Articles | Volume 19, issue 1
https://doi.org/10.5194/amt-19-333-2026
© Author(s) 2026. 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-19-333-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Jan 2026
Research article |
| 16 Jan 2026
| 16 Jan 2026
Quantifying CH4 point source emissions with airborne remote sensing: first results from AVIRIS-4
Empa, Laboratory for Air Pollution/Environmental Technology, Ueberlandstrasse 129, 8600 Duebendorf, Switzerland
Department of Geography, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland
Marius Vögtli
Department of Geography, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland
Andreas Hueni
Department of Geography, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland
Audrey McManemin
Department of Energy Science & Engineering, Stanford University, USA
Adam R. Brandt
Department of Energy Science & Engineering, Stanford University, USA
Catherine Juéry
Air Quality Laboratory, TotalEnergies, France
Vincent Blandin
TotalEnergies Anomalies Detection Initiatives (TADI), TotalEnergies, France
Dominik Brunner
Empa, Laboratory for Air Pollution/Environmental Technology, Ueberlandstrasse 129, 8600 Duebendorf, Switzerland
Empa, Laboratory for Air Pollution/Environmental Technology, Ueberlandstrasse 129, 8600 Duebendorf, Switzerland
Related authors
Sandro Meier, Erik F. M. Koene, Maarten Krol, Dominik Brunner, Alexander Damm, and Gerrit Kuhlmann
Atmos. Chem. Phys., 24, 7667–7686, https://doi.org/10.5194/acp-24-7667-2024, https://doi.org/10.5194/acp-24-7667-2024, 2024
Short summary
Short summary
Nitrogen oxides (NOx = NO + NO2) are important air pollutants. This study addresses the challenge of accurately estimating NOx emissions from NO2 satellite observations. We develop a realistic model to convert NO2 to NOx by using simulated plumes from various power plants. We apply the model to satellite NO2 observations, significantly reducing biases in estimated NOx emissions. The study highlights the potential for a consistent, high-resolution estimation of NOx emissions using satellite data.
Gerrit Kuhlmann, Erik Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
Geosci. Model Dev., 17, 4773–4789, https://doi.org/10.5194/gmd-17-4773-2024, https://doi.org/10.5194/gmd-17-4773-2024, 2024
Short summary
Short summary
We present a Python software library for data-driven emission quantification (ddeq). It can be used to determine the emissions of hot spots (cities, power plants and industry) from remote sensing images using different methods. ddeq can be extended for new datasets and methods, providing a powerful community tool for users and developers. The application of the methods is shown using Jupyter notebooks included in the library.
Gerrit Kuhlmann, Erik Franciscus Maria Koene, Chloe Natasha Schooling, Paul Ian Palmer, Òscar Collado López, and Marc Guevara
EGUsphere, https://doi.org/10.5194/egusphere-2025-6057, https://doi.org/10.5194/egusphere-2025-6057, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
We used satellite measurements of nitrogen dioxide (NO2) to estimate top-down nitrogen oxide (NOx) emissions from power plants in Europe and the United States. Our study shows that these observations can track seasonal and short-term changes in emissions and agree well with bottom-up estimates. This approach offers a promising way to monitor NOx and indirectly carbon dioxide (CO2) emissions, supporting anthropogenic emissions monitoring systems.
Nikolai Ponomarev, Michael Steiner, Erik Koene, Pascal Rubli, Stuart Grange, Lionel Constantin, Michel Ramonet, Leslie David, Arash Hamzehloo, Lukas Emmenegger, and Dominik Brunner
Atmos. Chem. Phys., 26, 547–570, https://doi.org/10.5194/acp-26-547-2026, https://doi.org/10.5194/acp-26-547-2026, 2026
Short summary
Short summary
Urban inversions are gaining increasing attention, as cities are major contributors to anthropogenic emissions, making accurate emission estimates at this scale essential for supporting climate action plans and verifying reported emission reductions. We estimated carbon dioxide emissions in Zurich and Paris over one year by combining atmospheric observations with mesoscale model simulations. Our study shows how factors like city size, terrain, and measurement methods affect emission estimates.
Xin Zhang, Joannes D. Maasakkers, Tobias A. de Jong, Paul Tol, Frances Reuland, Adam R. Brandt, Eric A. Kort, Taylor J. Adams, and Ilse Aben
EGUsphere, https://doi.org/10.5194/egusphere-2025-6127, https://doi.org/10.5194/egusphere-2025-6127, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
Reducing emissions of greenhouse gases such as methane and carbon dioxide is essential for addressing climate change. We developed HyperGas, an open tool that uses hyperspectral satellite images to retrieve and detect greenhouse gas plumes. It helps scientists locate emission sources, estimate their strength, and examine uncertainties through an easy workflow and visual app. Our goal is to make tracking human-made emissions more accurate and accessible, supporting better climate monitoring.
Eleftherios Ioannidis, Antoon Meesters, Michael Steiner, Dominik Brunner, Friedemann Reum, Isabelle Pison, Antoine Berchet, Rona Thompson, Espen Sollum, Frank-Thomas Koch, Christoph Gerbig, Fenjuan Wang, Shamil Maksyutov, Aki Tsuruta, Maria Tenkanen, Tuula Aalto, Guillaume Monteil, Hong Lin, Ge Ren, Marko Scholze, and Sander Houweling
Earth Syst. Sci. Data, 18, 167–198, https://doi.org/10.5194/essd-18-167-2026, https://doi.org/10.5194/essd-18-167-2026, 2026
Short summary
Short summary
This paper describes a detailed study on CH4 European emissions, using different methodologies (9 total inverse models). The study spans over 15 years and provides detailed information on European CH4 emission trends and seasonality, using in-situ data, including Integrated Carbon Observation System (ICOS) network. Our results highlight the importance of improving details in the inversion setup, such as the treatment of lateral boundary conditions to narrow the uncertainty ranges further.
Riley Duren, Daniel Cusworth, Alana Ayasse, Katherine Howell, Alex Diamond, Tia Scarpelli, Jinsol Kim, Kelly O'neill, Judy Lai-Norling, Andrew Thorpe, Sander R. Zandbergen, Lucas Shaw, Mark Keremedjiev, Jeff Guido, Paul Giuliano, Malkam Goldstein, Ravi Nallapu, Geert Barentsen, David R. Thompson, Keely Roth, Daniel Jensen, Michael Eastwood, Frances Reuland, Taylor Adams, Adam Brandt, Eric A. Kort, James Mason, and Robert O. Green
Atmos. Meas. Tech., 18, 6933–6958, https://doi.org/10.5194/amt-18-6933-2025, https://doi.org/10.5194/amt-18-6933-2025, 2025
Short summary
Short summary
We describe the Carbon Mapper emissions monitoring system including methane and carbon dioxide observations from the constellation of Tanager hyperspectral satellites, a global monitoring strategy optimized for enabling mitigation impact at the scale of individual facilities, and a data platform that delivers timely and transparent information for diverse stakeholders. We present early findings from Tanager-1 including the use of our data to locate and repair a leaking oil and gas pipeline.
Dominik Brunner, Ivo Suter, Leonie Bernet, Lionel Constantin, Stuart K. Grange, Pascal Rubli, Junwei Li, Jia Chen, Alessandro Bigi, and Lukas Emmenegger
Atmos. Chem. Phys., 25, 14387–14410, https://doi.org/10.5194/acp-25-14387-2025, https://doi.org/10.5194/acp-25-14387-2025, 2025
Short summary
Short summary
To support the city of Zurich in tracking its path to net-zero greenhouse gas emissions planned to be reached by 2040, a CO2 emission monitoring system was established. The system combines a dense network of CO2 sensors with a high-resolution atmospheric transport model GRAMM/GRAL. This study presents the setup of the model together with its numerous inputs and evaluates its performance in comparison with observations from the CO2 sensor network.
Rainer Hilland, Josh Hashemi, Stavros Stagakis, Dominik Brunner, Lionel Constantin, Natascha Kljun, Ann-Kristin Kunz, Betty Molinier, Samuel Hammer, Lukas Emmenegger, and Andreas Christen
Atmos. Chem. Phys., 25, 14279–14299, https://doi.org/10.5194/acp-25-14279-2025, https://doi.org/10.5194/acp-25-14279-2025, 2025
Short summary
Short summary
We present a study of simultaneously measured fluxes of carbon dioxide (CO2) and co-emitted species in the city of Zurich. Flux measurements of CO2 alone cannot be attributed to specific emission sectors, such as road transport or residential heating. We present a model which uses the measured ratios of CO2 to carbon monoxide (CO) and nitrogen oxides (NOx) as well as sector-specific reference ratios, to attribute measured fluxes to their emission sectors.
Erik Franciscus Maria Koene, Gerrit Kuhlmann, and Dominik Brunner
EGUsphere, https://doi.org/10.5194/egusphere-2025-4477, https://doi.org/10.5194/egusphere-2025-4477, 2025
Short summary
Short summary
We developed methods to reduce noise in satellite images that track air pollution, good for making faint emission signals easier to detect. By using clearer measurements of a related gas, our techniques improve image quality by up to 60 percent, allowing more accurate identification of pollution sources. Tested with simulated and real satellite data, this approach could enhance monitoring of emissions and support better environmental decisions.
Gholam Ali Hoshyaripour, Andreas Baer, Sascha Bierbauer, Julia Bruckert, Dominik Brunner, Jochen Foerstner, Arash Hamzehloo, Valentin Hanft, Corina Keller, Martina Klose, Pankaj Kumar, Patrick Ludwig, Enrico Metzner, Lisa Muth, Andreas Pauling, Nikolas Porz, Thomas Reddmann, Luca Reißig, Roland Ruhnke, Khompat Satitkovitchai, Axel Seifert, Miriam Sinnhuber, Michael Steiner, Stefan Versick, Heike Vogel, Michael Weimer, Sven Werchner, and Corinna Hoose
EGUsphere, https://doi.org/10.5194/egusphere-2025-3400, https://doi.org/10.5194/egusphere-2025-3400, 2025
Short summary
Short summary
This paper presents recent advances in ICON-ART, a modeling system that simulates atmospheric composition—such as gases and particles—and their interactions with weather and climate. By integrating updated chemistry, emissions, and aerosol processes, ICON-ART enables detailed, scale-spanning simulations. It supports both scientific research and operational forecasts, contributing to improved air quality and climate predictions.
Audrey McManemin, Catherine Juéry, Vincent Blandin, James L. France, Philippine Burdeau, and Adam R. Brandt
EGUsphere, https://doi.org/10.5194/egusphere-2025-3793, https://doi.org/10.5194/egusphere-2025-3793, 2025
Short summary
Short summary
This experiment tested the ability of different technologies to detect and measure methane emissions. Participating teams used satellites, drones, and other systems to estimate methane leak rates without knowing the true rate. Some systems were more accurate than others, and wind and other environmental conditions made measurements harder. Our findings help improve these tools and support efforts to track and reduce methane emissions as new environmental rules take shape in Europe and beyond.
Luce Creman, Stuart K. Grange, Pascal Rubli, Andrea Fischer, Dominik Brunner, Christoph Hueglin, Lukas Emmenegger, and Leonie Bernet
EGUsphere, https://doi.org/10.5194/egusphere-2025-3425, https://doi.org/10.5194/egusphere-2025-3425, 2025
Short summary
Short summary
ZiCOS-L is a network of low-cost sensors in Zurich (Switzerland) to monitor carbon dioxide (CO2) concentrations. After correcting for drift and checking the sensor performance, we found that local factors like traffic, public events and vegetation affect CO2 levels. Even though the sensors have higher uncertainties than other sensors, the lower cost allows for a denser network with detailed insights into CO2 levels across the city, helping cities track emissions and support climate action plans.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 18, 3607–3622, https://doi.org/10.5194/gmd-18-3607-2025, https://doi.org/10.5194/gmd-18-3607-2025, 2025
Short summary
Short summary
We developed a deep learning method to estimate CO2 emissions from power plants using satellite images. Trained and validated on simulated data, our model accurately predicts emissions despite challenges like cloud cover. When applied to real OCO3 satellite images, the results closely match reported emissions. This study shows that neural networks trained on simulations can effectively analyse real satellite data, offering a new way to monitor CO2 emissions from space.
Gerrit Kuhlmann, Foteini Stavropoulou, Stefan Schwietzke, Daniel Zavala-Araiza, Andrew Thorpe, Andreas Hueni, Lukas Emmenegger, Andreea Calcan, Thomas Röckmann, and Dominik Brunner
Atmos. Chem. Phys., 25, 5371–5385, https://doi.org/10.5194/acp-25-5371-2025, https://doi.org/10.5194/acp-25-5371-2025, 2025
Short summary
Short summary
A measurement campaign in 2019 found that methane emissions from oil and gas in Romania were significantly higher than reported. In 2021, our follow-up campaign using airborne remote sensing showed a marked decreases in emissions by 20 %–60 % due to improved infrastructure. The study highlights the importance of measurement-based emission monitoring and illustrates the value of a multi-scale assessment integrating ground-based observations with large-scale airborne remote sensing campaigns.
Stavros Stagakis, Dominik Brunner, Junwei Li, Leif Backman, Anni Karvonen, Lionel Constantin, Leena Järvi, Minttu Havu, Jia Chen, Sophie Emberger, and Liisa Kulmala
Biogeosciences, 22, 2133–2161, https://doi.org/10.5194/bg-22-2133-2025, https://doi.org/10.5194/bg-22-2133-2025, 2025
Short summary
Short summary
The balance between CO2 uptake and emissions from urban green areas is still not well understood. This study evaluated for the first time the urban park CO2 exchange simulations with four different types of biosphere model by comparing them with observations. Even though some advantages and disadvantages of the different model types were identified, there was no strong evidence that more complex models performed better than simple ones.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
Short summary
Short summary
The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Stuart K. Grange, Pascal Rubli, Andrea Fischer, Dominik Brunner, Christoph Hueglin, and Lukas Emmenegger
Atmos. Chem. Phys., 25, 2781–2806, https://doi.org/10.5194/acp-25-2781-2025, https://doi.org/10.5194/acp-25-2781-2025, 2025
Short summary
Short summary
Carbon dioxide (CO2) is a very important atmospheric pollutant, and to better understand the gas's source and sink dynamics, a mid-cost sensor network hosting 26 sites was deployed in and around Zurich, Switzerland. The sensor measurement performance was quantified, and natural and anthropogenic CO2 emission sources were explored with a focus on what drives high CO2 levels. The observations will be used further by others to validate what is thought to be known about CO2 emissions in the region.
Hossein Maazallahi, Foteini Stavropoulou, Samuel Jonson Sutanto, Michael Steiner, Dominik Brunner, Mariano Mertens, Patrick Jöckel, Antoon Visschedijk, Hugo Denier van der Gon, Stijn Dellaert, Nataly Velandia Salinas, Stefan Schwietzke, Daniel Zavala-Araiza, Sorin Ghemulet, Alexandru Pana, Magdalena Ardelean, Marius Corbu, Andreea Calcan, Stephen A. Conley, Mackenzie L. Smith, and Thomas Röckmann
Atmos. Chem. Phys., 25, 1497–1511, https://doi.org/10.5194/acp-25-1497-2025, https://doi.org/10.5194/acp-25-1497-2025, 2025
Short summary
Short summary
This article presents insights from airborne in situ measurements collected during the ROmanian Methane Emissions from Oil and gas (ROMEO) campaign supported by two models. Results reveal Romania's oil and gas methane emissions were significantly under-reported to the United Nations Framework Convention on Climate Change (UNFCCC) in 2019. A large underestimation was also found in the Emissions Database for Global Atmospheric Research (EDGAR) v7.0 for the study domain in the same year.
Diego Santaren, Janne Hakkarainen, Gerrit Kuhlmann, Erik Koene, Frédéric Chevallier, Iolanda Ialongo, Hannakaisa Lindqvist, Janne Nurmela, Johanna Tamminen, Laia Amorós, Dominik Brunner, and Grégoire Broquet
Atmos. Meas. Tech., 18, 211–239, https://doi.org/10.5194/amt-18-211-2025, https://doi.org/10.5194/amt-18-211-2025, 2025
Short summary
Short summary
This study evaluates data-driven inversion methods for estimating CO2 emissions from local sources, such as power plants and cities, using meteorological data and XCO2 and NO2 satellite images rather than atmospheric transport modeling. We assess and compare the performance of five different methods using simulations of 1 year of satellite images, taken from the upcoming Copernicus CO2 Monitoring Mission, covering 15 power plants and the city of Berlin, Germany.
Michael Steiner, Luca Cantarello, Stephan Henne, and Dominik Brunner
Atmos. Chem. Phys., 24, 12447–12463, https://doi.org/10.5194/acp-24-12447-2024, https://doi.org/10.5194/acp-24-12447-2024, 2024
Short summary
Short summary
Atmospheric greenhouse gas inversions have great potential to independently check reported bottom-up emissions; however they are subject to large uncertainties. It is paramount to address and reduce the largest source of uncertainty, which stems from the representation of atmospheric transport in the models. In this study, we show that the use of a temporally varying flow-dependent atmospheric transport uncertainty can enhance the accuracy of emission estimation in an idealized experiment.
Ana Maria Roxana Petrescu, Glen P. Peters, Richard Engelen, Sander Houweling, Dominik Brunner, Aki Tsuruta, Bradley Matthews, Prabir K. Patra, Dmitry Belikov, Rona L. Thompson, Lena Höglund-Isaksson, Wenxin Zhang, Arjo J. Segers, Giuseppe Etiope, Giancarlo Ciotoli, Philippe Peylin, Frédéric Chevallier, Tuula Aalto, Robbie M. Andrew, David Bastviken, Antoine Berchet, Grégoire Broquet, Giulia Conchedda, Stijn N. C. Dellaert, Hugo Denier van der Gon, Johannes Gütschow, Jean-Matthieu Haussaire, Ronny Lauerwald, Tiina Markkanen, Jacob C. A. van Peet, Isabelle Pison, Pierre Regnier, Espen Solum, Marko Scholze, Maria Tenkanen, Francesco N. Tubiello, Guido R. van der Werf, and John R. Worden
Earth Syst. Sci. Data, 16, 4325–4350, https://doi.org/10.5194/essd-16-4325-2024, https://doi.org/10.5194/essd-16-4325-2024, 2024
Short summary
Short summary
This study provides an overview of data availability from observation- and inventory-based CH4 emission estimates. It systematically compares them and provides recommendations for robust comparisons, aiming to steadily engage more parties in using observational methods to complement their UNFCCC submissions. Anticipating improvements in atmospheric modelling and observations, future developments need to resolve knowledge gaps in both approaches and to better quantify remaining uncertainty.
Jean-Louis Bonne, Ludovic Donnat, Grégory Albora, Jérémie Burgalat, Nicolas Chauvin, Delphine Combaz, Julien Cousin, Thomas Decarpenterie, Olivier Duclaux, Nicolas Dumelié, Nicolas Galas, Catherine Juery, Florian Parent, Florent Pineau, Abel Maunoury, Olivier Ventre, Marie-France Bénassy, and Lilian Joly
Atmos. Meas. Tech., 17, 4471–4491, https://doi.org/10.5194/amt-17-4471-2024, https://doi.org/10.5194/amt-17-4471-2024, 2024
Short summary
Short summary
We present a top-down approach to quantify CO2 and CH4 emissions at the scale of an industrial site, based on a mass balance model relying on atmospheric concentrations measurements from a new sensor embarked on board uncrewed aircraft vehicles (UAVs). We present a laboratory characterization of our sensor and a field validation of our quantification method, together with field application to the monitoring of two real-world offshore oil and gas platforms.
Rodrigo Rivera-Martinez, Pramod Kumar, Olivier Laurent, Gregoire Broquet, Christopher Caldow, Ford Cropley, Diego Santaren, Adil Shah, Cécile Mallet, Michel Ramonet, Leonard Rivier, Catherine Juery, Olivier Duclaux, Caroline Bouchet, Elisa Allegrini, Hervé Utard, and Philippe Ciais
Atmos. Meas. Tech., 17, 4257–4290, https://doi.org/10.5194/amt-17-4257-2024, https://doi.org/10.5194/amt-17-4257-2024, 2024
Short summary
Short summary
We explore the use of metal oxide semiconductors (MOSs) as a low-cost alternative for detecting and measuring CH4 emissions from industrial facilities. MOSs were exposed to several controlled releases to test their accuracy in detecting and quantifying emissions. Two reconstruction models were compared, and emission estimates were computed using a Gaussian dispersion model. Findings show that MOSs can provide accurate emission estimates with a 25 % emission rate error and a 9.5 m location error.
Sandro Meier, Erik F. M. Koene, Maarten Krol, Dominik Brunner, Alexander Damm, and Gerrit Kuhlmann
Atmos. Chem. Phys., 24, 7667–7686, https://doi.org/10.5194/acp-24-7667-2024, https://doi.org/10.5194/acp-24-7667-2024, 2024
Short summary
Short summary
Nitrogen oxides (NOx = NO + NO2) are important air pollutants. This study addresses the challenge of accurately estimating NOx emissions from NO2 satellite observations. We develop a realistic model to convert NO2 to NOx by using simulated plumes from various power plants. We apply the model to satellite NO2 observations, significantly reducing biases in estimated NOx emissions. The study highlights the potential for a consistent, high-resolution estimation of NOx emissions using satellite data.
Gerrit Kuhlmann, Erik Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
Geosci. Model Dev., 17, 4773–4789, https://doi.org/10.5194/gmd-17-4773-2024, https://doi.org/10.5194/gmd-17-4773-2024, 2024
Short summary
Short summary
We present a Python software library for data-driven emission quantification (ddeq). It can be used to determine the emissions of hot spots (cities, power plants and industry) from remote sensing images using different methods. ddeq can be extended for new datasets and methods, providing a powerful community tool for users and developers. The application of the methods is shown using Jupyter notebooks included in the library.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 17, 1995–2014, https://doi.org/10.5194/gmd-17-1995-2024, https://doi.org/10.5194/gmd-17-1995-2024, 2024
Short summary
Short summary
Our research presents an innovative approach to estimating power plant CO2 emissions from satellite images of the corresponding plumes such as those from the forthcoming CO2M satellite constellation. The exploitation of these images is challenging due to noise and meteorological uncertainties. To overcome these obstacles, we use a deep learning neural network trained on simulated CO2 images. Our method outperforms alternatives, providing a positive perspective for the analysis of CO2M images.
Michael Steiner, Wouter Peters, Ingrid Luijkx, Stephan Henne, Huilin Chen, Samuel Hammer, and Dominik Brunner
Atmos. Chem. Phys., 24, 2759–2782, https://doi.org/10.5194/acp-24-2759-2024, https://doi.org/10.5194/acp-24-2759-2024, 2024
Short summary
Short summary
The Paris Agreement increased interest in estimating greenhouse gas (GHG) emissions of individual countries, but top-down emission estimation is not yet considered policy-relevant. It is therefore paramount to reduce large errors and to build systems that are based on the newest atmospheric transport models. In this study, we present the first application of ICON-ART in the inverse modeling of GHG fluxes with an ensemble Kalman filter and present our results for European CH4 emissions.
Robert Hanfland, Dominik Brunner, Christiane Voigt, Alina Fiehn, Anke Roiger, and Margit Pattantyús-Ábrahám
Atmos. Chem. Phys., 24, 2511–2534, https://doi.org/10.5194/acp-24-2511-2024, https://doi.org/10.5194/acp-24-2511-2024, 2024
Short summary
Short summary
To show that the three-dimensional dispersion of plumes simulated by the Atmospheric Radionuclide Transport Model within the planetary boundary layer agrees with real plumes, we identify the most important input parameters and analyse the turbulence properties of five different turbulence models in very unstable stratification conditions using their deviation from the well-mixed state. Simulations show that one model agrees slightly better in unstable stratification conditions.
Pramod Kumar, Christopher Caldow, Grégoire Broquet, Adil Shah, Olivier Laurent, Camille Yver-Kwok, Sebastien Ars, Sara Defratyka, Susan Warao Gichuki, Luc Lienhardt, Mathis Lozano, Jean-Daniel Paris, Felix Vogel, Caroline Bouchet, Elisa Allegrini, Robert Kelly, Catherine Juery, and Philippe Ciais
Atmos. Meas. Tech., 17, 1229–1250, https://doi.org/10.5194/amt-17-1229-2024, https://doi.org/10.5194/amt-17-1229-2024, 2024
Short summary
Short summary
This study presents a series of mobile measurement campaigns to monitor the CH4 emissions from an active landfill. These measurements are processed using a Gaussian plume model and atmospheric inversion techniques to quantify the landfill CH4 emissions. The methane emission estimates range between ~0.4 and ~7 t CH4 per day, and their variations are analyzed. The robustness of the estimates is assessed depending on the distance of the measurements from the potential sources in the landfill.
Evan D. Sherwin, Sahar H. El Abbadi, Philippine M. Burdeau, Zhan Zhang, Zhenlin Chen, Jeffrey S. Rutherford, Yuanlei Chen, and Adam R. Brandt
Atmos. Meas. Tech., 17, 765–782, https://doi.org/10.5194/amt-17-765-2024, https://doi.org/10.5194/amt-17-765-2024, 2024
Short summary
Short summary
Countries and companies increasingly rely on a growing fleet of satellites to find large emissions of climate-warming methane, particularly from oil and natural gas systems across the globe. We independently assessed the performance of nine such systems by releasing controlled, undisclosed amounts of methane as satellites passed overhead. The tested systems produced reliable detection and quantification results, including the smallest-ever emission detected from space in such a test.
Apisada Chulakadabba, Maryann Sargent, Thomas Lauvaux, Joshua S. Benmergui, Jonathan E. Franklin, Christopher Chan Miller, Jonas S. Wilzewski, Sébastien Roche, Eamon Conway, Amir H. Souri, Kang Sun, Bingkun Luo, Jacob Hawthrone, Jenna Samra, Bruce C. Daube, Xiong Liu, Kelly Chance, Yang Li, Ritesh Gautam, Mark Omara, Jeff S. Rutherford, Evan D. Sherwin, Adam Brandt, and Steven C. Wofsy
Atmos. Meas. Tech., 16, 5771–5785, https://doi.org/10.5194/amt-16-5771-2023, https://doi.org/10.5194/amt-16-5771-2023, 2023
Short summary
Short summary
We show that MethaneAIR, a precursor to the MethaneSAT satellite, demonstrates accurate point source quantification during controlled release experiments and regional observations in 2021 and 2022. Results from our two independent quantification methods suggest the accuracy of our sensor and algorithms is better than 25 % for sources emitting 200 kg h−1 or more. Insights from these measurements help establish the capabilities of MethaneSAT and MethaneAIR.
Ioannis Katharopoulos, Dominique Rust, Martin K. Vollmer, Dominik Brunner, Stefan Reimann, Simon J. O'Doherty, Dickon Young, Kieran M. Stanley, Tanja Schuck, Jgor Arduini, Lukas Emmenegger, and Stephan Henne
Atmos. Chem. Phys., 23, 14159–14186, https://doi.org/10.5194/acp-23-14159-2023, https://doi.org/10.5194/acp-23-14159-2023, 2023
Short summary
Short summary
The effectiveness of climate change mitigation needs to be scrutinized by monitoring greenhouse gas (GHG) emissions. Countries report their emissions to the UN in a bottom-up manner. By combining atmospheric observations and transport models someone can independently validate emission estimates in a top-down fashion. We report Swiss emissions of synthetic GHGs based on kilometer-scale transport and inverse modeling, highlighting the role of appropriate resolution in complex terrain.
Foteini Stavropoulou, Katarina Vinković, Bert Kers, Marcel de Vries, Steven van Heuven, Piotr Korbeń, Martina Schmidt, Julia Wietzel, Pawel Jagoda, Jaroslav M. Necki, Jakub Bartyzel, Hossein Maazallahi, Malika Menoud, Carina van der Veen, Sylvia Walter, Béla Tuzson, Jonas Ravelid, Randulph Paulo Morales, Lukas Emmenegger, Dominik Brunner, Michael Steiner, Arjan Hensen, Ilona Velzeboer, Pim van den Bulk, Hugo Denier van der Gon, Antonio Delre, Maklawe Essonanawe Edjabou, Charlotte Scheutz, Marius Corbu, Sebastian Iancu, Denisa Moaca, Alin Scarlat, Alexandru Tudor, Ioana Vizireanu, Andreea Calcan, Magdalena Ardelean, Sorin Ghemulet, Alexandru Pana, Aurel Constantinescu, Lucian Cusa, Alexandru Nica, Calin Baciu, Cristian Pop, Andrei Radovici, Alexandru Mereuta, Horatiu Stefanie, Alexandru Dandocsi, Bas Hermans, Stefan Schwietzke, Daniel Zavala-Araiza, Huilin Chen, and Thomas Röckmann
Atmos. Chem. Phys., 23, 10399–10412, https://doi.org/10.5194/acp-23-10399-2023, https://doi.org/10.5194/acp-23-10399-2023, 2023
Short summary
Short summary
In this study, we quantify CH4 emissions from onshore oil production sites in Romania at source and facility level using a combination of ground- and drone-based measurement techniques. We show that the total CH4 emissions in our studied areas are much higher than the emissions reported to UNFCCC, and up to three-quarters of the detected emissions are related to operational venting. Our results suggest that oil and gas production infrastructure in Romania holds a massive mitigation potential.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Marc Bocquet, Jinghui Lian, Grégoire Broquet, Gerrit Kuhlmann, Alexandre Danjou, and Thomas Lauvaux
Geosci. Model Dev., 16, 3997–4016, https://doi.org/10.5194/gmd-16-3997-2023, https://doi.org/10.5194/gmd-16-3997-2023, 2023
Short summary
Short summary
Monitoring of CO2 emissions is key to the development of reduction policies. Local emissions, from cities or power plants, may be estimated from CO2 plumes detected in satellite images. CO2 plumes generally have a weak signal and are partially concealed by highly variable background concentrations and instrument errors, which hampers their detection. To address this problem, we propose and apply deep learning methods to detect the contour of a plume in simulated CO2 satellite images.
Rodrigo Andres Rivera Martinez, Diego Santaren, Olivier Laurent, Gregoire Broquet, Ford Cropley, Cécile Mallet, Michel Ramonet, Adil Shah, Leonard Rivier, Caroline Bouchet, Catherine Juery, Olivier Duclaux, and Philippe Ciais
Atmos. Meas. Tech., 16, 2209–2235, https://doi.org/10.5194/amt-16-2209-2023, https://doi.org/10.5194/amt-16-2209-2023, 2023
Short summary
Short summary
A network of low-cost sensors is a good alternative to improve the detection of fugitive CH4 emissions. We present the results of four tests conducted with two types of Figaro sensors that were assembled on four chambers in a laboratory experiment: a comparison of five models to reconstruct the CH4 signal, a strategy to reduce the training set size, a detection of age effects in the sensors and a test of the capability to transfer a model between chambers for the same type of sensor.
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.
Dominik Brunner, Gerrit Kuhlmann, Stephan Henne, Erik Koene, Bastian Kern, Sebastian Wolff, Christiane Voigt, Patrick Jöckel, Christoph Kiemle, Anke Roiger, Alina Fiehn, Sven Krautwurst, Konstantin Gerilowski, Heinrich Bovensmann, Jakob Borchardt, Michal Galkowski, Christoph Gerbig, Julia Marshall, Andrzej Klonecki, Pascal Prunet, Robert Hanfland, Margit Pattantyús-Ábrahám, Andrzej Wyszogrodzki, and Andreas Fix
Atmos. Chem. Phys., 23, 2699–2728, https://doi.org/10.5194/acp-23-2699-2023, https://doi.org/10.5194/acp-23-2699-2023, 2023
Short summary
Short summary
We evaluated six atmospheric transport models for their capability to simulate the CO2 plumes from two of the largest power plants in Europe by comparing the models against aircraft observations collected during the CoMet (Carbon Dioxide and Methane Mission) campaign in 2018. The study analyzed how realistically such plumes can be simulated at different model resolutions and how well the planned European satellite mission CO2M will be able to quantify emissions from power plants.
Zhan Zhang, Evan D. Sherwin, Daniel J. Varon, and Adam R. Brandt
Atmos. Meas. Tech., 15, 7155–7169, https://doi.org/10.5194/amt-15-7155-2022, https://doi.org/10.5194/amt-15-7155-2022, 2022
Short summary
Short summary
This work developed a multi-band–multi-pass–multi-comparison-date Sentinel-2 methane retrieval algorithm, and the method was calibrated by data from a controlled release test. To our knowledge, this is the first study that validates the performance of a Sentinel-2 methane detection algorithm by calibration with a ground-truth testing. It illustrates the potential for additional validation with systematic future experiments wherein algorithms can be tuned to meet different detection expectations.
Prabhakar Shrestha, Jana Mendrok, and Dominik Brunner
Atmos. Chem. Phys., 22, 14095–14117, https://doi.org/10.5194/acp-22-14095-2022, https://doi.org/10.5194/acp-22-14095-2022, 2022
Short summary
Short summary
The study extends the Terrestrial Systems Modeling Platform with gas-phase chemistry aerosol dynamics and a radar forward operator to enable detailed studies of aerosol–cloud–precipitation interactions. This is demonstrated using a case study of a deep convective storm, which showed that the strong updraft in the convective core of the storm produced aerosol-tower-like features, which affected the size of the hydrometeors and the simulated polarimetric features (e.g., ZDR and KDP columns).
Peter Bergamaschi, Arjo Segers, Dominik Brunner, Jean-Matthieu Haussaire, Stephan Henne, Michel Ramonet, Tim Arnold, Tobias Biermann, Huilin Chen, Sebastien Conil, Marc Delmotte, Grant Forster, Arnoud Frumau, Dagmar Kubistin, Xin Lan, Markus Leuenberger, Matthias Lindauer, Morgan Lopez, Giovanni Manca, Jennifer Müller-Williams, Simon O'Doherty, Bert Scheeren, Martin Steinbacher, Pamela Trisolino, Gabriela Vítková, and Camille Yver Kwok
Atmos. Chem. Phys., 22, 13243–13268, https://doi.org/10.5194/acp-22-13243-2022, https://doi.org/10.5194/acp-22-13243-2022, 2022
Short summary
Short summary
We present a novel high-resolution inverse modelling system, "FLEXVAR", and its application for the inverse modelling of European CH4 emissions in 2018. The new system combines a high spatial resolution of 7 km x 7 km with a variational data assimilation technique, which allows CH4 emissions to be optimized from individual model grid cells. The high resolution allows the observations to be better reproduced, while the derived emissions show overall good consistency with two existing models.
Simone M. Pieber, Béla Tuzson, Stephan Henne, Ute Karstens, Christoph Gerbig, Frank-Thomas Koch, Dominik Brunner, Martin Steinbacher, and Lukas Emmenegger
Atmos. Chem. Phys., 22, 10721–10749, https://doi.org/10.5194/acp-22-10721-2022, https://doi.org/10.5194/acp-22-10721-2022, 2022
Short summary
Short summary
Understanding regional greenhouse gas emissions into the atmosphere is a prerequisite to mitigate climate change. In this study, we investigated the regional contributions of carbon dioxide (CO2) at the location of the high Alpine observatory Jungfraujoch (JFJ, Switzerland, 3580 m a.s.l.). To this purpose, we combined receptor-oriented atmospheric transport simulations for CO2 concentration in the period 2009–2017 with stable carbon isotope (δ13C–CO2) information.
Randulph Morales, Jonas Ravelid, Katarina Vinkovic, Piotr Korbeń, Béla Tuzson, Lukas Emmenegger, Huilin Chen, Martina Schmidt, Sebastian Humbel, and Dominik Brunner
Atmos. Meas. Tech., 15, 2177–2198, https://doi.org/10.5194/amt-15-2177-2022, https://doi.org/10.5194/amt-15-2177-2022, 2022
Short summary
Short summary
Mapping trace gas emission plumes using in situ measurements from unmanned aerial vehicles (UAVs) is an emerging and attractive possibility to quantify emissions from localized sources. We performed an extensive controlled-release experiment to develop an optimal quantification method and to determine the related uncertainties under various environmental and sampling conditions. Our approach was successful in quantifying local methane sources from drone-based measurements.
Gerrit Kuhlmann, Ka Lok Chan, Sebastian Donner, Ying Zhu, Marc Schwaerzel, Steffen Dörner, Jia Chen, Andreas Hueni, Duc Hai Nguyen, Alexander Damm, Annette Schütt, Florian Dietrich, Dominik Brunner, Cheng Liu, Brigitte Buchmann, Thomas Wagner, and Mark Wenig
Atmos. Meas. Tech., 15, 1609–1629, https://doi.org/10.5194/amt-15-1609-2022, https://doi.org/10.5194/amt-15-1609-2022, 2022
Short summary
Short summary
Nitrogen dioxide (NO2) is an air pollutant whose concentration often exceeds air quality guideline values, especially in urban areas. To map the spatial distribution of NO2 in Munich, we conducted the Munich NO2 Imaging Campaign (MuNIC), where NO2 was measured with stationary, mobile, and airborne in situ and remote sensing instruments. The campaign provides a unique dataset that has been used to compare the different instruments and to study the spatial variability of NO2 and its sources.
Marc Schwaerzel, Dominik Brunner, Fabian Jakub, Claudia Emde, Brigitte Buchmann, Alexis Berne, and Gerrit Kuhlmann
Atmos. Meas. Tech., 14, 6469–6482, https://doi.org/10.5194/amt-14-6469-2021, https://doi.org/10.5194/amt-14-6469-2021, 2021
Short summary
Short summary
NO2 maps from airborne imaging remote sensing often appear much smoother than one would expect from high-resolution model simulations of NO2 over cities, despite the small ground-pixel size of the sensors. Our case study over Zurich, using the newly implemented building module of the MYSTIC radiative transfer solver, shows that the 3D effect can explain part of the smearing and that building shadows cause a noticeable underestimation and noise in the measured NO2 columns.
Antoine Berchet, Espen Sollum, Rona L. Thompson, Isabelle Pison, Joël Thanwerdas, Grégoire Broquet, Frédéric Chevallier, Tuula Aalto, Adrien Berchet, Peter Bergamaschi, Dominik Brunner, Richard Engelen, Audrey Fortems-Cheiney, Christoph Gerbig, Christine D. Groot Zwaaftink, Jean-Matthieu Haussaire, Stephan Henne, Sander Houweling, Ute Karstens, Werner L. Kutsch, Ingrid T. Luijkx, Guillaume Monteil, Paul I. Palmer, Jacob C. A. van Peet, Wouter Peters, Philippe Peylin, Elise Potier, Christian Rödenbeck, Marielle Saunois, Marko Scholze, Aki Tsuruta, and Yuanhong Zhao
Geosci. Model Dev., 14, 5331–5354, https://doi.org/10.5194/gmd-14-5331-2021, https://doi.org/10.5194/gmd-14-5331-2021, 2021
Short summary
Short summary
We present here the Community Inversion Framework (CIF) to help rationalize development efforts and leverage the strengths of individual inversion systems into a comprehensive framework. The CIF is a programming protocol to allow various inversion bricks to be exchanged among researchers.
The ensemble of bricks makes a flexible, transparent and open-source Python-based tool. We describe the main structure and functionalities and demonstrate it in a simple academic case.
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.
David R. Lyon, Benjamin Hmiel, Ritesh Gautam, Mark Omara, Katherine A. Roberts, Zachary R. Barkley, Kenneth J. Davis, Natasha L. Miles, Vanessa C. Monteiro, Scott J. Richardson, Stephen Conley, Mackenzie L. Smith, Daniel J. Jacob, Lu Shen, Daniel J. Varon, Aijun Deng, Xander Rudelis, Nikhil Sharma, Kyle T. Story, Adam R. Brandt, Mary Kang, Eric A. Kort, Anthony J. Marchese, and Steven P. Hamburg
Atmos. Chem. Phys., 21, 6605–6626, https://doi.org/10.5194/acp-21-6605-2021, https://doi.org/10.5194/acp-21-6605-2021, 2021
Short summary
Short summary
The Permian Basin (USA) is the world’s largest oil field. We use tower- and aircraft-based approaches to measure how methane emissions in the Permian Basin changed throughout 2020. In early 2020, 3.3 % of the region’s gas was emitted; then in spring 2020, the loss rate temporarily dropped to 1.9 % as oil price crashed. We find this short-term reduction to be a result of reduced well development, less gas flaring, and fewer abnormal events despite minimal reductions in oil and gas production.
Cited articles
Alexe, M., Bergamaschi, P., Segers, A., Detmers, R., Butz, A., Hasekamp, O., Guerlet, S., Parker, R., Boesch, H., Frankenberg, C., Scheepmaker, R. A., Dlugokencky, E., Sweeney, C., Wofsy, S. C., and Kort, E. A.: Inverse modelling of CH4 emissions for 2010–2011 using different satellite retrieval products from GOSAT and SCIAMACHY, Atmospheric Chemistry and Physics, 15, 113–133, https://doi.org/10.5194/acp-15-113-2015, 2015. a
Ayasse, A. K., Cusworth, D., O'Neill, K., Fisk, J., Thorpe, A. K., and Duren, R.: Performance and sensitivity of column-wise and pixel-wise methane retrievals for imaging spectrometers, Atmospheric Measurement Techniques, 16, 6065–6074, https://doi.org/10.5194/amt-16-6065-2023, 2023. a, b
Balcombe, P., Brandon, N., and Hawkes, A.: Characterising the distribution of methane and carbon dioxide emissions from the natural gas supply chain, Journal of Cleaner Production, 172, 2019–2032, https://doi.org/10.1016/j.jclepro.2017.11.223, 2018. a
Borchardt, J., Gerilowski, K., Krautwurst, S., Bovensmann, H., Thorpe, A. K., Thompson, D. R., Frankenberg, C., Miller, C. E., Duren, R. M., and Burrows, J. P.: Detection and quantification of CH4 plumes using the WFM-DOAS retrieval on AVIRIS-NG hyperspectral data, Atmospheric Measurement Techniques, 14, 1267–1291, https://doi.org/10.5194/amt-14-1267-2021, 2021. a, b
Bousquet, P., Pierangelo, C., Bacour, C., Marshall, J., Peylin, P., Ayar, P. V., Ehret, G., Bréon, F.-M., Chevallier, F., Crevoisier, C., Gibert, F., Rairoux, P., Kiemle, C., Armante, R., Bès, C., Cassé, V., Chinaud, J., Chomette, O., Delahaye, T., Edouart, D., Estève, F., Fix, A., Friker, A., Klonecki, A., Wirth, M., Alpers, M., and Millet, B.: Error Budget of the MEthane Remote LIdar missioN and Its Impact on the Uncertainties of the Global Methane Budget, Journal of Geophysical Research: Atmospheres, 123, 11766–11785, https://doi.org/10.1029/2018JD028907, 2018. a, b
Bruno, J. H., Jervis, D., Varon, D. J., and Jacob, D. J.: U-Plume: automated algorithm for plume detection and source quantification by satellite point-source imagers, Atmospheric Measurement Techniques, 17, 2625–2636, https://doi.org/10.5194/amt-17-2625-2024, 2024. a
Conrad, B. M., Tyner, D. R., and Johnson, M. R.: Robust probabilities of detection and quantification uncertainty for aerial methane detection: Examples for three airborne technologies, Remote Sensing of Environment, 288, 113499, https://doi.org/10.1016/j.rse.2023.113499, 2023. a, b, c
Cusworth, D. H., Duren, R. M., Thorpe, A. K., Eastwood, M. L., Green, R. O., Dennison, P. E., Frankenberg, C., Heckler, J. W., Asner, G. P., and Miller, C. E.: Quantifying Global Power Plant Carbon Dioxide Emissions With Imaging Spectroscopy, AGU Advances, 2, e2020AV000350, https://doi.org/10.1029/2020AV000350, 2021. a
Duren, R. M., Thorpe, A. K., Foster, K. T., Rafiq, T., Hopkins, F. M., Yadav, V., Bue, B. D., Thompson, D. R., Conley, S., Colombi, N. K., Frankenberg, C., McCubbin, I. B., Eastwood, M. L., Falk, M., Herner, J. D., Croes, B. E., Green, R. O., and Miller, C. E.: California’s methane super-emitters, Nature, 575, 180–184, 2019. a, b
Eastwood, M. L., Thompson, D., Green, R. O., Fahlen, J., Adams, T., Brandt, A., Brodrick, P. G., Chlus, A., Kort, E. A., Reuland, F., and Thorpe, A. K.: Direct Measurement of Plume Velocity to Characterize Point Source Emissions, Proceedings of the National Academy of Sciences, 122, e2507350122, https://doi.org/10.1073/pnas.2507350122, 2025. a
European Parliament and the Council of the European Union: REGULATION (EC) No 166/2006: Establishment of a European Pollutant Release and Transfer Register and amending Council Directives 91/689/EEC and 96/61, Official Journal of the European Union, http://data.europa.eu/eli/reg/2006/166/oj (last access: 22 December 2025), 2006. a
Fahlen, J. E., Brodrick, P. G., Coleman, R. W., Elder, C. D., Thompson, D. R., Thorpe, A. K., Green, R. O., Green, J. J., Lopez, A. M., and Xiang, C.: Sensitivity and Uncertainty in Matched-Filter-Based Gas Detection With Imaging Spectroscopy, IEEE Transactions on Geoscience and Remote Sensing, 62, 1–10, https://doi.org/10.1109/TGRS.2024.3440174, 2024. a
Fleagle, R. G. and Businger, J. A.: An introduction to atmospheric physics, Academic Press, https://doi.org/10.1016/S0074-6142(08)60498-2, 1980. a
Foote, M. D., Dennison, P. E., Thorpe, A. K., Thompson, D. R., Jongaramrungruang, S., Frankenberg, C., and Joshi, S. C.: Fast and accurate retrieval of methane concentration from imaging spectrometer data using sparsity prior, IEEE Transactions on Geoscience and Remote Sensing, 58, 6480–6492, 2020. a
Fraser, A., Palmer, P. I., Feng, L., Boesch, H., Cogan, A., Parker, R., Dlugokencky, E. J., Fraser, P. J., Krummel, P. B., Langenfelds, R. L., O'Doherty, S., Prinn, R. G., Steele, L. P., van der Schoot, M., and Weiss, R. F.: Estimating regional methane surface fluxes: the relative importance of surface and GOSAT mole fraction measurements, Atmospheric Chemistry and Physics, 13, 5697–5713, https://doi.org/10.5194/acp-13-5697-2013, 2013. a
Gorroño, J., Varon, D. J., Irakulis-Loitxate, I., and Guanter, L.: Understanding the potential of Sentinel-2 for monitoring methane point emissions, Atmospheric Measurement Techniques, 16, 89–107, https://doi.org/10.5194/amt-16-89-2023, 2023. a
Gorroño, J., Pei, Z., Valverde, A., and Guanter, L.: Considering the observation and illumination angular configuration for an improved detection and quantification of methane emissions, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-4924, 2025. a, b, c, d
Green, R. O., Schaepman, M. E., Mouroulis, P., Geier, S., Shaw, L., Hueini, A., Bernas, M., McKinley, I., Smith, C., Wehbe, R., Eastwood, M., Vinckier, Q., Liggett, E., Zandbergen, S., Thompson, D., Sullivan, P., Sarture, C., Van Gorp, B., and Helmlinger, M.: Airborne Visible/Infrared Imaging Spectrometer 3 (AVIRIS-3), in: 2022 IEEE Aerospace Conference (AERO), 1–10, https://doi.org/10.1109/AERO53065.2022.9843565, 2022. a, b
Guanter, L., Irakulis-Loitxate, I., Gorroño, J., Sánchez-García, E., Cusworth, D. H., Varon, D. J., Cogliati, S., and Colombo, R.: Mapping methane point emissions with the PRISMA spaceborne imaging spectrometer, Remote Sensing of Environment, 265, 112671, https://doi.org/10.1016/j.rse.2021.112671, 2021. a
Guanter, L., Warren, J., Omara, M., Chulakadabba, A., Roger, J., Sargent, M., Franklin, J. E., Wofsy, S. C., and Gautam, R.: Detection and quantification of methane plumes with the MethaneAIR airborne spectrometer, Atmospheric Measurement Techniques, 18, 3857–3872, https://doi.org/10.5194/amt-18-3857-2025, 2025. a, b
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.adbb2d47, 2018. a, b, c
Hueni, A., Geier, S., Vögtli, M., LaHaye, J., Rosset, J., Berger, D., Sierro, L. J., Jospin, L. V., Thompson, D. R., Schläpfer, D., Green, R. O., Loeliger, T., Skaloud, J., and Schaepman, M. E.: The AVIRIS-4 Airborne Imaging Spectrometer, IEEE Geoscience and Remote Sensing Letters, 22, 1–5, https://doi.org/10.1109/LGRS.2025.3572349, 2025. a, b, c, d, e
IGN: RGE ALTI® v2.0: Digital Elevation Model (DEM) of France, https://geoservices.ign.fr/documentation/donnees/alti/rgealti (last access: 28 March 2025), 2018. a
Jacob, D. J., Varon, D. J., Cusworth, D. H., Dennison, P. E., Frankenberg, C., Gautam, R., Guanter, L., Kelley, J., McKeever, J., Ott, L. E., Poulter, B., Qu, Z., Thorpe, A. K., Worden, J. R., and Duren, R. M.: Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane, Atmos. Chem. Phys., 22, 9617–9646, https://doi.org/10.5194/acp-22-9617-2022, 2022. a, b
Jongaramrungruang, S., Thorpe, A. K., Matheou, G., and Frankenberg, C.: MethaNet – An AI-driven approach to quantifying methane point-source emission from high-resolution 2-D plume imagery, Remote Sensing of Environment, 269, 112809, https://doi.org/10.1016/j.rse.2021.112809, 2022. a, b
Joyce, P., Ruiz Villena, C., Huang, Y., Webb, A., Gloor, M., Wagner, F. H., Chipperfield, M. P., Barrio Guilló, R., Wilson, C., and Boesch, H.: Using a deep neural network to detect methane point sources and quantify emissions from PRISMA hyperspectral satellite images, Atmospheric Measurement Techniques, 16, 2627–2640, https://doi.org/10.5194/amt-16-2627-2023, 2023. a, b
Krautwurst, S., Fruck, C., Wolff, S., Borchardt, J., Huhs, O., Gerilowski, K., Gałkowski, M., Kiemle, C., Quatrevalet, M., Wirth, M., Mallaun, C., Burrows, J. P., Gerbig, C., Fix, A., Bösch, H., and Bovensmann, H.: Identification and quantification of CH4 emissions from Madrid landfills using airborne imaging spectrometry and greenhouse gas lidar, Atmos. Chem. Phys., 25, 14669–14702, https://doi.org/10.5194/acp-25-14669-2025, 2025. a
Kuhlmann, G., Koene, E., Meier, S., Santaren, D., Broquet, G., Chevallier, F., Hakkarainen, J., Nurmela, J., Amorós, L., Tamminen, J., and Brunner, D.: The ddeq Python library for point source quantification from remote sensing images (version 1.0), Geoscientific Model Development, 17, 4773–4789, https://doi.org/10.5194/gmd-17-4773-2024, 2024. a, b, c, d, e
Kuhlmann, G., Stavropoulou, F., Schwietzke, S., Zavala-Araiza, D., Thorpe, A., Hueni, A., Emmenegger, L., Calcan, A., Röckmann, T., and Brunner, D.: Evidence of successful methane mitigation in one of Europe's most important oil production region, Atmospheric Chemistry and Physics, 25, 5371–5385, https://doi.org/10.5194/acp-25-5371-2025, 2025. a, b, c, d, e, f, g, h
Meier, S., Vögtli, M., Hueni, A., McManemin, A., Brandt, A. R., Juéry, C., Blandin, V., Brunner, D., and Kuhlmann, G.: AVIRIS-4 CH4 Retrievals and Estimated Emissions of Controlled Release Experiment in Pau, France, in September 2024, Zenodo [data set], https://doi.org/10.5281/zenodo.16410532, 2025. a
Ouerghi, E., Ehret, T., Facciolo, G., Meinhardt, E., Marion, R., and Morel, J.-M.: Tightening up methane plume source rate estimation in EnMAP and PRISMA images, Atmospheric Measurement Techniques, 18, 4611–4629, https://doi.org/10.5194/amt-18-4611-2025, 2025. a
Pei, Z., Han, G., Mao, H., Chen, C., Shi, T., Yang, K., Ma, X., and Gong, W.: Improving quantification of methane point source emissions from imaging spectroscopy, Remote Sensing of Environment, 295, 113652, https://doi.org/10.1016/j.rse.2023.113652, 2023. a, b
Plewa, T., Butz, A., Frankenberg, C., Thorpe, A. K., and Marshall, J.: Improvements of AI-driven emission estimation for point sources applied to high resolution 2-D methane-plume imagery, Remote Sensing of Environment, 331, 115002, https://doi.org/10.1016/j.rse.2025.115002, 2025. a
Rouet-Leduc, B. and Hulbert, C.: Automatic detection of methane emissions in multispectral satellite imagery using a vision transformer, Nature Communications, 15, 3801, https://doi.org/10.1038/s41467-024-47754-y, 2024. a
Sánchez-García, E., Gorroño, J., Irakulis-Loitxate, I., Varon, D. J., and Guanter, L.: Mapping methane plumes at very high spatial resolution with the WorldView-3 satellite, Atmospheric Measurement Techniques, 15, 1657–1674, https://doi.org/10.5194/amt-15-1657-2022, 2022. a, b, c
Saunois, M., Stavert, A. R., Poulter, B., Bousquet, P., Canadell, J. G., Jackson, R. B., Raymond, P. A., Dlugokencky, E. J., Houweling, S., Patra, P. K., Ciais, P., Arora, V. K., Bastviken, D., Bergamaschi, P., Blake, D. R., Brailsford, G., Bruhwiler, L., Carlson, K. M., Carrol, M., Castaldi, S., Chandra, N., Crevoisier, C., Crill, P. M., Covey, K., Curry, C. L., Etiope, G., Frankenberg, C., Gedney, N., Hegglin, M. I., Höglund-Isaksson, L., Hugelius, G., Ishizawa, M., Ito, A., Janssens-Maenhout, G., Jensen, K. M., Joos, F., Kleinen, T., Krummel, P. B., Langenfelds, R. L., Laruelle, G. G., Liu, L., Machida, T., Maksyutov, S., McDonald, K. C., McNorton, J., Miller, P. A., Melton, J. R., Morino, I., Müller, J., Murguia-Flores, F., Naik, V., Niwa, Y., Noce, S., O'Doherty, S., Parker, R. J., Peng, C., Peng, S., Peters, G. P., Prigent, C., Prinn, R., Ramonet, M., Regnier, P., Riley, W. J., Rosentreter, J. A., Segers, A., Simpson, I. J., Shi, H., Smith, S. J., Steele, L. P., Thornton, B. F., Tian, H., Tohjima, Y., Tubiello, F. N., Tsuruta, A., Viovy, N., Voulgarakis, A., Weber, T. S., van Weele, M., van der Werf, G. R., Weiss, R. F., Worthy, D., Wunch, D., Yin, Y., Yoshida, Y., Zhang, W., Zhang, Z., Zhao, Y., Zheng, B., Zhu, Q., Zhu, Q., and Zhuang, Q.: The Global Methane Budget 2000–2017, Earth System Science Data, 12, 1561–1623, https://doi.org/10.5194/essd-12-1561-2020, 2020. a, b, c
Schläpfer, D. and Richter, R.: Geo-atmospheric processing of airborne imaging spectrometry data. Part 1: Parametric orthorectification, International Journal of Remote Sensing, 23, 2609–2630, https://doi.org/10.1080/01431160110115825, 2002. a
Schläpfer, D., Hueni, A., and Richter, R.: Cast Shadow Detection to Quantify the Aerosol Optical Thickness for Atmospheric Correction of High Spatial Resolution Optical Imagery, Remote Sensing, 10, https://doi.org/10.3390/rs10020200, 2018. a, b
Schwaerzel, M., Emde, C., Brunner, D., Morales, R., Wagner, T., Berne, A., Buchmann, B., and Kuhlmann, G.: Three-dimensional radiative transfer effects on airborne and ground-based trace gas remote sensing, Atmospheric Measurement Techniques, 13, 4277–4293, https://doi.org/10.5194/amt-13-4277-2020, 2020. a, b
Shaw, L. A., Geier, S., Mckinley, I. M., Bernas, M. A., Gharakhanian, M., Dergevorkian, A., Eastwood, M. L., Mouroulis, P., and Green, R. O.: Design, alignment, and laboratory calibration of the compact wide swath imaging spectrometer II (CWIS-II), in: Imaging Spectrometry XXV: Applications, Sensors, and Processing, 12235, 1223502, SPIE, https://doi.org/10.1117/12.2634282, 2022. a
Stavropoulou, F., Vinković, K., Kers, B., de Vries, M., van Heuven, S., Korbeń, P., Schmidt, M., Wietzel, J., Jagoda, P., Necki, J. M., Bartyzel, J., Maazallahi, H., Menoud, M., van der Veen, C., Walter, S., Tuzson, B., Ravelid, J., Morales, R. P., Emmenegger, L., Brunner, D., Steiner, M., Hensen, A., Velzeboer, I., van den Bulk, P., Denier van der Gon, H., Delre, A., Edjabou, M. E., Scheutz, C., Corbu, M., Iancu, S., Moaca, D., Scarlat, A., Tudor, A., Vizireanu, I., Calcan, A., Ardelean, M., Ghemulet, S., Pana, A., Constantinescu, A., Cusa, L., Nica, A., Baciu, C., Pop, C., Radovici, A., Mereuta, A., Stefanie, H., Dandocsi, A., Hermans, B., Schwietzke, S., Zavala-Araiza, D., Chen, H., and Röckmann, T.: High potential for CH4 emission mitigation from oil infrastructure in one of EU's major production regions, Atmospheric Chemistry and Physics, 23, 10399–10412, https://doi.org/10.5194/acp-23-10399-2023, 2023. a
Thompson, D. R., Leifer, I., Bovensmann, H., Eastwood, M., Fladeland, M., Frankenberg, C., Gerilowski, K., Green, R. O., Kratwurst, S., Krings, T., Luna, B., and Thorpe, A. K.: Real-time remote detection and measurement for airborne imaging spectroscopy: a case study with methane, Atmospheric Measurement Techniques, 8, 4383–4397, https://doi.org/10.5194/amt-8-4383-2015, 2015. a
Thorpe, A., Frankenberg, C., Aubrey, A., Roberts, D., Nottrott, A., Rahn, T., Sauer, J., Dubey, M., Costigan, K., Arata, C., Steffke, A., Hills, S., Haselwimmer, C., Charlesworth, D., Funk, C., Green, R., Lundeen, S., Boardman, J., Eastwood, M., Sarture, C., Nolte, S., Mccubbin, I., Thompson, D., and McFadden, J.: Mapping methane concentrations from a controlled release experiment using the next generation airborne visible/infrared imaging spectrometer (AVIRIS-NG), Remote Sensing of Environment, 179, 104–115, https://doi.org/10.1016/j.rse.2016.03.032, 2016. a, b
Thorpe, A. K., O'Handley, C., Emmitt, G. D., DeCola, P. L., Hopkins, F. M., Yadav, V., Guha, A., Newman, S., Herner, J. D., Falk, M., and Duren, R. M.: Improved methane emission estimates using AVIRIS-NG and an Airborne Doppler Wind Lidar, Remote Sensing of Environment, 266, 112681, https://doi.org/10.1016/j.rse.2021.112681, 2021. a
Varon, D. J., Jacob, D. J., McKeever, J., Jervis, D., Durak, B. O. A., Xia, Y., and Huang, Y.: Quantifying methane point sources from fine-scale satellite observations of atmospheric methane plumes, Atmospheric Measurement Techniques, 11, 5673–5686, https://doi.org/10.5194/amt-11-5673-2018, 2018. a, b, c, d, e, f, g
Williams, J. P., Omara, M., Himmelberger, A., Zavala-Araiza, D., MacKay, K., Benmergui, J., Sargent, M., Wofsy, S. C., Hamburg, S. P., and Gautam, R.: Small emission sources in aggregate disproportionately account for a large majority of total methane emissions from the US oil and gas sector, Atmospheric Chemistry and Physics, 25, 1513–1532, https://doi.org/10.5194/acp-25-1513-2025, 2025. a, b
Zavala-Araiza, D., Lyon, D., Alvarez, R. A., Palacios, V., Harriss, R., Lan, X., Talbot, R., and Hamburg, S. P.: Toward a Functional Definition of Methane Super-Emitters: Application to Natural Gas Production Sites, Environmental Science & Technology, 49, 8167–8174, https://doi.org/10.1021/acs.est.5b00133, 2015. a
Zhang, S., Ma, J., Zhang, X., and Guo, C.: Atmospheric remote sensing for anthropogenic methane emissions: Applications and research opportunities, Science of The Total Environment, 893, 164701, https://doi.org/10.1016/j.scitotenv.2023.164701, 2023. a
Short summary
We tested a new airborne imaging instrument to detect and measure methane emissions. Flying over controlled test releases in France, we compared our measurements with known release rates. The instrument detected emissions as low as 5.5 kilograms per hour in good weather and 1.45 kilograms per hour in ideal conditions. Our results show that better wind information is crucial for accurate totals. Our new instrument is important for helping target methane leaks in energy and waste systems.
We tested a new airborne imaging instrument to detect and measure methane emissions. Flying over...
