Please use this identifier to cite or link to this item: http://hdl.handle.net/10321/2321
Title: Anaerobic digestion model to enhance treatment of brewery wastewater for biogas production using UASB reactor
Authors: Enitan, Abimbola Motunrayo 
Adeyemo, Josiah 
Swalaha, Feroz Mahomed 
Bux, Faizal 
Keywords: Bio-kinetic;Brewery wastewater;Methane generation model;Upflow anaerobic sludge blanket reactor;Volumetric methane production
Issue Date: 2015
Publisher: Springerlink
Source: Enitan, A. M. 2015. Anaerobic digestion model to enhance treatment of brewery wastewater for biogas production using UASB reactor. Environmental Modeling and Assessment. 20: 673-685.
Abstract: Biogas produced from an upflow anaerobic sludge blanket (UASB) reactor is a clean and an environmentally friendly by-product that could be used to meet partial energy needs. In this study, a modified methane generation model (MMGM) was developed on the basis of mass balance prin-ciples to predict and increase methane production rate in a UASB reactor during anaerobic fermentation of brewery wastewater. Model coefficients were determined using the da-ta collected from a full-scale reactor. The results showed that the composition of wastewater and operational conditions of the reactor strongly influence the kinetics of the digestion process. Simulation of the reactor process using the model was used to predict the effect of organic loading rate and temperature on methane production with an optimum methane production at 29 °C and 8.26 g COD/L/day. Methane produc-tion rate increased from 0.29 to 1.46 L CH4/g COD, when the loading rate was increased from 2.0 to 8.26 g COD/L/day. The results showed the applicability of MMGM to predict usable methane component of biogas produced during anaerobic digestion of brewery wastewater. This study would help industries to predict and increase the generation of renewable energy by improving methane production from a UASB reac-tor. To the best of our knowledge, MMGM is the first reported developed model that could serve as a predictive tool for brewery wastewater treatment plant available in the literature.
URI: http://hdl.handle.net/10321/2321
ISSN: 1420-2026 (print)
1573-2967 (online)
Appears in Collections:Research Publications (Water and Wastewater Technology)

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