A NOVEL MODEL OF ACTIVATED SLUDGE USING MONOD KINETICS TO DESCRIBE THE COMPETITION OF MICROBIAL POPULATIONS ON GROWTH LIMITING SUBSTRATE

A novel model for activated sludge sewage treatment was developed to predict exploitative competition of six heterotrophic bacterial species competing for three complementary growth limiting substrates using the non-interactive Monod equation. The central hypothesis of the model is that in a multi-species/substrate system the number of coexisting bacterial species, N, exceeds the number of limiting resources, K, available for them. The explanation for this is that for certain species combinations, the dynamics of the competition process generate non-equilibrium conditions and oscillations, and these oscillations in bacterial community structure allow the coexistence of greater number of species than the number of limiting substrates (N>K). This result is a direct contradiction of an existing activated sludge competition theory, “the principle of competitive exclusion,” which states that the competition process results in equilibrium conditions, which allow only N≤K species to coexist. The model was used to investigate the effect of varying solids retention times (SRT) and hydraulic retention time (HRT) values on the species diversity using the conventional, completely mixed activated sludge configuration. The results of model simulations showed that for a certain range of solids retention times (SRT = 2.6-5.6 days) the competition of six microbial species for three growth limiting substrates produces oscillations within the structure of the bacterial community allowing for the sustained growth of the six species on the three substrates. Also, the model simulations showed that low SRT values (2.3-2.5 days) act as a strong selective pressure reducing the diversity of the bacterial species through the mechanism of washout. At high SRT values (5.7-30 days), the competitive exclusion principle dominates and the diversity of the microbial community is reduced such that N ≤ K. The results of this model are of general importance for the design and operation of activated sludge systems demonstrating robust performance due to the presence of a diverse community of microorganisms. By developing a model to predict the diversity of the microbial community based upon operating conditions, we are providing a first step in the development of a system of rules-based design that maximizes the diversity of the microbial community in activated sludge systems.