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Meeting the EAT-Lancet ‘healthy’ diet target while protecting land and water resources

Nature Sustainability volume 7, pages 1651–1661 (2024)Cite this article

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Abstract

Healthy diets are known for their co-benefits of reducing environmental impacts and enabling the same agricultural resources to feed a larger human population. The EAT-Lancet (healthy reference) diet allows for compound benefits to human health and the ecosystem. It is unclear, however, to what extent the requirements of the EAT-Lancet diet may be sustainably met at the global scale. Here we combine a spatially distributed agro-hydrological model with a linear optimization analysis to relocate crops, minimizing, at the country scale, the irrigation-water consumption while improving the worldwide achievement of the EAT-Lancet nutritional goals. To that end, we define six dietary scenarios based on country-specific dietary habits from religion-related traditions, and existing livestock production systems, maintaining the same agricultural trade patterns (import–export relations). Our results suggest that an optimized global cropland allocation, and an adjustment in trade flows, would allow the global population to be fed with the EAT-Lancet diet, with a global reduction of the cultivated area of 37–40%, irrigation-water consumption of 78% (±3%), and unsustainably irrigated areas of 22%. The adoption of the EAT-Lancet diet increases the global food trade share of global food production, measured in kilocalories, from 25% (baseline) to 36% (±2%).

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Fig. 1: Crop production by diet scenario.
Fig. 2: Average SP per country, grouped by SDI for the diet scenario D100.
Fig. 3: Number of months in blue water scarcity conditions mapped at 5 arcmin resolution and global irrigated area under blue water scarcity.
Fig. 4: The country-specific cost of diet in each diet scenario across the 153 countries in the analysis (n = 153) in 2017 international dollars converted from local currency units using purchasing power parity, by major geographic regions.

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Data availability

All data supporting the study have been sourced from freely and publicly available sources, which are cited within the main text or Supplementary Information.

Code availability

The code for the optimization process is available via Zenodo at https://doi.org/10.5281/zenodo.13886864 (ref. 70).

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Acknowledgements

C.G., N.G.,D.D.C. and M.C.R. acknowledge support from EC-NextGeneration EU EP RETURN (CUP D43C22003030002). C.G., D.D.C., M.S. and M.C.R. acknowledge support from EC-H2020-PRIMA AG-WAMED (CUP D43C21000410001). N.G., L.R., D.D.C. and M.C.R. acknowledge support from EC-H2020-PRIMA NEXUS-NESS (CUP D49J21005050006). P.D. was funded by the USDA Hatch Multistate project no. W5190 capacity fund.

Author information

Authors and Affiliations

  1. Department of Civil and Environmental Engineering, Politecnico di Milano, Milan, Italy

    Maria Cristina Rulli, Martina Sardo, Livia Ricciardi, Camilla Govoni, Nikolas Galli & Davide Danilo Chiarelli

  2. School of Agriculture and Food Sustainability, University of Queensland, Gatton, Queensland, Australia

    Adam M. Komarek

  3. Department of Environmental Science, Policy, and Management, University of California, Berkeley, Berkeley, CA, USA

    Paolo D’Odorico

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Contributions

M.C.R. and P.D. have conceptualized and supervised the study. M.C.R., M.S., L.R., C.G., N.G., D.D.C., A.M.K. and P.D. contributed to the development of methodology, execution of formal analysis, writing, review and editing of the paper. A.M.K., N.G., C.G., L.R. and M.S. have contributed to the visuals.

Corresponding authors

Correspondence to Maria Cristina Rulli or Martina Sardo.

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Competing interests

The authors declare no competing interests.

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Nature Sustainability thanks Michalis Hadjikakou 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 Soybean global trade flows in the Baseline (a) and in reallocation scenarios (b–g).

Figures S25–S31 show the ‘final trade’ of commodities for the crop macro-groups (tonnes), for the baseline and the EAT-Lancet diet scenarios, considering trade flows as reported by FAOSTAT’s trade matrix (FAO, 2020). The detailed final trade flows and imports and exports quantities for each country are reported respectively in Supplementary Tables 4–6, while final trade flows and imports and exports quantities, calculated using the method from Kastner et al.32, are reported respectively in Supplementary Tables 7–9.

Extended Data Fig. 2 Resulting number of countries per each SP interval.

6 intervals of SP values have been considered (SP < 0.2; 0.2 ≤ SP < 0.5; 0.5 ≤ SP < 0.75; 0.75 ≤ SP < 0.85; 0.85 ≤ SP < 0.95; SP = 1)—and each diet scenario, compared with the current scenario In the small states or territories of Hong Kong, Lithuania and Macau and the islands of Comoros, Kiribati, Samoa and Maldives the algorithm allocated no harvested area (resulting in SP = 0), because of the low availability of cropland suitable for crop reallocation. SP is the degree of satisfaction of the EAT-Lancet diet requirement by relocated crop production, it has been assessed per country, scenario and crop by dividing the relocated domestic crop production by the crop production required by the EAT-Lancet diet (SI, Section S2).

Extended Data Fig. 3

Percentage of population satisfied by the EAT- Lancet diet in each country, by the new domestic food supply, in the diet scenario D40. Grey circle line indicates 100% of population satisfaction.

Extended Data Fig. 4 Food group’s share of diet cost in each dietary scenario by geographic region.

Food group’s share is calculated as the summation over all countries in a geographic region for a specific food group’s cost per person per day divided by the summation over all countries in a geographic region for the total diet cost per person per day.

Extended Data Table 1 Summary of the different diet scenarios analysed
Full size table
Extended Data Table 2 New global crop production (million tonnes) required by the EAT-Lancet diet, for each crop macro-group, for each diet scenario and the baseline
Full size table
Extended Data Table 3 Actual relocated crop production (million tonnes) and SP values (%) in parenthesis, for each crop macro-group, for each diet scenario and for the baseline
Full size table
Extended Data Table 4 Total population satisfied in each diet scenario, at the global level, by domestic crop supply, considering a total global average population of 7 490 million, for the years 2015–2019
Full size table
Extended Data Table 5 Country-specific cost (in $ purchasing power parity from 2017 per person per day) of dietary scenarios
Full size table
Extended Data Table 6 Correspondence between the EAT-Lancet diet2 and the Healthy Diet Basket (HDB)
Full size table

Supplementary information

Supplementary Information

Supplementary Figs. 1–43, Tables 1–6, Methods and references.

Reporting Summary

Supplementary Data 1

Correction factors for SPAM yields.

Supplementary Data 2

Crop production demand required by the EAT-Lancet dietary guidelines (tonnes).

Supplementary Data 3

Percentage trade flow variations from the baseline.

Supplementary Data 4

Total exports (tonnes) per crop macro-group and country that are actually satisfied by crop reallocation.

Supplementary Data 5

Country variation in blue water consumption compared to the total BW consumed in the baseline (%).

Supplementary Data 6

Hectares of irrigated harvested area interested by water scarcity (WS).

Supplementary Data 7

Country variation in rainfed harvested area compared to the total irrigated area in the baseline (%).

Supplementary Data 8

Country variation in irrigated harvested area per crop-group, compared to the irrigated area in the baseline.

Supplementary Data 9

Country variation in rainfed harvested area per crop-group, compared to the irrigated area in the baseline.

Supplementary Data 10

Satisfied population percentage.

Supplementary Data 11

Simpson Index per country and scenario.

Supplementary Data 12

Shannon Index and Effective Number of Crop Species per country and scenario.

Supplementary Data 13

Country-specific cost (in $ purchasing power parity from 2017 per person per day) of dietary scenarios.

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Rulli, M.C., Sardo, M., Ricciardi, L. et al. Meeting the EAT-Lancet ‘healthy’ diet target while protecting land and water resources. Nat Sustain 7, 1651–1661 (2024). https://doi.org/10.1038/s41893-024-01457-w

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