Comparative Modelling and Optimization of Different Pretreatment Technologies for Bioethanol Production

Bioethanol production from lignocellulose biomass is becoming of increasing importance because of its low-cost, widely available, non-food competence and high sugar content. However, lignocellulose is more difficult to convert than sugars, starches and oils because it consists of a complex mixture o...

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Main Authors: Melanie T. Ramirez-Jaramillo, Eric S. Fraga
Format: Article
Language:English
Published: Universidad Central "Marta Abreu" de Las Villas 2011-01-01
Series:Revista Centro Azúcar
Subjects:
Online Access:http://centroazucar.uclv.edu.cu/index.php/centro_azucar/article/view/359
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author Melanie T. Ramirez-Jaramillo
Eric S. Fraga
author_facet Melanie T. Ramirez-Jaramillo
Eric S. Fraga
author_sort Melanie T. Ramirez-Jaramillo
collection DOAJ
description Bioethanol production from lignocellulose biomass is becoming of increasing importance because of its low-cost, widely available, non-food competence and high sugar content. However, lignocellulose is more difficult to convert than sugars, starches and oils because it consists of a complex mixture of cellulose, hemicellulose and lignin. To break down its complex structure, a pretreatment step is required. For that purpose physical, physico-chemical, chemical, biological or a combination of pretreatment steps have been proposed to process the raw materials [23]. Pretreatment is essential for the economic success of the entire system because the pretreatment may represent up to one-third of the overall processing cost [14]. The impact of the pretreatment step on the overall process motivates the development of models suitable for process design and optimization. This study presents the modelling and optimization of the pretreatment of sugarcane bagasse for bioethanol production. Alternative pretreatment steps are considered, including dilute-acid hydrolysis (with different acids) and processing with liquid hot water. Models for each pretreatment step are derived from experimental data from the literature, based on an understanding of the kinetics involved in the different reactions and incorporating the kinetics into mass balances models to quantify the consumption and generation of the different components. The models are implemented in the Jacaranda system for process design and optimisation [8] to identify the optimal process conditions for each pretreatment. Results show the interaction between design variables (i.e. residence time, operating temperature or acid concentration) and optimal conditions
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spelling doaj.art-b61a117283234ebeabde1685534b45c52022-12-22T01:21:22ZengUniversidad Central "Marta Abreu" de Las VillasRevista Centro Azúcar0253-57772223-48612011-01-01381359Comparative Modelling and Optimization of Different Pretreatment Technologies for Bioethanol ProductionMelanie T. Ramirez-Jaramillo0Eric S. Fraga1Department of Agro-industrial Engineering, University of Tolima, Ibague, ColombiaCentre for Process Systems Engineering, Department of Chemical Engineering, University College London (UCL), London, UKBioethanol production from lignocellulose biomass is becoming of increasing importance because of its low-cost, widely available, non-food competence and high sugar content. However, lignocellulose is more difficult to convert than sugars, starches and oils because it consists of a complex mixture of cellulose, hemicellulose and lignin. To break down its complex structure, a pretreatment step is required. For that purpose physical, physico-chemical, chemical, biological or a combination of pretreatment steps have been proposed to process the raw materials [23]. Pretreatment is essential for the economic success of the entire system because the pretreatment may represent up to one-third of the overall processing cost [14]. The impact of the pretreatment step on the overall process motivates the development of models suitable for process design and optimization. This study presents the modelling and optimization of the pretreatment of sugarcane bagasse for bioethanol production. Alternative pretreatment steps are considered, including dilute-acid hydrolysis (with different acids) and processing with liquid hot water. Models for each pretreatment step are derived from experimental data from the literature, based on an understanding of the kinetics involved in the different reactions and incorporating the kinetics into mass balances models to quantify the consumption and generation of the different components. The models are implemented in the Jacaranda system for process design and optimisation [8] to identify the optimal process conditions for each pretreatment. Results show the interaction between design variables (i.e. residence time, operating temperature or acid concentration) and optimal conditionshttp://centroazucar.uclv.edu.cu/index.php/centro_azucar/article/view/359lignocellulosebiomassethanolmodeloptimisationdesign
spellingShingle Melanie T. Ramirez-Jaramillo
Eric S. Fraga
Comparative Modelling and Optimization of Different Pretreatment Technologies for Bioethanol Production
Revista Centro Azúcar
lignocellulose
biomass
ethanol
model
optimisation
design
title Comparative Modelling and Optimization of Different Pretreatment Technologies for Bioethanol Production
title_full Comparative Modelling and Optimization of Different Pretreatment Technologies for Bioethanol Production
title_fullStr Comparative Modelling and Optimization of Different Pretreatment Technologies for Bioethanol Production
title_full_unstemmed Comparative Modelling and Optimization of Different Pretreatment Technologies for Bioethanol Production
title_short Comparative Modelling and Optimization of Different Pretreatment Technologies for Bioethanol Production
title_sort comparative modelling and optimization of different pretreatment technologies for bioethanol production
topic lignocellulose
biomass
ethanol
model
optimisation
design
url http://centroazucar.uclv.edu.cu/index.php/centro_azucar/article/view/359
work_keys_str_mv AT melanietramirezjaramillo comparativemodellingandoptimizationofdifferentpretreatmenttechnologiesforbioethanolproduction
AT ericsfraga comparativemodellingandoptimizationofdifferentpretreatmenttechnologiesforbioethanolproduction