Articles | Volume 15, issue 9
https://doi.org/10.5194/gmd-15-3969-2022
© 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-15-3969-2022
© 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
| 
16 May 2022
Model description paper |
| 16 May 2022
| 16 May 2022
Description and evaluation of the community aerosol dynamics model MAFOR v2.0
Matthias Karl
CORRESPONDING AUTHOR
Chemistry Transport Modelling, Helmholtz-Zentrum Hereon, Geesthacht, Germany
Liisa Pirjola
Department of Physics, University of Helsinki, Helsinki, Finland
Department of Automotive and Mechanical Engineering, Metropolia University of Applied Sciences, Vantaa, Finland
Tiia Grönholm
Atmospheric Composition Research, Finnish Meteorological Institute, Helsinki, Finland
Mona Kurppa
Atmospheric Composition Research, Finnish Meteorological Institute, Helsinki, Finland
Srinivasan Anand
Health Physics Division, Bhabha Atomic Research Centre, Mumbai, India
Xiaole Zhang
Institute of Environmental Engineering (IfU), ETH Zürich, Zürich, Switzerland
Andreas Held
Environmental Chemistry and Air Research, Technische Universität Berlin, Berlin, Germany
Rolf Sander
Air Chemistry Department, Max Planck Institute for Chemistry, Mainz, Germany
Miikka Dal Maso
Aerosol Physics, Faculty of Engineering and Natural Sciences, Tampere University, Tampere, Finland
David Topping
Department of Earth and Environmental Science, University of Manchester, Manchester, UK
Shuai Jiang
School of Information Science and Technology, University of Science and Technology of China, Hefei, Anhui, China
Leena Kangas
Atmospheric Composition Research, Finnish Meteorological Institute, Helsinki, Finland
Jaakko Kukkonen
Atmospheric Composition Research, Finnish Meteorological Institute, Helsinki, Finland
Centre for Atmospheric and Climate Physics Research, and Centre for Climate Change Research, University of Hertfordshire, Hatfield, UK
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Rolf Sander
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Meghna Soni, Rolf Sander, Lokesh K. Sahu, Domenico Taraborrelli, Pengfei Liu, Ankit Patel, Imran A. Girach, Andrea Pozzer, Sachin S. Gunthe, and Narendra Ojha
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Magdalena Okuljar, Olga Garmash, Miska Olin, Joni Kalliokoski, Hilkka Timonen, Jarkko V. Niemi, Pauli Paasonen, Jenni Kontkanen, Yanjun Zhang, Heidi Hellén, Heino Kuuluvainen, Minna Aurela, Hanna E. Manninen, Mikko Sipilä, Topi Rönkkö, Tuukka Petäjä, Markku Kulmala, Miikka Dal Maso, and Mikael Ehn
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Rolf Sander
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Lea Fink, Matthias Karl, Volker Matthias, Sonia Oppo, Richard Kranenburg, Jeroen Kuenen, Sara Jutterström, Jana Moldanova, Elisa Majamäki, and Jukka-Pekka Jalkanen
Atmos. Chem. Phys., 23, 10163–10189, https://doi.org/10.5194/acp-23-10163-2023, https://doi.org/10.5194/acp-23-10163-2023, 2023
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Jani Strömberg, Xiaoyu Li, Mona Kurppa, Heino Kuuluvainen, Liisa Pirjola, and Leena Järvi
Atmos. Chem. Phys., 23, 9347–9364, https://doi.org/10.5194/acp-23-9347-2023, https://doi.org/10.5194/acp-23-9347-2023, 2023
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Jonas Elm, Aladár Czitrovszky, Andreas Held, Annele Virtanen, Astrid Kiendler-Scharr, Benjamin J. Murray, Daniel McCluskey, Daniele Contini, David Broday, Eirini Goudeli, Hilkka Timonen, Joan Rosell-Llompart, Jose L. Castillo, Evangelia Diapouli, Mar Viana, Maria E. Messing, Markku Kulmala, Naděžda Zíková, and Sebastian H. Schmitt
Aerosol Research, 1, 13–16, https://doi.org/10.5194/ar-1-13-2023, https://doi.org/10.5194/ar-1-13-2023, 2023
Lea Fink, Matthias Karl, Volker Matthias, Sonia Oppo, Richard Kranenburg, Jeroen Kuenen, Jana Moldanova, Sara Jutterström, Jukka-Pekka Jalkanen, and Elisa Majamäki
Atmos. Chem. Phys., 23, 1825–1862, https://doi.org/10.5194/acp-23-1825-2023, https://doi.org/10.5194/acp-23-1825-2023, 2023
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Petri Kiuru, Marjo Palviainen, Arianna Marchionne, Tiia Grönholm, Maarit Raivonen, Lukas Kohl, and Annamari Laurén
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Peatlands are large carbon stocks. Emissions of carbon dioxide and methane from peatlands may increase due to changes in management and climate. We studied the variation in the gas diffusivity of peat with depth using pore network simulations and laboratory experiments. Gas diffusivity was found to be lower in deeper peat with smaller pores and lower pore connectivity. However, gas diffusivity was not extremely low in wet conditions, which may reflect the distinctive structure of peat.
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
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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.
Chao Yan, Yicheng Shen, Dominik Stolzenburg, Lubna Dada, Ximeng Qi, Simo Hakala, Anu-Maija Sundström, Yishuo Guo, Antti Lipponen, Tom V. Kokkonen, Jenni Kontkanen, Runlong Cai, Jing Cai, Tommy Chan, Liangduo Chen, Biwu Chu, Chenjuan Deng, Wei Du, Xiaolong Fan, Xu-Cheng He, Juha Kangasluoma, Joni Kujansuu, Mona Kurppa, Chang Li, Yiran Li, Zhuohui Lin, Yiliang Liu, Yuliang Liu, Yiqun Lu, Wei Nie, Jouni Pulliainen, Xiaohui Qiao, Yonghong Wang, Yifan Wen, Ye Wu, Gan Yang, Lei Yao, Rujing Yin, Gen Zhang, Shaojun Zhang, Feixue Zheng, Ying Zhou, Antti Arola, Johanna Tamminen, Pauli Paasonen, Yele Sun, Lin Wang, Neil M. Donahue, Yongchun Liu, Federico Bianchi, Kaspar R. Daellenbach, Douglas R. Worsnop, Veli-Matti Kerminen, Tuukka Petäjä, Aijun Ding, Jingkun Jiang, and Markku Kulmala
Atmos. Chem. Phys., 22, 12207–12220, https://doi.org/10.5194/acp-22-12207-2022, https://doi.org/10.5194/acp-22-12207-2022, 2022
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Atmospheric new particle formation (NPF) is a dominant source of atmospheric ultrafine particles. In urban environments, traffic emissions are a major source of primary pollutants, but their contribution to NPF remains under debate. During the COVID-19 lockdown, traffic emissions were significantly reduced, providing a unique chance to examine their relevance to NPF. Based on our comprehensive measurements, we demonstrate that traffic emissions alone are not able to explain the NPF in Beijing.
Janine Lückerath, Andreas Held, Holger Siebert, Michel Michalkow, and Birgit Wehner
Atmos. Chem. Phys., 22, 10007–10021, https://doi.org/10.5194/acp-22-10007-2022, https://doi.org/10.5194/acp-22-10007-2022, 2022
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Three different methods were applied to estimate the vertical aerosol particle flux in the marine boundary layer (MBL) and between the MBL and free troposphere. For the first time, aerosol fluxes derived from these three methods were estimated and compared using airborne aerosol measurements using data from the ACORES field campaign in the northeastern Atlantic Ocean in July 2017. The amount of fluxes was small and directed up and down for different cases, but the methods were applicable.
Miska Olin, Magdalena Okuljar, Matti P. Rissanen, Joni Kalliokoski, Jiali Shen, Lubna Dada, Markus Lampimäki, Yusheng Wu, Annalea Lohila, Jonathan Duplissy, Mikko Sipilä, Tuukka Petäjä, Markku Kulmala, and Miikka Dal Maso
Atmos. Chem. Phys., 22, 8097–8115, https://doi.org/10.5194/acp-22-8097-2022, https://doi.org/10.5194/acp-22-8097-2022, 2022
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Atmospheric new particle formation is an important source of the total particle number concentration in the atmosphere. Several parameters for predicting new particle formation events have been suggested before, but the results have been inconclusive. This study proposes an another predicting parameter, related to a specific type of highly oxidized organic molecules, especially for similar locations to the measurement site in this study, which was a coastal agricultural site in Finland.
Ronny Badeke, Volker Matthias, Matthias Karl, and David Grawe
Geosci. Model Dev., 15, 4077–4103, https://doi.org/10.5194/gmd-15-4077-2022, https://doi.org/10.5194/gmd-15-4077-2022, 2022
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For air quality modeling studies, it is very important to distribute pollutants correctly into the model system. This has not yet been done for shipping pollution in great detail. We studied the effects of different vertical distributions of shipping pollutants on the urban air quality and derived advanced formulas for it. These formulas take weather conditions and ship-specific parameters like the exhaust gas temperature into account.
Jaakko Kukkonen, Juha Nikmo, Kari Riikonen, Ilmo Westerholm, Pekko Ilvessalo, Tuomo Bergman, and Klaus Haikarainen
Geosci. Model Dev., 15, 4027–4054, https://doi.org/10.5194/gmd-15-4027-2022, https://doi.org/10.5194/gmd-15-4027-2022, 2022
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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.
Victoria Anne Sinclair, Jenna Ritvanen, Gabin Urbancic, Irene Erner, Yurii Batrak, Dmitri Moisseev, and Mona Kurppa
Atmos. Meas. Tech., 15, 3075–3103, https://doi.org/10.5194/amt-15-3075-2022, https://doi.org/10.5194/amt-15-3075-2022, 2022
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We investigate the boundary-layer (BL) height and surface stability in southern Finland using radiosondes, a microwave radiometer and ERA5 reanalysis. Accurately quantifying the BL height is challenging, and the diagnosed BL height can depend strongly on the method used. Microwave radiometers provide reliable estimates of the BL height but only in unstable conditions. ERA5 captures the BL height well except under very stable conditions, which occur most commonly at night during the warm season.
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.
Petri Kiuru, Marjo Palviainen, Tiia Grönholm, Maarit Raivonen, Lukas Kohl, Vincent Gauci, Iñaki Urzainki, and Annamari Laurén
Biogeosciences, 19, 1959–1977, https://doi.org/10.5194/bg-19-1959-2022, https://doi.org/10.5194/bg-19-1959-2022, 2022
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Peatlands are large sources of methane (CH4), and peat structure controls CH4 production and emissions. We used X-ray microtomography imaging, complex network theory methods, and pore network modeling to describe the properties of peat macropore networks and the role of macropores in CH4-related processes. We show that conditions for gas transport and CH4 production vary with depth and are affected by hysteresis, which may explain the hotspots and episodic spikes in peatland CH4 emissions.
Andrea Pozzer, Simon F. Reifenberg, Vinod Kumar, Bruno Franco, Matthias Kohl, Domenico Taraborrelli, Sergey Gromov, Sebastian Ehrhart, Patrick Jöckel, Rolf Sander, Veronica Fall, Simon Rosanka, Vlassis Karydis, Dimitris Akritidis, Tamara Emmerichs, Monica Crippa, Diego Guizzardi, Johannes W. Kaiser, Lieven Clarisse, Astrid Kiendler-Scharr, Holger Tost, and Alexandra Tsimpidi
Geosci. Model Dev., 15, 2673–2710, https://doi.org/10.5194/gmd-15-2673-2022, https://doi.org/10.5194/gmd-15-2673-2022, 2022
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A newly developed setup of the chemistry general circulation model EMAC (ECHAM5/MESSy for Atmospheric Chemistry) is evaluated here. A comprehensive organic degradation mechanism is used and coupled with a volatility base model.
The results show that the model reproduces most of the tracers and aerosols satisfactorily but shows discrepancies for oxygenated organic gases. It is also shown that this model configuration can be used for further research in atmospheric chemistry.
Miska Olin, David Patoulias, Heino Kuuluvainen, Jarkko V. Niemi, Topi Rönkkö, Spyros N. Pandis, Ilona Riipinen, and Miikka Dal Maso
Atmos. Chem. Phys., 22, 1131–1148, https://doi.org/10.5194/acp-22-1131-2022, https://doi.org/10.5194/acp-22-1131-2022, 2022
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An emission factor particle size distribution was determined from the measurements at an urban traffic site. It was used in updating a pre-existing emission inventory, and regional modeling was performed after the update. Emission inventories typically underestimate nanoparticle emissions due to challenges in determining them with high certainty. This update reveals that the simulated aerosol levels have previously been underestimated especially for urban areas and for sub-50 nm particles.
Philipp G. Eger, Luc Vereecken, Rolf Sander, Jan Schuladen, Nicolas Sobanski, Horst Fischer, Einar Karu, Jonathan Williams, Ville Vakkari, Tuukka Petäjä, Jos Lelieveld, Andrea Pozzer, and John N. Crowley
Atmos. Chem. Phys., 21, 14333–14349, https://doi.org/10.5194/acp-21-14333-2021, https://doi.org/10.5194/acp-21-14333-2021, 2021
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We determine the impact of pyruvic acid photolysis on the formation of acetaldehyde and peroxy radicals during summer and autumn in the Finnish boreal forest using a data-constrained box model. Our results are dependent on the chosen scenario in which the overall quantum yield and the photolysis products are varied. We highlight that pyruvic acid photolysis can be an important contributor to acetaldehyde and peroxy radical formation in remote, forested regions.
Magdalena Okuljar, Heino Kuuluvainen, Jenni Kontkanen, Olga Garmash, Miska Olin, Jarkko V. Niemi, Hilkka Timonen, Juha Kangasluoma, Yee Jun Tham, Rima Baalbaki, Mikko Sipilä, Laura Salo, Henna Lintusaari, Harri Portin, Kimmo Teinilä, Minna Aurela, Miikka Dal Maso, Topi Rönkkö, Tuukka Petäjä, and Pauli Paasonen
Atmos. Chem. Phys., 21, 9931–9953, https://doi.org/10.5194/acp-21-9931-2021, https://doi.org/10.5194/acp-21-9931-2021, 2021
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To estimate the relative contribution of different sources to the particle population in an urban environment, we conducted simultaneous measurements at a street canyon and an urban background station in Helsinki. We investigated the contribution of traffic and new particle formation to particles with a diameter between 1 and 800 nm. We found that during spring traffic does not dominate the particles smaller than 3 nm at either of the stations.
Simon Rosanka, Rolf Sander, Andreas Wahner, and Domenico Taraborrelli
Geosci. Model Dev., 14, 4103–4115, https://doi.org/10.5194/gmd-14-4103-2021, https://doi.org/10.5194/gmd-14-4103-2021, 2021
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The Jülich Aqueous-phase Mechanism of Organic Chemistry (JAMOC) is developed and implemented into the Module Efficiently Calculating the Chemistry of the Atmosphere (MECCA). JAMOC is an explicit in-cloud oxidation scheme for oxygenated volatile organic compounds (OVOCs), which is suitable for global model applications. Within a box-model study, we show that JAMOC yields reduced gas-phase concentrations of most OVOCs and oxidants, except for nitrogen oxides.
Simon Rosanka, Rolf Sander, Bruno Franco, Catherine Wespes, Andreas Wahner, and Domenico Taraborrelli
Atmos. Chem. Phys., 21, 9909–9930, https://doi.org/10.5194/acp-21-9909-2021, https://doi.org/10.5194/acp-21-9909-2021, 2021
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In-cloud destruction of ozone depends on hydroperoxyl radicals in cloud droplets, where they are produced by oxygenated volatile organic compound (OVOC) oxygenation. Only rudimentary representations of these processes, if any, are currently available in global atmospheric models. By using a comprehensive atmospheric model that includes a complex in-cloud OVOC oxidation scheme, we show that atmospheric oxidants are reduced and models ignoring this process will underpredict clouds as ozone sinks.
Langwen Huang and David Topping
Geosci. Model Dev., 14, 2187–2203, https://doi.org/10.5194/gmd-14-2187-2021, https://doi.org/10.5194/gmd-14-2187-2021, 2021
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As our knowledge and understanding of atmospheric aerosol particle evolution and impact grows, designing community mechanistic models requires an ability to capture increasing chemical, physical and therefore numerical complexity. As the landscape of computing software and hardware evolves, it is important to profile the usefulness of emerging platforms in tackling this complexity. With this in mind we present JlBox v1.1, written in Julia.
Luis M. F. Barreira, Aku Helin, Minna Aurela, Kimmo Teinilä, Milla Friman, Leena Kangas, Jarkko V. Niemi, Harri Portin, Anu Kousa, Liisa Pirjola, Topi Rönkkö, Sanna Saarikoski, and Hilkka Timonen
Atmos. Chem. Phys., 21, 6297–6314, https://doi.org/10.5194/acp-21-6297-2021, https://doi.org/10.5194/acp-21-6297-2021, 2021
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We present results from the long-term measurements (5 years) of highly time-resolved atmospheric PM1 composition at an urban street canyon site. Overall, the results increased knowledge of the variability of PM1 concentration, composition, and sources in a traffic site and the implications for urban air quality. The investigation of pollution episodes showed that both local and long-range-transported pollutants can still cause elevated PM1 and PM2.5 concentrations in northern Europe.
Julian Rüdiger, Alexandra Gutmann, Nicole Bobrowski, Marcello Liotta, J. Maarten de Moor, Rolf Sander, Florian Dinger, Jan-Lukas Tirpitz, Martha Ibarra, Armando Saballos, María Martínez, Elvis Mendoza, Arnoldo Ferrufino, John Stix, Juan Valdés, Jonathan M. Castro, and Thorsten Hoffmann
Atmos. Chem. Phys., 21, 3371–3393, https://doi.org/10.5194/acp-21-3371-2021, https://doi.org/10.5194/acp-21-3371-2021, 2021
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We present an innovative approach to study halogen chemistry in the plume of Masaya volcano in Nicaragua. An unique data set was collected using multiple techniques, including drones. These data enabled us to determine the fraction of activation of the respective halogens at various plume ages, where in-mixing of ambient air causes chemical reactions. An atmospheric chemistry box model was employed to further examine the field results and help our understanding of volcanic plume chemistry.
Domenico Taraborrelli, David Cabrera-Perez, Sara Bacer, Sergey Gromov, Jos Lelieveld, Rolf Sander, and Andrea Pozzer
Atmos. Chem. Phys., 21, 2615–2636, https://doi.org/10.5194/acp-21-2615-2021, https://doi.org/10.5194/acp-21-2615-2021, 2021
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Atmospheric pollutants from anthropogenic activities and biomass burning are usually regarded as ozone precursors. Monocyclic aromatics are no exception. Calculations with a comprehensive atmospheric model are consistent with this view but only for air masses close to pollution source regions. However, the same model predicts that aromatics, when transported to remote areas, may effectively destroy ozone. This loss of tropospheric ozone rivals the one attributed to bromine.
Simon Patrick O'Meara, Shuxuan Xu, David Topping, M. Rami Alfarra, Gerard Capes, Douglas Lowe, Yunqi Shao, and Gordon McFiggans
Geosci. Model Dev., 14, 675–702, https://doi.org/10.5194/gmd-14-675-2021, https://doi.org/10.5194/gmd-14-675-2021, 2021
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User-friendly and open-source software for simulating aerosol chambers is a valuable tool for research scientists in designing and analysing their experiments. This paper describes a new version of such software and will therefore provide a useful reference for those applying it. Central to the paper is an assessment of the software's accuracy through comparison against previously published simulations.
Krista Luoma, Jarkko V. Niemi, Minna Aurela, Pak Lun Fung, Aku Helin, Tareq Hussein, Leena Kangas, Anu Kousa, Topi Rönkkö, Hilkka Timonen, Aki Virkkula, and Tuukka Petäjä
Atmos. Chem. Phys., 21, 1173–1189, https://doi.org/10.5194/acp-21-1173-2021, https://doi.org/10.5194/acp-21-1173-2021, 2021
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This study combined black carbon measurements from 15 Finnish sites that represented different environments (traffic, detached housing area, urban background, and regional background). The seasonal and diurnal variations in the black carbon concentration were associated with local emissions from traffic and residential wood burning. The study observed decreasing trends in the black carbon concentration and associated them with decreases in traffic emissions.
Douglas Morrison, Ian Crawford, Nicholas Marsden, Michael Flynn, Katie Read, Luis Neves, Virginia Foot, Paul Kaye, Warren Stanley, Hugh Coe, David Topping, and Martin Gallagher
Atmos. Chem. Phys., 20, 14473–14490, https://doi.org/10.5194/acp-20-14473-2020, https://doi.org/10.5194/acp-20-14473-2020, 2020
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We provide conservative estimates of the concentrations of bacteria within transatlantic dust clouds, originating from the African continent. We observe significant seasonal differences in the overall concentrations of particles but no seasonal variation in the ratio between bacteria and dust. With bacteria contributing to ice formation at warmer temperatures than dust, our observations should improve the accuracy of climate models.
David Topping, David Watts, Hugh Coe, James Evans, Thomas J. Bannan, Douglas Lowe, Caroline Jay, and Jonathan W. Taylor
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-270, https://doi.org/10.5194/gmd-2020-270, 2020
Publication in GMD not foreseen
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Time-series forecasting methods have often been used to mitigate some of the challenges associated with deploying chemical transport models. In this study we deploy and evaluate Facebook’s Prophetmodel v0.6 in predicting hourly concentrations of Nitrogen Dioxide [NO2]. et. Overall we find the Prophet model offers a relatively effective and simple way to make predictions about NO2 at local levels.
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
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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.
Petroc D. Shelley, Thomas J. Bannan, Stephen D. Worrall, M. Rami Alfarra, Ulrich K. Krieger, Carl J. Percival, Arthur Garforth, and David Topping
Atmos. Chem. Phys., 20, 8293–8314, https://doi.org/10.5194/acp-20-8293-2020, https://doi.org/10.5194/acp-20-8293-2020, 2020
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The methods used to estimate the vapour pressures of compounds in the atmosphere typically perform poorly when applied to organic compounds found in the atmosphere. New measurements have been made and compared to previous experimental data and estimated values so that the limitations within the estimation methods can be identified and in the future be rectified.
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 %).
Natalie R. Gervasi, David O. Topping, and Andreas Zuend
Atmos. Chem. Phys., 20, 2987–3008, https://doi.org/10.5194/acp-20-2987-2020, https://doi.org/10.5194/acp-20-2987-2020, 2020
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Organic aerosols have been shown to exist often in a semi-solid or amorphous, glassy state. Highly viscous particles behave differently than their well-mixed liquid analogues with consequences for a variety of aerosol processes. Here, we introduce a new predictive mixture viscosity model called AIOMFAC-VISC. It enables us to predict the viscosity of aqueous organic mixtures as a function of temperature and chemical composition, covering the full range of liquid, semi-solid, and glassy states.
Parya Broomandi, Xueyu Geng, Weisi Guo, Jong Ryeol Kim, Alessio Pagani, and David Topping
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-342, https://doi.org/10.5194/gmd-2019-342, 2020
Revised manuscript not accepted
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As a result of our novel graph-based reduced modeling, we are able to represent high-dimensional knowledge into a causal inference and stability framework.
Kathryn Fowler, Paul Connolly, and David Topping
Atmos. Chem. Phys., 20, 683–698, https://doi.org/10.5194/acp-20-683-2020, https://doi.org/10.5194/acp-20-683-2020, 2020
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Observations of low–temperature cirrus clouds have found unexpectedly low ice crystal numbers and high supersaturations, suggesting an incomplete understanding of the freezing mechanisms under these conditions. The existence of viscous organic aerosol has offered alternative ice nucleation pathways, which have been observed in laboratory studies. We have developed the first cloud parcel model to investigate the effect of viscosity on ice nucleation.
Miska Olin, Heino Kuuluvainen, Minna Aurela, Joni Kalliokoski, Niina Kuittinen, Mia Isotalo, Hilkka J. Timonen, Jarkko V. Niemi, Topi Rönkkö, and Miikka Dal Maso
Atmos. Chem. Phys., 20, 1–13, https://doi.org/10.5194/acp-20-1-2020, https://doi.org/10.5194/acp-20-1-2020, 2020
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Photochemically formed sulfuric acid is generally considered the main source for new particle formation in the atmosphere. Contrary to current understanding, our measurements of nanoclusters and gaseous sulfuric acid performed in an urban area imply that traffic contributes to sulfuric acid concentration and that even for the smallest particles, the traffic-emitted fraction mostly exceeds the photochemistry-driven regional new particle formation.
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.
Miska Olin, Jenni Alanen, Marja R. T. Palmroth, Topi Rönkkö, and Miikka Dal Maso
Atmos. Chem. Phys., 19, 6367–6388, https://doi.org/10.5194/acp-19-6367-2019, https://doi.org/10.5194/acp-19-6367-2019, 2019
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The mechanism for new particle formation (NPF) in vehicle exhaust is currently unknown. This study focuses on determining the NPF rate in vehicle exhaust caused by sulfuric acid, which is the most promising candidate involved in the NPF process. The NPF rate function obtained in this study helps in examining the NPF mechanism in exhaust plumes, and it can also be used to improve air quality models. The results also imply that the NPF process cannot be fully explained by sulfuric acid only.
Rolf Sander, Andreas Baumgaertner, David Cabrera-Perez, Franziska Frank, Sergey Gromov, Jens-Uwe Grooß, Hartwig Harder, Vincent Huijnen, Patrick Jöckel, Vlassis A. Karydis, Kyle E. Niemeyer, Andrea Pozzer, Hella Riede, Martin G. Schultz, Domenico Taraborrelli, and Sebastian Tauer
Geosci. Model Dev., 12, 1365–1385, https://doi.org/10.5194/gmd-12-1365-2019, https://doi.org/10.5194/gmd-12-1365-2019, 2019
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We present the atmospheric chemistry box model CAABA/MECCA which
now includes a number of new features: skeletal mechanism
reduction, the MOM chemical mechanism for volatile organic
compounds, an option to include reactions from the Master
Chemical Mechanism (MCM) and other chemical mechanisms, updated
isotope tagging, improved and new photolysis modules, and the new
feature of coexisting multiple chemistry mechanisms.
CAABA/MECCA is a community model published under the GPL.
Thomas J. Bannan, Michael Le Breton, Michael Priestley, Stephen D. Worrall, Asan Bacak, Nicholas A. Marsden, Archit Mehra, Julia Hammes, Mattias Hallquist, M. Rami Alfarra, Ulrich K. Krieger, Jonathan P. Reid, John Jayne, Wade Robinson, Gordon McFiggans, Hugh Coe, Carl J. Percival, and Dave Topping
Atmos. Meas. Tech., 12, 1429–1439, https://doi.org/10.5194/amt-12-1429-2019, https://doi.org/10.5194/amt-12-1429-2019, 2019
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The Filter Inlet for Gases and AEROsols (FIGAERO) is an inlet designed to be coupled with a high-resolution time-of-flight chemical ionization mass spectrometer (HR-ToF-CIMS) and provides simultaneous molecular information relating to both the gas- and particle-phase samples. This method has been used to extract vapour pressures of compounds whilst giving quantitative concentrations in the particle phase. Here we detail an ideal set of benchmark compounds for characterization of the FIGAERO.
Elizabeth Forde, Martin Gallagher, Virginia Foot, Roland Sarda-Esteve, Ian Crawford, Paul Kaye, Warren Stanley, and David Topping
Atmos. Chem. Phys., 19, 1665–1684, https://doi.org/10.5194/acp-19-1665-2019, https://doi.org/10.5194/acp-19-1665-2019, 2019
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The abundance and diversity of airborne biological particles in different environments remains poorly constrained. Measurements of such particles were conducted at four sites in the United Kingdom, using real-time fluorescence instrumentation. Using local land cover types, sources of suspected particle types were identified and compared. Most sites exhibited a wet-discharged fungal spore dominance, with the exception of one site, which was inferred to be influenced by a local dairy farm.
Simon Ruske, David O. Topping, Virginia E. Foot, Andrew P. Morse, and Martin W. Gallagher
Atmos. Meas. Tech., 11, 6203–6230, https://doi.org/10.5194/amt-11-6203-2018, https://doi.org/10.5194/amt-11-6203-2018, 2018
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Pollen, bacteria and fungal spores are common in the environment, can have very important implications for public health and may influence the weather. Biological sensors potentially could be used to monitor quantities of these types of particles. However, it is important to transform the measurements from these instruments into counts of these biological particles. The paper tests a variety of approaches for achieving this aim on data collected in a laboratory.
Dawei Hu, David Topping, and Gordon McFiggans
Atmos. Chem. Phys., 18, 14925–14937, https://doi.org/10.5194/acp-18-14925-2018, https://doi.org/10.5194/acp-18-14925-2018, 2018
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Co-condensation of inorganic or organic vapours on growing droplets could significantly enhance both CCN and cloud droplet number concentration, thereby influencing climate. Until now, there has been very few direct observational evidence of this process. We exposed involatile inorganic particles to a moist atmosphere containing a controlled amount of an organic semi-volatile vapour. We measured a much greater growth of the particles than if they had only been exposed to water vapour.
Zacharias Marinou Nikolaou, Jyh-Yuan Chen, Yiannis Proestos, Jos Lelieveld, and Rolf Sander
Geosci. Model Dev., 11, 3391–3407, https://doi.org/10.5194/gmd-11-3391-2018, https://doi.org/10.5194/gmd-11-3391-2018, 2018
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Chemistry is an important component of the atmosphere that describes many important physical processes. However, atmospheric chemical mechanisms include hundreds of species and reactions, posing a significant computational load. In this work, we use a powerful reduction method in order to develop a computationally faster chemical mechanism from a detailed mechanism. This enables accelerated simulations, which can be used to examine a wider range of processes in increased detail.
Chinmay Mallik, Laura Tomsche, Efstratios Bourtsoukidis, John N. Crowley, Bettina Derstroff, Horst Fischer, Sascha Hafermann, Imke Hüser, Umar Javed, Stephan Keßel, Jos Lelieveld, Monica Martinez, Hannah Meusel, Anna Novelli, Gavin J. Phillips, Andrea Pozzer, Andreas Reiffs, Rolf Sander, Domenico Taraborrelli, Carina Sauvage, Jan Schuladen, Hang Su, Jonathan Williams, and Hartwig Harder
Atmos. Chem. Phys., 18, 10825–10847, https://doi.org/10.5194/acp-18-10825-2018, https://doi.org/10.5194/acp-18-10825-2018, 2018
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OH and HO2 control the transformation of air pollutants and O3 formation. Their implication for air quality over the climatically sensitive Mediterranean region was studied during a field campaign in Cyprus. Production of OH, HO2, and recycled OH was lower in aged marine air masses. Box model simulations of OH and HO2 agreed with measurements except at high terpene concentrations when model RO2 due to terpenes caused large HO2 loss. Autoxidation schemes for RO2 improved the agreement.
Michael Le Breton, Yujue Wang, Åsa M. Hallquist, Ravi Kant Pathak, Jing Zheng, Yudong Yang, Dongjie Shang, Marianne Glasius, Thomas J. Bannan, Qianyun Liu, Chak K. Chan, Carl J. Percival, Wenfei Zhu, Shengrong Lou, David Topping, Yuchen Wang, Jianzhen Yu, Keding Lu, Song Guo, Min Hu, and Mattias Hallquist
Atmos. Chem. Phys., 18, 10355–10371, https://doi.org/10.5194/acp-18-10355-2018, https://doi.org/10.5194/acp-18-10355-2018, 2018
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This paper utilizes a chemical ionisation mass spectrometer measuring gas and particle-phase organosulfates (OS) simultaneously during a field campaign in Beijing, China, and highlights how high time frequency online measurements enable a detailed analysis of dominant production mechanisms. We find that high aerosol acidity, organic precursor concentration and relative humidity promote the production of OS. The thermogram desorption reveals the potential for semi-volatile gas-phase OS.
Barbara Altstädter, Andreas Platis, Michael Jähn, Holger Baars, Janine Lückerath, Andreas Held, Astrid Lampert, Jens Bange, Markus Hermann, and Birgit Wehner
Atmos. Chem. Phys., 18, 8249–8264, https://doi.org/10.5194/acp-18-8249-2018, https://doi.org/10.5194/acp-18-8249-2018, 2018
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This article describes the appearance of ultrafine aerosol particles (size < 12 nm) within the atmospheric boundary layer under cloudy conditions. New particle formation (NPF) was observed with the ALADINA unmanned aerial system in relation to increased turbulence near the inversion layer. Fast mixing processes and rapid dilution of surrounding air led to an insufficient particle growth rate, seen in sporadic clusters at ground. These events might not have been classified as NPF by surface data.
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
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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.
Stefano Decesari, Simona Kovarich, Manuela Pavan, Arianna Bassan, Andrea Ciacci, and David Topping
Atmos. Chem. Phys., 18, 2329–2340, https://doi.org/10.5194/acp-18-2329-2018, https://doi.org/10.5194/acp-18-2329-2018, 2018
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Particulate matter (PM) chemical composition includes thousands of individual organic compounds that have never been tested for their toxicological potential. Computational (in silico) screenings represent a promising approach to identify new target compounds for more in-depth toxicological analyses. We provide here a proof-of-concept evaluation based on ca. 100 aerosol organic compounds. Reliable toxicological predictions were obtained for more than 80 % of them.
Kathryn Fowler, Paul J. Connolly, David O. Topping, and Simon O'Meara
Atmos. Chem. Phys., 18, 1629–1642, https://doi.org/10.5194/acp-18-1629-2018, https://doi.org/10.5194/acp-18-1629-2018, 2018
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This is the first time the Maxwell–Stefan framework has been applied to an atmospheric aerosol core–shell model and shows that there is a complex interplay between the viscous and solubility effects on aerosol composition. Understanding aerosol composition is essential to accurately model their interactions within atmospheric systems. We use simple binary systems to demonstrate how viscosity and solubility both play a role in affecting the rate of diffusion through aerosol particles.
Ulrich K. Krieger, Franziska Siegrist, Claudia Marcolli, Eva U. Emanuelsson, Freya M. Gøbel, Merete Bilde, Aleksandra Marsh, Jonathan P. Reid, Andrew J. Huisman, Ilona Riipinen, Noora Hyttinen, Nanna Myllys, Theo Kurtén, Thomas Bannan, Carl J. Percival, and David Topping
Atmos. Meas. Tech., 11, 49–63, https://doi.org/10.5194/amt-11-49-2018, https://doi.org/10.5194/amt-11-49-2018, 2018
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Vapor pressures of low-volatility organic molecules at atmospheric temperatures reported in the literature often differ by several orders of magnitude between measurement techniques. These discrepancies exceed the stated uncertainty of each technique, which is generally reported to be smaller than a factor of 2. We determined saturation vapor pressures for the homologous series of polyethylene glycols ranging in vapor pressure at 298 K from 1E−7 Pa to 5E−2 Pa as a reference set.
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
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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.
Simon O'Meara, David O. Topping, Rahul A. Zaveri, and Gordon McFiggans
Atmos. Chem. Phys., 17, 10477–10494, https://doi.org/10.5194/acp-17-10477-2017, https://doi.org/10.5194/acp-17-10477-2017, 2017
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To simulate particle-phase diffusion, an analytical expression is desired because it takes less calculation time than a differential equation. Here a correction is found for the analytical solution for when diffusivity is dependent on composition, thereby making it more widely applicable than before. Consequently, we are able to more realistically evaluate the rate limitation (if any) imposed by particle-phase diffusion on component partitioning between the gas and particle phase.
Bettina Derstroff, Imke Hüser, Efstratios Bourtsoukidis, John N. Crowley, Horst Fischer, Sergey Gromov, Hartwig Harder, Ruud H. H. Janssen, Jürgen Kesselmeier, Jos Lelieveld, Chinmay Mallik, Monica Martinez, Anna Novelli, Uwe Parchatka, Gavin J. Phillips, Rolf Sander, Carina Sauvage, Jan Schuladen, Christof Stönner, Laura Tomsche, and Jonathan Williams
Atmos. Chem. Phys., 17, 9547–9566, https://doi.org/10.5194/acp-17-9547-2017, https://doi.org/10.5194/acp-17-9547-2017, 2017
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The aim of the study was to examine aged air masses being transported from the European continent towards Cyprus. Longer-lived oxygenated volatile organic compounds (OVOCs) such as methanol were mainly impacted by long-distance transport and showed higher values in air masses from eastern Europe than in a flow regime from the west. The impact of the transport through the marine boundary layer as well as the influence of the residual layer/free troposphere on OVOCs were studied.
Stephan Keßel, David Cabrera-Perez, Abraham Horowitz, Patrick R. Veres, Rolf Sander, Domenico Taraborrelli, Maria Tucceri, John N. Crowley, Andrea Pozzer, Christof Stönner, Luc Vereecken, Jos Lelieveld, and Jonathan Williams
Atmos. Chem. Phys., 17, 8789–8804, https://doi.org/10.5194/acp-17-8789-2017, https://doi.org/10.5194/acp-17-8789-2017, 2017
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In this study we identify an often overlooked stable oxide of carbon, namely carbon suboxide (C3O2), in ambient air. We have made C3O2 and in the laboratory determined its absorption cross section data and the rate of reaction with two important atmospheric oxidants, OH and O3. By incorporating known sources and sinks in a global model we have generated a first global picture of the distribution of this species in the atmosphere.
David O. Topping, James Allan, M. Rami Alfarra, and Bernard Aumont
Geosci. Model Dev., 10, 2365–2377, https://doi.org/10.5194/gmd-10-2365-2017, https://doi.org/10.5194/gmd-10-2365-2017, 2017
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Our ability to model the chemical and thermodynamic processes that lead to secondary organic aerosol (SOA) formation is thought to be hampered by the complexity of the system. In this proof of concept study, the ability to train supervised methods to predict electron impact ionisation (EI) mass spectra for the AMS is evaluated to facilitate improved model evaluation. The study demonstrates the use of a methodology that would be improved with more training data and data from simple mixed systems.
Hilkka Timonen, Panu Karjalainen, Erkka Saukko, Sanna Saarikoski, Päivi Aakko-Saksa, Pauli Simonen, Timo Murtonen, Miikka Dal Maso, Heino Kuuluvainen, Matthew Bloss, Erik Ahlberg, Birgitta Svenningsson, Joakim Pagels, William H. Brune, Jorma Keskinen, Douglas R. Worsnop, Risto Hillamo, and Topi Rönkkö
Atmos. Chem. Phys., 17, 5311–5329, https://doi.org/10.5194/acp-17-5311-2017, https://doi.org/10.5194/acp-17-5311-2017, 2017
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The effect of fuel ethanol content (10–100 %) on primary emissions and the subsequent secondary aerosol formation was investigated for a Euro 5 flex-fuel gasoline vehicle. The emissions were characterized during the New European Driving Cycle (NEDC) using high time-resolution instruments. The chemical composition of the exhaust particulate matter was studied using a soot particle aerosol mass spectrometer (SP-AMS), and the secondary aerosol formation was studied with an oxidation chamber.
Pauli Simonen, Erkka Saukko, Panu Karjalainen, Hilkka Timonen, Matthew Bloss, Päivi Aakko-Saksa, Topi Rönkkö, Jorma Keskinen, and Miikka Dal Maso
Atmos. Meas. Tech., 10, 1519–1537, https://doi.org/10.5194/amt-10-1519-2017, https://doi.org/10.5194/amt-10-1519-2017, 2017
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Atmospheric particles affect climate, health and visibility, and a large source of these particles is secondary aerosol formation. We developed a new oxidation flow reactor for studying the secondary aerosol formation potential of rapidly changing emission sources. Using laboratory measurements, we show that this flow reactor is suitable for studying the secondary aerosol potential of, for example, light duty vehicle emissions during a transient driving cycle.
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
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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.
Simon Ruske, David O. Topping, Virginia E. Foot, Paul H. Kaye, Warren R. Stanley, Ian Crawford, Andrew P. Morse, and Martin W. Gallagher
Atmos. Meas. Tech., 10, 695–708, https://doi.org/10.5194/amt-10-695-2017, https://doi.org/10.5194/amt-10-695-2017, 2017
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Particles such as bacteria, pollen and fungal spores have important implications within the environment and public health sectors. Here we evaluate the performance of various different methods for distinguishing between these different types of particles using a new instrument. We demonstrate that there may be better alternatives to the currently used methods which can be further investigated in future research.
Martin Brüggemann, Laurent Poulain, Andreas Held, Torsten Stelzer, Christoph Zuth, Stefanie Richters, Anke Mutzel, Dominik van Pinxteren, Yoshiteru Iinuma, Sarmite Katkevica, René Rabe, Hartmut Herrmann, and Thorsten Hoffmann
Atmos. Chem. Phys., 17, 1453–1469, https://doi.org/10.5194/acp-17-1453-2017, https://doi.org/10.5194/acp-17-1453-2017, 2017
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Using complementary mass spectrometric techniques during a field study in central Europe, characteristic contributors to the organic aerosol mass were identified. Besides common marker compounds for biogenic secondary organic aerosol, highly oxidized sulfur species were detected in the particle phase. High-time-resolution measurements revealed correlations between these organosulfates and particulate sulfate as well as gas-phase peroxyradicals, giving hints to underlying formation mechanisms.
Laura Riuttanen, Marja Bister, Veli-Matti Kerminen, Viju O. John, Anu-Maija Sundström, Miikka Dal Maso, Jouni Räisänen, Victoria A. Sinclair, Risto Makkonen, Filippo Xausa, Gerrit de Leeuw, and Markku Kulmala
Atmos. Chem. Phys., 16, 14331–14342, https://doi.org/10.5194/acp-16-14331-2016, https://doi.org/10.5194/acp-16-14331-2016, 2016
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Here we show observational evidence that aerosols increase upper tropospheric humidity (UTH) via changes in the microphysics of deep convection. Using remote sensing data over the ocean east of China in summer, we show that increased aerosol loads are associated with an UTH increase of 2.2 ± 1.5 in units of relative humidity. We show that humidification of aerosols or other meteorological covariation is very unlikely to be the cause for this result indicating relevance for the global climate.
François Benduhn, Graham W. Mann, Kirsty J. Pringle, David O. Topping, Gordon McFiggans, and Kenneth S. Carslaw
Geosci. Model Dev., 9, 3875–3906, https://doi.org/10.5194/gmd-9-3875-2016, https://doi.org/10.5194/gmd-9-3875-2016, 2016
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We present a new mathematical formalism that serves to represent exchanges of inorganic matter between the atmosphere gas phase and the aerosol aqueous phase. In a global modelling framework, taking into account these processes may help represent many important features more accurately, such as the formation of cloud droplets or the radiative properties of the atmosphere. The formalism strives to keep an appropriate balance between accuracy and computation efficiency requirements.
Matthew Crooks, Paul Connolly, David Topping, and Gordon McFiggans
Geosci. Model Dev., 9, 3617–3637, https://doi.org/10.5194/gmd-9-3617-2016, https://doi.org/10.5194/gmd-9-3617-2016, 2016
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Semi-volatile compounds, like water, can exist in both vapour phases and condensed phases within a system. This paper presents a method of calculating the condensed and vapour phases of semi-volatile compounds at equilibrium, in particular, when the condensed mass occurs within particles of different sizes and chemical composition. The applications of interest to the authors are those of atmospheric importance such as cloud droplet formation and reflection or absorption of solar radiation.
Samuel Lowe, Daniel G. Partridge, David Topping, and Philip Stier
Atmos. Chem. Phys., 16, 10941–10963, https://doi.org/10.5194/acp-16-10941-2016, https://doi.org/10.5194/acp-16-10941-2016, 2016
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A novel inverse modelling framework is developed for analysing the sensitivity of cloud condensation nuclei (CCN) concentrations to simultaneous perturbations in multiple model parameters at atmospherically relevant humidities. Many parameter interactions are identified and CCN concentrations are found to be relatively insensitive to bulk–surface partitioning, while aerosol concentration, surface tension, composition and solution ideality exhibit a higher degree of sensitivity.
Panu Karjalainen, Hilkka Timonen, Erkka Saukko, Heino Kuuluvainen, Sanna Saarikoski, Päivi Aakko-Saksa, Timo Murtonen, Matthew Bloss, Miikka Dal Maso, Pauli Simonen, Erik Ahlberg, Birgitta Svenningsson, William Henry Brune, Risto Hillamo, Jorma Keskinen, and Topi Rönkkö
Atmos. Chem. Phys., 16, 8559–8570, https://doi.org/10.5194/acp-16-8559-2016, https://doi.org/10.5194/acp-16-8559-2016, 2016
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We characterized time-resolved primary particulate emissions and secondary particle formation from a modern gasoline passenger car. In mass terms, the amount of secondary particles was 13 times the amount of primary particles. The highest emissions were observed after a cold start when the engine and catalyst performance were suboptimal. The key parameter for secondary particle formation was the amount of gaseous hydrocarbons in the exhaust.
Fanni Mylläri, Eija Asmi, Tatu Anttila, Erkka Saukko, Ville Vakkari, Liisa Pirjola, Risto Hillamo, Tuomas Laurila, Anna Häyrinen, Jani Rautiainen, Heikki Lihavainen, Ewan O'Connor, Ville Niemelä, Jorma Keskinen, Miikka Dal Maso, and Topi Rönkkö
Atmos. Chem. Phys., 16, 7485–7496, https://doi.org/10.5194/acp-16-7485-2016, https://doi.org/10.5194/acp-16-7485-2016, 2016
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The primary emissions of a coal-fired power plant were highly affected by the flue-gas cleaning technologies. The primary emission results were used as input values for a Gaussian plume model and the model correlated well with the atmospheric measurements from the flue-gas plume. Concentrations of newly formed particles in the flue gas plume were higher than the primary particle concentration, and thus the source of particle-forming precursors should be characterized in more detail.
Miska Olin, Tatu Anttila, and Miikka Dal Maso
Atmos. Chem. Phys., 16, 7067–7090, https://doi.org/10.5194/acp-16-7067-2016, https://doi.org/10.5194/acp-16-7067-2016, 2016
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We introduce a new representation of particle size distribution, in which a power law form is used in addition to the most commonly used log-normal representation. The new representation is beneficial in simulations involving the initial steps of aerosol formation, where power law behaviour is typically seen, instead of less accurate pure log-normal representation or computationally more expensive sectional representation.
David Cabrera-Perez, Domenico Taraborrelli, Rolf Sander, and Andrea Pozzer
Atmos. Chem. Phys., 16, 6931–6947, https://doi.org/10.5194/acp-16-6931-2016, https://doi.org/10.5194/acp-16-6931-2016, 2016
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The global atmospheric budget and distribution of monocyclic aromatic compounds is estimated, using an atmospheric chemistry general circulation model. Simulation results are evaluated with observations with the goal of understanding emission, production and removal of these compounds. Anthropogenic and biomass burning are the main sources of aromatic compounds to the atmosphere. The main sink is photochemical decomposition and in lesser importance dry deposition.
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
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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.
Simon O'Meara, David O. Topping, and Gordon McFiggans
Atmos. Chem. Phys., 16, 5299–5313, https://doi.org/10.5194/acp-16-5299-2016, https://doi.org/10.5194/acp-16-5299-2016, 2016
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To understand the effect of atmospheric particulate matter on climate and human health we need to know how it evolves. We investigate how best to estimate diffusion of components through particles by comparing diffusion times from three approaches to solving Fick's Law and find that they agree. This means that scientists can simulate Fickian diffusion through atmospheric particles using the approach best suited to their requirements and have confidence that their model is mathematically sound.
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.
Patrick Jöckel, Holger Tost, Andrea Pozzer, Markus Kunze, Oliver Kirner, Carl A. M. Brenninkmeijer, Sabine Brinkop, Duy S. Cai, Christoph Dyroff, Johannes Eckstein, Franziska Frank, Hella Garny, Klaus-Dirk Gottschaldt, Phoebe Graf, Volker Grewe, Astrid Kerkweg, Bastian Kern, Sigrun Matthes, Mariano Mertens, Stefanie Meul, Marco Neumaier, Matthias Nützel, Sophie Oberländer-Hayn, Roland Ruhnke, Theresa Runde, Rolf Sander, Dieter Scharffe, and Andreas Zahn
Geosci. Model Dev., 9, 1153–1200, https://doi.org/10.5194/gmd-9-1153-2016, https://doi.org/10.5194/gmd-9-1153-2016, 2016
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With an advanced numerical global chemistry climate model (CCM) we performed several detailed
combined hind-cast and projection simulations of the period 1950 to 2100 to assess the
past, present, and potential future dynamical and chemical state of the Earth atmosphere.
The manuscript documents the model and the various applied model set-ups and provides
a first evaluation of the simulation results from a global perspective as a quality check of the data.
David Topping, Mark Barley, Michael K. Bane, Nicholas Higham, Bernard Aumont, Nicholas Dingle, and Gordon McFiggans
Geosci. Model Dev., 9, 899–914, https://doi.org/10.5194/gmd-9-899-2016, https://doi.org/10.5194/gmd-9-899-2016, 2016
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In this paper we describe the development and application of a new web-based and open-source facility, UManSysProp (http://umansysprop .seaes.manchester.ac.uk), for automating predictions of molecular and atmospheric aerosol properties. Current facilities include pure component vapour pressures, critical properties, and sub-cooled densities of organic molecules; activity coefficient predictions for mixed inorganic-organic liquid systems; hygroscopic growth factors and CCN activation potential.
Shang Sun, Alexander Moravek, Lisa von der Heyden, Andreas Held, Matthias Sörgel, and Jürgen Kesselmeier
Atmos. Meas. Tech., 9, 599–617, https://doi.org/10.5194/amt-9-599-2016, https://doi.org/10.5194/amt-9-599-2016, 2016
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We present a dynamic twin-cuvette system for quantifying the trace gas exchange fluxes between plants and the atmosphere under controlled temperature, light, and humidity conditions. We found out that at a relative humidity of 40 %, the deposition velocity ratio of O3 and PAN was determined to be 0.45. At that humidity, the O3-deposition to the plant leaves was found to be only controlled by leaf stomata. For PAN, an additional resistance inhibited the uptake of PAN by the leaves.
M. Dal Maso, L. Liao, J. Wildt, A. Kiendler-Scharr, E. Kleist, R. Tillmann, M. Sipilä, J. Hakala, K. Lehtipalo, M. Ehn, V.-M. Kerminen, M. Kulmala, D. Worsnop, and T. Mentel
Atmos. Chem. Phys., 16, 1955–1970, https://doi.org/10.5194/acp-16-1955-2016, https://doi.org/10.5194/acp-16-1955-2016, 2016
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In this paper, we present the first direct laboratory observations of nanoparticle formation from sulfuric acid and realistic BVOC precursor vapour mixtures performed at atmospherically relevant concentration levels. We found that the formation rate was proportional to the product of sulphuric acid and biogenic VOC emission strength, and that the formation rates were consistent with a mechanism in which nucleating BVOC oxidation products are rapidly formed and activate with sulfuric acid.
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.
A. J. G. Baumgaertner, P. Jöckel, A. Kerkweg, R. Sander, and H. Tost
Geosci. Model Dev., 9, 125–135, https://doi.org/10.5194/gmd-9-125-2016, https://doi.org/10.5194/gmd-9-125-2016, 2016
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The Community Earth System Model (CESM1) is connected to the the Modular Earth Submodel System (MESSy) as a new base model. This allows MESSy users the option to utilize either the state-of-the art spectral element atmosphere dynamical core or the finite volume core of CESM1. Additionally, this makes several other component models available to MESSy users.
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.
I. Crawford, S. Ruske, D. O. Topping, and M. W. Gallagher
Atmos. Meas. Tech., 8, 4979–4991, https://doi.org/10.5194/amt-8-4979-2015, https://doi.org/10.5194/amt-8-4979-2015, 2015
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HCA analysis methods were evaluated for the purpose of identifying primary biological aerosol sampled with a WIBS. The ward linkage with z-score normalisation could discriminate between five test particles with 98% accuracy. We applied these methods to a previously studied ambient data set, where both methods produced similar results with some minor differences in cluster partitioning. Finally we compared to previous approaches and found our new method offered improved quantification of PBA.
P. Roldin, L. Liao, D. Mogensen, M. Dal Maso, A. Rusanen, V.-M. Kerminen, T. F. Mentel, J. Wildt, E. Kleist, A. Kiendler-Scharr, R. Tillmann, M. Ehn, M. Kulmala, and M. Boy
Atmos. Chem. Phys., 15, 10777–10798, https://doi.org/10.5194/acp-15-10777-2015, https://doi.org/10.5194/acp-15-10777-2015, 2015
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We used the ADCHAM model to study new particle formation events in the JPAC chamber. The model results show that the new particles may be formed by a kinetic type of nucleation involving both sulphuric acid and organic compounds formed from OH oxidation of volatile organic compounds (VOCs). The observed particle growth may either be controlled by the condensation of semi- and low-volatililty organic compounds or by the formation of low-volatility compounds (oligomers) at the particle surface.
L. Pirjola, M. Karl, T. Rönkkö, and F. Arnold
Atmos. Chem. Phys., 15, 10435–10452, https://doi.org/10.5194/acp-15-10435-2015, https://doi.org/10.5194/acp-15-10435-2015, 2015
M. Sörgel, I. Trebs, D. Wu, and A. Held
Atmos. Chem. Phys., 15, 9237–9251, https://doi.org/10.5194/acp-15-9237-2015, https://doi.org/10.5194/acp-15-9237-2015, 2015
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We measured near-surface (< 2m) profiles of HONO in a clearing and on a forest floor. Both HONO deposition and emissions were observed. By comparing three postulated sources to observed daytime emissions, we made several important findings: ● conversion of NO2 is mostly independent of light due to light saturation ● HONO emissions from a very acidic soil were low ● photolysis of adsorbed HNO3 could serve as HONO source based on empirical parameters but unlikely via the proposed reaction pathway.
M. Olin, T. Rönkkö, and M. Dal Maso
Atmos. Chem. Phys., 15, 5305–5323, https://doi.org/10.5194/acp-15-5305-2015, https://doi.org/10.5194/acp-15-5305-2015, 2015
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This article presents a new model that simulates particle formation in vehicle exhaust. The model is used to examine particle dynamics, such as nucleation, inside a diesel exhaust laboratory sampling system. The results suggest lower slope of nucleation rate versus sulfuric acid concentration than previously found.
R. Sander
Atmos. Chem. Phys., 15, 4399–4981, https://doi.org/10.5194/acp-15-4399-2015, https://doi.org/10.5194/acp-15-4399-2015, 2015
D. Plake, M. Sörgel, P. Stella, A. Held, and I. Trebs
Biogeosciences, 12, 945–959, https://doi.org/10.5194/bg-12-945-2015, https://doi.org/10.5194/bg-12-945-2015, 2015
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Grasslands cover vast terrestrial areas and the main biomass is concentrated in the lowest part of the canopy. We found that measured transport times in the lowermost canopy layer are fastest during nighttime. During daytime, the reaction of NO with O3, as well as NO2 uptake by plants, was faster than transport. This suggests that grassland canopies of similar structure may exhibit a strong potential to retain soil emitted NO due to oxidation and subsequent uptake of NO2 by plants.
S. Anand and Y. S. Mayya
Atmos. Chem. Phys., 15, 753–756, https://doi.org/10.5194/acp-15-753-2015, https://doi.org/10.5194/acp-15-753-2015, 2015
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This study examines the parameterized model of Stuart et al. (2013) vis-a-vis a diffusion based model proposed by Anand and Mayya (2011) to estimate the fraction of aerosol particles surviving coagulation in a dispersing plume. Results show that the two models agree with each other within a difference of 10%, and suggest either of the two models might be suitable for incorporation into global-/regional-scale air pollution models.
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
R. Sander, P. Jöckel, O. Kirner, A. T. Kunert, J. Landgraf, and A. Pozzer
Geosci. Model Dev., 7, 2653–2662, https://doi.org/10.5194/gmd-7-2653-2014, https://doi.org/10.5194/gmd-7-2653-2014, 2014
S. G. Gonser, F. Klein, W. Birmili, J. Größ, M. Kulmala, H. E. Manninen, A. Wiedensohler, and A. Held
Atmos. Chem. Phys., 14, 10547–10563, https://doi.org/10.5194/acp-14-10547-2014, https://doi.org/10.5194/acp-14-10547-2014, 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
K. Hens, A. Novelli, M. Martinez, J. Auld, R. Axinte, B. Bohn, H. Fischer, P. Keronen, D. Kubistin, A. C. Nölscher, R. Oswald, P. Paasonen, T. Petäjä, E. Regelin, R. Sander, V. Sinha, M. Sipilä, D. Taraborrelli, C. Tatum Ernest, J. Williams, J. Lelieveld, and H. Harder
Atmos. Chem. Phys., 14, 8723–8747, https://doi.org/10.5194/acp-14-8723-2014, https://doi.org/10.5194/acp-14-8723-2014, 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
E.-M. Kyrö, R. Väänänen, V.-M. Kerminen, A. Virkkula, T. Petäjä, A. Asmi, M. Dal Maso, T. Nieminen, S. Juhola, A. Shcherbinin, I. Riipinen, K. Lehtipalo, P. Keronen, P. P. Aalto, P. Hari, and M. Kulmala
Atmos. Chem. Phys., 14, 4383–4396, https://doi.org/10.5194/acp-14-4383-2014, https://doi.org/10.5194/acp-14-4383-2014, 2014
S. Bleicher, J. C. Buxmann, R. Sander, T. P. Riedel, J. A. Thornton, U. Platt, and C. Zetzsch
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-10135-2014, https://doi.org/10.5194/acpd-14-10135-2014, 2014
Revised manuscript has not been submitted
M. S. Long, W. C. Keene, R. C. Easter, R. Sander, X. Liu, A. Kerkweg, and D. Erickson
Atmos. Chem. Phys., 14, 3397–3425, https://doi.org/10.5194/acp-14-3397-2014, https://doi.org/10.5194/acp-14-3397-2014, 2014
M. Tjernström, C. Leck, C. E. Birch, J. W. Bottenheim, B. J. Brooks, I. M. Brooks, L. Bäcklin, R. Y.-W. Chang, G. de Leeuw, L. Di Liberto, S. de la Rosa, E. Granath, M. Graus, A. Hansel, J. Heintzenberg, A. Held, A. Hind, P. Johnston, J. Knulst, M. Martin, P. A. Matrai, T. Mauritsen, M. Müller, S. J. Norris, M. V. Orellana, D. A. Orsini, J. Paatero, P. O. G. Persson, Q. Gao, C. Rauschenberg, Z. Ristovski, J. Sedlar, M. D. Shupe, B. Sierau, A. Sirevaag, S. Sjogren, O. Stetzer, E. Swietlicki, M. Szczodrak, P. Vaattovaara, N. Wahlberg, M. Westberg, and C. R. Wheeler
Atmos. Chem. Phys., 14, 2823–2869, https://doi.org/10.5194/acp-14-2823-2014, https://doi.org/10.5194/acp-14-2823-2014, 2014
J. A. Adame, M. Martínez, M. Sorribas, P. J. Hidalgo, H. Harder, J.-M. Diesch, F. Drewnick, W. Song, J. Williams, V. Sinha, M. A. Hernández-Ceballos, J. Vilà-Guerau de Arellano, R. Sander, Z. Hosaynali-Beygi, H. Fischer, J. Lelieveld, and B. De la Morena
Atmos. Chem. Phys., 14, 2325–2342, https://doi.org/10.5194/acp-14-2325-2014, https://doi.org/10.5194/acp-14-2325-2014, 2014
N. Niedermeier, A. Held, T. Müller, B. Heinold, K. Schepanski, I. Tegen, K. Kandler, M. Ebert, S. Weinbruch, K. Read, J. Lee, K. W. Fomba, K. Müller, H. Herrmann, and A. Wiedensohler
Atmos. Chem. Phys., 14, 2245–2266, https://doi.org/10.5194/acp-14-2245-2014, https://doi.org/10.5194/acp-14-2245-2014, 2014
P. J. Connolly, D. O. Topping, F. Malavelle, and G. McFiggans
Atmos. Chem. Phys., 14, 2289–2302, https://doi.org/10.5194/acp-14-2289-2014, https://doi.org/10.5194/acp-14-2289-2014, 2014
K. A. Kamilli, L. Poulain, A. Held, A. Nowak, W. Birmili, and A. Wiedensohler
Atmos. Chem. Phys., 14, 737–749, https://doi.org/10.5194/acp-14-737-2014, https://doi.org/10.5194/acp-14-737-2014, 2014
R. Sander, A. A. P. Pszenny, W. C. Keene, E. Crete, B. Deegan, M. S. Long, J. R. Maben, and A. H. Young
Earth Syst. Sci. Data, 5, 385–392, https://doi.org/10.5194/essd-5-385-2013, https://doi.org/10.5194/essd-5-385-2013, 2013
H. Keller-Rudek, G. K. Moortgat, R. Sander, and R. Sörensen
Earth Syst. Sci. Data, 5, 365–373, https://doi.org/10.5194/essd-5-365-2013, https://doi.org/10.5194/essd-5-365-2013, 2013
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
E. Regelin, H. Harder, M. Martinez, D. Kubistin, C. Tatum Ernest, H. Bozem, T. Klippel, Z. Hosaynali-Beygi, H. Fischer, R. Sander, P. Jöckel, R. Königstedt, and J. Lelieveld
Atmos. Chem. Phys., 13, 10703–10720, https://doi.org/10.5194/acp-13-10703-2013, https://doi.org/10.5194/acp-13-10703-2013, 2013
S. G. Gonser and A. Held
Atmos. Meas. Tech., 6, 2339–2348, https://doi.org/10.5194/amt-6-2339-2013, https://doi.org/10.5194/amt-6-2339-2013, 2013
Th. F. Mentel, E. Kleist, S. Andres, M. Dal Maso, T. Hohaus, A. Kiendler-Scharr, Y. Rudich, M. Springer, R. Tillmann, R. Uerlings, A. Wahner, and J. Wildt
Atmos. Chem. Phys., 13, 8755–8770, https://doi.org/10.5194/acp-13-8755-2013, https://doi.org/10.5194/acp-13-8755-2013, 2013
E.-M. Kyrö, V.-M. Kerminen, A. Virkkula, M. Dal Maso, J. Parshintsev, J. Ruíz-Jimenez, L. Forsström, H. E. Manninen, M.-L. Riekkola, P. Heinonen, and M. Kulmala
Atmos. Chem. Phys., 13, 3527–3546, https://doi.org/10.5194/acp-13-3527-2013, https://doi.org/10.5194/acp-13-3527-2013, 2013
M. S. Long, W. C. Keene, R. Easter, R. Sander, A. Kerkweg, D. Erickson, X. Liu, and S. Ghan
Geosci. Model Dev., 6, 255–262, https://doi.org/10.5194/gmd-6-255-2013, https://doi.org/10.5194/gmd-6-255-2013, 2013
N. L. Prisle, N. Ottosson, G. Öhrwall, J. Söderström, M. Dal Maso, and O. Björneholm
Atmos. Chem. Phys., 12, 12227–12242, https://doi.org/10.5194/acp-12-12227-2012, https://doi.org/10.5194/acp-12-12227-2012, 2012
R. Sander and J. Bottenheim
Earth Syst. Sci. Data, 4, 215–282, https://doi.org/10.5194/essd-4-215-2012, https://doi.org/10.5194/essd-4-215-2012, 2012
Related subject area
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A novel method for quantifying the contribution of regional transport to PM2.5 in Beijing (2013–2020): combining machine learning with concentration-weighted trajectory analysis
Quantification of CO2 hotspot emissions from OCO-3 SAM CO2 satellite images using deep learning methods
Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data
Improving winter condition simulations in SURFEX-TEB v9.0 with a multi-layer snow model and ice
UA-ICON with the NWP physics package (version ua-icon-2.1): mean state and variability of the middle atmosphere
Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations
HTAP3 Fires: towards a multi-model, multi-pollutant study of fire impacts
Using a data-driven statistical model to better evaluate surface turbulent heat fluxes in weather and climate numerical models: a demonstration study
Pochva: a new hydro-thermal process model in soil, snow, and vegetation for application in atmosphere numerical models
ClimKern v1.2: a new Python package and kernel repository for calculating radiative feedbacks
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Similarity-based analysis of atmospheric organic compounds for machine learning applications
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Estimation of aerosol and cloud radiative heating rate in the tropical stratosphere using a radiative kernel method
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
A REtrieval Method for optical and physical Aerosol Properties in the stratosphere (REMAPv1)
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
Generalized local fractions – a method for the calculation of sensitivities to emissions from multiple sources for chemically active species, illustrated using the EMEP MSC-W model (rv5.5)
SanDyPALM v1.0: Static and Dynamic Drivers for the PALM-4U Model to Facilitate Realistic Urban Microclimate Simulations
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
Accurate and fast prediction of radioactive pollution by Kriging coupled with Auto-Associative Models
Mitigating Hail Overforecasting in the 2-Moment Milbrandt-Yau Microphysics Scheme (v2.25.2_beta_04) in WRF (v4.5.1) by Incorporating the Graupel Spongy Wet Growth Process (MY2_GSWG v1.0)
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Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Comprehensive evaluation of iAMAS (v1.0) in simulating Antarctic meteorological fields with observations and reanalysis
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
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.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
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The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
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The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Cited articles
Abdul-Razzak, H. and Ghan, S. J.: A parameterization of aerosol activation, 3. Sectional representation, J. Geophys. Res., 107, 4026, https://doi.org/10.1029/2001JD000483, 2002. a
Adams, P. J. and Seinfeld, J. H.: Predicting global aerosol size distributions in general circulation models, J. Geophys. Res., 107, 4370, https://doi.org/10.1029/2001JD001010, 2002. a
Alam, M. K.: The effect of van der Waals and viscous forces on aerosol coagulation, Aerosol Sci. Technol., 6, 41–52, https://doi.org/10.1080/02786828708959118, 1987. a
Alanen, J., Saukko, E., Lehtoranta, K., Murtonen, T., Timonen, H., Hillamo, R., Karjalainen, P., Kuuluvainen, H., Harra, J., Keskinen, J., and Rönkkö, T.: The formation and physical properties of the particle emissions from a natural gas engine, Fuel, 162, 155–161, https://doi.org/10.1016/j.fuel.2015.09.003, 2015. a, b
Anand, S. and Mayya, Y. S.: Coagulation in a diffusing Gaussian aerosol puff: Comparison of analytical approximations with numerical solutions, J.
Aerosol Sci., 40, 348–361, https://doi.org/10.1016/j.jaerosci.2008.12.004, 2009. a
Anand, S. and Mayya, Y. S.: Comment on “Reduced efficacy of marine cloud brightening geoengineering due to in-plume aerosol coagulation: parameterization and global implications” by Stuart et al. (2013), Atmos. Chem. Phys., 15, 753–756, https://doi.org/10.5194/acp-15-753-2015, 2015. a, b, c
Anand, S., Mayya, Y. S., Yu, M., Seipenbusch, M., and Kasper, G.: A numerical study of coagulation of nanoparticle aerosols injected continuously into a large, well stirred chamber, J. Aerosol Sci., 52, 18–32, https://doi.org/10.1016/j.jaerosci.2012.04.010, 2012. a, b
Andersson, C., Bergström, R., Bennet, C., Robertson, L., Thomas, M., Korhonen, H., Lehtinen, K. E. J., and Kokkola, H.: MATCH-SALSA – Multi-scale Atmospheric Transport and CHemistry model coupled to the SALSA aerosol microphysics model– Part 1: Model description and evaluation, Geosci. Model Dev., 8, 171–189, https://doi.org/10.5194/gmd-8-171-2015, 2015. a
Andreae, M. O. and Rosenfeld, D.: Aerosol-cloud-precipitation interactions. Part 1. The nature and sources of cloud-active aerosols, Earth Sci. Rev., 89, 13–41, https://doi.org/10.1016/j.earscirev.2008.03.001, 2008. a
Bakand, S., Hayes, A., and Dechsakulthorn, F.: Nanoparticles: a review of particle toxicology following inhalation exposure, Inhal. Toxicol., 24, 125–135, https://doi.org/10.3109/08958378.2010.642021, 2012. a
Baranizadeh, E., Murphy, B. N., Julin, J., Falahat, S., Reddington, C. L., Arola, A., Ahlm, L., Mikkonen, S., Fountoukis, C., Patoulias, D., Minikin, A., Hamburger, T., Laaksonen, A., Pandis, S. N., Vehkamäki, H., Lehtinen, K. E. J., and Riipinen, I.: Implementation of state-of-the-art ternary new-particle formation scheme to the regional chemical transport model PMCAMx-UF in Europe, Geosci. Model Dev., 9, 2741–2754, https://doi.org/10.5194/gmd-9-2741-2016, 2016. a, b
Bergman, T., Kerminen, V.-M., Korhonen, H., Lehtinen, K. J., Makkonen, R., Arola, A., Mielonen, T., Romakkaniemi, S., Kulmala, M., and Kokkola, H.: Evaluation of the sectional aerosol microphysics module SALSA implementation in ECHAM5-HAM aerosol-climate model, Geosci. Model Dev., 5, 845–868, https://doi.org/10.5194/gmd-5-845-2012, 2012. a
Bolsaitis, P. and Elliott, J. F.: Thermodynamic activities and equilibrium partial pressures for aqueous sulfuric acid solutions, J. Phys. Chem. Eng. Data., 35, 69–85, https://doi.org/10.1021/je00059a022, 1990. a
Bowman, F. M., Odum, J. R., Seinfeld, J. H., and Pandis, S. N.: Mathematical model for gas-particle partitioning of secondary organic aerosols, Atmos. Environ., 31, 3921–3931, https://doi.org/10.1016/S1352-2310(97)00245-8, 1997. a
Boy, M., Hellmuth, O., Korhonen, H., Nilsson, E. D., ReVelle, D., Turnipseed, A., Arnold, F., and Kulmala, M.: MALTE – model to predict new aerosol formation in the lower troposphere, Atmos. Chem. Phys., 6, 4499–4517, https://doi.org/10.5194/acp-6-4499-2006, 2006. a
Breitner, S., Liu, L., Cyrys, J., Brüske, I., Franck, U., Schlink, U., Leitte, A. M., Herbarth, O., Wiedensohler, A., Wehner, B., Hu, M., Pan, X.-C., Wichmann, H.-E., and Peters, A.: Sub-micrometer
particulate air pollution and cardiovascular mortality in Beijing, China, Sci. Total Environ., 409, 5196–5204, https://doi.org/10.1016/j.scitotenv.2011.08.023, 2011. a
Capaldo, K. P., Pilinis, C., and Pandis, S.: A computationally efficient hybrid approach for dynamic gas/aerosol transfer in air quality models, Atmos. Environ., 34, 3617–3627, https://doi.org/10.1016/S1352-2310(00)00092-3, 2000. a
Carlton, A. G., Bhave, P. V., Napelenok, S. L., Edney, E. O., Sarwar, G., Pinder, R. W., Pouliot, G. A., and Houyoux, M.: Model representation of secondary organic aerosol in CMAQv4.7, Environ. Sci.
Technol., 44, 8553–8560, https://doi.org/10.1021/es100636q, 2010. a
Carslaw, D. C. and Ropkins, K.: openair – an R package for air quality data analysis, Environ. Model. Softw., 27–28, 52–61, https://doi.org/10.1016/j.envsoft.2011.09.008, 2012. a
Chan, C. K., Flagan, R. C., and Seinfeld, J. H.: Water activities of NH4NO3
Chan, T. L., Luo, D. D., Cheung, C. S., Chan, C. K.: Large eddy simulation of flow structures and pollutant dispersion in the near-wake region of the studied ground vehicle for different driving conditions, Atmos. Environ., 42, 5317–5339, https://doi.org/10.1016/j.atmosenv.2008.02.068, 2008. a
Chen, X., Wang, Z., Li, J., Yang, W., Chen, H., Wang, Z., Hao, J., Ge, B., Wang, D., and Huang, H.: Simulation on different response characteristics of aerosol particle number concentration and mass
concentration to emission changes over mainland China, Sci. Total Environ., 643, 692–703, https://doi.org/10.1016/j.scitotenv.2018.06.181, 2018. a
Chosson, F., Paoli, R., and Cuenot, B.: Ship plume dispersion rates in convective boundary layers for chemistry models, Atmos. Chem. Phys., 8, 4841–4853, https://doi.org/10.5194/acp-8-4841-2008, 2008. a
DeCarlo, P. F., Slowik, J. G., Worsnop, D. R., Davidovits, P., and Jimenez, J. L.: Particle morphology and density characterization by combined mobility and aerodynamic diameter measurements. Part 1: Theory, Aerosol Sci. Technol., 38, 1185–1205, https://doi.org/10.1080/027868290903907, 2004. a
Donahue, N. M., Robinson, A. L., Stanier, C. O., and Pandis, S. N.: Coupled partitioning, dilution, and chemical aging of semivolatile organics, Environ. Sci. Technol., 40, 2635–2643, https://doi.org/10.1021/es052297c, 2006. a
Donahue, N. M., Epstein, S. A., Pandis, S. N., and Robinson, A. L.: A two-dimensional volatility basis set: 1. organic-aerosol mixing thermodynamics, Atmos. Chem. Phys., 11, 3303–3318, https://doi.org/10.5194/acp-11-3303-2011, 2011. a, b, c, d
Ehn, M., Thornton, J. A., Kleist, E., Sipilä, M., Junninen, H., Pullinen, I., Springer, M., Rubach, F., Tillmann, R., Lee, B., Lopez-Hilfiker, F., Andres, S., Ismail-Hakki, A., Rissanen, M., Jokinen, T., Schobesberger, S., Kangasluoma, J., Kontkanen, J., Nieminen, T., Kurtén, T., Nielsen, L. B., Jørgensen, S., Kjaergaard, H. G., Canagaratna, M., Dal Maso, M., Berndt, T., Petäjä, T., Wahner, A., Kerminen, V.-M., Kulmala, M., Worsnop, D. R., Wildt, J., and Mentel, T. F.: A large source of low-volatility secondary organic aerosol, Nature, 506, 476–479, https://doi.org/10.1038/nature13032, 2014. a
Emerson, E. W., Hodshire, A. L., DeBolt, H. M., Bilsback, K. R., Pierce, J. R., McMeeking, G. R., and Farmer, D. K.: Revisiting particle dry deposition and its role in radiative effect estimates, Proc. Natl. Acad. Sci. USA, 117, 26076–26082, https://doi.org/10.1073/pnas.2014761117, 2020. a
Ervens, B., Feingold, G., Frost, G. J., and Kreidenweis, S. M.: A modeling study of aqueous production of dicarboxylic acids: 1. Chemical pathways and speciated organic mass production, J. Geophys. Res., 109, D15205, https://doi.org/10.1029/2003JD004387, 2004. a
Evans, K. A., Halterman, J. S., Hopke, P. K., Fagnano, M., and Rich, D. Q.: Increased ultrafine particles and carbon monoxide concentrations are associated with asthma exacerbation among urban children, Environ. Res., 129, 11–19, https://doi.org/10.1016/j.envres.2013.12.001, 2014. a
Farren, N. J., Davison, J., Rose, R. A., Wagner, R. L., and Carslaw, D. C.: Underestimated ammonia emissions from road vehicles, Environ. Sci. Technol., 54, 15689–15697, https://doi.org/10.1021/acs.est.0c05839, 2020. a
Fitzgerald, J. W., Hoppel, W. A., and Gelbard, F.: A one-dimensional sectional model to simulate multicomponent aerosol dynamics in the marine boundary layer. 1. Model description, J. Geophys. Res., 103, 16085–16102, https://doi.org/10.1029/98JD01018, 1998. a
Fountoukis, C., Riipinen, I., Denier van der Gon, H. A. C., Charalampidis, P. E., Pilinis, C., Wiedensohler, A., O'Dowd, C., Putaud, J. P., Moerman, M., and Pandis, S. N.: Simulating ultrafine particle formation in Europe using a regional CTM: contribution of primary emissions versus secondary formation to aerosol number concentrations, Atmos. Chem. Phys., 12, 8663–8677, https://doi.org/10.5194/acp-12-8663-2012, 2012. a
Ge, X., Wexler, A. S., and Clegg, S. L.: Atmospheric amines – Part II. Thermodynamic properties and gas/particle partitioning, Atmos. Environ., 45, 561–577, https://doi.org/10.1016/j.atmosenv.2010.10.013, 2011. a
Gelbard, F.: Modeling multicomponent aerosol particle growth by vapor condensation, Aerosol Sci. Technol., 12, 399–412, https://doi.org/10.1080/02786829008959355, 1990. a
Gelbard, F. and Seinfeld, J. H.: Simulation of multicomponent aerosol dynamics, J. Colloid Interface Sci., 78, 485–501, https://doi.org/10.1016/0021-9797(80)90587-1, 1980. a, b
Gidhagen, L., Johansson, C., Ström, J., Kristensson, A., Swietlicki, E., Pirjola, L., and Hansson H.-C.: Model simulation of ultrafine particles inside a road tunnel, Atmos. Environ., 37, 2023–2036,
https://doi.org/10.1016/S1352-2310(03)00124-9, 2003. a
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, https://doi.org/10.1016/j.atmosenv.2004.02.014, 2004. a, b, c
Gidhagen, L., Johansson, C., Langner, J., and Foltescu, V. L.: Urban scale modeling of particle number concentration in Stockholm, Atmos. Environ., 39, 1711–1725, https://doi.org/10.1016/j.atmosenv.2004.11.042,
2005. a
Hamilton, R. S. and Mansfield, T. A.: Airborne particulate elemental carbon: its sources, transport and contribution to dark smoke and soiling, Atmos. Environ., 25A, 715–723, https://doi.org/10.1016/0960-1686(91)90070-N, 1991. a
Harrison, R. M., Jones, A. M., Beddows, D. C. S., Dall'Osto, M., and Nikolova, I.: Evaporation of traffic-generated nanoparticles during advection from source, Atmos. Environ., 125, 1–7, https://doi.org/10.1016/j.atmosenv.2015.10.077, 2016. a
Henschel, H., Kurtén, T., and Vehkamäki, H.: Computational study on the effect of hydration on new particle formation in the sulfuric acid/ammonia and sulphuric acid/dimethylamine systems, J. Phys. Chem. A, 120, 1886–1896, https://doi.org/10.1021/acs.jpca.5b11366, 2016. a
Hietikko, R., Kuuluvainen, H., Harrison, R. M., Portin, H., Timonen, H., Niemi, J. V., and Rönkkö, T.: Diurnal variation of nanocluster aerosol concentrations and emission factors in a street canyon, Atmos. Environ., 189, 98–106, https://doi.org/10.1016/j.atmosenv.2018.06.031, 2018. a
Hussein, T., Smolik, J., Kerminen, V.-M., and Kulmala, M.: Modeling dry deposition of aerosol particles onto rough surfaces, Aerosol Sci. Technol., 46, 44–59, https://doi.org/10.1080/02786826.2011.605814, 2012. a, b
Hyvärinen, A.-P., Lihavainen, H., Gaman, A., Vairila, L., Ojala, H., Kulmala, M. and Viisanen, Y.: Surface tensions and densities of oxalic, malonic, succinic, maleic, malic, and cis-pinonic acids, J. Chem. Eng. Data 51, 255–260, https://doi.org/10.1021/je050366x, 2006. a
Jacobson, M. Z.: Development and application of a new air pollution modeling system – II. Aerosol module structure and design, Atmos. Environ., 31, 131–144, https://doi.org/10.1016/1352-2310(96)00202-6, 1997a. a
Jacobson, M. Z.: Numerical techniques to solve condensational and dissolutional growth equations when growth is coupled to reversible reactions, Aerosol Sci. Technol., 27, 491–498, https://doi.org/10.1080/02786829708965489, 1997b. a, b, c
Jacobson, M. Z.: Studying the effects of calcium and magnesium on size-distributed nitrate and ammonium with EQUISOLV II, Atmos. Environ., 33, 3635–3649, https://doi.org/10.1016/S1352-2310(99)00105-3, 1999. a
Jacobson, M. Z. and Seinfeld, J. H.: Evolution of nanoparticle size and mixing state near the point of emission, Atmos. Environ., 38, 1839–1850, https://doi.org/10.1016/j.atmosenv.2004.01.014, 2004. a, b, c, d
Jacobson, M. Z. and Turco, R. P.: Simulating condensational growth, evaporation, and coagulation of aerosols using a combined moving and stationary size grid, Aerosol Sci. Technol., 22, 73–92, https://doi.org/10.1080/02786829408959729, 1995. a, b
Jacobson, M. Z., Kittelson, D. B., and Watts, W. F.: Enhanced coagulation due to evaporation and its effect on nanoparticle evolution. Environ. Sci. Technol., 39, 9486–9492, https://doi.org/10.1021/es0500299, 2005. a
Jaecker-Voirol, A., Mirabel, P. and Reiss, H.: Hydrates in supersaturated binary sulfuric acid-water vapor: a re-examination, J. Chem. Phys. 87, 4849–4852, https://doi.org/10.1063/1.452847, 1987. a
Järvinen, A., Timonen, H., Karjalainen, P., Bloss, M., Simonen, P., Saarikoski, S., Kuuluvainen, H., Kalliokoski, J., Dal Maso, M., Niemi, J. V., Keskinen, J., and Rönkkö, T.: Particle emissions of Euro
VI, EEV and retrofitted EEV city buses in real traffic, Environ. Pollut., 250, 708–716, https://doi.org/10.1016/j.envpol.2019.04.033, 2019. a
Julin, J., Winkler, P. M., Donahue, N. M., Wagner, P. E., and Riipinen, I.: Near-unity mass accommodation coefficient of organic molecules of varying structure, Environ. Sci. Technol., 48, 12083–12089, https://doi.org/10.1021/es501816h, 2014. a
Kangasniemi, O., Kuuluvainen, H., Heikkilä, J., Pirjola, L., Niemi, J. V., Timonen, H., Saarikoski, S., Rönkkö, T., and Dal Maso, M.: Dispersion of a traffic related nanocluster aerosol near a major road, Atmosphere, 10, 309, https://doi.org/10.3390/atmos10060309, 2019. a
Karl, M., Gross, A., Leck, C., and Pirjola, L.: Intercomparison of dimethylsulfide oxidation mechanisms for the marine boundary layer: gaseous and particulate sulfur constituents, J. Geophys. Res., 112, D15304, https://doi.org/10.1029/2006JD007914, 2007. a, b
Karl, M., Leck, C., Gross, A., and Pirjola, L.: A study of new particle formation in the marine boundary layer over the central Arctic Ocean using a flexible multicomponent aerosol dynamic model, Tellus B, 64, 17158, https://doi.org/10.3402/tellusb.v64i0.17158, 2012a. a, b, c
Karl, M., Dye, C., Schmidbauer, N., Wisthaler, A., Mikoviny, T., D'Anna, B., Müller, M., Borrás, E., Clemente, E., Muñoz, A., Porras, R., Ródenas, M., Vázquez, M., and Brauers, T.: Study of OH-initiated degradation of 2-aminoethanol, Atmos. Chem. Phys., 12, 1881–1901, https://doi.org/10.5194/acp-12-1881-2012, 2012b. a, b, c, d
Karl, M., Leck, C., Coz, E., and Heintzenberg, J.: Marine nanogels as a source of atmospheric nanoparticles in the high Arctic, Geophys. Res. Lett., 40, 3738–3743, https://doi.org/10.1002/grl.50661, 2013. a, b
Karl, M., Kukkonen, J., Keuken, M. P., Lützenkirchen, S., Pirjola, L., and Hussein, T.: Modeling and measurements of urban aerosol processes on the neighborhood scale in Rotterdam, Oslo and Helsinki, Atmos. Chem. Phys., 16, 4817–4835, https://doi.org/10.5194/acp-16-4817-2016, 2016. a, b, c, d, e, f, g, h
Karl, M., Walker, S.-E., Solberg, S., and Ramacher, M. O. P.: The Eulerian urban dispersion model EPISODE – Part 2: Extensions to the source dispersion and photochemistry for EPISODE–CityChem v1.2 and its application to the city of Hamburg, Geosci. Model Dev., 12, 3357–3399, https://doi.org/10.5194/gmd-12-3357-2019, 2019. a, b, c, d
Karl, M., Pirjola, L., Karppinen, A., Jalkanen, J.-P., Ramacher, M. O. P., and Kukkonen, J.: Modeling of the concentrations of ultrafine particles in the plumes of ships in the vicinity of major harbors, Int. J. Environ. Res. Public Health, 17, 777, https://doi.org/10.3390/ijerph17030777, 2020. a, b, c
Karl, M., Pirjola, L., Grönholm, T., Kurppa, M., Anand, S., Zhang, X.,
Held, A., Sander, R., Dal Maso, M., Topping, D., Jiang, S., Kangas, L., and Kukkonen, J.: Release of the community aerosol dynamics model MAFOR v2 and the urban case dataset published in Karl et al., GMD, (v1.9.9), Zenodo [code], https://doi.org/10.5281/zenodo.5718580, 2021. a, b, c
Karppinen, A., Kukkonen, J., Elolähde, T., Konttinen, M., Koskentalo, T., and Rantakrans, E.: A modelling system for predicting urban air pollution: Model description and applications in the Helsinki metropolitan area, Atmos. Environ., 34, 3723–3733, https://doi.org/10.1016/S1352-2310(00)00074-1, 2000. a
Kerminen, V.-M., Mäkelä, T. E., Ojanen, C. H., Hillamo, R. E., Vilhunen, J. K., Rantanen, L., Havers, N., von Bohlen, A., and Klockow, D.: Characterization of the particulate phase in the exhaust from a diesel car, Environ. Sci. Technol., 31, 1883–1889, https://doi.org/10.1021/es960520n, 1997. a, b, c
Kerminen, V.-M., Pakkanen, T. A., Mäkelä, T., Hillamo, R. E., Rönkkö, T., Virtanen, A., Keskinen, J., Pirjola, L., Hussein, T., and Hämeri, K.: Development of particle number size distribution near a major road in Helsinki during an episodic inversion situation, Atmos. Environ., 41, 1759–1767, https://doi.org/10.1016/j.atmosenv.2006.10.026, 2007. a
Keuken, M. P., Henzing, J. S., Zandveld, P., van den Elshout, S., and Karl, M.: Dispersion of particle numbers and elemental carbon from road traffic, a harbor and an airstrip in the Netherlands, Atmos. Environ., 54, 320–327, https://doi.org/10.1016/j.atmosenv.2012.01.012, 2012. a, b
Keuken, M. P., Moerman, M., Zandveld, P., and Henzing, J. S.: Total and size-resolved particle number and black carbon concentrations near an industrial area, Atmos. Environ., 122, 196–205, https://doi.org/10.1016/j.atmosenv.2015.01.015, 2015. a
Kokkola, H.: UCLALES-SALSA/SALSA-standalone 2.0 (v2.0), Zenodo [code], https://doi.org/10.5281/zenodo.1251669, 2018. a
Kokkola, H., Korhonen, H., Lehtinen, K. E. J., Makkonen, R., Asmi, A., Järvenoja, S., Anttila, T., Partanen, A.-I., Kulmala, M., Järvinen, H., Laaksonen, A., and Kerminen, V.-M.: SALSA – a Sectional Aerosol module for Large Scale Applications, Atmos. Chem. Phys., 8, 2469–2483, https://doi.org/10.5194/acp-8-2469-2008, 2008. a, b, c, d
Kokkola, H., Kühn, T., Laakso, A., Bergman, T., Lehtinen, K. E. J., Mielonen, T., Arola, A., Stadtler, S., Korhonen, H., Ferrachat, S., Lohmann, U., Neubauer, D., Tegen, I., Siegenthaler-Le Drian, C., Schultz, M. G., Bey, I., Stier, P., Daskalakis, N., Heald, C. L., and Romakkaniemi, S.: SALSA2.0: The sectional aerosol module of the aerosol–chemistry–climate model ECHAM6.3.0-HAM2.3-MOZ1.0, Geosci. Model Dev., 11, 3833–3863, https://doi.org/10.5194/gmd-11-3833-2018, 2018. a
Kouznetsov, R. and Sofiev, M.: A methodology for evaluation of vertical dispersion and dry deposition of atmospheric aerosols, J. Geophys. Res., 117, 1–19, https://doi.org/10.1029/2011JD016366, 2012. a
Kreidenweis, S. M. and Seinfeld, J. H.: Nucleation of sulfuric acid-water and methanesulfonic acid-water solution particles: Implications for the atmospheric chemistry of organosulfur species, Atmos. Environ., 22, 283–296, https://doi.org/10.1016/0004-6981(88)90034-0, 1988. a
Kukkonen, J., Olsson, T., Schultz, D. M., Baklanov, A., Klein, T., Miranda, A. I., Monteiro, A., Hirtl, M., Tarvainen, V., Boy, M., Peuch, V.-H., Poupkou, A., Kioutsioukis, I., Finardi, S., Sofiev, M., Sokhi, R., Lehtinen, K. E. J., Karatzas, K., San José, R., Astitha, M., Kallos, G., Schaap, M., Reimer, E., Jakobs, H., and Eben, K.: A review of operational, regional-scale, chemical weather forecasting models in Europe, Atmos. Chem. Phys., 12, 1–87, https://doi.org/10.5194/acp-12-1-2012, 2012. a
Kukkonen, J., Karl, M., Keuken, M. P., Denier van der Gon, H. A. C., Denby, B. R., Singh, V., Douros, J., Manders, A., Samaras, Z., Moussiopoulos, N., Jonkers, S., Aarnio, M., Karppinen, A., Kangas, L., Lützenkirchen, S., Petäjä, T., Vouitsis, I., and Sokhi, R. S.: Modelling the dispersion of particle numbers in five European cities, Geosci. Model Dev., 9, 451–478, https://doi.org/10.5194/gmd-9-451-2016, 2016. a, b, c, d
Kukkonen, J., Kangas, L., Kauhaniemi, M., Sofiev, M., Aarnio, M., Jaakkola, J. J. K., Kousa, A., and Karppinen, A.: Modelling of the urban concentrations of PM2.5 on a high resolution for a period of 35 years, for the assessment of lifetime exposure and health effects, Atmos. Chem. Phys., 18, 8041–8064, https://doi.org/10.5194/acp-18-8041-2018, 2018. a, b
Kulmala, M., Pirjola, L., and Mäkelä, J. M.: Stable sulphate clusters as a source of new atmospheric particles, Nature, 404, 66–69, https://doi.org/10.1038/35003550, 2000. a
Kulmala, M., Vehkamäki, H., Petäjä, T., Dal Maso, M., Lauri, A., Kerminen, V.-M., Birmili, W., and McMurry, P. H.: Formation and growth rates of ultrafine atmospheric particles: a review of observations, J. Aerosol Sci., 35, 143–176, https://doi.org/10.1016/j.jaerosci.2003.10.003, 2004. a
Kulmala, M., Lehtinen, K. E. J., and Laaksonen, A.: Cluster activation theory as an explanation of the linear dependence between formation rate of 3 nm particles and sulphuric acid concentration, Atmos. Chem. Phys., 6, 787–793, https://doi.org/10.5194/acp-6-787-2006, 2006. a, b, c, d
Kumar, P., Fennell, P., Langley, D., and Britter, R.: Pseudo-simultaneous measurements for the vertical variation of coarse, fine and ultrafine particles in an urban street canyon, Atmos. Environ., 42, 4304–4319, https://doi.org/10.1016/j.atmosenv.2008.01.010, 2008. a
Kumar, P., Robins, A., and Britter, R.: Fast response measurements for the dispersion of nanoparticles in a vehicle wake and in a street canyon, Atmos. Environ., 43, 6110–6118, https://doi.org/10.1016/j.atmosenv.2009.08.042, 2009. a
Kurppa, M., Hellsten, A., Roldin, P., Kokkola, H., Tonttila, J., Auvinen, M., Kent, C., Kumar, P., Maronga, B., and Järvi, L.: Implementation of the sectional aerosol module SALSA2.0 into the PALM model system 6.0: model development and first evaluation, Geosci. Model Dev., 12, 1403–1422, https://doi.org/10.5194/gmd-12-1403-2019, 2019. a, b, c, d
Kurppa, M., Roldin, P., Strömberg, J., Balling, A., Karttunen, S., Kuuluvainen, H., Niemi, J. V., Pirjola, L., Rönkkö, T., Timonen, H., Hellsten, A., and Järvi, L.: Sensitivity of spatial aerosol particle distributions to the boundary conditions in the PALM model system 6.0, Geosci. Model Dev., 13, 5663–5685, https://doi.org/10.5194/gmd-13-5663-2020, 2020. a, b, c
Lambe, A. T., Miracolo, M. A., Hennigan, C. J., Robinson, A. L., and Donahue, N. M.: Effective rate constants and uptake coefficients for the reactions of organic molecular markers (n-alkanes, hopanes, and steranes) in motor oil and diesel primary organic aerosols with hydroxyl radicals, Environ. Sci. Technol., 43, 8794–8800, https://doi.org/10.1021/es901745h, 2009. a
Landgraf, J. and Crutzen, P. J.: An efficient method for online calculations of photolysis and heating rates, J. Atmos. Sci., 55, 863–878, https://doi.org/10.1175/1520-0469(1998)055<0863:AEMFOC>2.0.CO;2, 1998. a
Lee, Y. H. and Adams, P. J.: Evaluation of aerosol distributions in the GISS-TOMAS global aerosol microphysics model with remote sensing observations, Atmos. Chem. Phys., 10, 2129–2144, https://doi.org/10.5194/acp-10-2129-2010, 2010. a
Legates, D. R. and McCabe, G. J.: Evaluating the use of “goodness-of-fit” Measures in hydrologic and hydroclimatic model validation, Water Resour. Res., 35, 233–241, https://doi.org/10.1029/1998WR900018, 1999. a
Lehtinen, K. E. J. and Kulmala, M.: A model for particle formation and growth in the atmosphere with molecular resolution in size, Atmos. Chem. Phys., 3, 251–257, https://doi.org/10.5194/acp-3-251-2003, 2003. a
Lemmetty, M., Pirjola, L., Mäkelä, J. M., Rönkkö, T., and Keskinen, J.: Computation of maximum rate of water-sulphuric acid nucleation in diesel exhaust, J. Aerosol Sci., 37, 1596–1604, https://doi.org/10.1016/j.jaerosci.2006.04.003, 2006. a
Lemmetty, M., Rönkkö, T., Virtanen, A., Keskinen, J. and Pirjola, L.: The Effect of Sulphur in Diesel Exhaust Aerosol: Models Compared with Measurements, Aerosol Sci. Technol., 42, 11916–11929, https://doi.org/10.1080/02786820802360682, 2008. a
Lim, Y. B. and Ziemann, P. J.: Effects of molecular structure on aerosol yields from OH radical-initiated reactions of linear, branched, and cyclic alkanes in the presence of NOx, Environ. Sci. Technol., 43, 2328–2334, https://doi.org/10.1021/es100636q, 2009. a
LIPASTO: Calculation system for traffic exhaust emissions and energy use in Finland, VTT Technical Research Centre of Finland Ltd., http://lipasto.vtt.fi/en/index.htm, last access: 8 November 2021. a
Määttänen, A., Merikanto, J., Henschel, H., Duplissy, J., Makkonen, R., Ortega, I. K., and Vehkamäki, H.: New parameterizations for neutral and ion-induced sulfuric acid-water particle formation in nucleation and kinetic regimes, J. Geophys. Res.-Atmos., 123, 1269–1296, https://doi.org/10.1002/2017JD027429, 2018a. a, b, c, d
Määttänen, A., Merikanto, J., Henschel, H., Duplissy, J., Makkonen, R., Ortega, I. K., and Vehkamäki, H.: Revised release of a Fortran code including the particle formation parameterizations published in Määttänen et al., JGR D, 2018 (v1.0, Vol. 123, pp. 1269–1296), J. Geophys. Res.-Atmos., Zenodo [code], https://doi.org/10.5281/zenodo.1217782, 2018b. a, b
Mallik, C., Tomsche, L., Bourtsoukidis, E., Crowley, J. N., Derstroff, B., Fischer, H., Hafermann, S., Hüser, I., Javed, U., Keßel, S., Lelieveld, J., Martinez, M., Meusel, H., Novelli, A., Phillips, G. J., Pozzer, A., Reiffs, A., Sander, R., Taraborrelli, D., Sauvage, C., Schuladen, J., Su, H., Williams, J., and Harder, H.: Oxidation processes in the eastern Mediterranean atmosphere: evidence from the modelling of HOx measurements over Cyprus, Atmos. Chem. Phys., 18, 10825–10847, https://doi.org/10.5194/acp-18-10825-2018, 2018. a
Maricq, M. M., Xu, N., and Chase, R. E.: Measuring particulate mass emissions with the Electrical Low Pressure Impactor, Aerosol Sci. Technol., 40, 68–79, https://doi.org/10.1080/02786820500466591, 2006. a
Mårtensson, E. M., Nilsson, E. D., de Leeuw, G., Cohen, L. H., and Hansson, H.-C.: Laboratory simulations and parameterization of the primary marine aerosol production, J. Geophys. Res., 108, 4297, https://doi.org/10.1029/2002JD002263, 2003. a
Mauritsen, T., Sedlar, J., Tjernström, M., Leck, C., Martin, M., Shupe, M., Sjogren, S., Sierau, B., Persson, P. O. G., Brooks, I. M., and Swietlicki, E.: An Arctic CCN-limited cloud-aerosol regime, Atmos. Chem. Phys., 11, 165–173, https://doi.org/10.5194/acp-11-165-2011, 2011. a
McGraw, R.: Description of aerosol dynamics by the quadrature method of moments, Aerosol Sci. Technol., 27, 255–265, https://doi.org/10.1080/02786829708965471, 1997. a
Merikanto, J., Napari, I., Vehkamäki, H., Anttila, T., and Kulmala, M.: New parameterization of sulphuric acid-ammonia-water ternary nucleation rates at tropospheric conditions, J. Geophys. Res., 112, 1–9, https://doi.org/10.1029/2006JD007977, 2007. a, b
Merikanto, J., Napari, I., Vehkamäki, H., Anttila, T., and Kulmala, M.: Correction to “New parameterization of sulphuric acid-ammonia-water ternary nucleation rates at tropospheric conditions”, J. Geophys. Res., 114, 1–2, https://doi.org/10.1029/2009JD012136, 2009. a
Meskhidze, N., Jaimes-Correa, J. C., Petters, M. D., Royalty, T. M., Phillips, B. N., Zimmerman, A., and Reed, R.: Possible wintertime sources of fine particles in an urban environment, J. Geophys. Res.-Atmos., 124,, 13055–13070, https://doi.org/10.1029/2019JD031367, 2019. a
Morawska, L., Ristovski, Z., Jayaratne, E. R., Koegh, D. U., and Ling, X.: Ambient nano and ultrafine particles from motor vehicle emissions: characteristics, ambient processing and implications on human exposure, Atmos. Environ., 42, 8113–8138, https://doi.org/10.1016/j.atmosenv.2008.07.050, 2008. a
Meng, Z. and Seinfeld, J. H.: Time scales to achieve gas-aerosol equilibrium for volatile species, Atmos. Environ., 30, 2889–2900, https://doi.org/10.1016/1352-2310(95)00493-9, 1996.
Metzger, A., Verheggen, B., Dommen, J., Duplissy, J., Prevôt, A. S., Weingartner, E., Riipinen, I., Kulmala, M., Spracklen, D. V., Carslaw, K. S., and Baltensperger, U.: Evidence for the role of organics in aerosol particle formation under atmospheric conditions, P. Natl. Acad. Sci., 107, 6646–6651, https://doi.org/10.1073/pnas.0911330107, 2010. a
Monahan, E. C., Spiel, D. E., and Davidson, K. L.: A model of marine aerosol generation via whitecaps and wave disruption, in: Oceanic Whitecaps, 1st edn., Oceanographic Sciences Library, edited by: Monahan, E. C. and Mac Niocaill, G., 167–174, D. Reidel, Norwell, Massachusetts, ISBN: 9789027722515, 1986. a
Napari, I., Noppel, M., Vehkamäki, H., and Kulmala, M.: An improved model for ternary nucleation of sulfuric-acid-ammonia water, J. Chem. Phys., 116, 4221–4227, https://doi.org/10.1063/1.1450557, 2002. a
Nenes, A., Pandis, S. N., and Pilinis, C.: Continued development and testing of a new thermodynamic aerosol module for urban and regional air quality models, Atmos. Environ., 33, 1553–1560, https://doi.org/10.1016/S1352-2310(98)00352-5, 1999. a
Nielsen, C. J., D'Anna, B., Karl, M., Aursnes, M., Boreave, A., Bossi, R., Bunkan, A. J. C., Glasius, M., Hallquist, M., Hansen, A.-M. K., Kristensen, K., Mikoviny, T., Maguta, M. M., Müller, M., Nguyen, Q., Westerlund, J., Salo, K., Skov, H., Stenstrøm, Y., and Wisthaler, A.: Atmospheric Degradation of Amines. Summary Report: Photo-oxidation of methylamine, dimethylamine and trimethylamine, CLIMIT project no. 201604, NILU Report OR 2/2011, Norwegian Institute for Air Research,
Kjeller, Norway, https://www.nilu.com/publication/25495/ (last access: 9 May 2022), 2011. a
Nikolova, I., Janssen, S., Vos, P., and Berghmans, P.: Modelling the mixing of size resolved traffic induced and background ultrafine particles from an urban street canyon to adjacent backyards, Aerosol Air Qual. Res., 14, 145–155, https://doi.org/10.4209/aaqr.2013.06.0221, 2014. a, b
Noppel, M., Vehkamäki, H., and Kulmala, M.: An improved model for hydrate formation in sulfuric acid-water nucleation, J. Chem. Phys., 116, 218–228, https://doi.org/10.1063/1.1423333, 2002. a
Olenius, T., Kupiainen-Määttä, O., Ortega, I. K., Kurtén, T., and Vehkamäki, H.: Free energy barrier in the growth of sulphuric acid–ammonia and sulfuric acid–dimethylamine clusters, J. Chem. Phys., 139, 084312, https://doi.org/10.1063/1.4819024, 2013. a
Olin, M., Kuuluvainen, H., Aurela, M., Kalliokoski, J., Kuittinen, N., Isotalo, M., Timonen, H. J., Niemi, J. V., Rönkkö, T., and Dal Maso, M.: Traffic-originated nanocluster emission exceeds H2SO4-driven photochemical new particle formation in an urban area, Atmos. Chem. Phys., 20, 1–13, https://doi.org/10.5194/acp-20-1-2020, 2020. a
Paasonen, P., Nieminen, T., Asmi, E., Manninen, H. E., Petäjä, T., Plass-Dülmer, C., Flentje, H., Birmili, W., Wiedensohler, A., Hõrrak, U., Metzger, A., Hamed, A., Laaksonen, A., Facchini, M. C., Kerminen, V.-M., and Kulmala, M.: On the roles of sulphuric acid and low-volatility organic vapours in the initial steps of atmospheric new particle formation, Atmos. Chem. Phys., 10, 11223–11242, https://doi.org/10.5194/acp-10-11223-2010, 2010. a, b, c, d
Paasonen, P., Kupiainen, K., Klimont, Z., Visschedijk, A., Denier van der Gon, H. A. C., and Amann, M.: Continental anthropogenic primary particle number emissions, Atmos. Chem. Phys., 16, 6823–6840, https://doi.org/10.5194/acp-16-6823-2016, 2016. a
Peng, C. and Chan, C. K.: The water cycles of water-soluble organic salts of atmospheric importance, Atmos. Environ., 35, 1183–1192, https://doi.org/10.1016/S1352-2310(00)00426-X ,2001. a
Petersen, W. B.: User's Guide for Hiway-2: A Highway Air Pollution Model, US Environmental Protection Agency, EPA-600/8-80-018, Research Triangle Park, NC, USA, https://nepis.epa.gov (last access: 8 November 2021), 1980. a
Petroff, A., Mailliat, A., Amielh, M., and Anselmet, F.: Aerosol dry deposition on vegetative canopies. Part II: A new modelling approach and applications, Atmos. Environ., 42, 3654–3683, https://doi.org/10.1016/j.atmosenv.2007.12.060, 2008. a
Petters, M. D. and Kreidenweis, S. M.: A single parameter representation of hygroscopic growth and cloud condensation nucleus activity, Atmos. Chem. Phys., 7, 1961–1971, https://doi.org/10.5194/acp-7-1961-2007, 2007. a
Pierce, J., Theodoritsi, G., Adams, P., and Pandis, S. N.: Parameterization of the effect of sub-grid scale aerosol dynamics on aerosol number emission rates, J. Aerosol Sci., 40, 385–393, https://doi.org/10.1016/j.jaerosci.2008.11.009, 2009. a
Pirjola, L.: Effects of the increased UV radiation and biogenic VOC emissions on ultrafine sulphate aerosol formation, J. Aerosol Sci., 3, 355–367, https://doi.org/10.1016/S0021-8502(98)00065-2, 1999. a, b
Pirjola, L. and Kulmala, M.: Modelling the formation of H2SO4-H2O particles in rural, urban and marine conditions, Atmos. Res., 46, 321–347, https://doi.org/10.1016/S0169-8095(97)00072-0, 1998. a
Pirjola, L. and Kulmala, M.: Development of particle size and composition distributions with a novel aerosol dynamics model, Tellus B, 53, 491–509, https://doi.org/10.3402/tellusb.v53i4.17128, 2001. a, b, c
Pirjola, L., Laaksonen, A., Aalto, P., and Kulmala, M.: Sulfate aerosol formation in the Arctic boundary layer, J. Geophys. Res., 103, 8309–8321, https://doi.org/10.1029/97JD03079, 1998. a, b
Pirjola, L., O'Dowd, C. D. and Kulmala, M.: A model prediction of the yield of CCN from tidal-related nucleation events, J. Geophys. Res., 107, PAR3-1–PAR3-15, https://doi.org/10.1029/2000JD000213, 2002. a
Pirjola, L., Tsyro, S., Tarrason, L., and Kulmala, M.: A monodisperse aerosol dynamics module – a promising candidate for use in the Eulerian long-range transport model, J. Geophys. Res., 108, 4258, https://doi.org/10.1029/2002JD002867, 2003. a
Pirjola, L., Lehtinen, K. E. J., Hansson, H.-C., and Kulmala, M.: How important is nucleation in regional/global modelling, Geophys. Res. Lett., 31, L12109, 1–4, https://doi.org/10.1029/2004GL019525, 2004. a
Pirjola, L., Lähde, T., Niemi, J. V., Kousa, A., Rönkkö, T., Karjalainen, P., Keskinen, J., Frey, A., and Hillamo, R.: Spatial and temporal characterization of traffic emissions in urban microenvironments with a mobile laboratory, Atmos. Environ., 63, 156–167, https://doi.org/10.1016/j.atmosenv.2012.09.022, 2012. a, b, c, d, e, f
Pirjola, L., Pajunoja, A., Walden, J., Jalkanen, J.-P., Rönkkö, T., Kousa, A., and Koskentalo, T.: Mobile measurements of ship emissions in two harbour areas in Finland, Atmos. Meas. Tech., 7, 149–161, https://doi.org/10.5194/amt-7-149-2014, 2014. a
Pnueli, D., Gutfinger, C., and Fichman, M.: A turbulent-Brownian model for aerosol coagulation, Aerosol Sci. Technol., 14, 201–209, https://doi.org/10.1080/02786829108959483, 1991. a
Pohjola, M. A., Pirjola, L., Kukkonen, J., and Kulmala, M.: Modelling of the influence of aerosol processes for the dispersion of vehicular exhaust plumes in street environment, Atmos. Environ., 37, 339–351, https://doi.org/10.1016/S1352-2310(02)00887-7, 2003. a
Pohjola, M. A., Pirjola, L., Karppinen, A., Härkönen, J., Korhonen, H., Hussein, T., Ketzel, M., and Kukkonen, J.: Evaluation and modelling of the size fractionated aerosol particle number concentration measurements nearby a major road in Helsinki – Part I: Modelling results within the LIPIKA project, Atmos. Chem. Phys., 7, 4065–4080, https://doi.org/10.5194/acp-7-4065-2007, 2007. a, b, c, d, e, f, g, h, i, j
Pringle, K. J., Tost, H., Message, S., Steil, B., Giannadaki, D., Nenes, A., Fountoukis, C., Stier, P., Vignati, E., and Lelieveld, J.: Description and evaluation of GMXe: a new aerosol submodel for global simulations (v1), Geosci. Model Dev., 3, 391–412, https://doi.org/10.5194/gmd-3-391-2010, 2010. a
Pruppacher, H. R. and Klett, J. D.: Microphysics of Clouds and Precipitation, 2nd edn., Kluwer Academic Publishers, Dordrecht, The Netherlands, 954 pp., ISBN: 0-79-234211-1, 1997. a
Reid, R. C., Prausnitz, J. M., and Poling, B. E.: The Properties of Gases and Liquids, 4th edn., edited by: Sun, B. and Fleck, G. H., McGraw-Hill, New York, USA, 741 pp., ISBN: 0070517991, 1987. a
Riemer, N., West, M., Zaveri, R. A., and Easter, R. C.: Simulating the evolution of soot mixing state with a particle-resolved aerosol model, J. Geophys. Res., 114, 1–22, https://doi.org/10.1029/2008JD011073, 2009. a, b
Rivas, I., Beddows, D. C. S., Amato, F., Green, D. C., Järvi, L., Hueglin, C., Reche, C., Timonen, H., Fuller, G. W., Niemi, J. V., Pérez, N., Aurela, M., Hopke, P. K., Alastuey, A., Kulmala, M., Harrison, R. M., Querol, X., and Kelly, F. J.: Source apportionment of particle number size distribution in urban background and traffic stations in four European cities, Environ. Int., 135, 1–19, https://doi.org/10.1016/j.envint.2019.105345, 2020. a
Rogak, S. N. and Flagan, R. C.: Coagulation of aerosol agglomerates in the transition regime, J. Colloid Interface Sci., 151, 203–224, https://doi.org/10.1016/0021-9797(92)90252-H, 1992. a
Roldin, P., Swietlicki, E., Schurgers, G., Arneth, A., Lehtinen, K. E. J., Boy, M., and Kulmala, M.: Development and evaluation of the aerosol dynamics and gas phase chemistry model ADCHEM, Atmos. Chem. Phys., 11, 5867–5896, https://doi.org/10.5194/acp-11-5867-2011, 2011. a, b, c
Rönkkö, T., Virtanen, A., Kannosto, J., Keskinen, J., Lappi, M., and Pirjola, L.: Nucleation mode particles with a non-volatile core in the exhaust of a heavy duty diesel vehicle, Environ. Sci. Technol., 41, 6384–6389, https://doi.org/10.1021/es0705339, 2007. a
Rönkkö, T., Lähde, T., Heikkilä, J., Pirjola, L., Bauschke, U., Arnold, F., Schlager, H., Rothe, D., Yli-Ojanperä, J., and Keskinen, J.: Effects of gaseous sulphuric acid on diesel exhaust nanoparticle formation and characteristics, Environ. Sci. Technol., 47, 11882–11889, 2013. a
Rönkkö, T., Kuuluvainen, H., Karjalainen, P., Keskinen, J., Hillamo, R., Niemi, J. V., Pirjola, L., Timonen, H. J., Saarikoski, S., Saukko, E., Järvinen, A., Silvennoinen, H., Rostedt, A., Olin, M., Yli-Ojanperä, J., Nousiainen, P., Kousa, A., Dal Maso, M.: Traffic is a major source of atmospheric nanocluster aerosol, Proc. Natl. Acad. Sci. USA, 114, 7549–7554, https://doi.org/10.1073/pnas.1700830114, 2017. a
Salo, L., Mylläri, F., Maasikmets, M., Niemelä, V., Konist, A., Vainumäe, K., Kupri, H.-L., Titova, R., Simonen, P., Aurela, M., Bloss, M., Keskinen, J., Timonen, H., and Rönkkö, T.: Emission
measurements with gravimetric impactors and electrical devices: An aerosol instrument comparison, Aerosol Sci. Technol., 53, 526–539, https://doi.org/10.1080/02786826.2019.1578858, 2019. a
Sander, S. P., Abbatt, J., Barker, J. R., Burkholder, J. B., Friedl, R. R., Golden, D. M., Huie, R. E., Kolb, C. E., Kurylo, M. J., Moortgat, G. K., Orkin, V. L., and Wine, P. H.: Chemical Kinetics and Photochemical Data for Use in Atmospheric Studies, Evaluation No. 17, JPL Publication 10-6, Jet Propulsion Laboratory, Pasadena, https://jpldataeval.jpl.nasa.gov/pdf/JPL%2010-6%20Final%2015June2011.pdf (last access: 8 November 2021), 2011. a
Sander, R., Jöckel, P., Kirner, O., Kunert, A. T., Landgraf, J., and Pozzer, A.: The photolysis module JVAL-14, compatible with the MESSy standard, and the JVal PreProcessor (JVPP), Geosci. Model Dev., 7, 2653–2662, https://doi.org/10.5194/gmd-7-2653-2014, 2014. a, b
Sander, R., Baumgaertner, A., Cabrera-Perez, D., Frank, F., Gromov, S., Grooß, J.-U., Harder, H., Huijnen, V., Jöckel, P., Karydis, V. A., Niemeyer, K. E., Pozzer, A., Riede, H., Schultz, M. G., Taraborrelli, D., and Tauer, S.: The community atmospheric chemistry box model CAABA/MECCA-4.0, Geosci. Model Dev., 12, 1365–1385, https://doi.org/10.5194/gmd-12-1365-2019, 2019. a, b
Sandu, A. and Sander, R.: Technical note: Simulating chemical systems in Fortran90 and Matlab with the Kinetic PreProcessor KPP-2.1, Atmos. Chem. Phys., 6, 187–195, https://doi.org/10.5194/acp-6-187-2006, 2006. a
Sarkar, T., Anand, S., Singh, K. D., Tripathi, R. M., Pradeepkumar, K. S., Goto, D., and Nakajima, T. :Simulating long range transport of radioactive aerosols using a global aerosol transport model, Aerosol Air Qual. Res., 17, 2631–2642, https://doi.org/10.4209/aaqr.2017.01.0049, 2017. a
Sarkar, T., Anand, S., Singh, K. D., Kulkarni, M. S., Mayya, Y. S., and Venkataraman, C.: Near-source aerosol dynamics – a parameterization scheme for global aerosol transport model, European Aerosol Conference (EAC 2020), Aachen, Germany, 31 August–4 September 2020, https://phaidra.univie.ac.at/view/o:1164483 (last access: 10 May 2022), 2020. a, b, c
Schack Jr., C. J., Pratsinis, S. E., and Friedlander, S. K.: A general correlation for deposition of suspended particles from turbulent gases to completely rough surfaces, Atmos. Environ., 19, 953–960, https://doi.org/10.1016/0004-6981(85)90240-9, 1985. a, b
Schmitt-Ott, A. and Burtscher, H.: The effect of van der Waals forces on aerosol coagulation, J. Colloid Interface Sci., 89, 353–357, https://doi.org/10.1016/0021-9797(82)90187-4, 1982. a
Schwartz S. E.: Mass transport considerations pertinent to aqueous phase reactions of gases in liquid water clouds, in: Chemistry of Multiphase Atmospheric Systems, NATO ASI Series, Vol. 6, edited by: Jaeschke, W., Springer, Berlin, 415–471, https://doi.org/10.1007/978-3-642-70627-1_16, 1986. a
Seinfeld, J. H. and Pandis, S. N.: Atmospheric Chemistry and Physics: From Air Pollution to Climate Change, 2nd edn., Wiley-Interscience, Hoboken, NJ, USA, ISBN: 9780471720188, 2006. a
Sihto, S.-L., Kulmala, M., Kerminen, V.-M., Dal Maso, M., Petäjä, T., Riipinen, I., Korhonen, H., Arnold, F., Janson, R., Boy, M., Laaksonen, A., and Lehtinen, K. E. J.: Atmospheric sulphuric acid and aerosol formation: implications from atmospheric measurements for nucleation and early growth mechanisms, Atmos. Chem. Phys., 6, 4079–4091, https://doi.org/10.5194/acp-6-4079-2006, 2006. a
Simpson, D.: Long-period modelling of photochemical oxidants in Europe. Model calculations for July 1985, Atmos. Environ., 26, 1609–1634, 1992. a
Singh, V., Sokhi, R., and Kukkonen, J.: PM2.5 concentrations in London for 2008 – A modeling analysis of contributions from road traffic, JAPCA J. Air. Waste Ma., 64, 509–518, https://doi.org/10.1080/10962247.2013.848244, 2014. a
Smith, M. H., Park, P. M., and Consterdine, I. E.: Marine aerosol concentrations and estimated fluxes over the sea, Q. J. Roy. Meteor. Soc., 119, 809–824, https://doi.org/10.1002/qj.49711951211, 1993. a
Spada, M., Jorba, O., Pérez García-Pando, C., Janjic, Z., and Baldasano, J. M.: Modeling and evaluation of the global sea-salt aerosol distribution: sensitivity to size-resolved and sea-surface temperature dependent emission schemes, Atmos. Chem. Phys., 13, 11735–11755, https://doi.org/10.5194/acp-13-11735-2013, 2013. a, b
Spracklen, D. V., Pringle, K. J., Carslaw, K. S., Chipperfield, M. P., and Mann, G. W.: A global off-line model of size-resolved aerosol microphysics: I. Model development and prediction of aerosol properties, Atmos. Chem. Phys., 5, 2227–2252, https://doi.org/10.5194/acp-5-2227-2005, 2005. a
Stier, P., Feichter, J., Kinne, S., Kloster, S., Vignati, E., Wilson, J., Ganzeveld, L., Tegen, I., Werner, M., Balkanski, Y., Schulz, M., Boucher, O., Minikin, A., and Petzold, A.: The aerosol-climate model ECHAM5-HAM, Atmos. Chem. Phys., 5, 1125–1156, https://doi.org/10.5194/acp-5-1125-2005, 2005. a
Tang, I. N. and Munkelwitz, H. R.: Water activities, densities, and refractive indices of aqueous sulfates and sodium nitrate droplets of atmospheric importance, J. Geophys. Res., 99, 18801–18808, https://doi.org/10.1029/94JD01345, 1994. a
Tang, I. N., Tridico, A. C., and Fung, K. H.: Thermodynamic and optical properties of sea salt aerosols, J. Geophys. Res., 102, 23269–23275, https://doi.org/10.1029/97JD01806, 1997. a
Tian, J., Riemer, N., West, M., Pfaffenberger, L., Schlager, H., and Petzold, A.: Modeling the evolution of aerosol particles in a ship plume using PartMC-MOSAIC, Atmos. Chem. Phys., 14, 5327–5347, https://doi.org/10.5194/acp-14-5327-2014, 2014. a
Tonttila, J., Maalick, Z., Raatikainen, T., Kokkola, H., Kühn, T., and Romakkaniemi, S.: UCLALES–SALSA v1.0: a large-eddy model with interactive sectional microphysics for aerosol, clouds and precipitation, Geosci. Model Dev., 10, 169–188, https://doi.org/10.5194/gmd-10-169-2017, 2017. a, b
Tsang, T. H. and Rao, A.: Comparison of different numerical schemes for condensational growth of aerosols, Aerosol Sci. Technol., 9, 271–277, https://doi.org/10.1080/02786828808959214, 1988. a
Tsimpidi, A. P., Karydis, V. A., Zavala, M., Lei, W., Molina, L., Ulbrich, I. M., Jimenez, J. L., and Pandis, S. N.: Evaluation of the volatility basis-set approach for the simulation of organic aerosol formation in the Mexico City metropolitan area, Atmos. Chem. Phys., 10, 525–546, https://doi.org/10.5194/acp-10-525-2010, 2010. a
Tzivion, S., Feingold, G., and Levin, Z.: An efficient numerical-solution to the stochastic collection equation, J. Atmos. Sci., 44, 3139–3149, 1987. a
Vardoulakis, S., Fisher, B. E. A., Pericleous, K., and Gonzalez-Flesca, N.: Modelling air quality in street canyons: a review, Atmos. Environ., 37, 155–182, https://doi.org/10.1016/S1352-2310(02)00857-9, 2003. a
Vehkamäki, H., Kulmala, M., Napari, I., Lehtinen, K. E. J., Timmreck, C., Noppel, M., and Laaksonen, A.: An improved parameterization for sulfuric acid-water nucleation rates for tropospheric and stratospheric conditions, J. Geophys. Res., 107, 4622, AAC3-1–AAC3-10, https://doi.org/10.1029/2002JD002184, 2002. a, b
Vehkamäki, H., Kulmala, M., Lehtinen, K. E. J., and Noppel, M.: Modelling binary homogeneous nucleation of water-sulfuric acid vapours: Parameterisation for high temperature emissions, Environ. Sci. Technol., 37, 3392–3398, https://doi.org/10.1021/es0263442, 2003. a, b
Vignati, E., Wilson, J., and Stier, P.: M7 – An efficient size-resolved aerosol microphysics module for large-scale aerosol transport models, J. Geophys. Res., 109, D22202, https://doi.org/10.1029/2003JD004485, 2004. a, b
Wang, M., Chen, D., Xiao, M., Ye, Q., Stolzenburg, D., Hofbauer, V., Ye, P., Vogel, A. L., Mauldin III, R. L., Amorim, A., Baccarini, A., Baumgartner, B., Brilke, S., Dada, L., Dias, A., Duplissy, J., Finkenzeller, H., Garmash, O., He, X.-C., Hoyle, C. R., Kim, C., Kvashnin, A., Lehtipalo, K., Fischer, L., Molteni, U., Petäjä, T., Pospisilova, V., Quéléver, L. L. J., Rissanen, M., Simon, M., Tauber, C., Tomé, A., Wagner, A. C., Weitz, L., Volkamer, R., Winkler, P. M., Kirkby, J., Worsnop, D. R., Kulmala, M., Baltensperger, U., Dommen, J., El-Haddad, I., and Donahue, N. M.: Photo-oxidation of aromatic hydrocarbons produces low-volatility organic compounds, Environ. Sci. Technol., 54, 7911–7921, https://doi.org/10.1021/acs.est.0c02100, 2020. a
Warren, D. R. and Seinfeld, J. H.: Simulation of aerosol size distribution evolution in systems with simultaneous nucleation, condensation, and coagulation, Aerosol Sci. Technol., 4, 31–43, https://doi.org/10.1080/02786828508959037, 1985. a
Weber, R. J., McMurry, P. H., Mauldin, R. L., Tanner, D., Eisele, F. L., Clarke, A. D., and Kapustin, V.: New particle formation in the remote troposphere: A comparison of observations at various sites, Geophys. Res. Lett., 26, 307–310, https://doi.org/10.1029/1998GL900308, 1999. a
Wexler, A. S. and Clegg, S. L.: Atmospheric aerosol models for systems including the ions H+,
Whitby, E. R. and McMurry, P. H.: Modal aerosol dynamics modeling, Aerosol Sci. Technol., 27, 673–688, https://doi.org/10.1080/02786829708965504, 1997. a
Wichmann, H. E. and Peters, A.: Epidemiological evidence of the effects of ultrafine particle exposure, Philos. Trans. Royal Soc. A, 358, 2751–2769, https://doi.org/10.1098/rsta.2000.0682, 2000. a
Willmott, C. J., Robeson, S. M., and Matsuura, K.: A refined index of model performance, Int. J. Climatol., 32, 2088–2094, https://doi.org/10.1002/joc.2419, 2012. a, b
Wright, D. L., Kasibhatla, P. S., McGraw, R., and Schwartz, S. E.: Description and evaluation of a six-moment aerosol microphysical module for use in atmospheric chemical transport models, J. Geophys. Res., 106, 20275–20291, https://doi.org/10.1029/2001JD900098, 2001. a
Wyslouzil, B. E., Seinfeld, J. H., Flagan, R. C., and Okuyama, K.: Binary nucleation in acid-water systems – Part 1: methanesulfonic acid-water, J. Chem. Phys., 94, 6827–6841, https://doi.org/10.1063/1.460261, 1991. a
Yu, F. and Turco, R. P.: From molecular clusters to nanoparticles: Role of ambient ionization in tropospheric aerosol formation, J. Geophys. Res., 106, 4797–4814, https://doi.org/10.1029/2000JD900539, 2001. a
Yu, F., Nadykto, A. B., Herb, J., Luo, G., Nazarenko, K. M., and Uvarova, L. A.: H2SO4–H2O–NH3 ternary ion-mediated nucleation (TIMN): kinetic-based model and comparison with CLOUD measurements, Atmos. Chem. Phys., 18, 17451–17474, https://doi.org/10.5194/acp-18-17451-2018, 2018. a
Yu, F., Nadykto, A. B., Luo, G., and Herb, J.: H2SO4–H2O binary and H2SO4–H2O–NH3 ternary homogeneous and ion-mediated nucleation: lookup tables version 1.0 for 3-D modeling application, Geosci. Model Dev., 13, 2663–2670, https://doi.org/10.5194/gmd-13-2663-2020, 2020. a, b
Zaveri, R. A., Easter, R. C., and Wexler, A. S.: A new method for multicomponent activity coefficients of electrolytes in aqueous atmospheric aerosols, J. Geophys. Res., 110, D02201, https://doi.org/10.1029/2004JD004681, 2005a. a
Zaveri, R. A., Easter, R. C., and Peter, L. K.: A computationally efficient Multicomponent Equilibrium Solver for Aerosols (MESA), J. Geophys. Res., 110, D24203, https://doi.org/10.1029/2004JD005618, 2005b. a, b, c
Zaveri, R. A., Easter, R. C., Fast, J. D., and Peters, L. K.: Model for Simulating Aerosol Interaction and Chemistry (MOSAIC), J. Geophys. Res., 113, D13204, https://doi.org/10.1029/2007JD008782, 2008.
a, b, c
Zhang, K. M. and Wexler, A. S.: Evolution of particle number distribution near roadways – Part I: Analysis of aerosol dynamics and its implications for engine emission measurement, Atmos. Environ., 38, 6643–6653, https://doi.org/10.1016/j.atmosenv.2004.06.043, 2004. a
Zhang, L., Gong, S., Padro, J., and Barrie, L.: A size-segregated particle dry deposition scheme for an atmospheric aerosol module, Atmos. Environ., 35, 549–560, https://doi.org/10.1016/S1352-2310(00)00326-5, 2001. a, b, c
Zhang, R., Khalizov, A. F., Pagels, J., Zhang, D., Xue, H., and McMurry, P. H.: Variability in morphology, hygroscopicity, and optical properties of soot particles during atmospheric processing, Proc. Natl. Acad. Sci. USA, 105, 10291–10296, https://doi.org/10.1073/pnas.0804860105, 2008. a
Zhang, R., Khalizov, A., Wang, L., Hu, M., and Xu, W.: Nucleation and growth of nanoparticles in the atmosphere, Chem. Rev., 112, 1957–2011, https://doi.org/10.1021/cr2001756, 2012. a
Zhang, X., Karl, M., Zhang, L., and Wang, J.: Influence of aviation emission on the particle number concentration near Zurich Airport, Environ. Sci. Technol., 54, 14161–14171, https://doi.org/10.1021/acs.est.0c02249, 2020. a, b
Zhang, Y., Easter, R. C., Ghan, S. J., and Abdul-Razzak, H.: Impact of aerosol size representation on modeling aerosol-cloud interactions, J. Geophys. Res., 107, 4558, https://doi.org/10.1029/2001JD001549, 2002. a
Zhong, J., Nikolova, I., Cai, X., MacKenzie, A. R., Alam, M. S., Xu, R., Singh, A., and Harrison, R. M.: Traffic-induced multicomponent ultrafine particle microphysics in the WRF v3.6.1 large eddy simulation model: General behaviour from idealised scenarios at the neighbourhood-scale, Atmos. Environ., 223, 117213, https://doi.org/10.1016/j.atmosenv.2019.117213, 2020. a
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.
The community aerosol dynamics model MAFOR includes several advanced features: coupling with an...
