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Application of response surface methodology for optimizing process parameters for the removal of Pb and Cu by Acacia Concinna from contaminated soil

This work investigates the remediation of lead (Pb) and copper (Cu) contaminated soil in batch washing experiments by using biodegradable saponin from the plant, Acacia concinna is commonly known as shikakai. The results indicate that the optimal values for the surfactant concentration (Conc), pH and soil-solution ratio (SSR) are 3.3, 3 and 28.78 respectively for Pb removal while the corresponding values for Cu are 3.70, 3 and 30.30 respectively. The predicted Pb removal efficiency was 78.17% while that for the Cu was 92.96%. The influencing parameters: conc., pH and SSR were optimised using Response surface methodology (RSM) based on the Box-Behnken design (BBD). A second-order quadratic polynomial model was used to correlate the effect of these three independent variables. The ANOVA analysis and Pareto plot were generated using Minitab 18 software show that conc., SSR and pH were all significant (P < 0.05) for Pb and Cu removal while the conc. and pH were significant (P< 0.05) for Cu removal. The lower values of S (1.87 and 4.5) and higher values of R2 (99.6% and 98.70%), adjusted R2 (98.96% and 96.37%) and predicted R2 (95.69% and 80.10%) suggested a good fit of the model to the experimental data. The high correlation between the predicted value of 78.17% and 92.96% and the experimental value of 78.79% and 90.79% for Pb and Cu respectively further confirm the adequacy as well as the applicability of this model. The results show the application of RSM as a suitable approach for optimal parameters determination in soil washing for heavy metal remediation using shikakai.