Zurück zur Übersicht

Regime Shift and Microbial Dynamics in a Sequencing Batch Reactor for Nitrification and Anammox Treatment of Urine

Publikationsart Peer-reviewed
Publikationsform Originalbeitrag (peer-reviewed)
Autor/in Bürgmann Helmut, Jenni Sarina, Vazquez Francisco, Udert Kai M.,
Projekt Decentralized urine treatment with the nitritation/anammox process (DUNOX)
Alle Daten anzeigen

Originalbeitrag (peer-reviewed)

Zeitschrift Applied and Environmental Microbiology
Volume (Issue) 77(17)
Seite(n) 5897 - 5907
Titel der Proceedings Applied and Environmental Microbiology
DOI 10.1128/AEM.02986-10


The microbial population and physicochemical process parameters of a sequencing batch reactor for nitrogen removal from urine were monitored over a 1.5-year period. Microbial community fingerprinting (automated ribosomal intergenic spacer analysis), 16S rRNA gene sequencing, and quantitative PCR on nitrogen cycle functional groups were used to characterize the microbial population. The reactor combined nitrification (ammonium oxidation)/anammox with organoheterotrophic denitrification. The nitrogen elimination rate initially increased by 400%, followed by an extended period of performance degradation. This phase was characterized by accumulation of nitrite and nitrous oxide, reduced anammox activity, and a different but stable microbial community. Outwashing of anammox bacteria or their inhibition by oxygen or nitrite was insufficient to explain reactor behavior. Multiple lines of evidence, e.g., regime-shift analysis of chemical and physical parameters and cluster and ordination analysis of the microbial community, indicated that the system had experienced a rapid transition to a new stable state that led to the observed inferior process rates. The events in the reactor can thus be interpreted to be an ecological regime shift. Constrained ordination indicated that the pH set point controlling cycle duration, temperature, airflow rate, and the release of nitric and nitrous oxides controlled the primarily heterotrophic microbial community. We show that by combining chemical and physical measurements, microbial community analysis and ecological theory allowed extraction of useful information about the causes and dynamics of the observed process instability.