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ORIGINAL RESEARCH article

Front. Environ. Sci.
Sec. Environmental Economics and Management
Volume 13 - 2025 | doi: 10.3389/fenvs.2025.1539223
This article is part of the Research Topic Urban Carbon Emissions and Anthropogenic Activities View all 12 articles

Carbon Reduction Effects of Government Digital Attention

Provisionally accepted
Rong Hu Rong Hu 1Song Kaiyi Song Kaiyi 2*
  • 1 Nanjing University of Aeronautics and Astronautics Jincheng College, Nanjing, Liaoning Province, China
  • 2 Nanjing Xiaozhuang University, Nanjing, China

The final, formatted version of the article will be published soon.

    In the digital economy era, increasing government's adoption and attention to digital technology is not only conducive to accelerating the improvement of governance capacity, but also an important measure to achieve green economic development. This paper uses text analysis to measure the government digital attention at the city level, and then uses panel data econometric models to estimate the impact of government digital attention on carbon emissions reduction. The findings reveal that government digital attention can significantly reduce carbon dioxide emissions by improving the government's low-carbon governance, strengthening the public's low-carbon attention, and encouraging the enterprises' low-carbon transformation. Further, government digital attention mainly reduces carbon dioxide from direct energy consumption, transportation and electricity product. The carbon reduction effect of government digital attention is also affected by degree of marketization, and the high degree of marketization helps to reinforce the effect. Moreover, there is spatial heterogeneity in the effect, it is more significant in the eastern region. Our conclusions are then of important implications for promoting China's carbon dioxide reduction and achieving high-quality sustainable development.

    Keywords: Government digital attention, Carbon reduction, Low-carbon governance, Public concern, enterprise low-carbon transformation

    Received: 04 Dec 2024; Accepted: 08 Jan 2025.

    Copyright: © 2025 Hu and Kaiyi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Song Kaiyi, Nanjing Xiaozhuang University, Nanjing, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.