Elucidating the performance of integrated anoxic/oxic moving bed biofilm reactor: Assessment of organics and nutrients removal and optimization using feed forward back propagation neural network.

A lab-scale integrated anoxic and oxic (A/O) moving bed biofilm reactor (MBBR) was investigated for the removal of organics and nutrients by varying chemical oxygen demand (COD) to NH-N ratio (C/N ratio: 3.5, 6.75, and 10), hydraulic retention time (HRT: 6 h, 15 h, and 24 h), and recirculation ratio (R: 1, 2, and 3). The use of activated carbon coated carriers prepared from waste polyethylene material and polyurethane sponges attached to a cylindrical frame in the integrated A/O MBBR increased the attached growth biomass significantly. >95 % of COD removal was observed under the C/N ratio of 10 at an HRT of 24 h. While the low C/N ratio favored the removal of NH-N (∼98 %) and PO-P (∼90 %) with an optimal R of 1.75. Using the experimental dataset, to predict and forecast the performance of integrated A/O MBBR, a feed-forward-backpropagation-neural-network model was developed.