Hydrogen Peroxide dosage strategy for Paracetamol degradation in a Ferrioxalate assisted photo-Fenton process

BARBARA N. GIMÉNEZ; SOFÍA A. DUARTE; ORLANDO M. ALFANO; LEANDRO O. CONTE; AGUSTINA V. SCHENONE

Buenos Aires

Congreso; 11th World Congress of Chemical Engineering and II Iberoamerican Congress of Chemical Engineering - Global Symposium on Advanced Oxidation Processes; 2023

Asociación Argentina de Ingenieros Químicos

Photo-Fenton is one of the most efficient water treatments among the Advanced Oxidation Processes [1]. Complexing the iron with organic ligands allows working at a neutral pH and increases the photocatalytic activity of the system, expanding the fraction of usable solar radiation. These enhancements eliminate the costs associated with consumption of electricity from the lamps (if natural solar energy is used) and from the pH adjustment before and after the treatment. Then, the oxidizing agent can be considered the main source of costs. An alternative that would reduce its consumption is hydrogen peroxide (HP) dosage during the degradation process. The aim of this study was to examine the efficiency of hydrogen peroxide punctual dosing strategy for the abatement of paracetamol (PCT) at near neutral pH, using ferrioxalate as iron source. The experimental device was a lab-flat plate photoreactor irradiated with a solar simulator [2]. For all tests, pH was 5.5, initial PCT concentration was 40 ppm, Fe3+ concentration was 3 ppm and oxalate concentration was 47.5 ppm. An historical data experimental design (24 experiments in total) was applied to model the behavior of the system, where the conversion of PCT at 180 min of reaction (X_PCT^180 (%)) was the response under evaluation. The process parameters studied were: HP total concentration (A, [HP] = 94.5 to 756 ppm), HP dosage (B, DOS=YES or NO) and Radiation (C, RAD=ON or OFF). In order to statistically evaluate the degradation of PCT, the X_PCT^180 were fitted to a polynomial model. Multiple regression analysis was used to calculate the model coefficients and the analysis of variance (ANOVA) with 95% confidence level to validate them, resulting in the following expression:X_PCT^180 (%)=75.25-17.06*A+6.58*B+19.57*C+13.36*A*C-3.72*B*C-5.07*A^2Satisfactory values of R2, Adjusted-R2 and coefficient of variation (0.966, 0.951 and 9.22%, respectively) were obtained for the model and all the terms resulted significant (p