Hu, J., H. Zhang, S. Chen, Q. Ying, Environmental Science & Technology, 48, 4980-4990, doi:10.1021/es404810z., , and M. J. Kleeman, 2014: Identifying PM2.5 and PM0.1 sources for epidemiological studies in California.
|Title:||Identifying PM2.5 and PM0.1 sources for epidemiological studies in California|
|Abstract:||The University of California-Davis_Primary (UCD_P) model was applied to simultaneously track 900 source contributions to primary particulate matter (PM) in California for seven continuous years (January 1st, 2000 to December 31st, 2006). Predicted source contributions to primary PM₂.₅ mass, PM₁.₈ elemental carbon (EC), PM₁.₈ organic carbon (OC), PM₀.₁ EC, and PM₀.₁ OC were in general agreement with the results from previous source apportionment studies using receptor-based techniques. All sources were further subjected to a constraint check based on model performance for PM trace elemental composition. A total of 151 PM₂.₅ sources and 71 PM₀.₁ sources contained PM elements that were predicted at concentrations in general agreement with measured values at nearby monitoring sites. Significant spatial heterogeneity was predicted among the 151 PM₂.₅ and 71 PM₀.₁ source concentrations, and significantly different seasonal profiles were predicted for PM₂.₅ and PM₀.₁ in central California vs southern California. Population-weighted concentrations of PM emitted from various sources calculated using the UCD_P model spatial information differed from the central monitor estimates by up to 77% for primary PM₂.₅ mass and 148% for PM₂.₅ EC because the central monitor concentration is not representative of exposure for nearby population. The results from the UCD_P model provide enhanced source apportionment information for epidemiological studies to examine the relationship between health effects and concentrations of primary PM from individual sources.|
|Copyright Information:||Copyright 2014 American Chemical Society.|
|OpenSky citable URL:||ark:/85065/d7fx7bdn|