The different intensities of household consumption across European expenditure deciles can be attributed to a combination of two plausible causes: first, the composition of consumption baskets could systematically differ according to the level of household expenditure [@tobben_regional_2017]. Second, the energy and carbon intensity within individual final consumption categories could systematically differ across countries. Within countries, sectoral energy and carbon intensities are uniform due to the homogeneous product assumption of input-output models. However, since household purchasing power is distributed very unequally across European countries, many Eastern European households, for example, end up in the lower expenditure deciles and Scandinavian households tend to be in the higher ones (Figure S1 in SI). This gives us different intensities in the expenditure deciles, allowing us to capture part of the differences in energy and carbon efficiencies across Europe (Figure 2).
The different intensities of household consumption across European expenditure deciles can be attributed to a combination of two plausible causes: first, the composition of consumption baskets could systematically differ according to the level of household expenditure [@tobben_regional_2017]. Second, the energy and carbon intensity within individual final consumption categories could systematically differ across countries. Within countries, sectoral energy and carbon intensities are uniform due to the homogeneous product assumption of input-output models. However, since household purchasing power is distributed very unequally across European countries, many Eastern European households, for example, end up in the lower expenditure deciles and Scandinavian households tend to be in the higher ones (see SI, Figure S1). This gives us different intensities in the expenditure deciles, allowing us to capture part of the differences in energy and carbon efficiencies across Europe (Figure 2).
Our results show that in 2015, higher-income households in higher-income countries had access to the most energy-efficient energy services across the final consumption categories (Figure 2). Since we are interested in the largest numerically possible inequality in the distribution of energy footprints from actual household consumption, we calculated a counterfactual in which all European deciles use the best technology available in 2015 (Figure 4). In practice, this corresponds, for example, to the need for large-scale investments in the technical efficiency of heat, electricity and hot water supply, especially in Eastern Europe [@bianco_understanding_2019]. Improving technical efficiency is already a major part of the EU platform, and new transition funds for lower-income countries, whether public or private under a Green Deal framework, need to be appropriately targeted, and at an appropriately large scale, to reduce the high intensities of consumption in the lower deciles [@european_commission_communication_2019; @european_commission_european_2020].
Around `r energy_total_hh_diff` EJ net energy would have been saved in total in 2015, if all deciles had the same energy intensity per consumption category as the top decile (`r energy_final_diff` EJ from final consumption and `r energy_losses_diff` EJ from avoided losses). The average net energy footprint would have been `r energy_pae_mean_new` GJ/ae instead of `r energy_net_pae_mean` GJ/ae, and the net energy footprint of the bottom decile would have been less than half (-`r improvement_bottom_decile$energy_net_relchange`%) its 2015 value (Figure 4a) with a `r improvement_bottom_decile$energy_final_relchange`% reduction in final energy use and `r improvement_bottom_decile$energy_losses_relchange`% fewer conversion losses. The saved energy would have been especially large in Eastern Europe, over 60% for Bulgaria and the Czech Republic for example (Figure 4b). Poland would have saved the most in absolute terms, at `r poland_energy_savings_ej` EJ. Energy inequality would have been higher, at a 90:10 ratio of `r energy_10_10_new` (for both net and final energy; close to expenditure inequality, at `r exp_10_10`, as the differences in intensity per decile are removed but differences in the consumption baskets remain), compared to our actual 2015 energy inequality estimate of a 90:10 ratio of `r energy_10_10` (net energy; `r final_energy_10_10` for final energy).
Around `r energy_total_hh_diff` EJ net energy would have been saved in total in 2015, if all deciles had the same energy intensity per final consumption category as the top decile (`r energy_final_diff` EJ from final energy and `r energy_losses_diff` EJ from avoided losses). The average net energy footprint would have been `r energy_pae_mean_new` GJ/ae instead of `r energy_net_pae_mean` GJ/ae, and the net energy footprint of the bottom decile would have been less than half (-`r improvement_bottom_decile$energy_net_relchange`%) its 2015 value (Figure 4a) with a `r improvement_bottom_decile$energy_final_relchange`% reduction in final energy use and `r improvement_bottom_decile$energy_losses_relchange`% fewer conversion losses. The saved energy would have been especially large in Eastern Europe, over 60% for Bulgaria and the Czech Republic for example (Figure 4b). Poland would have saved the most in absolute terms, at `r poland_energy_savings_ej` EJ. Energy inequality would have been higher, at a 90:10 ratio of `r energy_10_10_new` (for both net and final energy; close to expenditure inequality, at `r exp_10_10`, as the differences in intensity per decile are removed but differences in the consumption baskets remain), compared to our actual 2015 energy inequality estimate of a 90:10 ratio of `r energy_10_10` (net energy; `r final_energy_10_10` for final energy).
