edit ms

analysis/paper/paper.Rmd

@@ -409,13 +409,23 @@ pdat_int_co2 = get_sector_summary_by_eu_ntile_direct(eu_q_count) %>%
   ungroup() %>%
   filter(year==2015) %>%
   left_join(read_csv(here("analysis/data/derived/sectors_agg_method1_ixi.csv")), by="sector_agg_id") %>% 
-  mutate(value = (total_co2_kg)/(total_fd_me*1000000)) %>%
+  mutate(value = (total_co2eq_kg)/(total_fd_me*1000000)) %>%
   select(five_sectors, eu_q_rank, 
          value) %>%
   mutate(indicator = "Carbon intensity (kgCO2eq/€)")
 
+pdat_int_energy = get_sector_summary_by_eu_ntile_direct(eu_q_count) %>%
+  ungroup() %>%
+  filter(year==2015) %>%
+  left_join(read_csv(here("analysis/data/derived/sectors_agg_method1_ixi.csv")), by="sector_agg_id") %>% 
+  mutate(value = (total_energy_use_tj)/(total_fd_me*1000)) %>%
+  select(five_sectors, eu_q_rank,
+         value) %>%
+  mutate(indicator = "Energy intensity (MJ/€)")
+
 library(viridis)
 pdat = pdat_int_co2 %>%
+  bind_rows(pdat_int_energy) %>%
   bind_rows(pdat_basket)
 
 a = ggplot(pdat, aes(x=value, y=five_sectors, color=eu_q_rank)) +
@@ -424,7 +434,7 @@ a = ggplot(pdat, aes(x=value, y=five_sectors, color=eu_q_rank)) +
   scale_color_viridis(option = "A", end = 0.8,
                       direction = -1, 
                       breaks = c(1, 5, 10), 
-                      name="EU decile") +
+                      name="European decile") +
   facet_wrap(~indicator, scales="free_x") +
   theme_minimal() +
   labs(x="", y="")+
@@ -734,7 +744,7 @@ ggsave(here("analysis", "figures", "figure4-test.pdf"))
 knitr::include_graphics(here::here("analysis", "figures", "figure4-test.pdf"))
 ```
 
-Our results show that in 2015, rich people in rich countries had access to the most energy-efficient energy services across all final demand sectors (Figure 2b [*todo currently figure shows only carbon*]). 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. 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 demand sector as the 10th decile. Around 17 EJ would have been saved in total, and the energy footprint of the first 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, rich people in rich countries had access to the most energy-efficient energy services across all final demand 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. 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 demand sector as the 10th decile. Around 17 EJ would have been saved in total, and the energy footprint of the first 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.
 
 Points to hit: - Improving energy efficiency is the most politically uncontroversial step towards mitigation targets. The EU has a bunch of policies for that, old and new. The GD has a transition fund to pay for this for poorer countries, sort of.