A prototype of textile wastewater treatment using coagulation and adsorption by Fe/Cu nanoparticles: Techno-economic and scaling-up studies. (6th September 2021)

• Record Type: Journal Article
• Authors: Mahmoud, Ahmed S; Mostafa, Mohamed K; Peters, Robert W
• Is Part Of: Nanomaterials and nanotechnology. Volume:11(2021)
• Publication Date: 2021-09-06
• Subjects: real textile wastewater -- coagulation -- filtration -- degradation -- adsorption -- nano-bimetallic Fe/Cu -- economical evaluation -- scale up and continuous feed; Nanostructured materials -- Periodicals; Nanotechnology -- Periodicals; Nanostructured materials; Nanotechnology; Periodicals; 620.5
• DOI: 10.1177/18479804211041181
• Languages: English
• ISSNs: 1847-9804

Abstract

This study aims to investigate the efficiency of a pilot prototype system comprising coagulation/flocculation, filtration, and nano-bimetallic iron/copper (Fe/Cu) degradation and adsorption units for the removal of chemical oxygen demand (COD), biological oxygen demand (BOD), color, total nitrogen (TN), total phosphorus (TP), and TSS from real textile wastewater. The total removal efficiencies of the system were 96, 98, 82, 69, 88, and 97%, respectively, using 0.5 g/L ferric chlorides as a coagulant under an optimum adsorption condition of pH 6.0, nano-dosage 1.4 g/L, contact time 80 min, and stirring rate 250 r/min at room temperature. Adsorption isotherms indicated that the removal of COD and TP obeys both Koble–Corrigan and Freundlich adsorption models, removal of color obeys both Koble–Corrigan and Hill adsorption models, and removal of TN and TSS obeys Koble–Corrigan and Khan models, respectively. Avrami kinetic models adequately describe the adsorption data for COD, BOD, TN, and TSS, while pseudo-second-order and intraparticle models described the removal mechanism of color and TSS, respectively. An artificial neural network (ANN) with r 2 -value exceeding 0.98 is accurate and can be used with confidence in predicting removal efficiencies of the targeted parameters. Sensitivity analysis results showed that the initial concentration was the most influential parameter for TSS removal with relative importance greater than 25%, while the bimetallic Fe/Cu dosage was the most influential factor for all other studied parameters with relative importance greater than 40%. The total treatment cost of the proposed system per m 3 after scaling up was found to be US$4.5 for reuse of the treated water for the irrigation of forest trees.