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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) - PowerPoint PPT Presentation
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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
• Extraction of multi- dimensional and multi-component factors from data bases
• Classification of typical situations with respectto main factors
• Investigation of variability
• Formation of “leading” spaces
Analysis of the climatic system for constructionof long-term scenarios
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Model of transport and transformation
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•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
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
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
Risk assessment of volcano eruption
Source of emission: ShiveluchRelease time 19-21.05.2001
Surface level150 mb
1
1
12
2
2
3
3
45
6
11 110 0.59 0.18 0.057 0.016 0.0055 0.0014 0.00053 0.00012 5E-051 1E-05
Risk domain to get pollution within the time interval 19.05-19.06.2001.Surface level, gases.Source of emission: volcano Shiveluch.
Release time 19.05-21.05 2001
1
1
1
1
2
2
3
33
45
7
11 110 0.59 0.18 0.057 0.016 0.0055 0.0014 0.00053 0.00012 5E-051 1E-05
Risk domain to get pollution within the time interval 19.05-19.06.2001.150mb, gases.Source of emission: volcano Shiveluch.
Release time 19.05-21.05 2001
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
Winter scenario animation
Spring scenario animation
Risk assessment for two versions of military action in Iraq:•winter•spring
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 Teling Vladivostok Fu-shun Dalian Dantung In-Cou Jin-Jou Fu-Sin Beijng Harbin Changchun
animation
Inverse problem: cities as receptors
Vladivistok Khabarovsk Beijng Shenyang Dalian Seoul
animation
Conclusion
Combination of the forward and inverse modeling seems to be advanced technology for risk / vulnerabilitystudies
Joint use of sensitivity and observability techniques givesthe 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
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 13Program 14Program 1.3.2
•Siberian Division of Russian Academy of SciencesIntegrating projects 130, 131, 137, 138