Impact of Thermodynamic Modeling Accuracy on Guaiacol Recovery from Bio-Oil: Experimental Validation, Process Optimization, and Techno-Economic Assessment

This study investigates how thermodynamic modeling choices influence technically and economically downstream processes in the biorefinery context. Due to the lack of literature data, experimental liquid–liquid equilibrium (LLE) measurements – binodal and tie–line data – were conducted for a representative ternary system at 293.15 K and 1 atm. Other missing parameters were estimated using the UNIFAC group-contribution method. Six case studies were developed for process simulation and optimization. Cases 1–3 evaluated the system using (i) default NRTL parameters (Case 1), (ii) regressed NRTL parameters (Case 2), and (iii) regressed NRTL–HOC (Hayden-O’Connell) parameters for vapor-phase corrections (Case 3). Cases 4–6 mirrored these three scenarios but incorporated the effect of two representative pyrolytic lignins in the mixture. A comparative analysis of the NRTL, NRTL-HOC, and UNIFAC models revealed that predictive approaches often misrepresented the equilibrium behavior, whereas regressed NRTL parameters more accurately captured experimental trends. Process simulations revealed that small deviations in thermodynamic representation can significantly impact separation efficiency and economic outcomes: guaiacol production varied from 10.9 to 15.4 kton/y, while the minimum selling price ranged from 3868 to 4600 USD/t. Capital expenditure varied in the range 20.5 to 22.4 million USD, but OPEX dominated costs, particularly in cases with higher guaiacol losses. The results highlight that even minor inaccuracies in thermodynamic modeling propagate into amplified impacts on recovery and cost, directly influencing process viability.