Biofuel Discount Rates and Stochastic Techno-Economic Analysis for a Prospective Pennycress (Thlaspi arvense L.) Sustainable Aviation Fuel Supply Chain

• Published in: Frontiers in energy research Vol. 9
• Main Authors: Trejo-Pech, Carlos Omar, Larson, James A., English, Burton C., Yu, T. Edward
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 10.12.2021
• Subjects: biofuel discount rates; investment hurdle rates; pennycress supply chain; profitability and risk; stochastic tecno-economic analysis; sustainable aviation fuel supply
• DOI: 10.3389/fenrg.2021.770479
• ISSN: 2296-598X

The international aviation industry has the goal to gradually reduce carbon emissions mainly by using sustainable aviation fuel (SAF). However, currently SAF cannot be produced at competitive prices relative to petroleum-based jet fuel. Pennycress is a crop whose oilseed could be used as a relatively low-cost feedstock to produce SAF, potentially benefiting farmers and the environment. This stochastic techno-economic analysis (TEA) studies an enterprise buying pennycress oilseed from farmers, extracting the bio-oil and selling it to a biorefinery that converts bio-oil into SAF. Maximum buying prices (MBP)—prices that yield a zero net present value—the crushing enterprise could pay farmers for pennycress oilseed are estimated. To conduct the analysis, discount rates are estimated based on financial data of biofuel firms, thus providing a realistic benchmark to evaluate profitability and feedstock buying prices. Estimated risk-adjusted discount rates vary between 12 and 17%, above rates typically used in similar valuations. Estimated stochastic MBP range between 10.18 and 11.73 ¢ pound −1 , which is below the price at which farmers are willing to plant pennycress, according to recent research. By considering the crushing facility’s inherent cash flow structure and risk, the distributions of stochastic modified internal rate of return suggest the crushing enterprise could be economically attractive at a 14% discount rate, our most likely estimate. However, between 11 and 17% times the cash flow model is simulated, the firm falls under financial distress. Overall, the findings suggest potential barriers for deployment of a SAF supply chain without governmental incentives or related policies.