Fire

At present, the selection criteria and configuration methods for fireproof clapboards in cable tunnels are not yet perfect, making it difficult to achieve effective fire protection. Therefore, an equivalent fire condition testing method is proposed to analyze the fire-resistant property of fireproof clapboards of different materials. Firstly, a tunnel fire experiment platform was built to carry out the combustion experiment of the high-voltage cable intermediate joint. The cable combustion equivalent fire source device is developed based on the temperature rise characteristics under different combustion conditions. However, the temperature rise characteristics of the equivalent fire source and the actual cable combustion error are within 10%. Then, four typical fireproof clapboards were tested under equivalent fire sources. The results indicate that the organic molded board has the best performance. In addition, factors such as the thickness, side panel height, and installation method of the fireproof clapboards were tested and analyzed. The results indicate that a minimum thickness of 5 mm for the fireproof clapboard and a height of 200 mm for the side panel of the clapboard are necessary to ensure effective protection. The installation method of hoisting fireproof clapboards can effectively extend the protection time by about 30% compared to the flat method. Full article

Electrostatic precipitators (ESPs) have shown promise in reducing particulate matter (PM) emissions, but their potential for simultaneous NOx reduction in small-scale combustion systems remains underexplored. This study focuses on using non-thermal plasma generated in a corona discharge to reduce PM and NOx emissions from small-scale combustion. ESP was specifically designed for a commercially available 15 kW boiler with wood pellet combustion and used with both positive and negative discharge polarity to control emissions without any chemical additives. ESP performance was evaluated across a range of specific input energies (SIE) in terms of particle mass and number concentrations and NOx concentrations obtained by continuous gas analysis. ESP ensured the reduction in PM concentrations from 48 mg/m³ to the magnitude of PM content in the ambient air. The highest precipitation efficiency was observed for particles in the 20–200 nm range. Concurrently, NOx emissions were reduced by up to 78%, from 178 mg/m³ to 39 mg/m³. These results were achieved at specific input energies of 36 for positive and 48 J/L for negative corona, which is significantly lower than those reported for many existing separate PM and NOx control systems. This study demonstrates the potential of ESPs as a compact, energy-efficient solution for simultaneous PM and NOx removal in small-scale combustion systems, offering promising implications for improving air pollution control technologies for small-scale combustion systems. Full article

Forest fires are increasingly destructive, contributing to significant ecological damage, carbon emissions, and economic losses. Monitoring these fires promptly and accurately, particularly by delineating fire perimeters, is critical for mitigating their impact. Satellite-based remote sensing, especially using active fire products from VIIRS and MODIS, has proven indispensable for real-time forest fire monitoring. Despite advancements, challenges remain in accurately clustering and delineating fire perimeters in a timely manner, as many existing methods rely on manual processing, resulting in delays. Active fire perimeter (AFP) and Timely Active Fire Progression (TAFP) models were developed which aim to be an automated approach for clustering active fire data points and delineating perimeters. The results demonstrated that the combined dataset achieved the highest matching rate of 85.13% for fire perimeters across all size classes, with a 95.95% clustering accuracy for fires ≥100 ha. However, the accuracy decreased for smaller fires. Overall, 1500 m radii with alpha values of 0.1 were found to be the most effective for fire perimeter delineation, particularly when applied at larger radii. The proposed models can play a critical role in improving operational responses by fire management agencies, helping to mitigate the destructive impact of forest fires more effectively. Full article

Coal spontaneous combustion (CSC) is a multifaceted research domain that has been widely explored in the literature, ranging from analytical and numerical modeling to the development of fire suppression materials and methods. A comprehensive review of the literature has revealed several distinct research trajectories, or “roadmaps”, identified through criteria such as the volume of studies addressing each theme, the presence of review papers dedicated to a specific roadmap, and the explicit mention of coal spontaneous combustion in the title or keywords. This classification framework has outlined six primary roadmaps: (1) spread, quantification, and impact; (2) mechanisms, models, factors, and parameters; (3) experimental studies and models; (4) detection, monitoring, and prediction; (5) prevention and control; and (6) applications. While interconnections exist between these roadmaps, and all ultimately converge towards roadmap 5 (prevention and control), each roadmap constitutes a distinct research cluster. The focus of this review is on roadmap 4, specifically addressing the methods and technologies for detection, monitoring, and prediction of CSC events. This review encompasses studies published from 2010 to the present, providing a thorough examination of the various detection techniques employed, with particular emphasis on their limitations and the strategies proposed to overcome these challenges. A critical analysis highlights the key advantages and disadvantages of each category of techniques, offering insights into their practical applications and the potential for future advancements in this field. The present review aims to contribute to the refinement of detection and monitoring methods for CSC, with the goal of enhancing early detection capabilities and improving fire management strategies. Full article

Spontaneous coal combustion adversely affects coal mine safety and restricts safe, efficient, and green coal mining. Inert gas fire prevention and extinguishing technology is a widely used fire prevention and extinguishing method in coal mines. CO₂ is often used as the primary raw material for inert gas fire prevention and extinguishing, owing to its good inerting and cooling characteristics. However, the lack of data on the physical and chemical properties and fire extinguishing mechanism of CO₂ by field personnel has limited the efficient application of CO₂ in coal mine fire prevention and extinguishing. To explore the practical application effects of CO₂ fire prevention and extinguishing technology on coal mine sites, this paper summarised and analysed the research and development status of CO₂ fire prevention and extinguishing technology and expounded the physical and chemical properties, phase characteristics, and fire prevention and extinguishing mechanisms of CO₂. The CO₂ pipeline, CO₂ pipeline intelligent monitoring and control system, CO₂ inerting mechanism, and comprehensive gas fire prevention and extinguishing technology are summarised and discussed. This study provides a systematic theoretical basis for the field application of CO₂ fire prevention and extinguishing technology. Full article

High-voltage cables will continue to operate for a period of time in the event of a small current arc fault, which poses a risk of fire. Two simulated ignition methods, moving electrode and melting fuses, are proposed to analyze the ignition characteristics of low-current arcs. The ignition test was carried out, and the combustion effect was compared. The results indicate that the moving electrode ignition method can achieve long-distance arc ignition test when the current is small and is suitable for simulating the arc ignition situation of cable outer protective layer damage. By controlling the movement speed, it can be ensured that the arc will not be interrupted during the electrode movement process. However, the arc is difficult to sustain using the fuse melting method when the current is small and the distance is long. The fuse melting method is suitable for simulating insulation breakdown situations. The results show that the critical arc duration for cable ignition under five different current conditions of 2–10 A is 28 s, 21 s, 14 s, 9 s, and 4 s, respectively. The maximum height of the cable flame under 2–10 A arc current is 9–52 cm and 16–63 cm, respectively, when the arc duration is 50 s and 100 s. The self-ignition time of the cable after the arc extinguishing is 8–95 s and 14–261 s, respectively. The maximum temperature of the cable flame is positively correlated with arc current, and the maximum flame temperature of the cable under 2–10 A arc current is 540–980 °C. Based on the actual current monitoring data in cable tunnels, the research results can provide reference for the risk assessment and protection of cable tunnel fires. Full article

Polyurethane (PU) foam has a high flammability and is widely used in aircraft interiors, presenting a significant danger to occupants. This study analysed three composite intumescent flame-retardant (IFR) coatings for flexible PU foam; expandable graphite (EG), ammonium polyphosphate (APP) and alginate (AG). The coatings were prepared in concentrations of 5 wt%, 10 wt%, and 50 wt% with an acrylic binder. The coated samples were characterised using cone calorimetry, SEM, and mechanical testing. The findings showed peak heat release rate, total heat release, and carbon dioxide production from the 10 wt% triple-layer coating (EG:APP:AG) was 52%, 32%, and 58% less than the PU control. The char of the 10 wt% triple-layer sample effectively suppressed smoke release and inhibited the transfer of fuel and gas volatiles. Mechanical testing demonstrated a 3.4 times increase in tensile strength and a 15.4 times increase in compressive strength (50% compression) compared to the control PU with the 10 wt% triple-layer coating. A fire dynamics simulator model was developed that demonstrated large-scale flammability modelling for commercial aircraft. Future work can explore the integration of IFR coatings into computational analysis. These new bio-based coatings produced promising results for aircraft fire safety and flammability performance for PU polymers. Full article

The flashover mechanism in an aircraft cargo compartment under low pressure was investigated in this study. A series of fire experiments were conducted in a scale model of a one-quarter volume FAA standard aircraft cargo compartment at 96 kPa and 60 kPa. The ignition of single-walled corrugated cardboard was chosen as the criterion of the flashover. The influence of different fire sizes and fuel types on the flashover was studied by comparing the average temperature of the smoke layer, the radiation heat flux at the floor level, and the heat release rate of the fire source. The critical condition and behavior of the flashover were analyzed. The results show that under low pressure, the flashover occurs at a higher temperature and radiation heat flux. Increasing the fire source size brings the flashover forward. At 60 kPa and 96 kPa, the cardboard ignites under a flashover when the average temperature of the smoke layer reaches 551 °C and 450 °C, and the average radiant heat flux at the floor level reaches 19.6 kW/m² and 14 kW/m², respectively. In addition, the minimum fire size for a flashover is directly proportional to the heat of evaporation and inversely proportional to the heat of combustion. Full article

The Australian megafires of 2019–2020 were considered catastrophic for flora and fauna, yet little is known about their impacts on reptiles. We investigated the impacts of the 2019–2020 megafires on reptiles in Morton National Park, New South Wales, in eastern Australia. To understand how fire severity affects reptile species richness and occupancy, we surveyed 28 replicate plots across unburnt areas and areas affected by high and low fire severity. We estimated reptile species richness and occupancy by performing systematic searches for reptiles during five sampling occasions in 2023, three years after the megafires. We measured vegetation structure and quantified the thermal environment in shelter sites used by reptiles. Vegetation structure varied significantly between burn severity groups. High-severity plots had the least canopy cover and the thinnest leaf litter depth but had a taller understorey with more stems. The thermal quality within reptile retreat sites did not differ between fire severity classes. Despite strong differences in post-fire vegetation structure, there was no evidence that fire severity affected reptile species richness or occupancy of the delicate skink, Lampropholis delicata. These results highlight the complexity of reptile responses to fires and contribute to increasing our understanding of the impacts of megafires on reptile communities. Full article

Coal-to-liquid technology is a key technology to ensuring national energy security, with the Fischer–Tropsch synthesis process at its core. However, in actual production, Fischer–Tropsch wax residue exhibits the characteristics of spontaneous combustion due to heat accumulation, posing a fire hazard when exposed to air for extended periods. This significantly threatens the safe production operations of coal-to-liquid chemical enterprises. This study primarily focuses on the experimental investigation of the oxidative spontaneous combustion process of three typical types of wax residues produced during Fischer–Tropsch synthesis. Differential Scanning Calorimetry (DSC) was used to test the thermal flow curves of the three wax residue samples. Kinetic analysis was performed using the Kissinger–Akahira–Sunose (KAS) and Flynn–Wall–Ozawa (FWO) methods to calculate their apparent activation energy. This study analyzed the thermal behavior characteristics, exothermic properties, and kinetic parameters of three typical wax residue samples, exploring the ease of reaction between wax residues and oxygen and their tendency for spontaneous combustion. The results indicate that Wax Residue 1 is rich in low-carbon chain alkanes and olefins, Wax Residue 2 contains relatively fewer low-carbon chain alkanes and olefins, while Wax Residue 3 primarily consists of high-carbon chain alkanes and olefins. This leads to different thermal behavior characteristics among the three typical wax residue samples, with Wax Residue 1 having the lowest heat release and average apparent activation energy and Wax Residue 3 having the highest heat release and average apparent activation energy. These findings suggest that Wax Residue 1 has a higher tendency for spontaneous combustion. This research provides a scientific basis for the safety management of the coal chemical industry, and further exploration into the storage and handling methods of wax residues could reduce fire risks in the future. Full article

This study analyzed the fire regime in the highly diverse Paraguayan Chaco, focusing on different aspects of fire patterns, including spatial (area burned) and temporal (frequency) aspects and magnitude (severity). We focused on fire as it is a natural phenomenon that drives ecosystem change and has significant economic, ecological and social impacts of particular concern in vulnerable ecosystems. Using the K-means clustering technique, we identified four distinct fire regimes in the study region: High (H), Moderately High (MH), Moderately Low (ML) and Low (L). On the one hand, the Dry Chaco predominantly featured Low and Moderately High regimes, characterized by a low fire frequency due to arid conditions. On the other hand, the Humid Chaco was particularly affected by agricultural burning, driven by extensive livestock activity and higher biomass productivity. Finally, in the Pantanal, the variations in fire intensity were influenced by flood pulses and rainfall patterns. Our findings highlight the distinct fire regimes across the Paraguayan Chaco and detail the differences in the regimes. The study’s findings are valuable for developing efficient management strategies that account for fire behaviour during agricultural burning in this poorly studied region. Full article

Forest fire is one of the dominant disturbances in the forests of Heilongjiang Province, China, and is one of the most rapid response predictors that indicate the impact of climate change on forests. This study calculated the Canadian FWI (Fire Weather Index) and its components from meteorological record over past years, and a linear model was built from the monthly mean FWI and monthly fire numbers. The significance test showed that fire numbers and FWI had a very pronounced correlation, and monthly mean FWI was suitable for predicting the monthly fire numbers in this region. Then FWI and its components were calculated from the SRES (IPCC Special Report on Emission Scenarios) A2 and B2 climatic scenarios, and the linear model was rebuilt to be suitable for the climatic scenarios. The results indicated that fire numbers would increase by 2.98–129.97% and −2.86–103.30% in the A2 and B2 climatic scenarios during 2020–2090, respectively. The monthly variation tendency of the FWI components is similar in the A2 and B2 climatic scenarios. The increasing fire risk is uneven across months in these two climatic scenarios. The monthly analysis showed that the FFMC (Fine Fuel Moisture Code) would increase dramatically in summer, and the decreasing precipitation in summer would contribute greatly to this tendency. The FWI would increase rapidly from the spring fire season to the autumn fire season, and the FWI would have the most rapid increase in speed in the spring fire season. DMC (Duff Moisture Code) and DC (Drought Code) have relatively balanced rates of increasing from spring to autumn. The change in the FWI in this region is uneven in space as well. In early 21st century, the FWI of the north of Heilongjiang Province would increase more rapidly than the south, whereas the FWI of the middle and south of Heilongjiang Province would gradually catch up with the increasing speed of the north from the middle of 21st century. The changes in the FWI across seasons and space would influence the fire management policy in this region, and the increasing fire numbers and variations in the FWI scross season and space suggest that suitable development of the management of fire sources and forest fuel should be conducted. Full article

The detection of ship fires is a critical aspect of maritime safety and surveillance, demanding high accuracy in both identification and response mechanisms. However, the scarcity of ship fire images poses a significant challenge to the development and training of effective machine learning models. This research paper addresses this challenge by exploring advanced data augmentation techniques aimed at enhancing the training datasets for ship and ship fire detection. We have curated a dataset comprising ship images (both fire and non-fire) and various oceanic images, which serve as target and source images. By employing diverse image blending methods, we randomly integrate target images of ships with source images of oceanic environments under various conditions, such as windy, rainy, hazy, cloudy, or open-sky scenarios. This approach not only increases the quantity but also the diversity of the training data, thus improving the robustness and performance of machine learning models in detecting ship fires across different contexts. Furthermore, we developed a Gradio web interface application that facilitates selective augmentation of images. The key contribution of this work is related to object extraction-based blending. We propose basic and advanced data augmentation techniques while applying blending and selective randomness. Overall, we cover eight critical steps for dataset creation. We collected 9200 ship fire and 4100 ship non-fire images. From the images, we augmented 90 ship fire images with 13 background images and achieved 11,440 augmented images. To test the augmented dataset performance, we trained Yolo-v8 and Yolo-v10 models with “Fire” and “No-fire” augmented ship images. In the Yolo-v8 case, the precision-recall curve achieved 96.6% (Fire), 98.2% (No-fire), and 97.4% mAP score achievement in all classes at a 0.5 rate. In Yolo-v10 model training achievement, we got 90.3% (Fire), 93.7 (No-fire), and 92% mAP score achievement in all classes at 0.5 rate. In comparison, both trained models’ performance is outperforming other Yolo-based SOTA ship fire detection models in overall and mAP scores. Full article

Transitioning to low-carbon energy systems is crucial for sustainable development, particularly in oil-rich developing countries (ORDCs) that face intertwined economic and environmental challenges. This review uses the PRISMA methodology to systematically assess the current state and prospects of low-carbon thermal electricity generation and utilization technologies in ORDCs. The study emphasizes clean thermal technologies such as biogas, biofuels, biomass, hydrogen, and geothermal energy, focusing on solutions that are technically feasible, economically viable, and efficient in combustion processes. These nations face significant challenges, including heavy reliance on fossil fuels, transmission losses, and financial constraints, making energy diversification urgent. The global shift towards renewable energy and the need to mitigate climate change presents an opportunity to adopt low-carbon solutions that align with Sustainable Development Goals related to energy access, economic growth, and climate action. This review aims to (1) evaluate the current state of low-carbon thermal electricity technologies, (2) analyze the technical and economic challenges related to combustion processes and energy efficiency, and (3) provide recommendations for research and policy initiatives to advance the transition toward sustainable thermal energy systems in ORDCs. The review highlights practical approaches for diversifying energy sources in these nations, focusing on overcoming existing barriers and supporting the implementation of clean thermal technologies. Full article

Wildfires cause severe consequences, including property loss, threats to human life, damage to natural resources, biodiversity, and economic impacts. Consequently, numerous wildland fire detection systems were developed over the years to identify fires at an early stage and prevent their damage to both the environment and human lives. Recently, deep learning methods were employed for recognizing wildfires, showing interesting results. However, numerous challenges are still present, including background complexity and small wildfire and smoke areas. To address these challenging limitations, two deep learning models, namely CT-Fire and DC-Fire, were adopted to recognize wildfires using both visible and infrared aerial images. Infrared images detect temperature gradients, showing areas of high heat and indicating active flames. RGB images provide the visual context to identify smoke and forest fires. Using both visible and infrared images provides a diversified data for learning deep learning models. The diverse characteristics of wildfires and smoke enable these models to learn a complete visual representation of wildland fires and smoke scenarios. Testing results showed that CT-Fire and DC-Fire achieved higher performance compared to baseline wildfire recognition methods using a large dataset, which includes RGB and infrared aerial images. CT-Fire and DC-Fire also showed the reliability of deep learning models in identifying and recognizing patterns and features related to wildland smoke and fires and surpassing challenges, including background complexity, which can include vegetation, weather conditions, and diverse terrain, detecting small wildfire areas, and wildland fires and smoke variety in terms of size, intensity, and shape. CT-Fire and DC-Fire also reached faster processing speeds, enabling their use for early detection of smoke and forest fires in both night and day conditions. Full article

The frequency of extreme wildfire events (EWEs) is expected to increase due to climate change, leading to higher levels of atmospheric pollutants being released into the air, which could cause significant short-term impacts on human health (both for the population and firefighters) and on visibility. This study aims to gain a better understanding of the effects of EWEs’ smoke on air quality, its short-term impacts on human health, and how it reduces visibility by applying a modelling system to the Portuguese EWEs of October 2017. The Weather Research and Forecasting Model was combined with a semi-empirical fire spread algorithm (WRF-SFIRE) to simulate particulate matter smoke dispersion and assess its impacts based on up-to-date numerical approaches. Hourly simulated particulate matter values were compared to hourly monitored values, and the WRF-SFIRE system demonstrated accuracy consistent with previous studies, with a correlation coefficient ranging from 0.30 to 0.76 and an RMSE varying between 215 µg/m³ and 418 µg/m³. The estimated daily particle concentration levels exceeded the European air quality limit value, indicating a potential strong impact on human health. Health indicators related to exposure to particles were estimated, and their spatial distribution showed that the highest number of hospital admissions (>300) during the EWE, which occurred downwind of the fire perimeters, were due to the combined effect of high smoke pollution levels and population density. Visibility reached its worst level at night, when dispersion conditions were poorest, with the entire central and northern regions registering poor visibility levels (with a visual range of less than 2 km). This study emphasises the use of numerical models to predict, with high spatial and temporal resolutions, the population that may be exposed to dangerous levels of air pollution caused by ongoing wildfires. It offers valuable information to the public, civil protection agencies, and health organisations to assist in lessening the impact of wildfires on society. Full article

For adjacent coal seams, the downward invasion of harmful gases from an overlying coal mine goaf to the lower mining face could occur, and a high-level drainage tunnel is usually adopted for disaster prevention. Due to the high cost, instead of a high-level drainage tunnel, the high-level directional boreholes are widely adopted. In this study, the effect of a high-level drainage tunnel to prevent the downward invasion of carbon dioxide from the overlying coal mine goaf is analysed by applying a flow model in the numerical simulation. Then, the high-level directional boreholes are analysed to investigate the possibility of taking the place of the high-level drainage tunnel. The research results show that (1) for close adjacent coal seams, the downward invasion range of harmful carbon dioxide from the overlying coal mine goaf reaches one-third of the mining face, around 60 m wide; (2) a high-level drainage tunnel can effectively prevent the downward invasion of carbon dioxide from the overlying coal mine goaf by reducing carbon dioxide concentration within 0.3%; (3) the nine high-level directional boreholes with a careful layout can reduce the downward invasion of carbon dioxide from the overlying coal mine goaf to keep carbon dioxide concentration below 0.8% at the mining area, ensuring the coal mining safety. Full article

Natural disasters like hurricanes, wildfires, and floods pose immediate hazards. Such events often necessitate prompt emergency evacuations to save lives and reduce fatalities, injuries, and property damage. This study focuses on optimizing wildfire evacuations by analyzing the influence of different transportation infrastructures and the penetration of autonomous vehicles (AVs) on a historical wildfire event. The methodology involves modeling various evacuation scenarios and incorporating different intersection traffic controls such as roundabouts and stop signs and an evacuation strategy like lane reversal with various AV penetration rates. The analysis results demonstrate that specific interventions on evacuation routes can significantly reduce travel times during evacuations. Additionally, a comparative analysis across different scenarios shows a promising improvement in travel time with a higher level of AV penetration. These findings advocate for the integration of autonomous technologies as a crucial component of future emergency response strategies, demonstrating the potential for broader applications in disaster management. Future studies can expand on these findings by examining the broader implications of integrating AVs in emergency evacuations. Full article

Fire is a key ecological factor in marshes, significantly influencing the nitrogen (N) cycle. The impacts of different fire regimes on marshes have garnered increasing attention. This study aims to reveal the effects of fire regimes on N distribution in marshes. We conducted field experiments with fixed–point prescribed burning in typical Sanjiang Plain freshwater marshes, exploring the influences of various fire regimes on the distribution of N in marshes. We found that in the spring–burned plots, the soil ammonium (${\mathrm{NH}}_4^{+}–\mathrm{N}$) content increased by 318% with thrice–burned approaches compared to once–burned, and by 186% with thrice–burned compared to twice–burned. In the autumn–burned plots, ${\mathrm{NH}}_4^{+}–\mathrm{N}$ content increased by 168% and 190%, respectively. Similarly, the soil nitrate (${\mathrm{NO}}_3^{–}–\mathrm{N}$) content three years subsequent to burning increased by 29.1% compared to one year since burning, and by 5.96% compared to two years since burning in the spring–burned plots (73.8% and 32.9% increases, respectively, in the autumn–burned plots). The plant stem–N content of the autumn burns increased by 30.9%, 119%, and 89.1% compared to the spring burns after one, two, and three years since burning, respectively. Our results indicate that high fire–frequency promotes marsh N cycling within the span of three years. The marsh soil conversion of ${\mathrm{NH}}_4^{+}–\mathrm{N}$ to ${\mathrm{NO}}_3^{–}–\mathrm{N}$ was enhanced with increased time since burning. High fire–frequency promotes plant growth, exacerbating competition between plant populations, with this effect being more significant in autumn–burned plots than in spring–burned plots. Full article