Optimization of cadmium ions biosorption by fish scale from aqueous solutions using factorial design analysis and Monte Carlo simulation studies

Amine Jaafar (1, 2) , A. Darchen (3) , S.E. Hamzi (2) , Z. Lakbaibi (4) , A. Driouich (5) , A. Boussaoud (2) , A. Yaacoubi (2) , M. El Makhfouk (2) , M. Hachkar (2)

1 Université Hassan 1er [Settat]
2 UCA - Université Cadi Ayyad [Marrakech]
3 ISCR - Institut des Sciences Chimiques de Rennes
4 UMI - جامعة مولاي إسماعيل = Université Moulay Ismaïl
5 University Hassan II [Casablanca]

This work investigated cadmium ions biosorption on Fish scales (FS) of Sardina pilchardus. Different relevant parameters such as initial pH in the range 2.14-7.76, initial cadmium concentration from 35 to 150 mg L-1, and biosorbent dose in the range 50-300 mg L-1, were examined. The effect of these parameters on the cadmium removal was analyzed and optimized using full factorial design methodology and the analysis of variance. The kinetics were modelized for pseudo-second order and pseudo-first order models. Results showed that the pseudo-second order kinetic gave the best fit for equilibrium data. The biosorption isotherms were investigated for Freundlich and Langmuir models. Langmuir isotherm model gave the best fit and led to a maximum biosorption capacity of Cd(II) on FS of 52.08 mg g-1. The results indicated that FS of was effective in the removal of cadmium ions. Optimum Cd(II) removal of 88.2 % was calculated for pH 3, 75 mg L-1 of Cd(II) and 250 mg L-1 of FS. Monte Carlo simulation was used as relatively greener pathway to study the biosorption behavior of Cd(II) ions onto FS. It showed that the interaction Cd(II) - hydroxyapatite was more favored than Cd(II) - collagen.

Mots clés: Analysis of variance; Biosorption; Cadmium ions; Fish scale; Full factorial design; Monte Carlo method

Domaines: Chimie

Amine Jaafar, A. Darchen, S.E. Hamzi, Z. Lakbaibi, A. Driouich, et al.. Optimization of cadmium ions biosorption by fish scale from aqueous solutions using factorial design analysis and Monte Carlo simulation studies. Journal of Environmental Chemical Engineering, 2021, 9 (1), pp.104727. ⟨10.1016/j.jece.2020.104727⟩. ⟨hal-03157951⟩