Pingjian Yang

Enhancing energy efficiency is a critical pathway for China’s achievement of carbon peaking and carbon neutrality goals while maintaining economic growth. The deviation between actual factor prices and shadow prices is a major source of low total factor energy efficiency. Therefore, evaluating the allocative efficiency of production factors, including energy, should be addressed. In consideration of China’s energy endowment, energy transition, and unbalanced sustainability of various energy sources, this study adopts a stochastic frontier model with a generalized cost function to measure the allocative inefficiency of coal, oil, natural gas, and electricity and heat in China. The results indicate the following: (1) From 2005 to 2022, both technical efficiency and energy factor allocative efficiency remained below 1 at the provincial level, while technical efficiency declined gradually and allocative efficiency exhibited an upward spiral trend. (2) Labor, coal, oil, natural gas, and electricity and heat are found to be overutilized relative to capital; moreover, except for capital, all other factors are excessively employed relative to electricity and heat. (3) Setting capital factors as standardization factors, the shadow prices of coal, oil, natural gas, and electricity and heat are all higher than the actual prices. This indicates that China can reasonably allocate factors through full market competition and government regulation, thereby improving energy utilization efficiency.

Frequent bird strikes during peak migration periods pose a significant risk to aviation safety. Existing prevention methods rely on static historical patterns and lack the ability to adapt to real-time changes. Short-term meteorological fluctuations are crucial in shaping bird migration behavior, influencing both its timing and intensity. Climate change increases the variability of these factors, making predictions more difficult. Simple models may describe migration patterns under stable conditions but struggle to capture the complexity introduced by climate-driven fluctuations. To address this, we propose a model that integrates convolutional neural networks (CNNs), long short-term memory (LSTM) networks, and an attention mechanism, achieving prediction accuracy consistently above 0.9. CNN extracts features, LSTM captures temporal dependencies, and attention assigns weights to important features. Unlike traditional statistical methods, this model transitions from traditional heuristic approaches to data-driven quantitative forecasting, offering insights into migration intensity while accounting for meteorological fluctuations influenced by climate change. Ablation experiments showed that removing the attention mechanism, CNN module, and both components reduced the average prediction accuracy by 3.93%, 8.47%, and 10.96%, respectively. These results demonstrate that bird migration predominantly occurs at night and is significantly influenced by radiation levels and wind conditions. This research incorporates meteorological variability into predictive modeling to develop data-driven strategies for enhancing aviation safety. Additionally, it addresses environmental challenges and promotes sustainable practices by optimizing flight schedules to reduce bird strikes, improve fuel efficiency, and minimize emissions. This approach also contributes to ecological conservation and supports sustainability goals.

China has made significant progress in environmental protection. As the country advances towards modernizing its environmental governance, environmental sociology plays an increasingly crucial role. This study employs a bibliometric analysis of 3867 publications from the Web of Science Core Collection (1972–2023) and CNKI (1990–2023) to reveal the disparities between Chinese and international environmental sociology research, with a particular focus on assessing the contributions of environmental sociology to environmental governance in China. The findings reveal several key insights. The results show a steady increase in global research output, with the United States (42.79%) and the United Kingdom (11.15%) leading in publication volume. While international research has expanded interdisciplinary collaboration, Chinese studies remain highly concentrated. The findings also reveal a growing tension between internationalization and localization in Chinese environmental sociology. Since 2017, publications in international journals have surged, while domestic publications have declined, reflecting scholars’ prioritization of global recognition over local policy engagement. However, language barriers and limited interdisciplinary integration—with over 80% of scholars rooted in philosophy and sociology—restrict the discipline’s ability to address complex governance challenges. Institutional influence remains imbalanced. Renmin University, Hohai University, and the Ocean University of China contribute 42.72% of domestic publications, yet no Chinese institution ranks among the global top 10, and citation impact lags behind leading Western institutions. This contrasts with international research, which tends to focus on global environmental issues, whereas Chinese research emphasizes localized case studies. Our analysis identifies a notable gap in Chinese research’s understanding and study of environmental governance experiences. It is recommended to strengthen the role of environmental sociology throughout the governance process from public opinion collection to policy formulation, policy implementation, dynamic feedback, and post-implementation evaluation.