A Data-Driven Techno-Economic and Life-Cycle Framework for Assessing Feedstock and Operating Uncertainty in Lignocellulosic Fatty Alcohol Production

Abstract Fatty alcohols are important bio-based chemicals with applications in fuels, materials, and specialty products, yet their large-scale production from lignocellulosic biomass remains economically and environmentally challenging. This study presents an integrated framework combining experimental data, Aspen Plus process simulation, machine learning, and techno-economic and life-cycle assessment to evaluate fatty alcohol production from lignocellulosic feedstocks. A detailed process model was developed in Aspen Plus V14, incorporating pretreatment, fermentation in a novel modified Taylor Vortex Reactor (TVR), downstream separation, wastewater treatment, and combined heat and power generation. Experimentally informed relationships between fatty alcohol concentration and hydraulic retention time (HRT) were used to guide process modeling, while realistic biomass variability was represented using 3000 synthetic feedstock compositions generated by a generative adversarial network. Monte Carlo sampling enabled the execution of 3000 process simulations to train a machine-learning surrogate for rapid prediction of fatty alcohol production. Glucan availability and hydraulic retention time were the principal drivers of fatty alcohol production. Capital and operating cost were made responsive to both, which places the economic optimum between 60 and 66 h of retention time. Probability-based analysis indicates a minimum-selling price (MSP) of $30.6 ± 17.9 kg–1. A waterfall analysis indicates that simultaneous improvement in feedstock price, yield, capital cost, and operating hours would bring the MSP to approximately $3 kg–1. The corresponding global warming potential (GWP) is 2.78 ± 0.07 kg CO2-eq kg–1. Overall, this study demonstrates how data-driven process modeling can support large-scale uncertainty analysis, risk-informed decision making, and identification of economically and environmentally favorable operating regions for the sustainable production of fatty alcohols from lignocellulosic biomass.