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Characteristics of air quality in different climatic zones of China during the COVID-19 lockdown

The diverse climate types and the complex anthropogenic source emissions in China lead to the great regional differences of air pollution mechanisms. The COVID-19 lockdown has given us a precious opportunity to understand the effect of weather conditions and anthropogenic sources on the distribution...

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Autores principales: Wang, Honglei, Tan, Yue, Zhang, Lianxia, Shen, Lijuan, Zhao, Tianliang, Dai, Qihang, Guan, Tianyi, Ke, Yue, Li, Xia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Turkish National Committee for Air Pollution Research and Control. Production and hosting by Elsevier B.V. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8548732/
https://www.ncbi.nlm.nih.gov/pubmed/34720609
http://dx.doi.org/10.1016/j.apr.2021.101247
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author Wang, Honglei
Tan, Yue
Zhang, Lianxia
Shen, Lijuan
Zhao, Tianliang
Dai, Qihang
Guan, Tianyi
Ke, Yue
Li, Xia
author_facet Wang, Honglei
Tan, Yue
Zhang, Lianxia
Shen, Lijuan
Zhao, Tianliang
Dai, Qihang
Guan, Tianyi
Ke, Yue
Li, Xia
author_sort Wang, Honglei
collection PubMed
description The diverse climate types and the complex anthropogenic source emissions in China lead to the great regional differences of air pollution mechanisms. The COVID-19 lockdown has given us a precious opportunity to understand the effect of weather conditions and anthropogenic sources on the distribution of air pollutants in different climate zones. In this study, to understand the impact of meteorological and socio-economic factors on air pollution during COVID-19 lockdown, we divided 358 Chinese cities into eight climate regions. Temporal, spatial and diurnal variations of six major air pollutants from January 1 to April 18, 2020 were analyzed. The differences in the characteristics of air pollutants in different climate zones were obvious. PM(2.5) reduced by 59.0%–64.2% in cold regions (North-East China (NEC) and North-Western (NW)), while O(3) surged by 99.0%–99.9% in warm regions (Central South (CS) and Southern Coast (SC)). Diurnal variations of atmospheric pollutants were also more prominent in cold regions. Moreover, PM(2.5), PM(10), CO and SO(2) showed more prominent reductions (20.5%–64.2%) in heating regions (NEC, NW, NCP and MG) than no-heating regions (0.8%–48%). Climate has less influence on NO(2,) which dropped by 41.2%–57.1% countrywide during the lockdown. The influences of weather conditions on the atmospheric pollutants in different climate zones were different. The wind speed was not the primary reason for the differences in air pollutants in different climate zones. Temperature, precipitation, and air pollution emissions led to prominent regional differences in air pollutants throughout the eight climates. The effect of temperature on PM, SO(2), CO, and NO(2) varied obviously with the latitude, at which condition temperature was negatively correlated to PM, SO(2), CO, and NO(2) in the north but positively in the south. The temperature was positively correlated to ozone in different climate zones, and the correlation was the highest in NEC and the lowest in SC. The rainfall has a strong removal effect on atmospheric pollutants in the climate regions with more precipitation, but it increases the pollutant concentrations in the climate regions with less precipitation. In regions with more emission sources, air pollutants experienced more significant variations and returned to pre-lockdown levels earlier.
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spelling pubmed-85487322021-10-27 Characteristics of air quality in different climatic zones of China during the COVID-19 lockdown Wang, Honglei Tan, Yue Zhang, Lianxia Shen, Lijuan Zhao, Tianliang Dai, Qihang Guan, Tianyi Ke, Yue Li, Xia Atmos Pollut Res Article The diverse climate types and the complex anthropogenic source emissions in China lead to the great regional differences of air pollution mechanisms. The COVID-19 lockdown has given us a precious opportunity to understand the effect of weather conditions and anthropogenic sources on the distribution of air pollutants in different climate zones. In this study, to understand the impact of meteorological and socio-economic factors on air pollution during COVID-19 lockdown, we divided 358 Chinese cities into eight climate regions. Temporal, spatial and diurnal variations of six major air pollutants from January 1 to April 18, 2020 were analyzed. The differences in the characteristics of air pollutants in different climate zones were obvious. PM(2.5) reduced by 59.0%–64.2% in cold regions (North-East China (NEC) and North-Western (NW)), while O(3) surged by 99.0%–99.9% in warm regions (Central South (CS) and Southern Coast (SC)). Diurnal variations of atmospheric pollutants were also more prominent in cold regions. Moreover, PM(2.5), PM(10), CO and SO(2) showed more prominent reductions (20.5%–64.2%) in heating regions (NEC, NW, NCP and MG) than no-heating regions (0.8%–48%). Climate has less influence on NO(2,) which dropped by 41.2%–57.1% countrywide during the lockdown. The influences of weather conditions on the atmospheric pollutants in different climate zones were different. The wind speed was not the primary reason for the differences in air pollutants in different climate zones. Temperature, precipitation, and air pollution emissions led to prominent regional differences in air pollutants throughout the eight climates. The effect of temperature on PM, SO(2), CO, and NO(2) varied obviously with the latitude, at which condition temperature was negatively correlated to PM, SO(2), CO, and NO(2) in the north but positively in the south. The temperature was positively correlated to ozone in different climate zones, and the correlation was the highest in NEC and the lowest in SC. The rainfall has a strong removal effect on atmospheric pollutants in the climate regions with more precipitation, but it increases the pollutant concentrations in the climate regions with less precipitation. In regions with more emission sources, air pollutants experienced more significant variations and returned to pre-lockdown levels earlier. Turkish National Committee for Air Pollution Research and Control. Production and hosting by Elsevier B.V. 2021-12 2021-10-27 /pmc/articles/PMC8548732/ /pubmed/34720609 http://dx.doi.org/10.1016/j.apr.2021.101247 Text en © 2021 Turkish National Committee for Air Pollution Research and Control. Production and hosting by Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Wang, Honglei
Tan, Yue
Zhang, Lianxia
Shen, Lijuan
Zhao, Tianliang
Dai, Qihang
Guan, Tianyi
Ke, Yue
Li, Xia
Characteristics of air quality in different climatic zones of China during the COVID-19 lockdown
title Characteristics of air quality in different climatic zones of China during the COVID-19 lockdown
title_full Characteristics of air quality in different climatic zones of China during the COVID-19 lockdown
title_fullStr Characteristics of air quality in different climatic zones of China during the COVID-19 lockdown
title_full_unstemmed Characteristics of air quality in different climatic zones of China during the COVID-19 lockdown
title_short Characteristics of air quality in different climatic zones of China during the COVID-19 lockdown
title_sort characteristics of air quality in different climatic zones of china during the covid-19 lockdown
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8548732/
https://www.ncbi.nlm.nih.gov/pubmed/34720609
http://dx.doi.org/10.1016/j.apr.2021.101247
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