Identifying PM2.5 and PM0.1 Sources for Epidemiological Studies in California

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• 作者：Jianlin Hu ; Hongliang Zhang ; Shuhua Chen ; Qi Ying ; Christine Wiedinmyer ; Francois Vandenberghe ; Michael J. Kleeman
• 刊名：Environmental Science & Technology
• 出版年：2014
• 出版时间：May 6, 2014
• 年：2014
• 卷：48
• 期：9
• 页码：4980-4990
• 全文大小：840K
• 年卷期：v.48,no.9(May 6, 2014)
• ISSN：1520-5851

文摘

The University of California鈥擠avis_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 PM_2.5 mass, PM_1.8 elemental carbon (EC), PM_1.8 organic carbon (OC), PM_0.1 EC, and PM_0.1 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 PM_2.5 sources and 71 PM_0.1 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 PM_2.5 and 71 PM_0.1 source concentrations, and significantly different seasonal profiles were predicted for PM_2.5 and PM_0.1 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 PM_2.5 mass and 148% for PM_2.5 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.