4.7 Article

The impacts of multi-dimension urbanization on energy-environmental efficiency: Empirical evidence from Guangdong Province, China

Journal

JOURNAL OF CLEANER PRODUCTION
Volume 296, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2021.126513

Keywords

Urbanization; Energy-environmental efficiency; Super slack-based measure model; Panel data; STIRPAT model; Guangdong Province

Funding

  1. National Key Research Program of China [2016YFC0502800]
  2. National Natural Science Foundation of China [41801203, 71673027]
  3. Natural Science Foundation for Distinguished Young Scholars of Guangdong Province [2017A030306032]
  4. GDUPS

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This study evaluated the impacts of urbanization on energy-environmental efficiency (EEE) in 21 cities in Guangdong Province, finding that the proportion of urban resident population and urban compactness had significant positive impacts on EEE, while per capita GDP, contribution of the secondary industry, and proportion of land used for urban construction had significant negative impacts on EEE. Other factors such as population size and urban built-up area did not significantly affect EEE.
Understanding the complex ways in which urbanization influences energy-environmental efficiency (EEE) is essential for achieving energy savings and emission reductions. The multidimensional impacts of urbanization on EEE were evaluated using a hybrid approach that combined a super slack-based measure (SBM) model with a stochastic impacts by regression on population, affluence, and technology (STIRPAT) model. This approach was applied to evaluate the influences of multi-dimension urbanization on EEE, taking account of undesirable outputs from environmental pollution. The appropriateness of the approach was verified using panel data of 21 cities in Guangdong Province from 2005 to 2016. The results indicated there existed obvious regional differences in the indexes of urbanization and EEE in Guangdong Province during this period. Further analysis of the multidimensional impacts of urbanization revealed that two factors (i.e., proportion of the urban resident population and urban compactness) had significant positive impacts on EEE. Conversely, the impacts of the following three factors on EEE were significant negative: (1) per capita GDP, (2) contribution of the secondary industry, and (3) proportion of land used for urban construction. Some factors (e.g., population size and urban built-up area) did not have significant effects on EEE in Guangdong Province. These findings indicated that decision makers in Guangdong Province could consider the positive influences of the population urbanization and the negative influences of the land urbanization on EEE. (c) 2021 Elsevier Ltd. All rights reserved.

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