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Regional Modeling

Regional Modeling. Joseph Cassmassi South Coast Air Quality Management District USA. Regional Modeling Applications. Determine a “carrying capacity” for a region Provides a view of current, past and future air quality Planning tool to develop a long term control strategy.

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Regional Modeling

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  1. Regional Modeling Joseph Cassmassi South Coast Air Quality Management District USA

  2. Regional Modeling Applications • Determine a “carrying capacity” for a region • Provides a view of current, past and future air quality • Planning tool to develop a long term control strategy

  3. Expectations vs. Limitations • Performance of regional models is as good as the worst component • In data rich environments modeling errors range between 15-50% • Requires a significant investment -- data -- man hours -- computation resources

  4. Modeling Overview • Goal or purpose • Conceptual model • Model selection • Define modeling domain • Emissions inventory • Air quality and meteorological data • Define an episode for model application

  5. Conceptual Model • Understanding of the overall picture -- extent of data availability -- confidence in the data -- processes that are contributing to the observed air quality • Meteorological and air quality description of the episode • Understanding of why the episode stands apart from normal or average conditions

  6. Model Selection • Air quality -- platform (dedicated or family) -- chemistry module -- dispersion • Meteorological -- objective analysis -- diagnostic analysis -- prognostic models

  7. Modeling Domain • Regional approach -- focus on Delhi? -- up and down wind areas (from the conceptual model) • Meteorological modeling domain may be greater than the air quality domain • Grid scales may be different • Need accurate terrain file

  8. General Data Requirements • Data required is domain dependent -- size -- complexity of terrain -- pollutant sensitive • Levels of model applications -- limited surface and upper air -- moderately dense surface and multiple upper air -- intensive field study

  9. Air Quality Data Requirements • Surface -- routine air quality monitoring -- chemical speciation ` -- define boundaries/initialization • Upper air -- boundaries/initialization -- transport

  10. Meteorological Data Requirements • Surface -- winds, temperature, humidity -- insolation and cloud cover • Upper Air -- winds, temperature, moisture -- lapse rates and stability -- mixing heights

  11. Southern California Monitoring • Air Quality Monitoring -- 75+ ambient monitoring sites -- 10+ sites speciated data -- upper air characterization - as needed • Meteorology -- 125+ monitoring or reporting sites -- 5 sounding/aircraft sites -- 10 radar profilers/sounders

  12. Delhi Monitoring • ~ 6-10 air monitoring sites -- fixed & mobile vans -- representative of high traffic areas -- limited speciation • Surface meteorological at air monitoring locations • Twice daily soundings: Delhi, Gwalior, Jodhpur

  13. Emissions • Gridded emissions inventory -- point -- mobile -- area • Day specific • Allocation factor/surrogates • Temporal profile • Weekdays vs. weekends

  14. Applications: Episode Selection • Data Availability -- meteorology -- air quality -- boundary conditions • Episode severity • Representative of problem • Field study data available

  15. Delhi Profile • Reasonably flat terrain • Upper air -- limited upper air meteorology may characterize domain • Surface meteorology -- river valleys will channel winds -- urban heat island -- Great Indian Desert -- need additional monitoring

  16. Delhi Profile (continued) • Ambient air quality monitoring -- may not characterize regional issue -- need to characterize background profile -- identify locations of maximum pollution impact

  17. Recommendations • Meteorology -- enhance surface network -- consider upper air profiling • Air quality -- enhance network -- speciation profiles -- characterize boundaries • Investigate potential for field study -- PM - fall, Ozone - late spring

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