Compatible Fossil Fuel CO2 Emissions in the CMIP6 Earth System Models’ Historical and Shared Socioeconomic Pathway Experiments of the Twenty-First Century

Spencer K. Liddicoat aMet Office Hadley Centre, Exeter, United Kingdom

Search for other papers by Spencer K. Liddicoat in
Current site
Google Scholar
PubMed
Close
,
Andy J. Wiltshire aMet Office Hadley Centre, Exeter, United Kingdom

Search for other papers by Andy J. Wiltshire in
Current site
Google Scholar
PubMed
Close
,
Chris D. Jones aMet Office Hadley Centre, Exeter, United Kingdom

Search for other papers by Chris D. Jones in
Current site
Google Scholar
PubMed
Close
,
Vivek K. Arora bCanadian Centre for Climate Modelling and Analysis, Environment Canada, University of Victoria, Victoria, British Columbia, Canada

Search for other papers by Vivek K. Arora in
Current site
Google Scholar
PubMed
Close
,
Victor Brovkin cMax Planck Institute for Meteorology, Hamburg, Germany
dCEN, Universität Hamburg, Hamburg, Germany

Search for other papers by Victor Brovkin in
Current site
Google Scholar
PubMed
Close
,
Patricia Cadule eIPSL, CNRS, Sorbonne Université, Paris, France

Search for other papers by Patricia Cadule in
Current site
Google Scholar
PubMed
Close
,
Tomohiro Hajima fResearch Institute for Global Change, Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan

Search for other papers by Tomohiro Hajima in
Current site
Google Scholar
PubMed
Close
,
David M. Lawrence gClimate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, Colorado

Search for other papers by David M. Lawrence in
Current site
Google Scholar
PubMed
Close
,
Julia Pongratz cMax Planck Institute for Meteorology, Hamburg, Germany
hLudwig-Maximilian University, Munich, Germany

Search for other papers by Julia Pongratz in
Current site
Google Scholar
PubMed
Close
,
Jörg Schwinger iNORCE Norwegian Research Centre, Bjerknes Centre for Climate Research, Bergen, Norway

Search for other papers by Jörg Schwinger in
Current site
Google Scholar
PubMed
Close
,
Roland Séférian jCNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France

Search for other papers by Roland Séférian in
Current site
Google Scholar
PubMed
Close
,
Jerry F. Tjiputra iNORCE Norwegian Research Centre, Bjerknes Centre for Climate Research, Bergen, Norway

Search for other papers by Jerry F. Tjiputra in
Current site
Google Scholar
PubMed
Close
, and
Tilo Ziehn kCSIRO Oceans and Atmosphere, Aspendale, Victoria, Australia

Search for other papers by Tilo Ziehn in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

We present the compatible CO2 emissions from fossil fuel (FF) burning and industry, calculated from the historical and Shared Socioeconomic Pathway (SSP) experiments of nine Earth system models (ESMs) participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). The multimodel mean FF emissions match the historical record well and are close to the data-based estimate of cumulative emissions (394 ± 59 GtC vs 400 ± 20 GtC, respectively). Only two models fall inside the observed uncertainty range; while two exceed the upper bound, five fall slightly below the lower bound, due primarily to the plateau in CO2 concentration in the 1940s. The ESMs’ diagnosed FF emission rates are consistent with those generated by the integrated assessment models (IAMs) from which the SSPs’ CO2 concentration pathways were constructed; the simpler IAMs’ emissions lie within the ESMs’ spread for seven of the eight SSP experiments, the other being only marginally lower, providing confidence in the relationship between the IAMs’ FF emission rates and concentration pathways. The ESMs require fossil fuel emissions to reduce to zero and subsequently become negative in SSP1-1.9, SSP1-2.6, SSP4-3.4, and SSP5-3.4over. We also present the ocean and land carbon cycle responses of the ESMs in the historical and SSP scenarios. The models’ ocean carbon cycle responses are in close agreement, but there is considerable spread in their land carbon cycle responses. Land-use and land-cover change emissions have a strong influence over the magnitude of diagnosed fossil fuel emissions, with the suggestion of an inverse relationship between the two.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-19-0991.s1.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Spencer K. Liddicoat, spencer.liddicoat@metoffice.gov.uk

Abstract

We present the compatible CO2 emissions from fossil fuel (FF) burning and industry, calculated from the historical and Shared Socioeconomic Pathway (SSP) experiments of nine Earth system models (ESMs) participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). The multimodel mean FF emissions match the historical record well and are close to the data-based estimate of cumulative emissions (394 ± 59 GtC vs 400 ± 20 GtC, respectively). Only two models fall inside the observed uncertainty range; while two exceed the upper bound, five fall slightly below the lower bound, due primarily to the plateau in CO2 concentration in the 1940s. The ESMs’ diagnosed FF emission rates are consistent with those generated by the integrated assessment models (IAMs) from which the SSPs’ CO2 concentration pathways were constructed; the simpler IAMs’ emissions lie within the ESMs’ spread for seven of the eight SSP experiments, the other being only marginally lower, providing confidence in the relationship between the IAMs’ FF emission rates and concentration pathways. The ESMs require fossil fuel emissions to reduce to zero and subsequently become negative in SSP1-1.9, SSP1-2.6, SSP4-3.4, and SSP5-3.4over. We also present the ocean and land carbon cycle responses of the ESMs in the historical and SSP scenarios. The models’ ocean carbon cycle responses are in close agreement, but there is considerable spread in their land carbon cycle responses. Land-use and land-cover change emissions have a strong influence over the magnitude of diagnosed fossil fuel emissions, with the suggestion of an inverse relationship between the two.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-19-0991.s1.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Spencer K. Liddicoat, spencer.liddicoat@metoffice.gov.uk

Supplementary Materials

    • Supplemental Materials (PDF 1.85 MB)
Save
  • Arora, V. K., and J. F. Scinocca, 2016: Constraining the strength of the terrestrial CO2 fertilization effect in the Canadian Earth System Model version 4.2 (CanESM4.2). Geosci. Model Dev., 9, 23572376, https://doi.org/10.5194/gmd-9-2357-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Arora, V. K., and Coauthors, 2020: Carbon–concentration and carbon–climate feedbacks in CMIP6 models, and their comparison to CMIP5 models. Biogeosciences, 17, 41734222, https://doi.org/10.5194/bg-17-4173-2020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ballantyne, A. P., and Coauthors, 2015: Audit of the global carbon budget: Estimate errors and their impact on uptake uncertainty. Biogeosciences, 12, 25652584, https://doi.org/10.5194/bg-12-2565-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bastos, A., and Coauthors, 2016: Re-evaluating the 1940s CO2 plateau. Biogeosciences, 13, 48774897, https://doi.org/10.5194/bg-13-4877-2016.

  • Bennedsen, M., E. Hillebrand, and S. J. Koopman, 2019: Trend analysis of the airborne fraction and sink rate of anthropogenically released CO2. Biogeosciences, 16, 36513663, https://doi.org/10.5194/bg-16-3651-2019.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Canadell, J. G., and Coauthors, 2007: Contributions to accelerating atmospheric CO2 growth from economic activity, carbon intensity, and efficiency of natural sinks. Proc. Natl. Acad. Sci. USA, 104, 18 86618 870, https://doi.org/10.1073/pnas.0702737104.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ciais, P., and Coauthors, 2013: Carbon and other biogeochemical cycles. Climate Change 2013: The Physical Science Basis, T. F. Stocker et al., Eds., Cambridge University Press, 465–570.

  • Collins, M., and Coauthors, 2013: Long-term climate change: Projections, commitments and irreversibility. Climate Change 2013: The Physical Science Basis, T. F. Stocker et al., Eds., Cambridge University Press, 1029–1136.

  • Collins, W. J., and Coauthors, 2017: Aerchemmip: Quantifying the effects of chemistry and aerosols in CMIP6. Geosci. Model Dev., 10, 585607, https://doi.org/10.5194/gmd-10-585-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dellink, R., J. Chateau, E. Lanzi, and B. Magné, 2017: Long-term economic growth projections in the shared socioeconomic pathways. Global Environ. Change, 42, 200214, https://doi.org/10.1016/j.gloenvcha.2015.06.004.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Denman, K., and Coauthors, 2007: Couplings between changes in the climate system and biogeochemistry. Climate Change 2007: The Physical Science Basis, S. Solomon et al., Eds., Cambridge University Press, 499–587.

  • Etheridge, D. M., L. P. Steele, R. L. Langenfelds, R. J. Francey, J.-M. Barnola, and V. I. Morgan, 1996: Natural and anthropogenic changes in atmospheric CO2 over the last 1000 years from air in Antarctic ice and firn. J. Geophys. Res., 101, 41154128, https://doi.org/10.1029/95JD03410.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Eyring, V., S. Bony, G. A. Meehl, C. A. Senior, B. Stevens, R. J. Stouffer, and K. E. Taylor, 2016: Overview of the coupled model intercomparison project phase 6 (CMIP6) experimental design and organization. Geosci. Model Dev., 9, 19371958, https://doi.org/10.5194/gmd-9-1937-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fisher, R. A., and Coauthors, 2019: Parametric controls on vegetation responses to biogeochemical forcing in the CLM5. J. Adv. Model. Earth Syst., 11, 28792895, https://doi.org/10.1029/2019MS001609.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Friedlingstein, P., and Coauthors, 2006: Climate–carbon cycle feedback analysis: Results from the C4MIP model intercomparison. J. Climate, 19, 33373353, https://doi.org/10.1175/JCLI3800.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Friedlingstein, P., and Coauthors, 2019: Global carbon budget 2019. Earth Syst. Sci. Data, 11, 17831838, https://doi.org/10.5194/essd-11-1783-2019.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gasser, T., G. P. Peters, J. S. Fuglestvedt, W. J. Collins, D. T. Shindell, and P. Ciais, 2017: Accounting for the climate–carbon feedback in emission metrics. Earth Syst. Dyn., 8, 235253, https://doi.org/10.5194/esd-8-235-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gasser, T., L. Crepin, Y. Quilcaille, R. A. Houghton, P. Ciais, and M. Obersteiner, 2020: Historical CO2 emissions from land use and land cover change and their uncertainty. Biogeosciences, 17, 40754101, https://doi.org/10.5194/bg-17-4075-2020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gidden, M. J., and Coauthors, 2019: Global emissions pathways under different socioeconomic scenarios for use in CMIP6: A dataset of harmonized emissions trajectories through the end of the century. Geosci. Model Dev., 12, 14431475, https://doi.org/10.5194/gmd-12-1443-2019.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gilfillan, D., G. Marland, T. Boden, and R. Andres, 2019: Global, regional, and national fossil-fuel CO2 emissions. CDIAC at AppState, accessed 12 May 2020, https://energy.appstate.edu/research/work-areas/cdiac-appstate.

  • Hajima, T., and Coauthors, 2020: Development of the MIROC-ES2L Earth System Model and the evaluation of biogeochemical processes and feedbacks. Geosci. Model Dev., 13, 21972244, https://doi.org/10.5194/gmd-13-2197-2020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hansis, E., S. J. Davis, and J. Pongratz, 2015: Relevance of methodological choices for accounting of land use change carbon fluxes. Global Biogeochem. Cycles, 29, 12301246, https://doi.org/10.1002/2014GB004997.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Haustein, K., M. R. Allen, P. M. Forster, F. E. L. Otto, D. M. Mitchell, H. D. Matthews, and D. J. Frame, 2017: A real-time global warming index. Sci. Rep., 7, 15417, https://doi.org/10.1038/s41598-017-14828-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Houghton, R. A., and A. A. Nassikas, 2017: Global and regional fluxes of carbon from land use and land cover change 1850–2015. Global Biogeochem. Cycles, 31, 456472, https://doi.org/10.1002/2016GB005546.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Houghton, R. A., J. I. House, J. Pongratz, G. R. van der Werf, R. S. DeFries, M. C. Hansen, C. Le Quéré, and N. Ramankutty, 2012: Carbon emissions from land use and land-cover change. Biogeosciences, 9, 51255142, https://doi.org/10.5194/bg-9-5125-2012.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hurtt, G. C., and Coauthors, 2020: Harmonization of global land use change and management for the period 850–2100 (LUH2) for CMIP6. Geosci. Model Dev., 13, 54255464, https://doi.org/10.5194/gmd-13-5425-2020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • IPCC, 2014: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. C. B. Field et al., Eds., Cambridge University Press, 1132 pp., http://www.ipcc.ch/pdf/assessment-report/ar5/wg2/WGIIAR5-PartA_FINAL.pdf.

  • Jiang, L., and B. C. O’Neill, 2017: Global urbanization projections for the shared socioeconomic pathways. Global Environ. Change, 42, 193199, https://doi.org/10.1016/j.gloenvcha.2015.03.008.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jones, C., and Coauthors, 2013: Twenty-first-century compatible CO2 emissions and airborne fraction simulated by CMIP5 Earth system models under four representative concentration pathways. J. Climate, 26, 43984413, https://doi.org/10.1175/JCLI-D-12-00554.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jones, C., and Coauthors, 2016: C4MIP—The Coupled Climate–Carbon Cycle Model Intercomparison Project: Experiments protocol for CMIP6. Geosci. Model Dev., 9, 28532880, https://doi.org/10.5194/gmd-9-2853-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Joos, F., R. Meyer, M. Bruno, and M. Leuenberger, 1999: The variability in the carbon sinks as reconstructed for the last 1000 years. Geophys. Res. Lett., 26, 14371440, https://doi.org/10.1029/1999GL900250.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Keeling, C., T. Whorf, and M. Wahlen, 1995: Interannual extremes in the rate of rise of atmospheric carbon dioxide since 1980. Nature, 375, 666670, https://doi.org/10.1038/375666a0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Knorr, W., 2009: Is the airborne fraction of anthropogenic CO2 emissions increasing? Geophys. Res. Lett., 36, L21710, https://doi.org/10.1029/2009GL040613.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lauvset, S. K., J. Tjiputra, and H. Muri, 2017: Climate engineering and the ocean: Effects on biogeochemistry and primary production. Biogeosciences, 14, 56755691, https://doi.org/10.5194/bg-14-5675-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lawrence, D. M., and Coauthors, 2016: The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6: Rationale and experimental design. Geosci. Model Dev., 9, 29732998, https://doi.org/10.5194/gmd-9-2973-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Le Quéré, C., M. Raupach, and J. Canadell, 2009: Trends in the sources and sinks of carbon dioxide. Nat. Geosci., 2, 831836, https://doi.org/10.1038/ngeo689.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Le Quéré, C., and Coauthors, 2018: Global Carbon Budget 2018. Earth Syst. Sci. Data, 10, 21412194, https://doi.org/10.5194/essd-10-2141-2018.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lombardozzi, D. L., Y. Lu, P. J. Lawrence, D. M. Lawrence, S. Swenson, K. W. Oleson, W. R. Wieder, and E. A. Ainsworth, 2020: Simulating agriculture in the Community Land Model version 5. J. Geophys. Res. Biogeosci., 125, e2019JG005529, https://doi.org/10.1029/2019JG005529.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • MacFarling Meure, C., D. Etheridge, C. Trudinger, P. Steele, R. Langenfelds, T. van Ommen, A. Smith, and J. Elkins, 2006: Law Dome CO2, CH4 and N2O ice core records extended to 2000 years BP. Geophys. Res. Lett., 33, L14810, https://doi.org/10.1029/2006GL026152.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Meinshausen, M., S. C. B. Raper, and T. M. L. Wigley, 2011: Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6—Part 1: Model description and calibration. Atmos. Chem. Phys., 11, 14171456, https://doi.org/10.5194/acp-11-1417-2011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Meinshausen, M., and Coauthors, 2020: The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500. Geosci. Model Dev., 13, 35713605, https://doi.org/10.5194/gmd-13-3571-2020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mercado, L., N. Bellouin, S. Sitch, O. Boucher, C. Huntingford, M. Wild, and P. Cox, 2009: Impact of changes in diffuse radiation on the global land carbon sink. Nature, 458, 10141017, https://doi.org/10.1038/nature07949.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • O’Neill, B. C., and Coauthors, 2016: The scenario model intercomparison project (ScenarioMIP) for CMIP6. Geosci. Model Dev., 9, 34613482, https://doi.org/10.5194/gmd-9-3461-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pongratz, J., C. H. Reick, R. A. Houghton, and J. I. House, 2014: Terminology as a key uncertainty in net land use and land cover change carbon flux estimates. Earth Syst. Dyn., 5, 177195, https://doi.org/10.5194/esd-5-177-2014.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Raupach, M. R., J. G. Canadell, and C. Le Quéré, 2008: Anthropogenic and biophysical contributions to increasing atmospheric CO2 growth rate and airborne fraction. Biogeosciences, 5, 16011613, https://doi.org/10.5194/bg-5-1601-2008.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Raupach, M. R., and Coauthors, 2014: The declining uptake rate of atmospheric CO2 by land and ocean sinks. Biogeosciences, 11, 34533475, https://doi.org/10.5194/bg-11-3453-2014.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rayner, P. J., M. R. Raupach, M. Paget, P. Peylin, and E. Koffi, 2010: A new global gridded data set of CO2 emissions from fossil fuel combustion: Methodology and evaluation. J. Geophys. Res., 115, D19306, https://doi.org/10.1029/2009JD013439.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Riahi, K., and Coauthors, 2017: The shared socioeconomic pathways and their energy, land use, and greenhouse gas emissions implications: An overview. Global Environ. Change, 42, 153168, https://doi.org/10.1016/j.gloenvcha.2016.05.009.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rogelj, J., and Coauthors, 2018: Scenarios towards limiting global mean temperature increase below 1.5°C. Nat. Climate Change, 8, 325332, https://doi.org/10.1038/s41558-018-0091-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rubino, M., and Coauthors, 2013: A revised 1000 year atmospheric δ13C-CO2 record from Law Dome and South Pole, Antarctica. J. Geophys. Res. Atmos., 118, 84828499, https://doi.org/10.1002/jgrd.50668.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Samir, K., and W. Lutz, 2017: The human core of the shared socioeconomic pathways: Population scenarios by age, sex and level of education for all countries to 2100. Global Environ. Change, 42, 181192, https://doi.org/10.1016/j.gloenvcha.2014.06.004.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sitch, S., P. Cox, W. J. Collins, and C. Huntingford, 2007: Indirect radiative forcing of climate change through ozone effects on the land-carbon sink. Nature, 448, 791794, https://doi.org/10.1038/nature06059.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smith, C. J., and Coauthors, 2020: Effective radiative forcing and adjustments in CMIP6 models. Atmos. Chem. Phys., 20, 95919618, https://doi.org/10.5194/acp-20-9591-2020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stocker, T., and Coauthors, 2013: Technical summary. Climate Change 2013: The Physical Science Basis, T. F. Stocker et al., Eds., Cambridge University Press, 33–115.

  • Taylor, K. E., R. J. Stouffer, and G. A. Meehl, 2012: An overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc., 93, 485498, https://doi.org/10.1175/BAMS-D-11-00094.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thornhill, G. D., and Coauthors, 2021: Effective radiative forcing from emissions of reactive gases and aerosols—A multimodel comparison. Atmos. Chem. Phys., 21, 853874, https://doi.org/10.5194/acp-21-853-2021.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tjiputra, J. F., and Coauthors, 2014: Long-term surface pCO2 trends from observations and models. Tellus, 66B, 23083, https://doi.org/10.3402/tellusb.v66.23083.

    • Search Google Scholar
    • Export Citation
  • Tjiputra, J. F., A. Grini, and H. Lee, 2016: Impact of idealized future stratospheric aerosol injection on the large-scale ocean and land carbon cycles. J. Geophys. Res. Biogeosci., 121, 227, https://doi.org/10.1002/2015JG003045.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • UNFCCC, 2015: Adoption of the Paris Agreement. United Nations, 32 pp., https://unfccc.int/resource/docs/2015/cop21/eng/l09r01.pdf.

  • Unger, N., X. Yue, and K. L. Harper, 2017: Aerosol climate change effects on land ecosystem services. Faraday Discuss., 200, 121142, https://doi.org/10.1039/C7FD00033B.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vuuren, D., and Coauthors, 2011: The representative concentration pathways: An overview. Climatic Change, 109, 531, https://doi.org/10.1007/s10584-011-0148-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wei, X., M. Shao, W. Gale, and L. Li, 2014: Global pattern of soil carbon losses due to the conversion of forests to agricultural land. Sci. Rep., 4, 4062, https://doi.org/10.1038/srep04062.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yue, C., P. Ciais, S. Luyssaert, W. Li, M. Mcgrath, J. Chang, and S. Peng, 2018: Representing anthropogenic gross land use change, wood harvest, and forest age dynamics in a global vegetation model ORCHIDEE-MICT v8.4.2. Geosci. Model Dev., 11, 409428, https://doi.org/10.5194/gmd-11-409-2018.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, Y., and Coauthors, 2019: Increased global land carbon sink due to aerosol-induced cooling. Global Biogeochem. Cycles, 33, 439457, https://doi.org/10.1029/2018GB006051.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 1599 0 0
Full Text Views 5309 2508 110
PDF Downloads 2600 477 34