Search Results (36,587)

Emerging contaminants (ECs) and microplastics (MPs) are increasingly detected in surface waters, wastewaters, and drinking water, often as complex mixtures, transformation products, and particle-associated burdens that challenge routine monitoring. This critical review examines current analytical strategies for the detection and characterization of both molecular and particulate emerging contaminants in aquatic systems, with particular emphasis on their relevance to environmental and human health risk assessment. For molecular ECs, targeted LC–MS/MS and GC–MS and GC–MS/MS approaches are evaluated alongside high-resolution mass spectrometry (HRMS)-based suspect and non-target screening, retrospective data mining, and transformation-product elucidation. For MPs, particle-resolved vibrational spectroscopy including µ-FTIR and µ-Raman is critically assessed in comparison with complementary thermal analysis methods, such as pyrolysis–GC–MS and thermal extraction–desorption GC–MS (TED–GC–MS). Particular attention is given to the influence of sampling design, matrix-adapted sample preparation, analytical confidence, and method-dependent size and polymer coverage on data quality and interstudy comparability. The review further highlights the risks of ECs in relation to exposure pathways, mixture effects, and the potential carrier role of MPs for ECs, additives, and microorganisms. Finally, key priorities are identified for next-generation monitoring frameworks, including harmonized workflows, transparent confidence reporting, and stronger integration of analytical evidence with fate, exposure, and risk assessment. Full article

Ocular surface inflammation is a major disruptor of corneal epithelial homeostasis and a key driver of limbal stem cell deficiency (LSCD). Limbal stem cells (LSCs), residing within the specialized limbal niche, maintain corneal transparency through continuous epithelial renewal and by preventing conjunctival encroachment onto the corneal surface. Chronic or severe inflammatory insults—stemming from systemic autoimmune disorders, ocular surface diseases, infections, trauma, or environmental stressors—can damage both LSCs and their microenvironment, ultimately leading to limbal insufficiency. This review synthesizes current insights into the mechanisms by which inflammation impairs LSC survival, including cytokine-mediated cytotoxicity, oxidative stress, immune cell infiltration, and disruption of essential signaling pathways such as Wnt, Notch, and BMP. The distinction between LSC depletion and LSC dysfunction is highlighted, as residual stem cells may persist even in clinically advanced disease and can regenerate the corneal surface once the inflammatory milieu is corrected. Clinical manifestations, staging systems, and diagnostic markers—including p63α, ABCG2, and additional emerging molecular indicators—are summarized to support accurate assessment of LSCD severity. Current therapeutic strategies, ranging from anti-inflammatory medical management to surgical approaches such as SLET, CLET, and allogeneic transplantation, are reviewed alongside evolving regenerative and cell-based therapies. By integrating mechanistic understanding with clinical implications, this review underscores the critical interplay between inflammation and limbal niche failure and emphasizes the importance of early recognition and targeted intervention to preserve or restore LSC function. Full article

This study develops a Fuzzy C-Means-based mathematical framework for the storage-oriented evaluation and classification of hybrid energy system alternatives. The analysis considers fifteen hybrid configurations generated through pairwise combinations of solar, wind, biomass, geothermal, hydropower, and fossil-based energy sources. These alternatives are evaluated with respect to fourteen storage-related criteria, namely energy efficiency, exergy efficiency, entropy, lifetime, cost, CO₂ emissions, recyclability, decarbonization potential, discharge duration, charge duration, power capacity, energy capacity, sustainability, and environmental impact. After constructing and normalizing the decision matrix, the Fuzzy C-Means algorithm is employed to identify latent similarity structures and to determine the degree of membership of each hybrid alternative to multiple clusters. To support the selection of an analytically meaningful partition, alternative cluster structures are compared in terms of partition quality and interpretability. The results indicate that the considered hybrid configurations can be grouped into distinct yet partially overlapping storage-oriented profiles, reflecting differences in technical performance, environmental burden, and sustainability characteristics. In particular, hydropower-supported systems are associated with more stable and infrastructure-compatible profiles, while biomass- and geothermal-related combinations occupy more balanced transitional positions. By extending fuzzy clustering to the storage-oriented analysis of hybrid energy systems, the study provides a mathematically transparent basis for comparative assessment, exploratory classification, and preliminary decision support. Full article

The performance of native landraces of Capsicum annuum L. under contrasting production systems remains poorly understood, limiting their evaluation under locally relevant production scenarios. This study evaluated the phenological and productive responses of five genotypes (four native landraces and one commercial cultivar) under two systems representing locally relevant production conditions: open-field (OF) and a substrate-based hydroponic system under low-technology, passively ventilated tunnel-type greenhouse conditions (GH), to describe genotype-specific responses under contrasting production conditions during the 2023 growing season in Puebla, Mexico. Agroclimatic and agronomic variables were analyzed using independent ANOVA by system and canonical correlation analysis (CCA). The GH system exhibited restrictive microclimatic conditions, with maximum temperatures exceeding 48 °C and photosynthetically active radiation reduced by approximately 53% compared to OF conditions. Environmental conditions were not standardized between systems; therefore, the results reflect the contrasting microclimates of locally relevant production systems and provide a context-specific assessment of genotype performance. Under the specific conditions evaluated, yield was lower in GH compared to OF across all genotypes. The commercial cultivar Serrano Tampico achieved the highest yield (1.118 kg per plant under OF), while Mixteco Largo and Cola de Ratón produced the highest number of fruits. The CCA identified genotype-specific associations between environmental and agronomic variables, suggesting distinct performance patterns under contrasting production conditions, with native landraces exhibiting better agronomic performance under OF conditions. Overall, the results provide a context-specific characterization of genotype performance under contrasting production conditions. Full article

Foot-and-mouth disease (FMD) is a highly transmissible viral infection of livestock that threatens food security and causes substantial economic losses in endemic regions. Despite its economic impact, the role of environmental viral load and wildlife reservoirs in sustaining FMD transmission remains poorly quantified. The aim of this study is to assess the extent to which community viral load sustains FMD persistence and to identify key transmission drivers in a coupled livestock–wildlife–environment system. A Susceptible–Exposed–Infected (SEI) model with a free-living virus compartment was analyzed via the basic reproduction number ($R_0$) and solved numerically using a Nonstandard Finite Difference Method. Sensitivity analysis identified wild host population size, transmission rates, host recruitment, environmental viral decay, and viral load thresholds as major determinants of $R_0$. Results indicate that higher transmission rates accelerate susceptible depletion and increase exposed and infected classes, with wildlife dominating environmental viral contributions. Community viral load is central to sustaining outbreaks and informs targeted control strategies. Full article

Nature-based solutions (NBSs) involving tree-based interventions deliver multiple community benefits, yet evidence linking these benefits to underlying socio-ecological vulnerabilities remains limited. This study synthesised metadata from 131 European treescape NBS case studies spanning eight biogeographical regions using reverse-logic, thematic qualitative analysis. Case studies were identified via adapted PRISMA guidelines from open-access repositories, with community benefit themes categorised and mapped spatially across bioregions. The analysis revealed eleven principal community benefit categories and distinct region-specific patterns: Mediterranean interventions primarily mitigated extreme heat and drought vulnerabilities, whilst Alpine projects addressed slope stability and hazard reduction. The Continental and Atlantic regions emphasised social cohesion, recreational access, and the preservation of cultural heritage. The reverse-logic methodology successfully identified underlying socio-ecological vulnerabilities through systematic analysis of observed benefit profiles across diverse European contexts. This approach provides evidence-based guidance for designing location-sensitive treescape NBS that advance environmental research and public health objectives. The findings establish a methodological foundation for future assessments of NBS effectiveness and for refining location-specific treescape interventions that address community vulnerabilities and enhance adaptive capacity. Full article

Cyanobacterial harmful algal blooms are an increasing concern for wildlife health, particularly in eutrophic wetlands, yet well-documented avian cases supported by environmental, pathological, and toxicological evidence remain scarce. This study describes a sentinel case of probable microcystin toxicosis in a Red-gartered coot (Fulica armillata) from Laguna Petrel, a protected coastal wetland in central Chile, during a broader wildlife mortality event. Surface-water monitoring included nutrient analyses, in situ physicochemical measurements, phytoplankton assessment, and cyanotoxin quantification. The evaluated bird was documented alive with severe motor impairment, euthanized, and examined by gross necropsy, histopathology, and tissue toxicology. Water analyses showed elevated nutrients, persistently alkaline and highly productive conditions, marked dominance of Microcystis aeruginosa, and high concentrations of microcystin-LR, microcystin-RR, microcystin-YR, and nodularin. The bird showed marked hepatic lesions at necropsy, histopathological changes compatible with acute hepatotoxic injury, and detectable microcystin-LR in lyophilized liver tissue. Taken together, these findings support a diagnosis of probable microcystin toxicosis in this individual. This case highlights the value of waterfowl as sentinels of ecosystem health threats and underscores the importance of integrated monitoring in protected coastal wetlands potentially affected by toxic cyanobacterial blooms. Full article

Railway cable-stayed bridge construction is characterized by high complexity and substantial safety risk. Deficiencies in safety control may result in serious accidents (e.g., collapse and falls), causing significant casualties and economic losses; therefore, clarifying risk interactions and accident-causing mechanisms is essential. This study proposes a fuzzy DEMATEL–ISM approach in which fuzzy sets capture uncertainty in experts’ linguistic assessments. DEMATEL quantifies influence strengths and causal relationships among factors, and ISM constructs a multi-level hierarchy to explain accident causation. Twenty safety influencing factors are identified and grouped into five categories: management, human, material and equipment, construction technology, and environmental conditions. The obtained accident-causing mechanism comprises seven hierarchical levels: L₁: collapse and fall accidents, L₂: direct factors, L₃–L₅: indirect factors, and L₆–L₇: root factors. This mechanism is a chain of events that leads to an accident, with the nodes improper prestressing, structural deformation and differential settlement. These key nodes can be avoided by reinforcing safety management system implementation, daily supervision and inspection, and education and training on the subject of safety to ensure the safety of railway cable-stayed bridge construction. Full article

Coastal cities are typical regions where economic growth, population agglomeration, and eco-environmental pressures are strongly coupled. Assessing the coordination between urban development and the eco-environment is therefore important for regional sustainability. This study selected seven representative coastal cities in China—Dalian, Qinhuangdao, Qingdao, Shanghai, Fuzhou, Xiamen, and Zhuhai—and integrated multisource remote sensing data with statistical yearbook data to construct a comprehensive evaluation system for urban development level (UDL) and eco-environmental quality (EEQ). An ecologically enhanced indicator system incorporating vegetation condition index (VCI), biological richness index (BRI), normalized difference vegetation index (NDVI), and dynamic habitat index (DHI) was developed. The coupling coordination degree (CCD) model was then used to evaluate urban sustainable development from 2014 to 2023. In addition, an EWM–MLP adaptive weighting strategy was applied to refine entropy-derived weights, and Random Forest was used to identify variables associated with CCD prediction. The results show that CCD values generally increased during the study period, indicating improved coordination between urban development and the eco-environment. However, the evolutionary pathways differed markedly among cities, and UDL and EEQ changes were not fully synchronized. The EWM–MLP strategy introduced adaptive numerical refinements to CCD values while maintaining the overall stability of coordination-level classification. Random Forest analysis showed that CCD prediction was mainly associated with a limited number of high-contribution indicators. For all indicators combined, approximately 7–10 top-ranked variables were generally required to exceed 80% of the total importance, whereas the UDL and EEQ subsystems reached this threshold with fewer indicators. UDL-related variation was mainly associated with land-use structure, population agglomeration, and economic activity, whereas EEQ-related variation was related to ecological conditions, land-cover composition, and environmental pressure. The high-importance indicators exhibited clear inter-city heterogeneity, suggesting the need for differentiated governance strategies. The proposed framework provides methodological support for sustainable development assessment and differentiated governance in coastal cities. Full article

Plastic pollution has emerged as one of the most pervasive environmental challenges, with microplastics (MPs) widely distributed across marine ecosystems worldwide. This study aimed to assess the uptake of MPs by key fish and invertebrate species from different locations in the coastal zone of the Bulgarian Black Sea. Fish were collected during routine monitoring surveys in September–November 2024, while invertebrates were obtained via scuba diving. The presence of MPs in fish stomachs and invertebrate soft tissues, and their polymer composition, shape and size were analyzed using an Agilent 8700 LDIR Chemical Imaging System. Potential biological effects of ingested MPs were evaluated by an integrated Specific Oxidative Stress (SOS) index. The results revealed MP uptake levels comparable to those reported globally. Small-sized particles (<50 µm) with rounded shapes were most abundant across studied taxa. Polymer composition varied considerably depending on species and sampling region, indicating differences in exposure sources and environmental conditions. Oxidative stress levels in both fish and invertebrates showed substantial interspecific variation, and clear differences between the northern and southern region of the Bulgarian Black Sea. Overall, elevated uptake of MPs appears to contribute to oxidative stress in marine organisms, potentially affecting their health status, resilience, and adaptive capacity, as reflected by increased SOS index values. Full article

With the deepening integration of 5G-Advanced (5G-A) technology into smart manufacturing, the large-scale deployment of dynamic terminals—such as mobile robots and automated guided vehicles (AGVs)—within industrial private networks introduces complex, time-varying penetration and path losses. This significantly degrades the accuracy of conventional signal quality and capacity estimation methods, which were primarily designed for static terminal scenarios, thereby posing substantial challenges to coverage and deployment planning of industrial 5G access points, with downstream implications for power capacity dimensioning. To address this problem, this paper proposes a coverage-driven base station deployment optimization method formulated as a combinatorial optimization problem. The study constructs a signal strength assessment and network throughput calculation model tailored for dynamic industrial environments. This model captures the joint impact of terminal mobility and environmental obstacles on signal propagation, thereby enabling more reliable estimation of coverage performance and power consumption. Furthermore, by formulating the base station placement optimization as a combinatorial optimization problem, and by introducing mechanisms for equivalent transformation of the objective function and data preprocessing, the proposed method substantially reduces redundant computations during heuristic iterations. Simulation results verify that, compared with conventional static planning approaches, the proposed scheme enhances both the accuracy and computational efficiency of deployment planning while maintaining coverage quality. This work provides a theoretical foundation and a practical methodology for deploying reliable and energy-efficient industrial 5G-A private networks. Full article

The dramatic increase in the volume of postconsumer textile waste poses not only a major environmental problem but also an untapped opportunity for the development of sustainable infrastructure through the use of synthetic and composite textile waste-derived materials (SCTWDMs) in the field of asphalt pavement engineering, contributing to the achievement of the United Nations Sustainable Development Goals (SDGs 9, 11, 12, and 13). This systematic review was performed according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A systematic search of the literature in the field of SCTWDMs in asphalt pavement engineering was performed between 2010 and 2025 using the Web of Science and Scopus databases. A total of 65 studies were identified and analysed according to the inclusion and exclusion criteria of the current review. The quality of the studies and the risk of bias were assessed according to the transparency of the methods and the reporting of the results. The triangulated methodological framework consisted of bibliometric analysis, systematic review, and SWOT analysis. The bibliometric analysis was carried out via VOSviewer software version 1.6.20. The results of this study indicate an increase in the number of publications in SCTWDMs; however, there is fragmentation in the field. This denotes poor interrelationships among themes, insufficient collaboration across research streams, and scattered networks of keyword associations, suggesting a lack of a coherent research framework for SCTWDM research. The results of this study indicate that SCTWDMs generally improve the rheological properties, cracking resistance, and mechanical characteristics of asphalt mixtures. However, variability in fibre properties, optimisation of dosage, and limited field validation remain major challenges in SCTWDMs. The SWOT analysis also highlights important technical, institutional, and standardisation barriers, as well as opportunities for further development in sustainable pavement technologies. Despite this, the body of evidence is limited by heterogeneity in study design and a lack of long-term results. The review is not preregistered, but all the methodological procedures are transparently described. In conclusion, this body of evidence offers a strategic direction for further research, policy development, and industry practice, highlighting the importance of linking laboratory results to applications to position SCTWDMs as a viable option within the global sustainability agenda. Full article

Hospital gardens are increasingly recognized as therapeutic environments; however, many Post-Occupancy Evaluation (POE) studies remain limited to perception-based assessments without explicitly linking spatial characteristics to user experience. This study develops an evidence-based evaluation framework integrating spatial analysis with user-centered data. A mixed-methods approach was employed, combining systematic observations, spatial mapping, and a structured short-form questionnaire administered to 350 users. The study area was classified into three micro-climatic zones—hot, moderate, and cool/shaded—based on solar exposure, vegetation density, and surface characteristics. User experience was evaluated through composite indices of comfort, satisfaction, and perceived restorativeness (Cronbach’s α = 0.83). The results indicate a clear spatial gradient: mean comfort scores increased from 2.8 in hot zones to 3.5 in moderate zones and 4.2 in cool/shaded areas. These differences were statistically significant (p < 0.05) and supported by meaningful effect sizes (Cohen’s d). Furthermore, multiple linear regression analysis demonstrated that natural components—specifically mature vegetation and clean air—are strongly associated with psychological recovery (β = 0.54, p < 0.001). Spatial analysis also revealed a mismatch between design configuration and environmental performance. The findings provide a transferable, spatially grounded framework for optimizing therapeutic landscapes in healthcare settings. Full article

Current challenges in the construction field emphasize the need for compatible and durable materials for heritage interventions. Traditional lime-based mortars often exhibit limitations under environmental exposure, particularly in terms of water absorption and freeze–thaw resistance. This article investigates the performance of hydroxyapatite (HAp)-modified lime mortars applied in a real-scale heritage context, namely a student built micro-museum developed within the Apoș Architecture Summer School. Following the premature degradation of a conventional lime mortar layer applied at roof level, HAp-modified formulations were introduced as a protective and consolidating solution. The experimental approach combines laboratory testing and in situ evaluation, including compressive strength measurements, water absorption, capillarity tests, chromatic analysis, and freeze–thaw assessment. The results indicate a reduction in water absorption from approximately 22% to 12%, an increase in compressive strength from 6.57 MPa to 19.95 MPa and a significant improvement in freeze–thaw resistance, reflected by a decrease in gelivity from 61.2% to 5.73%, compared to traditional lime mortars. In addition, the contact angle increased from 36° to 82°, indicating enhanced hydrophobic behavior. These improvements are associated with pore structure refinement, reduced capillary uptake, and enhanced interfacial bonding within the mortar matrix. The study also highlights the role of real-scale educational environments in validating sustainable material solutions. Full article

With the rapid development of the world economy in recent years, the mineral resources in the shallow part of the Earth can no longer meet the needs of mankind, and resource development is continually moving into the deep part of the Earth. The filling method, in particular, has gradually been employed for the treatment of mining goaves in response to the requirements of environmentally sustainable development. As an important part of the filling system, the wear and tear of the deep filling pipeline is of great significance to the normal operation of the system, the safe production of the mine and the reasonable protection of the environment. In this paper, the wear situation of the deep well vertical filling pipeline is selected as the analysis angle to carry out the research, and the risk assessment model is constructed by combining the distance discriminant weighting method and the cloud model for the uncertainty of the wear risk grading assessment. Firstly, 11 quantitative factors and three qualitative factors were selected as evaluation indicators and employed as cloud model variables. Appropriate cloud model digital features were picked based on cloud model theory, to construct the cloud model of each indicator. Secondly, the distance discriminant weighting method is introduced to obtain the weight of each indicator, and the risk level of the vertical filling pipeline in deep wells is obtained by calculating the comprehensive certainty of the risk evaluation object belonging to different levels. Finally, the model was applied to Dongguashan Copper Mine, and the model calculation results were analyzed and compared with the actual wear situation. The results show that the model transforms the ambiguity and randomness into a certain quantitative value of certainty, completing the map from qualitative to quantitative. This method introduces a new idea and method for dealing with similar problems of vertical filling pipes in deep wells. Full article