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Ecological risk control in the context of sustainable development: methods. Vladimir Penenko. ICM&MG SD RAS, Novosibirsk. Tools for scenario approach: models & techniques. Models of hydrodynamics Models of transport and transformation of pollutants (gases and aerosols)
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Ecological risk control in the context of sustainable development: methods Vladimir Penenko ICM&MG SD RAS, Novosibirsk
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
Analysis of the climatic system for construction of long-term scenarios • 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
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
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
Hydrological cycle of atmospheric circulation for studying aerosols Main processes: - autoconversion of cloud water to rain water - accretion of cloud droplets by rain drops - evaporation of rain water - condensation of water-vapour - evaporation of cloud-water
The structure of the source term source power source shape reference point of the source control parameters Particular case
Symmetrized form for operators of turbulent exchange and transformation of substances M- transport operators, R – transformation operators,
The main sensitivity relations The algorithm for calculation of sensitivity functions The feed-back relations are the sensitivity functions are the parameter variations
Sensitivity relation for estimation of risk/vulnerability and observability
Risk assessment with the help of sensitivity functions Threshold of safety intervals safe ecological conditions Estimations for deterministic case
Risk domain Safe range
System organisation of the risk management algorithms • 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.
Numerical algorithm of control and identification • Calculation of SFs for goal functionals. Assessment of parameter variations • Calculation of SFs for restriction functionals • Formation of linearized manifold to take into account every restriction • Projection of estimations of item 1 on the restriction manifold of items 2&3 • Check of convergence criteria
Applications Global and regional models of hydrodynamics Models of pollutants’ transport Hybrid vertical coordinate system (p-sigma) Fast data assimilation Reanalysis NCEP/NCAR data base
Risk assessment of volcano eruption Source of emission: Shiveluch Release time 19-21.05.2001 150 mb Surface level
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
Risk assessment • for two versions of military action in Iraq: • winter • spring Winter scenario animation Spring scenario animation
Transboundary transport and risks in the Russian Far East, China and Korea
Forward problem: cities as aggregated sources of pollution Shenyang Pyonguyang Laoyang Seoul Anshan Khabarovsk TelingVladivostok Fu-shun Dalian Dantung In-Cou Jin-Jou Fu-Sin Beijng Harbin Changchun
Inverse problem: cities as receptors Vladivistok Khabarovsk Beijng Shenyang Dalian Seoul animation
Conclusion Forecasting and management of ecological risks is a key element in the choice of the strategies of sustainable development and social safety 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 • Subjects require amplification: • refinement of goal criteria and constrains; • forecasting and management in the conditions of uncertainties
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