Articles | Volume 23, issue 2
https://doi.org/10.5194/acp-23-1131-2023
© Author(s) 2023. 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-23-1131-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Jan 2023
Research article |
| 23 Jan 2023
| 23 Jan 2023
Climate-driven deterioration of future ozone pollution in Asia predicted by machine learning with multi-source data
Huimin Li
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric
Environment and Equipment Technology, School of Environmental Science &
Engineering, Nanjing University of Information Science & Technology,
Nanjing, Jiangsu, China
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric
Environment and Equipment Technology, School of Environmental Science &
Engineering, Nanjing University of Information Science & Technology,
Nanjing, Jiangsu, China
Jianbing Jin
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric
Environment and Equipment Technology, School of Environmental Science &
Engineering, Nanjing University of Information Science & Technology,
Nanjing, Jiangsu, China
Hailong Wang
Atmospheric Sciences and Global Change Division, Pacific Northwest
National Laboratory, Richland, Washington, USA
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric
Environment and Equipment Technology, School of Environmental Science &
Engineering, Nanjing University of Information Science & Technology,
Nanjing, Jiangsu, China
Pinya Wang
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric
Environment and Equipment Technology, School of Environmental Science &
Engineering, Nanjing University of Information Science & Technology,
Nanjing, Jiangsu, China
Hong Liao
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric
Environment and Equipment Technology, School of Environmental Science &
Engineering, Nanjing University of Information Science & Technology,
Nanjing, Jiangsu, China
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Cited
14 citations as recorded by crossref.
- The joint effect of long-term exposure to multiple air pollutants on non-accidental and cause-specific mortality: A longitudinal cohort study X. Wei et al. 10.1016/j.jhazmat.2024.134507
- Ozone exceedance forecasting with enhanced extreme instance augmentation: A case study in Germany T. Deng et al. 10.1016/j.envsoft.2024.106162
- Rapid reduction of air pollution and short-term exposure risks in China H. Fan et al. 10.1016/j.jes.2023.11.002
- 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
- Large differences of highly oxygenated organic molecules (HOMs) and low-volatile species in secondary organic aerosols (SOAs) formed from ozonolysis of β-pinene and limonene D. Liu et al. 10.5194/acp-23-8383-2023
- Meteorological and anthropogenic drivers of surface ozone change in the North China Plain in 2015–2021 M. Wang et al. 10.1016/j.scitotenv.2023.167763
- Contrasting changes in ozone during 2019–2021 between eastern and the other regions of China attributed to anthropogenic emissions and meteorological conditions Y. Ni et al. 10.1016/j.scitotenv.2023.168272
- Impacts of projected changes in sea surface temperature on ozone pollution in China toward carbon neutrality J. Zhu et al. 10.1016/j.scitotenv.2024.170024
- Meteorological characteristics of extreme ozone pollution events in China and their future predictions Y. Yang et al. 10.5194/acp-24-1177-2024
- Understanding the variability of ground-level ozone and fine particulate matter over the Tibetan plateau with data-driven approach H. Zhong et al. 10.1016/j.jhazmat.2024.135341
- Explainable Machine Learning Reveals the Unknown Sources of Atmospheric HONO during COVID-19 Z. Gao et al. 10.1021/acsestair.4c00087
- A review of the CAMx, CMAQ, WRF-Chem and NAQPMS models: Application, evaluation and uncertainty factors Z. Gao & X. Zhou 10.1016/j.envpol.2023.123183
- Uncovering the evolution of ozone pollution in China: A spatiotemporal characteristics reconstruction from 1980 to 2021 S. Ding et al. 10.1016/j.atmosres.2024.107472
- Spatiotemporal modeling of air pollutant concentrations in Germany using machine learning V. Balamurugan et al. 10.5194/acp-23-10267-2023
14 citations as recorded by crossref.
- The joint effect of long-term exposure to multiple air pollutants on non-accidental and cause-specific mortality: A longitudinal cohort study X. Wei et al. 10.1016/j.jhazmat.2024.134507
- Ozone exceedance forecasting with enhanced extreme instance augmentation: A case study in Germany T. Deng et al. 10.1016/j.envsoft.2024.106162
- Rapid reduction of air pollution and short-term exposure risks in China H. Fan et al. 10.1016/j.jes.2023.11.002
- 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
- Large differences of highly oxygenated organic molecules (HOMs) and low-volatile species in secondary organic aerosols (SOAs) formed from ozonolysis of β-pinene and limonene D. Liu et al. 10.5194/acp-23-8383-2023
- Meteorological and anthropogenic drivers of surface ozone change in the North China Plain in 2015–2021 M. Wang et al. 10.1016/j.scitotenv.2023.167763
- Contrasting changes in ozone during 2019–2021 between eastern and the other regions of China attributed to anthropogenic emissions and meteorological conditions Y. Ni et al. 10.1016/j.scitotenv.2023.168272
- Impacts of projected changes in sea surface temperature on ozone pollution in China toward carbon neutrality J. Zhu et al. 10.1016/j.scitotenv.2024.170024
- Meteorological characteristics of extreme ozone pollution events in China and their future predictions Y. Yang et al. 10.5194/acp-24-1177-2024
- Understanding the variability of ground-level ozone and fine particulate matter over the Tibetan plateau with data-driven approach H. Zhong et al. 10.1016/j.jhazmat.2024.135341
- Explainable Machine Learning Reveals the Unknown Sources of Atmospheric HONO during COVID-19 Z. Gao et al. 10.1021/acsestair.4c00087
- A review of the CAMx, CMAQ, WRF-Chem and NAQPMS models: Application, evaluation and uncertainty factors Z. Gao & X. Zhou 10.1016/j.envpol.2023.123183
- Uncovering the evolution of ozone pollution in China: A spatiotemporal characteristics reconstruction from 1980 to 2021 S. Ding et al. 10.1016/j.atmosres.2024.107472
- Spatiotemporal modeling of air pollutant concentrations in Germany using machine learning V. Balamurugan et al. 10.5194/acp-23-10267-2023
Latest update: 23 Nov 2024
Short summary
Future climate change will aggravate ozone pollution in Asia, especially in high-forcing scenarios. Ozone pollution in China will expand from North China to South China and extend into the cold season in a warmer future. The emphasis of this work is to quantify the impacts of future climate change on O3 pollution in Asia, which is of great significance for future O3 pollution mitigation strategies.
Future climate change will aggravate ozone pollution in Asia, especially in high-forcing...
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