The PAO/GAO competition on biological phosphorus removal process

Enhanced Biological Phosphorus Removal (EBPR) has become a widely applied wastewater treatment process. Simple configuration (an anaerobic and an anoxic/aerobic tank in series), lower operation costs and lower sludge production compared to chemical phosphorus removal are some of the factors that have favorably influenced its popularity. EBPR relies on the enrichment of the activated sludge with Polyphosphate Accumulating Organisms (PAO). Directing the influent to the anaerobic tank and recycling the biomass between the anaerobic and anoxic/aerobic zones promote the development of PAO in the system.

Despite that the process configuration creates a favorable environment for the substrate uptake of PAO and, thus, their enrichment, studies carried out at either lab- or full-scale EBPR wastewater treatment plants (wwtp) have reported the presence of Glycogen Accumulating Organisms (GAO). In certain cases, proliferation of GAO was linked with the deterioration of EBPR systems and, in extreme events, with the failure of the process. GAO have a similar metabolism as PAO, they also store under anaerobic conditions readily biodegradable organic matter (such as volatile fatty acids) as poly--hydroxyalkanoates (PHA). However, GAO’s metabolism does not involve anaerobic P-release and subsequent aerobic (and anoxic) P-uptake as PAO’s. Since GAO do not store poly-phosphate (poly-P) the glycolysis of intracellular stored glycogen provides the required energy for the transport and storage of carbon sources as well as for covering the maintenance energy requirements.

The aim of this research is to get a better understanding about the interaction between PAO and GAO at lab- and full-scale wastewater treatment systems in order to comprehend the EBPR stability, under different operating and environmental conditions, where mathematical modeling will play a major role to explore key aspects for their competition. This may lead to the proposal of measures towards the EBPR optimization.