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Source apportionment of PM2.5 in North India using source-oriented air quality models

机译：使用面向污染源的空气质量模型，对印度北部PM2.5进行污染源分配

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摘要

In recent years, severe pollution events were observed frequently in India especially at its capital, New Delhi. However, limited studies have been conducted to understand the sources to high pollutant concentrations for designing effective control strategies. In this work, source-oriented versions of the Community Multi-scale Air Quality (CMAQ) model with Emissions Database for Global Atmospheric Research (EDGAR) were applied to quantify the contributions of eight source types (energy, industry, residential, on-road, off-road, agriculture, open burning and dust) to fine particulate matter (PM2.5) and its components including primary PM (PPM) and secondary inorganic aerosol (SIA) i.e. sulfate, nitrate and ammonium ions, in Delhi and three surrounding cities, Chandigarh, Lucknow and Jaipur in 2015. PPM mass is dominated by industry and residential activities (>60%). Energy (similar to 39%) and industry (similar to 45%) sectors contribute significantly to PPM at south of Delhi, which reach a maximum of 200 mu g/m(3) during winter. Unlike PPM, SIA concentrations from different sources are more heterogeneous. High SIA concentrations (similar to 25 mu g/m(3)) at south Delhi and central Uttar Pradesh were mainly attributed to energy, industry and residential sectors. Agriculture is more important for SIA than PPM and contributions of on road and open burning to SIA are also higher than to PPM. Residential sector contributes highest to total PM2.5 (similar to 80 mu g/m(3)), followed by industry (similar to 70 mu g/m(3)) in North India. Energy and agriculture contribute similar to 25 mu g/m(3) and similar to 16 mu g/m(3) to total PM2.5, while SOA contributes <5 mu g/m(3). In Delhi, industry and residential activities contribute to 80% of total PM2.5. (C) 2017 Elsevier Ltd. All rights reserved.
机译：近年来，在印度尤其是在其首都新德里，经常观察到严重的污染事件。然而，进行了有限的研究以了解高污染物浓度的来源，以设计有效的控制策略。在这项工作中，采用了面向社区的多尺度空气质量（CMAQ）模型和全球大气研究排放数据库（EDGAR）来量化八种排放源类型的贡献（能源，工业，住宅，公路，越野，农业，露天焚烧和粉尘）到德里和三个周边地区的细颗粒物（PM2.5）及其成分，包括初级PM（PPM）和次级无机气溶胶（SIA），即硫酸根，硝酸根和铵离子。 2015年是昌迪加尔，勒克瑙和斋浦尔等城市。PPM质量主要由工业和居民活动（> 60％）主导。能源（约占39％）和工业（约占45％）部门为德里南部的PPM做出了重要贡献，冬季最高达到200μg / m（3）。与PPM不同，来自不同来源的SIA浓度更加不均匀。新德里南部和北方邦中部的SIA浓度较高（约25μg/ m（3）），主要归因于能源，工业和居民部门。农业对于SIA而言比PPM更为重要，并且公路运输和露天焚烧对SIA的贡献也高于对PPM的贡献。居民部门对总PM2.5的贡献最高（约80μg / m（3）），其次是印度北部的工业（约70μg/ m（3））。能源和农业对PM2.5的总贡献量接近25μg/ m（3）和16μg/ m（3），而SOA的贡献<5μg/ m（3）。在德里，工业和居民活动占PM2.5总量的80％。 （C）2017 Elsevier Ltd.保留所有权利。

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  • 来源
    《Environmental Pollution》 |2017年第1期|426-436|共11页
  • 作者

    Guo Hao; Kota Sri Harsha; Sahu Shovan Kumar; Hu Jianlin; Ying Qi; Gao Aifang; Zhang Hongliang;

  • 作者单位

    Louisiana State Univ, Dept Civil & Environm Engn, Baton Rouge, LA 70803 USA;

    Indian Inst Technol Guwahati, Dept Civil Engn, Gauhati 781039, India;

    Indian Inst Technol Guwahati, Dept Civil Engn, Gauhati 781039, India;

    Nanjing Univ Informat Sci & Technol, Jiangsu Engn Technol Res Ctr Environm Cleaning Ma, Collaborat Innovat Ctr Atmospher Environm & Equip, Sch Environm Sci & Engn,Jiangsu Key Lab Atmospher, 219 Ningliu Rd, Nanjing 210044, Jiangsu, Peoples R China;

    Texas A&M Univ, Zachry Dept Civil Engn, College Stn, TX 77843 USA;

    Hebei GEO Univ, Sch Water Resources & Environm, Shijiazhuang 050031, Hebei, Peoples R China|Hebei Key Lab Sustained Utilizat & Dev Water Reso, Shijiazhuang 050031, Hebei, Peoples R China;

    Louisiana State Univ, Dept Civil & Environm Engn, Baton Rouge, LA 70803 USA|Nanjing Univ Informat Sci & Technol, Jiangsu Engn Technol Res Ctr Environm Cleaning Ma, Collaborat Innovat Ctr Atmospher Environm & Equip, Sch Environm Sci & Engn,Jiangsu Key Lab Atmospher, 219 Ningliu Rd, Nanjing 210044, Jiangsu, Peoples R China;

  • 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

    Source apportionment; PM2.5; India; Delhi; CMAQ;

    机译：来源分配;PM2.5;印度;德里;CMAQ;

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