Articles | Volume 15, issue 10
https://doi.org/10.5194/gmd-15-4027-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-4027-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
24 May 2022
Model description paper |
| 24 May 2022
| 24 May 2022
An emergency response model for the formation and dispersion of plumes originating from major fires (BUOYANT v4.20)
Jaakko Kukkonen
CORRESPONDING AUTHOR
Finnish Meteorological Institute, Erik Palménin aukio 1, P.O. Box 503, 00101, Helsinki, Finland
Centre for Atmospheric and Climate Physics Research, and Centre for
Climate Change Research, University of Hertfordshire, College Lane, Hatfield, AL10 9AB, UK
Juha Nikmo
Finnish Meteorological Institute, Erik Palménin aukio 1, P.O. Box 503, 00101, Helsinki, Finland
Kari Riikonen
Finnish Meteorological Institute, Erik Palménin aukio 1, P.O. Box 503, 00101, Helsinki, Finland
Ilmo Westerholm
Finnish Meteorological Institute, Erik Palménin aukio 1, P.O. Box 503, 00101, Helsinki, Finland
Pekko Ilvessalo
Finnish Meteorological Institute, Erik Palménin aukio 1, P.O. Box 503, 00101, Helsinki, Finland
Tuomo Bergman
Finnish Meteorological Institute, Erik Palménin aukio 1, P.O. Box 503, 00101, Helsinki, Finland
Klaus Haikarainen
Finnish Meteorological Institute, Erik Palménin aukio 1, P.O. Box 503, 00101, Helsinki, Finland
Related authors
Androniki Maragkidou, Tiia Grönholm, Laura Rautiainen, Juha Nikmo, Jukka-Pekka Jalkanen, Timo Mäkelä, Timo Anttila, Lauri Laakso, and Jaakko Kukkonen
EGUsphere, https://doi.org/10.5194/egusphere-2024-1703, https://doi.org/10.5194/egusphere-2024-1703, 2024
Short summary
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The Baltic Sea's designation as a Sulphur Emission Control Area in 2006, with subsequent regulations, significantly reduced sulphur emissions from shipping. Our study analyzed air quality data from 2003 to 2020 at Utö island and employed modelling, showing a continuous decrease in SO2 concentrations since 2003 and evidencing, thus, the effectiveness of such regulations in improving air quality. It also underscored the importance of long-term, high-resolution monitoring at remote marine sites.
Leena Kangas, Jaakko Kukkonen, Mari Kauhaniemi, Kari Riikonen, Mikhail Sofiev, Anu Kousa, Jarkko V. Niemi, and Ari Karppinen
Atmos. Chem. Phys., 24, 1489–1507, https://doi.org/10.5194/acp-24-1489-2024, https://doi.org/10.5194/acp-24-1489-2024, 2024
Short summary
Short summary
Residential wood combustion is a major source of fine particulate matter. This study has evaluated the contribution of residential wood combustion to fine particle concentrations and its year-to-year and seasonal variation in te Helsinki metropolitan area. The average concentrations attributed to wood combustion in winter were up to 10- or 15-fold compared to summer. Wood combustion caused 12 % to 14 % of annual fine particle concentrations. In winter, the contribution ranged from 16 % to 21 %.
Svetlana Sofieva, Eija Asmi, Nina S. Atanasova, Aino E. Heikkinen, Emeline Vidal, Jonathan Duplissy, Martin Romantschuk, Rostislav Kouznetsov, Jaakko Kukkonen, Dennis H. Bamford, Antti-Pekka Hyvärinen, and Mikhail Sofiev
Atmos. Meas. Tech., 15, 6201–6219, https://doi.org/10.5194/amt-15-6201-2022, https://doi.org/10.5194/amt-15-6201-2022, 2022
Short summary
Short summary
A new bubble-generating glass chamber design with an extensive set of aerosol production experiments is presented to re-evaluate bubble-bursting-mediated aerosol production as a function of water parameters: bubbling air flow, water salinity, and temperature. Our main findings suggest modest dependence of aerosol production on the water salinity and a strong dependence on temperature below ~ 10 °C.
Matthias Karl, Liisa Pirjola, Tiia Grönholm, Mona Kurppa, Srinivasan Anand, Xiaole Zhang, Andreas Held, Rolf Sander, Miikka Dal Maso, David Topping, Shuai Jiang, Leena Kangas, and Jaakko Kukkonen
Geosci. Model Dev., 15, 3969–4026, https://doi.org/10.5194/gmd-15-3969-2022, https://doi.org/10.5194/gmd-15-3969-2022, 2022
Short summary
Short summary
The community aerosol dynamics model MAFOR includes several advanced features: coupling with an up-to-date chemistry mechanism for volatile organic compounds, a revised Brownian coagulation kernel that takes into account the fractal geometry of soot particles, a multitude of nucleation parameterizations, size-resolved partitioning of semi-volatile inorganics, and a hybrid method for the formation of secondary organic aerosols within the framework of condensation and evaporation.
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
Short summary
Short summary
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.
Jaakko Kukkonen, Mikko Savolahti, Yuliia Palamarchuk, Timo Lanki, Väinö Nurmi, Ville-Veikko Paunu, Leena Kangas, Mikhail Sofiev, Ari Karppinen, Androniki Maragkidou, Pekka Tiittanen, and Niko Karvosenoja
Atmos. Chem. Phys., 20, 9371–9391, https://doi.org/10.5194/acp-20-9371-2020, https://doi.org/10.5194/acp-20-9371-2020, 2020
Short summary
Short summary
We have developed a mathematical model that can be used to analyse the benefits that could be achieved by implementing alternative air quality abatement measures, policies or strategies. The model was applied to determine pollution sources in the whole of Finland in 2015. Clearly the most economically effective measures were the reduction in emissions from low-level sources in urban areas. Such sources include road transport, non-road vehicles and machinery, and residential wood combustion.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Jaakko Kukkonen, Leena Kangas, Mari Kauhaniemi, Mikhail Sofiev, Mia Aarnio, Jouni J. K. Jaakkola, Anu Kousa, and Ari Karppinen
Atmos. Chem. Phys., 18, 8041–8064, https://doi.org/10.5194/acp-18-8041-2018, https://doi.org/10.5194/acp-18-8041-2018, 2018
Short summary
Short summary
We have quantified the emissions and concentrations of fine particulate matter in the Helsinki area for an unprecedentedly extensive period, from 1980 to 2014. The modelled concentrations agree well with the measured data. The concentrations of fine particles have decreased drastically since the 1980s, to about a half of the highest values. The results make it possible to evaluate the long-term health impacts of air pollution substantially better.
John Backman, Curtis R. Wood, Mikko Auvinen, Leena Kangas, Hanna Hannuniemi, Ari Karppinen, and Jaakko Kukkonen
Geosci. Model Dev., 10, 3793–3803, https://doi.org/10.5194/gmd-10-3793-2017, https://doi.org/10.5194/gmd-10-3793-2017, 2017
Short summary
Short summary
Meteorological input parameters for urban- and local-scale dispersion models can be derived from meteorological observations. This study presents a sensitivity analysis of a meteorological model that utilises readily available meteorological data to derive specific parameters required to model the atmospheric dispersion of pollutants. The study shows that wind speed is the most fundamental meteorological input parameter followed by solar radiation.
Heidi Hellén, Leena Kangas, Anu Kousa, Mika Vestenius, Kimmo Teinilä, Ari Karppinen, Jaakko Kukkonen, and Jarkko V. Niemi
Atmos. Chem. Phys., 17, 3475–3487, https://doi.org/10.5194/acp-17-3475-2017, https://doi.org/10.5194/acp-17-3475-2017, 2017
Short summary
Short summary
Estimating impacts of wood combustion on ambient levels of PAHs is challenging. In this study effect of residential wood combustion on the benzo[a]pyrene concentrations in the air of Helsinki metropolitan area was studied, using ambient air measurements, emission estimates and dispersion modeling. Combining all this information enabled a quantitative characterization of the influence of residential wood combustion, which was found to be the main local source and more important than for PM2.5.
Marje Prank, Mikhail Sofiev, Svetlana Tsyro, Carlijn Hendriks, Valiyaveetil Semeena, Xavier Vazhappilly Francis, Tim Butler, Hugo Denier van der Gon, Rainer Friedrich, Johannes Hendricks, Xin Kong, Mark Lawrence, Mattia Righi, Zissis Samaras, Robert Sausen, Jaakko Kukkonen, and Ranjeet Sokhi
Atmos. Chem. Phys., 16, 6041–6070, https://doi.org/10.5194/acp-16-6041-2016, https://doi.org/10.5194/acp-16-6041-2016, 2016
Short summary
Short summary
Aerosol composition in Europe was simulated by four chemistry transport models and compared to observations to identify the most prominent areas for model improvement. Notable differences were found between the models' predictions, attributable to different treatment or omission of aerosol sources and processes. All models underestimated the observed concentrations by 10–60 %, mostly due to under-predicting the carbonaceous and mineral particles and omitting the aerosol-bound water.
Matthias Karl, Jaakko Kukkonen, Menno P. Keuken, Susanne Lützenkirchen, Liisa Pirjola, and Tareq Hussein
Atmos. Chem. Phys., 16, 4817–4835, https://doi.org/10.5194/acp-16-4817-2016, https://doi.org/10.5194/acp-16-4817-2016, 2016
Short summary
Short summary
Particles emitted from road traffic are subject to complex dilution processes as well as microphysical transformation processes. Particle measurements at major roads in Rotterdam, Oslo and Helsinki were used to analyze the relevance of microphysical transformation processes. Transformation processes caused changes of the particle number concentration of up to 20–30 % on the neighborhood scale. A simple parameterization to predict particle number concentrations in urban areas is presented.
J. Kukkonen, M. Karl, M. P. Keuken, H. A. C. Denier van der Gon, B. R. Denby, V. Singh, J. Douros, A. Manders, Z. Samaras, N. Moussiopoulos, S. Jonkers, M. Aarnio, A. Karppinen, L. Kangas, S. Lützenkirchen, T. Petäjä, I. Vouitsis, and R. S. Sokhi
Geosci. Model Dev., 9, 451–478, https://doi.org/10.5194/gmd-9-451-2016, https://doi.org/10.5194/gmd-9-451-2016, 2016
Short summary
Short summary
For analyzing the health effects of particulate matter, it is necessary to consider not only the mass of particles, but also their sizes and composition. A simple measure for the former is the number concentration of particles. We present particle number concentrations in five major European cities, namely Helsinki, Oslo, London, Rotterdam, and Athens, in 2008, based mainly on modelling. The concentrations of PN were mostly influenced by the emissions from local vehicular traffic.
J.-P. Jalkanen, L. Johansson, and J. Kukkonen
Atmos. Chem. Phys., 16, 71–84, https://doi.org/10.5194/acp-16-71-2016, https://doi.org/10.5194/acp-16-71-2016, 2016
Short summary
Short summary
This manuscript describes the emissions from shipping in European sea areas. The work is based on automatic position reports (AIS) sent by ships and reflects realistic activity patterns of ships. The work demonstrates that it is feasible to construct full bottom-up emission inventories based on large-volume activity data sets.
J. Kukkonen, J. Nikmo, M. Sofiev, K. Riikonen, T. Petäjä, A. Virkkula, J. Levula, S. Schobesberger, and D. M. Webber
Geosci. Model Dev., 7, 2663–2681, https://doi.org/10.5194/gmd-7-2663-2014, https://doi.org/10.5194/gmd-7-2663-2014, 2014
M. Kauhaniemi, A. Stojiljkovic, L. Pirjola, A. Karppinen, J. Härkönen, K. Kupiainen, L. Kangas, M. A. Aarnio, G. Omstedt, B. R. Denby, and J. Kukkonen
Atmos. Chem. Phys., 14, 9155–9169, https://doi.org/10.5194/acp-14-9155-2014, https://doi.org/10.5194/acp-14-9155-2014, 2014
J. Soares, A. Kousa, J. Kukkonen, L. Matilainen, L. Kangas, M. Kauhaniemi, K. Riikonen, J.-P. Jalkanen, T. Rasila, O. Hänninen, T. Koskentalo, M. Aarnio, C. Hendriks, and A. Karppinen
Geosci. Model Dev., 7, 1855–1872, https://doi.org/10.5194/gmd-7-1855-2014, https://doi.org/10.5194/gmd-7-1855-2014, 2014
A. Virkkula, J. Levula, T. Pohja, P. P. Aalto, P. Keronen, S. Schobesberger, C. B. Clements, L. Pirjola, A.-J. Kieloaho, L. Kulmala, H. Aaltonen, J. Patokoski, J. Pumpanen, J. Rinne, T. Ruuskanen, M. Pihlatie, H. E. Manninen, V. Aaltonen, H. Junninen, T. Petäjä, J. Backman, M. Dal Maso, T. Nieminen, T. Olsson, T. Grönholm, J. Aalto, T. H. Virtanen, M. Kajos, V.-M. Kerminen, D. M. Schultz, J. Kukkonen, M. Sofiev, G. De Leeuw, J. Bäck, P. Hari, and M. Kulmala
Atmos. Chem. Phys., 14, 4473–4502, https://doi.org/10.5194/acp-14-4473-2014, https://doi.org/10.5194/acp-14-4473-2014, 2014
L. Johansson, J.-P. Jalkanen, J. Kalli, and J. Kukkonen
Atmos. Chem. Phys., 13, 11375–11389, https://doi.org/10.5194/acp-13-11375-2013, https://doi.org/10.5194/acp-13-11375-2013, 2013
Androniki Maragkidou, Tiia Grönholm, Laura Rautiainen, Juha Nikmo, Jukka-Pekka Jalkanen, Timo Mäkelä, Timo Anttila, Lauri Laakso, and Jaakko Kukkonen
EGUsphere, https://doi.org/10.5194/egusphere-2024-1703, https://doi.org/10.5194/egusphere-2024-1703, 2024
Short summary
Short summary
The Baltic Sea's designation as a Sulphur Emission Control Area in 2006, with subsequent regulations, significantly reduced sulphur emissions from shipping. Our study analyzed air quality data from 2003 to 2020 at Utö island and employed modelling, showing a continuous decrease in SO2 concentrations since 2003 and evidencing, thus, the effectiveness of such regulations in improving air quality. It also underscored the importance of long-term, high-resolution monitoring at remote marine sites.
Leena Kangas, Jaakko Kukkonen, Mari Kauhaniemi, Kari Riikonen, Mikhail Sofiev, Anu Kousa, Jarkko V. Niemi, and Ari Karppinen
Atmos. Chem. Phys., 24, 1489–1507, https://doi.org/10.5194/acp-24-1489-2024, https://doi.org/10.5194/acp-24-1489-2024, 2024
Short summary
Short summary
Residential wood combustion is a major source of fine particulate matter. This study has evaluated the contribution of residential wood combustion to fine particle concentrations and its year-to-year and seasonal variation in te Helsinki metropolitan area. The average concentrations attributed to wood combustion in winter were up to 10- or 15-fold compared to summer. Wood combustion caused 12 % to 14 % of annual fine particle concentrations. In winter, the contribution ranged from 16 % to 21 %.
Svetlana Sofieva, Eija Asmi, Nina S. Atanasova, Aino E. Heikkinen, Emeline Vidal, Jonathan Duplissy, Martin Romantschuk, Rostislav Kouznetsov, Jaakko Kukkonen, Dennis H. Bamford, Antti-Pekka Hyvärinen, and Mikhail Sofiev
Atmos. Meas. Tech., 15, 6201–6219, https://doi.org/10.5194/amt-15-6201-2022, https://doi.org/10.5194/amt-15-6201-2022, 2022
Short summary
Short summary
A new bubble-generating glass chamber design with an extensive set of aerosol production experiments is presented to re-evaluate bubble-bursting-mediated aerosol production as a function of water parameters: bubbling air flow, water salinity, and temperature. Our main findings suggest modest dependence of aerosol production on the water salinity and a strong dependence on temperature below ~ 10 °C.
Matthias Karl, Liisa Pirjola, Tiia Grönholm, Mona Kurppa, Srinivasan Anand, Xiaole Zhang, Andreas Held, Rolf Sander, Miikka Dal Maso, David Topping, Shuai Jiang, Leena Kangas, and Jaakko Kukkonen
Geosci. Model Dev., 15, 3969–4026, https://doi.org/10.5194/gmd-15-3969-2022, https://doi.org/10.5194/gmd-15-3969-2022, 2022
Short summary
Short summary
The community aerosol dynamics model MAFOR includes several advanced features: coupling with an up-to-date chemistry mechanism for volatile organic compounds, a revised Brownian coagulation kernel that takes into account the fractal geometry of soot particles, a multitude of nucleation parameterizations, size-resolved partitioning of semi-volatile inorganics, and a hybrid method for the formation of secondary organic aerosols within the framework of condensation and evaporation.
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
Short summary
Short summary
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.
Jaakko Kukkonen, Mikko Savolahti, Yuliia Palamarchuk, Timo Lanki, Väinö Nurmi, Ville-Veikko Paunu, Leena Kangas, Mikhail Sofiev, Ari Karppinen, Androniki Maragkidou, Pekka Tiittanen, and Niko Karvosenoja
Atmos. Chem. Phys., 20, 9371–9391, https://doi.org/10.5194/acp-20-9371-2020, https://doi.org/10.5194/acp-20-9371-2020, 2020
Short summary
Short summary
We have developed a mathematical model that can be used to analyse the benefits that could be achieved by implementing alternative air quality abatement measures, policies or strategies. The model was applied to determine pollution sources in the whole of Finland in 2015. Clearly the most economically effective measures were the reduction in emissions from low-level sources in urban areas. Such sources include road transport, non-road vehicles and machinery, and residential wood combustion.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Jaakko Kukkonen, Leena Kangas, Mari Kauhaniemi, Mikhail Sofiev, Mia Aarnio, Jouni J. K. Jaakkola, Anu Kousa, and Ari Karppinen
Atmos. Chem. Phys., 18, 8041–8064, https://doi.org/10.5194/acp-18-8041-2018, https://doi.org/10.5194/acp-18-8041-2018, 2018
Short summary
Short summary
We have quantified the emissions and concentrations of fine particulate matter in the Helsinki area for an unprecedentedly extensive period, from 1980 to 2014. The modelled concentrations agree well with the measured data. The concentrations of fine particles have decreased drastically since the 1980s, to about a half of the highest values. The results make it possible to evaluate the long-term health impacts of air pollution substantially better.
John Backman, Curtis R. Wood, Mikko Auvinen, Leena Kangas, Hanna Hannuniemi, Ari Karppinen, and Jaakko Kukkonen
Geosci. Model Dev., 10, 3793–3803, https://doi.org/10.5194/gmd-10-3793-2017, https://doi.org/10.5194/gmd-10-3793-2017, 2017
Short summary
Short summary
Meteorological input parameters for urban- and local-scale dispersion models can be derived from meteorological observations. This study presents a sensitivity analysis of a meteorological model that utilises readily available meteorological data to derive specific parameters required to model the atmospheric dispersion of pollutants. The study shows that wind speed is the most fundamental meteorological input parameter followed by solar radiation.
Heidi Hellén, Leena Kangas, Anu Kousa, Mika Vestenius, Kimmo Teinilä, Ari Karppinen, Jaakko Kukkonen, and Jarkko V. Niemi
Atmos. Chem. Phys., 17, 3475–3487, https://doi.org/10.5194/acp-17-3475-2017, https://doi.org/10.5194/acp-17-3475-2017, 2017
Short summary
Short summary
Estimating impacts of wood combustion on ambient levels of PAHs is challenging. In this study effect of residential wood combustion on the benzo[a]pyrene concentrations in the air of Helsinki metropolitan area was studied, using ambient air measurements, emission estimates and dispersion modeling. Combining all this information enabled a quantitative characterization of the influence of residential wood combustion, which was found to be the main local source and more important than for PM2.5.
Marje Prank, Mikhail Sofiev, Svetlana Tsyro, Carlijn Hendriks, Valiyaveetil Semeena, Xavier Vazhappilly Francis, Tim Butler, Hugo Denier van der Gon, Rainer Friedrich, Johannes Hendricks, Xin Kong, Mark Lawrence, Mattia Righi, Zissis Samaras, Robert Sausen, Jaakko Kukkonen, and Ranjeet Sokhi
Atmos. Chem. Phys., 16, 6041–6070, https://doi.org/10.5194/acp-16-6041-2016, https://doi.org/10.5194/acp-16-6041-2016, 2016
Short summary
Short summary
Aerosol composition in Europe was simulated by four chemistry transport models and compared to observations to identify the most prominent areas for model improvement. Notable differences were found between the models' predictions, attributable to different treatment or omission of aerosol sources and processes. All models underestimated the observed concentrations by 10–60 %, mostly due to under-predicting the carbonaceous and mineral particles and omitting the aerosol-bound water.
Matthias Karl, Jaakko Kukkonen, Menno P. Keuken, Susanne Lützenkirchen, Liisa Pirjola, and Tareq Hussein
Atmos. Chem. Phys., 16, 4817–4835, https://doi.org/10.5194/acp-16-4817-2016, https://doi.org/10.5194/acp-16-4817-2016, 2016
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Particles emitted from road traffic are subject to complex dilution processes as well as microphysical transformation processes. Particle measurements at major roads in Rotterdam, Oslo and Helsinki were used to analyze the relevance of microphysical transformation processes. Transformation processes caused changes of the particle number concentration of up to 20–30 % on the neighborhood scale. A simple parameterization to predict particle number concentrations in urban areas is presented.
J. Kukkonen, M. Karl, M. P. Keuken, H. A. C. Denier van der Gon, B. R. Denby, V. Singh, J. Douros, A. Manders, Z. Samaras, N. Moussiopoulos, S. Jonkers, M. Aarnio, A. Karppinen, L. Kangas, S. Lützenkirchen, T. Petäjä, I. Vouitsis, and R. S. Sokhi
Geosci. Model Dev., 9, 451–478, https://doi.org/10.5194/gmd-9-451-2016, https://doi.org/10.5194/gmd-9-451-2016, 2016
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For analyzing the health effects of particulate matter, it is necessary to consider not only the mass of particles, but also their sizes and composition. A simple measure for the former is the number concentration of particles. We present particle number concentrations in five major European cities, namely Helsinki, Oslo, London, Rotterdam, and Athens, in 2008, based mainly on modelling. The concentrations of PN were mostly influenced by the emissions from local vehicular traffic.
J.-P. Jalkanen, L. Johansson, and J. Kukkonen
Atmos. Chem. Phys., 16, 71–84, https://doi.org/10.5194/acp-16-71-2016, https://doi.org/10.5194/acp-16-71-2016, 2016
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This manuscript describes the emissions from shipping in European sea areas. The work is based on automatic position reports (AIS) sent by ships and reflects realistic activity patterns of ships. The work demonstrates that it is feasible to construct full bottom-up emission inventories based on large-volume activity data sets.
J. Kukkonen, J. Nikmo, M. Sofiev, K. Riikonen, T. Petäjä, A. Virkkula, J. Levula, S. Schobesberger, and D. M. Webber
Geosci. Model Dev., 7, 2663–2681, https://doi.org/10.5194/gmd-7-2663-2014, https://doi.org/10.5194/gmd-7-2663-2014, 2014
M. Kauhaniemi, A. Stojiljkovic, L. Pirjola, A. Karppinen, J. Härkönen, K. Kupiainen, L. Kangas, M. A. Aarnio, G. Omstedt, B. R. Denby, and J. Kukkonen
Atmos. Chem. Phys., 14, 9155–9169, https://doi.org/10.5194/acp-14-9155-2014, https://doi.org/10.5194/acp-14-9155-2014, 2014
J. Soares, A. Kousa, J. Kukkonen, L. Matilainen, L. Kangas, M. Kauhaniemi, K. Riikonen, J.-P. Jalkanen, T. Rasila, O. Hänninen, T. Koskentalo, M. Aarnio, C. Hendriks, and A. Karppinen
Geosci. Model Dev., 7, 1855–1872, https://doi.org/10.5194/gmd-7-1855-2014, https://doi.org/10.5194/gmd-7-1855-2014, 2014
A. Virkkula, J. Levula, T. Pohja, P. P. Aalto, P. Keronen, S. Schobesberger, C. B. Clements, L. Pirjola, A.-J. Kieloaho, L. Kulmala, H. Aaltonen, J. Patokoski, J. Pumpanen, J. Rinne, T. Ruuskanen, M. Pihlatie, H. E. Manninen, V. Aaltonen, H. Junninen, T. Petäjä, J. Backman, M. Dal Maso, T. Nieminen, T. Olsson, T. Grönholm, J. Aalto, T. H. Virtanen, M. Kajos, V.-M. Kerminen, D. M. Schultz, J. Kukkonen, M. Sofiev, G. De Leeuw, J. Bäck, P. Hari, and M. Kulmala
Atmos. Chem. Phys., 14, 4473–4502, https://doi.org/10.5194/acp-14-4473-2014, https://doi.org/10.5194/acp-14-4473-2014, 2014
L. Johansson, J.-P. Jalkanen, J. Kalli, and J. Kukkonen
Atmos. Chem. Phys., 13, 11375–11389, https://doi.org/10.5194/acp-13-11375-2013, https://doi.org/10.5194/acp-13-11375-2013, 2013
Related subject area
Atmospheric sciences
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
Assessment of object-based indices to identify convective organization
The Global Forest Fire Emissions Prediction System version 1.0
NEIVAv1.0: Next-generation Emissions InVentory expansion of Akagi et al. (2011) version 1.0
FLEXPART version 11: improved accuracy, efficiency, and flexibility
Challenges of high-fidelity air quality modeling in urban environments – PALM sensitivity study during stable conditions
Air quality modeling intercomparison and multiscale ensemble chain for Latin America
Recommended coupling to global meteorological fields for long-term tracer simulations with WRF-GHG
Selecting CMIP6 global climate models (GCMs) for Coordinated Regional Climate Downscaling Experiment (CORDEX) dynamical downscaling over Southeast Asia using a standardised benchmarking framework
Improved definition of prior uncertainties in CO2 and CO fossil fuel fluxes and its impact on multi-species inversion with GEOS-Chem (v12.5)
RASCAL v1.0: an open-source tool for climatological time series reconstruction and extension
Introducing graupel density prediction in Weather Research and Forecasting (WRF) double-moment 6-class (WDM6) microphysics and evaluation of the modified scheme during the ICE-POP field campaign
Enabling high-performance cloud computing for the Community Multiscale Air Quality Model (CMAQ) version 5.3.3: performance evaluation and benefits for the user community
Atmospheric-river-induced precipitation in California as simulated by the regionally refined Simple Convective Resolving E3SM Atmosphere Model (SCREAM) Version 0
Recent improvements and maximum covariance analysis of aerosol and cloud properties in the EC-Earth3-AerChem model
GPU-HADVPPM4HIP V1.0: using the heterogeneous-compute interface for portability (HIP) to speed up the piecewise parabolic method in the CAMx (v6.10) air quality model on China's domestic GPU-like accelerator
Preliminary evaluation of the effect of electro-coalescence with conducting sphere approximation on the formation of warm cumulus clouds using SCALE-SDM version 0.2.5–2.3.0
Similarity-Based Analysis of Atmospheric Organic Compounds for Machine Learning Applications
Exploring the footprint representation of microwave radiance observations in an Arctic limited-area data assimilation system
Orbital-Radar v1.0.0: A tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
Analysis of model error in forecast errors of extended atmospheric Lorenz 05 systems and the ECMWF system
Description and validation of Vehicular Emissions from Road Traffic (VERT) 1.0, an R-based framework for estimating road transport emissions from traffic flows
AeroMix v1.0.1: a Python package for modeling aerosol optical properties and mixing states
Impact of ITCZ width on global climate: ITCZ-MIP
Deep-learning-driven simulations of boundary layer clouds over the Southern Great Plains
Mixed-precision computing in the GRIST dynamical core for weather and climate modelling
A conservative immersed boundary method for the multi-physics urban large-eddy simulation model uDALES v2.0
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
RCEMIP-II: mock-Walker simulations as phase II of the radiative–convective equilibrium model intercomparison project
The MESSy DWARF (based on MESSy v2.55.2)
Objective identification of meteorological fronts and climatologies from ERA-Interim and ERA5
TAMS: a tracking, classifying, and variable-assigning algorithm for mesoscale convective systems in simulated and satellite-derived datasets
Development of the adjoint of the unified tropospheric–stratospheric chemistry extension (UCX) in GEOS-Chem adjoint v36
New explicit formulae for the settling speed of prolate spheroids in the atmosphere: theoretical background and implementation in AerSett v2.0.2
ZJU-AERO V0.5: an Accurate and Efficient Radar Operator designed for CMA-GFS/MESO with the capability to simulate non-spherical hydrometeors
The Year of Polar Prediction site Model Intercomparison Project (YOPPsiteMIP) phase 1: project overview and Arctic winter forecast evaluation
Evaluating CHASER V4.0 global formaldehyde (HCHO) simulations using satellite, aircraft, and ground-based remote-sensing observations
Global variable-resolution simulations of extreme precipitation over Henan, China, in 2021 with MPAS-Atmosphere v7.3
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
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A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
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To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
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Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
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Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
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The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
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Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
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Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
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This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
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Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
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Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
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This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
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In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
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The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
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The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
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Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Jaroslav Resler, Petra Bauerová, Michal Belda, Martin Bureš, Kryštof Eben, Vladimír Fuka, Jan Geletič, Radek Jareš, Jan Karel, Josef Keder, Pavel Krč, William Patiño, Jelena Radović, Hynek Řezníček, Matthias Sühring, Adriana Šindelářová, and Ondřej Vlček
Geosci. Model Dev., 17, 7513–7537, https://doi.org/10.5194/gmd-17-7513-2024, https://doi.org/10.5194/gmd-17-7513-2024, 2024
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Detailed modeling of urban air quality in stable conditions is a challenge. We show the unprecedented sensitivity of a large eddy simulation (LES) model to meteorological boundary conditions and model parameters in an urban environment under stable conditions. We demonstrate the crucial role of boundary conditions for the comparability of results with observations. The study reveals a strong sensitivity of the results to model parameters and model numerical instabilities during such conditions.
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512, https://doi.org/10.5194/gmd-17-7467-2024, https://doi.org/10.5194/gmd-17-7467-2024, 2024
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Latin America (LAC) has some of the most populated urban areas in the world, with high levels of air pollution. Air quality management in LAC has been traditionally focused on surveillance and building emission inventories. This study performed the first intercomparison and model evaluation in LAC, with interesting and insightful findings for the region. A multiscale modeling ensemble chain was assembled as a first step towards an air quality forecasting system.
David Ho, Michał Gałkowski, Friedemann Reum, Santiago Botía, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig
Geosci. Model Dev., 17, 7401–7422, https://doi.org/10.5194/gmd-17-7401-2024, https://doi.org/10.5194/gmd-17-7401-2024, 2024
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Atmospheric model users often overlook the impact of the land–atmosphere interaction. This study accessed various setups of WRF-GHG simulations that ensure consistency between the model and driving reanalysis fields. We found that a combination of nudging and frequent re-initialization allows certain improvement by constraining the soil moisture fields and, through its impact on atmospheric mixing, improves atmospheric transport.
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev., 17, 7285–7315, https://doi.org/10.5194/gmd-17-7285-2024, https://doi.org/10.5194/gmd-17-7285-2024, 2024
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We use a comprehensive approach to select a subset of CMIP6 models for dynamical downscaling over Southeast Asia, taking into account model performance, model independence, data availability and the range of future climate projections. The standardised benchmarking framework is applied to assess model performance through both statistical and process-based metrics. Ultimately, we identify two independent model groups that are suitable for dynamical downscaling in the Southeast Asian region.
Ingrid Super, Tia Scarpelli, Arjan Droste, and Paul I. Palmer
Geosci. Model Dev., 17, 7263–7284, https://doi.org/10.5194/gmd-17-7263-2024, https://doi.org/10.5194/gmd-17-7263-2024, 2024
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Monitoring greenhouse gas emission reductions requires a combination of models and observations, as well as an initial emission estimate. Each component provides information with a certain level of certainty and is weighted to yield the most reliable estimate of actual emissions. We describe efforts for estimating the uncertainty in the initial emission estimate, which significantly impacts the outcome. Hence, a good uncertainty estimate is key for obtaining reliable information on emissions.
Álvaro González-Cervera and Luis Durán
Geosci. Model Dev., 17, 7245–7261, https://doi.org/10.5194/gmd-17-7245-2024, https://doi.org/10.5194/gmd-17-7245-2024, 2024
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RASCAL is an open-source Python tool designed for reconstructing daily climate observations, especially in regions with complex local phenomena. It merges large-scale weather patterns with local weather using the analog method. Evaluations in central Spain show that RASCAL outperforms ERA20C reanalysis in reconstructing precipitation and temperature. RASCAL offers opportunities for broad scientific applications, from short-term forecasts to local-scale climate change scenarios.
Sun-Young Park, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, and Jason A. Milbrandt
Geosci. Model Dev., 17, 7199–7218, https://doi.org/10.5194/gmd-17-7199-2024, https://doi.org/10.5194/gmd-17-7199-2024, 2024
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We enhance the WDM6 scheme by incorporating predicted graupel density. The modification affects graupel characteristics, including fall velocity–diameter and mass–diameter relationships. Simulations highlight changes in graupel distribution and precipitation patterns, potentially influencing surface snow amounts. The study underscores the significance of integrating predicted graupel density for a more realistic portrayal of microphysical properties in weather models.
Christos I. Efstathiou, Elizabeth Adams, Carlie J. Coats, Robert Zelt, Mark Reed, John McGee, Kristen M. Foley, Fahim I. Sidi, David C. Wong, Steven Fine, and Saravanan Arunachalam
Geosci. Model Dev., 17, 7001–7027, https://doi.org/10.5194/gmd-17-7001-2024, https://doi.org/10.5194/gmd-17-7001-2024, 2024
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We present a summary of enabling high-performance computing of the Community Multiscale Air Quality Model (CMAQ) – a state-of-the-science community multiscale air quality model – on two cloud computing platforms through documenting the technologies, model performance, scaling and relative merits. This may be a new paradigm for computationally intense future model applications. We initiated this work due to a need to leverage cloud computing advances and to ease the learning curve for new users.
Peter A. Bogenschutz, Jishi Zhang, Qi Tang, and Philip Cameron-Smith
Geosci. Model Dev., 17, 7029–7050, https://doi.org/10.5194/gmd-17-7029-2024, https://doi.org/10.5194/gmd-17-7029-2024, 2024
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Using high-resolution and state-of-the-art modeling techniques we simulate five atmospheric river events for California to test the capability to represent precipitation for these events. We find that our model is able to capture the distribution of precipitation very well but suffers from overestimating the precipitation amounts over high elevation. Increasing the resolution further has no impact on reducing this bias, while increasing the domain size does have modest impacts.
Manu Anna Thomas, Klaus Wyser, Shiyu Wang, Marios Chatziparaschos, Paraskevi Georgakaki, Montserrat Costa-Surós, Maria Gonçalves Ageitos, Maria Kanakidou, Carlos Pérez García-Pando, Athanasios Nenes, Twan van Noije, Philippe Le Sager, and Abhay Devasthale
Geosci. Model Dev., 17, 6903–6927, https://doi.org/10.5194/gmd-17-6903-2024, https://doi.org/10.5194/gmd-17-6903-2024, 2024
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Aerosol–cloud interactions occur at a range of spatio-temporal scales. While evaluating recent developments in EC-Earth3-AerChem, this study aims to understand the extent to which the Twomey effect manifests itself at larger scales. We find a reduction in the warm bias over the Southern Ocean due to model improvements. While we see footprints of the Twomey effect at larger scales, the negative relationship between cloud droplet number and liquid water drives the shortwave radiative effect.
Kai Cao, Qizhong Wu, Lingling Wang, Hengliang Guo, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongxing Li, Lina Liu, Dongqing Li, Hao Wu, and Lanning Wang
Geosci. Model Dev., 17, 6887–6901, https://doi.org/10.5194/gmd-17-6887-2024, https://doi.org/10.5194/gmd-17-6887-2024, 2024
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AMD’s heterogeneous-compute interface for portability was implemented to port the piecewise parabolic method solver from NVIDIA GPUs to China's GPU-like accelerators. The results show that the larger the model scale, the more acceleration effect on the GPU-like accelerator, up to 28.9 times. The multi-level parallelism achieves a speedup of 32.7 times on the heterogeneous cluster. By comparing the results, the GPU-like accelerators have more accuracy for the geoscience numerical models.
Ruyi Zhang, Limin Zhou, Shin-ichiro Shima, and Huawei Yang
Geosci. Model Dev., 17, 6761–6774, https://doi.org/10.5194/gmd-17-6761-2024, https://doi.org/10.5194/gmd-17-6761-2024, 2024
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Solar activity weakly ionises Earth's atmosphere, charging cloud droplets. Electro-coalescence is when oppositely charged droplets stick together. We introduce an analytical expression of electro-coalescence probability and use it in a warm-cumulus-cloud simulation. Results show that charge cases increase rain and droplet size, with the new method outperforming older ones. The new method requires longer computation time, but its impact on rain justifies inclusion in meteorology models.
Hilda Sandström and Patrick Rinke
EGUsphere, https://doi.org/10.48550/arXiv.2406.18171, https://doi.org/10.48550/arXiv.2406.18171, 2024
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Machine learning has the potential to aid the identification 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 model in atmospheric sciences.
Máté Mile, Stephanie Guedj, and Roger Randriamampianina
Geosci. Model Dev., 17, 6571–6587, https://doi.org/10.5194/gmd-17-6571-2024, https://doi.org/10.5194/gmd-17-6571-2024, 2024
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Satellite observations provide crucial information about atmospheric constituents in a global distribution that helps to better predict the weather over sparsely observed regions like the Arctic. However, the use of satellite data is usually conservative and imperfect. In this study, a better spatial representation of satellite observations is discussed and explored by a so-called footprint function or operator, highlighting its added value through a case study and diagnostics.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-129, https://doi.org/10.5194/gmd-2024-129, 2024
Revised manuscript accepted for GMD
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Orbital-radar is a Python tool transferring sub-orbital radar data (ground-based, airborne, and forward-simulated NWP) into synthetical space-borne cloud profiling radar data mimicking the platform characteristics, e.g. EarthCARE or CloudSat CPR. The novelty of orbital-radar is the simulation platform characteristic noise floors and errors. By this long time data sets can be transformed into synthetic observations for Cal/Valor sensitivity studies for new or future satellite missions.
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 17, 6489–6511, https://doi.org/10.5194/gmd-17-6489-2024, https://doi.org/10.5194/gmd-17-6489-2024, 2024
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The forecast error growth of atmospheric phenomena is caused by initial and model errors. When studying the initial error growth, it may turn out that small-scale phenomena, which contribute little to the forecast product, significantly affect the ability to predict this product. With a negative result, we investigate in the extended Lorenz (2005) system whether omitting these phenomena will improve predictability. A theory explaining and describing this behavior is developed.
Giorgio Veratti, Alessandro Bigi, Sergio Teggi, and Grazia Ghermandi
Geosci. Model Dev., 17, 6465–6487, https://doi.org/10.5194/gmd-17-6465-2024, https://doi.org/10.5194/gmd-17-6465-2024, 2024
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In this study, we present VERT (Vehicular Emissions from Road Traffic), an R package designed to estimate transport emissions using traffic estimates and vehicle fleet composition data. Compared to other tools available in the literature, VERT stands out for its user-friendly configuration and flexibility of user input. Case studies demonstrate its accuracy in both urban and regional contexts, making it a valuable tool for air quality management and transport scenario planning.
Sam P. Raj, Puna Ram Sinha, Rohit Srivastava, Srinivas Bikkina, and Damu Bala Subrahamanyam
Geosci. Model Dev., 17, 6379–6399, https://doi.org/10.5194/gmd-17-6379-2024, https://doi.org/10.5194/gmd-17-6379-2024, 2024
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A Python successor to the aerosol module of the OPAC model, named AeroMix, has been developed, with enhanced capabilities to better represent real atmospheric aerosol mixing scenarios. AeroMix’s performance in modeling aerosol mixing states has been evaluated against field measurements, substantiating its potential as a versatile aerosol optical model framework for next-generation algorithms to infer aerosol mixing states and chemical composition.
Angeline G. Pendergrass, Michael P. Byrne, Oliver Watt-Meyer, Penelope Maher, and Mark J. Webb
Geosci. Model Dev., 17, 6365–6378, https://doi.org/10.5194/gmd-17-6365-2024, https://doi.org/10.5194/gmd-17-6365-2024, 2024
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The width of the tropical rain belt affects many aspects of our climate, yet we do not understand what controls it. To better understand it, we present a method to change it in numerical model experiments. We show that the method works well in four different models. The behavior of the width is unexpectedly simple in some ways, such as how strong the winds are as it changes, but in other ways, it is more complicated, especially how temperature increases with carbon dioxide.
Tianning Su and Yunyan Zhang
Geosci. Model Dev., 17, 6319–6336, https://doi.org/10.5194/gmd-17-6319-2024, https://doi.org/10.5194/gmd-17-6319-2024, 2024
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Using 2 decades of field observations over the Southern Great Plains, this study developed a deep-learning model to simulate the complex dynamics of boundary layer clouds. The deep-learning model can serve as the cloud parameterization within reanalysis frameworks, offering insights into improving the simulation of low clouds. By quantifying biases due to various meteorological factors and parameterizations, this deep-learning-driven approach helps bridge the observation–modeling divide.
Siyuan Chen, Yi Zhang, Yiming Wang, Zhuang Liu, Xiaohan Li, and Wei Xue
Geosci. Model Dev., 17, 6301–6318, https://doi.org/10.5194/gmd-17-6301-2024, https://doi.org/10.5194/gmd-17-6301-2024, 2024
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This study explores strategies and techniques for implementing mixed-precision code optimization within an atmosphere model dynamical core. The coded equation terms in the governing equations that are sensitive (or insensitive) to the precision level have been identified. The performance of mixed-precision computing in weather and climate simulations was analyzed.
Sam O. Owens, Dipanjan Majumdar, Chris E. Wilson, Paul Bartholomew, and Maarten van Reeuwijk
Geosci. Model Dev., 17, 6277–6300, https://doi.org/10.5194/gmd-17-6277-2024, https://doi.org/10.5194/gmd-17-6277-2024, 2024
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Designing cities that are resilient, sustainable, and beneficial to health requires an understanding of urban climate and air quality. This article presents an upgrade to the multi-physics numerical model uDALES, which can simulate microscale airflow, heat transfer, and pollutant dispersion in urban environments. This upgrade enables it to resolve realistic urban geometries more accurately and to take advantage of the resources available on current and future high-performance computing systems.
Felipe Cifuentes, Henk Eskes, Folkert Boersma, Enrico Dammers, and Charlotte Bryan
EGUsphere, https://doi.org/10.5194/egusphere-2024-2225, https://doi.org/10.5194/egusphere-2024-2225, 2024
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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 derived 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 NO2 lifetime, NOX:NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces a strong model dependency, reducing the simplicity of the original FDA formulation.
Allison A. Wing, Levi G. Silvers, and Kevin A. Reed
Geosci. Model Dev., 17, 6195–6225, https://doi.org/10.5194/gmd-17-6195-2024, https://doi.org/10.5194/gmd-17-6195-2024, 2024
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This paper presents the experimental design for a model intercomparison project to study tropical clouds and climate. It is a follow-up from a prior project that used a simplified framework for tropical climate. The new project adds one new component – a specified pattern of sea surface temperatures as the lower boundary condition. We provide example results from one cloud-resolving model and one global climate model and test the sensitivity to the experimental parameters.
Astrid Kerkweg, Timo Kirfel, Doung H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-117, https://doi.org/10.5194/gmd-2024-117, 2024
Revised manuscript accepted for GMD
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This article introduces the MESSy DWARF. Usually, the Modular Earth Submodel System (MESSy) is linked to full dynamical models to build chemistry climate models. However, due to the modular concept of MESSy, and the newly developed DWARF component, it is now possible to create simplified models containing just one or some process descriptions. This renders very useful for technical optimisation (e.g., GPU porting) and can be used to create less complex models, e.g., a chemical box model.
Philip G. Sansom and Jennifer L. Catto
Geosci. Model Dev., 17, 6137–6151, https://doi.org/10.5194/gmd-17-6137-2024, https://doi.org/10.5194/gmd-17-6137-2024, 2024
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Weather fronts bring a lot of rain and strong winds to many regions of the mid-latitudes. We have developed an updated method of identifying these fronts in gridded data that can be used on new datasets with small grid spacing. The method can be easily applied to different datasets due to the use of open-source software for its development and shows improvements over similar previous methods. We present an updated estimate of the average frequency of fronts over the past 40 years.
Kelly M. Núñez Ocasio and Zachary L. Moon
Geosci. Model Dev., 17, 6035–6049, https://doi.org/10.5194/gmd-17-6035-2024, https://doi.org/10.5194/gmd-17-6035-2024, 2024
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TAMS is an open-source Python-based package for tracking and classifying mesoscale convective systems that can be used to study observed and simulated systems. Each step of the algorithm is described in this paper with examples showing how to make use of visualization and post-processing tools within the package. A unique and valuable feature of this tracker is its support for unstructured grids in the identification stage and grid-independent tracking.
Irene C. Dedoussi, Daven K. Henze, Sebastian D. Eastham, Raymond L. Speth, and Steven R. H. Barrett
Geosci. Model Dev., 17, 5689–5703, https://doi.org/10.5194/gmd-17-5689-2024, https://doi.org/10.5194/gmd-17-5689-2024, 2024
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Atmospheric model gradients provide a meaningful tool for better understanding the underlying atmospheric processes. Adjoint modeling enables computationally efficient gradient calculations. We present the adjoint of the GEOS-Chem unified chemistry extension (UCX). With this development, the GEOS-Chem adjoint model can capture stratospheric ozone and other processes jointly with tropospheric processes. We apply it to characterize the Antarctic ozone depletion potential of active halogen species.
Sylvain Mailler, Sotirios Mallios, Arineh Cholakian, Vassilis Amiridis, Laurent Menut, and Romain Pennel
Geosci. Model Dev., 17, 5641–5655, https://doi.org/10.5194/gmd-17-5641-2024, https://doi.org/10.5194/gmd-17-5641-2024, 2024
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We propose two explicit expressions to calculate the settling speed of solid atmospheric particles with prolate spheroidal shapes. The first formulation is based on theoretical arguments only, while the second one is based on computational fluid dynamics calculations. We show that the first method is suitable for virtually all atmospheric aerosols, provided their shape can be adequately described as a prolate spheroid, and we provide an implementation of the first method in AerSett v2.0.2.
Hejun Xie, Lei Bi, and Wei Han
Geosci. Model Dev., 17, 5657–5688, https://doi.org/10.5194/gmd-17-5657-2024, https://doi.org/10.5194/gmd-17-5657-2024, 2024
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A radar operator plays a crucial role in utilizing radar observations to enhance numerical weather forecasts. However, developing an advanced radar operator is challenging due to various complexities associated with the wave scattering by non-spherical hydrometeors, radar beam propagation, and multiple platforms. In this study, we introduce a novel radar operator named the Accurate and Efficient Radar Operator developed by ZheJiang University (ZJU-AERO) which boasts several unique features.
Jonathan J. Day, Gunilla Svensson, Barbara Casati, Taneil Uttal, Siri-Jodha Khalsa, Eric Bazile, Elena Akish, Niramson Azouz, Lara Ferrighi, Helmut Frank, Michael Gallagher, Øystein Godøy, Leslie M. Hartten, Laura X. Huang, Jareth Holt, Massimo Di Stefano, Irene Suomi, Zen Mariani, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Teresa Remes, Rostislav Fadeev, Amy Solomon, Johanna Tjernström, and Mikhail Tolstykh
Geosci. Model Dev., 17, 5511–5543, https://doi.org/10.5194/gmd-17-5511-2024, https://doi.org/10.5194/gmd-17-5511-2024, 2024
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The YOPP site Model Intercomparison Project (YOPPsiteMIP), which was designed to facilitate enhanced weather forecast evaluation in polar regions, is discussed here, focussing on describing the archive of forecast data and presenting a multi-model evaluation at Arctic supersites during February and March 2018. The study highlights an underestimation in boundary layer temperature variance that is common across models and a related inability to forecast cold extremes at several of the sites.
Hossain Mohammed Syedul Hoque, Kengo Sudo, Hitoshi Irie, Yanfeng He, and Md Firoz Khan
Geosci. Model Dev., 17, 5545–5571, https://doi.org/10.5194/gmd-17-5545-2024, https://doi.org/10.5194/gmd-17-5545-2024, 2024
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Using multi-platform observations, we validated global formaldehyde (HCHO) simulations from a chemistry transport model. HCHO is a crucial intermediate in the chemical catalytic cycle that governs the ozone formation in the troposphere. The model was capable of replicating the observed spatiotemporal variability in HCHO. In a few cases, the model's capability was limited. This is attributed to the uncertainties in the observations and the model parameters.
Zijun Liu, Li Dong, Zongxu Qiu, Xingrong Li, Huiling Yuan, Dongmei Meng, Xiaobin Qiu, Dingyuan Liang, and Yafei Wang
Geosci. Model Dev., 17, 5477–5496, https://doi.org/10.5194/gmd-17-5477-2024, https://doi.org/10.5194/gmd-17-5477-2024, 2024
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In this study, we completed a series of simulations with MPAS-Atmosphere (version 7.3) to study the extreme precipitation event of Henan, China, during 20–22 July 2021. We found the different performance of two built-in parameterization scheme suites (mesoscale and convection-permitting suites) with global quasi-uniform and variable-resolution meshes. This study holds significant implications for advancing the understanding of the scale-aware capability of MPAS-Atmosphere.
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Short summary
A mathematical model has been developed for the dispersion of plumes originating from major fires. We have refined the model for the early evolution of the fire plumes; such a module has not been previously presented. We have evaluated the model against experimental field-scale data. The predicted concentrations agreed well with the aircraft measurements. We have also compiled an operational version of the model, which can be used for emergency contingency planning in the case of major fires.
A mathematical model has been developed for the dispersion of plumes originating from major...
