Adsorption of Arsenic From Synthetic Wastewaters: Linear and Non-linear of 2-parameters Adsorption Equilibrium Isotherm Models

Abstract

Abstract Contamination of groundwater with arsenic (Asic) has become emerging health and environmental problem around the world. This problem has received significant attention amongst scientists for the development of new adsorbents to remediate Asic -contaminated water. The ability of the immobilized powdered eggshell (Poes), as adsorbent, to remove Asic was studied under batch conditions. Equilibrium data were analysed using non-linear and linearized two-parameter adsorption isotherms models (Langmuir, Freundlich, Elovich, Flory–Huggins, Temkin, Frenkel- Hasley- Hill; Langmuir- Vageler, Hill-de Boer, Kiselev, Fowler- Guggenheim, Dubinin – Radushkevich, Jovanovic, Harkins–Jura and Halsey). The performance of adsorption equilibrium isotherm models was evaluated statistically using the following analysis of variance (ANOVA), model of' selection criterion (MSC), Coefficient of Determination (CD), Correlation coefficient (R) and Akaike Information Criterion (AIC). The study revealed that for non-linear equilibrium isotherm models, Freundlich (0.986 and 3.906) > Fowler—Guggenheim (0.996 and 5.176) and Hasley (0.986 and 3.906) performed well in predicting experimental data based on the values of R and MSC. For linearized equilibrium isotherm models, Kiselev (0.9999 and 8.856) > Temkin (0.994 and 4.701) and Dubinin – Radushkevich (0.993 and 4.621) are the best isotherm models for Asic adsorption onto Poes. It was concluded that Poes particles are with various inorganic materials for Asic adsorption. Based on the performance indicators and to ensure reliable results of adsorption equilibrium data analysis through the adsorption isotherm models, it is necessary that these data sets should be evaluated by both linear and non-linear regression analyses.