Post-treatment of coking industry wastewater by the electro-Fenton process.

Effluents of the coking industry cannot be effectively treated in biological treatment units because of non-biodegradable organic matters and phenolic compounds present in the wastewater. In this study, post-treatment of biologically treated coking wastewater via the electro-Fenton process was investigated to minimize the effects of discharge of this kind of wastewater on the environment. The electro-Fenton experiments were performed using cast iron electrodes. Chemical oxygen demand (COD) and phenol were selected as the target parameters. The optimum operating conditions were as follows: reaction time = 10 minutes, pH = 3.0, electrical current = 1.0 A, and [H2O2] = 2000 mg/L. Under these conditions, COD and phenol removal efficiencies were 67.8% and 98.0%, respectively. In addition, it was determined that COD removal followed first-order reaction kinetics. Consequently, the electro-Fenton process was determined as an effective alternative post-treatment method for coking industry effluents.

Artificial neural network modelling of a large-scale wastewater treatment plant operation.

Artificial Neural Networks (ANNs), a method of artificial intelligence method, provide effective predictive models for complex processes. Three independent ANN models trained with back-propagation algorithm were developed to predict effluent chemical oxygen demand (COD), suspended solids (SS) and aeration tank mixed liquor suspended solids (MLSS) concentrations of the Ankara central wastewater treatment plant. The appropriate architecture of ANN models was determined through several steps of training and testing of the models. ANN models yielded satisfactory predictions. Results of the root mean square error, mean absolute error and mean absolute percentage error were 3.23, 2.41 mg/L and 5.03% for COD; 1.59, 1.21 mg/L and 17.10% for SS; 52.51, 44.91 mg/L and 3.77% for MLSS, respectively, indicating that the developed model could be efficiently used. The results overall also confirm that ANN modelling approach may have a great implementation potential for simulation, precise performance prediction and process control of wastewater treatment plants.