Energy Ecological Footprint of China : Trend of Spatial Differences and Convergence.

Autor: YU Nan, SUN Renjin, SHI Hongling, YANG Su
Předmět:
Zdroj: Environmental Science & Technology (10036504); 2024, Vol. 47 Issue 3, p37-47, 11p
Abstrakt: This paper describes the measurement of the energy ecological footprint of the country and the regions during the period of 1997-2021 by using the net primary productivity model from the perspective of embodied carbon. With the kernel density estimation model being applied to the analysis of dynamic distribution characteristics, which depicts the evolution law of spatial absolute difference, the spatial absolute β convergence and spatial conditional β convergence models were constructed to further explore the spatial convergence of energy ecological footprint. As a result of the study it was showed that the energy ecological footprint China appeared to be a steady ascending trend, and its spatial distribution could be characterized as "higher in coastal regions and lower in inland regions". There was a trend regarding the overall distribution of China's energy ecological footprint, i.e., "the transition from unimodal to multi-modal and the left shift of the major peak of wave", and except for the tendency toward "unimodal" of the energy ecological footprint in the mid-reach of the Yellow River and the mid-reach of the Yangtze River, the energy ecological footprint in other regions showed the characteristics of "the transition from unimodal to bimodal", "the decline of major wave peak height" and "right trailing", it can be seen that the differences among regions showed an expansion tendency. The phenomenon of regional polarization has been intensified since 2003, which among others, the northern and southern coastal regions were the severest, on the contrary, the northeast, southwest and northwest regions were the weakest. For China as a whole and each of the regions, the energy ecological footprint showed a tendency towards spatial conditional convergence and spatial absolute β convergence, and the spatial conditional convergence rate is faster than the spatial absolute convergence rate. The convergence rate is fastest in northeast China region, and slowest in the mid-reach of the Yangtze River. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index