Search Results (1,264)

The concentration characteristics of SO₂, NO₂, O₃, and CO in the marine atmosphere are of great significance for understanding air–sea interactions and regional atmospheric chemical processes. However, due to the challenging conditions of marine monitoring, long-term continuous observational data remain scarce. To address this gap, this study proposes a Transfer Learning–Convolutional Neural Network (TL-CNN) model that integrates ERA5 meteorological data, EAC4 atmospheric composition reanalysis data, and ground-based observations through multi-source data fusion. During data preprocessing, the Data Interpolating Empirical Orthogonal Function (DINEOF), inverse distance weighting (IDW) spatial interpolation, and Gaussian filtering methods were employed to improve data continuity and consistency. Using ERA5 meteorological variables as inputs and EAC4 pollutant concentrations as training targets, a CNN-based inversion framework was constructed. Results show that the CNN model achieved an average coefficient of determination (R²) exceeding 0.80 on the pretraining test set, significantly outperforming random forest and deep neural networks, particularly in reproducing nearshore gradients and regional spatial distributions. After incorporating transfer learning and fine-tuning with station observations, the model inversion results reached an average R² of 0.72 against site measurements, effectively correcting systematic biases in the reanalysis data. Among the pollutants, the inversion of SO₂ performed relatively poorly, mainly because emission reduction trends from anthropogenic sources were not sufficiently represented in the reanalysis dataset. Overall, the TL-CNN model provides more accurate pollutant concentration fields for offshore regions with limited observations, offering strong support for marine atmospheric environment studies and assessments of marine ecological effects. It also demonstrates the potential of combining deep learning and transfer learning in atmospheric chemistry research. Full article

The present investigation provides a comparative six-month analysis of atmospheric pollution by polycyclic aromatic hydrocarbons (PAHs) in the urban region of Opole, Poland. The study employs dual monitoring methods: traditional quartz filter-based active air sampling and active moss biomonitoring using Pleurozium schreberi, Sphagnum fallax, and Dicranum polysetum mosses. The experimental campaign took place from August 2021 to February 2022, spanning the autumn and winter seasons. PAH concentrations were measured using gas chromatography–mass spectrometry (GC-MS) following methodical sample extraction protocols. Filters documented transient air changes in PAHs, particularly high-molecular-weight (HMW) components such as benzo[a]pyrene (BaP), which exhibited considerable increases during the colder months due to heightened heating activities and less dispersion. The size of particles deposited on the filters varied from 0.16 to 73.6 μm, with an average size of 0.71 μm. Mosses exhibited cumulative uptake trends, with D. polysetum showing the greatest bioaccumulation efficiency, particularly for low- and medium-molecular-weight PAHs, followed by P. schreberi and S. fallax. Meteorological indices, including sun radiation and air temperature, demonstrated significant negative relationships with PAH buildup in mosses. Diagnostic ratio analysis verified primarily pyrogenic sources (e.g., fossil fuel burning), although petrogenic contributions were detected in D. polysetum, indicating its increased sensitivity to evaporative emissions. The study shows that the integration of moss biomonitoring with traditional filter samples provides a strong, complementary framework for assessing air quality, particularly in fluctuating meteorological settings. The results advocate for the integration of moss-based methodologies into environmental monitoring initiatives and provide significant insights into contaminant dynamics influenced by seasonal and meteorological factors. Full article

1,3-butadiene (BD) is a volatile organic pollutant. Upon inhalation, it is metabolically activated to reactive epoxides which alkylate genomic DNA and form potentially mutagenic monoadducts and DNA–DNA crosslinks including N7-(1-hydroxyl-3-buten-1-yl)guanine (EB-GII) and 1,4-bis-(guan-7-yl)-2,3-butanediol (bis-N7G-BD). While metabolic activation resulting in mutagenicity is a well-established mode of action for 1,3-butadiene, characterization of the extent of inter-individual variability in response to BD exposure is a gap in our knowledge. Previous studies showed that population-wide mouse models can be used to evaluate variability in 1,3-butadiene DNA adducts; therefore, we hypothesized that this approach can be used to also study variability in the formation and loss of BD DNA adducts across tissues and between sexes. To test this hypothesis, female and male mice from five genetically diverse Collaborative Cross (CC) strains were exposed to filtered air or 1,3-butadiene (600 ppm, 6 h/day, 5 days/week for 2 weeks) by inhalation. Some animals were kept for two additional weeks after exposure to study DNA adduct persistence. EB-GII and bis-N7G-BD adducts were quantified in liver, lungs and kidney using established isotope dilution ESI-MS/MS methods. We observed strain- and sex-specific effects on both the accumulation and loss of both DNA adducts, indicating that both factors play important roles in the mutagenicity of 1,3-butadiene. In addition, we quantified the intra-species variability for each adduct and found that for most tissues/adducts, variability values across strains were modest compared to default uncertainty factors. Full article

Trees are vital to both environmental health and human well-being. They purify the air we breathe, support biodiversity by providing habitats for wildlife, prevent soil erosion to maintain fertile land, and supply wood for construction, fuel, and a multitude of essential products such as fruits, to name a few. Therefore, it is important to monitor and preserve them to protect the natural environment for future generations and ensure the sustainability of our planet. Remote sensing is the rapidly advancing and powerful tool that enables us to monitor and manage trees and forests efficiently and at large scale. Statistical methods, machine learning, and more recently deep learning are essential for analyzing the vast amounts of data collected, making data the fundamental component of these methodologies. The advancement of these methods goes hand in hand with the availability of sample data; therefore, a review study on available high-resolution aerial datasets of trees can help pave the way for further development of analytical methods in this field. This study aims to shed light on publicly available datasets by conducting a systematic search and filter and an in-depth analysis of them, including their alignment with the FAIR—findable, accessible, interoperable, and reusable—principles and the latest trends concerning applications for such datasets. Full article

Lunar dust remains one of the most critical unresolved challenges to long-duration lunar missions. Its sharp, abrasive, and electrostatically charged particles are easily inhaled and can penetrate deep into the lungs, reaching the bloodstream and the brain. Despite airlocks and HEPA filtration systems, dust will inevitably infiltrate lunar habitats and threaten astronaut health. We present a novel patent protected helmet design. This system uses a multilayered, synergistic mitigation approach combining mechanical and electrostatic defenses. The mechanical system delivers HEPA-filtered, ionized air across the user’s face, while the electrostatic barrier repels charged particles away from the respiratory zone. These two systems work together to prevent dust from entering the user’s breathing space. Designed for use inside lunar habitats, this helmet represents a potential solution to an unaddressed, life-threatening problem. It allows astronauts to eat, talk, and sleep while maintaining a protected respiratory zone and provides targeted inhalation-level protection in an environment where dust exposure is otherwise unavoidable. This concept is presented at Technology Readiness Level 2 (TRL 2) to prompt early engagement and feedback from the scientific and engineering communities. Full article

Filtration of submicron particles and nanoparticles is an important problem in nano-industry and in air conditioning and ventilation systems. The presence of submicron particles comprising fungal spores, bacteria, viruses, microplastic, and tobacco-smoke tar in ambient air is a severe problem in air conditioning systems. Many nanotechnology material processes used for catalyst, solar cells, gas sensors, energy storage devices, anti-corrosion and hydrophobic surface coating, optical glasses, ceramics, nanocomposite membranes, textiles, and cosmetics production also generate various types of nanoparticles, which can retain in a conveying gas released into the atmosphere. Particles in this size range are particularly difficult to remove from the air by conventional methods, e.g., electrostatic precipitators, conventional filters, or cyclones. For these reasons, nanofibrous filters produced by electrospinning were developed to remove fine particles from the post-processing gases. The physical basis of electrospinning used for nanofilters production is an employment of electrical forces to create a tangential stress on the surface of a viscous liquid jet, usually a polymer solution, flowing out from a capillary nozzle. The paper presents results for investigation of the filtration process of metal oxide nanoparticles: TiO₂, MgO, and Al₂O₃ by electrospun nanofibrous filter. The filter was produced from polyvinylidene fluoride (PVDF). The concentration of polymer dissolved in dimethylacetamide (DMAC) and acetone mixture was 15 wt.%. The flow rate of polymer solution was 1 mL/h. The nanoparticle aerosol was produced by the atomization of a suspension of these nanoparticles in a solvent (methanol) using an aerosol generator. The experimental results presented in this paper show that nanofilters made of PVDF with surface density of 13 g/m² have a high filtration efficiency for nano- and microparticles, larger than 90%. The gas flow rate through the channel was set to 960 and 670 l/min. The novelty of this paper was the investigation of air filtration from various types of nanoparticles produced by different nanotechnology processes by nanofibrous filters and studies of the morphology of nanoparticle deposited onto the nanofibers. Full article

This study investigates the impacts of the gas environment, water matrix, and reactive species on the TiO₂-mediated photocatalytic degradation of safranin O (SO), a dye commonly found in wastewater. A slurry reactor (UVA, 365 nm) was used to quantify SO oxidation while systematically varying the SO concentration (5–40 mg/L), the TiO₂ loading (0–3 g/L), the temperature (15–45 °C), and the pH (2–12). The dissolved gases (air, nitrogen, and argon) and matrices (deionized water, mineral water, and seawater) were also examined. Eight mechanistic probes (ascorbic acid, methanol, azide, nitrite, benzoquinone, oxalate, sucrose, and phenol) were used to identify active oxidants. UVA/TiO₂ achieved rapid decolorization in approximately 90 min at 10 mg/L of SO and 0.4 g/L of TiO₂. Decolorization rates decreased with increasing SO concentration due to active-site competition and inner-filter effects. Rates also exhibited a bell-shaped dependence on TiO₂ loading due to light scattering and aggregation at high solids concentrations. Temperature exhibited a non-monotonic profile with an optimum around 25 °C, and the pH displayed an optimum range with maximal removal occurring around pH 10 and declining at pH 12. Air saturation outperformed N₂ and Ar, indicating that O₂ is the terminal electron acceptor. Photocatalytic performance decreased in the order deionized water > mineral water > seawater, owing to bicarbonate/chloride scavenging and ionic-strength effects. Scavenger tests converged on ^•OH dominance, with measurable contributions from superoxide/hydrogen peroxide (O₂^•−/H₂O₂) and valence-band holes (h⁺); singlet oxygen (¹O₂) played a minor role. These findings underscore the critical interplay between operational and environmental factors and offer a practical framework for scaling TiO₂-based SO abatement in real waters. Full article

Particulate matter (PM) suspended in the air has posed significant potential threats to human health. However, current air filters designed to intercept PM are confronted with several challenges, including a complicated preparation process, monotonous protective performance, and uncomfortable wearability. Herein, a novel jet-splitting electrospinning strategy was demonstrated to simply fabricate a hierarchically structured PLA membrane with a high filtration performance, antibacterial performance, and rapid heat dissipation for effective and comfortable air filtering. Formulating a cationic antibacterial surfactant in the PLA solution to tailor the splitting of charged jets enables the simultaneous formation of nanofibers, submicron-fibers, and beads in the hierarchical filtration network by the single-jet electrospinning. Benefiting from the synergistic effect of multi-scale fibers and beads, the hierarchically structured filter exhibited an excellent filtration efficiency of 99.979% and high quality factor of 0.45 Pa⁻¹ against PM_0.3, with a remarkably low pressure drop of 18.7 Pa. Furthermore, the hierarchical structure endowed the filter with excellent stability in filtration performance, even under 20-cyclic and 480 min long-term tests, high-humidity tests with sodium chloride aerosol particles, and the 20-cycle PM_2.5 smoke tests. Simultaneously, the filter also demonstrated remarkable antibacterial performance and an excellent heat dissipation property—all achieved due to its PLA formulation and the hierarchical structure. Full article

This study investigates the variations in the PM_2.5 particles in a baghouse filter unit under variable airflow conditions. PM_2.5 emissions originate from the insect repellents commonly used in homes during warmer months, potentially affecting human health. Three low-cost sensors were installed at the entry, middle, and exit of the filter unit to measure the particle concentrations. Various filter combinations were tested. The findings revealed that using all filters achieved complete PM_2.5 retention, while reduced filter setups led to only a partial reduction. These results offer useful insights for optimizing the design and performance of air filtration systems. Full article

The global aging population, particularly those aged 60 and above, is increasingly vulnerable to communicable diseases. Building ventilation (BV) plays a key role in residential aged-care (RAC) facilities, where COVID-19 has had a significant impact. This study systematically reviews the published literature to examine the influence of BV systems (BVSs) on airborne disease (COVID-19) transmission in RACs and recommends strategies to protect vulnerable residents. Using the PRISMA framework, articles published in the last decade were sourced from Scopus, Web of Science, and PubMed. Bibliometric analyses revealed key research clusters on risk factors, transmission, facilities and services, and gender-based and retrospective studies. Australia, the USA, Africa, and the UK have made the most scholarly contributions to this field. Three main research areas emerged: BVS functionality, ventilation’s role in COVID-19 transmission, and spatial building design for effective airflow. Findings reveal that inadequate ventilation and poor indoor air quality are major contributors to disease spread, further influenced by ventilation rate, airflow, temperature, humidity, and air distribution. A hybrid ventilation design that integrates natural and mechanical systems with technologies such as HEPA filters, UVGI, and HVAC is recommended in the current study. In addition, building form and layout should incorporate spatial, engineering, administrative, and hierarchical controls in line with sustainable ventilation design guidelines. This study adds to the growing body of knowledge on the roles of ventilation and design in infection control. It offers practical recommendations for architects, RAC managers, government agencies, and policymakers involved in designing and managing RACs to reduce the risk of communicable disease transmission. Full article

Freshwater environments of large protected areas such as national parks and biosphere reserves concentrate a significant amount of natural heritage. An active release of mercury (Hg) to the global environment may challenge the state of this heritage. The present work synthesizes tentatively the information on Hg-enrichment in freshwater environments of large protected areas. A major bibliographical database was used to find the related literature (articles in international journals), which then was filtered to leave only the most relevant sources. Their content was analyzed to extract the necessary information. This bibliographical survey permitted us to find a few dozen examples of protected areas with freshwater environments enriched in mercury and methylmercury. These areas are present in the different parts of the world, and most commonly the Americas. The researchers paid more attention to mercury in biota than in water and sediments. The reported factors of Hg-enrichment differ, with the prevalence of those anthropogenic. The role of volcanism and long-distance dispersal of mercury by air and water is also significant. Interpreting the examples faces various uncertainties, but it is generally clear that Hg-enrichment can be regarded as a potential threat to natural heritage of protected areas on the global scale. It is proposed that Hg-hotspots (e.g., in Nova Scotia in Canada and Patagonia in Argentina) are rare phenomena constituting a new category of heritage. This interpretation extends the vision of the overall natural heritage of national parks and biosphere reserves. Several recommendations to natural heritage management in large protected areas with Hg-enriched freshwater environments are specified. Full article

Air and seawater samples were collected in 2022–2023 and analyzed through a common DNA extraction, purification, and Next-Generation Sequencing protocol. The study targeted bacteria, archaea, fungi, and plant-associated taxa to compare community structure across both milieus. Given the scarcity of data on environmental microbiomes in Greece, we aimed to investigate further the diversity and variability of these microbiomes for the first time, using barcoding to provide data on microbial signatures in the air and seawater. Sequencing data revealed significant spatial and seasonal variability and a high diversity and richness of microbiome communities in both habitats. After quality filtering, we detected 21 phyla and 345 genera of bacteria and archaea, 3 phyla and 149 genera of fungi, and 17 Viridiplantae orders in the urban air. At the same time, in the recreational waters, we isolated 20 phyla and 420 genera of bacteria and archaea, 2 phyla, and 53 genera of fungi and 19 orders of Viridiplantae. Many of the fungal and bacterial taxa detected in this study can be potentially pathogenic. These findings highlight the potential of DNA barcoding as a reliable tool for integrative environmental monitoring, offering insights into the composition of environmental microbiomes. Microbiome monitoring is valuable for the environment and health, and it will be more efficient by integrating DNA analysis with the development of open databases and artificial intelligence. Full article

This study characterized the aerosol changes during the April 2023 Hongseong wildfire in Chungcheongnam-do, Korea, using physical, optical, and chemical data from the Anmyeon-do Global Atmosphere Watch station. The observation period was divided into three distinct phases: immediately after the wildfire (Period I), during precipitation (Period II), and the re-entry of wildfire smoke after precipitation (Period III). During Periods I and III, the PM₁₀ mass concentrations were 75.7 ± 31.2 and 98.2 ± 55.6 µg/m³, respectively, which were approximately 2.4 and 3.1 times higher than the 2023 annual average (31.8 µg/m³) at the Anmyeon-do site. Aerosol scattering coefficients increased by factors of 4.0 and 6.9, and absorption coefficients by 5.5 and 4.2, respectively. Source apportionment using real-time data from a Monitor for Aerosols and Gases in ambient Air (MARGA) instrument combined with PCA demonstrated that aerosol emissions during Periods I and III were predominantly influenced by biomass burning sources. Analysis of PM₁₀ and PM_2.5 filter samples showed biomass burning markers, such as K⁺ and C₂O₄²⁻, increased by 5.5–31.4 times compared with those in Period II. Elevated levels of combustion-related elements, including S, K, V, and Pb, further confirmed the influence of wildfire smoke on air quality during the affected periods. Full article

Space weather exerts a significant influence on the Earth’s atmosphere, driving a variety of physical processes, including the production of cosmogenic radionuclides. Among these, ⁷Be is a naturally occurring radionuclide formed through spallation reactions induced by cosmic-ray showers interacting with atmospheric constituents, primarily oxygen and nitrogen. Over long timescales, the atmospheric concentration of ⁷Be exhibits a direct correlation with the cosmic-ray flux reaching the Earth and an inverse correlation with solar activity, which modulates this flux via variations of the heliosphere. The large availability of ⁷Be concentration data, resulting from its use as a natural tracer employed in atmospheric transport studies and in monitoring the fallout from radiological incidents such as the Chernobyl disaster, can also be exploited to investigate the impact of space weather conditions on the terrestrial atmosphere and related geophysical processes. The present study analyzes a long-term dataset of monthly ⁷Be activity concentrations in air samples collected at ground level since 1987 at the ENEA Casaccia Research Center in Rome, Italy. In particular, the linear correlation of this time series with the galactic cosmic ray flux on Earth and solar activity have been investigated. Data from a ground-based neutron monitor and sunspot numbers have been used as proxies for galactic cosmic rays and solar activity, respectively. A centered running-mean low-pass filter was applied to the monthly ⁷Be time series to extract its low-frequency component associated with cosmic drivers, which is partially hidden by high-frequency modulations induced by atmospheric dynamics. For Solar Cycles 22, 23, 24, and partially 25, the analysis shows that a substantial portion of the relationship between stratospheric ⁷Be concentrations and cosmic drivers is captured by linear correlation. Within a statistically consistent framework, the evidence supports a correlation between ⁷Be and cosmic drivers consistent with solar-cycle variability. The ⁷Be radionuclide can therefore be regarded as a reliable atmospheric tracer of cosmic-ray variability and, indirectly, of solar modulation. Full article

Nowadays, there is an emphasis on reducing emissions due to industrial processes. In recent decades, filtration systems have become an integral part of the broadly understood heavy industry systems to reduce the emission of dust and other substances harmful to the environment and humans. Filters can also be found in heating, ventilation and air conditioning (HVAC) systems, in the transport industry, and their use in households is also increasing. The effective separation of micro- or nanometer contaminants is closely related to the development of new, sophisticated filter materials. Thanks to the use of modern tools for multiphase flow modeling, it becomes possible to model the flow inside the filter material. In this study, we propose a methodology to simulate the internal flow through porous structures with a fiber size of 5–30 µm. The geometry used to build the mathematical model is the actual geometry of the filter obtained using micro-Computed Tomography (CT) imaging method. The mathematical model has been validated against experimental data. In this article, we show the methodology to adapt a geometry scan for use in commercial Computational Fluid Dynamics (CFD) software (Ansys Fluent 2021 R1). Then we present the analysis of the influence of essential parameters of numerical model, namely the size of representative elementary volume (REV) of porous material, representation quality of porous matrix and numerical mesh density on the pressure drop in the filter. Based on the conducted research, the minimum size of the REV and the numerical mesh density were determined, allowing us to obtain a representative solution of the flow structure through the filtering material. The strong agreement between the model results and experimental data highlights the potential of using a multi-fluid mathematical model to understand filtration dynamics. Full article