Modelling the population dynamics and metabolic diversity of organisms relevant in anaerobic/anoxic/aerobic enhanced biological phosphorus removal processes

Abstract

In this study, enhanced biological phosphorus removal (EBPR) metabolic models are expanded in order to incorporate the competition between polyphosphate accumulating organisms (PAOs) and glycogen accumulating organisms (GAOs) under sequential anaerobic/anoxic/aerobic conditions, which are representative of most full-scale EBPR plants. Since PAOs and GAOs display different denitrification tendencies, which is dependent on the phylogenetic identity of the organism, the model was separated into six distinct biomass groups, constituting Accumulibacter Types I and II, as well as denitrifying and non-denitrifying Competibacter and Defluviicoccus GAOs. Denitrification was modelled as a multi-step process, with nitrate (NO(3)), nitrite (NO(2)), nitrous oxide (N(2)O) and di-nitrogen gas (N(2)) being the primary components. The model was calibrated and validated using literature data from enriched cultures of PAOs and GAOs, obtaining a good description of the observed biochemical transformations. A strong correlation was observed between Accumulibacter Types I and II, and nitrate-reducing and non-nitrate-reducing PAOs, respectively, where the abundance of each PAO subgroup was well predicted by the model during an acclimatization period from anaerobic-aerobic to anaerobic-anoxic conditions. Interestingly, a strong interdependency was observed between the anaerobic, anoxic and aerobic kinetic parameters of PAOs and GAOs. This could be exploited when metabolic models are calibrated, since all of these parameters should be changed by an identical factor from their default value. Factors that influence these kinetic parameters include the fraction of active biomass, relative aerobic/anoxic fraction and the ratio of acetyl-CoA to propionyl-CoA. Employing a metabolic approach was found to be advantageous in describing the performance and population dynamics in such complex microbial ecosystems.