Winter-autumn air pollution control plan in North China modified the PM2.5 compositions and sources in Central China

被引:2
作者
Jiang, Shuning [1 ]
Kong, Shaofei [1 ,2 ,3 ]
Zheng, Huang [1 ,3 ]
Wu, Jian [1 ,3 ]
Yao, Liquan [1 ]
Chen, Nan [3 ,4 ]
Zhu, Bo [3 ,4 ]
Zhao, Tianliang [2 ]
Bai, Yongqing [5 ]
Liu, Dantong [6 ]
Qi, Shihua [3 ]
机构
[1] China Univ Geosci, Sch Environm Studies, Dept Atmospher Sci, Wuhan 430074, Peoples R China
[2] Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Forecast & Evaluat Meteorol, Nanjing, Peoples R China
[3] Res Ctr Complex Air Pollut Hubei Prov, Wuhan, Peoples R China
[4] Ecoenvironm Monitoring Ctr Hubei Prov, Wuhan 430072, Peoples R China
[5] China Meteorol Adm, Inst Heavy Rain, Hubei Key Lab Heavy Rain Monitoring & Warning Res, Wuhan 430205, Peoples R China
[6] Zhejiang Univ, Sch Earth Sci, Dept Atmospher Sci, Hangzhou 310058, Peoples R China
基金
中国国家自然科学基金;
关键词
Winter -autumn air pollution control plan; PM (2.5) compositions and sources; North China; Central China; Machine -learning technique; POSITIVE MATRIX FACTORIZATION; YANGTZE-RIVER DELTA; HAZE EPISODES; METEOROLOGICAL NORMALIZATION; SOURCE APPORTIONMENT; EMISSION CONTROL; QUALITY; INSIGHTS; AEROSOL; TRENDS;
D O I
10.1016/j.atmosenv.2023.119827
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The additional impact of emission-reduction measures in North China (NC) during autumn and winter on the air quality of downwind regions is an interesting but less addressed topic. The mass concentrations of routine air pollutants, the chemical compositions, and sources of fine particles (PM2.5) for January 2018, 2019, and 2020 at a megacity of Central China were identified, and meteorology-isolated by a machine-learning technique. Their variations were classified according to air mass direction. An unexpectedly sharp increase in emission-related PM2.5 by 22.7% (18.0 mu gm(- 3)) and 25.7% (19.4 mu gm(-3)) for air masses from local and NC in 2019 was observed compared to those of 2018. Organic materials exhibited the highest increase in PM2.5 compositions by 6.90 mu gm(-3) and 6.23 mu g m(- 3) for the air masses from local and NC. PM2.5 source contributions related to emission showed an upsurge from 1.39 mu gm(-3) (biomass burning) to 24.9 mu gm(-3) (secondary inorganic aerosol) in 2019 except for industrial processes, while all reduced in 2020. From 2018 to 2020, the emission-related contribution of coal combustion to PM2.5 increased from 10.0% to 19.0% for air masses from the local area. To support the priority natural gas quotas in northern China, additional coal in cities of southern China was consumed, raising related emissions from transportation activities and road dust in urban regions, as well as additional biofuel consumption in suburban or rural regions. All these activities could explain the increased primary PM2.5 and related precursor NO2. This study gave substantial evidence of air pollution control measures impacting the downwind regions and promote the necessity of air pollution joint control across the administration.
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页数:10
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