The fire performance of ventilated facade systems incorporating combustible insulation remains a critical issue in contemporary building design. This study presents a full-scale natural-fire test of a ventilated, rendered facade system containing 150 mm expanded polystyrene (EPS) insulation, conducted in accordance with the DIN 4102-20 methodology. Temperature measurements were recorded at key facade locations via K-type thermocouples, and flame spread, materials melting, and degradation were documented through visual observations. The combustion chamber reached a peak temperature of 912 °C, while the thermocouple located above the opening recorded a maximum temperature of 786 °C. No sustained flaming or debris above the 3.5 m height limit was observed, yet significant internal EPS melting occurred throughout the cavity. These findings underscore the potency of the “chimney effect” in ventilated cavities, highlight the limitations of the current acceptance criteria, and provide evidence relevant to ongoing efforts to develop more coherent approaches to facade fire-safety assessment.

In night-time construction scenarios of under-construction nuclear power plants, some yellow lights and open flames exhibit highly similar visual characteristics, resulting in frequent false alarms of fire sources. Such false alarm information tends to drown out real fire alarm signals, which not only severely disrupts construction operations but also endangers fire safety. To address this problem, this paper proposes an intelligent fire risk identification method based on an enhanced YOLOv8n (named YOLO-Fire). Specifically, shallow convolutional layers embedded with a coordinate attention mechanism are integrated into the Backbone of YOLOv8n; the Neck is optimised to improve the efficiency of multi-scale feature fusion; and the Head is enhanced to strengthen the localization and classification branches. Additionally, a composite loss function combining classification loss, regression loss, and similarity loss is designed, coupled with night-scene-specific data augmentation techniques and a two-stage progressive training strategy. Experimental results show that YOLO-Fire reduces the false alarm rate by 14.3%, increases the mean average precision (mAP@0.5) for open flames by 11.3% to 75.2%, and maintains an inference speed of over 85 frames per second (FPS). This study achieves an optimal balance between false alarm control, small object detection accuracy, and real-time processing efficiency, effectively resolving the misclassification issue between open flames and lights in night-time construction scenarios, and providing precise and efficient intelligent technical support for fire risk prevention and control during the construction phase of nuclear power plants.

Two-dimensional cellular automata (CA) models are widely used for wildfire simulation due to their clean representation of environment and fire mechanics and their computational efficiency. In this review we describe the mechanisms through which forestry fuel characteristics, topographic features, firefighting suppression strategies, fire spotting behavior and meteorological conditions are represented and integrated within these models. While these models are effective for large scale simulations, in which high precision is not critical, their reliance on discrete representations of space and time, along with simplified local state transition rules, introduces additional challenges and limitations. This review presents key methodologies, hybrid implementations, and model extensions of CA-based wildfire simulation models, highlighting their inherent strengths, limitations, and practical challenges. In addition, it provides a classification of the computational and simulation techniques applied to wildfire spread and behavior.

The effective delineation of fire station response zones is critical for urban public safety planning, yet traditional methods often fail to account for dynamic traffic conditions, leading to suboptimal resource allocation. This study proposes a novel block-unit-based method that incorporates real-time traffic data to delineate fire station response zones, improving the scientificity of response time estimation. The method was validated using data from Daxiang District, China, a typical urban–rural mixed region, encompassing 2230 block units, 4 fire stations, and 13,097 demand points. Analysis of 1,225,047 data samples revealed an average travel time of 960.7 s, highlighting significant accessibility challenges. The re-delineated response zones cover areas ranging from 1.07 to 156.24 km2, with significant variations. It is attributed to the concentration of fire stations in urban areas, insufficient coverage of vast rural regions, and the proximity of one station to a river and regional boundary. These findings underscore the spatial inequities in fire service provision and the need for a more balanced resource allocation strategy. Recommendations include establishing rural fire stations, improving urban traffic conditions, and relocating certain fire stations. This approach can enhance regional accessibility and provides a scientific basis for fire service planning.

Fire refugia are critical for post-disturbance recovery, yet microhabitats such as stones remain understudied despite their ubiquity and thermal persistence. This study tested whether the depth- and area-dependent refugial capacity of stones previously demonstrated in Mediterranean oak forests also operates in intensively managed plantations and how forest type and management modulate this capacity. Immediate wildfire effects (1–8 days post-fire) on ground-dwelling macroinvertebrates were quantified under 660 stones across burnt and unburnt native maritime pine and exotic eucalypt plantations following a medium- to high-severity wildfire. Stones acted as thermal refugia in both plantation types, with burial depths greater than 5 cm and surface areas greater than 500 cm2 predicting survival. Despite severe impacts (richness declined by 56% in pine and 63% in eucalypt; overall mortality exceeding 50%), diverse taxa persisted under stones, particularly ground spiders, ants, centipedes, rock bristletails, and harvestmen, while plant-associated and moisture-dependent groups suffered the highest losses. Native pine supported a higher abundance and richness per stone than exotic eucalypt in both burnt and unburnt conditions, reflecting management-driven differences in stone size, depth, and availability. These findings show that retaining sufficiently large, deeply buried stones during plantation establishment can enhance post-fire biodiversity recovery in increasingly fire-prone production landscapes.

Long-term fire histories are well-documented across most North American temperate forest systems, yet the fire regimes of high-alpine treeline environments remain poorly understood. Here, we present a millennial-scale fire history from the Sawtooth Fen Palsa (SFP), a rare permafrost fen palsa located in the high-alpine treeline ecotone of the Beartooth Plateau, Wyoming, a permafrost system now unraveling due to recent decades of rapid warming. Analysis of paleoenvironmental proxies from peat sediments overlying the permafrost reveals a multi-century peak in fire activity at the beginning of the record, ca. 10,000 cal yr BP, coinciding with the afforestation of newly deglaciated, ice-free sites. This initial surge in high-severity fire activity was followed by a decline when solar-orbitally driven increases in growing-season temperatures likely promoted forest opening and more surface fire activity within the SFP watershed. High-severity fire activity increased again during the mid-Holocene (ca. 5800–5000 cal yr BP), when effective moisture increased, favoring subalpine forest expansion and increased connectivity of woody biomass (sagebrush and forest), enhancing the potential for canopy fire spread. Only two small fire episodes were recorded in recent millennia when a rapid change in the sedimentation rate may indicate a partial loss of the sediment record. Rapid warming in recent decades has triggered the formation of dozens of thermal collapse ponds across the fen palsa. The frequency of these features has more than doubled since 2000 CE, underscoring the degradation of underlying permafrost in response to changing climatic conditions. Continued warming is expected to cause the complete loss of the permafrost lens and alter ecosystem dynamics, disturbance regimes, and carbon and nutrient cycling in alpine systems throughout the Rocky Mountains.

Wildfires pose a significant hazard to buildings and communities located at the wildland–urban interface (WUI) in Canada. Climate change is expected to intensify the duration, frequency, and severity of the wildfires. Current hazard assessments rely on historical conditions and may underestimate future hazard. This study adjusts fire intensity in national wildfire hazard maps to reflect projected changes in fire weather. Analysis is conducted for 393 National Building Code of Canada (NBC) reference locations under a 2.5 °C of global warming scenario, which corresponds to a 50-year future time-frame, a typical design life of buildings. The results show a strong upward shift in national hazard, with the number of locations in the “High” hazard class nearly doubling from 28 to 53. These findings highlight the need to integrate climate-informed hazard projections into future hazard mapping, building codes, and resilience planning. To date, no large-scale Canadian study has examined how climate-driven changes in wildfire hazard may influence the application of building design guidance at the national scale. This study provides an assessment of hazard sensitivity to climate change, highlighting the importance of considering projected fire weather conditions in national hazard assessments.

Ammonia has great potential as a clean energy alternative and can contribute to reducing carbon emissions from conventional fossil fuels. To investigate the combustion characteristics of ammonia-doped natural gas and to evaluate its feasibility for practical applications, this study experimentally and numerically examined the temperature and pressure variations of ammonia-doped natural gas mixtures under different initial pressures. In addition, the combustion products corresponding to different ammonia doping ratios were simulated and analyzed. The results indicate that, with increasing ammonia doping ratio, both combustion temperature and pressure decrease to varying degrees. Under atmospheric pressure, the combustion temperature generally decreases by approximately 25%, while the peak pressure reduction reaches up to 87.85% in certain cases. Furthermore, under negative pressure conditions, a relatively low ammonia doping ratio enhances the combustion intensity of the mixture, and the peak combustion temperature occurs at lower ammonia concentrations. From an environmental perspective, the variation in combustion products with ammonia doping ratio was further analyzed. The results show that the CO concentration in the combustion products decreases progressively by approximately 71.11% as the ammonia doping ratio increases. In contrast, the NO concentration increases to a maximum value and then remains nearly constant, whereas the NO2 concentration initially increases and subsequently decreases after reaching a peak value of 0.813 ppm. Overall, these findings provide experimental and theoretical support for understanding the combustion characteristics of mixed gaseous fuels and offer a scientific basis for the application and safety assessment of ammonia-doped natural gas.

This study presents the Moisture Dynamic Model (MDM), a new semi-physical formulation designed to estimate Fuel Moisture Content (FMC) using only air temperature and relative humidity. The core innovation of this work lies in the introduction of an Arrhenius-type kinetic term into a fuel moisture prediction framework, allowing temperature-driven desorption processes to be explicitly represented within a lightweight operational model. Its predictive capability was assessed through experimental campaigns on Cistus monspeliensis shrublands in Corsica and validated using FireStar3D simulations. A second major contribution is the coupling of the MDM with the physical wildfire simulator FireStar3D to quantify how FMC prediction errors propagate into fire spread predictions. The MDM accurately reproduced the seasonal variability of FMC, achieving strong correlation with experimental data during dry summer periods. When coupled with FireStar3D, discrepancies in the predicted rate of spread remained below 4% under high-risk meteorological conditions. While the model performed robustly during summer, its accuracy decreased during spring, when rainfall events and microclimatic variability introduced greater uncertainty. This work represents a proof of concept demonstrating the potential of a simple physically interpretable FMC model for operational fire behaviour prediction.

The Gilé National Park (PNAG for its acronym in Portuguese), located in central Mozambique is one of the most important protected areas in the country. It is one of the last remnants of intact Miombo woodlands, providing critical habitat for endemic biodiversity. Fires are an important ecological factor in Miombo, but changes in fire regimes may compromise the stability of this ecosystem and thus, the conservation value of PNAG. This study assessed fire patterns and mapped fire risk in support of adaptive management in the PNAG. We investigated Miombo fire regime over 23 years (2001 to 2023) in terms of return interval, frequency, temporal distribution, spatial density and intensity, extent, and severity, by using two Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite products (MCD14ML active fire; MCD64A1 burned area). Primary risk drivers were established and spatial fire likelihood mapped, using the Random Forest algorithm. Analysis revealed pronounced late dry season burning (August–October) affecting approximately 60% of the PNAG annually, especially in central-northern and eastern landscapes. Remarkably, 88% of the park maintains a 1-to-2-year fire return interval across the entire fire season (May–October) while only 7% maintains return frequencies of 3-to-4-year cycles. The latter is important for maintaining Miombo ecosystem functionality. Medium to medium–high fire severity covered 98% of the total fire extension. Climate-related drivers and hunting activities were identified as key fire initiators, especially in central areas of the park. The findings demonstrate an urgent need for spatially differentiated fire management action through prescribed burning to maintain PNAG’s ecological resilience and conservation value.