Abstract
Three denitrifying bacteria, Paracoccus spp., Thauera spp., Pseudomonas-like spp., and two functional genes, nitrate reductase (narG and napA), were studied as potential biomarkers for total nitrogen removal. These bacterial genera and the functional genes showed significant negative correlations with total nitrogen in the effluent (TNeff). Thauera spp. had the highest correlation (r = −0.793, p < 0.001) with TNeff, and narG-like and napA genes also showed significant correlations (r = −0.663 and −0.643, respectively), suggesting functional genes have equal validity to 16S rRNA genes in monitoring denitrification performance. The most explanatory variables were a combination of constituents, with temperature emerging as the most important in Pearson’s correlation and redundancy analysis. Thauera spp. had the highest correlation with temperature (r = 0.739) followed closely by Paracoccus spp. (r = 0.705). Denitrification was also significantly affected by pH (r = 0.369), solids retention time (r = −0.377), total nitrogenin (r = 0.635), and organic matter in the influent (biochemical oxygen demand and chemical oxygen demand; r = 0.320 and 0.522, respectively). Our data verified that major denitrifiers’ 16S rRNA genes and nitrate reductase genes were better biomarkers than the biomass concentration, and any of the biomarkers could track denitrification in real time.
Highlights
In biological nitrogen removal (BNR) processes, nitrogen conversion relies on biological metabolism, and a number of physicochemical parameters have been found to affect the performance of BNR systems
Since engineering practices of wastewater treatment are normally based on overall process function, it may be better described by using predominant organisms responsible for denitrification as opposed to identifying all bacteria containing a suite of denitrification genes
Our findings suggested that the quantities and performance of denitrifying bacteria will noticeably benefit from keeping a stringent anoxic environment in denitrification process
Summary
In biological nitrogen removal (BNR) processes, nitrogen conversion relies on biological metabolism, and a number of physicochemical parameters have been found to affect the performance of BNR systems. Dissolved oxygen (DO) in the anoxic zone, pH, mixed liquor temperature, mixed liquor suspended solids concentration (MLSS), availability of biodegradable carbon, carbon to nitrogen ratio (C:N ratio), and toxicity of the influent have an impact on nitrogen removal efficiency [1,2,3]. Amongst these operational conditions, MLSS have been used to estimate the amount of biomass and served as a surrogate to design process configurations and to predict process outcomes through activated sludge models. Since engineering practices of wastewater treatment are normally based on overall process function, it may be better described by using predominant organisms responsible for denitrification as opposed to identifying all bacteria containing a suite of denitrification genes
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