Optimization Efficiency of Calcium Based Catalyst in Coconut Oil Transesterification via Box-Behnken Design

¹ Faculty of Bioresources and Food Industry, Universiti Sultan Zainal Abidin, Besut Campus, 22200 Besut, Terengganu, Malaysia
² UniSZA Science and Medicine Foundation Centre, Universiti Sultan Zainal Abidin, Gong Badak Campus, 21300 Kuala Nerus, Terengganu, Malaysia
³ East Coast Environmental Research Institute (ESERI), Universiti Sultan Zainal Abidin, Gong Badak Campus, 21300, Kuala Terengganu, Malaysia
⁴ Department of Chemistry, Faculty of Science, Universiti Teknologi Malaysia, 81310 UTM Skudai, Johor, Malaysia
⁵ Department of Basic Medical Sciences, Faculty of Medicine, Universiti Sultan Zainal Abidin, Kuala Terengganu, Terengganu, Malaysia

^* Corresponding author: salmiahjamal@unisza.edu.my

Abstract

The utilization of renewable biomass resources for biofuel production has gained significant attention as an effective strategy for converting waste into valuable energy sources. Biodiesel, a promising form of biofuel, is derived from vegetable oils or animal fats through transesterification with methanol. Among the various methods employed for biodiesel production, base-catalyzed transesterification is widely recognized as the most efficient and cost-effective process. This study focuses on optimizing biodiesel production from coconut oil (CO) using a CaO/Al₂O₃ catalyst synthesized via the incipient wetness impregnation method. The optimization process was conducted using the Box-Behnken response surface methodology (RSM) in Design Expert statistical software. The optimal conditions identified for biodiesel production included a calcination temperature of 1000°C, a reaction time of 1 hour, and a catalyst loading of 7% with biodiesel yield of 72.33% and 75.63%, respectively from waste cooking oil (WCO) and fresh cooking oil (FCO). Under these optimized conditions, an experimental fatty acid methyl ester (FAME) yield of 75.63% was achieved. The statistical models used to predict biodiesel yield demonstrated a high degree of correlation with experimental results, yielding an R-value of 0.9756. Furthermore, analysis of variance (ANOVA) confirmed the statistical significance of the model, with reaction time and catalyst loading identified as the most influential factors based on F- and P- values. The physicochemical properties of the produced biodiesel were found to be within the specifications recommended by ASTM standards, further validating the suitability of the synthesized catalyst and optimized reaction conditions for efficient biodiesel production.