Alavi Nadali, Dehvari Mahboobeh, Alekhamis Ghasem, Goudarzi Gholamreza, Neisi Abdolkazem, Babaei Ali Akbar
1Environmental and Occupational Hazards Control Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
2Department of Environmental Health Engineering, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
J Environ Health Sci Eng. 2019 May 8;17(1):417-431. doi: 10.1007/s40201-019-00361-2. eCollection 2019 Jun.
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), HO concentrations (theoretical ratio HO/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: V) 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 HO/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 (R > 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.
堆肥厂渗滤液被认为是污染严重的废水之一，需要采用简单、经济、快速且环保的方法进行处理。本研究对采用电芬顿（EF）工艺处理新鲜堆肥厂渗滤液进行了调查。
研究了各种输入变量的影响，如pH值（2 - 7）、直流电流（1.5 - 3 A）、过氧化氢浓度（理论过氧化氢/化学需氧量比例：0.1 - 0.6）、总溶解固体变化（4 - 6%）、进料方式以及在最佳点的生化需氧量/化学需氧量比例。还测定了处理产生的剩余污泥的沉降特性（30分钟沉降后的污泥体积：V）。采用人工神经网络（ANN）方法对实验数据进行建模。
结果表明，在pH值为3、直流电流恒定值为3 A、理论过氧化氢/化学需氧量比例为0.6以及四步注入进料方式下，化学需氧量的去除率最佳。最佳点的生化需氧量/化学需氧量比例为0.535，在总溶解固体 = 4%时实现了最大化学需氧量去除。在最佳条件下，85%的化学需氧量被去除，生化需氧量/化学需氧量比例从0.270提高到0.535。数据符合二级动力学（R > 0.9），神经网络建模也为测试数据提供了准确预测。
结果表明，采用适当的操作条件，电芬顿工艺可有效用于处理堆肥厂渗滤液。
