Search Results (412)

Global interest in nematode communities and their ecological relationships as unique and complex soil ecosystems has remarkably increased in recent years. As they have a representative role in the soil biota, nematodes present great potential to help understand soil health through analyzing their food chains in different environments. The objective of this study was to analyze the spatial and dynamic distributions of nematode communities and soil properties in two riparian areas of the Caatinga biome: one with native vegetation and the other with a history of agricultural use (modified). The study was carried out in a semi-arid region of Brazil in Parnamirim, PE. In both areas, sampling grids of 60 m × 40 m were established to obtain data on soil moisture, organic matter, particle size, electrical conductivity, and pH, as well as metabolic activity and ecological indices of nematode communities. There was a greater abundance and diversity of nematodes in riparian soils with native vegetation compared to in the modified area due to agricultural use and the dominance of exotic and invasive species. In both areas, bacterivores and plant-parasitic nematodes were dominant, with the genus Acrobeles and Tylenchorhynchus as the main contributors to the community. In the modified area, soil variables (fine sand, clay, and pH) positively influenced Fu4 and PP4 guilds, while in the area with native vegetation, moisture and organic matter exerted a greater influence on Om4, PP5, and Ba3 guilds. Kriging maps showed the soil variables were more concentrated in the center in the areas with native vegetation, in contrast to the area with modified vegetation, where they concentrated more on the margins. The functional guilds in the native vegetation did not exhibit a gradual increase towards the regions close to the riverbank, unlike in the modified area. The presence of plant-parasitic nematodes, especially of the genus Tylenchorhynchus, indicates the need for greater attention in the management of these ecosystems. The study contributes to understanding the interactions between nematode communities and soil in riparian areas of the Caatinga biome, emphasizing the importance of preserving native vegetation to maintain the diversity and balance of this ecosystem, in addition to highlighting the need for appropriate management practices in areas with a history of agricultural use, aiming to conserve soil biodiversity. Full article

The occurrence of haze pollution significantly deteriorates air quality and threatens human health, yet persistent knowledge gaps in real-time source apportionment of fine particulate matter (PM_2.5) hinder sustained improvements in atmospheric pollution conditions. Thus, this study employed single-particle aerosol mass spectrometry (SPAMS) to investigate PM_2.5 sources and dynamics during winter haze episodes in Yinchuan, Northwest China. Results showed that the average PM_2.5 concentration was 57 μg·m⁻³, peaking at 218 μg·m⁻³. PM_2.5 was dominated by organic carbon (OC, 17.3%), mixed carbonaceous particles (ECOC, 17.0%), and elemental carbon (EC, 14.3%). The primary sources were coal combustion (26.4%), fugitive dust (25.8%), and vehicle emissions (19.1%). Residential coal burning dominated coal emissions (80.9%), highlighting inefficient decentralized heating. Source contributions showed distinct diurnal patterns: coal combustion peaked nocturnally (29.3% at 09:00) due to heating and inversions, fugitive dust rose at night (28.6% at 19:00) from construction and low winds, and vehicle emissions aligned with traffic (17.5% at 07:00). Haze episodes were driven by synergistic increases in local coal (+4.0%), dust (+2.7%), and vehicle (+2.1%) emissions, compounded by regional transport (10.1–36.7%) of aged particles from northwestern zones. Fugitive dust correlated with sulfur dioxide (SO₂) and ozone (O₃) (p < 0.01), suggesting roles as carriers and reactive interfaces. Findings confirm local emission dominance with spatiotemporal heterogeneity and regional transport influence. SPAMS effectively resolved short-term pollution dynamics, providing critical insights for targeted air quality management in arid regions. Full article

This study assessed the influence of meteorological conditions on particulate matter (PM) concentrations in Campo Grande, Brazil, from May to December 2021. Using statistical analyses, including Pearson’s correlation coefficient and multivariate regression, we analyzed secondary data on PM2.5 and PM10 concentrations and meteorological variables from the Federal University of Mato Grosso do Sul’s Physics Department. Daily PM concentrations complied with Brazil’s National Ambient Air Quality Standards (PQAr). The PM2.5/PM10 ratios averaged 0.436 (hourly) and 0.442 (daily), indicating a mix of fine and coarse particles. Significant positive correlations were found with temperature, while relative humidity showed a negative correlation, reducing PM levels through deposition. Wind speed had no significant impact. Meteorological influences suggest that air quality management should be tailored to regional conditions, particularly addressing local emission sources like vehicular traffic and biomass burning. Full article

Maintenance dredging produces large volumes of fine sediments that are commonly discarded, despite increasing pressure for beneficial reuse. Lime–cement stabilization offers one pathway, yet field performance is highly variable. This study juxtaposes two French marine dredged sediments—DS-F (low plasticity, organic matter (OM) ≈ 2 wt.%) and DS-M (high plasticity, OM ≈ 18 wt.%)—treated with practical hydraulic road binder (HRB) dosages. This is the first French study that directly contrasts two different DS types under identical HRB treatment and proposes practical boundary thresholds. Physical indexes (particle size, methylene-blue value, Atterberg limits, OM) were measured; mixtures were compacted (Modified Proctor) and tested for immediate bearing index (IBI). IBI, unconfined compressive strength, indirect tensile strength, and elastic modulus were determined. DS-F reached IBI ≈ 90–125%, UCS ≈ 4.7–5.9 MPa, and ITS ≈ 0.40–0.47 MPa with only 6–8 wt.% HRB, satisfying LCPC-SETRA class S2–S3 requirements for road subgrades. DS-M never exceeded IBI ≈ 8%, despite 3 wt.% lime + 6 wt.% cement. A decision matrix distilled from these cases and recent literature shows that successful stabilization requires MBV < 3 g/100 g, plastic index < 25%, OM < 7 wt.%, and fine particles < 35%. These thresholds permit rapid screening of dredged lots before costly treatment. Highlighting both positive and negative evidence clarifies the realistic performance envelope of soil–cement reuse and supports circular-economy management of DS. Full article

Smectite clay minerals are known to readily form thixotropic physical gels in aqueous media, even at low volume fractions. Although the rheological properties of these gels are closely related to the microstructure of the network, the influence of the clay’s physicochemical characteristics remains insufficiently understood. In this study, we systematically investigated the relationships between particle size, cation exchange capacity, and zeta potential, and the rheological behavior of aqueous dispersions of four synthetic smectites. After thorough deionization, dispersions were prepared at controlled NaCl concentrations. We found that the zeta potential strongly correlates with the fineness of the network structure and governs macroscopic rheological responses such as viscosity, yield stress, and gelation behavior. Even under identical conditions, gel transparency and structural coarseness varied significantly among clay types. Furthermore, the storage modulus was influenced not only by network density but also by the intrinsic stiffness of the clay branches. These findings demonstrate that zeta potential serves as a unified indicator of structure and function in smectite dispersions and offer useful insights for gel design in colloidal and soft matter systems. Full article

Traditional coal quality assessment methods rely exclusively on the laboratory testing of physical samples, which impedes detailed stratigraphic evaluation and limits the integration of intelligent precision mining technologies. To resolve this challenge, this study investigates geophysical logging as an innovative method for coal quality prediction. By integrating scanning electron microscopy (SEM), X-ray analysis, and optical microscopy with interdisciplinary methodologies spanning mathematics, mineralogy, and applied geophysics, this research analyzes the coal quality and mineral composition of the Shanxi Formation coal seams in northern Jiangsu, China. A predictive model linking geophysical logging responses to coal quality parameters was established to delineate relationships between subsurface geophysical data and material properties. The results demonstrate that the Shanxi Formation coals are gas coal (a medium-metamorphic bituminous subclass) characterized by low sulfur content, low ash yield, low fixed carbon, high volatile matter, and high calorific value. Mineralogical analysis identifies calcite, pyrite, and clay minerals as the dominant constituents. Pyrite occurs in diverse microscopic forms, including euhedral and semi-euhedral fine grains, fissure-filling aggregates, irregular blocky structures, framboidal clusters, and disseminated particles. Systematic relationships were observed between logging parameters and coal quality: moisture, ash content, and volatile matter exhibit an initial decrease, followed by an increase with rising apparent resistivity (LLD) and bulk density (DEN). Conversely, fixed carbon and calorific value display an inverse trend, peaking at intermediate LLD/DEN values before declining. Total sulfur increases with density up to a threshold before decreasing, while showing a concave upward relationship with resistivity. Negative correlations exist between moisture, fixed carbon, calorific value lateral resistivity (LLS), natural gamma (GR), short-spaced gamma-gamma (SSGG), and acoustic transit time (AC). In contrast, ash yield, volatile matter, and total sulfur correlate positively with these logging parameters. These trends are governed by coalification processes, lithotype composition, reservoir physical properties, and the types and mass fractions of minerals. Validation through independent two-sample t-tests confirms the feasibility of the neural network model for predicting coal quality parameters from geophysical logging data. The predictive model provides technical and theoretical support for advancing intelligent coal mining practices and optimizing efficiency in coal chemical industries, enabling real-time subsurface characterization to facilitate precision resource extraction. Full article

This study was conducted in an urban park in a temperate-continental city of Europe (Timișoara, Romania) and aimed to investigate the contribution of urban vegetation in maintaining air quality and mitigating the heat in the analyzed city. The following air parameters were monitored: fine particulate matter PM_2.5, coarse particulate matter PM₁₀, AQI (Air Quality Index) (resulted from PM_2.5 and PM₁₀), particle number, air temperature, relative air humidity, TVOC (total volatile organic compounds), and HCHO (formaldehyde). The results of this study show that urban vegetation remains a reliable factor in reducing PM_2.5 and PM₁₀ in city air and in keeping the AQI within the limits corresponding to good air quality, but also that relative air humidity counteracts the contribution of vegetation in achieving this goal. Inside the park, the HCHO concentration increased by up to 4–5 times compared to the outside, and this increase was not caused by vehicle traffic but rather by the photochemical reactions generating HCHO. Regarding the cooling effect on air temperature, the studied green space did not exhibit this effect, as the air temperature inside it increased by up to 1–6 °C compared to the outside. Our results contrast with the general perception that urban parks and green spaces are cooler islands within the cities and draw attention to the fact that having a green space in a city does not necessarily mean achieving environmental goals, such as reducing the heat risk of cities. Based on the results, we consider that the main limitations in achieving these objectives were the park’s small size (88 hectares) and its morphology and architecture resulting from the integration of the species that compose it. It follows from these data that it is not enough for an urban green space to be established, but its design must be combined with urban morphology strategies if the heat mitigation effect is to be achieved and the cooling benefits are to be maximized in cities. Full article

Developing resource-efficient technologies for producing ceramic materials with specific properties and performance characteristics is one of the most important tasks in modern materials science. As natural resources face depletion, the use of anthropogenic wastes, including fly ash from coal combustion, for the development of new compositions and the production of ceramics with an improved microstructure is of particular significance. The use of PM₁₀ fly ash microspheres in ceramic production will help to reduce particulate matter emissions. In this study, fine narrow fractions of PM₁₀ microspheres were successfully separated from coal fly ash using aerodynamic and magnetic separation. Glass–ceramic materials with a homogeneous microstructure, an open porosity of 0.4–37%, a compressive strength of 5–159 MPa, and acid resistance of up to 99.9% were obtained using narrow fractions. The materials obtained are promising for application as highly porous ceramics, effective microfiltration membranes, and fine-structured technical ceramics, which can be used in installations operating in aggressive media and/or at high temperatures. The ceramic membranes were characterised by high liquid permeability values up to 1194 L·m⁻²·h⁻¹·bar⁻¹. Filtration tests showed that the retention coefficient for dispersed microsilica particles with d_av = 1.9 μm is 0.99. Full article

Fine particulate matter with an aerodynamic diameter ≤ 2.5 µm (PM_2.5) has been extensively studied due to its adverse health effects. Most research has focused on its impact on the respiratory system; however, increasing attention is being directed toward its effects on the brain. Associations between air pollution and neurological disorders—such as Alzheimer’s disease, cerebral infarction, and autism spectrum disorder—have been reported, with mechanism-based studies in animal models providing further insights. PM_2.5 comprises a complex mixture of thousands of chemical constituents. To elucidate its neurotoxicity mechanisms, it is essential to investigate both its transport pathways to the brain and the specific actions of its individual components. This review highlights key PM_2.5 components—water-soluble ions, metals, carbonaceous particles, polycyclic aromatic hydrocarbons, quinones, plastics, and bioaerosols—and outlines their potential routes of entry into the central nervous system, along with their associated mechanisms of action. By integrating these findings, this review contributes to a deeper understanding of the neurological effects mediated by PM_2.5, which represent one of the most critical aspects of its health impact. Full article

To meet the requirements for the efficient utilization of bulk solid wastes, technosols were cultivated using solid wastes as raw materials and their aggregate stability, bacterial community, mineralization process, and biological toxicity were investigated. A proportional mixture of four types of solid wastes (fly ash, sludge, straw, and earthworm manure) resulted in the formation of aggregates with excellent pore structure after two months of cultivation and four samples were obtained. Their soil organic matter (SOM) and total nitrogen (TN) contents were higher than those in Chinese surface soil. A total of 215 genera were common to all four samples. The high organic matter content in straw, along with its lignin content and the fine organic particles generated during the straw degradation process were conducive to the formation of highly stable aggregates, making the quality with added straw superior to that with added vermicompost. Furthermore, the addition of straw was more beneficial for increasing potential mineralized organic carbon. Amongst the four tested samples, sample 3# exhibited the best soil nutrient supply capacity along with strong mineralization but weak carbon sequestration. A seed germination test confirmed that four samples were all biologically safe. This study marked a shift from “pollution control” towards “resource utilization” in dealing with bulk solid wastes. Additionally, applying technosols for soil remediation could present an effective solution to ecological restoration challenges in soil degradation such as mining sites. Full article

Particulate matter is a mixture of fine dust and tiny droplets of liquid suspended in the air. PM₁₀ is a pollutant composed of particles smaller than 10 µm. These particles are harmful to the respiratory system. The air quality in the region and capital Lima in the Republic of Peru has been investigated in recent years. In this context, statistical analyses of PM₁₀ data with forecast models can contribute to planning actions that can improve air quality. The objective of this work is to perform a statistical analysis of the available PM₁₀ data and evaluate the quality of time series classical models and neural networks for short-term forecasting. This study demonstrates that classical time series models, particularly ARIMA and SSA, achieve lower average forecast errors than LSTM across stations SMP, CRB, and ATE. This finding suggests that for data with seasonal patterns and relatively short time series, traditional models may be more efficient and robust. Although neural networks have the potential to capture more complex relationships and long-term dependencies, their performance may be limited by hyperparameter settings and intrinsic data characteristics. 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

Ammonium nitrate (NH₄NO₃) is a major constituent of fine particulate matter (PM_2.5), playing a critical role in air quality and atmospheric chemistry. However, the dual regulatory role of ammonia (NH₃) in both the formation and volatilization of NH₄NO₃ under ambient atmospheric conditions remains inadequately understood. To address this gap, we conducted high-resolution field measurements at a clean tropical coastal site in China using an integrated system of Aerosol Ion Monitor-Ion Chromatography, a Scanning Mobility Particle Sizer, and online OC/EC analyzers. These observations were complemented by thermodynamic modeling (E-AIM) and source apportionment via a Positive Matrix Factorization (PMF) model. The E-AIM simulations revealed persistent thermodynamic disequilibrium, with particulate NO₃⁻ tending to volatilize even under NH_3gas-rich conditions during the northeast monsoon. This suggests that NH₄NO₃ in PM_2.5 forms rapidly within fresh combustion plumes and/or those modified by non-precipitation clouds and then undergoes substantial evaporation as it disperses through the atmosphere. Under the southeast monsoon conditions, reactions constrained by sea salt aerosols became dominant, promoting the formation of particulate NO₃⁻ while suppressing NH₄NO₃ formation despite ongoing plume influence. In scenarios of regional accumulation, elevated NH₃ concentrations suppressed NH₄NO₃ volatilization, thereby enhancing the stability of particulate NO₃⁻ in PM_2.5. PMF analysis identified five source factors, with NO₃⁻ in PM_2.5 primarily associated with emissions from local power plants and the large-scale regional background, showing marked seasonal variability. These findings highlight the complex and dynamic interplay between the formation and evaporation of NH₄NO₃ in NH_3gas-rich coastal atmospheres. Full article

Particulate matter (PM) has been associated with various health issues. However, the most hazardous constituents of fine particles remain unclear, particularly in Asia where the chemical compositions are highly diverse and understudied. This study investigated the concentration and health risks of particulate-bound polycyclic aromatic hydrocarbons (PAHs) and heavy metals in the indoor air of religious spaces in Bangkok, Thailand. Air samples were collected from four religious sites during periods of high activity using a six-stage NanoSampler to capture particle sizes ranging from <0.1 to >10 µm. Chemical analyses were conducted using gas chromatography-mass spectrometry (GC-MS/MS) for PAHs and inductively coupled plasma-mass spectrometry (ICP-MS) for heavy metals. The results revealed significantly elevated concentrations of PM2.5, PAHs (notably benzo[a]anthracene (BaA), chrysene (CHR), and fluoranthene (FLU)), and heavy metals (particularly Mn, Ni, and Cu). Health risk assessments indicated that both the incremental lifetime cancer risk (ILCR) and hazard quotient (HQ) values for several pollutants exceeded the U.S. EPA safety thresholds, suggesting serious cancer and non-cancer health risks for workers exposed to these environments over prolonged periods. This study highlights incense burning as a dominant source of toxic indoor air pollutants and underscores the urgent need for mitigation strategies to reduce occupational exposure in religious buildings. Full article

The combined pollution of fine particulate matter (PM_2.5) and ozone (O₃) is increasing synergistically on a global scale, posing a serious threat to human health. However, the joint toxicity and the underlying mechanisms associated with co-exposure to PM_2.5 and O₃ remain poorly understood. Through complementary in vivo animal models and in vitro cellular assays, the results demonstrate that although there was no synergistic cytotoxicity effect between PM_2.5 and O₃, the presence of O₃ significantly enhanced the genotoxicity of PM_2.5 by inducing severe DNA double-strand breaks. Furthermore, O₃ exposure significantly exacerbated the bioaccumulation of PM_2.5 by disturbing the cellular membrane integrity, thus leading to synergistic toxicity in bronchial cells and mouse lungs. Astaxanthin (AST) effectively antagonized the adverse effects of PM_2.5 and O₃ co-exposure by maintaining cell membrane integrity. These findings enhance our understanding of the pathophysiological mechanisms induced by co-exposure to PM_2.5 and O₃, and provide a promising therapeutic strategy for treating respiratory diseases caused by unavoidable exposure to these pollutants. Full article