Twin wildfires burned over 9500 ha in Seferihisar, İzmir, western Türkiye, on 29—30 June 2025 under extreme fire weather conditions. This study reconstructs the spatiotemporal progression of the fires and examines the drivers of contrasting behaviors and burn severity. Multi-source datasets—Sentinel-2 imagery, VIIRS/MODIS thermal detections, MTG images and thermal detections, aerial photos, and ground data—were integrated to delineate progression polygons and compute rate of spread (ROS), fuel consumption (FC), and fire-line intensity (FI). Kuyucak fire showed rapid early growth, burning 3554 ha in 2.5 h (mean ROS of 5.0 km h−1; mean FI of 37,789 kW m−1), driven by strong northeasterly winds of 40–50 km h−1, steep terrain, dense Pinus brutia fuels, and very low dead fine-fuel moisture (<6%). Kavakdere fire advanced more slowly (mean ROS of 1.6 km h−1) across open grassland and cropland, yielding lower FC and FI. Synoptic analysis revealed a strong pressure-gradient-induced northeasterly wind regime linked to a mid-tropospheric geopotential height dipole between Central Europe and the Eastern Mediterranean, while WRF simulations indicated a dry boundary layer and enhanced low-level winds during peak spread. Sentinel-2 dNBR burn severity mapping showed substantial spatial variability tied to fuel and topography contrasts. Findings demonstrate how twin ignitions under similar weather conditions can produce divergent outcomes, underscoring the need for terrain- and fuel-aware strategies during extreme Mediterranean fire outbreaks.

The increasing use of engineered timber in modern architecture raises critical concerns about fire safety, particularly when combustible linings are exposed within compartments. Classical compartment fire framework, largely derived from non-combustible enclosures, may not adequately capture the dynamics introduced by materials such as cross-laminated timber (CLT). This study investigates how combustible linings influence the fluid dynamic fields of compartment fires derived from the thermal field using CFD simulations informed by experimental data. A series of configurations, from inert to fully lined compartments, were analysed to isolate the effect of burning boundaries. Results show a progressive intensification of fire conditions with additional combustible surfaces: upper-layer temperatures approach 900 °C, smoke layers thicken, and stratification becomes more pronounced. Velocity fields are similarly affected, with peak inflow and outflow velocities doubling compared to the inert case and new vortical structures emerging near burning walls. These findings highlight that exposed CLT significantly amplifies radiative and convective heat feedback, modifying both temperature distributions and flow patterns in ways not captured by the traditional framework based on the inverse opening factor. This underscores the need for performance-based fire design approaches integrating both thermal and fluid dynamic perspectives, ensuring safe implementation of timber in modern construction.

Effective command-and-control (C2) decision-making during emergency response relies on timely access to spatially accurate information. It also requires a clear understanding of evolving incident conditions. Traditional fire-service training methods provide limited opportunities to rehearse complex, high-risk, and large-scale incidents under realistic yet safe conditions. This exploratory pilot study presents the design and experimental evaluation of an integrated training environment that combines geographic information system (GIS) data, unmanned aerial vehicle (UAV) imagery, and immersive virtual reality (VR) simulations to support C2 training for fire-service incident commanders. The system was assessed through scenario-based exercises involving 23 active incident commanders across three representative emergency scenarios: wildland fire, hazardous materials transport accident, and flood response. The training scenarios were based on real geographic areas in central Slovakia, using authentic terrain, land-cover, infrastructure, and hydrological GIS layers to ensure spatial realism of the simulated emergency environments. Pre-training and post-training questionnaires were used to evaluate perceived training realism, preparedness for command tasks, decision-making confidence, and the perceived usefulness of digital spatial information tools. Results indicate a substantial post-training increase in perceived realism and preparedness, with strong positive correlation between these variables (Spearman ρ = 0.71, p < 0.001). Participants reported improved confidence in assessing incident conditions, prioritizing operational tasks, and allocating resources under dynamically evolving scenarios. The study evaluates perceived spatial situational understanding derived from multi-source spatial information integration rather than directly measured situational awareness using standardized psychometric instruments. UAV imagery was found to be particularly valuable for rapid incident size-up, while GIS layers primarily supported spatial planning, hazard delineation, and resource coordination; VR served as a unifying platform for fusing these information sources into a coherent operational picture. Scenario-specific differences in tool usefulness were observed, reflecting the spatial and risk characteristics of each incident type. Overall, the findings indicate that integrated GIS–UAV–VR environments provide a realistic and scalable complement to traditional fire-service command training, enhancing spatially supported decision-making and preparedness for complex emergency response. Given the single-group pretest–posttest design, limited sample size, absence of a control group, and reliance on perceived evaluation measures, the results should be interpreted as indicative rather than as generalizable evidence of training effectiveness.

Polyimide aerogels (PIAs) possess enormous application potential in high-temperature thermal insulation scenarios. As high-efficiency thermal insulation materials, their thermal safety and thermal insulation performance are of crucial importance. Currently, poor dimensional stability, high-temperature pyrolysis, and severe shrinkage remain the key factors restricting their development and practical application. In this work, we employ an in situ co-gelation synthesis strategy, where methyltrimethoxysilane (MTMS) is introduced as the silica precursor to fabricate SiO2/polyimide aerogels (Si@PIAs). This strategy enhances the interfacial bonding strength between the organic and inorganic phases, enabling their complementation of strengths. Experimental results demonstrate that the incorporation of the inorganic SiO2 phase endows Si@PIAs with higher thermal safety, superior thermal insulation performance, lower density, and reduced shrinkage. Among them, Si10@PIA performs best with a density of 85 mg/cm3, a thermal conductivity of 23.28 mW/(m·K), and a heat flow peak temperature of 720.7 °C. More importantly, pyrolysis analysis reveals that the pyrolysis process of Si@PIAs shifts to a randomized nucleation and growth model (n = 2/5) with the mechanism function g(α) = [−ln(1 − α)]5/2. Compared with pure PIAs, Si@PIAs possess stronger resistance to pyrolysis, lower gross calorific value, and improved thermal safety. This study provides theoretical and practical guidance for the development of high-performance aerogel materials, promoting their application in lithium-ion battery separators, high-temperature insulation, and fire-resistant materials.

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.

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.

This study analyzes the flow and dispersion characteristics of fire smoke within the complex spatial structure of a T-type subway interchange station to clarify the impact of geometric parameter variations on the smoke spread timeline and evacuation environment. A three-dimensional numerical model of a typical T-type interchange station was constructed based on field survey data, with key variables defined as the height difference (H) between the platform and concourse layers and the horizontal distance (L) from the fire source to the track intersection. Through the simulation of multiple fire scenarios, the relationship between the smoke front arrival time (T) and the critical danger time (Ts) at key evacuation nodes was quantified in relation to the structural parameters. The results demonstrated significant linear correlations between vertical smoke spread and horizontal diffusion to adjacent tracks with H and L, respectively. Conversely, smoke intrusion at the transfer stairway exhibited nonlinear behavior driven by geometric constraints. The study notably highlights the dual effect of the height difference (H) on smoke spread. Significantly, the study highlights the dual effect of the height difference (H) on evacuation safety. While an increased height difference delays the initial vertical ascent and enlarges the smoke reservoir capacity, thereby extending the available safe egress time, it simultaneously elongates the physical evacuation path. Consequently, a trade-off emerges between the dispersion delay benefit and the increased evacuation distance. Strategies proposed based on the model analysis include the control of the vertical height difference to H≤ 11 m, the installation of smoke barriers, and the optimization of the smoke control system in the transfer corridors. These findings provide a theoretical basis and quantitative evidence for the optimization of smoke control systems and emergency evacuation design in T-type subway interchange stations.

Wildfires have emerged as a critical environmental and public health challenge globally, with their rising frequency and severity largely attributed to climate change. Although wildfire smoke is well recognized for its detrimental effects on respiratory and cardiovascular health, a growing body of evidence indicates that its immunological impacts are equally consequential. Composed of a complex mixture of particulate matter, volatile gases, and organic chemicals, wildfire smoke can disrupt immune homeostasis through multiple, interconnected pathways. Recent findings underscore the susceptibility of natural killer (NK) cells—key effectors of the innate immune system—to wildfire smoke-induced dysregulation. This review synthesizes current knowledge on the immunotoxicological effects of wildfire smoke with a specific focus on NK cell biology. It examines how both acute and chronic smoke exposures alter NK cell frequency, phenotype, and cytotoxic function, and explores the mechanistic contributions of inflammation, oxidative stress, and pollutant-mediated receptor modulation. Furthermore, the review considers potential long-term consequences of NK cell impairment, including heightened vulnerability to viral infections, diminished tumor surveillance, and broader disruptions in innate–adaptive immune crosstalk. Collectively, the evidence highlights the need for targeted research to delineate the pathways by which wildfire smoke compromises NK cell-mediated immunity and to inform strategies for mitigating these risks in exposed populations.

Video footage of a recent California wildfire confirmed that dangerous fire spread can lead to unsurvivable foreground conditions. This process thus needs enhanced awareness across the wildfire sector. The fire moved sideways, downwind of a ridgeline, and formed dense, rapidly spreading spot-fires. Effective lateral rates-of-spread up to 20 km h−1 were measured. This is discussed in detail. A HPWREN camera system was installed on Santiago Peak in California. The Airport Fire, on two consecutive days, burned past the cameras by means of vorticity-driven lateral spread (VLS). This provided the most complete sets of time-series observations of VLS on a landscape-scale. Some remarkable measurements are derived from the observations. The overall lateral rate-of-spread averaged at 1.9 km h−1. Around plume touch-down events, that speed rose to 4 km h−1, but also peaked at 20 km h−1. The effective downwind spread of the overall fire envelope was 45 km h−1. A major spot-fire had a slope-affected headfire rate-of-spread of 15 km h−1 (equivalent to c. 2 km h−1 on flat ground) and a burn rate of 60 ha h−1. The implications for fireground safety are extreme. An emphasis must be placed on predicting these events, as any burnover entrapments may well be unsurvivable. Avoiding a burnover requires good predictive capability, and observations such as these are critical for calibration.

Spontaneous combustion of coal piles threatens the production and transportation safety of coal mining, which is attracting more and more attention. To understand the underlying physics, conducting pore-scale research on the spontaneous combustion of coal piles is critical. To enable pore-scale research, a pore-scale model of the spontaneous combustion of a coal pile is described, and governing equations are introduced. To understand the competition between airflow, heat–mass transfer, and oxidation reaction, the lattice Boltzmann method (LBM) is utilized, which offers distinct advantages in handling complex pore geometries, multi-physics coupling, and reactive transport at the pore scale. The present model integrates, for the first time in a pore-scale LB framework, airflow driven by thermal buoyancy, convective heat and mass transfer, and Arrhenius-type oxidation kinetics within a realistic coal pile geometry. After the numerical method is validated, the effects of inflowing air velocity, inflowing air temperature, oxygen concentration, and coal particle size are discussed. With an increase in inflowing air velocity, convective heat transfer is enhanced, and the coal pile maximum temperature decreases monotonically. According to the Arrhenius equation, with an increase in the inflowing air temperature and oxygen concentration, the oxidation reaction is accelerated, and the coal pile maximum temperature increases. When the size of the coal particle increases, the oxidation reactive area decreases, and the coal pile maximum temperature decreases, while the steady temperature is not affected.