Search Results (14)

Forest sub-surface fires represent a challenging combustion phenomenon to control, and the process of smoldering is often overlooked in wildfire incidents. Traditional forest fire research has prioritized flaming combustion over smoldering dynamics, despite its critical risk factors including sustained high temperature and ground surface collapse that significantly endanger firefighter safety. This study focuses on The Daxing’an Mountains, a prime sub-surface fire-prone region in China, employing field investigations and controlled smoldering experiments to quantify the key risk factors for sub-surface fires suppression while elucidating moisture content’s regulatory effects. The results demonstrate that sub-surface smoldering fires maintain elevated temperatures with the surface peak temperature reaching 600.24 °C and sub-surface peak temperature up to 710.70 °C. The spread rate is relatively slow (maximum 27.00 cm/h), yet exhibits pronounced fluctuations along the vertical profile, creating a critical predisposition to overhanging collapse. The moisture content has extremely significant effects (p < 0.01) on key risk factors including surface temperature, sub-surface temperature, collapse time and ignition duration. Lower moisture content prompted earlier surface collapses, whereas higher moisture content displays delayed collapse but resulted in dangerously elevated temperatures at collapse points, presenting extreme suppression risks. Full article

Due to climate change, the electric vehicle (EV) industry is rapidly growing and drawing researchers interest. Driving conditions like mountainous roads, slick surfaces, and rough terrains illuminate the vehicles inherent nonlinearities. Under such scenarios, the behavior of power sources (fuel cell, battery, and super-capacitor), power processing units (converters), and power consuming units (traction motors) deviates from nominal operation. The increasing demand for FCHEVs necessitates control systems capable of handling nonlinear dynamics, while ensuring robust, precise energy distribution among fuel cells, batteries, and super-capacitors. This paper presents a DSMC strategy enhanced with Robust Uniform Exact Differentiators for FCHEV energy management. To optimally tune DSMC parameters, reduce chattering, and address the limitations of conventional methods, a hybrid metaheuristic framework is proposed. This framework integrates moth flame optimization (MFO) with the gravitational search algorithm (GSA) and Fractal Heritage Evolution, implemented through three spiral-based variants: MFOGSAPSO-A (Archimedean), MFOGSAPSO-H (Hyperbolic), and MFOGSAPSO-L (Logarithmic). Control laws are optimized using the Integral of Time-weighted Absolute Error (ITAE) criterion. Among the variants, MFOGSAPSO-L shows the best overall performance with the lowest ITAE for the fuel cell (56.38), battery (57.48), super-capacitor (62.83), and DC bus voltage (4741.60). MFOGSAPSO-A offers the most accurate transient response with minimum RMSE and MAE FC (0.005712, 0.000602), battery (0.004879, 0.000488), SC (0.002145, 0.000623), DC voltage (0.232815, 0.058991), and speed (0.030990, 0.010998)—outperforming MFOGSAPSO, GSA, and PSO. MFOGSAPSO-L further reduces the ITAE for fuel cell tracking by up to 29% over GSA and improves control smoothness. PSO performs moderately but lags under transient conditions. Simulation results conducted under EUDC validate the effectiveness of the MFOGSAPSO-based DSMC framework, confirming its superior tracking, faster convergence, and stable voltage control under transients making it a robust and high-performance solution for FCHEV. Full article

Forest fine fuels are a crucial component of surface fuels and play a key role in igniting forest fires. However, despite nearly 20 years of long-term prescribed burning management on Zhaobi Mountain in Xinping County, Yunnan Province, China, there remains a lack of specific quantification regarding the effectiveness of fine fuel management in Pinus yunnanensis forests. In this study, 10 m × 10 m sample plots were established on Zhaobi Mountain following one year of growth after prescribed burning. The plots were placed in a prescribed burning (PB) area and an unburned control (UB) area. We utilized indicators such as forest stand characteristics, fine fuel physicochemical properties, and potential fire behavior parameters for evaluation. The results indicate that prescribed burning at one-year intervals significantly affects stand characteristics, particularly in metrics such as crown base height, diameter breast height, and fuel load (p < 0.05). However, the physical and chemical properties of fine fuels did not show significant differences. Notably, the mean range of spread (RS) of PB fuels downhill was 43.3% lower than that of UB fuels, and the mean flaming height (FH) was 35.2% lower. The fire line intensity was <750 kW/m, categorizing it as a low-intensity fire. These findings provide data on the composition of fine fuels and the variables of fire behavior affected by prescribed burning, demonstrating that low-intensity prescribed burns can regulate fine fuels in the understory and maintain a stable regional fire risk level. Full article

Lake Markakol is located in a metal-rich mountain area of Kazakhstan. Metal input into the lake water and in the bottom sediments can be expected. Lead, cobalt and nickel monitoring in both near-surface and deep-water layers and in bottom sediments was carried out using flame atomic absorption spectrometric analyses. Lead contamination of surface water ranging from 2.6 to 6.8 µg/L occurs in all water samples with the exception of the surface water layer. In the deep-water section concentrations reach up to 13.0–16.2 µg/L. Cobalt concentrations range from 36.8 to 67.5 µg/L in the surface layer and from 25.5 to 69.2 µg/L in the deep-water layer. High values of nickel were found in the surface and bottom layers of the water, ranging from 13.5 to 49.0 and 17.2 to 49.0 µg/L, respectively. High concentrations of lead, cobalt and nickel were identified in all samples of the bottom sediments. The lead content in bottom sediments reaches 11.3, cobalt reaches 10.3–18.0 and nickel reaches 15.0 mg kg⁻¹. The results and their assessment can serve as a basis for future monitoring and measures to reduce pollution, restore the lake ecosystem and ensure the safety of fishery products for humans. Full article

In Japan, a country prone to earthquakes, numerous damaging earthquakes have been recorded throughout history, often accompanied by descriptions of mysterious earthquake lights (EQL), which may involve various mechanisms. In this article, the possible mechanisms for different types of EQL in 11 cases are reviewed among 21 selected earthquakes. These involve preseismic physicochemical variations in the geological structure of the fault in the lithosphere, which contains deep Earth gases such as radon, methane, and others, as a primary factor for EQL generation. Additionally, various seismic, atmospheric, hydrospheric, and ionospheric variations interact with each other, resulting in the visualization of characteristic anomalous phenomena, such as glowing or shining ground, mountains, offshore areas, and skies of various colors. These phenomena appear momentarily but can sometimes last for extended periods. Because EQL often appear just before an earthquake, their study might be significant for earthquake prediction. Additionally, EQL involving methane flames in the ground is an important research topic as it relates to public safety. Was what they witnessed paranormal? Full article

Red oregano (Origanum vulgare L. subsp. vulgare) is native to the mountainous slopes of Albania, thriving at altitudes ranging from 400 to 1300 m above sea level. The aerial components of oregano have been found to address a spectrum of health concerns. However, this subspecies presents intriguing characteristics that require comprehensive exploration and analysis. This study extensively analyzes the ex −situ collection of various genotype populations of red oregano in Albania. Essential oils were extracted by employing the hydrodistillation method. At the same time, their chemical analyses were carried out using gas chromatography coupled with a flame ionization detector (GC−FID) and gas chromatography coupled with a mass−spectrometer detector (GS−MS). We employed two statistical techniques, namely hierarchical cluster analysis (HCA) and principal component analysis (PCA), which allowed for a comprehensive examination of the relationships within the data set and more profound insights into the compositional patterns and interrelationships within the essential oils to be gained. The results revealed significant qualitative distinctions at the intraspecific level, particularly for sesquiterpenes, of populations originating from seven diverse geographic locations. The study’s findings enhance our understanding of the chemical composition of Albania’s red oregano and its chemical variation among different populations, which will potentially contribute to identifying the most suitable clones for breeding programs within red oregano populations. Full article

In the past, the dry mixed conifer forests of California’s Sierra Nevada mountains experienced frequent low to mixed severity fires. However, due to fire suppression and past management, forest structure has changed, and the new fire regimes are characterized by large, high severity fires which kill a majority of the overstory trees. These new disturbance patterns require novel approaches to regenerate the forest as they are not adapted to large, high severity fires. We forecasted growth and fire behavior of young plantations for 100 years into the future using the Forest Vegetation Simulator (FVS) and its Fire and Fuels Extension (FFE). In these simulations, we tested combinations of different fuel treatments (mastication only, mastication with prescribed burning, and no fuels treatments) with different overstory thinning intensities (residual densities of 370 SDI (stand density index), 495 SDI, 618 SDI (TPH), and no overstory thinning) on stand growth and potential fire behavior using analysis of variance. We compared growth and crowning index at the end of the simulation and the simulation age when the flame length, basal area mortality, and fire type reached low severity between fuel treatment, thinning intensity, and original management of stands (plantation with PCT [precommercial thinning], plantation without PCT, and natural regenerating stands). These comparisons are essential to identify which fuel treatment categories reduce fire risk. We found an overall pattern of decreasing crown fire occurrence and fire induced mortality across all simulations due to increasing canopy base height and decreasing canopy bulk density. In particular, stands with mastication and prescribed burning transitioned from crown fire types to surface fires 10 years earlier compared to mastication only or no fuel treatment. Furthermore, pre-commercially thinned stands transitioned from crown fire states to surface fires 10 years earlier in the simulations compared to un-thinned and naturally regenerating stands. Stands with mastication and burning went below 25% reference threshold of basal area mortality 11 and 17 years earlier before the mastication only and no fuel treatment, respectively. In addition, pre-commercially thinned stands went below 25% basal area mortality 9 and 5 years earlier in the simulation compared to un-thinned or naturally regenerated stands, respectively. Mastication with prescribed burning (MB) was the most effective treatment for quickly reducing fire behavior by consuming surface fuels, thus drastically lowing flame length (e.g., surface flame length of MB was 0.6 m compared to mastication only [1.3 m] and no treatment [1.4 m]). Furthermore, intensive thinning reduced risk of active crown fires spreading through the stand. Prioritizing prescribed burning, when possible, and thinning (both pre-commercially and from below) are the most effective ways to quickly improve fire resistance in mixed conifer plantations. Our results highlight the different stressors that post-fire planted forests experience and how different silvicultural treatments interact over time to reduce fire risk, which demonstrates the importance of treating stands early and the effectiveness of surface fuel treatments. Full article

Fibrinolytic enzymes are a kind of proteolytic enzymes that can hydrolyze fibrin and dissolve blood clots. They could be used as a therapeutic agent for treating thrombosis. It is important for the treatment of cardiovascular disease to find and develop new thrombolytic drugs. In order to explore new fibrinolytic enzymes, a strain named 214L-11 with protease and fibrinolytic enzyme activity, which was isolated from the Flaming Mountain of Xinjiang Province, was screened using the skimmed milk plate, the blood powder agarose plate and the fibrin plate methods. Phylogenetic analyses showed that strain 214L-11 shared the highest similarity with Streptomyces fumanus NBRC 13042T (98.88%), which indicated that it represented a potential novel species in the Streptomyces genus. The fibrinolytic enzyme produced by 214L-11 displayed thrombolytic and anticoagulant activities, and it could degrade a single specific protein in the thrombus, thereby destroying the thrombus structure. The fermentation medium optimized through response surface methodology was 15 g/L soluble starch, g/L KNO₃ 0.58, 0.43 g/L peptone, 0.01 g/L FeSO₄·7H₂O, 0.5 g/L MgSO₄·7H₂O, 0.2 g/L Mn²⁺, 0.5 g/L NaCl and 1 L distilled water, pH 8, and the maximum amount of fibrinolytic enzyme produced by strain 214L-11 in the optimal fermentation medium was 1255.3 FU/mL. Overall, the fibrinolytic enzyme-producing strain was screened from the Flaming Mountain of Xinjiang for the first time, which provided a basis for further research and the development of new efficient and safe hemolytic drugs. Full article

This paper reports two experimental fires conducted at field-scale in Corsica, across a particular mountain shrubland. The orientation of the experimental plots was chosen in such a way that the wind was aligned along the main slope direction in order to obtain a high intensity fire. The first objective was to study the high intensity fire behavior by evaluating the propagation conditions related to its speed and intensity, as well as the geometry of the fire front and its impact on different targets. Therefore, an experimental protocol was designed to determine the properties of the fire spread using UAV cameras and its impact using heat flux gauges. Another objective was to study these experiments numerically using a fully physical fire model, namely FireStar3D. Numerical results concerning the fire dynamics, particularly the ROS, were also compared to other predictions of the FireStar2D model. The comparison with experimental measurements showed the robustness of the 3D approach with a maximum difference of 5.2% for the head fire ROS. The fire intensities obtained revealed that these experiments are representative of high intensity fires, which are very difficult to control in the case of real wildfires. Other parameters investigated numerically (flame geometry and heat fluxes) were also in fairly good agreement with the experimental measurements and confirm the capacity of FireStar3D to predict surface fires of high intensity. Full article

In this work, bacterial community composition and actinobacteria resources were explored in extremely hot and hyper-arid areas of Flaming Mountain. This was achieved through a combination of PCR amplicon sequencing of bacterial 16S rRNA gene and cultivation-dependent isolation and characterization efforts. According to the high-throughput sequencing results and soil characteristics, 11 kinds of media were firstly designed to isolate actinobacteria, following the screening and identification of related strains. The results showed that a total of 2994 operational taxonomic units (OTUs) were obtained, involving 22 phyla, 77 orders and 121 genera. Among them, actinobacteria with the relative abundance of 8% ranked third, accounting for 33 genera and 47 species. A total of 132 strains distributed by eight families and 11 genera of actinobacteria were isolated from 11 media, of which six strains were potential new species. Furthermore, the functional characteristics of isolated strains were preliminarily evaluated. The results showed that the obtained strains generally had tolerance against heat, salt and alkali. Fifty-two strains had antibacterial activity, 69 strains could produce hydrolases, and 12.4% of the strains had quorum sensing inhibitory activity. The present study has laid a solid foundation for further understanding the bacterial diversity and exploiting actinobacteria resources in the Flaming Mountain area. Full article

A sub-surface forest fire is a kind of fire that spreads slowly with no flames and lower temperatures, and threatens the ecosystem and human life. The moisture content of humus is considered to be an important factor in determining fire occurrence and sustaining. The humus of the Larix gmelinii in the Daxing’an Mountains was selected for the experiment, the limit moisture content condition of sub-surface forest fires was determined by an experiment simulating smoldering, and the prediction model of the probability of sub-surface forest fire occurrence was established. The results will be of great significance for the prevention, monitoring, and fighting of sub-surface forest fires in the boreal forest. The results showed that when the moisture content of humus in the upper layer was low, the smoldering process could be self-sustaining at 20%. For deeper layers of a depth of 18 cm, this increased to 30% moisture content of the humus and was the critical depth for sub-surface fires. The moisture content of 40% was a limit to burning where smoldering can only last for a short duration and is then extinguished. When the moisture content of the humus was 20%, the smoldering temperature was higher and the rate of spread was faster, with smoldering being maintained for longer periods at 30% moisture content. The regression prediction model of the highest temperature and vertical rate of spread in a column of humus was correlated to moisture content and depth, and the model significance was good at p < 0.01. Based on moisture content and depth, the occurrence probability prediction model of sub-surface fires has a good correlation (R² = 0.93) and high prediction accuracy (AUC = 0.995). The effect of moisture content (Or = 4.008) on the occurrence probability of sub-surface fires is higher than that of depth (Or = 2.948). The results point out that it is necessary to prevent and monitor the occurrence of sub-surface fires when the humus moisture content is less than 40%. In order to reduce the risk of sub-surface fires, the monitoring time of the fire field should be extended after the fire is extinguished due to the slow-burning process of the sub-surface fire. Increasing the moisture content of the humus is an important method to reduce the probability and restrain the spread of sub-surface fires. Full article

Fire is one of the most serious disasters in the wild environment such as mountains and jungles, which not only causes huge property damage, but also may lead to the destruction of natural ecosystems and a series of other environmental problems. Considering the superiority and rapid development of computer vision, we present a novel intelligent wildfire detection method through video cameras for preventing wildfire hazards from becoming out of control. The model is improved based on YOLOV5S architectures. At first, we realize its lightweight design by incorporating the MobilenetV3 structure. Moreover, the improvement of detection accuracy is achieved by further improving its backbone, neck, and head layers. The experiments on a dataset containing a large number of wild flame and wild smoke images have demonstrated that the novel model is suitable for wildfire detection with excellent detection accuracy while meeting the requirements of real-time detection. Its wild deployment will help detect fire at the very early stage, effectively prevent the spread of wildfires, and therefore significantly contribute to loss prevention. Full article

The large amounts of emissions released by forest fires have a significant impact on the atmospheric environment, ecosystems, and human health. Revealing the main components of emissions released by forest fuel under different combustion states is of great importance to evaluate the impact of forest fires on the ecological environment. Here, a self-designed biomass combustion system was used to simulate the combustion of different parts (i.e., branch, trunk, and bark) of five tree species and branches, and three layers of surface dead fuel (i.e., litter layer, semi-humus layer, and humus layer) of three shrub species, in the Daxing’an Mountains, Inner Mongolia. The emission characteristics of the main gas pollutants (i.e., CO, CO₂, HC, and NO_x) and PM₂.₅ released under the two combustion states of smoldering and flaming, along with the correlation ratio among emission factors, were measured. The results show that the average amounts of emissions released by different trees and the three layers of surface dead fuel from a smoldering state are higher than those from the flaming state, while shrub combustion shows the opposite. The emissions released by trees, shrubs, and surface dead fuel from the flaming state are ordered from high to low as follows: CO₂ > CO > HC > NO_x > PM_2.5; and from the smoldering state as CO₂ > CO > HC > PM_2.5 > NO_x, indicating that the primary emissions under both conditions are mainly due to CO₂, CO, and HC, while the emissions of NO_x and PM_2.5 are dependent on the combustion state—flaming promotes the emission of NO_x, while smoldering promotes the emission of PM_2.5. The average emissions of PM_2.5 from the branches, bark, and trunks of Quercus mongolica are significantly higher than those of the other four tree species in the smoldering state, and the emissions of PM_2.5 from the five tree species are ordered as follows: bark > branch > trunk. This study will help to further understand the impact of forest fires on the atmospheric environment and ecosystems in Northern China. Full article

The envisaged promotion of local products contributes to environmental protection and is a valid tool for the promotion of socioeconomic development, enhancement of territories, and biodiversity preservation and sustainability. Provolone del Monaco is a semi hard pasta filata cheese granted PDO (Protected Designation of Origin) designation by the European Union. Provolone del Monaco is obtained from raw cow’s milk, produced in the specific areas of the Lattari Mountains and Sorrento Peninsula (Naples, Italy), and ripened for at least six months. To the best of our knowledge, no studies concerning the complete chemical characterization of Provolone del Monaco cheese are available. In the present study; the chemical characterization (moisture; pH; titratable acidity; nitrogen; and fat content), fatty acid composition determined by using gas-chromatography-flame-ionization-detector (GC-FID); volatile organic compounds by solid-phase microextraction followed by gas chromatography-mass spectrometry (SPME-GC/MS), and maturation indices were evaluated during ripening. Two different average typical cheese sizes (3 kg and 5 kg) and two different internal portions were studied. After 6 months of ripening, the most important changes recorded were the loss of water, the increase in acidity, the nitrogen (as ammonia) release, and the production of volatile organic compounds. The cheese size did not affect the chemical composition of Provolone del Monaco. Full article