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为加利福尼亚州的流行病学研究确定 PM2.5 和 PM0.1 的来源。

Identifying PM2.5 and PM0.1 sources for epidemiological studies in California.

机构信息

Department of Civil and Environmental Engineering, University of California-Davis , One Shields Avenue, Davis California 95616-5270, United States.

出版信息

Environ Sci Technol. 2014 May 6;48(9):4980-90. doi: 10.1021/es404810z. Epub 2014 Mar 13.

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.

摘要

加利福尼亚大学戴维斯分校-主(UCD_P)模型被应用于同时追踪加利福尼亚州近 900 个主要颗粒物(PM)源的贡献,为期七年(2000 年 1 月 1 日至 2006 年 12 月 31 日)。预测的主要 PM2.5 质量、PM1.8 元素碳(EC)、PM1.8 有机碳(OC)、PM0.1 EC 和 PM0.1 OC 的源贡献与以前使用基于受体的技术进行源分配研究的结果基本一致。所有来源都根据模型对痕量元素组成的性能进行了约束检查。共有 151 个 PM2.5 源和 71 个 PM0.1 源包含 PM 元素,这些元素的预测浓度与附近监测点的实测值基本一致。预测到 151 个 PM2.5 和 71 个 PM0.1 源浓度之间存在显著的空间异质性,与加利福尼亚州中部和南部的 PM2.5 和 PM0.1 相比,预测到明显不同的季节性分布。使用 UCD_P 模型的空间信息计算的各种来源排放的 PM 加权浓度与中心监测估计值相差高达 77%,对于主要 PM2.5 质量和 148%,对于 PM2.5 EC,因为中心监测浓度不能代表附近人口的暴露情况。UCD_P 模型的结果提供了增强的源分配信息,用于流行病学研究,以检查健康影响与个体源的主要 PM 浓度之间的关系。

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