Organic micropollutants (OMPs) are commonly detected in municipal wastewater. Conventional activated sludge processes partially remove these compounds, allowing them to enter receiving waters and pose ecological risks. Biotransformation, governed by microbial community composition and activity, is the main pathway for OMP removal. Aerobic granular sludge (AGS), with its distinct structure and microbial communities compared to conventional activated sludge, has emerged as a promising alternative. Full-scale AGS reactors contain predominately large granules (>1 mm), alongside medium (0.2–1 mm), and small (<0.2 mm) fractions, which differ in morphology and microbial composition and may influence OMP biotransformation. To date, the potential of different AGS size fractions for OMP biotransformation at environmentally relevant concentrations (1 µg L−1) remains poorly understood. This study evaluated the biotransformation of 23 OMPs (pharmaceuticals and industrial compounds) under nitrifying, aerobic heterotrophic, and denitrifying conditions, using batch microcosm with six AGS size fractions collected from a full-scale AGS plant. Eight OMPs (sulfamethoxazole, atenolol, furosemide, benzotriazole, trimethoprim, diclofenac, metoprolol, and gabapentin) showed biotransformation efficiencies above 10 % under at least one condition. Under aerobic conditions, smaller fractions showed higher biotransformation rate (Kbio), reflecting increased nitrifier and aerobic heterotroph activity. Under denitrifying conditions, three OMPs were biotransformed > 10 %, but Kbio did not correlate clearly with denitrifying activity, likely due to heterogeneous denitrifier distribution across size fractions. At the system level, AGS showed slightly lower Kbio than activated sludge, as smaller, more active AGS fractions comprised less than 40 % of total biomass in full-scale reactors. This study is the first to assess OMP biotransformation across AGS size fractions, highlighting the combined effects of granule size and bioconversion conditions. The findings provide insights for optimizing AGS systems, including potential granule size adjustments, to enhance OMP biotransformation and reduce environmental impacts.

Cow-dung is a widely used stabiliser applied in traditional earthen buildings with one objective to improve water resistance. However, most research has focused on explaining its mechanical strength, with only one study suggesting water resistance mechanism via formation of insoluble compounds at high pH, a phenomenon uncommon in natural cow dung and soil mixtures. This article investigates the water-resistance behaviour of cow-dung stabilised compressed earthen blocks (CD-CEBs) through an extensive experimental programme to understand the influence of cow-dung and soil related factors and to characterise the components of cow-dung responsible for its water resistance. It was found that the small-sized microbial aggregates (SSMA) present in cow-dung, which are negatively charged hydrophobic aggregates of low specific surface area, are responsible for enhanced water resistance of CD-CEBs. The insights gained from experiments are compiled to recommend the following strategies for improved performance of CD-CEBs: (i) The use of wet cow-dung is advised over dry cow-dung as it provided over 80 times better water resistance; (ii) Adopting a higher compaction liquid content (by 3%) improved the water resistance by over 40 times; (iii) The water resistance of CD-CEBs was improved over 30 times by using soils rich in low-swelling clay minerals such as kaolinite. A case study applying these findings demonstrates the successful scaleup from the lab to field showcasing potential of cow-dung and soil in low-carbon construction.

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.

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.

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.

The authors regret that an inconsistency was identified between the results presented in Fig. 6 and the inventory data reported in Tables S.11 and S.12 of the Supplementary Information. This discrepancy arose because an additional scenario from a previous version of the manuscript was inadvertently retained in the Supplementary Information, although it was not included in the final published article. As a result, the scenario numbering in the Supplementary Information did not correspond to the scenarios discussed in the main text, leading to apparent inconsistencies for Climate change and Marine ecotoxicity results for Scenario 3. The Supplementary Information has now been corrected by removing the tables related to the excluded scenario and aligning the remaining scenario numbering with the final version of the article. The results presented in the main article remain unchanged. The authors would like to apologise for any inconvenience caused.

Riverbank filtration is a nature-based water treatment strategy known for its effective removal of organic micropollutants. Yet, the mechanisms governing their biodegradation, especially the role of redox transitions in mediating biotransformation, remain insufficiently understood. Here, we integrate metagenomic profiling with chemical analytics in a 10 m simulated riverbank filtration system to demonstrate how sequential oxidizing–reducing degradation enhances organic micropollutant transformation. Oxygen stratification structured distinct microbial and enzymatic pathways: oxidizing zones (>+200 mV redox potential) facilitated cytochrome P450-mediated oxidation (oxidizing condition, OXD), while subsequent redox shifts to reducing conditions (←400 mV, sequential oxidizing–reducing (SOR) conditions) activated reductive transformations (e.g., via nitronate monooxygenase and aldehyde dehydrogenase) and conjugation pathways. These SOR conditions significantly enhanced the removal of recalcitrant compounds, including irbesartan (+25.3%), benzotriazole (13.4%), and gabapentin (+9.7%). Metagenomic analysis revealed redox-driven microbial specialization, with Pseudomonadota and Nitrospirota dominating in oxidizing zones and reducing microzones enriched in pathways associated with nitrotoluene and ethylbenzene degradation, providing genomic evidence for sequential organic micropollutant breakdown. These findings establish a mechanistic framework for harnessing oxidizing–reducing microbial partnerships to amplify organic micropollutant removal in nature-based water treatment systems, which can be used for riverbank filtration site selection and well field construction and optimization.

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.

Wastewater treatment is a major source of global greenhouse gas (GHG) emissions, largely driven by nitrous oxide (N2O) release during nitrogen removal processes. While anaerobic ammonium-oxidizing (anammox) bacteria have become widely adopted to optimize nitrogen removal, the pathways governing N2O emissions in anammox systems remain insufficiently characterized. Findings revealed that in aerobic environments with low dissolved oxygen, nitrifying microorganisms showed pronounced upregulation of N2O synthesis genes, confirming their pivotal role in emissions. Conversely, heterotrophic denitrification dominated N2O production in anaerobic systems. Crucially, anammox-dominated biofilms displayed substantially lower expression of N2O-related genes compared to suspended sludge, suggesting reduced emission risks in biofilm configurations. Batch experiments demonstrated a 2.78-fold lower N2O release from biofilms than suspended biomass. This mitigation was linked to restricted substrate transport within biofilms, which curbed NO2− buildup and subsequently suppressed nitrifier-derived N2O formation. Additionally, the high-density colonization of anammox bacteria in biofilms efficient scavenging of nitric oxide (NO) and hydroxylamine (NH2OH), critical intermediates in N2O synthesis. Employing an integrated multi-omics approach, this study investigates N2O production and consumption pathways in diverse anammox systems and unveils the N2O mitigation mechanisms of biofilms, offering fundamental insights for reducing N2O emissions in wastewater treatment.

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 long-term effects of environmental conditions, such as seawater salinity, on the extracellular investigated EPS changes during a stepwise increase in salinity (0–4%), renewing over 90% of biomass at each condition. Stable granulation, complete anaerobic acetate uptake, and phosphate removal were maintained throughout. FT-IR of granules showed significant changes in glycans (1025 cm⁻¹) and sialic acid (1730 cm⁻¹), which were reflected in the EPS. Lectin microarray revealed that increasing salinity reduced glycan diversity in EPS glycoproteins, while increasing negatively charged groups, including sialic acids and sulfated groups. At 4% salinity, EPS negative charge increased by 19.8% compared to 0%. Microbial community composition shifted from a diverse mix (Dechloromonas; 23%, “Candidatus Competibacter”; 13%, “Candidatus Accumulibacter”; 28%) at 0% to a dominant (69% – 75%) unclassified Accumulibacter clade I species at 1 - 4% salinity. Metaproteomic analysis showed strong upregulation of genes of “Ca. Accumulibacter” involved in monosaccharide, lipopolysaccharide, and peptidoglycan biosynthesis from 3% - 4% salinity, indicating its adaptation to salinity stress. Dechloromonas and “Ca. Competibacter” represented a minor or a non-significant fraction of those proteins related to glycan synthesis across the salinities. Despite that no glycoprotein biosynthesis pathways were identified in the metaproteomic data, three putative glycoproteins produced by “Ca. Accumulibacter” were detected across all conditions. They were downregulated as the salinity increased. These findings highlight how “Ca.Accumulibacter” dynamically adapts its EPS, particularly glycoprotein glycans, in response to increasing salinity, offering new insights into EPS adaptation under environmental stress.

Wastewater-based surveillance has become a powerful tool for monitoring the spread of pathogens, antibiotic resistance genes, and measuring population-level exposure to pharmaceuticals and chemicals. While surveillance methods commonly target small molecules, DNA, or RNA, wastewater also contains a vast spectrum of proteins. However, despite recent advances in environmental proteomics, large-scale monitoring of protein biomarkers in wastewater is still far from routine. Analyzing raw wastewater presents a challenge due to its heterogeneous mixture of organic and inorganic substances, microorganisms, cellular debris, and various chemical pollutants. To overcome these obstacles, we developed a wastewater metaproteomics approach including efficient protein extraction and an optimized data-processing pipeline. The pipeline utilizes de novo sequencing to customize large public sequence databases to enable comprehensive metaproteomic coverage. Using this approach, we analyzed wastewater samples collected over approximately three months from two urban locations. This revealed a core microbiome comprising a broad spectrum of microbes, gut bacteria and potential opportunistic pathogens. Additionally, we identified nearly 200 human proteins, including promising population-level health indicators, such as immunoglobulins, uromodulin, and cancer-associated proteins.

Aerobic Granular Sludge (AGS) is an innovative and efficient biotechnology for wastewater treatment that has been successfully applied on full-scale worldwide. Full-scale municipal AGS systems typically contain both granular sludge (granules) and flocculent sludge (flocs). Studies on the different roles of granules and flocs remain limited. In this study, a laboratory-scale AGS reactor fed with complex synthetic wastewater was operated to simulate full-scale AGS systems and to study the different functional roles of granules and flocs. The laboratory reactor achieved a coexistence of granules and flocs with a floc mass fraction of 17 %. The activities of different size fractions were evaluated using batch experiments and compared for carbon, nitrogen, and phosphorus removal: flocs (FL; <0.2 mm), small granules (SG; 0.2∼1.0 mm), medium granules (MG; 1.0∼2.0 mm), and large granules (LG; >2.0 mm). During feeding, large granules and medium granules exhibited more substrate uptake than small granules and flocs due to preferential substrate access. For aerobic conversion, flocs and small granules showed higher biomass-specific nitrification rates, while medium granules and large granules showed higher phosphorus uptake and denitrification capacity. Furthermore, large granules and medium granules showed stronger mass transfer limitation of oxygen, which limits their nitrification capability. Microbial community analysis using metagenomics and metaproteomics was performed across size fractions, and distinct communities in granules and flocs were shown. Granules showed a high abundance of Candidatus Accumulibacter (polyphosphate-accumulating organisms, PAOs) and Candidatus Competibacter (glycogen-accumulating organisms, GAOs). Flocs showed a high abundance of Nitrosomonas (ammonium-oxidizing bacteria, AOB) and Tetrasphaera (fermentative PAOs) and a low abundance of Ca. Accumulibacter. The distribution of microbial activities and microbial community over sludge size fractions in the laboratory reactor is similar to full-scale AGS systems, indicating that this laboratory setup can simulate full-scale systems and can be used for future research. Overall, this study highlights the importance of maintaining a good balance between different granule sizes and flocs to optimize nutrient removal.

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.

In methanogenic communities, two main pathways drive methanogenesis: acetoclastic methanogenesis, which converts acetate into CH4 and CO2, and hydrogenotrophic methanogenesis, which reduces CO2 with H2 to CH4. Under high-pH conditions, a shift in dominance from acetoclastic to hydrogenotrophic methanogenesis is often observed. The goal of this work was to identify the pH tipping point for this metabolic shift and to elucidate the influence of alkalinity on this transition in a haloalkaliphilic methanogenic community enriched from anaerobic soda lake sediments. To this end, a haloalkaliphilic microbial community was cultivated across a pH range (8.20–10.00) at three different alkalinities (0.1, 0.6, 1.2 eq/L). Specific qPCR probes were developed to quantify the two dominant methanogens for each catabolism: “Ca. Methanocrinis natronophilus” (acetoclastic) and Methanocalculus alkaliphilus (hydrogenotrophic). Results showed that the relative abundance of Methanocalculus increased with the rise of pH for all alkalinities, with alkalinity exerting a stronger influence than pH. At low alkalinity (0.1 eq/L), Methanocalculus abundance doubled from 5.14 ± 1.95% to 9.15 ± 0.77% (pH 8.40–10.35). At moderate alkalinity (0.6 eq/L), it increased from 8.33 ± 1.34% to 47.92 ± 3.76% (pH 8.41–10.00), and at the highest alkalinity (1.2 eq/L), it increased from 6.78 ± 1.06% to 60.25 ± 2.00% (pH 8.26–9.68). 16S rRNA gene amplicon sequencing further identified “Candidatus Contubernalis” as a putative syntrophic acetate-oxidizing bacterium likely partnering with Methanocalculus in indirect hydrogenotrophic methanogenesis. This work highlights that haloalkaliphilic hydrogenotrophic methanogens offer a promising strategy to integrate CO2 capture in alkaline solutions with biomethanation.

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.

Microbial aggregates of different sizes in aerobic granular sludge (AGS) systems have been shown to exhibit distinct microbial community compositions. However, studies comparing the microbial activities of different-sized aggregates in AGS systems remain limited. In this study, genome-resolved metatranscriptomics was used to investigate microbial activity patterns within differently sized aggregates in a full-scale AGS plant. Our analysis revealed a weak correlation between the relative abundance of metagenome-assembled genomes (MAGs) and their transcriptomic activity, indicating that microbial abundance does not directly correspond to metabolic activity within the system. Flocculent sludge (FL; <0.2 mm) predominantly featured active nitrifiers and fermentative polyphosphate-accumulating organisms (PAOs) from Candidatus Phosphoribacter, while small granules (SG; 0.2–1.0 mm) and large granules (LG; >1.0 mm) hosted more metabolically active PAOs affiliated with Ca. Accumulibacter. Differential gene expression analysis further supported these findings, demonstrating significantly higher expression levels of key phosphorus uptake genes associated with Ca. Accumulibacter in granular sludge (SG and LG) compared to flocculent sludge. Conversely, Ca. Phosphoribacter showed higher expression of these genes in the FL fraction. This study highlights distinct functional roles and metabolic activities of crucial microbial communities depending on aggregate size within AGS systems, offering new insights into optimizing wastewater treatment processes.

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.

Aerobic granular sludge (AGS) technology holds great promise of becoming the standard for biological wastewater treatment due to its lower energy consumption, small footprint, and high removal efficiency of nutrients compared to the conventional activated sludge processes. Different-sized aggregates have been shown to harbor a different microbial community composition. The central question is do full-scale AGS wastewater treatment plants (WWTPs) select for core microbial communities across different aggregate sizes and how these selected organisms differ between the different-sized aggregates. This study analyzed samples from nine geographically distributed full-scale AGS WWTPs that consistently perform well in terms of chemical oxygen demand (COD) and nutrient (N and P) removal. The main results showed that site-specific conditions highly influence microbial composition in smaller aggregates (< 1 mm), while larger granules form stable communities independent of WWTP location. Notably, all aggregates contained a small subset of 128–139 core OTUs that were both prevalent and abundant across all sizes. These core OTUs include key functional groups such as fermenters, aerobic heterotrophs, polyphosphate-accumulating organisms (PAOs), glycogen-accumulating organisms (GAOs), and nitrifiers, which play a crucial role in COD and nutrient removal. Additionally, an enrichment pattern was observed, with aerobic heterotrophs dominating in flocs, PAOs in small granules, and GAOs and nitrifiers in large granules. This study offers valuable insights into the core microbiome of different-sized aggregates in full-scale AGS WWTPs and highlights their potential role in overall system performance.

Methane removal is an essential step in drinking water production from methane-rich groundwaters. Conventional aeration-based stripping results in significant direct methane emissions, contributing up to one-third of a treatment plant's total carbon footprint. To address this, a full-scale trickling filter was operated for biological methane oxidation upstream of a submerged sand filter, and its performance was compared to a conventional aeration–submerged sand filtration set-up. Full-scale data were combined with ex-situ batch assays and metagenome-resolved metaproteomics to quantify the individual contribution of the main (a)biotic processes and characterize the enriched microbial communities. Both treatment setups fully removed methane, iron, ammonium, and manganese, yet the underlying mechanisms differed significantly. Methane was completely removed from the effluent after trickling filtration, with stripping and biological oxidation each accounting for half of the removal, thereby halving overall methane emissions. Methane-oxidizing bacteria not only outcompeted nitrifiers in the trickling filter, but also likely contributed directly to ammonia oxidation. In contrast to the submerged filter preceded by methane stripping, signatures of biological iron oxidation were almost completely absent in the trickling filter, suggesting that the presence of methane directly or indirectly promotes chemical iron oxidation. All systems had similar ex-situ manganese oxidation capacities, yet removal occurred only in the submerged filters but not the trickling filter. Ultimately, our results demonstrate that trickling filtration is effective in promoting biological methane oxidation at comparable produced drinking water quality, highlighting its potential for advancing sustainable drinking water production.