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Biological nitrogen removal with nitrification and denitrification via nitrite pathway

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Peng, Yongzhen, Zhu, Guibing·2006·Applied Microbiology and Biotechnology

Abstract

Presently, the wastewater treatment practices can be significantly improved through the introduction of new microbial treatment technologies. To meet increasingly stringent discharge standards, new applications and control strategies for the sustainable removal of ammonium from wastewater have to be implemented. Partial nitrification to nitrite was reported to be technically feasible and economically favorable, especially when wastewater with high ammonium concentrations or low C/N ratios is treated. For successful implementation of the technology, the critical point is how to maintain partial nitrification of ammonium to nitrite. Partial nitrification can be obtained by selectively inhibiting nitrite oxidizing bacteria through appropriate regulation of the system’s DO concentration, microbial SRT, pH, temperature, substrate concentration and load, operational and aeration pattern, and inhibitor. The review addressed the microbiology, its consequences for their application, the current status regarding application, and the future developments.

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Metadata

Authors
Peng, Y., & Zhu, G.
Venue
Applied Microbiology and Biotechnology
Published
2006-10-07
Volume
73
Issue
1
Pages
15-26
ISSN
  • 0175-7598 (ISSN-L)
  • 1432-0614
OpenAlex
W2013306379
Cited by
589
References
0
FWCI
11.94
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Biological nitrogen removal with nitrification and denitrification via nitrite pathway. https://app.cochat.ai/papers/10.1007/s00253-006-0534-z
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Peng, Y., & Zhu, G. (2006). Biological nitrogen removal with nitrification and denitrification via nitrite pathway. Applied Microbiology and Biotechnology. https://doi.org/10.1007/s00253-006-0534-z

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.