Optimización por metodología de superficie de respuesta (RSM) de la biodegradación de aceite de motor usado por...

Used engine oil is considered a major environmental concern due to difficulty in disposal or reuse. Using enrichment method, nine bacterial strains were isolated from the oil contaminated sites in Abbottabad. The NMD strain was considered the best biosurfactant producing strain, having the highest emulsification index and cell hydrophobicity up to 72% and 67% respectively. Based on morphology and 16S rRNA sequence analysis, the isolate was identified as Enterobacter hormaechei strain NMD. The effect of various factors which may influence the biodegradation rate including pH, incubation temperature and oil concentration were evaluated by response surface methodology with Box-Behnken design. The analysis of variance (ANOVA) indicated that regression coefficient (R²) is 0.99 with P-value 0.0325 with best fitted second-order quadratic regression model for used engine oil degradation. The F value of model is 338.13 with P-value < 0.0001 showed that the applied model is statistically significant and the optimal parameters i.e., temperature, pH and inoculum size, were observed to have significant effect on engine oil degradation efficiency. The optimum parameters temperature, pH and engine oil concentration were found to be 32.5℃, 6.5, and 4% (v/v) respectively. Under the optimized conditions, the degradation efficiency of used engine oil is observed 80%, which closely matched with the predicted values. The Monod kinetic equation is used to determine the growth rate of isolated strain utilizing used engine oil as sole carbon source with the highest rate of μmax (h-1) = 0.112, with Ks 9.5, and μmax/ Ks is 0.011 mg/L/h. The engine oil degradation was confirmed by GC/MS analysis, and its metabolites were also identified providing comprehensive insights into the breakdown products and degradation efficiency. This is the first report on the growth kinetics of these biosurfactants NMD on used engine oil, with these parameters helping to assess the isolated bacterial strain's capability to degrade the pollutant effectively and guiding the development of more efficient bioremediation strategies. The future study should elucidate detail metabolomic study, optimization study at larger scale bioremediation process and enhancement of bacterial degradation efficiency through immobilization and use of consortium approaches.