Please use this identifier to cite or link to this item: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/16224
Title: Optimization of Process Parameters influencing Biogas production from Rumen and municipal waste: Analytical Approache
Authors: Eterigho, E. J.
Musa, Michael A
Farrow, T. S.
Ejejigbe, Silver Eyenbi
Keywords: Biogas, Rumen waste, Municipal waste. Response Surface Methodology, Co-digestion, Methane
Issue Date: 24-Sep-2019
Publisher: APWEN
Citation: www.apwenconf.org.ng
Abstract: Rumen waste with high carbohydrate, protein and lipid content is considered as a suitable substrate for fermentation for methane gas. In this study, direct substrate and co-digestion of rumen waste (RW) and municipal waste (MW) were used. Response surface methodology (RSM) and central composite design were applied to optimize parameters of co-digestion of RW and MW at different temperature, initial pH values, agitation time (AGT) and carbon-nitrogen ratio C/N. A comparative analysis was done using RSM in a predictive model of the experimental data obtained in accordance with the central composite design. The combined effects of the independent variables (temperature, pH. AGT and C/N) as the most significant parameters of methane fermentation of RW and MW were investigated. Optimization using RSM showed a good fit between the experimental and the predicted data as elucidated by the coefficient of determination with R² values of 0.9214. Quadratic RSM predicted the maximum yield to be 7764 mL CH/g volatile solid (VS) at optimal conditions of 31°C: pH 7.05; 6s and C/N ratio 20.33. The maximum methane yield was 8550 mL CH/g VS, at the optimal conditions for the experimental response obtained. The verification experiment successfully produced 8550 mL CH4/g VS within 30 days of incubation. This experiment indicated that the developed model was successfully used to predict the fermentable methane production.
Description: An Annual national Conference
URI: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/16224
Appears in Collections:Chemical Engineering

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