Evidence map›Paper›PMID 38104204›Full record

ArticleScientific data2023

A dataset of low-carbon energy transition index for Chinese cities 2003-2019.

Yifan Shen, Xunpeng Shi, Zhibo Zhao, Jinghang Xu, Yongping Sun, Zhenliang Liao, Yingzhu Li, Yuli Shan

Abstract readDataset
In one paragraph

Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

8 authors.

Yifan ShenSchool of Economics and Management, Tongji University, Shanghai, 200092, China.
Xunpeng Shi *Australia-China Relations Institute, University of Technology Sydney, Sydney, 2007, Australia. xunpeng.shi@uts.edu.au.ORCID 0000-0001-9653-7395
Zhibo ZhaoSchool of Finance, Qilu University of Technology (Shandong Academy of Sciences), 58 Sangyuan Road, Jinan, 250100, China.
Jinghang XuSchool of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, B15 2TT, UK.
Yongping SunInstitute of State Governance, Huazhong University of Science and Technology, Wuhan, 430074, China.
Zhenliang LiaoCollege of Environmental Science and Engineering, Tongji University, Shanghai, 200092, China.
Yingzhu Li *School of Public Affairs, Zhejiang University, Hangzhou, 310058, China. li_yingzhu@zju.edu.cn.ORCID 0000-0003-3542-6274
Yuli Shan *School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, B15 2TT, UK. y.shan@bham.ac.uk.ORCID 0000-0002-5215-8657

Funding

National Natural Science Foundation of China (National Science Foundation of China) 72004200National Natural Science Foundation of China (National Science Foundation of China) 72074069National Natural Science Foundation of China (National Science Foundation of China) 72104184National Natural Science Foundation of China (National Science Foundation of China) 72174056
6 · The paper itself

Abstract

Cities are at the heart of climate change mitigation as they account for over 70% of global carbon emissions. However, cities vary in their energy systems and socioeconomic capacities to transition to renewable energy. To address this heterogeneity, this study proposes an Energy Transition Index (ETI) specifically designed for cities, and applies it to track the progress of energy transition in Chinese cities. The city-level ETI framework is based on the national ETI developed by the World Economic Forum (WEF) and comprises two sub-indexes: the Energy System Performance sub-index, which evaluates the current status of cities' energy systems in terms of energy transition, and the Transition Readiness sub-index, which assesses their socioeconomic capacity for future energy transition. The initial version of the dataset includes ETI and its sub-indexes for 282 Chinese cities from 2003 to 2019, with annual updates planned. The spatiotemporal data provided by the dataset facilitates research into the energy transition roadmap for different cities, which can help China achieve its energy transition goals.

Identifiers

PMID38104204
PMCPMC10725502

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.