Articles | Volume 15, issue 18
https://doi.org/10.5194/gmd-15-7257-2022
© 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-15-7257-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Atmospherically Relevant Chemistry and Aerosol box model – ARCA box (version 1.2)
Petri Clusius
CORRESPONDING AUTHOR
Institute for Atmospheric and Earth Systems Research/Physics, University of Helsinki, P.O. Box 64, 00014 Helsinki, Finland
Carlton Xavier
Institute for Atmospheric and Earth Systems Research/Physics, University of Helsinki, P.O. Box 64, 00014 Helsinki, Finland
Lukas Pichelstorfer
Department of Chemistry and Physics of Materials, University of Salzburg, 5020, Salzburg, Austria
Putian Zhou
Institute for Atmospheric and Earth Systems Research/Physics, University of Helsinki, P.O. Box 64, 00014 Helsinki, Finland
Tinja Olenius
Research Department, Unit of Meteorology/Environment and Climate,
Swedish Meteorological and Hydrological Institute (SMHI), 601 76 Norrköping, Sweden
Pontus Roldin
Division of Nuclear Physics, Department of Physics, Lund University, P.O. Box 118, 221 00 Lund, Sweden
Michael Boy
Institute for Atmospheric and Earth Systems Research/Physics, University of Helsinki, P.O. Box 64, 00014 Helsinki, Finland
LUT School of Engineering Science, Lappeenranta-Lahti University of Technology, P.O. Box 20, 53851 Lappeenranta, Finland
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Lukas Pichelstorfer, Pontus Roldin, Matti Rissanen, Noora Hyttinen, Olga Garmash, Carlton Xavier, Putian Zhou, Petri Clusius, Benjamin Foreback, Thomas Golin Almeida, Chenjuan Deng, Metin Baykara, Theo Kurten, and Michael Boy
EGUsphere, https://doi.org/10.5194/egusphere-2023-1415, https://doi.org/10.5194/egusphere-2023-1415, 2023
Preprint archived
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Secondary organic aerosols (SOA) form effectively from gaseous precursors via a process called autoxidation. While key chemical reaction types seem to be known, no general description of autoxidation chemistry exists. In the present work, we present a method to create autoxidation chemistry schemes for any atmospherically relevant hydrocarbon. We exemplarily investigate benzene and its potential to form aerosols. We found that autoxidation, under some conditions, can dominate the SOA formation.
Sanna Saarikoski, Heidi Hellén, Arnaud P. Praplan, Simon Schallhart, Petri Clusius, Jarkko V. Niemi, Anu Kousa, Toni Tykkä, Rostislav Kouznetsov, Minna Aurela, Laura Salo, Topi Rönkkö, Luis M. F. Barreira, Liisa Pirjola, and Hilkka Timonen
Atmos. Chem. Phys., 23, 2963–2982, https://doi.org/10.5194/acp-23-2963-2023, https://doi.org/10.5194/acp-23-2963-2023, 2023
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This study elucidates properties and sources of volatile organic compounds (VOCs) and organic aerosol (OA) in a traffic environment. Anthropogenic VOCs (aVOCs) were clearly higher than biogenic VOCs (bVOCs), but bVOCs produced a larger portion of oxidation products. OA consisted mostly of oxygenated OA, representing secondary OA (SOA). SOA was partly associated with bVOCs, but it was also related to long-range transport. Primary OA originated mostly from traffic.
Carlton Xavier, Metin Baykara, Robin Wollesen de Jonge, Barbara Altstädter, Petri Clusius, Ville Vakkari, Roseline Thakur, Lisa Beck, Silvia Becagli, Mirko Severi, Rita Traversi, Radovan Krejci, Peter Tunved, Mauro Mazzola, Birgit Wehner, Mikko Sipilä, Markku Kulmala, Michael Boy, and Pontus Roldin
Atmos. Chem. Phys., 22, 10023–10043, https://doi.org/10.5194/acp-22-10023-2022, https://doi.org/10.5194/acp-22-10023-2022, 2022
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The focus of this work is to study and improve our understanding of processes involved in the formation and growth of new particles in a remote Arctic marine environment. We run the 1D model ADCHEM along air mass trajectories arriving at Ny-Ålesund in May 2018. The model finds that ion-mediated H2SO4–NH3 nucleation can explain the observed new particle formation at Ny-Ålesund. The growth of particles is driven via H2SO4 condensation and formation of methane sulfonic acid in the aqueous phase.
Dean Chen, Putian Zhou, Tuomo Nieminen, Pontus Roldin, Ximeng Qi, Petri Clusius, Carlton Xavier, Lukas Pichelstorfer, Markku Kulmala, Pekka Rantala, Juho Aalto, Nina Sarnela, Pasi Kolari, Petri Keronen, Matti P. Rissanen, Metin Baykara, and Michael Boy
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-128, https://doi.org/10.5194/acp-2020-128, 2020
Preprint withdrawn
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Atmospheric oxidants OH, O3 and NO3 dominate the atmospheric oxidation capacity, and sulfuric acid (H2SO4) is considered as a main driver for new particle formation events. We studied how the trends of these atmospheric oxidants and H2SO4 changed in southern Finland during the past 12 years and discussed how these trends related to decreasing emissions of air pollutants in Europe. Our results showed that OH increased by 1.56 % yr−1 at daytime and NO3 decreased by 3.92 % yr−1 at nighttime.
Fredrik Lagergren, Robert G. Björk, Camilla Andersson, Danijel Belušić, Mats P. Björkman, Erik Kjellström, Petter Lind, David Lindstedt, Tinja Olenius, Håkan Pleijel, Gunhild Rosqvist, and Paul A. Miller
Biogeosciences, 21, 1093–1116, https://doi.org/10.5194/bg-21-1093-2024, https://doi.org/10.5194/bg-21-1093-2024, 2024
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The Fennoscandian boreal and mountain regions harbour a wide range of ecosystems sensitive to climate change. A new, highly resolved high-emission climate scenario enabled modelling of the vegetation development in this region at high resolution for the 21st century. The results show dramatic south to north and low- to high-altitude shifts of vegetation zones, especially for the open tundra environments, which will have large implications for nature conservation, reindeer husbandry and forestry.
Carl Svenhag, Moa Kristina Sporre, Tinja Olenius, Daniel Yazgi, Sara Marie Blichner, Lars Peter Nieradzik, and Pontus Roldin
EGUsphere, https://doi.org/10.5194/egusphere-2023-2665, https://doi.org/10.5194/egusphere-2023-2665, 2024
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Our research shows the importance of modeling new particle formation (NPF) and growth of particles in the atmosphere on a global scale, as they influence the outcomes of clouds and our climate. With the global model EC-Earth3 we showed that using a new method for NPF modeling, which includes new detailed processes with NH3 and H2SO4, significantly impacted the number of particles in the air and clouds. It also changed the radiation balance in the same magnitude as man-made greenhouse emissions.
Putian Zhou, Zhengyao Lu, Jukka-Pekka Keskinen, Qiong Zhang, Juha Lento, Jianpu Bian, Twan van Noije, Philippe Le Sager, Veli-Matti Kerminen, Markku Kulmala, Michael Boy, and Risto Makkonen
Clim. Past, 19, 2445–2462, https://doi.org/10.5194/cp-19-2445-2023, https://doi.org/10.5194/cp-19-2445-2023, 2023
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A Green Sahara with enhanced rainfall and larger vegetation cover existed in northern Africa about 6000 years ago. Biosphere–atmosphere interactions are found to be critical to explaining this wet period. Based on modeled vegetation reconstruction data, we simulated dust emissions and aerosol formation, which are key factors in biosphere–atmosphere interactions. Our results also provide a benchmark of aerosol climatology for future paleo-climate simulation experiments.
Daniel Yazgi and Tinja Olenius
Geosci. Model Dev., 16, 5237–5249, https://doi.org/10.5194/gmd-16-5237-2023, https://doi.org/10.5194/gmd-16-5237-2023, 2023
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We present flexible tools to implement aerosol formation rate predictions in climate and chemical transport models. New-particle formation is a significant but uncertain factor affecting aerosol numbers and an active field within molecular modeling which provides data for assessing formation rates for different chemical species. We introduce tools to generate and interpolate formation rate lookup tables for user-defined data, thus enabling the easy inclusion and testing of formation schemes.
Lukas Pichelstorfer, Pontus Roldin, Matti Rissanen, Noora Hyttinen, Olga Garmash, Carlton Xavier, Putian Zhou, Petri Clusius, Benjamin Foreback, Thomas Golin Almeida, Chenjuan Deng, Metin Baykara, Theo Kurten, and Michael Boy
EGUsphere, https://doi.org/10.5194/egusphere-2023-1415, https://doi.org/10.5194/egusphere-2023-1415, 2023
Preprint archived
Short summary
Short summary
Secondary organic aerosols (SOA) form effectively from gaseous precursors via a process called autoxidation. While key chemical reaction types seem to be known, no general description of autoxidation chemistry exists. In the present work, we present a method to create autoxidation chemistry schemes for any atmospherically relevant hydrocarbon. We exemplarily investigate benzene and its potential to form aerosols. We found that autoxidation, under some conditions, can dominate the SOA formation.
Erik Ahlberg, Stina Ausmeel, Lovisa Nilsson, Mårten Spanne, Julija Pauraite, Jacob Klenø Nøjgaard, Michele Bertò, Henrik Skov, Pontus Roldin, Adam Kristensson, Erik Swietlicki, and Axel Eriksson
Atmos. Chem. Phys., 23, 3051–3064, https://doi.org/10.5194/acp-23-3051-2023, https://doi.org/10.5194/acp-23-3051-2023, 2023
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To investigate the properties and origin of black carbon particles in southern Sweden during late summer, we performed measurements both at a rural site and the nearby city of Malmö. We found that local traffic emissions of black carbon led to concentrations around twice as high as those at the rural site. Modeling show that these emissions are not clearly distinguishable at the rural site, unless meteorology was favourable, which shows the importance of long-range transport and processing.
Sanna Saarikoski, Heidi Hellén, Arnaud P. Praplan, Simon Schallhart, Petri Clusius, Jarkko V. Niemi, Anu Kousa, Toni Tykkä, Rostislav Kouznetsov, Minna Aurela, Laura Salo, Topi Rönkkö, Luis M. F. Barreira, Liisa Pirjola, and Hilkka Timonen
Atmos. Chem. Phys., 23, 2963–2982, https://doi.org/10.5194/acp-23-2963-2023, https://doi.org/10.5194/acp-23-2963-2023, 2023
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This study elucidates properties and sources of volatile organic compounds (VOCs) and organic aerosol (OA) in a traffic environment. Anthropogenic VOCs (aVOCs) were clearly higher than biogenic VOCs (bVOCs), but bVOCs produced a larger portion of oxidation products. OA consisted mostly of oxygenated OA, representing secondary OA (SOA). SOA was partly associated with bVOCs, but it was also related to long-range transport. Primary OA originated mostly from traffic.
Carlton Xavier, Metin Baykara, Robin Wollesen de Jonge, Barbara Altstädter, Petri Clusius, Ville Vakkari, Roseline Thakur, Lisa Beck, Silvia Becagli, Mirko Severi, Rita Traversi, Radovan Krejci, Peter Tunved, Mauro Mazzola, Birgit Wehner, Mikko Sipilä, Markku Kulmala, Michael Boy, and Pontus Roldin
Atmos. Chem. Phys., 22, 10023–10043, https://doi.org/10.5194/acp-22-10023-2022, https://doi.org/10.5194/acp-22-10023-2022, 2022
Short summary
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The focus of this work is to study and improve our understanding of processes involved in the formation and growth of new particles in a remote Arctic marine environment. We run the 1D model ADCHEM along air mass trajectories arriving at Ny-Ålesund in May 2018. The model finds that ion-mediated H2SO4–NH3 nucleation can explain the observed new particle formation at Ny-Ålesund. The growth of particles is driven via H2SO4 condensation and formation of methane sulfonic acid in the aqueous phase.
Roseline C. Thakur, Lubna Dada, Lisa J. Beck, Lauriane L. J. Quéléver, Tommy Chan, Marjan Marbouti, Xu-Cheng He, Carlton Xavier, Juha Sulo, Janne Lampilahti, Markus Lampimäki, Yee Jun Tham, Nina Sarnela, Katrianne Lehtipalo, Alf Norkko, Markku Kulmala, Mikko Sipilä, and Tuija Jokinen
Atmos. Chem. Phys., 22, 6365–6391, https://doi.org/10.5194/acp-22-6365-2022, https://doi.org/10.5194/acp-22-6365-2022, 2022
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Every year intense cyanobacterial and macroalgal blooms occur in the Baltic Sea and in the coastal areas surrounding Helsinki, yet no studies have addressed the impact of biogenic emissions from these blooms on gas vapor concentrations, which in turn could influence new particle formation. This is the first study of its kind to address the chemistry driving new particle formation (NPF) during a bloom period in this region, highlighting the role of biogenic sulfuric acid and iodic acid.
Hanna K. Lappalainen, Tuukka Petäjä, Timo Vihma, Jouni Räisänen, Alexander Baklanov, Sergey Chalov, Igor Esau, Ekaterina Ezhova, Matti Leppäranta, Dmitry Pozdnyakov, Jukka Pumpanen, Meinrat O. Andreae, Mikhail Arshinov, Eija Asmi, Jianhui Bai, Igor Bashmachnikov, Boris Belan, Federico Bianchi, Boris Biskaborn, Michael Boy, Jaana Bäck, Bin Cheng, Natalia Chubarova, Jonathan Duplissy, Egor Dyukarev, Konstantinos Eleftheriadis, Martin Forsius, Martin Heimann, Sirkku Juhola, Vladimir Konovalov, Igor Konovalov, Pavel Konstantinov, Kajar Köster, Elena Lapshina, Anna Lintunen, Alexander Mahura, Risto Makkonen, Svetlana Malkhazova, Ivan Mammarella, Stefano Mammola, Stephany Buenrostro Mazon, Outi Meinander, Eugene Mikhailov, Victoria Miles, Stanislav Myslenkov, Dmitry Orlov, Jean-Daniel Paris, Roberta Pirazzini, Olga Popovicheva, Jouni Pulliainen, Kimmo Rautiainen, Torsten Sachs, Vladimir Shevchenko, Andrey Skorokhod, Andreas Stohl, Elli Suhonen, Erik S. Thomson, Marina Tsidilina, Veli-Pekka Tynkkynen, Petteri Uotila, Aki Virkkula, Nadezhda Voropay, Tobias Wolf, Sayaka Yasunaka, Jiahua Zhang, Yubao Qiu, Aijun Ding, Huadong Guo, Valery Bondur, Nikolay Kasimov, Sergej Zilitinkevich, Veli-Matti Kerminen, and Markku Kulmala
Atmos. Chem. Phys., 22, 4413–4469, https://doi.org/10.5194/acp-22-4413-2022, https://doi.org/10.5194/acp-22-4413-2022, 2022
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We summarize results during the last 5 years in the northern Eurasian region, especially from Russia, and introduce recent observations of the air quality in the urban environments in China. Although the scientific knowledge in these regions has increased, there are still gaps in our understanding of large-scale climate–Earth surface interactions and feedbacks. This arises from limitations in research infrastructures and integrative data analyses, hindering a comprehensive system analysis.
Zhuohui Lin, Yonghong Wang, Feixue Zheng, Ying Zhou, Yishuo Guo, Zemin Feng, Chang Li, Yusheng Zhang, Simo Hakala, Tommy Chan, Chao Yan, Kaspar R. Daellenbach, Biwu Chu, Lubna Dada, Juha Kangasluoma, Lei Yao, Xiaolong Fan, Wei Du, Jing Cai, Runlong Cai, Tom V. Kokkonen, Putian Zhou, Lili Wang, Tuukka Petäjä, Federico Bianchi, Veli-Matti Kerminen, Yongchun Liu, and Markku Kulmala
Atmos. Chem. Phys., 21, 12173–12187, https://doi.org/10.5194/acp-21-12173-2021, https://doi.org/10.5194/acp-21-12173-2021, 2021
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We find that ammonium nitrate and aerosol water content contributed most during low mixing layer height conditions; this may further trigger enhanced formation of sulfate and organic aerosol via heterogeneous reactions. The results of this study contribute towards a more detailed understanding of the aerosol–chemistry–radiation–boundary layer feedback that is likely to be responsible for explosive aerosol mass growth events in urban Beijing.
Robin Wollesen de Jonge, Jonas Elm, Bernadette Rosati, Sigurd Christiansen, Noora Hyttinen, Dana Lüdemann, Merete Bilde, and Pontus Roldin
Atmos. Chem. Phys., 21, 9955–9976, https://doi.org/10.5194/acp-21-9955-2021, https://doi.org/10.5194/acp-21-9955-2021, 2021
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This study presents a detailed analysis of the OH-initiated oxidation of dimethyl sulfide (DMS) based on experiments performed in the Aarhus University Research on Aerosol (AURA) smog chamber and the gas- and particle-phase chemistry kinetic multilayer model (ADCHAM). We capture the formation, growth and chemical composition of aerosols in the chamber setup by an improved multiphase oxidation mechanism and utilize our results to reproduce the important role of DMS in the marine boundary layer.
Anna Shcherbacheva, Tracey Balehowsky, Jakub Kubečka, Tinja Olenius, Tapio Helin, Heikki Haario, Marko Laine, Theo Kurtén, and Hanna Vehkamäki
Atmos. Chem. Phys., 20, 15867–15906, https://doi.org/10.5194/acp-20-15867-2020, https://doi.org/10.5194/acp-20-15867-2020, 2020
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Atmospheric new particle formation and cluster growth to aerosol particles is an important field of research, in particular due to the climate change phenomenon. Evaporation rates are very difficult to account for but they are important to explain the formation and growth of particles. Different quantum chemistry (QC) methods produce substantially different values for the evaporation rates. We propose a novel approach for inferring evaporation rates of clusters from available measurements.
Mona Kurppa, Pontus Roldin, Jani Strömberg, Anna Balling, Sasu Karttunen, Heino Kuuluvainen, Jarkko V. Niemi, Liisa Pirjola, Topi Rönkkö, Hilkka Timonen, Antti Hellsten, and Leena Järvi
Geosci. Model Dev., 13, 5663–5685, https://doi.org/10.5194/gmd-13-5663-2020, https://doi.org/10.5194/gmd-13-5663-2020, 2020
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High-resolution modelling is needed to solve the aerosol concentrations in a complex urban area. Here, the performance of an aerosol module within the PALM model to simulate the detailed horizontal and vertical distribution of aerosol particles is studied. Further, sensitivity to the meteorological and aerosol boundary conditions is assessed using both model and observation data. The horizontal distribution is sensitive to the wind speed and stability, and the vertical to the wind direction.
Yuan Yang, Yonghong Wang, Putian Zhou, Dan Yao, Dongsheng Ji, Jie Sun, Yinghong Wang, Shuman Zhao, Wei Huang, Shuanghong Yang, Dean Chen, Wenkang Gao, Zirui Liu, Bo Hu, Renjian Zhang, Limin Zeng, Maofa Ge, Tuukka Petäjä, Veli-Matti Kerminen, Markku Kulmala, and Yuesi Wang
Atmos. Chem. Phys., 20, 8181–8200, https://doi.org/10.5194/acp-20-8181-2020, https://doi.org/10.5194/acp-20-8181-2020, 2020
Dominik Stolzenburg, Mario Simon, Ananth Ranjithkumar, Andreas Kürten, Katrianne Lehtipalo, Hamish Gordon, Sebastian Ehrhart, Henning Finkenzeller, Lukas Pichelstorfer, Tuomo Nieminen, Xu-Cheng He, Sophia Brilke, Mao Xiao, António Amorim, Rima Baalbaki, Andrea Baccarini, Lisa Beck, Steffen Bräkling, Lucía Caudillo Murillo, Dexian Chen, Biwu Chu, Lubna Dada, António Dias, Josef Dommen, Jonathan Duplissy, Imad El Haddad, Lukas Fischer, Loic Gonzalez Carracedo, Martin Heinritzi, Changhyuk Kim, Theodore K. Koenig, Weimeng Kong, Houssni Lamkaddam, Chuan Ping Lee, Markus Leiminger, Zijun Li, Vladimir Makhmutov, Hanna E. Manninen, Guillaume Marie, Ruby Marten, Tatjana Müller, Wei Nie, Eva Partoll, Tuukka Petäjä, Joschka Pfeifer, Maxim Philippov, Matti P. Rissanen, Birte Rörup, Siegfried Schobesberger, Simone Schuchmann, Jiali Shen, Mikko Sipilä, Gerhard Steiner, Yuri Stozhkov, Christian Tauber, Yee Jun Tham, António Tomé, Miguel Vazquez-Pufleau, Andrea C. Wagner, Mingyi Wang, Yonghong Wang, Stefan K. Weber, Daniela Wimmer, Peter J. Wlasits, Yusheng Wu, Qing Ye, Marcel Zauner-Wieczorek, Urs Baltensperger, Kenneth S. Carslaw, Joachim Curtius, Neil M. Donahue, Richard C. Flagan, Armin Hansel, Markku Kulmala, Jos Lelieveld, Rainer Volkamer, Jasper Kirkby, and Paul M. Winkler
Atmos. Chem. Phys., 20, 7359–7372, https://doi.org/10.5194/acp-20-7359-2020, https://doi.org/10.5194/acp-20-7359-2020, 2020
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Sulfuric acid is a major atmospheric vapour for aerosol formation. If new particles grow fast enough, they can act as cloud droplet seeds or affect air quality. In a controlled laboratory set-up, we demonstrate that van der Waals forces enhance growth from sulfuric acid. We disentangle the effects of ammonia, ions and particle hydration, presenting a complete picture of sulfuric acid growth from molecular clusters onwards. In a climate model, we show its influence on the global aerosol budget.
Dean Chen, Putian Zhou, Tuomo Nieminen, Pontus Roldin, Ximeng Qi, Petri Clusius, Carlton Xavier, Lukas Pichelstorfer, Markku Kulmala, Pekka Rantala, Juho Aalto, Nina Sarnela, Pasi Kolari, Petri Keronen, Matti P. Rissanen, Metin Baykara, and Michael Boy
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-128, https://doi.org/10.5194/acp-2020-128, 2020
Preprint withdrawn
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Atmospheric oxidants OH, O3 and NO3 dominate the atmospheric oxidation capacity, and sulfuric acid (H2SO4) is considered as a main driver for new particle formation events. We studied how the trends of these atmospheric oxidants and H2SO4 changed in southern Finland during the past 12 years and discussed how these trends related to decreasing emissions of air pollutants in Europe. Our results showed that OH increased by 1.56 % yr−1 at daytime and NO3 decreased by 3.92 % yr−1 at nighttime.
Otso Peräkylä, Matthieu Riva, Liine Heikkinen, Lauriane Quéléver, Pontus Roldin, and Mikael Ehn
Atmos. Chem. Phys., 20, 649–669, https://doi.org/10.5194/acp-20-649-2020, https://doi.org/10.5194/acp-20-649-2020, 2020
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Highly oxygenated organic molecules have been suggested to form a large part of secondary organic aerosol. However, with their exotic structures, their volatilities are not well known, making their exact role in particle formation hard to assess. In laboratory experiments, we found the volatility of HOMs formed in the ozonolysis of the monoterpene alpha-pinene to be in the middle of earlier estimates. The volatilities of HOMs could be well explained in terms of their molecular formulae.
Yonghong Wang, Miao Yu, Yuesi Wang, Guiqian Tang, Tao Song, Putian Zhou, Zirui Liu, Bo Hu, Dongsheng Ji, Lili Wang, Xiaowan Zhu, Chao Yan, Mikael Ehn, Wenkang Gao, Yuepeng Pan, Jinyuan Xin, Yang Sun, Veli-Matti Kerminen, Markku Kulmala, and Tuukka Petäjä
Atmos. Chem. Phys., 20, 45–53, https://doi.org/10.5194/acp-20-45-2020, https://doi.org/10.5194/acp-20-45-2020, 2020
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We found a positive particle matter-mixing layer height feedback at three observation platforms at the 325 m Beijing meteorology tower, which is characterized by a shallower mixing layer height and a higher particle matter concentration. Measurements of solar radiation, aerosol chemical composition, meteorology parameters, trace gases and turbulent kinetic energy (TKE) could explain the feedback mechanism to some extent.
Arnaud P. Praplan, Toni Tykkä, Dean Chen, Michael Boy, Ditte Taipale, Ville Vakkari, Putian Zhou, Tuukka Petäjä, and Heidi Hellén
Atmos. Chem. Phys., 19, 14431–14453, https://doi.org/10.5194/acp-19-14431-2019, https://doi.org/10.5194/acp-19-14431-2019, 2019
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Our study shows that, despite our best efforts and recent progress, our knowledge of the chemical composition of the air under the canopy of a boreal forest still cannot be fully characterized. The discrepancy between the measured total reactivity of the air and the reactivity derived from the known chemical composition highlights the need to better understand the emissions from vegetation, but also other sources, such as the forest soil.
Carlton Xavier, Anton Rusanen, Putian Zhou, Chen Dean, Lukas Pichelstorfer, Pontus Roldin, and Michael Boy
Atmos. Chem. Phys., 19, 13741–13758, https://doi.org/10.5194/acp-19-13741-2019, https://doi.org/10.5194/acp-19-13741-2019, 2019
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Master Chemical Mechanism (MCM) coupled to peroxy radical autoxidation mechanism (PRAM) was used to simulate secondary organic aerosol mass loadings from oxidation of five selected biogenic volatile organic compounds. The simulations were designed to replicate idealized chamber and oxidative flow-tube setups. The mass yields using MCM + PRAM are in good agreement with the experimental yields, thereby allowing us to highlight a few important compounds which contribute to > 95 % of mass loadings.
Nanna Myllys, Jakub Kubečka, Vitus Besel, Dina Alfaouri, Tinja Olenius, James Norman Smith, and Monica Passananti
Atmos. Chem. Phys., 19, 9753–9768, https://doi.org/10.5194/acp-19-9753-2019, https://doi.org/10.5194/acp-19-9753-2019, 2019
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In atmospheric sulfuric-acid-driven particle formation, bases are able to stabilize the initial molecular clusters and thus enhance particle formation. We have investigated the enhancing potential of different bases in atmospheric particle formation. We show that strong bases with low abundance are likely to dominate electrically neutral particle formation, whereas weak bases with high abundance have a larger role in ion-mediated particle formation.
Lauriane L. J. Quéléver, Kasper Kristensen, Louise Normann Jensen, Bernadette Rosati, Ricky Teiwes, Kaspar R. Daellenbach, Otso Peräkylä, Pontus Roldin, Rossana Bossi, Henrik B. Pedersen, Marianne Glasius, Merete Bilde, and Mikael Ehn
Atmos. Chem. Phys., 19, 7609–7625, https://doi.org/10.5194/acp-19-7609-2019, https://doi.org/10.5194/acp-19-7609-2019, 2019
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Highly oxygenated organic molecules (HOMs) form rapidly in oxidation of monoterpenes and have been shown to be crucial for secondary organic aerosol formation. We studied the formation of HOMs under different temperatures, finding a strong dependence on their yields. As temperatures decrease, the isomerization reactions that allow rapid oxidation by molecular oxygen slow down, and competing reaction pathways can suppress the HOM formation almost completely, especially at high VOC loadings.
Mona Kurppa, Antti Hellsten, Pontus Roldin, Harri Kokkola, Juha Tonttila, Mikko Auvinen, Christoph Kent, Prashant Kumar, Björn Maronga, and Leena Järvi
Geosci. Model Dev., 12, 1403–1422, https://doi.org/10.5194/gmd-12-1403-2019, https://doi.org/10.5194/gmd-12-1403-2019, 2019
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This paper describes the implementation of a sectional aerosol module, SALSA, into the PALM model system 6.0. The first evaluation study shows excellent agreements with measurements. Furthermore, we show that ignoring the dry deposition of aerosol particles can overestimate aerosol number concentrations by 20 %, whereas condensation and dissolutional growth increase the total aerosol mass by over 10 % in this specific urban environment.
Nikos Kalivitis, Veli-Matti Kerminen, Giorgos Kouvarakis, Iasonas Stavroulas, Evaggelia Tzitzikalaki, Panayiotis Kalkavouras, Nikos Daskalakis, Stelios Myriokefalitakis, Aikaterini Bougiatioti, Hanna E. Manninen, Pontus Roldin, Tuukka Petäjä, Michael Boy, Markku Kulmala, Maria Kanakidou, and Nikolaos Mihalopoulos
Atmos. Chem. Phys., 19, 2671–2686, https://doi.org/10.5194/acp-19-2671-2019, https://doi.org/10.5194/acp-19-2671-2019, 2019
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New particle formation (NPF) is an important source of atmospheric aerosols. For the Mediterranean atmosphere, only few studies exist. In this study we present one of the longest series of NPF by analyzing 10 years of data from Crete, Greece. NPF took place on 27 % of the available days; it was more frequent in spring and less so in late summer. Model simulations showed that NPF in the subtropical environment may differ greatly from that in the boreal environment.
Erik Ahlberg, Axel Eriksson, William H. Brune, Pontus Roldin, and Birgitta Svenningsson
Atmos. Chem. Phys., 19, 2701–2712, https://doi.org/10.5194/acp-19-2701-2019, https://doi.org/10.5194/acp-19-2701-2019, 2019
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The effects of wet or dry salt seed particle concentration (ammonium nitrate and ammonium sulphate) on secondary organic aerosol mass yields from a mixture of m-xylene and α-pinene were examined in an oxidation flow reactor. The experiments confirmed that increasing the condensation sink significantly increases the particle mass yields in oxidation flow reactors. Further, wet seed particles increased the particle mass yield by 60 % more than dry particles.
Michael Boy, Erik S. Thomson, Juan-C. Acosta Navarro, Olafur Arnalds, Ekaterina Batchvarova, Jaana Bäck, Frank Berninger, Merete Bilde, Zoé Brasseur, Pavla Dagsson-Waldhauserova, Dimitri Castarède, Maryam Dalirian, Gerrit de Leeuw, Monika Dragosics, Ella-Maria Duplissy, Jonathan Duplissy, Annica M. L. Ekman, Keyan Fang, Jean-Charles Gallet, Marianne Glasius, Sven-Erik Gryning, Henrik Grythe, Hans-Christen Hansson, Margareta Hansson, Elisabeth Isaksson, Trond Iversen, Ingibjorg Jonsdottir, Ville Kasurinen, Alf Kirkevåg, Atte Korhola, Radovan Krejci, Jon Egill Kristjansson, Hanna K. Lappalainen, Antti Lauri, Matti Leppäranta, Heikki Lihavainen, Risto Makkonen, Andreas Massling, Outi Meinander, E. Douglas Nilsson, Haraldur Olafsson, Jan B. C. Pettersson, Nønne L. Prisle, Ilona Riipinen, Pontus Roldin, Meri Ruppel, Matthew Salter, Maria Sand, Øyvind Seland, Heikki Seppä, Henrik Skov, Joana Soares, Andreas Stohl, Johan Ström, Jonas Svensson, Erik Swietlicki, Ksenia Tabakova, Throstur Thorsteinsson, Aki Virkkula, Gesa A. Weyhenmeyer, Yusheng Wu, Paul Zieger, and Markku Kulmala
Atmos. Chem. Phys., 19, 2015–2061, https://doi.org/10.5194/acp-19-2015-2019, https://doi.org/10.5194/acp-19-2015-2019, 2019
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The Nordic Centre of Excellence CRAICC (Cryosphere–Atmosphere Interactions in a Changing Arctic Climate), funded by NordForsk in the years 2011–2016, is the largest joint Nordic research and innovation initiative to date and aimed to strengthen research and innovation regarding climate change issues in the Nordic region. The paper presents an overview of the main scientific topics investigated and provides a state-of-the-art comprehensive summary of what has been achieved in CRAICC.
Yuqin Liu, Jiahua Zhang, Putian Zhou, Tao Lin, Juan Hong, Lamei Shi, Fengmei Yao, Jun Wu, Huadong Guo, and Gerrit de Leeuw
Atmos. Chem. Phys., 18, 18187–18202, https://doi.org/10.5194/acp-18-18187-2018, https://doi.org/10.5194/acp-18-18187-2018, 2018
Liqing Hao, Olga Garmash, Mikael Ehn, Pasi Miettinen, Paola Massoli, Santtu Mikkonen, Tuija Jokinen, Pontus Roldin, Pasi Aalto, Taina Yli-Juuti, Jorma Joutsensaari, Tuukka Petäjä, Markku Kulmala, Kari E. J. Lehtinen, Douglas R. Worsnop, and Annele Virtanen
Atmos. Chem. Phys., 18, 17705–17716, https://doi.org/10.5194/acp-18-17705-2018, https://doi.org/10.5194/acp-18-17705-2018, 2018
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An aerosol mass spectrometer was used to characterize aerosol chemical composition during new particle formation periods. The time profiles of mass concentrations and chemical composition of observed aerosol particles are subjected to joint effects of boundary layer dilution, atmospheric chemistry and aerosol mixing in different boundary layers. During the nighttime, the increase in organic aerosol mass correlated well with the increase in condensed highly oxygenated organic molecules' mass.
Jenni Kontkanen, Tinja Olenius, Markku Kulmala, and Ilona Riipinen
Atmos. Chem. Phys., 18, 13733–13754, https://doi.org/10.5194/acp-18-13733-2018, https://doi.org/10.5194/acp-18-13733-2018, 2018
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New particle formation involving sulfuric acid, bases and organic compounds is an important source of atmospheric aerosol particles. We investigate the capability of nano-Köhler theory to describe this process by simulating the dynamics of atmospheric molecular clusters. We find that nano-Köhler-type behavior occurs in our simulations when the saturation ratio of the organic vapor and the ratio between organic and inorganic vapor concentrations are in a suitable range.
Ximeng Qi, Aijun Ding, Pontus Roldin, Zhengning Xu, Putian Zhou, Nina Sarnela, Wei Nie, Xin Huang, Anton Rusanen, Mikael Ehn, Matti P. Rissanen, Tuukka Petäjä, Markku Kulmala, and Michael Boy
Atmos. Chem. Phys., 18, 11779–11791, https://doi.org/10.5194/acp-18-11779-2018, https://doi.org/10.5194/acp-18-11779-2018, 2018
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In this study we simulate the HOM concentrations and discuss their roles in NPF at a remote boreal forest site in Finland and a suburban site in eastern China. We found that sulfuric acid and HOM organonitrate concentrations in the gas phase are significantly higher but other HOM monomers and dimers from monoterpene oxidation are lower in eastern China. This study highlights the need for molecular-scale measurements in improving the understanding of NPF mechanisms in polluted areas.
Ben H. Lee, Felipe D. Lopez-Hilfiker, Emma L. D'Ambro, Putian Zhou, Michael Boy, Tuukka Petäjä, Liqing Hao, Annele Virtanen, and Joel A. Thornton
Atmos. Chem. Phys., 18, 11547–11562, https://doi.org/10.5194/acp-18-11547-2018, https://doi.org/10.5194/acp-18-11547-2018, 2018
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Molecular identities and abundances of organic compounds residing in the gas and particle phases above a Finnish boreal forest are presented. We determined that in each phase, the organic components are categorized into three subgroups based on their behavior in time. Some are more enhanced at night, others during midday, and another around sunrise. Identifying such collective behavior can potentially connect the chemical processes that evolve in time to specific distributions of products.
Luciana Varanda Rizzo, Pontus Roldin, Joel Brito, John Backman, Erik Swietlicki, Radovan Krejci, Peter Tunved, Tukka Petäjä, Markku Kulmala, and Paulo Artaxo
Atmos. Chem. Phys., 18, 10255–10274, https://doi.org/10.5194/acp-18-10255-2018, https://doi.org/10.5194/acp-18-10255-2018, 2018
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Aerosols are tiny particles suspended in the air that can interact with sunlight and form clouds, which in turn affect the climate. They can also recycle nutrients in forest environments. Aerosols are naturally emitted at the surface in the Amazon forest, in addition to being brought down from above the boundary layer by intense air movements. In this work, we describe how the particle size number concentrations of aerosols change over hours, days and seasons in a multi-year study in Amazonia.
Putian Zhou, Laurens Ganzeveld, Ditte Taipale, Üllar Rannik, Pekka Rantala, Matti Petteri Rissanen, Dean Chen, and Michael Boy
Atmos. Chem. Phys., 17, 14309–14332, https://doi.org/10.5194/acp-17-14309-2017, https://doi.org/10.5194/acp-17-14309-2017, 2017
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In boreal forest, there is a large number of gaseous organic compounds called biogenic volatile organic compounds (BVOCs). Within the canopy, they can be emitted from vegetation and soil, react with each other and other gases, be transported in the air, and be removed from vegetation and soil surfaces. We applied a numerical model to simulate these processes and found that these BVOCs can be divided into five categories according to the significance of their sources and sinks.
Georgios Tsagkogeorgas, Pontus Roldin, Jonathan Duplissy, Linda Rondo, Jasmin Tröstl, Jay G. Slowik, Sebastian Ehrhart, Alessandro Franchin, Andreas Kürten, Antonio Amorim, Federico Bianchi, Jasper Kirkby, Tuukka Petäjä, Urs Baltensperger, Michael Boy, Joachim Curtius, Richard C. Flagan, Markku Kulmala, Neil M. Donahue, and Frank Stratmann
Atmos. Chem. Phys., 17, 8923–8938, https://doi.org/10.5194/acp-17-8923-2017, https://doi.org/10.5194/acp-17-8923-2017, 2017
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The H2SO4 vapour pressure plays key role in Earth's and Venus' atmospheres. In regions where RH is low and stabilising bases are scarce, H2SO4 can evaporate from particles; however the H2SO4 vapour pressure at low RH is uncertain. To address this, we measured H2SO4 evaporation versus T and RH in the CLOUD chamber and constrained the equilibrium constants for dissociation and dehydration of H2SO4. This study is important for nucleation, particle growth and H2SO4 formation occurring in atmosphere.
Emilie Öström, Zhou Putian, Guy Schurgers, Mikhail Mishurov, Niku Kivekäs, Heikki Lihavainen, Mikael Ehn, Matti P. Rissanen, Theo Kurtén, Michael Boy, Erik Swietlicki, and Pontus Roldin
Atmos. Chem. Phys., 17, 8887–8901, https://doi.org/10.5194/acp-17-8887-2017, https://doi.org/10.5194/acp-17-8887-2017, 2017
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We used a model to study how biogenic volatile organic compounds (BVOCs) emitted from the boreal forest contribute to the formation and growth of particles in the atmosphere. Some of these particles are important climate forcers, acting as seeds for cloud droplet fomation. We implemented a new gas chemistry mechanism that describes how the BVOCs are oxidized and form low-volatility highly oxidized organic molecules. With the new mechanism we are able to accurately predict the particle growth.
Eero Nikinmaa, Tuomo Kalliokoski, Kari Minkkinen, Jaana Bäck, Michael Boy, Yao Gao, Nina Janasik-Honkela, Janne I. Hukkinen, Maarit Kallio, Markku Kulmala, Nea Kuusinen, Annikki Mäkelä, Brent D. Matthies, Mikko Peltoniemi, Risto Sievänen, Ditte Taipale, Lauri Valsta, Anni Vanhatalo, Martin Welp, Luxi Zhou, Putian Zhou, and Frank Berninger
Biogeosciences Discuss., https://doi.org/10.5194/bg-2017-141, https://doi.org/10.5194/bg-2017-141, 2017
Manuscript not accepted for further review
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We estimated the impact of boreal forest management on climate, considering the effects of carbon, albedo, aerosols, and effects of industrial wood use. We made analyses both in current and warmer climate of 2050. The aerosol effect was comparable to that of carbon sequestration. Deciduous trees may have a large potential for mitigation due to their high albedo and aerosol effects. If the forests will be used more intensively and mainly for pulp and energy, the warming influence is clear.
Yuqin Liu, Gerrit de Leeuw, Veli-Matti Kerminen, Jiahua Zhang, Putian Zhou, Wei Nie, Ximeng Qi, Juan Hong, Yonghong Wang, Aijun Ding, Huadong Guo, Olaf Krüger, Markku Kulmala, and Tuukka Petäjä
Atmos. Chem. Phys., 17, 5623–5641, https://doi.org/10.5194/acp-17-5623-2017, https://doi.org/10.5194/acp-17-5623-2017, 2017
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The aerosol effects on warm cloud parameters over the Yangtze River Delta are systematically examined using multi-sensor retrievals. This study shows that the COT–CDR and CWP–CDR relationships are not unique, but are affected by atmospheric aerosol loading. CDR and cloud fraction show different behaviours for low and high AOD. Aerosol–cloud interaction (ACI) is stronger for clouds mixed with smoke aerosol than for clouds mixed with dust. Meteorological conditions play an important role in ACI.
Putian Zhou, Laurens Ganzeveld, Üllar Rannik, Luxi Zhou, Rosa Gierens, Ditte Taipale, Ivan Mammarella, and Michael Boy
Atmos. Chem. Phys., 17, 1361–1379, https://doi.org/10.5194/acp-17-1361-2017, https://doi.org/10.5194/acp-17-1361-2017, 2017
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We implemented a multi-layer O3 dry deposition model in a 1-D model SOSAA to simulate O3 flux and concentration within and above a boreal forest at SMEAR II in Hyytiälä, Finland, in August 2010. The results showed that when RH > 70 % the O3 uptake on leaf wet skin was ~ 51 % to the total deposition at night and ~ 19 % at daytime. The sub-canopy contribution below 4.2 m was ~ 38 % at daytime. The averaged daily chemical contribution to total O3 alteration inside the canopy was less than 10 %.
Natalia Babkovskaia, Ullar Rannik, Vaughan Phillips, Holger Siebert, Birgit Wehner, and Michael Boy
Atmos. Chem. Phys., 16, 7889–7898, https://doi.org/10.5194/acp-16-7889-2016, https://doi.org/10.5194/acp-16-7889-2016, 2016
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Turbulence, aerosol growth and microphysics of hydrometeors in clouds are intimately coupled. A new modelling approach was applied to quantify this linkage. We study the interaction in the cloud area under transient, high supersaturation conditions, using direct numerical simulations. Analysing the effect of aerosol dynamics on the turbulent kinetic energy and on vertical velocity, we conclude that the presence of aerosol has an effect on vertical motion and tends to reduce downward velocity.
David Brus, Lenka Skrabalova, Erik Herrmann, Tinja Olenius, Tereza Travnickova, and Joonas Merikanto
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-398, https://doi.org/10.5194/acp-2016-398, 2016
Revised manuscript not accepted
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We report laboratory measurements of the diffusion coefficient of sulfuric acid in humidified air. To our best knowledge, this is the first study, which investigates systematically the temperature dependency of the diffusion coefficient of H2SO4. We observed a rather strong power dependence with power of 5.4 when compared to 1.75 observed for other gases. We suggest that observed higher temperature dependence might be due to strong clustering of H2SO4 with base-impurities like amines.
Jenni Kontkanen, Tinja Olenius, Katrianne Lehtipalo, Hanna Vehkamäki, Markku Kulmala, and Kari E. J. Lehtinen
Atmos. Chem. Phys., 16, 5545–5560, https://doi.org/10.5194/acp-16-5545-2016, https://doi.org/10.5194/acp-16-5545-2016, 2016
Üllar Rannik, Luxi Zhou, Putian Zhou, Rosa Gierens, Ivan Mammarella, Andrey Sogachev, and Michael Boy
Atmos. Chem. Phys., 16, 3145–3160, https://doi.org/10.5194/acp-16-3145-2016, https://doi.org/10.5194/acp-16-3145-2016, 2016
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Atmospheric boundary layer (ABL) model coupled with detailed atmospheric chemistry and aerosol dynamical model was used to quantify the role of aerosol and ABL dynamics in the vertical transport of aerosols at a pine forest site in southern Finland. Simulations showed that under dynamical conditions the particle fluxes above canopy can significantly deviate from the dry deposition into the canopy. The deviation can be systematic for certain particle sizes over a period of several days.
Xin Huang, Luxi Zhou, Aijun Ding, Ximeng Qi, Wei Nie, Minghuai Wang, Xuguang Chi, Tuukka Petäjä, Veli-Matti Kerminen, Pontus Roldin, Anton Rusanen, Markku Kulmala, and Michael Boy
Atmos. Chem. Phys., 16, 2477–2492, https://doi.org/10.5194/acp-16-2477-2016, https://doi.org/10.5194/acp-16-2477-2016, 2016
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By combining a regional model and a box model, this study simulates new particle formation in Nanjing, China, when the air masses were affected by anthropogenic activities, biogenic emissions, or mixed ocean and continental sources. The simulations reveal that biogenic organic compounds play a vital role in growth of newly formed clusters. This novel combination of two models makes it possible to accomplish new particle formation simulation without direct measurements of all chemical species.
X. M. Qi, A. J. Ding, W. Nie, T. Petäjä, V.-M. Kerminen, E. Herrmann, Y. N. Xie, L. F. Zheng, H. Manninen, P. Aalto, J. N. Sun, Z. N. Xu, X. G. Chi, X. Huang, M. Boy, A. Virkkula, X.-Q. Yang, C. B. Fu, and M. Kulmala
Atmos. Chem. Phys., 15, 12445–12464, https://doi.org/10.5194/acp-15-12445-2015, https://doi.org/10.5194/acp-15-12445-2015, 2015
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We report 2 years of measurements of submicron particles at the SORPES station and provide a comprehensive understanding of main factors controlling temporal variation of the aerosol size distribution and NPF in eastern China. The number concentrations of total particles at Nanjing were comparable to other Chinese megacities but the frequency of NPF was much higher. Year-to-year differences of meteorological conditions could significantly influence the seasonal cycle of NPF and growth.
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. Zhou, R. Gierens, A. Sogachev, D. Mogensen, J. Ortega, J. N. Smith, P. C. Harley, A. J. Prenni, E. J. T. Levin, A. Turnipseed, A. Rusanen, S. Smolander, A. B. Guenther, M. Kulmala, T. Karl, and M. Boy
Atmos. Chem. Phys., 15, 8643–8656, https://doi.org/10.5194/acp-15-8643-2015, https://doi.org/10.5194/acp-15-8643-2015, 2015
D. Mogensen, R. Gierens, J. N. Crowley, P. Keronen, S. Smolander, A. Sogachev, A. C. Nölscher, L. Zhou, M. Kulmala, M. J. Tang, J. Williams, and M. Boy
Atmos. Chem. Phys., 15, 3909–3932, https://doi.org/10.5194/acp-15-3909-2015, https://doi.org/10.5194/acp-15-3909-2015, 2015
D. Mogensen and M. Boy
Atmos. Chem. Phys., 15, 3109–3110, https://doi.org/10.5194/acp-15-3109-2015, https://doi.org/10.5194/acp-15-3109-2015, 2015
E. Hermansson, P. Roldin, A. Rusanen, D. Mogensen, N. Kivekäs, R. Väänänen, M. Boy, and E. Swietlicki
Atmos. Chem. Phys., 14, 11853–11869, https://doi.org/10.5194/acp-14-11853-2014, https://doi.org/10.5194/acp-14-11853-2014, 2014
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Secondary organic aerosols (SOA), produced through oxidation processes, constitute a large part of the global organic aerosol load and affect the climate. We found that the modeled mass of SOA was highly dependent on how the oxidation processes were explained in models. The results indicated that it was especially important to get the volatility distribution of the products from the first oxidation step right and that fragmentation during the oxidation process played an important role.
S. Smolander, Q. He, D. Mogensen, L. Zhou, J. Bäck, T. Ruuskanen, S. Noe, A. Guenther, H. Aaltonen, M. Kulmala, and M. Boy
Biogeosciences, 11, 5425–5443, https://doi.org/10.5194/bg-11-5425-2014, https://doi.org/10.5194/bg-11-5425-2014, 2014
C. Wittbom, A. C. Eriksson, J. Rissler, J. E. Carlsson, P. Roldin, E. Z. Nordin, P. T. Nilsson, E. Swietlicki, J. H. Pagels, and B. Svenningsson
Atmos. Chem. Phys., 14, 9831–9854, https://doi.org/10.5194/acp-14-9831-2014, https://doi.org/10.5194/acp-14-9831-2014, 2014
L. Liao, V.-M. Kerminen, M. Boy, M. Kulmala, and M. Dal Maso
Atmos. Chem. Phys., 14, 8295–8308, https://doi.org/10.5194/acp-14-8295-2014, https://doi.org/10.5194/acp-14-8295-2014, 2014
P. Roldin, A. C. Eriksson, E. Z. Nordin, E. Hermansson, D. Mogensen, A. Rusanen, M. Boy, E. Swietlicki, B. Svenningsson, A. Zelenyuk, and J. Pagels
Atmos. Chem. Phys., 14, 7953–7993, https://doi.org/10.5194/acp-14-7953-2014, https://doi.org/10.5194/acp-14-7953-2014, 2014
Z. B. Wang, M. Hu, D. Mogensen, D. L. Yue, J. Zheng, R. Y. Zhang, Y. Liu, B. Yuan, X. Li, M. Shao, L. Zhou, Z. J. Wu, A. Wiedensohler, and M. Boy
Atmos. Chem. Phys., 13, 11157–11167, https://doi.org/10.5194/acp-13-11157-2013, https://doi.org/10.5194/acp-13-11157-2013, 2013
E. Z. Nordin, A. C. Eriksson, P. Roldin, P. T. Nilsson, J. E. Carlsson, M. K. Kajos, H. Hellén, C. Wittbom, J. Rissler, J. Löndahl, E. Swietlicki, B. Svenningsson, M. Bohgard, M. Kulmala, M. Hallquist, and J. H. Pagels
Atmos. Chem. Phys., 13, 6101–6116, https://doi.org/10.5194/acp-13-6101-2013, https://doi.org/10.5194/acp-13-6101-2013, 2013
M. Boy, D. Mogensen, S. Smolander, L. Zhou, T. Nieminen, P. Paasonen, C. Plass-Dülmer, M. Sipilä, T. Petäjä, L. Mauldin, H. Berresheim, and M. Kulmala
Atmos. Chem. Phys., 13, 3865–3879, https://doi.org/10.5194/acp-13-3865-2013, https://doi.org/10.5194/acp-13-3865-2013, 2013
L. V. Rizzo, P. Artaxo, T. Müller, A. Wiedensohler, M. Paixão, G. G. Cirino, A. Arana, E. Swietlicki, P. Roldin, E. O. Fors, K. T. Wiedemann, L. S. M. Leal, and M. Kulmala
Atmos. Chem. Phys., 13, 2391–2413, https://doi.org/10.5194/acp-13-2391-2013, https://doi.org/10.5194/acp-13-2391-2013, 2013
Z. B. Wang, M. Hu, Z. J. Wu, D. L. Yue, J. Zheng, R. Y. Zhang, X. Y. Pei, P. Paasonen, M. Dal Maso, M. Boy, and A. Wiedensohler
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-13-3419-2013, https://doi.org/10.5194/acpd-13-3419-2013, 2013
Revised manuscript not accepted
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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.
Cited articles
Adams, P. J. and Seinfeld, J. H.: Predicting global aerosol size distributions in general circulation models, J. Geophys. Res., 107, AAC 4-1–AAC 4-23, https://doi.org/10.1029/2001jd001010, 2002.
Akherati, A., He, Y., Coggon, M. M., Koss, A. R., Hodshire, A. L., Sekimoto, K., Warneke, C., de Gouw, J., Yee, L., Seinfeld, J. H., Onasch, T. B., Herndon, S. C., Knighton, W. B., Cappa, C. D., Kleeman, M. J., Lim, C. Y., Kroll, J. H., Pierce, J. R., and Jathar, S. H.: Oxygenated Aromatic Compounds are Important Precursors of Secondary Organic Aerosol in Biomass-Burning Emissions, Environ. Sci. Technol., 54, 8568–8579, https://doi.org/10.1021/acs.est.0c01345, 2020.
Almeida, J., Schobesberger, S., Kürten, A., Ortega, I. K., Kupiainen-Määttä, O., Praplan, A. P., Adamov, A., Amorim, A., Bianchi, F., Breitenlechner, M., David, A., Dommen, J., Donahue, N. M., Downard, A., Dunne, E., Duplissy, J., Ehrhart, S., Flagan, R. C., Franchin, A., Guida, R., Hakala, J., Hansel, A., Heinritzi, M., Henschel, H., Jokinen, T., Junninen, H., Kajos, M., Kangasluoma, J., Keskinen, H., Kupc, A., Kurtén, T., Kvashin, A. N., Laaksonen, A., Lehtipalo, K., Leiminger, M., Leppä, J., Loukonen, V., Makhmutov, V., Mathot, S., McGrath, M. J., Nieminen, T., Olenius, T., Onnela, A., Petäjä, T., Riccobono, F., Riipinen, I., Rissanen, M., Rondo, L., Ruuskanen, T., Santos, F. D., Sarnela, N., Schallhart, S., Schnitzhofer, R., Seinfeld, J. H., Simon, M., Sipilä, M., Stozhkov, Y., Stratmann, F., Tomé, A., Tröstl, J., Tsagkogeorgas, G., Vaattovaara, P., Viisanen, Y., Virtanen, A., Vrtala, A., Wagner, P. E., Weingartner, E., Wex, H., Williamson, C., Wimmer, D., Ye, P., Yli-Juuti, T., Carslaw, K. S., Kulmala, M., Curtius, J., Baltensperger, U., Worsnop, D. R., Vehkamäki, H., and Kirkby, J.: Molecular understanding of sulphuric acid–amine particle nucleation in the atmosphere, Nature, 502, 359–363, https://doi.org/10.1038/nature12663, 2013.
Besel, V., Kubečka, J., Kurtén, T., and Vehkamäki, H.: Impact of Quantum Chemistry Parameter Choices and Cluster Distribution Model Settings on Modeled Atmospheric Particle Formation Rates, J. Phys. Chem. A, 124, 5931–5943, https://doi.org/10.1021/acs.jpca.0c03984, 2020.
Bird, R. E. and Riordan, C.: Simple Solar Spectral Model for Direct and Diffuse Irradiance on Horizontal and Tilted Planes at the Earth's Surface for Cloudless Atmospheres, J. Appl. Meteorol. Clim., 25, 87–97, https://doi.org/10.1175/1520-0450(1986)025<0087:sssmfd>2.0.co;2, 1986.
Boy, M. and Kulmala, M.: The part of the solar spectrum with the highest influence on the formation of SOA in the continental boundary layer, Atmos. Chem. Phys., 2, 375–386, https://doi.org/10.5194/acp-2-375-2002, 2002.
Boy, M., Hellmuth, O., Korhonen, H., Nilsson, E. D., ReVelle, D., Turnipseed, A., Arnold, F., and Kulmala, M.: MALTE – model to predict new aerosol formation in the lower troposphere, Atmos. Chem. Phys., 6, 4499–4517, https://doi.org/10.5194/acp-6-4499-2006, 2006.
Boy, M., Sogachev, A., Lauros, J., Zhou, L., Guenther, A., and Smolander, S.: SOSA – a new model to simulate the concentrations of organic vapours and sulphuric acid inside the ABL – Part 1: Model description and initial evaluation, Atmos. Chem. Phys., 11, 43–51, https://doi.org/10.5194/acp-11-43-2011, 2011.
Boy, M., Mogensen, D., Smolander, S., Zhou, L., Nieminen, T., Paasonen, P., Plass-Dülmer, C., Sipilä, M., Petäjä, T., Mauldin, L., Berresheim, H., and Kulmala, M.: Oxidation of SO2 by stabilized Criegee intermediate (sCI) radicals as a crucial source for atmospheric sulfuric acid concentrations, Atmos. Chem. Phys., 13, 3865–3879, https://doi.org/10.5194/acp-13-3865-2013, 2013.
Bruun, H. H.: Hot-Wire Anemometry: Principles and Signal Analysis, Oxford University Press, Oxford, UK, ISBN 978-0-198-56342-6, 1995.
Chen, J.-P. and Lamb, D.: Simulation of Cloud Microphysical and Chemical Processes Using a Multicomponent Framework. Part I: Description of the Microphysical Model, J. Atmos. Sci., 51, 2613–2630, https://doi.org/10.1175/1520-0469(1994)051<2613:socmac>2.0.co;2, 1994.
Clusius P.: Dataset in GMD-2022-55 (Version 1), Zenodo [data set], https://doi.org/10.5281/zenodo.7002869, 2022.
Clusius P., Xavier C., Pichelstorfer L., Zhou P., Olenius T., Roldin P., and Boy M.: Atmospherically relevant chemistry and aerosol box model – ARCA box (version 1.2.2), Zenodo [code], https://doi.org/10.5281/zenodo.6787213, 2022.
Compernolle, S., Ceulemans, K., and Müller, J.-F.: EVAPORATION: a new vapour pressure estimation methodfor organic molecules including non-additivity and intramolecular interactions, Atmos. Chem. Phys., 11, 9431–9450, https://doi.org/10.5194/acp-11-9431-2011, 2011.
Daescu, D., Sandu, A., and Carmichael, G. R.: Direct and Adjoint Sensitivity Analysis of Chemical Kinetic Systems with KPP: II – Validation and Numerical Experiments, Atmos. Environ., 37, 5097–5114, 2003.
Damian, V., Sandu, A., Damian, M., Potra, F., and Carmichael, G. R.: The kinetic preprocessor KPP-a software environment for solving chemical kinetics, Comput. Chem. Eng., 26, 1567–1579, https://doi.org/10.1016/s0098-1354(02)00128-x, 2002.
Eckert, F. and Klamt, A.: Fast solvent screening via quantum chemistry: COSMO-RS approach, AIChE J., 48, 369–385, https://doi.org/10.1002/aic.690480220, 2002.
Fuchs, N. A.: The mechanics of aerosols, Pergamon Press, London, https://doi.org/10.1002/qj.49709138822, 1964.
Gelbard, F. and Seinfeld, J. H.: Simulation of multicomponent aerosol dynamics, J. Colloid Interf. Sci., 78, 485–501, https://doi.org/10.1016/0021-9797(80)90587-1, 1980.
Jacobson, M. Z.: Development and application of a new air pollution modeling system – II. Aerosol module structure and design, Atmos. Environ., 31, 131–144, https://doi.org/10.1016/1352-2310(96)00202-6, 1997a.
Jacobson, M. Z.: Numerical Techniques to Solve Condensational and Dissolutional Growth Equations When Growth is Coupled to Reversible Reactions, Aerosol Sci. Tech., 27, 491–498, https://doi.org/10.1080/02786829708965489, 1997b.
Jacobson, M. Z.: Analysis of aerosol interactions with numerical techniques for solving coagulation, nucleation, condensation, dissolution, and reversible chemistry among multiple size distributions, J. Geophys. Res., 107, AAC 2-1–AAC 2-23, https://doi.org/10.1029/2001jd002044, 2002.
Jacobson, M. Z.: Fundamentals of Atmospheric Modeling, 2nd edn., Cambridge University Press, https://doi.org/10.1017/cbo9781139165389, 2005.
Jenkin, M. E., Saunders, S. M., and Pilling, M. J.: The tropospheric degradation of volatile organic compounds: a protocol for mechanism development, Atmos. Environ., 31, 81–104, https://doi.org/10.1016/s1352-2310(96)00105-7, 1997.
Jenkin, M. E., Young, J. C., and Rickard, A. R.: The MCM v3.3.1 degradation scheme for isoprene, Atmos. Chem. Phys., 15, 11433–11459, https://doi.org/10.5194/acp-15-11433-2015, 2015.
Karl, M., Pirjola, L., Grönholm, T., Kurppa, M., Anand, S., Zhang, X., Held, A., Sander, R., Dal Maso, M., Topping, D., Jiang, S., Kangas, L., and Kukkonen, J.: Description and evaluation of the community aerosol dynamics model MAFOR v2.0, Geosci. Model Dev., 15, 3969–4026, https://doi.org/10.5194/gmd-15-3969-2022, 2022.
Kokkola, H., Kühn, T., Laakso, A., Bergman, T., Lehtinen, K. E. J., Mielonen, T., Arola, A., Stadtler, S., Korhonen, H., Ferrachat, S., Lohmann, U., Neubauer, D., Tegen, I., Siegenthaler-Le Drian, C., Schultz, M. G., Bey, I., Stier, P., Daskalakis, N., Heald, C. L., and Romakkaniemi, S.: SALSA2.0: The sectional aerosol module of the aerosol–chemistry–climate model ECHAM6.3.0-HAM2.3-MOZ1.0, Geosci. Model Dev., 11, 3833–3863, https://doi.org/10.5194/gmd-11-3833-2018, 2018.
Kürten, A., Bianchi, F., Almeida, J., Kupiainen-Määttä, O., Dunne, E. M., Duplissy, J., Williamson, C., Barmet, P., Breitenlechner, M., Dommen, J., Donahue, N. M., Flagan, R. C., Franchin, A., Gordon, H., Hakala, J., Hansel, A., Heinritzi, M., Ickes, L., Jokinen, T., Kangasluoma, J., Kim, J., Kirkby, J., Kupc, A., Lehtipalo, K., Leiminger, M., Makhmutov, V., Onnela, A., Ortega, I. K., Petäjä, T., Praplan, A. P., Riccobono, F., Rissanen, M. P., Rondo, L., Schnitzhofer, R., Schobesberger, S., Smith, J. N., Steiner, G., Stozhkov, Y., Tomé, A., Tröstl, J., Tsagkogeorgas, G., Wagner, P. E., Wimmer, D., Ye, P., Baltensperger, U., Carslaw, K., Kulmala, M., and Curtius, J.: Experimental particle formation rates spanning tropospheric sulfuric acid and ammonia abundances, ion production rates, and temperatures, J. Geophys. Res.-Atmos., 121, 12377–12400, https://doi.org/10.1002/2015jd023908, 2016.
Kurtén, T., Tiusanen, K., Roldin, P., Rissanen, M., Luy, J.-N., Boy, M., Ehn, M., and Donahue, N.: α-Pinene Autoxidation Products May Not Have Extremely Low Saturation Vapor Pressures Despite High O:C Ratios, J. Phys. Chem. A, 120, 2569–2582, https://doi.org/10.1021/acs.jpca.6b02196, 2016.
Kylling, A., Webb, A. R., Bais, A. F., Blumthaler, M., Schmitt, R., Thiel, S., Kazantzidis, A., Kift, R., Misslbeck, M., Schallhart, B., Schreder, J., Topaloglou, C., Kazadzis, S., and Rimmer, J.: Actinic flux determination from measurements of irradiance, J. Geophys. Res., 108, ACH 11-1–ACH 11-10, https://doi.org/10.1029/2002jd003236, 2003.
Lai, A. C. K. and Nazaroff, W. W.: Modeling indoor particle deposition from turbulent flow onto smooth surfaces, J. Aerosol Sci., 31, 463–476, https://doi.org/10.1016/S0021-8502(99)00536-4, 2000.
Lehtinen, K. E., Maso, M. D., Kulmala, M., and Kerminen, V.-M.: Estimating nucleation rates from apparent particle formation rates and vice versa: Revised formulation of the Kerminen–Kulmala equation, J. Aerosol Sci., 38, 988–994, https://doi.org/10.1016/j.jaerosci.2007.06.009, 2007.
Matsunaga, A. and Ziemann, P. J.: Gas-Wall Partitioning of Organic Compounds in a Teflon Film Chamber and Potential Effects on Reaction Product and Aerosol Yield Measurements, Aerosol Sci. Tech., 44, 881–892, https://doi.org/10.1080/02786826.2010.501044, 2010.
McGrath, M. J., Olenius, T., Ortega, I. K., Loukonen, V., Paasonen, P., Kurtén, T., Kulmala, M., and Vehkamäki, H.: Atmospheric Cluster Dynamics Code: a flexible method for solution of the birth-death equations, Atmos. Chem. Phys., 12, 2345–2355, https://doi.org/10.5194/acp-12-2345-2012, 2012.
McMurry, P. H. and Grosjean, D.: Gas and aerosol wall losses in Teflon film smog chambers, Environ. Sci. Technol., 19, 1176–1182, https://doi.org/10.1021/es00142a006, 1985.
Mohs, A. J. and Bowman, F. M.: Eliminating Numerical Artifacts When Presenting Moving Center Sectional Aerosol Size Distributions, Aerosol Air Qual. Res., 11, 21–30, https://doi.org/10.4209/aaqr.2010.06.0046, 2011.
Myllys, N., Kubečka, J., Besel, V., Alfaouri, D., Olenius, T., Smith, J. N., and Passananti, M.: Role of base strength, cluster structure and charge in sulfuric-acid-driven particle formation, Atmos. Chem. Phys., 19, 9753–9768, https://doi.org/10.5194/acp-19-9753-2019, 2019.
Nannoolal, Y., Rarey, J., and Ramjugernath, D.: Estimation of pure component properties, Fluid Phase Equilibr., 269, 117–133, https://doi.org/10.1016/j.fluid.2008.04.020, 2008.
O'Meara, S. P., Xu, S., Topping, D., Alfarra, M. R., Capes, G., Lowe, D., Shao, Y., and McFiggans, G.: PyCHAM (v2.1.1): a Python box model for simulating aerosol chambers, Geosci. Model Dev., 14, 675–702, https://doi.org/10.5194/gmd-14-675-2021, 2021.
Olenius, T., Kupiainen-Määttä, O., Ortega, I. K., Kurtén, T., and Vehkamäki, H.: Free energy barrier in the growth of sulfuric acid–ammonia and sulfuric acid–dimethylamine clusters, J. Chem. Phys., 139, 084312, https://doi.org/10.1063/1.4819024, 2013.
O'Meara, S., Booth, A. M., Barley, M. H., Topping, D., and McFiggans, G.: An assessment of vapour pressure estimation methods, Phys. Chem. Chem. Phys., 16, 19453–19469, https://doi.org/10.1039/c4cp00857j, 2014.
Ortega, I. K., Kupiainen, O., Kurtén, T., Olenius, T., Wilkman, O., McGrath, M. J., Loukonen, V., and Vehkamäki, H.: From quantum chemical formation free energies to evaporation rates, Atmos. Chem. Phys., 12, 225–235, https://doi.org/10.5194/acp-12-225-2012, 2012.
Paasonen, P., Nieminen, T., Asmi, E., Manninen, H. E., Petäjä, T., Plass-Dülmer, C., Flentje, H., Birmili, W., Wiedensohler, A., Hõrrak, U., Metzger, A., Hamed, A., Laaksonen, A., Facchini, M. C., Kerminen, V.-M., and Kulmala, M.: On the roles of sulphuric acid and low-volatility organic vapours in the initial steps of atmospheric new particle formation, Atmos. Chem. Phys., 10, 11223–11242, https://doi.org/10.5194/acp-10-11223-2010, 2010.
Pankow, J. F.: An absorption model of gas/particle partitioning of organic compounds in the atmosphere, Atmos. Environ., 28, 185–188, https://doi.org/10.1016/1352-2310(94)90093-0, 1994.
Pankow, J. F. and Asher, W. E.: SIMPOL.1: a simple group contribution method for predicting vapor pressures and enthalpies of vaporization of multifunctional organic compounds, Atmos. Chem. Phys., 8, 2773–2796, https://doi.org/10.5194/acp-8-2773-2008, 2008.
Pathak, R. K., Stanier, C. O., Donahue, N. M., and Pandis, S. N.: Ozonolysis of α-pinene at atmospherically relevant concentrations: Temperature dependence of aerosol mass fractions (yields), J. Geophys. Res., 112, D03201, https://doi.org/10.1029/2006jd007436, 2007.
Peng, Z. and Jimenez, J. L.: KinSim: A Research-Grade, User-Friendly, Visual Kinetics Simulator for Chemical-Kinetics and Environmental-Chemistry Teaching, J. Chem. Educ., 96, 806–811, https://doi.org/10.1021/acs.jchemed.9b00033, 2019.
Pichelstorfer, L. and Hofmann, W.: Modeling aerosol dynamics of cigarette smoke in a denuder tube, J. Aerosol Sci., 88, 72–89, https://doi.org/10.1016/j.jaerosci.2015.05.009, 2015.
Pichelstorfer, L., Winkler-Heil, R., Boy, M., and Hofmann, W.: Aerosol dynamics simulations of the anatomical variability of e-cigarette particle and vapor deposition in a stochastic lung, J. Aerosol Sci., 158, 105706, https://doi.org/10.1016/j.jaerosci.2020.105706, 2021.
Pierce, J. R., Engelhart, G. J., Hildebrandt, L., Weitkamp, E. A., Pathak, R. K., Donahue, N. M., Robinson, A. L., Adams, P. J., and Pandis, S. N.: Constraining Particle Evolution from Wall Losses, Coagulation, and Condensation-Evaporation in Smog-Chamber Experiments: Optimal Estimation Based on Size Distribution Measurements, Aerosol Sci. Tech., 42, 1001–1015, https://doi.org/10.1080/02786820802389251, 2008.
Riipinen, I., Pierce, J. R., Donahue, N. M., and Pandis, S. N.: Equilibration time scales of organic aerosol inside thermodenuders: Evaporation kinetics versus thermodynamics, Atmos. Environ., 44, 597–607, https://doi.org/10.1016/j.atmosenv.2009.11.022, 2010.
Roldin, P., Swietlicki, E., Schurgers, G., Arneth, A., Lehtinen, K. E. J., Boy, M., and Kulmala, M.: Development and evaluation of the aerosol dynamics and gas phase chemistry model ADCHEM, Atmos. Chem. Phys., 11, 5867–5896, https://doi.org/10.5194/acp-11-5867-2011, 2011.
Roldin, P., Eriksson, A. C., Nordin, E. Z., Hermansson, E., Mogensen, D., Rusanen, A., Boy, M., Swietlicki, E., Svenningsson, B., Zelenyuk, A., and Pagels, J.: Modelling non-equilibrium secondary organic aerosol formation and evaporation with the aerosol dynamics, gas- and particle-phase chemistry kinetic multilayer model ADCHAM, Atmos. Chem. Phys., 14, 7953–7993, https://doi.org/10.5194/acp-14-7953-2014, 2014.
Roldin, P., Ehn, M., Kurtén, T., Olenius, T., Rissanen, M. P., Sarnela, N., Elm, J., Rantala, P., Hao, L., Hyttinen, N., Heikkinen, L., Worsnop, D. R., Pichelstorfer, L., Xavier, C., Clusius, P., Öström, E., Petäjä, T., Kulmala, M., Vehkamäki, H., Virtanen, A., Riipinen, I., and Boy, M.: The role of highly oxygenated organic molecules in the Boreal aerosol-cloud-climate system, Nat. Commun., 10, 4370, https://doi.org/10.1038/s41467-019-12338-8, 2019.
Rose, C., Chaumerliac, N., Deguillaume, L., Perroux, H., Mouchel-Vallon, C., Leriche, M., Patryl, L., and Armand, P.: Modeling the partitioning of organic chemical species in cloud phases with CLEPS (1.1), Atmos. Chem. Phys., 18, 2225–2242, https://doi.org/10.5194/acp-18-2225-2018, 2018.
Sandu, A., Verwer, J., Blom, J., Spee, E., Carmichael, G., and Potra, F.: Benchmarking stiff ode solvers for atmospheric chemistry problems II: Rosenbrock solvers, Atmos. Environ., 31, 3459–3472, https://doi.org/10.1016/s1352-2310(97)83212-8, 1997.
Sandu, A., Daescu, D., and Carmichael, G.R.: Direct and Adjoint Sensitivity Analysis of Chemical Kinetic Systems with KPP: I – Theory and Software Tools, Atmos. Environ., 37, 5083–5096, 2003.
Saunders, S. M., Jenkin, M. E., Derwent, R. G., and Pilling, M. J.: Protocol for the development of the Master Chemical Mechanism, MCM v3 (Part A): tropospheric degradation of non-aromatic volatile organic compounds, Atmos. Chem. Phys., 3, 161–180, https://doi.org/10.5194/acp-3-161-2003, 2003.
Seinfeld, J. H. and Pandis, S. N.: Atmospheric Chemistry and Physics – From Air Pollution to Climate Change, 3rd edn., Wiley-Interscience, ISBN: 978-1-118-94740-1, 2016.
Shiraiwa, M., Pfrang, C., and Pöschl, U.: Kinetic multi-layer model of aerosol surface and bulk chemistry (KM-SUB): the influence of interfacial transport and bulk diffusion on the oxidation of oleic acid by ozone, Atmos. Chem. Phys., 10, 3673–3691, https://doi.org/10.5194/acp-10-3673-2010, 2010.
Smith, J. N., Draper, D. C., Chee, S., Dam, M., Glicker, H., Myers, D., Thomas, A. E., Lawler, M. J., and Myllys, N.: Atmospheric clusters to nanoparticles: Recent progress and challenges in closing the gap in chemical composition, J. Aerosol Sci., 153, 105733, https://doi.org/10.1016/j.jaerosci.2020.105733, 2021.
Su, T. and Chesnavich, W. J.: Parametrization of the ion–polar molecule collision rate constant by trajectory calculations, J. Chem. Phys., 76, 5183–5185, https://doi.org/10.1063/1.442828, 1982.
Topping, D., Connolly, P., and Reid, J.: PyBox: An automated box-model generator for atmospheric chemistry and aerosol simulations, Journal of Open Source Software, 3, 755, https://doi.org/10.21105/joss.00755, 2018.
Tsang, T. H. and Brock, J. R.: Simulation of Condensation Aerosol Growth by Condensation and Evaporation, Aerosol Sci. Tech., 2, 311–320, https://doi.org/10.1080/02786828308958637, 1982.
Valorso, R., Aumont, B., Camredon, M., Raventos-Duran, T., Mouchel-Vallon, C., Ng, N. L., Seinfeld, J. H., Lee-Taylor, J., and Madronich, S.: Explicit modelling of SOA formation from α-pinene photooxidation: sensitivity to vapour pressure estimation, Atmos. Chem. Phys., 11, 6895–6910, https://doi.org/10.5194/acp-11-6895-2011, 2011.
Vignati, E., Wilson, J., and Stier, P.: M7: An efficient size-resolved aerosol microphysics module for large-scale aerosol transport models, J. Geophys. Res.-Atmos., 109, D22202, https://doi.org/10.1029/2003jd004485, 2004.
von Smoluchowski, M.: Versuch einer mathematischen Theorie der Koagulationskinetik kolloider Lösungen, Z. Phys. Chem., 92U, 129–168, https://doi.org/10.1515/zpch-1918-9209, 1918.
Wagner, P. E.: Topics in Current Physics, in: Aerosol Microphysics II: Chemical Physics of Microparticles, edited by: Marlow, W. H., Springer, Berlin, Heidelberg, 129–178, https://doi.org/10.1007/978-3-642-81805-9_5, 1982.
Whitby, E. R. and McMurry, P. H.: Modal Aerosol Dynamics Modeling, Aerosol Sci. Tech., 27, 673–688, https://doi.org/10.1080/02786829708965504, 1997.
Wollesen de Jonge, R., Elm, J., Rosati, B., Christiansen, S., Hyttinen, N., Lüdemann, D., Bilde, M., and Roldin, P.: Secondary aerosol formation from dimethyl sulfide – improved mechanistic understanding based on smog chamber experiments and modelling, Atmos. Chem. Phys., 21, 9955–9976, https://doi.org/10.5194/acp-21-9955-2021, 2021.
Xavier, C., Rusanen, A., Zhou, P., Dean, C., Pichelstorfer, L., Roldin, P., and Boy, M.: Aerosol mass yields of selected biogenic volatile organic compounds – a theoretical study with nearly explicit gas-phase chemistry, Atmos. Chem. Phys., 19, 13741–13758, https://doi.org/10.5194/acp-19-13741-2019, 2019.
Xavier, C., Baykara, M., Wollesen de Jonge, R., Altstädter, B., Clusius, P., Vakkari, V., Thakur, R., Beck, L., Becagli, S., Severi, M., Traversi, R., Krejci, R., Tunved, P., Mazzola, M., Wehner, B., Sipilä, M., Kulmala, M., Boy, M., and Roldin, P.: Secondary aerosol formation in marine Arctic environments: a model measurement comparison at Ny-Ålesund, Atmos. Chem. Phys., 22, 10023–10043, https://doi.org/10.5194/acp-22-10023-2022, 2022.
Yli-Juuti, T., Barsanti, K., Hildebrandt Ruiz, L., Kieloaho, A.-J., Makkonen, U., Petäjä, T., Ruuskanen, T., Kulmala, M., and Riipinen, I.: Model for acid-base chemistry in nanoparticle growth (MABNAG), Atmos. Chem. Phys., 13, 12507–12524, https://doi.org/10.5194/acp-13-12507-2013, 2013.
Zhang, Q., Jimenez, J. L., Canagaratna, M. R., Allan, J. D., Coe, H., Ulbrich, I., Alfarra, M. R., Takami, A., Middlebrook, A. M., Sun, Y. L., Dzepina, K., Dunlea, E., Docherty, K., DeCarlo, P. F., Salcedo, D., Onasch, T., Jayne, J. T., Miyoshi, T., Shimono, A., Hatakeyama, S., Takegawa, N., Kondo, Y., Schneider, J., Drewnick, F., Borrmann, S., Weimer, S., Demerjian, K., Williams, P., Bower, K., Bahreini, R., Cottrell, L., Griffin, R. J., Rautiainen, J., Sun, J. Y., Zhang, Y. M., and Worsnop, D. R.: Ubiquity and dominance of oxygenated species in organic aerosols in anthropogenically-influenced Northern Hemisphere midlatitudes, Geophys. Res. Lett., 34, L13801, https://doi.org/10.1029/2007gl029979, 2007.
Zhang, X., Cappa, C. D., Jathar, S. H., McVay, R. C., Ensberg, J. J., Kleeman, M. J., and Seinfeld, J. H.: Influence of vapor wall loss in laboratory chambers on yields of secondary organic aerosol, P. Natl. Acad. Sci. USA, 111, 5802–5807, https://doi.org/10.1073/pnas.1404727111, 2014.
Zhang, Y., Seigneur, C., Seinfeld, J. H., Jacobson, M. Z., and Binkowski, F. S.: Simulation of Aerosol Dynamics: A Comparative Review of Algorithms Used in Air Quality Models, Aerosol Sci. Tech., 31, 487–514, https://doi.org/10.1080/027868299304039, 1999.
Short summary
Atmospheric chemistry and aerosol processes form a dynamic and sensitively balanced system, and solving problems regarding air quality or climate requires detailed modelling and coupling of the processes. The models involved are often very complex to use. We have addressed this problem with the new ARCA box model. It puts much of the current knowledge of the nano- and microscale aerosol dynamics and chemistry into usable software and has the potential to become a valuable tool in the community.
Atmospheric chemistry and aerosol processes form a dynamic and sensitively balanced system, and...