Articles | Volume 16, issue 11
https://doi.org/10.5194/amt-16-3027-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-16-3027-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Jun 2023
Research article |
| 15 Jun 2023
| 15 Jun 2023
Vertical information of CO from TROPOMI total column measurements in context of the CAMS-IFS data assimilation scheme
Netherlands Institute for Space Research, SRON, Leiden, the Netherlands
Teresa Campos
Atmospheric Chemistry Observations and Modeling Laboratory and Earth Observing Laboratory National Center for Atmospheric Research Boulder, Boulder, Colorado, USA
Natalie Kille
Department of Chemistry, University of Colorado Boulder, Boulder, Colorado, USA
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado, USA
Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, Colorado, USA
Kyle J. Zarzana
Department of Chemistry, University of Colorado Boulder, Boulder, Colorado, USA
Rainer Volkamer
Department of Chemistry, University of Colorado Boulder, Boulder, Colorado, USA
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado, USA
Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, Colorado, USA
Jochen Landgraf
Netherlands Institute for Space Research, SRON, Leiden, the Netherlands
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Atmos. Meas. Tech., 15, 4339–4371, https://doi.org/10.5194/amt-15-4339-2022, https://doi.org/10.5194/amt-15-4339-2022, 2022
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We present a computationally very efficient method for the synergetic use of level 2 remote-sensing data products. We apply the method to IASI vertical profile and TROPOMI total column space-borne methane observations and thus gain sensitivity for the tropospheric methane partial columns, which is not achievable by the individual use of TROPOMI and IASI. These synergetic effects are evaluated theoretically and empirically by inter-comparisons to independent references of TCCON, AirCore, and GAW.
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Andreas Schneider, Tobias Borsdorff, Joost aan de Brugh, Alba Lorente, Franziska Aemisegger, David Noone, Dean Henze, Rigel Kivi, and Jochen Landgraf
Atmos. Meas. Tech., 15, 2251–2275, https://doi.org/10.5194/amt-15-2251-2022, https://doi.org/10.5194/amt-15-2251-2022, 2022
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Tobias Küchler, Stefan Noël, Heinrich Bovensmann, John Philip Burrows, Thomas Wagner, Christian Borger, Tobias Borsdorff, and Andreas Schneider
Atmos. Meas. Tech., 15, 297–320, https://doi.org/10.5194/amt-15-297-2022, https://doi.org/10.5194/amt-15-297-2022, 2022
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Qiansi Tu, Frank Hase, Matthias Schneider, Omaira García, Thomas Blumenstock, Tobias Borsdorff, Matthias Frey, Farahnaz Khosrawi, Alba Lorente, Carlos Alberti, Juan J. Bustos, André Butz, Virgilio Carreño, Emilio Cuevas, Roger Curcoll, Christopher J. Diekmann, Darko Dubravica, Benjamin Ertl, Carme Estruch, Sergio Fabián León-Luis, Carlos Marrero, Josep-Anton Morgui, Ramón Ramos, Christian Scharun, Carsten Schneider, Eliezer Sepúlveda, Carlos Toledano, and Carlos Torres
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Tyler Wizenberg, Kimberly Strong, Kaley Walker, Erik Lutsch, Tobias Borsdorff, and Jochen Landgraf
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Atmos. Meas. Tech., 14, 6249–6304, https://doi.org/10.5194/amt-14-6249-2021, https://doi.org/10.5194/amt-14-6249-2021, 2021
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Neil M. Donahue, Victoria Hofbauer, Henning Finkenzeller, Dominik Stolzenburg, Paulus S. Bauer, Randall Chiu, Lubna Dada, Jonathan Duplissy, Xu-Cheng He, Martin Heinritzi, Christopher R. Hoyle, Andreas Kürten, Aleksandr Kvashnin, Katrianne Lehtipalo, Naser Mahfouz, Vladimir Makhmutov, Roy L. Mauldin III, Ugo Molteni, Lauriane L. J. Quéléver, Matti Rissanen, Siegfried Schobesberger, Mario Simon, Andrea C. Wagner, Mingyi Wang, Chao Yan, Penglin Ye, Ilona Riipinen, Hamish Gordon, Joachim Curtius, Armin Hansel, Imad El Haddad, Markku Kulmala, Douglas R. Worsnop, Rainer Volkamer, Paul M. Winkler, Jasper Kirkby, and Richard Flagan
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You Yi, William J. Randel, Laura L. Pan, Yi Liu, Shuangxi Fang, Zhaonan Cai, Teresa Campos, and Benjamin Gaubert
EGUsphere, https://doi.org/10.5194/egusphere-2026-2644, https://doi.org/10.5194/egusphere-2026-2644, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Kanwal Shahzadi, Matthias Schneider, Nga Ying Lo, Frank Hase, Jörg Meyer, Ugur Cayoglu, Tobias Borsdorff, and Mari C. Martinez-Velarte
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We merge TROPOMI and IASI L2 methane data from January 2018 to June 2021 on a global scale. The data merging yields total column-averaged and upper tropospheric/stratospheric partial column-averaged mole fractions (already provided by the individual data sets). In addition, it outputs tropospheric partial column-averaged mole fractions (not provided by any of the two individual data sets). We briefly document their increased potential for quantifying near-surface methane emissions.
Tobias Borsdorff, Maarten Krol, Pepijn Veefkind, and Jochen Landgraf
EGUsphere, https://doi.org/10.5194/egusphere-2026-1134, https://doi.org/10.5194/egusphere-2026-1134, 2026
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Industrial facilities release carbon dioxide and nitrogen dioxide. The TANGO mission, launching in 2028, will monitor both gases from ten thousand facilities per year using two satellites. We studied whether combining both improves carbon dioxide emission estimates and reveals plume chemistry. While this produces cleaner carbon dioxide images, precision does not improve as noise is redistributed not eliminated. Their ratio captures how nitrogen oxide converts to nitrogen dioxide within plumes.
Allison R. Moon, Leyang Liu, Xuan Wang, Yuk-Chun Chan, Alyson Fritzmann, Ryan Pound, Amy Lees, Lewis Marden, Mat Evans, Lucy J. Carpenter, Jochen Stutz, Joel A. Thornton, Gordon Novak, Andrew Rollins, Gregory P. Schill, Xu-Cheng He, Henning Finkenzeller, Mago Reza, Rainer Volkamer, Kelvin H. Bates, Alfonso Saiz-Lopez, Anoop S. Mahajan, and Becky Alexander
Atmos. Chem. Phys., 26, 2353–2389, https://doi.org/10.5194/acp-26-2353-2026, https://doi.org/10.5194/acp-26-2353-2026, 2026
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Global chemical transport models previously treated aerosols as a sink for reactive iodine (Iy); however, aerosol iodide is also a source of Iy via heterogeneous reactions involving hypohalous acids and halogen nitrates. We implemented this chemistry into GEOS-Chem, in addition to explicitly representing three aerosol iodine types: soluble organic iodine (SOI), iodide, and iodate. We found that aerosol recycling of iodide to form Iy is more than twice as fast as the other Iy sources combined.
Mari C. Martinez-Velarte, Jochen Landgraf, Ben Veihelmann, Bernd Sierk, and Tobias Borsdorff
EGUsphere, https://doi.org/10.5194/egusphere-2025-6328, https://doi.org/10.5194/egusphere-2025-6328, 2026
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Launched in August 2025, Sentinel-5 provides daily CH4 and CO retrievals and is sensitive to CO2. Its SWIR MCT detectors exhibit persistence effects causing scene-dependent biases. This study quantifies these biases for CH4, CO, CO2, and the CH4/CO2 proxy using RemoTeC over regions with high radiance variability. Typical biases are small (<0.34 %), but outliers reach 1.59–4.01 %. Targeted post-filtering can reduce outliers and meet mission performance.
Paul Konopka, Felix Ploeger, Francesco D'Amato, Teresa Campos, Marc von Hobe, Shawn B. Honomichl, Peter Hoor, Laura L. Pan, Michelle L. Santee, Silvia Viciani, Kaley A. Walker, and Michaela I. Hegglin
Atmos. Chem. Phys., 25, 17973–17996, https://doi.org/10.5194/acp-25-17973-2025, https://doi.org/10.5194/acp-25-17973-2025, 2025
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We present an improved version of the Chemical Lagrangian Model of the Stratosphere (CLaMS-3.0), which better represents transport from the lower atmosphere to the upper troposphere and lower stratosphere. By refining grid resolution and improving convection representation, the model more accurately simulates carbon monoxide transport. Comparisons with satellite and in situ observations highlight its ability to capture seasonal variations and improve our understanding of atmospheric transport.
Tyler R. Elgiar, Loknath Dhar, Lynne Gratz, A. Gannet Hallar, Rainer Volkamer, and Seth N. Lyman
Atmos. Chem. Phys., 25, 16387–16399, https://doi.org/10.5194/acp-25-16387-2025, https://doi.org/10.5194/acp-25-16387-2025, 2025
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We compare verified atmospheric mercury measurements against output from the GEOS-Chem photochemical transport model. We show the model is unable to reproduce measured atmospheric oxidized mercury concentrations, even in several cases where oxidation rates in the model are enhanced.
Andrew Gerald Barr, Jochen Landgraf, Mari Martinez-Velarte, Mihalis Vrekoussis, Ralf Sussmann, Isamu Morino, Kimberly Strong, Minqiang Zhou, Voltaire A. Velazco, Hirofumi Ohyama, Thorsten Warneke, Frank Hase, and Tobias Borsdorff
Atmos. Meas. Tech., 18, 6093–6123, https://doi.org/10.5194/amt-18-6093-2025, https://doi.org/10.5194/amt-18-6093-2025, 2025
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The Greenhouse Gases Observing Satellite-2 (GOSAT-2) is a satellite dedicated to measuring concentrations of greenhouse gases from space. Since its launch, the increase of CH4 and CO2 concentrations in the atmosphere is clear. The datasets obtained from GOSAT-2 are used in the Copernicus atmospheric services to monitor the climate, in light of the Paris Agreement. Here we present robust datasets of these gases from GOSAT-2, including a novel machine learning approach to data quality filtering.
Harikrishnan Charuvil Asokan, Jochen Landgraf, Pepijn Veefkind, Stijn Dellaert, and André Butz
Atmos. Meas. Tech., 18, 5247–5264, https://doi.org/10.5194/amt-18-5247-2025, https://doi.org/10.5194/amt-18-5247-2025, 2025
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Greenhouse gases like CO2 and CH4 drive climate change. Satellites enable monitoring of these emissions from space. Our simulations show that the upcoming Twin ANthropogenic Greenhouse gas Observers (TANGO) mission can detect about 500 targets per 4 d cycle under clear skies, but cloud cover reduces detection. Integrating cloud forecasts into TANGO’s manoeuvering boosts detection, highlighting its potential for improving global emission monitoring.
Yugo Kanaya, Roberto Sommariva, Alfonso Saiz-Lopez, Andrea Mazzeo, Theodore K. Koenig, Kaori Kawana, James E. Johnson, Aurélie Colomb, Pierre Tulet, Suzie Molloy, Ian E. Galbally, Rainer Volkamer, Anoop Mahajan, John W. Halfacre, Paul B. Shepson, Julia Schmale, Hélène Angot, Byron Blomquist, Matthew D. Shupe, Detlev Helmig, Junsu Gil, Meehye Lee, Sean C. Coburn, Ivan Ortega, Gao Chen, James Lee, Kenneth C. Aikin, David D. Parrish, John S. Holloway, Thomas B. Ryerson, Ilana B. Pollack, Eric J. Williams, Brian M. Lerner, Andrew J. Weinheimer, Teresa Campos, Frank M. Flocke, J. Ryan Spackman, Ilann Bourgeois, Jeff Peischl, Chelsea R. Thompson, Ralf M. Staebler, Amir A. Aliabadi, Wanmin Gong, Roeland Van Malderen, Anne M. Thompson, Ryan M. Stauffer, Debra E. Kollonige, Juan Carlos Gómez Martin, Masatomo Fujiwara, Katie Read, Matthew Rowlinson, Keiichi Sato, Junichi Kurokawa, Yoko Iwamoto, Fumikazu Taketani, Hisahiro Takashima, Mónica Navarro-Comas, Marios Panagi, and Martin G. Schultz
Earth Syst. Sci. Data, 17, 4901–4932, https://doi.org/10.5194/essd-17-4901-2025, https://doi.org/10.5194/essd-17-4901-2025, 2025
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The first comprehensive dataset of tropospheric ozone over oceans/polar regions is presented, including 77 ship/buoy and 48 aircraft campaign observations (1977–2022, 0–5000 m altitude), supplemented by ozonesonde and surface data. Air masses isolated from land for 72+ hours are systematically selected as essentially oceanic. Among the 11 global regions, they show daytime decreases of 11–16 % in the tropics, while near-zero depletions are rare, unlike in the Arctic, implying different mechanisms.
Aurélien Sicsik-Paré, Audrey Fortems-Cheiney, Isabelle Pison, Grégoire Broquet, Alvin Opler, Elise Potier, Adrien Martinez, Oliver Schneising, Michael Buchwitz, Joannes D. Maasakkers, Tobias Borsdorff, and Antoine Berchet
EGUsphere, https://doi.org/10.5194/egusphere-2025-2622, https://doi.org/10.5194/egusphere-2025-2622, 2025
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Assimilating satellite observations from TROPOMI provides top-down quantification of regional methane emissions. This study compares European emissions in 2019 estimated from the inversion of three TROPOMI datasets. We find inconsistencies in national budgets and spatial patterns, with no product clearly superior. We disentangle drivers of the differences, highlighting the impact of differences in coverage, observations and associated errors on the consistency of methane emission estimates.
Dongwook Kim, Pedro Campuzano-Jost, Hongyu Guo, Douglas A. Day, Da Yang, Suresh Dhaniyala, Leah Williams, Philip Croteau, John Jayne, Douglas Worsnop, Rainer Volkamer, and Jose L. Jimenez
Aerosol Research, 3, 371–404, https://doi.org/10.5194/ar-3-371-2025, https://doi.org/10.5194/ar-3-371-2025, 2025
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Quantitative real-time aerosol sampling on board aircraft platforms is challenging, especially at higher altitudes. Herein, we present comprehensive analyses of a new aircraft inlet system and tools for aerosol beam diagnostics for aerosol mass spectrometers (AMSs). The beam focusing of aerodynamic lenses and the thermal decomposition on the vaporizer were investigated. The new inlet system can be operated at higher altitudes while sampling aerosols over a broader size range than previous versions.
Gijs Leguijt, Joannes D. Maasakkers, Hugo A. C. Denier van der Gon, Arjo J. Segers, Tobias Borsdorff, Ivar R. van der Velde, and Ilse Aben
Atmos. Chem. Phys., 25, 555–574, https://doi.org/10.5194/acp-25-555-2025, https://doi.org/10.5194/acp-25-555-2025, 2025
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The production of steel coincides with large emissions of greenhouse gases and air pollutants including carbon monoxide. European facilities are required to report their emissions, which are estimated using a variety of methods. We evaluate these estimates using carbon monoxide concentrations measured via satellite. We find generally good agreement between our values and those reported but also identify some uncertainties, showing that satellites can provide insights into these emissions.
Yingjie Shen, Rudra P. Pokhrel, Amy P. Sullivan, Ezra J. T. Levin, Lauren A. Garofalo, Delphine K. Farmer, Wade Permar, Lu Hu, Darin W. Toohey, Teresa Campos, Emily V. Fischer, and Shane M. Murphy
Atmos. Chem. Phys., 24, 12881–12901, https://doi.org/10.5194/acp-24-12881-2024, https://doi.org/10.5194/acp-24-12881-2024, 2024
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The magnitude and evolution of brown carbon (BrC) absorption remain unclear, with uncertainty in climate models. Data from the WE-CAN airborne experiment show that model parameterizations overestimate the mass absorption cross section (MAC) of BrC. Observed decreases in BrC absorption with chemical markers are due to decreasing organic aerosol (OA) mass rather than a decreasing BrC MAC, which is currently implemented in models. Water-soluble BrC contributes 23 % of total absorption at 660 nm.
Theodore K. Koenig, François Hendrick, Douglas Kinnison, Christopher F. Lee, Michel Van Roozendael, and Rainer Volkamer
Atmos. Meas. Tech., 17, 5911–5934, https://doi.org/10.5194/amt-17-5911-2024, https://doi.org/10.5194/amt-17-5911-2024, 2024
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Atmospheric bromine destroys ozone, impacts oxidation capacity, and oxidizes mercury into its toxic form. We constrain bromine by remote sensing of BrO from a mountaintop. Previous measurements retrieved two to three pieces of information vertically; we apply new methods to get five and a half vertically and two more in time. We compare with aircraft measurements to validate the methods and look at variations in BrO over the Pacific.
Randall Chiu, Florian Obersteiner, Alessandro Franchin, Teresa Campos, Adriana Bailey, Christopher Webster, Andreas Zahn, and Rainer Volkamer
Atmos. Meas. Tech., 17, 5731–5746, https://doi.org/10.5194/amt-17-5731-2024, https://doi.org/10.5194/amt-17-5731-2024, 2024
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The ozone sink into oceans and marine clouds is seldom studied and highly uncertain. Calculations suggest O3 destruction at aqueous surfaces (ocean, droplets) may be strongly accelerated, but field evidence is missing. Here we compare three fast airborne O3 instruments to measure eddy covariance fluxes of O3 over the remote ocean, in clear and cloudy air. We find O3 fluxes below clouds are consistently directed into clouds, while O3 fluxes into oceans are much smaller and spatially variable.
Eleanor J. Derry, Tyler R. Elgiar, Taylor Y. Wilmot, Nicholas W. Hoch, Noah S. Hirshorn, Peter Weiss-Penzias, Christopher F. Lee, John C. Lin, A. Gannet Hallar, Rainer Volkamer, Seth N. Lyman, and Lynne E. Gratz
Atmos. Chem. Phys., 24, 9615–9643, https://doi.org/10.5194/acp-24-9615-2024, https://doi.org/10.5194/acp-24-9615-2024, 2024
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Mercury (Hg) is a globally distributed neurotoxic pollutant. Atmospheric deposition is the main source of Hg in ecosystems. However, measurement biases hinder understanding of the origins and abundance of the more bioavailable oxidized form. We used an improved, calibrated measurement system to study air mass composition and transport of atmospheric Hg at a remote mountaintop site in the central US. Oxidized Hg originated upwind in the low to middle free troposphere under clean, dry conditions.
Brian Nathan, Joannes D. Maasakkers, Stijn Naus, Ritesh Gautam, Mark Omara, Daniel J. Varon, Melissa P. Sulprizio, Lucas A. Estrada, Alba Lorente, Tobias Borsdorff, Robert J. Parker, and Ilse Aben
Atmos. Chem. Phys., 24, 6845–6863, https://doi.org/10.5194/acp-24-6845-2024, https://doi.org/10.5194/acp-24-6845-2024, 2024
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Venezuela's Lake Maracaibo region is notoriously hard to observe from space and features intensive oil exploitation, although production has strongly decreased in recent years. We estimate methane emissions using 2018–2020 TROPOMI satellite observations with national and regional transport models. Despite the production decrease, we find relatively constant emissions from Lake Maracaibo between 2018 and 2020, indicating that there could be large emissions from abandoned infrastructure.
Da Yang, Margarita Reza, Roy Mauldin, Rainer Volkamer, and Suresh Dhaniyala
Atmos. Meas. Tech., 17, 1463–1474, https://doi.org/10.5194/amt-17-1463-2024, https://doi.org/10.5194/amt-17-1463-2024, 2024
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This paper evaluates the performance of an aircraft gas inlet. Here, we use computational fluid dynamics (CFD) and experiments to demonstrate the role of turbulence in determining sampling performance of a gas inlet and identify ideal conditions for inlet operation to minimize gas loss. Experiments conducted in a high-speed wind tunnel under near-aircraft speeds validated numerical results. We believe that the results obtained from this work will greatly inform future gas inlet studies.
Berend J. Schuit, Joannes D. Maasakkers, Pieter Bijl, Gourav Mahapatra, Anne-Wil van den Berg, Sudhanshu Pandey, Alba Lorente, Tobias Borsdorff, Sander Houweling, Daniel J. Varon, Jason McKeever, Dylan Jervis, Marianne Girard, Itziar Irakulis-Loitxate, Javier Gorroño, Luis Guanter, Daniel H. Cusworth, and Ilse Aben
Atmos. Chem. Phys., 23, 9071–9098, https://doi.org/10.5194/acp-23-9071-2023, https://doi.org/10.5194/acp-23-9071-2023, 2023
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Using two machine learning models, which were trained on TROPOMI methane satellite data, we detect 2974 methane plumes, so-called super-emitters, in 2021. We detect methane emissions globally related to urban areas or landfills, coal mining, and oil and gas production. Using our monitoring system, we identify 94 regions with frequent emissions. For 12 locations, we target high-resolution satellite instruments to enlarge and identify the exact infrastructure responsible for the emissions.
Manu Goudar, Juliëtte C. S. Anema, Rajesh Kumar, Tobias Borsdorff, and Jochen Landgraf
Geosci. Model Dev., 16, 4835–4852, https://doi.org/10.5194/gmd-16-4835-2023, https://doi.org/10.5194/gmd-16-4835-2023, 2023
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A framework was developed to automatically detect plumes and compute emission estimates with cross-sectional flux method (CFM) for biomass burning events in TROPOMI CO datasets using Visible Infrared Imaging Radiometer Suite active fire data. The emissions were more reliable when changing plume height in downwind direction was used instead of constant injection height. The CFM had uncertainty even when the meteorological conditions were accurate; thus there is a need for better inversion models.
Gijs Leguijt, Joannes D. Maasakkers, Hugo A. C. Denier van der Gon, Arjo J. Segers, Tobias Borsdorff, and Ilse Aben
Atmos. Chem. Phys., 23, 8899–8919, https://doi.org/10.5194/acp-23-8899-2023, https://doi.org/10.5194/acp-23-8899-2023, 2023
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We present a fast method to evaluate carbon monoxide emissions from cities in Africa. Carbon monoxide is important for climate change in an indirect way, as it is linked to ozone, methane, and carbon dioxide. Our measurements are made with a satellite that sees the entire globe every single day. This means that we can check from space whether the current knowledge of emission rates is up to date. We make the comparison and show that the emission rates in northern Africa are underestimated.
Daniel J. Varon, Daniel J. Jacob, Benjamin Hmiel, Ritesh Gautam, David R. Lyon, Mark Omara, Melissa Sulprizio, Lu Shen, Drew Pendergrass, Hannah Nesser, Zhen Qu, Zachary R. Barkley, Natasha L. Miles, Scott J. Richardson, Kenneth J. Davis, Sudhanshu Pandey, Xiao Lu, Alba Lorente, Tobias Borsdorff, Joannes D. Maasakkers, and Ilse Aben
Atmos. Chem. Phys., 23, 7503–7520, https://doi.org/10.5194/acp-23-7503-2023, https://doi.org/10.5194/acp-23-7503-2023, 2023
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We use TROPOMI satellite observations to quantify weekly methane emissions from the US Permian oil and gas basin from May 2018 to October 2020. We find that Permian emissions are highly variable, with diverse economic and activity drivers. The most important drivers during our study period were new well development and natural gas price. Permian methane intensity averaged 4.6 % and decreased by 1 % per year.
Anna Agustí-Panareda, Jérôme Barré, Sébastien Massart, Antje Inness, Ilse Aben, Melanie Ades, Bianca C. Baier, Gianpaolo Balsamo, Tobias Borsdorff, Nicolas Bousserez, Souhail Boussetta, Michael Buchwitz, Luca Cantarello, Cyril Crevoisier, Richard Engelen, Henk Eskes, Johannes Flemming, Sébastien Garrigues, Otto Hasekamp, Vincent Huijnen, Luke Jones, Zak Kipling, Bavo Langerock, Joe McNorton, Nicolas Meilhac, Stefan Noël, Mark Parrington, Vincent-Henri Peuch, Michel Ramonet, Miha Razinger, Maximilian Reuter, Roberto Ribas, Martin Suttie, Colm Sweeney, Jérôme Tarniewicz, and Lianghai Wu
Atmos. Chem. Phys., 23, 3829–3859, https://doi.org/10.5194/acp-23-3829-2023, https://doi.org/10.5194/acp-23-3829-2023, 2023
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We present a global dataset of atmospheric CO2 and CH4, the two most important human-made greenhouse gases, which covers almost 2 decades (2003–2020). It is produced by combining satellite data of CO2 and CH4 with a weather and air composition prediction model, and it has been carefully evaluated against independent observations to ensure validity and point out deficiencies to the user. This dataset can be used for scientific studies in the field of climate change and the global carbon cycle.
Alba Lorente, Tobias Borsdorff, Mari C. Martinez-Velarte, and Jochen Landgraf
Atmos. Meas. Tech., 16, 1597–1608, https://doi.org/10.5194/amt-16-1597-2023, https://doi.org/10.5194/amt-16-1597-2023, 2023
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In the TROPOMI methane data, there are few false methane anomalies that can be misinterpreted as enhancements caused by strong emission sources. These artefacts are caused by features of the underlying surfaces that are not well characterized in the retrieval algorithm. Here we improve the representation of the surface reflectance dependency with wavelength in the forward model, removing the artificial localized CH4 enhancements found in several locations like Siberia, Australia and Algeria.
Adriana Bailey, Franziska Aemisegger, Leonie Villiger, Sebastian A. Los, Gilles Reverdin, Estefanía Quiñones Meléndez, Claudia Acquistapace, Dariusz B. Baranowski, Tobias Böck, Sandrine Bony, Tobias Bordsdorff, Derek Coffman, Simon P. de Szoeke, Christopher J. Diekmann, Marina Dütsch, Benjamin Ertl, Joseph Galewsky, Dean Henze, Przemyslaw Makuch, David Noone, Patricia K. Quinn, Michael Rösch, Andreas Schneider, Matthias Schneider, Sabrina Speich, Bjorn Stevens, and Elizabeth J. Thompson
Earth Syst. Sci. Data, 15, 465–495, https://doi.org/10.5194/essd-15-465-2023, https://doi.org/10.5194/essd-15-465-2023, 2023
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One of the novel ways EUREC4A set out to investigate trade wind clouds and their coupling to the large-scale circulation was through an extensive network of isotopic measurements in water vapor, precipitation, and seawater. Samples were taken from the island of Barbados, from aboard two aircraft, and from aboard four ships. This paper describes the full collection of EUREC4A isotopic in situ data and guides readers to complementary remotely sensed water vapor isotope ratios.
Alba Lorente, Tobias Borsdorff, Mari C. Martinez-Velarte, Andre Butz, Otto P. Hasekamp, Lianghai Wu, and Jochen Landgraf
Atmos. Meas. Tech., 15, 6585–6603, https://doi.org/10.5194/amt-15-6585-2022, https://doi.org/10.5194/amt-15-6585-2022, 2022
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The TROPOspheric Monitoring Instrument (TROPOMI) performs observations over ocean in every orbit, enhancing the monitoring capabilities of methane from space. In the sun glint geometry the mirror-like reflection at the water surface provides a signal that is high enough to retrieve methane with high accuracy and precision. We present 4 years of methane concentrations over the ocean, and we assess its quality. We also show the importance of ocean observations to quantify total CH4 emissions.
Antje Inness, Ilse Aben, Melanie Ades, Tobias Borsdorff, Johannes Flemming, Luke Jones, Jochen Landgraf, Bavo Langerock, Philippe Nedelec, Mark Parrington, and Roberto Ribas
Atmos. Chem. Phys., 22, 14355–14376, https://doi.org/10.5194/acp-22-14355-2022, https://doi.org/10.5194/acp-22-14355-2022, 2022
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The Copernicus Atmosphere Monitoring Service (CAMS) provides daily global air quality forecasts to users worldwide. One of the species of interest is carbon monoxide (CO), an important trace gas in the atmosphere with anthropogenic and natural sources, produced by incomplete combustion, for example, by wildfires. This paper looks at how well CAMS can model CO in the atmosphere and shows that the fields can be improved when blending CO data from the TROPOMI instrument with the CAMS model.
Amy P. Sullivan, Rudra P. Pokhrel, Yingjie Shen, Shane M. Murphy, Darin W. Toohey, Teresa Campos, Jakob Lindaas, Emily V. Fischer, and Jeffrey L. Collett Jr.
Atmos. Chem. Phys., 22, 13389–13406, https://doi.org/10.5194/acp-22-13389-2022, https://doi.org/10.5194/acp-22-13389-2022, 2022
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During the WE-CAN (Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption and Nitrogen) study, brown carbon (BrC) absorption was measured on the NSF/NCAR C-130 aircraft using a particle-into-liquid sampler and photoacoustic aerosol absorption spectrometer. Approximately 45 % of the BrC absorption in wildfires was observed to be due to water-soluble species. The ratio of BrC absorption to WSOC or ΔCO showed no clear dependence on fire dynamics or the time since emission over 9 h.
Ilann Bourgeois, Jeff Peischl, J. Andrew Neuman, Steven S. Brown, Hannah M. Allen, Pedro Campuzano-Jost, Matthew M. Coggon, Joshua P. DiGangi, Glenn S. Diskin, Jessica B. Gilman, Georgios I. Gkatzelis, Hongyu Guo, Hannah A. Halliday, Thomas F. Hanisco, Christopher D. Holmes, L. Gregory Huey, Jose L. Jimenez, Aaron D. Lamplugh, Young Ro Lee, Jakob Lindaas, Richard H. Moore, Benjamin A. Nault, John B. Nowak, Demetrios Pagonis, Pamela S. Rickly, Michael A. Robinson, Andrew W. Rollins, Vanessa Selimovic, Jason M. St. Clair, David Tanner, Krystal T. Vasquez, Patrick R. Veres, Carsten Warneke, Paul O. Wennberg, Rebecca A. Washenfelder, Elizabeth B. Wiggins, Caroline C. Womack, Lu Xu, Kyle J. Zarzana, and Thomas B. Ryerson
Atmos. Meas. Tech., 15, 4901–4930, https://doi.org/10.5194/amt-15-4901-2022, https://doi.org/10.5194/amt-15-4901-2022, 2022
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Understanding fire emission impacts on the atmosphere is key to effective air quality management and requires accurate measurements. We present a comparison of airborne measurements of key atmospheric species in ambient air and in fire smoke. We show that most instruments performed within instrument uncertainties. In some cases, further work is needed to fully characterize instrument performance. Comparing independent measurements using different techniques is important to assess their accuracy.
Sara Martínez-Alonso, Merritt N. Deeter, Bianca C. Baier, Kathryn McKain, Helen Worden, Tobias Borsdorff, Colm Sweeney, and Ilse Aben
Atmos. Meas. Tech., 15, 4751–4765, https://doi.org/10.5194/amt-15-4751-2022, https://doi.org/10.5194/amt-15-4751-2022, 2022
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AirCore is a novel balloon sampling system that can measure, among others, vertical profiles of carbon monoxide (CO) from 25–30 km of altitude to near the surface. Our analyses of AirCore and satellite CO data show that AirCore profiles are suited for satellite data validation, the use of shorter aircraft vertical profiles in satellite validation results in small errors (1–3 percent points) mostly at 300 hPa and above, and the error introduced by clouds in TROPOMI land data is small (1–2 %).
Pieternel F. Levelt, Deborah C. Stein Zweers, Ilse Aben, Maite Bauwens, Tobias Borsdorff, Isabelle De Smedt, Henk J. Eskes, Christophe Lerot, Diego G. Loyola, Fabian Romahn, Trissevgeni Stavrakou, Nicolas Theys, Michel Van Roozendael, J. Pepijn Veefkind, and Tijl Verhoelst
Atmos. Chem. Phys., 22, 10319–10351, https://doi.org/10.5194/acp-22-10319-2022, https://doi.org/10.5194/acp-22-10319-2022, 2022
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Using the COVID-19 lockdown periods as an example, we show how Sentinel-5P/TROPOMI trace gas data (NO2, SO2, CO, HCHO and CHOCHO) can be used to understand impacts on air quality for regions and cities around the globe. We also provide information for both experienced and inexperienced users about how we created the data using state-of-the-art algorithms, where to get the data, methods taking meteorological and seasonal variability into consideration, and insights for future studies.
Matthias Schneider, Benjamin Ertl, Qiansi Tu, Christopher J. Diekmann, Farahnaz Khosrawi, Amelie N. Röhling, Frank Hase, Darko Dubravica, Omaira E. García, Eliezer Sepúlveda, Tobias Borsdorff, Jochen Landgraf, Alba Lorente, André Butz, Huilin Chen, Rigel Kivi, Thomas Laemmel, Michel Ramonet, Cyril Crevoisier, Jérome Pernin, Martin Steinbacher, Frank Meinhardt, Kimberly Strong, Debra Wunch, Thorsten Warneke, Coleen Roehl, Paul O. Wennberg, Isamu Morino, Laura T. Iraci, Kei Shiomi, Nicholas M. Deutscher, David W. T. Griffith, Voltaire A. Velazco, and David F. Pollard
Atmos. Meas. Tech., 15, 4339–4371, https://doi.org/10.5194/amt-15-4339-2022, https://doi.org/10.5194/amt-15-4339-2022, 2022
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We present a computationally very efficient method for the synergetic use of level 2 remote-sensing data products. We apply the method to IASI vertical profile and TROPOMI total column space-borne methane observations and thus gain sensitivity for the tropospheric methane partial columns, which is not achievable by the individual use of TROPOMI and IASI. These synergetic effects are evaluated theoretically and empirically by inter-comparisons to independent references of TCCON, AirCore, and GAW.
Jonas Hachmeister, Oliver Schneising, Michael Buchwitz, Alba Lorente, Tobias Borsdorff, John P. Burrows, Justus Notholt, and Matthias Buschmann
Atmos. Meas. Tech., 15, 4063–4074, https://doi.org/10.5194/amt-15-4063-2022, https://doi.org/10.5194/amt-15-4063-2022, 2022
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Sentinel-5P trace gas retrievals rely on elevation data in their calculations. Outdated or inaccurate data can lead to significant errors in e.g. dry-air mole fractions of methane (XCH4). We show that the use of inadequate elevation data leads to strong XCH4 anomalies in Greenland. Similar problems can be expected for other regions with inaccurate elevation data. However, we expect these to be more localized. We show that updating elevation data used in the retrieval solves this issue.
Andreas Schneider, Tobias Borsdorff, Joost aan de Brugh, Alba Lorente, Franziska Aemisegger, David Noone, Dean Henze, Rigel Kivi, and Jochen Landgraf
Atmos. Meas. Tech., 15, 2251–2275, https://doi.org/10.5194/amt-15-2251-2022, https://doi.org/10.5194/amt-15-2251-2022, 2022
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This paper presents an extended H₂O/HDO total column dataset from short-wave infrared measurements by TROPOMI including cloudy and clear-sky scenes. Coverage is tremendously increased compared to previous TROPOMI HDO datasets. The new dataset is validated against recent ground-based FTIR measurements from TCCON and against aircraft measurements over the ocean. The use of the new dataset is demonstrated with a case study of a cold air outbreak in January 2020.
Tobias Küchler, Stefan Noël, Heinrich Bovensmann, John Philip Burrows, Thomas Wagner, Christian Borger, Tobias Borsdorff, and Andreas Schneider
Atmos. Meas. Tech., 15, 297–320, https://doi.org/10.5194/amt-15-297-2022, https://doi.org/10.5194/amt-15-297-2022, 2022
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We applied the air-mass-corrected differential optical absorption spectroscopy (AMC-DOAS) method to derive total column water vapour (TCWV) from Sentinel-5P measurements and compared it to independent data sets. The correlation coefficients of typically more than 0.9 and the small deviations up to 2.5 kg m−2 reveal good agreement between our data product and other TCWV data sets. In particular for the different Sentinel-5P water vapour products, the deviations are around 1 kg m−2.
Dongwook Kim, Changmin Cho, Seokhan Jeong, Soojin Lee, Benjamin A. Nault, Pedro Campuzano-Jost, Douglas A. Day, Jason C. Schroder, Jose L. Jimenez, Rainer Volkamer, Donald R. Blake, Armin Wisthaler, Alan Fried, Joshua P. DiGangi, Glenn S. Diskin, Sally E. Pusede, Samuel R. Hall, Kirk Ullmann, L. Gregory Huey, David J. Tanner, Jack Dibb, Christoph J. Knote, and Kyung-Eun Min
Atmos. Chem. Phys., 22, 805–821, https://doi.org/10.5194/acp-22-805-2022, https://doi.org/10.5194/acp-22-805-2022, 2022
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CHOCHO was simulated using a 0-D box model constrained by measurements during the KORUS-AQ mission. CHOCHO concentration was high in large cities, aromatics being the most important precursors. Loss path to aerosol was the highest sink, contributing to ~ 20 % of secondary organic aerosol formation. Our work highlights that simple CHOCHO surface uptake approach is valid only for low aerosol conditions and more work is required to understand CHOCHO solubility in high-aerosol conditions.
Qiansi Tu, Frank Hase, Matthias Schneider, Omaira García, Thomas Blumenstock, Tobias Borsdorff, Matthias Frey, Farahnaz Khosrawi, Alba Lorente, Carlos Alberti, Juan J. Bustos, André Butz, Virgilio Carreño, Emilio Cuevas, Roger Curcoll, Christopher J. Diekmann, Darko Dubravica, Benjamin Ertl, Carme Estruch, Sergio Fabián León-Luis, Carlos Marrero, Josep-Anton Morgui, Ramón Ramos, Christian Scharun, Carsten Schneider, Eliezer Sepúlveda, Carlos Toledano, and Carlos Torres
Atmos. Chem. Phys., 22, 295–317, https://doi.org/10.5194/acp-22-295-2022, https://doi.org/10.5194/acp-22-295-2022, 2022
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We use different methane ground- and space-based remote sensing data sets for investigating the emission strength of three waste disposal sites close to Madrid. We present a method that uses wind-assigned anomalies for deriving emission strengths from satellite data and estimate their uncertainty to 9–14 %. The emission strengths estimated from the remote sensing data sets are significantly larger than the values published in the official register.
Dalrin Ampritta Amaladhasan, Claudia Heyn, Christopher R. Hoyle, Imad El Haddad, Miriam Elser, Simone M. Pieber, Jay G. Slowik, Antonio Amorim, Jonathan Duplissy, Sebastian Ehrhart, Vladimir Makhmutov, Ugo Molteni, Matti Rissanen, Yuri Stozhkov, Robert Wagner, Armin Hansel, Jasper Kirkby, Neil M. Donahue, Rainer Volkamer, Urs Baltensperger, Martin Gysel-Beer, and Andreas Zuend
Atmos. Chem. Phys., 22, 215–244, https://doi.org/10.5194/acp-22-215-2022, https://doi.org/10.5194/acp-22-215-2022, 2022
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We use a combination of models for gas-phase chemical reactions and equilibrium gas–particle partitioning of isoprene-derived secondary organic aerosols (SOAs) informed by dark ozonolysis experiments conducted in the CLOUD chamber. Our predictions cover high to low relative humidities (RHs) and quantify how SOA mass yields are enhanced at high RH as well as the impact of inorganic seeds of distinct hygroscopicities and acidities on the coupled partitioning of water and semi-volatile organics.
Debora Griffin, Chris A. McLinden, Enrico Dammers, Cristen Adams, Chelsea E. Stockwell, Carsten Warneke, Ilann Bourgeois, Jeff Peischl, Thomas B. Ryerson, Kyle J. Zarzana, Jake P. Rowe, Rainer Volkamer, Christoph Knote, Natalie Kille, Theodore K. Koenig, Christopher F. Lee, Drew Rollins, Pamela S. Rickly, Jack Chen, Lukas Fehr, Adam Bourassa, Doug Degenstein, Katherine Hayden, Cristian Mihele, Sumi N. Wren, John Liggio, Ayodeji Akingunola, and Paul Makar
Atmos. Meas. Tech., 14, 7929–7957, https://doi.org/10.5194/amt-14-7929-2021, https://doi.org/10.5194/amt-14-7929-2021, 2021
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Satellite-derived NOx emissions from biomass burning are estimated with TROPOMI observations. Two common emission estimation methods are applied, and sensitivity tests with model output were performed to determine the accuracy of these methods. The effect of smoke aerosols on TROPOMI NO2 columns is estimated and compared to aircraft observations from four different aircraft campaigns measuring biomass burning plumes in 2018 and 2019 in North America.
Tyler Wizenberg, Kimberly Strong, Kaley Walker, Erik Lutsch, Tobias Borsdorff, and Jochen Landgraf
Atmos. Meas. Tech., 14, 7707–7728, https://doi.org/10.5194/amt-14-7707-2021, https://doi.org/10.5194/amt-14-7707-2021, 2021
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CO is an important atmospheric gas that influences both air quality and the climate. Here, we compare CO measurements from TROPOMI with those from ACE-FTS and an Arctic ground-based FTS at Eureka, Nunavut, to further characterize the accuracy of TROPOMI measurements. CO columns from the instruments agree well but show larger differences at high latitudes. Despite this, the results fall within the TROPOMI accuracy target, indicating good data quality at high latitudes.
Lucía Caudillo, Birte Rörup, Martin Heinritzi, Guillaume Marie, Mario Simon, Andrea C. Wagner, Tatjana Müller, Manuel Granzin, Antonio Amorim, Farnoush Ataei, Rima Baalbaki, Barbara Bertozzi, Zoé Brasseur, Randall Chiu, Biwu Chu, Lubna Dada, Jonathan Duplissy, Henning Finkenzeller, Loïc Gonzalez Carracedo, Xu-Cheng He, Victoria Hofbauer, Weimeng Kong, Houssni Lamkaddam, Chuan P. Lee, Brandon Lopez, Naser G. A. Mahfouz, Vladimir Makhmutov, Hanna E. Manninen, Ruby Marten, Dario Massabò, Roy L. Mauldin, Bernhard Mentler, Ugo Molteni, Antti Onnela, Joschka Pfeifer, Maxim Philippov, Ana A. Piedehierro, Meredith Schervish, Wiebke Scholz, Benjamin Schulze, Jiali Shen, Dominik Stolzenburg, Yuri Stozhkov, Mihnea Surdu, Christian Tauber, Yee Jun Tham, Ping Tian, António Tomé, Steffen Vogt, Mingyi Wang, Dongyu S. Wang, Stefan K. Weber, André Welti, Wang Yonghong, Wu Yusheng, Marcel Zauner-Wieczorek, Urs Baltensperger, Imad El Haddad, Richard C. Flagan, Armin Hansel, Kristina Höhler, Jasper Kirkby, Markku Kulmala, Katrianne Lehtipalo, Ottmar Möhler, Harald Saathoff, Rainer Volkamer, Paul M. Winkler, Neil M. Donahue, Andreas Kürten, and Joachim Curtius
Atmos. Chem. Phys., 21, 17099–17114, https://doi.org/10.5194/acp-21-17099-2021, https://doi.org/10.5194/acp-21-17099-2021, 2021
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We performed experiments in the CLOUD chamber at CERN at low temperatures to simulate new particle formation in the upper free troposphere (at −30 ºC and −50 ºC). We measured the particle and gas phase and found that most of the compounds present in the gas phase are detected as well in the particle phase. The major compounds in the particles are C8–10 and C18–20. Specifically, we showed that C5 and C15 compounds are detected in a mixed system with isoprene and α-pinene at −30 ºC, 20 % RH.
Sharmine Akter Simu, Yuzo Miyazaki, Eri Tachibana, Henning Finkenzeller, Jérôme Brioude, Aurélie Colomb, Olivier Magand, Bert Verreyken, Stephanie Evan, Rainer Volkamer, and Trissevgeni Stavrakou
Atmos. Chem. Phys., 21, 17017–17029, https://doi.org/10.5194/acp-21-17017-2021, https://doi.org/10.5194/acp-21-17017-2021, 2021
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The tropical Indian Ocean (IO) is expected to be a significant source of water-soluble organic carbon (WSOC), which is relevant to cloud formation. Our study showed that marine secondary organic formation dominantly contributed to the aerosol WSOC mass at the high-altitude observatory in the southwest IO in the wet season in both marine boundary layer and free troposphere (FT). This suggests that the effect of marine secondary sources is important up to FT, a process missing in climate models.
Arseniy Karagodin-Doyennel, Eugene Rozanov, Timofei Sukhodolov, Tatiana Egorova, Alfonso Saiz-Lopez, Carlos A. Cuevas, Rafael P. Fernandez, Tomás Sherwen, Rainer Volkamer, Theodore K. Koenig, Tanguy Giroud, and Thomas Peter
Geosci. Model Dev., 14, 6623–6645, https://doi.org/10.5194/gmd-14-6623-2021, https://doi.org/10.5194/gmd-14-6623-2021, 2021
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Here, we present the iodine chemistry module in the SOCOL-AERv2 model. The obtained iodine distribution demonstrated a good agreement when validated against other simulations and available observations. We also estimated the iodine influence on ozone in the case of present-day iodine emissions, the sensitivity of ozone to doubled iodine emissions, and when considering only organic or inorganic iodine sources. The new model can be used as a tool for further studies of iodine effects on ozone.
Linghan Zeng, Amy P. Sullivan, Rebecca A. Washenfelder, Jack Dibb, Eric Scheuer, Teresa L. Campos, Joseph M. Katich, Ezra Levin, Michael A. Robinson, and Rodney J. Weber
Atmos. Meas. Tech., 14, 6357–6378, https://doi.org/10.5194/amt-14-6357-2021, https://doi.org/10.5194/amt-14-6357-2021, 2021
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Three online systems for measuring water-soluble brown carbon are compared. A mist chamber and two different particle-into-liquid samplers were deployed on separate research aircraft targeting wildfires and followed a similar detection method using a long-path liquid waveguide with a spectrometer to measure the light absorption from 300 to 700 nm. Detection limits, signal hysteresis and other sampling issues are compared, and further improvements of these liquid-based systems are provided.
Mahesh Kumar Sha, Bavo Langerock, Jean-François L. Blavier, Thomas Blumenstock, Tobias Borsdorff, Matthias Buschmann, Angelika Dehn, Martine De Mazière, Nicholas M. Deutscher, Dietrich G. Feist, Omaira E. García, David W. T. Griffith, Michel Grutter, James W. Hannigan, Frank Hase, Pauli Heikkinen, Christian Hermans, Laura T. Iraci, Pascal Jeseck, Nicholas Jones, Rigel Kivi, Nicolas Kumps, Jochen Landgraf, Alba Lorente, Emmanuel Mahieu, Maria V. Makarova, Johan Mellqvist, Jean-Marc Metzger, Isamu Morino, Tomoo Nagahama, Justus Notholt, Hirofumi Ohyama, Ivan Ortega, Mathias Palm, Christof Petri, David F. Pollard, Markus Rettinger, John Robinson, Sébastien Roche, Coleen M. Roehl, Amelie N. Röhling, Constantina Rousogenous, Matthias Schneider, Kei Shiomi, Dan Smale, Wolfgang Stremme, Kimberly Strong, Ralf Sussmann, Yao Té, Osamu Uchino, Voltaire A. Velazco, Corinne Vigouroux, Mihalis Vrekoussis, Pucai Wang, Thorsten Warneke, Tyler Wizenberg, Debra Wunch, Shoma Yamanouchi, Yang Yang, and Minqiang Zhou
Atmos. Meas. Tech., 14, 6249–6304, https://doi.org/10.5194/amt-14-6249-2021, https://doi.org/10.5194/amt-14-6249-2021, 2021
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This paper presents, for the first time, Sentinel-5 Precursor methane and carbon monoxide validation results covering a period from November 2017 to September 2020. For this study, we used global TCCON and NDACC-IRWG network data covering a wide range of atmospheric and surface conditions across different terrains. We also show the influence of a priori alignment, smoothing uncertainties and the sensitivity of the validation results towards the application of advanced co-location criteria.
Mao Xiao, Christopher R. Hoyle, Lubna Dada, Dominik Stolzenburg, Andreas Kürten, Mingyi Wang, Houssni Lamkaddam, Olga Garmash, Bernhard Mentler, Ugo Molteni, Andrea Baccarini, Mario Simon, Xu-Cheng He, Katrianne Lehtipalo, Lauri R. Ahonen, Rima Baalbaki, Paulus S. Bauer, Lisa Beck, David Bell, Federico Bianchi, Sophia Brilke, Dexian Chen, Randall Chiu, António Dias, Jonathan Duplissy, Henning Finkenzeller, Hamish Gordon, Victoria Hofbauer, Changhyuk Kim, Theodore K. Koenig, Janne Lampilahti, Chuan Ping Lee, Zijun Li, Huajun Mai, Vladimir Makhmutov, Hanna E. Manninen, Ruby Marten, Serge Mathot, Roy L. Mauldin, Wei Nie, Antti Onnela, Eva Partoll, Tuukka Petäjä, Joschka Pfeifer, Veronika Pospisilova, Lauriane L. J. Quéléver, Matti Rissanen, Siegfried Schobesberger, Simone Schuchmann, Yuri Stozhkov, Christian Tauber, Yee Jun Tham, António Tomé, Miguel Vazquez-Pufleau, Andrea C. Wagner, Robert Wagner, Yonghong Wang, Lena Weitz, Daniela Wimmer, Yusheng Wu, Chao Yan, Penglin Ye, Qing Ye, Qiaozhi Zha, Xueqin Zhou, Antonio Amorim, Ken Carslaw, Joachim Curtius, Armin Hansel, Rainer Volkamer, Paul M. Winkler, Richard C. Flagan, Markku Kulmala, Douglas R. Worsnop, Jasper Kirkby, Neil M. Donahue, Urs Baltensperger, Imad El Haddad, and Josef Dommen
Atmos. Chem. Phys., 21, 14275–14291, https://doi.org/10.5194/acp-21-14275-2021, https://doi.org/10.5194/acp-21-14275-2021, 2021
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Experiments at CLOUD show that in polluted environments new particle formation (NPF) is largely driven by the formation of sulfuric acid–base clusters, stabilized by amines, high ammonia concentrations or lower temperatures. While oxidation products of aromatics can nucleate, they play a minor role in urban NPF. Our experiments span 4 orders of magnitude variation of observed NPF rates in ambient conditions. We provide a framework based on NPF and growth rates to interpret ambient observations.
Xuan Wang, Daniel J. Jacob, William Downs, Shuting Zhai, Lei Zhu, Viral Shah, Christopher D. Holmes, Tomás Sherwen, Becky Alexander, Mathew J. Evans, Sebastian D. Eastham, J. Andrew Neuman, Patrick R. Veres, Theodore K. Koenig, Rainer Volkamer, L. Gregory Huey, Thomas J. Bannan, Carl J. Percival, Ben H. Lee, and Joel A. Thornton
Atmos. Chem. Phys., 21, 13973–13996, https://doi.org/10.5194/acp-21-13973-2021, https://doi.org/10.5194/acp-21-13973-2021, 2021
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Halogen radicals have a broad range of implications for tropospheric chemistry, air quality, and climate. We present a new mechanistic description and comprehensive simulation of tropospheric halogens in a global 3-D model and compare the model results with surface and aircraft measurements. We find that halogen chemistry decreases the global tropospheric burden of ozone by 11 %, NOx by 6 %, and OH by 4 %.
Cited articles
Borsdorff, T., Hasekamp, O. P., Wassmann, A., and Landgraf, J.: Insights into Tikhonov regularization: application to trace gas column retrieval and the efficient calculation of total column averaging kernels, Atmos. Meas. Tech., 7, 523–535, https://doi.org/10.5194/amt-7-523-2014, 2014. a, b, c
Borsdorff, T., aan de Brugh, J., Hu, H., Hasekamp, O., Sussmann, R., Rettinger, M., Hase, F., Gross, J., Schneider, M., Garcia, O., Stremme, W., Grutter, M., Feist, D. G., Arnold, S. G., De Mazière, M., Kumar Sha, M., Pollard, D. F., Kiel, M., Roehl, C., Wennberg, P. O., Toon, G. C., and Landgraf, J.: Mapping carbon monoxide pollution from space down to city scales with daily global coverage, Atmos. Meas. Tech., 11, 5507–5518, https://doi.org/10.5194/amt-11-5507-2018, 2018a. a, b
Borsdorff, T., de Brugh, J. A., Hu, H., Aben, I., Hasekamp, O., and Landgraf, J.: Measuring Carbon Monoxide With TROPOMI: First Results and a Comparison With ECMWF‐IFS Analysis Data, Geophys. Res. Lett., 45, 2826–2832, https://doi.org/10.1002/2018GL077045, 2018b. a, b
Borsdorff, T., aan de Brugh, J., Pandey, S., Hasekamp, O., Aben, I., Houweling, S., and Landgraf, J.: Carbon monoxide air pollution on sub-city scales and along arterial roads detected by the Tropospheric Monitoring Instrument, Atmos. Chem. Phys., 19, 3579–3588, https://doi.org/10.5194/acp-19-3579-2019, 2019. a, b, c
Borsdorff, T., García Reynoso, A., Maldonado, G., Mar-Morales, B., Stremme, W., Grutter, M., and Landgraf, J.: Monitoring CO emissions of the metropolis Mexico City using TROPOMI CO observations, Atmos. Chem. Phys., 20, 15761–15774, https://doi.org/10.5194/acp-20-15761-2020, 2020. a
Clerbaux, C., Boynard, A., Clarisse, L., George, M., Hadji-Lazaro, J., Herbin, H., Hurtmans, D., Pommier, M., Razavi, A., Turquety, S., Wespes, C., and Coheur, P.-F.: Monitoring of atmospheric composition using the thermal infrared IASI/MetOp sounder, Atmos. Chem. Phys., 9, 6041–6054, https://doi.org/10.5194/acp-9-6041-2009, 2009. a
Cordero, P. R. F., Bayly, K., Man Leung, P., Huang, C., Islam, Z. F., Schittenhelm, R. B., King, G. M., and Greening, C.: Atmospheric carbon monoxide oxidation is a widespread mechanism supporting microbial survival, The ISME Journal, 13, 2868–2881, https://doi.org/10.1038/s41396-019-0479-8, 2019. a
Deeter, M., Francis, G., Gille, J., Mao, D., Martínez-Alonso, S., Worden, H., Ziskin, D., Drummond, J., Commane, R., Diskin, G., and McKain, K.: The MOPITT Version 9 CO product: sampling enhancements and validation, Atmos. Meas. Tech., 15, 2325–2344, https://doi.org/10.5194/amt-15-2325-2022, 2022. a
Deeter, M. N., Martínez-Alonso, S., Edwards, D. P., Emmons, L. K., Gille, J. C., Worden, H. M., Pittman, J. V., Daube, B. C., and Wofsy, S. C.: Validation of MOPITT Version 5 thermal-infrared, near-infrared, and multispectral carbon monoxide profile retrievals for 2000–2011, J. Geophys. Res.-Atmos., 118, 6710–6725, https://doi.org/10.1002/jgrd.50272, 2013. a
ECMWF: CAMS global atmospheric composition forecasts, ECMWF [data set], https://ads.atmosphere.copernicus.
eu/cdsapp#!/dataset/cams-global-atmospheric-composition-forecasts?tab=overview, last access: 7 June 2023. a
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Gerbig, C., Schmitgen, S., Kley, D., Volz-Thomas, A., Dewey, K., and Haaks, D.: An improved fast-response vacuum-UV resonance fluorescence CO instrument, J. Geophys. Res.-Atmos., 104, 1699–1704, https://doi.org/10.1029/1998JD100031, 1999. a
Gloudemans, A. M. S., de Laat, A. T. J., Schrijver, H., Aben, I., Meirink, J. F., and van der Werf, G. R.: SCIAMACHY CO over land and oceans: 2003–2007 interannual variability, Atmos. Chem. Phys., 9, 3799–3813, https://doi.org/10.5194/acp-9-3799-2009, 2009. a
Hansen, P. C. and O'Leary, D. P.: The Use of the L-Curve in the Regularization of Discrete Ill-Posed Problems, SIAM J. Sci. Comput., 14, 1487–1503, https://doi.org/10.1137/0914086, 1993. a
Holloway, T., Levy, H., and Kasibhatla, P.: Global distribution of carbon monoxide, J. Geophys. Res.-Atmos., 105, 12123–12147, https://doi.org/10.1029/1999jd901173, 2000. a
Inness, A., Blechschmidt, A.-M., Bouarar, I., Chabrillat, S., Crepulja, M., Engelen, R. J., Eskes, H., Flemming, J., Gaudel, A., Hendrick, F., Huijnen, V., Jones, L., Kapsomenakis, J., Katragkou, E., Keppens, A., Langerock, B., de Mazière, M., Melas, D., Parrington, M., Peuch, V. H., Razinger, M., Richter, A., Schultz, M. G., Suttie, M., Thouret, V., Vrekoussis, M., Wagner, A., and Zerefos, C.: Data assimilation of satellite-retrieved ozone, carbon monoxide and nitrogen dioxide with ECMWF's Composition-IFS, Atmos. Chem. Phys., 15, 5275–5303, https://doi.org/10.5194/acp-15-5275-2015, 2015. a, b
Inness, A., Flemming, J., Heue, K.-P., Lerot, C., Loyola, D., Ribas, R., Valks, P., van Roozendael, M., Xu, J., and Zimmer, W.: Monitoring and assimilation tests with TROPOMI data in the CAMS system: near-real-time total column ozone, Atmos. Chem. Phys., 19, 3939–3962, https://doi.org/10.5194/acp-19-3939-2019, 2019. a
Inness, A., Aben, I., Ades, M., Borsdorff, T., Flemming, J., Jones, L., Landgraf, J., Langerock, B., Nedelec, P., Parrington, M., and Ribas, R.: Assimilation of S5P/TROPOMI carbon monoxide data with the global CAMS near-real-time system, Atmos. Chem. Phys., 22, 14355–14376, https://doi.org/10.5194/acp-22-14355-2022, 2022. a
Krol, M., Houweling, S., Bregman, B., van den Broek, M., Segers, A., van Velthoven, P., Peters, W., Dentener, F., and Bergamaschi, P.: The two-way nested global chemistry-transport zoom model TM5: algorithm and applications, Atmos. Chem. Phys., 5, 417–432, https://doi.org/10.5194/acp-5-417-2005, 2005. a, b
Landgraf, J., aan de Brugh, J., Scheepmaker, R., Borsdorff, T., Hu, H., Houweling, S., Butz, A., Aben, I., and Hasekamp, O.: Carbon monoxide total column retrievals from TROPOMI shortwave infrared measurements, Atmos. Meas. Tech., 9, 4955–4975, https://doi.org/10.5194/amt-9-4955-2016, 2016. a, b
Pommier, M., McLinden, C. A., and Deeter, M.: Relative changes in CO emissions over megacities based on observations from space, Geophys. Res.
Lett., 40, 3766–3771, https://doi.org/10.1002/grl.50704, 2013. a
Rowe, J. P., Zarzana, K. J., Kille, N., Borsdorff, T., Goudar, M., Lee, C. F., Koenig, T. K., Romero-Alvarez, J., Campos, T., Knote, C., Theys, N., Landgraf, J., and Volkamer, R.: Carbon Monoxide in Optically Thick Wildfire Smoke: Evaluating TROPOMI Using CU Airborne SOF Column Observations, ACS Earth Space Chem., 6, 1799–1812, https://doi.org/10.1021/acsearthspacechem.2c00048, 2022. a
Schneising, O., Buchwitz, M., Reuter, M., Bovensmann, H., and Burrows, J. P.: Severe Californian wildfires in November 2018 observed from space: the carbon monoxide perspective, Atmos. Chem. Phys., 20, 3317–3332, https://doi.org/10.5194/acp-20-3317-2020, 2020. a
Sha, M. K., Langerock, B., Blavier, J.-F. L., Blumenstock, T., Borsdorff, T., Buschmann, M., Dehn, A., De Mazière, M., Deutscher, N. M., Feist, D. G., García, O. E., Griffith, D. W. T., Grutter, M., Hannigan, J. W., Hase, F., Heikkinen, P., Hermans, C., Iraci, L. T., Jeseck, P., Jones, N., Kivi, R., Kumps, N., Landgraf, J., Lorente, A., Mahieu, E., Makarova, M. V., Mellqvist, J., Metzger, J.-M., Morino, I., Nagahama, T., Notholt, J., Ohyama, H., Ortega, I., Palm, M., Petri, C., Pollard, D. F., Rettinger, M., Robinson, J., Roche, S., Roehl, C. M., Röhling, A. N., Rousogenous, C., Schneider, M., Shiomi, K., Smale, D., Stremme, W., Strong, K., Sussmann, R., Té, Y., Uchino, O., Velazco, V. A., Vigouroux, C., Vrekoussis, M., Wang, P., Warneke, T., Wizenberg, T., Wunch, D., Yamanouchi, S., Yang, Y., and Zhou, M.: Validation of methane and carbon monoxide from Sentinel-5 Precursor using TCCON and NDACC-IRWG stations, Atmos. Meas. Tech., 14, 6249–6304, https://doi.org/10.5194/amt-14-6249-2021, 2021.
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Short summary
ECMWF plans to assimilate TROPOMI CO with their CAMS-IFS model. This will constrain the total column and the vertical CO distribution of the model. To show this, we combine individual TROPOMI CO column retrievals with different vertical sensitivities and obtain a vertical CO concentration profile. We test the approach on three CO pollution events in comparison with CAMS-IFS simulations that do not assimilate TROPOMI CO data and in situ airborne measurements of the BB-FLUX campaign.
ECMWF plans to assimilate TROPOMI CO with their CAMS-IFS model. This will constrain the total...
