Written by Anne Van Den Oever, Daniele Mesquita Bordalo Da Costa, Maarten Messagie.
An enormous challenge of ex-ante Life Cycle Assessment (LCA) is to make assumptions of what the future will look like. It requires a more philosophical and constructivist discipline than conventional LCA and the development of this discipline calls for more application in real case studies. This work attempts to do just that by discussing the application of ex-ante LCA strategies to compile a Life Cycle Inventory (LCI) of a novel EN590 compliant biofuel with a high alcohol share, REDIFUEL. The production of this fuel is under development in the likewise named project REDIFUEL (Robust and Efficient processes and technologies for drop-in renewable FUELs for road transport), funded by European Union’s Horizon 2020 research and innovation programme under the Grant Agreement nº 817612. To guide the future developments of the process concept from an early stage on, a well-to-wheel LCA of REDIFUEL is ongoing. The basis for constructing the LCI is a storyline on the future techno-economic system in 2030, when REDIFUEL is assumed to be introduced to the market. Foreground data on biomass transformation processes are generated within the project based on experimental results on a pilot-scale and process simulation software for upscaling to a commercial-scale plant. Data on feedstocks are derived from woody biomass availability projections for different European regions in 2030, according to the scientific literature and experts. When it comes to the background energy system, the current policies and market trends indicate the evolution over the next decade. Two Shared Socioeconomic Pathways (SSP2 and SSP2-45) representing a world in which social, economic, and technological trends do not change markedly were selected to model the future energy system with spatial differentiation. Where possible, uncertainty distributions were constructed using experimental data, expert opinion or the Pedigree matrix. Our main finding is that a novel biofuel can lead to many different scenarios and it is important to investigate the effect of different fuel blends, feedstocks, geographic locations, process set-ups, and assumptions regarding the future and the combination of each of these. This may create an extra challenge during the life cycle interpretation stage, mainly when several indicators are being investigated. The next step of our work will be to tackle this challenge and find efficient and effective ways to interpret and communicate the results of the LCA.