An investigation into the disturbance effects of coal mining on groundwater and surface ecosystems.

Coal mining disturbs surface ecosystems in coal mining subsidence areas. Based on the groundwater-surface composite ecosystem analysis, we constructed an ecological disturbance evaluation index system (18 indices) in a coal mining subsidence area using the analytic hierarchy process (AHP). Taking the Nalinhe mining area in Wushen Banner, China, in 2018-2020 as an example, the weight, ecological disturbance grade and correlation of different indicators were determined by implementing fuzzy mathematics, weighting method, and correlation analysis method. The major conclusions of this review were: (i) After two years of mining, ecological disturbance was the highest in the study area (Grade III) and the lowest in the non-mining area (Grade I). (ii) Coal mining not only directly interfered with the environment, but also strengthened the connection of different ecological indicators, forming multiple ecological disturbance chains such as "mining intensity-mining thickness-buried depth/Mining thickness", "coal mining-surface subsidence-soil chemical factors", and "natural environment-soil physical factors". The disturbance chain that controls the ecological response factors in the region remains to be determined. However, the ecological response factors are the most important factor that hinders the restoration of the ecology in a coal mining subsidence area. (iii) The ecological disturbance in the coal mining subsidence area continued increasing over two years due to coal mining. The ecological disturbance by coal mining cannot be completely mitigated by relying on the self-repair capability of the environment. This study is of great significance for ecological restoration and governance of coal mining subsidence areas.

Analysis of carbon emission drivers of secondary industries in Energy "Golden Triangle" area based on LMDI and two-dimensional decoupling model.

As an essential energy and chemical base in China, carbon reduction in the Energy "Golden Triangle" (EGT) area is significant. This paper used the logarithmic mean Divisia index (LMDI) method to analyze the drivers of carbon emissions from secondary industry energy consumption (CESEC) in EGT from 2005 to 2019 and then used the GM (1,1) method to simulate carbon emissions in 2030. Meanwhile, the decoupling relationship between carbon emissions and economic development was also analyzed using the two-dimensional decoupling model to test the effectiveness of carbon reduction by the region's government. This paper showed the following: (1) CESEC in the EGT area increased from 1.89×108t to 2.617×108 t; (2) the economic output effect is the main factor influencing carbon emissions in the EGT area, followed by population effect and energy structure effect, while energy intensity effect mitigates carbon emissions; and (3) CESEC will peak at 12.362×108t in 2030, leaving an arduous task on carbon reduction. The two-dimensional decoupling condition between carbon emissions and economic growth in the EGT area is low level-weak decoupling (WD-LE) for 2005-2019. The decoupling condition in Yulin and Ningdong is concentrated in low level-expansion connection (EC-LE) and low level-weak decoupling (WD-LE). Furthermore, Erdos reached high level-expansion negative decoupling (END-HE) condition during 2015-2019. Based on the above findings, a low-carbon development strategy for EGT should consider improving emission reduction technologies for high-carbon energy sources like coal, adjusting the energy consumption structure and seeking government policy support for carbon reduction.