Source apportionment of particulate matter based on numerical simulation during a severe pollution period in Tangshan, North China
Source apportionment of particulate matter based on numerical simulation during a severe pollution period in Tangshan, North China
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基于数值模拟的华北唐山重污染期颗粒物来源解析
DOI：
10.1016/j.envpol.2020.115133
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发表时间：
2020-11-01
影响因子：
8.9
通讯作者：
Jing, Boyu
中科院分区：
文献类型：
--
作者：
He, Jianjun;Zhang, Lei;Jing, Boyu
面对严重的大气污染问题，中国政府采取了多项措施防治大气污染。了解污染物的来源对预防空气污染至关重要。采用数值模拟方法，分析了唐山市本地总排放量和不同行业（工业、交通、居民、农业和电厂）本地排放量对PM2. 5浓度的贡献、后向轨迹和潜在源区。研究了多尺度气象条件对污染物源解析的影响。2016年10月至2017年3月，本地排放总量占近地面PM2.5浓度的46.0%。从行业排放来看，唐山市工业排放是最主要的污染源，占近地面PM2. 5浓度的23. 1%。农业排放是第二大来源，占近地面PM2.5浓度的10.3%。电厂、交通、居民源的贡献率分别为2.0%、3.0%和7.2%。本地总排放量和不同部门排放量的贡献取决于多尺度气象条件，静稳天气显著增强了区域输送对近地面PM2. 5浓度的贡献。八个集群后向轨迹被确定为唐山。8个聚类轨迹的PM2.5浓度差异显著。唐山市区近地面PM2. 5主要来源于本地排放，天津市是另一个重要的潜在来源区域。源解析的结果表明，在城市或工业区密集的地区，大气污染联防联控的重要性。(C)2020爱思唯尔有限公司保留所有权利。
Facing serious air pollution problems, the Chinese government has taken numerous measures to prevent and control air pollution. Understanding the sources of pollutants is crucial to the prevention of air pollution. Using numerical simulation method, this study analysed the contributions of the total local emissions and local emissions from different sectors (such as industrial, traffic, resident, agricultural, and power plant emissions) to PM2.5 concentration, backward trajectory, and potential source regions in Tangshan, a typical heavy industrial city in north China. The impact of multi-scale meteorological conditions on source apportionment was investigated. From October 2016 to March 2017, total local emissions accounted for 46.0% of the near-surface PM2.5 concentration. In terms of emissions from different sectors, local industrial emissions which accounted for 23.1% of the near-surface PM2.5 concentration in Tangshan, were the most important pollutant source. Agricultural emissions were the second most important source, accounting for 10.3% of the near-surface PM2.5 concentration. The contributions of emissions from power plants, traffic, residential sources were 2.0%, 3.0%, and 7.2%, respectively. The contributions of total local emissions and emissions from different sectors depended on multi-scale meteorological conditions, and static weather significantly enhanced the contribution of regional transport to the near-surface PM2.5 concentration. Eight cluster backward trajectories were identified for Tangshan. The PM2.5 concentration for the 8 cluster trajectories significantly differed. The near-surface PM2.5 in urban Tangshan (receptor point) was mainly from the local emissions, and another important potential source regionwas Tianjin. The results of the source apportionment suggested the importance of joint prevention and control of air pollution in some areas where cities or industrial regions are densely distributed. (C) 2020 Elsevier Ltd. All rights reserved.