Evidence map›Paper›PMID 39015205›Full record

ArticleResearch (Washington, D.C.)2024

Quantifying the Resilience of Coal Energy Supply in China Toward Carbon Neutrality.

Yongzheng Sun, Guanghui Wen, Haifeng Dai, Yu Feng, Sandro Azaele, Wei Lin, Fubao Zhou

Abstract read
In one paragraph

Article in Research (Washington, D.C.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Yongzheng SunSchool of Mathematics, China University of Mining and Technology, Xuzhou 221116, China.ORCID https://orcid.org/0000-0001-9504-5663
Guanghui WenSchool of Mathematics, Southeast University, Nanjing 210096, China.ORCID https://orcid.org/0000-0003-0070-8597
Haifeng DaiSchool of Mathematics, China University of Mining and Technology, Xuzhou 221116, China.ORCID https://orcid.org/0000-0001-9960-8128
Yu FengChina Coal Transportation and Distribution Association, Beijing 100160, China.ORCID https://orcid.org/0009-0007-1478-8192
Sandro AzaeleDepartment of Physics and Astronomy "G. Galileo", University of Padova, Via F. Marzolo 8, Padova 35131, Italy.ORCID https://orcid.org/0000-0002-5153-4833
Wei LinResearch Institute of Intelligent Complex Systems, School of Mathematical Sciences, LMNS, and SCMS, Fudan University, Shanghai 200433, China.ORCID https://orcid.org/0000-0002-1863-4306
Fubao ZhouSchool of Safety Engineering, China University of Mining and Technology, Xuzhou 221116, China.ORCID https://orcid.org/0000-0003-3855-2647

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Facing the challenge of achieving the goal of carbon neutrality, China is decoupling the currently close dependence of its economy on coal use. The energy supply and demand decarbonization has substantial influence on the resilience of the coal supply. However, a general understanding of the precise impact of energy decarbonization on the resilience of the coal energy supply is still lacking. Here, from the perspective of network science, we propose a theoretical framework to explore the resilience of the coal market of China. We show that the processes of increasing the connectivity and the competition between the coal enterprises, which are widely believed to improve the resilience of the coal market, can undermine the sustainability of the coal supply. Moreover, our results reveal that the policy of closing small-sized coal mines may not only reduce the safety accidents in the coal production but also improve the resilience of the coal market network. Using our model, we also suggest a few practical policies for minimizing the systemic risk of the coal energy supply.

Identifiers

PMID39015205
PMCPMC11249919

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Registered trials

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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.