Greenhouse gas emission curves for advanced biofuel supply chains

  • Nature Climate Changevolume 7pages920924 (2017)
  • doi:10.1038/s41558-017-0006-8
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Most climate change mitigation scenarios that are consistent with the 1.5–2 °C target rely on a large-scale contribution from biomass, including advanced (second-generation) biofuels. However, land-based biofuel production has been associated with substantial land-use change emissions. Previous studies show a wide range of emission factors, often hiding the influence of spatial heterogeneity. Here we introduce a spatially explicit method for assessing the supply of advanced biofuels at different emission factors and present the results as emission curves. Dedicated crops grown on grasslands, savannahs and abandoned agricultural lands could provide 30 EJBiofuel yr−1 with emission factors less than 40 kg of CO2-equivalent (CO2e) emissions per GJBiofuel (for an 85-year time horizon). This increases to 100 EJBiofuel yr−1 for emission factors less than 60 kgCO2e GJBiofuel −1. While these results are uncertain and depend on model assumptions (including time horizon, spatial resolution, technology assumptions and so on), emission curves improve our understanding of the relationship between biofuel supply and its potential contribution to climate change mitigation while accounting for spatial heterogeneity.

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Author information


  1. PBL Netherlands Environmental Assessment Agency, the Hague, The Netherlands

    • Vassilis Daioglou
    • , Jonathan C. Doelman
    • , Elke Stehfest
    •  & Detlef P. van Vuuren
  2. Copernicus Institute of Sustainable Development, Utrecht University, Utrecht, The Netherlands

    • Vassilis Daioglou
    • , Birka Wicke
    •  & Detlef P. van Vuuren
  3. Potsdam Institute for Climate Impact Research, Potsdam, Germany

    • Christoph Müller
  4. Energy Sustainability Research Institute Groningen (ESRIG), University of Groningen, Groningen, The Netherlands

    • Andre Faaij


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V.D., J.C.D, E.S. B.W., A.F. and D.P.v.V developed the methodological framework. J.C.D. conducted the IMAGE-LPJmL model simulations. E.S. and C.M. checked the consistency of carbon stocks and flows in IMAGE-LPJmL. V.D. calculated the EFs and PBPs. All authors contributed to writing the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Vassilis Daioglou.

Supplementary information

  1. Supplementary Information

    Supplementary Notes, Supplementary Results (including Supplementary Figures 1–4, Supplementary Tables 1–5), and Supplementary References