Sustainable Process Design for Biofuel Production Via Syngas Conversion Pathway | AIChE

Sustainable Process Design for Biofuel Production Via Syngas Conversion Pathway

Authors 

Tan, E. - Presenter, National Renewal Energy Lab

The primary goal of a sustainability evaluation is to assess the impact of systems on areas sought to be protected and maintained over time, such as human well-being and ecosystems [1]. Sustainable process design to convert biomass to fuels and chemicals plays an integral part in the bioeconomy sustainability. It is recognized that the integration of sustainability in process design is core to the mission in developing renewable fuels and should be considered a best practice in biorefinery design. A myriad of approaches and methodologies for the design and evaluation of sustainable chemical processes have been reported. A plethora of indicators has been proposed to evaluate different dimensions of sustainability. Various sustainability dimensionality (such as economy and environment), efficiency (i.e., energy and mass), and categories (i.e., stand-alone indicators, impact categories) have been incorporated into the sustainability in biorefinery design. In this presentation, performance indicators are evaluated with the GREENSCOPE (Gauging Reaction Effectiveness for ENvironmental Sustainability with a multi-Objective Process Evaluator) methodology, which evaluates processes in four areas: Environment, Energy, Economics, and Efficiency. The method develops relative scores for indicators that allow comparisons across various technologies. This talk will explore the different methodologies for sustainability process design and provide an example application of the GREENSCOPE approach on biomass gasification to cellulosic hydrocarbon technology, as well as examples of learnings from these sustainability assessments and their impacts to support and inform on-going R&D efforts.

References:

  1. Schaubroeck T, Rugani B. A Revision of What Life Cycle Sustainability Assessment Should Entail: Towards Modeling the Net Impact on Human Well-Being. J. Ind. Ecol. 21(6), 1464–1477 (2017).

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