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Assessing the synergistic effects of artificial intelligence on pollutant and carbon emission mitigation in China

Author

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  • Zhong, Wenli
  • Liu, Yang
  • Dong, Kangyin
  • Ni, Guohua

Abstract

Artificial intelligence (AI) has become a key driver in the latest wave of scientific and technological advancement, and its rapid development, proliferation, and environmental impacts cannot be ignored. China and numerous emerging economies are confronted with the dual challenges of environmental degradation and climate change. Hence, it is imperative to assess whether the advancement of AI can contribute to a synergistic reduction in pollutant and CO2 emissions. This paper utilizes the system-generalized method of moments (SYS-GMM) to study the synergistic effect of artificial intelligence on mitigating pollutant and carbon emissions. The following three main conclusions are drawn: (1) AI plays a major role in synergistically decreasing pollutant and CO2 emissions; (2) AI indirectly helps lower pollutant and CO2 emissions by fostering technological advancements and enhancing industrial structures. Although it contributes to an increase in emissions by expanding production scale, its suppression effect dominates overall; (3) The impact of AI applications is particularly vital in cities with strict environmental controls, especially in the central and eastern regions. Finally, we suggest some policy measures to augment the influence of AI in reducing emissions and attaining sustainable development.

Suggested Citation

  • Zhong, Wenli & Liu, Yang & Dong, Kangyin & Ni, Guohua, 2024. "Assessing the synergistic effects of artificial intelligence on pollutant and carbon emission mitigation in China," Energy Economics, Elsevier, vol. 138(C).
    • Handle: RePEc:eee:eneeco:v:138:y:2024:i:c:s0140988324005371
    DOI: 10.1016/j.eneco.2024.107829
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    Keywords

    Artificial intelligence; Synergistic emissions of pollutants and CO2; Mediation effects; Sustainable development; SYS-GMM technique;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • L80 - Industrial Organization - - Industry Studies: Services - - - General
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth

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