Spatial and temporal pattern evolution and influencing factors of energy–environmental efficiency: A case study of Yangtze River urban agglomeration in China

Abstract

Improving energy–environmental efficiency is prerequisite for sustainable development. In order to explore ways to improve energy–environmental efficiency, this paper uses the undesired output slack-based model to measure the energy–environmental efficiency of the Yangtze River urban agglomeration based on the input and output index data from 2008 to 2017, and its spatial and temporal pattern evolution is analyzed by using kernel density estimation, Gini coefficient, and coefficient of variation. Moreover, the Tobit regression model is used to analyze the influencing factors of the energy–environmental efficiency of the Yangtze River urban agglomeration. The results indicate that the energy–environmental efficiency of each city is increased continuously, and the regional differences are gradually narrowed. The spatial pattern is changed from polar nucleus type to valley type, and finally the distribution characteristics of “overall high” are formed. Overall, the energy–environmental efficiency presents a spatial layout of “high in the east and low in the west.” The regression results show that the level of economic development and energy–environmental efficiency are “U-type” associated characteristics, and government regulation and population density have significant positive effects on it. Industrial structure and technological progress have negative effects on it, and the effect of opening degree is not significant.