Lignocellulosic biomass is largely available for the production of bioethanol; it is relatively inexpensive and does not compete with food. Much effort is being spent on the development of process schemes that can be economically and environmentally attractive. The production of bioethanol from lignocellulosic biomass through a biochemical route, requires a pretreatment stage, whose goal is to alter lignin and hemicellulose structure to make cellulose more accessible to hydrolysis. This step includes reduction of the sample size, breakdown of hemicellulose to sugars, and disclosure of cellulose to be in turn hydrolyzed by enzymes into glucose using microbial cellulases (saccharification). Following pretreatment and hydrolysis, the sugars extracted from cellulose and hemicellulose materials can be converted to ethanol through microbial fermentation.
In this work, we propose a model based optimization strategy for the production of bioethanol from lignocelllulosic biomass, through a continuous process. The objective is to determine optimal operation and design variables that maximizes ethanol production. A unique feature in this work is the integration of kinetic models for the pre-treatment stage (dilute acid hydrolysis) to saccharification (enzymatic hydrolysis) and simultaneous fermentation (co-fermentation) models. Although several pretreatment techniques exist,1,2 the dilute acid hydrolysis is selected due to its simplicity, effectiveness, and economic convenience, as compared to other pretreatment methods. Kinetic equations describing hemicellulose polymers (xylan, arabian) and a small fraction of glucan decomposition have been included. At this stage, the main sugar decomposition products are furfural and hydroxymetil furfural. Furthermore, an additional operation of detoxification is required after pretreatment because fermentation inhibitory compounds, mainly furfural and hydroximetyl furfural, are produced in the acid hydrolysis. A kinetic model for detoxification of acid hydrolyzates by the addition of Ca(OH)2 (overliming)3,4 is included. As in this latter stage not only furans degradation takes place but also sugar consumption3, a minimal sugar recovery has been imposed, while maximizing loss of inhibitors.
The problem has been formulated as a non-linear programming (NLP) model. Key variables are: equipment volumes, acid and enzyme concentrations, operating temperatures, and water consumption. Detailed kinetic equations3,5,6,7 and mass balances have been formulated in GAMS. Numerical results show the need for integrated models development for the optimization of the entire biochemical route to optimize bioethanol production and to be able to later minimize energy consumption.
1- Kumar et al., 2009. Methods for pretreatment of lignocellulosic biomass for efficient hydrolysis and biofuel production. Ind. Eng. Chem. Res. 48, 3713 – 3729.
2- Taherzadeh and Karimi, 2008. Pretreatment of lignocellulosic wastes to improve ethanol and biogas production: A review. Int. J. Mol. Sci. 9, 1621 – 1651.
3- Purwadi et al., 2004. Kinetic study of detoxification of dilute-acid hydrolyzates by Ca(OH)2. Journal of Biotechnology 114, 187 – 198.
4- Aden et al., 2002. Lignocellulosic Biomass to Ethanol Process Design and Economics Utilizing Co-Current Dilute Acid Prehydrolysis and Enzymatic Hydrolysis for Corn Stover. NREL / TP-510-32438.
5- Lavarack et al., 2002. The acid hydrolysis of sugarcane bagasse hemicelluloses to produce xylose, arabinose, glucose and other products. Biomass and Bioenergy 23, 367 – 380.
6- Kadam et al., 2004. Development and validation of a kinetic model for enzymatic saccharification of lignocellulosic Biomass. Biotechnology Progr. 20, 698 – 705.
7- Leksawasdi et al., 2001. Mathematical modeling of ethanol production from glucose/xylose mixtures by recombinant Zymomonas mobilis. Biotechnology Letters 23, 1087 – 1093.