Assessment of coal mining land subsidence by using an innovative comprehensive weighted cloud model combined with a PSR conceptual model

Xu, Chun; Zhou, Keping; Xiong, Xin; Gao, Feng

doi:10.1007/s11356-021-17052-x

Cited by 9 publications

(3 citation statements)

References 37 publications

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“…One of the main problems is land collapse owing to underground coal mining (Li et al, 2022). For example, every 10,000 tons of underground coal mining in China will lead to approximately 0.002-0.0033 km 2 of land subsidence (Xu et al, 2022). By the end of 2017, the subsidence area created by underground coal mining exceeded 20,000 km 2 , with a growth rate of approximately 700 km 2 per year in China (Chen et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Seasonal succession of microbial community co-occurrence patterns and community assembly mechanism in coal mining subsidence lakes

Fang

Fan

et al. 2023

Front. Microbiol.

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Coal mining subsidence lakes are classic hydrologic characteristics created by underground coal mining and represent severe anthropogenic disturbances and environmental challenges. However, the assembly mechanisms and diversity of microbial communities shaped by such environments are poorly understood yet. In this study, we explored aquatic bacterial community diversity and ecological assembly processes in subsidence lakes during winter and summer using 16S rRNA gene sequencing. We observed that clear bacterial community structure was driven by seasonality more than by habitat, and the α-diversity and functional diversity of the bacterial community in summer were significantly higher than in winter (p < 0.001). Canonical correspondence analysis indicated that temperature and chlorophyll-a were the most crucial contributing factors influencing the community season variations in subsidence lakes. Specifically, temperature and chlorophyll-a explained 18.26 and 14.69% of the community season variation, respectively. The bacterial community variation was driven by deterministic processes in winter but dominated by stochastic processes in summer. Compared to winter, the network of bacterial communities in summer exhibited a higher average degree, modularity, and keystone taxa (hubs and connectors in a network), thereby forming a highly complex and stable community structure. These results illustrate the clear season heterogeneity of bacterial communities in subsidence lakes and provide new insights into revealing the effects of seasonal succession on microbial assembly processes in coal mining subsidence lake ecosystems.

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Section: Introductionmentioning

confidence: 99%

Seasonal succession of microbial community co-occurrence patterns and community assembly mechanism in coal mining subsidence lakes

Fang

Fan

et al. 2023

Front. Microbiol.

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“…The PSR model was utilized to develop an evaluation system for multi-source coalbased site control. This involves establishing an evaluation index system, determining positive and negative indicators, standardizing the indicator data, employing the entropy weighting method to calculate the weights, and computing the evaluation composite score [26][27][28]. Pressure indicators include human behaviors that positively or negatively impact the environment.…”

Section: "Pressure-state-response" Control Evaluationmentioning

confidence: 99%

Precise Identification of Site Characteristics and Risk Management of Ningdong Coal Power Base

Ren,

Feng,

et al. 2023

Land

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With the active development of coal-related industries in Ningdong, problems such as land degradation caused by coal-based site expansion and soil pollution caused by coal-based solid waste discharge are getting progressively worse. The identification of space types and the proposal of risk management are the key basic issues of regional energy resource low-carbon development and ecological protection. This article proposes an index system for feature extraction at the regional and site scales. The spatial–temporal evolution trends and differences in Ningdong coal power base from 2003 to 2021 were identified and interpreted through feature recognition based on Landsat images at the regional scale. Accurate site type recognition was conducted based on 10 m resolution Sentinel-2 images from 2021. We utilized the PSR (pressure–state–response) model for a comprehensive assessment of risk management in Ningdong. The results of this study show that the coal site > the coal chemical site > the coal power site, and the risk of the coal power base is in a controllable state; thus, we put forward a zoning control strategy. Our data on the pollution risk management of large-scale coal-fired power generation complexes are of significant importance for site remediation and regional ecological restoration.

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“…First, geological survey and statistical analysis determined the influence factors of loess slope stability. Then, combined with the results of multivariable finite element numerical calculation and the gray correlation method [38,39], the classification standard of loess slope stability was obtained, and the fuzzy comprehensive evaluation model of loess slope stability was established using the principle of maximum membership degree [40]. Finally, the fuzzy comprehensive evaluation model for assessing the stability of loess slopes was implemented in practical engineering, subsequently validated and compared against real-time slope monitoring data.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Comprehensive Evaluation Method for Evaluating Stability of Loess Slopes

Deng,

Xiang

2023

Advances in Civil Engineering

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The stability assessment of loess slopes is of great significance for slope reinforcement and safety assessment. This research studies the main factors affecting the stability of the loess slope through the summary and analyzes the failure cases of the loess slope in Shaanxi Province. The importance of influencing factors was studied through numerical simulation method, sensitivity analysis method, and gray correlation analysis method, and the weight value method was given. On this basis, we have developed the fuzzy comprehensive evaluation model method for assessing the stability of loess slopes based on the principle of maximum membership degree. Finally, the method was applied to the stability analysis of the actual loess slope, and the rationality and correctness of the loess slope stability evaluation method proposed in this paper were demonstrated. The results showed that, for the Shaanxi loess slope, the probability of instability of the positive slopes is far greater than that of negative slopes; the greater the slope gradient, the more unstable the loess slopes. Collapse mainly occurs in the range of 10–40 m slope height. There is a significant positive correlation between rainfall and the probability of loess landslides. The degree of correlation between the factors influencing slope stability and the safety factor can be categorized from strong to weak as follows: slope inclination > internal friction angle > height of the slope > gravitational forces > cohesion > Poisson’s ratio > modulus of elasticity, and the influence of Poisson’s ratio and elastic modulus can be ignored. The fuzzy comprehensive evaluation method based on the gray correlation degree method established in this paper was used to evaluate the stability of the loess slopes. The evaluation results attested to the actual data of slope monitoring. The evaluation method proves reasonable and feasible and can be well applied to the stability analysis of the loess slopes.

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Assessment of coal mining land subsidence by using an innovative comprehensive weighted cloud model combined with a PSR conceptual model

Cited by 9 publications

References 37 publications

Seasonal succession of microbial community co-occurrence patterns and community assembly mechanism in coal mining subsidence lakes

Seasonal succession of microbial community co-occurrence patterns and community assembly mechanism in coal mining subsidence lakes

Precise Identification of Site Characteristics and Risk Management of Ningdong Coal Power Base

Fuzzy Comprehensive Evaluation Method for Evaluating Stability of Loess Slopes

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