Wednesday, 25 January 2017
4E (Washington State Convention Center )
Regional air quality modeling systems such as the Community Multi-Scale Air Quality (CMAQ) model driven by the Weather Research and Forecasting (WRF) meteorological model are often used to estimate ambient pollutant concentrations at high temporal and spatial resolutions. Nitrogen dioxide (NO2) and ozone (O3) in the atmosphere are air pollutants considered harmful to public health and the environment which are regulated by the U.S. Environmental Protection Agency under the Clean Air Act. Accurate prediction of pollutant concentrations is critical for the development and implementation of air quality control rules and regulations. A performance evaluation of the WRF-CMAQ modeling framework has been carried out for NO2 and O3 concentrations in 17 Western U.S. states across a two-year period (June 1997- December 1998) by comparing 12-km by 12-km grid model outputs to observational data from the EPA’s Air Quality Standard (AQS) Chemical Speciation Network (CSN). Temporal decomposition was applied in order to observe variations occurring at short-term (< 46 hours), synoptic (2.5-21 days), and long-term (> 21 days) time scales at each site. The results were analyzed in terms of type of setting—rural, suburban, and urban—as well as in terms of the dominant emissions source affecting each site. Model performance improved with length of temporal scale. Analysis of observational data shows that the variance of short-term concentrations tends to be most dominant of which the model has a difficulty reproducing. However, the model tends to perform better for synoptic and long-term scales. Further analysis has revealed there is no systematic correlation associated with site location setting and dominant source.
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