Methodology for Probabilistic Risk Assessments for the Euro-Arctic

Region “Arctic Risk” Project

http://glwww.dmi.dk/f+u/luft/eng/arctic-risk/main.html of the Nordic Arctic Research Programme (NARP)

(2001-2003)

A. Baklanov, A. Mahura, J.H. Sørensen

Danish Meteorological Institute, Copenhagen, Denmark

International Conference on Computational Information Technologies for Environmental Sciences:

“CITES-2005”Novosibirsk, Russia, March 20-23, 2005

GOALS, QUESTIONS & OBJECTIVESMain Goals:

- to develop a methodology for complex risk/vulnerability assessment & mapping; - to evaluate atmospheric transport patterns for harmful pollutants from ERSs based on the probabilistic point of view; and - to test methodology on estimation of a possible radiation risk to population in the Nordic countries in a case of severe accident at NRS and a long-term environment impact from large industrial sites.

Main Questions:• Which sources appear to be the most dangerous for people living close to and far from these sources? • Which regions are on the highest risk from a possible hypothetical accidental release in the Euro-Arctic region? • What is the probability for contaminant atmospheric transport to different neighbouring countries in a case of an accident at ERSs?

Specific Objectives:• Examination of general atmospheric transport pathways and airflow patterns from ERSs• Estimation of probability of fast transport of contaminant released from ERSs• Evaluation typical transport time, maximum reaching distance and possible impact zones • Investigation of possible impacts of removal processes during transport• GIS-integration of various indicators into a complex risk assessment• Combination of approaches for probabilistic risk analysis and cases studies• Evaluation of probabilistic risk for selected ERSs in the North-West Russia

METHODOLOGY FOR COMPLEX RISK ASSESSMENT

PROBABILISTIC RISK ANALYSIS

Territorial Vulnerability &

Residential Risk

Precipitation Factor

Probability

Atmospheric Transport Probability

GIS-CMA Method

Trajectory Modeling Cluster Analysis

Probability Fields Analysis

GIS Databases

Nuclear Risk Sites

Radiological Sensitivity

Population & Administrative

Units

SPECIFIC CASE STUDIES

Radioactive Contamination Fields (for most probable or worst-case scenarios)

Collective & Mean

Individual Doses

GIS-OVERLAY

Consequences & Doses Modeling: MACCS, COSYMA, Empirical Models

Dispersion Modeling: MATHEW / ADPIC

DMI - DERMA

After Rigina 2001

METHODOLOGY FOR

PROBABILISTIC RISK

ANALYSIS

GIS COMPLEX RISK ASSESSMENT

Pre-processing and Using of DataBases

Nuclear Risk Objects

Population and risk groups

Administrative Boundaries

Radioecological Sensitivity

of Territories

Economical Factors

Social Factors

Other Factors Political Factors

GIS Modelling of NRS Impact

TRAJECTORY ANALYSIS

Exploratory Data

Analysis of Trajectories

Cluster Analysis of Trajectories

Other Methods of Statistical

Analysis

Probability Fields

Analysis

METEOROLOGICAL DATA ARCHIVES

Data Extracting and Pre-processing

NCAR ECMWF DMI-HIRLAM Other archives

CHARACTERISTICS AND INDICATORS OF NRS IMPACT

Typical Transport Time

Field

Simple Characteristics for Selected Geographical Regions: - Upper & Lower Boundaries of NRS Impact - Average Transport Time - Atmospheric Transport by Layers - Fast Transport, etc.

Atmospheric Transport Pathways

Other Characteristics and

Indicators

Maximum Reaching Distance

and Maximum Possible

Impact Zone

Probability Fields

Airflow Fast Transport Precipitation and Relative Humidity

Mixing Layer Height

Dry, Wet and

Total Deposition

Concentration and

Doses

TRAJECTORY AND DISPERSION MODELLING

Isentropic Trajectory

Model

DMI- Trajectory

Model

Other Models

DERMA-Model of Long-Range

Transport

Models of Local

Scale

• Trajectory Modellingto calculate multiyear forward trajectories originated over the NRSs locations using isentropic trajectory model & 3-D DMI trajectory model

• Cluster Analysis Technique on Trajectoriesto identify atmospheric transport pathways from the NRSs regions

• Probability Fields Analysis on Trajectoriesto construct and analyze annual/seasonal/monthly probability fields for airflow, fast transport, etc to identify the potentially most impacted geographical areas

• Long-range transport DERMA & DMI-HIRLAM modelsto simulate meteorological fields and radionuclide transport, dispersion and deposition for the hypothetical accidental releases at NRSs, and compare with results of trajectory modelling

• Specific Case Studiesto estimate the consequences for environment and population after hypothetical accidents using experimental models based on the Chernobyl effects for the Nordic countries

• Evaluation of vulnerability to radioactive depositionto evaluate vulnerability to radioactive contamination concerning its persistence in the ecosystems with a focus on transfer of certain radionuclides into food chains of key importance for the intake and exposure of a whole population and certain groups in the Nordic countries

• Complex risk evaluation and mappingto analyse consequences for different geographical areas and various population groups taking into account social-geophysical factors and probabilities and using GIS-analysis

USED APPROACHES

Backward and Adjoint Simulations

• Sensitivity of Receptors or Source-term estimation.

• Trajectory modelling to calculate backward/forward individual or multiyear trajectory data sets for sensitivity studies.

• Cluster and Probability fields analysis of trajectory/ dispersion data sets by month, season, and year (Baklanov and Mahura, 2002).

• Adjoint modelling for atmospheric pollution problem to calculate receptor sensitivity or unknown source term based on monitoring data for local- and global scales (Penenko and Baklanov, 2001).

Structure of the Danish nuclear emergency modelling system

DMI-HIRLAM systemDMI-HIRLAM system

• G: 0.45°• E and N: 0.15°• D: 0.05°• L: 0.014°

ECMWF global modelECMWF global model

DERMA modelDERMA model

• 3-D trajectory model

• Long-range dispersion

• Deposition of radionuclides

• Radioactive decay

• Direct and inverse modes

ARGOS systemARGOS system

• Radiological monitoring

• Source term estimation

• Local-Scale Model Chain

• Health effects

The applicability of the method includes:

•    Initial estimates of probability of the atmospheric transport and consequences in the event of an accident;•    Improve emergency response to harmful releases from the ERSs locations;•    Social and economical consequences studies of the ERS impact for population and environment of the neighbouring countries;•    Multidisciplinary risk and vulnerability analysis, probabilistic assessment of pollutant meso-, regional-, and long-range transport;•    Verification and improvement of simple integrated models.

ERS POSSIBLE IMPACT INDICATORS BASED

ON TRAJECTORY & DISPERSION MODELLING Airflow Probability Fields, Fast Transport Probability Fields, Typical Transport Time Fields, Maximum Reaching Distance, Maximum Possible Impact Zone, Precipitation Factor or Relative Humidity Fields, Average and Summary Time Integrated Air Concentration, Average and Summary Dry Deposition Fields, Average and Summary Wet Deposition Fields.

INDICATORS FOR COMPLEX RISK ASSESSMENT

For assessment of risk/vulnerability we consider:

1. Social Geophysical Factors:proximity to the radiation risk sites; population density in the area of interest;presence of critical groups of population;ecological vulnerability of the area;risk perception, preparedness of safety measures, systems for emergency

response; economical and technical means, counteracting consequences of a possible

accident etc;

2) Probabilities: probability of an accident of a certain severity at NRS;probability of air transport pathways towards the area of interest from NRS

(from probabilistic trajectory modelling);probability of precipitation and deposition over the area of interest during the

transport of a plume along trajectories (from probabilistic modelling).

STUDY AREAS AND SELECTED RISK SITES

European North North Pacific region

Monthly variations in the average transport time (in days) from the Kamchatka NRS to geographical regions based on the

forward trajectories during 1987-1996

Monthly average transport time from the Kamchatka NRS to the geographical regions

0

1

2

3

4

5

6

7

8

9

10

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

Month

North J apan

Central J apan

South J apan

North Korea

South Korea

North China

Seashore China

Aleutian Chain US

Alaska State US

PROBABILISTIC NRSs IMPACT INDICATORS

AIRFLOW PROBABILITY FIELDS

BNP - Barsebäck NPPBGP – Group of German NPPs

FAST TRANSPORT PROBABILITY FIELDS

PROBABILISTIC NRSs IMPACT INDICATORS

TYPICAL TRANSPORT TIME FIELDS

LRS - Loviisa NPPINP - Ignalina NPP

MAXIMUM POSSIBLE IMPACT ZONE & MAXIMUM REACHING DISTANCE

ADDITIONAL NRSs IMPACT INDICATORSBASED ON TRAJECTORY MODELING

RELATIVE HUMIDITY FIELDS

KNRS - Kamchatka NRSKNPP - Kola NPP

ATMOSPHERIC TRANSPORT PATHWAYS

NRSs IMPACT INDICATORSBASED ON DISPERSION MODELING

Kamchatka NRS

AVERAGE INTEGRAL CONCENTRATION AT SURFACE FIELD

Vladivostok NRS

NRSs IMPACT INDICATORSBASED ON DISPERSION MODELING

SUMMARY WET DEPOSITION FIELD

Ignalina NPP

SUMMARY DRY DEPOSITION FIELD

GIS-METHODS FOR RISK EVALUATION(Rigina 2001)

n

i=i(x,y)RR(x,y)=

1

R P P P F F F F F Fi acc i tr i pr i dem dis i t i cg soc ev , , , , ,

Total risk function as a sum of risk functions from n NRSs

First method to define risk function:R P P P a F a F a F a F a F a Fi acc i tr i pr i dem dis i t i cg soc ev , , , , ,( )1 2 3 4 5 6

Second method to define risk function:

Pacc function defining probability Pk of an accident of a certain class k and severity Ik:

Ptr probability that the trajectory of the accidental plume will reach a certain territory (area of interest)

Ppr probability of precipitation over a certain territory during the plume pass

Fdis factor, representing dispersion and dry deposition of the radioactive plume on its way from the accident site

Fdem population factor for the general group

Ft function defining risk connected to a quick transport of contamination, and it is inversely proportional to the time for reaching a certain territory by the plume

Fcg factor defining vulnerability of the critical groups of the population to radioactive contamination: Fcg = rcg Dcr

/Dg

Fsoc factor of social risk, which depends on risk perception, preparedness of safety measures, systems for quick reaction, economical and technical means, counteracting consequences of a possible accident etc

Fev factor defining ecological vulnerability of an area

ai weight coefficients depending on the relative importance of each factor

P P Iacc k kk

m

1

PROBABILISTIC RISK MAPS

to the Nordic countries population for

Leningrad NPPKola NPP

Assessment Scheme

GIS Integration of Modelling Results & Avalailable Databases

DATABASES Population Dencity Social Factors

Political Factors

Time Integrated Air Concentration

Dry Deposition Wet Deposition

Total Deposition

Air Concentration

Calculation of Doses due to

Inhalation Ingestion External Exposure from Cloud

External Exposure from Surface

Total Dose

Maximum Reaching Distance AirFlow

Fast Transport Precipitation Factor

Long-Term Probabilistic Fields

Long-Term Modelling TRAJECTORY DISPERSION

Short-Term Probabilistic Fields

Short-Term Modelling DISPERSION

Probabilistic Approach Case Studies Approach

Soil Types & Properties Land-use, Urban Classes

Agricultural Crops Production Administrative Boundaries Domestic Animal Production

ECOMARCInstitute of Radiation Hygiene, St.Petersburg, Russia

Total accumulated dose of 137Cs during different time intervals according to the selected scenario of release.

Barsebaeck NPP

Annual Average Total/Individual Dose Annual Average Collective Dose

Annual Average Dose due to IngestionAnnual Average Dose due to Inhalation

Euro-Arctic Region NRSs

Annual Average Total/Individual Dose

Annual Average Collective Dose

Norilskiy Nickel Plant

Time Integrated Air Concentration

Dry Deposition

Wet Deposition

Annual SummaryField of SO_4

Severonickel Plant

Time Integrated Air Concentration

Wet Deposition

Dry Deposition

Annual SummaryField of SO_4

Chernobyl Nuclear Power Plant

RISO Model DERMA Model

Annual Summary Field of 137Cs Dry Deposition

PROBABILISTIC FIELDS ANALYSIS FOR RECEPTOR POINTS TO IDENTIFY SOURCE REGIONS

Nome, Alaska Anchorage, Alaska

Hypothetical release of 100 g Anthrax spores

Measurement stations:

Bio-terror: Source Determination

Inhalation dosecalculated by DERMAbased onDMI-HIRLAM-E

Determination of source location by inverse (adjoint) model calculation using DERMA based on measured data

CONCLUSIONS• Developed and tested a methodology for a complex risk and vulnerability assessment.

• Developed and tested a methodological approach for probabilistic atmospheric studies for evaluation of the atmospheric transport of radioactive pollutants from NRSs to different geographical regions. The evaluation is given from the probabilistic point of view.

• Suggested to apply a variety of research tools considering them as a sequence of interrelated approaches. Among these tools are the following: direct and adjoint trajectory and dispersion modelling, methods of statistical analysis (cluster & probability fields analyses), specific case studies, evaluation of vulnerability to radioactive contamination, and risk evaluation and mapping.

• Suggested indicators of possible nuclear risk sites impact: Airflow Probability Fields & Fast Transport Probability Fields, Maximum Reaching Distance & Maximum Possible Impact Zone, Typical Transport Time Fields & Precipitation Factor Fields, Summary and Average Time Integrated Concentration at Surface, Wet & Dry Deposition Fields.

• Estimated and mapped the regional vulnerability and complex probabilistic risk for population of the Nordic countries on example of the Kola and Leningrad NPPs.

APPLICATIONS

The results of this study are applicable for the further GIS analysis to estimate risk and vulnerability as well as for planning of systems for emergency response and preparedness measures in the cases of the accidental releases at ERSs.

The applicability of the method includes:

• Initial estimates of probability of the atmospheric transport in the event of an accident;

• Improve emergency response to harmful releases from the ERS locations;

• Social and economical consequences studies of the ERS impact for population and environment of the neighbouring countries;

• Multidisciplinary risk and vulnerability analysis, probabilistic assessment of contaminant meso-, regional-, and long-range transport;

• For long-term impact assessment from existing pollutant emission sources.

The methodology was employed for 16 NRSs and 3 NRSs + 2 ERSs in the Euro-Arctic and Siberian / North Pacific regions, respectively.

ACKNOWLEDGMENTS

• The authors are grateful for collaboration and constructive comments to Leif Laursen (Danish Meteorological Institute, DMI), Olga Rigina (Danish Technical University, DTU), Ronny Bergman (Swedish Defence Research Authority, FOI), John Merrill (University of Rhode Island, US), Vladimir Penenko and Elena Tsvetova (Siberian Division of RAS, Russia), Daniel Jaffe (University of Washington, Seattle, US), Boris Segerståhl (University of Oulu, Finland), Sven Nielsen (Risø National Laboratory, Denmark), Steen Hoe (Danish Emergency Management Agency).

• The computer facilities and data archives at the Danish Meteorological Institute (DMI, Copenhagen, Denmark) and National Center for Atmospheric Research (NCAR, Boulder, USA) had been used in this study.

• The authors are grateful for the collaboration, computer assistance, and advice to stuff of the Computer Services (DMI) & Scientific Computing Division (NCAR).

• Financial support from the Nordic Arctic Research Programme (NARP) and Nordisk Forskerutdannings Akademi (NorFA)

For more information:

Arctic Risk web-site:

http://glwww.dmi.dk/f+u/luft/eng/arctic-risk/main.html

FUMAPEX web-site: http://fumapex.dmi.dk

My e-mail: alb@dmi.dk

Thank you !