Aqueous film-forming foams (AFFFs) are widely used fire suppression products that have been identified as a direct source of environmental per- and polyfluoroalkyl substances (PFAS). Per- and polyfluoroalkyl substance exposure has demonstrated chronic and sub-lethal effects on biota. Ongoing efforts aim to reduce and, ideally, eliminate PFAS use in AFFF products. However, there is little known about the potential toxic effects of the new PFAS-free AFFFs, specifically on benthic organisms. The objective of this study is to quantify the effects of seven AFFFs on growth in the hard clam, Mercenaria mercenaria, over a 21-day exposure period with juvenile animals. Additionally, AFFF effects are reported from algal toxicity assays and a feeding study. Five of the PFAS-free AFFFs negatively impacted growth over the exposure period while one PFAS-free AFFF and the reference PFAS-containing AFFF had no observable effect. Median effect concentrations (EC50) for shell growth ranged from 5.81 mg/L to >100 mg/L. Clam dry and wet weights also decreased with increasing exposure concentration (p <0.05). Algal growth was impacted over a 96-hr exposure. Impacts were observed to final standing biomass and overall growth rates at the highest exposure concentrations. However, complete lethality was only observed for one PFAS-free product, suggesting lack of food availability was likely not the primary driver of growth inhibition for all products. Net particle clearance rates in AFFF exposed clams were not found to be impacted, suggesting there was no obvious AFFF influence on organismal feeding ability. The presented results identify chronic effects of exposure to these AFFFs in this economically and ecologically important bivalve species and is expected to inform decisions regarding PFAS replacement AFFF products.

Fire in China, driven by both natural and anthropogenic factors, significantly influences ecological stability. This study provides a comprehensive spatiotemporal analysis of active fires across China from 2003 to 2024 using MODIS Collection 6.1 active fire and land cover products. Our results reveal a significant national decline in fire counts since 2016, accompanied by with a marked geographical shift in hotspots from East China to Northeast China. It clarifies that croplands and savannas are the main fire-prone land covers, yet they have also experienced the most substantial decline in fire counts. East China (46.8%) and Central China (27.1%) were the largest contributors to the reduction in cropland fire counts. Temporal displacement toward nighttime straw burning was observed in East China. The decline in average fire radiative power (FRP) of daytime agricultural fires indicates that straw burning bans effectively reduced both the frequency and intensity of fires. Persistent savanna and forest fires are highly clustered in Southern China, while new emerging grassland fires are concentrated in Western China. Persistent cropland fires overlap with emerging zones in Northeast and Central China. Our study can assist in optimizing targeted fire policies and supporting better fire risk management.

Wildfire-induced disturbances to soil and vegetation can significantly impact streamflows for years, depending upon the degree of burn severity. Accurately predicting the effects of wildfire on streamflow at the watershed scale is essential for effective water budget management. This study presents a novel approach to generating a burn severity map on a small scale by integrating unmanned aerial vehicle (UAV)-based thermal imagery with Landsat-derived Differenced Normalized Burn Ratio (dNBR) and upscaling burned severity to the entire burned area. The approach was applied to the Thompson Ridge Fire perimeter, and the upscaled UAV-Landsat-based burn severity map achieved an overall accuracy of ~73% and a kappa coefficient of ~0.62 when compared with the Burned Area Emergency Response’s (BAER) fire product as a reference map, indicating moderate accuracy. We then tested the transferability of burn severity information to a Beaver River watershed by applying Random Forest models. Predictors included topography, spectral bands, vegetation indices, fuel, land cover, fire information, and soil properties. We calibrated and validated the Distributed Hydrology Soil Vegetation Model (DHSVM) against observed streamflow and Snow Water Equivalent (SWE) data within the Beaver River watershed and measured model performance using Nash–Sutcliffe Efficiency (NSE), Kling–Gupta Efficiency (KGE), and Percent Bias (PBIAS) metrics. We adjusted soil (maximum infiltration rate) and vegetation (fractional vegetation cover, snow interception efficiency, and leaf area index) parameters for the post-fire model setup and simulated streamflow for the post-fire years without vegetation regrowth. Streamflow simulations using the upscaled and transferred UAV-Landsat burn severity map and the Burned Area Emergency Response’s (BAER) fire product produced similar post-fire hydrologic responses, with annual average flows increasing under both approaches and the UAV-Landsat-based simulation yielding slightly lower values, by less than 6% compared to the BAER-based simulation. Our results demonstrate that the UAV-satellite integration method offers a cost- and time-effective method for generating a burn severity map, and when combined with the transferability method and hydrologic modeling, it provides a practical framework for predicting post-fire streamflow in both burned and unburned watersheds.

Abstract Background Subtropical pine forests dominated by Pinus roxburghii in northern Pakistan are increasingly vulnerable to forest fires, posing serious ecological and management challenges. This study (i) identifies the primary environmental and anthropogenic drivers of fire risk, (ii) evaluated the performance of four machine learning models Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM), and eXtreme Gradient Boosting (XGBoost) for fire susceptibility prediction, and (iii) develops a spatially explicit vulnerability map for the Malakand region using 2001–2023 fire occurrence data . Methods Spatial modeling was conducted using MODIS fire products (FIRMS and MCD64A1), along with topographic, climatic, vegetation, and human activity variables. Predictor importance and inter-variable relationships were analyzed prior to model training and evaluation. Results NDVI, skin temperature, and population density emerged as key predictors. Among the models tested, RF and XGBoost outperformed others, with RF achieving 86.2% accuracy and AUC 95.4, and XGBoost showing 87.2% accuracy and AUC 95.2. Multicollinearity analysis confirmed variable independence (Tolerance &gt; 0.1; VIF &lt; 10). Conclusion The resulting fire vulnerability map delineated distinct spatial patterns, identifying 6.88% of the study area as highly susceptible to fire. These findings provide actionable insights into targeted fire prevention and sustainable forest management in subtropical Himalayan ecosystems.

Abstract. Biomass burning (BB) aerosol significantly affects climate by altering the radiation budget and atmospheric chemistry. Accurate source estimation is vital for climate modeling, yet global observations remain scarce. This study introduces a novel framework for assessing the contribution of transported BB aerosol to smoke-associated aerosol optical depth (BB AOD) at selected locations. The approach integrates satellite fire data (Moderate Resolution Imaging Spectroradiometer Active Fire Product) with air parcel trajectory models (HYSPLIT), aerosol transport models (NAAPS), BB emissions (FLAMBE), and plume rise (CAMS GFAS). Tested in Warsaw (Poland, Central Europe) over 2006–2022, the methodology reveals a prominent influence of long-range BB aerosol transport from North America. Analysis indicates that USA (without Alaska) (37.3 %±3.4 %), Canada (25.4 %±6.7 %) and the Alaska (2.6 %±2.1 %) together contribute approximately 65 % of BB AOD during the BB season in the Northern Hemisphere, surpassing nearer European sources. Among European regions, Eastern Europe accounts for 16.6 %±5.3 % of BB AOD, followed by the Iberian Peninsula (10.6 %±1.5 %) and Southern Europe (7.5 %±2.1 %). Incorporating vertical plume dynamics is crucial: a planetary boundary layer plume-top threshold underestimates Canadian contribution while overestimating European sources, whereas removing altitude constraints overestimates Canadian influence. These findings underscore the importance of transatlantic transport, plume-rise processes, and vertical aerosol distribution in regional climatology. The presented framework for assessing BB AOD contributions is universal and can be applied at any location. Future work should incorporate the specific aerosol types emitted during BB events and their aging processes.

ABSTRACT Forest fires play a critical role in determining the ecological and vegetation dynamics of Central India’s deciduous forests. This study evaluates the impact of forest fire on plant diversity in a forest of Central India. Forest fire frequency was assessed using multi-temporal Landsat imagery (Landsat 5, 7, and 8) and validated with MODIS active fire products (MOD14/MYD14). The Phytosociological data were collected through field surveys in the Hoshangabad Forest Division, Madhya Pradesh, India. The results indicate that low fire frequency zones (LFZ) exhibit the highest species diversity and evenness, whereas high fire frequency zones (HFZ) show the lowest, suggesting fire plays a significant role in influencing forest composition. The moderate fire frequency zone (MFZ) shows an intermediate diversity pattern, supporting the intermediate disturbance hypothesis. Frequent fires in HFZ reduce species richness by favoring fire-resistant species such as Diospyros melanoxylon, which dominates across all fire zones, with the highest Importance Value Index (IVI) in HFZ (62.18). Tree density trends reveal that while HFZ has a slightly higher average density than non-fire zones, the reduced diversity suggests a shift toward homogeneous structure. The findings highlight the need for adaptive fire management strategies to balance biodiversity conservation in fire-prone landscapes. Focusing on the tropical dry deciduous forests of Central India, this study underscores the importance of region-specific and forest type-specific assessments, which are essential for developing fire management and biodiversity conservation strategies. This regional perspective not only adds significant value to India’s forest management discourse but also provides critical insights for forest policy and ecological restoration in dry deciduous landscapes, where recurrent fires strongly influence species diversity, forest structure, and regeneration patterns.

Forest fires significantly impact the global climate through carbon emissions, yet the multi-scale coupling mechanisms among meteorological factors, fire behavior, and emissions remain uncertain. Focusing on tropical Asia, this study integrated satellite-based fire behavior products, meteorological datasets, and emission factors, and employed machine learning together with structural equation modeling (SEM) to explore the mediating role of fire behavior in the meteorological regulation of carbon emissions. The results revealed significant differences among vegetation types in both carbon emission intensity and sensitivity to meteorological drivers. For example, average gas emissions (GEs) and particle emissions (PEs) in mixed forests (MF, 323.68 g/m2/year for GE and 0.73 g/m2/year for PE) were approximately 172% and 151% higher, respectively, than those in evergreen broadleaf forests (EBF, 118.92 g/m2/year for GE and 0.29 g/m2/year for PE), which exhibited the lowest emission intensity. Mixed forests and deciduous broadleaf forests exhibited stronger meteorological regulation effects, whereas evergreen broadleaf forests were comparatively stable. Temperature and vapor pressure deficit emerged as the core drivers of fire behavior and carbon emissions, exerting indirect control through fire behavior. Overall, the findings highlight fire behavior as a critical link between meteorological conditions and carbon emissions, with ecosystem-specific differences determining the responsiveness of carbon emissions to meteorological drivers. These insights provide theoretical support for improving the accuracy of wildfire emission simulations in climate models and for developing vegetation-specific fire management and climate adaptation strategies.

Development and analysis of a forest fire emission inventory in China considering daily variation patterns.

Liquefied natural gas (LNG) export facilities are booming worldwide to supply gas for the growing energy demand. Flaring, the controlled burning of natural gas, occurs at these facilities during operations ranging from start-up to ongoing maintenance and under emergency situations. Although flaring can be a significant air pollutant and greenhouse gas emission source, little information exists on the frequency, duration, and volume of gas flared by LNG export facilities. This study leveraged ten years of data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Night Fire (VNF) product associated with 48 existing LNG export facilities globally to develop probabilities of flaring at different life-cycle stages. We found a significantly higher volume of gas flared in the first two years of a facility's operation (i.e., on average 1.9 (1.0-3.2) billion cubic meters (bcm) per capacity vs 0.62 (0.43-0.92) bcm during subsequent years). During regular operations, the annual volume of gas flared was correlated with the facility's production capacity, and flaring varied greatly among facilities (148 (137-159) flaring days/year on average and 0.73 (0.64-0.85) bcm/capacity). Unfortunately, most environmental assessments overlook the start-up phase and fail to consider worst-case scenarios. As flaring is a source of air pollution, its potential health impacts on local populations may be underestimated in these assessments.

Abstract The purpose of this work is to study the kinetic features of the formation of phosphate agglomerates from low-grade phosphorites in the presence of phosphate–siliceous shales (PSSs), coke, and oil sludge. The selection of the Yerofeyev–Kolmogorov equation characterizing heterogeneous processes is justified by a comparative analysis of the Aravi equation used for the crystallization processes. The PSS/coke–oil sludge system has been studied in the temperature range of 1,073–1,373 K in the air environment, typical for agglomeration firing. Thermogravimetric analysis, X-ray fluorescence analysis, scanning electron microscopy, and IR spectrometry were used to study the features of oil sludge and the physicochemical characteristics of the phase composition and mineralogical structure of the firing products. The effect of the modulus of acidity and temperature on the strength parameters of phosphate agglomerate was studied for charges of 0.7–0.83, providing mechanical strength of 3.3–3.4 MPa at temperatures of 1,313–1,318 K of the onset of deformation. The calculation results of the apparent energy corresponding to 4.15–22.99 kJ·mol−1 indicate complex diffusion–reaction characteristics of the agglomeration process in the presence of PSS and oil sludge.

ABSTRACT A detailed, spatially explicit fire inventory is essential for improving our understanding of biomass burning and for supporting the formulation of targeted fire mitigation policies. However, such fire inventories remain limited, especially in tropical regions. Existing active fire (AF) products derived from low-resolution sensors (e.g. MODIS and VIIRS) generally have high omission errors (OE), especially when detecting small and relatively colder temperatures fires. While moderate-resolution sensors offer unprecedented opportunities for detecting small and subtle fires, they face the dilemma of high commission errors (CE). To address this problem, we propose an object-oriented method to effectively detect AFs from Sentinel-2 MSI images, which focuses on suppressing the interference of various CEs through object-level inter-spectral criteria cloud filtering, seamline exclusion based on granule footprints, and false positive refinement based on random forest classification model. Using more than 55,000 Sentinel-2 MSI images acquired during 2016–2021, we have compiled a novel 20 m fire inventory covering forests and peatlands in Borneo. Initial assessment of the fire inventory suggests a CE of approximately 7.2% and an OE of 11.5%. Analysis of the Borneo fire inventory revealed the following: (i) A significant concentration of AFs was observed in Kalimantan, with Central Kalimantan accounting for approximately 55.9% of all detected peatland fires in Borneo, and West Kalimantan contributing 33.7% of forest fires. (ii) Peatland fires dominated widespread fires in Borneo in 2019, with 1.4 to 2.6 times the size and 3.1 to 16 times the number compared to other years in 2016–2021. (iii) The MSI AF detections show slight differences in spatiotemporal patterns compared to MODIS and VIIRS AF products, which is attributed to variations in sensitivity to small fires. Our study clarifies the spatial dynamic distribution of AFs in Borneo, providing fundamental support for local fire monitoring, fire regime, and carbon emission research.

Worldwide escalation in wildfire incidences calls for continuous monitoring and early detection of fires to strengthen regional fire combating strategies. Inter-annual variability in fire count and Fire Radiative Power (FRP), spatial spread of fires in the most active seasons during 2012‒2023 on Indian landmass are reported. Fire data is extracted from 375 m active fire detection product of Visible Infrared Imaging Radiometer Suite (VIIRS) hosted by Suomi National Polar-orbiting Partnership. In every fire-year (March–February), constructed from the month of remarkable escalation in fires, fires were most populated in March or April in summer and November in winter. The yearly sum of fire spots ranged from 492,282 (2013) to 731,154 (2021). Inter-annual fire count trend grew at a rate of 10,794 per year, excluding COVID years of 2020 and 2021. Many cities with > 0.1 million population are located within or adjacent to the fire hot spots (20 km × 20 km grids), implying possibility of some impacts of seasonal fires both within and outside Wildfire Urban Interphases (WUIs). The study highlights the urgency of streamlining interventions to minimize wildfire incidences in order to protect forests, habitats, biodiversity, ecosystem services, human lives and property and minimize carbon loss, air pollution, perturbations in regional meteorology and radiative forcing.

Abstract Many fire weather index products have been developed to assist land managers, weather forecasters, and firefighters with anticipating weather conditions that may impact existing or potential new wildland fires in coming days. Most of these indices are designed to provide a single value for an entire 24-h period. Extreme wildfire activity in the western US in recent years, including the impact of mesoscale and microscale phenomena such as thunderstorm gust frontal passages, radiative shading by dense smoke plumes, and pyrocumulonimbus development and collapse, as well as the advent of operational convection-allowing model forecasts, has highlighted the need for a more frequently updated index. In this study, we present a proof of concept for an hourly fire weather index developed specifically for application within a rapidly-updating convection-allowing model. The index, termed the Hourly Wildfire Potential (HWP), is developed based on observations of fire radiative power (FRP) from polar-orbiting satellites during large western US wildfires in 2018 and 2020, and is evaluated against a merged dataset of FRP from polar-orbiting and geostationary satellites. The index is computed based on meteorological output from the NOAA operational High-Resolution Rapid Refresh (HRRR) model. The HWP index exhibits an improved representation of hourly FRP compared to a climatological approach, and also shows promise for distinguishing between conditions associated with flaming and smoldering combustion. This work paves the way for improved prediction of wildfire smoke emissions in the coming hours and days.

Fires disrupt ecosystems, release carbon, and reduce carbon uptake, which increases atmospheric CO2 concentration, warms the atmosphere, and fosters more frequent and intense fires. Quantifying postfire recovery is crucial for understanding the adaptability and resilience of ecosystems to fire disturbances. Observations from satellite-derived active fire (~1-km) and Gross Primary Productivity (GPP) products reveal that Australia experiences extensive fires annually, reducing vegetation productivity. Here we analyze the post-fire GPP recovery trajectories of 1.7 × 106 fire-affected pixels (or 1.5 × 106 km2) in Australia between 2011 and 2019, of which 1.3 × 106 pixels (1.2 × 106 km2) experienced a single fire (single-fire pixels), and 0.4 × 106 pixels (0.3 × 106 km2) experienced two or more fires (multiple-fire pixels). We found that Australia's postfire GPP recovery was strong and rapid. 88% of single-fire pixels recovered to 135% of the prefire level in an average of 2.3 years, whereas 86% of multiple-fire pixels recovered to 115% of the prefire level in an average of 1.2 years. NonForest ecosystems (e.g., grasslands, shrublands, and savannas) exhibited a higher postfire recovery magnitude (138% for single-fire pixels and 115% for multiple-fire pixels) compared to Forest (110% for single-fire pixels and 108% for multiple-fire pixels). This rapid and robust postfire GPP recovery is significantly influenced by postfire precipitation, fire (i.e., fire frequency, intensity) and fire severity (damage, impacts; a metric of resistance of terrestrial ecosystems to fire). Specifically, higher fire severity and higher postfire precipitation have a positive impact on postfire recovery, whereas increased fire frequency has a negative impact. Furthermore, fire dynamics have a smaller role in the long-term interannual continental GPP changes than climate or land-use changes, as strong and rapid GPP recovery offsets the short-term fire-induced GPP losses.

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 &lt; 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.

This research aims to analyze the implementation of Fire Product marketing management strategies in optimizing supply chain distribution at PT. Amman Mineral Nusa Tenggara Barat. An exploratory case study with a qualitative approach was conducted through semi-structured interviews, participatory observation, and documentation studies involving 20 key informants from various departments. The results show that PT. Amman Mineral implements multi-dimensional marketing strategies with a value-based marketing approach and the "Fire Safety Champion" program that significantly improves distribution efficiency. Five main factors affecting distribution effectiveness include geographical conditions, inter-departmental coordination, technology and information systems, demand fluctuations, and supplier availability and responsiveness. The implementation of product value-based marketing strategies positively correlates with distribution efficiency, marked by a 43% decrease in emergency requests and a 23% reduction in excess inventory without sacrificing availability in critical areas. An integrative model combining demand-based marketing, just-in-time inventory management, and digital monitoring systems is proposed to optimize Fire Product distribution. This research provides theoretical contributions to the development of an integrative marketing management and supply chain model for products with high strategic significance, as well as practical implications for improving distribution efficiency in industries with complex operational characteristics.

Biomass burning (BB) results from complex interactions between ecosystems, humans, and climate, releasing large amounts of gases and particles. Accurate BB emission estimates are essential for air quality, climate studies, and impact assessments. Various existing bottom-up BB emission inventories show significant discrepancies, varying by factors of 2 to 4 due to uncertainties in burned areas (BAs), emission factors (EFs), and vegetation parameters such as biomass density (BD) and burning efficiency (BE). Here, we investigate the role of vegetation parameters in these discrepancies in Africa. Two BB emission inventories, AMMABB-like (African Monsoon Multidisciplinary Analysis Biomass Burning) and GFED-like (Global Fire Emission Database) were developed for Organic Carbon (OC) and Black Carbon (BC). Both inventories used identical fire products, vegetation maps, and EF but different BD and BE values. Results highlight substantial differences in BD and BE, with relative gaps ranging from 44% to 85.12%, explaining the observed differences between BB emission inventories. Key vegetation classes responsible for BB emissions were identified. Discrepancies of 2.4 to 3.9 times were observed between AMMABB-like and GFED4-like, with higher values in the Southern Hemisphere. Better BD and BE estimates with regional distinctions for both hemispheres would improve BB emission accuracy in Africa.

Phase transformations in the zeolite-containing rock – calcite system during the synthesis of wollastonite in a temperature range of 800 to 1200 °C are studied. The components were mixed in a CaO/SiO2 ratio of 0.7, and then, in order to increase the contact area of the phases, grinding was performed in a Fritsch Pulverisette 5/2 planetary mill for 5 min at 200 rpm. Solid-phase synthesis was carried out in SNOL 1100/7.2 and Nabertherm LH 120/13 muffle furnaces at temperatures ranging from 800 to 1200 °C with intervals of 50 °C and an isothermal holding time of 1 to 4 h. The phase composition of the component firing products is quantitatively evaluated by quantitative X-ray analysis. The process of wollastonite formation proves to begin at temperatures ranging between 800 and 900 °C. A smooth growth of calcium metasilicate content continues up to 1100 °C, and wollastonite becomes the main product at this temperature. The maximum yield of wollastonite (81%) is reached at 1175 °C isothermal holding for 3 hours. The temperature of phase transition from β- to α-wollastonite has been experimentally found to be 1190 °C.

Background. The combat operations taking place in Ukraine present many questions to anesthesiologists regarding the medical assistance to the injured with blast injury. Explosive trauma is combined in pathogenesis and localization. It occurs as a result of the combined damaging effect on the human body of shock wave, gas jets, fire, toxic explosion and combustion pro-ducts, ammunition casing fragments, secondary projectiles. This type of trauma is often combined with damage to 2–4 anatomical areas and sometimes more. Moreover, the hospital care is mostly provided in civilian hospitals located next to the combat operation zone. Aim: reduction of mortality by choosing the anesthetic technology and intraoperative intensive care in victims of explosive trauma, depending on its severity and their condition. Materials and methods. During January-December 2023, 1059 (1040 men, 19 women) victims of explosive injuries who were examined according to the GKO scale (a standardized system for assessing the severity of injuries and the patient condition) were admitted to the operating rooms of the Zaporizhzhia Regional Clinical Hospital. 1071 surgeries were performed: in 1 anatomical area — 593 operations; in 2 — 292; in 3 — 118; in 4 — 49; in 5 — 19. When assessing the patient condition on the GKO scale, 106 patients had up to 10 points; 201 had 11–19 points; 402 had 20–29 points; 350 had more than 30 points. Results. Before the operation, there was normotension and moderate tachycardia. However, 202 victims had a systolic blood pressure of less than 90 mm Hg, which required the use of sympathomimetics and infusion therapy with crystalloids and colloids. Sympathomimetics and their combinations continued to be used during the surgery in 202 patients. Norepinephrine was used in 148 patients in a dose of 0.1–0.4 μg/kg/min, dopamine — in 39, adrenaline — in 4, mezaton — in 11 victims in bolus doses of 20–100 μg. The indicators of systolic, diastolic, pulse, mean arterial pressure and heart rate at the completion operative stage did not differ significantly from the baseline. Before the surgery, the victims had subcompensated metabolic and respiratory acidosis, increased lactate concentration (3.6 ± 0.1 mmol/l). During the operation, the metabolic acidosis phenomena increased, respiratory acidosis and an increase in pCO2 in the blood persisted. The blood lactate concentration increased significantly, on average up to 4.0 ± 0.1 mmol/l (р &lt; 0.001). Conclusions. Assessment of the victim severity according to the GKO scale allows choosing the anesthesia technology taking into account the hemodynamic effect of anesthetics. During treatment of blast injury victims, it was possible to maintain normotension thanks to infusion-transfusion therapy and vasopressor support. At the end of the operation, mixed decompensated acidosis and increased lactate required further treatment in the intensive care unit.

Abstract The fire season of 2020 in Siberia set a precedent for extreme wildfires in the Arctic tundra. Recent estimates indicated that the 2020 fires contributed 66% of the region's burned area over the last two decades. These fires burned in the carbon‐rich permafrost landscape, releasing vast amounts of carbon, and changing land surface processes by burning vegetation and organic soils. However, little is known about the mosaics of burned and unburned patches formed by tundra fires and the underlying processes that generate them. In this study, we investigated six fire scars in the northeastern Siberian tundra using high‐resolution PlanetScope imagery (3 m) to map burned fraction within the scars. We then used Bayesian mixed models to identify which biotic and abiotic predictors influenced the burned fraction. We observed high spatial variation in burned fraction across all tundra landforms common to the region. Current medium‐resolution fire products could not capture this heterogeneity, thereby underestimating the burned area of fire scars by a factor of 1.2–4.7. The heterogeneity of the burn mosaic indicates a mix of burned and unburned patches, with median unburned patch sizes ranging between 189 and 288 m2 per fire scar. Pre‐fire land surface temperature, vegetation heterogeneity and topography predicted burned fraction in our analysis, matching factors previously shown to influence large‐scale fire occurrence in the Arctic. Future studies need to consider the fine‐scale heterogeneity within tundra landscapes to improve our understanding and predictions of fire spread, carbon emissions, post‐fire recovery and ecosystem functioning.