Quantifying PM2.5 Source Contributions for the San Joaquin Valley with Multivariate Receptor Models
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- 作者：L.-W. Antony Chen ; John G. Watson ; Judith C. Chow ; Karen L. Magliano
- 刊名：Environmental Science & Technology
- 出版年：2007
- 出版时间：April 15, 2007
- 年：2007
- 卷：41
- 期：8
- 页码：2818 - 2826
- 全文大小：782K
- 年卷期：v.41,no.8(April 15, 2007)
- ISSN：1520-5851
文摘
UNMIX and Positive Matrix Factorization (PMF) solutionsto the Chemical Mass Balance (CMB) equations were appliedto chemically speciated PM2.5 measurements from 23sites in California's San Joaquin Valley to estimate sourcecontributions. Six and seven factors were determined byUNMIX for the low_PM2.5 period (February to October) andhigh_PM2.5 period (November to January), respectively.PMF resolved eight factors for each period that correspondedwith the UNMIX factors in chemical profiles and timeseries. These factors are attributed to marine sea salt,fugitive dust, agriculture-dairy, cooking, secondary aerosol,motor vehicle, and residential wood combustion (RWC)emissions, with secondary aerosol and RWC accountingfor over 70% of PM2.5 mass during the high_PM2.5 period. Azinc factor was only resolved by PMF. The contributionfrom motor vehicles was between 10 and 25% with higherpercentages occurring in summer. The PMF model wasfurther evaluated by examining (1) site-specific residualsbetween the measured and calculated concentrations, (2)comparability of motor vehicle and RWC factors againstsource profiles obtained from recent emission tests, (3) edgesin bi-plots of key indicator species, and (4) spatiotemporalvariations of the factors' strengths. These evaluationssupport the compliance with model assumptions and givea higher confidence level to source apportionmentresults for the high_PM2.5 period.