Articles | Volume 13, issue 1
https://doi.org/10.5194/gmd-13-363-2020
https://doi.org/10.5194/gmd-13-363-2020
Development and technical paper
 | 
31 Jan 2020
Development and technical paper |  | 31 Jan 2020

Are contributions of emissions to ozone a matter of scale? – a study using MECO(n) (MESSy v2.50)

Mariano Mertens, Astrid Kerkweg, Volker Grewe, Patrick Jöckel, and Robert Sausen

Related authors

Chemistry–climate feedback of atmospheric methane in a methane-emission-flux-driven chemistry–climate model
Laura Stecher, Franziska Winterstein, Patrick Jöckel, Michael Ponater, Mariano Mertens, and Martin Dameris
Atmos. Chem. Phys., 25, 5133–5158, https://doi.org/10.5194/acp-25-5133-2025,https://doi.org/10.5194/acp-25-5133-2025, 2025
Short summary
Effects of different emission inventories on tropospheric ozone and methane lifetime
Catherine Acquah, Laura Stecher, Mariano Mertens, and Patrick Jöckel
EGUsphere, https://doi.org/10.5194/egusphere-2025-294,https://doi.org/10.5194/egusphere-2025-294, 2025
Short summary
Airborne in situ quantification of methane emissions from oil and gas production in Romania
Hossein Maazallahi, Foteini Stavropoulou, Samuel Jonson Sutanto, Michael Steiner, Dominik Brunner, Mariano Mertens, Patrick Jöckel, Antoon Visschedijk, Hugo Denier van der Gon, Stijn Dellaert, Nataly Velandia Salinas, Stefan Schwietzke, Daniel Zavala-Araiza, Sorin Ghemulet, Alexandru Pana, Magdalena Ardelean, Marius Corbu, Andreea Calcan, Stephen A. Conley, Mackenzie L. Smith, and Thomas Röckmann
Atmos. Chem. Phys., 25, 1497–1511, https://doi.org/10.5194/acp-25-1497-2025,https://doi.org/10.5194/acp-25-1497-2025, 2025
Short summary
Ozone source attribution in polluted European areas during summer 2017 as simulated with MECO(n)
Markus Kilian, Volker Grewe, Patrick Jöckel, Astrid Kerkweg, Mariano Mertens, Andreas Zahn, and Helmut Ziereis
Atmos. Chem. Phys., 24, 13503–13523, https://doi.org/10.5194/acp-24-13503-2024,https://doi.org/10.5194/acp-24-13503-2024, 2024
Short summary
Climate Forcing due to Future Ozone Changes: An intercomparison of metrics and methods
William J. Collins, Fiona M. O'Connor, Connor R. Barker, Rachael E. Byrom, Sebastian D. Eastham, Øivind Hodnebrog, Patrick Jöckel, Eloise A. Marais, Mariano Mertens, Gunnar Myhre, Matthias Nützel, Dirk Olivié, Ragnhild Bieltvedt Skeie, Laura Stecher, Larry W. Horowitz, Vaishali Naik, Gregory Faluvegi, Ulas Im, Lee T. Murray, Drew Shindell, Kostas Tsigaridis, Nathan Luke Abraham, and James Keeble
EGUsphere, https://doi.org/10.5194/egusphere-2024-3698,https://doi.org/10.5194/egusphere-2024-3698, 2024
Short summary

Related subject area

Atmospheric sciences
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025,https://doi.org/10.5194/gmd-18-2861-2025, 2025
Short summary
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025,https://doi.org/10.5194/gmd-18-2747-2025, 2025
Short summary
Similarity-based analysis of atmospheric organic compounds for machine learning applications
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025,https://doi.org/10.5194/gmd-18-2701-2025, 2025
Short summary
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025,https://doi.org/10.5194/gmd-18-2679-2025, 2025
Short summary
Estimation of aerosol and cloud radiative heating rate in the tropical stratosphere using a radiative kernel method
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025,https://doi.org/10.5194/gmd-18-2569-2025, 2025
Short summary

Cited articles

Butler, T., Lupascu, A., Coates, J., and Zhu, S.: TOAST 1.0: Tropospheric Ozone Attribution of Sources with Tagging for CESM 1.2.2, Geosci. Model Dev., 11, 2825–2840, https://doi.org/10.5194/gmd-11-2825-2018, 2018. a
Christensen, J. H., Carter, T. R., Rummukainen, M., and Amanatidis, G.: Evaluating the performance and utility of regional climate models: the PRUDENCE project, Clim. Change, 81, 1–6, https://doi.org/10.1007/s10584-006-9211-6, 2007. a
Clappier, A., Belis, C. A., Pernigotti, D., and Thunis, P.: Source apportionment and sensitivity analysis: two methodologies with two different purposes, Geosci. Model Dev., 10, 4245–4256, https://doi.org/10.5194/gmd-10-4245-2017, 2017. a
Dahlmann, K., Grewe, V., Ponater, M., and Matthes, S.: Quantifying the contributions of individual NOx sources to the trend in ozone radiative forcing, Atmos. Environ., 45, 2860–2868, https://doi.org/10.1016/j.atmosenv.2011.02.071, 2011. a
Deckert, R., Jöckel, P., Grewe, V., Gottschaldt, K.-D., and Hoor, P.: A quasi chemistry-transport model mode for EMAC, Geosci. Model Dev., 4, 195–206, https://doi.org/10.5194/gmd-4-195-2011, 2011. a
Download
Short summary
This study investigates if ozone source apportionment results using a tagged tracer approach depend on the resolutions of the applied model and/or emission inventory. For this we apply a global to regional atmospheric chemistry model, which allows us to compare the results on global and regional scales. Our results show that differences on the continental scale (e.g. Europe) are rather small (10 %); on the regional scale, however, differences of up to 30 % were found.
Share