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A sustainable development pathway for climate action within the UN 2030 Agenda

Nature Climate Change volume 11, pages 656–664 (2021)Cite this article

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Abstract

Ambitious climate policies, as well as economic development, education, technological progress and less resource-intensive lifestyles, are crucial elements for progress towards the UN Sustainable Development Goals (SDGs). However, using an integrated modelling framework covering 56 indicators or proxies across all 17 SDGs, we show that they are insufficient to reach the targets. An additional sustainable development package, including international climate finance, progressive redistribution of carbon pricing revenues, sufficient and healthy nutrition and improved access to modern energy, enables a more comprehensive sustainable development pathway. We quantify climate and SDG outcomes, showing that these interventions substantially boost progress towards many aspects of the UN Agenda 2030 and simultaneously facilitate reaching ambitious climate targets. Nonetheless, several important gaps remain; for example, with respect to the eradication of extreme poverty (180 million people remaining in 2030). These gaps can be closed by 2050 for many SDGs while also respecting the 1.5 °C target and several other planetary boundaries.

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Fig. 1: Overview of headline SDG indicator values grouped into five clusters.
Fig. 2: Decomposition of SDG outcomes, highlighting the effects of the different interventions.
Fig. 3: Global SDG achievement and gap analysis for selected indicators.
Fig. 4: Regional outcomes for selected indicators resulting from the sustainable development interventions.
Fig. 5: Regional SDG indicator scores in our SDP scenario in 2030.

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Data availability

The data and analysis scripts supporting the findings of this study112 are available at https://doi.org/10.5281/zenodo.4787613. The following publicly accessible datasets were used for the institutional quality and conflict fatalities models (Supplementary Information references): Varieties of Democracy (V-Dem) (Country–Year/Country–Data) Dataset v.10, the Uppsala Conflict Data Program (UCDP) Georeferenced Event Dataset (GED) Global v.20.1 and Population and Human Capital Stocks data by the Wittgenstein Centre. They can be accessed via the following links: https://www.v-dem.net/en/data/archive/previous-data/v-dem-dataset/; https://ucdp.uu.se/downloads/; http://dataexplorer.wittgensteincentre.org/wcde-v2/

Code availability

Both REMIND and MAgPIE are available open source under the following links: REMIND: https://github.com/remindmodel/remind; MAgPIE: https://github.com/magpiemodel/magpie. The exact model versions used are: REMIND: https://github.com/bs538/remind/tree/SDP_runs; MAgPIE: https://github.com/magpiemodel/magpie/releases/tag/v4.2.1

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Acknowledgements

We thank D. Soergel for valuable comments on figure designs and proof-reading of the manuscript and F. Piontek, S. Madeddu and the other members of the REMIND and MAgPIE teams for helpful discussions. The SDG icons and circle used in the figures and tables were created by the United Nations: https://www.un.org/sustainabledevelopment/sustainable-development-goals/. The content of this publication has not been approved by the United Nations and does not reflect the views of the United Nations or its officials or Member States. This work has been partially funded through the project SHAPE. SHAPE is part of AXIS, an ERA-NET initiated by JPI Climate and funded by FORMAS (SE), FFG/BMWFW (AT), DLR/BMBF (DE, grant no. 01LS1907A), NWO (NL) and RCN (NO) with cofunding by the European Union (grant no. 776608). This work was also supported by the European Union’s Horizon 2020 research and innovation programme under grant nos. 821124 (NAVIGATE) and 821471 (ENGAGE). Further support is provided by the Global Commons Stewardship (GCS) project funded by the University of Tokyo/ Institute for Future Initiatives, and by the Food System Economics Commission (FSEC) funded by Rockefeller Foundation (no. 2020 FOD 008) and Wellcome Trust (no. 221362/Z/20/Z).

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Authors and Affiliations

  1. Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, Potsdam, Germany

    Bjoern Soergel, Elmar Kriegler, Isabelle Weindl, Sebastian Rauner, Alois Dirnaichner, Matthias Hofmann, Nico Bauer, Christoph Bertram, Benjamin Leon Bodirsky, Marian Leimbach, Antoine Levesque, Gunnar Luderer, Michaja Pehl, Lavinia Baumstark, Felicitas Beier, Jan Philipp Dietrich, Florian Humpenöder, Patrick von Jeetze, David Klein, Johannes Koch, Robert Pietzcker, Jessica Strefler, Hermann Lotze-Campen & Alexander Popp

  2. Universität Potsdam, Potsdam, Germany

    Elmar Kriegler

  3. Goethe-Universität, Frankfurt am Main, Germany

    Constantin Ruhe

  4. German Development Institute—Deutsches Institut für Entwicklungspolitik (DIE), Bonn, Germany

    Constantin Ruhe, Julia Leininger & Christopher Wingens

  5. Global Energy Systems Analysis, Technische Universität Berlin, Berlin, Germany

    Gunnar Luderer

  6. Humboldt-Universität zu Berlin, Berlin, Germany

    Hermann Lotze-Campen

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Contributions

B.S. and E.K. designed the research with contributions from I.W., C.B., G.L. and the other authors. B.S., I.W., S.R. and A.D. performed the REMIND–MAgPIE modelling and the overall analysis, with contributions from the other authors. C.R., J.L. and C.W. performed the modelling for political institutions and conflict indicators. M.H. did the ocean modelling. B.S. and N.B. worked on the calculation of education and gender equality indicators. B.S. created all figures shown in the main paper; B.S., E.K., I.W., S.R., A.D. and C.R. created additional figures for the Extended Data and Supplementary Information. B.S., E.K., I.W., S.R., A.D. and C.R. wrote the paper with contributions and feedback from all other authors.

Corresponding author

Correspondence to Bjoern Soergel.

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The authors declare no competing interests.

Additional information

Peer review information Nature Climate Change thanks Alexandros Nikas, Toon Vandyck 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 Illustration of the scenario setup for this study.

The setup was designed to analyse the collective and individual impact of a range of sustainable development interventions: A - development, B - resource efficiency, C - climate change mitigation. D-food and energy: sufficient, healthy and sustainable nutrition; improved access to modern energy services in lower-income regions; ambitious shift to sustainable lifestyles in high-income regions; additional energy- and land-system sustainability policies. E - global equity: international burden sharing through climate and development finance. F - equality and poverty alleviation: progressive redistribution policies funded from the carbon pricing revenues. Note that the SDG icons attached to the interventions serve only as an illustration of the SDGs that are most strongly affected by the respective intervention, and are not intended to imply a specific grouping of SDGs.

Extended Data Fig. 2 Overview of the modelling framework.

We show the linkages between the different models comprising our modelling framework built around REMIND–MAgPIE. The linkage between REMIND and MAgPIE is bi-directional (iterative soft coupling), the linkages to the downstream models for further SDG indicators are one-directional. The most relevant variables passed between models are specified next to the arrows. The colour-coding of the additional models broadly matches the SDGs they cover.

Extended Data Fig. 3 Decomposition of the SD interventions D–F.

We unpack the additional SD interventions that are part of our SDP scenario (shown together in Fig. 2 in the main paper) into the steps D-energy (both demand & supply), D-food (nutrition & land use), E (global equity) and F (national redistribution). This decomposition highlights the effect of the individual interventions on the respective SDG indicator. Note that the interventions are ‘applied’ incrementally, that is we show the additional effect of an intervention starting from a scenario already including the previous interventions (same as in Fig. 2 in the main paper). Therefore the order of interventions matters in this decomposition. A more thorough discussion of this decomposition (including this figure) is given in SI Section 3.

Extended Data Fig. 4 Regional outcomes for selected indicators that describe key dynamics of the land and food system.

Transparent wide bars represent 2030 values, solid thin bars are values for 2050 and the 2015 values are given by the dotted vertical lines. We show the SSP2-NDC (red, top), SSP1-1.5C (green, centre) and SDP-1.5C (blue, bottom) scenarios; the SSP1-NDC scenario is omitted for reasons of visual clarity. a, Drivers of land use (crop demand, the share of plant-based protein in total dietary protein supply and bioenergy demand), b, Production and food system characteristics (N surplus on cropland, cereal yields and food price index w.r.t. 2010), c, Agricultural land (including cropland for food/feed crops and dedicated bioenergy crops as well as pasture) d, Forest cover differentiated between unmanaged (primary as well as secondary) forest and managed forest (including timber plantations and afforestation). Region abbreviations: Sub-Saharan Africa (SSA), India (IND), Latin America (LAM), European Union (EUR), United States of America (USA). A more detailed discussion on the land and food system (including this figure) is given in Section 4.1 of the SI.

Extended Data Fig. 5 Regional and sectoral outcomes for selected energy system dynamics indicators.

Transparent wide bars represent 2030 values, solid thin bars are values for 2050, the 2015 values are given by the dotted vertical line. We show the SSP2-NDC (red, top), SSP1-1.5C (green, centre) and SDP-1.5C (blue, bottom) scenarios; the SSP1-NDC scenario is omitted for reasons of visual clarity. a, Sectoral final energy demand per capita, b, Electricity and hydrogen share of final energy, by sector c, Total final energy demand compared to the 2050 values of Grubler et al.34 and Millwards-Hopkins et al.43 and the 2030 values of the IEA ‘Sustainable Development’ scenario113. Note the imperfect mapping between the IEA ‘Africa’ region and our SSA region. The Grubler et al. model only distinguishes between two model regions (Global North and Global South). d, Sectoral CO2 emissions. Region abbreviations: Sub-Saharan Africa (SSA), India (IND), China (CHA), Europe (EUR), United States of America (USA). A more detailed discussion on the energy system (including this figure) is given in Section 4.2 of the SI.

Supplementary information

Supplementary Information

Supplementary results, text, Tables 1–6, Figs. 1–27 and references.

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Soergel, B., Kriegler, E., Weindl, I. et al. A sustainable development pathway for climate action within the UN 2030 Agenda. Nat. Clim. Chang. 11, 656–664 (2021). https://doi.org/10.1038/s41558-021-01098-3

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