The theatre of activity of complex microbial communities underpins the Aerobic Granular Sludge (AGS) systems, resulting in efficient wastewater treatment. Here, we present the first meta-analysis of DNA sequencing data from both published and newly generated AGS samples, aiming to define the “core microbiota” of AGS reactors, consisting of bacteria, archaea, eukaryotes and DNA viruses consistently featured and shared across different scales and operational settings. Briefly, the results indicated that a sequencing depth of at least 10 GB is required to profile the majority of the AGS community, revealed the core taxa, detected the recurrent presence of the uncultured genus ADurb.Bin028 in full-scale reactors and identified Rotaria and Diploscapter, as well as the sessile ciliates Stentor and Thuricola, as the most abundant eukaryotes in AGS. In conclusion, this work provided a taxonomic overview of AGS’ common microbes and addressed potential technical caveats, aiming to establish a reference for future studies.

A highly pure biomethane stream (≈97% CH₄) was produced continuously under halo-alkaline conditions (pH > 9, 0.6 M Na⁺) from complex alkaline organic waste residue originating from biopolymer extraction from sewage sludge. During the proof-of-concept operation, the substrate was degraded with similar efficiency (40% of the volatile solids, VS) compared to neutral conditions (36% of the VS). Operational data was utilised in a technical evaluation to identify bottlenecks for full-scale implementation at an early stage of process development and for comparison to conventional biogas upgrading using pressure swing and membranes. Initially identified bottlenecks for alkaline fermentation were related to overcautious assumptions, while others could be technically solved. Alkaline fermentation offers an attractive method for supplying increasingly needed high-purity biomethane using various recalcitrant substrates that have undergone alkaline pre-treatment. This is more feasible than the conventional ex-situ biogas upgrading. Next, upscaling steps for alkaline fermentation should be pursued. Strategies for integrated CO₂ sequestration and nutrient recovery are outlined, which will offer additional benefits in the future.

The recovery of C, N, and P elements by sludge biorefinery potentially reduces operation costs and increases the extra benefits. Herein, we analyzed the elemental stoichiometry of C, N, and P and functional microbiome involved in enzymatic anaerobic fermentation. Enzymatic hydrolysis was observed to increase the release of C, N, and P into the sludge supernatants by 21.8 %–26.3 %. Metatranscriptome analysis indicated that enzymatic pretreatment enhanced the metabolism of the organic carbon degradation, ammonium conversion, and P solubilization in subsequent fermentation. Specifically, enzymatic pretreatment enhanced endogenous carbon hydrolase activity by 48.4 %–72.7 % and upregulated intra-C metabolic pathways, such as glycolysis and pyruvate metabolism. Ammonium transport and conversion were significantly increased by 4–6 fold, stimulating the synthesis of glutamine and endogenous amino acids. Additionally, enzymatic hydrolysis promoted phosphatase secretion and enhanced bacterial P uptake. These effects improved the recovery of C, N, and P as dentification carbon source and struvite by 13.7 %–41.8 % and the dry sludge production was reduced by 24.3 %–28.1 %. Life cycle assessment (LCA) indicated the shift of CO₂ emissions from net positive to net negative levels as compared to the conventional A²/O process. This study offers valuable insights into the redistribution and metabolism of various elements involved in the enzymatic anaerobic fermentation, and proposes the potential strategy to recovery C, N, and P from sewage via sludge biorefinery.

Fire hydrants are widely installed in drinking water distribution systems, where stagnant water forms multiple ‘high-risk zones’. The stagnant water quality at hydrant terminals has been poorly studied. Here we show that stagnant water exhibited an 18-fold increase in manganese, a 40-fold increase in total cell counts, a 13-fold increase in adenosine triphosphate and enrichment of opportunistic pathogens compared with flowing water. Notable changes were also observed in microbial communities and dissolved organic matter composition, including shifts in dominant bacterial taxa, transformation of saturated oxidized compounds and generation of unsaturated reduced compounds. This study also explored the ecological mechanisms underlying the covariation of microorganisms and dissolved organic matter after water stagnation. This finding provides an additional possibility for drinking water quality deterioration in drinking water distribution systems, highlighting the potential threat posed by stagnant water in non-consumer terminals (fire hydrants) to water safety.

Escalating global freshwater scarcity demands more energy-efficient and sustainable brackish water reverse osmosis (BWRO) desalination. This study demonstrates how integrating high-fidelity Artificial Neural Network (ANN) surrogates with a robust Non-dominated Sorting Genetic Algorithm II (NSGA-II) can deliver reliable multi-objective optimization for pilot-scale BWRO systems. Unlike conventional polynomial response surface models (RSM), which rely on static assumptions and often oversimplify dynamic membrane processes (and exhibit prediction errors of 15–25 %), the proposed framework directly learns the complex, nonlinear relationships among feed salinity, flow rate, pressure, temperature, and membrane type.

Validated against pilot-scale data with R2 > 0.99 and absolute average relative errors below 5 %, the ANN models accurately predict energy consumption (EC) and recovery (Re) under realistic operational conditions. Coupled with NSGA-II, the framework systematically generates Pareto-optimal operating regions that balance low EC (0.6 kWh/m³) with high Re (up to 80 %) while respecting fouling and scaling constraints. This multi-objective approach provides a flexible operating envelope, such as 3–4.5 LPM feed flow and 90–125 psi with higher-permeability membranes, surpassing the limitations of single-point optima. The optimized recovery represents a 3- to 5-fold increase over the typical factory baseline (∼15 %), translating to energy savings of >50 % and CO₂ emission reductions of 0.1–0.2 kg/m³. Sensitivity analysis confirms feed flow rate and pressure as dominant drivers of EC (31.3 % and 28.6 % relative factor) and membrane type and flow rate as primary influencers of Re (32.2 % and 30.2 %).

This optimum region approach surpasses the limitations of traditional single-point design optimization by providing flexible operating envelopes that accommodate seasonal feed variability, equipment aging, and membrane fouling. All models and the optimization framework are shared via an open-source repository to ensure full reproducibility and facilitate industrial adoption.

Overall, this AI-driven multi-objective optimization framework bridges the gap between theoretical performance and field-ready operation, laying the foundation for more adaptive, cost-effective, and climate-smart brackish water desalination. The modular approach is directly adaptable to multi-stage and hybrid systems, offering a scalable and resilient solution to urgent global water scarcity challenges.

Nitrification in biological wastewater treatment is a significant source of nitrous oxide (N2O), a potent greenhouse gas (GHG). There are some models that describe the biological N2O production process, but they don't include abiotic N2O production pathways which, remarkably, contribute up to 50% of the total N2O emissions under high nitrite (NO2-) conditions. This limitation frequently results in pronounced predictive biases under high influent ammonium (NH4+) and intermediate NO2- conditions (such as in the partial nitrification + Anammox system), leading to the misidentification of N2O emissions, undermining the development of effective mitigation strategies. To address this gap, a key abiotic N2O production pathway was integrated into an existing model of nitrification which includes biological N2O emissions. The upgraded model was systematically evaluated using literature-derived case studies, and can effectively predict the contributions of the abiotic pathway to N2O emissions (49%), compared to experimental data (51%). A local sensitivity analysis confirms that the upgraded model has a resilience to perturbations within most parameters, although very high concentrations of NO2- (>1,000 mg N/L) necessitate a precise calibration of ammonium oxidation to nitrite (the AOB process), in which related parameters can more easily be measured in experiments. Moreover, a global sensitivity analysis demonstrates that dissolved oxygen (DO) and alkalinity are the most sensitive of the four key environmental factors (NH4+, NO2-, DO and alkalinity) which control N2O emissions.

Activated sludge (AS) wastewater treatment generates substantial excess sludge which needs to be discarded and thereby increasing operational costs. Extracellular polymeric substances (EPS) within AS present a potential resource for recovery, reducing sludge volume and mass while adding value. Achieving this goal requires a better characterization of EPS, as the relationship between its composition and the microbial communities responsible for its production remains insufficiently understood. Here, we analysed extracted EPS from 16 wastewater treatment plants across 13 countries and 5 continents and found that alkaline extractable EPS yields varied widely (2.81–18.5 wt.% VSS). The microbial community composition of abundant species varied across plants and particularly across continents and did not correlate to the EPS yield. Only sludge retention time had a significant correlation with the EPS yield (p < 0.005). Traditional colorimetric assays failed to detect compositional trends of the EPS, but Fourier Transform Infrared (FTIR) analysis indicated that extracted EPS from biological phosphorus removal systems had higher lipid and polysaccharide content, while chemical phosphorus removal systems had higher relative protein content. Thus, FTIR proved effective for distinguishing extracted EPS composition, demonstrating its potential as a high-throughput characterization tool. These findings highlighted that the wastewater treatment design and operation may shape the functional groups in EPS when using the alkaline method. More investigations are needed to find possible correlations between the composition of extracted EPS and the microbial community structure. Overall, the study presents a baseline for the amount and overall composition of biopolymers that can be extracted from global AS plants for recovery.

Extracellular proteins are supposed to play crucial roles in the formation and structure of biofilms and aggregates. However, often little is known about these proteins, in particular for microbial communities. Here, we use two advanced metaproteomic approaches to study the extracellular proteome in a granular Candidatus Accumulibacter enrichment as a proxy for microbial communities that form solid microbial granules, such as those used in biological wastewater treatment. Limited proteolysis of whole granules and metaproteome isolation from the culture's supernatant successfully classified over 50% of the identified protein biomass to be secreted. Moreover, structural and sequence-based classification identified 387 proteins, corresponding to over 50% of the secreted protein biomass, with characteristics that could aid the formation of aggregates, including filamentous, beta-barrel containing, and cell surface proteins. While various of these aggregate-forming proteins originated from Ca. Accumulibacter, some proteins associated with other taxa. This suggests that not only a range of different proteins but also multiple organisms contribute to granular biofilm formation. Therefore, the obtained extracellular metaproteome data from the granular Ca. Accumulibacter enrichment provides a resource for exploring proteins that potentially support the formation and stability of granular biofilms, whereas the demonstrated approaches can be applied to explore biofilms of microbial communities in general.

The immense microbial diversity on Earth represents a vast genomic resource, yet discovering novel enzymes from complex environments remains challenging. Here, we combine a microbial enrichment with metagenomics and metaproteomics to facilitate the identification of microbial glycoside hydrolases that operate under defined conditions. We enriched microbial communities on the carbohydrate polymer pullulan at elevated temperatures under acidic conditions. Pullulan is a natural polysaccharide composed of maltotriose units linked by α-1,6-glycosidic bonds. Pullulan, along with its hydrolyzing enzymes, has broad applications across various industries. The enrichment inocula were sampled from thermophilic compost and from soil from the bank of a pond. In both cases, Alicyclobacillus was identified as the dominant microorganism. Metaproteomic analysis of the enriched biomass and secretome enabled the identification of several pullulan-degrading enzyme candidates from this organism. These enzymes were absent in the metagenomic analysis of the initial inoculum, which is highly complex with a wide diversity of species. This underscores the effectiveness of combining microbial enrichment with multi-omics for uncovering novel enzymes and sequence variants that operate under defined conditions from complex microbial environments.

This study compares two membrane bioreactor-based enrichment strategies to produce polyhydroxyalkanoates (PHAs) from domestic waste-activated sludge. The aerobic dynamic feeding was implemented in layout 1 while layout 2 employs an aerobic/anoxic enrichment adopting an additional nitritation reactor. Both systems achieved around 38 % w/w of PHA with storage yields of 0.28–0.42 and 0.35–0.53 gCOD_PHA/gCOD_VFA for layouts 1 and 2, respectively. Layout 2 demonstrated an average N removal efficiency of 88.8 ± 3.9 %, slightly higher than layout 1 (82.7 ± 9.9 %). However, layout 2 showed greater nitrous oxide (N₂O) emissions, averaging 0.7 ± 0.2 mg N₂O-N/L almost doubling layout 1 (0.4 ± 0.1 mg N₂O-N/L). Additionally, layout 2 exhibited a 42 % increase in carbon footprint compared to layout 1, reaching 10.2 kg CO₂/day. This research highlights the high potential and drawbacks of the AE/AN enrichment strategy for integrating PHA production into wastewater treatment plant operations.

The hydrolysis of structural extracellular polymeric substances (St-EPS) is considered a major limiting step in the anaerobic fermentation of waste activated sludge (WAS). However, the degradation of heteropolysaccharides, characterized by complex monomers of uronic acids and neutral saccharides in St-EPS, has rarely been reported. In this study, microbial-produced xanthan-like heteropolysaccharides, characterized by a blue filamentary film, were identified. The xanthan-producing bacteria comprised ∼7.2% of total genera present in WAS. An xanthan-degrading consortium (XDC) was enriched in an anaerobic batch reactor. This consortium could degrade Xanthan for over 90% and disrupt the gel structure of xanthan while promoting methane production from WAS by 29%. The xanthan degradation network consisting of extracellular enzymes and bacteria was elucidated by combining high-throughput sequencing, metagenomic, and metaproteomic analyses. Five enzymes were identified as responsible for hydrolyzing xanthan to monomers, including xanthan lyase, β-D-glucosidase, β-D-glucanase, α-D-mannosidase, and unsaturated glucuronyl hydrolase. Seven genera, including Paenibacillus (0.2%) and Clostridium (3.1%), were identified as key bacteria excreting one to five of the aforementioned enzymes. This study thus provides insights into the complex conversions in anaerobic digestion of WAS and gives a foundation for future optimization of this process.

Microorganisms encoding for the N2O reductase (NosZ) are the only known biological sink of the potent greenhouse gas N2O and are central to global N2O mitigation efforts. Clade II NosZ populations are of particular biotechnological interest as they usually feature high N2O affinities and often lack other denitrification genes. We focus on the yet-unresolved ecological constraints selecting for different N2O-reducers strains and controlling the assembly of N2O-respiring communities. Two planktonic N2O-respiring mixed cultures were enriched at low dilution rates under limiting and excess dissolved N2O availability to assess the impact of substrate affinity and N2O cytotoxicity, respectively. Genome-resolved metaproteomics was used to infer the metabolism of the enriched populations. Under N2O limitation, clade II N2O-reducers fully outcompeted clade I affiliates, a scenario previously only theorized based on pure-cultures. All enriched N2O-reducers encoded and expressed the sole clade II NosZ, while also possessing other denitrification genes. Two Azonexus and Thauera genera affiliates dominated the culture, and we hypothesize their coexistence to be explained by the genome-inferred metabolic exchange of cobalamin intermediates. Under excess N2O, clade I and II populations coexisted; yet, proteomic evidence suggests that clade II affiliates respired most of the N2O, de facto outcompeting clade I affiliates. The single dominant N2O-reducer (genus Azonexus) notably expressed most cobalamin biosynthesis marker genes, likely to contrast the continuous cobalamin inactivation by dissolved cytotoxic N2O concentrations (400 μM). Ultimately, our results strongly suggest the solids dilution rate to play a pivotal role in controlling the selection among NosZ clades, albeit the conditions selecting for genomes possessing the sole nosZ remain elusive. We furthermore highlight the potential significance of N2O-cobalamin interactions in shaping the composition of N2O-respiring microbiomes.

Division of metabolic labour is a defining trait of natural and engineered microbiomes. Denitrification-the stepwise reduction of nitrate and nitrite to nitrogenous gases-is inherently modular, catalysed either by a single microorganism (termed complete denitrifier) or by consortia of partial denitrifiers. Despite the pivotal role of denitrification in biogeochemical cycles and environmental biotechnologies, the ecological factors selecting for complete versus partial denitrifiers remain poorly understood. In this perspective, we critically review over 1500 published metagenome-assembled genomes of denitrifiers from diverse and globally relevant ecosystems. Our findings highlight the widespread occurrence of labour division and the dominance of partial denitrifiers in complex ecosystems, contrasting with the prevalence of complete denitrifiers only in simple laboratory cultures. We challenge current labour division theories centred around catabolic pathways, and discuss their limits in explaining the observed niche partitioning. Instead, we propose that labour division benefits partial denitrifiers by minimising resource allocation to denitrification, enabling broader metabolic adaptability to oligotrophic and dynamic environments. Conversely, stable, nutrient-rich laboratory cultures seem to favour complete denitrifiers, which maximise energy generation through denitrification. To resolve the ecological significance of metabolic trade-offs in denitrifying microbiomes, we advocate for mechanistic studies that integrate mixed-culture enrichments mimicking natural environments, multi-meta-omics, and targeted physiological characterisations. These undertakings will greatly advance our understanding of global nitrogen turnover and nitrogenous greenhouse gases emissions.

The post-pandemic world still faces ongoing COVID-19 infections, although international travel has returned to pre-pandemic conditions. Wastewater-based epidemiology (WBE) is considered an efficient tool for the population-wide surveillance of COVID-19 infections during the pandemic. However, the performance of WBE in post-pandemic era with travel restrictions lifted remains unknown. Utilizing weekly county-level wastewater surveillance data from June 2021-November 2022 for 222 counties in 49 states (covering 104 million people) in the United States of America, we retrospectively evaluated the correlations between SARS-CoV-2 RNA (CRNA) and reported cases, as well as the impacts of international air travel, demographics, socioeconomic aspects, test accessibility, epidemiological, and environmental factors on reported cases under the corresponding CRNA. The lifting of travel restrictions in June 2022, shifted the correlation between CRNA and COVID-19 incidence in the following 7-day and 14-day from 0.70 (IQR: 0.30–0.88) in June 2021-May 2022 (pandemic) to 0.01 (IQR: -0.31–0.36) in June-November 2022 (post-pandemic), and from 0.74 (IQR: 0.31–0.90) to -0.01 (IQR: -0.38–0.45), respectively. Besides, after lifting the travel restrictions, under the same CRNA, the reported case numbers were impacted by many factors, including the variations of international passengers, test accessibility, Omicron prevalence, ratio of population aged between 18 and 65, minority vulnerability, and healthcare system. This highlights the importance of demographics, infection testing, variants and socioeconomic status on the accuracy and implication of WBE to monitor COVID-19 infection status in post-pandemic era. Our findings facilitate the public health authorities to dynamically adjust their WBE-based tools/strategies to the local contexts to achieve optimal community surveillance.

Valuable and rare materials in seawater brine are often discarded during desalination. However, there is an increasing focus on recovering these resources, due to the economic and environmental opportunities it can bring. Despite this shift, current Sustainability Assessments (SA) in desalination overlook the brine handling and social dimensions, and brine treatment assessments remain centered on techno-economic dimensions. This work proposes a comprehensive framework for the SA of integrated desalination and resource recovery options, focusing on recovering valuable materials from brine. The framework not only evaluates pre-defined systems but supports the identification of system features of interest, such as products to assess and technologies to include, as well as the transparent selection of indicators, considering specific contexts. To develop this framework, a review of the literature on SA in desalination and brine treatment systems was conducted. Looking at the identified gaps, we synthesized the findings and key messages and proposed the integration of Multi-Criteria Analysis and Value-Sensitive Design in the decision-making process. This allows stakeholders to be involved and incorporates their values at different stages of the assessment, making it distinct from traditional SA methods. This framework offers structured guidance to stakeholders on how to carry out qualitative and quantitative assessments while ensuring transparency in the assessment process.

Sensor availability and costs are nowadays no longer limiting data gathering at wastewater treatment plants (WWTPs). However, one should be aware that a higher amount of measured data gathered does not necessarily imply that also more information is obtained. In this light, this contribution assesses the general applicability and the added value of a structured experimental design approach for planning measurement campaigns at WWTPs, in view of mass-balance-based data reconciliation. To this end, the results from full-scale WWTP case studies available in the literature were compared to those obtained with the developed structured experimental design procedure. Planning measurement campaigns comprises the selection of (additional) measurements to meet a pre-set main goal. The need for a structured experimental design procedure replacing past expert judgment approaches became clear from the fact that three out of five case studies available in the literature failed to meet the main goal and/or performed unnecessary additional measurements. Translating the main goal into specific key variables was found essential in this respect. The general applicability of the procedure was proven with three outcomes. First, the procedure, involving well-defined steps, could be applied to different WWTP layouts. Second, it ensured the fulfilment of various main goals. Third, it provided useful outcomes, i.e., optimal measurement campaigns, which reduced the need for additional measurements (40-70% less) compared to expert knowledge approaches, hence more information could be obtained with less analytical data. Overall, the experimental design procedure proved a fast and useful tool ensuring the success of subsequent mass-balance-based data reconciliation.

城市污水集中收集率是城市污水系统运行效率的关键指标，城市污水污染物排放量是计算城市污水集中收集率的必需参数，但城市污水系统较高溢流量和缺乏溢流监测带来计算城市污水排污量的困扰。为此，应用城市污水系统模型和用水、污水处理、常住人口数等常规市政数据，首次提出了根据污水处理厂进水流量和负荷计算城市污水污染物排放量和污水集中收集率的2种方法。以面积约110 km2、常住居民近100×104 人口的城区污水系统为例，展示了应用2种方法的所需数据、具体步骤和计算结果，分析了2种方法各自的适用性。对流动人口、工商业活动和人日排污量等因素对城市污水污染物排污量的影响和估算进行了讨论。2种方法对当下国内和国外一些国家的城市污水排污量、污水集中收集率的计算和城市污水系统运行效率的评估，具有现实意义。

The centralized collection rate of urban sewage is a key indicator of the operational efficiency of urban sewage systems, urban sewage pollutant loading is an essential parameter for calculating the sewage collection ratio. The high overflow of urban sewage systems and lack of monitoring data pose difficulties in calculating sewage collection ratio. By using the urban sewage system model and regular domestic water consumption and sewage treatment information, this study first time proposed two methods, which were based on the influent flow and pollutant loadings of the sewage treatment plant to calculate the urban sewage pollutant loadings and sewage collection ratio. The applicability of two methods was demonstrated including the required data, specific steps, and calculation results by a case of an urban area with almost 110 km2 square meters and nearly 100×104 inhabitants in a city in the Yangtze Delta area. The applicability of each method was discussed. Furthermore, the effects of the commuters, industry and commercial activities, personal discharge load on the estimation of sewage collection ratio in the cities at different levels of economic development are discussed and analyzed. The methods introduced in this study had practical significance for calculating the sewage collection ratio and evaluating the operation efficiency of urban sewage systems in China and part of the other countries.

Protozoa contribute to water purification through predation in wastewater treatment systems. Full-scale aerobic granular sludge (AGS) reactors treating municipal wastewater contain AGS of varying sizes, with those larger than 2 mm dominating. These size fractions exhibit different sludge morphologies and microbial communities. To date, little is known about protozoan communities and their role in the removal of human-associated bacteria (like pathogens) in AGS plants, particularly across different size fractions. This study conducted uptake experiments with fluorescent Escherichia coli, as a model for human-associated bacteria, followed by microscopic observation to investigate protozoan communities and their predatory behavior in six AGS size fractions and activated sludge collected from full-scale municipal wastewater treatment plants. Sessile ciliates, particularly Epistylis and Vorticella, dominated protozoan populations across six AGS size fractions, with Epistylis being more abundant in larger AGS fractions (>1 mm) and Vorticella in smaller fractions (<1 mm). Additionally, microcosm experiments under aerobic (including predation) and anoxic conditions (excluding predation) revealed that predation was likely to be the main E. coli removal pathway, contributing an additional 0.5 to 2.5 log10CFU mL^–1reduction over a combination of non-predatory biological and abiotic processes. Larger AGS fractions showed greater predation capacity, linked to higher Epistylis abundance, while activated sludge, dominated by Vorticella, resembled smaller AGS fractions with lower predation capacity. These findings advance the understanding of the distribution of protozoan communities and their contribution to E. coli removal by predation in AGS wastewater treatment.

To meet the increasing drinking water demand, membrane technologies are used to treat previously unavailable water sources. A byproduct of membrane technologies is the concentrate stream, containing valuable resources in higher concentrations. We studied the recovery of iron from different groundwater matrices and anaerobic reverse osmosis (RO) concentrates via precipitation of vivianite and the co-removal of other common groundwater divalent cations Mn²⁺, Mg²⁺ and Ca²⁺ during vivianite precipitation. The formed precipitates were characterized using X-Ray Diffraction and Scanning Electron Microscopy. Vivianite precipitation removed a maximum of 89 % of Fe²⁺ in raw groundwater and 52 % Fe²⁺ from RO concentrate. Substantial co-removal of Mn²⁺ (max 91 %) and limited co-removal of Mg²⁺ (max 7 %) were found, without hindering Fe removal efficiencies or altering morphological changes of the vivianite crystal. In contrast, co-removal of Ca²⁺ occurred at the expense of iron removal, forming amorphous calcium phosphate precipitates. This study shows the potential of vivianite precipitation for iron recovery across a wide range of groundwater matrices and highlights the need for further research to optimize this novel method to treat concentrate streams that are challenging to dispose of.

Polyhydroxyalkanoate (PHA) production is a promising technology fostering the spread of the circular bio-economy approach. However, the environmental implication of the process is usually neglected. This paper shows the results of a membrane-based PHA production pilot plant fed with no-pretreated waste activated sludge (WAS). The system was monitored for effluent water quality, nitrous oxide (N₂O), and PHA production by dynamic accumulation over a long-term period to assess the consistency of the results over several fluctuations. The experimental study was characterized by three C/N ratios of 9, 4.5, and 4 g COD/g N. The system achieved a stable and high removal efficiency for carbon and nitrogen (96.3 ± 2.6 % and 89.9 ± 6.7 %, respectively), despite the only legislation limit respected being the biological oxygen demand concentration discharge limits imposed by 2020/741/EU. Low N₂O gaseous and liquid concentrations were achieved over the 200-day experimental period, never exceeding 0.52 mg N₂O-N/L. Despite the high concentration, the N₂O emission factor accounted for only 0.21 ± 0.14 % of the influent nitrogen. Finally, the system produced an average of 36.3 ± 1.8 % g PHA/g VSS with a storage yield of up to 0.42 g COD_PHA/g COD_VFA. The system revealed a high stability over a long-term experimental period, achieving a considerable amount of PHA while maintaining a low N₂O emission. Promising effluent water quality was achieved, highlighting the potential of applying the water reuse practices.