Reconsidering hydrolysis kinetics for anaerobic digestion of waste activated sludge applying cascade reactors with ultra-short residence times

Designing synthetic microbial communities for enhanced anaerobic waste treatment

Synthetic microbial communities (SynComs) are powerful tools for investigating microbial interactions and community assembly by focusing on minimal yet functionally representative members. Here, we will highlight key principles for designing SynComs, specifically emphasizing the anaerobic digestion (AD) microbiome for waste treatment and upcycling. The AD process has traditionally been used to reduce organic waste volume while producing biogas as a renewable energy source. Its microbiome features well-defined trophic layers and metabolic groups. There has been growing interest in repurposing the AD process to produce value-added products and chemical precursors, contributing to sustainable waste management and the goals of a circular economy. Optimizing the AD process requires a better understanding of microbial interactions and the influence of both biotic and abiotic parameters, where SynComs offer great promise. Focusing on AD microbiomes, we review the principles of SynComs' design, including keystone taxa and function, cross-feeding interactions, and metabolic redundancy, as well as how modeling approaches could guide SynComs design. Furthermore, we address practical considerations for working with AD SynComs and examine constructed SynComs designed for anaerobic waste digestion. Finally, we discuss the challenges associated with designing and applying SynComs to enhance our understanding of the AD process. This review aims to explore the use of synthetic communities in studying anaerobic digestion and highlights their potential for developing innovative biotechnological processes.

Pilot-scale evaluation of cascade anaerobic digestion of mixed municipal wastewater treatment sludges

This work assessed the performance of a pilot-scale cascade anaerobic digestion (AD) system when treating mixed municipal wastewater treatment sludges. The cascade system was compared with a conventional continuous stirred tank reactor (CSTR) digester (control) in terms of process performance, stability, and digestate quality. The results showed that the cascade system achieved higher volatile solids removal (VSR) efficiencies (28-48%) than that of the reference (25-41%) when operated at the same solids residence time (SRT) in the range of 11-15 days. When the SRT of the cascade system was reduced to 8 days the VSR (32-36%) was only slightly less than that of the reference digester that was operated at a 15-day SRT (39-43%). Specific hydrolysis rates in the first stage of the cascade system were 66-152% higher than those of the reference. Additionally, the cascade system exhibited relatively stable effluent concentrations of volatile fatty acids (VFAs: 100-120 mg/l), while the corresponding concentrations in the control effluent demonstrated greater fluctuations (100-160 mg/l). The cascade system's effluent pH and VFA/alkalinity ratios were consistently maintained within the optimal range. During a dynamic test when the feed total solids concentration was doubled, total VFA concentrations (85-120 mg/l) in the cascade system were noticeably less than those (100-170 mg/l) of the control, while the pH and VFA/alkalinity levels remained in a stable range. The cascade system achieved higher total solids (TS) content in the dewatered digestate (19.4-26.8%) than the control (17.4-22.1%), and E. coli log reductions (2.0-4.1 log MPN/g TS) were considerably higher (p < 0.05) than those in the control (1.3-2.9 log MPN/g TS). Overall, operating multiple CSTRs in cascade mode at typical SRTs and mixed sludge ratios enhanced the performance, stability digesters, and digestate quality of AD. PRACTITIONER POINTS: Enhanced digestion of mixed sludge digestion with cascade system. Increased hydrolysis rates in the cascade system compared to a reference CSTR. More stable conditions for methanogen growth at both steady and dynamic states. Improved dewaterability and E. coli reduction of digestate from the cascade system.

Performance and microbial community composition of full-scale high-rate cascade sludge digestion system via pie-shaped reactor configuration

A full-scale high-rate cascade anaerobic digestion (CAD) system was evaluated for its ability to enhance enzymatic sludge hydrolysis. The system included a newly built digester, innovatively divided into three pie-shaped compartments (500 m3 each), followed by an existing, larger digester (1500 m3). The system treated a mixture of waste activated sludge and primary sludge, achieving a stable total chemical oxygen demand reduction efficiency (56.1 ± 6.8 %), and enhanced sludge hydrolytic enzyme activities at a 14.5-day total solids retention time (SRT). High-throughput sequencing data revealed a consistent microbial community across reactors, dominated by consortia that govern hydrolysis and acidogenesis. Despite relatively short SRTs in the initial reactors of the CAD system, acetoclastic methanogens belonging to Methanosaeta became the most abundant archaea. ‬‬‬‬‬‬‬‬‬‬‬‬‬ This study proves that the CAD system achieves stable sludge reduction, accelerates enzymatic hydrolysis at full-scale, and paves the way for its industrialization in municipal waste sewage sludge treatment.

Bacterial community composition in a two-stage anaerobic membrane bioreactor for co-digestion of food waste and food court wastewater

This study investigated the microbial community of a two-stage anaerobic membrane bioreactor (2S-AnMBR) co-digesting food waste and food court wastewater. The hydrolysis reactor (HR) was dominated by Bacteroidetes and Firmicutes phylum, with genus Lactobacillus enriched due to food waste fermentation. The up-flow anaerobic sludge blanket (UASB) was dominated by genus such as Methanobacterium and Methanosaeta. The presence of Methanobacterium (91 %) and Methanosaeta (7.5 %) suggested that methane production pathways inevitably undergo both hydrogenotrophic and acetoclastic methanogenesis. Hydrogen generated during hydrolysis fermentation in the HR contributed to methane production in the UASB via hydrogenotrophic pathways. However, the low abundance of Methanosaeta in the UASB can be attributed to the limited inffluent of volatile fatty acids (VFA) and the competitive presence of acetate-consuming bacteria Acinetobacter. The UASB exhibited more excellent dispersion and diversity of metabolic pathways compared to the HR, indicating efficient methane production.

A pilot study of situ sludge fermentation-driven multiple biological nitrogen removal pathways (SFBNR): Revealing microbial synergy mechanism based on co-occurrence network analysis

The sludge fermentation-driven biological nitrogen removal (SFBNR) has garnered increasing attention due to its efficient carbon resource utilization from waste activated sludge (WAS). This study successfully extended the application of this technique to a 38 m3 reactor, facilitating a daily ultra-low carbon to nitrogen ratio (<1) wastewater treatment capacity of 16 tons and a WAS capacity of 500 L. After 185-days operation, the system demonstrated commendable performance with a denitrification efficiency (DNE) of 93.22 % and a sludge reduction efficiency (SRE) of 72.07 %. To better understand the potential mechanisms, various functional bacteria interactions were revealed by co-occurrence network analysis. The results unveiled module hubs (e.g., Anaerolineaceae, Denitratisoma, and Candidatus Brocadia) and connectors (e.g., Tuaera and Candidatus Alysiosphaera) in the network exhibited synergistic relationships facilitated by carbon metabolism and nitrogen cycling. Furthermore, the interaction between biofilm sludge (BS) and suspended sludge (SS) contributed to the in-situ enrichment of anaerobic ammonium oxidizing bacteria (AnAOB), whose abundance in BS reached 1.8 % (200-times higher than in SS) after six months, and the suspend-biofilm interface served as a hotspot for anammox activity.

Nanobubbles in water and wastewater treatment systems: Small bubbles making big difference

Since the discovery of nanobubbles (NBs) in 1994, NBs have been attracting growing attention for their fascinating properties and have been studied for application in various environmental fields, including water and wastewater treatment. However, despite the intensive research efforts on NBs' fundamental properties, especially in the past five years, controversies and disagreements in the published literature have hindered their practical implementation. So far, reviews of NB research have mainly focused on NBs' role in specific treatment processes or general applications, highlighting proof-of-concept and success stories primarily at the laboratory scale. As such, there lacks a rigorous review that authenticates NBs' potential beyond the bench scale. This review aims to provide a comprehensive and up-to-date analysis of the recent progress in NB research in the field of water and wastewater treatment at different scales, along with identifying and discussing the challenges and prospects of the technology. Herein, we systematically analyze (1) the fundamental properties of NBs and their relevancy to water treatment processes, (2) recent advances in NB applications for various treatment processes beyond the lab scale, including over 20 pilot and full-scale case studies, (3) a preliminary economic consideration of NB-integrated treatment processes (the case of NB-flotation), and (4) existing controversies in NBs research and the outlook for future research. This review is organized with the aim to provide readers with a step-by-step understanding of the subject matter while highlighting key insights as well as knowledge gaps requiring research to advance the use of NBs in the wastewater treatment industry.

Restructuring anaerobic hydrolysis kinetics in plant-wide models for accurate prediction of biogas production

In this study, the effect of anaerobic hydrolysis rate on biogas production was investigated with mesophilic digesters in seven large-scale wastewater treatment plants. A linear correlation was determined between the percentage of primary sludge mass in the total sludge fed to the digester and the overall anaerobic hydrolysis rate. The anaerobic hydrolysis rate of primary sludge was determined to be three times higher than that of biological sludge. The reduction factors for anaerobic hydrolysis (ηHYD,ana) were identified in the range of 0.11-0.30 which is lower compared to the recommended range (0.30-0.50) given in the literature. This study proposes a new model approach where anaerobic degradation kinetics of influent originated (XB) and decay originated (XB,E) particulate biodegradable organics are separated. Current plant-wide models with a single kinetic expression required recalibration of the model for calculating biogas flowrate for each treatment facility with different primary and secondary sludge ratios fed to the digesters. The new model structure is able to predict biogas production of all wastewater treatment plants without any recalibration effort by segregating degradation kinetics of two particulate biodegradable organic fractions (XB, XB,E).

Volatile fatty acids bio-production using extracellular polymeric substances disengaged from sludge for carbon source recycling

Excessive waste-activated sludge (WAS) and insufficient carbon source (CS) for biological nitrogen removal (BNR) often coexist in municipal sewage treatment. Although the production of volatile fatty acids (VFAs) from WAS has been recognized as a promising solution, the development is limited by low VFAs production efficiency and dewatering deterioration of sludge. This study extracted the extracellular polymeric substances (EPS) from sludge by low-temperature thermal-hydrolysis (LTH) and high-speed hydro-cyclone (HSHC) pretreatment and recovered it for high-quality VFAs bio-production in thermophilic fermentation. Microbial mechanism analysis disclosed that interspecific interaction networks composed of functional flora, which accumulate VFAs by bio-converting EPS primarily and supplemented by EPS synthesis, guaranteed the efficient bio-production of VFAs. This process scheme shows promise in providing alternative denitrification CSs and avoiding deterioration of sludge dewaterability.

Physics-informed neural network-based serial hybrid model capturing the hidden kinetics for sulfur-driven autotrophic denitrification process

Sulfur-driven autotrophic denitrification (SdAD) is a biological process that can remove nitrate from low carbon/nitrogen (C/N) ratio wastewater. Although this process has been intensively researched, the mechanism whereby its intermediates (i.e., elemental sulfur and nitrite ions) are generated and accumulated remains elusive. Existing mathematical models developed for SdAD cannot accurately predict the intermediates in SdAD because of the incomplete knowledge of process kinetic resulting from changes in the environmental conditions and electron competition during SdAD. To address this limitation, we proposed a novel serial hybrid model structure based on a physics-informed neural network (PINN) to capture the dynamics of the process kinetics and predict the substrate concentrations in SdAD. In this study, we evaluated the model through numerical experiments and applied it to real case studies involving batch and continuous-flow reactor scenarios. By leveraging the PINN approach, the hybrid model yielded accurate predictions at both the state (i.e. substrate concentration) and kinetic levels in the numerical experiments and performed better than both mechanistic and purely data-driven models in the case studies. Furthermore, we used the trained hybrid model to design control strategies for SdAD and a novel integrated process involving SdAD and anammox for energy-efficient nitrogen removal. Finally, we discuss the advantages and application scope of the PINN-based hybrid model.

Impact of sandwich-type composite anodic membrane on membrane fouling and methane recovery from sewage sludge and food waste via electrochemical anaerobic membrane bioreactor

Membrane fouling presents a big challenge for the real-world implementation of anaerobic membrane bioreactors (AnMBRs) in digesting high-solid biowastes. In this study, an electrochemical anaerobic membrane bioreactor (EC-AnMBR) with a novel sandwich-type composite anodic membrane was designed and constructed for controlling membrane fouling whilst improving the energy recovery. The results showed that EC-AnMBR produced a higher methane yield of 358.5 ± 74.8 mL/d, rising by 12.8% compared to the AnMBR without applied voltage. Integration of composite anodic membrane induced a stable membrane flux and low transmembrane pressure through forming an anodic biofilm while total coliforms removal reached 97.9%. The microbial community analysis further provided compelling evidence that EC-AnMBR enriched the relative abundance of hydrolyzing (Chryseobacterium 2.6%) bacteria and methane-producing (Methanobacterium 32.8%) archaea. These findings offered new insights into anti-biofouling performance and provided significant implications for municipal organic waste treatment and energy recovery in the new EC-AnMBR.

Decreasing lactate input for cost-effective sulfidogenic metal removal in sulfate-rich effluents: Mechanistic insights from (bio)chemical kinetics to microbiome response

High material cost is the biggest barrier for the industrial use of low-molecular-weight organics (i.e. lactate) as external carbon and electron source for sulfidogenic metal removal in sulfate-rich effluents. This study aims to provide mechanistic evidence from kinetics to microbiome analysis by batch modeling to support the possibility of decreasing the lactate input to achieve cost-effective application. The results showed that gradient COD/SO42- ratios at a low level had promising treatment performance, reaching neutralized pH with nearly total elimination of COD (91%-99%), SO42- (85%-99%), metals (80%-99%) including Cu, Zn, and Mn. First-order kinetics exhibited the best fit (R2 = 0.81-0.98) to (bio)chemical reactions, and the simulation results revealed that higher COD/SO42- accelerated the reaction rate of SO42- and COD but not suitable to that of metals. On the other hand, we found that the decreasing COD/SO42- ratio increased average path distance but decreased clustering coefficient and heterogeneity in microbial interaction network. Genetic prediction found that the sulfate-reduction-related functions were significantly correlated with the reaction kinetics changed with COD/SO42- ratios. Our study, combining reaction kinetics with microbiome analysis, demonstrates that the use of lactate as a carbon source under low COD/SO42- ratios entails significant efficiency of metal removal in sulfate-rich effluent using SRB-based technology. However, further studies should be carried out, including parameter-driven optimization and life cycle assessments are necessary, for its practical application.

Hydrochar mediated anaerobic digestion of bio-wastes: Advances, mechanisms and perspectives

Bio-wastes treatment and disposal has become a challenge because of their increasing output. Given the abundant organic matter in bio-wastes, its related resource treatment methods have received more and more attention. As a promising strategy, anaerobic digestion (AD) has been widely used in the treatment of bio-wastes, during which not only methane as energy can be recovered but also their reduction can be achieved. However, AD process is generally disturbed by some internal factors (e.g., low hydrolysis efficiency and accumulated ammonia) and external factors (e.g., input pollutants), resulting in unstable AD operation performance. Recently, hydrochar was wildly found to improve AD performance when added to AD systems. This review comprehensively summarizes the research progress on the performance of hydrochar-mediated AD, such as increased methane yield, improved operation efficiency and digestate dewatering, and reduced heavy metals in digestate. Subsequently, the underlying mechanisms of hydrochar promoting AD were systematically elucidated and discussed, including regulation of electron transfer (ET) mode, microbial community structure, bio-processes involved in AD, and reaction conditions. Moreover, the effects of properties of hydrochar (e.g., feedstock, hydrothermal carbonization (HTC) temperature, HTC time, modification and dosage) on the improvement of AD performance are systematically concluded. Finally, the relevant knowledge gaps and opportunities to be studied are presented to improve the progress and application of the hydrochar-mediated AD technology. This review aims to offer some references and directions for the hydrochar-mediated AD technology in improving bio-wastes resource recovery.

Augmentation in polyhydroxybutyrate and biogas production from waste activated sludge through mild sonication induced thermo-fenton disintegration

In this study, an innovative approach was developed to enhance the hydrolysis through phase-separated pretreatment by removing exopolymeric substances via mild sonication followed by thermo-Fenton disintegration. The exopolymeric substances fragmentation was enhanced at the sonic specific energy input of 2.58 kJ/kg total solids. After exopolymeric substance removal, the disintegration of biomass by thermo-Fenton yield the solubilization of 29.8 % at Fe²⁺:H₂O₂ dosage and temperature of 0.009:0.036 g/g suspended solids and 80 °C as compared to thermo-Fenton alone disintegration. The polyhydroxybutyrate content of 93.1 % was accumulated by Bacillus aryabhattai at the optimum time of 42 h, while providing 70 % (v/v) pre-treated supernatant as a carbon source under nutrient-limiting condition. Moreover, the biogas generation of 0.187 L/g chemical oxygen demand was achieved using settled pretreated sludge. The pretreated sludge sample thus served as a carbon source for polyhydroxybutyrate producers as well as substrate for biogas production.

Implementing machine learning to optimize the cost-benefit of urban water clarifier geometrics

Clarification basins are ubiquitous water treatment units applied across urban water systems. Diverse applications include stormwater systems, stabilization lagoons, equalization, storage and green infrastructure. Residence time (RT), surface overflow rate (SOR) and the Storm Water Management Model (SWMM) are readily implemented but are not formulated to optimize basin geometrics because transport dynamics remain unresolved. As a result, basin design yields high costs from hundreds of thousands to tens of million USD. Basin optimization and retrofits can benefit from more robust and efficient tools. More advanced methods such as computational fluid dynamics (CFD), while demonstrating benefits for resolving transport, can be complex and computationally expensive for routine applications. To provide stakeholders with an efficient and robust tool, this study develops a novel optimization framework for basin geometrics with machine learning (ML). This framework (1) leverages high-performance computing (HPC) and the predictive capability of CFD to provide artificial neural network (ANN) development and (2) integrates a trained ANN model with a hybrid evolutionary-gradient-based optimization algorithm through the ANN automatic differentiation (AD) functionality. ANN model results for particulate matter (PM) clarification demonstrate high predictive capability with a coefficient of determination (R²) of 0.998 on the test dataset. The ANN model for total PM clarification of three (3) heterodisperse particle size distributions (PSDs) also illustrates good performance (R²>0.986). The proposed framework was implemented for a basin and watershed loading conditions in Florida (USA), the ML basin designs yield substantially improved cost-effectiveness compared to common designs (square and circular basins) and RT-based design for all PSDs tested. To meet a presumptive regulatory criteria of 80% PM separation (widely adopted in the USA), the ML framework yields 4.7X to 8X lower cost than the common basin designs tested. Compared to the RT-based design, the ML design yields 5.6X to 83.5X cost reduction as a function of the finer, medium, and coarser PSDs. Furthermore, the proposed framework benefits from ANN's high computational efficiency. Optimization of basin geometrics is performed in minutes on a laptop using the framework. The framework is a promising adjuvant tool for cost-effective and sustainable basin implementation across urban water systems.

Consideration of biological and inorganic additives in upgraded anaerobic digestion BioModel

This paper deals with the numerical simulation of biogas production in the anaerobic digestion process of organic waste. Special attention is focused on the modeling of the activities of biological and inorganic additives, which are used to enhance the process and reduce H₂S content in the biogas. For this purpose, an existing BioModel is upgraded with the modified Michaelis-Menten kinetics in order to model the enzymatic hydrolysis and with adequate modeling of physicochemical processes. The upgraded BioModel was calibrated with experimental data obtained from a full-scale biogas plant, used in combination with an active set optimization procedure; the relative agreement indices were 0.9376, 0.9419, 0.7957, and 0.7663 for biogas, CH₄, H₂, and H₂S flow rates, respectively. Statistical efficiency criteria differ up to 5% in model calibration and validation. The obtained results confirm the importance of additives modeling and the usefulness of the proposed model for industrial biogas plants' performance improvement.

Quorum quenching of autoinducer 2 increases methane production in anaerobic digestion of waste activated sludge

The ubiquitous signaling molecule autoinducer 2 (AI-2) is involved in intra- and interspecies communication, most notably between Gram-negative and Gram-positive bacteria. AI-2 accumulates during the exponential phase of the Escherichia coli (E. coli) monoculture and then rapidly decreases upon entry into the stationary phase. However, deleting both the genes encoding AI-2 synthase (LuxS) and the lsr operon regulator (LsrR) in the E. coli genome causes impaired AI-2 production and continuous AI-2 scavenging from the environment. This genetically-engineered E. coli mutant capable of quenching AI-2 quorum sensing (QS) system was utilized to evaluate the effect of AI-2 quenching on the anaerobic digestion of waste activated sludge (WAS) because the role of QS system via AI-2 in the process remains obscure. In this study, E. coli ∆luxS lsrR mutant cells were microencapsulated in sodium alginate beads and incubated with WAS anaerobically. After 15 days of anaerobic fermentation, the WAS containing double mutant cells produced significantly more methane than that of the parent E. coli cells. AI-2 quenching occurred concurrently with a shift of microbial communities that contribute to increasing acetate consumption by the Methanosarcina spp. resulting in an increase in methane production. KEY POINTS: • Impact of autoinducer 2 quenching in complex bacterial populations were determined. • Key microorganisms contributing to the increase of methane in WAS anaerobic digestion were found. • The AI-2 quenching is a potential regulatory in wastewater treatment and bioenergy research.

Optimising the Flux Enhancer Dosing Strategy in a Pilot-Scale Anaerobic Membrane Bioreactor by Mathematical Modelling

Flux enhancers (FEs) have been successfully applied for fouling mitigation in membrane bioreactors. However, more research is needed to compare and optimise different dosing strategies to improve the filtration performance, while minimising the use of FEs and preventing overdosing. Therefore, the goal of this research is to develop an optimised control strategy for FE dosing into an AnMBR by developing a comprehensive integrated mathematical model. The integrated model includes filtration, flocculation, and biochemical processes to predict the effect of FE dosing on sludge filterability and membrane fouling rate in an AnMBR. The biochemical model was based on an ADM1, modified to include FEs and colloidal material. We developed an empirical model for the FE-induced flocculation of colloidal material. Various alternate filtration models from the literature and our own empirical models were implemented, calibrated, and validated; the best alternatives were selected based on model accuracy and capacity of the model to predict the effect of varying sludge characteristics on the corresponding output, that is fouling rate or sludge filterability. The results showed that fouling rate and sludge filterability were satisfactorily predicted by the selected filtration models. The best integrated model was successfully applied in the simulation environment to compare three feedback and two feedforward control tools to manipulate FE dosing to an AnMBR. The modelling results revealed that the most appropriate control tool was a feedback sludge filterability controller that dosed FEs continuously, referred to as ∆R20_10. Compared to the other control tools, application of the ∆R20_10 controller resulted in a more stable sludge filterability and steady fouling rate, when the AnMBR was subject to specific disturbances. The simulation environment developed in this research was shown to be a useful tool to test strategies for dosing flux enhancer into AnMBRs.

Insights into the Anaerobic Hydrolysis Process for Extracting Embedded EPS and Metals from Activated Sludge

The amount of sewage sludge generated from wastewater treatment plants globally is unavoidably increasing. In recent years, significant attention has been paid to the biorefinery concept based on the conversion of waste streams to high-value products, material, and energy by microorganisms. However, one of the most significant challenges in the field is the possibility of controlling the microorganisms’ pathways in the anaerobic environment. This study investigated two different anaerobic fermentation tests carried out with real waste activated sludge at high organic loading rate (10 g COD L⁻¹d⁻¹) and short hydraulic retention time (HRT) to comprehensively understand whether this configuration enhances extracellular polymeric substance (EPS) and metal solubilisation. The quantity of EPS recovered increased over time, while the chemical oxygen demand to EPS ratio remained in the range 1.31–1.45. Slightly acidic conditions and sludge floc disintegration promoted EPS matrix disruption and release, combined with the solubilisation of organically bound toxic metals, such as As, Be, Cu, Ni, V, and Zn, thereby increasing the overall metal removal efficiency due to the action of hydrolytic microorganisms. Bacteroidetes, Firmicutes, and Chloroflexi were the most abundant phyla observed, indicating that the short HRT imposed on the systems favoured the hydrolytic and acidogenic activity of these taxa.