDOR                                  72Corridor ID                                  RAILWAY
Route Berlin -Frankfurt/Oder – German-Polish Route Nos:
border
Version 1                       Date 18 June 2007                                        Name of preparer    Ralf Fiedler
Infrastructure
Length 85,2                                 Rail type Conventional                       Activity: Passenger         and freight
Number of tracks 2                          Traction Electrified                         Voltage 15  KV 16 2/3
Load gauge:                                 Signalling standard: ERTMS       3           Degree of capacity utilisation 100%
Max axle load: 22,5                         Max train length                             Max train weight:

Speed: (1) Design 120   km/h   (2) Max   120 km/h    (3) Min   n.a.   (4) Freight   120 km/h

Traffic
Existing, Yr 2005               Trains/d   61                     Tons/yr    n.a.                    TEU/yr   n.a.
Forecast 2008                   Trains/d 117    (2008)            Tons/yr   n.a.                     TEU/yr   n.a.


Investments (MEURO)
New construction                            2007-2013                                    2014-2020
Rehabilitation                              2007-2013                                    2014-2020
Upgrade                                     2007-2013   500 m Euro                       2014-2020   n.a.

Comments

The railway is very heavily used. Today, 100% of its capacity is used. Capacity is today 61
trains/day, which equals the current numbers of trains.

By 2008 the railway will be modernised. Capacity will be increased to 144 trains/day. In
addition, measures are aimed at increasing the speed of the corridor.




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COUNTRY REPORT                                                COUNTRY     LATVIA
Corridors:
Version                                   Date                                     Name of preparer
4                                         18 June 2007                             I. Kabashkin,
                                                                                   W. Segercrantz




National regulations

Heavy Goods Vehicles                                          Max speed   80 km/h
Max weight              Max axle weight          Max height                Max length                 Max width
40 ton                  10 ton                   4.0 m                     12 / 18,75m* m             2.55 m
Railways                                                      Railway gauge
                                                                              1 520 mm
General comments

Latvia has harmonized its vehicle standards with those of the EU. The only major difference
is the maximum axle weight of 10 tons, which falls short of the EU standard of 11.5 tons.

Latvia has the wide railway gauge as inheritance from Russia/Soviet Union. That does not
present a problem, because the only railway border crossing in the corridor is with Russia.
.



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CORRIDOR                              41
                                       Corridor ID                             ROAD
Route Terehovka/Rezekne – Riga –Ventspils                   Route Nos   E22 (National A6, A10 and A12)
Version                                Date                                    Name of preparer I. Kabashkin,
1                                      18 June 2007                            W. Segercrantz
Infrastructure
Length 525 km           (including           High quality road 493
                                       Road type                               Design speed
access to Riga)                        km, motorway 32 km
Tolled                                 Responsibility.                         No of lanes:   Road 2 lanes
No                                     National                                               Motorway 4 lanes
Pavement   Asphalt concrete            Urban areas   39km                      Accidents


Traffic
Existing, Yr                 Avg                            Max   33 145/ HGV 9%           Min 2 175/ HGV 31%
Forecast 2025                Avg                            Max   87 389                   Min 6 655
Share of HGVs in %           Avg                            Max   9%                       Min 26%
Internat’l HGV in %          Avg                            Max                            Min


 Investments (MEURO)
New construction                       2007-2013:
Rehabilitation           (Pavement     2007-2015: 45,71
rehabilit.)                            2007-2015: 1,85
Rehabiltation of bridges
Upgrade (HQR to MW)                    2007-2015: 30,62                        2014-2020




Comments

Existing E 22 road connects Latvia with Russia, more particularly Riga and Ventspils with
Moscow. The road corridor comprises three Latvian national roads: A10 (Ventpils-Riga), A6
(Riga-Jekabpils), and A 12 (Jekabpils-Rezekne/Terehova at the Russian border). In Riga
the route runs along the Riga southern bypass.

For most of its length the road is a high quality 2-lane road. There is a motorway (4-lane) in
the section east of Riga (47 km).

Traffic from Ventspils to the Riga suburbs is close to 6000 vehicles per day (13% HGV). In
the bypass of Riga the existing traffic exceeds 10 000 vehicles per day. Existing traffic in the
border stretch (Jekabpils - Russian border) is low, a little above 2 000 vehicles per day, but
the share of HGVs is quite high (23% to 31%).

Traffic growth is strong. The forecast for 2025 expects nearly tripling of traffic flow in most of
the road corridor, which makes the roads in the Riga area as bottlenecks.

The plans call for upgrading some road sections by 2015: approaches to Ventspils and the
Koknese-Jekabpils section of road.




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CORRIDOR                                  Corridor ID   42                       RAILWAY
                                                                 Route Nos:
Version                                   Date                                   Name of preparer         I. Kabashkin,
1                                         18 June 2007                           W. Segercrantz
Infrastructure
Length 456 / 424     km                   Rail type: Conventional                              and freight
                                                                                 Activity: Passenger
Number of tracks :                        Traction                               Voltage3000 DC (commuter
Single                                    Diesel                                 trains only)
Load gauge                                Signalling    standard:    Automatic   Degree of capacity utilisation
GB (Latvian)                              blocking
Max axle load 230   kN                    Max train length 850                   Max train weight 5500
Speed: 120   / 80

Traffic
Existing, Yr 2006             Trains/d:    Passenger    trains   Tons/yr                     TEU/yr
                              18/3
                              Freight trains
Forecast                      Trains/d                           Tons/yr                     TEU/yr



Investments (MEURO)
New construction                          2007-2013                              2014-2020
Rehabilitation                            2007-2013                              2014-2020
Upgrade                                   2007 – 2013   1760                     2014-2020


Comments

The Ventspils-Riga-Zilupe (Russian border) railway corridor has two routes: (1) a freight
route to Venstpils via Jelgava (456 km) and (2) passenger/freight route via Riga (424 km). It
is the main railway line from Latvia, particularly the seaports, to Moscow.

Railway has 2 tracks for most of its length. In the last 150 km towards the Russian border,
the railway has only a single track. It is diesel driven, excepting the commuter trains near
Riga.

The railway is built to heavy trains (5 500 tons) even if the allowable axle weight of 23 tons is
less than e.g. in Estonia.

The railway corridor has heavy freight traffic to the ports of Riga and Ventspils – 25 freight
trains per day. The sections leading from west and east to Riga have high passenger train
volumes.

Train controls are compatible with those of the Russian railways (RZD).

Considerable investments are planned covering almost the entire railway corridor.
Investments consist of construction of a second track in many sections, electrification of the
line and provision of GSM-R service troughout the Latvian section of the railway.
Construction will start in 2008.




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COUNTRY REPORT                                                 COUNTRY     LITHUANIA
Branchs:   5 and 6
Version                                    Date                                               A.Shakalis,
                                                                                    Name of preparer
1                                          5 October 2007                           W.Segercrantz




Heavy Goods Vehicles                                           Max speed   90 km/h
Max weight               Max axle weight          Max height                Max length                 Max width
40 ton                   115 KN                   4,0 m                     12 / 18,75m*               2,55 m
Railways                                                       Railway gauge
                                                                               1 520 mm
General comments

Lithuania has harmonized its vehicle standards with those of the EU.

Lithuania has the wide railway gauge as inheritance from Russia/Soviet Union. That does
not present a problem, because the only railway border crossings in the branch are with
Russia and Belarus, which also applies Russian/Soviet Union standards.




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BRANCH                              51
                                     Branch                                 ROAD
Route Klaipeda-Kaunas-Vilnius-Medinikai                    Route Nos
(Belarus border)                                           E 85
Version                              Date                                             A.Shakalis,
                                                                            Name of preparer
1                                    5 October 2007                         W.Segercrantz
Infrastructure
Length 339 km                        Road type  Motorway                    Design speed       120 km/h
Tolled No                            Responsibility National                No of lanes:   4
Pavement Asphalt                     Urban areas                            Accidents



Traffic
Existing, Yr                Avg                            Max   28 671                 Min
Forecast 2020               Avg                            Max                          Min
Share of HGVs in %          Avg                            Max                          Min
Internat’l HGV in %         Avg                            Max                          Min


Investments (MEURO)
New construction                     2006-2013                              2014-2020
Rehabilitation                       2007-2013                              2014-2020
Upgrade                              2007-2013     169                      2014-2020      121



Comments:

The road branch is Lithuania’s main internal road connecting the three largest cities of
Vilnius, Kaunas and Klaipeda, the port city. It also provides connection to/from Belarus and
Moscow in Russia.

The entire length of the road Klaipeda-Kaunas-Vilnius-Belarus border is a motorway. The
exception is in Vilnius, where the southern bypass road is under construction.

Traffic is high and growing.

Major investment projects in Lithuanian include upgrading of the road in the corridor
Klaipeda-Vilnius-LT/BY border.




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BRANCH                        61     Branch                                 ROAD
Route   Kaunas – Marianpole - Kybartai                    Route Nos
(Kaliningrad border)
Version                              Date                                             A.Shakalis,
                                                                            Name of preparer
1                                    5 October 2007                         W.Segercrantz
Infrastructure
Length 105 km                        Road type High quality road            Design speed    100 km/h
Tolled No                            Responsibility National                No of lanes:   2 lanes
Pavement Asphalt                     Urban areas                            Accidents



Traffic
Existing, Yr 2005           Avg                           Max   13 100                  Min
Forecast 2020               Avg                           Max                           Min
Share of HGVs in %          Avg                           Max                           Min
Internat’l HGV in %         Avg                           Max                           Min


Investments (MEURO)
New construction                     2006-2013                              2014-2020
Rehabilitation                       2007-2013                              2014-2020
Upgrade                              2007-2013     95                       2014-2020      70


Comments:

The road Kaunas-Kybartai is the second of the two main road connections from Lithuania to
the Kaliningrad region of Russia.

The road from Kaunas to Kybartai (at Kaliningrad border) is a 2-lane high quality road.

Major investment projects in Lithuanian include upgrading the road between Kaliningrad-
Kaunas-Vilnius.




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BRANCH                                    Branch ID   52                               RAILWAY
Route Kena   – Klaipeda                                         Route Nos:
Version                                   Date                                         Name of preparer A.Shakalis,
1                                         5 October 2007                               W.Segercrantz
Infrastructure
Length   412 km                           Rail type Conventional                       Activity freight   +passenger
Number of tracks 2                        Traction Diesel                              Voltage 25kV
Load gauge GC                             Signalling standard ALSN                     Degree of capacity utilisation
Max axle load: 225 kN                     Max train length:   850 m                    Max train weight

Speed: (1) Design 120 (2) Max 120    (3) Min     (4) Freight 80?


Traffic
Existing, Yr 2005             Trains/d:   55 max                Tons/yr   15,7 million             TEU/yr   25 600
Forecast 2015                 Trains/d                          Tons/yr   20 million               TEU/yr



Investments (MEURO)
New construction                          2007-2015                                    2014-2020
Rehabilitation                            2007-2013                                    2014-2020
Upgrade                                   2007-2013   427                              2014-2020   148

Comments

The railway is Lithuania’s main rail line connecting the eastern and western parts of the
country, more particularly Vilnius with the port of Klaipeda. The railway is also an important
transit branch for Belarus and Russia (Moscow). In addition, the railway serves as a
connection between the Baltic and Black Seas.

The railway has a fairly high freight volume, which is forecast to increase with time.

Major investment projects in Lithuanian include upgrading of the road in the corridor
Klaipeda-Vilnius-LT/BY border.

In addition, the Kena railway border station will be improved.




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BRANCH                                     Branch ID   62                         RAILWAY
Route; Kaisiadorys   - Kybartai                               Route Nos:
Version                                    Date                                   Name of preparer A.Shakalis,
1                                          5 October 2007                         W.Segercrantz
Infrastructure
Length:  125 km                            Rail typeConventional                  Activity freight   +passenger
Number of tracks 2                        Traction Diesel                         Voltage 25kV
Load gauge GC                             Signalling standard ALSN                Degree of capacity utilisation
Max axle load: 225 kN                     Max train length 850                    Max train weight

Speed: (1) Design 120 (2) Max 120    (3) Min (4) Freight 80?


Traffic
Existing, Yr 2005              Trains/d   28                  Tons/yr   17,3 million          TEU/yr

Forecast 2015                  Trains/d                       Tons/yr   19,5 million          TEU/yr



Investments (MEURO)
New construction                           2007-2015                              2014-2020
Rehabilitation                             2007-2013                              2014-2020
Upgrade                                    2007-2013   58                         2014-2020   92



Comments

The railway is the second of the two railway connections to Kaliningrad of Russia. This
railway is used to a large extent to transport Russian supplies to Kaliningrad. It also provides
the route to the Kaliningrad port.

Rail traffic is fairly high.

Major investment projects in Lithuanian include upgrading the railway between Kaliningrad-
Kaunas-Vilnius.




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COUNTRY REPORT                                                  COUNTRY     NORWAY
Corridors:   1, 8 and 9
Version                                     Date                                                  Norwegian Rail
                                                                                    Name of preparer
1                                           27.06.2007                              Administration




National regulations

Heavy Goods Vehicles                                            Max speed   80 km/h
Max weight                Max axle weight          Max height               Max length                 Max width
50 tons                   10 tons                  4,5 m                    18,75 m                    2,55 m
Railways                                                        Railway gauge
                                                                                1 435 mm
General comments

Heavy goods vehicle regulations in Norway conform to those of the EU. The main exception
is the maximum 10-ton axle weight. Currently, there are plans to allow larger vehicles, close
to Scandinavian sizes, to use selected sections of the main roads in Norway.

Track gauge is the European standard gauge, which does not present a problem at the
Swedish border. Norway has the only railway border crossings with Sweden.




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CORRIDOR                             Corridor ID   11                       ROAD
Route  Narvik – Bjornfjell (SWE border)           Route Nos E6 and E10
Version 1                         Date 27 June 2007                 Name of preparer Gunpet
Infrastructure
Length44 km                          Road type   Ordinary road              Design speed     80 km/h
Tolled No                                         National
                                     Responsibility                         No of lanes:    2
Pavement Asphalt                     Urban areas 1,5 km                     Accidents   4

Traffic (vehicles per day, AADT)
Existing, Yr 2006           Avg                           Max                           Min
Forecast 2020               Avg                           Max                           Min
Share of HGVs in %          Avg                           Max                           Min
Internat’l HGV in %         Avg                           Max                           Min


Investments (MEURO)
New construction                     2007-2013                              2014-2020
Rehabilitation                       2007-2013                              2014-2020
Upgrade                              2007-2013                              2014-2020



Comments

The road corridor in Norway is short, but still has two different stretches: E6 and E10.

E6, is the main national north-south route connecting all the main urban centres along the
long Norwegian coast. Traffic is low to moderate.

E10 is the east-west connection to/from Sweden over the mountains. Road is narrow (<8 m)
and has low traffic.

No major investments are planned on these roads. However, the condition of E6 is poor and
studies are underway for improvements. Also, on E10 studies of upgrading the road will be
carried out.




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CORRIDOR                                12   Corridor ID                             RAILWAY
Route  Narvik – Vassjaure (Swedish border)                          Route Nos:
Version                                      Date                                    Name of preparer Norwegian Rail
1                                            10.05.2007                              Administration
Infrastructure
Length 38,2                                  Rail type Conventional                  Activity: Passenger         and freight
Number of tracks 1                           Traction Electrified         Voltage 15 kV
Load   gauge:    U-gauge, P/C73,                         RTC/ATC/Line Degree of capacity utilisation
                                             Signalling standard:
P/C403                               Block – GSM-R                         80%
Max axle load: 30                    Max train length: 500                Max train weight: 6000
Speed: (1) Design 70 km/h (2) Max 130 km/h (3) Min n.a. (4) Freight 50 km/h


Traffic
Existing, Yr 2005                Trains/d   n.a.                    Tons/yr   n.a.               TEU/yr   n.a.
Forecast 2020                    Trains/d n.a.                      Tons/yr   n.a.               TEU/yr   n.a.


Investments (MEURO)
New construction                             2007-2013                               2014-2020
Rehabilitation                               2007-2013                               2014-2020
Upgrade                                      2007-2013                               2014-2020



Comments

The railway (Ofotbanen) is a part of the ore railway from Kiruna, Sweden to the Port of
Narvik. The railway has been built as a heavy freight line, but is also used by passenger
trains (15%).

Heavy ore train traffic is high on the railway. Its capacity utilisation is 80%.

Due to the private nature of railway traffic, no traffic data are publicly available.

There are no major investments planned for the railway.




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CORRIDOR                       Corridor ID 81                                     ROAD
Route Oslo – Riksgrens (Stockholm)                             Route Nos   E 18
Version   1                             Date   27 June 2007                       Name of preparer   Gunpet
Infrastructure
Length                                  Road    type       Motorway/High Design speed
91 km                                   quality road/Ordinary road       80-100 km/h
Tolled No                               Responsibility National          No of lanes: 2 or 4
Pavement Asphalt                        Urban areas 24 km                Accidents 8


Traffic (vehicles per day, AADT)
Existing, Yr 2005              Avg   11 600                    Max   29 000                   Min    5 000
Forecast 2020                  Avg                             Max                            Min
Share of HGVs in %             Avg                             Max                            Min
Internat’l HGV in %            Avg                             Max                            Min


Investments (MEURO)
New construction                        2007-2013      170                        2014-2020   360
Rehabilitation                          2007-2013                                 2014-2020
Upgrade                                 2007-2013                                 2014-2020



Comments

The E 18 road corridor is a part of the Nordic Triangle, the link between Oslo and
Stockholm.

Traffic is fairly high in the Oslo end. It gradually declines towards the border. However, the
border traffic is relatively high at 5 400 vehicles/day.

The road standard changes between motorway, high quality road and ordinary road. In both
ends the road standard is the lowest. The sections of motorway and high quality roads are
located in between. Speed limit is mainly 80 km/h, but in the motorway section it is 100
km/h.

Since the early 2000, there has been an extensive program to convert most of the road
length (70 km) into a motorway. The first motorway section (6 km) was opened to traffic in
2005. The program is under way and the completion will probably be after 2015. The speed
of construction depends on the national road budget and how it develops over the years.




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CORRIDOR                            82     Corridor ID                                   RAILWAY
Route Oslo – Konsvinger - Charlottenberg                           Route Nos:
(Swedish border)
Version                                    Date                                                        Norwegian Rail
                                                                                         Name of preparer
1                                          10.05.2007                                    Administration
Infrastructure
Length 143    km                           Rail type Conventional                        Activity: Passenger         and freight
Number of tracks 1            Traction Electrified                Voltage 15 kV
Load gauge:  P/C80, P/C410, U Signalling standard: Remote Traffic Degree of capacity utilisation
and       Multipurpose Wagon Control /D ATC/ Line Block           30-95%
gauge
Max axle load: 22,5                        Max train length: 600                         Max train weight:   3920
Speed: (1) Design   130 km/h   (2) Max   130 km/h      (3) Min   n.a.   (4) Freight   km/h

Traffic
Existing, Yr 2007              Trains/d   20-400                   Tons/yr    n.                     TEU/yr   n.a.
Forecast 2020                  Trains/d n.a.                       Tons/yr   n.a.                    TEU/yr   n.a.


Investments (MEURO)
New construction                           2007-2013                                     2014-2020
Rehabilitation                             2007-2013                                     2014-2020
Upgrade                                    2007-2013                                     2014-2020




Comments

The railway is the main rail connection between Southern Norway and Central Sweden,
particularly Oslo and Stockholm. It is located on the Nordic Triangle (TEN Priority Axis).

Near Oslo there is very heavy commuter traffic. Traffic and particularly passenger traffic
decreases towards the Swedish border and the share of freight trains increases. Capacity
utilisation changes considerably ranging between 95% near Oslo and 30% at the Swedish
border.

There are no major investments planned for the railway.




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CORRIDOR                 Corridor ID 91                                     ROAD
Route Oslo – Svinesund (SWE border)-                       Route Nos
                                                           E6
(Copenhagen)
Version 1                            Date   27 June 2007                    Name of preparer   Gunpet
Infrastructure
Length122 km                         Road type     Motorway                 Design speed    80-100 km/h
Tolled No                            Responsibility National                No of lanes:    4
Pavement Asphalt                     Urban areas   40 km                    Accidents   8

Traffic (vehicles per day, AADT)
Existing, Yr 2005           Avg   25 850                   Max   49 000                 Min    9 000
Forecast 2020               Avg                            Max                          Min
Share of HGVs in %          Avg                            Max                          Min
Internat’l HGV in %         Avg                            Max                          Min


Investments (MEURO)
New construction                     2007-2013                              2014-2020
Rehabilitation                       2007-2013                              2014-2020
Upgrade                              2007-2013                              2014-2020



Comments

The E 6 road corridor is a part of the Nordic Triangle, the link between Oslo, Southern
Sweden (Gothenburg) and Copenhagen.

Traffic is quite high over the entire length of the road. While traffic gradually declines
towards the border, the flow at the border is still high at 9 000 vehicles per day.

Road standard has been deficient due to an old 2-lane road, but it now improves rapidly.
About half of the road length is already a 4-lane motorway.

In early 2000s, a major motorway construction project has been underway on this road in
the second half of the road towards the Swedish border. By autumn 2008, an entirely new
motorway between Oslo and the border will be opened to traffic parallel to the old E6. The
last project will be a new Nostvedt tunnel (3,7 km), which will be opened to traffic in 2009.




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CORRIDOR                                  Corridor ID   92                      RAILWAY
Route Oslo   – Kornsjø (Swedish border)                        Route Nos:
Version                                   Date                                  Name of preparer: Norwegian Rail
1                                         10.05.2007                            Administration
Infrastructure
Length 169    km                      Rail type Conventional              Activity: Passenger and freight
Number of tracks 1-2                  Traction Electrified                Voltage 15 kV
Load gauge: P/C80, P/C410, U Signalling standard: Remote Traffic Degree of capacity utilisation
and Multipurpose Wagon Control /D ATC/ Line Block                         27-75%
gauge
Max axle load: 22,5                   Max train length: 600               Max train weight: 3920
Speed: (1) Design : 120-160 km/h (2) Max 120-160 km/h (3) Min n.a. (4) Freight km/h


Traffic
Existing, Yr 2007             Trains/d   12-226                Tons/yr   n.a.               TEU/yr   n.a.
Forecast 2020                 Trains/d n.a.                    Tons/yr   n.a.               TEU/yr   n.a.


Investments (MEURO)
New construction                          2007-2013                             2014-2020
Rehabilitation                            2007-2013                             2014-2020
Upgrade                                   2007-2013                             2014-2020




Comments

The railway is the main rail connection between Southern Norway and Southern Sweden,
particularly Oslo, Gothenburg and Copenhagen. It is located on the Nordic Triangle (TEN
Priority Axis).

Near Oslo there is heavy commuter traffic. Traffic and particularly passenger traffic
decreases towards the Swedish border and the share of freight trains increases. Capacity
utilisation changes considerably ranging between 75% near Oslo and 27% at the Swedish
border.

There are no major investments planned for the railway.




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ANALYTICAL SUPPORT FRAMEWORK TO MONITOR THE IMPLEMENTATION OF THE
INFRASTRUCTURE AND “SOFT” MEASURES PROPOSED BY THE HIGH LEVEL GROUP
COUNTRY REPORT                                                    COUNTRY     POLAND
Corridors:   7
Version                 2                     Date      29 October 2007                Name of preparer Andy   Sadlak




National regulations
Heavy Goods Vehicles                                              Max speed
Max weight                  Max axle weight          Max height                Max length             Max width
40 / 44 ton                 11.5 ton                 4.0 m                     18.75 (22.00) m        2.6 m
Railways                                                          Railway gauge
                                                                                  1 435 mm
General comments
HGV sizes and weights equal those of the EU. The Polish railway meets the European
standards with regard track gauge, but not for electric power supply and signalling.
Ministry of Transport (MoT) works on legislation revisions. The transport investment
financing procedures shall be more flexible. Project preparation procedures, especially land
acquisition, shall be streamlined to facilitate project scheduling. MoT harmonises railway
investments included in the Operational Program "Infrastructure and Environment" for
EURO 2012 with Ministry of Regional Development.
Ministry of Regional Development is responsible for co-ordination of strategical projects for
EURO 2012 included in the Operational Programs "Infrastructure and Environment" and
"Innovative Economy".


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CORRIDOR                              Corridor ID   71                         ROAD
Route  Świecko – Warszawa - Kukuryki                        Route Nos A2 / at present E30 or 2
Version 2                     Date 29 October 2007                           Name of preparer Andy     Sadlak
Infrastructure
Length   651 km                       Road type Motorway                     Design speed   A2: 130 km / h
Tolled    YES / Concessions /         Responsibility                         Width
State                                 Private / National                     A2: 2 x 2 lanes
Pavement                              Urban areas                            Accidents (causalities)
Asphalt                                                                      A2: 0.14 acc/km/y

Traffic (vehicles per day, AADT) A2
Existing, Yr 2006            Avg   12 740                   Max   25 400                 Min   9 440
Forecast 2020                Avg                            Max                          Min
Share of HGVs in %           Avg   A2: 27%                  Max                          Min
Internat’l HGV in %          Avg                            Max                          Min


Investments (MEURO)
New construction                      2007-2013     3 406                    2014-2020   579
Rehabilitation                        2007-2013                              2014-2020
Upgrade                               2007-2013   126                        2014-2020



Comments 1

At present, A2 motorway covers 252 km of the planned motorway (651 km):
• Poznań — Modła (149 km toll motorway opened between 2002 and 2004)
• Modła - Strykỏw (103 km toll motorway opened 2006)

The remaining sections run currently on E-30, which is a single carriageway road.

Planned A-2 motorway construction sections (BS GDDKiA 14.12.2006) are as follows:
• Świecko — Nowy Tomyśl (105 km 2007 - 2009)
• Konotopa (new section 94 km 2008 - 2010)
• Warszawa, wezeł Lubelski - Miedzyrzec Podlaski (new section 92 km 2011 - 2011)
• Kukuryki (new section 62 km after 2013)

The A2/E30 road is important mostly for domestic inter-urban and urban traffic. Traffic is
highest near and between Warsaw and Poznan. Cross-border and transit traffic is minor.

Minister of Transport on 18.01.07 sent to Autostrada Wielkopolska S.A proposal for new
implementation schedule for toll sections of A-2 motorway
• Nowy Tomyśl – Trzciel – May 2009
• Trzciel – Świecko – December 2009 / January 2010.




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Comments 2
In November 2004, the Warsaw Municipal Authorities agreed with Ministry of Infrastructure to
build two roads for the Warsaw A-2 stretch. S2 is the south bypass which will go from
Konotopa interchange, via Wlochy suburb, tunnel along Ursynow, and Wilanow, new bridge
over Vistula and forests of Wawer to Konik Nowy interchange. In September 2006, the
GDDKiA announced that it plans to build the Warsaw road sections using the PPP method.




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CORRIDOR                                  Corridor ID   72                         RAILWAY
Route Kunowice      - Terespol                                  Route Nos:E20   and C-E20
Version                                   Date   29 October 2007                   Name of preparer   Andy Sadlak
Infrastructure
Length E20    723 km              Rail type                      Activity Passenger and freight
       C-E20 174 km               Conventional                   traffic
Number of tracks 2                Traction Electric              Voltage DC 3000 V
Load gauge 1SM, 2SM, UIC B, Signalling           standard ALBS - Degree of capacity utilisation
GA, GB, GB+,GC                    automatic line block system,                          Up to 51 %
                                  SALBS - semiautomatic line
                                  block        system,     AWS -
                                  automatic warning system,
                                  RDSS - radio stop system
Max axle load 21 – 22.5 ton       Max train length 600 – 750 m   Max train weight
Speed: (1) Design 2002 - 70/160 km/h, 2020 up to 250 km/h (2) Max 160 km/h (3) Min 70 km/h
(4) Freight 40 km/h – 100 km/h

Traffic
Existing, Yr 2005             Trains/d   41 – 123               Tons/yr                        TEU/yr

Forecast 2020                 Trains/d                          Tons/yr                        TEU/yr



Investments (MEURO)
New construction                          2007-2013                                2014-2020
Rehabilitation                            2007-2013                                2014-2020
Upgrade                                   2007-2013     1 700                      2014-2020


Comments

The railway is a cargo/combined transport line in accordance with the AGTC agreement of
Geneva 01.02.9. It has the southern by-pass of Poznan (Poznan Staroleka - Swarzedz) and
southern and northern by-passes (Łowicz - Łukỏw) in Warsaw.

In December 2006, the MoT initiated the Rail Transport Master Plan. The National Strategic
Reference Framework 2007 – 2013 (Infrastructure and Environment Operational Programme
2007 – 2013) was adopted by the Council of Ministers in November 2006.

In the railway upgrading, alignments of the railways (E 20 and Cargo E 20 by pass of
Warsaw) are not going to change very much, even if the scale of upgrading of the rail
infrastructure will be intensive, as per the present plans until 2013. At present, the tracks are
modernised for speed of 160 km/h.

Railway plans according to the MoT (14.12.2006):
• E 20 Kunowice – Terespol (modernization completed 2006)
• E 20 Kunowice – Rzepiń (modernization 2007 – 2013 priority project)
• Poznań (modernization after 2013 priority project)
• Warszawa – Siedlce (no plans for further actions at present)
• Terespol (modernization 2007 till 2013 reserved project or after 2013)
• C-E 20 Łowicz - Łukỏw (modernization after 2013)




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BRANCH ANALYTICAL SUPPORT FRAMEWORK TO MONITOR THE IMPLEMENTATION OF THE
INFRASTRUCTURE AND “SOFT” MEASURES PROPOSED BY THE HIGH LEVEL GROUP


COUNTRY REPORT                                                 COUNTRY     RUSSIA
Branchs:   1, 2, 3, 4, 6 and 7
Version                                    Date                                     Name of preparer
1                                          22 August 2007                           A.Strijevsky,              E. Mahlin,
                                                                                    W. Segercrantz




National regulations

Heavy Goods Vehicles                                           Max speed   No special limit
Max weight               Max axle weight          Max height                Max length                 Max width
38 tons                  100 kN1                  4.0 m                     20 m
Railways                                                       Railway gauge
                                                                               1 520 mm
General comments
1
  In spring time special restriction might be in use on most of the network




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BRANCH                              11   Branch ID    ROAD
Fin-Rus: Finnish border(Lytta)-Kostamus- Route Nos
Kola road-St.Petersburg                  E102, Regional road
Version                                  Date                               Name of preparer
1                                        22 August 2007                     A.Strijevsky,
                                                                            W. Segercrantz
Infrastructure
Length                                   Road type:     Ordinary road / Design speed: 100 /120 km/h
942 km                                   High quality road
Tolled                                   Responsibility:   Regional   / Width: Pavement 7-16m,
No                                       Federal                        lanes 1+1 and 2+2
Pavement   Asphalt                       Urban areas: 30,3 km           Accidents: 346 with injuries


Traffic
Existing, Yr 2002              Avg                        Max       6656,   HGV      Min   2286, HGV 21%
                                                          26%
Forecast 2010                  Avg                        Max       7500,   HGV      Min   3500, HGV 24%
                                                          28%
Forecast 2020                  Avg                        Max       9000,   HGV      Min   5000, HGV 28%
                                                          32%
Internat’l HGV in %            No data

Investments (MEURO)
New construction                         2006-2013                          2014-2020
Rehabilitation                           2007-2013                          2014-2020
Upgrade                                  2007-2013    107,6                 2014-2020


Comments:

The road branch has two distinctly different sections:
• The section from Finnish – Russian border (Lytta) to the junction of St. Petersburg
   – Murmansk road (203 km) is an ordinary regional road. It has relatively low traffic
   volume. The road is paved (7,0 m) and its design speed is 100 km/h.
• The section from the junction at the St. Petersburg – Murmansk road to St.
   Petersburg (739 km) is federal road with a higher design standard (120 km/h).
   The road has mostly 1+1 lanes. In the approach to St. Petersburg the road has
   2+2 lanes. This road has higher traffic flows, particularly near St. Petersburg.




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BRANCH                                   12
                                          Branch ID                                  RAILWAY
Route Finnish border (Kivijärvi)-Petrozavodsk-                 Route Nos:
St.Petersbourg (Mga)
Version                                   Date                                                  E. Mahlin,
                                                                                     Name of preparer
1                                         22 August 2007                             W. Segercrantz
Infrastructure

Length: 905   km                          Rail type Conventional                                   + passenger2
                                                                                     Activity Freight
                                                                                 3
Number of tracks 21                       Traction Diesel and      Electrified       Voltage  DC3000V and 25kV
Load gauge                                Signalling standard:                       Degree of capacity utilisation
1T                                        Automatic block4                           46 – 87%5
Max axle load 22,5 tons                   Max train length 800 m                     Max train weight 5200     tons
Speed: (1) Design (2) Max (3) Min   (4) Freight
Maximum speeds are 80 – 120 km/h7
Traffic:
Existing, Yr 2005             Trains/d8                        Tons/yr8                           TEU/yr
                              6-10/ 30-39                      6,2-8,1/ 12,5-21,7
Forecast 2010                 Trains/d                         Tons/yr                            TEU/yr
                              8-10/ 39-45                      10,3/ 32,3-38,3
2020                          8-10/ 53-61                      11,1/ 47,6-55,2
2030                          8-10/ 58-65                      11,9/ 52,1-59,4

Investments (MEURO)
New construction                          2007-2013:                                 2014-2020:
Rehabilitation                            2007-2013                                  2014-2020
Upgrade                                   2007-2013:   150                           2014-2020:   275

Comments

Branch can be divided from the point of view of technical standards and traffic volumes into
two different sections:

1) The section Finnish border-Ledmozero has low traffic and freight volumes. On section
Ledmozero – Kochkoma there are freight traffic only. The railway has a single track and is
diesel-driven with a semi-automatic train traffic control system. Maximum speed is 80 km /h.

2) The section on the Murmansk route (Lietmajärvi – Volhovstroj) has both freight and
passenger traffic. About four quarters of the railway length has a double track. The single-
track section is located in the northern part, which presents the most critical point of the route
with 80% utilisation rate. This section of the railway is fully electrified and is under the
centralised train control system. The allowed speed is 100 km/h.

The major new construction/upgrading project consists of a second track on the single-track
section from Kotchkoma to Petrozavodsk. Completion of this project is estimated by 2015.
Additional investments include the upgrading of three stations and marshalling yards
(Kivijarvi, Volhovstroi, Babajevo) by 2015.




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BRANCH                            21Branch ID                           ROAD
Finnish border (Torfjanovka)-Vyborg-St. Route Nos
Petersburg-Moscow                       E 18, E 105
Version                             Date                                              A.Strijevsky,
                                                                        Name of preparer
1                                   22 August 2007                      E. Mahlin, W. Segercrantz
Infrastructure
Length    793 km                    Road type High   quality road       Design speed 120 km/h
Tolled                              Responsibility                      Width: sections 1+1 lanes, 3
No                                  Federal                             lanes and 2+2 lanes
Pavement   Asphalt                  Urban areas   202,3 km (?)                 1519 with injuries
                                                                        Accidents:


Traffic
Existing, Yr 2002                                       Max 91755,                   Min 6799,
                                                        HGV 31%                      HGV 27%
Forecast 2010               Avg                         Max 98500,                   Min 8500,
                                                        HGV 26%                      HGV 24%
Forecast 2020               Avg                         Max 105000,                  Min 10000,
                                                        HGV 22%                      HGV 22%
Internat’l HGV in %         Avg                         Max                          Min


Investments (MEURO) No data
New construction                    2006-2013   23                      2014-2020
Rehabilitation                      2007-2013                           2014-2020
Upgrade                             2007-2013   150+6                   2014-2020



Comments
The road branch Finnish border (Torfjanovka)-Vyborg-St. Petersburg-Moscow is
composed from two different road sections (Length of St. Petersburg section is
excluded):
1. “Scandinavian Road” from Finnish – Russian border to St. Petersburg (152 km).
This road has 1+1 lanes with widths 11 to 15m.
2. “Rossya Road” from St. Petersburg to Moscow (length 641 km). There are near
semi-motorway sections with 2+2 lanes with widths of 15 m. Other sections have 1+1
lanes (7,5m) and some sections 3 lanes (11 m).

Highest traffic volumes are near Moscow and in the St. Petersburg area.

Accidents with injured persons are as follows: Scandinavian Road 105 accidents,
Rossiya Road 1 414 accidents.

The main investments are the start of construction of the motorway Moscow-
St.Petersburg, and upgrading of the existing road. Smaller investments take place
between Finnish border-Vyborg



    St. Petersburg Ring Road
    The new Ring Road of St. Petersburg is not listed in the above figures for road
    branch 21. The eastern half of the Ring Road (64 km) is already partly open to
    traffic. In 2008 it will be completed providing a motorway-quality bypass (8 lanes) to
    the east of the city. The entire Ring Road (138 km) will be built by 2012. The total
    cost of the project is estimated at € 3,6 billion.


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BRANCH                                    Branch ID      22                           RAILWAY
Route Finnish border (Buslovskaya)-Vyborg-                      Route Nos:
St. Petersburg-Moscow
Version 1                                 Date    22 August 2007                                 E. Mahlin,
                                                                                      Name of preparer
                                                                                      W. Segercrantz
Infrastructure
Length                                    Rail    type    Conventional /high          Activity
760km                                     speed                                       Passenger + freight
Number of tracks Mostly   2               Traction Electrified          Voltage DC 3000
Load gauge                                Signalling Standard automatic Degree of capacity utilisation
1T                                        block                         52-89%
Max axle load 22,5                        Max train length 800          Max train weight 2600 - 4000
Speed: (1) Design (2) Max (3) Min   (4) Freight
Buslovskaya-Vyborg 130, Vyborg-Chudovo 160 and Chudovo-Moscow 200 km/h
Traffic
Existing, Yr 2005             Trains/d   20 - 122               Tons/yr   4,6 -34,5               TEU/yr   a)
2010                          26- 121                           0,9 – 55,4
2020                          30 - 123                          1,0 – 15,0
2030                          34 - 124                          1,0-17,0

Investments (MEURO)
New construction                          2007-2015                                   2014-2020
Rehabilitation                            2007-2015:                                  2014-2020
Upgrade                                            265 (Finnish border
                                          2006-2008:                                  2014-2020
                                          St. Petersb.) and 417
                                          (St.Petersb. – Moscow)

Comments
The route must be divided from the point of technical standards into two different sections:

1. Buslovskaya – St.Petersburg is a conventional railway, which has single-track sections.
Maximum speed of passenger trains is 130-160 km/h. Freight train traffic is also high (41-
50%). In the future, it is planned to redirect most of the freight traffic to the parallel route.
Until 2010, the section St. Petersburg – Vyborg has heavy freight flows, up to 55,4 million
tonnes.

2. St. Petersburg – Moscow section has a double track on the full length with the maximum
speed of 160 – 200 km/h. It can be classified as a high-speed railway. Traffic on this section
consists mostly of passenger trains (66-89%). Most of the conventional freight trains are
using parallel connections through Jaroslav or Velikye Luki. Special container trains can use
the railway at speeds of 120 km/h.

Main investments are connected with development of the high-speed traffic. Trains can run
at 160 km/h between St. Petersburg and the Finnish border, and up to 300-350 km/h
between St. Petersburg-Moscow, when the freight trains have been redirected to the new
parallel routes.




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BRANCH                              Branch ID    31                   ROAD
Route   Estonian border (Ivangorod)- St. Route Nos
Petersburg                               E-20
Version                             Date                              Name of preparer
1                                   22 August 2007                    A.Strijevsky,
                                                                      W. Segercrantz
Infrastructure
Length118 km                        Road type: High quality road      Design speed: 120   km/h
Tolled No                                        Federal
                                    Responsibility                    Width: 2    lanes
Pavement Asphalt                    Urban areas 31 km                 Accidents   71with injuries

Traffic
Existing, Yr 2002         Avg                         Max:8345,                   Min: 3656,
                                                      38% HGV                     43% HGV
Forecast 2010             Avg                         Max 10000,                  Min 4500,
                                                      32% HGV                     36% HGV
Forecast 2020             Avg                         Max 12500,                  Min 6000,
                                                      26% HGV                     32% HGV
Internat’l HGV in %       No data

Investments (MEURO) No investments declared
New construction                    2006-2013                         2014-2020
Rehabilitation                      2007-2013                         2014-2020
Upgrade                             2007-2013    26                   2014-2020


Comments

This Russian part of E-20 road is an ordinary road, which has in total of 31 km
locations in built-up areas. The most critical is the middle section (km 60 to km 138) of
which 28,2% is located in built-up areas. That issue is causing both safety and
environmental risks. As built up areas have speed limits, it will has economical impact
too. At the moment, no measures to rehabilitate the situation are planned on the
Russian side.

Traffic volumes increase and can be quite high near St. Petersburg.

The road has possible weight limits for HGV from km 60 till 149 in springtime.

According to recent information, are problems with the bridge over the Narva River.
The Estonian and Russian border is on the middle of the Narva River bridge. Views of
both sides on the technical condition of this bridge differ.

Investments are planned for upgrading the road connection to the Port of Ust Luga.




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BRANCH                                             32
                                           Branch ID                              RAILWAY
Route     Estonian border                 (Ivangorod)-St.     Route Nos:
Petersburg (Gatchina)
Version 1                                  Date    22 August 2007                            E. Mahlin,
                                                                                  Name of preparer
                                                                                  W. Segercrantz
Infrastructure
Length 111    km                           Rail type Conventional                 Activity: Passenger       and freight
Number   of   tracks   1 (near St.         Traction                               Voltage
Petersburg 2)                              Diesel
Load gauge                                 Signalling  Standard: automatic, Degree of capacity utilization:
1-T                                        semi automatic block and 60-78%
                                           automatic block
Max axle load 22,5                         Max train length 800             Max train weight 5000
Speed: (1) Design (2) Max (3) Min    (4) Freight
Max speed of passenger trains 120km/h
Traffic
Existing, Yr 2005              Trains/d   23 -25              Tons/yr   22-23,6               TEU/yr   a)
Forecast 2010                  Trains/d 16-33                 Tons/yr   11,8 -32,1            TEU/yr

2020                           13-34                          10,1 – 36,6
2030                           11-36                          8,5- 38,5


Investments (MEURO) No investments have been planned
New construction                           2007-2015                              2014-2020
Rehabilitation                             2007-2013                              2014-2020
Upgrade                                    2007-2013                              2014-2020


Comments

The St. Petersburg-Tallinn railway is a traditional route for the Russian exports. Even if the
railway is diesel driven it has a high capacity and does not have any major obstacles.

Recently, the Russian side has forecasted an essential decrease of rail freight transport from
Russia to Estonia. At present, there are 4 passenger trains and 19 freight trains crossing the
border. The Russian forecast for 2030 are 3 passenger and 8 freight trains, which is based
on the Russian Transportation Strategy. No investments have been planned to develop this
rail branch in sections leading to Estonia.

At the same time, there is foreseen an essential increase of freight volume in the section
Gatchina –Veimarn due to the development of Port of Ust-Luga.




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BRANCH                              Branch ID    41                   ROAD
Route      Latvian border-Novosokolniki-              Route Nos
Moscow
Version                             Date                                           A.Strijevsky,
                                                                      Name of preparer
1                                   22 August 2007                    W. Segercrantz
Infrastructure
Length: 420 km                      Road type: High quality road      Design speed: 120km/h
Tolled: No                          Responsibility Federal            Width: 2 to 6 lanes
Pavement Asphalt                    Urban areas: 7,4 km               Accidents: 273 with injuries


Traffic3
Existing, Yr 2002                                     Max 69787,               Min 3945,
                                                      HGV 32%                  HGV 43%
Forecast 2010             Avg                         Max 72000,               Min 4250,
                                                      HGV 26%                  HGV 36%
Forecast 2020             Avg                         Max 74000,               Min 4430,
                                                      HGV 21%                  HGV 37%
Internat’l HGV in %       No data

Investments (MEURO) No investments declared
New construction                    2006-2013                         2014-2020
Rehabilitation                      2007-2013                         2014-2020
Upgrade                             2007-2013    3                    2014-2020


Comments:

There are three types of roads in this road branch:
• The first section starting from Moscow Ring road has 3+3 lanes with a total road
   width of 45m (18 km)
• The second section has 2+2 lanes (79 km)
• The third section towards the Latvian border has 2 lanes (1+1).(305 km)

Traffic decreases toward Latvia. Very higher traffic volumes can be found in sections
approaching Moscow.

There are only minor investments for upgrading two intersections on the route.




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BRANCH                               42  Branch ID                               RAILWAY
Route Latvian border– Novosokolniki-Velikie                  Route Nos:
Luki-Moscow
Version                                  Date                                               E. Mahlin,
                                                                                 Name of preparer
1                                        22 August 2007                          W. Segercrantz
Infrastructure
Length 580   km                          Rail type Conventional             Activity Freight +passenger
                  2
Number of tracks 1                       Traction Diesel    / Electrified1  Voltage DC 3000V
Load gauge 1T                            Signalling standard Semi automatic Degree of capacity utilisation 55% -
                                         block3                             85%
Max axle load 22,5 T                     Max train length 800               Max train weight 3000 -3500 T
Speed: (1) Design (2) Max (3) Min   (4) Freight
Max speed 100 km /h
Traffic
Existing, Yr 2005             Trains/d 17   - 24             Tons/yr   9,3 – 17,4 milj.      TEU/yr)
                                                             t
Forecast 2010                 Trains/d 14   - 25             Tons/yr   11 - 16               TEU/yr

2020                          12- 39                         8,8 – 23,9
2030                          13-44                          8,5- 26


Investments (MEURO)
New construction                         2007-2015                               2014-2020
Rehabilitation                           2007-2013                               2014-2020
Upgrade                                  2007-2013                               2014-2020   12,6

Comments

The railway is another traditional Russian export route, which has no operational problems. It
is mainly diesel driven, as the track is electrified only for the first 101 km from Moscow. It is
also mostly single-track. Only the section Shakhovskaya – Moscow (28km) has a double
track. From Rzhev to Moscow there is centralized traffic control.

Number of passenger trains between Russia and Latvia is estimated to stay on low level – 2
trains daily. Freight volumes are estimated to decrease, as is determined in the Russian
transport strategy.

Long-term investments include upgrading the signalling and train control system.




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                                      of the infrastructure and “soft” measures proposed by the High Level Group
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BRANCH                              Branch ID    61                        ROAD
Route      Lithuania -Kaliningrad                       Route Nos   E-28
Version                             Date                                               A.Strijevsky,
                                                                           Name of preparer
1                                   22 August 2007                         W. Segercrantz
Infrastructure
Length    142 km                    Road type: High quality road                            km/h
                                                                           Design speed : 120
Tolled     No                       Responsibility Federal                 Width: Both 1+1 lanes and
                                                                           2+2 lanes
Pavement   Asphalt                  Urban areas: 22,1   km                 Accidents 63 with injuries


Traffic
Existing, Yr 2002          Avg                          Max 5917                    Min 5227
                                                        HGV 22%                     HGV 18%
Forecast 2010              Avg                          Max 9500                    Min 7500
                                                        HGV 26%                     HGV 20%
Forecast 2020              Avg                          Max 12500                   Min 9000
                                                        HGV 28%                     HGV 24%
Internat’l HGV in %        No data

Investments (MEURO) No investments declared
New construction                    2006-2013                              2014-2020
Rehabilitation                      2007-2013    26                        2014-2020
Upgrade                             2007-2013                              2014-2020


Comments

The road is one of the two main connections between Lithuania and Kaliningrad, as
well as to/from the mainland Russia.

The current road has differing road standards:
• 19 km from Kaliningrad has a road width of 10m (1+1 lane)
• 13 km has a width of 15 m (2+2 lanes)
• 110 km has the pavement width 7,5 m (1+1 lanes)

About 21 km of the road will be rehabilitated.




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                                                                                       Appendix 1: Country Reports


BRANCH                                      Branch ID    62                             RAILWAY
Route Lithuania      -Kaliningrad                                 Route Nos:
Version                                     Date                                        Name of preparer E. Mahlin,
1                                           22 August 2007                              W. Segercrantz
Infrastructure
Length 151   km                             Rail type Conventional                      Activity Passenger      and freight
Number of tracks 2   (Double)               Traction Diesel                             Voltage
Load gauge 1T                               Signalling     standard    semi       –     Degree of capacity utilisation 74-88%
                                            automatic block
Max axle load 22,5 T                        Max train length 800 m                      Max train weight 5000   T
Speed: (1) Design (2) Max (3) Min     (4) Freight
Max speed 100 km/h
Traffic
Existing, Yr (2005)             Trains/d   24-30                  Tons/yr   16,8 – 16,6             TEU/yr

Forecast 2010                   Trains/d 33-37                    Tons/yr   23,4-23,8               TEU/yr

2020                            36-37                             27,9-26,5
2030                            39-40                             30,5-28,5


Investments (MEURO)
New construction                            2007-2015    19,4                           2014-2020
Rehabilitation                              2007-2013                                   2014-2020
Upgrade                                     2007-2013    4,4                            2014-2020


Comments

As the railway connection of Kaliningrad region and the ports are connected with Russian
hinterland through Lithuania there are development projects under implementation:
• Upgrade of the signalling system from semi-automatic to full automatic block system on
    the section Kaliningrad –Nesterov
• Construction of new railway border crossing station “Nesterov”, project is under way




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BRANCH                              Branch ID     71                       ROAD
Route     Belarus – Smolensk - Moscow                   Route Nos   E 30
Version                             Date                                   Name of preparer A.Strijevsky,
1                                   22 August 2007                         W. Segercrantz
Infrastructure
Length    441 km                    Road type: High quality road           Design speed: 120km/h
Tolled     No                       Responsibility: Federal                Width: 15m (1+1)
                                                                           22.25m (2+2)
Pavement   Asphalt                  Urban areas   49,4 km                  Accidents 564 with injuries


Traffic
Existing, Yr 2002           Avg                         Max 81953                  Min 7712
                                                        HGV 22%                    HGV48%
Forecast 2010               Avg                         Max 84000                  Min 16000
                                                        HGV 18%                    HGV 36%
Forecast 2020               Avg                         Max 86500                  Min 20500
                                                        HGV 16%                    HGV 24%
Internat’l HGV in %         No data

Investments (MEURO)
New construction                    2006-2013                              2014-2020
Rehabilitation                      2007-2013                              2014-2020
Upgrade                             2007-2013     217                      2014-2020


Comments

The road is one of Russian main road branches and links Russia with Belarus and
Central Europe in general. Design standard of the road is high.

The road also has moderate to high traffic volumes. Higher traffic volumes are found
in sections nearer to Moscow.




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                                         of the infrastructure and “soft” measures proposed by the High Level Group
                                                                                          Appendix 1: Country Reports


BRANCH                               72      Branch ID                                 RAILWAY
Route Belarus-Smolensk-Moscow (Kubinka)                            Route Nos:
Version                                      Date                                      Name of preparer E. Mahlin,
1                                            22 August 2007                            W. Segercrantz
Infrastructure
Length 429 km                                Rail type Conventional                    Activity Passenger+freight
Number of tracks 2                           Traction Electrified                      Voltage 25kV    and DC 3000V
Load gauge 1T                                Signalling    standard:       Automatic                             44% -
                                                                                       Degree of capacity utilisation
                                             block                                     73%2
Max axle load 22,5T                          Max train length 1000     m               Max train weight 5000   - 45003
Speed: (1) Design (2) Max (3) Min      (4) Freight
Maximum speed 140 km/h
Traffic4
Existing, Yr 2005                Trains/d   45-67                  Tons/yr 23,3-44,5               TEU/yr
Forecast 2010                    Trains/d   55-81                  Tons/yr 32,8-40,5               TEU/yr
Forecast 2020                    Trains/d   62-89                  Tons/yr 37,1-43,1
Forecast 2030                    Trains/d   67-92                  Tons/yr 40,0-45,0


Investments (MEURO)
New construction                             2007-2013                                 2014-2020
Rehabilitation                               2007-2013                                 2014-2020
Upgrade                                      2002-2006:   15,3                         2007-2015 362


Comments

The railway Moscow-Belarus is part of Pan-European Branch II and an important
connection between Russia, Belarus and Central European countries. The railway
has different characteristics:
• Traction power of 25 kV is used from the Belorussian border to Vjazma (250
   km). From Vjazma to Moscow the railway has DC 3000 V.
• The maximum train weight 4500 t is allowed between Vjazma and Moscow.

Higher train traffic volumes are in sections near Moscow. Capacity utilization is also
higher also due to Moscow commuter traffic.

The only investment project on the Russian side of the branch is related to
increasing the speed of passenger trains from the present 140 km/h to the level of
160 km/h. The project was started in 2002 and estimated year of completion is 2015.




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                                          of the infrastructure and “soft” measures proposed by the High Level Group
                                                                                           Appendix 1: Country Reports
ANALYTICAL  SUPPORT FRAMEWORK TO MONITOR THE IMPLEMENTATION OF THE
INFRASTRUCTURE AND “SOFT” MEASURES PROPOSED BY THE HIGH LEVEL GROUP


COUNTRY REPORT                                                     COUNTRY     SWEDEN
Corridors:   1
Version                  1                     Date      18 June 2007                  Name of preparer   Krister Palo,
                                                                                       Mikael Erikson




National regulations

Heavy Goods Vehicles                                               Max speed   80 km/h
Max weight                   Max axle weight          Max height               Max length             Max width
60 ton                       11,5 ton                 4.5 m                    25,25 m                2.6 m
Railways                                                           Railway gauge
                                                                                   1 435 mm
General comments

HGV sizes and weights are the same or exceed those of the EU.

Track gauge is the European standard gauge. The gauge difference is at the border with
Finland.




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                                     of the infrastructure and “soft” measures proposed by the High Level Group
                                                                                      Appendix 1: Country Reports


CORRIDOR                                 1
                                      Corridor ID                ROAD
Route Haparanda-Töre-Gällivare-Riksgränsen     Route Nos E4 and E10
Version 1                      Date 18 June 2007                 Name of preparer Krister Palo
Infrastructure
Length                                Road type    Ordinary road             Design speed
Tolled   No                           Responsibility National                No of lanes:   2
Pavement  Asphalt                     Urban areas 23 km                      Accidents   39

Traffic (vehicles per day, AADT)
Existing, Yr 2006            Avg 1 400 – 4 000            Max   11 400                   Min 1 300
Forecast 2020                Avg 1 700 – 5 000            Max   16 000                   Min 1 600
Share of HGVs in %           Avg 13                       Max   16                       Min 6
Internat’l HGV in %          Avg                          Max                            Min


Investments (MEURO)
New construction                      2007-2013 none                         2014-2020 none
Rehabilitation                        2007-2013 none                         2014-2020 none
Upgrade                               2007-2013 none                         2014-2020 none



Comments

The road corridor has two quite different stretches: E4 and E10.

E4, between Töre (junction E4/E10) and Haparanda at the Finnish border, is Sweden’s main
north-south road, which has been built to a high, uniform standard of an ordinary 2-lane road
paved with asphalt. In Haparanda the road has a street-like character.

The road’s traffic at 4 000 vehicles per day is rather low. Only few locations near urban
settlements have higher volumes, most notably in Haparanda. Traffic is estimated to grow
23% by 2020.

E10, between Riksgränsen at the Norwegian border and Töre, has more variable
characteristics when it rises from the coast up to the mountains at the Norwegian-Swedish
border. The road gets narrower in the higher altitudes. However, the entire road is paved
and can carry heavy axle loads. Traffic volume of about 1 400 vehicles per day on E10 is
low. Estimated traffic growth is 23%.

The Swedish Road Administration has no major investments planned for the road. There
are, however, two design projects under way:
• E4, between Töre and Haparanda. Design studies on three separate road sections have
    a goal of installing a mid-barrier on the road to avoid head-on collisions. Total length of
    the three sections is 45 kilometres. As of today, funding for construction has not been
    guaranteed. Funding for these types of measures is decided on annual basis.
• E10 in Kiruna. New road investments have to be made due to the mining industry’s
    expansion. Study is currently under way.




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CORRIDOR                                    Corridor ID   1                    RAILWAY
Route  Riksgränsen-Boden-Haparanda            Route Nos:

Version 1                     Date 18 June 2007                                Name of preparer   Mikael Eriksson
Infrastructure
Length   604 km                             Rail type   Conventional           Activity Mainly freight, also
                                                                               passengers
               1
Number of tracks                            Traction Electric / Diesel         Voltage 16 000
Load gauge  GC /                                              Swedish ATP /
                                            Signalling standard                Degree of capacity utilisation
Swedish C                                   manual dispatching
Max axle load 250 - 300 kN                  Max train length 750 m             Max train weight   8 500 tons
Speed: (1) Design   140   (2) Max (3) Min   70 (4) Freight

Traffic
Existing, Yr                     Trains/d                         Tons/yr                  TEU/yr

Forecast 2020                    Trains/d                         Tons/yr                  TEU/yr



Investments (MEURO)
New construction                            2007-2013                          2014-2020
Rehabilitation                              2007-2013                          2014-2020
Upgrade                                     2007-2013                          2014-2020


Comments

The railway corridor consists of two very distinct railways: (1) the high-duty ore railway
between Boden and Riksgränsen at the Norwegian border, and (2) an old, low volume freight
railway Boden-Haparanda up to the Finnish border.

(1) The ore railway was first built by the mining company LKAB for hauling ore to the Atlantic
    Port of Narvik, but also to the Luleå port on the Baltic Sea. The railway is one of Europe’s
    high capacity railways when it comes to carrying capacity. Maximum train weights of the
    ore trains, up to 8 500 tons, are nearly three times those that are standard maximums of
    European railways. Today, 25-40% of the trains are for passengers. The ore railway is
    electrified.

Investments: The railway experiences capacity problems due to high ore train traffic. A
program has been launched to lengthen the meeting sites to 750 m. The program is gradually
being implemented.

(2) The railway between Boden and Haparanda is an old railway, which has low usage. The
    current condition of the railway is also poor. E.g. the train dispatching system is still
    manual. Today, the railway is only for freight. Driving power is diesel.

Investments: The railway will be rebuilt between Kalix-Haparanda and upgraded between
Boden-Kalix. The works consist of electrification, new ERTMS, increasing axle weight to 25
tons, and capacity increase with a provision of more frequent sites for passing.




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                                           Appendix 2: Basic Road and Rail Parameter and Performance Data



Appendix 2: Basic Road and Rail Parameter and Performance Data

ROADS

ROAD PERFORMANCE BY BRANCH

LEGENDS

 V/C                               <0.99
                                   1.00-1.50
                                   >1,50

 Speed limit                       > 80 km/h
                                   <80 km/h

 Time loss                         None
                                   0.01-20 min
                                   >20 min

                                                     8
 Accident rate                     <20 accidents/10 vehicle-km
                                                     8
                                   20-40 accidents/10 vehicle-km
                                                   8
                                   >40 accidents/10 vehicle-km

 Environment                       < 5 km of urban sections
                                   > 5 km of urban sections
                                   >10% of link length
                                   >25% of link length

 Bearing capacity                  max 11,5 tons
                                   max 10 tons




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                                                  Appendix 2: Basic Road and Rail Parameter and Performance Data
BRANCH 1          Narvik-St. Petersburg

ROAD PERFORMANCE


            ROADPARAMETER                  TRAFFIC DATA, FORECASTS       CAPACITY           SPEED/DELAY ANALYSIS                SAFETY   ENV    Bearing
                                                                                             Actual   Time              Total                    cap,
Sect                                                                                Speed
                                  Length                    of which %                         car  lost per Incident   time    Accident Urban tons/axle
 ion Start node     End node               year     AADT                   V/C       limit,
                                   km                         of HGV                         speed, truck, loss, min    loss,     rate    km
  ID                                                                                 km/h
                                                                                              km/h    min                min
NORWAY - Narvik
1-2 Narvik      E6/E10             17,3                                              80                                                  15,0     10,0
1-1 E6/E10      Bjørnfjell          27                                               80                                                  87 %     10,0
NO-SE border
157 Gällivare   Riksgränsen        133     2006      1300      15         0,10       90      88                                   20,6    9,0
                                           2020      1600      16         0,12       90      88                                           7%
                                           2040      2000      18         0,16       90      87
123 Töre          Gällivare        175     2006      1450      16         0,11       90      88                                   13,0    6,0
                                           2020      1800      17         0,14       90      87                                           3%
                                           2040      2300      18         0,19       90      86
 43 Töre          Månsbyn                  2006      3770      14         0,22       90      86
                                           2020      4600      15         0,27       90      85
                                           2040      6000      16         0,35       90      83
 59 Månsbyn       Kalix            26      2006      4350      13         0,25       90      85                                   2,4     3,0
                                           2020      5400      13         0,31       90      84                                          12 %
                                           2040      6800      15         0,40       90      82
 35 Kalix         Karlsborg        18      2006      4700      11         0,26       90      85                                   13,0    4,0
                                           2020      5800      11         0,33       90      83                                          22 %
                                           2040      7400      13         0,42       90      82
102 Karlsborg     Haparanda        36      2006      3370      11         0,19       90      86                                   15,8
                                           2020      4100      12         0,23       90      85
                                           2040      5300      13         0,30       90      84
150 Haparanda      Haparanda        2      2006     11400      5          0,60       50      42       0,1      0,1       0,2      12,0    1,0
                     border                2010     15000      5          0,79       50      40       0,2      0,2       0,3             50 %
                                           2025     16000      6          0,85       50      39       0,2      0,2       0,4
SE-FI border      Haparanda-Tornio
567 Tornio        Kemi           26        2005      8170       8         0,11       120     115                                  13,4    2,0
                                           2020      8900                  0,12      120     115                                          8%
                                           2030      9200                  0,13      120     115
                                           2040      9200                  0,13      120     115
631 Kemi          Kemi              4      2005      7100      14          0,41      80       75      0,0      0,0       0,0      77,2
                                           2020      7700                  0,44      80       74      0,1      0,1       0,1
                                           2030      8000                  0,46      80       74      0,1      0,1       0,2
                                           2040      8000                  0,46      80       74      0,1      0,1       0,2
297 Kemi          Ojakylä          76      2005      6000      15          0,35      120     116
                                           2020      6500                  0,38      120     115
                                           2030      6700                  0,39      120     115
                                           2040      6700                  0,39      120     115
313 Ojakylä       Oulu             32      2005     15000       7          0,20      120     112                                  3,4
                                           2020     18900                  0,25      120     110
                                           2030     20100                  0,27      120     110
                                           2040     20700                  0,28      120     109
567 Oulu          Mieslahti        146     2005      2000      11          0,11      120     119                                  9,4
                                           2020      2500                  0,14      120     118
                                           2030      2700                  0,15      120     118
                                           2040      2800                  0,16      120     118
571 Mieslahti     Vartius          98      2005      500       10          0,03      100     100                                  11,2
                                           2020      600                   0,03      100     100
                                           2030      700                   0,04      100     100
                                           2040      700                   0,04      100     100
FI-RU border      Vartius-Lytta
 3c km 1          km 203           203     2007     2286       21          0,14      90      88                                   39,6     3      10,0
                                           2010     3500       24          0,22      90      87                                           1%
                                           2020     5000       28          0,33      90      86
 3b km76          km752            676     2007     3945       42          0,29      90      86                                   18,6    25      10,0
                                           2010     5000       36          0,35      90      86                                           4%
                                           2020     6500       30          0,43      90      85
 3a    Sankt     km 76             63      2002     6656       26          0,11      90      85                                   64,0    2,3     10,0
    Petersburg                             2010     7500       28          0,12      90      84                                           4%
      km 13                                2020     9000       32          0,15      90      82
RUSSIA - St. Petersburg




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                                          of the infrastructure and “soft” measures proposed by the High Level Group
                                                   Appendix 2: Basic Road and Rail Parameter and Performance Data
BRANCH 2            Heksinki - Moscow

ROAD PERFORMANCE


          ROADPARAMETER                   TRAFFIC DATA, FORECASTS CAPACITY              SPEED/DELAY ANALYSIS                SAFETY   ENV     Bearing
                                                                                         Actual  Time               Total                     cap,
Sec                                                         of which            Speed
                                 Length                                                    car  lost per Incident   time    Accident Urban tons/axle
tion   Start node    End node              year    AADT       % of       V/C     limit,
                                   km                                                    speed, truck, loss, min    loss,     rate    km
 ID                                                           HGV                km/h
                                                                                          km/h    min                min
FINLAND - Helsinki
 77 Highway 4     Porvoo          36       2005    17700      12         0,25    120     119                                  8,6
    (Helsinki)                             2020    23500                 0,33    120     119
                                           2030    25700                 0,36    120     119
                                           2040    26200                 0,37    120     119
456 Porvoo          Koskenkylä    24       2005    17700      12         0,25    120     119                                  12,9
                                           2020    23500                 0,33    120     119
                                           2030    25700                 0,36    120     119
                                           2040    26200                 0,37    120     119
130 Koskenkylä      Kotka         55       2005    8100       18         0,49    100      87                                  9,8
                                           2020    10800                 0,65    100      87
                                           2030    11700                 0,70    100      87
                                           2040    12000                 0,72    100      87
398 Kotka           Hamina        19       2005    18300      15         0,27    120     119                                  15,8
                                           2020    24300                 0,35    120     119
                                           2030    26500                 0,39    120     119
                                           2040    27100                 0,39    120     119
195 Hamina          Vaalimaa      40       2005    5000       24         0,32    100      87                                  21,9    5,0
                                           2020    6700                  0,42    100      87                                         13 %
                                           2030    7300                  0,46    100      87
                                           2040    7400                  0,47    100      87
FI-RU Border
 9i km 149          km 200        51       2002    9 769      63       0,83      90      80                                   7,1     3,0     10,0
                                  51       2010    12 500     46       0,94      90      78                                           6%
                                  51       2020    14 000     34       0,96      90      78
9h km 138        km 149           11       2002    13 789     64       1,17      90      75                                   1,8     5,0     10,0
   Vyborg bypass                  11       2010    15 000     48       1,15      90      76                                          45 %
                                  11       2020    18 000     36       1,26      90      74       0,1      0,1       0,2
9g St. Petersburg km 138          90       2002    6 799      27       0,44      90      84                                   40,7    1,0     10,0
   km 48                          90       2010    8 500      24       0,54      90      83                                           1%
                                  90       2020    10 000     22       0,62      90      82
St. Petersburg
 9f km 532          km 570         38      2002    15 270     36       0,53      90       73      0,9      0,9       1,7      92,1    42,0    10,0
                                   38      2010    17 500     32       0,59      90       71      1,7      1,7       3,4             100 %
                                   38      2020    20 000     28       0,65      90       69      2,6      2,6       5,2
9e km 501           km 532         31      2002    10 857     67       0,94      90       78                                  25,2    1,3     10,0
                                   31      2010    13 500     54       1,08      90       77                                          4%
                                   31      2020    15 000     42       1,10      90       76
9d km 194           km 501        307      2002    18 141     50       0,35      90      107                                  17,0   62,0     10,0
                                  307      2010    22 500     42       0,41      90      105                                         20 %
                                  307      2020    24 000     36       0,42      90      105
9c km 158           km 194        36       2002    15 763     61       0,66      90       77                                  39,6    6,0     10,0
                                   36      2010    18 500     48       0,71      90       76                                         17 %
                                   36      2020    22 000     36       0,77      90       75
9b km 50            km 158        108      2002    30 548     43       0,56      90      100                                  38,1   37,0     10,0
                                  108      2010    35 500     36       0,62      90       98                                         34 %
                                  108      2020    40 000     28       0,65      90       96
9a Moscow,          km 50          21      2002    91 755     31       1,54      90       29     26,5     26,5      52,9      21,6    9,0     10,0
   km 29                           21      2010    98 500     26       1,58      90       27     30,6     30,6      61,2             43 %
                                   21      2020   105 000     22       1,63      90       24     35,8     35,8      71,6
Moscow




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                                          of the infrastructure and “soft” measures proposed by the High Level Group
                                                   Appendix 2: Basic Road and Rail Parameter and Performance Data
BRANCH 3             Tallinn - St. Petersburg

ROAD PERFORMANCE

            ROADPARAMETER                 TRAFFIC DATA, FORECASTS      CAPACITY         SPEED/DELAY ANALYSIS        SAFETY ENV Bearing
                                                                                          Actual Time Inci- Total                   cap,
Secti                                                       of which              Speed
                                 Length                                                     car lost per dent time Accident Urban tons/axle
 on     Start node    End node            year     AADT       % of       V/C       limit,
                                   km                                                     speed, truck, loss, loss,   rate   km
 ID                                                           HGV                 km/h
                                                                                           km/h   min    min min
ESTONIA - Tallinn
631a VÄO          MAARDU          5,6     2006     28660      16         0,42      110    104                                        10,0
                                          2010     28940      11         0,41             105
                                          2020     35720       9         0,49             102
                                          2035     41670       8         0,57             99
631b MAARDU          KIIU         21      2006      9650      18         0,14      110    114                        12,2            10,0
                                          2010     10100      13         0,14             114
                                          2020     12470      11         0,17             113
                                          2035     15000       9         0,21             112
632a KIIU            LIIAPEKSI    15      2006      9650      22         0,15      110    114                        13,2            10,0
                                          2010      6990      13         0,10             116
                                          2020      8650      11         0,12             115
                                          2035     10060      10         0,14             114
632b LIIAPEKSI       VIITNA       19      2006      4870      25         0,08      110    116                        8,9             10,0
                                          2010      5260      13         0,08             116
                                          2020      6500      11         0,09             116
                                          2035      7560      10         0,10             115
632c VIITNA          JÕHVI        84,7    2006      4720      25         0,30      90     86                         2,1             10,0
                                          2010      4590      18         0,27      90     87
                                          2020      5600      15         0,33      90     86
                                          2035      6500      14         0,38      90     85
611a JÕHVI           TOILA         14     2006     9 100      17         0,54      90     83                         68,8            10,0
                                   14     2010      8 360     14         0,48      90     84
                                   14     2020     10 260     11         0,58      90     83
                                   14     2035     11 900     10         0,66      90     82
611b TOILA           SILLAMÄE     14,2    2006      4 870     28         0,32      90     86                         39,6    4,0     10,0
                                          2010      4 600     20         0,28      90     86                                28 %
                                          2020      5 550     17         0,33      90     86
                                          2035      6 400     14         0,37      90     85
612a SILLAMÄE        NARVA        24,9    2006      4 870     24         0,31      90     86                         42,9    4,0     10,0
                                  24,9    2010      3 600     20         0,22      90     87                                16 %
                                  24,9    2020      4 360     16         0,26      90     87
                                  24,9    2035      5 020     14         0,29      90     86
612b NARVA CITY- ESTONIA -         3,5    2006     10000                           50     28     2,9    2,9   5,9            3,5     10,0
     BORDER      RUSSIA            3,5    2010     10000                           50     28     2,9    2,9   5,9           100 %
                                   3,5    2020     10000                           50     28     2,9    2,9   5,9
EE - RU border
 6c km 138           km 149       11      2002     3 656      43        0,27       90     87                         6,8     2,0     10,0
                                          2010      4 500     36        0,31       90     86                                18 %
                                          2020      6 000     32        0,41       90     85
 6b km 60            km 138       78      2002     4 964      44        0,37       90     85                         26,2   22,0     10,0
                                          2010      6 000     36        0,42       90     85                                28 %
                                          2020      7 500     32        0,51       90     84
 6a Sankt            km 60        29      2002      8 345     38        0,59       90     83                         37,4    7,0     10,0
    Petersburg                    29      2010     10 000     32        0,68       90     82                                24 %
                                  29      2020     12 500     26        0,80       90     80
RUSSIA - St. Petersburg




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                                            of the infrastructure and “soft” measures proposed by the High Level Group
                                                     Appendix 2: Basic Road and Rail Parameter and Performance Data
BRANCH 4             Ventspils - Riga - Moscow

ROAD PERFORMANCE

               ROADPARAMETER                 TRAFFIC DATA, FORECASTS        CAPACITY               SPEED/DELAY ANALYSIS             SAFETY   ENV     Bearing
                                                                                                 Actual Time Incide Total                  cap,
Secti                                                            of which                Speed
                                   Length                                                          car lost per nt   time Accident Urban tons/axle
 on Start node         End node               year     AADT        % of        V/C        limit,
                                     km                                                          speed, truck, loss, loss,  rate    km
 ID                                                                HGV                   km/h
                                                                                                  km/h   min    min min
LATVIA - Ventspils
A95 Ventspils    Priedaine           168      2005      5670        13         0,32          90         86                                    5       10,0
                                     168      2025     14822        15         0,86          90         79                                   3%
A95 Priedaine        Babite           6       2005     10435        11         0,15          90         114
                                              2025     27642        19         0,42          90         105
A95 Babite           Riga            15       2005     33145         9         0,46          90         103                                    15     10,0
                                     15       2025     87389         9         1,20          90         50    6,1     6,1   12,2             100 %
Latvia - Riga
A95 Babite           Skulte           4       2005     10755        18         0,16          90         114                                           10,0
                                              2025     26340        15         0,38          90         106
AS4 Skulte           Berzpils        13       2005      6520        20         0,40          90         85                                            10,0
                                     13       2025     11705        18         0,70          90         81
IA     Kekava        Berzpils        13       2005     6405         24         0,40          90         85                                            10,0
                                     13       2025     12862        19         0,78          90         80
I      Salaspils     Kekava          9        2005     11380        24         0,72          90         81                                            10,0
                                     9        2025     27605        29         1,82          90         67    0,8     0,8    1,7
AS4 Salaspils        Ogre            22       2005     17790        13         0,25          90         110                                    7      10,0
                                              2025     29988        21         0,46          90         103                                  32 %
AS4 Ogre             Jekabpils       109      2005     10230        18         0,61          90         82                                     8      10,0
                                     109      2025     19086        29         1,26          90         74    0,9     0,9    1,7             7%
AS4 Jekabpils        Rezekne         102      2005      2640        23         0,17          90         88                                     4      10,0
                                              2025      6970        29         0,46          90         84                                   4%
AS4 Rezekne          Terehova        64       2005      2175        31         0,15          90         88                                            10,0
                                              2025      6655        26         0,43          90         85
LV - RU border
7с    km 115         BORDER          305      2002      3945        43         0,29          90         86                            24,6    4       10,0
                     WITH                     2010      4250        36         0,30          90         86                                   1%
                     LATVIA, km               2020      4430        27         0,29          90         86
7b     km 36         km 115          79       2002     19308        28         0,32          90         108                           18,1    1       10,0
                                              2010     22000        22         0,34          90         107                                  1%
                                              2020     23500        18         0,35          90         107
7a     MOSCOW, km 36                 18       2002     69787        32         0,79          90         92                            14,0    2,4     10,0
       km 18                                  2010     72000        26         0,77          90         92                                   13 %
                                              2020     74000        21        0,76           90         93
RUSSIA - Moscow




BRANCH 5              Klaipeda - Vilnius - Minsk

ROAD PERFORMANCE

               ROADPARAMETER                TRAFFIC DATA, FORECASTS       CAPACITY                SPEED/DELAY ANALYSIS              SAFETY    ENV    Bearing
                                                                                              Actual       Time             Total                     cap,
Sec                                                            of which               Speed
                                  Length                                                        car       lost per Incident time    Accident Urban tons/axle
tion    Start node     End node             year     AADT        % of       V/C        limit,
                                    km                                                        speed,       truck, loss, min loss,     rate    km
 ID                                                              HGV                  km/h
                                                                                               km/h         min              min
LITHUANIA - Klaipeda
    Medininkai    Klaipeda         338,9      2005     28671         15        0,42    120         105                                                 11,5
                                              2010     33238         15        0,48    120         102
                                              2020     44668         15        0,65    120          96
LT - BY border
4b km 58              BORDER W        32                                                                                                       2       11,5
                                                                                                                                             6%
4a     Minsk          km 58           90      2006      5970         24        0,38    90          85                                         11       11,5
                                              2010      7000         26        0,45    90          84                                        12 %
                                              2020      8500         28        0,56    90          83
BELARUS - Minsk




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                                       of the infrastructure and “soft” measures proposed by the High Level Group
                                                Appendix 2: Basic Road and Rail Parameter and Performance Data
BRANCH 6          Kaliningrad - Kaunas

ROAD PERFORMANCE

       ROADPARAMETER                TRAFFIC DATA, FORECASTS     CAPACITY          SPEED/DELAY ANALYSIS                  SAFETY    ENV   Bearing
                                                                                   Actual     Time              Total                    cap,
Sec                                                  of which              Speed
                   End     Length                                                    car    lost per Incident   time    Accident Urban tons/axle
tion Start node                     year     AADT      % of       V/C       limit,
                   node      km                                                    speed,    truck, loss, min   loss,     rate    km
 ID                                                    HGV                 km/h
                                                                                    km/h       min               min
RUSSIA - Kaliningrad
5a Kaliningrad, km27        19      2002      5917     22         0,37      90       85                                   29,2    0,1     10,0
   km8                      19      2010      9500     26         0,61      90       82                                           1%
                            19      2020     12500     28         0,82      90       80
5b   km27         km40      13      2002      5560     17         0,08      90      116                                   22,7            10,0
                                    2010      7500     20         0,11      90      115
                                    2020     10500     24         0,17      90      113
5c   km 40        km 150    110     2002      5227     18         0,31      90       86                                   21,4    22      10,0
                                    2010      7500     20         0,46      90       84                                          20 %
                                    2020      9000     24         0,57      90       83
RU - LT border
     Kaunas    Kybartai    104,7    2005     13093     15         0,76      100     90                                                    11,5
                                    2010       0       15         0,88      100     89
                                    2020       0       15         1,19      100     85
Lithuania - Kaunas




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                                              of the infrastructure and “soft” measures proposed by the High Level Group
                                                       Appendix 2: Basic Road and Rail Parameter and Performance Data
BRANCH 7              Berlin - Warsaw - Minsk - Moscow

ROAD PERFORMANCE

                 ROADPARAMETER                         TRAFFIC DATA, FORECASTS       CAPACITY          SPEED/DELAY ANALYSIS                SAFETY    ENV    Bearing
                                                                                                        Actual    Time             Total                     cap,
Sec                                                                       of which              Speed
                                              Length                                                      car    lost per Incident time    Accident Urban tons/axle
tion    Start node            End node                 year     AADT        % of       V/C       limit,
                                                km                                                      speed,    truck, loss, min loss,     rate    km
 ID                                                                         HGV                 km/h
                                                                                                         km/h      min              min
GERMANY - Berlin
433 Dreieck      AS Müllrose                           2005     29 900      24         0,47      130     103                                                 11,5
    Spreeau                                             or      43 600                 0,69      130      95
                                                       2015     37 000      45         0,69      130      95
                                                        or      45 000                 0,84      130      90
433 AS Müllrose       AS Frankfurt (Oder) -            2005     27 700      23         0,43      130     104                                                 11,5
                      Mitte                             or      30 500                 0,48      130     102
                                                       2015     38 000      38         0,67      130      96
                                                        or      47 000                 0,83      130      90
433 AS Frankfurt      Bundesgrenze                     2005     16 500     40,9        0,30      130     109                                                 11,5
     (Oder)-Mitte     Frankfurt Oderbrücke             2015     19 000      63         0,40      130     105
DE - PL border
A2 Swiecko            Nowy Tomyśl              105     2005     15000      0,41        1,09      90       76
     (D/PL)                                            2010     17389      41 %        1,26      90       74      0,9      0,9      1,7
                                                       2020     23370      43 %        1,72      90       68      11,4     11,4    22,8
A2 Nowy Tomyśl Poznan                          52      2005      9674      53 %        0,19              112
                                                       2010     10300      33 %        0,18              113
                                                       2020     13100      34 %        0,22              111
A2 Poznan             Poznan (Krzesiny)        13      2005     24598      34 %        0,42              104
   (Komorniki)                                         2010     29100      29 %        0,48              102
                                                       2020     43500      35 %        0,75               93
A2 Poznan             Wrzesnia                 37      2005     11795      48 %        0,23              111
                                                       2010     13700      30 %        0,23              111
                                                       2020     20200      31 %        0,34              107
A2 Wrzesnia           Konin (Modla)            48      2005     14057      42 %        0,26              110
                                                       2010     15000      31 %        0,25              110
                                                       2020     22000      32 %        0,37              106
A2 Konin (Modla) Strykow (A1)                  105     2005     14000      0,10        0,78      90       80
                                                       2010     13000      10 %        0,18              113
                                                       2020     26800      19 %        0,41              105
A2 Strykow (A1)       Warszawa (Konotopa)      80      2005      9000      0,26        0,58      90       83
                                                       2010    10433,47    26 %        0,67      90       82
                                                       2020     14022      24 %        0,89      90       79
A2 Warszawa (w. Siedlce                        101     2005     12000      0,21        0,74      90       81
   Lubelska)                                           2010    13911,29    0,21        0,86      90       79
                                                       2020    18695,61    21 %        1,15      90       76
A2 Siedlce            Terespol (PL/BY)         95      2005      6000      0,25        0,38      90       85
                                                       2010    6955,644    0,25        0,44      90       84
                                                       2020    9347,804    25 %        0,60      90       83
BY - PL border
2e BORDER        BORDER WITH                   610     2006     6090        35         0,11      120     115                                         13,0    11,5
     WITH RUSSIA POLAND                                2010     6500        33         0,11      120     115                                         2%
                                                       2020     7500        28         0,12      120     115
RU - PL border
2d km 385             BORDER WITH              72      2002     7712        48         0,15      120     114                                 16,3    6,0     10,0
                      BELARUS, km 457                  2010     16000       36         0,28      120     109                                         8%
                                                       2020     20500       24         0,32      120     108
2c     km 96          km 385                   289     2002     11416       42         0,21      120     112                                 20,3    24      10,0
                                                       2010     18000       37         0,32      120     108                                         8%
                                                       2020     22000       28         0,36      120     107
2b     km 37          km 96                    59      2002     23714       38         0,42      120     104                                 33,5   11,0     10,0
                                                       2010     25500       33         0,43      120     104                                        19 %
                                                       2020     34000       26         0,55      120     100
2a     MOSCOW,        km 37                    21      2002     81953       22         1,27      120      44      11,8     11,8    23,7      18,3    8,4     10,0
       km 16                                           2010     84000       18         1,26      120      45      11,3     11,3    22,6             40 %
                                                       2020     86500       16         1,27      120      44      11,8     11,8    23,6
RUSSIA - Moscow




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                                          of the infrastructure and “soft” measures proposed by the High Level Group
                                                   Appendix 2: Basic Road and Rail Parameter and Performance Data
BRANCH 8            Oslo - NO/SE border (Stockholm)

ROAD PERFORMANCE

           ROADPARAMETER                   TRAFFIC DATA, FORECASTS     CAPACITY          SPEED/DELAY ANALYSIS                SAFETY    ENV   Bearing
                                                                                          Actual    Time             Total                    cap,
Sec                                                         of which              Speed
                                  Length                                                    car    lost per Incident time    Accident Urban tons/axle
tion   Start node    End node              year     AADT      % of       V/C       limit,
                                    km                                                    speed,    truck, loss, min loss,     rate    km
 ID                                                           HGV                 km/h
                                                                                           km/h      min              min
SE - NO border
2-1 Riksgrensen     Ørje            6,6    2005     5400      15         0,31      80       76                                 1,7     1,8     10,0
                                    6,6    2010     6260      15         0,36      80       75                                        27 %
                                    6,6    2020     8413      15         0,49      80       74       0,1      0,1     0,2
2-2 Ørje            Melleby        14,9    2005     5000      17         0,30      90       86                                 0,3             10,0
                                   14,9    2010     5797      17         0,34      90       86
                                   14,9    2020     7790      17         0,46      90       84
2-3 Melleby         Momarken         7     2005     7000      19         0,42      80       75                                 1,9      1      10,0
                                     7     2010     8115      19         0,49      80       74       0,1      0,1     0,2              7%
                                     7     2020     10906     19         0,66      80       72       0,3      0,3     0,5
2-4 Momarken        Krosby         13,4    2005     8500      17         0,13      100     115                                 2,8      7      10,0
                                   13,4    2010     9854      17         0,15      100     114                                        53 %
                                   13,4    2020     13243     17         0,20      100     112
2-5 Krosby          Knapstad         8     2005     14000     13         0,20      100     112                                 2,1     3,9     10,0
                                     8     2010     16230     13         0,23      100     111                                        49 %
                                     8     2020     21812     13         0,31      100     108
2-6 Knapstad        Akershus         6     2005     12600     14         0,73      80       71       0,3      0,3     0,6      1,8             10,0
                    grense           6     2010     14607     14         0,84      80       69       0,4      0,4     0,8
                                     6     2020     19631     14         1,13      80       66       0,7      0,7     1,3
2-7 Østfold grense Vinterbro       17,5    2005     9700      12         0,55      80       73       0,4      0,4     0,7      1,6      3      10,0
                                   17,5    2010     11245     12         0,64      80       72       0,6      0,6     1,1             17 %
                                   17,5    2020     15113     12         0,86      80       69       1,1      1,1     2,3
2-8 Vinterbro       Oslo grense     8,6    2005     19000     10         1,05      80       67       0,8      0,8     1,7      0,6             10,0
                                    8,6    2010     22027     10         1,22      80       65       1,1      1,1     2,2
                                    8,6    2020     29602     10         1,64      80       59       1,8      1,8     3,6
2-9 Akershus        Bispelokket     8,9    2005     29000     10         1,61      80       60       1,8      1,8     3,6      3,6     7,8     10,0
    grense          (x rv 190)      8,9    2010     33620     10         1,87      80       57       2,3      2,3     4,6             88 %
                                    8,9    2020     45182     10         2,51      80       49       3,9      3,9     7,7
NORWAY - Oslo




BRANCH 9            Oslo - NO/SE border (Copenhangen)

ROAD PERFORMANCE

           ROADPARAMETER                   TRAFFIC DATA, FORECASTS     CAPACITY          SPEED/DELAY ANALYSIS                SAFETY    ENV   Bearing
                                                                                          Actual    Time             Total                    cap,
Sec                                                         of which              Speed
                                  Length                                                    car    lost per Incident time    Accident Urban tons/axle
tion   Start node    End node              year     AADT      % of       V/C       limit,
                                    km                                                    speed,    truck, loss, min loss,     rate    km
 ID                                                           HGV                 km/h
                                                                                           km/h      min              min
SE - NO border
1-1 Svinesund       Svingenskog    4,5     2005     9000      18         0,13      90      114                                 1,8             10,0
                                           2010     10434     18         0,16      90      114
                                           2020     14022     18         0,21      90      112
1-2 SvingenskogenÅrum              18      2005     15000     14         0,22      100     112                                 5,1             10,0
                                           2010     17390     14         0,25      100     110
                                           2020     23370     14         0,34      100     107
1-3 Årum            Åsgård         15,3    2005     18000     14         0,26      100     110                                 6,2      6      10,0
                                           2010     20867     14         0,30      100     109                                        39 %
                                           2020     28044     14         0,40      100     105
1-4 Åsgård          Akershus gre 24,7      2005     23000     15         0,33      100     107                                 6,7     16      10,0
                                           2010     26664     15         0,39      100     106                                        65 %
                                           2020     35834     15         0,52      100     101
1-5 Østfold grense Vinterbro       30,9    2005     26500     14         0,38      100     106                                 14,3     4      10,0
                                           2010     30721     14         0,44      100     104                                        13 %
                                           2020     41287     14         0,60      100      98
1-6 Vinterbro       Assurtjern     5,5     2005     26000     13         0,37      90      106                                 9,1     0,8     10,0
                                           2010     30142     13         0,43      90      104                                        15 %
                                           2020     40508     13         0,58      90       99
1-7 Assurtjern      Oslo grense     5      2005     30800     11         0,43      90      104                                 15,9            10,0
                                           2010     35706     11         0,50      90      102
                                           2020     47986     11         0,67      90       96
1-8 Akershus grensAlnabru          18      2005     49000     10         0,68      80       95                                 35,3   12,7     10,0
                                   18      2010     56806     10         0,79      80       92                                        71 %
                                   18      2020     76342     10         1,06      80       69       1,2      1,2     2,3
NORWAY - Oslo




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                                  of the infrastructure and “soft” measures proposed by the High Level Group
                                           Appendix 2: Basic Road and Rail Parameter and Performance Data
RAILWAYS

RAILWAY PERFORMANCE BY BRANCH

LEGEND

 Track gauge                                      1435 mm
                                                  1520 mm
                                                  1524 mm

 Axle load                                        22,5 tons
                                                 < 22,5 tons

 Power supply                                  AC15000-16000
                                                 AC25000
                                                  Diesel
                                                 DC3000

 Maximum speed                                   > 100 km/h
                                                 <100 km/h

 Capacity utilisation                               <70%
                                                   70-85%
                                                   85-99%
                                                   > 100%




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                  The Northern Transport Axis - Pilot for the analytical support framework to monitor the implementation
                                           of the infrastructure and “soft” measures proposed by the High Level Group
                                                    Appendix 2: Basic Road and Rail Parameter and Performance Data
BRANCH 1               Narvik-St. Petersburg

RAILWAY PERFORMANCE


                                                  RAILPARAMETER                                                     TRAFFIC DATA AND FORECAST            CAPACITY   Capac.
Sect                                                                   Number                                                                            Trains/d   utilis. %
                                                                                    Axle Train     Power     Max         passenger   freigth
 ion      Start node                   End node                 Length   of   Gauge                                 year                       Mton/yr
                                                                                    load weight    supply   speed          trains     trains
  ID                                                                   Tracks
NORWAY - Narvik
    3 Narvik           Swedish Border Bjørnfjell/(Vassijaure)     38,2    1    1435   30   6000 AC15000      50                                 16,0                   80
NO - SE border
   30 Boden            Haparanda                                  160     1    1435   25         Diesel     70                                  1,0
   46 Boden            Kiruna                                     444     1    1435   30   8500 AC16000     140                                 7,6
   46 Kiruna           Riksgränsen                                        1    1435   30   8500 AC16000     140                                 16,0
SE - FI border
 389 Tornio            Laurila                                     19     1    1524   23   2700   AC 25000 120      2006     2         13        0,8       50          30
 132 Laurila           Oulu                                       112     1    1524   23   2700   AC25000 140       2006    20         15        1,9       50          70
 205 Oulu              Kontiomäki                                 166     1    1524   23   2700   AC25000 120       2006    11         17        4,9       50          56
 490 Kontiomäki        Vartius                                     94     1    1524   23   2300   AC25000 60…80     2006     0         7         3,6       50          14
FI - RU border
8.1 Kivijarvi          Ledmozero                                  123     1    1520   23   5200    Diesel    80     2005     2          8       8,1         16        62
                                                                                                                    2010     2          8       10,3        16         62
                                                                                                                    2020     2          8       11,1        16         63
                                                                                                                    2030     2          8       11,9        16         63
8.2   Ledmozero        Kochkoma                                   127     1    1520   23   5200    Diesel    80     2005     0          6       6,2         8         77
                                                                                                                    2010     0          8       10,3        8         103
                                                                                                                    2020     0          8       11,1        8         100
                                                                                                                    2030     0          8       11,9        8         100
8.3   Kochkoma         Medvezhya Gora                             147    1…2   1520   23   5200 AC25000     100     2005    17         13       12,5        34        87
                                                                                                                    2010    19         20       32,3        34        113
                                                                                                                    2020    20         33       47,6        34        156
                                                                                                                    2030    21         37       51,3        34        171
8.4   Medvezhya Gora Petrozavodsk                                 155    1…2   1520   23   5200 AC25000     100     2005    18         14       13,8        40         80
                                                                                                                    2010    20         20       33,3        40        100
                                                                                                                    2020    21         33       48,8        40        135
                                                                                                                    2030    22         37       52,1        40        148
8.5   Petrozavodsk     Svir                                       115     2    1520   23   5200 AC25000     100     2005    20         16       19,4        71         51
                                                                                                                    2010    23         22       36,0        71         64
                                                                                                                    2020    24         36       52,8        71         85
                                                                                                                    2030    25         40       57,8        71         92
8.6   Svir             Lodeinoe Pole                               45     2    1520   23   5200   DC3000    100     2005    20         16       19,4        71        51
                                                                                                                    2010    23         22       36,0        71         64
                                                                                                                    2020    24         36       52,8        71         85
                                                                                                                    2030    25         40       57,8        71         92
8.7   Lodeinoe Pole    Volkhovstroi                               118     2    1520   23   5200   DC3000    100     2005    21         18       21,7       115        34
                                                                                                                    2010    23         22      38,3        115         39
                                                                                                                    2020    24         37       55,2       115        53
                                                                                                                    2030    25         40       59,4       115        57
8.8   Volkhovstroy     Saint-Petersburg(Mga)                       75     2    1520   23   6000   DC3000    100     2005    36         53       75,9       125        71
                                                                                                                    2010    39         75       98,3       125        91
                                                                                                                    2020    40         73      108,2       125        90
                                                                                                                    2030    41         74      116,0       125        92
RUSSIA - St. Petersburg




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BRANCH 2              Heksinki - Moscow

RAILWAY PERFORMANCE


                                        RAILPARAMETER                                           TRAFFIC DATA AND FORECAST              CAPACITY   Capac.
Secti                                           Number                                                                                 Trains/d   utilis.
                                                             Axle Train        Power      Max       passenger freigth
 on     Start node        End node       Length   of   Gauge                                   year                   Mton/yr                       %
                                                             load weight       supply    speed        trains   trains
 ID                                             Tracks
FINLAND - Helsinki
 366 Helsinki         Pasila                6     9      1524   22,5   2700   AC25000     200    2006        200        16      1,4      High
                                                                                                 2010                   18      1,6
                                                                                                 2025                   22      1,9
 372 Pasila           Kerava               29     4      1524   22,5   2700   AC25000     200    2006        133        16      1,4      High
                                                                                                 2010                   18      1,6
                                                                                                 2025                   22      1,9
 803 Kerava           Hakosilta            65     2      1524   22,5   2700   AC25000     220    2006        56         4       0,3      200        30
                                                                                                 2010                   31      2,3                 43
                                                                                                 2025                   33      2,5                 45
 279 Hakosilta        Kouvola              72     2      1524   22,5   2700   AC25000     140    2006        47         23      5,1      200        35
                                                                                                 2010                   24      5,3                 35
                                                                                                 2025                   26      5,7                 36
 328 Kouvola          Kouvola               3     2      1524   22,5   2700   AC25000     140    2006        47         23      6,8      200        35
                                                                                                 2010                   18      5,3                 32
                                                                                                 2025                   19      5,7                 33
 347 Kouvola          Luumäki              59     2      1524   22,5   2700   AC25000     140    2006        26         61     10,1      200        44
                                                                                                 2010                   68     11,2                 47
                                                                                                 2025                   69     11,5                 48
 196 Luumäki          Vainikkala           32     1      1524   22,5   2700   AC25000     120    2006         8         27     6,8        50        70
                                                                                                 2010        11         35      8,7                 91
                                                                                                 2025        12         36      9,1                 96
FI - RU border
2.1 Buslovskaya       Vyborg               28     1      1520   22,5   3000   DC3000      130    2005        10         10      7,7       38        52
                                                                                                 2010        11         15     12,3       38        68
                                                                                                 2020        12         18      15        38        79
                                                                                                 2030        14         20      17        38        89
2.2   Vyborg          Saint-Petersburg     143   1…2     1520   22,5   4000   DC3000      160    2005        48         34     34,5      137        60
                                                                                                 2010        58         49     55,4      137        78
                                                                                                 2020        50         8       5,3      137        42
                                                                                                 2030        50         8        5       137        42
RUSSIA - St. Petersburg
2.3 Saint-Petersburg Chudovo               109    2      1520   22,5   2600   DC3000     160     2005        89         13     8,9       142        72
                                                                                                 2010         93        4      0,9       142        68
                                                                                                 2020         86        4       1        142        63
                                                                                                 2030         85        4       1        142        63
2.4   Chudovo         Bologoe              201    2      1520   22,5   2600   DC3000     200     2005        83         8      5,3       138        66
                                                                                                 2010         86        4      1,1       137        65
                                                                                                 2020         73        4      1,2       137        56
                                                                                                 2030         73        4      1,2       137        56
2.5   Bologoe         Moscow               279    2      1520   22,5   2600   DC3000      200    2005        114        8      4,6       137        89
                      (Povarovo)                                                                 2010        117        4      1,3       137        88
                                                                                                 2020        119        4      1,6       137        90
                                                                                                 2030        120        4      1,5       137        91
RUSSIA - Moscow


BRANCH 3           Tallinn - St. Petersburg

RAILWAY PERFORMANCE


                                   RAILPARAMETER                                                TRAFFIC DATA AND FORECAST             CAPACITY    Capac.
Secti                          Number                                                                                                 Trains/d    utilis.
                                            Axle Train                  Power      Max       passenger freigth                                      %
 on Start node End node Length   of   Gauge                                             year                   Mton/yr
                                            load weight                 supply    speed        trains   trains
 ID                            Tracks
Tallinn - Estonia
  1 Kopli        Lagedi   15     2     1520  32   5500                 Diesel   70 2006                 18         7          6,1        71         35
                                                                     (DC3000)        2010               21         7          6,6        71         39
  2   Lagedi      Tapa             63      2     1520    32     5500   Diesel 120/90 2006               18         32         38        125         40
                                                                     (DC3000)        2010               21         37        43,6       125         46
  3   Tapa        Narva           132      1     1520    32     5500   Diesel 120/90 2006                3         28         25         44         70
                                                                     (DC3000)        2010                5         30        25,9        44         80
EE-RU Border
 4 Ivangorod Veimarn               37      1     1520    22,5   5000    Diesel     120    2005          4          19         22        38          60
                                                                                          2010          4          12        11,8       38          42
                                                                                          2020          3          10        10,1       38          34
  5   Veimarn     Saint-           74     1…2    1520    22,5   5000    Diesel     120    2005          5          20        23,6       32          78
                  Petersburg                                                              2010          5          27        32,1       32         100
                  (Gatchina)                                                              2020          4          30         36        32         106
St. Petersburg

Note: (DC3000) is used for commuter trains in Estonia.
Note: Max. Speed 120/90 is for parrengers/freight




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BRANCH 4              Ventspils - Riga - Moscow

RAILWAY PERFORMANCE


                                      RAILPARAMETER                                          TRAFFIC DATA AND FORECAST      CAPACITY   Capac.
Secti                                           Number                                                                      Trains/d   utilis.
                                                             Axle Train     Power     Max       passenger freigth                        %
 on     Start node        End node       Length   of   Gauge                               year                   Mton/yr
                                                             load weight    supply   speed        trains   trains
 ID                                             Tracks
LATVIA - Ventspils
  1 VENTSPILS         TUKUMS              108     2    1520   23     5500   Diesel    80    2005     0     17,76              39         45
                                                                                            2007     0      25                39         64
 2   TUKUMS           JELGAVA             56      2    1520   23     5500   Diesel    80    2005     0     16,9               29         59
                                                                                            2007     0      21                29         72
 3   JELGAVA          KRUSTPILS           138     2    1520   23     5500   Diesel    80    2005     0     16,71              37         45
                                                                                            2007     0      23                37         62
 18 TUKUMS            RIGA                33    1…2    1520   23     5000   Diesel    80    2005    38     0,72               62         62
                                                                                            2007    42       6                62         77
 6   RIGA             KRUSTPILS           129     2    1520   23     6000   Diesel    80    2005    34     19,26              64         83
                                                                                            2007    34      27                64         95
 7   KRUSTPILS        REZEKNE             95      1    1520   23     5500   Diesel    80    2005     6     11,91              45         40
                                                                                            2007     6      23                45         64
 8   REZEKNE          ZILUPE-State bor    59      1    1520   23     4900   Diesel    80    2005     6     7,61               30         46
                                                                                            2007     6      15                30         70
LV - RU border
 4.1 Posin            Novosokolniki       126     1    1520   22,5   3500   Diesel    100   2005     4       13     9,3        22        78
                                                                                            2010     4       10     11         22        64
                                                                                            2020     4       8      8,8        22        55
                                                                                            2030     4       7      8,5        22        50
4.2 Novosokolniki     Velikie Luki        29      1    1520   22,5   3500   Diesel    100   2005     9       21    17,4        35        85
                                                                                            2010     9       13    15,9        35        63
                                                                                            2020    13       20     23         35        94
                                                                                            2030    14       23     25         35       106
4.3 Velikie Luki      Rzhev               241     1    1520   22,5   3500   Diesel    100   2005     5       18    16,4        32        72
                                                                                            2010     6       13    15,4        32        59
                                                                                            2020    10       20    22,5        32        94
                                                                                            2030    12       23     25         32       109
4.4 Rzhev             Shakhovskaya        83      1    1520   22,5   3500   Diesel    100   2005     5       17    15,9        40        55
                                                                                            2010     6       13    15,7        40        48
                                                                                            2020    10       20     23         40        75
                                                                                            2030    12       23     25         40       87,5
4.5 Shakhovskaya      Volokolamsk         28      1    1520   22,5   3500   DC3000   100    2005    11       13    15,6        28        85
                                                                                            2010    12       13     16         28        89
                                                                                            2020    17       22    23,5        28       139
                                                                                            2030    19       25     26         28       157
4.6 Volokolamsk       Moskow (Manihin     73      2    1520   22,5   3500   DC3000   100    2005    54       14    16,2       111        61
                                                                                            2010    55       14    17,9       111        62
                                                                                            2020    60       22    25,5       111        74
                                                                                            2030    62       25    27,5       111        78
RUSSIA - Moscow




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BRANCH 5           Klaipeda - Vilnius - Minsk

RAILWAY PERFORMANCE


                                     RAILPARAMETER                                                TRAFFIC DATA AND FORECAST       CAPACITY    Capac.
Secti                                       Number                                                                                Trains/d    utilis.
                                                         Axle Train         Power      Max       passenger freigth                              %
 on    Start node  End node          Length   of   Gauge                                    year                   Mton/yr
                                                         load weight        supply    speed        trains   trains
 ID                                         Tracks
LITHUANIA - Klaipeda
      Klaipeda    Siauliai                     2     1520   22,5           AC25000 120/90 2006                      27    14,2      100         27
                                                                                          2010                      31    16,3      100         31
                                                                                          2015                      35    18,1      100         35
     Siauliai      Kasiadorys                  2     1520   22,5           AC25000 120/90 2006                      35    18,9      100         35
                                                                                          2010                      40    21,8      100         40
                                                                                          2015                      45    24,2      100         45
     Kasiadorys    Vilna ring rail             2     1520   22,5           AC25000 120/90 2006                      60    33,5      100         60
                                                                                          2010                      69    38,5      100         69
                                                                                          2015                      77    42,9      100         77
     Vilna ring    Kena                        2     1520   22,5           AC25000 120/90 2006                      45    24,6      100         45
                                                                                          2010                      52    28,3      100         52
                                                                                          2015                      58    31,5      100         58
LT - BY border
      Gudogay      Molodechno         80       2     1520   22,5 5000       Diesel        120   2005      17        30    19,2      100         47
                                                                                                2010      18        34    22,0      100         52
                                                                                                2020      18        38    24,5      100         56
                                                                                                2030      18        41    26,9      100         59
     Molodechno Minsk                 77       2     1520   22,5 5000       Diesel        120   2005      61        32    20,5      100         93
                                                                                                2010      62        35    22,7      100         97
                                                                                                2020      62        39    25,0      100        101
                                                                                                2030      62        42    27,2      100        104
BELARUS - Minsk

Note: Max. Speed 120/90 is for parrengers/freight




BRANCH 6             Kaliningrad - Kaunas

RAILWAY PERFORMANCE


                                       RAILPARAMETER                                                TRAFFIC DATA AND FORECAST     CAPACITY    Capac.
Secti                                             Number                                                                           Trains/d   utilis.
                                                               Axle Train        Power      Max       passenger freigth                         %
 on    Start node       End node           Length   of   Gauge                                   year                   Mton/yr
                                                               load weight       supply    speed        trains   trains
 ID                                               Tracks
RUSSIA - Kaliningrad
 6.1 Kaliningrad    Chernyakhovsk             90       2 1520      22,5 5000     Diesel     100    2005        13    17    16,6      34         88
                                                                                                   2010        14    23    23,8      34        109
                                                                                                   2020        11    26    26,5      34        109
                                                                                                   2030        12    28    28,5      34        118
6.2 Chernyakhovsk Nesterov                    61       2 1520      22,5 5000     Diesel     100    2005        9     17    16,8      35         74
                                                                                                   2010        10    23    23,4      35         94
                                                                                                   2020         9    27    27,9      35        103
                                                                                                   2030         9    30    30,5      35        111
LITHUANIA
    Kaisiadorys      Kybartai               125,1      2 1520      22,5         AC25000     120    2005              28    17,3      100        28
                                                                                                   2010              30    18,3      100        30
                                                                                                   2015              32    19,5      100        32




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BRANCH 7                   Berlin - Warsaw - Minsk - Moscow

RAILWAY PERFORMANCE

                                         RAILPARAMETER                                                  TRAFFIC DATA AND FORECAST           CAPACITY   Capac.
 Secti                                           Number                                                                                     Trains/d   utilis.
                                                              Axle Train          Power     Max                 passenger freigth                        %
  on       Start node       End node      Length   of   Gauge                                           year                      Mton/yr
                                                              load weight         supply   speed                  trains   trains
   ID                                            Tracks
 GERMANY - Berlin
  728 Berlin               Frankfurt       85        2        1435   22,5        AC16000    120         2008               117                117       100
       Friedrichsstarsse   Oder
 DE - PL border
       Frankfurt/Oder      Zbaszynek       92,5      2        1435   22,1        DC3000     160     Current        25       32                204        28
       (GER)
       Zbaszynek           Poznan           81       2        1435   22,1        DC3000     160     Current        44       22                200        33
       Poznan              Konin           94,5      2        1435   22,1        DC3000     160     Current        66       48                200        57
       Konin               Lowicz          122       2        1435   22,1        DC3000     160     Current        68       30                213        46
       Lowicz              Skierniewice              2        1435               DC3000     160     Current                 16
       Skierniewice        Lukow                     2        1435               DC3000     160     Current                 18
       Lukow               Terespol        88,8      2        1435   22,5        DC3000     160     Current                 22
rsaw loop:
       Lowicz              Warsaw         84,5                                                      Current        85       14
       Warsaw              Lukow          159,7                                                     Current
 PL - BY border
  7.1 Brest                Baranovichi     206       2        1520   22,5 5100 AC25000      120         2005       10        6      6,5       100        16
                                                                                                        2010       11        7      7,2       100        18
                                                                                                        2020       12        8       8        100        20
                                                                                                        2030       13        9       9        100        22
 7.2 Baranovichi           Minsk           139       2        1520   22,5 4500 AC25000      120         2005       58       18     15,6       100        76
                                                                                                        2010       60       20     17,5       100        80
                                                                                                        2020       62       21     19,5       100        83
                                                                                                        2030       64       24      21        100        88
 7.3 Minsk                 Orsha           216       2        1520   22,5 4500 AC25000      120         2005       58       31     27,6       100        89
                                                                                                        2010       60       34     30,5       100        94
                                                                                                        2020       62       38      34        100       100
                                                                                                        2030       64       42      37        100       106
 7.4 Orsha                 Osinovka        48        2        1520   22,5 5000 AC25000      120         2005       28       30     23,4       100        58
                                                                                                        2010       30       33     25,7       100        63
                                                                                                        2020       32       39      30        100        71
                                                                                                        2030       34       42     32,9       100        76
BY - RU border
 7.1 Krasnoe               Smolensk        74        2        1520   22,5 5000 AC25000      140         2005       26       19     23,3       102        44
                                                                                                        2010       28       27     32,8       102        54
                                                                                                        2020       30       32     37,1       102        61
                                                                                                        2030       32       35      40        102        66
 7.2 Smolensk              Vyazma          175       2        1520   22,5 5000 AC25000      140         2005       29       30     37,2       105        56
                                                                                                        2010       31       28     33,8       105        56
                                                                                                        2020       33       32     37,3       105        62
                                                                                                        2030       35       35      40        105        67
 7.3 Vyazma                Mozhaisk        133       2        1520   22,5 4500 AC25000      140         2005       40       30     43,5       100        70
                                                                                                        2010       42       29     39,2       100        71
                                                                                                        2020       44       33     42,9       100        77
                                                                                                        2030       45       34     43,5       100        79
 7.4 Mozhaisk              Moskow          47        2        1520   22,5 4500 AC25000      140         2005       52       32     44,5       115        73
                           (Kubinka)                                                                    2010       54       29     40,5       115        72
                                                                                                        2020       56       33     43,1       115        77
                                                                                                        2030       58       35      45        115        81
RUSSIA - Moscow




BRANCH 8             Oslo - NO/SE border (Stockholm)

RAILWAY PERFORMANCE


                                          RAILPARAMETER                                                   TRAFFIC DATA AND FORECAST         CAPACITY   Capac.
                                                                                                                                            Trains/d   utilis.
Secti                                                  Number
                                                                    Axle Train         Power     Max       passenger freigth                             %
 on     Start node           End node           Length   of   Gauge                                   year                   Mton/yr
                                                                    load weight        supply   speed        trains   trains
 ID                                                    Tracks
NORWAY - Oslo
B 2-1 Oslo S         Lillestrøm             21           >2      1435   22,5   3960   AC15000     130    2007      400       0     0,435      571        70
B 2-2 Lillestrøm     Årnes                 37,5          1       1435   22,5   3960   AC15000     130    2007       52       16    0,435       72        95
B 2-3 Årnes          Kongsvinger           41,8          1       1435   22,5   3960   AC15000     130    2007                18    0,435       43        42
B 2-4 Kongsvinger    Riksgrensen (Sweden - 42,6          1       1435   22,5   3960   AC15000     130    2007                12    0,435       40        30
                     Charlottenberg)
NO - SE border




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                                               Appendix 2: Basic Road and Rail Parameter and Performance Data
BRANCH 9          Oslo - NO/SE border (Copenhangen)

RAILWAY PERFORMANCE


                                 RAILPARAMETER                                       TRAFFIC DATA AND FORECAST       CAPACITY   Capac.
Secti                                   Number                                                                       Trains/d   utilis.
                                                     Axle Train      Power     Max       passenger freigth                        %
 on Start node        End node   Length   of   Gauge                                year                   Mton/yr
                                                     load weight     supply   speed        trains   trains
 ID                                     Tracks
NORWAY - Oslo
A 1-1 Oslo S      Ski             24,3    2    1435   22,5   3960   AC15000    130   2007   210       16               301        75
A 1-2 Ski         Moss            35,9    2    1435   22,5   3960   AC15000    160   2007    84       16               200        50
A 1-3 Moss        Sarpsborg       49,3         1435   22,5   3960   AC15000    130                                                70
A 1-4 Sarpsborg   Halden          27,1    1    1435   22,5   3960   AC15000    130   2007    38       12               75         67
A 1-5 Halden      Riksgrensen     32,5    1    1435   22,5   3960   AC15000    120   2007    6        6                44         27
                  (Sweden -
NO - SE border




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                                                                                   Appendix 3: Database Report



Appendix 3: Database Report

Overview
This database report describes the TEN Northern Axis database (later TEN-North) data model
and validation rules of the data. The data model represents the details about the logical and
physical structure of the database, its classes of entities, their attributes and the associations
between them.
The data validation rules describe the procedures that were adopted to verify the technical
correctness of the collected data.
The database itself is handed over separately to DG TREN in electronic form.


The TEN-North database
The database contains information for the following transport modes:
          roads
          railways
Database is implemented using ESRI geodatabase structure. TEN-North database is built
using the same schema that was used in the TEN-T2 database
The TEN-North database consists of two main feature types: links and nodes. Links represent
roads and railways. Nodes represent junctions, endpoints and major cities or stations along
roads and railways. All features are linked with textual attributes presenting technical
information and investment data.The database is built on a specific concept with the same
schema used for both transportation modes. For each mode, the geographical information is
linked with detailed transport infrastructure data, investments technical and financial
information and priority axis/section allocation.
The spatial reference system of the TEN-North database is the European Terrestrial Reference
System 1989 (ETRS89), as in TEN-T2 database. It is the geodetic datum for Pan-European
spatial data collection, storage and analysis. The ETRS89 is based on the GRS80 ellipsoid and
is the basis for a coordinate reference system using ellipsoidal coordinates.


The database model
The TEN-North database model is based on following design principles:
      design is as simple as possible
      maximum compatibility with the TEN-T2 database has been kept

The following naming conventions are used in the database:
       classes and attributes have long, self-explanatory names
       package and class names are always singular
       there are no spaces, hyphens or underscores in package, class and attribute names
       package, class and attribute names are capitalized, and each constituent word in the
       name is capitalized
       The tables that have been added to TEN-North database (i.e. tables that didn’t exist in
       the TEN-T2 database) are named with suffix –NA (eg. RoadParameterNA).


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9.3.1   Roads
The TEN-North road network consists of road sections. This is represented by the Road
feature, which has a polyline geometry. Each road section is described by the StartNode /
EndNode information and National- and International Number in order to be precisely located
on the maps.
The Roads are further described by technical parameters grouped in RoadParameter and
RoadParameterNA objects. They are related on a 1..* to 1 relationship to the respective
Road feature. Roads are described by technical information for certain period of time, defined
by year date.
The road measures information (investments information for all TEN-North road sections) is
located in RoadMeasure objects. In addition, detailed investment information is available in
RoadMeasureCostPerYear, RoadMeasureFunding and RoadMeasureCardNA objects.
With the StartNode and EndNode attributes, the investment is exactly located on the network.
Since an investment can span over more than one section and one section can have more than
one investment, the roads sections and investments are linked using Road2Measure class.
Each investment might have (0..*) detailed information on costs per year and the sources of
funding. In RoadMeasureCardNA, official information about new road projects in Russia and
Belarus was not available. The data has been gathered from various sources and may therefore
not be of same quality as other data in the database.
Traffic volume information is located in RoadVolumeNA objects. RoadVolumeNA table
holds both current trafic information and forecast traffic information. RoadVolume object is
related on a 1..* to 1 relationship to the respective road feature.
Border crossing places along roads are featured in RoadBorderNodeNA feature class.
Detailed technical parameters for RoadBorderNodeNA objects are available in
RoadCrossBorderParameterNA table which is related to RoadBorderNodeNA on a 1 to 1
relation. Traffic volume information for RoadBorderNodeNA objects can be found from
RoadCrossBorderVolumeNA table which is related to RoadBorderNodeNA on a 1 to 1..*
relation. Note, that all border crossing data has been gethered to these three objects
(RoadBorderNodeNA, RoadCrossBorderParameterNA, RoadCrossBorderVolumeNA). There
are border links at Road feature class also (Road id numbers 9000-9015), but they have been
created only to make the geometry solid at border crossings. This is why these border links do
not hold any data in e.g. RoadParameter table.
Relationships between road objects in the database are further described in pictures 1 and 2.
Tables 1 to 12 describe the tabular structure of road feature classes and tables. Domains used
in road objects are described in table 32.




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Picture 1. Relationship diagram for roads




Picture 2. Relationship diagram for road border crossings




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Table 1. Road feature class attribute table. This feature class contains the geometry of the road links.
 Road

 Alias                   Road                  Geometry:Polyline
                                               Has M:No
 Dataset Type            FeatureClass          Has Z:No
 FeatureType             Simple                Grid Size:1000
 Field Name              Type                  Length                Null                  Description     Example        Unit
 OBJECTID                OID                   4                     No
 SHAPE                   Geometry              0                     Yes
 ID                      Integer               4                     Yes                   Road id
                                                                                           Country
 IDCOUNTRY               Integer               4                     Yes                   code
 IDSTARTNODE             Integer               4                     Yes                   Star node id
 IDENDNODE               Integer               4                     Yes                   End node id
                                                                                           Verified yes /
 VERIFIED                Integer               4                     Yes                   no
 LASTVERIFIED            Double                8                     Yes                   When verified if yes
                                                                                           When      data    was   last
 LASTMODIFIED            Double                8                     Yes                   modified
                                                                                           Who
 USERMODIFIED            String                255                   Yes                   modified
 USERVERIFIED            String                255                   Yes                   Who verified if yes
 INTROADNUMBER           String                255                   Yes                   International road number
 NATIONALROADNUMBER      String                255                   Yes                   National road number
                                                                                           Combination                    code
 CODE                    String                255                   Yes                   (cntry,transp.mode,roadno.)
 SHAPE_Length            Double                8                     Yes
 Index Name              Ascending             Unique                Fields
 IDCountry               CountryNA
 FDO_OBJECTID            Yes                   Yes                   OBJECTID
 GDB_2_ID                Yes                   No                    ID
 GDB_2_IDENDNODE         Yes                   No                    IDENDNODE
 GDB_2_IDSTARTNOD        Yes                   No                    IDSTARTNODE
 SHAPE_INDEX             Yes                   No                    SHAPE



Table 2. RoadNode feature class attribute table. This feature class contains the geometry of the road nodes.
 RoadNode

 Alias          RoadNode                Geometry:Point
                                        Has M:No
 Dataset Type   FeatureClass            Has Z:No
 FeatureType    Simple                  Grid Size:1000
 Field Name     Type                    Length            Null              Description        Example       Unit
 OBJECTID       OID                     4                 No
 SHAPE          Geometry                0                 Yes
 ID             Integer                 4                 Yes               Road node id
 IDCOUNTRY      Integer                 4                 Yes               Country code
 NAME           String                  255               Yes               Name
 Index Name     Ascending               Unique            Fields
 IDCountry      CountryNA
 FDO_OBJECTID   Yes                     Yes               OBJECTID
 GDB_1_ID       Yes                     No                ID
 SHAPE_INDEX    Yes                     No                SHAPE




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Table 3. RoadBorderNodeNA feature class attribute table. This feature class contains the geometry of the
road nodes that are situated at border crossings.
 RoadBorderNodeNA

 Alias                    RoadBorderNode     Geometry:Point
                                             Has M:No
 Dataset Type             FeatureClass       Has Z:No
 FeatureType              Simple             Grid Size:1000
 Field Name               Type               Length                Null           Description      Example         Unit
 OBJECTID                 OID                4                     No
 SHAPE                    Geometry           0                     Yes
 RoadCrossBorderId        Integer            4                     Yes            Crossbordernode id
 IdCountry                Integer            4                     Yes            Country code
 IdRoadNode               Integer            4                     Yes            Road node id
 IdForeignCountry         Integer            4                     Yes            Id of the country at opposite side of border
 IdForeignNode            Integer            4                     Yes            Id of the node at opposite side of border
 YearOfConstruction       Integer            4                     Yes            Year of construction
 Name                     String             50                    Yes            Name
 Index Name               Ascending          Unique                Fields
 IDCountry                CountryNA
 FDO_OBJECTID             Yes                Yes                   OBJECTID
 SHAPE_INDEX              Yes                Yes                   SHAPE



Table 4. RoadParameter table. This table contains parameter data for roads.
 RoadParameter

 Alias                RoadParameter
 Dataset Type         Table
 Field Name           Type          Length    Null            Description                 Example                         Unit
 OBJECTID             OID           4         No
 ID                   Integer       4         Yes             Parameter id
 IDROAD               Integer       4         Yes             Road id
 INFOYEAR             Integer       4         Yes             Year of the Information     2005                            year
 LENGTH               Double        8         Yes             Length                                                      km
 ROADTYPE             Integer       4         Yes             Road type                   Motorway/HiQual./Ordin.         code
 NOLANES              Integer       4         Yes             Number of lanes
 DESIGNSPEED          Integer      4          Yes             Design speed                                                km/h
 MAXGRADIENT          Integer       4         Yes             Max gradient                                                %
 MAXAXLELOAD          Integer       4         Yes             Max axle load                                               kN
 TOLLED               Integer       4         Yes             Tolled                      yes/no/no data                  code
 MAXWEIGHT            Integer       4         Yes             Max total vehicle weight                                    tons
 ObjectClass          Domain
 INFOYEAR             geomYear
 ROADTYPE             geomRoadType
 TOLLED               geomYesNo
 Index Name           Ascending     Unique    Fields
 FDO_OBJECTID         Yes           Yes       OBJECTID
 GDB_19_IDROAD        Yes           No        IDROAD




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Table 5. RoadParameterNA table. This table contains additional parameter data for roads.
 RoadParameterNA

 Alias                RoadParameterNA
 Dataset Type         Table
 Field Name           Type          Length            Null        Description                  Example                     Unit
 OBJECTID             OID           4                 No
 IdRoad               Integer       4                 Yes         Road id
 State                Integer       4                 Yes         State                        Exist./Und.Constr./Plann.   code
 SpeedLimit           Integer       4                 Yes         Speed limit                                              km/h
 SpeedLimitHgv        Integer       4                 Yes         Heavy Goods Vehicle speedlimit                           km/h
 RoadWidth            Double        8                 Yes         Road width                                               m
 PavementType         Integer       4                 Yes         Pavement type                asphalt/concrete/light      code
 MaxVehicleHeight     Double        8                 Yes         Max vehicle height                                       m
 InurbanAreas         Double        8                 Yes         Road length in urban/built-up areas                      km
 Responsibility       Integer       4                 Yes         Responsibility               Nat./Fed./Region./Priv.     code
 MaxVehicleLenght     Double        8                 Yes         Max vehicle length                                       m
 InfoYear             Integer       4                 Yes         Year of the Information      2005                        year
                                                                  Annual      number      of
 Accidents            Double          8               Yes         accidents
 ObjectClass          Domain
 PavementType         PavementNA
 Responsibility       ResponsibilityNA
 MaxVehicleLenght     ResponsibilityNA
 InfoYear             geomYear
 Index Name           Ascending       Unique          Fields
 FDO_OBJECTID         Yes             Yes             OBJECTID
 GDB_18_IdRoad        Yes             No              IdRoad



Table 6. RoadVolumeNA table. This table contains traffic volume data for roads.
 RoadVolumeNA

 Alias              RoadVolumeNA
 Dataset Type       Table
 Field Name         Type         Length        Null          Description                  Example               Unit
 OBJECTID           OID          4             No
 Id                 Integer      4             Yes           Road id
 YearNA             Integer      4             Yes           year of the estimation       2007                  year
 VolumeType         Integer      4             Yes           Type of the estimate         counting/forecast     code
                                                             Annual Average Daily
 Aadt               Double       8             Yes           Traffic                                            vehic./d
                                                             Heavy     Goods    Vehicle
 Hgvshare           Double       8             Yes           share                                              %
 ObjectClass        Domain
 VolumeType         VolumeType
 Index Name         Ascending    Unique        Fields
 FDO_OBJECTID       Yes          Yes           OBJECTID
 GDB_17_Id          Yes          No            Id



Table 7. Road2Measure table. This table describes the correspondence of road id numbers with road measure
id numbers. This table has been created to avoid many to many relationships.
 Road2Measure

 Alias                 Road2Measure
 Dataset Type          Table
 Field Name            Type         Length           Null          Description      Example        Unit
 OBJECTID              OID          4                No
 IDMEASURE             Integer      4                Yes           Measure id
 IDROAD                Integer      4                Yes           Road id
 Index Name            Ascending    Unique           Fields
 FDO_OBJECTID          Yes          Yes              OBJECTID
 GDB_27_IDMEASURE      Yes          No               IDMEASURE
 GDB_27_IDROAD         Yes          No               IDROAD




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Table 8. RoadMeasure table. This table contains general investment measure information for roads.
 RoadMeasure

 Alias                  RoadMeasure
 Dataset Type           Table
 Field Name             Type        Length      Null         Description                 Example                Unit
 OBJECTID               OID         4           No
                        Small
 VERIFIED               Integer     2           Yes          Verified yes / no
                                                             When data was last
 LASTMODIFIED           Double      8           Yes          modified
 LASTVERIFIED           Double      8           Yes          When verified if yes
 USERMODIFIED           String      255         Yes          Who modified
 USERVERIFIED           String      255         Yes          Who verified if yes
 ID                     Integer     4           Yes          Measure id
 IDCOUNTRY              Integer     4           Yes          country code                 205
 CODE                   String      255         Yes          measure code by country      FIRD018005
 DESCRIPTION            String      255         Yes          description of the project
 IDSTARTNODE            Integer     4           Yes          Start node id
 IDENDNODE              Integer     4           Yes          end node id
 STAGE                  Integer     4           Yes          stage of the project         Compl./Und.Constr./Und.Study/Plan
 STAGEUNDERSTUDY1       Integer     4           Yes          If under study, study phase
 STAGEUNDERSTUDY2       Integer     4           Yes          If under study, study phase
 STAGEUNDERSTUDY3       Integer     4           Yes          If under study, study phase
 ESTIMATEDTOTALCOST     Double      8           Yes          total cost of the project                           M euro
 MEASURETYPE            Integer     4           Yes          type of the project
                                                             length of the project
 LENGTH                 Double      8           Yes          route                                               km
                                                             Starting year of the
 STARTYEAR              Integer     4           Yes          project                      2007                   year
 ENDYEAR                Integer     4           Yes          End year of the project      2010                   year
                                                             Description             n/a,
 WHOLENETWORK           Integer     4           Yes          transferred from T2
 ObjectClass            Domain
 IDCountry              CountryNA
 STAGE                  geomMeasureStage
 STAGEUNDERSTUDY1       geomMeasureUnderStudy
 STAGEUNDERSTUDY2       geomMeasureUnderStudy
 STAGEUNDERSTUDY3       geomMeasureUnderStudy
 MEASURETYPE            geomMeasureType
 STARTYEAR              geomMeasureYear
 WHOLENETWORK           geomYesNo
 ENDYEAR                geomMeasureYear
 Index Name             Ascending   Unique      Fields
 FDO_OBJECTID           Yes         Yes         OBJECTID
 GDB_23_ID              Yes         No          ID




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Table 9. RoadMeasureCardNA table. This table contains investment project descriptions.
 RoadMeasureCardNA
 Alias                  RoadMeasureCardNA
 Dataset Type           Table
 Field Name             Type           Length    Null             Description                     Example              Unit
 OBJECTID               OID            4         No
 Id                     Integer        4         Yes
 IdRoadMeasure2         Integer        4         Yes              Measure id
 ProjectName            String         255       Yes              Name of the project
 ProjectOwner           String         255       Yes              Organisation                                         text
 ProjectDescription     String         255       Yes              Description of the project                           text
 ProjectGoal            String         255       Yes              Project goal                                         text
 ProjectSEImpacts       String         255       Yes              Socio-economic Impacts                               text
 ProjectEnvImpacts      String         255       Yes              Environmental Impacts                                text
 BC                     Double         8         Yes              Benefit/Cost quotient
                                                                                                  Compl./Und.Con
                                                                                                  str.
 Stage                  Integer         4        Yes              Stage of Project                /Und.Study/Plan
                                                                                                  Feasibility/
                                                                  Design phase, if stage in       Environmental/
 DesignPhase            Integer         4        Yes              design phase                    Technical
                                                                                                  Compl./Underw.
 EIAPhase               Integer         4        Yes              EIA Phase                       /Plann./N/A
                                                                                                  http://ten-
 ReportInternet         String          255      Yes              WWW address                     naxis.info/
 ObjectClass            Domain
 Stage                  StageNA
 DesignPhase            DesignPhaseNA
 EIAPhase               EIAPhaseNA
 Index Name             Ascending       Unique   Fields
 FDO_OBJECTID           Yes             Yes      OBJECTID
 GDB_22_IdRoadMea       Yes             No       IdRoadMeasure2



Table 10. RoadMeasureCostPerYear table. This table contains estimated investment project costs per year.
 RoadMeasureCostPerYear
 Alias                RoadMeasureCostPerYear
 Dataset Type         Table
 Field Name           Type        Length         Null             Description                  Example        Unit
 OBJECTID             OID         4              No
 ID                   Integer     4              Yes              Measure cost per year id
 IDMEASURE            Integer     4              Yes              Measure id
 COSTYEAR             Integer     4              Yes              Financial Year               2007           year
 COST                 Double      8              Yes              Cost in this year                           M euro
 Index Name           Ascending   Unique         Fields
 FDO_OBJECTID         Yes         Yes            OBJECTID
 GDB_21_IDMEASURE     Yes         No             IDMEASURE



Table 11. RoadMeasureFunding table. This table contains financial sources for road projects.
 RoadMeasureFunding
 Alias                    RoadMeasureFunding
 Dataset Type             Table
 Field Name               Type        Length     Null             Description                  Example      Unit
 OBJECTID                 OID         4          No
 IDMEASURE                Integer     4          Yes              Measure id
 NATIONALBUDGET           Double      8          Yes              National budget                           M euro
 TENTBUDGET               Double      8          Yes              TEN-T budget                              M euro
 COHESIONFUNDS            Double      8          Yes              Cohesion funds                            M euro
 ISPAFUNDS                Double      8          Yes              ISPA funds                                M euro
 ERDFFUNDS                Double      8          Yes              ERDF funds                                M euro
 EIBLOANS                 Double      8          Yes              EIB loans                                 M euro
 EBRDLOANS                Double      8          Yes              EBRD loans                                M euro
 OTHERIFISLOANS           Double      8          Yes              Other IFIS loans                          M euro
 PRIVATECAPITAL           Double      8          Yes              Private capital                           M euro
 OTHERSOURCE              Double      8          Yes              Other source                              M euro
 Index Name               Ascending   Unique     Fields
 FDO_OBJECTID             Yes         Yes        OBJECTID
 GDB_20_IDMEASURE         Yes         No         IDMEASURE




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Table 12. RoadCrossBorderParameterNA table. This table contains parameter data for road border crossings.
 RoadCrossBorderParameterNA

 Alias                        RoadCrossBorderParameterNA
 Dataset Type                 Table
 Field Name                   Type         Length      Null          Description                            Example         Unit
 OBJECTID                     OID          4           No
 Id                           Integer      4           Yes           Parameter id
 RoadCrossBorderId            Integer      4           Yes           Road cross border node id
 Year_                        Integer      4           Yes           Year of construction                     2007          yyyy
                                                                     Number of lanes (approaching
 NoLanesIn                    Integer      4            Yes          road)
 NoLanesBetween               Integer      4            Yes          Number of lanes (between the two border stations)
 NoOfServicePointsEnter       Integer      4            Yes          Number of service points/windows, entering
 NoOfServicePointsExit        Integer      4            Yes          Number of service points/windows, exiting
 OpeningHours                 String       50           Yes          Opening hours                            24 h          text
                                                                     Capacity, entering of motor
 CapacityEnterMotorVehicles   Double       8            Yes          vehicles                                               veh/hour
 CapacityEnterTrucks          Double       8            Yes          Capacity, entering of trucks                           veh/hour
 CapacityExitMotorVehicles    Double       8            Yes          Capacity, exiting of motor vehicles                    veh/hour
 CapacityExitTrucks           Double       8            Yes          Capacity, exiting of trucks                            veh/hour
 ParkingFacilities            String       255          Yes          Parking and other overflow facilities at border        text
 Index Name                   Ascending    Unique       Fields
 FDO_OBJECTID                 Yes          Yes          OBJECTID



Table 13. RoadCrossBorderVolumeNA table. This table contains traffic volume data for road border
crossings.
 RoadCrossBorderVolumeNA

 Alias                        RoadCrossBorderVolumeNA
 Dataset Type                 Table
 Field Name                   Type         Length       Null         Description                            Example                Unit
 OBJECTID                     OID          4            No
 RoadCrossBorderId            Integer      4            Yes          Road cross border node id
 Year_                        Integer      4            Yes          Estimated year                         2007                   year
 VolumeType                   Integer      4            Yes          Type of the estimate                   counting/forecast      code
 Cars                         Double       8            Yes          Annual average daily traffic                                  veh/day
 BusOrCoach                   Double       8            Yes          Annual average daily traffic                                  veh/day
 TruckOrVan                   Double       8            Yes          Annual average daily traffic                                  veh/day
 TotalVehicles                Double       8            Yes          Annual average daily traffic                                  veh/day
 FreightImported              Double       8            Yes          Imported freight                                              ton/a
 FreightExported              Double       8            Yes          Exported freight                                              ton/a
                                                                     Annual      number      of     total
 Passengers                   Double       8            Yes          passengers                                                    PAX
 ObjectClass                  Domain
 VolumeType                   VolumeType
 Index Name                   Ascending    Unique       Fields
 FDO_OBJECTID                 Yes          Yes          OBJECTID




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9.3.2   Railways
The TEN-North railway network consists of railway sections. This is represented by the Rail
feature, which has a polyline geometry. Each railway section is described by the StarNode /
EndNode information and InternationalNumber in order to be precisely located on the maps.
The railways are further described by technical parameters grouped in RailParameter and
RailParameterNA objects. They are related on a 1..* to 1 relationship to the respective Rail
feature. The railway is described by technical information for certain period of time, defined
by year date.
The railway measures information (investments information for all TEN-North railway
sections) is located in RailMeasure objects. In addition, detailed investment information is
available in RailMeasureCostPerYear, RailMeasureFunding and RailMeasureCardNA
objects. With the StartNode and EndNode attributes, the investment is exactly located on the
network. Since an investment can span over more than one section and one section can have
more than one investment, the railways sections and investments are linked using
Rail2Measure class. Each investment might have (0..*) detailed information on costs per year
and the sources of funding.
Traffic volume information is located in RailVolumeNA objects. RailVolumeNA table holds
both current trafic information and forecast traffic information. RailVolume object is related
on a 1..* to 1 relationship to the respective rail feature.
Border crossing places along railways are featured in RailBorderNodeNA feature class.
Detailed technical parameters for RailBorderNodeNA objects are available in
RailCrossBorderParameterNA table which is related to RailBorderNodeNA on a 1 to 1
relation. Traffic volume information for RailBorderNodeNA objects can be found from
RailCrossBorderVolumeNA table which is related to RailBorderNodeNA on a 1 to 1..*
relation. Note, that all border crossing data has been gethered to these three objects
(RailBorderNodeNA, RailCrossBorderParameterNA, RailCrossBorderVolumeNA). There are
border links at Rail feature class also (Rail id numbers 9000-9015), but they have been
created only to make the geometry solid at border crossings. This is why these border links do
not hold any data in e.g. RailParameter table.
Relationships between railway objects in the database are further described in pictures 3 and
4. Tables 14 to 26 describe the tabular structure of railway feature classes and tables.
Domains used in railway objects are described in table 32.




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Picture 3. Relationship diagram for railways




Picture 4. Relationship diagram for railway border crossings




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Table 14. Rail feature class attribute table. This feature class contains the geometry of the railway links.
 Rail

 Alias                     Rail                  Geometry:Polyline
                                                 Has M:No
 Dataset Type              FeatureClass          Has Z:No
 FeatureType               Simple                Grid Size:1000
 Field Name                Type                  Length               Null               Description     Example           Unit
 OBJECTID                  OID                   4                    No
 SHAPE                     Geometry              0                    Yes
 ID                        Integer               4                    Yes                Rail id
                                                                                         Country
 IDCOUNTRY                 Integer               4                    Yes                code
 IDSTARTNODE               Integer               4                    Yes                Start node id
 IDENDNODE                 Integer               4                    Yes                End node id
                                                                                         Verified yes /
 VERIFIED                  Integer               4                    Yes                no
 LASTVERIFIED              Double                8                    Yes                When verified if yes
                                                                                         When      data     was   last
 LASTMODIFIED              Double                8                    Yes                modified
                                                                                         Who
 USERMODIFIED              String                255                  Yes                modified
 USERVERIFIED              String                255                  Yes                Who verified if yes
 CODE                      String                255                  Yes                Combination code (cntry,transp.mode,railwayno.)
 INTRAILNUMBER             String                255                  Yes                International railway number
 SHAPE_Length              Double                8                    Yes                Length of the link
 Index Name                Ascending             Unique               Fields
 IDCountry                 CountryNA
 FDO_OBJECTID              Yes                   Yes                  OBJECTID
 GDB_4_ID                  Yes                   No                   ID
 GDB_4_IDENDNODE           Yes                   No                   IDENDNODE
 GDB_4_IDSTARTNOD          Yes                   No                   IDSTARTNODE
 SHAPE_INDEX               Yes                   No                   SHAPE

Table 15. RailNode feature class attribute table. This feature class contains the geometry of the railway
nodes.
 RailNode

 Alias                RailNode               Geometry:Point
                                             Has M:No
 Dataset Type         FeatureClass           Has Z:No
 FeatureType          Simple                 Grid Size:1000
 Field Name           Type                   Length                  Null           Description      Example        Unit
 OBJECTID             OID                    4                       No
 SHAPE                Geometry               0                       Yes
 ID                   Integer                4                       Yes            Rail node id
 IDCOUNTRY            Integer                4                       Yes            Country code
 NAME                 String                 255                     Yes            Name
 Index Name           Ascending              Unique                  Fields
 IDCountry            CountryNA
 FDO_OBJECTID         Yes                    Yes                     OBJECTID
 GDB_3_ID             Yes                    No                      ID
 SHAPE_INDEX          Yes                    No                      SHAPE

Table 16. RailBorderNodeNA feature class attribute table. This feature class contains the geometry of the
railway nodes that are situated at border crossings.
 RailBorderNodeNA

 Alias                            RailBorderNode          Geometry:Point
                                                          Has M:No
 Dataset Type                     FeatureClass            Has Z:No
 FeatureType                      Simple                  Grid Size:1000
 Field Name                       Type                    Length                Null          Description      Example            Unit
 OBJECTID                         OID                     4                     No
 SHAPE                            Geometry                0                     Yes
 RailCrossBorderId                Integer                 4                     Yes           Crossbordernode id
 Name                             String                  50                    Yes           Name
 IdCountry                        Integer                 4                     Yes           Country code
 IdRailNode                       Integer                 4                     Yes           Road node id
 IdForeignCountry                 Integer                 4                     Yes           Id of the country at opposite side of border
 IdForeignNode                    Integer                 4                     Yes           Id of the node at opposite side of border
 YearOfConstruction               Integer                 4                     Yes           Year of construction
 Index Name                       Ascending               Unique                Fields
 IDCountry                        CountryNA
 FDO_OBJECTID                     Yes                     Yes                   OBJECTID
 SHAPE_INDEX                      Yes                     Yes                   SHAPE



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Table 17. RailParameter table. This table contains parameter data for railways.
 RailParameter

 Alias                   RailParameter
 Dataset Type            Table
 Field Name              Type            Length   Null     Description               Example                                 Unit
 OBJECTID                OID             4        No
 ID                      Integer         4        Yes      Parameter id
 IDRAIL                  Integer         4        Yes      Rail id
                                                           Year        of      the
 INFOYEAR                Integer         4        Yes      Information               2007                                    year
 LENGTH                  Double          8        Yes      Length of the route                                               km
 RAILTYPE                Integer         4        Yes      Rail type                 Convent./HiSpeed/UpgrHiSpeed            code
 ACTIVITY                Integer         4        Yes      Activity                  Freight/Pass./Pass.&Freight             code
 NOTRACKS                Integer         4        Yes      Number of tracks                                                  number
 TRACTION                Integer         4        Yes      Traction (power)          Electr./Dies.                           code
 TRACKGAUGE              Integer         4        Yes      Track gauge               1435/1520/1668/1524/1602/1000/1600      code
 MAXLOADGAUGE            String          255      Yes      Max load gauge            GA/GB/GC/etc.                           text
 MINRADIUS               Integer         4        Yes      Minimum radius                                                    m
 DESIGNSPEED             Integer         4        Yes      Design speed                                                      km/h
 MAXSPEED                Integer         4        Yes      Maximum speed                                                     km/h
 MAXGRADIENT             Integer         4        Yes      Maximum gradient                                                  1/1000
 MAXAXLELOAD             Double          8        Yes      Maximum axle load                                                 kN
 VOLTAGE                 Integer         4        Yes      Voltage                                                           V
 SIGNALINGSTANDARD       String          255      Yes      Signalling standard                                               text
 ERTMS                   Integer         4        Yes      ERTMS in operation        yes/no/no data                          code
 ERTMSLEVEL              Integer         4        Yes      ERTMS level               Level1/Level2/Level3                    code
                                                           Category     of   High
 HSCATEGORY              Integer        4         Yes      Speed                     I/II/III                                code
 ObjectClass             Domain
 INFOYEAR                geomYear
 RAILTYPE                geomRailType
 ACTIVITY                geomActivity
 TRACTION                geomRailTraction
 TRACKGAUGE              geomRailTrackGauge
 ERTMS                   geomYesNo
 HSCATEGORY              geomRailHSCategory
 Index Name              Ascending      Unique    Fields
                                                  OBJECT
 FDO_OBJECTID            Yes             Yes      ID
 GDB_50_IDRAIL           Yes             No       IDRAIL

Table 18. RailParameterNA table. This table contains additional parameter data for railways.
 RailParameterNA

 Alias                    RailParameterNA
 Dataset Type             Table
 Field Name               Type          Length      Null         Description                      Example           Unit
 OBJECTID                 OID           4           No
 IdRail                   Integer       4           Yes          Rail id
 InfoYear                 Integer       4           Yes          Year of the Information          2005              year
 MaxTrainLenght           Integer       4           Yes          Max train length                                   m
 MaxTrainweight           Integer       4           Yes          Max train weight                                   tons
 IntermodalTrains         Integer       4           Yes          Intermodal trains                yes/no/no data    code
 PercentPassTrains        Integer       4           Yes          Percent of passenger trains                        %
 CapacityForFreight       Integer       4           Yes          Capacity for freight                               number
 DegreeOfCapacity         Integer       4           Yes          Degree of capacity utilization                     %
 Punctuality              Integer       4           Yes          Punctuality data                                   %
 AccidentCausingDelay     Single        4           Yes          Accidents/events causing delay                     /month
 ObjectClass              Domain
 InfoYear                 geomYear
 IntermodalTrains         geomYesNo
 Index Name               Ascending     Unique      Fields
 FDO_OBJECTID             Yes           Yes         OBJECTID
 GDB_45_IdRail            Yes           No          IdRail




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Table 19. RailVolumeNA table. This table contains traffic volume data for railways.
 RailVolumeNA
 Alias           RailVolumeNA
 Dataset Type    Table
 Field Name      Type            Length        Null             Description                   Example                 Unit
 OBJECTID        OID             4             No
 Id              Integer         4             Yes              Rail id
 VolumeType      Integer         4             Yes              Type of the estimate           counting/forecast      code
 InfoYear        Integer         4             Yes              year of the estimation         2007                   year
 PassTrains      Integer         4             Yes              Average daily passenger trains                        train/day
 FreightTrains   Integer         4             Yes              Average daily freigth trains                          train/day
 FreightVolume   Double          8             Yes              Annual freight volume                                 M ton/a
 Capacity        Integer         4             Yes              Capacity                                              train/day
 ObjectClass     Domain
 VolumeType      VolumeType
 Index Name      Ascending       Unique        Fields
 FDO_OBJECTID    Yes             Yes           OBJECTID

Table 20. Rail2Measure table. This table connects rail id numbers to rail measure id numbers. This table has
been created to avoid many to many relationships.
 Rail2Measure
 Alias                 Rail2Measure
 Dataset Type          Table
 Field Name            Type               Length      Null                 Description       Example         Unit
 OBJECTID              OID                4           No
 IDMEASURE             Integer            4           Yes                  Measure id
 IDRAIL                Integer            4           Yes                  Rail id
 Index Name            Ascending          Unique      Fields
 FDO_OBJECTID          Yes                Yes         OBJECTID
 GDB_46_IDMEASURE      Yes                No          IDMEASURE
 GDB_46_IDRAIL         Yes                No          IDRAIL

Table 21. RailMeasure table. This table contains general investment measure information for railways.
 RailMeasure
 Alias                 RailMeasure
 Dataset Type          Table
 Field Name            Type                Length         Null         Description                             Example               Unit
 OBJECTID              OID                 4              No
 VERIFIED              Small Integer       2              Yes          Verified yes / no
 LASTMODIFIED          Double              8              Yes          When data was last modified
 LASTVERIFIED          Double              8              Yes          When verified if yes
 USERMODIFIED          String              255            Yes          Who modified
 USERVERIFIED          String              255            Yes          Who verified if yes
 ID                    Integer             4              Yes          Measure Id
 IDCOUNTRY             Integer             4              Yes          Country code                            205
 CODE                  String              255            Yes          Measure code by country                 LVRD001
 DESCRIPTION           String              255            Yes          Description of the project
 IDSTARTNODE           Integer             4              Yes          Start node id
 IDENDNODE             Integer             4              Yes          End node id
                                                                                                               Compl./Und.Constr./
 STAGE                 Integer             4              Yes          Stage of the project                    Und.Study/Plan.
 STAGEUNDERSTUDY1      Integer             4              Yes          If under study, study phase
 STAGEUNDERSTUDY2      Integer             4              Yes          If under study, study phase
 STAGEUNDERSTUDY3      Integer             4              Yes          If under study, study phase
 ESTIMATEDTOTALCOST    Double              8              Yes          Total cost of the project                                     Meur
                                                                                                               NewConstr./Rehabil.
 MEASURETYPE           Integer        4                   Yes          Type of the project                     /Upgr./N/A
 LENGTH                Double         8                   Yes          Length of the project route                                   km
 STARTYEAR             Integer        4                   Yes          Starting year of the project            2007                  year
 ENDYEAR               Integer        4                   Yes          End year of the project                 2010                  year
 WHOLENETWORK          Integer        4                   Yes          Description n/a,transferred from T2
 ObjectClass           Domain
 IDCountry             CountryNA
 STAGE                 geomMeasureStage
 STAGEUNDERSTUDY1      geomMeasureUnderStudy
 STAGEUNDERSTUDY2      geomMeasureUnderStudy
 STAGEUNDERSTUDY3      geomMeasureUnderStudy
 MEASURETYPE           geomMeasureType
 STARTYEAR             geomMeasureYear
 ENDYEAR               geomMeasureYear
 WHOLENETWORK          geomYesNo
 Index Name            Ascending      Unique              Fields
 FDO_OBJECTID          Yes            Yes                 OBJECTID
 GDB_47_ID             Yes            No                  ID


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Table 22. RailMeasureCardNA table. This table contains investment project descriptions.
 RailMeasureCardNA

 Alias                RailMeasureCardNA
 Dataset Type         Table
 Field Name           Type          Length       Null         Description                   Example                              Unit
 OBJECTID             OID           4            No
 Id                   Integer       4            Yes
 IdRailmeasure2       Integer       4            Yes          Measure id
 ProjectName          String        255          Yes          Name of the project
 ProjectOwner         String        255          Yes          Name of the organisation
 ProjectDescription   String        255          Yes          Description of the project
 ProjectGoal          String        255          Yes          Target of the project
 ProjectSEImpacts     String        255          Yes          Socio-economic Impacts
 ProjectENVImpacts    String        255          Yes          Environmental Impacts
 BC                   Double        8            Yes          Benefit/Cost quotient
 Stage                Integer       4            Yes          Stage of Project              Compl./Und.Constr./Und.Study/Plan.
                                                              Designphase,if          in
 DesignPhase          Integer       4            Yes          designphase                   Feasib./Environm./Techn.
 EIAPhase             Integer       4            Yes          EIA Phase                     Compl./Underw./Plann./N/A
 ReportInternet       String        255          Yes          WWW address                   http://ten-naxis.info/
 ObjectClass          Domain
 Stage                StageNA
 DesignPhase          DesignPhaseNA
 EIAPhase             EIAPhaseNA
 Index Name           Ascending     Unique       Fields
 FDO_OBJECTID         Yes           Yes          OBJECTID
 GDB_16_IdRailmea     Yes           No           IdRailmeasure2

Table 23. RailMeasureCostPerYear table. This table contains estimated investment project costs per year.
 RailMeasureCostPerYear

 Alias                    RailMeasureCostPerYear
 Dataset Type             Table
 Field Name               Type          Length          Null             Description                   Example       Unit
 OBJECTID                 OID           4               No
 ID                       Integer       4               Yes              Measure cost per year id
 IDMEASURE                Integer       4               Yes              Measure id
 COSTYEAR                 Integer       4               Yes              Financial Year                2007          year
 COST                     Double        8               Yes              Cost in this year                           M euro
 Index Name               Ascending     Unique          Fields
 FDO_OBJECTID             Yes           Yes             OBJECTID
 GDB_48_IDMEASURE         Yes           No              IDMEASURE

Table 24. RailMeasureFunding table. This table contains financial sources for road projects.
 RailMeasureFunding

 Alias                    RailMeasureFunding
 Dataset Type             Table
 Field Name               Type          Length          Null             Description                   Example       Unit
 OBJECTID                 OID           4               No
 IDMEASURE                Integer       4               Yes              Measure id
 NATIONALBUDGET           Double        8               Yes              National budget                             M euro
 TENTBUDGET               Double        8               Yes              TEN-T budget                                M euro
 COHESIONFUNDS            Double        8               Yes              Cohesion funds                              M euro
 ISPAFUNDS                Double        8               Yes              ISPA funds                                  M euro
 ERDFFUNDS                Double        8               Yes              ERDF funds                                  M euro
 EIBLOANS                 Double        8               Yes              EIB loans                                   M euro
 EBRDLOANS                Double        8               Yes              EBRD loans                                  M euro
 OTHERIFISLOANS           Double        8               Yes              Other IFIS loans                            M euro
 PRIVATECAPITAL           Double        8               Yes              Private capital                             M euro
 OTHERSOURCE              Double        8               Yes              Other source                                M euro
 Index Name               Ascending     Unique          Fields
 FDO_OBJECTID             Yes           Yes             OBJECTID
 GDB_49_IDMEASURE         Yes           No              IDMEASURE




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Table 25. RailCrossBorderParameterNA table. This table contains parameter data for railway border
crossings.
 RailCrossBorderParameterNA

 Alias                       RailCrossBorderParameterNA
 Dataset Type                Table
 Field Name                  Type            Length       Null         Description                             Example               Unit
 OBJECTID                    OID             4            No
 RailCrossBorderId           Integer         4            Yes          Rail cross border node id
 NoTracksIn                  Integer         4            Yes          No. of tracks (approaching railway)
 NoTracksBetween             Integer         4            Yes          No. of tracks (between the border stations)
 NoTracksYard                Integer         4            Yes          Railway yard, no. of tracks
 NoTracksInspection          Integer         4            Yes          No. of tracks for inspection of freight trains
                                                                       Passenger         trains,     border      Border/Train/No
 PassengerFormalities        Integer         4            Yes          formalities                               Data
 OpeningHours                String          50           Yes          Opening hours                             24 h                text
 Reload                      Integer         4            Yes          Reloading at border                       yes/no/no data
 AxelChange                  Integer         4            Yes          Axel change facilities at border          yes/no/no data
 CapacityEnterFreightTrain
 s                           Double          8            Yes          Capacity, entering freight trains                             train/d
 CapacityEnterPassengerT                                               Capacity, entering passenger
 rains                       Double          8            Yes          trains                                                        train/d
 CapacityExitFreightTrains   Double          8            Yes          Capacity, exiting freight trains                              train/d
 CapacityExitPassengerTra
 ins                         Double            8          Yes          Capacity, exiting passenger trains                            train/d
 Year_                       Integer           4          Yes          Year of construction                                          yyyy
 ObjectClass                 Domain
 PassengerFormalities        PassengerFormalitiesNA
 Reload                      geomYesNo
 AxelChange                  geomYesNo
 Index Name                  Ascending         Unique     Fields
 FDO_OBJECTID                Yes               Yes        OBJECTID



Table 26. RailCrossBorderVolumeNa table. This table contains traffic volume data for railway border
crossings.
 RailCrossBorderVolumeNA

 Alias                RailCrossBorderVolumeNA
 Dataset Type         Table
 Field Name           Type           Length        Null          Description                             Example                   Unit
 OBJECTID             OID            4             No
 RailCrossBorderId    Integer        4             Yes           Rail cross border node id
 Year_                Integer        4             Yes           Estimated year                          2007                      year
 VolumeType           Integer        4             Yes           Type of the estimate                    counting/forecast         code
 PassengerTrains      Double         8             Yes           Annual number of passenger trains                                 train/a
 FreightTrains        Double         8             Yes           Annual number of freight trains                                   train/a
 FreightImported      Double         8             Yes           Imported freight                                                  ton/a
 FreightExported      Double         8             Yes           Exported freight                                                  ton/a
 Passengers           Double         8             Yes           Annual number of total passengers                                 PAX
 ObjectClass          Domain
 VolumeType           VolumeType
 Index Name           Ascending      Unique        Fields
 FDO_OBJECTID         Yes            Yes           OBJECTID




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9.3.3    TEN-North integration to TEN-Link data
In the TEN-North database, many road and rail sections in EU-nations have similar geometry
with sections that exist in the TEN-Link database. These common geometries were linked to
each other with the means of linear referencing. As a result, two route event tables were added
to the TEN-North database. The linkage of TEN-North road sections to TEN-Link road
sections is described in the RoadToTenLink table. Similarly, the linkage of TEN-North
railway sections to TEN-Link railway sections is described in the RailToTenLink table.

Table 27. RoadToTenLink table. This is a event table links the TEN-North roads to TEN-Link roads.
 RoadToTenLink

 Alias           RoadToTenLink
 Dataset Type    Table
 Field Name      Type            Length   Null       Description         Example   Unit
 OBJECTID        OID             4        No
 RoadID          Integer         4        No         TEN-North road id
 FromMeas        Double          8        Yes        From value                    /100=%
 ToMeas          Double          8        Yes        To value                      /100=%
 TENLINKID       Integer         4        Yes        TEN-Link id
 Index Name      Ascending       Unique   Fields
 FDO_OBJECTID    Yes             Yes      OBJECTID


Table 28. RailToTenLink table. This is a event table links the TEN-North railways to TEN-Link railways.
 RailToTenLink

 Alias           RailToTenLink
 Dataset Type    Table
 Field Name      Type            Length   Null       Description     Example       Unit
 OBJECTID        OID             4        No
 RailID          Integer         4        No         TEN-North rail id
 FromMeas        Double          8        Yes        From value                    /100=%
 ToMeas          Double          8        Yes        To value                      /100=%
 TENLINKID       Integer         4        Yes        TEN-Link id
 Index Name      Ascending       Unique   Fields
 FDO_OBJECTID    Yes             Yes      OBJECTID



In the RoadToTenLink table (Table 27) TEN-North road id number can be found from
RoadID field. The corresponding TEN-Link id number is in LinkID field. Fields FromMeas
and ToMeas represent the proportions of intersection between TEN-North links and TEN-
Link links as percentage values.


In the RailToTenLink table (Table 28) TEN-North rail id number can be found from RailID
field. The corresponding TEN-Link id number is in LinkID field. Fields FromMeas and
ToMeas represent the proportions of intersection between TEN-North links and TEN-Link
links as percentage values.


9.3.4    Other objects
Other objects include three tables that decribe how particular road and railway sections in the
TEN-North data are part of priority axis projects. PriorityAxis table (table 29) lists priority
axis projects and PrioritySection table (table 30) lists sections of the priority axis projects.
PrioritySection2Section (table 31) connects priority axis sections to TEN-North sections.




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Table 29. PriorityAxis table. This table lists Prioroty axis projects.
 PriorityAxis

 Alias                              PriorityAxis
 Dataset Type                       Table
 Field Name                         Type              Length        Null         Description             Example       Unit
 OBJECTID                           OID               4             No
 ID                                 Integer           4             Yes          Id priority axis
 DESCRIPTION                        String            255           Yes          Description
 Index Name                         Ascending         Unique        Fields
 FDO_OBJECTID                       Yes               Yes           OBJECTID
 GDB_5_ID                           Yes               No            ID



Table 30. PrioritySection table. This table lists sections of priority section projects.
 PrioritySection

 Alias                              PrioritySection
 Dataset Type                       Table
 Field Name                         Type              Length        Null         Description                 Example      Unit
 OBJECTID                           OID               4             No
 ID                                 Integer           4             Yes          Id priority section
 DESCRIPTION                        String            255           Yes          Description
 IDAXIS                             Integer           4             Yes          Id priority axis
 Index Name                         Ascending         Unique        Fields
 FDO_OBJECTID                       Yes               Yes           OBJECTID
 GDB_6_ID                           Yes               No            ID
 GDB_6_IDAXIS                       Yes               No            IDAXIS



Table 31. PrioritySection2Section table. This table connects priority axis sections to TEN-North sections.
 PrioritySection2Section

 Alias                              PrioritySection2Section
 Dataset Type                       Table
 Field Name                         Type            Length          Null                 Description                 Example       Unit
 OBJECTID                           OID             4               No
 IDPRIORSECTION                     Integer         4               Yes                  Id priority section
 IDSECTION                          Integer         4               Yes                  Id road/rail section
 MODE                               Integer         4               Yes                  Transport mode
 Index Name                         Ascending       Unique          Fields
 FDO_OBJECTID                       Yes             Yes             OBJECTID
 GDB_7_IDPRIORSEC                   Yes             No              IDPRIORSECTION
 GDB_7_IDSECTION                    Yes             No              IDSECTION

9.3.5        Domains
Table 32. TEN-North domains.
 DesignPhaseNA                             EIAPhaseNA                           geomActivity                            geomAirportType

 Domain Type        Coded Value            Domain Type         Coded Value      Domain Type          Coded Value        Domain Type        Coded Value
 Field Type         Integer                Field Type          Integer          Field Type           Integer            Field Type         Integer
 Merge Policy       Default Value          Merge Policy        Default Value    Merge Policy         Default Value      Merge Policy       Default Value
 Split Policy       Default Value          Split Policy        Default Value    Split Policy         Default Value      Split Policy       Default Value
 Domain Members                            Domain Members                       Domain Members                          Domain Members
 Name               Value                  Name                Value            Name                 Value              Name               Value
 Feasibilty         1                      Completed           1                Freight              1                  Community          1
 Environmental      2                      Underway            2                Passenger            2                  International      2
                                                                                Passenger    and
 Technical          3                      N/A                 3                freight              3                  Regional           3
                                                                                No data              4                  No data            4

 geomIwwECMTClass                          geomIwwType                          geomMeasureStage                        geomMeasureType

 Domain Type        Coded Value            Domain Type         Coded Value      Domain Type          Coded Value        Domain Type        Coded Value
 Field Type         Integer                Field Type          Integer          Field Type           Integer            Field Type         Integer
 Merge Policy       Default Value          Merge Policy        Default Value    Merge Policy         Default Value      Merge Policy       Default Value
 Split Policy       Default Value          Split Policy        Default Value    Split Policy         Default Value      Split Policy       Default Value
 Domain Members                            Domain Members                       Domain Members                          Domain Members
 Name               Value                  Name                Value            Name                 Value              Name               Value
 I                  1                      River               1                Completed            1                  New construction   1
 III                2                      Canal               2                Under construction   2                  Rehabilitation     2
 IV                 3                      No data             3                Under study          3                  Upgrade            3
 Va                 4                                                           Planned              4                  No data            4
 Vb                 5                                                           No data              5
 Vc                 6
 VIc                7
 VIb                8
 VIa                9
 VII                10
 No data            11




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geomMeasureUnderStudy                       geomRailERTMSLevel                    geomRailHSCategory                      geomMeasureYear

Domain Type                 Coded Value     Domain Type          Coded Value      Domain Type             Coded Value     Domain Type         Coded Value
Field Type                  Integer         Field Type           Integer          Field Type              Integer         Field Type          Integer
Merge Policy                Default Value   Merge Policy         Default Value    Merge Policy            Default Value   Merge Policy        Default Value
Split Policy                Default Value   Split Policy         Default Value    Split Policy            Default Value   Split Policy        Default Value
Domain Members                              Domain Members                        Domain Members                          Domain Members
Name                        Value           Name                 Value            Name                    Value           Name                Value

                                                                                  I - speed equal to
                                                                                  or greater then 250
feasibility                 1               1                    1                km/h                    1               1996                1996
                                                                                  II - speed of the
environmental               2               2                    2                order of 200 km/h       2               1997                1997
                                                                                  III - speed adapted
                                                                                  to topogr., relief or
                                                                                  town-planning
technical                   3               3                    3                const.                  3               1998                1998
feasibility,
environmental               4               No data              4                No data                 4               1999                1999
feasibility, technical      5                                                                                             2000                2000
environmental,
technical                   6                                                                                             2001                2001
feasibility,
environmental,
technical                   7                                                                                             2002                2002
No data                     8                                                                                             2003                2003
                                                                                                                          2004                2004
                                                                                                                          2005                2005
                                                                                                                          2006                2006
                                                                                                                          2007                2007
                                                                                                                          2008                2008
                                                                                                                          2009                2009
                                                                                                                          2010                2010
                                                                                                                          2011                2011
                                                                                                                          2012                2012
                                                                                                                          2013                2013
                                                                                                                          2014                2014
                                                                                                                          2015                2015
                                                                                                                          2016                2016
                                                                                                                          2017                2017
                                                                                                                          2018                2018
                                                                                                                          2019                2019
                                                                                                                          2020                2020
                                                                                                                          No data             2222

geomRailTrackGauge                          geomRailTraction                      geomRailType                            geomRoadType

Domain Type                 Coded Value     Domain Type          Coded Value      Domain Type             Coded Value     Domain Type         Coded Value
Field Type                  Integer         Field Type           Integer          Field Type              Integer         Field Type          Integer
Merge Policy                Default Value   Merge Policy         Default Value    Merge Policy            Default Value   Merge Policy        Default Value
Split Policy                Default Value   Split Policy         Default Value    Split Policy            Default Value   Split Policy        Default Value
Domain Members                              Domain Members                        Domain Members                          Domain Members
Name                        Value           Name                 Value            Name                    Value           Name                Value
1435                        1               Electrified          1                conventional            1               motorway            1
1520                        2               Diesel               2                high speed              2               high quality road   2
1668                        3               No data              3                No data                 3               ordinary road       3
1524                        4                                                                                             No data             4
1602                        5
1000                        6
1600                        7
No data                     8

geomYear                                    geomYesNo                             PassengerFormalitiesNA                  PavementNA

Domain Type                 Coded Value     Domain Type          Coded Value      Domain Type             Coded Value     Domain Type         Coded Value
Field Type                  Integer         Field Type           Integer          Field Type              Integer         Field Type          Integer
Merge Policy                Default Value   Merge Policy         Default Value    Merge Policy            Default Value   Merge Policy        Default Value
Split Policy                Default Value   Split Policy         Default Value    Split Policy            Default Value   Split Policy        Default Value
Domain Members                              Domain Members                        Domain Members                          Domain Members
Name                        Value           Name                 Value            Name                    Value           Name                Value
2002                        2002            Yes                  1                Border                  1               asphalt             1
2003                        2003            No                   2                Train                   2               concrete            2
2004                        2004            No data              3                nodata                  3               light               3
2005                        2005
2013                        2013
2020                        2020
No data                     2222
2007                        2007

ResponsibilityNA                            StageNA                               VolumeType                              CountryNA

Domain Type                 Coded Value     Domain Type          Coded Value      Domain Type             Coded Value     Domain Type         Coded Value
Field Type                  Integer         Field Type           Integer          Field Type              Integer         Field Type          Integer
Merge Policy                Default Value   Merge Policy         Default Value    Merge Policy            Default Value   Merge Policy        Default Value
Split Policy                Default Value   Split Policy         Default Value    Split Policy            Default Value   Split Policy        Default Value
Domain Members                              Domain Members                        Domain Members                          Domain Members
Name                        Value           Name                 Value            Name                    Value           Name                Value
National                    1               DesingStudyPhase     1                Traffic                 1               Estonia             204
Federal                     2               PlanningPhase        2                Forecast                2               Finland             205
Regional                    3               UnderConstruction    3                                                        Germany             206
Privat                      4               Completed            4                                                        Latvia              210
                                                                                                                          Lithuania           212
                                                                                                                          Poland              216
                                                                                                                          Sweden              222
                                                                                                                          Belarus             227
                                                                                                                          Norway              228
                                                                                                                          Russia              229
                                                                                                                          border              999




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Data validation


The TEN-North data went through several data validation rules during data collection and
data loading into database. After the data was collected from providers, it was checked and
possible shortcomings of the data were requested to be filled. Next country reports were made
and sent to country experts, who also examined the data for possible errors or shortcomings.
After country experts’ examination, data was loaded into database. During data loading
process, data was continuously reviewed and checked for errors that might have passed
antecedent investigations. Eventually, when data was completely loaded into database,
topological checks were made to the geometries of the data.
During the data collection and data loading processes, checks were done using certain
validation rules. Rules were adopted from TEN-T database guidelines.
Validation rules are presented in the table 33 below. Rules were mainly applied manually.
Geometrical validation rules were however applied automatically, using geodatabase topology
rules.
Table 33. Validation rules
 ROADS SECTIONS
 Attribute                      Validation rule
 Country                        Country cannot be Null
 Code                           Code cannot be Null / Code must be unique
 Start node                     Start node cannot be Null
 End node                       End node cannot be Null
 Geometry                       Geometry cannot be Null
                                The roads sections must be smoothly linked (snapped) to other sections / the network
 Geometry
                               cannot contain holes / the sections cannot overlap / the sections cannot cross
 Start node                     Start node must be located at the geometrical start of the section
 End node                       End node must be located at the geometrical end of the section

 ROADS’ PARAMETERS
 Attribute                      Validation rule
 Design speed                   Design speed value must be numeric (integer) or Null
 Design speed                   Value must be between 50 and 250
 Max. gradient                  Max. gradient speed value must be numeric (integer) or Null
 Max. gradient                  Value must be between 0 and 50
 Max. axle load                 Max. axle load value must be numeric (integer) or Null
 Max. vehicle weight            Max. vehicle weight value must be numeric (integer) or Null
 Max. vehicle weight            Value must be between 1 and 100
 Nr of lanes                    Nr of lanes value must be numeric (integer)
 Nr of lanes                    Value must be between 2 and 10
 Type/Year                     The network elements cannot degrade its status over the certain period of time
 Length                        If the type of the section does not change the total length cannot change
 Design speed Max. gradient
                               If the type of the section does not change the section parameters cannot degrade over
 Max. axle load Max. vehicle
                               the certain period of time
 weight Nr of lanes

 ROADS’ NODES & ROAD BORDER NODES
 Attribute                     Validation rule
 Country                       Country cannot be Null
 Name                          Name cannot be Null / Name must be unique
 Geometry                      Geometry cannot be Null

 RAILWAYS SECTIONS
 Name                           Validation rule
 Country                        Country cannot be Null
 Code                           Code cannot be Null / Code must be unique
 Start node                     Start node cannot be Null
 End node                       End node cannot be Null
 Geometry                       Geometry cannot be Null
                                The railways sections must be smoothly linked (snapped) to other sections / the
 Geometry
                               network cannot contain holes / the sections cannot overlap / the sections cannot cross
 Start node                     Start node must be located at the geometrical start of the section
 End node                       End node must be located at the geometrical end of the section




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RAILWAYS’ PARAMETERS
Name                            Validation rule
Nr of tracks                    Nr of tracks value must be numeric (integer)/ Value must be between 1 and 10
Min. radius                     Min. radius value must be numeric (integer) or Null
Design speed                    Design speed value must be numeric (integer) or Null
Design speed                    Value must be between 50 and 500
Max. speed                      Max. speed value must be numeric (integer) or Null
Max. speed                      Value must be between 10 and 500
Max. gradient                   Max. gradient value must be numeric (integer) or Null
Max. gradient                   Value must be between 0 and 50
Max. axle load                  Max. axle load value must be numeric (double) or Null
Power supply voltage            Power supply voltage value must be numeric (integer) or Null
Power supply voltage            Value must be between 1000 and 500000
Type/Year                      The network elements cannot degrade its status over the certain period of time
Length                         If the type of the section does not change the total length cannot change
Design speed Max. gradient
                               If the type of the section does not change the section parameters cannot degrade over
Max. speed Max. axle load
                               the certain period of time
Min. radius Nr of tracks
Track gauge                    Track gauge value cannot change over the certain period of time

RAILWAYS’ NODES RAILWAY BORDER NODES
Attribute                      Validation rule
Country                        Country cannot be Null
Name                           Name cannot be Null / Name must be unique
Geometry                       Geometry cannot be Null

MEASURES
Attribute                      Validation rule
Country                        Country cannot be Null
Code                           Code cannot be Null / Code must be unique in the country
Start node                     Start node cannot be Null
End node                       End node cannot be Null
Start year                     Start year cannot be Null
End year                       End year cannot be Null
Start year                     Start year must be less or equal to End year
Total Cost                     Total Cost value must be numeric (double) / Total cost cannot be Null
Type                           Type cannot be Null
                               Measure must be referenced with one or more infrastructural section (road or railway)
Description/Type               The measure description must be correlated with the measure type.

MEASURES’ FUNDING
Attribute                      Validation rule
National Budget Contribution   National Budget Contribution value must be numeric (double) or Null
TEN-T Budget Contribution      TEN-T Budget Contribution value must be numeric (double) or Null
Cohesion Funds Contribution    Cohesion Funds Contribution value must be numeric (double) or Null
ISPA/IPA Contribution          ISPA/IPA Contribution value must be numeric (double) or Null
ERDF Funds Contribution        ERDF Funds Contribution value must be numeric (double) or Null
EIB Contribution               EIB value must be numeric (double) or Null
EBRD Contribution              EBRD Contribution value must be numeric (double) or Null
Other IFIs Contribution        Other IFIs Contribution value must be numeric (double) or Null
Private Capital Contribution   Private Capital Contribution value must be numeric (double) or Null
Other Contribution             Other Contribution value must be numeric (double) or Null
                               The sum of all Contributions must be equal to project’s total cost

MEASURE COSTS PER YEAR
Attribute                      Validation rule
Year                           Year cannot be Null
Cost                           Cost value must be numeric (double) or Null
Cost                           Sum of all project’s Costs must be less or equal to project’s total cost




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Appendix 4: Evaluation System of Roads and Railways

ROADS

ANALYSIS OF ROAD PERFORMANCE

In Chapter 3, Analytical Support Framework, it was proposed that the analysis of the
Northern Axis road system should be done using the selected performance measures. Because
this is not possible due to lack of data, an alternate method emulating the selected
performance-based approach is presented below.

The basic rationale for analysing the Northern Axis roads is that the all the roads of the
system should be able to carry a heavy commercial vehicle of the EU dimensions and weights
at the reasonable speed. The reasonable speed is assumed 80 km/h, which is the most
common speed limit for HGVs in Europe. All deficiencies in road performance with regard
these basis requirements can be considered bottlenecks.

It should be pointed out that the analysis system achieves only the screening of the Northern
Axis road system in very broad terms, which is limited by available data. Bottleneck analysis
and prioritizing is carried out as a separate step.

The analysis of roads is composed of three different tests, which are described below.

1. Heavy Goods Vehicle regulations

The test deals with the harmonisation of HGV dimensions in axes countries. The base
standards of the EU for HGV sizes and weights are as follows, which represent the allowable
maximums of the heaviest articulated tractor-trailer combination:
Max length (m)                   18,75
Max height (m)                    4,00
Max width (m)                     2,55
Max weight (t)                   44,00
Max axle weight (t)              11,50

2. Basic road capacity

The test is the first rough estimate of road capacity. It is based on two types of roads: 2-lane
standard road and a 4-lane motorway. The default capacities are as follows:

Average Daily Volumes (ADT):
2-lane road        20 000 passenger car units per day (PCU/day)
4-lane motorway    80 000 passenger car units per day

Peak Hour Volumes:

2-lane road              2 000 passenger car units per day (PCU/day)
4-lane motorway          8 000 passenger car units per day


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The above capacities are rounded values, which are based on the Highway Capacity Manual
2000 (HCM2000) of the U.S. Transportation Research Board. These values must be
considered as defaults, as the road section specific values should be used, if known.

HCM defines different levels of service, which relate the observed and forecast traffic volume
to the type of road, i.e. volume/capacity. In this study the levels of service are not used, but
the main indicator of performance is the attainable speed of an HGV and ensuing delay.

3. HGV speed and speed loss

It is assumed that the desired HGV speed limit is 80 km/h or greater in the entire system.
Converting it into travel speed, it will mean 75 km/h. This is used as a threshold value in the
analyses.

HGVs can maintain this speed as long as the general speed of traffic is greater than 75 km/h.
When the speed of passenger cars also drops below 75 km/h, it is assumed that the HGVs
must lower their speed accordingly. At speeds below 75 km/h the HGVs travel at the speed of
other traffic.

Volume and speed relationships are best presented in the HCM. Based on the HCM principles
and other field data there are also more advanced methods developed for such analyses. Here
the method developed by the Texas Transportation Institute for “The 2005 Urban Mobility
Report, May 2005” covering the entire USA is used. If better and locally adopted methods are
available, they should be used in further analyses.

2-lane roads

HCM 2000 presents the graph below which shows average travel speeds as a function of two-
way flows on an ordinary 2-lane road. (In the graph FFS is Free Flow Speed)

The graph can also be converted into an equation for spreadsheet analyses. The equation is as
follows

        Average Travel Speed = (Free Flow Speed) – 0.0125*PCU/h




Average travel speed vs. two-way flow on a 2-lane road (source: HCM 2000)


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Motorways

For motorways with four or more lanes the TTI method and equations are used as shown in
the table below.

Estimating motorway speeds
Level of congestion      ADT per lane              Speed function
Uncongested              Under 15 000              60 mph * 1,6 = 100 km/h
Moderate                 15 001 – 17 500           74.45-(1.09 ADT/lane) * 1,6
Heavy                    17 5001 – 20 000          109.76-(3.10*ADT/lane) * 1,6
Severe                   20 001 – 25 000           135.08-(4.33 ADT/lane) * 1,6
Extreme                  Over 25 000               72.03-(1.75 ADT/lane) * 1,6
                                                   (Assume minimum speed 35 km/h)
Note:
• Original formulas give speeds in mph, therefore the multiplier 1,6 is used to give speeds in km/h
• ADT/ lane is expressed in 1000s.

The above formulas are based on a large volume of field studies all around the USA,
primarily in urban regions. In Europe the formulas might be somewhat different. However,
the severe congestion in the Northern Axis road system can only be found in the vicinity of
large urban centres.

In the formulas a 5% HGV share has been used. As on the Northern Axis roads much higher
HGV shares are common, PCUs have been used in the analyses instead of ADTs directly.

4. Recurring and incident delay

The speed loss and ensuing delay due to congestion, as described above, is reasonably regular
and can be anticipated and estimated. Therefore, it can be called “recurring delay”. In addition
to congestion, there are also other types of delays, which are caused by various incidents such
as accidents, weather, road works, and signals or signalised road sections. While they do not
affect any given location very frequently, they do occur regularly in the system. With
increasing traffic volumes, congestion and ageing infrastructure those kinds of incidents have
become more frequent and their impacts more severe. They cause incident-related delay,
which affect particularly heavily HGV traffic.

With new investigation methods incident-related delay has become more transparent and it
can even be predicted with increasing accuracy in the system or over a period of time.

In the USA, a good database has been collected of incident-related delay, which shows how
significant its effect is. On American freeways incidents have found to add anywhere between
60%-250% to the recurring congestion-related delay. On the arterial street system the effect is
110% on average.

Based on the above, in the Northern Axis analysis we assume that the incident-related delay
adds 100% or doubles the estimated congestion related delay.

In Chapter 3, Analytical Support Framework, there is a description of the concept of travel
time reliability and buffer time. For the purposes of this analysis the incident-related delay
can be considered to represent the variability of travel time that one must be plan for before
the trip. Planning is done by assuming a reasonable buffer time in case of unknown events
during the trip.

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5. Other cases and events that are not considered in the analysis

For completing the delay discussion, additional and often important cases must be mentioned,
which are not considered in the analysis due to lack of information. They include the
following:
• Poor road pavements, which are mostly a transport cost issue due to wear and tear on a
    vehicle. However, there may be so poor pavements over extended lengths of the road,
    which are not repaired over a long time. These situations may considerably slow down
    traffic that is using them. Road roughness is measured in IRI and data is available in many
    countries today.
• Weak bridges that cause some HGVs to divert to long detours.
• Narrow or low bridges and tunnels, which also present bottlenecks to some HGVs.

These considerations should be brought into the analysis in the future work as well.




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RAILWAYS

The evaluation system for railways is composed of five different tests, which are described
below.

1. Operational requirements

                               National      UIC                 Non-
                             reguirement reguirement           compliance

Train length, max                                  750
Train weight, max                                 3000
Speed of freight train (km/h)                      100




2. Technical requirements

                               National      UIC                 Non-
                             requirement requirement           compliance

Track gauge (m)
Load gauge (class)                                 GC
Max. Axle load (tons)                              22,5
Power supply (type)
Signalling system (type)                         ERTMS
Communications (type)                            GMS-R


3. Basic railway capacity

According to the European Rail Infrastructure Master Plan (ERIM) study of the UIC,
the theoretical capacities of European railways are as shown in table below.


                Single          Double
                 track           track
Insufficient      <74            <275        trains per day in both directions
Good            74-150          275-400
Excellent        >150            >400

UN/ECE recommends to use practical capacities as follows:
Single track     60-80 trains/day
Double track     100-200 trains/day

The above values can be considered as defaults, if no better information
is available. Normally the railway companies know the link-specific
capacities, which should be used in the analysis.




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4. Capacity utilisation (congestion)


                                           Capacity utilization
Case 1     Free flow                       < 70 %
Case 2     Normal                          70%-85%
Case 3     Congestion                      85%-100%
Case 4     Heavily congested               > 100%




5. Transport delay (freight)


                                     Single track                    Double track
                                     Insufficient Good     Excellent Insufficient Good               Excellent
Case 1   Free flow                       <52                 <105       <193                           <280
Case 2   Normal                         52-63               105-128    193-220                        280-340
Case 3   Congestion                     63-74               128-150    220-275                        340-400
                                                                                  275-
Case 4   Heavily congested                >74       74-150   >150        275       400                  400




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Appendix 5: Transport Modelling

FREIGHT TRANSPORT

Freight modelling
The objectives and scope of the freight modelling, methods and data is described in a general
way in the Chapter 7.2, Freight. This appendix includes additional and supportive material for
freight modelling, not found in the report itself.

Commodity segmentation and base year matrix
Different segmentations are used in the alternative sources both for the commodity
classifications and for the geographical zoning. The reference classifications are those used in
FRISBEE as this model is the tool used for the simulation of traffic scenarios and through
adopting the same classifications the need to recalibrate the model can be avoided. Therefore,
the data from the other sources has to be translated into the FRISBEE classifications.

The segmentation of commodities used in FRISBEE is based on the SITC classification and
includes 12 different segments. A reasonable correspondence can be defined between the
FRISBEE segments and the NST/R classification which is the base for the segmentation used
in the SCENES model (13 segments) and used in the ETIS-BASE segmentation.

All things considered, it has been decided to use the COMEXT database as the reference
source for the international part of freight matrix, while the SCENES model was considered
for adding the domestic demand. The choice can be justified as follows:

      •   COMEXT is an official European source which report observed trade data;
      •   COMEXT data is available according to a very detailed commodity classification
          which can be used to match the reference segmentation used in FRISBEE
      •   Even if also ETIS-BASE includes domestic data, SCENES was considered more
          reliable on this respect14.

From the original COMEXT data, a country to country matrix for the 12 freight segments has
been extracted in terms of thousand tonnes per year. Starting from this matrix, further
operations were required to translate the base year freight matrix in the requested format.

The following task was aimed at splitting or aggregating the country-to-country matrix
according to the FRISBEE zoning system. The aggregation of more countries in a single zone
was straightforward. The split of countries into NUTS2 or NUTS3 zones has been obtained
using the original FRISBEE matrix as reference. The relative share of freight leaving from or
arriving at each zone for each segment and each country-to-country O/D pair has been
computed from the FRISBEE matrix and applied to the COMEXT data. Since the FRISBEE


14
     There are two main reasons for this choice: first ETIS uses the NST/R segmentation which is less
      correspondent than the SCENES one to the FRISBEE flows. Second, the ETIS matrix is symmetrical (i.e.
      includes return trips) while the objective of the estimation was to get a pure matrix of shipment between
      zones.


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matrix did not report data for some O/D pairs with Russia, the relative shares of Russian
zones have been estimated according to the population of the zones.

The next task needed to produce the base year matrix consisted of adding the amount of
freight flows between Russia and non European countries. Such flows are not reported in
COMEXT nor in other matrices like SCENES or ETIS. Data on freight flows between Russia
and non-European countries had been provided by MATREX and drawn from previous
projects (EUVELI).

The final step required to generate the base year matrix involved adding the domestic demand
drawn from the SCENES matrix (except for Russia which were drawn from FRISBEE). As
for the international flows, a translation into the zoning system and the commodity
classification of FRISBEE has been carried out. The same approach described above has been
adopted.

The final result of the tasks described above was the base year matrix of freight flows for the
study area. Some aggregate figures describing the matrix are reported in the following tables.

This matrix was used as base for the estimation of the matrices for the future years (2010 and
2020).

Forecast approach
The forecasts (2010 and 2020) were produced following the approach described below.

The economic forecasts provided by Task 4A (Chapter 6) were taken as reference for
estimating the change of trades in the North Corridor area. Task 4A produced estimates of the
development of the total trade between each country belonging to the study area. From these
estimates the growth rates for each country-to-country flow is calculated.

On the other hand, also the freight matrices for the future years (2010 and 2020) produced in
SCENES were considered. From these matrices two key elements can be drawn:

The growth rates of freight flows for each sector and;
The growth rates of freight flows for origin-destination pairs at the regional level.

These two elements were used together with the Task 4A results, using the latter as reference
for the average evolution of flows and the SCENES data for defining the differences among
demand segments and origin-destination pairs at the NUTS2 level.

The specific growth rates were therefore applied to the base year matrix in order to compute
the two future matrices: for the year 2010 and for the year 2020.




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Matrices


Freight flow forecast 2010 between Northern axis countries (1000 tons/a)
Country     Bel    Est      FIN          Ger         Lat       Lit       Nor      Pol       Rus           Swe       Sum
Belarus        -     235        56         1 340      1 090      1 919       -     1 833            -         38      6 512
Estonia       26       -     2 143           974        770        333     854       175          151      3 244      8 670
Finland       11     911         -        6 442         317        120     643       752        1 925      4 696     15 817
Germany      688     489     2 849             -        221        565    2535    12 490        2 494      8 565     30 897
Latvia        39     339       667         1 653          -        441      60       152          190      5 275      8 816
Lithuania    271     196       134         1 441      1 082          -     205     1 386          631      1 110      6 455
Norway         -      63     5 250       35 078          69         57       -     1 147            -     16821      58 486
Poland       423     122     3 869       28 887         241        436     986         -        1 276      2 580     38 821
Russia         -   3 679    29 987       56 371       1 667     10 701       -    41 984            -      7 823    152213
Sweden        13     246     6 154       13 980         314        175    6309     1 949          417          -     29 558
Sum         1471   6 281    51 109       146166       5 773     14 747   11592    61 869        7 083     50152     356244




Russian growth scenarios
The Russian exports by commodity, Base year (2000), Forecasts 2010 and 2020, Basic, Min and
Max economic growth
Russia export, million                               Basic                       Max                        Min
tons/a
Demand segment               Base                  2010        2020       2010          2020            2010        2020
                             year
1 - Food and Live              0,71                0,90         1,21       0,81          0,98            1,17        2,04
Animals
2 - Beverages and                 0,02             0,03         0,04       0,02          0,03            0,04        0,06
Tobacco
3 - Raw materials,            61,90             82,06         109,48      73,59         88,69       106,15         184,31
inedible, except fuels
4 - Mineral fuels,            312,4            402,18         514,25     402,18        467,50       446,05         650,25
lubricants and related            7
materials
5 - Animal and vegetable          0,00             0,00         0,00       0,00          0,00            0,00        0,00
oils, fats, waxes
6 - Chemicals and related     11,21             19,61          32,79      24,94         53,01           13,83       16,18
products
7 - Paper, paper board,           2,42             4,15         7,13       5,28         11,52            2,93        3,52
paper pulp
8 - Metal products            41,95             72,42         123,98      92,09        200,44           51,07       61,17
9 - Manufactured goods         1,87              3,33           5,64       4,23          9,12            2,35        2,78
10 - Machinery                 0,63              1,08           1,82       1,37          2,93            0,76        0,90
11 - Miscellaneous             0,09              0,15           0,25       0,19          0,41            0,11        0,12
manufactured items
12 - Valuable machinery,          0,04             0,06         0,09       0,07          0,15            0,04        0,04
manufactured articles
Total                             433               586         797        605           835             624         921




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The Russian imports by commodity, Base year (2000), Forecasts 2010 and 2020, Basic, Min and Max
economic growth
Russian import, million                         Base                   Max                   Min
tons/a
Demand segment              Current    2010        2020       2010       2020       2010       2020
1 - Food and Live           73,12      102,14      143,50     112,35     172,64     102,14     143,50
Animals
2 - Beverages and           0,16       0,22        0,31       0,24       0,37       0,22       0,31
Tobacco
3 - Raw materials,          20,10      28,13       39,58      30,94      47,62      28,13      39,58
inedible, except fuels
4 - Mineral fuels,          0,20       0,27        0,37       0,30       0,44       0,27       0,37
lubricants and related
materials
5 - Animal and vegetable    0,45       0,61        0,84       0,67       1,01       0,61       0,84
oils, fats, waxes
6 - Chemicals and related   1,44       2,22        3,23       2,44       3,88       2,22       3,23
products
7 - Paper, paper board,     3,05       4,32        6,12       4,75       7,36       4,32       6,12
paper pulp
8 - Metal products          3,52       4,96        6,97       5,45       8,39       4,96       6,97
9 - Manufactured goods      1,07       1,62        2,38       1,78       2,86       1,62       2,38
10 - Machinery              3,38       4,77        6,72       5,25       8,08       4,77       6,72
11 - Miscellaneous          0,29       0,43        0,63       0,48       0,76       0,43       0,63
manufactured items
12 - Valuable machinery,    0,17       0,25        0,36       0,28       0,43       0,25       0,36
manufactured articles
Total                       107        150         211        165        254        150        211




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PASSENGER TRANSPORT

Data sources
The main data sources used for the analysis of the road passenger traffic are:
   • The SCENES model travel demand data by mode of travelling for EU Member
       States15.
   • The ETIS data for the year 2000 (and 2020) on road passengers between the EU27
       Member States plus Russia, Belarus and Ukraine.
   • The Finnish Road Administration data on the monthly statistics of border traffic; lists
       the numbers of vehicles having crossed the border at each border post. In addition, the
       Finnish Border Guard Administration records similarly also the numbers of passengers
       at each border post.

The ETIS database gives information on the private car passenger transport between the
countries, and as such is not directly comparable to the FRA data. Summary of the Finnish
National Board of Customs data for vehicles arriving and departing Finland by crossed border
is given in the table below.

Road transport arriving and departing Finland16

           Road Transport - Vehicles arrived and
                  departed (thousands)                       Passengers cars                     Buses
Year                                                 Arrived        Departed            Arrived     Departed
          Land border with Russian Federation             1241.08          1275.427         16.735      18.305
          Land border with Sweden                         2785.53          2846.654         10.199      10.083
 2005




          Land border with Norway                         461.625            431.577         4.335       5.375
          Sea border                                      672.192            640.041        18.591      18.949
          All borders                                    5160.427          5193.699          49.86      52.712
          Land border with Russian Federation            1246.452          1289.621         16.195       17.02
          Land border with Sweden                        2769.264          2769.401         15.905       16.01
 2000




          Land border with Norway                         468.583            432.707         5.938       5.711
          Sea border                                      510.596            502.827        14.815      14.905
          All borders                                    4994.895          4994.556         52.853      53.646
          Land border with Russian Federation             575.821            591.068        14.883      14.625
          Land border with Sweden                        2931.869          2932.072          9.315       9.335
 1995




          Land border with Norway                         401.137            401.952          7.87       7.791
          Sea border                                      418.949            410.258        12.443      12.254
          All borders                                    4327.776            4335.35        44.511      44.005

The Finnish National Board of Customs data (FNBC, 2007) on the monthly statistics of the
number of vehicles having crossed the border indicates that the passenger car journeys to and
from Finland had slightly increased (by 3.7%) between the 2000 and 2005, contrary to the bus
journeys that had declined, apart on the Russian border that seem to have attracted more bus
journeys in 2005 than in 2000. The Sea border is emerging as one with the highest growth in
the car and bus passenger traffic.

15
  The main data source used for the estimation of the 2000 base year matrix in SCENES model is EUROSTAT
(2005) [ETIF 2004] for 1993-2002/03. The passenger data is used from Tables 3.3.7-12.
16
     Source: Finnish National Board of Customs, 2007

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The total passenger car traffic on the Finland-Russia border had a sharp rise (117%) between
the 1995 and 2000, and then a slight decline (-0.8%) between the 2000 and 2005.

The definitions for the FAA and ETIS data are different and hence the two data sources are
not directly comparable. The ETIS definitions imply that it is likely that the car passenger
trips in ETIS reflect long distance cross border movements only.

The main data sources for the analysis of rail passenger journeys are:
   • The SCENES model travel demand data by mode of travelling for EU Member States.
   • The ETIS data for the year 2000 (and 2020) on rail passengers between the EU27
      Member States plus Russia, Belarus and Ukraine.

The FRA (Finish Railway Administration) data only gives the aggregated data on passenger
volumes by rail to and from Finland. More detailed data on passenger flows by the railway
companies is not available for the study. Generally no other origin-destination data other than
the ETIS is available.

The Finish Railway Administration data (FRA, 2007) on passenger volumes by rail indicates
that the rail journeys have been steadily increasing in the last 25 years, with the long distance
international journeys having a higher growth of 30% between the year 2000 and 2005, than
the national long distance journeys (over 75 km) with an increase of 6% between the year
2000 and 2005. The FRA data is shown in the table below.

FRA Rail transport passenger demand in Finland over the period 1980 - 200517

 Railway Transport -
 passengers, total (1,000)   1980       1990      2000       2001       2002      2003       2004       2005
 Long Distance, over 75
 km                           11170      11440     11783      11561      11643     11915      12129      12503
 Of which in international
 transport                      119        277        206        240       266        256        252       267


For the year 2000, the ETIS database gives the total number of rail journeys within Finland of
11.8 millions which matches reasonably well with the FRA long distance rail journeys.
The major rail corridor within the study area is Helsinki - St. Petersburg - Moscow. Passenger
numbers crossing the Finnish-Russian border have been validated by local expert’s data
sources, and the number of total crossings in the 2005 matches the FRA estimates.
Apart from the above main data sources, a variety of research papers have been checked in
order to assess the current travel demand for the study area. This was important in particularly
for rail journeys as the information on rail travelling is very poor. The study Trade and
Transport Facilitation Audit of The Baltic States (The World Bank, 2005)18 collected
information on inland and international rail passengers in the Baltic States.




17
  Source: FRA, 2006
18
  The World Bank, 2005, Trade and Transport Facilitation Audit of The Baltic States, On a
Fast Track to Economic Development.

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Rail Passengers in the Baltic States from 1996 to 2002/3 (10)
 Country      Pax transported     1996     1997     1998        1999   2000   2001    2002     2003
              (millions)
 Estonia      Inland              6.2      5.1      6.5         6.6    7.1    5.4     5.1
              International       0.5      0.5      0.3         0.2    0.1    0.1     0.1
 Latvia       Inland              34       31.9     29.2        24.1   17.5   19.6    21.5     22.6
              International       1.2      1.1      0.9         0.7    0.7    0.5     0.5      0.4
 Lithuania    Inland              11.2     9.2      9           9.1    7.4    6.3     5.8      6
              International       2        1.9      1.7         1.5    1.4    1.4     1.5      1


The rail journeys, both international and ‘inland’ (national) were in decline in Estonia and
Lithuania, with only Latvia having an increase of the inland rail passenger demand.

The ETIS rail passenger journeys are in general below above figures. Based on the
methodology used to estimate the passenger demand in ETIS, it is concluded that the ETIS
figures for the rail passenger demand are likely to reflect the long distance cross border trips.

The main data sources used for the analysis of air passenger demand are:
    • The SCENES model travel demand data by mode of travelling for EU Member States.
    • The ETIS data for the year 2000 (and 2020); gives origin-destination matrix of air
        passengers between EU 27 Member States plus Russia, Belarus and Ukraine.
    • International Civil Aviation Organization (ICAO) On-Flight Origin and Destination
        (OFOD) data that shows on an aggregate basis the number of passengers between all
        international city-pairs on scheduled services. The information is available for the
        period from 1995 to 4th quarter of 2005. However for some of the city pairs that are on
        the Northern Axis corridor, for example Helsinki-Moscow, the data is given for 2003,
        2004 and 2005. Despite those gaps in the data, it still provides a useful source for the
        study.
A cross-check of the base year 2000 data in the ETIS database and the FAA data is shown in
the following table.
International air travel in Finland; 200019

 From Finland                 Air Passengers 2000       % difference
 to Country Destination       ETIS       FAA            ETIS versus FAA
 Norway                       68915      75088          -8%
 Sweden                       648166     655026         -1%
 Estonia                      78668      76438          3%
 Latvia                       32929      32647          1%
 Lithuania                    20300      19168          6%
 Germany                      339574     411175         -17%
 Russia                       97930      92528          6%
 Ukraine                      3922       2559           53%
 Poland                       43278      44895          -4%


19
     Source: ETIS, FAA 2007

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The two data sets match well for some of the country pairs (for instance, Finland-Sweden,
Finland-Latvia, the differences in traffic are within 1%), apart for the traffic to Ukraine that is
in general of a smaller magnitude and is of lesser concern, and to Germany where the
difference of 17% is more considerable.

For the air travel analysis, the ICAO data was used to give the number of passengers between
the major city pairs. Below figure shows the data on the main corridors between the 2000 and
2005. The data for Helsinki – St Petersburg, and Berlin – Helsinki were missing for the years
from 2000 to 2005, and represented trends are the extrapolations based on the past trends.

                                     AIR PASSENGER DEMAND ON NORTHERN AXIS CORRIDORS

               400000

               350000

               300000

               250000
  Passengers




               200000

               150000

               100000

                50000

                    0
                          Oslo -    Stockholm -   Helsinki - St.     Helsinki -      Berlin -   Berlin Moscow Riga - Moscow   W arsaw -   Riga - Helsinki   Vilnius -
                        Stockholm     Helsinki    Petersburg         Moscow          Helsinki                                 Moscow                        Helsinki

                                                                   2000       2001       2002      2003      2004       2005

Air passenger demand between major city pairs in Northern Axis


This shows that the passenger demand towards Moscow has been increasing on all of the
major corridors. The passenger demand on the Oslo-Stockholm and Stockholm-Helsinki
corridors are in line, with the demand declining between the 2000 and 2004. The trend has
stabilised from 2004 onwards.

GDP assumptions
Difference in GDP growth assumption in DG TREN (used in the SCENES Model) and this study
                    DG TREN Growth rates per Time Period TEN-Naxis GDP growth rates per Time Period DGTREN and this study GDP difference
Country               2000-2010 2010-2020      2000-2020     2000-2010     2010-2020       2000-2020 2000-2010 2010-2020      2000-2020
Germany                  113.1%    118.2%         133.6%        139.2%        114.9%          159.9%      1.23         0.97          1.20
Finland                  126.0%    120.5%         151.8%        126.2%        123.1%          155.4%      1.00         1.02          1.02
Sweden                   126.6%    125.8%         159.1%        132.0%        123.1%          162.5%      1.04         0.98          1.02
Estonia                  173.1%    150.3%         260.3%        168.6%        155.3%          261.8%      0.97         1.03          1.01
Latvia                   203.2%    163.7%         333.0%        158.3%        155.3%          246.0%      0.78         0.95          0.74
Lithuania                187.7%    160.9%         301.9%        149.2%        155.3%          231.7%      0.79         0.97          0.77
Poland                   146.9%    153.4%         225.1%        125.9%        141.1%          177.6%      0.86         0.92          0.79


The two GDP forecasts are broadly in line for Scandinavian countries, whereas there are some
considerable differences for the economies in the New Member States.




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           The Northern Transport Axis - Pilot for the analytical support framework to monitor the implementation
                                    of the infrastructure and “soft” measures proposed by the High Level Group
                                                                                 Appendix 5: Transport Modelling
Passenger Forecasts

Below table gives the ETIS forecast of the annual percentage change of total road passengers
on a country level for the period between 2000 and 2020 and the ASSESS forecast of the
annual percentage change of passenger kilometres over the period from 2000 and 2020.

Road passenger demand projections
                                                            ACCESS "Partial" scenario annual
                    ETIS annual % change of private         % change of road passenger
                    car passengers for the period           kilometres for the period 2000-
 By country         2000-2020                               2020
 Finland                                     1.1%                                      1.2%
 Norway                                      1.7%           na
 Sweden                                      1.0%                                      1.3%
 Estonia                                     1.7%                                      1.9%
 Latvia                                      0.1%                                      2.7%
 Lithuania                                    2.6%                                     2.4%
 Germany                                     0.7%                                      1.5%
 Russia                                      1.4%           na
 Ukraine                                     1.2%           na
 Poland                                      2.6%                                      3.2%
 Moldova                                     3.9%           na
 Belarus                                     1.5%           na
Note: data not directly comparable

Following table gives the ETIS forecast of the annual percentage change of rail passengers on
a country level for the period between 2000 and 2020 and the ASSESS forecast of the annual
percentage change of rail passenger kilometres over the period from 2000 and 2020.

Rail passenger demand projections
                                                            ACCESS "Partial" scenario annual
                    ETIS annual % change of rail            % change of rail passenger
                    passengers for the period 2000-         kilometres for the period 2000-
 By country         2020                                    2020
 Finland                                      0.6%                                     0.5%
 Norway                                       3.0%          na
 Sweden                                       0.6%                                     0.9%
 Estonia                                      0.2%                                    -0.4%
 Latvia                                       0.1%                                    -0.5%
 Lithuania                                    1.1%                                    -0.4%
 Germany                                      0.6%                                     0.7%
 Russia                                      -0.5%          na
 Ukraine                                      1.2%          na
 Poland                                       1.0%                                    -0.4%
 Moldova                                      4.1%          na
 Belarus
Note: data not directly comparable




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            The Northern Transport Axis - Pilot for the analytical support framework to monitor the implementation
                                     of the infrastructure and “soft” measures proposed by the High Level Group
                                                                                  Appendix 5: Transport Modelling
Below table gives the ETIS forecast of the annual percentage change of air passengers on a
country level for the period between 2000 and 2020 and the ASSESS forecast of the annual
percentage change of passenger kilometres over the period from 2000 and 2020. The table
also gives the EUROCONTROL forecast of the annual percentage change of the flight
movement over the forecast period from the 2007 and 2013 (EUROCONTROL, 2007).

Air passenger traffic annual growth based on ETIS, SCENES, and EUROCONTROL forecasts
                                                                           EUROCONTROL
                                              ACCESS "Partial" scenario Medium-Term Forecast:
                    ETIS annual % change annual % change of air IFR Flight Movements
                    of air passengers for the passenger kilometres for the 2007-2013 “Medium”
 By country         period 2000-2020          period 2000-2020             forecast
 Finland            2.5%                      3.7%                         3.1%
 Norway             2.7%                                                   2.8%
 Sweden             2.8%                      3.3%                         3.6%
 Estonia            4.0%                      5.8%                         6.9%
 Latvia             3.4%                      1.3%                         7.5%
 Lithuania          3.9%                      1.7%                         7.1%
 Germany            2.6%                      3.8%                         3.3%
 Russia             2.4%
 Ukraine            2.5%                                                   6.2%
 Poland             4.6%                      4.8%                         6.6%
 Moldova            3.9%                                                   6.7%
 Belarus            2.8%                                                   7.3%
Note: Forecasts are not directly comparable due to differences in the forecast definitions

The ASSESS most likely scenario for the total distance travelled gives higher growth rates
than in the ETIS for Finland, Sweden, and Germany. This is probably due to higher rise of
long distance journeys in these countries. Growth rates for the number of IFR movement are
predicted to be very high for the Baltic countries; that is Estonia, Latvia and Lithuania as well
as for Poland and Russia. It is likely that the 2020 air passenger demand projections on the
country and country to country level, for the Baltic countries, rather represent lower growth
scenario, and that the effect of the low cost market expansion in those countries has not been
fully represented in the two projections.




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