Combination of coagulation and adsorption technologies for advanced wastewater treatment for potable water reuse: By ANN, NSGA-II, and RSM

To reuse water and reduce water pollution, such as chemical oxygen demand (COD), total suspended solids (TSS), PO4, NTU, and NO3, advanced wastewater treatment technologies (a combination of coagulation (FeCl3) and adsorption (Activated Carbon (AC))) are attractive. Considering that water reclamatio...

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Veröffentlicht in:Journal of environmental management 2024-01, Vol.349, p.119429, Article 119429
Hauptverfasser: Zahmatkesh, Sasan, Karimian, Melika, Chen, Zhijie, Ni, Bing-Jie
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Karimian, Melika
Chen, Zhijie
Ni, Bing-Jie
description To reuse water and reduce water pollution, such as chemical oxygen demand (COD), total suspended solids (TSS), PO4, NTU, and NO3, advanced wastewater treatment technologies (a combination of coagulation (FeCl3) and adsorption (Activated Carbon (AC))) are attractive. Considering that water reclamation can help provide an irrigation system for crops and domestic purified water, removing organic matter and nutrients prior to wastewater reuse is fundamental. In order to remove contaminants like organic matter and nutrients from wastewater, advanced wastewater treatment processes are recommended. The purpose of this paper is to investigate various doses of AC and FeCl3 in wastewater treatment and study the optimum conditions for the removal of COD, TSS, PO4, NTU, and NO3. Furthermore, the evaluated FeCl3'/AC's optimum functioning pH ranges from 6.5 to 8.0, and their optimum working times range from 2.5 to 5.5 h. The optimum concentrations of AC were 0.1–25 g/L and 0.1–5 g/L of FeCl3. The most significant COD elimination rate (98%), the highest TSS elimination efficiency (94%), NTU elimination performance (99%), PO4 elimination (99%), and NO3 elimination (67%), among the investigated FeCl3 and AC. Secondly, the effects of operational variables such as AC, FeCl3, time, and solution pH were modeled, optimized, and evaluated using response surface techniques based on the D-Optimal design. Input from the response surface approach findings was used to develop an artificial neural network-based prediction model and Non-dominated Sorting Genetic Algorithm II (NSGA-II). [Display omitted] •COD, TSS, PO4, NTU, and NO3 were effective FeCl3 and PAC coagulants at optimal conditions.•Co-degradation outputs are compared to experimental results using ANNs and RSMs.•The RSM correlation coefficient was 0.973 and the ANN correlation coefficient was 0.997.•Activated carbon and FeCl3 are suitable technologies for the decline of organic matter in advanced water treatment.
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Considering that water reclamation can help provide an irrigation system for crops and domestic purified water, removing organic matter and nutrients prior to wastewater reuse is fundamental. In order to remove contaminants like organic matter and nutrients from wastewater, advanced wastewater treatment processes are recommended. The purpose of this paper is to investigate various doses of AC and FeCl3 in wastewater treatment and study the optimum conditions for the removal of COD, TSS, PO4, NTU, and NO3. Furthermore, the evaluated FeCl3'/AC's optimum functioning pH ranges from 6.5 to 8.0, and their optimum working times range from 2.5 to 5.5 h. The optimum concentrations of AC were 0.1–25 g/L and 0.1–5 g/L of FeCl3. The most significant COD elimination rate (98%), the highest TSS elimination efficiency (94%), NTU elimination performance (99%), PO4 elimination (99%), and NO3 elimination (67%), among the investigated FeCl3 and AC. Secondly, the effects of operational variables such as AC, FeCl3, time, and solution pH were modeled, optimized, and evaluated using response surface techniques based on the D-Optimal design. Input from the response surface approach findings was used to develop an artificial neural network-based prediction model and Non-dominated Sorting Genetic Algorithm II (NSGA-II). 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Secondly, the effects of operational variables such as AC, FeCl3, time, and solution pH were modeled, optimized, and evaluated using response surface techniques based on the D-Optimal design. Input from the response surface approach findings was used to develop an artificial neural network-based prediction model and Non-dominated Sorting Genetic Algorithm II (NSGA-II). 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subjects activated carbon
adsorption
Adsorption (activated carbon)
advanced wastewater treatment
Advanced wastewater treatment technologies
algorithms
Artificial neural network
chemical oxygen demand
coagulation
Coagulation (FeCl3)
drinking water
irrigation systems
neural networks
organic matter
Response surface methodology
wastewater
water pollution
water reuse
title Combination of coagulation and adsorption technologies for advanced wastewater treatment for potable water reuse: By ANN, NSGA-II, and RSM
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