Garrido, Manel

Garrido, Manel

Manel Garrido is a speaker at WEFTEC 2026.

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About Garrido, Manel

Manel Garrido is a speaker at WEFTEC 2026.

Garrido, Manel

Manel Garrido is a speaker at WEFTEC 2026.

Titles from this speaker

Description: Controlling Mainstream PdNA Through Advanced Aeration Control Strategies at Nine...

Controlling Mainstream PdNA Through Advanced Aeration Control Strategies at Nine North American Facilities

Abstract

Introduction The widespread adoption of partial denitrification-anammox (PdNA) technology depends not on proving its benefits-which include 60% carbon savings, 25% aeration reduction, and 30-50% capacity increases-but on demonstrating reliable control strategies across diverse configurations. This combination of resource efficiency and capacity enhancement positions PdNA as both an operational optimization and capital avoidance strategy. While the water sector has implemented conventional nitrification-denitrification control successfully, PdNA introduces unique challenges: maintaining precise ammonia-to-NOx (AvN) ratios, coordinating carbon dosing, and managing anammox biomass retention at reduced solids retention times. This research addresses these challenges through a multi-site demonstration spanning nine facilities across North America. Unlike previous single-implementation studies, this effort evaluates control strategies across pre-anoxic, post-anoxic, and tertiary PdNA configurations simultaneously. The work builds upon successful implementations including HRSD's York River plant, where automated AvN control has enabled stable operation at nearly half the original design SRT while maintaining stringent effluent limits. Central to this effort is developing comprehensive process models using BioTwin (BioWin's real-time platform) to implement distinct mathematical frameworks for anammox kinetics, biofilm dynamics, and real-time monitoring. The modeling extends beyond steady-state design by incorporating dynamic control algorithms that reproduce transient behavior under diurnal loads, seasonal temperature fluctuations, and influent perturbations. Five controller approaches were evaluated through 30-day simulations, spanning a tuning complexity spectrum: from simple timer-based intermittent aeration requiring minimal calibration, through single-parameter ABAC, to multi-variable AvN and STAR strategies requiring systematic sensitivity analysis for setpoints and cascade loop optimization. Methodological Approach This research employs systematic validation using full-scale operational data to establish transferable control frameworks. HRSD's York River facility serves as primary calibration site, with five years of data supporting control strategy development. Parallel efforts at WSSC's Seneca sidestream pilot test ABAC with intermittent aeration in an integrated N/DN configuration, evaluating aerobic fraction control under different process constraints. Results and Discussion The modeling effort successfully replicated York River's transition from conventional operation to PdNA, achieving calibration R² values >0.85 for MLSS (2000-2600 mg/L), aerobic SRT (4-6 days), and effluent TIN (<3 mg/L). Models captured the operational shift where aerobic SRT was decoupled from total SRT through intermittent aeration, maintaining 7-8 days total SRT while reducing aerobic SRT by 40-50%-directly translating to capacity increases. Five control approaches were evaluated across the tuning complexity spectrum: Timer-based intermittent aeration: Fixed aerobic/anoxic cycles requiring minimal tuning 1.ABAC: Continuous aeration with DO setpoint adjusted based on ammonia concentration only 2.STAR Control: Intermittent aeration using dual-parameter control with ammonia and NOx monitoring, creating aerobic/anoxic cycles 3.AvN Control: Modified STAR optimized for anammox with equal slopes and zero intercept 4.AvN with carbon trim: Cascade configuration adding feedforward-feedback carbon dosing to AvN control Results indicate that controller selection should be driven by effluent TIN requirements and existing infrastructure rather than pursuing maximum complexity. Facilities targeting TIN <3 mg/L benefit from AvN control with carbon trim, while those with moderate limits (>5 mg/L) achieve comparable results using simpler ABAC or timer-based approaches. The critical finding: ammonia-only instrumentation paired with intermittent aeration delivers 70-80% of the benefits achievable with full NOx monitoring, substantially lowering the barrier to entry for utilities considering PdNA adoption. Conclusion This research provides configuration-specific guidance for PdNA control implementation. For post-polishing systems, AvN control with tight setpoint management (0.4-0.6) maximizes anammox activity. For integrated systems, ABAC with aerobic fraction control delivers robust performance while reducing instrumentation requirements. The framework developed enables utilities to select control strategies matched to their TIN limits, automation capabilities, and operational constraints, rather than defaulting to complex approaches that may exceed facility needs or staff capacity.

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

SpeakerGarrido, Manel

Presentation time

16:30:00

17:00:00

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)

Garrido, Manel, Al-Omari, Ahmed, Yiannou, Angelos, Jimenez, Jose

Author(s)M. Garrido1, A. Al-Omari1, A. Yiannou2, J. Jimenez1

Author affiliation(s)Brown and Caldwell, 1Brown and Caldwell, 1Brown and Caldwell, 1

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Sep 2026

DOI10.2175/193864718825160413

Volume / Issue

Content sourceWEFTEC

Word count14

Description: Denitrification, Hydrolysis and Internal Store Carbon in Low Dissolved Oxygen...

Denitrification, Hydrolysis and Internal Store Carbon in Low Dissolved Oxygen Biological Nutrient Removal

Abstract

Introduction

Dissolved oxygen (DO) is a key factor in the activated sludge process, influencing aeration costs, nitrogen/phosphorus removal, and N2O emissions. Research shows nitrifiers and denitrifiers can coexist and function in low DO zones, enabling 'simultaneous nitrification-denitrification' (SND). This highlights microbial adaptation to suboptimal nitrogen removal conditions. While progress has been made on nitrification and microbial selection at low DO (WRF Project No. 5083, 2025), low DO denitrification during SND remains underexplored. Understanding its mechanisms and influencing factors is crucial for optimizing low DO BNR systems, enhancing nitrogen removal, reducing costs, and improving carbon management.

Among the critical processes in BNR, denitrification (DN) -the biological conversion of nitrogen oxide (nitrate [NO3], nitrite [NO2-]) to nitrogen gas (N2)-plays a pivotal role in removing nitrogen from wastewater. Conventionally, DN is considered an anoxic process, occurring in environments with low or negligible DO concentrations. However, studies have challenged this paradigm by demonstrating the potential for DN under low DO conditions, opening new avenues for optimizing BNR systems using aeration controls.

The interplay between DN, DO conditions and electron donor are particularly relevant in energy-efficient wastewater treatment designs, which aim to reduce aeration energy without compromising treatment efficacy. This paper explores the dynamics of DN in low DO environments within BNR systems providing insights into hydrolysis and internally store carbon utilization. Key factors such as microbial community structure, substrate availability, removal pathways and reactor design are analyzed to understand their roles in enabling DN under such conditions. The findings aim to inform the development of optimized BNR strategies that leverage low DO DN during SND to improve efficiency, reduce energy consumption, and address the growing need for sustainable wastewater treatment solutions.

Materials and Methods
To evaluate the effects of oxygen on denitrification kinetics, microbial communities, and substrate availability, including hydrolysis, several full-scale and pilot-scale facilities operating under low DO conditions were analyzed. Long-term operational data from these facilities were compared with baseline information from a literature review. Mixed liquor samples were collected for laboratory-scale studies, and microbial ecology was examined using Quantitative PCR (qPCR) on DNA extracts. These findings enhanced understanding of the role of oxygen in DN within SND systems.

Results
The performance of full-scale low DO BNR plants was evaluated using one-year average data from facilities with DO levels ≤0.6 mg/L. These plants, with varied configurations, climates, and capacities, showed TIN removal from 65—95% with influent COD:N ratios of 7.5—13. SND contributed ~50% of TIN removal, depending on configuration. Complete nitrification (effluent NH4+ <0.5 mgN/L) was achieved. High selector F/M and rbCOD bleed-through enhanced DN under low DO conditions, as observed by profiling and lab tests not included in the abstract.

To study DO's effect on DN rates, mixed liquor from a low DO (<0.5 mg/L) plant performing SND was tested in batch reactors at varying DO concentrations (Figure 2). Results show maximum NUR under anoxic conditions, with rapid declines as DO rises. At 0.5 mg/L DO, NUR decreases by ~50%, and no DN occurs at 1.0 mg/L, likely due to fully aerobic flocs and oxidized carbon. The DN's oxygen half-saturation inhibition coefficient (Kio) averaged 0.19 ± 0.08 mg/L across facilities. This is an important process modeling parameter to simulate SND.

The role of soluble substrate (Ss) in DN is well-studied, but less is known about the role of the carbon dynamics on DN in low DO systems. Particulate substrate (Xs) biodegradation begins with hydrolysis, a critical step in DN during SND. In wastewater treatment, hydrolysis involves extracellular enzymes in microbial flocs converting Xs to Ss, enabling bacterial growth and carbon availability for denitrification. This process, slower than heterotrophic growth, is the rate-limiting step for organic compound degradation and DN in SND. DN rates were tested in two NUR batch tests under anoxic and low DO conditions using settled wastewater and acetate (Figures 3). In anoxic tests, rapid NO3 reduction with sCOD removal was followed by slower NO3 reduction attributed to hydrolysis, with specific sCOD removal of 4.8 mg sCOD/mgNO3. In low DO tests, three NUR slopes were observed: rapid NUR using sCOD, slower NUR using stored COD, and the slowest NUR via hydrolysis. The higher sCOD removal (e.g., 6.2 mg sCOD/mgNO3) was likely due to aerobic oxidation for cell growth. Process model predictions were fitted to the measured NUR and the hydrolysis rates were 2.9 d-1 (anoxic) and 3.8 d-1 (low DO).

Conclusions
SND has the potential to maximize TIN removal with influent carbon while reducing energy and chemical dependency. Denitrification in low DO systems is a critical step in SND with many factors in play. Understanding internal stored carbon and hydrolysis are key aspects of denitrification, especially in low DO systems. This study establishes important kinetic parameters including hydrolysis rate that can be used to simulate denitrification in low DO systems.

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

Presentation time

08:50:00

09:00:00

Session time

08:30:00

10:00:00

SessionMicrobial Selection and Performance Under Low DO Conditions

Session locationMcCormick Place, Chicago, Illinois, USA

TopicLiquid Stream Treatment - Nutrient Removal and Recovery

Author(s)

Jimenez, Jose, Bauhs, Kayla, Al-Omari, Ahmed, Garrido, Manel, Sturm, Belinda, Miller, Mark

Author(s)J. Jimenez1, K. Bauhs1, A. Al-Omari1, M. Garrido1, B. Sturm, M. Miller1

Author affiliation(s)Brown and Caldwell1, Jacobs2

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Sep 2025

DOI10.2175/193864718825159962

Volume / Issue

Content sourceWEFTEC

Word count14

Description: From Soft Sensors to Smart Advisors: Agentic AI for Real-Time VFA and Alkalinity...

From Soft Sensors to Smart Advisors: Agentic AI for Real-Time VFA and Alkalinity Management in Anaerobic Digestion

Abstract

Introduction Volatile fatty acid (VFA) and alkalinity monitoring remain critical yet challenging aspects of anaerobic digestion operations. While VFA/alkalinity ratios below 0.3-0.4 indicate stable operation, conventional laboratory analysis introduces 24-48 hour delays that limit proactive response to process upsets. Hardware sensors capable of real-time VFA measurement require substantial capital investment and maintenance in harsh digester environments. This gap between continuous monitoring needs and practical measurement limitations has driven interest in data-driven soft sensors that estimate VFA and alkalinity from readily available process measurements. This research advances beyond conventional soft sensor approaches by integrating machine learning predictions with process modeling and natural language interfaces, creating an 'agentic' digital twin that predicts stability parameters, diagnoses root causes, recommends corrective actions, and evaluates intervention scenarios on demand. Methodological Approach The soft sensor framework was developed using four years of operational data from a full-scale co-digestion facility processing food waste, fats/oils/grease, and municipal sludge. The dataset encompassed over 150 process variables including biogas flow and composition, digester temperature, pH, mixing intensity, feed characteristics, and laboratory measurements of VFA, alkalinity, ammonia, and COD. Feature selection employed Spearman correlation analysis, mutual information-based redundancy minimization (mRMR), and gradient boosting importance ranking to identify optimal predictor subsets. Multiple machine learning architectures were evaluated including linear regression, Lasso regularization, random forest, XGBoost, and neural networks using repeated k-fold cross-validation. The selected models predict total VFA concentration, bicarbonate alkalinity, and VFA/alkalinity ratio from standard SCADA instrumentation: biogas flow rate, methane and CO2 composition, digester temperature, pH, and feed flow rates. The agentic layer integrates calibrated soft sensors with a SUMO-based process model through Python APIs, enabling real-time simulation capabilities. Natural language processing allows operators to query the system conversationally: 'Why is biogas production declining?' triggers automatic comparison against historical patterns and model predictions. 'What happens if we accept 5,000 gallons of FOG tomorrow?' executes a forward simulation incorporating the proposed feed change. The framework was subsequently deployed at a blackwater treatment pilot in Girona, Spain, where source-separated blackwater undergoes anaerobic treatment in a CSTR configuration, testing soft sensor transferability from high-strength co-digestion to lower-strength domestic waste streams. Results and Discussion The co-digestion soft sensors achieved prediction accuracy (R²) of 0.85-0.92 for VFA concentration and 0.88-0.94 for alkalinity across validation datasets spanning seasonal variations and feed composition changes. Feature importance analysis identified biogas flow rate, methane percentage, pH, and temperature as dominant predictors, collectively explaining over 75% of VFA and alkalinity variance. This confirms operators can achieve meaningful stability monitoring without dedicated VFA analyzers using only standard instrumentation. The agentic interface demonstrated particular value during feed upset events, identifying developing instability 6-12 hours before VFA/alkalinity ratios exceeded warning thresholds. Initial deployment at Girona confirmed soft sensor transferability, with recalibration requiring only 45 days of site-specific data to achieve comparable prediction accuracy. The conversational interface reduced operator response time to stability queries from 15-30 minutes of dashboard navigation to under 2 minutes of natural language interaction. Conclusions Integrating machine learning soft sensors with process models and natural language interfaces creates a fundamentally different operational tool than conventional monitoring systems. The agentic digital twin transforms anaerobic digestion management from reactive response to proactive optimization, enabling operators to anticipate stability issues and evaluate interventions before implementation. The framework's successful transfer between facilities suggests broad applicability across anaerobic systems while minimal instrumentation requirements lower adoption barriers.

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

Presentation time

11:00:00

11:15:00

Session time

10:30:00

12:00:00

SessionOptimizing Industrial Water Treatment with AI

Session locationErnest N. Morial Convention Center

TopicIndustrial Issues and Treatment Technologies, Research and Innovation

Author(s)

Garrido, Manel, Jimenez, Jose

Author(s)M. Garrido1, J. Jimenez1

Author affiliation(s)Brown and Caldwell, 1Brown and Caldwell, 1

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Sep 2026

DOI10.2175/193864718825160557

Volume / Issue

Content sourceWEFTEC

Word count18

Description: Understanding the Kinetics of Densified Activated Sludge: Implications in Design and...

Understanding the Kinetics of Densified Activated Sludge: Implications in Design and Optimization

Abstract

INTRODUCTION
For densification at full-scale continuous flow water resource recovery facilities (WRRFs), biological selection principles derived from selector design and aerobic granular sludge (AGS) concepts have been coupled with physical selection to lower the sludge volume index (SVI) and achieve superior sludge settling. In densified activated sludge (DAS), flocs co-exist with granules, and significant efforts have been made to research their settling behavior. However, the respective roles of flocs and different sized granules in biological nutrient removal kinetics and their impact on process performance and design of densified WRRFs remain unclear. The relative abundance and microbial activity distribution of ammonia oxidizing bacteria (AOB), nitrite oxidizing bacteria (NOB), and ordinary heterotrophic organisms (OHO) among flocs and granules and its influence on the process performance was investigated. This study focused on the kinetic contribution of different particle size-classes in DAS.

MATERIAL AND METHODS
DAS samples from the full-scale WRRF at Pueblo CO's James R. Dilorio WRRF (referred herein as Pueblo) and from the DAS demonstration treatment train at Metro Water Recovery's Robert W. Hite Treatment Facility (referred herein as Metro) were collected and characterized.

Size-class distribution of DAS was determined by sieving: flocs were 200 µm or smaller particles, small granules were 200-600 µm and large granules were 600 µm and larger. Particle size distribution analysis was conducted for each size-class.

Samples for microbial community analysis were collected from each size-class and stored at -18°C. Microbial community analyses were conducted with Illumina-based 16S rRNA amplicon sequencing. Quantitative PCR (qPCR) was performed on the DNA extracts to quantify total bacteria (16S). Species-level microbial communities were determined with long-read amplicon sequencing.

The biological kinetic rates for nitrification, denitrification and SND for each size-class were assessed through lab-scale studies.

RESULTS AND DISCUSSION
Nitrification Activity for Different Size-Class Distribution: Figure 1 presents the microscopy imaging for the three particle size classes investigated during this study for Metro. Specific nitrification rate (NH4RR) experiments were performed, since abundance and activity of nitrifiers among the different size-classes in DAS are not necessarily proportional. In general, the larger the size of the bio-aggregates, the slower their specific AOB and NOB activities (Figure 2). Small aggregates or flocs have higher specific NH4RR at DO concentrations ranging from 0.2 to 3.0 mg/L. Figure 3 depicts the maximum nitrification rates for the size-classes for Pueblo and Metro's DAS samples; the highest rates were observed for the small granules. In the case of Pueblo, the large granules offered the lowest nitrification rates. For Metro, the maximum rates for flocs and large granules were comparable. Therefore, the benefit of large granules is unclear when it comes to nitrification in DAS.

Figure 4 shows the observed half-saturation oxygen concentration for AOB (KDO, AOB) for the size-classes determined from lab tests. As the size of aggregate increases, there is greater diffusion resistance, so the higher their apparent KDO, AOB (similar results for NOB were observed). The KDO, AOB for Pueblo are generally lower than those estimated at Metro, as Pueblo operates at comparatively low DO concentrations.

Denitrification and SND Activity for Different Size-Class Distribution: The larger the size of the bio-aggregates, the smaller their specific denitrification rates (SDR). In the case of Metro, 4.58, 3.80, and 3.11 mg N/g MLVSS/hr were measured for flocs, small granules, and large granules, respectively. TIN removal efficiencies via SND for the bio-aggregate classes from Pueblo were measured and results are presented in Figure 5. Lower DO concentrations increased SND for all the size-classes. The highest SND efficiencies were observed at DO concentrations of 0.3 mg/L, 0.75 mg/L and 1.0 mg/L for flocs, small and large granules, respectively. For granules, SND reactions were nitrification-limited at low DO conditions, since the operating DO was much lower than the apparent KDO, AOB (reported in Figure 4). After maximum TIN removal efficiencies were achieved for each size-class, higher DO values decreased the TIN removal as the oxygen in the bulk liquid penetrated deeper inside the granules reducing the anoxic zone. A main challenge is finding a balance for aeration: to achieve full nitrification while also establishing anoxic zones in the core of the granules to preserve SND.

Microbial Ecology for Size-Class Distribution: Results will be included for the paper and presentation.

CONCLUSION
The study confirmed that diffusion and counter-diffusion resistance of substrates are inversely correlated with the size of the particles. Nitrification is maximized as particle size is decreased or DO is increased. SND is maximized in flocs when DO is decreased because nitrification is not limited, while it is maximized in small and large granules at higher DO. Controlling the size-class distribution in DAS must be considered for the design and operation of BNR systems, as optimized size will balance settleability and nutrient removal benefits.

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

Presentation time

14:00:00

14:30:00

Session time

13:30:00

15:00:00

SessionDensified Activated Sludge (DAS) Fundamentals

Session locationMcCormick Place, Chicago, Illinois, USA

TopicLiquid Stream Treatment - Nutrient Removal and Recovery

Author(s)

Bauhs, Kayla, Jimenez, Jose, Al-Omari, Ahmed, Miller, Mark, Garrido, Manel, Freedman, Daniel, Maltos, Rudy, McGowan, Patrick, Sturm, Belinda

Author(s)K. Bauhs1, J. Jimenez1, A. Al-Omari1, M. Miller1, M. Garrido1, D. Freedman2, R. Maltos2, P. McGowan3, B. Sturm4

Author affiliation(s)Brown and Caldwell1, Metro Water Recovery2, City of Pueblo3, University of Kansas4

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Sep 2025

DOI10.2175/193864718825160029

Volume / Issue

Content sourceWEFTEC

Word count13

Description: Water and Wastewater Decentralization at Urban District-Level to Enhance Resiliency...

Water and Wastewater Decentralization at Urban District-Level to Enhance Resiliency and Sustainability

Abstract

Decentralized source separation systems for water, energy, and nutrient recovery are emerging as promising solutions to address the mounting challenges in urban water management, particularly as traditional centralized infrastructure faces increasing pressure from population growth, climate change, and resource constraints (Bhambhabi, 2025; Keller, 2024; Garrido-Baserba, 2024; Leigh, 2019; Capodaglio, 2020). Traditional water and wastewater infrastructures and the energy-intense activated sludge process are being questioned because of their environmental and economic burden and negligible resilience against climate change extreme events (Sedlak, 2023; van Loosdrecht & Brdjanovic, 2014; Roefs et al., 2017).

This study presents a comprehensive four-year investigation into the technical, economic, and environmental implications of implementing decentralized source separation systems for urban water management. The study confirms that increasing the recovery efficiencies of water, energy, and nutrients by combining decentralized source separation, anaerobic digestion, and filtration approaches holds the most potential for the global water system's sustainability, reliability, and resilience.

Methodological Approach.
The research methodology incorporated multiple complementary approaches: experimental pilot plants (2 CSTR for black water and 1 dual-reactor for grey water), advanced digital twin development (with real-time capabilities), process and cost modeling for techno-economic assessment, and a dedicated life cycle analysis in collaboration with top experts.

While decentralized source separation could take many forms and configurations, the following setup was chosen as a representative candidate for future systems. Two distinct experimental setups were developed and operated. The first consisted of thermophilic continuously stirred-tank reactors (CSTRs) for black water treatment, operating at 55°C with a daily flow rate of 200 mL, distributed across four feeding events at 6-hour intervals. The reactors were inoculated with thermophilically digested material from a full-scale plant and designed to examine various feeding regimes relevant to decentralized scenarios, including variations in food waste availability, urban density patterns, and fluctuating organic loading rates. The second setup featured a dual-compartment constructed wetland system for grey water treatment, integrating physical filtration mechanisms with phytoremediation processes. Comprehensive monitoring included key parameters such as pH, alkalinity, BOD5, COD, total nitrogen, total phosphorus, and surfactant concentrations at multiple sampling points throughout the treatment process.

These experimental systems were complemented by an advanced digital twin developed using SIMBA# modeling software. This twin incorporated real-time data from supervisory control systems, laboratory parameters, biogas production, and weather forecasting APIs. The digital twin facilitated comprehensive analysis across three critical domains: cost analysis (including monitoring requirements, sensor specifications, and infrastructure sizing), technical specifications (controlling strategies and operational parameters), and life cycle assessment. Additionally, it allowed for the evaluation of potential synergies with complementary technologies such as rainwater harvesting, solar photovoltaics, and vertical farming for nutrient recovery, with a specific focus on nitrogen and phosphorus recovery pathways.

Key Findings
This study confirmed the potential advantages of decentralized source separation approaches compared to conventional centralized systems. The economic analysis revealed that these integrated services demonstrated potential for more than 50% reduction in overall operational costs following a payback period of 5-10 years, varying by location and local utility rates. Space requirements were found to be manageable within urban contexts, with the core system requiring 7-9% of basement space at the city block scale, while integration with vertical farming would require an additional 15% of basement floor space. The system could require 85% less water from utilities while simultaneously improving resource recovery rates - showing a 50% increase in nitrogen recovery and a 90% increase in phosphorus recovery.

Environmental impact assessments revealed less than one-third of the conventional system's global warming potential and eutrophication impacts. The life cycle analysis demonstrated a 60% reduction in carbon footprint compared to centralized systems, primarily due to reduced energy consumption and improved resource recovery efficiency. The vertical farming integration showed particular promise, with the potential to utilize recovered nutrients for local food production, demonstrating a circular economy approach to urban resource management.

This research provides the most comprehensive techno-economic and environmental assessment of decentralized source separation systems to date. The findings demonstrate these systems' viability as sustainable alternatives to centralized infrastructure, with improved resource recovery rates, reduced environmental impacts, and significant economic benefits. These insights inform urban planners, environmental engineers, and policymakers on implementing decentralized water management systems and advancing circular economy principles in urban development.

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

Presentation time

11:30:00

12:00:00

Session time

10:30:00

12:00:00

SessionPathways for Decarbonization and Circular Water Economy

Session locationMcCormick Place, Chicago, Illinois, USA

TopicClimate Change Adaptation and Resilience

Author(s)

Garrido, Manel, Sedlak, David, Molinos-Senante, Maria, Schraa, Oliver, Rosso, Diego, Barnosell, Irene, Poch Espallargas, Manuel

Author(s)M. Garrido1, D. Sedlak2, M. Molinos-Senante3, O. Schraa4, D. Rosso5, I.Barnosell6, M. Poch Espallargas6

Author affiliation(s)Brown and Caldwell1, Univ Of California At Berkley2, University of Valladolid3, InCTRL Solutions, Inc.4, University of California Irvine5, LEQUiA6

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Oct 2025

DOI10.2175/193864718825159910

Volume / Issue

Content sourceWEFTEC

Word count13

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