Docstoc

San Diego International Airport Expansion Sustainability Analysis

Document Sample
San Diego International Airport Expansion Sustainability Analysis Powered By Docstoc
					San Diego International
Airport Expansion
Sustainability Analysis




                                  February 2008




              A Global Alliance
          San Diego International Airport Expansion




          San Diego International Airport Expansion –
          Sustainability Analysis


          February 2008

          Prepared for:


          California Independent Voter Project



          Report Prepared By:

          Malcolm Pirnie, Inc.
          8001 Irvine Center Drive
          Suite 1100
          Irvine, CA 92618

          Sinclair Knight Merz
          590 Orrong Road
          Armadale Melbourne VIC
          3143 Australia




6189001
                                A Global Alliance
                                                                                                               Table of Contents



Contents

Executive Summary                                                                                                                        1

1. Introduction                                                                                                                         1-1
     1.1. Background ................................................................................................................... 1-1
     1.2. Expansion Alternatives ................................................................................................. 1-3
          1.2.1.  DEIR No Project Alternative .......................................................................... 1-4
          1.2.2.  DEIR Preferred Alternative (Proposed Project with Parking Structure) ........ 1-5
          1.2.3.  Proposed Lindbergh Intermodal Transportation Center................................ 1-5
     1.3. Report Objectives and Content................................................................................... 1-10

2. Transportation Analysis                                                                                                              2-1
     2.1. Background ................................................................................................................... 2-1
          2.1.1.  Regional Transportation ................................................................................ 2-1
     2.2. Airport Ground Transportation ...................................................................................... 2-3
          2.2.1.    Road Network................................................................................................ 2-3
          2.2.2.    Transit............................................................................................................ 2-5
          2.2.3.    Trolley............................................................................................................ 2-7
          2.2.4.    Bus ................................................................................................................ 2-9
          2.2.5.    Coaster .......................................................................................................... 2-9
          2.2.6.    Amtrak ........................................................................................................... 2-9
          2.2.7.    SDCRAA Airport Transit Plan ..................................................................... 2-10
          2.2.8.    Mitigation Measures to Address Airport Related Traffic.............................. 2-10
     2.3. Scenario Modeling ...................................................................................................... 2-12
          2.3.1.   Modeling Approach ..................................................................................... 2-12
          2.3.2.   Modeled Scenarios...................................................................................... 2-13
     2.4. Results and Discussion............................................................................................... 2-15
          2.4.1.   Mode Share................................................................................................. 2-15
                   2.4.1.1.     Transit Demand ...................................................................... 2-20
                   2.4.1.2.     Transit Capacity...................................................................... 2-24
          2.4.2.   Vehicle Miles Traveled (VMT) ..................................................................... 2-25
          2.4.3.   Level of Service........................................................................................... 2-27
                   2.4.3.1.     Traffic Analysis – Road Network Level of Service for Scenario 3
                                (DEIR Preferred Alternative) .................................................. 2-28
                   2.4.3.2.     Traffic Analysis – Road Network Level of Service for Scenario 4
                                (Lindbergh ITC) ...................................................................... 2-30
          2.4.4.   Impact of Assumptions ................................................................................ 2-30
          2.4.5.   Equity and Wider Sustainability Benefits..................................................... 2-32

3. Greenhouse Gas and Criteria Pollutant Emissions                                                                                      3-1
     3.1. Greenhouse Gases....................................................................................................... 3-1
          3.1.1.  Background ................................................................................................... 3-1
          3.1.2.  Methods......................................................................................................... 3-2
          3.1.3.  Results........................................................................................................... 3-4
     3.2. Criteria Pollutant Emissions from Airport-Related Ground Transportation ................... 3-6
          3.2.1.    Background ................................................................................................... 3-6
          3.2.2.    Methods......................................................................................................... 3-7

San Diego International Airport Expansion: Sustainability Analysis
                                                                                                                                    i
Table of Contents


          3.2.3.        Results and Discussion ................................................................................. 3-9

4. Sustainability and Green Airport and Green Building Opportunities for
    SDIA Expansion                                                       4-1
   4.1. Why Sustainability?....................................................................................................... 4-1
        4.1.1.  Local to Global Context ................................................................................. 4-2
        4.1.2.  Opportunities for Sustainability ..................................................................... 4-3
   4.2. Green Airport Concept and Framework........................................................................ 4-5
   4.3. Green Buildings and the LEED System at Airports ...................................................... 4-7
        4.3.1.  LEED-Certified and LEED-Registered Projects Related to Airports and Transit
                Centers .......................................................................................................... 4-8
   4.4. Sustainability Opportunities for SDIA Expansion Alternatives...................................... 4-8
        4.4.1.   Scenario 2 (No Project Alternative @ 2030) ................................................. 4-9
        4.4.2.   Scenario 3 (DEIR Preferred Alternative) ....................................................... 4-9
        4.4.3.   Scenario 4 (Lindbergh ITC) ......................................................................... 4-10

5. Summary and Discussion                                                                                                       5-1

6. References                                                                                                                   6-1




                                                            San Diego International Airport Expansion: Sustainability Analysis
  ii
                                                                                                                      Table of Contents



Tables
Table 2-1. Level-of-Service (LOS) Descriptions........................................................................... 2-5
Table 2-2a. Transit Mode Shares by Scenario (Conservative Assumptions)............................. 2-17
Table 2-2b.Transit Mode Shares by Scenario (Optimistic Assumptions)…………… ………….2-18
Table 2-3. Transit Mode Share for Commuting in Major U.S. Cities (U.S. Census Data, 2000)..................2-23
Table 2-4a. Change in Average Daily Vehicle Miles Traveled (VMT) Per Day Basis by Scenario -
Conservative Assumptions…………………………………………………………………………….2-26
Table 2-4b. Change in Average Daily Vehicle Miles Traveled (VMT) Per Day Basis by Scenario -
Optimistic Assumptions ……………………………………………………………………………….2-26
Table 3-1.Change in Average Daily Greenhouse Gas Emissions by Scenario ........................... 3-4
Table 3-2. Current Designation for Selected Criteria Pollutants .................................................. 3-7
Table 3-3. Estimated Percent Change in Daily Criteria Pollutant Emissions from 2005 to 2030
with No Infrastructure Pollutant Changes (Scenario 1 versus Scenario 2) .................................. 3-9
Table 3-4. Estimated Percent Change in Daily Criteria Pollutant Emissions - Passenger Cars ..3-9
Table 4-1. Comparison of Sustainability Opportunities for Alternatives ....................................... 4-9
Table 5-1.Sustainability Components Summary for Scenarios 2 Through 6 ............................... 5-3



Figures
Figure 1-1: San Diego Region Transportation System................................................................. 1-2
Figure 1-2: Map of San Diego International Airport and Vicinity ................................................. 1-3
Figure 1-3: Map of Proposed Lindbergh Intermodal Transportation Center. .............................. 1-6
Figure 1-4: High Oblique Rendering of Lindbergh Intermodal Transportation Center ................ 1-7
Figure 1-5: Vertical Rendering of the Lindbergh Intermodal Transportation Center ................... 1-8
Figure 2-1: Study Area Transport Network.................................................................................. 2-2
Figure 2-2: Current Percent Airport Related Traffic by Road Segment (SDIA DEIR, 2007) ....... 2-4
Figure 2-3: Airport Related Traffic with Current LOS (SDIA DEIR, 2007)................................... 2-4
Figure 2-4: Airport Passenger Ground Transportation Mode Shares at SDIA (HNTB, 2007)..... 2-6
Figure 2-5: Ground Transportation Mode Shares for Employees at SDIA (HNTB, 2007) .......... 2-6
Figure 2-6: Entrance to Existing Old Town Transit Center.......................................................... 2-8
Figure 2-7: Tested Trolley Networks ......................................................................................... 2-14
Figure 2-8: Mode Share for Conservative Scenario .................................................................. 2-16
Figure 2-9: Mode Share for Optimistic Scenario ....................................................................... 2-16
Figure 2-10: Airport Related Traffic with Current (LOS) (SDIA DEIR,2007)……….…………….2-29
Figure 2-11: Traffic Level of Service - Preferred Alternative in 2030……………………………..2-29
Figure 2-12 Traffic Level of Service - Lindberg ITC in 2030……………………………………….2-29
Figure 3-1: Greenhouse Gas Emissions on a Per Day Basis by Scenario ................................. 3-5
Figure 4-1: Airport Sustainability and its Local to Global Context ............................................... 4-3
Figure 4-2: Relationship of Sustainable Design Value and the Cost of Impact Mitigation .......... 4-4
Figure 5-1: Additional Average Daily Vehicle Miles Traveled in 2030 Compared to the 2005
Baseline. ....................................................................................................................................... 5-4
Figure 5-2: Greenhouse Gas Emissions Percent Change from Scenario 2 (No Project @2030)5-6
Figure 5-3: Proportion of Passengers and Employees Using Transit………………………………5-6




San Diego International Airport Expansion: Sustainability Analysis
                                                                                                                                           iii
Table of Contents




Appendices
       A. Case Studies

       B. Transportation Modeling

       C. Calculations of Greenhouse Gas Emissions

       D. Calculations of Criteria Air Pollutants

       E. LEED Background Information

       F. Worldwide Airport Environmental Initiatives from the Airports Council International




                                             San Diego International Airport Expansion: Sustainability Analysis
  iv
                                                                     Table of Contents



Abbreviations and Acronyms

ACI                 Airports Council International
ACI-NA              Airports Council International-North America
ACRP                Airport Cooperative Research Program
CAP                 Clean Airport Partnership, Inc.
CAIVP               California Independent Voter Project
CFCs                Chlorofluorocarbons
CI                  Commercial Interiors
CS                  Core and Shell
DEIR                Draft Environmental Impact Report
EB                  Existing Building
EIRs                Environmental Impact Reports
HCFCs               Hydrochlorofluorocarbons
HFCs                Hydrofluorocarbons
HOV                 High-occupancy vehicle
ITC                 Intermodal Transportation Center
LAX                 Los Angeles International Airport
LEED                Leadership in Energy and Environmental
LOS                 Level-of-service
MTS                 Metropolitan Transit System
NCTD                North County Public Transit District
ND                  Neighborhood Development
OAK                 Oakland International Airport
SANDAG              San Diego Association of Governments
SDCRAA              San Diego County Regional Airport Authority
SDIA                San Diego International Airport
SFO                 San Francisco International Airport
TSA                 Transportation Security Administration
USGBC               United States Green Building Council
VMT                 Vehicle miles traveled




San Diego International Airport Expansion: Sustainability Analysis
                                                                                 v
Table of Contents




This page left intentionally blank.




                                      San Diego International Airport Expansion: Sustainability Analysis
  vi
                                                                  Executive Summary

                           San Diego International Airport Expansion –
                                                                 Sustainability Analysis
The San Diego International Airport/Lindbergh Field (SDIA) is the major commercial
airport for business, personal, and cargo transportation servicing the San Diego region;
therefore, SDIA is vital to prosperity and growth of the community. SDIA is the smallest
major airport in the U.S. yet provided service to 17.7 million passengers in 2006. Growth
in demand is expected to reach 28.2 million passengers by 2030 (SH&E 2004; SDCRAA
2007) 1 . The San Diego County Regional Airport Authority (SDCRAA) is in the
planning process for meeting demand through an update of the Airport Master Plan. The
Master Plan objectives are to:

       Provide adequate facilities to accommodate air service demand through 2015 while
       improving airport levels of service, airport safety and security, and enhancing airport
       access;
       Develop facilities that effectively utilize the current airport property and facilities and
       are compatible with surrounding land uses; and
       Provide for future public transit options in airport land use planning.
SDCRAA issued a Draft Environmental Impact Report (DEIR) for public comment in
October, 2007 (SDCRAA 2007) which evaluated five alternatives for airport facility
expansion to accommodate air service through 2015 and provide for future public transit
options in airport land use planning. The DEIR analyzed impacts through 2030 to allow
comparison to regional transportation plans. The key elements of two DEIR proposed
alternatives (the No Project Alternative, and the Proposed Project (Preferred Alternative))
and a third alternative (Lindbergh Intermodal Transportation Center (LTC))
independently developed by the California Independent Voter Project (CAIVP) are
described below and evaluated in this study.

Master Plan DEIR No Project Alternative - The SDIA DEIR No Project Alternative
proposes no new projects to improve airport infrastructure and maintains the airport
facility ‘as is’ over the DEIR planning horizon of 2015 even though airport passenger
traffic is expected to rise 2.8 percent per year. Under this alternative, the level of service
within the airport would be expected to deteriorate and the traffic congestion around the
airport would be expected to increase. The No Project Alternative serves as a baseline
for comparison of the other alternatives and scenarios.

1
    References are available in the main report and are not included in the Executive Summary.


San Diego International Airport Expansion -
Sustainability Analysis                                                                          ES-1
Executive Summary


Master Plan DEIR Proposed Project (Preferred Alternative) - The DEIR Preferred
Alternative includes the following components:

   Expand existing Terminal Two West with 10 new jet gates;
   Construct new aircraft parking and replacement Remain-Over-Night aircraft parking
   apron;
   Construct a new apron and aircraft taxi lane;
   Construct a second level road/curb and vehicle circulation serving Terminal Two;
   Construct a new parking structure (providing approximately 4,300 new parking
   spaces) and vehicle circulation serving Terminal Two;
   Relocate and reconfigure SAN Park Pacific Highway parking facility providing
   approximately 500 additional parking spaces;
   Construct a new access road from Sassafras Street/Pacific Highway intersection to
   provide access to the SAN Park Pacific Highway and new general aviation facilities;
   Construct new general aviation facilities including access, terminal/hangers, and
   apron to improve Airport safety for Airport customers/users;
   Demolish the existing general aviation facilities to improve airport safety and
   circulation airfield; and
   Reconstruct Taxiway C, construct new apron hold areas, and new taxiway east of
   Taxiway D.
The proposed airport modifications remain completely within the existing SDIA property
boundary, which consists of 661 acres and is constrained by its proximity to San Diego
Bay and downtown. Traffic congestion resulting from the airport operations will be
addressed partly through local road and intersection improvements but also through
proposals outlined in a separate draft Airport Transit Plan.

Draft Airport Transit Plan - In cooperation with regional transportation agencies,
SDCRAA has been involved in the development of an Airport Transit Plan to reduce
traffic congestions in the vicinity of the airport. The draft Transit Plan aspires to increase
air passenger transit ridership from 1.2 percent to 4-6 percent in the next 3-5 years based
on a series of measures designed to increase public transit use. These include near-term
measures (until the end of 2009) such as increased marketing efforts, free rides for
arriving passengers and extending bus service to the convention center. Mid-term
measures (2010 to 2011) include reducing bus service interval times to 10 minutes,
adding evening and weekend Coaster trips, and providing a shuttle to the Old Town
Transit Center and remote parking sites.




                                                            San Diego International Airport Expansion –
                                                                                 Sustainability Analysis
 ES-2
                                                                       Executive Summary


Proposed CAIVP Lindbergh ITC - Given the significant financial investment required
for SDIA expansion needs, the California Independent Voter Project (CAIVP) was
concerned that implementation of SDCRAA proposed plans without a more rigorous
evaluation of alternative sustainable designs might reduce future community options due
to high sunk project costs. To stimulate further evaluation, CAIVP prepared a conceptual
additional alternative to address airport expansion and traffic congestion, the Lindbergh
Intermodal Transportation Center (Lindbergh ITC or ITC).

The proposed CAIVP Lindbergh ITC Alternative is not a “final plan” but instead an
alternative vision of what might be done to improve the efficiency of SDIA for its
passengers, reduce adverse consequences, and improve the quality of life for the
community. The concept includes moving the existing terminals to the opposite (north)
side of the runway adjacent to Pacific Highway and developing an intermodal transit
facility (Figures ES-1 and ES-2). The ITC would be a five-story parking facility that
would consolidate all parking, rental cars, and public transit access into one enclosed
facility with direct access to the newly located terminals. More specifically, it would
include the following:

    Long-term parking for more than 20,000 vehicles and short-term parking for 2,000
    vehicles;
    Room for on-site car rental agencies and their vehicles;
    Bi-level drop-off and pick-up roads for plane, train, bus and trolley passengers;
    Direct access from the Lindbergh ITC to airport terminals via sky bridges that would
    include moving sidewalks;
    Provide new off ramps and on ramps directly to Interstate 5 and Pacific Highway for
    vehicular access to and from the new terminal location;
    Room for a downtown people mover and a high-speed rail between airports;
    Trolley stops where one can catch the Orange, Blue, Green and special event lines;
    An Amtrak Pacific Surfline stop (serving San Luis Obispo, Santa Maria, Santa
    Barbara, Ventura, Oxnard, Camarillo, Simi Valley, Van Nuys, Los Angeles, Santa
    Ana, and points in-between; and
    A Coaster stop bringing people in from Oceanside, Carlsbad, Encinitas, Solana Beach
    and Sorrento Valley.




San Diego International Airport Expansion –
Sustainability Analysis                                                                 ES-3
Executive Summary


The Lindbergh ITC would require an additional 90 acres of land adjacent to the airport on
the north side bounded by Pacific Highway, Interstate 5, Washington Street, and Laurel
Street. Approximately half of this land is presently owned by public agencies and much
of the remainder is currently used for airport parking and rental cars. Additionally, the
ITC would require a 27-acre strip of land owned by the Marine Corps Recruit Depot to
allow taxiway C to be extended to the end of the runway.

        Figure ES-1. Map of Proposed Lindbergh Intermodal Transportation Center.




CAIVP believes the Lindbergh ITC would provide the following benefits:

   Provide airport passengers and workers more efficient and environmentally friendly
   alternatives to reach the airport;
   Reduce automobile congestion in the vicinity of the airport;
   Encourage the use of transit;
   Provide SDIA an opportunity to reduce its carbon and environmental footprint; and
   Improve the quality of life and traffic congestion along the waterfront.
Study Approach and Objectives - CAIVP requested Malcolm Pirnie and Sinclair Knight
Merz (SKM) prepare an independent analysis of selected expansion alternatives
developed in support of the SDCRAA Airport Master Plan and the Airport Transit Plan
along with a third alternative, the Lindbergh ITC. This report provides an independent
and objective analysis of key sustainability components of the SDIA expansion.




                                                          San Diego International Airport Expansion –
                                                                               Sustainability Analysis
 ES-4
                                                                                               Executive Summary


  Figure ES-2. High Oblique Rendering of Lindbergh Intermodal Transportation Center.




Figure ES-2. The ITC is in light blue and is located at the right. The turquoise blue color is the short-term parking area.
The drop-off and pickup areas are in red and green. The existing airport terminals occur to the left of the runway in this
rendering. Source: California Independent Voter Project.

The major sustainability components evaluated in this report include:

     The ability to increase public transit ridership (mode share);
     Changes in daily vehicle miles traveled (VMT) by airport passengers and workers
     commuting to and from the airport;
     Changes in road traffic congestion on the streets around the SDIA;
     Impact of passenger and airport worker travel changes on greenhouse gas emissions;
     Impact of passenger and airport worker travel changes on air quality; and
     Lessons learned from a qualitative review of the experience at other international
     airports to implement “green airport” practices into a modified airport infrastructure.
Other positive sustainability components result from the above and these are also
identified.

Transportation Modeling and Analyses - To compare the basic metrics or differences in
the impacts of the three expansion alternatives, we conducted quantitative transportation
modeling. The model examines transit choices of travelers to the airport and from SDIA,


San Diego International Airport Expansion –
Sustainability Analysis                                                                                           ES-5
Executive Summary


in turn, the traffic congestion that these choices would generate. This model predicts
travelers mode choices based on the travel times, costs and other factors that are
important in a traveler’s decision-making process. Based on these choices, the model
calculated values for average daily vehicle miles traveled (VMT) by airport passengers
and workers traveling to and from the airport. In addition, the transport mode choice
model predicts the traffic level of service (LOS), which is an indicator of how well traffic
flows on individual city streets based on the cumulative use by airport passengers and
workers, as well as other users of the transportation system. LOS predictions range from
LOS A (free-flowing traffic) to LOS F (major traffic disruption with long lines of stopped
traffic). LOS E and F are typically considered unacceptable for efficient roadway
operation.

Modeled Scenarios - To understand the impacts of the expansion alternatives and their
sensitivity to possible variations, several current and future transport scenarios were
developed. These modeled scenarios evaluate the effect of varied travel times, costs and
other factors on a traveler’s transportation decisions.

   •    Scenario 1 (2005 Baseline) – Modeled existing conditions in 2005 based on
        infrastructure as it exists presently.

   •    Scenario 2 (No Project Alternative @ 2030) – Same as the DEIR No Project
        Alternative at 2030. Predicted traffic based on no changes in infrastructure or in
        the Airport Transit Plan. Scenario 2 differs from Scenario 1 based on increases in
        demand and how increased congestion may influence passenger and airport
        worker choices without any changes in transportation infrastructure or incentive
        programs.

   •    Scenario 3 (Preferred Alternative) – This scenario included recommendations
        from the DEIR Master Plan Preferred Alternative at 2030 but does not include the
        traffic mitigation measures or draft Airport Transit Plan.

   •    Scenario 4 (Preferred Alternative with Airport Transit Plan) – Same as
        Scenario 3 except with an Old Town shuttle bus service, free Flyer fares, reduced
        Flyer headways from 12 to 10 minutes, evening and weekend Coaster rail service
        and FlyAway sites at Escondido Transit Center, I-15/SR52 and I-805/SR54
        junctions. These measures are part of the draft Airport Transit Plan.

   •    Scenario 5 (Lindbergh ITC) – Predicted traffic in 2030 based on the Lindbergh
        ITC with the removal of the 992 Flyer route, extension of the Trolley Green line
        south from Old Town Transit Center to the ITC, extension of the Orange line
        north to the ITC and transit improvements from Scenario 4 (except for Old Town
        shuttle).



                                                          San Diego International Airport Expansion –
                                                                               Sustainability Analysis
 ES-6
                                                                                                          Executive Summary


Predicted Transit Mode Share and Daily Average Vehicle Miles Traveled (VMT) –
Based on our quantitative transportation modeling, the only scenario that both increased
public transit ridership (Figure ES-3) and substantially reduced the increase in daily VMT
(Table ES-1) was the Lindbergh ITC (Scenario 5). Figure ES-3 (for conservative
assumptions) shows that the Lindbergh ITC increased transit ridership by 1.4 percent
more than Scenario 4 (Preferred Alternative with Airport Transit Plan). More than 48
percent of the transit ridership for the ITC is on the Trolley system which reduces traffic
on the streets around the airport while Scenario 4 (Preferred Alternative with Airport
Transit Plan) has 54 percent of transit ridership on the bus.

Table ES-1 shows the daily average VMT among the five scenarios with conservative
assumptions. Table ES-1 also shows the differences in both miles and percent for the
scenarios in comparison to the 2005 Baseline, the No Project Alternative at 2030, and the
Preferred Alternative (also for conservative assumptions). These values reflect the effect
of travel times, costs and other factors on a traveler’s transportation decision. The DEIR
No Project Alternative at 2030 (Scenario 2) indicates increased demand for air travel
would result in an additional 685,000 average daily miles driven to or from SDIA per day
(or 250 million VMT annually). This represents a 57 percent increase in daily average
VMT traveled by airport passengers and workers over the 2005 Baseline. The Preferred
Alternative at 2030 with Airport Transit Plan (Scenario 4) was 1.6 percent less than a no
project alternative in that daily average VMT were reduced by only 30,000 miles per day
compared to the No Project Alternative at 2030 (Scenario 2).

The Lindbergh ITC scenario reduced daily average VMT by 169,000 miles per day or 9.0
percent and 139,000 miles per day or 7.5 percent compared to the No Project Alternative
at 2030. (Scenario 2) and the Preferred Alternative with Airport Transit Plan at 2030
(Scenario 4), respectively. This represents a savings in annual VMT for the ITC.

Figure ES-3. Proportion of Passengers and Employees Using Different Modes of Public
Transit (Conservative Assumptions)

                     4.5
                                                                                                    4.0
                       4
                     3.5
                       3                                                                                         FlyAway
                                                                                  2.6
           Percent




                     2.5                                                                                         Coaster
                       2                                                                                         Trolley
                                1.2               1.3            1.3
                     1.5                                                                                         Bus
                       1
                     0.5
                       0
                           Scenario 1 (2005 Scenario 2 (No    Scenario 3      Scenario 4         Scenario 5
                              Baseline)     Project @ 2030)   (Preferred       (Preferred      (Lindbergh ITC)
                                                              Alternative)   Alternative w
                                                                             Airport Transit
                                                                                  Plan)




San Diego International Airport Expansion –
Sustainability Analysis                                                                                                    ES-7
Executive Summary




      Table ES-1. Change in Average Daily Vehicle Miles Traveled (VMT) Per Day Basis by
                            Scenario (Conservative Assumptions)


                                     Daily Ave.     Daily Ave. VMT       Daily Ave. VMT           Daily Ave. VMT
                                       VMT              Change               Change                Change from
        Scenario Modeled                          from 2005 Baseline   from No Project @             Preferred
                                                                       2030 and Preferred         Alternative with
                                                                       Alternative @ 2030       Airport Transit Plan
                                                                                                      @ 2030

                                                    Miles     Perce     Miles       Percent       Miles      Percent
                                                               nt

  1      2005 Baseline               1,204,040       ---        ---       ---          ---         ---          ---

  2      No Project Alternative      1,889,503    +685,463     +56.9      ---          ---         ---          ---
         @ 2030

  3      Preferred Alternative @     1,889,503    +685,463     +56.9      ---          ---         ---          ---
         2030

  4      Preferred Alternative       1,859,146    +655,106     +54.4   -30,357        -1.6         ---          ---
         with Airport Transit Plan
         @ 2030

  5      Lindbergh ITC @ 2030        1,720,364    +516,324     +42.9   -169,139       -9.0      -138,782       -7.5




compared to the No Project Alternative and Preferred Alternative with Airport Transit
Plan of 61.7 million and 50.6 million miles, respectively. These reduced values reflect
the increase in transit use and the reduction of trip length by providing direct access to the
airport terminal from I-5. However, even with alternative transportation choices
available associated with the Lindbergh ITC scenario, average daily VMT was projected
to increase by 516,000 miles (43 percent) over the 2005 Baseline.

The impact of changes in VMT on traffic congestion in the vicinity of SDIA was also
evaluated. Airport related traffic is currently a substantial percentage of the total traffic
on downtown streets – ranging from 40 percent to 76 percent of total traffic on Grape
Street, Hawthorn Street and Laurel Street (Figure ES-4). Presently, traffic on many
streets in the vicinity of the airport currently operates at and beyond desirable levels of
service (Figure ES-5).

The projected increase in demand for airport travel results in approximately 685,000
additional average daily VMT (equivalent to 250 million miles per year) from airport
related ground transportation. Both the No Project Alternative at 2030 (Scenario 2) and
the Preferred Alternative with Airport Transit Plan at 2030 (Scenario 4; Figure ES-6),


                                                                       San Diego International Airport Expansion –
                                                                                            Sustainability Analysis
 ES-8
                                                                        Executive Summary


would result in significant additional traffic congestion and further decline in the level of
service on many streets in the vicinity of the airport. In contrast, the increased public
transit use, reduced VMT, and placement of the airline terminals close to I-5 result in
substantially reduced traffic volume and traffic congestion (i.e., increased levels of
service) in the vicinity of SDIA as a result of the Lindbergh ITC (Figure ES-7). This
improvement occurs despite the projected increase of 169,000 average daily VMT. The
most significant effect is due to re-routing traffic away from streets such as Rosecrans,
Laurel, and Hawthorn Streets with the ITC. LOS on these streets would improve to
acceptable levels as a result of the ITC. Improvements are also seen on India, Kettner,
Grape, Washington, and Hancock Streets.

Under Scenario 3 (Preferred Alternative) potential mitigation to improve LOS on these
streets (Figure ES-6) to acceptable levels (LOS D) is identified. These mitigation
measures include road widening, removing on street parking, increasing the number of
lanes on these streets and intersection improvements. If implemented such measures
could improve the LOS but they do not improve VMT and thus maintain the traffic
increase on streets adjacent to the airport making access for residents and local businesses
more difficult. The measures do not reduce local criteria pollutants or overall greenhouse
gases (see below).




San Diego International Airport Expansion –
Sustainability Analysis                                                                ES-9
Executive Summary




    Figure ES-4. Percent airport related traffic by road segment in the vicinity of SDIA for
    2005.




                                                             San Diego International Airport Expansion –
                                                                                  Sustainability Analysis
ES-10
                                                Executive Summary




                                              Figure ES-5. Traffic Level of
                                              Service for surface streets in the
                                              vicinity of SDIA for Scenario 1 –
                                              2005 Baseline.




                                              Figure ES-6. Traffic Level of Service
                                              for surface streets in the vicinity of
                                              SDIA for Scenario 3 – Preferred
                                              Alternative in 2030.




                                              Figure ES-7. Traffic Level for surface
                                              streets in the vicinity of SDIA for
                                              Scenario 4 – Lindberg ITC in 2030.




San Diego International Airport Expansion –
Sustainability Analysis                                        ES-11
Executive Summary


Estimation of Greenhouse Gas and Criteria Pollutant Emissions - Greenhouse gas
emissions from gasoline-powered cars and vans and compressed natural gas buses used to
transport passengers to and from SDIA are calculated for the modeled transport scenarios
(Table ES-2). Similar to the VMT and LOS data, these results reflect the effect of travel
times, costs and other factors on a traveler’s transportation decision. The greenhouse gas
emissions are calculated as carbon dioxide equivalent (CO2e) reflecting the combined
effect of CO2, CH4 (methane) and N2O (nitrous oxide) from vehicle emissions. The
values are reported in the standard format of metric tons CO2e. The calculations also
reflect a mix of more fuel efficient vehicles that will result from the new Corporate
Average Fleet Economy (CAFE) standards passed by Congress and signed by the
President in December 2007. The new CAFE standard requires new automobiles to
achieve 35 miles per gallon vehicle average by 2020.



 Table ES-2. Change in Average Daily Greenhouse Gas Emissions on a Per Day Basis by
                                       Scenario


                                                                                             Change from
                                             Change from 2005     Change from No               Preferred
                                    Daily        Baseline        Project @ 2030 and         Alternative with
                                    Metric                            Preferred           Airport Transit Plan
      Scenario Modeled              Tons                         Alternative @ 2030             @ 2030
                                    CO2e
                                             Metric    Percent    Metric      Percent      Metric      Percent
                                             Tons                 Tons                     Tons

  1     2005 Baseline                479      ---         ---       ---          ---         ---          ---

  2     No Project Alternative       587     +108       +22.5       ---          ---         ---          ---
        @ 2030

  3     Preferred Alternative @      587     +108       +22.5       0            0           ---          ---
        2030

  4     Preferred Alternative        582     +103       +21.5       -5          -0.9         ---          ---
        with Airport Transit Plan
        @ 2030

  5     Lindbergh ITC @ 2030         533      +54       +11.3      -54          -9.2         -49         -8.4




                                                                 San Diego International Airport Expansion –
                                                                                      Sustainability Analysis
ES-12
                                                                        Executive Summary




The results show that the Lindbergh ITC provided the most benefits for reducing the rate
of growth in greenhouse gas emissions. The daily average CO2e emissions from
passenger vehicle travel to and from SDIA would increase by approximately 23 percent
(108 metric tons per day, which is equivalent to 39,420 metric tons per year), under the
No Project Alternative at 2030 (Table ES-2). The Preferred Alternative with Airport
Transit Plan at 2030 (Scenario 4) would result in approximately 103 metric tons of daily
CO2e emissions above the 2005 Baseline. This represents a less than one percent (5
metric tons per day) reduction below the No Project Alternative at 2030 (Scenario 2;
Table ES-2).

In contrast, the increased use of pubic transportation and reduced traffic through
downtown and along Harbor Drive associated with the Lindbergh ITC (Scenario 3)
would result in greenhouse gas emissions of 533 metric tons CO2e by 2030. This
represents a 11.3 percent increase from the 2005 Baseline; however, this increase is 54
percent lower than the increase projected for the No Project Alternative at 2030 (Table
ES-2). None of the Scenarios (3, 4, or 5) would reduce greenhouse gas emissions to the
2005 baseline or to the California Air Resources Board’s goal of 1990 levels. However,
the estimated 8 percent reduction of greenhouse gas emissions in the Lindbergh ITC
Scenario 5 could form an important component of an overall plan to decrease greenhouse
gas emissions associated with the SDIA.

Ambient air quality standards are implemented to protect human health and the
environment from the harmful impacts of air pollution. The standards apply to a subset
of possible air contaminant called ‘criteria pollutants’. Criteria pollutants include: carbon
monoxide (CO), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), particulate
matter (less than 10 microns and less than 2.5 microns), and lead (Pb) among other state-
listed pollutants. The screening-level evaluation estimated that some criteria pollutants
from airport-related ground transportation can be expected to decrease by 2030 (CO =
-56%, NOx = -65%, and ROG = -44%) under the No Project Alternative (Scenario 2).
These values decline because of federal and state emission requirements. Other criteria
pollutants would increase (SOx = +56%, PM10 = +79%, and PM2.5 = +91%) under the No
Project Alternative. The Preferred Alternative with Airport Transit Plan at 2030
(Scenario 4) resulted in less than a two percent reduction of criteria pollutants while the
Lindbergh ITC Scenario resulted in an estimated 9.7 percent reduction in criteria
pollutant emissions from the No Project Alternative at 2030 (Scenario 2). The transit
analysis indicates the VMT reductions (and, therefore, associated emissions) would
decrease most significantly in the residential neighborhoods and surface streets near the
airport. From a qualitative perspective, the distribution of reduced VMTs suggests that
residential exposure to air contaminants would also decrease in areas where VMTs are



San Diego International Airport Expansion –
Sustainability Analysis                                                               ES-13
Executive Summary


reduced. Overall, the Lindbergh ITC would be expected to provide a greater reduction in
criteria pollutants than the Master/Transit Plan and no project scenarios.

Green Airport and Green Building Opportunities – The analysis presented in previous
sections compared the No Project, the DEIR Preferred Project Alternative (both with and
without the Transit Plan), and the Lindbergh ITC relative to sustainability criteria for
public transit (mode share), average daily VMT, traffic congestion on streets around
SDIA, and both greenhouse gas and air emissions by air passengers and airport workers
traveling to and from SDIA. The other sustainability criteria evaluated in this report was
a qualitative review of green airport practices being implemented by U.S. and
international airports in order to compare opportunities for incorporating lessons learned
under the various expansion scenarios evaluated in this report. Broad concepts and
conclusions are summarized here while specific lessons learned are identified and
discussed in the report.

The opportunities to deliver sustainability are greatest at the outset of a project (i.e.
during the concept stage) and progressively declines through the following stages of
feasibility, detailed design, procurement, construction, and operation. The No Project
Alternative provides the least change in the physical facilities and, therefore,
sustainability improvements are largely based on operational changes. The Preferred
Alternative provides some new terminal space while maintaining most of the rest of the
existing facilities. In contrast, the Lindbergh ITC proposal is essentially the development
of a new airport terminal and consequently it provides the maximum ability to
incorporate the newest efficiencies and most effective sustainable design concepts
ranging from access to the airport, green design for built infrastructure, and
improvements in the integrated processes of airport operation. It should be noted
however, one-time emissions associated with new construction, which can offset
operational gains, were not evaluated. It would be expected that one-time emissions
would be highest under the ITC Scenario and lowest under the No Project Alternative.
but would increase as the amount of new construction increased.

The most direct potential for green airport concepts is within the physical component of
the airport (green buildings). Buildings account for a substantial percentage of overall
resource use. Consequently, designing and constructing new buildings to the most up-to-
date standards would substantially reduce the airport’s overall environmental footprint.
Sustainable design can be applied to the physical building in addition to the specific
processes occurring in the airport concerning energy, waste production, and water.

Energy use, which depletes natural resources and contributes to greenhouse gas
emissions, is one of the first targets of efficient building design. Conserving energy used
for heating, air-conditioning and lighting could be accomplished at the Lindbergh ITC
using intelligent sensors and designs that use passive solar energy to heat and cool. The


                                                          San Diego International Airport Expansion –
                                                                               Sustainability Analysis
ES-14
                                                                         Executive Summary


Vancouver Airport in Canada uses solar panels to heat hot water and the Chicago and San
Francisco Airports produce electricity from solar energy. La Palma Airport in Spain
generates the majority of electricity it uses from wind power generators. Green roofs can
help to offset carbon emissions from other energy sources.

The circulation of resources and waste could also be implemented to reduce the airport’s
overall ecological footprint. For example, certain waste streams could be separated and
potentially re-used. Los Angeles International Airport has implemented an anaerobic
digester to turn 8,000 tons of food waste produced each year into methane gas which can
be used for on-site electricity. Hong Kong International Airport uses its food waste as
fertilizer for landscaping. Other materials that are now recycled or re-used at other
airports around the world include de-icing fluid, waste oil, excavated soil, airline pillows,
coffee grounds, runway concrete, demolition debris, cut grass, food grease, and large
batteries. Water can also be re-used and recycled. The Canberra Airport in Australia
implemented an Aquacell Water System to recycle 26,400 gallons of water across the
airport daily. Treated sewerage can re-routed and used for irrigation as is done at the
Athens International Airport. The Auckland International Airport in New Zealand
collects and passively treats its stormwater before discharging it into the bay.

The Lindbergh ITC concept provides the opportunity to obtain other unknown but
potentially significant operational efficiencies in the re-designed airport. Instituting a
ground-level up integrated system that enhances operational efficiencies through
infrastructure, siting/location, staff allocation, and communication systems has the
potential for other non-obvious synergistic improvements. From baggage
transport/loading to security checkpoints, building from the ground up allows for
complete restructuring to improve efficiency and sustainability of the new facility.

In addition to tangible reductions in energy use, water consumption, carbon emissions
and waste generation, there are many social benefits to be recognized as a result of a
comprehensive sustainable airport design. Societal pressure to reduce greenhouse gas
emissions will almost certainly increase in the near future due to state, national and
international pressures. Although public transit use in the California and the City of San
Diego is much lower compared to the eastern U.S. and Europe, it will remain an
important part of the tool box that society uses to reduce traffic congestion and
greenhouse gas emissions in the future. The consolidation of transit types at the
Lindbergh ITC would enhance the effectiveness of any future public transit expansions in
the area and would also enhance their ridership by improving public perception of public
transportation.

The combined effects of the increased public transit use and the ability to enhance future
public transit expansions will also have positive benefits for redevelopment along the
waterfront south of the SDIA. The overall improvements in traffic and access to


San Diego International Airport Expansion –
Sustainability Analysis                                                                ES-15
Executive Summary


integrated public transit would extend to this area and enhance the over quality of
experience for visitors and residents.

The modeled increase in public transit ridership to the airport, coupled with the
synergistic increase in overall public transit effectiveness provided by the ITC, would
provide airport employees, particularly lower income employees, with more attractive
transit access to the airport. Consequently, the social equity component of sustainability
would be increased.

The extent of the infrastructure change (buildings, operations, transportation) influences
the opportunity for environmental and social benefits. The Lindbergh ITC features both a
replacement of existing infrastructure and a vast expansion of the system transportation
design that maximizes opportunities and benefits. Although cost was not considered in
this analysis, it is clear that the potential environmental and social benefits could be
significantly enhanced by expanding the proposed design beyond the boundaries of the
current infrastructure and addressing the entire airport system as a more comprehensive,
interactive unit. Therefore, the feasibility of more expansive designs like the Lindbergh
ITC should be considered as candidates for a full cost-benefit analysis.

Discussion

SDIA expansion and implementation of a new Airport Transit Plan are being proposed at
a time when San Diegan’s are demanding greater environmental stewardship, including a
more sustainable and carbon-neutral natural and built environment, as well as lifestyle.
Examples of these mandates include: San Diego’s Sustainable Community Program;
California AB 32 Global Warming Solutions Act; California AB 1493, a proposed state
regulation contested by the U.S. Environmental Protection Agency and not implemented;
and the international Bali Pact addressing global greenhouse gas emissions. AB 32
requires a reduction in California greenhouse gas emissions to 1990 levels by 2020 (an
estimated 25 percent reduction). AB 32 mandatory greenhouse gas caps will begin in
2012 and the California Energy Commission and Air Resources Board are currently
developing and releasing specific regulations. In addition, the Governor’s Executive
Order S-3-05 mandates a reduction of greenhouse gas emissions to 80 percent below
1990 levels by 2050. At present these regulations do not address transportation.
However, since passage of AB 32, the California Attorney General has been proactively
engaging various levels of local government seeking the means to address greenhouse
issues that are not now directly included by expected regulation

Transportation makes up a significant and growing component of greenhouse gas
emissions, including 31.5 percent of the 2001 CO2 emissions in the U.S. (WRI, 2008).
Transportation was the fastest growing source of greenhouse gas emissions between 1990
and 2002 with emissions of CO2 increasing by 24 percent over this period (WRI, 2005).
Increasing demand associated with travel is forecast to exceed benefits accruing from

                                                          San Diego International Airport Expansion –
                                                                               Sustainability Analysis
ES-16
                                                                       Executive Summary


improved vehicle efficiency such that by 2020 transportation emissions in North
America are forecast to be 30 percent above 2002 levels (WRI, 2005). Forecasts suggest
that air travel will grow by 60 percent between 2000 and 2025, well above projected
increases in aircraft fuel efficiency (which have increased approximately one percent per
year over the past ten years (FAA, 2005)).

The City of San Diego reported a 36 percent increase in average weekday VMT from
1990 to 2004 for the community (City of San Diego, No Date) which resulted in an
average of 38.4 million miles per weekday. VMT to and from SDIA from our study was
estimated to be 1.2 million miles per day in 2005 (approximately 3 percent of total miles
not accounting for differences between weekday and daily averages and years).
Although the SDIA ground transportation may be a small component of the total
community transportation, the projected increase in SDIA related transportation demand
and its proximity to downtown is expected to contribute to further deterioration of traffic
congestion in the vicinity of the airport under the No Project and Preferred Alternatives.
In contrast, the Lindbergh ITC appears to have the potential to result in significant
reductions in traffic congestion around the airport.

A number of policy, marketing, and incentive-based programs from the Airport Transit
Plan were not included in our analysis of the Preferred Alternative with Airport Transit
Plan. Such policy, marketing, and incentive-based programs are expected to be at least
as, but probably more, effective in the Lindbergh ITC Scenario than under the Preferred
Alternative because more options and choices would exist with an integrated
transportation system. This may be an added benefit to the ITC approach because any
additional improvements would be on top of the reductions in congestion indicated under
Scenario 5.

Modeling results predict airport passengers place a heavy priority on time compared to
other parameters impacting their choice of transit mode. This reduces their sensitivity to
standard incentive programs. The modeling results from our study suggested that the
mode shares indicated in the Transit Plan will only be in the range of 2.6-3.0 percent
without additional incentives or influences (whether intentional or from external
influences outside the control of the SDCRAA). For example, our results predicted a
mode share for the Old Town Shuttle Bus Service and the Coaster Service were
approximately 20-30 percent of the mode shares anticipated by the Transit Plan and that
modeled increases in mode share were predominantly in bus use. Together, our results
indicate that the Draft Airport Transit Plan will not be adequate to mitigate increased
traffic and congestion under the No Project and Preferred Alternatives.

The City of San Diego has developed a greenhouse gas inventory for 1990 and 2004
(City of San Diego, No Date). The transportation sector in San Diego was reported to
contribute 7,864,800 greenhouse gas tons per year (approximately 21,547 greenhouse
tons per day) in 2004. This represented 52 percent of the community’s total greenhouse

San Diego International Airport Expansion –
Sustainability Analysis                                                              ES-17
Executive Summary


gas emissions. Both past (1990 to 2004) and predicted (2005 to 2030) data indicates that
the increase in fuel economy in vehicles has not and will not be adequate to keep up with
the greenhouse gas emissions from increased VMT unless new policies, transportation
alternatives, or behaviors are developed. Absent such dramatic change, the Lindbergh
ITC provided the most benefits of the scenarios evaluated. However, the ITC was
insufficient by itself to make sufficient reductions in VMT to reach even short-term goals
for greenhouse gas reductions if goals were uniformly applied across each segment of
society. However, the estimated 8 percent reduction of greenhouse gas emissions in the
Lindbergh ITC Scenario 5 could form an important component of an overall plan to
decrease greenhouse gas emissions associated with the SDIA.

This study is not a comprehensive evaluation of the sustainability of airport expansion
alternatives. We have limited our analysis to the ability to increase public transit
ridership, changes in VMT and LOS, greenhouse gas emissions, criteria pollutants, green
airport and green building opportunities and other sustainability components which result
from the above. The consideration of additional sustainability criteria and how they may
influence airport expansion decisions is warranted given the significant capital costs for
the project.

As stated previously, SDCRAA identified the following three objectives for the Master
Plan:

   Provide adequate facilities to accommodate air service demand through 2015 while
   improving airport levels of service, airport safety and security, and enhancing airport
   access;
   Develop facilities that effectively utilize the current airport property and facilities and
   are compatible with surrounding land uses; and
   Provide for future public transit options in airport land use planning.
Our analysis indicates that the Lindbergh ITC scenario meets the first and third SDCRAA
objectives better than the Preferred Alternative with Airport Transit Plan (Scenario 4).
The Lindbergh ITC provides opportunities to improve airport efficiencies, levels of
service, and access and provides substantially more effective options for enhanced future
public transit and land use planning. In addition, the Preferred Alternative with Airport
Transit Plan (Scenario 4) may limit future public transit options because high capital
costs for Terminal Two expansion and parking may preclude other options not rigorously
investigated given the constraints associated with the second objective. The Lindbergh
ITC is also generally compatible with adjacent land uses buy by design it does not stay
within the existing airport property boundary. Staying within the existing airport
boundary, however, is more a DEIR analysis constraint than an objective.




                                                            San Diego International Airport Expansion –
                                                                                 Sustainability Analysis
ES-18
                                                                       Executive Summary


The CAIVP identified the following potential benefits of the Lindbergh ITC scenario:

    Provide airport passengers and workers more efficient and environmentally friendly
    alternatives to reach the airport;
    Reduce automobile congestion in the vicinity of the airport;
    Encourage the use of transit;
    Provide SDIA an opportunity to reduce its carbon and environmental footprint; and
    Improve the quality of life and traffic congestion along the waterfront.
Our analysis indicates that the Lindbergh ITC scenario fulfills the potential benefits that
CAIVP identified. The transportation analysis shows that traveler public transit decisions
and mode choices would be positively influenced by the ITC. These traveler decisions
would result in reduced VMT, reduced congestion on in the vicinity of the airport and
downtown and would also reduce transportation related greenhouse gases and criteria
pollutants. The ITC improves public transit use and also enhances the effectiveness of
any future public transit expansions in the area. Consequently, the Lindbergh ITC would
also improve the opportunity to enhance the quality of life along the waterfront. The
demonstrated improvements to traffic, greenhouse gases, criteria pollutants, and other
sustainability components, coupled with the fact that the Lindbergh ITC meets the
SDCRAA objectives better than the Preferred Alternative indicates that the Lindbergh
ITC merits further detailed public discussion.




San Diego International Airport Expansion –
Sustainability Analysis                                                             ES-19
Executive Summary


This page left intentionally blank.




                                      San Diego International Airport Expansion –
                                                           Sustainability Analysis
ES-20
                                                                     1.     Introduction

This report analyzes several specific sustainability components related to the expansion
of the San Diego International Airport/Lindbergh Field (SDIA), including the Lindbergh
Intermodal Transportation Center (Lindbergh ITC or ITC) which has been independently
proposed by the California Independent Voter Project (CAIVP). The main purpose for
conducting this analysis is to provide the public, elected officials, and the San Diego
County Regional Airport Authority (SDCRAA) with a
                                                                  Intermodal refers to
broader understanding of the sustainability of the proposed       transportation system connecting
airport expansion plan and how that may compare to an             or including different types or
                                                                  modes of transport. The
integrated approach to address customer demand, traffic           Lindbergh ITC would link short-
                                                                  term parking, rental cars, and bi-
congestion in the vicinity of the airport, emissions of           level drop-off and pick-up roads
greenhouse gases and other air toxics, and other aspects
related to improving the sustainability of the greater San Diego community. This
sustainability analysis compares their proposed Lindbergh ITC , the SDIA DEIR No
Project Alternative and the DEIR Preferred Alternative. This chapter provides some
background information for the SDIA, describes the expansion alternatives, and lastly
describes the report objectives and contents.

1.1. Background
The City of San Diego and surrounding communities are serviced by one major airport,
SDIA, for commercial passenger and cargo traffic. Constrained by San Diego Bay and its
proximity to downtown San Diego, it is the smallest major airport in the U.S. with only
661 acres of land and a single east-west runway. The airport, operated by the SDCRAA,
served 17.7 million passengers in 2004. Passenger demand is expected to rise to 28.2
million by 2030 along with increases in cargo, general aviation, and military use (SH&E
2004; SDCRAA DEIR 2007). However, existing terminal facilities and the presence of a
single runway presents logistical problems for SDIA to satisfy its direct clients (the
airlines and cargo carriers) and their clients.

SDIA is a vital regional hub for business, personal and cargo transportation in the City of
San Diego, San Diego County and southernmost “to” the airportCalifornia (Figure 1-1
and Figure 1-2). It generates approximately 26,000 person-trips on a typical weekday (or
an assumed 52,000 trips to and from the airport). The airport is located within the City of
San Diego adjacent to San Diego Bay with Pacific Highway and I-5 to the east. SDIA has
two main passenger terminals, a commuter terminal, general aviation facilities, air cargo
facilities, aviation support facilities as well as airport rescue and fire fighting facilities.
Vehicular access to the airport is via surface streets through downtown or via Rosecrans
Street on the west.

San Diego International Airport Expansion: Sustainability Analysis
                                                                                               1-1
Chapter 1
Introduction

As required by state law, SDCRAA conducted a county-wide survey of potential
alternative airport sites from 2003 through 2006. They placed a measure on the 2006
ballot to share Marine Corps Air Station Miramar. That ballot measure did not pass, and
the current SDIA will be the regional airport for the foreseeable future.

               Figure 1-1: San Diego Region Transportation System.




                                         San Diego International Airport Expansion: Sustainability Analysis
  1-2
                                                                               Chapter 1
                                                                             Introduction




          Figure 1-2: Map of San Diego International Airport and Vicinity




1.2. Expansion Alternatives
The SDCRAA is in the planning process for implementing their Airport Master Plan
(www.san.org/airport_authority/airport master_plan/index.asp) and issued a Draft
Environmental Impact Report (DEIR) for public comment in October 2007. The DEIR
evaluates several alternatives for expanding SDIA within its existing boundaries.
SDCRAA has also prepared a draft Airport Transit Plan with staff from all the regional
transportation agencies (http://www.sdcraa.com/airport_authority/
airport_master_plan/transit_plan.asp) . This transit plan recommendation includes short-
term (1 to 3 years), mid-term (3 to 5 years) and long-term (greater than 5 year)
improvements. The plan’s target is to increase air passenger transit ridership from 1.2
percent to between 4 and 6 over the next three to five years.




San Diego International Airport Expansion: Sustainability Analysis
                                                                                    1-3
Chapter 1
Introduction

The Master Plan objectives are to:

   Provide adequate facilities to accommodate air service demand through 2015 while
   improving airport levels of services, airport safety and security and enhancing airport
   access;
   Develop facilities that efficiently utilize the current airport property and facilities and
   that are compatible with adjacent land uses; and
   Provide for future public transit options in airport land use planning.
The DEIR indicates that growth in passengers in 2004, 2005 and 2006 exceeded the
projected amounts. Overall airport passengers are expected to increase by 2.8 percent
each year for 2005 to 2015. The DEIR points out that the single runway constrains the
maximum amount of take-offs and landings. Consequently, increasing the capacity
efficiency of other airport components or having more terminal gates does not improve
the airport’s ability to accept more arriving flights (i.e., its practical capacity). The
projected demand increase for use of and access to the airport will continue despite
constraints on practical capacity.

The Master Plan DEIR evaluated five approaches to modify airport facilities to
accommodate increases in projected demand, ranging from a No Project Alternative, the
Preferred Alternative (Proposed Project with Parking Structure), the Proposed Project
without the Parking Structure, and an East Terminal with and without a Parking
Structure. Although the 2007 draft plan represents the latest thinking by the SDCRAA
for meeting the needs for airport services for San Diego and the surrounding communities
through 2015, this is not a new subject for the community. The ability of SDIA to meet
the needs of the community given its constraints and projected demand has been the
subject of an on-going discussion for many decades.

1.2.1.   DEIR No Project Alternative
The No Project Alternative under the Master Plan DEIR proposed no new projects to
improve the airport. Consequently the existing facilities at the airport would remain the
same despite the increased demand. The airport would not be able to maintain adequate
in-airport levels of service to airline passengers and airlines as the anticipated increase in
demand occurred. As disclosed in the DEIR, ground loading of passengers would be
required and terminal crowding and wait times would increase. No improvements to
transportation avenues are proposed under the no project alternative; therefore, traffic
congestion on all roadways leading to the airport would progressively increase. The
DEIR analysis of direct airport greenhouse gas emissions indicates that they would
increase by 41 percent from 2010 to 2030. Some criteria pollutants would exceed
thresholds in 2030.




                                           San Diego International Airport Expansion: Sustainability Analysis
  1-4
                                                                                  Chapter 1
                                                                                Introduction

1.2.2.      DEIR Preferred Alternative (Proposed Project with Parking
            Structure)
This DEIR Preferred Alternative includes the following components:

     Expand existing Terminal Two West with 10 new jet gates;
     Construct new aircraft parking and replacement Remain-Over-Night aircraft parking
     apron;
     Construct a new apron and aircraft taxi lane;
     Construct a second level road/curb and vehicle circulation serving Terminal Two;
     Construct a new parking structure (providing approximately 4,300 new parking
     spaces) and vehicle circulation serving Terminal Two;
     Relocate and reconfigure SAN Park Pacific Highway parking facility providing
     approximately 500 additional parking spaces;
     Construct a new access road from Sassafras Street/Pacific Highway intersection to
     provide access to the SAN Park Pacific Highway and new general aviation facilities;
     Construct new general aviation facilities including access, terminal/hangers, and
     apron to improve Airport safety for Airport customers/users;
     Demolish the existing general aviation facilities to improve airport safety and
     circulation airfield; and
     Reconstruct Taxiway C, construct new apron hold areas, and new taxiway east of
     Taxiway D.
The proposed airport modifications remain completely within the existing SDIA property
boundary.

The DEIR Preferred Alternative accommodates forecast growth in on-airport use through
2015 and improves the in-airport level of service. Customer access would still be via I-5
via surface streets to Harbor Drive either from downtown San Diego or via Rosecrans
Street. As noted by the DEIR, the increase in traffic congestion over the planning horizon
is projected to be minimized by implementation of Airport Transit Plan measures. These
measures have an aspirational goal of increasing transit use from the current 1.5 percent
to 4-6 percent within 5 years. The DEIR analysis of direct airport greenhouse gas
emissions would increase by 39 percent from 2010 to 2030. Similarly, some criteria
pollutants exceed thresholds by 2030.

1.2.3.      Proposed Lindbergh Intermodal Transportation Center
Given the high costs of airport expansion and the increased public awareness and
regulatory requirements to address the sustainability of new projects, including their
potential impacts on climate change, the California Independent Voter Project (CAIVP)
requested that Malcolm Pirnie and Sinclair Knight Merz (Pirnie/SKM) analyze selected

San Diego International Airport Expansion: Sustainability Analysis
                                                                                         1-5
Chapter 1
Introduction

sustainability aspects of both the No Project and the Preferred Alternatives of the DEIR
along with an alternative proposal prepared by the CAIVP. The CAIVP proposal is a
quite different vision for the SDIA (Figures 1-3, 1-4, and 1-5). This vision includes a
relocation of the airport terminals and their integration with a regional transportation hub
called the Lindbergh Intermodal Transportation Center (Lindbergh ITC or ITC).

    Figure 1-3: Map of Proposed Lindbergh Intermodal Transportation Center.




.




                                          San Diego International Airport Expansion: Sustainability Analysis
     1-6
                                                                                                    Chapter 1
                                                                                                  Introduction



            Figure 1-4: High Oblique Rendering of Lindbergh Intermodal
                              Transportation Center.
The ITC is in light blue and is located at the right. The turquoise blue color is the short-term parking area.
The drop-off and pickup areas are in red and green. The existing airport terminals occur to the left of the
runway in this rendering. Source: California Independent Voter Project.




San Diego International Airport Expansion: Sustainability Analysis
                                                                                                           1-7
Chapter 1
Introduction

Figure 1-5: Vertical Rendering of the Lindbergh Intermodal Transportation
                                  Center.
The new terminal location can be seen fronting Pacific Highway. The footprint of the ITC is shown in gray.
Source: California Independent Voter Project.




The ITC concept involves moving the airport’s terminals to the north side of the runway.
The existing 41-jet-gate configuration on the Harbor Drive (south) side of the runway
would be eliminated over time in a phased manner and a new 63-jet-gate terminal would
be created between Pacific Highway, the Marine Corps Recruit Depot property line, and
the runway. The existing fuel farm, Federal Aviation Administration control tower,
general aviation facilities, and cargo operations would move to the south side of the
runway, adjacent to Harbor Drive.

Ninety acres of land adjacent to the airport on the north side, bounded by Pacific
Highway, Interstate 5, Washington Street, and Laurel Street, would become an
intermodal transportation center, built over the existing train and trolley tracks.
Approximately half of this land is already owned by public agencies and much of the
remainder is already used for airport parking and rental cars. This structure would rise to

                                                  San Diego International Airport Expansion: Sustainability Analysis
  1-8
                                                                                  Chapter 1
                                                                                Introduction

the elevation of Interstate 5 (five stories tall) and structurally would be a large parking
facility. Under the CAIVP plan, the new airport terminals and the Lindbergh ITC would
have direct freeway links from I-5 in both directions. The Lindbergh ITC would include
the following features:

     Long-term parking for more than 20,000 vehicles and short-term parking for 2,000
     vehicles;
     Room for all car rental agencies and their rental cars;
     Bi-level drop-off and pick-up roads for plane, train, bus and trolley passengers;
     Provide direct access from the Lindbergh ITC to airport terminals via sky bridges that
     would include moving sidewalks;
     Provide new off ramps and on ramps directly to Interstate 5 to Pacific Highway for
     vehicular access to and from the new terminal location;
     Room for a downtown people mover and a high-speed rail between airports;
     Trolley stops where one can catch the Orange, Blue, Green and special event lines;
     An Amtrak Pacific Surfline stop (serving San Luis Obispo, Santa Maria, Santa
     Barbara, Ventura, Oxnard, Camarillo, Simi Valley, Van Nuys, Los Angeles, Santa
     Ana, and points in-between; and
     A Coaster stop bringing people in from Oceanside, Carlsbad, Encinitas, Solana Beach
     and Sorrento Valley.
The Lindbergh ITC would connect to all forms of transportation.

In addition to the 90 acres of public and private property described above, the Lindbergh
ITC would require a 27-acre strip of land owned by the Marine Corps Recruit Depot to
allow taxiway C to be extended to the end of the runway.

Because the Lindbergh ITC also includes constructing new airport terminals, it also
provides the opportunity for the creation of an enhanced green and sustainable SDIA by
incorporating up-to-date features to reduce energy use and carbon emissions. In addition
the concept itself aims to reduce traffic, miles driven by automobiles, and the concurrent
negative environmental impacts associated with vehicle use by transferring a portion of
airport access to rail-based modes of transportation.

A similar concept, proposed by the Port of San Diego in 2001, was estimated to cost $1.2
billion (CAVIP). While no up-to-date estimates are available, with construction
escalation, the CAIVP estimates that present costs may have tripled to roughly $3.5
billion.




San Diego International Airport Expansion: Sustainability Analysis
                                                                                         1-9
Chapter 1
Introduction

CAIVP believes the Lindbergh ITC would provide the following benefits:

   Provide airport passengers and workers more efficient and environmentally friendly
   alternatives to reach the airport;
   Reduce automobile congestion in the vicinity of the airport;
   Encourage the increased use of transit;
   Provide SDIA an opportunity to reduce its carbon and environmental footprint; and
   Improve the quality of life and traffic congestion along the waterfront.

1.3. Report Objectives and Content
CAIVP requested that Malcolm Pirnie and Sinclair Knight Merz (SKM) (Pirnie/SKM)
prepare an independent analysis of selected expansion alternatives developed in support
of the SDCRAA Airport Master Plan and the Airport Transit Plan along with a third
alternative, the Lindbergh ITC. This report provides an independent and objective
analysis of key sustainability components of the SDIA expansion. The report is intended
to stimulate further thinking and review about traffic, transit and sustainability
opportunities. It is not intended to provide a complete analysis of airport sustainability
nor provide a definitive analysis of all sources of greenhouse gas emissions and
sustainability. The major sustainability components evaluated in this report include:

   The ability to increase public transit ridership (mode share);
   Changes in daily vehicle miles traveled (VMT) by airport passengers and workers
   commuting to and from the airport;
   Changes in road traffic congestion on the streets around the SDIA;
   Impact of passenger and airport worker travel changes on greenhouse gas emissions;
   Impact of passenger and airport worker travel changes on air quality; and
   Lessons learned from a qualitative review of the experience at other international
   airports to implement “green airport” practices into a modified airport infrastructure.
Other positive sustainability components result from the above and these are also
identified.

This report is organized as follows:

   Chapter 2 discusses the modeled changes in vehicular traffic and public transport
   associated with the Lindbergh ITC;
   Chapter 3 discusses the changes in greenhouse gas emissions and criteria pollutants
   that occur as a result of the changes in vehicular traffic and public transport use;




                                          San Diego International Airport Expansion: Sustainability Analysis
 1-10
                                                                                   Chapter 1
                                                                                 Introduction

     Chapter 4 discusses a context for sustainability and describes the potential for
     sustainability benefits associated with green airport approaches and green building
     standards;
     Chapter 5 summarizes the report’s conclusions;
     Chapter 6 contains references;
     Appendix A presents case studies on mass transit access to five airports;
     Appendix B presents a detailed description of the transport modeling;
     Appendix C presents detailed calculations of greenhouse gas emissions;
     Appendix D presents detailed calculations of criteria pollutants;
     Appendix E presents information on the Leadership in Energy and Environmental
     Design (LEED) system;
     Appendix F presents information on worldwide airport environmental initiatives from
     the Airports Council International.




San Diego International Airport Expansion: Sustainability Analysis
                                                                                       1-11
Chapter 1
Introduction



This page left intentionally blank.




                                      San Diego International Airport Expansion: Sustainability Analysis
 1-12
                                                      2.        Transportation Analysis

This chapter describes the existing and possible future transportation conditions (traffic
and transit) associated with the SDIA and the Lindbergh ITC concept proposal in
comparison to the SDCRAA DEIR. The first section provides background on the San
Diego area and the airport, the second discusses airport ground transportation, the third
describes the scenario modeling including the modeling approach and the scenarios or
alternatives analyzed, and the fourth presents the results and discussion. Appendices
include case studies of airports in other U.S. cities for comparison with San Diego
(Appendix A) and a description of the transportation model developed for this study
(Appendix B).

2.1. Background
2.1.1.      Regional Transportation
The San Diego region had a metropolitan population of just over 3 million in 2007 with
1.3 million living in the city. The city and region have grown rapidly in population and
the region is forecast to increase further to approximately 3.9 million residents in 2030
(SANDAG, 2004). Redevelopment of a number of areas, including the waterfront, will
result in substantial increases in downtown population over this period. This increased
population, along with increased employment in the area, is likely to increase traffic use
on city roads already heavily used by airport traffic, such as North Harbor Drive, Grape
Street and Hawthorn Street. In addition, total exposure to the local air quality pollutants
and noise generated by airport related traffic movements through city streets is also likely
to increase.

The transportation network around SDIA is illustrated in Figure 2-1. The existing
highway network has not kept pace with increased travel demand resulting both from the
rapidly rising population and increased prosperity of the region. The result is
increasingly congested traffic conditions. According to the Texas Transportation
Institute’s annual review of traffic congestion across the country, San Diego has the worst
traffic congestion of all medium sized cities (one to three million residents) in the U.S.
when measured as excess trip time in peak periods compared to off-peak periods. Peak
period travelers in the San Diego region suffered from an average annual delay of 57
hours each in 2005 as a result of congestion. This compares unfavorably with other




San Diego International Airport Expansion: Sustainability Analysis
                                                                                       2-1
Chapter 2
Transportation Analysis




                    Figure 2-1: Study Area Transport Network




rapidly growing cities such as Sacramento, where the average annual delay was 41 hours,
and Las Vegas, where the average delay was 39 hours. A number of older, midsize cities
that are experiencing stable or declining populations have lower average congestion
delay; for example Pittsburgh experienced an average of 16 hours annual delay and
Cleveland 13 hours. Car trips on freeways in San Diego were on average 31 percent
longer in the peak period compared to free-flow conditions. In Sacramento, they were 26
percent longer and in San Francisco 25 percent longer.

Increased road traffic congestion has a direct negative impact on the operations of SDIA,
by increasing the time and reducing the reliability for passengers and employees to travel
to the airport. Road traffic congestion also adversely impacts San Diego’s competitive
position by making it less attractive to air passengers who may have alternatives for
vacations or business meetings. Cargo operators who rely on the airport road system to
transport goods rapidly to and from the airport are also adversely affected by traffic
congestion.

Traffic congestion also serves to erode the quality of life in the urban environment though
degraded air quality, increased noise and unpleasant urban spaces. Given the highly
populated inner urban nature of many of the roads which are most congested as a result of

                                          San Diego International Airport Expansion: Sustainability Analysis
  2-2
                                                                                  Chapter 2
                                                                     Transportation Analysis

airport traffic, especially Grape and Hawthorn Streets, the exposure to these negative
aspects may be expected to be higher than in less populated suburban areas.
Furthermore, congestion results in additional fuel consumption which results in higher
costs to travelers and increased criteria pollutants and greenhouse gas emissions (see
Chapter 4). Approaches to reducing congestion, as well as minimizing the distances
driven, could help to alleviate these impacts.

2.2. Airport Ground Transportation
2.2.1.      Road Network
The location of the airport close to downtown San Diego, and directly to the south of the
I-5 and near the I-8 highways offers an opportunity to improve public access to airport
facilities by developing efficient access to the highway network, albeit a network that is
increasingly capacity-constrained. However, the location of the airport terminals on the
south side of the airfield results in the need for airport traffic coming from the freeway
corridors to use a number of local streets, including through the downtown area. This
physical layout has adverse implications for both congestion and the quality of life in
urban environment in the vicinity of these streets.

Figure 2-2 illustrates the current proportion of airport related traffic on key road links in
the vicinity of the airport. As shown, the airport is a dominant traffic generator in the
local area and a major source of local traffic congestion.

Levels of congestion are commonly measured on a level-of-service scale that ranges from
A for free flow conditions to F for major traffic disruption; the levels are described in
Table 2-1. Levels of service of E and F are typically deemed unacceptable for efficient
roadway operation. Figure 2-3 illustrates the level-of-service (LOS) that is currently
experienced on the major roads in the area. A number of routes during peak periods,
such as Grape Street and Rosecrans Street operate at LOS E or F. This has implications
for trip times and reliability as well as of wider urban amenity resulting from the noise,
emissions and adverse impacts on the streetscape that result. As airport traffic makes up
substantial proportions of the traffic along many of these routes which are operating
beyond capacity it follows that a reduction in airport traffic would help to alleviate
congestion on some of these routes.




San Diego International Airport Expansion: Sustainability Analysis
                                                                                         2-3
Chapter 2
Transportation Analysis

Figure 2-2: Current Percent Airport Related Traffic by Road Segment (SDIA
                               DEIR, 2007)




   Figure 2-3: Airport Related Traffic with Current LOS (SDIA DEIR, 2007)




                                   San Diego International Airport Expansion: Sustainability Analysis
  2-4
                                                                                                 Chapter 2
                                                                                    Transportation Analysis




                           Table 2-1. Level-of-Service (LOS) Descriptions

      LOS                                                      Description

       A           Free-flow conditions
       B           Reasonably free-flow conditions, ability to maneuver within the traffic stream is only slightly
                   restricted.
       C           Traffic speeds remain close to free-flow but freedom to maneuver within the traffic stream is
                   noticeably restricted, resulting in a need for added driver vigilance.
       D           Traffic speeds decline slightly with increasing flow and maneuvering becomes increasingly
                   limited.
       E           Operating at capacity resulting in volatile road performance and no usable gaps in the traffic
                   stream.
        F          Breakdown in traffic flow where lines are extensive and can extend significant distances
                   upstream.



The location of the terminal buildings to the southeast of the airport makes access by car
difficult from many locations. Traffic is required to circulate through city streets such as
Hawthorn and Grape Streets, along arterials such as Rosecrans Street and along Kettner
Boulevard to the north. Furthermore, the number of airport-related uses to the north of
the airport, such as car rental and parking, results in additional shuttle van movements
and inconvenience for air passengers in accessing the terminal buildings.

2.2.2.      Transit
Public transit use for airport access is low by comparison to other U.S. and international
cities. Approximately 1 percent of air passengers use local bus services to access the
airport, most predominantly the 992 Airport Flyer service. As shown in Figure 2-4,
approximately 55 percent of passenger movements to and from the airport are made by
private car (park on-airport, park off-airport, drop off) while another 28 percent are by
rental car or taxi (HNTB, 2007). Similarly, as shown in Figure 2-5 airport employees
predominantly use car to access the airport, with only approximately 2 percent using bus
(HNTB, 2007). This fraction does, however, make up two thirds of total bus ridership to
the airport. By comparison, Chicago O’Hare Airport has 4 percent share of rail and over
5 percent share of bus (local and express services) for air passenger access to the airport
(Leigh River Associates et al., 2002).




San Diego International Airport Expansion: Sustainability Analysis
                                                                                                           2-5
Chapter 2
Transportation Analysis



Figure 2-4: Airport Passenger Ground Transportation Mode Shares at SDIA
                              (HNTB, 2007)


                                       Charter/other bus,
                                             1.0%
                  Courtesy van, 5.8%
                         Bus, 1.0%                       Private Car: park on-
                                                            airport, 19.5%
           Shared van, 9.5%




            Taxi, 8.6%
                                                                    Private Car: park off-
                                                                       airport, 10.0%




          Rental car, 19.1%

                                                      Private Car: drop
                                                          off, 25.5%




  Figure 2-5: Ground Transportation Mode Shares for Employees at SDIA
                             (HNTB, 2007)

                                        Bus, 2%




                                          Private Car, 98%




                                             San Diego International Airport Expansion: Sustainability Analysis
  2-6
                                                                                  Chapter 2
                                                                     Transportation Analysis




2.2.3.      Trolley
The San Diego Trolley, operated by the Metropolitan Transit System (MTS) is a light rail
system consisting of three main lines:

     Blue line which runs from the Mexican border at San Ysidro north through downtown
     and then to the north of the airport to Old Town Transit Center.
     Orange line which runs from Gillespie Field to downtown, running in a loop from the
     12th & Imperial Transit Center around the downtown area.
     Green line, completed in 2005, which connects the Old Town Transit Center to
     Santee.
Bus feeder services provide connecting services to the trolley system at 34 of the 53
stations (64 percent) while parking is provided at 28 (53 percent) of the stations. Most
stations provide free parking, and in the majority of cases there are no current capacity
constraints on parking at the stations. There may, however, be issues for air passenger
parking at these locations because air passengers may require parking for more than one
day. This would introduce issues of parking security (particularly overnight) as well as
increasing pressures on overall parking capacity. Changes in the way in which parking
lots operate would be required. For example, while ample parking is available at
Qualcomm Stadium when events are not taking place, there is currently no parking
specifically allocated for the trolley station. It is likely that dedicated parking would be
required should such a site be allocated for airport-related transit trips. Similarly, Old
Town Transit Center does not currently provide long-term parking. Existing parking is
relatively constrained and the site location would limit opportunities to substantially
increase parking capacity at this site. An additional issue is that Old Town is operated by
California State Parks and serves as parking for visitors to the Old Town State Park in
addition to the transit center. This is reinforced by the signing at the site, which
emphasizes the site as the location of the state park (Figure 2-6).

Major trolley interchanges are provided at Old Town Transit Center, Santa Fe Depot, and
the 12th and Imperial Transit Center. The southbound Green line currently terminates at
Old Town Transit Center, where the southbound Blue line service to downtown and San
Ysidro begins. All Coaster services stop at Old Town, and some Amtrak Surfliner
services also stop at the station. Santa Fe Depot is the terminus of the Coaster and
Amtrak passenger services as well as servicing the Blue line. America Plaza station,
located directly across Kettner Boulevard from the Santa Fe Depot, provides connections
to the Orange line as well as a stop on the Blue line. The 12th and Imperial Transit Center
provides a connection between the Orange and Blue lines on the south side of the
downtown area. The system has among the highest levels of ridership of any light rail



San Diego International Airport Expansion: Sustainability Analysis
                                                                                       2-7
Chapter 2
Transportation Analysis



             Figure 2-6: Entrance to Existing Old Town Transit Center




system in the U.S. with 124,000 average weekday riders in the first three quarters of 2007
(APTA, 2007). This compares favorably with the 106,000 average daily riders on the
light rail systems in Portland (OR) and 82,000 in Saint Louis (MO) over the same period
(APTA, 2007).

A number of studies are, or have been completed, examining potential extensions of the
trolley system including:

   Green line extensions to downtown.
   Mid-Coast Corridor Study to examine the potential for a trolley or bus rapid transit
   extension from old Town Transit Center north to University City.
While ridership has increased substantially over recent years, the network has excess
capacity available across much of the day and could accommodate more frequent services
on the current infrastructure should there be sufficient demand, sufficient subsidy and
sufficient light rail vehicles acquired. The proposed ITC could leverage from this


                                         San Diego International Airport Expansion: Sustainability Analysis
  2-8
                                                                                  Chapter 2
                                                                     Transportation Analysis

available capacity to provide additional trolley ridership at little marginal cost to the
transit service provider. It is likely that the net operating subsidy required would
decrease given that ridership is likely to increase at little marginal cost. However, as
indicated by the analysis later in this chapter, extending the trolley system such that more
lines would access the ITC would improve ridership further. The infrastructure required
to achieve this enhancement would not appear to be insurmountable given that sufficient
rolling stock and service paths are available on the existing alignment.

2.2.4.      Bus
Local bus services are provided by MTS. These services include feeder bus services to
the Coaster and trolley system as well as standalone bus services such as the 992 Airport
Flyer, which provides services at 12 minute intervals during the day on weekdays and at
15 minute headways at other times between 5am and 12am. The service connects the
downtown area to the airport, serving all three airport terminal buildings. The service is
now provided by dedicated low floor vehicles fitted with luggage storage and are clearly
branded as airport services. Recent passenger surveys suggest that approximately 65
percent of users of the service are airport employees.

The 923 route also serves the airport, providing serves roughly every half hour between
downtown and Ocean Beach. The service is not marketed as an airport service because it
does not enter the terminal area, and the location of the nearest stops on North Harbor
Drive are inconvenient for air passengers and airport employees.

2.2.5.      Coaster
The Coaster rail service, operated on behalf of North County Public Transit District
(NCTD), provides a regional rail service between San Diego Santa Fe station and
Oceanside. All services stop at the Old Town Transit Center. The rail alignment runs
parallel to the trolley service between Santa Fe station and Old Town, passing directly to
the north of the airport site. North of Old Town much of the alignment is single track,
with several passing loops. In addition to sharing the tracks with Amtrak intercity
services and freight trains, this imposes a cap on the number of daily trips available to the
public and the services that can be provided. Currently eleven services are offered daily
in each direction with a much reduced service on Saturdays and no service on Sundays.

2.2.6.      Amtrak
Amtrak provides intercity services from the San Diego Santa Fe station to Los Angeles
and further north to Santa Barbara and Paso Robles on the Pacific Surfliner route. Twelve
trains provide services operating on weekdays at least as far as Los Angeles, with a
slightly reduced service of ten to eleven services per day per direction on weekends. This
Amtrak route shares the alignment with the Coaster services operated by NCTD as far
north as Oceanside.


San Diego International Airport Expansion: Sustainability Analysis
                                                                                       2-9
Chapter 2
Transportation Analysis

2.2.7.   SDCRAA Airport Transit Plan
SDCRAA have been consulting on their draft Airport Transit Plan during 2007. The plan
has an aspirational target of increasing air passenger transit ridership from 1.2 percent to
4-6 percent in the next 3-5 years. In order to achieve this goal, they describe a series of
measures both near-term (until the end of 2009) and mid-term (2010 to 2011). They also
identify more broadly longer term measures (beyond 2012) that may be considered. Of
the near-term measures for which a quantified mode split target is given, the total
increase in transit mode share would be 2.5 percent (accounting of 1.5 percent from
marketing, 0.5 percent from offering free rides to arriving passengers and 0.5 percent
from extending the bus service to the convention centre).

Mid-term measures for which quantified mode share targets are provided include
reducing bus service intervals to 10 minutes (0.25 percent shift in mode share), adding
evening and weekend Coaster trips (1.0 percent), providing a shuttle to Old Town Transit
Center (1.0 percent) and remote parking sites (1.5 percent). This gives a total of 3.75
percent, or 6.25 percent when incorporating the near-term measures.

There may be additional positive influences from many of the other unquantified
measures, such as using low floor buses and the introduction of NextBus signs. The
assessment of transit mode shares achievable with each of these options was based on
professional judgment in the Transit Plan.

SDCRAA along with other local stakeholders have also been exploring the using of
remote park & ride facilities along major corridors, potentially including sites in North
County (I-5), Escondido/Poway (I-15), Miramar/Mira Mesa and El Cajon/La Mesa (I-8).
These may be similar to the ‘remote terminal’ concept as used by LAX at Van Nuys,
where passengers can check-in their baggage and receive their boarding pass and then
travel by dedicated bus service to LAX.

2.2.8.   Mitigation Measures to Address Airport Related Traffic
Measures to mitigate the adverse impacts of airport related traffic, particularly with
regard to congestion relief, may include providing alternative or expanded roadway
capacity. The DEIR proposes a number of measures to enhance roadway capacity in the
vicinity of the airport, including targeted road widening, intersection improvements and
removal of on street car parking. While these approaches are shown to satisfactorily
address congestion to 2030 on all but North Harbor Drive no assessment is made of their
viability financially, environmentally or in terms of public acceptability. The multi-use
nature of most of the local road network would likely limit what could be achieved given
the needs of local residents and businesses for the road network beyond airport access. It
is unclear whether the FAA would contribute to the financing of such infrastructure given
that it would be located outside the airport boundary. Any funding shortfall would most
likely come from local sources such as SDCRAA, Caltrans and the City government. By

                                          San Diego International Airport Expansion: Sustainability Analysis
 2-10
                                                                                  Chapter 2
                                                                     Transportation Analysis

comparison, mitigation measures that result in reduced traffic demand – such as the ITC
proposal, may receive substantial financial contributions from the FAA, resulting in a
much lower financial burden on SDCRAA, Caltrans and the City government.

Traffic flows on the I-5 corridor in the vicinity of the airport were studied in 2003 as part
of the Central I-5 Corridor Study (URS, 2003), which made a number of
recommendations in regard to airport access, including:

     New I-5 on/off ramps between I-5 north and the Pacific Highway just south of the
     Old Town interchange. The southbound off-ramp would exit I-5 south of Old Town,
     cross over the trolley and railroad tracks and remain elevated until coming to grade at
     Pacific Highway, north of Washington Street. The on-ramp from Pacific Highway to
     northbound I-5 would also be on structure and would cross over I-5, requiring
     braiding with the northbound off-ramp to Old Town. It was recommended that this
     option also include enhancements to the I-5/Old Town interchange including
     realignment of the southbound on-ramp, as well as Hancock Street.
     Modification of existing Pacific Highway viaduct to provide on/off ramps between
     south I-5 and the airport. The existing eastbound exit ramp from the Pacific Highway
     viaduct onto Pacific Highway to the east of Washington Street would need to be
     replaced as part of the works.
In addition, the study recommended the expanded use of parallel arterial routes to relieve
short distance I-5 traffic in the central city area from needing to use the route as well as
the development of high-occupancy vehicle (HOV) lanes either on the I-5 itself or, more
likely, on Pacific Highway. Other related road infrastructure changes proposed include
the redesign of the I-5/I-8 interchange, which could conceivably result in more airport
traffic using Rosecrans Street when traveling from the north. Much of the analysis in the
URS study was based on the assumption of the development of a north terminal that
would operate in conjunction with the existing south terminal; the resulting new on/off
ramps between the I-5 and Pacific Highway would, therefore, provide direct highway
connection to the new north terminal.

The URS study noted that despite the cost and engineering complexity of the proposed
road enhancements in the vicinity of the I-5 and Pacific Highway that much of the road
network leading to the (existing) south terminal would remain at an unacceptable level of
service, particularly at the intersections of Laurel Street and Pacific Highway and Laurel
Street and Harbor Drive. The study recommended grade separation of these junctions,
although it did note that such separation may not be consistent with other developments
in the vicinity of the airport, where such separation may have adverse local noise and
viewing corridor impacts.

The study identified a number of design deficiencies on the I-5 that serve to decrease its
capacity, including substandard distances between interchanges (resulting in greater
traffic weaving) and substandard ramp geometries which serve to exacerbate driver
San Diego International Airport Expansion: Sustainability Analysis
                                                                                       2-11
Chapter 2
Transportation Analysis

confusion and weaving movements in the vicinity of the junctions. Redesign of the
junctions in the vicinity may be expected to help with capacity, but given the present
terminal locations would be unlikely to relieve congestion on Hawthorn, Grape and
Rosecrans Streets.

While roadway expansion or other measures designed to improve traffic flow to the
airport may well assist in enhancing access to the airport, it may also be desirable to
improve access by providing efficient transit alternatives and in so doing reduce total
vehicle movements. Mass transit can be more energy efficient than private cars and
reduce emissions of local air pollutants and greenhouse gases. However, for transit to be
an attractive alternative it must go to where air passengers and employees want to travel,
be reliable, be safe, operate at hours when travelers wish to access the airport, be cost
effective for the traveler and be visible (that is, travelers need to be aware that the transit
alternative exists). Understanding the demand for transit alternatives is, therefore, a
complicated process, requiring an understanding of how travelers perceive the attributes
of different mode alternatives in making their travel decisions. Likewise, where multiple
changes are being considered in parallel – for example, improved access to the trolley
system as well as roadway enhancements, then it is important to consider such
improvements together rather than in isolation. Improving access to the trolley system
would be expected to improve trolley ridership, but improving road access as well may
make travel by car sufficiently more attractive to negate any trolley ridership benefits. It
is the role of modeling to evaluate these counterbalancing effects.

2.3. Scenario Modeling
2.3.1.   Modeling Approach
In order to examine the impact of the Proposed Alternative in the DEIR and the ITC on
the choices of travelers to the airport, and in turn on the congestion and emissions
impacts that these choices would have, a transit mode choice model was developed. This
model predicts travelers mode choices based on the trip times, costs and other factors that
are important in the decision-making process of travelers.

An understanding of the distribution of where people come from (travel origins) was
required for both air passengers and airport employees in order to develop the model.
Due to limited data availability, it was necessary to assume the same distribution for both
groups. In reality, it would be expected that airport employees would tend to live closer
to the airport. Other required data, such as travel times and costs, were obtained from the
SANDAG regional transportation model and other public domain sources.

The sensitivity to time and cost will differ across different types of traveler. For
example, those traveling on business would be expected to be more time sensitive than
cost sensitive in comparison to leisure travelers. These sensitivities were obtained based
on a model from San Jose International Airport and adjusted to reflect values of time

                                            San Diego International Airport Expansion: Sustainability Analysis
 2-12
                                                                                            Chapter 2
                                                                               Transportation Analysis

found across other airports in the U.S. Ideally these sensitivities would be derived from
local surveys of travelers to San Diego Airport; however, such a study was outside the
scope of the present work. Reasonable assumptions can be made based on studies from
other U.S. airports. More robust estimates could be developed later by initiating a local
data collection and modeling study to obtain local sensitivities, which could then be
incorporated into the model system developed for this study.

The model system was developed in a spreadsheet to allow rapid evaluation of various
transportation improvements both in total, for specific types of travelers (for example,
business travelers or non-residents) and along specific corridors. The region was divided
into 78 zones such that the travel times and costs for each transport mode was determined
for each scenario. The modeling approach is described in detail in Appendix B.

2.3.2.      Modeled Scenarios
Several current and future transport scenarios were developed for analysis:

     Scenario 1 (2005 Baseline) – Or ‘As now’ with modeled conditions in 2005 based on
     infrastructure as it exists presently. There are no changes in ground transportation
     access to the airport.
     Scenario 2 (No Project Alternative @ 2030) – Same as the DEIR No Project
     Alternative at 2030. Predicted traffic based on no changes in infrastructure or in the
     Airport Transit Plan. Scenario 2 differs from Scenario 1 based on increases in
     demand and how increased congestion may influence passenger and airport worker
     choices without any changes in transportation infrastructure or incentive programs.
     Scenario 3 (Preferred Alternative) – This scenario included recommendations from
     the DEIR Master Plan Preferred Alternative at 2030 but does not include the traffic
     mitigation measures or draft Airport Transit Plan.
     Scenario 4 (Preferred Alternative with Airport Transit Plan) – Same as Scenario 3
     except with an Old Town shuttle bus service, free Flyer fares, reduced Flyer
     headways from 12 to 10 minutes, evening and weekend Coaster rail service and
     FlyAway sites at Escondido Transit Center, I-15/SR52 and I-805/SR54 junctions.
     These measures are part of the draft Airport Transit Plan.1
     Scenario 5 (Lindbergh ITC) – Predicted traffic in 2030 based on the Lindbergh ITC
     with the removal of the 992 Flyer route, extension of the Trolley Green line south


1
  Other proposed elements of the draft Transit Plan (including improved marketing, customer service
training, ticket machines and NextBus signs) were not included in this scenario because they were not
readily amenable to quantitative analysis and did not change the basic infrastructure-based options
available to airport passengers and workers. While these types of policy, marketing and incentive-based
programs are expected to have some influence on mode choice, they are at least, but probably more,
effective in the Lindbergh ITC scenarios defined below than Scenario 4 because more options and choices
would exist for travelers with an integrated transportation system. As in any modeling, the scenario results
may not predict ‘absolute’ data but they are useful for comparative evaluations among the scenarios.

San Diego International Airport Expansion: Sustainability Analysis
                                                                                                     2-13
Chapter 2
Transportation Analysis

   from Old Town Transit Center to the ITC, extension of the Orange line north to the
   ITC and transit improvements from Scenario 4 (except for Old Town shuttle).


                          Figure 2-7: Tested Trolley Network




The development to the trolley network as part of the ITC that were tested are shown in
Figure 2-7. This is an indicative network only for the purposes of estimating passenger
demand; it is not proposed as a potential service pattern. There would be issues
associated with introducing these extensions. For example, the Siemens SD70 vehicles
currently used on the Green line would not be compatible with stations south of Old
Town. However, it is expected that in the timescales of the proposed development that


                                         San Diego International Airport Expansion: Sustainability Analysis
 2-14
                                                                                    Chapter 2
                                                                       Transportation Analysis

such modifications to stations could be incorporated as part of a fleet update strategy and
potential extensions of the Green line irrespective of any airport redevelopment.

The scenarios were analyzed using both a conservative and an optimistic set of
assumptions. Specifically:

     A conservative assumption that the intrinsic features of bus, trolley and rail services
     (such as ride quality, service reliability and other qualitative service characteristics)
     are the same aside from fare and trip time differences; and
     An optimistic assumption that assumes that trolley and rail services have features
     which makes them more attractive than bus services. These features include ride
     quality, permanence of routes and other onboard conveniences.
The optimistic assumption estimates that these intrinsic benefits of rail are valued as
being equivalent to six minutes of trip time. This is consistent with SANDAG’s regional
transportation model and with findings from studies in other locations. It is, however,
highly dependent on the specific services being compared; it would, for example, be
possible for a very high quality bus service to be similarly attractive to a rail service.

2.4. Results and Discussion
The forecasted 60 percent growth in air passengers between 2005 and 2030 will add
substantially to ground transportation demand within the vicinity of SDIA. In addition,
background traffic growth resulting from continued population growth and
redevelopment in the vicinity of the airport will further add to demand, increasing
congestion on the local road and transit networks. This section presents the results of the
modeling for each scenario and discusses the implications on mode share, vehicle miles
traveled (VMT) and transit ridership.

2.4.1.      Mode Share
The forecast mode shares for each of the scenarios are detailed in Figure 2-8 and Figure
2-9 for the conservative and optimistic scenarios, respectively. The forecast mode share
values are summarized in Tables 2-2a and 2-2b for conservative and optimistic
assumptions, respectively. If the Lindbergh ITC concept were implemented, then total
transit ridership would increase from 2.6 percent to 4.0 percent (an additional 1,128 riders
per day) using the conservative assumption and 5.2 percent using the optimistic
assumption (an additional 1,986 riders per day).




San Diego International Airport Expansion: Sustainability Analysis
                                                                                          2-15
Chapter 2
Transportation Analysis

  Figure 2-8: Mode Share for Conservative Scenario (Air Passengers and
                           Airport Employees)

                35%
                                                                                                           Scenario 2 (No Proj Alt @ 2030)
                                                                                                           Scenario 4 (Preferred Alt)
                30%
                                                                                                           Scenario 5 (Lindbergh ITC)

                25%
  Mode share




                20%


                15%


                10%


                5%


                0%
                      Car - On-   Car - Off-   Car - Kiss Car - rental     Taxi    Shared van    Bus      Trolley    Coaster     FlyAw ay
                       Airport     Airport       & Fly
                        Park        Park




           Figure 2-9: Mode Share for Optimistic Scenario (Air Passengers and
                                   Airport Employee)

                35%
                                                                                                           Scenario 2 (No Proj Alt @ 2030)
                                                                                                           Scenario 4 (Preferred Alt)
                30%
                                                                                                           Scenario 5 (Lindbergh ITC)

                25%
   Mode share




                20%


                15%


                10%


                 5%


                 0%
                      Car - On-   Car - Off-   Car - Kiss Car - rental     Taxi    Shared van    Bus      Trolley    Coaster     FlyAw ay
                       Airport     Airport       & Fly
                        Park        Park




                                                                         San Diego International Airport Expansion: Sustainability Analysis
 2-16
                                                                                                      Chapter 2
                                                                                         Transportation Analysis




             Table 2-2a. Transit Mode Shares by Scenario (Conservative Assumptions)

                         Bus                      Trolley                   Coaster                FlyAway              All Transit


 Scenario       Mode       Boarding       Mode      Boarding         Mode     Boarding     Mode      Boarding     Mode      Boarding
                share      Change         share     Change           share    Change       share     Change       share     Change
                (%)                       (%)                        (%)                   (%)                    (%)


 No Project       0.8           ---         0.2          ---          0.3         ---        ---         ---          1.3        ---
 Alternative
 @ 2030


                  1.4         +491          0.3         +60           0.2        +98        0.5        +435           2.6     +1,084
 Preferred
 Alternative
 with Airport
 Transit
 Plan @
 2030


                  0.6          -234         1.9       +1,415          1.0        +632       0.5        +399           4.0     +2,212
 Lindbergh
 ITC @
 2030




San Diego International Airport Expansion: Sustainability Analysis
                                                                                                               2-17
Chapter 2
Transportation Analysis




                Table 2-2b. Transit Mode Shares by Scenario (Optimistic Assumptions)


                          Bus                Trolley                  Coaster                   FlyAway                   All Transit


 Scenario         Mode    Boarding   Mode      Boarding         Mode      Boarding       Mode       Boarding       Mode       Boarding
                  share   Change     share     Change           share     Change         share      Change         share      Change
                  (%)                (%)                        (%)                      (%)                       (%)


 No Project       0.8     ---        0.2       ---              0.3       ---            0.0        ---            1.3        ---
 Alternative
 @ 2030


                  1.4     +490       0.4       +80              0.5       +128            0.7       +604           3.0        +1,303
 Preferred
 Alternative
 with Airport
 Transit
 Plan @
 2030


                  0.6     -234       2.6       +1,905           1.4       +849            0.7       +550           5.2        +3,070
 Lindbergh
 ITC @
 2030




                                                     San Diego International Airport Expansion: Sustainability Analysis
 2-18
                                                                                             Chapter 2
                                                                                Transportation Analysis




The increase in transit share for airport employees is somewhat lower than for air
passengers, as the relative costs between the modes makes car the cheaper mode for
many trips. For example, from Mission Valley the fare to the airport using transit is
$2.50 while the distance by car is 4.2 miles and so assumed cost (based on $0.15/mile) is
$0.63 2 3 . The improvements made to the transit network result in trip time benefits (a
reduction in transit in-vehicle time from 45 to 20 minutes) to make transit competitive
with car (for which the trip time was assumed to be 15-20 minutes) before accounting for
the additional time to access the transit service. There would, however, be no cost
savings for transit users, and so the air passenger transit share increases more than that for
airport employees because the former are more time sensitive.

A number of policy, marketing, and incentive-based programs from the Airport Transit
Plan were not included in our analysis of the Preferred Alternative with Airport Transit
Plan. Such policy, marketing, and incentive-based programs are expected to be at least
as, but probably more, effective in the Lindbergh ITC Scenarios than under the Preferred
Alternative because more options and choices would exist with an integrated
transportation system. This may be an added benefit to the ITC approach because any
additional improvements would be on top of the reductions in congestion indicated under
Scenario 5. The Convention Center shuttle bus service was not included in the modeling
because of the coarse nature of the zoning system in the downtown area, which was a
result of limitations in the available data. While this exclusion will tend to understate the
transit potential of the Preferred Alternative with Airport Transit Plan marginally, it is
assumed to have no effect on the ITC scenario as the Trolley Orange line would serve the
Convention Center directly from the ITC.




2
  The assumed perceived cost per mile of $0.15 is to be consistent with the SANDAG regional
transportation model. This is significantly lower than the rate of $0.485 per mile allowable for income tax
purposes. The latter number attempts to account for perceptions regarding insurance, maintenance,
depreciation and other costs not generally perceived on a per mile basis. At gas prices of approximately
$3.00 per gallon, a typical car that achieves 25 mpg would cost approximately $0.12 per mile based on gas
costs alone, which is broadly consistent with the value assumed here. Sensitivity tests with the value set to
$0.485 per mile indicate that the reduction of VMT would be less than 1 percent. This low responsiveness
to fuel prices is due to the relative cost insensitivity of air passengers, for whom timelines are more
important than cost.
3
  Background traffic forecasts, as well as the mode choices of airport travelers, assume car operating costs
consistent with the SANDAG regional transportation model. This model assumes that fuel prices will
increase from $1.70/gal in 2000 to $2.80/gal in 2030. Given that fuel prices were hovering around
$3.00/gal in early 2008 it is not clear whether this assumption is robust. If in fact fuel prices were to be
significantly above $2.80/gal in 2030 then it may be expected that background traffic levels would be
somewhat lower than forecast and that the transit mode share to the airport would be higher. This may be
particularly true for scenarios where the Lindbergh ITC is in place, as the improved transit alternatives
combined with higher fuel prices would act to encourage greater transit use.

San Diego International Airport Expansion: Sustainability Analysis
                                                                                                       2-19
Chapter 2
Transportation Analysis

Modeling results predict airport passengers place a heavy priority on time compared to
other parameters impacting their choice of transit mode. This reduces their sensitivity to
standard incentive programs. Furthermore, our results indicated the mode shares
obtainable as reported in the draft Airport Transit Plan may not achieve the plan’s
aspirational goals. The quantified mode share contributions listed in the draft Airport
Transit Plan add to 6.25 percent while our results suggest that the improvement in transit
mode share would be significantly lower, leading to a total mode share of 2.6 to 3.0
percent. Together, our results suggest that the draft Airport Transit Plan will not be
adequate to mitigate increased traffic and congestion under the No Project and Preferred
Alternatives.

2.4.1.1.   Transit Demand
In the present study the approach taken is to model, even at a relatively high level, the
potential impacts in order to evaluate the potential impacts in a neutral manner. We feel
that this approach is more robust than the process of professional judgment applied as
part of the draft Airport Transit Plan, at least for measures where there are readily
quantifiable benefits (for example, the Old Town shuttle which would offer trip time
benefits for users compared to current transit alternatives). Based on our modeling
results, we feel that the assessment of mode shares obtainable as reported in the draft
transit plan may be overly optimistic. We find that the increased mode share attributable
to the introduction of an Old Town shuttle bus service would be in the order of 0.2
percent rather than the 1.0 percent anticipated by the transit plan. We do note, however,
that the ridership of the shuttle service would be dependent on a host of factors –
including service frequency and marketing, for which only crude assumptions are made
in the present modeling.

Another indication that the anticipated mode shares in the transit plan may be overly
optimistic is the forecast increase in mode share of 1.0 percent attributable to evening and
weekend Coaster services. Our model assumes that the transit alternative would be
available whenever passengers would wish to use the service, which in the case of the
Coaster service is overly optimistic given that the last weekday service currently arrives
at Santa Fe at 6:35 PM, there are only limited Saturday services and no Sunday services.
Nevertheless, our model predicts only a 0.5 percent mode share by Coaster under this
best-case scenario, significantly less than the 1.0 percent predicted in the transit plan.

Our analysis suggests that comparatively minor changes in transit services, such as a
shuttle bus service from Old Town Transit Center, would tend to attract only limited
numbers of users. This is primarily because there would be only minor trip time benefits
to users, and even then this benefit would apply only to those for which transit is a viable
option. Furthermore, the Old Town Transit Center as it is currently configured is poorly
marked as a transit interchange for car drivers on Pacific Highway and the I-5, and there
is no provision for long-term parking. Although there is adequate parking capacity for

                                          San Diego International Airport Expansion: Sustainability Analysis
 2-20
                                                                                  Chapter 2
                                                                     Transportation Analysis

current use, it is not clear whether sufficient long-term parking could be allocated to
upgrade the Old Town Transit Center to a fully fledged airport park & ride site. The
built-up nature of the area would limit the ability to expand the site, and the need to
facilitate short-term commuter parking in addition to airport use would complicate site
management.

The number of passengers for whom public transit would be viable appears limited,
partly because of the dispersed nature of the San Diego region and limited number of
transit corridors (particularly with regard to the trolley system). In addition, trip times are
uncompetitive for many travelers compared to car travel. For the majority of travelers,
the total trip time by transit, accounting for access and waiting time as well as actual
travel time, would be significantly longer by transit than by car such that traffic
congestion, and hence delay, would need to increase very substantially (perhaps by 50
percent or more) for transit to become attractive. Nonetheless, assuming the trolley
system was extended to connect the Green and Orange lines to the proposed ITC,
modeling indicates that transit could account for 4.0 to 5.2 percent of the airport trips.
This may be higher if traffic congestion levels deteriorate very significantly, fuel prices
increase further than anticipated and enhancements to the transit system were
incorporated (such as proposed trolley extensions).

This increase in transit mode share from under 2 percent currently to up to 5.2 percent
would have a net effect of further decreasing total car VMT, but the impact would be
approximately an additional 2 percent VMT reduction because most of the trips that
would be attracted to transit would be relatively short trips. By contrast, the average
reduction in VMT of 7 percent accruing from moving the terminal closer to the I-5 would
make up the majority of the VMT savings.

While the trolley would account for much of the increase in transit ridership (providing
1,400-1,900 extra riders to the airport per day) the Coaster service is also likely to benefit
by receiving an additional 600-850 riders per day to the airport. This assumes that the
service would be extended to operate earlier on weekday mornings and later in evenings
as well as on weekends. The service frequency is assumed to remain unaltered, such that
during peak periods there are services approximately every half hour but outside this
period service frequency is reduced such that there are one to two hour gaps between
services. Infrequent service is likely to act as an impediment to consider using the
service for many travelers, especially air passengers who are concerned with missing
their flight connection. Should the Lindbergh ITC concept be developed further, there is
merit in considering the option of improving the service frequency to make the service
more attractive to airport travelers along the corridor. Significant infrastructure
investment may be required as part of this process, such as dual tracking sections to the
north of San Diego.



San Diego International Airport Expansion: Sustainability Analysis
                                                                                        2-21
Chapter 2
Transportation Analysis

The forecast trolley and Coaster level of transit share is somewhat low when compared to
some other airports in the U.S. with airport rail links, particularly in comparison to San
Francisco International Airport (SFO) and Oakland International Airport (OAK), which
both have transit shares between 6 and 7 percent (Leigh River Associates et al., 2002).
Part of this difference may arise from the higher population densities in the Bay Area as
well as a greater proportion of trips to the airports in these locations arising from routes
along the rail corridors. The location of these airports further from the downtown area (a
major attractor of trips) makes shared van, and particularly taxi, more expensive relative
to public transit. A similar relationship does not exist at SDIA, which is very close to
downtown and so the costs for these alternatives are not as high. For example, the transit
fare to the airport from downtown is $2.25 but the taxi fare is approximately $11. If a
group is traveling together the cost differences quickly reduce further. For many, the
additional $8-$9 may be considered reasonable for the ease of traveling with baggage,
fast trip and comfort of knowing the service will deliver them directly to the airport.

The transit mode shares for commuting trips in a number of U.S. cities is given in Table
2-3 (U.S. Census Data, 2000), and reflects the differences in transit usage across these
cities. San Diego has a low mode share compared to many other cities, particularly in
comparison to comparable airports with rail links examined in Appendix A. For
example, the San Diego transit share of 3.4 percent is substantially lower than the 9.5
percent of the Bay Area, approximately half that of Portland (OR), and three quarters of
that of Minneapolis-St. Paul (MN). This reflects a host of factors, including the
extensiveness of the transit systems, land use policies (such as transit-oriented
developments and population density) and local cultural factors. It is also lower than the
national average of 4.7 percent (U.S. Census Data, 2000). It does, however, lend support
to a lower predicted transit share to SDIA compared with a number of other airports.




                                          San Diego International Airport Expansion: Sustainability Analysis
 2-22
                                                                                        Chapter 2
                                                                           Transportation Analysis




  Table 2-3. Transit Mode Share for Commuting in Major U.S. Cities (U.S. Census
                                    Data, 2000)

                                           City                      Transit share (%)
                Atlanta (GA)                                                3.7

                Chicago (IL)                                               11.5

                Los Angeles – Riverside – Orange County (CA)                4.7

                Minneapolis – St. Paul (MN)                                 4.6

                New York – North New Jersey – Long Island                  24.9

                Phoenix (AZ)                                                2.0

                Pittsburgh (PA)                                             6.2

                Portland (OR)                                               5.7

                San Diego (CA)                                              3.4

                San Francisco – Oakland – San Jose (CA)                     9.5

                St. Louis (MO)                                              2.4



SDIA transit mode share of 4.0-5.2 percent with the Lindbergh ITC remains rather low
compared with other airports in the U.S. (described in Appendix A). The modeling
suggests that to raise it close to the levels of OAK and SFO (where transit shares are
above 6 percent) would require both substantial increases to car trip times and costs and
the presence of the Lindbergh ITC. For example, the Lindbergh ITC with the additional
measures defined in the Airport Transit Plan, optimistic mode constant assumption for
rail as well as a 50 percent increase in car trip times and doubling of perceived car
operating costs would be required to achieve a transit mode share of 6.4 percent. There
are, however, other less quantifiable changes that may make these predictions overly
conservative. For example, attitudes towards environmental issues as well as
increasingly stringent legislation may lead to greater interest in using non-car access
modes. Further, effective marketing and branding campaigns may serve to increase
awareness of the transit services and in combination with wider environmental awareness
may serve to drive up the transit mode shares. Incentives can be negative, for example,
parking rates that include offset carbon emission sequestration costs.

As stated previously, many of the measures proposed as part of the draft Airport Transit
Plan would be equally applicable should the Lindbergh ITC concept be adopted. Given
the improvements in transit accessibility provided by the ITC, it is possible that many



San Diego International Airport Expansion: Sustainability Analysis
                                                                                            2-23
Chapter 2
Transportation Analysis

measures – such as improved marketing – would have an even greater effect than for the
current transit services.

2.4.1.2.   Transit Capacity
Other than parking constraints at certain trolley stations, it is probable that the existing
trolley and Coaster services could absorb a great deal of additional ridership without
crowding becoming a major concern or requiring additional services. However, should
additional services be desired, either to meet additional demand or to improve service
quality, then there exists the opportunity to do so on the Trolley network without
significant additional infrastructure. The Coaster service is more constrained by the
presence of large sections of single track north of San Diego and the need to share this
track with freight and Amtrak services. Should the proposed California High-Speed Rail
Link be implemented, it may be feasible to consider dual tracking the low speed track as
part of this project (or even independently of it).

The trolley network currently operates with excess capacity across much of the day, the
most congested part of the network being the Blue line south of downtown. The current
maximum service frequency is 10 vehicles/hour/direction during peak periods (equivalent
to approximately 640 seats in total plus room for 860 standing). Total loadings across the
day past Middletown were approximately 6,500 riders in each direction. Assuming that
peak period loadings are approximately 2.5 times the daily average, then peak hour
loadings would be approximately 1,000 riders in each direction. Although this implies
standing room only in peak periods, up to an additional 875 riders (1,850 individual trips)
from the Lindbergh ITC would be expected to be able to be accommodated assuming that
less than 500 of these riders travel during the peak hours. This is inline with the
maximum forecast increase in trolley ridership of 1,900 riders per day forecast for the
Lindbergh ITC scenario with optimistic assumptions. Should demands necessitate it,
additional services up to 30 vehicles/hour/direction, could potentially be handled, which
would serve to increase the level of service through reduced trip times and further
enhance demand.

Not included in this study were analyses of potential additional transit benefits that may
arise from the opening of the Sprinter light rail service connecting Escondido to
Oceanside. This service will provide a rail connection through the Coaster service at
Oceanside to the proposed ITC and the proposed FlyAway service from Escondido
Transit Center. Given the distance of this corridor from the airport, and the need to
connect onto the (currently) infrequent Coaster rail service, it is not anticipated that the
Sprinter would contribute significant additional transit share for airport trips.

The Mid-Coast Corridor Transit Project is another proposed transit improved not
incorporated into the analysis. This would provide an 11-mile extension to the trolley
system from Old Town Transit Center to University City. Should such an approach be

                                           San Diego International Airport Expansion: Sustainability Analysis
 2-24
                                                                                  Chapter 2
                                                                     Transportation Analysis

developed, this may be expected to provide additional direct services from this corridor to
the ITC. This latter project may well further enhance the attractiveness of transit in this
corridor and further improve the airport transit mode share, which would otherwise
require a bus service and connection onto the trolley system. We have not quantified
how substantial the additional ridership may be.

2.4.2.      Vehicle Miles Traveled (VMT)
Table 2-4a shows the daily average VMT among the five scenarios with conservative
assumptions while Table 2-4b shows the change in daily average VMT with optimistic
assumptions. These tables show the differences in both miles and percent for the
scenarios in comparison to the 2005 Baseline, the No Project Alternative at 2030, and the
Preferred Alternative. These values reflect the effect of travel times, costs and other
factors on a traveler’s transportation decision. The DEIR No Project Alternative at 2030
(Scenario 2) indicates increased demand for air travel would result in an additional
685,000 miles driven to or from SDIA per day (or 250.2 million VMT annually). This
represents a 57 percent increase in daily average VMT traveled by airport passengers and
workers over the 2005 Baseline. The Preferred Alternative with Airport Transit Plan at
2030 (Scenario 4) reduced VMT only marginally compared with a no project alternative
in that daily average VMT were reduced by only 30,000 miles per day, or just over one
percent, compared to the No Project Alternative at 2030 (Scenario 2).

The Lindbergh ITC would reduce daily average VMT by approximately 169,000 miles
and 139,000 miles per day compared to the No Project Alternative at 2030 (Scenario 2)
and the Preferred Alternative with Airport Transit Plan at 2030 (Scenario 4), respectively.
This represents a savings in annual VMT for the ITC compared to the No Project and
Preferred Alternatives of 61.7 million and 50.7 million miles, respectively. However,
even with alternative transportation choices available associated with the Lindbergh ITC
scenarios, average daily VMT was projected to increase by 516,000 miles (43 percent)
over the 2005 Baseline.




San Diego International Airport Expansion: Sustainability Analysis
                                                                                      2-25
Chapter 2
Transportation Analysis



 Table 2-4a. Change in Average Daily Vehicle Miles Traveled (VMT) Per Day Basis
                   by Scenario – Conservative Assumptions

    Scenario Modeled         Daily Ave.     Daily Ave. VMT            Daily Ave. VMT           Daily Ave. VMT
                               VMT              Change                    Change                 Change from
                                          from 2005 Baseline        from No Project @        Preferred Alternative
                                                                    2030 and Preferred        @ 2030 w Airport
                                                                    Alternative @ 2030           Transit Plan

                                           Miles         Perce       Miles      Percent       Miles      Percent
                                                          nt

 2005 Baseline               1,204,040       ---                                   ---          ---         ---
 No Project Alternative
 @ 2030                      1,889,503    +685,463       +56.9        ---          ---          ---         ---
 Preferred Alternative @
 2030                        1,889,503    +685,463       +56.9        ---          ---          ---         ---

 Preferred Alternative       1,859,146    +655,106       +54.4      -30,357       -1.6          ---         ---
 with Airport Transit Plan
 @ 2030

 Lindbergh ITC @ 2030        1,720,364    +516,324       +42.9     -169,139       -9.0      -138,782        -7.5
Source: SKM/Pirnie

 Table 2-4b. Change in Average Daily Vehicle Miles Traveled (VMT) Per Day Basis
                      by Scenario - Optimistic Assumptions


    Scenario Modeled         Daily Ave.     Daily Ave. VMT            Daily Ave. VMT           Daily Ave. VMT
                               VMT              Change                    Change                 Change from
                                          from 2005 Baseline        from No Project @        Preferred Alternative
                                                                           2030               @ 2030 w Airport
                                                                                                 Transit Plan

                                           Miles         Perce       Miles      Percent       Miles      Percent
                                                          nt

 2005 Baseline               1,204,040       ---                                   ---          ---         ---

 No Project Alternative      1,884,994    +680,954       +56.6        ---          ---          ---         ---
 @ 2030

 Preferred Alternative @     1,884,994    +680,954       +56.6        ---          ---          ---         ---
 2030

 Preferred Alternative       1,848,733    +644,693       +53.5      -36,261       -1.9          ---         ---
 with Airport Transit Plan
 @ 2030

 Lindbergh ITC @ 2030        1,700,861    +496,821       +41.3     -184,133       -9.8      -147,872        -8.0
Source: SKM/Pirnie




                                                     San Diego International Airport Expansion: Sustainability Analysis
  2-26
                                                                                  Chapter 2
                                                                     Transportation Analysis

The reduction in daily average VMT achieved with the ITC is partly as a result of
increased transit mode share but also because total trip distances for many trips are
reduced as a result of more direct road access to the terminal. Average car trip distances
would reduce from 19.1 to 17.8 miles (a reduction of 7 percent) with the relocation of the
terminal to the north side of the airfield. This reduction in trip length would make up the
majority of the VMT savings achieved. As shown in Table 2-4a and Table 2-4b an
additional 2-3 percent VMT saving would be achieved through the increase in transit
usage over and above that achieved through trip length reductions achieved due to the
closer proximity of the ITC to the road network.

The VMT reductions with the ITC compared to the non-ITC scenarios are significant,
reducing VMT by over 147,000 miles per day compared to the Preferred Alternative with
Airport Transit Plan (Scenario 4). To put these reductions in context the following
potential policy changes, in VMT, were modeled under scenarios 2 (No Project
Alternative @ 2030).

     If transit fares were reduced to zero, then VMT would decrease by 7,559 miles (0.4
     percent). .
     If the perceived cost of car driving were to double, then daily average VMT would
     decrease by 7,077 miles (0.4 percent).
     If road trip times (car, taxi, bus) increased by 50 percent, then VMT would decrease
     by 35,791 miles (1.9 percent).
Again, in contrast to the above 0.4 to 1.9 percent reductions, the Lindbergh ITC
reductions in VMT are approximately 10 percent. Consequently, the important
implication is that increasing the accessibility of the airport by transit, through step
changes such as proposed by the ITC would be essential to achieving substantial
reductions in daily average VMT. Furthermore, once the ITC were in place other effects
– such as increasing car costs or trip times would all have a much greater positive effect
on transit demand because the transit alternative would be more attractive (although, to
an extent, so too would be car alternative given the improved road connections). The
Lindbergh ITC alternative could contribute to an increase in airport operational
efficiency, and hence sustainability, by providing incentives for taking public transit, for
example, show your receipts and go to the head of the check in and security lines.
2.4.3.      Level of Service
The impact of changes in daily average VMT on traffic congestion in the vicinity of
SDIA was evaluated as part of the modeling. Airport related traffic is currently a
substantial percentage of the total traffic on downtown streets – ranging from 40 percent
to 76 percent of total traffic on Grape Street, Hawthorn Street and Laurel Street (Figure
2-2). Presently, traffic on many streets in the vicinity of the airport currently operates at
and beyond desirable levels of service (Figure 2-10).



San Diego International Airport Expansion: Sustainability Analysis
                                                                                        2-27
Chapter 2
Transportation Analysis

In order to examine the potential benefits of the Lindbergh ITC concept on traffic route
assignment, assumptions were required with regard to the routes travelers used from their
origins to the airport. This decision would be based on travel time but also more difficult
to quantify factors such as reliability, pleasantness of the route and traveler knowledge
and experience.

Route Assignment: For many car trips travelers may have several routes available with
which to make their trip. For the purposes of the present analysis the most obvious route
(based on trip time) was assigned from each zone to the airport, involving primarily
major roads.

Volume Correction: In order to ensure consistency with the DEIR forecasts, the
SDCRAA Preferred Alternative was used to apply a correction factor to the link flows
following the manual assignment procedure. This resulted in adjustments of
approximately +/-20 percent to each link. In this way comparison could be made directly
with the DEIR.

2.4.3.1.    Traffic Analysis – Road Network Level of Service for Scenario 3 (DEIR
            Preferred Alternative)
Traffic circulation through the existing airport is limited by the location of the airport
away from I-5. As a result much of the traffic accessing the airport must travel through
downtown streets (particularly Hawthorn Street coming inbound and Grape Street
outbound) and arterials with a largely retail, light industrial and residential nature such as
Rosecrans Street (Figure 2-10). 4 This has detrimental impacts on traffic congestion,
access to local businesses, local air quality, greenhouse gas emissions and urban amenity.

The DEIR undertook detailed analyses of the traffic conditions currently and forecast to
occur with the master plan. As part of that analysis it was determined that a number of
streets in the vicinity of the airport were currently operating at and beyond desirable
levels of service. As shown in Figure 2-2 this includes a number of streets where airport-
related traffic constitutes a substantial component of the total. Such streets include Grape
Street, Hawthorn Street and India Street. Forecasts developed for the DEIR, shown in
Figure 2-11, suggest that the number of road links operating above capacity will increase
in the future as a result of airport-related traffic growth as well as background traffic
growth. Major airport access roads, such as North Harbor Drive, Grape and Hawthorn
Streets would all be severely congested in these forecasts.




4
 Non-airport related traffic on Rosecrans Street were incorrect in the DEIR. In order to correct for this
error traffic volumes from Series 11 of the Regional Transportation Model were used in 2030 for this link.
The non-airport traffic on other links remained consistent with the DEIR and are Series 10 forecasts.

                                                 San Diego International Airport Expansion: Sustainability Analysis
    2-28
                                                                                    Chapter 2
                                                                       Transportation Analysis




                                                                     Figure 2-10. Traffic Level of
                                                                     Service for surface streets in the
                                                                     vicinity of SDIA for Scenario 1 –
                                                                     2005 Baseline. (Note, this figure
                                                                     is the same as Figure 2-3.)




                                                                     Figure 2-11. Traffic Level of Service
                                                                     for surface streets in the vicinity of
                                                                     SDIA for Scenario 4 – Preferred
                                                                     Alternative with Airport Transit Plan in
                                                                     2030.




                                                                     Figure 2-12. Traffic Level for surface
                                                                     streets in the vicinity of SDIA for
                                                                     Scenario 5 – Lindberg ITC in 2030.




San Diego International Airport Expansion: Sustainability Analysis
                                                                                            2-29
Chapter 2
Transportation Analysis

2.4.3.2.    Traffic Analysis – Road Network Level of Service for Scenario 5
            (Lindbergh ITC)
The traffic volumes on major approach roads will differ with the proposed ITC both as a
result of travelers choosing other modes (for example, trolley) and as a result of re-
routing due to changes in road access. The levels of service on the road network with the
ITC (Scenario 5) is presented in Figure 2-12. The most significant effect on traffic
volumes and improvements in LOS is due to re-routing of traffic away from streets such
as Rosecrans, Laurel and Hawthorn Streets with Scenario 5. The level of service on
Rosecrans and Laurel Streets would reduce to acceptable levels with the Lindbergh ITC
in place. A number of other streets, particularly Hawthorn Street, would see
improvement on particular segments but background traffic growth would mean that
traffic flow on this street would remain congested. Improvements are also seen on a
number of other streets, particularly on India, Kettner, Grape, Washington, and Hancock.

Alternatives that would continue to require traffic to use the current access routes to the
airport terminals, as well as only having minor impacts on transit mode shares, would not
significantly alleviate traffic congestion on the road network. The Preferred Alternative
with Airport Transit Plan, while reducing overall VMT by 1.6-1.9 percent would not
significantly affect traffic volumes on the local road network. In order to alleviate traffic
congestion along the routes, the types of measures discussed in the DEIR would be
required – namely providing additional lane capacity and enhancements to signal timing.
These mitigation measures would require additional land and have only minimal impacts
on emission levels.

In summary, the projected increase in demand for airport travel results in approximately
681,000 additional average daily VMT from airport related ground transportation. Both
the No Project Alternative at 2030 (Scenario 2) and the Preferred Alternative at 2030
(Scenario 3; Figure 2-11), would result in significant additional traffic congestion and
further decline in the level of service on many streets in the vicinity of the airport. In
contrast, the transport mode choice model predicts significant improvements in traffic
volume and congestion in the vicinity of SDIA as a result of the Lindbergh ITC despite
the projected increase of 497,000 average daily VMT (Figure 2-12).

2.4.4.     Impact of Assumptions
The assumption that trip times and costs by car will not alter in the future is conservative
in so far as it is likely that both will increase in the long run compared with present
values. In the case of trip times this is particularly likely given that traffic growth is
likely to continue to outstrip road capacity growth (achieved both through improved road
operation and new construction). However, quantifying exactly how much trip times
would increase is particularly difficult. Trip times tend to increase in a highly nonlinear
manner as roads become increasingly congested. The rate of increase in trip times
depend to a significant extent on detailed road conditions such as at intersections and the

                                           San Diego International Airport Expansion: Sustainability Analysis
 2-30
                                                                                  Chapter 2
                                                                     Transportation Analysis

extent of weaving in traffic. Furthermore, trip times are likely to increase more on the
most congested links than on less congested links.

Sensitivity tests were performed to examine the impact of this critical assumption, in
addition to assumptions such as future fuel prices. These tests indicated that transit mode
shares would increase in the order of 1-2 percent. The impact on traffic congestion would
be small as a result of this comparatively small reduction in road traffic.

The model is most sensitive to travel times – particularly for air passengers. To a large
extent these would be outside the control of the airport authority. However, alternative
policies the airport authority could consider to increase the transit share include pricing
incentives. To test the impact such incentives may have a scenario was tested using the
Lindbergh ITC proposal (Scenario 5) and optimistic assumptions about rail usage. This
scenario differed by the following package of measures:

    Incentivize the use of transit by providing free travel for both air passengers and
    airport employees

    Discourage parking by quadrupling parking charges, both on and off-airport for all
    passengers and airport employees. It is assumed that the charges for non-SDCRAA
    off-airport car parking would also quadruple.

    Introduce a $10 charge for car trips made to the airport to drop off passengers (i.e. kiss
    and fly). One way this could be implemented would be to apply the charge to private
    vehicles that drive along the terminal forecourt. It is assumed that the minimum
    parking charge would increase to match this amount (to prevent kiss & fly travelers
    from using the car park for drop-off). Such a charge is particularly effective on
    overall VMT because each kiss & fly movement generates twice as many miles
    traveled as self-drive or taking a taxi.

The results of this scenario increased the transit share from 5.2 to 8.2 percent using the
optimistic assumptions. A total VMT reduction of 17.7 percent would be achieved in this
scenario, around double the 9.8 percent achievable through the introduction of the ITC
and extended transit systems alone.

If, in addition to the above scenarios, background traffic congestion levels were to
increase such that car trip times would increase by 50 percent, the transit share would
increase to 9.5 percent, and VMT would decrease by 20.0 percent compared to the No
Project 2030 baseline (Scenario 2).

Another transit service improvement strategy may be to double the service frequencies.
If this were done on all services (trolley, bus and Coaster and Amtrak) then the transit



San Diego International Airport Expansion: Sustainability Analysis
                                                                                          2-31
Chapter 2
Transportation Analysis

share would increase to 11.2 percent. VMT would decrease by 21.4 percent compared
with the No Project 2030 baseline scenario.

2.4.5.   Equity and Wider Sustainability Benefits
The development of the Lindbergh ITC makes public transit options more attractive
which benefits lower paid airport employees thereby contributing to the social equity
component of sustainability. A consolidated ITC potentially enhances security and safety
because it isolates all of its components from the adjacent uncontrolled streets. Enhanced
safety would be perceived by airport passengers using the consolidated parking and rental
car facilities, and riders of public transit that would move through the ITC. The
consolidation of transit types at the ITC would also enhance the effectiveness of any
future public transit expansions in the area and would also enhance their ridership.




                                         San Diego International Airport Expansion: Sustainability Analysis
 2-32
                  3.        Greenhouse Gas and Criteria Pollutant
                                                      Emissions

This chapter addresses greenhouse gas emissions and criteria pollutant emissions for
airport-related ground transportation for the scenarios modeled in Chapter 2. Section 3.1
addresses greenhouse gases while Section 3.2 addresses criteria pollutant emissions. This
chapter does not address greenhouse gas emissions associated with aircraft use as they
fall under federal jurisdiction.

3.1. Greenhouse Gases
3.1.1.      Background
Currently, the most prominent regulatory driver relative to SDIA, is the State of
California ‘AB 32 Global Warming Solutions Act’ of 2006. This law requires a
reduction in California greenhouse gas emissions to 1990 levels by 2020 (an estimated 25
percent reduction). Mandatory greenhouse gas caps will begin in 2012 and the California
Energy Commission and Air Resources Board (CARB) are currently developing and
releasing specific regulations. At present the above regulations do not address
transportation. Transportation accounted for 32.4 percent of greenhouse gas emissions in
the State of California in 2004 (not including the contribution to greenhouse gases from
airplanes themselves) (CEC, 2006). In addition, the Governor’s Executive Order S-3-05
mandates a reduction of greenhouse gas emissions to 80 percent below 1990 levels by
2050.

California also passed AB 1493 in 2002 requiring a 30 percent reduction in greenhouse
gas emissions from new motor vehicles by 2016. The law would require automakers to
improve fuel economy by an estimated 38 percent, to an average 35 mpg. This law was
challenged in the courts and has not been implemented to date. A federal judge
dismissed the blocking lawsuit in early December 2007 but implementation still required
a waiver from the U.S. Environmental Protection Agency (EPA). EPA denied the
California waiver request on December 19. They denied the waiver because Congress
passed and the President signed a bill that increases the federal Corporate Average Fuel
Economy (CAFE) standard to 35 miles per gallon by the year 2020, and the EPA
considers this adequate. California and several other states disagree and sued the EPA on
this matter so it will take additional time to fully resolve.

There are several other examples of the developing response to global change at the
national level. In April 2007, the U.S. Supreme Court ruled that greenhouse gases should
be regulated as an air pollutant under the federal Clean Air Act. EPA is currently
reviewing the implication of this decision and the need for additional regulations beyond

San Diego International Airport Expansion: Sustainability Analysis
                                                                                    3-1
Chapter 3
Greenhouse Gas and Criteria Pollutant Emissions

the new CAFE standards. In addition, both Houses of Congress are considering
numerous bills that would regulate greenhouse emissions in some manner. These bills
may or may not be signed into law in the next year but the discussion strongly suggests
that some form of federal greenhouse gas regulation beyond the CAFE standards may be
possible within the foreseeable future.

At the international level, the primary driver is the United Nations International
Framework Convention on Climate Change. The first phase of this Framework is the
Kyoto Protocol which is currently being implemented by many industrial nations
although the treaty was not ratified by the U.S. The second phase of the Framework was
addressed by an international meeting in Bali in December 2007. Although the final Bali
Pact or road map does not include hard targets for greenhouse gas reductions, it does
require agreement by 2009 for a treaty pushing for deep cuts in greenhouse gas emissions
as well as actions to mitigate climate change in a measurable, reportable and verifiable
manner. The U.S. is a signatory to this pact which may further accelerate actions to
reduce greenhouse gas emissions within the country.

3.1.2.   Methods
The combustion of gasoline and diesel fuels in motor vehicles results in the emission of
several pollutants. Included among a vehicle’s emissions are three greenhouse gases:
carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). The concentration of
these and other greenhouse gases in the atmosphere is directly related to global
temperatures. According to the CARB, more than half of the fossil fuel emissions of CO2
in California are related in some way to transportation.

Greenhouse gas emissions were calculated for each of the five scenarios described in
Section 2.3.2 of this report. These calculations are based on emissions from gasoline-
powered cars and vans and compressed natural gas (CNG) buses used to transport
passengers to and from SDIA. Airport deliveries and airport ground support equipment
were not included in the calculations as they are not directly affected by the alternatives
considered. In addition, the change in emissions from decreased use of the electric
trolley in Scenario 5 (Lindbergh ITC) is insignificant compared to vehicle emissions, and
therefore it was excluded from the calculations. The estimated change in greenhouse gas
emissions from the trolley is detailed in Appendix C. No change in emissions is
anticipated from commuter trains since they have sufficient capacity under existing
routes and schedules to handle the expected increase in riders.

Although CO2 is the primary source of greenhouse gases from vehicles, these
calculations also considered emissions of CH4 and N2O. Emissions of
hydrofluorocarbons (HFCs), which are another type of greenhouse gas, were not
considered because they are related to air conditioning systems and not fuel combustion.
HFCs may be released from vehicle air conditioning systems during servicing, when the

                                          San Diego International Airport Expansion: Sustainability Analysis
  3-2
                                                                                           Chapter 3
                                                     Greenhouse Gas and Criteria Pollutant Emissions

vehicle is scrapped, or during normal operation if there is a leak. HFCs are used as a
substitute for ozone depleting substances which are being phased out. Since each
greenhouse gas has a different potential to influence global warming, the total greenhouse
gas emissions are reported in the standard units of metric tons of carbon dioxide
equivalent (CO2e).

To better illustrate these terms, a typical car with 22.9 average miles per gallon generates
one metric ton of CO2e in approximately 2,600 miles. Approximately 97 percent of the
potential impact to global warming from the typical car comes from carbon dioxide
emissions; whereas nitrous oxide contributes approximately 3 percent and methane
contributes a fractional amount. If the average car is driven 12,000 miles per year, then
4.6 metric tons CO2e would be generated. The actual emissions of CO2e will depend on
the vehicle type and fuel burned, as well as the individual make and model. Larger
vehicles such as trucks and vans usually have lower fuel economy and generate more
greenhouse gases.

The greenhouse gas calculations used in this report are shown below, and the
assumptions are listed in Appendix C. All results are shown on a per day basis.

                   CO2 = vehicle miles traveled / fuel economy *emission factor
                                (CO2 / gallon) * conversion factor

                CH4 (in CO2 equivalents) = vehicle miles traveled * emission factor
                    (CH4 / mile) * conversion factor * global warming potential

               N2O (in CO2 equivalents) = vehicle miles traveled * emission factor
                   (N2O / mile) * conversion factor * global warming potential



The calculations and most of the assumptions are taken from the California Climate
Action Registry General Reporting Protocol. The results are based on the aggregate
number of vehicle miles traveled. Distinctions between city and highway driving speeds
and potential emissions decreases due to the greater use of alternative fuels were not
considered.

In particular, the calculation of CO2 emissions is based largely on a vehicle’s fuel
economy, or miles per gallon. In December 2007, Congress passed, and the President
signed, a bill that increases the Corporate Average Fuel Economy (CAFE) standard to
35 miles per gallon (mpg) by the year 2020. Overall, fuel economy is expected to
increase in the coming decades, but the 35 mpg CAFE standard does not reflect the actual
fuel economy in a given year. This is because the CAFE standard is applicable to an
automobile manufacturer’s current model year. It does not reflect the mix of older and
newer cars on the road or other key factors. The calculations reflected in Table 3-1 are


San Diego International Airport Expansion: Sustainability Analysis
                                                                                               3-3
Chapter 3
Greenhouse Gas and Criteria Pollutant Emissions

based on the assumptions in Appendix C that a certain percentage of the CAFE standard
will be met in the 2030 scenarios.

Although it may be assumed that cars will have higher fuel economy in the future, that
increase in fuel economy would apply to all the 2030 scenarios. Thus, these results
should be viewed from a comparative standpoint, and not necessarily from a quantitative
standpoint. The use of different emission factors, assumptions, or models would yield
different results, but the overall relative trends would not change.

3.1.3.      Results
The results of the approach described above and detailed in Appendix C are summarized
in Table 3-1. Figure 3-1 graphically displays the total greenhouse gas emissions for the
five scenarios that were modeled.

      Table 3-1.Change in Average Daily Greenhouse Gas Emissions by Scenario

                                                                                                      Change from
                                                Change from 2005           Change from No               Preferred
                                     Daily          Baseline              Project @ 2030 and         Alternative with
                                     Metric                                    Preferred           Airport Transit Plan
        Scenario Modeled             Tons                                 Alternative @ 2030             @ 2030
                                     CO2e
                                                Metric       Percent       Metric      Percent      Metric     Percent
                                                Tons                       Tons                     Tons

  1      2005 Baseline                479         ---            ---         ---          ---         ---          ---

  2      No Project Alternative       587        +108         +22.5          ---          ---         ---          ---
         @ 2030

  3      Preferred Alternative @      587        +108         +22.5          0            0           ---          ---
         2030

  4      Preferred Alternative        582        +103         +21.5          -5          -0.9         ---          ---
         with Airport Transit Plan
         @ 2030

  5      Lindbergh ITC @ 2030         533        +54          +11.3         -54          -9.2         -49         -8.4

Source: Malcolm Pirnie/SKM data and assumptions in Appendix C.


Table 3-1 and Figure 3-1 show that by 2030, the emissions of CO2e from vehicle travel to
and from SDIA is expected to increase by approximately 23 percent, or from 479 to 587
metric tons CO2e (108 metric tons per day which is equivalent to 39,420 metric tons per
year), if no changes to the airport are made (i.e., Scenario 1 (2005 Baseline) compared to
Scenario 2 (No Project Alternative @ 2030). This significant increase is attributed to the
increase in transit demand. The new CAFE standards provide a reduction in future
emission (23 percent increase in emissions compared to 57 percent increase in average



                                                    San Diego International Airport Expansion: Sustainability Analysis
  3-4
                                                                                                              Chapter 3
                                                                        Greenhouse Gas and Criteria Pollutant Emissions

daily VMT). However, they do not provide sufficient reductions to maintain, let alone
reduce, CO2e emissions.

The estimated greenhouse gas emissions from Scenario 3 (Preferred Alternative @ 2030)
are equivalent to Scenario 2 (No Project Alternative @ 2030). Based on the assumptions
outlined in Appendix C, Scenario 4 (Preferred Alternative with Airport Transit Plan @
2030) would achieve less than a 1 percent reduction in greenhouse gases. Thus, the
Scenario 4 does little to reduce emissions. The 9 percent reduction of greenhouse gases
with the Lindbergh ITC (Scenario 5; Table 3-1) is a significant improvement compared to
the Scenario 4. The increased use of public transportation and reduction in VMT under
Scenario 5 (Lindbergh ITC) would result in greenhouse gas emissions of 533 metric tons
CO2e by 2030. This represents an 11 percent increase from the 2005 Baseline and a
reduction of 9 percent when compared to Scenarios 2 and 3. However, this increase is 50
percent lower than the increase projected for Scenario 2 (No Project Alternative @ 2030).


   Figure 3-1: Greenhouse Gas Emissions on a Per Day Basis by Scenario

                               700
    Metric tons CO2e per day




                               600
                               500
                               400
                               300
                               200
                               100
                                0
                                     Scenario 1 (2005     Scenario 2 (No       Scenario 3       Scenario 4          Scenario 5
                                        Baseline)       Project Alternative    (Preferred       (Preferred      (Lindbergh ITC @
                                                             @ 2030)          Alternative @   Alternative w           2030)
                                                                                  2030)       Airport Transit
                                                                                               Plan @ 2030)




None of the proposed alternatives (Scenarios 3, 4, or 5) would reduce greenhouse gas
emissions to the 2005 baseline or to CARB’s goal of 1990 levels because of projected
population and traffic growth. The City of San Diego has developed a greenhouse gas
inventory for 1990 and 2004 (City of San Diego, No Date). The transportation sector in
San Diego was reported to contribute 7,864,800 greenhouse gas tons per year
(approximately 21,547 greenhouse tons per day) in 2004. This represented 52 percent of
the community’s total greenhouse gas emissions. Both past (1990 to 2004) and predicted
(2005 to 2030) data indicates that the increase in fuel economy in vehicles has not and
will not be adequate to keep up with the greenhouse gas emissions from increased VMT

San Diego International Airport Expansion: Sustainability Analysis
                                                                                                                             3-5
Chapter 3
Greenhouse Gas and Criteria Pollutant Emissions

unless new policies, transportation alternatives, or behaviors are developed. Absent such
dramatic change, the Lindbergh ITC provided the most benefits of the scenarios
evaluated. However, the ITC was insufficient by itself to make sufficient reductions in
VMT to reach even short-term goals for greenhouse gas reductions if goals were
uniformly applied across each segment of society. Even so, the estimated 8 percent
reduction of greenhouse gas emissions with the Lindbergh ITC (Scenario 5) could form
an important component of an overall plan to decrease greenhouse emissions associated
with the SDIA. Additionally, by providing a more robust public transit system the
Lindbergh ITC could also contribute to other regional initiatives.

3.2. Criteria Pollutant Emissions from Airport-Related Ground
     Transportation
Criteria pollutant emissions under the Clean Air Act are one of the several sustainability
components associated with a change in transit mode share across the five scenarios
discussed in Chapter 2. This section briefly considers one segment of criteria pollutant
emissions – the potential for change in emissions from airport-related ground
transportation. Specifically, this report compares the change in relative emissions
estimated for passenger vehicles for the five transport analysis scenarios described in
Chapter 2 and Appendix B. The screening-level nature of this comparison is not intended
to represent a complete air quality analysis of direct and indirect emissions from
demolition, construction or operational phases of the various scenarios. Nevertheless, the
comparison does offer an indication of the potential effect of proposed changes in transit
mode share on criteria pollutant emissions generated by what is described as “motor
vehicles (off-airport)” in Section 5.5 of the DEIR.

3.2.1.    Background
As noted in Section 5.5 of the DEIR, the EPA and CARB have set ambient air quality
standards (NAAQS/CAAQS) to protect public health and the environment from the
harmful impacts of air pollution. 1 The standards apply to a subset of possible air
contaminants called “criteria pollutants”. Criteria pollutants include: carbon monoxide
(CO), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), particulate matter (less
than 10 microns and less than 2.5 microns), and lead (Pb), among other state-listed
pollutants. CARB and the San Diego Air Pollution Control District (SDAPCD) monitor
emissions of these pollutants in San Diego County, forecast emissions, establish an
emissions budget, and develop implementation plans for attaining compliance with the
standards where a pollutant exceeds the federal or state limit.

Current attainment/non-attainment status for all criteria pollutants in San Diego County is
described in Section 5.5.2.4 of the DEIR. Table 3-2 below shows the County’s

1
 See CARB website for current federal and state ambient air quality standards at:
http://www.arb.ca.gov/research/aaqs/aaqs2.pdf, accessed December 2007.

                                                 San Diego International Airport Expansion: Sustainability Analysis
    3-6
                                                                                           Chapter 3
                                                     Greenhouse Gas and Criteria Pollutant Emissions

attainment status for those criteria pollutants considered in this screening-level
evaluation. 2 This table indicates that San Diego County is addressing maintenance or
non-attainment status for CO, O3, and PM. Although this report does not specifically
address conformity with federal or state requirements, opportunities for emissions
reduction or offset for these pollutants are potentially beneficial to the airshed.

               Table 3-2. Current Designation for Selected Criteria Pollutants
       Criteria              San Diego County Status                  Criteria     San Diego County Status
      Pollutant                   (Federal/State)                    Pollutant          (Federal/State)
         CO                   Maintenance/Attainment                   SO2           Attainment/Attainment

         NO2                    Attainment/Attainment                  PM10            Unclassifiable/Non-
                                                                                           attainment
          O3              Non-attainment/Non-attainment               PM2.5           Non-attainment/Non-
                                                                                          attainment



3.2.2.      Methods
This comparison was developed by producing rough order of magnitude estimates of
criteria pollutant emissions for the six scenarios presented in Chapter 2 of this report.
The emissions estimates were developed using the daily vehicle miles traveled (VMT)
data produced for this report and generalized emission factors for on-road passenger
vehicles and individual criteria pollutants posted. 3 Generalized emission factors for the
SDAPCD were not readily available. Instead, conservative emission factors developed
for the South Coast Air Quality Management District’s (SCAQMD) CEQA Air Quality
Handbook were used to estimate emissions for CO, NO2, O3, SO2, PM10, and PM2.5. The
conservative emission factors were applied for a relative comparison between emissions,
not for an assessment of absolute values. Relative changes between scenarios were noted
as a percent reduction in total emissions from the Scenario 2 (No Project Alternative @
2030) and are presented in Section 3.2.3 below.

As noted above, SCAQMD emission factors for on-road passenger vehicles were utilized
for this screening-level evaluation for the pollutants in Table 3-2 (see also Appendix D,
Tables D-2 and D-3 of this report). The emission factors were developed using the
EMFAC2007 model (v2.3), as currently recommended by CARB. Use of the factors
offers one means for estimating mobile source emissions based on number of vehicle
trips and miles per trip. These variables can be combined to reflect daily vehicle miles




2
 See Section 3.2.2 below for information on the selection of criteria pollutants considered in this report.
3
 See SCAQMD website for emission factors for onroad vehicles produced through the EMFAC2007 at
http://aqmd.gov/CEQA/handbook/onroad/onroad.html.

San Diego International Airport Expansion: Sustainability Analysis
                                                                                                        3-7
Chapter 3
Greenhouse Gas and Criteria Pollutant Emissions

traveled or VMT. Consistent with standard practice, emission factors for Reactive
Organic Gases (ROG) and oxides of Nitrogen (NOx) are provided as O3 precursors. 4

Emission factors generated through the EMFAC2007 model take into account vehicle
classes, speed improvements over time, mix of vehicle models and model years, and
anticipated improvements in fuel economy. SCAQMD’s current web page for Emission
Factors for On-Road Passenger Vehicles & Delivery Trucks further explains:

          All the emission factors account for the emissions from start, running and
          idling exhaust. In addition, the ROG emission factors include diurnal, hot
          soak, running and resting emissions, and the PM10 & PM2.5 emission
          factors include tire and brake wear. 5

In addition, SCAQMD’s web page explains that the emission factors provided represent
the most conservative value generated for each criteria pollutant based on variations for
annual, summer, or winter emissions. The CAFE standards discussed in Section 3.1 are
incorporated in the generalized emission factors; however, the factors do not yet reflect
the recent 2020 rule 6 . Note, however, that improved fuel economy is not expected to
directly effect emissions of criteria pollutants from new vehicles. Federal and state laws
require each new vehicle to meet federal emission standards on a gram per mile basis
independent of fuel economy. 7 Some research suggests that as vehicle emissions control
systems age, there is a relationship between fuel economy and criteria pollutant
emissions. 8

Emissions from on-road vehicles were developed for this report using:

          Emissions (pounds per day) = VMT x EF

where VMT = daily vehicle miles traveled (number of trips x trip length) and EF =
emission factor (pounds per mile).

Daily VMT values used in this screening-level evaluation were obtained from the transit
data generated for this report for passenger cars for all six scenarios. The VMT data was
modified to reflect round trips. It is shown in Appendix D, Tables D-1 and D-4.

As noted above, the results of the screening-level evaluation were used to compare the
proposed Lindbergh ITC (Scenario 5) with Scenario 3 (Preferred Alternative). These


4
  Emissions estimates for these ozone precursors are used to develop the state and county ozone budgets.
5
  See http://www.aqmd.gov/CEQA/handbook/onroad/onroad.html, accessed December 2007.
6
  Air Resources Board, El Monte office, December 2007, personal contact.
7
  National Research Council, Board on Energy and Environmental Systems, 2002, and U.S. DOT, National
Highway Transportation Safety Administration, August, 2005.
8
  See footnote 7.

                                                San Diego International Airport Expansion: Sustainability Analysis
    3-8
                                                                                           Chapter 3
                                                     Greenhouse Gas and Criteria Pollutant Emissions

results are not intended to provide a determination of conformity with federal or state air
quality standards.

3.2.3.      Results and Discussion
Table 3-3 shows the relative changes in estimated emissions by criteria pollutant between
Scenario 1 (2005 Baseline) and Scenario 2 (No Project @ 2030). This table provides a
context for the comparison between the various ‘build-out’ scenarios in 2030. It shows
that emissions of some criteria pollutants from airport-related passenger vehicles can be
expected to decrease by 2030 (CO, NOx, and ROG), while emissions of SOx, PM10, and
PM2.5 can be expected to increase without any project. The declines result from federal
and state emission requirements. Calculations and assumptions are presented in
Appendix D, along with the individual emission factors by year for each pollutant.

  Table 3-3. Estimated Percent Change in Daily Criteria Pollutant Emissions from
    2005 to 2030 with No Infrastructure Pollutant Changes (Scenario 1 versus
                                   Scenario 2)
   Pollutant             CO               NOx                ROG                 SOx               PM10               PM2.5


  % Change,
   Scenario 1
                       -56%               -65%               -44%                56%               79%                91%
  to Scenario
       2

Source: Malcolm Pirnie/SKM. See Appendix D, Table D-1 for calculations by pollutant.


Table 3-4 below compares the percent reduction anticipated for criteria pollutant
emissions from airport-related ground transportation for Scenarios 3 to 5 and Scenario 2
(No Project Alternative @ 2030). These ‘build-out’ scenarios include the Lindbergh ITC
(Scenario 5), Scenario 3 (Preferred Alternative) and Scenario 4 (Preferred Alternative
with Airport Master Plan).

     Table 3-4. Estimated Percent Change in Daily Criteria Pollutant Emissions -
                                  Passenger Cars
       Scenario                    1                 2                  3                 4                  5
                                                                                    Preferred
                                               No Project
           Scenario            2005                             Preferred          Alternative           Lindbergh
                                               Alternative
            Name              Baseline                          Alternative         w Airport               ITC
                                                @ 2030
                                                                                   Master Plan
       Year                      2005              2030                2030              2030               2030
       Assumed
       average daily          1,132,440          1,769,337           1,769,337         1,735,523          1,596,914
       VMT
       % change
       from Scenario
                                                                      -0.0%             -1.9%              -9.7%
       2 (No Project
       Alt. @ 2030)

     Source: Malcolm Pirnie/SKM. See Appendix D, Table D-2 for calculations by pollutant.

San Diego International Airport Expansion: Sustainability Analysis
                                                                                                                       3-9
Chapter 3
Greenhouse Gas and Criteria Pollutant Emissions

The assumed VMT in Table 3-4 is based on round trips for the daily “to airport” vehicle
miles traveled in Chapter 2 and Appendix B of this report. The percent reduction in
estimated emissions is the same for all criteria pollutants considered. Emissions
reductions estimated for the Lindbergh ITC proposal (Scenario 5) are approximately 10
percent from the Scenario 2 (No project Alternative @ 2030). The estimated emissions
reduction for Scenario 4 (Preferred Alternative with Airport Master Plan) is 1.9 percent
for all criteria pollutants considered. The estimated percent reductions parallel what was
observed in the greenhouse gas emissions estimates performed separately and presented
in Section 3.1 of this report.

As noted above, changes in emissions between Scenario 1 (2005 Baseline) and Scenario
2 (No Project Alternative @ 2030) vary by pollutant. This means that the percentages
also reflect a further reduction from 2005 emissions for CO, NOx, and ROG. By
contrast, for SOx, PM10, and PM2.5, the percent change reflects a reduction in increased
emissions. For example, Scenario 5 reflects a 9.7 percent reduction from the Scenario 2
(No Project Alternative @ 2030) values, which already represents a substantial reduction
in CO, NOx, and ROG. The 9.7 percent change for the same scenario reflects a reduced
increase in emissions of SOx (46 percent), PM10 (69 percent), and PM2.5 (81 percent)
when compared to the percentages in Table 3-3. A small change in criteria pollutant
emissions would be anticipated from implementation of Scenario 4 (Preferred Alternative
with Airport Transit Plan).

In addition, the transit analysis presented in Chapter 2 indicates that VMT reductions
(and, therefore, related emissions) would decrease most significantly in the residential
neighborhoods and surface streets near the airport. From a qualitative perspective, the
distribution of reduced VMTs suggests that residential exposure to air contaminants
would also decrease in areas where VMTs are reduced. More detailed air quality
modeling should be considered to verify results and identify geographic sensitivities or
risks to public health.

In summary, this screening-level evaluation compares criteria pollutant emissions from
airport-related passenger vehicles for the various ‘build-out’ scenarios. An estimated 8
percent reduction in criteria pollutant emissions could be achieved by implementing the
Lindbergh ITC (Scenario 5) when compared to Scenario 2 (No Project Alternative @
2030). By contrast, the reduction in criteria pollutant emissions predicted for
implementation of Scenario 4 (Preferred Alternative with Airport Transit Plan) is 1.9
percent when compared to Scenario 2 (No Project Alternative @ 2030). The reductions
approximate the percentages estimated for greenhouse gas emissions from airport-related
ground transportation in presented in Section 4.1 of this chapter. Importantly, these
criteria pollutant reductions would occur in areas where VMTs are reduced most, i.e., in
residential and surface streets near the airport. Some of these changes in criteria pollutant
emissions (CO, NOx, and ROG) also reflect a further reduction from estimated 2005

                                          San Diego International Airport Expansion: Sustainability Analysis
 3-10
                                                                                           Chapter 3
                                                     Greenhouse Gas and Criteria Pollutant Emissions

emissions. On the basis of these comparisons, the increase of public transit mode share
in the Lindbergh ITC scenario offer a greater reduction in these emissions than Scenario
4 (Preferred Alternative with Airport Transit Plan).




San Diego International Airport Expansion: Sustainability Analysis
                                                                                              3-11
Chapter 3
Greenhouse Gas and Criteria Pollutant Emissions

This page left intentionally blank.




                                      San Diego International Airport Expansion: Sustainability Analysis
 3-12
       4.        Sustainability and Green Airport and Green
                 Building Opportunities for SDIA Expansion

This chapter reviews sustainability and green airport and green building concepts,
including a review of experience at other major international airports, and discusses
opportunities for their use with respect to the SDIA expansion alternatives. To meet the
challenge of limiting or mitigating their impacts on the environment, airports have
instituted a variety of sustainability measures. SDIA has adopted many active policies
and programs to minimize its effects on air and water quality, wildlife, noise, energy
consumption and waste materials (SDCRAA website www.san.org/Airport _Authority/;
Manasjan 2006). We have made no attempt to directly evaluate these programs.
However, several airports throughout the world have adopted sustainability programs that
are recognized as valuable lessons to learn from, emulate as appropriate and improve
upon. Therefore, this other information is presented as a benchmark for SDCRAA to
consider in establishing its goals and evaluating its success.

This chapter is organized in four main parts. Section 4.1 provides background
information on sustainability concepts which are applicable to the previous chapters and
to green airport and green building concepts. Sections 4.2 and 4.3 briefly present the
concept and framework of “green airport” and green buildings, respectively, and provide
examples of the sustainability opportunities which may be worthy of additional
consideration with respect to the expansion of the SDIA. Detailed background
information on these is presented in Appendix E. Specific examples of the concepts
presented in these sections are further documented in Appendix F. Section 4.4 briefly
summarizes the sustainability opportunities for Scenario 2 (No Project Alternative @
2030), Scenario 3 (Preferred Alternative), Scenario 4 (Preferred Alternative with Airport
Transit Plan) and Scenario 5 (Lindbergh ITC).

4.1. Why Sustainability?
There is no single universally accepted definition of what it means for a project, product,
or activity to be sustainable. A widely accepted definition of sustainability is that
provided by the Brundtland Commission (www.unece.org/oes/nutshell/2004-
2005/focus_sustainable_development.htm) which defined sustainability as meeting the
needs of the present society without compromising the ability of future generations to
meet their needs. There are various other definitions but they all imply continuity –
providing economic, environmental, and social benefits while eliminating (or at least
minimizing) direct and indirect negative impacts. Therefore the pursuit of sustainability

San Diego International Airport Expansion: Sustainability Analysis
                                                                                      4-1
Chapter 4
Sustainability and Green Airport and
Green Building Opportunities for SDIA Expansion


needs to move beyond impact mitigation and address the key questions of “what is being
sustained” and “for whom.” In doing so, project design considerations move beyond
evaluating operational efficiency (traditionally a short term perspective) and move into
the realm of effectiveness, ultimately creating enduring value, which is a longer term
proposition.

There are many aspects one could consider when evaluating the sustainability of airport
operations. In pursuit of sustainability the challenge is to reach an outcome that delivers
value over both short-term and long-term timeframes. Clearly, economic, environmental
and social concerns, coupled with political and technological ones, create multiple drivers
of change that can affect this value. As noted by various airport managers, sustainability
itself must also be cost-effective or it cannot be sustained (Hewitt 2007). Therefore the
key attributes to pursue are:

   Flexibility in maximizing opportunities over time;
   Adaptability to changing regulatory, market, social and environmental conditions and
   technological opportunities; and
   Longevity in considering the cost-value equation over the design life of SDIA to
   optimize resource use, recognize and internalize externalities and the capacity to meet
   projected growth in aviation demand.
The following provides an overview of the SDIA within its local, regional, national and
global context and provides an overview of sustainability potential.

4.1.1.   Local to Global Context
The SDIA and SDCRAA operates within a
                                                   SELECTION OF PROGRAMS, REGULATIONS AND LAWS
social, political and economic framework
                                                   RELATED TO SUSTAINABILITY
that is inextricably linked to local
                                                        City of San Diego ‘Sustainable Community Program’
communities, the region, and the state via              City of San Diego ‘Cities for Climate Protection Campaign’
the transportation services and associated              City of San Diego ‘Climate Protection Action Plan’
                                                        San Diego Association of Governments (SANDAG)
economic benefits it provides, its nine-                ‘Regional Comprehensive Plan’
                                                        SANDAG’s regional transportation plan ‘Mobility 2030’
member board, its own codes, policies,                  Port of San Diego ‘Port Sustainability Program’
programs and mission statements, and local              State of California AB 32 – Global Warming Solutions Act
                                                        On-going national discussions that may result in some form of
and state laws (Figure 4-1).                            federal greenhouse gas legislation
                                                        Environmental Protection Agency - Potential regulation on
                                                        CO2 as pollutant
As society adjusts to the implications of               Framework Convention on Climate Change - Bali
global climate change, all of its components            California Attorney General and Port of Los Angeles
                                                        Memorandum of Understanding on Reducing Greenhouse
are being called upon anew to address their             Gases
sustainability and greenhouse gas emissions.
These policies, programs, campaigns, regulations and laws are in an on-going state of
development and adjustment. The City and County of San Diego, other regional entities

                                          San Diego International Airport Expansion: Sustainability Analysis
  4-2
                                                                                            Chapter 4
                                                                  Sustainability and Green Airport and
                                                      Green Building Opportunities for SDIA Expansion


and the State of California have been actively engaged in sustainability and greenhouse
gas issues through a variety of initiatives (see Text Box). Many of these impact directly
or indirectly on the SDIA, and conversely, many SDIA activities directly and indirectly
impact these local, regional, state, federal and global processes.

         Figure 4-1: Airport Sustainability and its Local to Global Context
The upper level of this graphic shows the potential effects that an airport has with what can be called it direct
environmental footprint, i.e., its energy use, waste streams, wildlife, air emissions, and water use and water
discharge. However, as shown by the lower level an airport also has a wide variety of connections to the
local, regional, national and global community. The graphic identifies some of the specific connections that
SDIA can affect or that can, in turn, affect the SDIA.




4.1.2.      Opportunities for Sustainability
Implementing sustainability goals into daily activities increases the likelihood of
mitigating and reducing adverse unintended consequences. The opportunities to deliver
sustainability are greatest at the outset of a project (i.e., during the concept stage) and
progressively decline through the following stages (Figure 4-2). If not incorporated
early, the cost of future mitigation rises. Identification of sustainability goals after
commitment of major financial resources generally will lead to significantly higher costs
for mitigation or less effective avoidance of unintended consequences.



San Diego International Airport Expansion: Sustainability Analysis
                                                                                                          4-3
Chapter 4
Sustainability and Green Airport and
Green Building Opportunities for SDIA Expansion


    Figure 4-2: Relationship of Sustainable Design Value and the Cost of
                              Impact Mitigation
Diagram showing how the greatest sustainable design value is obtained at the earliest stages in a project life
cycle. Sustainable design value progressively declines the later it is addressed and the cost of impact
mitigation progressively increases. A project life cycle progresses from concept, feasibility, detailed design,
procurement, construction, and operations to decommissioning. The concept phase provides the greatest
potential to deliver long-term sustainability. Source: Modified from Fleming (2007).




                     Value of                                                   Cost of
                  sustainable                                                   impact
                      design                                                    mitigation

                              Concept                            Decommissioning
                                     Point at which sustainability
                               is first addressed in project life cycle


A good sustainability program must identify the values it seeks to sustain and the
recipients of this value. Vehicle miles traveled, traffic congestion, greenhouse gas
emissions and criteria pollutant reductions are the focus of our report even though these
are but several of many potential sustainability criteria. Green airport and green building
potentials are also addressed. The SDIA has a diverse set of on-going policies and
programs underway to reduce its environmental footprint in many areas. These include
storm water pollution prevention, hazardous waste and emergency response, air quality
and industrial hygiene, environmental assessment and construction monitoring, site
remediation, solid waste management and recycling, vector control, wildlife preservation,
noise mitigation, water conservation, land use compatibility, and transport and roadway
improvements (Figure 4-1; SDCRAA website www.san.org/Airport _Authority/;
Manasjan 2006). We believe these as well as other elements are needed to create an
effective sustainability program.

An organization’s environmental footprint can extend beyond its direct activities to
influence the actions and consequences of its clients, its suppliers, and its community.
This means that an organization needs to evaluate a “working boundary” for its planning
process that is in sync with other organizations and entities it influences. In addition,
costs and consequences can vary widely over time among alternative projects and
actions. This in turn requires managers to establish a method to value present versus
future costs and conditions. Together, these factors can make it difficult to frame the
boundary of a sustainability analysis or program.

                                                   San Diego International Airport Expansion: Sustainability Analysis
  4-4
                                                                                            Chapter 4
                                                                  Sustainability and Green Airport and
                                                      Green Building Opportunities for SDIA Expansion


4.2. Green Airport Concept and Framework
Green airport practices benefit the environment by reducing the airport global
environmental footprint, generate cost-savings to the airport through the use of renewable
or more efficient power sources, and improve the community’s airport image as being
environmentally-responsible. Sustainable initiatives at green airports address issues
related to water quality, local air quality, greenhouse gas emissions, wetlands, noise and
land use compatibility, recycling and waste management, wildlife, and sustainability and
overall environmental management (Airports Council International (ACI), 2007a and c).
The worldwide airport environmental initiatives tracker file prepared by ACI compiles
and describes sustainability efforts conducted around the world. The tracker file current
as of November 28, 2007, is included as Appendix F (ACI, 2007d). Over 70 initiatives
are classified into nine categories:

     Airfield emissions reductions
     Intermodality and surface access
     Recycling initiatives
     “Smart” buildings and energy efficiency
     Water pollution reduction
     Winter services
     Noise mitigation
     Communications initiatives and airport-wide campaigns
     Other environmental initiatives
The most pertinent to the present discussion are air emissions, intermodality and surface
access, recycling initiatives, and some other environmental initiative examples. Specific
examples are reviewed below.

Air emissions are addressed by initiatives such as using renewable energy sources and the
use of alternative fuel or low emission vehicles, compressed natural gas vehicles, battery
powered vehicles, and providing ground power and pre-conditioned air so that aircraft do
not need to use their auxiliary power units. Vancouver International Airport in Canada
uses solar panels to heat water and the Chicago and San Francisco International Airports
produce electricity from solar panels. La Palma Airport in Spain generates the majority
of its electricity from wind power generators. Auckland International Airport in New
Zealand has a fuel reduction trial by allowing planes to have a glide descent profile with
aircraft engines set at idle. Stockholm-Arlanda Airport has a similar aircraft coasting
program from cruising altitude to the runway. As noted in the greenhouse gas discussion
in Chapter 3, the use of ground power units (GPUs) to power the plane on the ground

San Diego International Airport Expansion: Sustainability Analysis
                                                                                                4-5
Chapter 4
Sustainability and Green Airport and
Green Building Opportunities for SDIA Expansion


minimizes the use of aviation fuel thereby reducing associated air emissions. Pre-
conditioned air units may also work in tandem with GPUs. They provide automatically
controlled air conditioning for ventilation, cooling, dehumidifying, filtering, and heating
of air to parked aircraft. Dallas-Fort Worth International Airport has an energy plant
upgrade with innovative technology that includes a large thermal energy tank and state-
of-the art boilers and chillers which has projected high future energy reductions. The
system also reduced NOx emissions by 95 percent. San Francisco International Airport
has an aircraft towing trial with Virgin Atlantic, Boeing and the FAA. For the trial an
aircraft was towed from the gate to near the runway providing substantial fuel and
greenhouse gas emission savings.

Reducing airport-related traffic also reduces emissions. With respect to intermodality
and surface access (i.e., getting to and from the airport) many airports have ambitious
goals for public transit use. For example, Zurich Airport in Switzerland has 42 percent of
persons reaching the airport via public transit. Madrid Spain’s airport expects a new
subway terminal to be used by 20,000 people daily. Boston’s Logan Airport provides
preferred parking to hybrid and alternative-fuel vehicles and hybrid taxis go to the head
of the line twice during a 12-hour shift thereby promoting reduced greenhouse gas and
criteria pollutant emissions. The “smart” buildings and energy efficiency category is also
noteworthy as a growing and creative trend in airport development. Section 4.3
addresses this subject in detail.

Recycling initiatives continue a long history of working to improve use, reuse and
recycling and there are many examples. At Seattle-Tacoma International Airport the
recycling program increased their tonnage from 112 five years ago to 1,200 in 2007.
Vendors also recycle their coffee grounds to a compost station. They now recycle 10 to
12 tons of coffee grounds per month. Seattle-Tacoma also has a program of providing
left-over pre-packaged food to the cities needy. At Los Angeles International Airport
food waste is used to produce methane gas which is recycled and turned into electricity.
Athens International Airport in Greece recycles treated water from their sewage treatment
plants and uses it for irrigation. The Canberra Airport in Australia implemented an
Aquacell Water System to recycle 26,400 gallons of water across the airport daily.
Oakland International Airport participated in a pillow recycling program so that rather
than disposing of pillows in landfills they are used for insulation or in furniture. Portland
International Airport also recycles its coffee and food waste but they also have a food
grease recycling program where kitchen waste oils are collected and processed into
biodiesel at an offsite facility. They also recycle foreign language periodicals from
airlines for reuse in local schools.

With respect to other environmental programs Phoenix International Airport has
participated in the testing of alternative pavements that are meant to reduce heat
                                          San Diego International Airport Expansion: Sustainability Analysis
  4-6
                                                                                            Chapter 4
                                                                  Sustainability and Green Airport and
                                                      Green Building Opportunities for SDIA Expansion


adsorption. By reducing the amount of heat absorbed the amount of heat released is also
reduced with the intent of reducing air temperatures (i.e., the urban heat island effect).
Phoenix has also assisted in the design of concrete benches with crumb rubber that are
both cooler and easier to move. The Hong Kong International Airport collaborated on a
green roofing student competition intended to reduce building temperature and related air
conditioning related energy use.

4.3. Green Buildings and the LEED System at Airports
In the United States, buildings account for 65 percent of electricity consumption, 36
percent of energy use, 30 percent of greenhouse gas emissions, 30 percent of raw
materials use, 30 percent of waste output (136 million tons annually), and 12 percent of
potable water consumption (USGBC, 2007). These numbers should not be surprising
considering that buildings include where we live and most of us work. However, because
of their large environmental footprint, buildings provide a target where environmental
improvements can have a large benefit.

In 2002, the United States Green Building Council (USGBC) defined the concept of
“green building” as design and construction practices that significantly reduce or
eliminate the negative impact of buildings on the environment and occupants. According
to USGBC, the benefits of green buildings are three-fold: environmental, economic, and
social. First, environmental benefits include the enhancement and protection of
ecosystems and biodiversity, the improvement of air and water quality, the reduction of
solid waste, and the conservation of natural resources. Second, economic benefits
include the reduction of operating costs, the enhancement of asset value and profits, the
improvement of employee productivity and satisfaction, and the optimization of life-
cycle economic performance. Finally, the social benefits related to health and
community include the improvement of air, thermal, and acoustic environments, the
enhancement of occupant comfort and health, the minimization of strain on local
infrastructure, and the contribution to overall quality of life.

The USGBC developed the Leadership in Energy and Environmental Design (LEED)
green building rating system and certification process. LEED is a third party validation
of achievement and LEED certification is a mark of recognition of quality buildings and
environmental stewardship. The LEED Green Building Rating System is a nationally-
accepted benchmark for the design, construction, and operation of high performance
green buildings and it has standards for specific building types or uses (e.g., health care,
office, schools, laboratory and retail). Various aspects of buildings, including design,
materials, and water and energy efficiency, are assigned points related to specific
performance criteria. Details of the rating system, performance criteria, different
certification levels and other details are provided in Appendix E.

San Diego International Airport Expansion: Sustainability Analysis
                                                                                                4-7
Chapter 4
Sustainability and Green Airport and
Green Building Opportunities for SDIA Expansion


4.3.1.   LEED-Certified and LEED-Registered Projects Related to Airports
         and Transit Centers
There are no explicit standards for airports or transit centers in the LEED system.
Nonetheless some airports and transit centers have achieved LEED certification or
registration for some buildings. Results of a search of LEED-certified and LEED-
registered projects related to airports and transit centers are summarized below and
included in Appendix F. To date, only five buildings related to airports and transit
centers are LEED-certified. They are:

   One airport terminal (Logan International Airport-Delta Terminal A Redevelopment)
   is LEED-certified at the certified level;
   Two transit centers are LEED-certified at the certified level (Interurban Transit
   Partnership, Grand Rapids, Michigan and Salt Lake City Intermodal Passenger Hub,
   Salt Lake City, Utah);
   One transit center is LEED-certified at the gold level (Colorado State University
   Transit Center, Fort Collins, Colorado); and
   One radar control building is LEED-certified at the gold level (Seattle Terminal
   Radar Approach Control, Burien, Washington).
LEED-registered projects show a total of 19 projects. The results include all types of
buildings at airports and transit centers, except for administration buildings. Out of these
19 projects, six buildings are terminals; six buildings are transit centers; four buildings
are other types of buildings, such as maintenance facilities or operations facilities; and no
additional information was available to determine the nature of the remaining three
projects.

These examples of LEED-certified and LEED-registered buildings demonstrate that these
standards can be met by airport buildings even though there are currently no specific
criteria for airport or transit centers.

4.4. Sustainability Opportunities for SDIA Expansion
     Alternatives
This section addresses the sustainability opportunities for Scenario 2 (No Project
Alternative @2030), Scenario 3 (Preferred Alternative), and Scenario 4 (Preferred
Alternative with Airport Transit Plan) and Scenario 5 (Lindbergh ITC). Table 4-1
summarizes the conclusions presented in this section.




                                           San Diego International Airport Expansion: Sustainability Analysis
  4-8
                                                                                            Chapter 4
                                                                  Sustainability and Green Airport and
                                                      Green Building Opportunities for SDIA Expansion

         Table 4-1. Comparison of Sustainability Opportunities for Alternatives
 Sustainability                  Scenario 2 (No Project            Scenarios 3 & 4       Scenario 5 (Lindbergh
 Opportunities                    Alternative @ 2030)           (Preferred Alternative           ITC)
                                                                   without and with
                                                                 Airport Transit Plan)
 Operational                                 +                           ++                      +++
 Structural (New                              -                           +                      +++
 Building)
 Overall Sustainability                   Lowest                      Increased                 Highest



4.4.1.      Scenario 2 (No Project Alternative @ 2030)
Under Scenario 2, the physical structures (e.g., terminals, runways, and other airport
buildings and infrastructures) and access to SDIA will remain unchanged. This
alternative provides the least sustainability opportunities for SDIA. While retrofitting of
structures and infrastructures is an option, many potential projects may not be cost-
effective on their own. Thus, unless major building renovations occur, there are fewest
structural and infrastructural opportunities for this alternative. However, some
sustainability opportunities for this scenario may exist in airport operations. Such
opportunities will include the implementation or modification of some operational
programs, for example:

     Controlling or reducing air emissions by targeting landside vehicles, ground support
     equipment, aircrafts, auxiliary power units on aircrafts, electric power consumption
     associated with airport operation, alternative electricity supply, emissions shifting and
     time of day controls (CPA, 2002); and
     Continuing to improve energy efficiency including buying green power and using
     renewable energy sources or biofuels.
4.4.2.      Scenario 3 (Preferred Alternative) and Scenario 4 (Preferred
            Alternative with Airport Transit Plan)
Under Scenario 3 and Scenario 4 the SDIA footprint will remain very similar to present.
There will be an addition to Terminal Two West, new general aviation facilities including
access and hangers, and a new parking structure as well as the demolishing of the existing
general aviation facilities. The rest of the airport buildings and infrastructures will
remain unchanged. Similar to the No Project Alternative, many potential projects
associated with retrofitting of existing structures and infrastructures may not be cost-
effective unless major renovations occur. In addition, the opportunities listed for
Scenario 2 can also be applied to Scenario 3 and Scenario 4. However, in addition to
sustainable airport operational options described above for the No Project Alternative,
this scenario also offers some additional sustainability opportunities in the new building
additions and reconstruction, for example:
San Diego International Airport Expansion: Sustainability Analysis
                                                                                                          4-9
Chapter 4
Sustainability and Green Airport and
Green Building Opportunities for SDIA Expansion


   Design and integration of energy efficient building systems and green components in
   new buildings;
   Re-use and recycle of materials from the demolished buildings for the construction of
   new buildings;
   Installation of solar panels on existing buildings and on new buildings; and
   Updating electrical systems with automatic on-off sensors.
Indeed, as mentioned in Section 6.1 – Significant Irreversible Environmental Changes of
the SDIA DEIR, implementation of the Proposed Project will address high standards of
efficiency and environmental design, consistent with LEED standards to reduce the use
of renewable and nonrenewable resources. The two examples listed in the DEIR include
the re-use of asphalt and concrete in new airfield aprons and taxiways, and the use of
windows and window treatment in terminals to conserve energy. Although the DEIR
mentions that the Preferred Alternative will follow LEED standards, it does not explicitly
commit to LEED certification of any new buildings or terminals.

4.4.3.   Scenario 5 (Lindbergh ITC)
In this scenario there would be a complete redesign of the existing airport terminals as
well as the development of the Lindbergh ITC. The airport terminals would be moved
from the south side to the north side of the runway. Because the Lindbergh ITC scenario
involves such a complete redesign of the airport there are substantial opportunities to
include sustainable options into the new design and to streamline operational
effectiveness from both a sustainability perspective such as energy efficiency and for
overall employee and passenger ease. As noted in Section 4.1.2 the greatest opportunity
to deliver sustainability is during the concept phase of a project. Consequently, this
alternative is very different than Scenarios 2, 3 and 4.

While there are substantial sustainability benefits associated with this alternative, the
current analysis does not include cost-benefit analysis which is a component of
sustainability. Implementation of the Lindbergh ITC and use of any specific design,
green building or operational efficiencies would need to be carefully evaluated and
financing secured. However, in addition to the traffic, air quality and greenhouse gas
benefits which are presented in Chapters 2 and 3, the redesign and rebuilding of the
airport does provide substantial opportunity for incorporating highly sustainable LEED
components strategies into their physical structure. These new terminals would provide
the potential for a substantial increase in overall sustainable components compared to the
current terminals. In addition, LEED components could be incorporated into the
Lindbergh ITC itself making it a sustainable structure and contributing to an overall
reduced airport carbon footprint and the potential to evaluate features such as
construction of gray water lines and recycled water lines. Quantifying the actual net

                                         San Diego International Airport Expansion: Sustainability Analysis
 4-10
                                                                                            Chapter 4
                                                                  Sustainability and Green Airport and
                                                      Green Building Opportunities for SDIA Expansion


reduction for the airport terminals would require a detailed design and accounting for
them minus the footprint of demolition and recycling of the current infrastructure
compared to the airport as it currently exists as well as to the developing plans for
implementing the LEED program standards at the existing airport (Scenario 3 and
Scenario 4).

Some of the green airport and green building opportunities are:

     Re-use and recycle materials from the demolished buildings;
     Incorporate LEED standards into the design, construction and operation to the
     maximum feasible extent;
     Use the most energy efficient windows available;
     Install solar panels on the Lindbergh ITC roof;
     Install solar panels on the new airport terminal roof;
     Use solar tubes to increase internal natural lighting during daylight hours and
     reducing electrical use;
     Use the most up-to-date and energy efficient lighting systems and lights including
     automatic sensors;
     Create green roofs on the new airport terminal and Lindbergh ITC that minimize their
     heat absorption characteristics thereby minimizing heat island effects;
     Create rainwater collection systems on the airport and Lindbergh ITC roofs designed
     to allow reuse for landscaping irrigation or similar purposes;
     Recycled water lines for airport landscaping; aned
     Integrated food handling and recycling with the potential for on-site composting for
     use with airport landscaping.
In addition starting with a new footprint would allow numerous operational efficiencies
to be incorporated which would have both positive sustainability effects and improved
efficiencies for employees and airport customers contributing to an overall increase in
satisfaction. For example, there would be opportunities for:

     Newly designed traveler check in and security queuing areas providing efficiencies to
     airlines, Transportation Security Administration, and travelers;
     More efficiency for caterers and their access to planes;
     Increased efficiency in baggage handling providing convenience for travelers and
     potential savings to airlines;
     An underground fuel hydrant system to reduce the use of fuel trucks; and


San Diego International Airport Expansion: Sustainability Analysis
                                                                                                4-11
Chapter 4
Sustainability and Green Airport and
Green Building Opportunities for SDIA Expansion


   Increased cooperation and planning with airlines by designing the new airport to
   include developing technologies that assist in reducing the airside impacts associated
   with airlines, e.g., towing planes to the runway, using landside plug-ins so that
   airplane auxiliary power units do not need to power air conditioning and other plane
   electrical needs while at the gate.
Instituting a ground-level up integrated system that enhances operational efficiencies
through infrastructure, siting/location, staff allocation, and communication systems has
the potential for other non-obvious synergistic improvements.




                                         San Diego International Airport Expansion: Sustainability Analysis
 4-12
                                                  5.        Summary and Discussion

Although there are many potential sustainability goals and indicators associated with
SDIA and the San Diego community, one goal which the community is required to
address is the reduction of greenhouse gas emissions in order to reduce the potential
impacts from climate change. California AB 32 requires an overall reduction in
greenhouse gas emissions to 1990 levels (approximately a 25 percent reduction) by 2020.
Additional local, state, federal, international, and market-driven drivers for reducing
greenhouse gas emissions exist or emerge almost daily.

Transportation is a significant source of greenhouse gas emissions which contributes to
global climate change. For example, the City of San Diego reported that in 2004 the
transportation sector contributed 7.9 million tons of greenhouse gas emissions tons per
year (approximately 21.5 thousand tons per day; City of San Diego, no date). This was
equivalent to more than 50 percent of the community’s projected total greenhouse gas
emissions. San Diego also has the worst traffic congestion of all medium sized cities
which further exacerbates greenhouse gas emissions. The high proportion of San Diego,
California and U.S. emissions that come from the transportation sector, added to
projections for significant increased transportation needs which in turn are projected to
yield further increases in emissions, make the probability of new restrictive policies and
regulations on this sector significant. Indeed, implementation of California AB 1493
(which is in dispute with the EPA) and on-going development of other California
initiatives, including those related to AB 32, are the beginning of a significant trend.

As a society, Americans enjoy the opportunity to travel freely and we exercise that right
more every year. The draft Airport Master Plan for SDIA projects an increase in demand
for air travel of approximately 60 percent by 2030, and the actual growth rate the past
several years has exceeded annual projections. Results from our study project show that
air passengers and airport employees will increase travel to and from SDIA by 57
percent, or 250 million miles annually in 2030 compared to 2005 levels under the No
Project Scenario. Results from this study demonstrate substantial benefits associated
with requirements to improve new vehicle fuel efficiency. Both past (1990 to 2004) and
predicted (2005 to 2030) data indicates that the increase in fuel economy in vehicles will
slow the rate of increase in greenhouse gas emissions. However, at the levels being
required in the new regulations, they will not be adequate to maintain, let alone reduce
greenhouse gas emissions if the level of increased transportation demand increases as
projected unless radical new technologies, policies, transportation alternatives, or
behaviors are developed.


San Diego International Airport Expansion: Sustainability Analysis
                                                                                     5-1
Chapter 5
Summary and Discussions

Given the significant increase in projected demand for air travel at SDIA, the existing
impact of airport related travel on traffic congestion on streets around the SDIA, and the
contribution of the transportation sector to greenhouse gas emissions, this report focused
on a comparison of the sustainability associated with ground transportation of airport
passengers and employees. It evaluated the No Project and Preferred Alternatives from
the Airport Master Plan DEIR, as well as the CAIVP proposed Lindbergh Intermodal
Transportation Center. Similar to the DEIR Master Plan, emissions from actual air travel
were not included in this study due to complexity and federal regulation of air travel.

The major sustainability components evaluated in this report include:

   The ability to increase public transit ridership (mode share);
   Changes in daily vehicle miles traveled (VMT) by airport passengers and workers
   commuting to and from the airport;
   Changes in road traffic congestion (level of service) on the streets around the SDIA;
   Impact of passenger and airport worker travel changes on greenhouse gas emissions;
   and
   Impact of passenger and airport worker travel changes on air quality (criteria
   pollutants);
Other positive sustainability components resulted from the above and these were also
identified, including lessons learned from a qualitative review of the experience at other
international airports to implement “green airport” practices. We acknowledge the value
of existing SDIA efforts to reduce its environmental footprint by minimizing its effects
on air and water quality, wildlife, noise, energy consumption, and waste materials. The
exclusion of these SDIA programs from our study is not intended as a judgment of the
value of these programs.
A summary and comparison of the No Project Alternative, the DEIR Master Plan
Preferred Alternative with Airport Master Plan and the Lindbergh ITC at 2030 with
respect to various sustainability indicators is provided in Table 5-1.




                                          San Diego International Airport Expansion: Sustainability Analysis
  5-2
                                                                                                    Chapter 5
                                                                                       Summary and Discussion




        Table 5-1.Sustainability Components Summary for Scenarios 2, 4 and 6
                                                               Scenario 4 (Preferred
                                      Scenario 2 (No                                       Scenarios 5 (Lindbergh
                                                               Alternative with Airport
                                      Project @ 2030)                                          ITC @ 2030)
   Sustainability Indicator                                    Transit Plan @ 2030)
 1. Transit Mode Share                     1.3%                         2.6-3.0%                   4.0-5.2%
                                         (Baseline)
 2. Daily Average                   57% increase over          1.6-1.9% reduction from     9.0-9.8% reduction from
 Vehicle Miles Traveled               2005 Baseline               No Project at 2030         No Project @ 2030


 3. Annual VMT                           690 million            11.1 million less than      61.7 million less than
                                                                 No Project @ 2030           No Project @ 2030
 4. Traffic Congestion in           Reduced Levels of           Similar to Scenario 2        Improved Levels of
 Airport Vicinity                   Service from 2005                                      Service on Rosecrans,
                                        Baseline                                           India, Kettner, Grape,
                                                                                                Hawthorne,
                                                                                           Washington, Hancock
 5. Traffic Congestion               Level of Service             Level of Service           Generally improved
 Beyond Airport                     decreases notably           decreases but slightly        Levels of Service
                                                                  better than 2005         compared to Scenarios
                                                                      Baseline                    2 and 3
 6. Greenhouse Gas                 22.6% increase over           < 1% reduction from        > 9% reduction from
 Emissions from Airport               2005 Baseline                  Scenario 2                 Scenario 2
 Related Passenger
 Vehicles (CO2e)
 7. Criteria Air Pollutants              CO -56%                < 1.9% reduction in all     9.7% reduction in all
 from Airport Related                   NOx -65%                    pollutants from            pollutants from
 Passenger Vehicles                     ROG -44%                      Scenario 2                 Scenario 2
                                        SOx +56%
                                        PM10 +79%
                                        PM2.5 +91%
 8. Opportunity to                        Baseline                   Modest Increase           Most Significant
 Increase Efficiency of
 Regional Transit
 9. Opportunity for                Minimal except for            Good on expanded          Substantial opportunity
 Incorporating Green              occasional renovation         Terminal 2 West and              for reduced
 Building Design                                                new general aviation       environmental footprint
                                                                       facilities.          from operation. One-
                                                                 Implementation of          time costs associated
                                                                LEED certification for         with expanded
                                                                  new and existing             demolition and
                                                               buildings would reduce       construction exist but
                                                               environmental footprint.         not quantified.
 10. Opportunity for                      Baseline               Some improvement          Potentially substantial if
 Sustainability                                                   over No Project            incorporated in new
 Improvements from                                                  Alternative            terminal and ITC design
 Operational Efficiency




San Diego International Airport Expansion: Sustainability Analysis
                                                                                                               5-3
Chapter 5
Summary and Discussions

The DEIR Master Plan Preferred Alternative, with the Airport Master Plan provided
small reductions in daily average VMT (1.6-1.9 percent) and greenhouse gas emissions
(0.9 percent) at 2030 compared to the No Project Alternative at 2030 (Figures 5-1 and 5-
2). The DEIR references the draft Airport Transit Plan as to how it will mitigate
increased traffic and possible congestion by identifying measures to increase transit mode
share. The draft Airport Transit Plan includes a variety of measures that, when
implemented, have an aspirational goal of increasing transit mode share from 1.2 percent
to 4-6 percent over the next 3-5 years. The modeling results from our study suggested
that the mode shares indicated in the Transit Plan will only be in the range of 2.6-3.0
percent without additional incentives or influences (whether intentional or from external
influences outside the control of the SDCRAA). For example, our results predicted a
mode share for the Old Town Shuttle Bus Service and the Coaster Service measures that
were approximately 20-30 percent of that included in the draft Airport Transit Plan and
that modeled increases in mode share were predominantly in bus use. Consequently, the
ability of the Preferred Alternative with the Airport Transit Plan to provide significant
reductions in greenhouse gas emissions, average daily VMT, and traffic congestion
appears low.


           Figure 5-1: Additional Average Daily Vehicle Miles Traveled in 2030
                             Compared to the 2005 Baseline.

                                                                                       Conservative Assumptions
                                                                                       Optimistic Assumptions
           1,950,000
           1,900,000
           1,850,000
           1,800,000
   Miles




           1,750,000
           1,700,000
           1,650,000
           1,600,000
                       Scenario 2 (No Project   Scenario 3 (Preferred   Scenario 4 (Preferred   Scenario 5 (Lindbergh
                            @ 2030)                 Alternative)        Alternative w Airport           ITC)
                                                                             Transit Plan)




                                                        San Diego International Airport Expansion: Sustainability Analysis
  5-4
                                                                                                            Chapter 5
                                                                                               Summary and Discussion

 Figure 5-2: Greenhouse Gas Emissions Percent Change from Scenarios 2
                          (No Project @ 2030)

                                                                Scenario 4 (Preferred Alt w Airport
                           Scenario 3 (Preferred Alternative)             Transit Plan)               Scenario 5 (Lindbergh ITC)
                       0
                                          0
                      -1
                      -2
                                                                              -1.9
    Percent Change




                      -3
                      -4
                      -5
                      -6
                      -7
                      -8
                      -9
                                                                                                                 -9
                     -10

SDCRAA identified three objectives for the proposed Master Plan:

1. Provide adequate facilities to accommodate air service demand through 2015 while
   improving airport levels of service, airport safety and security, and enhancing airport
   access;
2. Develop facilities that effectively utilize the current airport property and facilities and
   are compatible with surrounding land uses; and
3. Provide for future public transit options in airport land use planning.
Our modeling results suggest that the DEIR Preferred Alternative with Airport Master
Plan does not effectively address “enhancing airport access” criteria under the first
objective above. In addition, the DEIR Preferred Alternative may limit, rather than
promote, future public transit options because high capital costs for Terminal Two
expansion and parking may preclude other options not rigorously investigated given the
constraints associated with the second objective.
In comparison to the DEIR Master Plan No Project and Preferred Alternatives (including
with Airport Transit Plan), the Lindbergh ITC provided substantial progress towards the
sustainability indicators (Table 5-1). Based on our quantitative transportation modeling
(which reflects the effect of travel times, costs, and other factors on traveler’s
transportation decisions) the only scenarios that substantially increased public transit
ridership (Figure 5-3) and reduced the rate of increase in average daily vehicle miles
traveled (Figure 5-1) was the Lindbergh ITC scenario. The increase in transit use and the
reduction of trip length by providing direct access to the airport terminal from I-5 resulted
in a reduction of 139 thousand average daily vehicle miles (or more than 50 million
annual miles) traveled by airport passengers and employees compared to the Preferred
Alternative with Airport Master Plan (Figure 5-1).


San Diego International Airport Expansion: Sustainability Analysis
                                                                                                                       5-5
Chapter 5
Summary and Discussions

The increased public transit use, reduced VMT, and placement of the airline terminals
close to I-5 also result in substantially reduced traffic congestion (i.e., improved levels of
service) on the streets in the neighborhoods surrounding SDIA for the Lindbergh ITC
compared to DEIR Preferred Alternative without requiring mitigation measures such as
the removal of on street parking and increasing the number of lanes. Details are shown in
Figures 2-10, 2-11 and 2-12 in Chapter 2 Transportation Analysis. Specifically, the level
of service on Rosecrans and Laurel Streets would improve to acceptable levels with the
Lindbergh ITC in place. Hawthorn Street would experience improvements on particular
segments and improvements are also projected on a number of other streets, particularly
India, Kettner, Grape, Washington, and Hancock. Our modeling also shows that criteria
pollutants are reduced approximately in proportion to the VMT so that they are reduced
approximately 9.7 percent with the Lindberg ITC versus 1.9 percent for the Preferred
Alternative with Airport Master Plan. Much of this reduction would be expected in the

         Figure 5-3: Proportion of Passengers and Employees Using Transit


             6

             5

             4                                                                                                                                                          FlyAway
   Percent




                                                                                                                                                                        Coaster
             3
                                                                                                                                                                        Trolley
             2                                                                                                                                                          Bus
             1

             0
                                  Optimistic




                                                                Optimistic




                                                                                                 Optimistic




                                                                                                                              Optimistic




                                                                                                                                                           Optimistic
                   Conservative




                                                 Conservative




                                                                             Conservative




                                                                                                               Conservative




                                                                                                                                            Conservative




                 Scenario 1 (2005               Scenario 2 (No               Scenario 3                        Scenario 4                    Scenario 5
                    Baseline)                  Project @ 2030)               (Preferred                         (Preferred                 (Lindbergh ITC)
                                                                             Alternative)                     Alternative w
                                                                                                              Airport Transit


vicinity of the airport as a result of the reduced traffic congestion. The combination of
reduced criteria pollutants, increased transit use, the redirection of airport related traffic,
and less traffic congestion would all contribute to an overall enhanced quality of life in
the area. Under the DEIR Preferred Alternative potential mitigation to improve LOS to
acceptable levels on these streets includes road widening, removing on street parking,
increasing the number of lanes and intersection improvements. If implemented such
measures could improve LOS but they do not improve VMT and thus maintain the traffic
increase on streets adjacent to the airport making access for residents and local businesses
more difficult. The measures do not reduce local criteria pollutants or overall greenhouse
gases.
                                                                                            San Diego International Airport Expansion: Sustainability Analysis
  5-6
                                                                                  Chapter 5
                                                                     Summary and Discussion

The Lindbergh ITC provided the most benefits for reducing the rate of growth in
greenhouse gas emissions. Specifically, the Lindbergh ITC resulted in an 8.4 percent
reduction in greenhouse gases compared to Scenario 4 (Preferred Alternative with
Airport Master Plan) or 9.2 percent less than Scenario 2 (No Project @ 2030) and
Scenario 3 (Preferred Alternative) (Figure 5-2). However, while there are percent
reductions from Scenario 2 there is still an overall substantial growth in the absolute
amount of greenhouse gas emissions. The Lindbergh ITC would still have a 54 metric
tons per day increase over 2005 Baseline. Thus, the ITC by itself was insufficient to
make sufficient reductions in VMT to reach even short-term goals for greenhouse gas
reductions if goals were uniformly applied across each segment of society. However, the
estimated 8 percent reduction of greenhouse gas emissions in the Lindbergh ITC scenario
could form an important component of an overall plan to decrease greenhouse gas
emissions associated with the SDIA.

Since the Lindbergh ITC proposal is essentially the development of a new airport
terminal it provides the maximum ability to incorporate the newest efficiencies and most
effective sustainable design concepts of the alternatives evaluated. In addition, using the
most energy efficient materials and systems would enhance overall sustainability. The
design of new terminal and associated ITC also provides the opportunity for a variety of
operational efficiencies.

This study is not a comprehensive evaluation of the sustainability of airport expansion
alternatives. Modeling results are suitable for an initial high-level comparison of
alternatives, but there are elements of a complete evaluation that were beyond the scope
of this study. We have conducted a preliminary evaluation of a concept rather than a full
evaluation and comparison of detailed plans. Our study does not include a detailed
environmental assessment, cost benefit comparisons of the scenarios, nor an evaluation of
other approaches to reduce traffic congestion and emissions. We have limited our
analysis to the increase in public transit ridership, changes in VMT and levels of service,
greenhouse gas emissions, criteria pollutants and other sustainability components which
result from the above. The consideration of other sustainability criteria and how they
may influence airport expansion is warranted given the significant capital costs for the
project. However, the demonstrated improvements associated with the Lindbergh ITC
indicate that it merits further detailed public consideration.




San Diego International Airport Expansion: Sustainability Analysis
                                                                                      5-7
Chapter 5
Summary and Discussions

This page left intentionally blank.




                                      San Diego International Airport Expansion: Sustainability Analysis
  5-8
                                                                     6.   References

Airports Council International. 2007a. Airports and the Environment. March.
       http://www.airports.org/aci/aci/file/ACI_Priorities/Environment/position%20brief
       _ENVIRONMENT.pdf

Airports Council International. 2007b. Climate Change. May.
       http://www.airports.org/aci/aci/file/ACI_Priorities/Environment/position%20brief
       _CLIMATECHANGE2.pdf

Airports Council International. 2007c. Going Green. November.
        http://www.aci-na.org/docs/Going%20Green%209-7-07.pdf

Airports Council International. 2007d. Worldwide airport environmental initiatives
       tracker file. November.
       http://www.airports.org/aci/aci/file/ACI_Priorities/Environment/TRACKER%20F
       ILE_Airport%20environment%20initiatives.pdf

APTA (2007) Light Rail Transit Ridership Report - Third Quarter 2007, American Public
     Transportation Association.

California Energy Commission. 2006. Inventory of California greenhouse gas emissions
       and sinks: 1990 to 2004. CEC-600-2006-013-SF. 117 pp.

Cambridge Systematics. 2007. Bay Area/California High-Speed Rail Ridership and
      Revenue Forecasting Study. Prepared for Metropolitan Transportation
      Commission and the California High-Speed Rail Authority.

City of San Diego. No date. San Diego Greenhouse Gas Emission Inventory.
        (www.sandiego.gov/environmental-services/sustainable/pdf/ghginventory.pdf)

Clean Airport Partnership, Inc. Green Airport Initiative.
       http://www.cleanairports.com/reports/GAI.pdf

Clean Airport Partnership, Inc. 2002. Dallas Fort Worth International: Building a Model
       Green Airport. April. http://www.cleanairports.com/reports/gai_dfwforweb.pdf

Clean Airport Partnership, Inc. 2003. Executive Summary: The Green Airport Initiative
       at Fort Lauderdale-Hollywood International Airport. August.
       http://www.cleanairports.com/reports/gai_fllforweb.pdf



San Diego International Airport Expansion: Sustainability Analysis
                                                                                   6-1
Chapter 6
References

Davis Langdon. 2004. Costing Green: A comprehensive cost database and budgeting
       methodology. Lisa Fay Matthiesen and Peter Morris. July.

Davis Langdon. 2007. Cost of Green Revisited: Reexamining the feasibility and cost
       impact of sustainable design in the light of increased market adoption. Lisa Fay
       Matthiesen and Peter Morris. July.

Dowling Associates, Inc. 2002. San Jose International Airport Transit Connection
      Ridership. Prepared for San Jose International Airport, Lea Elliott and Walker
      Parking.

FAA (2005) Aviation & Emissions - A Primer, Washington, DC.
      (www.faa.gov/regulations_policies/policy_guidance/envir_policy/media/AEPRI
      MER.pdf)

Fleming, N. 2007. Creating a world of difference, Part 2, Delivering enduring value.
      Prepared by Sinclair Knight Merz.

Gupta, S., Vovsha, P. and Donnelly, R. 2007. A Model for Joint Choice of Airport and
       Ground Access Mode. 11th National Transportation Planning Applications
       Conference, Transportation Research Board.

Harvey, G. 1987. Airport choice in a multiple airport region. Transportation Research,
      A21(6), pp. 439-449.

Hess, S., and Polak, J.W. 2005. Mixed Logit Modeling of Airport Choice in Multi-airport
       Regions. Journal of Air Transport Management, 11 (2), pp.59-68.

Hewitt, W.F. 2007. Airports and airlines are going green. Planning. November 2007, pp.
       22-25.

HNTB. 2007. Airport Transit Plan – San Diego International Airport. Prepared for
     Airport Transit/Roadway Committee; Sponsored by San Diego County Regional
     Airport Authority. November 2007.

HR&A (2006) 2005-2035 Airport Economic Analysis, Draft prepared for San Diego
    County Regional Airport Authority.

Leigh River Associates, M.A. Coogan, and MarketSense. 2002. Strategies for improving
       public transportation access to large airports. TCRP Report 83, Transportation
       Research Board, Washington, D.C.




                                         San Diego International Airport Expansion: Sustainability Analysis
  6-2
                                                                              Chapter 6
                                                                             References

Manasjan, P. 2006. San Diego International Airport: tracking our environmental
      footprint. Presented at the California Integrated Waste Management Board/Local
      Enforcement Agencies Annual Conference, August 1, 2006.
      http://www.ciwmb.ca.gov/Part2000/Events/06Conf/Presentation/Day1/Keynote.p
      df

National Research Council, Board on Energy and Environmental Systems, Effectiveness
       and Impact of Corporate Average Fuel Economy (CAFE) Standards, National
       Academy Press, 2002. http://www.nap.edu/openbook.php?record_id=10172
       &page=R1, accessed December 2007.

SANDAG. 2004. 2030 Regional Growth Forecast. SANDAG SourcePoint, June 2004,
    No. 4, 8 pp.

San Diego County Regional Airport Authority. 2007. Airport Master Plan – San Diego
       International Airport – Draft Environmental Impact Report. October 2007.

Schrank, D and T. Lomax. 2007. The 2007 urban mobility report. Texas Transportation
      Institute, Texas A&M University.

SH&E, Inc. 2004. San Diego Airport Aviation Activity Forecasts. Prepared for San
     Diego Regional Airport Authority. June 2004.

U.S. Department of Transportation, National Highway Transportation Safety
       Administration, "Draft Environmental Assessment, Proposed Corporate
       Average Fuel Economy Standards", August 2005.
       http://www.nhtsa.dot.gov/cars/rules/rulings/LightTrucksRuling-2008-
       2001/Assessment/index.html, accessed December 2007.

United States Green Building Council. 2006. LEED for New Construction Version 2.2.
       November

United States Green Building Council. 2007. Website. http://www.usgbc.org/

URS (2003). Central Interstate 5 Corridor Study. Prepared for SANDAG.

WRI (2005) Navigating the Numbers - Greenhouse Gas Data and International Climate
      Policy. World Resources Institute, Washington, DC.
      (http://pdf.wri.org/navigating_numbers.pdf)

WRI (2008) Climate Analysis Indicators Tool (CAIT US) Version 2.0. World Resources
      Institute, Washington, DC. (http://cait.wri.org/)




San Diego International Airport Expansion: Sustainability Analysis
                                                                                   6-3
Chapter 6
References

Zweig White, 2004. Architecture, Engineering, and Construction (AEC) Industry
      Outlook. Strategy & Insight for Design and Construction Firms. November 2004.


Websites:
Airport Cooperative Research Program. www.trb.org/news/blurb_detail.asp?ID=575

Airports Council International. www.airports.org/

California Independent Voter Project. www.caivp.org/index.html

Clean Airport Partnership, Inc. www.cleanairports.com/

Green Skies. www.greenskies.org/

San Diego County Regional Airport Authority.
       www.san.org/Airport_Authority/splash.asp




                                        San Diego International Airport Expansion: Sustainability Analysis
  6-4
          San Diego International Airport Expansion
          Sustainability Analysis




          Appendix A - Case Studies




6189001
                                                          Appendix A - Case Studies

For purposes of comparison, five U.S. airports with transit connections were compared to
SDIA. These airports vary widely in context – from large cities with major airports such
as Chicago O’Hare to cities smaller than San Diego such as Portland. The key
characteristics of the cities, airports and transit links are summarized in Table A-1.

                           Table A-1.Case Study Airports - Comparative Data
                                                                             Airport
             Designator               SAN               SFO            OAK               PDX           ORD               STL
                City                San Diego      San Francisco     Oakland           Portland      Chicago        St Louis
 Annual passengers
 - Total (million)                    17.4              34.3           14.4              14.0          76.2              15.2
 - O&D (million)                      16.7              25.1           13.2              10.9          33.2              10.4
 Purpose split (business)             45%               23%            28%                n.a.          n.a.             n.a.
 Distance to downtown (miles)          3.3              14.0            9.9              12.3          17.0              15.1
 Proportion of residents              60%               56%            58%               40%            35%                -
 City characteristics
 2005 population (million)            1.26              1.22           1.46              0.54          9.50              2.80
                                2
 Popul’n density (persons/mi )         668             1,976           1,549              359          1,619             410
 Rail
 Number of rail lines                   3               n.a.             4                 3             8                2
 Track per 100,000 people           4.06 miles          n.a.         6.65 miles        8.17 miles    3.69 miles     1.64 miles
 Stations per 100,000 people          4.21              n.a.           1.99              11.9          5.01              1.32
 Dedicated                             No               n.a.            No                No            No                No
 Ground transportation between downtown and airport
 Taxi fare                             $11             $30-45           $20             $27-32        $35-40             $35
 Shared van fare                       $11              $16             $17               $20           $25              $15
 Journey time (car/taxi)              10-20            24-40           17-30              20           30-70              22
 Public transit
 Rail        - type                     -              Heavy          Heavy              Light        Heavy              Light
             - fare                     -              $5.15           $4.40             $2.05         $2.00          $3.50
             - journey time             -                31             33                30            42                31
             (mins)
             - headway (mins)           -                20             15                15             7                10
                                                               1               2                 3             4               5
             - mode share               -              6.3%            8.0%              6.7%          4.0%              5%
 Bus         - fare                   $2.25            $4.00           $1.75               -            $25                -
             - journey time            16                35             15                 -           40-80               -
             (mins)

             - headway (mins)          12                30             15                 -           5-10                -
             - mode share             1.4%              n.a.            n.a.               -            n.a.               -




San Diego International Airport Expansion: Sustainability Analysis
                                                                                                                   A-1
Appendix A
Case Studies

Notes:
Dedicated bus feeder to rail station
1.   Percentage of average access/egress at SFO over nine months to March 2004. These values are total percentages (i.e., include air
     passenger, airport employees, and “others” who use BART to get to and from SFO).
2.   Passenger survey response, Oakland International Airport, 2002
3.   Percentage of average access/egress at PDX over 22 months to November 2003. These values are total percentages.
4.   Percentage mode shares, data from 1998 reported in TCRP, 2000
5.   Passenger survey response, 2002




Comments on each airport, compared with San Diego, are made in the following
paragraphs.



 San Francisco, CA (SFO)


Context

SFO is the second largest airport in California after LAX. Its geographical location
makes it a significant hub for international flights on the western seaboard and for
connecting flights within the USA. As such, the airport operates with a high proportion of
transfer/transit passengers relative to other ports of a comparable size.

As one of three airports in the Bay Area, SFO faces competition from Oakland
International (OAK) and Mineta San Jose International (SJO), particularly in the low cost
domestic airline market. This has impacted traffic in recent years; however positive
growth in this market is expected from FY2008 as low cost carriers increase services
from SFO. In comparison to San Diego, San Francisco Airport handles a greater
proportion of international, non-business and connecting passengers.

The city of San Francisco is a fairly densely populated city of 740,000 with a wider
metropolitan population of 1.22 million along the peninsula. BART (Figure A-1) is a
metro rail system servicing the needs of Bay Area residents. It traverses the city and
county of San Francisco along one corridor only, with limited connections to the MUNI
Metro light rail system.

The airport is accessible by an adjacent freeway and by rail, integrated within the BART
system. A dedicated BART station is located within the international terminal. The
BART line extension connecting the airport, San Francisco and the greater Bay Area was
opened in 2003.

San Diego is one third the population density of San Francisco, adversely affecting the
ability of transit to conveniently serve a large proportion of the population. The


                                                             San Diego International Airport Expansion: Sustainability Analysis
   A-2
                                                                             Appendix A
                                                                            Case Studies

accessibility of San Diego airport, located only three miles from the downtown,
somewhat differs from San Francisco, however each lies adjacent to major arterials.



                Figure A-1: BART Rail Transit Network in the Bay Area




                    Source: Bay Area Rapid Transit


Success Factors

The city of San Francisco has a relatively high level of public transit usage by North
American standards, at approximately 17 percent of trips. The density of the city,
concentration of economic activity in the downtown area and a robust public transport
network are contributing factors.

The expansion of the BART system to SFO was coupled with ridership estimates that
have proven to be optimistic. In 2005 there were 7,116 daily boardings compared with
the 2010 forecast of 17,800. Though ridership from the airport has been somewhat lower
than predicted, it has been the much lower ridership from other travelers along the
corridor that has hurt the forecasts the most. The line has been a significant dampener on
the profitability of the BART system.

                    :
San Diego International Airport Expansion: Sustainability Analysis
                                                                                      A-3
Appendix A
Case Studies

The current patronage levels from the airport link may be attributed to several factors:

   Ease of accessibility to freeways and the small differential in mode journey times
   limits the system’s attractiveness.
   The limited corridor through which BART connects to San Francisco; connections to
   other modes of transit are required from the single line if not within close proximity
   to the station.
   The spread of stations per capita is low reflecting relatively poor geographical
   distribution of BART access.
   Recent downward trend in traffic of low cost carriers into SFO may affect public
   transport patronage from price sensitive air travelers.
   Low service frequency and non-dedicated rolling stock.
Despite the high visibility of the service and the strong positive brand recognition of the
BART system, the integrated and accessible airport link is underutilized compared to
capacity and prior estimates. The main disadvantage to this service is that the single
BART line is not in close proximity to a majority of the population within San Francisco.


Oakland, CA (OAK)

Context

Oakland International Airport (OAK) is the second largest of the three commercial
airports to service the Bay Area and the 24th largest origin and destination (O&D) airport
in the United States. In recent years, Oakland has proven to be a popular alternative to
SFO particularly within the low cost carrier market. The presence of ATA Airlines and
JetBlue has buoyed strong growth in airport passenger numbers in the post-2001 airline
era.

Oakland International draws primarily from ground access trip origins of Oakland and
surrounding Alameda country. Significantly more passengers for OAK originate from
San Francisco compared to SFO passengers who originate from Oakland. This may
reflect the influence of low cost carriers on the travel preferences of Bay Area residents.

In comparison to San Diego airport, OAK is slightly smaller but of a similar O&D ratio.
The purpose split for San Diego is much more business oriented while both are in urban
locations.

Alameda County has a population of 1.22 million and has a fairly moderate density
owing to the geography of the region. BART extensively services the city in addition to


                                          San Diego International Airport Expansion: Sustainability Analysis
  A-4
                                                                                  Appendix A
                                                                                 Case Studies

connections to San Francisco. Approximately one hundred miles of track are located on
the Oakland side of the bay alone, establishing a strong network effect for the system.

Accessibility to the airport is provided by freeway, local bus and the BART via the
AirBART shuttle bus service. The current AirBART service, utilizing low floor buses
which operate every 10 minutes throughout the day providing connections to the
Coliseum/Oakland Airport station with a journey time that can vary widely depending on
traffic conditions from 15 to 60 minutes. Events at the Oakland Coliseum can also
adversely affect journey times, as well as making navigation through the BART station
more difficult for air passengers. There are advanced plans for an automated people
mover to be introduced to serve the 3.2 miles route, which could open around 2011.

Success Factors

The long running AirBART is one of the most successful public transport airport ground
access services within the United States. Established in 1985, recent surveys have
suggested a mode share of up to eight percent.

Ridership of the service may be explained by a number of reasons:

     High visibility of service, with dedicated vehicles with ample baggage room
     High frequency, high reliability and relatively fast service to downtown, particularly
     in high traffic.
     Robust BART network in place throughout Oakland with a comparatively high
     density of track and stations per capita. This results in a readily accessible service for
     a higher proportion of the population.
     High share of price sensitive passengers as a result of low cost carrier presence at
     OAK.
The relative success of the AirBART service has been despite circumstances which might
otherwise have proven to be barriers to success. The non-integrated nature of the service,
both in terms of ticketing and the required inter-modal connection lessens the perceived
convenience. Further, once on BART, the rolling stock is non-dedicated and air
passengers must compete for space alongside commuters. On the positive side, the
network effect of the BART system throughout Oakland strongly augments the
effectiveness of the AirBART service by making it attractive to travelers with
destinations through a significant part of the Oakland area..




                    :
San Diego International Airport Expansion: Sustainability Analysis
                                                                                          A-5
Appendix A
Case Studies




Portland, OR (PDX)

Context

Portland International Airport (PDX) is a significant port in the northwest providing
flights to major air hubs, smaller regional centers and increasingly, direct flights to
overseas destinations. Total international passengers for year on year FY2007 grew by 13
percent with strong growth also in national passenger volumes. It is also the 27th largest
O&D airport within the United States, with a ratio of 91 percent to total passengers. This
proportion is similar to SDIA.

PDX faces negligible levels of competition for commercial services and accounts for
approximately 90 percent of passenger air travel for Oregon.

Portland is a moderately dense city with a population of around 2.3 million within the
metropolitan area. It is the second most populous US city in the Northwest after Seattle
with a strong reputation for engaged urban planning and positive investment in public
transport.

The Metropolitan Area Express (MAX) is a light rail system servicing the greater metro
area of Portland (Figure A-2). With four lines extending from the city center the system
enjoys a high level of public support, with one of the highest levels of ridership for a light
rail system within the United States. The system shares many similarities with the San
Diego trolley system. They are each distinct standalone light rail systems rather than a
part of a larger subway network; San Diego has the highest level of ridership for a
standalone system in the U.S. with Portland second. Further, both systems have three
metro lines, with the miles of track, number of stations and distribution of network to the
population being very similar.




                                           San Diego International Airport Expansion: Sustainability Analysis
  A-6
                                                                               Appendix A
                                                                              Case Studies

                        Figure A-2: Portland MAX Light Rail Network




Source: Portland TriMet


Success Factors

The airport is accessible by an adjacent freeway and by light rail, with the Red line
linking PDX to the downtown in less than 30 minutes. Constructed in 2001 in response to
heavy traffic congestion along the connecting highway, the service enjoys a modal share
to the airport of over six percent.

The level of mode split may be attributed to a number of factors:

     The MAX system is a well regarded and highly patronized service, with strong
     positive brand recognition.
     Fares are simple and extremely competitive compared to alternate modes of ground
     transportation from the airport.
     Ticketing and services are integrated within the wider Portland public transport
     ticketing systems.
     The MAX is strongly integrated with local land use plans and the urban environment.
A number of factors may work against the utilization of the MAX service. The light rail
is non-dedicated and has no additional accommodating services or specific luggage space
for air passengers. This may be significant, particularly during peak periods, at times
when commuter usage of the line is likely to be at its highest. However it is asserted that
the cumulative effect of strong public support for the MAX system and its effectiveness
in connecting the airport and a high proportion of the population through a wholly
integrated service more than compensates for these factors.



                    :
San Diego International Airport Expansion: Sustainability Analysis
                                                                                        A-7
Appendix A
Case Studies



Chicago, IL (ORD)


Context

Chicago O’Hare International Airport (ORD) is the second largest airport by passenger
volumes both in the United States and internationally with approximately 76 million
passengers passing though its gates annually. Further, the airport is one of the largest
international gateways within the country servicing over 60 international destinations. As
such, it places third in terms of volume of domestic O&D passengers, behind Las Vegas
and Los Angeles. The city of Chicago is the third largest city in the U.S. with a
population in excess of nine million people.

Chicago O’Hare is well connected to the wider highway network in Chicago and by rail
through the metro rail system (termed ‘L’) operated by the Chicago Transit Authority
(Figure 0 3). The Blue line of the ‘L’ terminates at O’Hare and runs 24 hours a day from
the airport through downtown Chicago. The service is also used by commuters. It does
not have special luggage provision for air passengers and is not branded as an airport
shuttle. Nonetheless, the service frequency and fare makes it an attractive option for those
with a destination along the route. Once through the downtown area, the line continues
into the south-western suburbs of the city or connections can be made for other areas of
the city. However, travel times from these locations are such that it would be an
unattractive option for most air passengers.




                                          San Diego International Airport Expansion: Sustainability Analysis
  A-8
                                                                                   Appendix A
                                                                                  Case Studies

                        Figure A-3: Chicago CTA Metro Rail Network




          Source: Chicago Transit Authority

Success Factors

For trips distant from the city center, taxi and private car quickly become the preferred
modes. Ridership on the rail service thus suffers for a number of reasons:

     The urban sprawl of much of Chicago makes effective public transit provision
     difficult and particularly limits the attractiveness of the service outside the specific
     corridors in which it operates.



                    :
San Diego International Airport Expansion: Sustainability Analysis
                                                                                           A-9
Appendix A
Case Studies

   Travel times for door-to-door in downtown Chicago are worse than road based modes
   in off peak. In peak travel times when trip times are most likely to be competitive,
   the trains are likely to be crowded with commuters
   The service does not operate dedicated rolling stock or have any branding that
   associates the service with the airport, despite good signage and good levels of access
   from the airport terminals.
   Air passengers must compete with commuters for space on the trains, particularly
   during peak periods when the service can be crowded.
   The service suffers from the problem of not offering competitive journey times for
   many travelers, and from having to share highly utilized commuter train services. The
   system is inexpensive and frequent, yet not ideal for many airport access trips.



St. Louis, MO (STL)


Context

Lambert - Saint Louis International Airport (STL) is the largest airport in the state of
Missouri. Much has changed since 2001 when the airport operated at twice present day
capacity. A downturn in the air travel market, airline bankruptcy and acquisitions as well
as service cut backs have strongly affected passenger volumes. Recent trends suggest the
airport is rebounding, though far more slowly than the initial decline.

A moderately densely populated city, St Louis lies at the center of Greater St Louis, a
sprawling region which encompasses several counties within both the states of Missouri
and Illinois. The metropolitan region is the 18th largest in the U.S. with approximately 2.8
million residents.

Metrolink is the light rail public transport system which operates throughout greater St
Louis. It is predominantly one line running east-west across the city, traversing the
Mississippi River and the state border. An additional line was introduced in 2006, but is
only around one fifth the length of the major line.

In comparison to the trolley system of San Diego, the linear nature of the St Louis service
limits its attractiveness to passengers originating from locations distant from the rail
corridor. Unlike San Diego, there are no network benefits from interchanging from other
rail services, although bus feeder services are provided.

The airport is accessible by an adjacent freeway and by rail, fully integrated within the
Metrolink system (Figure A-4). STL is served by two light rail stations located within the

                                          San Diego International Airport Expansion: Sustainability Analysis
 A-10
                                                                                 Appendix A
                                                                                Case Studies

airport itself in both the Main and East Terminals, with regular service direct to
downtown St Louis.

                            Figure A-1: St Louis Metro Network Map




Source: St. Louis Metro Service



Success Factors

The airport link was opened in 1994, one year after the section between North Hanley
and 5th & Missouri stations. The overall service initially exceeded predicted ridership
levels. Current modal share from the airport is approximately five percent.

This share may be attributed to a number of factors:

     The Metrolink could not adequately be described as a network, there is effectively
     only one line.
     This poor geographical distribution of service is reflected in both low miles of track
     and stations per capita.
     The cost of competing transportation services, while somewhat higher than light rail,
     is still not very high in absolute terms and yet offers convenience of door-to-door
     travel.
     The service operates on non-dedicated rolling, nor does it have specific branding
     associating the service with the airport.
It is contended that the success of this service is hampered by the limited distribution of
the light rail system. The single linear line is not in close proximity to a majority of the
population within St Louis. However, for trips to the city center, the service can offer
moderately competitive travel times (particularly in peak periods) at low cost.




                    :
San Diego International Airport Expansion: Sustainability Analysis
                                                                                        A-11
          San Diego International Airport Expansion
          Sustainability Analysis




          Appendix B - Transportation
          Modeling




6189001
                             Appendix B – Transportation Modeling

Overview
Transportation modeling is a quantitative framework that allows for predictions to be
made of the likely impact on travel demand to changes in the transport tier system. In the
case of SDIA, these may include improved transit or road access to the existing terminals,
or a concept such as the Lindbergh ITC which may substantially improve airport access
for air passengers and employees by providing ready access to the Trolley, Coaster and
Amtrak rail services.

It is typical practice with airport surface access models to consider only trips made to the
airport. It is possible that trips made away from the airport would be somewhat different
(for example, there would be a ‘meet & greet’ component). However, consistent with the
majority of other airport surface access studies it is assumed here that the inward and
outward legs are symmetrical. Results are presented in Section 2 based on multiplying
modeled mileage “to” the airport by a factor of two.

The modeling approach used a discrete choice modeling framework. Discrete choice
models are probabilistic in nature. That is, they do not assume that an individual will
definitely chose a particular mode. Rather, these models identify the probability that an
individual will choose each mode available. So, for example, an individual living in
downtown San Diego who owns a car may have a probability of 40 percent of driving
their car to the airport, 20 percent getting dropped off by a friend or colleague, 20 percent
of taking a taxi and 10 percent by the airport flyer bus. These probabilities would differ
depending on the purpose of the journey (business or non-business) and, perhaps, their
socioeconomic characteristics (such as income). The probabilistic nature of these models
is a key benefit of the models. Travelers make mode choice decisions based on a host of
factors, many of which are difficult to observe and which may vary from day to day (e.g.,
weather or availability of colleagues for dropping off).

Discrete choice models work on the basis of utility differences, that is, how different one
service is from another. Within the family of discrete choice models, the logit
formulation is most widely used, and has been used in this study. Consider as an example
two travelers. One lives close to the airport and has a choice between two otherwise
identical trips except one of which takes 10 minutes and the other takes 11 minutes. A
second traveler may live further from the airport such that they have two otherwise
identical alternatives that take 60 and 61 minutes respectively. Logit models would
predict in both cases that the probability of selecting the faster trip would be 26 percent.
Intuitively, we may expect that the one minute time difference would make little

San Diego International Airport Expansion: Sustainability Analysis
                                                                                       B-1
Appendix B
Transportation Modeling

difference in the longer example and so the probability would be closer to 50 percent in
this case. However, because only the differences are important (one minute in both case)
the logit model does not consider the absolute travel times.

Experience from airport ground transportation studies elsewhere has suggested that
dividing the utility by the square root of the trip distance helps to correct this problem.
So, in the example above, if the shorter trip was 5 miles and the longer trip was 30 miles
then the probability of choosing the faster journey for the short distance traveler would be
39 percent while for the longer distance traveler the probability would be 45 percent. This
would result in probabilities that would more reasonably represent intuition, and evidence
from studies elsewhere.

Data Availability
The quality of any model, and the robustness of the forecasts are dependent on the
availability of appropriate data and the assumptions made. These are now summarized
and referred to as required throughout the report.

Modeling future travel choices requires data about current choices and travel conditions
as well as forecasts about how these conditions will alter in the future. High quality data
is essential to robust model forecasts, and data limitations impose significant caveats on
interpreting model outputs. Likewise, the further into the future that forecasts are made,
the greater the uncertainty. It is, for example, particularly difficult to predict the price of
fuel in the long run. A number of data sources were used in the present modeling effort:

    SDCRAA
    - Airport Master Plan Environmental Impact Report (EIR)
        •   Current and future background traffic forecasts
        •   Traffic distribution
    - Transit Demand and Access Study (draft: November 2007)
    - Passenger Satisfaction Survey (2007 – 2Q Results)
    SANDAG Regional Transportation Model
    - Mode Choice Model documentation
    - Parameters
    - Level-of-service (road travel times)
    MTS/NCTD
    - Timetables
    - Fares

                                            San Diego International Airport Expansion: Sustainability Analysis
  B-2
                                                                                 Appendix B
                                                                     Transportation Modeling



     Other sources
     - Google Maps – road travel times, route assignment.

These data sources were compiled wherever possible to a base year of 2005 consistent
with the EIR. For testing major airport developments such as the Lindbergh ITC concept,
a horizon year of 2030 was used; it is assumed this would be a time by which should such
a concept be developed it would be fully in operation. Future passenger traffic forecasts
and background traffic levels for 2030 were based on those used in the EIR to ensure
consistency.

Assumptions
Due to a lack of data in some instances, and the desire to undertake a top level analysis a
number of assumptions were required. These assumptions are described in further detail
throughout this chapter, but are summarized in Table B-1. Where appropriate an
indication is provided of the likely impact these assumptions have both on the modeling
accuracy and, if relevant, in which direction these may affect the results.




                    :
San Diego International Airport Expansion: Sustainability Analysis
                                                                                      B-3
Appendix B
Transportation Modeling




                         Table B-1. Summary of Modeling Assumptions

 Assumption                           Importance       Effect

 Passenger and airport employee       ●●●●●            Very likely to overstate travel distances of
 distributions are identical                           employees and understate transit mode share
                                                       potential
 Mode share model parameters          ●●●              Specific local effects not accounted for such as
 derived from other cities                             passenger type mix, attitudes towards existing
                                                       transit alternatives.
 78 zone system                       ●●●              Relatively coarse zoning system, may
                                                       understate transit demand in some zones and
                                                       overstate in others based on assumptions
                                                       regarding access to transit services.
 Interchange penalties                ●●               May tend to underestimate transit demand on
                                                       some corridors where quality of interchange is
                                                       high (e.g. America Plaza) and overstate on
                                                       others where interchange quality is low.
 Airport employee forecasts for       ●                If economies of scale are less or greater than
 2030                                                  predicted as air passenger numbers grow then
                                                       total employee numbers may differ.
 Distribution of air passengers and   ●●●●             Increased urban density, particularly at locations
 employees does not change                             currently well served by transit (such as much of
 between 2005 and 2030                                 the downtown and waterfront regeneration
                                                       areas) may tend to increase transit share to the
                                                       airport. Conversely, greenfield developments on
                                                       the outskirts of the city may decrease the transit
                                                       share.
 No changes in transit or highway     ●●●              This assumption assumes that transit services
 journey times across the day                          operate across the day and that travel times both
                                                       by transit and car do not change. This
                                                       overestimates transit demand if travelers wish to
                                                       access the airport outside existing transit service
                                                       hours. Conversely, increased highway travel
                                                       times during peak periods may tend to increase
                                                       transit share.
 Real car and transit costs remain    ●                It is assumed that there will be no real change in
 unchanged                                             car or transit costs to 2030. This further implies
                                                       no change in relative costs between the two
                                                       modes. If oil prices are very much higher in
                                                       2030 then this assumption will tend to
                                                       underpredict transit share; conversely, if transit
                                                       fares increase faster than car costs then it will
                                                       tend to overstate the transit share. This is more
                                                       important for airport employees (who are more
                                                       cost sensitive) than for air passengers.
 Transit networks do not change       ●●               No changes in the transit network will occur (for
 unless stated                                         example, cancelling bus routes or altering
                                                       service frequencies). This may tend to
                                                       understate the transit share if, for example, the
                                                       Lindbergh ITC were to become a hub for trolley
                                                       and bus services to the region. The proposed
                                                       LRT/BRT extension from Old Town to University
                                                       City is therefore not included.

                                               San Diego International Airport Expansion: Sustainability Analysis
  B-4
                                                                                             Appendix B
                                                                                 Transportation Modeling

The modeling process is illustrated in Figure B-1.

                          Figure B-1. Flow Chart of Modeling Process




Demand
For consistency with the EIR, the same air passenger forecasts for 2030 are assumed.
This represents the unconstrained low growth forecast for the airport. Total origin &
destination air passenger and airport employees are summarized in Table B-2.

                    Table B-2. O&D Air Passengers and Airport Employees
                                                   Air passengers
Year                                                                                Airport employees
                                      Annual (m)                     Avg Daily
2005                                      16.7                        45,830        5,000
2030                                      27.0                        74,199        6,467



Based on data provided by SDCRAA, it was assumed that there were 5,000 airport
employees working on or in the immediate vicinity of the airport site 1 . This was
assumed to include off-airport parking and car rental facilities directly to the north of the
airport site. Experience at SDIA and elsewhere has indicated that the number of airport
employees relative to air passengers tends to decrease as airports increase in size due to
greater efficiencies of scale. In the absence of employee forecasts it was assumed that the


1
    The draft Airport Transit Plan assumes 4,900 employees.
                    :
San Diego International Airport Expansion: Sustainability Analysis
                                                                                                    B-5
Appendix B
Transportation Modeling

number of passengers per employee would increase by 25 percent between 2005 and
2030, giving 6,467 employees in 2030.

The availability of transit to air passengers and airport employees alike will be dependent
on the level of service provided at the times of day when passengers wish to travel. The
first weekday service on the Blue line of the trolley currently passes through Middletown
at approximately 04:50 southbound and 05:35 northbound. The last service of the day
leaves in the southbound direction at 11:50 while the last northbound service stops at
01:48. Similarly, the first weekday 992 bus service arrives at the commuter terminal at
05:18 and the last service departs at 00:21. The existing services provide coverage across
much of the day, including when the airport is busiest. In 2005 there were no aircraft
movements between midnight and 04:00 after which there were seven aircraft
movements before 06:00. In the evening, there were four flights between 23:00 and
midnight. The absence of flights at night is largely due to a curfew that is imposed
between 11:30 pm and 06:30 am. As the airport has minimal overnight operations it is
likely that the trolley system would not need to extend its hours to facilitate air passenger
and airport employee movements 2 . On weekends however the service frequency is
reduced, particularly on the Coaster which operated a very reduced Saturday service and
no service on Sundays.

The base year is taken as 2005 and future year as 2030. It is assumed that growth in air
passengers is distributed evenly across all zones.

Background Traffic
A significant number of developments are in various stages of construction, development
or planning in the vicinity of the airport. These developments will all have an impact on
background (non-airport) traffic growth in the area, which in turn will adversely affect
traffic congestion. In order to maintain consistency with the DEIR, the background
traffic forecasts used as part of that analysis were used in the present study. These
forecasts were in turn based on SANDAG Series 10 forecasts. A number of
developments are incorporated, such as those identified in:

      Naval Training Center/Liberty Station Precise Plan EIR

      North Embarcadero Visionary Plan Final EIR

However, as noted in the DEIR (Section 5.3.1.4), a number of developments were not
explicitly included in the traffic forecasts (such as the CCDC Master Plan and Woodfin
Suites Hotel). However, the general plan zoning assumed for these areas results in the

2
 This assumption assumes that airport employees do not need to be present at the airport when there are
not aircraft movements. This is clearly incorrect, but given the top level nature of the modeling this is
considered a reasonable assumption.
                                                  San Diego International Airport Expansion: Sustainability Analysis
    B-6
                                                                                                Appendix B
                                                                                    Transportation Modeling

generation of traffic equivalent or greater than that predicted by the EIRs for these sites.
On this basis, given that proxy traffic generation was assumed for these zones, and
consistency with the DEIR, the background traffic forecasts for the DEIR were used in
this study. While specific developments may introduce additional traffic onto particular
areas of the local road network and may have particularly important localized impacts on
airport traffic, such impacts could not reliably be forecast as part of the present study. In
addition, it was felt that these impacts would not materially affect the outcome of
analysis.

An error was identified in the DEIR in reporting very significant decreases in non-airport
traffic on Rosecrans Street after 2015. This error resulted in an improvement in LOS at
2030 compared with 2005 even after substantial increases in airport related traffic were
accounted for. As a result, Series 11 traffic forecasts were used for Rosecrans Street.

Distribution
The distribution of trip origins is critically important to understanding the current and
future travel patterns, as the origins will influence which roads will most likely be used to
access the airport and the availability of transit alternatives. The EIR reported traffic
origins across a 78-zone system based on the SANDAG Regional Transportation Model.
This distribution is given in Table B-3 as are the assumed travel times.

                          Table B-3.Distribution of SDIA Traffic by Origin

                                                                                         Current Terminal

                                                                                 Car       Transit    Number of
                                Distribution       Distance          Distance
                                                                                travel      travel      transit
                                      (%)              to               to
         Location                                                               time        time     interchanges
                                                    current          proposed
                                                                                (mins)     (mins)
                                                   terminal          ITC (mi)
                                                      (mi)


 32nd St Naval Station                0.1              7.0             6.1       18.0        35              1

 Balboa Park                          0.0              4.2             3.4       13.2        28              1

 Barrio Logan                         0.1              5.5             5.5       16.8        28              1

 Black Mountain Ranch                 0.6             28.2             26.0      46.8        56              1

 CARLSBAD                             5.8             35.2             33.0      48.0        74              1

 Carmel Mountain                      0.5             21.7             19.4      34.8        84              1
 Ranch

 Carmel Valley                        0.8             20.6             18.4      33.6        95              2

 Center City                          8.8              3.3             2.3       12.0        16              0
                    :
San Diego International Airport Expansion: Sustainability Analysis
                                                                                                            B-7
Appendix B
Transportation Modeling


                                                                                 Current Terminal

                                                                        Car         Transit        Number of
                          Distribution   Distance     Distance
                                                                       travel        travel          transit
                              (%)           to            to
          Location                                                      time          time       interchanges
                                         current     proposed
                                                                      (mins)         (mins)
                                         terminal     ITC (mi)
                                           (mi)


 CHULA VISTA                  4.6          11.8          10.7           22.8           40               2

 Clairemont Mesa              1.6          11.2          8.9            20.4           39               2

 College Area                 0.6          12.1          11.3           25.2           52               1

 CORONADO                     1.1          9.2           8.2            22.8           51               1

 DEL MAR                      0.3          20.7          18.5           34.8          102               3

 Del Mar Mesa                 0.2          20.9          18.7           34.8           89               2

 East Elliott                 0.0          18.6          16.2           36.0           65               2

 EL CAJON                     2.4          19.4          19.5           31.2           58               2

 ENCINITAS                    1.6          26.5          24.4           39.6           60               1

 ESCONDIDO                    2.9          33.8          31.5           50.4           62               1

 Fairbanks Country Club       0.0          22.9          20.7           37.2           56               1

 Flower Hill                  0.0          21.5          19.3           32.4           56               1

 Greater Golden Hill          0.3          6.0           5.0            14.4           33               1

 Greater North Park           1.0          6.0           4.9            15.6           41               1

 Harbor                       0.0          7.6           7.4            18.0           36               1

 IMPERIAL BEACH               0.4          17.4          16.3           28.8           66               1

 Kearny Mesa                  1.9          11.6          9.3            21.6           52               1

 La Jolla                     1.0          13.4          11.2           26.4           65               1

 LA MESA                      1.3          14.2          13.1           25.2           55               1

 LEMON GROVE                  0.5          12.0          11.0           22.8           50               1

 Linda Vista                  0.5          7.7           5.4            18.0           52               1

 Lindbergh Field              1.2          1.0           1.0            6.0                            

 Mid-City: City Heights       1.0          8.7           7.7            18.0           56               1

 Mid-City: Eastern Area       0.7          9.9           8.9            21.6           51               1

 Mid-City: Kensington-        0.3          11.7          10.7           21.6           55               1
 Talmadge

                                            San Diego International Airport Expansion: Sustainability Analysis
  B-8
                                                                                                Appendix B
                                                                                    Transportation Modeling


                                                                                         Current Terminal

                                                                                 Car       Transit    Number of
                                Distribution       Distance          Distance
                                                                                travel      travel      transit
                                      (%)              to               to
          Location                                                              time        time     interchanges
                                                    current          proposed
                                                                                (mins)     (mins)
                                                   terminal          ITC (mi)
                                                      (mi)


 Mid-City: Normal                     0.3             10.7             9.7       24.0        47              1
 Heights

 Midway-Pacific                       0.5              4.5             2.5       13.2        11              1
 Highway

 Mira Mesa                            3.1             19.8             18.1      33.6        81              2

 Miramar Air Station                  0.1             14.3             10.0      26.4        55              1

 Miramar Ranch North                  0.4             20.8             18.4      34.8        70              2

 Mission Bay Park                     1.5              6.0             5.9       19.2        48              2

 Mission Beach                        0.4              5.9             5.9       19.2        41              2

 Mission Valley                       4.1              7.0             4.2       18.0        46              1

 NATIONAL CITY                        1.1              8.8             7.7       16.8        36              1

 Navajo                               1.2             18.3             17.3      30.0        69              2

 NCFUA Subarea 2                      0.0             16.7             14.0      28.8        88              2

 Ocean Beach                          0.3              4.1             5.0       13.2        13              0

 OCEANSIDE                            4.1             38.6             36.9      54.0        78              1

 Old San Diego                        0.1              4.9             2.1       13.2        15              1

 Otay Mesa                            1.0             16.1             15.0      26.4        53              1

 Otay Mesa-Nestor                     0.8             19.2             14.9      32.4        56              1

 OUTSIDE SD COUNTY                    3.6             60.0             60.0     200.0                       

 Pacific Beach                        1.0             10.3             8.2       22.8        49              1

 Pacific Highlands                    0.2             22.6             20.4      43.2        89              2
 Ranch

 Peninsula                            2.2              3.7             5.2       12.0         7              1

 POWAY                                1.3             24.3             21.9      40.8        123             2

 Rancho Bernardo                      1.4             25.3             25.3      37.2        55              1

 Rancho Encantado                     0.0             23.7             21.4      46.8        129             2

                    :
San Diego International Airport Expansion: Sustainability Analysis
                                                                                                            B-9
Appendix B
Transportation Modeling


                                                                                 Current Terminal

                                                                        Car         Transit        Number of
                          Distribution   Distance     Distance
                                                                       travel        travel          transit
                              (%)           to            to
         Location                                                       time          time       interchanges
                                         current     proposed
                                                                      (mins)         (mins)
                                         terminal     ITC (mi)
                                           (mi)


 Rancho Penasquitos           0.8          20.9          24.0           34.8           79               1

 Sabre Springs                0.2          21.5          19.2           34.8           77               1

 SAN MARCOS                   1.8          37.5          35.2           54.0           62               1

 San Pasqual                  0.0          37.7          35.4           58.8                           

 San Ysidro                   0.6          19.5          18.5           30.0           53               1

 SANTEE                       1.2          23.3          23.3           40.8           75               2

 Scripps Miramar Ranch        0.5          17.7          15.4           31.2           68               1

 Serra Mesa                   0.4          9.8           9.0            21.6           53               2

 Skyline-Paradise Hills       0.8          12.7          14.1           26.4           52               1

 SOLANA BEACH                 0.5          22.2          20.0           33.6           56               1

 Southeastern: Encanto        0.6          10.6          9.5            22.8           44               1
 Neighborhoods

 Southeastern:                0.7          6.2           5.2            15.6           34               1
 Southeastern SD

 Tierrasanta                  0.5          15.3          13.2           26.4           54               1

 Tijuana River Valley         0.0          18.8          17.8           32.4           52               2

 Torrey Highlands             0.1          24.0          21.8           36.0                           

 Torrey Hills                 0.1          16.7          14.5           30.0           88               2

 Torrey Pines                 0.4          16.7          14.5           28.8           88               2

 UNINCORPORATED              13.2          20.0          20.0           34.3                           

 University                   3.0          13.2          11.0           22.8           55               2

 Uptown                       1.2          3.3           1.8            10.8           21               1

 Via De La Valle              0.0          23.9          21.7           37.2           56               1

 VISTA                        2.1          44.1          41.9           61.2           74               1

 Weighted Average                          19.1          17.8           37.2          43.7




                                            San Diego International Airport Expansion: Sustainability Analysis
 B-10
                                                                                             Appendix B
                                                                                 Transportation Modeling

For modeling purposes, the geographic center of each of these zones was used from
which to define the travel times to SDIA. In the case of the trips from unincorporated
areas and outside San Diego county it was assumed that private car was the only mode
alternative available. This is a conservative assumption – it is possible that some
travelers, for example who are traveling from south LA, may have the option of using the
Amtrak service. Equally, this assumption excludes the possibility of construction of the
proposed Californian High-Speed Rail (HSR) link, which would potentially connect
Sacramento, San Francisco and Los Angeles directly to San Diego, possibly with a stop
at an airport-related ITC. It is, however, unlikely that residents of Los Angeles or
northern California would fly from SDIA even with a direct high speed rail link given
their proximity to larger airports in central and northern California. More critically, as
13.2 percent of movements come from unincorporated areas assuming none of these
journeys could use transit is a highly conservative assumption.

Critically, it was not possible to divide the distributions by air passengers and airport
employees. These trip distributions are likely to be very different, with the latter more
concentrated in the vicinity of the airport.

Future growth in air passenger demand will most likely not be generated equally across
the region according to the current proportions. However, in the absence of forecast data
on future population growth and passenger demand by zone, it was assumed that future
demand would be distributed in the same manner as currently.

Mode Choice
The mode choice model takes the input demand from air passengers and airport
employees for travel to the airport and estimates the likelihood that they will chose each
of nine modes listed in Table B-4. ‘Kiss & Fly’ refers to escort trips to the airport where
the air passenger receives a ride in a private car. This mode can be particularly important
for traffic forecasting as every air passenger movement will generate two car movements
(an inward and outward leg).

                                  Table B-4.Modeled transport modes
                                     Mode       Description
                                      1         Private car – park on-airport
                                      2         Private car – park off-airport
                                      3         Private car – Kiss & Fly
                                      4         Rental car
                                      5         Taxi
                                      6         Shared van
                                      7         Transit – Bus
                                      8         Transit – Trolley
                                      9         Transit – Coaster


                    :
San Diego International Airport Expansion: Sustainability Analysis
                                                                                                  B-11
Appendix B
Transportation Modeling

Taxi and limousine services were treated together in the analysis although the cost profile
of limousine services would be expected to be different. The latter was considered
sufficiently minor that the services could be combined for forecasting purposes. Cycling
and walking were not included as potential access modes, although there may be some
potential for such low impact modes, particularly for airport employees who live in the
vicinity of the airport.

The probability of choosing a particular mode for a trip to the airport will depend on a
host of factors, including:

   Trip characteristics
   Time
   In-vehicle time (IVT)
   Access time (transit)
   Egress time
   Waiting time (transit)
   Transfer time (transit)
   Cost
   Fuel cost
   Tolls
   Fares
   Purpose
   Business, non-business
   Individual/group characteristics
   Income
   Traveling party size
   Duration of stay away.
The factors listed above are easily quantified and were derived from the existing
SANDAG regional transportation model and public domain sources.

Level-of-service Data
Level-of-service data are the travel times and costs by the various transport modes.
These were compiled from various sources, including Google Maps, MTS, NCTD and
SANDAG. The data represented current (2007) conditions apart from the SANDAG
data, which represented 2004 conditions. For the purposes of the present analysis the
data was considered to be equivalent to the 2005 base year for modeling purposes.



                                          San Diego International Airport Expansion: Sustainability Analysis
 B-12
                                                                                            Appendix B
                                                                                Transportation Modeling

Parking
On-airport parking was defined as the parking provided directly in front of the terminal
buildings by SDCRAA. Off-airport parking refers to sites operated by SDCRAA (three
SAN Park sites) and by other operators (such as Aladdin Parking and San Diego Airport
Parking). Average daily costs at these sites were obtained and used to derive the cost
functions shown in Figure B-2. For all durations longer than one day the off-airport
parking sites are cheaper. However, in the generalized cost calculations the additional
time and hassle associated with needing to take a shuttle bus between the off-airport
parking site and the terminals is accounted for, thereby making parking on-airport
somewhat more attractive than a simple cost calculation alone would infer.

                                      Figure B-2. Parking Cost Functions


                               $800
                                          On-Airport
                               $700       Off-Airport

                               $600

                               $500
                        Cost




                               $400

                               $300

                               $200

                               $100

                                $0
                                      0           5     10      15    20   25        30

                                                               Days




SDCRAA charges a fee for the annual rental of airport employee parking. It is unlikely
however that this charge is passed on by many employers to employees. For the purposes
of the present study it was assumed that on average employees pay $2 per day to park at
the airport. This charge may or may not be passed on in reality, rather it acts to represent
the disutility associated with driving to the airport.

Parking search times and access to the terminal was assumed to be 10 minutes for air
passengers and 5 minutes for airport employees. These times were applied only to
parking on-airport; for off-airport parking a schedule of shuttle bus services of 10
minutes was assumed and a journey time of 7 minutes between the off-airport parking
and terminal was assumed. In addition, an interchange penalty of one-third of the transit
value was assumed; this was lower than that for transit on the assumption that the shuttle
waiting facilities would be of high standard and there would be no confusion as to the
                    :
San Diego International Airport Expansion: Sustainability Analysis
                                                                                                 B-13
Appendix B
Transportation Modeling

destination of the shuttle service. The result of this series of assumptions is that parking
off-airport has a disincentive equivalent to 17 minutes of travel time (as shuttle bus wait
time is valued at twice in-vehicle time).

Taxi and Shared Van
Cost profiles for local taxi and shared van operators were obtained and functions derived
based on distances traveled to obtain trip costs; as shown in Figure B-3. Taxi costs were
assumed to increase linearly with distance traveled while for shared vans the rate
increased at an exponential rate.

                           Figure B-3. Taxi and Shared Van Cost Profiles

                 $90

                 $80
                                                                            Taxi
                 $70
                                                                              y = 2.6x + 2.4
                 $60

                 $50
          Cost




                                                                    Shared van
                 $40
                                                                           y = 14.012e0.0425x
                 $30

                 $20

                 $10

                 $0
                       0         5       10       15           20            25             30

                                                Miles




Transit Networks
The transit level-of-service was based on timetables for existing MTS, NCTD and
Amtrak services in the region. Where there would be multiple transit alternatives,
assumptions were made regarding the most likely alternative.

Transit fares are based on one-way fares. This is a reasonable assumption given that no
discount applies for return fares. Period and bulk purchase tickets are available, and
would reduce the cost to regular users. However, for the purposes of the present analysis
it was assumed that the uptake of these alternative tickets was sufficiently small so as to
be neglected.



                                              San Diego International Airport Expansion: Sustainability Analysis
 B-14
                                                                                 Appendix B
                                                                     Transportation Modeling

Time-of-Day Variation
The current transit fare pricing strategy does not vary by time-of-day. However, traffic
congestion on a number of key corridors (such as the I-5 and I-8) during peak periods
would likely increase journey times by road-based modes compared with off-peak
periods.

Modeling Framework
How these factors are perceived, and particularly how ‘valuable’ travelers consider their
trip time to be are critical to the modeling process. The concept of value of time is very
important in understanding the mode choices of air passengers, as they typically highly
value the time required to access the airport as they have a fixed flight departure time. As
the model is highly sensitive to the value of time assumptions, considerable effort was
expended in determining appropriate values of time for the study.

Value of Time
It is widely recognized that air passengers tend to have higher values of time than other
travelers. There may be several reasons for this, including:

     An explicit need to be at the airport at a particular time
     Higher average incomes of air passengers compared with the wider population
     Higher proportion of business trips made by aircraft compared with other modes
     High cost of air travel, resulting in lower cost sensitivity for ground transportation as
     it may form a small part of the total travel cost.
Experience from studies at airports in the U.S., Europe and Australia have all indicated
that air passengers have a value of time that is typically at least twice that of other
travelers. Similarly, these studies have indicated that air passengers making business trips
tend to value their time much more highly than passengers making other types of trips
(e.g. holidays, visiting friends and relatives). Typically, business travelers tend to value
their time at about twice the rate of non-business travelers, although the evidence
indicates wide variation between sites.

The implication of high values of time exhibited by air passengers to effective ground
transportation policy is profound. For example, high values of time imply that travelers
would significantly respond to changes in the relative travel times between modes, such
that even marginal time savings by one mode would be highly regarded. Conversely,
travelers would be relatively insensitive to travel costs. So, for example, decreasing
transit fares would not result in significant changes in transit mode share unless combined
with improvements to travel times. In the SDIA context, this implies that for a mode to
be attractive it must offer travel time savings; cost savings alone are unlikely to lead to
                    :
San Diego International Airport Expansion: Sustainability Analysis
                                                                                         B-15
Appendix B
Transportation Modeling

significant increases in use of that mode. The relatively cheap cost of taxis (by
international standards) mean that transit may not offer sufficiently substantial cost
savings for many travelers to make it attractive, particularly where the travel times are
uncompetitive. This is likely to be the case for travelers who do not have ready access to
a convenient transit alternative.

SDIA’s proximity to the downtown area and much of the suburban area means that car
trips are relatively short and, importantly, that taxi fares are low compared with airports
in other cities (where the airport is often located a greater distance from the population
center). Furthermore, in cities with successful airport rail links, there is often a
disproportionate amount of travel to the downtown areas in some of the more successful
international examples that is not present in more dispersed cities such as San Diego,
where only around 9 percent of airport trips originate in the downtown area.

More difficult to quantify, travelers will tend to highly value the reliability of their travel
time; that is, they place a high valuation on knowing their chosen method of transport to
the airport will arrive in an expected time. How this should be valued is a subject of
much research and so is not explicitly accounted for in this analysis, although indirectly it
may be incorporated in the mode specific constants if a particular mode is perceived as
unreliable.

The values of time (VOT) of air passengers were established based on existing studies at
airports elsewhere in the U.S. and professional judgment. Table B-5 summarizes the
VOTs reported in the literature after making two adjustments:

   RPI adjustments to obtain 2005 prices
   Factoring by median household income growth with an elasticity of 0.8, consistent
   with UK value of time experience.


         Table B-5.Air Passenger Values of Time Reported in the Literature
                                                       Values of time (2005 $/hr)
        Study            Year       Region          Employer’s              Non-EB            EB / non-EB
                                                   Business (EB)
California HSR          2006    California                 26                   13                  2.0
Gupta, Vovsha and       2007    New York City              61                   40                  1.5
Donnelly
Harvey                  1987    San Francisco             74
Hess, Polak             2001    San Francisco          93 – 155
Dowling Assoc.          2002    San Jose                  16                    11                  1.5



The wide variation in VOTs is indicative of the techniques used to obtain the values,
analysis procedures, and location-specific factors. Values of time of $50/hr for EB and
                                             San Diego International Airport Expansion: Sustainability Analysis
 B-16
                                                                                 Appendix B
                                                                     Transportation Modeling

$25/hr for non-EB purposes were selected for the present study. These VOTs are broadly
consistent with the range reported in the literature, and are significantly higher than the
value of time assumed for airport employees, as discussed below.

The SANDAG Regional Transport Model used 1/3 of the average wage rate to define the
value of time for commuting purposes. In 2005 value and prices, this corresponds to a
value of time of $6.44/hour . The resulting value of time for employees is around four
times lower than for non-business air passengers and eight times smaller than business air
passengers. These large differentials reflect the much greater sensitivity to time of air
passengers in comparison to airport employees and lower sensitivity to cost.

Access and Wait Time
In addition to travel time in a vehicle (termed in-vehicle time, IVT), travelers typically
must also travel to the vehicle and from it to their destination. In the case of public transit
this may involve a walk or drive to the nearest bus stop or rail station, and then a walk at
the airport to the terminal building. The traveler will more than likely also have to wait
for their bus or train service when at the stop or station. In addition, it may be possible
that a traveler may have to change vehicle in route, for example by transferring between
train services or from a bus to a train. Experience from a wide range of studies elsewhere
indicates that these components of a trip are perceived as more onerous than IVT. For
example, the consensus is that access/egress time is valued at about twice IVT while time
spent waiting for a transit service is valued at three times IVT. These values may differ
somewhat depending on the context - including the quality of waiting facilities at stations
and climatic conditions; however these ratios were deemed reasonable for the current
analysis.

When transferring between transit services, there tends to be an additional disincentive in
addition to the additional wait time as a result of having to wait for the connecting
service. This additional disincentive may be attributed to the disruption to the trip,
‘hassle’ and additional stress involved with having to change service. The magnitude of
this disincentive will depend on the difficulty of the transfer; at relatively small stations
where simply walking across to the other side of a platform is required, the disincentive is
likely to be small, while at larger stations the disincentive may be larger. Furthermore, in
exposed locations, additional qualitative factors such as the prevalent weather conditions,
perceived safety and cleanliness can all play a role. Quantifying such effects is difficult;
however, previous experience would suggest that air passengers tend on average to
associate an equivalent of 20 minutes of IVT with an interchange. To illustrate the
implication of this assumption, consider two bus services, one of which is direct and
takes one hour while another takes 40 minutes but requires a transfer. Assuming no other
differences between the services, and that there would be no waiting required for the


                    :
San Diego International Airport Expansion: Sustainability Analysis
                                                                                         B-17
Appendix B
Transportation Modeling

transfer, both services would be considered equally attractive on the assumption that a
transfer is considered to be equivalent to 20 minutes of IVT.

Airport employees are likely to consider transfer to be less of an impediment because the
stress component is less clear – the traveler probably makes the trip regularly and so is
more aware of where their connecting service would depart from. For this reason, it was
assumed that employees considered a transit transfer to be equivalent to 10 minutes of
travel time, half of that of air passengers.

In summary, the following assumptions were made regarding transit travel times:

   Access time was valued twice as highly as in-vehicle time
   Wait time was valued three times as highly as in-vehicle time
   Interchanges were valued as equivalent to 20 minutes of IVT for air passengers and
   15 minutes for airport employees.
In-Vehicle Times
The travel times by public transit were based on published timetables from the transit
operators (MTS, NCTD and Amtrak). Where there was some variation across the day in
travel times, a weighted-average time was used to represent the average travel time from
each zone to the airport.

Group Size
It is assumed, consistent with other studies, that costs would be distributed among the
traveling group. For this reason, costs such as car costs and taxi fares are divided across
the group. Survey data had indicated that the average group size for business trips is 1.2
while for non-business trips the average group size is 2.1. These group sizes were
assumed in the model.

For the purposes of the traffic analysis the occupancy of a shared van was assumed to be
6 persons and for a local bus 10 persons. These assumptions were based on observation
of vehicles leaving the airport during site visits in November 2007; more extensive
surveys would be warranted to verify these assumptions as part of any future analysis.

Duration of Stay
The duration of stay away was important in the assumption regarding parking costs.
Airport survey data indicated that business travelers spent on average 1.5 days away
while non-business travelers spent on average 3 days. The parking cost assumed for each
trip leg was half of the total parking cost.



                                          San Diego International Airport Expansion: Sustainability Analysis
 B-18
                                                                                 Appendix B
                                                                     Transportation Modeling

Distance
In the chosen generalized cost specification, the level-of-service variables related to
distance (i.e. time and operating cost) were divided by the square root of trip distance.
This is consistent with experience from some airport surface access studies in other
locations, where it was found that this specification increased the accuracy of the model.
The explanation for this improved model fit is that small changes in time or cost on
longer trips would be less significant than for shorter trips.

Headways
Headway is the time between services, so for example the headway for a bus service that
operates at 9:00, 9:20, 9:40 and 10:00 would be 20 minutes. As per standard practice, it
was assumed that the average traveler experiences a wait time equivalent to half the
headway. Real-world experience indicates that below about a 10 minute headway,
travelers tend to just ‘turn up, wait briefly and go’ whereas with longer headways they
plan their trips more carefully to ensure they arrive close to the departure of their service.
For services with large headways such as the Coaster rail services where the average
headway across the day is over 70 minutes, it is unlikely that a passenger would wait at
the station for a period of time equivalent to half the headway (i.e. 35 minutes).
However, there is an indirect disutility associated with the long headways that would tend
to discourage travelers from using the service. For this reason the headway is not capped.

Kiss & Fly
It would be plausible to expect that at least some air passengers would assign a value to
the escorting drivers’ time and perhaps also to the costs associated with driving the car.
Research elsewhere has indicated that air passengers on employer’s business trips tend to
fully consider the drivers’ time to and from the airport as if it were their own time.
Likewise, they also tend to consider the return car cost. For non-employer’s business
trips only the time spent taking the passenger to the airport is considered. In research
undertaken elsewhere, it was found that some 15 percent of air passengers would directly
contributing to the cost of the trip – for this reason in the model non-EB trips are assumed
to incur 15 percent of the return trip car costs.

Zoning System
The zoning system is based on a relatively coarse 78 zones, consistent with survey data
available on air passenger origins. The result is that some important zones, such as
downtown, are represented as a single zone – resulting in coarse assumptions regarding
access times and IVT from this zone.



                    :
San Diego International Airport Expansion: Sustainability Analysis
                                                                                       B-19
Appendix B
Transportation Modeling

Mode-Specific Constants
In addition to the basic travel attributes of time, cost and – in the case of transit – service
headway and transfers, it may be expected that other less readily quantifiable mode
attributes also contribute to selecting a particular alternative. These may include, but are
not limited to:

    Perceived safety, particularly at night
    Accessibility at stations and to transit vehicles, particularly for mobility impaired
    travelers or air passengers carrying luggage
    Cleanliness
    Ride quality
    Perceived service reliability.
These attributes are typically accounted for by assigning a constant to each mode which
then ensures the mode shares match the base (i.e. known) situation. This process is
known as calibration.

In considering transit modes, there is much disagreement about how these attributes
affect ridership between bus-based and rail-based modes. While a number of factors may
be considered to make rail services more attractive than local bus – perhaps their ride
quality, permanent and highly visible infrastructure, this may not always be the case.
This is particularly true for high quality bus services, which in the case of airport services
may involve dedicated vehicles with unique branding (such as the existing 992 Flyer) and
perhaps some form of physical segregation from the roadway which infers a degree of
permanence and visibility to the service. The SANDAG Regional Transportation Model
found that commuters in San Diego tended on average to favor rail and express bus over
local bus. In terms of the mode-specific constants, this was reflected in a 6 minute
equivalent travel time benefit for rail and 14 minutes for express bus. This illustrates
both that rail may well be inherently preferred to local bus but that high quality, express
bus services can be even more attractive. Because of the uncertainty surrounding any
intrinsic difference in preference between rail and bus, both conservative and optimistic
assumptions were made in the modeling. In the conservative scenario it was assumed that
there is no intrinsic difference in preference between the modes, while in the optimistic
assumption it was assumed that there is preference for rail equivalent to 6 minutes of
travel time.

Model Parameters
The model parameters are values that indicate the relative weighting of the different
service attributes. These parameters are used in logit-based discrete choice models,
which are widely used for transportation modeling. They provide a mathematical

                                              San Diego International Airport Expansion: Sustainability Analysis
 B-20
                                                                                 Appendix B
                                                                     Transportation Modeling

framework around which these factors come together to provide an indication of the
overall likelihood of selecting each mode. As discussed earlier, this is an important
advantage of this type of model – that it assigns probabilities to choices rather than
inferring certainty. In a transport action context this is a significant advantage, as it helps
to account for the factors that are more difficult to quantify and the wide variation of
preferences across the population.

The model parameters are typically estimated using statistical techniques based on local
data. This data is typically obtained using a dedicated survey and data collection
procedure. We are not aware of such a procedure having been conducted at SDIA. The
scope and schedule of this study precluded any primary data research and estimation of
models from local data sources. Instead, model parameters were derived from relevant
studies in other locations. The most useful of these was the air passenger model
estimated for San Jose Airport (SJC) in 2002. This model provided parameter estimates
across four air passenger segments – resident business journeys, resident non-business
trips, non-resident business trips and non-resident non-business trips.

In order to tailor the model to San Diego the value of time was adjusted and the mode
specific constants adjusted using a calibration procedure to ensure the existing mode
shares were replicated. The resulting model parameters are given in Table B-6 for air
passengers and Table B-7 for airport employees. The constants are presented both in
terms of the parameters themselves and in parenthesis in terms of equivalent in-vehicle
time. The latter provides a ‘physical’ indication of any intrinsic attractiveness of
particular modes.

The IVT parameter was set to -0.028 for airport employees, which is consistent with that
used in the SANDAG Regional Transportation Model for home-based work trips.

Other relevant model parameters that were used in the model and discussed in previous
sections are summarized in Table B-8.




                    :
San Diego International Airport Expansion: Sustainability Analysis
                                                                                         B-21
Appendix B
Transportation Modeling




                            Table B-6. Air Passenger Model
                        Resident                           Non-Resident
                Business     Non-Business            Business     Non-Business                     Units
Parameters
Time             -0.2272          -0.1078                -0.2108            -0.0975         mins
Cost             -0.2770          -0.2574                -0.2560            -0.2385         $
Constants
Car – off-apt      0.47              0.47                   --                  --
                   (2.1)            (4.4)                   --                  --          mins
PT                -1.60            -2.20                  0.40               -0.70
                   (7.0)           (20.4)                 (1.9)               (7.2)         mins
Kiss & Fly        -1.95             0.05                 -1.95                0.05
                   (8.6)            (0.5)                 (9.3)               (0.5)         mins
Rental car        -2.80            -4.00                  4.00                1.10
                  (12.3)           (37.1)                (19.0)              (11.3)         mins
Taxi               -2.80            -2.70                -0.30               -1.30
                  (12.3)           (25.0)                 (1.4)              (13.3)         mins
Shared van         -2.66            -2.86                -0.86               -1.56
                  (11.7)           (26.5)                 (4.1)              (16.0)         mins




                           Table B-7. Airport Employee Model
                             Parameter          Value        Units
                             Time              -0.0280       mins
                             Cost              -0.2608       $
                             Constants
                             PT                  -2.25
                                                (80.3)       Mins




                                            San Diego International Airport Expansion: Sustainability Analysis
 B-22
                                                                                             Appendix B
                                                                                 Transportation Modeling




                              Table B-8. Summary of Model Parameters
                         Parameter                                   Value   Units
                         Values of Time
                         Air passenger – business                     50     $/hr
                         Air passenger – non-business                 25     $/hr
                         Airport employees                           6.44    $/hr
                         Transit
                         Interchange penalty – air passengers         20     IVT mins
                         Interchange penalty – airport                20     IVT mins
                         employees
                         Access time factor                           2      –
                         Wait time factor                             3      –
                         Parking
                         On-Airport
                         Park search and access – air                 10     mins
                         passengers
                         Park search and access – airport             5      mins
                         employees
                         Off-Airport
                         Shuttle bus headway                          10     mins
                         Shuttle bus IVT                               7     mins
                         Interchange penalty                          20     mins
                         Group size
                         Business trips                               1.2    persons
                         Non-business trips                           2.1    persons
                         Duration of stay
                         Business trips                               1.5    days
                         Non-business trips                           3.0    days
                         Car rental
                         Component of rental car cost                 20     $



Model Structure
The model uses a sample enumeration-type approach for air passengers and airport
employees. The samples are derived from the known purpose splits (business 4percent,
non-business 55percent) and residency status (60percent of air passengers are from the
greater San Diego area). Weights for each zone are applied consistent with surveys of
staff and air passengers. Note that the distribution across zones of air passengers and
airport employees are assumed to be identical due to a lack of data separating out the two
categories.

The model implemented is multinomial logit; it is recognized that such an approach may
lead to non-intuitive rates of substitution between alternatives. However, as no model
estimations were undertaken it was not evident how nest coefficients could be derived.



                    :
San Diego International Airport Expansion: Sustainability Analysis
                                                                                                  B-23
Appendix B
Transportation Modeling

Model Specification
The model specification is a set of utility functions that define the total ‘attractiveness’ of
each mode, taking into account the times, costs and other factors. These were defined as
follows, based on experience from studies elsewhere:

                  ⎛ p onapt − park d cD                                                    ⎞ 1
  U car −onapt = ⎜⎜                  +   + VOT ⋅ t hwy + VOT ⋅ t park − search ⋅ accfactor ⎟ ⋅
                                                                                           ⎟ D
                  ⎝       2g           g                                                   ⎠
                  ⎛ p offapt − park d cD                                                           h park ⎞ 1
  U car −offapt = ⎜                  +   + VOT ⋅ t hwy + VOT ⋅ t park ⋅ accfactor + VOT ⋅ t wait ⋅        ⎟⋅  K
                  ⎜
                  ⎝       2g           g                                                             2 ⎟ D⎠
                       τ
              + VOT ⋅ + ASC car −offapt
                     3

                                   ⎛                     2t hwy 2cD ⎞ 1
For business trips: U kiss − fly = ⎜ VOT ⋅ t hwy + VOT ⋅
                                   ⎜                           +    ⎟⋅  + ASC kiss − fly
                                   ⎝                       g     g ⎟ D
                                                                    ⎠
For non-business trips:

U rent = (VOT ⋅ t hwy + 15 )⋅
                                1
                                  + ASC rent
                                D
         ⎛ 2 . 6 D + 2 .4                ⎞ 1
U taxi = ⎜
         ⎜                 + VOT ⋅ t hwy ⎟ ⋅
                                         ⎟ D + ASC taxi
         ⎝        g                      ⎠
         ⎛ 14.0124 e    0.04246 D
                                                ⎞ 1
U van = ⎜⎜                        + VOT ⋅ t hwy ⎟ ⋅
                                                ⎟ D + ASC van
         ⎝          g                           ⎠
          ⎛                                     h                      ⎞ 1
U bus = ⎜ fare + VOT ⋅ t PT + VOT ⋅ θ wait ⋅ PT + VOT ⋅ θ acc ⋅ t acc ⎟ ⋅     + VOT ⋅τ ⋅ i + ASC bus
          ⎝                                      2                     ⎠ D
             ⎛                                    h                       ⎞ 1
U trolley = ⎜ fare + VOT ⋅ t PT + VOT ⋅ θ wait ⋅ PT + VOT ⋅ θ acc ⋅ t acc ⎟ ⋅   + VOT ⋅τ ⋅ i + ASC trolley
             ⎝                                     2                      ⎠ D
              ⎛                                    h                       ⎞ 1
U coaster = ⎜ fare + VOT ⋅ t PT + VOT ⋅ θ wait ⋅ PT + VOT ⋅ θ acc ⋅ t acc ⎟ ⋅   + VOT ⋅τ ⋅ i + ASC coaster
              ⎝                                     2                      ⎠ D
              ⎛                                   h                       ⎞ 1
U amtrak = ⎜ fare + VOT ⋅ t PT + VOT ⋅ θ wait ⋅ PT + VOT ⋅ θ acc ⋅ t acc ⎟ ⋅    + VOT ⋅τ ⋅ i + ASC amtrak
              ⎝                                     2                     ⎠ D
                 VOT ⋅ t hwy
U courtesyva n =             + ASC courtesyva n
                     D

               ⎛                     t hwy 2 ⋅ 0.15 ⋅ cD ⎞ 1
U kiss − fly = ⎜ VOT ⋅ t hwy + VOT ⋅
               ⎜                          +              ⎟⋅
                                                         ⎟ D + ASC kiss − fly
               ⎝                       g         g       ⎠



                                                  San Diego International Airport Expansion: Sustainability Analysis
 B-24
                                                                                 Appendix B
                                                                     Transportation Modeling

Where:
D      =     distance to airport by car (miles)
thwy =       in-vehicle time by car (minutes)
tPT    =     in-vehicle time by public transit (minutes)
hhwy =       total headway (minutes)
τ      =     interchange penalty (minutes of IVT time equivalent)
θwait =      wait time factor (relative to IVT time)
θacc =       access time factor (relative to IVT time)
i      =     number of interchanges
VOT =        value of time ($/minute)
ASCx =       alternative specific constant
g      =     group size (persons)
c      =     perceived car operating cost ($/mile)


Residents and non-residents are modeled as having different mode availabilities; non-
residents are not allocated the car (park on-airport and park off-airport) alternatives while
residents are not allocated the car rental and courtesy van alternatives.

As noted earlier, because logit models work on the basis of utility differences there is a
concern that the model would not adequately reflect travel time savings for short and long
distance trips appropriately. For this reason, and consistent with airport ground access
models developed in other locations, the utilities were divided by the square root of travel
distance. This has the effect of scaling the utility such that for longer trips a time saving
of, say, one minute would be less important than for a shorter trip (where a one minute
saving would represent a larger proportion of the whole travel time).

B.1       Distribution of Transit Ridership
The model takes each of the 78 zones and determines the ridership based on the times and
costs for each mode to the airport. In this way the introduction of the ITC, and improved
trolley and rail connections, will result in increased transit ridership in those zones for
which transit becomes an increasingly attractive alternative. Table B-9 below
summarizes the ridership for the SDCRAA preferred alternative with transit plan and
Lindbergh ITC and the optimistic assumptions.




                    :
San Diego International Airport Expansion: Sustainability Analysis
                                                                                       B-25
Appendix B
Transportation Modeling

                       Table B-9. Distribution of Transit Ridership

                           2030 Preferred
                       Alternative with Transit            2030 Lindbergh ITC                       Difference
        Location
                                  Plan

                       Ridership          Transit       Ridership         Transit         Ridership           Transit
                        per day          share (%)       per day         share (%)          per day          share (%)

 32nd St Naval             2                2.7              8               9.7               6                 6.9
 Station

 Balboa Park               ─                ─                ─                ─                ─                  ─

 Barrio Logan              2                2.3              8               9.8               6                 7.5

 Black Mountain            18               3.5             36               7.2               18                3.7
 Ranch

 CARLSBAD                 189               4.0             401              8.4              211                4.4

 Carmel Mountain           11               2.7             10               2.5               -1                -0.2
 Ranch

 Carmel Valley             24               3.7             53               8.0               28                4.3

 Center City              594               8.2             797             11.0              203                2.8

 CHULA VISTA               71               1.9             123              3.3               52                1.4

 Clairemont Mesa           42               3.2             40               3.0               0                 0.0

 College Area              17               3.5             51              10.3               34                6.8

 CORONADO                  17               1.8             17               1.8               0                 0.0

 DEL MAR                   9                3.6             19               7.5               10                3.9

 Del Mar Mesa              6                3.5             12               7.4               6                 3.9

 East Elliott              ─                ─                ─                ─                ─                  ─

 EL CAJON                  51               2.6             179              9.0              128                6.4

 ENCINITAS                 48               3.6             101              7.6               53                4.0

 ESCONDIDO                 76               3.2             73               3.0               -3                -0.1

 Fairbanks Country         ─                ─                ─                ─                ─                  ─
 Club

 Flower Hill               ─                ─                ─                ─                ─                  ─

 Greater Golden Hill       6                2.2              6               2.3               0                 0.0

 Greater North Park        16               1.9             16               1.9               0                 0.0

 Harbor                    ─                ─                ─                ─                ─                  ─


                                                  San Diego International Airport Expansion: Sustainability Analysis
 B-26
                                                                                                Appendix B
                                                                                    Transportation Modeling


                                   2030 Preferred
                              Alternative with Transit           2030 Lindbergh ITC               Difference
         Location
                                         Plan

                              Ridership          Transit      Ridership     Transit      Ridership        Transit
                               per day          share (%)       per day    share (%)      per day        share (%)

 IMPERIAL BEACH                    7               2.1               12       3.7            5                 1.6

 Kearny Mesa                      33               2.1               32       2.0           -1                 -0.1

 La Jolla                         14               1.7               13       1.6           -1                 -0.1

 LA MESA                          29               2.7               102      9.5           72                 6.7

 LEMON GROVE                      11               2.7               39       9.5           28                 6.7

 Linda Vista                      11               2.6                9       2.2           -2                 -0.4

 Lindbergh Field                   ─                ─                ─         ─             ─                  ─

 Mid-City: City                   15               1.9               16       1.9            0                 0.0
 Heights

 Mid-City: Eastern                 4               0.6               11       1.8            7                 1.2
 Area

 Mid-City:                         4               1.6                4       1.6            0                 0.0
 Kensington-
 Talmadge

 Mid-City: Normal                  5               2.2                5       2.2            0                 0.0
 Heights

 Midway-Pacific                    8               2.0               32       7.9           24                 5.9
 Highway

 Mira Mesa                        52               2.0               48       1.9           -4                 -0.2

 Miramar Air Station               3               3.5               2        2.9            0                 -0.6

 Miramar Ranch                    12               3.6               11       3.5            0                 -0.1
 North

 Mission Bay Park                 31               2.5               28       2.2           -4                 -0.3

 Mission Beach                     9               2.7                8       2.3           -1                 -0.4

 Mission Valley                   101              3.0               305      9.0           204                6.0

 NATIONAL CITY                    21               2.3               69       7.6           48                 5.3

 Navajo                           19               1.9               34       3.4           15                 1.5

 NCFUA Subarea 2                   ─                ─                ─         ─             ─                  ─

 Ocean Beach                      16               6.4               15       6.1           -1                 -0.3

                    :
San Diego International Airport Expansion: Sustainability Analysis
                                                                                                        B-27
Appendix B
Transportation Modeling


                          2030 Preferred
                      Alternative with Transit            2030 Lindbergh ITC                       Difference
         Location
                                 Plan

                      Ridership          Transit       Ridership         Transit         Ridership           Transit
                       per day          share (%)       per day         share (%)          per day          share (%)

 OCEANSIDE                144              4.3             315              9.3              171                5.1

 Old San Diego             8              10.1              9              10.5               0                 0.4

 Otay Mesa                30               3.7             74               9.0               44                5.3

 Otay Mesa-Nestor         27               4.1             55               8.4               28                4.3

 OUTSIDE SD               49               1.6             47               1.6               -1                0.0
 COUNTY

 Pacific Beach            16               1.9             15               1.8               -1                -0.1

 Pacific Highlands         7               4.0             14               8.8               8                 4.8
 Ranch

 Peninsula                28               1.6             35               1.9               7                 0.4

 POWAY                    23               2.1             21               2.0               -1                -0.1

 Rancho Bernardo          33               2.9             34               3.0               1                 0.1

 Rancho Encantado         ─                ─                ─                ─                ─                  ─

 Rancho Penasquitos       22               3.3             23               3.5               1                 0.1

 Sabre Springs             6               3.4              5               3.2               0                 -0.1

 SAN MARCOS               61               4.1             129              8.7               68                4.6

 San Pasqual              ─                ─                ─                ─                ─                  ─

 San Ysidro               21               4.2             51              10.2               30                6.0

 SANTEE                   46               4.7             118             11.9               71                7.2

 Scripps Miramar          14               3.5             14               3.3               -1                -0.2
 Ranch

 Serra Mesa                5               1.6              5               1.6               0                 0.0

 Skyline-Paradise          5               0.7             14               2.2               10                1.5
 Hills

 SOLANA BEACH             14               3.3             29               6.9               15                3.6

 Southeastern:            14               2.9             51              10.2               36                7.3
 Encanto
 Neighborhoods



                                                 San Diego International Airport Expansion: Sustainability Analysis
 B-28
                                                                                                Appendix B
                                                                                    Transportation Modeling


                                   2030 Preferred
                              Alternative with Transit           2030 Lindbergh ITC              Difference
        Location
                                         Plan

                              Ridership          Transit      Ridership     Transit      Ridership       Transit
                               per day          share (%)       per day    share (%)      per day       share (%)

 Southeastern:                    14               2.5               57       9.9           43                7.4
 Southeastern SD

 Tierrasanta                       7               1.8                7       1.6           -1                -0.2

 Tijuana River Valley              ─                ─                ─         ─             ─                 ─

 Torrey Highlands                  3               3.8               7        7.9            3                4.1

 Torrey Hills                      3               3.2               6        7.0            3                3.8

 Torrey Pines                     10               3.2               22       6.8           12                3.6

 UNINCORPORATED                   124              1.1               124      1.1            0                0.0

 University                       58               2.3               56       2.3           -2                -0.1

 Uptown                           17               1.8               15       1.5           -2                -0.2

 Via De La Valle                   ─                ─                ─         ─             ─                 ─

 VISTA                            76               4.4               163      9.4           86                5.0




                    :
San Diego International Airport Expansion: Sustainability Analysis
                                                                                                       B-29
          San Diego International Airport Expansion
          Sustainability Analysis




          Appendix C - Calculations of
          Greenhouse Gas Emissions




6189001
Table C-1: Greenhouse Gas Emission Calculations

Scenario:     No Project
Year:         2005
Timeframe:    All calculations are on a per day basis

Calculations
CO2 = vehicle miles traveled / fuel efficiency * emission factor (CO2 / gallon) * conversion factor
CH4 (in CO2 equivalents) = vehicle miles traveled * emission factor (CH4 / mile) * conversion factor * global warming potential
N2O (in CO2 equivalents) = vehicle miles traveled * emission factor (N2O / mile) * conversion factor * global warming potential

              Car              Van           Units                             Source                                       Assumptions / Notes
                    1132440            71600 miles                             SKM data (2007)                              round-trip mileage
                                                                                                                            miles per gallon based on 2005 data
                                                                               Transportation Energy Data Book, Edition
                        22.9             16.2 miles / gallon                   26 , Oak Ridge National Laboratory, 2007     van miles per gallon includes vans,
                                                                               (ORNL-6978)                                  pickup trucks, and sport utility
    CO2                                                                                                                     vehicles
                      49452             4420 gallons                           calculation
                                                                                                                            fuel is CA reformulated gasoline,
                        8.55             8.55 kg CO2 / gallon                  emission factor from CCAR, Table C.3
                                                                                                                            5.7% ethanol
                     422811            37789 kg CO2                            calculation
                      0.001            0.001 metric tons / kg                  conversion factor
                      422.8             37.8 metric tons CO2                   calculation

              Car              Van           Units                             Source                                       Assumptions / Notes
                    1132440            71600 miles                             SKM data (2007)                              round-trip mileage
                                                                                                                            car is model year 2000-present, fuel
                                                                                                                            is gasoline
                        0.04             0.12 g CH4 / mile                     emission factor from CCAR, Table C.4
                                                                                                                            van is a heavy-duty vehicle with
                                                                                                                            GVWR >5751 lbs., model year is
    CH4                                                                                                                     1990-present, fuel is gasoline
                     45297.6           8592.0 g CH4                            calculation
                    0.000001         0.000001 metric tons / g                  conversion factor
                       0.045            0.009 metric tons CH4                  calculation
                                                                               global warming potential from CCAR Table
                          23               23 GWP
                                                                               III.6.1
                       1.042            0.198 metric tons CO2 equivalent       calculation

              Car              Van           Units                             Source                                       Assumptions / Notes
                    1132440            71600 miles                             SKM data (2007)                              round-trip mileage
                                                                                                                            car is model year 2000-present, fuel
                                                                                                                            is gasoline
                        0.04             0.20 g N2O / mile                     emission factor from CCAR, Table C.4
                                                                                                                            van is a heavy-duty vehicle with
                                                                                                                            GVWR >5751 lbs., model year is
    N2 O                                                                                                                    1990-present, fuel is gasoline
                     45297.6          14320.0 g N2O                            calculation
                    0.000001         0.000001 metric tons / g                  conversion factor
                       0.045            0.014 metric tons N2O                  calculation
                                                                               global warming potential from CCAR Table
                        296              296 GWP
                                                                               III.6.1
                      13.408            4.239 metric tons CO2 equivalent       calculation

  Total by
                       437.3             42.2 metric tons CO2 equivalent
  Vehicle

  Scenario
                          479.5               metric tons CO2 equivalent
   Total




                                                                                C-1
Table C-2: Greenhouse Gas Emission Calculations

Scenario:     No Project
Year:         2030
Timeframe:    All calculations are on a per day basis

Calculations
CO2 = vehicle miles traveled / fuel efficiency * emission factor (CO2 / gallon) * conversion factor
CH4 (in CO2 equivalents) = vehicle miles traveled * emission factor (CH4 / mile) * conversion factor * global warming potential
N2O (in CO2 equivalents) = vehicle miles traveled * emission factor (N2O / mile) * conversion factor * global warming potential

              Car              Van           Units                             Source                                       Assumptions / Notes
                    1769337           115617 miles                             SKM data (2007)                              round-trip mileage
                                                                                                                            The new CAFE standard is 35 mpg
                                                                                                                            by 2020. The fuel economy in this
                                                                                                                            table assumes that by 2030, cars will
                                                                                                                            achieve 83% of this standard and
                                                                                                                            vans will achieve 78% of this
                        29.1             27.4 miles / gallon
                                                                                                                            standard. These percentages are
                                                                                                                            based on the current CAFE standard:
    CO2
                                                                                                                            cars must exceed an average of 27.5
                                                                                                                            mpg and light trucks (i.e., vans) must
                                                                                                                            exceed an average of 20.7.
                      60907             4220 gallons                           calculation
                                                                                                                            fuel is CA reformulated gasoline,
                        8.55             8.55 kg CO2 / gallon                  emission factor from CCAR, Table C.3
                                                                                                                            5.7% ethanol
                     520752            36078 kg CO2                            calculation
                      0.001            0.001 metric tons / kg                  conversion factor
                      520.8             36.1 metric tons CO2                   calculation

              Car              Van           Units                             Source                                       Assumptions / Notes
                    1769337           115617 miles                             SKM data (2007)                              round-trip mileage
                                                                                                                            car is model year 2000-present, fuel
                                                                                                                            is gasoline
                        0.04             0.12 g CH4 / mile                     emission factor from CCAR, Table C.4
                                                                                                                            van is a heavy-duty vehicle with
                                                                                                                            GVWR >5751 lbs., model year is
    CH4                                                                                                                     1990-present, fuel is gasoline
                     70773.5          13874.0 g CH4                            calculation
                    0.000001         0.000001 metric tons / g                  conversion factor
                       0.071            0.014 metric tons CH4                  calculation
                                                                               global warming potential from CCAR Table
                          23               23 GWP
                                                                               III.6.1
                       1.628            0.319 metric tons CO2 equivalent       calculation

              Car              Van           Units                             Source                                       Assumptions / Notes
                    1769337           115617 miles                             SKM data (2007)                              round-trip mileage
                                                                                                                            car is model year 2000-present, fuel
                                                                                                                            is gasoline
                        0.04             0.20 g N2O / mile                     emission factor from CCAR, Table C.4
                                                                                                                            van is a heavy-duty vehicle with
                                                                                                                            GVWR >5751 lbs., model year is
    N2 O                                                                                                                    1990-present, fuel is gasoline
                     70773.5          23123.4 g N2O                            calculation
                    0.000001         0.000001 metric tons / g                  conversion factor
                       0.071            0.023 metric tons N2O                  calculation
                                                                               global warming potential from CCAR Table
                        296              296 GWP
                                                                               III.6.1
                      20.949            6.845 metric tons CO2 equivalent       calculation

  Total by
                       543.3             43.2 metric tons CO2 equivalent
  Vehicle

  Scenario
                          586.6               metric tons CO2 equivalent
   Total




                                                                                C-2
Table C-3: Greenhouse Gas Emission Calculations

Scenario:     Preferred Alternative
Year:         2030
Timeframe:    All calculations are on a per day basis

Calculations
CO2 = vehicle miles traveled / fuel efficiency * emission factor (CO2 / gallon) * conversion factor
CH4 (in CO2 equivalents) = vehicle miles traveled * emission factor (CH4 / mile) * conversion factor * global warming potential
N2O (in CO2 equivalents) = vehicle miles traveled * emission factor (N2O / mile) * conversion factor * global warming potential

              Car              Van              Bus              Units                             Source                                               Assumptions / Notes
                    1769377           115617                     miles                             SKM data (2007)                                      round-trip mileage

                                                                                                                                                        The new CAFE standard is 35 mpg
                                                                                                                                                        by 2020. The fuel economy in this
                                                                                                                                                        table assumes that by 2030, cars will
                                                                                                                                                        achieve 83% of this standard and
                                                                                                   bus miles per gallon of gasoline equivalent from Ten vans will achieve 78% of this
                                                                 miles / gallon
                                                                                                   Years of Compressed Natural Gas (CNG) Operations standard. These percentages are
                        29.1             27.4              3.1                                     at SunLine Transit Agency, National Renewable        based on the current CAFE standard:
                                                                 (for CNG bus, units in miles /
                                                                                                   Energy Laboratory, January 2006 (NREL/SR-540-        cars must exceed an average of 27.5
                                                                 gallon of gasoline equivalent)
                                                                                                   39180)                                               mpg and light trucks (i.e., vans) must
    CO2                                                                                                                                                 exceed an average of 20.7.

                                                                                                                                                        By 2030 all San Diego buses will run
                                                                                                                                                        on compressed natural gas (CNG).

                      60908             4220                 0 gallons                             calculation
                                                               kg CO2 / gallon
                                                                                                                                                        fuel is CA reformulated gasoline,
                        8.55             8.55             6.86                                     emission factor from CCAR, Table C.3
                                                               (for CNG bus, units in kg CO2 /                                                          5.7% ethanol
                                                               gallon of gasoline equivalent)
                     520763            36078                 0 kg CO2                              calculation
                      0.001            0.001             0.001 metric tons / kg                    conversion factor
                      520.8             36.1               0.0 metric tons CO2                     calculation

              Car              Van              Bus            Units                               Source                                               Assumptions / Notes
                    1769377           115617                 0 miles                               SKM data (2007)                                      round-trip mileage
                                                                                                                                                        car is model year 2000-present, fuel
                                                                                                                                                        is gasoline

                                                                                                                                                        van is a heavy-duty vehicle with
                        0.04             0.12             3.48 g CH4 / mile                        emission factor from CCAR, Table C.4
                                                                                                                                                        GVWR >5751 lbs., model year is
    CH4                                                                                                                                                 1990-present, fuel is gasoline

                                                                                                                                                        bus is a CNG/LNG heavy duty truck
                     70775.1          13874.0              0.0   g CH4                             calculation
                    0.000001         0.000001         0.000001   metric tons / g                   conversion factor
                       0.071            0.014            0.000   metric tons CH4                   calculation
                          23               23               23   GWP                               global warming potential from CCAR Table III.6.1
                       1.628            0.319            0.000   metric tons CO2 equivalent        calculation

              Car              Van              Bus            Units                               Source                                               Assumptions / Notes
                    1769377           115617                 0 miles                               SKM data (2007)                                      round-trip mileage
                                                                                                                                                        car is model year 2000-present, fuel
                                                                                                                                                        is gasoline

                                                                                                                                                        van is a heavy-duty vehicle with
                        0.04             0.20             0.05 g N2O / mile                        emission factor from CCAR, Table C.4
                                                                                                                                                        GVWR >5751 lbs., model year is
    N 2O                                                                                                                                                1990-present, fuel is gasoline

                                                                                                                                                        bus is a CNG/LNG heavy duty truck
                     70775.1          23123.4              0.0   g N2O                             calculation
                    0.000001         0.000001         0.000001   metric tons / g                   conversion factor
                       0.071            0.023          0.00000   metric tons N2O                   calculation
                         296              296              296   GWP                               global warming potential from CCAR Table III.6.1
                      20.949            6.845            0.000   metric tons CO2 equivalent        calculation

  Total by
                       543.3             43.2              0.0 metric tons CO2 equivalent
  Vehicle

  Scenario
                                 586.6                           metric tons CO2 equivalent
   Total

Note:
The total CO2 equivalent includes emissions reductions from decreased bus usage.




                                                                                                  C-3
Table C-4: Greenhouse Gas Emission Calculations

Scenario:     Preferred Alternative with Airport Transit Plan
Year:         2030
Timeframe:    All calculations are on a per day basis

Calculations
CO2 = vehicle miles traveled / fuel efficiency * emission factor (CO2 / gallon) * conversion factor
CH4 (in CO2 equivalents) = vehicle miles traveled * emission factor (CH4 / mile) * conversion factor * global warming potential
N2O (in CO2 equivalents) = vehicle miles traveled * emission factor (N2O / mile) * conversion factor * global warming potential

              Car              Van              Bus           Units                                Source                                               Assumptions / Notes
                    1735523           113210             2680 miles                                SKM data (2007)                                      round-trip mileage

                                                                                                                                                        The new CAFE standard is 35 mpg
                                                                                                                                                        by 2020. The fuel economy in this
                                                                                                                                                        table assumes that by 2030, cars will
                                                                                                                                                        achieve 83% of this standard and
                                                                                                   bus miles per gallon of gasoline equivalent from Ten vans will achieve 78% of this
                                                                 miles / gallon
                                                                                                   Years of Compressed Natural Gas (CNG) Operations standard. These percentages are
                        29.1             27.4              3.1                                     at SunLine Transit Agency, National Renewable        based on the current CAFE standard:
                                                                 (for CNG bus, units in miles /
                                                                                                   Energy Laboratory, January 2006 (NREL/SR-540-        cars must exceed an average of 27.5
                                                                 gallon of gasoline equivalent)
                                                                                                   39180)                                               mpg and light trucks (i.e., vans) must
    CO2                                                                                                                                                 exceed an average of 20.7.

                                                                                                                                                        By 2030 all San Diego buses will run
                                                                                                                                                        on compressed natural gas (CNG).

                      59743             4132              865 gallons                              calculation
                                                              kg CO2 / gallon
                                                                                                                                                        fuel is CA reformulated gasoline,
                        8.55             8.55             6.86                                     emission factor from CCAR, Table C.3
                                                               (for CNG bus, units in kg CO2 /                                                          5.7% ethanol
                                                               gallon of gasoline equivalent)
                     510799            35326             5931 kg CO2                               calculation
                      0.001            0.001             0.001 metric tons / kg                    conversion factor
                      510.8             35.3               5.9 metric tons CO2                     calculation

              Car              Van              Bus           Units                                Source                                               Assumptions / Notes
                    1735523           113210             2680 miles                                SKM data (2007)                                      round-trip mileage
                                                                                                                                                        car is model year 2000-present, fuel
                                                                                                                                                        is gasoline

                                                                                                                                                        van is a heavy-duty vehicle with
                        0.04             0.12             3.48 g CH4 / mile                        emission factor from CCAR, Table C.4
                                                                                                                                                        GVWR >5751 lbs., model year is
    CH4                                                                                                                                                 1990-present, fuel is gasoline

                                                                                                                                                        bus is a CNG/LNG heavy duty truck
                     69420.9          13585.2           9326.4   g CH4                             calculation
                    0.000001         0.000001         0.000001   metric tons / g                   conversion factor
                       0.069            0.014            0.009   metric tons CH4                   calculation
                          23               23               23   GWP                               global warming potential from CCAR Table III.6.1
                       1.597            0.312            0.215   metric tons CO2 equivalent        calculation

              Car              Van              Bus           Units                                Source                                               Assumptions / Notes
                    1735523           113210             2680 miles                                SKM data (2007)                                      round-trip mileage
                                                                                                                                                        car is model year 2000-present, fuel
                                                                                                                                                        is gasoline

                                                                                                                                                        van is a heavy-duty vehicle with
                        0.04             0.20             0.05 g N2O / mile                        emission factor from CCAR, Table C.4
                                                                                                                                                        GVWR >5751 lbs., model year is
    N 2O                                                                                                                                                1990-present, fuel is gasoline

                                                                                                                                                        bus is a CNG/LNG heavy duty truck
                     69420.9          22642.0            134.0   g N2O                             calculation
                    0.000001         0.000001         0.000001   metric tons / g                   conversion factor
                       0.069            0.023          0.00013   metric tons N2O                   calculation
                         296              296              296   GWP                               global warming potential from CCAR Table III.6.1
                      20.549            6.702            0.040   metric tons CO2 equivalent        calculation

  Total by
                       532.9             42.3              6.2 metric tons CO2 equivalent
  Vehicle

  Scenario
                                 581.5                           metric tons CO2 equivalent
   Total

Note:
The total CO2 equivalent includes emissions reductions from decreased bus usage.




                                                                                                  C-4
Table C-5: Greenhouse Gas Emission Calculations

Scenario:     ITC (including FlyAway)
Year:         2030
Timeframe:    All calculations are on a per day basis

Calculations
CO2 = vehicle miles traveled / fuel efficiency * emission factor (CO2 / gallon) * conversion factor
CH4 (in CO2 equivalents) = vehicle miles traveled * emission factor (CH4 / mile) * conversion factor * global warming potential
N2O (in CO2 equivalents) = vehicle miles traveled * emission factor (N2O / mile) * conversion factor * global warming potential

              Car              Van              Bus           Units                                Source                                               Assumptions / Notes
                    1596914           103947             1744 miles                                SKM data (2007)                                      round-trip mileage

                                                                                                                                                        The new CAFE standard is 35 mpg
                                                                                                                                                        by 2020. The fuel economy in this
                                                                                                                                                        table assumes that by 2030, cars will
                                                                                                                                                        achieve 83% of this standard and
                                                                                                   bus miles per gallon of gasoline equivalent from Ten vans will achieve 78% of this
                                                                 miles / gallon
                                                                                                   Years of Compressed Natural Gas (CNG) Operations standard. These percentages are
                        29.1             27.4              3.1                                     at SunLine Transit Agency, National Renewable        based on the current CAFE standard:
                                                                 (for CNG bus, units in miles /
                                                                                                   Energy Laboratory, January 2006 (NREL/SR-540-        cars must exceed an average of 27.5
                                                                 gallon of gasoline equivalent)
                                                                                                   39180)                                               mpg and light trucks (i.e., vans) must
    CO2                                                                                                                                                 exceed an average of 20.7.

                                                                                                                                                        By 2030 all San Diego buses will run
                                                                                                                                                        on compressed natural gas (CNG).

                      54971             3794              563 gallons                              calculation
                                                              kg CO2 / gallon
                                                                                                                                                        fuel is CA reformulated gasoline,
                        8.55             8.55             6.86                                     emission factor from CCAR, Table C.3
                                                               (for CNG bus, units in kg CO2 /                                                          5.7% ethanol
                                                               gallon of gasoline equivalent)
                     470004            32436             3859 kg CO2                               calculation
                      0.001            0.001             0.001 metric tons / kg                    conversion factor
                      470.0             32.4               3.9 metric tons CO2                     calculation

              Car              Van              Bus           Units                                Source                                               Assumptions / Notes
                    1596914           103947             1744 miles                                SKM data (2007)                                      round-trip mileage
                                                                                                                                                        car is model year 2000-present, fuel
                                                                                                                                                        is gasoline

                                                                                                                                                        van is a heavy-duty vehicle with
                        0.04             0.12             3.48 g CH4 / mile                        emission factor from CCAR, Table C.4
                                                                                                                                                        GVWR >5751 lbs., model year is
    CH4                                                                                                                                                 1990-present, fuel is gasoline

                                                                                                                                                        bus is a CNG/LNG heavy duty truck
                     63876.6          12473.6           6069.1   g CH4                             calculation
                    0.000001         0.000001         0.000001   metric tons / g                   conversion factor
                       0.064            0.012            0.006   metric tons CH4                   calculation
                          23               23               23   GWP                               global warming potential from CCAR Table III.6.1
                       1.469            0.287            0.140   metric tons CO2 equivalent        calculation

              Car              Van              Bus           Units                                Source                                               Assumptions / Notes
                    1596914           103947             1744 miles                                SKM data (2007)                                      round-trip mileage
                                                                                                                                                        car is model year 2000-present, fuel
                                                                                                                                                        is gasoline

                                                                                                                                                        van is a heavy-duty vehicle with
                        0.04             0.20             0.05 g N2O / mile                        emission factor from CCAR, Table C.4
                                                                                                                                                        GVWR >5751 lbs., model year is
    N 2O                                                                                                                                                1990-present, fuel is gasoline

                                                                                                                                                        bus is a CNG/LNG heavy duty truck
                     63876.6          20789.4             87.2   g N2O                             calculation
                    0.000001         0.000001         0.000001   metric tons / g                   conversion factor
                       0.064            0.021          0.00009   metric tons N2O                   calculation
                         296              296              296   GWP                               global warming potential from CCAR Table III.6.1
                      18.907            6.154            0.026   metric tons CO2 equivalent        calculation

  Total by
                       490.4             38.9              4.0 metric tons CO2 equivalent
  Vehicle

  Scenario
                                 533.3                           metric tons CO2 equivalent
   Total

Note:
The total CO2 equivalent includes additional emissions from increased bus usage.




                                                                                                  C-5
Table C-6: Greenhouse Gas Emission Calculations
               Not Used
Calculation:   Trolley Emissions
Scenario:      Lindberg ITC + Green and Orange Line (Scenario 5)
Year:          2030
Timeframe:     All calculations are on a per day basis

Calculations
MWh = miles * power consumption (kWh / vehicle km) * conversion factor
CO2 = MWh * emission factor (CO 2 / MWh) * conversion factor
CH4 (in CO2 equivalents) = MWh * emission factor (CH 4 / MWh) * conversion factor * global warming potential
N2O (in CO2 equivalents) = MWh * emission factor (N 2O / MWh) * conversion factor * global warming potential

               Trolley          Units                           Source                                        Assumptions / Notes
                            -22 miles                           SKM data (2007)
                           1.61 kilometers / mile               conversion factor
                          -35.4 kilometers                      calculation
                                                                                                              power consumption is for Siemens SD160 Light Rail Vehicle in
                                                                                                              Calgary, Canada; this model is similar to San Diego's S70
                                                                                                              Light Rail Vehicle
    MWh
                           3.23 kWh / vehicle km of operation   City of Calgary Transportation Department     power consumption is based on actual usage (not on technical
                                                                                                              specifications), in order to account for typical operating speeds
                                                                                                              and starts/stops

                                                                                                              assuming one vehicle per train
                           -114 kWh                             calculation
                          0.001 MWh / kWh                       conversion factor
                         -0.114 MWh                             calculation

               Trolley          Units                           Source                                        Assumptions / Notes
                         -0.114 MWh                             see above
                                                                                                              regional electricity generation emission factor based on EPA's
                         804.54 lbs CO2 / MWh                   emission factor from CCAR, Table C.1          Emissions and Generation Resource Integrated Database
    CO2
                                                                                                              (eGRID) for the WECC California subregion
                       -91.99 lbs CO2                           calculation
                    0.000454 metric tons / lb                   conversion factor
                       -0.042 metric tons CO2                   calculation

               Trolley          Units                           Source                                        Assumptions / Notes
                         -0.114 MWh                             see above
                                                                                                              regional electricity generation emission factors from the
                                                                                                              Energy Information Administration, Updated State- and
                         0.0067 lbs CH4 / MWh                   emission factor from CCAR, Table C.2
                                                                                                              Regional-level Greenhouse Gas Emission Factors for
                                                                                                              Electricity (March 2002) for California
    CH4
                   -7.66E-04 lbs CH4                            calculation
                    0.000454 metric tons / lb                   conversion factor
                   -3.47E-07 metric tons CH4                    calculation
                                                                global warming potential from CCAR Table
                            23 GWP
                                                                III.6.1
                   -7.99E-06 metric tons CO2 equivalent         calculation

               Trolley          Units                           Source                                        Assumptions / Notes
                         -0.114 MWh                             see above                                     round-trip mileage
                                                                                                              regional electricity generation emission factors from the
                                                                                                              Energy Information Administration, Updated State- and
                         0.0037 lbs N2O / MWh                   emission factor from CCAR, Table C.2
                                                                                                              Regional-level Greenhouse Gas Emission Factors for
                                                                                                              Electricity (March 2002) for California
    N2O
                   -4.23E-04 lbs N2O                            calculation
                    0.000454 metric tons / lb                   conversion factor
                   -1.92E-07 metric tons N2O                    calculation
                                                                global warming potential from CCAR Table
                           296 GWP
                                                                III.6.1
                   -5.68E-05 metric tons CO2 equivalent         calculation

  Total for
                         -0.042 metric tons CO2 equivalent
   Trolley

Conclusion:
The change in GHG emissions from decreased use of the electric trolley (in Scenario 5) is insignificant compared to vehicle emissions.

Note:
GHG emissions from utility companies will decrease in the future (i.e., in 2030) due to greater use of renewable energy sources, but this has not been factored into the
calculations.




                                                                                      C-6
          San Diego International Airport Expansion
          Sustainability Analysis




          Appendix D - Calculations of
          Criteria Pollutant Emissions




6189001
Table D-1: Summary of Daily Criteria Pollutant Emissions - Personal Cars only

Scenario                   1                 2                             3                   4                   5
                                                        % Change in    Preferred     Preferred Alternative
Scenario Name          No Project        No Project                                                           Lindbergh ITC
                                                         Emissions     Alternative   w Airport Transit Plan
Year                     2005              2030         2005 to 2030     2030                2030                 2030
pounds CO per day       13081.5           5817.2           -56%         5817.2              5706.0               5250.3
percent reduction
                                                                         0.0%                1.9%                 9.7%
from 2030 baseline
pounds N0x per
                        1374.0             480.2           -65%          480.2               471.0               433.4
day
percent reduction
                                                                         0.0%                1.9%                 9.7%
from 2030 baseline
pounds ROG per
                        1338.9             744.1           -44%          744.1               729.8               671.5
day
percent reduction
                                                                         0.0%                1.9%                 9.7%
from 2030 baseline
pounds S0x per
                          12.2              19.0           56%            19.0               18.7                 17.2
day
percent reduction
                                                                         0.0%                1.9%                 9.7%
from 2030 baseline
pounds PM10 per
                          95.7             171.4           79%           171.4               168.1               154.7
day
percent reduction
                                                                         0.0%                1.9%                 9.7%
from 2030 baseline
pounds PM2.5 per
                          59.4             113.5           91%           113.5               111.3               102.4
day
percent reduction
                                                                         0.0%                1.9%                 9.7%
from 2030 baseline


Source: SKM/Pirnie data and Tables D-2, D-3, and D-4.




                                                                         D-1
Table D-2: Estimated Daily Emissions of Criteria Pollutants for Personal Cars


Scenario                                 (1) 2005 -                                      (2) 2030 -                                     (3) 2030 -
                                         No Project                                      No Project                                  Lindbergh ITC
Estimated VMTcar                                            1132440                                          1769337                                      1769337
                         Emission Factor          Estimated Daily          Emission Factor         Estimated Daily        Emission Factor       Estimated Daily
Criteria Pollutant         (lbs/mile)               Emissions                (lbs/mile)              Emissions              (lbs/mile)            Emissions
                  CO             0.01155158           13081.46954926               0.00328779           5817.20817256             0.00328779         5817.20817256
                 NOx             0.00121328            1373.96201828               0.00027141            480.21516061             0.00027141          480.21516061
                 ROG             0.00118234            1338.93014314               0.00042052            744.05018617             0.00042052          744.05018617
                 SOx             0.00001078              12.20507891               0.00001076             19.03507735             0.00001076           19.03507735
                PM10             0.00008447              95.66142930               0.00009687            171.40423137             0.00009687          171.40423137
                PM2.5            0.00005243              59.37605956               0.00006415            113.50218214             0.00006415          113.50218214


                                       (4) 2030 -                                       (5) 2030 -                                    (6) 2030 -
Scenario                       Lindbergh ITC + Green Line                 Lindberg ITC + Green and Orange Line            SDCRAA Preferred Alternative with Old
                                                                                                                                    Town Shuttle
Estimated VMTcar                                             1735523                                          1596914                                             0

                         Emission Factor          Estimated Daily          Emission Factor         Estimated Daily        Emission Factor       Estimated Daily
Criteria Pollutant         (lbs/mile)               Emissions                (lbs/mile)              Emissions              (lbs/mile)            Emissions
                  CO             0.00328779               5706.034848              0.00328779              5250.317589            0.00328779                      0
                 NOx             0.00027141               471.0377142              0.00027141              433.4178921            0.00027141                      0
                 ROG             0.00042052               729.8305587              0.00042052               671.542029            0.00042052                      0
                 SOx             0.00001076               18.67129583              0.00001076              17.18009713            0.00001076                      0
                PM10             0.00009687               168.1285057              0.00009687              154.7007816            0.00009687                      0
                PM2.5            0.00006415               111.3330291              0.00006415              102.4413233            0.00006415                      0


Sources :
(1) VMT is daily vehicle miles traveled for personal vehicles, based on 2007 SKM transit data presented in this report.

(2) Emission Factors for On-Road Passenger Vehicles & Delivery Trucks, SCAQMD Projects 2007-2026, "Most Conservative" EMFAC2007 data,
South Coast Air Quality Management District CEQA Handbook (http://aqmd.gov/CEQA/handbook/onroad, accessed December 2007); See Appendix D-1.



Notes :
(1) VMT data is based on Year 2005 and 2030, however, available emission factors are based on years 2007 and 2026.
(2) Emission Factors derived from Peak Emissions Inventory (Winter, Annual, Summer)




                                                                                         D-2
                          Table D-3: Highest (Most Conservative) EMFAC2007 (version 2.3)
                         Emission Factors for On-Road Passenger Vehicles & Delivery Trucks
                                            Projects in the SCAQMD (Scenario Years 2007 - 2026)
                                      Derived from Peak Emissions Inventory (Winter, Annual, Summer)

                                                           Vehicle Class:
                                 Passenger Vehicles (<8500 pounds) & Delivery Trucks (>8500 pounds)

The following emission factors were compiled by running the California Air Resources Board's EMFAC2007
(version 2.3) Burden Model, taking the weighted average of vehicle types and simplifying into two categories:
                                             Passenger Vehicles & Delivery Trucks.

These emission factors can be used to calculate on-road mobile source emissions for the vehicle categories
listed in the tables below, by use of the following equation:
                                               Emissions (pounds per day) = N x TL x EF
                   where N = number of trips, TL = trip length (miles/day), and EF = emission factor (pounds per mile)

This methodology replaces the old EMFAC emission factors in Tables A-9-5-J-1 through A-9-5-L in
Appendix A9 of the current SCAQMD CEQA Handbook. All the emission factors account for the emissions
from start, running and idling exhaust. In addition, the ROG emission factors include diurnal, hot soak, running
and resting emissions, and the PM10 & PM2.5 emission factors include tire and brake wear.

                       Scenario Year: 2007                                                  Scenario Year: 2026
          All model years in the range 1965 to 2007                            All model years in the range 1982 to 2026
  Passenger Vehicles                         Delivery Trucks           Passenger Vehicles                         Delivery Trucks
    (pounds/mile)                             (pounds/mile)              (pounds/mile)                             (pounds/mile)

       CO 0.01155158                            CO 0.02407553               CO 0.00328779                            CO 0.00569435
      NOx 0.00121328                            NOx 0.02508445             NOx 0.00027141                            NOx 0.00589869
      ROG 0.00118234                           ROG 0.00323145              ROG 0.00042052                           ROG 0.00088403
      SOx 0.00001078                            SOx 0.00002626             SOx 0.00001076                            SOx 0.00002716
     PM10 0.00008447                          PM10 0.00091020             PM10 0.00009687                          PM10 0.00027657
     PM2.5 0.00005243                         PM2.5 0.00078884            PM2.5 0.00006415                         PM2.5 0.00020187



Source :
Excerpt from SCAQMD website: http://www.aqmd.gov/CEQA/handbook/onroad/onroadEF07_26.xls
Notes :
a) On the basis of DOT data reviewed, the gross vehicle weight (GVWR) of cars and 6-8 passenger SUVs is <8500; 10-15
passenger vans is >8500 pounds.
b) The calculation is modified for the Lindbergh ITC report as follows -
Emissions (pounds per day) = VMTcar (car vehicle miles traveled per day) * EF(passenger vehicles).




                                                                                                  D-3
Table D-4: VMT totals

Scenario        VMT Cars             VMT Vans            VMT Vans+delta
            1              1132440               71600            71600
            2              1769337              115617           115617
            3              1769337              115617           115617
            4              1735523              113210           115890
            5              1596914              103947           105691



Source : SKM data, GHG emission tables VMT sum of vehicle classes.
Note : The column labeled "VMT Vans+ delta" includes changes in VMT anticipated
for buses and trolleys. Absent an emission factor to assess buses and trolleys, the
EMFAC2007 emission factor for delivery trucks is used in this report to cover the
entire category of vans and other vehicles >8500 and <30,001 pounds.




                                                                            D-4
Table D-5: Assumptions for Use of SCAQMD Emissions Factors

Number                                                Assumption
         Emissions calculations for this evaluation were performed for passenger vehicles only (defined by
   1     SCAQMD as <8500 pounds). Passenger vehicles includes taxis.
         There is no clear comparison for the vehicle classes of “vans”, “buses”, and “trolleys” as used in this
         report. The SCAQMD emission factors for “delivery trucks” (>8500 pounds) may not apply directly
         to the passenger vehicles considered for airport-related ground transportation; consequently, these
   2     factors were not used in this evaluation.
         Airport-related ground transportation does not refer to ground transportation vehicles used by
         airlines or the SIA to move baggage; start, move, or maintain aircraft; or provide food service or fuel
   3     to aircraft.

         Emissions estimates consider the build-out year 2030 and baseline years 2005 and 2030 without
         any airport project. Emissions during demolition and construction can be substantial, for example,
         as projected in the SDCRAA DEIR. These emissions are not included in this screening-level
   4     evaluation for any of the airport proposals.


         Emission factors are provided for years 2007 through 2026. For the purposes of this evaluation, the
   5     emission factor for 2007 is used to reflect year 2005 and the factor for 2026 to reflect year 2030.




                                                                       D-5
          San Diego International Airport Expansion
          Sustainability Analysis




          Appendix E – LEED Background
          Information




6189001
    Appendix E – Green Airports and Green Buildings

E.1. Green Airport Concept and Framework
Airports in the United States are subject to many laws and regulations enforced by the
United States Federal Aviation Administration, the United States Environmental
Protection Agency and state and local government agencies. Environmental regulations
concern air and water quality, solid waste and hazardous materials management, natural
resources, and endangered species. Moreover, U.S. airports must evaluate the
environmental impacts of any airport development as required by the National
Environmental Policy Act (ACI, 2007c) 1 . The concept of green airports addresses the
challenges that airports face to comply with environmental regulations. As airports grow
and air traffic increases, airport environmental footprints also increase despite significant
environmental progress pursued. Green airports are looking at globally minimizing their
environmental footprint and implementing proactive measures fostering environmental
stewardship to further minimize the environmental impacts (ACI, 2007c). Green airport
practices benefit the environment by reducing the airport global environmental footprint,
generate cost-savings to the airport through the use of renewable or more efficient power
sources, and improve the community’s airport image as being environmentally-
responsible.

Since the Clean Air Act Amendments passed in 1990, environmental programs targeting
airports, such as the Clean Airports Program in 1996 and the International Centre for
Aviation and Environment in 1997, have been developed in the United States. Today,
through applied research, technical activities, consideration of innovative but proven
technologies and operational practices, promotion and recognition of environmental
innovation, regular information sharing, education, and/or publication of guidebooks,
several organizations in the United States provide resources to airports to:

1. Help better understand and address many of the environmental issues airports face
   [Airport Cooperative Research Program (ACRP) and Airports Council International-
   North America (ACI-NA)].
2. Guide future airport development and promote environmental sustainability while
   taking into account the needs of the local communities (CAP).

GreenSkies, an active European organization, consists of a worldwide information
network of environmental organizations concerned with aviation's environmental effects.
The GreenSkies network works together to exchange information and raise awareness of
the issues to promote the reduction of noise and contribution to global climate change

1
    References are available in the main report and are not included in the appendix.
San Diego International Airport Expansion: Sustainability Analysis
                                                                                        E-1
Appendix E
Green Airports and Green Buildings

(GreenSkies website). In December 2007, GreenSkies announced a launch to foster
better aviation practices and environmental responsibility in North America, through a
large conference event in May 2008.

E.2. Green Buildings
Through an overview of green buildings and the LEED Green Building Rating System,
this section summarizes existing information on “green” airports and sustainable
practices in buildings and other areas related to the build environment.

E.2.1. Overview of Green Building Concepts
Within the broad framework of sustainability, the concept of green buildings is an
expanding practice. Recent experience and research have led scientists, builders,
developers, governments, and communities to realize that the design, construction, and
operation of buildings have an irreversible impact on the environment. Irreversible
environmental impacts of a building include the use of non-renewable resources (e.g.,
construction materials, energy use), water consumption, and the adverse effects of
building footprint to the local ecology and potentially biologically-diverse habitats. More
precisely, in the United States alone, buildings account for 65 percent of electricity
consumption, 36 percent of energy use, 30 percent of greenhouse gas emissions, 30
percent of raw materials use, 30 percent of waste output (136 million tons annually), and
12 percent of potable water consumption (USGBC, 2007). These numbers should not be
surprising considering that buildings include where we all live and work. However,
because of their large environmental footprint buildings provide a target where
environmental improvements can have a large benefit. In 2002, the United States Green
Building Council (USGBC) defined the concept of “green building” as design and
construction practices that significantly reduce or eliminate the negative impact of
buildings on the environment and occupants. According to USGBC, the benefits of green
buildings are three-fold: environmental, economic, and social. First, environmental
benefits include the enhancement and protection of ecosystems and biodiversity, the
improvement of air and water quality, the reduction of solid waste, and the conservation
of natural resources. Second, economic benefits include the reduction of operating costs,
the enhancement of asset value and profits, the improvement of employee productivity
and satisfaction, and the optimization of life-cycle economic performance. Finally, the
social benefits related to health and community include the improvement of air, thermal,
and acoustic environments, the enhancement of occupant comfort and health, the
minimization of strain on local infrastructure, and the contribution to overall quality of
life.




                                          San Diego International Airport Expansion: Sustainability Analysis
  E-2
                                                                                              Appendix E
                                                                         Green Airport and Green Buildings

E.2.2. LEED Green Building Rating System
The LEED Green Building Rating System developed by USGBC is a nationally-accepted
benchmark for the design, construction, and operation of high performance green
buildings. LEED was created to:

     Facilitate positive results for the environment, occupant health and financial return;
     Define “green” by providing a standard for measurement,
     Encourage and accelerates global adoption of sustainable green building and
     development practices through the creation and implementation of universally
     understood and accepted tools and performance criteria, and
     Promote whole-building, integrated design processes (USGBC, 2007). Founded in
     1993, USGBC started conducting research in green buildings.


   Table E-1.Basis and Main Objectives of the Five Performance Criteria for New
                                  Construction

 Performance Criteria for New Construction                      Basis and Main Objectives

                                                                Development and construction processes often are
                                                                destructive to local ecology

                                                                Selection of an appropriate project location can
 Sustainable Sites                                              reduce the need for cars and reduce urban sprawl

                                                                Project integration into the surroundings and
                                                                become a considerate and beneficial neighbor for
                                                                the lifetime of the building
                                                                Strategies to reduce potable water usage for
                                                                personnel and landscaping
 Water Efficiency
                                                                Innovative waste treatment technologies

                                                                Adaptive landscaping not requiring irrigation
                                                                Buildings consume 35% of the energy and 65% of
                                                                the electricity produced in the United States with
                                                                major impacts to the natural environment

                                                                Chlorofluorocarbons (CFCs) and
 Energy and Atmosphere (Energy Efficiency)
                                                                hydrochlorofluorocarbons (HCFCs) have major
                                                                impact on the natural environment and human
                                                                health

                                                                Use of renewable and alternative energy




                    :
San Diego International Airport Expansion: Sustainability Analysis
                                                                                                                E-3
Appendix E
Green Airports and Green Buildings


 Performance Criteria for New Construction          Basis and Main Objectives

                                                    Extraction, processing and transportation of
                                                    materials have major environmental impacts

                                                    30% of landfill volume consists of construction and
 Materials and Resources                            demolition waste

                                                    Reduce, reuse and recycle

                                                    Use of rapidly renewable materials
                                                    Americans spend 90% of their time indoors

                                                    Indoor air can be as much as 100 times more
 Indoor Air Quality                                 polluted than outdoor air

                                                    Focus on material off-gassing, personal comfort,
                                                    productivity and health; minimum IAQ performance
Adapted from USGBC, 2006, LEED for New Construction Version 2.2. November.


Working with a committee of diverse professionals, such as architects, realtors, a
building owner, an environmental professional, a lawyer, and industry representatives,
USGBC developed the first LEED Pilot Project Program in August 1998 through an
open, consensus-based process (USGBC, 2006). The Pilot Program matured and evolved
into the LEED Green Building Rating System Version 2.0 released in March 2000, and
then into the LEED Green Building Rating System for New Commercial Construction
and Major Renovations, or LEED for New Construction Version 2.2 (LEED-NC),
released in October 2005. Under the LEED-NC, application standards are available for
specific types of buildings, such as healthcare, school, laboratory, and retail. In addition
to the LEED-NC, the LEED rating system product portfolio include a LEED standard for
Existing Buildings (EB), Commercial Interiors (CI), and three pilot LEED standards,
namely, Core and Shell (CS), Home (H), and Neighborhood Development (ND). LEED
standards are organized around five performance criteria, including sustainable site
development, water efficiency, energy efficiency, materials and resources, and indoor
environmental quality. Performance criteria for LEED rating systems other than New
Construction are similar. Table E-1 highlights the basis and main objectives of each
performance criteria for New Construction.

Each of these performance criteria contains a list of credits. If requirement(s) under a
credit is achieved, points are accumulated towards LEED certification. The minimum
number of points for a New Construction building to achieve certification is 26. There
are four levels of certification under LEED-NC, with the number of points to obtain
shown in Table E-2.




                                             San Diego International Airport Expansion: Sustainability Analysis
  E-4
                                                                                           Appendix E
                                                                      Green Airport and Green Buildings

                     Table E-2.LEED New Construction Certification Levels
                      Certification Level for New                    Point Range
                      Certified                                         26-32
                      Silver                                            33-38
                      Gold                                              39-51
                      Platinum                                          52-69
                    Source: USGBC, 2006, LEED for New Construction Version 2.2. November.


As a third party validation of achievement, LEED certification is a mark of recognition of
quality buildings and environmental stewardship. Nevertheless, perceived barriers exist
in the adoption of LEED and limit the expansion of green buildings. Some of the
perceived barriers are higher first costs, lack of “green” awareness principles, and the
prevalent short term budget pressures. In a 2005 study, 70 percent of stakeholders
interviewed saw costs as a perceived barrier; however, 80 percent agree on the economic
payback of green design (Zweig White, 2004). In addition, recent trends have shown that
construction costs per square foot of LEED-certified buildings are not consistently higher
than a building with environmentally-friendly goals (Davis Langdon, 2004). Although
construction costs have dramatically increased overall recently, buildings are still
achieving LEED-certification, but the idea that green is an added feature continues to be
a problem (Davis Langdon, 2007).

E.2.3. Who Uses LEED?
LEED certification is voluntary, although several local governments around the United
States have included LEED concepts in their codes and have passed city
ordinances/executive orders that require LEED standards for new buildings. Indeed,
local, state, and federal governments (which correspond to approximately 48 percent of
all LEED users) are incorporating LEED standards into their design. Other LEED users
include private sector (33 percent) and non-profit organizations (14 percent). From 2001
to 2007 (as of April 12, 2007), the total number of LEED-registered projects (which
indicates an intent for a building to achieve LEED certification) jumped from 321 to
7,315; and the total number of LEED-certified projects (which indicates the building
received a LEED certification plaque) raised from five to 1,004.




                    :
San Diego International Airport Expansion: Sustainability Analysis
                                                                                                  E-5
Appendix E
Green Airports and Green Buildings

This page left intentionally blank.




                                      San Diego International Airport Expansion: Sustainability Analysis
  E-6
          San Diego International Airport Expansion
          Sustainability Analysis




          Appendix F - Worldwide Airport
          Environmental Initiatives from the
          Airports Council International




6189001
                                                                                                                                          Last updated: Wednesday, 28 November 2007


Worldwide airport environmental initiatives tracker file
Airports around the world are finding innovative ways to reduce their impact upon the environment in which they operate. Each initiative goes some way to reducing airport’s footprint
and contributes to the larger steps that the whole aviation industry is making in the environmental area. The following is just a small sample of some of the different schemes in place
at airports.
                  Airfield emissions reductions
                  Noise mitigation
                  Recycling initiatives
                  Winter services
                  Water pollution reduction
                  “Smart” buildings and energy efficiency
                  Communications initiatives and airport-wide campaigns
                  Intermodality and surface access
                  Other environmental initiatives
Airport                  Initiative                     Results / notes

Airfield emissions reductions
Seattle-Tacoma           Powering its auto fleet with
International Airport    compressed natural gas
USA
Phoenix International    Alternative fuels programme    PHX has used compressed natural gas for its auto fleet and bus fleet, starting in 1994 with (at that time) the largest CNG fill station in the U.S.
Airport, USA                                            Currently PHX has 3 CNG fill stations, 2 of which are among the highest volume public access CNG stations in the country. PHX has increased its
                                                        CNG bus fleet to 98 buses (Interterminal and to the Consolidated Rental Car Center). Besides giving access for the public (the U.S. Postal
                                                        Service is among those users), PHX modified its contracting process for taxis and shuttles to require CNG use in those vehicles, and now has 90
                                                        SuperShuttle vans and 174 taxicabs using CNG as a condition of their contracts.

BAA’s airports, UK       Emissions reduction targets    At our airports, BAA has established an absolute CO2 emissions reductions target of 15% below 1990 levels by 2010, despite a projected growth
                                                        in passenger numbers of around 70% during this period. This is being achieved through improvements in energy efficiency and conservation and
                                                        through increasing the use of renewable energy sources. We also continue to invest in public transport alternatives for access to airports, to
                                                        encourage passengers and staff to leave their cars at home.

Auckland International   Air traffic management         Airways New Zealand has been working with Air New Zealand and Qantas in a trial to reduce fuel use and emissions as the aircraft came into
Airport, New Zealand     techniques                     land. Some flights into Auckland would be spaced to allow a glide descent into the airport from their top of descent point. Airways New Zealand
                                                        main trunk manager Lew Jenkins said, "These glide descent profiles will be flown with the aircraft engines set at idle, thereby significantly reducing
                                                        fuel burn and emissions," The trial is to establish what the actual fuel burn was for an arriving flight and to gauge the potential fuel savings and
                                                        associated emission reductions. The trial will target Air New Zealand and Qantas 747 aircraft which typically arrived when other traffic was light,
                                                        meaning minimum disruption to other aircraft. – From NZPA

Auckland International   Use of ground power units      In partnership with the Board of Airline Representatives New Zealand (BARNZ), Auckland Airport will be the first New Zealand airport to install
Airport, New Zealand                                    ground power units (GPUs). GPUs reduce fuel consumption and fuel emissions as well as noise, aircraft maintenance costs and per-passenger
                                                        costs. The installation of this technology negates the use of aviation fuel as aircraft would normally have to remain powered up to maintain internal
                                                        operating conditions while on the stand. Pre-conditioned air (PCA) units work in tandem with GPU units. The PCA unit will be an electric, self-
                                                        contained, automatically controlled airconditioning unit that provides ventilation, cooling, dehumidifying, filtering, and optional heating of air
                                                        supplied to parked aircraft. The units will be located on 10 hard stands at the internal terminal pier. As a result of the installation, airlines will
                                                        reduce emissions at Auckland Airport by up to 189 tonnes per annum.

Frankfurt Airport,       Hydrogen vehicle trial         As part of a long-term test program co-financed by the European Union (EU), Fraport AG has started using two hydrogen-powered vehicles at
Germany                                                 Frankfurt Airport (FRA). Two A-Class cars from DaimlerChrysler will undergo practical testing on and off the airport site until the end of 2009.
                                                        Fraport received the keys to its fuel-cell test vehicles last Friday at the premises of Infraserv Höchst in Frankfurt-Höchst, where the first public
                                                        hydrogen refueling station in the German state of Hesse was opened earlier by Hessian state minister of economics Dr. Alois Rhiel. Fraport will
                                                        take delivery of two more of same hydrogen cars at the end of next year.

Hong Kong International Green Apron Policy              The airport authority adopted a Green Apron Policy as part of a number of initiatives to demonstrate commitment to corporate social responsibility
Airport                                                 and to minimse air pollution. One of the programmes is to replace our existing 43 vehicle fleet with alternative fuel or low emission vehicles over
                                                        the next five years. To date, there are 3 LPG and 4 hybrid vehicles in the fleet. We have in place fixed ground power and pre-conditioned air
                                                        supply at each frontal gate such that aircraft can shut down their APUs while parked at the gate.




                                                                                   2
Airport                       Initiative                             Results / notes
Dallas/Fort Worth         Boiler and ground fleet renewal Energy plant upgrade project Innovative technology included new 6 million gallon thermal energy tank storage and state-of-the-art boilers and
International Airport USA                                 chillers and yields a projected avoided future energy use of 25 million MMBTUs over the useful life of the facilities. This reduced NOx emissions
                                                                     by 95 percent. 100 percent of the light-to-medium duty fleet, 72 percent of heavy duty and off-road fleet; and 100 percent of the bus and shuttle
                                                                     van fleet were replaced with low emissions or alternative fuel vehicles. This reduced nitrogen oxide emissions by 39 tons a year with an 86%
                                                                     reduction in Air Emissions. DFW has achieved an estimated 2 tons per ozone season day (475 tons a year) reduction in NOx emissions from the
                                                                     fleet conversion programme.

Zurich Airport,               Fixed energy systems for               Operation of aircraft APU is subject to gaseous emissions and noise, thus often contributing significantly to the local air quality impacts and site
Switzerland                   aircraft (FES)                         noise impacts. To mitigate emissions and noise, fixed energy systems (FES) can be designed that provide electrical energy and preconditioned air
                                                                     to aircraft. At Zurich Airport all hard stands (or terminal stands, connected to the concourses by passenger loading bridges) provide FES. The use
                                                                     of auxiliary power units (APU) is subject to certain restrictions and the airlines are obligated to use the FES primarily. The ecological benefits of the
                                                                     fixed ground power systems are convincing: In 2001, a total of 118,000 cycles of aircraft equipped with APU has been recorded (of a total of
                                                                     309,000 aircraft movements and 21 million passengers). The use of the fixed energy system has saved 12,170 t of fuel amounting to 38,500 t of
                                                                     CO2 and 75 t of NOx. The NOx reduced equals 4.3% of all airport induced NOx-emissions and 60% of all APU induced NOx-emissions.

San Francisco Airport,        Taxiing trials                         In March 2007, the airport worked jointly with Virgin Atlantic, Boeing, and FAA to conduct the first aircraft towing trial in North America. In the trial,
USA                                                                  an aircraft was towed from the gate closer to the runway, reducing the time the aircraft engines were running on the taxiway. Preliminary
                                                                     calculations showed that 595 pounds of jet fuel were saved and 1,709 pounds of carbon dioxide emissions were prevented without causing delays
                                                                     or congestion. While further study is required, if only 30% of departing flights use this protocol at SFO, 16,000 tonnes of carbon dioxide emissions
                                                                     could potentially be eliminated each year.

Toronto International         Alternative energy sources             The Airport Authority constructed a three turbine cogeneration plant at Toronto Pearson International Airport for simultaneous production of
Airport, Canada                                                      electrical power and thermal energy from natural gas. The plant is the first in a series of natural gas turbine facilities built to meet Ontario’s pursuit
                                                                     for alternative clean electrical generation. The Airport Authority worked closely with both federal and provincial governments to develop an
                                                                     Environmental Assessment process satisfactory to both levels of government. Using natural gas instead of coal results in reduced greenhouse
                                                                     gas, particulate, and sulfur dioxide emissions.



Noise mitigation
Oakland International         Residential sound insulation           The airport has established a sound insulation program for noise impacts associated with aircraft noise and vibration, for all residences
Airport, USA                                                         located within the 65 to 70 Community Noise Equivalent Level (CNEL) contour to reduce interior noise to acceptable levels. Noise insulation
                                                                     is also offered for certain school buildings that lie within the future 65 CNEL. In some areas homes and schools outside the 65 CNEL contour
                                                                     have been offered sound insulation partly due to historical reasons and separate agreements although federal funds cannot be used.

Hamburg Airport               Noise budget                           The airport’s operating licence is subject to noise limits based on the surface area of land around the airport where the noise exposure exceeds a
                                                                     certain noise level – Leq 62 dBA. The airport conducts continuous noise monitoring and reports annually on its operation within the noise budget.

Hamburg Airport               Noise surcharge                        Landing fees levied upon airlines are structured according to aircraft weight and noise. For some classes of aircraft, landing fees can be a factor
                                                                     or 4 to 10 higher than for other less noisy aircraft.

Vienna Airport , Austria      Mediation for new runway               Vienna Airport emabarked on a mediation process between the airport, local government and local communities regarding a possible new runway.
                              approval                               The process took five years and was successful in achieving, not only agreement on the location and operation of a new third runway, but far
                                                                     reaching cooperation on issues including runway and night time operation, flight tracks and the prevention of new housing in high noise areas.



                                                                                                 3
Airport                    Initiative                      Results / notes
Detroit Metropolitan       Residential sound insulation    The Residential Sound Insulation Programme (RSIP) is one element in a larger noise compatibility plan voluntarily initiated by DTW which included
Airport, USA                                               the installation of noise berms around the airport’s perimeter, the acquisition of homes most impacted by airport related noise, modified air traffic
                                                           control procedures, preferential runway use and aircraft engine ground run-up procedures. Residential sound insulation typically includes new
                                                           acoustic windows, primary and secondary doors, attic insulation and other architectural treatments. In most homes, it also included new heating,
                                                           ventilation and air-conditioning systems, allowing homeowners to keep windows closed to block noise infiltration. Seven schools were also
                                                           insulated and 265 homes most impacted by aircraft noise were acquired by the programme at the appraised market value.



Recycling initiatives
Seattle-Tacoma             Vendors recycle their coffee    The original goal was to send two tons of coffee grounds to a compost station every month. Three years later, Sea-Tac recycles 10 to 12 tons of
International Airport      grounds.                        coffee grounds a month.
USA
Seattle-Tacoma             Food-donation programme         Vendors give leftover pre-packaged goods to a food bank for the city’s needy.
International Airport
USA
Seattle-Tacoma             Major recycling programme       Sea-Tac went from recycling 112 tons of material five years ago to an estimated 1,200 tons this year — everything from contaminated soil to motor
International Airport                                      oil. And this year's materials are expected to bring in $40,000, while saving about $130,000 in disposal fees.
USA
Los Angeles                Electricity from waste          8,000 tonnes of food waste produced each year at the airport is used to produce methane gas which is then recycled and turned into electricity
International Airport,
USA
Jersey Airport, United     Recycling concrete              Old runway concrete is crushed and recycled to be used in footpaths and other pavements – approximately 30,000 square metres in one current
Kingdom                                                    project.

Zurich Airport,            Recycling                       Since 1992 Zurich Airport is operating its waste management according to an airport wide waste management concept. It governs the organisation
Switzerland                                                and generally applicable principles of waste management at Zurich Airport, and includes standard requirements concerning recycling in given
                                                           areas. Regarding the results 2006, Zurich had a recycling quote of 0.71 (recycling to incineration, according to the ADV Guideline “environmental
                                                           key figures for airports”). Collecting waste for recycling is only one part of a complete resource life cycle. For instance: If there is no demand for
                                                           recycled paper on the market, separation does not make much sense. Due to this, Unique (Flughafen Zürich AG), owner and operator of Zurich
                                                           Airport, supports paper recycling not only by waste management but also by consistent using recycling paper in its administration and offices. The
                                                           quota of recycling paper was 86 percent in 2006.

Stansted Airport, United   Re-using cut grass instead of   UK airports operator, BAA, is required to keep grass areas around the runways at a particular height to prevent birds nesting and landing, which
Kingdom                    fertiliser                      could interfere with aircraft. So, in 2003, it started composting and recycling 2,000 tonnes of cut grass from Stansted Airport, rather than having it
                                                           removed by waste contractors. The compost is left to mature for five months, and then analysed before being recycled on to the grassy areas,
                                                           replacing the artificial fertiliser previously used.



                                                                                      4
Airport                       Initiative                           Results / notes
Leeds Bradford Airport,       General waste recycling              To encourage waste reduction at Leeds Bradford Airport in the UK, initiatives have been implemented that include both aircraft and terminal waste.
United Kingdom                                                     The airport recycles cardboard, glass, newspapers, magazines, scrap metal and large batteries, and there is a further incentive for on-site
                                                                   business partners to reduce their waste through a scale of charges for waste disposal calculated on the quantities of waste produced and the
                                                                   amount recycled.

Hong Kong International Composting and planting                    The airport authority recycles 60 tonnes of food waste per year from the passenger terminal building to produce compost for use in airport
Airport                                                            landscaping. The airport sponsored an organic farming project called ‘planting love and care” which was organised by the Hong Kong Sheng Kung
                                                                   Hui Tung Chung Integrated Services (SKH). Participants include families from Tung Chung and members of the airport community. Young plants
                                                                   are nursed at individuals’ homes with soil conditioners generated from the food waste composting program at HKIA. Training courses on organic
                                                                   farming were given to the participants. At the end of the competition period, mature plants will be placed at the HKIA Historic Garden. The
                                                                   planting ceremony and experience sharing session will be held at the HKIA Historic Garden on 31 Mar 07.

Athens International          Reuse and recycle                    422,000 cubic meters of treated water from the airport’s sewage treatment plants are used for irrigation. Furthermore, the extensive airport
Airport “Eleftherios                                               recycling programme, which is based on the “polluter pays principle”, has lead to the recycling of more than 1,740 tons of materials, such as paper,
                                                                   wood, plastic, glass, etc. The new recycling centre, where employees can also bring recyclables from home, and the continuing office recycling
Venizelos”                                                         programme (mainly for paper) contribute significantly to the achievement of the 20% recycling rate goal by 2008.

Dallas/Fort Worth         Reduced 2.5 million cubic yards At the beginning of DFW Airport’s 2.8 billion capital development program in the year 2001, a protocol was established to sort, segregate,
International Airport USA of excavated soil.              manage, test and reuse excavated soil being generated by the project work. Approximately 2 million cubic yards of soil have been excavated and
                                                                   stockpiled on the Airport for future use. The reuse of this material to date has saved the Airport approximately $1,500,000 in disposal costs and
                                                                   avoided clean soil purchase costs for capital projects.

Dallas/Fort Worth         Recycled 355,000 tons of                 A concrete recycling program was also established to reuse demolition debris generated by DFW Airport’s capital development program.
International Airport USA demolition debris for on-airport         Concrete rubble being generated by the demolition of existing structures and pavements were crushed to provide usable material for use as
                                                                   bedding for underground utilities such as storm drain pipe, temporary roads, contractor lay down yards, as base under airfield runway extensions
                          cement production                        and taxiways. To date, approximately 190,000 tons of demolished concrete has been recycled as a result of this initiative; savings to the Airport of
                                                                   about $1,140,000 in disposal costs and materials acquisition costs.

Oakland International         Airline pillow recycling             OAK is one of the first airports in the nation to participate in a pillow recycling program. Normally, airline pillows are immediately disposed of
Airport, USA                                                       following the completion of a flight. This waste goes directly into landfills. The pillow recycling programme collects these pillows for use as
                                                                   insulation or as material in making furniture.

Oakland International         Consolidated waste and               Prior to 2003, each airline contracted separately with a waste company, resulting in inefficient garbage disposal and inconsistent recycling. Then,
Airport, USA                  recycling programme                  in 2003, OAK worked with the airlines to consolidate their waste and recycling into one coordinated program. The airlines now recycle magazines,
                                                                   newspaper, cardboard and bottles, diverting over 101 tons of recycling from landfills in 2004, resulting in less waste going to the landfills and about
                                                                   $14,000 in cost savings monthly.

Canberra Airport,             Water recycling system               Canberra International Airport announced (10-May-07) plans to become the first Australian airport to recycle its water. The airport will install an
Australia                                                          Aquacell Water System at a cost of AUD1.2 million. Around 100,000 litres of water will be recycled across the airport daily from the initiative.

Portland International        Recycling programme                  The waste management programme thrives through partnerships with passengers, airlines, tenants, and neighbours. It resulted in 770 tonnes of
Airport, USA                                                       recycled materials being diverted from landfills in 2006 alone. The airport recycled 98 tonnes of paper, plastic, and glass and composted 157
                                                                   tonnes of coffee and food waste. Through an innovative food grease recycling programme, kitchen waste oils are collected and sent offsite for
                                                                   processing into biodiesel. Foreign language periodicals are also distributed for reuse at local schools.




                                                                                              5
Airport                  Initiative                      Results / notes

Winter services
Munich Airport, Germany Recycling de-icing fluid heats   Aircraft are de-iced on specially designated, remote areas at the airport, which are provided with a recovery system for de-icing fluids. Sprayed
                        the terminal building            fluid that falls onto the de-icing areas is channelled – along with melted ice and snow – via gutters into large subterranean storage tanks. This
                                                         mixture is then trucked to the recycling facility, refined and distilled, enabling the glycol-based de-icing agent to be recovered. It is then mixed with
                                                         additives to produce de-icing fluid, which, after laboratory analysis and clearance by the manufacturer, can be used again. This form of recycling
                                                         produces between 60% and 70% of the airport’s annual de-icing fluid requirements. The process generates ‘waste heat’ as a by-product which
                                                         helps keep Munich Airport warm. When this system is in full operation, it covers a substantial share of the airport's heating requirements.

Detroit Metropolitan     Recycling de-icing fluid        DTW has a very effective de-icing fluid management program. Airlines have agreed to perform most of their aircraft de-icing operations at four
Airport, USA                                             runway-end de-ice pads, where the fluid is more concentrated and thus has a value to recyclers. Spent anti-freeze is collected at these pads by an
                                                         outside contractor, taken off airport, and filtered and distilled. The company produces 99.9% pure propylene glycol, which then becomes a
                                                         component in other products such as automotive dashboards, anti-freeze, etc. DTW has recycled more spent anti-freeze than any airport in the
                                                         world for the past seven years.

Seattle-Tacoma           Recycling de-icing fluid        Following 10 years and over $60 million of construction, the Port of Seattle implements AKART for their treatment of aircraft de-icing fluids
International Airport                                    captured on their aircraft operations areas at the terminals. The Industrial Waste Treatment Plant (IWTP) AKART diverts industrial stormwater
                                                         captured in over 20 miles of collection piping systems and segregates those flows containing high concentrations of aircraft de-icing fluids into two
USA                                                      of three storage lagoons containing over 80 million gallons of storage. With this new system, in conjunction with other process improvements and
                                                         a new 20,000 foot forced main pumping system to the local POTW, over 90% of the aircraft de-icing fluid that enters the system is removed from
                                                         the estimated 300 million gallons per year of processed flow. The new system reduces the hydraulic loading to the POTW by approximately 80%
                                                         over sending the entire annual flow to the POTW for treatment. The remaining low concentrated runoff is treated for the removal of fuels and
                                                         suspended solids and is then discharged through a deep water outfall located in Puget Sound.

Hamburg Airport,         Recycling de-icing fluid        Winter de-icing only takes place on sealed apron surfaces that ensures no-one of the fluid run-off can reach the soil or groundwater. Hot water is
Germany                                                  used first and glycol is only used to prevent re-icing if necessary.

Dallas/Fort Worth        Recycling de-icing fluid        Captured and treated five million pounds of spent aircraft deicing fluids preventing discharge to the creeks and rivers surrounding the Airport over
International Airport,                                   the past five years. DFW accomplished this pollution prevention and source reduction metric by constructing seven source isolation deicing pads,
                                                         capturing and storing spent glycol-based deicing/anti-icing fluids in 1.5 million gallons of underground tanks and 20,000,000 gallons above ground
USA                                                      storage ponds, constructing super-pipes to convey captured and stored spent glycol to treatment and constructed a reverse osmosis treatment
                                                         facility to remove the glycol from the collected effluents before discharging the clarified effluent to the regional publicly-owned sewerage treatment
                                                         plant.

Zurich Airport,          Treatment of de-icing waste     By the treatment of de-icing waste, Zurich Airport follows a new approach of a spray irrigation system. A major part of the de-icing sewage
Switzerland                                              (moderately contaminated) is sprayed via a sprinkler system over suitable fields at the airport. As the waste water seeps through the ground, it is
                                                         cleansed through natural processes to acceptable purity levels. The idea behind this method is based on the observation that for some time a
                                                         considerable amount of the de-icing agents used at the airport have been blown by the wind into the surrounding meadowland, where they have
                                                         seeped into the ground and decomposed without having a detectable impact on the condition of the ground water. The pollutants decompose
                                                         through a natural process involving microbiological action as they are filtered in the upper 60-90 cm of ground layer. The decomposition processes
                                                         are mostly aerobic. The purified de-icing waste water then flows via the drainage system into the receiving waterway. This method relies heavily on
                                                         natural processes and is relatively inexpensive. Further information: Treatment of De-icing Sewage




                                                                                    6
Airport                   Initiative                    Results / notes

Water pollution reduction
Auckland International    Storm water treatment ponds   All water runoff from the airfield and a number of other areas is caught by the airport’s drainage system. There are fuel catchment pits in a number
Airport, New Zealand                                    of areas, to collect any excess fuel if there is a spill and between the drainage system and the discharge are eight massive treatment ponds in
                                                        which the wastewater is forced it through bales of wool – this removes impurities. It is often joked by airport staff that the water discharged into the
                                                        Manukau Harbour (on which the airport sits) is cleaner than the water in the bay itself – but the likelihood is that this is a factual statement



“Smart” buildings and energy efficiency
Phoenix International     Energy efficient terminals    All terminals at PHX have sophisticated Energy Management Systems with digitised controls, electronic valves, etc. and centralised control rooms.
Airport, USA
Vancouver Airport,        Solar hot water heating       Vancouver International Airport Authority has installed a solar powered hot water heating system which the airport has estimated contributes to
Canada                                                  savings of nearly $90,000 and 8,569 GJ per year. The 100 solar panels have been installed on the roof of the domestic terminal building and help
                                                        to heat an average of 800 gallons of hot water each hour. The $500,000 project is paid for in part through $85,000 of incentive funding through BC
                                                        Hydro’s Power Smart Programme. Since 2003, Vancouver International Airport Authority and BC Hydro have worked in tandem to reduce energy
                                                        consumption and energy costs at the airport. The savings associated with the installation of the solar panel heating system will add to the nearly
                                                        $2 million saved to-date through various Power Smart and energy reduction initiatives already put in place at the airport.

La Palma Airport, Spain   Wind power                    La Palma Airport has become the first in Spain to be equipped with wind power generators. The plant consists of two 660kW nominal strength
                                                        wind generators that produce most of the energy need to run the airport facilities. The wind generator turbines are situated in the eastern part of
                                                        the airport where they do not interfere with air navigation. Between May and November 2003, 943 MWh were produced saving 34,000 Euros.

Auckland International    Energy efficient buildings    Auckland Airport employs an energy manager, has an asset management and control team, and uses an energy conservation committee to review
Airport, New Zealand                                    performance. The international terminal is the major user of energy at the airport. Ventilation, heating and air conditioning account for about 80 per
                                                        cent of the energy use in the terminal. Most of the remaining 20 per cent is used for lighting. The challenge is to maintain a comfortable ambient
                                                        temperature and a bright crisp environment. Features of the terminal climate control system: A combination of efficient building insulation and
                                                        intelligent control systems make terminal buildings comfortable and energy efficient. The terminal system uses natural light as much as possible;
                                                        integrates the flight information display system and the building management system. This means that temperature, air conditioning and lighting
                                                        are automatically adjusted depending on weather, daylight, and the numbers of arriving and departing passengers; uses daylight sensors, timers
                                                        and motion detectors to minimise unnecessary light use

Hamburg Airport           New terminal features         The new Terminal 1 now features a rainwater utilisation system, a thermo-labyrinth has been built to pre-warm or pre-cool outside air and to
                                                        reduce air conditioning needs, and water-saving tap filters are used throughout the building. Other features include a new water softening plant,
                                                        reduced indoor heating temperatures and hangar illumination levels.

Zurich Airport,           Stabilisation of the energy   One of the requirements attached to the building permit for expansion stage 5 was that, following its completion, energy consumption at Zurich
Switzerland               consumption                   Airport has to be stabilised at the 1994 level. An audit carried out 2006 validated that this ambitious objective has being met.
                                                        Further information: Energy Management at Zurich Airport

Chicago Airports, USA     Solar panels                  The Department of Aviation unveiled a 3,860 square-foot green roof and solar panel array atop the Chicago Fire Department’s Rescue Building #3
                                                        at O’Hare Airport. Recently, a solar panel array was installed on the roof of the firehouse at Midway Airport.



                                                                                   7
Airport                  Initiative                            Results / notes
Arlanda Airport,         Climate neutral                       The LFV Group operates Arlanda Airport and is the first major Swedish business to choose to become climate neutral. This means that LFV is now
Stockholm, Sweden                                              able to offer goods and services that are produced without negative impact on the climate. A climate neutral enterprise calculates and reduces its
                                                               carbon dioxide emissions via an effective action programme. An audit is carried out annually and those emissions that the enterprise could not
                                                               eliminate can be compensated for by the purchase of emission reduction units or certificates that show emission reduction measures have
                                                               occurred elsewhere. Actions taken to reduce emissions of such gases will lead to reduced costs as fewer certificates will have to be purchased.
                                                               Greater emphasis is placed on, for example, energy-saving actions, as these will be more profitable than previously.

Boston Logan Airport,    LEED-certified terminal building The Massachusetts Port Authority and Delta Airlines opened the new Terminal A at Boston Logan International Airport in 2005. The Terminal was
USA                                                            the first in the country to be certified by the Leadership in Energy and Environmental Design (LEED) rating system and the U.S. Green Building
                                                               Council. The project included such elements of sustainable design as alternative transportation options, a special storm water filtration device, a
                                                               heat island membrane, mechanisms to enhance water efficiency, daylighting for energy efficiency, use of sustainable materials, and measures to
                                                               enhance indoor air quality. The airport has realized 12 percent energy savings, equating to almost $300,000 annually, and 36 percent water
                                                               savings (or 1.7 million gallons per year).

San Francisco Airport,   Solar Panels on roof                  San Francisco International Airport Terminal 3 now boasts more than 2,800 solar panels on its rooftop. The solar panels were implemented as part
USA                                                            of the San Francisco Public Utilities Commission and SFO's joint solar energy project to help reduce energy use. The new energy system will
                                                               provide enough electricity for all of the daytime lighting needs within Terminal 3 with excess power to spare. The solar panels will save enough
                                                               energy to power about 300 homes each year. In addition, utilising the solar panels as opposed to typical energy generating methods that require
                                                               fossil fuels will save approximately 7,200 tonnes of carbon dioxide over a period of 30 years.



Airport-wide education or communications programmes
San Diego Airport, USA   Recycling education                   San Diego International Airport’s recycling programme boasts 50 recycling bins through the terminals collecting paper, glass bottles, cans and
                         programme                             plastic drinks bottles. The airport doubled its recycling efforts to 250 tonnes per year in 2003 and has published an educational handbook in
                                                               Spanish and English explaining how its recycling programme works and what can and cannot be recycled. The airport also promotes an
                                                               educational anti-littering campaign called “Don’t Trash California”, the aim of which is to reduce the amount of litter in and around the airport by
                                                               recycling wherever possible. Recent follow-up initiatives have included a sponsored ‘house-cleaning’ event at the airport that gave airport staff and
                                                               tenants the opportunity to dispose properly of items that can no longer be classed as general rubbish, such as old computers, batteries and
                                                               fluorescent light bulbs. More than three tonnes of electronic waste was collected and either recycled or disposed of during the week.

Aeroport de Paris        Environment Partners Club             As part of their work on the environment, Paris-Charles de Gaulle and Paris-Orly airports opened their Environment Partners Clubs in 2003 and
                                                               2005 respectively. The purpose of these structures is to commit companies operating at the airports to implementing an Environmental
                                                               Management System covering their operations and to thereby make Paris-Charles de Gaulle and Paris-Orly truly environmentally friendly airports.
                                                               Today, these Clubs, in addition to offering a resource centre for best environmental practices, are becoming the new driving forces behind the
                                                               airport Environmental Management Systems. The Environment Partners Clubs at Paris-Charles de Gaulle and Paris-Orly airports operate on the
                                                               basis of the three pillars that form an Environmental Management System: gathering information, training staff/raising their awareness and self-
                                                               evaluation to foster improvements. www.ecoairport.fr (FR)




                                                                                          8
Airport                  Initiative                         Results / notes
Auckland Airport, New    “Greening the airport”             Greening the Airport is an Auckland International Airport Limited (AIAL) strategy developed to raise environmental awareness amongst staff. The
Zealand                  programme                          strategy involves encouraging airport staff to participate in environmental initiatives and to build environmental awareness into their everyday
                                                            working life. By motivating staff to carry out environmentally beneficial actions, the airport’s overall environmental impact is reduced. Greening the
                                                            Airport focuses on resource efficiency, waste minimisation and energy conservation. Specific initiatives being developed include increasing
                                                            recycling facilities, lowering office paper consumption, energy conservation education and such small initiative as replacing water cooler plastic or
                                                            paper cups with glasses that can be washed and reused.. The long-term goal is to encourage other airport-based companies to implement the
                                                            Greening the Airport programme.

Chicago Airports, USA    Green education programme          Green-themed kiosks are sprouting up throughout the terminals at O’Hare and Midway Airports as part of the Chicago Department of Aviation’s
                                                            second annual “Month of Environment.” The informational kiosks aim to educate travellers about the City of Chicago’s green initiatives and provide
                                                            information about what they can do to recycle while at the airports. In addition, the Department of Aviation’s Environment Office will distribute
                                                            environmentally friendly-themed activity books to children, and bookmarks and postcards to travellers at both airports during the month of April.
                                                            The Month of Environment kiosks are part of an ongoing public education campaign that encourages everyone to work together to conserve and
                                                            protect the environment, and improve the quality of life for all Chicagoans. The 22 informational kiosks provide travellers with practical tips and
                                                            ideas that promote best practices, such as: turning off water faucets when not in use; saving coffee grounds for compost; using public
                                                            transportation to alleviate traffic and minimise air pollutants; purchasing recycled products; and recycling appropriately.

Hong Kong International Airport Environmental Best          The 2007 competition is is the 4th airport-wide competition with our business partners. The purpose is to promote environmental best practice
Airport                 Practice Competition                across the airport community. Past year’s themes include green office, energy management and green restaurant. This year’s theme is air quality
                                                            management. All participants benefit from learning about and incorporating environmental best practices into their daily operation in terms of
                                                            process improvement, waste reduction, as well as monetary and energy savings.



Intermodality and surface access – getting to and from the airport
Heathrow Airport, UK     “Changing Direction” – the         This airport staff travel plan covers the 70,000 employees at Heathrow Airport and covers travel to and from the airport as well as around the
                         airport travel plan                airport itself. Free and discounted travel on public transport, employee car pooling, incentives to walk or cycle to the airport and emissions checks
                                                            for vehicles are all part of the scheme that has been running for a number of years. www.baa.com/assets//B2CPortal/Static%20Files/travelplan.pdf

Zurich Airport,          Landside traffic (modal split)     Another requirement attached to the building permit for expansion stage 5 was that the modal split of landside traffic at Zurich Airport has to be
Switzerland                                                 established at the level of 42%. The survey carried out in autumn 2003 and evaluated in spring 2004 showed that the proportion of people using
                                                            public transport to travel to and from the airport (= modal split) has reached 43 percent, and has thus surpassed the level stipulated. It is estimated
                                                            that more than 59 percent of passengers travel to the airport by rail or bus, while the proportion of employees using public transport is slowly
                                                            increasing to around 28 percent.

Auckland International   “lift” – the airport travel plan   Auckland International Airport has developed a staff travel plan for the airport. The travel plan, called lift, initially encompasses staff from Auckland
Airport, New Zealand                                        International Airport Limited, Air New Zealand, Customs, the Ministry of Agriculture and Forestry (MAF) and the Aviation Security Service (AvSec)
                                                            – these represent nearly 60% of the 10,000 people who work on-airport. The lift programme will find ways to make travel to work more attractive,
                                                            fun and user-friendly. It is about taking steps to help airport employees to better understand travel choices and reduce their reliance on bringing
                                                            their own vehicles to the airport. Initiatives include car pooling, encouragement of sue of public transport and more flexible working. The goal has
                                                            been to encourage people to car pool once a week, or use public transport once a fortnight – setting a reasonable and achieveable goal that
                                                            makes a difference. www.liftataucklandairport.com




                                                                                       9
Airport                   Initiative                           Results / notes
Boston Logan, USA         Preferred parking for                Drivers of hybrid and alternative-fuel vehicles get preferred parking at Boston Logan. The airport has set aside about 100 parking spaces that are
                          environmentally friendly cars        close to the elevators. The environmental programs are part of Massport's Earth Day celebration. Taxi drivers with hybrid cars can also get in front
                                                               of the line twice in a 12-hour shift. Taxi drivers typically wait 30 to 60 minutes in the taxi line. Since last year, the city has been trying to encourage
                                                               operators to buy more hybrid or alternative-fuel cabs.

Madrid Barajas Airport,   Direct metro from city centre        Barajas International's new Terminal 4 now has its own Metro subway station, in addition to the one in Terminal 1. The city expects more than
Spain                                                          20,000 people daily (17 million a year) to use the extended Metro line. Travel from the airport to downtown takes about 20 minutes. Along with
                                                               London Heathrow, Madrid's is one of the few airports in the world with two Metro stations.

Auckland Airport, New     Priority car parking for efficient   Auckland Airport is encouraging the use of hybrid and fuel-efficient vehicles as part of its mission to “green the airport”. The airport will set aside
Zealand                   vehicles                             car parks specifically for hybrid and smaller-engine vehicles as part of its plan to reduce fuel consumption and engine emissions. Initially, 21
                                                               priority spaces will be allocated for use by low-emission vehicles in the public car park and 4 in the staff car park. Seven spaces will also be
                                                               allocated for fuel-efficient cars (up to 1.8-litre capacity). New additions to the airport company’s vehicle fleet are a Hyundai Getz and a VW Polo
                                                               BlueMotion – the world’s lowest carbon dioxide-emitting production car. The five-door Polo emits just 104g of CO2/km and can travel 1,184km on
                                                               a single tank of diesel.



Other environmental programmes
Phoenix International     Urban Heat Island Studies            PHX is working with Arizona State University and the National Center for Excellence on the impacts of pavements to urban climate. Heat is
Airport, USA                                                   retained in pavements and does not dissipate during the night, the build- up of which can cause changes in weather patterns around Cities.
                                                               Design, materials testing and demonstration projects are being performed by ASU, and PHX has assisted by allowing alternative-type pavement
                                                               installation and controlled testing of properties and temperature retention characteristics in areas of the airport. A report is forthcoming. Also, PHX
                                                               and ASU worked together to design crumb rubber (recycled from auto tires) / concrete benches that result in cooler bench surfaces and are easier
                                                               to move as needed for operational changes.

Hong Kong International Waste Reduction Framework              To further help waste minimisation and support the HKSAR Government’s waste reduction framework plan, the AA launched the “No Plastic Bag
Airport                                                        Shopping at HKIA” campaign in Mar 07 to retail shops at T1 and T2. Reusable shopping bags are available for sale inside both T1 and T2.


Athens International      Green Areas                          In the last 5 years, five Green Area projects have been constructed (total area of 6 hectars) by the Airport, at the surrounding community. These
Airport, Greece                                                projects, which include theatres, playgrounds, walking paths, planted areas, etc., contribute to the protection and improvement of environmental
                                                               conditions.

Hong Kong International Insulation programme                   The Hong Kong Airport Authority collaborated with Hong Chi Association and other corporations to organize the “2006/2007 Roof Greening
Airport                                                        Competition for Primary and Secondary Schools in Hong Kong”. The objective is to encourage students’ participation in roof greening to reduce
                                                               building temperature. Training workshop was held at the Hong Kong Baptist University in Dec 06. Basic planting materials were provided to the
                                                               schools and the award ceremony will be held at JW Marriott Hong Kong in May 07.

Chicago O’Hare Airport,   Modernisation programme              The City of Chicago’s O’Hare International Airport Modernisation Program will reconfigure O’Hare’s intersecting airfield layout, reducing delays and
USA                                                            increasing capacity at the airport. O’Hare developed a Sustainable Design Manual to achieve environmental improvements while providing long-
                                                               term sustainability, economic benefits and improved quality of life for Chicago’s citizens and businesses. The Sustainable Design Manual
                                                               addresses issues such as brownfield development, water efficiency, optimising energy performance, recycling, indoor environmental quality, air
                                                               quality, and construction practices.



                                                                                           10
Airport                    Initiative                                Results / notes
Detroit Metropolitan       Wetlands area development                 Received an award for a newly created wetlands area. Due to increased air traffic demand, expansion at the airport resulted in impacts to over
Wayne County Airport,                                                three hundred acres of wetlands. The airport purchased land twelve miles southwest of the airport to create new wetlands (referred to as
                                                                     Crosswinds Marsh) to compensate for the losses due to expansion. Crosswinds Marsh, the largest wetland site in Michigan and the Midwest,
USA                                                                  provides sanctuary to wildlife while also providing outdoor activities enjoyed by members of the Detroit community.

Southwest Florida          Nature reserve establishment              Mitigation Park was established to offset environmental impacts associated with the long-term development of the airport. The park is 7,000-acres
International Airport,                                               of preserve owned by the Lee County Port Authority that will be managed for the long-term by Florida Wildlife. Enhancement activities to be
                                                                     completed in the park will improve the quality of the natural environment and result in a net benefit to the region. Establishment of the park has led
USA                                                                  to streamlined permitting of airport development at Southwest Florida International Airport.

Atlanta International      Runway construction aggregate             The airport turned to a state-of-the-art, overland belt conveyor system that transported 93 percent of the 21.5 million cubic yards of fill necessary
                                                                     for the runway’s construction. The programme resulted in reduced truck trips on local roads, elimination of truck-generated air emissions, and
Airport, USA               delivery                                  diversion of a significant amount of construction material waste from landfills.

Stockholm-Arlanda          1,800 green flights completed             About 1,800 green flights have been implemented at Stockholm-Arlanda Airport, with aircraft “coasting” from cruising altitude down to the runway.
Airport                    at Stockholm-Arlanda                      This means less fuel consumption, emissions and noise. Green flights are based on collaboration between an aircraft’s flight management
                                                                     computer and the technical systems used by air traffic controllers. Through a data link, all affected parties can have real-time access to the same
                                                                     information about a given flight. Arrival time can be calculated more exactly, which simplifies ground handling at the airport. In a Boeing 737, the
                                                                     savings potential from green approaches averages 150 kilos of aircraft fuel or about 475 kilos of carbon dioxide emissions per landing at Arlanda.
                                                                     For a long-haul aircraft, which is larger and heavier, the savings potential is about 200- 300 kilos of aircraft fuel or some 600 – 950 kilos of carbon
                                                                     dioxide per landing.

Munich and Frankfurt       Economic incentives                       Munich and Frankfurt airports have announced plans to introduce an emission-linked component in take-off and landing fees for a three-year test
Airports, Germany                                                    phase. The pilot project was developed by the German Airport Transport Initiative in consultation with the Ministry of Transport, Building and Urban
                                                                     Affairs, and will introduce a charge of 3 euros per kilogram of nitrous oxide (NOx) emissions for all airlines landing in Frankfurt and Munich
                                                                     effective January 1, 2008.

Johannesburg               Soweto tree planting                      Airports Company South Africa (ACSA) has committed to the Soweto Greening Project in a bid to preserve and boost the appeal of the
International Airport,                                               environment in the sprawling township. In a planting ceremony led by ACSA staff members, a total of 400 trees were committed to be planted
                                                                     along the June 16 tourist route which spans about four kilometres in total. The project is a partnership between ACSA and Johannesburg City
South Africa                                                         Parks and aims to keep the environment tourist-friendly. The planting of the trees in Soweto is part of ACSA’s corporate social investment (CSI)
                                                                     programme.




                         If you know of environmental initiative that are occurring at airports and are not included on this list, please email details to Haldane Dodd or Xavier Oh at ACI World Headquarters for inclusion.




                                                                                                11
A Global Alliance

				
DOCUMENT INFO
Shared By:
Categories:
Tags:
Stats:
views:19
posted:7/14/2012
language:
pages:194