Search Results (489)

Platinum group elements (PGEs), especially platinum (Pt), palladium (Pd), and rhodium (Rh), are analyzed as emerging airborne contaminants in urban environments. This study aimed to monitor the spatial and temporal distribution of PGEs in urban air and to evaluate their potential as indicators of traffic-related emissions. The paper presents a five-year monitoring of Pt, Pd, and Rh mass concentrations in airborne particulate matter collected from three urban locations (North, Center, and South) with different traffic loads in Zagreb, Croatia. Weekly samples were digested in acid under high temperature and high pressure, and analyzed using inductively coupled plasma mass spectrometry (ICP-MS). At the monitoring location South, mass concentrations of all PGEs were generally 20–40% higher than at other locations, consistent with its higher traffic density. The PGEs showed seasonal variability, with 40–60% higher mass concentrations in winter and autumn than in spring and summer. The spatial and temporal distribution of PGE mass concentrations across urban locations demonstrates their potential as indicators of traffic-related activity. Palladium mass concentrations were consistently the highest, as a result of its increased use in modern catalytic converters. These findings underscore the relevance of long-term PGE monitoring for understanding urban atmospheric pollution dynamics within changing environmental conditions. Full article

Nanoparticles (interchangeably called ultrafine particles) constitute one of the growing risks encountered in everyday life. Both short- and long-term exposure to them, as well as to particulate matter in general, may pose serious health risks. In this study, we focus on monitoring of particle concentration in urban air for 200 days, with special attention to nanoparticles. The overall data coverage exceeded 80%, reaching over 97% in three selected months. Measurements were carried out at 25.5 m height in southern Warsaw, in close vicinity to residential blocks with apartments also at the same level. Data were collected from January to first half of August 2025 using a Grimm MINI-WRAS portable wide-range aerosol spectrometer and a thermo-hygro-barometer. Over the 8-month period, significant variations between months and days in both nanoparticle and all particulate matter concentrations were observed. Winter months were almost four times more polluted with particles (both nanoparticles and those above 100 nm) than spring and summer periods. Although nanoparticle concentration in colder months was higher, the percentage of nanoparticles was lower. An important aspect of these investigations was comparing the obtained results with publicly available air pollution data from urban air quality monitoring stations, which represent ground-level measurements. At rooftop altitude, PM_2.5/PM₁₀ ratios were significantly higher than those measured at ground level. Full article

The reliability of adhesive bonding to CAD/CAM resin composites is influenced not only by material composition and surface treatment but also by the testing methodology used to assess bond strength. However, the impact of different shear bond strength (SBS) test configurations remains insufficiently clarified. This study evaluated the influence of different surface pretreatment protocols and SBS test methods on the bonding performance of a self-adhesive resin cement to two CAD/CAM materials: a conventional particulate-filled composite (Cerasmart 270) and an experimental short glass fiber-reinforced composite (SFRC CAD). Specimens (14 × 12 × 3 mm; n = 80 per material) were ground with 320-grit silicon carbide paper and divided according to surface pretreatment: airborne-particle abrasion (APA) or APA followed by hydrofluoric acid application for 60 s (APA + HF). Each group was further subdivided based on the SBS test method using either resin cement cylinders fabricated with a custom transparent mold (diameter: 3.6 mm; height: 3 mm) or metallic cylinders cemented to the treated surface. Half of the specimens were tested after 48 h of water storage, while the remainder underwent hydrothermal aging by boiling in water for 16 h prior to testing. Material type, SBS test method, surface pretreatment, and aging significantly affected bond strength (p < 0.05). The metallic cylinder method produced higher SBS values than the transparent mold technique, particularly for SFRC CAD. APA + HF tended to reduce SBS in Cerasmart 270, particularly after aging, whereas SFRC CAD showed comparable or higher bond strength values with APA alone. Aging decreased SBS in most groups. Overall, bond strength was influenced by both material type and test methodology. Within the limitations of this study, airborne-particle abrasion alone may be sufficient for SFRC CAD materials, while additional HF treatment may not provide further benefit. These findings highlight the importance of considering both material characteristics and test configuration when interpreting laboratory bond strength data. Full article

Municipal solid waste (MSW) landfills are seldom regarded as potential sources of airborne mineral fibres, notwithstanding the possible presence of legacy asbestos-containing materials within mixed waste streams. Prolonged exposure to asbestos fibres is well established as causally associated with severe adverse health outcomes, prompting stringent regulatory measures across the European Union, most recently reinforced by Directive (EU) 2023/2668 amending Directive 2009/148/EC on the protection of workers from the risks related to asbestos exposure. This study presents systematic annual monitoring of airborne mineral fibres (MinFib), including asbestos fibres (AsbFib), conducted between 2019 and 2025 at an MSW landfill in the Czech Republic. Personal air sampling targeted heavy equipment operators as the most exposed occupational group and was conducted in accordance with established occupational hygiene principles. Fibre identification and quantification were carried out using Scanning Electron Microscopy coupled with Energy-Dispersive X-ray analysis (SEM/EDX) according to accredited laboratory internal standard operating procedures (SOPs). Across all monitoring campaigns, asbestos fibre concentrations remained below the analytical detection limits, including during handling of asbestos-containing materials. However, the analytical sensitivity appears to be within the range relevant to the current EU occupational exposure limit (0.01 fibres/cm³), potentially limiting the ability to identify very low-level exposures. These findings indicate that occupational exposure under routine operational conditions was below analytical detection limits, suggesting a low exposure potential. However, non-detectable results should be interpreted as method-limited rather than as indicating that exposure did not occur. Continued monitoring using more sensitive analytical approaches is therefore warranted. Full article

Airborne particulate matter (PM) poses a major health risk, yet species selection for vertical greening systems (VGS) is poorly quantified. We evaluated PM retention by seven commercially available shade-tolerant species grown in a modular living wall system (LWS) on a north-facing façade at Sapienza University of Rome. After 3 months of in situ exposure, leaves were analyzed via SEM (1000×), collecting 210 images, 30 per species. An automated FIJI/ImageJ pipeline segmented particles, computed equivalent circular diameters, and classified them into (PM < 0.5, PM [0.5, 1), PM [1, 2.5), PM [2.5, 10), and PM ≥ 10 µm). Across species, ultrafine and fine fractions dominated deposits, with the <0.5 µm class typically comprising 60–70% of counts. Vinca minor cv. albomarginata exhibited the highest densities in ultrafine and fine classes, closely followed by Fatsia japonica; Hedera helix captured more coarse particles (2.5–10 µm and >10 µm). Heuchera sanguinea consistently displayed the lowest densities across all size classes. Performance patterns aligned with leaf surface traits: wax-coated, moderately rough or gently structured cuticles favored adhesion, whereas highly irregular microrelief did not consistently enhance retention. Methodological considerations include thresholding sensitivity, use of equivalent circular diameter for irregular particles, and an upper area filter that may undercount large aggregates. The findings identify Vinca minor cv. albomarginata and Fatsia japonica as priority species for PM mitigation in shaded VGS, with Hedera helix complementing coarse PM capture. The results provide trait-based, design-oriented guidance for living wall species selection in Mediterranean urban and indoor contexts. Full article

Particulate matter (PM) is a complex mixture of airborne solid particles and liquid droplets originating from various environmental sources, and it has been implicated in the initiation, development, and progression of pulmonary inflammation and respiratory diseases. However, the underlying associated molecular mechanisms remain unclear. Adenophora divaricate Franch. & Sav. (AD) is a medicinal herb classified within the Campanulaceae family and genus Adenophora, with a broad geographic distribution across East Asia, including Korea, Asia, and Russia. In this study, we investigated the mechanisms underlying the effects of AD on PM-induced lung inflammation in both PM-stimulated RAW264.7 cells and PM-exposed mice. Considering that the reactive oxygen species (ROS)-mediated thioredoxin-interacting protein (TXNIP) and NOD-like receptor pyrin domain containing (NLRP3) inflammasome pathway plays a role in PM-induced inflammatory responses, we focused on determining whether AD exerts its anti-inflammatory effects through modulation of this signaling pathway. The anti-inflammatory properties of the methanolic extract of AD were evaluated using PM-stimulated RAW264.7 cells and PM-exposed mice. PM was administered intranasally to mice for 7 days, whereas AD or dexamethasone was orally administered for the same duration. AD treatment significantly attenuated pulmonary inflammation, as evidenced by reduced inflammatory cell counts and decreased cytokine levels in bronchoalveolar lavage fluid. In addition, AD decreased oxidative stress marker (ROS and thiobarbituric acid reactive substances) while increasing glutathione content, leading to suppression of TXNIP/NLRP3 inflammasome expression. Histopathological analysis revealed a marked alleviation of inflammatory responses in lung tissue, characterized by diminished inflammatory cell infiltration and reduced alveolar wall thickening. Collectively, these findings suggest ROS-mediated TXNIP serves as a key regulatory factor, and AD may serve as a potential therapeutic agent for pulmonary inflammation. Full article

Military confined spaces face poor ventilation and severe airborne hazards (toxic gases/particulates), while conventional air purification systems with separate filtration–adsorption units are bulky and hard to miniaturize. Activated carbon fiber paper (ACFP) is a promising integrated filtration–adsorption material, but existing studies lack systematic comparisons of different ACF precursors and rational balancing of adsorption, filtration, and mechanical properties. Herein, ACFPs were fabricated via wet papermaking technology, using two ACFs (rayon-based, RACF, and phenolic-based, PACF) as the adsorptive component, glass wool as a filtration enhancer, and dual-melting-point polyethylene terephthalate (PET) fibers as a mechanical reinforcer. Dynamic adsorption was evaluated via DMMP (a Sarin simulant). Results showed that PACF had a micropore ratio twice that of RACF. Under the optimal formulation (20% glass wool, 30% PET, and 50% ACF), both types of ACFP showed FE_0.3 μm ≥ 90%. PACFP outperformed RACFP in comprehensive performance, showing higher adsorption capacity, tensile strength, and filtration quality factor. Both ACFPs exhibited superior bed utilization efficiency (RACFP: 91.3%; PACFP: 86.0%) to granular activated carbon (AC: 82.7%), confirming better dynamic adsorption kinetics. This work provides a rational optimization strategy for ACFPs, offering a lightweight, integrated material for air purification in military confined spaces. Full article

Airborne microbial contamination in dairy cattle housing is strongly influenced by housing conditions and management practices. This study evaluated the influence of environmental and housing parameters on total bacterial, coliform, and mold levels across four dairy farms. Microclimatic variables, including temperature, relative humidity, wind speed, bedding moisture, air volume per cow, particulate matter (PM₁, PM_2.5, PM₁₀), and total volatile organic compounds (TVOCs), were measured. Comparative analyses showed that air volume per cow and bedding moisture were consistently associated with variability in total microbial and mold counts, while particulate matter and wind speed were linked to differences in airborne coliforms. Generalized linear mixed models indicated that most environmental variables did not have statistically significant effects, with the exception of farm type for coliforms and temperature for molds. The predominance of non-significant environmental effects, together with more consistent differences observed between farms, suggests that variability in airborne microbial levels is more strongly associated with farm-specific management and housing characteristics than with individual environmental parameters. Overall, the findings highlight the combined influence of housing design, management practices, and environmental conditions, emphasizing the importance of optimized ventilation and bedding management to improve air quality in dairy cattle housing. Full article

We evaluated the indoor environmental quality of the administrative office at University Medical Center Ho Chi Minh City branch 2 and implemented a multi-stage engineering control strategy to optimize occupational health conditions. A cross-sectional assessment monitored important air quality parameters, including carbon dioxide (CO₂), fine particulate matter (PM2.5 and PM10), humidity, and illumination. Following baseline measurements, an integrated system was deployed to address pollutant mass balance, consisting of High-Efficiency Particulate Air (HEPA) filtration units for mechanical particle scrubbing, ceiling-mounted axial fans to induce forced convection, and ultraviolet-C germicidal lamps for photochemical disinfection. Post-intervention results demonstrated significant gains in system removal efficiency. CO₂ concentrations decreased by over 60% due to enhanced volumetric air exchange, while PM2.5 levels decreased by more than 40% through interception and diffusion mechanisms within the HEPA media. Furthermore, UVC irradiation achieved a 90% reduction in viable airborne microbial colonies. The results of this study show that low-cost, scalable environmental engineering controls and fluid dynamic optimizations effectively mitigate indoor air pollution and enhance workplace stability in healthcare administrative settings. Full article

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

Phosphate mining companies in Morocco pose many environmental and occupational safety risks, especially through the release of airborne particulates, gas pollutants, and heavy metals. While there is increased implementation of monitoring systems within industrial mining contexts, current methodologies are still predominantly founded on rule-based systems or classical statistics that presume linearity in relationships between an arbitrary set of environmental parameters and the likelihood of an incident. Conversely, mining operations are characterized by intricately dynamic nonlinear combinations of numerous environmental and operational variables. As a result, a potential research opportunity exists for the application of sophisticated machine learning techniques that provide the ability to detect various levels of operational risk within phosphate mining scenarios. This study has three objectives. First, to examine the mining environmental and operational data from the phosphate mining sites to determine the mining operational conditions that present the highest risk. Second, to create a machine learning classification model which utilizes a Feedforward Neural Network (FNN) to identify operational states that are prone to incidents based on multivariate sensor data. Third, to assess the validity and reliability of the model using machine learning validity and reliability evaluation techniques along with statistical validation methods. In this study, an artificial intelligence-based approach for AI-based safety monitoring was proposed by using a Feedforward Neural Network (FNN) on a detailed data set of 1536 hourly measurements, directly recorded onsite at OCP plants in Benguerir and Khouribga. Environmental and industrial parameters (dust concentration, gas emissions, temperature, and toxic metal content) were measured using industrial-grade sensors certified for such a type of application. By means of training the proposed FNN model with adaptive gradient descent and dropout regularization with early stopping, a test mean squared error of 0.057 and over 85% accuracy on incident detection were obtained. Gradient tracking and m-adaptive validation proved the stability and convergence of the model. Emissions and dust were identified as the main risk classifiers in a variable importance analysis. The findings demonstrate that the mining sector may move from reactive to proactive safety management and validate the incorporation of AI into a real-time monitoring infrastructure inside the OCP ecosystem. Practical concerns of industrial data gathering, model interpretability, and the moral application of AI in high-risk settings are also addressed by the study. Full article

Urban air quality is influenced by the removal of particulate matter through dry deposition, yet this process is often simplified in models, potentially underestimating the role of vertical building surfaces. This study investigates the impact of aerosol deposition on building walls on PM_2.5 concentrations and the deposition budget within the urban canopy. We utilized a Large Eddy Simulation model coupled with a Lagrangian Particle Transport module to simulate aerosol dispersion in randomized urban configurations corresponding to Local Climate Zones (LCZs) 4, 5, and 6. The results indicate that under the considered conditions, vertical walls can act as a primary sink for PM_2.5, capturing over 70% of deposited particles downwind from sources in high-rise environments. We observed a non-linear sensitivity of airborne concentrations to wall deposition efficiency; a relatively low capture probability (10%) reduced near-surface concentrations by 25–30%. Furthermore, for fine and coarse particles (up to ~20 µm), the uncertainty in wall deposition parameterization appeared to outweigh the influence of particle physical properties on dispersion patterns. These findings suggest that neglecting wall deposition may lead to overestimation of urban pollution levels, highlighting the importance of refining particle–wall interaction parameterizations in air quality models. Full article

The impending Euro 7 regulation will impose strict limits on brake particulate matter (PM) emissions from new light-duty vehicles, driving manufacturers to explore alternative rotor materials and/or surface treatments. This paper evaluates the friction and wear emission performance of both a laser-clad grey cast iron (GCI) rotor surface and a plasma electrolytic oxidation (PEO) treated aluminium surface compared to that of an uncoated GCI. Tests were conducted on a small-scale tribometer rig, which was specially adapted to measure airborne emissions while emulating the standard Worldwide harmonised Light vehicle Test Procedure (WLTP). The laser-clad coating was applied via extreme high-speed laser cladding to form an initial 430 L stainless steel layer, followed by a topcoat of 80/20 vol% 430L steel/TiC, both layers being c.100 micron thick. The PEO treatment applies a c.50 micron alumina coating to both a wrought and cast alloy, the latter being more suitable for the manufacture of full-size vented brake rotors. Results show that all rotor materials achieved a satisfactory coefficient of friction (CoF) against suitable low-metallic pad material, although the CoF for the wrought PEO-Al alloy was significantly higher at c.0.65 compared with c.0.50 for the other materials. The gravimetric wear of all the coated rotor surfaces after 8 WLTP cycles was almost undetectable, and pad wear was also significantly reduced. This improved wear resistance led to significant reductions in PM emissions, with the PM10 levels of the uncoated GCI reduced by around 75% for the laser-clad GCI and PEO wrought Al alloy, and by about 60% for the PEO cast Al alloy. When extrapolated to a full-sized passenger vehicle, the results indicated that both the laser-clad GCI and PEO-treated surfaces have the potential to meet the current Euro 7 emissions targets. Full article

Metal additive manufacturing relies on fine powders whose properties influence flow, spreading, and airborne release during processing, yet published data on powder characteristics, reuse effects, and emissions remain fragmented and difficult to compare. This study reviews quantitative measurements reported for metallic feedstocks used in laser powder bed fusion and directed energy deposition. A numerical evaluation model is developed to connect powder properties, process conditions, dispersion tendency, and material recovery. Particle size distribution values, density metrics, flow test results, reuse-related oxidation, and nanoparticle counts were compiled from the literature and normalized on a 0–1 scale. Four independent indices were defined: Material Fingerprint, process–powder interaction, airborne dispersion potential, and recovery. Adaptiveness refers to index sensitivity to changes in powder, reuse, and process conditions. The results indicate stable spreading for gas-atomized feedstocks, while wider particle size distributions and rougher surfaces increase cohesion and agglomeration, particularly under humid conditions and during reuse. Emission data indicate nanoparticle formation during processing, with recovery efficiency dependent on cyclone or high-efficiency particulate air filtration selection. The proposed model offers a screening approach for comparing powders and planning recovery strategies using data already available in the literature. Full article