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Meteorological Influences on Spatiotemporal Variation of PM(2.5) Concentrations in Atmospheric Pollution Transmission Channel Cities of the Beijing–Tianjin–Hebei Region, China

Understanding the spatiotemporal characteristics of PM(2.5) concentrations and identifying their associated meteorological factors can provide useful insight for implementing air pollution interventions. In this study, we used daily air quality monitoring data for 28 air pollution transmission chann...

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Detalles Bibliográficos
Autores principales: Wang, Suxian, Gao, Jiangbo, Guo, Linghui, Nie, Xiaojun, Xiao, Xiangming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8834796/
https://www.ncbi.nlm.nih.gov/pubmed/35162629
http://dx.doi.org/10.3390/ijerph19031607
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author Wang, Suxian
Gao, Jiangbo
Guo, Linghui
Nie, Xiaojun
Xiao, Xiangming
author_facet Wang, Suxian
Gao, Jiangbo
Guo, Linghui
Nie, Xiaojun
Xiao, Xiangming
author_sort Wang, Suxian
collection PubMed
description Understanding the spatiotemporal characteristics of PM(2.5) concentrations and identifying their associated meteorological factors can provide useful insight for implementing air pollution interventions. In this study, we used daily air quality monitoring data for 28 air pollution transmission channel cities in the Beijing–Tianjin–Hebei region during 2014–2019 to quantify the relative contributions of meteorological factors on spatiotemporal variation in PM(2.5) concentration by combining time series and spatial perspectives. The results show that annual mean PM(2.5) concentration significantly decreased in 24 of the channel cities from 2014 to 2019, but they all still exceeded the Grade II Chinese Ambient Air Quality Standards (35 μg m(−3)) in 2019. PM(2.5) concentrations exhibited clear spatial agglomeration in the most polluted season, and their spatial pattern changed slightly over time. Meteorological variables accounted for 31.96% of the temporal variation in PM(2.5) concentration among the 28 cities during the study period, with minimum temperature and average relative humidity as the most critical factors. Spatially, atmospheric pressure and maximum temperature played a key role in the distribution of PM(2.5) concentration in spring and summer, whereas the effect of sunshine hours increased greatly in autumn and winter. These findings highlight the importance of future clean air policy making, but also provide a theoretical support for precise forecasting and prevention of PM(2.5) pollution.
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spelling pubmed-88347962022-02-12 Meteorological Influences on Spatiotemporal Variation of PM(2.5) Concentrations in Atmospheric Pollution Transmission Channel Cities of the Beijing–Tianjin–Hebei Region, China Wang, Suxian Gao, Jiangbo Guo, Linghui Nie, Xiaojun Xiao, Xiangming Int J Environ Res Public Health Article Understanding the spatiotemporal characteristics of PM(2.5) concentrations and identifying their associated meteorological factors can provide useful insight for implementing air pollution interventions. In this study, we used daily air quality monitoring data for 28 air pollution transmission channel cities in the Beijing–Tianjin–Hebei region during 2014–2019 to quantify the relative contributions of meteorological factors on spatiotemporal variation in PM(2.5) concentration by combining time series and spatial perspectives. The results show that annual mean PM(2.5) concentration significantly decreased in 24 of the channel cities from 2014 to 2019, but they all still exceeded the Grade II Chinese Ambient Air Quality Standards (35 μg m(−3)) in 2019. PM(2.5) concentrations exhibited clear spatial agglomeration in the most polluted season, and their spatial pattern changed slightly over time. Meteorological variables accounted for 31.96% of the temporal variation in PM(2.5) concentration among the 28 cities during the study period, with minimum temperature and average relative humidity as the most critical factors. Spatially, atmospheric pressure and maximum temperature played a key role in the distribution of PM(2.5) concentration in spring and summer, whereas the effect of sunshine hours increased greatly in autumn and winter. These findings highlight the importance of future clean air policy making, but also provide a theoretical support for precise forecasting and prevention of PM(2.5) pollution. MDPI 2022-01-30 /pmc/articles/PMC8834796/ /pubmed/35162629 http://dx.doi.org/10.3390/ijerph19031607 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wang, Suxian
Gao, Jiangbo
Guo, Linghui
Nie, Xiaojun
Xiao, Xiangming
Meteorological Influences on Spatiotemporal Variation of PM(2.5) Concentrations in Atmospheric Pollution Transmission Channel Cities of the Beijing–Tianjin–Hebei Region, China
title Meteorological Influences on Spatiotemporal Variation of PM(2.5) Concentrations in Atmospheric Pollution Transmission Channel Cities of the Beijing–Tianjin–Hebei Region, China
title_full Meteorological Influences on Spatiotemporal Variation of PM(2.5) Concentrations in Atmospheric Pollution Transmission Channel Cities of the Beijing–Tianjin–Hebei Region, China
title_fullStr Meteorological Influences on Spatiotemporal Variation of PM(2.5) Concentrations in Atmospheric Pollution Transmission Channel Cities of the Beijing–Tianjin–Hebei Region, China
title_full_unstemmed Meteorological Influences on Spatiotemporal Variation of PM(2.5) Concentrations in Atmospheric Pollution Transmission Channel Cities of the Beijing–Tianjin–Hebei Region, China
title_short Meteorological Influences on Spatiotemporal Variation of PM(2.5) Concentrations in Atmospheric Pollution Transmission Channel Cities of the Beijing–Tianjin–Hebei Region, China
title_sort meteorological influences on spatiotemporal variation of pm(2.5) concentrations in atmospheric pollution transmission channel cities of the beijing–tianjin–hebei region, china
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8834796/
https://www.ncbi.nlm.nih.gov/pubmed/35162629
http://dx.doi.org/10.3390/ijerph19031607
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