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Food–energy–water implications of negative emissions technologies in a +1.5 °C future

Nature Climate Change volume 10, pages 920–927 (2020)Cite this article

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Abstract

Scenarios for meeting ambitious climate targets rely on large-scale deployment of negative emissions technologies (NETs), including direct air capture (DAC). However, the tradeoffs between food, water and energy created by deploying different NETs are unclear. Here we show that DAC could provide up to 3 GtCO2 yr−1 of negative emissions by 2035—equivalent to 7% of 2019 global CO2 emissions—based on current-day assumptions regarding price and performance. DAC in particular could exacerbate demand for energy and water, yet it would avoid the most severe market-mediated effects of land-use competition from bioenergy with carbon capture and storage and afforestation. This could result in staple food crop prices rising by approximately fivefold relative to 2010 levels in many parts of the Global South, raising equity concerns about the deployment of NETs. These results highlight that delays in aggressive global mitigation action greatly increase the requirement for DAC to meet climate targets, and correspondingly, energy and water impacts.

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Fig. 1: Side effects of limiting warming to below 1.5 °C without DAC available.
Fig. 2: Positive and negative CO2 emissions by sector and region.
Fig. 3: Food crop price and global land-use impacts of NET deployment.
Fig. 4: Water use and displacement of emissions abatement of large-scale DAC.
Fig. 5: Effects of DAC on primary energy consumption.

Data availability

To enable replication of our work, the input files required to run our scenarios, as well as python scripts used in generating figures for this study, may be downloaded at https://doi.org/10.18130/V3/JKJAOG55. Source data are provided with this paper.

Code availability

The full model is available for download at https://github.com/JGCRI/gcam-core.

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Acknowledgements

We thank K. Holcomb of the UVA Advanced Research Computing Service for her assistance with setting up GCAM on UVA’s high-performance computing cluster. We also thank the University of Virginia’s Office of the Vice President for Research–3 Cavaliers Program, the University of Virginia Environmental Resilience Institute and the Joint Global Change Research Institute Global Technology Strategy Program for supporting this work.

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Authors and Affiliations

  1. Department of Engineering Systems and Environment, University of Virginia, Charlottesville, VA, USA

    Jay Fuhrman & Andres F. Clarens

  2. Joint Global Change Research Institute, University of Maryland and Pacific Northwest National Laboratory, College Park, MD, USA

    Haewon McJeon & Pralit Patel

  3. Department of Environmental Sciences, University of Virginia, Charlottesville, VA, USA

    Scott C. Doney

  4. Batten School of Leadership and Public Policy, University of Virginia, Charlottesville, VA, USA

    William M. Shobe

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Contributions

J.F., H.M., S.C.D., W.M.S. and A.F.C. led the study design and the writing of the paper, J.F., H.M. and P.P. conducted the modelling.

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Correspondence to Andres F. Clarens.

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Extended data

Extended Data Fig. 1 Projected NET deployments to limit global warming to 1.5 °C.

Modelling results underpinning the IPCC’s Special Report on Global Warming of 1.5 °C. The thicker coloured lines show the median projected deployments of the individual afforestation, BECCS, and DAC technologies, for those model results which report them. The thin grey lines represent the combined negative emissions deployment for individual scenarios. The grey shading represents the 68% confidence interval (+/− 1 standard deviation) on combined negative emissions deployment.

Source data

Extended Data Fig. 2 Effect of representative high and low overshoot of the 1.5 °C end-of-century temperature target.

a, Temperature anomalies from pre-industrial, b, CO2 concentrations, and c, emissions trajectories. Historical data for emissions, CO2 concentrations, and temperature are indicated by grey lines. The “no climate policy scenario” is the GCAM reference scenario. After the year 2020, CO2 emissions pathways represent imposed model constraints which result in the CO2 concentration and temperature trajectories reported.

Source data

Supplementary information

Supplementary Information

Supplementary Figs. 1–16, discussion and Tables 1 and 2.

Source data

Source Data Fig. 1

Numerical source data for Fig. 1.

Source Data Fig. 2

Numerical source data for Fig. 2.

Source Data Fig. 3

Numerical source data for Fig. 3.

Source Data Fig. 4

Numerical source data for Fig. 4.

Source Data Fig. 5

Numerical source data for Fig. 5.

Source Data Extended Data Fig. 1

Numerical source data for Extended Data Fig. 1.

Source Data Extended Data Fig. 2

Numerical Source data for Extended Data Fig. 2.

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Fuhrman, J., McJeon, H., Patel, P. et al. Food–energy–water implications of negative emissions technologies in a +1.5 °C future. Nat. Clim. Chang. 10, 920–927 (2020). https://doi.org/10.1038/s41558-020-0876-z

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