期刊
JOURNAL OF WATER SUPPLY RESEARCH AND TECHNOLOGY-AQUA
卷 61, 期 7, 页码 413-426出版社
IWA PUBLISHING
DOI: 10.2166/aqua.2012.054
关键词
activated carbon; artificial neural network; cephalexin; multiobjective optimization; ozonation; response surface methodology
This study examines the effect of pH of solution, cephalexin (CEX) concentration, and O-3 dosage on removal of CEX by catalytic ozonation. All three parameters were found to exert a significant effect on the removal of cephalexin and on the enhancement in biodegradability of solution. The operating conditions were optimized using response surface methodology (RSM) and artificial neural network (ANN). Both RSM and ANN models were found capable of predicting removal of CEX during catalytic ozonation. Simultaneous optimization of two responses (chemical oxygen demand (COD) removal and CEX removal) was carried out using genetic algorithm based multiobjective optimization. Non-dominated Pareto optimal solutions provided the range of optimum conditions for the catalytic ozonation process. The optimized values of pH (9.7), ozone supply (34.5 mg/L), and CEX concentration (33.6 mg/L) using GA multiobjective optimization corresponded to complete conversion of CEX with 72% removal of COD.
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