Abstract
Due to ongoing climate change, methane (CH4) emissions from vegetated wetlands are projected to increase during the 21st century, challenging climate mitigation efforts aimed at limiting global warming. However, despite reports of rising emission trends, a comprehensive evaluation and attribution of recent changes remains limited. Here we assessed global wetland CH4 emissions from 2000-2020 based on an ensemble of 16 process-based wetland models. Our results estimated global average wetland CH4 emissions at 158 ± 24 (mean ± 1σ) Tg CH4 yr-1 over a total annual average wetland area of 8.0 ± 2.0×106 km2 for the period 2010-2020, with an average increase of 6-7 Tg CH4 yr-1 in 2010-2019 compared to the average for 2000-2009. The increases in the four latitudinal bands of 90-30° S, 30° S-30° N, 30-60° N, and 60-90° N were 0.1-0.2, 3.6-3.7, 1.8-2.4, and 0.6-0.8 Tg CH4 yr-1, respectively, over the 2 decades. The modeled CH4 sensitivities to temperature show reasonable consistency with eddy-covariance-based measurements from 34 sites. Rising temperature was the primary driver of the increase, while precipitation and rising atmospheric CO2 concentrations played secondary roles with high levels of uncertainty. These modeled results suggest that climate change is driving increased wetland CH4 emissions and that direct and sustained measurements are needed to monitor developments.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 305-321 |
| Number of pages | 17 |
| Journal | Biogeosciences |
| Volume | 22 |
| Issue number | 1 |
| Early online date | Jan 15 2025 |
| DOIs | |
| State | Published - Jan 15 2025 |
ASJC Scopus subject areas
- Ecology, Evolution, Behavior and Systematics
- Earth-Surface Processes
Online availability
- 10.5194/bg-22-305-2025License: CC BY
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In: Biogeosciences, Vol. 22, No. 1, 15.01.2025, p. 305-321.
Research output: Contribution to journal › Article › peer-review
}
TY - JOUR
T1 - Ensemble estimates of global wetland methane emissions over 2000-2020
AU - Zhang, Zhen
AU - Poulter, Benjamin
AU - Melton, Joe R.
AU - Riley, William J.
AU - Allen, George H.
AU - Beerling, David J.
AU - Bousquet, Philippe
AU - Canadell, Josep G.
AU - Fluet-Chouinard, Etienne
AU - Ciais, Philippe
AU - Gedney, Nicola
AU - Hopcroft, Peter O.
AU - Ito, Akihiko
AU - Jackson, Robert B.
AU - Jain, Atul K.
AU - Jensen, Katherine
AU - Joos, Fortunat
AU - Kleinen, Thomas
AU - Knox, Sara H.
AU - Li, Tingting
AU - Li, Xin
AU - Liu, Xiangyu
AU - Mcdonald, Kyle
AU - Mcnicol, Gavin
AU - Miller, Paul A.
AU - Müller, Jurek
AU - Patra, Prabir K.
AU - Peng, Changhui
AU - Peng, Shushi
AU - Qin, Zhangcai
AU - Riggs, Ryan M.
AU - Saunois, Marielle
AU - Sun, Qing
AU - Tian, Hanqin
AU - Xu, Xiaoming
AU - Yao, Yuanzhi
AU - Xi, Yi
AU - Zhang, Wenxin
AU - Zhu, Qing
AU - Zhu, Qiuan
AU - Zhuang, Qianlai
N1 - This paper is the result of a collaborative international effort under the umbrella of the Global Carbon Project, a project of Future Earth, and a research partner of the World Climate Research Programme. Joe R. Melton thanks Jade Skye for her assistance in running and processing the CLASSIC model simulations. Zhen Zhang acknowledges support from the National Natural Science Foundation of China Basic Science Center for Tibetan Plateau Earth System project. Yi Xi and Shushi Peng were funded by NSFC (41830643, 41722101). Thomas Kleinen acknowledges support from the German Federal Ministry of Education and Research ((BMBF) grant no. 01LP1921A). Akihiko Ito and Prabir Patra were partly supported by the Arctic Challenge for Sustainability II (ArCS-II) project (grant no. JPMXD1420318865), funded by Japan's Ministry of Education, Culture, Sports, Science and Technology (MEXT). Xiangyu Liu and Qianlai Zhuang are supported by a NASA project (NNX17AK20G). Qiuan Zhu and Changhui Peng are supported by the Second Tibetan Plateau Scientific Expedition (2019QZKK0304). Jurek M\u00FCller, Qing Sun, and Fortunat Joos were supported by the Swiss National Science Foundation (#200020-200511). Qing Zhu and William Riley were supported by the Reducing Uncertainties in Biogeochemical Interactions through Synthesis and Computation (RUBISCO) Scientific Focus Area and Energy Exascale Earth System Modeling Project, which are sponsored by the Earth and Environmental Systems Modeling (EESM) program under the Office of Biological and Environmental Research of the U.S. Department of Energy Office of Science. Yuanzhi Yao and Hanqin Tian are funded in part by an NSF program (award number: #1903722) and the NASA CMS Program (award number: NX14AO73G). Tingting Li was supported by the National Key Scientific and Technological Infrastructure project \"Earth System Science Numerical Simulator Facility\" (EarthLab) and the Open Research Program of the International Research Center of Big Data for Sustainable Development Goals (grant no. CBAS2023ORP02). Peter Hopcroft was supported by a Birmingham Fellowship and the University of Birmingham's BlueBEAR high-performance computing (HPC) service. Wenxin Zhang acknowledges support from the LUNARC computation project LU 2021/2-114 and the Swedish Research Council (Vetenskapsr\u00E5det), starting grant 2020-05338. Wenxin Zhang and Paul A. Miller acknowledge this study as a contribution to the strategic research areas Modeling the Regional and Global Earth System (MERGE) and Biodiversity and Ecosystem Services in a Changing Climate (BECC) at Lund University. Robert B. Jackson acknowledges support from the United Nations Environment Programme (UNEP) to Stanford University DTIE21-EN3143. Nicola Gedney was supported by the Newton Fund through the Met Office Climate Science for Service Partnership Brazil (CSSP Brazil). Atul K. Jain and Xiaoming Xu were supported by the US National Science Foundation (NSF-831361857) and would like to acknowledge the high-performance computing support from Cheyenne (https:// www.cisl.ucar.edu/ncar-supercomputing-history/cheyenne, last access: 15 January 2025, Cheyenne HPE, 2016), provided by NCAR's Computational and Information Systems Laboratory, sponsored by the National Science Foundation. Philippe Ciais acknowledges support from the space Agency Climate Change Initiative (ESA CCI) RECCAP2 project (grant no. ESRIN/4000123002/18/I-NB). Josep G. Canadell acknowledges the support of the Australian National Environmental Climate Science Program - Climate Systems hub. Gavin McNicol acknowledges support from the NASA CMS program (award number: NNH20ZDA001N). Zhen Zhang acknowledges support from the National Natural Science Foundation of China Basic Science Center for Tibetan Plateau Earth System project. Yi Xi and Shushi Peng were funded by NSFC (41830643, 41722101). Thomas Kleinen acknowledges support from the German Federal Ministry of Education and Research ((BMBF) grant no. 01LP1921A). Akihiko Ito and Prabir Patra were partly supported by the Arctic Challenge for Sustainability II (ArCS-II) project (grant no. JPMXD1420318865), funded by Japan's Ministry of Education, Culture, Sports, Science and Technology (MEXT). Xiangyu Liu and Qianlai Zhuang are supported by a NASA project (NNX17AK20G). Qiuan Zhu and Changhui Peng are supported by the Second Tibetan Plateau Scientific Expedition (2019QZKK0304). Jurek M\u00FCller, Qing Sun, and Fortunat Joos were supported by the Swiss National Science Foundation (#200020_200511). Qing Zhu and William Riley were supported by the Reducing Uncertainties in Biogeochemical Interactions through Synthesis and Computation (RUBISCO) Scientific Focus Area and Energy Exascale Earth System Modeling Project, which are sponsored by the Earth and Environmental Systems Modeling (EESM) program under the Office of Biological and Environmental Research of the U.S. Department of Energy Office of Science. Yuanzhi Yao and Hanqin Tian are funded in part by an NSF program (award number: #1903722) and the NASA CMS Program (award number: NX14AO73G). Tingting Li was supported by the National Key Scientific and Technological Infrastructure project \u201CEarth System Science Numerical Simulator Facility\u201D (EarthLab) and the Open Research Program of the International Research Center of Big Data for Sustainable Development Goals (grant no. CBAS2023ORP02). Peter Hopcroft was supported by a Birmingham Fellowship and the University of Birmingham's BlueBEAR high-performance computing (HPC) service. Wenxin Zhang acknowledges support from the LUNARC computation project LU 2021/2-114 and the Swedish Research Council (Vetenskapsr\u00E5det), starting grant 2020-05338. Wenxin Zhang and Paul A. Miller acknowledge this study as a contribution to the strategic research areas Modeling the Regional and Global Earth System (MERGE) and Biodiversity and Ecosystem Services in a Changing Climate (BECC) at Lund University. Robert B. Jackson acknowledges support from the United Nations Environment Programme (UNEP) to Stanford University DTIE21-EN3143. Nicola Gedney was supported by the Newton Fund through the Met Office Climate Science for Service Partnership Brazil (CSSP Brazil). Atul K. Jain and Xiaoming Xu were supported by the US National Science Foundation (NSF-831361857) and would like to acknowledge the high-performance computing support from Cheyenne ( https://www.cisl.ucar.edu/ncar-supercomputing-history/cheyenne , last access: 15 January 2025, Cheyenne HPE, 2016), provided by NCAR\u2019s Computational and Information Systems Laboratory, sponsored by the National Science Foundation. Philippe Ciais acknowledges support from the space Agency Climate Change Initiative (ESA CCI) RECCAP2 project (grant no. ESRIN/4000123002/18/I-NB). Josep G. Canadell acknowledges the support of the Australian National Environmental Climate Science Program \u2013 Climate Systems hub. Gavin McNicol acknowledges support from the NASA CMS program (award number: NNH20ZDA001N).
PY - 2025/1/15
Y1 - 2025/1/15
N2 - Due to ongoing climate change, methane (CH4) emissions from vegetated wetlands are projected to increase during the 21st century, challenging climate mitigation efforts aimed at limiting global warming. However, despite reports of rising emission trends, a comprehensive evaluation and attribution of recent changes remains limited. Here we assessed global wetland CH4 emissions from 2000-2020 based on an ensemble of 16 process-based wetland models. Our results estimated global average wetland CH4 emissions at 158 ± 24 (mean ± 1σ) Tg CH4 yr-1 over a total annual average wetland area of 8.0 ± 2.0×106 km2 for the period 2010-2020, with an average increase of 6-7 Tg CH4 yr-1 in 2010-2019 compared to the average for 2000-2009. The increases in the four latitudinal bands of 90-30° S, 30° S-30° N, 30-60° N, and 60-90° N were 0.1-0.2, 3.6-3.7, 1.8-2.4, and 0.6-0.8 Tg CH4 yr-1, respectively, over the 2 decades. The modeled CH4 sensitivities to temperature show reasonable consistency with eddy-covariance-based measurements from 34 sites. Rising temperature was the primary driver of the increase, while precipitation and rising atmospheric CO2 concentrations played secondary roles with high levels of uncertainty. These modeled results suggest that climate change is driving increased wetland CH4 emissions and that direct and sustained measurements are needed to monitor developments.
AB - Due to ongoing climate change, methane (CH4) emissions from vegetated wetlands are projected to increase during the 21st century, challenging climate mitigation efforts aimed at limiting global warming. However, despite reports of rising emission trends, a comprehensive evaluation and attribution of recent changes remains limited. Here we assessed global wetland CH4 emissions from 2000-2020 based on an ensemble of 16 process-based wetland models. Our results estimated global average wetland CH4 emissions at 158 ± 24 (mean ± 1σ) Tg CH4 yr-1 over a total annual average wetland area of 8.0 ± 2.0×106 km2 for the period 2010-2020, with an average increase of 6-7 Tg CH4 yr-1 in 2010-2019 compared to the average for 2000-2009. The increases in the four latitudinal bands of 90-30° S, 30° S-30° N, 30-60° N, and 60-90° N were 0.1-0.2, 3.6-3.7, 1.8-2.4, and 0.6-0.8 Tg CH4 yr-1, respectively, over the 2 decades. The modeled CH4 sensitivities to temperature show reasonable consistency with eddy-covariance-based measurements from 34 sites. Rising temperature was the primary driver of the increase, while precipitation and rising atmospheric CO2 concentrations played secondary roles with high levels of uncertainty. These modeled results suggest that climate change is driving increased wetland CH4 emissions and that direct and sustained measurements are needed to monitor developments.
UR - http://www.scopus.com/inward/record.url?scp=85216370223&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85216370223&partnerID=8YFLogxK
U2 - 10.5194/bg-22-305-2025
DO - 10.5194/bg-22-305-2025
M3 - Article
AN - SCOPUS:85216370223
SN - 1726-4170
VL - 22
SP - 305
EP - 321
JO - Biogeosciences
JF - Biogeosciences
IS - 1
ER -