Predicting Anaerobic Membrane Bioreactor Performance Using Flow-Cytometry-Derived High and Low Nucleic Acid Content Cells.

Having a tool to monitor the microbial abundances rapidly and to utilize the data to predict the reactor performance would facilitate the operation of an anaerobic membrane bioreactor (AnMBR). This study aims to achieve the aforementioned scenario by developing a linear regression model that incorporates a time-lagging mode. The model uses low nucleic acid (LNA) cell numbers and the ratio of high nucleic acid (HNA) to LNA cells as an input data set.

Understanding the role of sorption and biodegradation in the removal of organic micropollutants by membrane aerated biofilm reactor (MABR) with different biofilm thickness.

The role of sorption and biodegradation in a membrane aerated biofilm reactor (MABR) were investigated for the removal of 10 organic micropollutants (OMPs) including endocrine disruptors and pharmaceutical active compounds. The influence of the biofilm thickness on the mechanisms of removal was analyzed via kinetic test at three different stages. At all biofilm stages, biodegradation was demonstrated to dominate the removal of selected OMPs.

Biomass generation and heterologous isoprenoid milking from engineered microalgae grown in anaerobic membrane bioreactor effluent.

Wastewater (WW) treatment in anaerobic membrane bioreactors (AnMBR) is considered more sustainable than in aerobic reactors. However, outputs from AnMBR are a mixed methane and carbon dioxide gas stream as well as ammonium- (N) and phosphate- (P) containing waters. Using AnMBR outputs as inputs for photoautotrophic algal cultivation can strip the CO while removing N and P from effluent which feed algal biomass generation.