Search Results (806)

Chronic obstructive pulmonary disease (COPD) is strongly associated with the inhalation of harmful particulate matter in ambient air. This study examined 786,290 COPD-related hospital admissions among patients aged 45–64 in Istanbul from 2013 to 2015, using a Generalized Linear Model (GLM) with meteorological variables included as covariates and air pollutant effects evaluated across lag days 0–9. Daily mean concentrations of PM₁₀, PM_2.5, and NO₂ were used as air pollution indicators, while average temperature and relative humidity were considered as meteorological variables. Relative risk (RR) and excess relative risk (ERR) estimates were calculated for a 10 μg/m³ increase in pollutant concentrations across the lag period. Significant associations were found between air pollution and COPD-related hospital admissions in overall analyses as well as seasonal assessments, especially for temperature-related effects. A 10 μg/m³ increase in PM_2.5 was associated with an ERR of 1.26% in females and 1.07% in males at lag 1, while NO₂ exposure showed ERRs of 1.31% in males and 1.30% in females. The effects of PM₁₀ were comparatively smaller, peaking at about 1.13% ERR at lag 5. Stronger associations were observed in both summer and winter seasons. PM_2.5 demonstrated the highest overall impact, particularly among females, with an excess risk of 1.7%. Pollutant effects were more pronounced at ambient temperatures around 0 °C and 25 °C. Full article

The Phoenix Metropolitan Area (PMA) is situated in the Sonoran Desert of Central Arizona, USA. The PMA is a focus of ongoing climate change and urban heat island research. This paper addresses differences in the receipt of shortwave irradiance (global radiation) between the city and its surroundings. Several weather networks (e.g., AZ Met, an Arizona agricultural network) and air quality monitoring sites allow for the determination of shortwave irradiance between urban and rural locales, as well as a preliminary relation to seasonal patterns of suspended particulates. Particulate matter 10 μm and smaller (PM10) ranges from ca. 10 µg/m³ to 30 µg/m³ from winter to summer in rural areas, whereas in the metropolitan area, PM10 often exceeds 40 µg/m³ year-round. On average, urban transmissivity (T) of shortwave irradiance is lower than rural values by 1% in summer to over 5% in winter, like other urban studies evaluating effects on irradiance. Percentage differences between a site on a local mountain and the valley floor (about 400 m difference) range from 1% in summer to 5% in winter, in sync with seasonal mixing height changes and vertical mixing of particulates. Full article

Blast furnace tuyeres are the primary dust emission source in ironmaking facilities (accounting for over 30% of total pollutants). High-temperature dust plumes with intense thermal energy are prone to dispersion, while China’s steel industry ultra-low emission standards (particulate matter ≤ 10 mg/m³) impose strict requirements on capture efficiency. Existing technologies often neglect crosswind interference and lack coordinated design between air volume regulation and hood structure, leading to excessive fugitive emissions and non-compliance. This study established a localized numerical model for high-temperature dust capture at blast furnace tuyeres, investigating air volume’s impact on velocity fields and capture efficiency, revealing crosswind interference mechanisms, and proposing optimization strategies (adding hood baffles, adjusting dimensions, installing ejector fans). Results show crosswind significantly reduces efficiency—only 78% at 1.5 m/s crosswind and 400,000 m³/h flow rate. The optimal configuration (2.5 m side flaps plus1.4 m baffles) achieves 99% efficiency, maintaining high performance at lower flow rates: 350,000 m³/h (1.5 m/s crosswind) and 250,000 m³/h (0.9 m/s crosswind). This study provides technical support for blast furnace tuyere dust control and facilitates ultra-low emission compliance in the steel industry. This study supports blast furnace tuyere dust control and aids the steel industry in meeting ultra-low emission standards. Notably, the proposed optimization scheme boasts simple structural adjustments, low retrofitting costs, and good compatibility with existing production lines, enabling direct industrial promotion and notable environmental and economic gains. Full article

Brake wear particles (BWPs) represent a major source of non-exhaust particulate matter from road traffic, contributing substantially to human exposure, particularly in urban environments. While traditionally associated with coarse and fine fractions, mounting evidence shows that brake systems emit large quantities of ultrafine particles (UFPs; <100 nm), which dominate number concentrations despite contributing little to mass. This paper synthesizes current knowledge on BWP formation mechanisms, physicochemical characteristics, environmental behavior, and toxicological effects, with a specific emphasis on UFPs. Mechanical friction and high-temperature degradation of pad and disc materials generate nanoscale primary particles that rapidly agglomerate yet retain ultrafine structural features. Reported real-world and laboratory number concentrations commonly range from 10³ to over 10⁶ particles/cm³, with diameters between 10 and 100 nm, rising sharply during intensive braking. Toxicological studies consistently demonstrate that UFP-rich and metal-laden BWPs, particularly those containing Fe, Cu, Mn, Cd, and Sb compounds, induce oxidative stress, inflammation, mitochondrial dysfunction, genotoxicity, and epithelial barrier disruption in human lung and immune cells. Ecotoxicological studies further reveal adverse impacts across aquatic organisms, plants, soil invertebrates, and mammals, with evidence of environmental persistence and food-chain transfer. Despite these findings, current regulatory frameworks address only the mass of particulate matter from brakes and omit UFP number-based limits, leaving a major gap in emission control. Full article

This study assessed the spatial distribution and composition of airborne particulate matter within a 10 km long urban green corridor in Zacatecas, Mexico, using magnetic biomonitoring with Tillandsia recurvata and SEM-EDS particle characterization. A total of 44 samples were collected from distinct urban park contexts (e.g., commercial zones, malls, bus stops), revealing mass-specific magnetic susceptibility χ values ranging from −6.71 to 61.1 × 10⁻⁸ m³ kg⁻¹. Three compositional groups were identified based on a PCA performed using elemental concentrations from SEM-EDS and magnetic data, which are associated with traffic emissions and industrial inputs. SEM-EDS images confirmed abundant magnetite-like particles (1–8 μm) with hazardous metals including Pb (up to 5.6 wt.%), Ba (up to 67.6 wt.%), and Cr (up to 31.5 wt.%). Wind direction data indicated predominant SSW–NNE transport, correlating with hotspots in central and northeastern park areas. Overall, vegetated zones exhibited markedly lower magnetic loads (mean χ = 8.84 × 10⁻⁸ m³ kg⁻¹) than traffic-exposed sites (mean χ = 17.27 × 10⁻⁸ m³ kg⁻¹), representing an approximate 50% reduction in magnetic particle accumulation, which highlights the effective role of continuous vegetation cover as a functional green barrier that attenuates the lateral transport and deposition of airborne particulate matter within the park. This research highlights the applicability of combined magnetic and microscopic techniques for evaluating the dynamics of airborne pollution in urban parks and supports their use for identifying both pollution hotspots and mitigation zones, reinforcing the role of urban green spaces as biofunctional filters in cities facing vehicular air pollution. Full article

Background: Fine particulate matter (PM_2.5) is an established systemic toxicant, yet its association with clinical skin aging remains incompletely characterized. Although pigmentary changes and wrinkles are commonly attributed to ultraviolet exposure, experimental and epidemiologic evidence suggests that long-term PM_2.5 exposure may contribute to extrinsic skin aging through oxidative, inflammatory, and aryl hydrocarbon receptor-mediated pathways. However, human studies specifically quantifying PM_2.5 exposure in relation to validated skin aging outcomes are sparse, and no prior meta-analysis has systematically synthesized this evidence. Objective: To conduct a systematic review and meta-analysis of epidemiologic studies reporting measured or modeled long-term PM_2.5 exposure and extractable quantitative associations with clinical skin aging outcomes. Methods: We performed a comprehensive PRISMA 2020-guided search of PubMed, Embase, Web of Science, and Scopus (inception to 18 November 2025). Eligible studies included human participants, quantified long-term PM_2.5 exposure, validated clinical or imaging-based skin aging outcomes, and extractable effect estimates. Ratio-type effect measures (arithmetic mean ratios, geometric mean ratios, and odds ratios) were transformed to the natural-log scale, standardized to a common exposure contrast of per 10 µg/m³ PM_2.5, and synthesized as generic relative association metrics. Random-effects models with DerSimonian–Laird estimation and Hartung–Knapp adjustment were applied for pigmentary outcomes. VISIA imaging β-coefficients were synthesized narratively. Results: Four epidemiologic cohorts met predefined eligibility criteria. From these, we extracted seven PM_2.5-specific pigmentary effect estimates, one clinically assessed wrinkle estimate, and two VISIA imaging outcomes. The pooled relative association for pigmentary aging corresponded to a ratio of 1.11 per 10 µg/m³ PM_2.5 (95% CI, 0.82–1.50), indicating a directionally positive but statistically imprecise association compatible with both increased and unchanged pigmentary aging. All individual pigmentary estimates were directionally positive. A single cohort reported a 3.2% increase in wrinkle severity per 10 µg/m³ PM_2.5 (ratio 1.032). VISIA imaging showed significant worsening of brown spot severity (+9.5 percentile per 10 µg/m³), while wrinkle percentiles showed a non-significant change. Conclusions: Based on a comprehensive PRISMA-guided search, the available epidemiologic evidence suggests a consistent directionally positive association between long-term PM_2.5 exposure and pigmentary skin aging outcomes, with limited and uncertain evidence for wrinkle-related phenotypes. The current evidence base remains small, heterogeneous, and of low certainty. Accordingly, these findings should be interpreted as hypothesis-generating and underscore the need for larger, longitudinal, and methodologically harmonized studies. (Registration: PROSPERO CRD420251231462) Full article

Nanoemulsions (NEs) offer a promising strategy for delivering lipophilic cannabidiol (CBD) to protect skin from particulate matter (PM)-induced damage. In this study, CBD-loaded oil-in-water NEs based on Brij^® O10 (polyoxyethylene (10) oleyl ether) and olive oil were prepared by the phase inversion temperature (PIT) method and characterized. A 20% w/w Brij^® O10 formulation (B20) remained clear and stable for 30 days. CBD solubility was markedly enhanced in Brij^® O10 micelles and further increased in NEs, exceeding theoretical predictions and indicating synergistic solubilization in the oil–surfactant system. CBD incorporation lowered the PIT and induced nonlinear changes in droplet size with oil content. All formulations exhibited nanoscale droplets by dynamic light scattering and transmission electron microscopy, moderately low zeta potentials consistent with nonionic steric stabilization, and maintained physical stability despite increased turbidity at higher oil levels. In a full-thickness human ex vivo skin model exposed to PM, both blank and CBD-loaded NEs reduced interleukin-6 (IL-6) and matrix metalloproteinase-1 (MMP-1) in PM-exposed skin, with CBD-loaded NEs providing additional reductions and uniquely restoring procollagen type I C-peptide (PIP) relative to their blanks. Overall, PIT-based CBD NEs enhance CBD solubilization and protect human ex vivo skin from PM-induced inflammation and extracellular matrix degradation. Full article

On-road vehicles are a primary source of urban air pollution. It is known that high-emitting vehicles represent a fraction of the fleet but contribute significantly to the total emissions. Usually, road transportation emission inventories do not capture the impact of these types of vehicles, underestimating emissions. This study introduces a simple method to refine vehicle emission inventories by incorporating data from Ecuador’s Inspection and Maintenance (I/M) program. We analyzed I/M data from Quito to develop a correction factor for the Vehicular Emissions INventory (VEIN) model, accounting for the higher emissions from vehicles that fail inspection. Our analysis shows that while less than 10% of gasoline and 20% of diesel vehicles failed inspection, their emissions were substantially higher; for instance, accounting for reproved vehicles produced 60% more Carbon Monoxide (CO), 18% more Non-Methanic Volatile Organic Compounds (NMVOC), 40% more Particulate Matter with aerodynamical diameter of 2.5 µm or less (PM_2.5), and 34% more or lower than 10 µm (PM₁₀). These findings demonstrate that incorporating I/M data is crucial for accurately quantifying vehicular pollution. The proposed methodology offers a way to create more accurate emission estimates, providing a tool for policymakers to manage air quality. Full article

Air pollution is an important environmental issue that affects social development and human life. Atmospheric fine particulate matter (PM_2.5) is the primary pollutant affecting the air quality of most cities in the authors’ country. It can cause severe haze, reduce air visibility and cleanliness, and affect people’s daily lives and health. Therefore, it has become a primary research object. Ground monitoring and satellite remote sensing are currently the main ways to obtain PM_2.5 data. Satellite remote sensing technology has the advantages of macro-scale, dynamic, and real-time functioning, which can make up for the limitations of the uneven distribution and high cost of ground monitoring stations. Therefore, it provides an effective means to establish a mathematical model—based on atmospheric aerosol optical thickness data obtained through satellite remote sensing and PM_2.5 concentration data measured by ground monitoring stations—in order to estimate the PM_2.5 concentration and temporal and spatial distribution. This study takes the Yangtze River Delta region as the research area. Based on the measured PM_2.5 concentration data obtained from 184 ground monitoring stations in 2023, the newly released sixth version of the MODIS aerosol optical depth product obtained via the US Terra and Aqua satellites is used as the main prediction factor. Dark-pixel AOD data with a 3 km resolution and dark-blue AOD data with a 10 km resolution are combined with the European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis meteorological, land use, road network, and population density data and other auxiliary prediction factors, and XGBoost and LSTM models are used to achieve high-precision estimation of the spatiotemporal changes in PM_2.5 concentration in the Yangtze River Delta region. Full article

Microscopic Particulate Matter (PM) below 10 µm can enter the respiratory system and affect human health in the short and long term. Railway enclosures are sites with high concentrations of fine PM and technical solutions like mechanical filtration exist to increase the air quality. However, several crucial factors must be evaluated and optimized like energy consumption, maintenance cost/interval, design and control. A fast and adaptable evaluation of decontamination solutions is required to find the optimal solution. To answer this, a 1D multizone model based on station discretization aligned with the track direction is proposed to precisely place decontamination systems along the station. In each zone, a set of ordinary differential equations is used to forecast the daily progression of PM concentrations, based on physical parameters (air and train velocities, and train traffic) used to describe the different physical phenomena (resuspension, deposition, ventilation and generation). Three-dimensional CFD (Computational Fluid Dynamics) simulations are used to characterize the efficiency and range of decontamination products and reproduce their effect in the 1D model. This approach allows for flexible optimization of local and global decontamination efficiencies with multiple parameter changes. PM₁₀ and PM_2.5 (below 10 and 2.5 µm) are studied here as they are often monitored. Full article

Fine particulate matter (PM_2.5) poses substantial urban health risks that vary across space, time, and population vulnerability. We integrate a spatio-temporal INLA–SPDE PM_2.5 field with an agent-based model (ABM) of 10,000 daily home–work commuters in Indianapolis’s Pleasant Run airshed (50 weeks; 250 m grid). The PM_2.5 surface fuses 23 corrected PurpleAir PA-II-SD sensors with meteorology, land use, road proximity, and MODIS AOD. Validation indicated strong agreement (leave-one-out R² = 0.79, RMSE = 3.5 μg/m³; EPA monitor comparison R² = 0.81, RMSE = 3.1 μg/m³). We model a spatial-equity counterfactual by assigning susceptibility independently of residence and workplace, isolating vulnerability from residential segregation. Under this design, annual PM_2.5 exposure was statistically indistinguishable across groups (16.22–16.29 μg/m³; max difference 0.07 μg/m³, <0.5%), yet VWDI differed by ~10× (High vs. Very Low). Route-level maps reveal recurrent micro-corridors (>20 μg/m³) near industrial zones and arterials that increase within-group variability without creating between-group exposure gaps. These findings quantify a policy-relevant “floor effect” in environmental justice: even with perfect spatial equity, substantial health disparities remain driven by susceptibility. Effective mitigation, therefore, requires dual strategies—place-based emissions and mobility interventions to reduce exposure for all, paired with vulnerability-targeted health supports (screening, access to care, indoor air quality) to address irreducible risk. The data and code framework provides a reproducible baseline against which real-world segregation and mobility constraints can be assessed in future, stratified scenarios. Full article

Particulate matter (PM) pollution is high in most Bulgarian regions, especially large urban areas. In a previous study covering one year of data collection and analysis by source apportionment techniques such as positive matrix factorization we show that the main source of high PM₁₀ (PM with a diameter of 10 μm or less) concentration in the city of Sofia is soil and road dust resuspension into the surface layer of the air. Resuspension has seasonal variations, with a relatively large impact (25%) associated with drying periods. In the present paper we combine classical indices (NDVI, BSI, NDMI) derived from Sentinel-2 imagery with meteorological and air quality data, as well as other related variables regarding yearly average traffic and inventory estimates, transportation infrastructure and demographic data, including motorized inhabitants and wood/coal stoves in use, by area. We apply statistical and machine learning methods to analyze the contribution of bare soil surfaces to the overall PM resuspension. Based on a series of stack ensemble meta-models with coefficient of determination $R^2\approx 0.9$ we conclude that the contribution of bare soil surfaces to the overall PM₁₀ resuspension is around $10\%$ (between $5\%$ and $15\%$), by our preliminary rough estimates. Full article

Urban trees are vital for air pollution mitigation, but their function is often compromised by exposure to particulate matter (PM), which impairs physiological processes and reduces growth. Enhancing tree resilience is therefore essential for maintaining their ecosystem services in polluted urban environments. This study examined the early growth and biochemical responses of Norway spruce (Picea abies) and Norway maple (Acer platanoides) seedlings to foliar PM exposure and assessed whether biochar (BC) soil amendment can alleviate PM-induced stress. Seedlings were cultivated outdoors under three treatments: Control (no treatment), PM (foliar exposure to particulate matter), and PM + BC (PM exposure with 10% biochar added to the substrate). Results revealed that Norway maple showed significant biochemical sensitivity to PM, including substantial reductions in chlorophyll and increases in antioxidant activity. However, Norway spruce showed more moderate pigment changes but reduced height growth. BC modulated oxidative and phenolic responses (TPC, TFC, MDA) and partially mitigated PM-induced stress, although its effectiveness varied by species. For Norway spruce, BC significantly enhanced resilience by restoring height growth, stabilizing pigments, and reducing oxidative stress compared with treatment using PM alone. In contrast, for Norway maple, BC failed to restore chlorophyll levels and increased oxidative and phenolic activity, yielding mixed outcomes. Despite physiological differences between the two species, multivariate PCA consistently showed that PM-treated seedlings diverged from the control cluster, whereas PM + BC-treated seedlings were closer to the controls, with mitigation substantially stronger in Norway spruce. These findings demonstrate that biochar can reduce PM-induced stress, but its successful implementation depends fundamentally on selecting appropriate species traits and understanding their specific metabolic response strategies. Full article

Indoor air quality (IAQ) in residential settings is often dominated by high-concentration pollutant events from activities such as cooking and occupancy, which are overlooked by traditional 24 h average assessments. In this, we have designed and implemented a low-cost unit for remote IAQ monitoring. We deployed these units for high-resolution remote monitoring of CO₂, particulate matter (PM), and volatile organic compounds (VOCs) in three different domestic environments: a kitchen, a living room, and a bedroom. The monitoring campaign confirmed that, while daily averages frequently remained below guideline limits, transient peaks (e.g., CO₂ exceeding 2800 ppm in bedrooms and significant increases in PM during cooking) posed acute exposure risks. This dataset was used to train and evaluate machine learning models for 10 min ahead pollutant forecasting. Ensemble tree-based methods (Random Forest) and gradient boosting algorithms (XGBoost, LGBM, and CatBoost) were effective and robust. The predictability of the models correlated with room dynamics: performance improved under clear cyclical patterns (bedroom) and remained stable under stochastic events (kitchen). This work shows that integrating low-cost IoT sensing with machine learning enables proactive IAQ management, supporting health interventions driven by predictive risk rather than static averages. Full article

This study investigates the environmental impact of combined missile and drone attacks on Kyiv, the capital of Ukraine, with a focus on the release of particulate matter (PM) into the urban atmosphere. These military strikes frequently result in the destruction of residential and industrial infrastructure, as well as fires, leading to acute increases in ambient concentrations of fine particulate matter (PM2.5). Observational data were collected between 1 and 30 June 2025 using a distributed network of low-cost air quality monitoring stations aggregated by the SaveEcoBot platform. The optical particle counters, based on light scattering technology, enable real-time monitoring of airborne particulate fractions of PM2.5 along with meteorological parameters and gas pollutants. The study period included two significant attacks (10 and 17 June), during which the temporal and spatial dynamics of PM2.5 concentrations were analyzed in comparison to baseline levels observed under non-attack conditions. Raw concentrations of PM2.5 up to 241 μg/m³ were observed in the epicenters of air-strike-induced fires, while smog plumes covered half of the city area. Elevated PM2.5 concentrations were recorded during and for several hours following the attacks and corresponding air raid alerts. The findings show days of PM2.5 exceedances above the World Health Organization (WHO) daily threshold of 15 μg/m³. These results underscore the acute environmental and public health hazards posed by military assaults on urban centers. Furthermore, this research highlights the role of citizen-driven environmental monitoring as a valuable tool for both scientific documentation and potential evidentiary support in assessing the environmental impacts of warfare. Full article