The structural transformation and reburning characteristics of gas coal in Ningwu coalfield fire

Xin, Haihui; Sun, Jianguo; Tian, Wenjiang; Zhou, Banghao; Tang, Zuo; Xu, Qihong; Di, Cui Cui; Zhong, Xiao Xing; Wang, De Ming

doi:10.1177/01445987211023866

Cited by 4 publications

(1 citation statement)

References 36 publications

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“…In addition, complex natural geographic conditions and frequent coal-mining activities have aggravated the fragility of the local ecological environment [45]. According to reports, this area has become one of the most serious areas of coal dust pollution and coal spontaneous combustion in Shanxi Province [46,47], and it is also accompanied by vegetation degradation and soil erosion [48,49]. Ningwu Coalfield has a history of large-scale coal mining for nearly 40 years and is very suitable for remote-sensing monitoring in long time-series.…”

Section: Study Areamentioning

confidence: 99%

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

Nie

Ruan

et al. 2022

Remote Sensing

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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.

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Section: Study Areamentioning

confidence: 99%

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

Nie

Ruan

et al. 2022

Remote Sensing

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Ecological environment quality assessment of coal mining cities based on GEE platform: A case study of Shuozhou, China

Duo,

Wang,

Zhong

et al. 2024

Int J Coal Sci Technol

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Shuozhou is a typical coal mining city, and the Pingshuo Antaibao open-pit coal mine in its area is one of the largest open-pit coal mines in China. The mining of coal resources is an important part of ensuring national energy security, and at the same time, it inevitably has a certain impact on the ecology, such as coal dust generated by open-pit mining will affect air quality, soil, water and vegetation. It is of great significance to explore the temporal and spatial variation of ecological environment quality in coal mining cities for ecological protection and sustainable social and economic development. Based on the Google Earth Engine (GEE) platform, this paper combines the index-based coal dust index (ICDI) and Remote Sensing Ecological Index (RSEI) models to construct an improved RSEI (IRSEI) that can reflect coal mining cities. This paper explores the spatial–temporal evolution characteristics and spatial correlation of ecological environment quality in Shuozhou from 2000 to 2020. The results showed that the average value of IRSEI in Shuozhou was between 0.262 and 0.418, and the overall change showed an upward trend. The growth areas of ecological environment quality are mainly located in the eastern and southwestern areas with good vegetation growth, and these regions have vigorously implemented the Northern Shelter Forest Project, afforestation and greening projects, implemented the forest resource management and protection responsibility system, promoted the construction of ecological civilization, and significantly improved the ecological environment. While the declining areas are mainly located in the central and southern regions where mining activities and human activities are more intensive. The IRSEI in the study area showed a significant spatial positive correlation, and the agglomeration types of the spatial pattern were mainly high-high and low-low agglomeration types, with the high-high agglomeration types mainly distributed in the eastern and southwestern regions, and the low-low agglomeration types distributed in the northern and south-central regions of the study area. The trend of low and low agglomeration has decreased, which further proves that the ecological restoration measures taken by the government, such as returning farmland to forests, integrating protection and restoration of mountains, waters, forests, fields, lakes, grasslands, and sands, controlling soil erosion, and stage wise reclamation of coal mining subsidence areas, have improved the ecological environment quality of Shuozhou. This study provides a reference for understanding the spatiotemporal changes of the ecological environment of coal mining cities, and is conducive to formulating appropriate ecological protection strategies.

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Fire zone forefront residual tar combustion characteristics and functional group transformation mechanism: Appling the based on thermogravimetric and in-situ high-temperature FTIR

Bai,

Xin,

Zhang

et al. 2024

Applied Thermal Engineering

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The structural transformation and reburning characteristics of gas coal in Ningwu coalfield fire

Cited by 4 publications

References 36 publications

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

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

Ecological environment quality assessment of coal mining cities based on GEE platform: A case study of Shuozhou, China

Fire zone forefront residual tar combustion characteristics and functional group transformation mechanism: Appling the based on thermogravimetric and in-situ high-temperature FTIR

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