Cargando…
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...
Autores principales: | , , , , , , , , , |
---|---|
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 |
_version_ | 1783692266649419776 |
---|---|
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. |
format | Online Article Text |
id | pubmed-8121134 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT zhaochenkai spatiotemporalanalysisofurbanairpollutantsthroughoutchinaduring20142019 AT sunying spatiotemporalanalysisofurbanairpollutantsthroughoutchinaduring20142019 AT zhongyaping spatiotemporalanalysisofurbanairpollutantsthroughoutchinaduring20142019 AT xusenhao spatiotemporalanalysisofurbanairpollutantsthroughoutchinaduring20142019 AT liangyue spatiotemporalanalysisofurbanairpollutantsthroughoutchinaduring20142019 AT liushu spatiotemporalanalysisofurbanairpollutantsthroughoutchinaduring20142019 AT hexiaodong spatiotemporalanalysisofurbanairpollutantsthroughoutchinaduring20142019 AT zhujinghai spatiotemporalanalysisofurbanairpollutantsthroughoutchinaduring20142019 AT shibamototakayuki spatiotemporalanalysisofurbanairpollutantsthroughoutchinaduring20142019 AT hemiao spatiotemporalanalysisofurbanairpollutantsthroughoutchinaduring20142019 |