| Title |
A spatial analysis of an effective path for low-carbon development of energy-intensive industries |
| ID_Doc |
32440 |
| Authors |
Xu, B |
| Title |
A spatial analysis of an effective path for low-carbon development of energy-intensive industries |
| Year |
2023 |
| Published |
|
| DOI |
10.1016/j.spc.2023.03.002 |
| Abstract |
Reducing the carbon intensity of the energy-intensive heavy industry is the key to achieving low-carbon develop-ment. The existing literature often ignore the important role of spatial effects, when investigating the heavy indus-try. The innovation of this paper is to incorporate important spatial geographic information into the analysis framework, and use the geographically weighted regression model to investigate the carbon intensity of the heavy industry in China. The findings display that: (1) environmental decentralization generates a greater impact in the eastern region, on account of the more investment in energy conservation and environmental protection. (2) The impact of urbanization on the carbon intensity in the central region is the most obvious, because this region invests more scientific and technological talents. (3) Green technology innovation contributes more to reducing carbon intensity in the central region, due to the faster growth of renewable energy patented technologies. (4) The industrial structure has little impact in the central and western regions, because their tertiary industry is underdeveloped. (5) The carbon intensity of the western region receives the least impact from foreign direct invest-ment, since the area attracts the least foreign investment. Therefore, the local governments ought to make targeted policies according to local specific conditions, in order to realize the low-carbon development of the heavy industry. ?? 2023 Institution of Chemical Engineers. Published by Elsevier Ltd. All rights reserved. |
| Author Keywords |
Carbon intensity; The heavy industry; Geographically weighted regression model |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000984015700001 |
| WoS Category |
Green & Sustainable Science & Technology; Environmental Studies |
| Research Area |
Science & Technology - Other Topics; Environmental Sciences & Ecology |
| PDF |
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