Articles | Volume 24, issue 6
https://doi.org/10.5194/acp-24-3541-2024
© 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-24-3541-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Mar 2024
Research article |
| 21 Mar 2024
| 21 Mar 2024
Mixing-layer-height-referenced ozone vertical distribution in the lower troposphere of Chinese megacities: stratification, classification, and meteorological and photochemical mechanisms
Zhiheng Liao
Institute of Urban Meteorology, China Meteorological Administration, Beijing, China
School of Atmospheric Sciences, Sun Yat-Sen University, Zhuhai, China
Department of Geography, Hong Kong Baptist University, Hong Kong SAR, China
Jinqiang Zhang
Key Laboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
Jiaren Sun
Key Laboratory of Urban Ecological Environmental Simulation and Protection of Ministry of Environmental Protection, South China Institute of Environmental Sciences, Ministry of Ecology and Environment of the PRC, Guangzhou, China
Jiannong Quan
Institute of Urban Meteorology, China Meteorological Administration, Beijing, China
Xingcan Jia
Institute of Urban Meteorology, China Meteorological Administration, Beijing, China
Yubing Pan
Institute of Urban Meteorology, China Meteorological Administration, Beijing, China
Shaojia Fan
CORRESPONDING AUTHOR
School of Atmospheric Sciences, Sun Yat-Sen University, Zhuhai, China
Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Key Laboratory of Tropical Atmosphere–Ocean System, Ministry of Education, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
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Cited
16 citations as recorded by crossref.
- Exploring Aerosol Vertical Distributions and Their Influencing Factors: Insight from MAX-DOAS and Machine Learning S. Zhang et al. https://doi.org/10.1021/acs.est.4c14483
- Overestimation of Stratospheric Intrusion Impacts on Surface Ozone in China H. Wang et al. https://doi.org/10.1021/acs.est.6c03439
- Rainfall-induced changes in vertical O3 and SO2 within and above a boreal-temperate forest Y. Zhang et al. https://doi.org/10.1016/j.agrformet.2025.110748
- Influence of weather patterns on ground-level ozone pollution: a 2023 summer case study in Jilin City with health risk assessment A. Akhtar et al. https://doi.org/10.1007/s10661-026-15520-w
- Quantitative impacts of dominant large-scale circulation systems on surface ozone pollution in China S. Zhang et al. https://doi.org/10.1016/j.jes.2024.07.015
- Shipborne lidar measurements of ozone over the southeastern coastal regions of China in winter L. Lv et al. https://doi.org/10.1016/j.envres.2025.121165
- Machine learning estimation of surface ozone using Sentinel-5P data and meteorological and ground observations A. Sam-Khaniani et al. https://doi.org/10.1016/j.asr.2026.04.089
- Widespread stratospheric intrusion influence on summer ozone pollution over China revealed by multi-site ozonesonde and validated EAC4 reanalysis Z. Liao et al. https://doi.org/10.5194/acp-25-14865-2025
- Seasonal Variations of the Impacts of Low-Level Jets on Surface Ozone Photochemistry in Beijing Y. Wang et al. https://doi.org/10.1021/acs.est.6c00516
- 2022年春季合肥市臭氧垂直分布特征及气象影响因素分析 李. Li Mei et al. https://doi.org/10.3788/AOS251884
- WRF-Chem Modeling of Tropospheric Ozone in the Coastal Cities of the Gulf of Finland G. Nerobelov et al. https://doi.org/10.3390/atmos15070775
- Constructing the 3D Spatial Distribution of the HCHO/NO2 Ratio via Satellite Observation and Machine Learning Model Z. Jiang et al. https://doi.org/10.1021/acs.est.4c12362
- Analysis of potential sources and influencing factors of O3 pollution in the Hexi region based on XGBoost and SHAP models P. Wang et al. https://doi.org/10.1016/j.uclim.2026.102860
- A dataset of vertical profiles of O3 and HONO from the hyperspectral vertical remote sensing network in China (2021–2024) T. Zou et al. https://doi.org/10.5194/essd-18-3559-2026
- Multi-scale impacts of Indochina biomass burnings on tropospheric ozone in coastal South China: Insights from long-term (2000–2024) observations Z. Liao et al. https://doi.org/10.1016/j.atmosres.2025.108465
- A selective review of ozone differential absorption lidar systems J. Ji et al. https://doi.org/10.1016/j.optlastec.2025.114603
16 citations as recorded by crossref.
- Exploring Aerosol Vertical Distributions and Their Influencing Factors: Insight from MAX-DOAS and Machine Learning S. Zhang et al. https://doi.org/10.1021/acs.est.4c14483
- Overestimation of Stratospheric Intrusion Impacts on Surface Ozone in China H. Wang et al. https://doi.org/10.1021/acs.est.6c03439
- Rainfall-induced changes in vertical O3 and SO2 within and above a boreal-temperate forest Y. Zhang et al. https://doi.org/10.1016/j.agrformet.2025.110748
- Influence of weather patterns on ground-level ozone pollution: a 2023 summer case study in Jilin City with health risk assessment A. Akhtar et al. https://doi.org/10.1007/s10661-026-15520-w
- Quantitative impacts of dominant large-scale circulation systems on surface ozone pollution in China S. Zhang et al. https://doi.org/10.1016/j.jes.2024.07.015
- Shipborne lidar measurements of ozone over the southeastern coastal regions of China in winter L. Lv et al. https://doi.org/10.1016/j.envres.2025.121165
- Machine learning estimation of surface ozone using Sentinel-5P data and meteorological and ground observations A. Sam-Khaniani et al. https://doi.org/10.1016/j.asr.2026.04.089
- Widespread stratospheric intrusion influence on summer ozone pollution over China revealed by multi-site ozonesonde and validated EAC4 reanalysis Z. Liao et al. https://doi.org/10.5194/acp-25-14865-2025
- Seasonal Variations of the Impacts of Low-Level Jets on Surface Ozone Photochemistry in Beijing Y. Wang et al. https://doi.org/10.1021/acs.est.6c00516
- 2022年春季合肥市臭氧垂直分布特征及气象影响因素分析 李. Li Mei et al. https://doi.org/10.3788/AOS251884
- WRF-Chem Modeling of Tropospheric Ozone in the Coastal Cities of the Gulf of Finland G. Nerobelov et al. https://doi.org/10.3390/atmos15070775
- Constructing the 3D Spatial Distribution of the HCHO/NO2 Ratio via Satellite Observation and Machine Learning Model Z. Jiang et al. https://doi.org/10.1021/acs.est.4c12362
- Analysis of potential sources and influencing factors of O3 pollution in the Hexi region based on XGBoost and SHAP models P. Wang et al. https://doi.org/10.1016/j.uclim.2026.102860
- A dataset of vertical profiles of O3 and HONO from the hyperspectral vertical remote sensing network in China (2021–2024) T. Zou et al. https://doi.org/10.5194/essd-18-3559-2026
- Multi-scale impacts of Indochina biomass burnings on tropospheric ozone in coastal South China: Insights from long-term (2000–2024) observations Z. Liao et al. https://doi.org/10.1016/j.atmosres.2025.108465
- A selective review of ozone differential absorption lidar systems J. Ji et al. https://doi.org/10.1016/j.optlastec.2025.114603
Saved (final revised paper)
Latest update: 30 Aug 2026
Short summary
This study collected 1897 ozonesondes from two Chinese megacities (Beijing and Hong Kong) in 2000–2022 to investigate the climatological vertical heterogeneity of lower-tropospheric ozone distribution with a mixing-layer-height-referenced (h-referenced) vertical coordinate system. This vertical coordinate system highlighted O3 stratification features existing at the mixing layer–free troposphere interface and provided a better understanding of O3 pollution in urban regions.
This study collected 1897 ozonesondes from two Chinese megacities (Beijing and Hong Kong) in...
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