Competitive Sorption Of Nickel Research Articles

Competitive sorption of nickel, copper, lead and cadmium on okra leaves (Abelmoschus esculentus)

In this study, potential of okra leaves for the removal of Ni(II), Cu(II), Pb(II) and Cd(II) from the mixed metal aqueous solution were evaluated. The data were analyzed by Freundlich, Langmuir, D-R, Flory-Huggins and Halsey adsorption models. Pseudo first order rate, Pseudo second order rate, Morris-Weber and Elovich equations were employed to understand the kinetics of the reaction. The characterization of the adsorbent was carried out by EDX and FTIR techniques. The order of maximum metal uptake calculated by D-R isotherm was Cu(II) > Pb(II) > Cd(II) and Ni(II), 453 mg g-1, 81 mg g-1, 13.82 mg g-1 and 1 mg g-1 respectively, with the energy of adsorption in the range of 9-15 for Ni(II) and Cd(II) expected for the ion exchange nature of adsorption and 7-8 for Cu(II) and Pb(II) showing the physical nature of adsorption. The calculated thermodynamic parameters like Gibbs free energy and enthalpy change demonstrate that adsorption process was spontaneous and endothermic in nature. Further it was observed that all four metal ions could be adsorbed at pH 6 with detection limits of 0.04-0.1 µg L-1. The method was successfully applied for the removal of these metal ions from the ground water, tap water and wastewater samples collected from different areas of Pakistan.

Competitive sorption of nickel, cadmium, zinc and copper on palygorskite and sepiolite silicate clay minerals

The fate of heavy metals in the environment is largely controlled by sorption reactions. In the current study, sorption of Ni, Cd, Zn and Cu to distinctive silicate clay minerals that occur primarily in arid and semiarid regions, namely palygorskite and sepiolite, was assessed in multi-metal batch experiments. The results confirmed that competitive sorption pattern of Ni, Cd, Zn and Cu on the minerals varies with mineral type and the metal concentrations of the solution. Sorption of all four metals on palygorskite increased with increasing of metal concentrations in solution from 0 to 100mgL−1. The sequence of sorption maxima on palygorskite was Cu>Zn>Cd>Ni. In the case of sepiolite, sorption isotherms of Zn, Cd and Ni showed an initial increase, up to metal concentrations of about 10mgL−1, but declined significantly afterward in the presence of increasing Cu concentration. Overall, Cu and Ni were the most and the least preferentially retained metals, respectively, by both palygorskite and sepiolite minerals.

Competitive Sorption of Nickel and Cadmium in Different Soils

Competing ions strongly affect heavy-metal retention and release in soils. In this study, we evaluated the sorption of Ni and Cd in single and binary Ni-Cd systems for one neutral and 2 acidic soils. Ni and Cd sorption isotherms were obtained using batch techniques over a wide range of concentrations. Both Ni and Cd adsorption isotherms exhibited strong nonlinear behavior with similar overall patterns for all soils. Sorption of Ni and Cd correlated well the cation exchange capacity for all soils. Moreover, Cd sorption by the two acidic soils was greater than Ni, whereas for the neutral soil, Ni sorption was greater than Cd. The Freundlich model was utilized to describe the family of Ni and Cd isotherms in the presence of competing ions. For both Ni and Cd isotherms, the Freundlich distribution coefficient K decreased with increasing concentration of the competing ion. The dimensionless parameter n was within a narrow range of 0.50 to 0.64 for both Ni and Cd and was not affected by the competing ion. Competitive sorption was described using the Sheindorf-Rebhun-Sheintuch (SRS) equation, which is based on multicomponent Freundlich-type models. Estimates of SRS competitive sorption coefficients indicated that for the neutral soil, Ni sorption was least affected by Cd. The SRS equation was also capable of describing the overall competitive Ni and Cd sorption patterns for all soils. However, SRS model modifications are needed to improve sorption prediction for the highest competing concentrations.