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A PRELIMINARY EVALUATION OF MODELS-3 CMAQ USING PARTICULATE MATTER DATA FROM THE IMPROVE NETWORK
Citation:
Eder, B K., M R. Mebust, AND S K. LeDuc. A PRELIMINARY EVALUATION OF MODELS-3 CMAQ USING PARTICULATE MATTER DATA FROM THE IMPROVE NETWORK. Presented at 25th NATO/CCMS International Technical Meeting on Air Pollution Modeling and Its Application, Louvain-la-Neuve, Belgium, October 15-19, 2001.
Impact/Purpose:
The goal of this task is to thoroughly characterize the performance of the emissions, meteorological and chemical/transport modeling components of the Models-3 system, with an emphasis on the chemical/transport model, CMAQ. Emissions-based models are composed of highly complex scientific hypotheses concerning natural processes that can be evaluated through comparison with observations, but not validated. Both performance and diagnostic evaluation together with sensitivity analyses are needed to establish credibility and build confidence within the client and scientific community in the simulations results for policy and scientific applications. The characterization of the performance of Models-3/CMAQ is also a tool for the model developers to identify aspects of the modeling system that require further improvement.
Description:
The Clean Air Act and its Amendments require the United States Environmental Protection Agency (EPA) to establish National Ambient Air Quality Standards for Particulate Matter (PM) and to assess current and future air quality regulations designed to protect human health and welfare. Air quality models, such as EPA's Models-3 Community Multiscale Air Quality model (CMAQ) [Byun and Ching, 1999], provide one of the most reliable tools for performing such assessments. CMAQ simulates air concentrations and deposition of various pollutants including PM. These simulations, which can be conducted on a myriad of spatial and temporal scales, support both regulatory assessment as well as scientific studies by research institutions. Within CMAQ is an aerosol component, or module, designed to simulate the complex processes involving PM, which is commonly separated into PM2.5 and PM10. In order to determine its value to the air quality regulatory communities, CMAQ needs to be evaluated using observational data. One such evaluation, which compared visibility parameters derived from CMAQ to visibility parameters obtained from National Weather Service observations, revealed that CMAQ was able to replicate general spatial and temporal patterns [Eder et al., 2000]. The current evaluation compares PM simulated by CMAQ with PM data collected by the Interagency Monitoring of PROtected Visual Environments (IMPROVE) network.