| Title |
Do Artificial Intelligence Applications Affect Carbon Emission Performance?-Evidence from Panel Data Analysis of Chinese Cities |
| ID_Doc |
32315 |
| Authors |
Chen, P; Gao, JW; Ji, Z; Liang, H; Peng, Y |
| Title |
Do Artificial Intelligence Applications Affect Carbon Emission Performance?-Evidence from Panel Data Analysis of Chinese Cities |
| Year |
2022 |
| Published |
Energies, 15, 15 |
| DOI |
10.3390/en15155730 |
| Abstract |
A growing number of countries worldwide have committed to achieving net zero emissions targets by around mid-century since the Paris Agreement. As the world's greatest carbon emitter and the largest developing economy, China has also set clear targets for carbon peaking by 2030 and carbon neutrality by 2060. Carbon-reduction AI applications promote the green economy. However, there is no comprehensive explanation of how AI affects carbon emissions. Based on panel data for 270 Chinese cities from 2011 to 2017, this study uses the Bartik method to quantify data on manufacturing firms and robots in China and demonstrates the effect of AI on carbon emissions. The results of the study indicate that (1) artificial intelligence has a significant inhibitory effect on carbon emission intensity; (2) the carbon emission reduction effect of AI is more significant in super- and megacities, large cities, and cities with better infrastructure and advanced technology, whereas it is not significant in small and medium cities, and cities with poor infrastructure and low technology level; (3) artificial intelligence reduces carbon emissions through optimizing industrial structure, enhancing information infrastructure, and improving green technology innovation. In order to achieve carbon peaking and carbon neutrality as quickly as possible during economic development, China should make greater efforts to apply AI in production and life, infrastructure construction, energy conservation, and emission reduction, particularly in developed cities. |
| Author Keywords |
artificial intelligence; carbon emission; heterogeneity; mechanism |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000839789200001 |
| WoS Category |
Energy & Fuels |
| Research Area |
Energy & Fuels |
| PDF |
https://www.mdpi.com/1996-1073/15/15/5730/pdf?version=1659950636
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