Source apportionment of particulate matter and selected volatile organic compounds with multiple time resolution data.
Source apportionment of particulate matter and selected volatile organic compounds with multiple time resolution data.
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DOI：
10.1016/j.scitotenv.2013.11.114
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发表时间：
2014-02
期刊：
影响因子：
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通讯作者：
Cheng-Pin Kuo;H. Liao;C. Chou;Chang-Fu Wu
中科院分区：
文献类型：
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作者：
Cheng-Pin Kuo;H. Liao;C. Chou;Chang-Fu Wu
细颗粒物（PM2.5）和挥发性有机化合物（VOCs）共存于环境空气中，对人类健康造成不利影响。本研究的目的是为了证明利用包括pm2.5和VOC数据在内的多时间分辨率的复合数据集进行源分配的可行性。每小时VOC和12小时pm2.5形态数据被合并到一个改进的来源分配模型中，以量化不同污染源对pm2.5和VOC混合物的贡献。提取了车辆1、车辆2、工业加工、运输区域和二次污染源等5个因素。最大的贡献者是车辆排放的挥发性有机化合物（62%）和PM2.5（35%）。然而，相对于挥发性有机化合物（分别为8%和5%），运输区域污染源和二次污染源在PM2.5中所占的比例分别为27%和25%。额外的敏感性分析表明，排除pm2.5数据或降低相关的时间分辨率（12- 24小时）可检索到更少的源因子，并增加了源贡献估计的误差。
Fine particulate matter (PM2.5) and volatile organic compounds (VOCs) co-exist in ambient air and contribute to adverse health effects in human populations. This study was conducted to demonstrate the feasibility of utilizing a composite data set which included PM2.5and VOC data with multiple time resolutions for source apportionment. Hourly VOC and 12-h PM2.5speciation data were combined into an improved source apportionment model to quantify different pollutant source contributions to PM2.5and VOC mixtures. Five factors were retrieved, including vehicle 1, vehicle 2, industrial processing, transported regional, and secondary pollution sources. The largest contributors were vehicular emissions for VOCs (62%) and PM2.5(35%). Nonetheless, transported regional and secondary pollution sources accounted for a noteworthy portion of PM2.5(27% and 25%, respectively) relative to VOCs (8% and 5%, respectively). Additional sensitivity analyses showed that excluding the PM2.5data or reducing the associated temporal resolution (12-h to 24-h) retrieved fewer source factors and increased the errors of source contribution estimates.