scholarly journals Estimation of Denitrifying Polyphosphate-Accumulating Organisms in Enhanced Biological Phosphorus Removal Process Treating Municipal Wastewater

2004 ◽  
Vol 27 (4) ◽  
pp. 255-260
Author(s):  
Tadashi SHOJI ◽  
Hiroyasu SATOH ◽  
Takashi MINO
2018 ◽  
Vol 2018 (5) ◽  
pp. 223-239
Author(s):  
Nicholas B Tooker ◽  
Guangyu Li ◽  
Varun Srinivasan ◽  
James L Barnard ◽  
Charles Bott ◽  
...  

2006 ◽  
Vol 54 (1) ◽  
pp. 199-207 ◽  
Author(s):  
A.J. Schuler

Computer simulation of activated sludge population dynamics is a useful tool in process design, operation, and troubleshooting, but currently available programs rely on the assumption of “lumped,” or average, system characteristics in each reactor, such as microbial storage product contents. In reality, the states of individual bacteria are likely to vary due to variable residence times in reactors with completely mixed hydraulics. Earlier work by the present author introduced the MATLAB-based distributed state simulation program, Dissimulator 1.0, and demonstrated that distributed states may be particularly important in enhanced biological phosphorus removal (EBPR) systems, which rely on the cycling of bacteria through anaerobic and aerobic reactors to select for a population accumulating multiple microbial storage products. This paper explores the relationships between distributed state profiles, variable anaerobic and aerobic SRTs, and the process rates predicted by lumped and distributed approaches. Consistent with previous results, the lumped approach consistently predicted better EBPR performance than did the distributed approach. The primary reason for this was the presence of large fractions of polyphosphate accumulating organisms (PAOs) with depleted microbial storage product contents, which led to overestimation of process rates by the lumped approach. Distributed and lumped predictions were therefore most similar when microbial storage product depletion was minimal. The effects of variable anaerobic and aerobic SRTs on distributed profile characteristics and process rates are presented. This work demonstrated that lumped assumptions may overestimate EBPR performance, and the degree of this error is a function of the distributed state profile characteristics such as the degree to which fractions of the biomass contain depleted microbial storage product contents.


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