Source identification of personal exposure to fine particulate matter using organic tracers

被引:26
|
作者
Brinkman, Gregory L. [1 ]
Milford, Jana B. [1 ]
Schauer, James J. [2 ,3 ]
Shafer, Martin M. [2 ,3 ]
Hannigan, Michael P. [1 ]
机构
[1] Univ Colorado, Dept Mech Engn, Boulder, CO 80309 USA
[2] Univ Wisconsin, Wisconsin State Lab Hyg, Madison, WI 53706 USA
[3] Univ Wisconsin, Environm Chem & Technol Program, Madison, WI 53706 USA
关键词
Personal exposure; Fine particulate matter; Principal component analysis; Source apportionment; Organic tracers; AIR-POLLUTION SOURCES; SOURCE APPORTIONMENT; ELEMENTAL COMPOSITION; EMISSIONS; PM2.5; PARTICLES; OUTDOOR; AEROSOL; BALTIMORE; AMBIENT;
D O I
10.1016/j.atmosenv.2009.01.023
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Personal exposure to fine particulate matter (PM2.5) is due to both indoor and outdoor sources. Contributions of sources to personal exposure can be quite different from those observed at ambient sampling locations. The primary goal of this study was to investigate the effectiveness of using trace organic speciation data to help identify sources influencing PM2.5 exposure concentrations. Sixty-four 24-h PM2.5 samples were obtained on seven different subjects in and around Boulder, CO. The exposure samples were analyzed for PM2.5 mass, elemental and organic carbon, organic tracer compounds, water-soluble metals, ammonia, and nitrate. This study is the first to measure a broad distribution of organic tracer compounds in PM2.5 personal samples. PM2.5 mass exposure concentrations averaged 8.4 mu g m(-3). Organic carbon was the dominant constituent of the PM2.5 mass. Forty-four organic species and 19 water-soluble metals were quantifiable in more than half of the samples. Fifty-four organic species and 16 water-soluble metals had measurement signal-to-noise ratios larger than two after blank subtraction. The dataset was analyzed by Principal Component Analysis (PCA) to determine the factors that account for the greatest variance. Eight significant factors were identified: each factor was matched to its likely source based primarily on the marker species that loaded the factor. The results were consistent with the expectation that multiple marker species for the same source loaded the same factor. Meat cooking was an important source of variability. The factor that represents meat cooking was highly correlated with organic carbon concentrations (r = 0.84). The correlation between ambient PM2.5 and PM2.5 exposure was relatively weak (r = 0.15). Time participants spent performing various activities was generally not well correlated with PCA factor scores, likely because activity duration does not measure emissions intensity. The PCA results demonstrate that organic tracers can aid in identifying factors that influence personal exposures to PM2.5. (c) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1972 / 1981
页数:10
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