Evidence map›Paper›PMID 35886642›Full record

ArticleInternational journal of environmental research and public health2022

Research on Determining the Critical Influencing Factors of Carbon Emission Integrating GRA with an Improved STIRPAT Model: Taking the Yangtze River Delta as an Example.

Feipeng Guo, Linji Zhang, Zifan Wang, Shaobo Ji

Abstract read
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Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

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0cells of the map it votes in
6citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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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

4 authors.

Feipeng GuoSchool of Management and E-Business, Zhejiang Gongshang University, Hangzhou 310018, China.ORCID 0000-0003-1263-2067
Linji ZhangSchool of Management and E-Business, Zhejiang Gongshang University, Hangzhou 310018, China.
Zifan WangSchool of Management and E-Business, Zhejiang Gongshang University, Hangzhou 310018, China.
Shaobo JiSprott School of Business, Carleton University, Ottawa, ON K1S 5B6, Canada.ORCID 0000-0002-0932-6758

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Driven by China's peak carbon emissions and carbon neutrality goals, each region should choose a suitable local implementation path according to local conditions, so it is of great significance to mine and analyze the critical influencing factors of regional carbon emissions. Therefore, this paper integrates grey relation analysis (GRA) and an improved STIRPAT model and selects the Yangtze River Delta region of China as the research object to analyze the factors affecting carbon emissions in four provinces in the region. Firstly, it uses the IPCC method to calculate the energy carbon emissions of each province. Secondly, according to the existing research, the relevant influencing factors of carbon emissions are sorted and summarized as candidate sets and this paper uses GRA to calculate the correlation degree of the above candidate sets. On this basis, this paper combines with the characteristics of the improved STIRPAT model to determine the index selection criteria and filter out the critical factors of each province. Thirdly, an improved STIRPAT model is constructed for each province to explore the influence of critical factors and analyze the influencing factors of carbon emissions in detail. The empirical results show that during the period from 2005 to 2019, the carbon emissions of the four provinces in the Yangtze River Delta are significantly different in structure and trend. At the same time, the critical influencing factors of each province are different and the influence of the same factor on different regions is significantly different. Finally, the policy suggestions for the provinces to achieve their peak carbon emissions and carbon neutrality goals are precisely tailored to the different carbon emission influencing factors.

Indexed as

CarbonRiversCarbon DioxideChinaEconomic DevelopmentCarbonCarbon Dioxidecarbon emission influencing factorsenergy consumptionGRAimproved STIRPAT modelYangtze River Delta

Identifiers

PMID35886642
PMCPMC9318623

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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.