Coal Mining Sustainable Development: Economics and Technological Outlook

Defining and Operationalizing Sustainability in the Context of Energy

The terms sustainable and sustainability are currently often used in scientific journals, including Energies. There are cases where these terms are defined or operationalized, but more often they are not. This is problematic, as there are reportedly hundreds of (different) definitions and operationalizations (in terms of standards or goals) of sustainability. This large number has its roots in history. Many current definitions and operationalizations of sustainability are social constructs. As these constructs vary, there can be variation in the characterization of specific ways to provide energy as sustainable or not sustainable. There are also definitions of sustainability that have emerged from the sciences. These definitions can also lead to differences in the characterization of specific ways to provide energy as sustainable or not sustainable. In view thereof, there is a case to define and/or operationalize sustainable and sustainability when these terms are used in the context of energy.

Coal Mine Safety Evaluation Based on Machine Learning: A BP Neural Network Model

As the core of artificial intelligence, machine learning has strong application advantages in multi-criteria intelligent evaluation and decision-making. The level of sustainable development is of great significance to the safety evaluation of coal mining enterprises. BP neural network is a classical algorithm model in machine learning. In this paper, the BP neural network is applied to the sustainable development level decision-making and safety evaluation of coal mining enterprises. Based on the analysis of the evaluation method for sustainable development of coal enterprises, the evaluation index system of sustainable development of coal enterprises is established, and a multi-layer forward neural network model based on error backpropagation algorithm is constructed. Based on the system theory of man, machine, environment, and management, and taking the four single elements and the whole system in a coal mine as the research object, this paper systematically analyzes and studies the evaluation and continuous improvement of coal mine intrinsic safety. The BP neural network evaluation model is used to analyze and study the intrinsic safety of coal mines, the shortcomings of the intrinsic safety construction of coal mines are found, and then improvement measures are put forward to effectively promote the safe production of coal mines and finally realize the intrinsic safety goal of the coal mine.

Reutilisation of Water Contaminated by Mining Waste for the Encapsulation of Potentially Toxic Elements

Mining activities are essential for a population’s development; however, they also produce negative effects such as the production of waste, an impact on flora and water pollution. On the other hand, construction is one of the sectors which is most demanding of raw materials, with one of the main such materials being water. For this reason, this research evaluates the feasibility of incorporating water contaminated by mining waste into ceramic materials for bricks. In this way, the use of water is reduced and, on the other hand, the contaminating elements of the mining water are encapsulated in the ceramic matrix. To achieve this, the clay used and the contaminated water were first analysed, then different families of samples were conformed with different percentages of contaminated water. These samples were tested to determine their physical and mechanical properties. At the same time, leachate tests were carried out to determine that the ceramic material created did not cause environmental problems. The test results showed that the physical and mechanical properties of the ceramics were not influenced by the addition of contaminated water. On the other hand, the leachate tests showed that encapsulation of most of the potentially toxic elements occurred. However, the use of contaminated water as mixing water for ceramics could only be performed up to 60%, as higher percentages would leach impermissible arsenic concentrations. Accordingly, a new way of reusing water contaminated by mining activities is developed in this study, taking advantage of resources, avoiding environmental pollution and creating economic and environmentally friendly end products.