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Options for keeping the food system within environmental limits

Nature volume 562, pages 519–525 (2018)Cite this article

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Abstract

The food system is a major driver of climate change, changes in land use, depletion of freshwater resources, and pollution of aquatic and terrestrial ecosystems through excessive nitrogen and phosphorus inputs. Here we show that between 2010 and 2050, as a result of expected changes in population and income levels, the environmental effects of the food system could increase by 50–90% in the absence of technological changes and dedicated mitigation measures, reaching levels that are beyond the planetary boundaries that define a safe operating space for humanity. We analyse several options for reducing the environmental effects of the food system, including dietary changes towards healthier, more plant-based diets, improvements in technologies and management, and reductions in food loss and waste. We find that no single measure is enough to keep these effects within all planetary boundaries simultaneously, and that a synergistic combination of measures will be needed to sufficiently mitigate the projected increase in environmental pressures.

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Fig. 1: Present (2010) and projected (2050) environmental pressures on five environmental domains divided by food group.
Fig. 2: Impacts of reductions in food loss and waste, technological change, and dietary changes on global environmental pressures in 2050.
Fig. 3: Planetary option space.
Fig. 4: Combination and relative contributions of mitigation measures that simultaneously reduce environmental impacts below the mean values of the planetary-boundary range.

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Data availability

The data that support the findings of this study are available from the Oxford University Research Archive (ORA; https://ora.ox.ac.uk) at https://ora.ox.ac.uk/objects/uuid:d9676f6b-abba-48fd-8d94-cc8c0dc546a2.

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Acknowledgements

This research was funded by the EAT as part of the EAT–Lancet Commission on Healthy Diets from Sustainable Food Systems, and by the Wellcome Trust, Our Planet Our Health (Livestock, Environment and People (LEAP)), award number 205212/Z/16/Z. In addition, K.W. and D.M.-D. acknowledge support from the CGIAR Research Programs on Policies, Institutions, and Markets (PIM) and on Climate Change, Agriculture and Food Security (CCAFS). K.M.C. acknowledges support from the USDA National Institute of Food and Agriculture Hatch project HAW01136-H, managed by the College of Tropical Agriculture and Human Resources. J.F. thanks Bloomberg Philanthropies and USAID for support. B.L.B. acknowledges support from the European Union’s Horizon 2020 research and innovation programme under grant agreement 689150 SIM4NEXUS; the SUSTAg project; and the German Federal Minister of Education and Research (BMBF) under reference number FKZ 031B0170A. L.L. acknowledges support from MINECO, Spain, co-funded by European Commission ERDF (Ramon y Cajal fellowship, RYC-2016-20269). M.T. and M.J. thank FORMAS (grant 2016-00227). M.C. acknowledges a Balzan Award Prize and the Grand Challenge Curriculum at the University of Minnesota–Twin Cities. M.S. and H.C.J.G. acknowledge support from the Wellcome Trust, Our Planet Our Health (Livestock, Environment and People (LEAP)), award number 205212/Z/16/Z. P.S. acknowledges support from a British Heart Foundation Intermediate Basic Science Research Fellowship, FS/15/34/31656. M.R. thanks the British Heart Foundation, grant number 006/PSS/CORE/2016/OXFORD. J.R. acknowledges support from the ERC-2016-ADG 743080 (ERA).

Reviewer information

Nature thanks K. J. Boote, G. Robertson, P. Smith and the other anonymous reviewer(s) for their contribution to the peer review of this work.

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Authors and Affiliations

  1. Oxford Martin Programme on the Future of Food, Oxford Martin School, University of Oxford, Oxford, UK

    Marco Springmann & H. Charles J. Godfray

  2. Centre on Population Approaches for Non-Communicable Disease Prevention, Nuffield Department of Population Health, University of Oxford, Oxford, UK

    Marco Springmann, Peter Scarborough & Mike Rayner

  3. Natural Resources Science and Management, University of Minnesota, St Paul, MN, USA

    Michael Clark

  4. Environment and Production Technology Division, International Food Policy Research Institute (IFPRI), Washington, DC, USA

    Daniel Mason-D’Croz & Keith Wiebe

  5. CSIRO Agriculture and Food, Commonwealth Scientific and Industrial Research Organisation, St Lucia, Brisbane, Australia

    Daniel Mason-D’Croz & Mario Herrero

  6. Potsdam Institute for Climate Impact Research, Potsdam, Germany

    Benjamin Leon Bodirsky & Johan Rockström

  7. CEIGRAM/Agricultural Production, Universidad Politécnica de Madrid, Madrid, Spain

    Luis Lassaletta

  8. Environmental Systems Analysis Group, Wageningen University, Wageningen, The Netherlands

    Wim de Vries

  9. WWF International, Gland, Switzerland

    Sonja J. Vermeulen

  10. Hoffmann Centre for Sustainable Resource Economy, Chatham House, London, UK

    Sonja J. Vermeulen

  11. Department of Natural Resources and Environmental Management, University of Hawai’i at Manoa, Honolulu, HI, USA

    Kimberly M. Carlson

  12. Stockholm Resilience Centre, Stockholm University, Stockholm, Sweden

    Malin Jonell, Max Troell, Line J. Gordon, Brent Loken & Johan Rockström

  13. Beijer Institute of Ecological Economics, The Royal Swedish Academy of Sciences, Stockholm, Sweden

    Max Troell

  14. EAT, Oslo, Norway

    Fabrice DeClerck & Brent Loken

  15. Agricultural Biodiversity and Ecosystem Services, Bioversity International, Rome, Italy

    Fabrice DeClerck

  16. Department of Landscape Design and Ecosystem Management, Faculty of Agricultural and Food Sciences, American University of Beirut, Beirut, Lebanon

    Rami Zurayk

  17. Nitze School of Advanced International Studies (SAIS), Berman Institute of Bioethics, Johns Hopkins University, Baltimore, MD, USA

    Jess Fanzo

  18. Department of International Health of the Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA

    Jess Fanzo

  19. Department of Zoology, University of Oxford, Oxford, UK

    H. Charles J. Godfray

  20. Department of Ecology, Evolution and Behavior, University of Minnesota, St Paul, MN, USA

    David Tilman

  21. Bren School of Environmental Science and Management, University of California, Santa Barbara, CA, USA

    David Tilman

  22. Department of Epidemiology and Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, USA

    Walter Willett

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  1. Marco Springmann
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Contributions

M.S. designed the study, compiled the models, conducted the analysis, interpreted the results and wrote the manuscript. K.W., D.M.-D. and M.C. contributed data and model components for the food-systems model. B.L.B., L.L. and W.d.V. contributed data and model components for the analysis of nitrogen and phosphorus. S.J.V., M.H. and K.M.C. contributed data for the analysis of GHG emissions. M.J. and M.T. contributed data for the analysis of fish and seafood. W.W. designed the flexitarian diet and contributed to the discussion on the health aspects of dietary change. F.D. contributed to the discussion on the planetary boundary related to land use. L.J.G. and R.Z. contributed to the discussion on water use. P.S. and M.R. contributed to discussion on the health aspects of dietary change. B.L. facilitated discussions and contributed to the discussion on the planetary boundaries related to the food system. J.F. contributed to the discussion and background of the study. J.R., H.C.J.G. and D.T. contributed to discussion on the planetary boundaries related to the food system. All authors commented on the manuscript draft and approved the submission.

Corresponding author

Correspondence to Marco Springmann.

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The authors declare no competing interests.

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Extended data figures and tables

Extended Data Fig. 1 Reduction in environmental impacts when measures are combined.

Shown are combinations of all measures of medium ambition (comb(med)) and of all measures of high ambition (comb(high)). The mitigation measures include changes in food loss and waste (loss&waste), technological change (technology) and dietary change (diets) for a middle-of-the-road development pathway. The differences to development pathways that are more optimistic (higher income and lower population growth) and more pessimistic (lower income and higher population growth) are indicated by the uncertainty range around the markers (socio-econ).

Source data

Extended Data Fig. 2 Overview of major flows of phosphorus at the global scale.

The external acceptable phosphorus (P) input is determined by the acceptable long-term accumulation of phosphorus in the soil (P soil) and sediment (P sediment) at a phosphorus concentration in surface waters (P surface water) that equals a critical threshold. The phosphorus boundary is affected by the fraction of phosphorus that is taken up by humans (P human; frPuptake being the P-use efficiency, PUE, of the complete food chain, from mined phosphorus (P mine) to P intake) and the fraction of phosphorus excreted by humans (P waste) that is not recycled to land (1 − frPrec), which becomes a point source for water pollution. This phosphorus can only be stored in sediment at a given phosphorus-retention fraction (frPret,sed), while the recycled phosphorus can additionally be stored in soil (at a retention fraction frPret,soil). The critical phosphorus input (Pin(crit)) can be calculated as the sum of critical phosphorus retention in the soil and sediment, and a critical input to surface water (oceans) that is due to run-off and leaching. The Supplementary Information contains a full derivation of phosphorus flows and quantitative estimates of critical phosphorus inputs.

Source data

Extended Data Fig. 3 Planetary option space related to different control variables of nitrogen and yield-related feedback effects.

The control variables include nitrogen inputs related to synthetic fertilizers as used in the main analysis, and the more comprehensive measure of nitrogen surplus that accounts for all inputs and offtakes of nitrogen. The types of feedback effects include changes in nitrogen and phosphorus application associated with closing yield gaps by 75%, as modelled in the tech scenario for cropland use (main), and changes associated with closing yield gaps by 90%, as modelled in the tech+ scenario for cropland use (high yields). Colours and numbers indicate combinations that are below the lower bound of the planetary-boundary range (dark green, 1), below the mean value but above the minimum value (light green, 2), above the mean value but below the maximum (orange, 3), and above the maximum value (red, 4).

Source data

Extended Data Table 1 Scenarios of reductions in food loss and waste, technological change and dietary change
Full size table
Extended Data Table 2 Global food production in 2010 and 2050 differentiated by food group and step along the food chain
Full size table
Extended Data Table 3 Environmental footprints of food commodities (per weight of product)
Full size table
Extended Data Table 4 Reductions in environmental footprints (as percentages) resulting from technological changes by food group
Full size table
Extended Data Table 5 Food-based dietary recommendations for healthy, more plant-based (flexitarian) diets
Full size table
Extended Data Table 6 Decomposition of impacts of dietary scenarios
Full size table
Extended Data Table 7 Derivation of planetary-boundary values of the food system
Full size table

Supplementary information

Supplementary Information

This file contains Supplementary Methods which provide additional detail about the food systems model, the planetary boundary estimate for phosphorus application, and the nitrogen budget model used in a sensitivity analysis.

Reporting Summary

Supplementary Table 1

This file contains an overview of income and population changes in the socioeconomic development pathways.

Supplementary Table 2

This file contains estimates of global food consumption in the dietary scenarios.

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Springmann, M., Clark, M., Mason-D’Croz, D. et al. Options for keeping the food system within environmental limits. Nature 562, 519–525 (2018). https://doi.org/10.1038/s41586-018-0594-0

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