4.6 Article

Photo fermentative biohydrogen production potential using microalgae-activated sludge co-digestion in a sequential flow batch reactor (SFBR)

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RSC ADVANCES
卷 12, 期 46, 页码 29785-29792

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ROYAL SOC CHEMISTRY
DOI: 10.1039/d2ra06014k

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  1. National Water Center
  2. United Arab Emirates University [G00003296]

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This study analyzed the performance characteristics of a sequential flow batch reactor (SFBR) for biohydrogen production using co-cultures. The results showed that optimizing organic loading rate (OLR) and hydraulic retention time (HRT) can increase biohydrogen production. Additionally, the limitations of continuous stirred tank reactor (CSTR) handling need to be addressed.
Biohydrogen (bioH(2)) is a sustainable energy source that can produce carbon-free energy upon combustion. BioH(2) can be generated from microalgae by photolytic and anaerobic digestion (AD) pathways. The AD pathway faces many challenges when scaling up using different bioreactors, particularly the continuous stirred tank reactor (CSTR) and sequential flow batch reactor (SFBR). Therefore, the performance characteristics of SFBR were analysed in this study using Chlorella vulgaris and domestic wastewater activated sludge (WWAS) co-culture. An organic loading rate (OLR) of 4.7 g COD L-1 day(-1) was fed to the SFBR with a hydraulic retention time (HRT) of five days in the presence of light under anaerobic conditions. The pH of the medium was maintained at 6 using a pH controller for the incubation period of 15 days. The maximum bioH(2) concentrations of 421.1 mu mol L-1 and 56.6 mu mol L-1 were observed in the exponential and steady-state phases, respectively. The effluent had an unusually high amount of acetate of 16.6 g L-1, which remained high with an average of 11.9 g L-1 during the steady state phase. The amount of bioH(2) produced was found to be inadequate but consistent when operating the SFBR with a constant OLR. Because of the limitations in CSTR handling, operating a SFBR by optimizing OLR and HRT might be more feasible in operation for bioH(2) yield in upscaling. A logistic function model was also found to be the best fit for the experimental data for the prediction of bioH(2) generation using co-culture in the SFBR.

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