Kinetic Data Analysis by MLR and ANN Models for Phenol Attenuation in Peat Soil

AbstractThe efficacy of phenol transport from the aqueous phase to peat soil for assessment of the attenuation capacity for migratory phenol in subsurface water pollution was investigated by the application of multiple linear regression (MLR) and artificial neural network (ANN) models. The batch kinetics study was performed, which revealed that the Freundlich isotherm model fits reasonably well with experimental results. A maximum value of 43% phenol removal efficiency was achieved in 200 g/L of soil, an initial concentration of phenol of 10 mg/L, and an equilibration time of 6 h. A sum total of 270 laboratory batch adsorption tests were conducted, and the results were applied in MLR and ANN models. Some of the influencing factors, such as pH, initial concentration, mass of soil, contact time, and so forth, on removal of sorbate by peat were also investigated in the present research. The experimental results exhibit a reasonable goodness of fit [higher coefficient of determination, R2, and lower root-mean...

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