Removal of COD from landfill leachate by predication and evaluation of multiple linear regression (MLR) model and Fenton process

Abstract

MUNICIPAL Solid Waste (MSW) landfill leachate contains highly concentrated organic substances which are hazardous to the environment. Therefore, it must be treated before discharged into water bodies and suitable techniques are essential for effective treatment. In this regard, multiple linear regression (MLR) model has shown to be a favorable technique for optimization of landfill leachate treatment. In this study, four operational variables, H2O2:Fe2+ ratio, pH, reaction time, and Fe2+ concentration, were assessed using the model. The chemical oxygen demand (COD) removal was 96.43% by experiment, while the predicted assessment was 100% under the optimized settings; time = 33.87 min, concentration of Fe2+ = 749.64 mg/L, pH = 3, and ratio of H2O2:Fe2+ = 2 during Fenton treatment. The high value of the coefficient of determination, R2 = 0.896, designates a resilient relationship between the experimental and model values. The residual study (residual plot) specified that the points were randomly distributed, confirming the appropriateness of the model. The MLR model established may possibly be used for assessment of other landfill leachate treatment.