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, cilt.171, sa.2, ss.557-562, 2011 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 171 Sayı: 2
  • Basım Tarihi: 2011
  • Doi Numarası: 10.1016/j.cej.2011.04.030
  • Dergi Adı: CHEMICAL ENGINEERING JOURNAL
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.557-562
  • Anahtar Kelimeler: Dead leaves, Fixed-bed, Neural network, Methylene blue, Posidonia oceanica, AQUEOUS-SOLUTION, ACTIVATED-CARBON, LEAF POWDER, BIOSORPTION, SORPTION, REMOVAL, BATCH
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

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.