Impact of influent characteristics and operational parameters on nitrous oxide emissions in wastewater treatment: Strategies for mitigation and microbial insights

Zhao, Yi-Wei; Du, Li-Li; Hu, Bing; Lin, Hong-Yong; Liang, Bin; Song, Yun-Peng; Wang, Yu-Qi; Wang, Hong-Wu; Li, Peng-Fei; Wang, Ai-Jie; Wang, Hong-Cheng

doi:10.1016/j.crbiot.2024.100207

Current Research in Biotechnology

2024

DOI: 10.1016/j.crbiot.2024.100207

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Impact of influent characteristics and operational parameters on nitrous oxide emissions in wastewater treatment: Strategies for mitigation and microbial insights

Yi-Wei Zhao,

Li-Li Du,

Bing Hu

et al.

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2024

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Cited by 2 publications

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Predicting COD and TN in A2O+AO Process Considering Influent and Reactor Variability: A Dynamic Ensemble Model Approach

Guo,

Kim,

Park

et al. 2024

Water

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The prediction of the chemical oxygen demand (COD) and total nitrogen (TN) in integrated anaerobic–anoxic–oxic (A2O) and anoxic–oxic (AO) processes (i.e., A2O+AO process) was achieved using a dynamic ensemble model that reflects the dynamics of wastewater treatment plants (WWTPs). This model effectively captures the variability in the influent characteristics and fluctuations within each reactor of the A2O+AO process. By employing a time-lag approach based on the hydraulic retention time (HRT), artificial intelligence (AI) selects suitable input (i.e., pH, temperature, total dissolved solid (TDS), NH3-N, and NO3-N) and output (COD and TN) data pairs for training, minimizing the error between predicted and observed values. Data collected over two years from the actual A2O+AO process were utilized. The ensemble model adopted machine learning-based XGBoost for COD and TN predictions. The dynamic ensemble model outperformed the static ensemble model, with the mean absolute percentage error (MAPE) for the COD ranging from 9.5% to 15.2%, compared to the static ensemble model’s range of 11.4% to 16.9%. For the TN, the dynamic model’s errors ranged from 9.4% to 15.5%, while the static model showed lower errors in specific reactors, particularly in the anoxic and oxic stages due to their stable characteristics. These results indicate that the dynamic ensemble model is suitable for predicting water quality in WWTPs, especially as variability may increase due to external environmental factors in the future.

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Predicting COD and TN in A2O+AO Process Considering Influent and Reactor Variability: A Dynamic Ensemble Model Approach

Guo,

Kim,

Park

et al. 2024

Water

View full text Add to dashboard Cite

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Variable contribution of wastewater treatment plant effluents to downstream nitrous oxide concentrations and emissions

Tang,

Talbott,

Jones

et al. 2024

Biogeosciences

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Abstract. Nitrous oxide (N2O), a potent greenhouse gas and ozone-destroying agent, is produced during nitrogen transformations in both natural and human-constructed environments. Wastewater treatment plants (WWTPs) produce and emit N2O into the atmosphere during the nitrogen removal process. However, the impact of WWTPs on N2O emissions in downstream aquatic systems remains poorly constrained. By measuring N2O concentrations at a monthly resolution over a year in the Potomac River estuary, a tributary of the Chesapeake Bay in the eastern United States, we found a strong seasonal variation in N2O concentrations and fluxes: N2O concentrations were larger in fall and winter, but the flux was larger in summer and fall. Observations at multiple stations across the Potomac River estuary revealed hotspots of N2O emissions downstream of WWTPs. N2O concentrations were higher at stations downstream of WWTPs compared to other stations (median: 21.2 nM vs. 16.2 nM) despite the similar concentration of dissolved inorganic nitrogen, suggesting the direct discharge of N2O from WWTPs into the aquatic system or a higher N2O production yield in waters influenced by WWTPs. Meta-analysis of N2O measurements associated with WWTPs globally revealed variable influence of WWTPs on downstream N2O concentrations and emissions. Since wastewater production has increased substantially with the growing population and is projected to continue to rise, accurately accounting for N2O emissions downstream of WWTPs is important for constraining and predicting future global N2O emissions. Efficient N2O removal, in addition to dissolved nitrogen removal, should be an essential part of water quality control in WWTPs.

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Impact of influent characteristics and operational parameters on nitrous oxide emissions in wastewater treatment: Strategies for mitigation and microbial insights

Cited by 2 publications

References 101 publications

Predicting COD and TN in A2O+AO Process Considering Influent and Reactor Variability: A Dynamic Ensemble Model Approach

Predicting COD and TN in A2O+AO Process Considering Influent and Reactor Variability: A Dynamic Ensemble Model Approach

Variable contribution of wastewater treatment plant effluents to downstream nitrous oxide concentrations and emissions

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