Record Display for the EPA National Library Catalog


Main Title Eight-Site Source Apportionment of PM2.5 Speciation Trends Data.
Author B. W. Coutant ; C. H. Holloman ; K. E. Swinton ; H. R. Hafner
CORP Author Battelle Memorial Inst., Columbus, OH.; Sonoma Technology, Inc., Petaluma, CA.; Environmental Protection Agency, Research Triangle Park, NC. Office of Air Quality Planning and Standards.
Year Published 2003
Report Number 68-D-02-061
Stock Number PB2012-102082
Additional Subjects Air pollution standards ; Air quality ; Particulates ; Air sampling ; Procedures ; Sources ; Meteorological data ; Tables (Data) ; Figures ; Urban areas ; Particle size ; Air pollution control ; Source apportionment ; Back trajectory ; Source apportionment analysis ; Back trajectory analysis
Library Call Number Additional Info Location Last
NTIS  PB2012-102082 Some EPA libraries have a fiche copy filed under the call number shown. 07/26/2022
Collation 394p
This source apportionment and back trajectory study analyzes speciated PM2.5 data from eight of Environmental Protection Agency's (EPA's) Trends Sites located in Birmingham, Alabama; Bronx, New York; Charlotte, North Carolina; Houston, Texas; Indianapolis, Indiana; Milwaukee, Wisconsin; St. Louis, Missouri; and Washington, D.C. Unlike previous studies of IMPROVE and CASTNET data, these sites are in urban areas that are expected to include strong local effects as well as effects from long-range transport. The results of both the source apportionment and back trajectory analyses are consistent with this expectation. This report covers the results and methods used to apportion the data into the major sources of the PM2.5. It also covers the methods used to identify those sources on the basis of the apportioned chemical characteristics. The methods applied are somewhat different from the methods used in previous source apportionment work of IMPROVE and CASTNET sites. The screening criteria used were much less stringent to allow more data to be used, since the data cover a significantly shorter time period. At the same time, the model fitting criteria were more stringent to protect against inappropriate model results. One important consequence of the differences in the methods is that the methods used here identify relatively infrequent sources, such as fireworks, while the data screening frequently used in source apportionment studies are in part designed to exclude those sources. The development of the back trajectories is documented and slightly extends the methods developed in previous studies. The extra step in the analysis of the back trajectories ensures that the scales are comparable across sites. Analyses of the source strengths with respect to various meteorological data are also included as a part of developing an understanding of the sources.