Improving Formaldehyde Removal from Water and Wastewater by Fenton, Photo-Fenton and Ozonation/Fenton Processes through Optimization and Modeling

نویسندگان

چکیده

This study aimed to assess, optimize and model the efficiencies of Fenton, photo-Fenton ozonation/Fenton processes in formaldehyde elimination from water wastewater using response surface methodology (RSM) artificial neural network (ANN). A sensitivity analysis was used determine importance independent variables. The influences different variables, including H2O2 concentration, initial Fe dosage, pH, contact time, UV ozonation, on removal efficiency were studied. optimized Fenton process demonstrated 75% water. best performance with 80% achieved combined process. developed ANN better adequacy goodness fit a R2 0.9454 than RSM 0. 9186. showed pH as most important factor (31%) affecting process, followed by concentration (23%), dosage (21%), time (14%) (12%). findings that these treatment models are tools for wastewater.

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ژورنال

عنوان ژورنال: Water

سال: 2021

ISSN: ['2073-4441']

DOI: https://doi.org/10.3390/w13192754