diff --git a/analysis/preprocessing/full_code_europe.inequality.Rmd b/analysis/preprocessing/full_code_europe.inequality.Rmd
index 1f36bd067ae9e928950e4cd0ef51df2def277d34..69d4610a0ea99ddb59c0fe6ed8cd0804896df892 100644
--- a/analysis/preprocessing/full_code_europe.inequality.Rmd
+++ b/analysis/preprocessing/full_code_europe.inequality.Rmd
@@ -30,6 +30,7 @@ knitr::opts_chunk$set(
if (!require("pacman")) install.packages("pacman")
pacman::p_load(tidyverse,
janitor,
+ readr,
here,
wbstats,
ISOcodes,
@@ -2064,217 +2065,6 @@ for (i in years_exb_ixi){
ZA) %>%
select(TIV_energy_europe,TIV_energy_not_europe)
- # biomass
-
- Exiobase_TIV_biomass_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_biomass_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_biomass_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_biomass_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_biomass_domestic)
-
- Exiobase_TIV_europe_breakdown_biomass_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_biomass_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_biomass_europe = AT +
- BE + BG + CY + CZ +
- DE + DK + EE +
- ES + FI + FR +
- GB + GR + HR +
- HU + IE + IT +
- LT + LU + LV +
- MT + NL + PL +
- PT + TR + SK +
- SI + SE + RO +
- NO,
- TIV_biomass_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_biomass_europe,TIV_biomass_not_europe)
-
- # construction materials
-
- Exiobase_TIV_const_materials_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_const_materials_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_const_materials_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_const_materials_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_const_materials_domestic)
-
- Exiobase_TIV_europe_breakdown_const_materials_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_const_materials_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_const_materials_europe = AT +
- BE + BG + CY + CZ +
- DE + DK + EE +
- ES + FI + FR +
- GB + GR + HR +
- HU + IE + IT +
- LT + LU + LV +
- MT + NL + PL +
- PT + TR + SK +
- SI + SE + RO +
- NO,
- TIV_const_materials_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_const_materials_europe,TIV_const_materials_not_europe)
-
- # fossil fuels
-
- Exiobase_TIV_ffuels_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ffuels_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ffuels_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ffuels_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_ffuels_domestic)
-
- Exiobase_TIV_europe_breakdown_ffuels_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ffuels_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_ffuels_europe = AT +
- BE + BG + CY + CZ +
- DE + DK + EE +
- ES + FI + FR +
- GB + GR + HR +
- HU + IE + IT +
- LT + LU + LV +
- MT + NL + PL +
- PT + TR + SK +
- SI + SE + RO +
- NO,
- TIV_ffuels_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_ffuels_europe,TIV_ffuels_not_europe)
-
- # ores
-
- Exiobase_TIV_ores_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ores_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ores_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ores_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_ores_domestic)
-
- Exiobase_TIV_europe_breakdown_ores_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ores_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_ores_europe = AT +
- BE + BG + CY + CZ +
- DE + DK + EE +
- ES + FI + FR +
- GB + GR + HR +
- HU + IE + IT +
- LT + LU + LV +
- MT + NL + PL +
- PT + TR + SK +
- SI + SE + RO +
- NO,
- TIV_ores_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_ores_europe,TIV_ores_not_europe)
-
- # cropland
-
- Exiobase_TIV_cropland_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_cropland_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_cropland_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_cropland_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_cropland_domestic)
-
- Exiobase_TIV_europe_breakdown_cropland_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_cropland_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_cropland_europe = AT +
- BE + BG + CY + CZ +
- DE + DK + EE +
- ES + FI + FR +
- GB + GR + HR +
- HU + IE + IT +
- LT + LU + LV +
- MT + NL + PL +
- PT + TR + SK +
- SI + SE + RO +
- NO,
- TIV_cropland_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_cropland_europe,TIV_cropland_not_europe)
-
- # forest land
-
- Exiobase_TIV_forest_land_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_forest_land_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_forest_land_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_forest_land_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_forest_land_domestic)
-
- Exiobase_TIV_europe_breakdown_forest_land_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_forest_land_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_forest_land_europe = AT +
- BE + BG + CY + CZ +
- DE + DK + EE +
- ES + FI + FR +
- GB + GR + HR +
- HU + IE + IT +
- LT + LU + LV +
- MT + NL + PL +
- PT + TR + SK +
- SI + SE + RO +
- NO,
- TIV_forest_land_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_forest_land_europe,TIV_forest_land_not_europe)
-
- # pasture land
-
- Exiobase_TIV_pasture_land_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_pasture_land_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_pasture_land_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_pasture_land_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_pasture_land_domestic)
-
- Exiobase_TIV_europe_breakdown_pasture_land_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_pasture_land_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_pasture_land_europe = AT +
- BE + BG + CY + CZ +
- DE + DK + EE +
- ES + FI + FR +
- GB + GR + HR +
- HU + IE + IT +
- LT + LU + LV +
- MT + NL + PL +
- PT + TR + SK +
- SI + SE + RO +
- NO,
- TIV_pasture_land_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_pasture_land_europe,TIV_pasture_land_not_europe)
-
-
# join with labels
TIV_with_labels = cbind(Exiobase_T_labels,
@@ -2300,14 +2090,7 @@ for (i in years_exb_ixi){
t(Exiobase_TIV_sf6_bp),
t(Exiobase_TIV_hfc_bp),
t(Exiobase_TIV_pfc_bp),
- t(Exiobase_TIV_energy_use_bp),
- t(Exiobase_TIV_biomass_bp),
- t(Exiobase_TIV_const_materials_bp),
- t(Exiobase_TIV_ffuels_bp),
- t(Exiobase_TIV_ores_bp),
- t(Exiobase_TIV_cropland_bp),
- t(Exiobase_TIV_forest_land_bp),
- t(Exiobase_TIV_pasture_land_bp)) %>%
+ t(Exiobase_TIV_energy_use_bp)) %>%
rename(TIV_CO2 = "t(Exiobase_TIV_co2_bp)",
TIV_CO2_noncombustion_cement = "t(Exiobase_TIV_co2_noncombustion_cement_bp)",
TIV_CO2_noncombustion_lime = "t(Exiobase_TIV_co2_noncombustion_lime_bp)",
@@ -2330,14 +2113,7 @@ for (i in years_exb_ixi){
TIV_SF6 = "t(Exiobase_TIV_sf6_bp)",
TIV_HFC = "t(Exiobase_TIV_hfc_bp)",
TIV_PFC = "t(Exiobase_TIV_pfc_bp)",
- TIV_energy = "t(Exiobase_TIV_energy_use_bp)",
- TIV_biomass = "t(Exiobase_TIV_biomass_bp)",
- TIV_const_materials = "t(Exiobase_TIV_const_materials_bp)",
- TIV_ffuels = "t(Exiobase_TIV_ffuels_bp)",
- TIV_ores = "t(Exiobase_TIV_ores_bp)",
- TIV_cropland = "t(Exiobase_TIV_cropland_bp)",
- TIV_forest_land = "t(Exiobase_TIV_forest_land_bp)",
- TIV_pasture_land = "t(Exiobase_TIV_pasture_land_bp)") %>%
+ TIV_energy = "t(Exiobase_TIV_energy_use_bp)") %>%
mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"))
year = as.character(rep(year_current,nrow(TIV_with_labels)))
@@ -2375,14 +2151,7 @@ for (i in years_exb_ixi){
Exiobase_TIV_country_breakdown_sf6_bp %>% select(-country),
Exiobase_TIV_country_breakdown_hfc_bp %>% select(-country),
Exiobase_TIV_country_breakdown_pfc_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_energy_use_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_biomass_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_const_materials_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ffuels_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ores_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_cropland_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_forest_land_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_pasture_land_bp %>% select(-country)) %>%
+ Exiobase_TIV_country_breakdown_energy_use_bp %>% select(-country)) %>%
mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"),
country = dplyr::recode(country, "GR" = "EL", "GB" = "UK"))
@@ -2412,14 +2181,7 @@ for (i in years_exb_ixi){
TIV_SF6_domestic = as.numeric(TIV_SF6_domestic),
TIV_HFC_domestic = as.numeric(TIV_HFC_domestic),
TIV_PFC_domestic = as.numeric(TIV_PFC_domestic),
- TIV_energy_domestic = as.numeric(TIV_energy_domestic),
- TIV_biomass_domestic = as.numeric(TIV_biomass_domestic),
- TIV_const_materials_domestic = as.numeric(TIV_const_materials_domestic),
- TIV_ffuels_domestic = as.numeric(TIV_ffuels_domestic),
- TIV_ores_domestic = as.numeric(TIV_ores_domestic),
- TIV_cropland_domestic = as.numeric(TIV_cropland_domestic),
- TIV_forest_land_domestic = as.numeric(TIV_forest_land_domestic),
- TIV_pasture_land_domestic = as.numeric(TIV_pasture_land_domestic))
+ TIV_energy_domestic = as.numeric(TIV_energy_domestic))
domestic_TIVs = rbind(domestic_TIVs, look_domestic)
@@ -2448,14 +2210,7 @@ for (i in years_exb_ixi){
Exiobase_TIV_europe_breakdown_sf6_bp,
Exiobase_TIV_europe_breakdown_hfc_bp,
Exiobase_TIV_europe_breakdown_pfc_bp,
- Exiobase_TIV_europe_breakdown_energy_use_bp,
- Exiobase_TIV_europe_breakdown_biomass_bp,
- Exiobase_TIV_europe_breakdown_const_materials_bp,
- Exiobase_TIV_europe_breakdown_ffuels_bp,
- Exiobase_TIV_europe_breakdown_ores_bp,
- Exiobase_TIV_europe_breakdown_cropland_bp,
- Exiobase_TIV_europe_breakdown_forest_land_bp,
- Exiobase_TIV_europe_breakdown_pasture_land_bp) %>%
+ Exiobase_TIV_europe_breakdown_energy_use_bp) %>%
mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"))
year_europe = as.character(rep(year_current,nrow(europe_TIV_with_labels)))
@@ -2484,14 +2239,7 @@ for (i in years_exb_ixi){
TIV_SF6_europe = as.numeric(TIV_SF6_europe),
TIV_HFC_europe = as.numeric(TIV_HFC_europe),
TIV_PFC_europe = as.numeric(TIV_PFC_europe),
- TIV_energy_europe = as.numeric(TIV_energy_europe),
- TIV_biomass_europe = as.numeric(TIV_biomass_europe),
- TIV_const_materials_europe = as.numeric(TIV_const_materials_europe),
- TIV_ffuels_europe = as.numeric(TIV_ffuels_europe),
- TIV_ores_europe = as.numeric(TIV_ores_europe),
- TIV_cropland_europe = as.numeric(TIV_cropland_europe),
- TIV_forest_land_europe = as.numeric(TIV_forest_land_europe),
- TIV_pasture_land_europe = as.numeric(TIV_pasture_land_europe))
+ TIV_energy_europe = as.numeric(TIV_energy_europe))
europe_TIVs = rbind(europe_TIVs, look_europe)
@@ -2550,20 +2298,6 @@ for (i in years_exb_ixi){
national_energy_footprints = Exiobase_FD * t(Exiobase_TIV_energy_use_bp)
- national_biomass_footprints = Exiobase_FD * t(Exiobase_TIV_biomass_bp)
-
- national_const_materials_footprints = Exiobase_FD * t(Exiobase_TIV_const_materials_bp)
-
- national_ffuels_footprints = Exiobase_FD * t(Exiobase_TIV_ffuels_bp)
-
- national_ores_footprints = Exiobase_FD * t(Exiobase_TIV_ores_bp)
-
- national_cropland_footprints = Exiobase_FD * t(Exiobase_TIV_cropland_bp)
-
- national_forest_land_footprints = Exiobase_FD * t(Exiobase_TIV_forest_land_bp)
-
- national_pasture_land_footprints = Exiobase_FD * t(Exiobase_TIV_pasture_land_bp)
-
# together
@@ -2590,14 +2324,7 @@ for (i in years_exb_ixi){
rowSums(t(national_SF6_footprints)),
rowSums(t(national_HFC_footprints)),
rowSums(t(national_PFC_footprints)),
- rowSums(t(national_energy_footprints)),
- rowSums(t(national_biomass_footprints)),
- rowSums(t(national_const_materials_footprints)),
- rowSums(t(national_ffuels_footprints)),
- rowSums(t(national_ores_footprints)),
- rowSums(t(national_cropland_footprints)),
- rowSums(t(national_forest_land_footprints)),
- rowSums(t(national_pasture_land_footprints))) %>%
+ rowSums(t(national_energy_footprints))) %>%
mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"))
year_national_fp = as.character(rep(year_current,nrow(national_footprints_w_labels)))
@@ -2632,13 +2359,6 @@ for (i in years_exb_ixi){
direct_FD_hfc = direct_FD_extensions[425,]
direct_FD_pfc = direct_FD_extensions[426,]
direct_FD_energy = direct_FD_extensions[470,]
- direct_FD_biomass = colSums(direct_FD_extensions[c(471:499,501,522:688),])
- direct_FD_const_materials = colSums(direct_FD_extensions[514:521,])
- direct_FD_ffuels = direct_FD_extensions[500,]
- direct_FD_ores = colSums(direct_FD_extensions[502:513,])
- direct_FD_cropland = colSums(direct_FD_extensions[447:459,])
- direct_FD_forest_land = colSums(direct_FD_extensions[c(460,466),])
- direct_FD_pasture_land = colSums(direct_FD_extensions[462:464,])
direct_FD_fp = data.frame(direct_FD_co2,
@@ -2663,14 +2383,7 @@ for (i in years_exb_ixi){
direct_FD_sf6,
direct_FD_hfc,
direct_FD_pfc,
- direct_FD_energy,
- direct_FD_biomass,
- direct_FD_const_materials,
- direct_FD_ffuels,
- direct_FD_ores,
- direct_FD_cropland,
- direct_FD_forest_land,
- direct_FD_pasture_land)
+ direct_FD_energy)
look_national_fp = as.data.frame(cbind(year_national_fp,
national_footprints_w_labels,
@@ -2700,14 +2413,7 @@ for (i in years_exb_ixi){
sf6 = "rowSums(t(national_SF6_footprints))",
hfc = "rowSums(t(national_HFC_footprints))",
pfc = "rowSums(t(national_PFC_footprints))",
- energy = "rowSums(t(national_energy_footprints))",
- biomass = "rowSums(t(national_biomass_footprints))",
- const_materials = "rowSums(t(national_const_materials_footprints))",
- ffuels = "rowSums(t(national_ffuels_footprints))",
- ores = "rowSums(t(national_ores_footprints))",
- cropland = "rowSums(t(national_cropland_footprints))",
- forest_land = "rowSums(t(national_forest_land_footprints))",
- pasture_land = "rowSums(t(national_pasture_land_footprints))") %>%
+ energy = "rowSums(t(national_energy_footprints))") %>%
select(year,
geo,
fd_category,
@@ -2756,21 +2462,7 @@ for (i in years_exb_ixi){
pfc,
direct_FD_pfc,
energy,
- direct_FD_energy,
- biomass,
- direct_FD_biomass,
- const_materials,
- direct_FD_const_materials,
- ffuels,
- direct_FD_ffuels,
- ores,
- direct_FD_ores,
- cropland,
- direct_FD_cropland,
- forest_land,
- direct_FD_forest_land,
- pasture_land,
- direct_FD_pasture_land)
+ direct_FD_energy)
national_fp = rbind(national_fp, look_national_fp)
@@ -2842,20 +2534,6 @@ for (i in years_exb_ixi){
energy_carrier_use = satellite[470,]
- biomass = as.data.frame(colSums(satellite[c(471:499,501,522:688),]))
-
- ores = as.data.frame(colSums(satellite[502:513,]))
-
- const_materials = as.data.frame(colSums(satellite[514:521,]))
-
- ffuels = satellite[500,]
-
- cropland = as.data.frame(colSums(satellite[447:459,]))
-
- pasture_land = as.data.frame(colSums(satellite[462:464,]))
-
- forest_land = as.data.frame(colSums(satellite[c(460,466),]))
-
territorial = data.frame(t(CO2_combustion_air),
t(CO2_noncombustion_cement_air),
@@ -2879,14 +2557,7 @@ for (i in years_exb_ixi){
t(SF6_air),
t(HFC_air),
t(PFC_air),
- t(energy_carrier_use),
- biomass,
- ores,
- const_materials,
- t(ffuels),
- cropland,
- pasture_land,
- forest_land) %>%
+ t(energy_carrier_use)) %>%
rename(CO2 = 1,
CO2_noncombustion_cement = 2,
CO2_noncombustion_lime = 3,
@@ -2907,11 +2578,7 @@ for (i in years_exb_ixi){
N2O = 18,
N2O_agriculture = 19,
SF6 = 20,
- HFC = 21, PFC = 22, energy = 23,
- biomass = 24, ores = 25,
- const_materials = 26, ffuels = 27,
- cropland = 28, pasture_land = 29,
- forest_land = 30)
+ HFC = 21, PFC = 22, energy = 23)
year_territorial = as.character(rep(year_current,nrow(territorial)))
@@ -3092,14 +2759,7 @@ direct_FD_fp_long = national_fp %>%
direct_FD_sf6,
direct_FD_hfc,
direct_FD_pfc,
- direct_FD_energy,
- direct_FD_biomass,
- direct_FD_const_materials,
- direct_FD_ffuels,
- direct_FD_ores,
- direct_FD_cropland,
- direct_FD_forest_land,
- direct_FD_pasture_land) %>%
+ direct_FD_energy) %>%
slice(rep(1:n(), each = 3))
sector = rep(c("HH_HEAT","HH_TRA","HH_OTH"), nrow(direct_FD_fp_long)/3)
@@ -3403,49 +3063,7 @@ results = fd_exiobase %>%
q3_energy_europe = QUINTILE3*(TIV_energy_europe - TIV_energy_domestic),
q4_energy_europe = QUINTILE4*(TIV_energy_europe - TIV_energy_domestic),
q5_energy_europe = QUINTILE5*(TIV_energy_europe - TIV_energy_domestic),
- energy_total_europe = q1_energy_europe+q2_energy_europe+q3_energy_europe+q4_energy_europe+q5_energy_europe,
- TIV_materials = TIV_biomass+TIV_const_materials+TIV_ffuels+TIV_ores,
- q1_materials = QUINTILE1*TIV_materials,
- q2_materials = QUINTILE2*TIV_materials,
- q3_materials = QUINTILE3*TIV_materials,
- q4_materials = QUINTILE4*TIV_materials,
- q5_materials = QUINTILE5*TIV_materials,
- materials_total = q1_materials+q2_materials+q3_materials+q4_materials+q5_materials,
- TIV_materials_domestic = TIV_biomass_domestic+TIV_const_materials_domestic+TIV_ffuels_domestic+TIV_ores_domestic,
- q1_materials_domestic = QUINTILE1*TIV_materials_domestic,
- q2_materials_domestic = QUINTILE2*TIV_materials_domestic,
- q3_materials_domestic = QUINTILE3*TIV_materials_domestic,
- q4_materials_domestic = QUINTILE4*TIV_materials_domestic,
- q5_materials_domestic = QUINTILE5*TIV_materials_domestic,
- materials_total_domestic = q1_materials_domestic+q2_materials_domestic+q3_materials_domestic+q4_materials_domestic+q5_materials_domestic,
- TIV_materials_europe = TIV_biomass_europe+TIV_const_materials_europe+TIV_ffuels_europe+TIV_ores_europe,
- q1_materials_europe = QUINTILE1*(TIV_materials_europe - TIV_materials_domestic),
- q2_materials_europe = QUINTILE2*(TIV_materials_europe - TIV_materials_domestic),
- q3_materials_europe = QUINTILE3*(TIV_materials_europe - TIV_materials_domestic),
- q4_materials_europe = QUINTILE4*(TIV_materials_europe - TIV_materials_domestic),
- q5_materials_europe = QUINTILE5*(TIV_materials_europe - TIV_materials_domestic),
- materials_total_europe = q1_materials_europe+q2_materials_europe+q3_materials_europe+q4_materials_europe+q5_materials_europe,
- TIV_land_use = TIV_cropland+TIV_forest_land+TIV_pasture_land,
- q1_land_use = QUINTILE1*TIV_land_use,
- q2_land_use = QUINTILE2*TIV_land_use,
- q3_land_use = QUINTILE3*TIV_land_use,
- q4_land_use = QUINTILE4*TIV_land_use,
- q5_land_use = QUINTILE5*TIV_land_use,
- land_use_total =q1_land_use+q2_land_use+q3_land_use+q4_land_use+q5_land_use,
- TIV_land_use_domestic = TIV_cropland_domestic+TIV_forest_land_domestic+TIV_pasture_land_domestic,
- q1_land_use_domestic = QUINTILE1*TIV_land_use_domestic,
- q2_land_use_domestic = QUINTILE2*TIV_land_use_domestic,
- q3_land_use_domestic = QUINTILE3*TIV_land_use_domestic,
- q4_land_use_domestic = QUINTILE4*TIV_land_use_domestic,
- q5_land_use_domestic = QUINTILE5*TIV_land_use_domestic,
- land_use_total_domestic =q1_land_use_domestic+q2_land_use_domestic+q3_land_use_domestic+q4_land_use_domestic+q5_land_use_domestic,
- TIV_land_use_europe = TIV_cropland_europe+TIV_forest_land_europe+TIV_pasture_land_europe,
- q1_land_use_europe = QUINTILE1*(TIV_land_use_europe - TIV_land_use_domestic),
- q2_land_use_europe = QUINTILE2*(TIV_land_use_europe - TIV_land_use_domestic),
- q3_land_use_europe = QUINTILE3*(TIV_land_use_europe - TIV_land_use_domestic),
- q4_land_use_europe = QUINTILE4*(TIV_land_use_europe - TIV_land_use_domestic),
- q5_land_use_europe = QUINTILE5*(TIV_land_use_europe - TIV_land_use_domestic),
- land_use_total_europe =q1_land_use_europe+q2_land_use_europe+q3_land_use_europe+q4_land_use_europe+q5_land_use_europe)
+ energy_total_europe = q1_energy_europe+q2_energy_europe+q3_energy_europe+q4_energy_europe+q5_energy_europe)
results_with_direct_FD_fp = bind_rows(results,direct_FD_fp_wide)
@@ -4430,216 +4048,6 @@ for (i in years_exb_pxp){
ZA) %>%
select(TIV_energy_europe,TIV_energy_not_europe)
- # biomass
-
- Exiobase_TIV_biomass_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_biomass_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_biomass_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_biomass_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_biomass_domestic)
-
- Exiobase_TIV_europe_breakdown_biomass_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_biomass_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_biomass_europe = AT +
- BE + BG + CY + CZ +
- DE + DK + EE +
- ES + FI + FR +
- GB + GR + HR +
- HU + IE + IT +
- LT + LU + LV +
- MT + NL + PL +
- PT + TR + SK +
- SI + SE + RO +
- NO,
- TIV_biomass_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_biomass_europe,TIV_biomass_not_europe)
-
- # construction materials
-
- Exiobase_TIV_const_materials_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_const_materials_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_const_materials_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_const_materials_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_const_materials_domestic)
-
- Exiobase_TIV_europe_breakdown_const_materials_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_const_materials_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_const_materials_europe = AT +
- BE + BG + CY + CZ +
- DE + DK + EE +
- ES + FI + FR +
- GB + GR + HR +
- HU + IE + IT +
- LT + LU + LV +
- MT + NL + PL +
- PT + TR + SK +
- SI + SE + RO +
- NO,
- TIV_const_materials_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_const_materials_europe,TIV_const_materials_not_europe)
-
- # fossil fuels
-
- Exiobase_TIV_ffuels_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_ffuels_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ffuels_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ffuels_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_ffuels_domestic)
-
- Exiobase_TIV_europe_breakdown_ffuels_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ffuels_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_ffuels_europe = AT +
- BE + BG + CY + CZ +
- DE + DK + EE +
- ES + FI + FR +
- GB + GR + HR +
- HU + IE + IT +
- LT + LU + LV +
- MT + NL + PL +
- PT + TR + SK +
- SI + SE + RO +
- NO,
- TIV_ffuels_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_ffuels_europe,TIV_ffuels_not_europe)
-
- # ores
-
- Exiobase_TIV_ores_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_ores_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ores_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ores_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_ores_domestic)
-
- Exiobase_TIV_europe_breakdown_ores_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ores_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_ores_europe = AT +
- BE + BG + CY + CZ +
- DE + DK + EE +
- ES + FI + FR +
- GB + GR + HR +
- HU + IE + IT +
- LT + LU + LV +
- MT + NL + PL +
- PT + TR + SK +
- SI + SE + RO +
- NO,
- TIV_ores_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_ores_europe,TIV_ores_not_europe)
-
- # cropland
-
- Exiobase_TIV_cropland_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_cropland_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_cropland_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_cropland_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_cropland_domestic)
-
- Exiobase_TIV_europe_breakdown_cropland_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_cropland_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_cropland_europe = AT +
- BE + BG + CY + CZ +
- DE + DK + EE +
- ES + FI + FR +
- GB + GR + HR +
- HU + IE + IT +
- LT + LU + LV +
- MT + NL + PL +
- PT + TR + SK +
- SI + SE + RO +
- NO,
- TIV_cropland_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_cropland_europe,TIV_cropland_not_europe)
-
- # forest land
-
- Exiobase_TIV_forest_land_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_forest_land_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_forest_land_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_forest_land_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_forest_land_domestic)
-
- Exiobase_TIV_europe_breakdown_forest_land_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_forest_land_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_forest_land_europe = AT +
- BE + BG + CY + CZ +
- DE + DK + EE +
- ES + FI + FR +
- GB + GR + HR +
- HU + IE + IT +
- LT + LU + LV +
- MT + NL + PL +
- PT + TR + SK +
- SI + SE + RO +
- NO,
- TIV_forest_land_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_forest_land_europe,TIV_forest_land_not_europe)
-
- # pasture land
-
- Exiobase_TIV_pasture_land_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_pasture_land_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_pasture_land_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_pasture_land_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_pasture_land_domestic)
-
- Exiobase_TIV_europe_breakdown_pasture_land_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_pasture_land_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_pasture_land_europe = AT +
- BE + BG + CY + CZ +
- DE + DK + EE +
- ES + FI + FR +
- GB + GR + HR +
- HU + IE + IT +
- LT + LU + LV +
- MT + NL + PL +
- PT + TR + SK +
- SI + SE + RO +
- NO,
- TIV_pasture_land_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_pasture_land_europe,TIV_pasture_land_not_europe)
-
# join with labels
@@ -4666,14 +4074,7 @@ for (i in years_exb_pxp){
t(Exiobase_TIV_sf6_bp),
t(Exiobase_TIV_hfc_bp),
t(Exiobase_TIV_pfc_bp),
- t(Exiobase_TIV_energy_use_bp),
- t(Exiobase_TIV_biomass_bp),
- t(Exiobase_TIV_const_materials_bp),
- t(Exiobase_TIV_ffuels_bp),
- t(Exiobase_TIV_ores_bp),
- t(Exiobase_TIV_cropland_bp),
- t(Exiobase_TIV_forest_land_bp),
- t(Exiobase_TIV_pasture_land_bp)) %>%
+ t(Exiobase_TIV_energy_use_bp)) %>%
rename(TIV_CO2 = "t(Exiobase_TIV_co2_bp)",
TIV_CO2_noncombustion_cement = "t(Exiobase_TIV_co2_noncombustion_cement_bp)",
TIV_CO2_noncombustion_lime = "t(Exiobase_TIV_co2_noncombustion_lime_bp)",
@@ -4696,14 +4097,7 @@ for (i in years_exb_pxp){
TIV_SF6 = "t(Exiobase_TIV_sf6_bp)",
TIV_HFC = "t(Exiobase_TIV_hfc_bp)",
TIV_PFC = "t(Exiobase_TIV_pfc_bp)",
- TIV_energy = "t(Exiobase_TIV_energy_use_bp)",
- TIV_biomass = "t(Exiobase_TIV_biomass_bp)",
- TIV_const_materials = "t(Exiobase_TIV_const_materials_bp)",
- TIV_ffuels = "t(Exiobase_TIV_ffuels_bp)",
- TIV_ores = "t(Exiobase_TIV_ores_bp)",
- TIV_cropland = "t(Exiobase_TIV_cropland_bp)",
- TIV_forest_land = "t(Exiobase_TIV_forest_land_bp)",
- TIV_pasture_land = "t(Exiobase_TIV_pasture_land_bp)") %>%
+ TIV_energy = "t(Exiobase_TIV_energy_use_bp)") %>%
mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"))
year = as.character(rep(year_current,nrow(TIV_with_labels)))
@@ -4740,14 +4134,7 @@ for (i in years_exb_pxp){
Exiobase_TIV_country_breakdown_sf6_bp %>% select(-country),
Exiobase_TIV_country_breakdown_hfc_bp %>% select(-country),
Exiobase_TIV_country_breakdown_pfc_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_energy_use_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_biomass_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_const_materials_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ffuels_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ores_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_cropland_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_forest_land_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_pasture_land_bp %>% select(-country)) %>%
+ Exiobase_TIV_country_breakdown_energy_use_bp %>% select(-country)) %>%
mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"),
country = dplyr::recode(country, "GR" = "EL", "GB" = "UK"))
@@ -4777,14 +4164,7 @@ for (i in years_exb_pxp){
TIV_SF6_domestic = as.numeric(TIV_SF6_domestic),
TIV_HFC_domestic = as.numeric(TIV_HFC_domestic),
TIV_PFC_domestic = as.numeric(TIV_PFC_domestic),
- TIV_energy_domestic = as.numeric(TIV_energy_domestic),
- TIV_biomass_domestic = as.numeric(TIV_biomass_domestic),
- TIV_const_materials_domestic = as.numeric(TIV_const_materials_domestic),
- TIV_ffuels_domestic = as.numeric(TIV_ffuels_domestic),
- TIV_ores_domestic = as.numeric(TIV_ores_domestic),
- TIV_cropland_domestic = as.numeric(TIV_cropland_domestic),
- TIV_forest_land_domestic = as.numeric(TIV_forest_land_domestic),
- TIV_pasture_land_domestic = as.numeric(TIV_pasture_land_domestic))
+ TIV_energy_domestic = as.numeric(TIV_energy_domestic))
domestic_TIVs = rbind(domestic_TIVs, look_domestic)
@@ -4813,14 +4193,7 @@ for (i in years_exb_pxp){
Exiobase_TIV_europe_breakdown_sf6_bp,
Exiobase_TIV_europe_breakdown_hfc_bp,
Exiobase_TIV_europe_breakdown_pfc_bp,
- Exiobase_TIV_europe_breakdown_energy_use_bp,
- Exiobase_TIV_europe_breakdown_biomass_bp,
- Exiobase_TIV_europe_breakdown_const_materials_bp,
- Exiobase_TIV_europe_breakdown_ffuels_bp,
- Exiobase_TIV_europe_breakdown_ores_bp,
- Exiobase_TIV_europe_breakdown_cropland_bp,
- Exiobase_TIV_europe_breakdown_forest_land_bp,
- Exiobase_TIV_europe_breakdown_pasture_land_bp) %>%
+ Exiobase_TIV_europe_breakdown_energy_use_bp) %>%
mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"))
year_europe = as.character(rep(year_current,nrow(europe_TIV_with_labels)))
@@ -4849,14 +4222,7 @@ for (i in years_exb_pxp){
TIV_SF6_europe = as.numeric(TIV_SF6_europe),
TIV_HFC_europe = as.numeric(TIV_HFC_europe),
TIV_PFC_europe = as.numeric(TIV_PFC_europe),
- TIV_energy_europe = as.numeric(TIV_energy_europe),
- TIV_biomass_europe = as.numeric(TIV_biomass_europe),
- TIV_const_materials_europe = as.numeric(TIV_const_materials_europe),
- TIV_ffuels_europe = as.numeric(TIV_ffuels_europe),
- TIV_ores_europe = as.numeric(TIV_ores_europe),
- TIV_cropland_europe = as.numeric(TIV_cropland_europe),
- TIV_forest_land_europe = as.numeric(TIV_forest_land_europe),
- TIV_pasture_land_europe = as.numeric(TIV_pasture_land_europe))
+ TIV_energy_europe = as.numeric(TIV_energy_europe))
europe_TIVs = rbind(europe_TIVs, look_europe)
@@ -4914,20 +4280,6 @@ for (i in years_exb_pxp){
national_energy_footprints = Exiobase_FD * t(Exiobase_TIV_energy_use_bp)
- national_biomass_footprints = Exiobase_FD * t(Exiobase_TIV_biomass_bp)
-
- national_const_materials_footprints = Exiobase_FD * t(Exiobase_TIV_const_materials_bp)
-
- national_ffuels_footprints = Exiobase_FD * t(Exiobase_TIV_ffuels_bp)
-
- national_ores_footprints = Exiobase_FD * t(Exiobase_TIV_ores_bp)
-
- national_cropland_footprints = Exiobase_FD * t(Exiobase_TIV_cropland_bp)
-
- national_forest_land_footprints = Exiobase_FD * t(Exiobase_TIV_forest_land_bp)
-
- national_pasture_land_footprints = Exiobase_FD * t(Exiobase_TIV_pasture_land_bp)
-
# together
@@ -4954,14 +4306,7 @@ for (i in years_exb_pxp){
rowSums(t(national_SF6_footprints)),
rowSums(t(national_HFC_footprints)),
rowSums(t(national_PFC_footprints)),
- rowSums(t(national_energy_footprints)),
- rowSums(t(national_biomass_footprints)),
- rowSums(t(national_const_materials_footprints)),
- rowSums(t(national_ffuels_footprints)),
- rowSums(t(national_ores_footprints)),
- rowSums(t(national_cropland_footprints)),
- rowSums(t(national_forest_land_footprints)),
- rowSums(t(national_pasture_land_footprints))) %>%
+ rowSums(t(national_energy_footprints))) %>%
mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"))
year_national_fp = as.character(rep(year_current,nrow(national_footprints_w_labels)))
@@ -4997,13 +4342,6 @@ for (i in years_exb_pxp){
direct_FD_hfc = direct_FD_extensions[425,]
direct_FD_pfc = direct_FD_extensions[426,]
direct_FD_energy = direct_FD_extensions[470,]
- direct_FD_biomass = colSums(direct_FD_extensions[c(471:499,501,522:688),])
- direct_FD_const_materials = colSums(direct_FD_extensions[514:521,])
- direct_FD_ffuels = direct_FD_extensions[500,]
- direct_FD_ores = colSums(direct_FD_extensions[502:513,])
- direct_FD_cropland = colSums(direct_FD_extensions[447:459,])
- direct_FD_forest_land = colSums(direct_FD_extensions[c(460,466),])
- direct_FD_pasture_land = colSums(direct_FD_extensions[462:464,])
direct_FD_fp = data.frame(direct_FD_co2,
@@ -5028,14 +4366,7 @@ for (i in years_exb_pxp){
direct_FD_sf6,
direct_FD_hfc,
direct_FD_pfc,
- direct_FD_energy,
- direct_FD_biomass,
- direct_FD_const_materials,
- direct_FD_ffuels,
- direct_FD_ores,
- direct_FD_cropland,
- direct_FD_forest_land,
- direct_FD_pasture_land)
+ direct_FD_energy)
look_national_fp = as.data.frame(cbind(year_national_fp,
national_footprints_w_labels,
@@ -5065,14 +4396,7 @@ for (i in years_exb_pxp){
sf6 = "rowSums(t(national_SF6_footprints))",
hfc = "rowSums(t(national_HFC_footprints))",
pfc = "rowSums(t(national_PFC_footprints))",
- energy = "rowSums(t(national_energy_footprints))",
- biomass = "rowSums(t(national_biomass_footprints))",
- const_materials = "rowSums(t(national_const_materials_footprints))",
- ffuels = "rowSums(t(national_ffuels_footprints))",
- ores = "rowSums(t(national_ores_footprints))",
- cropland = "rowSums(t(national_cropland_footprints))",
- forest_land = "rowSums(t(national_forest_land_footprints))",
- pasture_land = "rowSums(t(national_pasture_land_footprints))") %>%
+ energy = "rowSums(t(national_energy_footprints))") %>%
select(year,
geo,
fd_category,
@@ -5121,21 +4445,7 @@ for (i in years_exb_pxp){
pfc,
direct_FD_pfc,
energy,
- direct_FD_energy,
- biomass,
- direct_FD_biomass,
- const_materials,
- direct_FD_const_materials,
- ffuels,
- direct_FD_ffuels,
- ores,
- direct_FD_ores,
- cropland,
- direct_FD_cropland,
- forest_land,
- direct_FD_forest_land,
- pasture_land,
- direct_FD_pasture_land)
+ direct_FD_energy)
national_fp = rbind(national_fp, look_national_fp)
@@ -5205,20 +4515,6 @@ for (i in years_exb_pxp){
energy_carrier_use = satellite[470,]
- biomass = as.data.frame(colSums(satellite[c(471:499,501,522:688),]))
-
- ores = as.data.frame(colSums(satellite[502:513,]))
-
- const_materials = as.data.frame(colSums(satellite[514:521,]))
-
- ffuels = satellite[500,]
-
- cropland = as.data.frame(colSums(satellite[447:459,]))
-
- pasture_land = as.data.frame(colSums(satellite[462:464,]))
-
- forest_land = as.data.frame(colSums(satellite[c(460,466),]))
-
territorial = data.frame(t(CO2_combustion_air),
t(CO2_noncombustion_cement_air),
@@ -5242,14 +4538,7 @@ for (i in years_exb_pxp){
t(SF6_air),
t(HFC_air),
t(PFC_air),
- t(energy_carrier_use),
- biomass,
- ores,
- const_materials,
- t(ffuels),
- cropland,
- pasture_land,
- forest_land) %>%
+ t(energy_carrier_use)) %>%
rename(CO2 = 1,
CO2_noncombustion_cement = 2,
CO2_noncombustion_lime = 3,
@@ -5270,11 +4559,7 @@ for (i in years_exb_pxp){
N2O = 18,
N2O_agriculture = 19,
SF6 = 20,
- HFC = 21, PFC = 22, energy = 23,
- biomass = 24, ores = 25,
- const_materials = 26, ffuels = 27,
- cropland = 28, pasture_land = 29,
- forest_land = 30)
+ HFC = 21, PFC = 22, energy = 23)
year_territorial = as.character(rep(year_current,nrow(territorial)))
@@ -5456,14 +4741,7 @@ direct_FD_fp_long = national_fp %>%
direct_FD_sf6,
direct_FD_hfc,
direct_FD_pfc,
- direct_FD_energy,
- direct_FD_biomass,
- direct_FD_const_materials,
- direct_FD_ffuels,
- direct_FD_ores,
- direct_FD_cropland,
- direct_FD_forest_land,
- direct_FD_pasture_land) %>%
+ direct_FD_energy) %>%
slice(rep(1:n(), each = 3))
sector = rep(c("HH_HEAT","HH_TRA","HH_OTH"), nrow(direct_FD_fp_long)/3)
@@ -5767,49 +5045,7 @@ results = fd_exiobase %>%
q3_energy_europe = QUINTILE3*(TIV_energy_europe - TIV_energy_domestic),
q4_energy_europe = QUINTILE4*(TIV_energy_europe - TIV_energy_domestic),
q5_energy_europe = QUINTILE5*(TIV_energy_europe - TIV_energy_domestic),
- energy_total_europe = q1_energy_europe+q2_energy_europe+q3_energy_europe+q4_energy_europe+q5_energy_europe,
- TIV_materials = TIV_biomass+TIV_const_materials+TIV_ffuels+TIV_ores,
- q1_materials = QUINTILE1*TIV_materials,
- q2_materials = QUINTILE2*TIV_materials,
- q3_materials = QUINTILE3*TIV_materials,
- q4_materials = QUINTILE4*TIV_materials,
- q5_materials = QUINTILE5*TIV_materials,
- materials_total = q1_materials+q2_materials+q3_materials+q4_materials+q5_materials,
- TIV_materials_domestic = TIV_biomass_domestic+TIV_const_materials_domestic+TIV_ffuels_domestic+TIV_ores_domestic,
- q1_materials_domestic = QUINTILE1*TIV_materials_domestic,
- q2_materials_domestic = QUINTILE2*TIV_materials_domestic,
- q3_materials_domestic = QUINTILE3*TIV_materials_domestic,
- q4_materials_domestic = QUINTILE4*TIV_materials_domestic,
- q5_materials_domestic = QUINTILE5*TIV_materials_domestic,
- materials_total_domestic = q1_materials_domestic+q2_materials_domestic+q3_materials_domestic+q4_materials_domestic+q5_materials_domestic,
- TIV_materials_europe = TIV_biomass_europe+TIV_const_materials_europe+TIV_ffuels_europe+TIV_ores_europe,
- q1_materials_europe = QUINTILE1*(TIV_materials_europe - TIV_materials_domestic),
- q2_materials_europe = QUINTILE2*(TIV_materials_europe - TIV_materials_domestic),
- q3_materials_europe = QUINTILE3*(TIV_materials_europe - TIV_materials_domestic),
- q4_materials_europe = QUINTILE4*(TIV_materials_europe - TIV_materials_domestic),
- q5_materials_europe = QUINTILE5*(TIV_materials_europe - TIV_materials_domestic),
- materials_total_europe = q1_materials_europe+q2_materials_europe+q3_materials_europe+q4_materials_europe+q5_materials_europe,
- TIV_land_use = TIV_cropland+TIV_forest_land+TIV_pasture_land,
- q1_land_use = QUINTILE1*TIV_land_use,
- q2_land_use = QUINTILE2*TIV_land_use,
- q3_land_use = QUINTILE3*TIV_land_use,
- q4_land_use = QUINTILE4*TIV_land_use,
- q5_land_use = QUINTILE5*TIV_land_use,
- land_use_total =q1_land_use+q2_land_use+q3_land_use+q4_land_use+q5_land_use,
- TIV_land_use_domestic = TIV_cropland_domestic+TIV_forest_land_domestic+TIV_pasture_land_domestic,
- q1_land_use_domestic = QUINTILE1*TIV_land_use_domestic,
- q2_land_use_domestic = QUINTILE2*TIV_land_use_domestic,
- q3_land_use_domestic = QUINTILE3*TIV_land_use_domestic,
- q4_land_use_domestic = QUINTILE4*TIV_land_use_domestic,
- q5_land_use_domestic = QUINTILE5*TIV_land_use_domestic,
- land_use_total_domestic =q1_land_use_domestic+q2_land_use_domestic+q3_land_use_domestic+q4_land_use_domestic+q5_land_use_domestic,
- TIV_land_use_europe = TIV_cropland_europe+TIV_forest_land_europe+TIV_pasture_land_europe,
- q1_land_use_europe = QUINTILE1*(TIV_land_use_europe - TIV_land_use_domestic),
- q2_land_use_europe = QUINTILE2*(TIV_land_use_europe - TIV_land_use_domestic),
- q3_land_use_europe = QUINTILE3*(TIV_land_use_europe - TIV_land_use_domestic),
- q4_land_use_europe = QUINTILE4*(TIV_land_use_europe - TIV_land_use_domestic),
- q5_land_use_europe = QUINTILE5*(TIV_land_use_europe - TIV_land_use_domestic),
- land_use_total_europe =q1_land_use_europe+q2_land_use_europe+q3_land_use_europe+q4_land_use_europe+q5_land_use_europe)
+ energy_total_europe = q1_energy_europe+q2_energy_europe+q3_energy_europe+q4_energy_europe+q5_energy_europe)
results_with_direct_FD_fp = bind_rows(results,direct_FD_fp_wide)
#write.csv(results, paste0(data_dir_income_stratified_footprints, "/results_no_rent_ixi.csv"))
@@ -7116,217 +6352,6 @@ for (i in years_exb_ixi){
ZA) %>%
select(TIV_energy_europe,TIV_energy_not_europe)
- # biomass
-
- Exiobase_TIV_biomass_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_biomass_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_biomass_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_biomass_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_biomass_domestic)
-
- Exiobase_TIV_europe_breakdown_biomass_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_biomass_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_biomass_europe = AT +
- BE + BG + CY + CZ +
- DE + DK + EE +
- ES + FI + FR +
- GB + GR + HR +
- HU + IE + IT +
- LT + LU + LV +
- MT + NL + PL +
- PT + TR + SK +
- SI + SE + RO +
- NO,
- TIV_biomass_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_biomass_europe,TIV_biomass_not_europe)
-
- # construction materials
-
- Exiobase_TIV_const_materials_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_const_materials_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_const_materials_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_const_materials_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_const_materials_domestic)
-
- Exiobase_TIV_europe_breakdown_const_materials_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_const_materials_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_const_materials_europe = AT +
- BE + BG + CY + CZ +
- DE + DK + EE +
- ES + FI + FR +
- GB + GR + HR +
- HU + IE + IT +
- LT + LU + LV +
- MT + NL + PL +
- PT + TR + SK +
- SI + SE + RO +
- NO,
- TIV_const_materials_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_const_materials_europe,TIV_const_materials_not_europe)
-
- # fossil fuels
-
- Exiobase_TIV_ffuels_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ffuels_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ffuels_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ffuels_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_ffuels_domestic)
-
- Exiobase_TIV_europe_breakdown_ffuels_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ffuels_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_ffuels_europe = AT +
- BE + BG + CY + CZ +
- DE + DK + EE +
- ES + FI + FR +
- GB + GR + HR +
- HU + IE + IT +
- LT + LU + LV +
- MT + NL + PL +
- PT + TR + SK +
- SI + SE + RO +
- NO,
- TIV_ffuels_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_ffuels_europe,TIV_ffuels_not_europe)
-
- # ores
-
- Exiobase_TIV_ores_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ores_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ores_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ores_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_ores_domestic)
-
- Exiobase_TIV_europe_breakdown_ores_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ores_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_ores_europe = AT +
- BE + BG + CY + CZ +
- DE + DK + EE +
- ES + FI + FR +
- GB + GR + HR +
- HU + IE + IT +
- LT + LU + LV +
- MT + NL + PL +
- PT + TR + SK +
- SI + SE + RO +
- NO,
- TIV_ores_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_ores_europe,TIV_ores_not_europe)
-
- # cropland
-
- Exiobase_TIV_cropland_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_cropland_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_cropland_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_cropland_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_cropland_domestic)
-
- Exiobase_TIV_europe_breakdown_cropland_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_cropland_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_cropland_europe = AT +
- BE + BG + CY + CZ +
- DE + DK + EE +
- ES + FI + FR +
- GB + GR + HR +
- HU + IE + IT +
- LT + LU + LV +
- MT + NL + PL +
- PT + TR + SK +
- SI + SE + RO +
- NO,
- TIV_cropland_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_cropland_europe,TIV_cropland_not_europe)
-
- # forest land
-
- Exiobase_TIV_forest_land_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_forest_land_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_forest_land_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_forest_land_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_forest_land_domestic)
-
- Exiobase_TIV_europe_breakdown_forest_land_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_forest_land_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_forest_land_europe = AT +
- BE + BG + CY + CZ +
- DE + DK + EE +
- ES + FI + FR +
- GB + GR + HR +
- HU + IE + IT +
- LT + LU + LV +
- MT + NL + PL +
- PT + TR + SK +
- SI + SE + RO +
- NO,
- TIV_forest_land_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_forest_land_europe,TIV_forest_land_not_europe)
-
- # pasture land
-
- Exiobase_TIV_pasture_land_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_pasture_land_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_pasture_land_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_pasture_land_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_pasture_land_domestic)
-
- Exiobase_TIV_europe_breakdown_pasture_land_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_pasture_land_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_pasture_land_europe = AT +
- BE + BG + CY + CZ +
- DE + DK + EE +
- ES + FI + FR +
- GB + GR + HR +
- HU + IE + IT +
- LT + LU + LV +
- MT + NL + PL +
- PT + TR + SK +
- SI + SE + RO +
- NO,
- TIV_pasture_land_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_pasture_land_europe,TIV_pasture_land_not_europe)
-
-
# join with labels
TIV_with_labels = cbind(Exiobase_T_labels,
@@ -7352,14 +6377,7 @@ for (i in years_exb_ixi){
t(Exiobase_TIV_sf6_bp),
t(Exiobase_TIV_hfc_bp),
t(Exiobase_TIV_pfc_bp),
- t(Exiobase_TIV_energy_use_bp),
- t(Exiobase_TIV_biomass_bp),
- t(Exiobase_TIV_const_materials_bp),
- t(Exiobase_TIV_ffuels_bp),
- t(Exiobase_TIV_ores_bp),
- t(Exiobase_TIV_cropland_bp),
- t(Exiobase_TIV_forest_land_bp),
- t(Exiobase_TIV_pasture_land_bp)) %>%
+ t(Exiobase_TIV_energy_use_bp)) %>%
rename(TIV_CO2 = "t(Exiobase_TIV_co2_bp)",
TIV_CO2_noncombustion_cement = "t(Exiobase_TIV_co2_noncombustion_cement_bp)",
TIV_CO2_noncombustion_lime = "t(Exiobase_TIV_co2_noncombustion_lime_bp)",
@@ -7382,14 +6400,7 @@ for (i in years_exb_ixi){
TIV_SF6 = "t(Exiobase_TIV_sf6_bp)",
TIV_HFC = "t(Exiobase_TIV_hfc_bp)",
TIV_PFC = "t(Exiobase_TIV_pfc_bp)",
- TIV_energy = "t(Exiobase_TIV_energy_use_bp)",
- TIV_biomass = "t(Exiobase_TIV_biomass_bp)",
- TIV_const_materials = "t(Exiobase_TIV_const_materials_bp)",
- TIV_ffuels = "t(Exiobase_TIV_ffuels_bp)",
- TIV_ores = "t(Exiobase_TIV_ores_bp)",
- TIV_cropland = "t(Exiobase_TIV_cropland_bp)",
- TIV_forest_land = "t(Exiobase_TIV_forest_land_bp)",
- TIV_pasture_land = "t(Exiobase_TIV_pasture_land_bp)") %>%
+ TIV_energy = "t(Exiobase_TIV_energy_use_bp)") %>%
mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"))
year = as.character(rep(year_current,nrow(TIV_with_labels)))
@@ -7424,14 +6435,7 @@ for (i in years_exb_ixi){
Exiobase_TIV_country_breakdown_sf6_bp %>% select(-country),
Exiobase_TIV_country_breakdown_hfc_bp %>% select(-country),
Exiobase_TIV_country_breakdown_pfc_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_energy_use_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_biomass_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_const_materials_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ffuels_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ores_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_cropland_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_forest_land_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_pasture_land_bp %>% select(-country)) %>%
+ Exiobase_TIV_country_breakdown_energy_use_bp %>% select(-country)) %>%
mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"),
country = dplyr::recode(country, "GR" = "EL", "GB" = "UK"))
@@ -7461,14 +6465,7 @@ for (i in years_exb_ixi){
TIV_SF6_domestic = as.numeric(TIV_SF6_domestic),
TIV_HFC_domestic = as.numeric(TIV_HFC_domestic),
TIV_PFC_domestic = as.numeric(TIV_PFC_domestic),
- TIV_energy_domestic = as.numeric(TIV_energy_domestic),
- TIV_biomass_domestic = as.numeric(TIV_biomass_domestic),
- TIV_const_materials_domestic = as.numeric(TIV_const_materials_domestic),
- TIV_ffuels_domestic = as.numeric(TIV_ffuels_domestic),
- TIV_ores_domestic = as.numeric(TIV_ores_domestic),
- TIV_cropland_domestic = as.numeric(TIV_cropland_domestic),
- TIV_forest_land_domestic = as.numeric(TIV_forest_land_domestic),
- TIV_pasture_land_domestic = as.numeric(TIV_pasture_land_domestic))
+ TIV_energy_domestic = as.numeric(TIV_energy_domestic))
domestic_TIVs = rbind(domestic_TIVs, look_domestic)
@@ -7497,14 +6494,7 @@ for (i in years_exb_ixi){
Exiobase_TIV_europe_breakdown_sf6_bp,
Exiobase_TIV_europe_breakdown_hfc_bp,
Exiobase_TIV_europe_breakdown_pfc_bp,
- Exiobase_TIV_europe_breakdown_energy_use_bp,
- Exiobase_TIV_europe_breakdown_biomass_bp,
- Exiobase_TIV_europe_breakdown_const_materials_bp,
- Exiobase_TIV_europe_breakdown_ffuels_bp,
- Exiobase_TIV_europe_breakdown_ores_bp,
- Exiobase_TIV_europe_breakdown_cropland_bp,
- Exiobase_TIV_europe_breakdown_forest_land_bp,
- Exiobase_TIV_europe_breakdown_pasture_land_bp) %>%
+ Exiobase_TIV_europe_breakdown_energy_use_bp) %>%
mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"))
year_europe = as.character(rep(year_current,nrow(europe_TIV_with_labels)))
@@ -7533,14 +6523,7 @@ for (i in years_exb_ixi){
TIV_SF6_europe = as.numeric(TIV_SF6_europe),
TIV_HFC_europe = as.numeric(TIV_HFC_europe),
TIV_PFC_europe = as.numeric(TIV_PFC_europe),
- TIV_energy_europe = as.numeric(TIV_energy_europe),
- TIV_biomass_europe = as.numeric(TIV_biomass_europe),
- TIV_const_materials_europe = as.numeric(TIV_const_materials_europe),
- TIV_ffuels_europe = as.numeric(TIV_ffuels_europe),
- TIV_ores_europe = as.numeric(TIV_ores_europe),
- TIV_cropland_europe = as.numeric(TIV_cropland_europe),
- TIV_forest_land_europe = as.numeric(TIV_forest_land_europe),
- TIV_pasture_land_europe = as.numeric(TIV_pasture_land_europe))
+ TIV_energy_europe = as.numeric(TIV_energy_europe))
europe_TIVs = rbind(europe_TIVs, look_europe)
@@ -7597,20 +6580,6 @@ for (i in years_exb_ixi){
national_energy_footprints = Exiobase_FD * t(Exiobase_TIV_energy_use_bp)
- national_biomass_footprints = Exiobase_FD * t(Exiobase_TIV_biomass_bp)
-
- national_const_materials_footprints = Exiobase_FD * t(Exiobase_TIV_const_materials_bp)
-
- national_ffuels_footprints = Exiobase_FD * t(Exiobase_TIV_ffuels_bp)
-
- national_ores_footprints = Exiobase_FD * t(Exiobase_TIV_ores_bp)
-
- national_cropland_footprints = Exiobase_FD * t(Exiobase_TIV_cropland_bp)
-
- national_forest_land_footprints = Exiobase_FD * t(Exiobase_TIV_forest_land_bp)
-
- national_pasture_land_footprints = Exiobase_FD * t(Exiobase_TIV_pasture_land_bp)
-
# together
@@ -7637,14 +6606,7 @@ for (i in years_exb_ixi){
rowSums(t(national_SF6_footprints)),
rowSums(t(national_HFC_footprints)),
rowSums(t(national_PFC_footprints)),
- rowSums(t(national_energy_footprints)),
- rowSums(t(national_biomass_footprints)),
- rowSums(t(national_const_materials_footprints)),
- rowSums(t(national_ffuels_footprints)),
- rowSums(t(national_ores_footprints)),
- rowSums(t(national_cropland_footprints)),
- rowSums(t(national_forest_land_footprints)),
- rowSums(t(national_pasture_land_footprints))) %>%
+ rowSums(t(national_energy_footprints))) %>%
mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"))
year_national_fp = as.character(rep(year_current,nrow(national_footprints_w_labels)))
@@ -7679,13 +6641,6 @@ for (i in years_exb_ixi){
direct_FD_hfc = direct_FD_extensions[425,]
direct_FD_pfc = direct_FD_extensions[426,]
direct_FD_energy = direct_FD_extensions[470,]
- direct_FD_biomass = colSums(direct_FD_extensions[c(471:499,501,522:688),])
- direct_FD_const_materials = colSums(direct_FD_extensions[514:521,])
- direct_FD_ffuels = direct_FD_extensions[500,]
- direct_FD_ores = colSums(direct_FD_extensions[502:513,])
- direct_FD_cropland = colSums(direct_FD_extensions[447:459,])
- direct_FD_forest_land = colSums(direct_FD_extensions[c(460,466),])
- direct_FD_pasture_land = colSums(direct_FD_extensions[462:464,])
direct_FD_fp = data.frame(direct_FD_co2,
@@ -7710,14 +6665,7 @@ for (i in years_exb_ixi){
direct_FD_sf6,
direct_FD_hfc,
direct_FD_pfc,
- direct_FD_energy,
- direct_FD_biomass,
- direct_FD_const_materials,
- direct_FD_ffuels,
- direct_FD_ores,
- direct_FD_cropland,
- direct_FD_forest_land,
- direct_FD_pasture_land)
+ direct_FD_energy)
look_national_fp = as.data.frame(cbind(year_national_fp,
national_footprints_w_labels,
@@ -7747,14 +6695,7 @@ for (i in years_exb_ixi){
sf6 = "rowSums(t(national_SF6_footprints))",
hfc = "rowSums(t(national_HFC_footprints))",
pfc = "rowSums(t(national_PFC_footprints))",
- energy = "rowSums(t(national_energy_footprints))",
- biomass = "rowSums(t(national_biomass_footprints))",
- const_materials = "rowSums(t(national_const_materials_footprints))",
- ffuels = "rowSums(t(national_ffuels_footprints))",
- ores = "rowSums(t(national_ores_footprints))",
- cropland = "rowSums(t(national_cropland_footprints))",
- forest_land = "rowSums(t(national_forest_land_footprints))",
- pasture_land = "rowSums(t(national_pasture_land_footprints))") %>%
+ energy = "rowSums(t(national_energy_footprints))") %>%
select(year,
geo,
fd_category,
@@ -7803,21 +6744,7 @@ for (i in years_exb_ixi){
pfc,
direct_FD_pfc,
energy,
- direct_FD_energy,
- biomass,
- direct_FD_biomass,
- const_materials,
- direct_FD_const_materials,
- ffuels,
- direct_FD_ffuels,
- ores,
- direct_FD_ores,
- cropland,
- direct_FD_cropland,
- forest_land,
- direct_FD_forest_land,
- pasture_land,
- direct_FD_pasture_land)
+ direct_FD_energy)
national_fp = rbind(national_fp, look_national_fp)
@@ -7877,8 +6804,7 @@ weighted_mean_TIV_with_labels = cbind(TIVs,Eurostat_countries_hh_fd_mean_TIV) %>
-TIV_CH4_noncombustion_subbituminouscoal,-TIV_CH4_noncombustion_oilrefinery,
-TIV_CH4_agriculture,-TIV_CH4_waste,
-TIV_N2O,-TIV_N2O_agriculture,-TIV_SF6,-TIV_HFC,-TIV_PFC,
- -TIV_energy,-TIV_biomass,-TIV_const_materials,-TIV_ffuels,
- -TIV_ores,-TIV_cropland,-TIV_forest_land,-TIV_pasture_land) %>%
+ -TIV_energy) %>%
group_by(geo,year,coicop) %>%
mutate(fd = as.numeric(fd)) %>%
mutate(TIV_CO2_weighted_average = sum((fd/sum(fd))*TIV_CO2),
@@ -7903,14 +6829,7 @@ weighted_mean_TIV_with_labels = cbind(TIVs,Eurostat_countries_hh_fd_mean_TIV) %>
TIV_SF6_weighted_average = sum((fd/sum(fd))*TIV_SF6),
TIV_HFC_weighted_average = sum((fd/sum(fd))*TIV_HFC),
TIV_PFC_weighted_average = sum((fd/sum(fd))*TIV_PFC),
- TIV_energy_weighted_average = sum((fd/sum(fd))*TIV_energy),
- TIV_biomass_weighted_average = sum((fd/sum(fd))*TIV_biomass),
- TIV_const_materials_weighted_average = sum((fd/sum(fd))*TIV_const_materials),
- TIV_ffuels_weighted_average = sum((fd/sum(fd))*TIV_ffuels),
- TIV_ores_weighted_average = sum((fd/sum(fd))*TIV_ores),
- TIV_cropland_weighted_average = sum((fd/sum(fd))*TIV_cropland),
- TIV_forest_land_weighted_average = sum((fd/sum(fd))*TIV_forest_land),
- TIV_pasture_land_weighted_average = sum((fd/sum(fd))*TIV_pasture_land)) %>%
+ TIV_energy_weighted_average = sum((fd/sum(fd))*TIV_energy)) %>%
select(year,geo,coicop,TIV_CO2_weighted_average,
TIV_CO2_noncombustion_cement_weighted_average,
TIV_CO2_noncombustion_lime_weighted_average,
@@ -7933,14 +6852,7 @@ weighted_mean_TIV_with_labels = cbind(TIVs,Eurostat_countries_hh_fd_mean_TIV) %>
TIV_SF6_weighted_average,
TIV_HFC_weighted_average,
TIV_PFC_weighted_average,
- TIV_energy_weighted_average,
- TIV_biomass_weighted_average,
- TIV_const_materials_weighted_average,
- TIV_ffuels_weighted_average,
- TIV_ores_weighted_average,
- TIV_cropland_weighted_average,
- TIV_forest_land_weighted_average,
- TIV_pasture_land_weighted_average) %>%
+ TIV_energy_weighted_average) %>%
unique()
weighted_mean_europe_TIV_with_labels = cbind(europe_TIVs, Eurostat_countries_hh_fd_mean_TIV) %>%
@@ -7966,10 +6878,7 @@ weighted_mean_europe_TIV_with_labels = cbind(europe_TIVs, Eurostat_countries_hh_
-TIV_N2O_agriculture_europe,-TIV_N2O_agriculture_not_europe,
-TIV_SF6_europe,-TIV_SF6_not_europe,
-TIV_HFC_europe,-TIV_HFC_not_europe,-TIV_PFC_europe,-TIV_PFC_not_europe,
- -TIV_energy_europe,-TIV_energy_not_europe,-TIV_biomass_europe,-TIV_biomass_not_europe,
- -TIV_const_materials_europe,-TIV_const_materials_not_europe,-TIV_ffuels_europe,-TIV_ffuels_not_europe,
- -TIV_ores_europe,-TIV_ores_not_europe,-TIV_cropland_europe,-TIV_cropland_not_europe,
- -TIV_forest_land_europe,-TIV_forest_land_not_europe,-TIV_pasture_land_europe,-TIV_pasture_land_not_europe) %>%
+ -TIV_energy_europe,-TIV_energy_not_europe) %>%
group_by(geo,year,coicop) %>%
mutate(fd = as.numeric(fd)) %>%
mutate(TIV_CO2_europe_weighted_average = sum((fd/sum(fd))*TIV_CO2_europe),
@@ -7994,14 +6903,7 @@ weighted_mean_europe_TIV_with_labels = cbind(europe_TIVs, Eurostat_countries_hh_
TIV_SF6_europe_weighted_average = sum((fd/sum(fd))*TIV_SF6_europe),
TIV_HFC_europe_weighted_average = sum((fd/sum(fd))*TIV_HFC_europe),
TIV_PFC_europe_weighted_average = sum((fd/sum(fd))*TIV_PFC_europe),
- TIV_energy_europe_weighted_average = sum((fd/sum(fd))*TIV_energy_europe),
- TIV_biomass_europe_weighted_average = sum((fd/sum(fd))*TIV_biomass_europe),
- TIV_const_materials_europe_weighted_average = sum((fd/sum(fd))*TIV_const_materials_europe),
- TIV_ffuels_europe_weighted_average = sum((fd/sum(fd))*TIV_ffuels_europe),
- TIV_ores_europe_weighted_average = sum((fd/sum(fd))*TIV_ores_europe),
- TIV_cropland_europe_weighted_average = sum((fd/sum(fd))*TIV_cropland_europe),
- TIV_forest_land_europe_weighted_average = sum((fd/sum(fd))*TIV_forest_land_europe),
- TIV_pasture_land_europe_weighted_average = sum((fd/sum(fd))*TIV_pasture_land_europe)) %>%
+ TIV_energy_europe_weighted_average = sum((fd/sum(fd))*TIV_energy_europe)) %>%
select(year,geo,coicop,TIV_CO2_europe_weighted_average,
TIV_CO2_noncombustion_cement_europe_weighted_average,
TIV_CO2_noncombustion_lime_europe_weighted_average,
@@ -8024,14 +6926,7 @@ weighted_mean_europe_TIV_with_labels = cbind(europe_TIVs, Eurostat_countries_hh_
TIV_SF6_europe_weighted_average,
TIV_HFC_europe_weighted_average,
TIV_PFC_europe_weighted_average,
- TIV_energy_europe_weighted_average,
- TIV_biomass_europe_weighted_average,
- TIV_const_materials_europe_weighted_average,
- TIV_ffuels_europe_weighted_average,
- TIV_ores_europe_weighted_average,
- TIV_cropland_europe_weighted_average,
- TIV_forest_land_europe_weighted_average,
- TIV_pasture_land_europe_weighted_average) %>%
+ TIV_energy_europe_weighted_average) %>%
unique()
domestic_TIVs_Eurostat = domestic_TIVs %>%
@@ -8124,14 +7019,7 @@ weighted_mean_domestic_TIV_with_labels = cbind(domestic_TIVs_Eurostat,Eurostat_c
TIV_SF6_domestic_weighted_average = sum((fd/sum(fd))*TIV_SF6_domestic),
TIV_HFC_domestic_weighted_average = sum((fd/sum(fd))*TIV_HFC_domestic),
TIV_PFC_domestic_weighted_average = sum((fd/sum(fd))*TIV_PFC_domestic),
- TIV_energy_domestic_weighted_average = sum((fd/sum(fd))*TIV_energy_domestic),
- TIV_biomass_domestic_weighted_average = sum((fd/sum(fd))*TIV_biomass_domestic),
- TIV_const_materials_domestic_weighted_average = sum((fd/sum(fd))*TIV_const_materials_domestic),
- TIV_ffuels_domestic_weighted_average = sum((fd/sum(fd))*TIV_ffuels_domestic),
- TIV_ores_domestic_weighted_average = sum((fd/sum(fd))*TIV_ores_domestic),
- TIV_cropland_domestic_weighted_average = sum((fd/sum(fd))*TIV_cropland_domestic),
- TIV_forest_land_domestic_weighted_average = sum((fd/sum(fd))*TIV_forest_land_domestic),
- TIV_pasture_land_domestic_weighted_average = sum((fd/sum(fd))*TIV_pasture_land_domestic)) %>%
+ TIV_energy_domestic_weighted_average = sum((fd/sum(fd))*TIV_energy_domestic)) %>%
select(year,geo,coicop,TIV_CO2_domestic_weighted_average,
TIV_CO2_noncombustion_cement_domestic_weighted_average,
TIV_CO2_noncombustion_lime_domestic_weighted_average,
@@ -8154,14 +7042,7 @@ weighted_mean_domestic_TIV_with_labels = cbind(domestic_TIVs_Eurostat,Eurostat_c
TIV_SF6_domestic_weighted_average,
TIV_HFC_domestic_weighted_average,
TIV_PFC_domestic_weighted_average,
- TIV_energy_domestic_weighted_average,
- TIV_biomass_domestic_weighted_average,
- TIV_const_materials_domestic_weighted_average,
- TIV_ffuels_domestic_weighted_average,
- TIV_ores_domestic_weighted_average,
- TIV_cropland_domestic_weighted_average,
- TIV_forest_land_domestic_weighted_average,
- TIV_pasture_land_domestic_weighted_average) %>%
+ TIV_energy_domestic_weighted_average) %>%
unique()
@@ -8414,14 +7295,7 @@ direct_FD_fp_long = national_fp %>%
direct_FD_sf6,
direct_FD_hfc,
direct_FD_pfc,
- direct_FD_energy,
- direct_FD_biomass,
- direct_FD_const_materials,
- direct_FD_ffuels,
- direct_FD_ores,
- direct_FD_cropland,
- direct_FD_forest_land,
- direct_FD_pasture_land) %>%
+ direct_FD_energy) %>%
slice(rep(1:n(), each = 3))
sector = rep(c("HH_HEAT","HH_TRA","HH_OTH"), nrow(direct_FD_fp_long)/3)