Identification of Key Drivers of Cost and Environmental Impact for Biomass-Derived Fuel for Advanced Multimode Engines Based on Techno-Economic and Life Cycle Analysis

Abstract

Early stage research and development are needed to accelerate the introduction of advanced biofuel and engine technologies. Under the Co-Optima initiative, the U.S. Department of Energy is leveraging capabilities from its nine national laboratories and more than 35 university and industry partners including advanced computational tools, process design, data analysis, and economic and sustainability modeling tools to simultaneously design fuels and engines capable of running efficiently in an affordable, scalable, and sustainable way. In this work, we conducted techno-economic analysis (TEA) and life cycle assessment (LCA) to understand the cost, technology development, and environmental impacts of producing selected bioblendstocks for advanced engines such as multimode (MM) type engines at the commercial scale. We assessed 12 biofuel production pathways from renewable lignocellulosic biomass feedstocks using different conversion technologies (biochemical, thermochemical, or hybrid) to produce target co-optimized biofuels. TEA and LCA were used to evaluate 19 metrics across technology readiness, economic viability, and environmental impact and for each ranked on a set of criteria as favorable, neutral, unfavorable, or unknown. We found that most bioblendstocks presented in this study showed favorable economic metrics, while the technology readiness metrics were mostly neutral. The economic viability results showed potentially competitive target costs of less than $4 per gasoline gallon equivalent (GGE) for six candidates and less than $2.5/GGE for methanol. We identified 10 MM bioblendstock candidates with synergistic blending performance and with the potential to reduce greenhouse gas (GHG) emissions by 60% or more compared to petroleum-derived gasoline. The analysis presented here also provides insights into major economic and sustainability drivers of the production process and potential availability of the feedstocks for producing each MM bioblendstock.