Optimization Study of Calophyllum inophyllum Methyl Ester using Statistical Analysis

Abstract

Conventional fuels are the transportation sector’s major occupants since they provide more power and efficiency with harmful environmental pollution. Researchers have focused on alternative and suitable solutions over a decade, considering the depletion of conventional fuels and environmental pollution. The present work is trying to explore an alternative solution resulting from Calophyllum inophyllum seed oil. This oil is extracted mechanically from seeds and the acid value is found to be very high. Acid esterification of oil is done with diluted H₂SO₄ to reduce the acid oil value of oil to make the oil suitable for the transesterification process. Here, a less expensive and abundantly available CaO catalyst is synthesized from wastages of gas industries. Further, the independent factors of transesterification, such as the molar ratio of methanol and oil, type and concentration of the process catalyst, process temperature, stirring rate and process time need to be optimized to get maximum biodiesel yield through the process. The process is optimized by Response Surface Methodology (RSM) through Box Behnken Design with minimum experimental runs. The optimization results show that optimum values are 9 : 1, 50°C and 3 wt % of molar ratio of methanol and oil, process temperature and concentration of catalyst, respectively. During this process, the Analysis of Variance ANOVA table was also employed to identify the significance and fitness of the model.