Fire Risk Assessment Research Articles

Scaled experimental study on the initial oil thickness effect on the combustion characteristic of the typical transformer insulating oil

Compared with mineral oil, plant insulation oil has a higher flash point, excellent natural degradation ability, and higher electrical insulation. It is expected to become the main component of transformer insulation oil, but the fire safety of this oil needs to be further analyzed and improved. In this paper, a cone calorimeter was used to test the combustion of typical plant insulating oil (camellia seed oil, soybean oil) and mineral oil (25# mineral oil) under different radiant heat flows and initial oil thickness. The combustion parameters such as ignition time, heat release rate, and carbon generation rate were measured. The combustion characteristics of 25# mineral oil were greatly affected by radiative heat flow and oil thickness. The peak heat release rate and carbon generation rate of mineral oil under high heat flow (50 kW/m2) were significantly higher than those under low heat flow (25 kW/m2) and increased with the increase of initial oil thickness. Plant insulating oil (camellia seed oil and soybean oil) had similar laws, but the peak value of the heat release rate and carbon generation rate of soybean oil were relatively small. Petrella fire risk assessment method showed that the fire risk ranking in descending order was mineral oil, camellia seed oil, and soybean oil, which provided a reference for the further popularization and application of plant insulation oil transformer.

A temperature-dependent fire risk assessment framework for solar photovoltaic station

Since solar photovoltaic (PV) stations are experiencing rapid growth, their potential fire risk needs to be studied as a priority to avoid catastrophic consequences. This study developed a temperature-dependent fire risk assessment framework and applied it to a typical solar PV station. To overcome the challenges of lacking probabilities and subjective judgment, the overall fire risk of a solar PV station was calculated by combining fault tree analysis, Cloud-Analytic Hierarchy Process and Weighted Average Cloud Aggregation algorithms. Additionally, as an innovative part of the developed framework, an information diffusion technique was introduced to quantify the impacts of air temperature on the probability of those influencing events and the solar PV fire spread risk. It was known that high ambient temperatures and solar radiations, which lead to overheating and installation error of solar PV modules, are the important causes of fire incidents. The results showed that influences of the air temperatures cannot be ignored as certain basic events’ probabilities are affected. The occurrence possibility of installation error decreases with increasing air temperature and then increases with a higher air temperature, whose trend is validated by previous experiments. After synthesizing the impacts, the trend of the fire spread risk considering different air temperatures was quantified, showing the lowest risk at an air temperature of 10 °C. The developed framework of this study presents a new perspective for future dynamic risk assessment of those scenarios under changing environmental and other conditions.

Experimental study on the combustion properties of four common engineered bamboo and wood composites

AbstractEngineered bamboo and wood composites are increasingly utilized in construction due to their eco‐friendly, low‐carbon footprint, and superior mechanical properties. To investigate the effect of heat flux and grain direction on the combustion properties of parallel strand bamboo (PSB), laminated veneer bamboo (LVB), cross‐laminated timber (CLT), and laminated veneer lumber (LVL), a total of 54 specimens in 3 groups were tested through a cone calorimeter. Parameters including the ignition time, heat release rate, mass loss rate, and smoke production rate were investigated. The analytic hierarchy process method was adopted for a multi‐level, qualitative, and quantitative comprehensive fire risk assessment of the corresponding structural materials. The test results reveal that PSB and LVB demonstrated superior performance to the CLT and LVL through the comparison of four combustion characteristics parameters, despite their drawbacks and virtues. The heat flux increases in inverse proportion to the ignition time. As for the heat release rate, the larger peak value is accompanied by an earlier appearance, along with the greater average mass loss rate and the lower smoke rate of engineered bamboo. The peak heat release rate of engineered bamboo composites parallel to the grain is larger than that perpendicular to the grain, whereas other parameters are not significantly influenced by the grain direction. Compared with engineered wood, engineered bamboo composites have the potential to be a safer and more reliable building material in terms of fire risk assessment.Highlights Cone calorimeter was used to analyze the combustion properties of materials. PSB, LVB, CLT, and LVL were studied considering different grain directions. Analytic hierarchy process method was adopted for a fire risk assessment. Engineered bamboo has the potential to be a reliable building material.

Experimental investigation and numerical simulation of transverse heat flux attenuation during fire in utility tunnel

To analyze transverse fire protection, the distribution law and evolution mechanism of transverse heat transfer during fire in utility tunnels is required urgently. In this study, the experiment and numerical simulation were employed to investigate the evolution of transverse heat transfer under the curved ceiling. After validation, the fire dynamics simulation models with unstructured geometry were established to predict the transverse heat flux. Through the experiment and simulation, the fire source and target location under the curved ceiling were considered, and the prediction models of heat flux provided by the flame body before the impingement point and the heat flux provided by the extension flame body and thermal environment were proposed. Based on the proposed models, the shift relationship (competition mechanism) between the components provided by flame body before the impingement point and the extension flame body (including the thermal environment) under the curved ceiling was illustrated. The transverse heat flux attenuation of each component in different fire scenarios with different fire sources and target point locations was compared to reveal the competition mechanism among the components in the heat flux. This work provides a reference for the transverse fire protection design and risk assessment in utility tunnels.

Geoinformatics and Machine Learning for Comprehensive Fire Risk Assessment and Management in Peri-Urban Environments: A Building-Block-Level Approach

Forest fires can result in loss of life, damage to infrastructure, and adverse environmental impacts. This study showcases an integrated approach for conducting high-detail fire risk assessment and supporting strategic planning and management of fire events in peri-urban areas that are susceptible to forest fires. The presented methodology encompasses fire hazard modeling, vulnerability and exposure assessment, and in situ observations. Numerous fire hazard scenarios were tested, simulating the spatiotemporal spread of fire events under different wind characteristics. The vulnerability of the studied areas was assessed by combining population data (density and age) and building characteristics, while the exposure parameter employed land value (EUR/m2) as an indicator for qualitatively estimating potential economic effects in the study area. Field campaigns facilitated the identification and recording of critical areas and points, including high-risk buildings and population gathering areas, which subsequently informed the mitigation and fire management planning suggestions. Moreover, field recordings acted as an iterative process for validating and updating the fire risk maps. This research work utilizes state-of-the-art techniques to achieve an analysis of fire risk at a building-block level. Overall, the study presents an applied and end-to-end methodology for effectively addressing forest fire risk in peri-urban areas.

A Combined Method to Build Bayesian Network for Fire Risk Assessment of Historical Buildings

A Combined Method to Build Bayesian Network for Fire Risk Assessment of Historical Buildings

Development of two-layer zone model BRI2-CRIEPI applicable to fire PRA for nuclear power plants

In implementing practical fire Probabilistic Risk Assessment (PRA) for nuclear power plants, a practical fire model is required for more realistic fire scenarios. The fire simulation zone model BRI2-CRIEPI has been continuously improved to allow analysis considering the characteristics of compartment fires under mechanical ventilation conditions.In this study, the specific characteristics of the fire model under mechanical ventilation conditions to estimate inner pressure and flow rate fluctuation were newly applied, such as the relationship between compartment pressure and flow rate of a ventilating fan, i.e., the fan curve, the vitiation effect of the mass loss rate (MLR) due to the depletion of oxygen owing to fire progress, the representative oxygen concentration corresponding to the elevation of a fire source, and a thermal radiation feedback model from the flame and surrounding environment in case of flame impingement beneath the ceiling.The analytical results with the BRI2-CRIEPI were validated by full-scale compartment fire test results performed by the international Organisation for Economic Co-operation and Development (OECD) Nuclear Energy Agency (NEA) project PRISME3 (Propagation d'un incendie pour des scénarios multi-locaux élémentaires in French). Especially, validation result for HGL temperature, which is very important metric in the fire PRA, shows that there is no obvious bias (the model bias factor of 1.03) and no particular systematic trend (the model relative standard deviation of 0.14) in the model prediction.

A fire risk assessment system and application for process industry using fuzzy Petri net and HAZID method

The safety risk assessment of process industries can determine the degree of safety risk and remind or warn safety management personnel to take corresponding measures according to the probability of accidents. In this paper, hazard identification (HAZID) method is combined with fuzzy Petri net to construct a hybrid safety assessment system. Firstly, the fire risk factors of HAZID are determined according to the fire statistics data. By dividing the whole industrial process into four stages, the complex hazard sources in the factory are investigated item by item, thus the fuzzy Petri net of real-time risk assessment is constructed. Taking an acetic acid enterprise as a case, this paper introduces how to construct such a risk assessment system in detail, and the system can dynamically predict the risk with changes in process conditions. This also demonstrates the feasibility of this method, which can be used as a reference for related research.

Study of the Combustion Characteristics and Flame Retardant Assessment of Windows in Buildings

With the increasing size and density of domestic buildings, the spread of fire from one building to adjacent ones has become a significant concern, leading to greater fire damage. The openings in these buildings have been identified as the main cause of horizontal and vertical fire diffusion, as flames repeatedly enter adjacent compartments. In this study, we focused on buildings with a high fire risk by conducting a fire risk assessment of existing structures. Commercial facilities (such as accommodation facilities) and industrial facilities (including warehouses and factories) were classified as buildings with a relatively high risk. We specifically selected PVC and AL windows, which are commonly used in buildings, to evaluate the risk of fire spread based on flame retardant assessment. However, during a fire, the exposed cross-section and quality of windows differ, making it inappropriate to evaluate their fire risk using the currently regulated flame retardant assessment test. Therefore, there is a need to establish methods and standards for flame retardant assessment tests that are specifically designed for windows.

A novel IoT-based framework with Prognostics and Health Management and short term fire risk assessment in smart firefighting system

In recent years, “smart firefighting” becomes a popular research topic which aims at improving the efficiency of fire protection and safety. However, in existing smart firefighting systems: (1) state and analog firefighting IoT data is not fully utilized; (2) fire risk assessment requires a long time to update; (3) few existing works can recognize faults and forecast potential risks with both temporal and spatial information from multiple IoT sensors. Therefore, a novel framework is proposed to solve the above problems as follows: (1) Short-term Fire Risk Assessment (SFRA) is proposed by considering the working status, maintenance and rectification performance of firefighting facilities based on IoT state data; (2) Prognostics and Health Management (PHM) algorithms are applied in the fire safety field for the first time to detect faults and forecast potential risks with temporal and spatial information with IoT analog data from single or multiple sensors. A case study is carried out in a building in Shanghai and a smart firefighting system is deployed with the edge computing gateway. The experimental results of the SFRA and PHM are presented and analyzed in details. The performance evaluation and comparison results are presented with multiple metrics. The reliability of the proposed framework is discussed. The case study concluded that the proposed framework extends the utilization of IoT data, improves the efficiency of fire risk assessment and enhances the accuracy of faults detection and potential risk forecast. Moreover, the deployed firefighting system improves the data privacy and computational efficiency.

A New Perspective on Hydrogen Chloride Scavenging at High Temperatures for Reducing the Smoke Acidity of PVC Cables in Fires V: Comparison between EN 60754-1 and EN 60754-2

Regulation (EU) No 305/2011 lays down harmonized conditions for marketing construction products in the European Union. One of its consequences has been the introduction of the product standard EN 50575 and standard EN 130501-6, concerning power, control, and communication cables permanently installed in buildings to prevent the risk of a fire and its consequences. EN 13501-6 provides the reaction to fire classifications for cables, the test methods to be performed, the requirements to meet a specific reaction to fire, and additional classifications for smoke production, flaming droplets, and acidity. It requires EN 60754-2 as the technical standard to assess acidity, and it defines three classes: a1, a2, and a3 (the less performant). Due to the release of hydrogen chloride during the combustion, acidity is the weak point of PVC cables, which are not yet capable of achieving the a1 or a2 classes required for specific locations according to fire risk assessments. EN 13501-6 does not include EN 60754-1, used in harmonized standards outside the scope of Regulation (EU) No 305/2011. EN 60754-1 and EN 60754-2 are common standards for determining halogen gas content, and acidity/conductivity, respectively. While they involve the same type of test apparatus, they differ in heating regimes, final temperatures, and detection methods. In particular, EN 60754-2 requires testing at temperatures between 935–965 °C in the tube furnace, where the sample burns, the smoke is collected in bubblers, and pH and conductivity are measured as an indirect assessment of acidity. On the other hand, the temperature regime of EN 60754-1 is a gradual heating run, followed by isothermal heating at 800 °C. The paper shows that when potent acid scavengers are used in PVC compounds, performing EN 60754-2 with the thermal profile of EN 60754-1 or at 500 °C in isothermal conditions, the evolution of hydrogen chloride changes significantly up to 10 times less than the test performed in isothermal at 950 °C. The reason lies behind the kinetic of hydrogen chloride release during the combustion of PVC compounds: the higher the temperature or faster the heat release, the quicker hydrogen chloride evolution and the lower the probability for the acid scavenger to trap it. Thus, these findings emphasize the “fragility” of EN 60754-2 as a tool for assessing risks associated with the release of hydrogen chloride during fires.

Modified analytic hierarchy process for risk assessment of fire and explosion accidents of external floating roof tanks

AbstractTo ensure the safe operation of external floating roof (EFR) tanks, it is important to conduct risk assessments for fire and explosion accidents. In this study, we develop a modified analytic hierarchy process to overcome the subjectivity in traditional analytic hierarchy analysis, improved analytic hierarchy process, and fuzzy fault tree analysis. We propose a parameter with a correction factor: the role of the parameter in the model can be gained from further modifying the structural importance of each basic event so as to overcome the subjectivity in traditional analytic hierarchy analysis, improved analytic hierarchy process, and fuzzy fault tree analysis. The judgment matrix for the analytic hierarchy process is constructed based on the modified structural importance of each basic event in a fault tree. The weight factor for each index to the top goal, combined with the fuzzy comprehensive assessment method, is adopted to conduct risk assessments for the fire and explosion accidents of EFR tanks.

Attention-Based Wildland Fire Spread Modeling Using Fire-Tracking Satellite Observations

Modeling the spread of wildland fires is essential for assessing and managing fire risks. However, this task remains challenging due to the partially stochastic nature of fire behavior and the limited availability of observational data with high spatial and temporal resolutions. Herein, we propose an attention-based deep learning modeling approach that can be used to learn the complex behaviors of wildfires across different fire-prone regions. We integrate optimized spatial and channel attention modules with a convolutional neural network (CNN) modeling architecture and train the attention-based fire spread models using a recently derived fire-tracking satellite observational dataset in conjunction with corresponding fuel, terrain, and weather conditions. The evaluation results and their comparison with benchmark models, such as a deeper and more complex autoencoder model and the semi-empirical FARSITE fire behavior model, demonstrate the effectiveness of the attention-based models. These new data-driven fire spread models exhibit promising modeling performances in both the next-step prediction (i.e., predicting fire progression from one timestep earlier) and recursive prediction (i.e., recursively predicting final fire perimeters from initial ignition points) of observed large wildfires in California, and they provide a foundation for further practical applications including short-term active fire spread prediction and long-term fire risk assessment.

Are high-severity burns in Alpine beech forests related to eruptive fire behavior?

Abstract In the complex Alpine topography, canyon-like terrain morphology combined with steep slopes may cause sudden changes in fire behavior, for instance, turning fast-spreading surface fires into eruptive fires. This phenomenon was observed during the vegetation dormancy in mountain beech (Fagus sylvatica L.) stands, a forest type usually spared from wildfires. The aim of this study is to understand the impact of eruptive fire behavior on the post-fire trajectories of beech trees. To this end, over the course of 3 years, we monitored the post-fire dynamics of 100 beech trees subjected to different fire intensities in February 2020, including a small-scale eruptive fire behavior associated with a steep slope (~41.4° on average) and canyon-like terrain features. Dendrometric and sylvicultural parameters and fire-related damages such as the presence of bark blackening, scars, foliage loss, crashes of branches or whole trees, and parasitic attacks were assessed. The observed medium to high fire severity was highly dependent on the position of the tree within the eruptive fire sector, whereas the relationship with dendrometric and sylvicultural tree characteristics, such as the crown position or the stem diameter, was less clear. Due to the lethal temperatures generated by the heat convection within the eruptive fire sector, the exposed bud and cambium tissues of the beech trees partially or totally failed to develop in the first post-fire season. Beech crown and stem tissue killed by exposure to convective heat fluxes rapidly dries out, loses its elasticity, and becomes brittle. Starting from the second post-fire season, this greatly increases the risk of the crashing of these crown parts and/or entire trees. A detailed understanding of the factors leading to an eruptive fire behavior would highly benefit the fire risk assessment and the detailed planning of the firefighting tactics in mountain areas, eventually increasing the safety of firefighters and preventing post-fire natural hazards, such as rockfall, erosion, surface runoff, and debris flow.

Enhancing predictive ability of optimized group method of data handling (GMDH) method for wildfire susceptibility mapping

Wildfire is one of the most significant environmental challenges and causing damage to ecosystems, habitats, infrastructure and especially human lives. Thus, spatial assessment of fire risk is vital to reduce the impacts of wildfires. This paper introduces an effective wildfire susceptibility mapping framework by applying a group method of data handling (GMDH) with three metaheuristic methods of biogeography-based optimization (BBO), imperialist competitive algorithm (ICA), and teacher-learning-based optimization (TLBO). A total of 13 wildfire influencing factors, including elevation, slope, aspect, plan curvature, profile curvature, topographic wetness index, valley depth, wind speed, normalized difference vegetation index, rainfall, temperature, distance to roads, and distance to rivers were used in the proposed models for wildfire susceptibility mapping of Oahu Island in Hawaii, USA. The predictive performance of models was evaluated by the root mean square error (RMSE), mean squared error (MSE), and area under the receiver operating characteristic curve (AUC). The findings demonstrated that the three hybrid models outperformed the standalone GMHD in the study area. For example, in the validation phase, the models of GMDH-TLBO, GMDH-ICA, GMDH-BBO, and GMDH produced AUC values of 0.81, 0.80, 0.79, and 0.75, respectively. The MSE values for the GMDH, GMDH-ICA, GMDH-BBO, and GMDH-TLBO models were 0.048, 0.026, 0.030, and 0.020 and the RMSE values were 0.2119, 0.162, 0.17, and 0.142, respectively. Thus, the GMDH-TLBO and GMDH were the most and least effective algorithms because they had the highest and lowest predictive accuracy. Moreover, distance to road is the most effective factor for detecting wildfire-prone areas. It is followed by temperature, slope, and elevation. By localizing the input data, the methodology can be applied to other regions for wildfire susceptibility mapping, facilitating wildfire mitigation and prevention.

Spatial layout siting method for fire stations based on comprehensive forest fire risk distribution

In order to shorten the response time of forest fire (FF) rescue and improve the efficiency of forest fire prevention and control, this paper proposes a fire station spatial layout location method based on the spatial distribution of FF comprehensive risk. A comprehensive forest fire risk assessment model has been developed by three perspectives, namely the risk factors of forest fires, exposure degree of the disaster-bearing body, and vulnerability of the disaster-bearing body. The location-assignment model was introduced to scientifically plan the spatial layout of FF stations from different perspectives. Zhuhai in Guangdong Province, China, a typical “city surrounded by mountains,” was chosen as the research site for case analysis. The results show that the high-risk areas of Zhuhai are mainly concentrated in the forests of Xiangzhou District and Gaoxin District; the medium-risk areas mainly lie in the forests in the north of Gaoxin District, the forests of Hengqin Zone and some forests of Doumen District. Through a combination of the minimized facility point model and the maximized coverage model, it is calculated that 9 FF stations are the optimal choice, which can meet Zhuhai's demand for FF prevention and control with an acceptable construction cost and good coverage.

Factors Contributing to Increased Building Fire Incidents in Sri Lanka

Aim: Despite the existence of established fire codes, the frequency of building fires in Sri Lanka has been on the rise in recent years. The primary objective of building codes is to ensure minimum acceptable fire safety standards in buildings, but deviations from the code can increase fire risk factors and exacerbate the severity of fires. This study aims to identify and rank such risk factors in three stages, beginning with design and concluding with maintenance. Introduction: Metodologia tego badania obejmuje podejście jakościowe, które uwzględnia przegląd literatury, ankietę opartą na kwestionariuszu oraz częściowo ustrukturyzowane wywiady ze specjalistami z branży pożarniczej. Kwestionariusz został opracowany w kontekście Sri Lanki. Wykwalifikowany i doświadczony zespół specjalistów ds. pożarnictwa został poproszony o uszeregowanie przygotowanego kwestionariusza, który został podsumowany w dwunastu kategoriach ryzyka. Chociaż metod oceny ryzyka pożarowego jest niewiele, w niniejszym badaniu zastosowano metodę wskaźnika względnej istotności. Wyniki uzyskane z pięciostopniowej skali Likerta, gdzie „1” to najmniejszy poziom ryzyka, a „5” to najwyższy poziom ryzyka, zostały przekonwertowane w celu identyfikacji priorytetów z RII. Project and methods: The methodology of this research consists of a qualitative approach, which includes a literature review, a questionnaire-based survey, and semi-structured interviews with fire industry professionals. The questionnaire was developed in a Sri Lankan context following an extensive literature review that included the author's experience. The qualified and experienced panel of fire specialists was asked to rank the prepared questionnaire, which was summarized into twelve risk categories. Though there are few fire risk ranking methods, the relative importance index method was applied in this research as it is simple and easy to use for ranking the risk factors. The results obtained from the five-point Likert scale, where “1” is the least risk level and “5” is the highest risk level, were converted to identify priorities with RII. Results: In the Sri Lankan context, it was discovered that issues with design and the approval of inaccurate building plans are the first and second major isk factors, respectively, out of the twelve categories identified. Thus, it was evident that deviations made at the design stage are the most significant risk factors, according to the Sri Lankan setting. Most of the mistakes that are made at the design stage cannot be rectified at a later stage under normal conditions, as it could incur huge costs to change the building structures. Conclusions: The study summarizes twelve factors that contribute to fire-related incidents in Sri Lankan buildings. Among these factors, the survey data shows that incorrect building design and the approval of inaccurate building plans for construction are the primary contributors to the high frequency and severity of fire-related incidents. Despite the availability of comprehensive fire safety regulations in Sri Lanka, the research reveals a significant gap in their implementation, from design to maintenance. These findings stress the importance of incorporating fire and safety management criteria into the building design stage, covering both construction and subsequent maintenance, to prevent fire incidents in Sri Lanka. Keywords: prescriptive fire codes, fire risk factors, fire risk assessment, fire risk ranking, building fire safety

Comparison of Meteorological Drivers of Two Large Coastal Slope-Land Wildfire Events in Croatia and South-East Australia

Understanding the relationship between fire behavior and the driving weather conditions is critical for fire management and long-term fire risk assessment. In this study, we focus on two wildfire events: the Split wildfire in Croatia and the Forcett–Dunalley wildfire in Tasmania, Australia. The antecedent weather in both events included extremely dry conditions and higher-than-average air temperatures in the months prior to the events. The synoptic patterns in both events consisted of a large surface pressure gradient, which generated strong wind, driving the fire’s spread. The Weather Research and Forecasting (WRF) model was utilized to simulate fire weather conditions during the development of the two events. In the innermost domain of WRF, resolution is 500 m with explicit moisture calculation only, and there are 66 vertical levels, with about 20 of them to resolve the boundary layer. The WRF simulations are well verified by station observations, including upper-level wind speeds. The convergence line pattern in the Tasmanian event, which was conducive to intense plume development, has been well simulated. Only a slight discrepancy was identified in the simulation of the coastal change in wind direction in the Croatian event. It is identified that in the Split case, bura wind was highly coupled with an upper-level trough, which induced subsidence of the upper-level dry and cold air to the surface, causing rapid drying of the fuel. During the Forcett–Dunalley fire, the atmosphere was unstable, which enabled deep pyrocumulonimbus development. In general, the development from ignition to the timing of the most extreme fire intensity in both events was largely determined by the evolution of the surface to upper-level meteorological drivers. While these extreme meteorological conditions would impact fire-fighting strategies such as aircraft operations, a model-based estimate of the high-risk areas is critical. Our findings would also benefit an estimate of the climatology of fire events with similar behavior and thus a long-term fire risk assessment.

Quantitative integration of fire risk with life cycle analysis of building: The case of thermal insulation

Given the ever-growing importance of environmental sustainability, greater attention has been paid to the energy consumption of buildings. A significant share of such consumption is due to the thermal regulation of buildings’ interior spaces. Thermal insulation is highly effective in reducing these energy needs. Consequently, national policies have been introduced or revised to increase the minimum insulation requirements. Besides, a large share of thermal insulation materials is currently plastic-based. These materials were found to have increased the severity of fire consequences in a few recent major fires. Instead, inorganic fibrous insulation materials, especially those almost incombustible, have a lower impact on fire development but also lower thermal insulation performances. The optimization problem, with fire safety on one side and energy performances on the other, has been the subject of recent research. Nonetheless, due to the numerous uncertainties, such optimization is usually discussed only qualitatively. Conversely, in this work, full probabilistic methods and damage-to-impact conversion are applied to fire risk assessment and found to be a reliable strategy for a quantitative approach. Thus, a quantitative integration of fire risk-based environmental impact of thermal insulation, applied to a general case study, is presented. Damage-to-impact conversion is realized by using embodied carbon values and fire fragility functions. This application also accounts for direct greenhouse gas emissions from combustion. The final results show that fire consequences are comparable with the superior thermal performance effects in the environmental balance between plastic-based and inorganic fibrous insulation materials.

Fires in Waste Treatment Facilities: Challenges and Solutions from a Fire Investigation Perspective

Fires in waste treatment facilities have significant social, economic, and environmental implications. Factors such as self-heating of lithium-ion batteries, thermal runaway, friction, human activities, technical errors, and unfavorable storage conditions contribute to these fires. High-risk categories include illegal dumping sites, recycle collection stations, and wood-related facilities. The frequency of fires in waste treatment facilities and the emergence of new waste types have led to public discontent. Regulatory challenges and oversight difficulties pose further obstacles. This study analyzes fire incidents in Kaohsiung City’s waste treatment facilities over the past five years, exploring their causes, regulatory frameworks, and practical challenges. Valuable insights and recommendations are provided to enhance fire safety and risk assessment. These measures aim to mitigate fires’ environmental and facility consequences and their impact. Prioritizing fire prevention and reducing potential economic, social, and environmental consequences are crucial for improving fire safety in waste treatment facilities. Addressing these challenges and prioritizing the safety and sustainability of the waste treatment industry is imperative.