Global Methane Budget 2000–2020
<p>Understanding and quantifying the global methane (CH<span class="inline-formula"><sub>4</sub></span>) budget is important for assessing realistic pathways to mitigate climate change. CH<span class="inline-formula"><sub>4</sub><...
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Copernicus Publications
2025-05-01
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| author | M. Saunois A. Martinez B. Poulter Z. Zhang Z. Zhang P. A. Raymond P. Regnier J. G. Canadell R. B. Jackson P. K. Patra P. K. Patra P. Bousquet P. Ciais E. J. Dlugokencky X. Lan X. Lan G. H. Allen D. Bastviken D. J. Beerling D. A. Belikov D. R. Blake S. Castaldi M. Crippa B. R. Deemer F. Dennison G. Etiope G. Etiope N. Gedney L. Höglund-Isaksson M. A. Holgerson P. O. Hopcroft G. Hugelius A. Ito A. K. Jain R. Janardanan M. S. Johnson T. Kleinen P. B. Krummel R. Lauerwald T. Li X. Liu K. C. McDonald J. R. Melton J. Mühle J. Müller F. Murguia-Flores Y. Niwa Y. Niwa S. Noce S. Pan R. J. Parker C. Peng C. Peng M. Ramonet W. J. Riley G. Rocher-Ros J. A. Rosentreter M. Sasakawa A. Segers S. J. Smith S. J. Smith E. H. Stanley J. Thanwerdas J. Thanwerdas H. Tian A. Tsuruta F. N. Tubiello T. S. Weber G. R. van der Werf D. E. J. Worthy Y. Xi Y. Yoshida W. Zhang W. Zhang B. Zheng B. Zheng Q. Zhu Q. Zhu Q. Zhuang |
| author_facet | M. Saunois A. Martinez B. Poulter Z. Zhang Z. Zhang P. A. Raymond P. Regnier J. G. Canadell R. B. Jackson P. K. Patra P. K. Patra P. Bousquet P. Ciais E. J. Dlugokencky X. Lan X. Lan G. H. Allen D. Bastviken D. J. Beerling D. A. Belikov D. R. Blake S. Castaldi M. Crippa B. R. Deemer F. Dennison G. Etiope G. Etiope N. Gedney L. Höglund-Isaksson M. A. Holgerson P. O. Hopcroft G. Hugelius A. Ito A. K. Jain R. Janardanan M. S. Johnson T. Kleinen P. B. Krummel R. Lauerwald T. Li X. Liu K. C. McDonald J. R. Melton J. Mühle J. Müller F. Murguia-Flores Y. Niwa Y. Niwa S. Noce S. Pan R. J. Parker C. Peng C. Peng M. Ramonet W. J. Riley G. Rocher-Ros J. A. Rosentreter M. Sasakawa A. Segers S. J. Smith S. J. Smith E. H. Stanley J. Thanwerdas J. Thanwerdas H. Tian A. Tsuruta F. N. Tubiello T. S. Weber G. R. van der Werf D. E. J. Worthy Y. Xi Y. Yoshida W. Zhang W. Zhang B. Zheng B. Zheng Q. Zhu Q. Zhu Q. Zhuang |
| author_sort | M. Saunois |
| collection | DOAJ |
| description | <p>Understanding and quantifying the global methane (CH<span class="inline-formula"><sub>4</sub></span>) budget is important for assessing realistic pathways to mitigate climate change. CH<span class="inline-formula"><sub>4</sub></span> is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO<span class="inline-formula"><sub>2</sub></span>), and both emissions and atmospheric concentrations of CH<span class="inline-formula"><sub>4</sub></span> have continued to increase since 2007 after a temporary pause. The relative importance of CH<span class="inline-formula"><sub>4</sub></span> emissions compared to those of CO<span class="inline-formula"><sub>2</sub></span> for temperature change is related to its shorter atmospheric lifetime, stronger radiative effect, and acceleration in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in quantifying the factors responsible for the observed atmospheric growth rate arise from diverse, geographically overlapping CH<span class="inline-formula"><sub>4</sub></span> sources and from the uncertain magnitude and temporal change in the destruction of CH<span class="inline-formula"><sub>4</sub></span> by short-lived and highly variable hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to improve, synthesise, and update the global CH<span class="inline-formula"><sub>4</sub></span> budget regularly and to stimulate new research on the methane cycle. Following Saunois et al. (2016, 2020), we present here the third version of the living review paper dedicated to the decadal CH<span class="inline-formula"><sub>4</sub></span> budget, integrating results of top-down CH<span class="inline-formula"><sub>4</sub></span> emission estimates (based on in situ and Greenhouse Gases Observing SATellite (GOSAT) atmospheric observations and an ensemble of atmospheric inverse-model results) and bottom-up estimates (based on process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). We present a budget for the most recent 2010–2019 calendar decade (the latest period for which full data sets are available), for the previous decade of 2000–2009 and for the year 2020.</p>
<p>The revision of the bottom-up budget in this 2025 edition benefits from important progress in estimating inland freshwater emissions, with better counting of emissions from lakes and ponds, reservoirs, and streams and rivers. This budget also reduces double counting across freshwater and wetland emissions and, for the first time, includes an estimate of the potential double counting that may exist (average of 23 Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span>). Bottom-up approaches show that the combined wetland and inland freshwater emissions average 248 [159–369] Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> for the 2010–2019 decade. Natural fluxes are perturbed by human activities through climate, eutrophication, and land use. In this budget, we also estimate, for the first time, this anthropogenic component contributing to wetland and inland freshwater emissions. Newly available gridded products also allowed us to derive an almost complete latitudinal and regional budget based on bottom-up approaches.</p>
<p>For the 2010–2019 decade, global CH<span class="inline-formula"><sub>4</sub></span> emissions are estimated by atmospheric inversions (top-down) to be 575 Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> (range 553–586, corresponding to the minimum and maximum estimates of the model ensemble). Of this amount, 369 Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> or <span class="inline-formula">∼</span> 65 % is attributed to direct anthropogenic sources in the fossil, agriculture, and waste and anthropogenic biomass burning (range 350–391 Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> or 63 %–68 %). For the 2000–2009 period, the atmospheric inversions give a slightly lower total emission than for 2010–2019, by 32 Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> (range 9–40). The 2020 emission rate is the highest of the period and reaches 608 Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> (range 581–627), which is 12 % higher than the average emissions in the 2000s. Since 2012, global direct anthropogenic CH<span class="inline-formula"><sub>4</sub></span> emission trends have been tracking scenarios that assume no or minimal climate mitigation policies proposed by the Intergovernmental Panel on Climate Change (shared socio-economic pathways SSP5 and SSP3). Bottom-up methods suggest 16 % (94 Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span>) larger global emissions (669 Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span>, range 512–849) than top-down inversion methods for the 2010–2019 period. The discrepancy between the bottom-up and the top-down budgets has been greatly reduced compared to the previous differences (167 and 156 Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> in<span id="page1876"/> Saunois et al. (2016, 2020) respectively), and for the first time uncertainties in bottom-up and top-down budgets overlap. Although differences have been reduced between inversions and bottom-up, the most important source of uncertainty in the global CH<span class="inline-formula"><sub>4</sub></span> budget is still attributable to natural emissions, especially those from wetlands and inland freshwaters.</p>
<p>The tropospheric loss of methane, as the main contributor to methane lifetime, has been estimated at 563 [510–663] Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> based on chemistry–climate models. These values are slightly larger than for 2000–2009 due to the impact of the rise in atmospheric methane and remaining large uncertainty (<span class="inline-formula">∼</span> 25 %). The total sink of CH<span class="inline-formula"><sub>4</sub></span> is estimated at 633 [507–796] Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> by the bottom-up approaches and at 554 [550–567] Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> by top-down approaches. However, most of the top-down models use the same OH distribution, which introduces less uncertainty to the global budget than is likely justified.</p>
<p>For 2010–2019, agriculture and waste contributed an estimated 228 [213–242] Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> in the top-down budget and 211 [195–231] Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> in the bottom-up budget. Fossil fuel emissions contributed 115 [100–124] Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> in the top-down budget and 120 [117–125] Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> in the bottom-up budget. Biomass and biofuel burning contributed 27 [26–27] Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> in the top-down budget and 28 [21–39] Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> in the bottom-up budget.</p>
<p>We identify five major priorities for improving the CH<span class="inline-formula"><sub>4</sub></span> budget: (i) producing a global, high-resolution map of water-saturated soils and inundated areas emitting CH<span class="inline-formula"><sub>4</sub></span> based on a robust classification of different types of emitting ecosystems; (ii) further development of process-based models for inland-water emissions; (iii) intensification of CH<span class="inline-formula"><sub>4</sub></span> observations at local (e.g. FLUXNET-CH<span class="inline-formula"><sub>4</sub></span> measurements, urban-scale monitoring, satellite imagery with pointing capabilities) to regional scales (surface networks and global remote sensing measurements from satellites) to constrain both bottom-up models and atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) integration of 3D variational inversion systems using isotopic and/or co-emitted species such as ethane as well as information in the bottom-up inventories on anthropogenic super-emitters detected by remote sensing (mainly oil and gas sector but also coal, agriculture, and landfills) to improve source partitioning.</p>
<p>The data presented here can be downloaded from <a href="https://doi.org/10.18160/GKQ9-2RHT">https://doi.org/10.18160/GKQ9-2RHT</a> (Martinez et al., 2024).</p> |
| format | Article |
| id | doaj-art-2bae5c40cc674459b9a99a1091c931ae |
| institution | OA Journals |
| issn | 1866-3508 1866-3516 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Earth System Science Data |
| spelling | doaj-art-2bae5c40cc674459b9a99a1091c931ae2025-08-20T02:28:18ZengCopernicus PublicationsEarth System Science Data1866-35081866-35162025-05-01171873195810.5194/essd-17-1873-2025Global Methane Budget 2000–2020M. Saunois0A. Martinez1B. Poulter2Z. Zhang3Z. Zhang4P. A. Raymond5P. Regnier6J. G. Canadell7R. B. Jackson8P. K. Patra9P. K. Patra10P. Bousquet11P. Ciais12E. J. Dlugokencky13X. Lan14X. Lan15G. H. Allen16D. Bastviken17D. J. Beerling18D. A. Belikov19D. R. Blake20S. Castaldi21M. Crippa22B. R. Deemer23F. Dennison24G. Etiope25G. Etiope26N. Gedney27L. Höglund-Isaksson28M. A. Holgerson29P. O. Hopcroft30G. Hugelius31A. Ito32A. K. Jain33R. Janardanan34M. S. Johnson35T. Kleinen36P. B. Krummel37R. Lauerwald38T. Li39X. Liu40K. C. McDonald41J. R. Melton42J. Mühle43J. Müller44F. Murguia-Flores45Y. Niwa46Y. Niwa47S. Noce48S. Pan49R. J. Parker50C. Peng51C. Peng52M. Ramonet53W. J. Riley54G. Rocher-Ros55J. A. Rosentreter56M. Sasakawa57A. Segers58S. J. Smith59S. J. Smith60E. H. Stanley61J. Thanwerdas62J. Thanwerdas63H. Tian64A. Tsuruta65F. N. Tubiello66T. S. Weber67G. R. van der Werf68D. E. J. Worthy69Y. Xi70Y. Yoshida71W. Zhang72W. Zhang73B. Zheng74B. Zheng75Q. Zhu76Q. Zhu77Q. Zhuang78Laboratoire des Sciences du Climat et de l'Environnement, LSCE-IPSL (CEA-CNRS-UVSQ), Université Paris-Saclay, 91191 Gif-sur-Yvette, FranceLaboratoire des Sciences du Climat et de l'Environnement, LSCE-IPSL (CEA-CNRS-UVSQ), Université Paris-Saclay, 91191 Gif-sur-Yvette, FranceNASA Goddard Space Flight Center, Biospheric Science Laboratory, Greenbelt, MD 20771, USAState Key Laboratory of Tibetan Plateau Earth System, Environment and Resource (TPESER), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, ChinaEarth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740, USAYale School of the Environment, Yale University, New Haven, CT 06511, USADepartment Geoscience, Environment & Society (BGEOSYS), Université Libre de Bruxelles, 1050 Brussels, BelgiumGlobal Carbon Project, CSIRO Environment, Canberra, ACT 2601, AustraliaDepartment of Earth System Science, Woods Institute for the Environment, and Precourt Institute for Energy, Stanford University, Stanford, CA 94305-2210, USAResearch Institute for Global Change, JAMSTEC, 3173-25 Showa-machi, Kanazawa, Yokohama, 236-0001, JapanResearch Institute for Humanity and Nature, Kyoto 6038047, JapanLaboratoire des Sciences du Climat et de l'Environnement, LSCE-IPSL (CEA-CNRS-UVSQ), Université Paris-Saclay, 91191 Gif-sur-Yvette, FranceLaboratoire des Sciences du Climat et de l'Environnement, LSCE-IPSL (CEA-CNRS-UVSQ), Université Paris-Saclay, 91191 Gif-sur-Yvette, FranceNational Oceanic and Atmospheric Administration Global Monitoring Laboratory (NOAA/GML), 325 Broadway R/GML, Boulder, CO 80305, USANational Oceanic and Atmospheric Administration Global Monitoring Laboratory (NOAA/GML), 325 Broadway R/GML, Boulder, CO 80305, USACooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado Boulder, Boulder, CO 80309, USADepartment of Geosciences, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USADepartment of Thematic Studies – Environmental Change, Linköping University, 581 83 Linköping, SwedenSchool of Biosciences, University of Sheffield, Sheffield, S10 2TN, UKCenter for Environmental Remote Sensing, Chiba University, Chiba, 263-8522, JapanDepartment of Chemistry, University of California Irvine, 570 Rowland Hall, Irvine, CA 92697, USADipartimento di Scienze Ambientali, Biologiche e Farmaceutiche, Università degli Studi della Campania Luigi Vanvitelli, via Vivaldi 43, 81100 Caserta, ItalyEuropean Commission, Joint Research Centre (JRC), Ispra, ItalyU.S. Geological Survey, Southwest Biological Science Center, Flagstaff, AZ, USACSIRO Environment, Aspendale, Victoria 3195, AustraliaIstituto Nazionale di Geofisica e Vulcanologia, Sezione Roma 2, via V. Murata 605, 00143 Rome, ItalyFaculty of Environmental Science and Engineering, Babes-Bolyai University, Cluj-Napoca, RomaniaMet Office Hadley Centre, Joint Centre for Hydrometeorological Research, Maclean Building, Wallingford, OX10 8BB, UKPollution Management Group (PM), International Institute for Applied Systems Analysis (IIASA), 2361 Laxenburg, AustriaDepartment of Ecology & Evolutionary Biology, Cornell University, Ithaca, NY, USASchool of Geography, Earth & Environmental Sciences, University of Birmingham, Birmingham B15 2TT, UKDepartment of Physical Geography and Bolin Centre for Climate Research, Stockholm University, 106 91 Stockholm, SwedenGraduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo, JapanDepartment of Climate, Meteorology and Atmospheric Sciences (CLiMAS), University of Illinois, Urbana-Champaign, Urbana, IL 61801, USAEarth System Division, National Institute for Environmental Studies (NIES), Onogawa 16-2, Tsukuba, Ibaraki 305-8506, JapanEarth Science Division, NASA Ames Research Center, Moffett Field, CA, USAMax Planck Institute for Meteorology, Bundesstraße 53, 20146 Hamburg, GermanyCSIRO Environment, Aspendale, Victoria 3195, AustraliaUniversité Paris-Saclay, INRAE, AgroParisTech, UMR EcoSys, Palaiseau, FranceLAPC, Institute of Atmospheric Physics, Chinese Academy of Sciences, 100029 Beijing, ChinaDepartment of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, IN, USADepartment of Earth and Atmospheric Sciences, City College of New York, City University of New York, NY, USAClimate Research Division, Environment and Climate Change Canada, Victoria, BC, V8W 2Y2, CanadaScripps Institution of Oceanography, University of California San Diego, La Jolla, CA 92037, USAClimate and Environmental Physics, Physics Institute and Oeschger Centre for Climate Change Research, University of Bern, Sidlerstr. 5, 3012 Bern, SwitzerlandInstituto de Investigaciones en Ecología y Sustentabilidad, Universidad Nacional Autónoma de México, Morelia, MexicoEarth System Division, National Institute for Environmental Studies (NIES), Onogawa 16-2, Tsukuba, Ibaraki 305-8506, JapanDepartment of Climate and Geochemistry Research, Meteorological Research Institute (MRI), Nagamine 1-1, Tsukuba, Ibaraki 305-0052, JapanCMCC Foundation – Euro-Mediterranean Center on Climate Change, Via Igino Garbini, 51, 01100 Viterbo VT, ItalyDepartment of Engineering and Environmental Studies Program, Boston College, Chestnut Hill, MA 02467, USANational Centre for Earth Observation, School of Physics and Astronomy, University of Leicester, Leicester, LE1 7RH, UKDepartment of Biology Sciences, Institute of Environment Science, University of Quebec at Montreal, Montréal, QC H3C 3P8, CanadaSchool of Geographic Sciences, Hunan Normal University, 410081 Changsha, ChinaLaboratoire des Sciences du Climat et de l'Environnement, LSCE-IPSL (CEA-CNRS-UVSQ), Université Paris-Saclay, 91191 Gif-sur-Yvette, FranceClimate and Ecosystem Sciences Division, Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA 94720, USADepartment of Forest Ecology and Management, Swedish University of Agricultural Sciences, 90183 Umeå, SwedenFaculty of Science and Engineering, Southern Cross University, Lismore, NSW 2480, AustraliaEarth System Division, National Institute for Environmental Studies (NIES), Onogawa 16-2, Tsukuba, Ibaraki 305-8506, JapanTNO, Department of Climate Air & Sustainability, P.O. Box 80015, NL-3508-TA, Utrecht, the NetherlandsJoint Global Change Research Institute, Pacific Northwest National Lab, College Park, MD, USACenter for Global Sustainability, University of Maryland, College Park, MD, USACenter for Limnology, University of Wisconsin–Madison, Madison, WI, USAEmpa, Swiss Federal Laboratories for Materials Science and Technology, Dübendorf, Switzerlandformerly at: Laboratoire des Sciences du Climat et de l'Environnement, LSCE-IPSL (CEA-CNRS-UVSQ), Université Paris-Saclay, 91191 Gif-sur-Yvette, FranceCenter for Earth System Science and Global Sustainability, Schiller Institute for Integrated Science and Society, Department of Earth and Environmental Sciences, Boston College, Chestnut Hill, MA 02467, USAFinnish Meteorological Institute, P.O. Box 503, 00101, Helsinki, FinlandStatistics Division, Food and Agriculture Organization of the United Nations (FAO), Viale delle Terme di Caracalla, Rome 00153, ItalyDepartment of Earth and Environmental Sciences, University of Rochester, Rochester, NY 14627, USAMeteorology and Air Quality Group, Wageningen University and Research, Wageningen, the NetherlandsEnvironment and Climate Change Canada, 4905, Dufferin Street, Toronto, CanadaLaboratoire des Sciences du Climat et de l'Environnement, LSCE-IPSL (CEA-CNRS-UVSQ), Université Paris-Saclay, 91191 Gif-sur-Yvette, FranceEarth System Division, National Institute for Environmental Studies (NIES), Onogawa 16-2, Tsukuba, Ibaraki 305-8506, JapanSchool of Geographical and Earth Sciences, University of Glasgow, Glasgow, G12 8QQ, UKDepartment of Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12, 223 62, Lund, SwedenInstitute of Environment and Ecology, Tsinghua Shenzhen International Graduate School, Tsinghua University, 518055 Shenzhen, ChinaState Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, 100084 Beijing, ChinaClimate and Ecosystem Sciences Division, Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA 94720, USACollege of Geography and Remote Sensing, Hohai University, 210098 Nanjing, ChinaDepartment of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, IN, USA<p>Understanding and quantifying the global methane (CH<span class="inline-formula"><sub>4</sub></span>) budget is important for assessing realistic pathways to mitigate climate change. CH<span class="inline-formula"><sub>4</sub></span> is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO<span class="inline-formula"><sub>2</sub></span>), and both emissions and atmospheric concentrations of CH<span class="inline-formula"><sub>4</sub></span> have continued to increase since 2007 after a temporary pause. The relative importance of CH<span class="inline-formula"><sub>4</sub></span> emissions compared to those of CO<span class="inline-formula"><sub>2</sub></span> for temperature change is related to its shorter atmospheric lifetime, stronger radiative effect, and acceleration in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in quantifying the factors responsible for the observed atmospheric growth rate arise from diverse, geographically overlapping CH<span class="inline-formula"><sub>4</sub></span> sources and from the uncertain magnitude and temporal change in the destruction of CH<span class="inline-formula"><sub>4</sub></span> by short-lived and highly variable hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to improve, synthesise, and update the global CH<span class="inline-formula"><sub>4</sub></span> budget regularly and to stimulate new research on the methane cycle. Following Saunois et al. (2016, 2020), we present here the third version of the living review paper dedicated to the decadal CH<span class="inline-formula"><sub>4</sub></span> budget, integrating results of top-down CH<span class="inline-formula"><sub>4</sub></span> emission estimates (based on in situ and Greenhouse Gases Observing SATellite (GOSAT) atmospheric observations and an ensemble of atmospheric inverse-model results) and bottom-up estimates (based on process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). We present a budget for the most recent 2010–2019 calendar decade (the latest period for which full data sets are available), for the previous decade of 2000–2009 and for the year 2020.</p> <p>The revision of the bottom-up budget in this 2025 edition benefits from important progress in estimating inland freshwater emissions, with better counting of emissions from lakes and ponds, reservoirs, and streams and rivers. This budget also reduces double counting across freshwater and wetland emissions and, for the first time, includes an estimate of the potential double counting that may exist (average of 23 Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span>). Bottom-up approaches show that the combined wetland and inland freshwater emissions average 248 [159–369] Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> for the 2010–2019 decade. Natural fluxes are perturbed by human activities through climate, eutrophication, and land use. In this budget, we also estimate, for the first time, this anthropogenic component contributing to wetland and inland freshwater emissions. Newly available gridded products also allowed us to derive an almost complete latitudinal and regional budget based on bottom-up approaches.</p> <p>For the 2010–2019 decade, global CH<span class="inline-formula"><sub>4</sub></span> emissions are estimated by atmospheric inversions (top-down) to be 575 Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> (range 553–586, corresponding to the minimum and maximum estimates of the model ensemble). Of this amount, 369 Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> or <span class="inline-formula">∼</span> 65 % is attributed to direct anthropogenic sources in the fossil, agriculture, and waste and anthropogenic biomass burning (range 350–391 Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> or 63 %–68 %). For the 2000–2009 period, the atmospheric inversions give a slightly lower total emission than for 2010–2019, by 32 Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> (range 9–40). The 2020 emission rate is the highest of the period and reaches 608 Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> (range 581–627), which is 12 % higher than the average emissions in the 2000s. Since 2012, global direct anthropogenic CH<span class="inline-formula"><sub>4</sub></span> emission trends have been tracking scenarios that assume no or minimal climate mitigation policies proposed by the Intergovernmental Panel on Climate Change (shared socio-economic pathways SSP5 and SSP3). Bottom-up methods suggest 16 % (94 Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span>) larger global emissions (669 Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span>, range 512–849) than top-down inversion methods for the 2010–2019 period. The discrepancy between the bottom-up and the top-down budgets has been greatly reduced compared to the previous differences (167 and 156 Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> in<span id="page1876"/> Saunois et al. (2016, 2020) respectively), and for the first time uncertainties in bottom-up and top-down budgets overlap. Although differences have been reduced between inversions and bottom-up, the most important source of uncertainty in the global CH<span class="inline-formula"><sub>4</sub></span> budget is still attributable to natural emissions, especially those from wetlands and inland freshwaters.</p> <p>The tropospheric loss of methane, as the main contributor to methane lifetime, has been estimated at 563 [510–663] Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> based on chemistry–climate models. These values are slightly larger than for 2000–2009 due to the impact of the rise in atmospheric methane and remaining large uncertainty (<span class="inline-formula">∼</span> 25 %). The total sink of CH<span class="inline-formula"><sub>4</sub></span> is estimated at 633 [507–796] Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> by the bottom-up approaches and at 554 [550–567] Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> by top-down approaches. However, most of the top-down models use the same OH distribution, which introduces less uncertainty to the global budget than is likely justified.</p> <p>For 2010–2019, agriculture and waste contributed an estimated 228 [213–242] Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> in the top-down budget and 211 [195–231] Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> in the bottom-up budget. Fossil fuel emissions contributed 115 [100–124] Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> in the top-down budget and 120 [117–125] Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> in the bottom-up budget. Biomass and biofuel burning contributed 27 [26–27] Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> in the top-down budget and 28 [21–39] Tg CH<span class="inline-formula"><sub>4</sub></span> yr<span class="inline-formula"><sup>−1</sup></span> in the bottom-up budget.</p> <p>We identify five major priorities for improving the CH<span class="inline-formula"><sub>4</sub></span> budget: (i) producing a global, high-resolution map of water-saturated soils and inundated areas emitting CH<span class="inline-formula"><sub>4</sub></span> based on a robust classification of different types of emitting ecosystems; (ii) further development of process-based models for inland-water emissions; (iii) intensification of CH<span class="inline-formula"><sub>4</sub></span> observations at local (e.g. FLUXNET-CH<span class="inline-formula"><sub>4</sub></span> measurements, urban-scale monitoring, satellite imagery with pointing capabilities) to regional scales (surface networks and global remote sensing measurements from satellites) to constrain both bottom-up models and atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) integration of 3D variational inversion systems using isotopic and/or co-emitted species such as ethane as well as information in the bottom-up inventories on anthropogenic super-emitters detected by remote sensing (mainly oil and gas sector but also coal, agriculture, and landfills) to improve source partitioning.</p> <p>The data presented here can be downloaded from <a href="https://doi.org/10.18160/GKQ9-2RHT">https://doi.org/10.18160/GKQ9-2RHT</a> (Martinez et al., 2024).</p>https://essd.copernicus.org/articles/17/1873/2025/essd-17-1873-2025.pdf |
| spellingShingle | M. Saunois A. Martinez B. Poulter Z. Zhang Z. Zhang P. A. Raymond P. Regnier J. G. Canadell R. B. Jackson P. K. Patra P. K. Patra P. Bousquet P. Ciais E. J. Dlugokencky X. Lan X. Lan G. H. Allen D. Bastviken D. J. Beerling D. A. Belikov D. R. Blake S. Castaldi M. Crippa B. R. Deemer F. Dennison G. Etiope G. Etiope N. Gedney L. Höglund-Isaksson M. A. Holgerson P. O. Hopcroft G. Hugelius A. Ito A. K. Jain R. Janardanan M. S. Johnson T. Kleinen P. B. Krummel R. Lauerwald T. Li X. Liu K. C. McDonald J. R. Melton J. Mühle J. Müller F. Murguia-Flores Y. Niwa Y. Niwa S. Noce S. Pan R. J. Parker C. Peng C. Peng M. Ramonet W. J. Riley G. Rocher-Ros J. A. Rosentreter M. Sasakawa A. Segers S. J. Smith S. J. Smith E. H. Stanley J. Thanwerdas J. Thanwerdas H. Tian A. Tsuruta F. N. Tubiello T. S. Weber G. R. van der Werf D. E. J. Worthy Y. Xi Y. Yoshida W. Zhang W. Zhang B. Zheng B. Zheng Q. Zhu Q. Zhu Q. Zhuang Global Methane Budget 2000–2020 Earth System Science Data |
| title | Global Methane Budget 2000–2020 |
| title_full | Global Methane Budget 2000–2020 |
| title_fullStr | Global Methane Budget 2000–2020 |
| title_full_unstemmed | Global Methane Budget 2000–2020 |
| title_short | Global Methane Budget 2000–2020 |
| title_sort | global methane budget 2000 2020 |
| url | https://essd.copernicus.org/articles/17/1873/2025/essd-17-1873-2025.pdf |
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