Nadali Alavi1,2, Mahboobeh Dehvari3,4, Ghasem Alekhamis4, Gholamreza Goudarzi4,5, Abdolkazem Neisi4,5, Ali Akbar Babaei5. 1. 1Environmental and Occupational Hazards Control Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 2. 2Department of Environmental Health Engineering, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 3. 3Department of Environmental Health Engineering, Student Research Committee, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran. 4. 4Department of Environmental Health Engineering, School of Public Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran. 5. 5Environmental Technologies Research Center (ETRC), Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Abstract
BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSION: Results showed that EF process can be used efficiently for treatment of composting plant leachate using the proper operating conditions.
BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSION: Results showed that EF process can be used efficiently for treatment of composting plant leachate using the proper operating conditions.