Articles | Volume 8, issue 10
https://doi.org/10.5194/gmd-8-3231-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-8-3231-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
13 Oct 2015
Development and technical paper |
| 13 Oct 2015
Analysis of the impact of inhomogeneous emissions in the Operational Street Pollution Model (OSPM)
T.-B. Ottosen
Department of Chemical Engineering, Texas A&M University at Qatar, Doha, Qatar
Department of Chemical Engineering, Biotechnology and Environmental Technology, University of Southern Denmark, Odense, Denmark
K. E. Kakosimos
CORRESPONDING AUTHOR
Department of Chemical Engineering, Texas A&M University at Qatar, Doha, Qatar
C. Johansson
Department of Environmental Science and Analytical Chemistry, Stockholm University, Stockholm, Sweden
Environment and Health Administration, Stockholm, Sweden
O. Hertel
Department of Environmental Science, Aarhus University, Roskilde, Denmark
J. Brandt
Department of Environmental Science, Aarhus University, Roskilde, Denmark
Department of Chemical Engineering, Biotechnology and Environmental Technology, University of Southern Denmark, Odense, Denmark
Department of Environmental Science, Aarhus University, Roskilde, Denmark
R. Berkowicz
Department of Environmental Science, Aarhus University, Roskilde, Denmark
T. Ellermann
Department of Environmental Science, Aarhus University, Roskilde, Denmark
S. S. Jensen
Department of Environmental Science, Aarhus University, Roskilde, Denmark
M. Ketzel
Department of Environmental Science, Aarhus University, Roskilde, Denmark
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EGUsphere, https://doi.org/10.5194/egusphere-2024-3750, https://doi.org/10.5194/egusphere-2024-3750, 2025
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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
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Jakob Boyd Pernov, Jens Liengaard Hjorth, Lise Lotte Sørensen, and Henrik Skov
Atmos. Chem. Phys., 24, 13603–13631, https://doi.org/10.5194/acp-24-13603-2024, https://doi.org/10.5194/acp-24-13603-2024, 2024
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Jiemei Liu, Jesper H. Christensen, Zhuyun Ye, Shikui Dong, Camilla Geels, Jørgen Brandt, Athanasios Nenes, Yuan Yuan, and Ulas Im
Atmos. Chem. Phys., 24, 10849–10867, https://doi.org/10.5194/acp-24-10849-2024, https://doi.org/10.5194/acp-24-10849-2024, 2024
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China was chosen as an example to conduct a quantitative analysis using the Danish Eulerian Hemispheric Model (DEHM) system with meteorological input from the Weather Research and Forecasting (WRF) model. Meteorological conditions and emission inventories contributed 46 % (65 %) and 54 % (35 %) to the variations in PM2.5 concentrations (oxidative potential – OP), respectively, highlighting secondary aerosol formation and biomass burning as the primary contributors to PM2.5 and OP levels.
Ville-Veikko Paunu, Niko Karvosenoja, David Segersson, Susana López-Aparicio, Ole-Kenneth Nielsen, Marlene Schmidt Plejdrup, Throstur Thorsteinsson, Dam Thanh Vo, Jeroen Kuenen, Hugo Denier van der Gon, Jukka-Pekka Jalkanen, Jørgen Brandt, and Camilla Geels
Earth Syst. Sci. Data, 16, 1453–1474, https://doi.org/10.5194/essd-16-1453-2024, https://doi.org/10.5194/essd-16-1453-2024, 2024
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Air pollution is an important cause of adverse health effects, even in Nordic countries. To assess their health impacts, emission inventories with high spatial resolution are needed. We studied how national data and methods for the spatial distribution of the emissions compare to a European level inventory. For road transport the methods are well established, but for machinery and off-road emissions the current recommendations for the spatial distribution of these emissions should be improved.
Thibaud Sarica, Alice Maison, Yelva Roustan, Matthias Ketzel, Steen Solvang Jensen, Youngseob Kim, Christophe Chaillou, and Karine Sartelet
Geosci. Model Dev., 16, 5281–5303, https://doi.org/10.5194/gmd-16-5281-2023, https://doi.org/10.5194/gmd-16-5281-2023, 2023
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A new version of the Model of Urban Network of Intersecting Canyons and Highways (MUNICH) is developed to represent heterogeneities of concentrations in streets. The street volume is discretized vertically and horizontally to limit the artificial dilution of emissions and concentrations. This new version is applied to street networks in Copenhagen and Paris. The comparisons to observations are improved, with higher concentrations of pollutants emitted by traffic at the bottom of the street.
Eleftherios Ioannidis, Kathy S. Law, Jean-Christophe Raut, Louis Marelle, Tatsuo Onishi, Rachel M. Kirpes, Lucia M. Upchurch, Thomas Tuch, Alfred Wiedensohler, Andreas Massling, Henrik Skov, Patricia K. Quinn, and Kerri A. Pratt
Atmos. Chem. Phys., 23, 5641–5678, https://doi.org/10.5194/acp-23-5641-2023, https://doi.org/10.5194/acp-23-5641-2023, 2023
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Remote and local anthropogenic emissions contribute to wintertime Arctic haze, with enhanced aerosol concentrations, but natural sources, which also contribute, are less well studied. Here, modelled wintertime sea-spray aerosols are improved in WRF-Chem over the wider Arctic by including updated wind speed and temperature-dependent treatments. As a result, anthropogenic nitrate aerosols are also improved. Open leads are confirmed to be the main source of sea-spray aerosols over northern Alaska.
Andreas Massling, Robert Lange, Jakob Boyd Pernov, Ulrich Gosewinkel, Lise-Lotte Sørensen, and Henrik Skov
Atmos. Chem. Phys., 23, 4931–4953, https://doi.org/10.5194/acp-23-4931-2023, https://doi.org/10.5194/acp-23-4931-2023, 2023
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The effect of anthropogenic activities on cloud formation introduces the highest uncertainties with respect to climate change. Data on Arctic aerosols and their corresponding cloud-forming properties are very scarce and most important as the Arctic is warming about 2 times as fast as the rest of the globe. Our studies investigate aerosols in the remote Arctic and suggest relatively high cloud-forming potential, although differences are observed between the Arctic spring and summer.
Kevin C. H. Sze, Heike Wex, Markus Hartmann, Henrik Skov, Andreas Massling, Diego Villanueva, and Frank Stratmann
Atmos. Chem. Phys., 23, 4741–4761, https://doi.org/10.5194/acp-23-4741-2023, https://doi.org/10.5194/acp-23-4741-2023, 2023
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Ice-nucleating particles (INPs) play an important role in cloud formation and thus in our climate. But little is known about the abundance and properties of INPs, especially in the Arctic, where the temperature increases almost 4 times as fast as that of the rest of the globe. We observe higher INP concentrations and more biological INPs in summer than in winter, likely from local sources. We also provide three equations for estimating INP concentrations in models at different times of the year.
Erik Ahlberg, Stina Ausmeel, Lovisa Nilsson, Mårten Spanne, Julija Pauraite, Jacob Klenø Nøjgaard, Michele Bertò, Henrik Skov, Pontus Roldin, Adam Kristensson, Erik Swietlicki, and Axel Eriksson
Atmos. Chem. Phys., 23, 3051–3064, https://doi.org/10.5194/acp-23-3051-2023, https://doi.org/10.5194/acp-23-3051-2023, 2023
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James Brean, David C. S. Beddows, Roy M. Harrison, Congbo Song, Peter Tunved, Johan Ström, Radovan Krejci, Eyal Freud, Andreas Massling, Henrik Skov, Eija Asmi, Angelo Lupi, and Manuel Dall'Osto
Atmos. Chem. Phys., 23, 2183–2198, https://doi.org/10.5194/acp-23-2183-2023, https://doi.org/10.5194/acp-23-2183-2023, 2023
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Our results emphasize how understanding the geographical variation in surface types across the Arctic is key to understanding secondary aerosol sources. We provide a harmonised analysis of new particle formation across the Arctic.
Cynthia H. Whaley, Kathy S. Law, Jens Liengaard Hjorth, Henrik Skov, Stephen R. Arnold, Joakim Langner, Jakob Boyd Pernov, Garance Bergeron, Ilann Bourgeois, Jesper H. Christensen, Rong-You Chien, Makoto Deushi, Xinyi Dong, Peter Effertz, Gregory Faluvegi, Mark Flanner, Joshua S. Fu, Michael Gauss, Greg Huey, Ulas Im, Rigel Kivi, Louis Marelle, Tatsuo Onishi, Naga Oshima, Irina Petropavlovskikh, Jeff Peischl, David A. Plummer, Luca Pozzoli, Jean-Christophe Raut, Tom Ryerson, Ragnhild Skeie, Sverre Solberg, Manu A. Thomas, Chelsea Thompson, Kostas Tsigaridis, Svetlana Tsyro, Steven T. Turnock, Knut von Salzen, and David W. Tarasick
Atmos. Chem. Phys., 23, 637–661, https://doi.org/10.5194/acp-23-637-2023, https://doi.org/10.5194/acp-23-637-2023, 2023
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Ville Leinonen, Harri Kokkola, Taina Yli-Juuti, Tero Mielonen, Thomas Kühn, Tuomo Nieminen, Simo Heikkinen, Tuuli Miinalainen, Tommi Bergman, Ken Carslaw, Stefano Decesari, Markus Fiebig, Tareq Hussein, Niku Kivekäs, Radovan Krejci, Markku Kulmala, Ari Leskinen, Andreas Massling, Nikos Mihalopoulos, Jane P. Mulcahy, Steffen M. Noe, Twan van Noije, Fiona M. O'Connor, Colin O'Dowd, Dirk Olivie, Jakob B. Pernov, Tuukka Petäjä, Øyvind Seland, Michael Schulz, Catherine E. Scott, Henrik Skov, Erik Swietlicki, Thomas Tuch, Alfred Wiedensohler, Annele Virtanen, and Santtu Mikkonen
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We provide the first extensive comparison of detailed aerosol size distribution trends between in situ observations from Europe and five different earth system models. We investigated aerosol modes (nucleation, Aitken, and accumulation) separately and were able to show the differences between measured and modeled trends and especially their seasonal patterns. The differences in model results are likely due to complex effects of several processes instead of certain specific model features.
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
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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.
Ranjeet S. Sokhi, Nicolas Moussiopoulos, Alexander Baklanov, John Bartzis, Isabelle Coll, Sandro Finardi, Rainer Friedrich, Camilla Geels, Tiia Grönholm, Tomas Halenka, Matthias Ketzel, Androniki Maragkidou, Volker Matthias, Jana Moldanova, Leonidas Ntziachristos, Klaus Schäfer, Peter Suppan, George Tsegas, Greg Carmichael, Vicente Franco, Steve Hanna, Jukka-Pekka Jalkanen, Guus J. M. Velders, and Jaakko Kukkonen
Atmos. Chem. Phys., 22, 4615–4703, https://doi.org/10.5194/acp-22-4615-2022, https://doi.org/10.5194/acp-22-4615-2022, 2022
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This review of air quality research focuses on developments over the past decade. The article considers current and future challenges that are important from air quality research and policy perspectives and highlights emerging prominent gaps of knowledge. The review also examines how air pollution management needs to adapt to new challenges and makes recommendations to guide the direction for future air quality research within the wider community and to provide support for policy.
Danilo Custódio, Katrine Aspmo Pfaffhuber, T. Gerard Spain, Fidel F. Pankratov, Iana Strigunova, Koketso Molepo, Henrik Skov, Johannes Bieser, and Ralf Ebinghaus
Atmos. Chem. Phys., 22, 3827–3840, https://doi.org/10.5194/acp-22-3827-2022, https://doi.org/10.5194/acp-22-3827-2022, 2022
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As a poison in the air that we breathe and the food that we eat, mercury is a human health concern for society as a whole. In that regard, this work deals with monitoring and modelling mercury in the environment, improving wherewithal, identifying the strength of the different components at play, and interpreting information to support the efforts that seek to safeguard public health.
Julia Schmale, Sangeeta Sharma, Stefano Decesari, Jakob Pernov, Andreas Massling, Hans-Christen Hansson, Knut von Salzen, Henrik Skov, Elisabeth Andrews, Patricia K. Quinn, Lucia M. Upchurch, Konstantinos Eleftheriadis, Rita Traversi, Stefania Gilardoni, Mauro Mazzola, James Laing, and Philip Hopke
Atmos. Chem. Phys., 22, 3067–3096, https://doi.org/10.5194/acp-22-3067-2022, https://doi.org/10.5194/acp-22-3067-2022, 2022
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Long-term data sets of Arctic aerosol properties from 10 stations across the Arctic provide evidence that anthropogenic influence on the Arctic atmospheric chemical composition has declined in winter, a season which is typically dominated by mid-latitude emissions. The number of significant trends in summer is smaller than in winter, and overall the pattern is ambiguous with some significant positive and negative trends. This reflects the mixed influence of natural and anthropogenic emissions.
Jakob Boyd Pernov, Bjarne Jensen, Andreas Massling, Daniel Charles Thomas, and Henrik Skov
Atmos. Chem. Phys., 21, 13287–13309, https://doi.org/10.5194/acp-21-13287-2021, https://doi.org/10.5194/acp-21-13287-2021, 2021
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Atmospheric mercury species (GEM, GOM, PHg) are important constituents in the High Arctic due to their detrimental effects on human and ecosystem health. However, understanding their behavior in the High Arctic summer remains lacking. This research investigates the dynamics of mercury oxidation in the High Arctic summer. The cold, dry, sunlit free troposphere was associated with events of high GOM in the High Arctic summer, while individual events yielded unique origins.
Camilla Geels, Morten Winther, Camilla Andersson, Jukka-Pekka Jalkanen, Jørgen Brandt, Lise M. Frohn, Ulas Im, Wing Leung, and Jesper H. Christensen
Atmos. Chem. Phys., 21, 12495–12519, https://doi.org/10.5194/acp-21-12495-2021, https://doi.org/10.5194/acp-21-12495-2021, 2021
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In this study, we set up new shipping emissions scenarios and use two chemistry transport models and a health assessment model to assess the development of air quality and related health impacts in the Nordic region. Shipping alone is associated with about 850 premature deaths during present-day conditions, decreasing to approximately 550–600 cases in the 2050 scenarios.
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
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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.
Jakob B. Pernov, Rossana Bossi, Thibaut Lebourgeois, Jacob K. Nøjgaard, Rupert Holzinger, Jens L. Hjorth, and Henrik Skov
Atmos. Chem. Phys., 21, 2895–2916, https://doi.org/10.5194/acp-21-2895-2021, https://doi.org/10.5194/acp-21-2895-2021, 2021
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Volatile organic compounds (VOCs) are an important constituent in the Arctic atmosphere due to their effect on aerosol and ozone formation. However, an understanding of their sources is lacking. This research presents a multiseason high-time-resolution dataset of VOCs in the Arctic and details their temporal characteristics and source apportionment. Four sources were identified: biomass burning, marine cryosphere, background, and Arctic haze.
Xin Yang, Anne-M. Blechschmidt, Kristof Bognar, Audra McClure-Begley, Sara Morris, Irina Petropavlovskikh, Andreas Richter, Henrik Skov, Kimberly Strong, David W. Tarasick, Taneil Uttal, Mika Vestenius, and Xiaoyi Zhao
Atmos. Chem. Phys., 20, 15937–15967, https://doi.org/10.5194/acp-20-15937-2020, https://doi.org/10.5194/acp-20-15937-2020, 2020
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This is a modelling-based study on Arctic surface ozone, with a particular focus on spring ozone depletion events (i.e. with concentrations < 10 ppbv). Model experiments show that model runs with blowing-snow-sourced sea salt aerosols implemented as a source of reactive bromine can reproduce well large-scale ozone depletion events observed in the Arctic. This study supplies modelling evidence of the proposed mechanism of reactive-bromine release from blowing snow on sea ice (Yang et al., 2008).
Henrik Skov, Jens Hjorth, Claus Nordstrøm, Bjarne Jensen, Christel Christoffersen, Maria Bech Poulsen, Jesper Baldtzer Liisberg, David Beddows, Manuel Dall'Osto, and Jesper Heile Christensen
Atmos. Chem. Phys., 20, 13253–13265, https://doi.org/10.5194/acp-20-13253-2020, https://doi.org/10.5194/acp-20-13253-2020, 2020
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Mercury is toxic in all its forms. It bioaccumulates in food webs, is ubiquitous in the atmosphere, and atmospheric transport is an important source for this element in the Arctic. Measurements of gaseous elemental mercury have been carried out at the Villum Research Station at Station Nord in northern Greenland since 1999. The measurements are compared with model results from the Danish Eulerian Hemispheric Model. In this way, the dynamics of mercury are investigated.
Tuukka Petäjä, Ella-Maria Duplissy, Ksenia Tabakova, Julia Schmale, Barbara Altstädter, Gerard Ancellet, Mikhail Arshinov, Yurii Balin, Urs Baltensperger, Jens Bange, Alison Beamish, Boris Belan, Antoine Berchet, Rossana Bossi, Warren R. L. Cairns, Ralf Ebinghaus, Imad El Haddad, Beatriz Ferreira-Araujo, Anna Franck, Lin Huang, Antti Hyvärinen, Angelika Humbert, Athina-Cerise Kalogridis, Pavel Konstantinov, Astrid Lampert, Matthew MacLeod, Olivier Magand, Alexander Mahura, Louis Marelle, Vladimir Masloboev, Dmitri Moisseev, Vaios Moschos, Niklas Neckel, Tatsuo Onishi, Stefan Osterwalder, Aino Ovaska, Pauli Paasonen, Mikhail Panchenko, Fidel Pankratov, Jakob B. Pernov, Andreas Platis, Olga Popovicheva, Jean-Christophe Raut, Aurélie Riandet, Torsten Sachs, Rosamaria Salvatori, Roberto Salzano, Ludwig Schröder, Martin Schön, Vladimir Shevchenko, Henrik Skov, Jeroen E. Sonke, Andrea Spolaor, Vasileios K. Stathopoulos, Mikko Strahlendorff, Jennie L. Thomas, Vito Vitale, Sterios Vratolis, Carlo Barbante, Sabine Chabrillat, Aurélien Dommergue, Konstantinos Eleftheriadis, Jyri Heilimo, Kathy S. Law, Andreas Massling, Steffen M. Noe, Jean-Daniel Paris, André S. H. Prévôt, Ilona Riipinen, Birgit Wehner, Zhiyong Xie, and Hanna K. Lappalainen
Atmos. Chem. Phys., 20, 8551–8592, https://doi.org/10.5194/acp-20-8551-2020, https://doi.org/10.5194/acp-20-8551-2020, 2020
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The role of polar regions is increasing in terms of megatrends such as globalization, new transport routes, demography, and the use of natural resources with consequent effects on regional and transported pollutant concentrations. Here we summarize initial results from our integrative project exploring the Arctic environment and pollution to deliver data products, metrics, and indicators for stakeholders.
Jaakko Kukkonen, Susana López-Aparicio, David Segersson, Camilla Geels, Leena Kangas, Mari Kauhaniemi, Androniki Maragkidou, Anne Jensen, Timo Assmuth, Ari Karppinen, Mikhail Sofiev, Heidi Hellén, Kari Riikonen, Juha Nikmo, Anu Kousa, Jarkko V. Niemi, Niko Karvosenoja, Gabriela Sousa Santos, Ingrid Sundvor, Ulas Im, Jesper H. Christensen, Ole-Kenneth Nielsen, Marlene S. Plejdrup, Jacob Klenø Nøjgaard, Gunnar Omstedt, Camilla Andersson, Bertil Forsberg, and Jørgen Brandt
Atmos. Chem. Phys., 20, 4333–4365, https://doi.org/10.5194/acp-20-4333-2020, https://doi.org/10.5194/acp-20-4333-2020, 2020
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Residential wood combustion can cause substantial emissions of fine particulate matter and adverse health effects. This study has, for the first time, evaluated the impacts of residential wood combustion in a harmonised manner in four Nordic cities. Wood combustion caused major shares of fine particle concentrations in Oslo (up to 60 %) and Umeå (up to 30 %) and also notable shares in Copenhagen (up to 20 %) and Helsinki (up to 15 %).
Ulas Im, Jesper H. Christensen, Ole-Kenneth Nielsen, Maria Sand, Risto Makkonen, Camilla Geels, Camilla Anderson, Jaakko Kukkonen, Susana Lopez-Aparicio, and Jørgen Brandt
Atmos. Chem. Phys., 19, 12975–12992, https://doi.org/10.5194/acp-19-12975-2019, https://doi.org/10.5194/acp-19-12975-2019, 2019
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Sectoral contributions of anthropogenic emissions in Denmark, Finland, Norway and Sweden on air pollution and mortality over the Nordic and the Arctic regions are calculated. 80 % of PM2.5 over the Nordic countries is transported from outside Scandinavia. Residential combustion, industry and traffic are the main sectors to be targeted in emission mitigation. Exposure to ambient air pollution in the Nordic countries leads to more than 10 000 deaths in the region annually and costs EUR 7 billion.
Ana Stojiljkovic, Mari Kauhaniemi, Jaakko Kukkonen, Kaarle Kupiainen, Ari Karppinen, Bruce Rolstad Denby, Anu Kousa, Jarkko V. Niemi, and Matthias Ketzel
Atmos. Chem. Phys., 19, 11199–11212, https://doi.org/10.5194/acp-19-11199-2019, https://doi.org/10.5194/acp-19-11199-2019, 2019
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Nordic countries experience the deterioration of air quality in springtime due to high PM10 concentrations. Non-exhaust emissions from vehicular traffic are regarded as the most significant source of particulate air pollution during this time of year. The results from this study demonstrate the fact that changes in winter tyre types and adjustments to road maintenance could substantially reduce non-exhaust emissions.
Ingeborg E. Nielsen, Henrik Skov, Andreas Massling, Axel C. Eriksson, Manuel Dall'Osto, Heikki Junninen, Nina Sarnela, Robert Lange, Sonya Collier, Qi Zhang, Christopher D. Cappa, and Jacob K. Nøjgaard
Atmos. Chem. Phys., 19, 10239–10256, https://doi.org/10.5194/acp-19-10239-2019, https://doi.org/10.5194/acp-19-10239-2019, 2019
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Measurements of the chemical composition of sub-micrometer aerosols were carried out in northern Greenland during the Arctic haze (February–May) where concentrations are high due to favorable conditions for long-range transport. Sulfate was the dominant aerosol (66 %), followed by organic matter (24 %). The highest black carbon concentrations where observed in February. Source apportionment yielded three factors: a primary factor (12 %), an Arctic haze factor (64 %) and a marine factor (22 %).
Patricia Tarín-Carrasco, María Morales-Suárez-Varela, Ulas Im, Jørgen Brandt, Laura Palacios-Peña, and Pedro Jiménez-Guerrero
Atmos. Chem. Phys., 19, 9385–9398, https://doi.org/10.5194/acp-19-9385-2019, https://doi.org/10.5194/acp-19-9385-2019, 2019
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Air pollution has important implications for human health and external societal costs and is closely related to climate change. This work assesses the impacts of present and future air pollution on several cardiovascular and respiratory pathologies and estimates the costs associated with these health impacts on the European population. Premature deaths are the most important problem in terms of cases and costs (418 700 cases and EUR 158 billion per year, increasing by 17 % in the future).
Manuel Dall'Osto, David C. S. Beddows, Peter Tunved, Roy M. Harrison, Angelo Lupi, Vito Vitale, Silvia Becagli, Rita Traversi, Ki-Tae Park, Young Jun Yoon, Andreas Massling, Henrik Skov, Robert Lange, Johan Strom, and Radovan Krejci
Atmos. Chem. Phys., 19, 7377–7395, https://doi.org/10.5194/acp-19-7377-2019, https://doi.org/10.5194/acp-19-7377-2019, 2019
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We present a cluster analysis of particle size distributions simultaneously collected from three European high Arctic sites centred in the Fram Strait during a 3-year period. Confined for longer time periods by consolidated pack sea ice regions, the Greenland site shows lower ultrafine-mode aerosol concentrations during summer relative to the Svalbard sites. Our study supports international environmental cooperation concerning the Arctic region.
Heike Wex, Lin Huang, Wendy Zhang, Hayley Hung, Rita Traversi, Silvia Becagli, Rebecca J. Sheesley, Claire E. Moffett, Tate E. Barrett, Rossana Bossi, Henrik Skov, Anja Hünerbein, Jasmin Lubitz, Mareike Löffler, Olivia Linke, Markus Hartmann, Paul Herenz, and Frank Stratmann
Atmos. Chem. Phys., 19, 5293–5311, https://doi.org/10.5194/acp-19-5293-2019, https://doi.org/10.5194/acp-19-5293-2019, 2019
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We found an annual cycle for ice-nucleating particles in the Arctic. These particles are important for Arctic clouds, as they can change the lifetime of clouds. We suggest that higher concentrations of these particles in summertime originate from the Arctic biosphere (both marine and terrestrial). With a warming Arctic, these concentrations may increase further, influencing aerosol–cloud interactions and therewith the observed strong warming of the Arctic.
Marta G. Vivanco, Mark R. Theobald, Héctor García-Gómez, Juan Luis Garrido, Marje Prank, Wenche Aas, Mario Adani, Ummugulsum Alyuz, Camilla Andersson, Roberto Bellasio, Bertrand Bessagnet, Roberto Bianconi, Johannes Bieser, Jørgen Brandt, Gino Briganti, Andrea Cappelletti, Gabriele Curci, Jesper H. Christensen, Augustin Colette, Florian Couvidat, Cornelis Cuvelier, Massimo D'Isidoro, Johannes Flemming, Andrea Fraser, Camilla Geels, Kaj M. Hansen, Christian Hogrefe, Ulas Im, Oriol Jorba, Nutthida Kitwiroon, Astrid Manders, Mihaela Mircea, Noelia Otero, Maria-Teresa Pay, Luca Pozzoli, Efisio Solazzo, Svetlana Tsyro, Alper Unal, Peter Wind, and Stefano Galmarini
Atmos. Chem. Phys., 18, 10199–10218, https://doi.org/10.5194/acp-18-10199-2018, https://doi.org/10.5194/acp-18-10199-2018, 2018
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European wet and dry atmospheric deposition of N and S estimated by 14 air quality models was found to vary substantially. An ensemble of models meeting acceptability criteria was used to estimate the exceedances of the critical loads for N in habitats within the Natura 2000 network, as well as their lower and upper limits. Scenarios with 20 % emission reductions in different regions of the world showed that European emissions are responsible for most of the N and S deposition in Europe.
Ulas Im, Jesper Heile Christensen, Camilla Geels, Kaj Mantzius Hansen, Jørgen Brandt, Efisio Solazzo, Ummugulsum Alyuz, Alessandra Balzarini, Rocio Baro, Roberto Bellasio, Roberto Bianconi, Johannes Bieser, Augustin Colette, Gabriele Curci, Aidan Farrow, Johannes Flemming, Andrea Fraser, Pedro Jimenez-Guerrero, Nutthida Kitwiroon, Peng Liu, Uarporn Nopmongcol, Laura Palacios-Peña, Guido Pirovano, Luca Pozzoli, Marje Prank, Rebecca Rose, Ranjeet Sokhi, Paolo Tuccella, Alper Unal, Marta G. Vivanco, Greg Yarwood, Christian Hogrefe, and Stefano Galmarini
Atmos. Chem. Phys., 18, 8929–8952, https://doi.org/10.5194/acp-18-8929-2018, https://doi.org/10.5194/acp-18-8929-2018, 2018
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We evaluate the impact of global and regional anthropogenic emission reductions on major air pollutant levels over Europe and North America, using a multi-model ensemble of regional chemistry and transport models. Results show that ozone levels are largely driven by long-range transport over both continents while other pollutants such as carbon monoxide or aerosols are mainly controlled by domestic sources. Use of multi-model ensembles can help to reduce the uncertainties in individual models.
Jesper Kamp, Henrik Skov, Bjarne Jensen, and Lise Lotte Sørensen
Atmos. Chem. Phys., 18, 6923–6938, https://doi.org/10.5194/acp-18-6923-2018, https://doi.org/10.5194/acp-18-6923-2018, 2018
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Measurements of mercury fluxes over snow surfaces are carried out at the High Arctic site at Villum Research Station in North Greenland. The measurements were carried out from 23 April to 12 May during spring 2016, where atmospheric mercury depletion events (AMDEs) took place. The measurements showed a net emission of 8.9 ng m−2 min−1, with only a few depositional fluxes. GEM fluxes and atmospheric temperature measurements suggest that GEM emission partly could be affected by surface heating.
Ulas Im, Jørgen Brandt, Camilla Geels, Kaj Mantzius Hansen, Jesper Heile Christensen, Mikael Skou Andersen, Efisio Solazzo, Ioannis Kioutsioukis, Ummugulsum Alyuz, Alessandra Balzarini, Rocio Baro, Roberto Bellasio, Roberto Bianconi, Johannes Bieser, Augustin Colette, Gabriele Curci, Aidan Farrow, Johannes Flemming, Andrea Fraser, Pedro Jimenez-Guerrero, Nutthida Kitwiroon, Ciao-Kai Liang, Uarporn Nopmongcol, Guido Pirovano, Luca Pozzoli, Marje Prank, Rebecca Rose, Ranjeet Sokhi, Paolo Tuccella, Alper Unal, Marta Garcia Vivanco, Jason West, Greg Yarwood, Christian Hogrefe, and Stefano Galmarini
Atmos. Chem. Phys., 18, 5967–5989, https://doi.org/10.5194/acp-18-5967-2018, https://doi.org/10.5194/acp-18-5967-2018, 2018
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The impacts of air pollution on human health and their costs in Europe and the United States for the year 2010 ared modeled by a multi-model ensemble. In Europe, the number of premature deaths is calculated to be 414 000, while in the US it is estimated to be 160 000. Health impacts estimated by individual models can vary up to a factor of 3. Results show that the domestic emissions have the largest impact on premature deaths, compared to foreign sources.
Eyal Freud, Radovan Krejci, Peter Tunved, Richard Leaitch, Quynh T. Nguyen, Andreas Massling, Henrik Skov, and Leonard Barrie
Atmos. Chem. Phys., 17, 8101–8128, https://doi.org/10.5194/acp-17-8101-2017, https://doi.org/10.5194/acp-17-8101-2017, 2017
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This study analyses multi-year observations of atmospheric particles from five Arctic sites. These particles affect climate and air quality. The main factors that control the distinct annual cycle in the concentration of these particles are long-range transport and precipitation. The former brings pollution from the Asian sector – mostly during winter/spring – while the latter clears the air in summer/autumn. However, there are consistent differences between the sites due to regional factors.
Efisio Solazzo, Roberto Bianconi, Christian Hogrefe, Gabriele Curci, Paolo Tuccella, Ummugulsum Alyuz, Alessandra Balzarini, Rocío Baró, Roberto Bellasio, Johannes Bieser, Jørgen Brandt, Jesper H. Christensen, Augistin Colette, Xavier Francis, Andrea Fraser, Marta Garcia Vivanco, Pedro Jiménez-Guerrero, Ulas Im, Astrid Manders, Uarporn Nopmongcol, Nutthida Kitwiroon, Guido Pirovano, Luca Pozzoli, Marje Prank, Ranjeet S. Sokhi, Alper Unal, Greg Yarwood, and Stefano Galmarini
Atmos. Chem. Phys., 17, 3001–3054, https://doi.org/10.5194/acp-17-3001-2017, https://doi.org/10.5194/acp-17-3001-2017, 2017
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As part of the third phase of AQMEII, this study uses timescale analysis to apportion error to the responsible processes, detect causes of model error, and identify the processes and scales that require dedicated investigations. The analysis tackles model performance gauging through measurement-to-model comparison, error decomposition, and time series analysis of model biases for ozone, CO, SO2, NO, NO2, PM10, PM2.5, wind speed, and temperature over Europe and North America.
Francesca Sprovieri, Nicola Pirrone, Mariantonia Bencardino, Francesco D'Amore, Francesco Carbone, Sergio Cinnirella, Valentino Mannarino, Matthew Landis, Ralf Ebinghaus, Andreas Weigelt, Ernst-Günther Brunke, Casper Labuschagne, Lynwill Martin, John Munthe, Ingvar Wängberg, Paulo Artaxo, Fernando Morais, Henrique de Melo Jorge Barbosa, Joel Brito, Warren Cairns, Carlo Barbante, María del Carmen Diéguez, Patricia Elizabeth Garcia, Aurélien Dommergue, Helene Angot, Olivier Magand, Henrik Skov, Milena Horvat, Jože Kotnik, Katie Alana Read, Luis Mendes Neves, Bernd Manfred Gawlik, Fabrizio Sena, Nikolay Mashyanov, Vladimir Obolkin, Dennis Wip, Xin Bin Feng, Hui Zhang, Xuewu Fu, Ramesh Ramachandran, Daniel Cossa, Joël Knoery, Nicolas Marusczak, Michelle Nerentorp, and Claus Norstrom
Atmos. Chem. Phys., 16, 11915–11935, https://doi.org/10.5194/acp-16-11915-2016, https://doi.org/10.5194/acp-16-11915-2016, 2016
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This work presents atmospheric Hg concentrations recorded within the GMOS global network analyzing Hg measurement results in terms of temporal trends, seasonality and comparability within the network. The over-arching benefit of this coordinated Hg monitoring network would clearly be the production of high-quality measurement datasets on a global scale useful in developing and validating models on different spatial and temporal scales.
Quynh T. Nguyen, Marianne Glasius, Lise L. Sørensen, Bjarne Jensen, Henrik Skov, Wolfram Birmili, Alfred Wiedensohler, Adam Kristensson, Jacob K. Nøjgaard, and Andreas Massling
Atmos. Chem. Phys., 16, 11319–11336, https://doi.org/10.5194/acp-16-11319-2016, https://doi.org/10.5194/acp-16-11319-2016, 2016
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Aerosol particles strongly influence climate change as they can absorb or reflect solar radiation. This work investigates aerosol particles in the remote northern Arctic. "Newly born" particles are small, then they "age" and grow in size due to different mechanisms. The results showed that during the polar night and especially Arctic spring, particles were likely transported from longer distances and were aged. During summer, "younger" particles are observed, which might be linked to ozone.
Hélène Angot, Ashu Dastoor, Francesco De Simone, Katarina Gårdfeldt, Christian N. Gencarelli, Ian M. Hedgecock, Sarka Langer, Olivier Magand, Michelle N. Mastromonaco, Claus Nordstrøm, Katrine A. Pfaffhuber, Nicola Pirrone, Andrei Ryjkov, Noelle E. Selin, Henrik Skov, Shaojie Song, Francesca Sprovieri, Alexandra Steffen, Kenjiro Toyota, Oleg Travnikov, Xin Yang, and Aurélien Dommergue
Atmos. Chem. Phys., 16, 10735–10763, https://doi.org/10.5194/acp-16-10735-2016, https://doi.org/10.5194/acp-16-10735-2016, 2016
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This is a synthesis of the atmospheric mercury (Hg) monitoring data available in recent years (2011–2015) in the Arctic and in Antarctica along with a comparison of these observations with numerical simulations using four cutting-edge global models. Based on this comparison, we discuss whether the processes that affect atmospheric Hg seasonality and interannual variability are appropriately represented in the models, and identify remaining research gaps.
N. Evangeliou, Y. Balkanski, W. M. Hao, A. Petkov, R. P. Silverstein, R. Corley, B. L. Nordgren, S. P. Urbanski, S. Eckhardt, A. Stohl, P. Tunved, S. Crepinsek, A. Jefferson, S. Sharma, J. K. Nøjgaard, and H. Skov
Atmos. Chem. Phys., 16, 7587–7604, https://doi.org/10.5194/acp-16-7587-2016, https://doi.org/10.5194/acp-16-7587-2016, 2016
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In this study, we focused on how vegetation fires that occurred in northern Eurasia during the period 2002–2013 influenced the budget of BC in the Arctic. An average area of 250 000 km2 yr−1 was burned in northern Eurasia and the global emissions of BC ranged between 8.0 and 9.5 Tg yr−1, while 102 ± 29 kt yr−1 BC from biomass burning was deposited on the Arctic. About 46 % of the Arctic BC from vegetation fires originated from Siberia, 6 % from Kazakhstan, 5 % from Europe, and about 1 % from Mon
S. Eckhardt, B. Quennehen, D. J. L. Olivié, T. K. Berntsen, R. Cherian, J. H. Christensen, W. Collins, S. Crepinsek, N. Daskalakis, M. Flanner, A. Herber, C. Heyes, Ø. Hodnebrog, L. Huang, M. Kanakidou, Z. Klimont, J. Langner, K. S. Law, M. T. Lund, R. Mahmood, A. Massling, S. Myriokefalitakis, I. E. Nielsen, J. K. Nøjgaard, J. Quaas, P. K. Quinn, J.-C. Raut, S. T. Rumbold, M. Schulz, S. Sharma, R. B. Skeie, H. Skov, T. Uttal, K. von Salzen, and A. Stohl
Atmos. Chem. Phys., 15, 9413–9433, https://doi.org/10.5194/acp-15-9413-2015, https://doi.org/10.5194/acp-15-9413-2015, 2015
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The concentrations of sulfate, black carbon and other aerosols in the Arctic are characterized by high values in late winter and spring (so-called Arctic Haze) and low values in summer. Models have long been struggling to capture this seasonality. In this study, we evaluate sulfate and BC concentrations from different updated models and emissions against a comprehensive pan-Arctic measurement data set. We find that the models improved but still struggle to get the maximum concentrations.
H. A. C. Denier van der Gon, R. Bergström, C. Fountoukis, C. Johansson, S. N. Pandis, D. Simpson, and A. J. H. Visschedijk
Atmos. Chem. Phys., 15, 6503–6519, https://doi.org/10.5194/acp-15-6503-2015, https://doi.org/10.5194/acp-15-6503-2015, 2015
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Residential wood combustion (RWC) is increasing in Europe but may cause high emissions of particulate matter (PM). A revised bottom-up emission inventory was made which included the semi-volatile components. The revised RWC emissions are 2–3 times higher than the previous inventory. It significantly improved the modeling of PM and comparison with observations. Our results suggest primary PM2.5 emission from RWC as reported in Europe is underestimated and emission inventories need to be revised.
Q. T. Nguyen, M. K. Christensen, F. Cozzi, A. Zare, A. M. K. Hansen, K. Kristensen, T. E. Tulinius, H. H. Madsen, J. H. Christensen, J. Brandt, A. Massling, J. K. Nøjgaard, and M. Glasius
Atmos. Chem. Phys., 14, 8961–8981, https://doi.org/10.5194/acp-14-8961-2014, https://doi.org/10.5194/acp-14-8961-2014, 2014
N. Kivekäs, A. Massling, H. Grythe, R. Lange, V. Rusnak, S. Carreno, H. Skov, E. Swietlicki, Q. T. Nguyen, M. Glasius, and A. Kristensson
Atmos. Chem. Phys., 14, 8255–8267, https://doi.org/10.5194/acp-14-8255-2014, https://doi.org/10.5194/acp-14-8255-2014, 2014
A. M. K. Hansen, K. Kristensen, Q. T. Nguyen, A. Zare, F. Cozzi, J. K. Nøjgaard, H. Skov, J. Brandt, J. H. Christensen, J. Ström, P. Tunved, R. Krejci, and M. Glasius
Atmos. Chem. Phys., 14, 7807–7823, https://doi.org/10.5194/acp-14-7807-2014, https://doi.org/10.5194/acp-14-7807-2014, 2014
A. Zare, J. H. Christensen, A. Gross, P. Irannejad, M. Glasius, and J. Brandt
Atmos. Chem. Phys., 14, 2735–2756, https://doi.org/10.5194/acp-14-2735-2014, https://doi.org/10.5194/acp-14-2735-2014, 2014
R. G. Peel, P. V. Ørby, C. A. Skjøth, R. Kennedy, V. Schlünssen, M. Smith, J. Sommer, and O. Hertel
Biogeosciences, 11, 821–832, https://doi.org/10.5194/bg-11-821-2014, https://doi.org/10.5194/bg-11-821-2014, 2014
J. Brandt, J. D. Silver, J. H. Christensen, M. S. Andersen, J. H. Bønløkke, T. Sigsgaard, C. Geels, A. Gross, A. B. Hansen, K. M. Hansen, G. B. Hedegaard, E. Kaas, and L. M. Frohn
Atmos. Chem. Phys., 13, 7725–7746, https://doi.org/10.5194/acp-13-7725-2013, https://doi.org/10.5194/acp-13-7725-2013, 2013
J. Brandt, J. D. Silver, J. H. Christensen, M. S. Andersen, J. H. Bønløkke, T. Sigsgaard, C. Geels, A. Gross, A. B. Hansen, K. M. Hansen, G. B. Hedegaard, E. Kaas, and L. M. Frohn
Atmos. Chem. Phys., 13, 7747–7764, https://doi.org/10.5194/acp-13-7747-2013, https://doi.org/10.5194/acp-13-7747-2013, 2013
K. Hansen, L. L. Sørensen, O. Hertel, C. Geels, C. A. Skjøth, B. Jensen, and E. Boegh
Biogeosciences, 10, 4577–4589, https://doi.org/10.5194/bg-10-4577-2013, https://doi.org/10.5194/bg-10-4577-2013, 2013
E. Solazzo, R. Bianconi, G. Pirovano, M. D. Moran, R. Vautard, C. Hogrefe, K. W. Appel, V. Matthias, P. Grossi, B. Bessagnet, J. Brandt, C. Chemel, J. H. Christensen, R. Forkel, X. V. Francis, A. B. Hansen, S. McKeen, U. Nopmongcol, M. Prank, K. N. Sartelet, A. Segers, J. D. Silver, G. Yarwood, J. Werhahn, J. Zhang, S. T. Rao, and S. Galmarini
Geosci. Model Dev., 6, 791–818, https://doi.org/10.5194/gmd-6-791-2013, https://doi.org/10.5194/gmd-6-791-2013, 2013
G. B. Hedegaard, J. H. Christensen, and J. Brandt
Atmos. Chem. Phys., 13, 3569–3585, https://doi.org/10.5194/acp-13-3569-2013, https://doi.org/10.5194/acp-13-3569-2013, 2013
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Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
Geosci. Model Dev., 18, 3707–3733, https://doi.org/10.5194/gmd-18-3707-2025, https://doi.org/10.5194/gmd-18-3707-2025, 2025
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This work focuses on the prediction of aerosol concentration values at the ground level, which are a strong indicator of air quality, using artificial neural networks. A study of different variables and their efficiency as inputs for these models is also proposed and reveals that the best results are obtained when using all of them. Comparison between network architectures and information fusion methods allows for the extraction of knowledge on the most efficient methods in the context of this study.
Pauline Bonnet, Lorenzo Pastori, Mierk Schwabe, Marco Giorgetta, Fernando Iglesias-Suarez, and Veronika Eyring
Geosci. Model Dev., 18, 3681–3706, https://doi.org/10.5194/gmd-18-3681-2025, https://doi.org/10.5194/gmd-18-3681-2025, 2025
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Tuning a climate model means adjusting uncertain parameters in the model to best match observations like the global radiation balance and cloud cover. This is usually done by running many simulations of the model with different settings, which can be time-consuming and relies heavily on expert knowledge. To make this process faster and more objective, we developed a machine learning emulator to create a large ensemble and apply a method called history matching to find the best settings.
Kang Hu, Hong Liao, Dantong Liu, Jianbing Jin, Lei Chen, Siyuan Li, Yangzhou Wu, Changhao Wu, Shitong Zhao, Xiaotong Jiang, Ping Tian, Kai Bi, Ye Wang, and Delong Zhao
Geosci. Model Dev., 18, 3623–3634, https://doi.org/10.5194/gmd-18-3623-2025, https://doi.org/10.5194/gmd-18-3623-2025, 2025
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This study combines machine learning with concentration-weighted trajectory analysis to quantify regional transport PM2.5. From 2013–2020, local emissions dominated Beijing's pollution events. The Air Pollution Prevention and Control Action Plan reduced regional transport pollution, but the eastern region showed the smallest decrease. Beijing should prioritize local emission reduction while considering the east region's contributions in future strategies.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 18, 3607–3622, https://doi.org/10.5194/gmd-18-3607-2025, https://doi.org/10.5194/gmd-18-3607-2025, 2025
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We developed a deep learning method to estimate CO2 emissions from power plants using satellite images. Trained and validated on simulated data, our model accurately predicts emissions despite challenges like cloud cover. When applied to real OCO3 satellite images, the results closely match reported emissions. This study shows that neural networks trained on simulations can effectively analyse real satellite data, offering a new way to monitor CO2 emissions from space.
Wonbae Bang, Jacob T. Carlin, Kwonil Kim, Alexander V. Ryzhkov, Guosheng Liu, and GyuWon Lee
Geosci. Model Dev., 18, 3559–3581, https://doi.org/10.5194/gmd-18-3559-2025, https://doi.org/10.5194/gmd-18-3559-2025, 2025
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Microphysics model-based diagnosis, such as the spectral bin model (SBM), has recently been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM has a relatively higher accuracy for dry-snow and wet-snow events, whereas it has lower accuracy for rain events. When the microphysics scheme in the SBM was optimized for the corresponding region, the accuracy for rain events improved.
Gabriel Colas, Valéry Masson, François Bouttier, Ludovic Bouilloud, Laura Pavan, and Virve Karsisto
Geosci. Model Dev., 18, 3453–3472, https://doi.org/10.5194/gmd-18-3453-2025, https://doi.org/10.5194/gmd-18-3453-2025, 2025
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In winter, snow- and ice-covered artificial surfaces are important aspects of the urban climate. They may influence the magnitude of the urban heat island effect, but this is still unclear. In this study, we improved the representation of the snow and ice cover in the Town Energy Balance (TEB) urban climate model. Evaluations have shown that the results are promising for using TEB to study the climate of cold cities.
Markus Kunze, Christoph Zülicke, Tarique A. Siddiqui, Claudia C. Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev., 18, 3359–3385, https://doi.org/10.5194/gmd-18-3359-2025, https://doi.org/10.5194/gmd-18-3359-2025, 2025
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with an upper-atmospheric extension with the physics package for numerical weather prediction (UA-ICON(NWP)). We optimized the parameters for the gravity wave parameterizations and achieved realistic modeling of the thermal and dynamic states of the mesopause regions. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
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Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from individual basin to global scales with continuous emissions monitoring.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
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The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Maurin Zouzoua, Sophie Bastin, Fabienne Lohou, Marie Lothon, Marjolaine Chiriaco, Mathilde Jome, Cécile Mallet, Laurent Barthes, and Guylaine Canut
Geosci. Model Dev., 18, 3211–3239, https://doi.org/10.5194/gmd-18-3211-2025, https://doi.org/10.5194/gmd-18-3211-2025, 2025
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This study proposes using a statistical model to freeze errors due to differences in environmental forcing when evaluating the surface turbulent heat fluxes from numerical simulations with observations. The statistical model is first built with observations and then applied to the simulated environment to generate possibly observed fluxes. This novel method provides insight into differently evaluating the numerical formulation of turbulent heat fluxes with a long period of observational data.
Oxana Drofa
Geosci. Model Dev., 18, 3175–3209, https://doi.org/10.5194/gmd-18-3175-2025, https://doi.org/10.5194/gmd-18-3175-2025, 2025
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This paper presents the result of many years of effort of the author, who developed an original mathematical numerical model of heat and moisture exchange processes in soil, vegetation, and snow. The author relied on her 30 years of research experience in atmospheric numerical modelling. The presented model is the fruit of the author's research on physical processes at the surface–atmosphere interface and their numerical approximation and aims at improving numerical weather forecasting and climate simulations.
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
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We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
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Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
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
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We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
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
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This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
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
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Machine learning has the potential to aid the identification of organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning models in atmospheric sciences.
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
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The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
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
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Andrin Jörimann, Timofei Sukhodolov, Beiping Luo, Gabriel Chiodo, Graham Mann, and Thomas Peter
EGUsphere, https://doi.org/10.5194/egusphere-2025-145, https://doi.org/10.5194/egusphere-2025-145, 2025
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Aerosol particles in the stratosphere affect our climate. Climate models therefore need an accurate description of their properties and evolution. Satellites measure how strongly aerosol particles extinguish light passing through the stratosphere. We describe a method to use such aerosol extinction data to retrieve the number and sizes of the aerosol particles and calculate their optical effects. The resulting data sets for models are validated against ground-based and balloon observations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
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Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Peter Wind and Willem van Caspel
EGUsphere, https://doi.org/10.5194/egusphere-2024-3571, https://doi.org/10.5194/egusphere-2024-3571, 2025
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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.
Julian Vogel, Sebastian Stadler, Ganesh Chockalingam, Afshin Afshari, Johanna Henning, and Matthias Winkler
EGUsphere, https://doi.org/10.5194/egusphere-2025-144, https://doi.org/10.5194/egusphere-2025-144, 2025
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This study presents a toolkit to simplify input data creation for the urban microclimate model PALM-4U. It introduces novel methods to automate the use of open data sources. Our analysis of four test cases created from different geographic data sources shows variations in temperature, humidity, and wind speed, influenced by data quality. Validation indicates that the automated methods yield results comparable to expert-driven approaches, facilitating user-friendly urban climate modeling.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
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An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
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As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
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The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
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In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Raphaël Périllat, Sylvain Girard, and Irène Korsakissok
EGUsphere, https://doi.org/10.5194/egusphere-2024-3838, https://doi.org/10.5194/egusphere-2024-3838, 2025
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We developed a method to improve decision-making during nuclear crises by predicting the spread of radiation more efficiently. Existing approaches are often too slow, especially when analyzing complex data like radiation maps. Our method combines techniques to simplify these maps and predict them quickly using statistical tools. This approach could help authorities respond faster and more accurately in emergencies, reducing risks to the population and the environment.
Shaofeng Hua, Gang Chen, Baojun Chen, Mingshan Li, and Xin Xu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3834, https://doi.org/10.5194/egusphere-2024-3834, 2025
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Hail forecasting using numerical models remains a challenge. In this study, we found that the commonly used graupel-to-hail conversion parameterization method led to hail overforecasting in heavy rainfall cases where no hail was observed. By incorporating the spongy wet growth process, we successfully mitigated hail overforecasting. The modified scheme also produced hail in real hail events. This research contributes to a better understanding of hail formation.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
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We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
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Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
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This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
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Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Qike Yang, Chun Zhao, Jiawang Feng, Gudongze Li, Jun Gu, Zihan Xia, Mingyue Xu, and Zining Yang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-229, https://doi.org/10.5194/gmd-2024-229, 2025
Revised manuscript accepted for GMD
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This study presents the first comprehensive evaluation of unstructured meshes using the iAMAS model over Antarctica, encompassing both surface and upper-level meteorological fields. Comparison with ERA5 and observational data reveals that the iAMAS model performs well in simulating the Antarctic atmosphere; iAMAS demonstrates comparable, and in some cases superior, performance in simulating temperature and wind speed in East Antarctica when compared to ERA5.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
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Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
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Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Cited articles
Assael, M. J., Delaki, M., and Kakosimos, K. E.: Applying the OSPM model to the calculation of PM10 concentration levels in the historical centre of the city of Thessaloniki, Atmos. Environ., 42, 65–77, 2008.
Berkowicz, R., Palmgren, F., Hertel, O., and Vignati, E.: Using measurements of air pollution in streets for evaluiation of urban air quality – meteorological analysis and model calculations, Sci. Total Environ., 189/190, 259–265, 1996.
Berkowicz, R., Hertel, O., Larsen, S. E., Sørensen, N. N., and Nielsen, M.: Modelling traffic pollution in streets, Ministry of Environment and Energy, National Environmental Research Institute, Roskilde, Denmark, available at: http://www2.dmu.dk/1_viden/2_Miljoe-tilstand/3_luft/4_spredningsmodeller/5_OSPM/5_description/ModellingTrafficPollution_report.pdf (last access: October 2015), 1997.
Berkowicz, R., Winther, M., and Ketzel, M.: Traffic pollution modelling and emission data, Environ. Model. Softw., 21, 454–460, 2006.
Boulter, P. and McCrae, I.: Assessment and reliability of transport emission models and inventory systems, TRL Limited, available at: http://www.trl.co.uk/reports-publications/trl-reports/report/?reportid=6413 (last access: October 2015), 2007.
Burman, L. and Johansson, C.: Utsläpp och halter av kväveoxider och kvävedioxid på Hornsgatan, Environment and Health Administration, SLB-analys, Stockholm, Sweden, 2010.
Carslaw, D. C., Beevers, S. D., Tate, J. E., Westmoreland, E. J., and Williams, M. L.: Recent evidence concerning higher NOx emissions from passenger cars and light duty vehicles, Atmos. Environ., 45, 7053–7063, 2011.
Denby, B. R., Sundvor, I., Johansson, C., Pirjola, L., Ketzel, M., Norman, M., Kupiainen, K., Gustafsson, M., Blomqvist, G., Kauhaniemi, M., and Omstedt, G.: A coupled road dust and surface moisture model to predict non-exhaust road traffic induced particle emissions (NORTRIP). Part 2: Surface moisture and salt impact modelling, Atmos. Environ., 81, 485–503, 2013a.
Denby, B. R., Sundvor, I., Johansson, C., Pirjola, L., Ketzel, M., Norman, M., Kupiainen, K., Gustafsson, M., Blomqvist, G., and Omstedt, G.: A coupled road dust and surface moisture model to predict non-exhaust road traffic induced particle emissions (NORTRIP). Part 1: Road dust loading and suspension modelling, Atmos. Environ., 77, 283–300, 2013b.
EEA: EMEP/CORINAIR Atmospheric Emissions Inventory Guidebook, Chapter on Exhaust Emissions from Road Transport. Methodology for COPERT 4., European Environmental Agency, 2009.
Ellermann, T., Nøjgaard, J. K., Nordstrøm, C., Brandt, J., Christensen, J., Ketzel, M., Jansen, S., Massling, A., and Jensen, S. S.: The Danish Air Quality Monitoring Programme – Annual Summary for 2012, Arhus University, DCE – Danish Centre for Environment and Energy, 2013.
Ghenu, A., Rosant, J.-M., and Sini, J.-F.: Dispersion of pollutants and estimation of emissions in a street canyon in Rouen, France, Environ. Model. Softw., 23, 314–321, 2008.
Gidhagen, L., Johansson, C., Langner, J., and Olivares, G.: Simulation of NOx and ultrafine particles in a street canyon in Stockholm, Sweden, Atmos. Environ., 38, 2029–2044, 2004.
Gokhale, S. B., Rebours, A., and Pavageau, M.: The performance evaluation of WinOSPM model for urban street canyons of Nantes in France, Environ. Monit. Assess., 100, 153–176, 2005.
Hertel, O. and Berkowicz, R.: Modelling Pollution from Traffic in a Street Canyon, Evaluation of Data and Model Development, National Environmental Research Institute, Roskilde, Denmark, 1989.
Hertel, O., Hvidberg, M., Ketzel, M., Storm, L., and Stausgaard, L.: A proper choice of route significantly reduced air pollution exposure – A study on bicycle and bus trips in urban streets, Sci. Total Environ., 389, 58–70, 2008.
Johansson, C., Norman, M., and Burman, L.: Road traffic emission factors for heavy metals, Atmos. Environ., 43, 4681–4688, 2009.
Kakosimos, K. E., Hertel, O., Ketzel, M., and Berkowicz, R.: Operational Street Pollution Model OSPM) – a review of performed application and validation studies, and future prospects, Environ. Chem., 7, 485–503, 2010.
Kean, A. J., Harley, R. A., and Kendall, G. R.: Effects of Vehicle Speed and Engine Load on Motor Vehicle Emissions, Environ. Sci. Technol., 37, 3739–3746, 2003.
Ketzel, M., Omstedt, G., Johansson, C., Düring, I., Pohjola, M., Oettl, D., Gidhagen, L., Wåhlin, P., Lohmeyer, A., Haakana, M., and Berkowicz, R.: Estimation and validation of PM2.5/PM10 exhaust and non-exhaust emission factors for practical street pollution modelling, Atmos. Environ., 41, 9370–9385, 2007.
Ketzel, M., Berkowicz, R., Hvidberg, M., Jensen, S. S., and Raaschou-Nielsen, O.: Evaluation of AirGIS: A GIS-based air pollution and human exposure modelling system, Int. J. Environ. Pollut., 47, 226–238, 2011.
Ketzel, M., Jensen, S. S., Brandt, J., Ellermann, T., Olesen, H. R., Berkowicz, R., and Hertel, O.: Evaluation of the Street Pollution Model OSPM for Measurements at 12 Streets Stations Using a Newly Developed and Freely Available Evaluation Tool, J. Civil Environ. Eng., S:1004, https://doi.org/10.4172/2165-784X.S1-004, 2012.
Ketzel, M., Hertel, O., Ottosen, T.-B., Kakosimos, K., and Berkowicz, R.: Validation of New Parameterisations for the Operational Street Pollution Model (OSPM), in: Proceedings of Abstracts 9th International Conference on Air Quality – Science and Application, University of Hertfordshire, Hatfield, UK, 2014.
Kukkonen, J., Valkonen, E., Walden, J., Koskentalo, T., Karppinen, A., Berkowicz, R., and Kartastenpää, R.: Measurements and modelling of air pollution in a street canyon in Helsinki, Environ. Monit. Assess., 65, 371–379, 2000.
Larssen, S., Mellios, G., van den Hout, D., Kalognomou, E. A., and Moussiopoulos, N.: Street Emission Ceiling (SEC) exercise – Phase 3 report, European Topic Centre on Air and Climate Change, available at: http://acm.eionet.europa.eu/reports/ETCACC_TechnPaper_2006_7_SEC_phase3 (last access: October 2015), 2007.
Moussiopoulos, N., Kalognomou, E. A., Samaras, Z., Mellios, G., Larssen, S. E., Gjerstad, K. I., de Leeuw, F. A. A. M., van den Hout, K. D., and Teeuwisse, S.: Street Emission Ceiling exercise – Phase 1 report, European Topic Centre on Air and Climate Change, available at: http://acm.eionet.europa.eu/docs/ETCACC_TechnPaper2003_11_SEC_Phase1Rep.pdf (last access: October 2015), 2004.
Moussiopoulos, N., Kalognomou, E. A., Papathanasiou, A., Eleftheriadou, S., Barmpas, Ph., Vlachokostas, Ch., Samaras, Z., Mellios, G., Vouitsis, I., Larssen, S. E., Gjerstad, K. I., de Leeuw, F. A. A. M., van den Hout, K. D., Teeuwisse, S., and van Aalst, R.: Street Emission Ceiling exercise – Phase 2 report, European Topic Centre on Air and Climate Change, http://acm.eionet.europa.eu/docs/ETCACC_TechnPaper_2004_5_SEC_Phase2Rep.pdf (last access: October 2015), 2005.
Olivares, G., Johansson, C., Ström, J., and Hansson, H.-C.: The role of ambient temperature for particle number concentrations in a street canyon, Atmos. Environ., 41, 2145–2155, 2007.
Ottosen, T.-B., Ketzel, M., Skov, H., Hertel, O., Brandt, J., and Kakosimos, K.: A Parameter Estimation and Identifiability Analysis Methodology Applied to a Street Canyon Air Pollution Model, Environ. Model. Softw., submitted, 2015.
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Short summary
Semi-parameterised street canyon models are popular due to their speed and low input requirements. One often-used assumption is that emissions are homogeneously distributed in the entire length and width of the street. It is thus the aim of the present study to analyse the impact of this assumption by implementing an inhomogeneous emission geometry scheme and validating it. The results show an improved performance, however, confounded by challenges in estimating the emissions accurately.
Semi-parameterised street canyon models are popular due to their speed and low input...
