Home/Beni-Suef University Journal of Basic and Applied Sciences (BJBAS)/Article Record
Peer-Reviewed Article February 29, 2016

Acid-modified montmorillonite for sorption of heavy metals from automobile effluent

Are you an author of this work?Link to your sovereign AfriScholar profile
Published in: Beni-Suef University Journal of Basic and Applied Sciences (BJBAS)
Publisher: Springer Science+Business Media • Egypt • 2314-8535
DOI: https://doi.org/10.1016/j.bjbas.2016.01.003

Abstract

An acid treated montmorillonite was utilized as a low-cost adsorbent for the removal of heavy metals from an automobile effluent. The adsorbent was characterized by the Fourier transform infrared spectrophotometer and scanning electron microscope. The effects of pH, adsorbent dose, particle size and contact time on the sorption process were determined by batch methodology. Acid modification increased the Brunauer Emmett and Teller (BET) surface area and total pore volume of the montmorillonite from 55.76 to 96.48 m2/g and from 0.0688 to 0.101 cm3/g, respectively. The removal of heavy metals from the effluent followed the order: Zn > Cu > Mn > Cd > Pb > Ni, which is directly related to the concentration of metal ions in the effluents. The Freundlich isotherm was found to fit the experimental data properly than the Langmuir, Temkin and Dubinin–Radushkevich isotherm models. Kinetic analysis was performed by the application of the pseudo-first order, pseudo-second order, intraparticle diffusion and liquid film diffusion model. The process was found to be physisorption, controlled by the film diffusion mechanism. The acid treatment enhanced the adsorption capacity of the montmorillonite and was suitable for the removal of heavy metals from the automobile effluent.

Download Full Text PDFView at PublisherCrossref RecordCrossref XML

Verified Citation Velocity

Recorded scholarly citations in African and international peer-reviewed literature

129
Total Citations

Citations are continuously tracked and harvested across continental OJS endpoints and OpenAlex feeds.