环境科学与技术最新文献

Aquatic organisms may frequently be exposed to short-term discharges of contaminants, including those from pesticide use, stormwater runoff, or industrial effluents entering waterways. Here, a new microalgal multispecies flow cytometry-based bioassay is used to assess knowledge gaps in risk assessments posed by the short-term exposure of organisms to contaminants. The toxicities of atrazine, metolachlor, and copper were assessed using four exposure scenarios, a 72 h exposure (continuous), an 18 h pulse exposure, and two 3 h pulse exposures (light and dark conditions), that assessed chronotoxicity. The influence of duration on toxicity explored the utility of two expressions of chemical-exposure dose: pulse-exposure concentration (PeC) and time-weighted average concentrations (TACs). The three coexisting microalgae (Monoraphidium arcuatum, Nannochloropsis-like sp., and Pediastrum duplex) tolerated higher concentrations for shorter 3 and 18 h pulses compared to continuous 72 h exposures. Toxicity estimates calculated on a TAC basis were effective for predicting the toxicity of the pulses of atrazine, metolachlor, and copper. Fluorescence data collected using flow cytometry were linked to physiological diel changes for each species. Chronotoxicity was observed for copper with two species. While continuous contaminant exposures provide a conservative estimate of toxicity compared to pulses, the duration and time of exposure are critical factors to consider when assessing the toxicity of contaminants to microalgae.

Accurate estimation of atmospheric chemical concentrations from multiple observations is crucial for assessing the health effects of air pollution. However, existing methods are limited by imbalanced samples from observations. Here, we introduce a novel deep-learning model-measurement fusion method (DeepMMF) constrained by physical laws inferred from a chemical transport model (CTM) to estimate NO₂ concentrations over the Continental United States (CONUS). By pretraining with spatiotemporally complete CTM simulations, fine-tuning with satellite and ground measurements, and employing a novel optimization strategy for selecting proper prior emission, DeepMMF delivers improved NO₂ estimates, showing greater consistency and daily variation alignment with observations (with NMB reduced from −0.3 to −0.1 compared to original CTM simulations). More importantly, DeepMMF effectively addressed the sample imbalance issue that causes overestimation (by over 100%) of downwind or rural concentrations in other methods. It achieves a higher R² of 0.98 and a lower RMSE of 1.45 ppb compared to surface NO₂ observations, overperforming other approaches, which show R² values of 0.4–0.7 and RMSEs of 3–6 ppb. The method also offers a synergistic advantage by adjusting corresponding emissions, in agreement with changes (−10% to −20%) reported in the NEI between 2019 and 2020. Our results demonstrate the great potential of DeepMMF in data fusion to better support air pollution exposure estimation and forecasting.

This study introduces a novel physically constrained deep-learning fusion method for accurately estimating the atmospheric surface concentration to improve better exposure estimates for health assessment of air pollution.

Genotoxic and immunosuppressive characteristics are central to the carcinogenic profile of hexavalent chromium [Cr(VI)], with dysregulation of circulating exosomal miRNA potentially acting as oncogenes or tumor suppressors or participating in the carcinogenic landscape of heavy metals through immunomodulation. In this two-stage epidemiological investigation, we unveiled for the first time the perturbations of exosomal miRNAs among individuals exposed to Cr(VI), alongside their significant correlations with biomarkers of genetic injury (γ-H2AX positivity in circulating lymphocytes and the urinary 8-OHdG levels) and immunological indicators (immunosuppressive PD-1 expression), which was supported by validation in an external cohort. Employing a support vector machine model, we discerned that exosomal miRNAs, particularly miR-4467, miR-345-5p, miR-144-3p, and miR-206, exhibited a remarkable capacity to delineate the genetic damage stratum within the population with high precision, and the target genes predicted of these miRNAs further elucidated their intricate regulatory interplay with the effector biomarkers. Additionally, employing a Bayesian mediation framework, we observed the intermediary function of miR-4467 in the nexus between chromium exposure and the escalation of urinary 8-OHdG levels (mediation effect: 0.47, P < 0.05). Although our findings suggested a link between extracellular miRNAs and immunosuppressive biomarkers, this association did not achieve validation in the external cohort, possibly due to population heterogeneity. Collectively, this study advanced our understanding of the epigenetic orchestration of health hazards of Cr(VI) by exosomal miRNAs, shedding light on their expression signatures and their intricate interplay with Cr(VI)-induced genetic and immunological perturbations, thus providing novel perspectives on the toxic pathways of heavy metals.

Tire wear particles (TWPs), generated from tire abrasion, contribute significantly to environmental contamination. The toxicity of TWPs to organisms has raised significant concerns, yet their effects on terrestrial plants remain unclear. Here, we investigated the long-term impact of pristine and naturally aged TWPs on water spinach (Ipomoea aquatica) and its rhizospheric soil. The results indicated that natural aging reduced the toxicity of TWPs, as evidenced by decreased levels of polycyclic aromatic hydrocarbons (PAHs) in soil and TWPs themselves. Consequently, aged TWPs were found to enhance the plant growth and chlorophyll content, whereas pristine TWPs increased the plant stress. Furthermore, aged TWPs improved soil organic matter (SOM) and total organic carbon (TOC), thereby boosting the microbial enzymes involved in nitrogen cycling. Metabolomic analysis revealed that aged TWPs upregulated key pathways related to carbon and nitrogen metabolism, enhancing plant growth and stress responses. Additionally, rhizosphere bacterial diversity was higher under aged TWPs, favoring nutrient-cycling taxa such as Acidobacteriota and Nitrospirota. Pristine TWPs may lead to overproliferation of certain dominant species, thereby reducing microbial diversity in soil, which could ultimately compromise the soil health. These findings contribute to a deeper understanding of the mechanisms underlying TWP toxicity in plants and highlight the necessity for further research on the impact of aged TWPs across various plant species over different exposure durations for comprehensive risk assessment.