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Spatiotemporal Trajectory of China’s Provincial Energy Efficiency and Implications on the Route of Economic Transformation

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  • Chao Xu

    (State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
    Guangzhou Institute of Energy Consumption, Chinese Academy of Sciences, Guangzhou 510640, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Yunpeng Wang

    (State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China)

  • Lili Li

    (State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China)

  • Peng Wang

    (Guangzhou Institute of Energy Consumption, Chinese Academy of Sciences, Guangzhou 510640, China)

Abstract

A comparative analysis of the spatiotemporal trajectory of energy efficiency (STEE) among the provinces in China over the past 21 years was conducted based on a quadrant diagram of the GDP per capita and the energy consumption per capita. An energy macro-efficiency per capita indicator (EMEPCI) was established using the energy consumption data of 30 Chinese provinces from 1996 to 2016. The spatiotemporal trajectory clustering method (STCM) and the industrial structure upgrading index (ISUI) were used for an exploratory analysis of the driving force of the changes in the STEE. The results showed the following: (1) The growth rate and amplitude of energy efficiency differed by province. From a geospatial perspective, the energy efficiency of the eastern regions was higher than that of the western regions, and that of the southern regions was higher than that of the northern regions. The growth trends demonstrated a pattern in which the provinces with higher energy efficiency had higher growth rates, whereas the provinces with lower energy efficiency showed lower growth rates. (2) The majority of the Chinese provinces, particularly the southwest region and the regions near the middle stream of the Yangtze River, were still undergoing a development process. Thus, it is necessary to pay attention to the adjustment of the economic development model to avoid shifting towards quadrants I or II, where the energy consumption is higher. (3) A spatiotemporal trajectory clustering analysis grouped the different provinces into four categories. Besides the majority of the provinces, which remained in quadrant III, Beijing, Shanghai, and Tianjin have remained in the “dual-high” quadrant for long period of time and are shifting towards quadrant IV. The trajectory of the second group was characterized by movement almost directly from the “dual-low” quadrant (III) towards the target quadrant (IV). The common feature of the energy efficiency trajectory of the third group was that they remained in the high energy consumption and low GDP quadrant for a relatively long period, and immediate changes were required in their development models. (4) The provinces with a similar industrial structure transformation level were more likely to have similar spatiotemporal trajectories of energy efficiency. Particularly, provinces with a similar level of transformation from secondary industries to tertiary industries enjoyed a greater probability of transformation as well as similar spatiotemporal trajectories of energy efficiency.

Suggested Citation

  • Chao Xu & Yunpeng Wang & Lili Li & Peng Wang, 2018. "Spatiotemporal Trajectory of China’s Provincial Energy Efficiency and Implications on the Route of Economic Transformation," Sustainability, MDPI, vol. 10(12), pages 1-14, December.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:12:p:4582-:d:187783
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