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USING CMAQ FOR EXPOSURE MODELING AND CHARACTERIZING THE SUB-GRID VARIABILITY FOR EXPOSURE ESTIMATES
Citation:
ISAKOV, V., J. IRWIN, AND J. K. CHING. USING CMAQ FOR EXPOSURE MODELING AND CHARACTERIZING THE SUB-GRID VARIABILITY FOR EXPOSURE ESTIMATES. JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY. American Meteorological Society, Boston, MA, 46(9):1354-1371, (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.
"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:
Atmospheric processes and the associated transport and dispersion of atmospheric pollutants are known to be highly variable in time and space. Current air quality models that characterize atmospheric chemistry effects, e.g. the Community Multi-scale Air Quality (CMAQ), provide volume-average concentration values for each grid cell in the modeling domain given stated conditions. Given the assumptions made and the limited set of processes included in any model's implementation, there are many sources of "uresolved" sub-grid variability. This raises the question of the importance of the "unresolved" sub-grid variations on exposure assessment results if such models were to be used to assess air toxic exposures. In this study, we applied the Hazardous Air Pollutant Exposure Model (HAPEM) to estimate benzene and formaldehyde inhalation exposures using ambient annual average concentrations predicted by CMAQ to investigate how within-grid variability can affect exposure estimates. An urban plume dispersion model was used to estimate the sub-grid variability of annual average benzene concentration values within CMAQ grid cells for a modeling domain centered on Philadelphia, PA. Significant (greater than a factor of two) increases in maximum exposure impacts were seen in the exposure estimates in comparison to exposure estimates generating using CMAQ grid-average concentration values. These results consider only one source of sub-grid variability, namely the discrete location and distribution of emissions, but they do suggest the importance and value of developing improved characterizations of sub-grid concentration variability for use in air toxic exposure assessments.