Data and code: A data-driven techno-economic and life-cycle framework for assessing feedstock and operating uncertainty in lignocellulosic fatty alcohol production

Data, process model interfaces, machine-learning surrogate, and techno-economic and life-cycle assessment (TEA/LCA) analysis code supporting the manuscript on lignocellulosic fatty alcohol production. Includes the Aspen Plus Monte Carlo automation, GAN-generated feedstock compositions (trained on the Phyllis2 database), the Monte Carlo results, the TRACI 2.1 life-cycle inventory and characterization factors, and the analysis scripts that reproduce the MSP, GWP, and figures. The LCA applies energy-based co-product allocation between fatty alcohol and exported electricity (with substitution and economic allocation as sensitivities); the surrogate is a regularized Random Forest used for screening and uncertainty propagation.