Source apportionment of PM2.5 in North India using source-oriented air quality models
Source apportionment of PM2.5 in North India using source-oriented air quality models
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DOI：
10.1016/j.envpol.2017.08.016
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发表时间：
2017-12-01
影响因子：
8.9
通讯作者：
Zhang, Hongliang
中科院分区：
文献类型：
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作者：
Guo, Hao;Kota, Sri Harsha;Zhang, Hongliang
近年来，印度频繁发生严重污染事件，尤其是在首都新德里。然而，为了设计有效的控制策略，对高污染物浓度的来源进行了有限的研究。在这项工作中，基于全球大气研究排放数据库（EDGAR）的社区多尺度空气质量（CMAQ）模型的源导向版本被应用于量化八种源类型（能源、工业、住宅、道路、越野、农业、露天燃烧和粉尘）对细颗粒物（PM2.5）及其组分的贡献，包括初级PM （PPM）和次级无机气溶胶（SIA），即硫酸盐、硝酸盐和铵离子。在德里和三个周边城市昌迪加尔、勒克瑙和斋浦尔。PPM质量主要受工业和居民活动的影响（60%）。能源（类似39%）和工业（类似45%）部门对德里南部的PPM贡献很大，冬季最高可达200 μ g/m(3)。与PPM不同，不同来源的SIA浓度更具有异质性。德里南部和北方邦中部的高浓度SIA（类似于25 μ g/m(3)）主要归因于能源、工业和住宅部门。农业对SIA的贡献大于PPM，公路和露天焚烧对SIA的贡献也高于PPM。在印度北部，住宅部门对PM2.5总量的贡献最大（约为80 μ g/m(3)），其次是工业（约为70 μ g/m(3)）。能源和农业对PM2.5总量的贡献分别为25 μ g/m(3)和16 μ g/m(3)，而SOA则有贡献
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