RSM-based Optimization of Methane Yield From Palm Oil Mill Effluent

Abstract

The palm oil industry generates huge amounts of Palm Oil Mill Effluent (POME), which poses environmental challenges due to its high organic content and toxicity. Anaerobic digestion (AD) is a potential method to treat POME and produce methane-rich biogas as an alternate source of renewable energy. However, the maximum methane yield requires a statistical approach to deal with the complex interactions of key operating parameters. This study employs Response Surface Methodology (RSM) for the optimization and modeling of methane yield from POME under the conditions of pH (7.0 - 7.2), temperature (35.8 - 42.5 °C) and recirculation ratio (0.76 - 3.06). Dual parameter optimization was conducted by analyzing interactions between pH, temperature and recirculation ratio in pairs, allowing better insight into combined effects on methane yield. The developed RSM model used to predict the optimum conditions for maximum methane yield while minimizing hydrogen sulfide concentration. Among these 80, 100 and 120 runs that were generated by Design Expert V.13 software, the developed RSM model with 80 runs demonstrated high predictive accuracy with a R² of 0.9294. The optimized conditions at 37.39 °C, pH 7.08 and recirculation ratio of 3.06 resulted in a methane yield of 0.2825 Nm³ CH₄/kg COD removed and hydrogen sulfide concentration of 729.424 ppm, representing a 3.3% increase in methane yield and 33% reduction in hydrogen sulfide concentration to previous literature. These findings provide the reliability of RSM in enhancing biogas production efficiency, offering a valuable strategy for sustainable waste management and renewable energy generation in the palm oil sector.