Distributed state simulation of endogenous processes in biological wastewater treatment.
Distributed state-type simulations (based on modeling of individual bacteria as they move through a reactor system) predicted a greater sensitivity of enhanced biological phosphorus removal (EBPR) performance to endogenous degradation than did conventional, "lumped"-type simulations (based on average biomass compositions). Recent research has indicated that the variable hydraulic residence times experienced by individual microbial storage product accumulating bacteria in systems with completely mixed reactors tend to produce populations with diverse microbial storage product contents (distributed states). Endogenous degradation in EBPR systems is of particular interest because the polyphosphate accumulating organisms (PAOs) responsible for EBPR rely on the accumulation of three different storage products that may be endogenously degraded. Simulations indicated that as endogenous degradation rates of microbial storage products were increased, EBPR performance decreased more rapidly according to the distributed approach than according to the lumped approach. State profile analysis demonstrated that as these rates increased, the population fraction with depleted storage products also increased, and this tended to increase the error in calculated biokinetic rates by the lumped approach. Simulations based on recently reported endogenous rate coefficients also suggested large differences between distributed and lumped predictions of EBPR performance. These results demonstrated that endogenous decay processes may play a more important role in EBPR than predicted by the lumped approach. This suggests a need for further research to determine endogenous process rates, and for incorporation of this information to distributed-type simulators, as this should lead to improved accuracy of EBPR simulations.
Schuler
Andrew J
AJ
Department of Civil and Environmental Engineering, Duke University, Durham, NC 27701, USA. aschuler@duke.edu
Jassby
David
D
D019149:Bioreactors / Q000382:microbiology*; D003198:Computer Simulation; D007220:Industrial Waste / Q000517:prevention & control*; D008954:Models, Biological; D012722:Sewage / Q000382:microbiology*; D014874:Water Pollutants, Chemical / Q000378:metabolism*; D018508:Water Purification / Q000379:methods*
D007220:Industrial Waste; D012722:Sewage; D014874:Water Pollutants, Chemical