Abstract

Composting plant leachate is considered as one of the highly polluted wastewaters which is necessary to be treated by simple, economic, fast and environmentally compatible methods. In this study, treatment of fresh composting plant leachate by electro-Fenton (EF) process was investigated. The effect of various input variables like pH (2-7), DC currents (1.5-3 A), H2O2 concentrations (theoretical ratio H2O2/COD: 0.1-0.6), TDS changes (4-6%), feeding mode, and BOD/COD ratio at the optimal point were studied. The settling characteristics of the waste sludge produced by the treatment (sludge volumes after 30-min sedimentation: V30) were also determined. Artificial neural network (ANN) approach was used for modeling the experimental data. Based on the results, the best removal rate of COD was obtained at pH: 3, 3 A constant DC current value, 0.6 theoretical ratio H2O2/COD and the feeding mode at four step injection. BOD/COD ratio at the optimal point was 0.535 and the maximum COD removal was achieved at TDS = 4%. In the optimal conditions, 85% of COD was removed and BOD/COD ratio was increased from 0.270 to 0.535. The data follow the second-order kinetic (R2 > 0.9) and neural network modeling also provided the accurate prediction for testing data. Results showed that EF process can be used efficiently for treatment of composting plant leachate using the proper operating conditions.

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