Fire, Volume 8, Issue 9 (September 2025) – 38 articles

Assessing the energy flux delivered to ecosystem components by wildfires is hard because of technical and safety problems in performing measurements during such events. Here, we present a laboratory and field experimental assessment of a new method of evaluating a wildfire energy flux; our approach is based on the fact that different types of trash deform at different temperatures. We produced deformed trash in a laboratory environment using an iCone calorimeter to deliver a range of heat fluxes over a range of durations. We followed this by placing trash in instrumented prescribed fires. We show that finding melted or heat-altered plastic bottles and aluminium cans in the aftermath of wildfires can provide useful information about the heating that they received during the fire: plastic bottles are a useful indicator for areas that received less than 2 MJ/m² with a maximal temperature of <200 °C, while aluminium cans may be applied to higher-energy sites 100 MJ/m² that experienced a temperature above 600 °C. We provide a semi-quantitative proxy guide as to what different observed deformations may indicate in terms of energy flux and hope that this may allow scientists and forest managers to easily and cheaply assess the energy flux delivered to ecosystems and semi-quantitatively compare different wildfires. Full article

The accurate computation of the thermophysical properties of gases and gas mixtures is critical for combustion analysis but remains challenging due to the precision and numerical stability required across wide temperature ranges. In this study, we present Thermophy, a computational framework based on Chebyshev polynomial fitting, developed to calculate thermal conductivity, viscosity, and binary diffusion coefficients for pure gases and multicomponent mixtures. Unlike conventional tools that rely on low-order polynomial approximations, Thermophy applies Chebyshev fitting over defined temperature intervals, enabling higher accuracy, improved numerical stability, and computational efficiency. Thermophy is validated through four case studies involving pure gases, binary mixtures, and ternary mixtures relevant to combustion applications. For pure gases and air, deviations in thermal conductivity and viscosity were found to be 1.22–4.25% and 0.11–4.71%, respectively. For ternary mixtures, viscosity deviations ranged from 0.11 to 0.24%, while binary mixtures showed deviations of 2.60% and 0.20% for viscosity and thermal conductivity, respectively. Binary diffusion coefficients exhibited an overall deviation of approximately 3.35%. The combination of flexible input handling, extensibility, and high-fidelity calculations positions Thermophy as a robust and efficient alternative for integration into combustion modeling and other gas-phase simulation frameworks, including gasification, pyrolysis, global carbon cycle analysis, environmental systems, and fire modeling. Full article

Grassland fire risk perception constitutes a fundamental element of fire risk assessment and underpins the evaluation of response capacities in grassland regions. This study examines Qinghai Province, the fourth-largest pastoral region in China, as a case study to develop an evaluation index system for assessing residents’ perceptions of grassland fire risk. Using micro-level survey data, the study quantifies these perceptions and applies a quantile regression model to investigate influencing factors. The results indicate that: (1) the average grassland fire risk perception index among residents in Qinghai Province’s grassland areas is 0.509, with response behaviors contributing the most and response attitudes contributing the least; (2) Residents in agricultural areas perceive higher risks than those in semi-agricultural/semi-pastoral or purely pastoral areas, and individuals in regions with moderate dependency ratios and moderate fire-susceptibility conditions demonstrate the highest performance, whereas those in pastoral and high-susceptibility zones exhibit signs of “risk desensitization”; (3) risk communication and information dissemination are the primary drivers of enhanced perception, followed by climate variables, whereas individual characteristics of residents attributes exert no significant effect. It is recommended to monitor the impacts of climate change on fire risk patterns, update risk information dynamically, address deficits in residents’ cognition and capabilities, strengthen behavioral guidance and capacity-building initiatives, and foster a transition from passive acceptance to active engagement, thereby enhancing both cognitive and behavioral responses to grassland fires. Full article

Against the background of the accelerating global transition towards a low-carbon energy system, the lithium-ion battery (LIB) industry has witnessed a rapid development. Concurrently, fire accidents in LIB application scenarios have occurred frequently, with safety issues becoming increasingly prominent. Thermal runaway of LIBs is the direct cause of such fires. During the thermal runaway process of LIBs, lithium salts in the electrolyte undergo thermal decomposition reactions with carbonate-based electrolytes, releasing a large amount of heat and fire gases. Among them, the thermal decomposition reactions of LiPF₆ with electrolytes are coupled and superimposed, exhibiting a significant synergistic effect. This paper employs quantum chemical calculation methods to investigate the thermal decomposition reaction mechanisms between PF₅ and POF₃, which generated from the thermal decomposition of LiPF₆ and carbonate-based electrolytes (EC, DMC, and DEC) during the thermal runaway process of LIBs; and presents detailed chemical reaction mechanism models. The P atoms in PF₅ or POF₃ combine with the O atoms of the ether oxygen groups in carbonates, while the F atoms combine with the C atoms adjacent to the ether oxygen groups. This promotes the ring-opening or chain scission of carbonate molecules, reduces the energy required for the reaction, and accelerates the thermal decomposition reaction and the generation of fire gases. Modification of EC, DMC, and DEC through fluorination can effectively inhibit the catalytic effect of PF₅ and POF₃ and improve the oxidation resistance and thermal stability of the electrolytes. Full article

In order to provide fire-scene parameters for fire protection design and data support for fire safety management of waiting halls in high-speed railway stations, this study systematically investigated the combustion characteristics of single, two, and three massage chairs using an industrial calorimeter. The results showed the following: The change in heat release rate in the growth stage of the massage chairs’ combustion tests was consistent with the t² fast fire (with a growth coefficient of 0.04689). The maximum HRR was 1.2 MW for the single-massage-chair combustion test, 2.5 MW for the two-massage-chairs combustion test, and 3.5 MW for the three-massage-chairs combustion test. In the full-scale massage chairs combustion test, setting a 6.0 m fire isolation zone could effectively serve the functions of fire prevention and heat insulation. Considering a certain safety margin, and with a safety factor of 1.5 adopted, it is recommended that a fire isolation zone with a width of 9.0 m be used in the waiting halls of high-speed railway stations, which provides a direct, actionable design basis for engineering practice. Full article

Sandwich panels are widely used in industrial roofing due to their lightweight and thermal insulation properties; however, their structural fire resistance remains insufficiently understood. This study presents a data-driven approach to predict the mid-span deformation of glass wool-cored sandwich roof panels subjected to ISO 834-5 standard fire tests. A total of 39 full-scale furnace tests were conducted, yielding 1519 data points that were utilized to develop deep learning models. Feature selection identified nine key predictors: elapsed time, panel orientation, and seven unexposed-surface temperatures. Three deep learning architectures—convolutional neural network (CNN), multilayer perceptron (MLP), and long short-term memory (LSTM)—were trained and evaluated through rigorous 5-fold cross-validation and independent external testing. Among them, the CNN approach consistently achieved the highest accuracy, with an average cross-validation performance of $R^2=0.91(\mathrm{mean}\mathrm{absolute}\mathrm{error}\left(\mathrm{MAE}\right)=4.40;\mathrm{root}\mathrm{mean}\mathrm{square}\mathrm{error}\left(\mathrm{RMSE}\right)=6.42)$, and achieved $R^2=0.76(\mathrm{MAE}=6.52,\mathrm{RMSE}=8.62)$ on the external test set. These results highlight the robustness of CNN in capturing spatially ordered thermal–structural interactions while also demonstrating the limitations of MLP and LSTM regarding the same experimental data. The findings provide a foundation for integrating machine learning into performance-based fire safety engineering and suggest that data-driven prediction can complement traditional fire-resistance assessments of sandwich roofing systems. Full article

Fire has had a profound impact on Australia’s landscapes and biodiversity since the late Tertiary. Indigenous (Aboriginal) people have lived in Australia for at least 65,000 years and fire is an integral part of their culture and cosmology. In 2015, an Indigenous cultural burn was undertaken by Banbai rangers at Wattleridge Indigenous Protected Area, New England Tablelands, NSW. We compared the impact of this burn on the composition, cover, abundance, and species richness of dry sclerophyll vegetation and fuel hazard, with a hazard reduction burn at nearby Warra National Park, using a Before-After-Control-Impact experimental design. Our study found that the low-severity cultural burn and moderate-severity hazard reduction burn reduced fuel loads but did not have a significant impact on the composition of the vegetation overall or the herb layer. The hazard reduction burn had a significant impact on shrub and juvenile tree (woody species) cover, while the abundance of woody species was significantly affected by both fires, with a mass germination of ‘seeder’ species, particularly after the cultural burn. The long unburnt fire regime at Wattleridge may have made the vegetation more responsive to fire than the more frequently burnt vegetation at Warra, through accumulation of seed in the seed bank, so that the patchy cultural burn had a greater impact on woody species abundance. In terms of ecological and bushfire management outcomes, this study provides evidence to support claims that Indigenous cultural burning decreases fuel loads, stimulates regeneration of shrubs and trees, and manages at a local, place-based scale. We recommend cultural burning as a key management tool across Indigenous Protected Areas and other land tenures, with its implementation monitored and adaptively managed through two-way science, to foster fire regimes that are both culturally and ecologically beneficial. This is a vital element of our resilience in the Pyrocene and a significant step toward decolonizing science and land management. Full article

A unified WebGIS platform for wildfire simulation and visualization is presented, integrating three coupled physical models: HDWind for wind field computation, PhyFire for wildfire spread, and PhyNX for smoke plume dispersion. The system includes preprocessing and postprocessing scripts that enable the efficient integration of meteorological and cartographic data and support the visualization of outputs such as burned areas, wind and smoke fields, and emission estimates. The platform is deployed through a WebGIS interface that supports both decoupled and coupled simulations, providing operational flexibility and reducing computational demands when needed. A real wildfire scenario is simulated to demonstrate system capabilities. The case study highlights the platform’s applicability in operational contexts, reinforcing its potential to evolve into an accessible and user-oriented environmental decision support system for wildfire management. Full article

The main goal of this work is to analyse the thermo-mechanical effect in single shear dowelled timber connections under fire conditions. This research includes the development of numerical models using the finite element method. The numerical methodology was validated using previously published experimental and numerical data. New models were developed to evaluate the temperature evolution, charring rate, and load-bearing capacity of the connections throughout exposure to fire. The calculations based on Eurocode 5 are conservative in the dimensioning of connections at room temperature but have less impact on the design of fire resistance, as they do not consider factors such as geometric parameters or passive protection influence on structural performance. Finally, based on the results obtained, two useful design equations are proposed, allowing the calculation of the load-bearing capacity of single shear timber connections, with or without protection, as a function of fire exposure. Full article

This research examined how ambient pressure impacts the asymmetrical flow effects of fire induced under natural ventilation. Numerical simulations using Fire Dynamics Simulator (FDS) software were conducted, altering the longitudinal positions of fire sources and ambient pressure. The findings reveal that ambient pressure impacts the movement of smoke and air within the tunnel, with both outgoing smoke and incoming air increasing as ambient pressure rises. Asymmetric flow, influenced by the fire source’s longitudinal position, is observed under different ambient pressures. The intensity of these asymmetric flow effects can be characterized by the parameter of induced longitudinal flow mass rate, $m_i$. A dimensionless ambient pressure, P*, was introduced to assess its impact on longitudinal flow’s induction, leading to the development of a predictive model for calculating the $m_i$. While ambient pressure affects the mass flow values of smoke and airflow in tunnel fires under natural ventilation, it has minimal impact on their fundamental distribution patterns. A predictive model has been proposed for the distribution patterns of smoke overflow and air inflow under various ambient pressures. Full article

This study examined the structural and ecological drivers of burn severity during the March 2025 wildfire in Uiseong County, Republic of Korea, with a focus on developing a predictive framework using the differenced Normalized Burn Ratio (dNBR). Seventeen candidate variables were evaluated, among which the forest type, stand age, tree height, diameter at breast height (DBH), and Normalized Difference Vegetation Index (NDVI) were consistently identified as the most influential predictors. Burn severity increased across all forest types up to the 4th–5th age classes before declining in older stands. Coniferous forests exhibited the highest severity at the 5th age class (mean dNBR = 0.3069), followed by mixed forests (0.2771) and broadleaf forests (0.2194). Structural factors reinforced this pattern, as coniferous and mixed forests recorded maximum severity within the 5–11 m height range, while broadleaf forests showed relatively stable severity across 3–21 m but declined thereafter. In the final prediction model, NDVI emerged as the dominant variable, integrating canopy density, vegetation vigor, and moisture conditions. Notably, NDVI exhibited a positive correlation with burn severity in coniferous stands during this early-spring event, diverging from the generally negative relationship reported in previous studies. This seasonal anomaly underscores the need to interpret NDVI flexibly in relation to the forest type, stand age, and phenological stage. Overall, the model results demonstrate that mid-aged stands with moderate heights and dense canopy cover are the most fire-prone, whereas older, taller stands show reduced susceptibility. By integrating NDVI with structural attributes, this modeling approach provides a scalable tool for the spatial prediction of wildfire severity and supports resilience-based forest management under climate change. Full article

A major fire occurred in the wildland–urban interface in southern Portugal, on 13 July 2022, becoming uncontrolled due to weather conditions. This study investigates how atmospheric dynamics increased fire danger in Mainland Portugal during early July 2022. The synoptic circulation from European Centre for Medium-Range Weather Forecasts (ECMWF) analysis and mesoscale conditions from Meso-NH model simulation at 1.5 km resolution revealed atmospheric conditions before and during the fire. Fire risk was assessed using the Fire Weather Index (FWI) from Meso-NH outputs. A blocking pattern was configured by an upper-level low-pressure system in early July, remaining semi-stationary west of Mainland Portugal until 18 July. The counter-clockwise circulation of the cut-off low resulted in dry, warm air advection from North Africa, enhancing fire danger over the Iberian Peninsula. In southern Portugal, a jet-like wind with strong east/southeasterly flow from Gibraltar Strait favored rapid fire spread. This circulation below 1 km altitude from the Mediterranean Sea enhanced fire danger through strong winds, independent of the large-scale blocking pattern. This study presents an atmospheric scenario for evaluating fire danger in Southern Portugal, important for pre-firefighting management that complemented previous studies for the region. Also, high-resolution FWI calculations using Meso-NH emphasized the importance of improved temporal and spatial resolution for fire danger assessment. Full article

Building fires are considered major disasters because of their significant effects on people, property, and the environment. This understanding has led to increased attention on developing preventive measures, particularly through the creation of effective methods for assessing fire risk. However, the effectiveness of these methods relies heavily on detailed physical and functional information of the building and data-driven decision-making. Building Information Modeling (BIM) has proven effective in representing structures, even in three dimensions. When integrated with Geographic Information Systems (GIS), it enhances spatial intelligence, leading to improved decision-making through robust multi-criteria approaches. Hence, this study develops a framework to assess fire risk in an indoor environment that deploys a BIM-based GIS and Multi-Criteria Decision-Making; this is specifically known as Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The developed framework consists of four steps: identifying fire risk parameters, calculating weights, conducting spatial fire risk assessments, and visualizing the results, where the developed concepts are tested and validated. According to the significant findings, the developed framework estimates that 18% of building rooms are at moderate risk, while the compared model identifies only 1%. This considerable difference could potentially arise from the detailed data structure of BIM and the spatial insights gained from GIS. By implementing the designed framework, key fire risk factors can be identified in three dimensions, accompanied by a comprehensive quantitative evaluation platform for fire risks within indoor environments. Full article

This study evaluates the impact of different flame retardants on the mechanical and thermal properties of rigid polyisocyanurate (PIR) foams, focusing on formulations with isocyanate indexes of 335 and 400. The flame retardants tested include triethyl phosphate (TEP), ammonium polyphosphate (APP), aluminium hydroxide (Al(OH)₃), and a combination of APP and Al(OH)₃. FOAMAT^® was used to analyse the foaming kinetics, while further tests assessed density, thermal conductivity, and compression strength. TEP, a liquid flame retardant, was found to reduce peak heat release rate (pHRR) and total heat release significantly, outperforming solid flame retardants. Although solid flame retardants like APP slightly increase start times and gel times due to their non-reactive, filler role, they increase the foam’s density and somewhat limit the effectiveness in reducing flammability. The uneven dispersion and lower compatibility of solid additives may lead to suboptimal improvements in fire resistance. APP displayed dual-phase decomposition, aiding char formation to a degree. Overall, TEP proved most effective in enhancing PIR foam’s fire resistance, demonstrating the advantage of liquid over solid flame retardants in achieving uniform distribution and better integration with the foam matrix, thus optimising thermal insulation and mechanical performance. Full article

Sandwich panels, widely used in factory and warehouse construction, are highly susceptible to fire due to their fragile surfaces and polyurethane-insulated cores. Such structures facilitate rapid fire spread, significantly increasing the risk of extensive thermal damage. Although conventional measures, such as surface pre-wetting, are commonly utilized, their effectiveness is limited due to rapid evaporation. To address this issue, the current study evaluates the effectiveness of compressed air foam (CAF) applied as a pre-application treatment for delaying fire spread. Full-scale fire experiments were conducted to measure temperature variations across sandwich panel surfaces treated under three different conditions: untreated, water-treated, and CAF-treated. Experimental results indicated that CAF effectively formed a stable insulating barrier, maintaining temperatures well below critical thresholds, compared to untreated and water-treated panels. CAF application demonstrated superior thermal protection, reducing internal temperatures by up to 78% compared to untreated conditions and by 67.5% compared to water-treated conditions. These findings underscore the practical importance of adopting CAF pre-application as a proactive fire mitigation strategy, significantly enhancing fire safety standards in industrial and storage facilities constructed with sandwich panels. Full article

With the rapid development of large-space buildings, their fire risk has become increasingly prominent. Conventional fire detection technologies are often limited by spatial height and environmental interference, leading to false alarms, missed detections, and delayed responses. This paper reviews 83 publications to analyze the limitations of conventional methods in large spaces and highlights the advantages of and current developments in image-based fire detection technology. It outlines key aspects such as equipment selection, dataset construction, and target recognition algorithm optimization, along with improvement directions including scenario-adaptive datasets, model enhancement, and adaptability refinement. Research demonstrates that image-based technology offers broad coverage, rapid response, and strong anti-interference capability, effectively compensating for the shortcomings of conventional methods and providing a new solution for early fire warning in large spaces. Finally, future prospects are discussed, focusing on environmental adaptability, algorithm efficiency and reliability, and system integration, offering valuable references for related research and applications. Full article

The ammonia-n-heptane reaction mechanism is essential for simulation of the in-cylinder process for diesel-ignited ammonia engines. To gain insight into the differences in predictive performance among various ammonia-n-heptane reaction mechanisms, four mechanisms were comprehensively evaluated and analyzed based on the modeling of ignition, oxidation, laminar flame propagation and in-cylinder combustion processes. The result shows that only under high ammonia blending ratios and elevated temperatures are discrepancies in predicted ignition delay times observed among the studied reaction mechanisms. Regarding the oxidation process, on the whole, the concerned mechanisms can reasonably predict concentrations of reactants and complete combustion products. However, significant discrepancies exist among the mechanisms in predicting concentrations of intermediate species and other products. For laminar burning velocity, the modeled values from the studied mechanisms are consistent with experimental results under both fuel-lean and -rich conditions. The Wang mechanism exhibits significant deviations from the other three mechanisms in predicting reaction pathways of ammonia and n-heptane. From the perspective of reaction class, the studied mechanisms are similar to each other, to some extent, in the key reactions governing consumption of ammonia and n-heptane. For the engine simulation, the predicted in-cylinder pressure and temperature profiles show minimal variations across different reaction mechanisms. In conclusion, the Fang mechanism can be selected to understand more accurately ignition, oxidation and flame characteristics of ammonia-n-heptane mixtures, while to reduce the engineering computational cost of the engine simulation, the Wang mechanism tends to be a good choice. Full article

Wildfires pose severe threats to ecosystems and human settlements, making early detection and rapid response critical for minimizing damage. The adage—“You fight fire in the first second with a spoon of water, in the first minute with a bucket, and in the first hour with a truckload”—illustrates the importance of early intervention. Over recent decades, significant research efforts have been directed toward developing efficient systems capable of identifying wildfires in their initial stages, especially in remote forests and wildland–urban interfaces (WUIs). This review paper introduces the Special Issue of Fire and is dedicated to advanced approaches to wildfire detection, monitoring, and surveillance. It summarizes state-of-the-art technologies for smoke and flame detection, with a particular focus on their integration into broader wildfire management systems. Emphasis is placed on distinguishing wildfire monitoring (the passive collection of data using various sensors) from surveillance (active data analysis and action based on visual information). The paper is structured as follows: a historical and theoretical overview; a discussion of detection validation and available datasets; a review of current detection methods; integration with ICT tools and GIS systems; the identification of system gaps; and future directions and emerging technologies. Full article

The combustion of liquid fuels that have leaked into inert porous media, such as sand, is a critical issue for industrial safety and fire risk assessment. Despite its importance, the complex influence of porous media on the combustion process, particularly the governing mechanisms of flame morphology and heat release, remains poorly understood, hindering accurate hazard prediction. This study addresses this gap by systematically investigating the combustion characteristics of 92# gasoline on quartz sand substrates with thicknesses ranging from 0 to 4 cm. Through a series of controlled laboratory experiments, key parameters including mass loss rate, heat release rate (HRR), and flame morphology were quantified. The findings reveal that, unlike the classical three-stage combustion of pool fires, the presence of porous media introduces a “slow burning period,” resulting in a unique four-stage combustion mode. The sand layer significantly suppresses combustion intensity, with the dimensionless heat release rate (Q*) being proportional to the dimensionless layer thickness (d*) raised to the power of −2.54. Crucially, flame height was found to be governed not by the HRR, but by a competition between the capillary effect (driving upward fuel transport) and the thermal effect (insulation and heat absorption). Based on this mechanism, a novel flame height prediction model was developed, which showed excellent agreement with 23 experimental datasets (R² = 0.92, average relative error 1.72%). This study elucidates the core physical mechanisms governing liquid fuel combustion in porous media. The proposed model provides a robust theoretical foundation for predicting fire development and assessing the risks associated with leaked fuel fires, offering a valuable tool for safety engineering and emergency response. Full article

Background: Rural fires represent a significant environmental and socioeconomic challenge in Mediterranean regions, particularly in Portugal, which experiences some of the highest fire incidences in Europe. Understanding the temporal evolution of fire occurrences and their relationship with climatic parameters is crucial for developing effective fire management strategies and adapting to climate change impacts. This study aims to analyze the evolution of rural fire occurrences in Guimarães, northern Portugal, during the period 1980–2020, and to investigate their relationship with climatic parameters, specifically temperature and precipitation patterns. Methods: We analyzed a comprehensive dataset of rural fire occurrences and burnt areas in the Guimarães municipality from 1980 to 2020, along with corresponding climatic data including mean annual temperature and total annual precipitation. Statistical analyses included descriptive statistics, Mann–Kendall trend analysis, Pearson and Spearman correlation analyses, and multiple linear regression modeling. The relationships between fire variables and climatic parameters were examined using both parametric and non-parametric approaches. Results: The analysis revealed significant temporal trends and climate–fire relationships. Mean annual temperature showed a statistically significant increasing trend (Mann–Kendall Z = 3.055, p = 0.002) with a Sen’s slope of 0.032 °C/year, representing approximately 1.3 °C warming over the 40-year period. Rural fire occurrences demonstrated a positive correlation with mean temperature (Pearson r = 0.459, p = 0.003; Spearman ρ = 0.453, p = 0.003), while total burnt area also showed significant positive correlation with temperature (Pearson r = 0.426, p = 0.005; Spearman ρ = 0.466, p = 0.002). Precipitation showed no significant correlation with fire variables. Multiple regression models explained 23.1% of the variance in fire occurrences and 18.3% of the variance in burnt area, with temperature being the primary climatic predictor. Conclusions: The study provides evidence of a significant warming trend in Guimarães over the past four decades, which is positively associated with increased rural fire activity. The consistent relationship between temperature and fire variables suggests that continued climate warming may lead to increased fire risk in the region. These findings have important implications for fire management strategies and climate adaptation planning in northern Portugal. Full article

To address the difficulty frontline commanders face in accurately perceiving fireground risks during the early stages of oil storage tank fires, in this study, we propose a method that integrates complex network theory with a multi-source information fusion approach based on cloud models and Dempster-Shafer (D-S) evidence theory for situational analysis and dynamic perception. Initially, the internal evolution of accident scenarios within individual tanks is modeled as a single-layer network, while scenario propagation between tanks is represented through inter-layer connections, forming a multi-layer complex network for the storage area. The importance of each node is evaluated to assess the risk level of scenario nodes, enabling preliminary situational awareness, with limited reconnaissance information. Subsequently, the cloud model’s capability to handle fuzziness is combined with D-S theory’s strength in fusing multi-source data. Multi-source heterogeneous information is integrated to obtain the confidence levels of key nodes across low, medium, and high-risk categories. Based on these results, high-risk scenarios in oil storage tank emergency response are dynamically adjusted, enabling the updating and prediction of accident evolution. Finally, the proposed method is validated using the 2015 Gulei PX plant explosion case study. The results demonstrate that the approach effectively identifies high-risk scenarios, enhances dynamic situational perception, and is generally consistent with actual accident progression, thereby improving emergency response capability. Full article

Green Firebreaks (GFBs), strips of strategically placed low-flammability vegetation, represent a proactive complement to other approaches to wildfire management. This review, which summarises the literature to elucidate GFBs’ potential to reduce fire spread and intensity, revealed that empirical studies validating their effectiveness remain scarce. It also revealed that comparisons of GFB techniques are challenging due to spatial and temporal complexity combined with inconsistent methods and terminology. Several researchers note that GFB effectiveness requires that their design is appropriate for the site conditions. Furthermore, GFBs are not a stand-alone solution to the wildfire problem, and a lack of consideration for trade-offs may undermine their effectiveness, particularly under extreme weather conditions. As climate change intensifies drought and heat, vegetation moisture content must be a key design factor given that even low-flammability vegetation becomes fuel under extreme drought conditions. In addition, poorly designed GFBs may unintentionally alter wind dynamics and increase ember transport and fire spread. There is a broad consensus in the literature that appropriately designed GFBs can complement wildfire management while providing additional biodiversity and other benefits. To achieve their potential, research is required for GFB designs to be site-specific, responsive to trade-offs, and effective in providing multiple benefits under different climate change scenarios. Full article

The effects of wildfires and prescribed burnings on soil are highly variable. In order to evaluate the effects of different burning intensities on soil properties, a surface-controlled burn of undisturbed soil monoliths was carried out by combining temperatures (50 and 80 °C) and residence times (12 and 24 min). The effects of this burning gradient are evaluated at two soil depths (0–1 and 1–3 cm), with time (just after burning or immediate effects, T0, and five months later, T5), as well as the influence of ash (presence or absence). The results indicate that most soil properties were affected by the burning gradient applied only in the most superficial cm (0–1 cm), with few effects at greater depths. The most intense burn had the strongest immediate impact, reducing soil organic carbon, recalcitrant organic carbon, and microbial biomass carbon, as well as increasing the labile organic carbon and the microbial activity. On the other hand, this burning caused a strong decrease in soil water repellency at a 0–1 cm depth and increased it at 1–3 cm. In contrast, medium-intensity burning caused the opposite effect, increasing water repellency at the soil surface and reducing it at 1–3 cm. As a result of the mineralization of organic matter, the EC and pH increased significantly in all burning combinations and both soil depths studied. After five months (T5), several of these parameters tended to approach the values of unburned soil. Full article

This study numerically investigated how varying pulse durations of water mist systems influence fire dynamics in long, narrow underground enclosures. A Fire Dynamics Simulator (FDS) model was built to represent a pulse-actuated, fine water mist test rig, and simulations of oil pan fires were performed to quantify the evolution of temperature and radiative heat flux. Results show that an 8 s spray followed by an 8 s pause yields the most effective suppression cycle. When spray and pause durations are equal, periodic momentum exchange resonates with the buoyant plume, intensifying the mixing of gas and enhancing cooling near the fire seat. Compared with continuous discharge, pulsed mist generates stronger buoyancy-driven disturbances and delivers superior performance in terms of local heat’s extraction and extinguishment. This study has, for the first time, determined the optimal pulse cycle (8 s spray/8 s stop) for oil pool fires in narrow and long underground spaces through FDS simulation, and revealed the enhancement effect of the gas disturbance resonance mechanism on fire suppression efficiency. Full article

With the increasing frequency of global forest fires, research on the spread of forest fires has become one of the important directions in fire research. In order to improve the accuracy of surface fire spread simulation, based on relevant forest resources map preprocessing technologies, this paper takes the triangle mesh division idea of Tri-14 CA model for crowd evacuation and the Wang Zhengfei’s improved forest surface fire spread speed model as the basis, obtains the basic equation set of forest fire spread speed in 14 directions, and establishes the spatio-temporal spread mathematical model of forest surface fire. Based on the above, a software platform is established by applying computer technology to realize the calculation and visualization simulation of forest fire spread. Combined with examples, the correctness and practicability of the model software are illustrated, aiming to provide information support for forest disaster emergency departments. Full article

This study focuses on firefighters’ relationship with different types of change in their profession and what barriers and facilitators might contribute to how they respond. Informed by the Force Field analysis of change, interviews were conducted to better understand what specific barriers and facilitators contribute to their views on types of change and the level of influence they carried. Twenty-five interviews were conducted with firefighters from a variety of backgrounds, including different ages, genders, ranks, and experience levels for both career and volunteer firefighters. Thematic analysis identified different responses to four common rationales that helped to explain the acceptance or dismissal of changes. These were as follows: (1) openness or apprehension towards change; (2) the results of a cost–benefit analysis that considered financial and manpower limits, perceived legitimacy of the problem, and efficacy of the solution; (3) reference to past experiences with changes that had failed or succeeded; and (4) trusted messengers that respected the chain of command were preferred. These themes are applicable across multiple types of changes, including technological and cultural adaptation. However, they also reveal challenges that may emerge due to friction with firefighters’ professional identities and traditional masculine norms. The patterns identified here can help to inform future efforts to implement changes and to anticipate likely points of friction or motivation that can be leveraged. Full article

Crown fire hazard assessment and behavior prediction in dwarf pine (Pinus pumila) forests are dictated by the amount of canopy fuel available, topography, and weather. In this study, we collected data on CFL (available canopy fuel load), CBD (canopy bulk density), and CBH (canopy base height) through the destructive sampling of dwarf pine trees in the Greater Khingan Mountains of Northeast China. Allometric equations were developed for estimating the canopy’s available biomass, CFL, and CBD to support the assessment of canopy fuel. Three burning scenarios were designed to investigate the impact of various environmental parameters on fire behavior. Our findings indicated that the average CFL of a dwarf pine was 0.36 kg·m⁻², while the average CBD was measured at 0.17 kg·m⁻³. The vertical variation trends of both CFL and CBD exhibited consistency, with values increasing progressively from the bottom to the top of the tree crown. Fire behavior simulations indicated that the low CBH of dwarf pine trees increased the likelihood of crown fires. Various factors, including wind speed, slope, and CBH, exerted considerable influence on fire behavior, with wind speed emerging as the most critical determinant. Silvicultural treatments, such as thinning and pruning, may effectively reduce fuel loads and elevate the canopy base height, thereby decreasing both the probability and intensity of crown fires. Full article

Despite increased focus on resilient planning and construction design in areas prone to wildfire impacts, recent research has found inconsistent approaches, a lack of evidence-based performance criteria, and limited suitable code-based verification methods for use in wildfire contexts. These limitations serve to reduce the potential effectiveness of measures intended to improve wildfire community and build resilience. The lack of suitable verification methods is particularly problematic in Australia, where complex building code requirements associated with enhanced wildfire resilience have been extended to hospitals, child care facilities, schools, and other assembly buildings. To address this issue, this paper proposes the Wildfire Expected Risk to Life and Property (WERLP) verification method. As a holistic absolute probabilistic verification method, WERLP can be applied to both building and urban design contexts within the Australian jurisdiction. The application of WERLP is demonstrated using the case study of a new hospital development. Full article

The disintegration of near-limit flames propagating through the gap of Hele–Shaw cells has recently become a subject of active research. In this paper, the flamelets resulting from the disintegration of the continuous front are interpreted in terms of the Zeldovich flame balls stabilized by volumetric heat losses. A complicated free-boundary problem for 2D self-drifting near circular flamelets is reduced to a quasi-1D model. The quasi-1D formulation is then utilized to obtain the locus of the flamelet velocity, size, heat losses, and Lewis numbers at which the self-drifting flamelets may exist. Full article

Forest fires pose severe ecological, climatic, and socio-economic threats, destroying habitats and emitting greenhouse gases. Early and timely warning is particularly challenging because fires often originate from small-scale, low-temperature ignition sources. Traditional monitoring approaches primarily rely on single-source satellite imagery and empirical threshold algorithms, and most forest fire monitoring tasks remain human-driven. Existing frameworks have yet to effectively integrate multiple data sources and detection algorithms, lacking the capability to provide continuous, automated, and generalizable fire monitoring across diverse fire scenarios. To address these challenges, this study first improves multiple monitoring algorithms for forest fire detection, including a statistically enhanced automatic thresholding method; data augmentation to expand the U-Net deep learning dataset; and the application of a freeze–unfreeze transfer learning strategy to the U-Net transfer model. Multiple algorithms are systematically evaluated across varying fire scales, showing that the improved automatic threshold method achieves the best performance on GF-4 imagery with an F-score of 0.915 (95% CI: 0.8725–0.9524), while the U-Net deep learning algorithm yields the highest F-score of 0.921 (95% CI: 0.8537–0.9739) on Landsat 8 imagery. All methods demonstrate robust performance and generalizability across diverse scenarios. Second, data-driven scheduling technology is developed to automatically initiate preprocessing and fire detection tasks, significantly reducing fire discovery time. Finally, an integrated framework of multi-source remote sensing data, advanced detection algorithms, and a user-friendly visualization interface is proposed. This framework enables all-weather, fully automated forest fire monitoring and early warning, facilitating dynamic tracking of fire evolution and precise fire line localization through the cross-application of heterogeneous data sources. The framework’s effectiveness and practicality are validated through wildfire cases in two regions of Yunnan Province, offering scalable technical support for improving early detection of and rapid response to forest fires. Full article