Simultaneous monitoring and compositions analysis of PM1 and PM2.5 in Shanghai: Implications for characterization of haze pollution and source apportionment
Simultaneous monitoring and compositions analysis of PM1 and PM2.5 in Shanghai: Implications for characterization of haze pollution and source apportionment
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上海PM1和PM2.5同步监测及成分分析：对雾霾污染表征及来源解析的启示
DOI：
10.1016/j.scitotenv.2016.03.095
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发表时间：
2016-07-01
影响因子：
9.8
通讯作者：
Yu, Jianzhen
中科院分区：
文献类型：
--
作者：
Qiao, Ting;Zhao, Mengfei;Yu, Jianzhen
对华东理工大学上海校区的PM 1和PM2.5进行了为期一年的同步观测，并对PM 1和PM2.5的组成进行了分析比较。结果表明，晴天PM2. 5以PM 1为主，而灰霾天PM 1 - 2. 5对PM2. 5的贡献增大，说明应优先考虑PM2. 5来表征或预测灰霾污染。在灰霾天，PM 1 -2.5中有机碳（OC）、元素碳（EC）和初级有机碳（POC）的积累速度均快于PM 1。灰霾天PM2. 5和PM 1中类胡敏素碳（Hulis-C）的形成速度快于水溶性有机碳（WSOC），因此Hulis-C/WSOC随灰霾污染的加剧而增大。在水溶性离子方面，PM 1中NO3-/SO 42-随灰霾污染的加重而增加，说明灰霾日以移动的污染源为主，氮氧化率（NOR）也随灰霾日增加而增加。PM 1和PM2. 5中的液态水含量与相对湿度（RH）呈正相关，与能见度呈负相关，说明吸湿增长可能是能见度降低的一个因素，尤其是PM 1中的液态水含量。通过对PM 1和PM2.5中LWC多元线性方程的比较发现，NO3-对PM 1吸湿性的影响大于PM2.5，而RH、WSOC、SO 42-和NH 4+对PM2.5的影响较大，尤其是WSOC。并对PM2.5的源解析进行了研究，为政策制定提供参考。利用HYSPLIT（HYbrid Single Particle Lagrangian Integrated Trajectory）模型对PM2. 5进行聚类分析，结果表明PM2. 5来源于海洋气溶胶、中尺度输送和大尺度输送。灰霾日PM2.5以中等尺度输送为主。根据PMF模型的源解析结果，PM2.5主要由次生无机物、老化海盐、燃烧排放、吸湿生长和次生有机物组成。二次形成是PM2.5的主要来源。燃烧排放对PM2. 5的贡献随灰霾污染的加剧而增加，与吸湿增长相反，而二次生成对PM2. 5的贡献在晴天和灰霾天基本保持稳定。(C)2016由Elsevier B. V.出版
A year-long simultaneous observation of PM1 and PM2.5 were conducted at ECUST campus in Shanghai, the compositions were analyzed and compared. Results showed that PM2.5 was dominated by PM1 on clear days while the contribution of PM1-2.5 to PM2.5 increased on haze days, indicating that PM2.5 should be given priority to characterize or predict haze pollution. On haze days, accumulation of organic carbon (OC), elemental carbon (EC) and primary organic carbon (POC) in PM1-2.5 was faster than that in PM1. Humic-like substances carbon (Hulis-C) in both PM2.5 and PM1 formed faster than water soluble organic carbon (WSOC) on haze days, hence Hulis-C/WSOC increased with the intensification of haze pollution. In terms of water soluble ions, NO3-/SO42- in PM1 increased with the aggravation of haze pollution, implying that mobile sources dominated on haze days, so is nitrogen oxidation ratio (NOR). Liquid water content (LWC) in both PM1 and PM2.5 had positive correlations with relative humidity (RH) but negative correlations with visibility, implying that hygroscopic growth might be a factor for visibility impairment, especially LWC in PM1. By comparison with multi-linear equations of LWC in PM1 and PM2.5, NO3- exerted a higher influence on hygroscopicity of PM1 than PM2.5, while RH, WSOC, SO42- and NH4+ had higher effects on PM2.5, especially WSOC. Source apportionment of PM2.5 was also investigated to provide reference for policy making. Cluster analysis by HYSPLIT (HYbrid Single Particle Lagrangian Integrated Trajectory) model showed that PM2.5 originated from marine aerosols, middle-scale transportation and large-scale transportation. Furthermore, PM2.5 on haze days was dominated by middle-scale transportation. In line with source apportionment by positive matrix factorization (PMF) model, PM2.5 was attributed to secondary inorganics, aged sea salt, combustion emissions, hygroscopic growth and secondary organics. Secondary formation was the principle source of PM2.5. Furthermore, the contribution of combustion emissions to PM2.5 increased with the intensification of haze pollution, which was just opposite to hygroscopic growth, while that of secondary formation kept quite stable on clear days and haze days. (C) 2016 Published by Elsevier B.V.