scholarly journals Geologic setting and water quality of selected basins in the active coal-mining areas of Ohio, 1989-91, with a summary of water quality for 1985-91

1993 ◽  
Keyword(s):  
Water Quality ◽  
Coal Mining ◽  
Mining Areas ◽  
Active Coal ◽  
Geologic Setting

INFLUENCE OF ROSIA POIENI AND ROSIA MONTANA MINING AREAS ON THE WATER QUALITY OF THE ARIES RIVER

2011 ◽  
Vol 10 (1) ◽  
pp. 23-29 ◽  
Author(s):  
Erika Levei ◽  
Marin Senila ◽  
Mirela Miclean ◽  
Bela Abraham ◽  
Cecilia Roman ◽  
...  
Keyword(s):  
Water Quality ◽  
Mining Areas ◽  
Rosia Montana

scholarly journals Seasonal Assessment of Groundwater Contamination in Coal Mining Areas of Balochistan

2020 ◽  
Vol 12 (17) ◽  
pp. 6889
Author(s):  
Ayesha Ayub ◽  
Sheikh Saeed Ahmad
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Coal Mining ◽  
Coal Mines ◽  
Physicochemical Analysis ◽  
Current Status ◽  
Mining Sites ◽  
Mining Areas ◽  
Quality Of Water ◽  
Who Standards

Balochistan is a semi-arid region. The assessment of water quality is very important, as the majority of people depend on groundwater for drinking purposes. The present study involves the quality assessment and mapping of drinking water in the five selected major coal mining sites in the four districts of Balochistan. A total of 50 samples were collected from these five coal mining sites in two seasons: i.e., summer and winter. A physicochemical analysis was carried out for groundwater samples: i.e., pH, electrical conductivity (EC), total dissolved solid (TDS), CO3, HCO3-, Cl-, Ca2+, Mg2+, Na+, K+, Cd, Cr, Co, Cu, Fe, Pb, Mn, Hg, Ni, and Zn. Thematic maps were used to depict the spatial distribution of significant variables and were compared with WHO standards (2011) during both seasons. The majority of parameters crossed the safe permissible limit of WHO standards. The water quality index (WQI) was calculated for the whole monitoring data obtained from both seasons from the perspective of drinking water in each of the selected sites. Moreover, a principle component analysis (PCA) and correlation matrix was carried out for the data analysis in order to identify the source of pollution and correlation among the variables. The results suggested that the overall quality of water from the selected coal mining sites deteriorated due to the overexploitation of coal mines and mining activity. The current investigation provides a comprehensive picture of the current status of water quality in and around the selected coal mines of Balochistan.

scholarly journals Remote-Sensing Evaluation and Temporal and Spatial Change Detection of Ecological Environment Quality in Coal-Mining Areas

2022 ◽  
Vol 14 (2) ◽  
pp. 345
Author(s):  
Xinran Nie ◽  
Zhenqi Hu ◽  
Mengying Ruan ◽  
Qi Zhu ◽  
Huang Sun
Keyword(s):  
Coal Mining ◽  
Coal Mine ◽  
Large Scale ◽  
Coal Dust ◽  
Ecological Environment ◽  
Ecological Index ◽  
Mining Areas ◽  
Environment Quality ◽  
Temporal And Spatial

The large-scale development and utilization of coal resources have brought great challenges to the ecological environment of coal-mining areas. Therefore, this paper has used scientific and effective methods to monitor and evaluate whether changes in ecological environment quality in coal-mining areas are helpful to alleviate the contradiction between human and nature and realize the sustainable development of such coal-mining areas. Firstly, in order to quantify the degree of coal dust pollution in coal-mining areas, an index-based coal dust index (ICDI) is proposed. Secondly, based on the pressure-state-response (PSR) framework, a new coal-mine ecological index (CMEI) was established by using the principal component analysis (PCA) method. Finally, the coal-mine ecological index (CMEI) was used to evaluate and detect the temporal and spatial changes of the ecological environment quality of the Ningwu Coalfield from 1987 to 2021. The research shows that ICDI has a strong ability to extract coal dust with an overall accuracy of over 96% and a Kappa coefficient of over 0.9. As a normalized difference index, ICDI can better quantify the pollution degree of coal dust. The effectiveness of CMEI was evaluated by four methods: sample image-based, classification-based, correlation-based, and distance-based. From 1987 to 2021, the ecological environment quality of Ningwu Coalfield was improved, and the mean of CMEI increased by 0.1189. The percentages of improvement and degradation of ecological environment quality were 71.85% and 27.01%, respectively. The areas with obvious degradation were mainly concentrated in coal-mining areas and built-up areas. The ecological environment quality of Pingshuo Coal Mine, Shuonan Coal Mine, Xuangang Coal Mine, and Lanxian Coal Mine also showed improvement. The results of Moran’s Index show that CMEI has a strong positive spatial correlation, and its spatial distribution is clustered rather than random. Coal-mining areas and built-up areas showed low–low clustering (LL), while other areas showed high–high clustering (HH). The utilization and popularization of CMEI provides an important reference for decision makers to formulate ecological protection policies and implement regional coordinated development strategies.

scholarly journals Research on Temporal and Spatial Resolution and the Driving Forces of Ecological Environment Quality in Coal Mining Areas Considering Topographic Correction

2021 ◽  
Vol 13 (14) ◽  
pp. 2815
Author(s):  
Xinran Nie ◽  
Zhenqi Hu ◽  
Qi Zhu ◽  
Mengying Ruan
Keyword(s):  
Remote Sensing ◽  
Coal Mining ◽  
Coal Mine ◽  
Ecological Environment ◽  
Topographic Correction ◽  
Ecological Index ◽  
Mining Areas ◽  
Environment Quality ◽  
Temporal And Spatial

Over the last few years, under the combined effects of climate change and human factors, the ecological environment of coal mining areas has undergone tremendous changes. Therefore, the rapid and accurate quantitative assessments of the temporal and spatial evolution of the ecological environment quality is of great significance for the ecological restoration and development planning of coal mining areas. This study applied the ecological environment index after topographic correction to improve the remote sensing ecological index (RSEI). Based on a series of Landsat images, the ecological environment quality of Yangquan Coal Mine in Shanxi Province from 1987 to 2020 was monitored and evaluated by an improved remote sensing ecological index. The results show that after topographic correction, the topographic effect of the remote sensing ecological index was greatly reduced, and its practicability was improved. From 1987 to 2020, the ecological environment quality of Yangquan Coal Mine was improved, and the mean of the RSEI increased from 0.4294 to 0.6379. The ecological environment quality of the six coal mines in the study area was improved. Among the six coal gangue dumps, the ecological environmental quality of D1, D2, D3, and D4 has improved, and the ecological environment quality of D5 and D6 worsened. The percentages of improved, unchanged, and degraded ecological environment quality in the entire coal mining area were 77.08%, 0.99%, and 21.93%, respectively. The global Moran’s index was between 0.7929 and 0.9057, and it was shown that there was a strong positive correlation between the ecological environmental qualities of the study area, and that its spatial distribution was clustered rather than random. The LISA cluster map showed that the aggregation and dispersion degree of ecological environment quality was mainly high–high clustering and low–low clustering over the whole stage. During the study period, temperature and precipitation had limited impacts on the ecological environment quality of Yangquan Coal Mine, while the coal mining activities and urbanization construction seriously affected the local ecological environment quality and the implementation of ecological restoration policies, regulations, and measures was the main reason for the improvement of the ecological environment quality.

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