High-resolution multi-objective optimization of feedstock landscape design for hybrid first and second generation biorefineries

Biofuels have been proposed as a potential solution for climate change mitigation. However, there exist several barriers, such as food vs fuel issues and technological constraints, restricting the sustainable commercialization of both first- and second-generation biofuels. Combining arable crops and their residues for hybrid first- and second-generation biofuel production provides opportunities to overcome these barriers. This study presents a high-resolution quantitative tool to support decision-making in feedstock production and sourcing for hybrid biofuel supply chains. We demonstrate this work with a case study on optimizing feedstock landscape design for a hybrid corn grain- and stover-based ethanol production system at Front Range Energy biorefinery, Windsor, Colorado, USA using a coupled simulation modeling and life-cycle assessment approach. The case study considered three competing design objectives including the minimization of feedstock-delivered costs, farm-to-refinery greenhouse gas emissions (GHG), and nitrogen (N) leaching, subject to constraints in land use and biofuel feedstock demand. Social costs of carbon (SC-CO2) and nitrogen leaching (SC-NL) were used as weighting factors for GHG and N leaching in the objective function. Our results showed that marginal decreases of feedstock delivered costs (below $0.31 L-1), N leaching (below 0.44 g N L-1), and GHG emissions (below 125 g CO(2)e L-1) resulted in extreme trade-offs among the design objectives. Changes in feedstock landscape design were most sensitive to the variations of the SC-CO2 between $400 and $800 per Mg CO(2)e, SC-NL between $0 and $50 per kg N leaching, and their ratio between 0 and 350, respectively.