Information System for Emergency Management
Version 0.9, March 2011, www.pdc.dk/argos/
Table of contents
1 ARGOS ..................................................................................................................... 3
2 Introduction ............................................................................................................. 3
3 Prognoses of Atmospheric Dispersion ....................................................................... 5
4 Nuclear and Radiological Scenarios ........................................................................ 10
5 Chemical Scenarios ................................................................................................ 19
6 Biological Scenarios ............................................................................................... 23
7 GIS Subsystem........................................................................................................ 23
8 Handling multiple incidents .................................................................................... 25
9 Export of results from ARGOS ................................................................................. 25
10 Communication with other DSS .............................................................................. 26
11 Support for the NATO ATP45 Format ...................................................................... 26
12 ARGOS Web (Unfinished) ....................................................................................... 26
13 ARGOS Integration possibilities (Unfinished) ........................................................... 28
14 Technology (Unfinished) ......................................................................................... 28
15 The ARGOS Consortium .......................................................................................... 29
16 User Testimonials (Unfinished) ............................................................................... 30
17 Contacts ................................................................................................................ 32
ARGOS Whitepaper Page 2 of 33
ARGOS is an Information System (IS) for possible decisions in case of a CBRN inci-
enhancing Crisis Management for inci- dent. The objectives of ARGOS are:
dents with CBRN releases. The target is
accidents as well as terrorist initiated
Prognosis of how the situation will
events related to CBRN industries, trans-
ports of hazardous materials etc. ARGOS
Calculate consequences of an inci-
is a prognostic tool as well as a database
system for collection and presentation of
data relevant for emergencies in an easily Decision support for countermeas-
understandable form. ARGOS facilitates ures.
decision support, improving of situation Information to the public.
awareness and information sharing Follow-up and evaluation.
among the Emergency response organisa- Dimensioning of emergency prepar-
tions. As a simulation instrument, ARGOS edness.
is also valuable for training of the re- Training and exercises
The mission of ARGOS is to support the
emergency organization to make the best
The original intentions with ARGOS were
to develop an IS for nuclear emergencies
to support the Nuclear Division of the
Danish Emergency Management Agency
(DEMA) in dealing with emergencies re-
lated to accidents in nuclear power plants
(NPP) and other nuclear installations. The
very first version of ARGOS was a simple
UNIX-based system developed by Risø
National Laboratory for Sustainable Ener-
gy, Technical University of Denmark (Risø
DTU). The Danish nuclear authorities used
this version during the Chernobyl accident
in 1986. In 1992, DEMA decided to change Figure 1. Chernobyl accident in 1986
platform for ARGOS to Windows NT and
the cooperation with Prolog Development
A fundamental feature in ARGOS is the
Center (PDC) took form.
ability to run, interpret and visualize re-
Even today the most elaborated function- sults from atmospheric dispersion mod-
alities of ARGOS relates to the Nuclear els. This means that given a basic set of
part, which is the driving force for the meteorological data and data about a
other elements. CBRN accident, ARGOS can prognostic a
time dependent fallout picture of areas
likely to be contaminated by fallout, in-
ARGOS Whitepaper Page 3 of 33
cluding air concentrations of relevant el- the atmospheric dispersion model
ements and contamination. “Risoe Meso-scale Puff Model”
Results are presented on digital maps, (RIMPUFF) for calculating local-scale
which may be overlaid with orthophotos dispersion forecasts,
and 3D building constructions. For some various long-range atmospheric dis-
scenarios, it is possible to incorporate the persion models running remotely on
effect of countermeasures in the calcula- meteorological computing centres,
tions. The results can easily be exported the “Food and Dose Module” (FDM)
to other presentation systems or pub- model for estimating doses in rural
lished. areas,the “Agricultural Counter-
measure Program” (AGRICP) which is
Another fundamental feature in ARGOS is the successor for FDM, that includes
the handling of monitoring data. ARGOS calculating the effects of applying
incorporates the collection, management countermeasures,
and presentation of monitoring data from the “European Model for Inhabited
mobile units (vehicle and aircraft) and Areas” (ERMIN) developed under the
online measuring stations. European Commissions Sixth Frame-
The Chemical part of ARGOS includes a work programme, for calculating
comprehensive database with chemical contamination on various surfaces in
substances. New models for releases from an urban environment, doses to the
containers have been included. These public and the effect of counter-
cover releases of aerosols and liquids as measures,
well as evaporation of spills on the the STRATEGY food-chain counter-
ground. A special model for dispersion of measure model developed under the
heavy gasses is also incorporated. European Commissions Fifth Frame-
a Risø DTU developed model for cal-
culating chemical release source
terms from containers based on a
specification of the release geometry
the HeavyGas model, a model devel-
oped at Risø DTU for calculation of
the atmospheric dispersion of heavy
the Urban Dispersion Model (URD)
Figure 2. ARGOS includes models for aerosol developed by Risø DTU.
and liquid releases from containers
The ARGOS system is making an intensive
use of GIS to display data on geographical
The Radiological part of ARGOS covers
maps. Colours can easily express the con-
explosions such as Radiological Dispersal
centration, contamination, time-of-arrival,
Devices (RDD or so-called dirty bombs)
trajectories, doses or inhalation etc., and
and primitive nuclear weapons, so-called
isocurves can display where important
improvised nuclear devices (IND).
thresholds are exceeded. The GIS system
ARGOS is an open platform with models can display maps for the whole world and
attached as loose-coupled modules to the may include NPP’s, measuring stations
system. This construction makes it easy to etc. Weather conditions like precipitation
adopt new models for enhancement of and wind fields can be displayed on maps
the system, and helps to keep ARGOS up- as well.
to-date and flexible for using models that
Development on ARGOS has been contin-
has a preference in individual countries.
uously ongoing since 1992 in a close co-
ARGOS integrates currently with a num-
ber of external models:
ARGOS Whitepaper Page 4 of 33
operation between DEMA, Risø DTU and Today ARGOS has become a central part
PDC and the other ARGOS users. of the Emergency management in a num-
ber of countries.
3 Prognoses of Atmospheric Dispersion
Atmospheric dispersion in ARGOS is divid- ment(URD), dispersion of heavy gases and
ed in several parts, a short and mesoscale coupling to long-range models: DERMA
dispersion model LSMC/RIMPUFF, a mod- (Danish), MLDP (Canada), SNAP (Norway)
el for dispersions in urban environ- and MATCH (Sweden).
3.1 The Short Range Model RIMPUFF
RIMPUFF is the primary short/medium etc.) based on data provided by Weather
range model for ARGOS. The Wind Energy prediction models or by meteorological
department of the Risø National Labora- masts. In the newest versions, 3D wind
tory for Sustainable Energy, Technical fields are calculated, and wet deposition
University of Denmark developed this may be estimated from weather radar
model based on Start and Wendells con- information. Different parameterisation
cept from 1974. The range of RIMPUFF is schemes for dispersion parameters may
up to many hundred km from the source, be used.
and validation is successful through a
number of experiments. RIMPUFF was
originally developed to be valid for short
distances up to 30 km. Risø DTU has now
developed a scheme for parameterisation
of dispersion parameters out to about 300
km from the source.
The big advantage of RIMPUFF compared Figure 4. RIMPUFF uses surface height to cal-
to many other similar models is that it culate the flow.
runs fast on a standard Windows comput-
er - instead of having to run in a super- Based on the meteorological data
computer centre. RIMPUFF calculates gamma doses (inhala-
tion dose, whole body dose etc.), air con-
centrations and ground deposition.
Standard deposition models are used.
These models are based on particle size.
Presently only one particle size are used
but more will be added. In addition,
RIMPUFF creates aggregated input data
for FDM and AGRICP.
RIMPUFF requires as input the release
points and the start time of the releases.
Figure 3. Local scale dispersion: Inhalation The source term must be specified con-
dose cerning both material and release rate,
and the current meteorological situation
RIMPUFF comprises a meteorological pre- for the area of interest. There are several
processor, which calculates time and additional parameters; some that de-
height dependent fields of meteorological scribe the requested prognosis in more
parameters (deposition, stability, wind detail and various parameters for how the
ARGOS Whitepaper Page 5 of 33
model should run, but most of these ARGOS suggests as default values.
Figure 5 For modelling a heat lift of a release ARGOS uses the so-called chimney effect. Above is
shown three simulations of the same release situation but with different chimney effect a) with no
chimney effect, b) with 1 MW effect and c) 5 MW effect.
3.1.1 Meteorological Data
Meteorological data are important to can run on a laptop in a car without con-
ARGOS because they enable the short- nection to mains or network.
range model to predict how and where a
plume of hazardous gasses and aerosols
will spread. The long-range prognoses
need meteorological data for a much
larger area and that is the main reason for
executing these models in meteorological
offices (Met-Office) that have all the nec-
essary data available.
ARGOS and RIMPUFF can use meteorolog-
ical data from three different sources:
The primary operating mode is NWP
(Numerical Weather Prediction) in which
the user at the emergency management
Figure 6. Geographical coverages of the oper-
centre does not have to worry about the ational versions of the DMI-HIRLAM numerical
availability of meteorological data. In this weather prediction model.
mode, a background program automati-
cally downloads (a subset of) numerical
weather-forecast datasets from the Met-
Office. Such forecasts typically cover up to ARGOS currently understands meteoro-
few days ahead, and the data download logical datasets in three different formats:
from the Met-Office occurs as soon as the HIRLAM, BUFR and GRIB. The BUFR and
data become available. This means that GRIB formats are endorsed by the World
the latest meteorological data are always Meteorological Organization (WMO),
present in ARGOS, and the prognosis can , for meteorologi-
start even in case of a temporarily inter- cal observational data and gridded NWP
rupted network connection to the Met- model output, respectively.
NWP models covering different regions of
If the meteorological data is stored on the the Earth run in operational schedules at
computer, no network connection is re- National Weather Services. Typically, each
quired at all for starting a prognosis. Even six hours updated model runs are carried
based on NWP model data the prognosis out. In the vertical, the model ranges from
ARGOS Whitepaper Page 6 of 33
the surface up to a height of about 30 km
above ground. An NWP model forecast is
initialised by assimilating the vast amount
of available routine meteorological obser-
vations thereby creating a so-called ana-
lysed model state. Thus, the analysed me-
teorological state is in accordance with
both the NWP model and the meteorolog-
As an example the operational DMI (Dan-
ish Meteorological Institute) version of
the High-Resolution Limited-Area Model Figure 7. ARGOS showing wind fields and rain.
(HIRLAM) runs on three domains, cf. Fig.
5. DMI-HIRLAM utilises nesting technique
implying a horizontal resolution ranging The NWP Import Service automatically
from 15 km over the Arctic (model version downloads and inserts forecasted numer-
T) and Europe down to 5 km over north- ical weather prediction data into the
ern Europe (S) and Greenland (Q). Cur- ARGOS weather database. The Service can
rently, an experimental version covering be configured to automatically delete old
Denmark at 1.4 km resolution is studied. data both from the database and from the
disk, at certain intervals. Interesting
In addition, DMI has access to the global weather situations can be flagged for
model developed and operated by the permanent storage.
European Centre for Medium-range
Weather Forecasts (ECMWF). For a sub- 22.214.171.124 Met-Towers
area of the S version covering Denmark
and surroundings, data are extracted for ARGOS and RIMPUFF can use data from
ARGOS following update of this model meteorological towers or stations. Typi-
four times a day. The extracted data are cally, this includes wind-speed, wind-
readily transferred to DEMA through a direction, and temperatures in one or
dedicated telecommunications line. The more heights.
data extraction, as well as the transfer, is
under surveillance by DMI operators.
HIRLAM/GRIB NWP files contains fields of
data in a number of vertical levels above
the ground and specific “HIRLAM areas” –
with dedicated identification numbers –
cover different geographical regions in
Figure 8. Display of Met-Towers.
An ARGOS import service inserts special
weather measurements from met-towers
into the ARGOS database. These meas-
urements are received by a dedicated
email account – a Windows MAPI Mail
ARGOS Whitepaper Page 7 of 33
126.96.36.199 NWP and Towers of a unique meteorological situation, that
covers a small area; typically Manual
NWP model data are primarily forecast
Weather is relevant only for C and B (and
data and hence cover the future, which is
R) prognoses - N dispersions usually have
what we are generally interested in when
too long range for such local meteorologi-
running a dispersion prognosis. A meteor-
cal specifications to be meaningful.
ological tower contains only data from the
past, and this might appear uninteresting.
188.8.131.52 RADAR Import
However, RIMPUFF can run on a combina-
tion of NWP and met-tower data. When a The RADAR Import Service inserts rainfall
prognosis is first-run for an accident, it is radar images into the ARGOS database.
typical only to use NWP because every- Radar images are used as a better approx-
thing of interest happens in the future. imation to the actual condition than the
After some hours, an adjusted ARGOS precipitation forecast data from the NWP
prognosis could be run with using met- data.
tower data from the start of the accident Three radar data formats are handled by
until current time; thereafter NWP data is ARGOS and the Radar Import Service can
used until the requested prognosis end- insert all three formats in the database.
time. The use of tower data is advanta- These formats include: 1) the VRIS format
geous only at the very local scale as given (Denmark), 2) a “HIRLAM format” precipi-
by the geographical domain represented tation field (Canada), and 3) the OPERA
by the meteorological tower. In any other BUFR format (Ireland).
case, use of analysed high-resolution NWP
model data is recommended. ARGOS has a special functionality for deal-
ing with wind-direction, wind-speed and
184.108.40.206 Manual Weather rain-radar images as well as a few other
parameters of special interest to the
Finally, it is possible to enter the local me- prognosis. In addition, ARGOS can read
teorological situation manually using a and display almost any other meteorolog-
met-data editor. Manually entered ical data submitted via any of the three
weather data are normally just wind di- above formats. This is for display-only
rection and wind speed in a single point, purposes and cannot be interpreted or
or a more complex situation with several used by the models. However, RIMPUFF
“observations”. Generally, manual weath- can utilize the rainfall data for calculation
er observations are less sophisticated of wet deposition, which will enhance the
than the NWP observations with higher detection of hot spots and the estimation
resolution both in time and grid size. of wash-out from the plume.
Therefore, Manual Weather is mostly rel-
evant simultaneously or for specification
3.2 Long Range Models
The long-range atmospheric dispersion operational numerical weather prediction
models are loosely coupled to ARGOS in (NWP) models.
the way that they can be started remotely
Typically, an operational FTP-server is
at the Met-Office by request directly from
used as the only interface between
ARGOS. The models require a description
ARGOS and the Met-Office.
of the release scenario similar to that
used by RIMPUFF. This input to a long- The Met-Office performs several calcula-
range model is automatically uploaded tions on different versions of the NWP
from ARGOS to the Met-Office where the model in operational use, with various
meteorological data are taken from the geographical coverage and resolution.
ARGOS Whitepaper Page 8 of 33
Thus, an ensemble of atmospheric disper- the user for downloads of the results. For
sion model results is produced for ARGOS Nuclear scenarios, the results of the long-
thereby supporting the decision making range dispersion calculation can be used
process. as input to countermeasure models.
When the calculations are finalised, the
monitor function in ARGOS will prompt
Figure 9. Long Range dispersion results
The long-range models currently support- tiscale Atmospheric Transport and Chem-
ed are the “Danish Emergency Response istry Model” (MATCH).
Model of the Atmosphere” (DERMA), the
The geographical model domain as well as
Canadian “Modele Lagrangien de Disper-
the spatial resolution of a long-range
sion de Particules d'Ordre 0” (MLDP0), the
model is given by the corresponding NWP
Norwegian “Severe Nuclear Accident Pro-
model, cf. Fig. 5.
gram” (SNAP) and the Swedish “Mul-
3.3 URban Dispersion - the URD model
In order to support CBR scenarios down to
the street level in cities between buildings
ARGOS incorporates the URD model.
URD is developed in a cooperation be-
tween Risø National Laboratory for Sus-
tainable Energy, Technical University of
Denmark and Danish Meteorological Insti-
tute (DMI) and FOI (Swedish Defence Re-
At the local scale, the results of a release
between buildings will be very different
Figure 10. ARGOS using the URD module for a
that if no building where present.
simulation in Copenhagen.
The buildings will reduce the range of the
release while the local scale turbulence
will in some spots create higher concen-
trations and spread the release in wider
ARGOS Whitepaper Page 9 of 33
An important part of supporting the Ur-
ban Dispersion is the 3D GIS module in
ARGOS. The 3D view can show how the
Puffs move in the Urban environment be-
tween the houses. The major advantage
in this is to understand the prognosis and
to support situation awareness.
ARGOS can bring in all buildings for a
country, and then feed in the relevant
building to the area of interest for the
Figure 11. ARGOS using the URD module for a URD model and the 3D views.
simulation in Copenhagen.
ARGOS can display trajectory output from jectories gives important information to
both long- and short-range models. Tra- understand the dispersion.
Figure 12. Trajectories example.
4 Nuclear and Radiological Scenarios
ARGOS has many advanced functionalities stationary automatic measuring stations,
for nuclear scenarios, including import, as well as special models for food-dose
export and display of measurement data calculations and countermeasure analysis
from both airborne systems, mobile and modules and more.
4.1 Accidents in Nuclear Power Plants
An accident in a Nuclear Power Plant the environment over a certain period of
(NPP) was the original target for ARGOS time. As part of the pre-defined data in
prognoses. The famous Chernobyl acci- ARGOS a number of model source terms
dent in April 1986 initiated the develop- has been defined, specifying amounts in
ment, in Denmark, of the ARGOS NT sys- percentage relative to the reactor inven-
tem (now “ARGOS”) – that built on princi- tory at the time of reactor shutdown, tak-
ples from an earlier system. A very im- ing radioactive decay and build-up into
portant step during a prognosis is to esti- account. A model source term can simu-
mate the source term - the amount and late whether a release originates from the
form of a radioactive source released to stack or from the cooling system and how
ARGOS Whitepaper Page 10 of 33
the release amount varies with time. ARGOS can also work with a release sce-
Combining a model source term with a nario that includes several source points –
certain reactor will then produce estimat- in this way can a stack release, for in-
ed amounts of radioactive release ex- stance, be combined with a radioactive
pressed in Becquerels in a number of time spill from a waste dump at the NPP site.
intervals. Another way of specifying a
source term is to manually specify the
release as an absolute activity in Becque-
rels based on stack monitor measure-
Figure 14. Ships and submarines powered by
Nuclear reactors represent a potential threat.
Figure 13. ARGOS showing Nuclear Power-
plants on the map.
4.2 Radiological Scenarios
The CBRN terminology is a rather new and small nuclear bombs as radiological
terminology introduced in connection scenarios.
with the growing awareness of potential
incidents or malicious use of Chemical,
4.2.1 Radiological Dispersal De-
Biological, radio-active (Radiological and
Nuclear) materials. Earlier Nuclear and
Radiological events were categorized in Radiological Dispersal Devices (RDD) or
one group as either Atomic (for instance so-called “dirty bombs” represent rather
ABC weapons) or Nuclear (NBC). primitive weapons where radioactive ma-
terial is dispersed into the environment by
The distinction between N and R is typi-
means of conventional explosive materi-
cally that N relates to fissile material and
the nu-clear fission process while R origi-
nates from radioactive sources without a
direct link to nuclear fission. According to
this definition, nuclear explosives should
be categorized as nuclear scenarios in line
with events related to nuclear installa-
tions such as nuclear power plants, while
dirty bombs should be included as radio-
logical scenarios. However, in ARGOS it is
more convenient to treat nuclear bombs
and radiological bombs in a similar way as
sources for distribution of radioactive ma-
terials in an urban environment. Conse- Figur 15. Setup in ARGOS for simulation of an
quently, ARGOS handles both radiological Radiological Dispersion Device
ARGOS Whitepaper Page 11 of 33
envisaged that the release takes place
4.2.2 Improvised Nuclear Devices outside the domain for which ARGOS has
(IND) access to meteorological data.
The handling of nuclear weapons in As it was the case for the RDD devices,
ARGOS is limited to so-called Improvised ARGOS may handle IND devices as surface
Nuclear Devices (IND). These are primitive bursts at ground level and airbursts with
nuclear weapons with limited destruction the devices elevated into the atmosphere.
capability. Professional weapons that
could result in massive destruction of the 4.2.3 Calculation of Dose from ‘R’
infrastructure of the urban environment
are not considered. The purpose is there-
fore to handle terrorist initiated events Radiological scenarios are likely to result
and not a nuclear war. However, even in fallout of radioactive material as well as
smaller nuclear weapons may have long- contamination on the ground, vegetation,
range consequences, especially under walls of buildings, roofs etc. Estimation of
stable meteorological conditions. In order the air concentrations as well as the dis-
to describe such scenarios, long-range tribution of the radioactive contamination
models interfaced with ARGOS should be is calculated by RIMPUFF. Doses to the
applied in addition to RIMPUFF, thereby public are calculated by ERMIN based on
providing the best possible advice to the the contamination distribution from
decision makers. In addition, it might be RIMPUFF.
4.3 Monitoring Data
ARGOS handles monitoring data stored in version 2.0, which is in use since the be-
SQL databases. This includes data from ginning of 2002.
domestic monitoring systems, but it can
ARGOS has already an implementation of
be important also to include nuclear mon-
the next proposal for EURDEP version 3.0,
itoring data from foreign countries into
which corresponds to the IRIX format.
the systems database. Data handling is
fast and without unnecessary request of Countries participating in the EURDEP
work force. network send gamma dose rate meas-
urements to a common FTP server on a
regular basis (once per day or hourly/bi-
4.3.1 EURDEP Format
hourly when in an elevated state.)
ARGOS provides functionality for interac-
tively import and export of data in the
EURDEP format; which includes most for-
eign data. Entering of such data into the
database occurs continuously by the au-
tomatic EURDEP import service. In addi-
tion, export of gamma station monitoring
data and data from local met towers is
done automatically by the DataExport
EURDEP (EUropean Radiological Data Ex-
change Platform) is both a standard for-
mat for radiological data and a network
for the exchange of automatic monitoring Figure 16. ARGOS showing imported nuclear
data. The current release of the format is measurements from European stations.
4.3.2 Permanent Monitoring Sys- for collecting data from permanent
tem (PMS) monitoring stations.
The PMS Station software designed
The ARGOS software for supporting Per-
to run at Permanent Monitoring sta-
manent Monitoring stations consists of 3 tions to control measuring instru-
ments and acquire the data to be
The PMS Server software; which in sent to the server
itself can be split up into the PMS da- The PMS Station hardware, a specific
tabase and client-side applications, concept for a permanent monitoring
and the PMS server-side applications station with a Geiger-Müller tube and
a NaI spectrometer.
Figure 17: The PMS stations.
220.127.116.11 PMS Database
The core of the PMS Server system is the
PMS database, which like the ARGOS da-
tabase runs on a Microsoft SQL Server.
Compared to the ARGOS database, the
PMS database is simple and basically con-
tains a few tables for configuration, a few
tables for logging and status and then the
tables to keep all the data. The data ta-
bles are easy to access via standard SQL
software, statistical software or even Ex-
cel if you need to perform ad-hoc analysis
Figure 18. Inspecting the data on a monitoring
on the data.
18.104.22.168 Data Collection
The data collection services consist of
several tools that can retrieve data from
ARGOS Whitepaper Page 13 of 33
the stations by a number of different addition – when an anomaly is detected –
communication mechanisms - and process this application can trigger various alarm-
and insert the data into the PMS database ing functions.
Another application is used for viewing
There is also a service, which can be set the results as time-series (as opposed to
up to continuously export data in the ARGOS which show only the last data –
EURDEP and other formats. The tools are but on a map). The application is ideal for
flexible and can be used as a basis to re- studying the development of radiation on
trieve data from different kind of meas- a station, and the application can be
urement stations. started from ARGOS. It can also export
data to NucSpec (see 4.3.6) or to EURDEP
files. The application is also available as a
4.3.3 Other PMS Software
The database and the data collection ser-
vices are enough for integration between
4.3.4 Airborne Gamma Spectrum
ARGOS and the PMS system. However,
there are more PMS applications and PMS Monitoring
can work as a stand alone system alarm- Data from an Airborne Gamma Survey
ing system independent of the ARGOS (AGS) Monitoring system is strongly sup-
system. ported by ARGOS. The time span from
The PMS Alarm application constantly extracting AGS-data from an aircraft until
scans the incoming data to look for the data are available for food dose mod-
anomalies. This application presents a list elling in ARGOS may be as short as 1 hour.
of all monitoring stations with each sta- Advanced software for this data handling
tion highlighted in green (all OK), yellow and analysis is part of the ARGOS consor-
(error) or red (alarm) colour. The applica- tium agreement software suite.
tion is also available as a web-page. In
Figure 19. AGS Monitoring: 1) Left, monitoring helicopter and diagram showing monitoring principle.
Normal measuring height is about 100 m. 2) Right, results from AGS monitoring survey of Risø DTU,
which is the only site in Denmark that had a nuclear installation.
ported in ARGOS as well. The data are
4.3.5 Carborne Gamma Spectrum treated in the same way as AGS data –
Monitoring just without the height information.
Data from the Carborne Gamma Survey
(CGS) monitoring systems are well sup-
ARGOS Whitepaper Page 14 of 33
Figure 20. Carborne Gamma Spectrum (CGS) Monitoring Systems pictured under exercise in Poland.
The monitoring principle is the same for AGS and CGS and the equipment is similar.
Export results to ARGOS in a grid-file
4.3.6 NucSpec Export individual measurements to
NucSpec is a separate application used for an EURDEP file
analyzing and visualizing spectral data Plot the data in an x/y grid
from Aerial Gamma Survey or Car-borne Perform Noise-Adjusted Singular Val-
Gamma Survey. With this software the ue Decomposition (NASVD) analysis
expert user can quickly spot and remove to split the measured spectra into
erroneous or irrelevant measurements. components. NASVD is an external li-
brary from Radiation Solutions – that
Using NucSpec it is easy to work with can be obtained by a separate
spectral data from an AGS/CGS measure- agreement.)
ment series and export the data in a way
suitable for further analysis or presenta-
tion on a digital map from within ARGOS.
4.3.7 Team/Route Management
As part of radiological/nuclear measure-
ment handling, ARGOS uses the concept
of “Measurement Teams” where prede-
fined networks of measurement routes
may be stored in the database. The emer-
gency management may decide which
routes the mobile teams for measuring
fall-out should follow in an emergency.
Entering the measured gamma dose rate
readings into the system creates a situa-
Figure 21. Screenshot of the NucSpec applica-
tion detecting a source. tion overview, and is an important infor-
mation for assessing the situation. Doses
for personnel participating in measure-
After validating and cleaning the meas- ment teams can be calculated and moni-
urements, the user can tored as well.
Figure 22. ARGOS has support for managing measurement routes.
4.4 FDM – Food Dose Calculation Module
For Nuclear scenarios, ARGOS includes a ment. Then, the transfer of radioactive
module for simulating the transfer of ra- material in food chains resulting in an in-
dioactive material in food chains, and for take of radioactivity by the population is
the assessment of doses via all relevant calculated.
pathways (internal exposure via inhala-
The locations for which the calculations
tion and ingestion, external exposure
are performed in FDM can in principle be
from the plume and from deposited radi-
arbitrary points in space, i.e. they can, but
oactive material) to the population. FDM
they need not to be points on a regular
estimates doses to the public - individual
grid. In ARGOS, the locations are consid-
as well as collective doses.
ered representative for political units, i.e.
The FDM module for ARGOS has been communities. This means, the output of
adapted from the RODOS FDMT module, the atmospheric dispersion modules
developed by the German GSF – National (which are working on a regular grid) is
Research Center for Environment and averaged in an appropriate interface
Health, Institute of Radiation Protection. module over the areas of the communi-
The adaptation was made by ConRad- ties, and these averaged data is input to
Consulting in Radioecology. FDM. Consequently, the FDM results are
considered representative for these
The Food and Dose Module FDM within
ARGOS aims at giving a comprehensive
picture of the present and future radio- Food chain and dose calculations with
logical situation in the presence of radio- FDM can be based not only on results of
active material in the atmosphere. It atmospheric dispersion calculations but
starts from the results of the Atmospheric also on measured data of nuclide specific
Dispersion Modules, i.e. the spatial distri- total deposition. Such results can be
bution of the concentration of activity in available e.g. from stationary and mobile
the near-ground air, and the activity de- (airborne) in situ gamma spectrometry.
posited by precipitation, which is predict-
The input data to FDM is mainly nuclide-
ed for a large area surrounding the point
specific, time-integrated concentration of
activity in air, wet deposited activity and
FDM first estimates the deposition of ra- the amount of rainfall. This data is not
dioactive particles and gases from the at- directly available from measurements of
mosphere onto soil, crops and other dep- deposition. Therefore, a pre-processor
osition surfaces in the human environ- (FDM-PP) is available which estimates the
required FDM input data from the deposi-
tion measurements. Since such estima-
tions are not straightforward in many cas-
es, certain assumptions are necessary
which, of course, increase the uncertainty
of the resulting predictions of food con-
tamination and doses. Nevertheless, it is
feasible at least to estimate an upper limit
of these radiological quantities.
FDM can provide a big variety of end-
points (e.g. feed and food contamination,
Figure 23. ARGOS Food Dose Modelling follow-
doses for different exposure pathways) in
ing a simulated nuclear accident
different graphical form (e.g. maps, histo-
grams, pie charts or time dependency di-
4.5 Countermeasure Modules
The estimation of the impact of counter- possible to assess different countermeas-
measures is an important addition to ra- ure packages regarding dose saved, cost,
diological dose assessment models. Due worker dose and amount of waste pro-
to differences in the domains, counter- duced.
measure packages for rural areas and for
inhabited areas are treated by different
countermeasure models. Currently
ARGOS has three countermeasure mod-
ERMIN dose calculation module for
use in inhabited areas, developed
under the EURANOS research project
under the European Commission's
sixth Framework Programme,
Figure 24. Calculating effects of countermeas-
EURATOM Research and Training ure.
Programme on Nuclear Energy.
The results of the estimations are con-
AGRICP, Agricultural Countermeasure verted into scores and then exported to a
Program, which is an extension of text file suitable for use by a standard
FDM to cover agricultural counter- Multi Attribute Decision Support Tool (like
measures (instead of just calculating V.I.S.A. from Simul8 Corporation). This
doses), also developed as part of interface to a Decision Analysis program
EURANOS. was made as part of the EVATECH EC pro-
STRATEGY food-chain countermeas- ject in the Fifth Framework Programme.
ure model developed under the Eu-
ropean Commissions Fifth Frame- 4.5.1 AGRICP
Rural areas consist primarily of scarcely
It is possible in ARGOS to do a screening populated open land that is used for pro-
of an area based on a dose estimation for ducing foodstuffs and are therefore han-
all pathways on airborne measurements dled by an agricultural countermeasure
of deposition or atmospheric dispersion program (AGRICP) that estimates the
calculations. Based on the calculations it is
ARGOS Whitepaper Page 17 of 33
transfer of radiation in the food chain. that indicates a relationship to a number
The AGRICP model is used on an adminis- of pre-calculated data-sets for relative
trative unit (municipality) scale. initial deposition of radioactivity between
environmental surfaces, for a range of
Figure 25. The AGRICP way of selecting Coun- Figure 26. Using of ERMIN in a local area spec-
termeasure Packages (or strategies). ifying environment breakdown in grid cells.
The ARGOS user interface allows a num-
4.5.2 ERMIN ber of the estimated doses to be dis-
played on the map and a plots of distribu-
Inhabited areas (cities) contain most of tion of surface dose on to groups of sur-
the population in more or less urbanized faces can be shown for each of the grid
environments, where more people are squares.
exposed to deposited contaminants. Such
areas should therefore be calculated in
much higher detail. The European Model
for Inhabited Areas (ERMIN) brings to-
gether a number of models and datasets
and embeds an actual transfer model that
also takes into account the weathering of
material on building surfaces and move-
ment of radionuclides around the inhabit-
ed environment. The ERMIN model is
used on a gridded 100-meter scale.
Figure 27. Distribution of surface dose.
It is necessary to specify for each grid
square an “environment breakdown”,
ARGOS Whitepaper Page 18 of 33
5 Chemical Scenarios
ARGOS is capable of forecasting the con- The source term for a release could be
sequence of various chemical releases. calculated by an integrated SourceModel.
The system comes with a chemical data- Alternatively if the source term is known
base featuring common dangerous com- or have been calculated by an external
pounds as well as the possibility to add model it could be typed directly into a
new compounds. form.
Figure 28. ARGOS can be used in case of fires
with dangerous smokes.
Figure 29 Form for typing known source terms
5.1 The Source Calculation Model
For calculating chemical releases, ARGOS Source Model predicts the following pro-
comes with an advanced integrated cesses:
source model developed by Risø DTU. The
Heat and mass balance of a leaking
Source Calculation Model predicts gas
releases from industrial storages or
Gas, liquid, and two-phase outflow:
transport containers, and when such re-
Initial state of an instantaneous re-
leases have negative buoyancy.
lease from a pressurized container;
The Source Calculation Model also calcu- Initial state of a continuous emission
lates the initial dispersion until a stage from a pressurized container;
where other dispersion models of the Heat and mass balance of an evapo-
ARGOS system are able to take over. The rating pool;
application in an emergency preparedness Initial state of an emission from an
system calls for relatively fast computa- evaporating pool;
tions and limited information must not Dispersion of an instantaneously re-
prevent calculation. leased heavy gas cloud;
The source model includes gaseous, liq- Dispersion of a heavy gas jet;
uid, or two-phase outflow from pressur- Dispersion of a heavy gas plume with
ized containers; evaporation from a boil- ground contact
ing or volatile pool; and heavy-gas disper- The combination of these processes is
sion form continuous and instantaneous flexible.
sources. Predictions are feasible both with
detailed and limited information on the
ARGOS Whitepaper Page 19 of 33
Figure 30. Various physical systems can be modelled in ARGOS
It is possible to describe the content and The second step is a heavy gas dispersion
exit geometry of the container, where calculation where the Source Model cal-
after the model decides how the material culates the dispersion of the heavy gas for
escapes including possible deposition in a the first couple of hundred meters.
pool from where it subsequently evapo-
That is until the gas starts acting in a way
rates. However, if detailed information is
that can be simulated by a dispersion
unavailable, the user may specify a simpli-
model like RIMPUFF.
fied scenario with his best judgement of
release rate, release type and duration. The user can decide whether RIMPUFF
should do the entire dispersion calcula-
tion based on the source term from the
Source Model or if RIMPUFF should take
over the puffs from the Source Model af-
ter the heavy gas calculation.
Figure 31. Description of detailed physical pa-
rameters for a release.
5.1.1 Emptying a Container
Figure 32: Many experiments have been made
The Source Model can model various sce- for validating the models.
narios of emptying a container of pres-
sure-liquefied material, from giving de-
In case of releases of large amounts of
tailed parameter to an estimate of what is
chemicals, or releases of sufficiently haz-
ardous material, the airborne spread may
The Source Model acts as a two-step take place over large distances at concen-
model where the first step is to calculate tration levels posing a risk. This may occur
the source term based on physical pa- especially under stable meteorological
rameters (as described above). conditions.
ARGOS Whitepaper Page 20 of 33
Figure 33. The scenario handling is powerful and flexible
ARGOS features several different ways of map position, or type in the address of
specifying the position of the release on the release, or select an already created
the map. The user can type in the coordi- plant, and more.
nates of the position, or click on the GIS
5.2 Results of Simulation
The results of the dispersion calculation
For all plots, it is possible to select con-
can be presented on the map. There are a
centrations in either (Parts-Per-Million)
number of different possibilities:
“ppm” or “mg/m3”.
Time of arrival It is also possible to display a number of
Instantaneous concentration different international defined Level of
Maximum instantaneous concentra- Concern (LOC) e.g. AEGL, ERPG, TEEL or
tion IDLH as isocurves on the plot. Alternative-
Time integrated concentration ly the user can setup ad-hoc isocurves at
Time integrated probit concentration individually selected levels.
Figure 34. ARGOS can show isocurves of a number of LOC's
ERPG Emergency Response Planning EPRG-3 The maximum airborne concen-
Guidelines (American Industrial Hygiene tration below which it is believed that
Association) nearly all individuals could be exposed for
up to 1 hour without experiencing or de-
ERPG-2 The maximum airborne concen-
veloping life-threatening health effects.
tration below which it is believed that
nearly all individuals could be exposed for IDLH Immediately dangerous to life or
up to 1 hr without experiencing or devel- health air concentration values (the Na-
oping irreversible or other serious health tional Institute for Occupational Safety
effects or symptoms which could impair and Health (NIOSH))
an individual's ability to take protective
5.3 The Chemical Database
The ARGOS database contains a number
of predefined chemicals, and new sub-
stances can easily be added to the list.
Figure 35. Chemical substances in the ARGOS
ARGOS Whitepaper Page 22 of 33
6 Biological Scenarios
When running prognoses of releases of ly infectious material, the airborne spread
biological agents ARGOS basically use the may take place over large distances at
same mechanisms and features as when concentration levels posing a risk. This
doing prognoses of chemical releases, may occur especially under stable mete-
namely the RIMPUFF and UDM models. orological conditions. In order to describe
such scenarios, the long-range dispersion
models interfaced with ARGOS should be
applied in addition to RIMPUFF, thereby
providing the best possible advice to the
decision makers. In addition, it might be
envisaged that the release takes place
outside the domain for which ARGOS has
access to meteorological data.
ARGOS includes a database for biological
Figure 36. Simulated release of Anthrax agents, which can (and should) be updat-
ed by the user. The initial database on
delivery has very few pre-defined agents.
In case of releases of large amounts of
biological agents, or releases of sufficient-
7 GIS Subsystem
ARGOS has its own subsystem for GIS (GIS
= Geographical Information System). The
GIS subsystem implements functionality
for displaying various information on top
of digital maps. ARGOS can display the
results of dispersion prognoses, meteoro-
logical data, and many other kinds of data
associated geographical coordinates.
ARGOS can be used to generate a map
with the basic civil infrastructure (land-
mass, borders, towns, roads etc) overlaid Figure 37. ARGOS has many GIS facilities.
with colour markings indicating areas hit
by fallout, air pollutions etc. as well as
The GIS subsystem also implements func-
meteorological information. This means
that complex information can be com-
piled into a single easy-to-understand importing and exporting geospatial
map – a very important feature when try- data from DXF, SHP or GeoTIFF files
ing to understand and communicate (SHP is ESRI-ShapeFile),
prognosis results under emergencies. working with and handling geospatial
data in the ARGOS database such as
population data, agricultural data
ARGOS Whitepaper Page 23 of 33
marking of the geographical location
for addresses from the ARGOS ad-
ARGOS can export the prognosis results to
PNG, GeoTIFF, KML and SHP files. The SHP
files contain also calculated values for
dose and/or other things, and hence the
SHP files can be opened in a GIS system or Figure 38. Results from Car measurements
statistical system for further analysis. displayed on top of a satellite picture from
ARGOS comes with a rather crude digital
map of the entire world. Additional details
can be compiled into the ARGOS map An organisation connecting to WMS serv-
from any other digital map data, e.g. ers must of course follow the license con-
maps supplied by different national ord- ditions of these servers using and in dis-
nance surveys. ARGOS is delivered with tributing results from these.
the SplitMap Utility providing this func-
Also ARGOS can connect can connect to
WMS servers including the various open
servers on the Internet such as Microsoft
Maps and Google Maps.
Figure 39. A Nuclear release on top of Mi-
crosoft Maps inside ARGOS.
7.1 Demography Support
For specific areas of interest selected di-
rectly by the user, or specified by certain
concentration levels or by safety distances
– ARGOS is able to provide information on
day- and night-time inhabitants of the
area as well as a calculation of the affect-
ed addresses in the area. It is also possible
to get on information regarding institu-
tions of interest – hospitals, cinemas, sta-
diums, kindergartens, schools etc. – to-
gether with relevant information regard-
ing the number of people possibly affect-
ed at the particular institution. Figure 40. An ARGOS display which shows
schools and hospitals affected by a simulated
ARGOS Whitepaper Page 24 of 33
7.2 Predefined Facilities
ARGOS is able to provide predefined in- standard release scenarios. Storing such
formation on chemical facilities for use predefined information for each facility
with atmospheric dispersion calculation makes for a very simplified and rapid set-
and for presentation in the system. The up of parameters for dispersion calcula-
information covers substances, container tions.
dimensions, storage capabilities and
7.3 Isocurves – Hazard Areas - levels of concern
To be written!!!
8 Handling multiple incidents
ARGOS supports working with multiple
simultaneously Incidents. For this purpose
ARGOS can work in a special “Incident”
When joined an Incident, ARGOS does a
number of things:
Helps the user focusing on the right
Easy loading of relevant scenarios.
Logging of actions in ARGOS.
Easy publish of results.
Figur 41. Definition of an Incident in ARGOS
9 Export of results from ARGOS
ARGOS can export many data and calcula-
tions in a number of different ways and
forms so they can be imported by other
systems and organisations.
As example publishing of prognosis results
can be done easily to a web-server in the
form of bitmap picture showing both the
underlying digital map and the dispersion
plume (or other prognosis results).
Figur 42. A prognosis may be published to the
web server as an animation.
10 Communication with other DSS
ARGOS can communicate with other DSS
systems with direct exchange of source
term data and other data via software
developed under the MODEM research
project; also the NARAC initiative is sup-
ported. Result from ARGOS may be pub-
lished directly on the Internet manually or
Figure 43. Presentation of an ARGOS prognosis
exported to the NARAC system.
11 Support for the NATO ATP45 Format
ARGOS supports a subset of the values inside ARGOS run a prognosis, and
ATP45/ADATP3 format (ROTA messages). in the end output a NBC3 message con-
taining warning zones.
A ROTA message can be used as input to
ARGOS. The user can then refine the input
12 ARGOS Web (Unfinished)
ARGOS provides a subset of its functional- CBRN rescue operation. But system will
ity through specialized web pages. also provide an Identification of the inci-
dent which can be used to communicate
with central ARGOS experts to further
12.1 Prognosis refine the prognosis.
The web prognosis interface supplied in A municipal or regional emergency man-
ARGOS is much simplified in comparison agement authority (or police, fire brigade
to the ARGOS GUI interface which has or similar) can run a prognosis from their
many detailed possibilities and options. local office rather than having to “call in”
The user input to the web page is a simple to the central emergency management
What, When and Where did the Incident authority. And it gives an easy opportuni-
happen. A fast prognosis will then be exe- ty for running exercises.
cuted at the servers returning the progno- A dispersion calculation is a rather pro-
sis on a GIS map together with various cessor consuming process and can take (in
information for the prognosis. web terminology) rather long time. In or-
This gives “a first guess” of the outline of der to prevent bottlenecks in case of sim-
the different safety and intervention ultaneous requests the system is setup so
zones that should be observed as part of a a number of servers can configured to
handle the calculations. It is also possible ganization. IRP offers a broad range of
to configure the system so that requests functionality:
from real life emergencies get priority
Logging during emergencies.
over requests from exercises.
Wikipedia for sharing information in
Reactor and site search.
Chemical substance search.
Publish of results from ARGOS.
Extensive user security settings.
ARGOS web interface.
Within emergency organizations there’s
often a demand to log every thing that’s
done during exercises and real incidents.
Such logged information is needed when
evaluating afterwards. By using IRP it’s
possible to log actions done in ARGOS au-
tomatically. Likewise the publishing of
Figure 44. Running a first simple prognosis
results done from ARGOS can also be
from a web page.
shared easily in the emergency organiza-
tion by publishing via IRP.
Nucinfo is an information centre dedicat-
ed to answering questions from con-
cerned citizens in case of a crisis situation,
and to support the information infrastruc-
ture of the Emergency Management or-
ganization itself. It is built as a web solu-
tion which can be deployed on both In-
tranet and the Internet.
The Information System handles data
from different information sources like
geographical maps, encyclopaedia, pic-
tures, lexical knowledge, various data-
bases etc. Also, the system has facilities to Figure 45. A listing from the log.
support communication in a crisis situa-
tion and a logging facility, to log all incom- IRP was originally made as an intranet
ing and outgoing communication during web application, but due to it’s high level
an emergency situation. of security, it can also be used a means to
share information to other authorities in
other departments. It’s possible to set
12.3 Integrated Response Plat- specific user rights on almost all function-
form (IRP) ality IRP offers.
Integrated Response platform (IRP) is a IRP also enables users to search for reac-
web based system that makes it possible tors and sites via a long range of search
to share information from ARGOS and options.
from other sources in the emergency or-
ARGOS Whitepaper Page 27 of 33
13 ARGOS Integration possibilities
and export of data can be established
through webservices on request.
13.1 Import and Export ser-
ARGOS comes with a number of data im- 13.3 Auto-Forecast Service
port and export services. These can im- The ARGOS Auto-Forecast Service can be
port data from files of emails, and also configured to automatically create prog-
export data to a number of formats. noses for one or more scenarios.
In this way, it can be possible to ascertain
13.2 Web services (SOA) the affected region of an accident in a
very short time. Once setup, the Service
ARGOS can be integrated in a Service Ori- will run perpetually, without interaction
ented Architecture. Prognoses can be in- and with the latest NWP forecast.
voked from other applications, and import
client PC should have at least 1GB of
memory and at least 5GB hard of free disk
14.1 Client side for optimal performance, but less may
The ARGOS application itself is a client- work. The CPU should be as fast as possi-
side application designed to run at indi- ble, but there are no CPU speed require-
vidual user’s laptops or workstations run- ments as such.
ning Microsoft Windows(XP, Vista,…). The
ARGOS Whitepaper Page 28 of 33
ARGOS can be operated remotely through 14.3 Security
CITRIX or Windows remote desktop, to
avoid installing software at the client ma- Access to individual functions in ARGOS
chine, or even operate ARGOS from a can be controlled via the ARGOS security
small PDA. subsystem. ARGOS security is based on
the Windows integrated security which is
also supported by the MS SQL Server.
14.2 Server side ARGOS can set permissions on the SQL
Server tables so a given user have no way
ARGOS stores data on an MS SQL Server to access data, if he is not allowed to ac-
(SQL Server 2000, 2005, ?). cess those data.
In a typical emergency management or-
ganisation, there will be a central SQL
server, which all the ARGOS clients access
to share data.
15 The ARGOS Consortium
ARGOS is based on a long lasting strong The consortium arranges an annual meet-
partnership between the users, research ing, where all members have equal oppor-
organisations and developers. tunities to influence the development of
the systems. The consortium discusses the
The users of ARGOS are mainly National
function of ARGOS and decides on which
organisations responsible for emergency
new facilities to develop, which new
management. The users of ARGOS have
models to include, etc. In this way, the
established the ARGOS Consortium with
ARGOS consortium ensures a user driven
the objective to maintain and further
development of ARGOS.
evolve ARGOS as a state-of-the-art deci-
sion support system for emergency re-
sponse as well as a network of expertise.
The current member countries of the con-
sortium are (May 2009): Denmark, Nor-
way, Ireland, Canada, Estonia, Sweden,
Poland, Lithuania, Australia, Brazil, Mon-
tenegro, Faroe Islands, Turkey.
Figure 47. A picture from one of the meetings
A new member can enter the consortium
and get access to the programmes with-
out paying any license fees, but there is
an annual fee to cover future develop-
ment and maintenance of ARGOS. The
fees for the countries are set relative to
the GDP of the country so larger countries
pay more than smaller countries.
Figure 46. The countries using ARGOS
For entering the consortium a new mem-
ber organisation (country), must sign a
three-part contract with Prolog Develop-
ARGOS Whitepaper Page 29 of 33
ment Center (PDC) and the Danish Emer-
gency Management Agency (DEMA) as co-
Membership of the consortium entitles
the organisation to install ARGOS and the
related systems on as many computers as
required in the organisation and other
organisations related to its emergency
Figure 48. Australia signing the ARGOS consor-
15.1 Training, Courses and Support
Training for ARGOS can be performed administrators or end users, contact PDC
from either PDC or from other users in the regarding next courses.
Support can be made from other users in
At regular intervals PDC will carry out the network – or by hourly rate from PDC.
standard courses for ARGOS for either
15.2 License conditions and pricing?
For public organisations it is required to are in EURO: Denmark 16k, Sweden 21k,
be member of the ARGOS consortium. Australia 35k. In return it is allowed to
There is no license fee as such, but it is install AROGOS on all computers in the
required to pay the yearly membership country involved in the public emergency
fee which is dependant on the GDP for management. Several organisations might
the country. Examples of the fee for 2009 share the fee.
15.3 How to get started with ARGOS
Contact , and we will put ed to implement ARGOS in an organisa-
you in contact with the relevant persons. tion.
Usually a presentation and a little feasibil- One way to get started is to join the
ity study is needed before it can be decid- ARGOS consortium for a year to see how
it all works…
16 User Testimonials
was made possible through funding from
the Canadian CBRN Research and Tech-
16.1 Canada nology Initiative (CRTI).
In Canada, ARGOS was fully implemented
in late March 2005 at Health Canada's
radioprotection Bureau as the official De-
cision Support System supporting the
Technical Advisory Group under the Fed-
eral Nuclear Emergency Plan. The project
ARGOS Whitepaper Page 30 of 33
ARGOS in Norway - so far… TO BE SOLVED
automatic on request
Short distance dispersion modelling, GIS
Figure 49. Eric Pellerin, Head of the Technical
National group of users: NRPA, met.no, FFI (Defence research institute)
As-sessments Coordination Section of Health www.nrpa.no
Canada's Radiation protection Bureau. Figure 50. Status of ARGOS implementation in
The Canadian ARGOS system interfaces
with the Canadian Meteorological Center
for the retrieval of real-time NWP-data 16.3 Ireland
and to use the centre’s supercomputing Since 2001 the RPII has used ARGOS as its
facility to generate the long-range disper-
primary tool for technical assessment of,
sion models. and preparedness for, a nuclear or radio-
It is also hooked-up to Health Canada's logical emergency. The installation of
radiation monitoring network for surveil- ARGOS in the RPII features the following
lance and alerting. components:
ARGOS should be shortly connected to the ARGOS database which contains
Health Canada's Laboratory Information radiological monitoring data1; nucle-
Management System (LIMS) to enable it ar base data (e.g. dose coefficients,
to perform food chain dose analysis based nuclear reactor characteristics, etc);
on environmental samples. The ARGOS and meteorological data (weather
system is now a major part of Canadian forecasts and radar rainfall meas-
RN emergency preparedness and re- urements);
RIMPUFF (RIsø DTU-Mesoscale-
After implementing the ARGOS solution, PUFF), an atmospheric dispersion
Health Canada's Radiation Protection Bu- model driven by meteorological fore-
reau and the CRTI project review commit- cast data provided by Met Éireann
tee have evaluated and were very satis- (the Irish National Meteorological
fied with the outcome of the project. Ac- Service), which enables the transport
cording to Eric Pellerin, "The ARGOS pro- and dispersal of radioactive contami-
ject is a huge success for NEPRD and HC. nation to be predicted;
The project reached its goals within the
FDM (Food and Dose Module), a
allocated time frame and budget. All key
model for simulation of contamina-
objectives for capability were accom-
tion of the food chain and assess-
plished and the project is well seen by our
ment of doses following a nuclear or
national and international partners".
radiological emergency; and
the PMS (Permanent Monitoring Sta-
tions) database which is used for dis-
play and reporting of gamma dose
rate data from the Irish monitoring
network and RIMNET. In the case of
ARGOS Whitepaper Page 31 of 33
elevated values being recorded, implemented at the Swedish Radiation
alerts are generated from this data- Protection Authority (SSI) in Stockholm
base and sent to the duty officer. and at the Swedish Defence Research Es-
tablishment (FOI) in Umeå. A full installa-
The ability to overlay measured data and
tion at the Swedish Meteorological and
model results on geographical maps and
Hydrological Institute (SMHI) in Norrkö-
to export these to standard Geographical
ping is currently pending. Furthermore,
Information Systems (GIS) for further
there have been some manifestations of
analysis are considered by the RPII to be
interest from the NPP operators to get
particularly useful functions of ARGOS.
access to the system.
Today, the core databases at SSI consist of
16.4 Sweden two identical implementations, a primary
system in Stockholm and a secondary,
Following an initial test and evaluation
geographically separated from the prima-
period, the ARGOS system has been in
ry, in Northern Sweden.
production use within the Swedish Nucle-
ar and Radiological Emergency Prepared-
ness since 2005. The system is currently
Prolog Development Center A/S Mr. Mads Skak Jensen
H.J. Holst Vej 3C-5C
Tlf. +45 36 36 00 00
Mr. Leo Schou-Jensen, Director
Mr. Jan Pehrsson, Area Manager
Mr. Hans Olav Nymand, Developer
Mr. Lars Henrik S. Jacobsen, Developer
Mr. Per Marquardsen, Developer
Mr. Jørgen H. Andersen, Developer
Danish Emergency Management Agency
Nuclear Division, Chemical Division,
DK-3460 Birkerød, Denmark
Phone +45 45906000
Mr. Michael Boesgaard Brøndel, Head of
Mr. Bjørn Thorlaksen, Chief Inspector
Mr. Steen Hoe, Senior Scientist
Mr. Dan Kampmann, Senior Scientist
Ms. Anette Espersen, Chief Inspector
Mr. Jan Steen Jensen, Senior Scientist
ARGOS Whitepaper Page 32 of 33
PO Box 49,
DK-4000 Roskilde, Denmark
Phone +45 4677 5026
Mr. Torben Mikkelsen
Mr. Poul Astrup,
Mr. Morten Nielsen
Mr. Kasper G. Andersson
Danish Meteorological Institute
DK-2100 Copenhagen, Denmark
Phone +45 3915 7500
Mr. Jens Havskov Sørensen, Senior Scien-
Mr. Alexander Baklanov, Senior Scientist
ARGOS Whitepaper Page 33 of 33