节能
技术变革
还原(数学)
面板数据
温室气体
能源消耗
中国
高效能源利用
溢出效应
环境科学
样品(材料)
驱动因素
自然资源经济学
环境经济学
生态学
计量经济学
工程类
地理
经济
微观经济学
数学
化学
生物
考古
色谱法
宏观经济学
电气工程
几何学
作者
Wangni Zhou,Yuqin Zhang,Xuekun Li
标识
DOI:10.1016/j.jclepro.2024.141142
摘要
Artificial Intelligence (AI), as the core driving force of industrial and technological innovation, has brought technological advances that profoundly affect energy conservation and carbon emission reduction in China. This study constructs a dynamic spatial Durbin model to empirically analyze AI's mechanism path using Chinese inter-provincial panel data as a sample. The findings show the following: (1) Spatial and temporal variations exist in AI development levels and energy conservation and carbon emission reduction. (2) AI has a significant negative impact on energy consumption efficiency and a significant negative spatial spillover effect on carbon emission efficiency, and the effects of AI development level on energy conservation and carbon emission reduction are mainly dominated short term. (3) Green technological progress on both the input and output sides has not played a determinant role in the effects of AI on energy conservation and carbon emission reduction. (4) Given the moderating effect of the degree of factor market development, the improvement of green technological advances can play a positive role in the impact of AI on energy and carbon reduction. These findings suggest the need to provide policy support for energy conservation and carbon emission reduction by improving the spatial and regional linkage mechanism to narrow spatial and temporal differences in development levels, formulate AI policies addressing regional heterogeneity, promote the full transformation of AI's short-term effects into long-term effects, emphasize the negative role of green technological advances, and accelerate the transformation of green technological achievements, among other measures.
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