Articles | Volume 24, issue 20
https://doi.org/10.5194/acp-24-11545-2024
© 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-24-11545-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Oct 2024
Research article |
| 16 Oct 2024
| 16 Oct 2024
Impact of methane and other precursor emission reductions on surface ozone in Europe: scenario analysis using the European Monitoring and Evaluation Programme (EMEP) Meteorological Synthesizing Centre – West (MSC-W) model
EMEP MSC-W, Norwegian Meteorological Institute, Oslo, Norway
Zbigniew Klimont
Pollution Management Research Group, Energy, Climate, and Environment (ECE) Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria
Chris Heyes
Pollution Management Research Group, Energy, Climate, and Environment (ECE) Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria
Hilde Fagerli
EMEP MSC-W, Norwegian Meteorological Institute, Oslo, Norway
Related authors
Peter Wind and Willem van Caspel
EGUsphere, https://doi.org/10.5194/egusphere-2024-3571, https://doi.org/10.5194/egusphere-2024-3571, 2025
Short summary
Short summary
This paper presents a numerical method to assess the origin of air pollution. Combined with a numerical air pollution transport and chemistry model, it can follow the contributions from a large number of emission sources. The result is a series of maps that give the relative contributions from for example all European countries at each point.
Yao Ge, Sverre Solberg, Mathew R. Heal, Stefan Reimann, Willem van Caspel, Bryan Hellack, Thérèse Salameh, and David Simpson
Atmos. Chem. Phys., 24, 7699–7729, https://doi.org/10.5194/acp-24-7699-2024, https://doi.org/10.5194/acp-24-7699-2024, 2024
Short summary
Short summary
Atmospheric volatile organic compounds (VOCs) constitute many species, acting as precursors to ozone and aerosol. Given the uncertainties in VOC emissions, lack of evaluation studies, and recent changes in emissions, this work adapts the EMEP MSC-W to evaluate emission inventories in Europe. We focus on the varying agreement between modelled and measured VOCs across different species and underscore potential inaccuracies in total and sector-specific emission estimates.
Willem E. van Caspel, David Simpson, Jan Eiof Jonson, Anna M. K. Benedictow, Yao Ge, Alcide di Sarra, Giandomenico Pace, Massimo Vieno, Hannah L. Walker, and Mathew R. Heal
Geosci. Model Dev., 16, 7433–7459, https://doi.org/10.5194/gmd-16-7433-2023, https://doi.org/10.5194/gmd-16-7433-2023, 2023
Short summary
Short summary
Radiation coming from the sun is essential to atmospheric chemistry, driving the breakup, or photodissociation, of atmospheric molecules. This in turn affects the chemical composition and reactivity of the atmosphere. The representation of photodissociation effects is therefore essential in atmospheric chemistry modeling. One such model is the EMEP MSC-W model, for which a new way of calculating the photodissociation rates is tested and evaluated in this paper.
Natalie M. Mahowald, Longlei Li, Julius Vira, Marje Prank, Douglas S. Hamilton, Hitoshi Matsui, Ron L. Miller, P. Louis Lu, Ezgi Akyuz, Daphne Meidan, Peter Hess, Heikki Lihavainen, Christine Wiedinmyer, Jenny Hand, Maria Grazia Alaimo, Célia Alves, Andres Alastuey, Paulo Artaxo, Africa Barreto, Francisco Barraza, Silvia Becagli, Giulia Calzolai, Shankararaman Chellam, Ying Chen, Patrick Chuang, David D. Cohen, Cristina Colombi, Evangelia Diapouli, Gaetano Dongarra, Konstantinos Eleftheriadis, Johann Engelbrecht, Corinne Galy-Lacaux, Cassandra Gaston, Dario Gomez, Yenny González Ramos, Roy M. Harrison, Chris Heyes, Barak Herut, Philip Hopke, Christoph Hüglin, Maria Kanakidou, Zsofia Kertesz, Zbigniew Klimont, Katriina Kyllönen, Fabrice Lambert, Xiaohong Liu, Remi Losno, Franco Lucarelli, Willy Maenhaut, Beatrice Marticorena, Randall V. Martin, Nikolaos Mihalopoulos, Yasser Morera-Gómez, Adina Paytan, Joseph Prospero, Sergio Rodríguez, Patricia Smichowski, Daniela Varrica, Brenna Walsh, Crystal L. Weagle, and Xi Zhao
Atmos. Chem. Phys., 25, 4665–4702, https://doi.org/10.5194/acp-25-4665-2025, https://doi.org/10.5194/acp-25-4665-2025, 2025
Short summary
Short summary
Aerosol particles are an important part of the Earth system, but their concentrations are spatially and temporally heterogeneous, as well as being variable in size and composition. Here, we present a new compilation of PM2.5 and PM10 aerosol observations, focusing on the spatial variability across different observational stations, including composition, and demonstrate a method for comparing the data sets to model output.
Marc Guevara, Augustin Colette, Antoine Guion, Valentin Petiot, Mario Adani, Joaquim Arteta, Anna Benedictow, Robert Bergström, Andrea Bolignano, Paula Camps, Ana C. Carvalho, Jesper Heile Christensen, Florian Couvidat, Ilia D’Elia, Hugo Denier van der Gon, Gaël Descombes, John Douros, Hilde Fagerli, Yalda Fatahi, Elmar Friese, Lise Frohn, Michael Gauss, Camilla Geels, Risto Hänninen, Kaj Hansen, Oriol Jorba, Jacek W. Kaminski, Rostislav Kouznetsov, Richard Kranenburg, Jeroen Kuenen, Victor Lannuque, Frédérik Meleux, Agnes Nyíri, Yuliia Palamarchuk, Carlos Pérez García-Pando, Lennard Robertson, Felicita Russo, Arjo Segers, Mikhail Sofiev, Joanna Struzewska, Renske Timmermans, Andreas Uppstu, Alvaro Valdebenito, and Zhuyun Ye
EGUsphere, https://doi.org/10.5194/egusphere-2025-1287, https://doi.org/10.5194/egusphere-2025-1287, 2025
Short summary
Short summary
Air quality models require hourly emissions to accurately represent dispersion and physico-chemical processes in the atmosphere. Since emission inventories are typically provided at the annual level, emissions are downscaled to a refined temporal resolution using temporal profiles. This study quantifies the impact of using new anthropogenic temporal profiles on the performance of an European air quality multi-model ensemble. Overall, the findings indicate an improvement of the modelling results.
Peter Wind and Willem van Caspel
EGUsphere, https://doi.org/10.5194/egusphere-2024-3571, https://doi.org/10.5194/egusphere-2024-3571, 2025
Short summary
Short summary
This paper presents a numerical method to assess the origin of air pollution. Combined with a numerical air pollution transport and chemistry model, it can follow the contributions from a large number of emission sources. The result is a series of maps that give the relative contributions from for example all European countries at each point.
Diego Guizzardi, Monica Crippa, Tim Butler, Terry Keating, Rosa Wu, Jacek W. Kamiński, Jeroen Kuenen, Junichi Kurokawa, Satoru Chatani, Tazuko Morikawa, George Pouliot, Jacinthe Racine, Michael D. Moran, Zbigniew Klimont, Patrick M. Manseau, Rabab Mashayekhi, Barron H. Henderson, Steven J. Smith, Rachel Hoesly, Marilena Muntean, Manjola Banja, Edwin Schaaf, Federico Pagani, Jung-Hun Woo, Jinseok Kim, Enrico Pisoni, Junhua Zhang, David Niemi, Mourad Sassi, Annie Duhamel, Tabish Ansari, Kristen Foley, Guannan Geng, Yifei Chen, and Qiang Zhang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-601, https://doi.org/10.5194/essd-2024-601, 2025
Preprint under review for ESSD
Short summary
Short summary
The global air pollution emission mosaic HTAP_v3.1 is the state-of-the-art database for addressing the evolution of a set of policy-relevant air pollutants over the past 2 decades. The inventory is made by the harmonization and blending of seven regional inventories, gapfilled using the most recent release of EDGAR (EDGARv8). By incorporating the best available local information, the HTAP_v3.1 mosaic inventory can be used for policy-relevant studies at both regional and global levels.
Augustin Colette, Gaëlle Collin, François Besson, Etienne Blot, Vincent Guidard, Frederik Meleux, Adrien Royer, Valentin Petiot, Claire Miller, Oihana Fermond, Alizé Jeant, Mario Adani, Joaquim Arteta, Anna Benedictow, Robert Bergström, Dene Bowdalo, Jorgen Brandt, Gino Briganti, Ana C. Carvalho, Jesper Heile Christensen, Florian Couvidat, Ilia D’Elia, Massimo D’Isidoro, Hugo Denier van der Gon, Gaël Descombes, Enza Di Tomaso, John Douros, Jeronimo Escribano, Henk Eskes, Hilde Fagerli, Yalda Fatahi, Johannes Flemming, Elmar Friese, Lise Frohn, Michael Gauss, Camilla Geels, Guido Guarnieri, Marc Guevara, Antoine Guion, Jonathan Guth, Risto Hänninen, Kaj Hansen, Ulas Im, Ruud Janssen, Marine Jeoffrion, Mathieu Joly, Luke Jones, Oriol Jorba, Evgeni Kadantsev, Michael Kahnert, Jacek W. Kaminski, Rostislav Kouznetsov, Richard Kranenburg, Jeroen Kuenen, Anne Caroline Lange, Joachim Langner, Victor Lannuque, Francesca Macchia, Astrid Manders, Mihaela Mircea, Agnes Nyiri, Miriam Olid, Carlos Pérez García-Pando, Yuliia Palamarchuk, Antonio Piersanti, Blandine Raux, Miha Razinger, Lennard Robertson, Arjo Segers, Martijn Schaap, Pilvi Siljamo, David Simpson, Mikhail Sofiev, Anders Stangel, Joanna Struzewska, Carles Tena, Renske Timmermans, Thanos Tsikerdekis, Svetlana Tsyro, Svyatoslav Tyuryakov, Anthony Ung, Andreas Uppstu, Alvaro Valdebenito, Peter van Velthoven, Lina Vitali, Zhuyun Ye, Vincent-Henri Peuch, and Laurence Rouïl
EGUsphere, https://doi.org/10.5194/egusphere-2024-3744, https://doi.org/10.5194/egusphere-2024-3744, 2024
Short summary
Short summary
The Copernicus Atmosphere Monitoring Service – Regional Production delivers daily forecasts, analyses, and reanalyses of air quality in Europe. The Service relies on a distributed modelling production by eleven leading European modelling teams following stringent requirements with an operational design which has no equivalent in the world. All the products are full, free, open and quality assured and disseminated with a high level of reliability.
Yao Ge, Sverre Solberg, Mathew R. Heal, Stefan Reimann, Willem van Caspel, Bryan Hellack, Thérèse Salameh, and David Simpson
Atmos. Chem. Phys., 24, 7699–7729, https://doi.org/10.5194/acp-24-7699-2024, https://doi.org/10.5194/acp-24-7699-2024, 2024
Short summary
Short summary
Atmospheric volatile organic compounds (VOCs) constitute many species, acting as precursors to ozone and aerosol. Given the uncertainties in VOC emissions, lack of evaluation studies, and recent changes in emissions, this work adapts the EMEP MSC-W to evaluate emission inventories in Europe. We focus on the varying agreement between modelled and measured VOCs across different species and underscore potential inaccuracies in total and sector-specific emission estimates.
Natalie M. Mahowald, Longlei Li, Julius Vira, Marje Prank, Douglas S. Hamilton, Hitoshi Matsui, Ron L. Miller, Louis Lu, Ezgi Akyuz, Daphne Meidan, Peter Hess, Heikki Lihavainen, Christine Wiedinmyer, Jenny Hand, Maria Grazia Alaimo, Célia Alves, Andres Alastuey, Paulo Artaxo, Africa Barreto, Francisco Barraza, Silvia Becagli, Giulia Calzolai, Shankarararman Chellam, Ying Chen, Patrick Chuang, David D. Cohen, Cristina Colombi, Evangelia Diapouli, Gaetano Dongarra, Konstantinos Eleftheriadis, Corinne Galy-Lacaux, Cassandra Gaston, Dario Gomez, Yenny González Ramos, Hannele Hakola, Roy M. Harrison, Chris Heyes, Barak Herut, Philip Hopke, Christoph Hüglin, Maria Kanakidou, Zsofia Kertesz, Zbiginiw Klimont, Katriina Kyllönen, Fabrice Lambert, Xiaohong Liu, Remi Losno, Franco Lucarelli, Willy Maenhaut, Beatrice Marticorena, Randall V. Martin, Nikolaos Mihalopoulos, Yasser Morera-Gomez, Adina Paytan, Joseph Prospero, Sergio Rodríguez, Patricia Smichowski, Daniela Varrica, Brenna Walsh, Crystal Weagle, and Xi Zhao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-1, https://doi.org/10.5194/essd-2024-1, 2024
Preprint withdrawn
Short summary
Short summary
Aerosol particles can interact with incoming solar radiation and outgoing long wave radiation, change cloud properties, affect photochemistry, impact surface air quality, and when deposited impact surface albedo of snow and ice, and modulate carbon dioxide uptake by the land and ocean. Here we present a new compilation of aerosol observations including composition, a methodology for comparing the datasets to model output, and show the implications of these results using one model.
Willem E. van Caspel, David Simpson, Jan Eiof Jonson, Anna M. K. Benedictow, Yao Ge, Alcide di Sarra, Giandomenico Pace, Massimo Vieno, Hannah L. Walker, and Mathew R. Heal
Geosci. Model Dev., 16, 7433–7459, https://doi.org/10.5194/gmd-16-7433-2023, https://doi.org/10.5194/gmd-16-7433-2023, 2023
Short summary
Short summary
Radiation coming from the sun is essential to atmospheric chemistry, driving the breakup, or photodissociation, of atmospheric molecules. This in turn affects the chemical composition and reactivity of the atmosphere. The representation of photodissociation effects is therefore essential in atmospheric chemistry modeling. One such model is the EMEP MSC-W model, for which a new way of calculating the photodissociation rates is tested and evaluated in this paper.
Monica Crippa, Diego Guizzardi, Tim Butler, Terry Keating, Rosa Wu, Jacek Kaminski, Jeroen Kuenen, Junichi Kurokawa, Satoru Chatani, Tazuko Morikawa, George Pouliot, Jacinthe Racine, Michael D. Moran, Zbigniew Klimont, Patrick M. Manseau, Rabab Mashayekhi, Barron H. Henderson, Steven J. Smith, Harrison Suchyta, Marilena Muntean, Efisio Solazzo, Manjola Banja, Edwin Schaaf, Federico Pagani, Jung-Hun Woo, Jinseok Kim, Fabio Monforti-Ferrario, Enrico Pisoni, Junhua Zhang, David Niemi, Mourad Sassi, Tabish Ansari, and Kristen Foley
Earth Syst. Sci. Data, 15, 2667–2694, https://doi.org/10.5194/essd-15-2667-2023, https://doi.org/10.5194/essd-15-2667-2023, 2023
Short summary
Short summary
This study responds to the global and regional atmospheric modelling community's need for a mosaic of air pollutant emissions with global coverage, long time series, spatially distributed data at a high time resolution, and a high sectoral resolution in order to enhance the understanding of transboundary air pollution. The mosaic approach to integrating official regional emission inventories with a global inventory based on a consistent methodology ensures policy-relevant results.
Marianne Tronstad Lund, Gunnar Myhre, Ragnhild Bieltvedt Skeie, Bjørn Hallvard Samset, and Zbigniew Klimont
Atmos. Chem. Phys., 23, 6647–6662, https://doi.org/10.5194/acp-23-6647-2023, https://doi.org/10.5194/acp-23-6647-2023, 2023
Short summary
Short summary
Here we show that differences, in magnitude and trend, between recent global anthropogenic emission inventories have a notable influence on simulated regional abundances of anthropogenic aerosol over the 1990–2019 period. This, in turn, affects estimates of radiative forcing. Our findings form a basis for comparing existing and upcoming studies on anthropogenic aerosols using different emission inventories.
Johannes Quaas, Hailing Jia, Chris Smith, Anna Lea Albright, Wenche Aas, Nicolas Bellouin, Olivier Boucher, Marie Doutriaux-Boucher, Piers M. Forster, Daniel Grosvenor, Stuart Jenkins, Zbigniew Klimont, Norman G. Loeb, Xiaoyan Ma, Vaishali Naik, Fabien Paulot, Philip Stier, Martin Wild, Gunnar Myhre, and Michael Schulz
Atmos. Chem. Phys., 22, 12221–12239, https://doi.org/10.5194/acp-22-12221-2022, https://doi.org/10.5194/acp-22-12221-2022, 2022
Short summary
Short summary
Pollution particles cool climate and offset part of the global warming. However, they are washed out by rain and thus their effect responds quickly to changes in emissions. We show multiple datasets to demonstrate that aerosol emissions and their concentrations declined in many regions influenced by human emissions, as did the effects on clouds. Consequently, the cooling impact on the Earth energy budget became smaller. This change in trend implies a relative warming.
Cynthia H. Whaley, Rashed Mahmood, Knut von Salzen, Barbara Winter, Sabine Eckhardt, Stephen Arnold, Stephen Beagley, Silvia Becagli, Rong-You Chien, Jesper Christensen, Sujay Manish Damani, Xinyi Dong, Konstantinos Eleftheriadis, Nikolaos Evangeliou, Gregory Faluvegi, Mark Flanner, Joshua S. Fu, Michael Gauss, Fabio Giardi, Wanmin Gong, Jens Liengaard Hjorth, Lin Huang, Ulas Im, Yugo Kanaya, Srinath Krishnan, Zbigniew Klimont, Thomas Kühn, Joakim Langner, Kathy S. Law, Louis Marelle, Andreas Massling, Dirk Olivié, Tatsuo Onishi, Naga Oshima, Yiran Peng, David A. Plummer, Olga Popovicheva, Luca Pozzoli, Jean-Christophe Raut, Maria Sand, Laura N. Saunders, Julia Schmale, Sangeeta Sharma, Ragnhild Bieltvedt Skeie, Henrik Skov, Fumikazu Taketani, Manu A. Thomas, Rita Traversi, Kostas Tsigaridis, Svetlana Tsyro, Steven Turnock, Vito Vitale, Kaley A. Walker, Minqi Wang, Duncan Watson-Parris, and Tahya Weiss-Gibbons
Atmos. Chem. Phys., 22, 5775–5828, https://doi.org/10.5194/acp-22-5775-2022, https://doi.org/10.5194/acp-22-5775-2022, 2022
Short summary
Short summary
Air pollutants, like ozone and soot, play a role in both global warming and air quality. Atmospheric models are often used to provide information to policy makers about current and future conditions under different emissions scenarios. In order to have confidence in those simulations, in this study we compare simulated air pollution from 18 state-of-the-art atmospheric models to measured air pollution in order to assess how well the models perform.
Jan Eiof Jonson, Hilde Fagerli, Thomas Scheuschner, and Svetlana Tsyro
Atmos. Chem. Phys., 22, 1311–1331, https://doi.org/10.5194/acp-22-1311-2022, https://doi.org/10.5194/acp-22-1311-2022, 2022
Short summary
Short summary
Ammonia emissions are expected to decrease less than SOx and NOx emissions between 2005 and 2030. As the formation of PM2.5 particles from ammonia depends on the ratio between ammonia on one hand and sulfate (from SOx) and HNO3 (from NOx) on the other hand, the efficiency of particle formation from ammonia is decreasing. Depositions of reduced nitrogen are decreasing much less than oxidized nitrogen. The critical loads for nitrogen deposition will also be exceeded in much of Europe in 2030.
Qing Mu, Bruce Rolstad Denby, Eivind Grøtting Wærsted, and Hilde Fagerli
Geosci. Model Dev., 15, 449–465, https://doi.org/10.5194/gmd-15-449-2022, https://doi.org/10.5194/gmd-15-449-2022, 2022
Short summary
Short summary
Our study has achieved air quality modelling down to 100 m for all of Europe. This solves the current problem that street-level air quality modelling is usually limited to individual cities. With publicly available downscaling proxy data, even regions without their own high-resolution proxy data can obtain air quality maps at 100 m. The work is of significance for air quality mitigation strategies and human health exposure studies.
Jessica L. McCarty, Juha Aalto, Ville-Veikko Paunu, Steve R. Arnold, Sabine Eckhardt, Zbigniew Klimont, Justin J. Fain, Nikolaos Evangeliou, Ari Venäläinen, Nadezhda M. Tchebakova, Elena I. Parfenova, Kaarle Kupiainen, Amber J. Soja, Lin Huang, and Simon Wilson
Biogeosciences, 18, 5053–5083, https://doi.org/10.5194/bg-18-5053-2021, https://doi.org/10.5194/bg-18-5053-2021, 2021
Short summary
Short summary
Fires, including extreme fire seasons, and fire emissions are more common in the Arctic. A review and synthesis of current scientific literature find climate change and human activity in the north are fuelling an emerging Arctic fire regime, causing more black carbon and methane emissions within the Arctic. Uncertainties persist in characterizing future fire landscapes, and thus emissions, as well as policy-relevant challenges in understanding, monitoring, and managing Arctic fire regimes.
Ulas Im, Kostas Tsigaridis, Gregory Faluvegi, Peter L. Langen, Joshua P. French, Rashed Mahmood, Manu A. Thomas, Knut von Salzen, Daniel C. Thomas, Cynthia H. Whaley, Zbigniew Klimont, Henrik Skov, and Jørgen Brandt
Atmos. Chem. Phys., 21, 10413–10438, https://doi.org/10.5194/acp-21-10413-2021, https://doi.org/10.5194/acp-21-10413-2021, 2021
Short summary
Short summary
Future (2015–2050) simulations of the aerosol burdens and their radiative forcing and climate impacts over the Arctic under various emission projections show that although the Arctic aerosol burdens are projected to decrease significantly by 10 to 60 %, regardless of the magnitude of aerosol reductions, surface air temperatures will continue to increase by 1.9–2.6 ℃, while sea-ice extent will continue to decrease, implying reductions of greenhouse gases are necessary to mitigate climate change.
Bruce Rolstad Denby, Michael Gauss, Peter Wind, Qing Mu, Eivind Grøtting Wærsted, Hilde Fagerli, Alvaro Valdebenito, and Heiko Klein
Geosci. Model Dev., 13, 6303–6323, https://doi.org/10.5194/gmd-13-6303-2020, https://doi.org/10.5194/gmd-13-6303-2020, 2020
Short summary
Short summary
Air pollution is both a local and a global problem. Since measurements cannot be made everywhere, mathematical models are used to calculate air quality over cities or countries. Modelling over countries limits the level of detail of the models. For countries, the level of detail is only a few kilometres, so air quality at kerb sides is not properly represented. The uEMEP model is used together with the regional air quality model EMEP MSC-W to model details down to kerb side for all of Norway.
Marianne T. Lund, Borgar Aamaas, Camilla W. Stjern, Zbigniew Klimont, Terje K. Berntsen, and Bjørn H. Samset
Earth Syst. Dynam., 11, 977–993, https://doi.org/10.5194/esd-11-977-2020, https://doi.org/10.5194/esd-11-977-2020, 2020
Short summary
Short summary
Achieving the Paris Agreement temperature goals requires both near-zero levels of long-lived greenhouse gases and deep cuts in emissions of short-lived climate forcers (SLCFs). Here we quantify the near- and long-term global temperature impacts of emissions of individual SLCFs and CO2 from 7 economic sectors in 13 regions in order to provide the detailed knowledge needed to design efficient mitigation strategies at the sectoral and regional levels.
Cited articles
Abernethy, S., O'Connor, F. M., Jones, C. D., and Jackson, R. B.: Methane removal and the proportional reductions in surface temperature and ozone, Philos. T. Roy. Soc. A, 379, 20210104, https://doi.org/10.1098/rsta.2021.0104, 2021. a
Alexandratos, N. and Bruinsma, J.: World agriculture towards 2030/2050: the 2012 revision, ESA Working paper No. 12-03, Rome, FAO, https://www.fao.org/3/ap106e/ap106e.pdf (last access: April 2024), 2012. a
Amann, M., Bertok, I., Borken-Kleefeld, J., Cofala, J., Heyes, C., Hoeglund-Isaksson, L., Klimont, Z., Nguyen, B., Posch, M., Rafaj, P., Sandler, R., Schoepp, W., Wagner, F., and Winiwarter, W.: Cost-effective control of air quality and greenhouse gases in Europe: Modeling and policy applications, Environ. Model. Softw., 26, 1489–1501, https://doi.org/10.1016/j.envsoft.2011.07.012, 2011. a, b, c, d
Amann, M., Klimont, Z., and Wagner, F.: Regional and Global Emissions of Air Pollutants: Recent Trends and Future Scenarios, Annu. Rev. Environ. Resour., 38, 31–55, https://doi.org/10.1146/annurev-environ-052912-173303, 2013. a
Amann, M., Kiesewetter, G., Schöpp, W., Klimont, Z., Winiwarter, W., Cofala, J., Rafaj, P., Höglund-Isaksson, L., Gomez-Sabriana, A., Heyes, C., Purohit, P., Borken-Kleefeld, J., Wagner, F., Sander, R., Fagerli, H., Nyiri, A., Cozzi, L., and Pavarini, C.: Reducing global air pollution: the scope for further policy interventions, Philos. T. Roy. Soc. A, 378, 20190331, https://doi.org/10.1098/rsta.2019.0331, 2020. a, b
elis, C. A. and Van Dingenen, R.: Air quality and related health impact in the UNECE region: source attribution and scenario analysis, Atmos. Chem. Phys., 23, 8225–8240, https://doi.org/10.5194/acp-23-8225-2023, 2023. a
Bergström, R., Hayman, G. D., Jenkin, M. E., and Simpson, D.: Update and comparison of atmospheric chemistry mechanisms for the EMEP MSC-W model system, Tech. rep., https://emep.int/publ/reports/2022/MSCW_technical_1_2022.pdf (last access: 10 October 2024), 2022. a
Colette, A., Andersson, C., Baklanov, A., Bessagnet, B., Brandt, J., Christensen, J. H., Doherty, R., Engardt, M., Geels, C., Giannakopoulos, C., Hedegaard, G. B., Katragkou, E., Langner, J., Lei, H., Manders, A., Melas, D., Meleux, F., Rouïl, L., Sofiev, M., Soares, J., Stevenson, D. S., Tombrou-Tzella, M., Varotsos, K. V., and Young, P.: Is the ozone climate penalty robust in Europe?, Environ. Res. Lett., 10, 084015, https://doi.org/10.1088/1748-9326/10/8/084015, 2015. a, b
Crutzen, P. J., Lawrence, M. G., and Pöschl, U.: On the background photochemistry of tropospheric ozone, Tellus B, 51, 123–146, https://doi.org/10.3402/tellusb.v51i1.16264, 1999. a, b
de Meij, A., Cuvelier, C., Thunis, P., Pisoni, E., and Bessagnet, B.: Sensitivity of air quality model responses to emission changes: comparison of results based on four EU inventories through FAIRMODE benchmarking methodology, Geosci. Model Dev., 17, 587–606, https://doi.org/10.5194/gmd-17-587-2024, 2024. a
Dentener, F., Stevenson, D., Cofala, J., Mechler, R., Amann, M., Bergamaschi, P., Raes, F., and Derwent, R.: The impact of air pollutant and methane emission controls on tropospheric ozone and radiative forcing: CTM calculations for the period 1990-2030, Atmos. Chem. Phys., 5, 1731–1755, https://doi.org/10.5194/acp-5-1731-2005, 2005. a
ECMWF: IFS Documentation CY40R1 – Part IV: Physical Processes, Tech. Rep. 4, ECMWF, https://doi.org/10.21957/f56vvey1x, 2014. a
Emberson, L.: Effects of ozone on agriculture, forests and grasslands, Philos. T. Roy. Soc. A, 378, 20190327, https://doi.org/10.1098/rsta.2019.0327, 2020. a
EMEP/CEIP: Present state of emission data, https://www.ceip.at/webdab-emission-database/reported-emissiondata (last access: February 2024), 2023. a
EMEP MSC-W: OpenSource v5.0 (202310), Zenodo [code], https://doi.org/10.5281/zenodo.8431553, 2023. a, b
EMEP MSC-W, CCC, CEIP, and CIAM: Transboundary particulate matter, photo-oxidants, acidifying and eutrophying components. EMEP Status Report 1/2023, Tech. rep., The Norwegian Meteorological Institute, Oslo, Norway, https://www.emep.int (last access: March 2024), 2023. a
EU: Consolidated text: Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008 on ambient air quality and cleaner air for Europe, Tech. rep., Publications Office, https://eur-lex.europa.eu/EN/legal-content/summary/cleaner-air-for-europe.html (last access: February 2024), 2008. a
Fiore, A. M., West, J. J., Horowitz, L. W., Naik, V., and Schwarzkopf, M. D.: Characterizing the tropospheric ozone response to methane emission controls and the benefits to climate and air quality, J. Geophys. Res.-Atmos., 113, D08307, https://doi.org/10.1029/2007JD009162, 2008. a
Fleming, Z. L., Doherty, R. M., von Schneidemesser, E., Malley, C. S., Cooper, O. R., Pinto, J. P., Colette, A., Xu, X., Simpson, D., Schultz, M. G., Lefohn, A. S., Hamad, S., Moolla, R., Solberg, S., and Feng, Z.: Tropospheric Ozone Assessment Report: Present-day ozone distribution and trends relevant to human health, Elementa: Science of the Anthropocene, 6, 12, https://doi.org/10.1525/elementa.273, 2018. a
Forster, P., Storelvmo, T., Armour, K., Collins, W., Dufresne, J.-L., Frame, D., Lunt, D., Mauritsen, T., Palmer, M., Watanabe, M., Wild, M., and Zhang, H.: The Earth's Energy Budget, Climate Feedbacks, and Climate Sensitivity, Climate Change 2021: The Physical Science Basis, Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, https://doi.org/10.1017/9781009157896.009, 923–1054, 2021. a
Fu, T.-M. and Tian, H.: Climate change penalty to ozone air quality: review of current understandings and knowledge gaps, Current Pollution Reports, 5, 159–171, 2019. a
Ge, Y., Solberg, S., Heal, M. R., Reimann, S., van Caspel, W., Hellack, B., Salameh, T., and Simpson, D.: Evaluation of modelled versus observed non-methane volatile organic compounds at European Monitoring and Evaluation Programme sites in Europe, Atmos. Chem. Phys., 24, 7699–7729, https://doi.org/10.5194/acp-24-7699-2024, 2024. a, b
Gliss, J., Griesfeller, J., and Svennevik, H.: metno/pyaerocom: Release version 0.8.0, Zenodo [code], https://doi.org/10.5281/zenodo.4159570, 2020. a
Gomez Sanabria, A., Kiesewetter, G., Klimont, Z., Schoepp, W., and Haberl, H.: Potential for future reductions of global GHG and air pollutants from circular waste management systems, Nat. Commun., 13, 106, https://doi.org/10.1038/s41467-021-27624-7, 2022. a
Guevara, M., Jorba, O., Tena, C., Denier van der Gon, H., Kuenen, J., Elguindi, N., Darras, S., Granier, C., and Pérez García-Pando, C.: Copernicus Atmosphere Monitoring Service TEMPOral profiles for the Global domain version 2.1 (CAMS-GLOB-TEMPOv2.1), Copernicus Atmosphere Monitoring Service, ECCAD, https://doi.org/10.24380/ks45-9147, 2020a. a
Guevara, M., Jorba, O., Tena, C., Denier van der Gon, H., Kuenen, J., Elguindi, N., Darras, S., Granier, C., and Pérez García-Pando, C.: Copernicus Atmosphere Monitoring Service TEMPOral profiles for the regional European domain version 2.1 (CAMS-REG-TEMPOv2.1), Copernicus Atmosphere Monitoring Service, ECCAD, https://doi.org/10.24380/1cx4-zy68, 2020b. a
Guevara, M., Jorba, O., Tena, C., Denier van der Gon, H., Kuenen, J., Elguindi, N., Darras, S., Granier, C., and Pérez García-Pando, C.: Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO): global and European emission temporal profile maps for atmospheric chemistry modelling, Earth Syst. Sci. Data, 13, 367–404, https://doi.org/10.5194/essd-13-367-2021, 2021. a
Guo, J., Feng, H., Peng, C., Chen, H., Xu, X., Ma, X., Li, L., Kneeshaw, D., Ruan, H., Yang, H., and Wang, W.: Global Climate Change Increases Terrestrial Soil CH4 Emissions, Global Biogeochem. Cy., 37, e2021GB007255, https://doi.org/10.1029/2021GB007255, 2023. a
He, X., Shen, W., Wallington, T. J., Zhang, S., Wu, X., Bao, Z., and Wu, Y.: Asia Pacific road transportation emissions, 1900–2050, Faraday Discuss., 226, 53–73, https://doi.org/10.1039/D0FD00096E, 2021. a
Höglund-Isaksson, L.: Global anthropogenic methane emissions 2005–2030: technical mitigation potentials and costs, Atmos. Chem. Phys., 12, 9079–9096, https://doi.org/10.5194/acp-12-9079-2012, 2012. a
Höglund-Isaksson, L., Gómez-Sanabria, A., Klimont, Z., Rafaj, P., and Schöpp, W.: Technical potentials and costs for reducing global anthropogenic methane emissions in the 2050 timeframe – results from the GAINS model, Environ. Res. Commun., 2, 025004, https://doi.org/10.1088/2515-7620/ab7457, 2020. a
Holmes, C. D., Prather, M. J., Søvde, O. A., and Myhre, G.: Future methane, hydroxyl, and their uncertainties: key climate and emission parameters for future predictions, Atmos. Chem. Phys., 13, 285–302, https://doi.org/10.5194/acp-13-285-2013, 2013. a, b
Huangfu, P. and Atkinson, R.: Long-term exposure to NO2 and O3 and all-cause and respiratory mortality: A systematic review and meta-analysis, Environ. Int., 144, 105998, https://doi.org/10.1016/j.envint.2020.105998, 2020. a
IEA: World Energy Outlook 2018, https://www.iea.org/reports/world-energy-outlook-2018 (last access: April 2024), 2018. a
Isaksen, I. S. A., Berntsen, T. K., Dalsøren, S. B., Eleftheratos, K., Orsolini, Y., Rognerud, B., Stordal, F., Søvde, O. A., Zerefos, C., and Holmes, C. D.: Atmospheric Ozone and Methane in a Changing Climate, Atmosphere, 5, 518–535, https://doi.org/10.3390/atmos5030518, 2014. a
Jonson, J. E., Schulz, M., Emmons, L., Flemming, J., Henze, D., Sudo, K., Tronstad Lund, M., Lin, M., Benedictow, A., Koffi, B., Dentener, F., Keating, T., Kivi, R., and Davila, Y.: The effects of intercontinental emission sources on European air pollution levels, Atmos. Chem. Phys., 18, 13655–13672, https://doi.org/10.5194/acp-18-13655-2018, 2018. a, b
Kanter, D. R., Winiwarter, W., Bodirsky, B. L., Bouwman, L., Boyer, E., Buckle, S., Compton, J. E., Dalgaard, T., de Vries, W., Leclère, D., Leip, A., Müller, C., Popp, A., Raghuram, N., Rao, S., Sutton, M. A., Tian, H., Westhoek, H., Zhang, X., and Zurek, M.: A framework for nitrogen futures in the shared socioeconomic pathways, Global Environ. Chang., 61, 102029, https://doi.org/10.1016/j.gloenvcha.2019.102029, 2020. a
Klimont, Z., Kupiainen, K., Heyes, C., Purohit, P., Cofala, J., Rafaj, P., Borken-Kleefeld, J., and Schöpp, W.: Global anthropogenic emissions of particulate matter including black carbon, Atmos. Chem. Phys., 17, 8681–8723, https://doi.org/10.5194/acp-17-8681-2017, 2017. a
Laj, P., Myhre, C. L., Riffault, V., Amiridis, V., Fuchs, H., Eleftheriadis, K., Petäjä, T., Salameh, T., Kivekäs, N., Juurola, E., Saponaro, G., Philippin, S., Cornacchia, C., Arboledas, L. A., Baars, H., Claude, A., Mazière, M. D., Dils, B., Dufresne, M., Evangeliou, N., Favez, O., Fiebig, M., Haeffelin, M., Herrmann, H., Höhler, K., Illmann, N., Kreuter, A., Ludewig, E., Marinou, E., Möhler, O., Mona, L., Murberg, L. E., Nicolae, D., Novelli, A., O’Connor, E., Ohneiser, K., Altieri, R. M. P., Picquet-Varrault, B., van Pinxteren, D., Pospichal, B., Putaud, J.-P., Reimann, S., Siomos, N., Stachlewska, I., Tillmann, R., Voudouri, K. A., Wandinger, U., Wiedensohler, A., Apituley, A., Comerón, A., Gysel-Beer, M., Mihalopoulos, N., Nikolova, N., Pietruczuk, A., Sauvage, S., Sciare, J., Skov, H., Svendby, T., Swietlicki, E., Tonev, D., Vaughan, G., Zdimal, V., Baltensperger, U., Doussin, J.-F., Kulmala, M., Pappalardo, G., Sundet, S. S., and Vana, M.: Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS): The European Research Infrastructure Supporting Atmospheric Science, B. Am. Meteor. Soc., 105, E1098–E1136, https://doi.org/10.1175/BAMS-D-23-0064.1, 2024 (data available at: https://dc.actris.nilu.no/, last access: February 2024). a, b
Lan, X., Thoning, K., and Dlugokencky, E.: Trends in globally-averaged CH4, N2O, and SF6 determined from NOAA Global Monitoring Laboratory measurements, Version 2024-07, https://doi.org/10.15138/P8XG-AA10, 2024. a, b
Lefohn, A. S., Malley, C. S., Smith, L., Wells, B., Hazucha, M., Simon, H., Naik, V., Mills, G., Schultz, M. G., Paoletti, E., De Marco, A., Xu, X., Zhang, L., Wang, T., Neufeld, H. S., Musselman, R. C., Tarasick, D., Brauer, M., Feng, Z., Tang, H., Kobayashi, K., Sicard, P., Solberg, S., and Gerosa, G.: Tropospheric ozone assessment report: Global ozone metrics for climate change, human health, and crop/ecosystem research, Elementa: Science of the Anthropocene, 6, 27, https://doi.org/10.1525/elementa.279, 2018. a
MAGICC7: MAGICCv7.5.3 binary and the probabilistic distribution, registration required, MAGICC7 [code], https://magicc.org/download/magicc7, last access: 9 October 2024. a
Malley, C. S., Borgford-Parnell, N., Haeussling, S., Howard, I. C., Lefèvre, E. N., and Kuylenstierna, J. C. I.: A roadmap to achieve the global methane pledge, Environmental Research: Climate, 2, 011003, https://doi.org/10.1088/2752-5295/acb4b4, 2023. a
Mar, K. A., Unger, C., Walderdorff, L., and Butler, T.: Beyond CO2 equivalence: The impacts of methane on climate, ecosystems, and health, Environ. Sci. Pol., 134, 127–136, https://doi.org/10.1016/j.envsci.2022.03.027, 2022. a
Meinshausen, M., Meinshausen, N., Hare, W., Raper, S. C., Frieler, K., Knutti, R., Frame, D. J., and Allen, M. R.: Greenhouse-gas emission targets for limiting global warming to 2 C, Nature, 458, 1158–1162, https://doi.org/10.1038/nature08017, 2009. a
Meinshausen, M., Raper, S. C. B., and Wigley, T. M. L.: Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 – Part 1: Model description and calibration, Atmos. Chem. Phys., 11, 1417–1456, https://doi.org/10.5194/acp-11-1417-2011, 2011. a, b
Meinshausen, M., Vogel, E., Nauels, A., Lorbacher, K., Meinshausen, N., Etheridge, D. M., Fraser, P. J., Montzka, S. A., Rayner, P. J., Trudinger, C. M., Krummel, P. B., Beyerle, U., Canadell, J. G., Daniel, J. S., Enting, I. G., Law, R. M., Lunder, C. R., O'Doherty, S., Prinn, R. G., Reimann, S., Rubino, M., Velders, G. J. M., Vollmer, M. K., Wang, R. H. J., and Weiss, R.: Historical greenhouse gas concentrations for climate modelling (CMIP6), Geosci. Model Dev., 10, 2057–2116, https://doi.org/10.5194/gmd-10-2057-2017, 2017. a, b, c
Meinshausen, M., Nicholls, Z. R. J., Lewis, J., Gidden, M. J., Vogel, E., Freund, M., Beyerle, U., Gessner, C., Nauels, A., Bauer, N., Canadell, J. G., Daniel, J. S., John, A., Krummel, P. B., Luderer, G., Meinshausen, N., Montzka, S. A., Rayner, P. J., Reimann, S., Smith, S. J., van den Berg, M., Velders, G. J. M., Vollmer, M. K., and Wang, R. H. J.: The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500, Geosci. Model Dev., 13, 3571–3605, https://doi.org/10.5194/gmd-13-3571-2020, 2020. a, b, c, d, e
Mills, G., Sharps, K., Simpson, D., Pleijel, H., Broberg, M., Uddling, J., Jaramillo, F., Davies, W. J., Dentener, F., Van den Berg, M., Agrawal, M., Agrawal, S. B., Ainsworth, E. A., Büker, P., Emberson, L., Feng, Z., Harmens, H., Hayes, F., Kobayashi, K., Paoletti, E., and Van Dingenen, R.: Ozone pollution will compromise efforts to increase global wheat production, Glob. Change Biol., 24, 3560–3574, https://doi.org/10.1111/gcb.14157, 2018. a, b
Monks, P. S., Archibald, A. T., Colette, A., Cooper, O., Coyle, M., Derwent, R., Fowler, D., Granier, C., Law, K. S., Mills, G. E., Stevenson, D. S., Tarasova, O., Thouret, V., von Schneidemesser, E., Sommariva, R., Wild, O., and Williams, M. L.: Tropospheric ozone and its precursors from the urban to the global scale from air quality to short-lived climate forcer, Atmos. Chem. Phys., 15, 8889–8973, https://doi.org/10.5194/acp-15-8889-2015, 2015. a
Nicholls, Z., Meinshausen, M., Lewis, J., Corradi, M. R., Dorheim, K., Gasser, T., Gieseke, R., Hope, A. P., Leach, N. J., McBride, L. A., Quilcaille, Y., Rogelj, J., Salawitch, R. J., Samset, B. H., Sandstad, M., Shiklomanov, A., Skeie, R. B., Smith, C. J., Smith, S. J., Su, X., Tsutsui, J., Vega-Westhoff, B., and Woodard, D. L.: Reduced Complexity Model Intercomparison Project Phase 2: Synthesizing Earth System Knowledge for Probabilistic Climate Projections, Earth's Future, 9, e2020EF001900, https://doi.org/10.1029/2020EF001900, 2021. a
Nicholls, Z., Meinshausen, M., Lewis, J., Smith, C. J., Forster, P. M., Fuglestvedt, J. S., Rogelj, J., Kikstra, J. S., Riahi, K., and Byers, E.: Changes in IPCC Scenario Assessment Emulators Between SR1.5 and AR6 Unraveled, Geophys. Res. Lett., 49, e2022GL099788, https://doi.org/10.1029/2022GL099788, 2022. a, b
Nicholls, Z. R. J., Meinshausen, M., Lewis, J., Gieseke, R., Dommenget, D., Dorheim, K., Fan, C.-S., Fuglestvedt, J. S., Gasser, T., Golüke, U., Goodwin, P., Hartin, C., Hope, A. P., Kriegler, E., Leach, N. J., Marchegiani, D., McBride, L. A., Quilcaille, Y., Rogelj, J., Salawitch, R. J., Samset, B. H., Sandstad, M., Shiklomanov, A. N., Skeie, R. B., Smith, C. J., Smith, S., Tanaka, K., Tsutsui, J., and Xie, Z.: Reduced Complexity Model Intercomparison Project Phase 1: introduction and evaluation of global-mean temperature response, Geosci. Model Dev., 13, 5175–5190, https://doi.org/10.5194/gmd-13-5175-2020, 2020. a
O’Neill, B. C., Kriegler, E., Ebi, K. L., Kemp-Benedict, E., Riahi, K., Rothman, D. S., van Ruijven, B. J., van Vuuren, D. P., Birkmann, J., Kok, K., Levy, M., and Solecki, W.: The roads ahead: Narratives for shared socioeconomic pathways describing world futures in the 21st century, Global Environ. Chang., 42, 169–180, https://doi.org/10.1016/j.gloenvcha.2015.01.004, 2017. a, b
Pandey, D., Sharps, K., Simpson, D., Ramaswami, B., Cremades, R., Booth, N., Jamir, C., Büker, P., Sinha, V., Sinha, B., and Emberson, L. D.: Assessing the costs of ozone pollution in India for wheat producers, consumers, and government food welfare policies, P. Natl. Acad. Sci. USA, 120, e2207081120, https://doi.org/10.1073/pnas.2207081120, 2023. a
Rafaj, P., Kiesewetter, G., Gül, T., Schöpp, W., Cofala, J., Klimont, Z., Purohit, P., Heyes, C., Amann, M., B.-K., and J., Cozzi, L.: Outlook for clean air in the context of sustainable development goals, Global Environ. Chang., 53, 1–11, https://doi.org/10.1016/j.gloenvcha.2018.08.008, 2018. a
Rasmussen, D., Hu, J., Mahmud, A., and Kleeman, M. J.: The ozone–climate penalty: past, present, and future, Environ. Sci. Technol., 47, 14258–14266, 2013. a
Riahi, K., van Vuuren, D. P., Kriegler, E., Edmonds, J., O’Neill, B. C., Fujimori, S., Bauer, N., Calvin, K., Dellink, R., Fricko, O., Lutz, W., Popp, A., Cuaresma, J. C., KC, S., Leimbach, M., Jiang, L., Kram, T., Rao, S., Emmerling, J., Ebi, K., Hasegawa, T., Havlik, P., Humpenöder, F., Da Silva, L. A., Smith, S., Stehfest, E., Bosetti, V., Eom, J., Gernaat, D., Masui, T., Rogelj, J., Strefler, J., Drouet, L., Krey, V., Luderer, G., Harmsen, M., Takahashi, K., Baumstark, L., Doelman, J. C., Kainuma, M., Klimont, Z., Marangoni, G., Lotze-Campen, H., Obersteiner, M., Tabeau, A., and Tavoni, M.: The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview, Global Environ. Chang., 42, 153–168, https://doi.org/10.1016/j.gloenvcha.2016.05.009, 2017. a, b
Saunois, M., Stavert, A. R., Poulter, B., Bousquet, P., Canadell, J. G., Jackson, R. B., Raymond, P. A., Dlugokencky, E. J., Houweling, S., Patra, P. K., Ciais, P., Arora, V. K., Bastviken, D., Bergamaschi, P., Blake, D. R., Brailsford, G., Bruhwiler, L., Carlson, K. M., Carrol, M., Castaldi, S., Chandra, N., Crevoisier, C., Crill, P. M., Covey, K., Curry, C. L., Etiope, G., Frankenberg, C., Gedney, N., Hegglin, M. I., Höglund-Isaksson, L., Hugelius, G., Ishizawa, M., Ito, A., Janssens-Maenhout, G., Jensen, K. M., Joos, F., Kleinen, T., Krummel, P. B., Langenfelds, R. L., Laruelle, G. G., Liu, L., Machida, T., Maksyutov, S., McDonald, K. C., McNorton, J., Miller, P. A., Melton, J. R., Morino, I., Müller, J., Murguia-Flores, F., Naik, V., Niwa, Y., Noce, S., O'Doherty, S., Parker, R. J., Peng, C., Peng, S., Peters, G. P., Prigent, C., Prinn, R., Ramonet, M., Regnier, P., Riley, W. J., Rosentreter, J. A., Segers, A., Simpson, I. J., Shi, H., Smith, S. J., Steele, L. P., Thornton, B. F., Tian, H., Tohjima, Y., Tubiello, F. N., Tsuruta, A., Viovy, N., Voulgarakis, A., Weber, T. S., van Weele, M., van der Werf, G. R., Weiss, R. F., Worthy, D., Wunch, D., Yin, Y., Yoshida, Y., Zhang, W., Zhang, Z., Zhao, Y., Zheng, B., Zhu, Q., Zhu, Q., and Zhuang, Q.: The Global Methane Budget 2000–2017, Earth Syst. Sci. Data, 12, 1561–1623, https://doi.org/10.5194/essd-12-1561-2020, 2020. a, b
Schiavina, M., Melchiorri, M., Pesaresi, M., Politis, P., Carneiro Freire, S., Maffenini, L., Florio, P., Ehrlich, D., Goch, K., Carioli, A., Uhl, J., Tommasi, P., and Kemper, T.: GHSL Data Package 2023, Publications Office of the European Union, https://doi.org/10.2760/098587, 2023. a
Schneider von Deimling, T., Meinshausen, M., Levermann, A., Huber, V., Frieler, K., Lawrence, D. M., and Brovkin, V.: Estimating the near-surface permafrost-carbon feedback on global warming, Biogeosciences, 9, 649–665, https://doi.org/10.5194/bg-9-649-2012, 2012. a
Simpson, D.: The EMEP MSC-W modelling programme: Its relationship to policy support, current challenges and future perspectives, in: Air Pollution Modelling and its Application XXII, edited by: Steyn, D., Builtjes, P., and Timmermans, R., NATO Science for Peace and Security Series C, Environmental Security, Springer, Dordrecht, 32nd NATO/SPS International Technical Meeting, 265–268, ISBN 978-94-007-5577-2, 2013. a
Simpson, D. and Darras, S.: Global soil NO emissions for Atmospheric Chemical Transport Modelling: CAMS-GLOB-SOIL v2.2, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2021-221, 2021. a
Simpson, D., Ashmore, M., Emberson, L., and Tuovinen, J.-P.: A comparison of two different approaches for mapping potential ozone damage to vegetation. A model study, Environ. Pollut., 146, 715–725, https://doi.org/10.1016/j.envpol.2006.04.013, 2007. a
Simpson, D., Benedictow, A., Berge, H., Bergström, R., Emberson, L. D., Fagerli, H., Flechard, C. R., Hayman, G. D., Gauss, M., Jonson, J. E., Jenkin, M. E., Nyíri, A., Richter, C., Semeena, V. S., Tsyro, S., Tuovinen, J.-P., Valdebenito, Á., and Wind, P.: The EMEP MSC-W chemical transport model – technical description, Atmos. Chem. Phys., 12, 7825–7865, https://doi.org/10.5194/acp-12-7825-2012, 2012. a, b, c
Simpson, D., Tsyro, S., and Wind, P.: Updates to the EMEP/MSC-W model, in: Transboundary particulate matter, photo-oxidants, acidifying and eutrophying components. EMEP Status Report 1/2015, The Norwegian Meteorological Institute, Oslo, Norway, 129–138, https://emep.int/publ/reports/2015/EMEP_Status_Report_1_2015.pdf (last access: July 2024), 2015. a
Stadtler, S., Simpson, D., Schröder, S., Taraborrelli, D., Bott, A., and Schultz, M.: Ozone impacts of gas–aerosol uptake in global chemistry transport models, Atmos. Chem. Phys., 18, 3147–3171, https://doi.org/10.5194/acp-18-3147-2018, 2018. a
The Food and Land Use Coalition: Growing Better: Ten Critical Transitions to Transform Food and Land Use, https://www.foodandlandusecoalition.org/ (last access: 10 October 2024), 2019. a
Thunis, P., Clappier, A., Pisoni, E., Bessagnet, B., Kuenen, J., Guevara, M., and Lopez-Aparicio, S.: A multi-pollutant and multi-sectorial approach to screening the consistency of emission inventories, Geosci. Model Dev., 15, 5271–5286, https://doi.org/10.5194/gmd-15-5271-2022, 2022. a
Tørseth, K., Aas, W., Breivik, K., Fjæraa, A. M., Fiebig, M., Hjellbrekke, A. G., Lund Myhre, C., Solberg, S., and Yttri, K. E.: Introduction to the European Monitoring and Evaluation Programme (EMEP) and observed atmospheric composition change during 1972–2009, Atmos. Chem. Phys., 12, 5447–5481, https://doi.org/10.5194/acp-12-5447-2012, 2012 (data available at: https://ebas.nilu.no/, last access: February 2024). a, b
Turnock, S. T., Wild, O., Dentener, F. J., Davila, Y., Emmons, L. K., Flemming, J., Folberth, G. A., Henze, D. K., Jonson, J. E., Keating, T. J., Kengo, S., Lin, M., Lund, M., Tilmes, S., and O'Connor, F. M.: The impact of future emission policies on tropospheric ozone using a parameterised approach, Atmos. Chem. Phys., 18, 8953–8978, https://doi.org/10.5194/acp-18-8953-2018, 2018. a, b, c, d, e
UNECE: Mapping critical levels for vegetations. Revised Chapter 3 of the Manual on Methodologies and Criteria for Modelling and Mapping Critical Loads and Levels and Air Pollution Effects, Risks and Trends., ICP vegetation, CEH, UK, https://unece.org/fileadmin/DAM/env/documents/2017/AIR/EMEP/Final__new_Chapter_3_v2__August_2017_.pdf (last access: March 2024), 2017. a, b
van Caspel, W. E., Simpson, D., Jonson, J. E., Benedictow, A. M. K., Ge, Y., di Sarra, A., Pace, G., Vieno, M., Walker, H. L., and Heal, M. R.: Implementation and evaluation of updated photolysis rates in the EMEP MSC-W chemistry-transport model using Cloud-J v7.3e, Geosci. Model Dev., 16, 7433–7459, https://doi.org/10.5194/gmd-16-7433-2023, 2023. a
van Caspel, W. E., Klimont, Z., Heyes, C., and Fagerli, H.: Dataset supporting the article: Impact of methane and other precursor emission reductions on surface ozone in Europe: Scenario analysis using the EMEP MSC-W model, Zenodo [data set], https://doi.org/10.5281/zenodo.13287103, 2024. a
WHO: WHO global air quality guidelines. Particulate Matter (PM2.5 and PM10), Ozone, Nitrogen Dioxide, Sulfur Dioxide and Carbon Monoxide, World Health Organization Geneva, Switzerland, Licence: CC BY-NC-SA 3.0 IGO, ISBN 9789240034228, 2021. a
Wiedinmyer, C., Kimura, Y., McDonald-Buller, E. C., Emmons, L. K., Buchholz, R. R., Tang, W., Seto, K., Joseph, M. B., Barsanti, K. C., Carlton, A. G., and Yokelson, R.: The Fire Inventory from NCAR version 2.5: an updated global fire emissions model for climate and chemistry applications, Geosci. Model Dev., 16, 3873–3891, https://doi.org/10.5194/gmd-16-3873-2023, 2023. a
Willett, W., Rockström, J., Loken, B., Springmann, M., Lang, T., Vermeulen, S., Garnett, T., Tilman, D., DeClerck, F., Wood, A., Jonell, M., Clark, M., Gordon, L. J., Fanzo, J., Hawkes, C., Zurayk, R., Rivera, J. A., De Vries, W., Majele Sibanda, L., Afshin, A., Chaudhary, A., Herrero, M., Agustina, R., Branca, F., Lartey, A., Fan, S., Crona, B., Fox, E., Bignet, V., Troell, M., Lindahl, T., Singh, S., Cornell, S. E., Srinath Reddy, K., Narain, S., Nishtar, S., and Murray, C. J. L.: Food in the Anthropocene: the EAT–Lancet Commission on healthy diets from sustainable food systems, Lancet, 393, 447–492, https://doi.org/10.1016/S0140-6736(18)31788-4, 2019. a
Winiwarter, W., Höglund-Isaksson, L., Klimont, Z., Schöpp, W., and Amann, M.: Technical opportunities to reduce global anthropogenic emissions of nitrous oxide, Environ. Res. Lett., 13, 014011, https://doi.org/10.1088/1748-9326/aa9ec9, 2018. a
Zhang, X.: Emission standards and control of PM2.5 from coal power plants, IEA Clean Coal Centre, London, ISBN: 978-92-9029-590-7, 2018. a
Short summary
Methane in the atmosphere contributes to the production of ozone gas – an air pollutant and greenhouse gas. Our results highlight that simultaneous reductions in methane emissions help avoid offsetting the air pollution benefits already achieved by the already-approved precursor emission reductions by 2050 in the European Monitoring and Evaluation Programme region, while also playing an important role in bringing air pollution further down towards World Health Organization guideline limits.
Methane in the atmosphere contributes to the production of ozone gas – an air pollutant and...
Altmetrics
Final-revised paper
Preprint