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

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

This study aimed to assess, optimize and model the efficiencies of Fenton, photo-Fenton and ozonation/Fenton processes in formaldehyde elimination from water and wastewater using the response surface methodology (RSM) and artificial neural network (ANN). A sensitivity analysis was used to determine...

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Bibliographic Details
Main Authors: Ahmad Hosseinzadeh, Ali Asghar Najafpoor, Ali Asghar Navaei, John L. Zhou, Ali Altaee, Navid Ramezanian, Aliakbar Dehghan, Teng Bao, Mohsen Yazdani
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Water
Subjects:
formaldehyde removal
wastewater
photo-Fenton
ozonation
artificial neural network
Online Access:https://www.mdpi.com/2073-4441/13/19/2754

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