Environmental Science & Technology Letters Environ.最新文献

Light absorption by brown carbon (BrC) represents a major uncertainty in assessing the climatic effects of carbonaceous aerosols. Using 38,622 PM_2.5 samples collected from the U.S. Chemical Speciation Network (2016–2018) and analyzed by a multiwavelength thermal/optical analyzer (TOA), we applied an enhanced spectral/mass balance receptor model to quantify black carbon (BC), BrC, and nonabsorbing white carbon (WtC) while allowing BrC optical properties to vary across samples. The model achieved excellent fits (r² > 0.98) and revealed a wide range of BrC absorption Ångström exponent (AAE_{405–635 nm} = 2.13 ± 0.74) and mass absorption efficiency (MAE_532 nm = 2.03 ± 0.35 m² g^–1). An inverse AAE–MAE relationship was found, with strongly to moderately absorbing BrC being the most prevalent BrC classes. Seasonal patterns showed higher “organic brownness” (i.e., higher BrC mass fraction in organic carbon regardless of BrC class) but lower MAE in winter and the opposite in summer, reflecting the bleaching evolution of BrC with photochemical aging. BrC abundance also influenced the reconciliation between BC- and TOA-derived elemental carbon, likely through altered thermal–optical carbon analysis splits. This study provides the first nationwide characterization of BrC optical variability from national network data, establishing a scalable framework toward long-term monitoring of organic aerosol absorption within existing regulatory programs.

Nitrous acid (HONO) enhances the atmospheric oxidative capacity by generating hydroxyl radicals (OH), which contribute to secondary pollutants such as ozone (O₃) and particulate matter (PM). These pollutants further modulate HONO formation pathways, creating a complex feedback loop. However, the mechanism by which nitrogen oxide (NO_x) emission reduction affects the HONO-O₃ cycle is not fully clarified. To address this knowledge gap, we conducted two distinct field campaigns during the Spring Festival periods in 2022 and 2023, representing low and high NO_x emission scenarios, respectively. Our results demonstrate that COVID-19 restrictions, combined with the holiday effect in 2022, suppressed HONO production from NO_x-related reactions but enhanced its generation via particulate nitrate (pNO₃^–) photolysis. In contrast, an opposite trend was observed in 2023. Chemical transport model simulations and sensitivity analyses further revealed that moderate anthropogenic NO_x reduction elevated O₃ and dinitrogen pentoxide (N₂O₅) levels, which subsequently elevated nocturnal pNO₃^– formation, establishing a positive feedback loop within the HONO-O₃ cycle. Our findings provide observational evidence of the recycling mechanism for atmospheric pNO₃^–-HONO-O₃ chemistry and suggest that moderate NO_x emission reduction alone is insufficient to mitigate HONO and O₃ pollution.

Interactions between endocrine-disrupting chemicals (EDCs) and nuclear receptors (NRs) are extensively used in virtual screening. However, most models overlook receptor dimerization. Here, we systematically investigate the dimerization dependencies of estrogen receptor α (ERα) and androgen receptor (AR) via big data mining, reporter gene assays, and molecular simulations and further construct a dimerization-driven quantitative framework for endocrine disruption prediction. Database analysis revealed that ERα predominantly functions as homodimers whereas AR primarily exists as monomers. Experiments and simulations further demonstrated that ERα forms stable dimeric complexes (agonist–ERα dimer–coactivator and antagonist–ERα dimer–none systems) while AR maintains stability as a monomer (ligand–AR monomer–coregulator system). Based on these mechanistic insights, receptor-specific quantitative models were developed and applied to predict the endocrine-disrupting potential of representative EDCs, including bisphenols and hydroxylated polybrominated diphenyl ethers. These dimerization-informed models showed robust performance for ERα dimers (R² = 0.605–0.726), whereas AR’s monomeric configuration yielded superior predictive accuracy (R² = 0.788–0.909). These predictive patterns match their mechanisms. Estrogenic disruption critically depends on dimerization and coactivator recruitment, while antiestrogenic activity appears to be primarily dependent on dimerization and largely independent of corepressor involvement. In contrast, AR disruption is primarily driven by ligand binding and coregulator interactions with minimal dimerization involvement. This framework provides an effective, mechanism-grounded alternative to EDC screening.

The widespread occurrence of psychoactive pollutants in surface waters raises concerns for aquatic ecosystems, yet impacts beyond behavioral disruption remain poorly understood. Designed to target neurotransmitter (NT) systems in humans, these contaminants may also interfere with conserved NT pathways in fish. Here we provide the first evidence that fish sperm contain NTs and their receptors, indicating an active NT-mediated signaling system essential for sperm function. Using European perch (Perca fluviatilis) exposed to environmentally relevant concentrations of methamphetamine, we quantified NTs in brain, gonads, and sperm, assessed tissue-specific bioaccumulation, and evaluated sperm performance. Methamphetamine accumulated across tissues, modified NT profiles, and altered sperm motility and velocity. These findings reveal a previously unrecognized pathway of reproductive vulnerability, identifying NT signaling in sperm as a novel target of psychoactive pollutants with potential implications for fertilization success and population resilience in aquatic ecosystems.

Conventional filter-only exhaust sampling misses gas-phase and semivolatile nitrated phenols (NPs), biasing vehicular emission estimates low. We deployed a tandem quartz filter-polyurethane foam (filter-PUF) sampler downstream of dilution to quantify 19 NPs from in-use diesel (China III–VI) and gasoline vehicles (China IV–V), and found that filter-only protocols underestimate total NPs (sum of filter and PUF retained under specified dilution) by 66–76% (diesel) and 66–71% (gasoline). Corrected fuel-based NP emission factors declined sharply with tighter standards (up to 97% lower from China-III to -VI), and the mixture was dominated by 4-nitrophenol and its methylated derivatives (∼50–63%). Applying the corrected factors to China’s 2023 fleet yields vehicular NP emissions of 528 Mg, which is comparable in magnitude to previous estimates for biomass burning (∼670 Mg, based on filter-only data) and potentially larger than that for residential coal (∼178 Mg, based on filter-only data). This suggests that vehicular emissions may rank similarly to, or even surpass, these sources when accounting for nonfilter-retained NPs. Recognizing and correcting this filter-only artifact with a drop-in filter-PUF fix enables more accurate inventories and will improve assessments of NPs’ impacts on urban air quality, HONO budgets, and brown carbon.

Levels of fine particulate matter (PM_2.5) air pollution in the United States have declined substantially in recent decades, yielding substantial benefits to public health. This study evaluates emission reductions across five key economic sectors─electricity, industrial, transportation, agriculture, and residential─and their impact on air quality and health. We employ a recently developed sector-specific inventory that provides emissions and their spatial disaggregation across time in a self-consistent framework. Using a national source-receptor matrix, we estimate annual PM_2.5-attributable mortality and its variability spatiotemporally and by sector. We find that annual PM_2.5-attributable mortality decreased 51% between 2002 (197,000 deaths) and 2019 (96,000 deaths). The largest reductions were from electricity and transportation, especially secondary PM_2.5 from NO_x, SO_x, and VOC emissions. Emissions reductions from industrial and residential sectors were more modest. In contrast, agricultural emissions, especially NH₃, increased over time; the importance of agriculture among the five sectors increased from second-smallest (2002) to the largest (2019). While the reductions in PM_2.5-attributable mortality have been large (approximately a factor of 2), future progress may need to focus greater attention on agricultural emissions, in addition to traditionally dominant sources such as transportation and industry.

Side-chain fluorinated polymers (SCFP) are a class of per- and polyfluoroalkyl substances (PFAS) that are extensively used in functional textiles as water and stain repellents. The potential for environmental contamination through the release of SCFP into aqueous waste streams during textile manufacturing is poorly understood. In this study, SCFP in textile wastewater were characterized using targeted analysis, total oxidizable precursor (TOP) and total hydrolyzable precursor (THP) assays, ultrafiltration, and asymmetric-flow field-flow fractionation (AF4). An investigation into point sources of PFAS precursors in Burlington, NC’s wastewater treatment plant (EBWWTP) using the TOP assay revealed a significant PFAS burden stemming from textile manufacturing operations within the city’s sewershed (max: 12,000,000 ng/L after oxidation), far outweighing domestic contributions. TOP and THP profiling of textile manufacturing wastewater showed that the dominant precursors contained 6:2 fluorotelomer functionality, and ultrafiltration and AF4 showed them to be colloidal in size (hydrodynamic diameter: ∼100 nm), resulting in the determination of SCFP in textile wastewater. PFAS mass loading analysis showed that most SCFP exiting the EBWWTP were associated with sludge rather than effluent, where ∑PFAS concentrations up to 150,000 ng/g were measured using the direct TOP assay; thus, the land application of SCFP-contaminated biosolids may represent a significant route of environmental contamination.

Pesticide gestational exposure may contribute to the development of allergies in childhood, yet evidence on its health impact on urban populations remains limited. This study investigates the association between prenatal exposure to individual and mixed pesticides and allergic outcomes, including asthma, wheezing, and eczema, at age 6 in 387 mother-child pairs from the German prospective cohort LiNA. Forty pesticides and metabolites were detected in urine during pregnancy through nontargeted screening, and 11 were selected (detection rate ≥ 17%) for further analysis. Multivariable logistic regression models adjusted for covariates revealed statistically significant associations between dihydroxy-pyrimethanil and asthma (aOR = 1.35, 95% CI: 1.02–1.79), and fluazifop-desbuthyl and wheezing (aOR = 1.14, 95% CI: 1.01–1.30). No significant associations were observed for eczema. The weighted quantile sum (WQS) regression showed that higher pesticide coexposures significantly increased wheezing odds (aOR = 2.08, 95% CI: 1.21–3.56). The main components of the WQS index were fluazifop-desbuthyl, flonicamid, hydroxy-metazachlor, and terbuthylazine, accounting for 67% of the overall mixture effect. These findings suggest that prenatal exposure to pesticides, likely from dietary sources, may increase the risk of childhood asthma and wheezing. Replication studies in populations with comparable pesticide exposures, along with experimental mechanistic validation, will strengthen the understanding of the observed associations.

The co-occurrence of microplastics and heavy metals poses significant environmental risks. However, conventional analytical methods are ex situ, destructive, and unable to capture real-time adsorption dynamics. We present a low-field nuclear magnetic resonance (LF-NMR) technique that enables the in situ, nondestructive, time-resolved quantification of paramagnetic metal adsorption onto microplastics. We applied this method to monitor the adsorption of Cu(II) and Cr(III) onto poly(vinyl chloride) and polystyrene microplastics under diverse water chemistry conditions. Validation using inductively coupled plasma mass spectrometry confirmed the excellent accuracy of the proposed method, which exhibited high linearity (R² > 0.99), an average recovery of 100.7%, and detection limits of approximately 0.1 mg L^–1. The method showed robust sensitivity and stability across varying salinity (0–250 mM) and pH (3.5–6.5) with minimal interference. LF-NMR revealed a two-stage adsorption mechanism characterized by rapid surface binding followed by slower intraparticle diffusion. Critically, the nondestructive nature preserved the microplastic–paramagnetic metal complexes for subsequent characterization, overcoming the limitations of conventional destructive techniques. This real-time approach bridges quantitative detection with mechanistic understanding, providing a powerful tool for elucidating microplastic–metal interactions and showing strong potential for nanoplastic and aging studies.

Natural attenuation (NA) and propane biostimulation (PB) are effective and cost-efficient in situ techniques for remediating 1,4-dioxane (dioxane)-contaminated groundwater. We designed and validated three primer/probe sets capable of distinguishing among three clusters of group-6 propane monooxygenases (PRMs) and evaluated their correlation with dioxane degradation in microcosms mimicking NA and PB treatments. These biomarkers demonstrated exclusive specificity and high sensitivity (500–1600 copies/mL groundwater). Microcosms prepared with groundwater at seven monitoring wells across two sites exhibited significant dioxane removal, particularly where active propane biosparging was implemented. Using Taqman-based qPCR assays, prmAI and prmAIII were most dominant, while prmAII and thmA were absent, indicating the pivotal roles of Cluster I and III PRMs in the observed dioxane biodegradation. Moreover, the average abundance of total prmA, as well as prmAI and prmAIII individually, correlated significantly with the dioxane degradation rates. Correlation and regression analyses highlighted a stronger association of prmAIII than prmAI, suggesting a greater influence of Cluster III PRMs under tested conditions. Samples with total prmA below 10^4.5 copies/mL groundwater exhibited negligible dioxane removal, suggesting a practical threshold for assessing the bioremediation potential. These findings establish cluster-specific group-6 PRM biomarkers as effective tools for predicting and monitoring dioxane biodegradation in impacted aquifers.