1. Ecological risk control in the context of sustainable development: methods Vladimir Penenko ICM&MG SD RAS, Novosibirsk

2. Tools for scenario approach: models & techniques Models of hydrodynamics Models of transport and transformation of pollutants (gases and aerosols) Functionals for management strategies ( generalized description of the system, restrictions, cost, etc.) Sensitivity and observability algorithms Combination of forward and inverse techniques Joint use of models and data

3. Extraction of multi- dimensional and multi-component factors from data bases Classification of typical situations with respect to main factors Investigation of variability Formation of “leading” spaces Analysis of the climatic system for construction of long-term scenarios

5. Model of hydrodynamics

7. Transformation of moisture and pollutants Gases and aerosols interaction with underlying surface dry and wet deposition condensation and evaporation coagulation Model of atmospheric chemistry Model of aerosol dynamics Model of moisture transformation water vapour cloud water rain water

8. is the function of pressure

9. Model of aerosol dynamics - concentration of particles in volume - coagulation kernel; - rates of condensation and evaporation; - coefficients of diffusive change of particles; - removal parameter; -source term; -parameters of collective interaction of particles

10. Hydrological cycle of atmospheric circulation for studying aerosols - evaporation of cloud-water - autoconversion of cloud water to rain water - accretion of cloud droplets by rain drops - evaporation of rain water - condensation of water-vapour Main processes:

12. Functionals of measurements

13. The structure of the source term source power source shape reference point of the source Particular case control parameters

14. Functionals for assessment of source parameters

18. Symmetrized form for operators of turbulent exchange and transformation of substances M- transport operators, R – transformation operators,

20. The main sensitivity relations The algorithm for calculation of sensitivity functions are the sensitivity functions are the parameter variations The feed-back relations

21. Sensitivity relation for estimation of risk/vulnerability and observability

22. Threshold of safety intervals safe ecological conditions Estimations for deterministic case Risk assessment with the help of sensitivity functions

23. Estimations for deterministic-stochastic case

24. Safe range Risk domain

25. specifying the set of receptors and the structure of the functionals; constructing and calculating the sensitivity relations ( solutions of the forward and adjoint problems); revealing the risk/vulnerability domains for given set of receptors and functionals; detecting the sources located in the risk domains; grading the sources in accord with the degree of potential danger and the level of significance of the sensitivity functions; separating the sources into two groups: open to control and placed beyond one’s reach ; construction of management strategy according to the goal criteria and restrictions. System organisation of the risk management algorithms

26. Numerical algorithm of control and identification 1.Calculation of SFs for goal functionals. Assessment of parameter variations 2.Calculation of SFs for restriction functionals 3.Formation of linearized manifold to take into account every restriction 4.Projection of estimations of item 1 on the restriction manifold of items 2&3 5. Check of convergence criteria

27. Global and regional models of hydrodynamics Models of pollutants’ transport Hybrid vertical coordinate system (p-sigma) Fast data assimilation Reanalysis NCEP/NCAR data base Applications

28. Risk assessment of volcano eruption Source of emission: Shiveluch Release time 19-21.05.2001 Surface level150 mb

29. Risk assessment for two versions of military action in Iraq: winter spring From Iraq's Weapons of Mass Destruction Programs, U.S. Director of Central Intelligence, October 2002

30. Winter scenarioanimation Spring scenarioanimation Risk assessment for two versions of military action in Iraq: winter spring

31. Transboundary transport and risks in the Russian Far East, China and Korea

32. Forward problem: cities as aggregated sources of pollution Shenyang Pyonguyang Laoyang Seoul Anshan Khabarovsk Teling Vladivostok Fu-shun Dalian Dantung In-Cou Jin-Jou Fu-Sin Beijng Harbin Changchun

33. animation

34. Inverse problem: cities as receptors Vladivistok Khabarovsk Beijng Shenyang Dalian Seoul animation

35. Conclusion Combination of the forward and inverse modeling seems to be advanced technology for risk / vulnerability studies Joint use of sensitivity and observability techniques gives the possibility to detect the unreachable and uncontrolled sources Forecasting and management of ecological risks is a key element in the choice of the strategies of sustainable development and social safety Subjects require amplification: refinement of goal criteria and constrains; forecasting and management in the conditions of uncertainties

36. Acknowledgements The work is supported by RFBR Grant 04-05-64562 Russian Ministry of Science and Education Contract № 37.011.11.0009 Russian Academy of Sciences Program 13 Program 14 Program 1.3.2 Siberian Division of Russian Academy of Sciences Integrating projects 130, 131, 137, 138