Linear and Non-Linear of 2-Parameters Adsorption Equilibrium Isotherm Models of Synthetic Arsenic Wastewaters

Abstract

Contamination of groundwater and surface water 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 magnitudes of R and MSC. The linearized adsorption equilibrium isotherm models, Dubinin –Radushkevich (0.993 and 4.621) <Temkin (0.994 and 4.701) < Kiselev (0.9999 and 8.856). These three models are the best isotherm
models for Asic adsorption onto Poes. It was concluded that Poes particles contain numerous materials that aid 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 non-linear and linear regression analyses.