Evidence map›Paper›PMID 38480765›Full record

ArticleScientific reports2024

Research on driving mechanism and prediction of electric power carbon emission in Gansu Province under dual-carbon target.

Fuwei Qiao, Qinzhe Yang, Wei Shi, Xuedi Yang, Guanwen Ouyang, Lulu Zhao

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Fuwei QiaoCollege of Economics, Northwest Normal University, Lanzhou, 730070, China. qfw279@nwnu.edu.cn.
Qinzhe YangCollege of Economics, Northwest Normal University, Lanzhou, 730070, China.
Wei ShiCollege of Geography and Environmental Sciences, Northwest Normal University, Lanzhou, 730070, China.
Xuedi YangCollege of Resources and Environment, Lanzhou University, Lanzhou, 730070, China.
Guanwen OuyangCollege of Economics, Northwest Normal University, Lanzhou, 730070, China.
Lulu ZhaoCollege of Economics, Northwest Normal University, Lanzhou, 730070, China.

Funding

Gansu Provincial Philosophy and social Science planning office 2023QN013Northwest Normal University NWNU-SKQN2021-22Science and Technology Department of Gansu Province 22JR5RA155
6 · The paper itself

Abstract

The electric power industry is a key industry for the country to achieve the double carbon target. Its low carbon development has a double effect on this industry and helps other industries to achieve the carbon peak target. This paper firstly uses the IPCC inventory method to calculate carbon emissions in the production phase of the power industry in Gansu Province from 2000 to 2019, followed by the ridge regression method and the STIRPAT model to analyse the quantitative impact of six major drivers on carbon emissions, and finally, the scenario analysis method is used to forecast carbon emissions in this phase. The results show that the carbon emissions of Gansu Province show a trend of rising and then falling, and reached a peak of 65.66 million tons in 2013. For every 1% increase in population effect, urbanisation level, affluence, clean energy generation share, technology level and industrial structure, carbon emissions will grow by 4.939%, 0.625%, 0.224%, - 0.259%, 0.063% and 0.022% respectively. Because of the clean energy advantage in Gansu Province, the low-carbon development scenario will continue to have low carbon emissions during the scenario cycle, which can be reduced to 53.454 million tons in 2030; the baseline scenario will achieve a carbon peak in 2025, with a peak of 62.627 million tons; the economic development scenario has not achieved carbon peak during the scenario cycle, and carbon emissions will increase to 73.223 million tons in 2030.

Indexed as

Carbon emissionsPower industryRidge regressionScenario prediction

Identifiers

PMID38480765
PMCPMC10937654

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