Biotechnology and Bioengineering, Vol.92, No.5, 600-613, 2005
A new approach for modelling simultaneous storage and growth processes for activated sludge systems under aerobic conditions
By critically evaluating previous models, anew mechanistic model is developed to describe simultaneous storage and growth processes occurring in activated sludge systems under aerobic conditions. Identifiability was considered an important criterion during the model development since it among others helps to increase the realiability and applicability of models to full-scale WWTPs. A second order model was proposed for description of the degradation of the storage products under famine conditions. The model is successfully calibrated by only using OUR data obtained from batch experiments. Calibrations were performed with biomass from full-scale WWTPs in Belgium and Spain. Predictions of the calk brated model were successfully confirmed using off-line PHB measurements, supporting the validity of the model. An iterative experimental design procedure was successfully applied and found to remarkably improve the parameter estimation accuracy for the growth on storage parameters K-1 and K-2, which used to have large confidence intervals when using standard experiments. The estimated biomass growth yield on substrate (0.58 mgCOD/mgCOD) is quite close to the theoretically expected range for heterotrophic growth. This became possible by properly accounting for the storage process. Moreover, the maximum growth rate was predicted in the range 0.7-1.3 per day. This range, albeit quite lower than the values reported for the growth-based ASM models, is believed to be more realistic. Finally, the new model is expected to better and more mechanistically describe simultaneous storage and growth activities of activated sludge systems and as such could contribute to improved design, operation and control of those systems. (c) 2005 Wiley Periodicals, Inc.
Keywords:activated sludge modelling;storage metabolism;respirometry;practical identifiability;optimal experimental design (OED)