Historical and future changes and present-day uncertainties of ozone in China from CMIP6 models

Abstract. Ozone (O3) contributes to global climate change and poses a direct threat to human health. This study analyzes historical and future changes, as well as current uncertainties, in surface O3 concentrations in China, based on CMIP6 and the Tracking Air Pollution in China (TAP) dataset. The results are as follows: (1) The Multi-Model Ensemble Mean (MME) of CMIP6 simulated O3 concentrations is higher during June–August (JJA), averaging 105 μg·m-3, and lowest during December–February (DJF) at 55 μg·m-3. (2) CMIP6 models generally underestimate O3 concentrations in most regions of China, with the most significant underestimation occurring in East China. (3) The MME-simulated O3 concentrations exhibit lower Bias, MAE, and RMSE over natural land surfaces compared to those over anthropogenic land surfaces. The Bias reaches its minimum under cloudy conditions and peaks under partly cloudy conditions. Furthermore, the Bias generally increases with rising PM2.5 concentrations, however, once PM2.5 exceeds a specific threshold, the Bias begins to decline. (4) Over the entire historical period, the MME simulates an increase of 39.3 μg·m-3 in the annual mean surface O3 concentration in China. (5) Under future SSP scenarios, MME projects generally increasing O3 under weak mitigation (SSP3-7.0), with East China rising by 26.9 %. Strong mitigation (SSP1-2.6) leads to widespread decreases, especially in Southwest and South China (>30 μg·m-3). (6) Differences in climate treatment, circulation, chemistry, and precursor emissions create substantial uncertainties, emphasizing the need to understand how emissions (including precursors and PM2.5), climate, and model processes jointly affect future O3 projections.

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Published
2025-09-25
DOI
https://doi.org/10.5194/egusphere-2025-4348
Primary Topic
Atmospheric Ozone and Climate
Type
article
Field-Weighted Citation Impact
0.00

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Historical and future changes and present-day uncertainties of ozone in China from CMIP6 models

Yonghang Chen, Hua Zhang, Zhili Wang, Shuai Li et al.
Atmospheric Ozone and Climate
article

Historical and future changes and present-day uncertainties of ozone in China from CMIP6 models

Yonghang Chen, Hua Zhang, Zhili Wang, Shuai Li, Qi Chen, Qi An, Xinping Wu
article en

Abstract

Abstract. Ozone (O3) contributes to global climate change and poses a direct threat to human health. This study analyzes historical and future changes, as well as current uncertainties, in surface O3 concentrations in China, based on CMIP6 and the Tracking Air Pollution in China (TAP) dataset. The results are as follows: (1) The Multi-Model Ensemble Mean (MME) of CMIP6 simulated O3 concentrations is higher during June–August (JJA), averaging 105 μg·m-3, and lowest during December–February (DJF) at 55 μg·m-3. (2) CMIP6 models generally underestimate O3 concentrations in most regions of China, with the most significant underestimation occurring in East China. (3) The MME-simulated O3 concentrations exhibit lower Bias, MAE, and RMSE over natural land surfaces compared to those over anthropogenic land surfaces. The Bias reaches its minimum under cloudy conditions and peaks under partly cloudy conditions. Furthermore, the Bias generally increases with rising PM2.5 concentrations, however, once PM2.5 exceeds a specific threshold, the Bias begins to decline. (4) Over the entire historical period, the MME simulates an increase of 39.3 μg·m-3 in the annual mean surface O3 concentration in China. (5) Under future SSP scenarios, MME projects generally increasing O3 under weak mitigation (SSP3-7.0), with East China rising by 26.9 %. Strong mitigation (SSP1-2.6) leads to widespread decreases, especially in Southwest and South China (>30 μg·m-3). (6) Differences in climate treatment, circulation, chemistry, and precursor emissions create substantial uncertainties, emphasizing the need to understand how emissions (including precursors and PM2.5), climate, and model processes jointly affect future O3 projections.

China Meteorological Administration (CN), Donghua University (CN), CITIC Group (China) (CN), Chinese Academy of Meteorological Sciences (CN), Beijing Meteorological Bureau (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 69%
Atmospheric Ozone and Climate
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