Modeling of simultaneous growth and storage kinetics variation under unsteady feast conditions for aerobic heterotrophic biomass

Insel G., YAVASBAY A., OZCAN O. Y., Cokgor E.

BIOPROCESS AND BIOSYSTEMS ENGINEERING, vol.35, no.8, pp.1445-1454, 2012 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 35 Issue: 8
  • Publication Date: 2012
  • Doi Number: 10.1007/s00449-012-0733-1
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1445-1454
  • Istanbul Technical University Affiliated: Yes


The heterotrophic biomass has the capacity of utilizing substrate predominantly for growth or storage processes under steady-state conditions. In this study, the short-term variations in growth and storage kinetics of activated sludge under disturbed feeding conditions were analyzed using a multi-component biodegradation model. The variations in growth and storage kinetics were investigated with the aid of multi-response modeling and identifiability analysis. It was found that the heterotrophic biomass is able to increase its direct growth activity together with reducing the substrate storage capability under the availability of external substrate. Reducing the sludge age (SRT) from 10 to 2 days increased the maximum specific growth rate, mu (OHO,Max) from 3.9 to 7.0 day(-1), but did not considerably affected the maximum storage rate, k (Stor,OHO). The alteration of sludge age also elevated the half-saturation constant for growth (K (S,OHO)) from 5 to 25 mg COD/L. The increase in primary growth metabolism together with reduced storage rate was validated by model for two different sludge ages in the availability of external substrate. Aside from having a lower storage capability, the biomass had fast adaptation ability to direct growth process at low SRTs. The alteration of feed conditions was found to have different impacts on storage and growth kinetics. These results are significant and advance the field of activated sludge modeling under dynamic conditions by incorporation of short-term effects. Appropriate modifications including short-term effects in model structure may also reduce dynamic model recalibration efforts in the future.