© K.Fedra 2000 1 Environmental modeling application domains anoverview of environmental topics and domains.

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Presentation transcript:

© K.Fedra Environmental modeling application domains anoverview of environmental topics and domains

© K.Fedra Modeling Domains Atmospheric systemsAtmospheric systems Hydrologic systemsHydrologic systems Land surface and subsurfaceLand surface and subsurface Biological and ecological systemsBiological and ecological systems Risks and hazardsRisks and hazards Technological systems (transportation)Technological systems (transportation) Management and policy modelsManagement and policy models Atmospheric systemsAtmospheric systems Hydrologic systemsHydrologic systems Land surface and subsurfaceLand surface and subsurface Biological and ecological systemsBiological and ecological systems Risks and hazardsRisks and hazards Technological systems (transportation)Technological systems (transportation) Management and policy modelsManagement and policy models

© K.Fedra Modeling Domains Atmospheric systems weather forecastingweather forecasting climate modelsclimate models air pollution: industry, traffic, domestic sources, accidental releases (hazardous substances)air pollution: industry, traffic, domestic sources, accidental releases (hazardous substances) Atmospheric systems weather forecastingweather forecasting climate modelsclimate models air pollution: industry, traffic, domestic sources, accidental releases (hazardous substances)air pollution: industry, traffic, domestic sources, accidental releases (hazardous substances)

© K.Fedra Modeling Domains Atmospheric systems weather forecastingweather forecasting climate modelsclimate models air pollution: industry, traffic, domestic sources, accidental releases (hazardous substances)air pollution: industry, traffic, domestic sources, accidental releases (hazardous substances) Atmospheric systems weather forecastingweather forecasting climate modelsclimate models air pollution: industry, traffic, domestic sources, accidental releases (hazardous substances)air pollution: industry, traffic, domestic sources, accidental releases (hazardous substances)

© K.Fedra Modeling Domains climate models: attempt to analyse the effects of greenhouse gas emissions on the global climate, global climate, energy balance, energy balance, sea level rise, sea level rise, water resources, water resources, vegetation and vegetation and wildlife, human wildlife, human health, etc. health, etc. climate models: attempt to analyse the effects of greenhouse gas emissions on the global climate, global climate, energy balance, energy balance, sea level rise, sea level rise, water resources, water resources, vegetation and vegetation and wildlife, human wildlife, human health, etc. health, etc.

© K.Fedra Modeling Domains climate models: global circulation models GCMs use a coarse resolution (between 3 to 6 deg. lat.long, 6 deg. lat.long, and a few vertical and a few vertical layers. layers. Comparison with Comparison with long-term climate long-term climate measurements measurements (30 year average (30 year average July temperatures). July temperatures). climate models: global circulation models GCMs use a coarse resolution (between 3 to 6 deg. lat.long, 6 deg. lat.long, and a few vertical and a few vertical layers. layers. Comparison with Comparison with long-term climate long-term climate measurements measurements (30 year average (30 year average July temperatures). July temperatures).

© K.Fedra Modeling Domains climate models: scenario assumptions usually are based on an increase in atmospheric CO 2 atmospheric CO 2 Example: UKMO Example: UKMO current CO 2 levels. current CO 2 levels. climate models: scenario assumptions usually are based on an increase in atmospheric CO 2 atmospheric CO 2 Example: UKMO Example: UKMO current CO 2 levels. current CO 2 levels.

© K.Fedra Modeling Domains climate models: scenario assumptions usually are based on an increase in atmospheric CO 2 atmospheric CO 2 Example: UKMO Example: UKMO doubled CO 2 levels. doubled CO 2 levels. climate models: scenario assumptions usually are based on an increase in atmospheric CO 2 atmospheric CO 2 Example: UKMO Example: UKMO doubled CO 2 levels. doubled CO 2 levels.

© K.Fedra Modeling Domains Air pollution modeling estimation of the source term:estimation of the source term: – rate and duration of release – source size, location –initial buoyancy and momentum Air pollution modeling estimation of the source term:estimation of the source term: – rate and duration of release – source size, location –initial buoyancy and momentum

© K.Fedra Modeling Domains estimation of the source term: embedded expert embedded expert system with an system with an object data base. object data base. estimation of the source term: embedded expert embedded expert system with an system with an object data base. object data base.

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© K.Fedra Modeling Domains Air pollution modeling pollutant transportpollutant transport – advection by wind – turbulent and molecular diffusion – buoyancy effects (gases, particles) – deposition, chemical reactions, radioactive decay radioactive decay Air pollution modeling pollutant transportpollutant transport – advection by wind – turbulent and molecular diffusion – buoyancy effects (gases, particles) – deposition, chemical reactions, radioactive decay radioactive decay

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© K.Fedra Modeling Domains pollutant pollutant transport transport Gaussian Gaussian 2D model 2D model (USEPA ISC) (USEPA ISC) pollutant pollutant transport transport Gaussian Gaussian 2D model 2D model (USEPA ISC) (USEPA ISC)

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© K.Fedra Real-time 48 hour air quality forecast: Helsinki metropolitan

© K.Fedra Modeling Domains Air pollution modeling impacts and hazardsimpacts and hazards – human end environmental exposure –damage through chemical reactions (corrosion) (corrosion) – damage through explosion and fire Air pollution modeling impacts and hazardsimpacts and hazards – human end environmental exposure –damage through chemical reactions (corrosion) (corrosion) – damage through explosion and fire

© K.Fedra Modeling Domains impacts and hazards: estimated by overlays of overlays of long-term air long-term air quality values quality values (simulated with (simulated with ISC-LT model) ISC-LT model) and land use and land use or population or population maps. maps. impacts and hazards: estimated by overlays of overlays of long-term air long-term air quality values quality values (simulated with (simulated with ISC-LT model) ISC-LT model) and land use and land use or population or population maps. maps.

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© K.Fedra Modeling Domains Air pollution modeling Management scenariosManagement scenarios – direct comparison of alternatives – computations of costs (investment, operations, repair and replacement) – optimization Air pollution modeling Management scenariosManagement scenarios – direct comparison of alternatives – computations of costs (investment, operations, repair and replacement) – optimization

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© K.Fedra Real-time POLLEN forecast: Kanto, Japan

© K.Fedra Real-time POLLEN forecast: Kanto, Japan

© K.Fedra Real-time POLLEN forecast: Kanto, Japan

© K.Fedra Real-time POLLEN forecast: Kanto, Japan

© K.Fedra Real-time POLLEN forecast: Kanto, Japan

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