The data presented in this article are related to the research article entitled “Multivariate analysis of trace elements leaching from coal and host rock” [1]. During coal mining, coal and host rock undergo water-rock interaction, leading to release of trace elements to surface and ground water. The batch experiments were designed and implemented to investigate the leaching behavior and mechanisms during the process of water-rock interaction. In different experimental sets, various types of leaching water, open/closed environments, temperature, and initial pH values were used to evaluate their impact on leaching of trace elements. These data could be used to analyze leaching mechanisms of trace elements from coal and host rock, and understand, predict, control trace elements’ contamination to surrounding waters.
Swimming is one of the most popular amusement activities. In order to keep the swimmers from microbiological, the water need to be constantly disinfected. In this study, several indoor and outdoor swimming pools water and drinking water were investigated, it has found that swimming pool water has much higher HAA concentration and toxicity than the drinking water. DCAA and TCAA are the most abundant species in the indoor and outdoor swimming pool water. In the outdoor swimming pool water, TCAA concentration was higher than DCAA, while [DCAA]/[TCAA] was higher in the indoor swimming pool water.
Large number of data has been accumulated in the long-term survey and statistics on forest resource, hidden in which is some useful knowledge, so acquiring the ability to utilize the knowledge has become increasingly important.
Coal mine water usually has high content of trace elements, leading to contamination of surrounding water bodies. Water treatment technologies are used to remove organic and inorganic matters from coal mine water. To evaluate the treating efficiency of conventional and advanced treatment on coal mine drainage, samples of coal mine, carbonate, surface water, and treated water from the treatment processes were collected and analysed. It turns out that the conventional treatment processes can hardly remove both major ions and trace elements in coal mine water. Reverse osmosis technology can reject major ions effectively, but weak in trace elements removal. The analysis of surface water quality suggested contamination by coal mine water in the coal-mine district. To control the contamination and reuse the coal mine water effectively and safe, it is necessary to evaluate more carefully the efficiency of water treatment and potential environment impact of coal mine water on the surrounding surface and ground waters.
Water inrush is a major threat to the working safety for coal mines in the Northern China coal district. The inrush pattern, threaten level, and also the geochemical characteristics varies according to the different of water sources. Therefore, identifying the water source correctly is an important task to predict and control the water inrush accidents. In this chapter, the algorithms and attempts to identify the water inrush sources, especially in the Northern China coal mine district, are reviewed. The geochemical and machine learning algorithms are two main methods to identify the water inrush sources. Four main steps need to apply, namely data processing, feature selection, model training, and evaluation, in the process of machine learning (ML) modelling. According to a calculation instance, most of the major ions, and some trace elements, such as Ti, Sr, and Zn, were identified to be important in light of geochemical analysis and machine learning modelling. The ML algorithms, such as random forest (RF), support vector machine (SVM), Logistica regression (LR) perform well in the source identification of coal mine water inrush.
Abstract. Two types of gel were developed, by taking fly ash and foaming cement as aggregate, which is usually used as filling material at the region where top-coal caves above coal entry in the Jinggezhuang coal mine, and adding high molecular polymer and bio-gel as additive. Sweating rates of the two types of gel under various matching ratio and temperature were tested. And then sweating ratio and water retention ratio of the two gels were calculated, based on which, the optimized matching ratios, were determined. Viscosity indexes of the two-type gel under different ratios were tested. The optimized filling ratios of the two types of gel were determined according to the two indexes, water retention rate and the viscosity. The filling experiments were implemented and evaluated in site, the Jinggezhuang coal mine. The results show that the fly ash gel has a good achievement on preventing spontaneous combustion at the Region where Top-Coal Caves above entries. It is promising, economically and environmental friendly, and valuable in popularization in coal mines.
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