Implementing the “dual-carbon” objective has profoundly affected China’s businesses, prompting a continuous process of transformation and innovation. Green, low-carbon transformation, upgrading, and sustainable development have emerged as the means to achieve high-quality company growth, with firms playing a crucial role in achieving the “dual-carbon” target. By prioritizing firms’ green, low-carbon, and sustainable growth, not only can their economic efficiency be improved, but it also serves as a vital measure to advance high-quality development. To achieve this objective, it is crucial to analyze the elements that impact the energy-saving effectiveness of businesses to develop optimization tactics that can enhance their competitiveness. This study combines the three-stage Data Envelopment Analysis (DEA) and the Tobit model to assess the energy-saving efficiency of green and low-carbon firms from 2018 to 2022. The analysis focuses on selected samples from various areas and industries. The study investigates the relationship between energy-saving effectiveness and different regional and industrial parameters, considering the distinct attributes of each firm and the key elements that influence its energy-saving performance. The findings indicate that green, low-carbon firms typically demonstrate suboptimal energy-saving efficiency but have considerable room for improvement. Upon considering environmental concerns, it becomes clear that the primary limitation on energy-saving performance is the lower efficiency of the enterprise scale. The energy-saving efficiency of green, low-carbon firms varies significantly across different regions and industries. On average, northern firms in the energy-saving and carbon reduction industry, as well as the resource recycling industry, have higher energy-saving efficiency compared to southern enterprises. In contrast, the environmental protection industry in southern firms demonstrates a better average energy-saving efficiency compared to their northern counterparts. Employee quality, policy support, and automation are key factors that greatly enhance the energy-saving efficiency of firms in both regions. Enterprise size has a beneficial impact on the energy-saving efficiency of southern firms but a negative impact on northern enterprises. Moreover, the industry and financial structures exert a detrimental influence on enhancing the energy-saving efficiency of green and low-carbon firms. Thus, in order to improve the energy-saving effectiveness of businesses, it is essential to utilize the elements that have a positive influence on energy-saving performance and reduce the impact of those that have negative impacts. This strategy will enhance the energy-saving efficiency of businesses and promote the development of an environmentally friendly and low-carbon society.

Atmospheric pressure fluctuation is one of the most important factors affecting the climate environment and gas emission in the fire area. To obtain the influence rule of the surface atmospheric pressure change on the gas sampling and abnormal emission in the mine closed goaf, the No. 1 coal mine in Dananhu was taken as the research object. Using Fourier transform and Fisher harmonic analysis and other statistical methods, the influence of the periodic variation of atmospheric pressure on the gas leakage and outflow in the closed goaf was studied. The results showed that there were three atmospheric pressure periods of 15.2 d, 1 d and 182.2 d, and the probability was greater than 95%. The time period with the highest number of atmospheric pressure peaks was 7:00–8:00, which accounted for 20.2% of total occurrence number in a day. And the time periods with the highest number of atmospheric pressure trough were 2:00, 15:00 and 16:00, accounting for 27.4%. The peak-to-trough transition time was mainly concentrated around 6 h, and the diurnal variation curve of atmospheric pressure was mainly bimodal. The atmospheric pressure change rate was mostly concentrated in 10–50 Pa/h. It was determined that the distance that the gas sampling pipe was pre-laid into the inner side of the closed wall should be greater than 44.4 m, and the CO concentration and atmospheric pressure in the closed goaf were both periodic and negative with atmospheric pressure. The research results have important guiding significance for the monitoring, early warning and environmental protection of the goaf.

University emergency management ability is an important part of university safety management. To evaluate university emergency management ability scientifically, objectively, and accurately, this study constructs three first-level indexes, namely, pre-prevention ability, in-process control ability, and post-recovery ability, and 15 s-level indexes, including the establishment of emergency management institutions; the construction of emergency plans; the allocation of emergency personnel, equipment, and materials; and the training and exercise of emergency plans. On the basis of the backpropagation (BP) neural network method and MATLAB platform, an evaluation model of university emergency management ability is constructed. The neural network evaluation model is trained with sample data, and a university in Beijing is adopted as an example to verify the good prediction effect of the model. The results show that applying the evaluation model based on the BP neural network to the emergency management ability of colleges and universities is feasible. The model provides a new method to evaluate the emergency management ability of colleges and universities.

Based on the “2–4” model of accident causation, a comprehensive index system of the safety culture construction level in colleges and universities is set up. This system consists of 4 primary indicators and 28 secondary indicators. Taking a university as an example, applying the analytic hierarchy process and fuzzy comprehensive evaluation method, this study establishes a comprehensive evaluation model to evaluate the construction level of the university’s safety culture. The results show that the construction level of the university’s safety culture is consistent with the actual situation. This study provides useful insights and feasible paths for promoting the safety and stability of colleges and universities and building a higher level of safety on campus.

Due to the non-renewability of coal resources and the effect of excessive resource loss on the economic development of enterprises forming a constraint, breakthroughs in high energy consumption to achieve energy saving and emission reduction in coal mines represent an important way to promote the development of coal enterprises. This paper takes the energy-saving work of the Wuyang coal mine, which is very representative of China’s Shanxi Province, as an example, and uses hierarchical analysis to establish an assessment system for energy conservation and emission reduction in coal mines. We adopted on-site research, expert scoring, and project guidance to divide the factors affecting energy conservation and emission reduction in the Wuyang coal mine into 24 categories, and we then used fuzzy mathematical calculations to assess potential, which is of better practicability. The study shows that the grade of energy saving and emission reduction in the Wuyang coal mine is of a medium level, and the potential of energy saving and emission reduction is large. The main influencing factors are improving the recovery rate of refined coal, renovating pressurized filters, eliminating high-energy-consuming equipment, optimizing the parking process, replacing the flotation machine, and ensuring the intelligent management of power metering. According to the relevant factors derived from the energy-saving and emission reduction work at the Wuyang coal mine for implementing the relevant measures, we provide a reference for the work of energy saving and emission reduction in mines in order to promote the sustainable development of the coal mining industry.

Safe and resilient operation of liquefied petroleum gas (LPG) storage and distribution stations is important to the sustainability of fuel infrastructure, yet boiling liquid expanding vapor explosion (BLEVE) prevention requires time-dependent barrier analysis and a clear separation between prevention priorities and post-rupture exposure. This study develops a dynamic–spatial screening framework that integrates evidence-graded basic events, a priority-AND dynamic fault tree, a continuous-time Markov chain (CTMC), memory-efficient Monte Carlo trajectory simulation, modeled-area prevention prioritization, and tank-origin relative-exposure screening. A one-million-trajectory accelerated numerical baseline produced 112,693 BLEVE-conditioned trajectories. Weld cracking and fire-pump failure had the highest dynamic criticality because they act in later barrier-degradation stages, whereas high-wind spread had the greatest conditional involvement. Tank structure had the highest modeled-area prevention priority. Receiver rankings depended on the assumed layout: P5 ranked first under the baseline schematic coordinates, whereas P2 ranked first under the illustrative metric-coordinate scenario across the tested distance-attenuation kernels. Convergence, acceleration-factor, evidence-grade, weight, recovery, alternative-path, static-importance, coordinate, and kernel sensitivities were evaluated. Prevention-priority scores and normalized exposure indices are reported separately and are not interpreted as calibrated accident frequency, physical dose, expected loss, or quantitative risk. By supporting targeted inspection, maintenance, monitoring, and emergency-resource allocation, the framework can contribute to safer, more resilient, and more sustainable operation of LPG infrastructure.