Impacts of Energy Structure on Carbon Emissions in China, 1997-2019.

To mitigate climate change, reducing carbon dioxide (CO2) emissions is of paramount importance. China, the largest global CO2 emitter, proposes to peak carbon emissions by 2030 and become carbon neutral by 2060; transforming the energy structure represents one of the primary means of addressing carbon emissions; thus, it is essential to investigate the impacts of alternate energy sources throughout the country. Based on energy consumption and carbon emissions data from 30 provincial-level administrative regions in China (excluding Tibet, Hong Kong, Taiwan, and Macau, due to the lack of data), the study here investigated the shares of coal, petroleum, natural gas, and non-fossil energy sources (i.e., hydropower, nuclear power, wind power, solar power, and biomass power), as they relate to total, per capita, and per unit GDP CO2 emissions via spatial regression. The results showed that: (1) The epicenters of coal and carbon emissions have shifted from the east to the central and western regions; (2) There is a significant correlation between energy structure and carbon emissions: coal has a positive effect, petroleum's effects are positive at first, and negative subsequently; while both natural gas and non-fossil energy sources have a negative impact; (3) Provincial-level carbon emissions are affected by energy structure, carbon emissions in neighboring regions, and other factors.

Assessment of Ecosystem Health and Its Key Determinants in the Middle Reaches of the Yangtze River Urban Agglomeration, China.

Urban agglomerations have gradually formed in different Chinese cities, exerting great pressure on the ecological environment. Ecosystem health is an important index for the evaluation of the sustainable development of cities, but it has rarely been used for urban agglomerations. In this study, the ecosystem health in the middle reaches of the Yangtze River Urban Agglomeration was assessed using the ecosystem vigor, organization, resilience, and services framework at the county scale. A GeoDetector was used to determine the effects of seven factors on ecosystem health. The results show that: (1) The spatial distribution of ecosystem health differs significantly. The ecosystem health in the centers of Wuhan Metropolis, Changsha-Zhuzhou-Xiangtan City Group, and Poyang Lake City Group is significantly lower than in surrounding areas. (2) Temporally, well-level research units improve gradually; research units with relatively weak levels remain relatively stable. (3) The land use degree is the main factor affecting ecosystem health, with interactions between the different factors. The effects of these factors on ecosystem health are enhanced or nonlinear; (4) The effect of the proportion of construction land on ecosystem health increases over time. The layout used in urban land use planning significantly affects ecosystem health.

The Nexus between Urbanization and Traffic Accessibility in the Middle Reaches of the Yangtze River Urban Agglomerations, China.

China has entered the stage where urban agglomerations underpin and spearhead the county's urbanization. Urban agglomerations in China have become economic growth poles, and the constantly improving transport networks in these agglomerations bring about opportunities for redistributing labor forces and promoting regional economic development, trade, and social progress for all. This is the foundation and fuel for urban development. However, lack of knowledge of the spatial features of, and the interrelationship between, regional urbanization and traffic accessibility constrains effective urban planning and decision-making. To fill this gap, this study attempted to evaluate the spatiotemporal distribution characteristics of urbanization levels and traffic accessibility in 1995, 2005, and 2015 in the Middle Reaches of the Yangtze River Urban Agglomerations (MRYRUA), China. The spatial interaction, spatial dependence effect, and spatial spillover effect between urbanization and traffic accessibility were tested by employing the bivariate spatial autocorrelation model and spatial regression models. The results showed that the urbanization level and traffic accessibility in the MRYRUA shot up over time and manifested similar spatial distribution characteristics. The global bivariate spatial autocorrelation coefficients were positive and significant during the period studied, and the main relationship types were the high urbanization and high traffic accessibility types and low urbanization and low traffic accessibility types. The spatial regression results showed that there was a significant positive association between urbanization and traffic accessibility, but with a significant scale effect. Urbanization is not only affected by the traffic accessibility of the individual grid unit but also by those in the adjacent or further grid units. The findings in this study provide important implications for urbanization development and transportation planning. The spatial dependence effect and spatial spillover effect between urbanization and traffic accessibility should be considered in future urban planning and transportation planning. The rational allocation of resources and inter-regional joint management can be an effective path toward regional sustainability.