Fire Threat Research Articles

Comparison between artificial restoration and natural recovery in vegetation regrowth following high-frequency fire disturbances in the Hengduan Mountains, Southwest China

The Hengduan Mountains in Southwest China are currently facing a recurring and escalating threat of forest fires, posing a significant challenge to vegetation restoration efforts given the ecological value of this region. However, the effects of artificial restoration compared to natural regeneration on vegetation recovery dynamics have been less explored. This study focused on two sites in the Hengduan Mountains, primarily composed of conifer forests. One site employed a mix of artificial restoration measures, including tree planting, aerial grass seeding, and fertilizer application. The other site, which is relatively drier and colder, relied on natural regeneration. Four fire events in these two sites were compared to examine the effects of artificial restoration on vegetation recovery using remotely sensed data from Landsat and MODIS. Fire severity was classified using the differenced Normalized Burn Ratio (dNBR) and validated with field samples. Vegetation greenness loss and recovery trajectory were quantified using the near-infrared reflectance of vegetation (NIRv). The effects of artificial restoration were further analyzed after employing unburnt controls to minimize the impact of climate fluctuations. Results showed that fire severity mapping achieved an overall accuracy of 82%. The average NIRv loss across the four fires was 30%, 49%, and 69% in areas of low, moderate, and high severity, respectively. In low severity areas, natural and artificial recovery rates were similar, at 21% and 26% respectively, three years post-fire. In moderate severity areas, artificial restoration achieved a 46% recovery rate compared to 31% for natural recovery. In high severity areas, artificial restoration resulted in a 63% recovery rate versus 45% for natural recovery. Although the differences in recovery patterns may also be attributed to inherent variations in the vegetation composition, physical environment, and their interactions, this study suggests that high severity areas benefit significantly from artificial intervention for rapid recovery. Future studies should include more controlled experiments at the plot scale to further elucidate the processes of vegetation response to different artificial restoration measures.

Potential threats and habitat of the night parrot on the Ngururrpa Indigenous Protected Area

Context The Endangered night parrot (Pezoporus occidentalis) is one of the rarest birds in Australia, with fewer than 20 known to occur in Queensland and, prior to 2020, only occasional detections from a handful of sites in Western Australia (WA). Here, we provide an introduction to night parrots on the Ngururrpa Indigenous Protected Area (IPA) in WA from the perspectives of both Indigenous rangers and scientists working together to understand their ecology. Aims We aimed to identify night parrot sites on the Ngururrpa IPA, compare habitat and likely threats with those in Queensland and identify appropriate management practices. Methods Between 2020 and 2023, we used songmeters (a type of acoustic recorder) to survey for the presence of night parrots at 31 sites (>2 km apart). At sites where parrots were detected, we used camera-traps to survey predators and collected predator scats for dietary analysis. Forty years of Landsat images were examined to assess the threat of fire to roosting habitat. Key results Night parrots were detected at 17 of the 31 sites surveyed on the Ngururrpa IPA. Positive detections were within an area that spanned 160 km from north to south and 90 km from east to west. Ten roosting areas were identified, and these occurred in habitat supporting the same species of spinifex (lanu lanu or bull spinifex, Triodia longiceps) used for roosting in Queensland. However, the surrounding landscapes differ in their vegetation types and inherent flammability, indicating that fire is likely to be a more significant threat to night parrots in the Great Sandy Desert than in Queensland. Dingoes (Canis dingo) were the predator species detected most frequently in night parrot roosting habitat and the feral cat was found to be a staple prey for dingoes at night parrot sites. Conclusions Our surveys indicated that there could be at least 50 night parrots on the Ngururrpa IPA, which is the largest known population in the world. Fire is a key threat to roosting habitat, occurring in the surrounding sandplain country every 6–10 years. Dingoes are common in night parrot habitat and regularly eat feral cats, which are only occasionally detected in roosting habitat. Implications We recommend management that focuses on strategic burning to reduce fuel loads in the surrounding landscape, and limiting predator control to methods that do not harm dingoes.

LD-YOLO: A Lightweight Dynamic Forest Fire and Smoke Detection Model with Dysample and Spatial Context Awareness Module

The threat of forest fires to human life and property causes significant damage to human society. Early signs, such as small fires and smoke, are often difficult to detect. As a consequence, early detection of smoke and fires is crucial. Traditional forest fire detection models have shortcomings, including low detection accuracy and efficiency. The YOLOv8 model exhibits robust capabilities in detecting forest fires and smoke. However, it struggles to balance accuracy, model complexity, and detection speed. This paper proposes LD-YOLO, a lightweight dynamic model based on the YOLOv8, to detect forest fires and smoke. Firstly, GhostConv is introduced to generate more smoke feature maps in forest fires through low-cost linear transformations, while maintaining high accuracy and reducing model parameters. Secondly, we propose C2f-Ghost-DynamicConv as an effective tool for increasing feature extraction and representing smoke from forest fires. This method aims to optimize the use of computing resources. Thirdly, we introduce DySample to address the loss of fine-grained detail in initial forest fire images. A point-based sampling method is utilized to enhance the resolution of small-target fire images without imposing an additional computational burden. Fourthly, the Spatial Context Awareness Module (SCAM) is introduced to address insufficient feature representation and background interference. Also, a lightweight self-attention detection head (SADH) is designed to capture global forest fire and smoke features. Lastly, Shape-IoU, which emphasizes the importance of boundaries’ shape and scale, is used to improve smoke detection in forest fires. The experimental results show that LD-YOLO realizes an mAP0.5 of 86.3% on a custom forest fire dataset, which is 4.2% better than the original model, with 36.79% fewer parameters, 48.24% lower FLOPs, and 15.99% higher FPS. Therefore, LD-YOLO indicates forest fires and smoke with high accuracy, fast detection speed, and a low model complexity. This is crucial to the timely detection of forest fires.

IoT-enabled fire detection for sustainable agriculture: A real-time system using flask and embedded technologies

In modern agriculture, the threat of fire poses significant economic and environmental risks. Additionally, traditional fire detection methods are inadequate and poorly integrated with advanced technologies. It is crucial to develop a more efficient and reliable fire detection system. Also, the lack of real-time and accurate monitoring in current systems compromises the resilience and sustainability of farming operations. This article details developing and implementing a real-time fire detection system tailored for smart agriculture. It integrates cutting-edge technologies, including the Internet of Things (IoT), embedded systems, and a Flask-based web application, fortified by cybersecurity measures such as login authentication and secure HTTP protocols. The system's primary aim is to monitor environmental conditions continuously in agricultural fields to detect signs of smoke or flame swiftly, facilitating preventive actions to safeguard crops and infrastructure. The architecture employs sensors distributed across fields to monitor conditions, a Raspberry Pi 3 B+ as the central processing unit for data acquisition and transmission, and a web interface developed using Flask, HTML, and CSS for secure and real-time visualization of detection data. Critical components like the MCP3208 analog-to-digital converter ensure the system's reliability and accuracy. Experimental results confirm the system's efficacy in early fire detection and real-time data visualization via the web browser. Enhanced security features, such as login authentication, protect sensitive information, while regular updates maintain data relevance. This study advances fire prevention and farm preservation efforts, offering a high-performance technological solution for proactive monitoring and quick response to fire risks, thereby supporting food security and sustainable agricultural practices.

Evaluation of Fire Protection System in Library Building Universitas Negeri Padang

The fire of a building will have a major impact on the building owner, both in the form of material, moral and environmental losses. In residential areas, offices and other public facilities often cause casualties. Therefore, a building needs to take into account the risk of fire so that building users can carry out activities safely and comfortably. One of the causes of fires is the fire suppression system that has not received full attention, where there is often an inadequate building fire protection system. The UNP Library Building is one of the public facilities buildings that are always crowded with students. It is necessary to evaluate the availability of the fire protection system to ensure the safety and comfort of its users. This research is in the form of an evaluation of the availability and completeness of the available fire protection systems and their remedies against the threat of fire. The data was taken through direct observation and question and answer and the distribution of questionnaires with the library. From the results of the analysis of the fire protection system inspection of the UNP Library building, it is known that on the 1st floor the lowest rediness value is 18.9%, for the 2nd and 3rd floors is 44.1%, the 4th and 5th floors are 45.9% and 45.6 % fulfilled the requirements based on the Minister of Public Works Regulation No. 26/PRT/M/2008.

Suppression effects of different extinguishing agents on vent gases fires from lithium-ion batteries after thermal runaway: A comprehensive experimental and numerical study

During the thermal runaway process of lithium-ion batteries, the release of vaporized electrolyte and combustible gases can lead to the formation of a jet flame, posing a significant fire or explosion risk. In order to deal with the threat of lithium-ion battery vent gas fires to the safety of energy storage power stations, it's crucial to identify effective fire extinguishing agents for lithium-ion battery systems. This study employs a combination of experimental and numerical simulation methods to assess the suppression capabilities of CO2, N2, and HFC-227ea on vent gas/air premixed flames originating from lithium-ion batteries with various cathode materials. Laminar flame speed of vent gas/air/extinguishing agent premixed flames at specific equivalence ratios were measured using a Bunsen burner device under ambient temperature and atmospheric pressure conditions. Additionally, numerical calculations of laminar flame speed and adiabatic flame temperature were conducted using CHEMKIN-Pro, accompanied by an analysis of the chemical inhibition mechanism of HFC-227ea. The findings reveal that although HFC-227ea may slightly elevate the adiabatic flame temperature at lower equivalence ratios, its overall fire extinguishing efficacy surpasses that of CO2 and N2. These results offer valuable insights for selecting appropriate fire extinguishing agents for energy storage power stations, thereby enhancing the safety standards of energy storage systems.

An Experimental Study on the Influence of Different Cooling Methods on the Mechanical Properties of PVA Fiber-Reinforced High-Strength Concrete after High-Temperature Action.

High-strength concrete (HSC) has a high compressive strength, high density, excellent durability, and seepage resistance, but its deformation ability is weak. Adding fibers can improve the physical and mechanical properties of HSC. Additionally, the HSC structure may face the threat of fire. In the process of fire extinguishing, the damage mechanism of high-temperature-resistant concrete is complicated due to the different contact conditions with water at different locations. Hence, it is essential to conduct pertinent research on the behavior of fiber-reinforced HSC with different cooling methods after high-temperature action. In this paper, polyvinyl alcohol fiber (PVA fiber) was selected to be added into the HSC to carry out high-temperature experimental research, so as to explore the apparent changes, failure pattern, and mass loss rate of the fiber-reinforced HSC using different cooling methods and analyze the influence of its residual compressive strength and flexural strength. The test results suggest that, with the increase in heating temperature, the color of the specimen's surface transitions from dark blue-gray to white, and the quantity of surface cracks on the specimen gradually rises. The mechanical strength gradually decreases as the heating temperature increases. At a consistent heating temperature, the mechanical strength initially rises, and then falls with an increase in fiber content. The maximum compressive strength and flexural strength were achieved at PVA fiber contents of 0.2% and 0.3%, respectively. For different temperatures and fiber contents, the mechanical strength after natural cooling is generally higher than that after immersion cooling. In addition, X-ray polycrystalline diffractometry (XRD) and scanning electron microscopy (SEM) tests were conducted to analyze the compositional alterations and microstructure of the fiber-reinforced HSC following high-temperature exposure, accompanied by an explanation of the factors influencing the alterations in the physical and mechanical properties. Therefore, the findings of this study can serve as a valuable reference for the utilization of HSC in engineering structures and contribute to the advancement of HSC technology.

Safety Awareness in Governmental and Private Hospitals in Saudi Arabia

Objectives: Healthcare workers (HCWs) are exposed to several occupational health risks that affect their safety and require enhancement of their knowledge and awareness towards the safety practices. In this study, we aimed to evaluate the safety awareness among HCWs in governmental and private hospitals in Saudi Arabia. Methods: A pre-designed safety questionnaire was distributed among HCWs in selected hospitals through emails or WhatsApp groups including the Saudi and non-Saudi staff who have been working for more than a year. Results: Only 30% of the participants showed awareness of the noise hazard, 43% were aware of the radiation hazard, whereas 53.7% were aware of the lighting hazard. The awareness of fire threats was comparatively greater at 68.5%. Conclusion: Our results highlight the need for focused education and training programs to guarantee a safer working environment in healthcare units, particularly large hospitals and evaluate the safety awareness levels among HCWs regularly to monitor progress and prepare responsive training programs.

Carbon density and sequestration in the temperate forests of northern Patagonia, Argentina

IntroductionForests are a crucial part of the global carbon cycle and their proper management is of high relevance for mitigating climate change. There is an urgent need to compile for each region reference data on the carbon (C) stock density and C sequestration rate of its principal forest types to support evidence-based conservation and management decisions in terms of climate change mitigation and adaptation. In the Andean Mountains of northern Patagonia, extensive areas of temperate forest have developed after massive anthropogenic fires since the beginning of the last century.MethodsWe used a plot design along belt transects to determine reference values of carbon storage and annual C sequestration in total live (above- and belowground biomass) and deadwood mass, as well as in the soil organic layer and mineral soil (to 20 cm depth) in different forest types dominated by Nothofagus spp. and Austrocedrus chilensis.ResultsAverage total carbon stock densities and C sequestration rates range from a minimum of 187 Mg.ha−1 and 0.7 Mg.ha−1.year−1 in pure and mixed N. antarctica shrublands through pure and mixed A. chilensis forests taller than 7 m and pure N. pumilio forests to a maximum in pure N. dombeyi forests with 339 Mg.ha−1 and 2.2 Mg.ha−1.year−1, respectively. Deadwood C represents between 20 and 33% of total wood mass C and is related to the amount of live biomass, especially for the coarse woody debris component. The topsoil contains between 33 and 57% of the total estimated ecosystem carbon in the tall forests and more than 65% in the shrublands, equaling C stocks of around 100–130 Mg.ha−1 in the different forest types.ConclusionWe conclude that the northern Patagonian temperate forests actually store fairly high carbon stocks, which must be interpreted in relation to their natural post-fire development and relatively low management intensity. However, the current high stand densities of these forests may well affect their future carbon storage capacity in a warming climate, and they represent a growing threat of high-intensity fires with the risk of a further extension of burned areas in the future.

Urgency of Social Capital to Improve the Resilience of Independent Oil Palm Farmers in Managing Oil Palm Plantations in Peat Areas: Lessons from Indonesia

Objective: This research focuses on studying the social capital of oil palm farmers in Sidomulyo Village, Wanaraya District, Barito Kuala District, South Kalimantan Province. Theoretical Framework: The study aims to achieve two main objectives: firstly, to identify the social capital possessed by independent oil palm farmers; secondly, to describe how they maintain this social capital. Method: Qualitative research methods were employed to gain a profound understanding of the social capital that supports the success of independent smallholders in managing oil palm plantations. The study was conducted in Sido Mulyo village, Wanaraya district, Barito Kuala Regency, South Kalimantan Province. Informants, serving as sources of information, were selected using purposive sampling techniques. Data collection involved observation, in-depth interviews with selected informants, and daily records, which played a crucial role in this research. The obtained data will be subjected to phenomenological analysis. The study revealed two key findings: first, various forms of social capital, and second, how this social capital is utilized. Results and Discussion: The identified forms of social capital include: (1) the social networks established by farmers with middlemen to sell palm oil to processing companies, (2) their membership in peasant groups, and (3) the work ethic exhibited by farmers as transmigrants. The utilization of social capital for their progress as farmers involves: (1) maintaining relationships in social networks to secure favorable palm oil prices and access to financial capital, (2) leveraging farmer groups to access fertilizer subsidies and protect against the threat of land fires, and (3) employing social norms to foster mutual assistance in preserving road access to oil palm plantations. Research Implications: This research contributes to understanding the various capitals owned by smallholders in oil palm plantation exploitation and the use of social capital for their success in plantation management palm oil. This model can be a reference for communities who want to get similar success in the development of oil palm plantations and can be done also in other locations that have the same land structure. Originality/Value: Social capital plays a crucial role in the success of independent farmers managing oil palm plantations. Several conclusions have been drawn regarding social capital in the management of oil palm plantations by independent smallholders. Firstly, the forms of social capital owned by independent oil palm plantation farmers include: (1) social networks established by farmers with middlemen for selling oil palm to processing companies, (2) membership in farmer groups, (3) the work ethic possessed by farmers as transmigrants, and (4) the social norms embraced by transmigrant farmers. Secondly, the utilization of social capital for their progress as farmers is carried out through: (1) maintaining relationships in social networks to secure palm oil prices and access capital, (2) utilizing farmer groups to access fertilizer subsidies and safeguard against the threat of land fires, and (3) applying social norms to foster mutual assistance in maintaining oil palm plantation infrastructure and addressing and preventing palm oil plantation fires.

Spatiotemporal dynamics of forest fires in the context of climate change: a review.

Forest fires are sudden, destructive, hazardous, and challenging to manage and rescue, earning them a place on UNESCO's list of the world's eight major natural disasters. Currently, amid global warming, all countries worldwide have entered a period of high forest fire incidence. Due to global warming, the frequency of forest fires has accelerated, the likelihood of large fires has increased, and the spatial and temporal dynamics of forest fires have shown different trends. Therefore, the impact of climate change on the spatiotemporal dynamics of forest fires has become a hot issue in the field of forest fire research in recent years. Therefore, it is of great significance and necessity to conduct a review of the research in this area. This review delves into the interactions and impacts between climate change and the spatiotemporal dynamics of forest fires. To address this issue, scholars have mainly adopted the following research methods: first, statistical analysis methods, second, the establishment of spatiotemporal prediction models for meteorology and forest fires, and third, the coupling of climate models with forest fire risk forecasting models. The statistical analysis method relies on the analysis of historical meteorological and fire-related data to study the effects of climate change and meteorological factors on fire occurrence. Meanwhile, forest fire prediction models utilize technical tools such as remote sensing. These models synthesize historical meteorological and fire-related data, incorporating key meteorological factors such as temperature, rainfall, relative humidity, and wind. The models revealed the spatial and temporal distribution patterns of fires, identified key drivers, and explored the interactions between climate change and forest fire dynamics, culminating in the construction of predictive models. With the deepening of the study, the coupling of climate models and fire risk ranking systems became a trend in the prediction of forest fire risk trends. Moreover, as the climate warms, the increased frequency of extreme weather events like heatwaves, droughts, snow and ice storms, and El Niño-Southern Oscillation (ENSO) has accelerated forest fire occurrences and raised the risk of major fires. This review offers valuable technical insights by comprehensively analyzing the spatial and temporal characteristics of forest fires, elucidating key meteorological drivers, and exploring potential mechanisms. These insights serve as a scientific foundation for preventive measures and effective forest fire management. In the face of a changing climate, this synthesis contributes to the development of informed strategies to mitigate the escalating threat of forest fires.

Assessing Potential Distributions of Bird Endemic Species: Case Studies of Macrocephalon maleo and Rhyticeros cassidix and Their Threats

Maleo and knobbed hornbill are bird species that are endemic on the island of Sulawesi, which is highly threatened by forest fires. Fires tend to destroy any affected species; however, it is not possible to survey the entire range of the original distribution of the two endemic bird species that are affected by forest fires due to practical constraints. Species distribution modeling using maximum entropy is considered to be an alternative to understanding the potential distribution area of species against the threat of forest fires. The prediction model from MaxEnt all have AUC values of greater than 0.70, which means that the model is good enough to classify the records of the presence of M. maleo and R. cassidix along with the past forest fires. The environmental variables that affect the distribution of M. maleo are its distance from hot water, rivers, and roads, while the distribution of R. cassidix is strongly influenced by its distance from roads, settlements, and rivers. Forest fire distribution is mostly influenced by soil type, land-use land cover, and rainfall. It is predicted that around 238,690 and 677,070 ha of the potential distribution of M. maleo and R. cassidix, respectively, are potentially disturbed and affected by forest fires. However, this number much greater outside conservation areas. The results of this study can be used by the government of the Republic of Indonesia (especially the Ministry of Environment and Forestry) for determining conservation actions for both species in the future.

High temperature-resistance modification of the magnesium phosphate inorganic adhesive and its bond properties between CFRP sheets and concrete

The carbon fibre reinforced polymer (CFRP)-strengthened concrete structures are faced with the great threat of fire due to the vulnerability of the epoxy organic adhesive to high temperature. The traditional epoxy organic adhesives are thus urgently needed to be replaced by the alternatives with high-temperature resistance. This paper explored the feasibility of using magnesium phosphate inorganic adhesive (MPIA) to serve as the bonding material for the CFRP-strengthened concrete structures. To this end, the high-temperature resistance modification of MPIA was conducted through the addition of glass powder (GP) in this study. The effects of the GP content ranging from 0% to 15% on the temperature development, mechanical property degradation, phase evolution and microstructural characteristics of the MPIA after exposure to different temperatures were investigated. The results showed that the glass powder could effectively fill the pores caused by the decomposition of the hydration products and the cracks caused by the shrinkage of MPIA matrix at elevated temperatures, which improved the microstructure of MPIA significantly and thus alleviated its strength degradation under high temperature. In terms of the mechanical properties, the MPIA with 10% GP (hereinafter referred to as TRMPIA) yielded the best high-temperature resistance. In addition, the interfacial bond property test after high temperature was also conducted on the concrete members strengthened with the CFRP sheets pasted by TRMPIA, and the test results were also compared with the specimens with epoxy served as the bonding material. The results showed that even after exposure to 600°C, the in-plane shear strength of TRMPIA still remained 14.0% of that at room temperature, while the bond strength of epoxy had been completely lost, which highlighted the advantage of high-temperature resistance of the modified MPIA served as the bonding material of CFRP-strengthened concrete structures.

Assessing silvopasture management as a strategy to reduce fuel loads and mitigate wildfire risk

Managing private forests for wildfire resilience is challenging due to conflicting social, economic, and ecological decisions that may result in an increase of surface fuel loads leading to greater fire risk. Due to fire suppression and a changing climate, land managers in fire-prone regions face an increasing threat of high severity fires. Thus, land managers need fuel treatment options that match their forest types and management objectives. One potential option for producers that graze livestock is silvopasture management, where livestock, forages, and overstory vegetation are carefully managed for co-benefits on the same unit of land. This study compared forest composition and structure, fuel types, and vegetative biomass between silvopasture and non-grazed managed forests in Washington, U.S. We show that silvopasture management results in reductions in grass biomass, litter, and duff depth when compared to non-grazed managed forest. These findings point to the integrated nature of silvopasture, where management of overstory composition and structure, understory vegetation, and grazing can reduce fuel loads and potential wildfire risk.

Optimizing the Benefits of Invasive Alien Plants Biomass in South Africa

The current political situation in South Africa is seeking opportunities to promote sustainable development and use of renewable resources for energy, poverty alleviation, economic development, and environmental protection (e.g., mitigation of greenhouse gas emissions). The present study is based on a critical literature review and synthesis of policy advice in South Africa. The study comprehensively examined the knowledge base and gathered relevant empirical findings and perspectives so as to identify the gaps, trends, and patterns in the optimal management and utilization of invasive alien plants (IAPs) biomass, thereby supporting evidence-based practice. Additionally, the literature review was supported by the first-hand experience of invasive alien plants management and its biomass utilization. This research proposes long-term options for optimizing the costs and benefits of invasive alien plants biomass and meeting rising energy demand. Biomass from the country’s approximately 300 “Working for Water (WfW) Projects” might be used for bioenergy, firewood, charcoal, and other value-added forest products, both for internal and international use. The extraction and use of biomass from invasive alien plants for green energy and other valuable products would aid in the elimination of hazardous invasive species and reduce the amount of fuel in the fields, as well as fire and flood threats. Biomass from invasive alien plants clearings can be distributed to rural regions and informal settlements as a supply of firewood with the aim of reducing reliance on nearby forests, conserving the environment and biodiversity, minimizing forest degradation, supporting climate change, and enhancing energy efficiency and wood waste management (e.g., recycling and prevention) for green economic development and industrial transformation. The findings of this study imply that for competitive biomass-to-energy conversion and bio-economic applications for the use of invasive alien plant biomass, cost management, particularly for transportation, and significant regulatory incentives are essential. In addition, effective policy instruments that aid in the promotion of innovative systems and knowledge generation are required so that biomass can be optimally used for bioenergy and other competitive bio-economic applications.

Design of Arduino-based LPG Gas Leak Detection Tool using MQ-6 Sensor

LPG (Liquefied Petroleum Gas) is a natural resource that has increased yearly consumption. LPG gas is used almost every time for human life in the household and industry sectors. LPG gas, besides being cheap, is also easier to use. However, the increasing use of LPG gas also increases the risk of fire or gas collection caused by LPG gas leaks. Therefore, a tool is needed to detect LPG gas leaks. So an LPG gas leak detector was made using the MQ-6 sensor, which can detect LPG gas leaks, and using a blower fan to overcome the collection of gas levels around LPG gas cylinders, using a buzzer as an alarm, using a servo to turn off the electricity so that an explosion does not occur, and use spray foam to spray onto the tube and stove if the blower cannot handle the LPG gas leak. Overall, the design components are controlled by Arduino Uno R3. This testing process takes an average of 9.56 seconds. If it is less than 9.56 seconds, then only one action is enough: the blower fan, active buzzer, and pump 1. If it is more than 9.56 seconds, the second action will be continued: spraying foam and turning off the electricity. On the other hand, there is an opportunity to bring this tool to commercial. Many households need this tool to save their house from fire threats. Finally, this tool can be a development tool for solving an incident from gas and will be a best-selling tool.

Field detection of indoor fire threat situation based on LSTM-Kriging network

Obtaining the fire development information quickly and accurately is an important part of indoor fire emergency evacuation and rescue. However, at present, buildings only use fire sensors to monitor whether a fire is occurring, and there is a lack of means to obtain real-time threat situation information on the development of fires. An LSTM-Kriging neural network model is proposed in this paper, which can quickly generate an indoor fire threat field using the temporal data of fire sensors when an indoor fire occurs. Firstly, the Kriging algorithm was improved by replacing the Euclidean distance used in the variational function with the nearest passable distance to obtain a more accurate representation of the indoor threat distribution trend, and combined it with the Long Short-Term Memory (LSTM) network to construct the LSTM-Kriging network. Secondly, indoor fire scenarios were constructed in PyroSim, and fire parameters were simulated randomly. After data augmentation, the indoor fire threat situation dataset was generated. Finally, the optimized LSTM-Kriging model was trained and compared with Transformer, LSTM, and Recurrent Neural Network (RNN) on the indoor fire hazardous situation dataset. The experimental results show that LSTM-Kriging is the most effective model compared with several models mentioned above and the prediction of threatening situation reaches an accuracy of 97.8 %, with an average computation time of 0.19s on the GPU, which can meet the requirement of real-time fire situation monitoring. The indoor fire threat situation field detection method proposed in this paper achieves intelligent indoor fire detection and improves the building fire safety.

Safety analysis of fire evacuation from Drilling and Production Platforms (DPP)

Offshore platforms are vulnerable to fire accidents and it is essential to conduct safety analysis in case of an evacuation and take measures to improve worker evacuation efficiency and reduce casualties. Based on the proposed Credible and Representative Fire Scenarios (CRFS) methodology, nine fire scenarios were selected and simulated. The safety analysis of fire evacuation was performed based on the coupled injury model and the modified social force model, while the effects of wind direction, wind speed, fire location and pre-evacuation time on the probability of death (POD) were investigated. The results demonstrated that the wind from the stern led to a higher coverage rate of smoke (CRS) on the decks and higher POD values. The wind from the bow, larboard and starboard sides was shown to be more conducive to the dissipation of smoke. As a result, the overall POD values were relatively low. The magnitude of wind speed affects the accumulation behavior of smoke between different decks, and the lower the wind speed, the higher the CRS on the decks and POD of the workers.The pool fire located on the lower deck was more likely to cause injuries than the fire on the working deck. In addition, it was found that the trend between POD and pre-evacuation time shows a non-linear relationship, thus the scenario with the most severe fire threat was used as an example for regression analysis. An approach was proposed to determine the fire-evacuation safety time windows in the event of a fire accident and the time windows in different areas of the nine selected scenarios were predicted. Finally, the time windows obtained from the regression curves and the proposed method were compared.

Forest fires in the Indian Central Himalaya: major drivers, implications, and mitigation measures

ABSTRACT Forest fires pose a significant threat in the Central Himalaya due to both natural and human factors. This study investigates key drivers, consequences, and mitigation measures. Data on 2022 forest fire incidents, affected areas, and economic losses were collected from the State Forest Department, Dehradun, and analyzed using statistical methods. The 2022 forest fire areas were mapped using data from the USGS and NASA FIRMS portals, revealing highly sensitive zones in river valleys and mid-altitudes below 1800 m, covering 13% of the total forest area (approximately 40,000 ha). These regions primarily host monsoon deciduous and flammable pine forests. Recent years have witnessed a notable increase in fire frequency and intensity, attributed to warming river valleys, middle altitudes, and dry climate spells during the fire season. This pioneering study recommends risk reduction strategies, including managing dry pine leaves, forest replacement, constructing fire lines, and providing fire control training to rural communities. Adopting these measures can effectively mitigate the escalating threat of forest fires in the Central Himalaya.

Self‐ignition of forest soil samples demonstrated through hot storage tests

AbstractThe increasing threat of forest fires on a global scale is not only a matter of concern due to the potential harm they may cause to both human and animal life but also due to their significant role in exacerbating climate change. In light of these circumstances, one might inquire as to whether forest soil can self‐ignite and, if so, under what conditions and at what temperatures this phenomenon may occur. This question is being addressed in the German pilot “Fire science of wildfires and safety measures” of the EU project TREEADS, and the first results are presented below. The importance of basic research into the self‐ignition of forest soil cannot be underestimated, as it provides crucial knowledge to prevent forest fires and protect human and animal health. Furthermore, mitigating the occurrence of forest fires can also play a role in reducing greenhouse gas emissions, contributing to global efforts to combat climate change. The procedure of the hot storage test is an effective means of determining whether a material can self‐ignite. During the investigation of six soil samples, it was found that five of them were indeed capable of self‐ignition. In addition to determining whether the material ignites, the modified hot storage test also analyzed the resulting smoke gases and measured their concentration. The research question of whether regional forest soil is capable of self‐ignition can be answered with yes based on these initial tests. Further experiments are needed to determine if self‐ignition causes forest fires.