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Do Artificial Intelligence Applications Affect Carbon Emission Performance?—Evidence from Panel Data Analysis of Chinese Cities

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  • Ping Chen

    (Dong Fureng Economic and Social Development School, Wuhan University, Wuhan 430072, China)

  • Jiawei Gao

    (Dong Fureng Economic and Social Development School, Wuhan University, Wuhan 430072, China)

  • Zheng Ji

    (Dong Fureng Economic and Social Development School, Wuhan University, Wuhan 430072, China
    National School of Development and Policy, Southeast University, Nanjing 211189, China)

  • Han Liang

    (Dong Fureng Economic and Social Development School, Wuhan University, Wuhan 430072, China
    National School of Development and Policy, Southeast University, Nanjing 211189, China)

  • Yu Peng

    (Dong Fureng Economic and Social Development School, Wuhan University, Wuhan 430072, China)

Abstract

A growing number of countries worldwide have committed to achieving net zero emissions targets by around mid-century since the Paris Agreement. As the world’s greatest carbon emitter and the largest developing economy, China has also set clear targets for carbon peaking by 2030 and carbon neutrality by 2060. Carbon-reduction AI applications promote the green economy. However, there is no comprehensive explanation of how AI affects carbon emissions. Based on panel data for 270 Chinese cities from 2011 to 2017, this study uses the Bartik method to quantify data on manufacturing firms and robots in China and demonstrates the effect of AI on carbon emissions. The results of the study indicate that (1) artificial intelligence has a significant inhibitory effect on carbon emission intensity; (2) the carbon emission reduction effect of AI is more significant in super- and megacities, large cities, and cities with better infrastructure and advanced technology, whereas it is not significant in small and medium cities, and cities with poor infrastructure and low technology level; (3) artificial intelligence reduces carbon emissions through optimizing industrial structure, enhancing information infrastructure, and improving green technology innovation. In order to achieve carbon peaking and carbon neutrality as quickly as possible during economic development, China should make greater efforts to apply AI in production and life, infrastructure construction, energy conservation, and emission reduction, particularly in developed cities.

Suggested Citation

  • Ping Chen & Jiawei Gao & Zheng Ji & Han Liang & Yu Peng, 2022. "Do Artificial Intelligence Applications Affect Carbon Emission Performance?—Evidence from Panel Data Analysis of Chinese Cities," Energies, MDPI, vol. 15(15), pages 1-16, August.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:15:p:5730-:d:882223
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    2. Weibo Jin & Yuqi Zhang & Yao Xu & Yi Zhang & Yanggi Kim & Yi Yan, 2024. "Does Intelligent Manufacturing Contribute to the Enhancement of Carbon Emission Performance? Evidence from Total Factor Carbon Emission Performance," Sustainability, MDPI, vol. 16(19), pages 1-24, September.
    3. Ning Xu & He Zhang & Tixin Li & Xiao Ling & Qian Shen, 2022. "How Big Data Affect Urban Low-Carbon Transformation—A Quasi-Natural Experiment from China," IJERPH, MDPI, vol. 19(23), pages 1-16, December.
    4. Shan Feng & Shuguang Liu, 2023. "Does AI Application Matter in Promoting Carbon Productivity? Fresh Evidence from 30 Provinces in China," Sustainability, MDPI, vol. 15(23), pages 1-19, November.
    5. Qian Zhang & Qizhen Wang, 2023. "Digitalization, Electricity Consumption and Carbon Emissions—Evidence from Manufacturing Industries in China," IJERPH, MDPI, vol. 20(5), pages 1-21, February.
    6. Tale Mi & Tiao Li, 2024. "Industrial Intelligence and Carbon Emission Reduction: Evidence from China’s Manufacturing Industry," Sustainability, MDPI, vol. 16(15), pages 1-21, July.
    7. Jiahui Tang & Wan Wang & Wangwang Ding, 2024. "Research into the Path and Mechanism by Which Intelligent Manufacturing Promotes Carbon Emission Reductions," Energies, MDPI, vol. 17(16), pages 1-18, August.
    8. Chițu Florentina & Mecu Andra-Nicoleta & Marin Georgiana-Ionela, 2024. "Exploring the Climate Change-AI Nexus: A Bibliometric and Scientometric Study," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 18(1), pages 1658-1670.
    9. Lu Zhang & Renyan Mu & Nigatu Mengesha Fentaw & Yuanfang Zhan & Feng Zhang & Jixin Zhang, 2022. "Industrial Coagglomeration, Green Innovation, and Manufacturing Carbon Emissions: Coagglomeration’s Dynamic Evolution Perspective," IJERPH, MDPI, vol. 19(21), pages 1-19, October.
    10. Wang, Linhui & Chen, Qi & Dong, Zhiqing & Cheng, Lu, 2024. "The role of industrial intelligence in peaking carbon emissions in China," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
    11. Hao Lv & Beibei Shi & Nan Li & Rong Kang, 2022. "Intelligent Manufacturing and Carbon Emissions Reduction: Evidence from the Use of Industrial Robots in China," IJERPH, MDPI, vol. 19(23), pages 1-20, November.
    12. Yang Shen & Zhihong Yang, 2023. "Chasing Green: The Synergistic Effect of Industrial Intelligence on Pollution Control and Carbon Reduction and Its Mechanisms," Sustainability, MDPI, vol. 15(8), pages 1-22, April.
    13. Kunpeng Ai & Wenjie Zhang & Xiang-Wu Yan, 2024. "Digital Economy and Urban Low-Carbon Transition: Theoretical Model and New Mechanisms," Sustainability, MDPI, vol. 16(14), pages 1-22, July.

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