TY - JOUR
T1 - Influence of meteorological conditions on PM2.5 concentrations across China
T2 - A review of methodology and mechanism
AU - Chen, Ziyue
AU - Chen, Danlu
AU - Zhao, Chuanfeng
AU - Kwan, Mei po
AU - Cai, Jun
AU - Zhuang, Yan
AU - Zhao, Bo
AU - Wang, Xiaoyan
AU - Chen, Bin
AU - Yang, Jing
AU - Li, Ruiyuan
AU - He, Bin
AU - Gao, Bingbo
AU - Wang, Kaicun
AU - Xu, Bing
N1 - Funding Information:
This research is supported by the National Key Research and Development Program of China (NO. 2016YFA0600104 ), the National Natural Science Foundation of China ( 41525018 and 41930970 ), Beijing Natural Science Foundation ( 8202031 ), and Open Fund of State Key Laboratory of Remote Sensing Science (Grant No. OFSLRSS201926 ).
Publisher Copyright:
© 2020 The Authors
PY - 2020/6
Y1 - 2020/6
N2 - 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.
AB - 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.
KW - CTM
KW - Causality model
KW - Interaction mechanism
KW - Meteorological condition
KW - PM
KW - Statistical model
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U2 - 10.1016/j.envint.2020.105558
DO - 10.1016/j.envint.2020.105558
M3 - Review article
C2 - 32278201
AN - SCOPUS:85082815991
SN - 0160-4120
VL - 139
JO - Environmental International
JF - Environmental International
M1 - 105558
ER -