Dezhi Zheng

China’s coal industry is reckoned as one of the topmost contributors to global carbon emissions, and as a result, poses severe challenges both to human health and climate change mitigation efforts. Achieving carbon neutrality requires thorough analyses of mechanisms driving the coal sector’s transition. This study employs a structural model to investigate the transmission pathways through/by which the “dual carbon” goals influence the coal industry, using a policy text quantification approach to assess specific carbon reduction measures. Findings reveal that the impact of the “dual carbon” target on the coal industry operates through multiple pathways. Carbon reduction policies significantly enhance technical advancements, social and economic factors, energy-saving measures, and alternative energy development, all of which indirectly affect coal supply. Notably, the pathway from coal demand to coal supply shows a high path coefficient of 1.121, far surpassing the path coefficient from factor input to coal supply, measured at 0.169. This highlights coal demand as the pivotal intermediary variable in determining the “dual carbon” target’s impact on the coal industry. While current technologies and alternative energy sources have limited immediate effects on coal supply, they hold significant potential as transformative factors in the future.

The study of coal consumption has become a focus of academic attention due to ecological and environmental concerns. This study proposed a method to evaluate sustainability for coal consumption by using a multiple-attribute decision-making (MADM) model. The data used are from the China Statistical Yearbook and the China Energy Statistical Yearbook over the years. The MADM model consists of attributes (standards), their importance weights, and alternatives. The comprehensive evaluation system for the sustainability of coal consumption, which was composed of four first-grade indicators including coal strength (CS), energy dependency (ED), social development level (SL), and population size (PS) and their corresponding 20 second-grade indicators, was included in the MADM model as attributes (standards). The importance weight of the attributes was determined by the entropy weight method (EWM) and the analytic hierarchy process (AHP), while the comprehensive evaluation of the sustainability of coal consumption in China over the years was considered as an alternative. The evaluation indices of four first-grade indicators were obtained through multiobjective optimization, and then through the weights and evaluation indices of the four first-grade indicators, multiobjective optimization was carried out for the overall objective of the comprehensive evaluation of the sustainability of coal consumption over the years, and the comprehensive evaluation indices of the sustainable development of coal consumption over the years were obtained. The results show that China’s coal consumption is sustainable, with the composite assessment index rising from 0.058 in 2011 to 0.837 in 2021, an increase of 13.4 times.

Currently, coal is still the main energy source for China’s economic development, and the environmental issues caused by coal consumption have aroused widespread concern. Predicting and analyzing coal consumption will help to formulate a higher level of energy consumption planning and economic development strategy. The main purpose of this study is to develop a new fractal time-series prediction (FTSP) model to predict coal consumption, providing reference for formulating effective energy consumption planning and economic development strategies. Hurst index is an important indicator of whether time-series data have long memory and fractal characteristics. This paper uses the rescaled range (R/S) method to calculate Hurst index of the coal consumption per-10000-Yuan-GDP (CC/GDP). The Hurst index is 0.8025, exceeding 0.5, indicating that the time-series data CC/GDP has a long memory and fractal characteristic. Based on this, this paper uses the FTSP model to predict China’s coal consumption (CC/GDP). The prediction results show that the FTSP model accurately predicted China’s coal consumption with a relative error rate (RER) of less than 5% and a mean absolute percentage error (MAPE) of 6.62%. The model predicts a decrease in China’s coal consumption from 0.25 tons of standard coal in 2021 to 0.11 tons of standard coal in 2030, a decrease of 44%. To sum up, the FTSP model provides a new and accurate way to predict coal consumption, and the results suggest that China’s coal consumption is sustainable and will decrease significantly in the coming years. This study has important implications for energy consumption planning and economic development strategies.

The environmental problems caused by building energy consumption (BEC) are becoming increasingly prominent. Reducing building energy consumption can not only effectively curb environmental pollution, but also continue to promote economic development. However, there are few reports on reducing building energy consumption to continuously promote economic development. Sustainable driving force (SDF) has been widely mentioned in past research as a common-sense concept, but few systematic studies have been carried out. The main research objectives of this article include two aspects: On the one hand, this study takes the lead in establishing an SDF model and conducting systematic research on SDF. On the other hand, based on the SDF model, an empirical study is conducted on the sustainable driving effect of reducing building energy consumption on economic development in China. The main conclusions are as follows: (1) Research on the SDF model: Based on common examples, the objective reality of SDF has been theoretically proven. Based on the relevant theories of econometrics, this article believes that the “Granger causality test” and the “distributed lag regression model” can be used as basic tools for quantitative research of SDF models. (2) Research on the application of SDF model: From the Granger causality test, it can be seen that the current BEC intensity is the Granger cause of China’s economic development in the first and eighth cycles of the future. According to the results of the distributed lag regression model, reducing BEC intensity has a sustainable driving effect on economic development. Specifically, in the lagged period 1~8, the sustainable driving effect (reverse effect) of BEC on economic development gradually increases at first (coefficient value from 3878.52 to 5163.87), and then gradually decreases (coefficient value from 5163.87 to 783.534). To sum up, the SDF model can provide a reference for the quantitative study of SDF; studying the sustainable driving effect of BEC on economic development can provide a macro reference for the government to formulate “energy conservation and emission reduction” measures.

This paper attempts to study the effect of China’s coal consumption on the upgrading of industrial structure based on the relevant data obtained from the China Statistical Yearbook (1992–2021). The results showed that (1) China’s coal consumption has a downward trend, but it is still more than 56.8%. Similarly, the consumption of nonpetrochemical energy is not high, but the increase with respect to time is large. (2) Percentage of China’s tertiary industry reached a maximum of 54.5% in 2020. However, there is a huge gap when compared to the global data. For example, the tertiary industries accounted for 77.4% in the US in 2017 and 71.3% in the UK in 2019. (3) In the short term, China’s coal consumption will continue to promote the upgrading of industrial structure; in the long run, it is not obvious that China’s coal consumption continues to drive the upgrading of industrial structure. (4) The intensity of the sustainable driving effect of China’s coal consumption on the upgrading of industrial structure will gradually weaken from 0.0647 to 0.00102.

At present, China’s intelligent coal mine construction is still in the primary development stage. The integrated development of a new generation of information and communication technology and the coal industry is accelerating, and this industry’s intelligent green transformation and upgrading is being promoted. With the continuous acceleration of China’s intelligent coal mine construction and the continuous improvement in the degree of coal mine intelligence, system compatibility, information acquisition, and intelligent research have raised awareness of new mining safety risks. Based on the analysis of the process of China’s intelligent construction, this paper describes the safety management and control risks and the technical challenges faced by China’s intelligent coal mine construction in terms of norms and standards, data acquisition, subsystem and terminal sensors, multisystem integration, safety risk management, and control ability. It is important to make full use of the collaborative advantages of intelligent scientific and technological coal mine resources. Technological innovation and intelligent equipment safety access verification need to be supported, so as to promote the intelligent and high-quality development of coal mines.

Coal is the most reliable energy resource in China and has been in existence for a long time. The development model of coal industry is of great significance to carbon emission and environmental protection. In order to evaluate the development mode of China’s coal industry, this paper presents the constructed evaluation index system of the development mode of the coal industry from two dimensions, demand pull and factor drive. And, coal consumption is the measurement index of demand pull and selecting resources, capital, technology, human resources, and the energy system form the measurement index of factor drive. By analyzing the evaluation index system of the coal industry development mode and optimal evaluation method, the minimum deviation comprehensive weighting evaluation model, based on the analytic hierarchy process (AHP), and entropy are constructed. The evaluation results show that the coal industry has continued the factor driven growth, driven by demand, in the past decades. Finally, the study analyzes the changes and challenges of the development of China’s coal industry from four aspects, development power, development mode, development effect, and development bottleneck, to provide support for revealing the internal mechanism of the development mode of China’s coal industry.