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Article: Influence of meteorological conditions on PM2.5 concentrations across China: A review of methodology and mechanism

TitleInfluence of meteorological conditions on PM<inf>2.5</inf> concentrations across China: A review of methodology and mechanism
Authors
KeywordsStatistical model
Interaction mechanism
Causality model
PM 2.5
CTM
Meteorological condition
Issue Date2020
Citation
Environment International, 2020, v. 139, article no. 105558 How to Cite?
AbstractAir pollution over China has attracted wide interest from public and academic community. PM is the primary air pollutant across China. Quantifying interactions between meteorological conditions and PM concentrations are essential to understand the variability of PM and seek methods to control PM . Since 2013, the measurement of PM has been widely made at 1436 stations across the country and more than 300 papers focusing on PM -meteorology interactions have been published. This article is a comprehensive review on the meteorological impact on PM concentrations. We start with an introduction of general meteorological conditions and PM concentrations across China, and then seasonal and spatial variations of meteorological influences on PM concentrations. Next, major methods used to quantify meteorological influences on PM 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 PM concentrations. Chemical Transport Models (CTMs) have the potential to provide dynamic estimation of PM 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 PM concentrations, including the dispersion, growth, chemical production, photolysis, and deposition of PM . The feedback effects of PM concentrations on meteorological factors are also carefully examined. Based on this review, suggestions on future research and major meteorological approaches for mitigating PM pollution are made finally. 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5
Persistent Identifierhttp://hdl.handle.net/10722/299621
ISSN
2023 Impact Factor: 10.3
2023 SCImago Journal Rankings: 3.015
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorChen, Ziyue-
dc.contributor.authorChen, Danlu-
dc.contributor.authorZhao, Chuanfeng-
dc.contributor.authorKwan, Mei po-
dc.contributor.authorCai, Jun-
dc.contributor.authorZhuang, Yan-
dc.contributor.authorZhao, Bo-
dc.contributor.authorWang, Xiaoyan-
dc.contributor.authorChen, Bin-
dc.contributor.authorYang, Jing-
dc.contributor.authorLi, Ruiyuan-
dc.contributor.authorHe, Bin-
dc.contributor.authorGao, Bingbo-
dc.contributor.authorWang, Kaicun-
dc.contributor.authorXu, Bing-
dc.date.accessioned2021-05-21T03:34:48Z-
dc.date.available2021-05-21T03:34:48Z-
dc.date.issued2020-
dc.identifier.citationEnvironment International, 2020, v. 139, article no. 105558-
dc.identifier.issn0160-4120-
dc.identifier.urihttp://hdl.handle.net/10722/299621-
dc.description.abstractAir pollution over China has attracted wide interest from public and academic community. PM is the primary air pollutant across China. Quantifying interactions between meteorological conditions and PM concentrations are essential to understand the variability of PM and seek methods to control PM . Since 2013, the measurement of PM has been widely made at 1436 stations across the country and more than 300 papers focusing on PM -meteorology interactions have been published. This article is a comprehensive review on the meteorological impact on PM concentrations. We start with an introduction of general meteorological conditions and PM concentrations across China, and then seasonal and spatial variations of meteorological influences on PM concentrations. Next, major methods used to quantify meteorological influences on PM 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 PM concentrations. Chemical Transport Models (CTMs) have the potential to provide dynamic estimation of PM 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 PM concentrations, including the dispersion, growth, chemical production, photolysis, and deposition of PM . The feedback effects of PM concentrations on meteorological factors are also carefully examined. Based on this review, suggestions on future research and major meteorological approaches for mitigating PM pollution are made finally. 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5-
dc.languageeng-
dc.relation.ispartofEnvironment International-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectStatistical model-
dc.subjectInteraction mechanism-
dc.subjectCausality model-
dc.subjectPM 2.5-
dc.subjectCTM-
dc.subjectMeteorological condition-
dc.titleInfluence of meteorological conditions on PM<inf>2.5</inf> concentrations across China: A review of methodology and mechanism-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1016/j.envint.2020.105558-
dc.identifier.pmid32278201-
dc.identifier.scopuseid_2-s2.0-85082815991-
dc.identifier.volume139-
dc.identifier.spagearticle no. 105558-
dc.identifier.epagearticle no. 105558-
dc.identifier.eissn1873-6750-
dc.identifier.isiWOS:000544887000004-

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