Hazardous Conditions Research Articles

Early impacts of fire suppression in Jeffrey pine – Mixed conifer forests in the Sierra San Pedro Martir, Mexico

Fire exclusion was first implemented across large areas of California and other areas of western North America in the late 19th or early 20th centuries but few studies have investigated how forests in the early decades after this decision were impacted. Jeffrey pine-mixed conifer forests of northern Baja California, Mexico, offer an area where this can be examined since fire suppression did not begin until the early 1970’s. We use repeated forest and fuel measurements taken over a 25-year period (1998–2023) and found significant changes in forest structure and fuel loads (increased tree density, fine fuel loads, large fuel loads, snag density, snag basal area) that together clearly demonstrate the cumulative effects of fire removal. Interestingly, Jeffrey pine became more dominant despite the lack of recent fire, which is counter to the shift towards more shade-tolerant tree species observed in many other fire-suppressed, frequent-fire forests in the western US. Although these changes in Baja California forests point towards increased fire hazard, they are still in relatively low hazard conditions compared to long-fire suppressed forests in the western US. Prescribed fire or managed wildfire could easily be applied to counter the increased fuel loads and tree densities detected in this work, without the need for mechanical manipulation. In addition to maintaining resilient forests, using fire will reduce the risk of losing the large astronomical observatory at this site to wildfire. Restoration and stewardship of resilient forest structures similar to those in Baja California is the only way forward to conserve similar forests of the Sierra Nevada, southern California mountains, and elsewhere in the western US.

Autonomous mining through cooperative driving and operations enabled by parallel intelligence

Autonomous mining is promising to address several current issues in the mining sector, such as low productivity, safety concerns, and labor shortages. Although partial automation has been achieved in some mining operations, fully autonomous mining remains challenging due to its complexity and scalability in field environments. Here we propose an autonomous mining framework based on the parallel intelligence methodology, employing self-evolving digital twins to model and guide mining processes in the real world. Our framework features a virtual mining subsystem that learns from simulating real-world scenarios and generates new ones, allowing for low-cost training and testing of the integrated autonomous mining system. Through initial validation and extensive testing, particularly in open-pit mining scenarios, our framework has demonstrated stable and efficient autonomous operations. We’ve since deployed it across more than 30 mines, resulting in the extraction of over 30 million tons of minerals. This implementation effectively eliminates the exposure of human operators to hazardous conditions while ensuring 24-hour uninterrupted operation.

Risk Identification of Mountain Torrent Hazard Using Machine Learning and Bayesian Model Averaging Techniques

Frequent mountain torrent disasters have caused significant losses to human life and wealth security and restricted the economic and social development of mountain areas. Therefore, accurate identification of mountain torrent hazards is crucial for disaster prevention and reduction. In this study, based on historical mountain torrent hazards, a mountain torrent hazard prediction model was established by using Bayesian Model Average (BMA) and three classic machine learning algorithms (gradient-boosted decision tree (GBDT), backpropagation neural network (BP), and random forest (RF)). The mountain torrent hazard condition factors used in modeling were distance to river, elevation, precipitation, slope, gross domestic product (GDP), population, and land use type. Based on the proposed BMA model, flood risk maps were produced using GIS. The results demonstrated that the BMA model significantly improved upon the accuracy and stability of single models in identifying mountain torrent hazards. The F1-values (comprehensively displays the Precision and Recall) of the BMA model under three sets of test samples at different locations were 3.31–24.61% higher than those of single models. The risk assessment results of mountain torrents found that high-risk areas were mainly concentrated in the northern border and southern valleys of Yuanyang County, China. In addition, the feature importance analysis result demonstrated that distance to river and elevation were the most important factors affecting mountain torrent hazards. The construction of projects in mountainous areas should be as far away from rivers and low-lying areas as possible. The results of this study can provide a scientific basis for improving the identification methods of mountain torrent hazards and assisting decision-makers in the implementation of appropriate measures for mountain torrent hazard prevention and reduction.

BASSAMI Mohammed, ADRIAUCH Amine, BENKACEM Mariem, AZZIOUAZ Fatima, MIMOUNI Hicham, RKAIN Ilham (2024), Mandibular Mass Revealing Vesicular Thyroid Carcinoma A Case Report. International Journal of Innovative Science and Research Technology (IJISRT) IJISRT24MAY099, 188-192. DOI: 10.38124/ijisrt/IJISRT24MAY099. https://www.ijisrt.com/mandibular-mass-revealing-vesicular-thyroid-carcinoma-a-case-report

Fault is a regular incidence on distribution power system because distribution lines are always exposed to the environment with high probability of fault occurrence which when it happens, can cause hazardous conditions, equipment failures, power instability, huge financial loss and other forms of setback. In order to avoid these setbacks, it is necessary to detect and locate the fault on the network as fast as possible so as to prevent power system damages and reduce system downtime. This research study designed a smart fault location system model that detected and located ground faults at the point of occurrence using a developed 33 kV Ubulu-Uku radial distribution system as a test feeder and then formulated fault location equations which resulted into one single equation for all ground fault types on the network. The designed algorithm was evaluated on MATLAB 2023a environment using different line impedances of 0.01 Ω, 0.15 Ω, 0.35 Ω, 0.50 Ω, and 0.65 Ω which produced various ground faults located along path 6 section 17, path 8 secAtion 21, path 8 section 21, path 4 section 12 and path 8 section 21 with distance of fault from the main substation obtained at 3.51 km, 3.93 km, 4.03 km, 4.81 km, and 4.21 km. The results presented show performance of the designed algorithm and can be encouraged for practical implementation with promising result which will achieve some benefits like precise fault location information analysis, reduce the overall response time spent by maintenance crew to locate fault and reduce cost of operational maintenance and supply interruptions.

Persistent Vulnerability after Disaster Risk Reduction (DRR) Response: The Case of Salgar, Colombia

Community-based disaster management (CBDM) has replaced traditional models of disaster risk reduction (DRR), giving the community a more participatory role in the planning and implementation of risk mitigation and preparedness strategies, disaster response, and post-disaster recovery measures. This shift in disaster response approaches has impacted understandings of vulnerability and resilience, leading scholars and policy makers to move away from a physical definition of vulnerability and to incorporate social variables. However, in Colombia, a traditional DRR approach still prevails. The National Risk Management Policy employs a top-down approach to risk reduction and disaster management, relying on the action of governmental authorities without community participation in the design or implementation of risk management planning and strategy. This article reveals the deficiencies of traditional DRR approaches. The Colombian government’s post-disaster resettlement project after a 2015 landslide in Salgar, Antioquia that resulted in 98 people dead or missing did not contribute to the reduction of vulnerability for the resettled community. To accurately measure post-disaster vulnerability and resilience, a new holistic model of indicators that includes both social and biophysical variables that illustrate and measure the relevance of preexisting vulnerabilities was developed. Local data was collected through 178 surveys administered to the inhabitants of Salgar’s three post-disaster resettlement sectors—La Habana, La Florida, and Las Margaritas—to construct an accurate picture of the populations affected by the disaster. Our results show that in the case of Salgar, social vulnerabilities persist even in the physical components of the resettlement sites where new infrastructure would be expected to reduce hazardous conditions and exposure to risk.

Effect of risk management on the performance of civil servants in Enugu State Nigeria

The study examined the effect of Risk Management on the performance of civil servants in Enugu State. The study used the descriptive survey design approach. The primary source of data was the administration of questionnaire. The population of the study was six hundred and twenty (620) staff from various ministries in the State Secretariat, Enugu, Enugu state. The sample size of 290, was used using Freund and William's statistic formula at 5 percent margin of error. 286 staff returned the questionnaire and accurately filled. Data were presented and analyzed using Likert Scale and the hypotheses was tested using Z- test. The findings indicated that, Risk identification had significant positive effect on the output, Z( 95, n = 286), 6.120 < 8.840,P. < .05. Risk monitoring had significant positive effect on the cost reduction, Z( 95, n = 286), 4.376 < 6.682,P. < .05 and Risk reporting had significant positive effect on the efficiency of civil servants in Enugu State, , Z( 95, n = 286), 6.268 < 8.249,P. < .05. The study concluded that Risk identification, Risk monitoring and Risk reporting had significant positive effect on the output, cost reduction and efficiency of civil servants in Enugu State. The study recommended among others that the management should identify potentially hazardous working conditions and practices to avoid damage to the organisations property or injury to personnel. Pre-empting risks can help the workers to comply with rules and regulations, which can lead to better and higher work production.

Studies on Cr (VI) removal by constructed wetland integrated microbial fuel cell: Effect of electrodes

Heavy metal contamination significantly threatens human health and the environment, even at low concentrations. Among these metals, hexavalent chromium (Cr (VI)), primarily originating from mining activities, stands out as a significant concern. The Constructed Wetland-Microbial Fuel Cell (CW-MFC) represents an engineered solution inspired by natural wetlands. This study presents a novel approach to utilizing cement-graphite (CG) electrodes in CW-MFC to reduce Cr (VI). In this study, Cr (VI) spiked synthetic wastewater (25 mg/L to 100 mg/L) was treated using CG-CW-MFC (Cement-Graphite) and G-CW-MFC (Graphite) systems, at a constant hydraulic retention time of 48 hours. The results indicated that both CG-CW-MFC and G-CW-MFC exhibited a removal efficiency of 99% for Cr (VI). COD removal rates for CG-CW-MFC and G-CW-MFC ranged from 89% to 94% and 82.5–91.35%, respectively. Meanwhile, CG-CW-MFC showed stable voltage generation at 100 mg/L of Cr (VI) (Average voltage 191.45 mV), while G-CW-MFC showed a steep reduction in voltage generation with an average voltage of 1.48 mV. Thus, the study concludes that, in contrast to the G-CW-MFC electrode, the CG electrode can generate voltage under highly hazardous conditions because of the porous structure of CG. The findings of this study highlight the potential of CG electrodes in CW-MFC systems designed to remediate wastewater contaminated with Cr (VI).

Understanding the Impact of Seismic Hazard and Climate Conditions on Multi Criteria–Based Retrofitting of Existing Buildings

A large share of the reinforced concrete (RC) building stock in Mediterranean countries faces a dual challenge of seismic vulnerability and energy inefficiency, calling for urgent renovation efforts. While energy upgrades have been the focus of previous renovation policies, recent research highlights the critical need for integrated retrofitting solutions that address both structural integrity and energy performance. Multi-criteria decision-making (MCDM) approaches are a promising tool for optimizing the combined choice of these integrated interventions, considering various decision variables (DVs) of economic, social, environmental, and technical nature. To understand the impact of climate and seismic hazard conditions on multi-criteria-based retrofitting assessment, a case-study RC school building is selected and assumed to be located in three distinct climate conditions, cold, mild, and warm, and three seismic hazard levels, low, medium and high. Moreover, given the complexity and challenges of quantifying seismic performance metrics for practitioners, an available simplified (practice-oriented) approach is compared herein with a more thorough research-based one for quantifying the seismic performance of RC buildings within the MCDM framework. Both approaches are applied to the case-study building, considering twelve possible combinations of energy and seismic interventions. The accuracy of the practice-oriented approach and its impact on the retrofitting rankings is evaluated, emphasizing the importance of accessible and efficient evaluation methods in facilitating informed decision-making for building renovation.

Path to autonomous soil sampling and analysis by ground-based robots

Good site characterization is essential for the selection of remediation alternatives for impacted soils. The value of site characterization is critically dependent on the quality and quantity of the data collected. Current methods for characterizing impacted soils rely on expensive manual sample collection and off-site analysis. However, recent advances in terrestrial robotics and artificial intelligence offer a potentially revolutionary set of tools and methods that will help to autonomously explore natural environments, select sample locations with the highest value of information, extract samples, and analyze the data in real-time without exposing humans to potentially hazardous conditions. A fundamental challenge to realizing this potential is determining how to design an autonomous system for a given investigation with many, and often conflicting design criteria. This work presents a novel design methodology to navigate these criteria. Specifically, this methodology breaks the system into four components – sensing, sampling, mobility, and autonomy – and connects design variables to the investigation objectives and constraints. These connections are established for each component through a survey of existing technology, discussion of key technical challenges, and highlighting conditions where generality can promote multi-application deployment. An illustrative example of this design process is presented for the development and deployment of a robotic platform characterizing salt-impacted oil & gas reserve pits. After calibration, the relationship between the in situ robot chloride measurements and laboratory-based chloride measurements had a good linear relationship (R2-value = 0.861) and statistical significance (p-value = 0.003).

Bridging depths and data in mines: 5G-based point cloud mapping in unstructured environments

Underground mines pose significant challenges, including hazardous working conditions, limited access, and the need to ensure the safety of human workers. Digital transformation through the integration of modern technologies is essential to mitigate these challenges and enhance the overall safety and efficiency of mining operations. This paper addresses the pressing need for 5G connectivity for the digital transformation of underground mines and demonstrates its application through a live 3D point cloud mapping by a mobile robot. The results of the experiments conducted to validate the network’s performance for such a use-case are presented. The first experiment involved testing the latency of the network over a test drift at various loads. The second experiment involved mapping the drift and streaming the 3D point cloud map of the drift over the 5G network. These initial experiments emphasize the potential of the 5G-enabled automation in underground mines and holds promise in digitalizing underground mining operations.

Risky business: How food-delivery platform riders understand and manage safety at work

This study explores the issue of workplace safety among food-delivery workers who use platforms like UberEATS and Deliveroo to secure work. Despite the high exposure to hazardous traffic, extreme weather conditions, and unsafe work hours and locations that these workers face daily, safety remains a low priority for both platforms and governments. This study utilizes in-depth qualitative interviews with 14 platform food delivery workers in Melbourne, Australia, to examine how they understand and manage safety risks at work, drawing on a theoretical framework of necropolitics and liminal precarity. The riders are predominantly migrant workers on temporary visas who face corporeal risks influenced by factors such as road conditions, time pressures, and weather. Despite their awareness of these dangers, the study reveals that platform-induced necropower, driven by economic incentives, significantly impacts those heavily dependent on gig economy earnings, ultimately turning safety into a trade-off between making a living and surviving. However, riders also demonstrate agency by mediating risks through experience, knowledge-sharing, and strategic use of the platform's features to resist potentially hazardous conditions.

Antioxidant vitamins in Benin bronze casters and their environmental cohorts: A preliminary nutritional assessment

The process of bronze casting often leads to prolonged exposure to air pollutants, heavy metals, and potentially hazardous working conditions. Understanding the levels of antioxidant vitamins among the Benin bronze casters is vital because their exposure to environmental pollutants and potential occupational hazards may increase their oxidative stress levels. Therefore, this study aimed to evaluate the levels of antioxidant vitamins; A, C, and E in Benin bronze casters. A total of ninety (90) consenting participants were recruited for this study; They included foundry workers (bronze casters), randomly selected individuals around the foundry site (environmental), and healthy unexposed individuals (control). Vitamins A, C, and E levels were determined using pectrophotometry. Data obtained was analyzed using Statistical Package for Social Science (SPSS) software. The findings revealed that vitamin A levels were significantly lower in bronze casters (36.06±9.15) when compared to environmental (58.57±41.05) and control groups (62.61±51.12) (p<0.05). Vitamin C levels were significantly lower in bronze casters (0.53±0.14) when compared to the environmental group (1.02±0.53) and the control group (1.55±0.37) (p<0.05). Also, there was a significant reduction in vitamin C levels in the environmental group when compared to the control group (p<0.05). Vitamin E levels were significantly lower in bronze casters (5.14±1.92) and environmental (6.28±3.32) groups when compared to the control group (11.49±3.75) (p<0.05). There was a strong positive correlation between vitamin A and vitamin C (r=-0.589, p=0.001). Vitamin C showed a strong positive correlation with vitamin E levels (r=0.562, p=0.001). In conclusion, the lower vitamin levels suggest an increased vulnerability to oxidative stress, which occupational hazards and environmental factors, such as exposure to metal toxins and pollutants may exacerbate.

Real-Time Perception Enhancement in Obscured Environments for Underground Mine Search and Rescue Teams

First responders in underground mines face a myriad of challenges when searching for personnel in a disaster scenario. Possibly, the most acute challenge is the complete lack of visibility owing to a combination of dust, smoke, and pitch-black conditions. Moreover, the complex environment compounds the difficulty of navigating and searching the area as well as identifying hazardous conditions until in close proximity. Enhanced perception and localization technologies that enable rapid and safe disaster response could mitigate the mine rescue team’s risk and reduce response times. We developed a proof of concept perception enhancement tool for mine rescue personnel in pitch-black conditions by leveraging LiDAR, thermal camera, and data fusion to reconstruct a 3D representation of the space in real-time. This enhancement is visualized on HoloLens, allowing the responders real-time situational awareness of personnel, walls, obstacles, or fires in otherwise opaque environments. The technology is a first step towards faster, safer, and more effective disaster response for mine rescue operations, including detection of unexpected hazards before they become imminent threats.

IoT-BASED COAL MINE WORKER MONITORING SYSTEM USING IOT

The coal mining industry faces numerous occupational hazards, with worker safety being a paramount concern. In response to this challenge, this paper proposes an IOT-based Coal Mine Worker Monitoring System (CMWMS) designed to enhance the safety and well-being of coal miners. The system integrates wearable sensors, wireless communication, and data analytics to continuously monitor vital signs, environmental conditions, and location information of mine workers in real time. Through the deployment of wearable devices equipped with sensors for measuring physiological parameters such as heart rate, body temperature, and respiratory rate, along with environmental sensors for detecting gas levels and ambient temperature, the CMWMS provides comprehensive monitoring capabilities. Data collected from these sensors are transmitted wirelessly to a central monitoring station where sophisticated algorithms analyze the information for early detection of potential health risks or hazardous conditions. Additionally, the system incorporates geo-location technology to track the movements of miners within the mine, enabling rapid response in case of emergencies such as accidents or cave-ins. By providing timely alerts and actionable insights, the IOT-based CMWMS empowers mine operators to proactively manage safety risks, mitigate accidents, and safeguard the well-being of coal mine workers. This paper discusses the architecture, components, and functionalities of the proposed system, along with its potential impact on improving safety standards in the coal mining industry. Keywords: Internet of Things, Temperature Sensor, Smoke Sensor, Humidity Sensor, Arduino Microcontroller

Remodelling and functional features of the left ventricle in miners

Introduction. Diseases of the circulatory system are the main cause of mortality in the employable population. Preserving occupational longevity involves the identification of early signs of myocardial damage by modern techniques, which will allow taking a fresh look at the prevention of cardiovascular pathology in people engaged in harmful working conditions. Materials and methods. The study included two hundred thirty six miners of average age of 47.1±0.36 years who underwent periodic medical examination at the Institute clinic. The work experience in hazardous occupation conditions was 22.7±0.6 years. The study was based on transthoracic echocardiography using tissue Dopplerography and speckle tracking technology. Results. Concentric remodelling of the left ventricle was detected in 25.9% of the miners. Arterial hypertension was revealed in 65.6% of the miners with concentric remodelling of the left ventricle versus 34.3% of the miners with its normal geometry (p=0.00002). There were no significant differences in the left ventricular contractile function indices in the groups. In both groups, diastolic dysfunction type 1 was predominantly detected, which was significantly more common in the miners with concentric remodelling of the left ventricle (62.3% and 42.0%, p=0.006). Pseudonormal type of diastolic dysfunction occurred in 8.2% of the group with concentric remodelling versus 5.14% with normal left ventricular geometry, p= 0.38. Limitations. The study was limited by the number of the examined persons undergoing periodic medical examination at the Research Institute for Complex Problems of Hygiene and Occupational Diseases. Conclusion. Remodelling of the left ventricular myocardium in miners did not correlate with a decrease in the longitudinal deformation of the left ventricle, which indicates the possible influence of harmful occupational factors on the development of its systolic dysfunction. Diastolic dysfunction of the left ventricle had a clear relationship with remodelling of the left ventricular myocardium. In this regard, it is recommended to conduct echocardiography during an in-depth periodic medical examination of miners with long-term work experience to identify a risk group for developing cardiovascular accidents.

Assessment of occupational health hazards among printing press workers

Background Workers in printing press are frequently exposed to various occupational health hazards, including physical, chemical, mechanical (ergonomic), biological, and psychological hazards while doing their jobs. Chemical and mechanical hazards pose a significant threat to the health and safety of printing press workers (PPWs). A hazardous working condition not only brings numerous health risks to the workers’ health but also minimizes the enterprise’s productivity. Recognizing these hazards and their consequences is the first step toward creating a safer and healthier work environment for this dedicated workforce. Aim To assess occupational health hazards (OHHs) as reported by PPW. Design A descriptive study design was utilized. Sample A purposive sample of 299 was approached for the current study. Tools Printing Press Workers Structured Questionnaire. Results Workers at the printing press were exposed to different types of OHHs, 44.6% of PPWs were exposed to chemical hazards, 46.3% were exposed to mechanical hazards, 58.5% were exposed to accidents in the workplace, and 39.5% had work accidents due to machines. Regarding causes of chemical hazards, 61.5, 55.2, 89.0, and 57.2% of PPWs were always exposed in the workplace to dust, organic solvents, ink, and lead, respectively. As for the causes of mechanical hazards, 61.9% of the study sample always have work that requires carrying heavy objects, 63.9% have a job that always requires a fixed work situation, and 61.9% have work that requires vigorous effort or maximum range of motion. Additionally, 68.9% of the study sample always have work that requires pushing or pulling, and 68.9% always have jobs that require similar repetitive movements. There were highly statistically significant positive correlations between the work stage and chemical and mechanical hazards (P=0.00). Conclusion PPWs faced various OHHs and health problems due to their work and environment. Over one-third were exposed to mild chemical hazards, almost half were exposed to moderate chemical hazards and less than one-fifth were exposed to high chemical hazards. Regarding mechanical hazards, over one-third of PPWs were exposed to mild mechanical hazards, another one-third were exposed to moderate mechanical hazards, and almost one-third were exposed to high mechanical hazards. Recommendations Conduct training programs on safety and health measures to increase knowledge and awareness of printing workers to minimize OHHs. Also, ensure effective usage of personal protective equipment (PPE).

Safety Helmet for Miners

Abstract: The safety helmets basically aim at safety of miners reducing the risks of accidents. It also highlights the hazardous environments of mining and potential dangers that the workers face while working in mines. Safety helmets will be containing infrared sensors which keep track of the environment of the miner. It highlights the inherent risks miners face, including poor visibility, potential collisions, and hazardous conditions. The helmets are capable of alerting the miners from dangers. Infrared sensors can sense the heat signatures and obstacles in real-time resulting in spatial awareness. The helmets also consist of Arduino to enable real-time data processing and communication integration. The helmet also consists of LoRa which provide wireless communication between helmets and receiver ends, which would notify them in case of any emergency. The abstract concludes by enhancing the importance of IR-sensors, LoRa and Arduino which interfaces all of the above equipment.

Landslide Deposit Erosion and Reworking Documented by Geomatic Surveys at Mount Meager, BC, Canada

Mount Meager is a deeply eroded quaternary volcanic complex located in southwestern British Columbia (BC) and is known for its frequent large landslides. In 2010, the south face of Mount Meager collapsed, generating a long-runout debris avalanche that was one of the largest landslides (50 × 106 m3) in Canadian history. Over the past 14 years, the landslide deposit has been reworked by stream action, delivering large amounts of sediment to Lillooet River, just downstream. In this study, we investigate 10 years of geomorphic evolution of the landslide deposit using orthophotos and digital elevation models (DEMs) generated using Structure from Motion (SfM) photogrammetry on aerial photographs acquired during unmanned aerial vehicle (UAV) and Global Navigation Satellite System (GNSS) surveys. The SfM products were used to produce a series of precise maps that highlight the geomorphological changes along the lower Meager Creek within the runout area of the landslide. Comparison of DEMs produced from 2010, 2012, 2015, and 2019 imagery allowed us to calculate deposit volume changes related to erosion, transport, and redeposition of landslide material. We estimate that about 1.1 × 106 m3 of sediment was eroded from the landslide deposit over the period 2015–2019. About 5.2 × 105 m3 of that sediment was redeposited inside the study area. About 5.8 × 105 m3 of sediment, mainly sand, silt, and clay, were exported from the study area and are being carried by Lillooet River towards Pemberton, 40 km from Mount Meager, and farther downstream. These remobilized sediments likely reduce the Lillooet River channel capacity and thus increase flood hazards to the communities of Pemberton and Mount Currie. Our study indicates a landslide persistence in the landscape, with an estimated 47-year half-life decay, suggesting that higher flood hazard conditions related to increased sediment supply may last longer than previously estimated. This study shows the value of using SfM in tandem with historic aerial photographs, UAV photos, and high-resolution satellite imagery for determining sediment budgets in fluvial systems.

A model for the prediction of thermal runaway in lithium–ion batteries

The increasing popularity of electric vehicles is driving research into lithium-ion batteries (LIBs). Thermal runaway (TR) in LIBs is a serious concern for the safe operation of these high–energy-density batteries that is yet to be overcome. A reliable model is needed to predict voltage variation, heat generation, temperature rise, and the process leading to TR of a LIB battery under its operating conditions (charging–discharging). Such a model can be used to design battery packs more resilient to thermal runaway or assess how a battery pack would perform under hazardous conditions. Furthermore, it can be used for generating a warning signal if there is a possibility of the battery going towards TR. This paper presents an approach to solving this problem, which is not currently well addressed in the literature. The approach adopted in this paper is based on a numerical analysis of a multilayered electrochemical–thermal model of LIB. Tuning the parameters of a LIB for accurate results from this numerical model is presented, as well as the details of the approach in the paper. Experiments are performed under several LIBs, and their voltage and surface temperature variations are measured under various operating conditions, including thermal runaway. The results of the experiments are compared with the predictions of the numerical simulations. An excellent agreement is observed with the experimental results, proving the accuracy of the proposed approach. This approach can be configured to give results in a few minutes. The paper also discusses how the developed approach can be used to create a TR warning during operating conditions or to change the mode of operation of a LIB before a hazard occurs.

Chemical and olfactometric inventory of gaseous spot vents in Mt. Amiata volcanic-geothermal area (Italy)

Geothermal areas are typically characterised by the presence of gases and odours in the background atmosphere, stemming from natural emissions and possible mining exploitation of the area. This study presents the first olfactometric investigation of endogenous gas emissions from natural and archaeo-industrial vents in a geothermal area. Mt. Amiata is known for its complex geology and historical cinnabar mining. This study offers an inventory of spot gas emissions, not only in terms of odour and chemical concentration but also including flux data, a ground-breaking achievement in this field. The primary challenge of this investigation was estimating the emitted flow from ground holes or mine entrances, posing the risk of hazardous anoxic conditions. To address this challenge, an innovative and adaptive approach was adopted. The main breakthrough method involved the adaptation of a balometer, typically employed for indoor ventilation systems, to measure the flow of endogenous gases. Field surveys revealed odour concentrations that can exceed 106 of ouE/m3, surpassing industrial emission level considerably. Chemical concentrations, primarily consisted of CO2 (80/90 %v/v) and CH4 (∼10%v/v), providing critical insights into the global warming potential (GWP) associated with natural emissions. Moreover, these spots, often located at ground level and lacking a substantial atmospheric dilution, pose potential risks to nearby individuals, with concentrations of gases such as H2S surpassing safety thresholds. Total emissive flux of the investigated spot vents in the Mt. Amiata area, showed that the emission rate of H2S is notably substantial (55 kg/h), roughly equivalent to emissions from approximately four 20 MW geothermal plants, as along with odour emission rates in the order of 107 ouE/s. Considering the GWP derived from emitted gases, the total inventory assessment of the spot vents resulted in 36 t/h or 23 t/h CO2eq, depending on the time horizon considered (GWP20 or GWP100 respectively).