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Spatio-temporal analysis of urban air pollutants throughout China during 2014–2019

Air pollution control has become the top priority of China’s “green development” concept since 2013. The Chinese government has enacted a range of policies and statutes to control contaminant emissions and improve air quality. On the basis of the national air quality ground observation database, the...

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Autores principales: Zhao, Chenkai, Sun, Ying, Zhong, Yaping, Xu, Senhao, Liang, Yue, Liu, Shu, He, Xiaodong, Zhu, Jinghai, Shibamoto, Takayuki, He, Miao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8121134/
https://www.ncbi.nlm.nih.gov/pubmed/34025820
http://dx.doi.org/10.1007/s11869-021-01043-5
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author Zhao, Chenkai
Sun, Ying
Zhong, Yaping
Xu, Senhao
Liang, Yue
Liu, Shu
He, Xiaodong
Zhu, Jinghai
Shibamoto, Takayuki
He, Miao
author_facet Zhao, Chenkai
Sun, Ying
Zhong, Yaping
Xu, Senhao
Liang, Yue
Liu, Shu
He, Xiaodong
Zhu, Jinghai
Shibamoto, Takayuki
He, Miao
author_sort Zhao, Chenkai
collection PubMed
description Air pollution control has become the top priority of China’s “green development” concept since 2013. The Chinese government has enacted a range of policies and statutes to control contaminant emissions and improve air quality. On the basis of the national air quality ground observation database, the spatial and temporal distribution of air quality index value (AQI), fine particulate matter (PM(2.5)), coarse particles (PM(10)), sulfur dioxide (SO(2)), nitrogen dioxide (NO(2)), carbon monoxide (CO), and ozone (O(3)) were explored in 336 cities throughout China from 2014 to 2019. AQI and most pollutants (except O(3)) decreased in concentrations from 2014 to 2019. In 2019, all cities except Henan reached the level 2 of the ambient air quality index, and six cities had a lower ambient air quality index and reached the level 1. Spatially, higher pollutant concentrations were concentrated in large city clusters, whereas the areas with high O(3) concentration were found across the country. Furthermore, central heating was shown to have a negative impact on air quality. The observed AQI value, PM(2.5), PM(10), SO(2), NO(2), and CO concentrations were highest in north and northwest China and Henan province in central China. The correlations among pollutants suggest that the main sources of pollutants are fossil fuel combustion, industrial production, and motor vehicle emissions. The influence of meteorological factors on air quality, long-distance transportation, and the transformations of pollutants should be explored in future research. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11869-021-01043-5.
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spelling pubmed-81211342021-05-17 Spatio-temporal analysis of urban air pollutants throughout China during 2014–2019 Zhao, Chenkai Sun, Ying Zhong, Yaping Xu, Senhao Liang, Yue Liu, Shu He, Xiaodong Zhu, Jinghai Shibamoto, Takayuki He, Miao Air Qual Atmos Health Article Air pollution control has become the top priority of China’s “green development” concept since 2013. The Chinese government has enacted a range of policies and statutes to control contaminant emissions and improve air quality. On the basis of the national air quality ground observation database, the spatial and temporal distribution of air quality index value (AQI), fine particulate matter (PM(2.5)), coarse particles (PM(10)), sulfur dioxide (SO(2)), nitrogen dioxide (NO(2)), carbon monoxide (CO), and ozone (O(3)) were explored in 336 cities throughout China from 2014 to 2019. AQI and most pollutants (except O(3)) decreased in concentrations from 2014 to 2019. In 2019, all cities except Henan reached the level 2 of the ambient air quality index, and six cities had a lower ambient air quality index and reached the level 1. Spatially, higher pollutant concentrations were concentrated in large city clusters, whereas the areas with high O(3) concentration were found across the country. Furthermore, central heating was shown to have a negative impact on air quality. The observed AQI value, PM(2.5), PM(10), SO(2), NO(2), and CO concentrations were highest in north and northwest China and Henan province in central China. The correlations among pollutants suggest that the main sources of pollutants are fossil fuel combustion, industrial production, and motor vehicle emissions. The influence of meteorological factors on air quality, long-distance transportation, and the transformations of pollutants should be explored in future research. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11869-021-01043-5. Springer Netherlands 2021-05-14 2021 /pmc/articles/PMC8121134/ /pubmed/34025820 http://dx.doi.org/10.1007/s11869-021-01043-5 Text en © The Author(s), under exclusive licence to Springer Nature B.V. 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Zhao, Chenkai
Sun, Ying
Zhong, Yaping
Xu, Senhao
Liang, Yue
Liu, Shu
He, Xiaodong
Zhu, Jinghai
Shibamoto, Takayuki
He, Miao
Spatio-temporal analysis of urban air pollutants throughout China during 2014–2019
title Spatio-temporal analysis of urban air pollutants throughout China during 2014–2019
title_full Spatio-temporal analysis of urban air pollutants throughout China during 2014–2019
title_fullStr Spatio-temporal analysis of urban air pollutants throughout China during 2014–2019
title_full_unstemmed Spatio-temporal analysis of urban air pollutants throughout China during 2014–2019
title_short Spatio-temporal analysis of urban air pollutants throughout China during 2014–2019
title_sort spatio-temporal analysis of urban air pollutants throughout china during 2014–2019
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8121134/
https://www.ncbi.nlm.nih.gov/pubmed/34025820
http://dx.doi.org/10.1007/s11869-021-01043-5
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