[Coupling Mechanisms of Eco-environmental Quality and Human Activities in China and Their Influencing Factors].

In the context of sustainable development, it is important to thoroughly investigate the coupling mechanism between China's eco-environmental quality and human activities, as well as identify the influencing factors, in order to provide scientific references for achieving sustainable development goals in China. This study applied trend analysis, coupling coordination degree, LMDI, and optimal parameter geographic detector models to explore and evaluate the coupling mechanism between China's eco-environmental quality and human activities. The findings of the study were as follows:① During the research period, there was a growth trend in China's coupling coordination degree, human activities, and eco-environmental quality. Human activities and coupling coordination degree exhibited a spatial differentiation pattern with the Hu Line as the boundary, showing an "east high, west low" distribution. The eco-environmental quality demonstrated a "south high, north low" differentiation pattern. ② The overall trend of China's coupling coordination type transformation was shifting from lower-level to higher-level coordination types. ③ Based on the geographic detector and LMDI models, the dominant factors influencing the coupling coordination degree in most provinces east of the Hu Line were social and economic factors, as well as the comprehensive coordination index. In contrast, the dominant factors in most provinces west of the Hu Line were natural environmental factors and coupling degree. ④ The evaluation of the impact of changes in human activities on eco-environmental quality revealed that the regions east of the Hu Line were mainly characterized by favorable development and effective protection, whereas the regions west of the line were mainly characterized by destructive development and ineffective protection. It is suggested that the regions on both sides of the Hu Line should prioritize development based on local prerequisites influencing the coupling coordination degree and the relative relationship between human activities and eco-environmental quality. It is crucial to actively adjust development strategies and pursue a sustainable development path towards the high-level coordination between eco-environmental quality and human activities.

The dynamic role of technological innovations and energy structure in China's industrial coal consumption growth: a joint production theoretical decomposition analysis.

China's energy-intensive industries utilize the leading proportion of coal to meet the demand for its industrial outputs, while on the other hand, these industries also assure the provision of livelihood to millions of people, and capping the share of coal consumption for these industries can adversely affect the industrial and economic growth of China. Thus, to achieve the Pareto improvement between environmental pollution and industrial output growth, it is essential to comprehend the patterns of coal consumption in these industries. Hence, the present research intended to analyze the potential drivers of coal consumption by applying a joint LMDI, DEA, and the production theoretical decomposition approach. Findings indices that, first, industrial output growth was the crucial driver to simulate the industrial coal consumption, while the potential coal intensity and coal technology changes exhibited the reverse effect. Second, the coal inputs and industrial output efficiency, along with the improvements in technological gaps, were found to be the imperative factors in decelerating coal consumption. Third, the energy industrial group was discovered to have more potentials of coal conversation as compared to the non-energy industrial group. Moreover, results also indicated that coal pure technical efficiency is accelerating coal growth, which revealed that coal can be saved by enhancing coal allocative efficiency. These findings laid the empirical ground to design a feasible coal conservation policy for achieving the imperative goals of environmental protection without compromising industrial output growth.

Spatio-temporal evolution characteristics of carbon emissions from road transportation in the mainland of China from 2006 to 2021.

The leaping forward of the economy has promoted the rapid growth of road traffic demand, resulting in the carbon emissions of road traffic increasing significantly. It is well known that a one-size-fits-all emission reduction policy is not feasible. Therefore, conducting an investigation on the carbon emissions of all provincial-level regions within a country can assist the government in formulating carbon emission policies at a macro level tailored to different regions. In this study, the whole provincial-level administrative regions in the mainland of China were selected to quantify the carbon emissions of road traffic, and the carbon emissions from 2006 to 2021 were obtained by employing the top-down model. What's more, spatiotemporal characteristics of road transportation carbon emissions in those regions were explored based on Moran's I spatial autocorrelation method. In addition, the LMDI model was constructed based on five driving factors, namely energy intensity, energy consumption intensity, industrial scale, economic development, and population size, and the decomposition analysis of driving factors is carried out. The results show that carbon emissions from road traffic in all provincial regions showed an overall rising trend in the research period, with an average annual growth rate of 11.83 %. The distribution of road transportation carbon emissions exhibited an east-high, west-low distribution, with significantly higher emissions in the eastern and coastal regions compared to inland areas, additionally, China's seven geographical regions showed an initial rapid increase in carbon emissions followed by a stable growth trend. Secondly, five types of spatial clustering were identified of carbon emissions within provincial regions. Thirdly, the impacts of energy intensity and industrial scale were detrimental to road transportation carbon emissions, whereas economic development, energy consumption intensity, and population size had contrasting effects. Implications according to the above conclusions were put forward, aiming to provide guidance for the sustainable development of road transportation and expediting the achievement of the "carbon peaking and carbon neutrality" objective.