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Commit d52f6e13 authored by Ingram Jaccard's avatar Ingram Jaccard
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...@@ -603,7 +603,7 @@ shelter_energy_direct = round(((energy_per_source %>% filter(five_sectors == "sh ...@@ -603,7 +603,7 @@ shelter_energy_direct = round(((energy_per_source %>% filter(five_sectors == "sh
``` ```
Figure 3 also shows the inequality in geographical source of the household energy and carbon footprints across final consumption sector. The shelter footprint was almost entirely domestic, with `r shelter_co2eq_direct`/`r shelter_energy_direct`% coming from direct household energy use/emissions from heating and cooling, and the rest embedded primarily along the domestic supply chain. The transport footprint, on the other hand, was around 1/4 non-European. The majority of the transport footprint, above 60%, came from vehicle fuel, either directly, or indirectly embedded along its supply chain. The manufactured goods footprint was mostly non-European, while services and food were both around 1/3 non-European. These results suggest that proposed future carbon border-adjustment mechanisms will especially impact the manufactured goods and transport footprints of the higher deciles, and to a lesser extent the food and services footprints, depending on mechanism design. Figure 3 also shows the inequality in geographical source of the household energy and carbon footprints across final consumption sector. The shelter footprint was almost entirely domestic, with `r shelter_co2eq_direct`/`r shelter_energy_direct`% coming from direct household energy use/emissions from heating and cooling, and the rest embedded primarily along the domestic supply chain. The transport footprint, on the other hand, was around 1/4 non-European. The majority of the transport footprint, above 60%, came from vehicle fuel, either directly, or indirectly embedded along its supply chain. The manufactured goods footprint was mostly non-European, while services and food were both around 1/3 non-European. These results suggest that proposed future carbon border-adjustment mechanisms will especially impact the manufactured goods and transport footprints of the higher deciles, and to a lesser extent the food and services footprints, depending on mechanism design [@european_commission_communication_2019].
# Counterfactual: a 1.5°C compatible Europe # Counterfactual: a 1.5°C compatible Europe
...@@ -752,7 +752,7 @@ ggsave(here("analysis", "figures", "figure4-test.pdf")) ...@@ -752,7 +752,7 @@ ggsave(here("analysis", "figures", "figure4-test.pdf"))
knitr::include_graphics(here::here("analysis", "figures", "figure4-test.pdf")) knitr::include_graphics(here::here("analysis", "figures", "figure4-test.pdf"))
``` ```
Our results show that in 2015, higher-income people in higher-income countries had access to the most energy-efficient energy services across all final consumption sectors (Figure 2). Since we are interested in the numerically possible inequality in the distribution of actual consumption of goods and services in the next section, these efficiency differences must first be adjusted. 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 European Union (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 (ref). Figure 4 shows the energy footprint savings per decile (Fig. 4a) that would have occurred in 2015 if all deciles had the same efficiency per final consumption sector as the top decile. Around 17 EJ would have been saved in total, and the energy footprint of the bottom decile would have been nearly half its 2015 value. Fig. 4b shows saved energy per country, with Eastern European countries especially saving large proportions of their 2015 footprint, over 60% for Bulgaria and Estonia for example. Our results show that in 2015, higher-income people in higher-income countries had access to the most energy-efficient energy services across all final consumption sectors (Figure 2). Since we are interested in the numerically possible inequality in the distribution of actual consumption of goods and services in the next section, these efficiency differences must first be adjusted. 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 European Union (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]. Figure 4 shows the energy footprint savings per decile (Fig. 4a) that would have occurred in 2015 if all deciles had the same efficiency per final consumption sector as the top decile. Around 17 EJ would have been saved in total, and the energy footprint of the bottom decile would have been nearly half its 2015 value. Fig. 4b shows saved energy per country, with Eastern European countries especially saving large proportions of their 2015 footprint, over 60% for Bulgaria and Estonia for example.
## Inequality in a 1.5°C compatible Europe ## Inequality in a 1.5°C compatible Europe
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