Search Results (286)

Extreme climate events such as heatwaves are becoming more frequent and pose serious challenges in cities. Urban areas are particularly vulnerable because built surfaces absorb and release heat, while human activities generate additional greenhouse gases. This increases health risks, making it crucial to study population exposure to heat stress. This research focuses on Naples, Italy’s most densely populated city, where intense human activity and unique geomorphological conditions influence local temperatures. The presence of a Surface Urban Heat Island (SUHI) is assessed by deriving high-resolution Land Surface Temperature (LST) in a time series ranging from 2013 to 2023, processed with the Statistical Mono Window (SMW) algorithm in the Google Earth Engine (GEE) environment. SMW needs brightness temperature (Tb) extracted from a Landsat 8 (L8) Thermal InfraRed Sensor (TIRS), emissivity from Advanced Spaceborne and Thermal Emission Radiometer Global Emissivity Database (ASTERGED), and atmospheric correction coefficients from the National Center for Environmental Prediction and Atmospheric Research (NCEP/NCAR). A total of 64 nighttime images were processed and analyzed to assess long-term trends and identify the main heat islands in Naples. The hottest image was compared with population data, including demographic categories such as children, elderly people, and pregnant women. A risk index was calculated by combining temperature values, exposure levels, and the vulnerability of each group. Results identified three major heat islands, showing that risk is strongly linked to both population density and heat island distribution. Incorporating Local Climate Zone (LCZ) classification further highlighted the urban areas most prone to extreme heat based on morphology. Full article

Amidst the global energy structure transition and intensification of climate warming, the temperature control targets of the Paris Agreement and China’s “dual carbon” goals have driven the rapid development of building-integrated photovoltaics (BIPVs). However, solar cells in BIPV systems may produce exhaust gases that affect local urban air quality if exposed to extreme environmental conditions such as high temperatures during operation. In this study, eight air quality monitoring points were established around the BIPV system at Shenyang Jianzhu University as the experimental group, along with one additional air quality monitoring point serving as a control group. The concentrations of four air pollutant indicators (PM_2.5, PM₁₀, SO₂, and NO₂) were monitored continuously for 14 days. The weight of each indicator was calculated using the principle of information entropy, and the air quality evaluation grades were determined by combining the homomorphic inverse correlation function. The Entropy-Weighted Set Pair Analysis model was applied to evaluate the air quality of the BIPV system at Shenyang Jianzhu University. The results indicated that due to the high concentrations of SO₂ and NO₂, the Air Quality Index (AQI) grade at Shenyang Jianzhu University was classified as “light pollution.” Corresponding recommendations were proposed to promote the sustainable development of urban BIPV. Simultaneously, the evaluation results of the Entropy-Weighted Set Pair Analysis model were similar to those obtained using other methods, demonstrating the feasibility of this evaluation model for assessing the impact on air quality. Full article

Under conditions of constant total nutrient input, the regulatory mechanisms of soil organic carbon components under gradient replacement ratios of organic materials for chemical fertilizers have not yet been systematically elucidated. This study took “Longjiao No. 2” as the research object, setting up CK (no fertilization), T0 (100% chemical fertilizer application), T20 (80% chemical fertilizer + 20% vegetable waste organic fertilizer), T40 (60% chemical fertilizer + 40% vegetable waste organic fertilizer), T60 (40% chemical fertilizer + 60% vegetable waste organic fertilizer), and T80 (20% chemical fertilizer + 80% vegetable waste organic fertilizer) as treatment groups. This study investigated the changes in soil organic carbon and organic carbon component content at different crop growth stages (seedling stage, budding stage, flowering and fruit-setting stage, and fruiting stage) under different organic matter replacement methods of chemical fertilizer treatments. It analyzed the response of greenhouse gas emissions to different fertilization conditions and assessed the changes in soil carbon pool management indices, as well as the interaction mechanisms between soil nutrients, carbon components, and greenhouse gases. The results showed that the combined application of chemical fertilizer and vegetable residue organic fertilizer significantly affected soil carbon pool dynamics and greenhouse gas emissions: the T60 treatment was the most effective, increasing soil organic carbon components at all growth stages. The soil carbon pool management index (CPMI) during the seedling stage was 21.3% higher than that of the T0 treatment, and the stable carbon pool components (MOC and POC) during the fruiting stage were 18.7–22.4% higher. This application mode reduced the global warming potential (GWP) by 25.6% compared to the T0 treatment throughout the entire growth stage. The CO₂ emissions peaked 19.3% lower during the flowering and fruit-setting stage. Applying organic fertilizer and chemical fertilizer in a 6:4 ratio balanced carbon turnover and sequestration while achieving the highest yield, providing a basis for low-carbon fertilization and increased production in semi-arid regions’ protected agriculture. Full article

In view of the bottleneck problems of serious spectral peak cross-interference, redundant data dimensions, and inefficient traditional dimensionality reduction methods in the infrared spectral analysis of mixed gases, this paper studies a joint dimensionality reduction strategy combining stacked self encoder (SAE) and partial least squares (PLS) and constructs an XGBoost regression model for quantitative detection. The experimental data are from the real infrared spectrum dataset of the National Institute of Standards and Technology (NIST) database, covering key industrial gases such as CO, CH₄, etc. Compared with the traditional principal component analysis (PCA), which relies on the variance contribution rate and leads to dimensional redundancy, and the calculation efficiency of dimension parameters that need to be cross-verified for PLS dimension reduction alone, the SAE-PLS joint strategy has two advantages: first, the optimal dimension reduction is automatically determined by SAE’s nonlinear compression mechanism, which effectively overcomes the limitations of linear methods in spectral nonlinear feature extraction; and second, the feature selection is carried out by combining the variable importance projection index of PLS. Compared with SAE, the compression efficiency is significantly improved. The XGBoost model was selected because of its adaptability to high-dimensional sparse data. Its regularization term and feature importance weighting mechanism can suppress the interference of spectral noise. The experimental results show that the mean square error (MSE) on the test set is reduced to 0.012% (71.4% lower than that of random forest), and the correlation coefficient (R²) is 0.987. By integrating deep feature optimization and ensemble learning, this method provides a new solution with high efficiency and high precision for industrial process gas monitoring. Full article

Understanding the trends and drivers of greenhouse gases (GHGs) is vital to making effective climate mitigation strategies and benefiting human health. In this study, we investigate carbon dioxide (CO₂) trends in the top three emitting states in the U.S. (i.e., Texas, California, and Florida) using column-averaged CO₂ concentrations (XCO₂) from the Greenhouse Gases Observing Satellite (GOSAT) from 2010 to 2022. Annual XCO₂ enhancements are derived by removing regional background values (XCO_{2, enhancement}), and their interannual changes (ΔXCO_{2, enhancement}) are analyzed against key influencing factors, including population, gross domestic product (GDP), nonrenewable and renewable energy consumption, and normalized vegetation difference index (NDVI). Overall, interannual changes in socioeconomic factors, particularly GDP and energy consumption, are more strongly correlated with ΔXCO_{2, enhancement} in Florida. In contrast, NDVI and state-specific environmental policies appear to play a more influential role in shaping XCO₂ trends in California and Texas. These differences underscore the importance of regionally tailored approaches to emissions monitoring and mitigation. Although renewable energy use is increasing, CO₂ trends remain primarily influenced by nonrenewable sources, limiting progress toward atmospheric CO₂ reduction. Full article

The plasma reactor and cylindrical-type electrostatic precipitator (PRESP), combined operation in one device, made in the metallic chimney of low-thermal power boilers (up to 50 kW) that burn wood, can be used in home applications. The discharge electrode is stretched and supported by two groups of medium-voltage insulators. The sensitive elements of PRESP are medium-voltage insulators. This article analyses the design, use, and effect of dirty gases on the medium-voltage insulators that support the discharge electrode under real operating conditions for a PRESP installed in a 20 kW thermal power boiler that burns wood (there are no studies on the performance of PRESP). The electrical properties of the medium-voltage insulators (isolation resistance, dielectric absorption ratio, and polarisation index) and the chemical analysis of the dust layer deposited on the medium-voltage insulators are analysed. Of the two types of insulators analysed, a longer length of the electrical insulators determines a safer and better operation of PRESP. After a period of operation of the PRESP, the insulation resistance decreases by more than 10 times. The polarisation index (values greater than 1.1–1.2) provides better information (compared to the dielectric absorption ratio) on the insulation quality. Full article

The production of gas and condensate from liquid-rich shale reservoirs, particularly within heterogeneous lacustrine systems, remains a critical challenge in unconventional hydrocarbon exploration due to intricate multiphase hydrocarbon partitioning, including gases (C₁–C₂), volatile liquids (C₃–C₇), and heavier liquids (C₇₊). This study investigates a 120-meter-thick interval dominated by lacustrine deposits from the Lower Cretaceous Shahezi Formation (K₁sh) in the Songliao Basin. This interval, characterized by high clay mineral content and silicate–pyrite laminations, was examined to identify the factors controlling hybrid shale gas condensate systems. We proposed the Hybrid Shale Condensate Index (HSCI), defined as the molar ratios of (C₁–C₇)/C₇₊, to categorize fluid phases and address shortcomings in traditional GOR/API ratios. Over 1000 samples were treated by geochemical pyrolysis logging, X-ray fluorescence (XRF) spectrum element logging, SEM-based automated mineralogy, and in situ gas desorption, revealing four primary controls: (1) Thermal maturity thresholds. Mature to highly mature shales exhibit peak condensate production and the highest total gas content (TGC), with maximum gaseous and liquid hydrocarbons at T_max = 490 °C. (2) Lithofacies assemblage. Argillaceous shales rich in mixed carbonate and clay minerals exhibit an intergranular porosity of 4.8 ± 1.2% and store 83 ± 7% of gas in intercrystalline pore spaces. (3) Paleoenvironmental settings. Conditions such as humid climate, saline water geochemistry, anoxic bottom waters, and significant input of volcanic materials promoted organic carbon accumulation (TOC reaching up to 5.2 wt%) and the preservation of organic-rich lamination. (4) Laminae and fracture systems. Silicate laminae account for 78% of total pore space, and pyrite laminations form interconnected pore networks conducive to gas storage. These findings delineate the “sweet spots” for unconventional hydrocarbon reservoirs, thereby enhancing exploration for gas condensate in lacustrine shale systems. Full article

Dissolved gas analysis (DGA) is one of the transformer testing methods that has been widely used for a long time because it does not require the transformer to be offline for testing. The inspection can be conducted while the transformer is operating normally, and it is cost-effective. In research on fault severity, thermodynamic theory has been applied to find the energy index of the hydrocarbon gases generated by faults, ${\mathrm{CH}}_4$, ${\mathrm{C}}_2{\mathrm{H}}_6$, ${\mathrm{C}}_2{\mathrm{H}}_4$ and ${\mathrm{C}}_2{\mathrm{H}}_2$, referred to as the Normalised Energy Intensity (NEI). This study examines the application of the Positive Cumulative Sum of Difference (CUSUM) method to hydrocarbon NEI and carbon dioxide NEI for fault severity assessment. The study demonstrates the effectiveness of this approach by means of case studies on the basis of DGA results from two steel plants. In the case of NEI from hydrocarbon gases (${\mathrm{NEI}}_{\mathrm{HC}}$), the positive CUSUM is compared with the NEI, the NEI score, and the cumulative NEI. In the case of NEI from carbon oxide gases (${\mathrm{NEI}}_{\mathrm{CO}}$), Positive CUSUM is compared with NEI and the ratio of ${\mathrm{CO}}_2$ to $\mathrm{CO}$. It was found that Positive CUSUM for ${\mathrm{NEI}}_{\mathrm{HC}}$ is a much better indicator of the severity of defects than the NEI, the NEI score, and the cumulative NEI. In contrast, Positive CUSUM for ${\mathrm{NEI}}_{\mathrm{CO}}$ gave excessively high values. However, combining NEI with the ${\mathrm{CO}}_2$/$\mathrm{CO}$ ratio gave better monitoring results. Therefore, from an online DGA perspective, Positive CUSUM can be used to effectively monitor fault severity. Full article

Balanced homodyne detection, which offers advantages that include low noise and strong anti-interference capabilities, is commonly used as a detection method in quantum metrology. In this article, we propose application of the balanced homodyne detection technique to the gas sensing and measurement field. By constructing a Mach–Zehnder interferometer based on balanced homodyne detection, we realize high-precision measurement of the refractive index of air. The device exhibits interference efficiency of 99% and a common-mode rejection ratio of 40 dB, thus enabling dynamic monitoring of optical phase changes. Under conditions that include a stabilized temperature of 25 °C, atmospheric pressure of 100.08 kPa, and relative humidity of 30%, the refractive index of air was measured experimentally to be $n=1.0002711$ with a measured minimum standard deviation of $1\times {10}^{-7}$. The proposed technique provides high measurement sensitivity and stability, and it also offers the advantage of noncontact measurement. Furthermore, the proposed scheme is applicable to both measurement and dynamic sensing of the refractive indices of gases, along with sensing and measurement of transparent liquids and biological samples. Full article

Livestock production systems can negatively affect soil structure, resulting in negative changes in physical–hydraulic properties, compromising soil functioning and productivity. This research aimed to evaluate the effects of rotational silvopastoral systems on soil physical–hydraulic functioning in their second year of implementation. The study was performed under Oxisol soil with a loamy sand texture in Southeast Brazil. We considered four grazing systems: an intensive silvopastoral system with Panicum maximum in consortium with Leucaena leucocephala (ISPS + L), an intensive silvopastoral system with Panicum maximum in consortium with Tithonia diversifolia (ISPS + T), an silvopastoral system with Panicum maximum (SPS) with tree row (TRs), and open pasture under a rotational grazing system with Panicum maximum (OP). The treatments ISPS + L, ISPS + T, and SPS had tree rows (TRs) every 20 m composed of Khaya ivorenses, Leucaena leucocephala, Eucalyptus urograndis, Acacia mangium, and Gliricidia sepium. Nine physical–hydraulic indicators were evaluated in the first 0.40 m of depth: bulk density (Bd), total porosity (TP), macroporosity (MaP), microporosity (MiP), field capacity (FC), permanent wilting point (PWP), available water content (AWC), total soil aeration capacity (ACt), and S-index. The soil physical–hydraulic properties were sensitive to the effects of the livestock systems. The use of silvopastoral systems in consortium with grass (ISPS + L and ISPS + T) allowed for better soil water retention, resulting in higher FC and AWC than the OP, SPS, and TR. The indicators Bd, ACt, MaP, FC, MiP, and S-index presented the greatest variance; however, FC, ACt, MaP, and MiP enabled the greatest differentiation among systems. Therefore, these properties are important in studies on soil physical quality since they provide information about the soil porous status and its ability to retain water and exchange soil air and gases. Therefore, enhancing the physical–hydraulic attributes of the soil in silvopastoral systems with shrub species is crucial for ensuring long-term productive sustainability and strengthening environmental resilience against future climate challenges. Full article

Recent research has focused on developing environmentally friendly flame-retardant coatings to improve the fire resistance of wood. In this study, phytic acid–guanazole (PG), a dual-functional compound synthesized through an ionic reaction between phytic acid and guanazole, was added to KH550-modified urea–formaldehyde resin (KUF) as both a curing agent and flame retardant. The $-{\mathrm{PO}}_4^{3-}$ groups from phytic acid act as an acid source to accelerate char formation during combustion, while the −NH₂ groups introduced by guanazole release non-combustible gases to dilute oxygen in the air, synergistically enhancing flame retardancy. Additionally, the hygroscopic $-{\mathrm{PO}}_4^{3-}$ groups absorb free water in the resin, reducing the curing temperature and accelerating coating solidification. The KH550 coupling agent improves compatibility between KUF and PG while introducing silicon, which forms SiO₂ during combustion to strengthen the char layer and further enhance flame resistance. Evaluations showed that PG outperforms conventional tannic acid (TA) in curing efficiency and fire resistance. Comprehensive analyses, including Differential Scanning Calorimetry (DSC), Limiting Oxygen Index (LOI), vertical flame tests, and cone calorimetry, confirmed PG’s dual functionality. Scanning Electron Microscope (SEM) and Raman spectroscopy revealed that PG-modified coatings form denser post-combustion char layers, directly linked to improved fire resistance. As a multifunctional additive, PG eliminates the need for separate curing agents and utilizes bio-based phytic acid, offering cost-effective and sustainable advantages for industrial applications. Full article

Background/Objectives: Myotonic dystrophy type 1 (DM1) is a rare neuromuscular disorder characterized by respiratory dysfunction that significantly impacts quality of life and longevity. This study aimed to explore the outcomes of pulmonary function tests and sleep-disordered breathing (SDB) workups in children with DM1 and to identify the factors contributing to SDB. Methods: A retrospective study examined patients’ medical records, including genetic analyses, clinical characteristics, and noninvasive pulmonary function testing (PFT), when possible. The Pediatric Sleep Questionnaire (PSQ), arterial blood gases, polygraphy, and overnight transcutaneous capnometry (PtcCO₂) were used to assess SDB. Results: The size of CTG expansion in the DMPK gene directly correlated with the severity of respiratory complications and the need for early tracheostomy tube insertion in 7/20 (35%) patients. A total of 13/20 (65%) children were available for respiratory evaluation during spontaneous breathing. While moderate/severe obstructive sleep apnea syndrome (OSAS) and hypoventilation were confirmed in 4/13 (31%) children, none of the patients had mixed or dominantly central sleep apnea syndrome. There was no correlation between apnea–hypopnea index (AHI) or PtcCO₂ and the presence of SDB-related symptoms or the PSQ score. Although a significant correlation between AHI and PtcCO₂ was not confirmed (p = 0.447), the oxygen desaturation index directly correlated with PtcCO₂ (p = 0.014). Conclusions: While SDB symptoms in children with DM1 may not fully correlate with observed respiratory events or impaired gas exchange during sleep, a comprehensive screening for SDB should be considered for all patients with DM1. Further research into disease-specific recommendations encompassing the standardization of PFT, as well as overnight polygraphic and capnometry recordings, could help to guide timely, personalized treatment. Full article

Extreme weather events are increasing the frequency and intensity of forest fires, generating serious environmental and socio-economic impacts. These fires cause soil loss through erosion, organic matter depletion, increased surface runoff and the release of greenhouse gases, intensifying climate change. They also affect biodiversity, terrestrial and aquatic ecosystems, and soil quality. The assessment of forest fires by remote sensing, such as the use of the Normalised Difference Vegetation Index (NDVI), allows rapid analysis of damaged areas, monitoring of vegetation changes and the design of restoration strategies. On the other hand, models such as RUSLE are key tools for calculating soil erosion and planning conservation measures. A study of the impacts on soils and vegetation in the south of Salamanca, where one of the worst fires in the province took place in 2022, has been carried out using RUSLE and NDVI models, respectively. The study confirms that fires significantly affect soil properties, increase erosion and hinder vegetation recovery, highlighting the need for effective restoration strategies. It was observed that erosion intensifies after fires (the maximum rate of soil loss before is 1551.85 t/ha/year, while after it is 4899.42 t/ha/year) especially in areas with steeper slopes, which increases soil vulnerability, according to the RUSLE model. The NDVI showed a decrease in vegetation recovery in the most affected areas (with a maximum value of 0.3085 after the event and 0.4677 before), indicating a slow regeneration process. The generation of detailed cartographies is essential to identify critical areas and prioritise conservation actions. Furthermore, the study highlights the importance of implementing restoration measures, designing sustainable agricultural strategies and developing environmental policies focused on the mitigation of land degradation and the recovery of fire-affected ecosystems. Full article

Mosses are widely used as biomonitors of atmospheric nitrogen (N) and sulfur (S) deposition due to their broad distribution, ease of sampling, and capacity to trap and accumulate atmospheric particles. However, since 2000, S emissions have decreased by more than 80% across Europe, and N oxides by 40–50%. This study evaluated whether moss remains effective for monitoring atmospheric N and S deposition after decades of emission reductions. This assessment was conducted at 33 rural sites in Tuscany, Central Italy, a region characterized by relatively low levels of N and S deposition. The content of N and S in moss were compared with the air concentrations (gases and particles) and wet and dry deposition of N and S from the Cooperative Programme for Monitoring and Evaluation of Long-range Transmission of Air Pollutants in Europe (EMEP) model and an air pollution index derived from trace element concentrations. The average N content of moss (1.15 ± 0.42%) was an order of magnitude greater than that of S (0.11 ± 0.02%), reflecting the dominance of N deposition. Nevertheless, N and S in moss were strongly correlated (r_s = 0.55), suggesting shared sources. Further, N showed a strong correlation with the dry deposition of oxidized N (r_s = 0.53), while S was strongly correlated with the wet deposition of S oxides (r_s = 0.53) and magnetic susceptibility (r_s = 0.69). Overall, our findings confirm that mosses remain effective biomonitors of N and S deposition and can provide reliable spatial and temporal monitoring, especially as the traditional monitoring networks decline. Full article

This study investigates the mechanical and optical characteristics of silicon nitride thin films deposited with PECVD at 80 °C for tunable silicon-rich SiN_x-SiO_y-based MEMS optical cavities. Varying the deposition parameters using SiH₄ and N₂ as precursor gases for silicon-rich SiN_x thin films allows us to tune the refractive index to a value as high as 2.40 ± 0.013 at an extinction coefficient of only 0.008, an extremely low surface roughness of only 0.26 nm, and a compressive stress of about 150 MPa. We deposited 6.5-layer pairs of silicon-rich SiN_x/SiO_y-distributed Bragg reflector (DBR) micro-electro-mechanical system (MEMS) mirror that covers the whole 1300 and 1550 nm range. Cavity architectures of 6.5 top and 6 bottom layer-pairs were fabricated in the clean room providing a variety of cavity lengths between 0.615 µm and 2.85 µm. These lengths were then simulated in order to estimate the Young’s Modulus of silicon-rich SiN_x, obtaining values from 56 to 92 GPa. One of the designs was characterised electro-thermally providing a tuning range of at least 86.7 nm centred at 1585 nm. The tunable filters are well suitable for implementation as tuning element in lasers for optical coherence tomography. Full article