Search

Coal mining in Shendong Mining area has an important impact on the local ecological environment, especially the growth of vegetation. In order to describe this effect quantitatively, this study uses a regional evapotranspiration model to calculate the Potential Net Primary Productivity (PNP,p) of the Shendong mining area. MODIS17A3 dataset (2001—2022) was used to characterize the Actual Net Primary Productivity (PNP,a), and combined with the monthly net primary productivity raster dataset of terrestrial ecosystems in China (PNP,al, 1988—2015), using GWR model construction correction method to correct PNP,al to obtain 1988—2000 PNP,a data, and using the difference between the two PNP,h to characterize the impact of coal mining. The effect of coal mining on vegetation PNP in Shendong mining area was evaluated. The results show that: ① the accuracy of PNP,al data corrected by GWR model is about 0.76, and the corrected PNP,al data has a strong spatial correlation with the MODIS17A3 dataset, which indicates the reliability of the accuracy of the corrected model; ② The overall PNP,a and PNP,h of Shendong mining area showed a trend of decreasing first and then recovering gradually, but the PNP of vegetation did not recover to the pre-mining level. The mean values of PNP,h before mining and PNP,h after mining are 21.50 g/m2 and −60.20 g/m2, respectively. PNP,h

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

[Objective] The impacts of a metal mine on the surrounding grassland were studied, and the ecological environment was evaluated using remote sensing technology as a significant aid to ecological restoration and environmental protection of mining areas. [Methods] The study was conducted at a desert-steppe gold mine located in an ecologically fragile area. Spatial and temporal dynamics of normalized difference vegetation index (NDVI) in the mine area were analyzed based on long time series remote sensing data to conduct a comprehensive evaluation of the ecological quality of the study area using the remote sensing ecological index (RSEI). [Results] The impacted area of desert-steppe gold mining was determined as the area with a radius of 5 km outward from the mine boundary. There was a fluctuating increase in NDVI values in the mine and impact areas that varied with the duration of mining in the steppe from 2009 to 2021. The annual average value of NVDI within the mine area during the underground mining operation period was 51.9% higher than during the open pit mining operation period. In addition, the impact of open pit mining on vegetation in the study area was higher compared with underground mining. The RSEI values in the mining area and the impacted area initially increased, then decreased, and then stabilized, resulting in an overall non-significant increase. The spatial distribution of RSEI indicated that the areas with poor ecological environmental quality in the mine and impact areas were mainly the waste dump and surrounding area. [Conclusion] Gold mining influenced the surrounding desert grassland within a radius of 5 km from the mine. The ecological environment of the mine and the impacted area gradually improved through management efforts during mining. Ecological restoration and environmental management of the waste dump and the surrounding area should be strengthened during the process of mine ecological construction.

Copyright of Bulletin of Soil & Water Conservation is the property of Bulletin of Soil & Water Conservation Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The karst groundwater in the catchment area of the Sangu Spring plays an important supporting role in the residents' living and coal base construction in southeastern Shanxi Province.With the large-scale coal mining and the intensification of human activities, the hydrochemistry of the regional karst groundwater has changed drastically. In this study, 125 karst groundwater, 14 surface water and 14 rain water samples were collected and tested. The descriptive statistical analysis, coefficient of variation analysis, hydrogen and oxygen stable isotopes, Gibbs model, ion correlation, mineral saturation index and factor analysis are comprehensively used to determine the replenishment sources of the karst groundwater, the differences of hydrochemical characteristics and evolution mechanism among the subsystems. The results show that the δD and δ18O values of the karst groundwater range from −77‰ to −42‰ and from −10.6‰ to −4.5‰, respectively, and the data points fall near the local meteoric water line (LMWL), indicating that the karst groundwater are mainly recharged by infiltration from precipitation. The hydrochemical characteristics and hydrogeochemical evolution processes between subsystems Ⅰ and Ⅱ-Ⅲwere obviously different. The karst groundwater of subsystem Ⅰhas low salinity and is soft water, and 73% of the groundwater is of HCO3—Ca(Mg) type. However, the karst groundwater in subsystems Ⅱ and Ⅲ changes from low salinity and soft water to high salinity and hard water, and 36% to 40% of the water is of HCO3·SO4—Ca·Mg type and 24% to 45%, of SO4·HCO3—Ca type. Factor analyses show that the hydrochemical evolution processes of the regional karst groundwater are mainly controlled by water-rock interactions, human activities, leakage of surface water and local fissure water. Hydrochemical compositions of \begin{document}${\rm{HCO}}_3^- $\end{document}, \begin{document}${\rm{SO}}_4^{2-} $\end{document}, Ca2+ and Mg2+are mainly controlled by water-rock interactions. A higher concentration of \begin{document}${\rm{SO}}_4^{2-} $\end{document} is controlled by mining activities, \begin{document}${\rm{NO}}_3^- $\end{document} is controlled by agriculture activities and Cl−and Na+are controlled by sewage discharge and leakage of fissure water. The results will be instructive for improving the management and utilization of groundwater resources for the local government.

Copyright of Hydrogeology & Engineering Geology / Shuiwendizhi Gongchengdizhi is the property of Hydrogeology & Engineering Geology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the past 30 years, the global normalized difference vegetation index (NDVI) showed an increasing trend, the start of the vegetation growing season (SOS) was advanced, the end of the growing season (EOS) was delayed and the length of growing season (LOS) was prolonged. As the most intensive industrial and mining area of human economic activities, its ecological environment is one of the focal issues of environment and development. Under the background of global climate change, the NDVI trend in the mining area and around can well reflect vegetation change in non-natural ecological zones and its response to global change at regional scale. Based on the long-term sequence of GIMMS AVHRR NDVI3g remote sensing images, the phenological information of vegetation cover was extracted by using IDL programming, linear regression and trend fitting in the study area from 1982 to 2013. Analyzing the monthly, quarterly and annually variations of the mining area, buffer zone (10 km, 20 km) and its calibration area, the variation trends in SOS, EOS and LOS length were obtained, and finally the correlation between the climatic driving factors (i. e. precipitation, temperature) and the change of NDVI was analyzed combined with meteorological records. The temporal-correlation analysis demonstrates that the average annual NDVI of Binchang mining area increased slowly with an annual growth rate of 13. 31% over the past 32 years. But the total NDVI in natural ecological check area (CK) showed apparent growth trend with an annual growth rate up to 19. 45%. Therefore, it can be concluded that the annual growth rate of NDVI in mining areas is significantly lower than that in the CK under the influence of human activities. Spatial-correlation analysis indicates that the original NDVI value of the Binchang mining area is higher than that of the CK. In the mining area, the vegetation SOS is 6±3 days ahead of time, the EOS lags behind 5±3 days and the LOS extends 11±3 days. The corresponding values in the CK area are 3±3 days, 3±3 days and 6±3 days, respectively. The extension of LOS in the mining area is longer than that in CK for 6 days. Climate-correlation analysis shows that Binchang mining area is located in the semi-humid climate zone. As a result, the response of vegetation to temperature change is higher than to precipitation, and vegetation growth has a lag of 2 to 3 years in response to precipitation. In other word, the increase of NDVI depends on the interactions of temperature rise and precipitation decrease. The study concludes that the mining activities slow down the vegetation growth in the mining area and around, and the annual growth rate of NDVI is obviously lower than that in the CK. Under the effects of global change and based on the extension of LOS, the vegetation LOS extends further in the mining area due to the human activities. [ABSTRACT FROM AUTHOR]

To explore the source and pollution characteristics of soil arsenic, mineralogy and chemical analysis methods were used to analyze the ore, waste rock, sediment, and river and soil samples around the mining area. Under a polarized light microscope, As-bearing mineral-arsenopyrite was found in the soil, ore, and waste rock around the Banbishan gold mine. Moreover, arsenopyrite in the waste rock has already experienced weathering and oxidation, and the oxidized arsenopyrite easily migrates and is released in the soil, which is potentially harmful. Because of the effect of mining transportation activities and indigenous smelting, arsenic was mainly distributed in the topsoil, at a depth of 0-20 cm, in the farmland on both sides of the road and in the places where villagers were gathered. The soil arsenic content in Xiaowulan Village and Gaozhangzi Village ranged from 7.2 to 196.2 mg·kg -1 and exceeded the rate of arsenic by 45.9% and 82.1%. According to the assessment by the RAC method, the farmland soil in Xiaowulan Village and Gaozhangzi Village were mainly at low to medium risk, although some soil points in Xiaowulan Village were at high risk. In general, the effects of the mining activities of the surrounding environment were not optimistic. As-bearing minerals in the oxidation of long-term weathering can cause much arsenic to be activated, which in turn, affects the local crops and long-term residents living around the mining area. It is suggested to carry out risk assessments for arsenic in the soil-crop-atmospheric-human system, and further study the conversion rules and mechanisms of arsenopyrite during weathering, to provide scientific guidance for the environmental protection of cultivated land.