Fire, Volume 6, Issue 8 (August 2023) – 45 articles

Regulation (EU) No 305/2011 lays down harmonized conditions for marketing construction products in the European Union. One of its consequences has been the introduction of the product standard EN 50575 and standard EN 130501-6, concerning power, control, and communication cables permanently installed in buildings to prevent the risk of a fire and its consequences. EN 13501-6 provides the reaction to fire classifications for cables, the test methods to be performed, the requirements to meet a specific reaction to fire, and additional classifications for smoke production, flaming droplets, and acidity. It requires EN 60754-2 as the technical standard to assess acidity, and it defines three classes: a₁, a₂, and a₃ (the less performant). Due to the release of hydrogen chloride during the combustion, acidity is the weak point of PVC cables, which are not yet capable of achieving the a₁ or a₂ classes required for specific locations according to fire risk assessments. EN 13501-6 does not include EN 60754-1, used in harmonized standards outside the scope of Regulation (EU) No 305/2011. EN 60754-1 and EN 60754-2 are common standards for determining halogen gas content, and acidity/conductivity, respectively. While they involve the same type of test apparatus, they differ in heating regimes, final temperatures, and detection methods. In particular, EN 60754-2 requires testing at temperatures between 935–965 °C in the tube furnace, where the sample burns, the smoke is collected in bubblers, and pH and conductivity are measured as an indirect assessment of acidity. On the other hand, the temperature regime of EN 60754-1 is a gradual heating run, followed by isothermal heating at 800 °C. The paper shows that when potent acid scavengers are used in PVC compounds, performing EN 60754-2 with the thermal profile of EN 60754-1 or at 500 °C in isothermal conditions, the evolution of hydrogen chloride changes significantly up to 10 times less than the test performed in isothermal at 950 °C. The reason lies behind the kinetic of hydrogen chloride release during the combustion of PVC compounds: the higher the temperature or faster the heat release, the quicker hydrogen chloride evolution and the lower the probability for the acid scavenger to trap it. Thus, these findings emphasize the “fragility” of EN 60754-2 as a tool for assessing risks associated with the release of hydrogen chloride during fires. Full article

Electric Vehicles (EVs) offer a promising solution to reduce the environmental impact compared to internal combustion engine vehicles. However, EV adoption in Australia has been hindered by concerns over fire safety. This study aims to comprehensively analyse EV fire risks and trends in Australia, including those related to charging stations and lithium-ion batteries. The research utilises secondary data from various reputable sources to develop statistical forecasting models, which estimate that Australia will have approximately 1.73 million EVs by 2030 and 15.8 million by 2050. The study reveals an average EV fire frequency of six fires per million EVs in Australia, aligning with the global average. Consequently, Australia is expected to experience 9 to 10 EV fire incidents annually in 2030, 37 to 42 EV fire incidents annually in 2040, and 84 to 95 EV fire incidents annually in 2050. To address these risks, an EV fire risk control framework is considered to identify and recommend appropriate measures for life safety, lithium-ion batteries, charging, EV handling, and EV locations. This research provides vital evidence for regulators, policymakers, and the fire industry to effectively manage EV fire risks and enhance preparedness for the growing EV market in Australia. Full article

Semiclosed tunnels are very common in engineering construction. They are not connected, so they easily accumulate heat. Once a fire breaks out in a semiclosed tunnel, the route for rescue workers to enter is limited, so it is tough to get close to the fire source. In this paper, taking a mine excavation roadway with local pressure ventilation as an example, the temperature field distribution and water spray fire prevention characteristics of the excavation roadway face were studied using numerical simulation and theoretical analysis. This paper provides an explanation of a dynamics-based smoke management method for water spraying in a semiclosed tunnel as well as the equilibrium relationship between droplet drag force and smoke buoyancy. A method was first developed to calculate the quantity of smoke blockage based on the thickness of the smoke congestion. The local ventilation and smoke movement created a circulating flow in the excavation face, which was discovered by investigating the velocity and temperature fields of the excavation face. The size of the high-temperature area and the pattern of temperature stratification varied due to this circulating flow. When local ventilation and sprinkler systems were operating simultaneously, when the volume of smoke was small, the smoke avoided the majority of the water spray effect with the circulation flow; however, when the volume of smoke was large, the effect of the circulation flow decreased and the smoke gathered close to the sprinkler head. At this time, the blocking effect of the water spray was significant. The mean square error analysis revealed that activating the sprinkler had the most significant cooling impact on the wall on one side of the air duct. Full article

This work analyzes a new indoor laboratory dataset looking at early fire indicators in controlled and realistic experiments representing different incipient fire scenarios. The experiments were performed within the constraints of an indoor laboratory setting using multiple distributed sensor nodes in different room positions. Each sensor node collected data of particulate matter (PM), volatile organic compounds (VOCs), carbon monoxide (CO), carbon dioxide (CO${}_2$), hydrogen (H${}_2$), ultraviolet radiation (UV), air temperature, and humidity in terms of a multivariate time series. These data hold immense value for researchers within the machine learning and data science communities who are keen to explore innovative and advanced statistical and machine learning techniques. They serve as a valuable resource for the development of early fire detection systems. The analysis of the collected data was carried out depending on the Manhattan distance between the fire source and the sensor node. We found that especially larger particles (>0.5 $\mathsf{\mu }$m) and VOCs show a significant dependency with respect to the intensity as a function of the Manhattan distance to the source. Moreover, we observed differences in the propagation behavior of VOCs, PM, and CO, which are particularly relevant in incipient fire scenarios due to the presence of strand propagation effects. Full article

Externally bonded fiber-reinforced polymers (FRPs) have been widely used for strengthening and retrofitting applications. However, their efficacy is hindered by the poor resistance of their epoxy resins to elevated temperatures and their limited compatibility with concrete substrates. To address these limitations, fabric-reinforced cementitious matrix (FRCM), also known as textile reinforced mortar (TRM), systems have emerged as an alternative solution. In this study, experimental tests were performed on concrete cylinders confined with FRCM systems that consisted of mineral mortar and poliparafenilenbenzobisoxazole fabric (PBO). The cylinders with concrete strengths of 30, 45, and 70 MPa, were confined with one or two FRCM layers, and were subjected to different target temperatures (100, 400, and 800 °C). The experimental results highlighted the confinement effect of FRCMs on the compressive strength of the tested cylinders. Cylinders exposed to 100 °C exhibited a slight increase in their compressive strength, while no specific trend was observed in the compressive strength of cylinders heated to 400 °C. Specimens heated up to 800 °C experienced a significant reduction in strength, reaching up to 82%. Full article

A deeper understanding of the influence of fine-scale fuel patterns on fire behavior is essential to the design of forest treatments that aim to reduce fire hazard, enhance structural complexity, and increase ecosystem function and resilience. Of particular relevance is the impact of horizontal and vertical forest structure on potential tree torching and large-tree mortality. It may be the case that fire behavior in spatially complex stands differs from predictions based on stand-level descriptors of the fuel distribution and structure. In this work, we used a spatially explicit fire behavior model to evaluate how the vertical and horizontal distribution of fuels influences the potential for fire to travel from the surface into overstory tree crowns. Our results support the understanding that crown fuels (e.g., needles and small-diameter branchwood) close to the surface can aid in this transition; however, we add important nuance by showing the interactive effect of overstory horizontal fuel connectivity. The influence of fuels low in the canopy space was overridden by the effect of horizontal connectivity at surface fire-line intensities greater than 1415 kW/m. For example, tree groups with vertically continuous fuels and limited horizontal connectivity sustained less large-tree consumption than tree groups with a significant vertical gap between the surface and canopy but high-canopy horizontal connectivity. This effect was likely the result of reduced net vertical heat transfer as well as decreased horizontal heat transfer, or crown-to-crown spread, in the upper canopy. These results suggest that the crown fire hazard represented by vertically complex tree groups is strongly mediated by the density, or horizontal connectivity, of the tree crowns within the group, and therefore, managers may be able to mitigate some of the torching hazard associated with vertically heterogenous tree groups. Full article

To accurately simulate realistic pedestrian evacuation from a fire, a cellular automaton model of the dynamic changes in pedestrian movement parameters is developed in conjunction with fire dynamics software. The fire dynamics software is used to simulate the spread of smoke within the scene to obtain visibility and CO concentration data within the scene. We imported the smoke data into the cellular automata and adjusted the pedestrian movement speed over time, resulting in simulation data that closely align with reality. The results show that for the single-room scenario, as pedestrian density increased from 0.1 to 0.5 persons per square meter ($\mathrm{p}/{\mathrm{m}}^2$), the influence of the percentage of pedestrians familiar with their location on evacuation efficiency decreased from 44.93% to 24.52%. Conversely, in the multi-room scenario, it increased from 23.68% to 38.79%. The proportion of pedestrians less affected by smoke decreases and stabilizes as the CO yield increases. In the single-room scenario, when the CO yield is below 10%, the crowd with a low percentage of pedestrians familiar with the site is more affected by smoke than those with a high percentage. In the multi-room scenario, the victimization rate of the crowd follows an increasing-then-decreasing curve, ultimately stabilizing with changes in CO yield. Full article

Accurate predictions of daily wildfire growth rates are crucial, as extreme wildfires have become increasingly frequent in recent years. The factors which determine wildfire growth rates are complex and depend on numerous meteorological factors, topography, and fuel loads. In this paper, we have built upon previous studies that have mapped daily burned areas at the individual fire level around the globe. We applied several Machine Learning (ML) algorithms including XGBoost, Random Forest, and Multilayer Perceptron to predict daily fire growth rate based on meteorological factors, topography, and fuel loads. Our best model on the entire dataset obtained a 1.15 km² MAE. The ML model obtained a 90% accuracy when predicting whether a fire’s growth rate will increase or decrease the following day, compared to 61% using a logistic regression. We discuss the central factors that determine wildfire growth rate. To the best of our knowledge, this study is the first to perform such analyses on a global dataset. Full article

The process of combustion of a liquid fuel layer (diesel, kerosene, gasoline, separated petroleum, and oil) in the presence of CO₂ hydrate has been studied. These fuels are widely used in engineering, which explains the great interest in effective methods of extinguishing. Extinguishing liquid fuels is quite a complicated scientific and technical task. It is often necessary to deal with fire extinction during oil spills and at fuel burning in large containers outdoors and in warehouses. Recently, attention to new extinguishing methods has increased. Advances in technology of the production, storage, and transportation of inert gas hydrates enhance the opportunities of using CO₂ hydrate for extinguishing liquid fuels. Previous studies have shown a fairly high efficiency of CO₂ hydrate (compared to water spray) in the extinction of volumetric fires. To date, there are neither experimental data nor methods for determining the dissociation rate of CO₂ hydrate powder at the time of the gas hydrate fall on the burning layer of liquid fuel. The value of the dissociation rate is important to know in order to determine the temperatures of stable combustion and, accordingly, the mass of CO₂ hydrate required to extinguish the flame. For the first time, a method jointly accounting for both the combustion of liquid fuel and the dissociation rate of the falling powder of gas hydrate at a negative temperature is proposed. The combustion stability depends on many factors. This paper defines three characteristic modes of evaporation of a liquid fuel layer, depending on the prevalence of vapor diffusion or free gas convection. The influence of the diameter and height of the layer on the nature of fuel evaporation is investigated. Full article

The generation of biomass residues in different productive activities of rural communities in Mexico represents an area of opportunity for the generation of bioenergy for various purposes. Solid biofuels (SBF), for example, are an alternative for the exploitation of these residues. The present study shows a comprehensive proposal for the analysis of residues of Pinus spp. generated by the artisanal sector of a rural community in Mexico. The proposal is based on four stages: a) characterization of the physico-chemical and functional properties of the residues, by Scanning Electron Microscopy (SEM), Infrared (FTIR) and Raman Spectroscopy, Thermogravimetry (TGA-DTG), determining the calorific coefficient and polymeric compounds present by fiber analysis; (b) spatial, temporal and dimensional analysis of the waste generated in the town studied; (c) assessment of the energy potential available in space and time; (d) definition of guidelines for the management of solid biofuels for the community through collection, processing and final disposal centers. The results of the assessment of timber residue from 50 artisan workshops that represent 25% of the total in the community show that the identified heating value of the dry residue ranges from 17.6 MJ/kg to 18.1 MJ/kg, attributed to the presence of polymeric compounds such as cellulose, hemicellulose and lignin, the latter in the order of 28%, which contributes to a high energy potential, and whose compounds were identified by TGA-DTG analysis, FTIR, SEM and fiber analysis. The energy potential was estimated at approximately 7 TJ/year for the analyzed workshops. In which case, the economic savings obtained from unburned firewood would amount to about $20,000 USD/year. As regards the reduction in firewood consumption due to the use of residues for energy purposes, about 350 Tn/year would be mitigated, which would reduce the community’s emissions by more than 76 TnCO₂/year. A strategic management proposal was also established, aimed at providing spaces for the collection, processing and final disposal of solid biofuels from wood residues, which in sum represent an energy alternative that is sustainable in environmental, economic and social terms, for the same community. Full article

The soot produced by fossil fuel combustion affects climate and human health, and the ethylene laminar flame is a crucial research object of soot generation. After verifying the accuracy of the numerical calculation model by comparing experimental data, the impact of changes in inlet flow rate and fuel flow composition operating conditions on the generation of soot were compared and analyzed. The calculated results obtained are consistent with the experimental data in terms of distribution trend. The deviation of the calculated peak integral smoke volume fraction is only 5%. Under the operating conditions set in this study, increasing the volume flow rate of the accompanying air will increase the volume fraction of soot generated by the ethylene laminar diffusion flame. Increasing the fuel volume flow rate will first increase and then decrease the volume fraction of soot. Full article

Among various calamities, conflagrations stand out as one of the most-prevalent and -menacing adversities, posing significant perils to public safety and societal progress. Traditional fire-detection systems primarily rely on sensor-based detection techniques, which have inherent limitations in accurately and promptly detecting fires, especially in complex environments. In recent years, with the advancement of computer vision technology, video-oriented fire detection techniques, owing to their non-contact sensing, adaptability to diverse environments, and comprehensive information acquisition, have progressively emerged as a novel solution. However, approaches based on handcrafted feature extraction struggle to cope with variations in smoke or flame caused by different combustibles, lighting conditions, and other factors. As a powerful and flexible machine learning framework, deep learning has demonstrated significant advantages in video fire detection. This paper summarizes deep-learning-based video-fire-detection methods, focusing on recent advances in deep learning approaches and commonly used datasets for fire recognition, fire object detection, and fire segmentation. Furthermore, this paper provides a review and outlook on the development prospects of this field. Full article

In recent years, changes in climate, land cover, and sociodemographic dynamics have created new challenges in wildfire management. As a result, advanced and integrated approaches in wildfire science have emerged. The objective of our study is to use geospatial analysis to identify strategic responses to wildfires in the Tangier-Tetouan-Al Hoceima (TTA) region, widely reputed to exhibit the most significant incidences of wildfires in Morocco. We adopted a combined approach, using burned area products (Fire_CCI51: 2002–2020) from the Moderate Resolution Imaging Spectroradiometer (MODIS) and active fires from the Fire Information for Resource Management System (FIRMS: 2001–2022) and processing them with spatiotemporal statistical methods: optimized hotspot analysis (OHA) and emerging hotspot analysis (EHA). The main findings indicate that the TTA region recorded an average of 39.78 km²/year of burned areas, mostly located in forests (74%), mainly cork oak and matorral stands (50%). The OHA detected hotspots covering 2081 km², with 63% concentrated in the provinces of Chefchaouen and Larache. Meanwhile, clusters of EHA extended over 740 km² and were composed of the oscillating coldspot (OCS) and oscillating hotspot (OHS) patterns at 50% and 30%, respectively. Additionally, an average of 149 fires/year occurred, located mostly in forests (75%), mainly cork oak and matorral stands (61%). The OHA detected active fire hotspots covering 3904 km², with 60% located in the provinces of Chefchaouen and Larache. Clusters of EHA over 941 km² were composed of the oscillating hotspot (OHS) and new hotspot (NHS) patterns at 57% and 25%, respectively. The prevalence of the oscillating and new models mirrors, respectively, the substantial fluctuations in wildfires within the region alternating between periods of high and low wildfire activities and the marked increase in fires in recent times, which has occasioned the emergence of novel hotspots. Additionally, we identified six homogeneous wildfire zones to which we assigned three strategic responses: “maintain” (73% of the territory), “monitor and raise awareness” (14% of the territory), and “reinforce” (13% of the territory). These strategies address current wildfire management measures, which include prevention, risk analysis, preparation, intervention, and rehabilitation. To better allocate firefighting resources, strategic responses were classified into four priorities (very high, high, medium, and low). Last, the wildfire zoning and strategic responses were validated using burned areas from 2021 to 2023, and a global scheme was suggested to assess the effectiveness of future wildfire measures. Full article

Flame recognition is an important technique in firefighting, but existing image flame-detection methods are slow, low in accuracy, and cannot accurately identify small flame areas. Current detection technology struggles to satisfy the real-time detection requirements of firefighting drones at fire scenes. To improve this situation, we developed a YOLOv5-based real-time flame-detection algorithm. This algorithm can detect flames quickly and accurately. The main improvements are: (1) The embedded coordinate attention mechanism helps the model more precisely find and detect the target of interest. (2) We advanced the detection layer for small targets to enhance the model’s associated identification ability. (3) We introduced a novel loss function, α-IoU, and improved the accuracy of the regression results. (4) We combined the model with transfer learning to improve its accuracy. The experimental results indicate that the enhanced YOLOv5′s mAP can reach 96.6%, 5.4% higher than the original. The model needed 0.0177 s to identify a single image, demonstrating its efficiency. In summary, the enhanced YOLOv5 network model’s overall efficiency is superior to that of the original algorithm and existing mainstream identification approaches. Full article

Assessing the characteristics of fuel flammability during fire is of major significance regarding fire intensity and fire spread control. Under the background of shifting forest composition from heliophytic to mesophytic species in mixed-oak forests, our objective is to determine the impacts of species-driven changes in fuel flammability characteristics and the specific relationships between fuel ignition variations at the species level. Oak and maple fuels were collected from ninety-four plots established in Zaleski State Forest, Ohio. A total of 30 combustion samples were separated (15 oak samples and 15 maple samples), with each combustion sample weighing 20 g to ignite under a laboratory fume hood. Our results determined that oak fuel showed significantly higher flame temperatures than maple fuel, and the fuel consumption and combustion duration time both varied between oak and maple fuel. These findings indicated that the shift from oak forest to mesophytic species could change a fire’s behavior. Combined with the cooler, moister, and less-flammable forest conditions generated by these mesophytic species, fires may not be able to reach their historical fire intensities, suggesting that updated data and new insights are needed for fire management. Full article

This study uses a combined research approach based on remote-sensing and numerical modeling to quantify the effects of burned areas on the surface climate in the two Brazilian biomes most affected by fires: the tropical savanna and the Amazon rainforest. Our estimates indicate that between 2007 and 2020, approximately 6% of the savanna and 2% of the rainforest were burned on average. Non-parametric regressions based on 14-year climate model simulations indicate that latent heat flux decreases on average by approximately 0.17 W m⁻² in the savanna and 0.60 W m⁻² in the rainforest per each 1 km² burned, with most of the impacts registered during the onset of the wet season. Sensible and ground heat fluxes are also impacted but at less intensity. Surface air is also warmer and drier, especially over rainforest burned sites. On average, fire reduced gross primary production in the savanna and rainforest by 12% and 10%, respectively, in our experiments. Full article

Forest fires are becoming a more significant problem in Central Europe, but their danger is not as high as that in Southern Europe. The exception, however, is forest fires occurring in disturbed areas (windthrow and bark beetle outbreak areas), which are comparable in severity and danger to the most serious forest fires. In this study, we describe the current situation in Central European countries in terms of fire protection for disturbed areas in managed forests and forest stands left to spontaneously develop (secondary succession). If a country has regulations and strategies in this area, they are often only published in the local language. In this review, we combine information from all Central European countries and summarize it in a unified international language, provide an opportunity for local authorities to express their own experiences, and integrate data from worldwide scientific research. Thus, this paper may be considered a universal guide for managing fire protection and preparedness in disturbed areas and can serve as a reference for the establishment of strict legislative rules at the state level. These laws must be obligatory for all stakeholders in individual countries. The motivation for this study was two large forest fires in an area left to spontaneously develop in the Bohemian Switzerland National Park in the Czech Republic and Harz Mountains in Germany in the summer of 2022. These incidents revealed that fire prevention legislation was inadequate or nonexistent in these areas. The strategy of the European Union is to increase the size of protected areas and spontaneous development areas. Therefore, we consider it necessary to provide governments with relevant information on this topic to create conditions for better management of these destructive events. Full article

A fire whirl, a unique fire behavior, occurs when a vertical vortex of flames skyrockets due to specific surrounding temperatures and thermal gradient conditions during a fire. Compared with conventional fire plumes, fire whirls exhibit a higher air entrainment rate, tangential velocity, and axial velocity, thus presenting greater risks and destructive capabilities. Thus, studying the combustion characteristics of fire whirls becomes necessary. This experiment employed a small-scale, fixed-frame fire whirl generator. We investigated how varying air-inlet widths and fuel pan diameters influence the fire whirl’s combustion characteristics. Experimental images indicated a negative correlation between the fire whirl’s flame height and the air-inlet width, and a positive correlation with the fuel pan diameter. Our findings showed that the burning rate of the fire whirl during the quasi-steady-state combustion phase initially increased and then decreased as the air-inlet width expanded, peaking at a width of 7 cm. The data demonstrated a corresponding power-law relationship between the fire whirl’s dimensionless flame height and excess temperature. Ultimately, our results indicated a positive correlation between the 2/5 power of the fire whirl’s dimensionless heat release rate and the dimensionless flame height. The ratios of maximum to mean flame height and mean to continuous flame height are 1.35 and 1.5, respectively. Significantly, these ratios remain unaffected by the air-inlet width, fuel pan diameter, environmental temperature, and heat release rate. Full article

There is a complex interaction between lightning-caused fire behavior and the flora and fauna of the forest, which involves the influence of a large number of ecological factors. However, more comprehensive simulation studies under multi-system interactions between lightning ignition, forest fire spread, and animal behavior are not well developed. In this paper, we propose a forest ecosystem model based on the Agent-based modelling approach to explore the detailed linkages between different forms of lightning-caused fires and forest biodiversity. The model simulates the lightning ignition, fire spread, vegetation burning and recovery, and multi-species-survival dynamics. The experimental results show the sensitivity between environmental parameters and the magnitude of lightning-caused fires, and the beneficial ecological consequences of lightning-caused fires on forest ecosystems. By exploring detailed linkages between different forms of lightning-caused fires and forest biodiversity, we provide theoretical insights and reference suggestions for forest system governance and biodiversity conservation. Full article

The functional group structures of coal molecules are one of the most important factors affecting spontaneous combustion. However, it is difficult to determine the exact effects of such structures. Extraction technology is able to modify the functional groups in coal as a means of inhibiting spontaneous combustion reactions. The present work extracted coal from the Caojiatan mine in northern Shaanxi, China, with various solvents. The extraction effectiveness of these solvents was found to decrease in the order of dioctyl sulfosuccinate (AOT) > water > n-hexane > cyclohexane + AOT + ethanol > cyclohexane > ethanol > methanol. With the exception of the AOT, the concentration of functional groups in the extracted coal was decreased compared with that in a control specimen extracted using only water. Ethanol, n-hexane, and methanol provided the optimal extraction efficiencies in terms of capturing coal molecules with aromatic structures, aliphatic structures, and oxygen-containing groups, respectively. The results of this work are expected to assist in future research concerning the extraction of coal molecules with specific functional groups. This work also suggests new approaches to the active prevention and control of spontaneous combustion during the mining, storage, and transportation of coal. Full article

Targeting the challenges in the risk analysis of laboratory fire accidents, particularly considering fire accidents in Chinese universities, an integrated approach is proposed with the combination of association rule learning, a Bayesian network (BN), and fuzzy set theory in this study. The proposed approach has the main advantages of deriving conditional probabilities of BN nodes based on historical accident data and association rules (ARs) and making good use of expert elicitation by using an augmented fuzzy set method. In the proposed approach, prior probabilities of the cause nodes are determined based on expert elicitation with the help of an augmented fuzzy set method. The augmented fuzzy set method enables the effective aggregation of expert opinions and helps to reduce subjective bias in expert elicitations. Additionally, an AR algorithm is applied to determine the probabilistic dependency between the BN nodes based on the historical accident data of Chinese universities and further derive conditional probability tables. Finally, the developed fuzzy Bayesian network (FBN) model was employed to identify critical causal factors with respect to laboratory fire accidents in Chinese universities. The obtained results show that H4 (bad safety awareness), O1 (improper storage of hazardous chemicals), E1 (environment with hazardous materials), and M4 (inadequate safety checks) are the four most critical factors inducing laboratory fire accidents. Full article

The effectiveness of fire towers in combating forest fires relies on their appropriate observation angles, enabling a swift and efficient response to fire incidents. The purpose of this study is to examine the effectiveness of 49 fire towers located within the Antalya Forestry Regional Directorate, situated in the Mediterranean basin—a region prone to frequent forest fires. The assessment encompasses the visibility of the entire study area, including forested regions, as well as the visibility of 2504 forest fires recorded by the towers between 2008 and 2021. Furthermore, the evaluation considers the objectives based on Forest Management Directorates and conducts a location suitability analysis for the six towers with the lowest visibility. We utilized the Viewshed Tool in the ArcGIS application and employed the Best–Worst approach. Two scenarios were devised, considering smoke height at 0 m or 100 m, to determine the visibility of fire lookout towers. In Scenario I, assuming a smoke height of 100 m, only three towers exhibited visibility above 70%. However, in Scenario II, assuming a smoke height of 0 m, no towers achieved visibility above 70%. Scenario I indicated that only two towers possessed a view of more than 70% of the forested region, while Scenario II suggested that no towers met this criterion. For the visibility of forest fires, Scenario I identified seven towers capable of observing more than 70%, whereas Scenario II indicated that no towers possessed such capability. In the tower suitability analysis, the visibility rates varied from 41.18% to 1016.67%. Based on the evaluation results, the current visibility capacities of the 49 fire towers proved insufficient for effective preventive measures. Full article

Large areas of forests burn annually in Siberia. Pyrogenic organic matter (PyOM) generated by wildfires acts as a stable carbon deposit and plays an important role in the global carbon cycle. Little is known about the properties of PyOM formed during fires in Siberian forests. In this work, we report the results of thermogravimetry (TG), differential scanning calorimetry (DSC), and Fourier transform infrared (FTIR) spectroscopy applied to the study of the chemical composition, structure, and thermal stability of PyOM formed during surface and crown fires of moderate to high severity in southern Siberia. We studied the PyOM produced from the forest floor, down wood, cones, and outer bark of tree stems in Scots pine, larch, spruce, and birch forests. We calculated the thermal recalcitrance indexes (R₅₀, Q₃) based on TG/DSC data. We found that wildfires resulted in a strong decrease in thermolabile components in burned fuels, enrichment by aromatic structures, and a significant increase in thermal stability (T₅₀) compared to unburned samples. In all the studied forests, bark PyOM revealed the highest value of T₅₀ while forest floor PyOM had the lowest one. At the same time, our results indicated that the properties of PyOM were more strongly driven by wildfire severity than by fuel type. Overall, the thermal recalcitrance R₅₀ index for PyOM samples increased by 9–29% compared to unburned plant residues, indicating a shift from low to intermediate carbon sequestration potential class in the majority of cases and hence less susceptibility of PyOM to biodegradation. Full article

This study developed an objective approach for determining fire source location based on an artificial neural network (ANN) model. The samples for the ANN model were obtained from computational fluid dynamics simulations. A data preprocessor was devised to transform numerical simulation results into a format that could be used by the ANN model prior to network training, and bootstrap aggregation was used to improve the model’s predictive performance, which was evaluated by the leave-one-out approach. The results show that the 95% left-tailed confidence limit was 0.7921 m for planar dimensions of 5 m × 5 m, which is sufficiently accurate for practical application. Additionally, comprehensive experiments were conducted in the confined space of a fire compartment that was geometrically similar to various fire source locations to explore soot patterns and verify the ANN model. The experimental results reveal that the differences between the locations determined in scaling experiments and the locations predicted by the ANN were invariably less than 1 m. In particular, the difference was only 0.17 m when the fire source was located in the centre of the fire compartment. These results demonstrate the feasibility of the devised ANN model for reconstructing fire source location in engineering applications. Full article

Efforts to delineate the influence of atmospheric variability on regional wildfire activity have previously been complicated by the stochastic occurrence of ignition and large fire events, particularly for Southern California, where anthropogenic modulation of the fire regime is extensive. Traditional metrics of wildfire activity inherently contain this stochasticity, likely weakening regional fire–climate relationships. To resolve this complication, we first develop a new method of quantifying regional wildfire activity that aims to more clearly capture the atmospheric fire regime component by aggregating four metrics of fire activity into an annual index value, the Annual Fire Severity Index (AFSI), for the 27-year period of 1992–2018. We then decompose the AFSI into trend and oscillatory components using singular spectrum analysis (SSA) and relate each component to a set of five climate predictors known to modulate macroscale fire activity in Southern California. These include the Atlantic Multidecadal Oscillation (AMO), Pacific Decadal Oscillation (PDO), El Niño–Southern Oscillation (ENSO), and Santa Ana wind (SAW) events, and marine layer frequency. The results indicate that SSA effectively isolates the individual influence of each predictor on AFSI quantified by generally moderate fire–climate correlations, $\left|r\right|>0.4$, over the full study period, and $\left|r\right|>0.5$ over select 13–15-year periods. A transition between weaker and stronger fire–climate relationships for each of the oscillatory PC–predictor pairs is centered around the mid-2000s, suggesting a significant shift in fire–climate variability at this time. Our approach of aggregating and decomposing a fire activity index yields a straightforward methodology to identify the individual influence of climatic predictors on macroscale fire activity even in fire regimes heavily modified by anthropogenic influence. Full article

Throughout the larch range, warming leads to frequent fires and an increase in burned areas. We test the hypothesis that fires are an essential natural factor that reset larch regeneration and support the existence of larch forests. The study area included Larix sibirica and L. gmelinii ranges within the permafrost zone. We used satellite-derived and field data, dendrochronology, and climate variables analysis. We found that warming led to an increase in fire frequency and intensity, mean, and extreme (>10,000 ha) burned areas. The burned area is increasing in the northward direction, while fire frequency is decreasing. The fire rate exponentially increases with decreasing soil moisture and increasing air temperature and air drought. We found a contrasting effect of wildfire on regeneration within continuous permafrost and within the southern lowland boundary of the larch range. In the first case, burnt areas regenerated via abounded larch seedlings (up to 500,000+ per ha), whereas the south burns regenerated mostly via broadleaf species or turned into grass communities. After the fire, vegetation GPP was restored to pre-fire levels within 3–15 years, which may indicate that larch forests continue to serve as carbon stock. At the southern edge of the larch range, an amplified fire rate led to the transformation of larch forests into grass and shrub communities. We suggested that the thawing of continuous permafrost would lead to shrinking larch-dominance in the south. Data obtained indicated that recurrent fires are a prerequisite for larch forests’ successful regeneration and resilience within continuous permafrost. It is therefore not necessary to suppress all fires within the zone of larch dominance. Instead, we must focus fire suppression on areas of high natural, social, and economic importance, permitting fires to burn in vast, larch-dominant permafrost landscapes. Full article

Historical land and fire management practices coupled with climate change and modern human development pressures are contributing to larger, more frequent, and more severe wildfires across Western U.S. forests. Human ignitions are the predominant cause of wildfire throughout the United States, necessitating wildfire management strategies that consider both the causes of human ignitions and the factors that influence them. Using a dataset of over 104,000 ignitions from 1992 to 2018 for Oregon and Washington (U.S), we examine the major causes of wildfire ignitions and build regression models to evaluate the potential influence of both biophysical and socioeconomic factors on human and natural ignitions across distinct fire regimes west and east of the Cascade Range. Our results corroborate prior findings that socioeconomic factors such as income, employment, population density, and age demographics are significantly correlated with human ignitions. In the Pacific Northwest, we found that the importance of socioeconomic factors on human ignitions differs significantly between the west and east sides of the Cascade Range. We also found that most human ignitions are linked to escaped fires from recreation or debris and open burning activities, highlighting opportunities to tailor wildfire prevention efforts to better control higher risk activities and reduce accidental ignitions. Full article

As a way to accommodate the rising demand for “green” wood-based products, agricultural waste from Areca (Areca catechu) nut farms, which is generally burned on-site, can be used to raise the value of alternative lignocellulosic raw materials. This research aimed to investigate and evaluate the effect of technical lignin (kraft lignin or lignosulfonate) addition on particleboard properties from areca bonded with ultra-low-emitting urea formaldehyde (UF) resin. The physical properties, mechanical properties, and fire resistance of the laboratory-made particleboards were tested and evaluated in accordance with the applicable Japanese industrial standards (JIS). The highest density of 0.84 g/cm³ was determined for the laboratory boards, bonded with an adhesive mixture of UF resin and kraft lignin with three washing treatments. The lowest moisture content of 9.06%, thickness swelling of 71.16%, and water absorption of 129.17% were determined for the boards bonded with lignosulfonate with three washing treatments, with commercial lignin, and with lignosulfonate with five washing treatments, respectively. The highest MOR and MOE values, i.e., 113.49 kg/cm² and 10,663 kg/cm², respectively, were obtained for the particleboards bonded with lignosulfonate with five washing treatments. Interestingly, all laboratory boards exhibited good fire resistance following the UL-94 standard. Based on the gas torch test, the lowest weight loss of 16.7% was determined in the boards fabricated with lignosulfonate with five washing treatments. This study demonstrated that adding lignin-based fire retardants represents a viable approach to producing lignocellulosic composites with enhanced fire resistance and a lower carbon footprint. Full article

The Victorian Government Inquiry into wildfires that killed 173 people in 2009 has driven an Australian policy shift from self-evacuation or staying and defending a well-prepared property (‘go or stay’) to self-evacuation under catastrophic fire weather (‘leave early’). The Inquiry also led to the establishment of national ‘performance standards’ for Private Fire Shelters (PFSs, that are also known as bunkers). Nonetheless, the incorporation of PFSs into national bushfire policy remains embryonic, with only Victoria having streamlined accreditation and planning approval processes. Arguments against PFSs include potentially engendering complacency about preparing dwellings to survive fire and encouraging risky behaviour in response to a fire threat. Counteracting these arguments is research that shows that residents without PFSs have low engagement with bushfire preparation and typically delay evacuation. In any case, because wildfire is unpredictable, it is accepted that self-evacuation plans must have fallback positions that include sheltering ‘in place’ from the bushfire, making properly used and well-maintained PFSs an important element of bushfire safety. A less discussed barrier to PFS uptake outside Victoria appears to hinge on a lack of clarity about obligations for their design, certification, and consistency with planning approvals. The escalating Australian fire crisis demands much greater research and development in legal frameworks, policy and planning processes for PFSs, as well as design and construction standards. Progress in enhancing Australian laws and policies on this issue may offer important opportunities for other jurisdictions that will experience similar challenges as climate change intensifies fire regimes around the world. Full article

The layout of a city is complex, and indoor spaces have thousands of aspects that make them susceptible to fire. If a fire breaks out, it is difficult to quell, so a fire in the city will cause great harm. However, the traditional fire detection algorithm has a low detection efficiency and high detection rate of small targets, and disasters have occurred during detection. Therefore, this paper proposes a fire safety detection algorithm based on CAGSA-YOLO and constructs a fire safety dataset to integrate common fire safety tools into fire detection, which has a preventive detection effect before a fire occurs. In the improved algorithm, the upsampling in the original YOLOv5 is replaced with the CARAFE module. By adjusting its internal Parameter contrast, the algorithm pays more attention to local regional information and obtains stronger feature maps. Secondly, a new scale detection layer is added to detect objects larger than 4 × 4. Furthermore, the sampling Ghost lightweight design replaces C3 with the C3Ghost module without reducing the mAP. Finally, a lighter SA mechanism is introduced to optimize visual information processing resources. Using the fire safety dataset, the precision, recall, and mAP of the improved model increase to 89.7%, 80.1%, and 85.1%, respectively. At the same time, the size of the improved model is reduced by 0.6 M to 13.8 M, and the Param is reduced from 7.1 M to 6.6 M. Full article