Articles | Volume 22, issue 18
https://doi.org/10.5194/acp-22-12543-2022
https://doi.org/10.5194/acp-22-12543-2022
Research article
 | 
26 Sep 2022
Research article |  | 26 Sep 2022

Correcting ozone biases in a global chemistry–climate model: implications for future ozone

Zhenze Liu, Ruth M. Doherty, Oliver Wild, Fiona M. O'Connor, and Steven T. Turnock

Related authors

The effect of different climate and air quality policies in China on in situ ozone production in Beijing
Beth S. Nelson, Zhenze Liu, Freya A. Squires, Marvin Shaw, James R. Hopkins, Jacqueline F. Hamilton, Andrew R. Rickard, Alastair C. Lewis, Zongbo Shi, and James D. Lee
Atmos. Chem. Phys., 24, 9031–9044, https://doi.org/10.5194/acp-24-9031-2024,https://doi.org/10.5194/acp-24-9031-2024, 2024
Short summary
Benefits of net-zero policies for future ozone pollution in China
Zhenze Liu, Oliver Wild, Ruth M. Doherty, Fiona M. O'Connor, and Steven T. Turnock
Atmos. Chem. Phys., 23, 13755–13768, https://doi.org/10.5194/acp-23-13755-2023,https://doi.org/10.5194/acp-23-13755-2023, 2023
Short summary
Tropospheric ozone changes and ozone sensitivity from the present day to the future under shared socio-economic pathways
Zhenze Liu, Ruth M. Doherty, Oliver Wild, Fiona M. O'Connor, and Steven T. Turnock
Atmos. Chem. Phys., 22, 1209–1227, https://doi.org/10.5194/acp-22-1209-2022,https://doi.org/10.5194/acp-22-1209-2022, 2022
Short summary
Contrasting chemical environments in summertime for atmospheric ozone across major Chinese industrial regions: the effectiveness of emission control strategies
Zhenze Liu, Ruth M. Doherty, Oliver Wild, Michael Hollaway, and Fiona M. O’Connor
Atmos. Chem. Phys., 21, 10689–10706, https://doi.org/10.5194/acp-21-10689-2021,https://doi.org/10.5194/acp-21-10689-2021, 2021
Short summary

Related subject area

Subject: Gases | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Chemistry (chemical composition and reactions)
The atmospheric oxidizing capacity in China – Part 2: Sensitivity to emissions of primary pollutants
Jianing Dai, Guy P. Brasseur, Mihalis Vrekoussis, Maria Kanakidou, Kun Qu, Yijuan Zhang, Hongliang Zhang, and Tao Wang
Atmos. Chem. Phys., 24, 12943–12962, https://doi.org/10.5194/acp-24-12943-2024,https://doi.org/10.5194/acp-24-12943-2024, 2024
Short summary
Role of chemical production and depositional losses on formaldehyde in the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMM)
T. Nash Skipper, Emma L. D'Ambro, Forwood C. Wiser, V. Faye McNeill, Rebecca H. Schwantes, Barron H. Henderson, Ivan R. Piletic, Colleen B. Baublitz, Jesse O. Bash, Andrew R. Whitehill, Lukas C. Valin, Asher P. Mouat, Jennifer Kaiser, Glenn M. Wolfe, Jason M. St. Clair, Thomas F. Hanisco, Alan Fried, Bryan K. Place, and Havala O.T. Pye
Atmos. Chem. Phys., 24, 12903–12924, https://doi.org/10.5194/acp-24-12903-2024,https://doi.org/10.5194/acp-24-12903-2024, 2024
Short summary
Review of source analyses of ambient volatile organic compounds considering reactive losses: methods of reducing loss effects, impacts of losses, and sources
Baoshuang Liu, Yao Gu, Yutong Wu, Qili Dai, Shaojie Song, Yinchang Feng, and Philip K. Hopke
Atmos. Chem. Phys., 24, 12861–12879, https://doi.org/10.5194/acp-24-12861-2024,https://doi.org/10.5194/acp-24-12861-2024, 2024
Short summary
Interpreting summertime hourly variation of NO2 columns with implications for geostationary satellite applications
Deepangsu Chatterjee, Randall V. Martin, Chi Li, Dandan Zhang, Haihui Zhu, Daven K. Henze, James H. Crawford, Ronald C. Cohen, Lok N. Lamsal, and Alexander M. Cede
Atmos. Chem. Phys., 24, 12687–12706, https://doi.org/10.5194/acp-24-12687-2024,https://doi.org/10.5194/acp-24-12687-2024, 2024
Short summary
An investigation into atmospheric nitrous acid (HONO) processes in South Korea
Kiyeon Kim, Kyung Man Han, Chul Han Song, Hyojun Lee, Ross Beardsley, Jinhyeok Yu, Greg Yarwood, Bonyoung Koo, Jasper Madalipay, Jung-Hun Woo, and Seogju Cho
Atmos. Chem. Phys., 24, 12575–12593, https://doi.org/10.5194/acp-24-12575-2024,https://doi.org/10.5194/acp-24-12575-2024, 2024
Short summary

Cited articles

Archer-Nicholls, S., Abraham, N. L., Shin, Y., Weber, J., Russo,M. R., Lowe, D., Utembe, S., O’Connor, F., Kerridge, B., Latter, B, Siddans, R., Jenkin, M., Wild, O., and Archibald, A. T.: The Common Representative Intermediates Mechanism version 2 in the United Kingdom Chemistry and Aerosols Model, J. Adv. Model. Earth Sy., 13, e2020MS002420, https://doi.org/10.1029/2020MS002420, 2021. a
Archibald, A., Neu, J., Elshorbany, Y., Cooper, O., Young,P., Akiyoshi, H., Cox, R., Coyle, M., Derwent, R., Deushi,M., Finco, A., Frost, G. J., Galbally, I. E., Gerosa, G., Granier, C., Griffiths, P. T., Hossaini, R., Hu, L., Jöckel, P., Josse, B., Lin, M. Y., Mertens, M., Morgenstern, O., Naja, M., Naik, V., Oltmans, S., Plummer, D. A., Revell, L. E., Saiz-Lopez, A., Saxena, P., Shin, Y. M., Shahid, I., Shallcross, D., Tilmes, S., Trickl, T., Wallington, T. J., Wang, T., Worden, H. M., and Zeng, G.: Tropospheric Ozone Assessment Report: A critical review of changes in the tropospheric ozone burden and budget from 1850 to 2100, Elementa, 8, 034, https://doi.org/10.1525/elementa.2020.034, 2020a. a, b
Archibald, A. T., O'Connor, F. M., Abraham, N. L., Archer-Nicholls, S., Chipperfield, M. P., Dalvi, M., Folberth, G. A., Dennison, F., Dhomse, S. S., Griffiths, P. T., Hardacre, C., Hewitt, A. J., Hill, R. S., Johnson, C. E., Keeble, J., Köhler, M. O., Morgenstern, O., Mulcahy, J. P., Ordóñez, C., Pope, R. J., Rumbold, S. T., Russo, M. R., Savage, N. H., Sellar, A., Stringer, M., Turnock, S. T., Wild, O., and Zeng, G.: Description and evaluation of the UKCA stratosphere–troposphere chemistry scheme (StratTrop vn 1.0) implemented in UKESM1, Geosci. Model Dev., 13, 1223–1266, https://doi.org/10.5194/gmd-13-1223-2020, 2020b. a
Archibald, A. T., Turnock, S. T., Griffiths, P. T., Cox, T., Derwent, R. G., Knote, C., and Shin, M.: On the changes in surface ozone over the twenty-first century: sensitivity to changes in surface temperature and chemical mechanisms, Philos. T. Roy. Soc. A, 378, 20190329, https://doi.org/10.1098/rsta.2019.0329, 2020c. a, b
Betancourt, C., Stomberg, T. T., Edrich, A.-K., Patnala, A., Schultz, M. G., Roscher, R., Kowalski, J., and Stadtler, S.: Global, high-resolution mapping of tropospheric ozone – explainable machine learning and impact of uncertainties, Geosci. Model Dev., 15, 4331–4354, https://doi.org/10.5194/gmd-15-4331-2022, 2022. a
Download
Short summary
Weaknesses in process representation in chemistry–climate models lead to biases in simulating surface ozone and to uncertainty in projections of future ozone change. We develop a deep learning model to demonstrate the feasibility of ozone bias correction and show its capability in providing improved assessments of the impacts of climate and emission changes on future air quality, along with valuable information to guide future model development.
Altmetrics
Final-revised paper
Preprint