Search Results (2,117)

Underestimation of PM_2.5 emissions from the agricultural sector persists as a major difficulty for air quality studies, partly because of underutilization of high-resolution observation platforms for constructing a global emissions inventory. Coarse-resolution products used for such purposes often miss fine-scale burnt areas created by stubble-burning practices, which are primary sources of agricultural PM_2.5 emissions. For this study, we used the high-resolution Sentinel-2 observations to examine the spatiotemporal variability of burnt areas in Punjab, a major hotspot of agricultural burning in India, during the post-monsoon fire season (October–December) in 2022–2024. The results highlight the Sentinel-2 capability of detecting more than 34,000 km² of burnt areas (approx. 68% of Punjab’s total area) as opposed to the less than 7000 km² (approx. 12% of Punjab’s total area) detected by MODIS. The study also reveals, in unprecedented detail, multi-annual spatial and temporal shifting of burning events from northern to central and southern Punjab. This detection discrepancy has led to marked disparities in estimated monthly emissions, with approximately 217.3 million tons of PM_2.5 emitted in October 2022 compared to 8.7 million tons found by EDGAR v.8.1. This underscores higher-resolution observation systems intended to support construction of a global PM_2.5 emissions inventory. Full article

Wildfires pose severe threats to ecosystems and human settlements, making early detection and rapid response critical for minimizing damage. The adage—“You fight fire in the first second with a spoon of water, in the first minute with a bucket, and in the first hour with a truckload”—illustrates the importance of early intervention. Over recent decades, significant research efforts have been directed toward developing efficient systems capable of identifying wildfires in their initial stages, especially in remote forests and wildland–urban interfaces (WUIs). This review paper introduces the Special Issue of Fire and is dedicated to advanced approaches to wildfire detection, monitoring, and surveillance. It summarizes state-of-the-art technologies for smoke and flame detection, with a particular focus on their integration into broader wildfire management systems. Emphasis is placed on distinguishing wildfire monitoring (the passive collection of data using various sensors) from surveillance (active data analysis and action based on visual information). The paper is structured as follows: a historical and theoretical overview; a discussion of detection validation and available datasets; a review of current detection methods; integration with ICT tools and GIS systems; the identification of system gaps; and future directions and emerging technologies. Full article

In many hardwood forests, resprouting is a common response to disturbance and basal resprouts may represent a substantial component of the forest understory, especially post-wildfire. Despite this, resprouts are often overlooked in biomass assessments and drivers of resprouting responses in certain species are still unknown. These knowledge gaps are problematic as the contribution of resprouts to understory fuel loads are needed for wildfire risk modeling and effective forest stewardship. Here, we validated the handheld mobile laser scanning (HMLS) of basal resprout volume and field measurements of stem count and clump height as methods to estimate the mass of California Bay Laurel (Umbellularia californica) basal resprouts at Pepperwood and Saddle Mountain Preserves, Sonoma County, California. In addition, we examined the role of tree size and wildfire severity in predicting post-wildfire resprouting response. Both field measurements (clump height and stem count) and remote sensing (HMLS-derived volume) effectively estimated dry mass (total, leaf and wood) of U. californica resprouts, but underestimated dry mass for a large resprout. Tree size was a significant factor determining post-wildfire resprouting response at Pepperwood Preserve, while wildfire severity significantly predicted post-wildfire resprout size at Saddle Mountain. These site differences in post-wildfire basal resprouting predictors may be related to the interactions between fire severity, tree size, tree crown topkill, and carbohydrate mobilization and point to the need for additional demographic and physiological research. Monitoring post-wildfire changes in U. californica will deepen our understanding of resprouting dynamics and help provide insights for effective forest stewardship and wildfire risk assessment in fire-prone northern California forests. Full article

Petroleum hydrocarbon pollution is a serious environmental and human health problem. In recent decades, the impact of this substance has been profound and persistent, affecting the balance of aquatic and terrestrial ecosystems and leading to significant physical and psychosocial effects among the population. Natural sources (crude oil, natural gas, forest fires, and volcanic eruptions) and anthropogenic (road traffic, smoking, pesticide use, oil drilling, underground water leaks, improper oil spills, industrial and mining waste water washing, etc.), the molar weight of the hydrocarbon, and the physicochemical properties are important factors in determining the degree of pollution. The effects of pollution on the environment consist of altering the fundamental structures for sustaining life (infertile lands, climate change, and loss of biodiversity). In terms of human health, diseases of the following systems occur: respiratory (asthma, bronchitis), cardiovascular (stroke, heart attack), pulmonary (infections, cancer), and premature death. To reduce contamination, sustainable intervention must be carried out in the early stages of the pollution-control process. These include physical techniques (isolation, soil vapor extraction, solvent extraction, soil washing), chemical techniques (dispersants–surfactants, chemical oxidation, solidification/stabilization, thermal desorption), biological techniques (bioremediation, phytoremediation), and indigenous absorbents (peat, straw, wood sawdust, natural zeolites, clays, hemp fibers, granular slag, Adabline II OS). Due to the significant environmental consequences, decisions regarding the treatment of contaminated sites should be made by environmental experts, who must consider factors such as treatment costs, environmental protection regulations, resource recovery, and social implications. Public awareness is also crucial, as citizens need to understand the severity of the issue. They must address the sources of pollution to develop sustainable solutions for ecosystem decontamination. By protecting the environment, we are also safeguarding human nature. Full article

Wildfires in Portugal have become increasingly frequent and severe, driven by a combination of fuel accumulation, extreme meteorological conditions, and topographic complexity. This study assesses the applicability of the Hot–Dry–Windy (HDW) index in characterizing fire-weather conditions during five major wildfires: Chamusca (2003), Pedrógão Grande and Lousã (2017), Monchique (2018), and Covilhã (2022). HDW values were computed at sub-daily resolution and compared against a 1991–2020 climatology. This study also evaluates the HDW index as a high-resolution fire danger indicator in Portugal and compares it with the traditional FWI using percentile-based climatology. The findings indicate that during 12 and 15 UTC, HDW in the wildfires in Chamusca (2003) and Lousã (2017) exceeded 180–370 units, suggesting extreme air conditions driven by hot, dry, and windy weather patterns. These values denoted extremely flammable conditions since they were significantly higher than the 95th percentile. A distinct peak at 15 UTC for Pedrógão Grande (2017) topped 140 units (>P95), which is consistent with the ignition timing and a rapid beginning spread. A continuous HDW anomaly that peaked above 200 units between 2 August and 5 August preceded the Monchique (2018) event, suggesting extended heat stress and increased wind contribution. While not as severe as in previous instances, HDW at Covilhã (2022) was above the 75th percentile in the early afternoon (12–18 UTC). Results show that in all cases, HDW values exceeded the 90th and 95th percentiles during the hours of ignition and early fire spread, with the most critical anomalies occurring between 12 UTC and 18 UTC. Spatial analyses revealed regional-scale patterns of HDW exceedance, aligning with observed ignition zones. Comparisons with the Canadian Fire Weather Index (FWI) revealed that while the FWI captured seasonal fuel aridity, the HDW more effectively resolved short-term meteorological extremes, particularly wind and atmospheric dryness. The HDW index was found to identify high-risk conditions even when FWI values were moderate, highlighting its added diagnostic value. These results support the inclusion of HDW in operational fire danger rating systems for Portugal and other Mediterranean countries, where compound fire-weather extremes are becoming more frequent due to climate change. Full article

Green Firebreaks (GFBs), strips of strategically placed low-flammability vegetation, represent a proactive complement to other approaches to wildfire management. This review, which summarises the literature to elucidate GFBs’ potential to reduce fire spread and intensity, revealed that empirical studies validating their effectiveness remain scarce. It also revealed that comparisons of GFB techniques are challenging due to spatial and temporal complexity combined with inconsistent methods and terminology. Several researchers note that GFB effectiveness requires that their design is appropriate for the site conditions. Furthermore, GFBs are not a stand-alone solution to the wildfire problem, and a lack of consideration for trade-offs may undermine their effectiveness, particularly under extreme weather conditions. As climate change intensifies drought and heat, vegetation moisture content must be a key design factor given that even low-flammability vegetation becomes fuel under extreme drought conditions. In addition, poorly designed GFBs may unintentionally alter wind dynamics and increase ember transport and fire spread. There is a broad consensus in the literature that appropriately designed GFBs can complement wildfire management while providing additional biodiversity and other benefits. To achieve their potential, research is required for GFB designs to be site-specific, responsive to trade-offs, and effective in providing multiple benefits under different climate change scenarios. Full article

Wildfire behavior and post-fire effects are strongly modulated by terrain, yet the relative influence of individual topographic factors on burn severity remains incompletely quantified at landscape scales. The Composite Burn Index (CBI) provides a field-calibrated measure of severity, but large-area analyses have been hampered by limited plot density and cumbersome data extraction workflows. In this study, we paired 6150 CBI plots from 234 U.S. wildfire events (1994–2017) with 30 m SRTM DEM, extracting mean elevation, slope, and compass aspect within a 90 m buffer around each plot to minimize geolocation noise. Topographic variables were grouped into ecologically meaningful classes—six elevation belts (≤500 m to >2500 m), six slope bins (≤5° to >25°), and eight aspect octants—and their relationships with CBI were evaluated using Tukey HSD post hoc comparisons. Our findings show that all three factors exerted highly significant influences on severity (p < 0.001): mean CBI peaked in the 1500–2000 m belt (0.42 higher than lowlands), rose almost monotonically with steepness to slopes > 20° (0.37 higher than <5°), and was greatest on east- and northwest-facing slopes (0.19 higher than south-facing aspects). Further analysis revealed that burn severity emerges from strongly context-dependent synergies among elevation, slope, and aspect, rather than from simple additive effects. By demonstrating a rapid, reproducible workflow for terrain-aware severity assessment entirely within GEE, the study provides both methodological guidance and actionable insights for fuel-management planning, risk mapping, and post-fire restoration prioritization. Full article

The increasing frequency and severity of forest fires, driven by climate change and intensified human activities, pose substantial threats to ecological security and sustainable development. However, most assessments remain centered on occurrence risk, lack a resilience-oriented perspective and comprehensive indicator systems, and therefore offer limited guidance for building system resilience. This study developed a forest fire resilience (FFR) assessment framework with 25 indicators in three levels and six domains across four resilience dimensions. Balancing expert judgment and data, we obtained indicator weights by integrating the Analytic Hierarchy Process (AHP) and the Criteria Importance Through Intercriteria Correlation (CRITIC) via a game-theoretic scheme. The analysis revealed that, among the level-2 indicators, climate factors, infrastructure, and vegetation characteristics exert the greatest influence on FFR. At the level-3 indicator scale, monthly minimum relative humidity, fine fuel load per unit area, and the deployment of smart monitoring systems were critical. Among the four resilience dimensions, absorption capacity plays the predominant role in shaping disaster response. Building on these findings, the study proposes targeted strategies to enhance FFR and applies the assessment framework to twelve administrative divisions of Baise City, China, highlighting marked spatial variability in resilience levels. The results offer valuable theoretical insights and practical guidance for strengthening FFR. Full article

High-temperature CaO-based CO₂ capture technology, energized by in situ coal combustion, exhibits substantial promise owing to its high energy efficiency, strong compatibility, and maturity. However, sorbent deactivation mechanisms under complex coal combustion conditions, particularly for industrially required pelletized sorbents, are unclear. Pelletized sorbents were co-fired with four representative coals (differing in Na-K, S, and Al-Si content) in this study. Key factors were decoupled, and two competing mechanisms were revealed: (1) High-temperature sintering deactivation: Single co-firing triggers localized overheating (>900 °C), causing severe sintering and pore collapse. This reduces the specific surface area by 29% and pore volume by 50%, occludes meso-/macropores, and leads to a significant drop in initial CO₂ capture capacity to 0.266–0.297 g/g. Coal types and minor residual surface impurities (<1.7%) are secondary factors. (2) Si-Al ash stabilization: During repeated co-firing (1–9 cycles), Si-Al ash components enrich on sorbents (0.1–7.6%), forming a thermally protective layer. After 20 adsorption–desorption cycles, the CO₂ capture capacity loss drops from 17.6% to 3.9%, improving cycle stability. These findings clarify these dual mechanisms, providing a theoretical basis for system optimization and highlighting precise control of the combustion temperature field as critical for industrial deployment. Full article

This article discusses the possibilities and methods for rescuing people from abandoned mine workings and the cooperation of the components of the Integrated Rescue System of the Slovak Republic when carrying out rescue work in underground spaces, specifically the Bankov mine. Additionally, the basic legislative restrictions on the level of rescue work that can be performed in underground spaces in Slovakia and abroad are characterized. In the study itself, exercises in a mining environment were designed and tested by rescuers from the fire and rescue corps of the Slovak Republic, while several methods for rescuing people from underground spaces using climbing equipment were tested. Since the research setting was an abandoned mine, the rescue methods were carried out with regard to the maximum achievable safety of the firefighters. With the demise of the Mine Rescue Service in the Slovak Republic in 2025, rescue activities passed into the hands of the fire and rescue corps, and it is therefore necessary to determine the best method for rescue from mining spaces that can be performed by firefighters when the priority is the rescue time: the most important factor for saving human life. Using the analysis of the data obtained in this study, the most effective method specifically for rescuing people from underground spaces was determined. Based on the information obtained, proposals and measures were established to make rescue work in underground spaces more efficient. The research met all standards set for firefighters, and all rescuers agreed to publish this research. Full article

Poly- and perfluorinated alkyl substances (PFAS) are a group of chemicals that are widely used, prevalent in the environment, associated with several toxic effects, and often have long half-lives. Their persistence and relevant toxicity are the primary causes of environmental and human health concerns, and they are referred to as “forever chemicals” because of their persistence. Environmental accumulation caused by slow natural biodegradation and subsequent long environmental half-lives leads to bioaccumulation and makes PFAS more likely to be chronically toxic with potential transgenerational effects. Ultimately, it is this persistence that causes the greatest concern because PFAS-contaminated sites need costly remediation techniques, or else the contaminated areas will not be available for proper economic development because of social and economic suppression. Non-PFAS, alternative Aqueous Film Forming Foams (AFFF) that are considered environmentally friendly, are being heavily considered or currently used for fire suppression instead of PFAS-based products. The bioaccumulation and toxicity of alternative AFFF are just starting to be studied. The purpose of this review is to discuss the basic environmental and human health effects of PFAS and alternative AFFF that propel regulatory changes, increase clean-up costs, reduce economic development, and drive the development of novel alternatives. Full article

Forest fires pose severe ecological, climatic, and socio-economic threats, destroying habitats and emitting greenhouse gases. Early and timely warning is particularly challenging because fires often originate from small-scale, low-temperature ignition sources. Traditional monitoring approaches primarily rely on single-source satellite imagery and empirical threshold algorithms, and most forest fire monitoring tasks remain human-driven. Existing frameworks have yet to effectively integrate multiple data sources and detection algorithms, lacking the capability to provide continuous, automated, and generalizable fire monitoring across diverse fire scenarios. To address these challenges, this study first improves multiple monitoring algorithms for forest fire detection, including a statistically enhanced automatic thresholding method; data augmentation to expand the U-Net deep learning dataset; and the application of a freeze–unfreeze transfer learning strategy to the U-Net transfer model. Multiple algorithms are systematically evaluated across varying fire scales, showing that the improved automatic threshold method achieves the best performance on GF-4 imagery with an F-score of 0.915 (95% CI: 0.8725–0.9524), while the U-Net deep learning algorithm yields the highest F-score of 0.921 (95% CI: 0.8537–0.9739) on Landsat 8 imagery. All methods demonstrate robust performance and generalizability across diverse scenarios. Second, data-driven scheduling technology is developed to automatically initiate preprocessing and fire detection tasks, significantly reducing fire discovery time. Finally, an integrated framework of multi-source remote sensing data, advanced detection algorithms, and a user-friendly visualization interface is proposed. This framework enables all-weather, fully automated forest fire monitoring and early warning, facilitating dynamic tracking of fire evolution and precise fire line localization through the cross-application of heterogeneous data sources. The framework’s effectiveness and practicality are validated through wildfire cases in two regions of Yunnan Province, offering scalable technical support for improving early detection of and rapid response to forest fires. Full article

Forest soil greenhouse gas emissions play a critical role in global climate change. This review synthesizes the mechanisms of temperature change impacts on forest soil greenhouse gas (CO₂, CH₄, N₂O) emissions, the complex response patterns of ecosystems, and existing knowledge gaps in current research. We highlight several critical mechanisms, such as the high temperature sensitivity (Q₁₀) of methane (CH₄) and CO₂ emissions from high-latitude peatlands, and the dual effect of chronic nitrogen deposition, which can cause short-term stimulation but long-term suppression of soil CO₂ emissions. It emphasizes how climatic factors, soil characteristics, vegetation types, and anthropogenic disturbances (such as forest management and fire) regulate emission processes through multi-scale interactions. This review further summarizes the advancements and limitations of current research methodologies and points out future research directions. These include strengthening long-term multi-factor experiments, developing high-precision models that integrate microbial functional genomics and isotope tracing techniques, and exploring innovative emission reduction strategies. Ultimately, this synthesis aims to provide a scientific basis and key ecological threshold references for developing climate-resilient sustainable forest management practices and effective climate change mitigation policies. Full article

Burned area (BA) mapping and fire severity assessment are essential for understanding fire occurrence patterns, formulating post-fire restoration strategies and evaluating vegetation recovery processes. However, existing BA datasets are primarily derived from coarse-resolution satellite imagery and often lack sufficient consideration of fire severity. To address these limitations, this study utilized dense time-series Landsat imagery available on the Google Earth Engine, applying the qualityMosaic method to generate annual composites of minimum normalized burn ratio values. These composites imagery enabled the rapid identification of fire sample points, which were subsequently used to train a random forest classifier for estimating per-pixel burn probability. Pixels with a burned probability greater than 0.9 were selected as the core of the BA, and used as candidate seeds for region growing to further expand the core and extract complete BA. This two-stage extraction method effectively balances omission and commission errors. To avoid the repeated detection of unrecovered BA, this study developed distinct correction rules based on the differing post-fire recovery characteristics of forests and grasslands. The extracted BA were further categorized into four fire severity levels using the delta normalized burn ratio. In addition, we conducted a quantitative validation of the BA mapping accuracy based on Sentinel-2 data between 2015 and 2023. The results indicated that the BA mapping achieved an overall accuracy of 93.90%, with a Dice coefficient of 82.04%, and omission and commission error rates of 26.32% and 5.25%, respectively. The BA dataset generated in this study exhibited good spatiotemporal consistency with existing products, including MCD64A1, FireCCI51, and GABAM. The BA fluctuated significantly between 1985 and 2010, with the highest value recorded in 1987 (13,315 km²). The overall trend of BA showed a decline, with annual burned areas remaining below 2000 km² after 2010 and reaching a minimum of 92.8 km² in 2020. There was no significant temporal variation across different fire severity levels. The area of high-severity burns showed a positive correlation with the annual total BA. High-severity fire-prone zones were primarily concentrated in the northeastern, southeastern, and western parts of the study area, predominantly within grasslands and forest–grassland ecotone regions. Full article

Frequent grassland fires have severely affected regional ecosystems as well as the production and living conditions of local residents. Grassland fire prevention capabilities constitute an integral part of the disaster prevention and mitigation system and play an important role in improving grassroots governance. To gain a deeper understanding of the practical foundation and influencing mechanisms of grassland fire prevention capabilities, establish an evaluation index system for prevention capabilities covering the four dimensions of disaster prevention, disaster resistance, disaster relief, and recovery. Combining micro-level survey data, a quantile regression model is used to analyze the influencing factors. The research findings indicate that (1) disaster resistance (0.49) plays a prominent role in grassland fire prevention capabilities, with economic foundations and individual disaster relief capabilities being particularly critical for overall improvement. Although residents have strong fire prevention awareness, their organizational collaboration capabilities are relatively weak, and there are significant differences in prevention capabilities across regions, necessitating tailored, precise enhancements. (2) There are significant differences in prevention capabilities among residents of different agricultural and pastoral production types, with semi-agricultural and semi-pastoral areas having the strongest comprehensive capabilities and pastoral areas relatively weaker. (3) A significant analysis of factors influencing grassland fire prevention capabilities: effective and diverse risk communication is a prerequisite for enhancing residents’ prevention capabilities; the level of panic regarding grassland fires and road infrastructure are important influencing factors, but residents’ understanding of climate change and grassroots organizations’ capacity for mechanism construction have insignificant impacts. Therefore, in future grassland fire disaster prevention and mitigation efforts, it is essential to strengthen risk communication, improve infrastructure, monitor environmental changes and the spatiotemporal patterns of grassland fires, enhance residents’ understanding of climate change, reinforce the emergency response capabilities of grassroots organizations, and stimulate public participation awareness to collectively build a multi-tiered grassland fire prevention system. Full article