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. 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. 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.

中文翻译：

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通过气体发酵模拟乙醇生产：大型气泡柱生物反应器中微生物生长的基于生物热力学和传质的混合模型

通过发酵含有 CO、CO2 和 H2 的气体混合物生产乙醇刚刚开始以商业规模运行。然而，文献中缺乏用于理解和预测生产率、产率、传质速率、气流分布和详细能量需求的定量方案；这些是流程改进和更好的系统设计的宝贵工具。本研究描述了一个混合模型的构建，用于模拟 700 m3 气泡柱生物反应器内的乙醇生产，该生物反应器使用两种可能成分的气体，即纯 CO 和 H2 和 CO2 的 3:1 混合物。使用基于热力学的微生物反应黑盒模型对底物阈值浓度、生物量产量、以及 CO 和 H2 的最大比吸收率与文献中报道的数据和观察结果相当吻合。根据生物反应器模拟，工艺性能对传质速率有很强的依赖性。当使用从氧气转移到水开发的模型估计传质系数时，乙醇生产率达到 5.1 g L-1 h-1；当 H2/CO2 混合物被送入生物反应器时，CO 发酵的生产率降低了 19%。H2/CO2 和 CO 发酵的气体利用率分别达到 23% 和 17%。如果传质系数比估计值高 100%，则在相同工艺条件下进料 H2/CO2 混合物时，乙醇生产率和气体利用率可能达到 9.4 g L-1 h-1 和 38%。一个完整的制造工厂对气体压缩和乙醇蒸馏的最大能量需求被确定，由于产生二氧化碳，二氧化碳发酵的能量需求更高。基于热力学的微生物反应黑盒模型可用于定量评估和巩固关于 CO、CO2 和 H2 阈值浓度、生物量产量、最大底物吸收率以及 CO 和 H2 半饱和常数的报告数据的多样性用于产乙酸菌的合成气发酵。生物反应器中乙醇生产率的最大化可能伴随着成本：气体利用率低。利用模型的灵活性，生物反应器性能的多目标优化可能会揭示如何调整工艺条件和配置以指导进一步的工艺开发。