Prediction of Heavy Metal Removal by Different Liner Materials from Landfill Leachate: Modeling of Experimental Results Using Artificial Intelligence Technique
Joint Authors
Turan, Nurdan Gamze
Gümüşel, Emine Beril
Ozgonenel, Okan
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-5, 5 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-06-10
Country of Publication
Egypt
No. of Pages
5
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
An intensive study has been made to see the performance of the different liner materials with bentonite on the removal efficiency of Cu(II) and Zn(II) from industrial leachate.
An artificial neural network (ANN) was used to display the significant levels of the analyzed liner materials on the removal efficiency.
The statistical analysis proves that the effect of natural zeolite was significant by a cubic spline model with a 99.93% removal efficiency.
Optimization of liner materials was achieved by minimizing bentonite mixtures, which were costly, and maximizing Cu(II) and Zn(II) removal efficiency.
The removal efficiencies were calculated as 45.07% and 48.19% for Cu(II) and Zn(II), respectively, when only bentonite was used as liner material.
However, 60% of natural zeolite with 40% of bentonite combination was found to be the best for Cu(II) removal (95%), and 80% of vermiculite and pumice with 20% of bentonite combination was found to be the best for Zn(II) removal (61.24% and 65.09%).
Similarly, 60% of natural zeolite with 40% of bentonite combination was found to be the best for Zn(II) removal (89.19%), and 80% of vermiculite and pumice with 20% of bentonite combination was found to be the best for Zn(II) removal (82.76% and 74.89%).
American Psychological Association (APA)
Turan, Nurdan Gamze& Gümüşel, Emine Beril& Ozgonenel, Okan. 2013. Prediction of Heavy Metal Removal by Different Liner Materials from Landfill Leachate: Modeling of Experimental Results Using Artificial Intelligence Technique. The Scientific World Journal،Vol. 2013, no. 2013, pp.1-5.
https://search.emarefa.net/detail/BIM-1011749
Modern Language Association (MLA)
Turan, Nurdan Gamze…[et al.]. Prediction of Heavy Metal Removal by Different Liner Materials from Landfill Leachate: Modeling of Experimental Results Using Artificial Intelligence Technique. The Scientific World Journal No. 2013 (2013), pp.1-5.
https://search.emarefa.net/detail/BIM-1011749
American Medical Association (AMA)
Turan, Nurdan Gamze& Gümüşel, Emine Beril& Ozgonenel, Okan. Prediction of Heavy Metal Removal by Different Liner Materials from Landfill Leachate: Modeling of Experimental Results Using Artificial Intelligence Technique. The Scientific World Journal. 2013. Vol. 2013, no. 2013, pp.1-5.
https://search.emarefa.net/detail/BIM-1011749
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1011749