Response Surface Optimisation of Biogas Potential in Co-Digestion of Miscanthus Fuscus and Cow Dung

Abstract

In this study, the effects of co-digestion operating conditions for the enhancement of biogas production from Miscanthus Fuscus mixed with cow dung, was investigated. The aforementioned organic wastes are good substrate resources for anaerobic co-digestion (AD) due to their high content of easily biodegradable materials. This source of effective and ecofriendly technology as AD is for generating energy from organic waste. Response surface methodology (RSM) based on the Box-Behnken (BBD) design was employed to evaluate and optimise four process variables: pH, temperature, and hydraulic retention time (HRT) and feedstock inoculum (F/I) ratio on the biogas production. This study signifies the interactions between the process conditions, and identifies the most significant variables of control in order to maximise the biogas production. A developed regression model established the relationship between the significant effect of the input variables and the response. The analysis of variance (ANOVA) showed a high coefficient of determination value (R 2 = 0.9997) at 95% confidence level. The results show that the F/I ratio has a major impact on biogas production. The model developed predicted values which were well fitted (P<0.005) with the values obtained from the experimental data. Thus, the regression model confirmed findings. The RSM and BBD employed proved to be economical and a reliable tool for modelling, optimizing and studying the interactive effects of the four process factors (pH, temperature, HRT and F/I ratio) for the biogas production.

Taguchi Optimization and Experimental Investigation of the Penetration Rate of Compact Polycrystalline Diamond Drilling Bits in Calcareous Rocks

“…In the mathematical model (Equation 6), Y represents the response xiu while xju are the input parameters (factors), b0 is the constant of the regression equation, bi are the linear coefficients, bii are the quadratic coefficients, bij are the interaction coefficients, and ɛ is the fitting error Wang et al, 2007;Tetteh et al, 2018).…”

Ion Exchange Dialysis for Aluminium Transport through a Face-Centred Central Composite Design Approach

“…the response surface methodology (RSM). The response surface methodology is a systematic methodology that consists of a group of mathematical and statistical techniques for experimental design, independent and interdependent analysis, model development and exploitation [37,38]. The empirical model (Equation (1)) is a relationship between process variables and the expected response to understand the process mechanism and to optimize the process using minimal experimental runs [39].…”

Multi-simultaneous Absorption and Adsorption Processes for Biogas Purification using Ca(OH)2 Solution and Activated Clinoptilolite Zeolite/Chitosan Composites

“…This anaerobic digestion process produced a biogas volume of approximately 28 m 3 with a high CO2 content per ton of POME (Harsono et al, 2014). Tetteh et al (2018) reported using an organic waste source such as cow dung for biogas production. It promotes waste generation and has promising implications for green energy for use in improved economic and environmental applications (Tetteh et al, 2018).…”

“…Tetteh et al (2018) reported using an organic waste source such as cow dung for biogas production. It promotes waste generation and has promising implications for green energy for use in improved economic and environmental applications (Tetteh et al, 2018).…”