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• W3157006346 abstract "This study will investigate the removal of nitrate from groundwater by aluminum–aluminum (Al–Al) electrocoagulation (EC) using response surface methodology. Box–Behnken design (BBD) will be used to investigate the mutual interaction effect of important process parameters, such as current density (A), electrolysis time (C), and spacing (B) on nitrate removal efficiency (NRE %) from four groundwater samples with different initial nitrate concentrations. Experiments will be performed according to the BBD matrix and the data obtained fitted well to a quadratic model that demonstrated a good association between the predicted and experimental values with >R2 = 0.97 for all samples. In ANOVA studies, a p-value of <0.00001 was obtained, which confirmed the suitability of the regression models (p-value <0.05). In addition, a small value for the coefficient of variation (3.95%, 1.65%, 2.90%, and 3.84%) for all the samples indicated a higher degree of accuracy and the reliability of the experiments. ANOVA results and three-dimensional (3D) plots suggested that A and C were the main process parameters in this study and B had a negative effect on NRE %. Maximum NREs (%) of 92.5 (106 mg/L), 91.5 (133 mg/L), 83.5 (148 mg/L), and 71 (231 mg/L) were obtained at C = 1.6–2.78 h, A = 0.065 A/cm2, and B = 1 cm. In addition, for the feasibility of EC at an industrial scale, the management of the generated sludge was explained by its characterization using scanning electron transmission microscopy (SEM). This study concluded that the EC approach might be a promising technique for application to nitrate removal from groundwater." @default.
• W3157006346 created "2021-04-26" @default.
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• W3157006346 date "2021-07-01" @default.
• W3157006346 modified "2023-10-18" @default.
• W3157006346 title "Nitrate Removal from Groundwater by Electrocoagulation: Process Optimization through Response Surface Method" @default.
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• W3157006346 doi "https://doi.org/10.1061/(asce)hz.2153-5515.0000617" @default.
• W3157006346 hasPublicationYear "2021" @default.
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