Evidence map›Paper›PMID 35067877›Full record

ArticleEnvironmental science and pollution research international2022

Carbon emission intensity and biased technical change in China's different regions: a novel multidimensional decomposition approach.

Lili Ding, Kaixuan Zhang, Ying Yang

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In one paragraph

Article in Environmental science and pollution research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.7field-weighted citation impact, top 37% of its field
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

1 citing paper in PubMed, 8 citations in OpenAlex.

  1. 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

3 authors at 1 institution in 1 country.

Lili DingSchool of Economics, Ocean University of China, Qingdao, China.
Kaixuan ZhangSchool of Economics, Ocean University of China, Qingdao, China.
Ying YangSchool of Economics, Ocean University of China, Qingdao, China. yangyingouc@126.com.ORCID http://orcid.org/0000-0001-5198-7552
Ocean University of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The decomposition analysis has been employed to discover the driving factors of carbon emission intensity, but the current studies assume that production functions are under the condition of the neutral technical change. Grounded on biased technical change production theory, this paper proposes a novel multidimensional decomposition approach which combines production-theory decomposition analysis (PDA) and index decomposition analysis (IDA). This novel approach can illustrate how energy structure effect, element substitution effect, efficiency change effect, input biased technical change, output biased technical change and magnitude of technical change affect carbon emission intensity of China's 30 provinces. The results indicate that during the 11th FYP and 13th FYP, output biased technical change and the magnitude of technical change are the critical factors in China's carbon emission intensity, while other four drivers increase carbon emissions. But, during the 12

Indexed as

CarbonIndustryCarbon DioxideChinaEconomic DevelopmentCarbonCarbon DioxideBiased technical changeCarbon emission intensityEfficiency changeElement substitutionEnergy structureMultidimensional decomposition approach

Identifiers

PMID35067877
OpenAlexW4206989637

What OpenQuestion holds

Textmetadata
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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.