Assessment of a two-step nitrification model for activated sludge

The objective of developing empirical models with well determined parameters is to obtain a better understanding of the nitrification of activated sludge. The D-optimal experimental design criterion and nonlinear regression analysis were used to obtain precise parameter estimates. Our experiment con...

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Bibliographic Details
Published in:Water research (Oxford) 1996, Vol.30 (4), p.939-953
Main Authors: Ossenbruggen, Paul J., Spanjers, Henri, Klapwik, Abraham
Format: Article
Language:English
Subjects:
activated sludge
Applied sciences
Biological and medical sciences
Biological treatment of waters
Biotechnology
Environment and pollution
Environmental Technology
Exact sciences and technology
experimental design
Fundamental and applied biological sciences. Psychology
General purification processes
Industrial applications and implications. Economical aspects
Mathematical models
Michaelis-Menten
Milieutechnologie
modeling
Monod
Nitrification
nonlinear regression
oxygen uptake rate
oxygen utilization rate
Pollution
Q1
respiration rate
Sectie Milieutechnologie
Sewage sludge
Sodium compounds
Sub-department of Environmental Technology
Wastewaters
Water treatment and pollution
WIMEK
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Summary:The objective of developing empirical models with well determined parameters is to obtain a better understanding of the nitrification of activated sludge. The D-optimal experimental design criterion and nonlinear regression analysis were used to obtain precise parameter estimates. Our experiment consisted of a series of 14 batch runs where activated sludge was spiked with ammonium chloride and sodium nitrite individually and in combination. Specific respiration rate, the ratio of respiration rate to mixed liquor suspended solids concentration, was used as the model response variable. Empirical models for specific respiration rate were specified as piecewise, Monod type functions of ammonium and nitrite concentration. Statistical methods were used to evaluate the effects of nonlinearity and parameter correlation on the models. The effect of experimental design on model specification and on parameter estimation is discussed.
ISSN:0043-1354
1879-2448
DOI:10.1016/0043-1354(95)00236-7