The objective of this study was to evaluate the significance of heterotrophic growth in nitrifying biofilm reactors fed only with ammonium as an energy source. The diversity, abundance and spatial distribution of nitrifying bacteria were studied using a combination of molecular tools and mathematical modeling, in two biofilm reactors operated with different hydraulic retention times. The composition and distribution of nitrifying consortia in biofilms were quantified by fluorescence in situ hybridization (FISH) with rRNA-targeted oligonucleotide probes combined with confocal laser scanning microscopy (CLSM) and digital image analysis. Autotrophic and heterotrophic biofilm fractions determined by FISH were compared to the output from a multispecies model that incorporates soluble microbial products (SMP) production/consumption. In reactor R1 (short retention time) nearly 100% of the total bacteria could be identified as either ammonia- or nitrite-oxidizing bacteria by quantitative FISH analyses, while in reactor R2 (long retention time) the identification rate was only 73%, with the rest probably consisting of heterotrophs. Mathematical simulations were performed to evaluate the influence of the hydraulic retention time (HRT), biofilm thickness, and substrate utilization associated SMP production on the growth of heterotrophic bacteria. The model predicts that low HRTs resulted in a lower availability of SMPs leading to purely autotrophic biofilms. These model predictions are consistent with experimental observations. At HRTs that are about an order of magnitude larger than the reciprocal of the net maximum growth rate the majority of the active biomass will grow suspended in the bulk phase rather than in the biofilm.
Evaluating heterotrophic growth in a nitrifying biofilm reactor using fluorescence in situ hybridization and mathematical modeling
R. Nogueira, D. Elenter, A. Brito, L.F. Melo, M. Wagner, E. Morgenroth; Evaluating heterotrophic growth in a nitrifying biofilm reactor using fluorescence in situ hybridization and mathematical modeling. Water Sci Technol 1 October 2005; 52 (7): 135–141. doi: https://doi.org/10.2166/wst.2005.0192
Download citation file:
Impact Factor 1.915
CiteScore 3.3 • Q2
13 days from submission to first decision on average