article · Desalination and Water Treatment
Electrocoagulation was tested for treating tannery wastewater using both aluminium and iron electrodes in plane and punched configurations. The optimum treatment conditions were established at a pH of 9, an operating voltage of 20 V, an electrode distance of 1 cm, and an electrolysis time of 90 minutes. Treatment performance was measured through the reduction of biochemical oxygen demand, chemical oxygen demand, chromium, and total dissolved solids. Across both metals, punched electrodes delivered higher contaminant removal rates than plane electrodes, with punched aluminium achieving the highest reductions. In addition, experimental design predictions were validated with 95 percent confidence using an artificial neural network model combined with linear regression, accurately predicting final pollutant levels in the treated effluent.
Tannery wastewater carries hazardous industrial pollutants, including toxic chromium and heavy organic loads. Identifying more effective electrode shapes, such as punched designs, improves purification efficiency. Pairing this physical process with reliable neural network predictive modelling allows plant operators to better forecast water quality outcomes, helping to mitigate environmental contamination and lower industrial processing costs.
This research is applied and tested at an experimental stage, directly targeting industrial wastewater treatment for tanneries and environmental management facilities. The findings could guide the design of more efficient industrial electrocoagulation reactors by adopting punched electrode configurations. Furthermore, the verified artificial neural network model could be incorporated into software monitoring tools for process control. Further pilot testing at full industrial scale would be needed before commercial deployment.
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This study investigated the electrocoagulation (EC) treatment of tannery wastewater using plane and punched aluminum and iron electrodes at the optimum condition of pH 9, voltage 20 V, electrode distance of 1 cm and 90 min electrolysis duration. The efficiency of the EC process was determined by evaluating the levels of biochemical oxygen demand (BOD), chemical oxygen demand (COD), and Chromium (Cr) in the treated effluents. The experiment utilized both linear regression and Artificial Neural Network (ANN) models for modeling, with the ANN model validating the predicted model from the experimental design with 95 % confidence. The use of plane aluminum electrodes resulted in an optimum removal efficiency of BOD (89.66 %), COD (96.21 %), Cr (96.05 %), and TDS (95.77 %). On the other hand, the punched electrodes achieved a removal efficiency of 90.86 % (BOD), 98.62 % (COD), 96.94 % (Cr), and 96.92 % (TDS). Similarly, when using plane iron electrodes, the removal efficiency of BOD, COD, Cr and TDS was 87.57 %, 94.77 % 93.42 % and 93.08 %, respectively, while punched iron electrodes removed 89.01 % of BOD, 96.59 % of COD, 94.66 % of Cr and 95 % of TDS. The results demonstrate that the proposed ANN effectively predicts effluent BOD, COD, Cr and TDS, addressing economic and environmental sustainability concerns.
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DOI: 10.1016/j.dwt.2024.100530
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