Environmental Science and Pollution Research

, Volume 22, Issue 17, pp 12849–12860 | Cite as

Modeling partial nitrification and denitrification in a hybrid biofilm reactor: calibration by retention time distribution and respirometric tests

  • Ming Zeng
  • Audrey Soric
  • Nicolas RocheEmail author
Treatment of pollution in constructed wetlands: from the fundamental mechanisms to the full scale applications. WETPOL 2013


In this study, partial nitrification coupled with denitrification is modeled in a hybrid biofilm reactor with different hydraulic saturation conditions. The activated sludge model with two-step nitrification is implemented in GPS-X software. Hydrodynamic modeling by retention time distribution analysis and biokinetic measurement by respirometric tests are two significant parts of model calibration. By combining these two parts, partial nitrification in the aerobic part of the column is well simulated with a good agreement between experimental and modeled effluent concentrations of NH4 + and NO2 . Particularly, fully hydraulic saturation condition contributes to the large hydraulic volume of 1.9 L and high produced NO2 concentration around 40 mg L−1. However, modeling denitrification still needs to be improved with more calibrated parameters. Furthermore, three alternatives are proposed for the optimization of reactor design and operation.


Hydrodynamic behavior Ammonium-oxidizing bacteria Respirometer Engineering GPS-X Wastewater treatment 



Specific surface area of porous media (square meters per cubic meter)


Decay (endogenous respiration) rate of heterotroph (per day)


Decay (endogenous respiration) rate of autotroph (per day)


Decay (endogenous respiration) rate of AOB (per day)


Decay (endogenous respiration) rate of NOB (per day)


Tracer concentration (grams per liter)


Retention time distribution (per minute)


Effective volume ratio (percent)


Fraction of inert material in biomass (−)


Substrate constant affinity for heterotroph (milligrams per liter)


Substrate constant affinity for autotroph (milligrams per liter)


Substrate constant affinity for AOB (milligrams per liter)


Substrate constant affinity for NOB (milligrams per liter)


Number of stirred tanks (−)


Water flow rate at the outlet (liters per minute)


Tracer recovery (percent)


Respiration rate (milligrams per liter per hour)


Actual hydraulic retention time (minutes)


Exchanging time between mobile and immobile volume (minutes)


Time of plug flow (minutes)


Hydraulic volume (liters)


Biomass concentration (milligrams per liter)


Yield rate of autotroph (grams COD per gram N)


Yield rate of AOB (grams COD per gram N)


Yield rate of heterotroph (grams COD per gram COD)


Yield rate of NOB (grams COD per gram N)


Mean square sensitivity measure (−)


Anoxic growth constant of heterotroph (−)


Nominal hydraulic retention time (−)


Maximum specific growth rate of autotroph (per day)


Maximum specific growth rate of AOB (per day)


Maximum specific growth rate of heterotroph (per day)


Maximum specific growth rate of NOB (per day)


Theoretical hydraulic retention time (minutes)

Supplementary material

11356_2014_3667_MOESM1_ESM.xlsm (150 kb)
Table A. 1 (XLSM 149 kb)


  1. Akunna J, Bizeau C, Moletta R, Bernet N, Héduit A (1994) Combined organic carbon and complete nitrogen removal using anaerobic and aerobic upflow filters. Water Sci Technol 30:297–306Google Scholar
  2. Eldyasti A, Andalib M, Hafez H, Nakhla G, Zhu J (2011) Comparative modeling of biological nutrient removal from landfill leachate using a circulating fluidized bed bioreactor (CFBBR). J Hazard Mater 187:140–149CrossRefGoogle Scholar
  3. Fall C, Hooijmans C, Esparza-Soto M, Olguin M, Bâ K (2012) Initial-rate based method for estimating the maximum heterotrophic growth rate parameter (μ H m a x. Bioresour Technol 116:126–132Google Scholar
  4. Gali A, Dosta J, Van Loosdrecht M, Mata-Alvarez J (2007) Two ways to achieve an anammox influent from real reject water treatment at lab-scale: partial SBR nitrification and SHARON process. Process Biochem 42:715–720CrossRefGoogle Scholar
  5. Gikas GD, Yiannakopoulou T, Tsihrintzis VA (2006) Modeling of non-point source pollution in a Mediterranean drainage basin. Environ Model Assess 11:219–233CrossRefGoogle Scholar
  6. Hellinga C, Van Loosdrecht M, Heijnen J (1999) Model based design of a novel process for nitrogen removal from concentrated flows. Math Comput Model Dyn Syst 5:351–371CrossRefGoogle Scholar
  7. Henze M, Grady C, Gujer W, Marais G, Matsuo T (1987) Activated sludge model No. 1. IAWPRC task group on mathematical modelling for design and operation of biological wastewater treatment, vol 1. Paper presented at the IAWPRC Scientific and Technical Reports, LondonGoogle Scholar
  8. Henze M, Gujer W, van Mino T, Loosdrecht M (2000) Activated sludge models: ASM1, ASM2, ASM2d and ASM3. IWA, LondonGoogle Scholar
  9. Huiliñir C, Romero R, Muñoz C, Bornhardt C, Roeckel M, Antileo C (2010) Dynamic modeling of partial nitrification in a rotating disk biofilm reactor: calibration, validation and simulation. Biochem Eng J 52:7–18CrossRefGoogle Scholar
  10. Hvala N, Strmčnik S, Šel D, Milanič S, Banko B (2005) Influence of model validation on proper selection of process models—an industrial case study. Comput Chem Eng 29:1507–1522CrossRefGoogle Scholar
  11. Kappeler J, Gujer W (1992) Estimation of kinetic parameters of heterotrophic biomass under aerobic conditions and characterization of wastewater for activated sludge modelling. Water Sci Technol 25:125–139Google Scholar
  12. Legates DR, McCabe GJ (1999) Evaluating the use of “goodness–of–fit” measures in hydrologic and hydroclimatic model validation. Water Resour Res 35:233–241CrossRefGoogle Scholar
  13. Libelli SM, Ratini P, Spagni A, Bortone G (2001) Implementation, study and calibration of a modified ASM2d for the simulation of SBR processes. Water Sci Technol 43:69–76Google Scholar
  14. Majewsky M, Gallé T, Bayerle M, Goel R, Fischer K, Vanrolleghem PA (2011) Xenobiotic removal efficiencies in wastewater treatment plants: residence time distributions as a guiding principle for sampling strategies. Water Res 45:6152–6162CrossRefGoogle Scholar
  15. Manser R, Gujer W, Siegrist H (2006) Decay processes of nitrifying bacteria in biological wastewater treatment systems. Water Res 40:2416–2426CrossRefGoogle Scholar
  16. McCarty PL, Meyer TE (2005) Numerical model for biological fluidized-bed reactor treatment of perchlorate-contaminated groundwater. Environ Sci Technol 39:850–858CrossRefGoogle Scholar
  17. Petersen B, Vanrolleghem P, Gernaey K, Henze M (2002) Evaluation of an ASM1 model calibration procedure on a municipal–industrial wastewater treatment plant. J Hydroinf 4:15–38Google Scholar
  18. Sánchez O, Michaud S, Escudié R, Delgenès J-P, Bernet N (2005) Liquid mixing and gas–liquid mass transfer in a three-phase inverse turbulent bed reactor. Chem Eng J 114:1–7CrossRefGoogle Scholar
  19. Séguret F, Racault Y, Sardin M (2000) Hydrodynamic behaviour of full scale trickling filters. Water Res 34:1551–1558CrossRefGoogle Scholar
  20. Torà JA, Moliné E, Carrera J, Pérez J (2013) Efficient and automated start-up of a pilot reactor for nitritation of reject water: from batch granulation to high rate continuous operation. Chem Eng J 226:319–325CrossRefGoogle Scholar
  21. Tremier A, De Guardia A, Massiani C, Paul E, Martel J (2005) A respirometric method for characterising the organic composition and biodegradation kinetics and the temperature influence on the biodegradation kinetics, for a mixture of sludge and bulking agent to be co-composted. Bioresour Technol 96:169–180CrossRefGoogle Scholar
  22. Vanrolleghem PA et al (2003) A comprehensive model calibration procedure for activated sludge models. Proc Water Environ Fed 2003:210–237CrossRefGoogle Scholar
  23. Zeng M, Soric A, Roche N (2013) Calibration of hydrodynamic behavior and biokinetics for TOC removal modeling in biofilm reactors under different hydraulic conditions. Bioresour Technol 144:202–209CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Aix Marseille University, Centrale MarseilleAix en ProvenceFrance

Personalised recommendations