Abstract

Micropollutants are a major concern for aquatic organisms and human health. Membrane bioreactors (MBRs) are an efficient wastewater treatment and water reuse solution, but their micropollutant removal performances are still not fully determined. Modeling micropollutant behavior in MBRs could help better understand and optimize the removal process. Here we provide detailed explanation on a model of micropollutant removal in MBRs that predicts biodegradation and sorption rates. Parameters were calibrated following an iterative two-step procedure developed in this work and using data from two full-scale plants. The calibrated set of parameters was then used (i) to determine the influence of MBR operating conditions such as the duration of aerobic time and the sludge concentration in bioreactor, on micropollutant removal, and (ii) to better understand micropollutant behavior and removal performances in MBRs in response to sudden changes in operating conditions (rain event, F:M ratio). These predictive simulations showed that increasing sludge concentration in bioreactor can decrease effluent concentrations of most of the micropollutants studied by up to 15%, and increasing the duration of aerobic time decreases effluent concentrations of few organic micropollutants tested by up to 15%. Rain events and F:M ratio can increase effluent concentrations of six out of nine micropollutants tested by more than 15%.

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