title: Degradation of aqueous methylene blue using an external loop airlift sonophotoreactor: Statistical analysis and optimization.
abstract: Degradation and mineralization of aqueous methylene blue (MB) are investigated in a bench scale external loop airlift sonophotoreactor. A central composite design along with response surface methodology is employed to model and optimize the sonophotolytic process. A quadratic empirical expression between responses and independent variables (pH and initial concentrations of H2O2 and MB) is derived. The efficiencies of the system for the MB degradation after 10, 15, and 30 min, and total organic carbon reduction after 150 min are considered as responses. The analysis of variance performed high values for the coefficient of determination R(2) and adjusted R(2) for all four responses. Optimum values of process variables for the maximum degradation and mineralization efficiency are pH 6.6 and initial concentrations of H2O2 and MB are 1,280 and 10.56 mg/L, respectively. With optimal operating conditions, 99.93% and 55.32% MB removal (after 10 min) and TOC reduction (after 150 min) are achieved, respectively. Artificial neural networks are also used to model the experimental data. The respirometric study is conducted to compare the biodegradability of untreated and sonophotolytically pre-treated MB solutions at different reaction times. Pre-treated solutions at 180, 240, and 300 min performed higher biodegradability compared to those of untreated MB solutions.
authors.affiliation: a Department of Chemical Engineering , Ryerson University , Toronto , Ontario , Canada.
authors.forename: Masroor
authors.initials: M
authors.lastname: Mohajerani
authors.affiliation: a Department of Chemical Engineering , Ryerson University , Toronto , Ontario , Canada.
authors.forename: Mehrab
authors.initials: M
authors.lastname: Mehrvar
authors.affiliation: a Department of Chemical Engineering , Ryerson University , Toronto , Ontario , Canada.
authors.forename: Farhad
authors.initials: F
authors.lastname: Ein-Mozaffari
mesh_terms: D002244:Carbon / Q000737:chemistry; D006861:Hydrogen Peroxide / Q000737:chemistry; D006863:Hydrogen-Ion Concentration; D008751:Methylene Blue / Q000737:chemistry*; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D058433:Photobioreactors; D010777:Photochemistry; D014465:Ultrasonics; D014466:Ultraviolet Rays
chemical_list: D002244:Carbon; D006861:Hydrogen Peroxide; D008751:Methylene Blue
keywords: Advanced oxidation process; artificial neural networks; response surface methodology; sonophotoreactor