Search Results (1,517)

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

Prescribed burning significantly influences the microbial communities and physicochemical characteristics of forest soils. However, studies on the impacts of prescribed burning on the stability of soil microbial co-occurrence networks, as well as on the combined effects of post-fire soil depth gradients and their interactions on soil physicochemical properties and microbial communities, remain poorly understood. This study was conducted in a subtropical Pinus yunnanensis plantation that has undergone annual prescribed burns since 2007. Using 16S and ITS rRNA gene sequencing techniques alongside analyses of soil physicochemical properties, we collected and examined soil samples from different depths (0–5 cm, 5–10 cm, and 10–20 cm) in June 2024. The study found that prescribed burning enhanced the complexity and stability of bacterial co-occurrence networks, boosting both the diversity (prescribed burning/unburned control: 3/1) and the abundance (prescribed burning/unburned control: 8/2) of key taxa, which were essential for maintaining bacterial community network stability. However, it also intensified competitive interactions (prescribed burning/unburned control: 0.3162/0.0262) within the community. Moreover, prescribed burning had a significant effect on the diversity, structure, and composition of microbial communities and the physicochemical properties in the 0–5 cm soil layer, while also showing notable effects in the 5–20 cm layer. Prescribed burning also enhanced the coupling between the soil environment and bacterial community composition. The bacterial community showed negative correlations with most physicochemical properties. Soil organic matter (SOM) (p = 0.002) and available potassium (AK) (p = 0.042) were identified as key determinants shaping the post-fire bacterial community structure. The relationship between physicochemical parameters and fungal community composition was weaker. Urease (UE) (p = 0.036) and total potassium (TK) (p = 0.001) emerged as two key factors influencing the composition of post-fire fungal communities. These results elucidate the distinct functional roles of bacteria and fungi in post-fire ecosystem recovery, emphasizing their contributions to maintaining the stability and functionality of microbial communities. The study provides valuable insights for refining prescribed burning management strategies to promote sustainable forest ecosystem recovery. Full article

With the escalating frequency of urban and forest fires driven by climate change, the development of intelligent and robust fire detection systems has become imperative for ensuring public safety and ecological protection. This paper presents a comprehensive multi-module fire detection framework based on visual computing, encompassing image enhancement and lightweight object detection. To address data scarcity and to enhance generalization, a projected generative adversarial network (Projected GAN) is employed to synthesize diverse and realistic fire scenarios under varying environmental conditions. For the detection module, an improved YOLOv8n architecture is proposed by integrating BiFormer Attention, Agent Attention, and CCC (Compact Channel Compression) modules, which collectively enhance detection accuracy and robustness under low visibility and dynamic disturbance conditions. Extensive experiments on both synthetic and real-world fire datasets demonstrated notable improvements in image restoration quality (achieving a PSNR up to 34.67 dB and an SSIM up to 0.968) and detection performance (mAP reaching 0.858), significantly outperforming the baseline. The proposed system offers a reliable and deployable solution for real-time fire monitoring and early warning in complex visual environments. Full article

The global infrastructure industry is faced with increasing system complexity and requirements driven by the Sustainable Development Goals, technological advancements, and the shift from Industry 4.0 to human-centric 5.0 principles. Coupled with persistent infrastructure investment deficits, these pressures necessitate improved methods for efficient requirements management and validation. While digital twins promise transformative real-time decision-making, reliance on static unstructured data formats inhibits progress. This paper presents a novel framework that integrates Building Information Modelling (BIM) and Model-Based Systems Engineering (MBSE), using Linked Data principles to preserve semantic meaning during information exchange between physical abstractions and requirements. The proposed approach automates a step of compliance validation against regulatory standards explored through a case study, utilising requirements from a high-speed railway station fire safety system and a modified duplex apartment digital model. The workflow (i) digitises static documents into machine-readable MBSE formats, (ii) integrates structured data into dynamic digital models, and (iii) creates foundations for data exchange to enable compliance validation. These findings highlight the framework’s ability to enhance traceability, bridge static and dynamic data gaps, and provide decision-making support in digital twin environments. This study advances the application of Linked Data in infrastructure, enabling broader integration of ontologies required for dynamic decision-making trade-offs. 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

With the rapid development of urban underground rail transit, its enclosed and densely populated environment significantly increases fire risks, posing serious threats to personnel safety and operational stability. Based on the WSR methodology and 4M theory, this study identifies fire-related factors from the physical, operational, and human dimensions. And refine indicators at the four levels of personnel, equipment and facilities, environment, and management to establish a resilience assessment system for urban underground rail transit fires. The results detailed display the application of Cross-Influence Analysis (CIA) and analytic network process (ANP) methods in fire resilience evaluation, including theoretical framework construction, computational procedures, and result analysis. A comprehensive assessment system is developed, comprising 14 secondary indicators under four primary criteria: resistance capacity, adaptation capacity, absorption capacity, and resilience capacity. And then, the CIA and ANP methods were employed to quantify inter-indicator relationships and weights through 15 expert evaluations and 52 judgment matrices, facilitating disaster-adaptive strategy formulation. Finally, an empirical analysis of Xi’an Metro Line 1 reveals that resistance capacity and resilience capacity are critical to fire resilience, with fire cause investigation and post-incident review exhibiting the highest weights. Meanwhile, resilience enhancement strategies are proposed, including optimized monitoring equipment deployment, strengthened emergency drills, and improved personnel training. The paper innovatively integrates WSR methodology and 4M theory to establish a comprehensive, representative metro fire resilience assessment system with CIA-ANP quantification. This study provides novel methodological support for fire safety assessment in urban underground rail transit systems, offering significant theoretical and practical value. 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

Designing fire evacuation strategies for hospitals involves navigating complex infrastructure and accommodating the unique needs of patients, many of whom may have limited mobility or require specialized support during emergencies. This study examines critical egress parameters and their impact on evacuation efficiency in hospital environments, emphasizing configurations that can improve safety and reduce evacuation time. Although the inclusion of smoke effects in recent evacuation models is gaining traction, their combined impact with assisted evacuation scenarios in hospital settings remains underexplored. By integrating smoke propagation data into evacuation modelling, we analyze the effects of reduced visibility and smoke spread on egress routes and occupant behavior. Findings show that smoke effects significantly increase evacuation time estimates (around 50%) compared to traditional models (without accounting for smoke effects), highlighting the risk of underestimation in practical applications, particularly in regions where strict codal compliance is lacking. The study also reveals that stairway width, number, and location substantially affect evacuation times, with about 40% reduction achieved by increasing stairway width from 44 to 66 inches. Additionally, situational awareness enhancements, such as real-time information on fire location and safe exits, can improve evacuation efficiency by about 35%. For taller hospital buildings, the findings highlight the need for implementation of situational awareness in addition to optimized egress planning to achieve safe and efficient evacuation strategies. Full article

Effective forest planning in Mediterranean environments requires tools capable of managing ecological complexity, socio-economic pressures, and fragmented governance. This study develops and applies a GIS- and GNSS-based methodological framework for regional forest planning, tested in the “Bosco della Ficuzza, Rocca Busambra, Bosco del Cappelliere, Gorgo del Drago” Regional Nature Reserve (western Sicily, Italy). The main objective is to create a multi-layered Territorial Information System (TIS) that integrates high-resolution cartographic data, a Digital Terrain Model (DTM), and GNSS-based field surveys to support adaptive, participatory, and replicable forest management. The methodology combines the following: (i) DTM generation using Kriging interpolation to model slope and aspect with ±1.2 m accuracy; (ii) road infrastructure mapping and classification, adapted from national and regional forestry survey protocols; (iii) spatial analysis of fire-risk zones and accessibility, based on slope, exposure, and road pavement conditions; (iv) the integration of demographic and land use data to assess human–forest interactions. The resulting TIS enables complex spatial queries, infrastructure prioritization, and dynamic scenario modeling. Results demonstrate that the framework overcomes the limitations of many existing GIS-based systems—fragmentation, static orientation, and limited interoperability—by ensuring continuous data integration and adaptability to evolving ecological and governance conditions. Applied to an 8500 ha Mediterranean biodiversity hotspot, the model enhances road maintenance planning, fire-risk mitigation, and stakeholder engagement, offering a scalable methodology for other protected forest areas. This research contributes an innovative approach to Mediterranean forest governance, bridging ecological monitoring with socio-economic dynamics. The framework aligns with the EU INSPIRE Directive and highlights how low-cost, interoperable geospatial tools can support climate-resilient forest management strategies across fragmented Mediterranean landscapes. Full article

This paper presents a novel approach to address the challenges of complex terrain, dynamic wind fields, and multi-objective constraints in multi-UAV collaborative path planning for forest firefighting missions. An extensible algorithm, termed Parallel Vectorized Differential Evolution-based Multi-Objective Jellyfish Search (PVDE-MOJS), is proposed to enhance path planning performance. A comprehensive multi-objective cost function is formulated, incorporating path length, threat avoidance, altitude constraints, path smoothness, and wind effects. Forest-specific constraints are modeled using cylindrical threat zones and segmented wind fields. The conventional jellyfish search algorithm is then enhanced through multi-core parallel fitness evaluation, vectorized non-dominated sorting, and differential evolution-based mutation. These improvements substantially boost convergence efficiency and solution quality in high-dimensional optimization scenarios. Simulation results on the Phillip Archipelago Forest Farm digital elevation model (DEM) in Australia demonstrate that PVDE-MOJS outperforms the original MOJS algorithm in terms of inverted generational distance (IGD) across benchmark functions UF1–UF10. The proposed method achieves effective obstacle avoidance, altitude optimization, and wind adaptation, producing uniformly distributed Pareto fronts. This work offers a viable solution for emergency UAV path planning in forest fire rescue scenarios, with future extensions aimed at dynamic environments and large-scale UAV swarms. Full article

In industrial production, flue gas heat exchangers are often affected by the low-temperature condensation of industrial flue gas due to the influence of the working environment, resulting in serious ash deposition and corrosion. In order to solve this problem, in this study, we developed an ash deposition and corrosion monitoring system to compare the ash deposition prevention performance and corrosion resistance of different materials, as well as its influence on the heat transfer performance of different materials in the same environment. The following coatings were selected for the experiment (values in parentheses are the concentrations of the added compounds): ND, Q235, 316L, Ni-Cu (0.4 g/L)-P, Ni-P-SiO₂ (40 g/L), Ni-Cu (0.4 g/L)-P-SiO₂ (20 g/L), Ni-Cu (0.4 g/L)-P-SiO₂ (40 g/L), and Ni-Cu (0.4 g/L)-P-SiO₂ (60 g/L). The results show that the Ni-Cu (0.4 g/L)-P-SiO₂ (40 g/L) coating has excellent corrosion resistance, while the Ni-Cu (0.4 g/L)-P-SiO₂ (60 g/L) coating shows excellent antifouling performance. Through the comparative analysis of polarization curves, impedance spectra, and coupled corrosion experiments, the test materials were ranked as follows based on their corrosion resistance: 316L > Ni-Cu-P-SiO₂ (40 g/L) > Ni-Cu-P-SiO₂ (20 g/L) > Ni-P-SiO₂ > Ni-Cu-P-SiO₂ (60 g/L) > Ni-Cu-P > ND > Q235. It was also demonstrated that the new coated pipes were able to reduce the exhaust temperature below the dew point and maximize the recovery of energy from the exhaust gas. The acid–ash coupling mechanism of the coating in the flue gas environment was further analyzed, and an acid–ash coupling model based on Cu and SiO₂ is proposed. This model analyzes the effect of the coating under the acid–ash coupling mechanism. Using coated tubes in heat exchangers helps to recover waste heat from coal-fired boilers, enhance heat exchange efficiency, extend the service life of heat exchangers, and reduce costs. Full article

Massive wildfires release enormous amounts of biomass-burning (BB) aerosols into the atmosphere, which might have a major impact on its thermal and radiative budget, as well as the environment and human health. This work presents the results of a study and characterization of a long-range transport episode of smoke aerosols from Canadian forest fires towards the entirety of Europe, as observed over Sofia, Bulgaria, in early October 2023. This study makes use of data from combined lidar, ceilometer, and sun-photometer measurements, supported by model and forecast data, meteorological radiosonde profiling, and (re)analyses, together with tracking and mapping of the aerosol air transport. A distinctive feature of the considered episode over Europe is the downward movement of the air masses, entraining smoke aerosols from the continental mid-troposphere down to the near-surface layers. The driving mechanism of the long-range transport of BB aerosols and their spread over Europe is revealed. Optical parameters of the registered aerosols are determined and vertically profiled with a high range resolution by lidar data analysis. A wide set of columnar optical and microphysical aerosol characteristics is also provided by sun-photometer measurements. The results show a dominance of relatively fine modes of dry smoke particles in the submicron size range, with a predominantly low degree of non-sphericity, indicating minimal up-size aging during the BB aerosol transport from Canada to the Sofia region. The average daily aerosol radiative forcing is determined by sun-photometer measurements and briefly discussed. Full article

Polycyclic aromatic hydrocarbons (PAHs) are increasingly recognized as a major contributor to the occupational cancer risk among firefighters. In response, the National Fire Protection Association (NFPA) and other regulatory bodies have recommended rigorous decontamination protocols to minimize PAH exposure. Despite these efforts, a critical gap persists: the absence of real-time, field-deployable devices capable of detecting these invisible and toxic compounds during firefighting operations or within fire stations. Additionally, the lack of effective and optimized methods for the removal of these hazardous substances from the immediate environments of firefighters continues to pose a serious occupational health challenge. Although numerous studies have investigated PAH detection in environmental contexts, current technologies are still largely confined to laboratory settings and are unsuitable for field use. This review critically examines recent advances in PAH decontamination strategies for firefighting and explores alternative sensing solutions. We evaluate both conventional analytical methods, such as gas chromatography, high-performance liquid chromatography, and mass spectrometry, and emerging portable PAH detection technologies. By highlighting the limitations of existing systems and presenting novel sensing approaches, this paper aims to catalyze innovation in sensor development. Our ultimate goal is to inspire the creation of robust, field-deployable tools that enhance decontamination practices and significantly improve the health and safety of firefighters by reducing their long-term risks of cancer. Full article

Underground mining environments are highly hazardous, often prone to gas explosions, cave-ins, and fires that may trap miners during emergencies. The accurate, real-time localization of miners is vital for effective self-escape and rescue operations. Although the Mine Improvement and New Emergency Response (MINER) Act of 2006 mandates communication and tracking systems, most current solutions rely on low-power devices and line-of-sight methods that are ineffective in GPS-denied, dynamic subsurface conditions. Delay-Tolerant Networking (DTN) has emerged as a promising alternative by supporting message relay through intermittent links. In this work, we propose a deep learning framework that combines Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks to predict miner locations using simulated DTN-based movement data. The model was trained on a simulated dataset of 1,048,575 miner movement entries, predicting miner locations across 26 pillar classes. It achieved an 89% accuracy, an 89% recall, and an 83% F1-score, demonstrating strong performance for real-time underground miner localization. These results demonstrate the model’s potential for the real-time localization of trapped miners in GPS-denied environments, supporting enhanced self-escape and rescue operations. Future work will focus on validating the model with real-world data and deploying it for operational use in mines. Full article

To enhance the understanding and management of fire risks in subway stations, this study aims to identify critical fire risk transmission paths using an integrated PSR–DEMATEL–ISM approach. A comprehensive evaluation framework is first constructed based on the Pressure–State–Response (PSR) model, systematically categorizing 22 influencing factors into three dimensions: pressure, state, and response. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is then employed to analyze the causal relationships and centrality among these factors, distinguishing between cause and effect groups. Subsequently, Interpretive Structural Modeling (ISM) is applied to organize the factors into a multi-level hierarchical structure, enabling the identification of risk propagation pathways. The analysis reveals five high-centrality and high-causality factors: fire safety education and training, completeness of fire management rules and regulations, fire smoke detection and firefighting capability, operational status of monitoring equipment, and effectiveness of emergency response plans. Based on these key drivers, six major transmission paths are derived, reflecting the internal logic of fire risk evolution in subway environments. Among them, chains originating from Fire Safety Education and Training (S6), Architectural Fire Protection Design (S7), and Completeness of Fire Management Rules and Regulations (S16) exhibit the most significant influence on system-wide safety performance. This study provides theoretical support and practical guidance for proactive fire prevention and emergency planning in urban rail transit systems, offering a structured and data-driven approach to identifying vulnerabilities and improving system resilience. Full article