School of Management, Xi 'an University of Architecture and Technology, Xi'an, 710399, China.
School of Management and Economics, Kunming University of Science and Technology, Kunming, Yunnan, 650093, China.
Environ Sci Pollut Res Int. 2023 Oct;30(50):108757-108773. doi: 10.1007/s11356-023-29859-x. Epub 2023 Sep 26.
The carbon-reducing effects of artificial intelligence (AI) will be a critical means of achieving carbon peak and carbon neutrality in China. However, in order to efficiently harness the power of AI, the relationship between AI and carbon reduction needs to be fully understood. In this study, we systematically investigated the impacts and mechanisms of action of AI on CO emissions by constructing econometric models using dynamic panel data from 30 provinces in mainland China from 2006 to 2019. The empirical results show that AI significantly reduces CO emissions. Further mediation effect tests found that in the western region, there are mediation effects of the quantity and quality of industrial structure advancedization and industrial structure ecology, while the mediation effect of industrial structure rationalization is not significant. In the eastern and central regions, the mediating effect of the quantity of industrial structure advanced is not significant, while the mediating effect of the quality of industrial structure advanced, industrial structure rationalization, and industrial structure ecology all exist. Our work provides evidence to support that AI reduces CO2 emissions in various regions of China. This can help regions formulate appropriate policies to promote the synergistic development of AI and the "dual-carbon" goal.
人工智能（AI）的减排效应将是中国实现碳达峰、碳中和的关键手段。然而，为了高效利用人工智能的力量，需要充分了解人工智能与碳减排之间的关系。本研究通过构建中国 2006 年至 2019 年 30 个省份的动态面板数据的计量经济学模型，系统地研究了人工智能对 CO 排放的影响及其作用机制。实证结果表明，人工智能显著降低了 CO 排放。进一步的中介效应检验发现，在西部地区，产业结构高级化的数量和质量以及产业结构生态存在中介效应，而产业结构合理化的中介效应不显著。在东部和中部地区，产业结构高级化数量的中介效应不显著，而产业结构高级化、产业结构合理化和产业结构生态的中介效应均存在。我们的工作为人工智能在中国各地区降低 CO2 排放提供了证据支持。这有助于各地区制定适当的政策，促进人工智能与“双碳”目标的协同发展。
