Evidence map›Paper›PMID 34849112›Full record

ArticleClean technologies and environmental policy2022

Analyzing driving forces of China's carbon emissions from 1997 to 2040 and the potential emission reduction path: through decomposition and scenario analysis.

Ce Song, Tao Zhao, Juan Wang

Abstract read
In one paragraph

Article in Clean technologies and environmental policy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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0cells of the map it votes in
4citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Building a novel multivariate nonlinear MGM(1,Environment, development and sustainability · 2022
    Article
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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

3 authors.

Ce SongSchool of Economics and Management, Tianjin University, Tianjin, 300072 People's Republic of China.ORCID 0000-0003-4148-6185
Tao ZhaoSchool of Economics and Management, Tianjin University, Tianjin, 300072 People's Republic of China.
Juan WangCollege of Finance, Tianjin University of Finance and Economics, Tianjin, 300222 People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Energy and environmental policies are important methods for the government to restrain carbon emissions growth. Identifying the potential dynamic trends of China's carbon emissions under different scenarios has important reference significance for the government's policy implementation. This paper firstly predicted China's carbon emissions from 2017 to 2040 based on three energy transition scenarios at the industrial level. Then, Logarithmic Mean Divisia Index decomposition model was applied to evaluate the driving forces of emissions changes during 1997-2040. Finally, the Spatial-Temporal Logarithmic Mean Divisia Index model was used to explore the emissions reduction potential and the potential reduction path at provincial level. The results showed that (1) as the reduction in energy intensity cannot offset the growth of industrial scale, the carbon emissions of all industries have shown an increasing trend from 1997 to 2017; (2) In the current policies scenario, China's carbon emissions cannot reach the peak before 2040. And only in the sustainable development scenario, the carbon emissions of the three industries will all reach the peaks before 2030. And the development of non-fossil energy will reduce carbon emissions by more than 30%; (3) Hebei, Shanxi, Inner Mongolia, Ningxia, and Heilongjiang are key provinces and improving energy efficiency of the secondary industry is a potential way to promote carbon emissions reduction. GRAPHICAL ABSTRACT: The framework and main content of this paper. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10098-021-02240-7.

Indexed as

Carbon emissionsDecomposition modelProvincial analysisScenario analysis

Identifiers

PMID34849112
PMCPMC8616976

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