Development and application of a predictive fermentation model for continuous and pressurized fermentation using Clostridium ljungdahlii

Utilization of CO$_2$-containing industrial waste gas emissions as substrates for fermentation with
acetogen bacteria is a novel approach. A key requirement for successful process optimization and the
development of advanced control strategies is a robust model that can sufficiently predict system
responses to varying process conditions. However, few fermentation models have been developed for
continuous cell retention or elevated pressure conditions, which are beneficial for integrating gas
fermentation with CO$_2$ separation technologies. Therefore, this study adapts a dynamic kinetic model
to simulate these conditions to enable model-supported process design with Clostridium ljungdahlii.
The literature model was modified by adjusting key equations and re-estimating important kinetic
parameters derived from long-term fermentation experiments in a continuous stirred tank reactor.
Addition of a carbon dioxide dependency to the hydrogen uptake rate and the acetate to ethanol
conversion rate improves the model’s accuracy to predict biomass and product concentration trends
under high hydrogen substrate gas and moderately increased pressure conditions. ... mehrModel predictions indicate that maximum ethanol production is linked with biomass growth and increases more than tenfold when the gas residence time is lowered from 1.80 to 0.09 h, and the H₂ content in the substrate gas is simultaneously raised from 60 to 80%, with the remainder being CO. Maximum acetate production is predicted to increase with lower gas residence time, 50% H₂ in the feedstock gas and a shift from CO to a mixture of CO and CO₂ as a carbon source, with a CO₂ content of up to 30%.