Abstract Wildfire in Siberia is extensive, affecting up to 15 Mha annually. The proportion of the vegetation affected by severe fires is yet unknown, and it is a problem that requires a solution because post-fire mortality of tree stands in Siberian taiga has a strong effect on the global budget of carbon. The impact of fire in our area of interest in eastern Siberia was analyzed using the normalized burn ratio (NBR) and its pre- versus post-fire difference (dNBR) applied to Landsat-8 (OLI) collected in 2020–2021. In this paper, we present the classification of fire impact in relation to dominant tree stands and vegetation types in boreal forests of eastern Siberia. The dNBR of post-fire plots ranged widely (0.30–0.60) in homogeneous larch (Larix sibirica, L. gmelinii) forests, pine (Pinus sylvestris) forests, dark coniferous stands (Pinus sibirica, Abies sibirica, Picea obovata), sparse larch stands, and Siberian dwarf pine (Pinus pumila) stands. We quantified the proportions of low, moderate, and high fire severity (37%, 39%, and 24% of the total area burned, respectively) in dense tree stands, which were varied to 30%, 57%, and 13%, respectively, for sparse stands and tundra vegetation dominated in the north of eastern Siberia. The proportion of severe fires varied according to the transition from dominant larch stands (33.2% of the area burned) to pine (12.6%) and dark coniferous (up to 26.4%). The current proportion of stand-replacement fires in eastern Siberia is 12–33%, depending on vegetation type and tree density, which is about 2500 thousand hectares in 2021 in the region. According to our findings, the “healthy/unburned vegetation” class was quantified as well at least 700 thousand hectares in 2021.

Abstract Natural ventilators can maintain the ventilation of buildings and tunnels, and can exhaust fire smoke without requiring energy. In this study, we optimized a natural ventilator by adding axial fan blades (equivalent to adding a fan system) to investigate the effect of wind speed on the ventilation and smoke exhaust performance of an optimized natural ventilator. The experimental results showed that the best configuration of the ventilator was five fan blades at an angle of 25◦ with set-forward curved fan blades. With this configuration, the ventilation volume of the optimized natural ventilator was increased by 11.1%, and the energy consumption was reduced by 2.952 J. The third experiment showed that, in the case of a fire, the optimized ventilator can reduce the temperature of the ventilator faster than the original ventilator, indicating better smoke exhaust performance. The reason for this effect is that, when the optimized natural ventilator rotates, the rotation of the blades creates a flow field with a more evenly distributed wind speed. The experiments proved that natural ventilators can be optimized by adding a fan system. The results of this study can be applied to effectively improve the ventilation performance of natural ventilators to quickly exhaust smoke in building and tunnel fires, and provide a reference for related research on natural ventilators.

Abstract This paper presents an investigation on the effect of fire intensity of a wind driven surface fire, similar to a large wildfire, on an idealized structure located downstream from the fire source. A numerical simulation was conducted using an open source CFD code called Fire FOAM, which is a transient solver for fire simulation and turbulent diffusion flames, supported by a large eddy simulation (LES) solver for incompressible flow. The numerical data were verified using the aerodynamic experimental data of a full-scale building model with no fire effects. An idealized cubic obstacle representing a simplified building with the dimension of 6 × 6 × 6 m; is considered downstream from the fire source. Different fire intensity values of the fire line representing different grassland fuels were simulated to analyse the impact of wind-fire interaction on a built area. To solve the problem, a coupled velocity and pressure method was applied through a PIMPLE scheme in FireFoam solver of OpenFoam platform. There is a good agreement between simulated results and experimental measurements with a maximum error of 18%, which confirms the validity and accuracy of the model. The results showed that by increasing the fire intensity; the velocity of the crosswind stream increases, which causes low-density air and generates an extra stream behind the fire plume. It was also found that increasing fire intensity from 10 MW/m to 18 MW/m raises the integrated temperature on the ground near the building and on the surface of the building by 26%, and 69%, respectively.

Abstract Massive wildfires and extreme fire behavior are becoming more frequent across the western United States, creating a need to better understand how megafire behavior will evolve in our warming world. Here, the fire spread model Prometheus is used to simulate the initial explosive growth of the 2020 August Complex, which occurred in northern California (CA) mixed conifer forests. High temperatures, low relative humidity, and daytime southerly winds were all highly correlated with extreme rates of modeled spread. Fine fuels reached very dry levels, which accelerated simulation growth and heightened fire heat release (HR). Model sensitivity tests indicate that fire growth and HR are most sensitive to aridity and fuel moisture content. Despite the impressive early observed growth of the fire, shifting the simulation ignition to a very dry September 2020 heatwave predicted a >50% increase in growth and HR, as well as increased nighttime fire activity. Detailed model analyses of how extreme fire behavior develops can help fire personnel prepare for problematic ignitions.

Abstract In this study, the interaction of two parallel line fires with a length-width ratio of greater than 50 was investigated and compared to a single line fire. Considering different length–width ratios and spacings between the fire sources, experiments were carried out to analyze the fire characteristics,such as the burning rate, the flame-merging state, the flame height, the flame tilt angle, and the flame length of the line fires. Its regularity was revealed by combining two mechanisms, namely, heat feedback enhancement and air entrainment restriction. The results revealed that the burning rate under different length–width ratios shows a uniform law, which increases first and then decreases with a greater spacing between the fire sources. There is a special relationship between the flame merging probability Pm and the dimensionless characteristic parameters (S/ZC)/(L/d)0.27. Based on this relationship, a critical criterion of flame merging can be obtained as (S/ZC)/(L/d)0.27 = 2.38. In addition, the height and the length of the flame were studied to better describe the flame shape when the flame is tilted. Since the flame is bent, the flame length has an abrupt change at a specific position, and the inclination angle also has the same phenomenon. Finally, it was found that the influence of the length–width ratio on the line fires is relatively limited, which is further weakened under a greater length–width ratio.

Abstract The simulation of forest fire spread is a key problem for the management of fire, and Cellular Automata (CA) has been used to simulate the complex mechanism of the fire spread for a long time. The simulation of CA is driven by the rate of fire spread (ROS), which is hard to estimate, because some input parameters of the current ROS model cannot be provided with a high precision, so the CA approach has not been well applied yet in the forest fire management system to date. The forest fire spread simulation model LSTM-CA using CA with LSTM is proposed in this paper. Based on the interaction between wind and fire, S-LSTM is proposed, which takes full advantage of the time dependency of the ROS. The ROS estimated by the S-LSTM is satisfactory, even though the input parameters are not perfect. Fifteen kinds of ROS models with the same structure are trained for different cases of slope direction and wind direction, and the model with the closest case is selected to drive the transmission between the adjacent cells. In order to simulate the actual spread of forest fire, the LSTM-based models are trained based on the data captured, and three correction rules are added to the CA model. Finally, the prediction accuracy of forest fire spread is verified though the KAPPA coefficient, Hausdorff distance, and horizontal comparison experiments based on remote sensing images of wildfires. The LSTM-CA model has good practicality in simulating the spread of forest fires.

Abstract Heavy smoke from building fires is the main cause of casualties. As smoke typically diffuses through building openings, smoke control performance of building openings is critical to survival and requires considerable attention. In the past, the detection method could only be used in the laboratory, and the detection equipment could not be moved. Therefore, the main purpose of this research was to develop a methodology for field testing of smoke control properties of doors in order to ensure that the smoke control performance of doors tested in the laboratory and doors installed in the field can be realized without any discrepancy. Furthermore, this test method underwent a comparison test with the CNS 15038 “Method of Test for Evaluating Smoke Control Performance of Doors” for the same subject. The test results showed no significant difference based on independent sample testing, demonstrating the feasibility of this test method and test apparatus. The instrument developed by this research is light and easy to carry, and the operation method is simple. Such a test method can be applied to different doors and is non-destructive, non-hazardous, and reusable. In the future, by extending the design principle of the system, this test method can be applied to other fire protection equipment for the inspection of smoke control capabilities and can be used as a reference for relevant organizations to establish test specifications and standards.

Abstract Fire alarm systems are typically equipped with various sensors such as heat, smoke, and gas detectors. These provide fire alerts and notifications of emergency exits when a fire has been detected. However, such systems do not give early warning in order to allow appropriate action to be taken when an alarm is first triggered, as the fire may have already caused severe damage. This paper analyzes a new dataset gathered from controlled realistic fire experiments conducted in an indoor laboratory environment. The experiments were conducted in a controlled manner by triggering the source of fire using electrical devices and charcoal on paperboard, cardboard or clothing. Important data such as humidity, temperature, MQ139, Total Volatile Organic Compounds (TVOC) and eCO2 were collected using sensor devices. These datasets will be extremely valuable to researchers in the machine learning and data science communities interested in pursuing novel advanced statistical and machine learning techniques and methods for developing early fire detection systems. The analysis of the collected data demonstrates the possibility of using eCO2 and TVOC reading levels for early detection of smoldering fires. The experimental setup was based on Low-Power Wireless Area Networks (LPWAN), which can be used to reliably deliver fire-related data over long ranges without depending on the status of a cellular or WiFi Network.

Abstract The requirements for the fire resistance of steel structures of oil and gas facilities for transportation and production of hydrocarbons are considered (structures of tankers and offshore platforms). It is found that the requirements for the values of fire resistance of structures under hydrocarbon rather than standard fire conditions are given only for offshore stationary platforms. Experimental studies on the loss of integrity (E) and thermal insulating capacity (I) of steel bulkheads and deck with mineral wool under standard and hydrocarbon fire regimes are presented. Simulation of structure heating was performed, which showed a good correlation with the experimental results (convective heat transfer coefficients for bulkheads of class H: 50 W/m2 ·K; for bulkheads of class A: 25 W/m2 ·K). The consumption of mineral slabs and endothermic mat for the H-0 bulkhead is predicted. It is calculated that under a standard fire regime, mineral wool with a density of 80–100 kg/m2 and a thickness of 40 to 85 mm should be used; under a hydrocarbon fire regime, mineral wool with a density above 100 kg/m2 and a thickness of 60–150 mm is required. It is shown that to protect the structures of decks and bulkheads in a hydrocarbon fire regime, it is necessary to use 30–40% more thermal insulation and apply the highest density of fire-retardant material compared to the standard fire regime. Parameters of thermal conductivity and heat capacity of the applied flame retardant in the temperature range from 0 to 1000 ◦C were clarified.

Abstract Wildland firefighters continue to die in the line of duty. Flammable landscapes intersect with bold but good-intentioned doers and trigger entrapment—a situation where personnel is unexpectedly caught in fire behaviour-related, life-threatening positions where planned escape routes or safety zones are absent, inadequate, or compromised. We often document, share and discuss these stories, but many are missed, especially when the situation is a near miss. Entrapment continues to be a significant cause of wildland firefighter deaths. Why do we still not know how to prevent them? We review a selection of entrapment reports courtesy of the Wildland Fire Lessons Learned Centre (WFLLC) and focus on human factors involved in entrapment rather than the specifics of fire behaviour and the environment. We found that in order for operational supervisors to make more informed strategic and tactical decisions, a more holistic and complete trend analysis is necessary of the existing database of entrapment incidents. Analysis of the entrapment data would allow training to include a more fulsome understanding of when suppression resources are applying strategies and tactics that might expose them to a higher likelihood of entrapment. Operational supervisors would make more informed decisions as to where and when to deploy resources in critical situations in order to reduce the exposure to unnecessary risk of entrapment.

Abstract Invasive species are an environmental problem affecting worldwide ecosystems. In the case of Acacia dealbata Link., the negative impacts affect the productivity of the forests due to the competition established with native species while contributing to a significant increment in the available fuel load, increasing the risk of fire. In Portugal, chemical and mechanical methods are mostly used in the control of these species. However, the costs are often unsustainable in the medium term, being abandoned before completing the tasks, allowing the recovery of the invasive species.The establishment of value chains for the biomass resulting from these actions was pointed out by several authors as a solution for the sustainability of the control process, as it contributes to reducing costs. However, the problems in quantifying the biomass availability make it challenging to organize and optimize these actions. This work, which started from a dendrometrical analysis carried out in stands of A. dealbata, created a model to assess woody biomass availability. The model proved to be statistically significant for stands with trees younger than 20 years old. However, the amount of data collected and the configuration of the settlements analyzed do not allow extrapolation of the model presented to older settlements.

Abstract Firebrand spotting is a potential threat to people and infrastructure, which is difficult to predict and becomes more significant when the size of a fire and intensity increases. To conduct realistic physics-based modeling with firebrand transport, the firebrand generation data such as numbers, size, and shape of the firebrands are needed. Broadly, the firebrand generation depends on atmospheric conditions, wind velocity and vegetation species. However, there is no experimental study that has considered all these factors although they are available separately in some experimental studies. Moreover, the experimental studies have firebrand collection data, not generation data. In this study, we have conducted a series of physics-based simulations on a trial-and-error basis to reproduce the experimental collection data, which is called an inverse analysis. Once the generation data was determined from the simulation, we applied the interpolation technique to calibrate the effects of wind velocity, relative humidity, and vegetation species. First, we simulated Douglas-fir (Pseudotsuga menziesii) tree-burning and quantified firebrand generation against the tree burning experiment conducted at the National Institute of Standards and Technology (NIST). Then, we applied the same technique to a prescribed forest fire experiment conducted in the Pinelands National Reserve (PNR) of New Jersey, the USA. The simulations were conducted with the experimental data of fuel load, humidity, temperature, and wind velocity to ensure that the field conditions are replicated in the experiments. The firebrand generation rate was found to be 3.22 pcs/MW/s (pcs-number of firebrands pieces) from the single tree burning and 4.18 pcs/MW/s in the forest fire model. This finding was complemented with the effects of wind, vegetation type, and fuel moisture content to quantify the firebrand generation rate.

Abstract Safety zones (SZs) are critical tools that can be used by wildland firefighters to avoid injury or fatality when engaging a fire. Effective SZs provide safe separation distance (SSD) from surrounding flames, ensuring that a fire’s heat cannot cause burn injury to firefighters within the SZ. Evaluating SSD on the ground can be challenging, and underestimating SSD can be fatal. We introduce a new online tool for mapping SSD based on vegetation height, terrain slope, wind speed, and burning condition: the Safe Separation Distance Evaluator (SSDE). It allows users to draw a potential SZ polygon and estimate SSD and the extent to which that SZ polygon may be suitable, given the local landscape, weather, and fire conditions. We begin by describing the algorithm that underlies SSDE. Given the importance of vegetation height for assessing SSD, we then describe an analysis that compares LANDFIRE Existing Vegetation Height and a recent Global Ecosystem Dynamics Investigation (GEDI) and Landsat 8 Operational Land Imager (OLI) satellite image-driven forest height dataset to vegetation heights derived from airborne lidar data in three areas of the Western US. This analysis revealed that both LANDFIRE and GEDI/Landsat tended to underestimate vegetation heights, which translates into an underestimation of SSD. To rectify this underestimation, we performed a bias-correction procedure that adjusted vegetation heights to more closely resemble those of the lidar data. SSDE is a tool that can provide valuable safety information to wildland fire personnel who are charged with the critical responsibility of protecting the public and landscapes from increasingly intense and frequent fires in a changing climate. However, as it is based on data that possess inherent uncertainty, it is essential that all SZ polygons evaluated using SSDE are validated on the ground prior to use.

Abstract Key Biodiversity Areas (KBAs) are sites that contribute significantly to the protection of the planet’s biodiversity. In this study, we evaluated the annual burned areas and the intensity of the fires that affected Bolivia and its 58 KBAs (23.3 million ha) over the last 20 years (2001–2020). In particular, we analyzed the impact of wildfires on the distribution of Bolivian birds at the levels of overall species richness, endemic species and threatened species (Critically Endangered, Endangered, Vulnerable). We found that at the KBA level, the cumulative area of wildfires was 21.6 million ha, while the absolute area impacted was 5.6 million ha. The KBAs most affected by the wildfires are located in the departments of Beni and Santa Cruz; mainly in the KBAs Área Natural de Manejo Integrado San Matías, Oeste del río Mamoré, Este del río Mamoré, Noel Kempff Mercado and Área Natural de Manejo Integrado Otuquis. The wildfires impacted the distribution of 54 threatened species and 15 endemic species in the KBAs. Based on the results of this study, it is a priority to communicate to Bolivian government authorities the importance of KBAs as a strategy for the conservation of the country’s biodiversity and the threats resulting from anthropogenic fires.