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The present research was carried out to examine the health and environmental impacts associated with coal mining activities in the Makarwal coal mining area in Pakistan. To achieve the objectives, 41 soil samples were collected from the coalmine-affected areas and analyzed for major and toxic trace elements (TTEs) using atomic absorption spectroscopy. Most of the soil samples have extremely high concentrations of toxic metals such as Ni, Cd, Cr, Cu, Zn, and Pb. The positive correlations and high concentration of trace elements in the Makarwal coalmine-affected region suggest an analogous origin of soil contamination. The factor analysis (FA) showed two components, i.e., F1 (53.4%) and F (74.21%), of total variability for soil. The F2 was loaded with Pb, Zn, Ni, and Cr, which was similar to cluster 2, while the F1 was loaded with Cu and Cr, having a similar pattern to cluster 1. This proves that the contamination in the surrounding area is mostly associated with geological ore strata existing in the Makarwal coalfield. Based on geoaccumulation (Igeo), the elemental concentration in the studied soil sample could be categorized as follows: (1) Pb, Ni, and Zn are moderate to severely polluted and (2) Cr and Cu are in the moderately polluted category. The ecological risk indices (ERIs) of the single trace element contamination index highlighted that Cd, Pb, Ni, and Cr pose a high risk to humans and the ecosystem. Based on different statistical tools performed for the source identification and distribution of metal contamination, it seems that the exposed sedimentary rocks, including limestone, dolomite, sandstone, and coal, are responsible for the toxic metal contamination in the study area. [ABSTRACT FROM AUTHOR]

Roof strata control is crucial to production safety in underground coal mines. In this study, a field trial was carried out involving large-scale hydraulic fracturing (LHF) to weaken strong, hard-to-cave rock strata above a longwall panel in an underground coal mine. Comprehensive monitoring was performed to monitor the generated hydraulic fractures, mining-induced pressure, periodic roof weighting, and microseismic events. The results suggest that LHF greatly promotes the caving of strong, hard-to-cave roofs behind the longwall face, which results in many favorable outcomes including a significant reduction of the periodic roof weighting (PRW) interval and likelihood of a long PRW duration. The PRW intensity is also dramatically mitigated on the longwall face, and the strong dynamic load pressures resulting from the massive roof rupture are largely eliminated. More importantly, LHF can significantly release mining-induced stress and alleviate microseismic events resulting from the fracturing of thick, strong rock strata above the gob area of a longwall panel. This approach shows promise as an efficient measure for the ground control of longwall entries and prevention of coal bursts. Highlights: A field trial was carried out using large-scale hydraulic fracturing to weaken strong overlying rock strata in an underground coal mine. Large-scale hydraulic fracturing in long directional drilling boreholes can generate highly expanded hydraulic fractures. Large-scale hydraulic fracturing promotes the caving of strong, hard-to-cave roofs. Large-scale hydraulic fracturing can release mining-induced stress and alleviate microseismic events. [ABSTRACT FROM AUTHOR]

Mine water inrush seriously threatens the safety of coal mine production. Quick and accurate identification of mine water inrush sources is of great significance to preventing mine water hazards. This paper combined partial least squares-discriminate analysis (PLS-DA) with inrush water chemical composition to identify the source of water inrush from multiple aquifers in mines. The Renlou Coal Mine in the Linhuan mining area was selected for this study, and seven conventional water chemical compositions from 54 water samples in three aquifers were collected and tested, of which 45 water samples were used to establish the PLS-DA discriminant model, and nine were used to test the prediction effect. To improve model accuracy and predictive ability, hierarchical clustering analysis method was used to eliminate seven unqualified water samples to reduce the errors caused by improper data. PCA and PLS-DA methods were used to analyze and process the remaining water sample data, and on the basis of PCA analysis, the remaining 38 water samples were used to establish the PLS-DA discriminant model. The model was validated using permutation and external prediction tests. The research shows the following results: (1) Both PCA and PLS-DA methods can distinguish water samples from three different water sources, but the classification effect of PLS-DA was better than PCA because it can strengthen the difference of water chemical composition between different water sources. (2) The correct discrimination rate of the PLS-DA discriminant model was as high as 100%, and permutation tests showed that the model was not overfit. External validation found that the model had good stability and discrimination. (3) HCO3- and total dissolved solids (TDS) were the most important differential marker compositions that affected the discrimination results based on Variable Importance for the Projection (VIP) scores. The discriminant model established in this study combined the advantages of principal component analysis and multiple regression analysis, providing a new method for accurately identifying the sources of water inrush in mines. [ABSTRACT FROM AUTHOR]

This study was conducted to evaluate ecological impacts of metals in soil from the restored Panyi coal mining area of China. Zn, Cr, Ni, Pb and Cd had significantly accumulated in the studied soil compared with regional background values ( p < 0.05). Geo-accumulation indices indicate that the soil was at low risk for Cu, Zn, Ni and Pb contamination, while a low to moderate risk for Cr and Cd contamination existed. The ecological impact of all the selected metals was identified by ecological soil screening levels, apart from Cr, the impact of which was determined based on Dutch Target and Intervention Values. Results suggest that plants may be significantly affected by Ni, the avian population by Zn, Pb and Cd, while mammals are possibly influenced by Cd. [ABSTRACT FROM AUTHOR]

Conventional hydrogeochemical data and environmental stable isotopes are used to identify the recharge sources and the water-rock interactions in the groundwater-flowing direction within the multilayer groundwater system of the Sulin coal-mining district in the north Anhui province in China. δD and δO of groundwater in the mining district decrease along the groundwater-flowing direction in the recharge areas, yet in the runoff or discharge areas, they rise and fall along average δ values ( δO = −8.68 ‰, δD = −67.4 ‰), which are lower than average δ values of local atmospheric precipitation ( δO = −7.80 ‰, δD = −52.4 ‰). Principal component analysis is used to analyze the conventional hydrogeochemical data (K + Na, Mg, Ca, Cl, SO, HCO, CO) in the groundwater. The first and second principal components have large variance contributions, and represent 'pyrite oxidation or groundwater hardening' and 'desulfurization or cation exchange and adsorption,' respectively. From conventional hydrogeochemical data and environmental stable isotopes, it is demonstrated that groundwater of the Sulin coal-mining district is characterized by a mixing type, which is confirmed by three recharge end-members: fresh groundwater, leaching groundwater, and retained groundwater. By means of a sample dot-encompassed triangle in the scatter diagram of load scores for Component 1-Component 2, whose vertexes stand for the three end-members, a model for calculating groundwater mixing ratio is established and applied successfully to the evaluation and management of groundwater hazards in the coal-mining districts. [ABSTRACT FROM AUTHOR]