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Transitions in pathways of human development and carbon emissions

Authors: Glen P. Peters; Julia K. Steinberger; Julia K. Steinberger; Alice Bows-Larkin; William F. Lamb; JT Roberts; F.R. Wood;

Transitions in pathways of human development and carbon emissions

Abstract

Countries are known to follow diverse pathways of life expectancy and carbon emissions, but little is known about factors driving these dynamics. In this letter we estimate the cross-sectional economic, demographic and geographic drivers of consumption-based carbon emissions. Using clustering techniques, countries are grouped according to their drivers, and analysed with respect to a criteria of one tonne of carbon emissions per capita and a life expectancy over 70 years (Goldemberg's Corner). Five clusters of countries are identified with distinct drivers and highly differentiated outcomes of life expectancy and carbon emissions. Representatives from four clusters intersect within Goldemberg's Corner, suggesting diverse combinations of drivers may still lead to sustainable outcomes, presenting many countries with an opportunity to follow a pathway towards low-carbon human development. By contrast, within Goldemberg's Corner, there are no countries from the core, wealthy consuming nations. These results reaffirm the need to address economic inequalities within international agreements for climate mitigation, but acknowledge plausible and accessible examples of low-carbon human development for countries that share similar underlying drivers of carbon emissions. In addition, we note differences in drivers between models of territorial and consumption-based carbon emissions, and discuss interesting exceptions to the drivers-based cluster analysis.

Countries
United Kingdom, Norway, United Kingdom, United Kingdom
Keywords

sustainable development, lowcarbon development pathways, Science, Physics, QC1-999, Q, Environmental technology. Sanitary engineering, Environmental sciences, low-carbon development pathways, climate change, GE1-350, world systems theory, TD1-1066

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    125
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
125
Top 1%
Top 10%
Top 1%
Green
gold