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An economic evaluation of alternative biofuel deployment scenarios in the USA

Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States

Topical Section: Bioenergy and Biofuel

Energy market conditions have shifted dramatically since the USA renewable fuel standards (RFS1 in 2005; RFS2 in 2007) were enacted. The USA has transitioned from an increasing dependence on oil imports to abundant domestic oil production. In addition, increases in the use of ethanol, the main biofuel currently produced in the USA, is now limited by the blend wall constraint. Given this, the current study evaluates alternative biofuel deployment scenarios in the USA, accounting for changes in market conditions. The analysis is performed with a general equilibrium model that reflects the structure of the USA biofuel market as the transition to advanced biofuels begins. Results suggest that ethanol consumption would increase, albeit slowly, if current biofuel deployment rates of about 10% are maintained as persistently lower oil prices lead to a gradual increase in the consumption of liquid transportation fuels. Without the blend wall constraint, this study finds that the overall economic impact of a full implementation of the USA RFS2 policy is largely neutral before 2022. However, the economic impacts become slightly negative under the blend wall constraint since more expensive bio-hydrocarbons are needed to meet the RFS2 mandates. Results for a scenario with reduced advanced biofuel deployment based on current policy plans show near neutral economic impacts up to 2027. This scenario is also consistent with another scenario where the volume of bio-hydrocarbons deployed is reduced to adjust for its higher cost and energy content relative to deploying the mandated RFS2 advanced biofuel volumes as ethanol. The important role of technological change is demonstrated under pioneer and accelerated technology scenarios, with the latter leading to neutral or positive economic effects up to 2023 under most blend wall scenarios. All scenarios evaluated in this study are found to have positive long-term benefits for the USA economy.
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Keywords biofuels; oil market shift; economic impacts; blend wall; technology learning

Citation: Gbadebo Oladosu. An economic evaluation of alternative biofuel deployment scenarios in the USA. AIMS Energy, 2017, 5(3): 374-396. doi: 10.3934/energy.2017.3.374


  • 1. Bracmort, Kelsi (2016) The Renewable Fuel Standard (RFS): Waiver Authority and Modification of Volumes. Congressional Service Report 7-5700. Available from: https://www.fas.org/sgp/crs/misc/R44045.pdf.
  • 2. United States Department of Energy-DOE (2011) "US billion-ton update: Biomass supply for a bioenergy and bioproducts Industry. RD Perlack and BJ Stokes (Leads)." ORNL/TM-2011/224. Oak Ridge National Laboratory. Available from: http://www1.eere.energy.gov/biomass/pdfs/ billion_ton_update.Pdf.
  • 3. U.S. Department of Energy 2016. 2016 Billion-Ton Report: Advancing Domestic Resources for a Thriving Bioeconomy, Volume 1: Economic Availability of Feedstocks. M. H. Langholtz, B. J. Stokes, and L. M. Eaton (Leads), ORNL/TM-2016/160. Oak Ridge National Laboratory, Oak Ridge, TN. 448p. Available from: http://energy.gov/sites/prod/files/2016/07/f33/2016_ billion_ton_report_0.pdf.
  • 4. National Research Council-NRC (2010) Limiting the magnitude of future climate change. The National Academies Press, Washington, DC.
  • 5. Kahouli S (2011) "Effects of technological learning and uranium price on nuclear cost: preliminary insights from a multiple factors learning curve and uranium market modeling". Energ Econ 33: 840–852.    
  • 6. Tao Lin, Dan Schell, Ryan Davis, et al. (2014) NREL 2012 Achievement of Ethanol Cost Targets: Biochemical Ethanol Fermentation via Dilute-Acid Pretreatment and Enzymatic Hydrolysis of Corn Stover, Technical Report: NREL/TP-5100-61563, April 2014. Available from: http://www.nrel.gov/docs/fy14osti/61563.pdf.
  • 7. Karatzos S, McMillan JD, Saddler JN (2014) The potential and challenges of drop-in biofuels. Report for IEA Bioenergy Task, 39. Available from: http://task39.sites.olt.ubc.ca/files/2014/01/Task-39-Drop-in-Biofuels-Report-FINAL-2-Oct-2014-ecopy.pdf.
  • 8. Johnson C, Emily N, Aaron B, et al. (2015) High Octane Mid-Level Ethanol Blend Market Assessment. NREL/TP-5400-63698. Available from: http://www.afdc.energy.gov/uploads/ publication/high-octane_mid-level_ethanol_mkt_ assessment.pdf.
  • 9. Oladosu G, Kline K, Leiby P, et al. (2012) Global economic effects of USA biofuel policy and the potential contribution from advanced biofuels. Biofuels 3: 703–723.    
  • 10. Oladosu G, Kline K (2013) A dynamic simulation of the ILUC effects of biofuel use in the USA. Energ policy 61: 1127–1139.    
  • 11. Oladosu G (2012) Estimates of the global indirect energy-use emission impacts of USA biofuel policy. Appl Energ 99: 85–96.    
  • 12. Schumacher K, Sands RD (2006) Innovative energy technologies and climate policy in Germany. Energ Policy 34: 3929–3941.    
  • 13. Schumacher K, Sands RD (2007) Where are the industrial technologies in energy-economy models? An innovative CGE approach for steel production in Germany. Energ Econ 29: 799–825.
  • 14. Dutta A, Talmadge M, Hensley J, et al. (2011) Process design and economics for conversion of lignocellulosic biomass to ethanol. Thermochemical pathway by indirect gasification and mixed alcohol synthesis. Report by National Renewable Energy Laboratory for US Department of Energy Contract 303: 275–300.
  • 15. Darzins A, Pienkos P, Edye L (2010) Current status and potential for algal biofuels production. A report to IEA Bioenergy Task, 39.
  • 16. Wright MM, Daugaard DE, Satrio JA, et al. (2010) Techno-economic analysis of biomass fast pyrolysis to transportation fuels. Fuel 89: S2–S10.    
  • 17. Swanson RM, Platon A, Satrio JA, et al. (2010) Techno-economic analysis of biomass-to-liquids production based on gasification. Fuel 89: S11–S19.    
  • 18. Fortman J, Anex R, Kothandaraman G, et al. (2010) Techno-economic analysis of biochemical scenarios for production of cellulosic ethanol. Golden, CO: National Renewable Energy Laboratory.
  • 19. Zhou X, Kojima S (2011) Biofuels data and social accounting matrices prepared for policy assessment models based on the GTAP 7 data base. Technical Report February, Institute for Global Environmental Strategies, Arlington, VA.
  • 20. Grinsted JH, Bjoernsson AH, Lind KM (2013) By-products from ethanol production-the forgotten part of the equation: Possibilities and challenges. Report-Institute of Food and Resource Economics, University of Copenhagen.
  • 21. Oladosu G, Kline K, Uria‐Martinez R, et al. (2011) Sources of corn for ethanol production in the United States: a decomposition analysis of the empirical data. Biofuel Bioprod Bior 5: 640–653.    
  • 22. Dantas GA, Legey LF, Mazzone A (2013) Energy from sugarcane bagasse in Brazil: an assessment of the productivity and cost of different technological routes. Renew Sust Energ Rev 21: 356–364.    
  • 23. Argo AJ, Gesick BD, Haq Z (2012) "Application of learning curves to IBR pioneer plant data, estimating transition of cellulosics to maturity". USDOE Communication.
  • 24. IMF-International Monetary Fund (2015) World Economic and Financial Surveys World Economic Outlook Database Available from: https://www.imf.org/external/ pubs/ft/weo/2015/02/weodata/index.aspx.
  • 25. EIA-United States Energy Information Administration (2015) "Annual Energy Outlook. Available from: http://www.eia.gov/forecasts/aeo/.
  • 26. EIA-United States Energy Information Administration (2013) "International Energy Outlook. Available from: http://www.eia.gov/forecasts/ieo/pdf/0484(2013).pdf.
  • 27. EPA-United States Environmental Protection Agency (2016) Proposed Renewable Fuel Standards for 2017, and the Biomass-Based Diesel Volume for 2018. Available from: https://www.epa.gov/renewable-fuel-standard-program/proposed-renewable-fuel-standards-2017-and-biomass-based-diesel.
  • 28. Oladosu G, Msangi S (2013) Biofuel-food market interactions: a review of modeling approaches and findings. Agriculture 3: 53–71.    


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