Membrane Bioreactor Air Scour Control Model to Address Fouling

Membrane Bioreactor (MBR) technology is essential for water reuse, which is especially important given increasing water scarcity. While MBRs provide affordable, high-quality treated water, fouling remains a major hurdle for stable operation. To mitigate fouling progression, operators utilize a rigorous set of actions; air scouring, back-pulsing (BP) and chemical cleanings. Notably, air scouring accounts for the largest proportion of operational costs, as its set-point often includes a large safety margin due to uncertainty regarding the required air scour flowrate. In previous study, we proposed and validated using data from two full-scale MBR plants a model (the K model) to estimate the necessary air scouring intensity under specific operational conditions. The model incorporates key variables, including permeate flux, mixed liquor suspended solid (MLSS) concentration, and membrane resistance, and enables the identification of thresholds where hydrodynamic conditions change abruptly, leading to the on-set of critical flux. The results demonstrated that system response can be effectively characterized using the proposed model, allowing optimization of the air scour flowrate (Jun et al., 2024). The model is consistent with the results of others indicating that higher resistance leads to increased local permeate flux, which in turn requires greater shear intensity.

Here we will present long-term operating data for an additional full-scale MBR plant that builds on the work of others to characterize fouling and its interaction with air scour control. Diez et al. (2013) suggested that resistance measured during back-pulsing (BP) cycles (hereafter referred to as intact resistance) characterizes irreversible membrane fouling. We use this to characterize pore blocking and external residuals not effectively removed during repeated permeation cycles, as suggested by Li and Wang (2006). Therefore, the intact resistance value in this study is determined by RT(Total resistance) — RBP(BP resistance) — Rm (Membrane resistance).

Increasing intact resistance results in increased local flux and accounts for the need to adjust air scouring appropriately. We introduce a pragmatic two-dimensional operational matrix, based on the K value, which represents the hydrodynamic balance between solids deposition during filtration and removal by air scouring, and intact resistance, which indicates the sensitivity of this balance. Under elevated intact resistance conditions, cake resistance tends to increase in response to external stimuli, such as high flux or high solid loading, even within the favorable hydrodynamic conditions.

The right side of Figure 1 presents the control matrix, including air scouring flowrate (characterized by K, x-axis), intact resistance (y-axis, while the left side presents supporting data from the full-scale MBR.) Plant data (left side of Figure 1) reveals resistance slope changes defined by two fine-tuned thresholds: KLim (limiting condition) and KS.F (incorporating safety factor). The numbers within each grid define sections (bottom left panel): section 9 indicates the optimal zone, sections 6 and 8 are attention zones, and the remaining sections are classified as limiting zones. The goal is to maintain operations within the optimal zone (i.e., minimizing cake development by controlling intact resistance), with two set-points ensuring stability during deviations. Cake resistance is modest above KS.F but begins to increase below it and more rapidly near KLim. Intact resistance has two thresholds: the Target Limit and the Warning Limit. Above the Target Limit, the rate of cake resistance increase become more sensitive to operational condition yet manageable but becomes increasingly difficult above the Warning Limit. Table 1 outlines the appropriate actions to reduce unnecessary excess of resources that has marginal benefits.

Detail case study and examples of use of these control measures based on data from the full-scale MBR will be presented. This approach facilitates optimal decision-making, including air scouring adjustments to reduce energy consumption, and measures to prolong operation before a recovery clean is necessary.