Predicting COD and TN in A2O+AO Process Considering Influent and Reactor Variability: A Dynamic Ensemble Model Approach DOI Open Access
Yingjie Guo, Jiyeon Kim, Jeong-Hyun Park

et al.

Water, Journal Year: 2024, Volume and Issue: 16(22), P. 3212 - 3212

Published: Nov. 8, 2024

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

Language: Английский

Variable contribution of wastewater treatment plant effluents to downstream nitrous oxide concentrations and emissions DOI Creative Commons
Weiyi Tang,

J. Talbott,

Timothy G. J. Jones

et al.

Biogeosciences, Journal Year: 2024, Volume and Issue: 21(14), P. 3239 - 3250

Published: July 17, 2024

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

Language: Английский

Citations

5
Mitigating Nitrous Oxide Emission from a Lab-Scale Membrane-Aerated Biofilm Reactor DOI Open Access

Andras Nemeth,

Eoin Casey, Eoin Syron

et al.

Water, Journal Year: 2025, Volume and Issue: 17(4), P. 500 - 500

Published: Feb. 11, 2025

The membrane-aerated biofilm reactor (MABR) is an emerging technology for the biological treatment of wastewaters. It can achieve simultaneous nitrification and denitrification due to anoxic liquid conditions. counter diffusion oxygen nutrients in allows aerobic layers, providing conditions where formation, accumulation consumption nitrous oxide all occur. microbial processes involved production N2O are complex, and, innovative nature MABR, understanding influence operational factors helps minimise emission. Using a lab-scale 20L MABR system, investigation was carried out determine on emission from reactor. A direct link between emissions bulk could not be established with only limited statistical correlation them. found that under both steady loading rates transient conditions, most influenced by air flow rate through membranes. majority occurred via membrane off-gas liquid. flux side but also gas residence time lumen side. Therefore, minimising effective strategy mitigate MABR.

Language: Английский

Citations

0
A review on optimization strategies for conventional nitrogen removal process and anammox process: Microbial community structure, functional genes and enzyme activity DOI
Nan Wang,

Jiaoteng Wei,

Shaoyuan Bai

et al.

Journal of environmental chemical engineering, Journal Year: 2025, Volume and Issue: 13(3), P. 116788 - 116788

Published: April 25, 2025

Language: Английский

Citations

0
Predicting COD and TN in A2O+AO Process Considering Influent and Reactor Variability: A Dynamic Ensemble Model Approach DOI Open Access
Yingjie Guo, Jiyeon Kim, Jeong-Hyun Park

et al.

Water, Journal Year: 2024, Volume and Issue: 16(22), P. 3212 - 3212

Published: Nov. 8, 2024

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

Language: Английский

Citations

0