Articles | Volume 25, issue 1
https://doi.org/10.5194/acp-25-347-2025
© Author(s) 2025. 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-25-347-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 Jan 2025
Research article |
| 09 Jan 2025
| 09 Jan 2025
Opposing trends in the peak and low ozone concentrations in eastern China: anthropogenic and meteorological influences
Zhuang Wang
Anhui Province Key Laboratory of Atmospheric Science and Satellite Remote Sensing, Anhui Institute of Meteorological Sciences, Hefei 230031, China
Shouxian National Climatology Observatory, Huaihe River Basin Typical Farm Eco-meteorological Experiment Field of CMA, Shouxian 232200, China
Chune Shi
Anhui Province Key Laboratory of Atmospheric Science and Satellite Remote Sensing, Anhui Institute of Meteorological Sciences, Hefei 230031, China
Shouxian National Climatology Observatory, Huaihe River Basin Typical Farm Eco-meteorological Experiment Field of CMA, Shouxian 232200, China
Hao Zhang
Anhui Province Key Laboratory of Atmospheric Science and Satellite Remote Sensing, Anhui Institute of Meteorological Sciences, Hefei 230031, China
Shouxian National Climatology Observatory, Huaihe River Basin Typical Farm Eco-meteorological Experiment Field of CMA, Shouxian 232200, China
Xianguang Ji
Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei 230601, China
Yizhi Zhu
School of Environmental Science and Engineering, Suzhou University of Science and Technology, Suzhou 215009, China
Congzi Xia
Institute of Big Data for Vocational Education, Guangdong Polytechnic of Science and Technology, Zhuhai 519000, China
Xiaoyun Sun
Anhui Province Key Laboratory of Atmospheric Science and Satellite Remote Sensing, Anhui Institute of Meteorological Sciences, Hefei 230031, China
Shouxian National Climatology Observatory, Huaihe River Basin Typical Farm Eco-meteorological Experiment Field of CMA, Shouxian 232200, China
Xinfeng Lin
Shouxian National Climatology Observatory, Huaihe River Basin Typical Farm Eco-meteorological Experiment Field of CMA, Shouxian 232200, China
Shaowei Yan
Shouxian National Climatology Observatory, Huaihe River Basin Typical Farm Eco-meteorological Experiment Field of CMA, Shouxian 232200, China
Suyao Wang
Huaibei Meteorological Bureau, Huaibei 235000, Anhui, China
Yuan Zhou
Jiangxi Ecological Meteorology Center, Nanchang 330096, China
Nanchang National Climate Observatory, Nanchang 330043, China
Key Lab of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
Anhui Province Key Laboratory of Atmospheric Science and Satellite Remote Sensing, Anhui Institute of Meteorological Sciences, Hefei 230031, China
Shouxian National Climatology Observatory, Huaihe River Basin Typical Farm Eco-meteorological Experiment Field of CMA, Shouxian 232200, China
Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China
Key Lab of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, University of Science and Technology of China, Hefei 230026, China
Viewed
Total article views: 4,703 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 30 Apr 2024)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 3,442 | 1,080 | 181 | 4,703 | 397 | 186 | 299 |
- HTML: 3,442
- PDF: 1,080
- XML: 181
- Total: 4,703
- Supplement: 397
- BibTeX: 186
- EndNote: 299
Total article views: 2,132 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 09 Jan 2025)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 1,655 | 405 | 72 | 2,132 | 102 | 60 | 86 |
- HTML: 1,655
- PDF: 405
- XML: 72
- Total: 2,132
- Supplement: 102
- BibTeX: 60
- EndNote: 86
Total article views: 2,571 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 30 Apr 2024)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 1,787 | 675 | 109 | 2,571 | 295 | 126 | 213 |
- HTML: 1,787
- PDF: 675
- XML: 109
- Total: 2,571
- Supplement: 295
- BibTeX: 126
- EndNote: 213
Viewed (geographical distribution)
Total article views: 4,703 (including HTML, PDF, and XML)
Thereof 4,703 with geography defined
and 0 with unknown origin.
Total article views: 2,132 (including HTML, PDF, and XML)
Thereof 2,132 with geography defined
and 0 with unknown origin.
Total article views: 2,571 (including HTML, PDF, and XML)
Thereof 2,571 with geography defined
and 0 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
15 citations as recorded by crossref.
- Trend analysis coupled with machine learning to reveal multi-scale formation regimes of surface ozone in the Yangtze River Delta of China L. Tong et al.
- Amplification of Surface Ozone by the Aerosol Direct Effect under COVID-19 Lockdown in Shanghai, China Z. Sun et al.
- Decadal air quality dynamics in the Yangtze River Delta: Evidence from machine learning–driven analysis S. Zaib et al.
- Interaction pathways of CO, NO2, and PM2.5 on cool season ozone: Insights from data-based model and mechanism-based model C. Liu et al.
- Carbonyl Compound Reduction Mitigates Ozone Pollution: Lessons from Pollution Control during the 19th Asian Games in Hangzhou, China G. Guo et al.
- Multi-scale analysis of ozone pollution Shanghai based on meteorological normalization: A case study of multi-model collaborative machine learning framework and MCM coupling mechanism M. Wu et al.
- Observational evidence of stronger subsidence and more active photochemistry aloft associated with severe ozone pollution over rural areas Z. Wang et al.
- High-resolution anthropogenic emission inventory for China (2015–2024): Spatiotemporal changes and environmental application D. Li et al.
- Unveiling the paradox of reduced surface solar radiation in February 2020 during COVID-19 lockdown: aerosol-cloud-dynamics interactions in Beijing X. Zhang et al.
- A multiyear concentration and flux-based O3 risk assessment of winter wheat in China: Trends and drivers X. Yuan et al.
- Impact of tropical cyclone intensity evolution under different tracks on ozone in the Pearl River Delta, China S. Ouyang et al.
- Extreme ozone pollution over North China linked to Rossby waves induced by North Atlantic sea surface temperature F. Wang et al.
- Machine-learning-assisted evaluation of heatwave impacts on surface ozone in China K. Zhang et al.
- Differentiated evolutions of co-occurrence of extreme heat and ozone pollution over the middle-lower Yangtze River basin during 2018–2024 X. Sun et al.
- The impact of China's Clean Air Action and future strategies: Actions targeting regionally dominant sources X. Peng et al.
15 citations as recorded by crossref.
- Trend analysis coupled with machine learning to reveal multi-scale formation regimes of surface ozone in the Yangtze River Delta of China L. Tong et al.
- Amplification of Surface Ozone by the Aerosol Direct Effect under COVID-19 Lockdown in Shanghai, China Z. Sun et al.
- Decadal air quality dynamics in the Yangtze River Delta: Evidence from machine learning–driven analysis S. Zaib et al.
- Interaction pathways of CO, NO2, and PM2.5 on cool season ozone: Insights from data-based model and mechanism-based model C. Liu et al.
- Carbonyl Compound Reduction Mitigates Ozone Pollution: Lessons from Pollution Control during the 19th Asian Games in Hangzhou, China G. Guo et al.
- Multi-scale analysis of ozone pollution Shanghai based on meteorological normalization: A case study of multi-model collaborative machine learning framework and MCM coupling mechanism M. Wu et al.
- Observational evidence of stronger subsidence and more active photochemistry aloft associated with severe ozone pollution over rural areas Z. Wang et al.
- High-resolution anthropogenic emission inventory for China (2015–2024): Spatiotemporal changes and environmental application D. Li et al.
- Unveiling the paradox of reduced surface solar radiation in February 2020 during COVID-19 lockdown: aerosol-cloud-dynamics interactions in Beijing X. Zhang et al.
- A multiyear concentration and flux-based O3 risk assessment of winter wheat in China: Trends and drivers X. Yuan et al.
- Impact of tropical cyclone intensity evolution under different tracks on ozone in the Pearl River Delta, China S. Ouyang et al.
- Extreme ozone pollution over North China linked to Rossby waves induced by North Atlantic sea surface temperature F. Wang et al.
- Machine-learning-assisted evaluation of heatwave impacts on surface ozone in China K. Zhang et al.
- Differentiated evolutions of co-occurrence of extreme heat and ozone pollution over the middle-lower Yangtze River basin during 2018–2024 X. Sun et al.
- The impact of China's Clean Air Action and future strategies: Actions targeting regionally dominant sources X. Peng et al.
Saved (final revised paper)
Latest update: 18 May 2026
Short summary
This study attempts to explain the surface ozone background and typical and peak trends in eastern China by combining a large number of ground-based and satellite observations. We found diametrically opposed trends in peak (decreasing) and low (increasing) ozone concentrations. Anthropogenic emissions primarily drive trends in low and peak ozone concentrations in eastern China, though meteorological effects also play a role.
This study attempts to explain the surface ozone background and typical and peak trends in...
Altmetrics
Final-revised paper
Preprint