Efficiency of Artificial Neural Networks for Modeling of Malachite Green Adsorption by Tea Waste and Adsorption Isotherm Study

Document Type : Research Paper

Authors

1 Assist. Prof., Dept. of Applied Chemistry, Faculty of Chemistry, University of Tabriz, Tabriz, Iran

2 BSc Student, Dept. of Applied Chemistry, Faculty of Chemistry, University of Tabriz, Tabriz, Iran

3 MSc Student, Dept. of Analytical Chemistry, Faculty of Chemistry, University of Tabriz, Tabriz, Iran

4 MSc Student, Dept. of Applied Chemistry, Faculty of Chemistry, University of Tabriz, Tabriz, Iran

Abstract

Nowadays water pollution is one of the most important problems in different societies. This problem increases with the development of countries. Existence of various dyes in waters is one of these important pollutions so adsorption can be used as an important method to eliminate dyes from waters. In this research, the adsorption of Malachite Green on odorant Do Ghazal tea waste was studied. The study of this issue was performed in laboratory’s temperature, with variation of different parameters like pH, adsorption time, amount of adsorbent and dye concentration. The results of the experiments show that the adsorption efficiency increases with more adsorbent addition, higher pH levels and time enhancement. Also the reduction of dye concentration causes better adsorption efficiencies. Moreover the study on isotherms of adsorption process confirmed that the adsorption obeys the Freundlich model. The results of this study show that the efficiency of Malachite Green elimination in aqueous solutions on odorant Do Ghazal tea waste was higher than 95%. An artificial neural networks (ANN) model was developed to predict the performance of the decolorization efficiency by the adsorption process based on the experimental data. A comparison between the predicted results of the designed ANN model and experimental data was also conducted. The ANN model yielded a determination coefficient of R2=0.9981. The model can describe the decolorization efficiency under different conditions. Odorant Do Ghazal tea can be used as a low cost and available adsorbent to removal of organic pollutants from contaminated waters. Artificial neural networks can be employed as an appropriate method for adsorption process modeling too.

Keywords

Main Subjects

References

Akar, S. T. & Uysal, R. 2010. Untreated clay with high adsorption capacity for effective removal of C.I. Acid Red 88 from aqueous solutions: batch and dynamic flow mode studies. Chemical Engineering Journal, 162, 591-598.
Aleboyeh, A., Kasiri, M. B., Olya, M. E. & Aleboyeh, H. 2008. Prediction of azo dye decolorization by UV/H2O2 using artificial neural networks. Dyes and Pigments, 77, 288-294.
Caselatto, A. M. F., Ferreira, J. F., Tambourgi, E. B., Moraes, R. & Silveira, E. 2011. Biodegradation of textile azo dyes by shewanella putrefaciens (CT 1967). Chemical Engineering Transactions, 24, 871-876.
Chang, K. 2015. World tea production and trade, current and future development. Food and Agriculture Organization of the United Nations, Rome, Italy.
Cristaldi, A., Conti, G. O., Jho, E. H., Zuccarello, P., Grasso, A., Copat, C. et al. 2017. Phytoremediation of contaminated soils by heavy metals and PAHs. A brief review. Environmental Technology and Innovation, 8, 309-326.
Despagne, F. & Luc Massart, D. 1998. Neural networks in multivariate calibration. Analyst, 123, 157-178.
Garg, V. K., Kumar, R. & Gupta, R. 2004. Removal of malachite green dye from aqueous solution by adsorption using agro-industry waste: a case study of Prosopis cineraria. Dyes and Pigments, 62, 1-10.
Hameed, B. H., Ahmad, A. L. & Latiff, K. N. A. 2007. Adsorption of basic dye (methylene blue) onto activated carbon prepared from rattan sawdust. Dyes and Pigments, 75, 143-149.
İnel, O. & Askin, A. 1996. Adsorption of monovalent cationic dyes on some silicates. Turkish Journal of Chemistry, 20, 276-282.
Janoš, P., Buchtová, H. & Rýznarová, M. 2003. Sorption of dyes from aqueous solutions onto fly ash. Water Research, 37, 4938-4944.
Khattri, S. D. & Singh, M. K. 1999. Adsorption of basic dyes from aqueous solution by natural adsorbent. Indian Journal of Chemical Technology, 6, 112-116.
Noori Motlagh, Z., Darvishi, R., Shams Khoram Abadi, G. H., Ghodini, H. & Foroughi, M. 2013. Study of the effective parameters on decolorization of methylene blue using UV radiation in the presence of immobilized catalyst. Journal of Ilam University of Medical Sciences, 21, 36-46. (In Persian)
Önal, Y., Akmil-Başar, C., Eren, D., Sarıcı-Özdemir, Ç. & Depci, T. 2006. Adsorption kinetics of malachite green onto activated carbon prepared from Tunçbilek lignite. Journal of Hazardous Materials, 128, 150-157.
Rao, K. V. K. 1995. Inhibition of DNA synthesis in primary rat hepatocyte cultures by malachite green: a new liver tumor promoter. Toxicology Letters, 81, 107-113.
Robinson, T., McMullan, G., Marchant, R. & Nigam, P. 2001. Remediation of dyes in textile effluent: a critical review on current treatment technologies with a proposed alternative. Bioresource Technology, 77, 247-255.
Salari, D., Daneshvar, N., Aghazadeh, F. & Khataee, A. R. 2005. Application of artificial neural networks for modeling of the treatment of wastewater contaminated with methyl tert-butyl ether (MTBE) by UV/H2O2 process. Journal of Hazardous Materials, 125, 205-210.
Shukla, R. J. & Singh, A. 1999. Adsorption of malachite green on to combination of chitin, activated charcoal and alumina. Asian Journal of Chemistry, 11(1), 259-260.
Srivastava, S., Sinha, R. & Roy, D. 2004. Toxicological effects of malachite green. Aquatic Toxicology, 66, 319-329.
Zarei, M., Niaei, A., Salari, D. & Khataee, A. R. 2010. Removal of four dyes from aqueous medium by the peroxi-coagulation method using carbon nanotube–PTFE cathode and neural network modeling. Journal of Electroanalytical Chemistry, 639, 167-174.
Zarei, M., Pezhhanfar, S. & Ahmadi Someh, A. 2017. Removal of acid red 88 from wastewater by adsorption on agro-based waste material. A case study of Iranian golden Sesamum indicum hull. Environmental Health Engineering and Management Journal, 4, 195-201.
Zuorro, A. & Lavecchia, R. 2014. Evaluation of UV/H2O2 advanced oxidation process (AOP) for the degradation of diazo dye Reactive green 19 in aqueous solution. Desalination and Water Treatment, 52, 1571-1577.
Zuorro, A., Lavecchia, R., Medici, F. & Piga, L. 2013. Spent tea leaves as a potential low-cost adsorbent for the removal of azo dyes from wastewater. Chemical Engineering Transactions, 32, 19-24.
Journal of Water and Wastewater; Ab va Fazilab ( in persian )
Volume 30, Issue 6 - Serial Number 124
November and December 2019
Pages 51-62

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