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Adsorption of Copper(II) and Zinc(II) ions by various agricultural by-products. Experimental studies and modelling

Turan N. G., Mesci B.

Environment Protection Engineering

2011

Vol. 37, nr 4

143-161

Effective removal of heavy metals from aqueous solutions belongs to the most important issues for many industrialized countries. Removal of copper(II) and zinc(II) ions from leaching solution of industrial waste were studied using hazelnut, almond and walnut shells. Batch adsorption experiments were performed in function of pH, contact time and adsorbent dosage. Adsorption kinetics was investigated using the pseudo-first and pseudo-second order, Elovich equations and intraparticle diffusion models. The results indicate that the second order model best describes adsorption kinetic data and the agricultural by products investigated may be used for removal of copper(II) and zinc(II) ions from leaching solution of industrial waste.

Adsorptive removal of Zinc by bentonite: application of time series modeling method

Mesci B.

Archives of Environmental Protection

2011

Vol. 37, no. 3

101-113

Zinc (II) removal using low-cost sorbents requires a proper process parametric study to determine its optimal performance characteristics. In this respect, the present study proposes a new modeling and simulation procedure for heavy metal removal system and is carried out to optimize input variables such as initial pH, adsorbent dosage, and contact time for biosorption of Zinc (II) by using bentonite. The proposed experimental system is cost-effective and requires less calculation for determining optimal values, i.e., input variables and their related removal capacity, R_em%. To optimize the adsorption process, cubic spline curve fitting and numerical differentiation techniques are used for required calculations. According to the proposed calculations, the removal capacity is calculated as 98.66%, while the optimal values are calculated as initial pH – 6.76, adsorbent dosage – 1.14 g L-1, contact time – 13 minutes. To evaluate the results, full factor experimental design and 3 way ANOVA test are used for comparison.