Literature DB >> 31612413

Configurational conditions of national carbon intensity: a fuzzy set analysis of 136 countries.

Yimin Mao1.   

Abstract

Drawing on the insights from the literature in environmental economics and politics, this study examines the configurational conditions of national carbon intensity by constructing a new analytical framework integrating six factors, i.e. population, affluence, industrial structure, energy intensity, urbanization rate and democracy. A fuzzy set analysis of 136 countries shows that national carbon intensity is not determined by any single factor but rather by the combined effects of multiple factors. There are two configurational pathways to low-carbon development while four pathways to high-carbon development, each with its own configuration. Low-carbon development occurs most often in those affluent, highly urbanized and democratic countries with low intensity of energy use, while high-carbon development is most likely in those small, poor countries with high intensity of energy use. This study also shows that the role of particular factor should be understood in the context as its combinations with different sets of other factors may produce opposite effects on national carbon intensity. That is, the policy efforts concentrated on single factor may be ineffective to reduce carbon intensity. These findings permit a more contextualized and systematic understanding of the determinants of national carbon intensity.

Entities:  

Keywords:  Carbon intensity; Configurational conditions; Cross-national data; Qualitative comparative analysis

Mesh:

Substances:

Year:  2019        PMID: 31612413     DOI: 10.1007/s11356-019-06471-6

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


  5 in total

1.  Tracking the anthropogenic drivers of ecological impacts.

Authors:  Eugene A Rosa; Richard York; Thomas Dietz
Journal:  Ambio       Date:  2004-12       Impact factor: 5.129

2.  Impact of population growth.

Authors:  P R Ehrlich; J P Holdren
Journal:  Science       Date:  1971-03-26       Impact factor: 47.728

3.  Does democratic transition reduce carbon intensity? Evidence from Indonesia using the synthetic control method.

Authors:  Yimin Mao
Journal:  Environ Sci Pollut Res Int       Date:  2018-05-08       Impact factor: 4.223

4.  The long-run effects of economic, demographic, and political indices on actual and potential CO2 emissions.

Authors:  Philip Kofi Adom; Paul Adjei Kwakwa; Afua Amankwaa
Journal:  J Environ Manage       Date:  2018-04-27       Impact factor: 6.789

5.  Effects of population and affluence on CO2 emissions.

Authors:  T Dietz; E A Rosa
Journal:  Proc Natl Acad Sci U S A       Date:  1997-01-07       Impact factor: 11.205

  5 in total
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1.  Formation Mechanism of a Coastal Zone Environment Collaborative Governance Relationship: A Qualitative Comparative Analysis Based on fsQCA.

Authors:  Wanjuan Wang; Hongbo Gong
Journal:  Int J Environ Res Public Health       Date:  2022-09-04       Impact factor: 4.614

  1 in total

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