A spatio-temporal analysis of low carbon development in China’s 30 provinces: A perspective on the maximum flux principle

Abstract

This study constructed a multidimensional indicator system to evaluate low carbon development of the whole country and 30 provinces in China from 2003 to 2013, based on the maximum flux principle, which reflects the dynamic evolutionary process of low carbon development. Then k-means cluster analysis was used to classify 30 provinces into three grades (highest, medium and lowest) according to their average low carbon development level. Finally, Moran’s I was used to investigate the spatial correlation of low carbon development in China. The simulation results show that the national low carbon development level increased with fluctuations from 2008 as the nation paid high attention to low carbon development, and the provincial low carbon development is unbalanced, which is closely related to the socioeconomic conditions, resources endowment and geographical locations. For each province, the development level of different evaluative dimension grows unequally. For each grade, the provinces of highest grade have good performance in energy and environmental dimensions and the provinces of medium grade have good performance in society or the economic dimension, but the provinces of lowest grade have a lower development level in all dimensions. There is significant positive spatial dependence and cluster characteristics in low carbon development in China. In general, high-level provinces are distributed in southern China while low-level provinces are mainly located in northern China. The high-level provinces should perform their demonstrating functions and promote low carbon development in their surrounding areas.