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Australia is a long-term key partner of China in coal trading, which is famous for high-quality coal and its price advantage. However, affected by the evolution of international political and economic situation, China has issued a coal ban on Australian coal since the end of 2020. The potential environmental consequences of this coal ban remain unclear. So, this paper quantifies the ban's impact on air pollution, human health and climate change by simulating the emission difference between the port scenario (simulating the emissions due to Australian coal import under business as usual) and the mine scenario (simulating the emissions due to domestic coal mining that converted from import share of Australian coal), and monetizes the losses into economic costs for direct comparison. The results illustrate the emission of SO 2 , VOCs and GHG in mine scenario grows up to 102, 12 and 6 times the amount of that in port scenario, mainly deriving from coal mining process in the North China Plain and Yunnan-Guizhou Plateau. It shows that the potential alternative of replacing import with mining leads to PM 2.5 pollution exacerbation and O 3 pollution abatement, which causes 148 (95 % CI: 101–183) non-communicable diseases and respiratory disease-related deaths in total. As for GHG, the emission of BC in transportation process and fugitive methane in coal mining process contribute to an impressive effect on warming potential with few quantities, which is worth noting in control process. In total, the environmental deterioration resulted in an economic loss of approximately 934 million yuan. The undiminished demand for high-quality industrial coal as well as growing carbon tax could make the economic value of the coal ban's environmental consequences more considerable in the near future. This research emphasizes the contradiction between economic development and environmental improvement caused by excessive dependence on coal and addresses a critical knowledge gap in assessing the ban's environmental impact by economic value. The result directly demonstrates the environmental consequences of the potential mining-replacing-import alternative and helps better understand environmental influences on the Chinese government's decision. [ABSTRACT FROM AUTHOR]

To effectively control and utilise large amounts of gas emissions from underground coal mining, Australia and many other countries rely heavily on a series of vertical boreholes to capture the gas during mining. This gas capture not only reduces the greenhouse gas impact but also recovers a significant amount of energy. Vacuum pumps are connected to surface boreholes to drive gas flow from the goaf and overlying fractured strata. However, applying high suction pressure to the boreholes may cause more oxygen to enter the goaf from the longwall working face. This influx of oxygen can potentially react with residual coal in the goaf, accelerating coal self-heating and possibly resulting in endogenous fires. By analysing extensive goaf gas drainage data collected from Australian longwalls, researchers have established the normal trend of goaf gas concentration and flow rate as a result of intensive goaf gas drainage. This paper further developed goaf gas flow CFD models with the operating vertical boreholes, which were then calibrated using field borehole production data under certain operating conditions. The CFD model simulated the distribution of O 2 and CH 4 as well as the gas flow pathways in the goaf, considering the complication of goaf gas drainage. This study found that the O 2 concentration is higher on the goaf tailgate side under the influence of tailgate side boreholes compared to the maingate side. Furthermore, for the well-compacted goaf, a significant proportion of the ventilation air travels through 'high permeability flow channels' provided by the goaf edge on tailgate side, and then circulates back into the goaf boreholes. These CFD modelling results not only enable ventilation engineers to visualize the goaf gas flow patterns under the impact of multiple operating boreholes, but also to understand the impact on goaf atmosphere through sensitivity analysis of natural goaf characteristics, such as goaf permeability distributions and gas emission rates. [ABSTRACT FROM AUTHOR]

Pretension is the pre-added axial tensile force on fully grouted bolt systems, which include rock bolts and cable bolts. Although a series of studies via lab testing and analytical modelling proved the importance of pretension in cable bolts, there is no systematic analysis to guide the optimal pretension values to be applied on cable bolts in different engineering geological conditions. Complicated geological conditions, such as anisotropic in-situ stress, bedding plane detachment and country rock deformation, cannot be fully represented in the lab or analytical work. In addition, field scale numerical models to investigate cable bolt performance and its interaction with various geological conditions are rare. This paper analyses the effect of pretension on the performance of cable bolts in underground coal mines via field scale numerical models, with considering different geological conditions (in-situ stress, bedding plane stiffness and rock mass properties). Numerical models were developed based on a case study mine in Australia with challenging ground conditions. The in-situ stress, properties of claystone and bedding planes are considered critical variables to be analysed. The results show higher pretension contributes to higher force along the cable bolt. Neutral points, where shear force in grout materials is zero, are used to describe the pretension-induced stress redistribution on cable bolts. Pretension also has a positive effect on roof and bedding plane management, resulting in a more stable roof condition. In addition, high pretension and high in-situ stress are more likely to result in cable-grout (CG) interface failure since the relative vertical displacement difference between cable bolts and the surrounding rock mass is higher. Once CG interface failure is generated, the pretension effect turns out to be negative, leading to severe roof sagging and bedding plane aperture. This paper provides a guide to the application of pretension in coal mining. • Developed a numerical model to illustrate the effect of pretension on cable bolts. • Analysed effects of pretension and cable-grout (CG) interface failure on cable bolts. • Investigated the relationship between pretension applied and CG interface failure generated along cable bolts. • CG interface failure induced by excessive pretension is more sensitive to bedding plane properties. [ABSTRACT FROM AUTHOR]

In gassy underground and spontaneous combustion prone coal mines, goaf management is a challenging task to reduce the risks of gas explosion and spontaneous combustion to acceptable levels. Goaf gas drainage via vertical surface goafholes is a primary control method to manage gas emissions in Australian coal mines. However, the operation of vertical surface goafholes maybe significantly impacted by insufficient understanding of goaf gas flow and coal self-heating behaviour, especially under different goaf gas drainage operating conditions. This paper focuses on analysing the field monitoring data collected from 161 goaf drainage holes at two coal mines in Australia. The data formed the basis to develop a conceptual model, which represents the changes of goaf atmosphere during the longwall retreat along with goaf drainage operations. The results indicate that the goaf drainage operating conditions may significantly affect goaf gas composition, which contributes to a different goaf atmosphere in comparison to existing models without goaf drainage. Within the studied longwall goaf, the 'oxidation zone' and 'inert zone' are identified with different carbon monoxide (CO) and oxygen (O 2) trends, and the 'oxidation zone' is conceptually further divided into the 'heat accumulation zone', 'elevated oxidation zone' and 'slow oxidation zone' based on the variation of gas composition and potential degree of oxidation of residual coal. The coal oxidation potential risk and corresponding goaf gas drainage strategies at these conceptual zones are also evaluated in this paper. The results of this study are expected to act as a guideline for future goaf gas drainage operations. • Gas composition analysis of goaf drainage production data was conducted. • A goaf environment conceptual model under various goaf gas drainage was proposed. • Coal oxidation risk at different goaf zones have been analysed. • Relevant goaf gas drainage plans have been proposed based on the conceptual model. [ABSTRACT FROM AUTHOR]

Most prediction methods used to calculate mining-induced subsidence are empirical, which cannot explain the mechanism of fundamental rock strata movement. In this paper, based on key stratum theory and the mechanical analysis of overburden, a new analytical solution, the Analogous Hyperbola Subsidence Model (AHSM), was proposed to describe the movement and damage of inner burden. Mining-induced rock strata movement was verified using the Distinct Element Method (UDEC), to assess the performance of the theoretical model. Three subsidence parameters (S max /T, S goaf /S max , D/H), generally used to describe surface subsidence trough, agree with statistical field measurements of the South Coalfield in Australia. The surface subsidence and the movement boundary in the overburden are very close to the theoretical predictions. Additionally, the primary key stratum damages the least in the overlying strata: its broken length is the smallest. The width of subsidence trough and maximum surface subsidence increase as the primary key stratum drops. • A new model of AHSM was proposed to describe the movement and damage of inner burden. • The damage of the primary key stratum is the minimal in all the overlying strata. • The simulation results obtained from UDEC are in good agreement with the theoretical predictions of AHSM. [ABSTRACT FROM AUTHOR]

Microseismic monitoring is a widely used technique in coal mine safe production. Microseismic events classification is one of the most important steps in microseismic monitoring. CNN has been proven to be the potential tool to identify microseismic events automatically. When the noise is serious and the signal is weak, the recognition ability of CNN is limited. Some scholars use denoising methods, such as wavelet transform, to enhance the signal-to-noise ratio (SNR) of the input data. However, the effective signal will be broken if the incorrect threshold parameters are set in this wavelet transform-based denoising method. In this paper, we intend to make the data volume of the time-frequency graph obtained by WPT as the input of CNN. But it may lead to a dimensional disaster if taking the time-frequency domain signals as input directly. To utilize the effective information extraction and reduce the data dimension, we propose a dual-channel CNN model by combining time domain information and wavelet packet decomposition coefficients (T-WPD CNN). The wavelet packet decomposition coefficients highlight the characteristics of the signal and suppress the characteristics of noise. In addition, the coefficients have the same dimension as the original signal. These advantages are useful for enhancing the performance of CNN. Two field datasets are used to test the network. One from Australia and another from Jiayang coal mine, Sichuan, China. The feature map of the convolutional layer with different inputs are shown to illustrate the influence effect of raw time domain signal and WPD coefficient on the classification performance. The final results show that the T-WPD CNN is superior to the traditional CNN method in accuracy and robustness. • The network combines time-domain information and wavelet packet decomposition coefficients of the microseismic data. • The more obvious feature map of the microseismic is extracted, which makes the classification performance better. • The wavelet packet decomposition coefficients can avoid the dimensional disaster of the input data. [ABSTRACT FROM AUTHOR]

Longwall coal mines in the Bowen Basin of Australia are highly productive and gassy, comprising many coal seams above the working seam. Predictive modelling of specific gas emission (SGE) using the conventional Winter model developed in Germany or other European based models often results in significant discrepancies from reality. To improve methane emission prediction and management, significant efforts on measuring gas release from different coal seams were made at three longwall mines by safely drilling core holes into the goaf. The vertical extent of the gas emission zone and the proportion of gas released from different coal seams were quantified. It was found that the Winter model significantly underestimates gas emissions for coal seams 75–150 m above the mining seam. This discrepancy is likely due to the intensive goaf drainage using large-diameter vertical wells in the high production Bowen Basin longwall mines. The Winter model also appears inadequate in estimating the height of the gas emission zone at different mines where the extraction thickness differs. Finally, a new empirical model for predicting the degree of gas emission from roof coal seams is developed for Bowen Basin mines and other mines with similar mining conditions. The measured post-mining gas content data and the newly developed model in this paper can provide guidance to the design of goaf drainage boreholes and capacity, as well as assessing coal mine methane and abandoned mine methane resources. [ABSTRACT FROM AUTHOR]

Resource-dependent communities in hinterland regions of Australia, Canada and elsewhere are rapidly aging, yet many features that distinguish them (e.g., geographic remoteness, small populations, infrastructure built with younger persons in mind) also pose significant challenges for healthy aging. These challenges can lead to substantial gaps in access to formal health and social services, with negative implications for older residents aging-in-place and the development aspirations of resource frontier communities. In this paper, we explore the efforts of voluntary sector leaders to transform resource communities into more livable and supportive places for older adults. We offer a case study of two small towns in Canada's aging resource frontier; one forestry-dependent and the other dependent on coal mining. Our findings suggest that place integration develops through volunteer work and explains how voluntarism works as both a process and outcome of 'placemaking'. We argue that greater attention to place integration is needed to bring into focus the transformative potential of the voluntary sector in creating supportive and sustainable environments for healthy aging. [ABSTRACT FROM AUTHOR]

Abstract Coal plays a key role in China's economy as a dominant primary energy resource. In this paper, we provide probability density forecasts for weekly steam coal prices in China based on daily factors such as renewable energy source, Daqing oil, Japanese natural gas, Australia steam coal prices, coal mining industry index, A-share power sector index, A-share index, coal industry index, and temperature. The empirical results show that the influence of temperature lasts longer than other factors, while the Australia steam coal prices, renewable energy source and A-share index are the three best predictors for steam coal prices. It is also shown that the high-frequency factors are useful to forecast steam coal prices and that considering the nonlinearity of coal prices can improve the forecast accuracy by about 22%. We further provide the probability density forecasts for steam coal prices based on the influence of all the selected factors, the results suggest that our proposed method can provide accurate and satisfying probability density forecasts. Given these results, the policy-makers can make effective strategies which can not only adjust the energy structure but also ensure economic growth. • High-frequency factors are useful to forecast coal prices. • C-MIDAS-X model considers the high-frequency factors and the nonlinearity of coal prices. • The probability density forecasts are satisfying. [ABSTRACT FROM AUTHOR]