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Activity Number:
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422
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Type:
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Contributed
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Date/Time:
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Wednesday, August 5, 2009 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistics and the Environment
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| Abstract - #304161 |
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Title:
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Improving Air Quality Management Strategies for Ozone Using an Ensemble of Air Quality Model Simulations
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Author(s):
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Kristen M. Foley*+ and Robert W. Pinder and Sergey L. Napelenok
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Companies:
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U.S. Environmental Protection Agency and U.S. Environmental Protection Agency and U.S. Environmental Protection Agency
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Address:
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109 TW Alexander Drive, Research Triangle Park, NC, 27711,
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Keywords:
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ozone ; ensemble prediction ; Bayesian model averaging ; emission standards
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Abstract:
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The USEPA uses regional scale air quality models to design emission control strategies for improving ambient ozone concentrations across the US. An ensemble of model simulations is created to account for uncertainty in the deterministic modeling system. The ensemble is used to estimate the probability of exceeding a given threshold concentration under different emissions scenarios. We apply Bayesian model averaging techniques to calibrate the ensemble predictions by weighting each individual ensemble member based on how closely it matches observed ozone values. Results are shown for a period of high ozone in the Southeast. Statistical post-processing reduces prediction bias and improves the ensemble skill in predicting the probability of an exceedance.
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