Articles | Volume 21, issue 11
https://doi.org/10.5194/acp-21-8693-2021
© 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-21-8693-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 Jun 2021
Research article |
| 09 Jun 2021
| 09 Jun 2021
Modeling the impact of COVID-19 on air quality in southern California: implications for future control policies
Zhe Jiang
Key Laboratory of Middle Atmosphere and Global Environment
Observation, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Carbon Neutrality Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Key Laboratory of Middle Atmosphere and Global Environment
Observation, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Pacific Northwest National Laboratory, Richland, WA, USA
Joint Institute for Regional Earth System Science and Engineering and Department of Atmospheric and Oceanic Sciences, University of California,
Los Angeles, CA, USA
Yifang Zhu
Institute of Environment and Sustainability, University of
California, Los Angeles, CA, USA
Kazuyuki Miyazaki
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA, USA
Xin Lu
Petrochina North China Gas Marketing Company, Beijing, China
Yuqiang Zhang
Nicholas School of the Environment, Duke University, Durham, NC, USA
Kevin W. Bowman
Joint Institute for Regional Earth System Science and Engineering and Department of Atmospheric and Oceanic Sciences, University of California,
Los Angeles, CA, USA
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA, USA
Takashi Sekiya
Japan Agency for Marine-Earth Science and Technology, Yokohama,
Japan
Kuo-Nan Liou
Joint Institute for Regional Earth System Science and Engineering and Department of Atmospheric and Oceanic Sciences, University of California,
Los Angeles, CA, USA
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31 citations as recorded by crossref.
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- Green recovery or pollution rebound? Evidence from air pollution of China in the post-COVID-19 era T. Feng et al. 10.1016/j.jenvman.2022.116360
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- WITHDRAWN: Assessment of COVID-19 pandemic effects on ship pollutant emissions in major international seaports J. Liu et al. 10.1016/j.envres.2021.112246
- Opinion: The strength of long-term comprehensive observations to meet multiple grand challenges in different environments and in the atmosphere M. Kulmala et al. 10.5194/acp-23-14949-2023
- Modeling Surface Air Pollution with Reduced Emissions during the COVID-19 Pandemic Using CHIMERE and COSMO-ART Chemical Transport Models I. Kuznetsova et al. 10.3103/S1068373922030025
- Air pollution benefits from reduced on-road activity due to COVID-19 in the United States C. Arter et al. 10.1093/pnasnexus/pgae017
- Radiative Impacts of Aerosols During COVID-19 Lockdown Period Over the Indian Region R. Bhawar et al. 10.3389/fenvs.2021.746090
- COVID-19 pandemic, port congestion, and air quality: Evidence from China B. Gu & J. Liu 10.1016/j.ocecoaman.2023.106497
- Impact of 2020 COVID-19 lockdowns on particulate air pollution across Europe J. Putaud et al. 10.5194/acp-23-10145-2023
- Study on the characteristics of urban background ozone pollution based on long-term observations from mountain sites in China during 2015–2022 W. Zhao et al. 10.1016/j.atmosres.2024.107696
- Responses of ozone concentrations to the synergistic control of NOx and VOCs emissions in the Chengdu metropolitan area X. Du et al. 10.3389/fenvs.2022.1024795
- The effect of COVID-19 pandemic on human mobility and ambient air quality around the world: A systematic review S. Faridi et al. 10.1016/j.uclim.2021.100888
- Response of Ozone Concentration to the Synergistic Control of Nox and Vocs Emissions in the Chengdu Metropolitan Area X. Du et al. 10.2139/ssrn.4011053
- Impact of COVID-19 Lockdown on NO2 Pollution and the Associated Health Burden in China: A Comparison of Different Approaches Z. Li 10.3390/toxics12080580
- Pop-up cycling infrastructure as a niche innovation for sustainable transportation in European cities: An inter- and transdisciplinary case study of Berlin S. Becker et al. 10.1016/j.scs.2022.104168
- Impact of Regional Mobility on Air Quality during COVID-19 Lockdown in Mississippi, USA Using Machine Learning F. Tuluri et al. 10.3390/ijerph20116022
- Characterizing the interruption-recovery patterns of urban air pollution under the COVID-19 lockdown in China W. Cai et al. 10.1016/j.buildenv.2021.108231
- COVID-19 perturbation on US air quality and human health impact assessment J. He et al. 10.1093/pnasnexus/pgad483
- Performance of machine learning for ozone modeling in Southern California during the COVID-19 shutdown K. Do et al. 10.1039/D3EA00159H
- Impacts of travel bans and travel intention changes on aviation emissions due to Covid-19 pandemic Ö. Zeydan & İ. Zeydan 10.1007/s10668-023-02916-8
- O3 Sensitivity to NOx and VOC During RECAP-CA: Implication for Emissions Control Strategies S. Wu et al. 10.1021/acsestair.4c00026
- Impacts of COVID-19 on air quality in mid-eastern China: An insight into meteorology and emissions X. Zhao et al. 10.1016/j.atmosenv.2021.118750
- WITHDRAWN: Machine Learning with Spatial Interpolation Techniques for Constructing 2-Dimensional Ozone Concentrations in Southern California during the COVID-19 Shutdown K. Do et al. 10.1016/j.envpol.2023.121881
- Air quality and public health co-benefits of 100% renewable electricity adoption and electrification pathways in Los Angeles Y. Li et al. 10.1088/1748-9326/ad24cc
- Integrated process analysis retrieval of changes in ground-level ozone and fine particulate matter during the COVID-19 outbreak in the coastal city of Kannur, India F. Ye et al. 10.1016/j.envpol.2022.119468
- Identification of synergistic control for ozone and PM2.5 pollution during a large-scale emission reduction in China K. Zhao et al. 10.1016/j.atmosres.2023.107025
- Response of PM2.5 pollution to meteorological and anthropogenic emissions changes during COVID-19 lockdown in Hunan Province based on WRF-Chem model S. Dai et al. 10.1016/j.envpol.2023.121886
- An updated modeling framework to simulate Los Angeles air quality – Part 1: Model development, evaluation, and source apportionment E. Pennington et al. 10.5194/acp-24-2345-2024
- Drivers of avian habitat use and detection of backyard birds in the Pacific Northwest during COVID-19 pandemic lockdowns O. Sanderfoot et al. 10.1038/s41598-022-16406-w
- From COVID-19 to future electrification: Assessing traffic impacts on air quality by a machine-learning model J. Yang et al. 10.1073/pnas.2102705118
29 citations as recorded by crossref.
- The Impact of COVID-19 Lockdowns on Air Quality—A Global Review A. Addas & A. Maghrabi 10.3390/su131810212
- Green recovery or pollution rebound? Evidence from air pollution of China in the post-COVID-19 era T. Feng et al. 10.1016/j.jenvman.2022.116360
- Modelling the effect of local and regional emissions on PM2.5 concentrations in Wuhan, China during the COVID-19 lockdown Y. BAI et al. 10.1016/j.accre.2021.09.013
- WITHDRAWN: Assessment of COVID-19 pandemic effects on ship pollutant emissions in major international seaports J. Liu et al. 10.1016/j.envres.2021.112246
- Opinion: The strength of long-term comprehensive observations to meet multiple grand challenges in different environments and in the atmosphere M. Kulmala et al. 10.5194/acp-23-14949-2023
- Modeling Surface Air Pollution with Reduced Emissions during the COVID-19 Pandemic Using CHIMERE and COSMO-ART Chemical Transport Models I. Kuznetsova et al. 10.3103/S1068373922030025
- Air pollution benefits from reduced on-road activity due to COVID-19 in the United States C. Arter et al. 10.1093/pnasnexus/pgae017
- Radiative Impacts of Aerosols During COVID-19 Lockdown Period Over the Indian Region R. Bhawar et al. 10.3389/fenvs.2021.746090
- COVID-19 pandemic, port congestion, and air quality: Evidence from China B. Gu & J. Liu 10.1016/j.ocecoaman.2023.106497
- Impact of 2020 COVID-19 lockdowns on particulate air pollution across Europe J. Putaud et al. 10.5194/acp-23-10145-2023
- Study on the characteristics of urban background ozone pollution based on long-term observations from mountain sites in China during 2015–2022 W. Zhao et al. 10.1016/j.atmosres.2024.107696
- Responses of ozone concentrations to the synergistic control of NOx and VOCs emissions in the Chengdu metropolitan area X. Du et al. 10.3389/fenvs.2022.1024795
- The effect of COVID-19 pandemic on human mobility and ambient air quality around the world: A systematic review S. Faridi et al. 10.1016/j.uclim.2021.100888
- Response of Ozone Concentration to the Synergistic Control of Nox and Vocs Emissions in the Chengdu Metropolitan Area X. Du et al. 10.2139/ssrn.4011053
- Impact of COVID-19 Lockdown on NO2 Pollution and the Associated Health Burden in China: A Comparison of Different Approaches Z. Li 10.3390/toxics12080580
- Pop-up cycling infrastructure as a niche innovation for sustainable transportation in European cities: An inter- and transdisciplinary case study of Berlin S. Becker et al. 10.1016/j.scs.2022.104168
- Impact of Regional Mobility on Air Quality during COVID-19 Lockdown in Mississippi, USA Using Machine Learning F. Tuluri et al. 10.3390/ijerph20116022
- Characterizing the interruption-recovery patterns of urban air pollution under the COVID-19 lockdown in China W. Cai et al. 10.1016/j.buildenv.2021.108231
- COVID-19 perturbation on US air quality and human health impact assessment J. He et al. 10.1093/pnasnexus/pgad483
- Performance of machine learning for ozone modeling in Southern California during the COVID-19 shutdown K. Do et al. 10.1039/D3EA00159H
- Impacts of travel bans and travel intention changes on aviation emissions due to Covid-19 pandemic Ö. Zeydan & İ. Zeydan 10.1007/s10668-023-02916-8
- O3 Sensitivity to NOx and VOC During RECAP-CA: Implication for Emissions Control Strategies S. Wu et al. 10.1021/acsestair.4c00026
- Impacts of COVID-19 on air quality in mid-eastern China: An insight into meteorology and emissions X. Zhao et al. 10.1016/j.atmosenv.2021.118750
- WITHDRAWN: Machine Learning with Spatial Interpolation Techniques for Constructing 2-Dimensional Ozone Concentrations in Southern California during the COVID-19 Shutdown K. Do et al. 10.1016/j.envpol.2023.121881
- Air quality and public health co-benefits of 100% renewable electricity adoption and electrification pathways in Los Angeles Y. Li et al. 10.1088/1748-9326/ad24cc
- Integrated process analysis retrieval of changes in ground-level ozone and fine particulate matter during the COVID-19 outbreak in the coastal city of Kannur, India F. Ye et al. 10.1016/j.envpol.2022.119468
- Identification of synergistic control for ozone and PM2.5 pollution during a large-scale emission reduction in China K. Zhao et al. 10.1016/j.atmosres.2023.107025
- Response of PM2.5 pollution to meteorological and anthropogenic emissions changes during COVID-19 lockdown in Hunan Province based on WRF-Chem model S. Dai et al. 10.1016/j.envpol.2023.121886
- An updated modeling framework to simulate Los Angeles air quality – Part 1: Model development, evaluation, and source apportionment E. Pennington et al. 10.5194/acp-24-2345-2024
2 citations as recorded by crossref.
- Drivers of avian habitat use and detection of backyard birds in the Pacific Northwest during COVID-19 pandemic lockdowns O. Sanderfoot et al. 10.1038/s41598-022-16406-w
- From COVID-19 to future electrification: Assessing traffic impacts on air quality by a machine-learning model J. Yang et al. 10.1073/pnas.2102705118
Latest update: 29 May 2025
Short summary
We use the COVID-19 pandemic as a unique natural experiment to obtain a more robust understanding of the effectiveness of emission reductions toward air quality improvement by combining chemical transport simulations and observations. Our findings imply a shift from current control policies in California: a strengthened control on primary PM2.5 emissions and a well-balanced control on NOx and volatile organic compounds are needed to effectively and sustainably alleviate PM2.5 and O3 pollution.
We use the COVID-19 pandemic as a unique natural experiment to obtain a more robust...
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