Downscaling Industrial-Scale Syngas Fermentation to Simulate Frequent and Irregular Dissolved Gas Concentration Shocks

Lars Puiman, Eduardo Almeida Benalcázar, Cristian Picioreanu, Henk J. Noorman, Cees Haringa

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


In large-scale syngas fermentation, strong gradients in dissolved gas (CO, H2) concentrations are very likely to occur due to locally varying mass transfer and convection rates. Using Euler-Lagrangian CFD simulations, we analyzed these gradients in an industrial-scale external-loop gas-lift reactor (EL-GLR) for a wide range of biomass concentrations, considering CO inhibition for both CO and H2 uptake. Lifeline analyses showed that micro-organisms are likely to experience frequent (5 to 30 s) oscillations in dissolved gas concentrations with one order of magnitude. From the lifeline analyses, we developed a conceptual scale-down simulator (stirred-tank reactor with varying stirrer speed) to replicate industrial-scale environmental fluctuations at bench scale. The configuration of the scale-down simulator can be adjusted to match a broad range of environmental fluctuations. Our results suggest a preference for industrial operation at high biomass concentrations, as this would strongly reduce inhibitory effects, provide operational flexibility and enhance the product yield. The peaks in dissolved gas concentration were hypothesized to increase the syngas-to-ethanol yield due to the fast uptake mechanisms in C. autoethanogenum. The proposed scale-down simulator can be used to validate such results and to obtain data for parametrizing lumped kinetic metabolic models that describe such short-term responses.
Original languageEnglish (US)
Pages (from-to)518
Issue number5
StatePublished - Apr 25 2023

Bibliographical note

KAUST Repository Item: Exported on 2023-05-02
Acknowledgements: This research was partly funded by the Netherlands Organization for Scientific Research (NWO) through the MicroSynC research program (grant number P16-10/5). The authors would like to thank colleagues at the TU Delft Bioprocess Engineering group for their critical input in discussions, with special mention to Rob van der Lans.


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