Prediction of COD and NH4+-N Concentrations in Leachate from Lab-scale Landfill Bioreactors Using Artificial Neural Networks

Document Type : Research Paper


1 M.Sc. of Environmental Eng., Faculty Member of Environmental Research Institute of Jahad Daneshgahi, Rasht

2 M.Sc. of Artificial Intelligence, Dept. of Computer Engineering, Shiraz University

3 Assoc. Prof., Dept. of Hydraulic and Environmental Eng., School of Civil Eng., Iran Uni. of Science and Tech., Tehran


In this study, we present an Artificial Neural Network (ANN) model for predicting COD and NH4+-N concentrations in landfill leachate from lab-scale landfill bioreactors. For this purpose, two different lab-scale systems were modeled. for neural network’s data obtained. In the first system, the leachate from a fresh-waste reactor was drained to a recirculation tank and recycled every two days. In the second, the leachate from a fresh waste landfill reactor was fed through a well-decomposed refuse landfill reactor, while the leachate from a well-decomposed refuse landfill reactor was simultaneously recycled to a fresh waste landfill reactor. The results indicate that leachate NH4+-N and COD concentrations accumulated to a high level in the first system, while. NH4+-N and COD removals were successfully carried out in the second. Also, average removal efficiencies in the second system reached 85% and 34% for COD and NH4+-N, respectively. Finally, the ANN’s results exhibited the success of the model as witnessed by the excellent agreement obtained between measured and predicted values.


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