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首页> 外文期刊>Environmental Pollution >Seasonal characteristics of aerosols (PM_(2.5) and PM_(10)) and their source apportionment using PMF: A four year study over Delhi, India
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Seasonal characteristics of aerosols (PM_(2.5) and PM_(10)) and their source apportionment using PMF: A four year study over Delhi, India

机译:气溶胶的季节性特征(PM_(2.5)和PM_(10))及其使用PMF分配的源分配:印度德里的四年研究

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摘要

The present study attempts to explore and compare the seasonal variability in chemical composition and contributions of different sources of fine and coarse fractions of aerosols (PM2.5 and PM10) in Delhi, India from January 2013 to December 2016. The annual average concentrations of PM2.5 and PM10 were 131 +/- 79 mg m(-3) (range: 17-417 mu g m(-3)) and 238 +/- 106 mu g m(-3) (range: 34-537 mu g m(-3)), respectively. PM2.5 and PM10 samples were chemically characterized to assess their chemical components [i.e. organic carbon (OC), elemental carbon (EC), water soluble inorganic ionic components (WSICs) and heavy and trace elements] and then used for estimation of enrichment factors (EFs) and applied positive matrix factorization (PMF5) model to evaluate their prominent sources on seasonal basis in Delhi. PMF identified eight major sources i.e. Secondary nitrate (SN), secondary sulphate (SS), vehicular emissions (VE), biomass burning (BB), soil dust (SD), fossil fuel combustion (FFC), sodium and magnesium salts (SMS) and industrial emissions (IE). Total carbon contributes similar to 28% to the total PM2.5 concentration and 24% to the total PM10 concentration and followed the similar seasonality pattern. SN and SS followed opposite seasonal pattern, where SN was higher during colder seasons while SS was greater during warm seasons. The seasonal differences in VE contributions were not very striking as it prevails evidently most of year. Emissions from BB is one of the major sources in Delhi with larger contribution during winter and post monsoon seasons due to stable meteorological conditions and aggrandized biomass burning (agriculture residue burning in and around the regions; mainly Punjab and Haryana) and domestic heating during the season. Conditional Bivariate Probability Function (CBPF) plots revealed that the maximum concentrations of PM2.5 and PM10 were carried by north westerly winds (north-western Indo Gangetic Plains of India). (C) 2020 Elsevier Ltd. All rights reserved.
机译:本研究试图从2013年1月到2016年1月到2016年1月,探索和比较德里德里德里艾德利的淡化和粗源源细分源和贡献的季节性变异和贡献。年度平均浓度的PM2 .5和PM10为131 +/- 79 mg m(-3)(范围:17-417 mm(-3))和238 +/- 106 mm gm(-3)(范围:34-537 mm gm( -3))分别。 PM2.5和PM10样品化学表征以评估其化学成分[即有机碳(OC),元素碳(EC),水溶性无机离子组分(WSIC)和重和痕量元素],然后用于估计富集因子(EF)和应用阳性基质分子(PMF5)模型来评估它们的突出德里季节性基础上的来源。 PMF确定了八个主要来源,即次级硝酸盐(Sn),仲硫酸盐(SS),车辆排放(BB),土壤粉尘(SD),化石燃料燃烧(FFC),钠和镁盐(SMS)和工业排放(即)。总碳含量与总PM2.5浓度的总碳含量相似,总PM10浓度为24%,然后遵循类似的季节性模式。 SN和SS遵循对面的季节性图案,在较冷的季节,SN更高,而SS在温暖的季节较大。由于大多数年度,VE贡献的季节性差异并不是惊人。 BB的排放是德里的主要来源之一,冬季贡献更大,季风季节由于稳定的气象条件和刺激生物量燃烧(农业残留物在地区燃烧;主要是Punjab和Haryana)和季节的家用加热。条件双变量概率函数(CBPF)地图显示,最大浓度的PM2.5和PM10由North Westerly Winds(印度西北部南北古玩)携带。 (c)2020 elestvier有限公司保留所有权利。

著录项

  • 来源
    《Environmental Pollution》 |2020年第7期|114337.1-114337.14|共14页
  • 作者单位

    Natl Phys Lab CSIR Dr KS Krishnan Rd New Delhi 110012 India|Acad Sci & Innovat Res AcSIR Ghaziabad 201002 India;

    Natl Phys Lab CSIR Dr KS Krishnan Rd New Delhi 110012 India|Acad Sci & Innovat Res AcSIR Ghaziabad 201002 India;

    Natl Phys Lab CSIR Dr KS Krishnan Rd New Delhi 110012 India;

    Natl Phys Lab CSIR Dr KS Krishnan Rd New Delhi 110012 India|Acad Sci & Innovat Res AcSIR Ghaziabad 201002 India;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    PM10; PM2.5; Chemical components; Seasonal variability; Source apportionment;

    机译:PM10;PM2.5;化学成分;季节性变异性;来源分配;

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