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Decision-making fitness of methods to understand Sustainable Development Goal interactions

Abstract

The integrated nature of the Sustainable Development Goals (SDGs) presents a challenge to implementing the 2030 Agenda. Analytical methods to support decision-makers are often developed without explicitly incorporating decision-makers’ views and experience. Here, we investigate whether existing methods are fit-for-purpose in supporting decision-makers at national and subnational levels. We identify prominent methods for SDG interaction analysis, which we then evaluate by engaging directly (via a survey and interviews) with method developers and decision-makers in Sweden. We find that decision-makers prioritize methods that are simple and flexible to apply and able to provide directly actionable and understandable results. They are less concerned with the accuracy, precision, completeness or quantitative nature of the knowledge. Prominent categories of methods include self-assessment, expert judgement, literature-based, statistical analyses and modelling. Interviewed decision-makers consider these methods in line with the features prioritized in the survey but highlight low performance on features they value highly, such as the extent to which results are actionable and overall ease of use. Methods developers have limited awareness of decision-makers’ priorities and requirements, so hindering methodological advancement. They should focus on the practical value of applications to support decision-makers, resource-constrained organizations and those seeking to evaluate multiple cases.

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Fig. 1: Methodological approaches to analysing SDG synergies and trade-offs in the scientific literature.
Fig. 2: Citation networks of the categories of prominent methods identified in the scientific literature.
Fig. 3: Developers’ and decision-makers’ views on the performance of methodological approaches to SDG interaction analysis.

Data availability

Data of the review of the literature and practice of SDG interaction research are available in the Supplementary Data and the source data for Fig. 1. Source data are provided with this paper. Additional data are available from the corresponding author on reasonable request.

References

  1. Transforming our World: The 2030 Agenda for Sustainable Development (United Nations, 2015); http://www.un.org/ga/search/view_doc.asp?symbol=A/RES/70/1&Lang=E

  2. Griggs, D. et al. An integrated framework for Sustainable Development Goals. Ecol. Soc. 19, 49 (2014).

    Article  Google Scholar 

  3. Breuer, A., Janetschek, H. & Malerba, D. Translating Sustainable Development Goal (SDG) interdependencies into policy advice. Sustainability 11, 2092 (2019).

    Article  Google Scholar 

  4. Bennich, T., Weitz, N. & Carlsen, H. Deciphering the scientific literature on SDG interactions: a review and reading guide. Sci. Total Environ. 728, 138405 (2020).

  5. Allen, C., Metternicht, G. & Wiedmann, T. National pathways to the Sustainable Development Goals (SDGs): a comparative review of scenario modelling tools. Environ. Sci. Policy 66, 199–207 (2016).

    Article  Google Scholar 

  6. Miola, A., Borchardt, S., Neher, F. & Buscaglia, D. Interlinkages and Policy Coherence for the Sustainable Development Goals Implementation (European Union, 2019).

  7. Johnsson, F., Karlsson, I., Rootzén, J., Ahlbäck, A. & Gustavsson, M. The framing of a Sustainable Development Goals assessment in decarbonizing the construction industry – avoiding “greenwashing”. Renew. Sustain. Energy Rev. 131, 110029 (2020).

    Article  Google Scholar 

  8. van Soest, H. L. et al. Analysing interactions among Sustainable Development Goals with Integrated Assessment Models. Glob. Transit. 1, 210–225 (2019).

    Article  Google Scholar 

  9. Allen, C., Metternicht, G. & Wiedmann, T. Priorities for Science to Support National Implementation of the Sustainable Development Goals: A Review of Progress and Gaps (Monash Sustainable Development Institute, 2021).

  10. Sachs, J. et al. Sustainable Development Report 2020: The Sustainable Development Goals and COVID-19 (Cambridge Univ. Press, 2020).

  11. Colledge, L. & Verlinde, R. Scival Metrics Guidebook (Elsevier, 2014).

  12. Climate, Land (Food), Energy and Water Systems Approach—CLEWs (Royal Institute of Technology, 2020).

  13. Messerli, P. et al. Expansion of sustainability science needed for the SDGs. Nat. Sustain. 2, 892–894 (2019).

    Article  Google Scholar 

  14. Talwar, S., Wiek, A. & Robinson, J. User engagement in sustainability research. Sci. Public Policy 38, 379–390 (2011).

    Article  Google Scholar 

  15. Weichselgartner, J. & Kasperson, R. Barriers in the science-policy-practice interface: toward a knowledge-action-system in global environmental change research. Glob. Environ. Change 20, 266–277 (2010).

    Article  Google Scholar 

  16. Cash, D. W. et al. Knowledge systems for sustainable development. Proc. Natl Acad. Sci. USA 100, 8086–8091 (2003).

    CAS  Article  Google Scholar 

  17. Norström, A. V. et al. Principles for knowledge co-production in sustainability research. Nat. Sustain. 3, 182–190 (2020).

    Article  Google Scholar 

  18. Allen, C., Metternicht, G. & Wiedmann, T. Initial progress in implementing the Sustainable Development Goals (SDGs): a review of evidence from countries. Sustain. Sci. 13, 1453–1467 (2018).

    Article  Google Scholar 

  19. SDG Impact Assessment Tool (Gothenburg Centre for Sustainable Development, 2021).

  20. Government Agencies and the 2030 Agenda (GD-Forum, 2020); https://www.folkhalsomyndigheten.se/gd-forum-agenda-2030/english/

  21. Glokala Sverige—Agenda 2030 i Kommuner och Regioner (United Nations Association Sweden, 2020); https://fn.se/vi-gor/utveckling-och-fattigdomsbekampning/agenda-2030/glokala-sverige/

  22. CONCORD Sweden (CONCORD Sweden, 2020).

  23. UN Global Compact—Participants (UN Global Compact, 2020).

  24. Swedish Investors for Sustainable Development and the SDGs (SIDA, 2019).

  25. Municipal Initiatives within Agenda 2030 (SKR, 2019).

  26. Regional Initiatives within Agenda 2030 (SKR, 2019).

  27. Framework to Review Models (UK National Audit Office, 2016).

  28. Louviere, J. J. & Woodworth, G. G. Best-Worst Scaling: A Model for the Largest Difference Judgments (Univ. of Alberta, 1991).

  29. Orme, B. Maxdiff Analysis: Simple Counting, Individual-level Logit, and HB (Sawtooth Software, 2009).

  30. Olfe-Kräutlein, B. Advancing CCU technologies pursuant to the SDGs: a challenge for policy making. Front. Energy Res. https://doi.org/10.3389/fenrg.2020.00198 (2020).

  31. Weitz, N., Carlsen, H., Nilsson, M. & Skånberg, K. Towards systemic and contextual priority setting for implementing the 2030 Agenda. Sustain. Sci. 13, 531–548 (2018).

    Article  Google Scholar 

  32. Nilsson, M., Griggs, D. & Visbeck, M. Policy: map the interactions between Sustainable Development Goals. Nature 534, 320–322 (2016).

    Article  Google Scholar 

  33. Nilsson, M. et al. Mapping interactions between the Sustainable Development Goals: lessons learned and ways forward. Sustain. Sci. 13, 1489–1503 (2018).

    Article  Google Scholar 

  34. SDG Synergies: An Approach for Coherent 2030 Agenda implementation (Stockholm Environmental institute, 2020).

  35. Fuso Nerini, F. et al. Connecting climate action with other Sustainable Development Goals. Nat. Sustain. 2, 674–680 (2019).

    Article  Google Scholar 

  36. Nerini, F. F. et al. Mapping synergies and trade-offs between energy and the Sustainable Development Goals. Nat. Energy 3, 10–15 (2018).

    Article  Google Scholar 

  37. Vinuesa, R. et al. The role of artificial intelligence in achieving the Sustainable Development Goals. Nat. Commun. 11, 233 (2020).

    CAS  Article  Google Scholar 

  38. Roy, J., Some, S., Das, N. & Pathak, M. Demand side climate change mitigation actions and SDGs: literature review with systematic evidence search. Environ. Res. Lett. 16, 043003 (2021).

  39. Castor, J., Bacha, K. & Fuso Nerini, F. SDGs in action: a novel framework for assessing energy projects against the Sustainable Development Goals. Energy Res. Soc. Sci. 68, 101556 (2020).

    Article  Google Scholar 

  40. de Almeida, C. M. L., Bergqvist, E., Thacker, S. & Nerini, F. F. Actions to align energy projects with the Sustainable Development Goals. Discov. Sustain. 2, 16 (2021).

  41. Kroll, C., Warchold, A. & Pradhan, P. Sustainable Development Goals (SDGs): are we successful in turning trade-offs into synergies? Palgrave Commun. 5, 140 (2019).

    Article  Google Scholar 

  42. Pradhan, P., Costa, L., Rybski, D., Lucht, W. & Kropp, J. P. A systematic study of Sustainable Development Goal (SDG) interactions. Earth’s Future 5, 1169–1179 (2017).

    Article  Google Scholar 

  43. Collste, D., Pedercini, M. & Cornell, S. E. Policy coherence to achieve the SDGs: using integrated simulation models to assess effective policies. Sustain. Sci. 12, 921–931 (2017).

    Article  Google Scholar 

  44. Pedercini, M., Zuellich, G., Dianati, K. & Arquitt, S. Toward achieving Sustainable Development Goals in Ivory Coast: simulating pathways to sustainable development. Sustain. Dev. 26, 588–595 (2018).

    Article  Google Scholar 

  45. iSDG—Integrated Simulation Tool (Millennium Institute, 2021).

  46. IMAGE Model 3.0 Model Documentation (Netherlands Environmental Assessment Agency, 2020); https://models.pbl.nl/image/index.php/Welcome_to_IMAGE_3.0_Documentation

  47. van Vuuren, D. P. et al. Pathways to achieve a set of ambitious global sustainability objectives by 2050: explorations using the IMAGE integrated assessment model. Technol. Forecast. Soc. Change 98, 303–323 (2015).

    Article  Google Scholar 

  48. Ramos, E. P. et al. The climate, land, energy, and water systems (CLEWs) framework: a retrospective of activities and advances to 2019. Environ. Res. Lett. 16, 033003 (2021).

    Article  Google Scholar 

  49. Engström, R. E. et al. Cross-scale water and land impacts of local climate and energy policy—a local Swedish analysis of selected SDG interactions. Sustainability 11, 1847 (2019).

    Article  Google Scholar 

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Acknowledgements

We thank all who collaborated with us on the data collection. We acknowledge the representative of Sweden’s national coordinator for the 2030 Agenda for the support with the engagement of decision-makers. This research was funded by NERC grant no. NE/S012834/1 (L.D. and R.S.) and Formas grant no. 2019-00040 (L.D. and J.K.) under the research initiative Towards a Sustainable Earth: Environment–Human Systems and the UN Global Goals.

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Authors

Contributions

L.D., R.S. and J.K. designed the research. L.D. collected and analysed the data and was the primary writer. All authors edited the manuscript.

Corresponding author

Correspondence to Lorenzo Di Lucia.

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The authors declare no competing interests.

Additional information

Peer review information Nature Sustainability thanks Francesco Fuso Nerini and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Sections 1–5, Figs. 1–7 and Tables 1–7.

Reporting Summary

Supplementary Data

Results of the search of methods in the practice of SDG decision-making.

Source data

Source Data Fig. 1

Published records identified in the scientific literature.

Source Data Fig. 2

Citation networks of prominent methods identified in the scientific literature.

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Di Lucia, L., Slade, R. & Khan, J. Decision-making fitness of methods to understand Sustainable Development Goal interactions. Nat Sustain 5, 131–138 (2022). https://doi.org/10.1038/s41893-021-00819-y

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