This work proposes a spatially explicit mixed integer linear programming modelling framework representing the dynamic evolution of a bioethanol supply chain (SC) under increasing biofuel demand and greenhouse gas (GHG) emission savings over time. Key features of the proposed framework comprise: (i) the incorporation of available set-aside rural surfaces for energy crop cultivation; (ii) the acknowledgement ofan economic value to the overall GHG emissions through the introduction of an Emission Trading System. Multiple technological options are assessed to exploit the co-product Distiller's Dried Grains with Solubles either as animal fodder (standard usage) or as fuel for heat and power generation or as raw material for biogas production (and hence heat and power). Bioethanol production in Northern Italy is chosen as a demonstrative case study.
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Ortiz-Gutiérrez et al. (2013) studied this question.
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