Optimization of Parameters Affecting Adsorption of Nickel (II), Zinc (II) and Lead (II) on Dowex 50 W Resin Using a Response Surface Methodology Approach

Biosorption of nickel (II) ion from synthetic wastewater on watermelon rind activated carbon using reponse surface methodology (RSM) optimization approach

“…Increasing adsorbent dosage beyond 25g/l at constant pH and contact time has little effect on nickel ion removal from solution. This may be as a result of oversaturation of available adsorption sites from the increased adsorbent dose thereby reducing the adsorption density [2,19] 3.3.4 Combined effect of pH and Contact Time Figure 5 shows the combined effect of contact time and pH on the response surface for total nickel ion removed from solution at constant adsorbent dosage and initial nickel ion concentration. The interactive effect is nonsignificant (p = 0.9693).…”

“…One of the major environmental problem currently facing many developing countries of the World is the introduction of heavy metals polluted wastewater into the environment [1,2]. Heavy metals found in untreated or partially treated industrial wastewater normally discharged into water bodies and soil include nickel (Ni), lead (Pb), mercury (Hg), arsenic (As) and other lethal metals [3] These metals pose both shortterm and long-term danger to both humans and the environment due to their non-biodegradability [4] One of the heavy metals contained in effluent wastewater that had not received much attention like others is nickel.…”

“…However, if the task at hand is purely predictive the aforementioned models need to be augmented with an appropriate optimization technique which is able to identify and evaluate interactive effects between all variables responsible for adsorption. Multivariable statistical experimental design methods that can identify a combination of factors and interactions between wide ranges of variables have been applied by many to reduce cost of research and save valuable time [2,3]. In most cases, various optimization techniques have been applied in validating the developed statistical experimental designs.…”

“…For example, the one-factor-at-a-time (OFAT) method was applied in validating experimental design for the removal of heavy metals from aqueous solution using Dowex 50W resin as adsorbent, the technique, however, was found to be too lengthy and time consuming [16]. However, the limitations associated with the OFAT were eliminated by optimizing the same process variables using factorial strategies that employ statistical experimental design with response surface methodology (RSM) [2,17]. In the later experiment, the central composite rotatable design (CCRD) was chosen to quantitatively identify the important interactive factors in the process and the results obtained was excellent.…”