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Exploring the impact of urban vitality on carbon emission mechanisms using multi-source data

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Abstract

Urbanization and low-carbon development are critical issues of global concern. As urbanization has reached its middle to late stages, cities face the dual pressures of development and environmental challenges. This study constructed a theoretical framework for urban vitality in six dimensions: social, economic, cultural, environmental, spatial, and perceptual. Using methods such as spatial syntax, entropy-weighted TOPSIS, deep learning models, and geographic detectors, we analysed the distribution characteristics of urban vitality in Yantai’s central area, explored how vitality-contributing factors influenced carbon emissions, and elucidated the association of urban vitality with carbon emissions. The results indicated that (1) urban vitality exhibited a multicentred distribution pattern of “low in the hinterland—high along the coast”; (2) significant differences existed in the impacts of various vitality dimensions on urban carbon emissions; (3) different urban vitality factors have varying levels of explanatory power regarding the spatial distribution of carbon emissions, with maximum building height exhibiting the strongest explanatory power, while the selection degree shows the weakest; and (4) the interactions between these factors typically demonstrate a two-factor enhancement, with the interaction between maximum building height and integration having the most significant effect on urban carbon emissions. This study innovatively integrates three-dimensional spatial and cultural perception perspectives, addressing the biases found in previous research that represented urban vitality from a singular viewpoint. It provides a more comprehensive framework and methodology for evaluating urban vitality, and the findings can offer recommendations for building low-carbon, high-vitality, and sustainable urban environments.

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Data availability

All the data sources are described in the text. However, if processed data and code are required, the corresponding author can provide the data based on reasonable request.

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Acknowledgements

We would like to extend our heartfelt gratitude to Dr. Jiang Hongqiang from Ludong University for his invaluable technical guidance. Additionally, we express our deepest appreciation to the anonymous reviewers and editors for their meticulous work and thoughtful suggestions, which have greatly enhanced this paper.

Funding

This research was funded by the Youth Innovation Team Project in Universities of Shandong Province, grant number (2022RW026); the National Natural Science Foundation of China, grant number (42377207); the national natural science foundation of China, grant number (42207553); the Shandong Taishan Scholar Young Expert Program (tsqn202306240); the Shandong Provincial Humanities and Social Sciences Project, grant number (2022-YYGL-31); the general project of Undergraduate Teaching Reform in Shandong Province, grant number (Z2021177); the Key project of Research and Development Program in Shandong Province, grant number (2022RKY07006); the open foundation of State Key Laboratory of Lake Science and Environment , grant number (2022SKL005); the open foundation of State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, CAS, grant number (SKLLQG2024); and Innovation Project for graduate students of Ludong University (Grant Number: IPGS2025-060).

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Authors and Affiliations

  1. School of Resources and Environmental Engineering, Ludong University, Yantai, 264025, China

    Yige Zhang, Xiaohui Wang, Longsheng Wang, Yanfeng Zhang & Junxi Song

  2. College of Architecture and Urban Planning, Tongji University, Shanghai, 200000, China

    Yu Ye

  3. School of Hydraulic and Civil Engineering, Ludong University, Yantai, 264025, China

    Guodong Liu

  4. Nanjing Institute of Geography and Lake Research, Limnology of Chinese Academy of Sciences, Nanjing, 210044, China

    Shimou Yao

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  1. Yige Zhang
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  2. Xiaohui Wang
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  3. Yu Ye
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  4. Longsheng Wang
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  5. Yanfeng Zhang
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  6. Junxi Song
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Contributions

Yige Zhang: Conceptualization, methodology, software, writing—original draft preparation and formal analysis. Xiaohui Wang: Conceptualization, validation, writing—original draft preparation and funding acquisition. Yu Ye: Software, validation and methodology. Longsheng Wang: Investigation, funding acquisition, writing—review and editing. Yanfeng Zhang: Investigation and data curation. Junxi Song: Investigation. Guodong Liu: Visualization. Shimou Yao: Conceptualization and supervision.

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Xiaohui Wang or Longsheng Wang.

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Zhang, Y., Wang, X., Ye, Y. et al. Exploring the impact of urban vitality on carbon emission mechanisms using multi-source data.
Sci Rep (2026). https://doi.org/10.1038/s41598-025-29624-9

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  • DOI: https://doi.org/10.1038/s41598-025-29624-9

Keywords

  • Urban vitality
  • Urban carbon emissions
  • Human perception
  • Entropy-weighted TOPSIS
  • Optimal parameter geographic detector

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