Full-coverage mapping and spatiotemporal variations of ground-level ozone (O3) pollution from 2013 to 2020 across China

Ozone (O3) is an important trace and greenhouse gas in the atmosphere, posing a threat to the ecological environment and human health at the ground level. Large-scale and long-term studies of O3 pollution in China are few due to highly limited direct ground and satellite measurements. This study off...

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Vydáno v:	Remote sensing of environment Ročník 270; s. 112775
Hlavní autoři:	Wei, Jing, Li, Zhanqing, Li, Ke, Dickerson, Russell R., Pinker, Rachel T., Wang, Jun, Liu, Xiong, Sun, Lin, Xue, Wenhao, Cribb, Maureen
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Elsevier Inc 01.03.2022 Elsevier BV
Témata:	Air pollution Air pollution control Anthropogenic factors China Coronaviruses Coverage COVID-19 COVID-19 infection data collection Datasets Disease transmission Emission inventories Emissions Ensemble learning environment Environmental health Greenhouse gases Ground level Ground-based observation Growth rate human health inventories Ozone probability Radiant flux density Remote sensing satellites Solar radiation Surface temperature China COVID-19 Ozone Air pollution Ensemble learning China
ISSN:	0034-4257, 1879-0704
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Abstract	Ozone (O3) is an important trace and greenhouse gas in the atmosphere, posing a threat to the ecological environment and human health at the ground level. Large-scale and long-term studies of O3 pollution in China are few due to highly limited direct ground and satellite measurements. This study offers a new perspective to estimate ground-level O3 from solar radiation intensity and surface temperature by employing an extended ensemble learning of the space-time extremely randomized trees (STET) model, together with ground-based observations, remote sensing products, atmospheric reanalysis, and an emission inventory. A full-coverage (100%), high-resolution (10 km) and high-quality daily maximum 8-h average (MDA8) ground-level O3 dataset covering China (called ChinaHighO3) from 2013 to 2020 was generated. Our MDA8 O3 estimates (predictions) are reliable, with an average out-of-sample (out-of-station) coefficient of determination of 0.87 (0.80) and root-mean-square error of 17.10 (21.10) μg/m3 in China. The unique advantage of the full coverage of our dataset allowed us to accurately capture a short-term severe O3 pollution exposure event that took place from 23 April to 8 May in 2020. Also, a rapid increase and recovery of O3 concentrations associated with variations in anthropogenic emissions were seen during and after the COVID-19 lockdown, respectively. Trends in O3 concentration showed an average growth rate of 2.49 μg/m3/yr (p < 0.001) from 2013 to 2020, along with the continuous expansion of polluted areas exceeding the daily O3 standard (i.e., MDA8 O3 = 160 μg/m3). Summertime O3 concentrations and the probability of occurrence of daily O3 pollution have significantly increased since 2015, especially in the North China Plain and the main air pollution transmission belt (i.e., the “2 + 26” cities). However, a decline in both was seen in 2020, mainly due to the coordinated control of air pollution and ongoing COVID-19 effects. This carefully vetted and smoothed dataset is valuable for studies on air pollution and environmental health in China. •A full-coverage of daily MDA8 O3 dataset (10 km) from 2013 to 2020 in China is generated.•The ChinaHighO3 dataset yields a high-quality information (CV-R2 = 0.87, RMSE = 17.10 μg/m3).•Ground-level O3 showed a significant increasing trend of 2.49 μg/m3/yr (p < 0.001) during 2013–2020.•Rapid O3 increase and recovery were observed during and after the COVID-19 lockdown.
AbstractList	Ozone (O₃) is an important trace and greenhouse gas in the atmosphere, posing a threat to the ecological environment and human health at the ground level. Large-scale and long-term studies of O₃ pollution in China are few due to highly limited direct ground and satellite measurements. This study offers a new perspective to estimate ground-level O₃ from solar radiation intensity and surface temperature by employing an extended ensemble learning of the space-time extremely randomized trees (STET) model, together with ground-based observations, remote sensing products, atmospheric reanalysis, and an emission inventory. A full-coverage (100%), high-resolution (10 km) and high-quality daily maximum 8-h average (MDA8) ground-level O₃ dataset covering China (called ChinaHighO₃) from 2013 to 2020 was generated. Our MDA8 O₃ estimates (predictions) are reliable, with an average out-of-sample (out-of-station) coefficient of determination of 0.87 (0.80) and root-mean-square error of 17.10 (21.10) μg/m³ in China. The unique advantage of the full coverage of our dataset allowed us to accurately capture a short-term severe O₃ pollution exposure event that took place from 23 April to 8 May in 2020. Also, a rapid increase and recovery of O₃ concentrations associated with variations in anthropogenic emissions were seen during and after the COVID-19 lockdown, respectively. Trends in O₃ concentration showed an average growth rate of 2.49 μg/m³/yr (p < 0.001) from 2013 to 2020, along with the continuous expansion of polluted areas exceeding the daily O₃ standard (i.e., MDA8 O₃ = 160 μg/m³). Summertime O₃ concentrations and the probability of occurrence of daily O₃ pollution have significantly increased since 2015, especially in the North China Plain and the main air pollution transmission belt (i.e., the “2 + 26” cities). However, a decline in both was seen in 2020, mainly due to the coordinated control of air pollution and ongoing COVID-19 effects. This carefully vetted and smoothed dataset is valuable for studies on air pollution and environmental health in China. Ozone (O3) is an important trace and greenhouse gas in the atmosphere, posing a threat to the ecological environment and human health at the ground level. Large-scale and long-term studies of O3 pollution in China are few due to highly limited direct ground and satellite measurements. This study offers a new perspective to estimate ground-level O3 from solar radiation intensity and surface temperature by employing an extended ensemble learning of the space-time extremely randomized trees (STET) model, together with ground-based observations, remote sensing products, atmospheric reanalysis, and an emission inventory. A full-coverage (100%), high-resolution (10 km) and high-quality daily maximum 8-h average (MDA8) ground-level O3 dataset covering China (called ChinaHighO3) from 2013 to 2020 was generated. Our MDA8 O3 estimates (predictions) are reliable, with an average out-of-sample (out-of-station) coefficient of determination of 0.87 (0.80) and root-mean-square error of 17.10 (21.10) μg/m3 in China. The unique advantage of the full coverage of our dataset allowed us to accurately capture a short-term severe O3 pollution exposure event that took place from 23 April to 8 May in 2020. Also, a rapid increase and recovery of O3 concentrations associated with variations in anthropogenic emissions were seen during and after the COVID-19 lockdown, respectively. Trends in O3 concentration showed an average growth rate of 2.49 μg/m3/yr (p < 0.001) from 2013 to 2020, along with the continuous expansion of polluted areas exceeding the daily O3 standard (i.e., MDA8 O3 = 160 μg/m3). Summertime O3 concentrations and the probability of occurrence of daily O3 pollution have significantly increased since 2015, especially in the North China Plain and the main air pollution transmission belt (i.e., the "2 + 26" cities). However, a decline in both was seen in 2020, mainly due to the coordinated control of air pollution and ongoing COVID-19 effects. This carefully vetted and smoothed dataset is valuable for studies on air pollution and environmental health in China. Ozone (O3) is an important trace and greenhouse gas in the atmosphere, posing a threat to the ecological environment and human health at the ground level. Large-scale and long-term studies of O3 pollution in China are few due to highly limited direct ground and satellite measurements. This study offers a new perspective to estimate ground-level O3 from solar radiation intensity and surface temperature by employing an extended ensemble learning of the space-time extremely randomized trees (STET) model, together with ground-based observations, remote sensing products, atmospheric reanalysis, and an emission inventory. A full-coverage (100%), high-resolution (10 km) and high-quality daily maximum 8-h average (MDA8) ground-level O3 dataset covering China (called ChinaHighO3) from 2013 to 2020 was generated. Our MDA8 O3 estimates (predictions) are reliable, with an average out-of-sample (out-of-station) coefficient of determination of 0.87 (0.80) and root-mean-square error of 17.10 (21.10) μg/m3 in China. The unique advantage of the full coverage of our dataset allowed us to accurately capture a short-term severe O3 pollution exposure event that took place from 23 April to 8 May in 2020. Also, a rapid increase and recovery of O3 concentrations associated with variations in anthropogenic emissions were seen during and after the COVID-19 lockdown, respectively. Trends in O3 concentration showed an average growth rate of 2.49 μg/m3/yr (p < 0.001) from 2013 to 2020, along with the continuous expansion of polluted areas exceeding the daily O3 standard (i.e., MDA8 O3 = 160 μg/m3). Summertime O3 concentrations and the probability of occurrence of daily O3 pollution have significantly increased since 2015, especially in the North China Plain and the main air pollution transmission belt (i.e., the “2 + 26” cities). However, a decline in both was seen in 2020, mainly due to the coordinated control of air pollution and ongoing COVID-19 effects. This carefully vetted and smoothed dataset is valuable for studies on air pollution and environmental health in China. •A full-coverage of daily MDA8 O3 dataset (10 km) from 2013 to 2020 in China is generated.•The ChinaHighO3 dataset yields a high-quality information (CV-R2 = 0.87, RMSE = 17.10 μg/m3).•Ground-level O3 showed a significant increasing trend of 2.49 μg/m3/yr (p < 0.001) during 2013–2020.•Rapid O3 increase and recovery were observed during and after the COVID-19 lockdown.
ArticleNumber	112775
Author	Cribb, Maureen Xue, Wenhao Liu, Xiong Wei, Jing Pinker, Rachel T. Li, Ke Sun, Lin Dickerson, Russell R. Wang, Jun Li, Zhanqing
Author_xml	– sequence: 1 givenname: Jing surname: Wei fullname: Wei, Jing email: weijing_rs@163.com organization: Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA – sequence: 2 givenname: Zhanqing surname: Li fullname: Li, Zhanqing email: zli@atmos.umd.edu organization: Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA – sequence: 3 givenname: Ke surname: Li fullname: Li, Ke organization: Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, China – sequence: 4 givenname: Russell R. surname: Dickerson fullname: Dickerson, Russell R. organization: Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA – sequence: 5 givenname: Rachel T. surname: Pinker fullname: Pinker, Rachel T. organization: Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA – sequence: 6 givenname: Jun surname: Wang fullname: Wang, Jun organization: Department of Chemical and Biochemical Engineering, Iowa Technology Institute, and Center for Global and Regional Environmental Research, University of Iowa, Iowa City, IA, USA – sequence: 7 givenname: Xiong surname: Liu fullname: Liu, Xiong organization: Atomic and Molecular Physics Division, Harvard Smithsonian Center for Astrophysics, Cambridge, MA, USA – sequence: 8 givenname: Lin surname: Sun fullname: Sun, Lin organization: College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, China – sequence: 9 givenname: Wenhao surname: Xue fullname: Xue, Wenhao organization: School of Economics, Qingdao University, Qingdao, China – sequence: 10 givenname: Maureen surname: Cribb fullname: Cribb, Maureen organization: Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
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Snippet	Ozone (O3) is an important trace and greenhouse gas in the atmosphere, posing a threat to the ecological environment and human health at the ground level.... Ozone (O₃) is an important trace and greenhouse gas in the atmosphere, posing a threat to the ecological environment and human health at the ground level....
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SubjectTerms	Air pollution Air pollution control Anthropogenic factors China Coronaviruses Coverage COVID-19 COVID-19 infection data collection Datasets Disease transmission Emission inventories Emissions Ensemble learning environment Environmental health Greenhouse gases Ground level Ground-based observation Growth rate human health inventories Ozone probability Radiant flux density Remote sensing satellites Solar radiation Surface temperature
Title	Full-coverage mapping and spatiotemporal variations of ground-level ozone (O3) pollution from 2013 to 2020 across China
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