Comparison of a deterministic and a data driven model to describe MBR fouling

Membrane bioreactors (MBRs) are a combination of activated sludge bioreactors and membrane filtration, enabling high quality effluent with a small footprint. However, they can be beset by fouling, which causes an increase in transmembrane pressure (TMP). Modelling and simulation of changes in TMP could be useful to describe fouling through the identification of the most relevant operating conditions. Using experimental data from a MBR pilot plant operated for 462days, two different models were developed: a deterministic model using activated sludge model n°2d (ASM2d) for the biological component and a resistance in-series model for the filtration component as well as a data-driven model based on multivariable regressions. Once validated, these models were used to describe membrane fouling (as changes in TMP over time) under different operating conditions. The deterministic model performed better at higher temperatures (>20°C), constant operating conditions (DO set-point, membrane air-flow, pH and ORP), and high mixed liquor suspended solids (>6.9gL-1) and flux changes. At low pH (<7) or periods with higher pH changes, the data-driven model was more accurate. Changes in the DO set-point of the aerobic reactor that affected the TMP were also better described by the data-driven model. By combining the use of both models, a better description of fouling can be achieved under different operating conditions

Towards integrated operation of membrane bioreactors : effects of aeration on biological and filtration performance

Two experimental studies evaluated the effect of aerobic and membrane aeration changes on sludge properties, biological nutrient removal and filtration processes in a pilot plant membrane bioreactor. The optimal operating conditions were found at an aerobic dissolved oxygen set-point (DO) of 0.5mgO2L-1 and a membrane specific aeration demand (SADm) of 1mh-1, where membrane aeration can be used for nitrification. Under these conditions, a total flow reduction of 42% was achieved (75% energy reduction) without compromising nutrient removal efficiencies, maintaining sludge characteristics and controlled filtration. Below these optimal operating conditions, the nutrient removal efficiency was reduced, increasing 20% for soluble microbial products, 14% for capillarity suction time and reducing a 15% for filterability. Below this DO set-point, fouling increased with a transmembrane pressure 75% higher. SADm below 1mh-1 doubled the values of transmembrane pressure, without recovery after achieving the initial conditions