Azithromycin (AZM), an antibacterial considered one of the most consumed drugs, especially during the period against the Covid 19 pandemic, and it is one of the persistent contaminants that can be released into aquatic ecosystems. The purpose of this study is to determine the efficacy of a Fenton-like process (chlorine/iron) for the degradation of AZM in an aqueous medium by determining the impact of several factors (the initial concentration of (FeSO, NaClO, pollutant), and the initial pH) on the degradation rate. The Response Surface Methodology (RSM) based on the Box-Wilson design as well as the Artificial Neural Network (ANN) modeling combined with a genetic algorithm (GA) approaches were used to determine the optimal levels of the selected variables and the optimal rate of degradation.
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