Response surface methodology and artificial neural network modeling of reactive red 33 decolorization by O3/UV in a bubble column reactor

Document Type : Research Paper


Department of Chemical Engineering, Faculty of Engineering, Razi University, Kermanshah, Iran


In this work, response surface methodology (RSM) and artificial neural network (ANN) were used to predict the decolorization efficiency of Reactive Red 33 (RR 33) by applying the O3/UV process in a bubble column reactor. The effects of four independent variables including time (20-60 min), superficial gas velocity (0.06-0.18 cm/s), initial concentration of dye (50-150 ppm), and pH (3-11) were investigated using a 3-level 4-factor central composite experimental design. This design was utilized to train a feed-forward multilayered perceptron artificial neural network with a back-propagation algorithm. A comparison between the models’ results and experimental data gave high correlation coefficients and showed that the two models were able to predict Reactive Red 33 removal by employing the O3/UV process. Considering the results of the yield of dye removal and the response surface-generated model, the optimum conditions for dye removal were found to be a retention time of 59.87 min, a superficial gas velocity of 0.18 cm/s, an initial concentration of 96.33 ppm, and a pH of 7.99.


Main Subjects

[1] Essadki, A. H., Bennajah, M., Gourich, B., Vial, C., Azzi, M., Delmas, H. (2008). Electrocoagulation /electroflotation in an external-loop airlift reactor—application to the decolorization of textile dye wastewater: a case study. Chemical engineering and processing: Process intensification, 47(8), 1211-1223.
[2] Daneshvar, N., Khataee, A. R., Ghadim, A. A.,    Rasoulifard, M. H. (2007). Decolorization of CI Acid Yellow 23 solution by electrocoagulation process: Investigation of operational parameters and evaluation of specific electrical energy consumption (SEEC). Journal of hazardous materials, 148(3), 566-572.
[3] Wu, C. H., Chang, C. L. (2006). Decolorization of Reactive Red 2 by advanced oxidation processes: Comparative studies of homogeneous and heterogeneous systems. Journal of hazardous materials, 128(2), 265-272.
[4] Anjaneyulu, Y., Chary, N. S., Raj, D. S. S. (2005). Decolourization of industrial effluents–available methods and emerging technologies–a review. Reviews in environmental science and biotechnology, 4(4), 245-273.
[5] Saratale, R. G., Saratale, G. D., Chang, J. S., Govindwar, S. P. (2011). Bacterial decolorization and degradation of azo dyes: A review. Journal of the Taiwan institute of chemical engineers, 42(1), 138-157.
[6] Wu, C. H., Kuo, C. Y., Chang, C. L. (2007). Decolorization of azo dyes using catalytic ozonation. Reaction kinetics and catalysis letters, 91(1), 161-168.
[7] Golder, A. K., Hridaya, N., Samanta, A. N., Ray, S. (2005). Electrocoagulation of methylene blue and eosin yellowish using mild steel electrodes. Journal of hazardous materials, 127(1), 134-140.
[8] Do, J. S., Chen, M. L. (1994). Decolourization of dye-containing solutions by electrocoagulation. Journal of applied electrochemistry, 24(8), 785-790.
[9] Jiang, J. Q., Graham, N. J. D. (1996). Enhanced coagulation using Al/Fe (III) coagulants: effect of coagulant chemistry on the removal of colour-causing NOM. Environmental technology, 17(9), 937-950.
[10] Slokar, Y. M., Le Marechal, A. M. (1998). Methods of decoloration of textile wastewaters. Dyes and pigments, 37(4), 335-356.
[11] Li, G., Zhao, X. S., Ray, M. B. (2007). Advanced oxidation of orange II using TiO2 supported on porous adsorbents: The role of pH, H2O2 and O3. Separation and purification technology, 55(1), 91-97.
[12] He, Z., Lin, L., Song, S., Xia, M., Xu, L., Ying, H., Chen, J. (2008). Mineralization of CI reactive blue 19 by ozonation combined with sonolysis: Performance optimization and degradation mechanism. Separation and purification technology, 62(2), 376-381.
[13] Sanches, S., Crespo, M. T. B., Pereira, V. J. (2010). Drinking water treatment of priority pesticides using low pressure UV photolysis and advanced oxidation processes. Water research, 44(6), 1809-1818.
[14] Gogate, P. R., Pandit, A. B. (2004). A review of imperative technologies for wastewater treatment I: oxidation technologies at ambient conditions. Advances in environmental research, 8(3), 501-551.
[15] Mohajerani, M., Mehrvar, M., Ein-Mozaffari, F. (2012). Using an external-loop airlift sonophotoreactor to enhance the biodegradability of aqueous sulfadiazine solution. Separation and purification technology, 90, 173-181.
[16] Lucas, M. S., Peres, J. A., Puma, G. L. (2010). Treatment of winery wastewater by ozone-based advanced oxidation processes (O3, O3/UV and O3/UV/H2O2) in a pilot-scale bubble column reactor and process economics. Separation and purification technology, 72(3), 235-241.
[17] Beltran, F. J. (2003). Ozone reaction kinetics for water and wastewater systems. CRC Press.
[18] Khan, H., Ahmad, N., Yasar, A., Shahid, R. (2010). Advanced oxidative decolorization of Red Cl-5B: Effects of dye concentration, process optimization and reaction kinetics. Polish journal of environmental studies., 19(1), 83-92.
[19] Beltrán, F. J., Encinar, J., González, J. F. (1997). Industrial wastewater advanced oxidation. Part 2. Ozone combined with hydrogen peroxide or UV radiation. Water research, 31(10), 2415-2428.
[20] Alnaizy, R., Akgerman, A. (2000). Advanced oxidation of phenolic compounds. Advances in environmental research, 4(3), 233-244.
[21] Gimeno, O., Carbajo, M., Beltrán, F. J., Rivas, F. J. (2005). Phenol and substituted phenols AOPs remediation. Journal of hazardous materials, 119(1), 99-108.
[22] Esplugas, S., Gimenez, J., Contreras, S., Pascual, E., Rodriguez, M. (2002). Comparison of different advanced oxidation processes for phenol degradation, Water research, 36(4), 1034-1042.
[23] Shu, H. Y., Chang, M. C. (2005). Decolorization effects of six azo dyes by O3, UV/O3 and UV/H 2O2 processes. Dyes and pigments, 65(1), 25-31.
[24] Peternel, I., Koprivanac, N., Kusic, H. (2006). UV-based processes for reactive azo dye mineralization. Water research, 40(3), 525-532.
[25] Maran, J. P., Sivakumar, V., Sridhar, R., Immanuel, V. P. (2013). Development of model for mechanical properties of tapioca starch based edible films. Industrial crops and products, 42, 159-168.
[26] Maran, J. P., Sivakumar, V., Sridhar, R., Thirugnanasambandham, K. (2013). Development of model for barrier and optical properties of tapioca starch based edible films. Carbohydrate polymers, 92(2), 1335-1347.
27] Maran, J. P., Manikandan, S., Nivetha, C. V., Dinesh, R. (2013). Ultrasound assisted extraction of bioactive compounds from Nephelium lappaceum L. fruit peel using central composite face centered response surface design. Arabian journal of chemistry
[28] Hemmat, J., MazaheriAssadi, M. (2013). Optimization of reactive blue 19 biodegradation by Phanerochaetechrysosporium. International journal of environmental research, 7(4), 957-962.
[29] Berkani, M., Bouhelassa, M., Bouchareb, M. K. (2015). Implementation of a venturi photocatalytic reactor: Optimization of photodecolorization of an industrial azo dye. Arabian Journal of Chemistry,
[30] Zobel, C. W., Cook, D. F. (2011). Evaluation of neural network variable influence measures for process control. Engineering applications of artificial intelligence, 24(5), 803-812.
[31] Alavala, C. R. (2007). Logic and Neural Networks: Basic concepts and applications. New Age. New Age Publications.
[32] Pilkington, J. L., Preston, C., Gomes, R. L. (2014). Comparison of response surface methodology (RSM) and artificial neural networks (ANN) towards efficient extraction of artemisinin from Artemisia annua. Industrial crops and products, 58, 15-24.
[33] Aber, S., Daneshvar, N., Soroureddin, S. M., Chabok, A., Asadpour-Zeynali, K. (2007). Study of acid orange 7 removal from aqueous solutions by powdered activated carbon and modeling of experimental results by artificial neural network. Desalination, 211(1), 87-95.
[34] Zarei, M., Khataee, A. R., Ordikhani-Seyedlar, R., Fathinia, M. (2010). Photoelectro-Fenton combined with photocatalytic process for degradation of an azo dye using supported TiO2 nanoparticles and carbon nanotube cathode: neural network modeling. Electrochimica Acta, 55(24), 7259-7265.
[35] 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(1), 167-174.
[36] Cheok, C. Y., Chin, N. L., Yusof, Y. A., Talib, R. A., Law, C. L. (2012). Optimization of total phenolic content extracted from Garcinia mangostana Linn. Hull using response surface methodology versus artificial neural network. Industrial crops and products, 40, 247-253.
[37] Khajeh, M., Kaykhaii, M., Sharafi, A. (2013).   Application of PSO-artificial neural network and response surface methodology for removal of methylene blue using silver nanoparticles from water samples. Journal of industrial and engineering chemistry, 19(5), 1624-1630.
[38] Ebrahimzadeh, H., Tavassoli, N., Sadeghi, O., Amini, M. M. (2012). Optimization of solid-phase extraction using artificial neural networks and response surface methodology in combination with experimental design for determination of gold by atomic absorption spectrometry in industrial wastewater samples. Talanta, 97, 211-217.
[39] Khayet, M., Cojocaru, C. (2013). Artificial neural network model for desalination by sweeping gas membrane distillation. Desalination, 308, 102-110.
[40] Lakshminarayanan, A. K., Balasubramanian, V. (2009). Comparison of RSM with ANN in predicting tensile strength of friction stir welded AA7039 aluminium alloy joints. Transactions of nonferrous metals society of China, 19(1), 9-18.
[41] Sinha, K., Saha, P. D., Datta, S. (2012). Response surface optimization and artificial neural network modeling of microwave assisted natural dye extraction from pomegranate rind. Industrial crops and products, 37(1), 408-414.
[42] Maran, J. P., Sivakumar, V., Thirugnanasambandham, K., Sridhar, R. (2013). Artificial neural network and response surface methodology modeling in mass transfer parameters predictions during osmotic dehydration of Carica papaya L. Alexandria engineering journal, 52(3), 507-516.
[43] Yang, S. H., Chung, P. W. H., Brooks, B. W. (1999). Multi-stage modelling of a semi-batch polymerization reactor using artificial neural networks. Chemical engineering research and design, 77(8), 779-783.
[44] Bassam, A., Ortega-Toledo, D., Hernandez, J. A., Gonzalez-Rodriguez, J. G., Uruchurtu, J. (2009). Artificial neural network for the evaluation of CO2 corrosion in a pipeline steel. Journal of solid state electrochemistry, 13(5), 773-780.
[45] Baughman, D. R., Liu, Y. A. (2014). Neural networks in bioprocessing and chemical engineering. Academic press.
[46] Kusic, H., Koprivanac, N., Bozic, A. L. (2006). Minimization of organic pollutant content in aqueous solution by means of AOPs: UV-and ozone-based technologies. Chemical engineering journal, 123(3), 127-137.
[47] Peternel, I., Koprivanac, N., Kusic, H. (2006). UV-based processes for reactive azo dye mineralization. Water research, 40(3), 525-532.
[48] Sevimli, M. F., Sarikaya, H. Z. (2002). Ozone treatment of textile effluents and dyes: effect of applied ozone dose, pH and dye concentration. Journal of chemical technology and biotechnology, 77(7), 842-850.
[49] Azbar, N., Yonar, T., Kestioglu, K. (2004). Comparison of various advanced oxidation processes and chemical treatment methods for COD and color removal from a polyester and acetate fiber dyeing effluent. Chemosphere, 55(1), 35-43.
[50] Sevimli, M. F., Sarikaya, H. Z. (2005). Effect of some operational parameters on the decolorization of textile effluents and dye solutions by ozonation. Environmental technology, 26(2), 135-144.
[51] Konsowa, A. H. (2003). Decolorization of wastewater containing direct dye by ozonation in a batch bubble column reactor. Desalination, 158(1), 233-240.
[52] Selcuk, H. (2005). Decolorization and detoxification of textile wastewater by ozonation and coagulation processes. Dyes and pigments, 64(3), 217-222.
[53] Aksu, Z. (2003). Reactive dye bioaccumulation by Saccharomyces cerevisiae. Process biochemistry, 38(10), 1437-1444.
[54] Asad, S., Amoozegar, M. A., Pourbabaee, A., Sarbolouki, M. N., Dastgheib, S. M. M. (2007). Decolorization of textile azo dyes by newly isolated halophilic and halotolerant bacteria. Bioresource technology, 98(11), 2082-2088.
[55] Wu, J., Wang, T. (2001). Ozonation of aqueous azo dye in a semi-batch reactor. Water research, 35(4), 1093-1099.
[56] Wang, K. H., Hsieh, Y. H., Wu, C. H., Chang, C. Y. (2000). The pH and anion effects on the heterogeneous photocatalytic degradation of o-methylbenzoic acid in TiO2 aqueous suspension. Chemosphere, 40(4), 389-394.
[57] Zhang, H., Duan, L., Zhang, D. (2006). Decolorization of methyl orange by ozonation in combination with ultrasonic irradiation. Journal of hazardous materials, 138(1), 53-59.
[58] Yetilmezsoy, K., Demirel, S. (2008). Artificial neural network (ANN) approach for modeling of Pb (II) adsorption from aqueous solution by Antep pistachio (Pistacia Vera L.) shells. Journal of hazardous materials, 153(3), 1288-1300.
[59] Bingöl, D., Hercan, M., Elevli, S., Kılıç, E. (2012). Comparison of the results of response surface methodology and artificial neural network for the   biosorption of lead using black cumin. Bioresource technology, 112, 111-115.
[60] Bali, U., Çatalkaya, E., Şengül, F. (2004). Photodegradation of reactive black 5, direct red 28 and direct yellow 12 using UV, UV/H2O2 and UV/H2O2/Fe2+: a comparative study. Journal of hazardous materials, 114(1), 159-166.
[61] Wu, J., Wang, T. (2001). Ozonation of aqueous azo dye in a semi-batch reactor. Water research, 35(4), 1093-1099.
[62] Neamtu, M., Yediler, A., Siminiceanu, I., Kettrup, A. (2003). Oxidation of commercial reactive azo dye aqueous solutions by the photo-Fenton and Fenton-like processes. Journal of photochemistry and photobiology A: Chemistry, 161(1), 87-93.
[63] Guendy, H. R. (2007). Ozone treatment of textile wastewater relevant to toxic effect elimination in marine environment. Egyptian journal of aquatic research, 33 (1), 98-115.
[64] Atchariyawut, S., Phattaranawik, J., Leiknes, T., Jiraratananon, R. (2009). Application of ozonation membrane contacting system for dye wastewater treatment. Separation and purification technology, 66(1), 153-158.