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首页> 外文期刊>The Science of the Total Environment >Simultaneous monitoring and compositions analysis of PM_1 and PM_(2.5) in Shanghai: Implications for characterization of haze pollution and source apportionment
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Simultaneous monitoring and compositions analysis of PM_1 and PM_(2.5) in Shanghai: Implications for characterization of haze pollution and source apportionment

机译:上海市PM_1和PM_(2.5)的同时监测和成分分析:雾霾污染特征和源头分配的意义

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摘要

A year-long simultaneous observation of PM_1 and PM_(2.5) were conducted at ECUST campus in Shanghai, the compositions were analyzed and compared. Results showed that PM_(2.5) was dominated by PM_1 on clear days while the contribution of PM_(1-2.5) to PM_(2.5) increased on haze days, indicating that PM_(2.5) 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 PM_(1-2.5) was faster than that in PM_1. Humic-like substances carbon (Hulis-C) in both PM_(2.5) and PM, 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, NO_3~-/SO_4~(2-) in PM_1 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 PM_1 and PM_(2.5) 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 PM_1. By comparison with multi-linear equations of LWC in PM_1 and PM_(2.5). NO_3~- exerted a higher influence on hygroscopicity of PM_1 than PM_(2.5), while RH, WSOC, SO_4~(2-) and NH_4~+ had higher effects on PM_(2.5), especially WSOC. Source apportionment of PM_(2.5) was also investigated to provide reference for policy making. Cluster analysis by HYSPLIT (HYbrid Single Particle Lagrangian Integrated Trajectory) model showed that PM_(2.5) originated from marine aerosols, middle-scale transportation and large-scale transportation. Furthermore, PM_(2.5) on haze days was dominated by middle-scale transportation. In line with source apportionment by positive matrix factorization (PMF) model, PM_(2.5) was attributed to secondary inorganics, aged sea salt, combustion emissions, hygroscopic growth and secondary organics. Secondary formation was the principle source of PM_(2.5). Furthermore, the contribution of combustion emissions to PM_(2.5) 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.
机译:在上海ECUST校区进行了为期一年的同时对PM_1和PM_(2.5)的观测,并对成分进行了分析和比较。结果表明,雾天PM_(2.5)以PM_1为主,而雾霾天PM_(1-2.5)对PM_(2.5)的贡献增加,表明PM_(2.5)应优先表征或预测雾霾污染。在雾霾天,PM_(1-2.5)中有机碳(OC),元素碳(EC)和一次有机碳(POC)的积累要快于PM_1。 PM_(2.5)和PM中的类腐殖质碳(Hulis-C)在阴霾天比水溶性有机碳(WSOC)形成更快,因此,随着阴霾污染的加剧,Hulis-C / WSOC升高。就水溶性离子而言,PM_1中的NO_3〜-/ SO_4〜(2-)随着雾霾污染的加剧而增加,这意味着在雾霾天中移动源占主导地位,氮氧化率(NOR)也占主导地位。 PM_1和PM_(2.5)中的液态水含量(LWC)与相对湿度(RH)呈正相关,而与可见度则呈负相关,这意味着吸湿性增长可能是可见度受损的一个因素,尤其是PM_1中的LWC。通过与PM_1和PM_(2.5)中LWC的多线性方程进行比较。 NO_3〜-对PM_1的吸湿性的影响要大于PM_(2.5),而RH,WSOC,SO_4〜(2-)和NH_4〜+对PM_1(2.5)的影响更大,尤其是WSOC。还研究了PM_(2.5)的来源分配,为政策制定提供参考。利用HYSPLIT(混合单粒子拉格朗日综合轨迹)模型进行的聚类分析表明,PM_(2.5)来源于海洋气溶胶,中等规模的运输和大规模的运输。此外,雾霾天的PM_(2.5)以中等规模的运输为主。与通过正矩阵分解(PMF)模型进行源分配相一致,PM_(2.5)归因于次生无机物,老化的海盐,燃烧排放,吸湿性增长和次生有机物。次生形成是PM_(2.5)的主要来源。此外,随着雾霾污染的加剧,燃烧排放对PM_(2.5)的贡献增加,这与吸湿性增长正好相反,而次生地层在晴天和雾霾日保持稳定。

著录项

  • 来源
    《The Science of the Total Environment》 |2016年第1期|386-394|共9页
  • 作者单位

    State Environmental Protection Key Laboratory of Risk Assessment and Control on Chemical Processes, School of Resources & Environmental Engineering, East China University of Science and Technology (ECUST), Shanghai 200237, China,The People's Government of Dong Ping Town, Chongming County, Shanghai Municipality, China;

    State Environmental Protection Key Laboratory of Risk Assessment and Control on Chemical Processes, School of Resources & Environmental Engineering, East China University of Science and Technology (ECUST), Shanghai 200237, China;

    State Environmental Protection Key Laboratory of Risk Assessment and Control on Chemical Processes, School of Resources & Environmental Engineering, East China University of Science and Technology (ECUST), Shanghai 200237, China,Australia-China Centre for Air Quality Science and Management (ACC-AQSM), China;

    Department of Chemistry, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    PM_1; PM_(2.5); Humic like substances (Hulis); Liquid water content (LWC); Haze pollution; Source apportionment;

    机译:PM_1;PM_(2.5);腐殖质类物质(Hulis);液态水含量(LWC);霾污染;源分配;

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