Search Results (614)

Soil fugitive dust (SFD) emissions pose a significant threat to both human health and the environment, highlighting the need for accurate and reliable estimation and assessment in the desert regions of northwest China. This study used climate, soil, and vegetation data from Bayingolin Prefecture (2001–2022) and applied the WEQ model to analyze temporal and spatial variations in total suspended particulate (TSP), PM₁₀, and PM_2.5 emissions and their driving factors. The region exhibited high emission factors for TSP, PM₁₀, and PM_2.5, averaging 55.46 t km⁻² a⁻¹, 27.73 t km⁻² a⁻¹, and 4.14 t km⁻² a⁻¹, respectively, with pronounced spatial heterogeneity and the highest values observed in Yuli, Qiemo, and Ruoqiang. The annual average emissions of TSP, PM₁₀, and PM_2.5 were 3.23 × 10⁷ t, 1.61 × 10⁷ t, and 2.41 × 10⁶ t, respectively. Bare land was the dominant source, contributing 72.55% of TSP emissions. Both total emissions and emission factors showed an overall upward trend, reaching their lowest point around 2012, followed by significant increases in most counties during 2012–2022. Annual precipitation, wind speed, and temperature were identified as the primary climatic drivers of soil dust emissions across all counties, and their influences exhibited pronounced spatial heterogeneity in Bazhou. In Ruoqiang, Bohu, Korla, and Qiemo, dust emissions are mainly limited by precipitation, although dry conditions and sparse vegetation can amplify the role of wind. In Heshuo, Hejing, and Yanqi, stable vegetation helps to lessen wind’s impact. In Yuli, wind speed and temperature are the main drivers, whereas in Luntai, precipitation and temperature are both important constraints. These findings highlight the need to consider emission intensity, land use, or surface condition changes, and the potential benefits of increasing vegetation cover in severely desertified areas when formulating regional dust mitigation strategies. 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

Clean and safe air quality is essential for public health, yet particulate matter (PM) significantly degrades air quality and poses serious health risks. The Gulf Cooperation Council (GCC) countries are particularly vulnerable to frequent and intense dust storms due to their vast desert landscapes. This study presents the first health risk assessment of carcinogenic and non-carcinogenic risks associated with exposure to PM2.5 and PM10 bound heavy metals and polycyclic aromatic hydrocarbons (PAHs) based on air quality data collected during the years of 2016–2018 near Dubai International Airport and Abu Dhabi International Airport. The results reveal no significant carcinogenic risks for lead (Pb), cobalt (Co), nickel (Ni), and chromium (Cr). Additionally, AI-based regression analysis was applied to time-series dust monitoring data to enhance predictive capabilities in environmental monitoring systems. The estimated incremental lifetime cancer risk (ILCR) from PAH exposure exceeded the acceptable threshold (10⁻⁶) in several samples at both locations. The relationship between visibility and key environmental variables—PM1, PM2.5, PM10, total suspended particles (TSPs), wind speed, air pressure, and air temperature—was modeled using three machine learning algorithms: linear regression, support vector machine (SVM) with a radial basis function (RBF) kernel, and artificial neural networks (ANNs). Among these, SVM with an RBF kernel showed the highest accuracy in predicting visibility, effectively integrating meteorological data and particulate matter variables. These findings highlight the potential of machine learning models for environmental monitoring and the need for continued assessments of air quality and its health implications in the region. Full article

Air quality forecasts play a crucial role in informing the public about atmospheric pollutant levels that pose risks to human health and the environment. The accuracy of these forecasts strongly depends on the quality and resolution of the input data used in the modelling process. At HungaroMet, the Hungarian Meteorological Service, the CHIMERE chemical transport model is used to provide two-day air quality forecasts for the territory of Hungary. This study compares two configurations of the CHIMERE model: the current operational setup, which uses climatological averages from the LMDz-INCA database for boundary conditions, and a test configuration that incorporates real-time boundary conditions from the CAMS global forecast. The primary objective of this work was to assess how the use of real-time versus climatological boundary conditions affects modelled concentrations of key pollutants, including NO₂, O₃, PM₁₀, and PM_2.5. The model results were evaluated against observational data from the Hungarian Air Quality Monitoring Network using a range of statistical metrics. The results indicate that the use of real-time boundary conditions, particularly for aerosol-type pollutants, improves the accuracy of PM₁₀ forecasts. This improvement is most significant under meteorological conditions that favour the long-range transport of particulate matter, such as during Saharan dust or wildfire episodes. These findings highlight the importance of incorporating dynamic, up-to-date boundary data, especially for particulate matter forecasting—given the increasing frequency of transboundary dust events. Full article

Since dust aerosols are one of the major pollutants in Georgia, it is important to study the aeolian desert dust (ADD) invasion to Georgia from the neighboring deserts to find out its contribution to the dust pollution problem. Therefore, the main objective of this study is to investigate the history, frequency and routes of ADD invasions to the Caucasus (Georgia) using modern models and technologies for 1.5 years. Using WRF-Chem/dust, CAMS and HYSPLIT mathematical models; MODIS satellite images; and PM10 field data, 38 cases of not strong ADD invasions to Georgia were found, and two typical cases are presented and analyzed in this paper. The results of the modeling studies from 15 March 2023 to 15 September 2024 showed that the WRF-Chem/dust (GOCART) v.4.5.1 model simulated the ADD transport to Georgia from the surrounding deserts quite well. Daily monitoring of ADD migration routes showed that in the easternmost region of Georgia (the most vinicultural and agricultural region), the number of ADD invasions was approximately three times higher than in other regions of Georgia, which is a novelty of this study due to the lack of ground dust measurement stations in the easternmost region of Georgia. Full article

Accurately identifying the sources of fine particulate matter (PM_2.5) pollution is crucial for pollution control and public health protection. Taking the PM_2.5 pollution event that occurred in Suzhou in June 2023 as a typical case, this study analyzed the characteristics and components of PM_2.5, and quantified the contributions of meteorological conditions, regional transport, and local emissions to the summertime PM_2.5 surge in a typical Yangtze River Delta (YRD) city. Chemical composition analysis highlighted a sharp increase in nitrate ions (NO₃⁻, contributing up to 49% during peak pollution), with calcium ion (Ca²⁺) and sulfate ion (SO₄²⁻) concentrations rising to 2 times and 7.5 times those of clean periods, respectively. Results from the random forest model demonstrated that emission sources (74%) dominated this pollution episode, significantly surpassing the meteorological contribution (26%). The Weather Research and Forecasting model combined with the Community Multiscale Air Quality model (WRF–CMAQ) further revealed that local emissions contributed the most to PM_2.5 concentrations in Suzhou (46.3%), while external transport primarily originated from upwind cities such as Shanghai and Jiaxing. The findings indicate synergistic effects from dust sources, industrial emissions, and mobile sources. Validation using electricity consumption and key enterprise emission data confirmed that intensive local industrial activities exacerbated PM_2.5 accumulation. Recommendations include strengthening regulations on local industrial and mobile source emissions, and enhancing regional joint prevention and control mechanisms to mitigate cross-boundary transport impacts. Full article

Glass curators often question how their treatments affect the long-term stability of historical glass. While damp cotton swabs are commonly used to remove surface salts and dust, the use of water remains controversial, particularly for heavily altered glass, due to concerns about worsening hydration. This study investigates the effect of water rinsing on an unstable soda-lime glass altered for six months (monoliths) and fifteen months (powders) at 35 °C and 85% relative humidity. Samples were then rinsed with Milli-Q water at 20 °C or 50 °C, and the monolithic glass was subsequently subjected to an additional 15 months of alteration under the same conditions. The glass surface was characterized by optical and scanning electron microscopy (SEM) as well as Raman spectroscopy to identify the nature of the salts. The evolution of the hydrated layer was assessed using transmission FTIR, Raman and solid-state NMR spectroscopies, ToF-SIMS, and thermogravimetric analysis (TGA). The results show that rinsing effectively removes surface salts—primarily sodium carbonate—and induces structural changes in the hydrated layer, promoting silicate network polymerization. Upon resuming alteration, rinsed monolithic samples exhibit no further degradation after the additional 15 months of alteration. These findings offer promising insights for conservation practices and may help curators refining their treatment strategies for altered glass. Full article

Shaking off the forgetfulness towards the methodological power of inosine-mediated error-prone PCR (epPCR), this study reintroduces an often-underappreciated method as a considerably powerful approach for generating aptamer libraries from a single decameric ATCG-repeat-oligonucleotide. The aim was to demonstrate that this simple way of creating sequence diversity was suitable for delivering functional starting libraries for a set of ten whole-cell-SELEX (Systematic Evolution of Ligands by Exponential Enrichment) processes. This epPCR method uses inosine to introduce targeted mutations, avoiding the need for commercial oligo pools or large-scale synthesis. We applied this method to a “universal aptamer” and subjected the three resulting libraries to two rounds of selection against ten diverse targets including probiotic and pathogenic bacteria (Gram-negative and -positive) as well as human cell lines. The enriched aptamers exhibited new binding specificities, demonstrating that the approach supports functional selection. Much like dusting off an old tool and finding it perfectly suited for a modern task, this work shows that revisiting established techniques can address current challenges in aptamer development. Our main finding is that epPCR provides a robust, cost-effective strategy for generating starting libraries and lowers the barrier for initiating successful SELEX campaigns. Full article

Large steam turbine generators are increasingly vulnerable to damage from shaft voltages and bearing currents due to the widespread adoption of modern power electronic excitation systems and more flexible operating regimes. Earthing brushes provide a critical path for discharging these shaft currents and voltages, but their effectiveness depends on the timely detection of brush degradation or faults. Conventional monitoring of shaft voltage and current is often rudimentary, typically limited to peak readings, making it challenging to identify specific fault conditions before mechanical damage occurs. This study addresses this gap by systematically analyzing shaft voltage and current signals under various controlled earthing brush fault conditions (floating brushes, worn brushes, and oil/dust contamination) in several large turbine generators. Experimental site tests identified distinct electrical signatures associated with each fault type, demonstrating that online shaft voltage and current measurements can reliably detect and classify earthing brush faults. These include unique RMS, DC, and harmonic patterns in both voltage and current signals, enabling accurate fault classification. These findings highlight the potential for more proactive maintenance and condition-based monitoring, which can reduce unplanned outages and improve the reliability and safety of power generation systems. Full article

Dust emissions from unpaved haul roads in open-pit coal mining pose a significant risk to air quality, health, and operational efficiency of mining operations. This study integrated real-time field monitoring with numerical simulations using ANSYS Fluent 2023 R1 to investigate the generation, dispersion, and migration of particulate matter (PM) at the Ha’erwusu open-pit coal mine under varying meteorological conditions. Real-time measurements of PM2.5, PM10, and TSP, along with meteorological variables (wind speed, wind direction, humidity, temperature, and air pressure), were collected and analyzed using Pearson’s correlation and multivariate linear regression analyses. Wind speed and air pressure emerged as dominant factors in winter, whereas wind and temperature were more influential in summer (R² = 0.391 for temperature vs. PM2.5). External airflow simulations revealed that truck-induced turbulence and high wind speeds generated wake vortices with turbulent kinetic energy (TKE) peaking at 5.02 m²/s², thereby accelerating particle dispersion. The dust migration rates reached 3.33 m/s within 6 s after emission and gradually decreased with distance. The particle settling velocities ranged from 0.218 m/s for coarse dust to 0.035 m/s for PM2.5, with dispersion extending up to 37 m downwind. The highest simulated dust concentration reached 4.34 × 10⁻² g/m³ near a single truck and increased to 2.51 × 10⁻¹ g/m³ under multiple-truck operations. Based on spatial attenuation trends, a minimum safety buffer of 55 m downwind and 45 m crosswind is recommended to minimize occupational exposure. These findings contribute to data-driven, weather-responsive dust suppression planning in open-pit mining operations and establish a validated modeling framework for future mitigation strategies in this field. Full article

Allergic diseases, particularly respiratory allergies like asthma and allergic rhinitis, are a growing public health concern influenced by environmental factors such as climate change and air pollution. The exposome framework enables a comprehensive assessment of how lifelong environmental exposures shape immune responses and allergic sensitization. Peru’s diverse ecosystems and climates provide a unique setting to investigate regional variations in allergic sensitization. This study characterized these patterns in five Peruvian regions with distinct climatic, urbanization, and socioeconomic characteristics. A total of 268 individuals from Lima, Piura, Tarapoto, Arequipa, and Tacna were analysed for allergen-specific IgE responses using a multiplex IgE detection system. The results revealed significant geographical differences in sensitization frequencies and serodominance profiles, based on descriptive statistics and supported by Chi-square comparative analysis. House dust mites were predominant in humid regions, while Arequipa exhibited higher sensitization to cat allergens. In Tacna, olive pollen showed notable prevalence alongside house dust mites. Tarapoto’s high humidity correlated with increased fungal and cockroach allergen sensitization. Notably, some allergens traditionally considered minor, such as Der p 5 and Der p 21, reached sensitization prevalences close to or exceeding 50% in certain regions. These findings provide the most detailed molecular characterization of allergic sensitization in Peru to date, highlighting the importance of region-specific allergy management strategies. Understanding environmental influences on allergic diseases can support more effective diagnostic, therapeutic, and preventive approaches tailored to diverse geographical contexts. Full article

Accurate projection of future climate trends in arid regions critically depends on reliable precipitation simulations. However, most Coupled Model Intercomparison Project Phase 6 (CMIP6) models exhibit systematic overestimations of precipitation in Northwest China, a bias that undermines the credibility of climate projections for this vulnerable region. This persistent bias likely stems from the omission of key physical processes in traditional models. In this study, we incorporate a dust–ice-cloud interaction scheme into the Community Atmosphere Model version 5 (CAM5) model to investigate its role in regulating precipitation over dust-rich arid regions. This physical mechanism, which is rarely included in conventional models, is particularly relevant for Northwest China where dust aerosols are abundant. Our results show that accounting for dust-induced ice nucleation leads to a significant reduction in total precipitation, especially in the convective component, thereby alleviating the longstanding wet bias in the region. These findings underscore the critical importance of dust–ice-cloud interactions in simulating precipitation in arid environments. To improve the accuracy of future climate projections in Northwest China, climate models must incorporate realistic representations of dust-related microphysical processes. Full article

This study aimed to examine trace element concentrations in indoor dust and evaluate health risks in child development centers in haze and industrial areas of Thailand from November 2023 to April 2024. The samples were extracted using a microwave oven and analyzed via ICP-OES. The finding indicated that the levels of As, Cr, Pb, V, Fe, Mn, and Zn in the dust from child development centers in the industrial area were significantly higher than those in the haze area (p < 0.05). The presence of trace element contaminants in indoor dust is indicative of anthropogenic sources. Cd and Zn in both areas have shown significantly elevated risks, according to the probable ecological risk factor. Source apportionment identified traffic, road dust, and biomass combustion as the principal sources of pollution in the haze area, while traffic and combustion activities were significant in the industrial area. Non-carcinogenic risk assessments for children exposed to As, Pb, Cu, and Cr revealed potential health risks (HI > 1). Furthermore, the total cancer risk (TCR) linked to As, Cr, and Ni is considered acceptable within the criteria of 10⁻⁶ to 10⁻⁴. However, long-term exposure may increase the risk of cancer in children. Full article

Aerosols play a critical role in modulating the land–atmosphere energy balance, influencing regional climate dynamics, and affecting air quality. Xinjiang, a typical arid and semi-arid region in China, frequently experiences dust events and complex aerosol transport processes. This study provides a comprehensive analysis of the spatiotemporal evolution and potential source regions of aerosols in Xinjiang from 2005 to 2023, based on Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products (MCD19A2), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) vertical profiles, ground-based PM_2.5 and PM₁₀ concentrations, MERRA-2 and ERA5 reanalysis datasets, and HYSPLIT backward trajectory simulations. The results reveal pronounced spatial and temporal heterogeneity in aerosol optical depth (AOD). In Northern Xinjiang (NXJ), AOD exhibits relatively small seasonal variation with a wintertime peak, while Southern Xinjiang (SXJ) shows significant seasonal and interannual variability, characterized by high AOD in spring and a minimum in winter, without a clear long-term trend. Dust is the dominant aerosol type, accounting for 96.74% of total aerosol content, and AOD levels are consistently higher in SXJ than in NXJ. During winter, aerosols are primarily deposited in the near-surface layer as a result of local and short-range transport processes, whereas in spring, long-range transport at higher altitudes becomes more prominent. In NXJ, air masses are primarily sourced from local regions and Central Asia, with stronger pollution levels observed in winter. In contrast, springtime pollution in Kashgar is mainly influenced by dust emissions from the Taklamakan Desert, exceeding winter levels. These findings provide important scientific insights for atmospheric environment management and the development of targeted dust mitigation strategies in arid regions. Full article

This study examines the influence mechanism of mining depth evolution on dust distribution, using the An Tai Bao open-pit coal mine as the research subject. A spatial coordinate system of the mining area was established utilizing a GIS positioning system, and high-resolution topographic data were extracted using Global Mapper. The research team developed a three-dimensional geological model updating algorithm with depth gradient as the characteristic parameter, enabling dynamic monitoring of mining depth with a model iteration accuracy of 0.5 m per update. A Fluent-based numerical simulation method was employed to construct a depth-dependent dust migration field solving system, aiming to elucidate the three-dimensional coupling mechanism between mining depth and dust dispersion. The findings reveal that mining depth demonstrates a three-stage critical response to dust migration. When the depth surpasses the threshold of 150 m, the wind speed attenuation rate at the pit bottom exhibits a marked change, and the dust dispersion distance decreases by 62% compared to shallow mining conditions. The slope pressure field evolution shows a significant depth-enhancement effect, with the maximum wind pressure at the leeward step boundary increasing by 22–35% for every additional 50 m of depth, resulting in dust accumulation zones with distinct depth-related characteristics. The west wind scenario demonstrates a particularly notable depth amplification effect, with the dust dispersion range in a 200-meter-deep pit expanding by 53.7% compared to the standard west wind condition. Furthermore, the interaction between particle size and depth causes the dust migration distance to exhibit exponential decay as depth increases. This research elucidates the progressive constraining influence of mining depth, a critical control parameter, on dust migration patterns. It establishes a depth-oriented theoretical framework for dust prevention and control strategies in deep open-pit mines. Full article