Modeling ethanol production through gas fermentation: a biothermodynamics and mass transfer-based hybrid model for microbial growth in a large-scale bubble column bioreactor
Abstract Background Ethanol production through fermentation of gas mixtures containing CO, CO2 and H2 has just started operating at commercial scale. However, quantitative schemes for understanding and predicting productivities, yields, mass transfer rates, gas flow profiles and detailed energy requ...
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doaj-c4de7efa22d14f7492a3693ca9a5a4832020-11-25T02:04:21ZengBMCBiotechnology for Biofuels1754-68342020-03-0113111910.1186/s13068-020-01695-yModeling ethanol production through gas fermentation: a biothermodynamics and mass transfer-based hybrid model for microbial growth in a large-scale bubble column bioreactorEduardo Almeida Benalcázar0Henk Noorman1Rubens Maciel Filho2John A. Posada3Department of Product and Process Development, Faculty of Chemical Engineering, State University of CampinasDepartment of Biotechnology, Faculty of Applied Sciences, Delft University of TechnologyDepartment of Product and Process Development, Faculty of Chemical Engineering, State University of CampinasDepartment of Biotechnology, Faculty of Applied Sciences, Delft University of TechnologyAbstract Background Ethanol production through fermentation of gas mixtures containing CO, CO2 and H2 has just started operating at commercial scale. However, quantitative schemes for understanding and predicting productivities, yields, mass transfer rates, gas flow profiles and detailed energy requirements have been lacking in literature; such are invaluable tools for process improvements and better systems design. The present study describes the construction of a hybrid model for simulating ethanol production inside a 700 m3 bubble column bioreactor fed with gas of two possible compositions, i.e., pure CO and a 3:1 mixture of H2 and CO2. Results Estimations made using the thermodynamics-based black-box model of microbial reactions on substrate threshold concentrations, biomass yields, as well as CO and H2 maximum specific uptake rates agreed reasonably well with data and observations reported in literature. According to the bioreactor simulation, there is a strong dependency of process performance on mass transfer rates. When mass transfer coefficients were estimated using a model developed from oxygen transfer to water, ethanol productivity reached 5.1 g L−1 h−1; when the H2/CO2 mixture is fed to the bioreactor, productivity of CO fermentation was 19% lower. Gas utilization reached 23 and 17% for H2/CO2 and CO fermentations, respectively. If mass transfer coefficients were 100% higher than those estimated, ethanol productivity and gas utilization may reach 9.4 g L−1 h−1 and 38% when feeding the H2/CO2 mixture at the same process conditions. The largest energetic requirements for a complete manufacturing plant were identified for gas compression and ethanol distillation, being higher for CO fermentation due to the production of CO2. Conclusions The thermodynamics-based black-box model of microbial reactions may be used to quantitatively assess and consolidate the diversity of reported data on CO, CO2 and H2 threshold concentrations, biomass yields, maximum substrate uptake rates, and half-saturation constants for CO and H2 for syngas fermentations by acetogenic bacteria. The maximization of ethanol productivity in the bioreactor may come with a cost: low gas utilization. Exploiting the model flexibility, multi-objective optimizations of bioreactor performance might reveal how process conditions and configurations could be adjusted to guide further process development.http://link.springer.com/article/10.1186/s13068-020-01695-yEthanolBioreactor simulationBiothermodynamicsSyngas fermentation |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Eduardo Almeida Benalcázar Henk Noorman Rubens Maciel Filho John A. Posada |
spellingShingle |
Eduardo Almeida Benalcázar Henk Noorman Rubens Maciel Filho John A. Posada Modeling ethanol production through gas fermentation: a biothermodynamics and mass transfer-based hybrid model for microbial growth in a large-scale bubble column bioreactor Biotechnology for Biofuels Ethanol Bioreactor simulation Biothermodynamics Syngas fermentation |
author_facet |
Eduardo Almeida Benalcázar Henk Noorman Rubens Maciel Filho John A. Posada |
author_sort |
Eduardo Almeida Benalcázar |
title |
Modeling ethanol production through gas fermentation: a biothermodynamics and mass transfer-based hybrid model for microbial growth in a large-scale bubble column bioreactor |
title_short |
Modeling ethanol production through gas fermentation: a biothermodynamics and mass transfer-based hybrid model for microbial growth in a large-scale bubble column bioreactor |
title_full |
Modeling ethanol production through gas fermentation: a biothermodynamics and mass transfer-based hybrid model for microbial growth in a large-scale bubble column bioreactor |
title_fullStr |
Modeling ethanol production through gas fermentation: a biothermodynamics and mass transfer-based hybrid model for microbial growth in a large-scale bubble column bioreactor |
title_full_unstemmed |
Modeling ethanol production through gas fermentation: a biothermodynamics and mass transfer-based hybrid model for microbial growth in a large-scale bubble column bioreactor |
title_sort |
modeling ethanol production through gas fermentation: a biothermodynamics and mass transfer-based hybrid model for microbial growth in a large-scale bubble column bioreactor |
publisher |
BMC |
series |
Biotechnology for Biofuels |
issn |
1754-6834 |
publishDate |
2020-03-01 |
description |
Abstract Background Ethanol production through fermentation of gas mixtures containing CO, CO2 and H2 has just started operating at commercial scale. However, quantitative schemes for understanding and predicting productivities, yields, mass transfer rates, gas flow profiles and detailed energy requirements have been lacking in literature; such are invaluable tools for process improvements and better systems design. The present study describes the construction of a hybrid model for simulating ethanol production inside a 700 m3 bubble column bioreactor fed with gas of two possible compositions, i.e., pure CO and a 3:1 mixture of H2 and CO2. Results Estimations made using the thermodynamics-based black-box model of microbial reactions on substrate threshold concentrations, biomass yields, as well as CO and H2 maximum specific uptake rates agreed reasonably well with data and observations reported in literature. According to the bioreactor simulation, there is a strong dependency of process performance on mass transfer rates. When mass transfer coefficients were estimated using a model developed from oxygen transfer to water, ethanol productivity reached 5.1 g L−1 h−1; when the H2/CO2 mixture is fed to the bioreactor, productivity of CO fermentation was 19% lower. Gas utilization reached 23 and 17% for H2/CO2 and CO fermentations, respectively. If mass transfer coefficients were 100% higher than those estimated, ethanol productivity and gas utilization may reach 9.4 g L−1 h−1 and 38% when feeding the H2/CO2 mixture at the same process conditions. The largest energetic requirements for a complete manufacturing plant were identified for gas compression and ethanol distillation, being higher for CO fermentation due to the production of CO2. Conclusions The thermodynamics-based black-box model of microbial reactions may be used to quantitatively assess and consolidate the diversity of reported data on CO, CO2 and H2 threshold concentrations, biomass yields, maximum substrate uptake rates, and half-saturation constants for CO and H2 for syngas fermentations by acetogenic bacteria. The maximization of ethanol productivity in the bioreactor may come with a cost: low gas utilization. Exploiting the model flexibility, multi-objective optimizations of bioreactor performance might reveal how process conditions and configurations could be adjusted to guide further process development. |
topic |
Ethanol Bioreactor simulation Biothermodynamics Syngas fermentation |
url |
http://link.springer.com/article/10.1186/s13068-020-01695-y |
work_keys_str_mv |
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