NICKEL ADSORPTION ONTO SWEET DATTOCK SHELL: STATISTICAL ERROR FUNCTION MODELS AS PARAMETRIC ISOTHERM PREDICTORS

Abstract

The speedy increase in the pollution of water bodies due to heavy metals discharged from tannery effluents is becoming a serious issue, calling for important measures to be taken to order to curtail water contamination. In this study, a low-cost adsorbent was prepared by carbonizing sweet dattock shell (Sd) for the removal of nickel (Ni) from tannery effluent. The two (Freundlich, Langmuir, Temkin) and three (Redlich Peterson, Sips, Toths) parameter isotherm models were used to fit the equilibrium data using linear regression methods by applying error functions in determine the best adsorption isotherm model. The scanning electron microscopy (SEM) and Fourier transform infrared (FTIR) were used to characterize the adsorbents. Sips and Langmuir were the best-fitted isotherm models for the process based on error functions. Chi-square error function predicted well for two-and three-parameter isotherm study having the lowest errors values. The FTIR showed a shift functional groups present at certain vibrations. The SEM affirmed irregular surface texture for the Sd with pore openings and whitish spots on the adsorbent. Also, Sd shell adsorption capacity proved efficient as an adsorbent for Ni removal from tannery effluents.