270
Views
29
CrossRef citations to date
0
Altmetric
Original Articles

STUDY OF HG(II) REMOVAL FROM AQUEOUS SOLUTION USING LIGNOCELLULOSIC COCONUT FIBER BIOSORBENTS: EQUILIBRIUM AND KINETIC EVALUATION

, , , &
Pages 1198-1220 | Published online: 01 May 2014
 

Abstract

Lignocellulosic coconut wastes such as pith and fiber, which are abundantly available and cheap, have the potential of being used as low-cost biosorbents for heavy metal ion removal. In this study, pristine (CF-Pristine) and NaOH-treated (CF-NaOH) coconut fibers were used as a biosorbent for Hg(II) removal from an aqueous solution. The coconut fiber biosorbent (CFB) was characterized by scanning electron microscopy (SEM) and Fourier transform-infrared (FTIR) spectroscopy. The Hg(II) sorption capacities obtained for CF-Pristine and CF-NaOH were 144.4 and 135.0 mg/g, respectively. Both the equilibrium and kinetic data of Hg(II) sorption onto CFB followed the Langmuir isotherm model and a pseudo-second-order kinetic model, respectively. A further analysis of the kinetic data suggested that the Hg(II) sorption process was governed by both intraparticle and external mass transfer processes, in which film diffusion was the rate-limiting step. These results demonstrated that both pristine- and alkali-treated coconut wastes could be potential low-cost biosorbent alternatives for the removal of Hg(II) from aqueous solutions, such as water containing Hg(II) produced in the oil and gas industry.

Notes

a S = strong, M = medium, and W = weak.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 1,086.00 Add to cart

* Local tax will be added as applicable

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.