Polyaromatic hydrocarbons biodegradation using mix culture of microorganisms from sewage waste sludge: application of artificial neural network modelling

Abstract

Purpose

In this study, we aimed to examine the tolerance of mixed culture of microorganisms isolated from sewage waste sludge to degrade high concentrations of polyaromatic hydrocarbons, naphthalene, and phenanthrene. The performance of the artificial neural network (ANN) model to predict and simulate the experimental biodegradation results was investigated.

Methods

The mixed culture of microorganisms was isolated from sewage waste sludge and adopted to biodegrade naphthalene and phenanthrene at different concentrations (100-1000mg/L). Sewage waste sludge obtained from wastewater treatment plants. A three-layer feed-forward network with a sigmoid transfer function (logsig) at the hidden layer, a linear transfer function (purelin) at the output layer, and a backpropagation training algorithm was used to set the ANN model.

Results

The results of this study show that naphthalene at concentrations of 100, 300, 700, and 1000 mg/L was depleted after incubation with the mixed culture for 6, 8, 14, and 16 days, respectively. For phenanthrene, depletion of 100, 300, 600, and 1000 mg/L was achieved after 8, 11, 16, and 19 days of incubation, respectively. A high correlation coefficient of 99.5% between the predicted and the experimental results were obtained by using the AAN model.

Conclusion

The results indicated that the mixed culture of microorganisms from sewage waste sludge could effectively consume naphthalene and phenanthrene as carbon and energy sources. Also, the ANN model could efficiently predict the experimental results for biodegradation treatment.