Search Results (434)

This study develops a reproducible and auditable workflow to prepare regulatory air-quality monitoring time series for subsequent temporal analysis, including observational PRE/POST applications around coal-fired power plant closures in northwestern Spain. The dataset comprises daily concentrations from 28 monitoring stations (2006–2023) for PM₁₀, PM_2.5, NO, NO₂, NO_x, O₃, SO₂, and CO, affected by missingness, structural inconsistencies, and extreme values. The contribution of this study lies in integrating standardized data ingestion and QA/QC chained-equation imputation with Bayesian Ridge regression, hold-out validation, physicochemical consistency checks, and robust extreme-value handling within a traceable processing workflow. Missing values are reconstructed per pollutant using plant-level multi-station pooling to improve stability. Performance is evaluated using a 5% masked hold-out and summarized with MAE, RMSE, R², and bias, complemented by an operational fit-quality label. Post-imputation controls enforce NO–NO₂–NO_x consistency and the physical constraint PM_2.5 ≤ PM₁₀, while extreme values are screened through a hierarchical robustness framework combining a Hampel filter, winsorization, and a Tukey IQR criterion. The workflow outputs documented diagnostics and robust daily series while preserving the traceability of observed values, flags, edits, and final decisions. Full article

Background/Objectives: Survival after out-of-hospital cardiac arrest (OHCA) is strongly influenced by the no-flow interval—the time between cardiac arrest and initiation of cardio-pulmonary resuscitation (CPR)—with the probability of good neurological outcome decreasing by 13% per minute without circulation. Rapid mobilization of all available responders is therefore critical. Fire services, due to their widespread local presence, can shorten response times, but turnout times—particularly in departments staffed with volunteers—may limit their benefit. In sparsely populated regions, dual dispatch of emergency medical service (EMS) and fire services may help reduce arrival times and thus improve outcomes. Methods: Response times to 1000 hypothetical OHCAs in Lower Austria (19,000 km², 1.73 million population) were modelled. Travel times were calculated from 121 EMS stations and 1590 fire stations using the fastest route. Turnout times were set at two minutes for EMS and five minutes for fire services, with a sensitivity analysis for eight minutes for fire services. For each event, the shortest travel time was compared for both single EMS and dual EMS and fire service dispatch. Results: Mean response time was 10.6 min (SD 4.7) for EMS alone vs. 7.2 min (SD 2.2) with dual dispatch (p < 0.0001). At the 90th percentile, times were 16.8 vs. 9.7 min. Within 10 min, 49.0% of cases were reached by EMS alone vs. 92.6% with dual dispatch; fire services arrived first in 62.7% of all simulations. With an 8 min turnout, mean dual-dispatch arrival increased to 8.8 min (SD 2.9), with 68.2% of all patients reached within 10 min and firefighters arriving first in 42.9%. Conclusions: Dual dispatch of fire services and EMS significantly reduced response times, particularly in areas with a low population density. Using a dual dispatch strategy, response times were below 10 min in nearly all of the patients. Full article

Accurately assessing the accessibility of fire services is critical for enhancing urban safety and the resilience of the built environment. However, existing studies often lack a systematic analysis of spatiotemporal dynamics across an entire municipality. To address this gap, this study develops a citywide dynamic assessment framework for Shanghai, integrating GIS with real-time traffic data across 240 consecutive intervals to assess the service accessibility of 195 fire stations in relation to 7973 key units of fire safety. The principal findings are threefold. First, the results reveal significant urban–suburban heterogeneity in emergency response times. Notably, the proximity advantage of fire stations in central urban areas is offset by traffic congestion, and the marginal benefit of traffic speed improvement exhibits a sharp decline once the average speed exceeds a critical threshold of 13.7–21.0 km/h. Second, the accessibility ratio demonstrates a clear temporal pattern, being highest on holidays and lowest during weekday peak hours, and follows a nonlinear spatial decline from the urban centre to the periphery. This pattern is influenced more critically by the matching of supply and demand than by fire station density alone. Third, the analysis identifies dynamic vulnerability hotspots, which display a ‘bimodal (M-shaped)’ pattern on weekdays and a ‘unimodal (A-shaped)’ pattern on weekends and holidays. This spatiotemporal mismatch shows that central urban areas, despite higher station density, can suffer from both high fire risk and low accessibility, revealing structural patterns consistent with the ‘Inverse Care Law’ in emergency service provision. This study concludes that merely improving traffic conditions is insufficient; optimising the spatial matching of resources is paramount for effective urban disaster prevention. By developing a refined dynamic assessment framework, this study advances current knowledge by focusing on demand locations consistent with actual fire regulatory priorities and examining spatiotemporal patterns across both urban and suburban areas, thereby providing quantitative, evidence-based support for the strategic planning of fire stations and the enhancement of infrastructure resilience. Full article

Port-area hydrogen refueling stations face low-frequency but high-consequence events when high-pressure leaks ignite as jet fires in wind-exposed, constrained environments. This study develops a consequence-based framework coupling theoretical screening, CFD combustion analysis, and hazard zoning to support separation-distance setting and emergency planning. A jet-fire model estimates flame-impingement distances for multiple leak diameters, and a weighted multi-point radiation model predicts heat-flux fields, from which lethal and irreversible-injury zones are delineated using thresholds of 7 and 5 kW/m², respectively. To move beyond wind-free screening, steady reacting-flow CFD is conducted for a representative release under four ambient conditions, with 4.34 m/s adopted as the representative wind speed for the windy cases based on Ningbo Port conditions. Validation against a visible-flame correlation defined by T ≥ 1573 K shows a deviation of 6.99%. Results show that radiation footprints expand markedly with diameter, with lethal and injury distances scaling approximately linearly within the studied range. Under wind, near-ground hot-plume extents defined by T ≥ 388 K and T ≥ 582 K depend strongly on wind direction and station geometry, whereas visible flame length is less sensitive. Additional sensitivity analyses indicate that the quasi-steady results are weakly affected by the selected ignition snapshot, while inclined releases modify projected plume/flame extents without altering the main engineering interpretation of the baseline case. The results support theory-based preliminary screening, but wind direction should be explicitly considered in exclusion-zone definition. Full article

Underground parking garages in high-density megacities are high-risk environments where strong confinement and large fire loads pose severe safety threats. In this study, an evaluation model is proposed based on the entropy weight method combined with dynamic traffic conditions to determine the regional fire service accessibility index $C_j$. Taking Shenzhen, a megacity in China, as the study area, POI data were used to identify 510 fire stations as supply points and 3378 underground parking garages as demand points, yielding 165,522 samples across 49 evaluation scenarios. The results show that the overall average travel time, distance, and velocity are 388.17 s, 2217.95 m, and 5.84 m/s. $C_j$ fluctuates between 0.572 and 0.813, demonstrating clear time-of-day differences. The overall average $C_j$ for all 49 scenarios is 0.697, corresponding to Grade “C”, representing the general level of regional fire service accessibility. It is recommended that additional fire resources be deployed during peak hours and that fire station layouts in peripheral areas be optimized to improve fire safety in underground parking garages. Full article

With rapid economic development in China’s coastal regions, more oil stations are being built on soft soil foundations, facing risks such as foundation settlement and pipeline failures. Mechanical vibrations of oil pumps can induce resonance in pipelines, leading to rupture, leakage, and fire or explosion, threatening both safety and sustainable operation. Traditional monitoring methods, relying on physical models or data-driven approaches alone, are limited in capturing these coupled risks. This study proposes an ABC-XGBoost hybrid risk warning model, where the artificial bee colony algorithm optimizes XGBoost hyperparameters (iteration number, tree depth, learning rate) to improve predictive accuracy. By using multidimensional data—such as internal pressure, vibration amplitude, and ground settlement—the model evaluates stress and resonance risks in real time, supporting sustainable safety management. Validation with real station data shows an accuracy of 95.22%, 2.61% higher than the unoptimized model, demonstrating effective early warning and contribution to sustainable pipeline operation. Full article

DUR (Deep Underground Railways) stations, such as Suseo Station in Korea, present unique evacuation challenges stemming from multi-level spatial depth, long vertical circulation paths, and rapid smoke spread dynamics. Conventional design guidelines often fail to capture these complexities, underscoring the need for advanced, simulation-driven safety evaluation frameworks. This study proposes a comprehensive Digital Twin-based methodology that integrates spatial topology modeling, agent-based evacuation simulation, and dynamic hazard-aware routing. A multi-layer map topology was constructed from high-fidelity architectural geometry, decomposing the station into functional regions and encoding connectivity across platforms, concourses, corridors, and vertical circulation elements. Real-time hazard conditions were reflected through dynamic adjustments to edge weights, allowing evacuation paths to adapt to blocked exits, fire shutter operations, and smoke-infiltrated domains. Ten evacuation scenarios were developed to assess sensitivity to fire origin, exit availability, vertical circulation failures, and onboard passenger loads. Simulation results reveal that evacuation performance is primarily constrained by vertical circulation bottlenecks, with emergency stairways (E1 and E2) serving as critical choke points under high-density conditions. Cases involving exit closures or fire-compartment failures produced significant delays, frequently exceeding NFPA 130 and KRCODE performance criteria. Conversely, guided evacuation strategies demonstrated marked improvements, reducing congestion and enabling compliance with platform evacuation thresholds even in full-load scenarios. These findings highlight the necessity of transitioning from static design evaluations toward Digital Twin-enabled, predictive safety management. The proposed framework enables real-time visualization, intervention testing, and operator decision support, offering a scalable foundation for next-generation evacuation planning in extreme-depth railway infrastructures. Full article

Injection-molding purges are heterogeneous, bulky residues whose uncertain composition and irregular geometry hinder direct reinsertion, making cold shredding costly and maintenance-intensive. This work develops a low-infrastructure solar-assisted pre-processing route using a PMMA Fresnel lens to induce controlled sub-onset softening and enable clean shear cutting without destructive thermal histories. The sub-onset softening is here defined into a viscoelastically active range (at or above T_g for the amorphous phase) while remaining below the melting onset (T_m, onset) and below the onset of thermal degradation (T_d, onset). The station was engineered via QFD and risk-oriented design tools, while a weighted Pugh matrix selected shear cutting over saw-based alternatives. A screening factorial DOE showed that lens height, angle, and their interaction significantly govern focal-spot diameter and receiver temperature, yielding linear relations for conservative set-point selection. Receiver benchmarking further indicated that copper reaches substantially higher temperatures than graphite under identical exposure conditions, supporting copper as the simplest, rapid-heating receiver. Under DOE-calibrated operation, tear-free shear cutting was achieved across representative purge families (PP–ABS, PC–ABS–PP, PA66, PA66-filler, and POM) without forced convection. From a recycling and waste-management perspective, the approach converts bulky purge scrap into mill-compatible feedstock with reduced mechanical resistance, lowering tool wear and fines generation, accelerating downsizing, and limiting stockpiling that elevates combustible-inventory fire risk. Overall, the proposed DOE-calibrated, operator-friendly framework improves recycling feasibility by enabling safer handling, more stable preprocessing throughput, and reduced reliance on disposal or long-term storage for heterogeneous industrial purges. Full article

This article addresses issues related to power supply reliability for electronic security systems (ESSs) during their operational lifetime. ESS are deployed both in enclosed building structures, where environmental conditions are stabilised, and across large open areas exposed to natural environmental conditions, such as transport depots, airports, railway stations, ports, and other similar facilities. Laboratory tests on selected power supply units used in ESSs have been conducted by the authors, as well as a theoretical analysis of the reliability of the power supply process. The reliability analysis of the power supply took into account the reliability of delivering electrical energy with specified parameters to all components forming a system aimed at ensuring the safety of electronic security systems (ESSs). Power supply is essential for the correct operation of all modules, components, devices, and alarm control panels (ACPs) within ESSs. In addition to meeting the basic requirements for the provision of electrical power, the system designer must also give particular consideration to power supply reliability, especially in facilities classified as part of the state critical infrastructure (CI). This issue is particularly significant in the case of Fire Detection and Alarm Systems (FASs), which constitute the most critical safety systems responsible for protecting human life and health. Accordingly, this article discusses selected aspects of power supply for representative electronic security systems (ESSs). The subsequent part of this paper presents operational tests of selected ESS power supply units. A further topic addressed in the article is the definition of models of the operational process of power supply systems and the execution of computer simulations. The analysis of the operational process of ESS power supply units, expressed as models and graphs and supported by computer simulations, enabled the formulation of conclusions regarding reliability. The conclusions drawn from this article may be applied in the design, routine maintenance, and operation of ESSs. Full article

The effective delineation of fire station response zones is critical for urban public safety planning, yet traditional methods often fail to account for dynamic traffic conditions, leading to suboptimal resource allocation. This study proposes a novel block-unit-based method that incorporates real-time traffic data to delineate fire station response zones, improving the scientificity of response time estimation. The method was validated using data from Daxiang District, China, a typical urban–rural mixed region, encompassing 2230 block units, 4 fire stations, and 13,097 demand points. Analysis of 1,225,047 data samples revealed an average travel time of 960.7 s, highlighting significant accessibility challenges. The re-delineated response zones cover areas ranging from 1.07 to 156.24 km², with significant variations. It is attributed to the concentration of fire stations in urban areas, insufficient coverage of vast rural regions, and the proximity of one station to a river and regional boundary. These findings underscore the spatial inequities in fire service provision and the need for a more balanced resource allocation strategy. Recommendations include establishing rural fire stations, improving urban traffic conditions, and relocating certain fire stations. This approach can enhance regional accessibility and provides a scientific basis for fire service planning. Full article

In a world of over 8.2 billion people, the land footprint of any infrastructure has become a critical factor in sustainable spatial planning. In the case of wind energy deployment, land use primarily involves hardstands, access roads, and interconnection infrastructure. This study focuses on Greece, a country with complex mountainous terrain, where Wind Power Stations are predominantly installed along ridgelines and slopes. Using GIS analysis based on digitization of actual on-site infrastructure, we measured the land coverage of wind energy facilities with a total installed capacity of nearly 2.6 GW. We found an average land-use intensity of 0.33 hectares per megawatt (ha/MW), placing it near the lower end of the range reported in international literature. For the subset of projects with available energy yield data, the value was 1.58 square meters per megawatt-hour (m²/MWh). This approach provides one of the largest, nationally representative, infrastructure-based estimates of actual wind energy land use in complex terrain. Applying these findings to the onshore wind deployment targets of Greece’s National Energy and Climate Plan (NECP) for 2030 and 2050, we estimate that only 0.02–0.03% of the country’s land area will be occupied by wind energy infrastructure. By comparison, lignite mining has already transformed approximately 0.13% of the national territory—almost four times more land than projected for wind energy use in 2050. Further spatial analysis was conducted to identify the land use categories associated with wind energy infrastructure, while for the subset of projects located within Natura 2000 protected areas, the types of affected habitats were also examined. Treating land coverage as a standalone proxy for environmental impact should be avoided; the study demonstrates the need for a context-sensitive interpretation of land use, accounting for ecological context, land-use compatibility, and positive co-benefits, such as improved forest accessibility, fire prevention works and recreation parks. Repowering maximizes land efficiency by extending wind farm lifetimes without expanding their footprint. Full article

To address the critical demand for real-time dynamic tracking of personnel in complex buildings during emergency rescue, a novel system was proposed integrating Back Propagation (BP) neural networks with Double-Sided Two-Way Ranging (DS-TWR) technology to achieve precise indoor localization and motionless detection. Comprising hardware (positioning base stations, tags, POE switches, routers, and a computer) and software (developed on LabVIEW), the system leverages the symmetric signal transmission of DS-TWR and the adaptive learning capability of BP neural networks to effectively mitigate multipath interference, enhancing positioning consistency and accuracy. Thresholds of time period and movement distance were set to determine whether the occupant was trapped. When tested in several common building structures, it demonstrated good stability and high accuracy—the average RMSE of the positioning system was within 0.012–0.018 m (static state) and 0.048–0.065 m (dynamic state). Furthermore, the system could real-time monitor and display the movement trajectory of each person, and automatically alarm when anyone was trapped in a fire scene. Hence, rescue measures can be taken timely according to the alarm information provided by the system, effectively ensuring the safety of personnel and improving the efficiency of fire rescue work. The proposed approach provides a symmetry-driven framework for intelligent building safety. Full article

The combustion of coal comes with a heavy price of pollutant emissions. To assist in the planning and management of these emissions and to protect human health, the current study uses the relatively heavy-tailed distributions, namely, the Weibull, Lognormal and Pareto distributions to analyse and characterise the distribution of NO₂ emission (in tons) from Arnot, a coal-fired power station of South Africa’s power utility, Eskom. Quantile–quantile (QQ) plots and their corresponding derivative plots for the three distributions are used to characterise the statistical distribution of NO₂ emissions. The strength and advantage of using derivative plots of the three distributions, in particular, for characterising NO₂ emissions from a coal-fuelled power station, is that they are able to better capture and explain the behaviour of the data across different components of this data. Although this method possesses flexible ways of characterisation of data, it is not commonly applied to emissions data, especially NO₂ emissions from a coal-fuelled power station belonging to Eskom, such as Arnot. The choice of the distributions of this study is motivated by their ability to cater to varied tails relative to the exponential distribution. Thus, the tail heaviness ranks of the distributions from lighter to heavier tail, that is, Weibull, Lognormal and Pareto, are taken into consideration in order to arrive at the best-fitting distribution(s). The Weibull distribution with a lighter tail than the Exponential distribution gave the best-fitting distribution over the Lognormal and Pareto distributions for the main body of the data. The Pareto distribution, however, captures the extreme emission tail behaviour much better than the other two distributions. The Kolmogorov–Smirnov and Vasicek–Song (VS) goodness of fit statistics were used to further assess the appropriateness of the fitted distributions. The selection of the Weibull distribution implies that milder high values and less frequent very high NO₂ emission data are expected, showing the weakness of such criteria when extremes are present. For authorities to plan and draw policies for the reduction and management of emissions, these findings may be of interest to them and can assist in better understanding their behaviour and the planning to reduce the impact on humans and the environment. This may also assist practitioners in air quality modelling before other, more sophisticated methods can be explored. Full article

Most machine learning (ML)-based facility location studies utilize uniform grid partitioning, often overlooking spatial heterogeneity. This limitation can compromise the validity and practical applicability of the resulting site selections. In response to this issue, this paper uses fire stations as the research subject and proposes a location prediction method that considers the heterogeneous characteristics within cities. Firstly, the Gaussian Mixture Model (GMM) is adopted based on the Point of Interest (POI) data to determine the clustering centres of the study area. Secondly, a Voronoi diagram is constructed to divide the study area reasonably. Then, a comprehensive feature matrix is constructed by integrating multi-source spatial data and five machine learning models: Random Forest (RF), Gradient Boosting Decision Tree (GBDT), Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost) and Logistic Regression (LR). These are then used for training and evaluation. Finally, the GBDT model with the best performance in terms of both the F1 score and the AUC value was selected to predict the location of fire stations in Chengguan District, Lanzhou City. The results demonstrate the GBDT model’s effectiveness in identifying the rationale behind existing fire station locations and predicting potential new locations. It predicts 12 suitable locations for new fire stations, and the suitability of these predicted locations is validated by comparing them with the existing fire station locations, 8 of which are in the same block as existing fire stations in Chengguan District. Adding micro fire stations at four new predicted locations would improve response efficiency. The results of the feature importance analysis show that road accessibility is the primary factor affecting fire station location selection. This study’s proposed method effectively enhances the reasonableness of fire station site selection and provides a basis for planning fire stations in new urban areas in the future. Full article

Fires caused by electric vehicle (EV) batteries can pose hazardous situations during accidents and during the servicing of critically damaged vehicles. Managing and preventing such fires requires a thorough understanding of the underlying causes and processes. This article analyses lithium-ion (Li-ion) batteries in electric vehicles, demonstrating the effects of cell overheating, the production of runaway gases, and the resulting thermal catastrophe. We examine the composition of cell eruption gases (CEGs) and their implications for fire protection. Based on these findings, we assess the conditions for safe battery storage, safety guidelines for servicing electric and hybrid vehicles, fire suppression methods, and measures following fire suppression. Additionally, we analyze the unique characteristics of EV fire incidents and, based on these, outline the implementation requirements and safety technologies for repair bays designed to service critically damaged electric and hybrid vehicles. Finally, we propose implementing repair stations suitable for safe servicing operations and accrediting such repair bays, including a flowchart detailing the implementation process. Although this concept is still in its early stages, its implementation would significantly enhance the safety of servicing operations and the effective management of hazardous situations. Full article