Search Results (5,426)

Liquefied natural gas (LNG) container trucks are regarded as clean energy vehicles with the potential to reduce air pollution. However, their CO₂ emissions remain relatively high and are not yet well understood. In this study, the actual CO₂ emissions of LNG container trucks in Shanghai were measured using a portable emissions measurement system (PEMS). This study quantitatively analyzed the relationship between traffic congestion levels and CO₂ emissions on elevated roadways, providing new insights into the impact of urban traffic conditions. In addition, distinct emission patterns were revealed under different uphill, downhill, and level road conditions, highlighting the substantial effects of roadway geometry on vehicle carbon emissions. Based on these findings, engine-related factors were identified as the dominant contributors, explaining 74% of the emission variance, while road slope analysis showed that uphill driving increased emissions by 13.41% compared with flat roads, whereas downhill driving reduced them by 76.22%. Finally, an efficient carbon emission prediction model for LNG container trucks was developed using machine learning methods. This study enriches the understanding of carbon emissions from LNG container trucks and provides theoretical support for their future applications in sustainable freight transportation. Full article

Sustainable landslide risk management is critical for achieving resilient communities and supporting the United Nations Sustainable Development Goals, particularly in vulnerable mountainous regions of developing countries. This study presents experimental evidence supporting dimensionless analysis approaches for characterizing granular flow behavior, contributing to cost-effective landslide hazard assessment frameworks. We designed a 4 m experimental flume to investigate the influence of particle characteristics on flow velocity and runout distance, using two materials with contrasting shapes but similar density (~460 kg/m³) and nominal size (~5 mm): uniform crystal beads (φ = 25.2°) and non-uniform crushed granite particles (φ = 36.9°). High-resolution imaging (30 fps, 2336 × 1752 pixels) captured 30 flow experiments from initiation to deposition. Results demonstrate significant differences in flow behavior: crystal beads achieved 50% longer runout distances and 46% higher maximum velocities (380 cm/s vs. 260 cm/s) compared to granite particles. The Savage number ($N_{sav}$) effectively captured fundamental flow-regime differences, with granite particles exhibiting values seven times lower than crystal beads (3.69 vs. 23.91, p < 0.001), indicating greater frictional energy dissipation relative to collisional energy transfer. The Bagnold number confirmed inertially dominated regimes ($N_{Bag}$ > 10⁶) with negligible viscous effects in both materials. These findings demonstrate that accessible material characterization using standard triaxial testing and dimensionless analysis can significantly improve landslide runout prediction accuracy, supporting evidence-based decision-making for sustainable territorial planning and community protection. This research supports the development of practical risk assessment methodologies implementable in resource-limited settings, promoting sustainable development through improved natural hazard management. Full article

Despite heightened sustainability agendas, green purchase behavior (GPB) remains uneven. This study develops a motive–mechanism account that distinguishes personal (self-regarding) and civic (other-regarding) motivation and specifies how these parallel motives operate through a dual-barrier/relational-enabler layer. Using survey data from urban consumers in China (n = 420) and structural equation modeling with bias-corrected bootstrapped indirect effects, we test a dual-path mediation model in which perceived cost and perceived risk function as inhibitory mechanisms, while social capital operates as a relational amplifier. Results indicate that both motivations positively predict GPB; cost and risk suppress GPB; and social capital facilitates GPB. Indirect effects via all three mediators are significant, yet direct paths from both motivations to GPB remain, indicating partial mediation. Two regularities are noteworthy: a pattern of motivational symmetry, whereby personal and civic motives exhibit comparable direct associations with behavior, and an attenuated risk pathway relative to cost, suggesting affordability—more than uncertainty—constrains adoption in the observed market context. Theoretically, the findings integrate TPB–VBN insights into a dual-motive, dual-barrier, relational-enabler framework that positions social capital as a conversion-efficiency multiplier and clarifies scope conditions under which each pathway dominates. Practically, the results prioritize interventions that lower out-of-pocket costs, reduce the salience of uncertainty, and leverage community trust and peer visibility. Full article

This paper assesses the green tourism readiness of six EU member states from Central and Eastern Europe—Slovenia, Croatia, Slovakia, Hungary, Bulgaria, and Romania—using a hybrid multi-criteria decision-making (MCDM) model. As tourism sectors face increasing pressure to align with the European Green Deal and sustainability goals, integrating green skills, environmental protection, and institutional governance becomes essential. The study applies a three-step framework that combines the Analytic Hierarchy Process (AHP), Best-Worst Method (BWM), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to evaluate national performance across four criteria: natural capital, rural infrastructure, governance readiness, and green skills in vocational education and training (VET). Results show that environmental sustainability and governance are the dominant enablers of green tourism transformation, with Slovenia and Croatia leading in overall readiness. Although green skills have a lower relative weight, their integration significantly strengthens performance in more advanced systems. The hybrid model demonstrated methodological robustness through sensitivity and consistency checks. This research contributes to both methodological innovation and evidence-based policymaking by offering a replicable tool for evaluating sustainable tourism development in transition economies. It provides actionable insights for aligning education, tourism, and environmental policy within the broader EU green transition framework. Full article

An experimental and theoretical investigation of the reaction between chlorine atoms and propane/deuterated propane (C₃H₈/C₃D₈) was performed. The experimental work aimed to determine absolute and site-specific rate constants for hydrogen and deuterium abstraction in the Cl + C₃H₈/C₃D₈ system. Measurements were conducted using the relative rate method at three temperatures between 298 and 387 K. Total rate constants for H/D abstraction by chlorine, as well as individual rate constants for abstraction from primary and secondary carbon sites, were obtained. The kinetic data for H abstraction agree well with previously reported literature values, confirming the reliability of the experimental approach. Notably, rate constants for the C₃D₈ + Cl reaction were determined for the first time, and the consistency of these results supports the reliability of the newly derived kinetic parameters. In the theoretical part of the study, hydrogen/deuterium abstraction from propane by atomic chlorine was analyzed within an atmospheric-chemistry context to clarify temperature dependence and site selectivity. Stationary points (SC, TS, PC, reactants, products) were optimized at MP2/aug-cc-pVDZ and verified by harmonic frequencies and intrinsic reaction-coordinate analyses. Eyring transition-state theory yielded 298–550 K rate constants with activation free energies referenced to SC. Our calculations indicate entrance-channel complex formation and effectively barrierless progress for most pathways; a small barrier appears only for RD1′. L-parameter evaluation classifies TS2 as reactant-like, and branching ratios identify –CH₂– abstraction (RX2) as dominant. These findings align with the experimental data. Full article

Landslide disasters pose severe threats to mountainous regions, where accurate monitoring and scientific prediction are crucial for early warning and risk mitigation. This study addresses this challenge by focusing on the Outang Landslide, a representative large-scale bank slope in the Three Gorges Reservoir area known for its significant deformation responses to rainfall and reservoir-level fluctuations. The landslide’s behavior, characterized by notable hysteresis and nonlinear trends, poses a significant challenge to accurate prediction. To address this, we derived high-precision time-series deformation data by applying atmosphere-corrected Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) to Sentinel-1A imagery, with validation from GNSS measurements. A systematic analysis was then conducted to uncover the correlation, hysteresis, and spatial heterogeneity between landslide deformation and key influencing variables (rainfall, water level, temperature). Furthermore, we proposed a Spatio-Temporal Enhanced Convolutional Neural Network (STE-CNN), which innovatively converts influencing variables into grayscale images to enhance spatial feature extraction, thereby improving prediction accuracy. The results indicate that: (1) From June 2022 to March 2024, the landslide showed an overall downward displacement trend, with maximum settlement and uplift rates of −49.34 mm/a and 21.77 mm/a, respectively; (2) Deformation exhibited significant correlation, hysteresis, and spatial variability with environmental factors, with dominant variables shifting across seasons—leading to intensified movement in flood seasons and relative stability in dry seasons; (3) The improved STE-CNN outperforms typical prediction models in forecasting landslide deformation.This study presents an integrated methodology that combines InSAR monitoring, multi-factor mechanistic analysis, and deep learning, offering a reliable solution for landslide early warning and risk management. Full article

Mesozooplankton are pivotal for Black Sea food webs, yet they are highly vulnerable to hydrographic variability, eutrophication, and human pressures. This study analysed mesozooplankton dynamics along the Romanian coast (2013–2020) across three sectors (north, central, and south) and two distinct periods (cold and warm seasons), integrating Abundance–Biomass Comparison (ABC) curves with Fuzzy Cognitive Mapping (FCM). Results revealed a clear disturbance gradient: the Danube-influenced north supported high abundances of small-bodied taxa; the central sector maintained the most resilient and functionally diverse assemblages; and the southern sector showed chronic degradation with Noctiluca scintillans dominance. ABC curves quantified disturbance, with curve convergence in the north and near overlap in the south during summer, while FCM highlighted network simplification and reduced functional redundancy. Climate scenario simulations projected further declines in cladocerans and meroplankton under warming and freshening, whereas copepods showed relative resilience. Collectively, the findings demonstrate progressive simplification of mesozooplankton and declining energy transfer efficiency, underscoring the need to integrate zooplankton-based indicators into Black Sea monitoring and management frameworks. Full article

The soil–water retention curve (SWRC) is a fundamental property that governs the hydraulic and mechanical behavior of unsaturated soils. Laboratory SWRC determination remains time-consuming and costly, promoting indirect estimation methods. However, existing methods often oversimplify the pore structure and particle arrangement of soils and neglect the effect of capillary menisci, resulting in discrepancies from natural soil behavior. This study proposes a novel method to estimate the SWRC of coarse-grained soils based on grain size distribution (GSD) and relative density. In the proposed method, soil particles are idealized as spheres in a two-dimensional (2D) plane, and the packing structure is modeled using representative quadrilaterals composed of four poly-disperse particles. The GSD is employed to calculate the probability of different particle sizes occupying the corners of the quadrilateral elements, while the relative density defines their geometric configuration. The water retention behavior is then evaluated using the geometric relationships between the air–water interface and particle radii. The predicted SWRCs are in good agreement with experimental data, indicating that the method can effectively capture the water retention characteristics of coarse-grained soils governed by capillary effects. The method’s applicability is limited to coarse-grained soils and excludes clayey soils where adsorbed water dominates retention mechanisms. Full article

Background: Hereditary hyperferritinemia-cataract syndrome (HHCS) is a rare autosomal dominant disorder characterized by persistently elevated serum ferritin and early-onset bilateral cataracts in the absence of systemic iron overload. It is caused by pathogenic variants in the iron-responsive element (IRE) of the FTL gene, leading to dysregulated L-ferritin synthesis. Methods: We evaluated a 12-year-old Czech girl with markedly elevated serum ferritin identified incidentally during workup for abdominal pain. Clinical assessment included biochemical, radiological, ophthalmological, and genetic testing of the proband and available family members. Results: Magnetic resonance imaging excluded systemic iron overload, while ophthalmological evaluation revealed bilateral cataracts. Family history indicated multiple affected relatives across three generations. Genetic testing confirmed a heterozygous FTL c.-168G>C variant. Additional screening for common HFE variants revealed heterozygous H63D in several family members, with no impact on ferritin or hepcidin levels. Beyond this case, we provide a comprehensive review of HHCS, including molecular mechanisms, an updated overview of reported FTL mutations, and ophthalmological features that distinguish HHCS cataracts from other congenital cataracts. Conclusions: This report underscores the translational relevance of combining molecular diagnostics, clinical evaluation, and family screening to improve recognition and management of HHCS, and to prevent misdiagnosis and unnecessary iron-depletion therapy. Full article

This study introduces a health-aware fuzzy logic (FL) energy management strategy (EMS) for fuel cell electric commercial vehicles (FCECVs) that aimed to improve energy efficiency and extending fuel cell system (FCS) lifespan. The FL-based EMS was developed using vehicle power demand and battery state of charge (SOC) as inputs, with the FCS power change rate as the output, aiming to mitigate degradation induced by abrupt load transitions. A multi-objective optimization framework was established to optimize the fuzzy logic controller (FLC) parameters, achieving a balanced trade-off between fuel economy and FCS longevity. The non-dominated sorting genetic algorithm-II (NSGA-II) was utilized for optimization across various driving cycles, with average Pareto-optimal solutions employed for real-time application. Performance evaluation under standard and stochastic driving cycles benchmarked the proposed strategy against dynamic programming (DP), charge-depletion charge-sustaining (CD-CS), conventional FL strategies, and a non-optimized baseline. Results demonstrated an approximately $38\%$ reduction in hydrogen consumption (HC) relative to CD-CS and over $75\%$ improvement in degradation mitigation, with performance superior to that of DP. Although the strategy exhibits an average $17.39\%$ increase in computation time compared to CD-CS, the average single-step computation time is only $2.1$ ms, confirming its practical feasibility for real-time applications. Full article

Despite extensive work on FeOCl-based photocatalysts, few studies have explored rare-earth (Ce) doping to simultaneously tune bandgap, suppress charge recombination, and enhance visible light-driven persulfate (PS) activation for the degradation of emerging contaminants. This study synthesized FeOCl/Ce composite photocatalysts via a partial pyrolysis method and systematically characterized their physicochemical properties. The results show that Ce doping significantly lowers the bandgap energy of the photocatalyst, enhances its visible light absorption ability, and effectively suppresses the recombination of photogenerated electron–hole pairs, thereby markedly improving photocatalytic performance under visible light. Analyses including XRD, EDS, XPS, and FT-IR confirm that Ce is incorporated into the FeOCl matrix and modulates the radial growth behavior of FeOCl without altering its intrinsic crystal structure. Morphological observations reveal that FeOCl/Ce exhibits a uniform nanosheet layered structure, with larger particles formed by the aggregation of smaller nanosheets. The nitrogen adsorption–desorption isotherm of FeOCl/Ce shows characteristics of Type IV with a relatively small BET surface area. The broadened optical absorption edge of FeOCl/Ce and the results of PL spectra and I-T curves further confirm its enhanced visible light absorption capacity and reduced electron–hole recombination compared to pure FeOCl. At an initial caffeine (CAF) concentration of 10 μM, FeOCl/Ce dose of 0.5 g/L, PS concentration of 1 mM, and initial pH of 5.06, the FeOCl/Ce-catalyzed PS system under visible light irradiation can degrade 91.2% of CAF within 30 min. An acidic environment is more favorable for CAF degradation, while the presence of SO₄²⁻, Cl⁻, and NO₃⁻ inhibits the process performance to varying degrees, possibly due to competitive adsorption on the photocatalyst surface or quenching of reactive species. Cyclic stability tests show that FeOCl/Ce maintains good catalytic performance over multiple runs. Mechanistic analysis indicates that ^•OH and holes are the dominant reactive species for CAF degradation, while PS mainly acts as an electron acceptor to suppress electron–hole recombination. Overall, the FeOCl/Ce photocatalytic system demonstrates high efficiency, good stability, and visible light responsiveness in CAF degradation, with potential applications for removing CAF and other emerging organic pollutants from aquatic environments. Full article

Plasma Transferred Arc (PTA) cladding is a versatile hardfacing technique that produces dense, metallurgically bonded overlays with excellent wear and corrosion resistance. However, optimizing bead shape is challenging due to complex multi-parameter interactions, an issue not fully addressed in existing studies. The bead morphology, defined by height, width, and penetration depth, remains highly sensitive to process parameters, directly affecting dilution and overall coating quality. In this work, single-pass powder PTA cladding was systematically studied using an orthogonal experimental design to assess the effects of arc current, powder feed rate, welding speed, oscillation width, and oscillation speed. A morphology index was proposed to integrate geometric attributes into a single metric for quality evaluation. Regression analysis and finite element simulations based on a Goldak double-ellipsoid heat source revealed that arc current is the dominant factor, where low-to-moderate values (100–115 A) promote wide–shallow pools and higher morphology index values, while higher currents induce excessive penetration and reduced stability. Multi-parameter coupling further indicated that optimal bead morphology is achieved under low-to-moderate current, a high welding speed, relatively high powder feed rate, wide oscillation width, and moderate oscillation speed. A representative optimal condition (100 A, 105 mm·min⁻¹, 35 g·min⁻¹, 10 mm, 2600 mm·min⁻¹) ensured minimal dilution and stable deposition. This integrative framework of orthogonal design, morphology index evaluation, and thermo-fluid simulation provides practical guidelines for parameter optimization and represents a novel combined approach for PTA bead optimization. Full article

This study reconstructs and projects relative sea-level change (RSLC) along Chesapeake Bay, a global hotspot for sea-level rise, from 1900 to 2100 by statistically extrapolating observed tide gauge trends, rather than employing climate model-based scenarios. The approach integrates global mean sea-level rise (GMSLR), regional sea-level rise (RSLR), and local land subsidence (LS) to evaluate both past and future behavior. Tide gauge data reveal that Chesapeake Bay’s sea level has accelerated at 0.099 ± 0.013 mm/year² since 1992, with a linear rate of 1.26 mm/year since 1900, slightly outpacing global averages. LS, primarily driven by glacial isostatic adjustment (GIA) and sediment compaction, has been the dominant contributor to RSLC since the early 20th century, accounting for up to 71% of the RSLC prior to 1992 across 15 tide gauge stations. However, with GMSLR accelerating at 0.120 ± 0.025 mm/year², the relative contribution of LS to RSLC is projected to decline to 31–43% by 2100. The reconstructed RSLC for the 20th century ranges between 32 and 44 cm, while extrapolated projections for the 21st century indicate a further increase of 53–99 cm. By 2100, GMSLR is expected to contribute to 60–70% of total RSLC. Spatial variability in RSLC across 15 tide gauge stations reflects differing geological conditions and anthropogenic influences such as groundwater withdrawal and construction-induced subsidence. These findings highlight the critical need for adaptive strategies to mitigate the impact of rising sea levels on coastal communities and infrastructure in the Chesapeake Bay region. Continued monitoring, improved modeling, and targeted resilience planning are essential to address the accelerating threats posed by sea-level rise and to ensure the sustainability of vulnerable coastal areas. Full article

This study investigates the long-term effects of catastrophic phosphate mining effluent contamination on the biocrust microbial community structure in sections of the ephemeral Ashalim Stream, Negev Desert, Israel. Microbial communities were characterized using next-generation sequencing of 16S rRNA gene fragments, conducted 1.5 and 5 years after the contamination event, across five stream strips. Samples from the nearby, uncontaminated Gmalim Stream served as controls. Biocrusts from Ashalim showed higher relative abundances of the phyla Actinobacteria and Firmicutes compared to Gmalim, whereas Chloroflexi were more prevalent in the controls. At the genus level, Blastococcus, Bacillus, Massilia, and Noviherbaspirillum were more abundant in the Ashalim strips, while Flavisolibacter, Segetibacter, and Rhodocytophaga were more abundant in the controls. Notably, genera within the Cyanobacteria phylum accounted for only 0.0–2.0% of sequences in Ashalim samples versus 2.5–20% in controls. The filamentous Leptolyngbya, Tychonema, and Trichocoleus genera were the most dominant cyanobacteria in all samples. The Nitrogen-fixing cyanobacterial genera Scytonema and Nostoc were consistently detected in Gmalim, but only in trace numbers in certain Ashalim sites. The results from both sampling campaigns support the hypothesis that phosphate effluent contamination had a profound impact on biocrust microbial community structure and function. In particular, the marked reduction in Cyanobacteria suggests a long-lasting disruption that may substantially hinder the natural ecosystem rehabilitation. Full article

The Tibetan Plateau is a globally critical climate-sensitive and ecologically fragile region. Vegetation phenology serves as a key indicator of ecosystem responses to climate change and simultaneously influences regional carbon cycling, water regulation, and ecological security. However, systematic quantitative assessments of phenological responses under the combined effects of multiple climate factors remain limited. This study integrates multi-source remote sensing data (MODIS MCD12Q2) and ERA5-Land meteorological data from 2001 to 2023, leveraging the Google Earth Engine (GEE) cloud platform to extract key phenological metrics, including the start (SOS) and end (EOS) of the growing season, and growing season length (GSL). Sen’s slope estimation, Mann–Kendall trend tests, and partial correlation analyses were applied to quantify the independent effects and spatial heterogeneity of temperature, precipitation, solar radiation, and evapotranspiration (ET) on GSL. Results indicate that: (1) GSL on the Tibetan Plateau has significantly increased, averaging 0.24 days per year (Sen’s slope +0.183 days/yr, Z = 3.21, p < 0.001; linear regression +0.253 days/yr, decadal trend 2.53 days, p = 0.0007), primarily driven by earlier spring onset (SOS: Sen’s slope −0.183 days/yr, Z = −3.85, p < 0.001), while autumn dormancy (EOS) showed limited delay (Sen’s slope +0.051 days/yr, Z = 0.78, p = 0.435). (2) GSL changes exhibit pronounced spatial heterogeneity and ecosystem-specific responses: southeastern warm–wet regions display the strongest responses, with temperature as the dominant driver (mean partial correlation coefficient 0.62); in high–cold arid regions, warming substantially extends GSL (Z = 3.8, p < 0.001), whereas in warm–wet regions, growth may be constrained by water stress (Z = −2.3, p < 0.05). Grasslands (Z = 3.6, p < 0.001) and urban areas (Z = 3.2, p < 0.01) show the largest GSL extension, while evergreen forests and wetlands remain relatively stable, reflecting both the “climate sentinel” role of sensitive ecosystems and the carbon sequestration value of stable ecosystems. (3) Multi-factor interactions are complex and nonlinear; temperature, precipitation, radiation, and ET interact significantly, and extreme climate events may induce lagged effects, with clear thresholds and spatial dependence. (4) The use of GEE enables large-scale, multi-year, pixel-level GSL analysis, providing high-precision evidence for phenological quantification and critical parameters for carbon cycle modeling, ecosystem service assessment, and adaptive management. Overall, this study systematically reveals the lengthening and asymmetric patterns of GSL on the Tibetan Plateau, elucidates diverse land cover and climate responses, advances understanding of high-altitude ecosystem adaptability and climate resilience, and provides scientific guidance for regional ecological protection, sustainable management, and future phenology prediction. Full article