کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
151033 | 456461 | 2011 | 13 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Modeling of iron activated persulfate oxidation treating reactive azo dye in water matrix Modeling of iron activated persulfate oxidation treating reactive azo dye in water matrix](/preview/png/151033.png)
Advanced oxidation processes (AOPs) offer effective solutions for the treatment of wastewaters containing hazardous and refractory organic pollutants. However, their efficiency is strongly influenced by varying process conditions thus the prediction of the system behavior is of an unappreciable interest. In this study iron activated persulfate oxidation was applied for degradation of reactive azo dye, C.I. Reactive Red 45 (RR45), in water matrix. Fe2+/S2O82− and Fe0/S2O82− processes were maintained in a dark as well as with UV light assistance. The main purpose was to develop the flexible mathematical/mechanistic model (MM) which would (i) predict not only the conversion of parent pollutant, i.e. decolorization of model dye solution, but also the mineralization of model pollutant, and (ii) could keep the predictive power regardless the process operating conditions. Hence, the pH dependent mechanism describing both organic and inorganic ferric complexes formation as one of the major limitations of iron activated processes, as well as iron activated persulfate oxidation, was built in the model. Developed MM showed a high accuracy in predicting the degradation of RR45 considering both decolorization and mineralization, as well as the profiles of iron species, persulfate decomposition, the subsequent formation of sulfates and pH changes during the treatment. Good agreement of the data predicted and the empirically obtained was confirmed by calculated root mean square deviation (RMSD) values.
► We study iron activated persulfate oxidation of reactive azo dye in water matrix.
► We investigate both dark- and photo-assisted processes.
► We propose simplified degradation mechanism of studied pollutant.
► We develop mechanistic model predicting degradation of studied pollutant.
► Model encompasses all relevant reactions accurately predicting system behavior.
Journal: Chemical Engineering Journal - Volume 172, Issue 1, 1 August 2011, Pages 109–121