Articles | Volume 24, issue 2
https://doi.org/10.5194/acp-24-1177-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-24-1177-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Jan 2024
Research article |
| 26 Jan 2024
| 26 Jan 2024
Meteorological characteristics of extreme ozone pollution events in China and their future predictions
Joint International Research Laboratory of Climate and Environment Change, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
Yang Zhou
Shanghai Baoshan Meteorology Bureau, Shanghai, China
Hailong Wang
Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USA
Mengyun Li
Joint International Research Laboratory of Climate and Environment Change, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
Huimin Li
Joint International Research Laboratory of Climate and Environment Change, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
Pinya Wang
Joint International Research Laboratory of Climate and Environment Change, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
Joint International Research Laboratory of Climate and Environment Change, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
Joint International Research Laboratory of Climate and Environment Change, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
Joint International Research Laboratory of Climate and Environment Change, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
Hong Liao
Joint International Research Laboratory of Climate and Environment Change, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
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Cited
8 citations as recorded by crossref.
- Seasonal Prediction of Ozone Pollution in Central-East China Using Machine Learning S. Yang et al. 10.1007/s41810-025-00310-7
- The Characteristics, Sources, and Health Risks of Volatile Organic Compounds in an Industrial Area of Nanjing T. Tan et al. 10.3390/toxics12120868
- Enhanced understanding of atmospheric blocking modulation on ozone dynamics within a high-resolution Earth system model W. Kou et al. 10.5194/acp-25-3029-2025
- Comparison of Surface Ozone Variability in Mountainous Forest Areas and Lowland Urban Areas in Southeast China X. Jiang et al. 10.3390/atmos15050519
- Using machine learning to unravel chemical and meteorological effects on ground-level ozone: Insights for ozone-climate control strategies Z. Li et al. 10.1016/j.envint.2025.109567
- Unique impacts of strong and westward-extended western Pacific subtropical high on ozone pollution over eastern China M. Li et al. 10.1016/j.envpol.2024.124515
- Evaluating spatiotemporal variations and exposure risk of ground-level ozone concentrations across China from 2000 to 2020 using high-resolution satellite-derived data Q. He et al. 10.5194/acp-25-6663-2025
- Carbonyl Compounds Observed at a Suburban Site during an Unusual Wintertime Ozone Pollution Event in Guangzhou A. Ge et al. 10.3390/atmos15101235
8 citations as recorded by crossref.
- Seasonal Prediction of Ozone Pollution in Central-East China Using Machine Learning S. Yang et al. 10.1007/s41810-025-00310-7
- The Characteristics, Sources, and Health Risks of Volatile Organic Compounds in an Industrial Area of Nanjing T. Tan et al. 10.3390/toxics12120868
- Enhanced understanding of atmospheric blocking modulation on ozone dynamics within a high-resolution Earth system model W. Kou et al. 10.5194/acp-25-3029-2025
- Comparison of Surface Ozone Variability in Mountainous Forest Areas and Lowland Urban Areas in Southeast China X. Jiang et al. 10.3390/atmos15050519
- Using machine learning to unravel chemical and meteorological effects on ground-level ozone: Insights for ozone-climate control strategies Z. Li et al. 10.1016/j.envint.2025.109567
- Unique impacts of strong and westward-extended western Pacific subtropical high on ozone pollution over eastern China M. Li et al. 10.1016/j.envpol.2024.124515
- Evaluating spatiotemporal variations and exposure risk of ground-level ozone concentrations across China from 2000 to 2020 using high-resolution satellite-derived data Q. He et al. 10.5194/acp-25-6663-2025
- Carbonyl Compounds Observed at a Suburban Site during an Unusual Wintertime Ozone Pollution Event in Guangzhou A. Ge et al. 10.3390/atmos15101235
Latest update: 15 Jul 2025
Short summary
This study reveals that extreme ozone pollution over the North China Plain and Yangtze River Delta is due to the chemical production related to hot and dry conditions, and the regional transport explains the ozone pollution over the Sichuan Basin and Pearl River Delta. The frequency of meteorological conditions of the extreme ozone pollution increases from the past to the future. The sustainable scenario is the optimal path to retaining clean air in China in the future.
This study reveals that extreme ozone pollution over the North China Plain and Yangtze River...
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