Non-Linear Regression Model for Estimating the Efficiency of Heavy Metals Removal by Soil Washing with Chitosan Solution

Abstract

The process of heavy metals removal by soil washing using chitosan as washing agent is a multivariate problem. According to the experimental data sets obtained during experiments performed at laboratory scale, the main parameters that influenced the efficiency of the soil washing process were the stirring time of the polluted soil with the investigated washing agent, washing solution concentration, and solid/liquid ratio (S/L ratio). This study explores the statistical relationships between the removal efficiency of Cu and Pb from polluted soil by washing with chitosan and factors influencing the soil washing process by use of a non-linear regression model. The non-linear regression model contains a non-linear component and a component of interaction among the two parameters (S/L ratio “X1”, the stirring time “X2”) which influences the efficiency of the Cu and Pb removal from soil by soil washing with the investigated washing agent. The proposed model is useful for predicting and estimating the effectiveness of the soil decontamination process by washing with chitosan. A comparison between the data calculated using the proposed mathematical model and the experimental data was also performed in order to determine the integrity and conformity of the mathematical model obtained. The results showed a good fit of the obtained model to the experimental data.

Keywords

• soil remediation
• lead
• copper
• chitosan
• prediction model