Evidence map›Paper›PMID 39799109›Full record

ArticleScientific data2025

City-level emergy metabolism accounts for China's 281 cities from 2000 to 2020.

Miaohan Tang, Gengyuan Liu, Jingke Hong, Weier Liu, Chao Zhong, Dan Wang, Yuli Shan

Abstract read
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

7 authors.

Miaohan TangSchool of Public Administration, Zhejiang University of Finance &Economics, Hangzhou, China.ORCID http://orcid.org/0000-0003-0091-2627
Gengyuan LiuState Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing, China.ORCID http://orcid.org/0000-0002-3488-9536
Jingke HongSchool of Management Science and Real Estate, Chongqing University, Chongqing, China. hongjingke@cqu.edu.cn.ORCID http://orcid.org/0000-0002-5038-4167
Weier LiuXianghu Laboratory, Hangzhou, Zhejiang, China.
Chao ZhongInstitute of European Studies, Chinese Academy of Social Sciences, Beijing, China. v_zhongchao@163.com.
Dan WangBiological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.
Yuli ShanSchool of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK. y.shan@bham.ac.uk.ORCID http://orcid.org/0000-0002-5215-8657

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cities exhibit diverse urban metabolism patterns in terms of the natural environment, industrial composition, energy, and material consumption. A chronicled city-level quantification of emergy metabolic flows over time can significantly enhance the understanding of the temporal dynamics and urban metabolism patterns, which provides critical insights for the transitions to sustainability. However, there exists no city-level urban emergy metabolism dataset in China that can support detailed spatial-temporal analysis. In this study, we present a city-level urban emergy metabolism dataset of China's 281 cities between 2000 and 2020. This dataset meticulously describes the production and import of 41 resource types that sustain metabolic activities in 281 Chinese cities over a span of 21 years. This database, for the first time, provides insights into the historical metabolic changes of China's cities by detailing emergy flows including production, consumption, and import of resources. Furthermore, these emergy flow inventories serve as valuable resources for studying urban metabolic characteristics, evaluating policy impacts, and formulating sustainable development strategies for China's cities.

Identifiers

PMID39799109
PMCPMC11724914

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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.