Articles | Volume 25, issue 10
https://doi.org/10.5194/acp-25-5331-2025
© 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-25-5331-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
28 May 2025
Research article |
| 28 May 2025
| 28 May 2025
How to trace the origins of short-lived atmospheric species: an Arctic example
Anderson Da Silva
CORRESPONDING AUTHOR
Laboratoire ATMosphères, Observations Spatiales (LATMOS), Sorbonne Université, UVSQ, CNRS, Paris, France
Louis Marelle
Laboratoire ATMosphères, Observations Spatiales (LATMOS), Sorbonne Université, UVSQ, CNRS, Paris, France
Jean-Christophe Raut
Laboratoire ATMosphères, Observations Spatiales (LATMOS), Sorbonne Université, UVSQ, CNRS, Paris, France
Yvette Gramlich
Center for Energy and Environmental Sciences, Paul Scherrer Institute, Villigen PSI, Switzerland
Karolina Siegel
Department of Environmental Science, Stockholm University, Stockholm, Sweden
Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
Sophie L. Haslett
Department of Environmental Science, Stockholm University, Stockholm, Sweden
Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
Claudia Mohr
Center for Energy and Environmental Sciences, Paul Scherrer Institute, Villigen PSI, Switzerland
Department of Environmental Systems Science, ETH Zurich, 8092 Zurich, Switzerland
Jennie L. Thomas
Institut des Géosciences de l'Environnement (IGE), Université Grenoble Alpes, CNRS, INRAE, IRD, Grenoble INP, Grenoble, France
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Ross C. Petersen, Thomas Holst, Cheng Wu, Radovan Krejci, Jeremy K. Chan, Claudia Mohr, and Janne Rinne
Atmos. Chem. Phys., 25, 17205–17236, https://doi.org/10.5194/acp-25-17205-2025, https://doi.org/10.5194/acp-25-17205-2025, 2025
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Ecosystem-scale emissions of biogenic volatile organic compounds (BVOCs) are important for atmospheric chemistry. Here we investigate boreal BVOC fluxes from a forest in central Sweden. BVOC fluxes were measured above-canopy using proton-transfer-reaction mass spectrometry, while compound-specific monoterpene (MT) fluxes were assessed using a concentration gradient method. We also evaluate the impact of chemical degradation on observed sesquiterpene (SQT) and nighttime MT fluxes.
Sean Clarke, Henry Holmstrand, Krishnakant Budhavant, Manoj Remani, Sophie Haslett, Katerina Rodiouchkina, Ellen Kooijman, and Örjan Gustafsson
EGUsphere, https://doi.org/10.5194/egusphere-2025-5334, https://doi.org/10.5194/egusphere-2025-5334, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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South Asia has the world's highest loadings of sulfate, scattering sunlight, altering clouds and masking greenhouse warming, yet there are large uncertainties regarding the relative contributions of natural and anthropogenic sources to the receptor atmosphere. Here we use δ34S isotopes to distinguish natural versus anthropogenic sulfate sources, revealing strong seasonal contrasts and quantifying the dominance of anthropogenic contributions.
Alfred W. Mayhew, Lauri Franzon, Kelvin H. Bates, Theo Kurtén, Felipe D. Lopez-Hilfiker, Claudia Mohr, Andrew R. Rickard, Joel A. Thornton, and Jessica D. Haskins
Atmos. Chem. Phys., 25, 17027–17046, https://doi.org/10.5194/acp-25-17027-2025, https://doi.org/10.5194/acp-25-17027-2025, 2025
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This work outlines an investigation into an understudied atmospheric chemical reaction pathway with the potential to form particulate pollution that has important impacts on air quality and climate. It suggests that this chemical pathway is responsible for a large fraction of the atmospheric particulate matter observed in tropical forested regions, but also highlights the need for further ambient and lab investigations to inform an accurate representation of this process in atmospheric models.
Almuth Neuberger, Rahul Ranjan, Hao Ding, Fredrik Mattsson, Lea Haberstock, Darrel Baumgardner, Stefano Decesari, Annica M. L. Ekman, Dagen D. Hughes, Claudia Mohr, Marco Paglione, Ilona Riipinen, Matteo Rinaldi, and Paul Zieger
EGUsphere, https://doi.org/10.5194/egusphere-2025-5419, https://doi.org/10.5194/egusphere-2025-5419, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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We studied how particles from air pollution that absorb water but do not yet form fog droplets influence fog and visibility in northern Italy’s Po Valley. Using detailed field observations and computer modeling, we found that these “hydrated” particles can explain many low-visibility events. Recognizing their role helps improve forecasts of fog, air quality, and climate effects in polluted regions.
Sneha Aggarwal, Priyanka Bansal, Yuwei Wang, Spiro Jorga, Gabrielle Macgregor, Urs Rohner, Thomas Bannan, Matthew Salter, Paul Zieger, Claudia Mohr, and Felipe Lopez-Hilfiker
Atmos. Meas. Tech., 18, 4227–4247, https://doi.org/10.5194/amt-18-4227-2025, https://doi.org/10.5194/amt-18-4227-2025, 2025
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Chemical ionization mass spectrometers used for trace gas analysis can be operated under various conditions, complicating quantitative comparisons. We evaluate sensitivity dependence on a relatively few key instrument parameters and show that when these are held constant, consistent performance is achieved. We show that the maximum sensitivity of a given flow tube reactor across various reagent ion chemistries is a constant, which aids in the quantification of compounds lacking analytical standards.
Tuomas Naakka, Daniel Köhler, Kalle Nordling, Petri Räisänen, Marianne Tronstad Lund, Risto Makkonen, Joonas Merikanto, Bjørn H. Samset, Victoria A. Sinclair, Jennie L. Thomas, and Annica M. L. Ekman
Atmos. Chem. Phys., 25, 8127–8145, https://doi.org/10.5194/acp-25-8127-2025, https://doi.org/10.5194/acp-25-8127-2025, 2025
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The effects of warmer sea surface temperatures and decreasing sea ice cover on polar climates have been studied using four climate models with identical prescribed changes in sea surface temperatures and sea ice cover. The models predict similar changes in air temperature and precipitation in the polar regions in a warmer climate with less sea ice. However, the models disagree on how the atmospheric circulation, i.e. the large-scale winds, will change with warmer temperatures and less sea ice.
Fredrik Mattsson, Almuth Neuberger, Liine Heikkinen, Yvette Gramlich, Marco Paglione, Matteo Rinaldi, Stefano Decesari, Paul Zieger, Ilona Riipinen, and Claudia Mohr
Atmos. Chem. Phys., 25, 7973–7989, https://doi.org/10.5194/acp-25-7973-2025, https://doi.org/10.5194/acp-25-7973-2025, 2025
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This study investigated aerosol–cloud interactions, focusing on organic nitrogen (ON) formation in the aqueous phase. Measurements were conducted in wintertime in the Po Valley, Italy, using aerosol mass spectrometry. The fog was enriched in more hygroscopic inorganic compounds and ON, containing, e.g., imidazoles. The formation of imidazole by aerosol–fog interactions could be confirmed for the first time in atmospheric observations. Findings highlight the role of fog in nitrogen aerosol formation.
Antonio Donateo, Gianluca Pappaccogli, Federico Scoto, Maurizio Busetto, Francesca Lucia Lovisco, Natalie Brett, Douglas Keller, Brice Barret, Elsa Dieudonné, Roman Pohorsky, Andrea Baccarini, Slimane Bekki, Jean-Christophe Raut, Julia Schmale, Kathy S. Law, Steve R. Arnold, Gilberto Javier Fochesatto, William R. Simpson, and Stefano Decesari
EGUsphere, https://doi.org/10.5194/egusphere-2025-1366, https://doi.org/10.5194/egusphere-2025-1366, 2025
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A study in Fairbanks, Alaska, measured winter aerosol fluxes on snow. Both emission and deposition occurred, with larger particles settling faster. Weather influenced dispersion and deposition, while wind-driven turbulence enhanced deposition despite stable conditions. Results show aerosol accumulation in snow impacts pollution and snowmelt. Findings help improve aerosol models and pollution studies in cold cities.
Delaney B. Kilgour, Christopher M. Jernigan, Olga Garmash, Sneha Aggarwal, Shengqian Zhou, Claudia Mohr, Matt E. Salter, Joel A. Thornton, Jian Wang, Paul Zieger, and Timothy H. Bertram
Atmos. Chem. Phys., 25, 1931–1947, https://doi.org/10.5194/acp-25-1931-2025, https://doi.org/10.5194/acp-25-1931-2025, 2025
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We report simultaneous measurements of dimethyl sulfide (DMS) and hydroperoxymethyl thioformate (HPMTF) in the eastern North Atlantic. We use an observationally constrained box model to show that cloud loss is the dominant sink of HPMTF in this region over 6 weeks, resulting in large reductions in DMS-derived products that contribute to aerosol formation and growth. Our findings indicate that fast cloud processing of HPMTF must be included in global models to accurately capture the sulfur cycle.
Natalie Brett, Kathy S. Law, Steve R. Arnold, Javier G. Fochesatto, Jean-Christophe Raut, Tatsuo Onishi, Robert Gilliam, Kathleen Fahey, Deanna Huff, George Pouliot, Brice Barret, Elsa Dieudonné, Roman Pohorsky, Julia Schmale, Andrea Baccarini, Slimane Bekki, Gianluca Pappaccogli, Federico Scoto, Stefano Decesari, Antonio Donateo, Meeta Cesler-Maloney, William Simpson, Patrice Medina, Barbara D'Anna, Brice Temime-Roussel, Joel Savarino, Sarah Albertin, Jingqiu Mao, Becky Alexander, Allison Moon, Peter F. DeCarlo, Vanessa Selimovic, Robert Yokelson, and Ellis S. Robinson
Atmos. Chem. Phys., 25, 1063–1104, https://doi.org/10.5194/acp-25-1063-2025, https://doi.org/10.5194/acp-25-1063-2025, 2025
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Processes influencing dispersion of local anthropogenic pollution in Arctic wintertime are investigated with Lagrangian dispersion modelling. Simulated power plant plume rise that considers temperature inversion layers improves results compared to observations (interior Alaska). Modelled surface concentrations are improved by representation of vertical mixing and emission estimates. Large increases in diesel vehicle emissions at temperatures reaching −35°C are required to reproduce observed NOx.
Léo Clauzel, Sandrine Anquetin, Christophe Lavaysse, Gilles Bergametti, Christel Bouet, Guillaume Siour, Rémy Lapere, Béatrice Marticorena, and Jennie Thomas
Atmos. Chem. Phys., 25, 997–1021, https://doi.org/10.5194/acp-25-997-2025, https://doi.org/10.5194/acp-25-997-2025, 2025
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Solar energy production in West Africa is set to rise and needs accurate solar radiation estimates which are affected by desert dust. This work analyses a March 2021 dust event using a modelling strategy incorporating desert dust. Results show that considering desert dust cuts errors in solar radiation estimates by 75 % and reduces surface solar radiation by 18 %. This highlights the importance of incorporating dust aerosols into solar forecasting for better accuracy.
Diego Aliaga, Victoria A. Sinclair, Radovan Krejci, Marcos Andrade, Paulo Artaxo, Luis Blacutt, Runlong Cai, Samara Carbone, Yvette Gramlich, Liine Heikkinen, Dominic Heslin-Rees, Wei Huang, Veli-Matti Kerminen, Alkuin Maximilian Koenig, Markku Kulmala, Paolo Laj, Valeria Mardoñez-Balderrama, Claudia Mohr, Isabel Moreno, Pauli Paasonen, Wiebke Scholz, Karine Sellegri, Laura Ticona, Gaëlle Uzu, Fernando Velarde, Alfred Wiedensohler, Doug Worsnop, Cheng Wu, Chen Xuemeng, Qiaozhi Zha, and Federico Bianchi
Aerosol Research, 3, 15–44, https://doi.org/10.5194/ar-3-15-2025, https://doi.org/10.5194/ar-3-15-2025, 2025
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This study examines new particle formation (NPF) in the Bolivian Andes at Chacaltaya mountain (CHC) and the urban El Alto–La Paz area (EAC). Days are clustered into four categories based on NPF intensity. Differences in particle size, precursor gases, and pollution levels are found. High NPF intensities increased Aitken mode particle concentrations at both sites, while volcanic influence selectively diminished NPF intensity at CHC but not EAC. This study highlights NPF dynamics in the Andes.
Rémy Lapere, Louis Marelle, Pierre Rampal, Laurent Brodeau, Christian Melsheimer, Gunnar Spreen, and Jennie L. Thomas
Atmos. Chem. Phys., 24, 12107–12132, https://doi.org/10.5194/acp-24-12107-2024, https://doi.org/10.5194/acp-24-12107-2024, 2024
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Elongated open-water areas in sea ice, called leads, can release marine aerosols into the atmosphere. In the Arctic, this source of atmospheric particles could play an important role for climate. However, the amount, seasonality and spatial distribution of such emissions are all mostly unknown. Here, we propose a first parameterization for sea spray aerosols emitted through leads in sea ice and quantify their impact on aerosol populations in the high Arctic.
Valeria Mardoñez-Balderrama, Griša Močnik, Marco Pandolfi, Robin L. Modini, Fernando Velarde, Laura Renzi, Angela Marinoni, Jean-Luc Jaffrezo, Isabel Moreno R., Diego Aliaga, Federico Bianchi, Claudia Mohr, Martin Gysel-Beer, Patrick Ginot, Radovan Krejci, Alfred Wiedensohler, Gaëlle Uzu, Marcos Andrade, and Paolo Laj
Atmos. Chem. Phys., 24, 12055–12077, https://doi.org/10.5194/acp-24-12055-2024, https://doi.org/10.5194/acp-24-12055-2024, 2024
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Levels of black carbon (BC) are scarcely reported in the Southern Hemisphere, especially in high-altitude conditions. This study provides insight into the concentration level, variability, and optical properties of BC in La Paz and El Alto and at the Chacaltaya Global Atmosphere Watch Station. Two methods of source apportionment of absorption were tested and compared showing traffic as the main contributor to absorption in the urban area, in addition to biomass and open waste burning.
Xiaoli Shen, David M. Bell, Hugh Coe, Naruki Hiranuma, Fabian Mahrt, Nicholas A. Marsden, Claudia Mohr, Daniel M. Murphy, Harald Saathoff, Johannes Schneider, Jacqueline Wilson, Maria A. Zawadowicz, Alla Zelenyuk, Paul J. DeMott, Ottmar Möhler, and Daniel J. Cziczo
Atmos. Chem. Phys., 24, 10869–10891, https://doi.org/10.5194/acp-24-10869-2024, https://doi.org/10.5194/acp-24-10869-2024, 2024
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Single-particle mass spectrometry (SPMS) is commonly used to measure the chemical composition and mixing state of aerosol particles. Intercomparison of SPMS instruments was conducted. All instruments reported similar size ranges and common spectral features. The instrument-specific detection efficiency was found to be more dependent on particle size than type. All differentiated secondary organic aerosol, soot, and soil dust but had difficulties differentiating among minerals and dusts.
Liine Heikkinen, Daniel G. Partridge, Sara Blichner, Wei Huang, Rahul Ranjan, Paul Bowen, Emanuele Tovazzi, Tuukka Petäjä, Claudia Mohr, and Ilona Riipinen
Atmos. Chem. Phys., 24, 5117–5147, https://doi.org/10.5194/acp-24-5117-2024, https://doi.org/10.5194/acp-24-5117-2024, 2024
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The organic vapor condensation with water vapor (co-condensation) in rising air below clouds is modeled in this work over the boreal forest because the forest air is rich in organic vapors. We show that the number of cloud droplets can increase by 20 % if considering co-condensation. The enhancements are even larger if the air contains many small, naturally produced aerosol particles. Such conditions are most frequently met in spring in the boreal forest.
Julia Maillard, Jean-Christophe Raut, and François Ravetta
Geosci. Model Dev., 17, 3303–3320, https://doi.org/10.5194/gmd-17-3303-2024, https://doi.org/10.5194/gmd-17-3303-2024, 2024
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Atmospheric models struggle to reproduce the strong temperature inversions in the vicinity of the surface over forested areas in the Arctic winter. In this paper, we develop modified simplified versions of surface layer schemes widely used by the community. Our modifications are used to correct the fact that original schemes place strong limits on the turbulent collapse, leading to a lower surface temperature gradient at low wind speeds. Modified versions show a better performance.
Wei Huang, Cheng Wu, Linyu Gao, Yvette Gramlich, Sophie L. Haslett, Joel Thornton, Felipe D. Lopez-Hilfiker, Ben H. Lee, Junwei Song, Harald Saathoff, Xiaoli Shen, Ramakrishna Ramisetty, Sachchida N. Tripathi, Dilip Ganguly, Feng Jiang, Magdalena Vallon, Siegfried Schobesberger, Taina Yli-Juuti, and Claudia Mohr
Atmos. Chem. Phys., 24, 2607–2624, https://doi.org/10.5194/acp-24-2607-2024, https://doi.org/10.5194/acp-24-2607-2024, 2024
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We present distinct molecular composition and volatility of oxygenated organic aerosol particles in different rural, urban, and mountain environments. We do a comprehensive investigation of the relationship between the chemical composition and volatility of oxygenated organic aerosol particles across different systems and environments. This study provides implications for volatility descriptions of oxygenated organic aerosol particles in different model frameworks.
Jing Cai, Juha Sulo, Yifang Gu, Sebastian Holm, Runlong Cai, Steven Thomas, Almuth Neuberger, Fredrik Mattsson, Marco Paglione, Stefano Decesari, Matteo Rinaldi, Rujing Yin, Diego Aliaga, Wei Huang, Yuanyuan Li, Yvette Gramlich, Giancarlo Ciarelli, Lauriane Quéléver, Nina Sarnela, Katrianne Lehtipalo, Nora Zannoni, Cheng Wu, Wei Nie, Juha Kangasluoma, Claudia Mohr, Markku Kulmala, Qiaozhi Zha, Dominik Stolzenburg, and Federico Bianchi
Atmos. Chem. Phys., 24, 2423–2441, https://doi.org/10.5194/acp-24-2423-2024, https://doi.org/10.5194/acp-24-2423-2024, 2024
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By combining field measurements, simulations and recent chamber experiments, we investigate new particle formation (NPF) and growth in the Po Valley, where both haze and frequent NPF occur. Our results show that sulfuric acid, ammonia and amines are the dominant NPF precursors there. A high NPF rate and a lower condensation sink lead to a greater survival probability for newly formed particles, highlighting the importance of gas-to-particle conversion for aerosol concentrations.
Arto Heitto, Cheng Wu, Diego Aliaga, Luis Blacutt, Xuemeng Chen, Yvette Gramlich, Liine Heikkinen, Wei Huang, Radovan Krejci, Paolo Laj, Isabel Moreno, Karine Sellegri, Fernando Velarde, Kay Weinhold, Alfred Wiedensohler, Qiaozhi Zha, Federico Bianchi, Marcos Andrade, Kari E. J. Lehtinen, Claudia Mohr, and Taina Yli-Juuti
Atmos. Chem. Phys., 24, 1315–1328, https://doi.org/10.5194/acp-24-1315-2024, https://doi.org/10.5194/acp-24-1315-2024, 2024
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Particle growth at the Chacaltaya station in Bolivia was simulated based on measured vapor concentrations and ambient conditions. Major contributors to the simulated growth were low-volatility organic compounds (LVOCs). Also, sulfuric acid had major role when volcanic activity was occurring in the area. This study provides insight on nanoparticle growth at this high-altitude Southern Hemispheric site and hence contributes to building knowledge of early growth of atmospheric particles.
Victoria A. Flood, Kimberly Strong, Cynthia H. Whaley, Kaley A. Walker, Thomas Blumenstock, James W. Hannigan, Johan Mellqvist, Justus Notholt, Mathias Palm, Amelie N. Röhling, Stephen Arnold, Stephen Beagley, Rong-You Chien, Jesper Christensen, Makoto Deushi, Srdjan Dobricic, Xinyi Dong, Joshua S. Fu, Michael Gauss, Wanmin Gong, Joakim Langner, Kathy S. Law, Louis Marelle, Tatsuo Onishi, Naga Oshima, David A. Plummer, Luca Pozzoli, Jean-Christophe Raut, Manu A. Thomas, Svetlana Tsyro, and Steven Turnock
Atmos. Chem. Phys., 24, 1079–1118, https://doi.org/10.5194/acp-24-1079-2024, https://doi.org/10.5194/acp-24-1079-2024, 2024
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It is important to understand the composition of the Arctic atmosphere and how it is changing. Atmospheric models provide simulations that can inform policy. This study examines simulations of CH4, CO, and O3 by 11 models. Model performance is assessed by comparing results matched in space and time to measurements from five high-latitude ground-based infrared spectrometers. This work finds that models generally underpredict the concentrations of these gases in the Arctic troposphere.
Meeta Cesler-Maloney, William Simpson, Jonas Kuhn, Jochen Stutz, Jennie Thomas, Tjarda Roberts, Deanna Huff, and Sol Cooperdock
EGUsphere, https://doi.org/10.5194/egusphere-2023-3082, https://doi.org/10.5194/egusphere-2023-3082, 2024
Preprint archived
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We used a one-dimensional model to simulate how pollution in Fairbanks, Alaska, accumulates in shallow layers near the ground when temperature inversions are present. We find pollution accumulates in a 20 m to 50 m thick layer. The model agrees with observations of SO2 pollution using only home heating emissions sources, which shows that ground-based sources dominate sulfur pollution in downtown Fairbanks. Air residence times in downtown are only a few hours, limiting chemical transformations.
Patrick Chazette and Jean-Christophe Raut
Atmos. Meas. Tech., 16, 5847–5861, https://doi.org/10.5194/amt-16-5847-2023, https://doi.org/10.5194/amt-16-5847-2023, 2023
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The vertical profiles of the effective radii of ice crystals and ice water content in Arctic semi-transparent stratiform clouds were assessed using quantitative ground-based lidar measurements. The field campaign was part of the Pollution in the ARCtic System (PARCS) project which took place from 13 to 26 May 2016 in Hammerfest (70° 39′ 48″ N, 23° 41′ 00″ E). We show that under certain cloud conditions, lidar measurement combined with a dedicated algorithmic approach is an efficient tool.
Leonard Kirago, Örjan Gustafsson, Samuel Mwaniki Gaita, Sophie L. Haslett, Michael J. Gatari, Maria Elena Popa, Thomas Röckmann, Christoph Zellweger, Martin Steinbacher, Jörg Klausen, Christian Félix, David Njiru, and August Andersson
Atmos. Chem. Phys., 23, 14349–14357, https://doi.org/10.5194/acp-23-14349-2023, https://doi.org/10.5194/acp-23-14349-2023, 2023
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This study provides ground-observational evidence that supports earlier suggestions that savanna fires are the main emitters and modulators of carbon monoxide gas in Africa. Using isotope-based techniques, the study has shown that about two-thirds of this gas is emitted from savanna fires, while for urban areas, in this case Nairobi, primary sources approach 100 %. The latter has implications for air quality policy, suggesting primary emissions such as traffic should be targeted.
Sophie L. Haslett, David M. Bell, Varun Kumar, Jay G. Slowik, Dongyu S. Wang, Suneeti Mishra, Neeraj Rastogi, Atinderpal Singh, Dilip Ganguly, Joel Thornton, Feixue Zheng, Yuanyuan Li, Wei Nie, Yongchun Liu, Wei Ma, Chao Yan, Markku Kulmala, Kaspar R. Daellenbach, David Hadden, Urs Baltensperger, Andre S. H. Prevot, Sachchida N. Tripathi, and Claudia Mohr
Atmos. Chem. Phys., 23, 9023–9036, https://doi.org/10.5194/acp-23-9023-2023, https://doi.org/10.5194/acp-23-9023-2023, 2023
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In Delhi, some aspects of daytime and nighttime atmospheric chemistry are inverted, and parodoxically, vehicle emissions may be limiting other forms of particle production. This is because the nighttime emissions of nitrogen oxide (NO) by traffic and biomass burning prevent some chemical processes that would otherwise create even more particles and worsen the urban haze.
Karolina Siegel, Yvette Gramlich, Sophie L. Haslett, Gabriel Freitas, Radovan Krejci, Paul Zieger, and Claudia Mohr
Atmos. Chem. Phys., 23, 7569–7587, https://doi.org/10.5194/acp-23-7569-2023, https://doi.org/10.5194/acp-23-7569-2023, 2023
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Hydroperoxymethyl thioformate (HPMTF) is a recently discovered oxidation product of dimethyl sulfide (DMS). We present a full year of concurrent gas- and particle-phase observations of HPMTF and other DMS oxidation products from the Arctic. We did not observe significant amounts of HPMTF in the particle phase but a good agreement between gas-phase HMPTF and methanesulfonic acid in the summer. Our study provides information about the relationship between HPMTF and other DMS oxidation products.
Emelie L. Graham, Cheng Wu, David M. Bell, Amelie Bertrand, Sophie L. Haslett, Urs Baltensperger, Imad El Haddad, Radovan Krejci, Ilona Riipinen, and Claudia Mohr
Atmos. Chem. Phys., 23, 7347–7362, https://doi.org/10.5194/acp-23-7347-2023, https://doi.org/10.5194/acp-23-7347-2023, 2023
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The volatility of an aerosol particle is an important parameter for describing its atmospheric lifetime. We studied the volatility of secondary organic aerosols from nitrate-initiated oxidation of three biogenic precursors with experimental methods and model simulations. We saw higher volatility than for the corresponding ozone system, and our simulations produced variable results with different parameterizations which warrant a re-evaluation of the treatment of the nitrate functional group.
Yvette Gramlich, Karolina Siegel, Sophie L. Haslett, Gabriel Freitas, Radovan Krejci, Paul Zieger, and Claudia Mohr
Atmos. Chem. Phys., 23, 6813–6834, https://doi.org/10.5194/acp-23-6813-2023, https://doi.org/10.5194/acp-23-6813-2023, 2023
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In this study, we investigate the chemical composition of aerosol particles forming clouds in the Arctic. During year-long observations at a mountain site on Svalbard, we find a large contribution of naturally derived aerosol particles in the fraction forming clouds in the summer. Our observations indicate that most aerosol particles can serve as cloud seeds in this remote environment.
Eleftherios Ioannidis, Kathy S. Law, Jean-Christophe Raut, Louis Marelle, Tatsuo Onishi, Rachel M. Kirpes, Lucia M. Upchurch, Thomas Tuch, Alfred Wiedensohler, Andreas Massling, Henrik Skov, Patricia K. Quinn, and Kerri A. Pratt
Atmos. Chem. Phys., 23, 5641–5678, https://doi.org/10.5194/acp-23-5641-2023, https://doi.org/10.5194/acp-23-5641-2023, 2023
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Remote and local anthropogenic emissions contribute to wintertime Arctic haze, with enhanced aerosol concentrations, but natural sources, which also contribute, are less well studied. Here, modelled wintertime sea-spray aerosols are improved in WRF-Chem over the wider Arctic by including updated wind speed and temperature-dependent treatments. As a result, anthropogenic nitrate aerosols are also improved. Open leads are confirmed to be the main source of sea-spray aerosols over northern Alaska.
Qiaozhi Zha, Wei Huang, Diego Aliaga, Otso Peräkylä, Liine Heikkinen, Alkuin Maximilian Koenig, Cheng Wu, Joonas Enroth, Yvette Gramlich, Jing Cai, Samara Carbone, Armin Hansel, Tuukka Petäjä, Markku Kulmala, Douglas Worsnop, Victoria Sinclair, Radovan Krejci, Marcos Andrade, Claudia Mohr, and Federico Bianchi
Atmos. Chem. Phys., 23, 4559–4576, https://doi.org/10.5194/acp-23-4559-2023, https://doi.org/10.5194/acp-23-4559-2023, 2023
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We investigate the chemical composition of atmospheric cluster ions from January to May 2018 at the high-altitude research station Chacaltaya (5240 m a.s.l.) in the Bolivian Andes. With state-of-the-art mass spectrometers and air mass history analysis, the measured cluster ions exhibited distinct diurnal and seasonal patterns, some of which contributed to new particle formation. Our study will improve the understanding of atmospheric ions and their role in high-altitude new particle formation.
Jing Cai, Kaspar R. Daellenbach, Cheng Wu, Yan Zheng, Feixue Zheng, Wei Du, Sophie L. Haslett, Qi Chen, Markku Kulmala, and Claudia Mohr
Atmos. Meas. Tech., 16, 1147–1165, https://doi.org/10.5194/amt-16-1147-2023, https://doi.org/10.5194/amt-16-1147-2023, 2023
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We introduce the offline application of FIGAERO-CIMS by analyzing Teflon and quartz filter samples that were collected at a typical urban site in Beijing with the deposition time varying from 30 min to 24 h. This method provides a feasible, simple, and quantitative way to investigate the molecular composition and volatility of OA compounds by using FIGAERO-CIMS to analyze offline samples.
Wiebke Scholz, Jiali Shen, Diego Aliaga, Cheng Wu, Samara Carbone, Isabel Moreno, Qiaozhi Zha, Wei Huang, Liine Heikkinen, Jean Luc Jaffrezo, Gaelle Uzu, Eva Partoll, Markus Leiminger, Fernando Velarde, Paolo Laj, Patrick Ginot, Paolo Artaxo, Alfred Wiedensohler, Markku Kulmala, Claudia Mohr, Marcos Andrade, Victoria Sinclair, Federico Bianchi, and Armin Hansel
Atmos. Chem. Phys., 23, 895–920, https://doi.org/10.5194/acp-23-895-2023, https://doi.org/10.5194/acp-23-895-2023, 2023
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Dimethyl sulfide (DMS), emitted from the ocean, is the most abundant biogenic sulfur emission into the atmosphere. OH radicals, among others, can oxidize DMS to sulfuric and methanesulfonic acid, which are relevant for aerosol formation. We quantified DMS and nearly all DMS oxidation products with novel mass spectrometric instruments for gas and particle phase at the high mountain station Chacaltaya (5240 m a.s.l.) in the Bolivian Andes in free tropospheric air after long-range transport.
Cynthia H. Whaley, Kathy S. Law, Jens Liengaard Hjorth, Henrik Skov, Stephen R. Arnold, Joakim Langner, Jakob Boyd Pernov, Garance Bergeron, Ilann Bourgeois, Jesper H. Christensen, Rong-You Chien, Makoto Deushi, Xinyi Dong, Peter Effertz, Gregory Faluvegi, Mark Flanner, Joshua S. Fu, Michael Gauss, Greg Huey, Ulas Im, Rigel Kivi, Louis Marelle, Tatsuo Onishi, Naga Oshima, Irina Petropavlovskikh, Jeff Peischl, David A. Plummer, Luca Pozzoli, Jean-Christophe Raut, Tom Ryerson, Ragnhild Skeie, Sverre Solberg, Manu A. Thomas, Chelsea Thompson, Kostas Tsigaridis, Svetlana Tsyro, Steven T. Turnock, Knut von Salzen, and David W. Tarasick
Atmos. Chem. Phys., 23, 637–661, https://doi.org/10.5194/acp-23-637-2023, https://doi.org/10.5194/acp-23-637-2023, 2023
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This study summarizes recent research on ozone in the Arctic, a sensitive and rapidly warming region. We find that the seasonal cycles of near-surface atmospheric ozone are variable depending on whether they are near the coast, inland, or at high altitude. Several global model simulations were evaluated, and we found that because models lack some of the ozone chemistry that is important for the coastal Arctic locations, they do not accurately simulate ozone there.
William F. Swanson, Chris D. Holmes, William R. Simpson, Kaitlyn Confer, Louis Marelle, Jennie L. Thomas, Lyatt Jaeglé, Becky Alexander, Shuting Zhai, Qianjie Chen, Xuan Wang, and Tomás Sherwen
Atmos. Chem. Phys., 22, 14467–14488, https://doi.org/10.5194/acp-22-14467-2022, https://doi.org/10.5194/acp-22-14467-2022, 2022
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Radical bromine molecules are seen at higher concentrations during the Arctic spring. We use the global model GEOS-Chem to test whether snowpack and wind-blown snow sources can explain high bromine concentrations. We run this model for the entire year of 2015 and compare results to observations of bromine from floating platforms on the Arctic Ocean and at Utqiaġvik. We find that the model performs best when both sources are enabled but may overestimate bromine production in summer and fall.
David M. Bell, Cheng Wu, Amelie Bertrand, Emelie Graham, Janne Schoonbaert, Stamatios Giannoukos, Urs Baltensperger, Andre S. H. Prevot, Ilona Riipinen, Imad El Haddad, and Claudia Mohr
Atmos. Chem. Phys., 22, 13167–13182, https://doi.org/10.5194/acp-22-13167-2022, https://doi.org/10.5194/acp-22-13167-2022, 2022
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A series of studies designed to investigate the evolution of organic aerosol were performed in an atmospheric simulation chamber, using a common oxidant found at night (NO3). The chemical composition steadily changed from its initial composition via different chemical reactions that were taking place inside of the aerosol particle. These results show that the composition of organic aerosol steadily changes during its lifetime in the atmosphere.
Varun Kumar, Stamatios Giannoukos, Sophie L. Haslett, Yandong Tong, Atinderpal Singh, Amelie Bertrand, Chuan Ping Lee, Dongyu S. Wang, Deepika Bhattu, Giulia Stefenelli, Jay S. Dave, Joseph V. Puthussery, Lu Qi, Pawan Vats, Pragati Rai, Roberto Casotto, Rangu Satish, Suneeti Mishra, Veronika Pospisilova, Claudia Mohr, David M. Bell, Dilip Ganguly, Vishal Verma, Neeraj Rastogi, Urs Baltensperger, Sachchida N. Tripathi, André S. H. Prévôt, and Jay G. Slowik
Atmos. Chem. Phys., 22, 7739–7761, https://doi.org/10.5194/acp-22-7739-2022, https://doi.org/10.5194/acp-22-7739-2022, 2022
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Here we present source apportionment results from the first field deployment in Delhi of an extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF). The EESI-TOF is a recently developed instrument capable of providing uniquely detailed online chemical characterization of organic aerosol (OA), in particular the secondary OA (SOA) fraction. Here, we are able to apportion not only primary OA but also SOA to specific sources, which is performed for the first time in Delhi.
Linyu Gao, Junwei Song, Claudia Mohr, Wei Huang, Magdalena Vallon, Feng Jiang, Thomas Leisner, and Harald Saathoff
Atmos. Chem. Phys., 22, 6001–6020, https://doi.org/10.5194/acp-22-6001-2022, https://doi.org/10.5194/acp-22-6001-2022, 2022
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We study secondary organic aerosol (SOA) from β-caryophyllene (BCP) ozonolysis with and without nitrogen oxides over 213–313 K in the simulation chamber. The yields and the rate constants were determined at 243–313 K. Chemical compositions varied at different temperatures, indicating a strong impact on the BCP ozonolysis pathways. This work helps to better understand the SOA from BCP ozonolysis for conditions representative of the real atmosphere from the boundary layer to the upper troposphere.
Cynthia H. Whaley, Rashed Mahmood, Knut von Salzen, Barbara Winter, Sabine Eckhardt, Stephen Arnold, Stephen Beagley, Silvia Becagli, Rong-You Chien, Jesper Christensen, Sujay Manish Damani, Xinyi Dong, Konstantinos Eleftheriadis, Nikolaos Evangeliou, Gregory Faluvegi, Mark Flanner, Joshua S. Fu, Michael Gauss, Fabio Giardi, Wanmin Gong, Jens Liengaard Hjorth, Lin Huang, Ulas Im, Yugo Kanaya, Srinath Krishnan, Zbigniew Klimont, Thomas Kühn, Joakim Langner, Kathy S. Law, Louis Marelle, Andreas Massling, Dirk Olivié, Tatsuo Onishi, Naga Oshima, Yiran Peng, David A. Plummer, Olga Popovicheva, Luca Pozzoli, Jean-Christophe Raut, Maria Sand, Laura N. Saunders, Julia Schmale, Sangeeta Sharma, Ragnhild Bieltvedt Skeie, Henrik Skov, Fumikazu Taketani, Manu A. Thomas, Rita Traversi, Kostas Tsigaridis, Svetlana Tsyro, Steven Turnock, Vito Vitale, Kaley A. Walker, Minqi Wang, Duncan Watson-Parris, and Tahya Weiss-Gibbons
Atmos. Chem. Phys., 22, 5775–5828, https://doi.org/10.5194/acp-22-5775-2022, https://doi.org/10.5194/acp-22-5775-2022, 2022
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Air pollutants, like ozone and soot, play a role in both global warming and air quality. Atmospheric models are often used to provide information to policy makers about current and future conditions under different emissions scenarios. In order to have confidence in those simulations, in this study we compare simulated air pollution from 18 state-of-the-art atmospheric models to measured air pollution in order to assess how well the models perform.
Haiyan Li, Thomas Golin Almeida, Yuanyuan Luo, Jian Zhao, Brett B. Palm, Christopher D. Daub, Wei Huang, Claudia Mohr, Jordan E. Krechmer, Theo Kurtén, and Mikael Ehn
Atmos. Meas. Tech., 15, 1811–1827, https://doi.org/10.5194/amt-15-1811-2022, https://doi.org/10.5194/amt-15-1811-2022, 2022
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This work evaluated the potential for PTR-based mass spectrometers to detect ROOR and ROOH peroxides both experimentally and through computations. Laboratory experiments using a Vocus PTR observed only noisy signals of potential dimers during α-pinene ozonolysis and a few small signals of dimeric compounds during cyclohexene ozonolysis. Quantum chemical calculations for model ROOR and ROOH systems showed that most of these peroxides should fragment partially following protonation.
Jing Cai, Cheng Wu, Jiandong Wang, Wei Du, Feixue Zheng, Simo Hakala, Xiaolong Fan, Biwu Chu, Lei Yao, Zemin Feng, Yongchun Liu, Yele Sun, Jun Zheng, Chao Yan, Federico Bianchi, Markku Kulmala, Claudia Mohr, and Kaspar R. Daellenbach
Atmos. Chem. Phys., 22, 1251–1269, https://doi.org/10.5194/acp-22-1251-2022, https://doi.org/10.5194/acp-22-1251-2022, 2022
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This study investigates the connection between organic aerosol (OA) molecular composition and particle absorptive properties in autumn in Beijing. We find that the molecular properties of OA compounds in different episodes influence particle light absorption properties differently: the light absorption enhancement of black carbon and light absorption coefficient of brown carbon were mostly related to more oxygenated OA (low C number and four O atoms) and aromatics/nitro-aromatics, respectively.
Lilian Loyer, Jean-Christophe Raut, Claudia Di Biagio, Julia Maillard, Vincent Mariage, and Jacques Pelon
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-326, https://doi.org/10.5194/amt-2021-326, 2021
Revised manuscript not accepted
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The Arctic is facing drastic climate changes, and more observations are needed to better understand what is happening. Unfortunately observations are limited in the High Arctic. To obtain more observations, multiples buoys equipped with lidar, have been deployed in this region. This paper presents an approach to estimate the optical properties of clouds, and solar plus terrestrial energies from lidar measurements in the Arctic.
Cheng Wu, David M. Bell, Emelie L. Graham, Sophie Haslett, Ilona Riipinen, Urs Baltensperger, Amelie Bertrand, Stamatios Giannoukos, Janne Schoonbaert, Imad El Haddad, Andre S. H. Prevot, Wei Huang, and Claudia Mohr
Atmos. Chem. Phys., 21, 14907–14925, https://doi.org/10.5194/acp-21-14907-2021, https://doi.org/10.5194/acp-21-14907-2021, 2021
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Night-time reactions of biogenic volatile organic compounds and nitrate radicals can lead to the formation of secondary organic aerosol (BSOANO3). Here, we study the impacts of light exposure on the BSOANO3 from three biogenic precursors. Our results suggest that photolysis causes photodegradation of a substantial fraction of BSOANO3, changes the chemical composition and bulk volatility, and might be a potentially important loss pathway of BSOANO3 during the night-to-day transition.
Julia Maillard, François Ravetta, Jean-Christophe Raut, Vincent Mariage, and Jacques Pelon
Atmos. Chem. Phys., 21, 4079–4101, https://doi.org/10.5194/acp-21-4079-2021, https://doi.org/10.5194/acp-21-4079-2021, 2021
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Clouds remain a major source of uncertainty in understanding the Arctic climate, due in part to the lack of measurements over the sea ice. In this paper, we exploit a series of lidar profiles acquired from autonomous drifting buoys deployed in the Arctic Ocean and derive a statistic of low cloud frequency and macrophysical properties. We also show that clouds contribute to warm the surface in the shoulder seasons but not significantly from May to September.
Cited articles
Allen, S., Allen, D., Baladima, F., Phoenix, V. R., Thomas, J. L., Le Roux, G., and Sonke, J. E.: Evidence of free tropospheric and long-range transport of microplastic at Pic du Midi Observatory, Nat. Commun., 12, 7242, https://doi.org/10.1038/s41467-021-27454-7, 2021. a, b
An, X., Yao, B., Li, Y., Li, N., and Zhou, L.: Tracking source area of Shangdianzi station using Lagrangian particle dispersion model of FLEXPART, Meteorol. Appl., 21, 466–473, https://doi.org/10.1002/met.1358, 2014. a
Ashbaugh, L. L.: A Statistical Trajectory Technique for Determining Air Pollution Source Regions, J. Air. Waste Manage., 33, 1096–1098, https://doi.org/10.1080/00022470.1983.10465702, 1983. a
Ashbaugh, L. L., Malm, W. C., and Sadeh, W. Z.: A residence time probability analysis of sulfur concentrations at grand Canyon National Park, Atmos. Environ., 19, 1263–1270, https://doi.org/10.1016/0004-6981(85)90256-2, 1985. a, b
Bond, T. C., Doherty, S. J., Fahey, D. W., Forster, P. M., Berntsen, T., DeAngelo, B. J., Flanner, M. G., Ghan, S., Kärcher, B., Koch, D., Kinne, S., Kondo, Y., Quinn, P. K., Sarofim, M. C., Schultz, M. G., Schulz, M., Venkataraman, C., Zhang, H., Zhang, S., Bellouin, N., Guttikunda, S. K., Hopke, P. K., Jacobson, M. Z., Kaiser, J. W., Klimont, Z., Lohmann, U., Schwarz, J. P., Shindell, D., Storelvmo, T., Warren, S. G., and Zender, C. S.: Bounding the role of black carbon in the climate system: A scientific assessment, J. Geophys. Res.-Atmos., 118, 5380–5552, https://doi.org/10.1002/jgrd.50171, 2013. a, b
Brioude, J., Arnold, D., Stohl, A., Cassiani, M., Morton, D., Seibert, P., Angevine, W., Evan, S., Dingwell, A., Fast, J. D., Easter, R. C., Pisso, I., Burkhart, J., and Wotawa, G.: The Lagrangian particle dispersion model FLEXPART-WRF version 3.1, Geosci. Model Dev., 6, 1889–1904, https://doi.org/10.5194/gmd-6-1889-2013, 2013. a
Bronselaer, B., Winton, M., Griffies, S. M., Hurlin, W. J., Rodgers, K. B., Sergienko, O. V., Stouffer, R. J., and Russell, J. L.: Change in future climate due to Antarctic meltwater, Nature, 564, 53–58, https://doi.org/10.1038/s41586-018-0712-z, 2018. a
Brunner, D., Henne, S., Keller, C. A., Vollmer, M. K., Reimann, S., and Buchmann, B.: Estimating European Halocarbon Emissions Using Lagrangian Backward Transport Modeling and in Situ Measurements at the Jungfraujoch High-Alpine Site, in: Lagrangian Modeling of the Atmosphere, American Geophysical Union (AGU), 207–222, ISBN 978-1-118-70457-8, https://doi.org/10.1029/2012GM001258, 2012. a
Burrows, S. M., Hoose, C., Pöschl, U., and Lawrence, M. G.: Ice nuclei in marine air: biogenic particles or dust?, Atmos. Chem. Phys., 13, 245–267, https://doi.org/10.5194/acp-13-245-2013, 2013. a
Carslaw, K. S., Lee, L. A., Reddington, C. L., Pringle, K. J., Rap, A., Forster, P. M., Mann, G. W., Spracklen, D. V., Woodhouse, M. T., Regayre, L. A., and Pierce, J. R.: Large contribution of natural aerosols to uncertainty in indirect forcing, Nature, 503, 67–71, https://doi.org/10.1038/nature12674, 2013. a
Cassiani, M., Stohl, A., Olivié, D., Seland, Ø., Bethke, I., Pisso, I., and Iversen, T.: The offline Lagrangian particle model FLEXPART–NorESM/CAM (v1): model description and comparisons with the online NorESM transport scheme and with the reference FLEXPART model, Geosci. Model Dev., 9, 4029–4048, https://doi.org/10.5194/gmd-9-4029-2016, 2016. a
Da Silva, A.: Origin detection tools for atmospheric species: FLEXPART-WRF post-processing scripts for the Ratio Method, Zenodo [code], https://doi.org/10.5281/zenodo.13902693, 2024. a
Dubovik, O., Lapyonok, T., Kaufman, Y. J., Chin, M., Ginoux, P., Kahn, R. A., and Sinyuk, A.: Retrieving global aerosol sources from satellites using inverse modeling, Atmos. Chem. Phys., 8, 209–250, https://doi.org/10.5194/acp-8-209-2008, 2008. a
Eker, E.: Phytoplankton distribution in the Caspian Sea during March 2001, Hydrobiologia, https://www.academia.edu/4864147/Phytoplankton_distribution_in_the_Caspian_Sea_during_March_2001 (last access: 13 June 2024), 2005. a
Fang, X., Stohl, A., Yokouchi, Y., Kim, J., Li, S., Saito, T., Park, S., and Hu, J.: Multiannual Top-Down Estimate of HFC-23 Emissions in East Asia, Environ. Sci. Technol., 49, 4345–4353, https://doi.org/10.1021/es505669j, 2015. a
Fang, X., Saito, T., Park, S., Li, S., Yokouchi, Y., and Prinn, R. G.: Performance of Back-Trajectory Statistical Methods and Inverse Modeling Method in Locating Emission Sources, ACS Earth and Space Chemistry, 2, 843–851, https://doi.org/10.1021/acsearthspacechem.8b00062, 2018. a, b
Farmer, D. K., Boedicker, E. K., and DeBolt, H. M.: Dry Deposition of Atmospheric Aerosols: Approaches, Observations, and Mechanisms, Annu. Rev. Phys. Chem., 72, 375–397, https://doi.org/10.1146/annurev-physchem-090519-034936, 2021. a
Freitas, G. P., Stolle, C., Kaye, P. H., Stanley, W., Herlemann, D. P. R., Salter, M. E., and Zieger, P.: Emission of primary bioaerosol particles from Baltic seawater, Environmental Science: Atmospheres, 2, 1170–1182, https://doi.org/10.1039/D2EA00047D, publisher: RSC, 2022. a
Ginoux, P., Chin, M., Tegen, I., Prospero, J. M., Holben, B., Dubovik, O., and Lin, S.-J.: Sources and distributions of dust aerosols simulated with the GOCART model, J. Geophys. Res.-Atmos., 106, 20255–20273, https://doi.org/10.1029/2000JD000053, 2001. a
Gong, X., Zhang, J., Croft, B., Yang, X., Frey, M. M., Bergner, N., Chang, R. Y.-W., Creamean, J. M., Kuang, C., Martin, R. V., Ranjithkumar, A., Sedlacek, A. J., Uin, J., Willmes, S., Zawadowicz, M. A., Pierce, J. R., Shupe, M. D., Schmale, J., and Wang, J.: Arctic warming by abundant fine sea salt aerosols from blowing snow, Nat. Geosci., 16, 768–774, https://doi.org/10.1038/s41561-023-01254-8, 2023. a
Grell, G. A. and Dévényi, D.: A generalized approach to parameterizing convection combining ensemble and data assimilation techniques, Geophys. Res. Lett., 29, 38–1–38–4, https://doi.org/10.1029/2002GL015311, 2002. a
Grell, G. A., Peckham, S. E., Schmitz, R., McKeen, S. A., Frost, G., Skamarock, W. C., and Eder, B.: Fully coupled “online” chemistry within the WRF model, Atmos. Environ., 39, 6957–6975, https://doi.org/10.1016/j.atmosenv.2005.04.027, 2005. a
Hartmann, M., Adachi, K., Eppers, O., Haas, C., Herber, A., Holzinger, R., Hünerbein, A., Jäkel, E., Jentzsch, C., van Pinxteren, M., Wex, H., Willmes, S., and Stratmann, F.: Wintertime Airborne Measurements of Ice Nucleating Particles in the High Arctic: A Hint to a Marine, Biogenic Source for Ice Nucleating Particles, Geophys. Res. Lett., 47, e2020GL087770, https://doi.org/10.1029/2020GL087770, 2020. a
Hartmann, M., Gong, X., Kecorius, S., van Pinxteren, M., Vogl, T., Welti, A., Wex, H., Zeppenfeld, S., Herrmann, H., Wiedensohler, A., and Stratmann, F.: Terrestrial or marine – indications towards the origin of ice-nucleating particles during melt season in the European Arctic up to 83.7° N, Atmos. Chem. Phys., 21, 11613–11636, https://doi.org/10.5194/acp-21-11613-2021, 2021. a, b, c
Hegarty, J., Draxler, R. R., Stein, A. F., Brioude, J., Mountain, M., Eluszkiewicz, J., Nehrkorn, T., Ngan, F., and Andrews, A.: Evaluation of Lagrangian Particle Dispersion Models with Measurements from Controlled Tracer Releases, J. Appl. Meteorol. Clim., 52, 2623–2637, https://doi.org/10.1175/JAMC-D-13-0125.1, 2013. a
Heutte, B., Bergner, N., Angot, H., Pernov, J. B., Dada, L., Mirrielees, J. A., Beck, I., Baccarini, A., Boyer, M., Creamean, J. M., Daellenbach, K. R., El Haddad, I., Frey, M. M., Henning, S., Laurila, T., Moschos, V., Petäjä, T., Pratt, K. A., Quéléver, L. L. J., Shupe, M. D., Zieger, P., Jokinen, T., and Schmale, J.: Observations of high-time-resolution and size-resolved aerosol chemical composition and microphysics in the central Arctic: implications for climate-relevant particle properties, Atmos. Chem. Phys., 25, 2207–2241, https://doi.org/10.5194/acp-25-2207-2025, 2025. a
Hirdman, D., Aspmo, K., Burkhart, J. F., Eckhardt, S., Sodemann, H., and Stohl, A.: Transport of mercury in the Arctic atmosphere: Evidence for a spring-time net sink and summer-time source, Geophys. Res. Lett., 36, L12814, https://doi.org/10.1029/2009GL038345, 2009. a, b
Hirdman, D., Sodemann, H., Eckhardt, S., Burkhart, J. F., Jefferson, A., Mefford, T., Quinn, P. K., Sharma, S., Ström, J., and Stohl, A.: Source identification of short-lived air pollutants in the Arctic using statistical analysis of measurement data and particle dispersion model output, Atmos. Chem. Phys., 10, 669–693, https://doi.org/10.5194/acp-10-669-2010, 2010. a, b, c, d, e, f, g
Hopkins, F. E., Archer, S. D., Bell, T. G., Suntharalingam, P., and Todd, J. D.: The biogeochemistry of marine dimethylsulfide, Nature Reviews Earth & Environment, 4, 361–376, https://doi.org/10.1038/s43017-023-00428-7, 2023. a
Hoyer, S. and Hamman, J.: xarray: N-D labeled Arrays and Datasets in Python, Journal of Open Research Software, 5, 10, https://doi.org/10.5334/jors.148, 2017. a
Hsu, Y.-K., Holsen, T. M., and Hopke, P. K.: Comparison of hybrid receptor models to locate PCB sources in Chicago, Atmos. Environ., 37, 545–562, https://doi.org/10.1016/S1352-2310(02)00886-5, 2003. a
Hunter, J. D.: Matplotlib: A 2D Graphics Environment, Comput. Sci. Eng., 9, 90–95, https://doi.org/10.1109/MCSE.2007.55, 2007. a
Iacono, M. J., Delamere, J. S., Mlawer, E. J., Shephard, M. W., Clough, S. A., and Collins, W. D.: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models, J. Geophys. Res.-Atmos., 113, D13103, https://doi.org/10.1029/2008JD009944, 2008. a
IPCC: The Sixth Assessment Report, Climate Change 2021: The Physical Science Basis, Tech. Rep., https://www.ipcc.ch/report/sixth-assessment-report-working-group-i/ (last access: 26 October 2023), 2021. a
Irish, V. E., Hanna, S. J., Willis, M. D., China, S., Thomas, J. L., Wentzell, J. J. B., Cirisan, A., Si, M., Leaitch, W. R., Murphy, J. G., Abbatt, J. P. D., Laskin, A., Girard, E., and Bertram, A. K.: Ice nucleating particles in the marine boundary layer in the Canadian Arctic during summer 2014, Atmos. Chem. Phys., 19, 1027–1039, https://doi.org/10.5194/acp-19-1027-2019, 2019. a, b, c, d, e, f, g
Jiang, J. H., Su, H., Massie, S. T., Colarco, P. R., Schoeberl, M. R., and Platnick, S.: Aerosol-CO relationship and aerosol effect on ice cloud particle size: Analyses from Aura Microwave Limb Sounder and Aqua Moderate Resolution Imaging Spectroradiometer observations, J. Geophys. Res.-Atmos., 114, D20207, https://doi.org/10.1029/2009JD012421, 2009. a
Jones, A., Thomson, D., Hort, M., and Devenish, B.: The U.K. Met Office's Next-Generation Atmospheric Dispersion Model, NAME III, in: Air Pollution Modeling and Its Application XVII, edited by: Borrego, C. and Norman, A.-L., Springer US, Boston, MA, 580–589, ISBN 978-0-387-68854-1, https://doi.org/10.1007/978-0-387-68854-1_62, 2007. a
Kirchstetter, T. W., Novakov, T., and Hobbs, P. V.: Evidence that the spectral dependence of light absorption by aerosols is affected by organic carbon, J. Geophys. Res.-Atmos., 109, D21208, https://doi.org/10.1029/2004JD004999, 2004. a
Lapere, R., Marelle, L., Rampal, P., Brodeau, L., Melsheimer, C., Spreen, G., and Thomas, J. L.: Modeling the contribution of leads to sea spray aerosol in the high Arctic, Atmos. Chem. Phys., 24, 12107–12132, https://doi.org/10.5194/acp-24-12107-2024, 2024. a
Lu, Z., Streets, D. G., Zhang, Q., and Wang, S.: A novel back-trajectory analysis of the origin of black carbon transported to the Himalayas and Tibetan Plateau during 1996–2010, Geophys. Res. Lett., 39, L01809, https://doi.org/10.1029/2011GL049903, 2012. a
Manning, A. J., O'Doherty, S., Jones, A. R., Simmonds, P. G., and Derwent, R. G.: Estimating UK methane and nitrous oxide emissions from 1990 to 2007 using an inversion modeling approach, J. Geophys. Res.-Atmos., 116, https://doi.org/10.1029/2010JD014763, 2011. a
Marelle, L., Raut, J.-C., Thomas, J. L., Law, K. S., Quennehen, B., Ancellet, G., Pelon, J., Schwarzenboeck, A., and Fast, J. D.: Transport of anthropogenic and biomass burning aerosols from Europe to the Arctic during spring 2008, Atmos. Chem. Phys., 15, 3831–3850, https://doi.org/10.5194/acp-15-3831-2015, 2015. a
Marelle, L., Raut, J.-C., Law, K. S., Berg, L. K., Fast, J. D., Easter, R. C., Shrivastava, M., and Thomas, J. L.: Improvements to the WRF-Chem 3.5.1 model for quasi-hemispheric simulations of aerosols and ozone in the Arctic, Geosci. Model Dev., 10, 3661–3677, https://doi.org/10.5194/gmd-10-3661-2017, 2017. a
Matus, A. V. and L'Ecuyer, T. S.: The role of cloud phase in Earth's radiation budget, J. Geophys. Res.-Atmos., 122, 2559–2578, https://doi.org/10.1002/2016JD025951, 2017. a
Met Office: Cartopy: a cartographic python library with a Matplotlib interface, Cartopy [code], https://scitools.org.uk/cartopy (last access: 16 September 2024), 2010. a
Möhler, O., Adams, M., Lacher, L., Vogel, F., Nadolny, J., Ullrich, R., Boffo, C., Pfeuffer, T., Hobl, A., Weiß, M., Vepuri, H. S. K., Hiranuma, N., and Murray, B. J.: The Portable Ice Nucleation Experiment (PINE): a new online instrument for laboratory studies and automated long-term field observations of ice-nucleating particles, Atmos. Meas. Tech., 14, 1143–1166, https://doi.org/10.5194/amt-14-1143-2021, 2021. a
Monahan, E. C., Spiel, D. E., and Davidson, K. L.: A Model of Marine Aerosol Generation Via Whitecaps and Wave Disruption, in: Oceanic Whitecaps: And Their Role in Air-Sea Exchange Processes, edited by Monahan, E. C. and Niocaill, G. M., Oceanographic Sciences Library, Springer Netherlands, Dordrecht, 167–174, ISBN 978-94-009-4668-2, https://doi.org/10.1007/978-94-009-4668-2_16, 1986. a, b
Morrison, H., Thompson, G., and Tatarskii, V.: Impact of Cloud Microphysics on the Development of Trailing Stratiform Precipitation in a Simulated Squall Line: Comparison of One- and Two-Moment Schemes, Mon. Weather Rev., 137, 991–1007, https://doi.org/10.1175/2008MWR2556.1, 2009. a
Morrison, H., van Lier-Walqui, M., Fridlind, A. M., Grabowski, W. W., Harrington, J. Y., Hoose, C., Korolev, A., Kumjian, M. R., Milbrandt, J. A., Pawlowska, H., Posselt, D. J., Prat, O. P., Reimel, K. J., Shima, S.-I., van Diedenhoven, B., and Xue, L.: Confronting the Challenge of Modeling Cloud and Precipitation Microphysics, J. Adv. Model. Earth Sy., 12, e2019MS001689, https://doi.org/10.1029/2019MS001689, 2020. a
Mungall, E. L., Wong, J. P. S., and Abbatt, J. P. D.: Heterogeneous Oxidation of Particulate Methanesulfonic Acid by the Hydroxyl Radical: Kinetics and Atmospheric Implications, ACS Earth and Space Chemistry, 2, 48–55, https://doi.org/10.1021/acsearthspacechem.7b00114, 2018. a
Murray, B. J., Carslaw, K. S., and Field, P. R.: Opinion: Cloud-phase climate feedback and the importance of ice-nucleating particles, Atmos. Chem. Phys., 21, 665–679, https://doi.org/10.5194/acp-21-665-2021, 2021. a
Nakanishi, M. and Niino, H.: Development of an Improved Turbulence Closure Model for the Atmospheric Boundary Layer, J. Meteorol. Soc. Jpn. Ser. II, 87, 895–912, https://doi.org/10.2151/jmsj.87.895, 2009. a
NASA Ocean Biology Processing Group: Aqua MODIS Level 3 Mapped Chlorophyll Data, Version R2022.0, NASA [data set], https://doi.org/10.5067/AQUA/MODIS/L3M/CHL/2022, 2022. a
National Centers for Environmental Prediction/National Weather Service/NOAA/U.S. Department of Commerce: NCEP FNL Operational Model Global Tropospheric Analyses, continuing from July 1999, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory [data set], https://doi.org/10.5065/D6M043C6, 2000. a
Ohata, S., Moteki, N., Mori, T., Koike, M., and Kondo, Y.: A key process controlling the wet removal of aerosols: new observational evidence, Scientific Reports, 6, 34113, https://doi.org/10.1038/srep34113, 2016. a
Park, K.-T., Jang, S., Lee, K., Yoon, Y. J., Kim, M.-S., Park, K., Cho, H.-J., Kang, J.-H., Udisti, R., Lee, B.-Y., and Shin, K.-H.: Observational evidence for the formation of DMS-derived aerosols during Arctic phytoplankton blooms, Atmos. Chem. Phys., 17, 9665–9675, https://doi.org/10.5194/acp-17-9665-2017, 2017. a
Parshintsev, J. and Hyötyläinen, T.: Methods for characterization of organic compounds in atmospheric aerosol particles, Anal. Bioanal. Chem., 407, 5877–5897, https://doi.org/10.1007/s00216-014-8394-3, 2015. a
Partridge, D. G., Vrugt, J. A., Tunved, P., Ekman, A. M. L., Gorea, D., and Sorooshian, A.: Inverse modeling of cloud-aerosol interactions – Part 1: Detailed response surface analysis, Atmos. Chem. Phys., 11, 7269–7287, https://doi.org/10.5194/acp-11-7269-2011, 2011. a
Pasquier, J. T., David, R. O., Freitas, G., Gierens, R., Gramlich, Y., Haslett, S., Li, G., Schäfer, B., Siegel, K., Wieder, J., Adachi, K., Belosi, F., Carlsen, T., Decesari, S., Ebell, K., Gilardoni, S., Gysel-Beer, M., Henneberger, J., Inoue, J., Kanji, Z. A., Koike, M., Kondo, Y., Krejci, R., Lohmann, U., Maturilli, M., Mazzolla, M., Modini, R., Mohr, C., Motos, G., Nenes, A., Nicosia, A., Ohata, S., Paglione, M., Park, S., Pileci, R. E., Ramelli, F., Rinaldi, M., Ritter, C., Sato, K., Storelvmo, T., Tobo, Y., Traversi, R., Viola, A., and Zieger, P.: The Ny-Ålesund Aerosol Cloud Experiment (NASCENT): Overview and First Results, B. Am. Meteorol. Soc., 103, E2533–E2558, https://doi.org/10.1175/BAMS-D-21-0034.1, 2022. a, b
Pernov, J. B., Harris, E., Volpi, M., Baumgartner, T., Hohermuth, B., Henne, S., Aeberhard, W. H., Becagli, S., Quinn, P. K., Traversi, R., Upchurch, L. M., and Schmale, J.: Pan-Arctic methanesulfonic acid aerosol: source regions, atmospheric drivers, and future projections, npj Clim. Atmos. Sci., 7, 166, https://doi.org/10.1038/s41612-024-00712-3, 2024. a
Pisso, I., Sollum, E., Grythe, H., Kristiansen, N. I., Cassiani, M., Eckhardt, S., Arnold, D., Morton, D., Thompson, R. L., Groot Zwaaftink, C. D., Evangeliou, N., Sodemann, H., Haimberger, L., Henne, S., Brunner, D., Burkhart, J. F., Fouilloux, A., Brioude, J., Philipp, A., Seibert, P., and Stohl, A.: The Lagrangian particle dispersion model FLEXPART version 10.4, Geosci. Model Dev., 12, 4955–4997, https://doi.org/10.5194/gmd-12-4955-2019, 2019. a, b, c
Polissar, A. V., Hopke, P. K., Paatero, P., Kaufmann, Y. J., Hall, D. K., Bodhaine, B. A., Dutton, E. G., and Harris, J. M.: The aerosol at Barrow, Alaska: long-term trends and source locations, Atmos. Environ., 33, 2441–2458, https://doi.org/10.1016/S1352-2310(98)00423-3, 1999. a
Porter, G. C. E., Adams, M. P., Brooks, I. M., Ickes, L., Karlsson, L., Leck, C., Salter, M. E., Schmale, J., Siegel, K., Sikora, S. N. F., Tarn, M. D., Vüllers, J., Wernli, H., Zieger, P., Zinke, J., and Murray, B. J.: Highly Active Ice-Nucleating Particles at the Summer North Pole, J. Geophys. Res.-Atmos., 127, e2021JD036059, https://doi.org/10.1029/2021JD036059, 2022. a, b
Rantanen, M., K. A. L. A.: he Arctic has warmed nearly four times faster than the globe since 1979, Communication Earth Environment, 3, 168, https://doi.org/10.1038/s43247-022-00498-3, 2022. a
Raut, J.-C., Marelle, L., Fast, J. D., Thomas, J. L., Weinzierl, B., Law, K. S., Berg, L. K., Roiger, A., Easter, R. C., Heimerl, K., Onishi, T., Delanoë, J., and Schlager, H.: Cross-polar transport and scavenging of Siberian aerosols containing black carbon during the 2012 ACCESS summer campaign, Atmos. Chem. Phys., 17, 10969–10995, https://doi.org/10.5194/acp-17-10969-2017, 2017. a
Ren, B., Xie, P., Xu, J., Li, A., Tian, X., Hu, Z., Huang, Y., Li, X., Zhang, Q., Ren, H., and Ji, H.: Use of the PSCF method to analyze the variations of potential sources and transports of NO2, SO2, and HCHO observed by MAX-DOAS in Nanjing, China during 2019, Sci. Total Environ., 782, 146865, https://doi.org/10.1016/j.scitotenv.2021.146865, 2021. a
Resovsky, A., Ramonet, M., Rivier, L., Tarniewicz, J., Ciais, P., Steinbacher, M., Mammarella, I., Mölder, M., Heliasz, M., Kubistin, D., Lindauer, M., Müller-Williams, J., Conil, S., and Engelen, R.: An algorithm to detect non-background signals in greenhouse gas time series from European tall tower and mountain stations, Atmos. Meas. Tech., 14, 6119–6135, https://doi.org/10.5194/amt-14-6119-2021, 2021. a
Ruckstuhl, A. F., Henne, S., Reimann, S., Steinbacher, M., Vollmer, M. K., O'Doherty, S., Buchmann, B., and Hueglin, C.: Robust extraction of baseline signal of atmospheric trace species using local regression, Atmos. Meas. Tech., 5, 2613–2624, https://doi.org/10.5194/amt-5-2613-2012, 2012. a
Saltzman, E. S., Savoie, D. L., Zika, R. G., and Prospero, J. M.: Methane sulfonic acid in the marine atmosphere, J. Geophys. Res.-Oceans, 88, 10897–10902, https://doi.org/10.1029/JC088iC15p10897, 1983. a
Schmale, J., Sharma, S., Decesari, S., Pernov, J., Massling, A., Hansson, H.-C., von Salzen, K., Skov, H., Andrews, E., Quinn, P. K., Upchurch, L. M., Eleftheriadis, K., Traversi, R., Gilardoni, S., Mazzola, M., Laing, J., and Hopke, P.: Pan-Arctic seasonal cycles and long-term trends of aerosol properties from 10 observatories, Atmos. Chem. Phys., 22, 3067–3096, https://doi.org/10.5194/acp-22-3067-2022, 2022. a
Serreze, M. C. and Barry, R. G.: Processes and impacts of Arctic amplification: A research synthesis, Global Planet. Change, 77, 85–96, https://doi.org/10.1016/j.gloplacha.2011.03.004, 2011. a
Shao, L., Liu, P., Jones, T., Yang, S., Wang, W., Zhang, D., Li, Y., Yang, C.-X., Xing, J., Hou, C., Zhang, M., Feng, X., Li, W., and BéruBé, K.: A review of atmospheric individual particle analyses: Methodologies and applications in environmental research, Gondwana Res., 110, 347–369, https://doi.org/10.1016/j.gr.2022.01.007, 2022. a
Si, M., Evoy, E., Yun, J., Xi, Y., Hanna, S. J., Chivulescu, A., Rawlings, K., Veber, D., Platt, A., Kunkel, D., Hoor, P., Sharma, S., Leaitch, W. R., and Bertram, A. K.: Concentrations, composition, and sources of ice-nucleating particles in the Canadian High Arctic during spring 2016, Atmos. Chem. Phys., 19, 3007–3024, https://doi.org/10.5194/acp-19-3007-2019, 2019. a, b, c, d, e
Siegel, K., Gramlich, Y., Haslett, S. L., Freitas, G., Krejci, R., Zieger, P., and Mohr, C.: Arctic observations of hydroperoxymethyl thioformate (HPMTF) – seasonal behavior and relationship to other oxidation products of dimethyl sulfide at the Zeppelin Observatory, Svalbard, Atmos. Chem. Phys., 23, 7569–7587, https://doi.org/10.5194/acp-23-7569-2023, 2023. a
Skamarock, W. C., Klemp, J. B., Dushia, J., Gill, D. O., Liu, Z., Berner, J., Wang, W., Powers, J. G., Duda, M. G., Barker, D. M., and Huang, X.: A Description of the Advanced Research WRF Version 4, https://doi.org/10.5065/1dfh-6p97, 2022. a
Sprenger, M. and Wernli, H.: The LAGRANTO Lagrangian analysis tool – version 2.0, Geosci. Model Dev., 8, 2569–2586, https://doi.org/10.5194/gmd-8-2569-2015, 2015. a
Stein, A. F., Draxler, R. R., Rolph, G. D., Stunder, B. J. B., Cohen, M. D., and Ngan, F.: NOAA's HYSPLIT Atmospheric Transport and Dispersion Modeling System, B. Am. Meteorol. Soc., 96, 2059–2077, https://doi.org/10.1175/BAMS-D-14-00110.1, 2015. a
Stohl, A., Hittenberger, M., and Wotawa, G.: Validation of the lagrangian particle dispersion model FLEXPART against large-scale tracer experiment data, Atmos. Environ., 32, 4245–4264, https://doi.org/10.1016/S1352-2310(98)00184-8, 1998. a
Stohl, A., Eckhardt, S., Forster, C., James, P., Spichtinger, N., and Seibert, P.: A replacement for simple back trajectory calculations in the interpretation of atmospheric trace substance measurements, Atmos. Environ., 36, 4635–4648, https://doi.org/10.1016/S1352-2310(02)00416-8, 2002. a
Stohl, A., Seibert, P., Arduini, J., Eckhardt, S., Fraser, P., Greally, B. R., Lunder, C., Maione, M., Mühle, J., O'Doherty, S., Prinn, R. G., Reimann, S., Saito, T., Schmidbauer, N., Simmonds, P. G., Vollmer, M. K., Weiss, R. F., and Yokouchi, Y.: An analytical inversion method for determining regional and global emissions of greenhouse gases: Sensitivity studies and application to halocarbons, Atmos. Chem. Phys., 9, 1597–1620, https://doi.org/10.5194/acp-9-1597-2009, 2009. a
Storelvmo, T.: Aerosol Effects on Climate via Mixed-Phase and Ice Clouds, Annu. Rev. Earth Pl. Sc., 45, 199–222, https://doi.org/10.1146/annurev-earth-060115-012240, 2017. a
Stuecker, M. F., Bitz, C. M., Armour, K. C., Proistosescu, C., Kang, S. M., Xie, S.-P., Kim, D., McGregor, S., Zhang, W., Zhao, S., Cai, W., Dong, Y., and Jin, F.-F.: Polar amplification dominated by local forcing and feedbacks, Nat. Clim. Change, 8, 1076–1081, https://doi.org/10.1038/s41558-018-0339-y, 2018. a
Tewari, M., Chen, F., Wang, W., Dudhia, J., LeMone, M., Gayno, G., Wegiel, J., and Cuenca, R.: Implementation and verification of the unified Noah land surface model in the WRF model, in: 20th Conference on Weather Analysis and Forecasting/16th Conference on Numerical Weather Prediction, Seattle, WA, 14 January 2004, https://ams.confex.com/ams/84Annual/techprogram/paper_69061.htm (last access: 12 May 2023), 2004. a
Wen, D., Lin, J., Millet, D., Stein, A., and Draxler, R.: A backward-time stochastic Lagrangian air quality model, Atmos. Environ., 54, 373–386, https://doi.org/10.1016/j.atmosenv.2012.02.042, 2012. a
Wex, H., Huang, L., Zhang, W., Hung, H., Traversi, R., Becagli, S., Sheesley, R. J., Moffett, C. E., Barrett, T. E., Bossi, R., Skov, H., Hünerbein, A., Lubitz, J., Löffler, M., Linke, O., Hartmann, M., Herenz, P., and Stratmann, F.: Annual variability of ice-nucleating particle concentrations at different Arctic locations, Atmos. Chem. Phys., 19, 5293–5311, https://doi.org/10.5194/acp-19-5293-2019, 2019. a, b
Winiger, P., Andersson, A., Eckhardt, S., Stohl, A., and Gustafsson, Ö.: The sources of atmospheric black carbon at a European gateway to the Arctic, Nat. Commun., 7, 12776, https://doi.org/10.1038/ncomms12776, 2016. a
Xu, J.-W., Martin, R. V., Morrow, A., Sharma, S., Huang, L., Leaitch, W. R., Burkart, J., Schulz, H., Zanatta, M., Willis, M. D., Henze, D. K., Lee, C. J., Herber, A. B., and Abbatt, J. P. D.: Source attribution of Arctic black carbon constrained by aircraft and surface measurements, Atmos. Chem. Phys., 17, 11971–11989, https://doi.org/10.5194/acp-17-11971-2017, 2017. a
Yun, J., Evoy, E., Worthy, S. E., Fraser, M., Veber, D., Platt, A., Rawlings, K., Sharma, S., Leaitch, W. R., and Bertram, A.: Ice nucleating particles in the Canadian High Arctic during the fall of 2018, Environmental Science: Atmospheres, 2, 279–290, https://doi.org/10.1039/D1EA00068C, 2022. a
Zeng, Y. and Hopke, P. K.: A study of the sources of acid precipitation in Ontario, Canada, Atmos. Environ., 23, 1499–1509, https://doi.org/10.1016/0004-6981(89)90409-5, 1989. a
Zhao, B., Donahue, N. M., Zhang, K., Mao, L., Shrivastava, M., Ma, P.-L., Shen, J., Wang, S., Sun, J., Gordon, H., Tang, S., Fast, J., Wang, M., Gao, Y., Yan, C., Singh, B., Li, Z., Huang, L., Lou, S., Lin, G., Wang, H., Jiang, J., Ding, A., Nie, W., Qi, X., Chi, X., and Wang, L.: Global variability in atmospheric new particle formation mechanisms, Nature, 631, 98–105, https://doi.org/10.1038/s41586-024-07547-1, 2024. a
Short summary
Particle sources in polar climates are unclear, affecting climate representation in models. This study introduces an evaluated method for tracking particles with backward modeling. Tests on simulated particles allowed us to show that traditional detection methods often misidentify sources. An improved method that accurately traces the origins of aerosol particles in the Arctic is presented. The study recommends using this enhanced method for better source identification of atmospheric species.
Particle sources in polar climates are unclear, affecting climate representation in models. This...
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