Thomas and artificial neural network models for the fixed-bed adsorption of methylene blue by a beach waste Posidonia oceanica (L.) dead leaves


ÇAVAŞ L., Karabay Z., ALYÜRÜK H., DOĞAN H., KALAYCI DEMİR G.

CHEMICAL ENGINEERING JOURNAL, vol.171, no.2, pp.557-562, 2011 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 171 Issue: 2
  • Publication Date: 2011
  • Doi Number: 10.1016/j.cej.2011.04.030
  • Journal Name: CHEMICAL ENGINEERING JOURNAL
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.557-562
  • Keywords: Dead leaves, Fixed-bed, Neural network, Methylene blue, Posidonia oceanica, AQUEOUS-SOLUTION, ACTIVATED-CARBON, LEAF POWDER, BIOSORPTION, SORPTION, REMOVAL, BATCH
  • Dokuz Eylül University Affiliated: Yes

Abstract

Posidonia oceanica (L) is an endemic sea grass in the Mediterranean Sea. Its dead leaves are accumulated in the beaches. Biomass based on dead leaves of P. oceanica is considered as a beach waste. Therefore. they are burned to keep beaches clean. In the present study, an alternative eco-friendly evaluation approach for removal of methylene blue by dead leaves of P. oceanica is studied. Dynamic removal of methylene blue from aqueous solution is performed in a fixed-bed column. Effects of different flow rates and bed heights on column performance are investigated and best flow rate and bed height are observed at 7.28 mL/min and 9 cm, respectively. Column performance has been modeled with Thomas and Artificial Neural Network models. The results confirm that dead leaves of P. oceanica can be used as a fixed-bed material for the dynamic removal of dyes in the waste waters from textile industry. (C) 2011 Published by Elsevier B.V.