Fire

Fire smoke significantly affects human health and air quality. The HYSPLIT dispersion model estimates the area impacted by smoke downwind, but the results are sensitive to input data. This study investigates the impact of different fire emission inputs on dispersion modeling results, focusing on three versions of the Wildland Fire Emissions Inventory System (WFEIS) used to initialize HYSPLIT. The three input datasets include MODIS (FEI_BASE), a combination of MODIS and MTBS (FEI_COMBO), and a version incorporating a cloud cover regression (FEI_COMBO+CC). Dispersion modeling results are compared across the western U.S. for 2013, 2016, and 2018, showing a variation of up to 200% in results depending on the emissions input. Model results are evaluated with ground-based PM_2.5 data and visible satellite imagery. The cloud cover regression improves the identification of fire days missed by FEI_BASE potentially impacting health effect studies. Correlations between modeled PM_2.5 and EPA data improve with FEI_COMBO+CC, particularly in 2013 and 2016, making it a stronger candidate for use in research on health effects. Despite some variability in RMSE, the higher correlation observed with FEI_COMBO+CC supports its use as a more accurate representation of fire-related PM_2.5 transport. Full article

Wildfires are increasing in frequency and severity, with Australia’s 2019–2020 Black Summer burning over 18 million hectares. Accurate prediction of wildfire behavior is essential for effective risk assessment and emergency response. This study presents a machine learning framework for predicting wildfire dynamics across Australia’s seven regions using the IBM wildfire dataset. Various Machine Learning (ML) models were evaluated to forecast three key indicators: Fire Area (km²), Fire Brightness Temperature (K), and Fire Radiative Power (MW). Lasso Regression consistently outperformed the other models, achieving an average RMSE of 0.04201 and R² of 0.29355. Performance varied across regions, with stronger results in areas like New South Wales and Queensland, likely influenced by differences in topography, microclimate, and vegetation. However, limitations include the exclusion of ignition sources such as lightning and human activity, which are critical for capturing the environment accurately and improving predictive accuracy. Future work will integrate these factors alongside more detailed weather and vegetation data. Practical implementation may face challenges related to real-time data availability, system integration, and response coordination, but this approach offers promising potential for operational wildfire decision support. Full article

To study the impact of the psychological and behavioral characteristics of people, fire environment, and evacuation routes on fire evacuation efficiency, this study focuses on a university library as the research subject. A fuzzy logic algorithm is employed to analyze how psychological and behavioral traits influence initial evacuation speed during a fire. Also, fire data simulated using PyroSim software is integrated, with gas temperature, CO concentration, and visibility quantified through empirical formulas to adjust the reduction factor of evacuation speed, examining the effects of fire-generated products on evacuation performance. By incorporating fire environment factors into the heuristic function and refining pheromone update rules through iterative strategies, the ant colony algorithm is enhanced to achieve path planning. Results show that the psychological–environmental-route correction method improves evacuation efficiency by 16.2% compared to traditional methods without correction. This demonstrates that the proposed correction method can improve the efficiency of building fire evacuation and provides theoretical support and technical solutions for future library fire safety management. Full article

Mixing hydrogen into natural gas pipelines for transportation is an effective solution to the imbalance between the supply and demand of hydrogen energy. Studying the influence of bent pipes in hydrogen-mixed natural gas explosion accidents can enhance the safety of hydrogen energy storage and transportation. Through experiments and LES, the influence of pipe spacing configuration on the vented explosion of this mixed gas in pipes with a large length-to-diameter ratio was analyzed. The maximum explosion pressure (Pmax) of the straight pipe is 21.7 kPa and the maximum pressure rise rate ((dp/dt)max) is 1.8 MPa/s. After adding the double elbow, Pmax increased to 65.2 kPa and (dp/dt)max increased to 3.7 MPa/s. By increasing the distance (D1) from bent pipe-1 to the ignition source, the flame shape changes from “finger-shaped” to “concave-shaped” to “wrinkled-shaped.” When D1 is at its minimum, the explosion reaction is the most intense. However, as D1 increases, each characteristic parameter decreases linearly and the flame propagation speed significantly reduces, the flame area decays more severely, and the flame acceleration effect is also suppressed. When the distance between the two bent pipes (D2) was gradually increased, the flame transformed from “finger-shaped” to “tongue-shaped” to “wrinkled-shaped”. The flame area curve exhibited a unique evolutionary process of “hitting bottom” to “rebounding” to “large-scale flame backflow”. This paper explores the development process of various characteristic parameters, which is of great reference value for preventing explosions in hydrogen-blended natural gas pipelines in underground pipe galleries. Full article

This study proposes an equivalent furniture fire model based on standard combustible assembly and verifies its feasibility as a substitute for real furniture through full-scale experiments and numerical simulations. Experiments show that the peak heat release rate and total heat release of the standard combustible assembly are highly consistent with those of the single-seat sofa. The numerical model has been verified by experimental data. The dynamic characteristics of the heat release rate (HRR) curve are consistent with the temperature evolution process, confirming its reliability for the numerical model. The research on optimizing fire extinguishing parameters is carried out based on this numerical simulation. The results show that the response time of the horizontal sprinkler is 22 s shorter than that of the vertical sprinkler, and the fire extinguishing efficiency is improved. Reducing the sprinkler height to 3 m can accelerate activation and reduce CO₂ release. A flow rate of 91.4 L/min can effectively control the fire, but when it exceeds 150 L/min, the fire extinguishing efficiency is significantly reduced. The low response time index sprinkler starts up 88 s faster than the standard type, significantly enhancing the initial fire suppression capability. This scheme provides a safe, economical, and repeatable standardized combustible assembly for fire training and offers theoretical support for the parameter design of intelligent fire extinguishing systems. Full article

In this paper, the effect of nozzle height on the combustion dynamics of jet fires in rotating flow fields (JFRFFs) is systematically investigated through experimental and numerical simulations. As the nozzle height increases, the JFRFF flame state transitions from stable rotation (SR) to unstable rotation (USR), and eventually to non-rotation (NR), indicating a weakening interaction between the vortex flow and the jet flame. The radial distribution of tangential velocity gradually deviates from the Burgers vortex model as the nozzle height increases, providing a criterion for distinguishing different flame states. Both vortex intensity and flame length are found to decrease with increasing nozzle height, whereas the maximum flame diameter increases. The relative position of the maximum flame diameter to the whole flame length firstly increases and then decreases to match that of the free jet fires, as the flame evolves from SR to USR and NR. In addition, the air entrainment near the nozzle exit decreases with increasing nozzle height, as evidenced by the gradual rise in lift-off height. These findings establish a theoretical basis for the fire performance design of flares in pipeline retrofitting and process industries. Full article

In recent years, devastating wildfires have occurred in less fire-prone areas, and an increase in boreal region wildfires is expected in the future. Using a qualitative comparative approach based on a literature review and policy document analysis, this study aims to examine the wildfire management systems and practices in Sweden and Finland, focusing on the remarkably different outcomes of the 2018 wildfire season. Despite experiencing similar climatic conditions, in Sweden a total of approximately 25,000 hectares of forest burned, compared to the 1200 hectares in Finland. The analysis examines thematic areas from general disaster management and wildfire-specific elements. The main differences in the organizational structures between the two countries are identified. Ecological aspects of boreal forests, fire suppression effectiveness, and response times are compared, and current and emerging technologies for fire detection and suppression, such as unmanned aerial vehicles, are presented. The role of volunteer fire brigades and their sustainability in rural areas, together with the effectiveness of host nation support arrangements and international cooperation mechanisms, are discussed. Based on this comparison of identified best practices and lessons learned, the authors provide recommendations for improving wildfire resilience both in Finland and Sweden, as well as in other boreal region countries. Full article

Wildfires are becoming more frequent and widespread, posing a threat to European ecosystems. Recent findings quantified a large fraction of Europe’s burnt areas within Natura 2000 protected area sites. This study analyzed total wildfire events and burnt areas in Greece. The frequency of protected area burn percentages per fire event and their trend over time were quantified. The mean protected area percentage of burn per fire event across other Mediterranean countries was compared. Results indicated an increase in the total number of wildfire events over time, while total burnt area was highest in recent years but generally varied. Forest-type vegetation burn exhibits no trend over time with the exception being that the transitional vegetation percentage of burn per wildfire is increasing, while agricultural land is decreasing. The protected area percentage of burn per wildfire is not related with total area burn. The majority of the high percentage protected area burns derive mainly from small or medium total area burn wildfires. More than a third of wildfires burned exclusively (100%) Natura protected area surfaces. Protected area percent per burn is increasing over time. This increase is not related to the increased total burnt area. Protected area percent per burn is considerably higher in Greece in comparison to Italy, Spain, and Portugal. Protected area percent per burn is increasing over time in Greece and with a slower slope in Portugal, while it has no monotonic trend in Italy and Spain. Reserves face increasing burn frequency, necessitating effective management strategies to conserve them. Climate change exacerbates total wildfires or surface area burned but cannot entirely explain the steep increase in protected area percent per burn. While a legislative framework preventing arson exists, management measures need to further improve the efficacy and clarity of legislation. High-power electricity networks and wind and solar energy facilities are often causes of wildfires and should receive low priority or not be licensed in Natura areas. Full article

Human activities are increasing the occurrence of megafires that alter ecological dynamics in forest ecosystems. The objective of this study was to understand the impacts of a 610 km² megafire on patterns of tree regeneration and herbivory across three forest types (aspen/fir, oak/maple, and pinyon/juniper). Seventeen transect pairs in adjacent burned/unburned forest stands (6 aspen/fir, 5 oak/maple, and 6 pinyon/juniper) were measured. Sapling density, meristem removal, and height were measured across the transect network over a three-year period from 2019 to 2021. Tree species able to resprout from surviving roots (oak and aspen) generally responded positively to fire while species that typically regenerate by seeding showed little post-fire regeneration. Browse pressure was concentrated on deciduous tree species and was greater in burned areas but the effect diminished over the three-year study period. Meristem removal by herbivores was below the critical threshold, resulting in vertical growth over time. Our results indicate that forest regeneration within the megafire scar was generally positive and experienced sustainable levels of ungulate browsing that were likely to result in forest recruitment success. Full article

In 2020, a high-intensity wildfire burned over 35,000 ha in the Santa Cruz Mountains of California, including over 1700 ha of old-growth coast redwood forest. This event created a unique opportunity to evaluate post-fire succession. We compared vegetation recovery in high versus low/moderate severity burned areas using data collected one year and four years following the fire. Random plot sampling was conducted at Big Basin Redwoods State Park to assess the regeneration of trees, shrubs, and herbaceous species. Descriptive and inferential statistical analyses were used to assess recovery over time and across burn severities. Results indicate significant increases in shrub cover and richness over time, with a positive association between shrub recruitment and high-severity fire. Notably, the fire-adapted species blue blossom (Ceanothus thyrsiflorus Eschsch.), which was not recorded one year following the fire, dominated the shrub layer after four years, particularly in higher severity areas. Herbaceous species also exhibited an increase in cover and richness over time, though a substantial portion of that increase was based on non-native species recruitment. Analysis did not indicate a significant relationship between fire severity and herbaceous species recovery, however. The regeneration of tree species occurred both through seedling recruitment and basal sprouting. The recruitment of basal sprouts was prolific following the fire, particularly for coast redwood. The number of basal sprouts declined significantly during the time frame of this study, as the sprouts became larger and began to self-thin. Seedling abundance, on the other hand, exhibited an approximately 30-fold increase. Seedling recruitment was primarily driven by coast redwood (Sequoia sempervirens [Lamb. ex D.Don] Endl) and Douglas fir (Pseudotsuga menziesii [Mirb.] Franco) and was positively correlated with low/moderate fire severity. These findings underscore the complex interactions shaping post-fire forest dynamics and highlight the importance of understanding such patterns to inform management strategies that support the resiliency of coast redwood forests in an era of increasing wildfires. Full article

The Northern Rocky Mountains, USA contain a vast forested landscape, managed primarily by the federal government. This region contains some of the highest elevations forests and most iconic endangered and threatened species in the contiguous United States. The influence of human impacts and climate change are evident on the landscape today, with larger and more frequent fires impacting vegetation composition and recovery. This project uses paleoecological data from six lake sediment cores to investigate what drives fire across this region over the Holocene. Count regression was used to predict charcoal influx as a function of Pinus pollen accumulation rates (PAR) and percent. The results show that fire activity increases significantly with Pinus pollen, and that baseline fire activity varies significantly across sites, largely following an elevation gradient. The results of this analysis illustrate a novel way to use paleoecological data to provide valuable information to federal agencies as they prepare for future management of these ecologically valuable areas. Full article

Fire occurs naturally and anthropogenically in the Cerrado biome, influenced by hydrology, climate, topography, and land use. Mapping burned areas is essential for understanding the causes of fire and improving prevention and regulation. However, fire scars are often confused with bare soil in agricultural regions. This study presents a method for mapping burned areas using spectral indices and artificial neural networks (ANN). We evaluated the accuracy of these techniques and identified the best input variables for scar detection. Using Sentinel-2 images from 2018 to 2021 during dry periods, we applied NDVI, SAVI, NBR, and CSI indices. The study included two stages: first, finding optimal classification configurations for fire scars, and second, mapping land use and cover with fire scars and crops. Results showed that using all Sentinel-2 bands and the four indices post-fire achieved over 93.7% accuracy and a kappa index of 0.92. Fire scars were mainly located in areas with temporary crops like soybean, sugarcane, rice, and cotton. This low-cost method allows for effective monitoring of fire scars, underscoring the need to regulate agricultural practices in the Cerrado, where burning poses environmental and health risks. Full article

Volunteer firefighters often have lower cardiorespiratory fitness (CRF) and less access to health monitoring and fitness programs than career firefighters, yet few studies explore how individual and departmental factors influence their CRF. This study assessed associations between CRF and both firefighter-level (e.g., years of service, firefighting calls, and firefighter rank) and department-level (e.g., department characteristics and fitness infrastructure) factors among volunteer firefighters. Surveys were administered to United States volunteer firefighters and departments, capturing CRF and related characteristics. CRF was analyzed as both a continuous and categorical variable (≤8, >8–<10, 10–<12, ≥12 METs) using bivariate analyses and mixed effects linear and logistic regression. Among 569 incumbent volunteer firefighters from 41 departments, 79.9% did not meet the recommended 12 METs threshold. Only 56.8% of departments provided routine physical exams; 35.1% had a wellness coordinator or committee; and 40.5% offered fitness resources. More years of service were associated with lower CRF and reduced odds of meeting the 12 METs benchmark, while more frequent training and responding to more calls were associated with better CRF. These findings highlight individual and structural challenges for CRF in volunteer fire service, underscoring the need for targeted fitness support to protect firefighter health and community safety. Full article

This article investigates the effects of pressure vacuum impregnation using inorganic, organic, and natural flame retardants on enhancing the fire resistance and chemical composition of structural beech wood (Fagus sylvatica). The study examines fire resistance characteristics such as the limiting oxidation number and heat of combustion, which indicate the effectiveness of the flame retardants used. Chemical changes in the beech wood were characterized through various analyses, including changes in chemical composition, FTIR spectra, DSC thermograms, and SEM images. The relationships between combustion characteristics and chemical changes were assessed using multiple methods. The results demonstrate that using 5% potassium acetate achieved a lower heat of combustion compared to 15% sodium phosphate, and it was significantly lower than the heat of combustion observed with 5% arabinogalactan or the reference sample of beech wood. However, neither potassium acetate nor diammonium phosphate significantly affected the macromolecular structures of the wood when compared to the reference sample. Low concentrations of flame retardants reduce environmental release and environmental impact while increasing fire resistance, which could be used for structural solutions made of hardwoods. Full article

This study investigates the thermal control effect of a water mist fire-extinguishing system in road tunnels under both single-source and double-source fire scenarios. A total of eight full-scale fire tests were executed in a physical tunnel, and the double-source fire scenarios were further subdivided into two spatial configurations, including fire sources close together and fire sources with a center-to-center distance of 2 m. During the fire tests, the evolution of fire, temporal and spatial temperature distributions of the tunnel ceiling, longitudinal and vertical temperature gradients, and smoke behavior within the tunnel were systematically recorded and interpreted. The results demonstrate that early activation of the water mist system optimizes its physicochemical mechanisms by preventing the transition from the growth phase of fire to a stable phase. In single-source fire scenarios, the water mist directly suppresses the flame and eliminates the high-temperature core, leading to a significant alteration in the vertical temperature gradient. For double-source fire scenarios, the high-temperature region on the ceiling is reduced upon the application of the water mist. However, when the fire sources are positioned in close proximity, they tend to merge into a larger fire source, with the water mist proving insufficient to prevent this fusion. Conversely, when the center-to-center distance between the fire sources is 2 m, the water mist effectively separates the sources, blocking thermal feedback between them and forcing the flames to develop vertically. This, in turn, accelerates the attenuation of the fire and the recovery of the ambient temperature. Additionally, within the effective coverage of the water mist, the longitudinal temperature distribution on the tunnel ceiling still follows an exponential attenuation pattern, with a significantly high rate of temperature decline. Full article

The use of remote sensing technologies for mapping forest fires has experienced significant growth in recent decades, driven by advancements in remote sensors, processing platforms, and artificial intelligence algorithms. This study presents a review of 192 scientific articles published between 1990 and 2024, selected using PRISMA criteria from the Scopus database. Trends in the use of active and passive sensors, spectral indices, software, and processing platforms as well as machine learning and deep learning approaches are analyzed. Bibliometric analysis reveals a concentration of publications in Northern Hemisphere countries such as the United States, Spain, and China as well as in Brazil in the Southern Hemisphere, with sustained growth since 2015. Additionally, the publishers, journals, and authors with the highest scientific output are identified. The normalized burn ratio (NBR) and the normalized difference vegetation index (NDVI) were the most frequently used indices in fire mapping, while random forest (RF) and convolutional neural networks (CNN) were prominent among the applied algorithms. Finally, the main technological and methodological limitations as well as emerging opportunities to enhance fire detection, monitoring, and prediction in various regions are discussed. This review provides a foundation for future research in remote sensing applied to fire management. Full article

Point-type smoke fire detectors have become one of the most commonly used technical means in the fire detection systems of ancient buildings. However, in practical applications, their performance is easily affected by special environmental interference factors. Therefore, in this study, a full-scale experimental scene of an ancient building with a typical flush gable roof structure was taken as the research object, and the differential influence laws of three typical interference sources, namely wind speed, water vapor, and incense burning, on the response times of point-type smoke detectors were quantified. Moreover, the prediction models of the alarm time of the detectors under the three interference conditions were established. The results indicate the following: (1) Within the range of experimental conditions, there is a quantitative relationship between the detector response delay and the type of interference source: the delay time shows a nonlinear positive correlation with the wind speed/water vapor interference gradient, while it exhibits a threshold unimodal change characteristic with the burning incense interference gradient; (2) under interference conditions, the detector response delay varies depending on the type of fire source: the detector has the best detection stability for smoldering smoke from a smoke cake, while it has the lowest detection sensitivity for smoldering smoke from a cotton rope. Moreover, the influence of wind speed interference is weaker than that of water vapor or smoke from burning incense, and the difference is the greatest in the wood block smoldering condition. (3) Construct a detector alarm time prediction model under three types of interference conditions, where the wind speed, water vapor, and burning incense interference conditions conform to third-order polynomial functions, Sigmoid functions, and fourth-order polynomial functions, respectively. Full article

Ventilation in subway and railway tunnels is a critical safety component, especially during fire emergencies, where effective smoke and heat management is essential for successful evacuation and firefighting efforts. The Subway Environmental Simulation (SES, Version 4.1) model is widely used for predicting airflow and thermal conditions during fire events, but its accuracy in real-world applications requires validation. This study compares SES predictions with experimental data from the Memorial Tunnel fire ventilation tests to evaluate its performance in simulating the effects of jet fans on longitudinal ventilation. The analysis focuses on SES’s ability to predict flow rate and temperature distributions. Results showed reasonable agreement between SES-predicted airflows and temperatures. However, SES tended to underpredict temperatures upstream and near the fire source, indicating a limitation in simulating thermal behavior close to the fire. These findings suggest that SES can be a reliable tool for tunnel ventilation design if certain safety margins, based on the error values identified in this study, are considered. Nonetheless, further improvements are necessary to enhance its accuracy, particularly in modeling heat transfer dynamics and the impact of fire-induced temperature changes. Future work should focus on conducting additional full-scale test validations and model refinements to improve SES’s predictive capabilities for fire safety planning. Full article

The increasing frequency and intensity of wildfires pose serious threats to ecosystems, property, and human safety worldwide. Accurate semantic segmentation of wildfire images is essential for real-time fire monitoring, spread prediction, and disaster response. However, existing deep learning methods heavily rely on large volumes of pixel-level annotated data, which are difficult and costly to obtain in real-world wildfire scenarios due to complex environments and urgent time constraints. To address this challenge, we propose a semi-supervised wildfire image segmentation framework that enhances segmentation performance under limited annotation conditions by integrating multi-scale structural information fusion and pixel-level contrastive consistency learning. Specifically, a Lagrange Interpolation Module (LIM) is designed to construct structured interpolation representations between multi-scale feature maps during the decoding stage, enabling effective fusion of spatial details and semantic information, and improving the model’s ability to capture flame boundaries and complex textures. Meanwhile, a Pixel Contrast Consistency (PCC) mechanism is introduced to establish pixel-level semantic constraints between CutMix and Flip augmented views, guiding the model to learn consistent intra-class and discriminative inter-class feature representations, thereby reducing the reliance on large labeled datasets. Extensive experiments on two public wildfire image datasets, Flame and D-Fire, demonstrate that our method consistently outperforms other approaches under various annotation ratios. For example, with only half of the labeled data, our model achieves 5.0% and 6.4% mIoU improvements on the Flame and D-Fire datasets, respectively, compared to the baseline. This work provides technical support for efficient wildfire perception and response in practical applications. Full article