Influence of meteorological conditions on PM2.5 concentrations across China: A review of methodology and mechanism
Air pollution over China has attracted wide interest from public and academic community. PM2.5 is the primary air pollutant across China. Quantifying interactions between meteorological conditions and PM2.5 concentrations are essential to understand the variability of PM2.5 and seek methods to contr...
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| Format: | Article |
| Language: | English |
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Elsevier
2020-06-01
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| Series: | Environment International |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0160412019323323 |
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doaj-54802a6155f2487b915b644f96c449a5 |
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Article |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Ziyue Chen Danlu Chen Chuanfeng Zhao Mei-po Kwan Jun Cai Yan Zhuang Bo Zhao Xiaoyan Wang Bin Chen Jing Yang Ruiyuan Li Bin He Bingbo Gao Kaicun Wang Bing Xu |
| spellingShingle |
Ziyue Chen Danlu Chen Chuanfeng Zhao Mei-po Kwan Jun Cai Yan Zhuang Bo Zhao Xiaoyan Wang Bin Chen Jing Yang Ruiyuan Li Bin He Bingbo Gao Kaicun Wang Bing Xu Influence of meteorological conditions on PM2.5 concentrations across China: A review of methodology and mechanism Environment International PM2.5 Meteorological condition Interaction mechanism Causality model Statistical model CTM |
| author_facet |
Ziyue Chen Danlu Chen Chuanfeng Zhao Mei-po Kwan Jun Cai Yan Zhuang Bo Zhao Xiaoyan Wang Bin Chen Jing Yang Ruiyuan Li Bin He Bingbo Gao Kaicun Wang Bing Xu |
| author_sort |
Ziyue Chen |
| title |
Influence of meteorological conditions on PM2.5 concentrations across China: A review of methodology and mechanism |
| title_short |
Influence of meteorological conditions on PM2.5 concentrations across China: A review of methodology and mechanism |
| title_full |
Influence of meteorological conditions on PM2.5 concentrations across China: A review of methodology and mechanism |
| title_fullStr |
Influence of meteorological conditions on PM2.5 concentrations across China: A review of methodology and mechanism |
| title_full_unstemmed |
Influence of meteorological conditions on PM2.5 concentrations across China: A review of methodology and mechanism |
| title_sort |
influence of meteorological conditions on pm2.5 concentrations across china: a review of methodology and mechanism |
| publisher |
Elsevier |
| series |
Environment International |
| issn |
0160-4120 |
| publishDate |
2020-06-01 |
| description |
Air pollution over China has attracted wide interest from public and academic community. PM2.5 is the primary air pollutant across China. Quantifying interactions between meteorological conditions and PM2.5 concentrations are essential to understand the variability of PM2.5 and seek methods to control PM2.5. Since 2013, the measurement of PM2.5 has been widely made at 1436 stations across the country and more than 300 papers focusing on PM2.5-meteorology interactions have been published. This article is a comprehensive review on the meteorological impact on PM2.5 concentrations. We start with an introduction of general meteorological conditions and PM2.5 concentrations across China, and then seasonal and spatial variations of meteorological influences on PM2.5 concentrations. Next, major methods used to quantify meteorological influences on PM2.5 concentrations are checked and compared. We find that causality analysis methods are more suitable for extracting the influence of individual meteorological factors whilst statistical models are good at quantifying the overall effect of multiple meteorological factors on PM2.5 concentrations. Chemical Transport Models (CTMs) have the potential to provide dynamic estimation of PM2.5 concentrations by considering anthropogenic emissions and the transport and evolution of pollutants. We then comprehensively examine the mechanisms how major meteorological factors may impact the PM2.5 concentrations, including the dispersion, growth, chemical production, photolysis, and deposition of PM2.5. The feedback effects of PM2.5 concentrations on meteorological factors are also carefully examined. Based on this review, suggestions on future research and major meteorological approaches for mitigating PM2.5 pollution are made finally. |
| topic |
PM2.5 Meteorological condition Interaction mechanism Causality model Statistical model CTM |
| url |
http://www.sciencedirect.com/science/article/pii/S0160412019323323 |
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doaj-54802a6155f2487b915b644f96c449a52020-11-25T03:29:33ZengElsevierEnvironment International0160-41202020-06-01139Influence of meteorological conditions on PM2.5 concentrations across China: A review of methodology and mechanismZiyue Chen0Danlu Chen1Chuanfeng Zhao2Mei-po Kwan3Jun Cai4Yan Zhuang5Bo Zhao6Xiaoyan Wang7Bin Chen8Jing Yang9Ruiyuan Li10Bin He11Bingbo Gao12Kaicun Wang13Bing Xu14State Key Laboratory of Remote Sensing Science, College of Global and Earth System Sciences, Beijing Normal University, 19 Xinjiekou Street, Haidian, Beijing 100875, China; Joint Center for Global Change Studies, Beijing 100875, ChinaState Key Laboratory of Remote Sensing Science, College of Global and Earth System Sciences, Beijing Normal University, 19 Xinjiekou Street, Haidian, Beijing 100875, ChinaState Key Laboratory of Remote Sensing Science, College of Global and Earth System Sciences, Beijing Normal University, 19 Xinjiekou Street, Haidian, Beijing 100875, China; Joint Center for Global Change Studies, Beijing 100875, ChinaDepartment of Geography and Resource Management, and Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, China; Department of Human Geography and Spatial Planning, Utrecht University, 3584 CB Utrecht, the NetherlandsDepartment of Earth System Science, Tsinghua University, Beijing 100084, ChinaState Key Laboratory of Remote Sensing Science, College of Global and Earth System Sciences, Beijing Normal University, 19 Xinjiekou Street, Haidian, Beijing 100875, ChinaDepartment of Geography, University of Washington, Seattle, Washington 98195, USAState Key Laboratory of Remote Sensing Science, College of Global and Earth System Sciences, Beijing Normal University, 19 Xinjiekou Street, Haidian, Beijing 100875, China; Institute of Atmospheric Science, Fudan University, Shanghai 200433, ChinaDepartment of Land, Air and Water Resources, University of California, Davis, CA 95616, USAState Key Laboratory of Earth Surface Processes and Resource Ecology (ESPRE), Faculty of Geographical Science, Beijing Normal University, 19 Xinjiekou Street, Haidian, Beijing 100875, ChinaState Key Laboratory of Remote Sensing Science, College of Global and Earth System Sciences, Beijing Normal University, 19 Xinjiekou Street, Haidian, Beijing 100875, ChinaState Key Laboratory of Remote Sensing Science, College of Global and Earth System Sciences, Beijing Normal University, 19 Xinjiekou Street, Haidian, Beijing 100875, China; Joint Center for Global Change Studies, Beijing 100875, ChinaChina College of Land Science and Technology, China Agriculture University, Tsinghua East Road, Haidian District, Beijing 100083, ChinaState Key Laboratory of Remote Sensing Science, College of Global and Earth System Sciences, Beijing Normal University, 19 Xinjiekou Street, Haidian, Beijing 100875, China; Joint Center for Global Change Studies, Beijing 100875, China; Corresponding authors at: State Key Laboratory of Remote Sensing Science, College of Global and Earth System Sciences, Beijing Normal University, 19 Xinjiekou Street, Haidian, Beijing 100875, China (K. Wang). Department of Earth System Science, Tsinghua University, Beijing 100084, China (B. Xu).Department of Earth System Science, Tsinghua University, Beijing 100084, China; Corresponding authors at: State Key Laboratory of Remote Sensing Science, College of Global and Earth System Sciences, Beijing Normal University, 19 Xinjiekou Street, Haidian, Beijing 100875, China (K. Wang). Department of Earth System Science, Tsinghua University, Beijing 100084, China (B. Xu).Air pollution over China has attracted wide interest from public and academic community. PM2.5 is the primary air pollutant across China. Quantifying interactions between meteorological conditions and PM2.5 concentrations are essential to understand the variability of PM2.5 and seek methods to control PM2.5. Since 2013, the measurement of PM2.5 has been widely made at 1436 stations across the country and more than 300 papers focusing on PM2.5-meteorology interactions have been published. This article is a comprehensive review on the meteorological impact on PM2.5 concentrations. We start with an introduction of general meteorological conditions and PM2.5 concentrations across China, and then seasonal and spatial variations of meteorological influences on PM2.5 concentrations. Next, major methods used to quantify meteorological influences on PM2.5 concentrations are checked and compared. We find that causality analysis methods are more suitable for extracting the influence of individual meteorological factors whilst statistical models are good at quantifying the overall effect of multiple meteorological factors on PM2.5 concentrations. Chemical Transport Models (CTMs) have the potential to provide dynamic estimation of PM2.5 concentrations by considering anthropogenic emissions and the transport and evolution of pollutants. We then comprehensively examine the mechanisms how major meteorological factors may impact the PM2.5 concentrations, including the dispersion, growth, chemical production, photolysis, and deposition of PM2.5. The feedback effects of PM2.5 concentrations on meteorological factors are also carefully examined. Based on this review, suggestions on future research and major meteorological approaches for mitigating PM2.5 pollution are made finally.http://www.sciencedirect.com/science/article/pii/S0160412019323323PM2.5Meteorological conditionInteraction mechanismCausality modelStatistical modelCTM |