57
Views
4
CrossRef citations to date
0
Altmetric
Articles

Natural zeolite for nickel ions removal from aqueous solutions: optimization and modeling using response surface methodology based on central composite design

, , , &
Pages 16898-16906 | Received 19 Jan 2015, Accepted 04 Aug 2015, Published online: 26 Aug 2015
 

Abstract

Natural zeolite was tested as a low-cost adsorbent for Ni(II) removal from aqueous solutions. In order to reduce the total number of experiments necessary for achieving the best conditions of the batch sorption procedure, response surface methodology based on central composite design was carried out for the natural zeolite. Four independent variables, viz. initial nickel ion concentration (10–200 mg/L), adsorbent dose (0.1–0.7 g/L), contact time (5–120 min), and initial pH of solution (2–8) were transformed to coded values and the quadratic model was built to predict the responses. Very high regression coefficients between the variables and the response indicate excellent evaluation of experimental data using a second-order polynomial regression model. Three-dimensional plots demonstrate relationships between the nickel ion uptake with the paired factors (as the fourth factor was kept at its optimal level), which illustrate the behavior of the sorption system in a batch process. The model showed that nickel uptake in aqueous solution was affected by all four factors studied. An optimum nickel uptake was achieved at an initial nickel ion concentration of 10–15 mg/L, clinoptilolite dosage of 0.37–0.43 g/L, a contact time of 56–68 min, and a pH of 4.8–6. On the basis of experimental results and model parameters, it can be inferred that the adsorbent, which exhibits a relatively high adsorption capacity, can be utilized for the removal of nickel from aqueous solution.

Acknowledgment

The authors would like to appreciate the financial support for this research project (No: 91043070) by Iran National Science Foundation (INSF). Thanks are also due to Dr M. Torab-Mostaedi for his close cooperation during the study.

Log in via your institution

Log in to Taylor & Francis Online

There are no offers available at the current time.

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.