Articles | Volume 21, issue 7
https://doi.org/10.5194/acp-21-5705-2021
© Author(s) 2021. 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-21-5705-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A study of the effect of aerosols on surface ozone through meteorology feedbacks over China
School of Atmospheric Sciences, Nanjing University, Nanjing, China
Leverhulme Centre for Wildfires, Environment and Society, Department of Physics, Imperial College London, London, UK
School of Intelligent Science and Control Engineering, Jinling Institute of Technology, Nanjing, China
Apostolos Voulgarakis
CORRESPONDING AUTHOR
Leverhulme Centre for Wildfires, Environment and Society, Department of Physics, Imperial College London, London, UK
School of Environmental Engineering, Technical University of Crete, Crete, Greece
Tijian Wang
CORRESPONDING AUTHOR
School of Atmospheric Sciences, Nanjing University, Nanjing, China
Matthew Kasoar
Leverhulme Centre for Wildfires, Environment and Society, Department of Physics, Imperial College London, London, UK
Chris Wells
Leverhulme Centre for Wildfires, Environment and Society, Department of Physics, Imperial College London, London, UK
Cheng Yuan
School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing, China
Sunil Varma
Leverhulme Centre for Wildfires, Environment and Society, Department of Physics, Imperial College London, London, UK
Laura Mansfield
Leverhulme Centre for Wildfires, Environment and Society, Department of Physics, Imperial College London, London, UK
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28 citations as recorded by crossref.
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- Potential Factors Contributing to Ozone Production in AQUAS–Kyoto Campaign in Summer 2020: Natural Source-Related Missing OH Reactivity and Heterogeneous HO2/RO2 Loss J. Li et al. 10.1021/acs.est.2c03628
- Full-coverage spatiotemporal estimation of surface ozone over China based on a high-efficiency deep learning model X. Mu et al. 10.1016/j.jag.2023.103284
- Enhancement of atmospheric oxidation capacity induced co-pollution of the O3 and PM2.5 in Lanzhou, northwest China L. Wang et al. 10.1016/j.envpol.2023.122951
- Understanding meteorological factors influencing heavy air pollution in Guwahati, India N. Behera & S. Gokhale 10.1016/j.apr.2024.102337
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- Tropospheric ozone and NOx: A review of worldwide variation and meteorological influences D. Nguyen et al. 10.1016/j.eti.2022.102809
- Random Forest Spatial-Temporal and State Space Models to Assess the Impact of Bushfire-Induced Aerosol Events on Ozone Depletion in Australia I. Hudson et al. 10.3390/app14219825
- Machine learning models for predicting interactions between air pollutants in Tehran Megacity, Iran A. Rad et al. 10.1016/j.aej.2024.08.023
- High-spatial resolution ground-level ozone in Yunnan, China: A spatiotemporal estimation based on comparative analyses of machine learning models X. Man et al. 10.1016/j.envres.2024.118609
- Impacts of aerosol–photolysis interaction and aerosol–radiation feedback on surface-layer ozone in North China during multi-pollutant air pollution episodes H. Yang et al. 10.5194/acp-22-4101-2022
- Lidar- and UAV-Based Vertical Observation of Spring Ozone and Particulate Matter in Nanjing, China Y. Qu et al. 10.3390/rs14133051
- Exploring the role of aerosol-ozone interactions on O3 surge and PM2.5 decline during the clean air action period in Eastern China 2014–2020 Y. Li et al. 10.1016/j.atmosres.2024.107294
- Deciphering the seasonal dynamics of multifaceted aerosol-ozone interplay: Implications for air quality management in Eastern China Y. Li et al. 10.1016/j.scitotenv.2024.174327
- Diagnosing drivers of PM2.5 simulation biases in China from meteorology, chemical composition, and emission sources using an efficient machine learning method S. Wang et al. 10.5194/gmd-17-3617-2024
- Impact of Wildfires on Meteorology and Air Quality (PM2.5 and O3) over Western United States during September 2017 A. Sharma et al. 10.3390/atmos13020262
- Machine learning elucidates ubiquity of enhanced ozone air pollution in China linked to the spring festival effect B. Zhu et al. 10.1016/j.apr.2024.102127
- Wavelet Analysis of Atmospheric Ozone and Ultraviolet Radiation on Solar Cycle-24 over Lumbini, Nepal P. Shrestha et al. 10.3390/atmos15040509
- The roles of environmental conditions in the pollutant emission-induced gross primary production change: Co-contribution of meteorological fields and regulation of its background gradients X. Gui et al. 10.1177/03091333231186893
- Impact of aerosol optics on vertical distribution of ozone in autumn over Yangtze River Delta S. Yan et al. 10.5194/acp-23-5177-2023
- Ambient fine particulate matter and ozone pollution in China: synergy in anthropogenic emissions and atmospheric processes Y. Jiang et al. 10.1088/1748-9326/aca16a
28 citations as recorded by crossref.
- Quantifying Contributions of Local Emissions and Regional Transport to NOX in Beijing Using TROPOMI Constrained WRF-Chem Simulation Y. Zhu et al. 10.3390/rs13091798
- Towards a Multi-Instrumental Approach to Closing Aerosol Optical Extinction Profiles A. Szkop et al. 10.3390/atmos13091443
- Intercomparison of multiple two-way coupled meteorology and air quality models (WRF v4.1.1–CMAQ v5.3.1, WRF–Chem v4.1.1, and WRF v3.7.1–CHIMERE v2020r1) in eastern China C. Gao et al. 10.5194/gmd-17-2471-2024
- The influence of the black carbon warming effect on near-surface ozone in China in summer H. Chen et al. 10.1016/j.atmosres.2024.107284
- Mitigating ozone damage to ecosystem productivity through sectoral and regional emission controls: a case study in the Yangtze River Delta, China Y. Lei et al. 10.1088/1748-9326/ac6ff7
- Tropospheric ozone and its natural precursors impacted by climatic changes in emission and dynamics S. Dewan & A. Lakhani 10.3389/fenvs.2022.1007942
- Black Carbon Radiative Impacts on Surface Atmospheric Oxidants in China with WRF-Chem Simulation W. Dai et al. 10.3390/atmos15101255
- New Deep Learning Model to Estimate Ozone Concentrations Found Worrying Exposure Level over Eastern China S. Wang et al. 10.3390/ijerph19127186
- Potential Factors Contributing to Ozone Production in AQUAS–Kyoto Campaign in Summer 2020: Natural Source-Related Missing OH Reactivity and Heterogeneous HO2/RO2 Loss J. Li et al. 10.1021/acs.est.2c03628
- Full-coverage spatiotemporal estimation of surface ozone over China based on a high-efficiency deep learning model X. Mu et al. 10.1016/j.jag.2023.103284
- Enhancement of atmospheric oxidation capacity induced co-pollution of the O3 and PM2.5 in Lanzhou, northwest China L. Wang et al. 10.1016/j.envpol.2023.122951
- Understanding meteorological factors influencing heavy air pollution in Guwahati, India N. Behera & S. Gokhale 10.1016/j.apr.2024.102337
- A High-Performance Convolutional Neural Network for Ground-Level Ozone Estimation in Eastern China S. Wang et al. 10.3390/rs14071640
- Tropospheric ozone and NOx: A review of worldwide variation and meteorological influences D. Nguyen et al. 10.1016/j.eti.2022.102809
- Random Forest Spatial-Temporal and State Space Models to Assess the Impact of Bushfire-Induced Aerosol Events on Ozone Depletion in Australia I. Hudson et al. 10.3390/app14219825
- Machine learning models for predicting interactions between air pollutants in Tehran Megacity, Iran A. Rad et al. 10.1016/j.aej.2024.08.023
- High-spatial resolution ground-level ozone in Yunnan, China: A spatiotemporal estimation based on comparative analyses of machine learning models X. Man et al. 10.1016/j.envres.2024.118609
- Impacts of aerosol–photolysis interaction and aerosol–radiation feedback on surface-layer ozone in North China during multi-pollutant air pollution episodes H. Yang et al. 10.5194/acp-22-4101-2022
- Lidar- and UAV-Based Vertical Observation of Spring Ozone and Particulate Matter in Nanjing, China Y. Qu et al. 10.3390/rs14133051
- Exploring the role of aerosol-ozone interactions on O3 surge and PM2.5 decline during the clean air action period in Eastern China 2014–2020 Y. Li et al. 10.1016/j.atmosres.2024.107294
- Deciphering the seasonal dynamics of multifaceted aerosol-ozone interplay: Implications for air quality management in Eastern China Y. Li et al. 10.1016/j.scitotenv.2024.174327
- Diagnosing drivers of PM2.5 simulation biases in China from meteorology, chemical composition, and emission sources using an efficient machine learning method S. Wang et al. 10.5194/gmd-17-3617-2024
- Impact of Wildfires on Meteorology and Air Quality (PM2.5 and O3) over Western United States during September 2017 A. Sharma et al. 10.3390/atmos13020262
- Machine learning elucidates ubiquity of enhanced ozone air pollution in China linked to the spring festival effect B. Zhu et al. 10.1016/j.apr.2024.102127
- Wavelet Analysis of Atmospheric Ozone and Ultraviolet Radiation on Solar Cycle-24 over Lumbini, Nepal P. Shrestha et al. 10.3390/atmos15040509
- The roles of environmental conditions in the pollutant emission-induced gross primary production change: Co-contribution of meteorological fields and regulation of its background gradients X. Gui et al. 10.1177/03091333231186893
- Impact of aerosol optics on vertical distribution of ozone in autumn over Yangtze River Delta S. Yan et al. 10.5194/acp-23-5177-2023
- Ambient fine particulate matter and ozone pollution in China: synergy in anthropogenic emissions and atmospheric processes Y. Jiang et al. 10.1088/1748-9326/aca16a
Latest update: 21 Nov 2024
Short summary
The meteorological effect of aerosols on tropospheric ozone is investigated using global atmospheric modelling. We found that aerosol-induced meteorological effects act to reduce modelled ozone concentrations over China, which brings the simulation closer to observed levels. Our work sheds light on understudied processes affecting the levels of tropospheric gaseous pollutants and provides a basis for evaluating such processes using a combination of observations and model sensitivity experiments.
The meteorological effect of aerosols on tropospheric ozone is investigated using global...
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