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.
Model description paper
| 
29 Sep 2022
Model description paper |
| 29 Sep 2022
| 29 Sep 2022
Atmospherically Relevant Chemistry and Aerosol box model – ARCA box (version 1.2)
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
Related authors
Petri Clusius, Metin Baykara, Carlton Xavier, Putian Zhou, Juniper Tyree, Benjamin Foreback, Mikko Äijälä, Frans Graeffe, Tuukka Petäjä, Markku Kulmala, Pauli Paasonen, Paul I. Palmer, and Michael Boy
EGUsphere, https://doi.org/10.5194/egusphere-2025-39, https://doi.org/10.5194/egusphere-2025-39, 2025
Short summary
Short summary
Cloud condensation nuclei are necessary to form clouds, and their size distribution affects cloud properties and therefore Earth’s energy budget. This study modelled the origins of cloud condensation nuclei at SMEAR II, Hyytiälä, Finland, and found that primary emissions and new particle formation separately contribute to more than half of the condensation nuclei, but they suppress each other, leading to current concentrations. Largest condensation nuclei originated mostly from emissions.
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.
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
Short summary
Short summary
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
Short summary
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.
Steven T. Turnock, Dimitris Akritidis, Larry Horowitz, Mariano Mertens, Andrea Pozzer, Carly L. Reddington, Hantao Wang, Putian Zhou, and Fiona O'Connor
Atmos. Chem. Phys., 25, 7111–7136, https://doi.org/10.5194/acp-25-7111-2025, https://doi.org/10.5194/acp-25-7111-2025, 2025
Short summary
Short summary
We assess the drivers behind changes in peak-season surface ozone concentrations and risks to human health between 1850 and 2014. Substantial increases in surface ozone have occurred over this period, resulting in an increased risk to human health, driven mainly by increases in anthropogenic NOx emissions and global CH4 concentrations. Fixing anthropogenic NOx emissions at 1850 values in the near-present-day period can eliminate the risk to human health associated with exposure to surface ozone.
Yunfeng He, Xiang Ding, Quanfu He, Yuqing Zhang, Duohong Chen, Tao Zhang, Kong Yang, Junqi Wang, Qian Cheng, Hao Jiang, Zirui Wang, Ping Liu, Xinming Wang, and Michael Boy
EGUsphere, https://doi.org/10.5194/egusphere-2025-2204, https://doi.org/10.5194/egusphere-2025-2204, 2025
Short summary
Short summary
The long-term field measurements in the Pearl River Delta revealed a significant decline in PM2.5 main components. As air quality improved, secondary species became more dominant. In addition, the proportion of nitrate had doubled. The changes in chemical composition led to the reductions in aerosol acidity, liquid water content and light extinction coefficient. Our results help to improve understanding of the secondary species formation under decreasing anthropogenic emissions.
Xinyang Li, Tuomo Nieminen, Rima Baalbaki, Putian Zhou, Pauli Paasonen, Risto Makkonen, Martha Arbayani Zaidan, Nina Sarnela, Chao Yan, Tuija Jokinen, Imre Salma, Máté Vörösmarty, Tuukka Petäjä, Veli-Matti Kerminen, Markku Kulmala, and Lubna Dada
Aerosol Research, 3, 271–291, https://doi.org/10.5194/ar-3-271-2025, https://doi.org/10.5194/ar-3-271-2025, 2025
Short summary
Short summary
Particle formation rate is one of the key factors in studying the physical properties of aerosols. By developing powerful and simple semi-empirical particle formation rate models, we can predict particle formation rates and compare them with real-time measurements to aid in discovering hidden particle formation mechanisms as well as global simulations of particle population to fill the knowledge gap caused by the uncertainty in aerosol cooling effects on Earth's atmosphere.
Petri Clusius, Metin Baykara, Carlton Xavier, Putian Zhou, Juniper Tyree, Benjamin Foreback, Mikko Äijälä, Frans Graeffe, Tuukka Petäjä, Markku Kulmala, Pauli Paasonen, Paul I. Palmer, and Michael Boy
EGUsphere, https://doi.org/10.5194/egusphere-2025-39, https://doi.org/10.5194/egusphere-2025-39, 2025
Short summary
Short summary
Cloud condensation nuclei are necessary to form clouds, and their size distribution affects cloud properties and therefore Earth’s energy budget. This study modelled the origins of cloud condensation nuclei at SMEAR II, Hyytiälä, Finland, and found that primary emissions and new particle formation separately contribute to more than half of the condensation nuclei, but they suppress each other, leading to current concentrations. Largest condensation nuclei originated mostly from emissions.
Carl Svenhag, Pontus Roldin, Tinja Olenius, Robin Wollesen de Jonge, Sara Blichner, Daniel Yazgi, and Moa Sporre
EGUsphere, https://doi.org/10.5194/egusphere-2024-3626, https://doi.org/10.5194/egusphere-2024-3626, 2024
Short summary
Short summary
This study investigates the model representation of how particles are formed and grow in the atmosphere. Using modeled and observed data from two boreal forest stations in 2018, we identify key factors for NPF to improve particle-climate predictions in the global EC-Earth3 model. Comparisons with the detailed ADCHEM model show that adding ammonia improves particle growth predictions, though EC-Earth3 still highly underestimates the number of particles during warmer months.
Zoé Brasseur, Julia Schneider, Janne Lampilahti, Ville Vakkari, Victoria A. Sinclair, Christina J. Williamson, Carlton Xavier, Dmitri Moisseev, Markus Hartmann, Pyry Poutanen, Markus Lampimäki, Markku Kulmala, Tuukka Petäjä, Katrianne Lehtipalo, Erik S. Thomson, Kristina Höhler, Ottmar Möhler, and Jonathan Duplissy
Atmos. Chem. Phys., 24, 11305–11332, https://doi.org/10.5194/acp-24-11305-2024, https://doi.org/10.5194/acp-24-11305-2024, 2024
Short summary
Short summary
Ice-nucleating particles (INPs) strongly influence the formation of clouds by initiating the formation of ice crystals. However, very little is known about the vertical distribution of INPs in the atmosphere. Here, we present aircraft measurements of INP concentrations above the Finnish boreal forest. Results show that near-surface INPs are efficiently transported and mixed within the boundary layer and occasionally reach the free troposphere.
Yuanyuan Luo, Ditte Thomsen, Emil Mark Iversen, Pontus Roldin, Jane Tygesen Skønager, Linjie Li, Michael Priestley, Henrik B. Pedersen, Mattias Hallquist, Merete Bilde, Marianne Glasius, and Mikael Ehn
Atmos. Chem. Phys., 24, 9459–9473, https://doi.org/10.5194/acp-24-9459-2024, https://doi.org/10.5194/acp-24-9459-2024, 2024
Short summary
Short summary
∆3-carene is abundantly emitted from vegetation, but its atmospheric oxidation chemistry has received limited attention. We explored highly oxygenated organic molecule (HOM) formation from ∆3-carene ozonolysis in chambers and investigated the impact of temperature and relative humidity on HOM formation. Our findings provide new insights into ∆3-carene oxidation pathways and their potential to impact atmospheric aerosols.
Carl Svenhag, Moa K. Sporre, Tinja Olenius, Daniel Yazgi, Sara M. Blichner, Lars P. Nieradzik, and Pontus Roldin
Geosci. Model Dev., 17, 4923–4942, https://doi.org/10.5194/gmd-17-4923-2024, https://doi.org/10.5194/gmd-17-4923-2024, 2024
Short summary
Short summary
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 show that using a new method for NPF modeling, which includes new detailed processes with NH3 and H2SO4, significantly impacts the number of particles in the air and clouds and changes the radiation balance of the same magnitude as anthropogenic greenhouse emissions.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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...
