Abstract
Bioenergy is a key option in climate change mitigation scenarios. Growing perennial grasses on recently abandoned cropland is a near-term strategy for gradual bioenergy deployment with reduced risks for food security and the environment. However, the extent of global abandoned cropland, bioenergy potentials and management requirements are unclear. Here we integrate satellite-derived land cover maps with a yield model to investigate the land–energy–water nexus of global bioenergy potentials. We identified 83 million hectares of abandoned cropland between 1992 and 2015, corresponding to 5% of today’s cropland area. Bioenergy potentials are 6–39 exajoules per year (11–68% of today’s bioenergy demand), depending on multiple local and management factors. About 20 exajoules per year can be achieved by increasing today’s global cropland area and water use by 3% and 8%, respectively, and without production inside biodiversity hotspots or irrigation in water-scarce areas. The consideration of context-specific practices and multiple environmental dimensions can mitigate trade-offs of bioenergy deployment.
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Data availability
Datasets used in this analysis are publicly available from the references provided within the paper. Other data supporting the findings of this study are available from the corresponding author on reasonable request. Source data are provided with this paper.
Code availability
Custom code used in this analyses is available at https://github.com/janjsn/lew_nexus_ac_bioenergy.
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Acknowledgements
The support of the Norwegian Research Council is acknowledged through the projects Bio4Fuels (project no. 257622), BioPath (project no. 293434) and MitiStress (project no. 286773). We thank B. Huang, X. Hu, H. Muri, D. Moran and C. Iordan for discussions regarding spatial data analysis. Additionally, we thank P. Chu for language editing. We gratefully acknowledge the provision of land cover data by ESA CCI-LC, GAEZ and SSP data by IIASA, lower heating values by Phyllis2, physical water scarcity data and cropland inventories by FAO, GPWv4 data and Panoply 4 by NASA and biodiversity hotspots data70.
Author information
Authors and Affiliations
Contributions
All authors designed the study, collected the data and analysed the results. J.S.N. developed custom code and generated all results and figures. J.S.N. wrote the manuscript with contributions from O.C. and F.C.
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The authors declare no competing interests.
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Peer review information Nature Sustainability thanks John Campbell, Katherine Zipp 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 Bioenergy potentials on abandoned cropland with a mixed management distribution based on existing yield gaps.
Results refer to present day climate with optimal crop allocation. Figures describe the agricultural management intensity distribution (a), global bioenergy potentials (b-c), bioenergy yields (d-e), and productivity distributions (f-g) for abandoned cropland (wide bars) and abandoned cropland outside biodiversity hotspots (thin bars). Figures (b, d, f), and (c, e, g) refer to rain-fed and mixed water supply, respectively. Average yields in (f) and (g) refer to only productive areas. Maps are shown at 5 arc minutes and 1 degree for (a) and (b-e), respectively (for improved visualization).
Extended Data Fig. 2 Spatial explicit changes in bioenergy potentials under future climatic conditions relative to present day.
Maps describe changes (%) in 2050 for RCP4.5 (a) and RCP8.5 (b), and in 2080 for RCP4.5 (c) and RCP8.5 (d). Results refer to optimal crop allocation, high management intensity, and rain-fed water supply. Crop allocation is re-optimized under each future climate projection. Maps are shown at one-degree resolution (aggregated for visualization purposes).
Extended Data Fig. 3 Global bioenergy potentials under climate change.
Bioenergy potentials (EJ year−1) on abandoned cropland are shown for 2050 and 2080 under RCP4.5 and RCP8.5 for a set of different constraints. Land availability is constrained by consideration of abandoned cropland with or without (thinner bars) biodiversity hotspots. Three agricultural management intensity levels (low, medium and high) and three water supply levels (rain-fed, irrigated and mixed) are considered. Specific contributions from irrigated areas and individual crops to total potentials are shown.
Extended Data Fig. 4 Spatially explicit water withdrawals and blue water footprint of irrigated bioenergy potentials on abandoned cropland.
Maps describe present day characteristics for two agricultural management intensities (medium, high), with optimal energy-based crop allocation per grid cell. Water withdrawals are given as million m3 year−1, and blue water footprint as m3 GJ−1. Maps are shown at one-degree resolution (aggregated for visualization purposes).
Extended Data Fig. 5 Comparison of bioenergy potentials with future projections.
Bioenergy potentials on abandoned cropland (optimal crop allocation), relative to median projected primary bioenergy demand in 2050 across different SSPs in top-down Integrated Assessment Models (%). Land availability for bioenergy production is constrained by consideration of abandoned cropland with or without biodiversity hotspots. Three agricultural management intensity levels (low, medium and high) and three water supply levels (rain-fed, irrigated and mixed) are considered. Individual figures refer to (a) bioenergy potentials at present day relative to median projected demand in 1.9 W m−2 scenarios, and (b) bioenergy potentials in 2050 for RCP4.5 relative to median projected demand in 4.5 W m−2 scenarios. SSP3 is not shown in a, as no models could reach the 1.5 °C climate target.
Supplementary information
Supplementary Information
Supplementary Figs. 1–5, Texts 1–3 and Tables 1–4.
Source data
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Næss, J.S., Cavalett, O. & Cherubini, F. The land–energy–water nexus of global bioenergy potentials from abandoned cropland. Nat Sustain 4, 525–536 (2021). https://doi.org/10.1038/s41893-020-00680-5
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DOI: https://doi.org/10.1038/s41893-020-00680-5
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