Understanding the sources and composition of the incremental excess of fine particles across multiple sampling locations in one air shed
Jerome E. McGinnis , Jongbae Heo , Michael R. Olson , Andrew P. Rutter , James J. Schauer
DOI:10.1016/S1001-0742(13)60508-2
Received June 01, 2013,Revised September 16, 2013, Accepted , Available online March 24, 2014
Volume 26,2014,Pages 818-826
Well-designed health studies and the development of effective regulatory policies need to rely on an understanding of the incremental differences in particulate matter concentrations and their sources. Although only a limited number of studies have been conducted to examine spatial differences in sources to particulate matter within an air shed, routine monitoring data can be used to better understand these differences. Measurements from the US EPA Chemical Speciation Network (CSN) collected between 2002-2008 were analyzed to demonstrate the utility of regulatory data across three sites located within 100 km of each other. Trends in concentrations, source contribution, and incremental excesses across three sites were investigated using the Positive Matrix Factorization model. Similar yearly trends in chemical composition were observed across all sites, however, excesses of organic matter and elemental carbon were observed in the urban center that originated from local emissions of mobile sources and biomass burning. Secondary sulfate and secondary nitrate constituted over half of the PM2.5 with no spatial differences observed across sites. For these components, the excess of emissions from industrial sources could be directly quantified. This study demonstrates that CSN data from multiple sites can be successfully used to derive consistent source profiles and source contributions for regional pollution, and that CSN data can be used to quantify incremental differences in source contributions of across these sites. The analysis strategy can be used in other regions of the world to take advantage of existing ambient particulate matter monitoring data to better the understanding of spatial differences in source contributions within a given air shed.
