Development of an individual exposure model for application to the Southern California children's health study

被引:38
作者
Wu, J
Lurmann, F
Winer, A
Lu, R
Turco, R
Funk, T
机构
[1] Univ Calif Los Angeles, Sch Publ Hlth, Dept Environm Hlth Sci, Los Angeles, CA 90095 USA
[2] Sonoma Technol Inc, Petaluma, CA 94954 USA
[3] Univ Calif Los Angeles, Dept Atmospher Sci, Los Angeles, CA 90095 USA
关键词
exposure model; vehicle-related pollutants; meteorologically transported pollutants; local pollutant emissions; timeactivity patterns;
D O I
10.1016/j.atmosenv.2004.09.061
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The Southern California Children's Health Study (CHS) investigated the relationship between air pollution and children's chronic respiratory health outcomes. Ambient air pollutant measurements from a single CHS monitoring station in each community were used as surrogates for personal exposures of all children in that community. To improve exposure estimates for the CHS children, we developed an Individual Exposure Model (IEM) to retrospectively estimate the long-term average exposure of the individual CHS children to CO, NO2, PM10, PM2.5, and elemental carbon (EC) of ambient origin. In the IEM, pollutant concentrations due to both local mobile source emissions (LMSE) and meteorologically transported pollutants were taken into account by combining a line source model (CALINE4) with a regional air quality model (SMOG). To avoid double counting, local mobile sources were removed from SMOG and added back by CALINE4. Limited information from the CHS survey was used to group each child into a specific time-activity category, for which corresponding Consolidated Human Activity Database (CHAD) time-activity profiles were sampled. We found local traffic significantly increased within-community variability of exposure to vehicle-related pollutants. PM-associated exposures were influenced more by meteorologically transported pollutants and local non-mobile source emissions than by LMSE. The overall within-community variability of personal exposures was highest for NO2 (+/- 20-40%), followed by EC (+/- 17-27%), PM10 (+/- 15- 25%), PM2.5 (+/- 15-20%), and CO (+/- 9-14%). Between- community exposure differences were affected by community location, traffic density, and locations of residences and schools in each community. Proper siting of air monitoring stations relative to emission sources is important to capture community mean exposures. (C) 2004 Elsevier Ltd. All rights reserved.
引用
收藏
页码:259 / 273
页数:15
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