Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Critical adjustment of land mitigation pathways for assessing countries’ climate progress

Nature Climate Change volume 11, pages 425–434 (2021)Cite this article

Subjects

Abstract

Mitigation pathways by Integrated Assessment Models (IAMs) describe future emissions that keep global warming below specific temperature limits and are compared with countries’ collective greenhouse gas (GHG) emission reduction pledges. This is needed to assess mitigation progress and inform emission targets under the Paris Agreement. Currently, however, a mismatch of ~5.5 GtCO2 yr−1 exists between the global land-use fluxes estimated with IAMs and from countries’ GHG inventories. Here we present a ‘Rosetta stone’ adjustment to translate IAMs’ land-use mitigation pathways to estimates more comparable with GHG inventories. This does not change the original decarbonization pathways, but reallocates part of the land sink to be consistent with GHG inventories. Adjusted cumulative emissions over the period until net zero for 1.5 or 2 °C limits are reduced by 120–192 GtCO2 relative to the original IAM pathways. These differences should be taken into account to ensure an accurate assessment of progress towards the Paris Agreement.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Global net anthropogenic land CO2 fluxes estimated by global models and reported in NGHGIs.
Fig. 2: Main conceptual inconsistencies between IAMs and NGHGIs in estimating what is considered the anthropogenic land CO2 flux, and proposed solution.
Fig. 3: Inconsistencies between IAMs and NGHGIs in the forest areas that are considered managed, and proposed solution for their reconciliation.
Fig. 4: Implementation of the proposed solutions to reconcile the inconsistencies between IAMs and NGHGIs in the ‘anthropogenic’ forest CO2 flux.
Fig. 5: Adjustment of the IAMs’ anthropogenic land CO2 fluxes to derive NGHGI-comparable estimates.
Fig. 6: Impact of adjusting the IAMs’ land CO2 fluxes to the NGHGI approach on global CO2 fluxes and the GHG mitigation pathways.

Data availability

The vast majority of data used in this study are included in the Supplementary Information (for example, from NGHGIs) or on public websites (for example, the SSP database for IAMs). Any other data that support the findings of this study are available from the corresponding author upon request.

References

  1. IPCC: Summary for Policymakers. In Special Report on Climate Change and Land (eds Shukla, P. R. et al.) (WMO, 2019).

  2. Friedlingstein, P., Sullivan, M. O., Jones, M. W., Andrew, R. & Hauck, J. Global carbon budget 2020. Earth Syst. Sci. Data 12, 3269–3340 (2020).

    Article  Google Scholar 

  3. Grassi, G. et al. The key role of forests in meeting climate targets requires science for credible mitigation. Nat. Clim. Change 7, 220–226 (2017).

    Article  Google Scholar 

  4. Griscom, B. W. et al. Natural climate solutions. Proc. Natl Acad. Sci. USA 114, 11645–11650 (2017).

    Article  CAS  Google Scholar 

  5. Roe, S. et al. Contribution of the land sector to a 1.5 °C world. Nat. Clim. Change 9, 817–828 (2019).

    Article  Google Scholar 

  6. Fuglestvedt, J. et al. Implications of possible interpretations of ‘greenhouse gas balance’ in the Paris Agreement. Philos. Trans. R. Soc. A 376, 20160445 (2018).

    Article  Google Scholar 

  7. Adoption of the Paris Agreement FCCC/CP/2015/L.9/Rev.1 (UNFCC, 2015); http://unfccc.int/resource/docs/2015/cop21/eng/l09r01.pdf

  8. Clarke L. et al. in Climate Change 2014: Mitigation of Climate Change (eds Edenhofer, O. et al) Ch. 6 (Cambridge Univ. Press).

  9. Riahi, K. et al. The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: an overview. Glob. Environ. Change 42, 153–168 (2017).

    Article  Google Scholar 

  10. Rogelj J. et al. in IPCC Special Report on Global Warming of 1.5 °C (eds Masson-Delmotte, V. et al.) Ch 2 (WMO, 2018).

  11. Smith, P. et al. in IPCC Climate Change 2014: Mitigation of Climate Change (eds Edenhofer, O. et al.) Ch. 11 (Cambridge Univ. Press, 2014).

  12. IPCC: Summary for Policymakers. In Special Report on Global Warming of 1.5 °C (WMO, 2018).

  13. van Vuuren, D. P. et al. Energy, land-use and greenhouse gas emissions trajectories under a green growth paradigm. Glob. Environ. Change 42, 237–250 (2017).

    Article  Google Scholar 

  14. Popp, A. et al. Land-use futures in the shared socio-economic pathways. Glob. Environ. Change 42, 331–345 (2017).

    Article  Google Scholar 

  15. Grassi, G. et al. Reconciling global-model estimates and country reporting of anthropogenic forest CO2 sinks. Nat. Clim. Change 8, 914–920 (2018).

    Article  CAS  Google Scholar 

  16. Joint SBSTA-IPCC Special Event: Special Report on Climate Change and Land (UNFCCC, 2019); https://sdg.iisd.org/events/joint-sbsta-ipcc-special-event-special-report-on-climate-change-and-land-srccl/https://unfccc-cop25.streamworld.de/webcast/joint-sbsta-ipcc-special-event-special-report-on-c

  17. Pongratz, J., Reick, C. H., Houghton, R. A. & House, J. I. Terminology as a key uncertainty in net land use and land cover change carbon flux estimates. Earth Syst. Dyn. 5, 177–195 (2014).

    Article  Google Scholar 

  18. Kauppi, P. E. et al. Carbon benefits from forest transitions promoting biomass expansions and thickening. Glob. Change Biol. 26, 5365–5370 (2020).

    Article  Google Scholar 

  19. Pugh, T. A. M. et al. Role of forest regrowth in global carbon sink dynamics. Proc. Natl Acad. Sci. USA 116, 4382–4387 (2019).

    Article  CAS  Google Scholar 

  20. Fujimori, S. et al. SSP3: AIM implementation of shared socioeconomic pathways. Glob. Environ. Change 42, 268–283 (2017).

    Article  Google Scholar 

  21. Calvin, K. et al. SSP4: a world of inequality. Glob. Environ. Change 42, 284–296 (2016).

    Article  Google Scholar 

  22. Fricko, O. et al. The marker quantification of the Shared Socioeconomic Pathway 2: A middle-of-the-road scenario for the 21st century. Glob. Environ. Change 42, 251–267 (2017).

    Article  Google Scholar 

  23. Kriegler, E. Fossil-fueled development (SSP5): an energy and resource intensive scenario for the 21st century. Glob. Environ. Change 42, 297–315 (2017).

    Article  Google Scholar 

  24. Schaphoff, S. et al. LPJmL4—a dynamic global vegetation model with managed land: Part II—model evaluation. Geosci. Model Dev. 11, 1377–1403 (2018).

    Article  CAS  Google Scholar 

  25. IPCC Guidelines for National Greenhouse Gas Inventories (eds Eggleston, H. S. et al.) (Institute for Global Environmental Strategies, 2006).

  26. IPCC Revisiting the Use of Managed Land as a Proxy for Estimating National Anthropogenic Emissions and Removals (eds Eggleston, S. et al.) (Institute for Global Environmental Strategies, 2010); https://www.ipcc-nggip.iges.or.jp/public/mtdocs/pdfiles/0905_MLP_Report.pdf

  27. IPCC 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (eds Calvo Buendia, E. et al.) Vol. 2 (WMO, 2019).

  28. Potapov, P. et al. The last frontiers of wilderness: tracking loss of intact forest landscapes from 2000 to 2013. Sci. Adv. 3, 1–14 (2017).

    Article  Google Scholar 

  29. Müller, C. et al. Drivers and patterns of land biosphere carbon balance reversal. Environ. Res. Lett. 11, 044002 (2016).

    Article  Google Scholar 

  30. Tharammal, T., Bala, G., Devaraju, N. & Nemani, R. A review of the major drivers of the terrestrial carbon uptake: model-based assessments, consensus, and uncertainties. Environ. Res. Lett. 14, 093005 (2019).

    Article  Google Scholar 

  31. Fyson, C. L. & Jeffery, M. L. Ambiguity in the land use component of mitigation contributions toward the Paris Agreement goals. Earth Future 7, 873–891 (2019).

    Article  Google Scholar 

  32. Erb, K. et al. Unexpectedly large impact of forest management and grazing on global vegetation biomass. Nature 553, 73–76 (2018).

    Article  CAS  Google Scholar 

  33. Schelhaas, M. J. et al. Actual European forest management by region, tree species and owner based on 714,000 re-measured trees in national forest inventories. PLoS ONE 13, 1–23 (2018).

    Article  Google Scholar 

  34. Harris, N. L. et al. Global maps of twenty-first century forest carbon fluxes. Nat. Clim. Change 11, 234–239 (2021).

    Article  Google Scholar 

  35. Ceccherini, G. et al. Abrupt increase in harvested forest area over Europe after 2015. Nature 583, 72–77 (2020).

    Article  CAS  Google Scholar 

  36. Houghton, R. A. et al. Terrestrial fluxes of carbon in GCP carbon budget. Glob. Change Biol. 26, 3006–3014 (2020).

    Article  Google Scholar 

  37. Emissions Gap Report 2019 (United Nations Environment Programme, 2019).

  38. Rogelj, J. et al. Understanding the origin of Paris Agreement emission uncertainty. Nat. Commun. 8, 15748 (2017).

    Article  CAS  Google Scholar 

  39. McCollum, D. L. et al. Energy investment needs for fulfilling the Paris Agreement and achieving the Sustainable Development Goals. Nat. Energy 3, 589–599 (2018).

    Article  Google Scholar 

  40. Rogelj, J., Hare, W., Chen, C. & Meinshausen, M. Discrepancies in historical emissions point to a wider 2020 gap between 2 C benchmarks and aggregated national mitigation pledges. Environ. Res. Lett. 6, 02400 (2011).

    Article  Google Scholar 

  41. van Soest, H. L., den Elzen, M. G. J. & van Vuuren, D. P. Net-zero emission targets for major emitting countries consistent with the Paris Agreement. Nat. Commun. 12, 2140 (2021).

    Article  CAS  Google Scholar 

  42. Haverd, V. et al. Higher than expected CO2 fertilization inferred from leaf to global observations. Glob. Chang. Biol. 26, 2390–2402 (2020).

    Article  Google Scholar 

  43. Jiang, M. et al. The fate of carbon in a mature forest under carbon dioxide enrichment. Nature 580, 227–231 (2020).

    Article  CAS  Google Scholar 

  44. Hubau, W. et al. Asynchronous carbon sink saturation in African and Amazonian tropical forests. Nature 579, 80–87 (2020).

    Article  CAS  Google Scholar 

  45. Meinshausen, M., Raper, S. C. B. & Wigley, T. M. L. Emulating coupled atmosphere–ocean and carbon cycle models with a simpler model, MAGICC6—Part 1: Model description and calibration. Atmos. Chem. Phys. 11, 1417–1456 (2011).

    Article  CAS  Google Scholar 

  46. Jones, C. D. et al. C4MIP—the Coupled Climate-Carbon Cycle Model Intercomparison Project: experimental protocol for CMIP6. Geosci. Model Dev. 9, 2853–2880 (2016).

    Article  CAS  Google Scholar 

  47. Friedlingstein, P. et al. Global carbon budget 2019. Earth Syst. Sci. Data 11, 1783–1838 (2019).

    Article  Google Scholar 

  48. Riahi, K., Grübler, A. & Nakicenovic, N. Scenarios of long-term socio-economic and environmental development under climate stabilization. Technol. Forecast. Soc. Change 74, 887–935 (2007).

    Article  Google Scholar 

  49. FAOSTAT Land Use Emissions (FAO, accessed 30 October 2020); http://www.fao.org/faostat/en/#data/GF/visualize

  50. Chen, Y., Feng, X. & Fu, B. An improved global remote-sensing-based surface soil moisture (RSSSM) dataset covering 2003–2018. Earth Syst. Sci. Data 13, 1–31 (2021).

    Article  Google Scholar 

  51. Erb, K.-H. et al. Bias in the attribution of forest carbon sinks. Nat. Clim. Change 3, 854–856 (2013).

    Article  CAS  Google Scholar 

  52. Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–853 (2013).

    Article  CAS  Google Scholar 

  53. Gütschow, J. et al. The PRIMAP-hist national historical emissions time series. Earth Syst. Sci. Data 8, 571–603 (2016).

    Article  Google Scholar 

  54. Transparency and Reporting (UNFCCC, accessed 20 February 2021); https://unfccc.int/process-and-meetings/transparency-and-reporting/the-big-picture/what-is-transparency-and-reporting

  55. National Inventory Submissions (UNFCCC, accessed 20 February 2021); https://unfccc.int/ghg-inventories-annex-i-parties/2020

  56. Nationally Determined Contributions (UNFCCC, accessed 20 February 2021); https://unfccc.int/nationally-determined-contributions-ndcs

  57. National Communications Non-Annex I (UNFCCC, accessed 20 February 2021); https://unfccc.int/non-annex-I-NCs

  58. Biennial Update Reports Non-Annex I (UNFCCC, accessed 20 February 2021); https://unfccc.int/BURs

  59. REDD+ Submissions (UNFCCC, accessed 20 February 2021); https://redd.unfccc.int/submissions.html

  60. Federici, S. et al. GHG Fluxes from Forests: An Assessment of National GHG Estimates and Independent Research in the Context of the Paris Agreement (Climate and Land Use Alliance, 2017); http://www.climateandlandusealliance.org/reports/ghg-fluxes-forests/

  61. IPCC Good Practice Guidance for Land Use, Land-Use Change and Forestry (eds Penman, J. et al.) (Institute for Global Environmental Strategies, 2003).

  62. Ogle, S. M. et al. Delineating managed land for reporting national greenhouse gas emissions and removals to the United Nations framework convention on climate change. Carbon Balance Manag. 13, 9 (2018).

    Article  Google Scholar 

  63. Forsell, N. et al. Assessing the INDCs’ land use, land use change, and forest emission projections. Carbon Balance Manag. 11, 26 (2016).

    Article  Google Scholar 

  64. van Vuuren, D. P. et al. A new scenario framework for climate change research: scenario matrix architecture. Climatic Change 122, 373–386 (2014).

    Article  Google Scholar 

  65. Rogelj, J. et al. Scenarios towards limiting global mean temperature increase below 1.5 °C. Nat. Clim. Change 8, 325–332 (2018).

    Article  CAS  Google Scholar 

  66. Stehfest, E. et al. Integrated Assessment of Global Environmental Change with IMAGE 3.0—Model Description and Policy Applications Report 07-07-2014 (PBL Netherlands Environmental Assessment Agency, 2014).

  67. Arets, E. J. M. M. et al. Global Wood Production. Assessment of Industrial Round Wood Supply from Forest Management Systems in Different Global Regions Report 1808 (Alterrah, 2011).

  68. Pan, Y. et al. A large and persistent carbon sink in the World’s forests. Science 333, 988–993 (2011).

    Article  CAS  Google Scholar 

  69. IPCC Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) (Cambridge Univ. Press, 2013).

Download references

Acknowledgements

G.G. acknowledges funding from the EU’s Horizon 2020 VERIFY project (no. 776810). J.R. acknowledges funding from the EU’s Horizon 2020 CONSTRAIN project (no. 820829). F.H. and D.v.V. acknowledge funding from the EU’s Horizon 2020 ENGAGE project (no. 821471). S. Fujimori and T.H. were supported by the Environment Research and Technology Development Fund (JPMEERF20202002) of the Environmental Restoration and Conservation Agency of Japan and the Sumitomo Foundation. F.N.T. was supported by regular programme funding by member states to FAO. FAOSTAT and FRA are made possible through country data reporting processes to FAO and contributions of experts in the member states. The views expressed are purely those of the writers and may not under any circumstances be regarded as stating an official position of the European Commission, FAO or any other institution.

Author information

Authors and Affiliations

  1. Joint Research Centre, European Commission, Ispra, Italy

    Giacomo Grassi, Alessandro Cescatti, Simone Rossi, Ramdane Alkama, Raúl Abad Viñas, Guido Ceccherini & Anu Korosuo

  2. PBL Netherlands Environmental Assessment Agency, the Hague, the Netherlands

    Elke Stehfest & Detlef van Vuuren

  3. Grantham Institute for Climate Change and the Environment, Imperial College London, London, UK

    Joeri Rogelj

  4. International Institute for Applied System Analysis (IIASA), Laxenburg, Austria

    Joeri Rogelj, Shinichiro Fujimori, Mykola Gusti & Petr Havlik

  5. Copernicus Institute of Sustainable Development, Utrecht University, Utrecht, the Netherlands

    Detlef van Vuuren

  6. Cabot Institute, Department of Geographical Sciences, University of Bristol, Bristol, UK

    Jo House

  7. Wageningen University and Research, Wageningen, the Netherlands

    Gert-Jan Nabuurs

  8. Pacific Northwest National Laboratory, Joint Global Change Research Institute at the University of Maryland–College Park, College Park, MD, USA

    Katherine Calvin

  9. Institute for Global Environmental Strategies, Hayama, Japan

    Sandro Federici

  10. Department of Environmental Engineering, Kyoto University, Kyoto City, Japan

    Shinichiro Fujimori

  11. Center for Social and Environmental Systems Research, National Institute for Environmental Studies (NIES), Ibaraki, Japan

    Shinichiro Fujimori & Tomoko Hasegawa

  12. Lviv Polytechnic National University, Lviv, Ukraine

    Mykola Gusti

  13. College of Science and Engineering, Ritsumeikan University, Shiga, Japan

    Tomoko Hasegawa

  14. Potsdam Institute for Climate Impact Research (PIK), Potsdam, Germany

    Florian Humpenöder & Alexander Popp

  15. Division on Climate Change Impacts on Agriculture, Forests and Ecosystem Services (IAFES), Foundation Euro-Mediterranean Center on Climate Change (CMCC), Viterbo, Italy

    Lucia Perugini

  16. FAO Statistics Division, Via Terme di Caracalla, Rome, Italy

    Francesco N. Tubiello

Authors
  1. Giacomo Grassi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Elke Stehfest
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Joeri Rogelj
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Detlef van Vuuren
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Alessandro Cescatti
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jo House
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Gert-Jan Nabuurs
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Simone Rossi
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Ramdane Alkama
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Raúl Abad Viñas
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Katherine Calvin
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Guido Ceccherini
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Sandro Federici
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Shinichiro Fujimori
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Mykola Gusti
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Tomoko Hasegawa
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Petr Havlik
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Florian Humpenöder
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Anu Korosuo
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Lucia Perugini
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Francesco N. Tubiello
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Alexander Popp
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

G.G. led the study design with the help of E.S., J.R., A.P., D.v.V., A.C. and J.H., wrote the first draft, performed the analysis and created the figures; J.R. and E.S. refined the draft paper, along with A.P., D.v.V., G.-J.N. and A.K.; E.S. provided the IMAGE/LPJmL data, which were combined with non-intact forest maps by S.R. supported by G.C.; S. Federici, R.A.V. and A.K. helped in the analysis of country GHG inventories. IAM data were provided and checked by S. Fujimori and T.H. (AIM/CGE), K.C. (GCAM), E.S. and D.v.V. (IMAGE), M.G. and P.H. (MESSAGE-GLOBIOM), F.H. and A.P. (REMIND-MAgPIE). F.N.T. provided FAOSTAT data and contributed to their analysis. All the authors provided feedback and contributed to writing the article.

Corresponding author

Correspondence to Giacomo Grassi.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Climate Change thanks Claire Fyson and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Summary of the selected components of land CO2 fluxes in IAMs, DGVMs and NGHGIs, and areas of managed and unmanaged forest and of intact and non-intact forest28,52.

Values are approximated (broadly based on the averages for 2005-2015) with the purpose to illustrate where the main differences are between IAMs and NGHGIs, that is not much on direct effects, but rather on how indirect effects are estimated and labelled (if anthropogenic or not). As a result, when considering a broadly similar area of forest (that is about 3 billion ha of non-intact forest), the sum of CO2 fluxes by global models (IAMs and DGVMs) match well those from NGHGIs. Numbers in parenthesis indicate values not included in the original IAM and NGHGI datasets, but estimated here (see footnotes).

Supplementary information

Supplementary Information

Supplementary information, including eight sections with eight tables and eight figures.

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Grassi, G., Stehfest, E., Rogelj, J. et al. Critical adjustment of land mitigation pathways for assessing countries’ climate progress. Nat. Clim. Chang. 11, 425–434 (2021). https://doi.org/10.1038/s41558-021-01033-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41558-021-01033-6

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing