Articles | Volume 19, issue 17
https://doi.org/10.5194/amt-19-5603-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-19-5603-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 Sep 2026
Research article |
| 04 Sep 2026
| 04 Sep 2026
Modelling wetland methane emission estimates by leveraging new observations of anthropogenic point-source plumes
Anthony Campbell
CORRESPONDING AUTHOR
Biospheric Sciences Laboratory, Goddard Space Flight Center, NASA, Greenbelt, MD, USA
Goddard Earth and Technology Research II, University of Maryland, Baltimore County, Baltimore, MD, USA
Lauren Potyk
Biospheric Sciences Laboratory, Goddard Space Flight Center, NASA, Greenbelt, MD, USA
John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
Benjamin Poulter
Spark Climate Solutions, San Francisco, USA
formerly at: Biospheric Sciences Laboratory, Goddard Space Flight Center, NASA, Greenbelt, MD, USA
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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.
Hanyu Liu, Charles E. Miller, Colm Sweeney, Kathryn McKain, Jennifer D. Watts, Róisín Commane, Luke D. Schiferl, Zhen Zhang, Benjamin Poulter, Leyang Feng, Ao Chen, Ziting Huang, Dylan C. Gaeta, Kristan L. Morgan, William S. Daniels, Qiulun Li, Joe R. Melton, Vineet Yadav, Deborah Huntzinger, and Scot M. Miller
EGUsphere, https://doi.org/10.5194/egusphere-2026-6528, https://doi.org/10.5194/egusphere-2026-6528, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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We combine NASA aircraft observations with atmospheric inverse modeling to estimate Alaska’s growing-season methane fluxes for 2012–2015 and 2017. Our statewide estimates are 1.3–2.9 times those of process-based models, with the largest discrepancies on Alaska’s North Slope. We find that differences in wetland inundation fraction maps contribute to these gaps, highlighting the need for improved inundation fraction mapping and atmospheric observations to constrain Arctic methane emissions.
Sarah E. Hancock, Daniel J. Jacob, Nicholas Balasus, Carlos Andres Garzon, Ciniro Costa Junior, Matthew R. Johnson, Nikolai Calderón-Cangrejo, Scott Winton, Megan He, Lauren Potyk, Lucas A. Estrada, Rodrigo Jimenez, Andrés Ardila, Luis Morales-Rincon, and James L. France
EGUsphere, https://doi.org/10.5194/egusphere-2026-5754, https://doi.org/10.5194/egusphere-2026-5754, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Satellite observations reveal why methane emissions rose in Colombia during 2019–2024. Wetlands drove most of the increase, with emissions peaking during the wet La Niña years of 2021–2022. Human activities showed a steadier rise, led by livestock, waste, and fossil fuels. Wetland emissions tracked changes in water storage more closely than flooded area alone. These findings help distinguish natural variability from human sources when tracking progress on methane mitigation.
Hui Li, Philippe Ciais, Frédéric Chevallier, Bo Zheng, Paul I. Palmer, Frank Hase, Morgan Lopez, Elsa M. Ordway, Shushi Peng, Danielle Monteverde, Michel Ramonet, Jason M. St. Clair, Le Bienfaiteur Sagang, and Benjamin Poulter
Atmos. Chem. Phys., 26, 11893–11908, https://doi.org/10.5194/acp-26-11893-2026, https://doi.org/10.5194/acp-26-11893-2026, 2026
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We studied how to best place methane monitoring instruments across Africa to better understand where emissions come from. Because observations can overlap in what they detect, adding more sites does not always improve results equally. Using a statistical approach, we identified both the ideal number and locations of sites (ten new sites can reduce emission uncertainty by over 65 % for total African CH4). Our results help guide cost-effective monitoring strategies in regions with limited data.
Sarah E. Hancock, Daniel J. Jacob, Rodrigo Jimenez, Andrés Ardila, Luis Morales-Rincon, Néstor Rojas, Lucas A. Estrada, Nicholas Balasus, James D. East, Melissa P. Sulprizio, Xiaolin Wang, James L. France, Lauren Potyk, Elise Penn, Zichong Chen, Daniel J. Varon, Christian Frankenberg, Marci Baranski, Andreea Calcan, and Robert J. Parker
Atmos. Chem. Phys., 26, 10455–10476, https://doi.org/10.5194/acp-26-10455-2026, https://doi.org/10.5194/acp-26-10455-2026, 2026
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We combined satellite observations with detailed national data to improve estimates of Colombia’s methane emissions. Our results show that total methane emissions are higher than reported, with the biggest differences from fossil fuels. This approach demonstrates how satellite data can make national greenhouse gas reporting more accurate and transparent under the Paris Agreement.
Nikola Besic, Philippe Ciais, Fa Li, Robert Jackson, Kunxiaojia Yuan, Shushi Peng, Benjamin Poulter, Zhen Zhang, and Qing Zhu
EGUsphere, https://doi.org/10.5194/egusphere-2026-2604, https://doi.org/10.5194/egusphere-2026-2604, 2026
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Wetlands are the largest natural source of methane, an important greenhouse gas, but current estimates of their emissions remain highly uncertain because models often disagree. We combined field measurements from wetlands around the world with advanced statistical methods to identify where different models perform best. Our results show that accounting for regional differences in model skill can substantially change local methane estimates and potentially improve future climate assessments.
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.
Min Feng, Joseph O. Sexton, Panshi Wang, Paul M. Montesano, Leonardo Calle, Nuno Carvalhais, Benjamin Poulter, Matthew J. Macander, Michael A. Wulder, Margaret Wooten, William Wagner, Akiko Elders, Saurabh Channan, and Christopher S. R. Neigh
Biogeosciences, 23, 1089–1101, https://doi.org/10.5194/bg-23-1089-2026, https://doi.org/10.5194/bg-23-1089-2026, 2026
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Analysis of 36 years of satellite tree cover data provide the first comprehensive confirmation of the northward advance of the boreal forest. Boreal tree cover expanded by 0.84 million km² (12%) from 1985 to 2020 and shifted northward by 0.43°. Gains outpaced losses across most latitudes, confirming a biome-wide poleward shift. Young forests now comprise 15% of the area of the world’s largest forest biome, storing 1–6 Pg C and potentially sequestering an additional 2–4 Pg C as they mature.
Hanyu Liu, Misa Ishizawa, Felix R. Vogel, Zhen Zhang, Benjamin Poulter, Leyang Feng, Ao Chen, Anna L. Gagné-Landmann, Deborah N. Huntzinger, Joe R. Melton, Vineet Yadav, Dylan C. Gaeta, Ziting Huang, Douglas E. J. Worthy, Douglas Chan, and Scot M. Miller
Atmos. Chem. Phys., 26, 1229–1247, https://doi.org/10.5194/acp-26-1229-2026, https://doi.org/10.5194/acp-26-1229-2026, 2026
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We find that the state-of-the-art process-based methane flux models have both lower flux magnitude and reduced inter-model uncertainty compared to a previous model inter-comparison from over a decade ago. Despite these improvements, methane flux estimates from process-based models are still likely too high compared to atmospheric observations. We also find that models with simpler parameterizations often result in better agreement with atmospheric observations in high-latitude North America.
Rubaya Pervin, Scott Robeson, Mallory Barnes, Stephen Sitch, Anthony Walker, Ben Poulter, Fabienne Maignan, Qing Sun, Thomas Colligan, Sönke Zaehle, Kashif Mahmud, Peter Anthoni, Almut Arneth, Vivek Arora, Vladislav Bastrikov, Liam Bogucki, Bertrand Decharme, Christine Delire, Stefanie Falk, Akihiko Ito, Etsushi Kato, Daniel Kennedy, Jürgen Knauer, Michael O’Sullivan, Wenping Yuan, and Natasha MacBean
EGUsphere, https://doi.org/10.5194/egusphere-2025-2841, https://doi.org/10.5194/egusphere-2025-2841, 2025
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Drylands contribute more than a third of the global vegetation productivity. Yet, these regions are not well represented in global vegetation models. Here, we tested how well 15 global models capture annual changes in dryland vegetation productivity. Models that didn’t have vegetation change over time or fire have lower variability in vegetation productivity. Models need better representation of grass cover types and their coverage. Our work highlights where and how these models need to improve.
Qing Ying, Benjamin Poulter, Jennifer D. Watts, Kyle A. Arndt, Anna-Maria Virkkala, Lori Bruhwiler, Youmi Oh, Brendan M. Rogers, Susan M. Natali, Hilary Sullivan, Amanda Armstrong, Eric J. Ward, Luke D. Schiferl, Clayton D. Elder, Olli Peltola, Annett Bartsch, Ankur R. Desai, Eugénie Euskirchen, Mathias Göckede, Bernhard Lehner, Mats B. Nilsson, Matthias Peichl, Oliver Sonnentag, Eeva-Stiina Tuittila, Torsten Sachs, Aram Kalhori, Masahito Ueyama, and Zhen Zhang
Earth Syst. Sci. Data, 17, 2507–2534, https://doi.org/10.5194/essd-17-2507-2025, https://doi.org/10.5194/essd-17-2507-2025, 2025
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We present daily methane (CH4) fluxes of northern wetlands at 10 km resolution during 2016–2022 (WetCH4) derived from a novel machine learning framework. We estimated an average annual CH4 emission of 22.8 ± 2.4 Tg CH4 yr−1 (15.7–51.6 Tg CH4 yr−1). Emissions were intensified in 2016, 2020, and 2022, with the largest interannual variation coming from Western Siberia. Continued, all-season tower observations and improved soil moisture products are needed for future improvement of CH4 upscaling.
Bernhard Lehner, Mira Anand, Etienne Fluet-Chouinard, Florence Tan, Filipe Aires, George H. Allen, Philippe Bousquet, Josep G. Canadell, Nick Davidson, Meng Ding, C. Max Finlayson, Thomas Gumbricht, Lammert Hilarides, Gustaf Hugelius, Robert B. Jackson, Maartje C. Korver, Liangyun Liu, Peter B. McIntyre, Szabolcs Nagy, David Olefeldt, Tamlin M. Pavelsky, Jean-Francois Pekel, Benjamin Poulter, Catherine Prigent, Jida Wang, Thomas A. Worthington, Dai Yamazaki, Xiao Zhang, and Michele Thieme
Earth Syst. Sci. Data, 17, 2277–2329, https://doi.org/10.5194/essd-17-2277-2025, https://doi.org/10.5194/essd-17-2277-2025, 2025
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The Global Lakes and Wetlands Database (GLWD) version 2 distinguishes a total of 33 non-overlapping wetland classes, providing a static map of the world’s inland surface waters. It contains cell fractions of wetland extents per class at a grid cell resolution of ~500 m. The total combined extent of all classes including all inland and coastal waterbodies and wetlands of all inundation frequencies – that is, the maximum extent – covers 18.2 × 106 km2, equivalent to 13.4 % of total global land area.
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.
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.
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.
Giacomo Grassi, Clemens Schwingshackl, Thomas Gasser, Richard A. Houghton, Stephen Sitch, Josep G. Canadell, Alessandro Cescatti, Philippe Ciais, Sandro Federici, Pierre Friedlingstein, Werner A. Kurz, Maria J. Sanz Sanchez, Raúl Abad Viñas, Ramdane Alkama, Selma Bultan, Guido Ceccherini, Stefanie Falk, Etsushi Kato, Daniel Kennedy, Jürgen Knauer, Anu Korosuo, Joana Melo, Matthew J. McGrath, Julia E. M. S. Nabel, Benjamin Poulter, Anna A. Romanovskaya, Simone Rossi, Hanqin Tian, Anthony P. Walker, Wenping Yuan, Xu Yue, and Julia Pongratz
Earth Syst. Sci. Data, 15, 1093–1114, https://doi.org/10.5194/essd-15-1093-2023, https://doi.org/10.5194/essd-15-1093-2023, 2023
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Striking differences exist in estimates of land-use CO2 fluxes between the national greenhouse gas inventories and the IPCC assessment reports. These differences hamper an accurate assessment of the collective progress under the Paris Agreement. By implementing an approach that conceptually reconciles land-use CO2 flux from national inventories and the global models used by the IPCC, our study is an important step forward for increasing confidence in land-use CO2 flux estimates.
Brendan Byrne, David F. Baker, Sourish Basu, Michael Bertolacci, Kevin W. Bowman, Dustin Carroll, Abhishek Chatterjee, Frédéric Chevallier, Philippe Ciais, Noel Cressie, David Crisp, Sean Crowell, Feng Deng, Zhu Deng, Nicholas M. Deutscher, Manvendra K. Dubey, Sha Feng, Omaira E. García, David W. T. Griffith, Benedikt Herkommer, Lei Hu, Andrew R. Jacobson, Rajesh Janardanan, Sujong Jeong, Matthew S. Johnson, Dylan B. A. Jones, Rigel Kivi, Junjie Liu, Zhiqiang Liu, Shamil Maksyutov, John B. Miller, Scot M. Miller, Isamu Morino, Justus Notholt, Tomohiro Oda, Christopher W. O'Dell, Young-Suk Oh, Hirofumi Ohyama, Prabir K. Patra, Hélène Peiro, Christof Petri, Sajeev Philip, David F. Pollard, Benjamin Poulter, Marine Remaud, Andrew Schuh, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Colm Sweeney, Yao Té, Hanqin Tian, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, John R. Worden, Debra Wunch, Yuanzhi Yao, Jeongmin Yun, Andrew Zammit-Mangion, and Ning Zeng
Earth Syst. Sci. Data, 15, 963–1004, https://doi.org/10.5194/essd-15-963-2023, https://doi.org/10.5194/essd-15-963-2023, 2023
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Changes in the carbon stocks of terrestrial ecosystems result in emissions and removals of CO2. These can be driven by anthropogenic activities (e.g., deforestation), natural processes (e.g., fires) or in response to rising CO2 (e.g., CO2 fertilization). This paper describes a dataset of CO2 emissions and removals derived from atmospheric CO2 observations. This pilot dataset informs current capabilities and future developments towards top-down monitoring and verification systems.
Andrew F. Feldman, Zhen Zhang, Yasuko Yoshida, Abhishek Chatterjee, and Benjamin Poulter
Atmos. Chem. Phys., 23, 1545–1563, https://doi.org/10.5194/acp-23-1545-2023, https://doi.org/10.5194/acp-23-1545-2023, 2023
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We investigate the conditions under which satellite-retrieved column carbon dioxide concentrations directly hold information about surface carbon dioxide fluxes, without the use of inversion models. We show that OCO-2 column carbon dioxide retrievals, available at 1–3 month latency, can be used to directly detect and roughly estimate extreme biospheric CO2 fluxes. As such, these OCO-2 retrievals have value for rapidly monitoring extreme conditions in the terrestrial biosphere.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, 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, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
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The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. 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.
Daniel J. Jacob, Daniel J. Varon, Daniel H. Cusworth, Philip E. Dennison, Christian Frankenberg, Ritesh Gautam, Luis Guanter, John Kelley, Jason McKeever, Lesley E. Ott, Benjamin Poulter, Zhen Qu, Andrew K. Thorpe, John R. Worden, and Riley M. Duren
Atmos. Chem. Phys., 22, 9617–9646, https://doi.org/10.5194/acp-22-9617-2022, https://doi.org/10.5194/acp-22-9617-2022, 2022
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We review the capability of satellite observations of atmospheric methane to quantify methane emissions on all scales. We cover retrieval methods, precision requirements, inverse methods for inferring emissions, source detection thresholds, and observations of system completeness. We show that current instruments already enable quantification of regional and national emissions including contributions from large point sources. Coverage and resolution will increase significantly in coming years.
Colm Sweeney, Abhishek Chatterjee, Sonja Wolter, Kathryn McKain, Robert Bogue, Stephen Conley, Tim Newberger, Lei Hu, Lesley Ott, Benjamin Poulter, Luke Schiferl, Brad Weir, Zhen Zhang, and Charles E. Miller
Atmos. Chem. Phys., 22, 6347–6364, https://doi.org/10.5194/acp-22-6347-2022, https://doi.org/10.5194/acp-22-6347-2022, 2022
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The Arctic Carbon Atmospheric Profiles (Arctic-CAP) project demonstrates the utility of aircraft profiles for independent evaluation of model-derived emissions and uptake of atmospheric CO2, CH4, and CO from land and ocean. Comparison with the Goddard Earth Observing System (GEOS) modeling system suggests that fluxes of CO2 are very consistent with observations, while those of CH4 have some regional and seasonal biases, and that CO comparison is complicated by transport errors.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
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The Global Carbon Budget 2021 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
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).
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.
Cited articles
Bloom, A. A., Bowman, K. W., Lee, M., Turner, A. J., Schroeder, R., Worden, J. R., Weidner, R., McDonald, K. C., and Jacob, D. J.: A global wetland methane emissions and uncertainty dataset for atmospheric chemical transport models (WetCHARTs version 1.0), Geosci. Model Dev., 10, 2141–2156, https://doi.org/10.5194/gmd-10-2141-2017, 2017.
Brandt, A. R., Heath, G. A., Kort, E. A., O'Sullivan, F., Pétron, G., Jordaan, S. M., Tans, P., Wilcox, J., Gopstein, A. M., Arent, D., and Wofsy, S.: Methane leaks from North American natural gas systems, Science, 343, 733–735, https://doi.org/10.1126/science.1247045, 2014.
Cary, I.: EPA Phase II Aggregate Site Report Cost-Effective Directed Inspection and Maintenance Control Opportunities at Five Gas Processing Plants and Upstream Gatllering C0111pressor Stations and Well Sites, https://www.epa.gov/sites/default/files/2016-08/documents/clearstone_ii_03_2006.pdf (last access: 18 August 2026), 2006.
Copernicus Sentinel-5P (processed by ESA): TROPOMI Level 2 Methane Total Column products. Version 02, European Space Agency [data set], https://doi.org/10.5270/S5P-3lcdqiv, 2021.
Crippa, M., Guizzardi, D., Solazzo, E., Muntean, M., Schaaf, E., Monforti-Ferrario, F., Banja, M., Olivier, J. G. J., Grassi, G., Rossi, S., and Vignati, E.: GHG emissions of all world countries – 2021 Report, EUR 30831 EN, Publications Office of the European Union, Luxembourg, ISBN 978-92-76-41547-3, https://doi.org/10.2760/173513, JRC126363, 2021.
Cusworth, D. H., Duren, R. M., Thorpe, A. K., Olson-Duvall, W., Heckler, J., Chapman, J. W., Eastwood, M. L., Helmlinger, M. C., Green, R. O., Asner, G. P. and Dennison, P. E.: Intermittency of large methane emitters in the Permian Basin, Environ. Sci. Technol. Lett., 8, 567–573, https://doi.org/10.1021/acs.estlett.1c00173, 2021.
Carbon Mapper: Product Guide: Data Definition & Specification; Carbon Mapper: Pasadena, CA, USA, https://carbonmapper.org/articles/product-guide (last access: 18 August 2026), 2025,
Carbon Mapper: L4A-Plume Emissions; Carbon Mapper, Pasadena, CA, USA, https://data.carbonmapper.org/ (last access: 18 August 2026), 2026.
Duren, R. M., Thorpe, A. K., Foster, K. T., Rafiq, T., Hopkins, F.M., Yadav, V., Bue, B. D., Thompson, D. R., Conley, S., Colombi, N. K., and Frankenberg, C.: California's methane super-emitters, Nature, 575, 180–184, https://doi.org/10.1038/s41586-019-1720-3, 2019.
Duren, R., Cusworth, D., Ayasse, A., Howell, K., Diamond, A., Scarpelli, T., Kim, J., O'neill, K., Lai-Norling, J., Thorpe, A., Zandbergen, S. R., Shaw, L., Keremedjiev, M., Guido, J., Giuliano, P., Goldstein, M., Nallapu, R., Barentsen, G., Thompson, D. R., Roth, K., Jensen, D., Eastwood, M., Reuland, F., Adams, T., Brandt, A., Kort, E. A., Mason, J., and Green, R. O.: The Carbon Mapper emissions monitoring system, Atmos. Meas. Tech., 18, 6933–6958, https://doi.org/10.5194/amt-18-6933-2025, 2025.
East, J. D., Jacob, D. J., Jervis, D., Balasus, N., Estrada, L. A., Hancock, S. E., Sulprizio, M. P., Thomas, J., Wang, X., Chen, Z., and Varon, D. J.: Worldwide inference of national methane emissions by inversion of satellite observations with UNFCCC prior estimates, Nat. Commun., 16, p. 11004, https://doi.org/10.1038/s41467-025-67122-8, 2025.
Etiope, G., Ciotoli, G., Schwietzke, S., and Schoell, M.: Gridded maps of geological methane emissions and their isotopic signature, Earth Syst. Sci. Data, 11, 1–22, https://doi.org/10.5194/essd-11-1-2019, 2019.
Fung, I., John, J., Lerner, J., Matthews, E., Prather, M., Steele, L. P., and Fraser, P. J.: Three-dimensional model synthesis of the global methane cycle, J. Geophys. Res.-Atmos., 96, 13033–13065, https://doi.org/10.1029/91JD01247, 1991.
He, M., Jacob, D. J., Estrada, L. A., Varon, D. J., Sulprizio, M., Balasus, N., East, J. D., Penn, E., Pendergrass, D. C., Chen, Z., and Mooring, T. A.: Attributing 2019–2024 methane growth using TROPOMI satellite observations, Sci. Adv., 12, p. eadz9007, https://doi.org/10.1126/sciadv.adz9007, 2026.
He, Z., Gao, L., Liang, M., and Zeng, Z.-C.: A survey of methane point source emissions from coal mines in Shanxi province of China using AHSI on board Gaofen-5B, Atmos. Meas. Tech., 17, 2937–2956, https://doi.org/10.5194/amt-17-2937-2024, 2024.
Henze, D. K., Hakami, A., and Seinfeld, J. H.: Development of the adjoint of GEOS-Chem, Atmos. Chem. Phys., 7, 2413–2433, https://doi.org/10.5194/acp-7-2413-2007, 2007.
Huang, X., Yang, J., Wang, W., and Liu, Z.: Mapping 10 m global impervious surface area (GISA-10 m) using multi-source geospatial data , Earth Syst. Sci. Data, 14, 3649–3672, https://doi.org/10.5194/essd-14-3649-2022, 2022.
Irakulis-Loitxate, I., Guanter, L., Maasakkers, J. D., Zavala-Araiza, D., and Aben, I.: Satellites detect abatable super-emissions in one of the world's largest methane hotspot regions, Environ. Sci. Technol., 56, 2143–2152, https://doi.org/10.1021/acs.est.1c04873, 2022.
Jackson, R. B., Saunois, M., Martinez, A., Canadell, J. G., Yu, X., Li, M., Poulter, B., Raymond, P. A., Regnier, P., Ciais, P., and Davis, S. J.: Human activities now fuel two-thirds of global methane emissions, Environ. Res. Lett., 19, p.101002, https://doi.org/10.1088/1748-9326/ad6463, 2024.
Jacob, D. J., Varon, D. J., Cusworth, D. H., Dennison, P. E., Frankenberg, C., Gautam, R., Guanter, L., Kelley, J., McKeever, J., Ott, L. E., Poulter, B., Qu, Z., Thorpe, A. K., Worden, J. R., and Duren, R. M.: Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane, Atmos. Chem. Phys., 22, 9617–9646, https://doi.org/10.5194/acp-22-9617-2022, 2022.
Janssens-Maenhout, G., Pagliari, V., Guizzardi, D. and Muntean, M.: Global emission inventories in the emission database for global atmospheric research (EDGAR)–Manual (I). Gridding: EDGAR emissions distribution on global gridmaps, Publications Office of the European Union, Luxembourg, 775, https://publications.jrc.ec.europa.eu/repository/bitstream/JRC78261/edgarv4_manual_i_gridding_pubsy_final.pdf (last access: 18 August 2026), 2013.
Jervis, D., McKeever, J., Durak, B. O. A., Sloan, J. J., Gains, D., Varon, D. J., Ramier, A., Strupler, M., and Tarrant, E.: The GHGSat-D imaging spectrometer, Atmos. Meas. Tech., 14, 2127–2140, https://doi.org/10.5194/amt-14-2127-2021, 2021.
Lehner, B., Anand, M., Fluet-Chouinard, E., Tan, F., Aires, F., Allen, G. H., Bousquet, P., Canadell, J. G., Davidson, N., Ding, M., Finlayson, C. M., Gumbricht, T., Hilarides, L., Hugelius, G., Jackson, R. B., Korver, M. C., Liu, L., McIntyre, P. B., Nagy, S., Olefeldt, D., Pavelsky, T. M., Pekel, J.-F., Poulter, B., Prigent, C., Wang, J., Worthington, T. A., Yamazaki, D., Zhang, X., and Thieme, M.: Mapping the world's inland surface waters: an upgrade to the Global Lakes and Wetlands Database (GLWD v2), Earth Syst. Sci. Data, 17, 2277–2329, https://doi.org/10.5194/essd-17-2277-2025, 2025.
Lorente, A., Borsdorff, T., Butz, A., Hasekamp, O., aan de Brugh, J., Schneider, A., Wu, L., Hase, F., Kivi, R., Wunch, D., Pollard, D. F., Shiomi, K., Deutscher, N. M., Velazco, V. A., Roehl, C. M., Wennberg, P. O., Warneke, T., and Landgraf, J.: Methane retrieved from TROPOMI: improvement of the data product and validation of the first 2 years of measurements, Atmos. Meas. Tech., 14, 665–684, https://doi.org/10.5194/amt-14-665-2021, 2021.
Lin, H., Jacob, D. J., Lundgren, E. W., Sulprizio, M. P., Keller, C. A., Fritz, T. M., Eastham, S. D., Emmons, L. K., Campbell, P. C., Baker, B., Saylor, R. D., and Montuoro, R.: Harmonized Emissions Component (HEMCO) 3.0 as a versatile emissions component for atmospheric models: application in the GEOS-Chem, NASA GEOS, WRF-GC, CESM2, NOAA GEFS-Aerosol, and NOAA UFS models, Geosci. Model Dev., 14, 5487–5506, https://doi.org/10.5194/gmd-14-5487-2021, 2021.
McLinden, C. A., Griffin, D., Davis, Z., Hempel, C., Smith, J., Sioris, C., Nassar, R., Moeini, O., Legault-Ouellet, E., and Malo, A.; An independent evaluation of GHGSat methane emissions: Performance assessment, J. Geophys. Res.-Atmos., 129, p. e2023JD039906, https://doi.org/10.1029/2023JD039906, 2024.
Naus, S., Maasakkers, J. D., Gautam, R., Omara, M., Stikker, R., Veenstra, A. K., Nathan, B., Irakulis-Loitxate, I., Guanter, L., Pandey, S., and Girard, M.: Assessing the relative importance of satellite-detected methane superemitters in quantifying total emissions for oil and gas production areas in Algeria, Environ. Sci. Technol., 57, 19545–19556, https://doi.org/10.1021/acs.est.3c04746, 2023.
Omara, M., Gautam, R., O'Brien, M. A., Himmelberger, A., Franco, A., Meisenhelder, K., Hauser, G., Lyon, D. R., Chulakadabba, A., Miller, C. C., Franklin, J., Wofsy, S. C., and Hamburg, S. P.: Developing a spatially explicit global oil and gas infrastructure database for characterizing methane emission sources at high resolution, Earth Syst. Sci. Data, 15, 3761–3790, https://doi.org/10.5194/essd-15-3761-2023, 2023.
Pekel, J. F., Cottam, A., Gorelick, N., and Belward, A. S.: High-resolution mapping of global surface water and its long-term changes, Nature, 540, 418–422, https://doi.org/10.1038/nature20584, 2016.
R Core Team: R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, https://www.R-project.org/ (last access: 18 August 2026), 2021.
Reuland, F., Puthuparambil, S., Kumble, S., Kirk, T., Muralidharan, R., Rabbani, M., Ayandele, E., Diaz, K., Wang, R., Owens, L., and Gordon, D.: Oil and gas, version 1: oil and gas production and refining, the Rocky Mountain Institute (RMI), Boulder, Colorado, USA, Climate TRACE Emissions Inventory [data set], https://climatetrace.org (last access: 9 September 2024), 2024.
Rosentreter, J. A., Borges, A. V., Deemer, B. R., Holgerson, M. A., Liu, S., Song, C., Melack, J., Raymond, P. A., Duarte, C. M., Allen, G. H., and Olefeldt, D.: Half of global methane emissions come from highly variable aquatic ecosystem sources, Nat. Geosci., 14, 225–230, https://doi.org/10.1038/s41561-021-00715-2, 2021.
Rößger, N., Sachs, T., Wille, C., Boike, J., and Kutzbach, L.: Seasonal increase of methane emissions linked to warming in Siberian tundra, Nat. Clim. Change, 12, 1031–1036, https://doi.org/10.1038/s41558-022-01512-4, 2022.
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.
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.
Scarpelli, T. R., Roy, E., Jacob, D. J., Sulprizio, M. P., Tate, R. D., and Cusworth, D. H.: Using new geospatial data and 2020 fossil fuel methane emissions for the Global Fuel Exploitation Inventory (GFEI) v3, Earth Syst. Sci. Data, 17, 7019–7033, https://doi.org/10.5194/essd-17-7019-2025, 2025.
Schuit, B. J., Maasakkers, J. D., Bijl, P., Mahapatra, G., van den Berg, A.-W., Pandey, S., Lorente, A., Borsdorff, T., Houweling, S., Varon, D. J., McKeever, J., Jervis, D., Girard, M., Irakulis-Loitxate, I., Gorroño, J., Guanter, L., Cusworth, D. H., and Aben, I.: Automated detection and monitoring of methane super-emitters using satellite data, Atmos. Chem. Phys., 23, 9071–9098, https://doi.org/10.5194/acp-23-9071-2023, 2023.
Shindell, D., Sadavarte, P., Aben, I., Bredariol, T. D. O., Dreyfus, G., Höglund-Isaksson, L., Poulter, B., Saunois, M., Schmidt, G. A., Szopa, S., and Rentz, K.: The methane imperative, Front. Sci., 2, p. 1349770, https://doi.org/10.3389/fsci.2024.1349770, 2024.
Shen, L., Jacob, D. J., Gautam, R., Omara, M., Scarpelli, T. R., Lorente, A., Zavala-Araiza, D., Lu, X., Chen, Z., and Lin, J.: National quantifications of methane emissions from fuel exploitation using high resolution inversions of satellite observations, Nat. Commun., 14, p. 4948, https://doi.org/10.1038/s41467-023-40671-6, 2023.
Sheng, Y., Smith, L. C., MacDonald, G. M., Kremenetski, K. V., Frey, K. E., Velichko, A. A., Lee, M., Beilman, D. W., and Dubinin, P.: A high-resolution GIS-based inventory of the west Siberian peat carbon pool, Global Biogeochem. Cy., 18, https://doi.org/10.1029/2003GB002190, 2004.
Sherwin, E. D., El Abbadi, S. H., Burdeau, P. M., Zhang, Z., Chen, Z., Rutherford, J. S., Chen, Y., and Brandt, A. R.: Single-blind test of nine methane-sensing satellite systems from three continents, Atmos. Meas. Tech., 17, 765–782, https://doi.org/10.5194/amt-17-765-2024, 2024.
Serikova, S., Pokrovsky, O. S., Laudon, H., Krickov, I. V., Lim, A. G., Manasypov, R. M., and Karlsson, J.: High carbon emissions from thermokarst lakes of Western Siberia, Nat. Commun., 10, p. 1552 https://doi.org/10.1038/s41467-019-09592-1, 2019.
Solazzo, E., Crippa, M., Guizzardi, D., Muntean, M., Choulga, M., and Janssens-Maenhout, G.: Uncertainties in the Emissions Database for Global Atmospheric Research (EDGAR) emission inventory of greenhouse gases, Atmos. Chem. Phys., 21, 5655–5683, https://doi.org/10.5194/acp-21-5655-2021, 2021.
Spiess, A.: propagate: Propagation of Uncertainty, R package version 1.0-6, https://CRAN.R-project.org/package=propagate (last access: 18 August 2026), 2018.
Suslov, N. I., Kryukov, V. A., Markova, V. M., and Churashev, V. N.: June. Energy sector of Russia and Siberia: problems and prospects, Journal of Physics: Conference Series (Vol. 1261, No. 1, p. 012035), IOP Publishing, https://doi.org/10.1088/1742-6596/1261/1/012035, 2019,
Thorpe, A. K., Green, R. O., Thompson, D. R., Brodrick, P. G., Chapman, J. W., Elder, C. D., Irakulis-Loitxate, I., Cusworth, D. H., Ayasse, A. K., Duren, R. M., and Frankenberg, C.: Attribution of individual methane and carbon dioxide emission sources using EMIT observations from space, Sci. Adv., 9, p. eadh2391, https://doi.org/10.1126/sciadv.adh2391, 2023.
Varon, D. J., Jacob, D. J., McKeever, J., Jervis, D., Durak, B. O. A., Xia, Y., and Huang, Y.: Quantifying methane point sources from fine-scale satellite observations of atmospheric methane plumes, Atmos. Meas. Tech., 11, 5673–5686, https://doi.org/10.5194/amt-11-5673-2018, 2018.
Varon, D. J., Jacob, D. J., Sulprizio, M., Estrada, L. A., Downs, W. B., Shen, L., Hancock, S. E., Nesser, H., Qu, Z., Penn, E., Chen, Z., Lu, X., Lorente, A., Tewari, A., and Randles, C. A.: Integrated Methane Inversion (IMI 1.0): a user-friendly, cloud-based facility for inferring high-resolution methane emissions from TROPOMI satellite observations, Geosci. Model Dev., 15, 5787–5805, https://doi.org/10.5194/gmd-15-5787-2022, 2022a.
Varon, D. J., Laestrada, W. D., and Jiawei, Z.: geoschem/integrated_methane_inversion: imi 1.0.0-beta.2 release (imi-1.0.0-beta.2), Zenodo [code], https://doi.org/10.5281/zenodo.6578547, 2022b.
Zhang, Y., Gautam, R., Pandey, S., Omara, M., Maasakkers, J. D., Sadavarte, P., Lyon, D., Nesser, H., Sulprizio, M. P., Varon, D. J., and Zhang, R.: Quantifying methane emissions from the largest oil-producing basin in the United States from space, Sci. Adv., 6, p. eaaz5120, https://doi.org/10.1126/sciadv.aaz5120, 2020.
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.
Zhang, Z., Poulter, B., Melton, J. R., Riley, W. J., Allen, G. H., Beerling, D. J., Bousquet, P., Canadell, J. G., Fluet-Chouinard, E., Ciais, P., Gedney, N., Hopcroft, P. O., Ito, A., Jackson, R. B., Jain, A. K., Jensen, K., Joos, F., Kleinen, T., Knox, S. H., Li, T., Li, X., Liu, X., McDonald, K., McNicol, G., Miller, P. A., Müller, J., Patra, P. K., Peng, C., Peng, S., Qin, Z., Riggs, R. M., Saunois, M., Sun, Q., Tian, H., Xu, X., Yao, Y., Xi, Y., Zhang, W., Zhu, Q., Zhu, Q., and Zhuang, Q.: Ensemble estimates of global wetland methane emissions over 2000–2020, Biogeosciences, 22, 305–321, https://doi.org/10.5194/bg-22-305-2025, 2025.
Short summary
CH4 observations from space are an essential component for improving our estimates of CH4 emissions from fossil fuels and natural sources. We utilized GHGSat, a CH4 plume mapping satellite constellation, to update the fossil fuel emission inventory in the Western Siberian Lowlands to understand how including plume observations in models changes emissions estimates. Our approach resulted in a reduction in CH4 emissions attributed to wetlands.
CH4 observations from space are an essential component for improving our estimates of CH4...
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