Hydrochemical characteristics and influencing factors of mine water in Tangjiahui mining area

Abstract In water-deficient areas, the reuse of water discharged from coal mining is highly desirable. In order to study the water quality in the Tangjiahui mining area in Jungar Coalfield (Inner Mongolia, China), 34 groups of mine water samples collected at various stages during coal mining process were analyzed for their hydrochemical characteristics using conventional and statistical methods. A Piper trilinear diagram was used to analyze the main ion composition characteristics and the hydrochemical type of the mine water. Gibbs map and ion correlation methods were used to investigate the sources and influencing factors of the main ions in mine water. The results showed that the TH of the mine water in the study area was in the range of 219.52–390.6 mg/L with an average of 315.04 mg/L, which can be classified as slightly hard/ hard water. The TDS was in the range of 926.61–1889.56 mg/L with an average of 1514.31 mg/L, which mostly belongs to brackish water. The cation content in the mine water was ranked from the highest to the lowest as Na + > Ca 2+ > Mg 2+ , while the anion content was ranked as Cl − > HCO 3 − > SO 4 2− . The Na + mass concentration was in the range of 179.00–523.06 mg/L with an average of 399.77 mg/L, while the Cl − mass concentration was in the range of 207.10–812.63 mg/L with an average of 550.88 mg/L. The hydrochemical type of the mine water was Cl-Na. According to the correlation matrix of the various chemical indicators in the mine water, the TDS was significantly positively correlated with Na + , Ca 2+ , Cl − , and SO 4 2− . Of these, the main sources of TDS were Na + and Cl − , as these had correlation coefficients > 0.9. The hydrochemical characteristics of the mine water were mainly controlled by the condensation-crystallization and anti-cation exchange, which indicated the main ions were largely derived from the dissolution of halite . Due to its high TDS, EC,SAR, and Na% values, the mine water in the study area was not suitable for human consumption and agricultural irrigation. These results can provide a reference towards water resource management and the sustainable use of mine water by local governments.

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Effect of Meteorological Parameters on Fine and Coarse Particulate Matter Mass Concentration in a Coal-Mining Area in Zonguldak, Turkey

Journal of the Air & Waste Management Association ◽

10.3155/1047-3289.58.4.543 ◽

2008 ◽

Vol 58 (4) ◽

pp. 543-552 ◽

Cited By ~ 53

Author(s):

Lokman Hakan Tecer ◽

Pinar Süren ◽

Omar Alagha ◽

Ferhat Karaca ◽

Gürdal Tuncel

Keyword(s):

Particulate Matter ◽

Coal Mining ◽

Mass Concentration ◽

Meteorological Parameters ◽

Mining Area ◽

Coal Mining Area ◽

Coarse Particulate Matter

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Prediction and Maintenance of Water Resources Carrying Capacity in Mining Area—A Case Study in the Yu-Shen Mining Area

Sustainability ◽

10.3390/su12187782 ◽

2020 ◽

Vol 12 (18) ◽

pp. 7782

Author(s):

Yujun Xu ◽

Liqiang Ma ◽

Naseer Muhammad Khan

Keyword(s):

Water Resources ◽

Prediction Model ◽

Coal Mining ◽

Carrying Capacity ◽

Mine Water ◽

Water Conservation ◽

Ground Deformation ◽

Mining Area ◽

Water Resources Carrying Capacity ◽

Mining Methods

The problem of water resources damage caused by coal mining has restricted the sustainable development of Yu-Shen mining area. Illustrating the relationship between mining and water resources carrying capacity is of great significance to solve this problem. In this study, the authors proposed an appraisal and prediction model of water resource carrying capacity in the mining area (WRCCMA) based on the analytic hierarchy process (AHP)-fuzzy comprehensive evaluation method. A triple-leveled structure model was developed, and the main influencing factors of the WRCCMA and the membership functions were analyzed. The prediction model was applied to Yubujie colliery to test its validity by investigating the changes of vegetation coverage and the ground deformation of the colliery and its adjacent coal mine before and after mining. Subsequently, we obtained the WRCCMA of the study area and zoning map of different grades of WRCCMA in the mining area by applying this model to the whole Yu-Shen mining area. Furthermore, three countermeasures to maintain the WRCCMA and realize water conservation coal mining (WCCM) were provided to collieries with different WRCCMA grades, including mining methods selection, mine water reutilization, and water-resisting layer reconstruction. Reasonable mining methods and water-resisting layer reconstruction can reduce the development of water conductive fractures and thus prevent groundwater from penetrating into the goaf. Mine water reutilization provides a source of water demand for collieries and families, contributing to the reduction of abstraction of water resources. These three countermeasures can help to maintain the WRCCMA. This paper successfully combines the fuzzy theory with mining engineering and provides theoretical and practical guidance for other mining areas in arid and semi-arid regions of Northwest China.

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Prediction of Soil Nutrients Based on Topographic Factors and Remote Sensing Index in a Coal Mining Area, China

Sustainability ◽

10.3390/su12041626 ◽

2020 ◽

Vol 12 (4) ◽

pp. 1626

Author(s):

Hongfen Zhu ◽

Ruipeng Sun ◽

Zhanjun Xu ◽

Chunjuan Lv ◽

Rutian Bi

Keyword(s):

Remote Sensing ◽

Least Squares ◽

Coal Mining ◽

Partial Least Squares ◽

Influencing Factors ◽

Soil Nutrients ◽

Partial Least Squares Regression ◽

Mining Area ◽

Least Squares Regression ◽

Coal Mining Area

(1) Background: Coal mining operations caused severe land subsidence and altered the distributions of soil nutrients that influenced by multiple environmental factors at different scales. However, the prediction performances for soil nutrients based on their scale-specific relationships with influencing factors remains undefined in the coal mining area. The objective of this study was to establish prediction models of soil nutrients based on their scale-specific relationships with influencing factors in a coal mining area. (2) Methods: Soil samples were collected based on a 1 × 1 km regular grid, and contents of soil organic matter, soil available nitrogen, soil available phosphorus, and soil available potassium were measured. The scale components of soil nutrients and the influencing factors collected from remote sensing and topographic factors were decomposed by two-dimensional empirical mode decomposition (2D-EMD), and the predictions for soil nutrients were established using the methods of multiple linear stepwise regression or partial least squares regression based on original samples (MLSROri or PLSROri), partial least squares regression based on bi-dimensional intrinsic mode function (PLSRBIMF), and the combined method of 2D-EMD, PLSR, and MLSR (2D-EMDPM). (3) Results: The correlation types and correlation coefficients between soil nutrients and influencing factors were scale-dependent. The variances of soil nutrients at smaller scale were stochastic and non-significantly correlated with influencing factors, while their variances at the larger scales were stable. The prediction performances in the coal mining area were better than those in the non-coal mining area, and 2D-EMDPM had the most stable performance. (4) Conclusions: The scale-dependent predictions can be used for soil nutrients in the coal mining areas.

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