Search Results (14,043)

This study estimates the association between respiratory outcomes among employees of a secondary aluminum plant and airborne pollutants. Additionally, it looks into the relationship between pulmonary dysfunction in workers and X-Ray repair cross-complementing one (XRCC1) gene polymorphisms. 110 exposed workers and 58 non-exposed workers were enrolled in the study. Measurements were conducted on sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and particulate particles. Pulmonary function was tested. Eosinophil cationic protein (ECP), C-reactive protein (CRP), matrix metalloproteinase-1 (MMP-1), interleukin 6 (IL6), granulocyte-macrophage colony-stimulating factor (GM-CSF), XRCC1 protein, and genotyping of XRCC1 gene polymorphisms were examined. The annual average concentrations of particulate matter (PM_2.5, PM₁₀), total suspended particulates (TSP), SO₂, and NO₂ were lower than the permissible limit. The areas around ovens, evaporators, and cold rolling mills exhibited the highest amounts. The majority of employees in these departments had impaired lung function. Prolonged exposure was associated with a significant decrease in forced expiratory volume in 1 s (FEV1%) and forced vital capacity (FVC%) among the exposed group (p = 0.001 & 0.04, respectively). Serum XRCC1 levels were significantly higher among exposed workers (p = 0.02). Inflammatory biomarkers showed no statistically significant differences between groups. Aluminum workers are at risk of developing respiratory disorders. The level of serum XRCC1 may serve as a potential biomarker for detecting susceptible workers. Full article

Driven by rapid global urbanization and expanding urban footprints, air pollution, particularly from industrial emissions and vehicular exhaust, has intensified, with rising concentrations of inhalable particulate matter (PM) posing direct threats to public health. To address this challenge, we conducted field measurements of ambient PM concentrations across diverse urban plant communities and quantitatively compared their capacity to mitigate four key size-fractionated pollutants: total suspended particles (TSPs), PM₁₀, PM_2.5, and PM₁. Our objective was to identify the most effective plant community type for PM abatement in urban settings. Results demonstrate that: (1) evergreen broad-leaved forests exhibit the highest overall PM removal efficiency among all studied communities; (2) removal efficacy declines markedly with decreasing particle size, indicating limited capacity to capture ultrafine particles (e.g., PM₁); and (3) seasonal performance peaks in summer, especially for deciduous broad-leaved forests attributable to maximal leaf area index, enhanced stomatal activity, and favorable meteorological conditions. By rigorously evaluating species composition, canopy structure, and seasonal dynamics, this study provides empirically grounded guidance for evidence-based urban greening strategies aimed at optimizing airborne particulate mitigation worldwide. Full article

Urban air pollution is increasingly recognised as a determinant of mental wellbeing, yet most existing studies rely on static exposure estimates and lack spatial granularity. This limits understanding of how pollutant-specific patterns influence psychological states in real-world settings. To address this gap, we integrate real-time environmental and physiological data from 40 participants using the DigitalExposome dataset, applying multivariate and spatial analysis techniques. Our findings confirm that Particulate Matter (PM_2.5) exerts the strongest negative association with mental wellbeing while extending prior work by establishing a preliminary ranking of other pollutants Particulate Matter (PM₁₀), Particulate Matter (PM₁), Carbon Monoxide (CO), Nitrogen Dioxide (NO₂), Ammonia (NH₃). We applied statistical and spatial analysis methods, including heatmaps and Voronoi diagrams, to explore links between pollutants and wellbeing and compare the relative influence of air pollution and noise. This enabled identification of pollutant-specific hotspots and multi-level wellbeing patterns across individual, accumulated, and collective scales. These results demonstrate the value of spatial analysis for environmental health research and support targeted urban interventions, such as green space placement and traffic re-routing, to mitigate mental wellbeing risks. Full article

Agroforestry, where trees and shrubs are planted in row-alley systems, can utilize the natural ability of plants to interact with pollutants and serve as a passive biotechnological method for improving air quality. A method for programming air phytoremediation processes is presented, using appropriately shaped plant structures, considering species characteristics and the spatial configuration of plants in row-alley plantings. The main objectives of this study were: to determine the relationship between pollution reduction and the characteristics of plant communities, considering the parameters of individual plants and group characteristics, to determine strategic parameters for the interaction between plants and pollutant flows, and to identify optimization paths for each stage. The optimization of the air phytoremediation process is presented using the example of changes in the fine particulate matter (PM_2.5) concentration pattern, analyzed through numerical experiments using micrometeorological computational fluid dynamics models (ENVI-met software). Ex-ante analysis of hypothetical scenarios showed that introducing appropriate configurations of variable vegetation structure could lead to pollution reductions of up to 19%. The effectiveness of the presented plant systems qualifies this method as a type of bioengineering technology, supporting the multifunctionality of agroforestry systems. Full article

Diseases like downy mildew (DM) and powdery mildew (PM) are characterized by whitish symptoms on leaves of many plant species. Hyperspectral imaging (HSI) has been successfully used for the detection and identification of various diseases associated with different symptoms. Proximal HSI (400–1000 nm) was tested under controlled conditions for its potential to differentiate among whitish disease symptoms on leaves of apple and grapevine due to DM, PM, and a non-melanized mutant of apple scab at the leaf and tissue (microscopic) level. Spectral traits were analyzed by using difference spectra and spectral ratios, spectral vegetation indices like NDVI, and average brightness and half NIR increase introduced here and were confirmed by supervised spectral angle mapper classification. Although similar, spectral signatures of whitish symptoms were significantly different and could be used for spectral separation of diseases; differences were greater on the tissue level than on the leaf level. However, disease detection and differentiation were affected by spectral differences between plant species, leaf sides, the variability of symptoms in space and time, and the integrity of superficial pathogen structures. In the case of similar disease symptoms, additional spectral information on the effects of pathogens on plant metabolism, e.g., leaf water patterns, supports spectral differentiation of leaf diseases. Full article

The global functional food market continues to expand, and edible mushrooms are emerging as high-value ingredients due to their rich nutritional profile, particularly their high protein content, balanced amino acid composition, and dietary fiber. This growing industrial interest is reflected in the registration of more than 322 patents in the past five years according to the Derwent Innovation patent database. Recent advances include the integration of precision mycology (PM) and omics-based approaches, such as CRISPR-Cas9, into solid-state fermentation and submerged fermentation, enabling improvements in natural umami flavor and bioactive composition. Innovative products, including meat analogues with fibrous textures, functional beverages such as kombucha and juices, and fermented dairy products such as yogurts and cheeses, have been formulated to deliver prebiotic, antioxidant, and immunomodulatory properties. Future trends indicate a shift towards the production of high-value nutraceutical peptides and biomass, together with the adoption of artificial intelligence (AI) and the Internet of Things (IoT) to enhance bioreactor automation and scalability. Nevertheless, significant challenges remain, including regulatory constraints, the scarcity of clinical validation in humans, and the need for strict control over the bioaccumulation of heavy metals in mushroom-derived raw materials. Addressing these gaps will be critical for advancing regulatory frameworks, improving industrial standardization, and supporting the translational development of mushroom-based functional foods. Full article

In the present study, an amperometric aflatoxin B1 sensor was constructed via modifying a nano-graphite carbon paste microelectrode with a cationic surfactant of cetyltrimethylammonium bromide (CTAB) and a perfluorosulfonic acid resin of Nafion through a simple and controllable electrochemical scanning method. The experiment results show that CTAB–Nafion composite film has a good catalytic effect on the electrochemical response of aflatoxin B1. The electrocatalytic mechanism was investigated with the aid of different analytical techniques, including square wave voltammetry, electrochemical impedance spectroscopy, chronocoulometry, energy-dispersive spectroscopy and scanning electron microscopy. Under the optimal conditions, the linear range of the sensor is from 0.1 nM to 100 nM, and its detection limit and sensitivity are 20 pM (S/N = 3) and (24.9 ± 1.51) μA/nM, respectively. The accurate and rapid detection of aflatoxin B1, which has strong carcinogenicity, is of great significance for food quality monitoring and the protection of human health. Therefore, finally, the sensor was used to detect the concentration of aflatoxin B1 in milk and soy sauce samples, and the favorable recovery results indicated its good application prospects. Full article

A novel sensitive and selective electrochemiluminescence (ECL) sensor using nitrogen-doped graphyne as the platform was proposed for kanamycin (KAN) detection. First, nitrogen-doped graphyne nanomaterial (1N-GY) with high conductivity was synthesized using a high-energy ball milling method. Compared with ordinary graphyne, the addition of nitrogen atoms can improve the conductivity of the material and reduce the electronic migration energy barrier. Then it was used as a substrate material of the ECL sensor, not only increasing the conductivity of the biosensor but also improving the sensitivity of the ECL sensor by providing more immobilization space for the luminescent probe of Nafion-coated mesoporous silica adsorbed Ru(bpy)₃²⁺ (mSiO₂@Nafion@Ru(bpy)₃²⁺). On this basis, mSiO₂@Nafion@Ru(bpy)₃²⁺ functionalized DNA probes were used as luminescent and capture probes to specifically recognize different concentrations of KAN to produce ECL signals. Under optimal conditions, the proposed ECL sensor exhibited good linearity (10⁻¹²–10⁻⁶ M KAN) and a low detection limit of 1.08 pM. The prepared biosensor with good stability and selectivity successfully detected KAN in honey and milk samples, with spiked recovery rates ranging from 98% to 111.79%. This method not only expands the application of 1N-GY as a novel graphitic material in ECL biosensors but also provides an effective way to check antibiotics in dairy products. Full article

Myo-inositol (MI) is recognized as a potential stress regulator capable of alleviating abiotic stress. The objective of this study is to analyze the role of MI in the salt stress response of Daucus carota L. and its potential mechanisms. “Hongxin Qicun” carrot seedlings were subjected to five treatments: control; salt stress (50 mM NaCl); and salt stress combined with 50, 100, or 200 μM of MI. Through an integrated approach combining physiological assays, non-invasive micro-test technology (NMT), and gene expression profiling, we found that salt stress severely inhibited seedling growth, disrupted K⁺/Na⁺ homeostasis, and triggered excessive H₂O₂ accumulation. Exogenous MI application mitigated these salt-induced damages, with 100 μM MI exerting the optimal effect. MI enhanced Na⁺ efflux and reduced K⁺ efflux in carrot roots under salt stress. Inhibitor experiments indicated that MI-promoted Na⁺ efflux relies on active transport via the plasma membrane (PM) Na⁺/H⁺ antiporter system, and qRT-PCR analysis showed that this response was accompanied by the upregulation of DcSOS1. Furthermore, MI contributes to K⁺ homeostasis by synergistically modulating PM H⁺-ATPase and high-affinity potassium transporters. The established proton gradient helps reduce salt-induced K⁺ loss through depolarization-activated potassium channels and non-selective cation channels. MI treatment decreased electrolyte leakage, malondialdehyde content, and H₂O₂ accumulation by enhancing the activities of the plant antioxidant defense system. Meanwhile, MI upregulated the expression of myo-inositol oxygenase (DcMIOXs) genes, which may contribute to osmotic balance maintenance and facilitate ROS scavenging. In conclusion, exogenous MI alleviates salt-induced physiological disorders in Daucus carota L. by coordinately regulating K⁺/Na⁺ and ROS homeostasis, with 100 μM identified as the optimal concentration for this effect. Full article

Cross-sectional surveys of psychological distress using the Kessler-6 tool (K6+) were conducted among training cohorts per year of New Jersey (NJ) secondary school teachers between January 2022 and December 2024. Data downloaded for 12–18 annual virtual synchronous live session training date ranges related to specified teacher cohorts, consisting of 30 calendar days prior to its date to relate to K6+ questions (575 unique participants across 42 total live sessions). Utilizing data from federal/state air quality monitoring stations (AQMS), we constructed a database of estimated exposures to ambient/outdoor air quality. Cohorts were broken down by school district (SD) and paired with AQMS based on approximate geographic proximity for each SD’s school’s physical address utilizing NJ-GeoWeb. Once addresses were reported and associated with two AQMS, associated reviewed daily criteria pollutant data (2021–2024) were retrieved for particulate matter (PM, PM₁₀ and PM_2.5) and ozone. Data were averaged for relevant stations. Analyses suggested prior 30-day PM_2.5 showed a significant negative correlation with K6+ scores, −0.32 with PM_2.5 concentration (p = 0.04) and −0.48 with PM_2.5 AQI (p = 0.002); however, wind speed had a positive association, 0.33, with K6+ scores (p = 0.03). These results suggested how specific events and meteorological conditions affected ambient air quality for only some of the prior 30 days yet still potentially influenced K6+ scores for some cohorts, e.g., large wildfires then prevailing winds. More research with improved exposure assessment is warranted. This initial environmental epidemiology study with ecological design can inform future collaborative research and practice work on mental health and the effects of environmental factors. Full article

The Chengdu–Chongqing Twin-City Economic Circle (CC-TCEC), located in the Sichuan Basin, frequently experiences persistent winter PM_2.5 pollution due to basin-constrained ventilation and strong meteorology–emission coupling. Using daily PM_2.5 observations from 113 monitoring stations with a strict two-year training and one-year testing split, we develop hybrid spatiotemporal forecasting models that couple a graph neural network (GCN/GAT) for inter-station spatial dependence learning with a temporal backbone (LSTM/Transformer) for evolving concentration dynamics. We adopt a rolling one-day-ahead forecasting scheme using a 7-day look-back window. Across 12-month, 6-month, and 3-month evaluation windows, the meteorology-augmented Multi-GAT-Transformer shows a slight but consistent advantage over the other tested variants, suggesting potential benefits of attention-based spatial weighting and long-range temporal self-attention under nonstationary basin pollution regimes. Spatiotemporal mappings derived from the best-performing configuration suggest that elevated winter PM_2.5 is mainly associated with low-lying areas such as the Chengdu Plain, industry clusters, and dense urban cores, with peaks that also coincide with the New Year and the pre-Lunar New Year period, suggesting a possible contribution from elevated traffic and production activity. These impacts are amplified by winter stagnation (low winds, high humidity, limited precipitation). From a policy perspective, the results support sustainability-oriented winter haze management by enabling early episode warning and hotspot prioritization. Full article

High-temperature particulate matter (PM) filtration remains a fundamental challenge, because most fiber filters not only face the challenge of high temperatures but also suffer from an inherent trade-off between capture efficiency, pressure drop, and service life. This paper reports a hierarchical layered zirconia (ZrO₂) ceramic fiber aerogel featuring a continuous multiscale gradient. The aerogel was prepared by gradient air-blown spinning, and the resulting structure has directional order, with the fiber diameter gradually decreasing from upstream to downstream, thus forming a pore size gradient and achieving hierarchical particle interception across multiple scales. This rational design simultaneously suppresses surface clogging and reduces flow resistance, resolving the longstanding trade-off between efficiency and permeability. Consequently, this aerogel achieves an ultra-high filtration efficiency of 99.96%, a low pressure drop of 156 Pa, and a high dust-holding capacity of 101 g m⁻². The material also exhibits outstanding mechanical toughness (80% compressive strain elasticity and 25.75% tensile fracture strain) and thermal stability up to 1000 °C. Moreover, it maintains over 99.95% filtration efficiency at high temperatures and can be fully regenerated through 800 °C heat treatment. This work establishes a structure-based design paradigm for high-temperature filtration media and provides a scalable pathway for next-generation industrial flue gas purification. Full article

Hourly concentrations of PM_2.5-bound elements were continuously monitored in Windsor, Canada, from April 2021 to April 2023. Health risk assessment methods of the USEPA were utilized to quantify lifetime cumulative cancer risks (CRs) using six PM_2.5-bound elements, and chronic non-cancer hazard quotients (HQs) using 11 elements, for each season, each source factor, and each hour of day. The two-year average PM_2.5 mass concentration was 9.2 μg/m³, slightly exceeding Ontario’s Ambient Air Quality Criteria of 8.8 μg/m³. A discernible diurnal concentration pattern was noted for most elements, peaking during morning rush hours and tapering during the daytime, largely attributed to local human activities and changes in atmospheric mixing heights. Despite this, both the total lifetime cumulative CR (4.1 × 10⁻⁵) and non-cancer total HQ (0.82) from exposure to ambient elements remained below the corresponding USEPA-acceptable levels. The seasonal variation in CRs and HQs was minimal. However, the diurnal variation was strong, with higher risks during morning rush hours (6:00–8:00) when traffic volume peaks, and lower risks during the daytime (12:00–20:00) when atmospheric mixing height is enhanced. Metal processing emerged as the most significant contributor to the total CR (52%) and HQ (60%), followed by coal/heavy oil burning (19% and 16%, respectively), and vehicular exhaust (19% and 12%, respectively). The remaining two source factors accounted for 10% of CR and 12% of HQ. Cd (62%) was the largest contributor to CRs, followed by Cr(VI) (25%), Co (6%), As (5%), Ni (2%), and Pb (<0.1%). Similarly, Cd dominated HQs (73%), followed by Mn (11%), Ni (6.3%), with the remaining eight elements collectively contributing 9.7%. Although levels of CRs and HQs are low, efforts to mitigate ambient Cd emissions from metal processing sources will help reduce exposure and protect the environment and human health, given Cd is the primary contributor to the total CR and HQ during the study period. Full article

This study investigates the reutilization of polylactic acid (PLA) waste generated by 3D printing through its transformation into electrospun membranes with tunable morphological, surface, thermal, and filtration properties. Polymer solutions containing 5–10 wt % recycled PLA were prepared in a dichloromethane/dimethylformamide system and characterized in terms of viscosity and electrical conductivity. Increasing PLA concentration raised solution viscosity (41.87–339.83 mPa·s) and reduced conductivity (7.63–1.63 µS·cm⁻¹), promoting the formation of bead-free fibers with larger diameters (0.221–1.213 µm) and enhanced hydrophobicity (contact angles 112.34–124.38°). FTIR confirmed preservation of the polymer chemical structure after recycling and electrospinning, while DSC revealed reduced crystallinity in the fibrous membranes. Exploratory correlation analysis indicated consistent associations between solution properties, fiber morphology, and wettability. Increasing the number of electrospun layers (1–3) generated denser networks with reduced pore size and improved particle retention. Filtration tests conducted under controlled airflow conditions (85 L min⁻¹, 1 cm s⁻¹ frontal velocity, 50 cm² effective area) showed removal efficiencies above 90% for PM2.5 and PM5, while PM1 capture improved with increasing membrane thickness. Quality factor analysis highlighted the trade-off between filtration efficiency and pressure drop, identifying intermediate multilayer configurations as providing a favorable balance. These findings demonstrate that electrospinning offers an effective strategy for converting recycled PLA into structurally tunable membranes with adjustable filtration performance, supporting sustainable valorization of additive manufacturing waste. Full article

This study investigates the vertical variation and temporal characteristics and indicates the sources of black carbon (BC) and brown carbon (BrC) within particulate matter fraction PM₁ during light (November–December 2024) and heavy (January–February 2025) haze episodes in Bangkok, Thailand, a topic where data are still limited data regarding Southeast Asian megacities. Continuous measurements were conducted at 30 and 110 m above ground level, together with particle size distribution measurement, micrometeorological observations, and backward air mass trajectory analysis. During the haze periods, the highest particle number concentrations occurred in the 0.3–0.4 µm size range, indicating dominant contributions from combustion-related emissions and secondary aerosol formation. Mean PM₁ mass concentrations during the heavy haze episodes were more than 2.5 times higher than those during light haze. BC concentrations increased substantially during heavy haze, while the BC fraction of PM₁ remained relatively constant (~10%). In contrast, the BrC fraction reached nearly 20%, reflecting an increasing influence of biomass burning emissions associated with regional transport. Combined analyses of BC/BrC relationships, wind-direction dependence, and air mass trajectories demonstrate mixed contributions from local fossil fuel combustion and long-range transport of biomass burning aerosols during severe haze events. Full article