Multivariate analysis of anionic, cationic and nonionic textile surfactant degradation with the H₂O₂/UV-C process by using the capabilities of response surface methodology
Anionic, cationic and nonionic surfactants being frequently employed in the textile preparation process were subjected to H₂O₂/UV-C treatment. As a consequence of the considerable number of parameters affecting the H₂O₂/UV-C process, an experimental design methodology was used to mathematically desc...
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Veröffentlicht in: | Journal of hazardous materials 2011-01, Vol.185 (1), p.193-203 |
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creator | Olmez-Hanci, Tugba Arslan-Alaton, Idil Basar, Gulcan |
description | Anionic, cationic and nonionic surfactants being frequently employed in the textile preparation process were subjected to H₂O₂/UV-C treatment. As a consequence of the considerable number of parameters affecting the H₂O₂/UV-C process, an experimental design methodology was used to mathematically describe and optimize the single and combined influences of the critical process variables treatment time, initial H₂O₂concentration and chemical oxygen demand (COD) on parent pollutant (surfactant) as well as organic carbon (COD and total organic carbon (TOC)) removal efficiencies. Multivariate analysis was based on two different photochemical treatment targets; (i) full oxidation/complete treatment of the surfactants or, alternatively, (ii) partial oxidation/pretreatment of the surfactants to comply with the legislative discharge requirements. According to the established polynomial regression models, the process independent variables “treatment time” (exerting a positive effect) and “initial COD content” (exerting a negative effect) played more significant roles in surfactant photodegradation than the process variable “initial H₂O₂ concentration” under the studied experimental conditions. |
doi_str_mv | 10.1016/j.jhazmat.2010.09.018 |
format | Article |
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As a consequence of the considerable number of parameters affecting the H₂O₂/UV-C process, an experimental design methodology was used to mathematically describe and optimize the single and combined influences of the critical process variables treatment time, initial H₂O₂concentration and chemical oxygen demand (COD) on parent pollutant (surfactant) as well as organic carbon (COD and total organic carbon (TOC)) removal efficiencies. Multivariate analysis was based on two different photochemical treatment targets; (i) full oxidation/complete treatment of the surfactants or, alternatively, (ii) partial oxidation/pretreatment of the surfactants to comply with the legislative discharge requirements. 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As a consequence of the considerable number of parameters affecting the H₂O₂/UV-C process, an experimental design methodology was used to mathematically describe and optimize the single and combined influences of the critical process variables treatment time, initial H₂O₂concentration and chemical oxygen demand (COD) on parent pollutant (surfactant) as well as organic carbon (COD and total organic carbon (TOC)) removal efficiencies. Multivariate analysis was based on two different photochemical treatment targets; (i) full oxidation/complete treatment of the surfactants or, alternatively, (ii) partial oxidation/pretreatment of the surfactants to comply with the legislative discharge requirements. According to the established polynomial regression models, the process independent variables “treatment time” (exerting a positive effect) and “initial COD content” (exerting a negative effect) played more significant roles in surfactant photodegradation than the process variable “initial H₂O₂ concentration” under the studied experimental conditions.</abstract><cop>Kidlington</cop><pub>Elsevier B.V</pub><doi>10.1016/j.jhazmat.2010.09.018</doi><tpages>11</tpages></addata></record> |
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subjects | Applied sciences Carbon Cationic Chemical engineering chemical oxygen demand Crack opening displacement Exact sciences and technology experimental design hydrogen peroxide Mathematical analysis Mathematical models multivariate analysis Nonionic Oxidation photolysis pollutants Pollution Reactors regression analysis response surface methodology Surfactants Textiles ultraviolet radiation |
title | Multivariate analysis of anionic, cationic and nonionic textile surfactant degradation with the H₂O₂/UV-C process by using the capabilities of response surface methodology |
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