Search Results (541)

With the growing severity of environmental pollution, people are paying increasing attention to their health. However, naturally occurring wood with health benefits and applications in human healthcare is still scarce. Natural wood exhibits a limited negative oxygen ion release capacity, and this release has a short duration, failing to meet practical application requirements. This study innovatively developed a humidity-responsive, healthy wood material with a high negative oxygen ion release capacity based on fast-growing poplar. Through vacuum cyclic impregnation technology, hexagonal stone powder was infused into the pores of poplar wood, endowing it with the ability to continuously release negative oxygen ions. The healthy wood demonstrated a static average negative oxygen ion release rate of 537 ions/cm³ (peaking at 617 ions/cm³) and a dynamic average release rate of 3,170 ions/cm³ (peaking at 10,590 ions/cm³). The results showed that the particle size of hexagonal stone powder in suspension was influenced by the dispersants and dispersion processes. The composite dispersion process demonstrated optimal performance when using 0.5 wt% silane coupling agent γ-(methacryloxy)propyltrimethoxysilane (KH570), achieving the smallest particle size of 8.93 μm. The healthy wood demonstrated excellent impregnation performance, with a weight gain exceeding 14.61% and a liquid absorption rate surpassing 165.18%. The optimal impregnation cycle for vacuum circulation technology was determined to be six cycles, regardless of the type of dispersant. Compared with poplar wood, the hygroscopic swelling rate of healthy wood was lower, especially in PEG-treated samples, where the tangential, radial, longitudinal, and volumetric swelling rates decreased by 70.93%, 71.67%, 69.41%, and 71.35%, respectively. Combining hexagonal stone powder with fast-growing poplar wood can effectively enhance the release of negative oxygen ions. The static average release of negative oxygen ions from healthy wood is 1.44 times that of untreated hexagonal stone powder, and the dynamic release reaches 2 to 3 times the concentration of negative oxygen ions specified by national fresh air standards. The water-responsive mechanism revealed that negative oxygen ion release surged when ambient humidity exceeded 70%. This work proposes a sustainable and effective method to prepare healthy wood with permanent negative oxygen ion release capability. It demonstrates great potential for improving indoor air quality and enhancing human health. Full article

Rapid industrialization and urbanization have progressed in Korea, yet public attention to hazardous pollutants emitted from industrial complexes remains limited. With the increasing coexistence of industrial and residential areas, there is a growing need for real-time monitoring and management plans that account for the rapid dispersion of hazardous air pollutants (HAPs). In this study, we conducted spatiotemporal data collection and analysis for the first time in Korea using real-time measurements obtained through mobile extractive differential optical absorption spectroscopy (Me-DOAS) mounted on a solar occultation flux (SOF) vehicle. The measurements were conducted in the Saha Sinpyeong–Janglim Industrial Complex in Busan, which comprises the Sasang Industrial Complex and the Sinpyeong–Janglim Industrial Complex. BTEX compounds were selected as target volatile organic compounds (VOCs), and real-time measurements of both BTEX and fine particulate matter (PM) were conducted simultaneously. Correlation analysis revealed a strong relationship between PM₁₀ and PM_2.5 (r = 0.848–0.894), indicating shared sources. In Sasang, BTEX levels were associated with traffic and localized facilities, while in Saha Sinpyeong–Janglim, the concentrations were more influenced by industrial zoning and wind patterns. Notably, inter-compound correlations such as benzene–m-xylene and p-xylene–toluene suggested possible co-emission sources. This study proposes a GIS-based, three-dimensional air quality management approach that integrates variables such as traffic volume, wind direction, and speed through real-time measurements. The findings are expected to inform effective pollution control strategies and future environmental management plans for industrial complexes. Full article

The Latin American and Caribbean (LAC) region faces persistent challenges of inequality, climate change vulnerability, and deteriorating air quality. The Aburrá Valley, where Medellín is located, is a narrow tropical valley with complex topography, strong thermal inversions, and unstable atmospheric conditions, all of which exacerbate the accumulation of pollutants. In Medellín, ${\mathrm{NO}}_2$ concentrations have remained nearly unchanged over the past eight years, consistently approaching critical thresholds, despite the implementation of air quality control strategies. These persistent high concentrations are closely linked to the variability of the atmospheric boundary layer (ABL) and are often intensified by prolonged dry periods. This study focuses on a representative street canyon in Medellín that has undergone recent urban interventions, including the construction of new public spaces and pedestrian areas, without explicitly considering their impact on ${\mathrm{NO}}_x$ dispersion. Using Computational Fluid Dynamics (CFD) simulations, this work evaluates the influence of urban morphology on ${\mathrm{NO}}_x$ accumulation. The results reveal that areas with high Aspect Ratios (AR > 0.65) and dense vegetation exhibit reduced wind speeds at the pedestrian level—up to 40% lower compared to open zones—and higher ${\mathrm{NO}}_2$ concentrations, with maximum simulated values exceeding 50 μg/m³. This study demonstrates that the design of pedestrian corridors in complex urban environments like Medellín can unintentionally create pollutant accumulation zones, underscoring the importance of integrating air quality considerations into urban planning. The findings provide actionable insights for policymakers, emphasizing the need for comprehensive modeling and field validation to ensure healthier urban spaces in cities affected by persistent air quality issues. Full article

Turbulent diffusion plays a critical role in atmospheric pollutant dispersion, particularly in complex environments such as urban areas. This study proposes a novel theoretical approach to enhance the calculation of the turbulent diffusion coefficient in pollutant dispersion models. We propose a new expression for the turbulent diffusion coefficient (KC), which incorporates both hydrodynamic and turbulence-related time scales. This formulation links the turbulent diffusion coefficient to pollutant travel time and turbulence intensity, offering more accurate predictions of pollutant concentration distributions. By addressing the limitations of existing empirical models, this approach improves the parameterization of turbulence and reduces uncertainties in predicting maximum individual exposure under various atmospheric conditions. The study presents a theoretical model designed to advance the current understanding of atmospheric dispersion modeling. Experimental validation, while recommended, is beyond the scope of this work and is suggested as a direction for future empirical research to confirm the practical utility of the model. This theoretical formulation could be integrated into urban air quality management frameworks, providing improved estimations of pollutant peaks in complex environments. Full article

Agriculture and animal feeding operations are responsible for 87% of ammonia emissions in the UK. Controlling NH₃ concentrations below 20 ppm is crucial to preserve workers’ and livestock’s well-being. Therefore, ammonia control systems are required for maintaining adequate air quality in livestock facilities. This study assessed the ammonia reduction efficiency of a novel air pollution abatement (APA) system used in a pig farm building. The monitoring duration was 11 weeks. The results were compared with the baseline from a previous pig cycle during the same time of year in 2023. A ventilation-controlled room was monitored during a two-phase campaign, and the actual ammonia concentrations were measured at different locations within the site and at the inlet/outlet of the APA system. A 98% ammonia reduction was achieved at the APA outlet through NH₃ absorption in tap water. Ion chromatography analyses of farm water samples revealed NH₃ concentrations of up to 530 ppm within 83 days of APA operation. Further scanning electron microscopy and energy-dispersive X-ray inspections revealed the presence of salts and organic/inorganic matter in the solid residues. This research can contribute to meeting current ammonia regulations (NECRs), also by reusing the process water as a potential nitrogen fertiliser in agriculture. Full article

Infectious diseases can spread through virus-laden respiratory droplets exhaled into the air. Ventilation systems are crucial in indoor settings as they can dilute or eliminate these droplets, underscoring the importance of understanding their efficacy in the management of indoor infections. Within the field of fluid dynamics methods, the dispersed droplets may be approached through either a Lagrangian framework or an Eulerian framework. In this study, various Eulerian methodologies are systematically compared against the Eulerian–Lagrangian (E-L) approach across three different scenarios: the pseudo-single-phase model (PSPM) for assessing the transport of gaseous pollutants in an office with displacement ventilation (DV), stratum ventilation (SV), and mixing ventilation (MV); the two-fluid model (TFM) for evaluating the transport of non-evaporating particles within an office with DV and MV; and the two-fluid model-population balance equation (TFM-PBE) approach for analyzing the transport of evaporating droplets in a ward with MV. The Eulerian and Lagrangian approaches present similar agreement with the experimental data, indicating that the two approaches are comparable in accuracy. The computational cost of the E-L approach is closely related to the number of tracked droplets; therefore, the Eulerian approach is recommended when the number of droplets required by the simulation is large. Finally, the performances of DV, SV, and MV are presented and discussed. DV creates a stratified environment due to buoyant flows, which transport respiratory droplets upward. MV provides a well-mixed environment, resulting in a uniform dispersion of droplets. SV supplies fresh air directly to the breathing zone, thereby effectively reducing infection risk. Consequently, DV and SV are preferred to reduce indoor infection. Full article

Source inversion optimization using sensor observations is a key method for rapidly and accurately identifying unknown source parameters (source strength and location) in abrupt hazardous gas leaks. Sensor number and location distribution both play important roles in source inversion; however, their combined impacts on source inversion optimization remain poorly understood. In our study, the optimization inversion method is established based on the Gaussian plume model and the generation algorithm. A research strategy combining random sampling and coefficient of variation methods was proposed to simultaneously quantify their combined impacts in the case of a single emission source. The sensor layout impact difference was analyzed under varying atmospheric conditions (unstable, neutral, and stable) and source location information (known or unknown) using the Prairie Grass experiments. The results indicated that adding sensors improved the source strength estimation accuracy more when the source location was known than when it was unknown. The impacts of sensor location distribution were strongly negatively correlated (r ≤ −0.985) with the number of sensors across scenarios. For source strength estimation, the impacts of the sensor location distribution difference decreased non-linearly with more sensors for known locations but linearly for unknown ones. The impacts of sensor number and location distribution on source strength estimation were amplified under stable atmospheric conditions compared to unstable and neutral conditions. The minimum number of randomly scattered sensors required for stable source strength inversion accuracy was 11, 12, and 17 for known locations under unstable, neutral, and stable atmospheric conditions, respectively, and 24, 9, and 21 for unknown locations. The multi-layer arc distribution outperformed rectangular, single-layer arc, and downwind-axis distributions in source strength estimation. This study enhances the understanding of factors influencing source inversion optimization and provides valuable insights for optimizing sensor layouts. Full article

Urban population growth has led to increased air pollution, influenced by disrupted wind patterns and the heterogeneous distribution of pollutants. Although the relationship between urban form and air quality is well recognized, it is often examined in isolation and through simplified urban geometries. This study addresses these limitations by numerically analyzing pollutant dispersion in densely populated hillside areas using idealized but topographically representative building geometries. A three-dimensional microclimatic simulation is conducted with ENVI-met software, incorporating parametric slope angles and building height variations. The results demonstrate that both slope steepness and building height significantly affect local pollutant concentrations: steeper slopes and taller buildings are associated with higher peak pollution values in the environment. Additionally, the simulation results show that vegetation is critical in mitigating pollution, acting as a natural barrier that enhances dispersion. These findings highlight the need for slope-sensitive urban planning and strategically integrating vegetation in hillside developments to improve air quality in complex urban terrains. Full article

The European Union views biogas production from landfills as a crucial element in achieving decarbonization goals by 2050. Biogas is primarily composed of methane (CH₄) and carbon dioxide (CO₂), produced through the anaerobic digestion of various residual materials. This study aimed to investigate CH₄ and CO₂ concentrations from municipal solid waste in biogas capture wells in a landfill in Romania between 2023 and 2024. A peak in CH₄ concentrations occurred in the fall of 2024 (P4 well), while the highest CO₂ content was recorded in the summer of 2023 (P3 well). The Aermod View software platform (version 11.2.0) was employed to model the dispersion of pollutants in the surrounding air. A worst-case scenario was applied to estimate the highest ground-level pollutant concentrations. The highest recorded CH₄ concentration was 90.1 mg/m³, while CO₂ reached 249 mg/m³ within the landfill. The highest CH₄ concentrations were found in the southern part of the site, less than 1 km from the landfill, while CO₂ was highest in the northern area. In conclusion, municipal solid waste landfills behave like unpredictable bioreactors, and without proper management and oversight, they can pose significant risks. An integrated system that combines prevention, reuse, and correct disposal is critical to minimizing these negative effects. Full article

Urban air pollution poses significant risks to cultural heritage buildings, particularly in polluted megacities like Delhi, India. The Red Fort, a UNESCO World Heritage Site and a symbol of India’s rich history, is highly susceptible to degradation caused by air pollutants. Despite its great importance as an Indian and world heritage site, no studies have focused on characterizing its constituent materials or the degradation phenomena taking place. This study was developed in the framework of the MAECI (Italian Ministry of Foreign Affairs) and the Department of Science and Technology under the Ministry of Science and Technology, India, project: Indo—Italian Centre of Excellence for Restoration and Assessment of Environmental Impacts on Cultural Heritage Monuments. To understand their composition and degradation, Vindhyan sandstone and black crust samples were studied. Scanning Electron Microscopy with Energy Dispersive X-ray Spectroscopy (SEM-EDX), X-ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), and Inductively Coupled Plasma Mass Spectrometry (ICP-MS) indicated that the red sandstone predominantly consisted of quartz and microcline, while the black crusts mainly comprised gypsum, bassanite, weddellite, quartz, and microcline. The analysis attributed the formation of gypsum to exogenous sources, such as construction activities and cement factory emissions. This pioneering study provides a basis for further research into the impacts of air pollution on Indian patrimony and promotes conservation strategies. Full article

This study introduces a digital twin paradigm that uses both stationary and mobile sensors and cutting-edge machine learning for urban air quality monitoring. By boosting $R^2$ values from 0.29 to 0.87–0.95, our two-step calibration method increased the accuracy of low-cost PM sensors, showing the possibility of growing monitoring networks without sacrificing measurement accuracy. Significant temporal and spatial variability in PM concentrations was found by mobile sensor deployments, with variations of up to 300% over short distances, predominantly during heavy traffic. During rush hours, peak concentrations were found on multi-lane boulevards and intersections, indicating important exposure concerns usually overlooked by stationary monitoring networks. According to our Graph Neural Network model, which successfully described pollutant dispersion patterns, road dust resuspension predominates in residential areas, while vehicle emissions account for 65% of PM_2.5 along high-traffic corridors. Urban green areas lower PM levels by 30%, yet when the current low-emission zones were first implemented, they had no discernible effect on air quality. Municipal authorities can use this digital twin strategy to acquire practical insights for focused air quality improvements. The method helps make evidence-based traffic management and urban planning judgments by identifying unidentified pollution hotspots and source contributions. The technique offers a scalable option for establishing healthier urban development and marks a substantial leap in environmental monitoring. Full article

The Tula Metropolitan Area in Mexico is characterized by significant industrial activity, including thermoelectric power plants, refineries, cement plants, and mining operations. While the impact of mining on air quality has been less studied compared to other industries, this research aims to estimate the contribution of mining areas to PM₁₀ air pollution in the region. Using the AERMOD dispersion model coupled with the WRF meteorological model, emission areas were identified through GIS analysis, and specific emission factors for mining activities were applied. The results indicate that mining areas can contribute up to 40 µg/m³ of PM₁₀, exceeding both national and international air quality standards. Monitoring data suggests that mining activities account for approximately 30% of the measured PM₁₀ concentrations in the area. Furthermore, spatial analysis using the Urban Marginalization Index (UMI) revealed that areas with high PM₁₀ concentrations often coincide with regions of high social vulnerability, particularly in communities with elevated levels of marginalization. This study concludes that mining operations significantly contribute to air pollution in the Tula Metropolitan Area, highlighting the need for targeted mitigation measures and public policies that address both environmental and social vulnerabilities. Full article

Tyre wear particles (TWPs), generated from tyre-road abrasion, are a pervasive and under-regulated environmental pollutant, accounting for a significant share of global microplastic contamination. Recent estimates indicate that 1.3 million metric tons of TWPs are released annually in Europe, dispersing via atmospheric transport, stormwater runoff, and sedimentation to contaminate air, water, and soil. TWPs are composed of synthetic rubber polymers, reinforcing fillers, and chemical additives, including heavy metals such as zinc (Zn) and copper (Cu) and organic compounds like polycyclic aromatic hydrocarbons (PAHs) and N-(1,3-dimethylbutyl)-N′-phenyl-p-phenylenediamine (6PPD). These constituents confer persistence and bioaccumulative potential. While TWP toxicity in aquatic systems is well-documented, its ecological impacts on terrestrial environments, particularly in agricultural soils, remain less understood despite global soil loading rates exceeding 6.1 million metric tons annually. This review synthesizes global research on TWP sources, environmental fate, and ecotoxicological effects, with a focus on soil–plant systems. TWPs have been shown to alter key soil properties, including a 25% reduction in porosity and a 20–35% decrease in organic matter decomposition, disrupt microbial communities (with a 40–60% reduction in nitrogen-fixing bacteria), and induce phytotoxicity through both physical blockage of roots and Zn-induced oxidative stress. Human exposure occurs through inhalation (estimated at 3200 particles per day in urban areas), ingestion, and dermal contact, with epidemiological evidence linking TWPs to increased risks of respiratory, cardiovascular, and developmental disorders. Emerging remediation strategies are critically evaluated across three tiers: (1) source reduction using advanced tyre materials (up to 40% wear reduction in laboratory tests); (2) environmental interception through bioengineered filtration systems (60–80% capture efficiency in pilot trials); and (3) contaminant degradation via novel bioremediation techniques (up to 85% removal in recent studies). Key research gaps remain, including the need for long-term field studies, standardized mitigation protocols, and integrated risk assessments. This review emphasizes the importance of interdisciplinary collaboration in addressing TWP pollution and offers guidance on sustainable solutions to protect ecosystems and public health through science-driven policy recommendations. Full article

Microplastics (MPs), defined as synthetic polymer particles less than 5 mm in diameter, are widely acknowledged as ubiquitous contaminants in aquatic ecosystems, including freshwater, marine, and polar environments. Global concern with MPs has significantly increased; nevertheless, much of the current knowledge remains fragmented and, at times, limited to specific regions or ecological compartments. This study emphasizes the necessity of a thorough synthesis by critically analyzing global microplastics’ dispersion patterns, ecological consequences, and associated human health concerns. A systematic approach was employed, integrating specific search terms and establishing inclusion and exclusion criteria across various scientific databases to obtain a representative collection of literature. The study covers important topics such as the classification of MPs, their distribution, environmental impacts, and interactions with other pollutants, including heavy metals, pharmaceuticals and endocrine-disrupting chemicals. Particular emphasis is placed on comparing ecosystem-specific vulnerabilities, such as those found in tropical wetlands, marine gyres, and polar systems. The review examines potential human exposure pathways, via contaminated seafood, water, and air, while also compiling new information about cellular and physiological damage, including oxidative stress, inflammation, hormone disruption, and possible genetic effects. This investigation highlights the value of collaborative monitoring, the adoption of biodegradable alternatives, policy development, and interdisciplinary research by integrating knowledge from ecology and public health. The primary objective is to advance ecosystem-specific mitigation techniques and promote evidence-based policy development in addressing this intricate environmental issue. Full article

This study presented a comprehensive physical–statistical analysis of atmospheric particulate matter (PM₁₀ and PM_2.5) and trace gases (SO₂ and O₃) over Faial Island in the Azores archipelago during 2024. We collected real-time data at the Espalhafatos rural background station, covering 35,137 observations per pollutant, with 15 min intervals. Descriptive statistics, probability distribution fitting (Normal, Lognormal, Weibull, Gamma), and correlation analyses were employed to characterize pollutant dynamics and identify extreme pollution episodes. The results revealed that PM_2.5 (fine particles) concentrations are best modeled by a Lognormal distribution, while PM₁₀ concentrations fit a Gamma distribution, highlighting the presence of heavy-tailed, positively skewed behavior in both cases. Seasonal and episodic variability was significant, with multiple Saharan dust transport events contributing to PM exceedances, particularly during winter and spring months. These events, confirmed by CAMS and SKIRON dust dispersion models, affected not only southern Europe but also the Northeast Atlantic, including the Azores region. Weak to moderate correlations were observed between PM concentrations and meteorological variables, indicating complex interactions influenced by atmospheric stability and long-range transport processes. Linear regression analyses between SO₂ and O₃, and between SO₂ and PM_2.5, showed statistically significant but low-explanatory relationships, suggesting that other meteorological and chemical factors play a dominant role. This result highlights the importance of developing air quality policies that address both local emissions and long-range transport phenomena. They support the implementation of early warning systems and health risk assessments based on probabilistic modeling of particulate matter concentrations, even in remote Atlantic locations such as the Azores. Full article