Article

Greenhouse gas emission curves for advanced biofuel supply chains

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Abstract

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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References

  1. 1.

    Collins, M. et al. in IPCC Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 1029–1136 (Cambridge Univ. Press, Cambridge, 2013).

  2. 2.

    Clarke, L. et al. in Climate Change 2014: Mitigation of Climate Change (eds Edenhofer, O. et al.) 413–510 (Cambridge Univ. Press, Cambridge, 2014).

  3. 3.

    Wise, M. et al. Implications of limiting CO2 concentrations for land use and energy. Science 324, 1183–1186 (2009).

  4. 4.

    IEA World Energy Outlook 2014 (OECD/IEA, 2014).

  5. 5.

    Kriegler, E. et al. The role of technology for achieving climate policy objectives: Overview of the EMF 27 study on global technology and climate policy strategies. Climatic Change 123, 353–367 (2014).

  6. 6.

    Rose, S. K. et al. Bioenergy in energy transformation and climate management. Climatic Change 123, 477–493 (2014).

  7. 7.

    Sorda, G., Banse, M. & Kemfert, C. An overview of biofuel policies across the world. Energy Policy 38, 6977–6988 (2010).

  8. 8.

    Leemans, R., van Amstel, A., Battjes, C., Kreileman, E. & Toet, S. The land cover and carbon cycle consequences of large scale utilizations of biomass as an energy source. Glob. Environ. Change 6, 556–563 (1996).

  9. 9.

    Kartha, S. in Bioenergy and Agriculture: Promises and Challenges (eds Hazel, P. & Pachauri, R. K.) Ch. 4 (International Food Policy Research Institute, 2006).

  10. 10.

    Sustainable Biofuels: Prospects and Challenges 37–48 (The Royal Society, 2008).

  11. 11.

    Gallagher, E. The Gallagher Review of the Indirect Effects of Biofuels Production (The Renewable Fuels Agency, 2008).

  12. 12.

    Searchinger, T. et al. Use of U.S. croplands for biofuels increases greenhouse gases through emissions from land use change. Science 319, 1238–1240 (2008).

  13. 13.

    Hoefnagels, R., Smeets, E. & Faaij, A. Greenhouse gas footprints of different biofuel production systems. Renew. Sustain. Energy Rev. 14, 1661–1694 (2010).

  14. 14.

    Laborde, D. Assessing the Land Use Change Consequences of European Biofuel Policies Report no. S12.580403 (IFPRI, 2011).

  15. 15.

    Wicke, B., Verwij, P., van Meijl, H., van Vuuren, D. & Faaij, A. P. C. Indirect land use change: review of existing models and strategies for mitigation. Biofuels 3, 87–100 (2012).

  16. 16.

    Lamers, P. & Junginger, M. The ‘debt’ is in the detail: A synthesis of recent temporal forest carbon analyses on woody biomass for energy. Biofuels Bioprod. Bior. 7, 373–385 (2013).

  17. 17.

    Plevin, R. J., Beckman, J., Golub, A. A., Witcover, J. & O’Hare, M. Carbon accounting and economic model uncertainty of emissions from biofuels-induced land use change. Environ. Sci. Technol. 49, 2656–2664 (2015).

  18. 18.

    Chum, H. et al. in IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation (eds Edenhofer, O. et al.) Ch. 2 (Cambridge University Press, Cambridge, 2011).

  19. 19.

    Popp, A. et al. Land-use futures in the shared socio-economic pathways. Glob. Environ. Change 42, 331–345 (2017).

  20. 20.

    Gibbs, H. K. et al. Carbon payback times for crop-based biofuel expansion in the tropics: the effects of changing yield and technology. Environ. Res. Lett. 3, 34001 (2008).

  21. 21.

    Elshout, P. M. F. et al. Greenhouse-gas payback times for crop-based biofuels. Nat. Clim. Change 5, 604–610 (2015).

  22. 22.

    Albanito, F. et al. Carbon implications of converting cropland to bioenergy crops or forest for climate mitigation: A global assessment. GCB Bioenerg. 8, 81–95 (2016).

  23. 23.

    Fargione, J., Hill, J., Tilman, D., Polasky, S. & Hawthorne, P. Land clearing and the biofuel carbon debt. Science 319, 1235–1238 (2008).

  24. 24.

    Creutzig, F. et al. Bioenergy andclimate change mitigation: An assessment. |GCB Bioenerg 7, 916–944 (2015).

  25. 25.

    Schauberger, B. et al. Consistent negative response of US crops to high temperatures in observations and crop models. Nat. Commun. 8, 13931 (2016).

  26. 26.

    Lobell, D. B. & Field, C. B. Global scale climate–crop yield relationships and the impacts of recent warming. Environ. Res. Lett. 2, 14002 (2007).

  27. 27.

    Long, S. P., Ainsworth, E. A., Leakey, A. D. B., Ort, D. R. & No, J. Food for thought: Lower-than-expected crop yield stimulation with rising CO2 concentrations. 312, 1918–1921 (2006). 

  28. 28.

    Urban, D., Roberts, M. J., Schlenker, W. & Lobell, D. B. Projected temperature changes indicate significant increase in interannual variability of U.S. maize yields: A Letter. Climatic Change 112, 525–533 (2012).

  29. 29.

    Ray, D. K., Gerber, J. S., MacDonald, G. K. & West, P. C. Climate variation explains a third of global crop yield variability. Nat. Commun. 6, 5989 (2015).

  30. 30.

    Rosenzweig, C. et al. Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison. Proc. Natl Acad. Sci. USA 111, 3268–3273 (2014).

  31. 31.

    Gingrich, S. et al. Exploring long-term trends in land use change and aboveground human appropriation of net primary production in nine European countries. Land Use Policy 47, 426–438 (2015).

  32. 32.

    Challinor, A. J. et al. A meta-analysis of crop yield under climate change and adaptation. Nat. Clim. Change 4, 287–291 (2014).

  33. 33.

    Lesk, C., Rowhani, P. & Ramankutty, N. Influence of extreme weather disasters on global crop production. Nature 529, 84–87 (2016).

  34. 34.

    Friend, A. et al. Carbon residence time dominates uncertainty in terrestrial vegetation responses to future climate and atmospheric CO2. Proc. Natl Acad. Sci. USA 111, 3280–3285 (2014).

  35. 35.

    Müller, C. et al. Implications of climate mitigation for future agricultural production. Environ. Res. Lett. 10, 125004 (2015).

  36. 36.

    Müller, C. et al. Global Gridded Crop Model evaluation: benchmarking, skills, deficiencies and implications. Geosci. Model Dev. Discuss. 1–39 (2016).

  37. 37.

    Tavoni, M. & Socolow, R. Modeling meets science and technology: an introduction to a special issue on negative emissions. Climatic Change 118, 1–14 (2013).

  38. 38.

    Daioglou, V., Wicke, B., Faaij, A. P. C. & van Vuuren, D. P. Competing uses of biomass for energy and chemicals: Implications for long-term global CO2 mitigation potential. GCB Bioenergy 7, 1321–1334 (2015).

  39. 39.

    Malins, C., Searle, S. & Baral, A. A Guide for the Perplexed to the Indirect Effects of Biofuels Production (International Council on Clean Transportation, 2014).

  40. 40.

    Gohin, A. Assessing the land use changes and greenhouse gas emissions of biofuels: elucidating the crop yield effects. Land Econ. 90, 575–586 (2014).

  41. 41.

    European Union Directive 2015/1513 L239, 29 (European Commission, 2015).

  42. 42.

    IPCC 2006 Guidelines for National Greenhouse Gas Inventories (National Greenhouse Gas Inventories Programme, IGES, 2006).

  43. 43.

    European Parliament. Directive 2009/28/EC of the European Parliament and of the Council of 23 April 2009. Off. J. Eur. Union 140, 16–62 (2009).

  44. 44.

    Renewable Fuel Standard Program (RFS2) Regulatory Impact Analysis (US Environmental Protection Agency, 2010).

  45. 45.

    Fearnside, P. M. Why a 100-year time horizon should be used for global warming mitigation calculations. Mitig. Adapt. Strateg. Glob. Change 7, 19–30 (2002).

  46. 46.

    ICF Lifecycle Greenhouse Gas Emissions due to Increased Biofuel Production—Methods and Approaches to Account for Lifecycle Greenhouse Gas Emissions from Biofuels Production Over Time (US EPA, 2009).

  47. 47.

    Humpenöder, F. et al. Investigating afforestation and bioenergy CCS as climate change mitigation strategies. Environ. Res. Lett. 9, 64029 (2014).

  48. 48.

    Slade, R., Bauen, A. & Gross, R. Global bioenergy resources. Nat. Clim. Change 4, 99–105 (2014).

  49. 49.

    Stehfest, E. et al. Integrated Assessment of Global Environmental Change with IMAGE 3.0: Model Description and Policy Applications (PBL Netherlands Environmental Assessment Agency, 2014).

  50. 50.

    Beringer, T., Lucht, W. & Schaphoff, S. Bioenergy production potential of global biomass plantations under environmental and agricultural constraints. GCB Bioenergy 3, 299–312 (2011).

  51. 51.

    Müller, C. et al. Drivers and patterns of land biosphere carbon balance reversal. Environ. Res. Lett. 11, 44002 (2016).

  52. 52.

    Dellink, R., Chateau, J., Lanzi, E. & Magné, B. Long-term economic growth projections in the shared socioeconomic pathways. Glob. Environ. Chang. 42, 200–214 (2017).

  53. 53.

    Samir, K. & Lutz, W. The human core of the shared socioeconomic pathways: Population scenarios by age, sex and level of education for all countries to 2100. Glob. Environ. Change 42, 181–192 (2017).

  54. 54.

    O’Neill, B. C. et al. The roads ahead: Narratives for shared socioeconomic pathways describing world futures in the 21st century. Glob. Environ. Change 42, 169–180 (2017).

  55. 55.

    van Vuuren, D. P. et al. Energy, land-use and greenhouse gas emissions trajectories under a green growth paradigm. Glob. Environ. Change 42, 237–250 (2017).

  56. 56.

    Banse, M. et al. Global impact of multinational biofuel mandates on land use, feedstock prices, international trade and land-use greenhouse gas emissions. Landbauforschung 64, 59–72 (2014).

  57. 57.

    Hoefnagels, R., Smeets, E. M. W. & Faaij, A. Greenhouse gas footprints of different biofuel production systems. Renew. Sustain. Energy Rev. 14, 1661–1694 (2010).

  58. 58.

    Cherubini, F. GHG balances of bioenergy systems - Overview of key steps in the production chain and methodological concerns. Renew. Energy 35, 1565–1573 (2010).

  59. 59.

    Haberl, H. et al. Correcting a fundamental error in greenhouse gas accounting related to bioenergy. Energy Policy 45, 18–23 (2012).

  60. 60.

    Wise, M. et al. An approach to computing marginal land use change carbon intensities for bioenergy in policy applications. Energy Econ. 47, 307–318 (2015).

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Author information

Affiliations

  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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Contributions

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