RESOURCES AND ENVIRONMENT IN THE YANGTZE BASIN >> 2025, Vol. 34 >> Issue (05): 964-.doi: 10.11870/cjlyzyyhj202505004

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Impact of Numerical Intelligence Integration Development on Collaborative Governance of Pollution and Carbon Reduction in the Yangtze River Delta Region

ZHANG Jie1,2,LIU Ya-qi1#br#   


  1. (1.Shandong University of Science and Technology,Qingdao 266590,China;2.School of Economics and Management, Northeast Forestry University, Harbin 150040,China)
  • Online:2025-05-20 Published:2025-05-22

Abstract: Eco-environmental protection in China will enter the key stage of coordinated management of pollution and carbon reduction. The in-depth integration and development of digital and intelligent technologies (DIT) will provide new major opportunities and technical support for coordinated management of pollution and carbon reduction (PCR). In this paper, an index system was constructed for the development level of DIT integration and the level of coordinated governance for PCR. The entropy weight method was used for hierarchical assignment and calculation. The panel data of 27 cities in Yangtze River Delta region of China from 2011 to 2022 were adopted as the research object. A spatial-temporal analysis of the development level of DIT integration and the level of coordinated governance for PCR was conducted. The bidirectional fixed effects model and the mediation effect model were employed to study the influence and mechanism of the development of DIT integration on the coordinated governance of PCR. The results showed that: (1) the level of numerical intelligence integration development (NID) and the level of collaborative governance for PCR in the Yangtze River Delta (YRD) region significantly increased from 2011 to 2022, accompanied by the occurrence of spatial diffusion phenomena; (2) NID significantly contributed to the improvement of collaborative governance for PCR in the YRD region; (3) The integration of DIT development could promote the coordinated management of PCR in the YRD region by improving the technological innovation capability and optimizing the energy production structure.

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