AlSaleh, Marwan

Alsaleh, Marwan

Marwan Alsaleh is a speaker at WEFTEC 2026.

Titles from this speaker

Description: Field Evaluation of Ammonia-Based Aeration Control and N₂O Response in a...

Field Evaluation of Ammonia-Based Aeration Control and N₂O Response in a Full-Scale BNR Reactor

Abstract

[b]Objectives and Status[/b] Wastewater treatment plants are under growing pressure to reduce aeration energy while also mitigating direct greenhouse gas emissions, particularly nitrous oxide (N₂O). Although ammonia-based aeration control (ABAC) is increasingly implemented to reduce energy demand, its combined impacts on aeration energy, nitrogen removal performance, and N₂O emissions have not been quantified comprehensively at full scale. Most previous studies have evaluated either energy savings or N₂O behavior in isolation, leaving their integrated effects under real operating conditions uncertain. This study presents a full-scale comparison of energy–N₂O–performance trade-offs under ABAC and conventional fixed dissolved oxygen (DO) control strategies in a mainstream biological nutrient removal (BNR) reactor. To the authors' knowledge, this is the first study to compare high-DO, reduced-DO, and ammonia-based aeration control within the same full-scale mainstream BNR reactor using continuous dissolved N₂O monitoring. [b]Methodology[/b] The investigation was conducted in a nine-cell BNR reactor serving approximately 1.37 million population equivalents in western Canada and treating 40–50 MLD. Three aeration strategies were implemented sequentially: (i) fixed high DO (1.5–3.0 mg L⁻¹), (ii) feedback-Feedforward ABAC using online ammonia measurements to dynamically adjust airflow to meet effluent ammonia targets, and (iii) fixed reduced DO (0.8–2.0 mg L⁻¹). Each strategy was operated for 3–4 weeks under steady-state conditions. Two online Clark-type dissolved N₂O sensors were installed along the reactor length to continuously measure dissolved N₂O, which was converted to gaseous emissions using established mass-transfer relationships. Blower airflow, bioreactor power, and specific aeration energy were extracted from the plant SCADA system, while routine grab samples and online sensors were used to monitor NH₄⁺–N, NO₂⁻–N, NO₃⁻–N, COD, DO, pH, temperature, and dissolved N₂O concentrations. [b]Findings[/b] All aeration strategies achieved stable organic matter removal, with COD removal ranging from 78–83% across all phases. Ammonia removal efficiencies were 98.2% under high DO, 96.9% under ABAC, and 89.0% under reduced DO, with ABAC consistently maintaining effluent ammonia within compliance limits despite operating at lower average DO. Relative to the high-DO baseline, ABAC reduced airflow by 16% and bioreactor power by 18%, lowering the specific aeration energy from 0.096 to 0.086 kWh m⁻³. Operation under reduced DO achieved larger energy savings, with airflow and power reductions of 24% and 26%, respectively, and specific energy decreasing to 0.074 kWh m⁻³. Despite these reductions in aeration demand, N₂O emission factors expressed as a percentage of total nitrogen removed remained statistically similar for high DO (0.50%) and ABAC (0.50%), demonstrating that ABAC delivered meaningful energy savings without increasing N₂O emissions. In contrast, reduced DO operation decreased the N₂O emission factor to 0.37% but was associated with reduced nitrification robustness, as reflected by lower ammonia removal efficiency. These results indicate that while more aggressive DO reduction can suppress N₂O formation, ABAC achieves a favorable balance by lowering energy consumption while preserving both treatment performance and N₂O stability. [b]Significance[/b] This full-scale dataset demonstrates that ammonia-based aeration control can achieve significant reductions in aeration energy while maintaining nitrogen removal performance and without increasing N₂O emissions relative to conventional high-DO operation. The findings provide rare full-scale evidence that dynamic ammonia-feedback-feedforward aeration represents an energy-efficiency strategy that is climate-neutral with respect to N₂O, whereas more aggressive DO minimization introduces trade-offs between energy savings, emissions, and process stability.

This paper was presented at WEFTEC 2026 in New Orleans, Louisiana.

SpeakerAlsaleh, Marwan

Presentation time

15:30:00

16:00:00

Session time

15:30:00

17:00:00

SessionDecarbonizing Water: Facility Optimization and N2O

Session locationErnest N. Morial Convention Center

TopicFacility Operations and Maintenance

Author(s)

Alsaleh, Marwan, Zaghloul, Mohamed Sherif, Alsayed, Ahmed, Elsayed, Ahmed, Al-Omari, Ahmed, Cavanaugh, Shannon, Kakar, Farokh Laqa, Da Silva, Allegra, Jayathilake, Nisa, Porro, Jose, Santoro, Domenico, Ismail, Amr, Elbeshbishy, Elsayed

Author(s)M. Alsaleh1, M. Zaghloul2, A. Alsayed3, A. Elsayed4, A. Al-Omari5, S. Cavanaugh5, F. Kakar5, A. Da Silva5, N. Jayathilake6, J. Porro7, D. Santoro8, A. Ismail4, E. Elbeshbishy4

Author affiliation(s)Toronto Metropolitan University, 1United Arab Emirates University, 2Western University, 3Toronto Metropolitan University, 4Brown and Caldwell, 5Brown and Caldwell, 5Brown and Caldwell, 5Brown and Caldwell, 5City of Calgary, 6Cobalt Water Global, 7USP Technologies, 8Toronto Metropolitan University, 4Toronto Metropolitan University, 4

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Sep 2026

DOI10.2175/193864718825160536

Volume / Issue

Content sourceWEFTEC

Word count15

Description: Operational Strategies and N2O Emission Hotspots: Integrating Monitoring Campaigns...

Operational Strategies and N2O Emission Hotspots: Integrating Monitoring Campaigns with Process Modelling

Abstract

Introduction and Objectives The wastewater sector is transforming as traditional wastewater treatment plants (WWTPs) evolve into water resource recovery facilities (WRRFs) to tackle resource scarcity. Simultaneously, the urgency of climate change calls for rapid progress toward net-zero greenhouse gas (GHG) emissions. However, achieving net-zero in the wastewater sector presents complex challenges. Scope 1 GHG emissions, especially methane (CHâ‚„) and nitrous oxide (N2O) from biological processes, are particularly significant as reliance on renewable energy reduces Scope 2 emissions. N2O is especially concerning, with a global warming potential (GWP) 265 times that of CO2 over 100 years, contributing up to 80% of a WRRF's carbon footprint. It is also the primary ozone-depleting substance of the 21st century [1]. Mitigating N2O emissions from WRRFs is challenging due to their high temporal and spatial variability, which complicates capturing actual emissions through short campaigns or simple methods. Factors like campaign duration, sampling frequency, and measurement techniques greatly influence results, limiting the effectiveness of monitoring efforts [2]. Additionally, N2O emissions depend heavily on process type, operational strategies, plant configuration, and environmental conditions, making standardized mitigation protocols difficult. Linking emissions to operational modes, control strategies, and environmental factors is crucial for effective mitigation [3]. This work presents a full-scale case study of N2O emissions as part of a project examining Canadian facilities with diverse treatment goals, operations, and designs. It underscores the significant impact of operational decisions on N2O production and emissions, challenging the assumption that plant design and process type are the primary determinants. By combining quantification, mathematical modeling, microbial analysis, and data analytics, this study demonstrates how a multi-faceted approach can overcome the limitations of monitoring campaigns and elucidate the complex relationships governing N2O dynamics. Methodology N2O emissions were monitored continuously using liquid sensors (Unisense A/S Denmark), and process data were collected from the biological treatment reactor in a local WRRF located in Canada, over 6 months period. During the campaign, different flow modes were testing including step-feed, semi-plug flow, and plug flow. Key parameters were measured including total ammonia nitrogen (NHx), nitrite (NO2-), nitrate (NO3-), soluble and total chemical oxygen demand (sCOD, TCOD), total nitrogen (TN), total phosphorus (TP), total suspended solids (TSS), volatile suspended solids (VSS), dissolved oxygen (DO), pH, and temperature. A mathematical model representing two-AOB pathways and HB pathways was calibrated using effluent data for NHâ‚“, NO2â», NOâ‚ƒâ», and N2O sensor data. Findings This study examines how operational changes in a biological wastewater treatment reactor influence N2O emissions. The monitoring campaign tracked dynamic shifts across three operational configurations: step-feed, semi-plug flow, and plug flow. Figure 1 shows that plug flow mode resulted in the highest N2O emissions (average: 0.120 mg N-N2O/L), followed by semi-plug flow (0.0115 mg N-N2O/L) and step-feed mode (0.0095 mg N-N2O/L). While nitrogen removal during step-feed was minimal, transitioning to semi-plug flow (fewer feeding points) increased nitrification rates, elevating N2O concentrations. Ammonia removal efficiency rose from 22% (step-feed) to 60% (semi-plug flow) and 85% (plug flow), but this alone could not explain the observed emission patterns. Notably, N2O concentrations dropped significantly in late July despite unchanged operational modes, possibly due to ammonia-oxidizing bacteria (AOB) acclimation, reducing intermediates like NO2â» and NH2OH. Ongoing microbial analysis aims to confirm this. A mathematical model was calibrated using effluent nitrogen and N2O concentration data from step-feed and semi-plug flow operations. Figure 3 compares observed and simulated concentrations of nitrogen species (NHâ‚“, NO2â», NOâ‚ƒâ»), with the model qualitatively capturing nitrogen dynamics. Key parameters influencing the model were AOB kinetics (e.g., maximum specific growth rate and oxygen affinity constant) and NOB oxygen affinity, highlighting NO2â»'s role in N2O production via the nitrifier denitrification pathway. The model revealed emission hotspots across reactor segments (Pass 1/1 to Pass 4/3), confirming increased emissions following the transition to semi-plug flow (Figure 4). The study underscores limitations of sensor-based N2O monitoring without strategic sensor placement. Figure 5 shows aggregated N2O concentrations from model simulations along reactor segments, revealing discrepancies between actual sensor readings and emission hotspots. For instance, during the final 10 days of operation, sensors captured less than 20% of actual emissions, emphasizing the importance of mathematical modeling for effective monitoring and accurate quantification. In conclusion, this study highlights the significant influence of operational patterns on N2O emissions and the necessity of integrating mathematical models into monitoring and mitigation strategies. Future research will incorporate advanced analytics and AI-based methods, extending the work to multiple wastewater treatment facilities in Canada.

This paper was presented at WEFTEC 2025, held September 27-October 1, 2025 in Chicago, Illinois.

Presentation time

16:30:00

16:45:00

Session time

15:30:00

17:00:00

SessionDecarbonizing Water: Mathematical Modeling and Digital Twins to Reduce N2O Emissions from WWTP

Session locationMcCormick Place, Chicago, Illinois, USA

TopicResearch

Author(s)

Khalil, Mostafa, AlSaleh, Marwan, AlSayed, Ahmed, Elsayed, Ahmed, Zaghloul, Mohamed, Al-Omari, Ahmed, Kakar, Farokh Laqa, Bell, Katherine, Cavanaugh, Shannon, Porro, Jose, Elbeshbishy, Elsayed

Author(s)M. Khalil1, M. AlSaleh2, A. AlSayed3, A. Elsayed2, M. Zaghloul, A. Al-Omari4, F. Kakar4, K. Bell5, S. Cavanaugh4, J. Porro, E. Elbeshbishy2

Author affiliation(s)Stantec, Inc.1, Toronto Metropolitan University2, Northwestern University3, Brown and Caldwell4, Hazen and Sawyer5, Cobalt Water Global6

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Sep 2025

DOI10.2175/193864718825160129

Volume / Issue

Content sourceWEFTEC

Word count13