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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Potential ship impact on air pollution in the Mediterranean Sea was simulated with five chemistry transport models. An evaluation of the results for NO2 and O3 air concentrations and dry deposition is presented. Emission data, modeled year and domain were the same. Model run outputs were compared to measurements from background stations. We focused on comparing model outputs regarding the concentration of regulatory pollutants and the relative ship impact on total air pollution concentrations.
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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
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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
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Janine Lückerath, Andreas Held, Holger Siebert, Michel Michalkow, and Birgit Wehner
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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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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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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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Victoria Anne Sinclair, Jenna Ritvanen, Gabin Urbancic, Irina Statnaia, 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
Atmospheric sciences
Modelling wind farm effects in HARMONIE–AROME (cycle 43.2.2) – Part 1: Implementation and evaluation
Analytical and adaptable initial conditions for dry and moist baroclinic waves in the global hydrostatic model OpenIFS (CY43R3)
Challenges of constructing and selecting the “perfect” boundary conditions for the large-eddy simulation model PALM
A machine learning approach for evaluating Southern Ocean cloud radiative biases in a global atmosphere model
Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India
How non-equilibrium aerosol chemistry impacts particle acidity: the GMXe AERosol CHEMistry (GMXe–AERCHEM, v1.0) sub-submodel of MESSy
A grid model for vertical correction of precipitable water vapor over the Chinese mainland and surrounding areas using random forest
MEXPLORER 1.0.0 – a mechanism explorer for analysis and visualization of chemical reaction pathways based on graph theory
Advances and prospects of deep learning for medium-range extreme weather forecasting
An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)
cloudbandPy 1.0: an automated algorithm for the detection of tropical–extratropical cloud bands
PyRTlib: an educational Python-based library for non-scattering atmospheric microwave radiative transfer computations
Deep learning applied to CO2 power plant emissions quantification using simulated satellite images
Sensitivity of the WRF-Chem v4.4 simulations of ozone and formaldehyde and their precursors to multiple bottom-up emission inventories over East Asia during the KORUS-AQ 2016 field campaign
Optimising urban measurement networks for CO2 flux estimation: a high-resolution observing system simulation experiment using GRAMM/GRAL
Assessment of climate biases in OpenIFS version 43r3 across model horizontal resolutions and time steps
High-resolution multi-scaling of outdoor human thermal comfort and its intra-urban variability based on machine learning
Effects of vertical grid spacing on the climate simulated in the ICON-Sapphire global storm-resolving model
Development of the tangent linear and adjoint models of the global online chemical transport model MPAS-CO2 v7.3
Impacts of updated reaction kinetics on the global GEOS-Chem simulation of atmospheric chemistry
Spatial spin-up of precipitation in limited-area convection-permitting simulations over North America using the CRCM6/GEM5.0 model
Sensitivity of atmospheric rivers to aerosol treatment in regional climate simulations: insights from the AIRA identification algorithm
The implementation of dust mineralogy in COSMO5.05-MUSCAT
Implementation of the ISORROPIA-lite aerosol thermodynamics model into the EMAC chemistry climate model (based on MESSy v2.55): implications for aerosol composition and acidity
Evaluation of surface shortwave downward radiation forecasts by the numerical weather prediction model AROME
GEO4PALM v1.1: an open-source geospatial data processing toolkit for the PALM model system
Modeling collision–coalescence in particle microphysics: numerical convergence of mean and variance of precipitation in cloud simulations using the University of Warsaw Lagrangian Cloud Model (UWLCM) 2.1
Modeling below-cloud scavenging of size-resolved particles in GEM-MACHv3.1
Impacts of a double-moment bulk cloud microphysics scheme (NDW6-G23) on aerosol fields in NICAM.19 with a global 14 km grid resolution
Sensitivity of air quality model responses to emission changes: comparison of results based on four EU inventories through FAIRMODE benchmarking methodology
A simple and realistic aerosol emission approach for use in the Thompson–Eidhammer microphysics scheme in the NOAA UFS Weather Model (version GSL global-24Feb2022)
Representing effects of surface heterogeneity in a multi-plume eddy diffusivity mass flux boundary layer parameterization
On the formation of biogenic secondary organic aerosol in chemical transport models: an evaluation of the WRF-CHIMERE (v2020r2) model with a focus over the Finnish boreal forest
The first application of a numerically exact, higher-order sensitivity analysis approach for atmospheric modelling: implementation of the hyperdual-step method in the Community Multiscale Air Quality Model (CMAQ) version 5.3.2
The ddeq Python library for point source quantification from remote sensing images (Version 1.0)
GAN-argcPredNet v2.0: a radar echo extrapolation model based on spatiotemporal process enhancement
Analysis of the GEFS-Aerosols annual budget to better understand aerosol predictions simulated in the model
A model for rapid PM2.5 exposure estimates in wildfire conditions using routinely available data: rapidfire v0.1.3
BoundaryLayerDynamics.jl v1.0: a modern codebase for atmospheric boundary-layer simulations
Investigating Ground-Level Ozone Pollution in Semi-Arid and Arid Regions of Arizona Using WRF-Chem v4.4 Modeling
The wave-age-dependent stress parameterisation (WASP) for momentum and heat turbulent fluxes at sea in SURFEX v8.1
FUME 2.0 – Flexible Universal processor for Modeling Emissions
Assessment of tropospheric ozone products from downscaled CAMS reanalysis and CAMS daily forecast using urban air quality monitoring stations in Iran
Application of regional meteorology and air quality models based on MIPS CPU Platform
Spherical air mass factors in one and two dimensions with SASKTRAN 1.6.0
An improved version of the piecewise parabolic method advection scheme: description and performance assessment in a bidimensional test case with stiff chemistry in toyCTM v1.0.1
INCHEM-Py v1.2: a community box model for indoor air chemistry
Implementation and evaluation of updated photolysis rates in the EMEP MSC-W chemistry-transport model using Cloud-J v7.3e
Representation of atmosphere-induced heterogeneity in land–atmosphere interactions in E3SM–MMFv2
How the meteorological spectral nudging impacts on aerosol radiation clouds interactions?
Jana Fischereit, Henrik Vedel, Xiaoli Guo Larsén, Natalie E. Theeuwes, Gregor Giebel, and Eigil Kaas
Geosci. Model Dev., 17, 2855–2875, https://doi.org/10.5194/gmd-17-2855-2024, https://doi.org/10.5194/gmd-17-2855-2024, 2024
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Wind farms impact local wind and turbulence. To incorporate these effects in weather forecasting, the explicit wake parameterization (EWP) is added to the forecasting model HARMONIE–AROME. We evaluate EWP using flight data above and downstream of wind farms, comparing it with an alternative wind farm parameterization and another weather model. Results affirm the correct implementation of EWP, emphasizing the necessity of accounting for wind farm effects in accurate weather forecasting.
Clément Bouvier, Daan van den Broek, Madeleine Ekblom, and Victoria A. Sinclair
Geosci. Model Dev., 17, 2961–2986, https://doi.org/10.5194/gmd-17-2961-2024, https://doi.org/10.5194/gmd-17-2961-2024, 2024
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An analytical initial background state has been developed for moist baroclinic wave simulation on an aquaplanet and implemented into OpenIFS. Seven parameters can be controlled, which are used to generate the background states and the development of baroclinic waves. The meteorological and numerical stability has been assessed. Resulting baroclinic waves have proven to be realistic and sensitive to the jet's width.
Jelena Radović, Michal Belda, Jaroslav Resler, Kryštof Eben, Martin Bureš, Jan Geletič, Pavel Krč, Hynek Řezníček, and Vladimír Fuka
Geosci. Model Dev., 17, 2901–2927, https://doi.org/10.5194/gmd-17-2901-2024, https://doi.org/10.5194/gmd-17-2901-2024, 2024
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Boundary conditions are of crucial importance for numerical model (e.g., PALM) validation studies and have a large influence on the model results, especially when studying the atmosphere of real, complex, and densely built urban environments. Our experiments with different driving conditions for the large-eddy simulation model PALM show its strong dependency on boundary conditions, which is important for the proper separation of errors coming from the boundary conditions and the model itself.
Sonya L. Fiddes, Marc D. Mallet, Alain Protat, Matthew T. Woodhouse, Simon P. Alexander, and Kalli Furtado
Geosci. Model Dev., 17, 2641–2662, https://doi.org/10.5194/gmd-17-2641-2024, https://doi.org/10.5194/gmd-17-2641-2024, 2024
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In this study we present an evaluation that considers complex, non-linear systems in a holistic manner. This study uses XGBoost, a machine learning algorithm, to predict the simulated Southern Ocean shortwave radiation bias in the ACCESS model using cloud property biases as predictors. We then used a novel feature importance analysis to quantify the role that each cloud bias plays in predicting the radiative bias, laying the foundation for advanced Earth system model evaluation and development.
Gaurav Govardhan, Sachin D. Ghude, Rajesh Kumar, Sumit Sharma, Preeti Gunwani, Chinmay Jena, Prafull Yadav, Shubhangi Ingle, Sreyashi Debnath, Pooja Pawar, Prodip Acharja, Rajmal Jat, Gayatry Kalita, Rupal Ambulkar, Santosh Kulkarni, Akshara Kaginalkar, Vijay K. Soni, Ravi S. Nanjundiah, and Madhavan Rajeevan
Geosci. Model Dev., 17, 2617–2640, https://doi.org/10.5194/gmd-17-2617-2024, https://doi.org/10.5194/gmd-17-2617-2024, 2024
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A newly developed air quality forecasting framework, Decision Support System (DSS), for air quality management in Delhi, India, provides source attribution with numerous emission reduction scenarios besides forecasts. DSS shows that during post-monsoon and winter seasons, Delhi and its neighboring districts contribute to 30 %–40 % each to pollution in Delhi. On average, a 40 % reduction in the emissions in Delhi and the surrounding districts would result in a 24 % reduction in Delhi's pollution.
Simon Rosanka, Holger Tost, Rolf Sander, Patrick Jöckel, Astrid Kerkweg, and Domenico Taraborrelli
Geosci. Model Dev., 17, 2597–2615, https://doi.org/10.5194/gmd-17-2597-2024, https://doi.org/10.5194/gmd-17-2597-2024, 2024
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The capabilities of the Modular Earth Submodel System (MESSy) are extended to account for non-equilibrium aqueous-phase chemistry in the representation of deliquescent aerosols. When applying the new development in a global simulation, we find that MESSy's bias in modelling routinely observed reduced inorganic aerosol mass concentrations, especially in the United States. Furthermore, the representation of fine-aerosol pH is particularly improved in the marine boundary layer.
Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Huang, and Feijuan Li
Geosci. Model Dev., 17, 2569–2581, https://doi.org/10.5194/gmd-17-2569-2024, https://doi.org/10.5194/gmd-17-2569-2024, 2024
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In this study, we have developed a model (RF-PWV) to characterize precipitable water vapor (PWV) variation with altitude in the study area. RF-PWV can significantly reduce errors in vertical correction, enhance PWV fusion product accuracy, and provide insights into PWV vertical distribution, thereby contributing to climate research.
Rolf Sander
Geosci. Model Dev., 17, 2419–2425, https://doi.org/10.5194/gmd-17-2419-2024, https://doi.org/10.5194/gmd-17-2419-2024, 2024
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The open-source software MEXPLORER 1.0.0 is presented here. The program can be used to analyze, reduce, and visualize complex chemical reaction mechanisms. The mathematics behind the tool is based on graph theory: chemical species are represented as vertices, and reactions as edges. MEXPLORER is a community model published under the GNU General Public License.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 2347–2358, https://doi.org/10.5194/gmd-17-2347-2024, https://doi.org/10.5194/gmd-17-2347-2024, 2024
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In the last decades, weather forecasting up to 15 d into the future has been dominated by physics-based numerical models. Recently, deep learning models have challenged this paradigm. However, the latter models may struggle when forecasting weather extremes. In this article, we argue for deep learning models specifically designed to handle extreme events, and we propose a foundational framework to develop such models.
Stefan Rahimi, Lei Huang, Jesse Norris, Alex Hall, Naomi Goldenson, Will Krantz, Benjamin Bass, Chad Thackeray, Henry Lin, Di Chen, Eli Dennis, Ethan Collins, Zachary J. Lebo, Emily Slinskey, Sara Graves, Surabhi Biyani, Bowen Wang, Stephen Cropper, and the UCLA Center for Climate Science Team
Geosci. Model Dev., 17, 2265–2286, https://doi.org/10.5194/gmd-17-2265-2024, https://doi.org/10.5194/gmd-17-2265-2024, 2024
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Here, we project future climate across the western United States through the end of the 21st century using a regional climate model, embedded within 16 latest-generation global climate models, to provide the community with a high-resolution physically based ensemble of climate data for use at local scales. Strengths and weaknesses of the data are frankly discussed as we overview the downscaled dataset.
Romain Pilon and Daniela I. V. Domeisen
Geosci. Model Dev., 17, 2247–2264, https://doi.org/10.5194/gmd-17-2247-2024, https://doi.org/10.5194/gmd-17-2247-2024, 2024
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This paper introduces a new method for detecting atmospheric cloud bands to identify long convective cloud bands that extend from the tropics to the midlatitudes. The algorithm allows for easy use and enables researchers to study the life cycle and climatology of cloud bands and associated rainfall. This method provides insights into the large-scale processes involved in cloud band formation and their connections between different regions, as well as differences across ocean basins.
Salvatore Larosa, Domenico Cimini, Donatello Gallucci, Saverio Teodosio Nilo, and Filomena Romano
Geosci. Model Dev., 17, 2053–2076, https://doi.org/10.5194/gmd-17-2053-2024, https://doi.org/10.5194/gmd-17-2053-2024, 2024
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PyRTlib is an attractive educational tool because it provides a flexible and user-friendly way to broadly simulate how electromagnetic radiation travels through the atmosphere as it interacts with atmospheric constituents (such as gases, aerosols, and hydrometeors). PyRTlib is a so-called radiative transfer model; these are commonly used to simulate and understand remote sensing observations from ground-based, airborne, or satellite instruments.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 17, 1995–2014, https://doi.org/10.5194/gmd-17-1995-2024, https://doi.org/10.5194/gmd-17-1995-2024, 2024
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Our research presents an innovative approach to estimating power plant CO2 emissions from satellite images of the corresponding plumes such as those from the forthcoming CO2M satellite constellation. The exploitation of these images is challenging due to noise and meteorological uncertainties. To overcome these obstacles, we use a deep learning neural network trained on simulated CO2 images. Our method outperforms alternatives, providing a positive perspective for the analysis of CO2M images.
Kyoung-Min Kim, Si-Wan Kim, Seunghwan Seo, Donald R. Blake, Seogju Cho, James H. Crawford, Louisa K. Emmons, Alan Fried, Jay R. Herman, Jinkyu Hong, Jinsang Jung, Gabriele G. Pfister, Andrew J. Weinheimer, Jung-Hun Woo, and Qiang Zhang
Geosci. Model Dev., 17, 1931–1955, https://doi.org/10.5194/gmd-17-1931-2024, https://doi.org/10.5194/gmd-17-1931-2024, 2024
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Three emission inventories were evaluated for East Asia using data acquired during a field campaign in 2016. The inventories successfully reproduced the daily variations of ozone and nitrogen dioxide. However, the spatial distributions of model ozone did not fully agree with the observations. Additionally, all simulations underestimated carbon monoxide and volatile organic compound (VOC) levels. Increasing VOC emissions over South Korea resulted in improved ozone simulations.
Sanam Noreen Vardag and Robert Maiwald
Geosci. Model Dev., 17, 1885–1902, https://doi.org/10.5194/gmd-17-1885-2024, https://doi.org/10.5194/gmd-17-1885-2024, 2024
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We use the atmospheric transport model GRAMM/GRAL in a Bayesian inversion to estimate urban CO2 emissions on a neighbourhood scale. We analyse the effect of varying number, precision and location of CO2 sensors for CO2 flux estimation. We further test the inclusion of co-emitted species and correlation in the inversion. The study showcases the general usefulness of GRAMM/GRAL in measurement network design.
Abhishek Savita, Joakim Kjellsson, Robin Pilch Kedzierski, Mojib Latif, Tabea Rahm, Sebastian Wahl, and Wonsun Park
Geosci. Model Dev., 17, 1813–1829, https://doi.org/10.5194/gmd-17-1813-2024, https://doi.org/10.5194/gmd-17-1813-2024, 2024
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The OpenIFS model is used to examine the impact of horizontal resolutions (HR) and model time steps. We find that the surface wind biases over the oceans, in particular the Southern Ocean, are sensitive to the model time step and HR, with the HR having the smallest biases. When using a coarse-resolution model with a shorter time step, a similar improvement is also found. Climate biases can be reduced in the OpenIFS model at a cheaper cost by reducing the time step rather than increasing the HR.
Ferdinand Briegel, Jonas Wehrle, Dirk Schindler, and Andreas Christen
Geosci. Model Dev., 17, 1667–1688, https://doi.org/10.5194/gmd-17-1667-2024, https://doi.org/10.5194/gmd-17-1667-2024, 2024
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We present a new approach to model heat stress in cities using artificial intelligence (AI). We show that the AI model is fast in terms of prediction but accurate when evaluated with measurements. The fast-predictive AI model enables several new potential applications, including heat stress prediction and warning; downscaling of potential future climates; evaluation of adaptation effectiveness; and, more fundamentally, development of guidelines to support urban planning and policymaking.
Hauke Schmidt, Sebastian Rast, Jiawei Bao, Amrit Cassim, Shih-Wei Fang, Diego Jimenez-de la Cuesta, Paul Keil, Lukas Kluft, Clarissa Kroll, Theresa Lang, Ulrike Niemeier, Andrea Schneidereit, Andrew I. L. Williams, and Bjorn Stevens
Geosci. Model Dev., 17, 1563–1584, https://doi.org/10.5194/gmd-17-1563-2024, https://doi.org/10.5194/gmd-17-1563-2024, 2024
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A recent development in numerical simulations of the global atmosphere is the increase in horizontal resolution to grid spacings of a few kilometers. However, the vertical grid spacing of these models has not been reduced at the same rate as the horizontal grid spacing. Here, we assess the effects of much finer vertical grid spacings, in particular the impacts on cloud quantities and the atmospheric energy balance.
Tao Zheng, Sha Feng, Jeffrey Steward, Xiaoxu Tian, David Baker, and Martin Baxter
Geosci. Model Dev., 17, 1543–1562, https://doi.org/10.5194/gmd-17-1543-2024, https://doi.org/10.5194/gmd-17-1543-2024, 2024
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The tangent linear and adjoint models have been successfully implemented in the MPAS-CO2 system, which has undergone rigorous accuracy testing. This development lays the groundwork for a global carbon flux data assimilation system, which offers the flexibility of high-resolution focus on specific areas, while maintaining a coarser resolution elsewhere. This approach significantly reduces computational costs and is thus perfectly suited for future CO2 geostationery and imager satellites.
Kelvin H. Bates, Mathew J. Evans, Barron H. Henderson, and Daniel J. Jacob
Geosci. Model Dev., 17, 1511–1524, https://doi.org/10.5194/gmd-17-1511-2024, https://doi.org/10.5194/gmd-17-1511-2024, 2024
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Accurate representation of rates and products of chemical reactions in atmospheric models is crucial for simulating concentrations of pollutants and climate forcers. We update the widely used GEOS-Chem atmospheric chemistry model with reaction parameters from recent compilations of experimental data and demonstrate the implications for key atmospheric chemical species. The updates decrease tropospheric CO mixing ratios and increase stratospheric nitrogen oxide mixing ratios, among other changes.
François Roberge, Alejandro Di Luca, René Laprise, Philippe Lucas-Picher, and Julie Thériault
Geosci. Model Dev., 17, 1497–1510, https://doi.org/10.5194/gmd-17-1497-2024, https://doi.org/10.5194/gmd-17-1497-2024, 2024
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Our study addresses a challenge in dynamical downscaling using regional climate models, focusing on the lack of small-scale features near the boundaries. We introduce a method to identify this “spatial spin-up” in precipitation simulations. Results show spin-up distances up to 300 km, varying by season and driving variable. Double nesting with comprehensive variables (e.g. microphysical variables) offers advantages. Findings will help optimize simulations for better climate projections.
Eloisa Raluy-López, Juan Pedro Montávez, and Pedro Jiménez-Guerrero
Geosci. Model Dev., 17, 1469–1495, https://doi.org/10.5194/gmd-17-1469-2024, https://doi.org/10.5194/gmd-17-1469-2024, 2024
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Atmospheric rivers (ARs) represent a significant source of water but are also related to extreme precipitation events. Here, we present a new regional-scale AR identification algorithm and apply it to three simulations that include aerosol interactions at different levels. The results show that aerosols modify the intensity and trajectory of ARs and redistribute the AR-related precipitation. Thus, the correct inclusion of aerosol effects is important in the simulation of AR behavior.
Sofía Gómez Maqueo Anaya, Dietrich Althausen, Matthias Faust, Holger Baars, Bernd Heinold, Julian Hofer, Ina Tegen, Albert Ansmann, Ronny Engelmann, Annett Skupin, Birgit Heese, and Kerstin Schepanski
Geosci. Model Dev., 17, 1271–1295, https://doi.org/10.5194/gmd-17-1271-2024, https://doi.org/10.5194/gmd-17-1271-2024, 2024
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Mineral dust aerosol particles vary greatly in their composition depending on source region, which leads to different physicochemical properties. Most atmosphere–aerosol models consider mineral dust aerosols to be compositionally homogeneous, which ultimately increases model uncertainty. Here, we present an approach to explicitly consider the heterogeneity of the mineralogical composition for simulations of the Saharan atmospheric dust cycle with regard to dust transport towards the Atlantic.
Alexandros Milousis, Alexandra P. Tsimpidi, Holger Tost, Spyros N. Pandis, Athanasios Nenes, Astrid Kiendler-Scharr, and Vlassis A. Karydis
Geosci. Model Dev., 17, 1111–1131, https://doi.org/10.5194/gmd-17-1111-2024, https://doi.org/10.5194/gmd-17-1111-2024, 2024
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This study aims to evaluate the newly developed ISORROPIA-lite aerosol thermodynamic module within the EMAC model and explore discrepancies in global atmospheric simulations of aerosol composition and acidity by utilizing different aerosol phase states. Even though local differences were found in regions where the RH ranged from 20 % to 60 %, on a global scale the results are similar. Therefore, ISORROPIA-lite can be a reliable and computationally effective alternative to ISORROPIA II in EMAC.
Marie-Adèle Magnaldo, Quentin Libois, Sébastien Riette, and Christine Lac
Geosci. Model Dev., 17, 1091–1109, https://doi.org/10.5194/gmd-17-1091-2024, https://doi.org/10.5194/gmd-17-1091-2024, 2024
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With the worldwide development of the solar energy sector, the need for reliable solar radiation forecasts has significantly increased. However, meteorological models that predict, among others things, solar radiation have errors. Therefore, we wanted to know in which situtaions these errors are most significant. We found that errors mostly occur in cloudy situations, and different errors were highlighted depending on the cloud altitude. Several potential sources of errors were identified.
Dongqi Lin, Jiawei Zhang, Basit Khan, Marwan Katurji, and Laura E. Revell
Geosci. Model Dev., 17, 815–845, https://doi.org/10.5194/gmd-17-815-2024, https://doi.org/10.5194/gmd-17-815-2024, 2024
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GEO4PALM is an open-source tool to generate static input for the Parallelized Large-Eddy Simulation (PALM) model system. Geospatial static input is essential for realistic PALM simulations. However, existing tools fail to generate PALM's geospatial static input for most regions. GEO4PALM is compatible with diverse geospatial data sources and provides access to free data sets. In addition, this paper presents two application examples, which show successful PALM simulations using GEO4PALM.
Piotr Zmijewski, Piotr Dziekan, and Hanna Pawlowska
Geosci. Model Dev., 17, 759–780, https://doi.org/10.5194/gmd-17-759-2024, https://doi.org/10.5194/gmd-17-759-2024, 2024
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In computer simulations of clouds it is necessary to model the myriad of droplets that constitute a cloud. A popular method for this is to use so-called super-droplets (SDs), each representing many real droplets. It has remained a challenge to model collisions of SDs. We study how precipitation in a cumulus cloud depends on the number of SDs. Surprisingly, we do not find convergence in mean precipitation even for numbers of SDs much larger than typically used in simulations.
Roya Ghahreman, Wanmin Gong, Paul A. Makar, Alexandru Lupu, Amanda Cole, Kulbir Banwait, Colin Lee, and Ayodeji Akingunola
Geosci. Model Dev., 17, 685–707, https://doi.org/10.5194/gmd-17-685-2024, https://doi.org/10.5194/gmd-17-685-2024, 2024
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The article explores the impact of different representations of below-cloud scavenging on model biases. A new scavenging scheme and precipitation-phase partitioning improve the model's performance, with better SO42- scavenging and wet deposition of NO3- and NH4+.
Daisuke Goto, Tatsuya Seiki, Kentaroh Suzuki, Hisashi Yashiro, and Toshihiko Takemura
Geosci. Model Dev., 17, 651–684, https://doi.org/10.5194/gmd-17-651-2024, https://doi.org/10.5194/gmd-17-651-2024, 2024
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Global climate models with coarse grid sizes include uncertainties about the processes in aerosol–cloud–precipitation interactions. To reduce these uncertainties, here we performed numerical simulations using a new version of our global aerosol transport model with a finer grid size over a longer period than in our previous study. As a result, we found that the cloud microphysics module influences the aerosol distributions through both aerosol wet deposition and aerosol–cloud interactions.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, Enrico Pisoni, and Bertrand Bessagnet
Geosci. Model Dev., 17, 587–606, https://doi.org/10.5194/gmd-17-587-2024, https://doi.org/10.5194/gmd-17-587-2024, 2024
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In our study the robustness of the model responses to emission reductions in the EU is assessed when the emission data are changed. Our findings are particularly important to better understand the uncertainties associated to the emission inventories and how these uncertainties impact the level of accuracy of the resulting air quality modelling, which is a key for designing air quality plans. Also crucial is the choice of indicator to avoid misleading interpretations of the results.
Haiqin Li, Georg A. Grell, Ravan Ahmadov, Li Zhang, Shan Sun, Jordan Schnell, and Ning Wang
Geosci. Model Dev., 17, 607–619, https://doi.org/10.5194/gmd-17-607-2024, https://doi.org/10.5194/gmd-17-607-2024, 2024
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We developed a simple and realistic method to provide aerosol emissions for aerosol-aware microphysics in a numerical weather forecast model. The cloud-radiation differences between the experimental (EXP) and control (CTL) experiments responded to the aerosol differences. The strong positive precipitation biases over North America and Europe from the CTL run were significantly reduced in the EXP run. This study shows that a realistic representation of aerosol emissions should be considered.
Nathan Patrick Arnold
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-245, https://doi.org/10.5194/gmd-2023-245, 2024
Revised manuscript accepted for GMD
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Earth System Models often represent the land surface at smaller scales than the atmosphere, but surface-atmosphere coupling uses only aggregated surface properties. This study presents a method to allow heterogeneous surface properties to modify boundary layer updrafts. The method is tested in single column experiments. Updraft properties are found to reasonably covary with surface conditions, and simulated boundary layer variability is enhanced over more heterogeneous land surfaces.
Giancarlo Ciarelli, Sara Tahvonen, Arineh Cholakian, Manuel Bettineschi, Bruno Vitali, Tuukka Petäjä, and Federico Bianchi
Geosci. Model Dev., 17, 545–565, https://doi.org/10.5194/gmd-17-545-2024, https://doi.org/10.5194/gmd-17-545-2024, 2024
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The terrestrial ecosystem releases large quantities of biogenic gases in the Earth's Atmosphere. These gases can effectively be converted into so-called biogenic aerosol particles and, eventually, affect the Earth's climate. Climate prediction varies greatly depending on how these processes are represented in model simulations. In this study, we present a detailed model evaluation analysis aimed at understanding the main source of uncertainty in predicting the formation of biogenic aerosols.
Jiachen Liu, Eric Chen, and Shannon L. Capps
Geosci. Model Dev., 17, 567–585, https://doi.org/10.5194/gmd-17-567-2024, https://doi.org/10.5194/gmd-17-567-2024, 2024
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Air pollution harms human life and ecosystems, but its sources are complex. Scientists and policy makers use air pollution models to advance knowledge and inform control strategies. We implemented a recently developed numeral system to relate any set of model inputs, like pollutant emissions from a given activity, to all model outputs, like concentrations of pollutants harming human health. This approach will be straightforward to update when scientists discover new processes in the atmosphere.
Gerrit Kuhlmann, Erik F. M. Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
EGUsphere, https://doi.org/10.5194/egusphere-2023-2936, https://doi.org/10.5194/egusphere-2023-2936, 2024
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We present a Python software library for data-driven emission quantification (ddeq). It can be used to determine the emissions of hot spots (cities, power plants and industry) from remote sensing images using different methods. ddeq can be extended for new datasets and methods, providing a powerful community tool for users and developers. The application of the methods is shown using Jupyter Notebooks included in the library.
Kun Zheng, Qiya Tan, Huihua Ruan, Jinbiao Zhang, Cong Luo, Siyu Tang, Yunlei Yi, Yugang Tian, and Jianmei Cheng
Geosci. Model Dev., 17, 399–413, https://doi.org/10.5194/gmd-17-399-2024, https://doi.org/10.5194/gmd-17-399-2024, 2024
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Radar echo extrapolation is the common method in precipitation nowcasting. Deep learning has potential in extrapolation. However, the existing models have low prediction accuracy for heavy rainfall. In this study, the prediction accuracy is improved by suppressing the blurring effect of rain distribution and reducing the negative bias. The results show that our model has better performance, which is useful for urban operation and flood prevention.
Li Pan, Partha S. Bhattacharjee, Li Zhang, Raffaele Montuoro, Barry Baker, Jeff McQueen, Georg A. Grell, Stuart A. McKeen, Shobha Kondragunta, Xiaoyang Zhang, Gregory J. Frost, Fanglin Yang, and Ivanka Stajner
Geosci. Model Dev., 17, 431–447, https://doi.org/10.5194/gmd-17-431-2024, https://doi.org/10.5194/gmd-17-431-2024, 2024
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A GEFS-Aerosols simulation was conducted from 1 September 2019 to 30 September 2020 to evaluate the model performance of GEFS-Aerosols. The purpose of this study was to understand how aerosol chemical and physical processes affect ambient aerosol concentrations by placing aerosol wet deposition, dry deposition, reactions, gravitational deposition, and emissions into the aerosol mass balance equation.
Sean Raffuse, Susan O'Neill, and Rebecca Schmidt
Geosci. Model Dev., 17, 381–397, https://doi.org/10.5194/gmd-17-381-2024, https://doi.org/10.5194/gmd-17-381-2024, 2024
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Large wildfires are increasing throughout the western United States, and wildfire smoke is hazardous to public health. We developed a suite of tools called rapidfire for estimating particle pollution during wildfires using routinely available data sets. rapidfire uses official air monitoring, satellite data, meteorology, smoke modeling, and low-cost sensors. Estimates from rapidfire compare well with ground monitors and are being used in public health studies across California.
Manuel F. Schmid, Marco G. Giometto, Gregory A. Lawrence, and Marc B. Parlange
Geosci. Model Dev., 17, 321–333, https://doi.org/10.5194/gmd-17-321-2024, https://doi.org/10.5194/gmd-17-321-2024, 2024
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Turbulence-resolving flow models have strict performance requirements, as simulations often run for weeks using hundreds of processes. Many flow scenarios also require the flexibility to modify physical and numerical models for problem-specific requirements. With a new code written in Julia we hope to make such adaptations easier without compromising on performance. In this paper we discuss the modeling approach and present validation and performance results.
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-234, https://doi.org/10.5194/gmd-2023-234, 2024
Revised manuscript accepted for GMD
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This research focuses on surface ozone (O3) pollution in Arizona, a historically air quality-challenged arid/semi-arid region in the US. The unique characteristics of semi-arid/arid regions, e.g., intense heat, minimal moisture, persistent desert shrubs, play a vital role in comprehending O3 exceedances. Using the WRF-Chem model, we analyzed O3 levels in the pre-monsoon month, revealing the model's skill in capturing diurnal and MDA8 O3 levels.
Marie-Noëlle Bouin, Cindy Lebeaupin Brossier, Sylvie Malardel, Aurore Voldoire, and César Sauvage
Geosci. Model Dev., 17, 117–141, https://doi.org/10.5194/gmd-17-117-2024, https://doi.org/10.5194/gmd-17-117-2024, 2024
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In numerical models, the turbulent exchanges of heat and momentum at the air–sea interface are not represented explicitly but with parameterisations depending on the surface parameters. A new parameterisation of turbulent fluxes (WASP) has been implemented in the surface model SURFEX v8.1 and validated on four case studies. It combines a close fit to observations including cyclonic winds, a dependency on the wave growth rate, and the possibility of being used in atmosphere–wave coupled models.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
EGUsphere, https://doi.org/10.5194/egusphere-2023-2740, https://doi.org/10.5194/egusphere-2023-2740, 2024
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For modeling atmospheric chemistry, it is necessary to provide data on emissions of pollutants. These can come from various sources and in various forms and preprocessing of the data to be ingestible by chemistry models can be quite challenging. We developed the FUME processor to use a database layer that internally transforms all input data into a rigid structure facilitating further processing to allow emission processing from continental to street scale.
Najmeh Kaffashzadeh and Abbas Ali Aliakbari Bidokhti
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-226, https://doi.org/10.5194/gmd-2023-226, 2024
Revised manuscript accepted for GMD
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Reanalysis data have been widely used as an initial condition for the daily forecast of the atmosphere or boundary conditions in regional models, for the study of climate change, and as proxies to complement insufficient in situ measurements. This paper assesses the capability of two state-of-the-art global datasets in simulating surface ozone over Iran using a new methodology.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
EGUsphere, https://doi.org/10.5194/egusphere-2023-2962, https://doi.org/10.5194/egusphere-2023-2962, 2024
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There are relatively limited researches on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPU, have distinct advantages in energy efficiency and scalability. In this study, the air quality modeling system can run stably on MIPS CPU platform, and the experiment results verify the stability of scientific computing on the platform. The work provides a technical foundation for the scientific application based on MIPS CPU platforms.
Lukas Fehr, Chris McLinden, Debora Griffin, Daniel Zawada, Doug Degenstein, and Adam Bourassa
Geosci. Model Dev., 16, 7491–7507, https://doi.org/10.5194/gmd-16-7491-2023, https://doi.org/10.5194/gmd-16-7491-2023, 2023
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This work highlights upgrades to SASKTRAN, a model that simulates sunlight interacting with the atmosphere to help measure trace gases. The upgrades were verified by detailed comparisons between different numerical methods. A case study was performed using SASKTRAN’s multidimensional capabilities, which found that ignoring horizontal variation in the atmosphere (a common practice in the field) can introduce non-negligible errors where there is snow or high pollution.
Sylvain Mailler, Romain Pennel, Laurent Menut, and Arineh Cholakian
Geosci. Model Dev., 16, 7509–7526, https://doi.org/10.5194/gmd-16-7509-2023, https://doi.org/10.5194/gmd-16-7509-2023, 2023
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We show that a new advection scheme named PPM + W (piecewise parabolic method + Walcek) offers geoscientific modellers an alternative, high-performance scheme designed for Cartesian-grid advection, with improved performance over the classical PPM scheme. The computational cost of PPM + W is not higher than that of PPM. With improved accuracy and controlled computational cost, this new scheme may find applications in chemistry-transport models, ocean models or atmospheric circulation models.
David R. Shaw, Toby J. Carter, Helen L. Davies, Ellen Harding-Smith, Elliott C. Crocker, Georgia Beel, Zixu Wang, and Nicola Carslaw
Geosci. Model Dev., 16, 7411–7431, https://doi.org/10.5194/gmd-16-7411-2023, https://doi.org/10.5194/gmd-16-7411-2023, 2023
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Exposure to air pollution is one of the greatest risks to human health, and it is indoors, where we spend upwards of 90 % of our time, that our exposure is greatest. The INdoor CHEMical model in Python (INCHEM-Py) is a new, community-led box model that tracks the evolution and fate of atmospheric chemical pollutants indoors. We have shown the processes simulated by INCHEM-Py, its ability to model experimental data and how it may be used to develop further understanding of indoor air chemistry.
Willem E. van Caspel, David Simpson, Jan Eiof Jonson, Anna M. K. Benedictow, Yao Ge, Alcide di Sarra, Giandomenico Pace, Massimo Vieno, Hannah L. Walker, and Mathew R. Heal
Geosci. Model Dev., 16, 7433–7459, https://doi.org/10.5194/gmd-16-7433-2023, https://doi.org/10.5194/gmd-16-7433-2023, 2023
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Radiation coming from the sun is essential to atmospheric chemistry, driving the breakup, or photodissociation, of atmospheric molecules. This in turn affects the chemical composition and reactivity of the atmosphere. The representation of photodissociation effects is therefore essential in atmospheric chemistry modeling. One such model is the EMEP MSC-W model, for which a new way of calculating the photodissociation rates is tested and evaluated in this paper.
Jungmin Lee, Walter M. Hannah, and David C. Bader
Geosci. Model Dev., 16, 7275–7287, https://doi.org/10.5194/gmd-16-7275-2023, https://doi.org/10.5194/gmd-16-7275-2023, 2023
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Representing accurate land–atmosphere interaction processes is overlooked in weather and climate models. In this study, we propose three methods to represent land–atmosphere coupling in the Energy Exascale Earth System Model (E3SM) with the Multi-scale Modeling Framework (MMF) approach. In this study, we introduce spatially homogeneous and heterogeneous land–atmosphere interaction processes within the cloud-resolving model domain. Our 5-year simulations reveal only small differences.
Laurent Menut, Bertrand Bessagnet, Arineh Cholakian, Guillaume Siour, Sylvain Mailler, and Romain Pennel
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-209, https://doi.org/10.5194/gmd-2023-209, 2023
Revised manuscript accepted for GMD
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This study is about the modelling of the atmospheric composition in Europe and during the summer 2022, when massive wildfires were observed. It is a sensitivity study dedicated to the relative impact of two modelling processes able to modify the meteorology used for the calculation of the atmospheric chemistry and transport of pollutants.
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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...
