Environmental Science & Technology Letters

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.

Background: Privacy curtains represent a uniquely difficult infection control surface because they are frequently touched by patients, visitors, and healthcare workers, yet are difficult to disinfect using routine environmental cleaning protocols. We sought to quantify the performance of a novel automated aerosolized hydrogen peroxide system against pathogens on privacy curtains. Methods: This study was performed in an enclosed office space ({approx} 65 m^3), approximating a patient exam room. Four Bacillus atrophaeus (ATCC 9372) biological indicators (BIs) were affixed to a standard polyester privacy curtain. A single one-minute fogging phase was followed by a ten-minute contact/aeration phase (total = 11 min). Four corresponding chemical indicators measured peak airborne aerosolized hydrogen peroxide concentration, and two control BIs were placed outside of the room. Results: All four BIs demonstrated complete inactivation (no growth after seven-day incubation), representing [≥] 4-log10 spore reduction. Peak dosages reached 42 ppm nearest the aerosolized hydrogen peroxide jet outlet, with the lowest value at the near point on the back side of the curtain reaching 27 ppm (exceeding the target dosage of 25 ppm). Control exposures failed to achieve sterilization. Conclusions: A next-generation aerosolized hydrogen peroxide dry-fogging disinfection system achieved full inactivation of resistant spores on both sides of privacy curtains within a short 11-minute automated cycle.

Wastewater-based epidemiology uses both targeted and non-targeted bioanalytical approaches to detect and track disease-causing microbes in wastewater. Targeted approaches such as quantitative polymerase chain reaction (qPCR) remain widely used while sequencing-based approaches have slowly gained popularity. However, concordance between established targeted molecular assays and sequencing approaches remains incompletely characterized. To assess the validity of sequencing as an alternative to qPCR, we compared outcomes of both methods targeting five respiratory viruses in wastewater samples collected across 16 Texas cities over 4 years (May 2022-July 2026) of continuous sampling. We found positive correlations between qPCR and sequencing measurements, with both methods independently correlating with statewide clinical emergency department visits. qPCR positivity also increased with genomic sequencing coverage, and sequencing demonstrated greater potential than qPCR as an early respiratory virus outbreak detection method. Our findings support metagenomic sequencing as a sensitive and highly specific alternative to targeted qPCR for wastewater surveillance, and reinforce its utility towards long-term longitudinal monitoring of respiratory viruses.

Abstract Antimicrobial resistance (AMR) is a pressing global public health challenge. AMR is driven in part by the spread of antibiotic resistance genes (ARGs) through bacterial communities via mobile genetic elements. Influent wastewater is a promising sample type for monitoring AMR because it pools biological inputs shed by individuals across a population. However, untargeted sequencing approaches, such as metagenomic sequencing, often miss low-abundance targets such as clinically important ARGs. In this work, we develop a ligation-mediated PCR (LM-PCR) enrichment strategy that can directionally capture the genomic context surrounding an ARG using long-read sequencing. We applied this method to study the natural genomic context diversity of four clinically relevant ARGs (blaCTX-M, blaKPC, and blaOXA-48-like, and qnrS) across 13 wastewater treatment plants in Washington state, each sampled at two timepoints. Across all timepoints, LM-PCR identified distinct genomic context cluster families associated with each ARG, including seven for blaKPC, 11 for blaCTX-M, 24 for qnrS, and one for blaOXA-48-like. Notably, 11 of the 24 qnrS containing clusters were putatively novel, with no matches to existing sequences in public databases. Genomic contexts associated with blaCTX-M and blaKPC were comparatively conserved across clusters, whereas qnrS was associated with a more diverse set of genetic sequences. Together, these results demonstrate that LM-PCR can resolve low-abundance, ARG-associated genomic variation in complex wastewater samples and provide a scalable framework for tracking the dissemination of clinically relevant AMR determinants.

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.

Wildfire smoke has increasingly affected air quality across North America, raising concerns about the health effects of fine particulate matter (PM2.5) exposure, including potential impacts on brain health. However, relatively few studies have characterized personal PM2.5 exposure during these events using wearable monitoring. We examined daily personal PM2.5 concentrations during wildfire smoke episodes in southeast Michigan alongside neighborhood outdoor PM2.5 estimates. Four participants (one adolescent and three adults) wore AirBeam3 personal monitors during ongoing studies. Neighborhood outdoor PM2.5 was estimated using the average of three nearest PurpleAir outdoor air quality sensors, and wildfire smoke days were identified using state air quality advisories. Group-level descriptive statistics summarized personal and neighborhood outdoor PM2.5 and self-reported time spent outdoors. Exploratory within-participant analyses quantified associations between neighborhood outdoor and personal PM2.5 concentrations on smoke and non-smoke days. Neighborhood outdoor daily PM2.5 concentrations were higher during wildfire smoke days than non-smoke days (87.6 + 80.2 vs. 12.3 + 7.0 {micro}g/m3). Personal PM2.5 concentrations were more than five times higher during wildfire smoke days (28.2 + 20.0 vs. 5.1 + 4.7 {micro}g/m3) than non-smoke days. Within participants, every 10 {micro}g/m3 increase in neighborhood PM2.5 was associated with 2.3 {micro}g/m3 increase in personal PM2.5 concentrations. Wearable PM2.5 monitoring captured elevated personal exposures while providing individual-level exposure information beyond neighborhood outdoor air quality estimates. These findings demonstrate that wearable monitoring complements neighborhood air quality measurements by capturing individual-level exposure, providing a more comprehensive assessment of real-world wildfire smoke exposure for future studies examining the effects on brain health.

Wildfire smoke poses a growing health risk worldwide, yet the magnitude and temporal evolution of mortality after episodic exposure remain poorly resolved, limiting burden assessment. Using monthly county-level wildfire PM2.5 and mortality data from the United State, we exploit episodic exposure contrasts to deconvolve overlapping mortality responses and recover the impulse-response function. The excess mortality response peaks approximately three years after an exposure pulse and subsides by five years. We estimate 1.7 (95% uncertainty interval: 1.1-2.3) million smoke-associated deaths during 2011-2023, approximately ten times estimates using long-term ambient PM2.5 mortality relative risks. Circulatory and respiratory diseases contribute comparably and dominate this burden. Responses are markedly greater among adults [≥]65 years; during the COVID-19 pandemic, population-wide cumulative responses are significantly higher over at least the first seven months after exposure. Reducing wildfire smoke exposure can thus yield substantial health benefits over multiple years, particularly when population vulnerability is heightened.

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.

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.

With the increase of recycled water to offset water demand, the potential possibility to spread contagious RNA viruses, such as Coxsackievirus B3, increases. However, detection of viral particles remains challenging because of low viral concentrations in wastewater and high mutation rates of the RNA virus. Robust monitoring is needed with low cost and low infrastructure technologies to increase accessibility of monitoring technologies worldwide. Novel viral detection methods have been developed, based on synthetic riboswitches that bind to the target virus and trigger a reporter gene, thus amplifying the detection signals. Such monitoring technologies can leverage machine learning to optimize the candidate nucleic acid sequences used for detection. To support the design of effective riboswitches, we present a machine learning model for classifying riboswitch performance, integrating RNA sequence data with secondary structural features based on free energy calculations and parameters that represent single strandedness. This model uses a sparsely gated Mixture of Experts (MoE) architecture to route sequence and thermodynamic features to specialized experts, achieving strong generalization performance across cross-validation and held-out testing. When evaluated against baseline Decision Tree, Random Forest, Gaussian Naive Bayes, and Dense Neural Network classifiers, the MoE model demonstrated near-zero classification errors. Furthermore, post-hoc feature importance and k-mer analyzes reveal that near-perfect predictive performance in silico is strongly driven by sequence constructs in addition to generalizable folding mechanics. An ablation study of numerical feature and sequence inputs showed that while the Dense Neural Network also achieved high accuracy across all ablation conditions, the MoE architecture was retained as the primary model because its specialized subnetworks do not require all model parameters to be activated offering a potential computational advantage.

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.

Mass gatherings are thought to create conditions for pathogen introduction and spread, yet whether such events measurably alter the viral community of a city has rarely been tested against an extensive historical baseline. We analyzed 5,137 hybrid-capture metagenomic wastewater samples collected from 55 sites across 17 Texas cities between June 2022 and July 2026, spanning the 2026 FIFA World Cup. We asked (1) whether host-city viral community composition during the tournament departed from its established summer-to-summer range, (2) whether targeted respiratory viruses rose above their characteristic summer trend, and (3) whether the load of rare and novel taxa was elevated in host cities relative to non-host cities. Despite the plausibility of these hypotheses, we detected no tournament-associated perturbations. Although based on a single event, these findings favor continuous wastewater surveillance over event-triggered deployment, both for detecting introductions that arrive unpredictably and for supplying the baseline against which any event should be judged.

Background: Children spend more than 90% of their time indoors, and early childhood education settings (ECEs) are an understudied, high-occupant-density indoor microenvironment where exposure to volatile organic compounds, particulate matter, and other toxicants has been documented. Limited knowledge exists on ECE-specific exposures affecting young children and how they compare to exposures in the home. Methods: This prospective, repeated-measures pilot study targeted enrollment of 44 preschool-aged children and 8 ECE staff across two geographically and sociodemographically distinct ECEs in metropolitan Atlanta, Georgia. Paired silicone wristbands, one home-designated and one ECE-designated, were exchanged between settings across three consecutive days and nights beginning at enrollment to characterize microenvironment-specific exposure. A single spot urine sample was also collected from each child. Continuous indoor air quality monitoring was conducted in two classrooms per site. Caregivers and ECE staff completed structured questionnaires assessing home and ECE environmental characteristics, child respiratory risk, and protocol feasibility and acceptability. Feasibility was evaluated using eight pre-specified indicators spanning recruitment and enrollment, wristband wear duration and loss by microenvironment, urine sample collection completeness, and survey completion by instrument and respondent group. Conclusion: This pilot will establish feasibility and acceptability parameters for a paired, multi-matrix silicone wristband protocol across home and ECE microenvironments. Findings will inform the design, sample size, and power calculations for a subsequent study testing indoor air interventions and pediatric respiratory outcomes in ECEs. Feasibility outcomes are reported in a companion manuscript.

Plastic products have greatly improved convenience in daily life. However, diverse pollutants released from these materials pose substantial risks to human health. Lactiplantibacillus plantarum PD01 has previously been demonstrated to reduce microplastic (MP) bioaccumulation and toxicity in murine model. In this study, we conducted a randomized, double-blind, placebo-controlled trial to further evaluate the efficacy of L. plantarum PD01 in reducing MPs and MP-associated chemicals in humans. A total of 106 participants were recruited in November 2025. Eligible participants were randomly assigned to either the placebo or intervention group, and orally received placebo or 1.0x1010 colony-forming units (CFU) L. plantarum PD01 after meals three times a day, respectively. Fecal, urinary, and blood samples were collected to determine the MPs contents, plasticizer levels, gut microbiota composition, blood metabolic profiles and biochemical indicators. Among these measurements, the analysis of urinary phthalate metabolites was completed first and revealed a significant reduction after the probiotic intervention. Compared with the placebo group, 6-week L. plantarum PD01 supplementation resulted in significant relative reductions in urinary levels of MCMHP by 60.2% (P = 0.0343), MMP by 51.2% (P < 0.001), MEHP by 49.6% (P = 0.0058), MiBP by 45.7% (P = 0.0085), MnBP by 35.8% (P = 0.0478), and {Sigma}DEHP by 46.2% (P = 0.0461). The interim results presented here provide the first clinical evidence that the probiotic strain PD01 can significantly reduce residual MP-associated chemicals in human body. To the best of our knowledge, this is the first randomized controlled trial (RCT) to evaluate probiotic intervention targeting MPs and MP-associated chemicals in humans.

Vaccine hesitancy remains a major public health challenge, highlighting the need for effective strategies to boost vaccine uptake. We conducted a county-randomized trial to evaluate whether a social media campaign grounded in alerts driven by community-level wastewater surveillance could increase COVID-19 and influenza vaccination. Forty New York State counties were selected for an 11-week campaign during fall 2024, with 20 counties assigned to the intervention and 20 serving as controls. The campaign reached more than 16.6 million impressions, with over 77K clicks on the call-to-action link, demonstrating substantial public engagement. During the campaign period, intervention counties administered significantly more COVID-19 vaccine doses ({beta} = 76.7, P = 0.01) but fewer influenza vaccine doses ({beta}= -140.9, P = 0.04) per 100,000 residents per week than control counties. However, season-level analysis showed no significant differences in COVID-19 or influenza vaccination uptake between groups. These findings highlight the potential of alerts from community-level wastewater surveillance to promote vaccination.

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.

Disinfection with bleach is recommended for surface cleaning in healthcare facilities, but bleach degrades over time, reducing disinfection effectiveness. We evaluated whether local bleach produced by hospitals using novel technology had adequate shelf life to justify use. Two hospitals (A and B) each produced and stored 0.5% bleach in two 20-liter plastic containers; bleach in one container was alkalinized for increased stability to pH 12; bleach in the other container was not stabilized and, for comparison, a third container of commercial bleach was tested. We tested three bleach samples from each of the containers produced by hospitals A and B, and commercial bleach for free available chlorine (FAC) using N,N-diethyl-p-phenylenediamine at irregular intervals up to 216 days. We compared the expected percent decrease in FAC per 7 days by bleach type using log-normal regression. Stabilized bleach decreased by 1% and 2% in hospitals A and B, respectively, every 7 days while non-stabilized bleach decreased by 21% and 12%, respectively (all p<0.001); commercial bleach decreased by <1% per 7 days. Bleach production proved feasible in hospitals, and both stabilized and commercial bleach maintained adequate concentration for disinfection; non-stabilized bleach maintains a useful concentration for not longer than three weeks after production.

Current health risk assessments from thirdhand exposure to methamphetamine (meth) to occupants of contaminated residences when no cooking or use is still occurring assume that inhalation exposure is insignificant. After Wright et al. (2021) reported substantial meth concentrations in a contaminated residence, the present study was conducted to further test the hypothesis that concentrations were high enough to contribute to total occupant dose. Air sampling was conducted in contaminated residences that had been previously sampled for surface contamination. Samples were collected on personal sampling pumps in fixed locations on treated glass fiber filters is cassettes and analyzed by gas or liquid chromatography with mass spectroscopy. Sixty-nine samples were collected from eighteen residences for the study. Meth concentrations ranged from 0.02 to 15 ug/m3. Concentrations in supply air vents were significantly higher than in return vents or in ambient air. Residences with no HVAC systems (baseboard heat) had airborne concentrations similar to residences with HVAC systems turned off, and lower than when HVAC was on. Whether a residence was occupied or not did not show differences. All data from residences with HVAC had a significant correlation with surface concentrations (R2 = 0.61) but some factors that affected results were not determined in the study. In the context of the risk assessment and regulatory standard established by California and adopted in several other states, the inhalation exposure would approximately double total occupant dose for infants, and this population would exceed the California reference dose by approximately 100%. Further studies should be conducted to refine these estimates and determine the factors that influence airborne concentrations.

Background: Environmental noise and air pollution are both shaped by road traffic and the built environment, and exposure assessment increasingly folds them into composite indices or proxies both by traffic exposure. Whether the two share a social distribution has rarely been tested against direct measurement of several exposures in the same communities, and community noise is almost always characterized by A-weighted levels alone, which discount low-frequency energy. Methods: At 176 sites across Rhode Island, spanning the contiguous urban area of Providence, Central Falls, and Pawtucket together with four rural municipalities, we measured the acoustic environment under A- and C-weighting (LAeq, LCeq), fine particulate matter (PM2.5), night-time illuminance, and relative humidity across four session types over roughly one year (704 site-sessions). Exposures were linked to census-tract composition (American Community Survey), and mixed-effects models were fitted for each of eight area-level markers of disadvantage, adjusting for campaign and session. Relative humidity was carried through the identical model as a negative control. Results: A-weighted noise was consistently higher in more disadvantaged tracts, rising with non-White, poverty, renter, and no-vehicle shares and falling with income and older-resident share (six of eight markers significant; 1.3 to 1.8 dBA per standard deviation; 6.6 dBA between the least and most racially diverse neighborhoods). C-weighted levels followed the same gradient on every marker and exceeded their A-weighted counterparts at block-group scale for renter occupancy and vehicle absence. Night-time illuminance was also socially patterned, whereas short-term PM2.5 was roughly an order of magnitude weaker and relative humidity showed no gradient. The acoustic gradient persisted within the urban core alone. Conclusions: Measured burden was carried by the acoustic environment, including its low-frequency component, and by night-time light, not by short-term particulates. The exposure metric and the averaging time determine which disparities are visible at all.

Wastewater treatment is an important barrier to the environmental dissemination of antimicrobial resistance (AMR). However, its effectiveness is typically assessed using measures that do not directly capture resistance gene mobility or pathogen association. Here, we applied a configuration-based genomic risk framework (MetaCompare2.0) to 100 metagenomes (50 paired influent and effluent samples) collected from nine wastewater treatment works over 11 months, quantifying resistome risk based on associations between antimicrobial resistance genes (ARGs), mobile genetic elements, and host taxa. Influent samples exhibited highly variable ecological risk associated with mobile ARGs. Pathogen-associated human health risk was lower and more constrained. Wastewater treatment consistently reduced both ecological and human health risks, driving convergence towards uniformly lower risk resistome configurations. Risk attenuation was reproducible across treatment technologies and could not be explained by assembly quality or physicochemical variation. These findings indicate that wastewater treatment disrupts high-risk ARG configurations and highlight configuration-based genomic risk metrics as scalable tools for benchmarking environmental AMR mitigation.