BackgroundWhile advantages of biofuel have been widely reported, studies also highlight the challenges in large scale production of biofuel. Cost of ethanol and process energy use in cellulosic ethanol plants are dependent on technologies used for conversion of feedstock. Process modeling can aid in identifying techno-economic bottlenecks in a production process. A comprehensive techno-economic analysis was performed for conversion of cellulosic feedstock to ethanol using some of the common pretreatment technologies: dilute acid, dilute alkali, hot water and steam explosion. Detailed process models incorporating feedstock handling, pretreatment, simultaneous saccharification and co-fermentation, ethanol recovery and downstream processing were developed using SuperPro Designer. Tall Fescue (Festuca arundinacea Schreb) was used as a model feedstock.ResultsProjected ethanol yields were 252.62, 255.80, 255.27 and 230.23 L/dry metric ton biomass for conversion process using dilute acid, dilute alkali, hot water and steam explosion pretreatment technologies respectively. Price of feedstock and cellulose enzymes were assumed as $50/metric ton and 0.517/kg broth (10% protein in broth, 600 FPU/g protein) respectively. Capital cost of ethanol plants processing 250,000 metric tons of feedstock/year was $1.92, $1.73, $1.72 and $1.70/L ethanol for process using dilute acid, dilute alkali, hot water and steam explosion pretreatment respectively. Ethanol production cost of $0.83, $0.88, $0.81 and $0.85/L ethanol was estimated for production process using dilute acid, dilute alkali, hot water and steam explosion pretreatment respectively. Water use in the production process using dilute acid, dilute alkali, hot water and steam explosion pretreatment was estimated 5.96, 6.07, 5.84 and 4.36 kg/L ethanol respectively.ConclusionsEthanol price and energy use were highly dependent on process conditions used in the ethanol production plant. Potential for significant ethanol cost reductions exist in increasing pentose fermentation efficiency and reducing biomass and enzyme costs. The results demonstrated the importance of addressing the tradeoffs in capital costs, pretreatment and downstream processing technologies.

Metabolic engineering to divert carbon flux from sucrose to oil in high biomass crop like sugarcane is an emerging strategy to boost lipid yields per hectare for biodiesel production. Sugarcane stems comprise more than 70% of the crops' biomass and can accumulate sucrose in excess of 20% of their extracted juice. The energy content of oils in the form of triacylglycerol (TAG) is more than twofold that of carbohydrates. Here, we report a step change in TAG accumulation in sugarcane stem tissues achieving an average of 4.3% of their dry weight (DW) in replicated greenhouse experiments by multigene engineering. The metabolic engineering included constitutive co‐expression of wrinkled1; diacylglycerol acyltransferase1‐2; cysteine‐oleosin; and ribonucleic acid interference‐suppression of sugar‐dependent1. The TAG content in leaf tissue was also elevated by more than 400‐fold compared to non‐engineered sugarcane to an average of 8.0% of the DW and the amount of total fatty acids reached about 13% of the DW. With increasing TAG accumulation an increase of 18:1 unsaturated fatty acids was observed at the expense of 16:0 and 18:0 saturated fatty acids. Total biomass accumulation, soluble lignin, Brix and juice content were significantly reduced in the TAG hyperaccumulating sugarcane lines. Overcoming this yield drag by engineering lipid accumulation into late stem development will be critical to exceed lipid yields of current oilseed crops.

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BioSTEAM, the Biorefinery Simulation and Techno-Economic Analysis Modules, is an open-source steady-state process simulator in Python that enables biorefinery design, simulation, and techno-economic analysis (TEA) under uncertainty through its fast and flexible framework. By incorporating uncertainty as a key feature, BioSTEAM aims to evaluate the landscape of design decisions and scenarios for conceptual and emerging technologies. The applicability of BioSTEAM is demonstrated here in the context of (i) the co-production of biodiesel and ethanol from lipid-cane and (ii) the production of second-generation ethanol from corn stover. Economic metrics evaluated in BioSTEAM closely match benchmark designs modeled in proprietary software (SuperPro Designer, Aspen Plus). Through the automation of unit operation sizing and characterization of utility requirements, process waste streams, and make-up water usage, BioSTEAM also generates data needed for environmental sustainability analyses (e.g., via life cycle assessment). Ultimately, BioSTEAM enables rapid and robust process design, mass and energy balances, and TEA to compare established and early-stage technologies and prioritize research, development, and deployment.