DEVELOPMENT OF A PREDICTIVE MODEL, DESCRIBING THE DISPERSION OF NAPHTHALENE IN CONTAMINATED SOIL.

This study investigated the transport and dispersion behavior of naphthalene in contaminated soil using a combination of laboratory column leaching experiments and predictive modeling in MATLAB. The objective was to assess how physicochemical soil properties influence contaminant migration and to develop a predictive model for estimating naphthalene concentration over time. Soil samples were collected and characterized for parameters such as moisture content, pH, porosity, and cation exchange capacity. A vertical soil column experiment was conducted to observe the movement of naphthalene through the soil matrix. Leachate samples were collected at different time intervals and analyzed for naphthalene concentration. A linear regression model was developed using MATLAB to predict the time-dependent concentration based on the experimental data. The experimental findings showed a progressive increase in naphthalene concentration with time, with minimal retardation due to low organic content and cation exchange capacity of the soil. The predictive model demonstrated strong agreement with experimental data, achieving a coefficient of determination (R²) of 0.9265 and a root mean square error (RMSE) of 0.1125 µg/mL. This validated the model’s accuracy in simulating solute transport under controlled conditions. The study concluded that naphthalene dispersion in sandy loam soil is primarily governed by physical flow mechanisms with limited chemical interaction. The integration of experimental results and MATLAB modeling provided a reliable and cost-effective framework for predicting organic contaminant behavior in soil. This approach has potential applications in environmental risk assessment and soil remediation planning.