Articles | Volume 25, issue 1
https://doi.org/10.5194/acp-25-685-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-685-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Technical note
| 
17 Jan 2025
Technical note |
| 17 Jan 2025
| 17 Jan 2025
Technical note: Towards atmospheric compound identification in chemical ionization mass spectrometry with pesticide standards and machine learning
Federica Bortolussi
CORRESPONDING AUTHOR
Department of Chemistry, University of Helsinki, 00560 Helsinki, Finland
Hilda Sandström
Department of Applied Physics, Aalto University, Espoo, Finland
Fariba Partovi
Aerosol Physics Laboratory, Physics Unit, Tampere University, 33720 Tampere, Finland
Karsa Ltd., A. I. Virtasen aukio 1, 00560 Helsinki, Finland
Joona Mikkilä
Karsa Ltd., A. I. Virtasen aukio 1, 00560 Helsinki, Finland
Patrick Rinke
Department of Applied Physics, Aalto University, Espoo, Finland
Physics Department, TUM School of Natural Sciences, Technical University of Munich, Garching, Germany
Atomistic Modelling Center, Munich Data Science Institute, Technical University of Munich, Garching, Germany
Munich Center for Machine Learning (MCML), Munich, Germany
Matti Rissanen
Department of Chemistry, University of Helsinki, 00560 Helsinki, Finland
Aerosol Physics Laboratory, Physics Unit, Tampere University, 33720 Tampere, Finland
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Neil M. Donahue, Victoria Hofbauer, Henning Finkenzeller, Dominik Stolzenburg, Paulus S. Bauer, Randall Chiu, Lubna Dada, Jonathan Duplissy, Xu-Cheng He, Martin Heinritzi, Christopher R. Hoyle, Andreas Kürten, Aleksandr Kvashnin, Katrianne Lehtipalo, Naser Mahfouz, Vladimir Makhmutov, Roy L. Mauldin III, Ugo Molteni, Lauriane L. J. Quéléver, Matti Rissanen, Siegfried Schobesberger, Mario Simon, Andrea C. Wagner, Mingyi Wang, Chao Yan, Penglin Ye, Ilona Riipinen, Hamish Gordon, Joachim Curtius, Armin Hansel, Imad El Haddad, Markku Kulmala, Douglas R. Worsnop, Rainer Volkamer, Paul M. Winkler, Jasper Kirkby, and Richard Flagan
EGUsphere, https://doi.org/10.5194/egusphere-2025-2412, https://doi.org/10.5194/egusphere-2025-2412, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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We describe accurate measurement of particle formation and growth in the CERN CLOUD chamber, using a suite of gas- and particle-phase instruments. The interconnected measurements establish high accuracy in key particle properties and critically important gas-phase sulfuric acid. This is a template for accurate calibration of similar experiments and thus accurate determination of aerosol nucleation and growth rates, which are an important source of uncertainty in climate science.
Mojtaba Bezaatpour, Miikka Dal Maso, and Matti Rissanen
EGUsphere, https://doi.org/10.5194/egusphere-2025-2564, https://doi.org/10.5194/egusphere-2025-2564, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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We developed a computer program that can read chemical formulas and identify key features in thousands of organic compounds. This helps scientists estimate how easily these compounds evaporate, which is important for understanding air pollution and climate. We tested the program using real-world data and found it to be highly accurate. Our work makes it faster and easier to study the behavior of many complex chemicals in the atmosphere.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
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Machine learning has the potential to aid the identification of organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning models in atmospheric sciences.
Henning Finkenzeller, Jyri Mikkilä, Cecilia Righi, Paxton Juuti, Mikko Sipilä, Matti Rissanen, Douglas Worsnop, Aleksei Shcherbinin, Nina Sarnela, and Juha Kangasluoma
Atmos. Meas. Tech., 17, 5989–6001, https://doi.org/10.5194/amt-17-5989-2024, https://doi.org/10.5194/amt-17-5989-2024, 2024
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Chemical ionisation mass spectrometry is used in the atmospheric sciences to measure trace gas concentrations. Neutral gases require charging in inlets before the mass-to-charge ratio of the resulting ions can be analysed. This study uses multiphysics modelling to investigate how the MION2 and Eisele type inlets work and shows the effect of tuning parameters and their current limitations. The findings are helpful for inlet users and are expected to aid in developing improved inlets.
Alex Rowell, James Brean, David C. S. Beddows, Zongbo Shi, Avinash Kumar, Matti Rissanen, Miikka Dal Maso, Peter Mettke, Kay Weinhold, Maik Merkel, and Roy M. Harrison
Atmos. Chem. Phys., 24, 10349–10361, https://doi.org/10.5194/acp-24-10349-2024, https://doi.org/10.5194/acp-24-10349-2024, 2024
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Ions enhance the formation and growth rates of new particles, affecting the Earth's radiation budget. Despite these effects, there is little published data exploring the sources of ions in the urban environment and their role in new particle formation (NPF). Here we show that natural ion sources dominate in urban environments, while traffic is a secondary source. Ions contribute up to 12.7 % of the formation rate of particles, indicating that they are important for forming urban PM.
Stéphanie Alage, Vincent Michoud, Sergio Harb, Bénédicte Picquet-Varrault, Manuela Cirtog, Avinash Kumar, Matti Rissanen, and Christopher Cantrell
Atmos. Meas. Tech., 17, 4709–4724, https://doi.org/10.5194/amt-17-4709-2024, https://doi.org/10.5194/amt-17-4709-2024, 2024
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Calibration exercises are essential for determining the accuracy of instruments. We performed calibrations on a NO3¯ ToFCIMS instrument to determine its sensitivity and linearity for detecting various organic compounds. Our findings revealed significant variability, over several orders of magnitude, in the calibration factors obtained. The results suggest that relying on a single calibration factor from H2SO4 for the quantification of all compounds detected by this technique is not appropriate.
Romain Salignat, Matti Rissanen, Siddharth Iyer, Jean-Luc Baray, Pierre Tulet, Jean-Marc Metzger, Jérôme Brioude, Karine Sellegri, and Clémence Rose
Atmos. Chem. Phys., 24, 3785–3812, https://doi.org/10.5194/acp-24-3785-2024, https://doi.org/10.5194/acp-24-3785-2024, 2024
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Using mass spectrometry data collected at the Maïdo Observatory (2160 m a.s.l., Réunion), we provide the first detailed analysis of molecular cluster chemical composition specifically in the marine free troposphere. The abundance of the identified species is related both to in situ meteorological parameters and air mass history, which also provide insight into their origin. Our work makes an important contribution to documenting the chemistry and physics of the marine free troposphere.
Xu-Cheng He, Jiali Shen, Siddharth Iyer, Paxton Juuti, Jiangyi Zhang, Mrisha Koirala, Mikko M. Kytökari, Douglas R. Worsnop, Matti Rissanen, Markku Kulmala, Norbert M. Maier, Jyri Mikkilä, Mikko Sipilä, and Juha Kangasluoma
Atmos. Meas. Tech., 16, 4461–4487, https://doi.org/10.5194/amt-16-4461-2023, https://doi.org/10.5194/amt-16-4461-2023, 2023
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In this study, the upgraded multi-scheme chemical ionisation inlet 2 is presented. Sulfuric acid, hypoiodous acid, iodine, sulfur dioxide, and hydroperoxyl radicals are calibrated, and the improved ion optics allow us to detect sulfuric acid and iodine-containing molecules at as low as a few parts per quadrillion by volume. Additionally, we confirm the reliable detection of iodic acid using both the nitrate and bromide chemical ionisation methods under atmospherically relevant conditions.
Shawon Barua, Siddharth Iyer, Avinash Kumar, Prasenjit Seal, and Matti Rissanen
Atmos. Chem. Phys., 23, 10517–10532, https://doi.org/10.5194/acp-23-10517-2023, https://doi.org/10.5194/acp-23-10517-2023, 2023
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This work illustrates how a common volatile hydrocarbon, hexanal, has the potential to undergo atmospheric autoxidation that leads to prompt formation of condensable material that subsequently contributes to aerosol formation, deteriorating the air quality of urban atmospheres. We used the combined state-of-the-art quantum chemical modeling and experimental flow reactor experiments under atmospheric conditions to resolve the autoxidation mechanism of hexanal initiated by a common oxidant.
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.
Melissa Meder, Otso Peräkylä, Jonathan G. Varelas, Jingyi Luo, Runlong Cai, Yanjun Zhang, Theo Kurtén, Matthieu Riva, Matti Rissanen, Franz M. Geiger, Regan J. Thomson, and Mikael Ehn
Atmos. Chem. Phys., 23, 4373–4390, https://doi.org/10.5194/acp-23-4373-2023, https://doi.org/10.5194/acp-23-4373-2023, 2023
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We discuss and show the viability of a method where multiple isotopically labelled precursors are used for probing the formation pathways of highly oxygenated organic molecules (HOMs) from the oxidation of the monoterpene a-pinene. HOMs are very important for secondary organic aerosol (SOA) formation in forested regions, and monoterpenes are the single largest source of SOA globally. The fast reactions forming HOMs have thus far remained elusive despite considerable efforts over the last decade.
Miska Olin, Magdalena Okuljar, Matti P. Rissanen, Joni Kalliokoski, Jiali Shen, Lubna Dada, Markus Lampimäki, Yusheng Wu, Annalea Lohila, Jonathan Duplissy, Mikko Sipilä, Tuukka Petäjä, Markku Kulmala, and Miikka Dal Maso
Atmos. Chem. Phys., 22, 8097–8115, https://doi.org/10.5194/acp-22-8097-2022, https://doi.org/10.5194/acp-22-8097-2022, 2022
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Atmospheric new particle formation is an important source of the total particle number concentration in the atmosphere. Several parameters for predicting new particle formation events have been suggested before, but the results have been inconclusive. This study proposes an another predicting parameter, related to a specific type of highly oxidized organic molecules, especially for similar locations to the measurement site in this study, which was a coastal agricultural site in Finland.
Dalrin Ampritta Amaladhasan, Claudia Heyn, Christopher R. Hoyle, Imad El Haddad, Miriam Elser, Simone M. Pieber, Jay G. Slowik, Antonio Amorim, Jonathan Duplissy, Sebastian Ehrhart, Vladimir Makhmutov, Ugo Molteni, Matti Rissanen, Yuri Stozhkov, Robert Wagner, Armin Hansel, Jasper Kirkby, Neil M. Donahue, Rainer Volkamer, Urs Baltensperger, Martin Gysel-Beer, and Andreas Zuend
Atmos. Chem. Phys., 22, 215–244, https://doi.org/10.5194/acp-22-215-2022, https://doi.org/10.5194/acp-22-215-2022, 2022
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We use a combination of models for gas-phase chemical reactions and equilibrium gas–particle partitioning of isoprene-derived secondary organic aerosols (SOAs) informed by dark ozonolysis experiments conducted in the CLOUD chamber. Our predictions cover high to low relative humidities (RHs) and quantify how SOA mass yields are enhanced at high RH as well as the impact of inorganic seeds of distinct hygroscopicities and acidities on the coupled partitioning of water and semi-volatile organics.
Mao Xiao, Christopher R. Hoyle, Lubna Dada, Dominik Stolzenburg, Andreas Kürten, Mingyi Wang, Houssni Lamkaddam, Olga Garmash, Bernhard Mentler, Ugo Molteni, Andrea Baccarini, Mario Simon, Xu-Cheng He, Katrianne Lehtipalo, Lauri R. Ahonen, Rima Baalbaki, Paulus S. Bauer, Lisa Beck, David Bell, Federico Bianchi, Sophia Brilke, Dexian Chen, Randall Chiu, António Dias, Jonathan Duplissy, Henning Finkenzeller, Hamish Gordon, Victoria Hofbauer, Changhyuk Kim, Theodore K. Koenig, Janne Lampilahti, Chuan Ping Lee, Zijun Li, Huajun Mai, Vladimir Makhmutov, Hanna E. Manninen, Ruby Marten, Serge Mathot, Roy L. Mauldin, Wei Nie, Antti Onnela, Eva Partoll, Tuukka Petäjä, Joschka Pfeifer, Veronika Pospisilova, Lauriane L. J. Quéléver, Matti Rissanen, Siegfried Schobesberger, Simone Schuchmann, Yuri Stozhkov, Christian Tauber, Yee Jun Tham, António Tomé, Miguel Vazquez-Pufleau, Andrea C. Wagner, Robert Wagner, Yonghong Wang, Lena Weitz, Daniela Wimmer, Yusheng Wu, Chao Yan, Penglin Ye, Qing Ye, Qiaozhi Zha, Xueqin Zhou, Antonio Amorim, Ken Carslaw, Joachim Curtius, Armin Hansel, Rainer Volkamer, Paul M. Winkler, Richard C. Flagan, Markku Kulmala, Douglas R. Worsnop, Jasper Kirkby, Neil M. Donahue, Urs Baltensperger, Imad El Haddad, and Josef Dommen
Atmos. Chem. Phys., 21, 14275–14291, https://doi.org/10.5194/acp-21-14275-2021, https://doi.org/10.5194/acp-21-14275-2021, 2021
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Experiments at CLOUD show that in polluted environments new particle formation (NPF) is largely driven by the formation of sulfuric acid–base clusters, stabilized by amines, high ammonia concentrations or lower temperatures. While oxidation products of aromatics can nucleate, they play a minor role in urban NPF. Our experiments span 4 orders of magnitude variation of observed NPF rates in ambient conditions. We provide a framework based on NPF and growth rates to interpret ambient observations.
Emma Lumiaro, Milica Todorović, Theo Kurten, Hanna Vehkamäki, and Patrick Rinke
Atmos. Chem. Phys., 21, 13227–13246, https://doi.org/10.5194/acp-21-13227-2021, https://doi.org/10.5194/acp-21-13227-2021, 2021
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The study of climate change relies on climate models, which require an understanding of aerosol formation. We train a machine-learning model to predict the partitioning coefficients of atmospheric molecules, which govern condensation into aerosols. The model can make instant predictions based on molecular structures with accuracy surpassing that of standard computational methods. This will allow the screening of low-volatility molecules that contribute most to aerosol formation.
Mingyi Wang, Xu-Cheng He, Henning Finkenzeller, Siddharth Iyer, Dexian Chen, Jiali Shen, Mario Simon, Victoria Hofbauer, Jasper Kirkby, Joachim Curtius, Norbert Maier, Theo Kurtén, Douglas R. Worsnop, Markku Kulmala, Matti Rissanen, Rainer Volkamer, Yee Jun Tham, Neil M. Donahue, and Mikko Sipilä
Atmos. Meas. Tech., 14, 4187–4202, https://doi.org/10.5194/amt-14-4187-2021, https://doi.org/10.5194/amt-14-4187-2021, 2021
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Atmospheric iodine species are often short-lived with low abundance and have thus been challenging to measure. We show that the bromide chemical ionization mass spectrometry, compatible with both the atmospheric pressure and reduced pressure interfaces, can simultaneously detect various gas-phase iodine species. Combining calibration experiments and quantum chemical calculations, we quantify detection sensitivities to HOI, HIO3, I2, and H2SO4, giving detection limits down to < 106 molec. cm-3.
Meri Räty, Otso Peräkylä, Matthieu Riva, Lauriane Quéléver, Olga Garmash, Matti Rissanen, and Mikael Ehn
Atmos. Chem. Phys., 21, 7357–7372, https://doi.org/10.5194/acp-21-7357-2021, https://doi.org/10.5194/acp-21-7357-2021, 2021
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Cyclohexene resembles certain relatively complex compounds in the atmosphere that through oxidation produce vapours that take part in aerosol formation. We studied the highly oxygenated organic molecules (HOMs) formed in cyclohexene ozonolysis, the relationship between their chemical composition and their tendency to condense onto seed aerosol, as well as the effect of NOx pollutants on their signals. Two existing models were also tested for their ability to predict the volatility of the HOMs.
Clémence Rose, Matti P. Rissanen, Siddharth Iyer, Jonathan Duplissy, Chao Yan, John B. Nowak, Aurélie Colomb, Régis Dupuy, Xu-Cheng He, Janne Lampilahti, Yee Jun Tham, Daniela Wimmer, Jean-Marc Metzger, Pierre Tulet, Jérôme Brioude, Céline Planche, Markku Kulmala, and Karine Sellegri
Atmos. Chem. Phys., 21, 4541–4560, https://doi.org/10.5194/acp-21-4541-2021, https://doi.org/10.5194/acp-21-4541-2021, 2021
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Sulfuric acid (H2SO4) is commonly accepted as a key precursor for atmospheric new particle formation. However, direct measurements of [H2SO4] remain challenging, motivating the development of proxies. Using data collected in two different volcanic plumes, we show, under these specific conditions, the good performance of a proxy from the literature and also highlight the benefit of the newly developed proxies for the prediction of the highest [H2SO4] values.
Martin Heinritzi, Lubna Dada, Mario Simon, Dominik Stolzenburg, Andrea C. Wagner, Lukas Fischer, Lauri R. Ahonen, Stavros Amanatidis, Rima Baalbaki, Andrea Baccarini, Paulus S. Bauer, Bernhard Baumgartner, Federico Bianchi, Sophia Brilke, Dexian Chen, Randall Chiu, Antonio Dias, Josef Dommen, Jonathan Duplissy, Henning Finkenzeller, Carla Frege, Claudia Fuchs, Olga Garmash, Hamish Gordon, Manuel Granzin, Imad El Haddad, Xucheng He, Johanna Helm, Victoria Hofbauer, Christopher R. Hoyle, Juha Kangasluoma, Timo Keber, Changhyuk Kim, Andreas Kürten, Houssni Lamkaddam, Tiia M. Laurila, Janne Lampilahti, Chuan Ping Lee, Katrianne Lehtipalo, Markus Leiminger, Huajun Mai, Vladimir Makhmutov, Hanna Elina Manninen, Ruby Marten, Serge Mathot, Roy Lee Mauldin, Bernhard Mentler, Ugo Molteni, Tatjana Müller, Wei Nie, Tuomo Nieminen, Antti Onnela, Eva Partoll, Monica Passananti, Tuukka Petäjä, Joschka Pfeifer, Veronika Pospisilova, Lauriane L. J. Quéléver, Matti P. Rissanen, Clémence Rose, Siegfried Schobesberger, Wiebke Scholz, Kay Scholze, Mikko Sipilä, Gerhard Steiner, Yuri Stozhkov, Christian Tauber, Yee Jun Tham, Miguel Vazquez-Pufleau, Annele Virtanen, Alexander L. Vogel, Rainer Volkamer, Robert Wagner, Mingyi Wang, Lena Weitz, Daniela Wimmer, Mao Xiao, Chao Yan, Penglin Ye, Qiaozhi Zha, Xueqin Zhou, Antonio Amorim, Urs Baltensperger, Armin Hansel, Markku Kulmala, António Tomé, Paul M. Winkler, Douglas R. Worsnop, Neil M. Donahue, Jasper Kirkby, and Joachim Curtius
Atmos. Chem. Phys., 20, 11809–11821, https://doi.org/10.5194/acp-20-11809-2020, https://doi.org/10.5194/acp-20-11809-2020, 2020
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With experiments performed at CLOUD, we show how isoprene interferes in monoterpene oxidation via RO2 termination at atmospherically relevant concentrations. This interference shifts the distribution of highly oxygenated organic molecules (HOMs) away from C20 class dimers towards C15 class dimers, which subsequently reduces both biogenic nucleation and early growth rates. Our results may help to understand the absence of new-particle formation in isoprene-rich environments.
Mario Simon, Lubna Dada, Martin Heinritzi, Wiebke Scholz, Dominik Stolzenburg, Lukas Fischer, Andrea C. Wagner, Andreas Kürten, Birte Rörup, Xu-Cheng He, João Almeida, Rima Baalbaki, Andrea Baccarini, Paulus S. Bauer, Lisa Beck, Anton Bergen, Federico Bianchi, Steffen Bräkling, Sophia Brilke, Lucia Caudillo, Dexian Chen, Biwu Chu, António Dias, Danielle C. Draper, Jonathan Duplissy, Imad El-Haddad, Henning Finkenzeller, Carla Frege, Loic Gonzalez-Carracedo, Hamish Gordon, Manuel Granzin, Jani Hakala, Victoria Hofbauer, Christopher R. Hoyle, Changhyuk Kim, Weimeng Kong, Houssni Lamkaddam, Chuan P. Lee, Katrianne Lehtipalo, Markus Leiminger, Huajun Mai, Hanna E. Manninen, Guillaume Marie, Ruby Marten, Bernhard Mentler, Ugo Molteni, Leonid Nichman, Wei Nie, Andrea Ojdanic, Antti Onnela, Eva Partoll, Tuukka Petäjä, Joschka Pfeifer, Maxim Philippov, Lauriane L. J. Quéléver, Ananth Ranjithkumar, Matti P. Rissanen, Simon Schallhart, Siegfried Schobesberger, Simone Schuchmann, Jiali Shen, Mikko Sipilä, Gerhard Steiner, Yuri Stozhkov, Christian Tauber, Yee J. Tham, António R. Tomé, Miguel Vazquez-Pufleau, Alexander L. Vogel, Robert Wagner, Mingyi Wang, Dongyu S. Wang, Yonghong Wang, Stefan K. Weber, Yusheng Wu, Mao Xiao, Chao Yan, Penglin Ye, Qing Ye, Marcel Zauner-Wieczorek, Xueqin Zhou, Urs Baltensperger, Josef Dommen, Richard C. Flagan, Armin Hansel, Markku Kulmala, Rainer Volkamer, Paul M. Winkler, Douglas R. Worsnop, Neil M. Donahue, Jasper Kirkby, and Joachim Curtius
Atmos. Chem. Phys., 20, 9183–9207, https://doi.org/10.5194/acp-20-9183-2020, https://doi.org/10.5194/acp-20-9183-2020, 2020
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Highly oxygenated organic compounds (HOMs) have been identified as key vapors involved in atmospheric new-particle formation (NPF). The molecular distribution, HOM yield, and NPF from α-pinene oxidation experiments were measured at the CLOUD chamber over a wide tropospheric-temperature range. This study shows on a molecular scale that despite the sharp reduction in HOM yield at lower temperatures, the reduced volatility counteracts this effect and leads to an overall increase in the NPF rate.
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.
Olga Garmash, Matti P. Rissanen, Iida Pullinen, Sebastian Schmitt, Oskari Kausiala, Ralf Tillmann, Defeng Zhao, Carl Percival, Thomas J. Bannan, Michael Priestley, Åsa M. Hallquist, Einhard Kleist, Astrid Kiendler-Scharr, Mattias Hallquist, Torsten Berndt, Gordon McFiggans, Jürgen Wildt, Thomas F. Mentel, and Mikael Ehn
Atmos. Chem. Phys., 20, 515–537, https://doi.org/10.5194/acp-20-515-2020, https://doi.org/10.5194/acp-20-515-2020, 2020
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Highly oxygenated organic molecules (HOMs) facilitate aerosol formation in the atmosphere. Using NO3− chemical ionization mass spectrometry we investigated HOM composition and yield in oxidation of aromatic compounds at different reactant concentrations, in the presence of NOx and seed aerosol. Higher OH concentrations increased HOM yield, suggesting multiple oxidation steps, and affected HOM composition, potentially explaining in part discrepancies in published secondary organic aerosol yields.
Matti P. Rissanen, Jyri Mikkilä, Siddharth Iyer, and Jani Hakala
Atmos. Meas. Tech., 12, 6635–6646, https://doi.org/10.5194/amt-12-6635-2019, https://doi.org/10.5194/amt-12-6635-2019, 2019
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A novel chemical ionization methodology for rapid gas–phase environmental monitoring is presented. The usefulness of the new inlet design is demonstrated by measuring various aerosol precursor compounds that are present at very low concentrations by using two consecutive ionization schemes. This new inlet enables the detection of a wide range of compounds of interest with a minimum of effort and at a fast repetition rate.
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.
Nina Sarnela, Tuija Jokinen, Jonathan Duplissy, Chao Yan, Tuomo Nieminen, Mikael Ehn, Siegfried Schobesberger, Martin Heinritzi, Sebastian Ehrhart, Katrianne Lehtipalo, Jasmin Tröstl, Mario Simon, Andreas Kürten, Markus Leiminger, Michael J. Lawler, Matti P. Rissanen, Federico Bianchi, Arnaud P. Praplan, Jani Hakala, Antonio Amorim, Marc Gonin, Armin Hansel, Jasper Kirkby, Josef Dommen, Joachim Curtius, James N. Smith, Tuukka Petäjä, Douglas R. Worsnop, Markku Kulmala, Neil M. Donahue, and Mikko Sipilä
Atmos. Chem. Phys., 18, 2363–2380, https://doi.org/10.5194/acp-18-2363-2018, https://doi.org/10.5194/acp-18-2363-2018, 2018
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Atmospheric trace gases can form small molecular clusters, which can grow to larger sizes through the condensation of vapours. This process is called new particle formation. In this paper we studied the formation of sulfuric acid and highly oxygenated molecules, the key compounds in atmospheric new particle formation, in chamber experiments and introduced a way to simulate these ozonolysis products of α-pinene in a simple manner.
Andreas Kürten, Chenxi Li, Federico Bianchi, Joachim Curtius, António Dias, Neil M. Donahue, Jonathan Duplissy, Richard C. Flagan, Jani Hakala, Tuija Jokinen, Jasper Kirkby, Markku Kulmala, Ari Laaksonen, Katrianne Lehtipalo, Vladimir Makhmutov, Antti Onnela, Matti P. Rissanen, Mario Simon, Mikko Sipilä, Yuri Stozhkov, Jasmin Tröstl, Penglin Ye, and Peter H. McMurry
Atmos. Chem. Phys., 18, 845–863, https://doi.org/10.5194/acp-18-845-2018, https://doi.org/10.5194/acp-18-845-2018, 2018
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A recent laboratory study (CLOUD) showed that new particles nucleate efficiently from sulfuric acid and dimethylamine (DMA). The reanalysis of previously published data reveals that the nucleation rates are even faster than previously assumed, i.e., nucleation can proceed at rates that are compatible with collision-controlled new particle formation for atmospheric conditions. This indicates that sulfuric acid–DMA nucleation is likely an important source of particles in the boundary layer.
Carla Frege, Ismael K. Ortega, Matti P. Rissanen, Arnaud P. Praplan, Gerhard Steiner, Martin Heinritzi, Lauri Ahonen, António Amorim, Anne-Kathrin Bernhammer, Federico Bianchi, Sophia Brilke, Martin Breitenlechner, Lubna Dada, António Dias, Jonathan Duplissy, Sebastian Ehrhart, Imad El-Haddad, Lukas Fischer, Claudia Fuchs, Olga Garmash, Marc Gonin, Armin Hansel, Christopher R. Hoyle, Tuija Jokinen, Heikki Junninen, Jasper Kirkby, Andreas Kürten, Katrianne Lehtipalo, Markus Leiminger, Roy Lee Mauldin, Ugo Molteni, Leonid Nichman, Tuukka Petäjä, Nina Sarnela, Siegfried Schobesberger, Mario Simon, Mikko Sipilä, Dominik Stolzenburg, António Tomé, Alexander L. Vogel, Andrea C. Wagner, Robert Wagner, Mao Xiao, Chao Yan, Penglin Ye, Joachim Curtius, Neil M. Donahue, Richard C. Flagan, Markku Kulmala, Douglas R. Worsnop, Paul M. Winkler, Josef Dommen, and Urs Baltensperger
Atmos. Chem. Phys., 18, 65–79, https://doi.org/10.5194/acp-18-65-2018, https://doi.org/10.5194/acp-18-65-2018, 2018
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It was recently shown that biogenic highly oxygenated molecules (HOMs) form particles in the absence of sulfuric acid and ions enhance the nucleation rate. Here we compare the molecular composition of positive and negative HOM clusters at 25, 5 and −25 °C. At lower temperatures the HOM average oxygen-to-carbon ratio decreases indicating a reduction in the rate of autoxidation due to rather high activation energy. The experimental findings are supported by quantum chemical calculations.
Xuemeng Chen, Lauriane L. J. Quéléver, Pak L. Fung, Jutta Kesti, Matti P. Rissanen, Jaana Bäck, Petri Keronen, Heikki Junninen, Tuukka Petäjä, Veli-Matti Kerminen, and Markku Kulmala
Atmos. Chem. Phys., 18, 49–63, https://doi.org/10.5194/acp-18-49-2018, https://doi.org/10.5194/acp-18-49-2018, 2018
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We analysed a 20-year-long dataset collected in a Finnish boreal forest at SMEAR II station to investigate the frequency and strength of ozone depletion events. We could identify a number of ozone depletion events that lasted for more than 3 h, mainly in the autumn and winter months. Their occurrence was likely related to the formation of a low mixing layer under the conditions of low temperatures, low wind speeds, high relative humidities and limited intensity of solar radiation.
Robert Wagner, Chao Yan, Katrianne Lehtipalo, Jonathan Duplissy, Tuomo Nieminen, Juha Kangasluoma, Lauri R. Ahonen, Lubna Dada, Jenni Kontkanen, Hanna E. Manninen, Antonio Dias, Antonio Amorim, Paulus S. Bauer, Anton Bergen, Anne-Kathrin Bernhammer, Federico Bianchi, Sophia Brilke, Stephany Buenrostro Mazon, Xuemeng Chen, Danielle C. Draper, Lukas Fischer, Carla Frege, Claudia Fuchs, Olga Garmash, Hamish Gordon, Jani Hakala, Liine Heikkinen, Martin Heinritzi, Victoria Hofbauer, Christopher R. Hoyle, Jasper Kirkby, Andreas Kürten, Alexander N. Kvashnin, Tiia Laurila, Michael J. Lawler, Huajun Mai, Vladimir Makhmutov, Roy L. Mauldin III, Ugo Molteni, Leonid Nichman, Wei Nie, Andrea Ojdanic, Antti Onnela, Felix Piel, Lauriane L. J. Quéléver, Matti P. Rissanen, Nina Sarnela, Simon Schallhart, Kamalika Sengupta, Mario Simon, Dominik Stolzenburg, Yuri Stozhkov, Jasmin Tröstl, Yrjö Viisanen, Alexander L. Vogel, Andrea C. Wagner, Mao Xiao, Penglin Ye, Urs Baltensperger, Joachim Curtius, Neil M. Donahue, Richard C. Flagan, Martin Gallagher, Armin Hansel, James N. Smith, António Tomé, Paul M. Winkler, Douglas Worsnop, Mikael Ehn, Mikko Sipilä, Veli-Matti Kerminen, Tuukka Petäjä, and Markku Kulmala
Atmos. Chem. Phys., 17, 15181–15197, https://doi.org/10.5194/acp-17-15181-2017, https://doi.org/10.5194/acp-17-15181-2017, 2017
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.
Federico Bianchi, Olga Garmash, Xucheng He, Chao Yan, Siddharth Iyer, Ida Rosendahl, Zhengning Xu, Matti P. Rissanen, Matthieu Riva, Risto Taipale, Nina Sarnela, Tuukka Petäjä, Douglas R. Worsnop, Markku Kulmala, Mikael Ehn, and Heikki Junninen
Atmos. Chem. Phys., 17, 13819–13831, https://doi.org/10.5194/acp-17-13819-2017, https://doi.org/10.5194/acp-17-13819-2017, 2017
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Naturally charged highly oxidised molecules (HOMs) were characterized using advanced mass spectrometers. Two different classes of compounds, clustered with the nitrate and bisulfate ions, were identified: HOMs containing only carbon, hydrogen and oxygen and nitrogen-containing HOMs or organonitrates (ONs). They exhibit strong diurnal variations where HOMs peak during night and ONs during day. Finally, large clusters containing up to 40 carbon atoms (four oxidized
α-pinene units) were observed.
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.
Michael J. Lawler, Paul M. Winkler, Jaeseok Kim, Lars Ahlm, Jasmin Tröstl, Arnaud P. Praplan, Siegfried Schobesberger, Andreas Kürten, Jasper Kirkby, Federico Bianchi, Jonathan Duplissy, Armin Hansel, Tuija Jokinen, Helmi Keskinen, Katrianne Lehtipalo, Markus Leiminger, Tuukka Petäjä, Matti Rissanen, Linda Rondo, Mario Simon, Mikko Sipilä, Christina Williamson, Daniela Wimmer, Ilona Riipinen, Annele Virtanen, and James N. Smith
Atmos. Chem. Phys., 16, 13601–13618, https://doi.org/10.5194/acp-16-13601-2016, https://doi.org/10.5194/acp-16-13601-2016, 2016
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We present chemical observations of newly formed particles as small as ~ 10 nm from new particle formation experiments using sulfuric acid, dimethylamine, ammonia, and water vapor as gas phase reactants. The nanoparticles were more acidic than expected based on thermodynamic expectations, particularly at the smallest measured sizes. The results suggest rapid surface conversion of SO2 to sulfate and show a marked composition change between 10 and 15 nm, possibly indicating a phase change.
Chao Yan, Wei Nie, Mikko Äijälä, Matti P. Rissanen, Manjula R. Canagaratna, Paola Massoli, Heikki Junninen, Tuija Jokinen, Nina Sarnela, Silja A. K. Häme, Siegfried Schobesberger, Francesco Canonaco, Lei Yao, André S. H. Prévôt, Tuukka Petäjä, Markku Kulmala, Mikko Sipilä, Douglas R. Worsnop, and Mikael Ehn
Atmos. Chem. Phys., 16, 12715–12731, https://doi.org/10.5194/acp-16-12715-2016, https://doi.org/10.5194/acp-16-12715-2016, 2016
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Highly oxidized multifunctional compounds (HOMs) are known to have a significant contribution to secondary aerosol formation, yet their dominating formation pathways remain unclear in the atmosphere. We apply positive matrix factorization (PMF) on HOM data, and successfully retrieve factors representing different formation pathways. The results improve our understanding of HOM formation, and provide new perspectives on using PMF to study the variation of short-lived specie.
J. Kim, L. Ahlm, T. Yli-Juuti, M. Lawler, H. Keskinen, J. Tröstl, S. Schobesberger, J. Duplissy, A. Amorim, F. Bianchi, N. M. Donahue, R. C. Flagan, J. Hakala, M. Heinritzi, T. Jokinen, A. Kürten, A. Laaksonen, K. Lehtipalo, P. Miettinen, T. Petäjä, M. P. Rissanen, L. Rondo, K. Sengupta, M. Simon, A. Tomé, C. Williamson, D. Wimmer, P. M. Winkler, S. Ehrhart, P. Ye, J. Kirkby, J. Curtius, U. Baltensperger, M. Kulmala, K. E. J. Lehtinen, J. N. Smith, I. Riipinen, and A. Virtanen
Atmos. Chem. Phys., 16, 293–304, https://doi.org/10.5194/acp-16-293-2016, https://doi.org/10.5194/acp-16-293-2016, 2016
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The hygroscopicity of nucleated nanoparticles was measured in the presence of sulfuric acid, sulfuric acid-dimethylamine, and sulfuric acid-organics derived from α-pinene oxidation during CLOUD7 at CERN in 2012. The hygroscopicity parameter κ decreased with increasing particle size, indicating decreasing acidity of particles.
R. L. Mauldin III, M. P. Rissanen, T. Petäjä, and M. Kulmala
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2015-398, https://doi.org/10.5194/amt-2015-398, 2016
Revised manuscript not accepted
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The manuscript describes a novel instrument for the measurement of OH, HO2+RO2, and other atmospheric species. The instrument described combines the chemical ionization techniques of nitrate CIMS, OH conversion to H2SO4, HO2+RO2 conversion to H2SO4, and high resolution time of flight mass spectroscopy into one system. By using one instrument to obtain spectra it is possible to compare spectra from the different modes and gain further chemical information towards peak identification.
M. Sipilä, N. Sarnela, T. Jokinen, H. Junninen, J. Hakala, M. P. Rissanen, A. Praplan, M. Simon, A. Kürten, F. Bianchi, J. Dommen, J. Curtius, T. Petäjä, and D. R. Worsnop
Atmos. Meas. Tech., 8, 4001–4011, https://doi.org/10.5194/amt-8-4001-2015, https://doi.org/10.5194/amt-8-4001-2015, 2015
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Atmospheric concentrations of amines are poorly known mainly due to challenges related to their reliable high-sensitivity detection. We have created a method and instrument that is capable for detecting amines with lowest limit of detection of around 0.01 parts per trillion. Application of the instrument in the field study indicates that concentrations of dimethyl amine in a boreal forest site are below 0.03ppt, not enough to account for the observed new particle formation rates.
T. F. Mentel, M. Springer, M. Ehn, E. Kleist, I. Pullinen, T. Kurtén, M. Rissanen, A. Wahner, and J. Wildt
Atmos. Chem. Phys., 15, 6745–6765, https://doi.org/10.5194/acp-15-6745-2015, https://doi.org/10.5194/acp-15-6745-2015, 2015
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We studied a series of cycloalkenes and methyl-substituted alkenes in order to elucidate the structural pre-requisites and chemical pathways to the recently discovered class of highly oxidized molecules ELVOC (Ehn et al., Nature, 2014). ELVOC may totally change the view on (parts of) the mechanism of SOA formation. We present results which support recent observations of H shifts from C-H to peroxy radicals, highlighting the pivotal role of peroxyradicals in organic atmospheric chemistry.
A. P. Praplan, S. Schobesberger, F. Bianchi, M. P. Rissanen, M. Ehn, T. Jokinen, H. Junninen, A. Adamov, A. Amorim, J. Dommen, J. Duplissy, J. Hakala, A. Hansel, M. Heinritzi, J. Kangasluoma, J. Kirkby, M. Krapf, A. Kürten, K. Lehtipalo, F. Riccobono, L. Rondo, N. Sarnela, M. Simon, A. Tomé, J. Tröstl, P. M. Winkler, C. Williamson, P. Ye, J. Curtius, U. Baltensperger, N. M. Donahue, M. Kulmala, and D. R. Worsnop
Atmos. Chem. Phys., 15, 4145–4159, https://doi.org/10.5194/acp-15-4145-2015, https://doi.org/10.5194/acp-15-4145-2015, 2015
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Our study shows, based on data from three atmospheric pressure interface time-of-flight mass spectrometers measuring in parallel charged and neutral molecules and molecular clusters, how oxidised organic compounds bind to inorganic ions (e.g. bisulfate, nitrate, ammonium). This ionisation is selective for compounds with lower molar mass due to their limited amount and variety of functional groups. We also found that extremely low volatile organic compounds (ELVOCs) can be formed immediately.
M. Sipilä, T. Jokinen, T. Berndt, S. Richters, R. Makkonen, N. M. Donahue, R. L. Mauldin III, T. Kurtén, P. Paasonen, N. Sarnela, M. Ehn, H. Junninen, M. P. Rissanen, J. Thornton, F. Stratmann, H. Herrmann, D. R. Worsnop, M. Kulmala, V.-M. Kerminen, and T. Petäjä
Atmos. Chem. Phys., 14, 12143–12153, https://doi.org/10.5194/acp-14-12143-2014, https://doi.org/10.5194/acp-14-12143-2014, 2014
J. Kangasluoma, C. Kuang, D. Wimmer, M. P. Rissanen, K. Lehtipalo, M. Ehn, D. R. Worsnop, J. Wang, M. Kulmala, and T. Petäjä
Atmos. Meas. Tech., 7, 689–700, https://doi.org/10.5194/amt-7-689-2014, https://doi.org/10.5194/amt-7-689-2014, 2014
Related subject area
Subject: Gases | Research Activity: Machine Learning | Altitude Range: Troposphere | Science Focus: Chemistry (chemical composition and reactions)
High-resolution greenhouse gas flux inversions using a machine learning surrogate model for atmospheric transport
Implications of VOC Oxidation in Atmospheric Chemistry: Development of a Comprehensive AI Model for Predicting Reaction Rate Constants
Multi-Machine Learning Approaches to Modeling Small-Scale Source Attribution of Ozone Formation
Identifying Drivers of Surface Ozone Bias in Global Chemical Reanalysis with Explainable Machine Learning
Diagnosing ozone–NOx–VOC–aerosol sensitivity and uncovering causes of urban–nonurban discrepancies in Shandong, China, using transformer-based estimations
A machine learning approach to downscale EMEP4UK: analysis of UK ozone variability and trends
Automated detection and monitoring of methane super-emitters using satellite data
Spatiotemporal modeling of air pollutant concentrations in Germany using machine learning
Estimating nitrogen and sulfur deposition across China during 2005 to 2020 based on multiple statistical models
Technical note: Improving the European air quality forecast of the Copernicus Atmosphere Monitoring Service using machine learning techniques
Nikhil Dadheech, Tai-Long He, and Alexander J. Turner
Atmos. Chem. Phys., 25, 5159–5174, https://doi.org/10.5194/acp-25-5159-2025, https://doi.org/10.5194/acp-25-5159-2025, 2025
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We developed an efficient GHG (greenhouse gas) flux inversion framework using a machine-learning emulator (FootNet) as a surrogate for an atmospheric transport model, resulting in a 650 × speedup. Paradoxically, the flux inversion using the ML (machine-learning) model outperforms the full-physics model in our case study. We attribute this to the ML model mitigating transport errors in the GHG flux inversion.
Xin Zhang, Jiaqi Luo, Wenxiao Pan, Qiao Xue, Xian Liu, Jianjie Fu, Aiqian Zhang, and Guibin Jiang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1241, https://doi.org/10.5194/egusphere-2025-1241, 2025
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VOCs drive atmospheric chemistry via oxidation, forming PM2.5/ozone precursors. This study introduces Vreact, a graph-based AI model predicting reaction rate constands (ki) for multiple oxidants simultaneously. It achieves high accuracy (MSE=0.281and R²=0.941 for log10ki ), overcoming single-oxidant model limits. A web tool enables rapid rate screening. Vreact advances pollutant formation insights and supports emission control strategies, aiding global air quality and public health efforts.
Zheng Xiao, Yifeng Lu, and Guangli Xiu
EGUsphere, https://doi.org/10.5194/egusphere-2025-160, https://doi.org/10.5194/egusphere-2025-160, 2025
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This study innovates air pollution tracking in industrial areas by merging AI with traditional methods. Analyzing three years of data from a Shanghai chemical park, we identified ozone pollution sources and seasonal variations, revealing that chemical solvents and fuel vapors are key contributors. Our method enables faster, accurate source identification, aiding better air quality decisions in rapidly developing regions.
Kazuyuki Miyazaki, Yuliya Marchetti, James Montgomery, Steven Lu, and Kevin Bowman
EGUsphere, https://doi.org/10.5194/egusphere-2024-3753, https://doi.org/10.5194/egusphere-2024-3753, 2025
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This study employs explainable machine learning to analyze the causes of significant biases in surface ozone estimates from chemical reanalysis. By analyzing global observations and chemical reanalysis outputs, key bias drivers such as meteorological conditions and precursor emissions were identified. This provides actionable insights to improve chemical transport models, observation systems, and emissions inventories, ultimately enhancing ozone reanalysis for better air pollution management.
Chenliang Tao, Yanbo Peng, Qingzhu Zhang, Yuqiang Zhang, Bing Gong, Qiao Wang, and Wenxing Wang
Atmos. Chem. Phys., 24, 4177–4192, https://doi.org/10.5194/acp-24-4177-2024, https://doi.org/10.5194/acp-24-4177-2024, 2024
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We developed a novel transformer framework to bridge the sparse surface monitoring for inferring ozone–NOx–VOC–aerosol sensitivity and their urban–nonurban discrepancies at a finer scale with implications for improving our understanding of ozone variations. The change in urban–rural disparities in ozone was dominated by PM2.5 from 2019 to 2020. An aerosol-inhibited regime on top of the two traditional NOx- and VOC-limited regimes was identified in Jiaodong Peninsula, Shandong, China.
Lily Gouldsbrough, Ryan Hossaini, Emma Eastoe, Paul J. Young, and Massimo Vieno
Atmos. Chem. Phys., 24, 3163–3196, https://doi.org/10.5194/acp-24-3163-2024, https://doi.org/10.5194/acp-24-3163-2024, 2024
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High-resolution spatial fields of surface ozone are used to understand spikes in ozone concentration and predict their impact on public health. Such fields are routinely output from complex mathematical models for atmospheric conditions. These outputs are on a coarse spatial resolution and the highest concentrations tend to be biased. Using a novel data-driven machine learning methodology, we show how such output can be corrected to produce fields with both lower bias and higher resolution.
Berend J. Schuit, Joannes D. Maasakkers, Pieter Bijl, Gourav Mahapatra, Anne-Wil van den Berg, Sudhanshu Pandey, Alba Lorente, Tobias Borsdorff, Sander Houweling, Daniel J. Varon, Jason McKeever, Dylan Jervis, Marianne Girard, Itziar Irakulis-Loitxate, Javier Gorroño, Luis Guanter, Daniel H. Cusworth, and Ilse Aben
Atmos. Chem. Phys., 23, 9071–9098, https://doi.org/10.5194/acp-23-9071-2023, https://doi.org/10.5194/acp-23-9071-2023, 2023
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Using two machine learning models, which were trained on TROPOMI methane satellite data, we detect 2974 methane plumes, so-called super-emitters, in 2021. We detect methane emissions globally related to urban areas or landfills, coal mining, and oil and gas production. Using our monitoring system, we identify 94 regions with frequent emissions. For 12 locations, we target high-resolution satellite instruments to enlarge and identify the exact infrastructure responsible for the emissions.
Vigneshkumar Balamurugan, Jia Chen, Adrian Wenzel, and Frank N. Keutsch
Atmos. Chem. Phys., 23, 10267–10285, https://doi.org/10.5194/acp-23-10267-2023, https://doi.org/10.5194/acp-23-10267-2023, 2023
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In this study, machine learning models are employed to model NO2 and O3 concentrations. We employed a wide range of sources of data, including meteorological and column satellite measurements, to model NO2 and O3 concentrations. The spatial and temporal variability, and their drivers, were investigated. Notably, the machine learning model established the relationship between NOx and O3. Despite the fact that metropolitan regions are NO2 hotspots, rural areas have high O3 concentrations.
Kaiyue Zhou, Wen Xu, Lin Zhang, Mingrui Ma, Xuejun Liu, and Yu Zhao
Atmos. Chem. Phys., 23, 8531–8551, https://doi.org/10.5194/acp-23-8531-2023, https://doi.org/10.5194/acp-23-8531-2023, 2023
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We developed a dataset of the long-term (2005–2020) variabilities of China’s nitrogen and sulfur deposition, with multiple statistical models that combine available observations and chemistry transport modeling. We demonstrated the strong impact of human activities and national pollution control actions on the spatiotemporal changes in deposition and indicated a relatively small benefit of emission abatement on deposition (and thereby ecological risk) for China compared to Europe and the USA.
Jean-Maxime Bertrand, Frédérik Meleux, Anthony Ung, Gaël Descombes, and Augustin Colette
Atmos. Chem. Phys., 23, 5317–5333, https://doi.org/10.5194/acp-23-5317-2023, https://doi.org/10.5194/acp-23-5317-2023, 2023
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Post-processing methods based on machine learning algorithms were applied to refine the forecasts of four key pollutants at monitoring sites across Europe. Performances show significant improvements compared to those of the deterministic model raw outputs. Taking advantage of the large modelling domain extension, an innovative
globalapproach is proposed to drastically reduce the period necessary to train the models and thus facilitate the implementation in an operational context.
Cited articles
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Besel, V., Todorović, M., Kurtén, T., Vehkamäki, H., and Rinke, P.: The search for sparse data in molecular datasets: Application of active learning to identify extremely low volatile organic compounds, J. Aerosol Sci., 179, 106375, https://doi.org/10.1016/j.jaerosci.2024.106375, 2024. a
Bortolussi, F., Partovi, F., Joona, M., and Matti, R.: Organic pesticide database with 716 molecules analyzed with chemical ionization mass spectrometry. Reagent ions: bromide, protonated acetone, hydronium ion, dioxide, Zenodo [data set], https://doi.org/10.5281/zenodo.11208543, 2024a. a
Bortolussi, F., Sandström, H., and Rinke, P.: PesticidesMS, Gitlab [code], https://gitlab.com/cest-group/pesticidesms (last access: 15 January 2025), 2024b. a
Breitenlechner, M., Fischer, L., Hainer, M., Heinritzi, M., Curtius, J., and Hansel, A.: PTR3: An Instrument for Studying the Lifecycle of Reactive Organic Carbon in the Atmosphere, Anal. Chem., 89, 5824–5831, https://doi.org/10.1021/acs.analchem.6b05110, 2017. a
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Dührkop, K., Shen, H., Meusel, M., Rousu, J., and Böcker, S.: Searching molecular structure databases with tandem mass spectra using CSI:FingerID, P. Natl. Acad. Sci. USA, 112, 12580–12585, https://doi.org/10.1073/pnas.1509788112, 2015. a, b
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Short summary
Chemical ionization mass spectrometry (CIMS) is widely used in atmospheric chemistry studies. We still have a limited understanding of the complex functioning of the instrument; therefore, we applied machine learning to provide insights from CIMS analyses. We were able to predict both detection and signal intensity with a fair error, and we found out the most important structural fragments for negative ionization schemes (NH and OH) and positive ones (nitrogen-containing groups).
Chemical ionization mass spectrometry (CIMS) is widely used in atmospheric chemistry studies. We...
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