Impacts of artificial intelligence on carbon emissions in China: in terms of artificial intelligence type and regional differences

被引:12
作者
Dong, Mingfang [1 ]
Wang, Guo [1 ]
Han, Xianfeng [2 ]
机构
[1] Xian Univ Architecture & Technol, Sch Management, Xian 710055, Peoples R China
[2] Kunming Univ Sci & Technol, Sch Management & Econ, Kunming 650093, Yunnan, Peoples R China
基金
美国国家科学基金会;
关键词
Urban smartification; Urban sustainable development; Carbon emissions; Heterogeneity of artificial intelligence types; Regional heterogeneity;
D O I
10.1016/j.scs.2024.105682
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The influence of artificial intelligence (AI) on carbon emissions has long been contentious, and accurately clarifying this impact is crucial for the realization of sustainable smart cities. This article investigates the impact of AI on carbon emissions, distinguishing between applied and innovative AI types. Analyzing data from 267 Chinese cities between 2008 and 2019, the study reveals that applied AI reduces carbon dioxide emissions by an average of 40,100 tons per unit increase. In contrast, innovative AI initially leads to emissions increases before ultimately decreasing, illustrating an inverted U-shaped relationship. Regional variations in AI's impact on emissions are influenced by each region's developmental focus and stage of AI deployment. Specifically, differences arise due to the continuous carbon reduction (-0.024) associated with applied AI and the initial emission increase (0.129) attributed to innovative AI. The study underscores the significance of tailored regional strategies in AI development for fostering sustainable smart cities. These findings contribute to the ongoing discourse on AI's environmental impact, offering insights to inform targeted approaches in green, sustainable urban planning.
引用
收藏
页数:13
相关论文
共 42 条
  • [31] Algorithmic urban planning for smart and sustainable development: Systematic review of the literature
    Son, Tim Heinrich
    Weedon, Zack
    Yigitcanlar, Tan
    Sanchez, Thomas
    Corchado, Juan M.
    Mehmood, Rashid
    [J]. SUSTAINABLE CITIES AND SOCIETY, 2023, 94
  • [32] Can smart city construction improve carbon productivity? -A quasi-natural experiment based on China's smart city pilot
    Song, Tian
    Dian, Jie
    Chen, Hongwen
    [J]. SUSTAINABLE CITIES AND SOCIETY, 2023, 92
  • [33] Wang Y., 2020, EC RES J, V10, P159, DOI DOI 10.1186/S12935-020-01230-X
  • [34] Wei X., 2020, Econ Perspect, V10, P92
  • [35] Inhibition of the cardiac fibroblast-enriched histone methyltransferase Dot1L prevents cardiac fibrosis and cardiac dysfunction
    Xu, Jie
    Wang, Jinghuan
    Long, Fen
    Zhong, Wen
    Su, Haibi
    Su, Zhenghua
    Liu, Xinhua
    [J]. CELL AND BIOSCIENCE, 2022, 12 (01)
  • [36] Is There a Conflict between Automation and Environment? Implications of Artificial Intelligence for Carbon Emissions in China
    Xu, Xianpu
    Song, Yuchen
    [J]. SUSTAINABILITY, 2023, 15 (16)
  • [37] Yu D., 2016, CHINA IND EC, V7, P57, DOI [10.19581/j.cnki.ciejournal.2016.07.005, DOI 10.19581/J.CNKI.CIEJOURNAL.2016.07.005]
  • [38] Towards low-carbon development: The role of industrial robots in decarbonization in Chinese cities
    Yu, Lingzheng
    Wang, Yao
    Wei, Xiahai
    Zeng, Chenyu
    [J]. JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2023, 330
  • [39] Zhang J. Y., 2021, Inquiry into. Economic Issues, V12, P160
  • [40] Zhao C. M., 2020, Journal of Beijing Normal University, V6, P113