Carbon Emission Performance of China's Power Industry
Regional Disparity and Spatial Analysis
Bibliographic Data
| ID | 19469126 |
|---|---|
| Authors | Xiping Wang (0009-0001-0115-7742, North China Electric Power University, corresponding author), Lei Du (0000-0002-8548-9997, Northwestern Polytechnic University) |
| Year | 2017 |
| Volume | 21 |
| Issue | 5 |
| Pages | 1323-1332 |
| Publication date | 2017-10-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Industrial Ecology (JOURNAL) |
| Journal identifiers | ISSN: 1088-1980 • E-ISSN: 1530-9290 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1111/jiec.12480 |
| OpenAlex | W2546877359 |
| Language | EN |
| Citations received | 1 |
| References cited | 43 |
This study employs an undesirable‐output–oriented data envelopment analysis model to measure the carbon emission performance of the power industry throughout China's 30 administrative regions during the period of 2003–2012. Also, it further studies the regional disparity and spatial correlation of the carbon emission performance of China's power industry. The main findings are as follows: (1) The carbon emission performance of China's power industry is at a relatively low level, but shows a rising trend. (2) The regional carbon emission performance of China's power industry is extremely unbalanced: The eastern area ranks first, with the highest performance of 0.851, followed by the central area, whereas the western area falls behind, with the lowest performance of 0.760. Provinces in the eastern area generally perform better than those in other areas. (3) According to spatial analysis, the global Moran's I values of carbon emission performance are significantly positive during the sample period, which indicates that the carbon emission performance is a positive spatial correlation and has an obvious clustering effect. The estimate of the local spatial autocorrelation index confirms the imbalance of spatial distribution of the power sector's carbon emission performance. Based on the above findings, several policy suggestions are presented in this article
Carbon fibers · China · Data envelopment analysis · Economic geography · Geography · Greenhouse gas · Spatial analysis · Spatial dependence · Spatial distribution · Statistics · Computer Science · Efficiency Analysis Using DEA · Energy, Environment, Economic Growth · Environmental Impact and Sustainability · Environmental Science · Mathematics
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| Citations per year | 1 |
|---|---|
| Citation span | 2025 - 2025 (1) |
| Highly cited | No |