Inequality can double the energy required to secure universal decent living

Abstract

Ecological breakdown and economic inequality are among the largest contemporary global challenges, and the issues are thoroughly entangled - as they have been throughout the history of civilisations. Yet, the global economy continues toward ecological crises, and inequalities remain far higher than citizens believe to be fair. Here, we explore the role of inequality, alongside traditional drivers of ecological impacts, in determining global energy requirements for providing universal decent living. We consider scenarios from fair inequality - where inequalities mirror public ideals - through a fairly unequal world, to one with a super-rich global elite. The energy-costs of inequality appear far more significant than population: even fair levels increase the energy required to provide universal decent living by 40%, and a super-rich global 1% could consume as much energy as would providing decent living to 1.7 billion. We finish by arguing that total population remains important nonetheless, but for reasons beyond ecological impacts.

Fig. 1. Estimates of global final energy use compared to key scenarios from the literature.

Total final energy use in 2050 for the six scenarios (a). In panel b, the axis is expanded and three scenarios shown, including DLE and two combination scenarios: high population, current technology & fair inequality (HP-CT-Fair) and high population, current technology, & fairly large inequality (HP-CT-FLI). Various other scenarios are shown in b for comparison, including a range of 1.5°C consistent scenarios from IPCC literature; the Net-zero by 2050 scenario (lower end of range) & Sustainable Development Scenario (upper end) of the IEA; and the Low Energy Demand (LED) scenario of Grubler et al. (2018).

Fig. 2. Estimates of final energy use per capita across global population quantiles.

Final energy per capita in 2050 for the three inequality scenarios, shown averaged across population quantiles for the lowest to highest consumption groups. For comparison the current distribution of final energy is also shown, as well as that for a selection of income groups and countries (from Oswald et al. (2020), but with government & capital energy added). The stepped patterns arise from the distributions produced in the inequality scenarios, which are at a resolution of deciles up to the top decile, which is split into three further groups (see Methods for more details). DUE Germany, ITA Italy, JPN Japan, IND India, TZA Tanzania, ETH Ethiopia.

Fig. 3. Energy inequality for different sectors and the composition of total energy use.

Panel a shows GINI coefficients of 2050 global final energy use across consumption categories for the inequality scenarios (DLE is omitted as inequalities are negligible). The vertical lines indicate GINI coefficients for total energy use for each scenario. Panel b shows the sectoral breakdown of global energy use for the inequality scenarios, alongside the DLE scenario. Note, some of the legend is abbreviated: FL Fairly Large Inequality, SR Super-rich and Power infra’ = Power infrastructure (i.e. the energy use involved in constructing power supply infrastructure).

Fig. 4. Final energy use by region alongside current final energy footprints.

Final energy is shown in absolute (a) and per-capita terms (b). Current final energy footprints (EF) are from Oswald et al. (2020). Regions are ordered from lowest to highest absolute energy footprint, and dashed lines are only included where a trend is observed. Note that for visual clarity, the super-rich scenario is omitted from panel b; the data lies in between the fair inequality and fairly large inequality scenarios. Note also that the regions in both panels match, but names in b are abbreviated due to space constraints.