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

Trung H. Nguyen, Julien Granger, Deval Pandya and Keith Paustian

Applied Energy, 2019, vol. 238, issue C, 1484-1496

Abstract: 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 CO2e 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 CO2e, SC-NL between $0 and $50 per kg N leaching, and their ratio between 0 and 350, respectively.

Keywords: Biofuel supply chain; Multi-objective optimization; Feedstock landscape design; Life cycle assessment; Ecosystem modeling; Ecosystem services (search for similar items in EconPapers)
Date: 2019
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