Fire Spread Rate Research Articles

Experimental Investigation of the Combustion Characteristics and Thermal Hazards of Methylsilyl-Modified Silica Aerogels

The thermal safety of hydrophobic silica aerogels (SAs) is essential to thermal insulation applications. Herein, trimethylchlorosilane (TMCS), dimethyldichlorosilane (DMDCS), and methyltrichlorosilane (MTCS) were employed as surface modifiers to prepare three different methylsilyl-modified SAs (i.e., TSA, DSA, and MSA) and their combustion characteristics and thermal hazards were experimentally studied in detail. The cone calorimeter test found that the three SAs have similar combustion processes and the variations in ignition time and fire spread rate with the heat flux obey simple logarithmic and linear relationships, respectively. It further found that TSA has the most methylsilyl groups on silica skeletons and thus has the largest heat release, followed by DSA and MSA in turn, implying that TSA has the greatest fire hazard among the three SAs. These results further demonstrate that the type and quantity of methylsilyl groups on the skeletons of SAs significantly affect the thermal hazard of methylsilyl-modified SAs. In addition, the combustion mechanism of the methylsilyl-modified SAs is discussed. In total, this work experimentally studies the combustion characteristics of methylsilyl-modified SAs and compares their thermal hazards, clarifying the potential fire risk of methylsilyl-modified SAs in practical thermal insulation applications.

Experimental study of flame morphology in slope buildings under the influence of aspect ratio and ambient wind

Slope structures are commonly used in buildings, but such slope structures can exacerbate the rate of fire spread, complicate building fire safety and suppression, and lead to injuries, deaths, and property damage. Particularly, the thermal hazards posed by ambient wind on sloped fires remain unquantified. In this study, a propane burner was used to simulate the flame morphology behavior of a sloped building fire. 480 tests were conducted with varying aspect ratios (1∼8) of the fire source, different ambient winds (0 m/s∼3.5 m/s), and slope inclination angles (0°∼40°). Results demonstrate that the flame length initially increases and then decreases with an increment in ambient wind velocity. Moreover, with an increased aspect ratio of the fire source (length-to-width ratio), the turning point at which the flame length peaks shift to occur at a lower wind velocity threshold. The tilt angle and height of the flame change (respectively increases and decreases) significantly at lower ambient wind speeds and they tend to asymptotically approach respective constant values. As the ambient wind is further promoted. Existing physical models of flame morphology do not consider the combined effects of fire source aspect ratio, slope inclination angle, and ambient wind. A new slope entrainment restriction factor (EF) was proposed based on an analysis of the upward and leeward entrainment volumes. Using this factor, new models for flame morphology (including flame length, flame tilt angle, and flame height) were established. The accuracy and generalizability of the new flame models have been validated using reference data.

OPTIMIZING THE AMOUNT OF FLAME RETARDANT USED FOR SPRUCE WOOD

The study investigated the effect of the amount of selected retardant coatings produced and used in the Slovak Republic on the fire resistance of spruce wood samples. Experiments were conducted for two different types of flame retardants: intumescent flame retardant (IFR) and inorganic salt-based flame retardant (IS). Based on different amounts of coating applied to spruce wood samples, the important parameters as mass loss, mass loss rate and fire spread rate were determined. The experiment consisted of applying a flame source to the samples at an angle of 45° and monitoring the mass of the samples during the experiment. The findings show that when IFR is used, the protection effect of the wooden samples increases linearly with the amount of coating. However, for the samples on which an IS flame retardant was applied, a higher amount of coating had no effect on increasing the fire resistance of the wood. In this case, the average total mass loss was the same regardless of the amount of coating, yet a significant retardation effect was observed compared to the untreated samples. Samples treated with IFR showed a lower total mass loss and also a significantly lower maximum mass loss rate compared to the samples with applied IS flame retardant.

Can green firebreaks help balance biodiversity, carbon storage and wildfire risk?

Green firebreaks (strategically placed plantings of low-flammability vegetation) are designed to reduce the rate of fire spread and thereby increase the suppressibility of fires. Successful examples have led to some fire-prone regions investing heavily in the establishment of green firebreaks as a method of reducing fire risk while improving biodiversity and carbon storage. However, beyond small-scale case studies there has been little research quantitatively exploring the interactions among biodiversity, carbon, and wildfire risk in relation to green firebreaks. Here, we combine a Bayesian Network (BN) analysis, and fire simulations in PHOENIX RapidFire (hereafter Phoenix), to identify planting designs that reduce wildfire risks while also providing positive biodiversity and carbon outcomes. Using a BN analysis, we prioritised optimal planting designs as the combination of elements (e.g., stem density, distance from houses, shrub design, age etc.) that delivered the greatest increase in biodiversity and carbon while reducing fire risk to people and property for eight sites across south-eastern Australia. We ranked combinations of planting designs, prioritising house, and life loss first, to identify optimal designs. Optimal planting designs varied among sites, although the design elements that best reduced risk to houses and lives were consistent. These elements included ‘scattered’ shrubs and planting densities of trees consistent with an open forest structure. Estimated fuel loads for the optimal planting design at each site were used to create a simulated revegetation area in Phoenix. We simulated fire behaviour in Phoenix across a grid of ∼1000 ignitions for each site, and for up to 54 historic weather conditions for a 'current fuel’ scenario (no green firebreaks present) compared with a ‘green firebreak fuel’ scenario. We found that the establishment of a green firebreak did not result in significant changes to fire behaviour at most sites. In some cases, it reduced risk to people and property, and where fire behaviour did change in terms of intensity, frequency, ember attack and overall risk, the differences relative to the current fuel scenario were less than two percent. Overall, simulated green firebreaks in most cases were found to provide biodiversity and carbon benefits without increasing fire risk. These findings illustrate their potential as an effective nature-based solution for managing multiple priorities; however, further testing of real plantings is required to evaluate this potential as an at-scale solution.

Applying and Evaluating the Modified Method of the Rothermel Model under No-Wind Conditions for Pinus koraiensis Plantations

Pinus koraiensis is one of the important tree species in Northeast China. Due to its high pine-needle-oil content and the density of human activities in its habitat, the forest-fire prevention situation is severe in the context of climate change. The rate of surface-fire spread is one of the key indicators for scientifically advancing early fire prevention and is crucial for guiding forest firefighting operations. In this study, we investigated how moisture content, load, and slope impact the surface-fire spread rate using indoor-simulated fire-spread experiments. Furthermore, we analyzed the limitations in the Rothermel model for predicting the surface-fire spread rate in P. koraiensis plantations and proposed modifications to the model by the modification method of priority to no-wind or slope conditions and slope conditions. Additionally, we evaluated the prediction accuracy of the original Rothermel model and two other modified models on the surface-fire spread rate. A high moisture content and low slope demonstrated an absolute inhibitory effect on the rate of surface-fire spread, whereas the promotional effect of a low moisture content and high slope was easily disturbed by the other factors. Under high-slope conditions, an overestimation situation was observed in the Rothermel model. Both of the modification methods involving priority to no-wind or slope conditions and slope conditions could improve this situation. Furthermore, the modification method demonstrated a better improvement effect on the prediction accuracy. Our findings provide valuable insights for refining the Rothermel model and offer guidance for improving the accuracy of predicting fire spread rates and behavior for Pinus koraiensis. This bears immense significance for advancing the understanding and calculation of the ROS of forest fires in the region.

Evaluation of an In‐Canopy Wind and Wind Adjustment Factor Model for Wildfire Spread Applications Across Scales

AbstractThe representation of vegetative sub‐canopy wind is critical in numerical weather prediction (NWP) models for the determination of the air‐surface exchange processes of heat, momentum, and trace gases. Because of the relationship between wind speed and fire behaviors, the influence of the canopy on near‐surface wind speed is critical for prognostic fire spread models used in regional NWP models. In practice, the wind speed at the midflame point of fires (midflame wind speed) is used to determine the rate of fire spread. However, the wind speeds from most in situ measurements and NWP models are taken at some reference height above the canopy and fire flames. Hence, this study develops a modular and computationally‐efficient one‐dimensional model set composed of a canopy wind model and a wind adjustment factor (WAF) model for NWP applications across scales. The model set uses prescribed foliage shape functions to represent the vertical vegetation profile and its impacts on the three‐dimensional structure of horizontal wind speeds. Results from the canopy wind model well agree with ground‐based observations with average mean absolute bias, root mean square error and determination coefficients around 0.18 m s−1, 0.40 m s−1and 0.90, respectively. The WAF model provides midflame wind speeds by estimating the WAF based on canopy, fire and flame characteristics. Various user‐definable options provide flexibility to adapt to variations in canopy characteristics and additional complexities associated with wildfires. The model set is expected to improve NWP models by providing an improved representation of the sub‐grid wind flows at any spatial scale.

Stochastic bulk density in the fire spread model

AbstractIn this study, we investigate the impact of inherent randomness on fire spread rates, with a particular focus on the stochastic parameter ε, representing the ratio of effective to actual fuel bulk density. By employing various probability distributions, such as the beta random distribution model ε, we explore the complex interplay between wind and slope factors in determining fire behavior. Our 3D visualizations and density plots illuminate the multidimensional nature of fire spread, emphasizing the significant role of stochastic variability in enhancing the accuracy of fire behavior models. This approach not only deepens our theoretical understanding but also provides valuable insights for improving fire management strategies.

Photogrammetric Measurement of Grassland Fire Spread: Techniques and Challenges with Low-Cost Unmanned Aerial Vehicles

The spread of natural fires is a complex issue, as its mathematical modeling needs to consider many parameters. Therefore, the results of such modeling always need to be validated by comparison with experimental measurements under real-world conditions. Remote sensing with the support of satellite or aerial sensors has long been used for this purpose. In this article, we focused on data collection with an unmanned aerial vehicle (UAV), which was used both for creating a digital surface model and for dynamic monitoring of the spread of controlled grassland fires in the visible spectrum. We subsequently tested the impact of various processing settings on the accuracy of the digital elevation model (DEM) and orthophotos, which are commonly used as a basis for analyzing fire spread. For the DEM generated from images taken during the final flight after the fire, deviations did not exceed 0.1 m compared to the reference model from LiDAR. Scale errors in the model with only approximal WGS84 exterior orientation parameters did not exceed a relative accuracy of 1:500, and possible deformations of the DEM up to 0.5 m in height had a minimal impact on determining the rate of fire spread, even with oblique images taken at an angle of 45°. The results of the experiments highlight the advantages of using low-cost SfM photogrammetry and provide an overview of potential issues encountered in measuring and performing photogrammetric processing of fire spread.

Iterative smoothing for change-point regression function estimation

Understanding wildfire spread in Canada is critical to promoting forest health and protecting human life and infrastructure. Quantifying fire spread from noisy images, where change-point boundaries separate regions of fire, is critical to accurately estimating fire spread rates. The challenge lies in denoising the fire images and accurately identifying highly non-linear fire lines without smoothing over boundaries. In this paper, we develop an iterative smoothing algorithm for change-point data that utilizes oversmoothed estimates of the underlying data generating process to inform re-smoothing. We demonstrate its effectiveness on simulated one- and two-dimensional change-point data, and robustness to response outliers. Then, we apply the methodology to fire spread images from laboratory micro-fire experiments and show that the regions fuel, burning and burnt-out are smoothed while boundaries are preserved.

A Survey of Flow Field and Combustion Characteristics under Subatmospheric Pressure

This paper presents a summary of and introduction to research on high-altitude and subatmospheric combustion concerning turbine and scramjet engines. The investigation includes theoretical analysis, experimental studies, and numerical simulations. The analysis encompasses the flow field structure, fuel atomization, and combustion performance. Subsequently, recent research on the combustion performance of liquid fuels, solid fuels, and gaseous fuels under high-altitude and low-pressure plateau environments is reviewed. This includes an evaluation of flame height, flame temperature, combustion rate, fire spread rate, and heat radiation flux. Additionally, combustion performance prediction models for high-altitude environments based on experimental and theoretical analysis have been introduced. Lastly, issues in subatmospheric combustion in the aerospace and plateau fire fields are presented based on the current research.

Relationships of Fire Rate of Spread with Spectral and Geometric Features Derived from UAV-Based Photogrammetric Point Clouds

Unmanned aerial vehicles (UAVs) equipped with RGB, multispectral, or thermal cameras have demonstrated their potential to provide high-resolution data before, during, and after wildfires and prescribed burns. Pre-burn point clouds generated through the photogrammetric processing of UAV images contain geometrical and spectral information of vegetation, while active fire imagery allows for deriving fire behavior metrics. This paper focuses on characterizing the relationship between the fire rate of spread (RoS) in prescribed burns and a set of independent geometrical, spectral, and neighborhood variables extracted from UAV-derived point clouds. For this purpose, different flights were performed before and during the prescribed burning in seven grasslands and open forest plots. Variables extracted from the point cloud were interpolated to a grid, which was sized according to the RoS semivariogram. Random Forest regressions were applied, obtaining up to 0.56 of R2 in the different plots studied. Geometric variables from the point clouds, such as planarity and the spectral normalized blue–red difference index (NBRDI), are related to fire RoS. In analyzing the results, the minimum value of the eigenentropy (Eigenentropy_MIN), the mean value of the planarity (Planarity_MEAN), and percentile 75 of the NBRDI (NBRDI_P75) obtained the highest feature importance. Plot-specific analyses unveiled distinct combinations of geometric and spectral features, although certain features, such as Planarity_MEAN and the mean value of the grid obtained from the standard deviation of the distance between points (Dist_std_MEAN), consistently held high importance across all plots. The relationships between pre-burning UAV data and fire RoS can complement meteorological and topographic variables, enhancing wildfire and prescribed burn models.

Fuel Drivers of Fire Behaviour in Coastal Mallee Shrublands

Coastal mallee shrubland wildfires present challenges for accurately predicting fire spread sustainability and rate of spread. In this study, we assess the fuel drivers contributing to coastal mallee shrubland fires. A review of shrubland fire behaviour models and fuel metrics was conducted to determine the current practice of assessing shrubland fuels. This was followed by workshops designed to elicit which fuel structural metrics are key drivers of fire behaviour in coastal mallee shrublands. We found that height is the most commonly used fuel metric in shrubland fire models due to the ease of collection in situ or as a surrogate for more complex fuel structures. Expert workshop results suggest that cover and connectivity metrics are key to modelling fire behaviour in coastal mallee shrublands. While height and cover are frequently used in fire models, we conclude that connectivity metrics would offer additional insights into fuel drivers in mallee shrublands. Future research into coastal mallee fire behaviour should include the measurements of fuel height, cover, and horizontal and vertical connectivity.

Ungulates mitigate the effects of drought and shrub encroachment on the fire hazard of Mediterranean oak woodlands.

Climate change is increasing the frequency of droughts and the risk of severe wildfires, which can interact with shrub encroachment and browsing by wild ungulates. Wild ungulate populations are expanding due, among other factors, to favorable habitat changes resulting from land abandonment or land-use changes. Understanding how ungulate browsing interacts with drought to affect woody plant mortality, plant flammability, and fire hazard is especially relevant in the context of climate change and increasing frequency of wildfires. The aim of this study is to explore the combined effects of cumulative drought, shrub encroachment, and ungulate browsing on the fire hazard of Mediterranean oak woodlands in Portugal. In a long-term (18 years) ungulate fencing exclusion experiment that simulated land abandonment and management neglect, we investigated the population dynamics of the native shrub Cistus ladanifer, which naturally dominates the understory of woodlands and is browsed by ungulates, comparing areas with (no fencing) and without (fencing) wild ungulate browsing. We also modeled fire behavior in browsed and unbrowsed plots considering drought and nondrought scenarios. Specifically, we estimated C. ladanifer population density, biomass, and fuel load characteristics, which were used to model fire behavior in drought and nondrought scenarios. Overall, drought increased the proportion of dead C. ladanifer shrub individuals, which was higher in the browsed plots. Drought decreased the ratio of live to dead shrub plant material, increased total fuel loading, shrub stand flammability, and the modeled fire parameters, that is, rate of surface fire spread, fireline intensity, and flame length. However, total fuel load and fire hazard were lower in browsed than unbrowsed plots, both in drought and nondrought scenarios. Browsing also decreased the population density of living shrubs, halting shrub encroachment. Our study provides long-term experimental evidence showing the role of wild ungulates in mitigating drought effects on fire hazard in shrub-encroached Mediterranean oak woodlands. Our results also emphasize that the long-term effects of land abandonment can interact with climate change drivers, affecting wildfire hazard. This is particularly relevant given the increasing incidence of land abandonment.

Performance of various water-based fire suppression systems in tunnels with longitudinal ventilation

Low pressure, medium pressure and high pressure water-based fire suppression systems were tested in a medium scale tunnel (scale 1:3). The primary objective was to investigate which of these systems are most effective in the suppression or control of different types of tunnel fires. The default low, medium and high pressure systems refer to full scale water flow rates of 10 mm/min, 6.8 mm/min and 3.7 mm/min, respectively. Some other water densities were also tested to investigate the effects, as well as different ventilation velocities and activation criteria. Several series of fire tests were conducted for different fire scenarios. The fire scenarios considered included idle wood pallet fires, loosely packed wood crib fires, loosely packed wood and plastic crib fires, and pool fires, with or without a top cover on the fuel load. Comparisons of the three default systems based on the three parameters: heat release rate, energy released and possibility of fire spread, show that the performance of the default low pressure system is usually the most effective based on the parameters studied. The default high pressure system usually yields results less effective in comparison to the default low pressure system. The performance of the default medium pressure system usually lies in between them. The high pressure system behaves very differently in comparison to the others, in terms of tunnel ventilation velocity, water density, operating pressure, and the presence of the top cover.

Sensitivity of Simulated Fire‐Generated Circulations to Fuel Characteristics During Large Wildfires

AbstractCoupled fire‐atmosphere models often struggle to simulate important fire processes like fire generated flows, deep flaming fronts, extreme updrafts, and stratospheric smoke injection during large wildfires. This study uses the coupled fire‐atmosphere model, WRF‐Fire, to examine the sensitivities of some of these phenomena to the modeled total fuel load and its consumption. Specifically, the 2020 Bear Fire and 2021 Caldor Fire in California's Sierra Nevada are simulated using three fuel loading scenarios (1X, 4X, and 8X LANDFIRE derived surface fuel), while controlling the fire rate of spread using observations. This approach helps isolate the fuel loading and consumption needed to produce fire‐generated winds and plume rise comparable to radar observations of these events. Increasing fuel loads and corresponding fire residence time in WRF‐Fire leads to deep plumes in excess of 10 km, strong vertical velocities of 40–45 m s−1, and combustion fronts several kilometers in width (in the along wind direction). These results indicate that LANDFIRE‐based surface fuel loads in WRF‐Fire likely under‐represent fuel loading, having significant implications for simulating landscape‐scale wildfire processes, associated impacts on spread, and fire‐atmosphere feedbacks.

Systematically tracking the hourly progression of large wildfires using GOES satellite observations

Abstract. In the western United States, prolonged drought, a warming climate, and historical fuel buildup have contributed to larger and more intense wildfires as well as to longer fire seasons. As these costly wildfires become more common, new tools and methods are essential for improving our understanding of the evolution of fires and how extreme weather conditions, including heat waves, windstorms, droughts, and varying levels of active-fire suppression, influence fire spread. Here, we develop the Geostationary Operational Environmental Satellites (GOES)-Observed Fire Event Representation (GOFER) algorithm to derive the hourly fire progression of large wildfires and create a product of hourly fire perimeters, active-fire lines, and fire spread rates. Using GOES-East and GOES-West geostationary satellite detections of active fires, we test the GOFER algorithm on 28 large wildfires in California from 2019 to 2021. The GOFER algorithm includes parameter optimizations for defining the burned-to-unburned boundary and correcting for the parallax effect from elevated terrain. We evaluate GOFER perimeters using 12 h data from the Visible Infrared Imaging Radiometer Suite (VIIRS)-derived Fire Event Data Suite (FEDS) and final fire perimeters from the California's Fire and Resource Assessment Program (FRAP). Although the GOES imagery used to derive GOFER has a coarser resolution (2 km at the Equator), the final fire perimeters from GOFER correspond reasonably well to those obtained from FRAP, with a mean Intersection-over-Union (IoU) of 0.77, in comparison to 0.83 between FEDS and FRAP; the IoU indicates the area of overlap over the area of the union relative to the reference perimeters, in which 0 is no agreement and 1 is perfect agreement. GOFER fills a key temporal gap present in other fire tracking products that rely on low-Earth-orbit imagery, where perimeters are available at intervals of 12 h or longer or at ad hoc intervals from aircraft overflights. This is particularly relevant when a fire spreads rapidly, such as at maximum hourly spread rates of over 5 km h−1. Our GOFER algorithm for deriving the hourly fire progression using GOES can be applied to large wildfires across North and South America and reveals considerable variability in the rates of fire spread on diurnal timescales. The resulting GOFER product has a broad set of potential applications, including the development of predictive models for fire spread and the improvement of atmospheric transport models for surface smoke estimates. The resulting GOFER product has a broad set of potential applications, including the development of predictive models for fire spread and the improvement of atmospheric transport models for surface smoke estimates (https://doi.org/10.5281/zenodo.8327264, Liu et al., 2023).

Mapping the distance between fire hazard and disaster for communities in Canadian forests.

Communities interspersed throughout the Canadian wildland are threatened by fires that have become bigger and more frequent in some parts of the country in recent decades. Identifying the fireshed (source area) and pathways from which wildland fire may ignite and spread from the landscape to a community is crucial for risk-reduction strategy and planning. We used outputs from a fire simulation model, including fire polygons and rate of spread, to map firesheds, fire pathways and corridors and spread distances for 1980 communities in the forested areas of Canada. We found fireshed sizes are larger in the north, where the mean distances between ecumene and fireshed perimeters were greater than 10 km. The Rayleigh Z test indicated that simulated fires around a large proportion of communities show significant directional trends, and these trends are stronger in the Boreal Plains and Shields than in the Rocky Mountain area. The average distance from which fire, when spreading at the maximum simulated rate, could reach the community perimeter was approximately 5, 12 and 18 km in 1, 2 and 3 days, respectively. The average daily spread distances increased latitudinally, from south to north. Spread distances were the shortest in the Pacific Maritime, Atlantic Maritime and Boreal Plains Ecozones, implying lower rates of spread compared to the rest of the country. The fire corridors generated from random ignitions and from ignitions predicted from local fire history differ, indicating that factors other than fuel (e.g. fire weather, ignition pattern) play a significant role in determining the direction that fires burn into a community.

Modification of the Rothermel model parameters – the rate of surface fire spread of Pinus koraiensis needles under no-wind and various slope conditions

Background The prediction accuracy for the rate of surface fire spread varies in different regions; thus, increasing the prediction accuracy for local fuel types to reduce the destructive consequences of fire is critically needed. Aims The objective of this study is to improve the Rothermel model’s accuracy in predicting the ROS for surface fuel burning in planted forests of Pinus koraiensis in the eastern mountains of north-east China. Methods Fuel beds with various fuel loads and moisture content was constructed on a laboratory burning bed, 276 combustion experiments were performed under multiple slope conditions, and the ROS data from the combustion experiments were used to modify the related parameters in the Rothermel model. Results The surface fire spread rate in Pinus koraiensis plantations was directly predicted using the Rothermel model but had significant errors. The Rothermel model after modification predicted the following: MRE = 25.09%, MAE = 0.46 m min−1, and R2 = 0.80. Conclusion The prediction accuracy of the Rothermel model was greatly enhanced through parameter tuning based on in-lab combustion experiments Implications This study provides a method for the local application of the Rothermel model in China and helps with forest fire fighting and management in China.

Providing a model to evaluate the spread of fire in a chemical warehouse using numerical simulation and Bayesian network

Chemical warehouses are one of the important sources in process units. Locations are one of the issues that should be investigated in closed environments due to the many types of chemicals and storage conditions. In this study, fire dynamics simulation (FDS), was used to simulation of fire in the presence and non-presence of the ventilation system. Then the spread of fire in the warehouse was evaluated based on domino methods and finally the Bayesian network (BN) was used to update the rate of fire spread. The simulation results in this approach showed that the highest amount of heat flux related to iso-octane fire at L/D= 0.3 when the ventilation system is off and the doors are closed. The updated results of the fire spread modeling in BN showed that if a fire occurs in isooctane barrels, it has the highest rate of spread with a probability of 22% and the lowest rate of spread in Diglycolamine(DGA) barrels with a probability of 0.4%. From the results of this study, it is possible to understand the importance of arranging materials according to the principles of compatibility of chemical materials, and based on this, appropriate control measures can be provided.

Effect of Spruce Wood Density on Selected Fire-Technical Parameters during Thermal Loading

The paper evaluates the effect of spruce wood density on the parameters of mass loss and mass loss rate during exposure to thermal load. The intention was to determine whether the effect of density is still evident after the application of flame retardants to the test samples. Groups of samples with different densities under the same retardant treatment were compared. The differences in densities of the compared groups of samples were different for each flame retardant. Water-soluble flame retardants based on inorganic salts were used. For testing, a simple test method was used in which the samples were exposed to direct flame from a Bunsen burner. The results of the study are the findings of how wood density affects the burning process of the samples treated with flame retardants. Statistical evaluation of the experimental results shows a significant effect of wood density on the monitored parameters even when flame retardants are used. For a difference in sample densities of 244 kg·m−3, there was a density dependence of the mass loss rate, with the lower density samples having a higher mass loss rate (0.158%·s−1) over the whole experimental period compared to the higher density samples (0.077%·s−1). The ANOVA test also demonstrated the influence of density on the mass loss of the samples at the above density difference. At lower density differences (51 kg·m−3 and below), the effect of sample density on the observed parameters was no longer evident. The fire spread rate parameter was also investigated. Here, a linear correlation between the difference in sample densities and the difference in the values of the above parameter at high and low densities is observed with a reliability coefficient R2 = 0.99.