Environmental challenges and high cost of fossil fuel has made Biodiesel gained more recognition as alternative fuel. In this study, heterogeneous catalyst was developed via dealumination of Ukpor clay and calcined snail shells. Basicity, morphology, textural characteristics among other properties of catalyst were studied using XRF, FTIR, SEM, XRD, EDS, BET, XPS and TGA analyses. The optimization of Moringa Oleifera seed oil biodiesel production was carried out via Central Composite Rotatable Design matrix (CCRD) and Response Surface Methodology (RMS). The variables investigated were temperature, time, catalyst concentration and agitation speed. Biodiesel samples were separated from reactant and impurities via decantation and distillation processes. At a combination of 240min, 300°C, 4.0wt%, and 300rpm of time, temperature, catalyst concentration and agitation speed, the maximum yield of 45.50% was obtained. The FTIR, GC-MS and characteristics of the biodiesel produced conform to ASTM standards. The statistical model developed for the effects and percentage contributions of the optimization variables is in the form of; Yield = +25.85 + 5.88*A + 3.19*B -2.60*C + 0.71*D + 2.29 *A*B + 1.67 *A*C -0.069*A*D+2.54*B*C + 0.66*B*D -2.27*C*D + 0.14*A 2 + 2.12 *B 2 + 1.49*C 2 -0.78*D 2 while the reaction obeys first order kinetics, the reaction proceeds faster at elevated temperatures. The calculated activation (E a ) recorded is 2.94 kJmol -1 K -1 .

A calcium oxide (CaO)-based heterogeneous catalyst derived from waste cow bone for the direct cracking of Moringa oleifera seed oil was investigated. Optimization was carried out using a five-level-four-factorial central composite design based on response surface methodology in 30 experimental runs. Under the optimal conditions of reaction temperature, catalyst concentration, reaction time, and agitation speed, 68 % biodiesel was achieved. A total of four major fatty acid methyl esters were identified in the synthesized biodiesel by the retention time and fragmentation pattern data of the gas chromatography-mass spectrometry analysis. The statistical model for predicting the biodiesel yield was developed for the effects and percentage contributions of the optimization variables.