A study of the assessment and management of air quality was carried out at 11 coal mines in India. Long-term observations (about 13 years, March 2000-December 2012) and modeling of aerosol loading over coal mines in India are analyzed in the present study. In this respect, the Box-Jenkins popular autoregressive integrated moving average (ARIMA) model was applied to simulate the monthly mean Terra Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD550 nm) over 11 sites in the coal mines region. The ARIMA model was found as the most suitable model with least normalized Bayesian information criterion (BIC) and root mean square error and high value of R (2). Estimation was done with the Ljung-Box test. Finally, a forecast for a 3-year period from January 2013 to December 2015 was calculated which showed that the model forecasted values are following the observed trend quite well over all mining areas in India. The average values of AOD for the next 3 years (2013-2015) at all sites are found to be 0.575 ± 0.13 (Raniganj), 0.452 ± 0.12 (Jharia), 0.339 ± 0.13 (Bokaro), 0.280 ± 0.09 (Bishrampur), 0.353 ± 0.13 (Korba), 0.308 ± 0.08 (Talcher), 0.370 ± 0.11 (Wardha), 0.35 ± 0.10 (Adilabad), 0.325 ± 0.09 (Warangal), 0.467 ± 0.09 (Godavari Valley), and 0.236 ± 0.07 (Cuddapah), respectively. In addition, long-term lowest monthly mean AOD550 values are observed over Bishrampur followed by Cuddapah, Talcher, Warangal, Adilabad, Korba, Wardha, Godavari Valley, Jharia, and Raniganj. Raniganj and Jharia exhibit the highest AOD values due to opencast mines and extensive mining activities as well as a large number of coal fires. Similarly, the highest AOD values are observed during the monsoon season among all four seasons over all the mining sites. Raniganj exhibits the highest AOD value at all seasons and at all sites. In contrast, the lowest seasonal AOD values are observed during the post-monsoon season over Raniganj, Talcher, Wardha, Adilabad, Warangal, and Godavari Valley. Similarly, over Jharia, Bokaro, Bishrampur, Korba, and Cuddapah, the lowest AOD values are found in the winter season. Increasing trends in AOD550 have been observed over Raniganj, Bokaro, Bishrampur, Korba, Talcher, and Wardha as well as over Adilabad and Godavari Valley, which is in agreement with previous works. Negative or decreasing AOD trend is found only over Jharia, Warangal, and Cuddapah without being statistically significant. Seasonal trends in AODs have also been studied in the present paper.
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Sci Rep
January 2025
College of Environment and Bioengineering, Henan University of Engineering, Zhengzhou, 451191, China.
This study aims to explore the mechanism behind the influence of stress on gas adsorption by coal during deep mining and improve the accuracy of gas disaster prevention and control. To achieve this aim, thermodynamic analysis was conducted on the process of gas adsorption by loaded coal, and modified thermodynamic model proposed by previous scholars. It is found that stress plays an important role in gas adsorption by coal.
View Article and Find Full Text PDFEnviron Pollut
January 2025
Department of Mineral Processing Engineering, Taiyuan University of Technology, Taiyuan 030024, China.
To realize the comprehensive utilization of large amounts of high-ash coal slime and comprehensively understand the excellent performance of nutrient release and lead and cadmium adsorption of high-ash coal slime silicon composite materials, green and safe mild hydrothermal conditions (200 °C) were used to prepare the rich-rich coal slime. Zeolite/tobermorite composites (Z-TOBs) were used in this study. Batch adsorption tests and repeated extraction tests were used to determine whether silicon, potassium, and calcium nutrients of Z-TOBs have sustained release properties and are affected by pH.
View Article and Find Full Text PDFSensors (Basel)
January 2025
School of Communication and Information Engineering, Xi'an University of Science and Technology, Xi'an 710054, China.
Artificial intelligence (AI), particularly through advanced large language model (LLM) technologies, is reshaping coal mine safety assessment methods with its powerful cognitive capabilities. Given the dynamic, multi-source, and heterogeneous characteristics of data in typical mining scenarios, traditional manual assessment methods are limited in their information processing capacity and cost-effectiveness. This study addresses these challenges by proposing an embodied intelligent system for mine safety assessment based on multi-level large language models (LLMs) for multi-source sensor data.
View Article and Find Full Text PDFSensors (Basel)
January 2025
SHCCIG Yubei Coal Industry Co., Ltd., Xi'an 710900, China.
The coal mining industry in Northern Shaanxi is robust, with a prevalent use of the local dialect, known as "Shapu", characterized by a distinct Northern Shaanxi accent. This study addresses the practical need for speech recognition in this dialect. We propose an end-to-end speech recognition model for the North Shaanxi dialect, leveraging the Conformer architecture.
View Article and Find Full Text PDFJ Environ Sci (China)
July 2025
Geology Institute of China Chemical Geology and Mine Bureau, Beijing 100101, China; Technology Innovation Center for Ecological Restoration Engineering in Mining Area, Ministry of Natural Resources, Beijing 100083, China.
Contaminants in the water environment of different pyrite mines have varying characteristics due to different geological origins. Sulfur isotope (δS) is an effective tool to reveal the mechanism of water environment contamination, but no investigations have yet analyzed the characteristics and environmental significance of the δS in the water environment of different pyrite mines. This study involved a field investigation of four typical pyrite mines in China (representing volcanic, skarn, sedimentary-metamorphic, and coal-deposited types) and the analysis of the hydrochemistry of aqueous samples and the δS of both pyrite and dissolved sulfates.
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