Mathematical modeling of nitrous oxide (N2O) production in anaerobic/anoxic/oxic processes: Improvements to published N2O models

- An improved model was proposed for N2O production modeling in the A2O process.
- Competition for electrons among four denitrification reductases was considered.
- One affinity constant for XSTO was divided into four constants in the model.
- The improved model better predicted N2O production and nitrite accumulation.
- N2O accumulation resulted from the more rapid decline of the N2O reduction rate.

Competition for electrons among different steps of denitrification on intracellular polymers (XSTO) plays a significant role in nitrous oxide (N2O) accumulation in the biological nitrogen removal process. In this work, this electron competition was considered in a mathematical model to predict N2O production in anaerobic/anoxic/oxic sequencing batch reactors (A2O-SBR) for the first time. The affinity constant for intracellular polymers of heterotrophs (KSTO) that was used in previously published models was divided into four affinity constants (KSTO,1, KSTO,2, KSTO,3 and KSTO,4) to represent the ability of each denitrification reductase to compete for intracellular polymers. The improved model was calibrated and validated using experimental data from three independent A2O-SBR systems. The results demonstrated that the modeling predictions strongly agreed with the measured data from all experimental tests under various operational conditions. The modeling results indicated that N2O accumulation resulted from the more rapid decline of the N2O reduction rate than the nitrite reduction rate for the inadequate XSTO in these A2O-SBR systems. The modeling results also suggested that distinguishing affinity constants for intracellular polymers during the four-step denitrification felicitously described a different XSTO distribution in each reduction step, thereby better predicting nitrogen dynamics and N2O production in A2O processes than the published model. The improved model is therefore a preferable tool to gain insight into N2O accumulation in A2O processes.

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