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Multi-objective optimization of a 1G-2G biorefinery: A tool towards economic and environmental viability

Journal of Cleaner Production(2021)

Cited 17|Views6
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Abstract
First-generation sugarcane ethanol production is a well-established technology. However, second-generation ethanol is not yet consolidated in industries. Under these circumstances, this work presents a multi-objective optimization of this process focusing on economic and environmental objectives. The impact of the Brazilian decarbonization program on an integrated biorefinery is analyzed, considering a first-generation ethanol conventional autonomous distillery and a second-generation process with hydrothermal pre-treatment, enzymatic hydrolysis and fermentation of the xylose liquor. The economic metric was the Net Present Value and the environmental assessment was based on the plant inventory considering Global Warming Potential. A multi-objective particle swarm optimization algorithm was used, considering the ratio of bagasse diverted to the second-generation process, enzyme loading and solid fraction in the hydrolysis reactor as optimization variables. The carbon credit price was estimated for each point in the Pareto set in order to make the process economically feasible. As the main conclusions, there is a trade-off between economic and environmental targets, indicating that carbon credits may be essential for second-generation ethanol economic feasibility. The optimized integrated biorefinery is able to increase ethanol production by approximately 24% compared to first-generation biorefineries, but an increase in ethanol production higher than 13% would make the process economically unfeasible, while the decarbonization credits are not being commercialized. A price of $ 15.77 for decarbonization credits would make it possible to produce 20% more ethanol, keeping the integrated biorefinery economically feasible.
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Key words
Multi-objective optimization,Decarbonization credit,Environmental impacts,Economic feasibility,1G-2G bioethanol biorefinery
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