Search Results (7,132)

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

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

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

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

Retrofit strategies to improve the energy performance of buildings have gained significant importance worldwide; however, asbestos in older residential buildings is considered a serious threat to both human health and the environment. Existing studies have generally focused on the health effects of asbestos, the properties of insulation materials, or individual aspects of energy performance, while a coherent and comparative conceptual framework for sustainable retrofit systems is limited. This review aims to systematically integrate the current scientific evidence on asbestos management, alternative insulation materials, life cycle assessment (LCA), and circular economy principles to present a literature-informed conceptual decision-support framework for sustainable retrofit. The study used the PRISMA-based literature selection approach, while the evidence from different peer-reviewed studies was comparatively organized in the context of process workflows, risk considerations, lifecycle impacts, and building-physics-related findings. The literature-based results indicate that incorporating safe asbestos management, low-carbon insulation materials, and circular retrofit strategies into an integrated approach can improve energy efficiency and environmental sustainability. However, this study is not based on a validated numerical simulation, an executed optimization model, or calibrated engineering analysis, but rather on a comparative synthesis and conceptual interpretation of the existing literature and presents a decision-support framework that can guide future low-carbon and safe construction strategies. Full article

Thyroid hormones (THs) are essential regulators of human brain development, and disrupted TH availability during pregnancy or early life is linked to adverse neurodevelopmental outcomes. Concerns that environmental chemicals interfere with TH signalling have increased the need for human-relevant in vitro systems to identify thyroid hormone system-disrupting chemicals (THSDCs) for risk assessment. Here, we compared two human-induced pluripotent stem cell (hiPSC)-derived brain organoid models for THSDC assessment: (i) human cortical organoids (COs) generated by unguided differentiation, offering higher architectural complexity but lower throughput; and (ii) neural stem cell-derived organoids (NSCOs), designed for scalability with reduced cellular diversity. Both models expressed key TH handling components, including the transporter SLC16A2 (MCT8) and the inactivating enzyme DIO3. Using LC–MS/MS, we show that exogenous T3 is depleted from culture media and metabolized to 3,3′-T2 and 3′-T1 in both models, alongside upregulation of T3-responsive genes (HR, KLF9, DIO3, SEMA3C). Pulse and chronic co-exposures to reference disruptors iopanoic acid (IA, deiodinase inhibitor) and silychristin (SC, MCT8 inhibitor) altered T3 metabolism and modulated T3-responsive transcriptional endpoints. In NSCOs, high-content imaging revealed treatment-associated changes in cell composition, with chronic T3 reducing the SOX2-positive progenitor pool and THSDCs blocking this effect. Together, these findings provide a framework for organoid qualification—linking TH handling, transcriptomic responsiveness, and scalable phenotypic readouts—as a necessary step toward model validation and implementation of brain organoids in THSDC risk assessment pipelines. Full article

The relevance of this study is determined by the need for a scientifically grounded assessment of environmental risks associated with rocket launches and by the necessity of ensuring environmental safety in areas potentially affected by space activities. Comprehensive monitoring of rocket-stage impact zones and adjacent populated areas is especially important because pollutant distribution depends on natural, climatic, and spatial factors. This study assesses the environmental impact of the “Soyuz-2.1a” launch with the “Progress MS-29” cargo spacecraft in Kazakhstan using integrated field monitoring, laboratory analysis, and geoinformation methods. The work should be interpreted as a single-event environmental monitoring assessment, while historical monitoring data from 2020–2023 were used only as a retrospective comparative background for the U-25 impact area and were not included in the main BACI statistical analysis. The study covered the launch site, adjacent populated areas, and the U-25 stage impact zone. A before–after control-impact (BACI) design with distance stratification and consideration of wind direction was applied to identify post-launch changes. Measurements below the limit of detection and limit of quantification were processed using censored-data methods, including Regression on Order Statistics (ROS) and the Kaplan–Meier estimator. Spatial analysis was used to generate concentration fields, contour maps, and risk zones, revealing an anisotropic distribution of environmental stress in the downwind sector. An integrated hazard quotient (HQ) metric was applied to compare air, water, and soil conditions on a unified scale. The results indicate that the post-launch impact was localized and time-limited, with the greatest sensitivity observed in the soil component of the U-25 zone during the early post-launch period. Atmospheric air and water indicators remained within regulatory limits in populated areas. The proposed approach combines BACI monitoring, censored-data analysis, spatial modeling, and GIS-based visualization, providing a reproducible framework for the environmental assessment of rocket-stage impact areas. The practical recommendations include staged post-launch monitoring, temporary restriction of access to high-stress zones, primary reclamation of contaminated soil, and the use of WebGIS tools to support environmental decision-making. Full article

This study integrates multidimensional computational approaches—network toxicology, machine learning, molecular docking, and molecular dynamics simulation—to systematically elucidate the toxic mechanism by which the environmental pollutant diisononyl cyclohexane-1,2-dicarboxylate (DINCH) contributes to atherosclerosis. By jointly mining multiple databases, we obtained 246 targets common to DINCH and atherosclerosis. LASSO regression and support vector machine–recursive feature elimination (SVM-RFE) then identified 8 significantly upregulated core targets (CSF1R, CD36, CCL3, CCR2, ADAM8, TLR1, CTSS, and MMP1). Functional enrichment analysis showed that these core targets were significantly associated with key signaling pathways, including lipid and atherosclerosis, the PPAR signaling pathway, the PI3K–Akt signaling pathway, and the AGE–RAGE signaling pathway in diabetic complications. Differential gene analysis confirmed that these genes were significantly upregulated in diseased tissues, and receiver operating characteristic (ROC) analysis demonstrated excellent diagnostic performance (AUC = 0.87–0.96). Immune cell infiltration analysis further revealed a strong association between the core targets and immune cell populations, notably macrophages and T cells. Molecular docking and molecular dynamics simulations showed that DINCH had high affinity for the core targets, and its binding to CCR2 was the most stable (binding free energy = −7.6 kcal/mol). The final AOP framework systematically presented the cascade by which DINCH may contribute to atherosclerosis through metabolic disruption and immune activation. This study provides new mechanistic insights into the development of DINCH-induced atherosclerosis and offers a theoretical basis for health risk assessment of environmental pollutants. Full article

Insufficient oxidative capacity can limit humification during municipal sludge composting. This study comparatively evaluated two Fenton-like amendment systems, a homogeneous copper-based treatment (CH) and a heterogeneous nano-iron-based treatment (NFH), for their effects on composting performance, humification-related indices, spectroscopic characteristics, and bacterial community succession. Both amended treatments improved composting performance relative to the control, reaching higher peak temperatures (68.5 °C for CH and 70.3 °C for NFH) and prolonging the thermophilic phase. NFH also showed stronger moisture removal, with the final moisture content decreasing to 58.1%, compared with 65.1% in CH and 64.1% in the control. CH showed the highest apparent humic acid accumulation (1173 mg kg⁻¹), whereas NFH exhibited spectroscopic features commonly associated with lower E₄/E₆ ratios and more pronounced humic-like fluorescence characteristics. Ultraviolet–visible spectroscopy (UV–Vis), Fourier transform infrared spectroscopy (FTIR), and excitation–emission matrix fluorescence spectroscopy (EEM) analyses collectively indicated progressive transformation toward more aromatic and humified organic matter in the amended treatments. Bacterial community succession also differed across treatments, and several enriched taxa, including Rhodanobacter and Thermobifida, showed positive associations with reactive oxygen species (ROS)-related variables and humification indices. These results describe treatment-linked dynamics in humification and suggest corresponding changes in microbial succession during sludge composting, with potential implications for process outcomes. Full article

The consumption of wild rodents in certain regions of Southwest China creates a potential interface for zoonotic pathogen exposure, yet the virome composition of edible rodents remains insufficiently characterized. In this study, we performed multi-organ RNA metatranscriptomic analysis of three commonly consumed rodent species (Niviventer andersoni, Berylmys bowersi, and Rattus losea) collected from Guizhou Province, analyzing five visceral organs per species. A total of 1198 viral contigs spanning 37 viral families were identified, revealing diverse viral communities across host species and tissues, with host identity emerging as a key factor shaping virome structure. Sequences related to Seoul virus were detected in the lungs of R. losea, showing high similarity to previously reported strains, and sequences closely related to porcine Rotavirus A were identified in the lung samples of N. andersoni, indicating a close phylogenetic relationship with livestock-associated viruses. While these findings do not confirm active infection or transmission, they may reflect potential environmental exposure or ecological links at the wildlife–livestock interface. Overall, this study provides a baseline characterization of the multi-organ virome of edible rodents and highlights the importance of integrated surveillance and risk assessment within a One Health framework. Full article

Diesel is a major soil contaminant that poses significant environmental risks, making its removal essential. This study investigates the synergistic application of thermal desorption (TD) and thermal plasma for the remediation of diesel-contaminated soil, while simultaneously converting desorbed contaminants into valuable gaseous products. Artificially contaminated soil (25 g/kg) was treated by TD at 250–300 °C and the resulting off-gas and volatilized diesel were subsequently processed in a thermal plasma system. Soil samples were characterized using CHNS, EDX, FTIR, and TGA/DTG analyses, while gas composition was determined using a gas analyzer. The results demonstrate that TD achieved diesel removal efficiencies of up to 86% at 300 °C and 65% at 250 °C. TD off-gas and volatilized diesel were predominantly converted into synthesis gas (H₂ + CO) in a thermal plasma environment, with H₂ and CO concentrations reaching up to 15.49 vol% and 7.61 vol%, respectively, depending on the plasma-forming gas, carrier gas flow rate, and remediation temperature. Thermal treatment of diesel-contaminated soil significantly altered key physicochemical properties, including reduced organic matter content, increased soil compaction, and temperature-dependent shifts in pH and nitrogen speciation (decreased NO₃⁻-N and increased NH₄⁺-N). These changes were accompanied by enhanced phosphorus availability, indicating substantial thermally induced transformation of soil nutrients. Phytotoxicity assessment using Lepidium sativum in a soil leachate-based bioassay indicated that higher treatment temperature (300 °C) increased toxicity and inhibited plant growth, whereas treatment at 250 °C resulted in lower phytotoxicity. These findings highlight the adaptability of the proposed combination of methods enabling effective soil remediation while supporting energy recovery. Full article

Unmanned aerial vehicles (UAVs) have emerged as flexible platforms for environmental monitoring, including water sampling in hard-to-reach or hazardous areas. However, most existing UAV-based sampling solutions are limited to single-point collection or rely on complex fluid routing mechanisms that increase the risk of leakage and cross-contamination. This paper presents a novel ribbon-based multisampling capsule that enables sequential water collection from multiple locations during a single UAV deployment. The proposed mechanism employs a motor-driven ribbon with a single movable orifice that is sequentially aligned with individual sampling containers, allowing controlled intake and closure through a combination of hydrostatic pressure and mechanical sealing. A functional prototype was developed and experimentally evaluated to assess sampling feasibility and operational robustness. Experimental results demonstrate that improvements in sealing significantly reduce leakage events and eliminate dispenser-related carry-over, while enabling repeatable multi-point sampling. In addition, exploratory computational fluid dynamics (CFD) simulations were conducted to characterize hydrodynamic loads acting on the capsule and to support future design iterations, rather than to provide fully converged hydrodynamic validation. The proposed solution offers a practical, lightweight, and mechanically simple approach to UAV-assisted multi-point water sampling, with clear potential for further optimization and field deployment. Full article

Background/Objectives: Amyotrophic Lateral Sclerosis (ALS) is a rare, neurodegenerative disease with complex genetic and environmental determinants. The MTHFR C677T (rs1801133) variant, known for reducing enzymatic activity in the folate cycle, has been implicated in ALS risk, though findings remain inconsistent across diverse populations. Methods: A population-based case–control study was conducted in 248 age-matched individuals to investigate the MTHFR C677T (rs1801133) and ALS susceptibility. Molecular analysis was performed using the polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP). Genetic associations were evaluated under multiple inheritance models, while survival analysis utilized the Kaplan–Meier method to assess the relationship between MTHFR genotypes and patient prognosis. Results: The C677T variant showed a significant association under the codominant and recessive models, suggesting involvement in ALS risk (OR = 4.63; p = 0.01 and OR = 3.92; p = 0.02), respectively. However, stratification by sex demonstrated an association predominantly in women (OR = 7.10, p = 0.02; OR = 5.87, p = 0.04). Additionally, Kaplan–Meier analysis revealed a numerically shorter mean survival time for the mutant genotype compared with wild-type and heterozygous carriers, without statistical significance. Conclusions: Notably, we identified a significant association between the MTHFR C677T (rs1801133) variant and ALS risk, particularly among women. These findings suggest that the mutant (T/T) genotype showed a stronger association, potentially reflecting postmenopausal hormonal influences on one-carbon metabolism and related susceptibility pathways. Full article

Surface rock movement can lead to geological or environmental problems such as surface subsidence, ground fissure development, and deformation of engineering structures, and its evolution process exhibits significant spatiotemporal heterogeneity. Therefore, conducting high-precision, spatiotemporally continuous monitoring of surface deformation is of great significance for revealing subsidence mechanisms, assessing potential risks, and guiding disaster reduction decisions. GNSS and InSAR have become mainstream methods for monitoring surface deformation, but they still have limitations in terms of spatial sparsity, 3D deformation inversion capability, and data gaps in areas of strong deformation. To address these issues, this paper takes the Jinchuan copper-nickel mine’s No. 2 mining area as the research object and comprehensively utilizes multi-source monitoring data from GNSS and InSAR to construct a joint inversion model of the surface 3D deformation field based on posterior variance component estimation, achieving adaptive optimization of weight allocation and collaborative solution of 3D deformation. To address the issue of InSAR decorrelation in areas of strong deformation, which leads to missing deformation information, a fitting and estimation approach was applied to supplement six decorrelated points that spatially coincide with GNSS stations. These points are located in key deformation areas, and their reconstruction effectively improves the completeness and reliability of the deformation field in critical regions. Based on this, an automated solution process for the fusion model is implemented using MATLAB R2022b, and the joint inversion yields spatiotemporally continuous 3D deformation fields in the northward, eastward, and vertical directions. The results show that compared with traditional monitoring methods, the proposed fusion model exhibits higher inversion accuracy and stability under different InSAR technology conditions, effectively suppressing the impact of single data source errors on the overall solution results. Among them, SBAS-InSAR shows slightly higher accuracy in the vertical direction, while PS-InSAR achieves higher accuracy in the planar direction, as indicated by lower RMSE and MAE values. The research results improve the accuracy and reliability of surface deformation monitoring in mining areas, providing important technical support for safe mining and refined management. Full article

Background and Objectives: New Caledonia, an archipelago in the South Pacific, experienced an unprecedented conjunction of prolonged border closure during the COVID-19 pandemic (2020 to 2022) and marked influence of the El Niño/Southern Oscillation (ENSO). This context provided a unique opportunity to explore how environmental drivers, island isolation, and socio-demographic factors interact to shape infectious disease dynamics. This study aimed to assess the respective and combined effects of climatic variability, travel restrictions, and socio-demographic factors on the dynamics of four priority infectious diseases. Materials and Methods: We retrospectively analysed data from 2017 to 2023 on four infectious diseases: leptospirosis, dengue, influenza, and hepatitis A (HAV). Satellite precipitation data and the Multivariate El Niño/Southern Oscillation Index (MEI) were used. Socio-demographic and economic variables were gathered. Statistical analyses employed descriptive analysis and Generalized Additive Mixed Models to evaluate the associations between climatic events, travel restrictions, and disease circulation using the communal level as a random effect and time (daily) as a spline effect. Results: We analysed 878 cases of leptospirosis, 165 of HAV, 6607 of influenza, and 7377 dengue cases. Influenza was associated with rainfall before lockdown (Odds Ratio (OR) 0.7, Confidence interval 95%, (CI95%), (0.6–0.8)) and disappeared during lockdown but resurged post-reopening losing its meteorological association. Dengue epidemics declined, coinciding with the Wolbachia program and border closure, and were associated with lower MEI (OR 0.78, CI95% (0.6–1) during the 2017 to 2020 period. HAV cases were correlated with the MEI (OR: 1.8, CI95% (1–3.3)). Leptospirosis cases were associated with cumulative rainfall (OR 1.12 (1.1–1.2)) and lower education (OR 1.04, CI95% (1–1.1)) and decreased with water supply (OR 0.7, CI95% (0.5–0.8)). Conclusions: Our findings highlight how climatic conditions, mobility restrictions, and socio-environmental inequities differentially shape infectious disease risks in island ecosystems. These results reinforce the need for integrated One Health surveillance that jointly addresses environmental change, social vulnerability, and infectious disease prevention. Full article