Monitoring off-gas O2/CO2 to predict nitrification performance in activated sludge processes

Shao Yuan Leu, Judy A. Libra, Michael K. Stenstrom

Research output: Journal article publicationJournal articleAcademic researchpeer-review

18 Citations (Scopus)


Nitrification/denitrification (NDN) processes are the most widely used technique to remove nitrogenous pollutants from municipal wastewater. The performance of nitrogen removal in the NDN process depends on the metabolism of nitrifying bacteria, and is dependent on adequate oxygen supply. Off-gas testing is a convenient and popular method for measuring oxygen transfer efficiency (OTE) under process conditions and can be performed in real-time. Since carbon dioxide is produced by carbonaceous oxidizing organism and not by nitrifiers, it should be possible to use the off-gas carbon dioxide mole fraction to estimate nitrification performance independently of the oxygen uptake rate (OUR) or OTE. This paper used off-gas data with a dynamic model to estimate nitrifying efficiency for various activated sludge process conditions. The relationship among nitrification, oxygen transfer, carbon dioxide production, and pH change was investigated. Experimental results of an online off-gas monitoring for a full-scale treatment plant were used to validate the model. The results showed measurable differences in OUR and carbon dioxide transfer rate (CTR) and the simulations successfully predicted the effluent ammonia by using the measured CO2 and O2 contents in off-gas as input signal. Carbon dioxide in the off-gas could be a useful technique to control aeration and to monitor nitrification rate.
Original languageEnglish
Pages (from-to)3434-3444
Number of pages11
JournalWater Research
Issue number11
Publication statusPublished - 1 Jun 2010
Externally publishedYes


  • Activated sludge process
  • Dynamic model
  • Nitrification
  • Off-gas
  • Wastewater

ASJC Scopus subject areas

  • Ecological Modelling
  • Water Science and Technology
  • Waste Management and Disposal
  • Pollution


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