AI-Powered Solutions for Urban Carbon Emission Challenges: Evidence from China

This study investigates the impact of artificial intelligenc on urban carbon emission efficienc, addressing the limited empirical evidence on the environmental effects of AI in the existing literature. Using panel data from Chinese cities covering the period 2011–2023, we employ a fixed-effects model to examine the relationship between AI development and carbon emission efficiency. Our analysis reveals that AI significantly improves urban carbon emission efficiency. Mechanism analyses further show that AI promotes CE by stimulating green technological innovation, upgrading industrial structure, and accelerating the development of the digital economy. In addition, the effect is stronger in non-old industrial cities, resource-based cities, and regions with stronger intellectual property protection and higher human capital. These findings provide new insights into the environmental implications of AI and offer important policy implications for promoting low-carbon transition and sustainable urban development.

本研究探讨人工智能（artificial intelligence）对城市碳排放效率的影响，弥补了现有文献中关于人工智能环境效应的实证研究较为匮乏的不足。研究采用2011-2023年中国城市面板数据，运用固定效应模型考察人工智能发展与碳排放效率之间的关联关系。实证分析结果显示，人工智能显著提升了城市碳排放效率。机制检验进一步表明，人工智能可通过激励绿色技术创新、推动产业结构升级以及加快数字经济发展，促进碳排放效率提升。此外，该提升效应在非老工业城市、资源型城市以及知识产权保护力度更强、人力资本水平更高的地区更为显著。本研究为人工智能的环境效应研究提供了全新视角，同时为推进低碳转型与城市可持续发展提供了重要的政策启示。