ORIGINAL RESEARCH article
Front. Environ. Sci.
Sec. Environmental Economics and Management
Volume 13 - 2025 | doi: 10.3389/fenvs.2025.1659608
Spatiotemporal Variations of Carbon Emissions in Digital Economy: Evidence from China
Provisionally accepted- 1Jiangxi Normal University, Nanchang, China
- 2Johns Hopkins University, Baltimore, United States
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The last few decades witnessed the tremendous growth of Chinese digital economy. How to calculate and estimate the carbon footprints of this rising economic formation, naturally becomes an issue. Based on the provincial panel from China spanning 2016 to 2021, we conduct an in-depth analysis of the spatial characteristics of carbon emissions in China's digital economy and empirically investigates the driving forces of the spatial differentiation. We show that: (1) Carbon emissions of Chinese digital economy present rapid growth trends, with a distinctive "T-shaped" spatial pattern. Notably, high-emission regions have significantly expanded, leading to the dispersion of carbon footprints and dynamic divergence. (2) The driving factors of the spatial differentiation could be split into six dimensions, which have strong interactive effects and jointly shape the patterns of carbon emissions of Chinese digital economy. By constructing a new emission measurement framework, we get deeper insights into the sources of the digital footprints from a spatiotemporal point of view. These results could provide instructive suggestions on how to enhance the sustainability in digital industry and furthermore, to achieve the global carbon reduction targets.
Keywords: carbon emission, digital economy, spatiotemporal differentiation, Geographical detector, Regional disparity
Received: 08 Jul 2025; Accepted: 20 Oct 2025.
Copyright: © 2025 Xia, Ji, Ren and Jiang. 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: Kaiwen Ji, jikaiwen668@163.com
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