Lee, Chengpeng

Chengpeng Lee is a speaker at WEFTEC 2026.

Titles from this speaker

Description: Addressing Controllability Challenges in Aeration Systems: Insights from Blue...

Addressing Controllability Challenges in Aeration Systems: Insights from Blue Plains

Abstract

Introduction
Advanced aeration control strategies, including DO control, ABAC, and AvN control, are critical for optimizing biological nutrient removal systems1. Despite their potential, confidence in these systems is often lost due to limitations and complexity2. Nearly 50% of wastewater facilities still operate in manual mode, bypassing basic PID control loops3. This highlights the need for online evaluation tools to identify issues related to tuning, probe maintenance, or control logic performance. This study evaluates DO control, ABAC with black-box and mechanistic feedforward approaches, and introduces Nitrate-Based Aeration Control (NBAC), aiming to establish a framework for real-time assessment and adjustment of aeration controls.

Methodology
Blue Plains operates 12 nitrification reactors with a daily flow of 300 MGD. Odd-side reactors use DO control, while Even-side reactors use ABAC (Fig.1). ABAC and DO control were evaluated over 267 days and 153 days, respectively. Weekly sampling assessed probe reliability and maintenance demands. Control performance was evaluated using setpoint accuracy, air valve limitations, and laboratory corrections. Setpoint accuracy measured the percentage of time setpoints were met within error thresholds. Physical limitations were identified by valve positions outside controllable ranges, and probe offsets were analyzed through laboratory correction. An integrated scoring metric reflected the percentage of time each criterion was met.

Results and Discussion
1.Overall Performance of the Control Systems
ABAC, operating with a setpoint of 2.0 mgN/L for NH4, demonstrated better performance compared to DO control, maintaining error margins within 30% thresholds (Fig.2). These margins were calculated as probe readings within 30% of the setpoint, detailed in Fig.2. In contrast, DO control systems, with setpoints ranging from 1.5 to 2.5 mgO2</Sub>/L, exhibited variability across zones, except for Zone 2B (Fig.2). Although NH4 concentrations remained below 0.5 mgN/L following DO control, the observed inconsistency suggests reliance on airflow and air valve control may not achieve precise control under dynamic conditions. Notably, Zone 2B displayed enhanced controllability following air valve maintenance in mid-Sep., highlighting the role of equipment upkeep in ensuring system performance.

2.Control System Performance Within Operational Limits
Physical limitations play a crucial role in achieving system performance. Positions below the controllable range are uncontrollable due to insufficient airflow, while those above the inflection point yield diminishing returns, reducing control precision. The DO control system demonstrated a lower percentage of time within the controllable range compared to ABAC, with Zones 1A and 2A exceeding the upper limits 77.8% and 63.2% of the time, indicating a reliance on fully open valves to meet airflow demands (Table1). In contrast, Zone 2B in the DO control system achieved setpoints more effectively when valve positions remained within the controllable range, as evidenced by the green data points in Fig.2D. The ABAC system outperformed DO control overall (Table1); however, instances where valve positions exceeded the upper limit (Fig.2A) hindered ABAC's ability to meet NH4 setpoints.

3.Control performance Considering Lab Correction
The reliability and maintenance demands of NH4 probes are critical for achieving setpoint accuracy in ABAC. Over the 267-day, ABAC required significant maintenance, including 14 matrix adjustments and electrode replacements (Fig.3A). While ABAC generally outperformed DO control in meeting setpoints, lab corrections revealed fluctuations due to probe inaccuracies (Fig.2A&3B). Scoring metrics showed 74% accuracy within a 10% error margin, rising to 82% within controllable airflow limits but falling to 29% with probe offsets (Fig.4). In contrast, DO control showed lower setpoint achievement due to physical limitations (Fig.4). Despite these constraints, DO probes demonstrated higher accuracy compared to NH4probes, with potential accuracy improvements from 24% to 72% within a 10% margin if physical limitations are resolved. Integrated scoring tools highlighted discrepancies between hourly and daily ABAC data, mainly driven by secondary effluent flow rates and air valve control (Fig.4&5). Fig. 5 illustrates Black Box ABAC control performance at Blue Plains, where valve positions were well-controlled between 0 to 11 AM, adjusting to NH4 loading. However, during high flows, the system often exceeded its capacity to open valves further, resulting in compromised setpoints. Comparisons between hourly and daily results in ABAC indicate that hourly real-time data reveal the need for improvements to handle flow rate dynamics (Fig.4A&B).

To address these challenges, novel aeration controls have been proposed. Mechanistic Feedforward ABAC integrates predictive modeling with feedback controls to anticipate system behaviors and adjust aeration proactively, reducing reliance on error-prone probe feedback5. Additionally, due to the unreliability of NH4 probes, a novel NBAC has been developed, incorporating a high-accuracy Wet Chemical Analyzer for NH4 feedforward signals and a UV NO3probe for feedback.

Conclusion
This study evaluates controllability to identify key constraints in aeration control and proposes strategies and solutions. The full paper will present proof-of-principle NBAC.

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

Presentation time

09:30:00

09:45:00

Session time

08:30:00

10:00:00

SessionOvercoming Challenges to Implement Advanced Aeration

Session locationMcCormick Place, Chicago, Illinois, USA

TopicLiquid Stream Treatment - Nutrient Removal and Recovery

Author(s)

Lee, Chengpeng, Hatcher, Jacob, Ngo, Khoa Nam, Fofana, Rahil, Wells, George, De Clippeleir, Haydee

Author(s)C. Lee1, J. Hatcher2, K. Ngo3, R. Fofana3, G. Wells1, H. De Clippeleir3

Author affiliation(s)Northwestern Univeristy1, The George Washington University2, DC Water and Sewer Authority3

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Sep 2025

DOI10.2175/193864718825160023

Volume / Issue

Content sourceWEFTEC

Word count11

An Evaluation of Dual External Carbon Source Strategies for the Full Denitrification Process

Abstract

Introduction Achieving low TIN levels in wastewater effluent often necessitates the addition of an electron donor (Fu et al., 2022). The selection of an appropriate carbon source is a critical decision, influenced by considerations of cost, availability, and effectiveness in terms of biomass yield (Peng et al., 2007). In the United States, methanol is a preferred choice due to its economic viability and low yield (WRF, 2019). However, recent literature suggests fermentate as a potential alternative (Ladipo-Obasa et al., 2022). One limitation of fermentate is its contribution of ammonium to the effluent. This study proposes an intermediate strategy wherein a portion of methanol is replaced with fermentate, aimed at reducing operational costs while easing the transition towards PdNA methodologies. The primary goal is to elucidate the denitrification stoichiometries under a dual carbon source, emphasising is placed on formulating operational strategies conducive to achieving desired effluent standards, along with an evaluation of reductions in methanol consumption. Methodologies A 360 L mainstream pilot system was operated for three phases. During the initial phase, methanol was utilized as the sole carbon source, with its dosing governed by a feedforward control. In the next phase, fermentate, derived from batch fermentation of primary sludge from full-scale primary clarifiers. The third phase introduced a dual carbon source strategy to facilitate a FdN process. Fermentate was dosed continuously, while methanol, serving as an additional carbon source, compensated for the remaining chemical oxygen demand necessary. Results and Discussion Phase 1: Baseline condition with methanol as external carbon source Over 153 days in this pilot operation the effluent targets were effectively met (1.91 mg N/L,Table 1). A stoichiometry factor of 4.9 g sCOD added/g NO3-N removed and a yield coefficient of 0.42 g COD/g COD were observed (Fig.1a,c); these are similar to expected literature values for methanol-driven denitrification (Mokhayeri et al., 2009). Phase 2: Nitrate removal with available primary sludge fermentate Fermentate dosed was of high quality and reached a yield of 0.21 g sCOD/g VSS (Table 2), which was on the higher end of previously reported yields (Ali et al., 2021). Throughout the operation of 125 days, a nitrate removal of 2.6 mg N/L was achieved (Table 1). The stoichiometry and yield coefficients of fermentate, recorded at 5.4 g sCOD added/g NO3-N removed and 0.47 g COD/ g COD, respectively (Fig.1a,c). Phase 3: Denitrification with dual methanol and fermentate addition a.Overall performance and impact on overall methanol needs Over a 137-day period utilizing dual external carbon sources, a feedforward control strategy was effective at achieving the average effluent TIN at only 1.91 mgN/L. (Table1). Despite significant variations in fermentate quality, particularly in terms of soluble COD due to primary sludge solids concentration variability the strategic incorporation of methanol to address these variations ensured the attainment of favorable TIN levels in the effluent (Table 1&2). It was observed that employing both carbon sources concurrently did not modify their individual behaviour. This was evident by the predicted nitrate removal using the stoichiometries from phase 1 and 2 being similar to the observed nitrate removal (Fig.1a). Even though the predicted nitrate removal showed a slightly improved efficiency of carbon use in phase 3, this was not statistically significant, as shown in (Fig.1b). The amount of external MeOH needed in this phase was 3.2+/-1.4 g sCOD added/gNO3-N removed or showed a MeOH saving of 35% compared to phase 1. b.Microbial selection and functionality under dual substrate addition Even though overall N removal was as expected under dual substrate dosing, a change in kinetic behavior was observed (Fig.2). Nitrite accumulation was observed in denitrification activity tests, irrespective of whether fermentate or methanol was the carbon source. Nitrite accumulation was never observed when doing activity tests with full-scale MeOH adapted biomass or during phase 1 (Fig.2a,d,e). The nitrite accumulation behaviour was also confirmed in the reactor by profiling tests (Fig. 3). Notably, the PdN efficiency was higher with fermentate at 76% and methanol at 52 % (Fig. 2b,c), mirroring findings from the pilot profiling experiment, which reported a PdN efficiency of 47%, as shown in (Fig.3). This result was surprising as methylotrophs do not tend to accumulate nitrite easily. The extended 262-day period of employing fermentate as a carbon source in the reactor potentially enhanced the diversity of nirS type denitrifiers, consequently altering the community-level dynamics in response to different electron donors (Hallin et al., 2006). Nitrate levels needed to be pushed below 1.97 mg N/L to avoid nitrite coming out of the denitrification zone. Conclusions This study at the Blue Plains AWTP underscores the efficacy of dual carbon sources-methanol and fermentate-in enhancing TIN removal in wastewater treatment. Employing a sequential methodology, the research highlighted the stoichiometric and operational efficiency of combining these carbon sources. These findings provide a strategic pathway for the implementation PdNA processes, signifying a substantial advancement in cost-effective and efficient nitrogen removal strategies.

This study assesses the effectiveness of using methanol and fermentate as dual carbon sources for Total Inorganic Nitrogen (TIN) removal in wastewater treatment. Findings show that combining these sources enhances nitrate removal efficiency and reduces methanol consumption, facilitating the transition towards Partial Denitrification- Anammox (PdNA) methodologies.

SpeakerLee, Chengpeng

Presentation time

15:30:00

16:00:00

Session time

15:30:00

17:00:00

SessionEnhancing Nitrogen Removal: Insights Into Carbon Sources and Mechanisms

Session number420

Session locationRoom 340

TopicAdvanced Level, Facility Operations and Maintenance, Municipal Wastewater Treatment Design, Nutrients, Research and Innovation

Author(s)

Lee, Chengpeng, Ngo, Nam, Islam, M.A. Sadikul, Hatcher, Jacob, Riffat, Rumana, Azam, Hossain, Wells, George, De Clippeleir, Haydee

Author(s)C. Lee1, N. Ngo2, M. Islam3, J. Hatcher4, R. Riffat5, H.M. Azam6, G. Wells7, H. De Clippeleir8

Author affiliation(s)1Northwestern University, VA, 2DC Water, VA, 3University of the District of Columbia, 4The George Washington University, MD, 5George Washington University, VA, 6University of the District of Columbia, DC, 7, IL, 8DC Water & Sewer Authority, VA

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Oct 2024

DOI10.2175/193864718825159619

Volume / Issue

Content sourceWEFTEC

Word count14

Description: Developing Approaches for Achieving Biological Phosphorous Removal and Improved...

Developing Approaches for Achieving Biological Phosphorous Removal and Improved Settleability in High-rate Activated Sludge Systems

Abstract

This study focuses on determining the minimum SRT maintaining significant bio-P activity, quantifying phosphorus removal methods, and evaluating sludge settling. This paper offers practical guidance on the implementation of HRAS systems for determining the actual bio-P phosphate removal through parallel contact stabilization assimilation reactors.

This work demonstrates that bio-P activity washed out of aerobic SRT of 1.2-1.8 day. Overall, about 56% of P removal was achieved through bio-P while the rest was achieved through assimilation. This study showed the need for developing strategies for SRT uncoupling to selectively retain PAOs in high-rate system to potentially achieve P removal and improved overall capacity of high-rate system through improving settling.

SpeakerNgo, Nam

Presentation time

11:30:00

12:00:00

Session time

10:30:00

12:00:00

SessionHealthy As A Horse? Assessing Bio-P Stability

Session locationRoom S403a - Level 4

TopicFacility Operations and Maintenance, Intermediate Level, Municipal Wastewater Treatment Design, Nutrients

Author(s)

Ngo, Khoa Nam

Author(s)K. Ngo 1; C. Lee 2 ; H. Truong 3; E. Kin 2; S. Fuentes 4; C, Chen 3 ; G. Wells 5; H. De Clippeleir 6; C. Lee 2;

Author affiliation(s)District of Columbia Water and Sewer Authority 1; District of Columbia Water and Sewer Authority, Northwestern University 2 ; District of Columbia Water and Sewer Authority, Northwestern University 3; District of Columbia Water and Sewer Authority, Northwestern University 2; District of Columbia Water and Sewer Authority 4; District of Columbia Water and Sewer Authority 3 ; District of Columbia Water and Sewer Authority 5; 6; 2;

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Oct 2023

DOI10.2175/193864718825159176

Volume / Issue

Content sourceWEFTEC

Word count16

Evaluation of Blue Plains PdNA full-scale demonstration pilot: Key Lessons and Future Directions

Abstract

[b]Abstract[/b] A full-scale post-anoxic PdNA demonstration was implemented at Blue Plains to evaluate the interaction between high-density IFAS media, screen hydraulics, and mixer operation in a 30-ft deep reactor. Rapid head loss developed across both influent and effluent screens due to debris accumulation and insufficient media scouring, leading to hydraulic and mixing challenges. The findings highlight the need for screen designs that increase interaction between screen and media, continuous or adaptive mixing strategies, and operational strategies to ensure stable operation under high flow conditions. [b]Introduction[/b] PdNA has progressed from concept to practice, with full-scale implementations showing reliable performance. Remaining challenges are largely design-driven, including hydraulic management, screen capacity, and media handling in deep reactors. At Blue Plains, the design evaluation focused on selecting media suitable for a 30-ft deep reactor and compatible with existing Invent® mixers. Media size governs allowable screen openings, making available screen area the key factor controlling flux and head loss. This paper presents the first use of heavy IFAS media in a deep post-anoxic application and outlines the associated hydraulic, screening, and mixing challenges, and design recommendations. [b]Materials and Methods[/b] A five-stage, 30-ft deep reactor (≈20 MGD equivalent) was configured with Stage 4 as the IFAS PdNA zone (Figures 1 & 2). MicroC was supplied through feedforward/feedback control. Hyperboloid mixers with Cyberprop elements were installed to maintain media suspension; mixers were shut off during wet-weather events. Influent expanded-metal screens and effluent wedge-wire screens retained media, with periodic air sparging for cleaning. Selection of a high-density media (SG 1.04–1.06) was made on the expectation that the increased specific gravity would allow the media to settle at high flows, reducing the potential for media stacking on screens while maintaining sufficient scouring during normal operation. [b]Results and Discussion[/b] [i]Influent Screen Performance[/i] A rapid head loss developed across the influent screen within the first day, creating a ~0.26 m water level difference between stages 3B & 4A (Figure 3) and elevating upstream levels relative to the adjacent non-PdNA reactor. The upstream expanded-metal screen accumulated fibrous debris (Figure 4), reducing effective open area, while limited media contact and lack of active cleaning prevented effective scouring. These factors restricted flow into the PdNA zone. Potential mitigation includes hydraulic controls (e.g., submersible weir), replacing expanded metal with a perforated plate screen on the IFAS side to promote media scouring, and implementing a defined cleaning and maintenance protocol. [i]Effluent Screen Performance[/i] Initially stable, even during short-wet weather mixer shutdowns, head loss over the effluent screens increased after several days (Figures 3&5), indicating onset of effluent screen fouling. Following heavy rainfall and extended mixer shutdowns, hydraulic capacity could not be recovered despite continuous air sparging. Media lodged on both effluent screens, confirming insufficient scouring velocities and contributing to MLSS concentrations exceeding 3,500 mg/L (Figure 6). Recommended improvements include increasing hydraulic openings between stages 4B & 5A, removing or perforating the long-wall shelf to create an open channel, repositioning the short-wall screen to improve approach velocities, enhancing air sparging with higher-intensity and large-bubble systems, and implementing level-based control strategies to actively manage head loss, mixing, and screen cleaning. [i]Mixer Performance[/i] As part of the wet-weather strategy, mixers were shut off when influent flow exceeded 330 MGD. While short shutdowns during early rain events allowed successful restart, extended shutdowns later caused mixers to fail to restart due to settled dense media, requiring diffuser air to resuspend the media or full reactor shutdown. These events revealed a critical interaction between media density, screen fouling, and mixer operation. Allowing media to settle eliminated continuous scouring, accelerated screen fouling, increased head loss and MLSS, and hindered mixer restart. The results indicate that fully shutting off mixers during wet weather is ineffective; continuous operation with adaptive speed control is needed to maintain media suspension, screen cleaning, and hydraulic stability, although higher mixer power may be required. [b]Conclusion[/b] This PdNA demonstration showed the critical interaction between media properties, screen hydraulics, and mixer operation in deep post-anoxic IFAS systems. Rapid head loss on both influent and effluent screens was driven by debris accumulation and insufficient media scouring, causing hydraulic constraints, elevated MLSS, and mixing challenges. While high-density media were expected to reduce the potential for media stacking at high flows, the results confirmed that continuous media scouring is the dominant mechanism for maintaining screen cleanliness and hydraulic capacity. Wet-weather mixer shutdowns eliminated scouring, accelerated fouling, and increased head loss, underscoring the need for screen designs that enhance media interaction, continuous mixing, and adaptive control strategies for stable high-flow operation.

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

Presentation time

15:30:00

16:00:00

Session time

15:30:00

17:00:00

SessionMainstream PdNA – Full-Scale Experience and Optimizations

Session locationErnest N. Morial Convention Center

TopicFacility Operations and Maintenance, Municipal Wastewater Treatment Design, Nutrients

Author(s)

Fofana, Rahil, Lee, Chengpeng, Pokharel, Nishedh, Fang, Jun, Martinelli, Shawna, Passarelli, Nicholas, Suzuki, Ryu, Wells, George, Azam, Hossain, Ngo, Khoa Nam, De Clippeleir, Haydee

Author(s)R. Fofana1, C. Lee1, N. Pokharel2, J. Fang1, S. Martinelli1, N. Passarelli1, R. Suzuki1, G. Wells3, H. Azam2, K. Ngo1, H. De Clippeleir1

Author affiliation(s)DC Water, 1DC Water & Sewer Authority, 1University of the District of Columbia, 2DC Water, 1DC Water & Sewer Authority, 1DC Water & Sewer Authority, 1DC Water & Sewer Authority, 1Northwestern University, 3University of the District of Columbia, 2DC Water, 1DC Water & Sewer Authority, 1

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Sep 2026

DOI10.2175/193864718825160320

Volume / Issue

Content sourceWEFTEC

Word count14

Feedforward-feedback Mechanistic Ammonium-based Aeration Control optimization at Blue Plains advanced wastewater treatment plant

Abstract

1.Introduction Ammonia-Based Aeration Control (ABAC) is widely used to reduce aeration energy demand in biological nutrient removal processes1,2. Conventional ABAC systems rely primarily on downstream ammonium feedback to trim dissolved oxygen (DO) setpoints, which results in delayed responses due to long hydraulic retention times and limits performance under dynamic loading conditions3. To address these challenges, black-box feedforward–feedback (FF–FB) ABAC systems have been implemented at Blue Plains since 2015, incorporating influent flow information to improve response to diurnal variability. However, these empirical approaches remain sensitive to wet-weather events and do not explicitly represent nitrification kinetics or the nonlinear relationship between DO and microbial activity4,5. To overcome these limitations, a mechanistic FF–FB ABAC strategy was developed based on linearization of the Monod DO term through a nitrification factor (N.F = DO/(K_DO + DO))6. This approach enables a more proportional and robust linkage between control actions and biological nitrification capacity. This study compares the two ABAC strategies and documents full-scale implementation, tuning, and performance outcomes. 2.Methodology This study evaluated two ABAC implementations in a full-scale nitrification system from April 1, 2024, to November 1, 2025. Black-box ABAC was operated from April 2024 to June 2025, followed by mechanistic ABAC from June to November 2025. System performance was assessed using Average Absolute Error (AAE), Average Percent Absolute Error, and the percentage of time within allowable thresholds for dissolved oxygen, airflow, and ammonium concentrations7. 2.1 Black Box feedforward-feedback ABAC: data-driven system that modulates the DO setpoint to achieve the target ammonia concentration in a feedforward action. The feedforward component utilizes a model to predict the required DO setpoint based on influent flow rates and empirical DO, flow – NH4 relationships. A nonlinear feedback loop adjusts the DO setpoint based on the error between the online ammonium concentration and the desired setpoint, Fig1A. 2.2 Mechanistic feedforward-feedback ABAC: model-based control strategy designed to linearize the relationship between the output and the nitrification factor (N.F), which represents the DO Monod terms within nitrification kinetics: DO/ (KDO + DO)6. The feedforward model calculates the required N.F using influent ammonia loads, nitrification kinetics, and an estimated mass of active nitrifiers. The feedback action corrects this N.F. fraction to meet NH4 setpoint and then the N.F, fraction is converted to DO setpoint to further control airflow rates and valve openings, Fig1B. 3.Results 3.1 Process optimization of the new ABAC Air-Valve Response Optimization: Prior to optimization, air-valve response times exhibited a 15–20 min delay between airflow setpoint changes and valve actuation, Fig2A. This mechanical lag prevented timely achievement of DO setpoints during rapid load transitions, resulting in ammonium deviations and oscillatory control behavior. By removing deadbands and delays in the airflow control loops, response times were reduced to 3–5 min, Fig2B, enabling rapid tracking of airflow setpoints, Fig2C and substantially improving DO controllability. Optimization of N.F Bounds: Initial mechanistic control constrained the N.F to a narrow range 0.55–0.88, corresponding to DO values of 0.48–2.93 mg O₂/L. Under low-load conditions, this limited flexibility resulted in excess aeration and suppressed ammonium concentrations. Reducing the lower N.F bound to 0.30 expanded the controllable DO range and mitigated over-aeration, Fig3. This adjustment reduced saturation at the upper N.F limit, enabled smoother transitions across diurnal loading conditions, and improved overall control stability. Integration of SRT adjustments: Early mechanistic runs revealed discrepancies between modeled and actual nitrifier inventories, leading to under-aeration during high-load morning periods. Process data indicated overestimation of nitrifier mass, prompting an update of the assumed aerobic SRT from 15 to 11 days, Fig3. This change improved alignment between modeled and real nitrification capacity, resulting in more accurate feedforward DO predictions and fewer ammonium excursions. Feedback Tuning: Initial PID feedback tuning resulted in conservative responses to ammonium deviations, limiting the benefits of the mechanistic feedforward layer, Fig4A. To enhance responsiveness, the lambda parameter was reduced from 3.0 to 2.5, proportional gain increased (0.79 to 1.06), and integral time decreased (2314 to 1543). Post-tuning performance showed faster correction of NH₄ deviations without inducing instability or collapse of the N.F term during load spikes, Fig4B. 3.2 Performance comparsions Table 1 shows that mechanistic ABAC outperformed the black-box approach, achieving lower AAE and maintaining ammonium within target limits for a greater fraction of time (84%). These improvements are attributed to enhanced feedforward predictions that explicitly incorporate ammonia loading and estimated nitrifier mass, allowing the controller to better anticipate oxygen demand under operating conditions. Conclusion: Transitioning from black-box to mechanistic ABAC improved ammonia control stability by explicitly incorporating nitrification kinetics, while indicating the need for further refinement.

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

Presentation time

09:00:00

09:30:00

Session time

8:30:00

10:00:00

SessionAdvanced Aeration Control for Nitrogen Removal

Session locationErnest N. Morial Convention Center

TopicFacility Operations and Maintenance

Author(s)

Lee, Chengpeng, Ngo, Khoa Nam, Fofana, Rahil, Wells, George, De Clippeleir, Haydee

Author(s)C. Lee1, K. Ngo1, R. Fofana1, G. Wells2, H. De Clippeleir1

Author affiliation(s)DC Water & Sewer Authority, 1DC Water, 1DC Water, 1Northwestern University, 2DC Water & Sewer Authority, 1

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Sep 2026

DOI10.2175/193864718825160322

Volume / Issue

Content sourceWEFTEC

Word count14

Full-Scale Optimization of Mechanistic Feedforward-Feedback Ammonium-Based Aeration Control at Blue Plains

Abstract

1. Introduction Ammonia-Based Aeration Control (ABAC) has become an increasingly important strategy for optimizing aeration energy use and stabilizing nitrification performance in biological nutrient removal processes (Medinilla et al., 2020; Uprety et al., 2015). While conventional ABAC systems typically utilize standard feedback (FB) loops, relying solely on ammonium sensor readings to trim the DO setpoint has shown limited control ability (Rieger et al., 2014). Because sensors are often placed downstream in zones with long hydraulic retention times, the system exhibits slow and delayed responses to rapid changes in daily flow. Therefore, at Blue Plains, black-box feedforward-feedback (FF-FB) ABAC systems were implemented since 2015 to provide a mechanism to better deal with diurnal flows and small rain events. However, these rely heavily on empirical correlations between influent flow, target ammonia, and dissolved oxygen (DO), making them still sensitive to diurnal load variation and limited under severe wet-weather events. These systems commonly use nonlinear feedback loops based on ammonium sensor readings to trim the DO setpoint; however, they do not explicitly represent nitrification kinetics or account for the non-linear relationship between DO and biological growth rates (Newhart et al., 2020; Regmi et al., 2015). Consequently, they struggle to maintain stability across broad operating conditions These limitations were observed at the study facility (Lee et al., 2025). To address these limitations, a mechanistic feedforward-feedback ABAC strategy was developed and implemented based on the work of (Gagnon et al., 2023). Unlike the black-box approach, the mechanistic controller explicitly incorporates Monod DO kinetics by linearizing the nitrification factor (N.F = DO / (K_DO + DO)), enabling a more proportional relationship between controller output and expected nitrification activity (figure 1B). The mechanistic FF-FB ABAC aims to improve robustness, enhance DO-airflow control interactions, and maintain stable ammonium setpoints under variable influent loads. This study evaluates the fundamental differences between the two ABAC approaches and documents the full-scale operational adjustments, tuning, and performance outcomes. 2. Material and methods This study evaluated two ABAC implementations at a full-scale nitrification system between 2024-04-01 and 2025-11-01. The operational period from 2024-04-01 to 2025-06-01 utilized the black-box ABAC, while 2025-06-01 to 2025-11-01 implemented the mechanistic ABAC. Performance metrics included Average Absolute Error (AAE), Average Percent Absolute Error (APAE), and Percentage of Time Within Allowed Threshold (Data in Control) for DO, airflow, and ammonium concentrations (Lee, et al, 2025). 2.1 Black Box feedforward-feedback ABAC: data-driven system that modulates the DO setpoint to achieve the target ammonia concentration in a feedforward action. The feedforward component utilizes a model to predict the required DO setpoint based on influent flow rates and empirical DO, flow - NH4 relationships. A nonlinear feedback loop adjusts the DO setpoint based on the error between the online ammonium concentration and the desired setpoint (Fig, 1A). 2.2 Mechanistic feedforward-feedback ABAC: model-based control strategy designed to linearize the relationship between the output and the nitrification factor (N.F), which represents the DO Monod terms within nitrification kinetics: DO/ (KDO + DO) (Gagnon et al., 2023). The feedforward model calculates the required N.F using influent ammonia loads, nitrification kinetics, and an estimated mass of active nitrifiers. The feedback action corrects this N.F. fraction to meet NH4 setpoint and then the N.F, fraction is converted to DO setpoint to further control airflow rates and valve openings. (Fig, 1B). The linearization of the first PID loop is hypothesized to help with more robust performance in a wider range of operating conditions. 3. Results and discussion: 3.1 Process Optimization of the New ABAC Air-Valve Response Optimization: Prior to optimization, the air-valve response exhibited significant latency, characterized by a 15-20 minute delay between an airflow setpoint change and the corresponding valve actuation (Figure 2A). This mechanical lag decoupled the controller from the process during periods of rapid load variation, preventing the system from achieving DO setpoints in a timely manner. Consequently, this delay induced ammonium deviations and unstable, oscillatory control behavior. To mitigate this, deadbands and signal delays within the airflow control loops were removed. This intervention reduced the response time to approximately 3-5 minutes (Figure 2B). The reduction in actuator latency facilitated near-instantaneous tracking of the airflow setpoint (Figure 2C), improving the physical system's ability to respond to control logic commands. Optimization of Nitrification Factor (N.F) Bounds: The initial mechanistic implementation constrained the Nitrification Factor (N.F) within a relatively narrow range (0.55 < N.F < 0.88), which corresponded to a calculated DO setpoint range of 0.48-2.93 mg O2/L. While sufficient for average loading, this constraint proved restrictive under low-load conditions. Specifically, the lower bound of 0.55 prevented the controller from reducing aeration sufficiently, resulting in over-aeration. Figure 3 illustrates the performance improvements achieved after extending the lower N.F bound to 0.30. This expansion increased the controller's turndown ratio, allowing it to allocate appropriate airflow without over-aerating during periods of low ammonia loading. Furthermore, this adjustment reduced the frequency at which the N.F term saturated at its upper limit. The expanded N.F range enabled smoother transitions between low and high aeration demands. Integration of SRT Adjustments: During the early phases of mechanistic control operation, the nitrifier mass estimates utilized by the feedforward model were inconsistent with the actual biological conditions of the system. Operational data suggested that the model was overestimating the nitrifier inventory; based on kinetic principles, an overestimated biomass results in a lower calculated oxygen demand per unit of biomass, leading to systematic under-aeration. In response, the Solids Retention Time (SRT) parameter in the control model was reduced from 15 to 11 days (Figure 3). This calibration improved the alignment between the modeled nitrification capacity and the actual system performance. By correcting the biomass inventory estimate, the feedforward layer provided more accurate aeration predictions, reducing deviations in ammonium control. PID Feedback Tuning to Improve Responsiveness: Prior to tuning, the mechanistic PID feedback loop exhibited a conservative response to deviations in NH4-N concentration. This sluggishness caused delayed corrective actions, which limited the mechanistic feedforward layer (Figure 4A). To address this, the lambda parameter, which dictates the closed-loop time constant, decreased from 3.0 to 2.5. In addition, the feedback gain was increased (from 0.79 to 1.06), and the integral term was reduced (from 2314 to 1543) to minimize windup and settling time. As shown in Figure 4B, the tuned controller responded more rapidly to ammonium setpoint deviations. These adjustments reduced undershooting and prevented the N.F term from collapsing to zero during sudden load increases, resulting in faster error correction and tighter overall closed-loop control. 3.2 Performance Comparisons Between Black-Box and Mechanistic ABAC The overall performance differences between the black-box and mechanistic ABAC systems are summarized in Table 1. Focusing on ammonium control loop, the mechanistic ABAC demonstrated lower AAE and Percentage of time within 0.6 mg N/L threshold, indicating improved setpoint tracking and reduced variability. The mechanistic controller kept the system within the acceptable control band for a greater percentage of time (84 ± 5.5%), demonstrating more stable operation under the same operational conditions. The improvements can be attributed to the more robust feedforward predictions under the mechanistic framework. Unlike the black-box controller, which based DO setpoint calculations solely on influent flow, the mechanistic controller integrates ammonia load and estimated nitrifier mass, thereby better anticipating the actual oxygen demand. Conclusion: Transitioning from black-box to mechanistic FF-FB ABAC improved ammonia control stability by explicitly incorporating nitrification kinetics through a linearized nitrification factor. While performance increased, further refinement is needed to optimize feedforward predictions and support integration of nitrate-based aeration control.

This paper was presented at the WEF Residuals, Biosolids, and Treatment Technology Conference in Kansas City, MO, May 11-14, 2026.

Presentation time

13:30:00

14:00:00

Session time

13:30:00

15:00:00

SessionControl What You Can At Full Scale

Session locationKansas City Convention Center

TopicInnovative and Advanced Treatment for Achieving Limit-of-Technology Performance

Author(s)

Lee, Chengpeng, Ngo, Khoa Nam, Fofana, Rahil, Wells, George, De Clippeleir, Haydee

Author(s)C. Lee1, K. Ngo1, R. Fofana1, G. Wells2, H. De Clippeleir1

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date May 2026

DOI10.2175/193864718825160230

Volume / Issue

Content sourceResiduals, Biosolids and Treatment Technology Conference

Word count12

Description: Optimizing Partial-Denitrification/Anammox (PdNA) Startup in IFAS system with Low...

Optimizing Partial-Denitrification/Anammox (PdNA) Startup in IFAS system with Low TIN Discharge Targets

Abstract

Introduction
To advance PdNA implementation, it is important to better understand PdNA startup strategies and timelines. Previous PdNA startups showed detection of anammox activity within three months for both methanol and glycerol as carbon sources, and MBBR, filters and IFAS configurations (Justin et al., 2022; Bachmann et al., 2024). At Blue Plains, PdNA integration is intended within the nitrification reactors, leaving a full denitrification polishing zone with MeOH downstream of the PdNA IFAS zone. This also means that the mixed liquor will maintain a full denitrification methylotroph population while PdN is targeted within the PdN zone. Previous work showed reduced PdN efficiencies under those conditions (Ladipo-Obasa et al., 2022) compared to only dosing MeOH with PdNA zone (Bachmann et al., 2024; Fofana et al., 2023) and also showed the importance of AnAOB presence to increase PdN efficiency by competing for nitrite (Ladipo-Obasa et al., 2022). The question remains however how one can startup a PdNA IFAS system when the MLSS maintains a healthy full denitrification methylotroph population and no initial AnAOB mass is present to compete for nitrite. The latter conditions are tested in this paper and the results of an IFAS PdNA system with MeOH for PdNA and downstream full denitrification is discussed.

Materials and Methods
A mainstream nitrogen removal pilot was operated at Blue Plains Advanced Wastewater Treatment Plant. The schematic for the pilot is shown in Fig.1. The pilot was initially inoculated with nitrification-denitrification sludge from the full-scale biological nutrient removal system.

Results and Discussions

1. Permit Compliance and Nitrogen Removal
As shown in Table.1, the effluent TIN concentration averaged 2.59 ± 1.2mg N/L, successfully complying with the discharge permit requirements throughout the entire operational period (< 3 mg N/L).

2 PdN selection
PdN was successfully established within seven days and gradually improved until day 42, reaching an PdN efficiency of 20%, and confirmed by activity tests (Fig.2). This result aligns with expectation of observing lower PdN efficiencies with MeOH in the absence of AnAOB (Ladipo-Obasa et al., 2022). However, PdN efficiency declined to below 10% between days 70 and 112, which coincided with suboptimal methanol dosing. Operational constraints, such as understaffing, also hindered the maintenance of conditions essential for optimizing PdN selection during this period. Fluctuations in PdN efficiency persisted throughout the first 100 operational days due to limitation in nitrate removal rates not allowing for observable nitrite accumulation (Fig.2). This limitation was corrected on day 115, by increasing nitrate removal rates. Also, SRT was reduced from 28±0.4 days to 21±4 days, minimizing endogenous decay. Those actions led to establishing PdN efficiencies back to 20% (Fig. 2A). An improvement in PdN efficiency was observed after the enrichment of AnAOB up to PdN efficiencies of 44.03±10.01%, providing results close the previously reported PdN efficiencies (Ladipo-Obasa et al., 2022). This reinforced the critical role of AnAOB in enhancing PdN performance with methanol.

3 AnAOB enrichment
The first measurable AnAOB activity was detected after 90 days (Fig.2D). However, operational inefficiencies delayed significant progress until corrective actions were implemented after day 115 (discussed above) to allow for nitrite levels of 0.82 ± 0.51 mg N/L to be maintained (Fig.2C). To ensure sufficient substrate availability, ammonium concentrations were maintained at ≥2.3 mg N/L (Fig.2C). After establishing nitrite levels > 0.5 mg N/L from day 131 onwards it took until day 153 to see consistent ammonium removal of at least 0.55±0.11 mg N/L or 22.38±10.71 mg N/m2/d (Fig 2D). For that point on, ammonium removal increased exponentially and reached 2.23±0.57 mg N/L or 151.48±48.8 mg N/m2/d at the end of the experiment (Fig.2D).

The observed anammox growth rate was calculated as 0.036 ± 0.004 d-1, which aligns with those reported in polishing filters and MBBR systems using glycerol as a carbon source (Fofana et al., 2022; Schoepflin et al., 2022) but is lower than growth rates in suspended PdNA systems (Le et al., 2021). This discrepancy may be attributed to diffusion limitations in biofilm systems or competition with heterotrophic denitrifiers for nitrite (Stewart Philip, 2003). Additionally, this study confirms that it is important to generate a limited amount of nitrite accumulation together with ammonium availability to enrich AnAOB.

The timing of the first measurable AnAOB activity (day 90) aligns with prior findings (Bachmann et al., 2024; Kocamemi et al., 2018; Verma et al., 2021), further validating the feasibility of these approaches under mainstream PdNA conditions. we believe earlier optimization of nitrate removal to maintain nitrite could have reduced startup time. During this experiment about 60 days were lost.

Conclusion
This study successfully demonstrated AnAOB enrichment in PdNA IFAS system with downstream MeOH based polishing.

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

Presentation time

08:30:00

09:00:00

Session time

08:30:00

10:00:00

SessionPdNA: Insights into Pilot and Full-scale Implementations

Session locationMcCormick Place, Chicago, Illinois, USA

TopicLiquid Stream Treatment - Nutrient Removal and Recovery

Author(s)

ISLAM, MD AL SADIKUL, Ngo, Khoa Nam, Lee, Chengpeng, Hatcher, Jacob, Riffat, Rumana, Azam, Hossain, Wells, George, De Clippeleir, Haydee

Author(s)M. ISLAM1, K. Ngo1, C. Lee1, J. Hatcher1, R. Riffat4, H. Azam3, G. Wells2, H. De Clippeleir1

Author affiliation(s)DC Water and Sewer Authority1, Northwestern University2, University of the District of Columbia3, The George Washington University4

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Oct 2025

DOI10.2175/193864718825160028

Volume / Issue

Content sourceWEFTEC

Word count13