International Journal of Coal Science & Technology最新文献

A simple and flexible mass balance approach was applied to observations of XCH₄ from TROPOMI to estimate CH₄ emissions over Shanxi Province, including the impacts of advective transport, pressure transport, and atmospheric diffusion. High-frequency eddy-covariance flux observations were used to constrain the driving terms of the mass balance equation. This equation was then used to calculate day-to-day and 5 km × 5 km grided CH₄ emissions from May 2018 to July 2022 based on TROPOMI RPRO column CH₄ observations. The Shanxi-wide emissions of CH₄, 126 ± 58.8 ug/m²/s, shows a fat tail distribution and high variability on a daily time scale (the 90th percentile is 2.14 times the mean and 2.74 times the median). As the number of days in the rolling average increases, the change in the variation decreases to 128 ± 35.7 ug/m²/s at 10-day, 128 ± 19.8 ug/m²/s at 30-day and 127 ± 13.9 ug/m²/s at 90-day. The range of values of the annual mean emissions on coal mine grids within Shanxi for the years 2018 to 2022 was 122 ± 58.2, 131 ± 71.2, 111 ± 63.6, 129 ± 87.1, and 138 ± 63.4 ug/m²/s, respectively. The 5-year average emissions from TROPOMI are 131 ± 68.0 ug/m²/s versus 125 ± 94.6 ug/m²/s on the grids where the EDGAR bottom-up database also has data, indicating that those pixels with mines dominate the overall emissions in terms of both magnitude and variability. The results show that high-frequency observation-based campaigns can produce a less biased result in terms of both the spatial and temporal distribution of CH₄ emissions as compared with approaches using either low-frequency data or bottom-up databases, that coal mines dominate the sources of CH₄ in Shanxi, and that the observed fat tail distribution can be accounted for using this approach.

Moisture content of rock/coal can change its mechanical properties and absorption capacities, which can directly affect gas diffusivity, change the stress distribution and hence cause significant impacts on the overall gas or coal extraction process. Observation of the water penetration process and water distribution in the coal matrix will be beneficial for the understanding of the fluid-solid coupling mechanism in hydraulic fracturing, aquifer cracking and coal seam infusion. However, the observation of water penetration process and the determination of water distribution mode were hard to be non-destructively achieved as coal is a non-uniform, inhomogeneous and un-transparent material. µ-CT imaging, which is based on variation of X-ray attenuation related to the density and atomic composition of the scanned objects, enables a four-dimensional (spatial-temporal) visualise of the heterogeneous and anisotropic coal samples. The primary aim of this paper is extending the application of µ-CT imaging to explore the moisture penetration and distribution within coal samples during water infusion process, which has been reported by very little literature. The working principle and procedures of CT imaging was firstly introduced. Then, the determination equation of moisture distribution based on density profile was established. The CT determined moisture content has been compared with weighting method for verification. The paper has demonstrated that µ-CT can be used for non-destructively imaging the moisture distribution within coal samples.

Dust pollution from Chinese open-pit coal mines (OPCMs) threatens the coexistence of resource development and environmental protection. This research introduces a new approach to designing OPCMs based on meteorological indicators for dust removal and diffusion. It analyzes the production, distribution, and dust emission features of large-scale OPCMs in China. The factors affecting dust dispersion and atmospheric pollution characteristics were also examined. The findings reveal a surge in the number and output of OPCMs, intensifying the conflict between resource development and environmental protection. Notably, over 80% of OPCMs are in arid and semi-arid regions, exacerbating the challenge. Microclimate effects, including circulation and inversion effects, further amplify dust pollution. Regional and seasonal dust pollution patterns were identified, with the southern region experiencing the highest pollution levels, followed by the northern and central regions. Seasonally, dust pollution exhibits the following pattern: winter > autumn > spring > summer. An alarming decline in atmospheric self-cleaning capacity over the past two decades underscores the pressing challenges ahead for dust control. The increase in air stagnation days/events highlights the urgency for effective dust prevention and control measures. This research suggests considering meteorological elements in OPCM design for dust control. Optimizing mining operations based on weather forecasts enables the utilization of natural conditions for effective dust prevention and control. The results provide insights for dust prevention and control in open-pit mines to foster green and climate-smart mining.

It is of great significance for coal mining and utilization to study the adsorption process of mixed gas in coal. In this paper, the Monte Carlo method (MC) is employed to study the competitive saturation adsorption of oxygen and water vapor inside coal particles, and then the convection, diffusion and adsorption inside and between particles are studied by lattice Boltzmann method (LBM). In addition, this study examines the impacts of porosity, average particle size, and gas concentration on the process of adsorption in coal porous media. The research results show that oxygen and water vapor present in the mixed gas experience increased permeability, diffusion rate, and saturated adsorption capacity as the porosity and average particle size of the coal porous medium increase. However, the time required to achieve saturated adsorption decreases. Under the condition of maintaining the proportion of gas components and altering the initial gas concentrations from 4.087 to 53.131 mol/m³, saturated adsorption capacity of both gases remains nearly unchanged. Yet, the effective diffusivity of gases declines with increasing initial concentration. Additionally, it is also found that water vapor diffuses more quickly than oxygen in the mixed gas and achieves adsorption saturation faster.

The extraction of valuables from waste has gained momentum. Thermal influence alters both the organic and inorganic components of coal. Insufficient knowledge on the association of rare earth elements (REEs) with the parent matrix of thermally altered high-ash coals (63% ash) limits the potential for such coals being utilized for isolation of valuables. In this study, we analyzed the distribution and occurrence modes of REEs within a magmatically altered high-ash coal via nine-step sequential extraction, combining Tessier and BCR methods. The total concentration of REEs in the coal sample, on whole coal basis, was found to be 820 ppm, which is significantly higher than the world average. Major mineral oxides were deduced to be those of Si, Fe, Al, Ca, Mg, and Ti. Sequential extraction confirmed that about 66% of HREE and 25% of LREE were included in the residual fraction. LREEs were concluded to be primarily in ionic form, whereas HREEs were speculated to be associated with the TiO₂ phase. XRD analyses showed that thermal alteration affected the dolomite phase specifically, which selectively got removed where carbonate-bound elements were assessed. Petrographic analysis supported the magmatic influence and demonstrated the presence of mosaic structures and pores containing unfused vitrinite, with a reflectance value of 3.6. To summarize, the present study pertaining to delineation of association of valuables in high-ash heat-altered coals from an Eastern coalfield in India can potentially open up new avenues for utilizing such coals, which are otherwise considered waste.

The ability to predict gas emissions accurately is pivotal in managing gas control and ensuring safe mining operations. Existing internationally acknowledged gas control and prediction software does not cater to the specific conditions in Chinese coal mines. Hence, this paper introduces an object-oriented programming method to design a software tool for calculating the total gas emission quantity using the MATLAB application program designer runtime environment. The software incorporates an algorithm, data structure, framework, and module functions, all of which enable seamless integration and visualization of gas emission calculation software. This software tool mitigates the inefficiencies and inaccuracies associated with manual, different-source forecast methods. Based on the field data of the Hulonggou Coal Mine in Shanxi province, this technical software was used to predict the gas emission of the mine. The research results show that the predicted value of the technical software is close to the actual measured value. The differing estimates of the working face and coal mine output primarily account for the deviation between the tool's predicted gas emission value and the field-measured value. The underlying design logic of this technical software determines that it has good adaptability to mines with clear mining technology parameters and gas geological parameters. This study provides a valuable method for researchers and engineers seeking to improve gas emission calculation efficiency.

Coal bed methane (CBM), the high-quality and efficient fuel, has caught the interest of many nations as they strive for environmentally friendly development. Therefore, the efficient exploitation and utilization of CBM has become one of the international focal research problems. A significant factor affecting the mining of CBM is coal permeability. To better capture the changes that occur during the extraction of CBM, the internal swelling coefficient of matrix (ISCM) has been gradually in permeability introduced into the permeability models, and such models have become an important type of the development of permeability models. The goal is to find out more precisely the evolution mechanism of the ISCM and its influence on the permeability models. In this paper, the selection of coal structure, determination of boundary conditions and influencing factors of permeability for were first analyzed. Then, according to the research process of ISCM, the permeability models including the ISCM were reviewed and divided into four phases: proposal phase, development phase, evaluation phase and display of internal structure phase. On the basis of the ISCM values in the current coal permeability models, the primary influencing factors and evolutionary laws of the ISCM are explored. The results obtained provide guidance for future theoretical refinement of permeability models with the ISCM.

Special attention was drawn to the heavy metals contained in coal, due to it will cause harm to the environment during coal processing and utilization. The sequential chemical extraction of Shanxi coal (SX coal) and Wulanchabu coal (WLCB coal) was carried out to investigate the distribution of arsenic (As) in coals. Two raw coals were pyrolyzed at 300–900 °C in horizontal tubular furnace to investigate release behavior of As during pyrolysis process. The results showed that As in SX coal mainly existed in aluminosilicate-bound state (40.25%) and disulfide-bound state (32.51%), followed by carbonate-bound state and organic-bound state. The As in WLCB coal mainly existed in aluminosilicate-bound state (62.50%), followed by disulfide-bound state (19.10%). The As contents of water-soluble, ion-exchange and residue states in the two coals were less than others. The modes of occurrence of As had great influence on its volatilization behavior. As in organic part was easy to volatilize at low temperature. Sulfide-bound state would escape with the decomposition of pyrite. Because SX coal contained higher organic state and sulfide-bound state, the volatilization rate of As was higher than WLCB coal at any temperature, and the difference was more obvious at low temperature. In addition, FactSage simulation value was basically consistent with the experimental value.

Forty Tertiary coals from Mukah-Balingian and Merit-Pila coalfields of the Sarawak Basin, Malaysia were investigated using bulk and molecular geochemical techniques such as proximate analysis, gas chromatography-mass spectrometry, elemental analyser, isotope ratio mass spectrometry, and inductively coupled plasma mass spectrometry to reconstruct their paleovegetation, paleoclimate, and environments of deposition. In addition, principal component analysis (PCA) of selected geochemical parameters was carried out to determine the controlling influences on the petroleum potential of the humic coals. δ¹³C values and the abundance of terpenoids imply the predominant contribution of angiosperms to the paleoflora. Bimetal proxies (Sr/Ba, Sr/Cu, and C-value), and δD values are generally suggestive of a warm and humid climate during the accumulation of the paleopeats. However, n-alkane proxies (P_wax, P_aq, n-C₂₃/n-C₂₉, etc.) and polycyclic aromatic hydrocarbons (PAHs) distribution suggest that Balingian coals accumulated under relatively drier and strongly seasonal paleoclimate in the Late Pliocene. When compared with published global average abundances, the investigated coals are mostly depleted in major oxides and trace elements, suggesting peat accumulation in freshwater-influenced environments. Nonetheless, higher (> 0.5 wt%) total sulfur content in some Mukah-Balingian coals suggests some degree of epigenetic marine influence. Furthermore, the low to moderately-high ash contents of the Sarawak Basin coals indicate the presence of ombrotrophic and rheotrophic peat deposits. PCA result of selected geochemical proxies suggests that source input, paleoflora, and marine incursions are not major controlling influences on the petroleum potential. However, climatic, and depositional conditions appear to slightly influence the petroleum potential of the studied humic coals.

This study employs similar simulation testing and discrete element simulation coupling to analyze the failure and deformation processes of a model coal seam's roof. The caving area of the overburden rock is divided into three zones: the delamination fracture zone, broken fracture zone, and compaction zone. The caving and fracture zones' heights are approximately 110 m above the coal seam, with a maximum subsidence of 11 m. The delamination fracture zone's porosity range is between 0.2 and 0.3, while the remainder of the roof predominantly exhibits a porosity of less than 0.1. In addition, the numerical model's stress analysis revealed that the overburden rock's displacement zone forms an 'arch-beam' structure starting from 160 m, with the maximum and minimum stress values decreasing as the distance of advancement increases. In the stress beam interval of the overburden rock, the maximum value changes periodically as the advancement distance increases. Based on a comparative analysis between observable data from on-site work and numerical simulation results, the stress data from the numerical simulation are essentially consistent with the actual results detected on-site, indicating the validity of the numerical simulation results.