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Start-up and performance of partial nitritation process using short-term starvation.

Lihong Ye1, Dong Li1, Jie Zhang2

  • 1Key Laboratory of Water Science and Water Environment Recovery Engineering, Beijing University of Technology, Beijing 100123, China.

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|January 10, 2019
PubMed
Summary

Short-term starvation rapidly achieved partial nitritation, a key step in biological nitrogen removal. This method effectively suppressed nitrite-oxidizing bacteria (NOB) while preserving ammonium-oxidizing bacteria (AerAOB) for efficient nitrite accumulation.

Keywords:
Air flow ratioMicrobial communityNitrite accumulationPartial nitritationStarvation

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Area of Science:

  • Environmental Science
  • Microbiology
  • Biotechnology

Background:

  • Partial nitritation is crucial for cost-effective biological nitrogen removal and the anammox process.
  • Achieving efficient partial nitritation often requires specific operational strategies.

Purpose of the Study:

  • To present a novel method for partial nitritation using short-term starvation and low airflow.
  • To investigate the impact of this method on reactor performance, nitrifying bacteria activity, and community structure.

Main Methods:

  • Utilizing a sequencing batch reactor (SBR) with mixed activated sludge under aerobic/anaerobic conditions.
  • Implementing short-term starvation and controlling low airflow rates.
  • Analyzing reactor performance, nitrifying bacteria activities, and bacterial community structures.

Main Results:

  • Rapid achievement of partial nitritation with an average nitrite accumulation rate (NAR) of 878 gNm⁻³d⁻¹.
  • Short-term starvation had a greater inhibitory effect on nitrite-oxidizing bacteria (NOB) than on aerobic ammonium-oxidizing bacteria (AerAOB).
  • Nitrosomonas and uncultured Nitrosomonadaceae were identified as dominant AerAOB species with good starvation adaptability.

Conclusions:

  • Short-term starvation is an effective strategy for achieving nitrite accumulation and partial nitritation.
  • This method offers a promising approach for optimizing biological nitrogen removal processes.
  • Understanding bacterial community dynamics is key to successful process implementation.