Assessing the Additional Carbon Savings with Biofuel

Abstract

A recent study by DeCicco et al. (Climatic Change 138:667–680, 2016) claims that corn used for ethanol should not be considered to be inherently biogenically carbon-neutral because not all that corn was grown additional to the level otherwise. By assessing the extent of carbon neutrality of corn for ethanol using the reference point baseline approach and historical data that study concluded that the carbon intensity of US corn ethanol is 27% higher than that of gasoline. We develop a framework to determine the carbon neutrality of corn for ethanol by assessing the additional carbon uptake by crops using an anticipated baseline approach. We also apply this framework to determine the additional corn produced for ethanol and include the direct life cycle carbon emissions of only that portion of corn in the direct life cycle carbon intensity of corn ethanol. We implement this framework by integrating an economic model of the agricultural sector in the USA with a biogenic carbon model and life cycle analysis to quantify biogenic carbon uptake and direct life cycle emissions with and without corn ethanol expansion over the 2007–2027 period. We find that the combined biogenic carbon emissions and direct life cycle carbon emission intensity of corn ethanol (not including indirect land use related emissions) is 21% lower than gasoline. The lower value of this carbon intensity of corn ethanol compared with gasoline is robust to a wide range of parametric assumptions.

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  1. 1.

    https://afdc.energy.gov/data/10339

  2. 2.

    https://unfccc.int/documents?f%5B0%5D=year%3A2018

  3. 3.

    The estimate of DDGS co-product credit is obtained from Wang et al. [26]. Although the BEPAM does calculate the amount of DDGS used as a replacement for corn and soybean in livestock feed, it does not include other factors that determine the magnitude of the co-product carbon credit, such as impact on methane emissions due to enteric fermentation in animals and the impact on cattle lifetimes and feeding days and on animal performance. Since our focus here is primarily on isolating the effects of additional corn production on feedstock emissions to be included on the carbon intensity of corn ethanol and comparing our estimates with those in the literature, we rely on estimates of carbon emissions at other stages of ethanol production and the co-product credit on the existing literature.

References

  1. 1.

    Adams D, Alig R, Callaway J, Mccarl B, Winnett S (1996) The forest and agricultural sector optimization model (FASOM): model structure and policy applications: USDA Forest Service Pacific Northwest Research Station Research Paper

  2. 2.

    Adams D, Alig R, McCarl BA, Murray BC, Bair L, Depro B, ... & Chen CC (2005) FASOMGHG conceptual structure, and specification: documentation. Unpublished paper. College Station, TX: Texas A&M University, Department of Agricultural Economics

  3. 3.

    Beach RH, & McCarl BA (2010) US Agricultural and forestry impacts of the energy independence and security act: FASOM results and model description. (Final report prepared for US Environmental Protection Agency, Washington DC, 2010).

  4. 4.

    CARB (2014) Initial statement of reasons for rulemaking. Proposed Re-Adoption of the Low Carbon Fuel Standard. Appendix I: Detailed Analysis for Indirect Land Use Change. Staff Report, California Air Resources Board CARB,

  5. 5.

    Chen X, Huang H, Khanna M, Önal H (2014) Alternative transportation fuel standards: welfare effects and climate benefits. J Environ Econ Manag 67:241–257

    Article  Google Scholar 

  6. 6.

    Chen X, Önal H (2012) Modeling agricultural supply response using mathematical programming and crop mixes. Am J Agric Econ 94:674–686

    Article  Google Scholar 

  7. 7.

    De Kleine RD, Wallington TJ, Anderson JE, Kim HC (2017) Commentary on “carbon balance effects of US biofuel production and use,” by DeCicco et al.(2016). Clim Chang 144:111–119

    Article  Google Scholar 

  8. 8.

    DeCicco JM, Liu DY, Heo J, Krishnan R, Kurthen A, Wang L (2016) Carbon balance effects of US biofuel production and use Climatic Change 138:667-680

  9. 9.

    EU (2009) Directive 2009/28/EC of the European Parliament and of the Council of 23 April 2009 on the promotion of the use of energy from renewable sources and amending and subsequently repealing Directives 2001/77/EC and 2003/30/EC. Off J Eur Union. http://www.nezeh.eu/assets/media/fckuploads/file/Legislation/RED_23April2009.pdf

  10. 10.

    FAO (2007) FAOSTAT-FAO’s corporate database. Food and Agriculture Organization of the United Nations

    Google Scholar 

  11. 11.

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

    CAS  Article  PubMed Central  Google Scholar 

  12. 12.

    Hudiburg TW et al (2016) Impacts of a 32-billion-gallon bioenergy landscape on land and fossil fuel use in the US Nature. Energy 1:15005

    Google Scholar 

  13. 13.

    IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National Greenhouse Gas Inventories Programme, Eggleston H.S., Buendia L., Miwa K., Ngara T. and Tanabe K. (eds). Published: IGES, Japan.

  14. 14.

    Khanna M, Crago CL (2012) Measuring indirect land use change with biofuels: implications for policy. Ann Rev Resour Econ 4:161–184

    Article  Google Scholar 

  15. 15.

    Miao R, Khanna M, Huang H (2016) Responsiveness of crop yield and acreage to prices and climate. Am J Agric Econ 98:191–211. https://doi.org/10.1093/ajae/aav025

    Article  Google Scholar 

  16. 16.

    Searchinger TD (2010) Biofuels and the need for additional carbon. Environ Res Lett 5:024007

    Article  Google Scholar 

  17. 17.

    Searchinger T et al (2009) Fixing a critical climate accounting error. Science 326:527–528

    CAS  Article  Google Scholar 

  18. 18.

    Taheripour F, Zhao X, Tyner WE (2017) The impact of considering land intensification and updated data on biofuels land use change and emissions estimates Biotechnology for Biofuels 10:191

  19. 19.

    UNFCCC (2006) United Nations Framework Convention on Climate Change, updated UNFCCC reporting guidelines on annual inventories following incorporation of the provisions of decision 14/CP.11, report FCCC/SBSTA/2006/9.

  20. 20.

    US Grain Council (2012) A guide to distiller’s dried grains with solubles (DDGS) https://www.biofuelscoproducts.umn.edu/sites/biodieselfeeds.cfans.umn.edu/files/cfans_asset_417244.pdf

  21. 21.

    USEPA (2010) Regulation of fuels and fuel additives: changes to renewable fuel standard program: final rule Federal Register 75:14790

  22. 22.

    USEPA (2012) Science advisory board review of EPA’s accounting framework for biogenic CO2 emissions from stationary sources (2011). United States Environmental Protection Agency, Washington DC

    Google Scholar 

  23. 23.

    USEPA (2014) Framework for assessing biogenic CO2 emissions from stationary sources, Office of Air and Radiation Office of Atmospheric Programs. Climate Change Division, United States Environmental Protection Agency, Washington DC

    Google Scholar 

  24. 24.

    USEPA (2017) Draft science advisory board review of framework for assessing biogenic CO2 emissions from stationary sources (2014). USEPA, Washington DC

    Google Scholar 

  25. 25.

    USEPA (2018) Inventory of US greenhouse gas emissions and sinks: 1990–2016. United States Environmental Protection Agency, Washington, DC.

  26. 26.

    Wang M, Han J, Dunn JB, Cai H, Elgowainy A (2012) Well-to-wheels energy use and greenhouse gas emissions of ethanol from corn, sugarcane and cellulosic biomass for US use. Environ Res Lett 7:045905

    Article  Google Scholar 

  27. 27.

    Wang W, Dwivedi P, Abt R, Khanna M (2015) Carbon savings with transatlantic trade in pellets: accounting for market-driven effects. Environ Res Lett 10:114019

    Article  Google Scholar 

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Acknowledgments

The authors thank Cristina Canter and Zhangcai Qin from the Argonne National Laboratory for data and helpful suggestions for this research. This work was funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research under Award Number DE-SC0018420..

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Correspondence to Madhu Khanna.

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Khanna, M., Wang, W. & Wang, M. Assessing the Additional Carbon Savings with Biofuel. Bioenerg. Res. 13, 1082–1094 (2020). https://doi.org/10.1007/s12155-020-10149-0

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Keywords

  • Biogenic carbon intensity
  • Corn ethanol
  • Economic model
  • Dynamic optimization
  • Anticipated baseline approach
  • Life cycle carbon intensity