Nitrous oxide (N
2
O) emissions from wastewater treatment plants vary substantially between plants, ranging from negligible to substantial (a few per cent of the total nitrogen load), probably because of different designs and operational conditions. In general, plants that achieve high levels of nitrogen removal emit less N
2
O, indicating that no compromise is required between high water quality and lower N
2
O emissions. N
2
O emissions primarily occur in aerated zones/compartments/periods owing to active stripping, and ammonia-oxidizing bacteria, rather than heterotrophic denitrifiers, are the main contributors. However, the detailed mechanisms remain to be fully elucidated, despite strong evidence suggesting that both nitrifier denitrification and the chemical breakdown of intermediates of hydroxylamine oxidation are probably involved. With increased understanding of the fundamental reactions responsible for N
2
O production in wastewater treatment systems and the conditions that stimulate their occurrence, reduction of N
2
O emissions from wastewater treatment systems through improved plant design and operation will be achieved in the near future.
Autotrophic ammonia oxidizing bacteria (AOB) have been recognized as a major contributor to N2O production in wastewater treatment systems. However, so far N2O models have been proposed based on a single N2O production pathway by AOB, and there is still a lack of effective approach for the integration of these models. In this work, an integrated mathematical model that considers multiple production pathways is developed to describe N2O production by AOB. The pathways considered include the nitrifier denitrification pathway (N2O as the final product of AOB denitrification with NO2(-) as the terminal electron acceptor) and the hydroxylamine (NH2OH) pathway (N2O as a byproduct of incomplete oxidation of NH2OH to NO2(-)). In this model, the oxidation and reduction processes are modeled separately, with intracellular electron carriers introduced to link the two types of processes. The model is calibrated and validated using experimental data obtained with two independent nitrifying cultures. The model satisfactorily describes the N2O data from both systems. The model also predicts shifts of the dominating pathway at various dissolved oxygen (DO) and nitrite levels, consistent with previous hypotheses. This unified model is expected to enhance our ability to predict N2O production by AOB in wastewater treatment systems under varying operational conditions.
Mathematical modeling of N2O emissions is of great importance toward understanding the whole environmental impact of wastewater treatment systems. However, information on modeling of N2O emissions from full-scale wastewater treatment plants (WWTP) is still sparse. In this work, a mathematical model based on currently known or hypothesized metabolic pathways for N2O productions by heterotrophic denitrifiers and ammonia-oxidizing bacteria (AOB) is developed and calibrated to describe the N2O emissions from full-scale WWTPs. The model described well the dynamic ammonium, nitrite, nitrate, dissolved oxygen (DO) and N2O data collected from both an open oxidation ditch (OD) system with surface aerators and a sequencing batch reactor (SBR) system with bubbling aeration. The obtained kinetic parameters for N2O production are found to be reasonable as the 95% confidence regions of the estimates are all small with mean values approximately at the center. The model is further validated with independent data sets collected from the same two WWTPs. This is the first time that mathematical modeling of N2O emissions is conducted successfully for full-scale WWTPs. While clearly showing that the NH2OH related pathways could well explain N2O production and emission in the two full-scale plants studied, the modeling results do not prove the dominance of the NH2OH pathways in these plants, nor rule out the possibility of AOB denitrification being a potentially dominating pathway in other WWTPs that are designed or operated differently.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.