Correlation of Community Dynamics and Process Parameters As a Tool for the Prediction of the Stability of Wastewater Treatment

Abstract

Wastewater treatment often suffers from instabilities and the failure of specific functions such as biological phosphorus removal by polyphosphate accumulating organisms. Since most of the microorganisms involved in water clarification are unknown it is challenging to operate the process accounting for the permanent varying abiotic parameters and the complex composition and unrevealed metabolic capacity of a wastewater microbial community. Fulfilling the demands for water quality irrespective of substrate inflow conditions may emit severe problems if the limited management resources of municipal wastewater treatment plants are regarded. We used flow cytometric analyses of cellular DNA and polyphosphate to create patterns mirroring dynamics in community structure. These patterns were resolved in up to 15 subclusters, the presence and abundances of which correlated with abiotic data. The study used biostatistics to determine the kind and strength of the correlation. Samples investigated were obtained from a primary clarifier and two activated sludge basins. The stability of microbial community structure was found to be high in the basins and low in the primary clarifier. Despite major abiotic changes certain subcommunities were dominantly present (up to 80% stability), whereas others emerged only sporadically (down to 3% stability, both according to equivalence testing). Additionally, subcommunities of diagnostic value were detected showing positive correlation with substrate influxes. For instance blackwater (r(s) = 0.5) and brewery inflow (both r(s) = 0.6) were mirrored by increases in cell abundances in subclusters 1 and 6 as well as 4 and 8, respectively. Phosphate accumulation was obviously positively correlated with nitrate (r(s) = 0.4) and the presence of denitrifying organisms (Rhodacyclaceae). Various other correlations between community structure and abiotic parameters were apparent. The bacterial composition of certain subcommunities was determined by cell sorting and phylogenetic tools like T-RFLP. In essence, we developed a monitoring tool which is quick, cheap and causal in its interpretation. It will make laborious PCR based technique less obligatory as it allows reliable process monitoring and control in wastewater treatment plants.