Design of a Sustainable Biodisel Supply Chain

Recent interest in biofuels has led to the development and use of models and computational tools at multiple scales including large-scale crop models, detailed chemical process design simulations, life cycle assessment models, and mathematical optimization tools. While these computational methods each provide unique and novel insights into the sustainability of emerging biofuels, these tools are often used in isolation and thus are limited in their ability for guiding decision-making.

Synthesis of these models and tools into a unified framework, via collaboration between researchers across disciplines and modeling scales is required to provide a broader understanding of the sustainability of emerging biomass-to-fuel supply chains. Accordingly, a modular multi-scale and multi-objective framework spanning from the field/lab scale, to the detailed process scale, the life cycle scale, and finally the ecosystems scale for holistic sustainability assessment of biofuel production are needed.

The envisioned multi-scale approach evaluates the process in a hierarchical fashion, starting from the field/lab scale and expanding the system boundaries as successive scales are added. Information from lab/field trials such as reactor kinetic studies, pilot-scale biomass growth trials, and experimental trials on biofuel yields are used to parameterize design blocks and crop models used at the process level. Information such as liquid product distribution and operating plant utility requirements obtained via the process level is subsequently utilized to model unit processes in the supply chain. Information at the supply chain is coupled with the larger economy and ecosystems via the use of environmentally extended economic models.

This multi-scale interdisciplinary approach provides stakeholders different tiers of decision-making criteria (i.e., capital and operating costs, environmental damages, or ecological impacts), and thus a holistic understanding of the broader consequences of emerging fuel pathways. Further, such an approach is conceptually attractive since it facilitates the evaluation procedure starting with simple systems and increasing complexity gradually as successive information layers are added.

Such an approach can allow for screening out bad alternatives, for example, those with a negative economic potential early in the design stage thus saving computational time and providing a range of alternatives to the decision maker while avoiding arbitrary combinations. Further, the proposed framework considers multi-objective optimization over the broader superstructure to identify supply chain configurations that optimize ecological and economic performance while simultaneous achieving minimum threshold sustainability criteria.