Abstract
As the world's largest developing nation, China faces significant challenges in balancing economic growth and environmental sustainability. While existing studies explored various strategies for reducing carbon emissions, the impact of artificial intelligence on marginal emission reduction costs across diverse regional contexts remains to be clarified furthermore. Using provincial panel data from 2014 to 2024, this study investigates how artificial intelligence adoption influences emission reduction costs in China's industrial sectors. Applying the generalized method of moments, it finds that the marginal cost of emissions reduction decreases by approximately 13.7%- 16.3% when the artificial intelligence investment one unit. But it varies significantly across regions. For example, artificial intelligence investment improves efficiency by 18.2% in the more technologically advanced eastern provinces. In contrast, central regions present a modest 4.7% cost reduction due to lower artificial intelligence integration. However, the cost of western provinces increase can by 6.3% because of high transitional costs, misaligned industrial structures, and inadequate digital infrastructure that limit artificial intelligence's effectiveness. Robustness checks confirm the validity of the results across alternative specifications, including variable substitution using artificial intelligence patent counts, sample restriction to the post-2018 rapid artificial intelligence expansion period, and exclusion of special municipalities, demonstrating consistent and statistically significant findings. Our findings underscore the need for region-specific policies to maximize artificial intelligence's role in sustainable environmental progress, offering key insights for policymakers seeking to integrate technological innovation with emission reduction efforts.
NETL
NSTL
Elsevier