Model for predicting transmembrane pressure jump for various membrane bioreactors

Abstract

Membrane bioreactors (MBRs) are widely used to purify wastewater for reuse. One crucial problem is membrane fouling. To reduce membrane fouling, chemical cleaning must be performed because some foulants cannot be removed by physical cleaning and these foulants will prevent the recovery of membrane performance. Hence, to allow chemical cleaning at an appropriate time, membrane fouling must be predicted in the long term. When an MBR plant is operated under a condition of constant-rate filtration, this corresponds to prediction of the transmembrane pressure (TMP). Because one reason to make TMP difficult to predict is a TMP jump, we have been developing a model that predicts the time of a TMP jump. In this study, many data-sets measured in MBRs that differ in operating conditions, such as flux and reactor size, and water quality, such as viscosity and mixed liquor suspended solids concentration, were collected from the literature. Then, TMP jump prediction models having high prediction performance could be constructed for each type and each material of membrane. In addition, we discussed MBR parameters, such as reactor volume and aeration that would be important for TMP jump prediction and membrane fouling.