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

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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.

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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.

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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.

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Authors and Affiliations

Authors

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.

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The authors declare no competing interests.

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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.

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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.

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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

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