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.

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 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.

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.

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.

Wastewater-based epidemiology (WBE) has become a cornerstone of public health surveillance, yet routine regulatory monitoring remains largely focused on respiratory viruses and selecting antimicrobial resistant bacteria. Emerging foodborne parasites, such as Cyclospora cayetanensis, remain excluded from standard environmental surveillance panels despite increasing domestic outbreaks. This study presents a laboratory-based pilot protocol evaluating the feasibility of extracting and quantifying C. cayetanensis from urban wastewater across the Chicago metropolitan area. Using sample concentration via centrifugation and mechanical bead-beating, automated magnetic bead nucleic acid extraction, and digital PCR (dPCR), we demonstrate high-sensitivity detection in municipal influents and sewer nodes. These findings establish a proof-of-concept laboratory methodology to support the expansion of regulatory public health surveillance frameworks to include non-routine protozoan pathogens.

Cyclosporiasis is a foodborne illness caused by the parasite Cyclospora cayetanensis. Clinical surveillance often lags infection by weeks because diagnosis depends on a clinician ordering a test that is not part of routine parasite panels. Wastewater metagenomic sequencing does not depend on care seeking, which may be useful for early detection and community monitoring. We designed 1,670 31-mers from C. cayetanensis mature ribosomal RNA and retained 1,464 without an exact non-target match in the 28 July 2025 NCBI core_nt release. By analyzing 293 public wastewater metagenomes, we selected a threshold of 24 distinct diagnostic 31-mers on one read. Applying that threshold to 2,333 public runs from BioProject PRJNA1247874 yielded putative C. cayetanensis reads in 81 runs, or 3.5%, and in 24 of the 30 longitudinally sampled sewersheds. Detections rose through the summer in two consecutive years, matching the known seasonality of cyclosporiasis. The most parsimonious explanation is that these reads come from parasites shed into wastewater, although undescribed Cyclospora species absent from reference databases cannot be excluded. The same approach can be applied to other pathogens in existing wastewater sequencing data.

Background: Amplicon-based next-generation sequencing is a cornerstone of viral genomic surveillance, but it often produces datasets with highly uneven read coverage due to PCR amplification bias. This leads to excessive data generation and substantial computational overhead for downstream bioinformatic analysis. Results: We evaluated the efficacy of two data reduction strategies on 220 SARS-CoV-2 clinical specimens and 12 wastewater samples: random subsampling with SeqKit and read depth normalization with BBNorm. FASTQ files were reduced to target depths from 10X to 10,000X to compare genome coverage, lineage assignment concordance, and computational resource usage. Both strategies markedly reduced total processing time. For clinical isolates, read depth normalization corrected for amplification bias resulting in highly concordant lineage assignments at a target depth of just 200X. Random subsampling preserved inherent bias but produced reliable assignments at depths over 500X. Reducing target depths below 500X in complex wastewater mixtures severely degraded variant deconvolution accuracy and heavily skewed lineage abundance profiles for both methods. Conclusion: Both random subsampling and read depth normalization successfully reduce computational overhead while preserving key clinical sequencing metrics at appropriate reduction settings. The optimal method depends on the analytical goal, ranging from computationally lightweight random subsampling for rapid lineage assignment, to read depth normalization for generating high-quality consensus sequences. However, aggressive data reduction should be avoided in environmental surveillance, where maintaining a high baseline sequencing depth is critical for accurate mixed-variant deconvolution.

Respiratory viruses pose a major threat to human health. Environmental virus persistence in respiratory secretions is essential for successful spread, yet studies have focused largely on a select few viruses in non-physiological matrices. Here, we compared the stability of structurally distinct human respiratory viruses, adenovirus, influenza virus, and rhinovirus, in deposited particles of pooled human saliva under indoor-relevant relative humidity (RH) conditions. Adenovirus exhibited <2.2-log10 decay over 6 h regardless of RH, while rhinovirus exhibited significantly greater degradation (>3.8-log10, at 50% and 80% RH). Influenza virus showed minimal decay at 20% and 50% RH but degraded significantly more (3-log10) at 80% RH. To distinguish aspects of human saliva that are key determinants in driving virus decay, we recapitulated saliva composition using the inorganic solute and protein concentrations determined via ion-coupled plasma mass spectrometry and proteomics, respectively. Rhinovirus was significantly more stable in simulated saliva than in human saliva at 50% RH, while influenza virus and adenovirus behaved similarly in both matrices. These findings emphasize virus-specific environmental persistence and highlight limitations of relying on a single virus and particle matrix for defining public health strategies. Ultimately, these insights will contribute to approaches for mitigating environmental transmission of distinct respiratory pathogens.

Urban green infrastructure is increasingly promoted as a public-health intervention, yet the biological features that determine exposure to potentially beneficial plant-derived volatile compounds remain poorly understood. Here we quantified airborne terpenes and terpenoids across five contrasting urban greenspaces in Oxford, UK, and related chemical profiles to plant diversity, vegetation structure and surrounding habitat characteristics. Ambient air samples collected across spring and summer were analysed by thermal-desorption gas chromatography-mass spectrometry, alongside field surveys of taxonomic richness, canopy cover, vegetation volume and ground composition. Terpene and terpenoid scentscapes differed strongly among sites and through time, with monoterpenes dominating detected profiles. Sites with greater plant richness and greater vegetation volume below 1.5 m consistently showed higher terpene/terpenoid abundance, whereas total vegetation volume, canopy cover and tree abundance were weaker and less consistent predictors. These relationships were specific to plant-associated chemical classes and were not observed for predominantly anthropogenic volatile compounds. These patterns were resolved across only five independent sampling sites, and the relationships reported here should therefore be considered exploratory. Our findings suggest that human exposure to plant-derived volatiles in cities may be maximised not simply by increasing tree cover, but by designing biodiverse, structurally complex lower-to-mid-storey vegetation within the breathing zone. These results provide an empirical basis for incorporating scentscape ecology into health-oriented urban greenspace design.

Antimicrobial resistance (AMR) is a major threat to modern medicine and an emerging environmental pollutant. Wastewater-based monitoring offers a scalable alternative to traditional surveillance by enabling population-level monitoring across One Health compartments. However, it remains unclear how well bacterial variants detected in wastewater reflect those causing clinical infections. Here, we assessed the prevalence of carbapenem-resistant Escherichia coli (CREC) in wastewater from Uppsala, Sweden, and compared wastewater isolates with clinical isolates from the same region and period. We observed partial overlap between wastewater and clinical CREC populations, but several common clinical variants were not detected in wastewater and vice versa. CREC prevalence was an order of magnitude higher in wastewater receiving hospital effluent, yet this did not improve concordance with clinical isolates, suggesting that hospital wastewater may artificially inflate CREC prevalence estimates. These findings indicate that wastewater CREC prevalence does not necessarily reflect the regional clinical burden. Furthermore, metagenomic sequencing of wastewater-derived E. coli populations rarely detected CREC resistance genes, suggesting that CREC abundance is below the detection limit of this approach and that targeted enrichment is required for reliable monitoring. Together, our results show that while wastewater-based monitoring can complement AMR surveillance, it should be interpreted cautiously when used as an indicator of clinical risk.

Background: Chronic arsenic exposure in drinking water causes skin lesions and cancers and raises infant, cardiovascular and all-cause mortality in Bangladesh. National surveys tested source water in 2012-13, 2019 and 2025 with different kits, so the trend is uncertain. Objectives: We estimated how arsenic in source water changed after laboratory adjustment of 2012-13 readings, and how many people remained exposed. We also assessed whether districts high in earlier surveys held most people exposed in 2025. Methods: We analysed 11,624 households in three Multiple Indicator Cluster Surveys. We counted arsenic strictly above 10 and 50 parts per billion (ppb). Results: Estimates reproduced published 2019 and 2025 tables. After laboratory adjustment of 2012-13, the share above 10 ppb fell from 24.0% to 14.4% (adjusted ratio 0.61, sampling 95% CI 0.55 to 0.67; 0.69 with interview month). Above 50 ppb it fell from 10.9% to 8.6% (0.80, 0.69 to 0.93; 0.93 with month). Most of the fall at 10 ppb occurred within source types. Without false positives, it would vanish only if later kits detected 61% of sources above 10 ppb. About 26 million people used such water in 2025 (kit scenarios 23 to 32 million). The 25 districts high in 2012-13 and 2019 held 39% of the population but 72% of those exposed (bootstrap 95% interval 60 to 76). Clustering was evident, but no district was a significant hotspot. Conclusions: Arsenic above 10 ppb was lower in 2025 than in 2012-13, but the size of the fall depends on unverified later kits. Change at 50 ppb and since 2019 was unclear after month adjustment. One household in seven exceeded the WHO guideline in 2025. Districts found high earlier held most exposed people, supporting prioritised well testing there alongside broader surveillance. Future surveys need one kit with a laboratory cross-check.

In 2024, Chicago experienced a measles virus outbreak. Air samples collected as part of routine respiratory virus surveillance from three hospitals that received measles patients were retrospectively analyzed. Measles virus was detected in air samples from one emergency department across five weeks when measles patients were present and another when no known cases were present. Two of three viral sequences derived from air samples were identical to measles patients. The source of one diverging sequence could not be identified and may represent a case not identified by traditional surveillance methods. Air sampling may supplement measles investigation, surveillance and response.

Total serum perfluorooctane sulfonate (PFOS) concentration and its isomer composition describe different aspects of internal exposure, but their respective associations with depressive symptoms remain uncertain. We examined adults aged 18-25 years in NHANES August 2021-August 2023 using survey-weighted models of the Patient Health Questionnaire-9 (PHQ-9). Total measured PFOS was the sum of linear PFOS and pooled monomethyl-branched PFOS; composition was their log-ratio. The analytic cohort included 169 participants, with 147 complete cases for core adjustment. Median total PFOS was 1.70 ng/mL, the median linear fraction was 72.2%, and the weighted prevalence of PHQ-9 [&ge;]10 was 22.6%. In the joint adjusted model, a doubling of total PFOS at fixed composition corresponded to -0.49 PHQ-9 points (95% CI, -1.65 to 0.68); a doubling of the linear-to-branched ratio at fixed total corresponded to 0.21 points (-1.94 to 2.36). Algebraic rescaling across the reported interquartile ranges yielded differences of -0.58 points (-1.95 to 0.81) for total PFOS and 0.13 points (-1.16 to 1.41) for composition. The inverse continuous-score association weakened with adjustment, whereas the screening odds ratio primarily lost precision. Excluding three observations with an isomer below detection shifted both joint coefficients. The data therefore do not establish an independent composition association or equivalent isomer effects. Experimental evidence supports candidate oxidative, inflammatory, and synaptic pathways, but differential protein binding and elimination prevent a serum composition ratio from being interpreted directly as brain dose or toxicity. Larger longitudinal analyses with isomer-resolved exposure and toxicokinetic measurements are needed to test these pathways.

Inhalation of airborne per- and polyfluoroalkyl substances (PFAS) represents an important yet understudied exposure route. While volatile organic compounds (VOCs) have been widely explored as biomarkers of toxicant exposure, their potential for early detection of PFAS-induced pulmonary toxicity remains largely unexplored. This study investigated VOC profiles in human alveolar (A549) and bronchial (BEAS-2B) epithelial cells following exposure to environmentally relevant PFAS concentrations (1, 5, and 10 ppb) for 12, 24, and 48 h. VOCs were analyzed using headspace solid-phase microextraction coupled with gas chromatography-Orbitrap mass spectrometry. We observed significant concentration- and time-dependent alterations in VOC profiles in both cell models. The principal VOCs associated with PFAS exposure include butanal, acetone, 2-butanone, 2-nonanone, (E)-2-nonenal, (E)-2-octenal, (E)-2-heptenal, 2,4-heptadienal, 2,4-nonadienal, 2,4-decadienal, 1-pentanol, and 1-hexanol. Cell type-specific regulations were observed, reflecting differential metabolic responses between transformed and non-transformed lung epithelial cells. Metabolite set enrichment analysis indicated perturbations in ketone body metabolism, consistent with altered cellular energy metabolism. Complementary qPCR analysis revealed altered expressions of CYP1A1, CYP2E1, ALDH1A1, and ALDH2, supporting a mechanistic link between PFAS exposure and oxidative stress, lipid peroxidation, and impaired aldehyde detoxification. These findings demonstrate that VOC profiling, combined with transcriptional analysis, can reveal PFAS-induced metabolic perturbations in pulmonary epithelial cells.

A central question in ecology and evolution is determining when environmental challenges translate into stress and biological harm. Human-derived pollutants are often assumed to be inherently damaging; however, their effects may depend strongly on ecological and physiological context. Microplastics exemplify this complexity, eliciting heterogeneous responses across taxa rather than uniform toxicity. Here, we synthesise evidence from 14 meta-analyses encompassing 9,101 effect sizes to identify the conditions under which microplastic exposure leads to damage, neutrality, compensation, or stimulation. These syntheses reveal clear negative effects alongside frequent neutral outcomes and occasional stimulatory responses. Microplastic effects vary with particle characteristics and exposure conditions and are strongly moderated by species-specific traits and life stage. We further argue that plasticity in the gut and in behavioural and physiological traits may buffer microplastic effects. Emerging evidence also indicates that biofilm colonisation alters the physicochemical and biological properties of microplastics, potentially modifying their ecological interactions and toxicity profiles. By reframing microplastics as context-dependent challenges rather than universally toxic agents, we provide a conceptual framework for understanding animal responses under realistic ecological conditions and identifying the biological and environmental contexts in which microplastic exposure is most likely to result in harm.

Coal-fired power plants remain a major source of fine particulate matter (PM2.5) exposure and mortality in the United States. Announced retirement dates mark when those burdens are expected to end, but rising electricity demand, partly from data centers supporting cloud computing and artificial intelligence, has led utilities and regulators to revisit them. Of 50 coal plants scheduled in January 2024 to retire before 2035, 20 had later or removed dates by January 2026. Projecting coal PM2.5 and mortality among Medicare beneficiaries from the 20 plants for 2026-2035, we estimate the revised schedule would result in 1,256 additional deaths (1,136 to 1,376), raising mortality to 3.1 times the original burden. Eighteen plants operate in balancing authorities with hyperscale data-center demand, and federal orders and utility filings supporting several plants' operation cited data-center growth. Retirement schedules are revised faster than health consequences are assessed, and those delays carry a measurable mortality cost.