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Study and Optimization of Operating Parameters of Nanophotocatalytic Wastewater Treatment Process

Qanbarzadeh, Mojtaba | 2016

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 48755 (06)
  4. University: Sharif University of Technology
  5. Department: Chemical and Petroleum Engineering
  6. Advisor(s): Soltanieh, Mohammad; Vossoughi, Manouchehr; Feilizadeh, Mehrzad
  7. Abstract:
  8. In this study, we investigate the effect of adding potassium persulfate (PDS) (K2S2O8) and hydrogen peroxide (H2O2) to E.coli (as a model microorganism) photocatalytic removal system in the presence of the TiO2-P25 as photocatalyst and UV irradiation. In this regard, the PDS and H2O2 oxidants were added separately in the different levels of pH and photocatalyst loading under UV irradiation. The experimental points were determined based on the central composite design (CCD) and in order to study the main and the interactive effects of the photocatalyst concentration (mg/L), oxidant concentration (mg/L) and the pH on the final concentration of E.coli (cfu/mL), a response surface model (RSM) and an artificial neural network model coupled with genetic algorithm (ANN/GA) were developed based on the experimental design points and the operating parameters were optimized by the two models. The results of the both models show that by adding PDS to the system, the optimize range of parameters were obtained; 200-250 mg/L, 420-470 mg/L and 5-5.5 for photocatalyst concentration, PDS concentration and pH respectively and in the optimize conditions the disinfection system can inactivate nearly 99.99% of bacteria in 1 hour. Also by adding H2O2 to the system, the optimize range of parameters were determined; 280-340 mg/L, 75-100 mg/L and 5.6-6 for photocatalyst concentration, PDS concentration and pH respectively and in the optimize conditions the disinfection system can inactivate nearly 99.99% of bacteria in 1 hour. Statistical parameters such as coefficient of determination and mean square error shows that ANN model (with R2=0.99 for both systems) has much better ability to explain and predict the system variations in related to the RSM model (with R2= 0.97 for both systems). In addition, results show that adding oxidants have a positive effect on the inactivation efficiency and H2O2 is more efficient than PDS. Adding H2O2 to the TiO2-P25 in order to inactivate E.coli under solar radiation shows that 99.9% disinfection in 45 minutes is accessible
  9. Keywords:
  10. Disinfection ; Photocatalyst ; Hydrogen Peroxide ; Response Surface Methodology ; Artificial Neural Network ; Waste Treatment ; Potassium Persulfate

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