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The Role of Models in Air Quality Management
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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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Types of models applications case studies estimating emissions conclusions

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

Air quality models

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



  • 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

Applications of comprehensive models

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

Noaa epa air quality forecast modeling system

NOAA-EPA Air Quality Forecast Modeling System

Numerical Weather

Prediction Model




EPA’s National

Emissions Inventory:


AQ Module:

Emissions Preprocessor


Air Quality


AQ Module:

Air Quality Reactive Transport


Predicted pollutant concentrations

Eta cmaq test guidance product predicted surface ozone concentration

Eta/CMAQ Test Guidance Product: Predicted Surface Ozone Concentration

Estimating pm 10 emissions with models

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

Measuring emissions

Measuring Emissions


Inverse modeling

‘Inverse’ Modeling

Results on pm 10 emission factors

Results on PM10 Emission Factors

Simple models are useful urban model

Simple Models are UsefulUrban Model

Results for delhi

Results for Delhi

Interpolating observations

Interpolating Observations

Concluding remarks

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



  • 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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