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Simultaneous biohydrogen production and starch wastewater treatment in an acidogenic expanded granular sludge bed reactor by mixed culture for long-term operation
Authors:Wan-Qian Guo  Nan-Qi Ren  Zhao-Bo Chen  Bing-Feng Liu  Xiang-Jing Wang  Wen-Sheng Xiang  Jie Ding
Affiliation:1. State Key Lab of Urban Water Resource and Environ, Harbin Institute of Technology, Harbin 150090, China;2. School of Materials Science & Chemical Engineering, Harbin Engineering University, Harbin 150001, China;3. Research Center of Life Science and Biotechnology, Northeast Agricultural University, Harbin 150030, China
Abstract:The biofilm-based expanded granular sludge bed (EGSB) reactor was developed to treat starch-containing wastewater and simultaneously recovery hydrogen by mixed microbial culture. Granular activated carbon (GAC) was used as the support media. Operating at the temperature of 30 °C for over 400 days (data not shown), the EGSB reactor presented high efficiency in hydrogen production and COD removal ability. The maximum hydrogen production rate (HPR) was found to be 1.64 L/L.d under the organic loading rate (OLR) of 1.0 g-starch/L.d, pH of 4.42 and HRT of 4 h. The hydrogen yield (HY) peaked at 0.11 L/g-COD, under the OLR of 0.5 g-starch/L.d, pH of 3.95 and HRT of 8 h. Hydrogen volume content was estimated to be 35–65% of the total biogas. The average COD removal rate was 31.1% under the OLR of 0.125 g-starch/L.d and HRT of 24 h. The main dissolved fermentation products were ethanol, acetate and butyrate. The average attached biofilm concentration was estimated to be 8.26 g/L, which favored hydrogen production and COD removal. It is speculated that the low pH operation in the present system would contribute significantly to lower the cost of alkaline amount required for pH control in the continuous operation, especially in the scale-up biohydrogen producing system. A model, built on the back propagation neural network (BPNN) theory and linear regression techniques, was developed for the simulation of EGSB system performance in the biodegradation of starch synthesis-based wastewater and simultaneous hydrogen production. The model well fitted the laboratory data, and could well simulate the removal of COD and the production of hydrogen in the EGSB reactor.
Keywords:Hydrogen production   EGSB   Starch wastewater   Low pH   Mixed culture   Back propagation neural network (BPNN)
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