Impact Of Fire Research Articles

Impact of forest fires in bromo national park: Analysis of the environment and recovery efforts

Background: Forest fires represent natural disasters that often stem from environmental conditions, including events like El Niño or extreme climatic situations. Rainfall, a crucial factor, plays a role in influencing extreme climate occurrences. In Indonesia, human activities predominantly contribute to forest fires, exacerbated by extreme climatic conditions. Areas with high potential for forest fires encompass conservation zones closely linked to human activities. An illustrative example is the Bromo Tengger Semeru National Park (TNBTS), which serves both as a conservation and tourist area. The presence of human tourists or visitors in these conservation zones creates conditions conducive to forest fires, particularly when supported by extreme climatic conditions. Method: This study used field observation methods, satellite data analysis, and interviews with authorities and environmental experts. The data collected included the area affected, the plant types, and the environmental conditions after the fire. Findings: TNBTS experiences a specific rainfall pattern, with the lowest precipitation observed in May-Jun-Jul-Aug-Sept and the highest in Nov-Dec-Jan-Feb-Mar. During periods of low rainfall, TNBTS becomes susceptible to fires, necessitating preventative measures in the month leading up to the dry season. Initiating preventative actions at the onset of the dry season, notably in May, is crucial for controlling forest fires. Analyzing hotspot data of fire incidents from 2001 to 2020 reveals peak occurrences among other nationalities in 2001, 2014, and 2019. Identification based on data indicates that not all hotspots signify fire incidents; some result from heat emanating from Mount Semeru's crater at the TNBTS location. Conclusion: This article concludes the importance of cooperation between authorities, environmental organizations, and communities in forest fire prevention and recovery efforts in Bromo National Park. It emphasizes the need for increased preventive and responsive measures to protect similar conservation areas in the future. Novelty/Originality in this article: This study also offers a new perspective in the interpretation of hotspot data by distinguishing between forest fires and volcanic activity and identifying May as a critical period for initiating preventive action analysis based on long-term rainfall patterns.

Prescribed fire and grass mulch impact on selected soil properties and amelioration potentials of amendments under an agricultural field in Ile-Ife, Nigeria

Prescribed fire (slash and burn) tends to impede the sustainable functionality of soil in agricultural systems. However, the use of amendment has a potential to reverse these negative effects. Prescribed fire is still used by farmers in Nigeria for land preparation before planting. This has continued to increase soil degradation in Nigeria with no agronomic activities that could ameliorate this effect in view. This study therefore examined the influence of prescribed fire and grass mulch on selected soil physical properties and organic carbon immediately after burning, and the potential of amendment to improve the soil properties negatively affected by fire. The prescribed fire treatments consisted of 200 °C and 500 °C fire intensities using Megathyrsus maximus (a large perennial bunch of grass that is dominant in the study area) as the fuel and also served as the grass mulch. Cured poultry manure at 7.5 t ha−1 was combined with urea at 40 kg N ha−1 and applied as a combined amendment while a single dose of urea was applied at 80 kg N ha−1 as an inorganic amendment. The experiment was carried out across three cropping seasons on maize (Zea mays L.) in 2019 and 2020. Soil water repellency (SWR), bulk density (Db), soil unsaturated hydraulic conductivity (Kunsat), water stable aggregates (WSA), soil strength (SS), and soil organic carbon (SOC) were determined immediately after burning and three months after amendments were applied. Data obtained were subjected to analysis of variance and means separated using the Duncan multiple range test at p≤0.05. Results showed that prescribed fires increased SWR by an average of 50.1 and 62.7 % for 200 °C and 500 °C intensities, respectively compared with the control. Three months later, the SWR was reduced by 25.9 % and 62.3 % for 200 °C and 500 °C, respectively when no amendment was added. Notably, the addition of sole urea and cured poultry manure + urea reduced the SWR by 50 % and 48.5 %, respectively in the 200 °C intensity, and 62.2 % and 62.7 % in the 500 °C intensity, respectively. Also, Kunsat was reduced by an average of 49.6 and 62.2 % by 200 °C and 500 °C intensities, respectively just after burning. However, it was not improved three months after the prescribed fires despite the applied amendments. The prescribed fire of 200 °C and grass mulch had no significant influence on OC just after the fire. Also, amendments did not significantly improve OC three months after prescribed fire. Therefore, the non-improvement of other soil properties, after the applied amendments, showed that further study is required to determine the required rate of the applied amendments that will significantly improve other soil properties negatively affected by prescribed fire in agricultural soils.

Temporal Variations in Fire Impacts on Characteristics and Composition of Soil-Derived Dissolved Organic Matter at Qipan Mountain, China.

Dissolved organic matter (DOM), the most reactive fraction of forest soil organic matter, is increasingly impacted by wildfires worldwide. However, few studies have quantified the temporal changes in soil DOM quantity and quality after fire. Here, soil samples were collected after the Qipan Mountain Fire (3-36 months) from pairs of burned and unburned sites. DOM contents and characteristics were analyzed using carbon quantification and various spectroscopic and spectrometric techniques. Compared with the unburned sites, burned sites showed higher contents of bulk DOM and most DOM components 3 months after the fire but lower contents of them 6-36 months after the fire. During the sharp drop of DOM from 3 to 6 months after the fire, carboxyl-rich alicyclic molecule-like and highly unsaturated compounds had greater losses than condensed aromatics. Notably, the burned sites had consistently higher abundances of oxygen-poor dissolved black nitrogen and fluorescent DOM 3-36 months after the fire, particularly the abundance of pyrogenic C2 (excitation/emission maxima of <250/∼400 nm) that increased by 150% before gradually declining. This study advances the understanding of temporal variations in the effects of fire on different soil DOM components, which is crucial for future postfire environmental management.

The Impact of Catastrophic Forest Fires of 2021 on the Light Soils in Central Yakutia

This paper presents the results of studying changes in the main parameters and properties of soils in larch and pine forests growing on sandy soils of the Lena-Vilyui interfluve of Central Yakutia, where catastrophic forest fires occurred in 2021. According to the remote monitoring information system of Rosleskhoz, in 2021, almost 8.5 million hectares of forests burned in Yakutia, which is considered as one of the largest forest fires in Russia and in the world in that year. After the fire passes through the forest floor, the content of organic matter decreases as a result of combustion processes. The acidity of the soil changes towards its alkalization due to the entry of combustion products. Changes in soil profiles occur; turbation processes begin more intensively, which in turn change the natural distribution of soil indicator values such as the organic carbon content, the pH, and the number of exchangeable bases. Due to the sharp increase in heat supply after a fire, the depth of seasonal thawing in the soils of burnt larch forests increases by a quarter and by twofold in pine forests. With the beginning of the thawing of the seasonally frozen layer, all the soils experience waterlogging, and ground water occurs above the permafrost.

The CHIMERE chemistry-transport model v2023r1

Abstract. A new version of the CHIMERE model is presented. This version contains both computational and physico-chemical changes. The computational changes make it easy to choose the variables to be extracted as a result, including values of maximum sub-hourly concentrations. Performance tests show that the model is 1.5 to 2 times faster than the previous version for the same setup. Processes such as turbulence, transport schemes and dry deposition have been modified and updated. Optimization was also performed for the management of emissions such as anthropogenic and mineral dust. The impact of fires on wind speed, soil properties and leaf area index (LAI) was added. Pollen emissions, transport and deposition were added for birch, ragweed, olive and grass. The model is validated with a simulation covering Europe with a 60 km × 60 km resolution and the entire year of 2019. Results are compared to various measurements, and statistical scores show that the model provides better results than the previous versions.

Analysis and forecasting of the scale and impact of forest fires on ecosystems of Ukraine

Forest fires are one of the most significant environmental problems that have a major impact on biodiversity and climate conditions. The purpose of the study was to investigate the impact of military operations on the ground cover in the area of the Bekhy forestry, which was disturbed by fire. It was revealed that for the period 2022-2023, 15 forest fires were recorded on the territory of the Korosten forest hunting enterprise of the state enterprise “Forests of Ukraine”, while the total area covered by fires was 15.13 ha. Overall, the number of fires increased from 5 to 10, but the total area covered by fires decreased from 12.1 to 3.03 ha. At the site of fires in 2022, the pH level increased to lower horizons, with the highest values at microhills (7.55) and microdepressions (7.35). There was a slight increase in the organic carbon content in the upper humus horizon of soils (0.42% on microhills and 0.46% on microdepressions). Bekhy forestry suffered a large forest fire in May 2023, which covered an area of 1.2 ha. The fire hazard assessment of each quarter was carried out separately. In the 50th and 51st compartments, Scots pine was the most fire-prone type of plantings. The 2023 fire site also showed an increase in pH in the lower horizons, with the highest values in microhills (7.35) and microdepressions (7.55). The 2023 fire site showed a decrease in organic carbon content compared to the background sites, with minimal values in the lower parts of the soil profile (0.33% on microdepressions and 0.38% on microhills). The results of the study can be used to develop and implement environmental measures and programmes aimed at restoring forests damaged by fire

Literatur Review: Impact of Land Clearing for Palm Oil by Burning on Carbon Releases and Wildlife in Indonesia

Fires on palm oil plantations always occur in Indonesia, although they have decreased from 2015 to 2020. This happens because fires are a fast and easy way to clear and clear land. Fires in palm oil plantations can damage the environment and wildlife. Knowing the impact on the environment and animals, this article searches for and collects the results of previous research using traditional literature review methods. The literature review results show that oil palm was initially an ornamental plant brought from Africa, then cultivated in the Bogor Botanical Gardens. Successful cultivation is then developed into plantation crops that have the potential to be widely cultivated in Indonesia. This causes an increase in the need for land to cultivate these plants. This increase in land demand causes fires to occur in Indonesia which impacts the release of carbon and wildlife. Carbon released from vegetation fires causes air pollution which results in environmental damage. These fires can also harm wildlife due to loss of habitat and food sources. To reduce the impact of fires, recommendations are given to increase CPO production without having to open new land, which can potentially increase forest and land fires. The recommended method is a partnership with oil palm farmers. This can meet CPO production needs for local and international markets without having to open new concessions. This method can also be used as an alternative to help oil palm farmers manage crops and improve the community's economy.

Forty-Year Fire History Reconstruction from Landsat Data in Mediterranean Ecosystems of Algeria following International Standards

Algeria, the main fire hotspot on the southern rim of the Mediterranean Basin, lacks a complete fire dataset with official fire perimeters, and the existing one contains inconsistencies. Preprocessed global and regional burned area (BA) products provide valuable insights into fire patterns, characteristics, and dynamics over time and space, and into their impact on climate change. Nevertheless, they exhibit certain limitations linked with their inherent spatio-temporal resolutions as well as temporal and geographical coverage. To address the need for reliable BA information in Algeria, we systematically reconstructed, validated, and analyzed a 40-year (1984–2023) BA product (NEALGEBA; North Eastern ALGeria Burned Area) at 30 m spatial resolution in the typical Mediterranean ecosystems of this region, following international standards. We used Landsat data and the BA Mapping Tools (BAMTs) in the Google Earth Engine (GEE) to map BAs. The spatial validation of NEALGEBA, performed for 2017 and 2021 using independent 10 m spatial resolution Sentinel-2 reference data, showed overall accuracies &gt; 98.10%; commission and omission errors &lt; 8.20%; Dice coefficients &gt; 91.90%; and relative biases &lt; 3.44%. The temporal validation, however, using MODIS and VIIRS active fire hotspots, emphasized the limitation of Landsat-based BA products in temporal fire reporting accuracy terms. The intercomparison with five readily available BA products for 2017, by using the same validation process, demonstrated the overall outperformance of NEALGEBA. Furthermore, our BA product exhibited the highest correspondence with the ground-based BA estimates. NEALGEBA currently represents the most continuous and reliable time series of BA history at fine spatial resolution for NE Algeria, offering a significant contribution to further national and international fire hazard and impact assessments and acts as a reference dataset for contextualizing future weather extremes, such as the 2023 exceptional heat wave, which we show not to have led to the most extreme fire year over the last four decades.

SIMULATION MODEL FOR UNMANNED AERIAL COMPLEXES AT LAUNCHING POSITIONS SURVIVABILITY ASSESSEMENT

The relevance of issues related to the justification of the rational approaches to the combat operations planning using unmanned aircraft systems, which are now assigned the main role in attacking the enemy by fire, necessitates the development of methods for evaluating such actions. The issue of increasing the survivability of unmanned aircraft systems under combat conditions is of important applied importance. The subject of the study is the unmanned aircraft systems application under the conditions of enemy action planning process. The article uses operations research methods. The purpose of the work is to develop a simulation model in the form of an algorithm, that allows conducting process research based on quantitative estimates and substantiating decisions aimed at increasing the survivability of unmanned aircraft systems under conditions of enemy action. By varying the parameters of the simulation model, it becomes possible to develop the most rational solutions for the unmanned aircraft systems use, ensuring the maximum level of their survivability under the specific conditions of combat operations. A simulation model is proposed, with the help of which it is possible to quantitatively evaluate decisions regarding the tactics of using UAV and finding ways to increase the level of their survivability under the conditions of enemy fire. During the implementation of the proposed model, statistics of the results of the simulated fire impact are accumulated, that allows to calculate estimates of the probability of UAV, deployed at the launching positions, to get various degrees of damage. By varying the specified parameters, it becomes possible to develop the most rational solutions aimed at increasing the survivability of UAV under the specific conditions of combat activities performing. The proposed simulation model for the survivability of unmanned aircraft systems assessment may be used in the decision support system for the appropriate level commander.

Fire protection priorities in the oak forests of Iran with an emphasis on vertebrate habitat preservation

This study examines the impact of fire incidents on wildlife and habitats in the western oak forests of Iran (Zagros region). These forests are globally recognized for their exceptional biodiversity but are frequently threatened by wildfires. To achieve this, the study uses the space–time scan statistics permutation (STSSP) model to identify areas with a higher frequency of fires. The study also analyzes the effects of fires on the Zagros forests from 2000 to 2021 using remote-sensing MODIS data. Also, to understand the elements at risk of fire, burned areas were assessed based on the richness of vertebrate species, determined by the distribution of 88 vertebrate species. The results show that the annual fire rate in the Zagros forests is 76.2 (fire occurrences per year), calculated using the Poisson distribution. Findings show the highest fire rates are found in the northwest and a part of the south of the Zagros. The northwest of the Zagros also has the largest number of single fires and clusters, indicating a wide spatial distribution of fire in these regions. On the other side, it was unexpectedly found that these regions have the richest number of species and higher habitat value. The results demonstrate a significant correlation between the value of the habitat and the extent of burned areas (p < 0.05). The study also reveals that the greatest impact of fires is on small vertebrates. The overlap of frequent fire spots with the richest regions of Zagros oak forests in terms of vertebrate diversity emphasizes the need for strategic forest risk reduction planning, especially in these priority zones.

Knowledge shortfalls and the effect of wildfires on biodiversity conservation in Guanajuato, Mexico

Knowledge of shortfalls could modify the geographic distribution patterns and limit the actions to conserve the biodiversity, even in the taxa best known. In addition, forest fires also could modify those patterns, but the potential effects of both factors have not been tested. Our aim was to analyze the effect of the Linnean and Wallacean shortfalls in the first evaluation of wildfire impacts on 22 amphibian and 13 mammal species distributed in Guanajuato, Mexico. We evaluated those shortfalls using the non-parametric estimator Chao2 and the Qs estimator and through maps of species richness patterns. To evaluate the effects of wildfires, we produced a fire recurrence map and quantified the burned area within species distributions and in 24 Protected Natural Areas (PNA) in the state. The Linnean shortfall showed some species missing to record in Guanajuato for both taxa, while the Wallacean shortfall showed poor quality of knowledge. Fire recurrence was high within 5 PNA. The richness patterns affected by fires covered nearly 17% of the surface of Guanajuato. Improving the knowledge of biogeographical patterns could provide better tools to stakeholders to decrease the negative impact of fires within PNA.

Stubble burning: What determines this fire?

Despite the recognized impact of agricultural fires on air pollution and public health globally, with significant consequences observed in regions such as China, India, and Turkiye, there remains a critical gap in understanding their underlying causes. This study aims to identify the key factors influencing agricultural fires in Turkiye between 2012 and 2021. This research conducts a thorough district-level evaluation using extensive micro-level data, remote sensing datasets, and robust methodologies, including fixed effects and spatial panel data methods. The study finds that variables such as the cultivation of second-crop corn and regional conflicts positively correlate with fire occurrences. In contrast, factors like cotton cultivation, livestock presence, and forested areas are inversely related to fire incidents. These findings underscore the complicated relationship between agricultural practices, environmental factors, and socio-economic conditions influencing fire occurrences. The study's outcomes offer significant policy implications, highlighting the necessity for customized strategies to curb agricultural fires. These strategies encompass promoting alternative crop patterns, tackling socio-economic determinants, and accommodating regional specificities.

Effects of management practices on Northern Bobwhite Colinus virginianus density in privately owned working forests across the Southeastern United States

Abstract Obtaining rigorous baseline density estimates of species of conservation interest is key when assisting landowners to achieve management goals on private lands. Northern bobwhite (Colinus virginianus) populations are declining throughout their range and despite being the focus of numerous private land conservation initiatives, baseline density estimates in privately owned pine forests are lacking. We sought to address this knowledge gap across the Southeastern United States by sampling 105 privately owned pine stands throughout 2018 to 2020 using observer point count and autonomous recording unit (ARU) sampling data. Using Bayesian hierarchical models, we investigated the influence of stand management (brush management or applied fire) on bobwhite density, as well as four landscape‐scale environmental variables. These included percentage cover of forest, herbaceous, agricultural or burnt land area across six different spatial scales ranging from 500‐m to 10‐km around each pine stand. Baseline density on sites with no management was estimated to be 2.24 coveys per 100 ha (1.00–5.03, 95% BCI), with little impact of applying brush management, but a trend for a positive effect of fire management (0.19, −0.01 to 0.38 95% BCI). This impact of fire was seen at both the stand‐scale, correlated with an increase in acreage of applied prescribed burn management, and across the greater landscape area, correlated with cover of burnt area within a 2‐km buffer around each site. There were also strong positive influences of herbaceous vegetation and a strong negative influence of forest cover on bobwhite density. Practical implication: our sampling efforts fill an important information gap regarding densities throughout private lands in the Southeastern United States. Our study also highlights the necessity of landscape scale planning for Northern Bobwhite conservation initiatives because the efficacy of conservation practices (i.e. prescribed fire and brush management) could be altered by the landscape surrounding the treated forest stand.

Robust Forest Fire Detection using Deep Convolutional Neural Networks

Forest fires pose significant threats to ecosystems, wildlife, and human lives, necessitating proactive measures for early detection and rapid response. This paper presents FireGuard, an efficient model for forest fire detection using deep convolutional neural networks (CNNs). Leveraging the power of deep learning and image processing techniques, FireGuard analyzes aerial imagery and satellite data to detect signs of smoke and fire outbreaks in forested areas. The model utilizes a lightweight CNN architecture optimized for real-time performance and resource-constrained environments, making it suitable for deployment on unmanned aerial vehicles (UAVs), surveillance cameras, and satellite platforms. Experimental results demonstrate the effectiveness of FireGuard in accurately identifying forest fires with high precision and recall, outperforming traditional methods and existing deep learning models. By providing early warnings of potential fire incidents, FireGuard enables timely intervention by fire fighting agencies, thereby mitigating the impact of forest fires and preserving natural habitats.

Firebreaks and Their Effect on Vegetation Composition and Diversity in Grasslands of Golden Gate Highlands National Park, South Africa

Southern African grasslands with a rich flora, shaped by fire, grazing, climate and geology, as well as playing a role in carbon sequestration, are becoming more important in conservation. Fire is often used as a management tool to improve vegetation and to protect property against uncontrolled fire. We therefore attempt to determine the effect consecutive burning has on vegetation. Paired plots along firebreaks were used to collect vegetation data using the Braun-Blanquet cover abundance scale. Soil samples were also collected to determine the impact of fire on below-ground nitrogen (N) and carbon (C) stocks and ratios. The results indicate that there is no difference between the plant communities of the firebreaks and the adjacent grassland; however, there are certain species that are favoured by firebreaks and others by the adjacent grassland. There is also no difference in diversity between the firebreaks and adjacent grassland areas. Carbon and nitrogen stocks as well as C:N ratios did not differ significantly between the firebreaks and the adjacent grassland plots although trends indicate a decline in both C and N with repeated burning.

Small Fires, Big Impact: Evaluating Fire Emission Estimates in Southern Africa Using New Satellite Imagery of Burned Area and Carbon Monoxide

AbstractVarious fire emission estimates for southern Africa during 2019, derived with multiple burned area data sets with resolutions ranging from 500 to 20 m, are evaluated using satellite carbon monoxide (CO) observations. Southern African emissions derived from burned area generated by 20 m Sentinel‐2 satellite imagery are up to 120% higher than other estimates because small fires are better detected with a higher‐resolution satellite instrument. A comprehensive comparison between simulated and observed atmospheric CO indicates that the Sentinel‐2 burned area data significantly improves emission estimates, with up to 15% reduction in CO concentration biases in comparison to emissions based on coarser resolution burned area data. We also found that the temporal lag between emissions and atmospheric CO concentrations during the peak fire month was related to atmospheric transport. These findings emphasize the importance of utilizing higher‐resolution satellite instruments in accurately estimating emissions and understanding the impact of small fires on global climate.

Impact and recovery of forest cover following wildfire in the Northern Rocky Mountains of the United States

BackgroundAnthropogenic climate change is expected to catalyze forest conversion to grass and shrublands due to more extreme fire behavior and hotter and drier post-fire conditions. However, field surveys in the Northern Rocky Mountains of the United States show robust conifer regeneration on burned sites. This study utilizes a machine learning (GBM) approach to monitor canopy cover systematically on a census of burned areas in two large wilderness areas from 1985 to 2021, to contextualize these recent field surveys and create a monitoring baseline for future change.ResultsA predictive model was developed from coincident LiDAR and Landsat observations and used to create time series of canopy cover on 352 burned sites (individual wildfires subset by number of times burned), which were then summarized using fire impact and recovery metrics. Fire impact, defined as canopy cover loss relative to pre-fire condition, was highly correlated with burn severity (Spearman’s R = 0.70). Recovery was characterized by the following: (1) whether a burned area began gaining canopy cover and (2) how long would it take to reach pre-fire cover given observed rates of gain. Eighty-five percent of the land area studied showed evidence of recovery. Areas that are failing to recover are burning more recently than their recovering counterparts, with 60% of non-recovering sites burning for the first time after 2003. However, the 5-year probability of recovery is similar among recent burns and for those that burned earlier in the record, suggesting that they may recover with more time. Once sites begin recovering, median time to reach pre-fire cover is 40 years. Seven sites have expected recovery times greater than 200 years, six of which burned for the first time after 2006.ConclusionOverall, burned sites in wilderness areas of the Northern Rocky Mountains are broadly recovering from wildfire. However, anthropogenic climate change adds a layer of uncertainty to the future prognosis of conifer recovery. This work provides a framework for systematic monitoring into the future and establishes a baseline of impact and recovery in the mountains of western Montana and northern Idaho.

Sentinel 2 based burn severity mapping and assessing post-fire impacts on forests and buildings in the Mizoram, a north-eastern Himalayan region

The Increasing frequency and severity of forest fires worldwide highlights the need for more effective Burnt area mapping. Finding the effects of fire on vegetation and putting mitigation methods in place, depends on post-fire evaluation. In this study, the location of the burned regions and the severity of the fire were determined using high-resolution multi-spectral images from Sentinel 2 on Google Earth Engine (GEE) platform. Three widely used fire severity indices—differenced Normalized Burn Ratio (dNBR), Relativized Burn Ratio (RBR), and Relativized dNBR (RdNBR)—based on pre-fire Normalized Burn Ratio (NBR) and post-fire NBR—were computed and compared based on their accuracy using very high-resolution planet imagery fire points and equal number of random non fire points. Maps also validated with active fires, ground based photos and crowdsourced images. The accuracy (AUC) of the RdNBR map was 85%, RBR - 84% and dNBR −82%. The RdNBR index demonstrated highest level of accuracy. Then the loss to vegetation using pre-fire and post-fire NDVI was analysed. The analysis of pre-fire and post-fire NDVI provided insights into the extent of vegetation loss. The analysis of vegetation loss offered valuable information regarding the impact of fire on the affected areas. Google building dataset was used to monitor the percent of buildings under threat due to these fires. Around 8.77% of buildings were found in high severity region. Accurate mapping aids post-fire evaluation, guided mitigation strategies, and enhanced forest management and ecological restoration.

The Dynamic Change in the Reliability Function Level in a Selected Fire Alarm System during a Fire.

This article discusses fundamental issues associated with the functional reliability of selected fire alarm systems (FASs) in operation during building fires. FASs operate under diverse external or internal natural environmental conditions, and the operational process of FAS should take into account the impacts of physical phenomena that occur during fires. Their operation is associated with the constant provision of reliability. FAS designers should also consider the system's reliability when developing fire control matrices, tables, algorithms, or scenarios. All functions arising from an FAS control matrix should be implemented with a permissible reliability level, RDPN(t), prior to, as well as during, a fire. This should be assigned to the controls saved in the fire alarm control unit (FCP). This article presents the process by which high temperatures generated during a fire impact the reliability of FAS functioning. It was developed considering selected critical paths for a specific scenario and the control matrix for an FAS. Such assumptions make it possible to determine the impact of various temperatures generated during a fire on the reliability of an FAS. To this end, the authors reviewed that the waveform of the R(t) function changes for a given FAS over time, Δt, and then determined the fitness paths. The critical paths are located within the fire detection and suppression activation process, using FAS or fixed extinguishing devices (FEDs), and the paths were modeled with acceptable and unacceptable technical states. The last section of this article defines a model and graph for the operational process of a selected FAS, the analysis of which enables conclusions to be drawn that can be employed in the design and implementation stages.

Greenhouse gas emissions related to fires in photovoltaic installations

Life cycle assessments, LCA, can be made on all types of materials and products where the total environmental impact of the production, use and end-of-life is quantified. By including fire as one potential end-of-life scenario, the emissions related to these, and potential benefits from reducing the risk of fire can be quantified. The question addressed in this article is how fires in photovoltaic (PV) installations affect the environmental impact in a life cycle perspective. This will be evaluated by using a methodology called Fire-LCA that is based on standard LCA according to ISO 14040. The total emissions from PV-related fires in buildings and the emissions related to rebuilding and replacing the damaged materials normalised over the amounts of produced electric energy are calculated to 0.3 g CO2eq/kWh. This is two orders of magnitude lower than the typical 43.6 g CO2eq/kWh for the normal life cycle of PV installations. This comparison puts the environmental impact of PV-related fires in perspective and underlines that PV installations still make a large positive impact on the reduction of CO2eq-emissions from electricity production even though they represent a certain fire hazard.