Evidence map›Paper›PMID 38933393›Full record

ArticleFundamental research2022

Toward carbon neutrality: Uncovering constraints on critical minerals in the Chinese power system.

Wendong Wei, Zewen Ge, Yong Geng, Mingkun Jiang, Zhujun Chen, Wei Wu

Abstract read
In one paragraph

Article in Fundamental research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

6 authors.

Wendong WeiSchool of International and Public Affairs, Shanghai Jiao Tong University, Shanghai 200030, China.
Zewen GeChina-UK Low Carbon College, Shanghai Jiao Tong University, Shanghai 201306, China.
Yong GengSchool of International and Public Affairs, Shanghai Jiao Tong University, Shanghai 200030, China.
Mingkun JiangKey Laboratory of Pressure Systems and Safety (MOE), School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai 200237, China.
Zhujun ChenBusiness School, University of Shanghai for Science and Technology, Shanghai 200093, China.
Wei WuShanghai Climate Center, Shanghai 200030, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

China has set up its ambitious carbon neutrality target, which mainly relies on significant energy-related carbon emissions reduction. As the largest important contributing sector, power sector must achieve energy transition, in which critical minerals will play an essential role. However, the potential supply and demand for these minerals are uncertain. This study aims to predict the cumulative demand for critical minerals in the power sector under different scenarios via dynamic material flow analysis (DMFA), including total demands, supplies and production capacities of different minerals. Then, these critical minerals are categorized into superior and scarce resources for further analysis so that more detailed results can be obtained. Results present that the total minerals supply will not meet the total minerals demand (74260 kt) in 2060. Serious resource shortages will occur for several key minerals, such as Cr, Cu, Mn, Ag, Te, Ga, and Co. In addition, the demand for renewable energy will be nearly fifty times higher than that of fossil fuels energy, implying more diversified demands for various minerals. Finally, several policy recommendations are proposed to help improve the overall resource efficiency, such as strategic reserves, material substitutions, and circular economy.

Indexed as

Carbon neutralityCircular economyCritical mineralMismatch gapPower system

Identifiers

PMID38933393
PMCPMC11197575

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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.