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Relative Efficacy of Intrinsic and Extant Parameters for Modeling Biodegradation of Synthetic Organic Compounds in Activated Sludge: Dynamic Systems
Author(s) -
Magbanua Benjamin S.,
Stanfill J. Chris,
Fehniger Steven M.,
Smets Barth F.,
Farkas Ferenc,
Leslie Grady C.P.
Publication year - 2004
Publication title -
water environment research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.356
H-Index - 73
eISSN - 1554-7531
pISSN - 1061-4303
DOI - 10.2175/106143004x141816
Subject(s) - extant taxon , biodegradation , biomass (ecology) , mineralization (soil science) , abiotic component , activated sludge , biological system , batch reactor , substrate (aquarium) , bioreactor , chemistry , pulp and paper industry , environmental science , environmental engineering , sewage treatment , biology , ecology , engineering , organic chemistry , nitrogen , evolutionary biology , catalysis
The utility of intrinsic and extant kinetic parameters for simulating the dynamic behavior of a biotreatment system coupled with a distributed, unstructured, balanced microbial growth model were evaluated against the observed response of test reactors to transient loads of synthetic organic compounds (SOCs). Biomass from a completely mixed activatedsludge (CMAS) system was tested in fed‐batch reactors, while a sequencing batch reactor (SBR) was tested by measuring SOC concentrations during the fill and react period. Both the CMAS system and the SBR were acclimated to a feed containing biogenic substrates and several SOCs, and the transient loading tests were conducted with biogenic substrates along with one or more SOCs. Extant parameters more closely reflect the steady‐state degradative capacity of activated‐sludge biomass than intrinsic parameters and, hence, were expected to be better predictors of system performance. However, neither extant nor intrinsic parameters accurately predicted system response and neither parameter set was consistently superior to the other. Factors that may have contributed to the inability of the model to predict system response were identified and discussed. These factors included the role of abiotic processes in SOC removal, disparity in the bases used to evaluate parameter estimates (substrate mineralization) and reactor performance (substrate disappearance), inhibitory substrate interactions under the severe loading conditions of the SBR, changes in the physiological state of the biomass during the transient loading tests, and the presumed correlation between the competent biomass concentration and the influent SOC concentration.