Abstract

This work performs integrated multi-objective optimization of lignocellulosic biorefinery system considering four objectives capturing the three dimensions of sustainability, namely, cost, life cycle greenhouse gas (GHG) emissions, and life cycle water footprint of ethanol and employment generation. Feedstock selection, biorefinery location and size, biorefinery conversion processes, and detailed biomass procurement and processing strategy are the decision variables. The model was applied to a case study of Maharashtra, India, considering 33 districts and five different feedstock to produce ethanol to meet the 10% gasoline blending target. The optimal values for ethanol cost, GHG emission, and water footprint were Rs. 50.39/l ($ 0.69/l), 0.933 kg CO2 eq./l and 0.271 m3/l, respectively, while a total of 5087 jobs were created in the biorefineries for job maximization. Feedstock selection, biorefinery number and their locations affected the objectives. Multi-objective optimization identified design possibilities with considerable reduction in water footprint at nominal increase in the cost and GHG emissions. The sensitivity of the model with respect to the ethanol demand, biomass availability, and cost of cotton stalk was studied. A reduction in biomass availability to 20% had minimal impact on minimal GHG emissions, but the minimum cost increased by 21% while the minimum water footprint increased by 81%. Sensitivity analysis based on cost of cotton stalk showed that it was a much more important feedstock from the economic perspective than from GHG emissions and water footprint perspectives. The results provide region-specific recommendations for scaling of lignocellulosic biofuel systems.

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