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.
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
13 citations as recorded by crossref.
- Impacts of sea-land breeze on the coastal ozone in the Pearl River Delta, China C. Liu et al. 10.1016/j.jes.2025.08.037
- The Characteristics, Sources, and Health Risks of Volatile Organic Compounds in an Industrial Area of Nanjing T. Tan et al. 10.3390/toxics12120868
- 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
- Tropospheric ozone trends and attributions over East and Southeast Asia in 1995–2019: an integrated assessment using statistical methods, machine learning models, and multiple chemical transport models X. Lu et al. 10.5194/acp-25-7991-2025
- Carbonyl Compounds Observed at a Suburban Site during an Unusual Wintertime Ozone Pollution Event in Guangzhou A. Ge et al. 10.3390/atmos15101235
- Seasonal Prediction of Ozone Pollution in Central-East China Using Machine Learning S. Yang et al. 10.1007/s41810-025-00310-7
- 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
- Ultra-high-resolution modeling of ground-level ozone for long-term exposure risk assessment driven by GTR-transformer J. Chen et al. 10.1016/j.envint.2025.109705
- 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
- Amplification of Surface Ozone by the Aerosol Direct Effect under COVID-19 Lockdown in Shanghai, China Z. Sun et al. 10.1021/acsestair.5c00130
- VOCs-driven ozone extremes during dry and wet heatwaves in the Jiangsu–Shandong–Henan–Anhui Boundary: Integrating meteorological forcings and SHAP interpretation C. Wang et al. 10.1016/j.atmosres.2025.108396
13 citations as recorded by crossref.
- Impacts of sea-land breeze on the coastal ozone in the Pearl River Delta, China C. Liu et al. 10.1016/j.jes.2025.08.037
- The Characteristics, Sources, and Health Risks of Volatile Organic Compounds in an Industrial Area of Nanjing T. Tan et al. 10.3390/toxics12120868
- 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
- Tropospheric ozone trends and attributions over East and Southeast Asia in 1995–2019: an integrated assessment using statistical methods, machine learning models, and multiple chemical transport models X. Lu et al. 10.5194/acp-25-7991-2025
- Carbonyl Compounds Observed at a Suburban Site during an Unusual Wintertime Ozone Pollution Event in Guangzhou A. Ge et al. 10.3390/atmos15101235
- Seasonal Prediction of Ozone Pollution in Central-East China Using Machine Learning S. Yang et al. 10.1007/s41810-025-00310-7
- 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
- Ultra-high-resolution modeling of ground-level ozone for long-term exposure risk assessment driven by GTR-transformer J. Chen et al. 10.1016/j.envint.2025.109705
- 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
- Amplification of Surface Ozone by the Aerosol Direct Effect under COVID-19 Lockdown in Shanghai, China Z. Sun et al. 10.1021/acsestair.5c00130
- VOCs-driven ozone extremes during dry and wet heatwaves in the Jiangsu–Shandong–Henan–Anhui Boundary: Integrating meteorological forcings and SHAP interpretation C. Wang et al. 10.1016/j.atmosres.2025.108396
Latest update: 30 Oct 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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