Fast DNA-analyses for surveillance of microbial communities in full-scale deammonification tanks: Potential for control and troubleshooting
•Fast and frequent DNA sequencing gave added value to online sensors for process surveillance and control.•Anammox bacteria (Ca. Brocadia) revealed unexpected variations causing poor N-removal.•Analyses of AOB and NOB allow increased DO to improve N-removal while keeping NOB in control.•Analyses of...
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Veröffentlicht in: | Water research (Oxford) 2023-06, Vol.236, p.119919-119919, Article 119919 |
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Sprache: | eng |
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Zusammenfassung: | •Fast and frequent DNA sequencing gave added value to online sensors for process surveillance and control.•Anammox bacteria (Ca. Brocadia) revealed unexpected variations causing poor N-removal.•Analyses of AOB and NOB allow increased DO to improve N-removal while keeping NOB in control.•Analyses of the flanking community provided improved process understanding.
The partial nitritation/anammox process is a popular process for sidestream nitrogen removal, but the process is sensitive to disturbances and requires extensive surveillance and monitoring for optimal performance. We followed two parallel sidestream full-scale deammonification reactors treating digester centrate for a year with high time-resolution of both online sensor data and microbial community as measured by Nanopore DNA sequencing. DNA surveillance revealed system disturbances and allowed for detection of process and equipment upsets, and it facilitated remediating operational actions. Surveillance of anammox bacteria (Ca. Brocadia) revealed unexpected variations, and the composition and dynamics of the flanking community indicated causes for occasional process disturbances with poor nitrogen removal. Monitoring the ammonia oxidizing bacteria (AOB) and nitrite oxidizing bacteria (NOB) could potentially allow reactor operation with increased dissolved oxygen (DO), yielding higher ammonia conversion while keeping NOB in control. The use of fast and frequent DNA sequencing (sampling 3–5 times a week, analysed once per week) was an important supplement, and in many cases superior, to the online sensor data for process surveillance, understanding and control.
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ISSN: | 0043-1354 1879-2448 |
DOI: | 10.1016/j.watres.2023.119919 |