Articles | Volume 22, issue 18
https://doi.org/10.5194/acp-22-12269-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-12269-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 Sep 2022
Research article |
| 20 Sep 2022
| 20 Sep 2022
Comparisons between the distributions of dust and combustion aerosols in MERRA-2, FLEXPART, and CALIPSO and implications for deposition freezing over wintertime Siberia
Lauren M. Zamora
CORRESPONDING AUTHOR
Earth System Science Interdisciplinary Center, University of Maryland, College Park, College Park, Maryland, USA
NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
Ralph A. Kahn
NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
Nikolaos Evangeliou
Department of Atmospheric and Climate Research, Norwegian Institute for Air Research (NILU), Kjeller, Norway
Christine D. Groot Zwaaftink
Department of Atmospheric and Climate Research, Norwegian Institute for Air Research (NILU), Kjeller, Norway
Klaus B. Huebert
CSS, Inc., Fairfax, Virginia, USA
Related authors
No articles found.
Sara Herrero-Anta, Sabine Eckhardt, Nikolaos Evangeliou, Stefania Gilardoni, Sandra Graßl, Dominic Heslin-Rees, Stelios Kazadzis, Natalia Kouremeti, Radovan Krejci, David Mateos, Mauro Mazzola, Christoph Ritter, Roberto Román, Kerstin Stebel, and Tymon Zielinski
EGUsphere, https://doi.org/10.5194/egusphere-2025-3423, https://doi.org/10.5194/egusphere-2025-3423, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
In summer 2019, unusually high aerosol levels were measured in the Arctic, linked to wildfires, volcanic eruptions, and anthropogenic pollution. Using various instruments and models, we traced their origins and found good agreement between methods. The particles were mostly non-absorbing, but still we found a reduction of the solar radiation reaching the surface. This study shows that combining different measurements improves our understanding of how distant events affect the Arctic climate.
Olga B. Popovicheva, Marina A. Chichaeva, Nikolaos Evangeliou, Sabine Eckhardt, Evangelia Diapouli, and Nikolay S. Kasimov
Atmos. Chem. Phys., 25, 7719–7739, https://doi.org/10.5194/acp-25-7719-2025, https://doi.org/10.5194/acp-25-7719-2025, 2025
Short summary
Short summary
High-quality measurements of light-absorbing carbon were performed at the polar aerosol station "Island Bely” (Western Siberian Arctic) from 2019 to 2022. The maximum light absorption coefficients were seen in summer due to gas flaring, which is the most significant source in the region. However, the increasing Siberian wildfires had a special share in carbon contribution at this high Arctic station, with a persistent smoke layer extending over the whole troposphere in summer.
Xin Xi, Jun Wang, Zhendong Lu, Andrew M. Sayer, Jaehwa Lee, Robert C. Levy, Yujie Wang, Alexei Lyapustin, Hongqing Liu, Istvan Laszlo, Changwoo Ahn, Omar Torres, Sabur Abdullaev, James Limbacher, and Ralph A. Kahn
Atmos. Chem. Phys., 25, 7403–7429, https://doi.org/10.5194/acp-25-7403-2025, https://doi.org/10.5194/acp-25-7403-2025, 2025
Short summary
Short summary
The Aralkum Desert is challenging for aerosol retrieval due to its bright, heterogeneous, and dynamic surfaces and the lack of in situ constraints on aerosol properties. The performance and consistency of satellite algorithms in observing Aralkum-generated saline dust remain unknown. This study compares multisensor UVAI (ultraviolet aerosol index), AOD (aerosol optical depth), and ALH (aerosol layer height) products and reveals inconsistencies and potential biases over the Aral Sea basin.
Xiaohua Pan, Mian Chin, Ralph A. Kahn, Hitoshi Matsui, Toshihiko Takemura, Meiyun Lin, Yuanyu Xie, Dongchul Kim, and Maria Val Martin
EGUsphere, https://doi.org/10.5194/egusphere-2025-2603, https://doi.org/10.5194/egusphere-2025-2603, 2025
Short summary
Short summary
Wildfire smoke can travel thousands of kilometers, affecting air quality far from the fire itself. This study looks at how two key factors – how much smoke is emitted & how high it rises – affect how smoke spreads. Using data from a major 2008 Siberian wildfire, four computer models were tested. Results show that models often inject smoke too low & remove it too quickly, missing high-altitude smoke seen by satellites. Better estimates of smoke height are crucial to improve air quality forecasts.
Lubna Dada, Benjamin T. Brem, Lidia-Marta Amarandi-Netedu, Martine Collaud Coen, Nikolaos Evangeliou, Christoph Hueglin, Nora Nowak, Robin Modini, Martin Steinbacher, and Martin Gysel-Beer
Aerosol Research, 3, 315–336, https://doi.org/10.5194/ar-3-315-2025, https://doi.org/10.5194/ar-3-315-2025, 2025
Short summary
Short summary
We investigated the sources of ultrafine particles (UFPs) in Payerne, Switzerland, highlighting the significant role of secondary processes in elevating UFP concentrations to levels comparable to urban areas. As the first study in rural midland Switzerland to analyze new particle formation events and secondary contributions, it offers key insights for air quality regulation and the role of agriculture in Switzerland and central Europe.
Bibhasvata Dasgupta, Malika Menoud, Carina van der Veen, Ingeborg Levin, Cora Veidt, Heiko Moossen, Sylvia Englund Michel, Peter Sperlich, Shinji Morimoto, Ryo Fujita, Taku Umezawa, Stephen Matthew Platt, Christine Groot Zwaaftink, Cathrine Lund Myhre, Rebecca Fisher, David Lowry, Euan Nisbet, James France, Ceres Woolley Maisch, Gordon Brailsford, Rowena Moss, Daisuke Goto, Sudhanshu Pandey, Sander Houweling, Nicola Warwick, and Thomas Röckmann
EGUsphere, https://doi.org/10.5194/egusphere-2025-2439, https://doi.org/10.5194/egusphere-2025-2439, 2025
Short summary
Short summary
We combined long-term methane mole fraction and isotope measurements from eight laboratories that sample high-latitude stations to compare, offset correct and harmonise the datasets into a hemisphere merged timeseries. Because each laboratory uses slightly different methods, we adjusted the data to make it directly comparable. This allowed us to create a consistent record of atmospheric methane concentration and its isotopes from 1988 to 2023.
Cameron McErlich, Felix Goddard, Alex Aves, Catherine Hardacre, Nikolaos Evangeliou, and Laura E. Revell
EGUsphere, https://doi.org/10.5194/egusphere-2025-1575, https://doi.org/10.5194/egusphere-2025-1575, 2025
Short summary
Short summary
Airborne microplastics are a new air pollutant but are not yet included in most global models. We add them to the UK Earth System Model to show how they move, change, and are removed from air. Smaller microplastics persist for longer and can travel further, even to Antarctica. While their current role in air pollution is small, their presence is expected to grow in future. This work offers a framework to assess future impacts of microplastics on air quality and climate.
Nikolaos Evangeliou, Ondřej Tichý, Marit Svendby Otervik, Sabine Eckhardt, Yves Balkanski, and Didier A. Hauglustaine
Aerosol Research, 3, 155–174, https://doi.org/10.5194/ar-3-155-2025, https://doi.org/10.5194/ar-3-155-2025, 2025
Short summary
Short summary
The COVID-19 lockdown measures in 2020 reduced emissions of various substances, improving air quality. However, PM2.5 stayed unchanged due to NH3 and related chemical transformations. Higher humidity favoured more SO42- production, as did the accumulated NH3. Excess NH3 reacted with HNO3 to make NO3-. In high-NH3 conditions such as those in 2020, a small reduction in NOx levels drove faster oxidation of NO3- and slower deposition of total inorganic NO3-, causing high secondary PM2.5.
Katherine T. Junghenn Noyes and Ralph A. Kahn
EGUsphere, https://doi.org/10.5194/egusphere-2025-395, https://doi.org/10.5194/egusphere-2025-395, 2025
Short summary
Short summary
With observations from NASA’s Multi-Angle Imaging Spectroradiometer (MISR) satellite instrument, we can constrain wildfire plume heights, smoke age, and particle size, shape, and light-absorption properties. We study over 3,600 wildfire plumes across Siberia by statistically comparing the MISR results to observations of fire strength, land cover type, and meteorology. We then stratify plumes by land cover type and infer the dominant aerosol aging mechanisms among different plume types.
Mariya Petrenko, Ralph Kahn, Mian Chin, Susanne E. Bauer, Tommi Bergman, Huisheng Bian, Gabriele Curci, Ben Johnson, Johannes W. Kaiser, Zak Kipling, Harri Kokkola, Xiaohong Liu, Keren Mezuman, Tero Mielonen, Gunnar Myhre, Xiaohua Pan, Anna Protonotariou, Samuel Remy, Ragnhild Bieltvedt Skeie, Philip Stier, Toshihiko Takemura, Kostas Tsigaridis, Hailong Wang, Duncan Watson-Parris, and Kai Zhang
Atmos. Chem. Phys., 25, 1545–1567, https://doi.org/10.5194/acp-25-1545-2025, https://doi.org/10.5194/acp-25-1545-2025, 2025
Short summary
Short summary
We compared smoke plume simulations from 11 global models to each other and to satellite smoke amount observations aimed at constraining smoke source strength. In regions where plumes are thick and background aerosol is low, models and satellites compare well. However, the input emission inventory tends to underestimate in many places, and particle property and loss rate assumptions vary enormously among models, causing uncertainties that require systematic in situ measurements to resolve.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
Short summary
Short summary
Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Myungje Choi, Alexei Lyapustin, Gregory L. Schuster, Sujung Go, Yujie Wang, Sergey Korkin, Ralph Kahn, Jeffrey S. Reid, Edward J. Hyer, Thomas F. Eck, Mian Chin, David J. Diner, Olga Kalashnikova, Oleg Dubovik, Jhoon Kim, and Hans Moosmüller
Atmos. Chem. Phys., 24, 10543–10565, https://doi.org/10.5194/acp-24-10543-2024, https://doi.org/10.5194/acp-24-10543-2024, 2024
Short summary
Short summary
This paper introduces a retrieval algorithm to estimate two key absorbing components in smoke (black carbon and brown carbon) using DSCOVR EPIC measurements. Our analysis reveals distinct smoke properties, including spectral absorption, layer height, and black carbon and brown carbon, over North America and central Africa. The retrieved smoke properties offer valuable observational constraints for modeling radiative forcing and informing health-related studies.
Karl Espen Yttri, Are Bäcklund, Franz Conen, Sabine Eckhardt, Nikolaos Evangeliou, Markus Fiebig, Anne Kasper-Giebl, Avram Gold, Hans Gundersen, Cathrine Lund Myhre, Stephen Matthew Platt, David Simpson, Jason D. Surratt, Sönke Szidat, Martin Rauber, Kjetil Tørseth, Martin Album Ytre-Eide, Zhenfa Zhang, and Wenche Aas
Atmos. Chem. Phys., 24, 2731–2758, https://doi.org/10.5194/acp-24-2731-2024, https://doi.org/10.5194/acp-24-2731-2024, 2024
Short summary
Short summary
We discuss carbonaceous aerosol (CA) observed at the high Arctic Zeppelin Observatory (2017 to 2020). We find that organic aerosol is a significant fraction of the Arctic aerosol, though less than sea salt aerosol and mineral dust, as well as non-sea-salt sulfate, originating mainly from anthropogenic sources in winter and from natural sources in summer, emphasizing the importance of wildfires for biogenic secondary organic aerosol and primary biological aerosol particles observed in the Arctic.
James A. Limbacher, Ralph A. Kahn, Mariel D. Friberg, Jaehwa Lee, Tyler Summers, and Hai Zhang
Atmos. Meas. Tech., 17, 471–498, https://doi.org/10.5194/amt-17-471-2024, https://doi.org/10.5194/amt-17-471-2024, 2024
Short summary
Short summary
We present the new Multi-Angle Geostationary Aerosol Retrieval Algorithm (MAGARA) that fuses observations from GOES-16 and GOES-17 to retrieve information about aerosol loading (at 10–15 min cadence) and aerosol particle properties (daily), all at pixel-level resolution. We present MAGARA results for three case studies: the 2018 California Camp Fire, the 2019 Williams Flats Fire, and the 2019 Kincade Fire. We also compare MAGARA aerosol loading and particle properties with AERONET.
Ondřej Tichý, Sabine Eckhardt, Yves Balkanski, Didier Hauglustaine, and Nikolaos Evangeliou
Atmos. Chem. Phys., 23, 15235–15252, https://doi.org/10.5194/acp-23-15235-2023, https://doi.org/10.5194/acp-23-15235-2023, 2023
Short summary
Short summary
We show declining trends in NH3 emissions over Europe for 2013–2020 using advanced dispersion and inverse modelling and satellite measurements from CrIS. Emissions decreased by −26% since 2013, showing that the abatement strategies adopted by the European Union have been very efficient. Ammonia emissions are low in winter and peak in summer due to temperature-dependent soil volatilization. The largest decreases were observed in central and western Europe in countries with high emissions.
Robert R. Nelson, Marcin L. Witek, Michael J. Garay, Michael A. Bull, James A. Limbacher, Ralph A. Kahn, and David J. Diner
Atmos. Meas. Tech., 16, 4947–4960, https://doi.org/10.5194/amt-16-4947-2023, https://doi.org/10.5194/amt-16-4947-2023, 2023
Short summary
Short summary
Shallow and coastal waters are nutrient-rich and turbid due to runoff. They are also located in areas where the atmosphere has more aerosols than open-ocean waters. NASA's Multi-angle Imaging SpectroRadiometer (MISR) has been monitoring aerosols for over 23 years but does not report results over shallow waters. We developed a new algorithm that uses all four of MISR’s bands and considers light leaving water surfaces. This algorithm performs well and increases over-water measurements by over 7 %.
Rimal Abeed, Camille Viatte, William C. Porter, Nikolaos Evangeliou, Cathy Clerbaux, Lieven Clarisse, Martin Van Damme, Pierre-François Coheur, and Sarah Safieddine
Atmos. Chem. Phys., 23, 12505–12523, https://doi.org/10.5194/acp-23-12505-2023, https://doi.org/10.5194/acp-23-12505-2023, 2023
Short summary
Short summary
Ammonia emissions from agricultural activities will inevitably increase with the rise in population. We use a variety of datasets (satellite, reanalysis, and model simulation) to calculate the first regional map of ammonia emission potential during the start of the growing season in Europe. We then apply our developed method using a climate model to show the effect of the temperature increase on future ammonia columns under two possible climate scenarios.
Michail Mytilinaios, Sara Basart, Sergio Ciamprone, Juan Cuesta, Claudio Dema, Enza Di Tomaso, Paola Formenti, Antonis Gkikas, Oriol Jorba, Ralph Kahn, Carlos Pérez García-Pando, Serena Trippetta, and Lucia Mona
Atmos. Chem. Phys., 23, 5487–5516, https://doi.org/10.5194/acp-23-5487-2023, https://doi.org/10.5194/acp-23-5487-2023, 2023
Short summary
Short summary
Multiscale Online Non-hydrostatic AtmospheRe CHemistry model (MONARCH) dust reanalysis provides a high-resolution 3D reconstruction of past dust conditions, allowing better quantification of climate and socioeconomic dust impacts. We assess the performance of the reanalysis needed to reproduce dust optical depth using dust-related products retrieved from satellite and ground-based observations and show that it reproduces the spatial distribution and seasonal variability of atmospheric dust well.
Ana Maria Roxana Petrescu, Chunjing Qiu, Matthew J. McGrath, Philippe Peylin, Glen P. Peters, Philippe Ciais, Rona L. Thompson, Aki Tsuruta, Dominik Brunner, Matthias Kuhnert, Bradley Matthews, Paul I. Palmer, Oksana Tarasova, Pierre Regnier, Ronny Lauerwald, David Bastviken, Lena Höglund-Isaksson, Wilfried Winiwarter, Giuseppe Etiope, Tuula Aalto, Gianpaolo Balsamo, Vladislav Bastrikov, Antoine Berchet, Patrick Brockmann, Giancarlo Ciotoli, Giulia Conchedda, Monica Crippa, Frank Dentener, Christine D. Groot Zwaaftink, Diego Guizzardi, Dirk Günther, Jean-Matthieu Haussaire, Sander Houweling, Greet Janssens-Maenhout, Massaer Kouyate, Adrian Leip, Antti Leppänen, Emanuele Lugato, Manon Maisonnier, Alistair J. Manning, Tiina Markkanen, Joe McNorton, Marilena Muntean, Gabriel D. Oreggioni, Prabir K. Patra, Lucia Perugini, Isabelle Pison, Maarit T. Raivonen, Marielle Saunois, Arjo J. Segers, Pete Smith, Efisio Solazzo, Hanqin Tian, Francesco N. Tubiello, Timo Vesala, Guido R. van der Werf, Chris Wilson, and Sönke Zaehle
Earth Syst. Sci. Data, 15, 1197–1268, https://doi.org/10.5194/essd-15-1197-2023, https://doi.org/10.5194/essd-15-1197-2023, 2023
Short summary
Short summary
This study updates the state-of-the-art scientific overview of CH4 and N2O emissions in the EU27 and UK in Petrescu et al. (2021a). Yearly updates are needed to improve the different respective approaches and to inform on the development of formal verification systems. It integrates the most recent emission inventories, process-based model and regional/global inversions, comparing them with UNFCCC national GHG inventories, in support to policy to facilitate real-time verification procedures.
Yunyao Li, Daniel Tong, Siqi Ma, Saulo R. Freitas, Ravan Ahmadov, Mikhail Sofiev, Xiaoyang Zhang, Shobha Kondragunta, Ralph Kahn, Youhua Tang, Barry Baker, Patrick Campbell, Rick Saylor, Georg Grell, and Fangjun Li
Atmos. Chem. Phys., 23, 3083–3101, https://doi.org/10.5194/acp-23-3083-2023, https://doi.org/10.5194/acp-23-3083-2023, 2023
Short summary
Short summary
Plume height is important in wildfire smoke dispersion and affects air quality and human health. We assess the impact of plume height on wildfire smoke dispersion and the exceedances of the National Ambient Air Quality Standards. A higher plume height predicts lower pollution near the source region, but higher pollution in downwind regions, due to the faster spread of the smoke once ejected, affects pollution exceedance forecasts and the early warning of extreme air pollution events.
Maureen Beaudor, Nicolas Vuichard, Juliette Lathière, Nikolaos Evangeliou, Martin Van Damme, Lieven Clarisse, and Didier Hauglustaine
Geosci. Model Dev., 16, 1053–1081, https://doi.org/10.5194/gmd-16-1053-2023, https://doi.org/10.5194/gmd-16-1053-2023, 2023
Short summary
Short summary
Ammonia mainly comes from the agricultural sector, and its volatilization relies on environmental variables. Our approach aims at benefiting from an Earth system model framework to estimate it. By doing so, we represent a consistent spatial distribution of the emissions' response to environmental changes.
We greatly improved the seasonal cycle of emissions compared with previous work. In addition, our model includes natural soil emissions (that are rarely represented in modeling approaches).
James A. Limbacher, Ralph A. Kahn, and Jaehwa Lee
Atmos. Meas. Tech., 15, 6865–6887, https://doi.org/10.5194/amt-15-6865-2022, https://doi.org/10.5194/amt-15-6865-2022, 2022
Short summary
Short summary
Launched in December 1999, NASA’s Multi-angle Imaging SpectroRadiometer (MISR) has given researchers qualitative constraints on aerosol particle properties for the past 22 years. Here, we present a new MISR research aerosol retrieval algorithm (RA) that utilizes over-land surface reflectance data from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) to address limitations of the MISR operational aerosol retrieval algorithm and improve retrievals of aerosol particle properties.
Priyanka deSouza, Ralph Kahn, Tehya Stockman, William Obermann, Ben Crawford, An Wang, James Crooks, Jing Li, and Patrick Kinney
Atmos. Meas. Tech., 15, 6309–6328, https://doi.org/10.5194/amt-15-6309-2022, https://doi.org/10.5194/amt-15-6309-2022, 2022
Short summary
Short summary
How sensitive are the spatial and temporal trends of PM2.5 derived from a network of low-cost sensors to the calibration adjustment used? How transferable are calibration equations developed at a few co-location sites to an entire network of low-cost sensors? This paper attempts to answer this question and offers a series of suggestions on how to develop the most robust calibration function for different end uses. It uses measurements from the Love My Air network in Denver as a test case.
Katherine T. Junghenn Noyes, Ralph A. Kahn, James A. Limbacher, and Zhanqing Li
Atmos. Chem. Phys., 22, 10267–10290, https://doi.org/10.5194/acp-22-10267-2022, https://doi.org/10.5194/acp-22-10267-2022, 2022
Short summary
Short summary
We compare retrievals of wildfire smoke particle size, shape, and light absorption from the MISR satellite instrument to modeling and other satellite data on land cover type, drought conditions, meteorology, and estimates of fire intensity (fire radiative power – FRP). We find statistically significant differences in the particle properties based on burning conditions and land cover type, and we interpret how changes in these properties point to specific aerosol aging mechanisms.
Olga B. Popovicheva, Nikolaos Evangeliou, Vasilii O. Kobelev, Marina A. Chichaeva, Konstantinos Eleftheriadis, Asta Gregorič, and Nikolay S. Kasimov
Atmos. Chem. Phys., 22, 5983–6000, https://doi.org/10.5194/acp-22-5983-2022, https://doi.org/10.5194/acp-22-5983-2022, 2022
Short summary
Short summary
Measurements of black carbon (BC) combined with atmospheric transport modeling reveal that gas flaring from oil and gas extraction in Kazakhstan, Volga-Ural, Komi, Nenets and western Siberia contributes the largest share of surface BC in the Russian Arctic dominating over domestic, industrial and traffic sectors. Pollution episodes show an increasing trend in concentration levels and frequency as the station is in the Siberian gateway of the highest anthropogenic pollution to the Russian Arctic.
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
Short summary
Short summary
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.
Christine D. Groot Zwaaftink, Wenche Aas, Sabine Eckhardt, Nikolaos Evangeliou, Paul Hamer, Mona Johnsrud, Arve Kylling, Stephen M. Platt, Kerstin Stebel, Hilde Uggerud, and Karl Espen Yttri
Atmos. Chem. Phys., 22, 3789–3810, https://doi.org/10.5194/acp-22-3789-2022, https://doi.org/10.5194/acp-22-3789-2022, 2022
Short summary
Short summary
We investigate causes of a poor-air-quality episode in northern Europe in October 2020 during which EU health limits for air quality were vastly exceeded. Such episodes may trigger measures to improve air quality. Analysis based on satellite observations, transport simulations, and surface observations revealed two sources of pollution. Emissions of mineral dust in Central Asia and biomass burning in Ukraine arrived almost simultaneously in Norway, and transport continued into the Arctic.
Stephen M. Platt, Øystein Hov, Torunn Berg, Knut Breivik, Sabine Eckhardt, Konstantinos Eleftheriadis, Nikolaos Evangeliou, Markus Fiebig, Rebecca Fisher, Georg Hansen, Hans-Christen Hansson, Jost Heintzenberg, Ove Hermansen, Dominic Heslin-Rees, Kim Holmén, Stephen Hudson, Roland Kallenborn, Radovan Krejci, Terje Krognes, Steinar Larssen, David Lowry, Cathrine Lund Myhre, Chris Lunder, Euan Nisbet, Pernilla B. Nizzetto, Ki-Tae Park, Christina A. Pedersen, Katrine Aspmo Pfaffhuber, Thomas Röckmann, Norbert Schmidbauer, Sverre Solberg, Andreas Stohl, Johan Ström, Tove Svendby, Peter Tunved, Kjersti Tørnkvist, Carina van der Veen, Stergios Vratolis, Young Jun Yoon, Karl Espen Yttri, Paul Zieger, Wenche Aas, and Kjetil Tørseth
Atmos. Chem. Phys., 22, 3321–3369, https://doi.org/10.5194/acp-22-3321-2022, https://doi.org/10.5194/acp-22-3321-2022, 2022
Short summary
Short summary
Here we detail the history of the Zeppelin Observatory, a unique global background site and one of only a few in the high Arctic. We present long-term time series of up to 30 years of atmospheric components and atmospheric transport phenomena. Many of these time series are important to our understanding of Arctic and global atmospheric composition change. Finally, we discuss the future of the Zeppelin Observatory and emerging areas of future research on the Arctic atmosphere.
Matthew W. Christensen, Andrew Gettelman, Jan Cermak, Guy Dagan, Michael Diamond, Alyson Douglas, Graham Feingold, Franziska Glassmeier, Tom Goren, Daniel P. Grosvenor, Edward Gryspeerdt, Ralph Kahn, Zhanqing Li, Po-Lun Ma, Florent Malavelle, Isabel L. McCoy, Daniel T. McCoy, Greg McFarquhar, Johannes Mülmenstädt, Sandip Pal, Anna Possner, Adam Povey, Johannes Quaas, Daniel Rosenfeld, Anja Schmidt, Roland Schrödner, Armin Sorooshian, Philip Stier, Velle Toll, Duncan Watson-Parris, Robert Wood, Mingxi Yang, and Tianle Yuan
Atmos. Chem. Phys., 22, 641–674, https://doi.org/10.5194/acp-22-641-2022, https://doi.org/10.5194/acp-22-641-2022, 2022
Short summary
Short summary
Trace gases and aerosols (tiny airborne particles) are released from a variety of point sources around the globe. Examples include volcanoes, industrial chimneys, forest fires, and ship stacks. These sources provide opportunistic experiments with which to quantify the role of aerosols in modifying cloud properties. We review the current state of understanding on the influence of aerosol on climate built from the wide range of natural and anthropogenic laboratories investigated in recent decades.
Jessica L. McCarty, Juha Aalto, Ville-Veikko Paunu, Steve R. Arnold, Sabine Eckhardt, Zbigniew Klimont, Justin J. Fain, Nikolaos Evangeliou, Ari Venäläinen, Nadezhda M. Tchebakova, Elena I. Parfenova, Kaarle Kupiainen, Amber J. Soja, Lin Huang, and Simon Wilson
Biogeosciences, 18, 5053–5083, https://doi.org/10.5194/bg-18-5053-2021, https://doi.org/10.5194/bg-18-5053-2021, 2021
Short summary
Short summary
Fires, including extreme fire seasons, and fire emissions are more common in the Arctic. A review and synthesis of current scientific literature find climate change and human activity in the north are fuelling an emerging Arctic fire regime, causing more black carbon and methane emissions within the Arctic. Uncertainties persist in characterizing future fire landscapes, and thus emissions, as well as policy-relevant challenges in understanding, monitoring, and managing Arctic fire regimes.
Ana Maria Roxana Petrescu, Chunjing Qiu, Philippe Ciais, Rona L. Thompson, Philippe Peylin, Matthew J. McGrath, Efisio Solazzo, Greet Janssens-Maenhout, Francesco N. Tubiello, Peter Bergamaschi, Dominik Brunner, Glen P. Peters, Lena Höglund-Isaksson, Pierre Regnier, Ronny Lauerwald, David Bastviken, Aki Tsuruta, Wilfried Winiwarter, Prabir K. Patra, Matthias Kuhnert, Gabriel D. Oreggioni, Monica Crippa, Marielle Saunois, Lucia Perugini, Tiina Markkanen, Tuula Aalto, Christine D. Groot Zwaaftink, Hanqin Tian, Yuanzhi Yao, Chris Wilson, Giulia Conchedda, Dirk Günther, Adrian Leip, Pete Smith, Jean-Matthieu Haussaire, Antti Leppänen, Alistair J. Manning, Joe McNorton, Patrick Brockmann, and Albertus Johannes Dolman
Earth Syst. Sci. Data, 13, 2307–2362, https://doi.org/10.5194/essd-13-2307-2021, https://doi.org/10.5194/essd-13-2307-2021, 2021
Short summary
Short summary
This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up and top-down CH4 and N2O emissions in the EU27 and UK. The data integrate recent emission inventories with process-based model data and regional/global inversions for the European domain, aiming at reconciling them with official country-level UNFCCC national GHG inventories in support to policy and to facilitate real-time verification procedures.
Karl Espen Yttri, Francesco Canonaco, Sabine Eckhardt, Nikolaos Evangeliou, Markus Fiebig, Hans Gundersen, Anne-Gunn Hjellbrekke, Cathrine Lund Myhre, Stephen Matthew Platt, André S. H. Prévôt, David Simpson, Sverre Solberg, Jason Surratt, Kjetil Tørseth, Hilde Uggerud, Marit Vadset, Xin Wan, and Wenche Aas
Atmos. Chem. Phys., 21, 7149–7170, https://doi.org/10.5194/acp-21-7149-2021, https://doi.org/10.5194/acp-21-7149-2021, 2021
Short summary
Short summary
Carbonaceous aerosol sources and trends were studied at the Birkenes Observatory. A large decrease in elemental carbon (EC; 2001–2018) and a smaller decline in levoglucosan (2008–2018) suggest that organic carbon (OC)/EC from traffic/industry is decreasing, whereas the abatement of OC/EC from biomass burning has been less successful. Positive matrix factorization apportioned 72 % of EC to fossil fuel sources and 53 % (PM2.5) and 78 % (PM10–2.5) of OC to biogenic sources.
Tianmeng Chen, Zhanqing Li, Ralph A. Kahn, Chuanfeng Zhao, Daniel Rosenfeld, Jianping Guo, Wenchao Han, and Dandan Chen
Atmos. Chem. Phys., 21, 6199–6220, https://doi.org/10.5194/acp-21-6199-2021, https://doi.org/10.5194/acp-21-6199-2021, 2021
Short summary
Short summary
A convective cloud identification process is developed using geostationary satellite data from Himawari-8.
Convective cloud fraction is generally larger before noon and smaller in the afternoon under polluted conditions, but megacities and complex topography can influence the pattern.
A robust relationship between convective cloud and aerosol loading is found. This pattern varies with terrain height and is modulated by varying thermodynamic, dynamical, and humidity conditions during the day.
Nikolaos Evangeliou, Yves Balkanski, Sabine Eckhardt, Anne Cozic, Martin Van Damme, Pierre-François Coheur, Lieven Clarisse, Mark W. Shephard, Karen E. Cady-Pereira, and Didier Hauglustaine
Atmos. Chem. Phys., 21, 4431–4451, https://doi.org/10.5194/acp-21-4431-2021, https://doi.org/10.5194/acp-21-4431-2021, 2021
Short summary
Short summary
Ammonia, a substance that has played a key role in sustaining life, has been increasing in the atmosphere, affecting climate and humans. Understanding the reasons for this increase is important for the beneficial use of ammonia. The evolution of satellite products gives us the opportunity to calculate ammonia emissions easier. We calculated global ammonia emissions over the last 10 years, incorporated them into a chemistry model and recorded notable improvement in reproducing observations.
Nikolaos Evangeliou, Stephen M. Platt, Sabine Eckhardt, Cathrine Lund Myhre, Paolo Laj, Lucas Alados-Arboledas, John Backman, Benjamin T. Brem, Markus Fiebig, Harald Flentje, Angela Marinoni, Marco Pandolfi, Jesus Yus-Dìez, Natalia Prats, Jean P. Putaud, Karine Sellegri, Mar Sorribas, Konstantinos Eleftheriadis, Stergios Vratolis, Alfred Wiedensohler, and Andreas Stohl
Atmos. Chem. Phys., 21, 2675–2692, https://doi.org/10.5194/acp-21-2675-2021, https://doi.org/10.5194/acp-21-2675-2021, 2021
Short summary
Short summary
Following the transmission of SARS-CoV-2 to Europe, social distancing rules were introduced to prevent further spread. We investigate the impacts of the European lockdowns on black carbon (BC) emissions by means of in situ observations and inverse modelling. BC emissions declined by 23 kt in Europe during the lockdowns as compared with previous years and by 11 % as compared to the period prior to lockdowns. Residential combustion prevailed in Eastern Europe, as confirmed by remote sensing data.
Ondřej Tichý, Miroslav Hýža, Nikolaos Evangeliou, and Václav Šmídl
Atmos. Meas. Tech., 14, 803–818, https://doi.org/10.5194/amt-14-803-2021, https://doi.org/10.5194/amt-14-803-2021, 2021
Short summary
Short summary
We present an investigation of the usability of newly developed real-time concentration monitoring systems, which are based on the gamma-ray counting of aerosol filters. These high-resolution data were used for inverse modeling of the 106Ru release in 2017. Our inverse modeling results agree with previously published estimates and provide better temporal resolution of the estimates.
Ondřej Tichý, Lukáš Ulrych, Václav Šmídl, Nikolaos Evangeliou, and Andreas Stohl
Geosci. Model Dev., 13, 5917–5934, https://doi.org/10.5194/gmd-13-5917-2020, https://doi.org/10.5194/gmd-13-5917-2020, 2020
Short summary
Short summary
We study the estimation of the temporal profile of an atmospheric release using formalization as a linear inverse problem. The problem is typically ill-posed, so all state-of-the-art methods need some form of regularization using additional information. We provide a sensitivity study on the prior source term and regularization parameters for the shape of the source term with a demonstration on the ETEX experimental release and the Cs-134 and Cs-137 dataset from the Chernobyl accident.
Priyanka deSouza, Ralph A. Kahn, James A. Limbacher, Eloise A. Marais, Fábio Duarte, and Carlo Ratti
Atmos. Meas. Tech., 13, 5319–5334, https://doi.org/10.5194/amt-13-5319-2020, https://doi.org/10.5194/amt-13-5319-2020, 2020
Short summary
Short summary
This paper presents a novel method to constrain the size distribution derived from low-cost optical particle counters (OPCs) using satellite data to develop higher-quality particulate matter (PM) estimates. Such estimates can enable cities that do not have access to expensive reference air quality monitors, especially those in the global south, to develop effective air quality management plans.
Cited articles
Acker, J. G. and Leptoukh, G.: Online analysis enhances use of NASA Earth science data, Eos Trans. AGU, 88, 14–17, 2007.
AIRS project: Aqua/AIRS L3 Daily Standard Physical Retrieval (AIRS+AMSU) 1
degree × 1 degree V7.0, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/8XB4RU470FJV, 2019.
Alterskjær, K., Kristjánsson, J. E., and Hoose, C.: Do anthropogenic
aerosols enhance or suppress the surface cloud forcing in the Arctic?, J.
Geophys. Res., 115, D22204, https://doi.org/10.1029/2010JD014015, 2010.
Amante, C. and Eakins, B. W.: ETOPO1 1 Arc-Minute Global Relief Model:
Procedures, Data Sources and Analysis, NOAA Technical Memorandum NESDIS
NGDC-24, National Geophysical Data Center, NOAA [data set],
https://doi.org/10.7289/V5C8276M, 2009.
Arnold, S. R., Law, K. S., Brock, C. A., Thomas, J. L., Starkweather, S. M.,
Salzen, K. von, Stohl, A., Sharma, S., Lund, M. T., Flanner, M. G.,
Petäjä, T., Tanimoto, H., Gamble, J., Dibb, J. E., Melamed, M.,
Johnson, N., Fidel, M., Tynkkynen, V.-P., Baklanov, A., Eckhardt, S., Monks,
S. A., Browse, J., and Bozem, H.: Arctic air pollution: Challenges and
opportunities for the next decade, Elem. Sci. Anth., 4, 000104,
https://doi.org/10.12952/journal.elementa.000104, 2016.
Bullard, J. E. and Mockford, T.: Seasonal and decadal variability of dust
observations in the Kangerlussuaq area, west Greenland, Arct., Antarct. Alp. Res., 50, S100011, https://doi.org/10.1080/15230430.2017.1415854, 2018.
Burkart, J., Hodshire, A. L., Mungall, E. L., Pierce, J. R., Collins, D. B.,
Ladino, L. A., Lee, A. K. Y., Irish, V., Wentzell, J. J. B., Liggio, J.,
Papakyriakou, T., Murphy, J., and Abbatt, J.: Organic Condensation and
Particle Growth to CCN Sizes in the Summertime Marine Arctic Is Driven by
Materials More Semivolatile Than at Continental Sites, Geophys. Res.
Lett., 44, 10725–10734, https://doi.org/10.1002/2017GL075671, 2017.
Burton, S. P., Ferrare, R. A., Vaughan, M. A., Omar, A. H., Rogers, R. R., Hostetler, C. A., and Hair, J. W.: Aerosol classification from airborne HSRL and comparisons with the CALIPSO vertical feature mask, Atmos. Meas. Tech., 6, 1397–1412, https://doi.org/10.5194/amt-6-1397-2013, 2013.
Campbell, J. R., Reid, J. S., Westphal, D. L., Zhang, J., Tackett, J. L.,
Chew, B. N., Welton, E. J., Shimizu, A., Sugimoto, N., Aoki, K., and Winker,
D. M.: Characterizing the vertical profile of aerosol particle extinction
and linear depolarization over Southeast Asia and the Maritime Continent:
The 2007–2009 view from CALIOP, Atmos. Res., 122, 520–543,
https://doi.org/10.1016/j.atmosres.2012.05.007, 2013.
Carlsen, T. and David, R. O.: Spaceborne Evidence That Ice-Nucleating
Particles Influence High-Latitude Cloud Phase, Geophys. Res. Lett.,
49, e2022GL098041, https://doi.org/10.1029/2022GL098041, 2022.
Cassiani, M., Stohl, A., and Brioude, J.: Lagrangian Stochastic Modelling of
Dispersion in the Convective Boundary Layer with Skewed Turbulence
Conditions and a Vertical Density Gradient: Formulation and Implementation
in the FLEXPART Model, Bound.-Lay. Meteorol., 154, 367–390,
https://doi.org/10.1007/s10546-014-9976-5, 2014.
Chen, X., Kang, S., Yang, J., and Ji, Z.: Investigation of black carbon
climate effects in the Arctic in winter and spring, Sci. Total
Environ., 751, 142145, https://doi.org/10.1016/j.scitotenv.2020.142145, 2021.
Colarco, P., Silva, A. da, Chin, M., and Diehl, T.: Online simulations of
global aerosol distributions in the NASA GEOS-4 model and comparisons to
satellite and ground-based aerosol optical depth, J. Geophys. Res.-Atmos., 115, D14207, https://doi.org/10.1029/2009JD012820, 2010.
Damoah, R., Spichtinger, N., Forster, C., James, P., Mattis, I., Wandinger, U., Beirle, S., Wagner, T., and Stohl, A.: Around the world in 17 days - hemispheric-scale transport of forest fire smoke from Russia in May 2003, Atmos. Chem. Phys., 4, 1311–1321, https://doi.org/10.5194/acp-4-1311-2004, 2004.
Di Biagio, C., Pelon, J., Ancellet, G., Bazureau, A., and Mariage, V.:
Sources, Load, Vertical Distribution, and Fate of Wintertime Aerosols North
of Svalbard From Combined V4 CALIOP Data, Ground-Based IAOOS Lidar
Observations and Trajectory Analysis, J. Geophys. Res.-Atmos., 123, 1363–1383, https://doi.org/10.1002/2017JD027530, 2018.
Di Pierro, M., Jaeglé, L., Eloranta, E. W., and Sharma, S.: Spatial and seasonal distribution of Arctic aerosols observed by the CALIOP satellite instrument (2006–2012), Atmos. Chem. Phys., 13, 7075–7095, https://doi.org/10.5194/acp-13-7075-2013, 2013.
Drakaki, E., Amiridis, V., Tsekeri, A., Gkikas, A., Proestakis, E., Mallios, S., Solomos, S., Spyrou, C., Marinou, E., Ryder, C., Bouris, D., and Katsafados, P.: Modelling coarse and giant desert dust particles, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2022-94, in review, 2022.
Dufour, A., Zolina, O., and Gulev, S. K.: Atmospheric Moisture Transport to
the Arctic: Assessment of Reanalyses and Analysis of Transport Components,
J. Climate, 29, 5061–5081, https://doi.org/10.1175/JCLI-D-15-0559.1, 2016.
Duncan, B. N., Ott, L. E., Abshire, J. B., Brucker, L., Carroll, M. L.,
Carton, J., Comiso, J. C., Dinnat, E. P., Forbes, B. C., Gonsamo, A., Gregg,
W. W., Hall, D. K., Ialongo, I., Jandt, R., Kahn, R. A., Karpechko, A.,
Kawa, S. R., Kato, S., Kumpula, T., Kyrölä, E., Loboda, T. V.,
McDonald, K. C., Montesano, P. M., Nassar, R., Neigh, C. S. R., Parkinson,
C. L., Poulter, B., Pulliainen, J., Rautiainen, K., Rogers, B. M.,
Rousseaux, C. S., Soja, A. J., Steiner, N., Tamminen, J., Taylor, P. C.,
Tzortziou, M. A., Virta, H., Wang, J. S., Watts, J. D., Winker, D. M., and
Wu, D. L.: Space-Based Observations for Understanding Changes in the
Arctic-Boreal Zone, Rev. Geophys., 58, e2019RG000652,
https://doi.org/10.1029/2019RG000652, 2020.
Eckhardt, S., Quennehen, B., Olivié, D. J. L., Berntsen, T. K., Cherian, R., Christensen, J. H., Collins, W., Crepinsek, S., Daskalakis, N., Flanner, M., Herber, A., Heyes, C., Hodnebrog, Ø., Huang, L., Kanakidou, M., Klimont, Z., Langner, J., Law, K. S., Lund, M. T., Mahmood, R., Massling, A., Myriokefalitakis, S., Nielsen, I. E., Nøjgaard, J. K., Quaas, J., Quinn, P. K., Raut, J.-C., Rumbold, S. T., Schulz, M., Sharma, S., Skeie, R. B., Skov, H., Uttal, T., von Salzen, K., and Stohl, A.: Current model capabilities for simulating black carbon and sulfate concentrations in the Arctic atmosphere: a multi-model evaluation using a comprehensive measurement data set, Atmos. Chem. Phys., 15, 9413–9433, https://doi.org/10.5194/acp-15-9413-2015, 2015.
Ferrare, R. A., Hair, J. W., Hostetler, C. A., Harper, D. B., Seaman, S. T.,
Shingler, T. J., Fenn, M. A., Scarino, A. J., Burton, S. P., Cook, A. L.,
Vaughan, M., Liu, H., Zhang, B., Diskin, G. S., Zuidema, P., Chellappan, S.,
Moore, R., Crosbie, E. C., Ziemba, L. D., Thornhill, K. L., Robinson, C. E.,
Shook, M., Schlosser, J., and Sorooshian, A.: Airborne High Spectral Resolution Lidar-2 Measurements of Enhanced Depolarization in Marine Aerosols, 2020 Fall Meeting, AGU, 1–17 December 2020, online, A035-0001, 2020.
Forster, C., Wandinger, U., Wotawa, G., James, P., Mattis, I., Althausen,
D., Simmonds, P., O'Doherty, S., Jennings, S. G., Kleefeld, C., Schneider,
J., Trickl, T., Kreipl, S., Jäger, H., and Stohl, A.: Transport of
boreal forest fire emissions from Canada to Europe, J. Geophys. Res., 106,
22887–22906, https://doi.org/10.1029/2001JD900115, 2001.
Forster, C., Stohl, A., and Seibert, P.: Parameterization of convective
transport in a Lagrangian particle dispersion model and its evaluation,
J. Appl. Meteorol. Clim., 46, 403–422, https://doi.org/10.1175/JAM2470.1, 2007.
Gagné, M.-È., Fyfe, J. C., Gillett, N. P., Polyakov, I. V., and
Flato, G. M.: Aerosol-driven increase in Arctic sea ice over the middle of
the 20th Century, Geophys. Res. Lett., 44, 7338–7346,
https://doi.org/10.1002/2016GL071941, 2017.
Gassó, S., Thorsteinsson, T., and McKenna-Neuman, C.: Assessing the Many
Influences of High-Latitude Dust, Eos, 99, https://doi.org/10.1029/2018EO090315, 2018.
Giglio, L., Randerson, J. T., and Werf, G. R.: Analysis of daily, monthly,
and annual burned area using the fourth-generation global fire emissions
database (GFED4), J. Geophys. Res.-Biogeo., 118,
317–328, https://doi.org/10.1002/jgrg.20042, 2013.
Global Modeling and Assimilation Office (GMAO): MERRA-2 inst3_3d_aer_Nv:
3d,3-Hourly,Instantaneous,Model-Level,Assimilation,Aerosol Mixing Ratio
V5.12.4, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information
Services Center (GES DISC) [data set], https://doi.org/10.5067/LTVB4GPCOTK2, 2015a.
Global Modeling and Assimilation Office (GMAO): MERRA-2 inst3_3d_asm_Nv:
3d,3-Hourly,Instantaneous,Model-Level,Assimilation,Assimilated
Meteorological Fields V5.12.4, Greenbelt, MD, USA, Goddard Earth Sciences
Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/WWQSXQ8IVFW8, 2015b.
Graham, R. M., Cohen, L., Petty, A. A., Boisvert, L. N., Rinke, A., Hudson,
S. R., Nicolaus, M., and Granskog, M. A.: Increasing frequency and duration
of Arctic winter warming events, Geophys. Res. Lett., 44,
6974–6983, https://doi.org/10.1002/2017GL073395, 2017.
Groot Zwaaftink, C. D., Grythe, H., Skov, H., and Stohl, A.: Substantial
contribution of northern high-latitude sources to mineral dust in the
Arctic, J. Geophys. Res.-Atmos., 121, 13678–13697,
https://doi.org/10.1002/2016JD025482, 2016.
Groot Zwaaftink, C. D., Arnalds, Ó., Dagsson-Waldhauserova, P., Eckhardt, S., Prospero, J. M., and Stohl, A.: Temporal and spatial variability of Icelandic dust emissions and atmospheric transport, Atmos. Chem. Phys., 17, 10865–10878, https://doi.org/10.5194/acp-17-10865-2017, 2017.
Grythe, H., Kristiansen, N. I., Groot Zwaaftink, C. D., Eckhardt, S., Ström, J., Tunved, P., Krejci, R., and Stohl, A.: A new aerosol wet removal scheme for the Lagrangian particle model FLEXPART v10, Geosci. Model Dev., 10, 1447–1466, https://doi.org/10.5194/gmd-10-1447-2017, 2017.
Hallen, H. D. and Philbrick, C. R.: Lidar detection of small aerosol size
distribution, in: Laser Radar Technology and Applications XXIII, Laser Radar
Technology and Applications XXIII, 106360J,
https://doi.org/10.1117/12.2304890, 2018.
Intrieri, J. M. and Shupe, M. D.: Characteristics and Radiative Effects of
Diamond Dust over the Western Arctic Ocean Region, J. Climate, 17,
2953–2960, https://doi.org/10.1175/1520-0442(2004)017<2953:CAREOD>2.0.CO;2, 2004.
Kacenelenbogen, M., Redemann, J., Vaughan, M. A., Omar, A. H., Russell, P.
B., Burton, S., Rogers, R. R., Ferrare, R. A., and Hostetler, C. A.: An
evaluation of CALIOP/CALIPSO's aerosol-above-cloud detection and retrieval
capability over North America, J. Geophys. Res.-Atmos.,
119, 230–244, https://doi.org/10.1002/2013JD020178, 2014.
Kanitz, T., Ansmann, A., Foth, A., Seifert, P., Wandinger, U., Engelmann, R., Baars, H., Althausen, D., Casiccia, C., and Zamorano, F.: Surface matters: limitations of CALIPSO V3 aerosol typing in coastal regions, Atmos. Meas. Tech., 7, 2061–2072, https://doi.org/10.5194/amt-7-2061-2014, 2014.
Kanji, Z. A., Ladino, L. A., Wex, H., Boose, Y., Burkert-Kohn, M., Cziczo,
D. J., and Krämer, M.: Overview of Ice Nucleating Particles,
Meteor. Mon., 58, 1.1–1.33, https://doi.org/10.1175/AMSMONOGRAPHS-D-16-0006.1, 2017.
Kendall, M. G.: The treatment of ties in ranking problems, Biometrika, 33,
239–251, https://doi.org/10.1093/biomet/33.3.239, 1945.
Kim, M.-H., Omar, A. H., Tackett, J. L., Vaughan, M. A., Winker, D. M., Trepte, C. R., Hu, Y., Liu, Z., Poole, L. R., Pitts, M. C., Kar, J., and Magill, B. E.: The CALIPSO version 4 automated aerosol classification and lidar ratio selection algorithm, Atmos. Meas. Tech., 11, 6107–6135, https://doi.org/10.5194/amt-11-6107-2018, 2018.
Klimont, Z., Kupiainen, K., Heyes, C., Purohit, P., Cofala, J., Rafaj, P., Borken-Kleefeld, J., and Schöpp, W.: Global anthropogenic emissions of particulate matter including black carbon, Atmos. Chem. Phys., 17, 8681–8723, https://doi.org/10.5194/acp-17-8681-2017, 2017.
Kok, J. F.: A scaling theory for the size distribution of emitted dust
aerosols suggests climate models underestimate the size of the global dust
cycle, P. Natl. Acad. Sci. USA, 108, 1016–1021, https://doi.org/10.1073/pnas.1014798108, 2011.
Koop, T., Luo, B., Tsias, A., and Peter, T.: Water activity as the
determinant for homogeneous ice nucleation in aqueous solutions, Nature,
406, 611–614, https://doi.org/10.1038/35020537, 2000.
Korolev, A. V. and Mazin, I. P.: Supersaturation of Water Vapor in Clouds,
J. Atmos. Sci., 60, 2957–2974,
https://doi.org/10.1175/1520-0469(2003)060<2957:SOWVIC>2.0.CO;2, 2003.
Lee, S., Lee, M.-I., Song, C.-K., Kim, K.-M., and da Silva, A. M.:
Interannual variation of the East Asia Jet Stream and its impact on the
horizontal distribution of aerosol in boreal spring, Atmos. Environ., 223, 117296, https://doi.org/10.1016/j.atmosenv.2020.117296, 2020.
Long, C. M., Nascarella, M. A., and Valberg, P. A.: Carbon black vs. black
carbon and other airborne materials containing elemental carbon: Physical
and chemical distinctions, Environ. Pollut., 181, 271–286,
https://doi.org/10.1016/j.envpol.2013.06.009, 2013.
Marcolli, C.: Deposition nucleation viewed as homogeneous or immersion freezing in pores and cavities, Atmos. Chem. Phys., 14, 2071–2104, https://doi.org/10.5194/acp-14-2071-2014, 2014.
Marcolli, C.: Pre-activation of aerosol particles by ice preserved in pores, Atmos. Chem. Phys., 17, 1595–1622, https://doi.org/10.5194/acp-17-1595-2017, 2017.
Marticorena, B. and Bergametti, G.: Modeling the atmospheric dust cycle: 1.
Design of a soil-derived dust emission scheme, J. Geophys. Res.-Atmos., 100, 16415–16430, https://doi.org/10.1029/95JD00690, 1995.
Maxwell, J. B.: The Climate of the Canadian Arctic Islands and Adjacent
Waters, Ministry of Supply and Services, Canada, 589 pp., ISBN 0660506416, 1982.
Mielonen, T., Aaltonen, V., Lihavainen, H., Hyvärinen, A.-P., Arola, A.,
Komppula, M., and Kivi, R.: Biomass Burning Aerosols Observed in Northern
Finland during the 2010 Wildfires in Russia, Atmosphere, 4, 17–34,
https://doi.org/10.3390/atmos4010017, 2013.
Morrison, H., de Boer, G., Feingold, G., Harrington, J., Shupe, M. D., and
Sulia, K.: Resilience of persistent Arctic mixed-phase clouds, Nat.
Geosci., 5, 11–17, https://doi.org/10.1038/ngeo1332, 2012.
Murphy, D. M. and Koop, T.: Review of the vapour pressures of ice and
supercooled water for atmospheric applications, Q. J. Roy. Meteor. Soc., 131, 1539–1565, https://doi.org/10.1256/qj.04.94, 2005.
Omar, A. H., Winker, D. M., Vaughan, M. A., Hu, Y., Trepte, C. R., Ferrare,
R. A., Lee, K.-P., Hostetler, C. A., Kittaka, C., Rogers, R. R., Kuehn, R.
E., and Liu, Z.: The CALIPSO automated aerosol classification and lidar
ratio selection algorithm, Journal of Atmospheric and Oceanic Technology J.
Atmos. Ocean. Tech., 26, 1994–2014, 2009.
Papagiannopoulos, N., Mona, L., Alados-Arboledas, L., Amiridis, V., Baars, H., Binietoglou, I., Bortoli, D., D'Amico, G., Giunta, A., Guerrero-Rascado, J. L., Schwarz, A., Pereira, S., Spinelli, N., Wandinger, U., Wang, X., and Pappalardo, G.: CALIPSO climatological products: evaluation and suggestions from EARLINET, Atmos. Chem. Phys., 16, 2341–2357, https://doi.org/10.5194/acp-16-2341-2016, 2016.
Paris, J.-D., Stohl, A., Nédélec, P., Arshinov, M. Yu., Panchenko, M. V., Shmargunov, V. P., Law, K. S., Belan, B. D., and Ciais, P.: Wildfire smoke in the Siberian Arctic in summer: source characterization and plume evolution from airborne measurements, Atmos. Chem. Phys., 9, 9315–9327, https://doi.org/10.5194/acp-9-9315-2009, 2009.
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.
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.
Prospero, J. M., Bullard, J. E., and Hodgkins, R.: High-Latitude Dust Over
the North Atlantic: Inputs from Icelandic Proglacial Dust Storms, Science,
335, 1078–1082, https://doi.org/10.1126/science.1217447, 2012.
Randles, C. A., da Silva, A. M., Buchard, V., Colarco, P. R., Darmenov, A.,
Govindaraju, R., Smirnov, A., Holben, B., Ferrare, R., Hair, J., Shinozuka,
Y., and Flynn, C. J.: The MERRA-2 Aerosol Reanalysis, 1980 Onward. Part I:
System Description and Data Assimilation Evaluation, J. Climate, 30,
6823–6850, https://doi.org/10.1175/JCLI-D-16-0609.1, 2017.
R Core Team: R: A language and environment for statistical computing, The R Foundation, https://www.R-project.org/, last access: 15 July 2022.
Reichle, R. H., Liu, Q., Koster, R. D., Draper, C. S., Mahanama, S. P. P.,
and Partyka, G. S.: Land Surface Precipitation in MERRA-2, J. Climate, 30, 1643–1664, https://doi.org/10.1175/JCLI-D-16-0570.1, 2017.
Rogers, R. R., Vaughan, M. A., Hostetler, C. A., Burton, S. P., Ferrare, R. A., Young, S. A., Hair, J. W., Obland, M. D., Harper, D. B., Cook, A. L., and Winker, D. M.: Looking through the haze: evaluating the CALIPSO level 2 aerosol optical depth using airborne high spectral resolution lidar data, Atmos. Meas. Tech., 7, 4317–4340, https://doi.org/10.5194/amt-7-4317-2014, 2014.
Sakai, T., Nagai, T., Nakazato, M., Mano, Y., and Matsumura, T.: Ice clouds
and Asian dust studied with lidar measurements of particle
extinction-to-backscatter ratio, particle depolarization, and water-vapor
mixing ratio over Tsukuba, Appl. Optics, 42, 7103–7116,
https://doi.org/10.1364/AO.42.007103, 2003.
Schmale, J., Zieger, P., and Ekman, A.: Aerosols in current and future
Arctic climate, Nat. Climate Change, 11, 95–105,
https://doi.org/10.1038/s41558-020-00969-5, 2021.
Shevlyakov, G. L. and Oja, H.: Robust correlation: theory and
applications, Wiley, ISBN 978-1-118-49345-8, 2016.
Shindell, D. and Faluvegi, G.: Climate response to regional radiative
forcing during the twentieth century, Nat. Geosci., 2, 294–300,
https://doi.org/10.1038/ngeo473, 2009.
Sitnov, S. A., Mokhov, I. I., and Likhosherstova, A. A.: Exploring
large-scale black-carbon air pollution over Northern Eurasia in summer 2016
using MERRA-2 reanalysis data, Atmos. Res., 235, 104763,
https://doi.org/10.1016/j.atmosres.2019.104763, 2020.
Sodemann, H., Pommier, M., Arnold, S. R., Monks, S. A., Stebel, K., Burkhart, J. F., Hair, J. W., Diskin, G. S., Clerbaux, C., Coheur, P.-F., Hurtmans, D., Schlager, H., Blechschmidt, A.-M., Kristjánsson, J. E., and Stohl, A.: Episodes of cross-polar transport in the Arctic troposphere during July 2008 as seen from models, satellite, and aircraft observations, Atmos. Chem. Phys., 11, 3631–3651, https://doi.org/10.5194/acp-11-3631-2011, 2011.
Stohl, A.: Characteristics of atmospheric transport into the Arctic
troposphere, J. Geophys. Res., 111, D11306, https://doi.org/10.1029/2005JD006888, 2006.
Stohl, A., Eckhardt, S., Forster, C., James, P., and Spichtinger, N.: On the
pathways and timescales of intercontinental air pollution transport,
J.-Geophys.-Res., 107, 4684, https://doi.org/10.1029/2001JD001396, 2002.
Stohl, A., Forster, C., Eckhardt, S., Spichtinger, N., Huntrieser, H.,
Heland, J., Schlager, H., Wilhelm, S., Arnold, F., and Cooper, O.: A
backward modeling study of intercontinental pollution transport using
aircraft measurements, J. Geophys. Res., 108, 4370,
https://doi.org/10.1029/2002JD002862, 2003.
Stohl, A., Forster, C., Frank, A., Seibert, P., and Wotawa, G.: Technical note: The Lagrangian particle dispersion model FLEXPART version 6.2, Atmos. Chem. Phys., 5, 2461–2474, https://doi.org/10.5194/acp-5-2461-2005, 2005.
Stohl, A., Aamaas, B., Amann, M., Baker, L. H., Bellouin, N., Berntsen, T. K., Boucher, O., Cherian, R., Collins, W., Daskalakis, N., Dusinska, M., Eckhardt, S., Fuglestvedt, J. S., Harju, M., Heyes, C., Hodnebrog, Ø., Hao, J., Im, U., Kanakidou, M., Klimont, Z., Kupiainen, K., Law, K. S., Lund, M. T., Maas, R., MacIntosh, C. R., Myhre, G., Myriokefalitakis, S., Olivié, D., Quaas, J., Quennehen, B., Raut, J.-C., Rumbold, S. T., Samset, B. H., Schulz, M., Seland, Ø., Shine, K. P., Skeie, R. B., Wang, S., Yttri, K. E., and Zhu, T.: Evaluating the climate and air quality impacts of short-lived pollutants, Atmos. Chem. Phys., 15, 10529–10566, https://doi.org/10.5194/acp-15-10529-2015, 2015.
Thorsen, T. J., Fu, Q., and Comstock, J.: Comparison of the CALIPSO
satellite and ground-based observations of cirrus clouds at the ARM TWP
sites, J. Geophys. Res.-Atmos., 116, D21203, https://doi.org/10.1029/2011JD015970, 2011.
Tian, B., Manning, E., Roman, J., Thrastarson, H., Fetzer, E., and Monarrez,
R.: AIRS Version 7 Level 3 Product User Guide, version 1.0, Goddard Earth Sciences Data and Information Services Center (GES DISC), https://doi.org/10.5067/Z03H907L0KMS, 2020.
Vaughan, M. A., Powell, K. A., Winker, D. M., Hostetler, C. A., Kuehn, R.
E., Hunt, W. H., Getzewich, B. J., Young, S. A., Liu, Z., and McGill, M. J.:
Fully Automated Detection of Cloud and Aerosol Layers in the CALIPSO Lidar
Measurements, J. Atmos. Ocean. Tech., 26, 2034–2050,
https://doi.org/10.1175/2009JTECHA1228.1, 2009.
Vinogradova, A. A., Kopeikin, V. M., Vasileva, A. V., Smirnov, N. S., and
Ivanova, Yu. A.: Concentration of Black Carbon in the Near-Surface
Atmosphere in the Pechora-Ilych Natural Reserve: Measurements and Merra-2
Reanalysis, Izv. Atmos. Ocean. Phys., 56, 1191–1201,
https://doi.org/10.1134/S0001433820100084, 2020.
Weinzierl, B., Ansmann, A., Prospero, J. M., Althausen, D., Benker, N.,
Chouza, F., Dollner, M., Farrell, D., Fomba, W. K., Freudenthaler, V.,
Gasteiger, J., Groß, S., Haarig, M., Heinold, B., Kandler, K.,
Kristensen, T. B., Mayol-Bracero, O. L., Müller, T., Reitebuch, O.,
Sauer, D., Schäfler, A., Schepanski, K., Spanu, A., Tegen, I., Toledano,
C., and Walser, A.: The Saharan Aerosol Long-Range Transport and
Aerosol–Cloud-Interaction Experiment: Overview and Selected Highlights,
B. Am. Meteorol. Soc., 98, 1427–1451, https://doi.org/10.1175/BAMS-D-15-00142.1, 2017.
Willis, M. D., Leaitch, W. R., and Abbatt, J. P. D.: Processes Controlling
the Composition and Abundance of Arctic Aerosol, Rev. Geophys., 56,
621–671, https://doi.org/10.1029/2018RG000602, 2018.
Winker, D. M.: CALIPSO Lidar Level 2 5 km Aerosol Layer Data V4-20, NASA
Langley Research Center Atmospheric Science Data Center DAAC [data set], https://doi.org/10.5067/CALIOP/CALIPSO/LID_L2_05kmALay-Standard-V4-20, 2018.
Winker, D. M., Tackett, J. L., Getzewich, B. J., Liu, Z., Vaughan, M. A., and Rogers, R. R.: The global 3-D distribution of tropospheric aerosols as characterized by CALIOP, Atmos. Chem. Phys., 13, 3345–3361, https://doi.org/10.5194/acp-13-3345-2013, 2013.
Wu, M., Liu, X., Yu, H., Wang, H., Shi, Y., Yang, K., Darmenov, A., Wu, C., Wang, Z., Luo, T., Feng, Y., and Ke, Z.: Understanding processes that control dust spatial distributions with global climate models and satellite observations, Atmos. Chem. Phys., 20, 13835–13855, https://doi.org/10.5194/acp-20-13835-2020, 2020.
Xian, P., Zhang, J., O'Neill, N. T., Toth, T. D., Sorenson, B., Colarco, P. R., Kipling, Z., Hyer, E. J., Campbell, J. R., Reid, J. S., and Ranjbar, K.: Arctic spring and summertime aerosol optical depth baseline from long-term observations and model reanalyses – Part 1: Climatology and trend, Atmos. Chem. Phys., 22, 9915–9947, https://doi.org/10.5194/acp-22-9915-2022, 2022.
Yang, Y., Zhao, C., Wang, Q., Cong, Z., Yang, X., and Fan, H.: Aerosol characteristics at the three poles of the Earth as characterized by Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations, Atmos. Chem. Phys., 21, 4849–4868, https://doi.org/10.5194/acp-21-4849-2021, 2021.
Zamora, L. M., Kahn, R. A., Eckhardt, S., McComiskey, A., Sawamura, P., Moore, R., and Stohl, A.: Aerosol indirect effects on the nighttime Arctic Ocean surface from thin, predominantly liquid clouds, Atmos. Chem. Phys., 17, 7311–7332, https://doi.org/10.5194/acp-17-7311-2017, 2017.
Zamora, L. M., Kahn, R. A., Huebert, K. B., Stohl, A., and Eckhardt, S.: A satellite-based estimate of combustion aerosol cloud microphysical effects over the Arctic Ocean, Atmos. Chem. Phys., 18, 14949–14964, https://doi.org/10.5194/acp-18-14949-2018, 2018.
Zamora, L. M., Evangeliou, N., Groot Zwaaftink, C. D., and Kahn, R. A.:
FLEXPART black carbon aerosol L4 global daily 1 × 1 degrees, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/XZOC4FV8LV3A, 2022a.
Zamora, L. M., Groot Zwaaftink, C. D., Evangeliou, N., and Kahn, R. A.:
FLEXPART dust aerosol L4 global daily 1 × 1 degrees, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/3QGSHO836JHP, 2022b.
Zamora, L. M., Evangeliou, N., Groot Zwaaftink, C. D., and Kahn, R. A.:
FLEXPART organic carbon aerosol L4 global daily 1 × 1 degrees, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/L4CD2D15VU2G, 2022c.
Zeng, S., Omar, A., Vaughan, M., Ortiz, M., Trepte, C., Tackett, J., Yagle,
J., Lucker, P., Hu, Y., Winker, D., Rodier, S., and Getzewich, B.:
Identifying Aerosol Subtypes from CALIPSO Lidar Profiles Using Deep Machine
Learning, Atmosphere, 12, 10, https://doi.org/10.3390/atmos12010010, 2021.
Zeng, X.: Radiatively Induced Precipitation Formation in Diamond Dust,
J. Adv. Model. Earth Syst., 10, 2300–2317, https://doi.org/10.1029/2018MS001382, 2018.
Zhuravleva, T. B., Artyushina, A. V., Vinogradova, A. A., and Voronina, Yu.
V.: Black Carbon in the Near-Surface Atmosphere Far Away from Emission
Sources: Comparison of Measurements and MERRA-2 Reanalysis Data, Atmos. Ocean. Opt., 33, 591–601, https://doi.org/10.1134/S1024856020060251, 2020.
Zygmuntowska, M., Mauritsen, T., Quaas, J., and Kaleschke, L.: Arctic Clouds and Surface Radiation – a critical comparison of satellite retrievals and the ERA-Interim reanalysis, Atmos. Chem. Phys., 12, 6667–6677, https://doi.org/10.5194/acp-12-6667-2012, 2012.
Short summary
Arctic dust, smoke, and pollution particles can affect clouds and Arctic warming. The distributions of these particles were estimated in three different satellite, reanalysis, and model products. These products showed good agreement overall but indicate that it is important to include local dust in models. We hypothesize that mineral dust effects on ice processes in the Arctic atmosphere might be highest over Siberia, where it is cold, moist, and subject to relatively high dust levels.
Arctic dust, smoke, and pollution particles can affect clouds and Arctic warming. The...
Altmetrics
Final-revised paper
Preprint