The stability of our planet is threatened by climate change, necessitating a shift towards a circular economy in the (bio-)chemical industry to sustainably meet our increasing product demand. Syngas fermentation by acetogenic bacteria, such as Clostridium autoethanogenum, has been identified as a sustainable alternative for the production of biofuels and other chemicals. These bacteria harbour the Wood-Ljungdahl pathway (WLP), enabling them to convert carbon monoxide (CO), carbon dioxide (CO₂) and hydrogen (H₂) into acetate and ethanol. Several process parameters influence the outcome of syngas fermentation and their effects on the metabolic behaviour of syngas fermenting bacteria can be quantified through kinetic modelling.

This study aimed to build a simple quantitative model for steady-state CO fermentation by C. autoethanogenum using unstructured microbial kinetics and the current insights into the ATP production of the CO pathways to acetate and ethanol. To this aim, a dataset compromising 37 steady-state lab-scale syngas fermentations was compiled. Incomplete data was reconciled and recovery gaps were addressed through data reconciliation applied to the dataset. Furthermore, the growth kinetics of C. autoethanogenum was described by coupling ATP production in the catabolism to energy requirements for growth and maintenance through a modified Herbert-Pirt equation. Finally, a preliminary model for CO fermentation by C. autoethanogenum was presented, which given the gas inflow rate, gas inflow composition and liquid dilution rate should predict the consumption and production rates. Moreover, this study emphasizes the necessity for methodologies to measure dissolved gas concentrations and highlights the research gap concerning gas uptake kinetics in syngas fermentation.

The use of syngas, a renewable energy source, has raised increasing interest for the production of chemicals. Syngas, a mixture containing CO, H2, and CO2, can be converted into hydrocarbons, such as ethanol and 2,3-butanediol, via biochemical conversion. In this process, the microorganism Clostridium auto ethanogenum (C. auto ethanogenum) converts syngas into these hydrocarbons under ambient conditions. Still, syngas fermentation has drawbacks which influence the commercialization and scale-up, including low mass transfer rates due to the low solubility of syngas and the slow growth rate of C. auto ethanogenum.

An external loop gas-lift reactor (ELGLR) was considered to potentially overcome the low mass transfer rates. The recirculation of liquid in the reactor induces pneumatic agitation and the recirculation of biomass, which can improve the mass transfer and growth of C. auto ethanogenum and is currently used at an industrial scale by the company LanzaTech.

A 1D model of an external loop gas-lift reactor can provide understanding of the hydrodynamics and syngas fermentation process with C. auto ethanogenum in an ELGLR. A 1D model has the advantage of being less computationally intensive compared to other dimensional models and can be solved dynamically, which is valuable for comprehending the phenomena of syngas fermentation over time in the reactor. The predictions obtained by this model can be used to roughly determine optimal ranges for syngas fermentation, which could be useful for higher dimensional models or experimental setups.

The model considered a continuous inflow and outflow as well as liquid recirculation between the riser and the downcomer. The hydrodynamics of the reactor were based on correlations and equations proposed in the literature, whereas the syngas conversion by C. autoethanogenum was described using a black-box approach.

The hydrodynamic parameters were validated with experimental data proposed in the literature and a CFD model, which was also used for comparison of the syngas fermentation parameters. Additionally, the syngas fermentation in the 1D model was further optimized by adjusting external variable parameters like the dilution rate, inlet biomass concentration, and the gas mass inflow rate.

The syngas fermentation parameters in terms of ethanol productivity and CO conversion yield were compared to the industrial syngas fermentation process operated by the company LanzaTech. The 1D model was found to predict the hydrodynamic parameters in the same order of magnitude as the experimental data. Yet, the hydrodynamic parameters predicted with the CFD and 1D model corresponded less. Additionally, the syngas fermentation parameters varied greatly between the 1D and CFD model, probably as a result of different hydrodynamic parameter estimations in both models.

Using an optimization procedure, a dilution rate of 3 × 10^-5 1/s, gas inflow rate of 2.5 kg/s, and a biomass inlet concentration of 10 g/L were found to be the most advantageous for syngas fermentation in the 1D ELGLR model, resulting in an ethanol productivity of 0.6 g/L/h and 24.9% conversion.

The comparison with the estimated industrial performance deviated by 75.5% and 4.3% in ethanol productivity and CO-to-ethanol conversion yield, respectively. Due to the rough estimations and calculations, the validity of the 1D model to predict the syngas fermentation in an industrial process could not be deduced.

In conclusion, the 1D model was considered to reasonably predict the hydrodynamics of an actual external loop gas-lift reactor and give a rough approximation of the syngas fermentation by C. auto ethanogen. However, more experimental data on the syngas fermentation process is necessary for a complete understanding of the syngas fermentation process within an ELGLR.