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A STATISTICAL APPROACH FOR ESTIMATING UNCERTAINTY IN DISPERSION MODELING: AN EXAMPLE OF APPLICATION IN THE SOUTHWESTERN U.S.
Citation:
KORACIN, D., A. PANORSKA, V. ISAKOV, J. S. TOUMA, AND J. SWALL. A STATISTICAL APPROACH FOR ESTIMATING UNCERTAINTY IN DISPERSION MODELING: AN EXAMPLE OF APPLICATION IN THE SOUTHWESTERN U.S. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, 41(3):617-628, (2007).
Impact/Purpose:
The objective of this task is to improve EPA's ability to accurately predict the concentrations and deposition of air pollutants in the atmosphere that are known or suspected to cause cancer or other serious health effects to humans, or adverse environmental effects. It is an essential component of EPA's National Air Toxics Assessment (NATA), which seeks to identify and quantify the concentrations and sources of those hazardous air pollutants which are of greatest potential concern, in terms of contribution to population risk. It is a major contributor to NERL's Air Toxics Research Program.
Description:
This paper presents a new method based on a statistical approach of estimating the uncertainty in simulating the transport and dispersion of atmospheric pollutants. The application of the method has been demonstrated by using observations and modeling results from a tracer experiment in the complex terrain of the southwestern US.