Analysis of spatial differences in global regional human development index under planetary pressure and decomposition study of driving factors.

To urge nations worldwide to implement robust measures for enhancing human development and mitigating the pressures exerted on the planet by human activities in pursuit of sustainable development, this study encompasses 154 countries globally, using the seven major regions as focal points. Leveraging the Planetary Pressure Adjusted Human Development Index (PHDI) proposed by the United Nations Development Programme on December 15, 2020, as a metric for human development levels, this paper aims to standardize and internationally compare human development data from 1990 to 2021. Subsequently, employing the Theil index, the study assesses the global human development status across the seven regions to analyze spatial disparities in PHDI. Lastly, a comprehensive Generalized Diese Index Method (GDIM) is constructed to accurately reflect absolute and latent factors, dissecting the driving forces impacting global PHDI. The study explores critical pathways for high-quality human development within the harmonious coexistence between humanity and nature. It validates the robustness of GDIM results through a stepwise regression. Research findings indicate varying levels of PHDI development across regions, with a distinct spatial hierarchy evolving: higher human development levels in Europe and Eastern Europe, favorable levels in North and South America, similar levels in Oceania and Asia, and significant improvement potential in Africa. As globalization progresses, overall differences in PHDI gradually decrease; however, disparities persist between and within regions. Economic, technological, and per capita welfare effects consistently positively drive PHDI. In contrast, environmental pressure effects, social effects, per capita value-added effects, and output carbon intensity effects consistently exert hostile driving forces. Population size effects on PHDI show a fluctuating trend. Moreover, in terms of cumulative contribution values, the top three contributors to driving forces are economic, technological, and per capita welfare effects.

Analysis of China's carbon emission driving factors based on the perspective of eight major economic regions.

Low-carbon transition has gradually become the focus of research on environmental issues. This paper takes China's eight major economic regions as the entry point. First, carbon emissions are measured according to United Nations' baseline methodologies. Second, the stochastic nonparametric data envelope analysis (StoNED) model is used to measure energy efficiency to improve the accuracy of the measurement. Finally, considering the temporal and spatial nonstationarity of carbon emission data, this paper constructs geographically and temporally weighted regression-stochastic impacts by regression on population, affluence, and technology (GTWR-STIRPAT) model, which can accurately analyze the impact of each driving factor of carbon emissions. This paper also explores efficient emission reduction paths in conjunction with the forcing mechanism. According to the study, China's carbon emissions show a decreasing trend from coastal areas to inland areas. In addition, there are significant problems with carbon emissions in China: some regions focus on improving energy efficiency but neglect increasing energy consumption; some regions focus on industrial development but neglect long-term emission reductions. Among the driving factors, energy efficiency, foreign trade, environmental regulations, and industrial structure have the effects of spatiotemporal heterogeneity, spatial heterogeneity, and time lag on carbon emissions, respectively. Graphical abstract.

Research on the relationship between China's greenhouse gas emissions and industrial structure and economic growth from the perspective of energy consumption.

A comprehensive understanding of the relationships between greenhouse gas (GHG) emissions and industrial structure and economic growth holds great significance for China to realize the development of a green economy. This paper calculates GHG emissions based on China's energy consumption, divides the industrial structure in detail, and uses the extended Stochastic Impacts by Regression on Population, Affluence, and Technology model that is realized by PLS method and Tapio decoupling model to study the relationship of GHG emissions to industrial structure and economic growth. The results show that (1) China's total GHG emissions showed a year-on-year growth trend from 2000 to 2017. For CO2, CH4, and N2O, only N2O emission showed a significant downward trend, while CO2 and CH4 emissions showed a slow growth trend. (2) The proportions of added value of industry and construction are positively correlated with GHG emissions, while those of farming, forestry, animal husbandry, and fishery; wholesale and retail trade; transport; and accommodation and catering are negatively correlated with GHG emissions. (3) China's GHG emissions and overall economic growth are in a decoupling state, but in the energy field, N2O emission reduction control has the best effect. Additionally, the overall economic growth of China's industrial sector and GHG emissions have experienced the process of decoupling-link-negative decoupling-link-decoupling. Graphical abstract.

Crisis resource management training in anaesthesia / 中华医学教育探索杂志

Anesthesia safety plays an important role in the medical safety of the perioperative.At present the medical institutions in many countries apply crew resource management model for training and assessment in anesthesiology,surgery and emergency.It emphasizes the training of nontechnical skills,called crisis resource management(CRM).This article analyzes the causes of human error incidents and preventive measures and introduces CRM principles in medical principles and anesthesia correlation and applications.CRM helps to foresee the crisis of environment and deal with the crisis source to ensure the safety of patients.