Evidence map›Paper›PMID 41191194›Full record

ArticleCarbon balance and management2025

The impact analysis of energy industry structure optimization on urban low-carbon transition.

Qiao Fan, Xinyu Wu

Abstract read
In one paragraph

Article in Carbon balance and management, 2025. 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

2 authors.

Qiao Fan *School of Economics, Lanzhou University, No.222 Tianshui South Road, Chengguan District, Lanzhou, 730000, Gansu, China.ORCID http://orcid.org/0000-0003-3072-2293
Xinyu Wu *School of Economics, Lanzhou University, No.222 Tianshui South Road, Chengguan District, Lanzhou, 730000, Gansu, China. wuxinyu2024@lzu.edu.cn.ORCID http://orcid.org/0009-0009-7330-3700

Funding

Gansu Provincial Basic Research Program Soft Science Project 24JRZA033
6 · The paper itself

Abstract

Accelerating urban low-carbon transition is vital for high-quality economic growth and sustainable development. The energy industry, a key driver of socioeconomic progress, is the main source of carbon emissions and is crucial for decarbonization. Optimizing its structure is essential for urban low-carbon transformation. Based on the panel data of 284 prefecture-level cities in China from 2003 to 2022, this study decomposes the optimization of the energy industry structure into basic structure optimization and spatial structure optimization, uses green total factor productivity (GTFP) to measure the level of urban low-carbon transformation, and uses the super-efficiency SBM model to calculate it, deeply explores whether and how the optimization of the energy industry structure affects the low-carbon transformation of cities and analyzes the mechanism effect of the level of green technology innovation in it. The results show that both the optimization of the energy industry basic structure and the optimization of the energy industry spatial structure can promote the low-carbon transformation of the city, and the results are still valid after the endogenous test and robustness test. The level of urban green innovation will play a positive moderating effect on the optimization of the energy industry structure on its low-carbon transformation and development. The relationship between energy industry structure optimization and urban low-carbon transformation is obviously heterogeneous in different regions, not only in different geographical locations, but also in different levels of economic development.

Indexed as

Double-fixed effects modelGreen total factor productivityLow-carbon transformationOptimization of energy industry structure

Identifiers

PMID41191194
PMCPMC12587655

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.