revision 0.2

analysis/paper/.~lock.paper_new.docx#

+,pichler,pichler-Latitude-7400,07.04.2021 09:10,file:///home/pichler/.config/libreoffice/4;
\ No newline at end of file

analysis/paper/figures.Rmd

@@ -73,7 +73,6 @@ pdat_sector_summary_by_eu_ntile =
 # Fig. 1
 
 ```{r ntiles-total}
-
 p1 = pdat_country_summary_by_eu_ntile %>%
   filter(year == 2015, 
          indicator == "total_fd_me") %>%
@@ -91,18 +90,26 @@ p1 = pdat_country_summary_by_eu_ntile %>%
 
 p2 = pdat_country_summary_by_eu_ntile %>%
   filter(year == 2015, 
-         indicator == "total_energy_use_tj") %>%
-  group_by(eu_q_rank) %>%
-  summarise(value = sum(value)*0.000001,
-            eu_ntile_name = first(eu_ntile_name)) %>%
-  ggplot(aes(x=eu_ntile_name, y=value)) +
-    geom_col(position = position_dodge(), fill=pal[1]) +
+         indicator %in% c("total_energy_use_tj", "total_energy_use_losses_tj")) %>%
+  group_by(eu_ntile_name, indicator) %>%
+  summarise(value = sum(value)*0.000001) %>%
+  pivot_wider(id_cols = eu_ntile_name, names_from = indicator, values_from = value) %>% 
+  mutate(total_energy_use_final_tj = total_energy_use_tj-total_energy_use_losses_tj) %>% 
+  select(-total_energy_use_tj) %>% 
+  pivot_longer(cols=-eu_ntile_name, names_to = "indicator", values_to = "value") %>% 
+  mutate(component = if_else(indicator=="total_energy_use_losses_tj", "Loss", "Final energy")) %>% 
+  mutate(component = factor(component, levels=c("Loss", "Final energy"))) %>% 
+  ggplot(aes(x=eu_ntile_name, y=value, fill=component)) +
+    geom_col(position = position_stack()) +
+    scale_fill_manual(name = "", values = pal[c(3,1)]) +
     #theme_ipsum() +
     theme_minimal() +
     theme(text=element_text(family="Liberation Sans Narrow")) +
-    labs(x="", y="Energy footprint (EJ)") +
+    labs(x="", y="Net energy footprint (EJ)") +
     theme(axis.text.x = element_text(angle = 90)) +
-    scale_x_discrete(labels = c("D01","D02","D03","D04","D05","D06","D07","D08","D09","D10")) 
+    scale_x_discrete(labels = c("D01","D02","D03","D04","D05","D06","D07","D08","D09","D10")) +
+  theme(legend.position = c(0.2,0.91),
+        legend.text = element_text(size=11))
 
 p3 = pdat_country_summary_by_eu_ntile %>%
   filter(year == 2015, 
@@ -189,10 +196,8 @@ p_bottom = p2 + p1 + p3
 
 ```{r , fig.width=12, fig.height=8}
 
-a = p_top / p_bottom + plot_annotation(tag_levels = 'a') +
-  plot_layout(guides = 'collect')  & 
+a = p_top / p_bottom + plot_annotation(tag_levels = 'a') & 
   theme(plot.margin = unit(c(0.25,0.25,0.25,0.25), "cm"),
-        legend.position = 'bottom',
         axis.title.y = element_text(size=13, hjust = 0.5),
         axis.text.x = element_text(size = 12),
         axis.text.y = element_text(size = 12),
@@ -203,7 +208,7 @@ ggsave(here("analysis", "figures", "figure1.pdf"), device=cairo_pdf)
 
 ```
 
-```{r figure1, out.width="98%", fig.cap="Household expenditure and environmental footprints and intensities across European expenditure deciles. Total expenditures (a), energy footprint (b), and carbon footprint (c) per decile. Energy intensity of consumption as energy footprint per expenditure (d), carbon intensity of consumption as carbon footprint per expenditure (e), and carbon intensity of energy as carbon footprint per energy footprint (f)."}
+```{r figure1, out.width="98%", fig.cap="Household expenditure and environmental footprints and intensities across European expenditure deciles. Total expenditures (a), net energy footprint (composed of final energy and losses) (b), and carbon footprint (c) per decile. Energy intensity of consumption as energy footprint per expenditure (d), carbon intensity of consumption as carbon footprint per expenditure (e), and carbon intensity of energy as carbon footprint per energy footprint (f)."}
 knitr::include_graphics(here::here("analysis", "figures", "figure1.pdf"))
 ```
 
@@ -349,7 +354,7 @@ p2 = ggplot(pdat %>% filter(indicator_type == "Energy GJ per adult eq"),
   #theme_ipsum() +
   theme_minimal() +
   #theme(text=element_text(family="Liberation Sans Narrow")) +
-  labs(x="", y="Energy footprint GJ per adult eq") #+
+  labs(x="", y="Net energy footprint GJ per adult eq") #+
   # theme(legend.position = "bottom", 
   #         axis.text.x = element_text(angle = 90, size = 12),
   #         axis.text.y = element_text(size = 12),
@@ -377,7 +382,7 @@ a = (p1 / p2) +
 ggsave(here("analysis", "figures", "figure3.pdf"))
 ```
 
-```{r figure3, out.width="100%", fig.cap="Energy and carbon footprints by final consumption sector and European expenditure decile in 2015, further broken down by emission source location."}
+```{r figure3, out.width="100%", fig.cap="Net energy and carbon footprints by final consumption sector and European expenditure decile in 2015, further broken down by emission source location."}
 knitr::include_graphics(here::here("analysis", "figures", "figure3.pdf"))
 ```
 
@@ -422,7 +427,7 @@ p1 = ggplot(pdat_final_demand, aes(x=eu_q_rank, y=value, fill=indicator, alpha=i
   scale_alpha_manual(values=c(0.3,1),labels=c("2015", "Best technology"), name="Energy\nfootprint")+
   scale_x_continuous(breaks = c(1,2,3,4,5,6,7,8,9,10), 
                      labels = c("D01","D02","D03","D04","D05","D06","D07","D08","D09","D10")) +
-  labs(y="Energy footprint (EJ)", x="") +
+  labs(y="Net energy footprint (EJ)", x="") +
   theme_minimal() +
   coord_flip() +
   theme(legend.position="bottom")
@@ -479,7 +484,7 @@ p1 = ggplot(pdat_final_demand, aes(x=eu_q_rank, y=value, fill=technology, alpha=
   scale_alpha_manual(values=c(0.3,1),labels=c("2015", "Best technology"), name="Energy\nfootprint")+
   scale_x_continuous(breaks = c(1,2,3,4,5,6,7,8,9,10), 
                      labels = c("D01","D02","D03","D04","D05","D06","D07","D08","D09","D10")) +
-  labs(y="Energy footprint (EJ)", x="") +
+  labs(y="Net energy footprint (EJ)", x="") +
   theme_minimal() +
   coord_flip() +
   theme(legend.position="bottom") +
@@ -732,7 +737,7 @@ ggsave(here("analysis", "figures", "figure5.pdf"))
 ```
 
 
-```{r figure5, out.width="70%", fig.align="center", fig.cap="Mean energy available for Europe in decarbonisation scenarios, positioned in option space between a range of minimum energy requirements and range of associated maximum inequality. All expenditure deciles have 'best technology' already."}
+```{r figure5, out.width="70%", fig.align="center", fig.cap="Mean final energy available for Europe in decarbonisation scenarios, positioned in option space between a range of minimum final energy requirements and range of associated maximum inequality. All expenditure deciles have 'best technology' already."}
 knitr::include_graphics(here::here("analysis", "figures", "figure5.pdf"))
 ```