Abstract
In this study, a batch-type, nanoscale, zero-valent iron process was used to treat trichloroethylene wastewater. Variations in oxidation–reduction potential (ORP) and pH in the reactor were monitored online for use in developing the model for process control. After the addition of nanoscale, zero-valent iron, the pH value increased rapidly, from 5.0–6.0 to around 8.5–9.5, whereas the ORP decreased dramatically, from around 300 mV to −700 to −800 mV. The degradation of trichloroethylene reached equilibrium at a reaction time of about 120 min. The use of a dose of 1.5 g/L to treat an influent that had a trichloroethylene concentration of 50 mg/L resulted in a removal efficiency of 94 %. Two models, i.e., a multiple regression model and an artificial neural network (ANN) model, were used to develop the control model to predict the trichloroethylene removal efficiencies. Both the regression model and the ANN model performed precise prediction results for the trichloroethylene removal efficiencies, with correlation coefficients of about 0.87 and 0.98, respectively, resulting in great potential for controlling the trichloroethylene removal.
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