A Novel Perspective on the Instability of Mainstream Partial Nitrification: The Niche Differentiation of Nitrifying
Xiaochuan Ran1, Tong Wang1, Mingda Zhou1
1State Key Laboratory of Water Pollution Control and Green Resources Recycling, Shanghai Institute of Pollution Control and Ecological Security, College of Environmental Science and Engineering, Tongji University, Siping Road, Shanghai 200092, PR China.
Abstract:
Short-cut biological nitrogen removal (sBNR) favors the paradigm shift toward energy-positive and carbon-neutral wastewater treatment processes. Partial nitrification (PN) is a key approach to provide nitrite for anammox or denitritation during sBNR, and its stability is the precondition for achieving robust nitrogen removal performance. However, maintaining a stable mainstream PN process has been a long-standing challenge. This review analyzes the mainstream PN process from a microbial ecology perspective, focusing on the niche differentiation among nitrifiers. First, we propose that mainstream PN systems are ecologically unstable, and the failure of the mainstream PN process due to the reactivation of nitrite-oxidizing bacteria (NOB) can be regarded as a behavior to restore system stabilization. Thus, maintaining mainstream PN systems primarily relies on enhancing the niche differentiation between ammonia-oxidizing bacteria (AOB) and NOB. We then summarize the realized niches of indigenous nitrifiers within nitrification systems and discuss their ecophysiological characteristics (e.g., cell structure and substrate affinity) that define their specific ecological niches. By comparing the niche breadths of AOB and NOB on various niche axes, we further discuss their niche differentiation and identify the different responses of AOB (resistance) and NOB (resilience) to exogenous perturbations. Finally, we propose outlook for achieving a stable mainstream PN process through an ecological lens. This review provides ecological insights into the instability of the mainstream PN process, which is intended to guide the derivation of optimized strategies from a single-factor approach to integrated solutions.
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