A stochastic techno-economic comparison of alternative jet fuel production pathways

This study quantifies and compares the costs of production for six alternative jet fuel pathways using consistent financial and technical assumptions. Uncertainty was propagated through the analysis using Monte Carlo simulations. The six processes assessed were hydroprocessed ester and fatty acids (HEFA) using soybean oil, yellow grease, and tallow; advanced fermentation (AF) using corn grain, sugarcane, and herbaceous biomass; conventional gasification and Fischer-Tropsch (FT) using municipal solid waste; aqueous phase processing (APP) using woody biomass; hydrothermal liquefaction (HTL) using woody biomass; and fast pyrolysis and hydroprocessing (FPH) using corn stover. The results indicate that none of the six processes would be profitable in the absence of government incentives, with HEFA using yellow grease, HEFA using tallow, and FT revealing the lowest mean jet fuel prices at $0.91/liter ($0.66/liter to $1.24/liter), $1.06/liter ($0.79/liter to $1.42/liter), and $1.15/liter ($0.95/liter to $1.39/liter), respectively. The highest mean NPV was the NPV calculated for HEFA yellow grease with a mean value (in $B) of -0.112 (95% range of -0.412 to 0.179), followed by HEFA tallow with -0.202 (-0.517 to 0.100) and FT with -0.210 (-0.424 to 0.033). This study also quantifies plant performance in the United States with a policy analysis. The alternative fuel production models were used to examine the economic viability of each pathway under a variety of existing and potential regulatory scenarios. Results indicate that some pathways could achieve positive NPV with relatively high likelihood under existing policy supports, with HEFA and FPH revealing the highest probability of positive NPV at 94.9% and 99.7%, respectively, in the best-case scenario.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Aeronautics and Astronautics

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2017

Author dc:creator

• Bann, Seamus J

Advisor dc:contributor.advisor

• Steven R. H. Barrett.

• Institute for Data, Systems, and Society.
• Engineering Systems Division.
• Technology and Policy Program.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/111238

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/111238