132
Views
10
CrossRef citations to date
0
Altmetric
Original Articles

Effect of acid and alkali treatments of a forest waste, Pinus brutia cones, on adsorption efficiency of methyl green

, , , , &
Pages 463-471 | Received 27 Mar 2016, Accepted 12 Apr 2016, Published online: 20 Apr 2016
 

ABSTRACT

The removal of methyl green (MG) dye from aqueous solutions using acid- or alkali-treated Pinus brutia cones (PBH and PBN) waste was investigated in this work. Adsorption removal of MG was conducted at natural pH, namely, 4.5 ± 0.10 for PBH and near 4.8 ± 0.10 for PBN. The pseudo-second-order model appeared to be the most appropriate to describe the adsorption process of MG on both PBN and PBH with a correlation coefficient R2 > 0.999. Among the tested isotherm models, the Langmuir isotherm was found to be the most relevant to describe MG sorption onto modified P. brutia cones with a correlation factor R2 > 0.999. The ionic strength (presence of other ions: Cl, Na+, and SO42−) also influences the adsorption due to the change in the surface properties; it had a negative impact on the adsorption of MG on these two supports. A reduction of 68.5% of the adsorption capacity for an equilibrium dye concentration Ce of 30 mg/L was found for the PBH; while with PBN no significant influence of the ionic strength on adsorption was observed, especially in the presence of NaCl for dye concentrations superior to 120 mg L−1.

GRAPHICAL ABSTRACT

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 666.00 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.