Inequality in energy consumption, both direct and indirect, affects the distribution of benefits that result from energy use. Detailed measures of this inequality are required to ensure an equitable and just energy transition. Here we calculate final energy footprints; that is, the energy embodied in goods and services across income classes in 86 countries, both highly industrialized and developing. We analyse the energy intensity of goods and services used by different income groups, as well as their income elasticity of demand. We find that inequality in the distribution of energy footprints varies across different goods and services. Energy-intensive goods tend to be more elastic, leading to higher energy footprints of high-income individuals. Our results consequently expose large inequality in international energy footprints: the consumption share of the bottom half of the population is less than 20% of final energy footprints, which in turn is less than what the top 5% consume.
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The expenditure data used is available at http://datatopics.worldbank.org/consumption/ and https://ec.europa.eu/eurostat/data/database. The IEA data can be downloaded under institutional license from the UK data service at https://stats2.digitalresources.jisc.ac.uk/ and https://doi.org/10.5257/iea/web/2018-10. The underlying GTAP 9 database can be purchased from https://www.gtap.agecon.purdue.edu/databases/v9/default.asp. The concordance matrices used in the footprint calculations are depicted in the Supplementary Tables 3 and 4. The final energy footprint data per consumption category, nation and income group as well as energy intensities, elasticities and scenario parameters are available from the corresponding author on reasonable request. Source data for Figures 1 to 6 are provided with the paper.
MATLAB code for obtaining final energy footprints from the MRIO and calculating elasticities and the Gini coefficient is available at https://github.com/eeyouol.
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Y.O. is supported by the Leverhulme Trust’s Research Leadership Award ‘Living Well Within Limits’ (RL2016–048) project awarded to J.K.S. J.K.S was partly supported by an International Academic Fellowship of the Leverhulme Trust (IAF-2018–018). The contributions of A.O. were supported by EPSRC Fellowship award EP/R005052/1. We also would like to thank M. Baltruszewicz, J. Vogel, J. Millward-Hopkins, P. Brockway and L. Hardt for helpful discussions.
The authors declare no competing interests.
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Energy footprints per capita, expenditure per capita.
Gini coefficients of countries in energy and expenditure.
Elasticities and energy intensities per country and consumption category.
Population-weighted average of elasticities and energy intensities.
Cumulative population and cumulative energy resources needed to generate Lorenz curves, Raw consumption-based energy accounts per country and consumption category.
Share of aggregated consumption categories in energy over time, Raw consumption-based energy accounts per country and consumption category with additional business as usual forecasts, OECD given and applied growth forecasts.
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Oswald, Y., Owen, A. & Steinberger, J.K. Large inequality in international and intranational energy footprints between income groups and across consumption categories. Nat Energy 5, 231–239 (2020). https://doi.org/10.1038/s41560-020-0579-8
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