Articles | Volume 18, issue 20
https://doi.org/10.5194/gmd-18-7357-2025
© 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/gmd-18-7357-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
15 Oct 2025
Model description paper |
| 15 Oct 2025
| 15 Oct 2025
Improved vapor pressure predictions using group contribution-assisted graph convolutional neural networks (GC2NN)
Matteo Krüger
Multiphase Chemistry Department, Max Planck Institute for Chemistry, Hahn-Meitner-Weg 1, 55128 Mainz, Germany
Tommaso Galeazzo
Department of Chemistry, University of California Irvine, Irvine, California, USA
Ivan Eremets
Multiphase Chemistry Department, Max Planck Institute for Chemistry, Hahn-Meitner-Weg 1, 55128 Mainz, Germany
Bertil Schmidt
Department of Computer Science, Johannes Gutenberg University Mainz, Staudingerweg 9, 55128 Mainz, Germany
Ulrich Pöschl
Multiphase Chemistry Department, Max Planck Institute for Chemistry, Hahn-Meitner-Weg 1, 55128 Mainz, Germany
Department of Chemistry, University of California Irvine, Irvine, California, USA
Multiphase Chemistry Department, Max Planck Institute for Chemistry, Hahn-Meitner-Weg 1, 55128 Mainz, Germany
Related authors
Thomas Berkemeier, Matteo Krüger, Aryeh Feinberg, Marcel Müller, Ulrich Pöschl, and Ulrich K. Krieger
Geosci. Model Dev., 16, 2037–2054, https://doi.org/10.5194/gmd-16-2037-2023, https://doi.org/10.5194/gmd-16-2037-2023, 2023
Short summary
Short summary
Kinetic multi-layer models (KMs) successfully describe heterogeneous and multiphase atmospheric chemistry. In applications requiring repeated execution, however, these models can be too expensive. We trained machine learning surrogate models on output of the model KM-SUB and achieved high correlations. The surrogate models run orders of magnitude faster, which suggests potential applicability in global optimization tasks and as sub-modules in large-scale atmospheric models.
Bruno B. Meller, Marco A. Franco, Rafael Valiati, Christopher Pöhlker, Luiz A. T. Machado, Florian Ditas, Leslie A. Kremper, Subha S. Raj, Cleo Q. Dias-Júnior, Flávio A. F. D'Oliveira, Luciana V. Rizzo, Ulrich Pöschl, and Paulo Artaxo
EGUsphere, https://doi.org/10.5194/egusphere-2025-4581, https://doi.org/10.5194/egusphere-2025-4581, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Aerosols are tiny particles that help clouds form and influence the climate. In the Amazon, clear events of new particle formation are rare, making it difficult to explain the origin of these particles. Using ten years of measurements, we discovered a subtle but frequent process called Quiet New Particle Formation. This hidden mechanism slowly produces and grows small particles and is responsible for nearly half of the smallest aerosols observed during the wet season.
Laura M. D. Heinlein, Junwei He, Michael Oluwatoyin Sunday, Fangzhou Guo, James Campbell, Allison Moon, Sukriti Kapur, Ting Fang, Kasey Edwards, Meeta Cesler-Maloney, Alyssa J. Burns, Jack Dibb, William Simpson, Manabu Shiraiwa, Becky Alexander, Jingqiu Mao, James H. Flynn III, Jochen Stutz, and Cort Anastasio
Atmos. Chem. Phys., 25, 9561–9581, https://doi.org/10.5194/acp-25-9561-2025, https://doi.org/10.5194/acp-25-9561-2025, 2025
Short summary
Short summary
High-latitude cities like Fairbanks, Alaska, experience severe wintertime pollution episodes. While conventional wisdom holds that oxidation is slow under these conditions, field measurements find oxidized products in particles. To explore this, we measured oxidants in aqueous extracts of winter particles from Fairbanks. We find high concentrations of oxidants during illumination experiments, indicating that particle photochemistry can be significant even in high latitudes during winter.
Sara L. Farrell, Quazi Z. Rasool, Havala O. T. Pye, Yue Zhang, Ying Li, Yuzhi Chen, Chi-Tsan Wang, Haofei Zhang, Ryan Schmedding, Manabu Shiraiwa, Jaime Greene, Sri H. Budisulistiorini, Jose L. Jimenez, Weiwei Hu, Jason D. Surratt, and William Vizuete
EGUsphere, https://doi.org/10.5194/egusphere-2025-2253, https://doi.org/10.5194/egusphere-2025-2253, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Fine particulate matter (PM2.5) has become increasingly important to regulate and model. In this study, we parameterize non-ideal aerosol mixing and phase state into the Community Multiscale Air Quality (CMAQ) model and analyze its impact on the formation of a globally important source of PM2.5, isoprene epoxydiol (IEPOX)-derived PM2.5. Incorporating these features furthers model bias in IEPOX-derived PM2.5, however, this work provides potential phase state bounds for future PM2.5 modeling work.
Christopher N. Rapp, Sining Niu, N. Cazimir Armstrong, Xiaoli Shen, Thomas Berkemeier, Jason D. Surratt, Yue Zhang, and Daniel J. Cziczo
Atmos. Chem. Phys., 25, 5519–5536, https://doi.org/10.5194/acp-25-5519-2025, https://doi.org/10.5194/acp-25-5519-2025, 2025
Short summary
Short summary
Atmospheric ice formation is initiated by particulate matter suspended in air and has profound impacts on Earth's climate. This study focuses on examining the effectiveness of ice formation by a subset of particles composed of organic matter and sulfate. We used experiments and computer modeling to obtain the result that these particles are not effective ice-nucleating particles, suggesting that molecular structure is important for ice formation on these types of particles.
Michael Oluwatoyin Sunday, Laura Marie Dahler Heinlein, Junwei He, Allison Moon, Sukriti Kapur, Ting Fang, Kasey C. Edwards, Fangzhou Guo, Jack Dibb, James H. Flynn III, Becky Alexander, Manabu Shiraiwa, and Cort Anastasio
Atmos. Chem. Phys., 25, 5087–5100, https://doi.org/10.5194/acp-25-5087-2025, https://doi.org/10.5194/acp-25-5087-2025, 2025
Short summary
Short summary
Hydrogen peroxide (HOOH) is an important oxidant that forms atmospheric sulfate. We demonstrate that the illumination of brown carbon can rapidly form HOOH within particles, even under the low-sunlight conditions of Fairbanks, Alaska, during winter. This in-particle formation of HOOH is fast enough that it forms sulfate at significant rates. In contrast, the formation of HOOH in the gas phase during the campaign is expected to be negligible because of high NOx levels.
Rafael Valiati, Bruno Backes Meller, Marco Aurélio Franco, Luciana Varanda Rizzo, Luiz Augusto Toledo Machado, Sebastian Brill, Bruna A. Holanda, Leslie A. Kremper, Subha S. Raj, Samara Carbone, Cléo Quaresma Dias-Júnior, Fernando Gonçalves Morais, Meinrat O. Andreae, Ulrich Pöschl, Christopher Pöhlker, and Paulo Artaxo
EGUsphere, https://doi.org/10.5194/egusphere-2025-1078, https://doi.org/10.5194/egusphere-2025-1078, 2025
Short summary
Short summary
This study highlights the different aerosol populations that are commonly observed in the central Amazon. Vertical gradients of aerosol optical and chemical properties were evaluated on different atmospheric conditions, and showed distinct characteristics of these particles. Intercontinental transport events bring to the region particles with a contrasting chemical composition, while vertical transport processes influence the aerosol properties by promoting the development of coating and aging.
Sebastian Brill, Björn Nillius, Jan-David Förster, Paulo Artaxo, Florian Ditas, Dennis Geis, Christian Gurk, Thomas Kenntner, Thomas Klimach, Mark Lamneck, Rafael Valiati, Bettina Weber, Stefan Wolff, Ulrich Pöschl, and Christopher Pöhlker
EGUsphere, https://doi.org/10.5194/egusphere-2025-295, https://doi.org/10.5194/egusphere-2025-295, 2025
Short summary
Short summary
Highly resolved vertical profiles are crucial for understanding ecosystem-atmosphere interactions. We developed the robotic lift (RoLi) as a platform for vertical profile measurements at the Amazon Tall Tower Observatory in the central Amazon basin. Initial results reveal distinct spatiotemporal patterns in altitude profiles of temperature, humidity, fog, and aerosol properties, offering new insights into the diurnal dynamics of convective daytime mixing and stable nighttime stratification.
Jianqiang Zhu, Guo Li, Uwe Kuhn, Bruno Backes Meller, Christopher Pöhlker, Paulo Artaxo, Ulrich Pöschl, Yafang Cheng, and Hang Su
EGUsphere, https://doi.org/10.5194/egusphere-2024-3911, https://doi.org/10.5194/egusphere-2024-3911, 2025
Short summary
Short summary
The manuscript reports unique measurement data on sub-40 nm particles and ions, especially those smaller than 10 nm in the Amazon from December 2022 to January 2023. A large number of sub-3 nm particles and naturally charged ions were present in the Amazonia boundary layer, and they showed a clear diurnal variation. The research will contribute to a better understanding of atmospheric processes in the pristine environment.
Barbara Ervens, Ken S. Carslaw, Thomas Koop, and Ulrich Pöschl
EGUsphere, https://doi.org/10.5194/egusphere-2025-419, https://doi.org/10.5194/egusphere-2025-419, 2025
Short summary
Short summary
Over the past two decades, the European Geosciences Union (EGU) has demonstrated the success, viability and benefits of interactive open access (OA) publishing with public peer review in its journals, its publishing platform EGUsphere and virtual compilations. The article summarizes the evolution of the EGU/Copernicus publications and of OA publishing with interactive public peer review at large by placing the EGU/Copernicus publications in the context of current and future global open science.
Denis Leppla, Stefanie Hildmann, Nora Zannoni, Leslie Kremper, Bruna Hollanda, Jonathan Williams, Christopher Pöhlker, Stefan Wolff, Marta Sà, Maria Cristina Solci, Ulrich Pöschl, and Thorsten Hoffmann
EGUsphere, https://doi.org/10.5194/egusphere-2025-141, https://doi.org/10.5194/egusphere-2025-141, 2025
Short summary
Short summary
The chemical composition of organic particles in the Amazon rainforest was investigated to understand how biogenic and human emissions influence the atmosphere in this unique ecosystem. Seasonal patterns were found where wet seasons were dominated by biogenic compounds from natural sources while dry seasons showed increased fire-related pollutants. These findings reveal how emissions, fires and long-range transport affect atmospheric chemistry, with implications for climate models.
Mega Octaviani, Benjamin A. Musa Bandowe, Qing Mu, Jake Wilson, Holger Tost, Hang Su, Yafang Cheng, Manabu Shiraiwa, Ulrich Pöschl, Thomas Berkemeier, and Gerhard Lammel
EGUsphere, https://doi.org/10.5194/egusphere-2025-186, https://doi.org/10.5194/egusphere-2025-186, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
This research explores the atmospheric concentration of benzo(a)pyrene (BaP), a harmful air pollutant linked to lung cancer. Using advanced Earth system modeling, the study examines how BaP's degradation varies with temperature and humidity, affecting its global distribution and associated lung cancer risks. The findings reveal that BaP persists longer in colder, less humid regions, leading to higher lung cancer risks in parts of Europe and Asia.
Florian Wieland, Nadine Bothen, Ralph Schwidetzky, Teresa M. Seifried, Paul Bieber, Ulrich Pöschl, Konrad Meister, Mischa Bonn, Janine Fröhlich-Nowoisky, and Hinrich Grothe
Biogeosciences, 22, 103–115, https://doi.org/10.5194/bg-22-103-2025, https://doi.org/10.5194/bg-22-103-2025, 2025
Short summary
Short summary
Betula pendula is a widespread birch tree species containing ice nucleation agents that can trigger the freezing of cloud droplets and thereby alter the evolution of clouds. Our study identifies three distinct ice-nucleating macromolecule (INM) aggregates of varying size that can nucleate ice at temperatures up to –5.4°C. Our findings suggest that these vegetation-derived particles may influence atmospheric processes, weather, and climate more strongly than previously thought.
Luiz A. T. Machado, Jürgen Kesselmeier, Santiago Botía, Hella van Asperen, Meinrat O. Andreae, Alessandro C. de Araújo, Paulo Artaxo, Achim Edtbauer, Rosaria R. Ferreira, Marco A. Franco, Hartwig Harder, Sam P. Jones, Cléo Q. Dias-Júnior, Guido G. Haytzmann, Carlos A. Quesada, Shujiro Komiya, Jost Lavric, Jos Lelieveld, Ingeborg Levin, Anke Nölscher, Eva Pfannerstill, Mira L. Pöhlker, Ulrich Pöschl, Akima Ringsdorf, Luciana Rizzo, Ana M. Yáñez-Serrano, Susan Trumbore, Wanda I. D. Valenti, Jordi Vila-Guerau de Arellano, David Walter, Jonathan Williams, Stefan Wolff, and Christopher Pöhlker
Atmos. Chem. Phys., 24, 8893–8910, https://doi.org/10.5194/acp-24-8893-2024, https://doi.org/10.5194/acp-24-8893-2024, 2024
Short summary
Short summary
Composite analysis of gas concentration before and after rainfall, during the day and night, gives insight into the complex relationship between trace gas variability and precipitation. The analysis helps us to understand the sources and sinks of trace gases within a forest ecosystem. It elucidates processes that are not discernible under undisturbed conditions and contributes to a deeper understanding of the trace gas life cycle and its intricate interactions with cloud dynamics in the Amazon.
Marco A. Franco, Rafael Valiati, Bruna A. Holanda, Bruno B. Meller, Leslie A. Kremper, Luciana V. Rizzo, Samara Carbone, Fernando G. Morais, Janaína P. Nascimento, Meinrat O. Andreae, Micael A. Cecchini, Luiz A. T. Machado, Milena Ponczek, Ulrich Pöschl, David Walter, Christopher Pöhlker, and Paulo Artaxo
Atmos. Chem. Phys., 24, 8751–8770, https://doi.org/10.5194/acp-24-8751-2024, https://doi.org/10.5194/acp-24-8751-2024, 2024
Short summary
Short summary
The Amazon wet-season atmosphere was studied at the Amazon Tall Tower Observatory site, revealing vertical variations (between 60 and 325 m) in natural aerosols. Daytime mixing contrasted with nighttime stratification, with distinct rain-induced changes in aerosol populations. Notably, optical property recovery at higher levels was faster, while near-canopy aerosols showed higher scattering efficiency. These findings enhance our understanding of aerosol impacts on climate dynamics.
Tommaso Galeazzo, Bernard Aumont, Marie Camredon, Richard Valorso, Yong B. Lim, Paul J. Ziemann, and Manabu Shiraiwa
Atmos. Chem. Phys., 24, 5549–5565, https://doi.org/10.5194/acp-24-5549-2024, https://doi.org/10.5194/acp-24-5549-2024, 2024
Short summary
Short summary
Secondary organic aerosol (SOA) derived from n-alkanes is a major component of anthropogenic particulate matter. We provide an analysis of n-alkane SOA by chemistry modeling, machine learning, and laboratory experiments, showing that n-alkane SOA adopts low-viscous semi-solid or liquid states. Our results indicate few kinetic limitations of mass accommodation in SOA formation, supporting the application of equilibrium partitioning for simulating n-alkane SOA in large-scale atmospheric models.
Zhiqiang Zhang, Ying Li, Haiyan Ran, Junling An, Yu Qu, Wei Zhou, Weiqi Xu, Weiwei Hu, Hongbin Xie, Zifa Wang, Yele Sun, and Manabu Shiraiwa
Atmos. Chem. Phys., 24, 4809–4826, https://doi.org/10.5194/acp-24-4809-2024, https://doi.org/10.5194/acp-24-4809-2024, 2024
Short summary
Short summary
Secondary organic aerosols (SOAs) can exist in liquid, semi-solid, or amorphous solid states, which are rarely accounted for in current chemical transport models. We predict the phase state of SOA particles over China and find that in northwestern China SOA particles are mostly highly viscous or glassy solid. Our results indicate that the particle phase state should be considered in SOA formation in chemical transport models for more accurate prediction of SOA mass concentrations.
Gabriela R. Unfer, Luiz A. T. Machado, Paulo Artaxo, Marco A. Franco, Leslie A. Kremper, Mira L. Pöhlker, Ulrich Pöschl, and Christopher Pöhlker
Atmos. Chem. Phys., 24, 3869–3882, https://doi.org/10.5194/acp-24-3869-2024, https://doi.org/10.5194/acp-24-3869-2024, 2024
Short summary
Short summary
Amazonian aerosols and their interactions with precipitation were studied by understanding them in a 3D space based on three parameters that characterize the concentration and size distribution of aerosols. The results showed characteristic arrangements regarding seasonal and diurnal cycles, as well as when interacting with precipitation. The use of this 3D space appears to be a promising tool for aerosol population analysis and for model validation and parameterization.
Daniel A. Knopf, Markus Ammann, Thomas Berkemeier, Ulrich Pöschl, and Manabu Shiraiwa
Atmos. Chem. Phys., 24, 3445–3528, https://doi.org/10.5194/acp-24-3445-2024, https://doi.org/10.5194/acp-24-3445-2024, 2024
Short summary
Short summary
The initial step of interfacial and multiphase chemical processes involves adsorption and desorption of gas species. This study demonstrates the role of desorption energy governing the residence time of the gas species at the environmental interface. A parameterization is formulated that enables the prediction of desorption energy based on the molecular weight, polarizability, and oxygen-to-carbon ratio of the desorbing chemical species. Its application to gas–particle interactions is discussed.
Rolf Müller, Ulrich Pöschl, Thomas Koop, Thomas Peter, and Ken Carslaw
Atmos. Chem. Phys., 23, 15445–15453, https://doi.org/10.5194/acp-23-15445-2023, https://doi.org/10.5194/acp-23-15445-2023, 2023
Short summary
Short summary
Paul J. Crutzen was a pioneer in atmospheric sciences and a kind-hearted, humorous person with empathy for the private lives of his colleagues and students. He made fundamental scientific contributions to a wide range of scientific topics in all parts of the atmosphere. Paul was among the founders of the journal Atmospheric Chemistry and Physics. His work will continue to be a guide for generations of scientists and environmental policymakers to come.
Hyun Gu Kang, Yanfang Chen, Yoojin Park, Thomas Berkemeier, and Hwajin Kim
Atmos. Chem. Phys., 23, 14307–14323, https://doi.org/10.5194/acp-23-14307-2023, https://doi.org/10.5194/acp-23-14307-2023, 2023
Short summary
Short summary
D5 is an emerging anthropogenic pollutant that is ubiquitous in indoor and urban environments, and the OH oxidation of D5 forms secondary organosiloxane aerosol (SOSiA). Application of a kinetic box model that uses a volatility basis set (VBS) showed that consideration of oxidative aging (aging-VBS) predicts SOSiA formation much better than using a standard-VBS model. Ageing-dependent parameterization is needed to accurately model SOSiA to assess the implications of siloxanes for air quality.
Adam Milsom, Shaojun Qi, Ashmi Mishra, Thomas Berkemeier, Zhenyu Zhang, and Christian Pfrang
Atmos. Chem. Phys., 23, 10835–10843, https://doi.org/10.5194/acp-23-10835-2023, https://doi.org/10.5194/acp-23-10835-2023, 2023
Short summary
Short summary
Aerosols and films are found indoors and outdoors. Our study measures and models reactions of a cooking aerosol proxy with the atmospheric oxidant ozone relying on a low-cost but sensitive technique based on mass changes and film rigidity. We found that film morphology changed and film rigidity increased with evidence of surface crust formation during ozone exposure. Our modelling results demonstrate clear potential to take this robust method to the field for reaction monitoring.
Najin Kim, Hang Su, Nan Ma, Ulrich Pöschl, and Yafang Cheng
Atmos. Meas. Tech., 16, 2771–2780, https://doi.org/10.5194/amt-16-2771-2023, https://doi.org/10.5194/amt-16-2771-2023, 2023
Short summary
Short summary
We propose a multiple-charging correction algorithm for a broad-supersaturation scanning cloud condensation nuclei (BS2-CCN) system which can obtain high time-resolution aerosol hygroscopicity and CCN activity. The correction algorithm aims at deriving the activation fraction's true value for each particle size. The meaningful differences between corrected and original κ values (single hygroscopicity parameter) emphasize the correction algorithm's importance for ambient aerosol measurement.
Ting Lei, Hang Su, Nan Ma, Ulrich Pöschl, Alfred Wiedensohler, and Yafang Cheng
Atmos. Chem. Phys., 23, 4763–4774, https://doi.org/10.5194/acp-23-4763-2023, https://doi.org/10.5194/acp-23-4763-2023, 2023
Short summary
Short summary
We investigate the hygroscopic behavior of levoglucosan and D-glucose nanoparticles using a nano-HTDMA. There is a weak size dependence of the hygroscopic growth factor of levoglucosan and D-glucose with diameters down to 20 nm, while a strong size dependence of the hygroscopic growth factor of D-glucose has been clearly observed in the size range 6 to 20 nm. The use of the DKA method leads to good agreement with the hygroscopic growth factor of glucose nanoparticles with diameters down to 6 nm.
Thomas Berkemeier, Matteo Krüger, Aryeh Feinberg, Marcel Müller, Ulrich Pöschl, and Ulrich K. Krieger
Geosci. Model Dev., 16, 2037–2054, https://doi.org/10.5194/gmd-16-2037-2023, https://doi.org/10.5194/gmd-16-2037-2023, 2023
Short summary
Short summary
Kinetic multi-layer models (KMs) successfully describe heterogeneous and multiphase atmospheric chemistry. In applications requiring repeated execution, however, these models can be too expensive. We trained machine learning surrogate models on output of the model KM-SUB and achieved high correlations. The surrogate models run orders of magnitude faster, which suggests potential applicability in global optimization tasks and as sub-modules in large-scale atmospheric models.
Haley M. Royer, Mira L. Pöhlker, Ovid Krüger, Edmund Blades, Peter Sealy, Nurun Nahar Lata, Zezhen Cheng, Swarup China, Andrew P. Ault, Patricia K. Quinn, Paquita Zuidema, Christopher Pöhlker, Ulrich Pöschl, Meinrat Andreae, and Cassandra J. Gaston
Atmos. Chem. Phys., 23, 981–998, https://doi.org/10.5194/acp-23-981-2023, https://doi.org/10.5194/acp-23-981-2023, 2023
Short summary
Short summary
This paper presents atmospheric particle chemical composition and measurements of aerosol water uptake properties collected at Ragged Point, Barbados, during the winter of 2020. The result of this study indicates the importance of small African smoke particles for cloud droplet formation in the tropical North Atlantic and highlights the large spatial and temporal pervasiveness of smoke over the Atlantic Ocean.
Yunfan Liu, Hang Su, Siwen Wang, Chao Wei, Wei Tao, Mira L. Pöhlker, Christopher Pöhlker, Bruna A. Holanda, Ovid O. Krüger, Thorsten Hoffmann, Manfred Wendisch, Paulo Artaxo, Ulrich Pöschl, Meinrat O. Andreae, and Yafang Cheng
Atmos. Chem. Phys., 23, 251–272, https://doi.org/10.5194/acp-23-251-2023, https://doi.org/10.5194/acp-23-251-2023, 2023
Short summary
Short summary
The origins of the abundant cloud condensation nuclei (CCN) in the upper troposphere (UT) of the Amazon remain unclear. With model developments of new secondary organic aerosol schemes and constrained by observation, we show that strong aerosol nucleation and condensation in the UT is triggered by biogenic organics, and organic condensation is key for UT CCN production. This UT CCN-producing mechanism may prevail over broader vegetation canopies and deserves emphasis in aerosol–climate feedback.
Meredith Schervish and Manabu Shiraiwa
Atmos. Chem. Phys., 23, 221–233, https://doi.org/10.5194/acp-23-221-2023, https://doi.org/10.5194/acp-23-221-2023, 2023
Short summary
Short summary
Secondary organic aerosols (SOAs) can exhibit complex non-ideal behavior and adopt an amorphous semisolid state. We simulate condensation of semi-volatile compounds into a phase-separated particle to investigate the effect of non-ideality and particle phase state on the equilibration timescale of SOA partitioning. Our results provide useful insights into the interpretation of experimental observations and the description and treatment of SOA in aerosol models.
Guo Li, Hang Su, Meng Li, Uwe Kuhn, Guangjie Zheng, Lei Han, Fengxia Bao, Ulrich Pöschl, and Yafang Cheng
Atmos. Meas. Tech., 15, 6433–6446, https://doi.org/10.5194/amt-15-6433-2022, https://doi.org/10.5194/amt-15-6433-2022, 2022
Short summary
Short summary
A large fraction of previous work using dynamic flow chambers was to quantify gas exchange in terms of flux or deposition/emission rate. Here, we extended the usage of this technique to examine uptake kinetics on sample surfaces. The good performance of the chamber system was validated. This technique can be further used for liquid samples and real atmospheric aerosol samples without complicated coating procedures, which complements the existing techniques in atmospheric kinetic studies.
Simon F. Reifenberg, Anna Martin, Matthias Kohl, Sara Bacer, Zaneta Hamryszczak, Ivan Tadic, Lenard Röder, Daniel J. Crowley, Horst Fischer, Katharina Kaiser, Johannes Schneider, Raphael Dörich, John N. Crowley, Laura Tomsche, Andreas Marsing, Christiane Voigt, Andreas Zahn, Christopher Pöhlker, Bruna A. Holanda, Ovid Krüger, Ulrich Pöschl, Mira Pöhlker, Patrick Jöckel, Marcel Dorf, Ulrich Schumann, Jonathan Williams, Birger Bohn, Joachim Curtius, Hardwig Harder, Hans Schlager, Jos Lelieveld, and Andrea Pozzer
Atmos. Chem. Phys., 22, 10901–10917, https://doi.org/10.5194/acp-22-10901-2022, https://doi.org/10.5194/acp-22-10901-2022, 2022
Short summary
Short summary
In this work we use a combination of observational data from an aircraft campaign and model results to investigate the effect of the European lockdown due to COVID-19 in spring 2020. Using model results, we show that the largest relative changes to the atmospheric composition caused by the reduced emissions are located in the upper troposphere around aircraft cruise altitude, while the largest absolute changes are present at the surface.
Alexander D. Harrison, Daniel O'Sullivan, Michael P. Adams, Grace C. E. Porter, Edmund Blades, Cherise Brathwaite, Rebecca Chewitt-Lucas, Cassandra Gaston, Rachel Hawker, Ovid O. Krüger, Leslie Neve, Mira L. Pöhlker, Christopher Pöhlker, Ulrich Pöschl, Alberto Sanchez-Marroquin, Andrea Sealy, Peter Sealy, Mark D. Tarn, Shanice Whitehall, James B. McQuaid, Kenneth S. Carslaw, Joseph M. Prospero, and Benjamin J. Murray
Atmos. Chem. Phys., 22, 9663–9680, https://doi.org/10.5194/acp-22-9663-2022, https://doi.org/10.5194/acp-22-9663-2022, 2022
Short summary
Short summary
The formation of ice in clouds fundamentally alters cloud properties; hence it is important we understand the special aerosol particles that can nucleate ice when immersed in supercooled cloud droplets. In this paper we show that African desert dust that has travelled across the Atlantic to the Caribbean nucleates ice much less well than we might have expected.
Marco Wietzoreck, Marios Kyprianou, Benjamin A. Musa Bandowe, Siddika Celik, John N. Crowley, Frank Drewnick, Philipp Eger, Nils Friedrich, Minas Iakovides, Petr Kukučka, Jan Kuta, Barbora Nežiková, Petra Pokorná, Petra Přibylová, Roman Prokeš, Roland Rohloff, Ivan Tadic, Sebastian Tauer, Jake Wilson, Hartwig Harder, Jos Lelieveld, Ulrich Pöschl, Euripides G. Stephanou, and Gerhard Lammel
Atmos. Chem. Phys., 22, 8739–8766, https://doi.org/10.5194/acp-22-8739-2022, https://doi.org/10.5194/acp-22-8739-2022, 2022
Short summary
Short summary
A unique dataset of concentrations and sources of polycyclic aromatic hydrocarbons (PAHs) and their alkylated, oxygenated and nitrated derivatives, in total 74 individual species, in the marine atmosphere is presented. Exposure to these substances poses a major health risk. We found very low concentrations over the Arabian Sea, while both local and long-range-transported pollution caused elevated levels over the Mediterranean Sea and the Arabian Gulf.
Ovid O. Krüger, Bruna A. Holanda, Sourangsu Chowdhury, Andrea Pozzer, David Walter, Christopher Pöhlker, Maria Dolores Andrés Hernández, John P. Burrows, Christiane Voigt, Jos Lelieveld, Johannes Quaas, Ulrich Pöschl, and Mira L. Pöhlker
Atmos. Chem. Phys., 22, 8683–8699, https://doi.org/10.5194/acp-22-8683-2022, https://doi.org/10.5194/acp-22-8683-2022, 2022
Short summary
Short summary
The abrupt reduction in human activities during the first COVID-19 lockdown created unprecedented atmospheric conditions. We took the opportunity to quantify changes in black carbon (BC) as a major anthropogenic air pollutant. Therefore, we measured BC on board a research aircraft over Europe during the lockdown and compared the results to measurements from 2017. With model simulations we account for different weather conditions and find a lockdown-related decrease in BC of 41 %.
M. Dolores Andrés Hernández, Andreas Hilboll, Helmut Ziereis, Eric Förster, Ovid O. Krüger, Katharina Kaiser, Johannes Schneider, Francesca Barnaba, Mihalis Vrekoussis, Jörg Schmidt, Heidi Huntrieser, Anne-Marlene Blechschmidt, Midhun George, Vladyslav Nenakhov, Theresa Harlass, Bruna A. Holanda, Jennifer Wolf, Lisa Eirenschmalz, Marc Krebsbach, Mira L. Pöhlker, Anna B. Kalisz Hedegaard, Linlu Mei, Klaus Pfeilsticker, Yangzhuoran Liu, Ralf Koppmann, Hans Schlager, Birger Bohn, Ulrich Schumann, Andreas Richter, Benjamin Schreiner, Daniel Sauer, Robert Baumann, Mariano Mertens, Patrick Jöckel, Markus Kilian, Greta Stratmann, Christopher Pöhlker, Monica Campanelli, Marco Pandolfi, Michael Sicard, José L. Gómez-Amo, Manuel Pujadas, Katja Bigge, Flora Kluge, Anja Schwarz, Nikos Daskalakis, David Walter, Andreas Zahn, Ulrich Pöschl, Harald Bönisch, Stephan Borrmann, Ulrich Platt, and John P. Burrows
Atmos. Chem. Phys., 22, 5877–5924, https://doi.org/10.5194/acp-22-5877-2022, https://doi.org/10.5194/acp-22-5877-2022, 2022
Short summary
Short summary
EMeRGe provides a unique set of in situ and remote sensing airborne measurements of trace gases and aerosol particles along selected flight routes in the lower troposphere over Europe. The interpretation uses also complementary collocated ground-based and satellite measurements. The collected data help to improve the current understanding of the complex spatial distribution of trace gases and aerosol particles resulting from mixing, transport, and transformation of pollution plumes over Europe.
Marco A. Franco, Florian Ditas, Leslie A. Kremper, Luiz A. T. Machado, Meinrat O. Andreae, Alessandro Araújo, Henrique M. J. Barbosa, Joel F. de Brito, Samara Carbone, Bruna A. Holanda, Fernando G. Morais, Janaína P. Nascimento, Mira L. Pöhlker, Luciana V. Rizzo, Marta Sá, Jorge Saturno, David Walter, Stefan Wolff, Ulrich Pöschl, Paulo Artaxo, and Christopher Pöhlker
Atmos. Chem. Phys., 22, 3469–3492, https://doi.org/10.5194/acp-22-3469-2022, https://doi.org/10.5194/acp-22-3469-2022, 2022
Short summary
Short summary
In Central Amazonia, new particle formation in the planetary boundary layer is rare. Instead, there is the appearance of sub-50 nm aerosols with diameters larger than about 20 nm that eventually grow to cloud condensation nuclei size range. Here, 254 growth events were characterized which have higher predominance in the wet season. About 70 % of them showed direct relation to convective downdrafts, while 30 % occurred partly under clear-sky conditions, evidencing still unknown particle sources.
Stefan Niebler, Annette Miltenberger, Bertil Schmidt, and Peter Spichtinger
Weather Clim. Dynam., 3, 113–137, https://doi.org/10.5194/wcd-3-113-2022, https://doi.org/10.5194/wcd-3-113-2022, 2022
Short summary
Short summary
We use machine learning to create a network that detects and classifies four types of synoptic-scale weather fronts from ERA5 atmospheric reanalysis data. We present an application of our method, showing its use case in a scientific context. Additionally, our results show that multiple sources of training data are necessary to perform well on different regions, implying differences within those regions. Qualitative evaluation shows that the results are physically plausible.
Kai Tang, Beatriz Sánchez-Parra, Petya Yordanova, Jörn Wehking, Anna T. Backes, Daniel A. Pickersgill, Stefanie Maier, Jean Sciare, Ulrich Pöschl, Bettina Weber, and Janine Fröhlich-Nowoisky
Biogeosciences, 19, 71–91, https://doi.org/10.5194/bg-19-71-2022, https://doi.org/10.5194/bg-19-71-2022, 2022
Short summary
Short summary
Metagenomic sequencing and freezing experiments of aerosol samples collected on Cyprus revealed rain-related short-term changes of bioaerosol and ice nuclei composition. Filtration experiments showed a rain-related enhancement of biological ice nuclei > 5 µm and < 0.1 µm. The observed effects of rainfall on the composition of atmospheric bioaerosols and ice nuclei may influence the hydrological cycle as well as the health effects of air particulate matter (pathogens, allergens).
Luiz A. T. Machado, Marco A. Franco, Leslie A. Kremper, Florian Ditas, Meinrat O. Andreae, Paulo Artaxo, Micael A. Cecchini, Bruna A. Holanda, Mira L. Pöhlker, Ivan Saraiva, Stefan Wolff, Ulrich Pöschl, and Christopher Pöhlker
Atmos. Chem. Phys., 21, 18065–18086, https://doi.org/10.5194/acp-21-18065-2021, https://doi.org/10.5194/acp-21-18065-2021, 2021
Short summary
Short summary
Several studies evaluate aerosol–cloud interactions, but only a few attempted to describe how clouds modify aerosol properties. This study evaluates the effect of weather events on the particle size distribution at the ATTO, combining remote sensing and in situ data. Ultrafine, Aitken and accumulation particles modes have different behaviors for the diurnal cycle and for rainfall events. This study opens up new scientific questions that need to be pursued in detail in new field campaigns.
Ramon Campos Braga, Barbara Ervens, Daniel Rosenfeld, Meinrat O. Andreae, Jan-David Förster, Daniel Fütterer, Lianet Hernández Pardo, Bruna A. Holanda, Tina Jurkat-Witschas, Ovid O. Krüger, Oliver Lauer, Luiz A. T. Machado, Christopher Pöhlker, Daniel Sauer, Christiane Voigt, Adrian Walser, Manfred Wendisch, Ulrich Pöschl, and Mira L. Pöhlker
Atmos. Chem. Phys., 21, 17513–17528, https://doi.org/10.5194/acp-21-17513-2021, https://doi.org/10.5194/acp-21-17513-2021, 2021
Short summary
Short summary
Interactions of aerosol particles with clouds represent a large uncertainty in estimates of climate change. Properties of aerosol particles control their ability to act as cloud condensation nuclei. Using aerosol measurements in the Amazon, we performed model studies to compare predicted and measured cloud droplet number concentrations at cloud bases. Our results confirm previous estimates of particle hygroscopicity in this region.
Najin Kim, Yafang Cheng, Nan Ma, Mira L. Pöhlker, Thomas Klimach, Thomas F. Mentel, Ovid O. Krüger, Ulrich Pöschl, and Hang Su
Atmos. Meas. Tech., 14, 6991–7005, https://doi.org/10.5194/amt-14-6991-2021, https://doi.org/10.5194/amt-14-6991-2021, 2021
Short summary
Short summary
A broad supersaturation scanning CCN (BS2-CCN) system, in which particles are exposed to a range of supersaturation simultaneously, can measure a broad range of CCN activity distribution with a high time resolution. We describe how the BS2-CCN system can be effectively calibrated and which factors can affect the calibration curve. Intercomparison experiments between typical DMA-CCN and BS2-CCN measurements to evaluate the BS2-CCN system showed high correlation and good agreement.
Ramon Campos Braga, Daniel Rosenfeld, Ovid O. Krüger, Barbara Ervens, Bruna A. Holanda, Manfred Wendisch, Trismono Krisna, Ulrich Pöschl, Meinrat O. Andreae, Christiane Voigt, and Mira L. Pöhlker
Atmos. Chem. Phys., 21, 14079–14088, https://doi.org/10.5194/acp-21-14079-2021, https://doi.org/10.5194/acp-21-14079-2021, 2021
Short summary
Short summary
Quantifying the precipitation within clouds is crucial for our understanding of the Earth's hydrological cycle. Using in situ measurements of cloud and rain properties over the Amazon Basin and Atlantic Ocean, we show here a linear relationship between the effective radius (re) and precipitation water content near the tops of convective clouds for different pollution states and temperature levels. Our results emphasize the role of re to determine both initiation and amount of precipitation.
Maria Prass, Meinrat O. Andreae, Alessandro C. de Araùjo, Paulo Artaxo, Florian Ditas, Wolfgang Elbert, Jan-David Förster, Marco Aurélio Franco, Isabella Hrabe de Angelis, Jürgen Kesselmeier, Thomas Klimach, Leslie Ann Kremper, Eckhard Thines, David Walter, Jens Weber, Bettina Weber, Bernhard M. Fuchs, Ulrich Pöschl, and Christopher Pöhlker
Biogeosciences, 18, 4873–4887, https://doi.org/10.5194/bg-18-4873-2021, https://doi.org/10.5194/bg-18-4873-2021, 2021
Short summary
Short summary
Bioaerosols in the atmosphere over the Amazon rain forest were analyzed by molecular biological staining and microscopy. Eukaryotic, bacterial, and archaeal aerosols were quantified in time series and altitude profiles which exhibited clear differences in number concentrations and vertical distributions. Our results provide insights into the sources and dispersion of different Amazonian bioaerosol types as a basis for a better understanding of biosphere–atmosphere interactions.
Bjorn Stevens, Sandrine Bony, David Farrell, Felix Ament, Alan Blyth, Christopher Fairall, Johannes Karstensen, Patricia K. Quinn, Sabrina Speich, Claudia Acquistapace, Franziska Aemisegger, Anna Lea Albright, Hugo Bellenger, Eberhard Bodenschatz, Kathy-Ann Caesar, Rebecca Chewitt-Lucas, Gijs de Boer, Julien Delanoë, Leif Denby, Florian Ewald, Benjamin Fildier, Marvin Forde, Geet George, Silke Gross, Martin Hagen, Andrea Hausold, Karen J. Heywood, Lutz Hirsch, Marek Jacob, Friedhelm Jansen, Stefan Kinne, Daniel Klocke, Tobias Kölling, Heike Konow, Marie Lothon, Wiebke Mohr, Ann Kristin Naumann, Louise Nuijens, Léa Olivier, Robert Pincus, Mira Pöhlker, Gilles Reverdin, Gregory Roberts, Sabrina Schnitt, Hauke Schulz, A. Pier Siebesma, Claudia Christine Stephan, Peter Sullivan, Ludovic Touzé-Peiffer, Jessica Vial, Raphaela Vogel, Paquita Zuidema, Nicola Alexander, Lyndon Alves, Sophian Arixi, Hamish Asmath, Gholamhossein Bagheri, Katharina Baier, Adriana Bailey, Dariusz Baranowski, Alexandre Baron, Sébastien Barrau, Paul A. Barrett, Frédéric Batier, Andreas Behrendt, Arne Bendinger, Florent Beucher, Sebastien Bigorre, Edmund Blades, Peter Blossey, Olivier Bock, Steven Böing, Pierre Bosser, Denis Bourras, Pascale Bouruet-Aubertot, Keith Bower, Pierre Branellec, Hubert Branger, Michal Brennek, Alan Brewer, Pierre-Etienne Brilouet, Björn Brügmann, Stefan A. Buehler, Elmo Burke, Ralph Burton, Radiance Calmer, Jean-Christophe Canonici, Xavier Carton, Gregory Cato Jr., Jude Andre Charles, Patrick Chazette, Yanxu Chen, Michal T. Chilinski, Thomas Choularton, Patrick Chuang, Shamal Clarke, Hugh Coe, Céline Cornet, Pierre Coutris, Fleur Couvreux, Susanne Crewell, Timothy Cronin, Zhiqiang Cui, Yannis Cuypers, Alton Daley, Gillian M. Damerell, Thibaut Dauhut, Hartwig Deneke, Jean-Philippe Desbios, Steffen Dörner, Sebastian Donner, Vincent Douet, Kyla Drushka, Marina Dütsch, André Ehrlich, Kerry Emanuel, Alexandros Emmanouilidis, Jean-Claude Etienne, Sheryl Etienne-Leblanc, Ghislain Faure, Graham Feingold, Luca Ferrero, Andreas Fix, Cyrille Flamant, Piotr Jacek Flatau, Gregory R. Foltz, Linda Forster, Iulian Furtuna, Alan Gadian, Joseph Galewsky, Martin Gallagher, Peter Gallimore, Cassandra Gaston, Chelle Gentemann, Nicolas Geyskens, Andreas Giez, John Gollop, Isabelle Gouirand, Christophe Gourbeyre, Dörte de Graaf, Geiske E. de Groot, Robert Grosz, Johannes Güttler, Manuel Gutleben, Kashawn Hall, George Harris, Kevin C. Helfer, Dean Henze, Calvert Herbert, Bruna Holanda, Antonio Ibanez-Landeta, Janet Intrieri, Suneil Iyer, Fabrice Julien, Heike Kalesse, Jan Kazil, Alexander Kellman, Abiel T. Kidane, Ulrike Kirchner, Marcus Klingebiel, Mareike Körner, Leslie Ann Kremper, Jan Kretzschmar, Ovid Krüger, Wojciech Kumala, Armin Kurz, Pierre L'Hégaret, Matthieu Labaste, Tom Lachlan-Cope, Arlene Laing, Peter Landschützer, Theresa Lang, Diego Lange, Ingo Lange, Clément Laplace, Gauke Lavik, Rémi Laxenaire, Caroline Le Bihan, Mason Leandro, Nathalie Lefevre, Marius Lena, Donald Lenschow, Qiang Li, Gary Lloyd, Sebastian Los, Niccolò Losi, Oscar Lovell, Christopher Luneau, Przemyslaw Makuch, Szymon Malinowski, Gaston Manta, Eleni Marinou, Nicholas Marsden, Sebastien Masson, Nicolas Maury, Bernhard Mayer, Margarette Mayers-Als, Christophe Mazel, Wayne McGeary, James C. McWilliams, Mario Mech, Melina Mehlmann, Agostino Niyonkuru Meroni, Theresa Mieslinger, Andreas Minikin, Peter Minnett, Gregor Möller, Yanmichel Morfa Avalos, Caroline Muller, Ionela Musat, Anna Napoli, Almuth Neuberger, Christophe Noisel, David Noone, Freja Nordsiek, Jakub L. Nowak, Lothar Oswald, Douglas J. Parker, Carolyn Peck, Renaud Person, Miriam Philippi, Albert Plueddemann, Christopher Pöhlker, Veronika Pörtge, Ulrich Pöschl, Lawrence Pologne, Michał Posyniak, Marc Prange, Estefanía Quiñones Meléndez, Jule Radtke, Karim Ramage, Jens Reimann, Lionel Renault, Klaus Reus, Ashford Reyes, Joachim Ribbe, Maximilian Ringel, Markus Ritschel, Cesar B. Rocha, Nicolas Rochetin, Johannes Röttenbacher, Callum Rollo, Haley Royer, Pauline Sadoulet, Leo Saffin, Sanola Sandiford, Irina Sandu, Michael Schäfer, Vera Schemann, Imke Schirmacher, Oliver Schlenczek, Jerome Schmidt, Marcel Schröder, Alfons Schwarzenboeck, Andrea Sealy, Christoph J. Senff, Ilya Serikov, Samkeyat Shohan, Elizabeth Siddle, Alexander Smirnov, Florian Späth, Branden Spooner, M. Katharina Stolla, Wojciech Szkółka, Simon P. de Szoeke, Stéphane Tarot, Eleni Tetoni, Elizabeth Thompson, Jim Thomson, Lorenzo Tomassini, Julien Totems, Alma Anna Ubele, Leonie Villiger, Jan von Arx, Thomas Wagner, Andi Walther, Ben Webber, Manfred Wendisch, Shanice Whitehall, Anton Wiltshire, Allison A. Wing, Martin Wirth, Jonathan Wiskandt, Kevin Wolf, Ludwig Worbes, Ethan Wright, Volker Wulfmeyer, Shanea Young, Chidong Zhang, Dongxiao Zhang, Florian Ziemen, Tobias Zinner, and Martin Zöger
Earth Syst. Sci. Data, 13, 4067–4119, https://doi.org/10.5194/essd-13-4067-2021, https://doi.org/10.5194/essd-13-4067-2021, 2021
Short summary
Short summary
The EUREC4A field campaign, designed to test hypothesized mechanisms by which clouds respond to warming and benchmark next-generation Earth-system models, is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. It was the first campaign that attempted to characterize the full range of processes and scales influencing trade wind clouds.
Mira L. Pöhlker, Minghui Zhang, Ramon Campos Braga, Ovid O. Krüger, Ulrich Pöschl, and Barbara Ervens
Atmos. Chem. Phys., 21, 11723–11740, https://doi.org/10.5194/acp-21-11723-2021, https://doi.org/10.5194/acp-21-11723-2021, 2021
Short summary
Short summary
Clouds cool our atmosphere. The role of small aerosol particles in affecting them represents one of the largest uncertainties in current estimates of climate change. Traditionally it is assumed that cloud droplets only form particles of diameters ~ 100 nm (
accumulation mode). Previous studies suggest that this can also occur in smaller particles (
Aitken mode). Our study provides a general framework to estimate under which aerosol and cloud conditions Aitken mode particles affect clouds.
Haijie Tong, Fobang Liu, Alexander Filippi, Jake Wilson, Andrea M. Arangio, Yun Zhang, Siyao Yue, Steven Lelieveld, Fangxia Shen, Helmi-Marja K. Keskinen, Jing Li, Haoxuan Chen, Ting Zhang, Thorsten Hoffmann, Pingqing Fu, William H. Brune, Tuukka Petäjä, Markku Kulmala, Maosheng Yao, Thomas Berkemeier, Manabu Shiraiwa, and Ulrich Pöschl
Atmos. Chem. Phys., 21, 10439–10455, https://doi.org/10.5194/acp-21-10439-2021, https://doi.org/10.5194/acp-21-10439-2021, 2021
Short summary
Short summary
We measured radical yields of aqueous PM2.5 extracts and found lower yields at higher concentrations of PM2.5. Abundances of water-soluble transition metals and aromatics in PM2.5 were positively correlated with the relative fraction of •OH but negatively correlated with the relative fraction of C-centered radicals among detected radicals. Composition-dependent reactive species yields may explain differences in the reactivity and health effects of PM2.5 in clean versus polluted air.
Tommaso Galeazzo, Richard Valorso, Ying Li, Marie Camredon, Bernard Aumont, and Manabu Shiraiwa
Atmos. Chem. Phys., 21, 10199–10213, https://doi.org/10.5194/acp-21-10199-2021, https://doi.org/10.5194/acp-21-10199-2021, 2021
Short summary
Short summary
We simulate SOA viscosity with explicit modeling of gas-phase oxidation of isoprene and α-pinene. While the viscosity dependence on relative humidity and mass loadings is captured well by simulations, the model underestimates measured viscosity, indicating missing processes. Kinetic limitations and reduction in mass accommodation may cause an increase in viscosity. The developed model is powerful for investigation of the interplay among gas reactions, chemical composition and phase state.
Eugene F. Mikhailov, Mira L. Pöhlker, Kathrin Reinmuth-Selzle, Sergey S. Vlasenko, Ovid O. Krüger, Janine Fröhlich-Nowoisky, Christopher Pöhlker, Olga A. Ivanova, Alexey A. Kiselev, Leslie A. Kremper, and Ulrich Pöschl
Atmos. Chem. Phys., 21, 6999–7022, https://doi.org/10.5194/acp-21-6999-2021, https://doi.org/10.5194/acp-21-6999-2021, 2021
Short summary
Short summary
Subpollen particles are a relatively new subset of atmospheric aerosol particles. When pollen grains rupture, they release cytoplasmic fragments known as subpollen particles (SPPs). We found that SPPs, containing a broad spectrum of biopolymers and hydrocarbons, exhibit abnormally high water uptake. This effect may influence the life cycle of SPPs and the related direct and indirect impacts on radiation budget as well as reinforce their allergic potential.
Patricia K. Quinn, Elizabeth J. Thompson, Derek J. Coffman, Sunil Baidar, Ludovic Bariteau, Timothy S. Bates, Sebastien Bigorre, Alan Brewer, Gijs de Boer, Simon P. de Szoeke, Kyla Drushka, Gregory R. Foltz, Janet Intrieri, Suneil Iyer, Chris W. Fairall, Cassandra J. Gaston, Friedhelm Jansen, James E. Johnson, Ovid O. Krüger, Richard D. Marchbanks, Kenneth P. Moran, David Noone, Sergio Pezoa, Robert Pincus, Albert J. Plueddemann, Mira L. Pöhlker, Ulrich Pöschl, Estefania Quinones Melendez, Haley M. Royer, Malgorzata Szczodrak, Jim Thomson, Lucia M. Upchurch, Chidong Zhang, Dongxiao Zhang, and Paquita Zuidema
Earth Syst. Sci. Data, 13, 1759–1790, https://doi.org/10.5194/essd-13-1759-2021, https://doi.org/10.5194/essd-13-1759-2021, 2021
Short summary
Short summary
ATOMIC took place in the northwestern tropical Atlantic during January and February of 2020 to gather information on shallow atmospheric convection, the effects of aerosols and clouds on the ocean surface energy budget, and mesoscale oceanic processes. Measurements made from the NOAA RV Ronald H. Brown and assets it deployed (instrumented mooring and uncrewed seagoing vehicles) are described herein to advance widespread use of the data by the ATOMIC and broader research communities.
Jake Wilson, Ulrich Pöschl, Manabu Shiraiwa, and Thomas Berkemeier
Atmos. Chem. Phys., 21, 6175–6198, https://doi.org/10.5194/acp-21-6175-2021, https://doi.org/10.5194/acp-21-6175-2021, 2021
Short summary
Short summary
This work explores the gas–particle partitioning of PAHs on soot with a kinetic model. We show that the equilibration timescale depends on PAH molecular structure, temperature, and particle number concentration. We explore scenarios in which the particulate fraction is perturbed from equilibrium by chemical loss and discuss implications for chemical transport models that assume instantaneous equilibration at each model time step.
Manabu Shiraiwa and Ulrich Pöschl
Atmos. Chem. Phys., 21, 1565–1580, https://doi.org/10.5194/acp-21-1565-2021, https://doi.org/10.5194/acp-21-1565-2021, 2021
Short summary
Short summary
Mass accommodation is a crucial process in secondary organic aerosol partitioning that depends on volatility, diffusivity, reactivity, and particle penetration depth of the chemical species involved. For efficient kinetic modeling, we introduce an effective mass accommodation coefficient that accounts for the above influencing factors, can be applied in the common Fuchs–Sutugin approximation, and helps to resolve inconsistencies and shortcomings of earlier experimental and model investigations.
Chuchu Chen, Xiaoxiang Wang, Kurt Binder, Mohammad Mehdi Ghahremanpour, David van der Spoel, Ulrich Pöschl, Hang Su, and Yafang Cheng
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-1329, https://doi.org/10.5194/acp-2020-1329, 2021
Publication in ACP not foreseen
Short summary
Short summary
Size dependence of succinic acid solvation in the nanoparticles is investigated based on the molecular dynamics (MD) simulation and energetic analysis. The results show a stronger surface preference and a weaker internal bulk volume solvation of succinic acid in the smaller droplets, which may explain the previously observed size-dependent phase-state of aerosol nanoparticles containing organic molecules, fundamentally promoting a better understanding of atmospheric aerosols.
Sabin Kasparoglu, Ying Li, Manabu Shiraiwa, and Markus D. Petters
Atmos. Chem. Phys., 21, 1127–1141, https://doi.org/10.5194/acp-21-1127-2021, https://doi.org/10.5194/acp-21-1127-2021, 2021
Short summary
Short summary
Viscosity is important because it determines the lifetime, impact, and fate of particulate matter. We collected new data to rigorously test a framework that is used to constrain the phase state in global simulations. We find that the framework is accurate as long as appropriate compound specific inputs are available.
Thomas Berkemeier, Masayuki Takeuchi, Gamze Eris, and Nga L. Ng
Atmos. Chem. Phys., 20, 15513–15535, https://doi.org/10.5194/acp-20-15513-2020, https://doi.org/10.5194/acp-20-15513-2020, 2020
Short summary
Short summary
This paper presents how environmental chamber data of secondary organic aerosol (SOA) formation can be interpreted using kinetic modeling techniques. Utilizing pure and mixed precursor experiments, we show that SOA formation and evaporation can be understood by explicitly treating gas-phase chemistry, gas–particle partitioning, and, notably, particle-phase oligomerization, but some of the non-linear, non-equilibrium effects must be accredited to diffusion limitations in the particle phase.
Guo Li, Hang Su, Nan Ma, Guangjie Zheng, Uwe Kuhn, Meng Li, Thomas Klimach, Ulrich Pöschl, and Yafang Cheng
Atmos. Meas. Tech., 13, 6053–6065, https://doi.org/10.5194/amt-13-6053-2020, https://doi.org/10.5194/amt-13-6053-2020, 2020
Short summary
Short summary
Aerosol acidity plays an important role in regulating the chemistry, health, and ecological effect of aerosol particles. However, a direct measurement of aerosol pH is very challenging because of its fast transition and equilibrium with adjacent environments. Therefore, most early studies have to use modeled pH, resulting in intensive debates about model uncertainties. Here we developed an optimized approach to measure aerosol pH by using pH-indicator papers combined with RGB-based colorimetry.
Lixia Liu, Yafang Cheng, Siwen Wang, Chao Wei, Mira L. Pöhlker, Christopher Pöhlker, Paulo Artaxo, Manish Shrivastava, Meinrat O. Andreae, Ulrich Pöschl, and Hang Su
Atmos. Chem. Phys., 20, 13283–13301, https://doi.org/10.5194/acp-20-13283-2020, https://doi.org/10.5194/acp-20-13283-2020, 2020
Short summary
Short summary
This modeling paper reveals how aerosol–cloud interactions (ACIs) and aerosol–radiation interactions (ARIs) induced by biomass burning (BB) aerosols act oppositely on radiation, cloud, and precipitation in the Amazon during the dry season. The varying relative significance of ACIs and ARIs with BB aerosol concentration leads to a nonlinear dependence of the total climate response on BB aerosol loading and features the growing importance of ARIs at high aerosol loading.
Ting Lei, Nan Ma, Juan Hong, Thomas Tuch, Xin Wang, Zhibin Wang, Mira Pöhlker, Maofa Ge, Weigang Wang, Eugene Mikhailov, Thorsten Hoffmann, Ulrich Pöschl, Hang Su, Alfred Wiedensohler, and Yafang Cheng
Atmos. Meas. Tech., 13, 5551–5567, https://doi.org/10.5194/amt-13-5551-2020, https://doi.org/10.5194/amt-13-5551-2020, 2020
Short summary
Short summary
We present the design of a nano-hygroscopicity tandem differential mobility analyzer (nano-HTDMA) apparatus that enables high accuracy and precision in hygroscopic growth measurements of aerosol nanoparticles with diameters less than 10 nm. We further introduce comprehensive methods for system calibration and validation of the performance of the system. We then study the size dependence of the deliquescence and the efflorescence of aerosol nanoparticles for sizes down to 6 nm.
Wei Tao, Hang Su, Guangjie Zheng, Jiandong Wang, Chao Wei, Lixia Liu, Nan Ma, Meng Li, Qiang Zhang, Ulrich Pöschl, and Yafang Cheng
Atmos. Chem. Phys., 20, 11729–11746, https://doi.org/10.5194/acp-20-11729-2020, https://doi.org/10.5194/acp-20-11729-2020, 2020
Short summary
Short summary
We simulated the thermodynamic and multiphase reactions in aerosol water during a wintertime haze event over the North China Plain. It was found that aerosol pH exhibited a strong spatiotemporal variability, and multiple oxidation pathways were predominant for particulate sulfate formation in different locations. Sensitivity tests further showed that ammonia, crustal particles, and dissolved transition metal ions were important factors for multiphase chemistry during haze episodes.
Cited articles
Akiba, T., Sano, S., Yanase, T., Ohta, T., and Koyama, M.: Optuna: A Next-generation Hyperparameter Optimization Framework, in: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, ACM, Anchorage AK USA, 2623–2631, ISBN 978-1-4503-6201-6, https://doi.org/10.1145/3292500.3330701, 2019. a
Armeli, G., Peters, J.-H., and Koop, T.: Machine-Learning-Based Prediction of the Glass Transition Temperature of Organic Compounds Using Experimental Data, ACS Omega, 8, 12298–12309, https://doi.org/10.1021/acsomega.2c08146, 2023. a, b
Atz, K., Grisoni, F., and Schneider, G.: Geometric deep learning on molecular representations, Nat. Mach. Intell., 3, 1023–1032, https://doi.org/10.1038/s42256-021-00418-8, 2021. a
Aumont, B., Szopa, S., and Madronich, S.: Modelling the evolution of organic carbon during its gas-phase tropospheric oxidation: development of an explicit model based on a self generating approach, Atmos. Chem. Phys., 5, 2497–2517, https://doi.org/10.5194/acp-5-2497-2005, 2005. a
Battaglia, P. W., Hamrick, J. B., Bapst, V., Sanchez-Gonzalez, A., Zambaldi, V., Malinowski, M., Tacchetti, A., Raposo, D., Santoro, A., Faulkner, R., Gulcehre, C., Song, F., Ballard, A., Gilmer, J., Dahl, G., Vaswani, A., Allen, K., Nash, C., Langston, V., Dyer, C., Heess, N., Wierstra, D., Kohli, P., Botvinick, M., Vinyals, O., Li, Y., and Pascanu, R.: Relational inductive biases, deep learning, and graph networks, arXiv [preprint], https://doi.org/10.48550/ARXIV.1806.01261, 2018. a
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, b
Bilde, M., Barsanti, K., Booth, M., Cappa, C. D., Donahue, N. M., Emanuelsson, E. U., McFiggans, G., Krieger, U. K., Marcolli, C., Topping, D., Ziemann, P., Barley, M., Clegg, S., Dennis-Smither, B., Hallquist, M., Hallquist, A. M., Khlystov, A., Kulmala, M., Mogensen, D., Percival, C. J., Pope, F., Reid, J. P., Ribeiro da Silva, M. A. V., Rosenoern, T., Salo, K., Soonsin, V. P., Yli-Juuti, T., Prisle, N. L., Pagels, J., Rarey, J., Zardini, A. A., and Riipinen, I.: Saturation Vapor Pressures and Transition Enthalpies of Low-Volatility Organic Molecules of Atmospheric Relevance: From Dicarboxylic Acids to Complex Mixtures, Chem. Rev., 115, 4115–4156, https://doi.org/10.1021/cr5005502, 2015. a, b, c
Bronstein, M. M., Bruna, J., LeCun, Y., Szlam, A., and Vandergheynst, P.: Geometric Deep Learning: Going beyond Euclidean data, IEEE Signal Process. Mag., 34, 18–42, https://doi.org/10.1109/MSP.2017.2693418, 2017. a
Burns, J., Zalte, A., and Green, W.: Descriptor-based Foundation Models for Molecular Property Prediction, arXiv [preprint], https://doi.org/10.48550/ARXIV.2506.15792, 2025. a, b
Donahue, N. M., Robinson, A. L., and Pandis, S. N.: Atmospheric organic particulate matter: From smoke to secondary organic aerosol, Atmos. Environ., 43, 94–106, https://doi.org/10.1016/j.atmosenv.2008.09.055, 2009. a, b, c
Duvenaud, D., Maclaurin, D., Aguilera-Iparraguirre, J., Gómez-Bombarelli, R., Hirzel, T., Aspuru-Guzik, A., and Adams, R. P.: Convolutional Networks on Graphs for Learning Molecular Fingerprints, arXiv [preprint], https://doi.org/10.48550/arXiv.1509.09292, 2015. a
Gadaleta, D., Lombardo, A., Toma, C., and Benfenati, E.: A new semi-automated workflow for chemical data retrieval and quality checking for modeling applications, J. Cheminform., 10, 60, https://doi.org/10.1186/s13321-018-0315-6, 2018. a
Galeazzo, T. and Shiraiwa, M.: Predicting glass transition temperature and melting point of organic compounds via machine learning and molecular embeddings, Environ. Sci. Atmos., 2, 362–374, https://doi.org/10.1039/D1EA00090J, 2022. a, b
Gani, R.: Group contribution-based property estimation methods: advances and perspectives, Curr. Opin. Chem. Eng., 23, 184–196, https://doi.org/10.1016/j.coche.2019.04.007, 2019. a
Geerlings, P., De Proft, F., and Langenaeker, W.: Conceptual Density Functional Theory, Chem. Rev., 103, 1793–1874, https://doi.org/10.1021/cr990029p, 2003. a
Goldstein, A. H. and Galbally, I. E.: Known and unexplored organic constituents in the earth's atmosphere, Environ. Sci. Technol., 41, 1514–1521, 2007. a
Huisman, A. J., Krieger, U. K., Zuend, A., Marcolli, C., and Peter, T.: Vapor pressures of substituted polycarboxylic acids are much lower than previously reported, Atmos. Chem. Phys., 13, 6647–6662, https://doi.org/10.5194/acp-13-6647-2013, 2013. a
Hyttinen, N., Pullinen, I., Nissinen, A., Schobesberger, S., Virtanen, A., and Yli-Juuti, T.: Comparison of saturation vapor pressures of α-pinene + O3 oxidation products derived from COSMO-RS computations and thermal desorption experiments, Atmos. Chem. Phys., 22, 1195–1208, https://doi.org/10.5194/acp-22-1195-2022, 2022. a
Intergovernmental Panel on Climate Change: Climate Change 2021 – The Physical Science Basis: Working Group I Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, 1 edn., Cambridge University Press, ISBN 978-1-00-915789-6, https://doi.org/10.1017/9781009157896, 2023. a
Isaacman-VanWertz, G. and Aumont, B.: Impact of organic molecular structure on the estimation of atmospherically relevant physicochemical parameters, Atmos. Chem. Phys., 21, 6541–6563, https://doi.org/10.5194/acp-21-6541-2021, 2021. a, b
Jimenez, J. L., Canagaratna, M. R., Donahue, N. M., Prevot, A. S. H., Zhang, Q., Kroll, J. H., DeCarlo, P. F., Allan, J. D., Coe, H., Ng, N. L., Aiken, A. C., Docherty, K. S., Ulbrich, I. M., Grieshop, A. P., Robinson, A. L., Duplissy, J., Smith, J. D., Wilson, K. R., Lanz, V. A., Hueglin, C., Sun, Y. L., Tian, J., Laaksonen, A., Raatikainen, T., Rautiainen, J., Vaattovaara, P., Ehn, M., Kulmala, M., Tomlinson, J. M., Collins, D. R., Cubison, M. J., E., Dunlea, J., Huffman, J. A., Onasch, T. B., Alfarra, M. R., Williams, P. I., Bower, K., Kondo, Y., Schneider, J., Drewnick, F., Borrmann, S., Weimer, S., Demerjian, K., Salcedo, D., Cottrell, L., Griffin, R., Takami, A., Miyoshi, T., Hatakeyama, S., Shimono, A., Sun, J. Y., Zhang, Y. M., Dzepina, K., Kimmel, J. R., Sueper, D., Jayne, J. T., Herndon, S. C., Trimborn, A. M., Williams, L. R., Wood, E. C., Middlebrook, A. M., Kolb, C. E., Baltensperger, U., and Worsnop, D. R.: Evolution of Organic Aerosols in the Atmosphere, Science, 326, 1525–1529, https://doi.org/10.1126/science.1180353, 2009. a
Kanakidou, M., Seinfeld, J. H., Pandis, S. N., Barnes, I., Dentener, F. J., Facchini, M. C., Van Dingenen, R., Ervens, B., Nenes, A., Nielsen, C. J., Swietlicki, E., Putaud, J. P., Balkanski, Y., Fuzzi, S., Horth, J., Moortgat, G. K., Winterhalter, R., Myhre, C. E. L., Tsigaridis, K., Vignati, E., Stephanou, E. G., and Wilson, J.: Organic aerosol and global climate modelling: a review, Atmos. Chem. Phys., 5, 1053–1123, https://doi.org/10.5194/acp-5-1053-2005, 2005. a
Kim, S., Thiessen, P. A., Bolton, E. E., Chen, J., Fu, G., Gindulyte, A., Han, L., He, J., He, S., Shoemaker, B. A., Wang, J., Yu, B., Zhang, J., and Bryant, S. H.: PubChem substance and compound databases, Nucleic Acids Research, 44, D1202–D1213, https://doi.org/10.1093/nar/gkv951, 2016. a
Kipf, T. N. and Welling, M.: Semi-Supervised Classification with Graph Convolutional Networks, arXiv [preprint], https://doi.org/10.48550/arXiv.1609.02907, 2017. a, b
Kirkby, J., Amorim, A., Baltensperger, U., Carslaw, K. S., Christoudias, T., Curtius, J., Donahue, N. M., Haddad, I. E., Flagan, R. C., Gordon, H., Hansel, A., Harder, H., Junninen, H., Kulmala, M., Kürten, A., Laaksonen, A., Lehtipalo, K., Lelieveld, J., Möhler, O., Riipinen, I., Stratmann, F., Tomé, A., Virtanen, A., Volkamer, R., Winkler, P. M., and Worsnop, D. R.: Atmospheric new particle formation from the CERN CLOUD experiment, Nat. Geosci., 16, 948–957, https://doi.org/10.1038/s41561-023-01305-0, 2023. a
Krüger, M. and Berkemeier T.: Code and data for `Improved vapor pressure predictions using group contribution-assisted graph convolutional neural networks (GC2NN)', Edmond, V2 [code and data], https://doi.org/10.17617/3.GIKHJL, 2025. a
Krüger, M., Wilson, J., Wietzoreck, M., Bandowe, B. A. M., Lammel, G., Schmidt, B., Pöschl, U., and Berkemeier, T.: Convolutional neural network prediction of molecular properties for aerosol chemistry and health effects, Nat. Sci., 2, e20220016, https://doi.org/10.1002/ntls.20220016, 2022. a, b, c, d, e, f, g, h, i, j
Kulmala, M. and Kerminen, V.-M.: On the formation and growth of atmospheric nanoparticles, Atmos. Res., 90, 132–150, https://doi.org/10.1016/j.atmosres.2008.01.005, 2008. a
Kurtén, T., Hyttinen, N., D'Ambro, E. L., Thornton, J., and Prisle, N. L.: Estimating the saturation vapor pressures of isoprene oxidation products C5H12O6 and C5H10O6 using COSMO-RS, Atmos. Chem. Phys., 18, 17589–17600, https://doi.org/10.5194/acp-18-17589-2018, 2018. a
Landrum, G.: RDKit: Open-source cheminformatics, Release, 1, 4, https://www.rdkit.org (last access: 1 October 2025), 2013. a
Lansford, J. L., Jensen, K. F., and Barnes, B. C.: Physics‐informed Transfer Learning for Out‐of‐sample Vapor Pressure Predictions, Propellants Explos. Pyrotech., 48, e202200265, https://doi.org/10.1002/prep.202200265, 2023. a
Longnecker, E. R., Bakker-Arkema, J. G., and Ziemann, P. J.: Comparison of Vapor Pressure Estimation Methods Used to Model Secondary Organic Aerosol Formation from Reactions of Linear and Branched Alkenes with OH/NOx, ACS Earth Space Chem., https://doi.org/10.1021/acsearthspacechem.4c00285, 2025. a
Lumiaro, E., Todorović, M., Kurten, T., Vehkamäki, H., and Rinke, P.: Predicting gas–particle partitioning coefficients of atmospheric molecules with machine learning, Atmos. Chem. Phys., 21, 13227–13246, https://doi.org/10.5194/acp-21-13227-2021, 2021. a, b, c
Moller, B., Rarey, J., and Ramjugernath, D.: Estimation of the vapour pressure of non-electrolyte organic compounds via group contributions and group interactions, J. Mol. Liq., 143, 52–63, https://doi.org/10.1016/j.molliq.2008.04.020, 2008. a
Naef, R. and Acree, W. E.: Calculation of the Vapour Pressure of Organic Molecules by Means of a Group-Additivity Method and Their Resultant Gibbs Free Energy and Entropy of Vaporization at 298.15 K, Molecules [data], 26, 1045, https://doi.org/10.3390/molecules26041045, 2021. a
Nannoolal, Y., Rarey, J., Ramjugernath, D., and Cordes, W.: Estimation of pure component properties, Fluid Phase Equilibria, 226, 45–63, https://doi.org/10.1016/j.fluid.2004.09.001, 2004. a
Pankow, J. F.: Review and comparative analysis of the theories on partitioning between the gas and aerosol particulate phases in the atmosphere, Atmos. Environ. (1967), 21, 2275–2283, https://doi.org/10.1016/0004-6981(87)90363-5, 1987. a
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. a, b, c, d
Paszke, A., Gross, S., Massa, F., Lerer, A., Bradbury, J., Chanan, G., Killeen, T., Lin, Z., Gimelshein, N., Antiga, L., Desmaison, A., Kopf, A., Yang, E., DeVito, Z., Raison, M., Tejani, A., Chilamkurthy, S., Steiner, B., Fang, L., Bai, J., Chintala, S.: Pytorch: An imperative style, high-performance deep learning library, Adv. Neural Inf. Process. Syst., 32, https://doi.org/10.48550/arXiv.1912.01703, 2019. a
Pöschl, U. and Shiraiwa, M.: Multiphase Chemistry at the Atmosphere–Biosphere Interface Influencing Climate and Public Health in the Anthropocene, Chem. Rev., 115, 4440–4475, https://doi.org/10.1021/cr500487s, 2015. a
Ratcliff, L. E., Mohr, S., Huhs, G., Deutsch, T., Masella, M., and Genovese, L.: Challenges in large scale quantum mechanical calculations, WIREs Comput. Mol. Sci., 7, e1290, https://doi.org/10.1002/wcms.1290, 2017. a
Reiser, P., Neubert, M., Eberhard, A., Torresi, L., Zhou, C., Shao, C., Metni, H., van Hoesel, C., Schopmans, H., Sommer, T., and Friederich, P.: Graph neural networks for materials science and chemistry, Commun. Mater., 3, 241722, https://doi.org/10.1038/s43246-022-00315-6, 2022. a
Sanchez-Lengeling, B., Wei, J., Lee, B., Reif, E., Wang, P., Qian, W., McCloskey, K., Colwell, L., and Wiltschko, A.: Evaluating Attribution for Graph Neural Networks, in: Adv. Neural Inf. Process. Syst., edited by: Larochelle, H., Ranzato, M., Hadsell, R., Balcan, M. F., and Lin, H., vol. 33, Curran Associates, Inc., 5898–5910, https://proceedings.neurips.cc/paper_files/paper/2020/file/417fbbf2e9d5a28a855a11894b2e795a-Paper.pdf (last access: 1 October 2025), 2020. a
Shiraiwa, M., Berkemeier, T., Schilling-Fahnestock, K. A., Seinfeld, J. H., and Pöschl, U.: Molecular corridors and kinetic regimes in the multiphase chemical evolution of secondary organic aerosol, Atmos. Chem. Phys., 14, 8323–8341, https://doi.org/10.5194/acp-14-8323-2014, 2014. a, b, c, d, e, f, g
Shrivastava, M., Cappa, C. D., Fan, J., Goldstein, A. H., Guenther, A. B., Jimenez, J. L., Kuang, C., Laskin, A., Martin, S. T., Ng, N. L., Petaja, T., Pierce, J. R., Rasch, P. J., Roldin, P., Seinfeld, J. H., Shilling, J., Smith, J. N., Thornton, J. A., Volkamer, R., Wang, J., Worsnop, D. R., Zaveri, R. A., Zelenyuk, A., and Zhang, Q.: Recent advances in understanding secondary organic aerosol: Implications for global climate forcing, Rev. Geophys., 55, 509–559, https://doi.org/10.1002/2016RG000540, 2017. a
Tabor, D. P., Gómez-Bombarelli, R., Tong, L., Gordon, R. G., Aziz, M. J., and Aspuru-Guzik, A.: Mapping the frontiers of quinone stability in aqueous media: implications for organic aqueous redox flow batteries, J. Mater. Chem. A, 7, 12833–12841, https://doi.org/10.1039/C9TA03219C, 2019. a
Tahami, S., Movagharnejad, K., and Ghasemitabar, H.: Estimation of the critical constants of organic compounds via a new group contribution method, Fluid Ph. Equilibria, 494, 45–60, https://doi.org/10.1016/j.fluid.2019.04.022, 2019. a
Tang, B., Kramer, S. T., Fang, M., Qiu, Y., Wu, Z., and Xu, D.: A self-attention based message passing neural network for predicting molecular lipophilicity and aqueous solubility, J. Cheminformatics, 12, 1–9, 2020. a
Ulrich, N., Goss, K.-U., and Ebert, A.: Exploring the octanol–water partition coefficient dataset using deep learning techniques and data augmentation, Commun. Chem., 4, 90, https://doi.org/10.1038/s42004-021-00528-9, 2021. a
Veličković, P., Cucurull, G., Casanova, A., Romero, A., Liò, P., and Bengio, Y.: Graph Attention Networks, arXiv [preprint], https://doi.org/10.48550/arxiv.1710.10903, 2017. a
von Lilienfeld, O. A. and Burke, K.: Retrospective on a decade of machine learning for chemical discovery, Nat. Commun., 11, https://doi.org/10.1038/s41467-020-18556-9, 2020. a, b
Wang, C., Yuan, T., Wood, S. A., Goss, K.-U., Li, J., Ying, Q., and Wania, F.: Uncertain Henry's law constants compromise equilibrium partitioning calculations of atmospheric oxidation products, Atmos. Chem. Phys., 17, 7529–7540, https://doi.org/10.5194/acp-17-7529-2017, 2017. a, b
Withnall, M., Lindelöf, E., Engkvist, O., and Chen, H.: Building attention and edge message passing neural networks for bioactivity and physical–chemical property prediction, J. Cheminformatics, 12, https://doi.org/10.1186/s13321-019-0407-y, 2020. a
Xiong, G., Wu, Z., Yi, J., Fu, L., Yang, Z., Hsieh, C., Yin, M., Zeng, X., Wu, C., Lu, A., Chen, X., Hou, T., and Cao, D.: ADMETlab 2.0: an integrated online platform for accurate and comprehensive predictions of ADMET properties, Nucleic Acids Research, 49, W5–W14, https://doi.org/10.1093/nar/gkab255, 2021. a
Zhang, S., Tong, H., Xu, J., and Maciejewski, R.: Graph convolutional networks: a comprehensive review, Comput. Soc. Netw., 6, 11, https://doi.org/10.1186/s40649-019-0069-y, 2019. a
Zhang, Y.-J., Khorshidi, A., Kastlunger, G., and Peterson, A. A.: The potential for machine learning in hybrid QM/MM calculations, J. Chem. Phys., 148, 241740, https://doi.org/10.1063/1.5029879, 2018. a
Short summary
This work uses machine learning to predict saturation vapor pressures of atmospherically-relevant organic compounds, crucial for partitioning of secondary organic aerosol (SOA). We introduce a new method using graph convolutional neural networks, in which molecular graphs enable the model to capture molecular connectivity better than with non-structural embeddings. The method shows strong agreement with experimentally determined vapor pressures, and outperforms existing estimation methods.
This work uses machine learning to predict saturation vapor pressures of...
