Phosphate removal from aqueous solutions using reversal mode electrocoagulation with iron and aluminum electrodes: RSM optimization and ANN modeling

Abstract Phosphate pollution significantly contributes to eutrophication and the degradation of aquatic ecosystems. The removal of phosphate from wastewater before discharging into the environment is essential for the sustainability of the ecosystem. This work focuses on using a polarity reversal mode electrocoagulation (PRM-EC) system integrated with iron (Fe) and aluminum (Al) electrodes to remove phosphate from wastewater. The conditions for the removal process were optimized using response surface methodology (RSM). Central composite design (CCD) was used to design the experiment and numerical optimization was utilized to find the optimal conditions. The phosphate removal efficiency could reach 93.12% at a current density of 40 A m −2 , time of 30 min, pH of 6.4, and electrode distance of 10.5 mm. The energy consumption was about 0.4 kW m −3 . The artificial neural network (ANN) modeling showed that the current density was the most influencing factor, followed by time, pH, and electrode distance. The mechanism underlying the PRM-EC process encompassed electrode dissolution, floc formation, phosphate adsorption, and precipitation. The findings in the work show that PRM-EC is an environmentally friendly and effective solution for phosphate removal.

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Publication Details

Journal
Environmental Research Communications
Published
2024-09-23
DOI
https://doi.org/10.1088/2515-7620/ad7e84
Citations
9
Primary Topic
Phosphorus and nutrient management
Type
article
Field-Weighted Citation Impact
2.64
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article

Phosphate removal from aqueous solutions using reversal mode electrocoagulation with iron and aluminum electrodes: RSM optimization and ANN modeling

Mai Nguyen, Trong Nghia-Nguyen, Balasubramani Ravindran, Nguyễn Thị Minh Nguyệt et al.
9 citations
Environmental Research Communications
Phosphorus and nutrient management
2.64
article

Phosphate removal from aqueous solutions using reversal mode electrocoagulation with iron and aluminum electrodes: RSM optimization and ANN modeling

Mai Nguyen, Trong Nghia-Nguyen, Balasubramani Ravindran, Nguyễn Thị Minh Nguyệt, Vinh Dinh Nguyen
article en
9 citations

Abstract

Abstract Phosphate pollution significantly contributes to eutrophication and the degradation of aquatic ecosystems. The removal of phosphate from wastewater before discharging into the environment is essential for the sustainability of the ecosystem. This work focuses on using a polarity reversal mode electrocoagulation (PRM-EC) system integrated with iron (Fe) and aluminum (Al) electrodes to remove phosphate from wastewater. The conditions for the removal process were optimized using response surface methodology (RSM). Central composite design (CCD) was used to design the experiment and numerical optimization was utilized to find the optimal conditions. The phosphate removal efficiency could reach 93.12% at a current density of 40 A m −2 , time of 30 min, pH of 6.4, and electrode distance of 10.5 mm. The energy consumption was about 0.4 kW m −3 . The artificial neural network (ANN) modeling showed that the current density was the most influencing factor, followed by time, pH, and electrode distance. The mechanism underlying the PRM-EC process encompassed electrode dissolution, floc formation, phosphate adsorption, and precipitation. The findings in the work show that PRM-EC is an environmentally friendly and effective solution for phosphate removal.

Environmental Research CommunicationsVol. 6(10)
Hung Yen University of Technology and Education (VN), Chettinad Academy of Research and Education (IN), Kyonggi University (KR), Thai Nguyen University (VN)
Openalex Percentile: Top 11%
Phosphorus and nutrient management
2.64
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Phosphate removal from aqueous solutions using reversal mode electrocoagulation with iron and aluminum electrodes: RSM optimization and ANN modeling — Mai Nguyen, Trong Nghia-Nguyen, et al. · Environmental Research Communications (2024) | TGRS Research Map | TGRS