Search Results (1,141)

Background: Poland was one of only 10 European countries listed teachers as a priority group for vaccination against COVID-19 among National Vaccination Program (NVP). The aim of this study was to analyse post-vaccination symptoms self-reported by teachers vaccinated under the national COVID-19 vaccination programme. Methods: The presented cross-sectional survey was conducted among teachers from all levels of education in public and non-public institutions, who received the SARS-CoV-2 virus vaccination campaign with the vaccine from AstraZeneca as part of the NVP. The survey was conducted using an original, self-designed questionnaire prepared for this study and distributed to teachers in the form of an online survey via email. Bayesian logistic and linear regression were used to estimate the relationship between predictors and dependent variables. Results: A total of 4622 teachers took part in the survey. Of this number, 3,908 teachers declared that they had taken the vaccine. (84.5%). In the study group, self-reported late post-vaccination reactions were very strongly [logBF > 3.4] associated with both gender and age. In contrast, self-reporting of serious late post-vaccination symptoms other than fever was very strongly associated only with gender. Only a small proportion of teachers (from 1.45% to 5.34% depending on age and gender) self-reported immediate post-vaccination reaction (up to 15 minutes after injection). Conclusions: Self-reporting of symptoms is a valuable tool for monitoring the effectiveness and safety of vaccinations and can also contribute to increased satisfaction with the vaccination process, especially when patients are made aware that post-vaccination symptoms are a natural sign of the body's immune response. Full article

Monitoring the condition of existing structures remains one of the most pressing challenges within the construction industry. Structural health monitoring (SHM) techniques have proven increasingly effective in this regard; however, maintaining and archiving complete lifecycle data for such structures remains costly. Data acquisition is particularly critical, as the SHM system relies upon this information to analyse and evaluate structural behaviour. Nonetheless, a range of challenges—such as environmental influences, sensor malfunction, and transmission failures—can lead to data corruption or loss. These issues compromise the reliability of the dataset, necessitating either data reconstruction or additional measurement campaigns, both of which are resource-intensive. This study proposes the use of a long short-term memory (LSTM) network to reconstruct missing or corrupted data. A complete dataset collected from an actual construction project is employed to train the network. Data loss scenarios are then simulated, including single-channel (loss from one sensor) and multi-channel (loss from multiple sensors) cases. The trained LSTM model is subsequently applied to reconstruct the missing data. A case study on a real bridge demonstrates that the reconstructed data show strong agreement with the original measurements in both the time and frequency domains. These findings indicate that the proposed approach has the potential to support engineers in conserving resources by reducing the need for costly and time-consuming additional measurement interventions. Full article

In July 2024, bluetongue virus serotype 3 (BTV-3) was first detected in southern Belgium, marking the onset of a major epidemic wave. This study documents, for the first time in Belgium, the ability of BTV-3 to cross the placental barrier in cattle, causing abortions and congenital central nervous system malformations. Abortion cases from January to December 2024 were monitored through the national abortion protocol, which mandates reporting and laboratory investigation (i.e., the year of emergence and the three previous years as the baseline data set). Among 5,751 reported abortions, 903 foetuses were tested by PCR, revealing widespread BTV-3 circulation. The first malformed PCR-positive foetus was recorded in mid-August, four weeks after a sharp increase in abortion rates. Lesions such as hydranencephaly were confirmed in PCR-positive foetuses, with a malformation rate of 32.24% in affected herds from weeks 36 to 52 (i.e., 22 times higher than in previous years). Gestational stage analysis indicated that congenital lesions were most frequent following infection between 70 and 130 days of gestation. Based on the observed gross lesions and the timing of abortion, it was deduced that the earliest maternal infections likely occurred in February–March 2024, implying low-level winter BTV-3 circulation before the official detection of the epidemic wave. These findings highlight the epidemiological value of systematic abortion monitoring as an early warning system tool and highlight the inadequacy of relying solely on clinical surveillance in adult ruminants. The abrupt emergence of BTV-3 across the territory without a gradual spatial spread underscores the need for anticipatory control strategies. Strategic, multivalent vaccination campaigns and enhanced abortion surveillance are critical to mitigate similar reproductive and economic losses in future bluetongue outbreaks. Full article

The Amazon hosts one of the richest diversities of mosquitoes in the family Culicidae, which are key both as arbovirus vectors and as environmental bioindicators. However, the state of Amapá remains poorly studied regarding its mosquito fauna. This study aimed to characterize the diversity and seasonal composition of Culicidae in the municipality of Mazagão, Eastern Amazon, within a rural landscape influenced by human activity and extreme climatic events. Three sampling campaigns were conducted between 2023 and 2024, covering rainy, intermediary, and dry periods. Mosquitoes were collected using Protected Human Attraction (PHA) and CDC light traps at both ground and canopy strata. A total of 3500 specimens were obtained, representing 38 species across 15 genera. The intermediary period yielded the highest abundance and richness, whereas the dry season presented very low diversity, probably because of severe drought and forest fires. Dominant species included Coquillettidia (Rhy.) venezuelensis, Cq. albicosta, and Mansonia titillans. There were significant differences in community diversity between dry and wetter periods, underscoring the strong role of seasonality in shaping mosquito populations. These findings represent the entomofaunistic survey of the region, contributing to biodiversity knowledge and highlighting potential public health risks, thus reinforcing the need for continuous entomological monitoring. Full article

This study aimed to assess the presence of microplastics (MPs) in an urban river (Gari, Lazio, Italy) using case-building caddisfly larvae as potential bioindicators. Results from the benthic faunal assemblage (STAR_ICMi = 0.797) revealed the presence of a rich and well-diversified macroinvertebrate community, thus reflecting a suitable ecological status. Of 279 caddisfly cases collected, 26% contained small plastic particles of various shapes and colours, while 542 MP items per m² were found in their substrate. Polyvinyl chloride (PVC) and Polyethylene terephthalate (PET) were the most abundant polymers identified by FT-IR analysis found in the Gari River, while the co-presence of lower-density polymers such as polystyrene (PS) and polyethylene (PE) or polypropylene (PP) reflects the contribution of multiple factors controlling MP deposition. The most abundant MPs were of secondary origin, as evidenced by the Carbonyl Index and the predominant shape. Despite the amounts of MPs found in the Gari River, their ecological and chemical status has been classified as “good” during the monitoring campaigns. These results highlight the need to further investigate the environmental impacts of MPs to implement water quality classification indices. 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

This paper presents a multivariable linear regression calibration method for non-dispersive infrared (NDIR) CO₂ sensors in a low-cost carbon monitoring network. We test this calibration method with data collected in a temperature- and pressure-controlled laboratory and evaluate the calibration method with long-term observational data collected at the Xinglong Atmospheric Background Observatory. Compared to data collected by a high-accuracy cavity ring-down spectrometer (Picarro), the results show that a multivariable linear regression approach incorporating temperature, pressure, and relative humidity can reduce the mean absolute bias from 5.218 ppm to 0.003 ppm, with root mean square errors (RMSE) within 2.1 ppm after calibration. For field observations, the RMSE is reduced from 8.315 ppm to 2.154 ppm, and the bias decreases from 39.170 ppm to 0.018 ppm. The calibrated data can effectively capture the diurnal variation of CO₂ mole fraction. The test of the number of reference data shows that about 10 days of co-located reference data are sufficient to obtain reliable measurements. Calibration windows taken from winter or summer provide better results, suggesting a strategy to optimize short-term calibration campaigns. Full article

Seawater intrusion into coastal river systems poses increasing challenges for freshwater availability and estuarine ecosystem integrity, especially under evolving climatic and anthropogenic pressures. This study presents a multidisciplinary investigation of marine intrusion dynamics within the Magra River estuary (Northwest Italy), integrating field monitoring, isotopic tracing (δ¹⁸O; δD), and multivariate statistical modeling. Over an 18-month period, 11 fixed stations were monitored across six seasonal campaigns, yielding a comprehensive dataset of water electrical conductivity (EC) and stable isotope measurements from fresh water to salty water. EC and oxygen isotopic ratios displayed strong spatial and temporal coherence (R² = 0.99), confirming their combined effectiveness in identifying intrusion patterns. The mass-balance model based on δ¹⁸O revealed that marine water fractions exceeded 50% in the lower estuary for up to eight months annually, reaching as far as 8.5 km inland during dry periods. Complementary δD measurements provided additional insight into water origin and fractionation processes, revealing a slight excess relative to the local meteoric water line (LMWL), indicative of evaporative enrichment during anomalously warm periods. Multivariate regression models (PLS, Ridge, LASSO, and Elastic Net) identified river discharge as the primary limiting factor of intrusion, while wind intensity emerged as a key promoting variable, particularly when aligned with the valley axis. Tidal effects were marginal under standard conditions, except during anomalous events such as tidal surges. The results demonstrate that marine intrusion is governed by complex and interacting environmental drivers. Combined isotopic and machine learning approaches can offer high-resolution insights for environmental monitoring, early-warning systems, and adaptive resource management under climate-change scenarios. Full article

This article presents an extensive experimental investigation of the dynamic characteristics of three-arch historical masonry bridges, using Operational Modal Analysis (OMA). The research thoroughly characterizes the dynamic behavior of four representative masonry bridges from the Apulia Region in Southern Italy through detailed experimental campaigns. These campaigns employed calibrated and optimally implemented accelerometric monitoring systems to acquire high-quality dynamic data under controlled excitation and environmental conditions. The selected bridges include the Santa Teresa Bridge in Bitonto, the Roman Bridge in Bovino, the Roman Bridge in Ascoli Satriano and a moderner road bridge on the Provincial Road SP123 in Troia; they span almost two millennia of construction history. The experimental framework incorporated several non-invasive excitation methods, including controlled vehicle passes, instrumented hammer impacts and ambient vibration tests, strategically chosen for optimal signal quality and heritage preservation. This investigation demonstrates the feasibility of capturing the dynamic behavior of these complex and specific historic structures through customized sensor configurations and various excitation methods. The resulting natural frequencies and mode shapes are accurate, robust, and reliable considering the extended data set used, and have allowed a rigorous seismic assessment. Eventually, this comprehensive data set establishes a fundamental basis for understanding and predicting the seismic response of several three-span masonry bridges to accurately identify their long-term resilience and effective conservation planning of these valuable and vulnerable heritage structures. In conclusion, the data comparison enabled the formulation of a predictive equation for the identification of the first natural frequency of bridges from geometric characteristics. Full article

Drought-induced forest mortality threatens biodiversity globally, particularly in arid, and semi-arid woodlands. The continual development of remote sensing approaches enables enhanced monitoring of forest health. Herein, we investigate the ability of a limited ground-truthed canopy dieback dataset and satellite image derived Normalised Difference Vegetation Index (NDVI) to make inferences about forest health as temporal and spatial extent from its collection increases. We used ground-truthed observations of relative canopy mortality from the Pinus edulis-Juniperus osteosperma woodlands of southeastern Utah, United States of America, collected after the 2017–2018 drought, and PlanetScope satellite imagery. Through assessing different modelling approaches, we found that NDVI is significantly associated with sitewide mean canopy dieback, with beta regression being the most optimal modelling framework due to the bounded nature of the variable relative canopy dieback. Model performance was further improved by incorporating the proportion of J. osteosperma as an interaction term, matching the reports of species-specific differential dieback. A time-series analysis revealed that NDVI retained its predictive power for our whole testing period; four years after the initial ground-truthing, thus enabling retrospective inference of defoliation and regreening. A spatial random forest model trained on our ground-truthed observations accurately predicted dieback across the broader landscape. These findings demonstrate that modest field campaigns combined with high-resolution satellite data can generate reliable, scalable insights into forest health, offering a cost-effective method for monitoring drought-impacted ecosystems under climate change. Full article

This work assesses sulfur dioxide (SO₂) emissions from two power plants in Baja California Sur, Mexico, using ground-based UV camera measurements and AERMOD dispersion modeling. Field campaigns conducted during 2022 in La Paz and Puerto San Carlos captured spatial and temporal variations in SO₂ slant column densities (SCDs) and fluxes, revealing higher emissions at the larger Punta Prieta (CTPP) thermoelectric power facility (mean flux: 1.13 kg s⁻¹) compared to the Agustín Olachea (CCI AO) internal combustion power plant (mean flux: 0.59 kg s⁻¹). The UV camera effectively monitored plume structure and dynamics, with error analyses indicating uncertainties of ~12% in flux estimates. AERMOD simulations showed ground-level SO₂ concentrations exceeding WHO and Mexican air quality standards near the plants, with localized exposure risks particularly for workers. The results underscore the substantial contribution of these facilities to regional SO₂ pollution and demonstrate the utility of combining remote sensing with modeling to assess industrial emissions and inform air quality management in sensitive regions. Full article

Coral reefs exposed to chronically turbid conditions challenge conventional assumptions about the optical environments required for reef persistence and productivity. This study investigates the utility of light absorption coefficients as indicators of optical water quality in Varadero Reef, an extreme coral ecosystem located in Cartagena Bay, Colombia. Field campaigns were conducted across three seasons (rainy, dry, and transitional) along a transect from fluvial to marine influence. Absorption coefficients at 440 nm were derived for particulate (a_p(440)) and chromophoric dissolved organic matter (a_CDOM(440)) to assess their contribution to underwater light attenuation. Average values across seasons show that a_p(440) reached 0.466 m⁻¹ in the rainy season (September 2021), 0.285 m⁻¹ in the dry season (February 2022), and 0.944 m⁻¹ in the transitional rainy season (June 2022). Meanwhile, mean a_CDOM(440) values were 0.368, 0.111, and 0.552 m⁻¹, respectively. These coefficients reflect the dominant influence of particulate absorption under turbid conditions and increasing a_CDOM(440) relevance during lower turbidity periods. Mean Secchi Disk Depth (ZSD) ranged from 0.6 m in the rainy season to 3.0 m in the dry season, aligning with variations in Kd PAR, which averaged 2.63 m⁻¹, 1.13 m⁻¹, and 1.08 m⁻¹ for the three campaigns. Chlorophyll-a concentrations at 1 m depth also varied significantly, with average values of 2.3, 2.7, and 6.2 μg L⁻¹, indicating phytoplankton biomass peaks associated with seasonal freshwater inputs. While particulate absorption limits light penetration, CDOM plays a potentially photoprotective role by attenuating UV radiation. The observed variability in these optical constituents reflects complex hydrodynamic and environmental gradients, providing insight into the mechanisms that sustain coral functionality under suboptimal light conditions. The absorption-based approach applied here, using standardized spectrophotometric methods, proved to be a reliable and reproducible tool for characterizing the spatial and temporal variability of IOPs. We propose integrating these indicators into monitoring frameworks as cost-effective, component-resolving tool for evaluating light regimes and ecological resilience in optically dynamic coastal systems. Full article

Atmospheric aerosols impact environmental quality and health, requiring accurate quantification. This study employed the PMeye scanning LiDAR, a UV system operating at 355 nm by Raymetrics S.A. for continuous, high-resolution monitoring in two campaigns: May 2024 (Vasilikos Power Station, Cyprus) and June 2024 (Port of Piraeus, Greece). Measurement days with dust presence were selected via AERONET-based aerosol classification and validated using a SKIRON model. A novel horizontal scanning method at 355 nm distinguished dust from anthropogenic emissions. Results showed higher pollution in Cyprus (~500 μg/m³) due to dust and chimney emissions, versus ~150 μg/m³ in Piraeus from dust and ship exhausts. Full article

The integration of Mechanical Ventilation with Heat Recovery (MVHR) systems into heritage buildings poses a series of challenges, largely attributable to architectural constraints and conservation requirements. The present study offers an operational campaign of an MVHR system installed during the energy retrofit of a protected residential heritage dwelling in Vitoria-Gasteiz, Spain. Although environmental monitoring was carried out throughout the year, representative spring, autumn and winter days of continuous operation were analysed, as the occupants frequently avoided using the system due to noise perception. This limitation highlights the importance of considering acoustic comfort and user acceptance as critical factors in the long-term viability of MVHR in heritage contexts. The system was assessed under real-life conditions using continuous environmental monitoring, with a focus on indoor air quality (IAQ), thermal efficiency, airflow balance, and pressure losses. Despite the acceptable mean apparent thermal effectiveness (0.74) and total useful efficiency (0.96), the system’s performance was found to be constrained by significant flow imbalance (up to 106%) and elevated pressure drops, which were attributed to the legacy of the duct geometry. The results obtained demonstrate IAQ improved overall, with mean CO₂ concentrations below ~650 ppm across the analysed dataset; however, daily means occasionally exceeded 900–1000 ppm during high-occupancy periods and in the absence of spatially distributed demand control. These exceedances are consistent with the measured outdoor baseline (~400–450 ppm) and reflect the need for post-commissioning balancing and room-level sensing to sustain Category II performance in heritage dwellings. This study provides empirical evidence on the limitations and opportunities of MVHR deployment in historic retrofits, thus informing future guidelines for sustainable interventions in heritage contexts. Full article

Indoor and outdoor air quality in school environments varies significantly with respect to particulate matter (PM) concentrations, carbon dioxide (CO₂) levels, and microclimatic conditions, all of which have a direct impact on the health, well-being, and performance of both students and staff. This study reports the findings of a monitoring campaign focused on PM₁₀ and PM_2.5 concentrations in two schools located in the urban area of Belgrade, Serbia. Measurements were carried out using low-cost sensor devices positioned in classrooms and in the surrounding outdoor environment. The PM concentration data were corrected through collocation with reference-grade automatic analyzers (Grimm EDM 180) from the National Air Quality Monitoring Network (NAQMN). During the winter season, the indoor-to-outdoor (I/O) concentration ratio for classrooms ranged between 0.7 and 0.8, indicating that indoor PM levels were generally lower than outdoor levels—likely a result of limited ventilation and reduced particle infiltration from outdoor sources. Conversely, in the summer season, the average I/O ratio typically exceeded 1.0 (ranging from 1.3 to 1.5), pointing to a more pronounced influence of indoor sources, such as occupant activities, resuspension of settled dust, and insufficient air exchange. Importantly, in over 60% of the measurements conducted during the summer period, indoor PM concentrations surpassed those outdoors, underscoring the critical need to address indoor emission sources and implement effective ventilation strategies, particularly during warmer months. Full article