A strong mitigation scenario maintains climate neutrality of northern peatlands

Chunjing Qiu*, Philippe Ciais, Dan Zhu, Bertrand Guenet, Jinfeng Chang, Nitin Chaudhary, Thomas Kleinen, Jurek Müller, Yi Xi, Wenxin Zhang, Ashley Ballantyne, Simon C. Brewer, Victor Brovkin, Dan J. Charman, Adrian Gustafson, Angela V. Gallego-Sala, Thomas Gasser, Joseph Holden, Fortunat Joos, Min Jung KwonRonny Lauerwald, Paul A. Miller, Shushi Peng, Susan Page, Benjamin Smith, Benjamin D. Stocker, A. Britta K. Sannel, Elodie Salmon, Guy Schurgers, Narasinha J. Shurpali, David Wårlind

*Corresponding author for this work

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    Abstract

    Northern peatlands store 300–600 Pg C, of which approximately half are underlain by permafrost. Climate warming and, in some regions, soil drying from enhanced evaporation are progressively threatening this large carbon stock. Here, we assess future CO2 and CH4 fluxes from northern peatlands using five land surface models that explicitly include representation of peatland processes. Under Representative Concentration Pathways (RCP) 2.6, northern peatlands are projected to remain a net sink of CO2 and climate neutral for the next three centuries. A shift to a net CO2 source and a substantial increase in CH4 emissions are projected under RCP8.5, which could exacerbate global warming by 0.21°C (range, 0.09–0.49°C) by the year 2300. The true warming impact of peatlands might be higher owing to processes not simulated by the models and direct anthropogenic disturbance. Our study highlights the importance of understanding how future warming might trigger high carbon losses from northern peatlands.

    Original languageEnglish
    JournalOne Earth
    Volume5
    Issue number1
    Pages (from-to)86-97
    Number of pages12
    ISSN2590-3330
    DOIs
    Publication statusPublished - 2022

    Bibliographical note

    Funding Information:
    This work was supported by the European Research Council Synergy grant (SyG-2013-610028 IMBALANCE-P) and the French State Aid managed by the ANR under the ?Investissements d'avenir? programme (ANR-16-CONV-0003_Cland). ORCHIDEE-PEAT performed simulations using HPC resources from GENCI-TGCC (2020-A0070106328). A.V.G.-S. was funded by the Natural Environment Research Council (NERC standard grant no. NE/I012915/1 and no. NE/S001166/1). W.Z. acknowledges funding from the Swedish Research Council FORMAS 2016-01201 and Swedish National Space Agency 209/19. N.C. acknowledges funding by the Nunataryuk (EU grant agreement no. 773421) and the Swedish Research Council FORMAS (contract no. 2019-01151). LPJ-GUESS_dyn simulations were performed on the supercomputing facilities at the University of Oslo, Norway, and on the Aurora and Tetralith resources of the Swedish National Infrastructure for Computing (SNIC) at the Lund University Centre for Scientific and Technical Computing (Lunarc), project no. 2021/2-61 and no. 2021/2-28, and Link?ping University, project no. snic2020/5-563. A.G. P.A.M. W.Z. B.S. D.W. and N.C. acknowledge support from 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. P.A.M. and D.W. received financial support from the H2020 CRESCENDO project (grant agreement no. 641816). LPJ-GUESS simulations were enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC) at LUNARC partially funded by the Swedish Research Council through grant agreement no. 2018-05973. J.M. and F.J. acknowledge financial support by the Swiss National Science Foundation (no. 200020_172476 and no. 200020_200511) and funding from the European Union's Horizon 2020 research and innovation program under grant agreement no. 820989 (project COMFORT) and no. 821003 (project 4C). The work reflects only the authors? views; the European Commission and their executive agency are not responsible for any use that may be made of the information the work contains. B.G. received funding from the European Union's Horizon 2020 research and innovation program under grant agreement no. 641816 (CRESCENDO) and no. 821003 (4C project). B.D.S was funded by the Swiss National Science Foundation grant no. PCEFP2_181115. T.K. acknowledges support from the German Federal Ministry for Education and Research (BMBF) through the PalMod programme (grant no. 01LP1507B and no. 01LP1921A). LPJ-MPI experiments were performed at the German Climate Computing Centre (DKRZ), using resources from the Max Planck Institute for Meteorology. N.J.S. acknowledges financial support from Academy of Finland (no. 296887 and no. 334422) and the Finnish Ministry of Agriculture and Forestry (no. VN/28562/2020). J.C. acknowledged support from the Fundamental Research Funds for the Central Universities (no. 2021QNA6005). D.Z. acknowledges funding from the National Natural Science Foundation of China (grant no. 42101090 and no. 41988101). W.Z and G.S. acknowledge support from the Danish National Research Foundation (DNRF100). C.Q. P.C. D.Z. and B.G. designed the research; C.Q. and P.C. drafted the manuscript; J.C. prepared the climate forcing for ORCHIDEE-PEAT and computed estimates of global and Northern Hemisphere CO2 emissions from ISIMIP2b terrestrial biosphere models; C.Q. N.C. T.K. X.Y.L. J.M. Y.X. and W.Z. performed model simulations; A.V.G.-S. and S.C.B. provided estimates for future peat carbon sink from Gallego-Sala et al.15; all authors contributed to the interpretation of the results and draft revision. The authors declare no competing interests.

    Funding Information:
    This work was supported by the European Research Council Synergy grant ( SyG-2013-610028 IMBALANCE-P) and the French State Aid managed by the ANR under the “Investissements d’avenir” programme ( ANR-16-CONV-0003_Cland ). ORCHIDEE-PEAT performed simulations using HPC resources from GENCI-TGCC ( 2020-A0070106328 ). A.V.G.-S. was funded by the Natural Environment Research Council ( NERC standard grant no. NE/I012915/1 and no. NE/S001166/1 ). W.Z. acknowledges funding from the Swedish Research Council FORMAS 2016-01201 and Swedish National Space Agency 209/19 . N.C. acknowledges funding by the Nunataryuk ( EU grant agreement no. 773421 ) and the Swedish Research Council FORMAS (contract no. 2019-01151 ). LPJ-GUESS_dyn simulations were performed on the supercomputing facilities at the University of Oslo, Norway, and on the Aurora and Tetralith resources of the Swedish National Infrastructure for Computing (SNIC) at the Lund University Centre for Scientific and Technical Computing (Lunarc), project no. 2021/2-61 and no. 2021/2-28 , and Linköping University , project no. snic2020/5-563 . A.G., P.A.M., W.Z., B.S., D.W., and N.C. acknowledge support from 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. P.A.M. and D.W. received financial support from the H2020 CRESCENDO project (grant agreement no. 641816 ). LPJ-GUESS simulations were enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC) at LUNARC partially funded by the Swedish Research Council through grant agreement no. 2018-05973 . J.M. and F.J. acknowledge financial support by the Swiss National Science Foundation (no. 200020_172476 and no. 200020_200511 ) and funding from the European Union’s Horizon 2020 research and innovation program under grant agreement no. 820989 (project COMFORT) and no. 821003 (project 4C). The work reflects only the authors’ views; the European Commission and their executive agency are not responsible for any use that may be made of the information the work contains. B.G. received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement no. 641816 (CRESCENDO) and no. 821003 (4C project). B.D.S was funded by the Swiss National Science Foundation grant no. PCEFP2_181115 . T.K. acknowledges support from the German Federal Ministry for Education and Research ( BMBF ) through the PalMod programme (grant no. 01LP1507B and no. 01LP1921A ). LPJ-MPI experiments were performed at the German Climate Computing Centre (DKRZ), using resources from the Max Planck Institute for Meteorology. N.J.S. acknowledges financial support from Academy of Finland (no. 296887 and no. 334422 ) and the Finnish Ministry of Agriculture and Forestry (no. VN/28562/2020 ). J.C. acknowledged support from the Fundamental Research Funds for the Central Universities (no. 2021QNA6005 ). D.Z. acknowledges funding from the National Natural Science Foundation of China (grant no. 42101090 and no. 41988101 ). W.Z and G.S. acknowledge support from the Danish National Research Foundation ( DNRF100 ).

    Publisher Copyright:
    © 2021 The Authors

    Keywords

    • carbon dioxide
    • carbon-cycle feedback
    • land surface models
    • long-term climate change
    • methane
    • peatland
    • permafrost

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