Search Results (4,015)

Geohazards such as landslides, earthquakes, debris flows, and floods are governed by complex interactions among geological, hydrological, and human processes. Traditional data-driven models have improved hazard prediction but often lack interpretability and adaptability. This review examines the evolution of knowledge-guided approaches in geohazard research, highlighting how knowledge representation and artificial intelligence have progressively converged to enhance understanding, reasoning, and model transparency. A bibliometric analysis of 1410 publications indexed in the Web of Science reveals an evolution from early ontology-based knowledge engineering for expert reasoning to knowledge graphs (KG), frameworks enabling multi-source data integration and relational inference, and more recently, to large language model (LLM), augmented systems for automated knowledge extraction and cognitive geoscience. This review synthesizes advances in knowledge representation, knowledge graphs, and LLM-based reasoning, demonstrating how hybrid models that embed physical laws and expert knowledge can improve the interpretability and generalization of machine learning. These developments enable new forms of knowledge-driven geohazard intelligence and support applications in hazard monitoring, early warning, and risk communication. There are challenges we still face, including semantic fragmentation, limited causal reasoning, and sparse data for extreme events. Future directions require unified knowledge–data–mechanism architectures, causality-aware modeling, and interoperable standards to advance trustworthy and explainable geohazard intelligence. Full article

The transition to AI-driven Cyber–Physical Systems has fundamentally reshaped transportation, introducing systemic risks that transcend traditional physical boundaries. Unlike prior reviews focused on isolated technological domains, this survey proposes a novel “End-to-End” analytical framework that models the causal propagation of vulnerabilities from physical sensing hardware to human cognitive responses. Synthesizing 140 research contributions (2017–2025), we evaluate the paradigm shift from deterministic control to Generative AI and Large Language Models (Transportation 5.0). To substantiate our framework, we introduce a structured cross-layer threat matrix and mathematically formalize the technology–cognition cascade, explicitly mapping how physical layer perturbations, such as optical jamming, bypass digital edge security to trigger hazardous behavioral reactions in human drivers. We conclude that ensuring the resilience of next-generation infrastructure requires a unified analytical architecture that formally bounds hardware constraints, algorithmic safety, and human trust. Full article

Microplastics (MPs) are prevalent in coastal habitats, but their occurrence in highly vulnerable coastal zones and human exposure risk are poorly understood, especially in developing nations like Bangladesh. This inquiry focused on the prevalence and potential hazards of MPs in surface sediment and shallow groundwater samples collected from 12 sites in Cox’s Bazar, Bangladesh, from August to October 2023. Using stereomicroscopy and FTIR, MPs were quantified, with concentrations ranging from 60 to 813.33 MPs/kg in surficial sediment and 3.34 to 36.66 MPs/L in shallow groundwater, with mean values of 294.38 ± 26.61 MPs/kg and 18.91 ± 4.75 MPs/L. The dominant MPs were composed of transparent and white fibers, ranging in size from 0 to 0.5 mm, with HDPE (High-Density Polyethylene) and PP (Polypropylene) identified as the most commonly found polymers. To assess MP exposure in humans and the environment, this investigation used three indices: the polymer hazard index (PHI), the pollutant load index (PLI), and the estimated daily intake (EDI). The findings indicate that children exhibit greater exposure than adults, with observed low contamination levels, alongside a spectrum of toxicity from moderate to extreme. This study enhances understanding of MP contamination in the surficial sediments and shallow groundwater of Bangladesh, highlighting the need for further investigation into ecotoxicology, human health risks, legislation, and related issues. Full article

Abandoned oil and gas wells pose significant risks to human health and the environment by emitting air pollutants, contaminating groundwater, and leaving behind hazardous debris. In the United States, approximately 3.9 million documented wells vary widely in the accuracy of their recorded locations and plugging status, creating major challenges for detection, mapping, and remediation. Existing well detection methods show some promise but often lose effectiveness under complex conditions, such as vegetation occlusion or construction without metal components. In this study, we propose a drone-based approach equipped with a highly sensitive methane sensor to identify statistical anomalies in methane concentrations around abandoned oil and gas well sites. To address the noisy and variable nature of environmental sensor data, statistical methods were developed that enable reliable anomaly detection under field conditions. Controlled release experiments with known emission points validated the method’s ability to statistically detect methane anomalies that may indicate nearby emission sources. We further tested the approach at a field site containing three abandoned wells with known locations and sparse emission profiles. The results demonstrate that the proposed drone-based sensing method can serve as a rapid survey approach to identify areas with elevated methane signals around well sites, helping to reduce the scope of the ground survey area, and supporting prioritization of follow-up ground investigations. This approach provides a practical means to support targeted monitoring and prioritization of remediation efforts, while supporting the future development of source attribution and localization methods. Full article

The Historical Lateral Mobility Zone (HLMZ) represents the portion of the alluvial plain occupied by the river channel over the last decades or centuries and represents the most flood-prone sector of the floodplain. Mapping Land-Use–Land Cover (LULC) changes within HLMZs helps reconstruct human-driven land-use dynamics and identify the areas potentially exposed to the highest flood risk. Among the rivers of Southern Italy, the Sele River is characterized by one of the largest mean annual discharges and has experienced extreme and destructive floods, such as those from 1935 and 2010. Over the last 150 years, it has also undergone remarkable channel adjustments, consisting of narrowing up to ~120 m, morphological changes, and riverbed degradation. In this study, LULC changes that occurred between 1988 and 2023 within the HLMZ of the Sele River, formed over the last 150 years, were analyzed and mapped in a GIS environment. Active channels were digitized from historical maps, topographic maps, and orthophotos to map the HLMZ. LULC changes were assessed through visual interpretation of orthophotos and Google Earth imagery in a GIS environment. Results show a transition, over 35 years towards more pristine conditions, with forest expansion, reduction in agricultural areas, and absence of further artificialization. LULC dynamics appear to be strictly controlled by an increased awareness of the high flood hazard within the HLMZ, with positive implications in terms of flood risk, which, however, should be further assessed quantitatively in future studies and, possibly, reduced, given the high proneness of the Sele River to destructive floods. Full article

Distributed recycling of high-density polyethylene (HDPE) into filament for use in material extrusion 3D printing has been proposed as part of a circular economy. There is a gap in the understanding of the potential for HDPE to release contaminants that are potentially hazardous to human health during reuse. Herein, HDPE from post-consumer packaging waste was sorted into food and non-food (NF) streams and virgin HDPE was taken as a benchmark material. All materials were extruded into filaments and recycled multiple times while monitoring emissions. In general, particle and organic chemical emissions decreased by 93 to 99% and 73 to 99%, respectively, with increased reprocessing cycle without appreciable decline in mechanical (Young’s modulus decreased by 5 to 16%), processability (melt flow index stable from 0.2 to 0.7 g/10 min for waste plastics), and thermal properties (crystallinity ranged from a 6% decrease to a 9% increase) of plastics. An exception was a sub-stream of NF plastic that had increased particle emissions (up to 3100%) with reprocessing cycle. Reductions in emissions during filament extrusion appeared to be more influenced by reprocessing cycle than by any specific process step (grinding, etc.). The progressive decline in emissions without appreciable loss of polymer integrity could be exploited to pre-condition HDPE to reduce potential hazardous emissions prior to extruding into filament. This work helps fill the knowledge gap on approaches to recycling plastics in distributed settings such as home-based businesses, which is critical for developing effective recommendations for controls to enable safe work practices such as the use of ventilation to minimize exposures. Full article

To address the hazards posed by formaldehyde emissions from wood-based products to human health and the indoor environment, research on wood adhesives has focused on developing green and eco-friendly alternatives. However, the limited water resistance and bonding strength of bio-based or glyoxal-based adhesives have hindered their practical application. In this work, a co-condensation method was employed to prepare glyoxal-based co-condensation adhesive incorporating starch and a small amount of chitosan as synergistic reinforcing agents to enhance their cross-linking extent. Considering cost control, the starch content was varied to adjust the adhesive properties. When the molar ratio of glyoxal to urea was 2:1 and the mass ratio of starch to urea was 0.5:1, the adhesive exhibited optimal bonding strength, reaching 1.48 MPa after immersion in cold water for 24 h and 0.91 MPa after treatment in 63 °C hot water for 3 h. These values exceeded the requirements of the Chinese national standard (GB/T 9846-2015, ≥0.7 MPa). Structural analysis indicated Schiff base and aldol condensation reactions among amino groups in chitosan and urea and hydroxyl and aldehyde groups in starch and glyoxal, forming chemical covalent cross-links that contributed to improved water resistance and bonding strength of plywood samples. Furthermore, the excellent penetration ability of the adhesive could promote the formation of a uniform and dense cross-linked network under hot-pressing conditions, thereby enhancing the overall performance of the plywood. Full article

Campylobacter spp. constitutes a significant global public health hazard as it is a leading cause of reported foodborne diseases. Human infection is predominantly acquired through the ingestion of contaminated food, unpasteurized milk and untreated water, prompting the widespread implementation of chemical disinfection across several sectors, from healthcare, domestic environments, and food-processing to animal husbandry. While these biocidal agents encompass multiples classes with different modes of action and efficacy, growing evidence suggests that their extensive and repeated use may unintentionally promote bacterial persistence, tolerance and adaptive responses. Although biocide resistance has been documented in several foodborne pathogens, data on biocide tolerance in Campylobacter spp. remain limited. Available studies report variable degrees of reduced susceptibility to commonly used biocides among isolates originating from poultry production, food-processing environments, and water systems. Importantly, while biocide-induced adaptive responses in Campylobacter spp. may potentially overlap with antimicrobial resistance mechanisms, the extent to which these agents drive co-selection, persistence, or dissemination requires further elucidation. Evidence remains limited on the effects of long-term and repeated exposure under realistic processing conditions, the interplay between stress-induced gene regulation and stable genetic changes, and the contribution of mobile genetic elements, biofilm formation, and microbial communities in shaping antimicrobial resistance evolution. In light of the global health burden imposed by campylobacteriosis and the rising challenge of antimicrobial-resistant Campylobacter, this review brings together current evidence on the role of biocides in shaping bacterial survival, adaptation, and resistance mechanisms. Full article

With non-rainfall water (NRW), principally dew and fog, serving as an important water source, especially in arid and semiarid regions, factors that may increase the NRW yield may have important hydrological and ecological consequences. On the other hand, dew and fog may also have hazardous effect on inorganic and human-made materials that may undergo corrosion and/or degradation. It has long been noted that dew and fog are affected by neighboring objects, the effect of which was, however, only barely explored. Hypothesizing that it may principally be linked to the sky view factor (SVF) (determining, in turn, substrate temperature and heat flow) and, therefore, to the angle that is formed between the collecting substrate and the height of the neighboring objects, a set of square boxes (30 × 30 or 60 × 60 cm) was constructed. The boxes had variable heights, forming angles of 15°, 30°, 45°, 60°, and 75° between 6 × 6 × 0.1 cm cloth attached to a substratum (10 × 10 × 0.2 cm glass plate overlying 10 × 10 × 0.5 cm plywood) at the center of each box and the top walls of the box. NRW that accumulated at the cloths was compared with cloths placed in the open, serving as control. Another set served to measure the plate temperatures. A clear decrease in NRW, with an angle corresponding to a third-degree polynomial equation, was found (r² = 0.998). Taking 0.1 mm as the threshold for vapor condensation (dew), and taking the average maximal NRW as measured for two years in the Negev (0.20 mm), angles of ≥45° will suffice to impair condensation. However, with the projected decrease in NRW with global warming, even angles of ≥30° may impair condensation in 1–2 decades. While it may decrease the dew amounts and subsequently negatively affect the vegetation in forest clearings and wadis or canyons, it may decrease the exposure of construction materials to corrosion and/or degradation, thus exerting a positive effect on construction materials in urban settings. Full article

Sustainable groundwater management is essential for water security and human health protection. Fluoride contamination is a serious concern for the sustainable drinking water supply in many parts of Pakistan, including Balochistan, where arid climate conditions and geological formations support the enrichment of fluoride. The toxic nature of fluoride contamination has resulted in negative health impacts on the local population. Conventional geostatistical techniques are usually ineffective to delineate the nonlinear relationships that affect the distribution of fluoride. This study aims to develop a machine learning-driven spatial modelling framework for classifying the spatial distribution of fluoride contamination in groundwater across the study area. The model will help to understand the spatial variability of fluoride contamination and its controlling factors, essential for effective mitigation and early warning systems. Physiochemical elements were used as predictive features in this study, utilizing a unified feature importance framework combining hydrogeochemical analysis, spatial distribution assessment, and ensemble SHAP-based interpretation to identify consistent predictors. Model performance was evaluated using a nested cross-validation framework, followed by validation on an independent geology-informed spatial holdout test set to ensure realistic generalization. Among machine learning models, the Logistic Regression (LR), Support Vector Classifier (SVC), XGBoost (XGB), Decision Tree (DT), Gaussian Naïve Bayes (GNB), and K-Nearest Neighbours (KNN) were evaluated. Support Vector Classifier (SVC) demonstrated a high predictive performance. On the independent spatial holdout dataset, SVC achieved an overall accuracy of 0.75 and an area under the receiver operating characteristic curve (AUC) of 0.821. In addition to classification, a human health risk assessment was conducted using chronic daily intake (CDI) and hazard quotient (HQ) calculations for children and adults, identifying several high-risk water supply schemes. The prediction maps successfully delineated high-risk fluoride points across specific areas, offering a tool for sustainable groundwater management. This study helps to achieve a Sustainable Development Goal (Clean Water and Sanitation, SDG#6) and promotes long-term sustainable planning in water-stressed areas by integrating spatial machine learning mapping and health risk assessment. Full article

6PPD-Quinone (6PPD-Q) is a tire derivative formed by the oxidation of N-(1,3-dimethylbutyl)-N′-phenyl-p-phenylenediamine (6PPD), a commonly used antioxidant and ozone stabilizer in rubber products, and has emerged as a significant environmental concern in recent years. It is widely present in the atmosphere, surface lakes, and soil. The primary routes of exposure to 6PPD-Q are the digestive tract and respiratory tract. Studies indicate that it is a major factor causing acute mortality in coastal coho salmon (Oncorhynchus kisutch). Reports indicate that 6PPD-Q exhibits greater chemical stability and stronger biological toxicity than 6PPD, demonstrating toxic effects across multiple species. 6PPD-Q has been detected in human urine samples, indicating a need for heightened attention to its potential health risks. 6PPD-Q exhibits multi-organ toxicity in organisms, including intestinal, hepatic, neurotoxic, and reproductive toxicity. Its potential toxic mechanisms are associated with oxidative stress and inflammatory responses, and it can disrupt amino acid metabolism, carbohydrate metabolism, and lipid metabolism while interfering with signal transduction pathways by binding to specific receptors. This paper reviews the environmental contamination of 6PPD-Q, explores its potential toxic effects on organisms and underlying mechanisms, analyzes gaps in the current research and future trends, and contributes to a better understanding of its environmental occurrence and biological hazards. Full article

Wildfires are a major natural hazard causing extensive ecological damage and endangering human survival. Previous studies on wildfires in China have mostly focused on specific regions or individual drivers, with limited systematic assessments at the long-term and national scales. The spatiotemporal patterns of wildfires and their multiple driving mechanisms under China’s diverse climatic regimes remain insufficiently understood. To bridge this gap, we combined MCD64A1 burned area data (2001–2023) with multi-source natural (meteorological, vegetation, and topographic) and anthropogenic factors, using random forest models at both the national and regional scales to examine the spatiotemporal patterns, dominant drivers, and response mechanisms of wildfires in China. The results revealed that: (1) Spatially, wildfires were concentrated in northeastern and southern China, which accounted for 86.20% of the total burned area. Temporally, northern wildfires were primarily a spring-dominated fire regime, with peak activity in March and April, whereas southern wildfires were winter-dominated, peaking in February. (2) At the national scale, elevation was the key topographic factor influencing wildfire occurrence (relative importance = 0.49), with low-elevation and gentle-slope areas being more fire-prone. At the regional scale, the driving factors exhibit spatial differentiation, forming a spatial pattern of topography-dominated and climate-dominated. (3) Partial dependence plot analysis revealed nonlinear and threshold responses. Fire probability increases rapidly when the soil moisture is below 20 mm, while extremely high land surface temperatures in arid regions suppress fire occurrence due to fuel limitations. This study enhances the understanding of spatially heterogeneous wildfire drivers in China and provides a scientific basis for region-specific wildfire prevention and management strategies. Full article

This study presents a comprehensive 35-year (1990–2025) shoreline change assessment along the southeast coast of Ireland, integrating multi-decadal Landsat satellite archives with GIS-based Digital Shoreline Analysis System (DSAS) metrics to quantify both spatial and temporal coastal dynamics. Unlike previous studies that focus on shorter timeframes or localized sectors, this research provides a regional-scale, orientation-specific comparison between the eastern-facing (SE1; County Wexford) and southern-facing (SE2; County Waterford) shorelines. Shoreline evolution was quantified using four complementary DSAS indicators—Shoreline Change Envelope (SCE), Net Shoreline Movement (NSM), End Point Rate (EPR), and Linear Regression Rate (LRR), allowing robust discrimination between short-term variability and multi-decadal trends. The results reveal noticeable spatial variability in shoreline behavior with 57% accretion and 42% erosion across the eastern-facing coast (SE1) in County Wexford and the southern-facing coast (SE2) in County Waterford. SCE values ranging from 2.26 m to 663.83 m indicate considerable short-term shoreline variability, particularly within dynamic barrier and embayed systems. NSM values between −216.65 m and +663.83 m indicate erosional hotspots, particularly along soft-sediment coasts and exposed southern-facing sectors, whereas accretion is limited to embayments, sandy beaches, and zones of effective sediment trapping. Rate-based analyses show EPR values between −14.82 and +20.38 m/yr and LRR values between −5.27 and +20 m/yr, with LRR providing more reliable estimates of multi-decadal trends in highly dynamic environments. The findings highlight the strong influence of coastal orientation, sediment availability, geological controls, and human activities on shoreline change in southeastern Ireland. These findings provide valuable evidence to support coastal management, hazard mitigation, and climate adaptation planning, with the assistance of policymakers, to develop effective strategies that enhance the resilience and quality of life of coastal communities. Full article

The heavy metal pollution linked to extractive activities has attracted broad public attention. To examine the current state of heavy metal pollution in river sediments around iron tailing zones, this study was carried out to evaluate the distribution features, potential sources, and environmental hazards of heavy metals (HMs, Cr, Cd, Ni, Cu, Zn, Pb, As, and Hg) in the surface sediments of rivers in the Xiangshan area of Ma’anshan City. Results indicated that, except for Cr, the mean heavy metal concentrations exceeded the soil background levels in Anhui’s Huaihe River Basin. Variability in metal concentrations among the sediments was moderate, exhibiting an uneven spatial distribution. Significant positive correlations were detected between various HMs in the sediments, suggesting a common pollution source. Source analysis findings revealed that the HMs primarily originate from agricultural fertilization, mining, and smelting activities. Evaluation results from both the single-factor pollution index and the Nemerow comprehensive index indicated that the upstream section of the Caishi River is severely polluted by HMs. The potential ecological risk index evaluation results demonstrated that 85% of sediment samples from sampling points achieved a high comprehensive potential ecological risk level for HMs, with Cd, Cu, and Hg identified as the key contributors. The human health risk assessment demonstrated that both adults and children are subjected to carcinogenic risks from heavy metal exposure, with children exhibiting a higher risk level. This study offers valuable insights into managing heavy metal contamination in river sediments adjacent to iron tailings regions. Full article

The development of new materials that are inherently safe and sustainable has become a critical objective in the context of the green transition. This challenge is especially significant for plastics, which often contain complex mixtures of chemicals that may be released during various stages of their life cycle and that can pose risks to human health and the environment. Within this context, the Safe and Sustainable by Design (SSbD) framework was followed to support the design of an innovative epoxy–vitrimer composite that integrates non-releasable fire-retardant functionalities, aiming to produce safer, sustainable, and recyclable materials suitable for railway applications. A simple methodology was developed to identify release hotspots potentially affecting workers, consumers, and environmental species and organisms. Based on this, experimental simulations were conducted to evaluate the release of materials such as flame retardants, non-intentionally added substances, and microplastics at hotspots and to compare release profiles between a benchmark material and an SSbD alternative. The results demonstrate that the newly developed recyclable and less hazardous composites can also reduce material release under weathering and abrasion conditions. Full article