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Greater gains for Australia by tackling all SDGs but the last steps will be the most challenging

Nature Sustainability volume 2, pages 1041–1050 (2019)Cite this article

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Abstract

The Sustainable Development Goals (SDGs) combine complex interlinkages, future uncertainty and transformational change. Recent studies highlight that trade-offs between SDG targets may undermine achievement of the goals. Significant gaps remain in scenario frameworks and modelling capabilities. We develop a novel approach nesting national SDG scenario modelling within the global Shared Socioeconomic Pathways, selecting Australia as a use case. The integrated SDG–Australia model is used to project four alternative scenarios that adopt different development approaches. Although we find that Australia is off-track to achieve the SDGs by 2030, considerable progress is possible by altering Australia’s development trajectory. A ‘Sustainability Transition’ scenario comprising a coherent set of policies and investments delivers rapid and balanced progress of 70% towards SDG targets by 2030, well ahead of the business-as-usual scenario (40%). A focus on economic growth, social inclusion or green economy in isolation foregoes opportunities for greater gains. However, future uncertainty and cascading risks could undermine progress, and closing the gap to 100% SDG achievement will be very challenging. This will require a shift from ‘transition’ to ‘transformation’.

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Fig. 1: The nested approach used to develop national scenarios, assumptions and settings.
Fig. 2: Aggregate performance on the SDGs across all Australian scenarios.
Fig. 3: Performance of each scenario on economic, social and environmental SDG targets.
Fig. 4: The proportion of SDG targets assessed as ‘achieved’ under different scenarios.
Fig. 5: Sensitivity analysis of SDG performance results: boxplots of frequency distributions from Monte Carlo simulations.

Data availability

The datasets collected and analysed during the current study are available from the corresponding author on reasonable request.

Code availability

The iSDG simulation model can be made available from the Millennium Institute on reasonable request.

References

  1. Spaiser, V., Ranganathan, S., Swain, R. B. & Sumpter, D. J. The sustainable development oxymoron: quantifying and modelling the incompatibility of Sustainable Development Goals. Int. J. Sustain. Dev. World Ecol. 24, 457–470 (2017).

    Google Scholar 

  2. Spangenberg, J. H. Hot air or comprehensive progress? A critical assessment of the SDGs. Sustain. Dev. 25, 311–321 (2017).

    Google Scholar 

  3. Hall, N. et al. Achieving the UN Sustainable Development Goals for Water and Beyond (Global Change Institute, Univ. of Queensland, 2016).

  4. Zhang, Q., Prouty, C., Zimmerman, J. B. & Mihelcic, J. R. More than Target 6.3: a systems approach to rethinking sustainable development goals in a resource-scarce world. Engineering 2, 481–489 (2016).

    Google Scholar 

  5. Allen, C., Metternicht, G. & Wiedmann, T. Prioritising SDG targets: assessing baselines, gaps and interlinkages. Sustain. Sci. 14, 421–438 (2019).

    Google Scholar 

  6. Zhou, X., Moinuddin, M. & Xu, M. Sustainable Development Goals Interlinkages and Network Analysis: A Practical Tool for SDG Integration and Policy Coherence (IGES, 2017).

  7. A Guide to SDG Interactions: From Science to Implementation (ICS, 2017).

  8. Le Blanc, D. Towards integration at last? The Sustainable Development Goals as a network of targets. Sustain. Dev. 23, 176–187 (2015).

    Google Scholar 

  9. Lusseau, D. & Mancini, F. Income-based variation in Sustainable Development Goal interaction networks. Nat. Sustain. 2, 242–247 (2019).

    Google Scholar 

  10. Mcgowan, P. J., Stewart, G. B., Long, G. & Grainger, M. J. An imperfect vision of indivisibility in the Sustainable Development Goals. Nat. Sustain. 2, 43–45 (2019).

    Google Scholar 

  11. Weitz, N., Carlsen, H., Nilsson, M. & Skånberg, K. Towards systemic and contextual priority setting for implementing the 2030 Agenda. Sustain. Sci. 13, 531–548 (2017).

    Google Scholar 

  12. Campagnolo, L. et al. The ex-ante evaluation of achieving Sustainable Development Goals. Soc. Indic. Res. 136, 73–116 (2018).

    Google Scholar 

  13. Gao, L. & Bryan, B. A. Finding pathways to national-scale land-sector sustainability. Nature 544, 217–222 (2017).

    CAS  Google Scholar 

  14. Moyer, J. D. & Bohl, D. K. Alternative pathways to human development: assessing trade-offs and synergies in achieving the Sustainable Development Goals. Futures 105, 199–210 (2019).

    Google Scholar 

  15. Pedercini, M., Zuellich, G., Dianati, K. & Arquitt, S. Toward achieving Sustainable Development Goals in Ivory Coast: simulating pathways to sustainable development. Sustain. Devel. https://doi.org/10.1002/sd.1721 (2018).

    Google Scholar 

  16. Costanza, R. et al. Scenarios for Australia in 2050: a synthesis and proposed survey. J. Futures Stud. 19, 49–76 (2015).

    Google Scholar 

  17. O’Connell, D. et al. Navigating Sustainability: Measurement, Evaluation and Action (CSIRO, 2013).

  18. 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).

    Google Scholar 

  19. Allen, C., Metternicht, G. & Wiedmann, T. An iterative framework for national scenario modelling for the Sustainable Development Goals (SDGs). Sustain. Dev. 25, 372–385 (2017).

    Google Scholar 

  20. Bauer, N. et al. Shared socio-economic pathways of the energy sector—quantifying the narratives. Glob. Environ. Change 42, 316–330 (2017).

    Google Scholar 

  21. O’Neill, B. C. et al. The roads ahead: narratives for shared socioeconomic pathways describing world futures in the 21st century. Glob. Environ. Change 42, 169–180 (2017).

    Google Scholar 

  22. O’Neill, B. C. et al. A new scenario framework for climate change research: the concept of shared socioeconomic pathways. Clim. Change 122, 387–400 (2014).

    Google Scholar 

  23. 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).

    Google Scholar 

  24. Arnell, N. W. & Lloyd-Hughes, B. The global-scale impacts of climate change on water resources and flooding under new climate and socio-economic scenarios. Clim. Change 122, 127–140 (2014).

    Google Scholar 

  25. Hasegawa, T., Fujimori, S., Takahashi, K. & Masui, T. Scenarios for the risk of hunger in the twenty-first century using Shared Socioeconomic Pathways. Environ. Res. Lett. 10, 1 (2015).

    CAS  Google Scholar 

  26. Frame, B., Lawrence, J., Ausseil, A.-G., Reisinger, A. & Daigneault, A. Adapting global shared socio-economic pathways for national and local scenarios. Clim. Risk Manag. 21, 39–51 (2018).

    Google Scholar 

  27. König, M., Loibl, W., Haas, W. & Kranzl, L. in Economic Evaluation of Climate Change Impacts (eds Steininger, K. et al.) 75–99 (Springer, 2015).

  28. Steininger, K. W., Bednar-Friedl, B., Formayer, H. & König, M. Consistent economic cross-sectoral climate change impact scenario analysis: method and application to Austria. Clim. Serv. 1, 39–52 (2016).

    Google Scholar 

  29. Zimm, C., Sperling, F. & Busch, S. Identifying sustainability and knowledge gaps in socio-economic pathways vis-à-vis the Sustainable Development Goals. Economies 6, 20 (2018).

    Google Scholar 

  30. Allen, C., Reid, M., Thwaites, J., Glover, R. & Kestin, T. Assessing national progress and priorities for the Sustainable Development Goals (SDGs): experience from Australia. Sustain. Sci. https://doi.org/10.1007/s11625-019-00711-x (2019).

  31. Hatfield-Dodds, S. et al. Australia is ‘free to choose’ economic growth and falling environmental pressures. Nature 527, 49–53 (2015).

    CAS  Google Scholar 

  32. United Nations Sustainable Development Goals: Guidelines for the Use of the SDG Logo (United Nations, 2016); https://www.un.org/sustainabledevelopment/news/communications-material/

  33. Bliemel, F. Theil’s forecast accuracy coefficient: a clarification. J. Mark. Res. 10, 444–446.

    Google Scholar 

  34. Theil, H. Applied Economic Forecasting (North-Holland, 1966).

  35. Spangenberg, J. H. The growth discourse, growth policy and sustainable development: two thought experiments. Int. J. Technol. Pol. Manag. 18, 561–566 (2010).

    Google Scholar 

  36. Kwakkel, J. H., Walker, W. E. & Marchau, V. A. Classifying and communicating uncertainties in model-based policy analysis. Int. J. Technol. Manag. 10, 299–315 (2010).

    Google Scholar 

  37. Maier, H. R. et al. An uncertain future, deep uncertainty, scenarios, robustness and adaptation: how do they fit together? Environ. Model. Softw. 81, 154–164 (2016).

    Google Scholar 

  38. National Resilience Taskforce Profiling Australia’s Vulnerability: The Interconnected Causes and Cascading Effects of Systemic Disaster Risk (Australian Government Department of Home Affairs, 2018).

  39. Díaz, S. et al. Summary for Policymakers of the Global Assessment Report on Biodiversity and Ecosystem Services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES Secretariat, 2019).

  40. IPCC Global Warming of 1.5 °C (eds Masson-Delmotte, V. et al.) (Cambridge Univ. Press, 2018).

  41. O’Connell, D. et al. Approach, Methods and Results for Co-Producing a Systems Understanding of Disaster (CSIRO, 2018).

  42. The Global Risks Report 2019 (WEF, 2019); http://www3.weforum.org/docs/WEF_Global_Risks_Report_2019.pdf

  43. Walker, W. E., Lempert, R. J. & Kwakkel, J. H. Deep uncertainty. Encycl. Oper. Res. Manage. Sci. https://doi.org/10.1007/978-1-4419-1153-7_1140 (2016).

    Google Scholar 

  44. Weaver, C. P. et al. Improving the contribution of climate model information to decision making: the value and demands of robust decision frameworks. Wiley Interdiscip. Rev. Clim. Change 4, 39–60 (2013).

    Google Scholar 

  45. Gao, L. et al. Robust global sensitivity analysis under deep uncertainty via scenario analysis. Environ. Model. Softw. 76, 154–166 (2016).

    Google Scholar 

  46. Ralston, B. & Wilson, I. The Scenario Planning Handbook (Thomson, 2006).

  47. Swanson, D. & Bhadwal, S. Creating Adaptive Policies—A Guide for Policy-Making in an Uncertain World (IISD, 2009).

  48. Van Vuuren, D. P. et al. The representative concentration pathways: an overview. Clim. Change 109, 5–31 (2011).

    Google Scholar 

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

    Google Scholar 

  50. Hatfield-Dodds, S. et al. Australian National Outlook 2015: Economic Activity, Resource Use, Environmental Performance and Living Standards, 1970–2050 (CSIRO, 2015).

  51. Raupach, M. R., Mcmichael, T., Finnigan, J. J., Manderson, L. & Walker, B. H. Negotiating Our Futures: Living Scenarios for Australia to 2050 (AAS, 2012).

  52. Chambers, I. et al. A public opinion survey of four future scenarios for Australia in 2050. Futures 107, 119–132 (2018).

    Google Scholar 

  53. Commission on Growth and Development The Growth Report: Strategies for Sustained Growth and Inclusive Development (World Bank, 2008).

  54. Gupta, J., Pouw, N. R. & Ros-Tonen, M. A. Towards an elaborated theory of inclusive development. Eur. J. Dev. Res. 27, 541–559 (2015).

    Google Scholar 

  55. Towards a Green Economy: Pathways to Sustainable Development and Poverty Eradication (UNEP, 2011).

  56. United Nations General Assembly United Nations Millennium Declaration A/RES/55/2 (United Nations, 2000).

  57. 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).

    Google Scholar 

  58. Vensim DSS v.7.3 (Ventana Systems Inc., 2018); https://vensim.com/vensim-software/

  59. Stella Architect (ISEE Systems, 2018); https://www.iseesystems.com

  60. iSDG Model Documentation (Millennium Institute, 2017); https://www.millennium-institute.org/documentation

  61. Bassi, A. M. A context-inclusive approach to support energy policy formulation and evaluation. Reg. Environ. Change 11, 285–295 (2011).

    Google Scholar 

  62. Bassi, A. M., Tan, Z. & Goss, S. An integrated assessment of investments towards global water sustainability. Water 2, 726–741 (2010).

    Google Scholar 

  63. Kopainsky, B., Pedercini, M., Davidsen, P. I. & Alessi, S. M. A blend of planning and learning: simplifying a simulation model of national development. Simul. Gaming 41, 641–662 (2010).

    Google Scholar 

  64. Pedercini, M. in International Conference on Software Engineering and Formal Methods Vol. 7041 (eds Barthe G., Pardo A. & Schneider G.) 447–463 (Springer, 2011).

  65. Pedercini, M., Kleemann, H., Dlamini, N., Dlamini, V. & Kopainsky, B. Integrated simulation for national development planning. Kybernetes 48, 208–223 (2019).

    Google Scholar 

  66. Partnership for Action on Green Economy The Integrated Green Economy Modelling Framework (UNEP, 2017).

  67. Green Economy Assessment Report: Kenya (UNEP, 2014).

  68. Green Economy Assessment Study: Burkina Faso (UNEP, 2014).

  69. Green Economy Assessment Study: Senegal (UNEP, 2014).

  70. Sterman, J. Business Dynamics: Systems Thinking and Modeling for a Complex World (Irwin McGraw-Hill, 2000).

  71. Saltelli, A. et al. Global Sensitivity Analysis: The Primer (John Wiley & Sons, 2008).

  72. Elsawah, S. et al. An overview of the system dynamics process for integrated modelling of socio-ecological systems: lessons on good modelling practice from five case studies. Environ. Model. Softw. 93, 127–145 (2017).

    Google Scholar 

  73. Mirchi, A., Madani, K., Watkins, D. & Ahmad, S. Synthesis of system dynamics tools for holistic conceptualization of water resources problems. Water Resour. Manag. 26, 2421–2442 (2012).

    Google Scholar 

  74. Moon, Y. B. Simulation modelling for sustainability: a review of the literature. Int. J. Sustain. Eng. 10, 2–19 (2017).

    Google Scholar 

  75. Barlas, Y. Formal aspects of model validity and validation in system dynamics. Syst. Dyn. Rev. 12, 183–210 (1996).

    Google Scholar 

  76. Forrester, J. W. & Senge, P. M. Tests for building confidence in system dynamics models. TIMS Stud. Manag. Sci. 14, 209–228 (1980).

    Google Scholar 

  77. Qudrat-Ullah, H. On the validation of system dynamics type simulation models. Telecommun. Syst. 51, 159–166 (2012).

    Google Scholar 

  78. Homer, J. B. Partial‐model testing as a validation tool for system dynamics (1983). Syst. Dyn. Rev. 28, 281–294 (2012).

    Google Scholar 

  79. Bennett, N. D. et al. Characterising performance of environmental models. Environ. Model. Softw. 40, 1–20 (2013).

    Google Scholar 

  80. Pianosi, F. et al. Sensitivity analysis of environmental models: a systematic review with practical workflow. Environ. Model. Softw. 79, 214–232 (2016).

    Google Scholar 

  81. R Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2013).

  82. Migrant Intake to Australia—Productivity Commission Inquiry Report (Australian Government Productivity Commission, 2016).

  83. Climateworks Australia, ANU, CSIRO & CoPS Pathways to Deep Decarbonisation: How Australia can Prosper in a Low Carbon World (ClimateWorks Australia, 2014).

  84. CSIRO Australian National Outlook 2019: Securing our Nation’s Future Prosperity (CSIRO, 2019); https://www.csiro.au/en/Showcase/ANO

  85. Mcdonald, P. F. & Temple, J. Immigration, Labour Supply and Per Capita Gross Domestic Product: Australia 2010–2050 (Australian Government Department of Immigration and Citizenship, 2010) .

  86. Schandl, H. et al. Decoupling global environmental pressure and economic growth: scenarios for energy use, materials use and carbon emissions. J. Clean. Prod. 132, 45–56 (2016).

    CAS  Google Scholar 

  87. Sobels, J. et al. Research into the Long-Term Physical Implications of Net Overseas Migration (National Institute of Labour Studies, Flinders University School of the Environment, CSIRO Sustainable Ecosystems, 2010).

  88. Syed, A., Melanie, J., Thorpe, S. & Penney, K. Australian Energy Projections to 2029–30 ABARE research report 10.02 (ABARES, 2010).

  89. Turner, G. M., Elliston, B. & Diesendorf, M. Impacts on the biophysical economy and environment of a transition to 100% renewable electricity in Australia. Energy Policy 54, 288–299 (2013).

    Google Scholar 

  90. Sachs, J., Schmidt-Traub, G., Kroll, C., Lafortune, G. & Fuller, G. SDG Index and Dashboards Report 2018 (Bertelsmann Stiftung, Sustainable Development Solutions Network, 2018).

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Acknowledgements

The authors thank J. West, H. Schandl and M. Stafford-Smith at the CSIRO for their informal advice, as well as the provision of data to support this study. We acknowledge the National Sustainable Development Council for their previous work in assessing Australia’s progress on the SDGs, which provided an important baseline for this study.

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Authors and Affiliations

  1. School of Biological, Earth and Environmental Sciences, PANGEA Centre, UNSW Sydney, Sydney, New South Wales, Australia

    Cameron Allen & Graciela Metternicht

  2. Sustainability Assessment Program, School of Civil and Environmental Engineering, UNSW Sydney, Sydney, New South Wales, Australia

    Thomas Wiedmann

  3. ISA, School of Physics A28, The University of Sydney, Sydney, New South Wales, Australia

    Thomas Wiedmann

  4. Millennium Institute, Washington, DC, USA

    Matteo Pedercini

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Contributions

C.A. led the research and undertook data collection, model calibration for iSDG–Australia, model adjustments, scenario development and simulations. M.P. developed the iSDG base model and provided advice and guidance data, model calibration and adjustment. G.M. and T.W. provided overall study supervision, advice and guidance regarding research framing, scenario development, methods and data sources. C.A. wrote the paper with inputs from G.M., T.W. and M.P.

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Correspondence to Cameron Allen.

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Allen, C., Metternicht, G., Wiedmann, T. et al. Greater gains for Australia by tackling all SDGs but the last steps will be the most challenging. Nat Sustain 2, 1041–1050 (2019). https://doi.org/10.1038/s41893-019-0409-9

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