284
Views
14
CrossRef citations to date
0
Altmetric
Original Articles

Breakthrough Data Analysis of Adsorption of Toluene Vapor in a Fixed‐Bed of Granular Activated Carbon

, &
Pages 2221-2233 | Received 27 Nov 2006, Accepted 04 Mar 2007, Published online: 14 Aug 2007
 

Abstract

Toluene vapor was adsorbed in a laboratory‐scale packed‐bed adsorber using granular activated carbon (GAC) at constant pressure (101.3 kPa). The adsorber was operated batchwise with the charge of GAC in the range of 2–4 g to obtain the breakthrough curves of toluene vapor. Experiments were carried out at different adsorption temperatures (25–50°C), sparger temperatures (20–30°C), and the flow rates of nitrogen (80–150 cm3/min) to investigate the effects of these experimental variables on the breakthrough curves. The deactivation model was tested for these curves by combining the adsorption of toluene vapor and the deactivation of adsorbent particles. The observed values of the adsorption rate constant and the deactivation rate constant were evaluated through analysis of the experimental breakthrough data using a nonlinear least squares technique. The experimental breakthrough data were fitted very well to the deactivation model than the adsorption isotherm models in the literature.

Acknowledgements

This work was supported with the Basic Research Program of the Korea Science and Engineering Foundation (KOSEF) through ARC and Brain Korea project.

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 681.00 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.