Evidence map›Paper›PMID 41484152›Full record

ArticleScientific reports2026

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

Yige Zhang, Xiaohui Wang, Yu Ye, Longsheng Wang, Yanfeng Zhang, Junxi Song, Guodong Liu, Shimou Yao

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Yige ZhangSchool of Resources and Environmental Engineering, Ludong University, Yantai, 264025, China.
Xiaohui WangSchool of Resources and Environmental Engineering, Ludong University, Yantai, 264025, China. xiaohuiwang881124@163.com.
Yu YeCollege of Architecture and Urban Planning, Tongji University, Shanghai, 200000, China.
Longsheng WangSchool of Resources and Environmental Engineering, Ludong University, Yantai, 264025, China. 52wls@163.com.
Yanfeng ZhangSchool of Resources and Environmental Engineering, Ludong University, Yantai, 264025, China.
Junxi SongSchool of Resources and Environmental Engineering, Ludong University, Yantai, 264025, China.
Guodong LiuSchool of Hydraulic and Civil Engineering, Ludong University, Yantai, 264025, China.
Shimou YaoNanjing Institute of Geography and Lake Research, Limnology of Chinese Academy of Sciences, Nanjing, 210044, China.

Funding

General Project of Undergraduate Teaching Reform in Shandong Province Z2021177Innovation Project for graduate students of Ludong University IPGS2025-060Key Project of Research and Development Program in Shandong Province 2022RKY07006National Natural Science Foundation of China 42207553Open Foundation of State Key Laboratory of Lake Science and Environment 2022SKL005Shandong Taishan Scholar Young Expert Program tsqn202306240Youth Innovation Team Project for Talent Introduction and Cultivation in Universities of Shandong Province 2022RW026
6 · The paper itself

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.

Indexed as

Entropy-weighted TOPSISHuman perceptionOptimal parameter geographic detectorUrban carbon emissionsUrban vitality

Identifiers

PMID41484152
PMCPMC12769675

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.