Nitrification has been widely applied in wastewater treatment, however gaining more insight into the nitrifiers’ physiology and stress response is necessary for the optimization of nutrient removal and design of advanced processes. Since nitrification initiates with ammonia oxidation performed by ammonia-oxidizing bacteria (AOB), the purpose of this study was to investigate the effects of short-term ammonia starvation on nitrogen uptake and transformation efficiency, as well as the performance of starved nitrifiers under various initial substrate concentrations and pH values. Ammonium deprivation for 3 days resulted in fast ammonium/ammonia accumulation upon nitrogen availability, with a maximum uptake rate of 3.87 mmol gprotein−1 min−1. Furthermore, a delay in the production of nitrate was observed with increasing starvation periods, resulting in slower recovery and lower nitrification rate compared to non-starved cells. The maximum accumulation capacity observed was 8.51% (w/w) independently of the external nitrogen concentration, at a range of 250–750 mg N L−1, while pH significantly affected ammonia oxidizers’ response, with alkaline values enhancing nitrogen uptake. In total, ammonia accumulation after short-term starvation might serve as an important strategy that helps AOB restore their activity, while concurrently it could be applied in wastewater treatment for effective nitrogen removal and subsequent biomass utilization.
Nitrification, a crucial process in wastewater treatment, involves the conversion of ammonium nitrogen to nitrate nitrogen through the sequential activities of ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB). In the present study, a comprehensive mathematical model was developed to describe the nitrification process in mixed cultures involving isolated NOB and starved AOB. The growth equation for NOB was divided into anabolism and catabolism, elucidating the key substrates driving their metabolic activities. Considering the ammonia starvation effect, a single cell-based model was developed to capture the mass transfer phenomena across the AOB cell membrane. This addition allowed for a more accurate representation of the biological dynamics during starvation conditions. The model’s accuracy was tested using experimental data that was not used in the model calibration step. The prediction’s coefficient of determination (R2) was estimated at 0.9. By providing insights into the intricate mechanisms underlying nitrification, this model contributes to the advancement of sustainable wastewater treatment practices.
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