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RESOLVING NEIGHBORHOOD-SCALE AIR TOXICS MODELING: A CASE STUDY IN WILMINGTON, CALIFORNIA
Citation:
ISAKOV, V. AND A. VENKATRAM. RESOLVING NEIGHBORHOOD-SCALE AIR TOXICS MODELING: A CASE STUDY IN WILMINGTON, CALIFORNIA. JOURNAL OF AIR AND WASTE MANAGEMENT. Air & Waste Management Association, Pittsburgh, PA, 56(5):559-568, (2006).
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.
"Air toxics" or "hazardous air pollutants" (HAPs) is a category that covers a large variety of chemicals, which range from relatively non reactive to extremely reactive; can exist in the gas, aqueous, and/or particle phases; display a large range of volatilities; experience varying deposition velocities, including in some cases revolatilization; and are emitted from a wide variety of sources at a large variety of different scales. In addition, concentrations of air toxics are needed by regulators for both short (days) as well as long (up to a year) time scales. These requirements challenge our current capabilities in air quality models far beyond the needs for other pollutants, such as ozone. The specific work being done under this task involves 1.) developing and testing chemical mechanisms which are appropriate for describing the chemistry of air toxics; 2.) incorporating these chemical and physical mechanisms into EPA's CMAQ modeling system and applying the model at a variety of scales; and 3.) developing the methods for using models to predict HAPs concentrations at subgrid or neighborhood scales; and 4.) using these tools to assess the magnitude and variability of concentrations to which urban populations are exposed.
Description:
Air quality modeling is useful for characterizing exposures to air pollutants. While models typically provide results on regional scales, there is a need for refined modeling approaches capable of resolving concentrations on the scale of tens of meters, across modeling domains 10-100 km2 in size. One approach for refined air quality modeling is to combine Gaussian and regional photochemical grid models. In this paper we demonstrate this approach on a case study of Wilmington, California, focused on diesel exhaust particulate matter. Modeling results suggest pollutant concentrations in the vicinity of emission sources are elevated and therefore an understanding of local emission sources is necessary to generate credible modeling results. A probabilistic evaluation of the Gaussian model application indicated that spatial allocation, emission rates, and meteorological data are important contributors to input and parameter uncertainty in the model results. This uncertainty can be substantially reduced through the collection and integration of site specific information about the location of emission sources, and the activity and emission rates of key sources affecting model concentrations.