Abstract
The development of a bio-based economy is seen as a key strategy towards a sustainable society in a world facing climate change, energy security and social distress. However, since substantial uncertainty is involved in early-stage design analyses, the ranking and identification of potential sustainable solutions is a challenging task. This work aims at facilitating the environmental sustainability assessment under uncertainty at the conceptual design of bioprocesses. This, in turn, enables screening design alternatives, and establishing a ranking of the most promising pathways. To this end, a step-wise methodology has been proposed to assist decision-makers to: (i) collect and generate the input data for bioprocesses; (ii) systematically reduce uncertainty concerning the material fluxes at the early stage design of bioprocesses, reducing overall uncertainty in the life cycle inventory; (iii) handle parameter uncertainty, by applying the Monte Carlo technique for the propagation of uncertainty in characterization factors to the potential impact categories' outcomes; (iv) establish sound quantitative thresholds for alternatives comparison by incorporating a probabilistic interpretation; and lastly, (v) rank the alternatives within the design space. Finally, the methodology's applicability is highlighted by screening early-stage glycerol bioconversion routes to value-added chemicals for future biorefinery concepts. Through the proposed methodology, it was demonstrated that the statistical approach suggested ensures consistent and robust ranking of alternatives; thereby identifying lactic acid as the best potential environmentally sustainable alternative within the design space.
Published Version
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