Demonstrating attainment of the air quality standards: integration of observations and model predictions into the probabilistic framework.
This paper introduces an integrated observational-modeling approach to transform the deterministic nature of attainment demonstrations of the National Ambient Air Quality Standard (NAAQS) into the probabilistic framework. While the methods presented here can be used to address any air quality standard that is based on extreme values, this paper focuses on the application to the 1-hr and 8-hr NAAQS for ozone. Extreme value statistics and resampling techniques are applied to estimate the probability of exceeding the NAAQS for both 1-hr and 8-hr ozone concentrations. Within the integrated observation-modeling analysis approach, we show that the model-to-model differences in the predicted responses to emission reductions are smaller than the model-to-model differences in predicted absolute ozone concentrations. We illustrate that the emission reductions stemming from a real-world emission control strategy would substantially reduce the probability of exceeding the NAAQS over a large portion of the eastern United States, especially for the 8-hr average ozone concentrations.
Hogrefe
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Department of Earth and Atmospheric Sciences, University at Albany, State University of New York, Albany, USA.
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D000397:Air Pollution / Q000517:prevention & control*; D003657:Decision Making; D005544:Forecasting; D015233:Models, Statistical; D010083:Oxidants, Photochemical / Q000302:isolation & purification*; D010126:Ozone / Q000302:isolation & purification*; D011786:Quality Control; D015203:Reproducibility of Results; D014481:United States
D010083:Oxidants, Photochemical; D010126:Ozone