Capson-Tojo Gabriel, Batstone Damien J, Hülsen Tim
Australian Centre for Water and Environmental Biotechnology, The University of Queensland, Brisbane, QLD 4072, Australia; Department of Chemical Engineering, CRETUS, Universidade de Santiago de Compostela, Santiago de Compostela, Galicia 15782, Spain; INRAE, University Montpellier, LBE, 102 Avenue des Etangs, Narbonne 11100, France.
Australian Centre for Water and Environmental Biotechnology, The University of Queensland, Brisbane, QLD 4072, Australia.
Water Res. 2023 Feb 1;229:119401. doi: 10.1016/j.watres.2022.119401. Epub 2022 Nov 23.
The economic feasibility of purple phototrophic bacteria (PPB) for resource recovery relies on using enriched-mixed cultures and sunlight. This work presents an extended Photo-Anaerobic Model (ePAnM), considering: (i) the diverse metabolic capabilities of PPB, (ii) microbial clades interacting with PPB, and (iii) varying environmental conditions. Key kinetic and stoichiometric parameters were either determined experimentally (with dedicated tests), calculated, or gathered from literature. The model was calibrated and validated using different datasets from an outdoors demonstration-scale reactor, as well as results from aerobic and anaerobic batch tests. The ePAnM was able to predict the concentrations of key compounds/components (e.g., COD, volatile fatty acids, and nutrients), as well as microbial communities (with anaerobic systems dominated by fermenters and PPB). The results underlined the importance of considering other microbial clades and varying environmental conditions. The model predicted a minimum hydraulic retention time of 0.5 d. A maximum width of 10 cm in flat plate reactors should not be exceeded. Simulations showed the potential of a combined day-anaerobic/night-aerobic operational strategy to allow efficient continuous operation.
紫色光合细菌（PPB）用于资源回收的经济可行性依赖于使用富集混合培养物和阳光。这项工作提出了一个扩展的光厌氧模型（ePAnM），该模型考虑了：（i）PPB的多种代谢能力，（ii）与PPB相互作用的微生物进化枝，以及（iii）变化的环境条件。关键的动力学和化学计量参数要么通过实验测定（进行专门测试）、计算得出，要么从文献中收集。该模型使用来自户外示范规模反应器的不同数据集以及好氧和厌氧批次测试的结果进行了校准和验证。ePAnM能够预测关键化合物/成分（如化学需氧量、挥发性脂肪酸和营养物质）的浓度，以及微生物群落（厌氧系统以发酵菌和PPB为主）。结果强调了考虑其他微生物进化枝和变化的环境条件的重要性。该模型预测的最短水力停留时间为0.5天。平板反应器的最大宽度不应超过10厘米。模拟显示了白天厌氧/夜间好氧联合运行策略实现高效连续运行的潜力。
