4.5 Article

Degradation of textile dyes Remazol Yellow Gold and reactive Turquoise: optimization, toxicity and modeling by artificial neural networks

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WATER SCIENCE AND TECHNOLOGY
卷 77, 期 -, 页码 812-823

出版社

IWA PUBLISHING
DOI: 10.2166/wst.2018.251

关键词

advanced oxidative processes; artificial neural networks; kinetic; textile dyes; toxicity

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In this work, the degradation of Remazol Yellow Gold RNL-150% and Reactive Turquoise Q-G125 were investigated using AOP: photolysis, UV/H2O2, Fenton and photo-Fenton. It was found that the photo-Fenton process employing sunlight radiation was the most efficient, obtaining percentages of degradation above 87%. The ideal conditions for the degradation of the dyes were determined from a factorial design 2(3) and study of the [H2O2] ([H2O2] equal to 100 mg.L-1); [Fe] equal to 1 mg.L-1 and pH between 3 and 4. In the kinetic study, a degradation of more than 97% was obtained after 150 min for the chromophoric groups and 91% for the aromatic compounds. The experimental data obtained presented a good fit to the nonlinear kinetic model. The model of artificial neural networks multilayer perceptron (MLP) (4-11-5) using the software Statistica 8.0 enabled the modeling of the degradation process and showed a better prediction of the data. The toxicity to the seeds of Lactuca sativa and the bacteria Escherichia coli and Salmonella enteritidis allowed to evaluate the effectiveness of the process. The results of this study suggest that the use of photo-Fenton process with sunlight radiation is an effective way to degrade the dyes under study.

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