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• W4385873277 abstract "The presence of copper in aqueous environments such as drinking water has led to several environmental effects, such as flavor and odor. The increase in Cu levels in ground and surface water has been mainly attributed to anthropogenic and natural sources. Consequently, this applied-analytical study aimed to investigate copper removal from urban drinking water through batch reactor electrocoagulation/flotation (ECF) with aluminum electrodes. The copper removal efficiency was evaluated under various operating conditions of current density (0.8-2.4 mA/cm2), initial concentration (1-100 mg/L), pH (3.5-10.5), and time (10-30 min). Cu was determined using the method outlined in the standard procedures (3500-Cu B at 4571 nm). The results indicated that increasing the current density from 0.8 to 2.4 mA/cm2 and the reaction time from 10 to 30 min improved Cu+2 removal efficiency (from 95 to 100%). In addition, the results demonstrated that Cu+2 reduction is 100% with an initial concentration of 100 mg/L, a pH of 7.5, a reaction time of 30 min, and an anode current density of 2.4 mA/cm2. The Taguchi method results for copper removal efficiency show that reaction time is the most significant variable. Furthermore, Cu removal kinetics models in an ECF reactor are second-order (R2 > 0.92). The Cu removal in the ECF reactor is due to redox and adsorption. Moreover, the operational costs of Cu treatment with Al electrode pairs are estimated to range from 8857 and 9636 Rial/kg of Cu removed. Thus, it can be concluded that the ECF process is very efficient in removing Cu from aqueous environments under optimum conditions." @default.
• W4385873277 created "2023-08-17" @default.
• W4385873277 creator A5055700735 @default.
• W4385873277 date "2023-08-16" @default.
• W4385873277 modified "2023-09-23" @default.
• W4385873277 title "Electrocoagulation/flotation process for removing copper from an aqueous environment" @default.
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• W4385873277 doi "https://doi.org/10.1038/s41598-023-40512-y" @default.
• W4385873277 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37587185" @default.
• W4385873277 hasPublicationYear "2023" @default.
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