NDLI: Heterogenous Lignocellulosic Composites as Bio-Based Adsorbents for Wastewater Dye Removal: a Kinetic Comparison

Content Provider	SpringerLink
Author	Perez Ameneiro, M. Bustos, G. Veci, X. Barbosa Pereira, L. Cruz, J. M. Moldes, A. B.
Copyright Year	2015
Abstract	Different lignocellulosic substrates consisting of modified barley husk, peanut shells and sawdust were entrapped in calcium alginate beads and used as adsorbents to remove dye compounds from vinasses. For comparative purposes, a biocomposite formulated with humus was also included in this work. Kinetic studies were carried out by applying pseudo-first-order, pseudo-second-order, Chien–Clayton and intraparticle diffusion models, observing a good agreement between theoretical and experimental results when the data were adjusted to pseudo-second-order kinetic model. The results of this study show that lignocellulosic-based biocomposites could be used as an effective and low-cost adsorbent for the removal of dyes from aqueous solutions. Among the heterogeneous biopolymers evaluated, the biocomposite based on barley husk gave the best capacity for dye removal. Moreover, in all cases, it was found that there exists a direct relationship between the capacity of the biocomposites to remove dyes and the percentage of carbon contained in the lignocellulosic residues.
Starting Page	1
Ending Page	10
Page Count	10
File Format	PDF
ISSN	00496979
Journal	Water, Air, and Soil Pollution
Volume Number	226
Issue Number	5
e-ISSN	15732932
Language	English
Publisher	Springer International Publishing
Publisher Date	2015-04-10
Publisher Place	Cham
Access Restriction	Subscribed
Subject Keyword	Peanut shell Barley husk Sawdust Alginate Dye adsorption kinetics Environment Water Quality/Water Pollution Atmospheric Protection/Air Quality Control/Air Pollution Soil Science & Conservation Hydrogeology Climate Change/Climate Change Impacts
Content Type	Text
Resource Type	Article
Subject	Pollution Environmental Engineering Water Science and Technology Environmental Chemistry Ecological Modeling

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