Search Results (152)

The Mediterranean region, identified by scientists as a ‘climate hot spot’, is experiencing warmer and drier conditions, along with an increase in the intensity and frequency of extreme weather events. One such extreme phenomena is droughts. The recent wildfires in this region are a concerning consequence of this phenomenon, causing severe environmental damage and transforming natural landscapes. However, droughts involve a two-way interaction: On the one hand, climate change and various human activities, such as urbanization and deforestation, influence the development and severity of droughts. On the other hand, droughts have a significant impact on various sectors, including ecology, agriculture, and the local economy. This study investigates drought dynamics in four Mediterranean countries, Greece, France, Italy, and Spain, each of which has experienced severe wildfire events in recent years. Using satellite-based Earth observation data, we monitored drought conditions across these regions over a five-year period that includes the dates of major wildfires. To support this analysis, we derived and assessed key indices: the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and Normalized Difference Drought Index (NDDI). High-resolution satellite imagery processed within the Google Earth Engine (GEE) platform enabled the spatial and temporal analysis of these indicators. Our findings reveal that, in all four study areas, peak drought conditions, as reflected in elevated NDDI values, were observed in the months leading up to wildfire outbreaks. This pattern underscores the potential of satellite-derived indices for identifying regional drought patterns and providing early signals of heightened fire risk. The application of GEE offered significant advantages, as it allows efficient handling of long-term and large-scale datasets and facilitates comprehensive spatial analysis. Our methodological framework contributes to a deeper understanding of regional drought variability and its links to extreme events; thus, it could be a valuable tool for supporting the development of adaptive management strategies. Ultimately, such approaches are vital for enhancing resilience, guiding water resource planning, and implementing early warning systems in fire-prone Mediterranean landscapes. Full article

The combustion behavior and thermal performance of industrial-scale borax pentahydrate (Na₂B₄O₇·5H₂O) melting furnaces remain underexplored despite their critical role in boric oxide (B₂O₃) production, a key input for high-performance manufacturing. This study addressed this gap by employing three-dimensional computational fluid dynamics (CFD) simulations to model two operational natural gas-fired furnaces with distinct burner configurations (four-burner and six-burner systems). The analysis focused on optimizing burner placement, specifically, the axial distance and inclination angle, to enhance thermal uniformity and reduce refractory wall damage caused by aggressive high-temperature borate corrosion. A comprehensive parametric study of twelve burner configurations revealed that tilting the burners at 5–10° significantly improved temperature uniformity while reducing peak wall temperatures and mitigating localized hot spots. The optimal design, incorporating a 10° burner angle and a staggered burner arrangement (Case 11), attained a melt pool temperature of 1831.3 K and a charging average wall temperature of 1812.0 K. These values represent essential benchmarks for maximizing furnace efficiency and operational stability. The modified designs for the four- and six-burner systems led to improved temperature distributions and a notable reduction in maximum wall temperatures, directly contributing to longer maintenance intervals and improved refractory durability. The findings of this study confirm that minor geometrical and angular adjustments in burner placement can yield significant performance gains. The validated CFD approach and proposed design modifications offer a scalable, low-cost strategy for improving combustion efficiency and furnace lifespan in borax processing facilities. Full article

The wildland–urban interface (WUI) has been a global phenomenon, yet parameter threshold determination remains a persistent challenge in this field. In China, a significant research gap exists in the development of WUI mapping methodology. This study proposes a novel mapping approach that delineates the WUI by integrating both vegetation and building environment perspectives. GaoFen 1 Panchromatic Multi-spectral Sensor (GF1-PMS) imagery was leveraged as the data source. Building location was extracted using object-oriented and hierarchical classification techniques, and the pixel dichotomy method was employed to estimate fractional vegetation coverage (FVC). Building location and FVC were used as input for the WUI mapping. In this methodology, the threshold of FVC was determined by incorporating the remote sensing characteristics of the WUI types, whereas the buffer range of vegetation was refined through sensitivity analysis. The proposed method demonstrated high applicability in Anning City, achieving an overall accuracy of 88.56%. The total WUI area amounted to 49,578.05 ha, accounting for 38.08% of Anning City’s entire area. Spatially, the intermix WUI was predominantly distributed in the Taiping sub-district of Anning City, while the interface WUI was mainly concentrated in the Bajie sub-district of Anning City. MODIS fire spots from 2003 to 2022 were primarily clustered in the Qinglong sub-district, Wenquan sub-district, and Caopu sub-district of Anning City. Our findings indicated a spatial overlap between the WUI and fire-prone areas in Anning City. This study presents an effective methodology for threshold determination and WUI mapping, making up for the scarcity of mapping methodologies in China. Moreover, our approach offers valuable insights for a wise decision in fire risk. Full article

Portugal’s increasing wildfire frequency has led to home destruction, large areas burned, ecological damage, and economic loss, emphasizing the need for effective fire exposure assessments. This study builds on a Canadian approach to wildfire exposure and evaluates wildfire exposure in the Portuguese municipality of Mafra, using artificial territories (AT) as a proxy for the wildland–urban interface (WUI) and integrates land use land cover (LULC) data with a neighborhood analysis to map exposure at the municipal scale. Fire exposure was assessed for three fire transmission distances: radiant heat (RH, <30 m), short-range spotting (SRS, <100 m), and longer-range spotting (LRS, 100–500 m) using fine resolution (5 m) LULC data. Results revealed that while AT generally exhibited lower exposure (<16% “very high” exposure), adjacent hazardous LULC subtypes significantly increase wildfire hazard, with up to 51% of LULC subtypes classified as “very high exposure”. Field validation confirmed the accuracy of exposure maps, supporting their use in wildfire risk reduction strategies. This cost-effective, scalable approach offers actionable insights for forest and land managers, civil protection agencies, and policymakers, aiding in fuel management prioritization, community preparedness, and the design of evacuation planning. The methodology is adaptable to other fire-prone regions, particularly mediterranean landscapes. Full article

Cotton aphids, Aphis gossypii, are an important pest worldwide and have evolved mutualistic relationships with the invasive fire ant Solenopsis invicta. Their body color varies from pale yellow to dark green, with an increase in body size and fecundity. The body color composition in a cotton aphid colony can be influenced by biotic interactions with mutualistic ants and predatory ladybugs. However, since the distribution of nutrients varies across host plant organs, there may exist special effects of biotic interactions on the body color composition of the aphids on different plant parts. In the present study, we found that, under constant laboratory conditions, the proportions of dark green morphs varied among the cotton aphids distributed on different parts of a cotton seedling, with significantly higher proportions on the stems, petioles, and sprouts (SPSs) than on leaves. The presence of mutualistic fire ants significantly increased the proportion of dark green morphs in the cotton aphid colony, but with a reduction in aphid body size, compared to the untended individuals. In contrast, the introduction of a predatory seven-spotted ladybug, Coccinella septempunctata, dramatically decreased the proportion of dark green morphs on SPSs, but not on leaves, leading to a reduction in the proportion of the whole colony. These results illustrate a spatial variation in the proportions of dark green morphs on host plants in cotton aphids, which may be an adaptive strategy used by the aphids to gain benefits and/or minimize costs in the interactions with mutualistic ants and predatory ladybugs. Full article

Accurate monitoring and assessment of forest disturbance and recovery dynamics are essential for sustainable forest management, particularly in ecological transition zones. This study analyzed forest disturbance and recovery patterns in China’s Funiu Mountains from 1991 to 2020 by integrating the LandTrendr algorithm with space-time cube analysis. Using Landsat time series data and the Geodetector method, we examined both the spatiotemporal characteristics and driving factors of forest change across three periods. The results showed that (1) between 1991 and 2020, the study area experienced 131.19 km² of forest disturbance and 495.88 km² of recovery, with both processes most active during the 1990s; (2) spatiotemporal analysis revealed that both disturbance and recovery patterns were predominantly characterized by cold spots, suggesting relatively stable forest conditions despite localized changes; (3) human activities were the primary drivers of forest disturbance in the early period, while forest recovery was consistently influenced by the combined effects of topographic conditions and precipitation. Additionally, forest fires emerged as an important factor affecting both disturbance and recovery patterns after 2010. These findings enhance our understanding of forest dynamics in transition zones and provide empirical support for regional forest management strategies. The results also highlight the importance of considering both spatial and temporal dimensions when monitoring long-term forest changes. Full article

To address the demands of efficient forest fire detection and suppression, an adaptive multiple UAV swarm collaborative firefighting strategy considering dynamic forest fire spread and resource constraints was proposed in this paper. The multiple UAV swarm adaptive information-driven collaborative search (MUSAIDCS) algorithm and the resource-limited firefighting model were established. A temperature change-driven adaptive step-length search strategy is proposed to improve the accuracy of the search and detection of fire spots. The critical water flow rate required for fire suppression is calculated to evaluate the firefight performance, and an emergency bidding algorithm is applied to enable multiple UAV swarms collaborative firefighting under limited resources, including different payloads per UAV and swarm number. The comparative simulations for four search strategies indicate that the MUSAIDCS search strategy can significantly reduce task completion time and improve firefighting efficiency compared with the other traditional search strategies. Increasing payload quantity per UAV and swarm number can further enhance task completion efficiency and firefighting effectiveness. This study demonstrates that a resource-constrained collaborative firefighting strategy enables the dynamic allocation of UAV swarm resources under limited conditions and then optimizes firefighting performance within constraints. Full article

Better understanding the complex mechanisms underlying the variations in crop residue burning (CRB) intensity and patterns is crucial for evaluating control strategies and developing sustainable policies aimed at the efficient recycling of crop residues. However, the intricate interplay between the CRB practices, climate variability, and human activities poses a significant challenge in this endeavor. Here, we utilize the high spatiotemporal resolution of satellite observations to characterize and explore the dynamics of summer CRB in North China at multiple scales. Between 2003 and 2012, there was a significant intensification of summer CRB in North China, with the annual number of burning spots increasing by an average of 499 (95% confidence interval, 252–1426) spots/year. However, in 2013, China promulgated the stringent Air Pollution Prevention and Control Action Plan, which led to a rapid decrease in the intensity of summer CRB. Local farmers also adjusted their burning practices, shifting from concentrated and intense burning to a more dispersed and uniformly intense approach. Between 2003 and 2020, the onset of summer CRB shifted earlier in North China by 0.75 (0.5–1.1) days/year, which is attributed to the combined effects of climate change and anthropogenic controls. Specifically, the onset time is found to be significantly and negatively correlated with spring temperature anomalies and positively correlated with anomalies in the number of spring frost days. Climate change has led to a shortened crop growing season, resulting in an earlier start to summer CRB. Moreover, the enhanced anthropogenic controls on CRB expedited this process, making the trend of an earlier start time even more pronounced from 2013 to 2020. Contrary to the earlier onset of summer CRB, the termination of local wheat residue burning experienced a notable delay by 1.0 (0.8–1.4) days/year, transitioning from mid-June to early July. Full article

(1) Background: Forest fires are widespread in Mediterranean-climate regions and are becoming very common in urban and peri-urban areas. (2) Methods: Wildfires in Attica since 1977 are mapped and types of vegetation burned are reported. (3) Results: Fires are becoming larger. During the period of study (1977–2024), 45% of the burned area was covered with Pinus halepensis forests, 1.4% with Abies cephalonica forests, and 18.5% with shrublands. A relatively high percentage of the burned area (BA) affected more than once consisted of pine forests (65%). Ten percent of the total BA lies within the boundaries of the Natura 2000 network, Europe’s most important network of protected areas, of which 38.9% was burned. At the interannual scale, the BA in Attica is negatively correlated with relative humidity, while reduced precipitation may contribute to the expansion of wildfires. (4) Conclusions: Fires are becoming larger over time, with low humidity increasing the higher fire risk. Since the changing climate is expected to create more severe and uncontrollable conditions, mitigation and adaptation measures should be planned and be introduced immediately. Full article

The ignition of combustible materials by electric welding spatters represents a significant cause of fires in welding operations, and the current intensity is a sensitive factor that affects the ignition capacity of welding spatters. In this work, the influence of different current intensities on the physical properties and ignition capacity of welding spatters on common combustible materials was investigated, and the ignition mechanism of electric welding spatter was also explained by means of the hot-spot theory. The results indicated that the splash range, the total generated quantity, the maximum diameter, and the temperature of electric welding spatters increased with the enhancement in current intensity. Furthermore, a higher current intensity was associated with a greater likelihood of producing irregular spatter particles. The probability of ignition of electrode welding spatters was found to be sensitive to their physical properties, exhibiting a non-linear increase with increasing current intensity. At a current intensity of 360 A, a surge in both the physical properties and ignition capacity of the spatters was observed, which is attributed to the coupling of a reduction in the critical hot-spot radius and an unstable pulsation in the arc. Full article

Previous evaluation models for cultural relic buildings in relation to fire risk fail to consider the necessity for effective firefighting and rescue capabilities in complex forest environments. This paper incorporates variables, including those pertaining to forest fires and climatic conditions, into the assessment index system. The hierarchical analysis method and the local punishment-incentive variable weighting method are employed to introduce a compensation coefficient score. A model for the evaluation of firefighting and rescue capability in a continuous area of cultural relic buildings in conjunction with the surrounding forest environment has been developed. The firefighting and rescue capability of the Yuelu Mountain scenic spot was evaluated at 73.91 (level III) using the fixed weight method and 69.52 (level IV) using the variable weight method. The variable weight method proved to be a more accurate approach for evaluating the status and importance of dynamic targets, thus enabling a more precise evaluation of the comprehensive evaluation area. The evaluation results inform the formulation of targeted improvement measures for enhancing the firefighting and rescue capabilities of cultural relic buildings. Full article

At the end of the dry season, from early March to early April each year, extensive agricultural biomass waste burnings occur throughout insular mainland Southeast Asia. During this biomass-burning period, smoke aerosols blanketed the whole region and were transported and dispersed by predominant westerly and southwesterly winds to southern China, Taiwan, and as far southern Japan and the Philippines. The extensive and intense burnings coincided with some wildfires in the forests due to high temperatures, making the region one of the global hot spots of biomass fires. In this study, we focus on the effect of pollutants emitted from biomass burnings in March 2019 at the height of the burning period on the exposed population and their health impact. The Weather Research Forecast-Chemistry (WRF-Chem) model was used to predict the PM_2.5 concentration over the simulating domain, and health impacts were then assessed on the exposed population in the four countries of Southeast Asia, namely Thailand, Laos, Cambodia, and Vietnam. Using the health impact based on log-linear concentration-response function and Integrated Exposure Response (IER), the results show that at the peak period of the burnings from 13 to 20 March 2019, Thailand experienced the highest impact, with an estimated 2170 premature deaths. Laos, Vietnam, and Cambodia followed, with estimated mortalities of 277, 565, and 315 deaths, respectively. However, when considering the impact per head of population, Laos exhibited the highest impact, followed by Thailand, Cambodia, and Vietnam. The results highlight the significant health impact of agricultural waste burnings in Southeast Asia at the end of the dry season. Hence, policymakers should take these into account to design measures to reduce the negative impact of widespread burnings on the exposed population in the region. Full article

Forest fires can occur suddenly and have significant environmental, economic, and social consequences. The timely and accurate evaluation and prediction of their progression, particularly the spread speed in difficult-to-access areas, are essential for emergency management departments to proactively implement prevention strategies and extinguish fires using scientific methods. This paper provides an analysis of models for predicting forest fire spread in China and globally. Incorporating remote sensing (RS) technology and forest fire science as the theoretical foundation, and utilizing the Wang Zhengfei forest fire spread model (1983), which is noted for its broad adaptability in China as the technical framework, this study constructs a forest fire spread model based on remote sensing interpretation. The model improves the existing model by adding elevation an factor and optimizes the method for acquiring certain parameters. By considering regional landforms (ridge lines, valley lines, and slopes) and vegetation coverage, this paper establishes three-dimensional visual interpretation markers for identifying hotspots; the orientation of the hotspots can be identified to simulate the spread of the fire uphill, downhill, in the direction of the wind, left-level slope, and right-level slope. Then, the data of Sentinel-2 and DEM were used to invert the fuel humidity and slope of pixels in the fire line areas. The statistical inversion data from pixels, which replaced fixed-point values in traditional models, were utilized for predicting forest fire spread speed. In this paper, the model was applied to the case of a forest fire in Mianning County, Sichuan Province, China, and verified using high-time-resolution Himawari-8 data, Gaofen-4 data, and historical data. The results demonstrate that the direction and maximum speed of fire spread for the fire lines in Baifen Mountai, Jiaguer Villageand, Muchanggou, Xujiabaozi, and Zhaizigou are uphill, 16.5 m/min; wind direction, 17.32 m/min; wind direction, 1.59 m/min; and wind direction, 5.67 m/min. The differences are mainly due to the locations of the fire lines, moisture content of combustibles, and maximum slopes being different. Across the entire fire line area, the average rate of increase in the area of open flames within one hour was 3.257 hm²/10 min (square hectares per 10 min), closely matching the average increase rate (3.297 hm²/10 min) monitored by the Himawari-8 satellite in 10 min intervals. In contrast, conventional fixed-point fire spread models predicted an average rate of increase of 3.5637 hm²/10 min, which shows a larger discrepancy compared to the Himawari-8 satellite monitoring results. Moreover, when compared to the fire spot monitoring results from the Gaofen-4 satellite taken 54 min after the initial location of the fire line, the predictions from the RS-enabled fire spread model, which integrates remote sensing interpretations, closely matched the actual observed fire boundaries. Although the predictions from the RS-enabled fire spread model and the traditional model both align with historical data in terms of the overall fire development trends, the RS-enabled model exhibits higher reliability and can provide more accurate information for forest fire emergency departments, enabling effective pre-emptive measures and scientific firefighting strategies. Full article

In recent years, due to the spike in natural gas spot prices, gas-fired power corporations’ operating costs have skyrocketed. Traditional power generation corporations have gradually been withdrawing from gas power generation investment, replaced by oil and gas enterprises with upstream resources. The development of gas-fired power plants helps to maintain the stability of the power grid and has a positive effect on the realization of carbon neutrality goals. At present, most of the financial evaluation methods for gas power generation projects tend to focus on the static tariffs of the project itself and lack consideration for the overall contribution to the industry chain and the latest “gas–electricity price linkage” mechanisms in China, leading to oil and gas enterprises reducing investment in gas-fired power plants due to yield constraints. In this paper, a financial evaluation methodology for gas power generation projects based on the industrial chain and the “gas–electricity price linkage” mechanism was proposed. The investment return characteristics of specific gas power generation projects under the “gas–electricity price linkage” mechanism in different provinces were revealed through this methodology. Considering the characteristics and industrial development trends in major provinces in China, investment and operation strategies for gas power generation were proposed. These studies provide oil and gas enterprises with references and suggestions for future investment decisions for new gas power generation projects. Full article

Lightning-induced forest fires frequently inflict substantial damage on forest ecosystems, with the Daxing’anling region in northern China recognized as a high-incidence region for such phenomena. To elucidate the occurrence patterns of forest fires caused by lightning and to prevent such fires, this study employs a multifaceted approach, including statistical analysis, kernel density estimation, and spatial autocorrelation analysis, to conduct a comprehensive examination of the spatiotemporal distribution patterns of lightning-induced forest fires in the Greater Khingan Mountains region from 2016–2020. Additionally, the geographical detector method is utilized to assess the explanatory power of three main factors: climate, topography, and fuel characteristics associated with these fires, encompassing both univariate and interaction detections. Furthermore, a mixed-methods approach is adopted, integrating the Zhengfei Wang model with a three-dimensional cellular automaton to simulate the spread of lightning-induced forest fire events, which is further validated through rigorous quantitative verification. The principal findings are as follows: (1) Spatiotemporal Distribution of Lightning-Induced Forest Fires: Interannual variability reveals pronounced fluctuations in the incidence of lightning-induced forest fires. The monthly concentration of incidents is most significant in May, July, and August, demonstrating an upward trajectory. In terms of temporal distribution, fire occurrences are predominantly concentrated between 1:00 PM and 5:00 PM, conforming to a normal distribution pattern. Spatially, higher incidences of fires are observed in the western and northwestern regions, while the eastern and southeastern areas exhibit reduced rates. At the township level, significant spatial autocorrelation indicates that Xing’an Town represents a prominent hotspot (p = 0.001), whereas Oupu Town is identified as a significant cold spot (p = 0.05). (2) Determinants of the Spatiotemporal Distribution of Lightning-Induced Forest Fires: The spatiotemporal distribution of lightning-induced forest fires is influenced by a multitude of factors. Univariate analysis reveals that the explanatory power of these factors varies significantly, with climatic factors exerting the most substantial influence, followed by topographic and fuel characteristics. Interaction factor analysis indicates that the interactive effects of climatic variables are notably more pronounced than those of fuel and topographical factors. (3) Three-Dimensional Cellular Automaton Fire Simulation Based on the Zhengfei Wang Model: This investigation integrates the fire spread principles from the Zhengfei Wang model into a three-dimensional cellular automaton framework to simulate the dynamic behavior of lightning-induced forest fires. Through quantitative validation against empirical fire events, the model demonstrates an accuracy rate of 83.54% in forecasting the affected fire zones. Full article