(314d) Optimization of Biorefinery Production Chains and Decision-Making through Sustainability Evaluation: A Biojet Fuel Case Study  

Authors: 
Vyhmeister, E., Georgia Institute of Technology
Ruiz-Mercado, G. J., U.S. Environmental Protection Agency
Posada, J. A., Delft University of Technology
The aviation industry is a large contributor to the environmental pollution. For example, during the course of a roundtrip flight from Paris to New York, 2.2 Tons of CO2 are released per passenger into the atmosphere; a number that is roughly equivalent to sixty five 100km trips in a medium sized car (2). Clearly, there is a need for solutions that help mitigate these emissions, and advocacy groups such as the Air Transport Action Group (ATAG) push for actions towards more sustainable operations. According to the International Air Transport Association (IATA) sustainable aviation fuels derived from biomass (i.e. biojet fuels) “can reduce the overall carbon footprint by around 80% over their full lifecycle” (3), and actively supports their development.

Previous contributions have addressed the production of biojet fuel; as examples Crawford et al. (4) and Klein-Marcuschamer et al. (5) have analyzed the economic viability of biojet fuel production under different geographical and technological contexts, while Klein-Marcuschamer et al. (5) have studied the air emissions for its production. Going a step forward, Agusdinata et al. (6) have recognized that multiple actors/ stakeholders (e.g. national/international policymakers, biorefineries, farmers) are involved in the development of biojet-fuels, each of which has differents objectives to consider in their decision-making.

In this work, we combine mathematical programming tools (optimization) and the GREENSCOPE approach developed by the U.S. Environmental Protection Agency (7) to assess the sustainability of production of biojet fuels from the perspective of the different actors that participate in the overall production chain. The GREENSCOPE approach allows for the quantification of process sustainability in four main areas: Efficiency, Energy, Economics, and Environment; in here, each E is characterized by a series of metrics that indicates the performance of a particular process. Optimization is applied to find the processing pathways that provide the best performance for each E, and for clusters of the indicators that represent the preferences of the different stakeholders. Multi-objective optimization is then used to find the Pareto frontier that describes the trade-offs among their optimal solutions.

As a case study, we consider the production of biojet fuels from three different organic material sources: eucalyptus, pine, and macauba, through three main technological pathways: fast pyrolysis, hydrothermal liquefaction, and gasification followed by Fischer-Tropsch synthesis. In all cases, the benefits of adding a follow-up cracking step of long-chain (hydrocarbon) residues, is also considered.

The views expressed in this presentation are those of the authors and do not necessarily represent the views or policies of the U.S. Environmental Protection Agency.

References

  1. Brasseur, G.P., M. Gupta, B.E. Anderson, S. Balasubramanian, S. Barrett, D. Duda, G. Fleming, P.M. Forster, J. Fuglestvedt, A. Gettelman, R.N. Halthore, S. Jacob, M.Z. Jacobson, A. Khodayari, K. Liou, M.T. Lund, R.C. Miake-Lye, P. Minnis, S. Olsen, J.E. Penner, R. Prinn, U. Schumann, H.B. Selkirk, A. Sokolov, N. Unger, P. Wolfe, H. Wong, D.W. Wuebbles, B. Yi, P. Yang, and C. Zhou ”Impact of Aviation on Climate: FAA’s Aviation Climate Change Research Initiative (ACCRI) Phase II.”, Bull. Amer. Meteor. Soc., 2016, 97, 561–583.

  2. Simulations done on the basis of the tool available at https://co2.myclimate.org/. Accessed on April 16, 2017.

  3. IATA website: http://www.iata.org/whatwedo/environment/Pages/sustainable-alternative-jet-fuels.aspx. Accessed on April 16, 2017.

  1. Crawford, J. T., Shan, C. W., Budsberg, E., Morgan, H., Bura, R. and Gustafson, R., "Hydrocarbon bio-jet fuel from bioconversion of poplar biomass: techno-economic assessment", Biotech. for Biofuels, 2016, 9 (1), 141.

  2. Klein-Marcuschamer, D., Turner, C., Allen, M., Gray, P., Dietzgen, R. G., Gresshoff, P. M., Hankamer, B., Heimann, K., Scott, P. T., Stephens, E., Speight, R. and Nielsen, L. K., “Technoeconomic analysis of renewable aviation fuel from microalgae, Pongamia pinnata, and sugarcane”. Biofuels, Bioprod. Bioref., 2013, 7: 416–428.

  3. Agusdinata, D. B., Zhao, F. and DeLaurentis, D. A., “Sustainability of Biojet Fuels: A Multiactor Life Cycle Assessment Approach”, IEEE Potentials, 2012, 31(1), 27-33.

  4. Ruiz-Mercado, G. J., Gonzalez, M. A. and Smith, R. L., "Sustainability Indicators for Chemical Processes: III. Biodiesel Case Study”, Ind. & Eng. Chem. Res., 2013, 52, (5), 6747-6760.