ACS ES&T Water

Electrochemical advanced oxidation processes (EAOPs) are increasingly investigated for tertiary wastewater treatment, yet their short-term effects on real wastewater effluent remain poorly constrained. This study investigated real wastewater treatment plant (WWTP) effluent following short-term boron-doped diamond (BDD) electrochemical treatment using an interdigitated double-diamond electrode (iDDE), combined with hydrochemical, stable-isotope and shotgun metagenomic analyses. After 10 min at 7.0 V and 1.02 A, physicochemical parameters and bulk carbon pools remained largely unchanged. In contrast, d18O-DO decreased by 31.3 +/-0.28 permille alongside a small increase in dissolved oxygen (0.16 +/-0.03 mmol/L), indicating substantial oxygen consistent with electrochemical oxygen generation. Shotgun metagenomics revealed pronounced restructuring of the recovered microbial DNA pool, including increases in Comamonadaceae (~12.3% vs. ~25.1%) and Zoogloeaceae (~3.3% vs. ~8.4%), whereas the oxidative-stress-defence gene repertoire showed no coherent response. These taxonomic changes cannot be interpreted as selective survival, as metagenomics do not resolve viability or intra-/extracellular DNA contribution. Overall, short-term iDDE treatment affected the microbial component of real WWTP effluent despite comparatively limited changes in bulk chemistry, highlighting that EAOP effects extend beyond conventional disinfection.

The 2020 SARS-CoV-2 pandemic renewed global interest in wastewater-based epidemiology (WBE) as a tool for monitoring public health. Molecular analyses of wastewater are often limited by the small volumes of wastewater that can be processed, due to column clogging, handling constraints, and processing time. Additionally, inhibitors in the complex wastewater matrix reduce the sensitivity of downstream assays such as RT-PCR and sequencing. To address these limitations, we developed a novel column by incorporating a hydrophobic pre-filtration layer and sequential glass fiber filters. This enhanced column design, PureBioX Xpurify Column, enables processing of 1.58 times more wastewater (a 58% increase in throughput) while reducing RT-PCR inhibitors and maintaining compatibility with existing workflows. Despite a modest reduction in nucleic acid yield, the modified column consistently improved viral RNA detection sensitivity, including for SARS-CoV-2. This accessible, scalable upgrade strengthens the utility of direct capture methods in WBE-based public health surveillance.

Hospital-based wastewater surveillance may complement community and clinical surveillance data in important ways, and may be useful in jurisdictions without community-based wastewater surveillance. From May 2024-April 2026, we analyzed weekly samples (n=190) from three hospitals in New York City using digital PCR to evaluate the sensitivity, specificity, and positive predictive value (PPV) of wastewater viral detection against facility SARS-CoV-2 and influenza A/B inpatient caseloads. Sensitivity was 38-42% for SARS-CoV-2 and 36-49% for influenza A/B, while specificity exceeded 72% for all pathogens. During respiratory seasons, sensitivity reached 81% for SARS-CoV-2 and 81% for influenza A; both had 100% sensitivity during peak case weeks. Notably, off-peak influenza detections occurred in hospital wastewater at all three hospitals in summer 2024 without corresponding hospital case detection, suggesting the presence of undiagnosed cases. These findings underscore the potential utility of hospital-based wastewater monitoring for tracking respiratory virus activity.

Per- and polyfluoroalkyl substances (PFAS) are present throughout the environment due to decades of use in many commercial products and industrial processes. These molecules contain a hydrophobic fluorocarbon tail and a functional headgroup (typically a carboxylic or sulfonic acid) that allows hydrophilic interactions with the surrounding environment. These properties make them inherently resistant to degradation, difficult to track through the environment, readily bioaccumulative, and likely to impact human health. Through collaboration with town officials, multiple meetings with local sustainability committee members and school officials, and direct contact with individual homeowners, we conducted community-driven sampling of PFAS in well water from 105 houses in Tremont, ME, a rural coastal town that relies on private wells for drinking water. The rate of PFAS detection for one or more analytes across all wells (N=105) was 69%. Of all wells tested, 16 (15%) exceeded the current public drinking water standard in Maine (20 ng/L for 6 PFAS), and an additional 17 (totaling 31% of all wells tested) exceeded Maine's newly adopted public drinking water standards for the state (based on EPA 2024 standards). Because private wells are unregulated, homeowners may use these results as a guide for taking action to maintain safe drinking water. Both hierarchical cluster analyses and pairwise Spearman's rank correlation of PFAS test results revealed similar profiles in households near and far from one another. Along with the absence of obvious, large-scale potential point sources of PFAS contamination, these findings support septic systems as the primary source of PFAS contamination in drinking water across this town. The community-driven approach to the sampling effort has enabled information sharing on the importance of water filtration options, discussion of long-term pollution abatement strategies for individual households and the town, and focused efforts for future well water testing and PFAS mitigation.

Since the COVID-19 pandemic, wastewater-based surveillance (WBS) has emerged as a key approach to assess community-level health and the evolution of pathogens. To date, most established WBS systems focus on polymerase chain reaction (PCR) based detection and targeted sequencing of known pathogens because these approaches are well-accepted and include amplification of pathogen target sequences of interest thereby enabling lower limits of detection. Metagenomic next-generation sequencing (mNGS) is a promising approach to enable pathogen detection and surveillance beyond predefined pathogen lists, but its regular application to WBS has not been yet widely adopted because many key performance characteristics are not well-understood, including limit of detection (LOD) and false positive/negative rates. This paper describes a computational analysis to estimate the operational LOD of various sequencing approaches using a simplified model of a local wastewater (WW) system involving a military base. This paper also presents findings from two types of experiments: 1) laboratory-spiked, those for which Atlantibacter subterraneus (Asub) is introduced into real-world WW samples in a laboratory setting, and 2) system-spiked, those for which Asub is introduced at a source location of a real-world WW system. Findings indicate that mNGS detection performance varies with sequencing method and the data analysis process. In addition, findings indicate that site-specific method characterization should be used when implementing mNGS for WBS because sites can have different WW system configurations, background organisms and sequencing inhibitors.

Wastewater contains a complex mixture of nucleic acids derived from human cells, microorganisms, diets, and agricultural or industrial inputs. Metatranscriptomics has the potential to broaden the understanding of wastewater viromes, but its utility is constrained by high-abundance RNA molecules that prevent the detection of lower-abundance signals, including human pathogens. Two major sources of this interfering background signal are ribosomal RNAs (rRNAs) from various organisms, and plant-infecting tobamoviruses from human diets, which are often the most abundant RNA viruses in wastewater. These rRNA molecules and RNA genomes can account for upwards of 95% of total RNA sequences, thereby obscuring the detection of lower-abundance viruses of public health importance. This study evaluated whether combined depletion of ribosomal RNAs and genomic RNA from abundant plant tobamoviruses can improve the recovery of underrepresented viral sequences from wastewater. RNA extracts from a large municipal wastewater treatment plant in Calgary, Canada, were processed with or without probe-based depletion of rRNAs and eight abundant tobamoviruses. Metatranscriptomes revealed that depletion reduced rRNA reads by 90%. Reads assigned to tobamoviruses, which accounted for up to 25% of viral reads in untreated samples, were reduced to <2% of viral reads after depletion. This decrease in undesired RNA signal led to an order of magnitude increase in viral read signals and improved assembled viral genome quality. Furthermore, the number of reads assigned to human and animal pathogens increased 42-fold after depletion, enabling the detection of important pathogens like influenza, RSV, and hepatitis A, which were undecteable in untreated samples. Together, these findings demonstrate that targeted depletion of abundant background RNAs improves the detection of low abundance viruses, and enhances the utility of metatranscriptomic approaches for wastewater viral surveillance.

The sewer microbiome is known to be the main source of process-critical bacteria involved in nitrogen and phosphorus removal in wastewater treatment plants (WWTPs) and is thus crucial for the assembly of activated sludge (AS) microbial communities. However, the extent of these bacterial loads arriving at WWTPs currently lacks scientific attention. We provide a quantitative description of the biomass loads from sewer systems to WWTPs by coupling microbial community data by 16S rRNA amplicon sequencing from the Aalborg municipality sewer catchment with mass balances and biomass production across gravity and pressure sewer systems. Accounting for microbial transformations in sewer wastewater, biofilm and sediments under steady state dry weather flow conditions, gravity sewers were found to produce higher biomass loads than pressure systems, with loads of 1.57 and 0.27 kgCOD m-3 d-1 respectively. A key feature of our sewer model is its ability to estimate biomass loads from specific taxa, such as polyphosphate accumulating organisms (PAOs). Using Aalborg West WWTP as a case study, model estimations correlated well with figures calculated based on influent wastewater data monitoring. The model-estimated loads for the PAOs Azonexus and Ca. Accumulibacter were 2.10 kg day-1 and 1.80 kg day-1, compared to the influent wastewater monitoring-based loads of 1.77 kg day-1 and 1.20 kg day-1, respectively. While providing a framework for further research on sewer microbial dynamics, this study offers a tool for gaining insights into microbial immigration, generating valuable information for improving microbial communities management in WWTPs, optimizing nutrient removal, and enhancing WWTP design.

In response to the growing need to recycle E-waste, specifically that of lithium-ion batteries (LIBs), the development of sustainable recycling methodologies will be vital. As one of the most sustainable and low-cost options, biohydrometallurgy (BioHM) uses biological organisms to facilitate the recovery of critical metals from spent LIBs. Despite the advantages of BioHM, its slow kinetics, due to the reliance on the metabolic activity of microorganisms, limit its large-scale application for the closed-loop recycling of LIBs. In this work, we investigate the correlation between the incubation time of Acidithiobacillus ferrooxidans (Atf) and its leaching efficiency of four common elements in LIBs: Li, Ni, Mn, and Co. We assess how specific incubation times along the biological growth curve affect the leaching efficiency of Li[Ni0.6Mn0.2Co0.2]O2 (NMC622), a model electrode material. Our results show that pH alone is not an accurate descriptor of the leaching efficiency of Atf cultures used at different growth stages. The addition of NMC622 during the bacterial lag phase reaches similar or even improved extraction compared to cultures used after reaching the exponential or stationary phases. A simple model of leaching dynamics shows predictions consistent with our experimental observations under the condition that the inhibition of bacterial growth by NMC is not severe. Our findings indicate that early-stage cultures can alleviate the kinetic bottleneck and improve the throughput of recovering critical materials from spent batteries.

Bioelectrochemical reduction of dilute nitrate (NO-; sub-mM to low-mM range) to ammonium (NH) offers a promising route toward circular nitrogen management from contaminated groundwater and environmental waters. However, on-site application of bioelectrochemical systems remains challenging due to low reduction rates and poor electron transfer efficiency of naturally formed biofilm electrodes. Here, we constructed a hydrogel biocathode by applying a carbon black/riboflavin/sodium alginate/cellulose hydrogel incorporating Shewanella oneidensis MR-1 cells to a graphite felt electrode via brush coating. The hydrogel electrode achieved NH production rates of 0.16-0.19 mol m-3 h-{superscript 1} without NO2- accumulation, and these rates were maintained without significant performance loss across three consecutive cycles with medium exchange over 1.5 days of total operation. The hydrogel electrode increased the current density by more than 5-fold compared with a conventional S. oneidensis biofilm electrode, indicating enhanced electron transfer efficiency per unit biomass, which directly contributed to the high NH production rates. The electricity consumption for NH production of 1.68-2.39 x 10{superscript 2} kJ g-N-{superscript 1} was substantially lower than that of metal catalyst systems at comparable NO- concentrations (typically, >104 kJ g-N-{superscript 1}). These findings demonstrate that the hydrogel electrode design represents an energy-efficient, and readily fabricated platform for bioelectrochemical NH production from dilute NO-.

Wastewater sequencing using probe-capture enrichment of public health-relevant viruses is a powerful, non-intrusive approach to monitor infectious diseases, but performance depends on sample type and processing approach. We compared two processing pipelines from wastewater influent samples collected at three timepoints across three wastewater treatment facilities. Each sample was split for parallel processing, with viruses concentrated (1) directly from whole influent using nano-sized affinity particles and (2) by settling and dewatering the solids fraction. Combined DNA/RNA extracts were prepared into libraries using a pre-commercial Illumina protocol, then probe-capture enrichment was performed with Illumina Viral Surveillance Panel (VSP) v1 (66 targets) and v2 (242 targets). Sequencing depth was increased for VSP v2 to accommodate the expanded target set. On average, 160 +/- 146 viral species were detected per sample, with wastewater fraction (sample type) explaining 19% of the variance in viral abundances. Solids contained a higher abundance of DNA viruses compared to RNA viruses, while influent exhibited the inverse. Metagenomic analysis of the VSP v2 sequencing data detected more viral species in influent (median 358) than in solids (median 184), but probe-capture enrichment produced more comparable target-virus readouts across fractions, supporting the use of either fraction for wastewater-based epidemiology.

The anaerobic biotransformation of lindane ({gamma}-hexachlorocyclohexane), a persistent legacy pesticide and challenging subsurface contaminant was modelled using an integrated Monod biokinetics framework. Calibrated against batch experimental data, this model accounted for the dissolution of solid phase lindane and the thermodynamics of reactions involved. The study focused on a methanogenic, lindane-degrading enrichment culture (GT2) that used ethanol as the electron donor, where ethanol fermentation supplied hydrogen to support reductive dechlorination of lindane. A Dehalobacter strain was identified as the lindane-degrading organism, while a member of bacterial order Geobacterales carried out ethanol fermentation. First-order decay constants for lindane-degrading Dehalobacter were estimated from experimental data and showed variation across different growth conditions. The biokinetics model captured interactions among key microbial processes, namely lindane dechlorination, ethanol fermentation, hydrogenotrophic methanogenesis, and acetoclastic methanogenesis. Thirteen biokinetics parameters including maximum substrate utilization rates (k), half-velocity constants (Ks), and decay constants for these microbial processes were estimated through a Bayesian optimization approach. Global sensitivity analysis showed that eight parameters, primarily k and Ks, had significant linear impact on the model output, whereas responses to decay constants were more variable and potentially non-linear. This study proposed an effective modelling approach for characterizing syntrophic microbial growth within enrichment cultures and provides valuable biokinetics parameters estimates for real-world applications of anaerobic lindane bioremediation.

Groundwater contamination by lead and nitrate exceeding the permissible limits of the World Health Organization (WHO) and the Bureau of Indian Standards (BIS) of 10 ppb lead and 45 to 50 ppm nitrate poses a severe health risk of systemic toxicity in humans and animals. Microbial nitrate reduction coupled with microbiologically induced calcite precipitation (MICP) proved to be a novel bioremediation strategy to transform soluble lead nitrate into insoluble lead biominerals. This study presents statistical optimization of operational parameters for nitrate reduction and co-precipitation of biogenic lead carbonate-calcium carbonate by nitrate-reducing bacterial consortia. The SEM, TEM with SEAD, and XRD analysis of the biomineral confirmed lead carbonate co-precipitation with CaCO3. A two-level factorial design was applied to screen significant variables and interactive factors that influence nitrate reduction and biomineral precipitation. The highest nitrate reduction, maximum ammonia production, and biogenic Pb-mineralization efficiency of > 90% were obtained at the optimum conditions (initial nitrate requirement of 600 ppm, temperature 37 oC, pH 8, and carbon content of 5.5 g/L) compared to those obtained under the common process parameters. ANOVA with a high correlation coefficient (R2 > 0.99) corroborated the linear model for the biogenic mineralization process. This study on the biogenic removal of Pb by nitrate-reducing bacterial consortia revealed possible opportunities for large-scale treatment of Pb-contaminated surface and subsurface water bodies.

Wastewater-based epidemiology (WBE) has emerged as a powerful population-level surveillance tool, but its coverage is structurally concentrated in in-network urban areas, potentially leaving rural populations underrepresented. Routine human movement between sewered (in-network) and unsewered (off-network) areas may, however, cause wastewater treatment plant (WWTP) measurements to reflect infectious disease dynamics beyond sewer boundaries. We evaluated this hypothesis using daily clinical COVID-19 testing data (January 2021-April 2022) across New York State excluding New York City (NYC). We disaggregated weekly cases and tests into in-network (WWTP catchment area) and off-network (outside WWTP catchment area) components applied to two geographic frameworks: administrative counties (N = 53 mixed-coverage) and mobility-defined communities identified through Walktrap community detection applied to census tract-level movement networks (N = 32 mixed-coverage). In/off-network COVID-19 trends were strongly correlated under both frameworks. County-level statewide aggregate correlations were high (incidence r = 0.994, positivity r = 0.996), as were individual county correlations (median r = 0.909 and 0.932, respectively). Mobility-defined community-level statewide correlations were similarly strong (r = 0.990 and 0.992), with comparable unit-level medians (r = 0.877 and 0.894). The mobility-defined community framework provided better population balance between in-network and off-network strata (87.5% vs. 69.8% in balanced range) and a higher floor on representativeness (minimum r = 0.440 vs. 0.177). Population size was the dominant predictor of in-network/off-network alignment at both scales; wastewater infrastructure density and off-network signal variability provided additional explanatory power at the mobility-defined community level. WWTPs broadly represent COVID-19 dynamics in surrounding off-network populations, supporting their use as sentinel surveillance sites. Representativeness weakens in smaller, more rural communities, and mobility-defined communities provide a complementary framework for identifying where this occurs.

Microplastic pollution and sunscreen contaminants increasingly threaten coastal ecosystems, yet many existing clean-up solutions rely on synthetic materials, creating additional carbon emissions during manufacturing, or address pollutant removal without subsequent treatment, leaving risk of future run-off back into the ocean. Here we evaluate coconut husk, an abundant and biodegradable agricultural byproduct, as a dual-function platform for physical pollutant capture and microbial bioremediation applications. To test the natural microbial community of coconuts for bioremediation potential, we isolated fungi from coconut husks and screened their growth under plastic- and sunscreen-containing conditions. 24 fungal isolates grew on plastic- and/or sunscreen media, with several isolates belonging to genera previously documented to degrade plastic, i.e. Chaetomium, Curvularia, Meyerozyma, Cladosporium, and Fusarium. We then developed filtration modules using coconut husks, fiber, and leaves, basing our design on traditional Hawaiian papale lau niu (coconut leaf hat) weaving. In filtration trials, the woven devices captured up to 76.58 +/- 3.73% of suspended microplastic particles in 2 minutes and captured suspended sunscreen with a 533.51 +/- 0.81 NTU decrease in net turbidity of the surrounding water than in control trials with no filter. Overall, this work introduces a form of natural innovation for pollution clean-up, building on coconut-based materials, traditional techniques, and microbial resilience to create a sustainable and cost-effective system.

Trace elements, such as iron, nickel, and cobalt are known to regulate methanogenic activity in anaerobic digestors used for waste valorisation, but the potential role of rare earth elements remains poorly understood. This study investigated the effects of lanthanum (La) supplementation on biogas production, methane generation, volatile fatty acid (VFA) formation, and carbohydrate utilisation in anaerobic digestion (AD). Biomethane potential (BMP) assays conducted under mesophilic conditions (37C) using methanogenic sludge granules, and glucose as substrate, were supplemented with 0.1, 1, 10, and 100 mg/L lanthanum chloride (LaCl3). Biogas production and composition was monitored over a 96-h incubation, while sacrificial, batch bioreactors were used to evaluate temporal VFA and carbohydrate profiles. La supplementation significantly enhanced biogas and methane production in a concentration-dependent manner. The highest cumulative biogas yield (478.9 mL, corresponding to 179.5 mL biogas/g COD) and methane production (285.7 mL, corresponding to 107.1 mL CH4/g COD) were observed with 100 mg/L LaCl3, corresponding to increases of 88.7% and 186%, respectively, compared with La-free controls. CO2 production also increased with La concentration, whereas hydrogen production remained comparatively low. Acetic and butyric acids represented the dominant fermentation products (80-88% of total VFAs), but profiles of accumulated VFA in the bioreactors diversified with La addition, including showing caproate production, indicating changed biodegradation dynamics in the methanogenic microbiome. These findings demonstrate that lanthanum can stimulate anaerobic digestion performance and methane generation, highlighting the potential as a novel trace element additive to enhance biogas production. Research is now required to elucidate the underlying microbial and biochemical mechanisms, and establish optimal dosing strategies for large-scale applications.

Surface water quality is a significant public health concern because contaminated rivers and lakes can spread waterborne diseases and expose communities to harmful pollutants, particularly in areas where water treatment and regulation are limited. This study assesses the anthropogenic impact on surface water quality in the Ahafo Ano Southwest District, Ghana. Water samples were collected from three locations within the Mankran watershed during both wet and dry seasons and analyzed for key parameters. Pollutant concentrations exhibited marked spatial and seasonal variability, with nitrate ranging from 1.09 to 13.77 mg/L, phosphate from 1.58 to 10.55 mg/L, and total suspended solids from 140.0 to 1680.0 mg/L. Heavy metals frequently exceeded acceptable limits, with zinc ranging from below detection to 0.11 mg/L, copper from below detection to 0.84 mg/L, and lead from below detection to 0.46 mg/L. Seasonal Water Quality Index (WQI) analysis indicated degraded water quality during the wet season in Baniekrom and Kunsu, due to increased runoff carrying agricultural residues, sediments, and mining contaminants. In contrast, Mmobrem showed improved wet-season quality, attributed to rainfall dilution. The Piper diagram further revealed that the water samples predominantly fall within the Ca-Cl hydrochemical facies, reflecting strong geogenic control through basaltic rock weathering, coupled with chloride enrichment likely intensified by agricultural and domestic inputs. Principal component analysis indicated that multiple anthropogenic and natural factors drive water quality variations across the catchment. Ecological risk assessment identified potential risks to algae, resulting from elevated levels of nutrients and metals. Overall, the combined WQI and hydrochemical evidence indicate an intensified nutrient influx during the wet season and increased suspended particulate matter during the dry season, primarily driven by agriculture, deforestation, and mining. The findings underscore the urgent need for sustainable water management strategies to mitigate the impacts of human activities on surface water quality in the region.

Wastewater surveillance (WS) offers a non-invasive means of tracking population-level circulation of infectious agents, including viruses linked to cancer. This study provides the first Australian assessment of oncogenic viruses in municipal wastewater by screening 76 influent samples collected over four months from six wastewater treatment plants in Southeast Queensland, Australia. Ten gene targets representing seven oncogenic viruses including Epstein-Barr virus (EBV), hepatitis B virus (HBV), hepatitis C virus (HCV), human herpesvirus 8 (HHV-8), human papillomavirus 16 and 18 (HPV-16 and -18), human T-lymphotropic virus type 1 (HTLV-1), and Merkel cell polyomavirus (MCPyV) were analysed using PCR-based methods. All viruses were detected in wastewater at least once, though with substantial variation in frequency. MCPyV was the most frequently detected virus, appearing in 97.3% of samples with concentrations ranging from 3.09-3.85 log10 gene copies (GC)/50 mL, indicating widespread population exposure. HBV (26.3%) and EBV (15.8%) were detected intermittently across multiple catchments, while HPV-16/18, HHV-8, HTLV-1, and HCV were detected at the lowest frequencies (<8%). This study reports the first baseline dataset for oncogenic viruses in Australian wastewater. More broadly, positive detection of all targeted oncogenic viruses including those associated with low prevalence infections in wastewater demonstrates the potential of WS to complement existing cancer surveillance systems in tracking community-level circulation of these infectious agents.

Coastal waters often experience fecal contamination from human (e.g., septic systems, wastewater treatment catchments and outfalls) and non-human (e.g., wildlife, domesticated pets, and livestock) origins, posing human health risks through contaminated fisheries and recreational waters. Quantitative PCR (qPCR) methods can identify and quantify fecal origins for their management by targeting Bacteroides, a dominant group of gastrointestinal bacteria with high host specificity. This study identified major contributors and drivers of fecal contamination to Mobile Bay, Alabama, an urbanized estuary in the southern United States. We utilized a multi-species qPCR source tracking approach targeting total Bacteroides and human-, pig-, dog-, cow-, and fowl-associated Bacteroides. Water samples and environmental parameters were collected over one year from 13 sites that represent a range of potential fecal inputs common to coastal waters. Human-associated feces were a consistent major contributor to the system (positive in 82% of samples), with localized inputs from pig (wild or domestic) and dog. Freshwater discharge and nitrogen constituents were good predictors of Bacteroides concentrations in this system, while areas with impervious surfaces and developed land cover may be contributing elevated fecal indicator levels. The multi-species qPCR source tracking approach described in this study can be implemented in other watersheds to support the development of better detection, identification, and fecal management strategies for community health of coastal areas.

Newly established freshwater aquaria rely on development of biofilter nitrifying populations to prevent ammonia and nitrite accumulation that can negatively impact fish health. Although initial fish loads impact water chemistry of new aquaria, little is known about the corresponding impact on microbial community succession within freshwater aquarium biofilters. To address this gap, fourteen home aquarium systems were established, stocked with a range of fish loads, and maintained for eight months. Aquaria were sampled regularly to monitor nitrogen species, microbial community composition (16S rRNA gene sequencing), and the abundance of nitrifiers (qPCR). Aquaria with higher fish loads developed microbial communities that were compositionally distinct from those with lower fish loads, and were dominated by Pseudomonas, Rhodobacter, and Planctomycetes. These patterns are consistent with increased nutrient availability supporting biofilm development, whereas lower fish loads may delay biofilm maturation. Increasing the number of fish in an aquarium significantly increased maximum ammonia and nitrite concentrations, although both were ultimately depleted within similar timeframes across treatments. Comammox Nitrospira were among the most abundant biofilter nitrifiers and were present in all biofilter samples regardless of fish load. Ammonia-oxidizing bacteria were detected at relatively low abundance but showed increases in relative abundance within high fish load aquarium filters. Ammonia-oxidizing archaea were below sequencing detection limits and detected only at low levels by qPCR, suggesting that their establishment in aquarium biofilters may require higher initial inoculation or longer timeframes. Overall, these results demonstrate that fish load shapes microbial community development in newly established aquarium biofilters, and that comammox Nitrospira dominate among nitrifiers during early biofilter establishment.

The unprecedented rise in greenhouse gases such as carbon dioxide (CO2), and their detrimental effects on the atmosphere have intensified the current climate emergency. This challenge has inspired the development of novel carbon capture and utilisation (CCU) technologies, specifically microbial electrosynthesis (MES), for the bioelectrochemical fixation of CO2 into commodity chemical compounds (CCCs) using microbial biocatalysts. In this study, we systematically enriched and maintained robust mixed microbial communities of electroactive bacteria (EAB) from wastewater treatment sludge to serve as biocatalysts for MES. The MES performance of these biocatalysts under different operational conditions in bioelectrochemical systems (BES) reactors were investigated. BES reactors with enriched biocatalysts incubated and maintained under controlled conditions produced higher CCCs yields than those developed at ambient temperatures, while strict anaerobic operations further improved the MES efficiency compared to aerobic conditions. At an applied potential of -1000 mV vs Ag/AgCl, CO2 conversion reached up to 88.11%, significantly outperforming the lower potential (-600 mV) operation. These findings underscore the importance of systematic development of robust and stable biocatalysts, as well as maintaining strict anaerobic conditions, for achieving efficient MES performance, thereby demonstrating the potential of our approach for scalable industrial CCU applications.