Dynamic Factor Analysis of Trends in Temporal–Spatial Patterns of China’s Coal Consumption

Abstract

This paper analyzes coal consumption in the 31 provinces and regions of China from 1995 to 2012. Using spatial analysis in Arc geographical information systems (ArcGIS) and the concept of the center of gravity in physics, we explore the regional differences in temporal-spatial coal consumption and the factors influencing them. The results show that China's coal consumption increased yearly, especially after 2003. It exhibits a marked spatial clustering phenomenon; consumption in the south and east exceeded that in the north and west respectively. Moreover, the center of gravity of consumption gradually moved toward the southwest, indicating reducing gaps in coal consumption between the north-south and the east-west regions. Both the level of economic development and coal consumption are positively related with regional coal production. Promoting urbanization and increasing the proportion of the tertiary industry can effectively reduce coal consumption and help readjust coal consumption patterns to sustainable levels.

Introduction to the Special Issue on the Sustainable Asia Conference 2015

“…DEA is especially important in the field of energy and environmental economics since it handles desirable outputs as well as undesirable outputs such as wastewater and land [4], mortality rate [14], and industrial sulfur dioxide [16]. SEM or similar stepwise approaches are other popular approaches to evaluate diverse survey-related issues as they clarify the role of intermediation or stepwise relationship resulting from the complexity among variables [3,5,11]. As the sustainability issues should examine the spatial and time dynamic effects, most DEA approaches are also based on the stepwise approach [4,14].…”

“…As coal consumption is strongly related to the distance of coal production sites, Sun et al (2015) [3] used the center of gravity models. This is advantageous as the model can demonstrate development trajectories visually and quantitatively with the support of geographical information systems (ArcGIS) to study the spatial distribution of energy consumption and carbon emissions, and the spatial distribution of energy consumption intensity, respectively, for China's provinces and regions.…”

“…In the second stage of determining the governance factors related to coal consumption, the urbanization level is found to be negatively related to coal consumption. Thus, when the proportion of the urban population is increased by 1%, coal consumption will reduce by 698,080 tons of standard coal [3]. Urbanization should be promoted with detailed fine-tuning, as it also triggers problems of social disparity and degradation of human health.…”

Spatio-Temporal Pattern Change of Winter Wheat Production and Its Implications in the North China Plain

“…The barycenter model was widely used to present spatial trend changes of geospatial factors in certain region and period [3,7,[28][29][30]. The barycenter model is expressed by the equations as follows:…”

Spatio‐temporal evolution of regional inequality and contribution decomposition of economic growth: A case study of Jiangsu Province, China

“…The barycentre model can provide visual development trajectories from the perspective of temporal and spatial coupling, which has been the main method in empirical studies for several decades (Qiao, Yang, & Zhang, ; Sun, ; Vincent, ). Many scholars have imported the barycentre model into the social, economic and resource fields, and their research achievements have had a profound impact on economic development (Fan, Kanbur, & Zhang, ; Grether & Mathys, ; Klein, ).…”