Turbidity and COD removal from leather processing effluents using TİO2-assisted photocatalytic-ozonation by response surface methodology

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dc.authorid0000-0001-6841-6457
dc.contributor.authorBüyükada, Musa
dc.date.accessioned2021-06-23T18:26:53Z
dc.date.available2021-06-23T18:26:53Z
dc.date.issued2018
dc.departmentBAİBÜ, Mühendislik Fakültesi, Kimya Mühendisliği Bölümüen_US
dc.description.abstractIn the present study, concurrently removal of COD and turbidity from leather processing effluents (LPE) using $TiO_2$ – assisted photocatalytic-ozonation were investigated by utilization of Box-Behnken design (BBD) in planning experiments. Effects of ozone dose (OD, mg $L^{-1}$), catalyst dose (CD, g $L^{-1}$), and aeration (A, mL $min^{-1}$) were performed as explanatory variables. An increase both in doses of ozone and catalyst and a decrease in aeration leaded increases both in removals of COD and turbidity. Values of 96.77% and 95.37% were obtained as the highest COD and turbidity removal efficiencies, respectively. This showed that $TiO_2$ -assisted photocatalytic-ozonation process was significantly effective for the treatment of LPE. By using BBD, 2.95 g $L^{-1}$ of CD, 19.99 mg $L^{-1}$ of OD, and 1.63 mL $min^{-1}$ of A were determined as BBD-optimized operating conditions. BBD suggested removals of 96.77% and 94.93% for COD and turbidity, respectively at these optimized conditions. Validation experiments at BBD-optimized conditions were resulted as 95.52%±1.28 and 94.36%±2.52 for COD removal and turbidity removal, respectively. Good agreement between predicted values and experimental results demonstrated the accuracy of BBD in optimization of explanatory variables of $TiO_2$ -assisted photocatalytic-ozonation process. Finally, multiple non-linear regression (MNLR) studies were performed to state the variation in responses and also to predict the responses. The proposed models predicted COD and turbidity removals with regression coefficients of 99.99% and 99.97%, respectively. These findings also showed that MNLR was an efficient way to model and to predict the response variables of photocatalytic-ozonation process.en_US
dc.identifier.endpage10en_US
dc.identifier.issn2636-8498
dc.identifier.issue3en_US
dc.identifier.scopus2-s2.0-85069716684en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage1en_US
dc.identifier.trdizinidTR-DizinIDen_US
dc.identifier.urihttps://app.trdizin.gov.tr/makale/TXpVMk16VXlNZz09
dc.identifier.urihttps://hdl.handle.net/20.500.12491/1557
dc.identifier.volume1en_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakTR-Dizinen_US
dc.institutionauthorBüyükada, Musa
dc.language.isoenen_US
dc.relation.ispartofEnvironmental Research & Technology (Online)en_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectLeather Processing Effluents
dc.subjectPhotocatalytic-Ozonation
dc.subjectCOD
dc.subjectTurbidity
dc.subjectEmpirical Modeling
dc.titleTurbidity and COD removal from leather processing effluents using TİO2-assisted photocatalytic-ozonation by response surface methodologyen_US
dc.typeArticleen_US

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