edit ms

analysis/paper/paper.Rmd

@@ -71,7 +71,8 @@ pacman::p_load(tidyverse,
                wesanderson,
                glue,
                ggridges,
-               patchwork)
+               patchwork,
+               kableExtra)
 
 pal <- wes_palette("Cavalcanti1", 5, type = "discrete")
 extrafont::loadfonts()
@@ -591,14 +592,29 @@ shelter_energy_direct = round(((energy_per_source %>% filter(five_sectors == "sh
 
 Global 1.5°C compatible decarbonisation scenarios achieve a similar climate outcome with different assumptions about the transformation of energy supply and demand, from renewable capacity, deployment of carbon-capture-and-storage (CCS), and socio-technological demand transformation.
 
-[*maybe table with scenario properties*]
+```{r}
+
+library(readxl)
+
+df_scenario_info = read_excel(here("analysis/data/raw/scenarios.xlsx"), sheet="overview") %>%
+  select(scenario, fe_gj_aeu = final_energy_gj_per_aeu_2050,
+         ccs_required = primary_energy_fossil_w_ccs2050_ej,
+         description) %>%
+  arrange(fe_gj_aeu) %>%
+  mutate(fe_gj_aeu = round(fe_gj_aeu),
+         ccs_required = round(ccs_required)) 
+
+library(flextable) 
+
+regulartable(df_scenario_info) %>%
+  autofit()
+
+```
 
 The various global supply side scenarios (SSP1-1.9, SSP2-1.9, GEA efficiency) envisage total EU (*or our sample*) energy consumption falling from the current X EJ to X-Y EJ by 2030 (or 2050), equivalent to a per household reduction from a current average of 250 GJ to X-Y GJ per adult equivalent. The differences in energy consumption in 2050 in the scenarios reflect different model assumptions about the rate of expansion of renewable energy and CCS capacity. Most/all of these scenarios rely on substantial amounts of CCS (*starting from when?*) which is still a fairly speculative technology and we therefore interpret them as ranges for the upper limits of 1.5°C-compatible energy supply.
 
 It is even more difficult to determine a lower limit for the minimum amount of energy needed for a decent life. This depends strongly on the one hand on the prevalent socio-cultural idea of what constitutes a decent life, and on the other hand, perhaps even more strongly, on the physical infrastructure available to deliver this life. The two (include Boell?) global demand side scenarios (LED, DLE) that attempt to define such a limit conclude that, in principle, a very low energy footprint (between 16-53 GJ per household adult equivalent) could be sufficient. However, these scenarios rely on socio-technological transformations on a scale that, especially at the lower end, far exceeds the current political discourse on the subject. All two/three scenarios are 1.5°C compatible without resorting to any CCS but they all implicitly (LED) or explicitly (DLE) assume near complete equality of consumption across the population. To put these low energy demand numbers in perspective, the average energy footprint in our sample is about a factor 5 above the high estimate (250 MJ/aeq). Households in the first European expenditure decile had an energy footprint of 130 GJ per adult equivalent in 2015 even though they fell almost entirely within the Eurostat definition of severe material deprivation.
 
-[*I struggle to separate between energy efficiency in purely technological terms, and energy efficiency of the energy service. This is relevant for the transformation we apply. Do we assume the efficiency differences are only due to inefficient energy carriers and transformation losses, or do we assume this is also due to differences in the demand/provision of energy services, e.g. more rural and car dependent. It would be easier if we could argue the former, which I will do for now.*]
-
 Based on these two constraints, the upper limit on the supply side and the lower limit on the demand side, it is possible to make a generalized estimate of how much inequality in the distribution of energy consumption is numerically possible, if at the same time global warming is to be kept below 1.5°C above pre-industrial levels and a good life for all is to be made possible. Before we can make this evaluation, we must take into account the existing large differences in the technological efficiency of energy provision (Figure 2). Since the European expenditure deciles discussed here include large population groups (\~X persons/households) with different demand structures for energy services (urban/rural, demographic, climatic), we assume that the variation in energy intensity across deciles is largely due to technological efficiency. These differences will be adjusted in the next step.
 
 ## Current empirical best technology per sector