Search Results (247)

Environmental fires pose a serious threat to energy security, ecosystems and public safety, whilst traditional halogenated flame retardants suffer from limitations such as high environmental residue risks and insufficient flame-retardant efficacy. In this study, sodium alginate (SA) was utilised as the matrix, with the incorporation of ammonium polyphosphate (APP) and phytic acid (PA), in conjunction with SiO₂-APTES surface modification, to prepare nitrogen–phosphorus synergistic bio-based flame-retardant gels. The present study systematically investigated the influence of the N/P molar ratio on the gelation kinetics, rheological behaviour, microstructure and flame-retardant performance of the gel. The study revealed a nitrogen–phosphorus coupled gas–solid two-phase synergistic flame-retardant mechanism. The results indicate that at an N/P ratio of 1/4, the gel forms a stable dual-network structure comprising ionic cross-links and Si–O–P covalent bonds. In the gas phase, the thermal decomposition of APP releases inert NH₃, which dilutes oxygen and quenches gas-phase radicals (·OH, ·H). In the condensed phase, the phosphate groups of PA-catalysed SA form Si–O–P covalent bonds with SiO₂ under the mediation of APTES, creating a dense, insulating char layer. In comparison with the control group (N/P = 0/0), the optimal gel sample (N/P = 1/4) demonstrated a 33% increase in shear stress, a 10% reduction in the peak heat release rate (HRR), a 75% decrease in total smoke production (TSP), and a 150% increase in char layer thickness after combustion, while maintaining adequate mechanical strength, thermal stability, and environmental friendliness. This work provides novel insights and strategies for the development of green, highly efficient flame-retardant materials for environmental fire prevention and control. Full article

Wooden, nature-based barrier structures are widely implemented after wildfire in Mediterranean forests to reduce runoff connectivity and trap sediment, yet their ecological footprint on early plant recovery remains poorly quantified in Greece. We assessed two-year vascular plant recovery in forest landscapes burned during the 2021 wildfire season (Parnitha, Attica; Mavrolimni, Corinthia/Peloponnese) using repeated field surveys in 2022 and 2023. Sixteen permanent plots were established within operational rehabilitation works and assigned to the dominant structure types: wattles (brush/branch piles), contour-oriented hillslope log barriers, and channel log dams. In each year, vascular plant composition and recovery endpoints (species richness and diversity indices, density, cover, and aboveground biomass) were quantified using standardized quadrat sampling. Vegetation cover and biomass increased strongly from 2022 to 2023 at both sites, indicating rapid early reassembly. Against this dominant year effect, structure type was associated with pronounced biodiversity and compositional differences, most clearly in Parnitha where log barriers exhibited markedly reduced diversity in 2022 and community turnover patterns differed among structures. Plot-level PERMANOVA on Bray–Curtis dissimilarities calculated from log(x + 1)-transformed abundances did not detect a statistically significant structure type effect in either year (p > 0.05), whereas descriptive Bray–Curtis heatmaps suggested compositional contrasts among structure type × year combinations. Indicator–species analysis further identified a limited set of taxa associated with specific structures, suggesting provisional structure-linked microsite filtering during early assembly. By quantifying community composition and indicator taxa alongside structural recovery, this study provides operational-scale evidence that common wooden post-fire measures may be associated with early biodiversity signals in the first two years after fire, although these patterns should be regarded as provisional given the short monitoring period and limited replication. Incorporating these signals into post-fire land management can improve intervention design and placement, aligning risk reduction with biodiversity recovery in Mediterranean landscapes. Full article

Fire hazard indices are fundamental for mitigating socioeconomic and environmental damage. This study evaluated the performance of the Ängstrom, FMA, FMA+, EVAP/P, and P-EVAP indices in the Cerrado-Amazon transition region (2010–2022), Brazil, using data from National Institute of Meteorology (INMET) and reanalysis (Copernicus). The efficiency of the models was validated by the Skill Score and Percentage of Success methods, correlating them with the hotspots from the DBQueimadas (INPE). The results reveal climatic seasonality typical of tropical regions, with rainy summers and severely dry winters, with minimum relative humidity below 30%. Although the average annual rainfall is 1662.20 mm, spatial heterogeneity and seasonal water reduction drove a 42% increase in the number of fire occurrences, totaling 3.9 million hotspots in the period. The P-EVAP and FMA+ indices showed greater predictive accuracy, with P-EVAP reaching a Skill Score of up to 0.74, especially with reanalysis data. FMA showed intermediate performance, while Ängstrom and EVAP/P were less reliable. Regionally, the highest sensitivity and accuracy of the indices were observed in Maranhão and Tocantins. It is concluded that regional meteorological variability directly influences the risk of wildfires, with P-EVAP and FMA+ being the most effective tools for monitoring and preventing fires in the region. Full article

Monitoring forest density is essential for understanding ecosystem health, wildfire risk, and post-disturbance recovery. This study proposes a robust methodology to extract forest density classes exclusively using Sentinel-2 multispectral imagery combined with vegetation indices (VIs), textural parameters, and spatial clustering metrics. The approach was applied to the northern part of Euboea Island, Greece, as a pilot area severely affected by a wildfire in August 2021. Four cloud-free Sentinel-2 images (2017–2024) were selected to capture pre- and post-fire conditions. A set of nine VIs—representing vegetation vigor, chlorophyll content, soil exposure, and canopy moisture—were calculated and statistically assessed for independence. To enhance classification accuracy, texture measures (homogeneity, correlation, and entropy) and spatial autocorrelation metrics (Moran’s I, Getis-Ord Gi) were derived for selected VIs. Supervised classification was performed using the Maximum Likelihood algorithm, yielding overall accuracies up to 89.4% and kappa coefficients above 0.85 when combining VIs with texture and spatial metrics. Results revealed a dramatic 49.3% reduction in forest cover immediately after the wildfire, with partial recovery (to 77.9% of pre-fire levels) three years later, mainly as a low-density forest. Approximately 12.1% of forest cover failed to regenerate, indicating potential long-term ecosystem degradation. The proposed approach provides a computationally efficient, high-accuracy alternative to data-fusion methods involving (Light Detection and Ranging) LiDAR or (Synthetic Aperture Radar) SAR datasets, making it suitable for operational forest monitoring and fire-risk management. Full article

The combined impacts of urban pluvial flooding and traffic congestion can severely delay emergency response. However, existing studies often focus on isolated scenarios, failing to systematically quantify the reduction in overall service capability and specific route disruptions to critical functional nodes under compound hazards. To address this problem, this study proposes a three-tier analytical framework to systematically evaluate the resilience of emergency services under compound hazards. The framework first utilizes spatial network analysis to simulate the overall spatial evolution of service capabilities for Emergency Medical Service (EMS) and Fire and Rescue Service (FRS) across various return periods and traffic conditions. It then delves into the emergency response coverage for vulnerable population places. Finally, the fastest-route analysis is employed to identify variations in rescue routing. The study reveals several critical insights. (1) As rainfall intensity and traffic congestion intensify, the coverage areas of EMS and FRS exhibit significant contraction and boundary erosion. Notably, the service areas of FRS show a distinct fragmentation pattern. (2) The protection levels for vulnerable population places (e.g., kindergartens, primary and secondary schools, and nursing homes) show a pronounced stepwise decline. Under extreme rainfall and the heaviest congestion, the 5 min coverage for these sites drops from 89.9% to 23.6% for EMS, and from 72.4% to only 15.1% for FRS, revealing a severe risk exposure for vulnerable groups. (3) Road inundation leads to a substantial extension of rescue routes and even results in the complete isolation of 141 primary and secondary schools. Overall, the framework provides actionable decision support to enhance urban emergency response under compound hazards. Full article

Prescribed fire is a vital tool for ecosystem management and wildfire risk reduction but its escalation is constrained by overly conservative burn windows because of uncertainties, for instance, in wind forecasts. This review describes the state of the art in weather product use by fire/smoke models and identifies three priority research gaps that artificial intelligence/machine learning (AI/ML) is well positioned to address: (1) spatial and temporal downscaling to meter-scale, sub-hourly wind fields; (2) bias correction for systematic model errors in complex terrain; and (3) robust uncertainty quantification to inform ensemble-based simulations. Emerging AI/ML techniques offer promising frameworks to address all three challenges. By providing high-resolution, bias-corrected, and probabilistic wind fields, AI/ML-enhanced forecasts will allow for expanded burn windows, improved ignition strategy design and a reduced reliance on expert intuition, especially when a prescribed fire is introduced into new areas. Full article

Bridges are critical components of transportation networks, and fire accidents can significantly impair their structural integrity, leading to safety risks and major economic losses. This study presents a comprehensive inspection, materials testing, repair, and field load testing program for a full-scale concrete box girder bridge (Delta Bridge, Alexandria, Egypt) following a fire exposure on two spans. A total of 28 concrete core samples were extracted and tested, revealing average compressive strengths of 48.50 MPa (slab), 53.90 MPa (web), and 45.88 MPa (columns), representing moderate reductions of approximately 8.5%, 7.9%, and 10.8%, respectively, relative to the original in situ concrete strength recorded during construction, and 29.2%, 43.7%, and 30.0% increases over the minimum acceptance limits specified by Egyptian code of practice (ECP 203). Tensile strength tests on reinforcement bars indicated an average yield strength reduction coefficient of 0.87, corresponding to an estimated peak exposure temperature of 600 °C, yet still satisfying Egyptian code requirements (≥500 MPa). Field static load tests using 40-ton tri-axle trucks demonstrated maximum midspan deflections of 6.7 mm in fire-exposed spans and full recovery (>94%) upon unloading, confirming that the residual stiffness and load-carrying capacity were within acceptable limits. Based on these results, a targeted repair program was executed, including concrete cover replacement with shotcrete; steel derusting; surface coating; and bearing replacement, followed by a verification load test that confirmed the effectiveness of the rehabilitation. This case study demonstrates a robust framework for post-fire condition assessment, residual capacity evaluation, and repair validation of concrete box girder bridges. The methodology and findings provide valuable guidance for engineers and transportation authorities in mitigating fire-induced risks and ensuring the safe reopening of critical bridge infrastructure. Full article

Precise Estimated Time of Arrival (ETA) prediction in Terminal Maneuvering Areas (TMA) constitutes a prerequisite for efficient arrival sequencing and airspace capacity management. While data-driven approaches outperform kinematic models, conventional Recurrent Neural Networks (RNNs) exhibit limitations in modeling complex multi-aircraft spatial interactions and lack the capability to quantify predictive uncertainty. Conversely, Spiking Neural Networks (SNNs) enable energy-efficient event-driven computation, yet their applicability to continuous trajectory regression is hindered by “input starvation,” where normalized state vectors fail to induce sufficient neural firing rates. This study proposes a Probabilistic Spiking Transformer (PST) architecture to integrate neuromorphic sparsity with global attention mechanisms. An Adaptive Spiking Temporal Encoding mechanism incorporating learnable linear projections is introduced to resolve the regression-spiking incompatibility, facilitating the autonomous mapping of continuous trajectory dynamics into sparse spike trains without heuristic scaling. Concurrently, a Distance-Biased Multi-Aircraft Cross-Attention (MACA) module models air traffic conflicts by weighting spatial interactions according to physical proximity, thereby embedding separation constraints into the feature extraction process. Evaluation on large-scale real-world ADS-B datasets demonstrates that the PST yields a Mean Absolute Error (MAE) of 49.27 s, representing a 60% error reduction relative to standard LSTM baselines. Furthermore, the model generates well-calibrated probabilistic distributions (Prediction Interval Coverage Probability > 94%), offering quantifiable uncertainty metrics for risk-based decision support while ensuring real-time inference suitable for operational deployment. Full article

Arc fault is the dominant cause of fire in photovoltaic (PV) systems, making its accurate identification crucial for PV fire prevention. This study investigates the influence of voltage (200, 300, and 400 V) and current (3, 5, 7, 9, and 11 A) on the DC series arc fault characteristics in PV systems obtained through experimental analysis. The results show that voltage variation has a negligible impact on arc fault behavior, while higher current levels substantially increase noise in the arc fault signals. To effectively mitigate noise, this paper proposes a denoising method that combines an improved moss growth optimization algorithm (IMGO) with improved complete ensemble empirical mode decomposition featuring adaptive noise (ICEEMDAN). It is found that the IMGO-ICEEMDAN denoising algorithm can effectively diminish noise in current signals, broaden characteristic frequency bands, and ameliorate arc feature discernibility. Subsequently, an integrated multi-scale spatiotemporal model is developed to extract arc fault features from the denoised signals. The model employs wide deep convolutional neural networks (WDCNNs) and bidirectional long short-term memory (BiLSTM) networks for parallel feature extraction, supplemented by a cross-attention (CA) module to optimize feature integration. The proposed WDCNN-BiLSTM-CA model ultimately achieves a detection accuracy of 99.89%, demonstrating superior detection performance over conventional methods, such as CNN-GRU and 1DCNN-LSTM models. This work provides a reliable framework for arc fault detection and fire risk reduction in PV systems. Full article

Firefighters face elevated risks of alcohol misuse due to occupational stress, trauma exposure, and cultural norms within the fire service. This beta test study evaluated the feasibility, acceptability, and preliminary outcomes of From Bottle to Nozzle, a digitally delivered alcohol awareness and prevention intervention tailored for firefighters. Fifty fire service personnel were invited to participate; 46 consented and completed baseline questionnaires, and 22 completed the full program. The intervention consisted of five self-paced online modules incorporating multimedia content, quizzes, and self-assessments that addressed alcohol history, fire service culture, risk-reduction strategies, communication, and health effects. Pre- and post-intervention assessments measured changes in alcohol-related knowledge, alcohol use, motivation to reduce drinking, and usability. Reinforcement messages were delivered via text and email. Alcohol-related knowledge improved significantly post-intervention, particularly in the general and total knowledge domains. Moderate drinkers showed reductions in drinking days and AUDIT scores. Among heavy drinkers, overall consumption declined slightly, though binge-drinking episodes increased. Changes in motivation to reduce drinking were mixed. Usability ratings were high, with an 80% module completion rate and favorable feedback on program brevity and format, though navigation and video length were noted as challenges. From Bottle to Nozzle demonstrated strong feasibility and acceptability. While knowledge gains were robust, behavioral outcomes were mixed, highlighting the need for larger controlled studies with extended follow-up. Full article

Growing renewable penetration increases deep peak-shaving demands, making stable wide-load operation of coal-fired boilers essential. A full-process CFD model of a 660 MW ultra-supercritical boiler was established, covering the furnace, heat-transfer surfaces, rear-pass duct, and selective catalytic reduction (SCR) system. Simulations at 25–100% boiler maximum continuous rating (BMCR) quantified load effects on combustion and emissions. Predicted furnace outlet temperature and major flue-gas species matched field data with deviations within ±6%. Lowering the load from 100% to 25% BMCR contracted the high-temperature core in the furnace and reduced mean temperature and mixing. Furnace nitrogen oxides (NO_x) formation decreased as the load decreased. However, NO_x at 25% BMCR increased because separated over-fire air (SOFA) was not applied. Reduced combustion intensity increased the level of unburned carbon in fly ash, which rose by approximately 3.5% at 25% BMCR, relative to the rated condition. Pronounced flow maldistribution also appeared at 25% BMCR. The SCR-inlet flow analysis indicated that the original guide vane design was not suitable for wide-load operation and that inlet-velocity uniformity deteriorated, especially at low loads. An optimized guide vane scheme is proposed, improving SCR-inlet uniformity over the full load range while mitigating ash deposition and erosion risks. Full article

The fire performance of existing reinforced concrete (RC) bridge decks strengthened by external prestressing systems is investigated, with particular attention to the vulnerability of externally applied tendons under realistic fire scenarios. Fire exposure represents a critical condition for such retrofitted structures, as the structural response is strongly influenced by load level, prestressing effectiveness, and thermal degradation of the strengthening system. A comprehensive assessment framework is proposed, combining thermal and mechanical analyses applied to representative highway overpass bridges. The thermal input adopted for the analyses is first validated through computational fluid dynamics (CFD) simulations, aimed at evaluating temperature development in typical RC beam–girder grillage decks subjected to fire from below. The CFD study considers variations in clearance height and span length and confirms that, in the case of hydrocarbon tanker accidents with fuel spilled on the roadway, conventional fire curves commonly adopted in the literature provide a reliable and conservative representation of both the temperature levels reached and their rate of increase within structural elements, thus supporting their use for rapid and simplified assessments. The validated thermal input is then employed in an analytical fire safety procedure applied to several realistic bridge case-studies. A parametric investigation is carried out by varying deck geometry, span length, reinforcement layout, and the presence of external prestressing retrofit, allowing the evaluation of the reduction in bending capacity and the time-dependent degradation of mechanical properties under fire exposure. The results highlight the critical role of external prestressing in fire scenarios, showing that significant loss of prestressing effectiveness may occur within the first minutes of fire, potentially leading to critical conditions even at service load levels. Finally, a multi-hazard assessment is performed by combining fire effects with pre-existing aging-related deterioration, such as reinforcement corrosion and long-term prestressing losses, demonstrating a marked increase in failure risk and, in the most severe cases, the possibility of premature collapse under dead loads. Full article

Atrial fibrillation (AF) is the most common sustained heart rhythm disorder. It is estimated that AF affects over 52 million people worldwide, with its prevalence expected to double in the next four decades. AF significantly increases the risk of stroke and heart failure, contributing to 340,000 excess deaths annually. Beyond these life-threatening complications, AF results in limitations in physical, emotional, and social well-being causing significant reductions in quality of life and resulting in 8.4 million disability-adjusted life-years per year, highlighting the wide-ranging impact of AF on public health. Moreover, AF is increasingly recognized for its association with cognitive decline and dementia. AF is a chronic and progressive disease characterized by rapid and erratic electrical activity in the atria, often in association with structural changes in the heart tissue. AF is often initiated by triggered activity, often from ectopic foci in the pulmonary veins. These triggered impulses may initiate AF via: (1) sustained rapid firing with secondary disorganization into fibrillatory waves, or (2) by triggering micro re-entrant circuits around the pulmonary venous-LA junction and within the atrial body. In each instance, AF perpetuation necessitates the presence of a vulnerable atrial substrate, which perpetuates and stabilizes re-entrant circuits through a combination of slowed and heterogeneous conduction, as well as functional conduction abnormalities (e.g., fibrosis disrupting tissue integrity, and abnormalities in the intercalated disks disrupting effective cell-to-cell coupling). The re-entry wavelength, determined by conduction velocity and refractory period, is shortened by slowed conduction, favoring AF maintenance. One major factor contributing to these changes is the disruption of the extracellular matrix (ECM), which is induced by atrial fibrosis. Fibrosis-driven disruption of the ECM, especially in the heart and blood vessels, is commonly caused by conditions such as aging, hypertension, diabetes, smoking, and chronic inflammatory or autoimmune diseases. These factors lead to excessive collagen and protein deposition by activated fibroblasts (i.e., myofibroblasts), resulting in increased tissue stiffness, maladaptive remodeling, and impaired organ function. Fibrosis typically occurs when cardiac fibroblasts are activated to myofibroblasts, resulting in the deposition of excessive collagen and other proteins. This change in ECM interferes with the normal electrical function of the heart by creating irregular, fibrotic regions. AF and atrial fibrosis have a reciprocal relationship: AF promotes fibrosis through fibroblast activation and extracellular matrix buildup, while atrial fibrosis can sustain and perpetuate AF, contributing to higher rates of AF recurrence after treatments such as catheter ablation or cardioversion. Full article

Polybutadiene has excellent mechanical properties and flexibility. It is widely used in elastomers and industrial fields. However, it has the characteristic of high flammability. The low LOI and rapid heat release upon ignition pose significant fire hazards. This results in a significant fire safety risk during service. Therefore, its application in some key fields has been restricted. In this study, polybutadiene with high-performance flame-retardant properties was developed by adding phosphorus–nitrogen synergistic flame retardants to address this challenge. This flame retardant mainly enhances its flame retardancy through the synergistic gas-phase and condensed-phase mechanisms. Dense and continuous carbon layers could be promoted by flame retardants during combustion. It provides an effective thermal barrier and oxygen barrier. In addition, phosphorus-containing volatiles can function by suppressing flame propagation via radical quenching in the gas phase. The modified polybutadiene reached UL-94 V-1 grade at the optimal load of 1.0 wt%. Meanwhile, its LOI increased to 27%. The cone calorimeter test further confirms a high reduction in peak heat release rate (pHRR). This work provides a feasible strategy for developing advanced polybutadiene materials. It can effectively enhance its fire safety. At the same time, it maintains a balance between flame retardancy and the overall material performance. Full article

Elderly welfare institutions in Taiwan have experienced multiple severe fire incidents, with smoke inhalation accounting for the majority of fatalities. Hot smoke can rapidly propagate through interconnected ceiling spaces, complicating evacuation for residents with limited mobility who depend heavily on caregiving staff and external responders. Field inspections conducted in this study indicate that 82% of residents require assisted evacuation, underscoring the critical role of early detection, staff-mediated response, and effective smoke control. Drawing on disaster management theory, this study examines key determinants of fire safety performance in elderly welfare institutions, where caregiving staff are primarily trained in medical care rather than fire safety. A total of 64 licensed institutions in Tainan City were investigated through on-site inspections, structured checklist-based surveys, and statistical analyses of fire protection systems. In addition, a comparative review of building and fire safety regulations in Taiwan, the United States, Japan, and China was conducted to contextualize the findings. Using the defense-in-depth framework, this study proposes a three-layer fire safety strategy comprising (1) prevention of fire occurrence, (2) rapid fire detection and early suppression, and (3) containment of fire and smoke spread. From a sustainability perspective, this study conceptualizes fire safety in elderly welfare institutions as a problem of risk governance, illustrating how defense-in-depth can be operationalized as a governance-oriented framework for managing fire and smoke risks, safeguarding vulnerable older adults, and sustaining the resilience and continuity of long-term care systems in an aging society. Full article