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Types of models Applications Case studies Estimating emissions Conclusions

The Role of Models in Air Quality Management Akula Venkatram University of California at Riverside and S.Trivikrama Rao NOAA Atmospheric Sciences Modeling Division. Types of models Applications Case studies Estimating emissions Conclusions. Air Quality Models. Comprehensive Model

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Types of models Applications Case studies Estimating emissions Conclusions

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  1. The Role of Models in Air Quality ManagementAkula Venkatram University of California at Riverside andS.Trivikrama RaoNOAA Atmospheric Sciences Modeling Division • Types of models • Applications • Case studies • Estimating emissions • Conclusions

  2. Air Quality Models Comprehensive Model Includes all the relevant physical and chemical processes in the atmosphere in as much detail as possible Semi-empirical Model Parameterizes major processes and is anchored explicitly to observations -Receptor Models

  3. Applications • Permitting new sources (e.g. ISC, AERMOD) • Examining the impact of emission changes • Interpolating among measured concentrations • Interpreting trends in air quality • Estimating emission strengths • Forecasting air quality

  4. Applications of Comprehensive Models • Photochemical pollution and Acid Deposition • Includes reactions among HCs and NOx and aerosol chemistry in the gas and aqueous phases Used to examine non-linear response of air quality to emission changes Have large input and computational requirements

  5. NOAA-EPA Air Quality Forecast Modeling System Numerical Weather Prediction Model NOAA/NWS Weather Observations EPA’s National Emissions Inventory: EPA/OAQPS AQ Module: Emissions Preprocessor NOAA/OAR +EPA/ORD Air Quality Observations AQ Module: Air Quality Reactive Transport NOAA/OAR + EPA/ORD Predicted pollutant concentrations

  6. Eta/CMAQ Test Guidance Product: Predicted Surface Ozone Concentration

  7. Estimating PM10 Emissions with Models Dust emissions from paved and unpaved roads are estimated using AP-42 formula, which depends on silt loading-unreliable Dispersion models can be used to estimate emissions by fitting model estimates to observations

  8. Measuring Emissions Wind

  9. ‘Inverse’ Modeling

  10. Results on PM10 Emission Factors

  11. Simple Models are UsefulUrban Model

  12. Results for Delhi

  13. Interpolating Observations

  14. Concluding Remarks • Need models to relate emissions to air quality • Cannot interpret ambient data without models • Emissions can be estimated using air quality data and dispersion models • Models do not have to be complex to be useful

  15. Thanks • P. Goyal, M. Sharan, M. Mohan (IIT, Delhi) • Innumerable papers on modeling by M.P. Singh, P. Goyal, M. Sharan, M. Mohan, S. K. Patil and others • World Bank Reports • BAQ Organizing Committee

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