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Updated: Jul 15, 2025
11:53
The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
Published on: October 14, 2017
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Artificial intelligence, industrial structure optimization, and CO2 emissions
Mingfang Dong1, Guo Wang2, Xianfeng Han3
1School of Management, Xi 'an University of Architecture and Technology, Xi'an, 710399, China. dongmingfang@xauat.edu.cn.
Environmental Science and Pollution Research International
|September 26, 2023
Summary
Artificial intelligence (AI) significantly reduces carbon dioxide (CO2) emissions in China. Understanding AI's role is key to achieving carbon neutrality goals through targeted regional strategies.
Area of Science:
- Environmental Science
- Economics
- Computer Science
Background:
- China's ambitious goals for carbon peak and carbon neutrality necessitate innovative solutions.
- Artificial intelligence (AI) presents a potential pathway for significant carbon reduction.
- A comprehensive understanding of AI's impact on CO2 emissions is crucial for effective policy implementation.
Purpose of the Study:
- To systematically investigate the impacts and mechanisms of AI on CO2 emissions in China.
- To analyze regional variations in AI's effectiveness in reducing carbon emissions.
- To provide empirical evidence for leveraging AI to achieve China's dual-carbon targets.
Main Methods:
- Econometric models were constructed using dynamic panel data.
- Data spanned 30 provinces in mainland China from 2006 to 2019.
- Mediation effect tests were employed to explore underlying mechanisms.
Main Results:
- AI was found to significantly reduce CO2 emissions across China.
- In western regions, AI's impact is mediated by industrial structure advancement (quantity and quality) and industrial ecology.
- In eastern and central regions, AI's impact is mediated by industrial structure advancement (quality), rationalization, and industrial ecology.
Conclusions:
- AI is a potent tool for mitigating CO2 emissions in China.
- Regional strategies should consider specific industrial structure factors for maximizing AI's carbon reduction potential.
- This research supports the synergistic development of AI and China's dual-carbon goals.
Keywords:
Advanced industrial structureArtificial intelligenceCarbon dioxide emissionEcological industrial structureIntermediary effectRational industrial structureMore Related Videos
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