Search Results (1,867)

The objective of this study is to evaluate the potential of airborne spore monitoring for predicting the severity of foliar diseases in winter wheat by developing variety-dependent disease models that account for variety susceptibility and applying a statistical procedure that accommodates the hierarchical structure of panel data. The experiments were conducted in the fields of the FSBSI Federal Research Center of Biological Plant Protection on plots sown with five winter wheat varieties exhibiting varying susceptibility to foliar diseases, while the processing of the data was carried out in 2025–2026. The concentration of spores in the air was estimated using a portable spore trap. Along with air sampling, visual assessments of the development of major fungal pathogens on plants were performed. The hypothesis of variety-specific susceptibility was tested using moderation analysis. The analysis revealed a relationship between leaf disease severity and the number of detected spores, with the strength of correlation varying depending on the pathogen species and variety susceptibility. Using pairwise comparisons of regression slopes for each variety, it was demonstrated that the development of Blumeria graminis depends primarily on spore concentration levels and climatic conditions rather than on variety identity. In contrast, for Puccinia striiformis, Puccinia triticina, and Pyrenophora tritici-repentis, variety susceptibility/resistance was shown to exert a statistically significant influence on disease development. These findings will serve as the foundation for a novel phytosanitary monitoring methodology, which is essential for generating forecasts and informing decision-making regarding plant protection measures. Full article

Urban heat island effects increasingly challenge pedestrian mobility by intensifying thermal stress and reducing the attractiveness of walking during hot periods. However, most pedestrian routing systems still prioritize distance or travel time, while environmental conditions such as heat exposure and shade are rarely incorporated into operational route generation. Existing comfort-aware approaches often rely on static maps, simulated microclimatic indicators, or descriptive greenery measures, limiting their direct integration into user-configurable pedestrian navigation. This study develops a thermal comfort-aware pedestrian routing framework that integrates heterogenic data sources including observed land surface temperature, pedestrian-perspective tree-canopy coverage, and network distance into a unified multi-criteria pathfinding model. The workflow proceeds in four steps: first, airborne thermal imagery is processed to derive a high-resolution land surface temperature layer; second, Google Street View images are sampled at street-segment locations and segmented using SegFormer to extract visible tree-canopy coverage; third, both environmental indicators are aggregated to a cleaned pedestrian network; and fourth, normalized distance, temperature, and canopy attributes are combined through a user-adjustable edge-cost formulation and solved using Dijkstra’s algorithm. The framework is implemented as an operational web-based routing tool for the historic center of Clermont-Ferrand, France. The routable graph includes 551 nodes and 796 edges, with 600 segments carrying GSV-derived canopy information and 623 segments carrying airborne-derived LST values. Across the network, we observed LST ranges from 19.5 °C to 39.1 °C, while canopy coverage ranged from 0 to 70.6%. For a representative origin–destination pair, the coolest route reduces average LST by nearly 5 °C and almost triples canopy coverage compared with the shortest path, although at the cost of a 72% longer distance. These results demonstrate that the framework can generate interpretable comfort–efficiency trade-offs and support user-comfort pathfinding as an operational approach for heat-resilient pedestrian navigation. Full article

Vector-borne diseases remain a public health concern, and ultra-low-volume (ULV) systems generate adulticide droplets that must remain airborne long enough to contact flying mosquitoes. Accurate droplet and aerosol size characterization is essential for equipment calibration, interpretation of efficacy studies, and evaluation of the airborne fraction relevant to spray transport. This study evaluated complementary nozzle-level and downstream airborne measurements under controlled chamber conditions using a DC-IV droplet counter, TSI APS 3321, and GRIMM MiniWRAS 1.371. Mineral oil and kerosene were atomized at 1.0 to 10.5 bar and 0.20 to 1.00 mL/min. Mass median diameter (MMD), count median diameter (CMD), regression relationships, and size distributions were evaluated. Four MMD calculation methods were also assessed, including Hatch–Choate conversion and a Volume-Based method. For mineral oil, DC-IV reported a mean MMD of 30.78 µm, compared with 4.88 µm for APS and 3.15 µm for MiniWRAS. For kerosene, differences narrowed to 6.21, 6.45, and 4.09 µm, respectively. Hatch–Choate estimates were unstable when lognormal assumptions were violated, whereas the Volume-Based method reproduced reported APS and MiniWRAS MMD values within ±1%. These findings support continued DC-IV use for nozzle calibration and indicate that APS and MiniWRAS can provide complementary real-time characterization of the downstream airborne spray aerosols. Full article

Marine boundary layer (MBL) clouds strongly influence radiation and precipitation over the Southern Ocean (SO), yet their vertical structures and microphysical properties remain poorly constrained across observational platforms. This study compares macrophysical and microphysical properties of single-layer, liquid-dominant MBL clouds below 3 km using aircraft observations from the SO Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES), ship-based observations from Measurements of Aerosols, Radiation, and Clouds over the SO (MARCUS), and satellite observations from CloudSat. An empirical reflectivity–microphysics retrieval framework developed from in situ droplet size distributions (DSDs) measured during SOCRATES was applied to MARCUS M-WACR and CloudSat CPR reflectivity observations to retrieve vertical profiles of number concentration (N), effective radius (r_e), and liquid water content (LWC) for cloud and drizzle particles. Cloud boundary heights and retrieved microphysical properties show broad agreement across the three platforms within the limitations imposed by instrumental sensitivity, sampling differences, and retrieval uncertainties. However, CloudSat CPR observations exhibit larger deviations because of their coarser vertical resolution and lower reflectivity sensitivity, including limited detection of low clouds below ~500 m. The observed vertical structures are consistent with condensational growth, entrainment, and collision–coalescence processes. Overall, the results demonstrate broad consistency in cloud and drizzle properties across the three platforms, while highlighting the impacts of instrumental sensitivity, vertical resolution, and sampling differences on cloud boundary detection and microphysical retrievals. Full article

Maternal exposure to polycyclic aromatic hydrocarbons (PAHs) during pregnancy has been associated with adverse obstetric and perinatal outcomes, including miscarriage, low birth weight, intrauterine growth restriction, and spontaneous abortion. Exposure occurs through multiple pathways, including dietary intake and inhalation, which ultimately determine the final body burden. PAHs may reach relevant levels in the blood, representing the initial step in their internal distribution to the placenta, umbilical cord, and breast milk, thereby compromising maternal–fetal health. In this exploratory study, maternal blood samples were collected from pregnant women residing in different regions of Antioquia, Colombia. Serum was isolated from whole blood, subsequently extracted using freezing-assisted liquid–liquid extraction, purified by solid-phase extraction, and analyzed by GC–MS. Method performance showed PAH recoveries between 60 and 120%, limits of detection (LOD) ranging from 0.5 to 3.3 ng·mL⁻¹, and limits of quantification (LOQ) ranging from 1.4 to 9.9 ng·mL⁻¹. Airborne PAH concentrations were measured using a photoelectric aerosol sensor, and higher levels were observed in municipalities intersected by major highways, indicating a strong vehicular contribution, with an average concentration of 72.6 ± 39.2 ng·m⁻³. Low and medium-molecular weight PAHs were detected in serum samples at an average concentration of 43.8 ± 8.8 ng·g⁻¹ of lipid (mean of ∑ individual congeners). In contrast, a high-molecular-weight PAH, benzo[a]pyrene (BaP), was detected in one participant. Pyrene (PYR) and fluoranthene (FLU) were the predominant congeners, suggesting combustion-related sources, primarily vehicular emissions. Serum PAH levels showed a correlation with the frequency of consumption of canned fish and meat, but not with short-term airborne PAH measurements. These exploratory findings suggest that dietary intake is a primary pathway of bioaccumulation during acute exposure and plays a key role in determining the parental PAHs burden during pregnancy in polluted environments. However, additional data on parent PAHs and their metabolites are needed to provide a more comprehensive assessment of cumulative exposure arising from dietary sources and chronic inhalation of airborne PAHs. Full article

The accurate classification of seabed sediment and benthic covers in shallow-water environments remains a key challenge for marine activities and oceanographic research. However, coastal areas of shallow waters are influenced by complex dynamic environments, making it difficult to obtain authentic sediment and benthic-cover samples. Therefore, to address the problem of few-shot classification of seabed sediment and benthic covers, a few-shot classification algorithm of seabed sediment and benthic covers based on the fusion model of airborne LiDAR bathymetry (ALB) and multispectral images is proposed in this article. Based on the extracted features, a scale-invariant feature transform-progressive sample consensus (SIFT-PROSAC) algorithm and perspective transform model were constructed to achieve feature fusion. Then, multi-modal feature selection is realized using a formal concept analysis-Relief-F (FCA-Relief-F) algorithm. Finally, a graph attention network-prototype network (GAT-PN) model was established to classify five types of sediment and benthic cover (coral reef, stone, sand, vegetation, and coastal zone). To validate the effectiveness of the proposed method, experimental data from actual measurements at Ganquan Island in the Xisha Islands of China were used. Compared to other classical classifiers, the GAT-PN algorithm achieves a higher classification accuracy, with an overall accuracy (OA) and Kappa coefficient of 97.50% and 0.97, respectively. The findings of this study provide effective technical support for marine engineering and related fields. Full article

This study investigated indoor environmental air quality (IEAQ) across university workspaces at a higher education institution in Sharjah, United Arab Emirates (UAE), assessing environmental conditions that may influence occupant health, the surrounding environment, and sustainability. Physical parameters (temperature, relative humidity, noise, and illuminance), chemical parameters (indoor gases and particulate matter), and biological contaminants (airborne bacteria and fungi) were measured in semi-occupied indoor environments with a total of 68 random samples collected and analyzed. Perceived heat discomfort and environmental variability were assessed using the Thom Discomfort Index (TDI), Humidex Index, ANOVA, Kruskal–Wallis, Mann–Whitney U, and one-sample t-tests. Average measurements of relative humidity, temperature, noise, and illuminance were 60.7%, 21.6 °C, 57.5 dB, and 440 lux, respectively. Average concentrations of PM_2.5, PM₁₀, CO, and CO₂ were 1223 ppm, 104 ppm, 1 ppm, and 623 ppm, respectively. Microbial contamination was generally insignificant across most investigated workspaces. While most measured parameters remained within recommended threshold limit values (TLVs), elevated levels of noise, illuminance, and particulate matter were observed in selected workspaces. These findings demonstrate that university indoor environments generally maintain acceptable air quality conditions; however, targeted interventions, including improved HVAC maintenance and indoor pollutant management, are required to enhance sustainable university indoor environments and optimize occupant comfort. Full article

Brake wear particles are an increasingly relevant source of traffic-related particulate emissions and are addressed by the recently introduced Euro 7 emission regulation. Airborne fractions of brake wear emissions, in particular, have been associated with adverse effects on human health and other organisms. Although several brake particle mitigation strategies have demonstrated promising results under controlled laboratory conditions, their effectiveness under variable open-road driving conditions remains insufficiently understood. This study therefore investigates the transfer of two test-bench-validated mitigation strategies to a fully instrumented passenger vehicle capable of measuring brake particle number (PN) and particulate mass (PM) emissions. The first strategy is a passive approach based on a modified brake pad–disc material pairing, while the second is an active filtration system that extracts particle-laden air directly from the brake friction zone. Both approaches were evaluated during two open-road driving cycles: a real driving emissions (RDE)-compliant cycle and a more dynamic cycle characterized by higher brake stress. Airborne particle emissions were measured over a size range from 300 nm to 10 µm. During the RDE-compliant cycle, the passive approach reduced PN and PM emissions by 44% and 94%, respectively, compared with the reference brake system. Under the higher thermal and mechanical loads of the dynamic cycle, the reductions decreased to 10% for PN and 64% for PM. The active filtration system achieved an increase in PN of 4% in RDE conditions and 11% under high-severity driving. Nevertheless, PM emissions were reduced by 23–97%, depending on its operating mode of the filtration system and the associated airflow and energy demand. For high-severity driving, the PM emissions have been reduced by 40% compared to the reference braking system. These results show that both mitigation approaches hold the potential to reduce brake particle emissions under open-road conditions, although their effectiveness depends strongly on brake load and system operation. The study extends previous laboratory-based investigations by directly comparing passive and active mitigation strategies on the same vehicle under real-world driving conditions. Full article

Pollen exposure drives allergic disease in millions of Americans, yet no standardized, publicly available national pollen dataset has existed until now. We describe the first nationally standardized and publicly available dataset of pollen season timing and airborne pollen concentrations. The data were derived from the National Allergy Bureau™ (NAB™), the only pollen and mold measuring network in the United States certified by the American Academy of Allergy, Asthma & Immunology (AAAAI), and curated, processed, and disseminated by the U.S. Centers for Disease Control and Prevention (CDC). The 2003–2024 dataset provides standardized measures of (1) taxa-specific historical average main pollen season (MPS) concentrations and timing (e.g., start dates, peak dates, end dates, season length); (2) taxa-specific yearly MPS concentrations and timing; (3) grouped weekly MPS concentrations, levels, and timing; and (4) grouped daily pollen levels and MPS timing. Pollen concentrations are reported as pollen grains per cubic meter (PPCM). MPS timing is computed using a 3-day consecutive method: season start occurs after the first occurrence of three consecutive days with concentrations > 1.0 PPCM; season peak is the day of maximum concentration; and season end occurs after the first occurrence of three consecutive days with concentrations < 1.0 PPCM after the peak. Historical average timing is calculated in a 365-day-of-year format and converted to calendar dates using 2024 as a reference year for display and consistency. By combining long-term data from monitoring sites across the country, this dataset shows how pollen levels vary over time and across geographic locations. This resource supports tracking pollen trends, linking pollen with weather and climate factors, and informing public health action, clinical care, and communication about population exposure and the impact to allergic diseases such as asthma and hay fever. Full article

The sound reduction index R is commonly determined using standardized laboratory procedures developed primarily for full-size building elements. However, in many research and development applications, including technical enclosures, lightweight panels, modular components, and new acoustic materials, only reduced-size specimens are available. In such cases, the influence of specimen dimensions and test-opening geometry on the measured sound insulation is not yet fully understood. This study investigates the effect of specimen size and geometry on the measured sound reduction index using a dedicated small-scale coupled reverberation room stand. Measurements were performed for five materials with different mechanical and structural properties: steel, polymethyl methacrylate (PMMA), medium-density fiberboard (MDF), gypsum board, and Sylomer. Six test openings were analyzed, including three square openings, one quasi-square opening, and two rectangular openings. The results show that specimen dimensions can significantly affect the measured values of R, especially in the low-frequency range, where modal behavior, boundary conditions, and the relationship between specimen dimensions and acoustic wavelength are important. The influence of specimen size was material-dependent and was more pronounced for stiff plate-like materials than for the highly compliant Sylomer specimen. Comparisons between square and rectangular openings with similar surface areas suggest that, within the investigated range of materials, specimen geometries, and measurement conditions, specimen surface area had a greater influence on R than specimen shape, although geometry can still contribute to the measured differences. The repeatability analysis confirmed that the measurement stand is sensitive to differences related to material type, specimen dimensions, and installation conditions. The proposed methodology may be particularly useful for comparative studies of novel acoustic materials and prototype building elements when only reduced-size specimens are available during the early stages of material development. The results support the use of small coupled reverberation rooms for comparative testing and preliminary material screening, while also showing that reduced-size sound insulation measurements require careful interpretation and cannot be treated as direct substitutes for full-scale standardized tests. Full article

Wood-processing industrial facilities in which Norway spruce wood (Picea abies) is processed and where products such as sawdust, wood chips or wood are generated are considered high-risk operations from the perspective of fire safety and explosion hazards. This is due to the combination of combustible material, fine particulate matter, ignition sources, and the potential for dust explosions. In this article, we focused on three different fractions of spruce wood (Picea abies) commonly present in the wood-processing industry: sawdust, wood chips, and compact wood. Experimental measurements were carried out under laboratory conditions in accordance with ISO 871. Ignition temperature, flash-ignition temperature, and activation energy are key parameters that determine the susceptibility of spruce wood, sawdust, and wood dust to ignition. Fine wood fractions exhibit lower activation energy and lower ignition temperatures, which increases the probability of combustion initiation. The activation energy for spontaneous ignition of sawdust was 45.1 kJ·mol⁻¹, compared with 66.5 kJ·mol⁻¹ for compact wood and 31.9 kJ·mol⁻¹ for wood chips. The activation energy for the flash point of sawdust was 48.5 kJ.mol⁻¹, for wood chips was 36.8 kJ.mol⁻¹ and for compact wood was 44.9 kJ.mol⁻¹. In combination with airborne wood dust, these conditions create a significant potential for fire development and dust explosions in wood-processing industrial facilities. Full article

Background: Long-term care facility (LTCF) residents are highly susceptible to healthcare-associated infections, and prevention is challenging given frailty, dementia, communal living, and resource constraints. Environmental surface and air contamination contribute to transmission. Novel no-touch automated disinfection technologies have been studied in hospitals, but evidence specific to LTCFs is scarce. This scoping review summarizes recent LTCF-focused interventions, their effectiveness, and implementation considerations. Methods: This scoping review was conducted following the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) Checklist. We searched PubMed, Medline, Embase, CINAHL, and Scopus for observational or experimental studies evaluating environmental disinfection in LTCFs/nursing homes, excluding body decolonization, non-LTCF settings, and reviews/protocols. Two reviewers independently screened and extracted data via Covidence. This review has been registered on OSF (Open Science Framework). Results: Of 1491 records, 7 studies met the inclusion criteria (6 from the USA, 1 from Australia): one cluster randomized trial, one interrupted time series studies, three prospective observational studies, and two pre–post designs. Interventions included physical methods (HVAC-integrated UV/UVGI, continuous UVGI) and chemical approaches (dry hydrogen peroxide, room fogging plus chlorine dioxide wipes, hydrogen peroxide wipes). Outcomes were heterogeneous (surface SARS-CoV-2 RNA, COVID-19 attack/case rates, airborne/surface microbial loads, and one clinical endpoint—acute respiratory illness). Several studies reported reductions in environmental or airborne bioburden; however, UV-based studies did not demonstrate statistically significant reductions in clinical infections. Certainty was limited by small numbers, non-randomized designs, and diverse outcome measures. Conclusions: No-touch automated disinfection methods appear promising as supplements to standard infection prevention control bundles for reducing environmental contamination in LTCFs. Nevertheless, consistent clinical benefits are unproven. Rigorous, LTCF-tailored, adequately powered trials with standardized clinical and environmental outcomes, plus implementation and cost-effectiveness evaluations, are needed. Full article

High-resolution surface soil moisture (SM) is needed for local hydrological and agricultural applications, but reliable retrieval at 100 m remains challenging. Within this broader methodological context, radiometer-constrained SAR change detection remains a practical and interpretable option for high-resolution soil moisture retrieval. It uses SAR-derived temporal changes to describe fine-scale wetting and drying processes, while passive microwave observations provide volumetric moisture references. This study proposes an improved SMAP-anchored Sentinel-1 change-detection framework (ISSF) for 100 m SM mapping. ISSF addresses these limitations by fitting NDVI-binned upper-envelope samples with a nonlinear quadratic function to normalize the vegetation-dependent backscatter-change range and by using multi-year SMAP dry/wet quantiles to scale the normalized relative wetness into volumetric SM. ISSF was evaluated using in situ measurements, a near-concurrent airborne reference, SMAP-based products, and direct transfer to OzNet. In the Shandian River Basin, ISSF achieved R = 0.549 and ubRMSE = 0.062 m³ m⁻³ at the point scale. Relative to three benchmark change-detection methods, ISSF increased R by 11–53% and reduced ubRMSE by 7–15%. For the airborne-referenced event, ISSF showed R = 0.635 and ubRMSE = 0.027 m³ m⁻³. Under direct transfer to OzNet, ISSF achieved mean R = 0.55 and mean ubRMSE = 0.05 m³ m⁻³. These results indicate that ISSF provides a practical and interpretable approach for 100 m soil moisture mapping in semi-arid regions with sparse to moderate vegetation. Full article

While state-of-the-art massive acoustic arrays typically rely on costly, specialized FPGA architectures or rigid proprietary hardware, there is a growing need for modular, high-density sensing in complex aeroacoustics environments. This paper presents the electronic and acoustic design of a multiplexed, modular, scalable, and low-cost massive acoustic array (MxArray) founded on an embedded Linux system. The AM3358 SoC microprocessor collects audio data through its multichannel audio peripheral, where it simultaneously receives four Time-Division Multiplexing streams of 16 microphones each. This multiplexed scheme enables the handling of 64 microphones per module, whose acquisition synchronization is set with the Precision Time Protocol and a pulse injection hardware. The combination of both BeagleBone Black and microphones based on Micro-Electro-Mechanical Systems yields a cost-effective solution with built-in Ethernet connectivity and accessible software development through an embedded Linux environment with audio libraries for hardware control. Sensors are arranged in an Underbrink Spiral pattern on a four-layer printed-circuit board. The perforated thin layout minimizes any airborne disturbance, exploiting a distribution that simultaneously achieves a low sidelobe level and a narrow main lobe when used with a beamforming algorithm. Measurement results for the developed module are presented, as well as an evaluation of a full-scale system comprising 16 modules (1024 microphones) arranged in a honeycomb pattern. The resulting instrument offers a practical and scalable solution for applications that require a large number of simultaneous microphone measurements, such as beamforming technology for aeroacoustics applications. Full article

We present the results of applications of ATLAS2.0 to experimental data in this final part of our series of publications. ATLAS2.0 retrieves particle microphysical parameters from multiwavelength Raman and high-spectral-resolution lidar measurements of backscatter (β) coefficients at three wavelengths, i.e., λ = 355, 532, and 1064 nm, extinction (α) coefficients at two wavelengths, i.e., 355 and 532 nm, and particle linear depolarization ratios (PLDR, δ) at three wavelengths, i.e., 355, 532, and 1064 nm, so-called 3β + 2α + 3δ datasets. The explicit use of PLDRs is a novel feature compared to all previously developed lidar data retrieval algorithms. For the tests of ATLAS2.0, we use data that were taken with NASA Langley Research Center’s airborne high-spectral-resolution lidar 2 (HSRL-2). We show the results of two case studies. We compare the particle microphysical parameters and single-scattering albedo (SSA) retrieved with ATLAS2.0 to results obtained with the first version of ATLAS, our Tikhonov regularization algorithm (TiARA), and in situ observations carried out aboard an aircraft that followed the airborne HSRL-2 instrument. The solutions converge within the retrieval uncertainties of these techniques. The discrepancy between the measured and backcalculated, i.e., retrieved 3β + 2α + 3δ data on average stays below 10%. The difference between the retrieved and measured PLDRs is, on average, even less. This comparably good convergence of the optical datasets (experimental versus backcalculated) of both measurement cases can only be achieved if the investigated aerosol particles are analyzed on the basis of a sphere-spheroid mixture. Full article