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Online monitoring of the nanoscale zero-valent iron process for trichloroethylene wastewater treatment
Yu, R.-F.; Chi, F.-H.; Cheng, W.-P. & Wang, M.-H.
Abstract
In this study, a batch-type, nanoscale, zerovalent
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.
Keywords
Artificial neural network; Monitoring and control; Nanoscale zero-valent iron; Oxidation–reduction potential; pH; Trichloroethylene
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