Source and sectoral contribution analysis of PM2.5 based on efficient response surface modeling technique over Pearl River Delta Region of China

被引:17
|
作者
Pan, Yuzhou [1 ]
Zhu, Yun [1 ]
Jang, Jicheng [1 ]
Wang, Shuxiao [2 ]
Xing, Jia [2 ]
Chiang, Pen-Chi [3 ,4 ]
Zhao, Xuetao [5 ]
You, Zhiqiang [1 ]
Yuan, Yingzhi [1 ]
机构
[1] South China Univ Technol, Guangzhou Higher Educ Mega Ctr, Sch Environm & Energy, Guangdong Prov Key Lab Atmospher Environm & Pollu, Guangzhou 510006, Peoples R China
[2] Tsinghua Univ, Sch Environm, State Key Joint Lab Environm Simulat & Pollut Con, Beijing 100084, Peoples R China
[3] Natl Taiwan Univ, Grad Inst Environm Engn, Taipei 10673, Taiwan
[4] Natl Taiwan Univ, Carbon Cycle Res Ctr, Taipei 10672, Taiwan
[5] Chinese Acad Environm Planning, Beijing 100012, Peoples R China
基金
中国国家自然科学基金;
关键词
PM2.5; Response surface model; Differential method; Brute force method; Source contribution; FINE PARTICULATE MATTER; TIANJIN-HEBEI REGION; SOURCE APPORTIONMENT; AIR-QUALITY; NONLINEAR RESPONSE; EMISSION CHANGES; SENSITIVITY-ANALYSIS; INORGANIC AEROSOLS; GUANGDONG PROVINCE; POLLUTION;
D O I
10.1016/j.scitotenv.2020.139655
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Identifying and quantifying, source contributions of pollutant emissions are crucial for an effective control strategy to break through the bottleneck in reducing ambient PM2.5 levels over the Pearl River Delta (PRD) region of China. In this study, an innovative response surface modeling technique with differential method (RSM-DM) has been developed and applied to investigate the PM2.5 contributions from multiple regions, sectors, and pollutants over the PRD region in 2015. The new differential method, with the ability to reproduce the nonlinear response surface of PM2.5 to precursor emissions by dissecting the emission changes into a series of small intervals, has shown to overcome the issue of the traditional brute force method in overestimating the accumulative contribution of precursor emissions to PM2.5. The results of this case study showed that PM2.5 in the PRD region was generally dominated by local emission sources (39-64%). Among the contributions of PM2.5 from various sectors and pollutants, the primary PM2.5 emissions from fugitive dust source contributed most (25-42%) to PM2.5 levels. The contributions of agriculture NH3 emissions (6-13%) could also play a significant role compared to other sectoral precursor emissions. Among the NOx sectors, the emissions control of stationary combustion source could be most effective in reducing PM2.5 levels over the PRD region. (C) 2020 Elsevier B.V. All rights reserved.
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页数:15
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