Haddad, Mathieu

Following his Ph.D in Microbiology at the University of Montreal (QC, Canada) focused on biohydrogen production from syngas fermentation, Mathieu worked in the field of algae and nutraceuticals at MBD Energy (Melbourne, VIC) and bioenergy at Monash University (Melbourne, VIC). He then joined SUEZ technical division (Paris metropolitan area, France) where he is developing SUEZ anaerobic digestion (AD) product line with a special focus on advanced AD processes (temperature-phased AD & thermal hydrolysis) and refractory compounds production.

Titles from this speaker

Description: Alternate: Forecasting Volatile Solids Reduction of Municipal Sludge Using 32 Years...

Alternate: Forecasting Volatile Solids Reduction of Municipal Sludge Using 32 Years of Data

Abstract

The prediction of performance indicators such as Volatile Solids Reduction (VSR) is key for the accurate sizing of municipal sludge digesters. However, prediction models available from the literature typically lack accuracy, leading to the use of conservative values and inadequate process sizing. The present study aims at developing an empirical model for VSR prediction. This model is based on over 32 years of operational data originating from six industrial plants featuring a diversity of wastewater treatment lines. The model was benchmarked against the Anaerobic Digestion Model No. 1 (ADM1) with or without calibration and displayed the lowest average prediction error (RMSE of 4.2%VSR) and bias (2.3 %VSR). These high performances were obtained when predicting VSR for plants, independent from the empirical model training data (i.e., unseen data), highlighting its applicability for design tasks. During the design phase, the proposed model can promote optimal sizing of biogas networks and ancillary equipment, reducing inefficiencies and operational costs. For operational optimization, the model supports dynamic sludge age control strategies to maximize methane yield, contributing to sustainable wastewater treatment practices. In the future, the proposed model can still be improved upon by integrating new operational data with the already available training data used in this study. INTRODUCTION Anaerobic Digestion (AD) is a crucial technology for sustainable waste management, offering the benefits of biogas production, solids reduction and nutrient recovery. With the depletion of fossil energy resources and a growing global population, AD is increasingly important for achieving energy neutrality in wastewater treatment plants (WWTPs). Volatile Solids Reduction (VSR) is a key performance indicator of AD systems. Accurately predicting the VSR is hence essential for optimizing AD plants sizing and performance. Existing design models often lack accuracy, leading to conservative designs and inefficiencies. This study aims to develop an empirical model for VSR prediction using a total of 32 years of data originating from six industrial plants, providing a more reliable tool for AD system design and operation. MATERIALS AND METHODS Plants Description: The study analyzed data from six WWTPs located in diverse regions, including Oceania, the Middle East, South America, Central America, and Western Europe with data from all plants pooled. These plants employed various wastewater treatment processes, such as Conventional Activated Sludge (CAS) and High Rate Activated Sludge (HRAS), with or without primary settling tanks. The sludge types processed included primary sludge, waste activated sludge, and combinations of both. Data Cleaning and Enrichment: To ensure the accuracy of the model, data anomalies were identified and removed. These included periods of digester shutdowns and startups, as well as anomalous observations based on industry standards. Missing values were imputed using an Expectation-Maximisation algorithm, and outliers were detected and removed using the Mahalanobis distance method. Anomalous periods were further investigated using mass balance checks and consistency verification between process inlets and outlets. Variables Definition & Calculation: Key variables for the model included wastewater temperature, Total Solids (TS) concentration, Volatile Solids (VS) fraction of primary and waste activated sludge, and the ratio of primary sludge to waste activated sludge at the digester inlet. Calculated variables included sludge age, Hydraulic Retention Time (HRT), and VSR. VSR was determined using either mass-balance and Van Kleeck methods. Empirical VSR Modelling: A linear model with feature engineering (Lasso) was developed, incorporating commonly measured process variables known to impact AD performance. These variables are the HRT, sludge age, temperature, primary sludge VS content, and the mass-based fraction of primary sludge in the mixed sludge fed to the AD system. The model was trained using a leave-one-plant-out (LOPO) validation approach, ensuring robustness and generalizability. Mechanistic VSR Modelling -- ADM1: The Anaerobic Digestion Model No. 1 (ADM1) was used for comparison, both with and without calibration. Key parameters, namely overall degradability (which is analogous to Biochemical methane potential), and hydrolysis coefficient, were calibrated using a grid search algorithm. The performance of the ADM1 model was assessed using the same test datasets as the empirical model. RESULTS AND DISCUSSION Empirical Model Performance: The empirical model outperformed the ADM1 model in predicting VSR, both in its calibrated and uncalibrated forms. The empirical model demonstrated lower Root Mean Square Error (RMSE) and bias, indicating higher accuracy and applicability for design tasks. The model's ability to integrate seasonal variability and provide reliable predictions without requiring plant-specific calibration was a significant advantage. Model Assessment: The empirical model's performance was validated across different plants and conditions, showcasing its robustness. The model's integration of seasonal variability, such as wastewater temperature, likely contributed to its superior performance compared to the ADM1 model, which assumes constant feedstock characteristics. The empirical model's ability to avoid overfitting, particularly in cases with limited data, further highlighted its reliability. Implications for AD Systems Design: Accurate VSR prediction is critical for optimal sizing of biogas networks and ancillary equipment. The empirical model reduces the risk of under or oversizing, leading to cost savings and improved operational efficiency. For instance, an 8.7% VSR uncertainty with the unfitted ADM1 model (vs. 2.3% VSR with the empirical model) could lead to a 19% relative error in biogas system sizing, compared to a 5% relative error with the empirical model. This precision is crucial for maintaining stable operation and minimizing costs associated with equipment purchase, maintenance, and efficiency. Implications for AD System Operation: The empirical model supports dynamic sludge age control strategies, enhancing methane yield and contributing to energy neutrality in WWTPs. By optimizing the activated sludge age, the model can significantly impact both water and sludge treatment lines. For example, reducing the activated sludge age from 22 to 14 days at a wastewater temperature of 17°C can increase VSR from 19% to 27%, translating to a 42% increase in biogas production. This optimization can enhance oxygen transfer in the aeration tank as well as improve AD performance, supporting a dynamic control strategy that accounts for seasonal variability. CONCLUSION The empirical model developed in this study represents a significant advancement in predicting VSR for municipal sludge digestion. Built on 32 years of data from six industrial plants, the model offers accurate and reliable predictions, supporting the design and operation of more efficient and sustainable AD systems. It may perform on plants outside its experience envelope, which can be addressed by increased training sets. By reducing the risk of under or oversizing and enhancing operational strategies, the model contributes to the broader goal of energy neutrality in WWTPs. Future improvements can be achieved by incorporating more operational data, expanding the dataset to include a wider variety of industrial plants and operational conditions, thereby improving the model's robustness and reliability.

This paper was presented at the WEF Residuals & Biosolids and Innovations in Treatment Technology Joint Conference, May 6-9, 2025.

SpeakerHaddad, Mathieu

Presentation time

13:30:00

16:45:00

Session time

13:30:00

16:45:00

SessionCase Studies for Optimizing THP, Dewatering, and Digestion

Session number7

Session locationBaltimore Convention Center, Baltimore, Maryland, USA

TopicAnaerobic Digestion, Biosolids, Dewatering Optimization, Energy and Carbon Neutrality, fugitive methane emission, Full-scale Optimization, Greenhouse Gases, Mesophilic Anaerobic Digestion, Odor/Air Emissions, Operations And Maintenance, Process modeling, Reliability, Sludge Digestion, THP, THP, CAMBI

Author(s)

Picard, Antoine, Trap, Danielle, Batstone, Damien, Moscoviz, Roman, Haddad, Mathieu

Author(s)A. Picard1, D. Trap1, D. Batstone2, R. Moscoviz1, M. Haddad1

Author affiliation(s)SUEZ, 1SUEZ, 1University of Queensland, 2

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date May 2025

DOI10.2175/193864718825159744

Volume / Issue

Content sourceResiduals and Biosolids Conference

Word count14

$Description: Full-Scale Thermal Hydrolysis Optimization: Impact on Refractory Organics and...$

Full-Scale Thermal Hydrolysis Optimization: Impact on Refractory Organics and Anaerobic Digestion Robustness

Abstract

Introduction Thermal hydrolysis (THP) is widely deployed to improve sludge treatment performance by enhancing anaerobic digestion (AD), increasing biogas production, boosting dewaterability, and achieving hygienization. However, THP also generates biologically recalcitrant compounds-particularly refractory chemical oxygen demand (rCOD) and refractory dissolved organic nitrogen (rDON)-that can resist downstream biological treatment and contribute to effluent residuals. This challenge is increasingly important as utilities face tightening discharge standards for COD and nitrogen and rising interest in high load solids strategies. This full scale study at the Dijon EauVitale WRRF (France) investigates how THP operating temperature (140-165â€¯ °C) influences the quantity and typology of refractory organics, their fate through digestion, and microbial community resilience. We combine high resolution chemometric fingerprints (UPLC SEC with UV/fluorescence detection) and artificial neural network (ANN) feature selection with parsimonious multiple linear regressions (MLRs) to build predictive models for rCOD and rDON using interpretable descriptors. We further assess PCDD/Fs concentrations and Toxic Equivalents (TEQ) around THP and characterize bacterial/archaeal diversity in digestate to evaluate operational robustness. A set of mass balances at full scale complements bench scale degradability tests to quantify how much refractory material is formed by THP and retained/released through AD and dewatering. Materials & Methods The study was conducted at the Dijon EauVitale WRRF equipped with thermal hydrolysis (140-165â€¯ °C) and mesophilic anaerobic digestion. Samples were collected at key process stages (pre-THP, post-THP, digestate, effluent) across multiple campaigns. Refractory COD and DON were quantified using standard colorimetric assays, while molecular fingerprints were characterized by UPLC-SEC with UV/fluorescence detection. Predictive models were developed using artificial neural networks and multiple linear regressions based on selected spectral descriptors. Microbial community structure was assessed via 16S rRNA sequencing and diversity metrics. Results & Discussion 1) Temperature vs Quantity and Typology of Refractory Organics Linear scaling of refractory formation. THP increased rCOD proportion linearly from 140 to 165â€¯ °C: â‰ˆ2.9 fold at 140â€¯ °C and â‰ˆ4 fold at 165â€¯ °C relative to PWAS. Despite quantity scaling, the rDON/rCOD ratio remained stable at ~4.5% (mean; 95% CI â‰ˆ3.8-5.1%), indicating a constant nitrogen share in refractory pools across the studied range. This stability suggests that temperature mainly scales the refractory quantity, not the nitrogenization of the refractory fraction. Chemometric fingerprints: typology conserved. PCA/HCA of the 144 spectral ratios revealed three robust clusters: (i) raw PWAS, (ii) THP/digestate streams, and (iii) final effluent. Analytical descriptors most discriminant (ANOVA, pâ€¯<â€¯0.05) were dominated by 20-40â€¯kDa signals combining tryptophan like and humic /melanoidin like features (e.g., TRY1/MEL, TRY1/HA, TRY2/AF2). Across temperatures, these fingerprints remained consistent, supporting that THP temperature does not materially alter molecular typology, even though it amplifies the amount of refractory material. ANN MLR predictive modeling. ANNs prioritized a subset of descriptors, from which compact MLRs reproduced measured rCOD and rDON with RÂ²â€¯=â€¯0.972 and 0.964 using 4-5 interpretable ratios per model. Coefficient signs provided mechanistic insight: low MW protein-melanoidin and humic normalized protein/fulvic contrasts acted as negative predictors of recalcitrance, while 20-40â€¯kDa protein/humic enrichments were positive predictors, consistent with the cluster discrimination. Practically, these descriptors can be embedded into monitoring to track refractory risk and guide temperature setpoints. Operational implication. For design/operations, increasing THP temperature predictably raises refractory load without altering its spectral signature, enabling utilities to use ANN MLR monitors as early indicators and control levers (e.g., temperature windows, blend strategies) rather than expecting typology shifts to ease downstream treatment. 2) Fate Through Anaerobic Digestion and Return Pathways AD mitigation (~31%). Full scale mass balances combined with degradability assays indicated that AD reduces refractory loads by ~30.6â€¯Â±â€¯2.3% (95% CI â‰ˆ20-40%). Evidence points to physical mechanisms-adsorption/copolymerization/association with biomass-more than biodegradation, consistent with literature on hydrophobic recalcitrants binding to flocs. This mitigation means not all THP derived refractory material returns to headworks; a significant share remains associated with digested sludge and exits with dewatered cake. Centrate contribution and effluent context. At Dijon, THP derived refractory accounted for ~23-34% of effluent refractory COD during campaigns, with the remainder dominated by external industrial leachates. Even so, the AD mediated reduction increases the liquids line's headroom, limiting residual build up during high load operation. For centralized solids hubs, this synergy suggests greater acceptance capacity for external sludges than expected if considering THP alone. Operational implication. Coupling THP with robust AD provides a two stage strategy: push hydrolysis for digestion gains while buffering refractory recirculation through physical capture in digesters and solids handling. Monitoring centrates and adjusting cake handling strategies (e.g., capture, conditioning) becomes essential when effluent residuals are rate limiting for compliance. 3) PCDD/Fs Risk Profile at THP Temperatures Measured concentrations and TEQ. Around THP, PCDD/Fs totals showed negligible change at 140â€¯ °C (PWASâ†’HWAS; within method uncertainty) but increased at 165â€¯ °C, with TEQ rising to ~9.2â€¯ng TEQ/kg TS. Although higher than at 140â€¯ °C (~2.9â€¯ng TEQ/kg TS), values remained below applicable agronomic thresholds currently discussed in the EU context (e.g., France's Socle Decree limit: 20â€¯ng TEQ/kg TS for land application). The total mass increase at 165â€¯ °C was accompanied by toxicity weighted increase, suggesting formation/enrichment of more dioxin like congeners at the upper end of the THP window. Operational implication. Within 140-165â€¯ °C, TEQ remains manageable, but facilities should adopt periodic screening when operating â‰¥160-165â€¯ °C, especially if feedstocks or legacy contamination could bias congener profiles. Pressure effects and catalyst/ash interactions warrant further study under THP conditions. 4) Microbial Diversity and Process Robustness Stable alpha diversity. Across THP temperatures, both bacterial and archaeal communities exhibited high and stable diversity (Shannon/Simpson), indicating that THP setpoints do not compromise the functional breadth of digestion. Archaeal communities remained dominated by hydrogenotrophic methanogens (e.g., Methanoculleus) typical of high ammonia sludge digestion, while bacteria showed moderate compositional shifts (e.g., Fastidiosipila vs. Proteiniphilum/Brevefilum) consistent with changes in substrate complexity rather than loss of core hydrolytic/acidogenic functions. Beta diversity insight. Bray-Curtis ordination highlighted greater sensitivity in bacterial assemblages to temperature than archaea, aligning with their broader roles in hydrolysis/acidogenesis. Functionally, the core trophic network remained intact, supporting operational resilience across the THP window. Operational implication. Utilities can tune THP temperature for digestion/performance gains without destabilizing microbial function, provided ammonia management and organic loading remain within design envelopes. Conclusions and Practical Guidance - Temperature effect: Increasing THP temperature (140â†’165â€¯ °C) linearly amplifies refractory organics without changing their molecular fingerprint; rDON shares remain proportionally constant. - Predictive control: A small, interpretable set of chemometric descriptors predicts rCOD/rDON with high fidelity, enabling ANN MLR monitoring to proactively manage refractory risk and temperature setpoints. - AD synergy: Anaerobic digestion removes ~31% of THP derived refractory material-primarily via physical association-meaning not all recalcitrants recirculate to the liquids line. - PCDD/Fs vigilance: TEQ remains below agronomic thresholds at 165â€¯ °C but rises versus 140â€¯ °C; adopt periodic screening when operating at the upper THP range. - Microbial resilience: High and stable diversity and conserved core functions confirm process robustness across the studied THP temperatures.

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

SpeakerHaddad, Mathieu

Presentation time

11:00:00

11:30:00

Session time

10:30:00

12:00:00

SessionTHP Process Optimization, GHG Reduction and Other Benefits

Session locationKansas City Convention Center

TopicDigestion

Author(s)