Studies on decolorization of dye wastewater in down flow jet loop sparged reactor using response surface methodology

被引:2
作者
Mugaishudeen, G. [1 ]
Shiran, M. S. [1 ]
Mubeen, H. Mohamed [1 ]
机构
[1] Kongu Engn Coll, Dept Chem Engn, Erode 638060, Tamil Nadu, India
关键词
Down flow jet loop reactor; Decolorization percentage; Dye wastewater; Ozonation; Response surface methodology; METHYLENE-BLUE; DEGRADATION; OZONATION; OZONE; EFFLUENT; REMOVAL; SYSTEMS; O-3;
D O I
10.5004/dwt.2022.28686
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Textile industries consume large quantities of water during the dyeing process, some amount of dyes remains unfixed and generates colored effluent. Untreated textile wastewater when discharged into the environment is one of the most hazardous practices. Many treatment methods like coagulation-flocculation, adsorption on activated carbon, membrane filtration process, electro-chemical and thermal separation processes are currently in use to treat textile wastewater are not only expensive but also inability to reuse the spent inorganic salts because of color acquired during the dyeing process. The main scope of this study is to propose an alternate method for the decolorization of textile wastewater using a down flow jet loop sparged reactor. Ozone and effluent were entered as gas and liquid phases respectively in a jet loop reactor to treat simulated dye wastewater. Color removal efficiencies have been studied for 100 and 50 ppm of Congo red synthetic dye. Response surface methodology ( RSM) was used to optimize the performance of the down flow jet loop sparged reactor. The effect of three variables ( effluent flow rate, ozonation time, and the sparger openings) on the percentage of decolorization was evaluated. The optimum condition was found at 0.4 L/min of effluent flow rate, 30 min of ozonation time, and 4 opening spargers for the maximum percentage of decolorization of about 95%-99%. The significance of the RSM model was determined by the R-2 value (95%). The experimental results were in close agreement with model prediction.
引用
收藏
页码:126 / 137
页数:12
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