105
Views
18
CrossRef citations to date
0
Altmetric
Articles

Removal of ammonium ions from aqueous solutions using zeolite synthesized from red mud

, , , , , , & show all
Pages 4720-4731 | Received 16 Dec 2013, Accepted 21 Nov 2014, Published online: 29 Jan 2015
 

Abstract

This study investigates the removal of ammonium from aqueous using zeolite synthesized from red mud. The zeolite was characterized with X-ray diffraction (XRD), scanning electron microscopy (SEM), the specific surface area, and the cation exchange capacity (CEC). SEM and XRD indicated that most of the synthetic zeolite was crystalline, with zeolite P and Analcime as the major components. The CEC increased from 81.9 to 111 mmol/100 g during the synthesis process. The effects of adsorbent dosage, shaking time, initial pH, initial ammonium ion concentration, and competitive cations were investigated by batch experiments. The result shows that the parameters mentioned above have great influence on the ammonium removal by using the synthesized zeolite, and the effect of cations follows the order Na+ > K+ > Ca2+ > Mg2+. To understand the exchange process of ammonium by the synthesized zeolite, the adsorption dynamics was described by Ho’s pseudo-second-order kinetic model. The Ho’s pseudo-second-order kinetic model was found to provide excellent kinetic data fitting. Five models including Langmuir, Freundlich, Koble–Corrigan, Tempkin and D–R were used in this experiment to fit with the equilibrium isotherm data, and the Koble–Corrigan model gave the best fit. The maximum ammonium adosorption capacity obtained is 17.5 mg/g. The results implies that the zeolites synthesized from red mud is an efficient adsorbent for the removal of ammonium ion.

Acknowledgements

The authors are grateful for the financial support provided by the National Key Technology R&D Program (2012BAJ21B04), National Natural Science Funds for Distinguished Young Scholar (No. 51325804) and the National Natural Science Foundation of China (No. 51108436).

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.