Source identifications of airborne fine particles using positive matrix factorization and U.S. Environmental Protection Agency positive matrix factorization.
作者： Eugene Kim , Philip K. Hopke
DOI: 10.3155/1047-3289.57.7.811
关键词:
摘要: Abstract The widely used source apportionment model, positive matrix factorization (PMF2), has been applied to various air pollution data. Recently, U.S. Environmental Protection Agency (EPA) developed EPA (PMF), a version of PMF that will be freely distributed by EPA. objectives this study were conduct studies for particulate matter less than 2.5 μm in aerodynamic diameter (PM2.5) speciation data using PMF2 and (version 1.1) compare identified sources between the two models. In present study, ambient PM2.5compositional datasets 24-hr integrated samples collected at Speciation Trends Network monitoring sites Chicago, IL, Portland, OR, analyzed. Both extracted eight Chicago 10 Portland model-resolved profiles similar models both datasets. However, several sources, average contributions did not agree well and...
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