Low-carbon development path based on carbon emission accounting and carbon emission performance evaluation: a case study of Chinese coal production enterprises.

Carbon emission accounting is the basic premise of effective carbon emission reduction and management. This study aimed to establish the carbon emission model and performance evaluation framework of coal mine production enterprises and clarify the low-carbon development path of enterprises. In this study, we took a typical coal production enterprise (K enterprise) in the Shanxi province of China as the research object. We also estimated the carbon emissions of the enterprise mainly according to the Chinese Carbon Emission Accounting Standard (GB/T 32151.11-2018). The triangular model was used to construct the carbon performance evaluation framework. On this basis, we suggested the enterprise's low-carbon development path. The results showed that (1) the carbon emission of K enterprise in 2021 was 36,875.38 tCO2eq; the carbon emission intensity of each ton of coal produced was 0.089 tCO2eq. The critical carbon emissions were electricity consumption and methane fugitive emissions during production. (2) The evaluation indicators for carbon emission performance revealed an imbalance in K enterprise's economic, energy, and environmental development in 2021. The work on energy saving and consumption reduction was relatively weak. (3) Countermeasures for low-carbon development, including a carbon emission ledger, were proposed based on carbon emission accounting and performance evaluation results. This study can help typical underground coal production enterprises in Shanxi province obtain more accurate carbon emission data, providing practical guidance and reference for the same underground coal production enterprises to improve the carbon emission control effect.

Identification of force chains in wet coal dust layer and the effect of porosity on three-body contact stiffness.

Aiming at the three-body contact problem of mechanical rough surface containing wet coal dust interface, the three-body contact model of rough surface containing wet coal dust interface is constructed by comprehensively considering the contact deformation of rough surface and contact characteristics of wet coal dust, and based on the crushing theory. By analysing the contact force, load-bearing particle size and adjacent contact angle thresholds of the wet coal dust layer, the force chain identification criterion is formulated. Finally, quantitative calculations of the force chain characteristics are performed to reveal the effect of different initial porosities on the three-body contact stiffness, which is verified experimentally. The results of the study show that the average contact force of the wet coal dust layer can be used as the force chain contact force threshold, the average particle size can be used as the force chain particle size threshold, and the force chain angle threshold is determined by the particle coordination number. As the initial porosity decreases, the number, length and stiffness of force chains in the wet coal dust layer increase significantly, and the stiffness reaches a maximum value of 2.007 × 108 pa/m at the moment of downward pressure to stabilisation, while the trend of force chain bending varies in the opposite direction, and its minimum bending degree decreases to 20°. The maximum relative error between the simulation and experimental results of three-body contact stiffness is 9.64%, which proves the accuracy of the force chain identification criterion and the quantitative calculation of three-body contact stiffness by force chain.

Gas displacement characteristics during the water wetting process of gas-bearing coal and microscopic influence mechanism.

Gas and dust posed a threat to the safe working environment of miners. The key to the effectiveness of coal seam water injection in controlling gas and dust was the wetting of the coal body by water. The gas displacement characteristics were crucial for evaluating the wetting effect of coal. To investigate gas displacement characteristics during the water wetting process of gas-bearing coal, this study employed an experimental equipment of water wetting gas-bearing coal to test the gas displacement quantity under varying gas pressure conditions, and the microscopic influence mechanism was revealed. During the water wetting gas-bearing coal, there was an increase in the accumulated displacement gas quantity corresponding to rising adsorption equilibrium pressures, whereas the accumulated displacement gas rate decreased. Water wetting progressively reduced the system's Helmholtz free energy, reaching a minimum at equilibrium, indicative of a balanced wetting state. The displacement gas quantity curve initially rose linearly, reflecting rapid infiltration, then curved upwards more gradually as gravity and viscosity slowed the process, until reaching a relatively stable state. The curve mirrored the coal's saturation progression. The molecular formula of anthracite was C123H58N2O5. Elemental compositions of carbon, hydrogen, oxygen, and nitrogen matched elemental analysis results. The bridge carbon ratio of this molecular model was aligning with the bridge carbon ratio ascertained from the 13C NMR spectrum analysis. Above the coal-water interface, the relative concentration of water molecules increased with the increase of gas pressure. However, below the coal and water interface, the relative concentration of water molecules increased with the decrease of gas pressures. As the gas pressure increased, the adsorption degree of water molecules weakened, the degree of gas displacement in coal decreased, the diffusion coefficient of methane molecules decreased, the dispersion degree of water molecules increased, the aggregation degree weakened, and the diffusion coefficient of water molecules increased. The study results laid a theoretical foundation for revealing the mechanism of coal seam water injection wetting gas-bearing coal, achieving collaborative gas disaster prevention and pre-wetting dust reduction.

Prevalence of nano-sized coal mine dust in North and Central Appalachian coal mines - Insights from SEM-EDS imaging.

The increasing prevalence of coal mine dust-related lung diseases in coal miners calls for urgent and meticulous scrutiny of airborne respirable coal mine dust (RCMD), specifically focusing on particles at the nano-level. This necessity is driven by expanding research, including the insights revealed in this paper, that establish the presence and significantly increased toxicity of nano-sized coal dust particles in contrast to their larger counterparts. This study presents an incontrovertible visual proof of these tiny particulates in samples collected from underground mines, utilizing advanced techniques such as scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS). The intricate elemental composition of nano-sized coal dust identified through EDS analysis reveals the presence of elements such as silica and iron, which are known to contribute to lung pathologies when inhaled over prolonged periods. The outcomes of the statistical analyses reveal significant relationships between particle size and elemental composition, highlighting that smaller particles tend to have higher carbon content, while larger particles exhibit increased concentrations of elements like silica and aluminum. These analyses underscore the complex interactions within nano-sized coal dust, providing critical insights into their behavior, transport, and health impacts. The nano-sized coal dust could invade the alveoli, carrying these toxic elements from where they are impossible to exhale. The revelation of nano-sized coal dust's existence and the associated health hazards necessitate their incorporation into the regulatory framework governing the coal mining industry. This study lays the groundwork for heightened protective measures for miners, urging the invention of state-of-the-art sampling instruments, comprehensive physicochemical profiling of RCMD nanoparticles, and the pursuit of groundbreaking remedies to neutralize their toxic impact. These findings advocate for a paradigm shift in how the coal mining industry views and handles particulate matter, proposing a re-evaluation of occupational health standards and a call to action for protecting coal miners worldwide.

Extraction of vegetation disturbance range using aboveground biomass estimated from Sentinel-2 imagery in coal mining areas with high groundwater table.

Coal mining in regions characterized by high groundwater table markedly predisposes to surface subsidence and water accumulation, thereby engendering substantial harm to surface vegetation, soil, and hydrological resources. Developing effective methods to extract surface disturbance information aids in quantitatively assessing the comprehensive impacts of coal mining on land, ecology, and society. Due to the shortcomings of traditional indicators in reflecting mining disturbance, vegetation aboveground biomass (AGB) is introduced as the primary indicator for extracting the mining disturbance range. Taking the Huaibei Coal Base as an example, Sentinel-2 MSI imagery is firstly used to calculate spectral factors and vegetation indices. Multiple machine learning algorithms are coupled to perform remote sensing estimation and spatial inversion of vegetation AGB based on measured samples of vegetation AGB. Secondly, an Orientation Distance-AGB (OD-AGB) curve is constructed outward from the center of subsidence water areas (SWA), with the Boltzmann function used for curve fitting. According to the location of the inflection point of the curve, the boundary points of vegetation disturbance are identified, and then the disturbance range is divided. The results show that (1) the TV-SVM model, utilizing total variables and support vector machine, achieves the highest estimation accuracy, with σMAE and σRMSE values of 208.47 g/m2 and 290.19 g/m2, respectively, for the validation set. (2) Thirty-six effective disturbance areas, totaling 29.89 km2, are identified; the Boltzmann function provides a good fit for the OD-AGB curve, with an R2 exceeding 0.8 for typical disturbance areas. (3) Analysis of general statistical laws indicates that disturbance distance conforms to the general characteristics of normal distribution, exhibiting boundedness and directional heterogeneity. The research is expected to provide scientific guidance for hierarchical zoning management, land reclamation, and ecological restoration in coal mining areas with high groundwater table.

Highly conductive Ti3C2 MXene-supported CoAl-layered double hydroxide nanosheets for ultrasensitive electrochemical detection of organophosphate pesticide fenitrothion.

A novel electrochemical method is presented for ultrasensitive detection of the organophosphate pesticide (OPP) fenitrothion by using Ti3C2 MXene/CoAl-LDH nanocomposite as the electrode modifier. The Ti3C2 MXene/CoAl-LDH nanocomposite is synthesized by growing CoAl-LDH in situ on MXene nanosheets. The combination of two ultrathin 2D materials provides more active sites, larger specific surface area, superior adsorption properties, and better electrical conductivity, which leads to rapid electron-transfer and mass-transfer between the substrate electrode and analytes when it is acted as the electrochemical sensing material. In addition, through the chelation of phosphate groups with the Ti defect sites enriched in MXene, OPP is adsorbed on the electrode. Consequently, the corresponding modified electrode gives rise to a wide linear response range of 0.03 ~ 120 µmol/L for the differential pulse voltammetry detection of fenitrothion with a low detection limit of 5.8 nmol/L (3σ). The method offers good repeatability, stability, selectivity, and practicability for real samples. This strategy provides a reference platform for the electrochemical monitoring of trace OPPs residue by using MXene/LDH-based nanocomposites.

Fast and nondestructive discrimination of coal types based on spectral feature parameters.

Coal type identification is the basic work of coal quality inspection, which is of great significance to the normal operation of power generation, metallurgy, and other industries. The traditional coal-type identification method is complicated and requires comprehensive determination of various chemical parameters to obtain more accurate analysis results. Hyperspectral detection and analysis technology has the advantages of being simple, fast, nondestructive, and safe, and is widely used in a variety of fields. In this study, typical spectral feature parameters of coal samples were extracted based on hyperspectral data, and the parameters' sensitivity to coal types was explored using one-way ANOVA. The results showed that the coal spectral feature parameters of DI1-2µm and AD2.2µm significantly differed with coal species, indicating that the two parameters were class-sensitive features. When DI1-2µm and AD2.2µm were used to construct the Fisher discriminant model, the coal types could be discriminated with high accuracy. At the same time, the correlation between the extracted spectral feature parameters and the physicochemical parameters of bituminous coal and anthracite was analyzed. The results showed that there was a certain basis for using the extracted spectral feature parameters as the sensitive spectral characteristics of the model, and the application potential of the spectral characteristics of coal in the nondestructive prediction analysis of coal parameters was further discussed.

Oxidation and spontaneous combustion characteristics of particulate coal under stress-heat-gas interactions.

Coal spontaneous combustion (CSC) is disturbed by complex downhole conditions. However, current research by scholars mainly focuses on the impact of single conditional disturbances on CSC, which is difficult to comprehensively characterize the oxidation and spontaneous combustion characteristics of granular coal in a complex environment. For this reason, a temperature-programmed gas chromatographer (TP-GC) hyphenated instrument and a C600 high-precision microcalorimeter was used for analysis. The variation rules of derived gas and oxidizing thermodynamic parameters in the coal oxidizing and heating process under stress-heat-gas interaction were obtained. The intrinsic action mechanism of stress-heat-gas interaction to increase the risk of spontaneous combustion of granular coal is described. The results showed that as the level of air leakage (AL) rate increased, the concentration of derived gases in the coal sample showed a "˄"-shaped trend, and the heat release intensity and heat release varied in stages, both reaching their peak at a leakage rate of 150 mL/min. Under different stress conditions, the heat release intensity and heat release of coal also reach their maximum at 150 mL/min, indicating a higher risk of spontaneous combustion of coal at 150 mL/min. As the stress increases, the coal­oxygen reaction is inhibited, leading to a decrease in the concentration of derived gases and a reduction in the average heat release of the coal sample. This indicates that particulate coal is prone to spontaneous combustion when subjected to high air leakage rate and low stress conditions. The experimental results provide a theoretical basis for the prevention of CSC under complex conditions.

Isotope hydrology of the intermontane Elk Valley, British Columbia: an assessment of water resources around coal mining operations.

This study aimed to synthesise and interpret stable isotopic data (δ2H and δ18O) from various sources to understand the isotope hydrology around coal mine operations in Elk Valley, B.C., Canada. The data, including precipitation, groundwaters, seeps, and mine rock drains, were used to construct a local meteoric water line (LMWL) for the Elk Valley, evaluate the spatiotemporal isotopic composition of its groundwater, and assess mine seepage and mine rock drain discharge. The study revealed a robust LMWL relation (δ2H = 7.4 ± 0.2 · δ18O - 4.3 ± 4.1). The groundwater and seep data indicated a winter season bias and a north-south latitudinal gradient, suggesting rapid near-surface groundwater flow without significant post-precipitation evaporation. Porewater isotope samples from unsaturated mine rock piles (MRPs) showed site-specific evaporation patterns, potentially due to convective air flows or exothermic sulphide oxidation. This research revealed the influence of groundwater and meltwater on rock drain discharge. Based on evaporative mass balance calculations, MRPs seasonally contributed ca. 5 %(December base flow) and 22 % (snowmelt) to drain discharge. The findings underscore the value of stable isotope data collections in the Elk Valley to help better define and quantify the hydrology-hydrogeology, including a better understanding of evaporative conditions in MRPs.

Characteristics of China's coal mine methane emission sources at national and provincial levels.

Methane (CH4) is the second most abundant greenhouse gas. China is the largest CH4 emitter in the world, with coal mine methane (CMM) being one of the main anthropogenic contributions. Thus, there is an urgent need for comprehensive estimates and strategies for reducing CMM emissions in China. However, the development of effective strategies is currently challenged by a lack of information on temporal variations in the contributions of different CMM sources and the absence of provincial spatial analysis. Here, considering five sources and utilization, we build a comprehensive inventory of China's CMM emissions from 1980 to 2022 and quantify the contributions of individual sources to the overall CMM emissions at the national and provincial levels. Our results highlight a significant shift in the source contributions of CMM emissions, with the largest contributor, underground mining, decreasing from 89% in 1980 to 69% in 2022. Underground abandoned coal mines, which were ignored or underestimated in past inventories, have become the second source of CMM emissions since 1999. From 2011 to 2022, we identified Shanxi, Guizhou, and Shaanxi as the three largest CMM-emitting provinces, while the Emissions Database for Global Atmospheric Research (EDGAR) v8 overestimated emissions from Inner Mongolia, ranking it third. Notably, we observed a substantial decrease (exceeding 1 Mt) in CMM emissions in Sichuan, Henan, Liaoning, and Hunan between 2011 and 2022, which was not captured by EDGAR v8. To develop targeted CMM emission reduction strategies at the provincial level, we classified 31 provinces into four groups based on their CMM emission structures. In 2022, the number of provinces with CMM emissions mainly from abandoned coal mines has exceeded that of provinces with mainly underground mines, which requires attention. This study reveals the characteristics of the source of CMM emissions in China and provides emission reduction directions for four groups of provinces.

Source-specific ecological risk analysis and critical source identification of heavy metal(loid)s in the soil of typical abandoned coal mining area.

Long-term coal mining activities in abandoned coal mining areas have resulted in the migration of large quantities of heavy metals into the surrounding soil environment, posing a threat to the regional ecological environment. This study focuses on the surface soil collected from a typical abandoned coal mining area. Methods such as the pollution index (PI) and potential ecological risk index (RI) were used to comprehensively evaluate the pollution levels and ecological risks of soil heavy metals. Geostatistical analysis and the APCS-MLR model were used to quantify the sources of soil heavy metals, and Nemerow integrated ecological risk (NIRI) model was coupled to apportion the ecological risks from different pollution sources. The results indicate that the average concentrations of Cd, As, and Zn are 4.58, 2.44, and 1.67 times the soil background values, respectively, while the concentrations of other heavy metals are below the soil background values. The soil of study area is strongly polluted by heavy metals, with the pollution level and ecological risk of Cd being significantly higher than those of other heavy metals. The NIRI calculation results show that the overall comprehensive ecological risk level is considerable, with sample points classified as relatively considerable, moderate, and low at 60.53 %, 36.84 %, and 2.63 %, respectively. The sources of soil heavy metals can be categorized into four types: traffic activities, natural sources, coal gangue accumulation, and a combined source of coal mining and agricultural activities, with contribution rates of 35.3 %, 36.1 %, 19.5 %, and 9.1 %, respectively. The specific source ecological risk assessment results indicate that coal gangue accumulation contributes the most to ecological risk (36.4 %) and should be prioritized for pollution control, with Cd being the priority control element for ecological risk. The findings provide theoretical support for the refined management of soil heavy metal pollution in abandoned coal mining areas.

Microseismic comprehensive evaluation method for coal burst: a case study in the Zhaolou Coal Mine.

To explore the multiparameter precursor characteristics of pre- and post-coal burst. Based on a coal burst of LW 1305 in the Zhaolou Coal Mine, an early warning method combining stress‒strain curve and microseismic multiparameter is proposed. The research results show that coal burst was induced by the intrinsic static high-stress concentration and the strong external impact loading generated by fracturing of the key stratum. The precursors mainly characterize the enhancement trend of the S value, the sudden and sharp increase in the A(t) value, the continuous and abnormal decrease in the b value, the increasing absolute value of Z sharply and larger than 2, the continuous and abnormal decrease in the Qt value, and the dominant frequency moving to the low-frequency band. Essentially, many micro-fissures inside the key stratum initiated, converged and connected to form macro-fractures, which was verified by the attenuation rate of the K value. Considering the time-varying effect of the overlying stratum movement, the curves of the six parameters agree well with those of stress vs. strain, which indicates that it is reasonable to take the observed zone as a whole system to investigate the variation in the multiple parameters and fracturing of the key stratum. The research results can be applied to the monitoring, early warning and control of coal burst so that effective safety measures can be taken in real time.

Harnessing coal and coal waste for environmental conservation: A review of photocatalytic materials.

Fossil fuels, especially coal, have played a pivotal role in driving technological and economic advancements over the past century, though accompanied by numerous environmental challenges. Rapid progress in green and sustainable energy sources, including tidal, wind, and solar energy, coupled with growing environmental concerns, the conventional coal industry is experiencing a sustained decline in both size and financial viability. This situation necessitates the urgent adoption of advanced approaches to coal utilization. Beyond serving as an energy source, coal and its by-products, known as coal waste, can serve as valuable resources for the development of advanced materials, including photocatalysts. The advancement of photocatalytic materials derived from coal and coal waste can capitalize on these natural carbon and mineral sources, providing a viable solution to numerous environmental challenges. Currently, research in this domain remains in its early stages, with existing studies primarily focusing on specific types of photocatalysts or particular aspects of the fabrication process. Therefore, available coal-based and coal waste-based photocatalytic materials were systematically examined and categorized into six types according to their composition and dimensional/structural characteristics. Each type of photocatalytic material was introduced, along with common fabrication and characterization technologies. Representative works were discussed in detail to highlight the unique features of different types of coal-based and coal waste-based photocatalytic materials. Furthermore, the promising applications of these materials in environmental protection and pollution treatment were summarized, while also addressing the challenges and prospects in this research field. This review comprehensively overviews the fundamental knowledge and recent advancements in photocatalytic materials derived from coal and coal waste, with the goal of catalyzing the development of next generation photocatalysts and contributing to the transformation of the conventional coal industry.

Role of water in the formation of low-temperature coal oxidation products: An experimental isotope tracer study.

The interaction between water and coal is of great significance to the study of coal spontaneous combustion (CSC) in humid mine environments. Here, using an isotope tracing method to trace oxygen atoms in water, the role of water in the formation of CO, CO2, product water, and other substances during CSC was quantitatively studied through thermogravimetry coupled with mass spectrometry (TG-MS). In addition, Pearson correlation analysis was used to evaluate the relationships between the amounts of CO and CO2 generated during CSC and the different functional groups. The migration and transformation paths of oxygen atoms in water were analyzed. The results showed that water participated in the CSC reaction to produce CO, CO2, and product water in a dynamic, temperature-dependent process. CO and CO2 were formed through different reaction paths involving reactions between water and aldehyde and carboxyl groups. Further, carboxyl groups were also involved in the reaction with coal to form product water. The results from this study are helpful for understanding the influence of water in each stage of CSC, thereby aiding in its prevention and control.

Generation and emission mechanism of polycyclic aromatic hydrocarbon (PAHs) during the coking process in Shanxi, China.

Although coking process is the important source of polycyclic aromatic hydrocarbons (PAHs) in the environment, the generation and emission of PAHs during this process is unclear. It is crucial to clarify the formation mechanism of PAHs in coal pyrolysis during the coking process for effectively identifying and controlling the emission of these organic pollutants. In this study, the combination of laboratory simulation and field sampling was used to analyze the mechanism of PAHs formation and emission in coking process. The release of PAHs from the pyrolysis process of coal blends used in coking plants was 1778.20 ± 111.95 µg · g-1, which was much higher than the content of free PAHs in raw coal (76.50 ± 12.46 µg · g-1). 3-ring PAHs were the most abundant components of free PAHs and pyrolysis-generated PAHs. PAH formation during pyrolysis of coal blends was primarily attributed to the cracking of the macromolecular structure of coal, with minimal influence of free PAHs in blended coal. The emission of PAHs from coal-charging was higher (62.93 ± 17.75 µg · m-3) than that from pushing of coke (11.79 ± 1.91 µg · m-3·, PC) and combustion of coke oven gas (5.53 ± 1.20 µg · m-3, CG), and was mainly related to free PAHs in coal. In contrast, the characteristics of PAHs in the flue gas of PC and CG were similar to those from blended coal pyrolysis. PAHs in fugitive emission from coke oven were primarily affected by flue gas leakage and were mainly related to coal pyrolysis and free PAHs in blended coal.

Study on preparation and properties of antifreeze compound road dust suppressant.

Open-pit mine pavement dust dries and breaks easily. As such, a composite pavement dust suppressant with good wettability, moisturizing, coagulation, and antifreezing properties in winter was investigated. Monomer screening and orthogonal experiments were conducted, using evaporation rate, permeability rate, viscosity, and freezing point as evaluation indexes. Consequently, a dust suppressant solution is a mixture of glycerol (GLY), sodium dodecylbenzene sulfonate (SDBS), polyacrylamide (PAM), compound propylene glycol (PG), and potassium acetate (PA). The characteristics of the dust suppressant and its interaction mechanism with road dust were measured and analyzed. The results showed that the optimal ratio of the antifreeze-type composite dust suppressant is 3%GLY, 0.30%SDBS, 0.07% PAM, and 50%PG + 10%PA; the contact angle is 27.62°, which can effectively wet coal dust. Moreover, it easily forms hydrogen bonds with water molecules to release free -OH, which increases the oxygen-containing functional groups in the dust. The maximum viscosity is 25.4 mPa·s, and the hydrophobic groups adsorbed on the surface of the dust can condense and agglomerate the dust to form large particles, and effectively inhibit the occurrence of dust. It freezes at - 34.2 â„ƒ, resists a temperature of - 30 â„ƒ without freezing, and improves dust suppression efficiency and antifreezing effect in cold areas.

Feasibility experimental study on plugging leakage in goaf based on two-phase foam.

Air leakage in goaf often leads to coal spontaneous combustion (CSC), which not only directly affects the safety production of mines but also causes significant environmental damage. Therefore, effectively sealing the airflow in goaf is crucial for preventing CSC. Feasibility experiments on using two-phase foam to seal air leakage in goaf were conducted, leveraging the advantages of large flow rate, wide diffusion range, and good accumulation characteristics of two-phase foam. The research results indicate that continuous injection of foam into loose media with maintained ventilation can completely seal the air leakage, with the foam capable of withstanding wind pressures of nearly 600 Pa. When the foam is used for one-time sealing with a length of 2 m, it remains effective for 60 min, and the sealing effectiveness improves with longer distances sealed against air leakage. Numerical simulation analysis and field measurements of airflow leakage in mine working faces reveal that effectively sealing the airflow passage in the goaf behind the corner of the return airway is crucial for preventing CSC. Two methods are proposed for sealing external airflow during coal mining: foam injection using a point drilling method near the heading and an incremental buried pipe injection method. Finally, the feasibility of two-phase foam sealing technology for goaf airflow leakage is analyzed from multiple perspectives including sealing effectiveness, practicality, economy, foaming process, and engineering implementation. The research findings provide new insights into goaf sealing technology, aiding in addressing safety and environmental issues caused by spontaneous combustion in goaf areas.

Conforming Capacitive Load Cells for Conical Pick Cutters.

In underground coal mining, machine operators put themselves at risk when getting close to the machine or cutting face to observe the process. To improve the safety and efficiency of machine operators, a cutting force sensor is proposed. A linear cutting machine is used to cut two separate coal samples cast in concrete with conical pick cutters to simulate mining with a continuous miner. Linear and neural network regression models are fit using 100 random 70:30 test/train splits. The normal force exceeds 60 kN during the rock-cutting tests, and it is averaged using a low pass filter with a 10 Hertz cutoff frequency. The sensor uses measurements of the resonant frequency of capacitive cells in a steel case to determine cutting forces. When used in the rock-cutting experiments, the sensor conforms to the tooling and the stiffness and sensitivity are increased compared to the initial configuration. The sensor is able to track the normal force on the conical picks with a mean absolute error less than 6 kN and an R2 score greater than 0.60 using linear regression. A small neural network with a second-order polynomial expansion is able to improve this to a mean absolute error of less than 4 kN and an R2 score of around 0.80. Filtering measurements before regression fitting is explored. This type of sensor could allow operators to assess tool wear and material type using objective force measurements while maintaining a greater distance from the cutting interface.

A Highly Selective Acetone Sensor Based on Coal-Based Carbon/MoO2 Nanohybrid Material.

High temperature represents a critical constraint in the development of gas sensors. Therefore, investigating gas sensors operating at room temperature holds significant practical importance. In this study, coal-based porous carbon (C-700) and coal-based C/MoO2 nanohybrid materials were synthesized using a simple one-step vapor deposition and sintering method, and their gas-sensing performance was investigated. The gas-sensing performance for several VOC gases (phenol, ethyl acetate, ethanol, acetone, triethylamine, and toluene) and a 95% RH high-humidity environment were tested. The results indicated that the C/MoO2-450 sample sintered at 450 °C exhibited excellent specific selectivity towards acetone at room temperature, with a response value of 4153.09% and response/recovery times of 10.8 s and 2.9 s, respectively. Furthermore, the C/MoO2-450 sample also demonstrated good repeatability and long-term stability. The sensing mechanism of the synthesized materials was also explored. The superior gas-sensing performance can be attributed to the synergistic effect between the porous carbon and MoO2 nanoparticles. Given the importance of enhancing the high-tech and high-value-added utilization of coal, this study provides a viable approach for utilizing coal-based carbon materials in detecting volatile organic compounds at room temperature.

Research progress on the pathogenesis and prediction of pneumoconiosis among coal miners.

Pneumoconiosis is the most common occupational disease among coal miners, which is a lung disease caused by long-term inhalation of coal dust and retention in the lungs. The early stage of this disease is highly insidious, and pulmonary fibrosis may occur in the middle and late stages, leading to an increase in patient pain index and mortality rate. Currently, there is a lack of effective treatment methods. The pathogenesis of pneumoconiosis is complex and has many influencing factors. Although the characteristics of coal dust have been considered the main cause of different mechanisms of pneumoconiosis, the effects of coal dust composition, particle size and shape, and coal dust concentration on the pathogenesis of pneumoconiosis have not been systematically elucidated. Meanwhile, considering the irreversibility of pneumoconiosis progression, early prediction for pneumoconiosis patients is particularly important. However, there is no early prediction standard for pneumoconiosis among coal miners. This review summarizes the relevant research on the pathogenesis and prediction of pneumoconiosis in coal miners in recent years. Firstly, the pathogenesis of coal worker pneumoconiosis and silicosis was discussed, and the impact of coal dust characteristics on pneumoconiosis was analyzed. Then, the early diagnostic methods for pneumoconiosis have been systematically introduced, with a focus on image collaborative computer-aided diagnosis analysis and biomarker detection. Finally, the challenge of early screening technology for miners with pneumoconiosis was proposed.