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IMPROVEMENTS IN EMISSIONS INVENTORIES USING SEMI-CONTINUOUS MONITORING DATA AND CONCENTRATIONS FIELD ANALYSIS
Impact/Purpose:
The goal of this project is to couple high-resolution meteorological modeling with existing high time resolution atmospheric pollutant data sets to assess and improve emissions inventories.
Description:
This project will focus on a three city study using yearlong datasets from St. Louis, Milwaukee, and Los Angeles. Emissions inventory data will be evaluated and improved for fine particle elemental carbon, ultrafine particle number concentrations and fine particle organic carbon using data from the EPA funded St. Louis Supersite; speciated mercury compounds in the Milwaukee region using data from an EPA STAR Project; and fine particle carbonaceous particulate matter and associated precursor gases in Los Angeles. Concentration Field Analysis (CFA) will be used to map emissions sources and identify unknown or poorly identified source regions using stochastic backward and forward particle trajectories with a temporal resolution finer than one hour and spatial resolution finer than 5 km during the yearlong study periods. The integration of high quality monitoring data with multiple 3D modeling approaches will assess existing emissions inventories and improve the understanding and representation of the temporal distribution of emissions, spatial distributions of emissions, missing sources, and inaccurate emissions estimates for point sources, mobile sources and area sources.