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Box-Behnken design-based biodiesel wastewater treatment using sequential acid cracking and electrochemical peroxidation process: Focus on COD, oil-grease and volatile fatty acids removals

The treatability of biodiesel wastewater by the electrochemical peroxidation process following acidification pretreatment was investigated. Box-Behnken design, one of the experimental designs of response surface methodology, was applied to optimize the process parameters for chemical oxygen demand (...

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Bibliographic Details
Published in:The Korean journal of chemical engineering 2022-09, Vol.39 (9), p.2555-2570
Main Authors: Guvenc, Senem Yazici, Cebi, Aleyna, Can-Güven, Emine, Demir, Ahmet, Ghanbari, Farshid, Varank, Gamze
Format: Article
Language:English
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Summary:The treatability of biodiesel wastewater by the electrochemical peroxidation process following acidification pretreatment was investigated. Box-Behnken design, one of the experimental designs of response surface methodology, was applied to optimize the process parameters for chemical oxygen demand (COD), oil-grease, and volatile fatty acids (VFAs) removal from biodiesel wastewater. The process parameters, i.e., applied current, H 2 O 2 /COD ratio, and reaction time, were optimized and the total cost of the process was determined. After the acidification process as a pretreatment, the COD, oil-grease, and VFAs removal efficiencies were 25.4%, 68.7%, and 50%, respectively Optimum conditions determined by the developed model for maximum oil-grease removal (98.2%) were applied: current 1.0 A, H 2 O 2 /COD ratio 0.4, and reaction time 32.8 minutes. This devised Box-Behnken model predicted removal efficiencies of 45.5%, 98.2%, and 49.5% for COD, oil-grease, and VFAs, respectively. The total cost of the process determined by the model and obtained from the validation experiments was 2.03 €/m 3 and 1.97 €/m 3 , respectively. The results of the study showed that the applied process was efficient in pollutant removal from acidified biodiesel wastewater and the Box-Behnken design can be applied to explain the mechanism of the process and optimize the process parameters.
ISSN:0256-1115
1975-7220
DOI:10.1007/s11814-022-1118-z