Influence of process dynamics on the microbial diversity in a nitrifying biofilm reactor: Correlation analysis and simulation study.

For engineers, it is interesting to gain insight in the effect of control strategies on microbial communities, on their turn influencing the process behavior and its stability. This contribution assesses the influence of process dynamics on the microbial community in a biofilm reactor for nitrogen removal, which was controlled according to several strategies aiming at nitrite accumulation. The process dataset, combining conventional chemical and physical data with molecular information, was analyzed through a correlation analysis and in a simulation study. During nitrate formation, an increased nitrogen loading rate (NLR) resulted in a drop of the bulk liquid oxygen concentration without resulting in nitrite accumulation. A biofilm model was able to reproduce the bulk liquid nitrogen concentrations in two periods before and after this increased NLR. As the microbial parameters calibrated for the ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB) in both periods were different, it was concluded that the increased NLR governed an AOB and NOB population shift. Based on the molecular data, it was assumed that each period was typified by one dominant AOB and probably several subdominant NOB populations. The control strategies for nitrite accumulation influenced the bulk liquid composition by controlling the competition between AOB and NOB. Biotechnol. Bioeng. 2016;113: 1962-1974. © 2016 Wiley Periodicals, Inc.

Considering microbial and aggregate heterogeneity in biofilm reactor models: how far do we need to go?

A model describing a given system should be as simple as possible - but not simpler. The appropriate level of complexity depends both on the type of system and on the intended use of the model. This paper addresses the critical question of which purposes justify increased complexity of biofilm (reactor) models. Additional model features compared to conventional models considered are: (1) the inclusion of microbial diversity, distinguishing between different species performing the same function; and (2) the distinction between flocs and granules in putatively granular sludge reactors. With a multispecies model considering interspecies diversity, it was demonstrated that a given macroscopic reactor performance does not necessarily reflect steady state conditions on the microscale. In a second case study, it was shown that the addition of a small level of flocs can have a significant impact on macroscale process performance and on microbial population and activity distributions in granular sludge reactors. It was concluded that increased complexity in biofilm models, concerning microbial diversity or mesoscale aggregate architecture, is likely more useful when the focus is on understanding fundamental microscale outputs, but under specific conditions, these additional model features can be critically informative for bulk reactor behavior prediction and general understanding.