Multivariate analysis of anionic, cationic and nonionic textile surfactant degradation with the H(2)O(2)/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 H(2)O(2)/UV-C treatment. As a consequence of the considerable number of parameters affecting the H(2)O(2)/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 H(2)O(2)concentration 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 H(2)O(2) concentration" under the studied experimental conditions.