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Economic optimization for a dual?feedstock lignocellulosic?based sustainable biofuel supply chain considering greenhouse gas emission and soil carbon stock

Environmental factors, including greenhouse gas (GHG) emissions and soil organic carbon (SOC), should be considered when building a sustainable biofuel supply chain. This work developed a three?step optimization approach integrating a geographical information system?based mixed?integer linear programming model to economically optimize the biofuel supply chain on the premise of meeting certain GHG emission criteria. The biomass supply grid cell was considered first, based on a maximum level of GHG emissions, prior to economic optimization. The optimization simultaneously considered dual?feedstock sourcing, selection between distributed and centralized configurations, and the impact of maintaining SOC balance in agricultural soil on biomass availability. The applicability of the modeling approach was demonstrated through a case study that optimized a dual?feedstock renewable jet fuel supply chain via a gasification?Fischer–Tropsch (gasification?FT) conversion pathway in 2050 under three biomass availability scenarios. The case study results show that the differences in procurement costs and GHG emissions between energy crops and agricultural residues have a large impact on the layout of the supply chain. The supply?chain configuration tends to be more centralized with large?scale biorefineries when a supply region has an intensive and centralized distribution of biomass resources. The cost?supply curves demonstrated the technical potential of biofuels that could be obtained at a certain level of cost. Additionally, sensitivity analysis shows that the GHG emission credit from producing extra electricity during the gasification?FT process will be significantly reduced with a rising share of renewable electricity generation in the future. © 2022 The Authors. Biofuels, Bioproducts and Biorefining published by Society of Industrial Chemistry and John Wiley & Sons Ltd.

Publication date: 11/04/2022

TNO (Artículos)


This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870292.