Abstract Wildfire incidents and their impact on the environment and socio-economic factors have been of major concern globally. Consequently, several studies sought to understand the influence of climate change-related extreme conditions and anthropogenic activities on wildfire occurrence and regimes and their subsequent impact on biodiversity, ecosystems, soil sustainability, air quality, and atmospheric processes. The current study particularly focuses on the additional pressure exerted by armed conflicts and wars, often overshadowed by more immediate concerns such as saving lives. Specifically, we explored the influence of the Russia-Ukraine war, that began in February 2022, on fire incidents and burned areas in Ukraine. We conducted a comparative analysis of MODIS and VIIRS active fire products to characterise spatio-temporal patterns of fire incidence hotspots between 2021 (pre-war) and 2022 (during the war). The results revealed a higher number of significant fire incident hotspots at a 95% confidence level and higher burning in 2022, particularly in croplands and forests, which has implications for food security and environmental sustainability in Europe. The forests were impacted as part of the war-related activities near Chornobyl Nuclear Power Station in northern Ukraine, while most croplands were burned in the eastern parts. The study also revealed that MODIS and VIIRS varied spatially and temporally in detecting fire incidents and hotspots, with VIIRS exhibiting significantly more fire incidents per land cover class (p < 0.02), and hotspots across all seasons. This finding is consistent with previous studies that found that VIIRS detects significantly more fires than MODIS. Furthermore, the spatio-temporal distributions of fire hotspots were mostly consistent with reports of war-related activities by Armed Conflict and Location Dataset. By evaluating the MODIS and VIIRS fire products, this study underscores the potential of remote sensing data in assessing war-induced fire incidents and their environmental consequences, which may persist for a long time after the war.

ABSTRACT Biomass and industrial fire points are crucial to forest fire prevention and industrial carbon emissions research. However, only a few investigations in the literature focus on fire point classification tasks using different spatial resolutions fire datasets in China. A comprehensive and accurate analysis of the spatial and temporal distribution characteristics and trends of fire points in China during the past decade is lacking. In this study, industrial heat source data, four fire point data, including VIIRS 750-m Nightfire (VNF), VIIRS 375-m Active Fire points (ACF), MODIS 1000-m fire points (MF) and Landsat-8 30 m fires data (LF), and land cover type data were integrated to more accurately classify fire points into biomass or industrial fire points. The result shows that our classification is more accurate than ACF’s results, and several conclusions were obtained from the spatial and temporal analysis of the total/biomass/industrial fire points across the four fire point datasets in China. (1) There was a high spatial and temporal correlation across all four datasets in China between 2012 and 2021. The annual numbers of fire points from the four fire point datasets all increased from 2012 to 2013, peaked in 2014, and have since declined. (2) The number of industrial fire points across the four datasets was static and persistent over the time series and had tight spatial aggregation, with little variation in their annual numbers and spatial distribution over time. In contrast, biomass fire points exhibited more significant changes in their spatial distribution, and the annual number declined after 2014. (3) The distribution of biomass fire points shifted northward over time, gradually moving from the Yangtze-Huai Plain and Yunnan Province in 2012 to northeastern China after 2018. These findings highlight the importance of considering temporal factors when analyzing fire point data, as well as the potential benefits of utilizing multiple datasets to achieve more accurate results.

Assessing environmental impacts of active fire protection and egress systems using environmental product declarations: A review

Background. Transboundary air pollution in Southeast Asia is driven largely by smoke from vegetation and peatland fires that carry fine particulates across borders and raise health risks. Objective of Study. We map the peer reviewed literature from 2000 to mid 2025 and translate the evidence into a roadmap for governance and resilience. Methodology. A targeted search was conducted on 11 July 2025, using the sole keyword phrase "Pollution Southeast Asia" restricted to the article title field. This search echoed a total of 72 documents, all of which were retained for this analysis, and produced keyword cooccurrence maps in VOSviewer. Results. Four stable clusters emerge: PM2.5 haze and fire emissions; monitoring and event attribution that pair station observations with satellite active fire detections; exposure and health outcomes; and regional framing within ASEAN cooperation. Collaboration is strongest among Indonesia, Malaysia, and Singapore. Top cited work quantifies excess mortality during severe haze seasons and separates local and transboundary PM2.5. Discussion. Overlay trends show a mature core and growing operational monitoring since 2018. An evidence based SWOT confirms the connected core and flags gaps in health integration, monitoring quality disclosure, and country coverage. Strategic roadmap. We propose time bound actions over 0 to 12 months, 1 to 3 years, and 3 to 5 years with indicators for outcomes (population weighted PM2.5, haze advisory days, stations meeting the WHO guideline), sources (peat fire counts, burned area), and system performance (station density, data capture, use of regional advisories). Conclusion. The roadmap aligns with ASEAN instruments and enables transparent evaluation of progress.

With rising global temperatures attributed to climate change, an increase in fire occurrences worldwide is anticipated. Therefore, a detailed examination of changing fire patterns is essential to improve our understanding of effective control strategies. This study analyzes the long-term trends of fire activity in Southern India (8–20° N, 73–85° E), utilizing MODIS active fire count data from January 2003 to December 2023. The climatological monthly mean results show that Southern India experiences heightened fire activity from December to May, reaching a peak in March. Yearly variations indicate that the highest fire counts occurred in 2021, followed by 2023, 2012, and 2018. The three most significant fire years in recent history reflect an upward trend in fire activity over the past decade, confirming insights from annual trend analysis. The correlation between inter-annual fire anomalies and different meteorological factors reveals a notable negative relationship with precipitation and soil moisture and a positive relationship with surface air temperature (SAT). Soil moisture demonstrates a stronger correlation (−0.45) than precipitation and SAT. In summary, long-term trends show a noteworthy annual increase of 3%. Additionally, monthly trends reveal interesting rising patterns in October, November, December, and January with higher significance levels. Our research supports regional climate action initiatives and policies addressing fire incidents in Southern India in light of the ongoing warming crisis.

The Selway-Bitterroot Wilderness, a vast 1.3-million-acre expanse in western Montana and eastern Idaho, is a landscape deeply intertwined with fire. Today, this rugged wilderness area has one of the most active fire regimes in the contiguous US, and continues to be a “natural laboratory” for us to understand how fire interacts with forests, especially in a time of changing climate. I have spent two summers in the heart of the Selway-Bitterroot as part of research teams from the University of Montana, gathering data from and creating images of this unique area. These images reveal a landscape where fire is an agent of destruction but also one of stability and rejuvenation—a balancing force that creates space for new growth and adaptation.

Fifteen percent of people receiving care for major burn injuries in urban burn centers across North America were homeless pre-injury. The number and risk of such injuries are increasing due to greater numbers of people experiencing homelessness (PEH) and the frequency of extreme climate events. Prevention education, along with passive and active fire and cold weather protections, is critical for preventing these injuries. To increase acceptability, understandability, and actionability, prevention education needs to be in plain language, contextualized, and consumer-tested. We aimed to test newly developed fire and burn and cold injury prevention education materials with PEH and gain insights for preferred prevention strategies to address and mitigate related risks and hazards. Forty cognitive interviews with PEH were conducted. The Model System Knowledge Translation Center's consumer-testing toolkit was used to evaluate the understandability and actionability of the education materials. Transcripts were analyzed using a harm reduction framework and deductive and inductive thematic coding. Themes were: (1) engage-being approachable and accessible, (2) use context-specific design to enhance relatability-reflect the lived experiences of PEH and their environments, (3) reduce harm-focus on mitigating rather than eliminating hazards, (4) empower-incorporate prevention guidance, guided by PEH in combination with conventional prevention strategies, and (5) integrate-disseminate prevention education and PEH preferred safety equipment within services and locations utilized by PEH. The process of consumer testing with PEH generated acceptable fire and burn and cold injury prevention and mitigation strategies. These strategies were used to develop actionable prevention education materials.

ABSTRACT Recent disastrous wildfire seasons highlight the urgent need for timely and accurate wildfire data to support relief efforts, to monitor the environmental impacts and to inform the public. While satellite-based thermal anomaly data is available in near real-time (NRT), deriving actual fire-affected areas from NRT imagery remains challenging. The proposed methodology combines a superpixel segmentation algorithm with rule-based and deep learning classification techniques to accurately derive burnt areas (BA) in NRT. This approach supports a range of mid- to high-resolution optical sensors and fuses data from diverse sources to continuously refine the burnt area during the monitoring of active fires. The NRT (DLRBAv2NRT) and the refined non-time critical (DLRBAv2NTC) BA product based on mid-resolution Sentinel-3 imagery were produced and tested against established global BA products for wildfire seasons in Greece 2023, British Columbia (Canada) 2023, and Central Chile 2023/2024. DLRBAv2NTC classified BA with the highest accuracies over all study regions (avg. IoU: 0.71; avg. F1-Score: 0.83). Despite its NRT processing capability, the DLRBAv2NRT achieved comparable accuracies (avg. IoU: 0.69; avg. F1-Score: 0.81) and could outperform the well-established and widely used global NASA burnt area product MCD64A1v061 by +2% (IoU) and +1% (F1-Score). Furthermore, the multi-sensor and fusion capability of the methodology was successfully demonstrated for the 2024 Valparaiso fire in Chile. The proposed mapping procedure demonstrates a fully-automated and flexible approach to derive burnt area delineations from satellite data in NRT with high accuracy. This allows for high-frequency monitoring of NRT burnt areas on a global scale.

The research looks into developing and deploying autonomous drone systems for automated detection and enhanced fire surveillance of active fire incidents occurring in forests. The goal is to utilize novel sensing and artificial intelligence (AI) technologies, or advanced AI algorithms, to achieve rapid, precise, and real-time identification of early fire outbreaks so response time can be minimized to lessen the consequential damage on the environment and economy. Our methodology employs thermal and visual cameras along with UAVs equipped with AI-powered imaging systems for real-time anomaly detection, autonomous navigation, and active surveillance. Findings show that autonomous systems allow early detection and autonomous drones allow for faster speeds as compared to traditional methods which provide critical early warnings. This effort aims to pioneer new frontiers of research in intelligent forest fire management while improving the management of natural disasters.

With increasing wildfire severity and duration driven by climate change, accurately predicting fire behavior over extended time frames is critical for effective management and mitigation of such wildfires. Fire propagation models play a pivotal role in these efforts, providing simulations that can be used to strategize and respond to active fires. This study examines the fire area simulator (FARSITE) model’s performance in simulating recent wildfire events that persisted over 24 h with limited firefighting intervention in mostly remote access areas across diverse ecosystems. Our findings reveal key insights into a prolonged wildfire scenarios potentially informing improvements in operational fire management and long-term predictive accuracy, as the area comparisons indexes showed reasonable results between the detected fires from the fire information for resource management systems (FIRMSs) in the first 24 h of the fire and the following days. A case study of a recent wildfire in Madeira Island highlights the integration of real-time weather predictions and post-event weather data analysis. This analysis underscores the potential of combining accurate forecasts with retrospective validation to improve predictive capabilities in dynamic fire environments, which guided the development of a software platform designed to analyse ongoing wildfire events in real-time, leveraging image satellite data and weather predictions.

Abstract. The article discusses the guiding principles of tactical medical triage. There are significant differences between the provision of emergency medical care (EMC) to civilian casualties in peacetime and during hostilities or casualties who have received combat trauma. The features of combat trauma are as follows. Combat trauma is the result of the action of unique factors that include high energy and determine the high lethality of the factors of injury, multiple causes of injuries, the predominance of penetrating wounds, the preservation of the threat of re-injury in tactical conditions, a complex and harsh environment with limited resources and delayed evacuation, and, accordingly, the difficulty or impossibility of providing full assistance in the desired period of time. Tactical medicine specialists clearly identify three zones in the theater of military events in which EMC can be provided only to a certain extent. The red zone, or zone of active shelling, has the least opportunities for providing EMC. A place protected from active fire is called the yellow zone. Accordingly, specialists operating in the yellow zone have wider opportunities to provide EMС. Thus, the scope of assistance is expanded. The green zone or evacuation sector represents places that are adapted or equipped for receiving and sorting wounded victims, providing them with assistance, treatment and preparation for further evacuation. When conducting medical triage in tactical conditions, specialists distinguish urgent, delayed, minimal and expected categories of victims. Accordingly, representatives of the medical service determine the procedure and scope of providing the necessary EMС, monitor the correct functioning of triage, movement of victims, the scope and adequacy of EMС, and the evacuation procedure.

Abstract Fire occurrence in tropical peatlands is closely related to both land cover (LC) type and proximity to drainage (canal) networks. However, little is known about the extent to which LC and drainage density interact to alter fire occurrence. Here, we assess the relationship between these variables in the peatlands of Sumatra and Kalimantan, Indonesia, spanning a five-year period of inter-annual climatic variability. Visible Infrared Imaging Radiometer Suite imagery was used to map active fire hotspots. Drained peatlands experienced up to 13 times greater annual mean hotspot density (number of fire hotspots per km2) when compared to peatlands without canals. The greatest difference in fire hotspot density between drained and undrained peatlands occurred in forested peatlands (by a factor of 2.6–13.3), followed by shrublands (1.1–7.6), crop lands (1.4–5.0) and plantations (1.2–2.6), where largest differences were found in El Niño Southern Oscillation (ENSO) neutral years. We found a curvilinear relationship between hotspot density and canal density, with the relationship depending on LC and ENSO status. At low to moderate drainage density, hotspot density increased with drainage density in all LC types in 2013–2017. Heavily drained plantations experienced a lower hotspot density than moderately drained plantations possibly due to factors such as management practices or impacts of previous fire history. The relationship with drainage density was strongest in 2013, an ENSO-neutral year, and weakest in the strong El Niño of 2015. Our findings support the critical need for fire management in drained tropical peat areas. Peat fire management planning and peatland restoration should be tailored to the differing responses of fire to climate variability, drainage density and LC types.

ABSTRACT Some bird species are known to be attracted to fire. This attraction is driven by foraging opportunities (e.g. prey, carcasses, and seeds) and the exploitation of thermal updraughts generated by fires. However, evidence remains largely anecdotal. We examined avian interactions with active fires in the Pantanal wetlands, Brazil, assessing how attraction and behaviour vary with fire intensity. We observed six prescribed burns in the Pantanal across 1 ha plots, recording the arrival time and behaviour of birds. We recorded 237 birds (61 species), of which 82 individuals of 14 species arrived during the fire. The Savanna Hawk (Heterospizias meridionalis) was the most numerous (n = 28, representing 34.2% of all birds observed post-ignition), followed by the Black Vulture (Coragyps atratus N = 19, 23.2%), and Crested Caracara (Caracara plancus, N = 13, 15.9%). Most birds (56,1%, n = 46) arrived during high-intensity flames, 15.9% (n = 13) during low-intensity flames, and 28% (n = 23) post-extinguishment. Fire triggered a trophic shift: insectivores, granivores, and omnivores declined, while scavengers (3.9% to 36.5%) and vertebrate predators (1.9% to 32.9%) increased. Species exhibited distinct fire-related behaviours: vultures (C. atratus, Cathartes aura) soared on thermal updraughts during active flames; insectivores (e.g. Pitangus sulphuratus) exploited smoke-disoriented prey; and raptors (H. meridionalis, C. plancus) hunted animals exposed to flames or vegetation loss. Our observational findings highlight the role of fire in shaping avian short-term foraging strategies and community dynamics, emphasising the need to integrate pyric-carnivory concepts into fire management.

Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) was a field campaign aimed at better understanding the impact of wildfires and agricultural fires on air quality and climate. The FIREX-AQ campaign took place in August 2019 and involved two aircraft and multiple coordinated satellite observations. This study applied and evaluated a self-supervised machine learning (ML) method for the active fire and smoke plume identification and tracking in the satellite and sub-orbital remote sensing datasets collected during the campaign. Our unique methodology combines remote sensing observations with different spatial and spectral resolutions. With as much as a 10% increase in agreement between our produced masks and high-certainty hand-labeled pixels, relative to evaluated operational products, the demonstrated approach successfully differentiates active fire pixels and smoke plumes from background imagery. This enables the generation of a per-instrument smoke and active fire mask product, as well as smoke and fire masks created from the fusion of selected data from independent instruments. This ML approach has the potential to enhance operational active wildfire monitoring systems and improve decision-making in air quality management through fast smoke plume identification and tracking and could improve climate impact studies through fusion data from independent instruments.

A spread day is defined as a day in which fires grow by a substantial amount of area, usually during high or extreme fire weather conditions. Accurately identifying a spread day under various environmental conditions could help both our understanding of fire regimes and with forecasting and managing fires on the ground. Although spread days could occur within a spectrum of fire weather conditions, a threshold is important to fire management and fire research. This study explores the relationships between spread days and fire activity in the forested area of Canada by spatially and temporally matching daily fire growth to interpolated daily gridded fire weather between 2001 and 2021. Using accumulative area burned density functions, we identified the fire weather conditions for spread days by Canadian Ecozones both annually and seasonally. Using these identifiers as thresholds, we estimated how extreme fire weather needs to be for a spread day to occur, and the proportions of potential spread days (PSDs) that would most likely be realized in real fire spread at various Canadian Ecozones. Our results showed that the median-level fire-conducive weather conditions are sufficient to support active fire growth, and on average, about 22–30% of such days may be realized in real fire spread at various Canadian Ecozones.This article is part of the theme issue ‘Novel fire regimes under climate changes and human influences: impacts, ecosystem responses and feedbacks’.

Abstract Introduction Almost a quarter of people receiving care for major burn injuries in urban burn centers across North America are unhoused at the time of injury. Prevention of these injuries, especially for populations living unhoused, requires the delivery of passive and active fire and cold weather projections along with education. For populations with low health literacy, it is extremely important that prevention education is written in plain language, contextualized, and consumer tested to increase a material’s acceptability, understandability, and actionability. We aimed to consumer test newly developed fire, burn, and cold injury prevention education materials with people experiencing homelessness (PEH) and identify PEH preferred prevention strategies to address and mitigate fire and cold weather risks and hazards. Methods 40 cognitive interviews with PEH were conducted. The Patient Education Materials Assessment Tool (PEMAT-P) and the Model System Knowledge Translation Center (MSKTC) consumer testing toolkit were used to evaluate the understandability and actionability of the six newly developed education materials. Transcripts were analyzed using a harm reduction lens and a combination of deductive and inductive thematic coding. Results Participants provided feedback on the understandability and actionability of newly developed educational materials. Feedback themes were categorized into the domains of 1) engage and relate – being relatable to the diverse experiences and literacy levels of PEH, 2) reduce harm – focus on mitigating rather than eliminating hazards, 3) use context-specific design – reflect the lived experiences of PEH and their environments in the materials, 4) empower – incorporate prevention guidance, tips and tricks from PEH in addition to conventional prevention strategies, and 5) prioritize both equipment and education – combine education with dissemination of safety equipment (e.g., fire blankets, cookstove adaptations, clothing). Conclusions The process of consumer testing with PEH generated acceptable and actionable prevention education materials and identified specific fire, burn and cold injury prevention and mitigation strategies for people living unhoused. Additionally, consumer testing increases collective support and trust from PEH and the organizations that work with them. Applicability of Research to Practice By developing and implementing targeted burn and cold injury prevention education in conjunction with PEH preferred prevention and mitigation strategies, public health initiatives will be strengthened and may be more effective. Funding for the Study This project was funded by a Population Health Initiative Grant and the David and Nancy Auth-Washington Research Foundation Endowed Chair for Restorative Burn Surgery.

Abstract Vegetation fires have become increasingly recognized as a potential entrainment mechanism for mineral dust. However, the global importance of this emission pathway remains largely unknown. Based on previous LES investigations, we developed a parameterization that relates the dust emission potential of wildfires to observational data of the fire radiative power and further soil‐surface conditions. It was implemented into the aerosol‐climate model ICON‐HAM and simulations with and without the new emission pathway were conducted for the 10‐year period 2004–2013. Fire‐dust emissions can account for around 230 (190–255) Tg yr−1, which represents around 18 (15–21) % of the total global dust emissions. These additional emissions originate largely from regions that are typically not known as significant sources of mineral dust. Locally, wildfires can enhance the presence of atmospheric dust particles and on the Southern hemisphere might even surpass other forms of dust emission. Highly dust active fire regions are identified in areas where burning grasslands create suitable emission conditions together with emissive soil types despite rather weak fires, for example, in Eastern Europe or the Central US. Fire‐dust emissions are subject to a strong seasonal cycle, mainly driven by the fire activity, following the hemispheric warm and dry seasons. Multi‐year comparisons with (dust) AOD observations revealed improvements due to the additional fire‐dust emissions, particularly in the most fire‐active regions on the Southern hemisphere. Nevertheless, further research and improvements of the parameterization are required to better classify the source areas and their variation with the changing climate and land use conditions.

Regional drinking water companies are regionally owned business units engaged in the distribution of clean water for public needs. One of the potential hazards and risks that may occur in office buildings is fire. Operational disruptions caused by fires can have widespread impacts, including disturbances in the distribution of clean water to customers. Therefore, this study aims to evaluate the implementation of the active fire protection system at the Head Office of Perumda Air Minum Surya Sembada, Surabaya, as an effort toward fire prevention and mitigation. This research employs a qualitative method with a descriptive observational approach. The results indicate that the compliance level of fire detectors, based on SNI 03-3985-2000, is 83%, which is classified as good. The compliance level of fire alarms, based on SNI 03-3985-2000, is also 83%, which is classified as good. The compliance level of sprinkler systems, based on SNI 03-3989-2000, is 70%, which is classified as fairly good. The compliance level of fire extinguishers, based on the Ministry of Labour and Transmigration Regulation No. Per. 04/MEN/1980, is 75%, which is classified as fairly good. The compliance level of hydrants, based on SNI 03-1745-2000, is 89%, which is classified as good. Thus, the overall compliance level of the active fire protection system implementation at the Head Office of Perumda Air Minum Surya Sembada, Surabaya, is 80%, which falls into the "fairly good" category.

About 95 % of wildfires are caused by human activities. The burning of grasslands as a method of sweeping for livestock and agricultural exploitation has been implemented for over two centuries on the American continent. Every winter, fires are used to promote the regrowth of forage species in the Paraná River Delta. Unusual weather conditions and climate change have intensified the global impact of wildfires. In 2020, the accumulation and spread of unprecedented wildfire emissions affected the inhabitants of the Rosario Metropolitan Area (AMR), Argentina. This work analyzed meteorological conditions, the number of active fires detected by the VIIRS satellite instrument, and the concentration of fine particulate matter (PM2.5) measured in the AMR. Anomalies of precipitation, relative humidity, and temperature recorded in situ between June and August in the period 2010- 2020 were calculated. The results show that for the year 2020, ambient humidity and temperature had an average decrease of 10 % and 3 %, respectively, while accumulated precipitation had a reduction of about 70 % with respect to previous years. The clustering model showed that the highest median of Number of active fires (NI) coincides with the lowest accumulated precipitation and low relative humidity, as well as prevailing winds from the northwest. Wind analysis reveals that currents from the northwest direction promoted larger surface fire impacts in the Paraná River Delta, and northeast winds increased PM2.5 levels in the AMR. These findings underline the importance of considering meteorological conditions in assessing environmental risks and in formulating mitigation strategies against air pollution and forest fires.

Real-Time Active Fire Detection in the Pantanal Biome, Brazil, Using Convolutional Neural Networks