Articles | Volume 18, issue 8
https://doi.org/10.5194/acp-18-5343-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-18-5343-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Understanding meteorological influences on PM2.5 concentrations across China: a temporal and spatial perspective
Ziyue Chen
State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, 19 Xinjiekouwai Street, Haidian, Beijing 100875, China
Joint Center for Global Change Studies, Beijing 100875,
China
Xiaoming Xie
State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, 19 Xinjiekouwai Street, Haidian, Beijing 100875, China
Ministry of Education Key Laboratory for Earth System
Modeling, Department of Earth System Science, Tsinghua
University, Beijing 100084, China
Danlu Chen
State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, 19 Xinjiekouwai Street, Haidian, Beijing 100875, China
Bingbo Gao
National Engineering Research
Center for Information Technology in Agriculture, 11 Shuguang
Huayuan Middle Road, Beijing 100097, China
Bin He
State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, 19 Xinjiekouwai Street, Haidian, Beijing 100875, China
Joint Center for Global Change Studies, Beijing 100875,
China
Nianliang Cheng
Beijing Municipal
Environmental Monitoring Center, Beijing 100048, China
Bing Xu
CORRESPONDING AUTHOR
Ministry of Education Key Laboratory for Earth System
Modeling, Department of Earth System Science, Tsinghua
University, Beijing 100084, China
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Latest update: 14 Dec 2024
Short summary
With an advanced causality analysis method CCM, we quantified the influence of individual meteorological factors on PM2.5 concentrations and revealed notable spatial and temporal variations of meteorological influences on PM2.5 concentrations across China. Temperature, humidity and wind exert the strongest influences on PM2.5 concentrations in most cities across China. Given the notable spatial variations, meteorological means for reducing PM2.5 concentrations should be designed accordingly.
With an advanced causality analysis method CCM, we quantified the influence of individual...
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