Jun, Changyoon, Jun

Jun, Changyoon

Changyoon Jun is pursuing his M.S. and Ph.D. in Environmental Engineering at the University of Michigan, while also completing a dual degree in Statistics. His research specializes in optimizing membrane bioreactor (MBR) systems by integrating fundamental process understanding with advanced data analytics, statistical modeling, and machine learning. With prior industry experience, he focuses on developing adaptive control and predictive modeling frameworks that enhance energy efficiency, and operational stability in full-scale water treatment facilities.

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Description: Experimental Measured Data Driven Diagnosing and Improving Biological Phosphorus...

Experimental Measured Data Driven Diagnosing and Improving Biological Phosphorus Removal at the Great Lakes Water Authority (GLWA) Water Resource Recovery Facility (WRRF)

Abstract

Background and Objectives
The Great Lakes Water Authority (GLWA) Water Resource Recovery Facility (WRRF) serves 3.1 million residences in Southeast Michigan. Treating a combined sewage inflow up to 3,560,000 m3/day (940 million gallons per day, MGD) it is one of the largest treatment facilities in the world. The secondary treatment process consists of four limited-nitrifying High Purity Oxygen (HPO) activated sludge bioreactors, consisting of eight cells in two bioreactors and ten cells in the other two bioreactors, followed by 25 circular secondary clarifiers. Phosphorus removal is achieved by a combination of ferric chloride addition to influent wastewater prior to primary treatment along with coincidental biological phosphorus removal (bio-P) occurring in the HPO system. Influent wastewater characteristics are highly variable, likely due to sedimentation and biological activity occurring in the large volume and high residence time of the combined sewer system.
This paper summarizes the results of over four years of work: (1) characterizing variations in the influent wastewater characteristics, (2) documenting the unique bio-P performance of the system resulting principally from fermentation occurring in the secondary clarifiers (a form of side-stream fermentation), and (3) consolidating these results in a plant-wide model characterizing chemical (ferric chloride) and biological phosphorus removal along with impacts of solids handling recycles. These results should be of interest to those working to achieve effective phosphorus removal along with those dealing with extreme wet weather flow conditions.
Methodology
Experimental work consisted of extensive analysis of 8-2/3 years of liquid stream operating data (from January 2013 to August 31, 2021), coupled with influent wastewater characterization, full-scale bioreactor profiles, batch reactor testing, and jar testing. Process modeling was conducted using SUMO21 (Dynamita), calibrated as depicted in Figure 1. Figure 2 is the developed model from this study to reflect actual operating conditions for modeling historical performance (i.e. calibration). Batch reactor tests conducted in the late summer of 2018, early winter of 2020, and early winter of 2021 assisted with model calibration. The tests were performed to simulate the anaerobic and aerobic periods occurring in the full-scale HPO bioreactors and within the secondary clarifier sludge blanket. Appropriate quantities of return activated sludge (RAS) or concentrated mixed liquor were combined with primary effluent, then sampled for measuring ortho-phosphorus, soluble COD (sCOD), and oxygen uptake rate (OUR). An initial half-hour anaerobic period was followed by two-hour aerobic period per one cycle of batch tests. In some cases, a further two-hour anaerobic period was added to simulate residence time within the secondary clarifier to measure bio-P's performance in different seasonal conditions. In 2021, another set of batch reactor was operated under strict anaerobic conditions for 72 hours to measure phosphorus release rate and possible phosphorus release amounts. Wastewater characteristics over the entire wastewater treatment region were separately analyzed for 5-days biological oxygen demand (BOD5), total chemical oxygen demand (COD), sCOD, total phosphorus (TP), total SP (TSP), total suspended solids (TSS), volatile suspended solids (VSS), and influent volatile fatty acid (VFA) concentration. A year-long intensive sampling phase evaluated particulate, colloidal, and dissolved biodegradable, and non-biodegradable organic matter.
Results
Influent fractionation is a crucial component of calibrating the model and predicting bio-P performance from modeling because biodegradable organic amounts (including soluble particulate forms) largely affect microbes' activities in the system, and it is generally assumed the fraction of biodegradable organic matter from influent VSS as 0.625. Although this assumption returns a reasonable estimation, it cannot capture the nature of fluctuating influent wastewater, resulting in deviations in model prediction. An interesting correlation was observed from the dataset (Figure 3), showing a robust correlation between influent BOD/VSS concentration and its removal ratio over primary clarifiers, dBOD/dVSS (here dBOD and dVSS refer to the removed fractions, respectively, of the two components). This leads to estimate fraction of biodegradable particulate organic matter from influent VSS, allowing reasonable approximation of daily varying wastewater characteristics for simulation. The modeling results are displayed in Figure 4 where MLVSS was used as an indicator for the calibration performance over the input mass balance. The bio-P performance was calibrated using batch test results (Figure 5), and Figure 6 compares the results predicted by the calibrated model. We find that influent VFA concentrations were insufficient to support bio-P activity, and the initial unaerated zones were not large enough to either supply or produce the VFA's needed for PAO growth. However, we found that sludge fermentation in the secondary clarifiers did provide sufficient VFA's for PAO growth. Analysis of the model results identified three general factors affecting bio-P performance: (1) For the GLWA WRRF, the data suggests that an SRT of 1.8 days or shorter at a wastewater temperature of about 10 Â°C leads to PAO washout, and subsequently to elevated effluent TSP. (2) During warm periods, even small amounts of nitrite and nitrate generated by nitrification adversely impact bio-P because they act as an alternative electron acceptor in the secondary clarifier sludge blanket, resulting in reduced fermentation and VFA production for PAO uptake and phosphorus release, which suppresses the PAO population. (3) A sufficient sludge blanket depth must be maintained to achieve sufficient fermentation and VFA production for PAO growth. Conclusion Influent characteristics are utilized to estimate time varying influent particulate organic matter fraction, which improves model prediction performance. The calibrated modeling results suggested operational protocols for improving bio-P performance, these include: (1) seasonal adjustment of SRT (range of 2.0 to 2.5 days) in response to wastewater temperature variations to avoid PAO washout during low-temperature conditions and to minimize nitrification during warmer periods, (2) maintaining a secondary clarifier sludge blanket of 3.3 feet. Minor physical modifications are also suggested, including the addition of mixers to the bioreactor's initial zones and the diversion of pure oxygen feed around these aeration deck stages to improve bio-P performance via the establishment of deeper fermentation conditions. The fermentation also could be increased by directing RAS to the first stage of the aeration deck and using step feed capabilities to direct influent to the second stage. The results of suggestions show the improved bio-P indicated in Figure 7.
Discussion
The effect of cessation of ferric chloride addition to the influent wastewater was simulated by adjusting PE, TP, and TSP concentrations to account for historical chemical phosphorus removal. Figure 8 presents estimated effluent TP level in comparison to revised influent TP concentration assuming ferric chloride is not added to the influent wastewater. The results indicate that plant effluent TP discharge limits can be met by developing these suggested conditions, suggesting that ferric chloride addition could be reduced or eliminated while sustaining required performance.

A process model for the GLWA WRRF HPO-AS process developed using SUMO21 based on batch reactor test results and 8-1/2 years of plant operating data demonstrated the functional mechanism for the routine occurrence of bio-P. It occurs because of the unique configuration of the HPO-AS process and the characteristics of the influent wastewater. VFA's needed for PAO growth are largely produced in the secondary clarifier sludge blanket, providing larger biomass inventory than ANA zone of bioreactor.

SpeakerJun, Changyoon

Presentation time

11:00:00

11:25:00

Session time

10:30:00

12:00:00

TopicAdvanced Level, Intelligent Water, Nutrients, Research and Innovation

Author(s)

Jun, Changyoon

Author(s)Changoon Jun1; John Norton, Jr.2; Majid Khan3; Catherine Wiley4; Andrea Busch5; Glen Daigger6

Author affiliation(s)University of Michigan, Ann Arbor, MI1; Great Lakes Water Authority, Detroit, MI2; Great Lakes Water Authority, Detroit, MI3; Great Lakes Water Authority, Detroit, MI4; Great Lakes Water Authority, Detroit, MI5; University of Michigan, Ann Arbor, MI6

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Oct 2022

DOI10.2175/193864718825158563

Volume / Issue

Content sourceWEFTEC

Word count23

Membrane Bioreactor Air Scour Control Model to Address Fouling

Abstract

Membrane Bioreactor (MBR) technology is essential for water reuse, which is especially important given increasing water scarcity. While MBRs provide affordable, high-quality treated water, fouling remains a major hurdle for stable operation. To mitigate fouling progression, operators utilize a rigorous set of actions; air scouring, back-pulsing (BP) and chemical cleanings. Notably, air scouring accounts for the largest proportion of operational costs, as its set-point often includes a large safety margin due to uncertainty regarding the required air scour flowrate. In previous study, we proposed and validated using data from two full-scale MBR plants a model (the K model) to estimate the necessary air scouring intensity under specific operational conditions. The model incorporates key variables, including permeate flux, mixed liquor suspended solid (MLSS) concentration, and membrane resistance, and enables the identification of thresholds where hydrodynamic conditions change abruptly, leading to the on-set of critical flux. The results demonstrated that system response can be effectively characterized using the proposed model, allowing optimization of the air scour flowrate (Jun et al., 2024). The model is consistent with the results of others indicating that higher resistance leads to increased local permeate flux, which in turn requires greater shear intensity.

Here we will present long-term operating data for an additional full-scale MBR plant that builds on the work of others to characterize fouling and its interaction with air scour control. Diez et al. (2013) suggested that resistance measured during back-pulsing (BP) cycles (hereafter referred to as intact resistance) characterizes irreversible membrane fouling. We use this to characterize pore blocking and external residuals not effectively removed during repeated permeation cycles, as suggested by Li and Wang (2006). Therefore, the intact resistance value in this study is determined by RT(Total resistance) — RBP(BP resistance) — Rm (Membrane resistance).

Increasing intact resistance results in increased local flux and accounts for the need to adjust air scouring appropriately. We introduce a pragmatic two-dimensional operational matrix, based on the K value, which represents the hydrodynamic balance between solids deposition during filtration and removal by air scouring, and intact resistance, which indicates the sensitivity of this balance. Under elevated intact resistance conditions, cake resistance tends to increase in response to external stimuli, such as high flux or high solid loading, even within the favorable hydrodynamic conditions.

The right side of Figure 1 presents the control matrix, including air scouring flowrate (characterized by K, x-axis), intact resistance (y-axis, while the left side presents supporting data from the full-scale MBR.) Plant data (left side of Figure 1) reveals resistance slope changes defined by two fine-tuned thresholds: KLim (limiting condition) and KS.F (incorporating safety factor). The numbers within each grid define sections (bottom left panel): section 9 indicates the optimal zone, sections 6 and 8 are attention zones, and the remaining sections are classified as limiting zones. The goal is to maintain operations within the optimal zone (i.e., minimizing cake development by controlling intact resistance), with two set-points ensuring stability during deviations. Cake resistance is modest above KS.F but begins to increase below it and more rapidly near KLim. Intact resistance has two thresholds: the Target Limit and the Warning Limit. Above the Target Limit, the rate of cake resistance increase become more sensitive to operational condition yet manageable but becomes increasingly difficult above the Warning Limit. Table 1 outlines the appropriate actions to reduce unnecessary excess of resources that has marginal benefits.

Detail case study and examples of use of these control measures based on data from the full-scale MBR will be presented. This approach facilitates optimal decision-making, including air scouring adjustments to reduce energy consumption, and measures to prolong operation before a recovery clean is necessary.

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

Presentation time

14:30:00

14:45:00

Session time

13:30:00

15:00:00

SessionApplications and Optimization of MBR Technology

Session locationMcCormick Place, Chicago, Illinois, USA

TopicLiquid Stream Treatment Technology - Secondary & Tertiary Treatment

Author(s)

Jun, Changyoon, AGHASADEGHI, KIMIA, Daigger, Glen