[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Accepted articles :: Archive :: Search :: Submit :: Contact ::
Main Menu
Home::
Journal Information::
Articles archive::
For Authors::
For Reviewers::
Registration::
Contact us::
Site Facilities::
Indexing::
Open Access Policy::
::
Search in website

Advanced Search
..
Receive site information
Enter your Email in the following box to receive the site news and information.
..
:: Volume 8, Issue 1 (11-2020) ::
jehe 2020, 8(1): 83-98 Back to browse issues page
Modeling and Optimization of Methylene Blue Adsorption from Aqueous Solution by Pumice Based on RSM-CCD and ANN-GA Methods
Ghorban Asgari , Mohammad Darvishmotevalli , Alireza Beheshti , Mehdi Salari *
Department of Environmental Health Engineering, School of Health, Hamadan University of Medical Sciences, Hamadan, Iran
Abstract:   (1309 Views)
 
Background: The discharge of a large volume of colored wastewater into receiving water sources has caused widespread concern around the world. The aim of this study was to investigate the efficiency of pumice as an adsorbent in removing methylene blue (MB) from aqueous solution. The adsorption process was also modeled and optimized by the methods as follows: central composite design-central composite design (RSM-CCD) and artificial neural network-genetic algorithm (ANN-GA).
Methods and Materials: The independent variables in the study were included pH (3-11), contact time (10-50 minutes), adsorbent dose (0.1-2 g/L), and MB concentration (20-100 mg/l). The effect of these parameters on the efficiency of pumice in MB uptake was modeled and optimized by RSM-CCD and ANN-GA methods. A spectrophotometer at 620 nm was used to measure the residual MB concentration in solution.
Results: The results showed that the RSM-CCD method has the ability to develop a quadratic polynomial model with high validity (R2 = 0.9997) for the adsorption process. Similarly, the ANN-GA method fitted well with experimental data to develop a model with high validity (R2 = 0.9978). The results of optimization process by RSM-CCD and ANN-GA methods obtained the highest adsorption efficiency at pH = 11, contact time = 50 minutes, adsorbent dose = 1 g/L, and concentration MB = 20 mg/L. Adsorption efficiency shows a direct relationship with pH, contact time and adsorbent dose and inversely with contaminant concentration. The linear effect of pollutant concentration and adsorbent dose variables had the greatest effect on adsorption efficiency.
Conclusion: In this study, it was observed that pumice as a cheap and available adsorbent can be considered as a suitable choice for absorbing dye pollutants from aqueous media. RSM-CCD and ANN-GA methods can also be used to model and optimize adsorption processes.
Keywords: Methylene blue, Pumice, Adsorption, Aqueous solution
Full-Text [PDF 1342 kb]   (697 Downloads)    
Type of Study: Research | Subject: Special
Received: 2020/08/3 | Accepted: 2020/12/7 | Published: 2021/01/4
Add your comments about this article
Your username or Email:

CAPTCHA



XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Asgari G, Darvishmotevalli M, Beheshti A, Salari M. Modeling and Optimization of Methylene Blue Adsorption from Aqueous Solution by Pumice Based on RSM-CCD and ANN-GA Methods. jehe 2020; 8 (1) :83-98
URL: http://jehe.abzums.ac.ir/article-1-808-en.html


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 8, Issue 1 (11-2020) Back to browse issues page
مجله مهندسی بهداشت محیط Journal of Environmental Health Enginering
Persian site map - English site map - Created in 0.04 seconds with 37 queries by YEKTAWEB 4645