Articles | Volume 18, issue 7
https://doi.org/10.5194/essd-18-4793-2026
© 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/essd-18-4793-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
10 Jul 2026
Data description article |
| 10 Jul 2026
| 10 Jul 2026
A global dataset of δ13C-CH4 source signatures and associated uncertainties (1998–2022), with a sensitivity analysis to support isotopic inversions
Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA, CNRS, UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
Antoine Berchet
Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA, CNRS, UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
Adrien Martinez
Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA, CNRS, UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
Malika Menoud
Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA, CNRS, UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
now at: UNEP, International Methane Emissions Observatory (IMEO), Paris, France
Joël Thanwerdas
Empa, Swiss Federal Laboratories for Materials Science and Technology, Dübendorf, Switzerland
CIRES, University of Colorado Boulder, CO, 80309, USA
NOAA Global Monitoring Laboratory, Boulder, CO, 80305, USA
Edward Malina
European Space Agency – ESRIN, Frascati, 00044, Italy
Daniele Gasbarra
European Space Agency – ESRIN, Frascati, 00044, Italy
Marielle Saunois
Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA, CNRS, UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
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Pierre Friedlingstein, Michael O'Sullivan, Robbie M. Andrew, Judith Hauck, Matthew W. Jones, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Kjetil Aas, Simone R. Alin, Vivek Arora, Nicholas R. Bates, Kimberly Bedard, David Martin Belda, Nicolas Bellouin, Alice Benoit-Cattin, Carla F. Berghoff, Sarah Berthet, Laurent Bopp, Ida Bagus Mandhara Brasika, Eleanor Burke, Leon Casse, Matthew A. Chamberlain, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Susan E. Curless, Tim DeVries, Tobias Ehmen, Matthew P. Enright, Kazutaka Enyo, Michael Erb, Wiley Evans, Amanda R. Fay, Ben Felzer, Daniel J. Ford, Adrianna Foster, Filippa Fransner, Agneta Fransson, Andrew Friedman, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Wensu Hao, Kirsty Harrington, Jens Heinke, George C. Hurtt, Tatiana Ilyina, Akihiko Ito, Andrew R. Jacobson, Atul K. Jain, Rajesh Janardanan, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Linus Kamb, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Taro Kunimitsu, Xin Lan, Vladimir Lapin, Siv K. Lauvset, Simone Le Chevère, Woo-Sung Lee, Enhui Liao, Junjie Liu, Zhu Liu, Sebastiaan Luyssaert, Lei Ma, Suman Maity, Gregg Marland, Patrick C. McGuire, Nicolas Metzl, Juliette Mignot, Natalie M. Monacci, Eric J. Morgan, Jens D. Müller, David R. Munro, Miaki Muramatsu, Shin-Ichiro Nakaoka, Craig Neill, Tobias Nützel, Léa Olivier, Timothy Osborn, Xosé A. Padín, Paul I. Palmer, Sudhanshu Pandey, Denis Pierrot, Ben Poulter, Zhangcai Qin, Yumou Qiu, Gregor Rehder, Laure Resplandy, Christian Rödenbeck, Alizée Roobaert, Thais M. Rosan, Simone Rossi, Jörg Schwinger, Gereon Seeberg, Roland Séférian, Elisabeth H. Shadwick, Ingunn Skjelvan, Karolina Slominska-Durdasiak, T. Luke Smallman, Mohanan G Sreeush, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Hiroaki Tatebe, Jens Terhaar, Hanqin Tian, Bronte Tilbrook, Takahiro Toyoda, Joaquin A. Triñanes, Francesco Tubiello, Guido R. van der Werf, Auke van der Woude, Sebastiaan J. van de Velde, Anthony P. Walker, Rik Wanninkhof, Xiaojuan Yang, Wenping Yuan, Xu Yue, Jiye Zeng, Ning Zheng, and Bo Zheng
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-895, https://doi.org/10.5194/essd-2026-895, 2026
Preprint under review for ESSD
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The Global Carbon Budget 2026 describes the methodology, main results, and datasets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2026). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Benjamin Gaubert, Mohammad Amin Mirrezaei, Rafael P. Fernandez, Ivan Ortega, Louisa Emmons, John Orlando, Youmi Oh, Lori Bruhwiler, Shuo Chen, Gabrielle Pétron, Xin Lan, Claire Granier, Nicolas Zilbermann, Idir Bouarar, Guy P. Brasseur, Chuan Feng, Yangyang Xu, Alfonso Saiz-Lopez, Carlos A. Cuevas, and Avelino F. Arellano Jr.
Atmos. Chem. Phys., 26, 15683–15719, https://doi.org/10.5194/acp-26-15683-2026, https://doi.org/10.5194/acp-26-15683-2026, 2026
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Atmospheric methane levels have been rising in ways scientists struggle to explain. Much of the uncertainty lies in a chemical that removes methane from the air. Using a detailed model of the Earth, we found that chemistry plays an important role in the fate of methane in the atmosphere, even small variations need to be included to track methane accurately.
Kalliopi Artemis Voudouri, Andreas Karipis, Alexandra Tsekeri, Otto Hasekamp, Kirk Knobelspiesse, Meng Gao, Santiago Gasso, Gerd-jan van Zadelhoff, Athanasios Tsikerdekis, Guangliang Fu, Anton Lopatin, Oleg Dubovik, Edward Malina, Eleni Marinou, and Vassilis Amiridis
EGUsphere, https://doi.org/10.5194/egusphere-2026-5990, https://doi.org/10.5194/egusphere-2026-5990, 2026
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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This study evaluates two satellite-based methods for retrieving aerosol layer height using observations from the PACE and EarthCARE missions. We assess the consistency of their retrievals under different atmospheric conditions and across diverse regions, identifying when they agree best and highlighting the strengths and limitations of each approach. The results support the validation of these missions, which are expected to provide long-term observations for reliable climate data records.
Johanna Mayer, Daniele Gasbarra, Robin J. Hogan, Edward Malina, Shannon L. Mason, and Blanka Piskala Gvozdikova
Atmos. Chem. Phys., 26, 14085–14110, https://doi.org/10.5194/acp-26-14085-2026, https://doi.org/10.5194/acp-26-14085-2026, 2026
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We investigate transitions from closed to open stratocumulus cells using synergistic observations from the EarthCARE and GOES satellites. Microphysical changes and increasing rain up to 25 hours before transitions support a precipitation-driven pathway. These findings provide new observational constraints on the processes driving stratocumulus breakup and its radiative impact.
Félix Langot, Cyril Crevoisier, Thomas Lauvaux, Antoine Berchet, Sophie Luise Wittig, Charbel Abdallah, Anke Roiger, Klaus-Dirk Gottschaldt, and Alina Fiehn
EGUsphere, https://doi.org/10.5194/egusphere-2026-5620, https://doi.org/10.5194/egusphere-2026-5620, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Wetlands in the far north are a major source of methane, a powerful greenhouse gas, but how much they release is poorly known. We flew an aircraft over northern Sweden, targeting known emission hotspots, and worked backwards from the methane measured in the air to estimate emissions on the ground. Models get the average right over these hotspots, but release methane steadily where real wetlands emit in bursts. Capturing that rhythm is what will let us track this source as the climate warms.
Fenjuan Wang, Shamil Maksyutov, Rajesh Janardanan, Dmitry A. Belikov, Prabir K. Patra, Ruosi Liang, Yuzhong Zhang, Ge Ren, Hong Lin, Nicole Montenegro, Antoine Berchet, Marielle Saunois, Adrien Martinez, Sara Hyvärinen, Aki Tsuruta, Samuel Takele Kenea, Miao Liang, Xin Lan, Yukio Terao, M. Kawser Ahmed, Manish Naja, Akihiko Ito, Isamu Morino, Yukio Yoshida, Yu Someya, Tazu Saeki, and Tsuneo Matsunaga
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-420, https://doi.org/10.5194/essd-2026-420, 2026
Preprint under review for ESSD
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Methane is a potent greenhouse gas driving climate change, yet Asian emissions remain highly uncertain. We conducted the first Methane Inversion inter-Comparison for Asia (MICA) combining seven models to estimate methane across Asia from 2010 to 2021 using satellite and ground data. We found that emissions are generally lower than prior inventories, though some countries underreport. This study provides a comprehensive, transparent dataset to quantify regional methane budgets across Asia.
Carlo Arosio, Alexei Rozanov, Vladimir Rozanov, Andrea Orfanoz-Cheuquelaf, John P. Burrows, Edward Malina, and Hartmut Boesch
EGUsphere, https://doi.org/10.5194/egusphere-2026-5113, https://doi.org/10.5194/egusphere-2026-5113, 2026
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We present an improved method for retrieving ozone profiles from OMPS satellite limb observations. The aim is to mitigate an artifact related to the variation of surface reflectivity along the satellite line of sight. We prescribe surface reflectivity from VIIRS to mitigate the artifact, particularly in regions with sharp changes in reflectivity, such as coastlines and transitions between clouds and ocean. Updated stratospheric ozone profiles and tropospheric ozone column products are presented.
Anteneh Getachew Mengistu, Aki Tsuruta, Antoine Berchet, Rona Thompson, Maria Tenkanen, Hannakaisa Lindqvist, Tiina Markkanen, Antti Leppänen, Antti Laitinen, Adrien Martinez, Audrey Fortems-Cheiney, Lena Höglund-Isaksson, and Tuula Aalto
Atmos. Chem. Phys., 26, 12295–12327, https://doi.org/10.5194/acp-26-12295-2026, https://doi.org/10.5194/acp-26-12295-2026, 2026
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Our manuscript presents a six-year, high-resolution inversion of European methane emissions using the Community Inversion Framework and FLEXPART. Leveraging an expanded in situ network, we reconcile inventories with observations, reveal regional biases, refine European methane budgets, and highlight the dominance of agricultural emissions. Results provide policy-relevant insights for mitigation and inventory verification.
Blanka Piskala Gvoždíková, Johanna Mayer, Saskia Maria Brose, Edward Malina, Daniele Gasbarra, Anežka Doležalová, and Krasen Samardzhiev
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-470, https://doi.org/10.5194/essd-2026-470, 2026
Preprint under review for ESSD
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This study introduces Lightning2EarthCARE, an open dataset linking satellite lightning observations with narrow vertical slices through storms from the Earth Cloud, Aerosol and Radiation Explorer mission. Covering August 2024 to January 2026, it includes more than 6000 storms available for case studies and broader analyses. The dataset can help reveal how lightning relates to cloud particles, precipitation, and storm motion, supporting better weather and climate models.
Fiona Lippert, Andrew Gerald Barr, Marcos Herreras-Giralda, Masahiro Momoi, Fernando Rejano, Sha Lu, Otto Hasekamp, Oleg Dubovik, Edward Malina, and Jochen Landgraf
EGUsphere, https://doi.org/10.5194/egusphere-2026-4724, https://doi.org/10.5194/egusphere-2026-4724, 2026
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Retrieving greenhouse gas concentrations from satellite measurements is computationally demanding. We show that machine learning can greatly accelerate this process while maintaining high accuracy and interpretability. Combining simplified atmospheric simulations with neural networks proved substantially more reliable than using machine learning alone. This hybrid approach could facilitate near-real time processing of rapidly increasing data volumes.
Joël Thanwerdas, Paolo Cristofanelli, Angela Fiore, Rianne Dröge, Sophie Van Mil, Yohanna Villalobos, Zhendong Wu, and Dominik Brunner
Atmos. Chem. Phys., 26, 10477–10507, https://doi.org/10.5194/acp-26-10477-2026, https://doi.org/10.5194/acp-26-10477-2026, 2026
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We assess how expanding Italy’s sparse ICOS (Integrated Carbon Observation System) methane network could improve methane emission estimates. Using transport modelling, data assimilation methods and synthetic observations, we test eight candidate sites. Chieti, in Central Italy and Mount Venda, in Northern Italy, provide the strongest added constraints, respectively. The framework developed here can be applied to other countries to optimize their atmospheric measurement networks and to improve constraints on greenhouse gas emissions.
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
Atmos. Chem. Phys., 26, 10423–10454, https://doi.org/10.5194/acp-26-10423-2026, https://doi.org/10.5194/acp-26-10423-2026, 2026
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Assimilating satellite methane observations provides top-down quantification of regional methane emissions. This study compares European emissions in 2019 estimated from the inversion of three satellite datasets. We find inconsistencies in national budgets and spatial patterns, with no product clearly superior. We disentangle drivers of the differences in emissions, highlighting the impact of differences in coverage, observations and errors on the consistency of methane emission estimates.
Bibhasvata Dasgupta, Sudhanshu Pandey, Sander Houweling, Malika Menoud, Carina van der Veen, John Miller, Ben Riddell-Young, Sylvia Englund Michel, Peter Sperlich, Shinji Morimoto, Ryo Fujita, Stephen Platt, Christine Groot Zwaaftink, Ingeborg Levin, Cordelia Veidt, Cathrine Lund Myhre, Ceres Woolley Maisch, Rebecca Fisher, Euan G. Nisbet, James France, Rowena Moss, Nicola Warwick, and Thomas Röckmann
Atmos. Chem. Phys., 26, 8601–8616, https://doi.org/10.5194/acp-26-8601-2026, https://doi.org/10.5194/acp-26-8601-2026, 2026
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Methane is a strong greenhouse gas, and its rise since the mid-2000s is debated in terms of sources and sinks. Using top-down and bottom-up data, along with inversion models and methane isotopes (δ13C-CH4 and δD-CH4), we find that wetlands are the primary driver of post-2006 increases, followed by agriculture and fossil fuels. Methane's lifetime has decreased by about 0.1 years. We also assess how isotope signatures and sink processes influence uncertainties.
Monika E. Szelag, Viktoria F. Sofieva, Edward Malina, Pekka T. Verronen, Michelle L. Santee, Manuel López-Puertas, Bernd Funke, Gabriele Stiller, Alexandra Laeng, Kaley A. Walker, Patrick E. Sheese, Mark E. Hervig, and Benjamin T. Marshall
Atmos. Chem. Phys., 26, 7503–7522, https://doi.org/10.5194/acp-26-7503-2026, https://doi.org/10.5194/acp-26-7503-2026, 2026
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We present a new global dataset of ozone profiles in the mesosphere and lower thermosphere, created by combining several satellite measurements covering more than three decades. Our results show that ozone is recovering in the stratosphere but decreasing in the mesosphere, with the strongest declines near the mesopause. This dataset provides a valuable resource for investigating long-term changes, improving model performance, and addressing an observational gap in the upper atmosphere.
Mengze Li, Robert B. Jackson, Marielle Saunois, Philippe Ciais, Ben Poulter, Josep G. Canadell, Prabir K. Patra, Hanqin Tian, Zhen Zhang, Etienne Fluet-Chouinard, Zutao Ouyang, Ting Zhang, David J. Beerling, Dmitry A. Belikov, Philippe Bousquet, Danilo Custodio, Naveen Chandra, Xinyu Dou, Nicola Gedney, Peter O. Hopcroft, Alison M. Hoyt, Kazuhito Ichii, Akihito Ito, Atul K. Jain, Katherine Jensen, Fortunat Joos, Thomas Kleinen, Masayuki Kondo, Fa Li, Tingting Li, Xiangyu Liu, Shamil Maksyutov, Avni Malhotra, Adrien Martinez, Kyle McDonald, Joe R. Melton, Jurek Müller, Yosuke Niwa, Shufen Pan, Shushi Peng, Changhui Peng, Zhangcai Qin, Peter Raymond, William Riley, Arjo Segers, Rona L. Thompson, Aki Tsuruta, Yi Xi, Kunxiaojia Yuan, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 18, 3507–3524, https://doi.org/10.5194/essd-18-3507-2026, https://doi.org/10.5194/essd-18-3507-2026, 2026
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We proposed a framework that combines machine-learning and climate data to predict global natural vegetated wetland methane emissions for 2000–2025. We found that although total global emissions remained stable in the post-2020s, Northern Hemisphere emissions surged whilst tropical emissions fell. This approach allows us to rapidly monitor emissions and provides early warnings for climate impacts.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Kjetil Aas, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Nicolas Bellouin, Alice Benoit-Cattin, Carla F. Berghoff, Raffaele Bernardello, Laurent Bopp, Ida Bagus Mandhara Brasika, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Nathan O. Collier, Thomas H. Colligan, Margot Cronin, Laique M. Djeutchouang, Xinyu Dou, Matt P. Enright, Kazutaka Enyo, Michael Erb, Wiley Evans, Richard A. Feely, Liang Feng, Daniel J. Ford, Adrianna Foster, Filippa Fransner, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Jefferson Goncalves De Souza, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Bertrand Guenet, Özgür Gürses, Kirsty Harrington, Ian Harris, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Akihiko Ito, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Steve D. Jones, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Yawen Kong, Jan Ivar Korsbakken, Charles Koven, Taro Kunimitsu, Xin Lan, Junjie Liu, Zhiqiang Liu, Zhu Liu, Claire Lo Monaco, Lei Ma, Gregg Marland, Patrick C. McGuire, Galen A. McKinley, Joe R. Melton, Natalie Monacci, Erwan Monier, Eric J. Morgan, David R. Munro, Jens D. Müller, Shin-Ichiro Nakaoka, Lorna R. Nayagam, Yosuke Niwa, Tobias Nutzel, Are Olsen, Abdirahman M. Omar, Naiqing Pan, Sudhanshu Pandey, Denis Pierrot, Zhangcai Qin, Pierre Regnier, Gregor Rehder, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, Ingunn Skjelvan, T. Luke Smallman, Victoria Spada, Mohanan G. Sreeush, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Didier Swingedouw, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Xiangjun Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Erik van Ooijen, Guido R. van der Werf, Sebastiaan J. van de Velde, Anthony P. Walker, Rik Wanninkhof, Xiaojuan Yang, Wenping Yuan, Xu Yue, and Jiye Zeng
Earth Syst. Sci. Data, 18, 3211–3288, https://doi.org/10.5194/essd-18-3211-2026, https://doi.org/10.5194/essd-18-3211-2026, 2026
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The Global Carbon Budget 2025 describes the methodology, main results, and datasets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2025). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
William F. Lamb, Robbie M. Andrew, Matthew Jones, Zebedee Nicholls, Glen P. Peters, Chris Smith, Marielle Saunois, Giacomo Grassi, Julia Pongratz, Steven J. Smith, Francesco N. Tubiello, Monica Crippa, Matthew Gidden, Pierre Friedlingstein, Jan Minx, and Piers M. Forster
Earth Syst. Sci. Data, 18, 2549–2572, https://doi.org/10.5194/essd-18-2549-2026, https://doi.org/10.5194/essd-18-2549-2026, 2026
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This study explores why global greenhouse gas (GHG) emissions estimates vary. Key reasons include different coverage of gases and sectors, varying definitions of anthropogenic land use change emissions, and the Paris Agreement not covering all emission sources. The study highlights three main ways emissions data is reported, each with different objectives and resulting in varying global emission totals. It emphasizes the need for transparency in choosing datasets and setting assessment scopes.
Nasrin Mostafavi Pak, Jonas Hachmeister, Markus Rettinger, Matthias Buschmann, Nicholas M. Deutscher, David W. T. Griffith, Laura T. Iraci, Xin Lan, Erin McGee, Isamu Morino, Dave Pollard, Coleen M. Roehl, Kimberly Strong, Rigel Kivi, and Paul Wennberg
Biogeosciences, 23, 1477–1495, https://doi.org/10.5194/bg-23-1477-2026, https://doi.org/10.5194/bg-23-1477-2026, 2026
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We studied how carbon dioxide (CO2) levels change each year using long-term measurements from twelve sites worldwide. Average growth rates from 2010 to 2024 were about 2.4 ppm/year, with notable year-to-year and regional differences. Natural climate patterns influenced these changes, while temporary shifts in human emissions, such as during COVID‑19, had modest local effects. Monitoring CO2 growth across regions helps track emissions and assess mitigation efforts.
Konstantinos Rizos, Emmanouil Proestakis, Thanasis Georgiou, Antonis Gkikas, Eleni Marinou, Peristera Paschou, Kalliopi Artemis Voudouri, Athanasios Tsikerdekis, David P. Donovan, Gerd-Jan van Zadelhoff, Angela Benedetti, Holger Baars, Athena Augusta Floutsi, Nikos Benas, Martin Stengel, Christian Retscher, Edward Malina, and Vassilis Amiridis
Atmos. Meas. Tech., 19, 699–728, https://doi.org/10.5194/amt-19-699-2026, https://doi.org/10.5194/amt-19-699-2026, 2026
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The Aeolus satellite's lidar system had limitations in detecting certain atmospheric layers and distinguishing between aerosol and cloud types. To improve accuracy, a new dust detection product was developed. By combining data from various sources and validating it with ground-based measurements, this enhanced product performs better than the original. It helps improve dust transport models and weather predictions, making it a valuable tool for atmospheric monitoring and forecasting.
Thomas Röckmann, Malika Menoud, Jacoline van Es, Carina van der Veen, Hossein Maazallahi, Pawel Jagoda, Jaroslav M. Necki, Jakub Bartyzel, Piotr Korben, Sara Defratyka, Martina Schmidt, Marius Corbu, Sebastian Iancu, Andreea Calcan, Magdalena Ardelean, Sorin Ghemulet, Cristian Pop, Andrei Radovici, Alexandru Mereuta, Horatiu Stefanie, and Calin Baciu
Atmos. Chem. Phys., 26, 723–731, https://doi.org/10.5194/acp-26-723-2026, https://doi.org/10.5194/acp-26-723-2026, 2026
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We report the isotopic composition of CH4 emitted from 48 installations in the gas production region of Transylvania, Romania which confirm the biogenic origin of the Transylvanian gas, produced by hydrogenotrophic CO2 reduction. This is similar to values reported previously from natural seeps and natural gas in a major city in the region. However, is more depleted in heavy isotopes than the oil-associated gas emitted in the Southern Romanian Plain, and gas leakages in the city of Bucharest.
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
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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.
Nicole Montenegro, Antoine Berchet, Adrien Martinez, Joël Thanwerdas, Phillipe Bousquet, Isabelle Pison, and Marielle Saunois
EGUsphere, https://doi.org/10.5194/egusphere-2025-5923, https://doi.org/10.5194/egusphere-2025-5923, 2025
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Top-down CH₄ flux estimates face substantial uncertainties arising from observational coverage, data and prior errors, and atmospheric transport. In this study, we use Observing System Simulation Experiments (OSSEs) to determine the capability of current observing systems to retrieve surface fluxes of CH₄ and to quantify the magnitude of their associated uncertainties. In situ data provide the strongest constraint, while combined systems inversions further enhance performance.
Pavel Litvinov, Cheng Chen, Oleg Dubovik, Siyao Zhai, Christian Matar, Chong Li, Anton Lopatin, David Fuertes, Tatyana Lapyonok, Lukas Bindreiter, Manuel Dornacher, Arthur Lehner, Alexandru Dandocsi, Daniele Gasbarra, and Christian Retscher
Atmos. Meas. Tech., 18, 7679–7716, https://doi.org/10.5194/amt-18-7679-2025, https://doi.org/10.5194/amt-18-7679-2025, 2025
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Developed SYREMIS (SYnergetic REtrieval from Multi-MISsion instruments) approach is based on three main principles: (i) harmonization of the multi-instruments L1 measurements, (ii) their “weighting”, and (iii) optimization of the forward models and the retrieval setups. It substantially enhances aerosol and surface characterization from spaceborne measurements. The approach can be extended to future missions, including synergy with multi-angular, multi-spectral, and polarimetric measurements.
Martin Vojta, Andreas Plach, Rona L. Thompson, Pallav Purohit, Kieran Stanley, Simon O'Doherty, Dickon Young, Joe Pitt, Jgor Arduini, Xin Lan, and Andreas Stohl
Atmos. Chem. Phys., 25, 15197–15243, https://doi.org/10.5194/acp-25-15197-2025, https://doi.org/10.5194/acp-25-15197-2025, 2025
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We determine European emissions of the highly potent greenhouse gas sulfur hexafluoride from 2005 to 2021 – focusing on high-emitting countries and the aggregated EU-27 emissions. Emissions declined in most regions, likely due to EU F-gas regulations. However, our results reveal that most studied countries underestimate their emissions in their national reports. Our sensitivity tests highlight the importance of dense observational networks for reliable inversion-based emission estimates.
Félix Langot, Cyril Crevoisier, Thomas Lauvaux, Charbel Abdallah, Jérôme Pernin, Xin Lin, Marielle Saunois, Axel Guedj, Thomas Ponthieu, Julien Moyé, Michel Ramonet, Anke Roiger, Klaus-Dirk Gottschaldt, and Alina Fiehn
Atmos. Meas. Tech., 18, 5955–5983, https://doi.org/10.5194/amt-18-5955-2025, https://doi.org/10.5194/amt-18-5955-2025, 2025
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Our study compares outputs from meteorological and atmospheric composition models to data from the MAGIC2021 campaign that took place in Sweden. Our results highlight performance differences among models, revealing strengths and weaknesses of different modelling techniques. We also found that wetland emission inventories overestimated emissions in regional simulations. This work helps to refine methane emission predictions, essential for understanding climate change.
Rimal Abeed, Audrey Fortems-Cheiney, Grégoire Broquet, Robin Plauchu, Isabelle Pison, Antoine Berchet, Elise Potier, Bo Zheng, Gaëlle Dufour, Adriana Coman, Dilek Savas, Guillaume Siour, Henk Eskes, Beatriz Revilla-Romero, Antony Delavois, and Philippe Ciais
EGUsphere, https://doi.org/10.5194/egusphere-2025-3329, https://doi.org/10.5194/egusphere-2025-3329, 2025
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We investigate changes in air pollution from nitrogen oxides NOx (=NO+NO2) across Eastern China from 2019 to 2021, using a satellite-based modelling approach. Our results show a drop in pollution in 2020 in most provinces, and along the China-Mongolia-Russia Economic Corridor. The analysis also captures emission variations during the Lunar New Year. By estimating emissions at the provincial level, the study provides insights into how major events and policy measures influence local air quality.
Carlo Arosio, Viktoria Sofieva, Andrea Orfanoz-Cheuquelaf, Alexei Rozanov, Klaus-Peter Heue, Diego Loyola, Edward Malina, Ryan M. Stauffer, David Tarasick, Roeland Van Malderen, Jerry R. Ziemke, and Mark Weber
Atmos. Meas. Tech., 18, 3247–3265, https://doi.org/10.5194/amt-18-3247-2025, https://doi.org/10.5194/amt-18-3247-2025, 2025
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Tropospheric ozone affects air quality and climate, being a pollutant and a greenhouse gas. We analyze satellite data of tropospheric ozone columns obtained by combining two types of observations: one providing stratospheric and the other total ozone. We compare common climatological features and study the influence of the tropopause (troposphere to stratosphere boundary) on the results. We also examine trends over the last 20 years and compare satellite data with ozonesondes to identify drifts.
Antoine Berchet, Isabelle Pison, Camille Huselstein, Clément Narbaud, Marine Remaud, Sauveur Belviso, Camille Abadie, and Fabienne Maignan
Atmos. Chem. Phys., 25, 7499–7525, https://doi.org/10.5194/acp-25-7499-2025, https://doi.org/10.5194/acp-25-7499-2025, 2025
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We use the measurements of atmospheric carbonyl sulfide (COS) concentrations at the monitoring site of Gif-sur-Yvette (in the Paris region) from August 2014 to December 2019, combined with existing knowledge on COS fluxes in the atmosphere and a transport model, to gain insight into COS fluxes, either natural, such as oceanic emissions or vegetation and soil fluxes, or anthropogenic, from industrial activities and power generation.
Yosuke Niwa, Yasunori Tohjima, Yukio Terao, Tazu Saeki, Akihiko Ito, Taku Umezawa, Kyohei Yamada, Motoki Sasakawa, Toshinobu Machida, Shin-Ichiro Nakaoka, Hideki Nara, Hiroshi Tanimoto, Hitoshi Mukai, Yukio Yoshida, Shinji Morimoto, Shinya Takatsuji, Kazuhiro Tsuboi, Yousuke Sawa, Hidekazu Matsueda, Kentaro Ishijima, Ryo Fujita, Daisuke Goto, Xin Lan, Kenneth Schuldt, Michal Heliasz, Tobias Biermann, Lukasz Chmura, Jarsolaw Necki, Irène Xueref-Remy, and Damiano Sferlazzo
Atmos. Chem. Phys., 25, 6757–6785, https://doi.org/10.5194/acp-25-6757-2025, https://doi.org/10.5194/acp-25-6757-2025, 2025
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This study estimated regional and sectoral emission contributions to the unprecedented surge of atmospheric methane for 2020–2022. The methane is the second most important greenhouse gas, and its emissions reduction is urgently required to mitigate global warming. Numerical modeling-based estimates with three different sets of atmospheric observations consistently suggested large contributions of biogenic emissions from South Asia and Southeast Asia to the surge of atmospheric methane.
Juliette Bernard, Catherine Prigent, Carlos Jimenez, Etienne Fluet-Chouinard, Bernhard Lehner, Elodie Salmon, Philippe Ciais, Zhen Zhang, Shushi Peng, and Marielle Saunois
Earth Syst. Sci. Data, 17, 2985–3008, https://doi.org/10.5194/essd-17-2985-2025, https://doi.org/10.5194/essd-17-2985-2025, 2025
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Wetlands are responsible for about a third of global emissions of methane, a potent greenhouse gas. We have developed the Global Inundation Extent from Multi-Satellites-MethaneCentric (GIEMS-MC) dataset to represent the dynamics of wetland extent on a global scale (0.25° × 0.25° resolution, monthly time step). This updated resource combines satellite data and existing wetland databases, covering 1992 to 2020. Consistent maps of other methane-emitting surface waters (lakes, rivers, reservoirs, rice paddies) are also provided.
Audrey Fortems-Cheiney, Grégoire Broquet, Elise Potier, Antoine Berchet, Isabelle Pison, Adrien Martinez, Robin Plauchu, Rimal Abeed, Aurélien Sicsik-Paré, Gaelle Dufour, Adriana Coman, Dilek Savas, Guillaume Siour, Henk Eskes, Hugo A. C. Denier van der Gon, and Stijn N. C. Dellaert
Atmos. Chem. Phys., 25, 6047–6068, https://doi.org/10.5194/acp-25-6047-2025, https://doi.org/10.5194/acp-25-6047-2025, 2025
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This study assesses the potential of the Ozone Monitoring Instrument (OMI) and the TROPOspheric Monitoring Instrument (TROPOMI) satellite observations to inform about the decrease in anthropogenic emissions of nitrogen oxides (NOx) in 2019 compared with 2005 at regional to national scales in Europe. Both the OMI and TROPOMI inversions show decreases in European NOx anthropogenic emission budgets in 2019 compared to 2005 but with different magnitudes.
Marielle Saunois, Adrien Martinez, Benjamin Poulter, Zhen Zhang, Peter A. Raymond, Pierre Regnier, Josep G. Canadell, Robert B. Jackson, Prabir K. Patra, Philippe Bousquet, Philippe Ciais, Edward J. Dlugokencky, Xin Lan, George H. Allen, David Bastviken, David J. Beerling, Dmitry A. Belikov, Donald R. Blake, Simona Castaldi, Monica Crippa, Bridget R. Deemer, Fraser Dennison, Giuseppe Etiope, Nicola Gedney, Lena Höglund-Isaksson, Meredith A. Holgerson, Peter O. Hopcroft, Gustaf Hugelius, Akihiko Ito, Atul K. Jain, Rajesh Janardanan, Matthew S. Johnson, Thomas Kleinen, Paul B. Krummel, Ronny Lauerwald, Tingting Li, Xiangyu Liu, Kyle C. McDonald, Joe R. Melton, Jens Mühle, Jurek Müller, Fabiola Murguia-Flores, Yosuke Niwa, Sergio Noce, Shufen Pan, Robert J. Parker, Changhui Peng, Michel Ramonet, William J. Riley, Gerard Rocher-Ros, Judith A. Rosentreter, Motoki Sasakawa, Arjo Segers, Steven J. Smith, Emily H. Stanley, Joël Thanwerdas, Hanqin Tian, Aki Tsuruta, Francesco N. Tubiello, Thomas S. Weber, Guido R. van der Werf, Douglas E. J. Worthy, Yi Xi, Yukio Yoshida, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 17, 1873–1958, https://doi.org/10.5194/essd-17-1873-2025, https://doi.org/10.5194/essd-17-1873-2025, 2025
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Methane (CH4) is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). A consortium of multi-disciplinary scientists synthesise and update the budget of the sources and sinks of CH4. This edition benefits from important progress in estimating emissions from lakes and ponds, reservoirs, and streams and rivers. For the 2010s decade, global CH4 emissions are estimated at 575 Tg CH4 yr-1, including ~65 % from anthropogenic sources.
Zhu Deng, Philippe Ciais, Liting Hu, Adrien Martinez, Marielle Saunois, Rona L. Thompson, Kushal Tibrewal, Wouter Peters, Brendan Byrne, Giacomo Grassi, Paul I. Palmer, Ingrid T. Luijkx, Zhu Liu, Junjie Liu, Xuekun Fang, Tengjiao Wang, Hanqin Tian, Katsumasa Tanaka, Ana Bastos, Stephen Sitch, Benjamin Poulter, Clément Albergel, Aki Tsuruta, Shamil Maksyutov, Rajesh Janardanan, Yosuke Niwa, Bo Zheng, Joël Thanwerdas, Dmitry Belikov, Arjo Segers, and Frédéric Chevallier
Earth Syst. Sci. Data, 17, 1121–1152, https://doi.org/10.5194/essd-17-1121-2025, https://doi.org/10.5194/essd-17-1121-2025, 2025
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This study reconciles national greenhouse gas (GHG) inventories with updated atmospheric inversion results to evaluate discrepancies for three principal GHG fluxes at the national level. Compared to our previous study, new satellite-based CO2 inversions were included and an updated mask of managed lands was used, improving agreement for Brazil and Canada. The proposed methodology can be regularly applied as a check to assess the gap between top-down inversions and bottom-up inventories.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Carla F. Berghoff, Henry C. Bittig, Laurent Bopp, Patricia Cadule, Katie Campbell, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Thomas Colligan, Jeanne Decayeux, Laique M. Djeutchouang, Xinyu Dou, Carolina Duran Rojas, Kazutaka Enyo, Wiley Evans, Amanda R. Fay, Richard A. Feely, Daniel J. Ford, Adrianna Foster, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Xin Lan, Siv K. Lauvset, Nathalie Lefèvre, Zhu Liu, Junjie Liu, Lei Ma, Shamil Maksyutov, Gregg Marland, Nicolas Mayot, Patrick C. McGuire, Nicolas Metzl, Natalie M. Monacci, Eric J. Morgan, Shin-Ichiro Nakaoka, Craig Neill, Yosuke Niwa, Tobias Nützel, Lea Olivier, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Zhangcai Qin, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Bronte Tilbrook, Olivier Torres, Etienne Tourigny, Hiroyuki Tsujino, Francesco Tubiello, Guido van der Werf, Rik Wanninkhof, Xuhui Wang, Dongxu Yang, Xiaojuan Yang, Zhen Yu, Wenping Yuan, Xu Yue, Sönke Zaehle, Ning Zeng, and Jiye Zeng
Earth Syst. Sci. Data, 17, 965–1039, https://doi.org/10.5194/essd-17-965-2025, https://doi.org/10.5194/essd-17-965-2025, 2025
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The Global Carbon Budget 2024 describes the methodology, main results, and datasets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2024). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
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
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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.
Juliette Bernard, Elodie Salmon, Marielle Saunois, Shushi Peng, Penélope Serrano-Ortiz, Antoine Berchet, Palingamoorthy Gnanamoorthy, Joachim Jansen, and Philippe Ciais
Geosci. Model Dev., 18, 863–883, https://doi.org/10.5194/gmd-18-863-2025, https://doi.org/10.5194/gmd-18-863-2025, 2025
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Despite their importance, uncertainties remain in the evaluation of the drivers of temporal variability of methane emissions from wetlands on a global scale. Here, a simplified global model is developed, taking advantage of advances in remote-sensing data and in situ observations. The model reproduces the large spatial and temporal patterns of emissions, albeit with limitations in the tropics due to data scarcity. This model, while simple, can provide valuable insights into sensitivity analyses.
Tuula Aalto, Aki Tsuruta, Jarmo Mäkelä, Jurek Müller, Maria Tenkanen, Eleanor Burke, Sarah Chadburn, Yao Gao, Vilma Mannisenaho, Thomas Kleinen, Hanna Lee, Antti Leppänen, Tiina Markkanen, Stefano Materia, Paul A. Miller, Daniele Peano, Olli Peltola, Benjamin Poulter, Maarit Raivonen, Marielle Saunois, David Wårlind, and Sönke Zaehle
Biogeosciences, 22, 323–340, https://doi.org/10.5194/bg-22-323-2025, https://doi.org/10.5194/bg-22-323-2025, 2025
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Wetland methane responses to temperature and precipitation were studied in a boreal wetland-rich region in northern Europe using ecosystem models, atmospheric inversions, and upscaled flux observations. The ecosystem models differed in their responses to temperature and precipitation and in their seasonality. However, multi-model means, inversions, and upscaled fluxes had similar seasonality, and they suggested co-limitation by temperature and precipitation.
Zhen Zhang, Benjamin Poulter, Joe R. Melton, William J. Riley, George H. Allen, David J. Beerling, Philippe Bousquet, Josep G. Canadell, Etienne Fluet-Chouinard, Philippe Ciais, Nicola Gedney, Peter O. Hopcroft, Akihiko Ito, Robert B. Jackson, Atul K. Jain, Katherine Jensen, Fortunat Joos, Thomas Kleinen, Sara H. Knox, Tingting Li, Xin Li, Xiangyu Liu, Kyle McDonald, Gavin McNicol, Paul A. Miller, Jurek Müller, Prabir K. Patra, Changhui Peng, Shushi Peng, Zhangcai Qin, Ryan M. Riggs, Marielle Saunois, Qing Sun, Hanqin Tian, Xiaoming Xu, Yuanzhi Yao, Yi Xi, Wenxin Zhang, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Biogeosciences, 22, 305–321, https://doi.org/10.5194/bg-22-305-2025, https://doi.org/10.5194/bg-22-305-2025, 2025
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This study assesses global methane emissions from wetlands between 2000 and 2020 using multiple models. We found that wetland emissions increased by 6–7 Tg CH4 yr-1 in the 2010s compared to the 2000s. Rising temperatures primarily drove this increase, while changes in precipitation and CO2 levels also played roles. Our findings highlight the importance of wetlands in the global methane budget and the need for continuous monitoring to understand their impact on climate change.
Martin Vojta, Andreas Plach, Saurabh Annadate, Sunyoung Park, Gawon Lee, Pallav Purohit, Florian Lindl, Xin Lan, Jens Mühle, Rona L. Thompson, and Andreas Stohl
Atmos. Chem. Phys., 24, 12465–12493, https://doi.org/10.5194/acp-24-12465-2024, https://doi.org/10.5194/acp-24-12465-2024, 2024
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We constrain the global emissions of the very potent greenhouse gas sulfur hexafluoride (SF6) between 2005 and 2021. We show that SF6 emissions are decreasing in the USA and in the EU, while they are substantially growing in China, leading overall to an increasing global emission trend. The national reports for the USA, EU, and China all underestimated their SF6 emissions. However, stringent mitigation measures can successfully reduce SF6 emissions, as can be seen in the EU emission trend.
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
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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.
Cynthia D. Nevison, Qing Liang, Paul A. Newman, Britton B. Stephens, Geoff Dutton, Xin Lan, Roisin Commane, Yenny Gonzalez, and Eric Kort
Atmos. Chem. Phys., 24, 10513–10529, https://doi.org/10.5194/acp-24-10513-2024, https://doi.org/10.5194/acp-24-10513-2024, 2024
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This study examines the drivers of interannual variability in tropospheric N2O. New insights are obtained from aircraft data and a chemistry–climate model that explicitly simulates stratospheric N2O. The stratosphere is found to be the dominant driver of N2O variability in the Northern Hemisphere, while both the stratosphere and El Niño cycles are important in the Southern Hemisphere. These results are consistent with known atmospheric dynamics and differences between the hemispheres.
Robin Plauchu, Audrey Fortems-Cheiney, Grégoire Broquet, Isabelle Pison, Antoine Berchet, Elise Potier, Gaëlle Dufour, Adriana Coman, Dilek Savas, Guillaume Siour, and Henk Eskes
Atmos. Chem. Phys., 24, 8139–8163, https://doi.org/10.5194/acp-24-8139-2024, https://doi.org/10.5194/acp-24-8139-2024, 2024
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This study uses the Community Inversion Framework and CHIMERE model to assess the potential of TROPOMI-S5P PAL NO2 tropospheric column data to estimate NOx emissions in France (2019–2021). Results show a 3 % decrease in average emissions compared to the 2016 CAMS-REG/INS, lower than the 14 % decrease from CITEPA. The study highlights challenges in capturing emission anomalies due to limited data coverage and error levels but shows promise for local inventory improvements.
Hanqin Tian, Naiqing Pan, Rona L. Thompson, Josep G. Canadell, Parvadha Suntharalingam, Pierre Regnier, Eric A. Davidson, Michael Prather, Philippe Ciais, Marilena Muntean, Shufen Pan, Wilfried Winiwarter, Sönke Zaehle, Feng Zhou, Robert B. Jackson, Hermann W. Bange, Sarah Berthet, Zihao Bian, Daniele Bianchi, Alexander F. Bouwman, Erik T. Buitenhuis, Geoffrey Dutton, Minpeng Hu, Akihiko Ito, Atul K. Jain, Aurich Jeltsch-Thömmes, Fortunat Joos, Sian Kou-Giesbrecht, Paul B. Krummel, Xin Lan, Angela Landolfi, Ronny Lauerwald, Ya Li, Chaoqun Lu, Taylor Maavara, Manfredi Manizza, Dylan B. Millet, Jens Mühle, Prabir K. Patra, Glen P. Peters, Xiaoyu Qin, Peter Raymond, Laure Resplandy, Judith A. Rosentreter, Hao Shi, Qing Sun, Daniele Tonina, Francesco N. Tubiello, Guido R. van der Werf, Nicolas Vuichard, Junjie Wang, Kelley C. Wells, Luke M. Western, Chris Wilson, Jia Yang, Yuanzhi Yao, Yongfa You, and Qing Zhu
Earth Syst. Sci. Data, 16, 2543–2604, https://doi.org/10.5194/essd-16-2543-2024, https://doi.org/10.5194/essd-16-2543-2024, 2024
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Atmospheric concentrations of nitrous oxide (N2O), a greenhouse gas 273 times more potent than carbon dioxide, have increased by 25 % since the preindustrial period, with the highest observed growth rate in 2020 and 2021. This rapid growth rate has primarily been due to a 40 % increase in anthropogenic emissions since 1980. Observed atmospheric N2O concentrations in recent years have exceeded the worst-case climate scenario, underscoring the importance of reducing anthropogenic N2O emissions.
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Bradley Hall, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan P. Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Blair Trewin, Myles Allen, Robbie Andrew, Richard A. Betts, Alex Borger, Tim Boyer, Jiddu A. Broersma, Carlo Buontempo, Samantha Burgess, Chiara Cagnazzo, Lijing Cheng, Pierre Friedlingstein, Andrew Gettelman, Johannes Gütschow, Masayoshi Ishii, Stuart Jenkins, Xin Lan, Colin Morice, Jens Mühle, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Jan C. Minx, Gunnar Myhre, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, Sophie Szopa, Peter Thorne, Mahesh V. M. Kovilakam, Elisa Majamäki, Jukka-Pekka Jalkanen, Margreet van Marle, Rachel M. Hoesly, Robert Rohde, Dominik Schumacher, Guido van der Werf, Russell Vose, Kirsten Zickfeld, Xuebin Zhang, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 16, 2625–2658, https://doi.org/10.5194/essd-16-2625-2024, https://doi.org/10.5194/essd-16-2625-2024, 2024
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This paper tracks some key indicators of global warming through time, from 1850 through to the end of 2023. It is designed to give an authoritative estimate of global warming to date and its causes. We find that in 2023, global warming reached 1.3 °C and is increasing at over 0.2 °C per decade. This is caused by all-time-high greenhouse gas emissions.
Sophie Wittig, Antoine Berchet, Isabelle Pison, Marielle Saunois, and Jean-Daniel Paris
Atmos. Chem. Phys., 24, 6359–6373, https://doi.org/10.5194/acp-24-6359-2024, https://doi.org/10.5194/acp-24-6359-2024, 2024
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The aim of this work is to analyse how accurately a methane bomb event could be detected with the current and a hypothetically extended stationary observation network in the Arctic. For this, we incorporate synthetically modelled possible future CH4 concentrations based on plausible emission scenarios into an inverse modelling framework. We analyse how well the increase is detected in different Arctic regions and evaluate the impact of additional observation sites in this respect.
Joshua L. Laughner, Geoffrey C. Toon, Joseph Mendonca, Christof Petri, Sébastien Roche, Debra Wunch, Jean-Francois Blavier, David W. T. Griffith, Pauli Heikkinen, Ralph F. Keeling, Matthäus Kiel, Rigel Kivi, Coleen M. Roehl, Britton B. Stephens, Bianca C. Baier, Huilin Chen, Yonghoon Choi, Nicholas M. Deutscher, Joshua P. DiGangi, Jochen Gross, Benedikt Herkommer, Pascal Jeseck, Thomas Laemmel, Xin Lan, Erin McGee, Kathryn McKain, John Miller, Isamu Morino, Justus Notholt, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Haris Riris, Constantina Rousogenous, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Steven C. Wofsy, Minqiang Zhou, and Paul O. Wennberg
Earth Syst. Sci. Data, 16, 2197–2260, https://doi.org/10.5194/essd-16-2197-2024, https://doi.org/10.5194/essd-16-2197-2024, 2024
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This paper describes a new version, called GGG2020, of a data set containing column-integrated observations of greenhouse and related gases (including CO2, CH4, CO, and N2O) made by ground stations located around the world. Compared to the previous version (GGG2014), improvements have been made toward site-to-site consistency. This data set plays a key role in validating space-based greenhouse gas observations and in understanding the carbon cycle.
Audrey Fortems-Cheiney, Gregoire Broquet, Elise Potier, Robin Plauchu, Antoine Berchet, Isabelle Pison, Hugo Denier van der Gon, and Stijn Dellaert
Atmos. Chem. Phys., 24, 4635–4649, https://doi.org/10.5194/acp-24-4635-2024, https://doi.org/10.5194/acp-24-4635-2024, 2024
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We have estimated the carbon monixide (CO) European emissions from satellite observations of the MOPITT instrument at the relatively high resolution of 0.5° for a period of over 10 years from 2011 to 2021. The analysis of the inversion results reveals the challenges associated with the inversion of CO emissions at the regional scale over Europe.
Joël Thanwerdas, Marielle Saunois, Antoine Berchet, Isabelle Pison, and Philippe Bousquet
Atmos. Chem. Phys., 24, 2129–2167, https://doi.org/10.5194/acp-24-2129-2024, https://doi.org/10.5194/acp-24-2129-2024, 2024
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We investigate the causes of the renewed growth of atmospheric methane (CH4) after 2007 using inverse modeling. We use the additional information provided by observations of CH4 isotopic compositions to better differentiate between the emission categories. Accounting for the large uncertainties in source signatures, our results suggest that the post-2007 increase in atmospheric CH4 was caused by similar increases in emissions from (1) fossil fuels and (2) agriculture and waste.
Zhendong Wu, Alex Vermeulen, Yousuke Sawa, Ute Karstens, Wouter Peters, Remco de Kok, Xin Lan, Yasuyuki Nagai, Akinori Ogi, and Oksana Tarasova
Atmos. Chem. Phys., 24, 1249–1264, https://doi.org/10.5194/acp-24-1249-2024, https://doi.org/10.5194/acp-24-1249-2024, 2024
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This study focuses on exploring the differences in calculating global surface CO2 and its growth rate, considering the impact of analysis methodologies and site selection. Our study reveals that the current global CO2 network has a good capacity to represent global surface CO2 and its growth rate, as well as trends in atmospheric CO2 mass changes. However, small differences exist in different analyses due to the impact of methodology and site selection.
Alina Fiehn, Maximilian Eckl, Julian Kostinek, Michał Gałkowski, Christoph Gerbig, Michael Rothe, Thomas Röckmann, Malika Menoud, Hossein Maazallahi, Martina Schmidt, Piotr Korbeń, Jarosław Neçki, Mila Stanisavljević, Justyna Swolkień, Andreas Fix, and Anke Roiger
Atmos. Chem. Phys., 23, 15749–15765, https://doi.org/10.5194/acp-23-15749-2023, https://doi.org/10.5194/acp-23-15749-2023, 2023
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During the CoMet mission in the Upper Silesian Coal Basin (USCB) ground-based and airborne air samples were taken and analyzed for the isotopic composition of CH4 to derive the mean signature of the USCB and source signatures of individual coal mines. Using δ2H signatures, the biogenic emissions from the USCB account for 15 %–50 % of total emissions, which is underestimated in common emission inventories. This demonstrates the importance of δ2H-CH4 observations for methane source apportionment.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
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The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Matthew J. McGrath, Ana Maria Roxana Petrescu, Philippe Peylin, Robbie M. Andrew, Bradley Matthews, Frank Dentener, Juraj Balkovič, Vladislav Bastrikov, Meike Becker, Gregoire Broquet, Philippe Ciais, Audrey Fortems-Cheiney, Raphael Ganzenmüller, Giacomo Grassi, Ian Harris, Matthew Jones, Jürgen Knauer, Matthias Kuhnert, Guillaume Monteil, Saqr Munassar, Paul I. Palmer, Glen P. Peters, Chunjing Qiu, Mart-Jan Schelhaas, Oksana Tarasova, Matteo Vizzarri, Karina Winkler, Gianpaolo Balsamo, Antoine Berchet, Peter Briggs, Patrick Brockmann, Frédéric Chevallier, Giulia Conchedda, Monica Crippa, Stijn N. C. Dellaert, Hugo A. C. Denier van der Gon, Sara Filipek, Pierre Friedlingstein, Richard Fuchs, Michael Gauss, Christoph Gerbig, Diego Guizzardi, Dirk Günther, Richard A. Houghton, Greet Janssens-Maenhout, Ronny Lauerwald, Bas Lerink, Ingrid T. Luijkx, Géraud Moulas, Marilena Muntean, Gert-Jan Nabuurs, Aurélie Paquirissamy, Lucia Perugini, Wouter Peters, Roberto Pilli, Julia Pongratz, Pierre Regnier, Marko Scholze, Yusuf Serengil, Pete Smith, Efisio Solazzo, Rona L. Thompson, Francesco N. Tubiello, Timo Vesala, and Sophia Walther
Earth Syst. Sci. Data, 15, 4295–4370, https://doi.org/10.5194/essd-15-4295-2023, https://doi.org/10.5194/essd-15-4295-2023, 2023
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Accurate estimation of fluxes of carbon dioxide from the land surface is essential for understanding future impacts of greenhouse gas emissions on the climate system. A wide variety of methods currently exist to estimate these sources and sinks. We are continuing work to develop annual comparisons of these diverse methods in order to clarify what they all actually calculate and to resolve apparent disagreement, in addition to highlighting opportunities for increased understanding.
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
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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.
Alice Drinkwater, Paul I. Palmer, Liang Feng, Tim Arnold, Xin Lan, Sylvia E. Michel, Robert Parker, and Hartmut Boesch
Atmos. Chem. Phys., 23, 8429–8452, https://doi.org/10.5194/acp-23-8429-2023, https://doi.org/10.5194/acp-23-8429-2023, 2023
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Changes in atmospheric methane over the last few decades are largely unexplained. Previous studies have proposed different hypotheses to explain short-term changes in atmospheric methane. We interpret observed changes in atmospheric methane and stable isotope source signatures (2004–2020). We argue that changes over this period are part of a large-scale shift from high-northern-latitude thermogenic energy emissions to tropical biogenic emissions, particularly from North Africa and South America.
Sophie Wittig, Antoine Berchet, Isabelle Pison, Marielle Saunois, Joël Thanwerdas, Adrien Martinez, Jean-Daniel Paris, Toshinobu Machida, Motoki Sasakawa, Douglas E. J. Worthy, Xin Lan, Rona L. Thompson, Espen Sollum, and Mikhail Arshinov
Atmos. Chem. Phys., 23, 6457–6485, https://doi.org/10.5194/acp-23-6457-2023, https://doi.org/10.5194/acp-23-6457-2023, 2023
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Here, an inverse modelling approach is applied to estimate CH4 sources and sinks in the Arctic from 2008 to 2019. We study the magnitude, seasonal patterns and trends from different sources during recent years. We also assess how the current observation network helps to constrain fluxes. We find that constraints are only significant for North America and, to a lesser extent, West Siberia, where the observation network is relatively dense. We find no clear trend over the period of inversion.
Piers M. Forster, Christopher J. Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Sonia I. Seneviratne, Blair Trewin, Xuebin Zhang, Myles Allen, Robbie Andrew, Arlene Birt, Alex Borger, Tim Boyer, Jiddu A. Broersma, Lijing Cheng, Frank Dentener, Pierre Friedlingstein, José M. Gutiérrez, Johannes Gütschow, Bradley Hall, Masayoshi Ishii, Stuart Jenkins, Xin Lan, June-Yi Lee, Colin Morice, Christopher Kadow, John Kennedy, Rachel Killick, Jan C. Minx, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sophie Szopa, Peter Thorne, Robert Rohde, Maisa Rojas Corradi, Dominik Schumacher, Russell Vose, Kirsten Zickfeld, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 15, 2295–2327, https://doi.org/10.5194/essd-15-2295-2023, https://doi.org/10.5194/essd-15-2295-2023, 2023
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This is a critical decade for climate action, but there is no annual tracking of the level of human-induced warming. We build on the Intergovernmental Panel on Climate Change assessment reports that are authoritative but published infrequently to create a set of key global climate indicators that can be tracked through time. Our hope is that this becomes an important annual publication that policymakers, media, scientists and the public can refer to.
Truls Andersen, Zhao Zhao, Marcel de Vries, Jaroslaw Necki, Justyna Swolkien, Malika Menoud, Thomas Röckmann, Anke Roiger, Andreas Fix, Wouter Peters, and Huilin Chen
Atmos. Chem. Phys., 23, 5191–5216, https://doi.org/10.5194/acp-23-5191-2023, https://doi.org/10.5194/acp-23-5191-2023, 2023
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The Upper Silesian Coal Basin, Poland, is one of the hot spots of methane emissions in Europe. Using an uncrewed aerial vehicle (UAV), we performed atmospheric measurements of methane concentrations downwind of five ventilation shafts in this region and determined the emission rates from the individual shafts. We found a strong correlation between quantified shaft-averaged emission rates and hourly inventory data, which also allows us to estimate the methane emissions from the entire region.
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
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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.
Clément Narbaud, Jean-Daniel Paris, Sophie Wittig, Antoine Berchet, Marielle Saunois, Philippe Nédélec, Boris D. Belan, Mikhail Y. Arshinov, Sergei B. Belan, Denis Davydov, Alexander Fofonov, and Artem Kozlov
Atmos. Chem. Phys., 23, 2293–2314, https://doi.org/10.5194/acp-23-2293-2023, https://doi.org/10.5194/acp-23-2293-2023, 2023
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We measured CH4 and CO2 from aircraft over the Russian Arctic. Analyzing our data with the Lagrangian model FLEXPART, we find a sharp east–west gradient in atmospheric composition. Western Siberia is influenced by strong wetland CH4 emissions, deep CO2 gradient from biospheric uptake, and long-range transport from Europe and North America. Eastern flights document less variability. Over the Arctic Ocean, we find a small influence from marine CH4 emissions compatible with reasonable inventories.
Yuanhong Zhao, Marielle Saunois, Philippe Bousquet, Xin Lin, Michaela I. Hegglin, Josep G. Canadell, Robert B. Jackson, and Bo Zheng
Atmos. Chem. Phys., 23, 789–807, https://doi.org/10.5194/acp-23-789-2023, https://doi.org/10.5194/acp-23-789-2023, 2023
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The large uncertainties in OH simulated by atmospheric chemistry models hinder accurate estimates of CH4 chemical loss through the bottom-up method. This study presents a new approach based on OH precursor observations and a chemical box model to improve the tropospheric OH distributions simulated by atmospheric chemistry models. Through this approach, both the global OH burden and the corresponding methane chemical loss reach consistency with the top-down method based on MCF inversions.
Bryce F. J. Kelly, Xinyi Lu, Stephen J. Harris, Bruno G. Neininger, Jorg M. Hacker, Stefan Schwietzke, Rebecca E. Fisher, James L. France, Euan G. Nisbet, David Lowry, Carina van der Veen, Malika Menoud, and Thomas Röckmann
Atmos. Chem. Phys., 22, 15527–15558, https://doi.org/10.5194/acp-22-15527-2022, https://doi.org/10.5194/acp-22-15527-2022, 2022
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This study explores using the composition of methane of in-flight atmospheric air samples for greenhouse gas inventory verification. The air samples were collected above one of the largest coal seam gas production regions in the world. Adjacent to these gas fields are coal mines, Australia's largest cattle feedlot, and over 1 million grazing cattle. The results are also used to identify methane mitigation opportunities.
Joël Thanwerdas, Marielle Saunois, Isabelle Pison, Didier Hauglustaine, Antoine Berchet, Bianca Baier, Colm Sweeney, and Philippe Bousquet
Atmos. Chem. Phys., 22, 15489–15508, https://doi.org/10.5194/acp-22-15489-2022, https://doi.org/10.5194/acp-22-15489-2022, 2022
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Atmospheric methane (CH4) concentrations have been rising since 2007, resulting from an imbalance between CH4 sources and sinks. The CH4 budget is generally estimated through top-down approaches using CH4 and δ13C(CH4) observations as constraints. The oxidation by chlorine (Cl) contributes little to the total oxidation of CH4 but strongly influences δ13C(CH4). Here, we compare multiple recent Cl fields and quantify the influence of Cl concentrations on CH4, δ13C(CH4), and CH4 budget estimates.
Sourish Basu, Xin Lan, Edward Dlugokencky, Sylvia Michel, Stefan Schwietzke, John B. Miller, Lori Bruhwiler, Youmi Oh, Pieter P. Tans, Francesco Apadula, Luciana V. Gatti, Armin Jordan, Jaroslaw Necki, Motoki Sasakawa, Shinji Morimoto, Tatiana Di Iorio, Haeyoung Lee, Jgor Arduini, and Giovanni Manca
Atmos. Chem. Phys., 22, 15351–15377, https://doi.org/10.5194/acp-22-15351-2022, https://doi.org/10.5194/acp-22-15351-2022, 2022
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Atmospheric methane (CH4) has been growing steadily since 2007 for reasons that are not well understood. Here we determine sources of methane using a technique informed by atmospheric measurements of CH4 and its isotopologue 13CH4. Measurements of 13CH4 provide for better separation of microbial, fossil, and fire sources of methane than CH4 measurements alone. Compared to previous assessments such as the Global Carbon Project, we find a larger microbial contribution to the post-2007 increase.
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
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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.
Angharad C. Stell, Michael Bertolacci, Andrew Zammit-Mangion, Matthew Rigby, Paul J. Fraser, Christina M. Harth, Paul B. Krummel, Xin Lan, Manfredi Manizza, Jens Mühle, Simon O'Doherty, Ronald G. Prinn, Ray F. Weiss, Dickon Young, and Anita L. Ganesan
Atmos. Chem. Phys., 22, 12945–12960, https://doi.org/10.5194/acp-22-12945-2022, https://doi.org/10.5194/acp-22-12945-2022, 2022
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Nitrous oxide is a potent greenhouse gas and ozone-depleting substance, whose atmospheric abundance has risen throughout the contemporary record. In this work, we carry out the first global hierarchical Bayesian inversion to solve for nitrous oxide emissions. We derive increasing global nitrous oxide emissions over 2011–2020, which are mainly driven by emissions between 0° and 30°N, with the highest emissions recorded in 2020.
Malika Menoud, Carina van der Veen, Dave Lowry, Julianne M. Fernandez, Semra Bakkaloglu, James L. France, Rebecca E. Fisher, Hossein Maazallahi, Mila Stanisavljević, Jarosław Nęcki, Katarina Vinkovic, Patryk Łakomiec, Janne Rinne, Piotr Korbeń, Martina Schmidt, Sara Defratyka, Camille Yver-Kwok, Truls Andersen, Huilin Chen, and Thomas Röckmann
Earth Syst. Sci. Data, 14, 4365–4386, https://doi.org/10.5194/essd-14-4365-2022, https://doi.org/10.5194/essd-14-4365-2022, 2022
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Emission sources of methane (CH4) can be distinguished with measurements of CH4 stable isotopes. We present new measurements of isotope signatures of various CH4 sources in Europe, mainly anthropogenic, sampled from 2017 to 2020. The present database also contains the most recent update of the global signature dataset from the literature. The dataset improves CH4 source attribution and the understanding of the global CH4 budget.
Elise Potier, Grégoire Broquet, Yilong Wang, Diego Santaren, Antoine Berchet, Isabelle Pison, Julia Marshall, Philippe Ciais, François-Marie Bréon, and Frédéric Chevallier
Atmos. Meas. Tech., 15, 5261–5288, https://doi.org/10.5194/amt-15-5261-2022, https://doi.org/10.5194/amt-15-5261-2022, 2022
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Atmospheric inversion at local–regional scales over Europe and pseudo-data assimilation are used to evaluate how CO2 and 14CO2 ground-based measurement networks could complement satellite CO2 imagers to monitor fossil fuel (FF) CO2 emissions. This combination significantly improves precision in the FF emission estimates in areas with a dense network but does not strongly support the separation of the FF from the biogenic signals or the spatio-temporal extrapolation of the satellite information.
Joël Thanwerdas, Marielle Saunois, Antoine Berchet, Isabelle Pison, Bruce H. Vaughn, Sylvia Englund Michel, and Philippe Bousquet
Geosci. Model Dev., 15, 4831–4851, https://doi.org/10.5194/gmd-15-4831-2022, https://doi.org/10.5194/gmd-15-4831-2022, 2022
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Estimating CH4 sources by exploiting observations within an inverse modeling framework is a powerful approach. Here, a new system designed to assimilate δ13C(CH4) observations together with CH4 observations is presented. By optimizing both the emissions and associated source signatures of multiple emission categories, this new system can efficiently differentiate the co-located emission categories and provide estimates of CH4 sources that are consistent with isotopic data.
Edward Malina, Ben Veihelmann, Matthias Buschmann, Nicholas M. Deutscher, Dietrich G. Feist, and Isamu Morino
Atmos. Meas. Tech., 15, 2377–2406, https://doi.org/10.5194/amt-15-2377-2022, https://doi.org/10.5194/amt-15-2377-2022, 2022
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Methane retrievals from remote sensing instruments are fundamentally based on spectroscopic parameters, which indicate spectral-line positions, and their characteristics. These parameters are stored in several databases that vary in their make-up. Here we assess how concentrations of methane isotopologues measured from the same Total Carbon Column Observing Network (TCCON) instruments vary across a range of spectral windows using different spectroscopic databases and comment on the implications.
Zhu Deng, Philippe Ciais, Zitely A. Tzompa-Sosa, Marielle Saunois, Chunjing Qiu, Chang Tan, Taochun Sun, Piyu Ke, Yanan Cui, Katsumasa Tanaka, Xin Lin, Rona L. Thompson, Hanqin Tian, Yuanzhi Yao, Yuanyuan Huang, Ronny Lauerwald, Atul K. Jain, Xiaoming Xu, Ana Bastos, Stephen Sitch, Paul I. Palmer, Thomas Lauvaux, Alexandre d'Aspremont, Clément Giron, Antoine Benoit, Benjamin Poulter, Jinfeng Chang, Ana Maria Roxana Petrescu, Steven J. Davis, Zhu Liu, Giacomo Grassi, Clément Albergel, Francesco N. Tubiello, Lucia Perugini, Wouter Peters, and Frédéric Chevallier
Earth Syst. Sci. Data, 14, 1639–1675, https://doi.org/10.5194/essd-14-1639-2022, https://doi.org/10.5194/essd-14-1639-2022, 2022
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In support of the global stocktake of the Paris Agreement on climate change, we proposed a method for reconciling the results of global atmospheric inversions with data from UNFCCC national greenhouse gas inventories (NGHGIs). Here, based on a new global harmonized database that we compiled from the UNFCCC NGHGIs and a comprehensive framework presented in this study to process the results of inversions, we compared their results of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O).
Marine Remaud, Frédéric Chevallier, Fabienne Maignan, Sauveur Belviso, Antoine Berchet, Alexandra Parouffe, Camille Abadie, Cédric Bacour, Sinikka Lennartz, and Philippe Peylin
Atmos. Chem. Phys., 22, 2525–2552, https://doi.org/10.5194/acp-22-2525-2022, https://doi.org/10.5194/acp-22-2525-2022, 2022
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Carbonyl sulfide (COS) has been recognized as a promising indicator of the plant gross primary production (GPP). Here, we assimilate both COS and CO2 measurements into an atmospheric transport model to obtain information on GPP, plant respiration and COS budget. A possible scenario for the period 2008–2019 leads to a global COS biospheric sink of 800 GgS yr−1 and higher oceanic emissions between 400 and 600 GgS yr−1.
Philippe Ciais, Ana Bastos, Frédéric Chevallier, Ronny Lauerwald, Ben Poulter, Josep G. Canadell, Gustaf Hugelius, Robert B. Jackson, Atul Jain, Matthew Jones, Masayuki Kondo, Ingrid T. Luijkx, Prabir K. Patra, Wouter Peters, Julia Pongratz, Ana Maria Roxana Petrescu, Shilong Piao, Chunjing Qiu, Celso Von Randow, Pierre Regnier, Marielle Saunois, Robert Scholes, Anatoly Shvidenko, Hanqin Tian, Hui Yang, Xuhui Wang, and Bo Zheng
Geosci. Model Dev., 15, 1289–1316, https://doi.org/10.5194/gmd-15-1289-2022, https://doi.org/10.5194/gmd-15-1289-2022, 2022
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The second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP) will provide updated quantification and process understanding of CO2, CH4, and N2O emissions and sinks for ten regions of the globe. In this paper, we give definitions, review different methods, and make recommendations for estimating different components of the total land–atmosphere carbon exchange for each region in a consistent and complete approach.
Jan C. Minx, William F. Lamb, Robbie M. Andrew, Josep G. Canadell, Monica Crippa, Niklas Döbbeling, Piers M. Forster, Diego Guizzardi, Jos Olivier, Glen P. Peters, Julia Pongratz, Andy Reisinger, Matthew Rigby, Marielle Saunois, Steven J. Smith, Efisio Solazzo, and Hanqin Tian
Earth Syst. Sci. Data, 13, 5213–5252, https://doi.org/10.5194/essd-13-5213-2021, https://doi.org/10.5194/essd-13-5213-2021, 2021
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We provide a synthetic dataset on anthropogenic greenhouse gas (GHG) emissions for 1970–2018 with a fast-track extension to 2019. We show that GHG emissions continued to rise across all gases and sectors. Annual average GHG emissions growth slowed, but absolute decadal increases have never been higher in human history. We identify a number of data gaps and data quality issues in global inventories and highlight their importance for monitoring progress towards international climate goals.
Cited articles
Allan, W., Struthers, H., and Lowe, D. C.: Methane carbon isotope effects caused by atomic chlorine in the marine boundary layer: global model results compared with Southern Hemisphere measurements, J. Geophys. Res.-Atmos., 112, https://doi.org/10.1029/2006JD007369, 2007. a
Barker, P. A., Allen, G., Gallagher, M., Pitt, J. R., Fisher, R. E., Bannan, T., Nisbet, E. G., Bauguitte, S. J.-B., Pasternak, D., Cliff, S., Schimpf, M. B., Mehra, A., Bower, K. N., Lee, J. D., Coe, H., and Percival, C. J.: Airborne measurements of fire emission factors for African biomass burning sampled during the MOYA campaign, Atmos. Chem. Phys., 20, 15443–15459, https://doi.org/10.5194/acp-20-15443-2020, 2020. a
Basu, S., Lan, X., Dlugokencky, E., Michel, S., Schwietzke, S., Miller, J. B., Bruhwiler, L., Oh, Y., Tans, P. P., Apadula, F., Gatti, L. V., Jordan, A., Necki, J., Sasakawa, M., Morimoto, S., Di Iorio, T., Lee, H., Arduini, J., and Manca, G.: Estimating emissions of methane consistent with atmospheric measurements of methane and δ13C of methane, Atmos. Chem. Phys., 22, 15351–15377, https://doi.org/10.5194/acp-22-15351-2022, 2022. a, b, c, d, e, f, g, h
Belikov, D. A., Patra, P. K., and Saitoh, N.: Hydroxyl interannual variability impacts estimation of regional methane emissions, J. Geophys. Res.-Atmos., 131, e2025JD044457, https://doi.org/10.1029/2025JD044457, 2026. a
Berchet, A., Sollum, E., Thompson, R. L., Pison, I., Thanwerdas, J., Broquet, G., Chevallier, F., Aalto, T., Berchet, A., Bergamaschi, P., Brunner, D., Engelen, R., Fortems-Cheiney, A., Gerbig, C., Groot Zwaaftink, C. D., Haussaire, J.-M., Henne, S., Houweling, S., Karstens, U., Kutsch, W. L., Luijkx, I. T., Monteil, G., Palmer, P. I., van Peet, J. C. A., Peters, W., Peylin, P., Potier, E., Rödenbeck, C., Saunois, M., Scholze, M., Tsuruta, A., and Zhao, Y.: The Community Inversion Framework v1.0: a unified system for atmospheric inversion studies, Geosci. Model Dev., 14, 5331–5354, https://doi.org/10.5194/gmd-14-5331-2021, 2021. a, b
Bergamaschi, P., Krol, M., Meirink, J. F., Dentener, F., Segers, A., van Aardenne, J., Monni, S., Vermeulen, A. T., Schmidt, M., Ramonet, M., Yver, C., Meinhardt, F., Nisbet, E. G., Fisher, R. E., O'Doherty, S., and Dlugokencky, E. J.: Inverse modeling of European CH4 emissions 2001–2006, J. Geophys. Res., 115, https://doi.org/10.1029/2010JD014180, 2010. a
Bergamaschi, P., Houweling, S., Segers, A., Krol, M., Frankenberg, C., Scheepmaker, R. A., Dlugokencky, E., Wofsy, S. C., Kort, E. A., Sweeney, C., Schuck, T., Brenninkmeijer, C., Chen, H., Beck, V., and Gerbig, C.: Atmospheric CH4 in the first decade of the 21st century: inverse modeling analysis using SCIAMACHY satellite retrievals and NOAA surface measurements, J. Geophys. Res.-Atmos., 118, 7350–7369, https://doi.org/10.1002/jgrd.50480, 2013. a
Bergamaschi, P., Karstens, U., Manning, A. J., Saunois, M., Tsuruta, A., Berchet, A., Vermeulen, A. T., Arnold, T., Janssens-Maenhout, G., Hammer, S., Levin, I., Schmidt, M., Ramonet, M., Lopez, M., Lavric, J., Aalto, T., Chen, H., Feist, D. G., Gerbig, C., Haszpra, L., Hermansen, O., Manca, G., Moncrieff, J., Meinhardt, F., Necki, J., Galkowski, M., O'Doherty, S., Paramonova, N., Scheeren, H. A., Steinbacher, M., and Dlugokencky, E.: Inverse modelling of European CH4 emissions during 2006–2012 using different inverse models and reassessed atmospheric observations, Atmos. Chem. Phys., 18, 901–920, https://doi.org/10.5194/acp-18-901-2018, 2018. a
Bernard, J., Salmon, E., Saunois, M., Peng, S., Serrano-Ortiz, P., Berchet, A., Gnanamoorthy, P., Jansen, J., and Ciais, P.: Satellite-based modeling of wetland methane emissions on a global scale (SatWetCH4 1.0), Geosci. Model Dev., 18, 863–883, https://doi.org/10.5194/gmd-18-863-2025, 2025. a
Bohn, T. J., Melton, J. R., Ito, A., Kleinen, T., Spahni, R., Stocker, B. D., Zhang, B., Zhu, X., Schroeder, R., Glagolev, M. V., Maksyutov, S., Brovkin, V., Chen, G., Denisov, S. N., Eliseev, A. V., Gallego-Sala, A., McDonald, K. C., Rawlins, M. A., Riley, W. J., Subin, Z. M., Tian, H., Zhuang, Q., and Kaplan, J. O.: WETCHIMP-WSL: intercomparison of wetland methane emissions models over West Siberia, Biogeosciences, 12, 3321–3349, https://doi.org/10.5194/bg-12-3321-2015, 2015. a
Bourn, M., Robinson, R., Innocenti, F., and Scheutz, C.: Regulating landfills using measured methane emissions: an English perspective, Waste Manage., 87, 860–869, https://doi.org/10.1016/j.wasman.2018.06.032, 2019. a
Brownlow, R., Lowry, D., Fisher, R. E., France, J. L., Lanoisellé, M., White, B., Wooster, M. J., Zhang, T., and Nisbet, E. G.: Isotopic ratios of tropical methane emissions by atmospheric measurement, Global Biogeochem. Cy., 31, 1408–1419, https://doi.org/10.1002/2017GB005689, 2017. a
Brychkova, G., Kekae, K., McKeown, P. C., Hanson, J., Jones, C. S., Thornton, P., and Spillane, C.: Climate change and land-use change impacts on future availability of forage grass species for ethiopian dairy systems, Sci. Rep.-UK, 12, 20512, https://doi.org/10.1038/s41598-022-23461-w, 2022. a, b
Butchart, N.: The Brewer-Dobson circulation, Rev. Geophys., 52, 157–184, https://doi.org/10.1002/2013RG000448, 2014. a
Camin, F., Besic, D., Brewer, P. J., Allison, C. E., Coplen, T. B., Dunn, P. J. H., Gehre, M., Gröning, M., Meijer, H. A. J., Hélie, J.-F., Iacumin, P., Kraft, R., Krajnc, B., Kümmel, S., Lee, S., Meija, J., Mester, Z., Mohn, J., Moossen, H., Qi, H., Skrzypek, G., Sperlich, P., Viallon, J., Wassenaar, L. I., and Wielgosz, R. I.: Stable isotope reference materials and scale definitions—outcomes of the 2024 IAEA experts meeting, Rapid Commun. Mass. Sp., 39, e10018, https://doi.org/10.1002/rcm.10018, 2025. a
Cantrell, C. A., Shetter, R. E., McDaniel, A. H., Calvert, J. G., Davidson, J. A., Lowe, D. C., Tyler, S. C., Cicerone, R. J., and Greenberg, J. P.: Carbon kinetic isotope effect in the oxidation of methane by the hydroxyl radical, J. Geophys. Res.-Atmos., 95, 22455–22462, https://doi.org/10.1029/JD095iD13p22455, 1990. a, b, c, d
Chandra, N., Patra, P. K., Fujita, R., Höglund-Isaksson, L., Umezawa, T., Goto, D., Morimoto, S., Vaughn, B. H., and Röckmann, T.: Methane emissions decreased in fossil fuel exploitation and sustainably increased in microbial source sectors during 1990–2020, Communications Earth and Environment, 5, 1–15, https://doi.org/10.1038/s43247-024-01286-x, 2024. a, b
Chang, J., Peng, S., Ciais, P., Saunois, M., Dangal, S. R. S., Herrero, M., Havlík, P., Tian, H., and Bousquet, P.: Revisiting enteric methane emissions from domestic ruminants and their δ13CCH4 source signature, Nat. Commun., 10, 3420, https://doi.org/10.1038/s41467-019-11066-3, 2019. a, b, c, d, e, f, g, h
Chanton, J. P., Rutkowski, C. M., Schwartz, C. C., Ward, D. E., and Boring, L.: Factors influencing the stable carbon isotopic signature of methane from combustion and biomass burning, J. Geophys. Res.-Atmos., 105, 1867–1877, https://doi.org/10.1029/1999JD900909, 2000. a
Chevallier, F., Fisher, M., Peylin, P., Serrar, S., Bousquet, P., Bréon, F. M., Chédin, A., and Ciais, P.: Inferring CO2 sources and sinks from satellite observations: method and application to TOVS data, J. Geophys. Res., 110, D24309, https://doi.org/10.1029/2005JD006390, 2005. a
Ciais, P., Zhu, Y., Cai, Y., Lan, X., Michel, S. E., Zheng, B., Zhao, Y., Hauglustaine, D. A., Lin, X., Zhang, Y., Sun, S., Tian, X., Zhao, M., Wang, Y., Chang, J., Dou, X., Liu, Z., Andrew, R., Quinn, C. A., Poulter, B., Ouyang, Z., Yuan, W., Yuan, K., Zhu, Q., Li, F., Pan, N., Tian, H., Yu, X., Rocher-Ros, G., Johnson, M. S., Li, M., Li, M., Feng, D., Raymond, P., Yang, X., Canadell, J. G., Jackson, R. B., Yu, X., Li, Y., Saunois, M., Bousquet, P., and Peng, S.: Why methane surged in the atmosphere during the early 2020s, Science, 391, eadx8262, https://doi.org/10.1126/science.adx8262, 2026. a, b, c
Collins, W. J., Lamarque, J.-F., Schulz, M., Boucher, O., Eyring, V., Hegglin, M. I., Maycock, A., Myhre, G., Prather, M., Shindell, D., and Smith, S. J.: AerChemMIP: quantifying the effects of chemistry and aerosols in CMIP6, Geosci. Model Dev., 10, 585–607, https://doi.org/10.5194/gmd-10-585-2017, 2017. a
Crippa, M., Guizzardi, D., Pagani, F., Banja, M., Muntean, M., Schaaf, E., Becker, W., Monforti-Ferrario, F., Quadrelli, R., Risquez Martin, A., Taghavi-Moharamli, P., Köykkä, J., Grassi, G., Rossi, S., Brandao De Melo, J., Oom, D., Branco, A., San-Miguel, J., and Vignati, E.: GHG emissions of all world countries, Publications Office of the European Union, Luxembourg, JRC134504, https://doi.org/10.2760/953322, 2023. a, b, c, d, e, f
Douglas, P. M. J., Stratigopoulos, E., Park, S., and Phan, D.: Geographic variability in freshwater methane hydrogen isotope ratios and its implications for global isotopic source signatures, Biogeosciences, 18, 3505–3527, https://doi.org/10.5194/bg-18-3505-2021, 2021. a
Drinkwater, A., Palmer, P. I., Feng, L., Arnold, T., Lan, X., Michel, S. E., Parker, R., and Boesch, H.: Atmospheric data support a multi-decadal shift in the global methane budget towards natural tropical emissions, Atmos. Chem. Phys., 23, 8429–8452, https://doi.org/10.5194/acp-23-8429-2023, 2023. a, b
Dunn, P. J. H., Malinovsky, D., Ogrinc, N., Potočnik, D., Flierl, L., Rienitz, O., Paul, D., and Meijer, H. A. J.: Re-determination of
European Commission: MEthane Goes MObile – MEasurements and MOdelling – MEMO2 – Projekt – Fact Sheet – H2020, https://cordis.europa.eu/project/id/722479 (last access: 16 July 2025), 2017. a
Ferrario, F. M., Crippa, M., Guizzardi, D., Muntean, M., Schaaf, E., Vullo, E. L., Solazzo, E., Olivier, J., and Vignati, E.: EDGAR v6.0 Greenhouse Gas Emissions, European Commission, Joint Research Centre [data set], https://doi.org/10.2905/JRC.787T5VR, 2021. a
Forster, P. M., Smith, C. J., Walsh, T., Lamb, W. F., Lamboll, R., Hauser, M., Ribes, A., Rosen, D., Gillett, N., Palmer, M. D., Rogelj, J., von Schuckmann, K., Seneviratne, S. I., Trewin, B., Zhang, X., Allen, M., Andrew, R., Birt, A., Borger, A., Boyer, T., Broersma, J. A., Cheng, L., Dentener, F., Friedlingstein, P., Gutiérrez, J. M., Gütschow, J., Hall, B., Ishii, M., Jenkins, S., Lan, X., Lee, J.-Y., Morice, C., Kadow, C., Kennedy, J., Killick, R., Minx, J. C., Naik, V., Peters, G. P., Pirani, A., Pongratz, J., Schleussner, C.-F., Szopa, S., Thorne, P., Rohde, R., Rojas Corradi, M., Schumacher, D., Vose, R., Zickfeld, K., Masson-Delmotte, V., and Zhai, P.: Indicators of Global Climate Change 2022: annual update of large-scale indicators of the state of the climate system and human influence, Earth Syst. Sci. Data, 15, 2295–2327, https://doi.org/10.5194/essd-15-2295-2023, 2023. a, b, c, d
France, J. L., Fisher, R. E., Lowry, D., Allen, G., Andrade, M. F., Bauguitte, S. J.-B., Bower, K., Broderick, T. J., Daly, M. C., Forster, G., Gondwe, M., Helfter, C., Hoyt, A. M., Jones, A. E., Lanoisellé, M., Moreno, I., Nisbet-Jones, P. B. R., Oram, D., Pasternak, D., Pitt, J. R., Skiba, U., Stephens, M., Wilde, S. E., and Nisbet, E. G.: δ13C methane source signatures from tropical wetland and rice field emissions, Philos. T. Roy. Soc. A, 380, 20200449, https://doi.org/10.1098/rsta.2020.0449, 2021. a
France, J. L., Lunt, M. F., Andrade, M., Moreno, I., Ganesan, A. L., Lachlan-Cope, T., Fisher, R. E., Lowry, D., Parker, R. J., Nisbet, E. G., and Jones, A. E.: Very large fluxes of methane measured above Bolivian seasonal wetlands, P. Natl. Acad. Sci. USA, 119, e2206345119, https://doi.org/10.1073/pnas.2206345119, 2022. a, b, c, d, e, f, g, h, i, j
Fujita, R., Morimoto, S., Maksyutov, S., Kim, H.-S., Arshinov, M., Brailsford, G., Aoki, S., and Nakazawa, T.: Global and regional CH4 emissions for 1995–2013 derived from atmospheric CH4, δ13C-CH4, and δD-CH4 observations and a chemical transport model, J. Geophys. Res.-Atmos., 125, e2020JD032903, https://doi.org/10.1029/2020JD032903, 2020. a, b, c
Fujita, R., Graven, H., Zazzeri, G., Hmiel, B., Petrenko, V. V., Smith, A. M., Michel, S. E., and Morimoto, S.: Global fossil methane emissions constrained by multi-isotopic atmospheric methane histories, J. Geophys. Res.-Atmos., 130, e2024JD041266, https://doi.org/10.1029/2024JD041266, 2025. a, b
Ganesan, A. L., Stell, A. C., Gedney, N., Comyn-Platt, E., Hayman, G., Rigby, M., Poulter, B., and Hornibrook, E. R. C.: Spatially resolved isotopic source signatures of wetland methane emissions, Geophys. Res. Lett., 45, 3737–3745, https://doi.org/10.1002/2018GL077536, 2018. a, b, c, d
Gaubert, B., Worden, H. M., Arellano, A. F. J., Emmons, L. K., Tilmes, S., Barré, J., Martinez Alonso, S., Vitt, F., Anderson, J. L., Alkemade, F., Houweling, S., and Edwards, D. P.: Chemical feedback from decreasing carbon monoxide emissions, Geophys. Res. Lett., 44, 9985–9995, https://doi.org/10.1002/2017GL074987, 2017. a
Global Methane Pledge: Global Methane Pledge, https://www.2717globalmethanepledge.org/#pledges (last access: 26 August 2024), 2023. a
Gromov, S., Brenninkmeijer, C. A. M., and Jöckel, P.: A very limited role of tropospheric chlorine as a sink of the greenhouse gas methane, Atmos. Chem. Phys., 18, 9831–9843, https://doi.org/10.5194/acp-18-9831-2018, 2018. a
Gupta, M. L., McGrath, M. P., Cicerone, R. J., Rowland, F. S., and Wolfsberg, M.:
Guthrie, P. D.: The CH4 - CO - OH conundrum: a simple analytic approach, Global Biogeochem. Cy., 3, 287–298, https://doi.org/10.1029/GB003i004p00287, 1989. a
Hauglustaine, D. A., Hourdin, F., Jourdain, L., Filiberti, M.-A., Walters, S., Lamarque, J.-F., and Holland, E. A.: Interactive chemistry in the Laboratoire de Météorologie Dynamique general circulation model: description and background tropospheric chemistry evaluation, J. Geophys. Res.-Atmos., 109, https://doi.org/10.1029/2003JD003957, 2004. a, b, c, d
Höglund-Isaksson, L., Gómez-Sanabria, A., Klimont, Z., Rafaj, P., and Schöpp, W.: Technical potentials and costs for reducing global anthropogenic methane emissions in the 2050 timeframe – results from the GAINS model, Environmental Research Communications, 2, 025004, https://doi.org/10.1088/2515-7620/ab7457, 2020. a, b, c, d
Holmes, C. D., Prather, M. J., Søvde, O. A., and Myhre, G.: Future methane, hydroxyl, and their uncertainties: key climate and emission parameters for future predictions, Atmos. Chem. Phys., 13, 285–302, https://doi.org/10.5194/acp-13-285-2013, 2013. a
Hossaini, R., Chipperfield, M. P., Saiz-Lopez, A., Fernandez, R., Monks, S., Feng, W., Brauer, P., and von Glasow, R.: A global model of tropospheric chlorine chemistry: organic versus inorganic sources and impact on methane oxidation, J. Geophys. Res.-Atmos., 121, 14271–14297, https://doi.org/10.1002/2016JD025756, 2016. a
Hourdin, F., Talagrand, O., and Idelkadi, A.: Eulerian backtracking of atmospheric tracers. II: Numerical aspects, Q. J. Roy. Meteor. Soc., 132, 585–603, https://doi.org/10.1256/qj.03.198.B, 2006. a
Houweling, S., Bergamaschi, P., Chevallier, F., Heimann, M., Kaminski, T., Krol, M., Michalak, A. M., and Patra, P.: Global inverse modeling of CH4 sources and sinks: an overview of methods, Atmos. Chem. Phys., 17, 235–256, https://doi.org/10.5194/acp-17-235-2017, 2017. a
IEA: US Natural Gas Production by Source, https://www.iea.org/data-and-statistics/charts/us-natural-gas-production-by-source-2013-2023 (last access: 13 June 2025), 2013–2023. a
Jackson, R. B., Saunois, M., Bousquet, P., Canadell, J. G., Poulter, B., Stavert, A. R., Bergamaschi, P., Niwa, Y., Segers, A., and Tsuruta, A.: Increasing anthropogenic methane emissions arise equally from agricultural and fossil fuel sources, Environ. Res. Lett., 15, 071002, https://doi.org/10.1088/1748-9326/ab9ed2, 2020. a
Jackson, R. B., Saunois, M., Martinez, A., Canadell, J. G., Yu, X., Li, M., Poulter, B., Raymond, P. A., Regnier, P., Ciais, P., Davis, S. J., and Patra, P. K.: Human activities now fuel two-thirds of global methane emissions, Environ. Res. Lett., 19, 101002, https://doi.org/10.1088/1748-9326/ad6463, 2024. a
Kangasaho, V., Tsuruta, A., Backman, L., Mäkinen, P., Houweling, S., Segers, A., Krol, M., Dlugokencky, E. J., Michel, S., White, J. W. C., and Aalto, T.: The role of emission sources and atmospheric sink in the seasonal cycle of CH4 and δ13-CH4: analysis based on the atmospheric chemistry transport model TM5, Atmosphere, 13, 888, https://doi.org/10.3390/atmos13060888, 2022. a
Karlson, M. and Bastviken, D.: Multi-source mapping of peatland types using Sentinel-1, Sentinel-2, and terrain derivatives—a comparison between five high-latitude landscapes, J. Geophys. Res.-Biogeo., 128, e2022JG007195, https://doi.org/10.1029/2022JG007195, 2023. a
Kirschke, S., Bousquet, P., Ciais, P., Saunois, M., Canadell, J. G., Dlugokencky, E. J., Bergamaschi, P., Bergmann, D., Blake, D. R., Bruhwiler, L., Cameron-Smith, P., Castaldi, S., Chevallier, F., Feng, L., Fraser, A., Heimann, M., Hodson, E. L., Houweling, S., Josse, B., Fraser, P. J., Krummel, P. B., Lamarque, J.-F., Langenfelds, R. L., Le Quéré, C., Naik, V., O'Doherty, S., Palmer, P. I., Pison, I., Plummer, D., Poulter, B., Prinn, R. G., Rigby, M., Ringeval, B., Santini, M., Schmidt, M., Shindell, D. T., Simpson, I. J., Spahni, R., Steele, L. P., Strode, S. A., Sudo, K., Szopa, S., van der Werf, G. R., Voulgarakis, A., van Weele, M., Weiss, R. F., Williams, J. E., and Zeng, G.: Three decades of global methane sources and sinks, Nature Geosci, 6, 813–823, https://doi.org/10.1038/ngeo1955, 2013. a
Knox, S. H., Bansal, S., McNicol, G., Schafer, K., Sturtevant, C., Ueyama, M., Valach, A. C., Baldocchi, D., Delwiche, K., Desai, A. R., Euskirchen, E., Liu, J., Lohila, A., Malhotra, A., Melling, L., Riley, W., Runkle, B. R. K., Turner, J., Vargas, R., Zhu, Q., Alto, T., Fluet-Chouinard, E., Goeckede, M., Melton, J. R., Sonnentag, O., Vesala, T., Ward, E., Zhang, Z., Feron, S., Ouyang, Z., Alekseychik, P., Aurela, M., Bohrer, G., Campbell, D. I., Chen, J., Chu, H., Dalmagro, H. J., Goodrich, J. P., Gottschalk, P., Hirano, T., Iwata, H., Jurasinski, G., Kang, M., Koebsch, F., Mammarella, I., Nilsson, M. B., Ono, K., Peichl, M., Peltola, O., Ryu, Y., Sachs, T., Sakabe, A., Sparks, J. P., Tuittila, E.-S., Vourlitis, G. L., Wong, G. X., Windham-Myers, L., Poulter, B., and Jackson, R. B.: Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales, Glob. Change Biol., 27, 3582–3604, https://doi.org/10.1111/gcb.15661, 2021. a
Krautwurst, S., Gerilowski, K., Jonsson, H. H., Thompson, D. R., Kolyer, R. W., Iraci, L. T., Thorpe, A. K., Horstjann, M., Eastwood, M., Leifer, I., Vigil, S. A., Krings, T., Borchardt, J., Buchwitz, M., Fladeland, M. M., Burrows, J. P., and Bovensmann, H.: Methane emissions from a Californian landfill, determined from airborne remote sensing and in situ measurements, Atmos. Meas. Tech., 10, 3429–3452, https://doi.org/10.5194/amt-10-3429-2017, 2017. a
Lan, X., Basu, S., Schwietzke, S., Bruhwiler, L. M. P., Dlugokencky, E. J., Michel, S. E., Sherwood, O. A., Tans, P. P., Thoning, K., Etiope, G., Zhuang, Q., Liu, L., Oh, Y., Miller, J. B., Pétron, G., Vaughn, B. H., and Crippa, M.: Improved constraints on global methane emissions and sinks using δ13C-CH4, Global Biogeochem. Cy., 35, e2021GB007000, https://doi.org/10.1029/2021GB007000, 2021a. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u, v, w, x, y, z, aa, ab, ac, ad, ae, af, ag
Lan, X., Nisbet, E. G., Dlugokencky, E. J., and Michel, S. E.: What do we know about the global methane budget? Results from four decades of atmospheric CH4 observations and the way forward, Philos. T. Roy. Soc. A, 379, 20200440, https://doi.org/10.1098/rsta.2020.0440, 2021b. a
Lan, X., Thoning, K., and Dlugokencky, E.: Trends in globally-averaged CH4, N2O, and SF6 Determined from NOAA Global Monitoring Laboratory Measurements, NOAA Global Monitoring Laboratory [data set], https://doi.org/10.15138/P8XG-AA10, 2025. a
Lan, X., Thoning, K., and Dlugokencky, E.: Trends in Globally-Averaged CH4, N2O, and SF6 Determined from NOAA Global Monitoring Laboratory Measurements Version 2026-06, NOAA Global Monitoring Laboratory [data set], https://doi.org/10.15138/P8XG-AA10, 2026. a
Lauerwald, R., Allen, G. H., Deemer, B. R., Liu, S., Maavara, T., Raymond, P., Alcott, L., Bastviken, D., Hastie, A., Holgerson, M. A., Johnson, M. S., Lehner, B., Lin, P., Marzadri, A., Ran, L., Tian, H., Yang, X., Yao, Y., and Regnier, P.: Inland water greenhouse gas budgets for RECCAP2: 1. State-of-the-art of global scale assessments, Global Biogeochem. Cy., 37, e2022GB007657, https://doi.org/10.1029/2022GB007657, 2023. a, b, c
Lauvaux, T., Giron, C., Mazzolini, M., d'Aspremont, A., Duren, R., Cusworth, D., Shindell, D., and Ciais, P.: Global assessment of oil and gas methane ultra-emitters, Science, 375, 557–561, https://doi.org/10.1126/science.abj4351, 2022. a
Lelieveld, J., Gromov, S., Pozzer, A., and Taraborrelli, D.: Global tropospheric hydroxyl distribution, budget and reactivity, Atmos. Chem. Phys., 16, 12477–12493, https://doi.org/10.5194/acp-16-12477-2016, 2016. a
Lin, X., Trainer, M., and Liu, S. C.: On the nonlinearity of the tropospheric ozone production, J. Geophys. Res.-Atmos., 93, 15879–15888, https://doi.org/10.1029/JD093iD12p15879, 1988. a
Liu, G., Peng, S., Lin, X., Ciais, P., Li, X., Xi, Y., Lu, Z., Chang, J., Saunois, M., Wu, Y., Patra, P., Chandra, N., Zeng, H., and Piao, S.: Recent slowdown of anthropogenic methane emissions in China driven by stabilized coal production, Environ. Sci. Tech. Let., 8, 739–746, https://doi.org/10.1021/acs.estlett.1c00463, 2021. a
Louis, J.-F.: A parametric model of vertical eddy fluxes in the atmosphere, Bound.-Lay. Meteorol., 17, 187–202, https://doi.org/10.1007/BF00117978, 1979. a
Malina, E., Yoshida, Y., Matsunaga, T., and Muller, J.-P.: Information content analysis: the potential for methane isotopologue retrieval from GOSAT-2, Atmos. Meas. Tech., 11, 1159–1179, https://doi.org/10.5194/amt-11-1159-2018, 2018. a, b
Malina, E., Hu, H., Landgraf, J., and Veihelmann, B.: A study of synthetic 13CH4 retrievals from TROPOMI and Sentinel-5/UVNS, Atmos. Meas. Tech., 12, 6273–6301, https://doi.org/10.5194/amt-12-6273-2019, 2019. a, b, c, d
Mannisenaho, V., Tsuruta, A., Backman, L., Houweling, S., Segers, A., Krol, M., Saunois, M., Poulter, B., Zhang, Z., Lan, X., Dlugokencky, E. J., Michel, S., White, J. W. C., and Aalto, T.: Global atmospheric δ13CH4 and CH4 trends for 2000–2020 from the atmospheric transport model TM5 using CH4 from carbon tracker Europe–CH4 inversions, Atmosphere, 14, 1121, https://doi.org/10.3390/atmos14071121, 2023. a, b
Martinez, A., Saunois, M., Poulter, B., Bousquet, P., Canadell, J. G., Jackson, R. B., Dlugokencky, E. J., Ciais, P., Bastviken, D., Blake, D. R., Castaldi, S., Etiope, G., Gedney, N., Höglund-Isaksson, L., Hugelius, G., Ito, A., Kleinen, T., Krummel, P. B., Liu, L., McDonald, K. C., Melton, J. R., Müller, J., Murguia-Flores, F., Niwa, Y., Noce, S., Parker, R. J., Peng, C., Ramonet, M., Riley, W. J., Rosentreter, J. A., Segers, A., Smith, S. J., Tian, H., Tubiello, F. N., Tsuruta, A., Weber, T. S., van der Werf, G. R., Worthy, D., Yoshida, Y., Zhang, W., Zhang, Z., Zheng, B., Zhu, Q., Zhu, Q., and Zhuang, Q.: Supplemental Data of the Global Carbon Project Methane Budget 2024 V1, ICOS ERIC – Carbon Portal [data set], https://doi.org/10.18160/GKQ9-2RHT, 2024. a, b, c, d, e, f, g, h, i, j, k
McNicol, G., Fluet-Chouinard, E., Ouyang, Z., Knox, S., Zhang, Z., Aalto, T., Bansal, S., Chang, K.-Y., Chen, M., Delwiche, K., Feron, S., Goeckede, M., Liu, J., Malhotra, A., Melton, J. R., Riley, W., Vargas, R., Yuan, K., Ying, Q., Zhu, Q., Alekseychik, P., Aurela, M., Billesbach, D. P., Campbell, D. I., Chen, J., Chu, H., Desai, A. R., Euskirchen, E., Goodrich, J., Griffis, T., Helbig, M., Hirano, T., Iwata, H., Jurasinski, G., King, J., Koebsch, F., Kolka, R., Krauss, K., Lohila, A., Mammarella, I., Nilson, M., Noormets, A., Oechel, W., Peichl, M., Sachs, T., Sakabe, A., Schulze, C., Sonnentag, O., Sullivan, R. C., Tuittila, E.-S., Ueyama, M., Vesala, T., Ward, E., Wille, C., Wong, G. X., Zona, D., Windham-Myers, L., Poulter, B., and Jackson, R. B.: Upscaling wetland methane emissions from the FLUXNET-CH4 Eddy covariance network (UpCH4 v1.0): model development, network assessment, and budget comparison, AGU Advances, 4, e2023AV000956, https://doi.org/10.1029/2023AV000956, 2023. a
McNorton, J., Wilson, C., Gloor, M., Parker, R. J., Boesch, H., Feng, W., Hossaini, R., and Chipperfield, M. P.: Attribution of recent increases in atmospheric methane through 3-D inverse modelling, Atmos. Chem. Phys., 18, 18149–18168, https://doi.org/10.5194/acp-18-18149-2018, 2018. a
Melton, J. R., Wania, R., Hodson, E. L., Poulter, B., Ringeval, B., Spahni, R., Bohn, T., Avis, C. A., Beerling, D. J., Chen, G., Eliseev, A. V., Denisov, S. N., Hopcroft, P. O., Lettenmaier, D. P., Riley, W. J., Singarayer, J. S., Subin, Z. M., Tian, H., Zürcher, S., Brovkin, V., van Bodegom, P. M., Kleinen, T., Yu, Z. C., and Kaplan, J. O.: Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP), Biogeosciences, 10, 753–788, https://doi.org/10.5194/bg-10-753-2013, 2013. a
Menoud, M.: The European Methane Isotope Database Coupled with a Global Inventory of Fossil and Non-Fossil δ13C- and δ2H-CH4 Source Signature Measurements, Utrecht University [data set], https://doi.org/10.24416/UU01-YP43IN, 2022. a, b, c, d
Menoud, M., van der Veen, C., Lowry, D., Fernandez, J. M., Bakkaloglu, S., France, J. L., Fisher, R. E., Maazallahi, H., Stanisavljević, M., NÄôcki, J., Vinkovic, K., Łakomiec, P., Rinne, J., Korbeń, P., Schmidt, M., Defratyka, S., Yver-Kwok, C., Andersen, T., Chen, H., and Röckmann, T.: New contributions of measurements in Europe to the global inventory of the stable isotopic composition of methane, Earth Syst. Sci. Data, 14, 4365–4386, https://doi.org/10.5194/essd-14-4365-2022, 2022. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u, v, w
Menoud, M., Thomas, R., Carina, v. d. V., Julianne, F., Semra, B., Dave, L., James, F., Rebecca, F., Hossein, M., Piotr, K., Martina, S., Mila, S., Jaroslaw, N., Patryk, Ł., Janne, R., Sara, D., Camille, Y.-K., Katarina, V., Truls, A., and Huilin, C.: The European Methane Isotope Database Coupled with a Global Inventory of Fossil and Non-Fossil δ13C- and δ2H-CH4 Source Signature Measurements, Utrecht University [data set], https://doi.org/10.24416/UU01-YP43IN, 2024. a, b, c, d, e, f, g, h, i
Michel, S. E., Lan, X., Miller, J., Tans, P., Clark, J. R., Schaefer, H., Sperlich, P., Brailsford, G., Morimoto, S., Moossen, H., and Li, J.: Rapid shift in methane carbon isotopes suggests microbial emissions drove record high atmospheric methane growth in 2020–2022, P. Natl. Acad. Sci. USA, 121, e2411212121, https://doi.org/10.1073/pnas.2411212121, 2024. a, b, c, d, e, f, g, h
Milkov, A. V. and Etiope, G.: Revised genetic diagrams for natural gases based on a global dataset of >20,000 samples, Org. Geochem., 125, 109–120, https://doi.org/10.1016/j.orggeochem.2018.09.002, 2018. a
Milkov, A. V., Faiz, M., and Etiope, G.: Geochemistry of shale gases from around the world: composition, origins, isotope reversals and rollovers, and implications for the exploration of shale plays, Org. Geochem., 143, 103997, https://doi.org/10.1016/j.orggeochem.2020.103997, 2020a. a
Milkov, A. V., Schwietzke, S., Allen, G., Sherwood, O. A., and Etiope, G.: Using global isotopic data to constrain the role of shale gas production in recent increases in atmospheric methane, Sci. Rep.-UK, 10, 4199, https://doi.org/10.1038/s41598-020-61035-w, 2020b. a, b, c
Morgenstern, O., Moss, R., Manning, M., Zeng, G., Schaefer, H., Usoskin, I., Turnbull, J., Brailsford, G., Nichol, S., and Bromley, T.: Radiocarbon monoxide indicates increasing atmospheric oxidizing capacity, Nat. Commun., 16, 249, https://doi.org/10.1038/s41467-024-55603-1, 2025. a, b
Nicely, J. M., Salawitch, R. J., Canty, T., Anderson, D. C., Arnold, S. R., Chipperfield, M. P., Emmons, L. K., Flemming, J., Huijnen, V., Kinnison, D. E., Lamarque, J.-F., Mao, J., Monks, S. A., Steenrod, S. D., Tilmes, S., and Turquety, S.: Quantifying the causes of differences in tropospheric OH within global models, J. Geophys. Res.-Atmos., 122, 1983–2007, https://doi.org/10.1002/2016JD026239, 2017. a
Nisbet, E. G.: Climate feedback on methane from wetlands, Nat. Clim. Change, 13, 421–422, https://doi.org/10.1038/s41558-023-01634-3, 2023. a
Nisbet, E. G. and Manning, M. R.: What is causing the methane surge?, Science, 391, 556–557, https://doi.org/10.1126/science.aee6226, 2026. a, b
Nisbet, E. G., Dlugokencky, E. J., Manning, M. R., Lowry, D., Fisher, R. E., France, J. L., Michel, S. E., Miller, J. B., White, J. W. C., Vaughn, B., Bousquet, P., Pyle, J. A., Warwick, N. J., Cain, M., Brownlow, R., Zazzeri, G., Lanoisellé, M., Manning, A. C., Gloor, E., Worthy, D. E. J., Brunke, E.-G., Labuschagne, C., Wolff, E. W., and Ganesan, A. L.: Rising atmospheric methane: 2007–2014 growth and isotopic shift, Global Biogeochem. Cy., 30, 1356–1370, https://doi.org/10.1002/2016GB005406, 2016. a, b
Nisbet, E. G., Manning, M. R., Dlugokencky, E. J., Fisher, R. E., Lowry, D., Michel, S. E., Myhre, C. L., Platt, S. M., Allen, G., Bousquet, P., Brownlow, R., Cain, M., France, J. L., Hermansen, O., Hossaini, R., Jones, A. E., Levin, I., Manning, A. C., Myhre, G., Pyle, J. A., Vaughn, B. H., Warwick, N. J., and White, J. W. C.: Very strong atmospheric methane growth in the 4 years 2014–2017: implications for the Paris Agreement, Global Biogeochem. Cy., 33, 318–342, https://doi.org/10.1029/2018GB006009, 2019. a, b, c
Nisbet, E. G., Fisher, R. E., Lowry, D., France, J. L., Allen, G., Bakkaloglu, S., Broderick, T. J., Cain, M., Coleman, M., Fernandez, J., Forster, G., Griffiths, P. T., Iverach, C. P., Kelly, B. F. J., Manning, M. R., Nisbet-Jones, P. B. R., Pyle, J. A., Townsend-Small, A., al-Shalaan, A., Warwick, N., and Zazzeri, G.: Methane mitigation: methods to reduce emissions, on the path to the Paris Agreement, Rev. Geophys., 58, e2019RG000675, https://doi.org/10.1029/2019RG000675, 2020. a
Nisbet, E. G., Allen, G., Fisher, R. E., France, J. L., Lee, J. D., Lowry, D., Andrade, M. F., Bannan, T. J., Barker, P., Bateson, P., Bauguitte, S. J.-B., Bower, K. N., Broderick, T. J., Chibesakunda, F., Cain, M., Cozens, A. E., Daly, M. C., Ganesan, A. L., Jones, A. E., Lambakasa, M., Lunt, M. F., Mehra, A., Moreno, I., Pasternak, D., Palmer, P. I., Percival, C. J., Pitt, J. R., Riddle, A. J., Rigby, M., Shaw, J. T., Stell, A. C., Vaughan, A. R., Warwick, N. J., and E. Wilde, S.: Isotopic signatures of methane emissions from tropical fires, agriculture and wetlands: the MOYA and ZWAMPS flights, Philos. T. Roy. Soc. A, 380, 20210112, https://doi.org/10.1098/rsta.2021.0112, 2021. a, b, c, d, e, f, g, h
Nisbet, E. G., Manning, M. R., Dlugokencky, E. J., Michel, S. E., Lan, X., Röckmann, T., Denier van der Gon, H. A. C., Schmitt, J., Palmer, P. I., Dyonisius, M. N., Oh, Y., Fisher, R. E., Lowry, D., France, J. L., White, J. W. C., Brailsford, G., and Bromley, T.: Atmospheric methane: comparison between methane's record in 2006–2022 and during glacial terminations, Global Biogeochem. Cy., 37, e2023GB007875, https://doi.org/10.1029/2023GB007875, 2023. a
Ocko, I. B., Sun, T., Shindell, D., Oppenheimer, M., Hristov, A. N., Pacala, S. W., Mauzerall, D. L., Xu, Y., and Hamburg, S. P.: Acting rapidly to deploy readily available methane mitigation measures by sector can immediately slow global warming, Environ. Res. Lett., 16, 054042, https://doi.org/10.1088/1748-9326/abf9c8, 2021. a
Oh, Y., Zhuang, Q., Welp, L. R., Liu, L., Lan, X., Basu, S., Dlugokencky, E. J., Bruhwiler, L., Miller, J. B., Michel, S. E., Schwietzke, S., Tans, P., Ciais, P., and Chanton, J. P.: Improved global wetland carbon isotopic signatures support post-2006 microbial methane emission increase, Communications Earth and Environment, 3, 1–12, https://doi.org/10.1038/s43247-022-00488-5, 2022. a, b, c, d, e, f, g, h, i, j, k, l, m, n
O'Rourke, P., Smith, S., Mott, A., Ahsan, H., Mcduffie, E., Crippa, M., Klimont, Z., Mcdonald, B., Wang, S., Nicholson, M., Hoesly, R., and Feng, L.: CEDS V_2021_04_21 Gridded Emissions Data, PNNL DataHub (Pacific Northwest National Laboratory) [data set], https://doi.org/10.25584/PNNLDATAHUB/1779095, 2021. a, b, c, d
Parker, R. J., Wilson, C., Comyn-Platt, E., Hayman, G., Marthews, T. R., Bloom, A. A., Lunt, M. F., Gedney, N., Dadson, S. J., McNorton, J., Humpage, N., Boesch, H., Chipperfield, M. P., Palmer, P. I., and Yamazaki, D.: Evaluation of wetland CH4 in the Joint UK Land Environment Simulator (JULES) land surface model using satellite observations, Biogeosciences, 19, 5779–5805, https://doi.org/10.5194/bg-19-5779-2022, 2022. a
Patra, P. K., Houweling, S., Krol, M., Bousquet, P., Belikov, D., Bergmann, D., Bian, H., Cameron-Smith, P., Chipperfield, M. P., Corbin, K., Fortems-Cheiney, A., Fraser, A., Gloor, E., Hess, P., Ito, A., Kawa, S. R., Law, R. M., Loh, Z., Maksyutov, S., Meng, L., Palmer, P. I., Prinn, R. G., Rigby, M., Saito, R., and Wilson, C.: TransCom model simulations of CH4 and related species: linking transport, surface flux and chemical loss with CH4 variability in the troposphere and lower stratosphere, Atmos. Chem. Phys., 11, 12813–12837, https://doi.org/10.5194/acp-11-12813-2011, 2011. a, b, c, d, e
Patra, P. K., Krol, M. C., Prinn, R. G., Takigawa, M., Mühle, J., Montzka, S. A., Lal, S., Yamashita, Y., Naus, S., Chandra, N., Weiss, R. F., Krummel, P. B., Fraser, P. J., O'Doherty, S., and Elkins, J. W.: Methyl chloroform continues to constrain the hydroxyl (OH) variability in the troposphere, J. Geophys. Res.-Atmos., 126, e2020JD033862, https://doi.org/10.1029/2020JD033862, 2021. a, b
Penn, E., Jacob, D. J., Chen, Z., East, J. D., Sulprizio, M. P., Bruhwiler, L., Maasakkers, J. D., Nesser, H., Qu, Z., Zhang, Y., and Worden, J.: What can we learn about tropospheric OH from satellite observations of methane?, Atmos. Chem. Phys., 25, 2947–2965, https://doi.org/10.5194/acp-25-2947-2025, 2025. a
Petrenko, V. V., Smith, A. M., Schaefer, H., Riedel, K., Brook, E., Baggenstos, D., Harth, C., Hua, Q., Buizert, C., Schilt, A., Fain, X., Mitchell, L., Bauska, T., Orsi, A., Weiss, R. F., and Severinghaus, J. P.: Minimal geological methane emissions during the younger dryas-preboreal abrupt warming event, Nature, 548, 443–446, https://doi.org/10.1038/nature23316, 2017. a
Pison, I., Bousquet, P., Chevallier, F., Szopa, S., and Hauglustaine, D.: Multi-species inversion of CH4, CO and H2 emissions from surface measurements, Atmos. Chem. Phys., 9, 5281–5297, https://doi.org/10.5194/acp-9-5281-2009, 2009. a
Poulter, B., Bousquet, P., Canadell, J. G., Ciais, P., Peregon, A., Saunois, M., Arora, V. K., Beerling, D. J., Brovkin, V., Jones, C. D., Joos, F., Gedney, N., Ito, A., Kleinen, T., Koven, C. D., McDonald, K., Melton, J. R., Peng, C., Peng, S., Prigent, C., Schroeder, R., Riley, W. J., Saito, M., Spahni, R., Tian, H., Taylor, L., Viovy, N., Wilton, D., Wiltshire, A., Xu, X., Zhang, B., Zhang, Z., and Zhu, Q.: Global wetland contribution to 2000–2012 atmospheric methane growth rate dynamics, Environ. Res. Lett., 12, 094013, https://doi.org/10.1088/1748-9326/aa8391, 2017. a, b
Prather, M. J., Holmes, C. D., and Hsu, J.: Reactive greenhouse gas scenarios: systematic exploration of uncertainties and the role of atmospheric chemistry, Geophys. Res. Lett., 39, L09803, https://doi.org/10.1029/2012GL051440, 2012. a
Qin, S., Tang, X., Song, Y., and Wang, H.: Distribution and fractionation mechanism of stable carbon isotope of coalbed methane, Sci. China Ser. D, 49, 1252–1258, https://doi.org/10.1007/s11430-006-2036-3, 2006. a
Randerson, J. T., Chen, Y., van der Werf, G. R., Rogers, B. M., and Morton, D. C.: Global burned area and biomass burning emissions from small fires, J. Geophys. Res.-Biogeo., 117, https://doi.org/10.1029/2012JG002128, 2012. a, b, c
Remaud, M., Chevallier, F., Cozic, A., Lin, X., and Bousquet, P.: On the impact of recent developments of the LMDz atmospheric general circulation model on the simulation of CO2 transport, Geosci. Model Dev., 11, 4489–4513, https://doi.org/10.5194/gmd-11-4489-2018, 2018. a
Rice, A. L., Butenhoff, C. L., Teama, D. G., Röger, F. H., Khalil, M. A. K., and Rasmussen, R. A.: Atmospheric methane isotopic record favors fossil sources flat in 1980s and 1990s with recent increase, P. Natl. Acad. Sci. USA, 113, 10791–10796, https://doi.org/10.1073/pnas.1522923113, 2016. a
Riddell-Young, B., Michel, S. E., Lan, X., Tans, P., Röckmann, T., Dasgupta, B., Oh, Y., Bruhwiler, L. M. P., Fujita, R., Umezawa, T., Morimoto, S., and Miller, J. B.: Microbial driver of 2006–2023 CH4 growth indicated by trends in atmospheric δD–CH4 and δ13C–CH4, P. Natl. Acad. Sci. USA, 122, e2516543122, https://doi.org/10.1073/pnas.2516543122, 2025. a
Rigby, M., Montzka, S. A., Prinn, R. G., White, J. W. C., Young, D., O'Doherty, S., Lunt, M. F., Ganesan, A. L., Manning, A. J., Simmonds, P. G., Salameh, P. K., Harth, C. M., Mühle, J., Weiss, R. F., Fraser, P. J., Steele, L. P., Krummel, P. B., McCulloch, A., and Park, S.: Role of atmospheric oxidation in recent methane growth, P. Natl. Acad. Sci. USA, 114, 5373–5377, https://doi.org/10.1073/pnas.1616426114, 2017. a
Röckmann, T., van Herpen, M., Brashear, C., van der Veen, C., Gromov, S., Li, Q., Saiz-Lopez, A., Meidan, D., Barreto, A., Prats, N., Mármol, I., Ramos, R., Baños, I., Arrieta, J. M., Zaehnle, S., Jordan, A., Moossen, H., Timas, H., Young, D., Sperlich, P., Moss, R., and Johnson, M. S.: The use of δ13C in CO to determine removal of CH4 by Cl radicals in the atmosphere, Environ. Res. Lett., 19, 064054, https://doi.org/10.1088/1748-9326/ad4375, 2024. a, b
Sansone, F. J., Popp, B. N., Gasc, A., Graham, A. W., and Rust, T. M.: Highly elevated methane in the eastern tropical North Pacific and associated isotopically enriched fluxes to the atmosphere, Geophys. Res. Lett., 28, 4567–4570, https://doi.org/10.1029/2001GL013460, 2001. a
Saueressig, G., Bergamaschi, P., Crowley, J. N., Fischer, H., and Harris, G. W.: Carbon kinetic isotope effect in the reaction of CH4 with Cl atoms, Geophys. Res. Lett., 22, 1225–1228, https://doi.org/10.1029/95GL00881, 1995. a, b
Saueressig, G., Crowley, J. N., Bergamaschi, P., Brühl, C., Brenninkmeijer, C. A. M., and Fischer, H.: Carbon 13 and D kinetic isotope effects in the reactions of CH4 with O(1D) and OH: new laboratory measurements and their implications for the isotopic composition of stratospheric methane, J. Geophys. Res.-Atmos., 106, 23127–23138, https://doi.org/10.1029/2000JD000120, 2001. a, b, c, d, e, f
Saunois, M., Bousquet, P., Poulter, B., Peregon, A., Ciais, P., Canadell, J. G., Dlugokencky, E. J., Etiope, G., Bastviken, D., Houweling, S., Janssens-Maenhout, G., Tubiello, F. N., Castaldi, S., Jackson, R. B., Alexe, M., Arora, V. K., Beerling, D. J., Bergamaschi, P., Blake, D. R., Brailsford, G., Bruhwiler, L., Crevoisier, C., Crill, P., Covey, K., Frankenberg, C., Gedney, N., Höglund-Isaksson, L., Ishizawa, M., Ito, A., Joos, F., Kim, H.-S., Kleinen, T., Krummel, P., Lamarque, J.-F., Langenfelds, R., Locatelli, R., Machida, T., Maksyutov, S., Melton, J. R., Morino, I., Naik, V., O'Doherty, S., Parmentier, F.-J. W., Patra, P. K., Peng, C., Peng, S., Peters, G. P., Pison, I., Prinn, R., Ramonet, M., Riley, W. J., Saito, M., Santini, M., Schroeder, R., Simpson, I. J., Spahni, R., Takizawa, A., Thornton, B. F., Tian, H., Tohjima, Y., Viovy, N., Voulgarakis, A., Weiss, R., Wilton, D. J., Wiltshire, A., Worthy, D., Wunch, D., Xu, X., Yoshida, Y., Zhang, B., Zhang, Z., and Zhu, Q.: Variability and quasi-decadal changes in the methane budget over the period 2000–2012, Atmos. Chem. Phys., 17, 11135–11161, https://doi.org/10.5194/acp-17-11135-2017, 2017. 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 Syst. Sci. Data, 12, 1561–1623, https://doi.org/10.5194/essd-12-1561-2020, 2020. a, b, c, d, e
Saunois, M., Martinez, A., Poulter, B., Zhang, Z., Raymond, P. A., Regnier, P., Canadell, J. G., Jackson, R. B., Patra, P. K., Bousquet, P., Ciais, P., Dlugokencky, E. J., Lan, X., Allen, G. H., Bastviken, D., Beerling, D. J., Belikov, D. A., Blake, D. R., Castaldi, S., Crippa, M., Deemer, B. R., Dennison, F., Etiope, G., Gedney, N., Höglund-Isaksson, L., Holgerson, M. A., Hopcroft, P. O., Hugelius, G., Ito, A., Jain, A. K., Janardanan, R., Johnson, M. S., Kleinen, T., Krummel, P. B., Lauerwald, R., Li, T., Liu, X., McDonald, K. C., Melton, J. R., Mühle, J., Müller, J., Murguia-Flores, F., Niwa, Y., Noce, S., Pan, S., Parker, R. J., Peng, C., Ramonet, M., Riley, W. J., Rocher-Ros, G., Rosentreter, J. A., Sasakawa, M., Segers, A., Smith, S. J., Stanley, E. H., Thanwerdas, J., Tian, H., Tsuruta, A., Tubiello, F. N., Weber, T. S., van der Werf, G. R., Worthy, D. E. J., Xi, Y., Yoshida, Y., Zhang, W., Zheng, B., Zhu, Q., Zhu, Q., and Zhuang, Q.: Global Methane Budget 2000–2020, Earth Syst. Sci. Data, 17, 1873–1958, https://doi.org/10.5194/essd-17-1873-2025, 2025. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t
Scarpelli, T. R., Jacob, D. J., Grossman, S., Lu, X., Qu, Z., Sulprizio, M. P., Zhang, Y., Reuland, F., Gordon, D., and Worden, J. R.: Updated Global Fuel Exploitation Inventory (GFEI) for methane emissions from the oil, gas, and coal sectors: evaluation with inversions of atmospheric methane observations, Atmos. Chem. Phys., 22, 3235–3249, https://doi.org/10.5194/acp-22-3235-2022, 2022. a, b, c
Schaefer, H.: On the causes and consequences of recent trends in atmospheric methane, Current Climate Change Reports, 5, 259–274, https://doi.org/10.1007/s40641-019-00140-z, 2019. a
Schaefer, H., Fletcher, S. E. M., Veidt, C., Lassey, K. R., Brailsford, G. W., Bromley, T. M., Dlugokencky, E. J., Michel, S. E., Miller, J. B., Levin, I., Lowe, D. C., Martin, R. J., Vaughn, B. H., and White, J. W. C.: A 21st-century shift from fossil-fuel to biogenic methane emissions indicated by 13CH4, Science, 352, 80–84, https://doi.org/10.1126/science.aad2705, 2016. a, b
Schoell, M., Jenden, P. D., Beeunas, M. A., and Coleman, D. D.: Isotope analyses of gases in gas field and gas storage operations, in: SPE Gas Technology Symposium, OnePetro, SPE-26171-MS, https://doi.org/10.2118/26171-MS, 1993. a
Schuldt, K. N., Aalto, T., Andrade, M., Arlyn Andrews, Apadula, F., Jgor Arduini, Arnold, S., Baier, B., Bäni, L., Bartyzel, J., Bergamaschi, P., Biermann, T., Biraud, S. C., Pierre-Eric Blanc, Boenisch, H., Brailsford, G., Brand, W. A., Brunner, D., Bui, T. P. V., Van Den Bulk, P., Benoit Burban, Francescopiero Calzolari, Chang, C. S., Huilin Chen, Lukasz Chmura, St. Clair, J. M., Sites Climadat, Coletta, J. D., Colomb, A., Condori, L., Conen, F., Conil, S., Couret, C., Cristofanelli, P., Cuevas, E., Curcoll, R., Daube, B., Davis, K. J., Dean-Day, J. M., Delmotte, M., Ankur Desai, DiGangi, E., DiGangi, J. P., Elsasser, M., Emmenegger, L., Forster, G., Frumau, A., Fuente-Lastra, M., Galkowski, M., Gatti, L. V., Gehrlein, T., Gerbig, C., Francois Gheusi, Gloor, E., Goto, D., Hammer, S., Hanisco, T. F., Haszpra, L., Hatakka, J., Heimann, M., Heliasz, M., Heltai, D., Henne, S., Hensen, A., Hermans, C., Hermansen, O., Hoheisel, A., Holst, J., Di Iorio, T., Iraci, L. T., Ivakhov, V., Jaffe, D. A., Jordan, A., Joubert, W., Kang, H.-Y., Karion, A., Kazan, V., Keeling, R. F., Keronen, P., Kers, B., Jooil Kim, Klausen, J., Kneuer, T., Ko, M.-Y., Kolari, P., Kominkova, K., Kort, E., Kozlova, E., Krummel, P. B., Kubistin, D., Kulawik, S. S., Kumps, N., Labuschagne, C., Lan, X., Langenfelds, R. L., Lanza, A., Laurent, O., Laurila, T., Lauvaux, T., Lavric, J., Choong-Hoon Lee, Lee, J., Lehner, I., Lehtinen, K., Leppert, R., Leskinen, A., Leuenberger, M., Levin, I., Levula, J., Lindauer, M., Lindroth, A., Mikaell Ottosson Löfvenius, Loh, Z. M., Lopez, M., Lowry, D., Lunder, C. R., Machida, T., Mammarella, I., Manca, G., Manning, A., Marek, M. V., Marklund, P., Marrero, J. E., Martin, D., Martin, M. Y., Giordane A. Martins, Matsueda, H., De Mazière, M., McKain, K., Meinhardt, F., Menoud, M., Jean-Marc Metzger, Miles, N. L., Miller, C. E., Miller, J. B., Mölder, M., Monteiro, V., Montzka, S., Moore, F., Moossen, H., Moreno, C., Morgan, E., Josep-Anton Morgui, Morimoto, S., Müller-Williams, J., Munro, D., Mutuku, M., Myhre, C. L., Jaroslaw Necki, Nichol, S., Nisbet, E., Niwa, Y., Njiru, D. M., Noe, S. M., O'Doherty, S., Obersteiner, F., Parworth, C. L., Peltola, O., Peters, W., Philippon, C., Piacentino, S., Pichon, J. M., Pickers, P., Pitt, J., Pittman, J., Plass-Dülmer, C., Platt, S. M., Popa, M. E., Prinzivalli, S., Ramonet, M., Richardson, S. J., Louis-Jeremy Rigouleau, Rivas, P. P., Röckmann, T., Rothe, M., Yves-Alain Roulet, Ju-Mee Ryoo, Santoni, G., Di Sarra, A. G., Sasakawa, M., Schaefer, H., Scheeren, B., Schmidt, M., Schuck, T., Schumacher, M., Seifert, T., Sha, M. K., Shepson, P., Daegeun Shin, Sloop, C. D., Smale, D., Smith, P. D., Sørensen, L. L., De Souza, R. A. F., Spain, G., Steger, D., Steinbacher, M., Stephens, B., Sweeney, C., Taipale, R., Takatsuji, S., Thoning, K., Timas, H., Torn, M., Trisolino, P., Turnbull, J., Van Der Veen, C., Vermeulen, A., Viner, B., Vitkova, G., De Vries, M., Watson, A., Weiss, R., Weyrauch, D., Wofsy, S. C., Worsey, J., Worthy, D., Xueref-Remy, I., Yates, E. L., Dickon Young, Yver-Kwok, C., Zaehle, S., Zahn, A., Zazzeri, G., Zellweger, C., and Miroslaw Zimnoch: Multi-Laboratory Compilation of Atmospheric Carbon Dioxide Data for the Period 1983–2023; obspack_ch4_1_GLOBALVIEWplus_v7.0_2024-10-29, NOAA Global Monitoring Laboratory [data set], https://doi.org/10.25925/20241001, 2024. a
Schuldt, K. N., Arlyn Andrews, Bartyzel, J., Brailsford, G., Brand, W. A., Huilin Chen, Clark, R., Heimann, M., Jordan, A., Kers, B., Lan, X., Lavric, J., Lowry, D., Menoud, M., Michel, S. E., Miller, J. B., Moossen, H., Morimoto, S., Jaroslaw Necki, Nisbet, E., Ortega, J., Popa, M. E., Röckmann, T., Rothe, M., Schaefer, H., Scheeren, B., Sweeney, C., Umezawa, T., Van Der Veen, C., De Vries, M., and Zazzeri, G.: Multi-Laboratory Compilation of Atmospheric Methane Isotope Data for the Period 1991–2023; Obspack_ch4c13_1_methane-Isotope_2025-04-07, NOAA Global Monitoring Laboratory [data set], https://doi.org/10.25925/20250401, 2025. a, b, c, d, e, f, g, h
Schwietzke, S., Griffin, W. M., Matthews, H. S., and Bruhwiler, L. M. P.: Global bottom-up fossil fuel fugitive methane and ethane emissions inventory for atmospheric modeling, ACS Sustain. Chem. Eng., 2, 1992–2001, https://doi.org/10.1021/sc500163h, 2014. a
Schwietzke, S., Sherwood, O. A., Bruhwiler, L. M. P., Miller, J. B., Etiope, G., Dlugokencky, E. J., Michel, S. E., Arling, V. A., Vaughn, B. H., White, J. W. C., and Tans, P. P.: Upward revision of global fossil fuel methane emissions based on isotope database, Nature, 538, 88–91, https://doi.org/10.1038/nature19797, 2016. a, b, c
Shaw, J. T., Allen, G., Barker, P., Pitt, J. R., Pasternak, D., Bauguitte, S. J.-B., Lee, J., Bower, K. N., Daly, M. C., Lunt, M. F., Ganesan, A. L., Vaughan, A. R., Chibesakunda, F., Lambakasa, M., Fisher, R. E., France, J. L., Lowry, D., Palmer, P. I., Metzger, S., Parker, R. J., Gedney, N., Bateson, P., Cain, M., Lorente, A., Borsdorff, T., and Nisbet, E. G.: Large methane emission fluxes observed from tropical wetlands in Zambia, Global Biogeochem. Cy., 36, e2021GB007261, https://doi.org/10.1029/2021GB007261, 2022. a, b, c
Sherwen, T., Schmidt, J. A., Evans, M. J., Carpenter, L. J., Großmann, K., Eastham, S. D., Jacob, D. J., Dix, B., Koenig, T. K., Sinreich, R., Ortega, I., Volkamer, R., Saiz-Lopez, A., Prados-Roman, C., Mahajan, A. S., and Ordóñez, C.: Global impacts of tropospheric halogens (Cl, Br, I) on oxidants and composition in GEOS-Chem, Atmos. Chem. Phys., 16, 12239–12271, https://doi.org/10.5194/acp-16-12239-2016, 2016. a
Shindell, D., Ravishankara, A. R., Kuylenstierna, J. C. I., Michalopoulou, E., Höglund-Isaksson, L., Zhang, Y., Seltzer, K., Ru, M., Castelino, R., Faluvegi, G., Naik, V., Horowitz, L., He, J., Lamarque, J.-F., Sudo, K., Collins, W. J., Malley, C., Harmsen, M., Stark, K., Junkin, J., Li, G., Glick, A., and Borgford-Parnell, N.: Global Methane Assessment: Benefits and Costs of Mitigating Methane Emissions, United Nations Environment Programme, 2021. a
Skeie, R. B., Hodnebrog, Ø., and Myhre, G.: Trends in atmospheric methane concentrations since 1990 were driven and modified by anthropogenic emissions, Communications Earth and Environment, 4, 1–14, https://doi.org/10.1038/s43247-023-00969-1, 2023. a
Snover, A. K. and Quay, P. D.: Hydrogen and carbon kinetic isotope effects during soil uptake of atmospheric methane, Global Biogeochem. Cy., 14, 25–39, https://doi.org/10.1029/1999GB900089, 2000. a, b, c
Stavert, A. R., Saunois, M., Canadell, J. G., Poulter, B., Jackson, R. B., Regnier, P., Lauerwald, R., Raymond, P. A., Allen, G. H., Patra, P. K., Bergamaschi, P., Bousquet, P., Chandra, N., Ciais, P., Gustafson, A., Ishizawa, M., Ito, A., Kleinen, T., Maksyutov, S., McNorton, J., Melton, J. R., Müller, J., Niwa, Y., Peng, S., Riley, W. J., Segers, A., Tian, H., Tsuruta, A., Yin, Y., Zhang, Z., Zheng, B., and Zhuang, Q.: Regional trends and drivers of the global methane budget, Glob. Change Biol., 28, 182–200, https://doi.org/10.1111/gcb.15901, 2022. a
Stevenson, D. S., Zhao, A., Naik, V., O'Connor, F. M., Tilmes, S., Zeng, G., Murray, L. T., Collins, W. J., Griffiths, P. T., Shim, S., Horowitz, L. W., Sentman, L. T., and Emmons, L.: Trends in global tropospheric hydroxyl radical and methane lifetime since 1850 from AerChemMIP, Atmos. Chem. Phys., 20, 12905–12920, https://doi.org/10.5194/acp-20-12905-2020, 2020. a
Still, C. J., Berry, J. A., Collatz, G. J., and DeFries, R. S.: Global distribution of C3 and C4 vegetation: carbon cycle implications, Global Biogeochem. Cy., 17, 6–1–6–14, https://doi.org/10.1029/2001GB001807, 2003. a, b, c, d
Stocker, T.: Climate Change 2013: The Physical Science Basis: Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, https://doi.org/10.1017/CBO9781107415324, 2014. a
Sugimoto, A., Inoue, T., Kirtibutr, N., and Abe, T.: Methane oxidation by termite mounds estimated by the carbon isotopic composition of methane, Global Biogeochem. Cy., 12, 595–605, https://doi.org/10.1029/98GB02266, 1998. a, b
Tans, P. P.: A note on isotopic ratios and the global atmospheric methane budget, Global Biogeochem. Cy., 11, 77–81, https://doi.org/10.1029/96GB03940, 1997. a
Tapin, E., Berchet, A., Martinez, A., Thanwerdas, J., Lan, X., Malina, E., Gasbarra, D., and Saunois, M.: Global δ13C(CH4) Source Signatures (Version 1), European Space Agency, [data set], https://doi.org/10.57780/ESA-6D202E9, 2025. a, b, c
Thanwerdas, J., Saunois, M., Berchet, A., Pison, I., Vaughn, B. H., Michel, S. E., and Bousquet, P.: Variational inverse modeling within the Community Inversion Framework v1.1 to assimilate δ13C(CH4) and CH4: a case study with model LMDz-SACS, Geosci. Model Dev., 15, 4831–4851, https://doi.org/10.5194/gmd-15-4831-2022, 2022a. a
Thanwerdas, J., Saunois, M., Pison, I., Hauglustaine, D., Berchet, A., Baier, B., Sweeney, C., and Bousquet, P.: How do Cl concentrations matter for the simulation of CH4 and δ13C(CH4) and estimation of the CH4 budget through atmospheric inversions?, Atmos. Chem. Phys., 22, 15489–15508, https://doi.org/10.5194/acp-22-15489-2022, 2022b. a, b, c, d, e, f, g, h, i, j
Thanwerdas, J., Saunois, M., Berchet, A., Pison, I., and Bousquet, P.: Investigation of the renewed methane growth post-2007 with high-resolution 3-D variational inverse modeling and isotopic constraints, Atmos. Chem. Phys., 24, 2129–2167, https://doi.org/10.5194/acp-24-2129-2024, 2024. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r
Thompson, R. L., Nisbet, E. G., Pisso, I., Stohl, A., Blake, D., Dlugokencky, E. J., Helmig, D., and White, J. W. C.: Variability in atmospheric methane from fossil fuel and microbial sources over the last three decades, Geophys. Res. Lett., 45, 11499–11508, https://doi.org/10.1029/2018GL078127, 2018. a, b
Tian, H., Xu, X., Liu, M., Ren, W., Zhang, C., Chen, G., and Lu, C.: Spatial and temporal patterns of CH4 and N2O fluxes in terrestrial ecosystems of North America during 1979–2008: application of a global biogeochemistry model, Biogeosciences, 7, 2673–2694, https://doi.org/10.5194/bg-7-2673-2010, 2010. a
Turner, A. J., Frankenberg, C., and Kort, E. A.: Interpreting contemporary trends in atmospheric methane, P. Natl. Acad. Sci. USA, 116, 2805–2813, https://doi.org/10.1073/pnas.1814297116, 2019. a
UNEP and Climate and Clean Air Coalition: Global Methane Assessment: 2030 Baseline Report, Technical report, United Nations Environment Programme, Nairobi, https://wedocs.unep.org/handle/20.500.11822/41107 (last access: 1 July 2024), 2022. a
Van Bergen, T. J. H. M., Barros, N., Mendonça, R., Aben, R. C. H., Althuizen, I. H. J., Huszar, V., Lamers, L. P. M., Lürling, M., Roland, F., and Kosten, S.: Seasonal and diel variation in greenhouse gas emissions from an urban pond and its major drivers, Limnol. Oceanogr., 64, 2129–2139, https://doi.org/10.1002/lno.11173, 2019. a, b
van Herpen, M. M. J. W., Li, Q., Saiz-Lopez, A., Liisberg, J. B., Röckmann, T., Cuevas, C. A., Fernandez, R. P., Mak, J. E., Mahowald, N. M., Hess, P., Meidan, D., Stuut, J.-B. W., and Johnson, M. S.: Photocatalytic chlorine atom production on mineral dust–sea spray aerosols over the North Atlantic, P. Natl. Acad. Sci. USA, 120, e2303974120, https://doi.org/10.1073/pnas.2303974120, 2023. a
van Wees, D., van der Werf, G. R., Randerson, J. T., Rogers, B. M., Chen, Y., Veraverbeke, S., Giglio, L., and Morton, D. C.: Global biomass burning fuel consumption and emissions at 500 m spatial resolution based on the Global Fire Emissions Database (GFED), Geosci. Model Dev., 15, 8411–8437, https://doi.org/10.5194/gmd-15-8411-2022, 2022. a, b
Vanselow, S., Schneising, O., Buchwitz, M., Reuter, M., Bovensmann, H., Boesch, H., and Burrows, J. P.: Automated detection of regions with persistently enhanced methane concentrations using Sentinel-5 Precursor satellite data, Atmos. Chem. Phys., 24, 10441–10473, https://doi.org/10.5194/acp-24-10441-2024, 2024. a
Wang, X., Jacob, D. J., Downs, W., Zhai, S., Zhu, L., Shah, V., Holmes, C. D., Sherwen, T., Alexander, B., Evans, M. J., Eastham, S. D., Neuman, J. A., Veres, P. R., Koenig, T. K., Volkamer, R., Huey, L. G., Bannan, T. J., Percival, C. J., Lee, B. H., and Thornton, J. A.: Global tropospheric halogen (Cl, Br, I) chemistry and its impact on oxidants, Atmos. Chem. Phys., 21, 13973–13996, https://doi.org/10.5194/acp-21-13973-2021, 2021. a, b, c, d, e
Wang, X., Liu, C.-Q., Yi, Y., Zeng, M., Li, S.-L., and Niu, X.: Machine learning predicts the methane clumped isotopologue (12CH2D2) distributions constrain biogeochemical processes and estimates the potential budget, Environ. Sci. Technol., 57, 17876–17888, https://doi.org/10.1021/acs.est.3c00184, 2023. a
Weber, T., Wiseman, N. A., and Kock, A.: Global ocean methane emissions dominated by shallow coastal waters, Nat. Commun., 10, 4584, https://doi.org/10.1038/s41467-019-12541-7, 2019. a
Wei, M., Yu, Z., Jiang, Z., and Zhang, H.: Microbial diversity and biogenic methane potential of a thermogenic-gas coal mine, Int. J. Coal Geol., 134–135, 96–107, https://doi.org/10.1016/j.coal.2014.09.008, 2014. a
Worden, J. R., Bloom, A. A., Pandey, S., Jiang, Z., Worden, H. M., Walker, T. W., Houweling, S., and Röckmann, T.: Reduced biomass burning emissions reconcile conflicting estimates of the post-2006 atmospheric methane budget, Nat. Commun., 8, 2227, https://doi.org/10.1038/s41467-017-02246-0, 2017. a
Yao, P., Belec, K., Holmstrand, H., Balacky, J., Salam, A., Budhavant, K., Manoj, M. R., Joy, K. S., Hossain, M. A., Singh, A., Patel, A., Rastogi, N., Mallik, C., Ram, K., Singh, G. K., and Gustafsson, Ö.: Distinct dual-isotopic signatures of major methane sources in South Asia, Atmos. Chem. Phys., 26, 7765–7787, https://doi.org/10.5194/acp-26-7765-2026, 2026. a
Zhang, Z., Poulter, B., Feldman, A. F., Ying, Q., Ciais, P., Peng, S., and Li, X.: Recent intensification of wetland methane feedback, Nat. Clim. Change, 13, 430–433, https://doi.org/10.1038/s41558-023-01629-0, 2023. a
Zhao, Y., Saunois, M., Bousquet, P., Lin, X., Berchet, A., Hegglin, M. I., Canadell, J. G., Jackson, R. B., Hauglustaine, D. A., Szopa, S., Stavert, A. R., Abraham, N. L., Archibald, A. T., Bekki, S., Deushi, M., Jöckel, P., Josse, B., Kinnison, D., Kirner, O., Marécal, V., O'Connor, F. M., Plummer, D. A., Revell, L. E., Rozanov, E., Stenke, A., Strode, S., Tilmes, S., Dlugokencky, E. J., and Zheng, B.: Inter-model comparison of global hydroxyl radical (OH) distributions and their impact on atmospheric methane over the 2000–2016 period, Atmos. Chem. Phys., 19, 13701–13723, https://doi.org/10.5194/acp-19-13701-2019, 2019. a, b, c, d
Zimmermann, P. H., Brenninkmeijer, C. A. M., Pozzer, A., Jöckel, P., Winterstein, F., Zahn, A., Houweling, S., and Lelieveld, J.: Model simulations of atmospheric methane (1997–2016) and their evaluation using NOAA and AGAGE surface and IAGOS-CARIBIC aircraft observations, Atmos. Chem. Phys., 20, 5787–5809, https://doi.org/10.5194/acp-20-5787-2020, 2020. a
Short summary
We present global δ¹³C-CH₄ source signature maps (1998–2022) at 1°×1° resolution for five emission sectors and 11 sub-sectors, with quantified uncertainties. Sensitivity experiments with an atmospheric transport model assess how uncertainties in emissions, isotopic signatures, OH sinks, and kinetic isotope effects influence atmospheric δ¹³C-CH₄ and CH₄, providing guidance for isotopic inversions.
We present global δ¹³C-CH₄ source signature maps (1998–2022) at 1°×1° resolution for five...
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