International Journal of Environmental Science and Development

Abstract—The present research focused on the optimization of coagulation process parameters by using iron-based coagulant for the treatment of most recalcitrant reactive dye i.e. Reactive Blue 19. The manual traditional methods of optimization and Central Composite Design (CCD) using RSM were applied to optimize three operating variables of coagulation/flocculation process including initial pH, coagulant dosage and initial dye concentration. The results obtained by using RSM software showed more relevant and specific results as compared with the traditional method. The RSM result shows that an increase in pH was beneficial for enhancing dye removal, up to a certain level but the further increment in pH, resulted in a decrease in dye removal. Decolorization of RB19 has been improved with increasing coagulant dose but its concentration in the treated water also increased as they showed more prominent oxidized color, when comes in contact with air. The optimum conditions found by RSM was most appropriate and accurate as compared to that of the traditional method. The optimum conditions i.e. initial pH, coagulant dosage and initial dye concentration were found to be 7.3, 234.82 mg /L and 150 mg/L, respectively for dye removal of 83.45 %. The test proved that RSM would be a good tool for the optimization process of parameters. Though ferric chloride gave better results as coagulant still presence of higher concentration of iron in the effluent can have adverse effects, that can be further evaluated.

Index Terms—Coagulation/flocculation, dye removal, ferric chloride, response surface design.

Sonalika Sonal and Brijesh Kumar Mishra are with the Department of Environmental Science and Engineering, Indian Institute of Engineering (Indian School of Mines), Dhanbad, Jharkhand, India (e-mail: brijesh@iitism.ac.in).

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Cite: Sonalika Sonal and Brijesh Kumar Mishra, "Optimization of the Operational Conditions for the Treatment of Reactive Dyes through a Statistical Tool: Response Surface Methodology," International Journal of Environmental Science and Development vol. 10, no. 6, pp. 193-196, 2019.