Degradation of distillery effluent by twisted-type Iron electrodes: experimental with ANN approach

Abstract

ABSTRACT The distillery spent wash consists of extremely high COD values, high content of pollutants and has an objectionable dark colour. These properties mark the effluent as one of the challenging tasks to treat ahead of exculpating into the surroundings. In this original research work, the raw distillery effluent was electrochemically treated using twisted-type Iron electrodes. Electrochemical treatment was performed for 2 hours and the treated effluent was sampled at defined periods to evaluate the efficiencies of spent wash degradation in terms of colour removal. Optimisation studies were conducted to evaluate the impact of various process parameters viz., applied electric current intensity, pH, mixing speed, electrolysis time and the inter-electrode space on the colour removal efficiencies. The maximum degradation of colour achieved by twisted-type Iron electrodes was found to be 83.75%. Operating conditions at which maximum colour removal efficiencies were achieved at current intensity 1.9 A, pH 3, 2 cm of inter-electrode distance, mixing speed of 100 rpm and for an electrolysis time of 2 h. The experimental results obtained were validated and evaluated using an Artificial Neural Network for modelling and predicting the electrocoagulation process for the degradation of distillery effluent employing twisted-type Iron electrodes.