diff --git a/analysis/preprocessing/full_code_europe.inequality.Rmd b/analysis/preprocessing/full_code_europe.inequality.Rmd
index f0793e7f3aaac56fa952a287d861bda8e32c6f51..8859aef11f01f44a5588fb14807dcea9dbf97f0f 100644
--- a/analysis/preprocessing/full_code_europe.inequality.Rmd
+++ b/analysis/preprocessing/full_code_europe.inequality.Rmd
@@ -18,28 +18,31 @@ This file contains all code to estimate the European income-stratified footprint
We first load required R packages.
-```{r setup, warning=F, message=F}
-
-# Libraries:
-library(tidyverse)
-library(ggpubr)
-library(knitr)
-library(kableExtra)
-library(readxl)
-library(latex2exp)
-library(stargazer)
-library(plm)
-library(lmtest)
-library(tseries)
-library(RColorBrewer)
-library(rworldmap)
-
-require(tidyverse)
-require(readr)
-require(janitor)
+```{r setup, echo = FALSE, include = FALSE, message = FALSE}
+knitr::opts_chunk$set(
+ collapse = TRUE,
+ warning = FALSE,
+ message = FALSE,
+ echo = FALSE,
+ comment = "#>"
+)
+
+if (!require("pacman")) install.packages("pacman")
+pacman::p_load(tidyverse,
+ janitor,
+ here,
+ wbstats,
+ ISOcodes,
+ viridis,
+ hrbrthemes,
+ wesanderson,
+ glue,
+ ggridges,
+ patchwork)
```
+
# Exiobase
```{r exiobase, eval = FALSE}
diff --git a/analysis/preprocessing/full_code_europe.inequality.html b/analysis/preprocessing/full_code_europe.inequality.html
index 1de3567d71a6cc11bc3309dff4beb74423417f61..45f9cead9cbac6a5c585931bce843a529b6ffd5a 100644
--- a/analysis/preprocessing/full_code_europe.inequality.html
+++ b/analysis/preprocessing/full_code_europe.inequality.html
@@ -1669,9695 +1669,12 @@ require(janitor)</code></pre>
</div>
<div id="exiobase" class="section level1">
<h1>Exiobase</h1>
-<pre class="r"><code># EXIOBASE_cluster_ixi_version
-
-# data directories (on cluster)
-data_dir_exiobase = paste("/",file.path("data","metab","Exiobase", fsep=.Platform$file.sep),sep="")
-
-years_exiobase_ixi = c(2005,2010,2015)
-
-for (i in years_exiobase_ixi){
-
-year_current = i
-
-A = read.delim(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/A.txt"),header = F)
-
-write.csv(A, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/A.csv"))
-
-A = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/A.csv",sep = ""),row.names=NULL,as.is=TRUE)[4:7990,4:7990]
-A[is.na(A)]=0
-A = mapply(A, FUN = as.numeric)
-A = matrix(data = A, ncol = 7987, nrow = 7987)
-
-L = solve(diag(dim(A)[1])-A) # this solves the Leontief inverse initially
-L[is.na(L)]=0
-
-
-# final demand
-
-FD = read.delim(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/Y.txt"),header = F)
-
-write.csv(FD, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/Y.csv"))
-
-
-Exiobase_T_labels_ixi = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/Y.csv"))[4:7990,1:3]
-
-write.csv(Exiobase_T_labels_ixi, paste0(data_dir_exiobase, "/Exiobase_T_labels_ixi.csv"))
-
-Exiobase_FD_labels_ixi = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/Y.csv"))[1:3,4:346]
-
-write.csv(Exiobase_FD_labels_ixi, paste0(data_dir_exiobase, "/Exiobase_FD_labels_ixi.csv"))
-
-
-FD = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/Y.csv",sep=""),row.names=NULL,as.is=TRUE)[4:7990,4:346]
-FD[is.na(FD)]=0
-FD = mapply(FD, FUN = as.numeric)
-FD = matrix(data=FD,ncol=343,nrow=7987)
-
-write.csv(FD, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/FD_",year_current,"_ixi.csv"))
-
-
-# total output
-total_output = L %*% rowSums(FD)
-
-write.csv(total_output, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/total_output_",year_current,"_ixi.csv"))
-
-
-# direct environmental vectors
-satellite = read.delim(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/satellite/F.txt"),header = F)
-
-write.csv(satellite, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/satellite/F.csv"))
-
-
-satellite = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/satellite/F.csv",sep=""),row.names=NULL,as.is=TRUE)[3:1115,3:7989]
-satellite[is.na(satellite)]=0
-satellite = mapply(satellite, FUN = as.numeric)
-satellite = matrix(data=satellite,ncol=7987,nrow=1113)
-
-
-write.csv(satellite, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/satellite/satellite_",year_current,"_ixi.csv"))
-
-
-# direct environmental vectors on final demand
-
-satellite_FD = read.delim(paste0(data_dir_exiobase, "/IOT_", year_current, "_ixi/satellite/F_hh.txt"),header = F)
-
-write.csv(satellite_FD, paste0(data_dir_exiobase, "/IOT_", year_current, "_ixi/satellite/F_hh.csv"))
-
-
-# CO2 combustion air
-CO2_combustion_air = satellite[24,]
-#write.csv(CO2_combustion_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/satellite/co2_combustion_air_",year_current,"_ixi.csv"))
-DIV_co2_combustion_air = CO2_combustion_air/total_output
-DIV_co2_combustion_air[is.na(DIV_co2_combustion_air)]=0
-DIV_co2_combustion_air[DIV_co2_combustion_air == Inf]<-0
-#write.csv(DIV_co2_combustion_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/DIV_co2_combustion_air_",year_current,"_ixi.csv"))
-TIV_co2_combustion_air = as.vector(DIV_co2_combustion_air) %*% L
-
-write.csv(TIV_co2_combustion_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_co2_combustion_air_",year_current,"_ixi.csv"))
-
-TIV_breakdown_co2_combustion_air = as.vector(DIV_co2_combustion_air) * L
-TIV_breakdown_co2_combustion_air_w_labels = cbind(Exiobase_T_labels_ixi, TIV_breakdown_co2_combustion_air)
-TIV_country_breakdown_co2_combustion_air_w_labels = t(TIV_breakdown_co2_combustion_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_co2_combustion_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_combustion_air_",year_current,"_ixi.csv"))
-
-
-# CO2 non-combustion air
-## cement
-CO2_noncombustion_cement_air = satellite[93,]
-DIV_co2_noncombustion_cement_air = CO2_noncombustion_cement_air/total_output
-DIV_co2_noncombustion_cement_air[is.na(DIV_co2_noncombustion_cement_air)]=0
-DIV_co2_noncombustion_cement_air[DIV_co2_noncombustion_cement_air == Inf]<-0
-TIV_co2_noncombustion_cement_air = as.vector(DIV_co2_noncombustion_cement_air) %*% L
-
-write.csv(TIV_co2_noncombustion_cement_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_co2_noncombustion_cement_air_",year_current,"_ixi.csv"))
-
-TIV_breakdown_co2_noncombustion_cement_air = as.vector(DIV_co2_noncombustion_cement_air) * L
-TIV_breakdown_co2_noncombustion_cement_air_w_labels = cbind(Exiobase_T_labels_ixi, TIV_breakdown_co2_noncombustion_cement_air)
-TIV_country_breakdown_co2_noncombustion_cement_air_w_labels = t(TIV_breakdown_co2_noncombustion_cement_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_co2_noncombustion_cement_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_noncombustion_cement_air_",year_current,"_ixi.csv"))
-
-## lime
-CO2_noncombustion_lime_air = satellite[94,]
-DIV_co2_noncombustion_lime_air = CO2_noncombustion_lime_air/total_output
-DIV_co2_noncombustion_lime_air[is.na(DIV_co2_noncombustion_lime_air)]=0
-DIV_co2_noncombustion_lime_air[DIV_co2_noncombustion_lime_air == Inf]<-0
-TIV_co2_noncombustion_lime_air = as.vector(DIV_co2_noncombustion_lime_air) %*% L
-
-write.csv(TIV_co2_noncombustion_lime_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_co2_noncombustion_lime_air_",year_current,"_ixi.csv"))
-
-TIV_breakdown_co2_noncombustion_lime_air = as.vector(DIV_co2_noncombustion_lime_air) * L
-TIV_breakdown_co2_noncombustion_lime_air_w_labels = cbind(Exiobase_T_labels_ixi, TIV_breakdown_co2_noncombustion_lime_air)
-TIV_country_breakdown_co2_noncombustion_lime_air_w_labels = t(TIV_breakdown_co2_noncombustion_lime_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_co2_noncombustion_lime_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_noncombustion_lime_air_",year_current,"_ixi.csv"))
-
-
-# CO2 agriculture peat decay air
-CO2_agriculture_peatdecay_air = satellite[428,]
-DIV_co2_agriculture_peatdecay_air = CO2_agriculture_peatdecay_air/total_output
-DIV_co2_agriculture_peatdecay_air[is.na(DIV_co2_agriculture_peatdecay_air)]=0
-DIV_co2_agriculture_peatdecay_air[DIV_co2_agriculture_peatdecay_air == Inf]<-0
-TIV_co2_agriculture_peatdecay_air = as.vector(DIV_co2_agriculture_peatdecay_air) %*% L
-
-write.csv(TIV_co2_agriculture_peatdecay_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_co2_agriculture_peatdecay_air_",year_current,"_ixi.csv"))
-
-TIV_breakdown_co2_agriculture_peatdecay_air = as.vector(DIV_co2_agriculture_peatdecay_air) * L
-TIV_breakdown_co2_agriculture_peatdecay_air_w_labels = cbind(Exiobase_T_labels_ixi, TIV_breakdown_co2_agriculture_peatdecay_air)
-TIV_country_breakdown_co2_agriculture_peatdecay_air_w_labels = t(TIV_breakdown_co2_agriculture_peatdecay_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_co2_agriculture_peatdecay_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_agriculture_peatdecay_air_",year_current,"_ixi.csv"))
-
-# CO2 waste air
-## biogenic
-CO2_waste_biogenic_air = satellite[438,]
-DIV_co2_waste_biogenic_air = CO2_waste_biogenic_air/total_output
-DIV_co2_waste_biogenic_air[is.na(DIV_co2_waste_biogenic_air)]=0
-DIV_co2_waste_biogenic_air[DIV_co2_waste_biogenic_air == Inf]<-0
-TIV_co2_biogenic_air = as.vector(DIV_co2_waste_biogenic_air) %*% L
-
-write.csv(TIV_co2_biogenic_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_co2_biogenic_air_",year_current,"_ixi.csv"))
-
-TIV_breakdown_co2_biogenic_air = as.vector(DIV_co2_waste_biogenic_air) * L
-TIV_breakdown_co2_biogenic_air_w_labels = cbind(Exiobase_T_labels_ixi, TIV_breakdown_co2_biogenic_air)
-TIV_country_breakdown_co2_biogenic_air_w_labels = t(TIV_breakdown_co2_biogenic_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_co2_biogenic_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_biogenic_air_",year_current,"_ixi.csv"))
-
-## fossil
-CO2_waste_fossil_air = satellite[439,]
-DIV_co2_waste_fossil_air = CO2_waste_fossil_air/total_output
-DIV_co2_waste_fossil_air[is.na(DIV_co2_waste_fossil_air)]=0
-DIV_co2_waste_fossil_air[DIV_co2_waste_fossil_air == Inf]<-0
-TIV_co2_waste_fossil_air = as.vector(DIV_co2_waste_fossil_air) %*% L
-
-write.csv(TIV_co2_waste_fossil_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_co2_waste_fossil_air_",year_current,"_ixi.csv"))
-
-TIV_breakdown_co2_waste_fossil_air = as.vector(DIV_co2_waste_fossil_air) * L
-TIV_breakdown_co2_waste_fossil_air_w_labels = cbind(Exiobase_T_labels_ixi, TIV_breakdown_co2_waste_fossil_air)
-TIV_country_breakdown_co2_waste_fossil_air_w_labels = t(TIV_breakdown_co2_waste_fossil_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_co2_waste_fossil_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_waste_fossil_air_",year_current,"_ixi.csv"))
-
-
-# CH4 combustion air
-CH4_combustion_air = satellite[25,]
-#write.csv(CH4_combustion_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/satellite/ch4_combustion_air_",year_current,"_ixi.csv"))
-CH4_combustion_air = CH4_combustion_air*28
-#write.csv(CH4_combustion_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/satellite/ch4_CO2eq_combustion_air_",year_current,"_ixi.csv"))
-DIV_ch4_combustion_air = CH4_combustion_air/total_output
-DIV_ch4_combustion_air[is.na(DIV_ch4_combustion_air)]=0
-DIV_ch4_combustion_air[DIV_ch4_combustion_air == Inf]<-0
-#write.csv(DIV_ch4_combustion_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/DIV_ch4_CO2eq_combustion_air_",year_current,"_ixi.csv"))
-TIV_ch4_combustion_air = as.vector(DIV_ch4_combustion_air) %*% L
-
-write.csv(TIV_ch4_combustion_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_combustion_air_",year_current,"_ixi.csv"))
-
-TIV_breakdown_ch4_combustion_air = as.vector(DIV_ch4_combustion_air) * L
-TIV_breakdown_ch4_combustion_air_w_labels = cbind(Exiobase_T_labels_ixi, TIV_breakdown_ch4_combustion_air)
-TIV_country_breakdown_ch4_combustion_air_w_labels = t(TIV_breakdown_ch4_combustion_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_ch4_combustion_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_combustion_air_",year_current,"_ixi.csv"))
-
-
-# CH4 noncombustion air
-## gas
-CH4_noncombustion_gas_air = satellite[68,]
-CH4_noncombustion_gas_air = CH4_noncombustion_gas_air*28
-DIV_ch4_noncombustion_gas_air = CH4_noncombustion_gas_air/total_output
-DIV_ch4_noncombustion_gas_air[is.na(DIV_ch4_noncombustion_gas_air)]=0
-DIV_ch4_noncombustion_gas_air[DIV_ch4_noncombustion_gas_air == Inf]<-0
-TIV_ch4_noncombustion_gas_air = as.vector(DIV_ch4_noncombustion_gas_air) %*% L
-
-write.csv(TIV_ch4_noncombustion_gas_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_noncombustion_gas_air_",year_current,"_ixi.csv"))
-
-TIV_breakdown_ch4_noncombustion_gas_air = as.vector(DIV_ch4_noncombustion_gas_air) * L
-TIV_breakdown_ch4_noncombustion_gas_air_w_labels = cbind(Exiobase_T_labels_ixi, TIV_breakdown_ch4_noncombustion_gas_air)
-TIV_country_breakdown_ch4_noncombustion_gas_air_w_labels = t(TIV_breakdown_ch4_noncombustion_gas_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_ch4_noncombustion_gas_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_gas_air_",year_current,"_ixi.csv"))
-
-## oil
-CH4_noncombustion_oil_air = satellite[69,]
-CH4_noncombustion_oil_air = CH4_noncombustion_oil_air*28
-DIV_ch4_noncombustion_oil_air = CH4_noncombustion_oil_air/total_output
-DIV_ch4_noncombustion_oil_air[is.na(DIV_ch4_noncombustion_oil_air)]=0
-DIV_ch4_noncombustion_oil_air[DIV_ch4_noncombustion_oil_air == Inf]<-0
-TIV_ch4_noncombustion_oil_air = as.vector(DIV_ch4_noncombustion_oil_air) %*% L
-
-write.csv(TIV_ch4_noncombustion_oil_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_noncombustion_oil_air_",year_current,"_ixi.csv"))
-
-TIV_breakdown_ch4_noncombustion_oil_air = as.vector(DIV_ch4_noncombustion_oil_air) * L
-TIV_breakdown_ch4_noncombustion_oil_air_w_labels = cbind(Exiobase_T_labels_ixi, TIV_breakdown_ch4_noncombustion_oil_air)
-TIV_country_breakdown_ch4_noncombustion_oil_air_w_labels = t(TIV_breakdown_ch4_noncombustion_oil_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_ch4_noncombustion_oil_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_oil_air_",year_current,"_ixi.csv"))
-
-## anthracite
-CH4_noncombustion_anthracite_air = satellite[70,]
-CH4_noncombustion_anthracite_air = CH4_noncombustion_anthracite_air*28
-DIV_ch4_noncombustion_anthracite_air = CH4_noncombustion_anthracite_air/total_output
-DIV_ch4_noncombustion_anthracite_air[is.na(DIV_ch4_noncombustion_anthracite_air)]=0
-DIV_ch4_noncombustion_anthracite_air[DIV_ch4_noncombustion_anthracite_air == Inf]<-0
-TIV_ch4_noncombustion_anthracite_air = as.vector(DIV_ch4_noncombustion_anthracite_air) %*% L
-
-write.csv(TIV_ch4_noncombustion_anthracite_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_noncombustion_anthracite_air_",year_current,"_ixi.csv"))
-
-TIV_breakdown_ch4_noncombustion_anthracite_air = as.vector(DIV_ch4_noncombustion_anthracite_air) * L
-TIV_breakdown_ch4_noncombustion_anthracite_air_w_labels = cbind(Exiobase_T_labels_ixi, TIV_breakdown_ch4_noncombustion_anthracite_air)
-TIV_country_breakdown_ch4_noncombustion_anthracite_air_w_labels = t(TIV_breakdown_ch4_noncombustion_anthracite_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_ch4_noncombustion_anthracite_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_anthracite_air_",year_current,"_ixi.csv"))
-
-## bituminous coal
-CH4_noncombustion_bituminouscoal_air = satellite[71,]
-CH4_noncombustion_bituminouscoal_air = CH4_noncombustion_bituminouscoal_air*28
-DIV_ch4_noncombustion_bituminouscoal_air = CH4_noncombustion_bituminouscoal_air/total_output
-DIV_ch4_noncombustion_bituminouscoal_air[is.na(DIV_ch4_noncombustion_bituminouscoal_air)]=0
-DIV_ch4_noncombustion_bituminouscoal_air[DIV_ch4_noncombustion_bituminouscoal_air == Inf]<-0
-TIV_ch4_noncombustion_bituminouscoal_air = as.vector(DIV_ch4_noncombustion_bituminouscoal_air) %*% L
-
-write.csv(TIV_ch4_noncombustion_bituminouscoal_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_noncombustion_bituminouscoal_air_",year_current,"_ixi.csv"))
-
-TIV_breakdown_ch4_noncombustion_bituminouscoal_air = as.vector(DIV_ch4_noncombustion_bituminouscoal_air) * L
-TIV_breakdown_ch4_noncombustion_bituminouscoal_air_w_labels = cbind(Exiobase_T_labels_ixi, TIV_breakdown_ch4_noncombustion_bituminouscoal_air)
-TIV_country_breakdown_ch4_noncombustion_bituminouscoal_air_w_labels = t(TIV_breakdown_ch4_noncombustion_bituminouscoal_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_ch4_noncombustion_bituminouscoal_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_bituminouscoal_air_",year_current,"_ixi.csv"))
-
-## coking coal
-CH4_noncombustion_cokingcoal_air = satellite[72,]
-CH4_noncombustion_cokingcoal_air = CH4_noncombustion_cokingcoal_air*28
-DIV_ch4_noncombustion_cokingcoal_air = CH4_noncombustion_cokingcoal_air/total_output
-DIV_ch4_noncombustion_cokingcoal_air[is.na(DIV_ch4_noncombustion_cokingcoal_air)]=0
-DIV_ch4_noncombustion_cokingcoal_air[DIV_ch4_noncombustion_cokingcoal_air == Inf]<-0
-TIV_ch4_noncombustion_cokingcoal_air = as.vector(DIV_ch4_noncombustion_cokingcoal_air) %*% L
-
-write.csv(TIV_ch4_noncombustion_cokingcoal_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_noncombustion_cokingcoal_air_",year_current,"_ixi.csv"))
-
-TIV_breakdown_ch4_noncombustion_cokingcoal_air = as.vector(DIV_ch4_noncombustion_cokingcoal_air) * L
-TIV_breakdown_ch4_noncombustion_cokingcoal_air_w_labels = cbind(Exiobase_T_labels_ixi, TIV_breakdown_ch4_noncombustion_cokingcoal_air)
-TIV_country_breakdown_ch4_noncombustion_cokingcoal_air_w_labels = t(TIV_breakdown_ch4_noncombustion_cokingcoal_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_ch4_noncombustion_cokingcoal_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_cokingcoal_air_",year_current,"_ixi.csv"))
-
-## lignite
-CH4_noncombustion_lignite_air = satellite[73,]
-CH4_noncombustion_lignite_air = CH4_noncombustion_lignite_air*28
-DIV_ch4_noncombustion_lignite_air = CH4_noncombustion_lignite_air/total_output
-DIV_ch4_noncombustion_lignite_air[is.na(DIV_ch4_noncombustion_lignite_air)]=0
-DIV_ch4_noncombustion_lignite_air[DIV_ch4_noncombustion_lignite_air == Inf]<-0
-TIV_ch4_noncombustion_lignite_air = as.vector(DIV_ch4_noncombustion_lignite_air) %*% L
-
-write.csv(TIV_ch4_noncombustion_lignite_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_noncombustion_lignite_air_",year_current,"_ixi.csv"))
-
-TIV_breakdown_ch4_noncombustion_lignite_air = as.vector(DIV_ch4_noncombustion_lignite_air) * L
-TIV_breakdown_ch4_noncombustion_lignite_air_w_labels = cbind(Exiobase_T_labels_ixi, TIV_breakdown_ch4_noncombustion_lignite_air)
-TIV_country_breakdown_ch4_noncombustion_lignite_air_w_labels = t(TIV_breakdown_ch4_noncombustion_lignite_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_ch4_noncombustion_lignite_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_lignite_air_",year_current,"_ixi.csv"))
-
-## subbituminous coal
-CH4_noncombustion_subbituminouscoal_air = satellite[74,]
-CH4_noncombustion_subbituminouscoal_air = CH4_noncombustion_subbituminouscoal_air*28
-DIV_ch4_noncombustion_subbituminouscoal_air = CH4_noncombustion_subbituminouscoal_air/total_output
-DIV_ch4_noncombustion_subbituminouscoal_air[is.na(DIV_ch4_noncombustion_subbituminouscoal_air)]=0
-DIV_ch4_noncombustion_subbituminouscoal_air[DIV_ch4_noncombustion_subbituminouscoal_air == Inf]<-0
-TIV_ch4_noncombustion_subbituminouscoal_air = as.vector(DIV_ch4_noncombustion_subbituminouscoal_air) %*% L
-
-write.csv(TIV_ch4_noncombustion_subbituminouscoal_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_noncombustion_subbituminouscoal_air_",year_current,"_ixi.csv"))
-
-TIV_breakdown_ch4_noncombustion_subbituminouscoal_air = as.vector(DIV_ch4_noncombustion_subbituminouscoal_air) * L
-TIV_breakdown_ch4_noncombustion_subbituminouscoal_air_w_labels = cbind(Exiobase_T_labels_ixi, TIV_breakdown_ch4_noncombustion_subbituminouscoal_air)
-TIV_country_breakdown_ch4_noncombustion_subbituminouscoal_air_w_labels = t(TIV_breakdown_ch4_noncombustion_subbituminouscoal_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_ch4_noncombustion_subbituminouscoal_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_subbituminouscoal_air_",year_current,"_ixi.csv"))
-
-## oil refinery
-CH4_noncombustion_oilrefinery_air = satellite[75,]
-CH4_noncombustion_oilrefinery_air = CH4_noncombustion_oilrefinery_air*28
-DIV_ch4_noncombustion_oilrefinery_air = CH4_noncombustion_oilrefinery_air/total_output
-DIV_ch4_noncombustion_oilrefinery_air[is.na(DIV_ch4_noncombustion_oilrefinery_air)]=0
-DIV_ch4_noncombustion_oilrefinery_air[DIV_ch4_noncombustion_oilrefinery_air == Inf]<-0
-TIV_ch4_noncombustion_oilrefinery_air = as.vector(DIV_ch4_noncombustion_oilrefinery_air) %*% L
-
-write.csv(TIV_ch4_noncombustion_oilrefinery_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_noncombustion_oilrefinery_air_",year_current,"_ixi.csv"))
-
-TIV_breakdown_ch4_noncombustion_oilrefinery_air = as.vector(DIV_ch4_noncombustion_oilrefinery_air) * L
-TIV_breakdown_ch4_noncombustion_oilrefinery_air_w_labels = cbind(Exiobase_T_labels_ixi, TIV_breakdown_ch4_noncombustion_oilrefinery_air)
-TIV_country_breakdown_ch4_noncombustion_oilrefinery_air_w_labels = t(TIV_breakdown_ch4_noncombustion_oilrefinery_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_ch4_noncombustion_oilrefinery_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_oilrefinery_air_",year_current,"_ixi.csv"))
-
-
-# CH4 agriculture air
-CH4_agriculture_air = satellite[427,]
-CH4_agriculture_air = CH4_agriculture_air*28
-DIV_ch4_agriculture_air = CH4_agriculture_air/total_output
-DIV_ch4_agriculture_air[is.na(DIV_ch4_agriculture_air)]=0
-DIV_ch4_agriculture_air[DIV_ch4_agriculture_air == Inf]<-0
-TIV_ch4_agriculture_air = as.vector(DIV_ch4_agriculture_air) %*% L
-
-write.csv(TIV_ch4_agriculture_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_agriculture_air_",year_current,"_ixi.csv"))
-
-TIV_breakdown_ch4_agriculture_air = as.vector(DIV_ch4_agriculture_air) * L
-TIV_breakdown_ch4_agriculture_air_w_labels = cbind(Exiobase_T_labels_ixi, TIV_breakdown_ch4_agriculture_air)
-TIV_country_breakdown_ch4_agriculture_air_w_labels = t(TIV_breakdown_ch4_agriculture_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_ch4_agriculture_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_agriculture_air_",year_current,"_ixi.csv"))
-
-
-# CH4 waste air
-CH4_waste_air = satellite[436,]
-CH4_waste_air = CH4_waste_air*28
-DIV_ch4_waste_air = CH4_waste_air/total_output
-DIV_ch4_waste_air[is.na(DIV_ch4_waste_air)]=0
-DIV_ch4_waste_air[DIV_ch4_waste_air == Inf]<-0
-TIV_ch4_waste_air = as.vector(DIV_ch4_waste_air) %*% L
-
-write.csv(TIV_ch4_waste_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_waste_air_",year_current,"_ixi.csv"))
-
-TIV_breakdown_ch4_waste_air = as.vector(DIV_ch4_waste_air) * L
-TIV_breakdown_ch4_waste_air_w_labels = cbind(Exiobase_T_labels_ixi, TIV_breakdown_ch4_waste_air)
-TIV_country_breakdown_ch4_waste_air_w_labels = t(TIV_breakdown_ch4_waste_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_ch4_waste_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_waste_air_",year_current,"_ixi.csv"))
-
-
-# N2O combustion air
-N2O_combustion_air = satellite[26,]
-#write.csv(N2O_combustion_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/satellite/n2o_combustion_air_",year_current,"_ixi.csv"))
-N2O_combustion_air = N2O_combustion_air*265
-#write.csv(N2O_combustion_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/satellite/n2o_CO2eq_combustion_air_",year_current,"_ixi.csv"))
-DIV_n2o_combustion_air = N2O_combustion_air/total_output
-DIV_n2o_combustion_air[is.na(DIV_n2o_combustion_air)]=0
-DIV_n2o_combustion_air[DIV_n2o_combustion_air == Inf]<-0
-#write.csv(DIV_n2o_combustion_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/DIV_n2o_CO2eq_combustion_air_",year_current,"_ixi.csv"))
-TIV_n2o_combustion_air = as.vector(DIV_n2o_combustion_air) %*% L
-
-write.csv(TIV_n2o_combustion_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_n2o_CO2eq_combustion_air_",year_current,"_ixi.csv"))
-
-TIV_breakdown_n2o_combustion_air = as.vector(DIV_n2o_combustion_air) * L
-TIV_breakdown_n2o_combustion_air_w_labels = cbind(Exiobase_T_labels_ixi, TIV_breakdown_n2o_combustion_air)
-TIV_country_breakdown_n2o_combustion_air_w_labels = t(TIV_breakdown_n2o_combustion_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_n2o_combustion_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_n2o_CO2eq_combustion_air_",year_current,"_ixi.csv"))
-
-
-# N2O agriculture air
-N2O_agriculture_air = satellite[430,]
-N2O_agriculture_air = N2O_agriculture_air*265
-DIV_n2o_agriculture_air = N2O_agriculture_air/total_output
-DIV_n2o_agriculture_air[is.na(DIV_n2o_agriculture_air)]=0
-DIV_n2o_agriculture_air[DIV_n2o_agriculture_air == Inf]<-0
-TIV_n2o_agriculture_air = as.vector(DIV_n2o_agriculture_air) %*% L
-
-write.csv(TIV_n2o_agriculture_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_n2o_CO2eq_agriculture_air_",year_current,"_ixi.csv"))
-
-TIV_breakdown_n2o_agriculture_air = as.vector(DIV_n2o_agriculture_air) * L
-TIV_breakdown_n2o_agriculture_air_w_labels = cbind(Exiobase_T_labels_ixi, TIV_breakdown_n2o_agriculture_air)
-TIV_country_breakdown_n2o_agriculture_air_w_labels = t(TIV_breakdown_n2o_agriculture_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_n2o_agriculture_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_n2o_CO2eq_agriculture_air_",year_current,"_ixi.csv"))
-
-
-# SF6 air
-SF6_air = satellite[424,]
-#write.csv(SF6_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/satellite/sf6_air_",year_current,"_ixi.csv"))
-SF6_air = SF6_air*23500
-#write.csv(SF6_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/satellite/sf6_CO2eq_air_",year_current,"_ixi.csv"))
-DIV_sf6_air = SF6_air/total_output
-DIV_sf6_air[is.na(DIV_sf6_air)]=0
-DIV_sf6_air[DIV_sf6_air == Inf]<-0
-#write.csv(DIV_sf6_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/DIV_sf6_CO2eq_air_",year_current,"_ixi.csv"))
-TIV_sf6_air = as.vector(DIV_sf6_air) %*% L
-
-write.csv(TIV_sf6_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_sf6_CO2eq_air_",year_current,"_ixi.csv"))
-
-TIV_breakdown_sf6_air = as.vector(DIV_sf6_air) * L
-TIV_breakdown_sf6_air_w_labels = cbind(Exiobase_T_labels_ixi, TIV_breakdown_sf6_air)
-TIV_country_breakdown_sf6_air_w_labels = t(TIV_breakdown_sf6_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_sf6_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_sf6_CO2eq_air_",year_current,"_ixi.csv"))
-
-
-# HFC air
-HFC_air = satellite[425,]
-#write.csv(HFC_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/satellite/hfc_CO2eq_air_",year_current,"_ixi.csv"))
-DIV_hfc_air = HFC_air/total_output
-DIV_hfc_air[is.na(DIV_hfc_air)]=0
-DIV_hfc_air[DIV_hfc_air == Inf]<-0
-#write.csv(DIV_hfc_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/DIV_hfc_CO2eq_air_",year_current,"_ixi.csv"))
-TIV_hfc_air = as.vector(DIV_hfc_air) %*% L
-
-write.csv(TIV_hfc_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_hfc_CO2eq_air_",year_current,"_ixi.csv"))
-
-TIV_breakdown_hfc_air = as.vector(DIV_hfc_air) * L
-TIV_breakdown_hfc_air_w_labels = cbind(Exiobase_T_labels_ixi, TIV_breakdown_hfc_air)
-TIV_country_breakdown_hfc_air_w_labels = t(TIV_breakdown_hfc_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_hfc_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_hfc_CO2eq_air_",year_current,"_ixi.csv"))
-
-
-# PFC air
-PFC_air = satellite[426,]
-#write.csv(PFC_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/satellite/pfc_CO2eq_air_",year_current,"_ixi.csv"))
-DIV_pfc_air = PFC_air/total_output
-DIV_pfc_air[is.na(DIV_pfc_air)]=0
-DIV_pfc_air[DIV_pfc_air == Inf]<-0
-#write.csv(DIV_pfc_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/DIV_pfc_CO2eq_air_",year_current,"_ixi.csv"))
-TIV_pfc_air = as.vector(DIV_pfc_air) %*% L
-
-write.csv(TIV_pfc_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_pfc_CO2eq_air_",year_current,"_ixi.csv"))
-
-TIV_breakdown_pfc_air = as.vector(DIV_pfc_air) * L
-TIV_breakdown_pfc_air_w_labels = cbind(Exiobase_T_labels_ixi, TIV_breakdown_pfc_air)
-TIV_country_breakdown_pfc_air_w_labels = t(TIV_breakdown_pfc_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_pfc_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_pfc_CO2eq_air_",year_current,"_ixi.csv"))
-
-
-# energy carrier use
-energy_carrier_use = satellite[470,]
-write.csv(energy_carrier_use, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/satellite/energy_carrier_use_",year_current,"_ixi.csv"))
-DIV_e_u = energy_carrier_use/total_output
-DIV_e_u[is.na(DIV_e_u)]=0
-DIV_e_u[DIV_e_u == Inf]<-0
-TIV_e_u = as.vector(DIV_e_u) %*% L
-
-write.csv(TIV_e_u, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_energy_carrier_use_",year_current,"_ixi.csv"))
-
-TIV_breakdown_e_u = as.vector(DIV_e_u) * L
-TIV_breakdown_e_u_w_labels = cbind(Exiobase_T_labels_ixi, TIV_breakdown_e_u)
-TIV_country_breakdown_e_u_w_labels = t(TIV_breakdown_e_u_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_e_u_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_energy_carrier_use_",year_current,"_ixi.csv"))
-}
-
-
-# EXIOBASE_cluster_pxp_version
-
-years_exiobase_pxp = c(2005,2010)
-
-for (i in years_exiobase_pxp){
-
-year_current = i
-
-A = read.delim(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/A.txt"),header = F)
-
-write.csv(A, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/A.csv"))
-
-A = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/A.csv",sep = ""),row.names=NULL,as.is=TRUE)[4:9803,4:9803]
-A[is.na(A)]=0
-A = mapply(A, FUN = as.numeric)
-A = matrix(data = A, ncol = 9800, nrow = 9800)
-
-L = solve(diag(dim(A)[1])-A) # this solves the Leontief inverse initially
-L[is.na(L)]=0
-
-
-# final demand
-
-FD = read.delim(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/Y.txt"),header = F)
-
-write.csv(FD, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/Y.csv"))
-
-
-Exiobase_T_labels_pxp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/Y.csv"))[4:9803,1:3]
-
-write.csv(Exiobase_T_labels_pxp, paste0(data_dir_exiobase, "/Exiobase_T_labels_pxp.csv"))
-
-Exiobase_FD_labels_pxp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/Y.csv"))[1:3,4:346]
-
-write.csv(Exiobase_FD_labels_pxp, paste0(data_dir_exiobase, "/Exiobase_FD_labels_pxp.csv"))
-
-
-FD = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/Y.csv",sep=""),row.names=NULL,as.is=TRUE)[4:9803,4:346]
-FD[is.na(FD)]=0
-FD = mapply(FD, FUN = as.numeric)
-FD = matrix(data=FD,ncol=343,nrow=9800)
-
-write.csv(FD, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/FD_",year_current,"_pxp.csv"))
-
-
-# total output
-total_output = L %*% rowSums(FD)
-
-write.csv(total_output, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/total_output_",year_current,"_pxp.csv"))
-
-
-# direct environmental vectors
-satellite = read.delim(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/F.txt"),header = F)
-
-write.csv(satellite, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/F.csv"))
-
-
-satellite = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/F.csv",sep=""),row.names=NULL,as.is=TRUE)[3:1106,3:9802]
-satellite[is.na(satellite)]=0
-satellite = mapply(satellite, FUN = as.numeric)
-satellite = matrix(data=satellite,ncol=9800,nrow=1104)
-
-
-write.csv(satellite, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/satellite_",year_current,"_pxp.csv"))
-
-
-# direct environmental vectors on final demand
-
-satellite_FD = read.delim(paste0(data_dir_exiobase, "/IOT_", year_current, "_pxp/satellite/F_hh.txt"),header = F)
-
-write.csv(satellite_FD, paste0(data_dir_exiobase, "/IOT_", year_current, "_pxp/satellite/F_hh.csv"))
-
-
-# CO2 combustion air
-CO2_combustion_air = satellite[24,]
-#write.csv(CO2_combustion_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/co2_combustion_air_",year_current,"_pxp.csv"))
-DIV_co2_combustion_air = CO2_combustion_air/total_output
-DIV_co2_combustion_air[is.na(DIV_co2_combustion_air)]=0
-DIV_co2_combustion_air[DIV_co2_combustion_air == Inf]<-0
-#write.csv(DIV_co2_combustion_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/DIV_co2_combustion_air_",year_current,"_pxp.csv"))
-TIV_co2_combustion_air = as.vector(DIV_co2_combustion_air) %*% L
-
-write.csv(TIV_co2_combustion_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_co2_combustion_air_",year_current,"_pxp.csv"))
-
-TIV_breakdown_co2_combustion_air = as.vector(DIV_co2_combustion_air) * L
-TIV_breakdown_co2_combustion_air_w_labels = cbind(Exiobase_T_labels_pxp, TIV_breakdown_co2_combustion_air)
-TIV_country_breakdown_co2_combustion_air_w_labels = t(TIV_breakdown_co2_combustion_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_co2_combustion_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_co2_combustion_air_",year_current,"_pxp.csv"))
-
-
-# CO2 non-combustion air
-## cement
-CO2_noncombustion_cement_air = satellite[93,]
-#saveRDS(CO2_noncombustion_cement_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/co2_noncombustion_cement_air_",year_current,".rds"))
-DIV_co2_noncombustion_cement_air = CO2_noncombustion_cement_air/total_output
-DIV_co2_noncombustion_cement_air[is.na(DIV_co2_noncombustion_cement_air)]=0
-DIV_co2_noncombustion_cement_air[DIV_co2_noncombustion_cement_air == Inf]<-0
-#saveRDS(DIV_co2_noncombustion_cement_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/DIV_co2_noncombustion_cement_air_",year_current,".rds"))
-TIV_co2_noncombustion_cement_air = as.vector(DIV_co2_noncombustion_cement_air) %*% L
-
-write.csv(TIV_co2_noncombustion_cement_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_co2_noncombustion_cement_air_",year_current,"_pxp.csv"))
-
-TIV_breakdown_co2_noncombustion_cement_air = as.vector(DIV_co2_noncombustion_cement_air) * L
-TIV_breakdown_co2_noncombustion_cement_air_w_labels = cbind(Exiobase_T_labels_pxp, TIV_breakdown_co2_noncombustion_cement_air)
-TIV_country_breakdown_co2_noncombustion_cement_air_w_labels = t(TIV_breakdown_co2_noncombustion_cement_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_co2_noncombustion_cement_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_co2_noncombustion_cement_air_",year_current,"_pxp.csv"))
-
-## lime
-CO2_noncombustion_lime_air = satellite[94,]
-#saveRDS(CO2_noncombustion_lime_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/co2_noncombustion_lime_air_",year_current,".rds"))
-DIV_co2_noncombustion_lime_air = CO2_noncombustion_lime_air/total_output
-DIV_co2_noncombustion_lime_air[is.na(DIV_co2_noncombustion_lime_air)]=0
-DIV_co2_noncombustion_lime_air[DIV_co2_noncombustion_lime_air == Inf]<-0
-#saveRDS(DIV_co2_noncombustion_lime_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/DIV_co2_noncombustion_lime_air_",year_current,".rds"))
-TIV_co2_noncombustion_lime_air = as.vector(DIV_co2_noncombustion_lime_air) %*% L
-
-write.csv(TIV_co2_noncombustion_lime_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_co2_noncombustion_lime_air_",year_current,"_pxp.csv"))
-
-TIV_breakdown_co2_noncombustion_lime_air = as.vector(DIV_co2_noncombustion_lime_air) * L
-TIV_breakdown_co2_noncombustion_lime_air_w_labels = cbind(Exiobase_T_labels_pxp, TIV_breakdown_co2_noncombustion_lime_air)
-TIV_country_breakdown_co2_noncombustion_lime_air_w_labels = t(TIV_breakdown_co2_noncombustion_lime_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_co2_noncombustion_lime_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_co2_noncombustion_lime_air_",year_current,"_pxp.csv"))
-
-
-# CO2 agriculture peat decay air
-CO2_agriculture_peatdecay_air = satellite[428,]
-#saveRDS(CO2_agriculture_peatdecay_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/co2_agriculture_peatdecay_air_",year_current,".rds"))
-DIV_co2_agriculture_peatdecay_air = CO2_agriculture_peatdecay_air/total_output
-DIV_co2_agriculture_peatdecay_air[is.na(DIV_co2_agriculture_peatdecay_air)]=0
-DIV_co2_agriculture_peatdecay_air[DIV_co2_agriculture_peatdecay_air == Inf]<-0
-#saveRDS(DIV_co2_agriculture_peatdecay_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/DIV_co2_agriculture_peatdecay_air_",year_current,".rds"))
-TIV_co2_agriculture_peatdecay_air = as.vector(DIV_co2_agriculture_peatdecay_air) %*% L
-
-write.csv(TIV_co2_agriculture_peatdecay_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_co2_agriculture_peatdecay_air_",year_current,"_pxp.csv"))
-
-TIV_breakdown_co2_agriculture_peatdecay_air = as.vector(DIV_co2_agriculture_peatdecay_air) * L
-TIV_breakdown_co2_agriculture_peatdecay_air_w_labels = cbind(Exiobase_T_labels_pxp, TIV_breakdown_co2_agriculture_peatdecay_air)
-TIV_country_breakdown_co2_agriculture_peatdecay_air_w_labels = t(TIV_breakdown_co2_agriculture_peatdecay_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_co2_agriculture_peatdecay_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_co2_agriculture_peatdecay_air_",year_current,"_pxp.csv"))
-
-
-# CO2 waste air
-## biogenic
-CO2_waste_biogenic_air = satellite[438,]
-#saveRDS(CO2_waste_biogenic_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/co2_waste_biogenic_air_",year_current,".rds"))
-DIV_co2_waste_biogenic_air = CO2_waste_biogenic_air/total_output
-DIV_co2_waste_biogenic_air[is.na(DIV_co2_waste_biogenic_air)]=0
-DIV_co2_waste_biogenic_air[DIV_co2_waste_biogenic_air == Inf]<-0
-#saveRDS(DIV_co2_waste_biogenic_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/DIV_co2_waste_biogenic_air_",year_current,".rds"))
-TIV_co2_biogenic_air = as.vector(DIV_co2_waste_biogenic_air) %*% L
-
-write.csv(TIV_co2_biogenic_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_co2_biogenic_air_",year_current,"_pxp.csv"))
-
-TIV_breakdown_co2_biogenic_air = as.vector(DIV_co2_waste_biogenic_air) * L
-TIV_breakdown_co2_biogenic_air_w_labels = cbind(Exiobase_T_labels_pxp, TIV_breakdown_co2_biogenic_air)
-TIV_country_breakdown_co2_biogenic_air_w_labels = t(TIV_breakdown_co2_biogenic_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_co2_biogenic_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_co2_biogenic_air_",year_current,"_pxp.csv"))
-
-## fossil
-CO2_waste_fossil_air = satellite[439,]
-#saveRDS(CO2_waste_fossil_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/co2_waste_fossil_air_",year_current,".rds"))
-DIV_co2_waste_fossil_air = CO2_waste_fossil_air/total_output
-DIV_co2_waste_fossil_air[is.na(DIV_co2_waste_fossil_air)]=0
-DIV_co2_waste_fossil_air[DIV_co2_waste_fossil_air == Inf]<-0
-#saveRDS(DIV_co2_waste_fossil_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/DIV_co2_waste_fossil_air_",year_current,".rds"))
-TIV_co2_waste_fossil_air = as.vector(DIV_co2_waste_fossil_air) %*% L
-
-write.csv(TIV_co2_waste_fossil_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_co2_waste_fossil_air_",year_current,"_pxp.csv"))
-
-TIV_breakdown_co2_waste_fossil_air = as.vector(DIV_co2_waste_fossil_air) * L
-TIV_breakdown_co2_waste_fossil_air_w_labels = cbind(Exiobase_T_labels_pxp, TIV_breakdown_co2_waste_fossil_air)
-TIV_country_breakdown_co2_waste_fossil_air_w_labels = t(TIV_breakdown_co2_waste_fossil_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_co2_waste_fossil_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_co2_waste_fossil_air_",year_current,"_pxp.csv"))
-
-
-# CH4 combustion air
-CH4_combustion_air = satellite[25,]
-#saveRDS(CH4_combustion_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/ch4_combustion_air_",year_current,".rds"))
-CH4_combustion_air = CH4_combustion_air*28
-#saveRDS(CH4_combustion_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/ch4_CO2eq_combustion_air_",year_current,".rds"))
-DIV_ch4_combustion_air = CH4_combustion_air/total_output
-DIV_ch4_combustion_air[is.na(DIV_ch4_combustion_air)]=0
-DIV_ch4_combustion_air[DIV_ch4_combustion_air == Inf]<-0
-#saveRDS(DIV_ch4_combustion_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/DIV_ch4_CO2eq_combustion_air_",year_current,".rds"))
-TIV_ch4_combustion_air = as.vector(DIV_ch4_combustion_air) %*% L
-
-#saveRDS(TIV_ch4_combustion_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_ch4_CO2eq_combustion_air_",year_current,".rds"))
-write.csv(TIV_ch4_combustion_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_ch4_CO2eq_combustion_air_",year_current,"_pxp.csv"))
-
-TIV_breakdown_ch4_combustion_air = as.vector(DIV_ch4_combustion_air) * L
-TIV_breakdown_ch4_combustion_air_w_labels = cbind(Exiobase_T_labels_pxp, TIV_breakdown_ch4_combustion_air)
-TIV_country_breakdown_ch4_combustion_air_w_labels = t(TIV_breakdown_ch4_combustion_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_ch4_combustion_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_combustion_air_",year_current,"_pxp.csv"))
-
-
-# CH4 non-combustion air
-## gas
-CH4_noncombustion_gas_air = satellite[68,]
-#saveRDS(CH4_noncombustion_gas_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/ch4_noncombustion_gas_air_",year_current,".rds"))
-CH4_noncombustion_gas_air = CH4_noncombustion_gas_air*28
-#saveRDS(CH4_noncombustion_gas_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/ch4_CO2eq_noncombustion_gas_air_",year_current,".rds"))
-DIV_ch4_noncombustion_gas_air = CH4_noncombustion_gas_air/total_output
-DIV_ch4_noncombustion_gas_air[is.na(DIV_ch4_noncombustion_gas_air)]=0
-DIV_ch4_noncombustion_gas_air[DIV_ch4_noncombustion_gas_air == Inf]<-0
-#saveRDS(DIV_ch4_noncombustion_gas_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/DIV_ch4_CO2eq_noncombustion_gas_air_",year_current,".rds"))
-TIV_ch4_noncombustion_gas_air = as.vector(DIV_ch4_noncombustion_gas_air) %*% L
-
-write.csv(TIV_ch4_noncombustion_gas_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_ch4_CO2eq_noncombustion_gas_air_",year_current,"_pxp.csv"))
-
-TIV_breakdown_ch4_noncombustion_gas_air = as.vector(DIV_ch4_noncombustion_gas_air) * L
-TIV_breakdown_ch4_noncombustion_gas_air_w_labels = cbind(Exiobase_T_labels_pxp, TIV_breakdown_ch4_noncombustion_gas_air)
-TIV_country_breakdown_ch4_noncombustion_gas_air_w_labels = t(TIV_breakdown_ch4_noncombustion_gas_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_ch4_noncombustion_gas_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_noncombustion_gas_air_",year_current,"_pxp.csv"))
-
-## oil
-CH4_noncombustion_oil_air = satellite[69,]
-#saveRDS(CH4_noncombustion_oil_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/ch4_noncombustion_oil_air_",year_current,".rds"))
-CH4_noncombustion_oil_air = CH4_noncombustion_oil_air*28
-#saveRDS(CH4_noncombustion_oil_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/ch4_CO2eq_noncombustion_oil_air_",year_current,".rds"))
-DIV_ch4_noncombustion_oil_air = CH4_noncombustion_oil_air/total_output
-DIV_ch4_noncombustion_oil_air[is.na(DIV_ch4_noncombustion_oil_air)]=0
-DIV_ch4_noncombustion_oil_air[DIV_ch4_noncombustion_oil_air == Inf]<-0
-#saveRDS(DIV_ch4_noncombustion_oil_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/DIV_ch4_CO2eq_noncombustion_oil_air_",year_current,".rds"))
-TIV_ch4_noncombustion_oil_air = as.vector(DIV_ch4_noncombustion_oil_air) %*% L
-
-write.csv(TIV_ch4_noncombustion_oil_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_ch4_CO2eq_noncombustion_oil_air_",year_current,"_pxp.csv"))
-
-TIV_breakdown_ch4_noncombustion_oil_air = as.vector(DIV_ch4_noncombustion_oil_air) * L
-TIV_breakdown_ch4_noncombustion_oil_air_w_labels = cbind(Exiobase_T_labels_pxp, TIV_breakdown_ch4_noncombustion_oil_air)
-TIV_country_breakdown_ch4_noncombustion_oil_air_w_labels = t(TIV_breakdown_ch4_noncombustion_oil_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_ch4_noncombustion_oil_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_noncombustion_oil_air_",year_current,"_pxp.csv"))
-
-## anthracite
-CH4_noncombustion_anthracite_air = satellite[70,]
-#saveRDS(CH4_noncombustion_anthracite_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/ch4_noncombustion_anthracite_air_",year_current,".rds"))
-CH4_noncombustion_anthracite_air = CH4_noncombustion_anthracite_air*28
-#saveRDS(CH4_noncombustion_anthracite_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/ch4_CO2eq_noncombustion_anthracite_air_",year_current,".rds"))
-DIV_ch4_noncombustion_anthracite_air = CH4_noncombustion_anthracite_air/total_output
-DIV_ch4_noncombustion_anthracite_air[is.na(DIV_ch4_noncombustion_anthracite_air)]=0
-DIV_ch4_noncombustion_anthracite_air[DIV_ch4_noncombustion_anthracite_air == Inf]<-0
-#saveRDS(DIV_ch4_noncombustion_anthracite_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/DIV_ch4_CO2eq_noncombustion_anthracite_air_",year_current,".rds"))
-TIV_ch4_noncombustion_anthracite_air = as.vector(DIV_ch4_noncombustion_anthracite_air) %*% L
-
-write.csv(TIV_ch4_noncombustion_anthracite_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_ch4_CO2eq_noncombustion_anthracite_air_",year_current,"_pxp.csv"))
-
-TIV_breakdown_ch4_noncombustion_anthracite_air = as.vector(DIV_ch4_noncombustion_anthracite_air) * L
-TIV_breakdown_ch4_noncombustion_anthracite_air_w_labels = cbind(Exiobase_T_labels_pxp, TIV_breakdown_ch4_noncombustion_anthracite_air)
-TIV_country_breakdown_ch4_noncombustion_anthracite_air_w_labels = t(TIV_breakdown_ch4_noncombustion_anthracite_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_ch4_noncombustion_anthracite_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_noncombustion_anthracite_air_",year_current,"_pxp.csv"))
-
-## bituminous coal
-CH4_noncombustion_bituminouscoal_air = satellite[71,]
-#saveRDS(CH4_noncombustion_bituminouscoal_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/ch4_noncombustion_bituminouscoal_air_",year_current,".rds"))
-CH4_noncombustion_bituminouscoal_air = CH4_noncombustion_bituminouscoal_air*28
-#saveRDS(CH4_noncombustion_bituminouscoal_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/ch4_CO2eq_noncombustion_bituminouscoal_air_",year_current,".rds"))
-DIV_ch4_noncombustion_bituminouscoal_air = CH4_noncombustion_bituminouscoal_air/total_output
-DIV_ch4_noncombustion_bituminouscoal_air[is.na(DIV_ch4_noncombustion_bituminouscoal_air)]=0
-DIV_ch4_noncombustion_bituminouscoal_air[DIV_ch4_noncombustion_bituminouscoal_air == Inf]<-0
-#saveRDS(DIV_ch4_noncombustion_bituminouscoal_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/DIV_ch4_CO2eq_noncombustion_bituminouscoal_air_",year_current,".rds"))
-TIV_ch4_noncombustion_bituminouscoal_air = as.vector(DIV_ch4_noncombustion_bituminouscoal_air) %*% L
-
-write.csv(TIV_ch4_noncombustion_bituminouscoal_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_ch4_CO2eq_noncombustion_bituminouscoal_air_",year_current,"_pxp.csv"))
-
-TIV_breakdown_ch4_noncombustion_bituminouscoal_air = as.vector(DIV_ch4_noncombustion_bituminouscoal_air) * L
-TIV_breakdown_ch4_noncombustion_bituminouscoal_air_w_labels = cbind(Exiobase_T_labels_pxp, TIV_breakdown_ch4_noncombustion_bituminouscoal_air)
-TIV_country_breakdown_ch4_noncombustion_bituminouscoal_air_w_labels = t(TIV_breakdown_ch4_noncombustion_bituminouscoal_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_ch4_noncombustion_bituminouscoal_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_noncombustion_bituminouscoal_air_",year_current,"_pxp.csv"))
-
-## coking coal
-CH4_noncombustion_cokingcoal_air = satellite[72,]
-#saveRDS(CH4_noncombustion_cokingcoal_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/ch4_noncombustion_cokingcoal_air_",year_current,".rds"))
-CH4_noncombustion_cokingcoal_air = CH4_noncombustion_cokingcoal_air*28
-#saveRDS(CH4_noncombustion_cokingcoal_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/ch4_CO2eq_noncombustion_cokingcoal_air_",year_current,".rds"))
-DIV_ch4_noncombustion_cokingcoal_air = CH4_noncombustion_cokingcoal_air/total_output
-DIV_ch4_noncombustion_cokingcoal_air[is.na(DIV_ch4_noncombustion_cokingcoal_air)]=0
-DIV_ch4_noncombustion_cokingcoal_air[DIV_ch4_noncombustion_cokingcoal_air == Inf]<-0
-#saveRDS(DIV_ch4_noncombustion_cokingcoal_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/DIV_ch4_CO2eq_noncombustion_cokingcoal_air_",year_current,".rds"))
-TIV_ch4_noncombustion_cokingcoal_air = as.vector(DIV_ch4_noncombustion_cokingcoal_air) %*% L
-
-write.csv(TIV_ch4_noncombustion_cokingcoal_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_ch4_CO2eq_noncombustion_cokingcoal_air_",year_current,"_pxp.csv"))
-
-TIV_breakdown_ch4_noncombustion_cokingcoal_air = as.vector(DIV_ch4_noncombustion_cokingcoal_air) * L
-TIV_breakdown_ch4_noncombustion_cokingcoal_air_w_labels = cbind(Exiobase_T_labels_pxp, TIV_breakdown_ch4_noncombustion_cokingcoal_air)
-TIV_country_breakdown_ch4_noncombustion_cokingcoal_air_w_labels = t(TIV_breakdown_ch4_noncombustion_cokingcoal_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_ch4_noncombustion_cokingcoal_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_noncombustion_cokingcoal_air_",year_current,"_pxp.csv"))
-
-## lignite
-CH4_noncombustion_lignite_air = satellite[73,]
-#saveRDS(CH4_noncombustion_lignite_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/ch4_noncombustion_lignite_air_",year_current,".rds"))
-CH4_noncombustion_lignite_air = CH4_noncombustion_lignite_air*28
-#saveRDS(CH4_noncombustion_lignite_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/ch4_CO2eq_noncombustion_lignite_air_",year_current,".rds"))
-DIV_ch4_noncombustion_lignite_air = CH4_noncombustion_lignite_air/total_output
-DIV_ch4_noncombustion_lignite_air[is.na(DIV_ch4_noncombustion_lignite_air)]=0
-DIV_ch4_noncombustion_lignite_air[DIV_ch4_noncombustion_lignite_air == Inf]<-0
-#saveRDS(DIV_ch4_noncombustion_lignite_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/DIV_ch4_CO2eq_noncombustion_lignite_air_",year_current,".rds"))
-TIV_ch4_noncombustion_lignite_air = as.vector(DIV_ch4_noncombustion_lignite_air) %*% L
-
-write.csv(TIV_ch4_noncombustion_lignite_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_ch4_CO2eq_noncombustion_lignite_air_",year_current,"_pxp.csv"))
-
-TIV_breakdown_ch4_noncombustion_lignite_air = as.vector(DIV_ch4_noncombustion_lignite_air) * L
-TIV_breakdown_ch4_noncombustion_lignite_air_w_labels = cbind(Exiobase_T_labels_pxp, TIV_breakdown_ch4_noncombustion_lignite_air)
-TIV_country_breakdown_ch4_noncombustion_lignite_air_w_labels = t(TIV_breakdown_ch4_noncombustion_lignite_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_ch4_noncombustion_lignite_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_noncombustion_lignite_air_",year_current,"_pxp.csv"))
-
-## subbituminous coal
-CH4_noncombustion_subbituminouscoal_air = satellite[74,]
-#saveRDS(CH4_noncombustion_subbituminouscoal_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/ch4_noncombustion_subbituminouscoal_air_",year_current,".rds"))
-CH4_noncombustion_subbituminouscoal_air = CH4_noncombustion_subbituminouscoal_air*28
-#saveRDS(CH4_noncombustion_subbituminouscoal_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/ch4_CO2eq_noncombustion_subbituminouscoal_air_",year_current,".rds"))
-DIV_ch4_noncombustion_subbituminouscoal_air = CH4_noncombustion_subbituminouscoal_air/total_output
-DIV_ch4_noncombustion_subbituminouscoal_air[is.na(DIV_ch4_noncombustion_subbituminouscoal_air)]=0
-DIV_ch4_noncombustion_subbituminouscoal_air[DIV_ch4_noncombustion_subbituminouscoal_air == Inf]<-0
-#saveRDS(DIV_ch4_noncombustion_subbituminouscoal_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/DIV_ch4_CO2eq_noncombustion_subbituminouscoal_air_",year_current,".rds"))
-TIV_ch4_noncombustion_subbituminouscoal_air = as.vector(DIV_ch4_noncombustion_subbituminouscoal_air) %*% L
-
-write.csv(TIV_ch4_noncombustion_subbituminouscoal_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_ch4_CO2eq_noncombustion_subbituminouscoal_air_",year_current,"_pxp.csv"))
-
-TIV_breakdown_ch4_noncombustion_subbituminouscoal_air = as.vector(DIV_ch4_noncombustion_subbituminouscoal_air) * L
-TIV_breakdown_ch4_noncombustion_subbituminouscoal_air_w_labels = cbind(Exiobase_T_labels_pxp, TIV_breakdown_ch4_noncombustion_subbituminouscoal_air)
-TIV_country_breakdown_ch4_noncombustion_subbituminouscoal_air_w_labels = t(TIV_breakdown_ch4_noncombustion_subbituminouscoal_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_ch4_noncombustion_subbituminouscoal_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_noncombustion_subbituminouscoal_air_",year_current,"_pxp.csv"))
-
-## oil refinery
-CH4_noncombustion_oilrefinery_air = satellite[75,]
-#saveRDS(CH4_noncombustion_oilrefinery_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/ch4_noncombustion_oilrefinery_air_",year_current,".rds"))
-CH4_noncombustion_oilrefinery_air = CH4_noncombustion_oilrefinery_air*28
-#saveRDS(CH4_noncombustion_oilrefinery_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/ch4_CO2eq_noncombustion_oilrefinery_air_",year_current,".rds"))
-DIV_ch4_noncombustion_oilrefinery_air = CH4_noncombustion_oilrefinery_air/total_output
-DIV_ch4_noncombustion_oilrefinery_air[is.na(DIV_ch4_noncombustion_oilrefinery_air)]=0
-DIV_ch4_noncombustion_oilrefinery_air[DIV_ch4_noncombustion_oilrefinery_air == Inf]<-0
-#saveRDS(DIV_ch4_noncombustion_oilrefinery_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/DIV_ch4_CO2eq_noncombustion_oilrefinery_air_",year_current,".rds"))
-TIV_ch4_noncombustion_oilrefinery_air = as.vector(DIV_ch4_noncombustion_oilrefinery_air) %*% L
-
-write.csv(TIV_ch4_noncombustion_oilrefinery_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_ch4_CO2eq_noncombustion_oilrefinery_air_",year_current,"_pxp.csv"))
-
-TIV_breakdown_ch4_noncombustion_oilrefinery_air = as.vector(DIV_ch4_noncombustion_oilrefinery_air) * L
-TIV_breakdown_ch4_noncombustion_oilrefinery_air_w_labels = cbind(Exiobase_T_labels_pxp, TIV_breakdown_ch4_noncombustion_oilrefinery_air)
-TIV_country_breakdown_ch4_noncombustion_oilrefinery_air_w_labels = t(TIV_breakdown_ch4_noncombustion_oilrefinery_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_ch4_noncombustion_oilrefinery_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_noncombustion_oilrefinery_air_",year_current,"_pxp.csv"))
-
-
-# CH4 agriculture air
-CH4_agriculture_air = satellite[427,]
-#saveRDS(CH4_agriculture_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/ch4_agriculture_air_",year_current,".rds"))
-CH4_agriculture_air = CH4_agriculture_air*28
-#saveRDS(CH4_agriculture_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/ch4_CO2eq_agriculture_air_",year_current,".rds"))
-DIV_ch4_agriculture_air = CH4_agriculture_air/total_output
-DIV_ch4_agriculture_air[is.na(DIV_ch4_agriculture_air)]=0
-DIV_ch4_agriculture_air[DIV_ch4_agriculture_air == Inf]<-0
-#saveRDS(DIV_ch4_agriculture_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/DIV_ch4_CO2eq_agriculture_air_",year_current,".rds"))
-TIV_ch4_agriculture_air = as.vector(DIV_ch4_agriculture_air) %*% L
-
-write.csv(TIV_ch4_agriculture_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_ch4_CO2eq_agriculture_air_",year_current,"_pxp.csv"))
-
-TIV_breakdown_ch4_agriculture_air = as.vector(DIV_ch4_agriculture_air) * L
-TIV_breakdown_ch4_agriculture_air_w_labels = cbind(Exiobase_T_labels_pxp, TIV_breakdown_ch4_agriculture_air)
-TIV_country_breakdown_ch4_agriculture_air_w_labels = t(TIV_breakdown_ch4_agriculture_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_ch4_agriculture_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_agriculture_air_",year_current,"_pxp.csv"))
-
-
-# CH4 waste air
-CH4_waste_air = satellite[436,]
-#saveRDS(CH4_waste_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/ch4_waste_air_",year_current,".rds"))
-CH4_waste_air = CH4_waste_air*28
-#saveRDS(CH4_waste_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/ch4_CO2eq_waste_air_",year_current,".rds"))
-DIV_ch4_waste_air = CH4_waste_air/total_output
-DIV_ch4_waste_air[is.na(DIV_ch4_waste_air)]=0
-DIV_ch4_waste_air[DIV_ch4_waste_air == Inf]<-0
-#saveRDS(DIV_ch4_waste_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/DIV_ch4_CO2eq_waste_air_",year_current,".rds"))
-TIV_ch4_waste_air = as.vector(DIV_ch4_waste_air) %*% L
-
-write.csv(TIV_ch4_waste_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_ch4_CO2eq_waste_air_",year_current,"_pxp.csv"))
-
-TIV_breakdown_ch4_waste_air = as.vector(DIV_ch4_waste_air) * L
-TIV_breakdown_ch4_waste_air_w_labels = cbind(Exiobase_T_labels_pxp, TIV_breakdown_ch4_waste_air)
-TIV_country_breakdown_ch4_waste_air_w_labels = t(TIV_breakdown_ch4_waste_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_ch4_waste_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_waste_air_",year_current,"_pxp.csv"))
-
-
-# N2O combustion air
-N2O_combustion_air = satellite[26,]
-#saveRDS(N2O_combustion_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/n2o_combustion_air_",year_current,".rds"))
-N2O_combustion_air = N2O_combustion_air*265
-#saveRDS(N2O_combustion_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/n2o_CO2eq_combustion_air_",year_current,".rds"))
-DIV_n2o_combustion_air = N2O_combustion_air/total_output
-DIV_n2o_combustion_air[is.na(DIV_n2o_combustion_air)]=0
-DIV_n2o_combustion_air[DIV_n2o_combustion_air == Inf]<-0
-#saveRDS(DIV_n2o_combustion_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/DIV_n2o_CO2eq_combustion_air_",year_current,".rds"))
-TIV_n2o_combustion_air = as.vector(DIV_n2o_combustion_air) %*% L
-
-#saveRDS(TIV_n2o_combustion_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_n2o_CO2eq_combustion_air_",year_current,".rds"))
-write.csv(TIV_n2o_combustion_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_n2o_CO2eq_combustion_air_",year_current,"_pxp.csv"))
-
-TIV_breakdown_n2o_combustion_air = as.vector(DIV_n2o_combustion_air) * L
-TIV_breakdown_n2o_combustion_air_w_labels = cbind(Exiobase_T_labels_pxp, TIV_breakdown_n2o_combustion_air)
-TIV_country_breakdown_n2o_combustion_air_w_labels = t(TIV_breakdown_n2o_combustion_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_n2o_combustion_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_n2o_CO2eq_combustion_air_",year_current,"_pxp.csv"))
-
-
-# N2O agriculture air
-N2O_agriculture_air = satellite[430,]
-#saveRDS(N2O_agriculture_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/n2o_agriculture_air_",year_current,".rds"))
-N2O_agriculture_air = N2O_agriculture_air*265
-#saveRDS(N2O_agriculture_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/n2o_CO2eq_agriculture_air_",year_current,".rds"))
-DIV_n2o_agriculture_air = N2O_agriculture_air/total_output
-DIV_n2o_agriculture_air[is.na(DIV_n2o_agriculture_air)]=0
-DIV_n2o_agriculture_air[DIV_n2o_agriculture_air == Inf]<-0
-#saveRDS(DIV_n2o_agriculture_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/DIV_n2o_CO2eq_agriculture_air_",year_current,".rds"))
-TIV_n2o_agriculture_air = as.vector(DIV_n2o_agriculture_air) %*% L
-
-write.csv(TIV_n2o_agriculture_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_n2o_CO2eq_agriculture_air_",year_current,"_pxp.csv"))
-
-TIV_breakdown_n2o_agriculture_air = as.vector(DIV_n2o_agriculture_air) * L
-TIV_breakdown_n2o_agriculture_air_w_labels = cbind(Exiobase_T_labels_pxp, TIV_breakdown_n2o_agriculture_air)
-TIV_country_breakdown_n2o_agriculture_air_w_labels = t(TIV_breakdown_n2o_agriculture_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_n2o_agriculture_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_n2o_CO2eq_agriculture_air_",year_current,"_pxp.csv"))
-
-
-# SF6 air
-SF6_air = satellite[424,]
-#write.csv(SF6_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/sf6_air_",year_current,"_pxp.csv"))
-SF6_air = SF6_air*23500
-#write.csv(SF6_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/sf6_CO2eq_air_",year_current,"_pxp.csv"))
-DIV_sf6_air = SF6_air/total_output
-DIV_sf6_air[is.na(DIV_sf6_air)]=0
-DIV_sf6_air[DIV_sf6_air == Inf]<-0
-#write.csv(DIV_sf6_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/DIV_sf6_CO2eq_air_",year_current,"_pxp.csv"))
-TIV_sf6_air = as.vector(DIV_sf6_air) %*% L
-
-write.csv(TIV_sf6_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_sf6_CO2eq_air_",year_current,"_pxp.csv"))
-
-TIV_breakdown_sf6_air = as.vector(DIV_sf6_air) * L
-TIV_breakdown_sf6_air_w_labels = cbind(Exiobase_T_labels_pxp, TIV_breakdown_sf6_air)
-TIV_country_breakdown_sf6_air_w_labels = t(TIV_breakdown_sf6_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_sf6_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_sf6_CO2eq_air_",year_current,"_pxp.csv"))
-
-
-# HFC air
-HFC_air = satellite[425,]
-#write.csv(HFC_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/hfc_CO2eq_air_",year_current,"_pxp.csv"))
-DIV_hfc_air = HFC_air/total_output
-DIV_hfc_air[is.na(DIV_hfc_air)]=0
-DIV_hfc_air[DIV_hfc_air == Inf]<-0
-#write.csv(DIV_hfc_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/DIV_hfc_CO2eq_air_",year_current,"_pxp.csv"))
-TIV_hfc_air = as.vector(DIV_hfc_air) %*% L
-
-write.csv(TIV_hfc_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_hfc_CO2eq_air_",year_current,"_pxp.csv"))
-
-TIV_breakdown_hfc_air = as.vector(DIV_hfc_air) * L
-TIV_breakdown_hfc_air_w_labels = cbind(Exiobase_T_labels_pxp, TIV_breakdown_hfc_air)
-TIV_country_breakdown_hfc_air_w_labels = t(TIV_breakdown_hfc_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_hfc_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_hfc_CO2eq_air_",year_current,"_pxp.csv"))
-
-
-# PFC air
-PFC_air = satellite[426,]
-#write.csv(PFC_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/satellite/pfc_CO2eq_air_",year_current,"_pxp.csv"))
-DIV_pfc_air = PFC_air/total_output
-DIV_pfc_air[is.na(DIV_pfc_air)]=0
-DIV_pfc_air[DIV_pfc_air == Inf]<-0
-#write.csv(DIV_pfc_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/DIV_pfc_CO2eq_air_",year_current,"_pxp.csv"))
-TIV_pfc_air = as.vector(DIV_pfc_air) %*% L
-
-write.csv(TIV_pfc_air, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_pfc_CO2eq_air_",year_current,"_pxp.csv"))
-
-TIV_breakdown_pfc_air = as.vector(DIV_pfc_air) * L
-TIV_breakdown_pfc_air_w_labels = cbind(Exiobase_T_labels_pxp, TIV_breakdown_pfc_air)
-TIV_country_breakdown_pfc_air_w_labels = t(TIV_breakdown_pfc_air_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_pfc_air_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_pfc_CO2eq_air_",year_current,"_pxp.csv"))
-
-
-# energy carrier use
-energy_carrier_use = satellite[470,]
-DIV_e_u = energy_carrier_use/total_output
-DIV_e_u[is.na(DIV_e_u)]=0
-DIV_e_u[DIV_e_u == Inf]<-0
-TIV_e_u = as.vector(DIV_e_u) %*% L
-
-#saveRDS(TIV_e_u, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_energy_carrier_use_",year_current,".rds"))
-write.csv(TIV_e_u, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_energy_carrier_use_",year_current,"_pxp.csv"))
-
-TIV_breakdown_e_u = as.vector(DIV_e_u) * L
-TIV_breakdown_e_u_w_labels = cbind(Exiobase_T_labels_pxp, TIV_breakdown_e_u)
-TIV_country_breakdown_e_u_w_labels = t(TIV_breakdown_e_u_w_labels %>%
- group_by(V1) %>%
- select(-X,-V2) %>%
- summarise_all(funs(sum)))
-
-write.csv(TIV_country_breakdown_e_u_w_labels, paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_energy_carrier_use_",year_current,"_pxp.csv"))
-}</code></pre>
</div>
<div id="isf" class="section level1">
<h1>isf</h1>
-<pre class="r"><code># income-stratified-footprints directory
-data_dir_income_stratified_footprints = paste("/",file.path("data","metab","income-stratified-footprints", fsep=.Platform$file.sep),sep="")
-
-
-################################################### !!!! method 1 - PPS HH - RENT NOT MAPPED TO EXIOBASE !!!! ###########################################
-##########################################################################################################################################################
-##########################################################################################################################################################
-
-#### IF YOU WANT THE RESULTS USING PPS PER ADULT EQUIVALENT - FILTER 'MEAN EXPENDITURE BY QUINTILE' BELOW FOR (unit == "PPS_AE") AND MAKE SURE TO UNCOMMENT
-#### THE LINE SAVING IT AT THE END (AND COMMENT OUT THE LINE SAVING THE 'PPS HH' VERSION) - for both ixi and pxp Exiobase versions
-
-## Eurostat Household Budget Survey
-
-# load 'mean expenditure by quintile' data
-hbs_exp_t133 = read_csv(paste0(data_dir_income_stratified_footprints, "/data/hbs_exp_t133.csv"))
-# rename and arrange by country
-mean_expenditure_by_quintile = hbs_exp_t133 %>%
- rename(geo = 3, quintile = "quantile") %>%
- arrange(geo)
-
-# load 'mean expenditure by quintile and coicop' data
-hbs_str_t223 = read_csv(paste0(data_dir_income_stratified_footprints, "/data/hbs_str_t223.csv"))
-# rename and arrange by country
-mean_expenditure_by_coicop_sector = hbs_str_t223 %>%
- rename(geo = 4, quintile = "quantile") %>%
- arrange(geo)
-
-# create long data set
-mean_expenditure_by_quintile_long = mean_expenditure_by_quintile %>%
- filter(!(quintile %in% c("UNK","TOTAL"))) %>%
- filter(!(geo %in% c("EA",
- "EA12",
- "EA13",
- "EA17",
- "EA18",
- "EA19",
- "EEA28",
- "EEA30_2007",
- "EFTA",
- "EU15",
- "EU25",
- "EU27_2007",
- "EU27_2020",
- "EU28"))) %>%
- gather(year,pps,-quintile,-unit,-geo) %>%
- rename(mean_expenditure = pps)
-
-write_csv(mean_expenditure_by_quintile_long, paste0(data_dir_income_stratified_footprints, "/mean_expenditure_by_quintile_long.csv"))
-
-# create long data sets for both
-mean_expenditure_by_quintile_long = mean_expenditure_by_quintile %>%
- filter(unit == "PPS_HH") %>% # filter 'mean expenditure by quintile' in PPS per HouseHold
- filter(!(quintile %in% c("UNK","TOTAL"))) %>% # filter out unknown and total expenditure
- select(-unit) %>%
- gather(year,pps,-quintile,-geo)
-
-mean_expenditure_by_coicop_sector_long = mean_expenditure_by_coicop_sector %>%
- filter(!(quintile %in% c("UNK","TOTAL"))) %>% # filter out unknown and total expenditure
- select(-unit) %>%
- gather(year,pm,-quintile,-coicop,-geo) %>%
- mutate(coicop = dplyr::recode(coicop, "CP041" = "rent",
- "CP042" = "rent")) %>%
- group_by(geo,quintile,coicop,year) %>%
- mutate(pm = parse_number(pm),
- pm = as.numeric(pm)) %>%
- summarise(pm = sum(pm, na.rm = TRUE)) %>%
- ungroup() %>%
- mutate(pm = ifelse(geo == "DE" & year == 2005 & quintile == "QUINTILE1" &
- coicop == "CP072", 92-21-14,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2005 & quintile == "QUINTILE2" &
- coicop == "CP072", 108-22-12,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2005 & quintile == "QUINTILE3" &
- coicop == "CP072", 124-32-11,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2005 & quintile == "QUINTILE4" &
- coicop == "CP072", 133-43-10,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2005 & quintile == "QUINTILE5" &
- coicop == "CP072", 162-81-11,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2010 & quintile == "QUINTILE1" &
- coicop == "CP044", 412-4-78-322,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2010 & quintile == "QUINTILE2" &
- coicop == "CP044", 355-5-68-265,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2010 & quintile == "QUINTILE3" &
- coicop == "CP044", 325-8-64-229,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2010 & quintile == "QUINTILE4" &
- coicop == "CP044", 300-9-58-204,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2010 & quintile == "QUINTILE5" &
- coicop == "CP044", 249-10-46-167,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2015 & quintile == "QUINTILE1" &
- coicop == "CP044", 433-3-82-340,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2015 & quintile == "QUINTILE2" &
- coicop == "CP044", 376-6-70-284,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2015 & quintile == "QUINTILE3" &
- coicop == "CP044", 351-9-67-251,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2015 & quintile == "QUINTILE4" &
- coicop == "CP044", 326-10-61-228,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2015 & quintile == "QUINTILE5" &
- coicop == "CP044", 280-9-49-195,pm))
-## In the code above, I collapse (sum) the two 'rent' HBS sectors 'CP041' and 'CP042' to create a
-## single 'rent' sector so as to allocate all rent to 'Real-estate services' in Exiobase.
-
-
-# join the HBS expenditure tables together
-join_expenditures = mean_expenditure_by_coicop_sector_long %>%
- left_join(mean_expenditure_by_quintile_long, by = c("geo","quintile","year")) %>%
- mutate(pps = as.numeric(pps),
- pm = as.numeric(pm),
- pps_coicop = pm*(pps/1000))
-
-
-
-################################################### !!!! method 1 - IXI version - PPS HH NO RENT !!!! ####################################################
-##########################################################################################################################################################
-##########################################################################################################################################################
-
-## Exiobase - ixi version
-
-years_exb_ixi = c(2005,2010,2015)
-
-disaggregated_final_demand = NULL
-
-TIVs = NULL
-
-domestic_TIVs = NULL
-
-europe_TIVs = NULL
-
-national_fp = NULL
-
-national_territorial = NULL
-
-for (i in years_exb_ixi){
- year_current = i
-
- Exiobase_FD = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/FD_",year_current,"_ixi.csv"))[,-1]
-
- # select household final demand vectors for study countries
-
- AT = Exiobase_FD[,1]
- BE = Exiobase_FD[,8]
- BG = Exiobase_FD[,15]
- CY = Exiobase_FD[,22]
- CZ = Exiobase_FD[,29]
- DE = Exiobase_FD[,36]
- DK = Exiobase_FD[,43]
- EE = Exiobase_FD[,50]
- EL = Exiobase_FD[,78]
- ES = Exiobase_FD[,57]
- FI = Exiobase_FD[,64]
- FR = Exiobase_FD[,71]
- HR = Exiobase_FD[,85]
- HU = Exiobase_FD[,92]
- IE = Exiobase_FD[,99]
- IT = Exiobase_FD[,106]
- LT = Exiobase_FD[,113]
- LU = Exiobase_FD[,120]
- LV = Exiobase_FD[,127]
- MT = Exiobase_FD[,134]
- NL = Exiobase_FD[,141]
- NO = Exiobase_FD[,288]
- PL = Exiobase_FD[,148]
- PT = Exiobase_FD[,155]
- RO = Exiobase_FD[,162]
- SE = Exiobase_FD[,169]
- SI = Exiobase_FD[,176]
- SK = Exiobase_FD[,183]
- TR = Exiobase_FD[,274]
- UK = Exiobase_FD[,190]
-
- Eurostat_countries = cbind(AT,BE,BG,CY,CZ,DE,DK,EE,EL,ES,FI,FR,HR,HU,IE,IT,LT,LU,LV,MT,NL,NO,PL,PT,RO,SE,SI,SK,TR,UK)
-
- # labels
-
- Exiobase_T_labels = read.csv(paste0(data_dir_income_stratified_footprints, "/data/Exiobase_T_labels_ixi_w_coicop_mapping_no_rent.csv")) %>%
- mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"))
-
-
- # hh fd with production sector labels
-
- hh_fd_with_production_sector_labels = cbind(Exiobase_T_labels,Eurostat_countries) %>% rename(geo = V1, sector = V2)
-
- # assumption of same purchase structure between quintiles of domestic and foreign final demand
-
- # replicate each cell of each country's hh final demand as many times as there are income groups in the HBS data - in this preliminary case:5
-
- cells_repeat = data.frame(hh_fd_with_production_sector_labels %>% slice(rep(1:n(), each = 5)))
-
- quintiles = data.frame(rep(c("QUINTILE1","QUINTILE2","QUINTILE3","QUINTILE4","QUINTILE5"),163)) %>% rename_at(1,~"quintile")
-
- replicated = cbind(cells_repeat,quintiles) %>% rename(country_of_production = geo)
-
- # make fd data long
-
- replicated_long = replicated %>% gather(geo, value,-sector,-coicop,-quintile,-five_sectors,-country_of_production)
-
- year = as.character(rep(year_current,nrow(replicated_long)))
-
- replicated_long = cbind(year,replicated_long)
-
-
- disaggregated_final_demand = rbind(disaggregated_final_demand, replicated_long)
-
-
- # TIVs
-
- # CO2 - combustion - air
-
- Exiobase_TIV_co2_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_co2_combustion_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_co2_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_combustion_air_", year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CO2_domestic)
-
- Exiobase_TIV_europe_breakdown_co2_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_combustion_air_", year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CO2_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_CO2_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CO2_europe,TIV_CO2_not_europe)
-
- # CO2 - noncombustion - cement - air
-
- Exiobase_TIV_co2_noncombustion_cement_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_co2_noncombustion_cement_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_co2_noncombustion_cement_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_noncombustion_cement_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CO2_noncombustion_cement_domestic)
-
- Exiobase_TIV_europe_breakdown_co2_noncombustion_cement_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_noncombustion_cement_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CO2_noncombustion_cement_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_CO2_noncombustion_cement_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CO2_noncombustion_cement_europe,TIV_CO2_noncombustion_cement_not_europe)
-
- # CO2 - noncombustion - lime - air
-
- Exiobase_TIV_co2_noncombustion_lime_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_co2_noncombustion_lime_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_co2_noncombustion_lime_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_noncombustion_lime_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CO2_noncombustion_lime_domestic)
-
- Exiobase_TIV_europe_breakdown_co2_noncombustion_lime_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_noncombustion_lime_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CO2_noncombustion_lime_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_CO2_noncombustion_lime_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CO2_noncombustion_lime_europe,TIV_CO2_noncombustion_lime_not_europe)
-
- # CO2 - agriculture - peat decay - air
-
- Exiobase_TIV_co2_agriculture_peatdecay_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_co2_agriculture_peatdecay_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_co2_agriculture_peatdecay_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_agriculture_peatdecay_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CO2_agriculture_peatdecay_domestic)
-
- Exiobase_TIV_europe_breakdown_co2_agriculture_peatdecay_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_agriculture_peatdecay_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CO2_agriculture_peatdecay_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_CO2_agriculture_peatdecay_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CO2_agriculture_peatdecay_europe,TIV_CO2_agriculture_peatdecay_not_europe)
-
- # CO2 - waste - biogenic - air
-
- Exiobase_TIV_co2_waste_biogenic_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_co2_biogenic_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_co2_waste_biogenic_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_biogenic_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CO2_waste_biogenic_domestic)
-
- Exiobase_TIV_europe_breakdown_co2_waste_biogenic_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_biogenic_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CO2_waste_biogenic_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_CO2_waste_biogenic_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CO2_waste_biogenic_europe,TIV_CO2_waste_biogenic_not_europe)
-
- # CO2 - waste - fossil - air
-
- Exiobase_TIV_co2_waste_fossil_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_co2_waste_fossil_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_co2_waste_fossil_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_waste_fossil_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CO2_waste_fossil_domestic)
-
- Exiobase_TIV_europe_breakdown_co2_waste_fossil_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_waste_fossil_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CO2_waste_fossil_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_CO2_waste_fossil_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CO2_waste_fossil_europe,TIV_CO2_waste_fossil_not_europe)
-
-
-
- # CH4 - combustion -air
-
- Exiobase_TIV_ch4_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_combustion_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_combustion_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_combustion_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_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_CH4_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_europe,TIV_CH4_not_europe)
-
- # CH4 - noncombustion - gas - air
-
- Exiobase_TIV_ch4_noncombustion_gas_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_noncombustion_gas_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_noncombustion_gas_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_gas_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_noncombustion_gas_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_gas_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_gas_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_noncombustion_gas_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_CH4_noncombustion_gas_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_noncombustion_gas_europe,TIV_CH4_noncombustion_gas_not_europe)
-
- # CH4 - noncombustion - oil - air
-
- Exiobase_TIV_ch4_noncombustion_oil_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_noncombustion_oil_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_noncombustion_oil_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_oil_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_noncombustion_oil_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_oil_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_oil_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_noncombustion_oil_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_CH4_noncombustion_oil_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_noncombustion_oil_europe,TIV_CH4_noncombustion_oil_not_europe)
-
- # CH4 - noncombustion - anthracite - air
-
- Exiobase_TIV_ch4_noncombustion_anthracite_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_noncombustion_anthracite_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_noncombustion_anthracite_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_anthracite_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_noncombustion_anthracite_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_anthracite_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_anthracite_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_noncombustion_anthracite_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_CH4_noncombustion_anthracite_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_noncombustion_anthracite_europe,TIV_CH4_noncombustion_anthracite_not_europe)
-
- # CH4 - noncombustion - bituminouscoal - air
-
- Exiobase_TIV_ch4_noncombustion_bituminouscoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_noncombustion_bituminouscoal_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_noncombustion_bituminouscoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_bituminouscoal_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_noncombustion_bituminouscoal_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_bituminouscoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_bituminouscoal_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_noncombustion_bituminouscoal_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_CH4_noncombustion_bituminouscoal_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_noncombustion_bituminouscoal_europe,TIV_CH4_noncombustion_bituminouscoal_not_europe)
-
- # CH4 - noncombustion - cokingcoal - air
-
- Exiobase_TIV_ch4_noncombustion_cokingcoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_noncombustion_cokingcoal_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_noncombustion_cokingcoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_cokingcoal_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_noncombustion_cokingcoal_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_cokingcoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_cokingcoal_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_noncombustion_cokingcoal_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_CH4_noncombustion_cokingcoal_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_noncombustion_cokingcoal_europe,TIV_CH4_noncombustion_cokingcoal_not_europe)
-
- # CH4 - noncombustion - lignite - air
-
- Exiobase_TIV_ch4_noncombustion_lignite_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_noncombustion_lignite_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_noncombustion_lignite_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_lignite_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_noncombustion_lignite_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_lignite_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_lignite_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_noncombustion_lignite_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_CH4_noncombustion_lignite_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_noncombustion_lignite_europe,TIV_CH4_noncombustion_lignite_not_europe)
-
- # CH4 - noncombustion - subbituminouscoal - air
-
- Exiobase_TIV_ch4_noncombustion_subbituminouscoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_noncombustion_subbituminouscoal_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_noncombustion_subbituminouscoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_subbituminouscoal_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_noncombustion_subbituminouscoal_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_subbituminouscoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_subbituminouscoal_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_noncombustion_subbituminouscoal_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_CH4_noncombustion_subbituminouscoal_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_noncombustion_subbituminouscoal_europe,TIV_CH4_noncombustion_subbituminouscoal_not_europe)
-
- # CH4 - noncombustion - oilrefinery - air
-
- Exiobase_TIV_ch4_noncombustion_oilrefinery_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_noncombustion_oilrefinery_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_noncombustion_oilrefinery_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_oilrefinery_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_noncombustion_oilrefinery_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_oilrefinery_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_oilrefinery_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_noncombustion_oilrefinery_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_CH4_noncombustion_oilrefinery_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_noncombustion_oilrefinery_europe,TIV_CH4_noncombustion_oilrefinery_not_europe)
-
- # CH4 - agriculture - air
-
- Exiobase_TIV_ch4_agriculture_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_agriculture_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_agriculture_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_agriculture_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_agriculture_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_agriculture_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_agriculture_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_agriculture_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_CH4_agriculture_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_agriculture_europe,TIV_CH4_agriculture_not_europe)
-
- # CH4 - waste - air
-
- Exiobase_TIV_ch4_waste_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_waste_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_waste_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_waste_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_waste_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_waste_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_waste_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_waste_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_CH4_waste_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_waste_europe,TIV_CH4_waste_not_europe)
-
-
- # N2O - combustion - air
-
- Exiobase_TIV_n2o_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_n2o_CO2eq_combustion_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_n2o_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_n2o_CO2eq_combustion_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_N2O_domestic)
-
- Exiobase_TIV_europe_breakdown_n2o_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_n2o_CO2eq_combustion_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_N2O_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_N2O_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_N2O_europe,TIV_N2O_not_europe)
-
- # N2O - agriculture - air
-
- Exiobase_TIV_n2o_agriculture_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_n2o_CO2eq_agriculture_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_n2o_agriculture_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_n2o_CO2eq_agriculture_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_N2O_agriculture_domestic)
-
- Exiobase_TIV_europe_breakdown_n2o_agriculture_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_n2o_CO2eq_agriculture_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_N2O_agriculture_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_N2O_agriculture_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_N2O_agriculture_europe,TIV_N2O_agriculture_not_europe)
-
- # SF6 - air
-
- Exiobase_TIV_sf6_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_sf6_CO2eq_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_sf6_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_sf6_CO2eq_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_SF6_domestic)
-
- Exiobase_TIV_europe_breakdown_sf6_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_sf6_CO2eq_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_SF6_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_SF6_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_SF6_europe,TIV_SF6_not_europe)
-
- # HFC - air
-
- Exiobase_TIV_hfc_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_hfc_CO2eq_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_hfc_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_hfc_CO2eq_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_HFC_domestic)
-
- Exiobase_TIV_europe_breakdown_hfc_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_hfc_CO2eq_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_HFC_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_HFC_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_HFC_europe,TIV_HFC_not_europe)
-
- # PFC - air
-
- Exiobase_TIV_pfc_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_pfc_CO2eq_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_pfc_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_pfc_CO2eq_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_PFC_domestic)
-
- Exiobase_TIV_europe_breakdown_pfc_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_pfc_CO2eq_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_PFC_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_PFC_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_PFC_europe,TIV_PFC_not_europe)
-
- # Energy use
-
- Exiobase_TIV_energy_use_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_energy_carrier_use_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_energy_use_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_energy_carrier_use_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_energy_domestic)
-
- Exiobase_TIV_europe_breakdown_energy_use_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_energy_carrier_use_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_energy_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_energy_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- 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,
- t(Exiobase_TIV_co2_bp),
- t(Exiobase_TIV_co2_noncombustion_cement_bp),
- t(Exiobase_TIV_co2_noncombustion_lime_bp),
- t(Exiobase_TIV_co2_agriculture_peatdecay_bp),
- t(Exiobase_TIV_co2_waste_biogenic_bp),
- t(Exiobase_TIV_co2_waste_fossil_bp),
- t(Exiobase_TIV_ch4_bp),
- t(Exiobase_TIV_ch4_noncombustion_gas_bp),
- t(Exiobase_TIV_ch4_noncombustion_oil_bp),
- t(Exiobase_TIV_ch4_noncombustion_anthracite_bp),
- t(Exiobase_TIV_ch4_noncombustion_bituminouscoal_bp),
- t(Exiobase_TIV_ch4_noncombustion_cokingcoal_bp),
- t(Exiobase_TIV_ch4_noncombustion_lignite_bp),
- t(Exiobase_TIV_ch4_noncombustion_subbituminouscoal_bp),
- t(Exiobase_TIV_ch4_noncombustion_oilrefinery_bp),
- t(Exiobase_TIV_ch4_agriculture_bp),
- t(Exiobase_TIV_ch4_waste_bp),
- t(Exiobase_TIV_n2o_bp),
- t(Exiobase_TIV_n2o_agriculture_bp),
- 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)) %>%
- 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)",
- TIV_CO2_agriculture_peatdecay = "t(Exiobase_TIV_co2_agriculture_peatdecay_bp)",
- TIV_CO2_waste_biogenic = "t(Exiobase_TIV_co2_waste_biogenic_bp)",
- TIV_CO2_waste_fossil = "t(Exiobase_TIV_co2_waste_fossil_bp)",
- TIV_CH4 = "t(Exiobase_TIV_ch4_bp)",
- TIV_CH4_noncombustion_gas = "t(Exiobase_TIV_ch4_noncombustion_gas_bp)",
- TIV_CH4_noncombustion_oil = "t(Exiobase_TIV_ch4_noncombustion_oil_bp)",
- TIV_CH4_noncombustion_anthracite = "t(Exiobase_TIV_ch4_noncombustion_anthracite_bp)",
- TIV_CH4_noncombustion_bituminouscoal = "t(Exiobase_TIV_ch4_noncombustion_bituminouscoal_bp)",
- TIV_CH4_noncombustion_cokingcoal = "t(Exiobase_TIV_ch4_noncombustion_cokingcoal_bp)",
- TIV_CH4_noncombustion_lignite = "t(Exiobase_TIV_ch4_noncombustion_lignite_bp)",
- TIV_CH4_noncombustion_subbituminouscoal = "t(Exiobase_TIV_ch4_noncombustion_subbituminouscoal_bp)",
- TIV_CH4_noncombustion_oilrefinery = "t(Exiobase_TIV_ch4_noncombustion_oilrefinery_bp)",
- TIV_CH4_agriculture = "t(Exiobase_TIV_ch4_agriculture_bp)",
- TIV_CH4_waste = "t(Exiobase_TIV_ch4_waste_bp)",
- TIV_N2O = "t(Exiobase_TIV_n2o_bp)",
- TIV_N2O_agriculture = "t(Exiobase_TIV_n2o_agriculture_bp)",
- 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)") %>%
- mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"))
-
- year = as.character(rep(year_current,nrow(TIV_with_labels)))
-
- look = cbind(year,TIV_with_labels) %>%
- rename(country_of_production = V1, sector = V2)
-
-
-
- TIVs = rbind(TIVs,look)
-
-
- # join domestic_TIVs with labels
-
- domestic_TIV_with_labels = cbind(Exiobase_T_labels,
- Exiobase_TIV_country_breakdown_co2_bp,
- Exiobase_TIV_country_breakdown_co2_noncombustion_cement_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_co2_noncombustion_lime_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_co2_agriculture_peatdecay_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_co2_waste_biogenic_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_co2_waste_fossil_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_noncombustion_gas_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_noncombustion_oil_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_noncombustion_anthracite_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_noncombustion_bituminouscoal_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_noncombustion_cokingcoal_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_noncombustion_lignite_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_noncombustion_subbituminouscoal_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_noncombustion_oilrefinery_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_agriculture_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_waste_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_n2o_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_n2o_agriculture_bp %>% select(-country),
- 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)) %>%
- mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"),
- country = dplyr::recode(country, "GR" = "EL", "GB" = "UK"))
-
- year_domestic = as.character(rep(year_current,nrow(domestic_TIV_with_labels)))
-
- look_domestic = cbind(year_domestic,domestic_TIV_with_labels) %>%
- rename(country_of_production = V1, sector = V2, geo = country, year = year_domestic) %>%
- mutate(TIV_CO2_domestic = as.numeric(TIV_CO2_domestic),
- TIV_CO2_noncombustion_cement_domestic = as.numeric(TIV_CO2_noncombustion_cement_domestic),
- TIV_CO2_noncombustion_lime_domestic = as.numeric(TIV_CO2_noncombustion_lime_domestic),
- TIV_CO2_agriculture_peatdecay_domestic = as.numeric(TIV_CO2_agriculture_peatdecay_domestic),
- TIV_CO2_waste_biogenic_domestic = as.numeric(TIV_CO2_waste_biogenic_domestic),
- TIV_CO2_waste_fossil_domestic = as.numeric(TIV_CO2_waste_fossil_domestic),
- TIV_CH4_domestic = as.numeric(TIV_CH4_domestic),
- TIV_CH4_noncombustion_gas_domestic = as.numeric(TIV_CH4_noncombustion_gas_domestic),
- TIV_CH4_noncombustion_oil_domestic = as.numeric(TIV_CH4_noncombustion_oil_domestic),
- TIV_CH4_noncombustion_anthracite_domestic = as.numeric(TIV_CH4_noncombustion_anthracite_domestic),
- TIV_CH4_noncombustion_bituminouscoal_domestic = as.numeric(TIV_CH4_noncombustion_bituminouscoal_domestic),
- TIV_CH4_noncombustion_cokingcoal_domestic = as.numeric(TIV_CH4_noncombustion_cokingcoal_domestic),
- TIV_CH4_noncombustion_lignite_domestic = as.numeric(TIV_CH4_noncombustion_lignite_domestic),
- TIV_CH4_noncombustion_subbituminouscoal_domestic = as.numeric(TIV_CH4_noncombustion_subbituminouscoal_domestic),
- TIV_CH4_noncombustion_oilrefinery_domestic = as.numeric(TIV_CH4_noncombustion_oilrefinery_domestic),
- TIV_CH4_agriculture_domestic = as.numeric(TIV_CH4_agriculture_domestic),
- TIV_CH4_waste_domestic = as.numeric(TIV_CH4_waste_domestic),
- TIV_N2O_domestic = as.numeric(TIV_N2O_domestic),
- TIV_N2O_agriculture_domestic = as.numeric(TIV_N2O_agriculture_domestic),
- 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))
-
- domestic_TIVs = rbind(domestic_TIVs, look_domestic)
-
- # european TIVs with labels
-
- europe_TIV_with_labels = cbind(Exiobase_T_labels,
- Exiobase_TIV_europe_breakdown_co2_bp,
- Exiobase_TIV_europe_breakdown_co2_noncombustion_cement_bp,
- Exiobase_TIV_europe_breakdown_co2_noncombustion_lime_bp,
- Exiobase_TIV_europe_breakdown_co2_agriculture_peatdecay_bp,
- Exiobase_TIV_europe_breakdown_co2_waste_biogenic_bp,
- Exiobase_TIV_europe_breakdown_co2_waste_fossil_bp,
- Exiobase_TIV_europe_breakdown_ch4_bp,
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_gas_bp,
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_oil_bp,
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_anthracite_bp,
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_bituminouscoal_bp,
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_cokingcoal_bp,
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_lignite_bp,
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_subbituminouscoal_bp,
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_oilrefinery_bp,
- Exiobase_TIV_europe_breakdown_ch4_agriculture_bp,
- Exiobase_TIV_europe_breakdown_ch4_waste_bp,
- Exiobase_TIV_europe_breakdown_n2o_bp,
- Exiobase_TIV_europe_breakdown_n2o_agriculture_bp,
- 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) %>%
- mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"))
-
- year_europe = as.character(rep(year_current,nrow(europe_TIV_with_labels)))
-
- look_europe = cbind(year_europe,europe_TIV_with_labels) %>%
- rename(country_of_production = V1, sector = V2, year = year_europe) %>%
- mutate(TIV_CO2_europe = as.numeric(TIV_CO2_europe),
- TIV_CO2_noncombustion_cement_europe = as.numeric(TIV_CO2_noncombustion_cement_europe),
- TIV_CO2_noncombustion_lime_europe = as.numeric(TIV_CO2_noncombustion_lime_europe),
- TIV_CO2_agriculture_peatdecay_europe = as.numeric(TIV_CO2_agriculture_peatdecay_europe),
- TIV_CO2_waste_biogenic_europe = as.numeric(TIV_CO2_waste_biogenic_europe),
- TIV_CO2_waste_fossil_europe = as.numeric(TIV_CO2_waste_fossil_europe),
- TIV_CH4_europe = as.numeric(TIV_CH4_europe),
- TIV_CH4_noncombustion_gas_europe = as.numeric(TIV_CH4_noncombustion_gas_europe),
- TIV_CH4_noncombustion_oil_europe = as.numeric(TIV_CH4_noncombustion_oil_europe),
- TIV_CH4_noncombustion_anthracite_europe = as.numeric(TIV_CH4_noncombustion_anthracite_europe),
- TIV_CH4_noncombustion_bituminouscoal_europe = as.numeric(TIV_CH4_noncombustion_bituminouscoal_europe),
- TIV_CH4_noncombustion_cokingcoal_europe = as.numeric(TIV_CH4_noncombustion_cokingcoal_europe),
- TIV_CH4_noncombustion_lignite_europe = as.numeric(TIV_CH4_noncombustion_lignite_europe),
- TIV_CH4_noncombustion_subbituminouscoal_europe = as.numeric(TIV_CH4_noncombustion_subbituminouscoal_europe),
- TIV_CH4_noncombustion_oilrefinery_europe = as.numeric(TIV_CH4_noncombustion_oilrefinery_europe),
- TIV_CH4_agriculture_europe = as.numeric(TIV_CH4_agriculture_europe),
- TIV_CH4_waste_europe = as.numeric(TIV_CH4_waste_europe),
- TIV_N2O_europe = as.numeric(TIV_N2O_europe),
- TIV_N2O_agriculture_europe = as.numeric(TIV_N2O_agriculture_europe),
- 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))
-
- europe_TIVs = rbind(europe_TIVs, look_europe)
-
-
-
- # total national footprints
-
- # FD labels
-
- Exiobase_FD_labels = as.data.frame(t(read.csv(paste0(data_dir_exiobase, "/Exiobase_FD_labels_ixi.csv")))[-1,-3]) %>%
- mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"))
-
- national_CO2_footprints = Exiobase_FD * t(Exiobase_TIV_co2_bp)
-
- national_CO2_noncombustion_cement_footprints = Exiobase_FD * t(Exiobase_TIV_co2_noncombustion_cement_bp)
-
- national_CO2_noncombustion_lime_footprints = Exiobase_FD * t(Exiobase_TIV_co2_noncombustion_lime_bp)
-
- national_CO2_agriculture_peatdecay_footprints = Exiobase_FD * t(Exiobase_TIV_co2_agriculture_peatdecay_bp)
-
- national_CO2_waste_biogenic_footprints = Exiobase_FD * t(Exiobase_TIV_co2_waste_biogenic_bp)
-
- national_CO2_waste_fossil_footprints = Exiobase_FD * t(Exiobase_TIV_co2_waste_fossil_bp)
-
- national_CH4_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_bp)
-
- national_CH4_noncombustion_gas_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_noncombustion_gas_bp)
-
- national_CH4_noncombustion_oil_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_noncombustion_oil_bp)
-
- national_CH4_noncombustion_anthracite_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_noncombustion_anthracite_bp)
-
- national_CH4_noncombustion_bituminouscoal_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_noncombustion_bituminouscoal_bp)
-
- national_CH4_noncombustion_cokingcoal_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_noncombustion_cokingcoal_bp)
-
- national_CH4_noncombustion_lignite_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_noncombustion_lignite_bp)
-
- national_CH4_noncombustion_subbituminouscoal_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_noncombustion_subbituminouscoal_bp)
-
- national_CH4_noncombustion_oilrefinery_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_noncombustion_oilrefinery_bp)
-
- national_CH4_agriculture_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_agriculture_bp)
-
- national_CH4_waste_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_waste_bp)
-
- national_N2O_footprints = Exiobase_FD * t(Exiobase_TIV_n2o_bp)
-
- national_N2O_agriculture_footprints = Exiobase_FD * t(Exiobase_TIV_n2o_agriculture_bp)
-
- national_SF6_footprints = Exiobase_FD * t(Exiobase_TIV_sf6_bp)
-
- national_HFC_footprints = Exiobase_FD * t(Exiobase_TIV_hfc_bp)
-
- national_PFC_footprints = Exiobase_FD * t(Exiobase_TIV_pfc_bp)
-
- 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
-
- national_footprints_w_labels = cbind(Exiobase_FD_labels,
- rowSums(t(national_CO2_footprints)),
- rowSums(t(national_CO2_noncombustion_cement_footprints)),
- rowSums(t(national_CO2_noncombustion_lime_footprints)),
- rowSums(t(national_CO2_agriculture_peatdecay_footprints)),
- rowSums(t(national_CO2_waste_biogenic_footprints)),
- rowSums(t(national_CO2_waste_fossil_footprints)),
- rowSums(t(national_CH4_footprints)),
- rowSums(t(national_CH4_noncombustion_gas_footprints)),
- rowSums(t(national_CH4_noncombustion_oil_footprints)),
- rowSums(t(national_CH4_noncombustion_anthracite_footprints)),
- rowSums(t(national_CH4_noncombustion_bituminouscoal_footprints)),
- rowSums(t(national_CH4_noncombustion_cokingcoal_footprints)),
- rowSums(t(national_CH4_noncombustion_lignite_footprints)),
- rowSums(t(national_CH4_noncombustion_subbituminouscoal_footprints)),
- rowSums(t(national_CH4_noncombustion_oilrefinery_footprints)),
- rowSums(t(national_CH4_agriculture_footprints)),
- rowSums(t(national_CH4_waste_footprints)),
- rowSums(t(national_N2O_footprints)),
- rowSums(t(national_N2O_agriculture_footprints)),
- 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))) %>%
- mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"))
-
- year_national_fp = as.character(rep(year_current,nrow(national_footprints_w_labels)))
-
- # direct FD emissions
-
- direct_FD_extensions = read.csv(paste0(data_dir_exiobase, "/IOT_", year_current, "_ixi/satellite/F_hh.csv", sep = ""),row.names=NULL,as.is=TRUE)[3:1115,3:345]
- direct_FD_extensions[is.na(direct_FD_extensions)]=0
- direct_FD_extensions = mapply(direct_FD_extensions, FUN = as.numeric)
- direct_FD_extensions = matrix(data=direct_FD_extensions,ncol=343,nrow=1113)
-
- direct_FD_co2 = direct_FD_extensions[24,]
- direct_FD_co2_noncombustion_cement = direct_FD_extensions[93,]
- direct_FD_co2_noncombustion_lime = direct_FD_extensions[94,]
- direct_FD_co2_agriculture_peatdecay = direct_FD_extensions[428,]
- direct_FD_co2_waste_biogenic = direct_FD_extensions[438,]
- direct_FD_co2_waste_fossil = direct_FD_extensions[439,]
- direct_FD_ch4 = direct_FD_extensions[25,]*28
- direct_FD_ch4_noncombustion_gas = direct_FD_extensions[68,]*28
- direct_FD_ch4_noncombustion_oil = direct_FD_extensions[69,]*28
- direct_FD_ch4_noncombustion_anthracite = direct_FD_extensions[70,]*28
- direct_FD_ch4_noncombustion_bituminouscoal = direct_FD_extensions[71,]*28
- direct_FD_ch4_noncombustion_cokingcoal = direct_FD_extensions[72,]*28
- direct_FD_ch4_noncombustion_lignite = direct_FD_extensions[73,]*28
- direct_FD_ch4_noncombustion_subbituminouscoal = direct_FD_extensions[74,]*28
- direct_FD_ch4_noncombustion_oilrefinery = direct_FD_extensions[75,]*28
- direct_FD_ch4_agriculture = direct_FD_extensions[427,]*28
- direct_FD_ch4_waste = direct_FD_extensions[436,]*28
- direct_FD_n2o = direct_FD_extensions[26,]*265
- direct_FD_n2o_agriculture = direct_FD_extensions[430,]*265
- direct_FD_sf6 = direct_FD_extensions[424,]*23500
- 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,
- direct_FD_co2_noncombustion_cement,
- direct_FD_co2_noncombustion_lime,
- direct_FD_co2_agriculture_peatdecay,
- direct_FD_co2_waste_biogenic,
- direct_FD_co2_waste_fossil,
- direct_FD_ch4,
- direct_FD_ch4_noncombustion_gas,
- direct_FD_ch4_noncombustion_oil,
- direct_FD_ch4_noncombustion_anthracite,
- direct_FD_ch4_noncombustion_bituminouscoal,
- direct_FD_ch4_noncombustion_cokingcoal,
- direct_FD_ch4_noncombustion_lignite,
- direct_FD_ch4_noncombustion_subbituminouscoal,
- direct_FD_ch4_noncombustion_oilrefinery,
- direct_FD_ch4_agriculture,
- direct_FD_ch4_waste,
- direct_FD_n2o,
- direct_FD_n2o_agriculture,
- 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)
-
- look_national_fp = as.data.frame(cbind(year_national_fp,
- national_footprints_w_labels,
- direct_FD_fp)) %>%
- rename(year = year_national_fp,
- geo = V1,
- fd_category = V2,
- co2 = "rowSums(t(national_CO2_footprints))",
- co2_noncombustion_cement = "rowSums(t(national_CO2_noncombustion_cement_footprints))",
- co2_noncombustion_lime = "rowSums(t(national_CO2_noncombustion_lime_footprints))",
- co2_agriculture_peatdecay = "rowSums(t(national_CO2_agriculture_peatdecay_footprints))",
- co2_waste_biogenic = "rowSums(t(national_CO2_waste_biogenic_footprints))",
- co2_waste_fossil = "rowSums(t(national_CO2_waste_fossil_footprints))",
- ch4 = "rowSums(t(national_CH4_footprints))",
- ch4_noncombustion_gas = "rowSums(t(national_CH4_noncombustion_gas_footprints))",
- ch4_noncombustion_oil = "rowSums(t(national_CH4_noncombustion_oil_footprints))",
- ch4_noncombustion_anthracite = "rowSums(t(national_CH4_noncombustion_anthracite_footprints))",
- ch4_noncombustion_bituminouscoal = "rowSums(t(national_CH4_noncombustion_bituminouscoal_footprints))",
- ch4_noncombustion_cokingcoal = "rowSums(t(national_CH4_noncombustion_cokingcoal_footprints))",
- ch4_noncombustion_lignite = "rowSums(t(national_CH4_noncombustion_lignite_footprints))",
- ch4_noncombustion_subbituminouscoal = "rowSums(t(national_CH4_noncombustion_subbituminouscoal_footprints))",
- ch4_noncombustion_oilrefinery = "rowSums(t(national_CH4_noncombustion_oilrefinery_footprints))",
- ch4_agriculture = "rowSums(t(national_CH4_agriculture_footprints))",
- ch4_waste = "rowSums(t(national_CH4_waste_footprints))",
- n2o = "rowSums(t(national_N2O_footprints))",
- n2o_agriculture = "rowSums(t(national_N2O_agriculture_footprints))",
- 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))") %>%
- select(year,
- geo,
- fd_category,
- co2,
- direct_FD_co2,
- co2_noncombustion_cement,
- direct_FD_co2_noncombustion_cement,
- co2_noncombustion_lime,
- direct_FD_co2_noncombustion_lime,
- co2_agriculture_peatdecay,
- direct_FD_co2_agriculture_peatdecay,
- co2_waste_biogenic,
- direct_FD_co2_waste_biogenic,
- co2_waste_fossil,
- direct_FD_co2_waste_fossil,
- ch4,
- direct_FD_ch4,
- ch4_noncombustion_gas,
- direct_FD_ch4_noncombustion_gas,
- ch4_noncombustion_oil,
- direct_FD_ch4_noncombustion_oil,
- ch4_noncombustion_anthracite,
- direct_FD_ch4_noncombustion_anthracite,
- ch4_noncombustion_bituminouscoal,
- direct_FD_ch4_noncombustion_bituminouscoal,
- ch4_noncombustion_cokingcoal,
- direct_FD_ch4_noncombustion_cokingcoal,
- ch4_noncombustion_lignite,
- direct_FD_ch4_noncombustion_lignite,
- ch4_noncombustion_subbituminouscoal,
- direct_FD_ch4_noncombustion_subbituminouscoal,
- ch4_noncombustion_oilrefinery,
- direct_FD_ch4_noncombustion_oilrefinery,
- ch4_agriculture,
- direct_FD_ch4_agriculture,
- ch4_waste,
- direct_FD_ch4_waste,
- n2o,
- direct_FD_n2o,
- n2o_agriculture,
- direct_FD_n2o_agriculture,
- sf6,
- direct_FD_sf6,
- hfc,
- direct_FD_hfc,
- 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)
-
-
- national_fp = rbind(national_fp, look_national_fp)
-
-
-
- # national territorial
-
- satellite = read.csv(paste0(data_dir_exiobase, "/IOT_", year_current, "_ixi/satellite/satellite_",year_current,"_ixi.csv"))[,-1]
-
-
- CO2_combustion_air = satellite[24,]
-
- CO2_noncombustion_cement_air = satellite[93,]
-
- CO2_noncombustion_lime_air = satellite[94,]
-
- CO2_agriculture_peatdecay_air = satellite[428,]
-
- CO2_waste_biogenic_air = satellite[438,]
-
- CO2_waste_fossil_air = satellite[439,]
-
- CH4_combustion_air = satellite[25,]
- CH4_combustion_air = CH4_combustion_air*28
-
- CH4_noncombustion_gas_air = satellite[68,]
- CH4_noncombustion_gas_air = CH4_noncombustion_gas_air*28
-
- CH4_noncombustion_oil_air = satellite[69,]
- CH4_noncombustion_oil_air = CH4_noncombustion_oil_air*28
-
- CH4_noncombustion_anthracite_air = satellite[70,]
- CH4_noncombustion_anthracite_air = CH4_noncombustion_anthracite_air*28
-
- CH4_noncombustion_bituminouscoal_air = satellite[71,]
- CH4_noncombustion_bituminouscoal_air = CH4_noncombustion_bituminouscoal_air*28
-
- CH4_noncombustion_cokingcoal_air = satellite[72,]
- CH4_noncombustion_cokingcoal_air = CH4_noncombustion_cokingcoal_air*28
-
- CH4_noncombustion_lignite_air = satellite[73,]
- CH4_noncombustion_lignite_air = CH4_noncombustion_lignite_air*28
-
- CH4_noncombustion_subbituminouscoal_air = satellite[74,]
- CH4_noncombustion_subbituminouscoal_air = CH4_noncombustion_subbituminouscoal_air*28
-
- CH4_noncombustion_oilrefinery_air = satellite[75,]
- CH4_noncombustion_oilrefinery_air = CH4_noncombustion_oilrefinery_air*28
-
- CH4_agriculture_air = satellite[427,]
- CH4_agriculture_air = CH4_agriculture_air*28
-
- CH4_waste_air = satellite[436,]
- CH4_waste_air = CH4_waste_air*28
-
- N2O_combustion_air = satellite[26,]
- N2O_combustion_air = N2O_combustion_air*265
-
- N2O_agriculture_air = satellite[430,]
- N2O_agriculture_air = N2O_agriculture_air*265
-
- SF6_air = satellite[424,]
- SF6_air = SF6_air*23500
-
- HFC_air = satellite[425,]
-
- PFC_air = satellite[426,]
-
- 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),
- t(CO2_noncombustion_lime_air),
- t(CO2_agriculture_peatdecay_air),
- t(CO2_waste_biogenic_air),
- t(CO2_waste_fossil_air),
- t(CH4_combustion_air),
- t(CH4_noncombustion_gas_air),
- t(CH4_noncombustion_oil_air),
- t(CH4_noncombustion_anthracite_air),
- t(CH4_noncombustion_bituminouscoal_air),
- t(CH4_noncombustion_cokingcoal_air),
- t(CH4_noncombustion_lignite_air),
- t(CH4_noncombustion_subbituminouscoal_air),
- t(CH4_noncombustion_oilrefinery_air),
- t(CH4_agriculture_air),
- t(CH4_waste_air),
- t(N2O_combustion_air),
- t(N2O_agriculture_air),
- t(SF6_air),
- t(HFC_air),
- t(PFC_air),
- t(energy_carrier_use),
- biomass,
- ores,
- const_materials,
- t(ffuels),
- cropland,
- pasture_land,
- forest_land) %>%
- rename(CO2 = 1,
- CO2_noncombustion_cement = 2,
- CO2_noncombustion_lime = 3,
- CO2_agriculture_peatdecay = 4,
- CO2_waste_biogenic = 5,
- CO2_waste_fossil = 6,
- CH4 = 7,
- CH4_noncombustion_gas = 8,
- CH4_noncombustion_oil = 9,
- CH4_noncombustion_anthracite = 10,
- CH4_noncombustion_bituminouscoal = 11,
- CH4_noncombustion_cokingcoal = 12,
- CH4_noncombustion_lignite = 13,
- CH4_noncombustion_subbituminouscoal = 14,
- CH4_noncombustion_oilrefinery = 15,
- CH4_agriculture = 16,
- CH4_waste = 17,
- 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)
-
- year_territorial = as.character(rep(year_current,nrow(territorial)))
-
- look_territorial = as.data.frame(cbind(year_territorial,
- Exiobase_T_labels,
- territorial)) %>%
- rename(year = year_territorial,
- geo = V1,
- sector = V2) %>%
- select(-coicop,-five_sectors)
-
- national_territorial = rbind(national_territorial, look_territorial)
-
-}
-
-write.csv(national_territorial, paste0(data_dir_income_stratified_footprints, "/national_territorial_ixi.csv"))
-write_rds(national_territorial, paste0(data_dir_income_stratified_footprints, "/national_territorial_ixi.rds"))
-
-
-write.csv(national_fp, paste0(data_dir_income_stratified_footprints, "/national_fp_ixi.csv"))
-write_rds(national_fp, paste0(data_dir_income_stratified_footprints, "/national_fp_ixi.rds"))
-
-# calculate quintile shares within each sector
-shares = join_expenditures %>%
- group_by(coicop,geo,year) %>%
- mutate(share = pps_coicop/sum(pps_coicop))
-
-# pre-processing
-
-fd_exiobase = disaggregated_final_demand %>%
- left_join(shares, by = c("year","geo","coicop","quintile")) %>%
- mutate(disaggregated_fd = value*share) %>%
- select(year,geo,quintile,country_of_production,sector,coicop,disaggregated_fd) %>%
- spread(quintile,disaggregated_fd)
-
-# direct from FD - to go back to results without direct FD fp, do not run this next chunk and do not bind_rows with 'results'
-
-env_ac_pefasu_no_TR = read_csv(paste0(data_dir_income_stratified_footprints, "/data/env_ac_pefasu_1_Data.csv")) %>%
- filter(TIME == 2015) %>%
- mutate(geo = dplyr::recode(GEO,"Austria" = "AT",
- "Belgium" = "BE",
- "Cyprus" = "CY",
- "Czechia" = "CZ",
- "Denmark" = "DK",
- "Estonia" = "EE",
- "Finland" = "FI",
- "France" = "FR",
- "Germany (until 1990 former territory of the FRG)" = "DE",
- "Greece" = "EL",
- "Hungary" = "HU",
- "Ireland" = "IE",
- "Italy" = "IT",
- "Latvia" = "LV",
- "Lithuania" = "LT",
- "Luxembourg" = "LU",
- "Malta" = "MT",
- "Netherlands" = "NL",
- "Norway" = "NO",
- "Poland" = "PL",
- "Portugal" = "PT",
- "Romania" = "RO",
- "Slovakia" = "SK",
- "Slovenia" = "SI",
- "Spain" = "ES",
- "Sweden" = "SE",
- "United Kingdom" = "UK",
- "Bulgaria" = "BG",
- "Croatia" = "HR")) %>%
- select(NACE_R2,geo,Value) %>%
- mutate(Value = parse_number(Value),
- Value = as.numeric(Value)) %>%
- spread(NACE_R2,Value) %>%
- clean_names() %>%
- mutate(HH_HEAT = heating_cooling_activities_by_households/total_activities_by_households,
- HH_TRA = transport_activities_by_households/total_activities_by_households,
- HH_OTH = other_activities_by_households/total_activities_by_households) %>%
- select(geo,HH_HEAT,HH_TRA,HH_OTH)
-
-
-env_ac_pefasu_TR = env_ac_pefasu_no_TR %>%
- filter(geo == "BG") %>%
- mutate(geo = dplyr::recode(geo,
- "BG" = "TR"))
-
-env_ac_pefasu = rbind(env_ac_pefasu_no_TR,env_ac_pefasu_TR) %>%
- gather(sector,share_of_total_energy,-geo)
-
-env_ac_ainah_r2 = read_csv(paste0(data_dir_income_stratified_footprints, "/data/env_ac_ainah_r2_1_Data.csv")) %>%
- filter(TIME == 2015) %>%
- mutate(geo = dplyr::recode(GEO,"Austria" = "AT",
- "Belgium" = "BE",
- "Cyprus" = "CY",
- "Czechia" = "CZ",
- "Denmark" = "DK",
- "Estonia" = "EE",
- "Finland" = "FI",
- "France" = "FR",
- "Germany (until 1990 former territory of the FRG)" = "DE",
- "Greece" = "EL",
- "Hungary" = "HU",
- "Ireland" = "IE",
- "Italy" = "IT",
- "Latvia" = "LV",
- "Lithuania" = "LT",
- "Luxembourg" = "LU",
- "Malta" = "MT",
- "Netherlands" = "NL",
- "Norway" = "NO",
- "Poland" = "PL",
- "Portugal" = "PT",
- "Romania" = "RO",
- "Slovakia" = "SK",
- "Slovenia" = "SI",
- "Spain" = "ES",
- "Sweden" = "SE",
- "Turkey" = "TR",
- "United Kingdom" = "UK",
- "Bulgaria" = "BG",
- "Croatia" = "HR")) %>%
- select(NACE_R2,AIRPOL,geo,Value) %>%
- mutate(Value = parse_number(Value),
- Value = as.numeric(Value)) %>%
- spread(NACE_R2,Value) %>%
- clean_names() %>%
- mutate(HH_HEAT = heating_cooling_activities_by_households/total_activities_by_households,
- HH_TRA = transport_activities_by_households/total_activities_by_households,
- HH_OTH = other_activities_by_households/total_activities_by_households) %>%
- select(geo,airpol,HH_HEAT,HH_TRA,HH_OTH)
-
-
-env_ac_ainah_r2_co2 = env_ac_ainah_r2 %>%
- filter(airpol == "Carbon dioxide") %>%
- select(-airpol) %>%
- gather(sector,share_of_total_co2,-geo)
-
-env_ac_ainah_r2_ch4 = env_ac_ainah_r2 %>%
- filter(airpol == "Methane") %>%
- select(-airpol) %>%
- gather(sector,share_of_total_ch4,-geo)
-
-env_ac_ainah_r2_n2o = env_ac_ainah_r2 %>%
- filter(airpol == "Nitrous oxide") %>%
- select(-airpol) %>%
- gather(sector,share_of_total_n2o,-geo)
-
-direct_FD_fp_long = national_fp %>%
- filter(fd_category == "Final consumption expenditure by households",
- geo %in% c("AT",
- "BE", "BG", "CY", "CZ",
- "DE" , "DK" , "EE" ,
- "ES" , "FI" , "FR" ,
- "UK", "EL", "HR" ,
- "HU" , "IE" , "IT" ,
- "LT" , "LU" , "LV" ,
- "MT" , "NL" , "PL" ,
- "PT" , "TR" , "SK" ,
- "SI" , "SE" , "RO" ,
- "NO")) %>%
- select(year,geo,fd_category,direct_FD_co2,
- direct_FD_co2_noncombustion_cement,
- direct_FD_co2_noncombustion_lime,
- direct_FD_co2_agriculture_peatdecay,
- direct_FD_co2_waste_biogenic,
- direct_FD_co2_waste_fossil,
- direct_FD_ch4,
- direct_FD_ch4_noncombustion_gas,
- direct_FD_ch4_noncombustion_oil,
- direct_FD_ch4_noncombustion_anthracite,
- direct_FD_ch4_noncombustion_bituminouscoal,
- direct_FD_ch4_noncombustion_cokingcoal,
- direct_FD_ch4_noncombustion_lignite,
- direct_FD_ch4_noncombustion_subbituminouscoal,
- direct_FD_ch4_noncombustion_oilrefinery,
- direct_FD_ch4_agriculture,
- direct_FD_ch4_waste,
- direct_FD_n2o,
- direct_FD_n2o_agriculture,
- 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) %>%
- slice(rep(1:n(), each = 3))
-
-sector = rep(c("HH_HEAT","HH_TRA","HH_OTH"), nrow(direct_FD_fp_long)/3)
-
-direct_FD_fp_long_disagg = cbind(sector,direct_FD_fp_long) %>%
- mutate(coicop = ifelse(sector == "HH_TRA","CP072",
- ifelse(sector == "HH_HEAT","CP045","CP05")),
- five_sectors = ifelse(sector == "HH_TRA", "transport",
- ifelse(sector == "HH_HEAT", "shelter", "manufactured goods"))) %>%
- left_join(env_ac_ainah_r2_co2, by = c("geo","sector")) %>%
- left_join(env_ac_ainah_r2_ch4, by = c("geo","sector")) %>%
- left_join(env_ac_ainah_r2_n2o, by = c("geo","sector")) %>%
- left_join(env_ac_pefasu, by = c("geo","sector")) %>%
- mutate(direct_FD_co2 = (direct_FD_co2 +
- direct_FD_co2_noncombustion_cement +
- direct_FD_co2_noncombustion_lime +
- direct_FD_co2_agriculture_peatdecay +
- direct_FD_co2_waste_biogenic +
- direct_FD_co2_waste_fossil)*share_of_total_co2,
- direct_FD_ch4 = (direct_FD_ch4 +
- direct_FD_ch4_noncombustion_gas +
- direct_FD_ch4_noncombustion_oil +
- direct_FD_ch4_noncombustion_anthracite +
- direct_FD_ch4_noncombustion_bituminouscoal +
- direct_FD_ch4_noncombustion_cokingcoal +
- direct_FD_ch4_noncombustion_lignite +
- direct_FD_ch4_noncombustion_subbituminouscoal +
- direct_FD_ch4_noncombustion_oilrefinery +
- direct_FD_ch4_agriculture +
- direct_FD_ch4_waste)*share_of_total_ch4,
- direct_FD_n2o = (direct_FD_n2o +
- direct_FD_n2o_agriculture)*share_of_total_n2o,
- direct_FD_energy = direct_FD_energy*share_of_total_energy) %>%
- left_join(shares, by = c("year","geo","coicop")) %>%
- mutate(disaggregated_direct_FD_co2 = direct_FD_co2*share,
- disaggregated_direct_FD_ch4 = direct_FD_ch4*share,
- disaggregated_direct_FD_n2o = direct_FD_n2o*share,
- disaggregated_direct_FD_energy = direct_FD_energy*share) %>%
- select(year,geo,sector, quintile,
- coicop, five_sectors,
- disaggregated_direct_FD_co2,
- disaggregated_direct_FD_ch4,
- disaggregated_direct_FD_n2o,
- disaggregated_direct_FD_energy)
-
-direct_FD_co2 = direct_FD_fp_long_disagg %>%
- select(year,geo,sector,quintile,coicop,five_sectors,disaggregated_direct_FD_co2) %>%
- spread(quintile,disaggregated_direct_FD_co2) %>%
- rename(q1_co2 = QUINTILE1,
- q2_co2 = QUINTILE2,
- q3_co2 = QUINTILE3,
- q4_co2 = QUINTILE4,
- q5_co2 = QUINTILE5) %>%
- mutate(q1_co2_domestic = q1_co2,
- q2_co2_domestic = q2_co2,
- q3_co2_domestic = q3_co2,
- q4_co2_domestic = q4_co2,
- q5_co2_domestic = q5_co2,
- co2_total = q1_co2+q2_co2+q3_co2+q4_co2+q5_co2,
- co2_total_domestic = q1_co2_domestic+
- q2_co2_domestic+q3_co2_domestic+
- q4_co2_domestic+q5_co2_domestic)
-
-direct_FD_ch4 = direct_FD_fp_long_disagg %>%
- select(year,geo,sector,quintile,coicop,five_sectors,disaggregated_direct_FD_ch4) %>%
- spread(quintile,disaggregated_direct_FD_ch4) %>%
- rename(q1_ch4 = QUINTILE1,
- q2_ch4 = QUINTILE2,
- q3_ch4 = QUINTILE3,
- q4_ch4 = QUINTILE4,
- q5_ch4 = QUINTILE5) %>%
- mutate(q1_ch4_domestic = q1_ch4,
- q2_ch4_domestic = q2_ch4,
- q3_ch4_domestic = q3_ch4,
- q4_ch4_domestic = q4_ch4,
- q5_ch4_domestic = q5_ch4,
- ch4_total = q1_ch4+q2_ch4+q3_ch4+q4_ch4+q5_ch4,
- ch4_total_domestic = q1_ch4_domestic+
- q2_ch4_domestic+q3_ch4_domestic+
- q4_ch4_domestic+q5_ch4_domestic)
-
-
-direct_FD_n2o = direct_FD_fp_long_disagg %>%
- select(year,geo,sector,quintile,coicop,five_sectors,disaggregated_direct_FD_n2o) %>%
- spread(quintile,disaggregated_direct_FD_n2o) %>%
- rename(q1_n2o = QUINTILE1,
- q2_n2o = QUINTILE2,
- q3_n2o = QUINTILE3,
- q4_n2o = QUINTILE4,
- q5_n2o = QUINTILE5) %>%
- mutate(q1_n2o_domestic = q1_n2o,
- q2_n2o_domestic = q2_n2o,
- q3_n2o_domestic = q3_n2o,
- q4_n2o_domestic = q4_n2o,
- q5_n2o_domestic = q5_n2o,
- n2o_total = q1_n2o+q2_n2o+q3_n2o+q4_n2o+q5_n2o,
- n2o_total_domestic = q1_n2o_domestic+
- q2_n2o_domestic+q3_n2o_domestic+
- q4_n2o_domestic+q5_n2o_domestic)
-
-direct_FD_energy = direct_FD_fp_long_disagg %>%
- select(year,geo,sector,quintile,coicop,five_sectors,disaggregated_direct_FD_energy) %>%
- spread(quintile,disaggregated_direct_FD_energy) %>%
- rename(q1_energy = QUINTILE1,
- q2_energy = QUINTILE2,
- q3_energy = QUINTILE3,
- q4_energy = QUINTILE4,
- q5_energy = QUINTILE5) %>%
- mutate(q1_energy_domestic = q1_energy,
- q2_energy_domestic = q2_energy,
- q3_energy_domestic = q3_energy,
- q4_energy_domestic = q4_energy,
- q5_energy_domestic = q5_energy,
- energy_total = q1_energy+q2_energy+q3_energy+q4_energy+q5_energy,
- energy_total_domestic = q1_energy_domestic+
- q2_energy_domestic+q3_energy_domestic+
- q4_energy_domestic+q5_energy_domestic)
-
-
-direct_FD_fp_wide = direct_FD_co2 %>%
- left_join(direct_FD_ch4, by = c("year","geo",
- "sector","coicop",
- "five_sectors")) %>%
- left_join(direct_FD_n2o, by = c("year","geo",
- "sector","coicop",
- "five_sectors")) %>%
- left_join(direct_FD_energy, by = c("year","geo",
- "sector","coicop",
- "five_sectors")) %>%
- mutate(country_of_production = geo) %>%
- mutate(q1_co2eq = q1_co2 + q1_ch4 + q1_n2o,
- q2_co2eq = q2_co2 + q2_ch4 + q2_n2o,
- q3_co2eq = q3_co2 + q3_ch4 + q3_n2o,
- q4_co2eq = q4_co2 + q4_ch4 + q4_n2o,
- q5_co2eq = q5_co2 + q5_ch4 + q5_n2o,
- co2eq_total = q1_co2eq +
- q2_co2eq + q3_co2eq +
- q4_co2eq + q5_co2eq,
- q1_co2eq_domestic = q1_co2_domestic + q1_ch4_domestic + q1_n2o_domestic,
- q2_co2eq_domestic = q2_co2_domestic + q2_ch4_domestic + q2_n2o_domestic,
- q3_co2eq_domestic = q3_co2_domestic + q3_ch4_domestic + q3_n2o_domestic,
- q4_co2eq_domestic = q4_co2_domestic + q4_ch4_domestic + q4_n2o_domestic,
- q5_co2eq_domestic = q5_co2_domestic + q5_ch4_domestic + q5_n2o_domestic,
- co2eq_total_domestic = q1_co2eq_domestic +
- q2_co2eq_domestic + q3_co2eq_domestic +
- q4_co2eq_domestic + q5_co2eq_domestic) %>%
- select(-q1_ch4,
- -q2_ch4,
- -q3_ch4,
- -q4_ch4,
- -q5_ch4,
- -ch4_total,
- -q1_ch4_domestic,
- -q2_ch4_domestic,
- -q3_ch4_domestic,
- -q4_ch4_domestic,
- -q5_ch4_domestic,
- -ch4_total_domestic,
- -q1_n2o,
- -q2_n2o,
- -q3_n2o,
- -q4_n2o,
- -q5_n2o,
- -n2o_total,
- -q1_n2o_domestic,
- -q2_n2o_domestic,
- -q3_n2o_domestic,
- -q4_n2o_domestic,
- -q5_n2o_domestic,
- -n2o_total_domestic)
-
-
-
-results = fd_exiobase %>%
- left_join(TIVs, by = c("year", "country_of_production", "coicop", "sector")) %>%
- left_join(europe_TIVs, by = c("year", "country_of_production", "coicop", "sector", "five_sectors")) %>%
- left_join(domestic_TIVs, by = c("year", "geo", "country_of_production", "coicop", "sector", "five_sectors")) %>%
- transmute(year,geo,country_of_production,sector,coicop,five_sectors,
- QUINTILE1,
- QUINTILE2,
- QUINTILE3,
- QUINTILE4,
- QUINTILE5,
- fd_total = QUINTILE1+QUINTILE2+QUINTILE3+QUINTILE4+QUINTILE5,
- TIV_CO2 = TIV_CO2 +
- TIV_CO2_noncombustion_cement +
- TIV_CO2_noncombustion_lime +
- TIV_CO2_agriculture_peatdecay +
- TIV_CO2_waste_biogenic +
- TIV_CO2_waste_fossil,
- q1_co2 = QUINTILE1*TIV_CO2,
- q2_co2 = QUINTILE2*TIV_CO2,
- q3_co2 = QUINTILE3*TIV_CO2,
- q4_co2 = QUINTILE4*TIV_CO2,
- q5_co2 = QUINTILE5*TIV_CO2,
- co2_total = q1_co2+q2_co2+q3_co2+q4_co2+q5_co2,
- TIV_CO2_domestic = TIV_CO2_domestic +
- TIV_CO2_noncombustion_cement_domestic +
- TIV_CO2_noncombustion_lime_domestic +
- TIV_CO2_agriculture_peatdecay_domestic +
- TIV_CO2_waste_biogenic_domestic +
- TIV_CO2_waste_fossil_domestic,
- q1_co2_domestic = QUINTILE1*TIV_CO2_domestic,
- q2_co2_domestic = QUINTILE2*TIV_CO2_domestic,
- q3_co2_domestic = QUINTILE3*TIV_CO2_domestic,
- q4_co2_domestic = QUINTILE4*TIV_CO2_domestic,
- q5_co2_domestic = QUINTILE5*TIV_CO2_domestic,
- co2_total_domestic = q1_co2_domestic+q2_co2_domestic+q3_co2_domestic+q4_co2_domestic+q5_co2_domestic,
- TIV_CO2_europe = TIV_CO2_europe +
- TIV_CO2_noncombustion_cement_europe +
- TIV_CO2_noncombustion_lime_europe +
- TIV_CO2_agriculture_peatdecay_europe +
- TIV_CO2_waste_biogenic_europe +
- TIV_CO2_waste_fossil_europe,
- q1_co2_europe = QUINTILE1*(TIV_CO2_europe - TIV_CO2_domestic),
- q2_co2_europe = QUINTILE2*(TIV_CO2_europe - TIV_CO2_domestic),
- q3_co2_europe = QUINTILE3*(TIV_CO2_europe - TIV_CO2_domestic),
- q4_co2_europe = QUINTILE4*(TIV_CO2_europe - TIV_CO2_domestic),
- q5_co2_europe = QUINTILE5*(TIV_CO2_europe - TIV_CO2_domestic),
- co2_total_europe = q1_co2_europe+q2_co2_europe+q3_co2_europe+q4_co2_europe+q5_co2_europe,
- TIV_CO2eq = TIV_CO2 +
- TIV_CH4 +
- TIV_CH4_noncombustion_gas +
- TIV_CH4_noncombustion_oil +
- TIV_CH4_noncombustion_anthracite +
- TIV_CH4_noncombustion_bituminouscoal +
- TIV_CH4_noncombustion_cokingcoal +
- TIV_CH4_noncombustion_lignite +
- 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,
- q1_co2eq = QUINTILE1*TIV_CO2eq,
- q2_co2eq = QUINTILE2*TIV_CO2eq,
- q3_co2eq = QUINTILE3*TIV_CO2eq,
- q4_co2eq = QUINTILE4*TIV_CO2eq,
- q5_co2eq = QUINTILE5*TIV_CO2eq,
- co2eq_total = q1_co2eq + q2_co2eq + q3_co2eq + q4_co2eq + q5_co2eq,
- TIV_CO2eq_domestic = TIV_CO2_domestic +
- TIV_CH4_domestic +
- TIV_CH4_noncombustion_gas_domestic +
- TIV_CH4_noncombustion_oil_domestic +
- TIV_CH4_noncombustion_anthracite_domestic +
- TIV_CH4_noncombustion_bituminouscoal_domestic +
- TIV_CH4_noncombustion_cokingcoal_domestic +
- TIV_CH4_noncombustion_lignite_domestic +
- TIV_CH4_noncombustion_subbituminouscoal_domestic +
- TIV_CH4_noncombustion_oilrefinery_domestic +
- TIV_CH4_agriculture_domestic +
- TIV_CH4_waste_domestic +
- TIV_N2O_domestic +
- TIV_N2O_agriculture_domestic +
- TIV_SF6_domestic + TIV_HFC_domestic + TIV_PFC_domestic,
- q1_co2eq_domestic = QUINTILE1*TIV_CO2eq_domestic,
- q2_co2eq_domestic = QUINTILE2*TIV_CO2eq_domestic,
- q3_co2eq_domestic = QUINTILE3*TIV_CO2eq_domestic,
- q4_co2eq_domestic = QUINTILE4*TIV_CO2eq_domestic,
- q5_co2eq_domestic = QUINTILE5*TIV_CO2eq_domestic,
- co2eq_total_domestic = q1_co2eq_domestic + q2_co2eq_domestic + q3_co2eq_domestic + q4_co2eq_domestic + q5_co2eq_domestic,
- TIV_CO2eq_europe = TIV_CO2_europe +
- TIV_CH4_europe +
- TIV_CH4_noncombustion_gas_europe +
- TIV_CH4_noncombustion_oil_europe +
- TIV_CH4_noncombustion_anthracite_europe +
- TIV_CH4_noncombustion_bituminouscoal_europe +
- TIV_CH4_noncombustion_cokingcoal_europe +
- TIV_CH4_noncombustion_lignite_europe +
- TIV_CH4_noncombustion_subbituminouscoal_europe +
- TIV_CH4_noncombustion_oilrefinery_europe +
- TIV_CH4_agriculture_europe +
- TIV_CH4_waste_europe +
- TIV_N2O_europe +
- TIV_N2O_agriculture_europe +
- TIV_SF6_europe + TIV_HFC_europe + TIV_PFC_europe,
- q1_co2eq_europe = QUINTILE1*(TIV_CO2eq_europe - TIV_CO2eq_domestic),
- q2_co2eq_europe = QUINTILE2*(TIV_CO2eq_europe - TIV_CO2eq_domestic),
- q3_co2eq_europe = QUINTILE3*(TIV_CO2eq_europe - TIV_CO2eq_domestic),
- q4_co2eq_europe = QUINTILE4*(TIV_CO2eq_europe - TIV_CO2eq_domestic),
- q5_co2eq_europe = QUINTILE5*(TIV_CO2eq_europe - TIV_CO2eq_domestic),
- co2eq_total_europe = q1_co2eq_europe + q2_co2eq_europe + q3_co2eq_europe + q4_co2eq_europe + q5_co2eq_europe,
- TIV_energy,
- q1_energy = QUINTILE1*TIV_energy,
- q2_energy = QUINTILE2*TIV_energy,
- q3_energy = QUINTILE3*TIV_energy,
- q4_energy = QUINTILE4*TIV_energy,
- q5_energy = QUINTILE5*TIV_energy,
- energy_total = q1_energy+q2_energy+q3_energy+q4_energy+q5_energy,
- TIV_energy_domestic,
- q1_energy_domestic = QUINTILE1*TIV_energy_domestic,
- q2_energy_domestic = QUINTILE2*TIV_energy_domestic,
- q3_energy_domestic = QUINTILE3*TIV_energy_domestic,
- q4_energy_domestic = QUINTILE4*TIV_energy_domestic,
- q5_energy_domestic = QUINTILE5*TIV_energy_domestic,
- energy_total_domestic = q1_energy_domestic+q2_energy_domestic+q3_energy_domestic+q4_energy_domestic+q5_energy_domestic,
- TIV_energy_europe,
- q1_energy_europe = QUINTILE1*(TIV_energy_europe - TIV_energy_domestic),
- q2_energy_europe = QUINTILE2*(TIV_energy_europe - TIV_energy_domestic),
- 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)
-
-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"))
-
-
-### create compressed results_ixi rds file
-
-#if (!require("pacman")) install.packages("pacman")
-#pacman::p_load(tidyverse,
-# janitor,
-# here)
-
-#dat_all = read_csv(here("data/results_ixi.csv")) %>%
-# clean_names()
-
-dat_all = results_with_direct_FD_fp %>%
- clean_names()
-
-# convert sector labels to IDs
-sectors = dat_all %>%
- distinct(sector) %>%
- mutate(sector_id = row_number())
-
-#write_csv(sectors, here("data/sector_labels.csv"))
-write_csv(sectors, paste0(data_dir_income_stratified_footprints, "/sectors_method1_ixi_pps_hh.csv"))
-
-# convert aggregated sector labels to IDs
-sectors_agg = dat_all %>%
- distinct(five_sectors) %>%
- mutate(sector_agg_id = row_number())
-
-#write_csv(sectors_agg, here("data/sector_agg_labels.csv"))
-write_csv(sectors_agg, paste0(data_dir_income_stratified_footprints, "/sectors_agg_method1_ixi_pps_hh.csv"))
-
-# convert COICOP labels to IDs
-coicop = dat_all %>%
- distinct(coicop) %>%
- mutate(coicop_id = row_number())
-
-#write_csv(sectors_agg, here("data/sector_agg_labels.csv"))
-write_csv(coicop, paste0(data_dir_income_stratified_footprints, "/coicop_method1_ixi_pps_hh.csv"))
-
-# replace sector text labels with numerical IDs (save space)
-dat_compressed = dat_all %>%
- left_join(sectors, by="sector") %>%
- left_join(sectors_agg, by="five_sectors") %>%
- left_join(coicop, by = "coicop") %>%
- select(-c(sector, five_sectors,coicop))
-
-# extract sector aggregation
-sector_mapping = dat_compressed %>%
- group_by(sector_id) %>%
- summarise(sector_agg_id = first(sector_agg_id),
- coicop_id = first(coicop_id))
-
-# collapse country of origin
-dat_results = dat_compressed %>%
- select(-sector_agg_id,-coicop_id) %>%
- group_by(year, geo, sector_id) %>%
- summarise_if(is.numeric, sum, na.rm = TRUE)
-
-## extract final demand and pivot long
-cols_final_demand = c("quintile1", "quintile2", "quintile3", "quintile4", "quintile5")
-tmp_fd = dat_results %>%
- select(year, geo, sector_id, cols_final_demand) %>%
- pivot_longer(cols = cols_final_demand,
- names_to = "quintile",
- values_to = "fd_me") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-## extract co2 and pivot long
-cols_co2 = c("q1_co2", "q2_co2", "q3_co2", "q4_co2", "q5_co2")
-tmp_co2 = dat_results %>%
- select(year, geo, sector_id, cols_co2) %>%
- pivot_longer(cols = cols_co2,
- names_to = "quintile",
- values_to = "co2_kg") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-## extract co2 domestic and pivot long
-cols_co2_domestic = c("q1_co2_domestic", "q2_co2_domestic", "q3_co2_domestic", "q4_co2_domestic", "q5_co2_domestic")
-tmp_co2_domestic = dat_results %>%
- select(year, geo, sector_id, cols_co2_domestic) %>%
- pivot_longer(cols = cols_co2_domestic,
- names_to = "quintile",
- values_to = "co2_domestic_kg") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-## extract co2 europe and pivot long
-cols_co2_europe = c("q1_co2_europe", "q2_co2_europe", "q3_co2_europe", "q4_co2_europe", "q5_co2_europe")
-tmp_co2_europe = dat_results %>%
- select(year, geo, sector_id, cols_co2_europe) %>%
- pivot_longer(cols = cols_co2_europe,
- names_to = "quintile",
- values_to = "co2_europe_kg") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-
-## extract co2eq and pivot long
-cols_co2eq = c("q1_co2eq", "q2_co2eq", "q3_co2eq", "q4_co2eq", "q5_co2eq")
-tmp_co2eq = dat_results %>%
- select(year, geo, sector_id, cols_co2eq) %>%
- pivot_longer(cols = cols_co2eq,
- names_to = "quintile",
- values_to = "co2eq_kg") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-## extract co2eq domestic and pivot long
-cols_co2eq_domestic = c("q1_co2eq_domestic", "q2_co2eq_domestic", "q3_co2eq_domestic", "q4_co2eq_domestic", "q5_co2eq_domestic")
-tmp_co2eq_domestic = dat_results %>%
- select(year, geo, sector_id, cols_co2eq_domestic) %>%
- pivot_longer(cols = cols_co2eq_domestic,
- names_to = "quintile",
- values_to = "co2eq_domestic_kg") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-## extract co2eq europe and pivot long
-cols_co2eq_europe = c("q1_co2eq_europe", "q2_co2eq_europe", "q3_co2eq_europe", "q4_co2eq_europe", "q5_co2eq_europe")
-tmp_co2eq_europe = dat_results %>%
- select(year, geo, sector_id, cols_co2eq_europe) %>%
- pivot_longer(cols = cols_co2eq_europe,
- names_to = "quintile",
- values_to = "co2eq_europe_kg") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-## extract energy use and pivot long
-cols_energy = c("q1_energy","q2_energy","q3_energy","q4_energy","q5_energy")
-tmp_energy = dat_results %>%
- select(year, geo, sector_id, cols_energy) %>%
- pivot_longer(cols = cols_energy,
- names_to = "quintile",
- values_to = "energy_use_TJ") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-## extract energy domestic and pivot long
-cols_energy_domestic = c("q1_energy_domestic","q2_energy_domestic","q3_energy_domestic","q4_energy_domestic","q5_energy_domestic")
-tmp_energy_domestic = dat_results %>%
- select(year, geo, sector_id, cols_energy_domestic) %>%
- pivot_longer(cols = cols_energy_domestic,
- names_to = "quintile",
- values_to = "energy_use_domestic_TJ") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-## extract energy europe and pivot long
-cols_energy_europe = c("q1_energy_europe","q2_energy_europe","q3_energy_europe","q4_energy_europe","q5_energy_europe")
-tmp_energy_europe = dat_results %>%
- select(year, geo, sector_id, cols_energy_europe) %>%
- pivot_longer(cols = cols_energy_europe,
- names_to = "quintile",
- values_to = "energy_use_europe_TJ") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-### TODO: also convert to other indicators to this format (as blocks above)
-### TODO: left join all indicators back to "results_formated" like her with co2
-results_recombined = tmp_fd %>%
- left_join(tmp_co2, by=c("year", "geo", "sector_id", "quint")) %>%
- left_join(tmp_co2_domestic, by=c("year", "geo", "sector_id", "quint")) %>%
- left_join(tmp_co2_europe, by = c("year", "geo", "sector_id", "quint")) %>%
- left_join(tmp_co2eq, by=c("year", "geo", "sector_id", "quint")) %>%
- left_join(tmp_co2eq_domestic, by=c("year", "geo", "sector_id", "quint")) %>%
- left_join(tmp_co2eq_europe, by = c("year", "geo", "sector_id", "quint")) %>%
- left_join(tmp_energy, by=c("year", "geo", "sector_id", "quint")) %>%
- left_join(tmp_energy_domestic, by=c("year", "geo", "sector_id", "quint")) %>%
- left_join(tmp_energy_europe, by = c("year", "geo", "sector_id", "quint"))
-
-
-
-# finally re-join aggregated sector IDs
-results_formatted = results_recombined %>%
- left_join(sector_mapping, by="sector_id") %>%
- ungroup() %>%
- select(-coicop_id)
-
-#write_rds(results_formated, here("/results_formated.rds"))
-
-write.csv(results_formatted, paste0(data_dir_income_stratified_footprints, "/results_formatted_method1_ixi_pps_hh_no_rent.csv"))
-
-write_rds(results_formatted, paste0(data_dir_income_stratified_footprints, "/results_formatted_method1_ixi_pps_hh_no_rent.rds"))
-
-
-#write.csv(results_formatted, paste0(data_dir_income_stratified_footprints, "/results_formatted_method1_ixi_pps_ae.csv"))
-#write_rds(results_formatted, paste0(data_dir_income_stratified_footprints, "/results_formatted_method1_ixi_pps_ae.rds"))
-
-
-################################################### !!!! method 1 - PXP version - PPS HH NO RENT !!!! ####################################################
-##########################################################################################################################################################
-##########################################################################################################################################################
-
-
-# Exiobase - pxp version
-
-years_exb_pxp = c(2005,2010)
-
-disaggregated_final_demand = NULL
-
-TIVs = NULL
-
-domestic_TIVs = NULL
-
-europe_TIVs = NULL
-
-national_fp = NULL
-
-national_territorial = NULL
-
-for (i in years_exb_pxp){
- year_current = i
-
- Exiobase_FD = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/FD_",year_current,"_pxp.csv"))[,-1]
-
- # select household final demand vectors for relevant countries - figure out how to soft code this
-
- AT = Exiobase_FD[,1]
- BE = Exiobase_FD[,8]
- BG = Exiobase_FD[,15]
- CY = Exiobase_FD[,22]
- CZ = Exiobase_FD[,29]
- DE = Exiobase_FD[,36]
- DK = Exiobase_FD[,43]
- EE = Exiobase_FD[,50]
- EL = Exiobase_FD[,78]
- ES = Exiobase_FD[,57]
- FI = Exiobase_FD[,64]
- FR = Exiobase_FD[,71]
- HR = Exiobase_FD[,85]
- HU = Exiobase_FD[,92]
- IE = Exiobase_FD[,99]
- IT = Exiobase_FD[,106]
- LT = Exiobase_FD[,113]
- LU = Exiobase_FD[,120]
- LV = Exiobase_FD[,127]
- MT = Exiobase_FD[,134]
- NL = Exiobase_FD[,141]
- NO = Exiobase_FD[,288]
- PL = Exiobase_FD[,148]
- PT = Exiobase_FD[,155]
- RO = Exiobase_FD[,162]
- SE = Exiobase_FD[,169]
- SI = Exiobase_FD[,176]
- SK = Exiobase_FD[,183]
- TR = Exiobase_FD[,274]
- UK = Exiobase_FD[,190]
-
- Eurostat_countries = cbind(AT,BE,BG,CY,CZ,DE,DK,EE,EL,ES,FI,FR,HR,HU,IE,IT,LT,LU,LV,MT,NL,NO,PL,PT,RO,SE,SI,SK,TR,UK)
-
- # labels
-
- Exiobase_T_labels = read.csv(paste0(data_dir_income_stratified_footprints, "/data/Exiobase_T_labels_pxp_w_coicop_mapping_no_rent.csv")) %>%
- mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"))
-
-
- # hh fd with production sector labels
-
- hh_fd_with_production_sector_labels = cbind(Exiobase_T_labels,Eurostat_countries) %>% rename(geo = V1, sector = V2)
-
- # assumption of same purchase structure between quintiles of domestic and foreign final demand
-
- # replicate each cell of each country's hh final demand as many times as there are income groups in the HBS data - in this preliminary case:5
-
- cells_repeat = data.frame(hh_fd_with_production_sector_labels %>% slice(rep(1:n(), each = 5)))
-
- quintiles = data.frame(rep(c("QUINTILE1","QUINTILE2","QUINTILE3","QUINTILE4","QUINTILE5"),200)) %>% rename_at(1,~"quintile")
-
- replicated = cbind(cells_repeat,quintiles) %>% rename(country_of_production = geo)
-
- # make fd data long
-
- replicated_long = replicated %>% gather(geo, value,-sector,-coicop,-quintile,-five_sectors,-country_of_production)
-
- year = as.character(rep(year_current,nrow(replicated_long)))
-
- replicated_long = cbind(year,replicated_long)
-
-
- disaggregated_final_demand = rbind(disaggregated_final_demand, replicated_long)
-
-
- # TIVs
-
- # CO2 - combustion - air
-
- Exiobase_TIV_co2_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_co2_combustion_air_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_co2_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_co2_combustion_air_", year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CO2_domestic)
-
- Exiobase_TIV_europe_breakdown_co2_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_co2_combustion_air_", year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CO2_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_CO2_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CO2_europe,TIV_CO2_not_europe)
-
- # CO2 - noncombustion - cement - air
-
- Exiobase_TIV_co2_noncombustion_cement_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_co2_noncombustion_cement_air_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_co2_noncombustion_cement_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_co2_noncombustion_cement_air_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CO2_noncombustion_cement_domestic)
-
- Exiobase_TIV_europe_breakdown_co2_noncombustion_cement_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_co2_noncombustion_cement_air_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CO2_noncombustion_cement_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_CO2_noncombustion_cement_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CO2_noncombustion_cement_europe,TIV_CO2_noncombustion_cement_not_europe)
-
- # CO2 - noncombustion - lime - air
-
- Exiobase_TIV_co2_noncombustion_lime_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_co2_noncombustion_lime_air_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_co2_noncombustion_lime_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_co2_noncombustion_lime_air_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CO2_noncombustion_lime_domestic)
-
- Exiobase_TIV_europe_breakdown_co2_noncombustion_lime_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_co2_noncombustion_lime_air_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CO2_noncombustion_lime_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_CO2_noncombustion_lime_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CO2_noncombustion_lime_europe,TIV_CO2_noncombustion_lime_not_europe)
-
- # CO2 - agriculture - peat decay - air
-
- Exiobase_TIV_co2_agriculture_peatdecay_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_co2_agriculture_peatdecay_air_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_co2_agriculture_peatdecay_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_co2_agriculture_peatdecay_air_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CO2_agriculture_peatdecay_domestic)
-
- Exiobase_TIV_europe_breakdown_co2_agriculture_peatdecay_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_co2_agriculture_peatdecay_air_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CO2_agriculture_peatdecay_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_CO2_agriculture_peatdecay_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CO2_agriculture_peatdecay_europe,TIV_CO2_agriculture_peatdecay_not_europe)
-
- # CO2 - waste - biogenic - air
-
- Exiobase_TIV_co2_waste_biogenic_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_co2_biogenic_air_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_co2_waste_biogenic_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_co2_biogenic_air_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CO2_waste_biogenic_domestic)
-
- Exiobase_TIV_europe_breakdown_co2_waste_biogenic_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_co2_biogenic_air_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CO2_waste_biogenic_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_CO2_waste_biogenic_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CO2_waste_biogenic_europe,TIV_CO2_waste_biogenic_not_europe)
-
- # CO2 - waste - fossil - air
-
- Exiobase_TIV_co2_waste_fossil_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_co2_waste_fossil_air_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_co2_waste_fossil_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_co2_waste_fossil_air_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CO2_waste_fossil_domestic)
-
- Exiobase_TIV_europe_breakdown_co2_waste_fossil_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_co2_waste_fossil_air_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CO2_waste_fossil_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_CO2_waste_fossil_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CO2_waste_fossil_europe,TIV_CO2_waste_fossil_not_europe)
-
-
-
- # CH4 - combustion -air
-
- Exiobase_TIV_ch4_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_ch4_CO2eq_combustion_air_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_combustion_air_", year_current, "_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_combustion_air_", year_current, "_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_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_CH4_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_europe,TIV_CH4_not_europe)
-
- # CH4 - noncombustion - gas - air
-
- Exiobase_TIV_ch4_noncombustion_gas_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_ch4_CO2eq_noncombustion_gas_air_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_noncombustion_gas_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_noncombustion_gas_air_", year_current, "_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_noncombustion_gas_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_gas_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_noncombustion_gas_air_", year_current, "_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_noncombustion_gas_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_CH4_noncombustion_gas_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_noncombustion_gas_europe,TIV_CH4_noncombustion_gas_not_europe)
-
- # CH4 - noncombustion - oil - air
-
- Exiobase_TIV_ch4_noncombustion_oil_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_ch4_CO2eq_noncombustion_oil_air_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_noncombustion_oil_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_noncombustion_oil_air_", year_current, "_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_noncombustion_oil_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_oil_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_noncombustion_oil_air_", year_current, "_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_noncombustion_oil_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_CH4_noncombustion_oil_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_noncombustion_oil_europe,TIV_CH4_noncombustion_oil_not_europe)
-
- # CH4 - noncombustion - anthracite - air
-
- Exiobase_TIV_ch4_noncombustion_anthracite_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_ch4_CO2eq_noncombustion_anthracite_air_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_noncombustion_anthracite_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_noncombustion_anthracite_air_", year_current, "_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_noncombustion_anthracite_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_anthracite_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_noncombustion_anthracite_air_", year_current, "_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_noncombustion_anthracite_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_CH4_noncombustion_anthracite_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_noncombustion_anthracite_europe,TIV_CH4_noncombustion_anthracite_not_europe)
-
- # CH4 - noncombustion - bituminouscoal - air
-
- Exiobase_TIV_ch4_noncombustion_bituminouscoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_ch4_CO2eq_noncombustion_bituminouscoal_air_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_noncombustion_bituminouscoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_noncombustion_bituminouscoal_air_", year_current, "_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_noncombustion_bituminouscoal_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_bituminouscoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_noncombustion_bituminouscoal_air_", year_current, "_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_noncombustion_bituminouscoal_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_CH4_noncombustion_bituminouscoal_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_noncombustion_bituminouscoal_europe,TIV_CH4_noncombustion_bituminouscoal_not_europe)
-
- # CH4 - noncombustion - cokingcoal - air
-
- Exiobase_TIV_ch4_noncombustion_cokingcoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_ch4_CO2eq_noncombustion_cokingcoal_air_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_noncombustion_cokingcoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_noncombustion_cokingcoal_air_", year_current, "_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_noncombustion_cokingcoal_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_cokingcoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_noncombustion_cokingcoal_air_", year_current, "_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_noncombustion_cokingcoal_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_CH4_noncombustion_cokingcoal_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_noncombustion_cokingcoal_europe,TIV_CH4_noncombustion_cokingcoal_not_europe)
-
- # CH4 - noncombustion - lignite - air
-
- Exiobase_TIV_ch4_noncombustion_lignite_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_ch4_CO2eq_noncombustion_lignite_air_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_noncombustion_lignite_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_noncombustion_lignite_air_", year_current, "_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_noncombustion_lignite_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_lignite_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_noncombustion_lignite_air_", year_current, "_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_noncombustion_lignite_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_CH4_noncombustion_lignite_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_noncombustion_lignite_europe,TIV_CH4_noncombustion_lignite_not_europe)
-
- # CH4 - noncombustion - subbituminouscoal - air
-
- Exiobase_TIV_ch4_noncombustion_subbituminouscoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_ch4_CO2eq_noncombustion_subbituminouscoal_air_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_noncombustion_subbituminouscoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_noncombustion_subbituminouscoal_air_", year_current, "_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_noncombustion_subbituminouscoal_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_subbituminouscoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_noncombustion_subbituminouscoal_air_", year_current, "_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_noncombustion_subbituminouscoal_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_CH4_noncombustion_subbituminouscoal_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_noncombustion_subbituminouscoal_europe,TIV_CH4_noncombustion_subbituminouscoal_not_europe)
-
- # CH4 - noncombustion - oilrefinery - air
-
- Exiobase_TIV_ch4_noncombustion_oilrefinery_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_ch4_CO2eq_noncombustion_oilrefinery_air_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_noncombustion_oilrefinery_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_noncombustion_oilrefinery_air_", year_current, "_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_noncombustion_oilrefinery_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_oilrefinery_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_noncombustion_oilrefinery_air_", year_current, "_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_noncombustion_oilrefinery_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_CH4_noncombustion_oilrefinery_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_noncombustion_oilrefinery_europe,TIV_CH4_noncombustion_oilrefinery_not_europe)
-
- # CH4 - agriculture - air
-
- Exiobase_TIV_ch4_agriculture_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_ch4_CO2eq_agriculture_air_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_agriculture_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_agriculture_air_", year_current, "_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_agriculture_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_agriculture_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_agriculture_air_", year_current, "_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_agriculture_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_CH4_agriculture_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_agriculture_europe,TIV_CH4_agriculture_not_europe)
-
- # CH4 - waste - air
-
- Exiobase_TIV_ch4_waste_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_ch4_CO2eq_waste_air_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_waste_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_waste_air_", year_current, "_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_waste_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_waste_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_ch4_CO2eq_waste_air_", year_current, "_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_waste_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_CH4_waste_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_waste_europe,TIV_CH4_waste_not_europe)
-
-
-
- # N2O - combustion - air
-
- Exiobase_TIV_n2o_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_n2o_CO2eq_combustion_air_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_n2o_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_n2o_CO2eq_combustion_air_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_N2O_domestic)
-
- Exiobase_TIV_europe_breakdown_n2o_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_n2o_CO2eq_combustion_air_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_N2O_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_N2O_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_N2O_europe,TIV_N2O_not_europe)
-
- # N2O - agriculture - air
-
- Exiobase_TIV_n2o_agriculture_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_n2o_CO2eq_agriculture_air_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_n2o_agriculture_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_n2o_CO2eq_agriculture_air_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_N2O_agriculture_domestic)
-
- Exiobase_TIV_europe_breakdown_n2o_agriculture_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_n2o_CO2eq_agriculture_air_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_N2O_agriculture_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_N2O_agriculture_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_N2O_agriculture_europe,TIV_N2O_agriculture_not_europe)
-
- # SF6 - air
-
- Exiobase_TIV_sf6_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_sf6_CO2eq_air_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_sf6_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_sf6_CO2eq_air_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_SF6_domestic)
-
- Exiobase_TIV_europe_breakdown_sf6_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_sf6_CO2eq_air_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_SF6_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_SF6_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_SF6_europe,TIV_SF6_not_europe)
-
- # HFC - air
-
- Exiobase_TIV_hfc_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_hfc_CO2eq_air_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_hfc_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_hfc_CO2eq_air_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_HFC_domestic)
-
- Exiobase_TIV_europe_breakdown_hfc_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_hfc_CO2eq_air_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_HFC_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_HFC_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_HFC_europe,TIV_HFC_not_europe)
-
- # PFC - air
-
- Exiobase_TIV_pfc_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_pfc_CO2eq_air_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_pfc_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_pfc_CO2eq_air_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_PFC_domestic)
-
- Exiobase_TIV_europe_breakdown_pfc_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_pfc_CO2eq_air_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_PFC_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_PFC_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_PFC_europe,TIV_PFC_not_europe)
-
- # Energy use
-
- Exiobase_TIV_energy_use_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_energy_carrier_use_",year_current,"_pxp.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_energy_use_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_energy_carrier_use_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_energy_domestic)
-
- Exiobase_TIV_europe_breakdown_energy_use_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_pxp/TIV_country_breakdown_energy_carrier_use_",year_current,"_pxp.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_energy_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_energy_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- 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
-
- TIV_with_labels = cbind(Exiobase_T_labels,
- t(Exiobase_TIV_co2_bp),
- t(Exiobase_TIV_co2_noncombustion_cement_bp),
- t(Exiobase_TIV_co2_noncombustion_lime_bp),
- t(Exiobase_TIV_co2_agriculture_peatdecay_bp),
- t(Exiobase_TIV_co2_waste_biogenic_bp),
- t(Exiobase_TIV_co2_waste_fossil_bp),
- t(Exiobase_TIV_ch4_bp),
- t(Exiobase_TIV_ch4_noncombustion_gas_bp),
- t(Exiobase_TIV_ch4_noncombustion_oil_bp),
- t(Exiobase_TIV_ch4_noncombustion_anthracite_bp),
- t(Exiobase_TIV_ch4_noncombustion_bituminouscoal_bp),
- t(Exiobase_TIV_ch4_noncombustion_cokingcoal_bp),
- t(Exiobase_TIV_ch4_noncombustion_lignite_bp),
- t(Exiobase_TIV_ch4_noncombustion_subbituminouscoal_bp),
- t(Exiobase_TIV_ch4_noncombustion_oilrefinery_bp),
- t(Exiobase_TIV_ch4_agriculture_bp),
- t(Exiobase_TIV_ch4_waste_bp),
- t(Exiobase_TIV_n2o_bp),
- t(Exiobase_TIV_n2o_agriculture_bp),
- 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)) %>%
- 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)",
- TIV_CO2_agriculture_peatdecay = "t(Exiobase_TIV_co2_agriculture_peatdecay_bp)",
- TIV_CO2_waste_biogenic = "t(Exiobase_TIV_co2_waste_biogenic_bp)",
- TIV_CO2_waste_fossil = "t(Exiobase_TIV_co2_waste_fossil_bp)",
- TIV_CH4 = "t(Exiobase_TIV_ch4_bp)",
- TIV_CH4_noncombustion_gas = "t(Exiobase_TIV_ch4_noncombustion_gas_bp)",
- TIV_CH4_noncombustion_oil = "t(Exiobase_TIV_ch4_noncombustion_oil_bp)",
- TIV_CH4_noncombustion_anthracite = "t(Exiobase_TIV_ch4_noncombustion_anthracite_bp)",
- TIV_CH4_noncombustion_bituminouscoal = "t(Exiobase_TIV_ch4_noncombustion_bituminouscoal_bp)",
- TIV_CH4_noncombustion_cokingcoal = "t(Exiobase_TIV_ch4_noncombustion_cokingcoal_bp)",
- TIV_CH4_noncombustion_lignite = "t(Exiobase_TIV_ch4_noncombustion_lignite_bp)",
- TIV_CH4_noncombustion_subbituminouscoal = "t(Exiobase_TIV_ch4_noncombustion_subbituminouscoal_bp)",
- TIV_CH4_noncombustion_oilrefinery = "t(Exiobase_TIV_ch4_noncombustion_oilrefinery_bp)",
- TIV_CH4_agriculture = "t(Exiobase_TIV_ch4_agriculture_bp)",
- TIV_CH4_waste = "t(Exiobase_TIV_ch4_waste_bp)",
- TIV_N2O = "t(Exiobase_TIV_n2o_bp)",
- TIV_N2O_agriculture = "t(Exiobase_TIV_n2o_agriculture_bp)",
- 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)") %>%
- mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"))
-
- year = as.character(rep(year_current,nrow(TIV_with_labels)))
-
- look = cbind(year,TIV_with_labels) %>%
- rename(country_of_production = V1, sector = V2)
-
-
- TIVs = rbind(TIVs,look)
-
-
- # join domestic_TIVs with labels
-
- domestic_TIV_with_labels = cbind(Exiobase_T_labels,
- Exiobase_TIV_country_breakdown_co2_bp,
- Exiobase_TIV_country_breakdown_co2_noncombustion_cement_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_co2_noncombustion_lime_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_co2_agriculture_peatdecay_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_co2_waste_biogenic_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_co2_waste_fossil_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_noncombustion_gas_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_noncombustion_oil_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_noncombustion_anthracite_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_noncombustion_bituminouscoal_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_noncombustion_cokingcoal_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_noncombustion_lignite_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_noncombustion_subbituminouscoal_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_noncombustion_oilrefinery_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_agriculture_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_waste_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_n2o_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_n2o_agriculture_bp %>% select(-country),
- 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)) %>%
- mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"),
- country = dplyr::recode(country, "GR" = "EL", "GB" = "UK"))
-
- year_domestic = as.character(rep(year_current,nrow(domestic_TIV_with_labels)))
-
- look_domestic = cbind(year_domestic,domestic_TIV_with_labels) %>%
- rename(country_of_production = V1, sector = V2, geo = country, year = year_domestic) %>%
- mutate(TIV_CO2_domestic = as.numeric(TIV_CO2_domestic),
- TIV_CO2_noncombustion_cement_domestic = as.numeric(TIV_CO2_noncombustion_cement_domestic),
- TIV_CO2_noncombustion_lime_domestic = as.numeric(TIV_CO2_noncombustion_lime_domestic),
- TIV_CO2_agriculture_peatdecay_domestic = as.numeric(TIV_CO2_agriculture_peatdecay_domestic),
- TIV_CO2_waste_biogenic_domestic = as.numeric(TIV_CO2_waste_biogenic_domestic),
- TIV_CO2_waste_fossil_domestic = as.numeric(TIV_CO2_waste_fossil_domestic),
- TIV_CH4_domestic = as.numeric(TIV_CH4_domestic),
- TIV_CH4_noncombustion_gas_domestic = as.numeric(TIV_CH4_noncombustion_gas_domestic),
- TIV_CH4_noncombustion_oil_domestic = as.numeric(TIV_CH4_noncombustion_oil_domestic),
- TIV_CH4_noncombustion_anthracite_domestic = as.numeric(TIV_CH4_noncombustion_anthracite_domestic),
- TIV_CH4_noncombustion_bituminouscoal_domestic = as.numeric(TIV_CH4_noncombustion_bituminouscoal_domestic),
- TIV_CH4_noncombustion_cokingcoal_domestic = as.numeric(TIV_CH4_noncombustion_cokingcoal_domestic),
- TIV_CH4_noncombustion_lignite_domestic = as.numeric(TIV_CH4_noncombustion_lignite_domestic),
- TIV_CH4_noncombustion_subbituminouscoal_domestic = as.numeric(TIV_CH4_noncombustion_subbituminouscoal_domestic),
- TIV_CH4_noncombustion_oilrefinery_domestic = as.numeric(TIV_CH4_noncombustion_oilrefinery_domestic),
- TIV_CH4_agriculture_domestic = as.numeric(TIV_CH4_agriculture_domestic),
- TIV_CH4_waste_domestic = as.numeric(TIV_CH4_waste_domestic),
- TIV_N2O_domestic = as.numeric(TIV_N2O_domestic),
- TIV_N2O_agriculture_domestic = as.numeric(TIV_N2O_agriculture_domestic),
- 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))
-
- domestic_TIVs = rbind(domestic_TIVs, look_domestic)
-
- # europe TIVs with labels
-
- europe_TIV_with_labels = cbind(Exiobase_T_labels,
- Exiobase_TIV_europe_breakdown_co2_bp,
- Exiobase_TIV_europe_breakdown_co2_noncombustion_cement_bp,
- Exiobase_TIV_europe_breakdown_co2_noncombustion_lime_bp,
- Exiobase_TIV_europe_breakdown_co2_agriculture_peatdecay_bp,
- Exiobase_TIV_europe_breakdown_co2_waste_biogenic_bp,
- Exiobase_TIV_europe_breakdown_co2_waste_fossil_bp,
- Exiobase_TIV_europe_breakdown_ch4_bp,
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_gas_bp,
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_oil_bp,
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_anthracite_bp,
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_bituminouscoal_bp,
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_cokingcoal_bp,
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_lignite_bp,
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_subbituminouscoal_bp,
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_oilrefinery_bp,
- Exiobase_TIV_europe_breakdown_ch4_agriculture_bp,
- Exiobase_TIV_europe_breakdown_ch4_waste_bp,
- Exiobase_TIV_europe_breakdown_n2o_bp,
- Exiobase_TIV_europe_breakdown_n2o_agriculture_bp,
- 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) %>%
- mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"))
-
- year_europe = as.character(rep(year_current,nrow(europe_TIV_with_labels)))
-
- look_europe = cbind(year_europe,europe_TIV_with_labels) %>%
- rename(country_of_production = V1, sector = V2, year = year_europe) %>%
- mutate(TIV_CO2_europe = as.numeric(TIV_CO2_europe),
- TIV_CO2_noncombustion_cement_europe = as.numeric(TIV_CO2_noncombustion_cement_europe),
- TIV_CO2_noncombustion_lime_europe = as.numeric(TIV_CO2_noncombustion_lime_europe),
- TIV_CO2_agriculture_peatdecay_europe = as.numeric(TIV_CO2_agriculture_peatdecay_europe),
- TIV_CO2_waste_biogenic_europe = as.numeric(TIV_CO2_waste_biogenic_europe),
- TIV_CO2_waste_fossil_europe = as.numeric(TIV_CO2_waste_fossil_europe),
- TIV_CH4_europe = as.numeric(TIV_CH4_europe),
- TIV_CH4_noncombustion_gas_europe = as.numeric(TIV_CH4_noncombustion_gas_europe),
- TIV_CH4_noncombustion_oil_europe = as.numeric(TIV_CH4_noncombustion_oil_europe),
- TIV_CH4_noncombustion_anthracite_europe = as.numeric(TIV_CH4_noncombustion_anthracite_europe),
- TIV_CH4_noncombustion_bituminouscoal_europe = as.numeric(TIV_CH4_noncombustion_bituminouscoal_europe),
- TIV_CH4_noncombustion_cokingcoal_europe = as.numeric(TIV_CH4_noncombustion_cokingcoal_europe),
- TIV_CH4_noncombustion_lignite_europe = as.numeric(TIV_CH4_noncombustion_lignite_europe),
- TIV_CH4_noncombustion_subbituminouscoal_europe = as.numeric(TIV_CH4_noncombustion_subbituminouscoal_europe),
- TIV_CH4_noncombustion_oilrefinery_europe = as.numeric(TIV_CH4_noncombustion_oilrefinery_europe),
- TIV_CH4_agriculture_europe = as.numeric(TIV_CH4_agriculture_europe),
- TIV_CH4_waste_europe = as.numeric(TIV_CH4_waste_europe),
- TIV_N2O_europe = as.numeric(TIV_N2O_europe),
- TIV_N2O_agriculture_europe = as.numeric(TIV_N2O_agriculture_europe),
- 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))
-
- europe_TIVs = rbind(europe_TIVs, look_europe)
-
-
- # total national footprints
-
- # FD labels
-
- Exiobase_FD_labels = as.data.frame(t(read.csv(paste0(data_dir_exiobase, "/Exiobase_FD_labels_pxp.csv")))[-1,-3]) %>%
- mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"))
-
- national_CO2_footprints = Exiobase_FD * t(Exiobase_TIV_co2_bp)
-
- national_CO2_noncombustion_cement_footprints = Exiobase_FD * t(Exiobase_TIV_co2_noncombustion_cement_bp)
-
- national_CO2_noncombustion_lime_footprints = Exiobase_FD * t(Exiobase_TIV_co2_noncombustion_lime_bp)
-
- national_CO2_agriculture_peatdecay_footprints = Exiobase_FD * t(Exiobase_TIV_co2_agriculture_peatdecay_bp)
-
- national_CO2_waste_biogenic_footprints = Exiobase_FD * t(Exiobase_TIV_co2_waste_biogenic_bp)
-
- national_CO2_waste_fossil_footprints = Exiobase_FD * t(Exiobase_TIV_co2_waste_fossil_bp)
-
- national_CH4_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_bp)
-
- national_CH4_noncombustion_gas_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_noncombustion_gas_bp)
-
- national_CH4_noncombustion_oil_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_noncombustion_oil_bp)
-
- national_CH4_noncombustion_anthracite_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_noncombustion_anthracite_bp)
-
- national_CH4_noncombustion_bituminouscoal_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_noncombustion_bituminouscoal_bp)
-
- national_CH4_noncombustion_cokingcoal_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_noncombustion_cokingcoal_bp)
-
- national_CH4_noncombustion_lignite_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_noncombustion_lignite_bp)
-
- national_CH4_noncombustion_subbituminouscoal_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_noncombustion_subbituminouscoal_bp)
-
- national_CH4_noncombustion_oilrefinery_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_noncombustion_oilrefinery_bp)
-
- national_CH4_agriculture_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_agriculture_bp)
-
- national_CH4_waste_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_waste_bp)
-
- national_N2O_footprints = Exiobase_FD * t(Exiobase_TIV_n2o_bp)
-
- national_N2O_agriculture_footprints = Exiobase_FD * t(Exiobase_TIV_n2o_agriculture_bp)
-
- national_SF6_footprints = Exiobase_FD * t(Exiobase_TIV_sf6_bp)
-
- national_HFC_footprints = Exiobase_FD * t(Exiobase_TIV_hfc_bp)
-
- national_PFC_footprints = Exiobase_FD * t(Exiobase_TIV_pfc_bp)
-
- 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
-
- national_footprints_w_labels = cbind(Exiobase_FD_labels,
- rowSums(t(national_CO2_footprints)),
- rowSums(t(national_CO2_noncombustion_cement_footprints)),
- rowSums(t(national_CO2_noncombustion_lime_footprints)),
- rowSums(t(national_CO2_agriculture_peatdecay_footprints)),
- rowSums(t(national_CO2_waste_biogenic_footprints)),
- rowSums(t(national_CO2_waste_fossil_footprints)),
- rowSums(t(national_CH4_footprints)),
- rowSums(t(national_CH4_noncombustion_gas_footprints)),
- rowSums(t(national_CH4_noncombustion_oil_footprints)),
- rowSums(t(national_CH4_noncombustion_anthracite_footprints)),
- rowSums(t(national_CH4_noncombustion_bituminouscoal_footprints)),
- rowSums(t(national_CH4_noncombustion_cokingcoal_footprints)),
- rowSums(t(national_CH4_noncombustion_lignite_footprints)),
- rowSums(t(national_CH4_noncombustion_subbituminouscoal_footprints)),
- rowSums(t(national_CH4_noncombustion_oilrefinery_footprints)),
- rowSums(t(national_CH4_agriculture_footprints)),
- rowSums(t(national_CH4_waste_footprints)),
- rowSums(t(national_N2O_footprints)),
- rowSums(t(national_N2O_agriculture_footprints)),
- 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))) %>%
- mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"))
-
- year_national_fp = as.character(rep(year_current,nrow(national_footprints_w_labels)))
-
-
- # direct FD emissions
-
- direct_FD_extensions = read.csv(paste0(data_dir_exiobase, "/IOT_", year_current, "_pxp/satellite/F_hh.csv", sep = ""),row.names=NULL,as.is=TRUE)[3:1106,3:345]
- direct_FD_extensions[is.na(direct_FD_extensions)]=0
- direct_FD_extensions = mapply(direct_FD_extensions, FUN = as.numeric)
- direct_FD_extensions = matrix(data=direct_FD_extensions,ncol=343,nrow=1104)
-
- direct_FD_co2 = direct_FD_extensions[24,]
- direct_FD_co2_noncombustion_cement = direct_FD_extensions[93,]
- direct_FD_co2_noncombustion_lime = direct_FD_extensions[94,]
- direct_FD_co2_agriculture_peatdecay = direct_FD_extensions[428,]
- direct_FD_co2_waste_biogenic = direct_FD_extensions[438,]
- direct_FD_co2_waste_fossil = direct_FD_extensions[439,]
- direct_FD_ch4 = direct_FD_extensions[25,]*28
- direct_FD_ch4_noncombustion_gas = direct_FD_extensions[68,]*28
- direct_FD_ch4_noncombustion_oil = direct_FD_extensions[69,]*28
- direct_FD_ch4_noncombustion_anthracite = direct_FD_extensions[70,]*28
- direct_FD_ch4_noncombustion_bituminouscoal = direct_FD_extensions[71,]*28
- direct_FD_ch4_noncombustion_cokingcoal = direct_FD_extensions[72,]*28
- direct_FD_ch4_noncombustion_lignite = direct_FD_extensions[73,]*28
- direct_FD_ch4_noncombustion_subbituminouscoal = direct_FD_extensions[74,]*28
- direct_FD_ch4_noncombustion_oilrefinery = direct_FD_extensions[75,]*28
- direct_FD_ch4_agriculture = direct_FD_extensions[427,]*28
- direct_FD_ch4_waste = direct_FD_extensions[436,]*28
- direct_FD_n2o = direct_FD_extensions[26,]*265
- direct_FD_n2o_agriculture = direct_FD_extensions[430,]*265
- direct_FD_sf6 = direct_FD_extensions[424,]*23500
- 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,
- direct_FD_co2_noncombustion_cement,
- direct_FD_co2_noncombustion_lime,
- direct_FD_co2_agriculture_peatdecay,
- direct_FD_co2_waste_biogenic,
- direct_FD_co2_waste_fossil,
- direct_FD_ch4,
- direct_FD_ch4_noncombustion_gas,
- direct_FD_ch4_noncombustion_oil,
- direct_FD_ch4_noncombustion_anthracite,
- direct_FD_ch4_noncombustion_bituminouscoal,
- direct_FD_ch4_noncombustion_cokingcoal,
- direct_FD_ch4_noncombustion_lignite,
- direct_FD_ch4_noncombustion_subbituminouscoal,
- direct_FD_ch4_noncombustion_oilrefinery,
- direct_FD_ch4_agriculture,
- direct_FD_ch4_waste,
- direct_FD_n2o,
- direct_FD_n2o_agriculture,
- 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)
-
- look_national_fp = as.data.frame(cbind(year_national_fp,
- national_footprints_w_labels,
- direct_FD_fp)) %>%
- rename(year = year_national_fp,
- geo = V1,
- fd_category = V2,
- co2 = "rowSums(t(national_CO2_footprints))",
- co2_noncombustion_cement = "rowSums(t(national_CO2_noncombustion_cement_footprints))",
- co2_noncombustion_lime = "rowSums(t(national_CO2_noncombustion_lime_footprints))",
- co2_agriculture_peatdecay = "rowSums(t(national_CO2_agriculture_peatdecay_footprints))",
- co2_waste_biogenic = "rowSums(t(national_CO2_waste_biogenic_footprints))",
- co2_waste_fossil = "rowSums(t(national_CO2_waste_fossil_footprints))",
- ch4 = "rowSums(t(national_CH4_footprints))",
- ch4_noncombustion_gas = "rowSums(t(national_CH4_noncombustion_gas_footprints))",
- ch4_noncombustion_oil = "rowSums(t(national_CH4_noncombustion_oil_footprints))",
- ch4_noncombustion_anthracite = "rowSums(t(national_CH4_noncombustion_anthracite_footprints))",
- ch4_noncombustion_bituminouscoal = "rowSums(t(national_CH4_noncombustion_bituminouscoal_footprints))",
- ch4_noncombustion_cokingcoal = "rowSums(t(national_CH4_noncombustion_cokingcoal_footprints))",
- ch4_noncombustion_lignite = "rowSums(t(national_CH4_noncombustion_lignite_footprints))",
- ch4_noncombustion_subbituminouscoal = "rowSums(t(national_CH4_noncombustion_subbituminouscoal_footprints))",
- ch4_noncombustion_oilrefinery = "rowSums(t(national_CH4_noncombustion_oilrefinery_footprints))",
- ch4_agriculture = "rowSums(t(national_CH4_agriculture_footprints))",
- ch4_waste = "rowSums(t(national_CH4_waste_footprints))",
- n2o = "rowSums(t(national_N2O_footprints))",
- n2o_agriculture = "rowSums(t(national_N2O_agriculture_footprints))",
- 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))") %>%
- select(year,
- geo,
- fd_category,
- co2,
- direct_FD_co2,
- co2_noncombustion_cement,
- direct_FD_co2_noncombustion_cement,
- co2_noncombustion_lime,
- direct_FD_co2_noncombustion_lime,
- co2_agriculture_peatdecay,
- direct_FD_co2_agriculture_peatdecay,
- co2_waste_biogenic,
- direct_FD_co2_waste_biogenic,
- co2_waste_fossil,
- direct_FD_co2_waste_fossil,
- ch4,
- direct_FD_ch4,
- ch4_noncombustion_gas,
- direct_FD_ch4_noncombustion_gas,
- ch4_noncombustion_oil,
- direct_FD_ch4_noncombustion_oil,
- ch4_noncombustion_anthracite,
- direct_FD_ch4_noncombustion_anthracite,
- ch4_noncombustion_bituminouscoal,
- direct_FD_ch4_noncombustion_bituminouscoal,
- ch4_noncombustion_cokingcoal,
- direct_FD_ch4_noncombustion_cokingcoal,
- ch4_noncombustion_lignite,
- direct_FD_ch4_noncombustion_lignite,
- ch4_noncombustion_subbituminouscoal,
- direct_FD_ch4_noncombustion_subbituminouscoal,
- ch4_noncombustion_oilrefinery,
- direct_FD_ch4_noncombustion_oilrefinery,
- ch4_agriculture,
- direct_FD_ch4_agriculture,
- ch4_waste,
- direct_FD_ch4_waste,
- n2o,
- direct_FD_n2o,
- n2o_agriculture,
- direct_FD_n2o_agriculture,
- sf6,
- direct_FD_sf6,
- hfc,
- direct_FD_hfc,
- 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)
-
-
- national_fp = rbind(national_fp, look_national_fp)
-
- # national territorial
-
- satellite = read.csv(paste0(data_dir_exiobase, "/IOT_", year_current, "_pxp/satellite/satellite_",year_current,"_pxp.csv"))[,-1]
-
-
- CO2_combustion_air = satellite[24,]
-
- CO2_noncombustion_cement_air = satellite[93,]
-
- CO2_noncombustion_lime_air = satellite[94,]
-
- CO2_agriculture_peatdecay_air = satellite[428,]
-
- CO2_waste_biogenic_air = satellite[438,]
-
- CO2_waste_fossil_air = satellite[439,]
-
- CH4_combustion_air = satellite[25,]
- CH4_combustion_air = CH4_combustion_air*28
-
- CH4_noncombustion_gas_air = satellite[68,]
- CH4_noncombustion_gas_air = CH4_noncombustion_gas_air*28
-
- CH4_noncombustion_oil_air = satellite[69,]
- CH4_noncombustion_oil_air = CH4_noncombustion_oil_air*28
-
- CH4_noncombustion_anthracite_air = satellite[70,]
- CH4_noncombustion_anthracite_air = CH4_noncombustion_anthracite_air*28
-
- CH4_noncombustion_bituminouscoal_air = satellite[71,]
- CH4_noncombustion_bituminouscoal_air = CH4_noncombustion_bituminouscoal_air*28
-
- CH4_noncombustion_cokingcoal_air = satellite[72,]
- CH4_noncombustion_cokingcoal_air = CH4_noncombustion_cokingcoal_air*28
-
- CH4_noncombustion_lignite_air = satellite[73,]
- CH4_noncombustion_lignite_air = CH4_noncombustion_lignite_air*28
-
- CH4_noncombustion_subbituminouscoal_air = satellite[74,]
- CH4_noncombustion_subbituminouscoal_air = CH4_noncombustion_subbituminouscoal_air*28
-
- CH4_noncombustion_oilrefinery_air = satellite[75,]
- CH4_noncombustion_oilrefinery_air = CH4_noncombustion_oilrefinery_air*28
-
- CH4_agriculture_air = satellite[427,]
- CH4_agriculture_air = CH4_agriculture_air*28
-
- CH4_waste_air = satellite[436,]
- CH4_waste_air = CH4_waste_air*28
-
- N2O_combustion_air = satellite[26,]
- N2O_combustion_air = N2O_combustion_air*265
-
- N2O_agriculture_air = satellite[430,]
- N2O_agriculture_air = N2O_agriculture_air*265
-
- SF6_air = satellite[424,]
- SF6_air = SF6_air*23500
-
- HFC_air = satellite[425,]
-
- PFC_air = satellite[426,]
-
- 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),
- t(CO2_noncombustion_lime_air),
- t(CO2_agriculture_peatdecay_air),
- t(CO2_waste_biogenic_air),
- t(CO2_waste_fossil_air),
- t(CH4_combustion_air),
- t(CH4_noncombustion_gas_air),
- t(CH4_noncombustion_oil_air),
- t(CH4_noncombustion_anthracite_air),
- t(CH4_noncombustion_bituminouscoal_air),
- t(CH4_noncombustion_cokingcoal_air),
- t(CH4_noncombustion_lignite_air),
- t(CH4_noncombustion_subbituminouscoal_air),
- t(CH4_noncombustion_oilrefinery_air),
- t(CH4_agriculture_air),
- t(CH4_waste_air),
- t(N2O_combustion_air),
- t(N2O_agriculture_air),
- t(SF6_air),
- t(HFC_air),
- t(PFC_air),
- t(energy_carrier_use),
- biomass,
- ores,
- const_materials,
- t(ffuels),
- cropland,
- pasture_land,
- forest_land) %>%
- rename(CO2 = 1,
- CO2_noncombustion_cement = 2,
- CO2_noncombustion_lime = 3,
- CO2_agriculture_peatdecay = 4,
- CO2_waste_biogenic = 5,
- CO2_waste_fossil = 6,
- CH4 = 7,
- CH4_noncombustion_gas = 8,
- CH4_noncombustion_oil = 9,
- CH4_noncombustion_anthracite = 10,
- CH4_noncombustion_bituminouscoal = 11,
- CH4_noncombustion_cokingcoal = 12,
- CH4_noncombustion_lignite = 13,
- CH4_noncombustion_subbituminouscoal = 14,
- CH4_noncombustion_oilrefinery = 15,
- CH4_agriculture = 16,
- CH4_waste = 17,
- 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)
-
- year_territorial = as.character(rep(year_current,nrow(territorial)))
-
- look_territorial = as.data.frame(cbind(year_territorial,
- Exiobase_T_labels,
- territorial)) %>%
- rename(year = year_territorial,
- geo = V1,
- sector = V2) %>%
- select(-coicop,-five_sectors)
-
- national_territorial = rbind(national_territorial, look_territorial)
-
-
-}
-
-write.csv(national_territorial, paste0(data_dir_income_stratified_footprints, "/national_territorial_pxp.csv"))
-write_rds(national_territorial, paste0(data_dir_income_stratified_footprints, "/national_territorial_pxp.rds"))
-
-
-write.csv(national_fp, paste0(data_dir_income_stratified_footprints, "/national_fp_pxp.csv"))
-write_rds(national_fp, paste0(data_dir_income_stratified_footprints, "/national_fp_pxp.rds"))
-
-# calculate quintile shares within each sector
-shares = join_expenditures %>%
- group_by(coicop,geo,year) %>%
- mutate(share = pps_coicop/sum(pps_coicop))
-
-# pre-processing
-
-fd_exiobase = disaggregated_final_demand %>%
- left_join(shares, by = c("year","geo","coicop","quintile")) %>%
- mutate(disaggregated_fd = value*share) %>%
- select(year,geo,quintile,country_of_production,sector,coicop,disaggregated_fd) %>%
- spread(quintile,disaggregated_fd)
-
-# direct from FD - to go back to results without direct FD fp, do not run this next chunk and do not bind_rows with 'results'
-
-env_ac_pefasu_no_TR = read_csv(paste0(data_dir_income_stratified_footprints, "/data/env_ac_pefasu_1_Data.csv")) %>%
- filter(TIME == 2015) %>%
- mutate(geo = dplyr::recode(GEO,"Austria" = "AT",
- "Belgium" = "BE",
- "Cyprus" = "CY",
- "Czechia" = "CZ",
- "Denmark" = "DK",
- "Estonia" = "EE",
- "Finland" = "FI",
- "France" = "FR",
- "Germany (until 1990 former territory of the FRG)" = "DE",
- "Greece" = "EL",
- "Hungary" = "HU",
- "Ireland" = "IE",
- "Italy" = "IT",
- "Latvia" = "LV",
- "Lithuania" = "LT",
- "Luxembourg" = "LU",
- "Malta" = "MT",
- "Netherlands" = "NL",
- "Norway" = "NO",
- "Poland" = "PL",
- "Portugal" = "PT",
- "Romania" = "RO",
- "Slovakia" = "SK",
- "Slovenia" = "SI",
- "Spain" = "ES",
- "Sweden" = "SE",
- "United Kingdom" = "UK",
- "Bulgaria" = "BG",
- "Croatia" = "HR")) %>%
- select(NACE_R2,geo,Value) %>%
- mutate(Value = parse_number(Value),
- Value = as.numeric(Value)) %>%
- spread(NACE_R2,Value) %>%
- clean_names() %>%
- mutate(HH_HEAT = heating_cooling_activities_by_households/total_activities_by_households,
- HH_TRA = transport_activities_by_households/total_activities_by_households,
- HH_OTH = other_activities_by_households/total_activities_by_households) %>%
- select(geo,HH_HEAT,HH_TRA,HH_OTH)
-
-
-env_ac_pefasu_TR = env_ac_pefasu_no_TR %>%
- filter(geo == "BG") %>%
- mutate(geo = dplyr::recode(geo,
- "BG" = "TR"))
-
-env_ac_pefasu = rbind(env_ac_pefasu_no_TR,env_ac_pefasu_TR) %>%
- gather(sector,share_of_total_energy,-geo)
-
-env_ac_ainah_r2 = read_csv(paste0(data_dir_income_stratified_footprints, "/data/env_ac_ainah_r2_1_Data.csv")) %>%
- filter(TIME == 2015) %>%
- mutate(geo = dplyr::recode(GEO,"Austria" = "AT",
- "Belgium" = "BE",
- "Cyprus" = "CY",
- "Czechia" = "CZ",
- "Denmark" = "DK",
- "Estonia" = "EE",
- "Finland" = "FI",
- "France" = "FR",
- "Germany (until 1990 former territory of the FRG)" = "DE",
- "Greece" = "EL",
- "Hungary" = "HU",
- "Ireland" = "IE",
- "Italy" = "IT",
- "Latvia" = "LV",
- "Lithuania" = "LT",
- "Luxembourg" = "LU",
- "Malta" = "MT",
- "Netherlands" = "NL",
- "Norway" = "NO",
- "Poland" = "PL",
- "Portugal" = "PT",
- "Romania" = "RO",
- "Slovakia" = "SK",
- "Slovenia" = "SI",
- "Spain" = "ES",
- "Sweden" = "SE",
- "Turkey" = "TR",
- "United Kingdom" = "UK",
- "Bulgaria" = "BG",
- "Croatia" = "HR")) %>%
- select(NACE_R2,AIRPOL,geo,Value) %>%
- mutate(Value = parse_number(Value),
- Value = as.numeric(Value)) %>%
- spread(NACE_R2,Value) %>%
- clean_names() %>%
- mutate(HH_HEAT = heating_cooling_activities_by_households/total_activities_by_households,
- HH_TRA = transport_activities_by_households/total_activities_by_households,
- HH_OTH = other_activities_by_households/total_activities_by_households) %>%
- select(geo,airpol,HH_HEAT,HH_TRA,HH_OTH)
-
-
-env_ac_ainah_r2_co2 = env_ac_ainah_r2 %>%
- filter(airpol == "Carbon dioxide") %>%
- select(-airpol) %>%
- gather(sector,share_of_total_co2,-geo)
-
-env_ac_ainah_r2_ch4 = env_ac_ainah_r2 %>%
- filter(airpol == "Methane") %>%
- select(-airpol) %>%
- gather(sector,share_of_total_ch4,-geo)
-
-env_ac_ainah_r2_n2o = env_ac_ainah_r2 %>%
- filter(airpol == "Nitrous oxide") %>%
- select(-airpol) %>%
- gather(sector,share_of_total_n2o,-geo)
-
-direct_FD_fp_long = national_fp %>%
- filter(fd_category == "Final consumption expenditure by households",
- geo %in% c("AT",
- "BE", "BG", "CY", "CZ",
- "DE" , "DK" , "EE" ,
- "ES" , "FI" , "FR" ,
- "UK", "EL", "HR" ,
- "HU" , "IE" , "IT" ,
- "LT" , "LU" , "LV" ,
- "MT" , "NL" , "PL" ,
- "PT" , "TR" , "SK" ,
- "SI" , "SE" , "RO" ,
- "NO")) %>%
- select(year,geo,fd_category,direct_FD_co2,
- direct_FD_co2_noncombustion_cement,
- direct_FD_co2_noncombustion_lime,
- direct_FD_co2_agriculture_peatdecay,
- direct_FD_co2_waste_biogenic,
- direct_FD_co2_waste_fossil,
- direct_FD_ch4,
- direct_FD_ch4_noncombustion_gas,
- direct_FD_ch4_noncombustion_oil,
- direct_FD_ch4_noncombustion_anthracite,
- direct_FD_ch4_noncombustion_bituminouscoal,
- direct_FD_ch4_noncombustion_cokingcoal,
- direct_FD_ch4_noncombustion_lignite,
- direct_FD_ch4_noncombustion_subbituminouscoal,
- direct_FD_ch4_noncombustion_oilrefinery,
- direct_FD_ch4_agriculture,
- direct_FD_ch4_waste,
- direct_FD_n2o,
- direct_FD_n2o_agriculture,
- 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) %>%
- slice(rep(1:n(), each = 3))
-
-sector = rep(c("HH_HEAT","HH_TRA","HH_OTH"), nrow(direct_FD_fp_long)/3)
-
-direct_FD_fp_long_disagg = cbind(sector,direct_FD_fp_long) %>%
- mutate(coicop = ifelse(sector == "HH_TRA","CP072",
- ifelse(sector == "HH_HEAT","CP045","CP05")),
- five_sectors = ifelse(sector == "HH_TRA", "transport",
- ifelse(sector == "HH_HEAT", "shelter", "manufactured goods"))) %>%
- left_join(env_ac_ainah_r2_co2, by = c("geo","sector")) %>%
- left_join(env_ac_ainah_r2_ch4, by = c("geo","sector")) %>%
- left_join(env_ac_ainah_r2_n2o, by = c("geo","sector")) %>%
- left_join(env_ac_pefasu, by = c("geo","sector")) %>%
- mutate(direct_FD_co2 = (direct_FD_co2 +
- direct_FD_co2_noncombustion_cement +
- direct_FD_co2_noncombustion_lime +
- direct_FD_co2_agriculture_peatdecay +
- direct_FD_co2_waste_biogenic +
- direct_FD_co2_waste_fossil)*share_of_total_co2,
- direct_FD_ch4 = (direct_FD_ch4 +
- direct_FD_ch4_noncombustion_gas +
- direct_FD_ch4_noncombustion_oil +
- direct_FD_ch4_noncombustion_anthracite +
- direct_FD_ch4_noncombustion_bituminouscoal +
- direct_FD_ch4_noncombustion_cokingcoal +
- direct_FD_ch4_noncombustion_lignite +
- direct_FD_ch4_noncombustion_subbituminouscoal +
- direct_FD_ch4_noncombustion_oilrefinery +
- direct_FD_ch4_agriculture +
- direct_FD_ch4_waste)*share_of_total_ch4,
- direct_FD_n2o = (direct_FD_n2o +
- direct_FD_n2o_agriculture)*share_of_total_n2o,
- direct_FD_energy = direct_FD_energy*share_of_total_energy) %>%
- left_join(shares, by = c("year","geo","coicop")) %>%
- mutate(disaggregated_direct_FD_co2 = direct_FD_co2*share,
- disaggregated_direct_FD_ch4 = direct_FD_ch4*share,
- disaggregated_direct_FD_n2o = direct_FD_n2o*share,
- disaggregated_direct_FD_energy = direct_FD_energy*share) %>%
- select(year,geo,sector, quintile,
- coicop, five_sectors,
- disaggregated_direct_FD_co2,
- disaggregated_direct_FD_ch4,
- disaggregated_direct_FD_n2o,
- disaggregated_direct_FD_energy)
-
-direct_FD_co2 = direct_FD_fp_long_disagg %>%
- select(year,geo,sector,quintile,coicop,five_sectors,disaggregated_direct_FD_co2) %>%
- spread(quintile,disaggregated_direct_FD_co2) %>%
- rename(q1_co2 = QUINTILE1,
- q2_co2 = QUINTILE2,
- q3_co2 = QUINTILE3,
- q4_co2 = QUINTILE4,
- q5_co2 = QUINTILE5) %>%
- mutate(q1_co2_domestic = q1_co2,
- q2_co2_domestic = q2_co2,
- q3_co2_domestic = q3_co2,
- q4_co2_domestic = q4_co2,
- q5_co2_domestic = q5_co2,
- co2_total = q1_co2+q2_co2+q3_co2+q4_co2+q5_co2,
- co2_total_domestic = q1_co2_domestic+
- q2_co2_domestic+q3_co2_domestic+
- q4_co2_domestic+q5_co2_domestic)
-
-direct_FD_ch4 = direct_FD_fp_long_disagg %>%
- select(year,geo,sector,quintile,coicop,five_sectors,disaggregated_direct_FD_ch4) %>%
- spread(quintile,disaggregated_direct_FD_ch4) %>%
- rename(q1_ch4 = QUINTILE1,
- q2_ch4 = QUINTILE2,
- q3_ch4 = QUINTILE3,
- q4_ch4 = QUINTILE4,
- q5_ch4 = QUINTILE5) %>%
- mutate(q1_ch4_domestic = q1_ch4,
- q2_ch4_domestic = q2_ch4,
- q3_ch4_domestic = q3_ch4,
- q4_ch4_domestic = q4_ch4,
- q5_ch4_domestic = q5_ch4,
- ch4_total = q1_ch4+q2_ch4+q3_ch4+q4_ch4+q5_ch4,
- ch4_total_domestic = q1_ch4_domestic+
- q2_ch4_domestic+q3_ch4_domestic+
- q4_ch4_domestic+q5_ch4_domestic)
-
-
-direct_FD_n2o = direct_FD_fp_long_disagg %>%
- select(year,geo,sector,quintile,coicop,five_sectors,disaggregated_direct_FD_n2o) %>%
- spread(quintile,disaggregated_direct_FD_n2o) %>%
- rename(q1_n2o = QUINTILE1,
- q2_n2o = QUINTILE2,
- q3_n2o = QUINTILE3,
- q4_n2o = QUINTILE4,
- q5_n2o = QUINTILE5) %>%
- mutate(q1_n2o_domestic = q1_n2o,
- q2_n2o_domestic = q2_n2o,
- q3_n2o_domestic = q3_n2o,
- q4_n2o_domestic = q4_n2o,
- q5_n2o_domestic = q5_n2o,
- n2o_total = q1_n2o+q2_n2o+q3_n2o+q4_n2o+q5_n2o,
- n2o_total_domestic = q1_n2o_domestic+
- q2_n2o_domestic+q3_n2o_domestic+
- q4_n2o_domestic+q5_n2o_domestic)
-
-direct_FD_energy = direct_FD_fp_long_disagg %>%
- select(year,geo,sector,quintile,coicop,five_sectors,disaggregated_direct_FD_energy) %>%
- spread(quintile,disaggregated_direct_FD_energy) %>%
- rename(q1_energy = QUINTILE1,
- q2_energy = QUINTILE2,
- q3_energy = QUINTILE3,
- q4_energy = QUINTILE4,
- q5_energy = QUINTILE5) %>%
- mutate(q1_energy_domestic = q1_energy,
- q2_energy_domestic = q2_energy,
- q3_energy_domestic = q3_energy,
- q4_energy_domestic = q4_energy,
- q5_energy_domestic = q5_energy,
- energy_total = q1_energy+q2_energy+q3_energy+q4_energy+q5_energy,
- energy_total_domestic = q1_energy_domestic+
- q2_energy_domestic+q3_energy_domestic+
- q4_energy_domestic+q5_energy_domestic)
-
-
-direct_FD_fp_wide = direct_FD_co2 %>%
- left_join(direct_FD_ch4, by = c("year","geo",
- "sector","coicop",
- "five_sectors")) %>%
- left_join(direct_FD_n2o, by = c("year","geo",
- "sector","coicop",
- "five_sectors")) %>%
- left_join(direct_FD_energy, by = c("year","geo",
- "sector","coicop",
- "five_sectors")) %>%
- mutate(country_of_production = geo) %>%
- mutate(q1_co2eq = q1_co2 + q1_ch4 + q1_n2o,
- q2_co2eq = q2_co2 + q2_ch4 + q2_n2o,
- q3_co2eq = q3_co2 + q3_ch4 + q3_n2o,
- q4_co2eq = q4_co2 + q4_ch4 + q4_n2o,
- q5_co2eq = q5_co2 + q5_ch4 + q5_n2o,
- co2eq_total = q1_co2eq +
- q2_co2eq + q3_co2eq +
- q4_co2eq + q5_co2eq,
- q1_co2eq_domestic = q1_co2_domestic + q1_ch4_domestic + q1_n2o_domestic,
- q2_co2eq_domestic = q2_co2_domestic + q2_ch4_domestic + q2_n2o_domestic,
- q3_co2eq_domestic = q3_co2_domestic + q3_ch4_domestic + q3_n2o_domestic,
- q4_co2eq_domestic = q4_co2_domestic + q4_ch4_domestic + q4_n2o_domestic,
- q5_co2eq_domestic = q5_co2_domestic + q5_ch4_domestic + q5_n2o_domestic,
- co2eq_total_domestic = q1_co2eq_domestic +
- q2_co2eq_domestic + q3_co2eq_domestic +
- q4_co2eq_domestic + q5_co2eq_domestic) %>%
- select(-q1_ch4,
- -q2_ch4,
- -q3_ch4,
- -q4_ch4,
- -q5_ch4,
- -ch4_total,
- -q1_ch4_domestic,
- -q2_ch4_domestic,
- -q3_ch4_domestic,
- -q4_ch4_domestic,
- -q5_ch4_domestic,
- -ch4_total_domestic,
- -q1_n2o,
- -q2_n2o,
- -q3_n2o,
- -q4_n2o,
- -q5_n2o,
- -n2o_total,
- -q1_n2o_domestic,
- -q2_n2o_domestic,
- -q3_n2o_domestic,
- -q4_n2o_domestic,
- -q5_n2o_domestic,
- -n2o_total_domestic)
-
-
-
-results = fd_exiobase %>%
- left_join(TIVs, by = c("year", "country_of_production", "coicop", "sector")) %>%
- left_join(europe_TIVs, by = c("year", "country_of_production", "coicop", "sector", "five_sectors")) %>%
- left_join(domestic_TIVs, by = c("year", "geo", "country_of_production", "coicop", "sector", "five_sectors")) %>%
- transmute(year,geo,country_of_production,sector,coicop,five_sectors,
- QUINTILE1,
- QUINTILE2,
- QUINTILE3,
- QUINTILE4,
- QUINTILE5,
- fd_total = QUINTILE1+QUINTILE2+QUINTILE3+QUINTILE4+QUINTILE5,
- TIV_CO2 = TIV_CO2 +
- TIV_CO2_noncombustion_cement +
- TIV_CO2_noncombustion_lime +
- TIV_CO2_agriculture_peatdecay +
- TIV_CO2_waste_biogenic +
- TIV_CO2_waste_fossil,
- q1_co2 = QUINTILE1*TIV_CO2,
- q2_co2 = QUINTILE2*TIV_CO2,
- q3_co2 = QUINTILE3*TIV_CO2,
- q4_co2 = QUINTILE4*TIV_CO2,
- q5_co2 = QUINTILE5*TIV_CO2,
- co2_total = q1_co2+q2_co2+q3_co2+q4_co2+q5_co2,
- TIV_CO2_domestic = TIV_CO2_domestic +
- TIV_CO2_noncombustion_cement_domestic +
- TIV_CO2_noncombustion_lime_domestic +
- TIV_CO2_agriculture_peatdecay_domestic +
- TIV_CO2_waste_biogenic_domestic +
- TIV_CO2_waste_fossil_domestic,
- q1_co2_domestic = QUINTILE1*TIV_CO2_domestic,
- q2_co2_domestic = QUINTILE2*TIV_CO2_domestic,
- q3_co2_domestic = QUINTILE3*TIV_CO2_domestic,
- q4_co2_domestic = QUINTILE4*TIV_CO2_domestic,
- q5_co2_domestic = QUINTILE5*TIV_CO2_domestic,
- co2_total_domestic = q1_co2_domestic+q2_co2_domestic+q3_co2_domestic+q4_co2_domestic+q5_co2_domestic,
- TIV_CO2_europe = TIV_CO2_europe +
- TIV_CO2_noncombustion_cement_europe +
- TIV_CO2_noncombustion_lime_europe +
- TIV_CO2_agriculture_peatdecay_europe +
- TIV_CO2_waste_biogenic_europe +
- TIV_CO2_waste_fossil_europe,
- q1_co2_europe = QUINTILE1*(TIV_CO2_europe - TIV_CO2_domestic),
- q2_co2_europe = QUINTILE2*(TIV_CO2_europe - TIV_CO2_domestic),
- q3_co2_europe = QUINTILE3*(TIV_CO2_europe - TIV_CO2_domestic),
- q4_co2_europe = QUINTILE4*(TIV_CO2_europe - TIV_CO2_domestic),
- q5_co2_europe = QUINTILE5*(TIV_CO2_europe - TIV_CO2_domestic),
- co2_total_europe = q1_co2_europe+q2_co2_europe+q3_co2_europe+q4_co2_europe+q5_co2_europe,
- TIV_CO2eq = TIV_CO2 +
- TIV_CH4 +
- TIV_CH4_noncombustion_gas +
- TIV_CH4_noncombustion_oil +
- TIV_CH4_noncombustion_anthracite +
- TIV_CH4_noncombustion_bituminouscoal +
- TIV_CH4_noncombustion_cokingcoal +
- TIV_CH4_noncombustion_lignite +
- 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,
- q1_co2eq = QUINTILE1*TIV_CO2eq,
- q2_co2eq = QUINTILE2*TIV_CO2eq,
- q3_co2eq = QUINTILE3*TIV_CO2eq,
- q4_co2eq = QUINTILE4*TIV_CO2eq,
- q5_co2eq = QUINTILE5*TIV_CO2eq,
- co2eq_total = q1_co2eq + q2_co2eq + q3_co2eq + q4_co2eq + q5_co2eq,
- TIV_CO2eq_domestic = TIV_CO2_domestic +
- TIV_CH4_domestic +
- TIV_CH4_noncombustion_gas_domestic +
- TIV_CH4_noncombustion_oil_domestic +
- TIV_CH4_noncombustion_anthracite_domestic +
- TIV_CH4_noncombustion_bituminouscoal_domestic +
- TIV_CH4_noncombustion_cokingcoal_domestic +
- TIV_CH4_noncombustion_lignite_domestic +
- TIV_CH4_noncombustion_subbituminouscoal_domestic +
- TIV_CH4_noncombustion_oilrefinery_domestic +
- TIV_CH4_agriculture_domestic +
- TIV_CH4_waste_domestic +
- TIV_N2O_domestic +
- TIV_N2O_agriculture_domestic +
- TIV_SF6_domestic + TIV_HFC_domestic + TIV_PFC_domestic,
- q1_co2eq_domestic = QUINTILE1*TIV_CO2eq_domestic,
- q2_co2eq_domestic = QUINTILE2*TIV_CO2eq_domestic,
- q3_co2eq_domestic = QUINTILE3*TIV_CO2eq_domestic,
- q4_co2eq_domestic = QUINTILE4*TIV_CO2eq_domestic,
- q5_co2eq_domestic = QUINTILE5*TIV_CO2eq_domestic,
- co2eq_total_domestic = q1_co2eq_domestic + q2_co2eq_domestic + q3_co2eq_domestic + q4_co2eq_domestic + q5_co2eq_domestic,
- TIV_CO2eq_europe = TIV_CO2_europe +
- TIV_CH4_europe +
- TIV_CH4_noncombustion_gas_europe +
- TIV_CH4_noncombustion_oil_europe +
- TIV_CH4_noncombustion_anthracite_europe +
- TIV_CH4_noncombustion_bituminouscoal_europe +
- TIV_CH4_noncombustion_cokingcoal_europe +
- TIV_CH4_noncombustion_lignite_europe +
- TIV_CH4_noncombustion_subbituminouscoal_europe +
- TIV_CH4_noncombustion_oilrefinery_europe +
- TIV_CH4_agriculture_europe +
- TIV_CH4_waste_europe +
- TIV_N2O_europe +
- TIV_N2O_agriculture_europe +
- TIV_SF6_europe + TIV_HFC_europe + TIV_PFC_europe,
- q1_co2eq_europe = QUINTILE1*(TIV_CO2eq_europe - TIV_CO2eq_domestic),
- q2_co2eq_europe = QUINTILE2*(TIV_CO2eq_europe - TIV_CO2eq_domestic),
- q3_co2eq_europe = QUINTILE3*(TIV_CO2eq_europe - TIV_CO2eq_domestic),
- q4_co2eq_europe = QUINTILE4*(TIV_CO2eq_europe - TIV_CO2eq_domestic),
- q5_co2eq_europe = QUINTILE5*(TIV_CO2eq_europe - TIV_CO2eq_domestic),
- co2eq_total_europe = q1_co2eq_europe + q2_co2eq_europe + q3_co2eq_europe + q4_co2eq_europe + q5_co2eq_europe,
- TIV_energy,
- q1_energy = QUINTILE1*TIV_energy,
- q2_energy = QUINTILE2*TIV_energy,
- q3_energy = QUINTILE3*TIV_energy,
- q4_energy = QUINTILE4*TIV_energy,
- q5_energy = QUINTILE5*TIV_energy,
- energy_total = q1_energy+q2_energy+q3_energy+q4_energy+q5_energy,
- TIV_energy_domestic,
- q1_energy_domestic = QUINTILE1*TIV_energy_domestic,
- q2_energy_domestic = QUINTILE2*TIV_energy_domestic,
- q3_energy_domestic = QUINTILE3*TIV_energy_domestic,
- q4_energy_domestic = QUINTILE4*TIV_energy_domestic,
- q5_energy_domestic = QUINTILE5*TIV_energy_domestic,
- energy_total_domestic = q1_energy_domestic+q2_energy_domestic+q3_energy_domestic+q4_energy_domestic+q5_energy_domestic,
- TIV_energy_europe,
- q1_energy_europe = QUINTILE1*(TIV_energy_europe - TIV_energy_domestic),
- q2_energy_europe = QUINTILE2*(TIV_energy_europe - TIV_energy_domestic),
- 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)
-
-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"))
-
-
-### create compressed results_ixi rds file
-
-#if (!require("pacman")) install.packages("pacman")
-#pacman::p_load(tidyverse,
-# janitor,
-# here)
-
-#dat_all = read_csv(here("data/results_ixi.csv")) %>%
-# clean_names()
-
-dat_all = results_with_direct_FD_fp %>%
- clean_names()
-
-# convert sector labels to IDs
-sectors = dat_all %>%
- distinct(sector) %>%
- mutate(sector_id = row_number())
-
-#write_csv(sectors, here("data/sector_labels.csv"))
-write_csv(sectors, paste0(data_dir_income_stratified_footprints, "/sectors_method1_pxp_pps_hh.csv"))
-
-# convert aggregated sector labels to IDs
-sectors_agg = dat_all %>%
- distinct(five_sectors) %>%
- mutate(sector_agg_id = row_number())
-
-#write_csv(sectors_agg, here("data/sector_agg_labels.csv"))
-write_csv(sectors_agg, paste0(data_dir_income_stratified_footprints, "/sectors_agg_method1_pxp_pps_hh.csv"))
-
-# convert COICOP labels to IDs
-coicop = dat_all %>%
- distinct(coicop) %>%
- mutate(coicop_id = row_number())
-
-#write_csv(sectors_agg, here("data/sector_agg_labels.csv"))
-write_csv(coicop, paste0(data_dir_income_stratified_footprints, "/coicop_method1_pxp_pps_hh.csv"))
-
-# replace sector text labels with numerical IDs (save space)
-dat_compressed = dat_all %>%
- left_join(sectors, by="sector") %>%
- left_join(sectors_agg, by="five_sectors") %>%
- left_join(coicop, by = "coicop") %>%
- select(-c(sector, five_sectors,coicop))
-
-# extract sector aggregation
-sector_mapping = dat_compressed %>%
- group_by(sector_id) %>%
- summarise(sector_agg_id = first(sector_agg_id),
- coicop_id = first(coicop_id))
-
-# collapse country of origin
-dat_results = dat_compressed %>%
- select(-sector_agg_id,-coicop_id) %>%
- group_by(year, geo, sector_id) %>%
- summarise_if(is.numeric, sum, na.rm = TRUE)
-
-## extract final demand and pivot long
-cols_final_demand = c("quintile1", "quintile2", "quintile3", "quintile4", "quintile5")
-tmp_fd = dat_results %>%
- select(year, geo, sector_id, cols_final_demand) %>%
- pivot_longer(cols = cols_final_demand,
- names_to = "quintile",
- values_to = "fd_me") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-## extract co2 and pivot long
-cols_co2 = c("q1_co2", "q2_co2", "q3_co2", "q4_co2", "q5_co2")
-tmp_co2 = dat_results %>%
- select(year, geo, sector_id, cols_co2) %>%
- pivot_longer(cols = cols_co2,
- names_to = "quintile",
- values_to = "co2_kg") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-## extract co2 domestic and pivot long
-cols_co2_domestic = c("q1_co2_domestic", "q2_co2_domestic", "q3_co2_domestic", "q4_co2_domestic", "q5_co2_domestic")
-tmp_co2_domestic = dat_results %>%
- select(year, geo, sector_id, cols_co2_domestic) %>%
- pivot_longer(cols = cols_co2_domestic,
- names_to = "quintile",
- values_to = "co2_domestic_kg") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-## extract co2 europe and pivot long
-cols_co2_europe = c("q1_co2_europe", "q2_co2_europe", "q3_co2_europe", "q4_co2_europe", "q5_co2_europe")
-tmp_co2_europe = dat_results %>%
- select(year, geo, sector_id, cols_co2_europe) %>%
- pivot_longer(cols = cols_co2_europe,
- names_to = "quintile",
- values_to = "co2_europe_kg") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-
-## extract co2eq and pivot long
-cols_co2eq = c("q1_co2eq", "q2_co2eq", "q3_co2eq", "q4_co2eq", "q5_co2eq")
-tmp_co2eq = dat_results %>%
- select(year, geo, sector_id, cols_co2eq) %>%
- pivot_longer(cols = cols_co2eq,
- names_to = "quintile",
- values_to = "co2eq_kg") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-## extract co2eq domestic and pivot long
-cols_co2eq_domestic = c("q1_co2eq_domestic", "q2_co2eq_domestic", "q3_co2eq_domestic", "q4_co2eq_domestic", "q5_co2eq_domestic")
-tmp_co2eq_domestic = dat_results %>%
- select(year, geo, sector_id, cols_co2eq_domestic) %>%
- pivot_longer(cols = cols_co2eq_domestic,
- names_to = "quintile",
- values_to = "co2eq_domestic_kg") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-## extract co2eq europe and pivot long
-cols_co2eq_europe = c("q1_co2eq_europe", "q2_co2eq_europe", "q3_co2eq_europe", "q4_co2eq_europe", "q5_co2eq_europe")
-tmp_co2eq_europe = dat_results %>%
- select(year, geo, sector_id, cols_co2eq_europe) %>%
- pivot_longer(cols = cols_co2eq_europe,
- names_to = "quintile",
- values_to = "co2eq_europe_kg") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-## extract energy use and pivot long
-cols_energy = c("q1_energy","q2_energy","q3_energy","q4_energy","q5_energy")
-tmp_energy = dat_results %>%
- select(year, geo, sector_id, cols_energy) %>%
- pivot_longer(cols = cols_energy,
- names_to = "quintile",
- values_to = "energy_use_TJ") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-## extract energy domestic and pivot long
-cols_energy_domestic = c("q1_energy_domestic","q2_energy_domestic","q3_energy_domestic","q4_energy_domestic","q5_energy_domestic")
-tmp_energy_domestic = dat_results %>%
- select(year, geo, sector_id, cols_energy_domestic) %>%
- pivot_longer(cols = cols_energy_domestic,
- names_to = "quintile",
- values_to = "energy_use_domestic_TJ") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-## extract energy europe and pivot long
-cols_energy_europe = c("q1_energy_europe","q2_energy_europe","q3_energy_europe","q4_energy_europe","q5_energy_europe")
-tmp_energy_europe = dat_results %>%
- select(year, geo, sector_id, cols_energy_europe) %>%
- pivot_longer(cols = cols_energy_europe,
- names_to = "quintile",
- values_to = "energy_use_europe_TJ") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-### TODO: also convert to other indicators to this format (as blocks above)
-### TODO: left join all indicators back to "results_formated" like her with co2
-results_recombined = tmp_fd %>%
- left_join(tmp_co2, by=c("year", "geo", "sector_id", "quint")) %>%
- left_join(tmp_co2_domestic, by=c("year", "geo", "sector_id", "quint")) %>%
- left_join(tmp_co2_europe, by = c("year", "geo", "sector_id", "quint")) %>%
- left_join(tmp_co2eq, by=c("year", "geo", "sector_id", "quint")) %>%
- left_join(tmp_co2eq_domestic, by=c("year", "geo", "sector_id", "quint")) %>%
- left_join(tmp_co2eq_europe, by = c("year", "geo", "sector_id", "quint")) %>%
- left_join(tmp_energy, by=c("year", "geo", "sector_id", "quint")) %>%
- left_join(tmp_energy_domestic, by=c("year", "geo", "sector_id", "quint")) %>%
- left_join(tmp_energy_europe, by = c("year", "geo", "sector_id", "quint"))
-
-
-
-# finally re-join aggregated sector IDs
-results_formatted = results_recombined %>%
- left_join(sector_mapping, by="sector_id") %>%
- ungroup() %>%
- select(-coicop_id)
-
-#write_rds(results_formated, here("/results_formated.rds"))
-
-write.csv(results_formatted, paste0(data_dir_income_stratified_footprints, "/results_formatted_method1_pxp_pps_hh_no_rent.csv"))
-
-#write_rds(results_formatted, paste0(data_dir_income_stratified_footprints, "/results_formatted_method1_pxp_pps_hh_no_rent.rds"))
-
-
-#write.csv(results_formatted, paste0(data_dir_income_stratified_footprints, "/results_formatted_method1_pxp_pps_ae.csv"))
-#write_rds(results_formatted, paste0(data_dir_income_stratified_footprints, "/results_formatted_method1_pxp_pps_ae.rds"))
-
-
-
-
-
-
-
-################################################### !!!! method 2 !!!! - IXI version - PPS HH - RENT NOT MAPPED TO EXIOBASE !!!!! #############################
-###############################################################################################################################################################
-###############################################################################################################################################################
-
-
-# 'results' data frame the second way
-
-# aggregate - playing around trying to go the other way
-
-# load 'mean expenditure by quintile' data
-hbs_exp_t133 = read_csv(paste0(data_dir_income_stratified_footprints, "/data/hbs_exp_t133.csv"))
-# rename and arrange by country
-mean_expenditure_by_quintile = hbs_exp_t133 %>%
- rename(geo = 3, quintile = "quantile") %>%
- arrange(geo)
-
-# load 'mean expenditure by quintile and coicop' data
-hbs_str_t223 = read_csv(paste0(data_dir_income_stratified_footprints, "/data/hbs_str_t223.csv"))
-# rename and arrange by country
-mean_expenditure_by_coicop_sector = hbs_str_t223 %>%
- rename(geo = 4, quintile = "quantile") %>%
- arrange(geo)
-
-# create long data sets for both
-
-mean_expenditure_by_quintile_long = mean_expenditure_by_quintile %>%
- filter(unit == "PPS_HH") %>%
- filter(!(quintile %in% c("UNK","TOTAL"))) %>%
- select(-unit) %>%
- gather(year,euro_pps,-quintile,-geo)
-
-mean_expenditure_by_coicop_sector_long = mean_expenditure_by_coicop_sector %>%
- filter(!(quintile %in% c("UNK","TOTAL"))) %>%
- select(-unit) %>%
- gather(year,pm,-quintile,-coicop,-geo) %>%
- mutate(coicop = dplyr::recode(coicop, "CP041" = "rent",
- "CP042" = "rent")) %>%
- group_by(geo,quintile,coicop,year) %>%
- mutate(pm = parse_number(pm),
- pm = as.numeric(pm)) %>%
- summarise(pm = sum(pm, na.rm = TRUE)) %>%
- ungroup() %>%
- mutate(pm = ifelse(geo == "DE" & year == 2005 & quintile == "QUINTILE1" &
- coicop == "CP072", 92-21-14,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2005 & quintile == "QUINTILE2" &
- coicop == "CP072", 108-22-12,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2005 & quintile == "QUINTILE3" &
- coicop == "CP072", 124-32-11,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2005 & quintile == "QUINTILE4" &
- coicop == "CP072", 133-43-10,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2005 & quintile == "QUINTILE5" &
- coicop == "CP072", 162-81-11,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2010 & quintile == "QUINTILE1" &
- coicop == "CP044", 412-4-78-322,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2010 & quintile == "QUINTILE2" &
- coicop == "CP044", 355-5-68-265,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2010 & quintile == "QUINTILE3" &
- coicop == "CP044", 325-8-64-229,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2010 & quintile == "QUINTILE4" &
- coicop == "CP044", 300-9-58-204,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2010 & quintile == "QUINTILE5" &
- coicop == "CP044", 249-10-46-167,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2015 & quintile == "QUINTILE1" &
- coicop == "CP044", 433-3-82-340,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2015 & quintile == "QUINTILE2" &
- coicop == "CP044", 376-6-70-284,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2015 & quintile == "QUINTILE3" &
- coicop == "CP044", 351-9-67-251,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2015 & quintile == "QUINTILE4" &
- coicop == "CP044", 326-10-61-228,pm)) %>%
- mutate(pm = ifelse(geo == "DE" & year == 2015 & quintile == "QUINTILE5" &
- coicop == "CP044", 280-9-49-195,pm))
-
-join_expenditures = mean_expenditure_by_coicop_sector_long %>%
- left_join(mean_expenditure_by_quintile_long, by = c("geo","quintile","year")) %>%
- mutate(euro_pps = as.numeric(euro_pps),
- pm = as.numeric(pm),
- euro_pps_coicop = pm*(euro_pps/1000))
-
-
-# load margin tables
-
-trade_and_transport = read.csv(paste0(data_dir_income_stratified_footprints, "/data/SNA_TABLE45_20042020103737298.csv")) %>%
- select(LOCATION, PRODUCT, Product, Year, Value) %>%
- mutate(geo = dplyr::recode(LOCATION,"AUT" = "AT",
- "BEL" = "BE",
- "CYP" = "CY",
- "CZE" = "CZ",
- "DNK" = "DK",
- "EST" = "EE",
- "FIN" = "FI",
- "FRA" = "FR",
- "DEU" = "DE",
- "GRC" = "EL",
- "HUN" = "HU",
- "IRL" = "IE",
- "ITA" = "IT",
- "LVA" = "LV",
- "LTU" = "LT",
- "LUX" = "LU",
- "MLT" = "MT",
- "MNE" = "ME",
- "NLD" = "NL",
- "NOR" = "NO",
- "POL" = "PL",
- "PRT" = "PT",
- "ROU" = "RO",
- "SRB" = "RS",
- "SVK" = "SK",
- "SVN" = "SI",
- "ESP" = "ES",
- "SWE" = "SE",
- "CHE" = "CH",
- "MKD" = "MK",
- "TUR" = "TR",
- "GBR" = "UK",
- "BGR" = "BG",
- "HRV" = "HR")) %>%
- select(geo, Year, PRODUCT, Value) %>%
- rename(year = Year,
- trade_and_transport = Value) %>%
- mutate(trade_and_transport = trade_and_transport/100) %>%
- rename(geo_join = geo)
-
-
-
-taxes_less_subsidies = read.csv(paste0(data_dir_income_stratified_footprints, "/data/SNA_TABLE45_20042020104120395.csv")) %>%
- select(LOCATION, PRODUCT, Product, Year, Value) %>%
- mutate(geo = dplyr::recode(LOCATION,"AUT" = "AT",
- "BEL" = "BE",
- "CYP" = "CY",
- "CZE" = "CZ",
- "DNK" = "DK",
- "EST" = "EE",
- "FIN" = "FI",
- "FRA" = "FR",
- "DEU" = "DE",
- "GRC" = "EL",
- "HUN" = "HU",
- "IRL" = "IE",
- "ITA" = "IT",
- "LVA" = "LV",
- "LTU" = "LT",
- "LUX" = "LU",
- "MLT" = "MT",
- "MNE" = "ME",
- "NLD" = "NL",
- "NOR" = "NO",
- "POL" = "PL",
- "PRT" = "PT",
- "ROU" = "RO",
- "SRB" = "RS",
- "SVK" = "SK",
- "SVN" = "SI",
- "ESP" = "ES",
- "SWE" = "SE",
- "CHE" = "CH",
- "MKD" = "MK",
- "TUR" = "TR",
- "GBR" = "UK",
- "BGR" = "BG",
- "HRV" = "HR")) %>%
- select(geo, Year, PRODUCT, Value) %>%
- rename(year = Year,
- taxes_less_subsidies = Value) %>%
- mutate(taxes_less_subsidies = taxes_less_subsidies/100) %>%
- rename(geo_join = geo)
-
-# create margins dataframe
-
-geo_real = rep(c("AT",
- "BE",
- "CY",
- "CZ",
- "DK",
- "EE",
- "FI",
- "FR",
- "DE",
- "EL",
- "HU",
- "IE",
- "IT",
- "LV",
- "LT",
- "LU",
- "MT",
- "ME",
- "NL",
- "NO",
- "PL",
- "PT",
- "RO",
- "RS",
- "SK",
- "SI",
- "ES",
- "SE",
- "MK",
- "TR",
- "UK",
- "BG",
- "HR"),each = 16)
-
-geo_join = rep(c("AT",
- "BE",
- "CY",
- "CZ",
- "DK",
- "LV",
- "FI",
- "FR",
- "AT",
- "EL",
- "HU",
- "UK",
- "IT",
- "LV",
- "LV",
- "LU",
- "MT",
- "ME",
- "NL",
- "FI",
- "PL",
- "PT",
- "RO",
- "RS",
- "SK",
- "SI",
- "PT",
- "FI",
- "MK",
- "BG",
- "UK",
- "BG",
- "HR"),each = 16)
-
-year = rep(2010,length(geo_real))
-
-PRODUCT = c("P10_12",
- "P13_15",
- "P68A",
- "PF",
- "PE",
- "PD",
- "PC",
- "PQ",
- "P29",
- "P19",
- "P30",
- "P61",
- "PR",
- "PP",
- "PI",
- "PS")
-
-margin_sectors = data.frame(geo_real,geo_join,year,PRODUCT)
-
-# join everything - and impute
-
-margins = margin_sectors %>%
- left_join(taxes_less_subsidies, by = c("geo_join","year","PRODUCT")) %>%
- left_join(trade_and_transport, by = c("geo_join","year","PRODUCT")) %>%
- select(-geo_join) %>%
- rename(geo = geo_real) %>%
- mutate(taxes_less_subsidies = ifelse(geo == "CZ" & PRODUCT == "P68A", 0, taxes_less_subsidies)) %>%
- mutate(trade_and_transport = ifelse(geo == "CZ" & PRODUCT == "P68A", 0, trade_and_transport)) %>%
- mutate(taxes_less_subsidies = ifelse(geo == "SK" & PRODUCT == "P68A", 0, taxes_less_subsidies)) %>%
- mutate(trade_and_transport = ifelse(geo == "SK" & PRODUCT == "P68A", 0, trade_and_transport)) %>%
- select(-year)
-
-
-# join margin data to join_expenditures
-
-with_margins = join_expenditures %>%
- mutate(year = as.numeric(year),
- PRODUCT = dplyr::recode(coicop,
- "CP011" = "P10_12",
- "CP012" = "P10_12",
- "CP02" = "P10_12",
- "CP03" = "P13_15",
- "rent" = "P68A",
- "CP043" = "PF",
- "CP044" = "PE",
- "CP045" = "PD",
- "CP05" = "PC",
- "CP06" = "PQ",
- "CP071" = "P29",
- "CP072" = "P19",
- "CP073" = "P30",
- "CP08" = "P61",
- "CP09" = "PR",
- "CP10" = "PP",
- "CP11" = "PI",
- "CP12" = "PS")) %>%
- left_join(margins, by = c("geo","PRODUCT")) %>%
- mutate(euro_pps_coicop_bp = euro_pps_coicop*(1 - (trade_and_transport + taxes_less_subsidies)))
-
-
-# re-create expenditure
-
-mean_expenditure_by_quintile_long_bp = with_margins %>%
- group_by(quintile,geo,year) %>%
- summarise(euro_pps_bp = sum(euro_pps_coicop_bp, na.rm = TRUE))
-
-
-mean_expenditure_by_coicop_sector_long_bp = with_margins %>%
- left_join(mean_expenditure_by_quintile_long_bp, by = c("quintile","geo","year")) %>%
- mutate(pm_bp = (euro_pps_coicop_bp/euro_pps_bp)*1000) %>%
- select(quintile,coicop,geo,year,pm_bp)
-
-
-###
-
-shares = join_expenditures %>%
- group_by(coicop,geo,year) %>%
- mutate(share = euro_pps_coicop/sum(euro_pps_coicop))
-
-
-################################################### !!!! method 2 - IXI version - PPS HH NO RENT !!!! ####################################################
-##########################################################################################################################################################
-##########################################################################################################################################################
-
-# pre-processing
-
-data_dir_exiobase = paste("/",file.path("data","metab","Exiobase", fsep=.Platform$file.sep),sep="")
-
-# Exiobase - ixi version
-
-years_exb_ixi = c(2005,2010,2015)
-
-
-Eurostat_countries_hh_fd = NULL
-
-total_fd = NULL
-
-TIVs = NULL
-
-domestic_TIVs = NULL
-
-europe_TIVs = NULL
-
-national_fp = NULL
-
-for (i in years_exb_ixi){
- year_current = i
-
- Exiobase_FD = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/FD_",year_current,"_ixi.csv"))[,-1]
-
- # select household final demand vectors for relevant countries - figure out how to soft code this
-
-
- AT = Exiobase_FD[,1]
- BE = Exiobase_FD[,8]
- BG = Exiobase_FD[,15]
- CY = Exiobase_FD[,22]
- CZ = Exiobase_FD[,29]
- DE = Exiobase_FD[,36]
- DK = Exiobase_FD[,43]
- EE = Exiobase_FD[,50]
- EL = Exiobase_FD[,78]
- ES = Exiobase_FD[,57]
- FI = Exiobase_FD[,64]
- FR = Exiobase_FD[,71]
- HR = Exiobase_FD[,85]
- HU = Exiobase_FD[,92]
- IE = Exiobase_FD[,99]
- IT = Exiobase_FD[,106]
- LT = Exiobase_FD[,113]
- LU = Exiobase_FD[,120]
- LV = Exiobase_FD[,127]
- MT = Exiobase_FD[,134]
- NL = Exiobase_FD[,141]
- NO = Exiobase_FD[,288]
- PL = Exiobase_FD[,148]
- PT = Exiobase_FD[,155]
- RO = Exiobase_FD[,162]
- SE = Exiobase_FD[,169]
- SI = Exiobase_FD[,176]
- SK = Exiobase_FD[,183]
- TR = Exiobase_FD[,274]
- UK = Exiobase_FD[,190]
-
- Eurostat_countries = cbind(AT,BE,BG,CY,CZ,DE,DK,EE,EL,ES,FI,FR,HR,HU,IE,IT,LT,LU,LV,MT,NL,NO,PL,PT,RO,SE,SI,SK,TR,UK)
-
- year = as.character(rep(year_current,nrow(Eurostat_countries)))
- look_Eurostat_countries = cbind(year,Eurostat_countries)
-
- Eurostat_countries_hh_fd = rbind(Eurostat_countries_hh_fd,look_Eurostat_countries)
-
-
- eurostat_countries_colsums = colSums(Eurostat_countries)
-
- geo = data.frame(c("AT","BE","BG","CY","CZ","DE","DK","EE","EL","ES","FI",
- "FR","HR","HU","IE","IT","LT","LU","LV","MT","NL","NO",
- "PL","PT","RO","SE","SI","SK","TR","UK")) %>% rename_at(1,~"geo")
-
- year = rep(year_current, 30)
-
- fds = cbind(geo,year,eurostat_countries_colsums) %>% slice(rep(1:n(), each = 5))
-
- quintiles = data.frame(rep(c("QUINTILE1","QUINTILE2","QUINTILE3","QUINTILE4","QUINTILE5"),30)) %>% rename_at(1,~"quintile")
-
- total_fd_year_current = cbind(fds,quintiles)
-
- total_fd = rbind(total_fd, total_fd_year_current)
-
- # labels
-
- Exiobase_T_labels = read.csv(paste0(data_dir_income_stratified_footprints, "/data/Exiobase_T_labels_ixi_w_coicop_mapping_no_rent.csv")) %>%
- mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"))
-
- # TIVs
-
- # CO2 - combustion - air
-
- Exiobase_TIV_co2_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_co2_combustion_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_co2_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_combustion_air_", year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CO2_domestic)
-
- Exiobase_TIV_europe_breakdown_co2_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_combustion_air_", year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CO2_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_CO2_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CO2_europe,TIV_CO2_not_europe)
-
- # CO2 - noncombustion - cement - air
-
- Exiobase_TIV_co2_noncombustion_cement_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_co2_noncombustion_cement_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_co2_noncombustion_cement_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_noncombustion_cement_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CO2_noncombustion_cement_domestic)
-
- Exiobase_TIV_europe_breakdown_co2_noncombustion_cement_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_noncombustion_cement_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CO2_noncombustion_cement_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_CO2_noncombustion_cement_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CO2_noncombustion_cement_europe,TIV_CO2_noncombustion_cement_not_europe)
-
- # CO2 - noncombustion - lime - air
-
- Exiobase_TIV_co2_noncombustion_lime_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_co2_noncombustion_lime_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_co2_noncombustion_lime_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_noncombustion_lime_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CO2_noncombustion_lime_domestic)
-
- Exiobase_TIV_europe_breakdown_co2_noncombustion_lime_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_noncombustion_lime_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CO2_noncombustion_lime_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_CO2_noncombustion_lime_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CO2_noncombustion_lime_europe,TIV_CO2_noncombustion_lime_not_europe)
-
- # CO2 - agriculture - peat decay - air
-
- Exiobase_TIV_co2_agriculture_peatdecay_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_co2_agriculture_peatdecay_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_co2_agriculture_peatdecay_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_agriculture_peatdecay_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CO2_agriculture_peatdecay_domestic)
-
- Exiobase_TIV_europe_breakdown_co2_agriculture_peatdecay_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_agriculture_peatdecay_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CO2_agriculture_peatdecay_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_CO2_agriculture_peatdecay_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CO2_agriculture_peatdecay_europe,TIV_CO2_agriculture_peatdecay_not_europe)
-
- # CO2 - waste - biogenic - air
-
- Exiobase_TIV_co2_waste_biogenic_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_co2_biogenic_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_co2_waste_biogenic_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_biogenic_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CO2_waste_biogenic_domestic)
-
- Exiobase_TIV_europe_breakdown_co2_waste_biogenic_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_biogenic_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CO2_waste_biogenic_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_CO2_waste_biogenic_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CO2_waste_biogenic_europe,TIV_CO2_waste_biogenic_not_europe)
-
- # CO2 - waste - fossil - air
-
- Exiobase_TIV_co2_waste_fossil_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_co2_waste_fossil_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_co2_waste_fossil_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_waste_fossil_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CO2_waste_fossil_domestic)
-
- Exiobase_TIV_europe_breakdown_co2_waste_fossil_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_co2_waste_fossil_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CO2_waste_fossil_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_CO2_waste_fossil_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CO2_waste_fossil_europe,TIV_CO2_waste_fossil_not_europe)
-
-
- # CH4 - combustion -air
-
- Exiobase_TIV_ch4_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_combustion_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_combustion_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_combustion_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_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_CH4_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_europe,TIV_CH4_not_europe)
-
- # CH4 - noncombustion - gas - air
-
- Exiobase_TIV_ch4_noncombustion_gas_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_noncombustion_gas_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_noncombustion_gas_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_gas_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_noncombustion_gas_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_gas_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_gas_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_noncombustion_gas_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_CH4_noncombustion_gas_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_noncombustion_gas_europe,TIV_CH4_noncombustion_gas_not_europe)
-
- # CH4 - noncombustion - oil - air
-
- Exiobase_TIV_ch4_noncombustion_oil_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_noncombustion_oil_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_noncombustion_oil_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_oil_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_noncombustion_oil_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_oil_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_oil_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_noncombustion_oil_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_CH4_noncombustion_oil_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_noncombustion_oil_europe,TIV_CH4_noncombustion_oil_not_europe)
-
- # CH4 - noncombustion - anthracite - air
-
- Exiobase_TIV_ch4_noncombustion_anthracite_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_noncombustion_anthracite_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_noncombustion_anthracite_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_anthracite_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_noncombustion_anthracite_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_anthracite_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_anthracite_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_noncombustion_anthracite_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_CH4_noncombustion_anthracite_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_noncombustion_anthracite_europe,TIV_CH4_noncombustion_anthracite_not_europe)
-
- # CH4 - noncombustion - bituminouscoal - air
-
- Exiobase_TIV_ch4_noncombustion_bituminouscoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_noncombustion_bituminouscoal_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_noncombustion_bituminouscoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_bituminouscoal_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_noncombustion_bituminouscoal_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_bituminouscoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_bituminouscoal_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_noncombustion_bituminouscoal_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_CH4_noncombustion_bituminouscoal_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_noncombustion_bituminouscoal_europe,TIV_CH4_noncombustion_bituminouscoal_not_europe)
-
- # CH4 - noncombustion - cokingcoal - air
-
- Exiobase_TIV_ch4_noncombustion_cokingcoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_noncombustion_cokingcoal_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_noncombustion_cokingcoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_cokingcoal_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_noncombustion_cokingcoal_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_cokingcoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_cokingcoal_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_noncombustion_cokingcoal_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_CH4_noncombustion_cokingcoal_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_noncombustion_cokingcoal_europe,TIV_CH4_noncombustion_cokingcoal_not_europe)
-
- # CH4 - noncombustion - lignite - air
-
- Exiobase_TIV_ch4_noncombustion_lignite_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_noncombustion_lignite_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_noncombustion_lignite_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_lignite_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_noncombustion_lignite_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_lignite_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_lignite_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_noncombustion_lignite_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_CH4_noncombustion_lignite_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_noncombustion_lignite_europe,TIV_CH4_noncombustion_lignite_not_europe)
-
- # CH4 - noncombustion - subbituminouscoal - air
-
- Exiobase_TIV_ch4_noncombustion_subbituminouscoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_noncombustion_subbituminouscoal_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_noncombustion_subbituminouscoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_subbituminouscoal_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_noncombustion_subbituminouscoal_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_subbituminouscoal_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_subbituminouscoal_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_noncombustion_subbituminouscoal_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_CH4_noncombustion_subbituminouscoal_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_noncombustion_subbituminouscoal_europe,TIV_CH4_noncombustion_subbituminouscoal_not_europe)
-
- # CH4 - noncombustion - oilrefinery - air
-
- Exiobase_TIV_ch4_noncombustion_oilrefinery_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_noncombustion_oilrefinery_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_noncombustion_oilrefinery_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_oilrefinery_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_noncombustion_oilrefinery_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_oilrefinery_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_noncombustion_oilrefinery_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_noncombustion_oilrefinery_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_CH4_noncombustion_oilrefinery_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_noncombustion_oilrefinery_europe,TIV_CH4_noncombustion_oilrefinery_not_europe)
-
- # CH4 - agriculture - air
-
- Exiobase_TIV_ch4_agriculture_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_agriculture_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_agriculture_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_agriculture_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_agriculture_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_agriculture_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_agriculture_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_agriculture_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_CH4_agriculture_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_agriculture_europe,TIV_CH4_agriculture_not_europe)
-
- # CH4 - waste - air
-
- Exiobase_TIV_ch4_waste_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_ch4_CO2eq_waste_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_ch4_waste_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_waste_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_CH4_waste_domestic)
-
- Exiobase_TIV_europe_breakdown_ch4_waste_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_ch4_CO2eq_waste_air_", year_current, "_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_CH4_waste_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_CH4_waste_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_CH4_waste_europe,TIV_CH4_waste_not_europe)
-
-
- # N2O - combustion - air
-
- Exiobase_TIV_n2o_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_n2o_CO2eq_combustion_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_n2o_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_n2o_CO2eq_combustion_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_N2O_domestic)
-
- Exiobase_TIV_europe_breakdown_n2o_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_n2o_CO2eq_combustion_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_N2O_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_N2O_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_N2O_europe,TIV_N2O_not_europe)
-
- # N2O - agriculture - air
-
- Exiobase_TIV_n2o_agriculture_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_n2o_CO2eq_agriculture_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_n2o_agriculture_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_n2o_CO2eq_agriculture_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_N2O_agriculture_domestic)
-
- Exiobase_TIV_europe_breakdown_n2o_agriculture_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_n2o_CO2eq_agriculture_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_N2O_agriculture_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_N2O_agriculture_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_N2O_agriculture_europe,TIV_N2O_agriculture_not_europe)
-
- # SF6 - air
-
- Exiobase_TIV_sf6_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_sf6_CO2eq_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_sf6_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_sf6_CO2eq_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_SF6_domestic)
-
- Exiobase_TIV_europe_breakdown_sf6_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_sf6_CO2eq_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_SF6_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_SF6_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_SF6_europe,TIV_SF6_not_europe)
-
- # HFC - air
-
- Exiobase_TIV_hfc_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_hfc_CO2eq_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_hfc_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_hfc_CO2eq_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_HFC_domestic)
-
- Exiobase_TIV_europe_breakdown_hfc_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_hfc_CO2eq_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_HFC_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_HFC_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_HFC_europe,TIV_HFC_not_europe)
-
- # PFC - air
-
- Exiobase_TIV_pfc_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_pfc_CO2eq_air_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_pfc_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_pfc_CO2eq_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_PFC_domestic)
-
- Exiobase_TIV_europe_breakdown_pfc_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_pfc_CO2eq_air_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_PFC_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_PFC_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- ZA) %>%
- select(TIV_PFC_europe,TIV_PFC_not_europe)
-
- # Energy use
-
- Exiobase_TIV_energy_use_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_energy_carrier_use_",year_current,"_ixi.csv"))[,-1]
-
- Exiobase_TIV_country_breakdown_energy_use_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_energy_carrier_use_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- gather(country, TIV_energy_domestic)
-
- Exiobase_TIV_europe_breakdown_energy_use_bp = read.csv(paste0(data_dir_exiobase, "/IOT_",year_current,"_ixi/TIV_country_breakdown_energy_carrier_use_",year_current,"_ixi.csv"))[,-1] %>%
- row_to_names(row_number = 1) %>%
- mutate_at(vars(AT:ZA), funs(as.numeric(as.character(.)))) %>%
- mutate(TIV_energy_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_energy_not_europe = AU +
- BR + CA + CH + CN +
- ID + IN + JP + KR +
- MX + RU + TW + US +
- WA + WE + WF + WL + WM +
- 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,
- t(Exiobase_TIV_co2_bp),
- t(Exiobase_TIV_co2_noncombustion_cement_bp),
- t(Exiobase_TIV_co2_noncombustion_lime_bp),
- t(Exiobase_TIV_co2_agriculture_peatdecay_bp),
- t(Exiobase_TIV_co2_waste_biogenic_bp),
- t(Exiobase_TIV_co2_waste_fossil_bp),
- t(Exiobase_TIV_ch4_bp),
- t(Exiobase_TIV_ch4_noncombustion_gas_bp),
- t(Exiobase_TIV_ch4_noncombustion_oil_bp),
- t(Exiobase_TIV_ch4_noncombustion_anthracite_bp),
- t(Exiobase_TIV_ch4_noncombustion_bituminouscoal_bp),
- t(Exiobase_TIV_ch4_noncombustion_cokingcoal_bp),
- t(Exiobase_TIV_ch4_noncombustion_lignite_bp),
- t(Exiobase_TIV_ch4_noncombustion_subbituminouscoal_bp),
- t(Exiobase_TIV_ch4_noncombustion_oilrefinery_bp),
- t(Exiobase_TIV_ch4_agriculture_bp),
- t(Exiobase_TIV_ch4_waste_bp),
- t(Exiobase_TIV_n2o_bp),
- t(Exiobase_TIV_n2o_agriculture_bp),
- 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)) %>%
- 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)",
- TIV_CO2_agriculture_peatdecay = "t(Exiobase_TIV_co2_agriculture_peatdecay_bp)",
- TIV_CO2_waste_biogenic = "t(Exiobase_TIV_co2_waste_biogenic_bp)",
- TIV_CO2_waste_fossil = "t(Exiobase_TIV_co2_waste_fossil_bp)",
- TIV_CH4 = "t(Exiobase_TIV_ch4_bp)",
- TIV_CH4_noncombustion_gas = "t(Exiobase_TIV_ch4_noncombustion_gas_bp)",
- TIV_CH4_noncombustion_oil = "t(Exiobase_TIV_ch4_noncombustion_oil_bp)",
- TIV_CH4_noncombustion_anthracite = "t(Exiobase_TIV_ch4_noncombustion_anthracite_bp)",
- TIV_CH4_noncombustion_bituminouscoal = "t(Exiobase_TIV_ch4_noncombustion_bituminouscoal_bp)",
- TIV_CH4_noncombustion_cokingcoal = "t(Exiobase_TIV_ch4_noncombustion_cokingcoal_bp)",
- TIV_CH4_noncombustion_lignite = "t(Exiobase_TIV_ch4_noncombustion_lignite_bp)",
- TIV_CH4_noncombustion_subbituminouscoal = "t(Exiobase_TIV_ch4_noncombustion_subbituminouscoal_bp)",
- TIV_CH4_noncombustion_oilrefinery = "t(Exiobase_TIV_ch4_noncombustion_oilrefinery_bp)",
- TIV_CH4_agriculture = "t(Exiobase_TIV_ch4_agriculture_bp)",
- TIV_CH4_waste = "t(Exiobase_TIV_ch4_waste_bp)",
- TIV_N2O = "t(Exiobase_TIV_n2o_bp)",
- TIV_N2O_agriculture = "t(Exiobase_TIV_n2o_agriculture_bp)",
- 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)") %>%
- mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"))
-
- year = as.character(rep(year_current,nrow(TIV_with_labels)))
-
- look = cbind(year,TIV_with_labels) %>%
- rename(country_of_production = V1, sector = V2)
-
- TIVs = rbind(TIVs,look)
-
- # domestic TIVs
-
- domestic_TIV_with_labels = cbind(Exiobase_T_labels,
- Exiobase_TIV_country_breakdown_co2_bp,
- Exiobase_TIV_country_breakdown_co2_noncombustion_cement_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_co2_noncombustion_lime_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_co2_agriculture_peatdecay_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_co2_waste_biogenic_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_co2_waste_fossil_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_noncombustion_gas_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_noncombustion_oil_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_noncombustion_anthracite_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_noncombustion_bituminouscoal_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_noncombustion_cokingcoal_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_noncombustion_lignite_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_noncombustion_subbituminouscoal_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_noncombustion_oilrefinery_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_agriculture_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_ch4_waste_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_n2o_bp %>% select(-country),
- Exiobase_TIV_country_breakdown_n2o_agriculture_bp %>% select(-country),
- 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)) %>%
- mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"),
- country = dplyr::recode(country, "GR" = "EL", "GB" = "UK"))
-
- year_domestic = as.character(rep(year_current,nrow(domestic_TIV_with_labels)))
-
- look_domestic = cbind(year_domestic,domestic_TIV_with_labels) %>%
- rename(country_of_production = V1, sector = V2, geo = country, year = year_domestic) %>%
- mutate(TIV_CO2_domestic = as.numeric(TIV_CO2_domestic),
- TIV_CO2_noncombustion_cement_domestic = as.numeric(TIV_CO2_noncombustion_cement_domestic),
- TIV_CO2_noncombustion_lime_domestic = as.numeric(TIV_CO2_noncombustion_lime_domestic),
- TIV_CO2_agriculture_peatdecay_domestic = as.numeric(TIV_CO2_agriculture_peatdecay_domestic),
- TIV_CO2_waste_biogenic_domestic = as.numeric(TIV_CO2_waste_biogenic_domestic),
- TIV_CO2_waste_fossil_domestic = as.numeric(TIV_CO2_waste_fossil_domestic),
- TIV_CH4_domestic = as.numeric(TIV_CH4_domestic),
- TIV_CH4_noncombustion_gas_domestic = as.numeric(TIV_CH4_noncombustion_gas_domestic),
- TIV_CH4_noncombustion_oil_domestic = as.numeric(TIV_CH4_noncombustion_oil_domestic),
- TIV_CH4_noncombustion_anthracite_domestic = as.numeric(TIV_CH4_noncombustion_anthracite_domestic),
- TIV_CH4_noncombustion_bituminouscoal_domestic = as.numeric(TIV_CH4_noncombustion_bituminouscoal_domestic),
- TIV_CH4_noncombustion_cokingcoal_domestic = as.numeric(TIV_CH4_noncombustion_cokingcoal_domestic),
- TIV_CH4_noncombustion_lignite_domestic = as.numeric(TIV_CH4_noncombustion_lignite_domestic),
- TIV_CH4_noncombustion_subbituminouscoal_domestic = as.numeric(TIV_CH4_noncombustion_subbituminouscoal_domestic),
- TIV_CH4_noncombustion_oilrefinery_domestic = as.numeric(TIV_CH4_noncombustion_oilrefinery_domestic),
- TIV_CH4_agriculture_domestic = as.numeric(TIV_CH4_agriculture_domestic),
- TIV_CH4_waste_domestic = as.numeric(TIV_CH4_waste_domestic),
- TIV_N2O_domestic = as.numeric(TIV_N2O_domestic),
- TIV_N2O_agriculture_domestic = as.numeric(TIV_N2O_agriculture_domestic),
- 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))
-
- domestic_TIVs = rbind(domestic_TIVs, look_domestic)
-
- # europe TIVs with labels
-
- europe_TIV_with_labels = cbind(Exiobase_T_labels,
- Exiobase_TIV_europe_breakdown_co2_bp,
- Exiobase_TIV_europe_breakdown_co2_noncombustion_cement_bp,
- Exiobase_TIV_europe_breakdown_co2_noncombustion_lime_bp,
- Exiobase_TIV_europe_breakdown_co2_agriculture_peatdecay_bp,
- Exiobase_TIV_europe_breakdown_co2_waste_biogenic_bp,
- Exiobase_TIV_europe_breakdown_co2_waste_fossil_bp,
- Exiobase_TIV_europe_breakdown_ch4_bp,
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_gas_bp,
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_oil_bp,
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_anthracite_bp,
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_bituminouscoal_bp,
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_cokingcoal_bp,
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_lignite_bp,
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_subbituminouscoal_bp,
- Exiobase_TIV_europe_breakdown_ch4_noncombustion_oilrefinery_bp,
- Exiobase_TIV_europe_breakdown_ch4_agriculture_bp,
- Exiobase_TIV_europe_breakdown_ch4_waste_bp,
- Exiobase_TIV_europe_breakdown_n2o_bp,
- Exiobase_TIV_europe_breakdown_n2o_agriculture_bp,
- 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) %>%
- mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"))
-
- year_europe = as.character(rep(year_current,nrow(europe_TIV_with_labels)))
-
- look_europe = cbind(year_europe,europe_TIV_with_labels) %>%
- rename(country_of_production = V1, sector = V2, year = year_europe) %>%
- mutate(TIV_CO2_europe = as.numeric(TIV_CO2_europe),
- TIV_CO2_noncombustion_cement_europe = as.numeric(TIV_CO2_noncombustion_cement_europe),
- TIV_CO2_noncombustion_lime_europe = as.numeric(TIV_CO2_noncombustion_lime_europe),
- TIV_CO2_agriculture_peatdecay_europe = as.numeric(TIV_CO2_agriculture_peatdecay_europe),
- TIV_CO2_waste_biogenic_europe = as.numeric(TIV_CO2_waste_biogenic_europe),
- TIV_CO2_waste_fossil_europe = as.numeric(TIV_CO2_waste_fossil_europe),
- TIV_CH4_europe = as.numeric(TIV_CH4_europe),
- TIV_CH4_noncombustion_gas_europe = as.numeric(TIV_CH4_noncombustion_gas_europe),
- TIV_CH4_noncombustion_oil_europe = as.numeric(TIV_CH4_noncombustion_oil_europe),
- TIV_CH4_noncombustion_anthracite_europe = as.numeric(TIV_CH4_noncombustion_anthracite_europe),
- TIV_CH4_noncombustion_bituminouscoal_europe = as.numeric(TIV_CH4_noncombustion_bituminouscoal_europe),
- TIV_CH4_noncombustion_cokingcoal_europe = as.numeric(TIV_CH4_noncombustion_cokingcoal_europe),
- TIV_CH4_noncombustion_lignite_europe = as.numeric(TIV_CH4_noncombustion_lignite_europe),
- TIV_CH4_noncombustion_subbituminouscoal_europe = as.numeric(TIV_CH4_noncombustion_subbituminouscoal_europe),
- TIV_CH4_noncombustion_oilrefinery_europe = as.numeric(TIV_CH4_noncombustion_oilrefinery_europe),
- TIV_CH4_agriculture_europe = as.numeric(TIV_CH4_agriculture_europe),
- TIV_CH4_waste_europe = as.numeric(TIV_CH4_waste_europe),
- TIV_N2O_europe = as.numeric(TIV_N2O_europe),
- TIV_N2O_agriculture_europe = as.numeric(TIV_N2O_agriculture_europe),
- 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))
-
- europe_TIVs = rbind(europe_TIVs, look_europe)
-
- # total national footprints
-
- # FD labels
-
- Exiobase_FD_labels = as.data.frame(t(read.csv(paste0(data_dir_exiobase, "/Exiobase_FD_labels_ixi.csv")))[-1,-3]) %>%
- mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"))
-
- national_CO2_footprints = Exiobase_FD * t(Exiobase_TIV_co2_bp)
-
- national_CO2_noncombustion_cement_footprints = Exiobase_FD * t(Exiobase_TIV_co2_noncombustion_cement_bp)
-
- national_CO2_noncombustion_lime_footprints = Exiobase_FD * t(Exiobase_TIV_co2_noncombustion_lime_bp)
-
- national_CO2_agriculture_peatdecay_footprints = Exiobase_FD * t(Exiobase_TIV_co2_agriculture_peatdecay_bp)
-
- national_CO2_waste_biogenic_footprints = Exiobase_FD * t(Exiobase_TIV_co2_waste_biogenic_bp)
-
- national_CO2_waste_fossil_footprints = Exiobase_FD * t(Exiobase_TIV_co2_waste_fossil_bp)
-
- national_CH4_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_bp)
-
- national_CH4_noncombustion_gas_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_noncombustion_gas_bp)
-
- national_CH4_noncombustion_oil_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_noncombustion_oil_bp)
-
- national_CH4_noncombustion_anthracite_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_noncombustion_anthracite_bp)
-
- national_CH4_noncombustion_bituminouscoal_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_noncombustion_bituminouscoal_bp)
-
- national_CH4_noncombustion_cokingcoal_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_noncombustion_cokingcoal_bp)
-
- national_CH4_noncombustion_lignite_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_noncombustion_lignite_bp)
-
- national_CH4_noncombustion_subbituminouscoal_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_noncombustion_subbituminouscoal_bp)
-
- national_CH4_noncombustion_oilrefinery_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_noncombustion_oilrefinery_bp)
-
- national_CH4_agriculture_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_agriculture_bp)
-
- national_CH4_waste_footprints = Exiobase_FD * t(Exiobase_TIV_ch4_waste_bp)
-
- national_N2O_footprints = Exiobase_FD * t(Exiobase_TIV_n2o_bp)
-
- national_N2O_agriculture_footprints = Exiobase_FD * t(Exiobase_TIV_n2o_agriculture_bp)
-
- national_SF6_footprints = Exiobase_FD * t(Exiobase_TIV_sf6_bp)
-
- national_HFC_footprints = Exiobase_FD * t(Exiobase_TIV_hfc_bp)
-
- national_PFC_footprints = Exiobase_FD * t(Exiobase_TIV_pfc_bp)
-
- 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
-
- national_footprints_w_labels = cbind(Exiobase_FD_labels,
- rowSums(t(national_CO2_footprints)),
- rowSums(t(national_CO2_noncombustion_cement_footprints)),
- rowSums(t(national_CO2_noncombustion_lime_footprints)),
- rowSums(t(national_CO2_agriculture_peatdecay_footprints)),
- rowSums(t(national_CO2_waste_biogenic_footprints)),
- rowSums(t(national_CO2_waste_fossil_footprints)),
- rowSums(t(national_CH4_footprints)),
- rowSums(t(national_CH4_noncombustion_gas_footprints)),
- rowSums(t(national_CH4_noncombustion_oil_footprints)),
- rowSums(t(national_CH4_noncombustion_anthracite_footprints)),
- rowSums(t(national_CH4_noncombustion_bituminouscoal_footprints)),
- rowSums(t(national_CH4_noncombustion_cokingcoal_footprints)),
- rowSums(t(national_CH4_noncombustion_lignite_footprints)),
- rowSums(t(national_CH4_noncombustion_subbituminouscoal_footprints)),
- rowSums(t(national_CH4_noncombustion_oilrefinery_footprints)),
- rowSums(t(national_CH4_agriculture_footprints)),
- rowSums(t(national_CH4_waste_footprints)),
- rowSums(t(national_N2O_footprints)),
- rowSums(t(national_N2O_agriculture_footprints)),
- 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))) %>%
- mutate(V1 = dplyr::recode(V1,"GR" = "EL","GB" = "UK"))
-
- year_national_fp = as.character(rep(year_current,nrow(national_footprints_w_labels)))
-
- # direct FD emissions
-
- direct_FD_extensions = read.csv(paste0(data_dir_exiobase, "/IOT_", year_current, "_ixi/satellite/F_hh.csv", sep = ""),row.names=NULL,as.is=TRUE)[3:1115,3:345]
- direct_FD_extensions[is.na(direct_FD_extensions)]=0
- direct_FD_extensions = mapply(direct_FD_extensions, FUN = as.numeric)
- direct_FD_extensions = matrix(data=direct_FD_extensions,ncol=343,nrow=1113)
-
- direct_FD_co2 = direct_FD_extensions[24,]
- direct_FD_co2_noncombustion_cement = direct_FD_extensions[93,]
- direct_FD_co2_noncombustion_lime = direct_FD_extensions[94,]
- direct_FD_co2_agriculture_peatdecay = direct_FD_extensions[428,]
- direct_FD_co2_waste_biogenic = direct_FD_extensions[438,]
- direct_FD_co2_waste_fossil = direct_FD_extensions[439,]
- direct_FD_ch4 = direct_FD_extensions[25,]*28
- direct_FD_ch4_noncombustion_gas = direct_FD_extensions[68,]*28
- direct_FD_ch4_noncombustion_oil = direct_FD_extensions[69,]*28
- direct_FD_ch4_noncombustion_anthracite = direct_FD_extensions[70,]*28
- direct_FD_ch4_noncombustion_bituminouscoal = direct_FD_extensions[71,]*28
- direct_FD_ch4_noncombustion_cokingcoal = direct_FD_extensions[72,]*28
- direct_FD_ch4_noncombustion_lignite = direct_FD_extensions[73,]*28
- direct_FD_ch4_noncombustion_subbituminouscoal = direct_FD_extensions[74,]*28
- direct_FD_ch4_noncombustion_oilrefinery = direct_FD_extensions[75,]*28
- direct_FD_ch4_agriculture = direct_FD_extensions[427,]*28
- direct_FD_ch4_waste = direct_FD_extensions[436,]*28
- direct_FD_n2o = direct_FD_extensions[26,]*265
- direct_FD_n2o_agriculture = direct_FD_extensions[430,]*265
- direct_FD_sf6 = direct_FD_extensions[424,]*23500
- 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,
- direct_FD_co2_noncombustion_cement,
- direct_FD_co2_noncombustion_lime,
- direct_FD_co2_agriculture_peatdecay,
- direct_FD_co2_waste_biogenic,
- direct_FD_co2_waste_fossil,
- direct_FD_ch4,
- direct_FD_ch4_noncombustion_gas,
- direct_FD_ch4_noncombustion_oil,
- direct_FD_ch4_noncombustion_anthracite,
- direct_FD_ch4_noncombustion_bituminouscoal,
- direct_FD_ch4_noncombustion_cokingcoal,
- direct_FD_ch4_noncombustion_lignite,
- direct_FD_ch4_noncombustion_subbituminouscoal,
- direct_FD_ch4_noncombustion_oilrefinery,
- direct_FD_ch4_agriculture,
- direct_FD_ch4_waste,
- direct_FD_n2o,
- direct_FD_n2o_agriculture,
- 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)
-
- look_national_fp = as.data.frame(cbind(year_national_fp,
- national_footprints_w_labels,
- direct_FD_fp)) %>%
- rename(year = year_national_fp,
- geo = V1,
- fd_category = V2,
- co2 = "rowSums(t(national_CO2_footprints))",
- co2_noncombustion_cement = "rowSums(t(national_CO2_noncombustion_cement_footprints))",
- co2_noncombustion_lime = "rowSums(t(national_CO2_noncombustion_lime_footprints))",
- co2_agriculture_peatdecay = "rowSums(t(national_CO2_agriculture_peatdecay_footprints))",
- co2_waste_biogenic = "rowSums(t(national_CO2_waste_biogenic_footprints))",
- co2_waste_fossil = "rowSums(t(national_CO2_waste_fossil_footprints))",
- ch4 = "rowSums(t(national_CH4_footprints))",
- ch4_noncombustion_gas = "rowSums(t(national_CH4_noncombustion_gas_footprints))",
- ch4_noncombustion_oil = "rowSums(t(national_CH4_noncombustion_oil_footprints))",
- ch4_noncombustion_anthracite = "rowSums(t(national_CH4_noncombustion_anthracite_footprints))",
- ch4_noncombustion_bituminouscoal = "rowSums(t(national_CH4_noncombustion_bituminouscoal_footprints))",
- ch4_noncombustion_cokingcoal = "rowSums(t(national_CH4_noncombustion_cokingcoal_footprints))",
- ch4_noncombustion_lignite = "rowSums(t(national_CH4_noncombustion_lignite_footprints))",
- ch4_noncombustion_subbituminouscoal = "rowSums(t(national_CH4_noncombustion_subbituminouscoal_footprints))",
- ch4_noncombustion_oilrefinery = "rowSums(t(national_CH4_noncombustion_oilrefinery_footprints))",
- ch4_agriculture = "rowSums(t(national_CH4_agriculture_footprints))",
- ch4_waste = "rowSums(t(national_CH4_waste_footprints))",
- n2o = "rowSums(t(national_N2O_footprints))",
- n2o_agriculture = "rowSums(t(national_N2O_agriculture_footprints))",
- 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))") %>%
- select(year,
- geo,
- fd_category,
- co2,
- direct_FD_co2,
- co2_noncombustion_cement,
- direct_FD_co2_noncombustion_cement,
- co2_noncombustion_lime,
- direct_FD_co2_noncombustion_lime,
- co2_agriculture_peatdecay,
- direct_FD_co2_agriculture_peatdecay,
- co2_waste_biogenic,
- direct_FD_co2_waste_biogenic,
- co2_waste_fossil,
- direct_FD_co2_waste_fossil,
- ch4,
- direct_FD_ch4,
- ch4_noncombustion_gas,
- direct_FD_ch4_noncombustion_gas,
- ch4_noncombustion_oil,
- direct_FD_ch4_noncombustion_oil,
- ch4_noncombustion_anthracite,
- direct_FD_ch4_noncombustion_anthracite,
- ch4_noncombustion_bituminouscoal,
- direct_FD_ch4_noncombustion_bituminouscoal,
- ch4_noncombustion_cokingcoal,
- direct_FD_ch4_noncombustion_cokingcoal,
- ch4_noncombustion_lignite,
- direct_FD_ch4_noncombustion_lignite,
- ch4_noncombustion_subbituminouscoal,
- direct_FD_ch4_noncombustion_subbituminouscoal,
- ch4_noncombustion_oilrefinery,
- direct_FD_ch4_noncombustion_oilrefinery,
- ch4_agriculture,
- direct_FD_ch4_agriculture,
- ch4_waste,
- direct_FD_ch4_waste,
- n2o,
- direct_FD_n2o,
- n2o_agriculture,
- direct_FD_n2o_agriculture,
- sf6,
- direct_FD_sf6,
- hfc,
- direct_FD_hfc,
- 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)
-
-
- national_fp = rbind(national_fp, look_national_fp)
-
-
-}
-
-
-
-# option holding HBS exp ratios
-
-mean_expenditure_by_quintile_toggle = mean_expenditure_by_quintile_long_bp %>%
- filter(!(quintile %in% c("TOTAL","UNK"))) %>%
- group_by(geo,year) %>%
- mutate(euro_pps_bp = as.numeric(euro_pps_bp),
- mean_exp_shares = euro_pps_bp/sum(euro_pps_bp))
-
-
-ala = total_fd %>%
- left_join(mean_expenditure_by_quintile_toggle, by = c("geo","year","quintile"))
-
-
-
-join_ala = mean_expenditure_by_coicop_sector_long_bp %>%
- left_join(ala, by = c("geo","quintile","year")) %>%
- mutate(year = as.numeric(year),
- eurostat_countries_colsums = as.numeric(eurostat_countries_colsums),
- pm_bp = as.numeric(pm_bp),
- fd_me = pm_bp*((eurostat_countries_colsums*mean_exp_shares)/1000))
-
-
-###################################################
-#%>%
-# rename(coicop_level1 = coicop)
-
-# TIV only taking the mean
-
-# mean_TIV_with_labels = TIV_with_labels %>% group_by(geo,year,coicop,coicop_level1) %>%
-# summarise(TIV_CO2 = mean(TIV_CO2))
-
-#ok = join_ala %>% left_join(mean_TIV_with_labels, by = c("geo","year","coicop")) %>%
-# mutate(CO2_normal = exp_normal*TIV_CO2,
-# CO2_pe = exp_pe*TIV_CO2,
-# CO2_pi = exp_pi*TIV_CO2)
-##################################################
-
-Eurostat_countries_hh_fd_mean_TIV = as.data.frame(Eurostat_countries_hh_fd) %>% select(-year)
-
-weighted_mean_TIV_with_labels = cbind(TIVs,Eurostat_countries_hh_fd_mean_TIV) %>%
- gather(geo,fd,-country_of_production,-year,-sector,-coicop,-five_sectors,
- -TIV_CO2,-TIV_CO2_noncombustion_cement,-TIV_CO2_noncombustion_lime,
- -TIV_CO2_agriculture_peatdecay,-TIV_CO2_waste_biogenic,
- -TIV_CO2_waste_fossil,-TIV_CH4,
- -TIV_CH4_noncombustion_gas,-TIV_CH4_noncombustion_oil,
- -TIV_CH4_noncombustion_anthracite,-TIV_CH4_noncombustion_bituminouscoal,
- -TIV_CH4_noncombustion_cokingcoal,-TIV_CH4_noncombustion_lignite,
- -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) %>%
- group_by(geo,year,coicop) %>%
- mutate(fd = as.numeric(fd)) %>%
- mutate(TIV_CO2_weighted_average = sum((fd/sum(fd))*TIV_CO2),
- TIV_CO2_noncombustion_cement_weighted_average = sum((fd/sum(fd))*TIV_CO2_noncombustion_cement),
- TIV_CO2_noncombustion_lime_weighted_average = sum((fd/sum(fd))*TIV_CO2_noncombustion_lime),
- TIV_CO2_agriculture_peatdecay_weighted_average = sum((fd/sum(fd))*TIV_CO2_agriculture_peatdecay),
- TIV_CO2_waste_biogenic_weighted_average = sum((fd/sum(fd))*TIV_CO2_waste_biogenic),
- TIV_CO2_waste_fossil_weighted_average = sum((fd/sum(fd))*TIV_CO2_waste_fossil),
- TIV_CH4_weighted_average = sum((fd/sum(fd))*TIV_CH4),
- TIV_CH4_noncombustion_gas_weighted_average = sum((fd/sum(fd))*TIV_CH4_noncombustion_gas),
- TIV_CH4_noncombustion_oil_weighted_average = sum((fd/sum(fd))*TIV_CH4_noncombustion_oil),
- TIV_CH4_noncombustion_anthracite_weighted_average = sum((fd/sum(fd))*TIV_CH4_noncombustion_anthracite),
- TIV_CH4_noncombustion_bituminouscoal_weighted_average = sum((fd/sum(fd))*TIV_CH4_noncombustion_bituminouscoal),
- TIV_CH4_noncombustion_cokingcoal_weighted_average = sum((fd/sum(fd))*TIV_CH4_noncombustion_cokingcoal),
- TIV_CH4_noncombustion_lignite_weighted_average = sum((fd/sum(fd))*TIV_CH4_noncombustion_lignite),
- TIV_CH4_noncombustion_subbituminouscoal_weighted_average = sum((fd/sum(fd))*TIV_CH4_noncombustion_subbituminouscoal),
- TIV_CH4_noncombustion_oilrefinery_weighted_average = sum((fd/sum(fd))*TIV_CH4_noncombustion_oilrefinery),
- TIV_CH4_agriculture_weighted_average = sum((fd/sum(fd))*TIV_CH4_agriculture),
- TIV_CH4_waste_weighted_average = sum((fd/sum(fd))*TIV_CH4_waste),
- TIV_N2O_weighted_average = sum((fd/sum(fd))*TIV_N2O),
- TIV_N2O_agriculture_weighted_average = sum((fd/sum(fd))*TIV_N2O_agriculture),
- 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)) %>%
- select(year,geo,coicop,TIV_CO2_weighted_average,
- TIV_CO2_noncombustion_cement_weighted_average,
- TIV_CO2_noncombustion_lime_weighted_average,
- TIV_CO2_agriculture_peatdecay_weighted_average,
- TIV_CO2_waste_biogenic_weighted_average,
- TIV_CO2_waste_fossil_weighted_average,
- TIV_CH4_weighted_average,
- TIV_CH4_noncombustion_gas_weighted_average,
- TIV_CH4_noncombustion_oil_weighted_average,
- TIV_CH4_noncombustion_anthracite_weighted_average,
- TIV_CH4_noncombustion_bituminouscoal_weighted_average,
- TIV_CH4_noncombustion_cokingcoal_weighted_average,
- TIV_CH4_noncombustion_lignite_weighted_average,
- TIV_CH4_noncombustion_subbituminouscoal_weighted_average,
- TIV_CH4_noncombustion_oilrefinery_weighted_average,
- TIV_CH4_agriculture_weighted_average,
- TIV_CH4_waste_weighted_average,
- TIV_N2O_weighted_average,
- TIV_N2O_agriculture_weighted_average,
- 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) %>%
- unique()
-
-weighted_mean_europe_TIV_with_labels = cbind(europe_TIVs, Eurostat_countries_hh_fd_mean_TIV) %>%
- gather(geo,fd,-country_of_production,-year,-sector,-coicop,-five_sectors,
- -TIV_CO2_europe,-TIV_CO2_not_europe,
- -TIV_CO2_noncombustion_cement_europe,-TIV_CO2_noncombustion_cement_not_europe,
- -TIV_CO2_noncombustion_lime_europe, -TIV_CO2_noncombustion_lime_not_europe,
- -TIV_CO2_agriculture_peatdecay_europe,-TIV_CO2_agriculture_peatdecay_not_europe,
- -TIV_CO2_waste_biogenic_europe, -TIV_CO2_waste_biogenic_not_europe,
- -TIV_CO2_waste_fossil_europe, -TIV_CO2_waste_fossil_not_europe,
- -TIV_CH4_europe,-TIV_CH4_not_europe,
- -TIV_CH4_noncombustion_gas_europe, -TIV_CH4_noncombustion_gas_not_europe,
- -TIV_CH4_noncombustion_oil_europe,-TIV_CH4_noncombustion_oil_not_europe,
- -TIV_CH4_noncombustion_anthracite_europe,-TIV_CH4_noncombustion_anthracite_not_europe,
- -TIV_CH4_noncombustion_bituminouscoal_europe,-TIV_CH4_noncombustion_bituminouscoal_not_europe,
- -TIV_CH4_noncombustion_cokingcoal_europe,-TIV_CH4_noncombustion_cokingcoal_not_europe,
- -TIV_CH4_noncombustion_lignite_europe,-TIV_CH4_noncombustion_lignite_not_europe,
- -TIV_CH4_noncombustion_subbituminouscoal_europe,-TIV_CH4_noncombustion_subbituminouscoal_not_europe,
- -TIV_CH4_noncombustion_oilrefinery_europe, -TIV_CH4_noncombustion_oilrefinery_not_europe,
- -TIV_CH4_agriculture_europe, -TIV_CH4_agriculture_not_europe,
- -TIV_CH4_waste_europe,-TIV_CH4_waste_not_europe,
- -TIV_N2O_europe,-TIV_N2O_not_europe,
- -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) %>%
- group_by(geo,year,coicop) %>%
- mutate(fd = as.numeric(fd)) %>%
- mutate(TIV_CO2_europe_weighted_average = sum((fd/sum(fd))*TIV_CO2_europe),
- TIV_CO2_noncombustion_cement_europe_weighted_average = sum((fd/sum(fd))*TIV_CO2_noncombustion_cement_europe),
- TIV_CO2_noncombustion_lime_europe_weighted_average = sum((fd/sum(fd))*TIV_CO2_noncombustion_lime_europe),
- TIV_CO2_agriculture_peatdecay_europe_weighted_average = sum((fd/sum(fd))*TIV_CO2_agriculture_peatdecay_europe),
- TIV_CO2_waste_biogenic_europe_weighted_average = sum((fd/sum(fd))*TIV_CO2_waste_biogenic_europe),
- TIV_CO2_waste_fossil_europe_weighted_average = sum((fd/sum(fd))*TIV_CO2_waste_fossil_europe),
- TIV_CH4_europe_weighted_average = sum((fd/sum(fd))*TIV_CH4_europe),
- TIV_CH4_noncombustion_gas_europe_weighted_average = sum((fd/sum(fd))*TIV_CH4_noncombustion_gas_europe),
- TIV_CH4_noncombustion_oil_europe_weighted_average = sum((fd/sum(fd))*TIV_CH4_noncombustion_oil_europe),
- TIV_CH4_noncombustion_anthracite_europe_weighted_average = sum((fd/sum(fd))*TIV_CH4_noncombustion_anthracite_europe),
- TIV_CH4_noncombustion_bituminouscoal_europe_weighted_average = sum((fd/sum(fd))*TIV_CH4_noncombustion_bituminouscoal_europe),
- TIV_CH4_noncombustion_cokingcoal_europe_weighted_average = sum((fd/sum(fd))*TIV_CH4_noncombustion_cokingcoal_europe),
- TIV_CH4_noncombustion_lignite_europe_weighted_average = sum((fd/sum(fd))*TIV_CH4_noncombustion_lignite_europe),
- TIV_CH4_noncombustion_subbituminouscoal_europe_weighted_average = sum((fd/sum(fd))*TIV_CH4_noncombustion_subbituminouscoal_europe),
- TIV_CH4_noncombustion_oilrefinery_europe_weighted_average = sum((fd/sum(fd))*TIV_CH4_noncombustion_oilrefinery_europe),
- TIV_CH4_agriculture_europe_weighted_average = sum((fd/sum(fd))*TIV_CH4_agriculture_europe),
- TIV_CH4_waste_europe_weighted_average = sum((fd/sum(fd))*TIV_CH4_waste_europe),
- TIV_N2O_europe_weighted_average = sum((fd/sum(fd))*TIV_N2O_europe),
- TIV_N2O_agriculture_europe_weighted_average = sum((fd/sum(fd))*TIV_N2O_agriculture_europe),
- 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)) %>%
- select(year,geo,coicop,TIV_CO2_europe_weighted_average,
- TIV_CO2_noncombustion_cement_europe_weighted_average,
- TIV_CO2_noncombustion_lime_europe_weighted_average,
- TIV_CO2_agriculture_peatdecay_europe_weighted_average,
- TIV_CO2_waste_biogenic_europe_weighted_average,
- TIV_CO2_waste_fossil_europe_weighted_average,
- TIV_CH4_europe_weighted_average,
- TIV_CH4_noncombustion_gas_europe_weighted_average,
- TIV_CH4_noncombustion_oil_europe_weighted_average,
- TIV_CH4_noncombustion_anthracite_europe_weighted_average,
- TIV_CH4_noncombustion_bituminouscoal_europe_weighted_average,
- TIV_CH4_noncombustion_cokingcoal_europe_weighted_average,
- TIV_CH4_noncombustion_lignite_europe_weighted_average,
- TIV_CH4_noncombustion_subbituminouscoal_europe_weighted_average,
- TIV_CH4_noncombustion_oilrefinery_europe_weighted_average,
- TIV_CH4_agriculture_europe_weighted_average,
- TIV_CH4_waste_europe_weighted_average,
- TIV_N2O_europe_weighted_average,
- TIV_N2O_agriculture_europe_weighted_average,
- 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) %>%
- unique()
-
-domestic_TIVs_Eurostat = domestic_TIVs %>%
- filter(geo %in% c("AT",
- "BG",
- "BE",
- "CY",
- "CZ",
- "DE",
- "DK",
- "EE",
- "EL",
- "ES",
- "FI",
- "FR",
- "HR",
- "HU",
- "IE",
- "IT",
- "LT",
- "LU",
- "LV",
- "MT",
- "NL",
- "NO",
- "PL",
- "PT",
- "RO",
- "SE",
- "SI",
- "SK",
- "TR",
- "UK"))
-
-Eurostat_countries_hh_fd_long = as.data.frame(Eurostat_countries_hh_fd) %>%
- gather(geo,fd,-year) %>%
- arrange(year, match(geo, c("AT",
- "BE",
- "BG",
- "CY",
- "CZ",
- "DE",
- "DK",
- "EE",
- "ES",
- "FI",
- "FR",
- "UK",
- "EL",
- "HR",
- "HU",
- "IE",
- "IT",
- "LT",
- "LU",
- "LV",
- "MT",
- "NL",
- "NO",
- "PL",
- "PT",
- "RO",
- "SE",
- "SI",
- "SK",
- "TR"))) %>% select(-year,-geo)
-
-weighted_mean_domestic_TIV_with_labels = cbind(domestic_TIVs_Eurostat,Eurostat_countries_hh_fd_long) %>%
- group_by(geo,year,coicop) %>%
- mutate(fd = as.numeric(fd)) %>%
- mutate(TIV_CO2_domestic_weighted_average = sum((fd/sum(fd))*TIV_CO2_domestic),
- TIV_CO2_noncombustion_cement_domestic_weighted_average = sum((fd/sum(fd))*TIV_CO2_noncombustion_cement_domestic),
- TIV_CO2_noncombustion_lime_domestic_weighted_average = sum((fd/sum(fd))*TIV_CO2_noncombustion_lime_domestic),
- TIV_CO2_agriculture_peatdecay_domestic_weighted_average = sum((fd/sum(fd))*TIV_CO2_agriculture_peatdecay_domestic),
- TIV_CO2_waste_biogenic_domestic_weighted_average = sum((fd/sum(fd))*TIV_CO2_waste_biogenic_domestic),
- TIV_CO2_waste_fossil_domestic_weighted_average = sum((fd/sum(fd))*TIV_CO2_waste_fossil_domestic),
- TIV_CH4_domestic_weighted_average = sum((fd/sum(fd))*TIV_CH4_domestic),
- TIV_CH4_noncombustion_gas_domestic_weighted_average = sum((fd/sum(fd))*TIV_CH4_noncombustion_gas_domestic),
- TIV_CH4_noncombustion_oil_domestic_weighted_average = sum((fd/sum(fd))*TIV_CH4_noncombustion_oil_domestic),
- TIV_CH4_noncombustion_anthracite_domestic_weighted_average = sum((fd/sum(fd))*TIV_CH4_noncombustion_anthracite_domestic),
- TIV_CH4_noncombustion_bituminouscoal_domestic_weighted_average = sum((fd/sum(fd))*TIV_CH4_noncombustion_bituminouscoal_domestic),
- TIV_CH4_noncombustion_cokingcoal_domestic_weighted_average = sum((fd/sum(fd))*TIV_CH4_noncombustion_cokingcoal_domestic),
- TIV_CH4_noncombustion_lignite_domestic_weighted_average = sum((fd/sum(fd))*TIV_CH4_noncombustion_lignite_domestic),
- TIV_CH4_noncombustion_subbituminouscoal_domestic_weighted_average = sum((fd/sum(fd))*TIV_CH4_noncombustion_subbituminouscoal_domestic),
- TIV_CH4_noncombustion_oilrefinery_domestic_weighted_average = sum((fd/sum(fd))*TIV_CH4_noncombustion_oilrefinery_domestic),
- TIV_CH4_agriculture_domestic_weighted_average = sum((fd/sum(fd))*TIV_CH4_agriculture_domestic),
- TIV_CH4_waste_domestic_weighted_average = sum((fd/sum(fd))*TIV_CH4_waste_domestic),
- TIV_N2O_domestic_weighted_average = sum((fd/sum(fd))*TIV_N2O_domestic),
- TIV_N2O_agriculture_domestic_weighted_average = sum((fd/sum(fd))*TIV_N2O_agriculture_domestic),
- 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)) %>%
- select(year,geo,coicop,TIV_CO2_domestic_weighted_average,
- TIV_CO2_noncombustion_cement_domestic_weighted_average,
- TIV_CO2_noncombustion_lime_domestic_weighted_average,
- TIV_CO2_agriculture_peatdecay_domestic_weighted_average,
- TIV_CO2_waste_biogenic_domestic_weighted_average,
- TIV_CO2_waste_fossil_domestic_weighted_average,
- TIV_CH4_domestic_weighted_average,
- TIV_CH4_noncombustion_gas_domestic_weighted_average,
- TIV_CH4_noncombustion_oil_domestic_weighted_average,
- TIV_CH4_noncombustion_anthracite_domestic_weighted_average,
- TIV_CH4_noncombustion_bituminouscoal_domestic_weighted_average,
- TIV_CH4_noncombustion_cokingcoal_domestic_weighted_average,
- TIV_CH4_noncombustion_lignite_domestic_weighted_average,
- TIV_CH4_noncombustion_subbituminouscoal_domestic_weighted_average,
- TIV_CH4_noncombustion_oilrefinery_domestic_weighted_average,
- TIV_CH4_agriculture_domestic_weighted_average,
- TIV_CH4_waste_domestic_weighted_average,
- TIV_N2O_domestic_weighted_average,
- TIV_N2O_agriculture_domestic_weighted_average,
- 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) %>%
- unique()
-
-
-
-
-
-ok = join_ala %>%
- mutate(year = as.character(year)) %>%
- left_join(weighted_mean_TIV_with_labels, by = c("geo","year","coicop")) %>%
- left_join(weighted_mean_europe_TIV_with_labels, by = c("geo","year","coicop")) %>%
- left_join(weighted_mean_domestic_TIV_with_labels, by = c("geo", "year", "coicop")) %>%
- mutate(co2_kg = fd_me*(TIV_CO2_weighted_average + TIV_CO2_noncombustion_cement_weighted_average +
- TIV_CO2_noncombustion_lime_weighted_average + TIV_CO2_agriculture_peatdecay_weighted_average +
- TIV_CO2_waste_biogenic_weighted_average + TIV_CO2_waste_fossil_weighted_average),
- co2_domestic_kg = fd_me*(TIV_CO2_domestic_weighted_average + TIV_CO2_noncombustion_cement_domestic_weighted_average +
- TIV_CO2_noncombustion_lime_domestic_weighted_average + TIV_CO2_agriculture_peatdecay_domestic_weighted_average +
- TIV_CO2_waste_biogenic_domestic_weighted_average + TIV_CO2_waste_fossil_domestic_weighted_average),
- co2_europe_kg = fd_me*((TIV_CO2_europe_weighted_average + TIV_CO2_noncombustion_cement_europe_weighted_average +
- TIV_CO2_noncombustion_lime_europe_weighted_average + TIV_CO2_agriculture_peatdecay_europe_weighted_average +
- TIV_CO2_waste_biogenic_europe_weighted_average + TIV_CO2_waste_fossil_europe_weighted_average) - (TIV_CO2_domestic_weighted_average + TIV_CO2_noncombustion_cement_domestic_weighted_average +
- TIV_CO2_noncombustion_lime_domestic_weighted_average + TIV_CO2_agriculture_peatdecay_domestic_weighted_average +
- TIV_CO2_waste_biogenic_domestic_weighted_average + TIV_CO2_waste_fossil_domestic_weighted_average)),
- co2eq_kg = fd_me*(TIV_CO2_weighted_average +
- TIV_CO2_noncombustion_cement_weighted_average +
- TIV_CO2_noncombustion_lime_weighted_average + TIV_CO2_agriculture_peatdecay_weighted_average +
- TIV_CO2_waste_biogenic_weighted_average + TIV_CO2_waste_fossil_weighted_average +
- TIV_CH4_weighted_average +
- TIV_CH4_noncombustion_gas_weighted_average +
- TIV_CH4_noncombustion_oil_weighted_average +
- TIV_CH4_noncombustion_anthracite_weighted_average +
- TIV_CH4_noncombustion_bituminouscoal_weighted_average +
- TIV_CH4_noncombustion_cokingcoal_weighted_average +
- TIV_CH4_noncombustion_lignite_weighted_average +
- TIV_CH4_noncombustion_subbituminouscoal_weighted_average +
- TIV_CH4_noncombustion_oilrefinery_weighted_average +
- TIV_CH4_agriculture_weighted_average +
- TIV_CH4_waste_weighted_average +
- TIV_N2O_weighted_average +
- TIV_N2O_agriculture_weighted_average +
- TIV_SF6_weighted_average +
- TIV_HFC_weighted_average +
- TIV_PFC_weighted_average),
- co2eq_domestic_kg = fd_me*(TIV_CO2_domestic_weighted_average +
- TIV_CO2_noncombustion_cement_domestic_weighted_average +
- TIV_CO2_noncombustion_lime_domestic_weighted_average + TIV_CO2_agriculture_peatdecay_domestic_weighted_average +
- TIV_CO2_waste_biogenic_domestic_weighted_average + TIV_CO2_waste_fossil_domestic_weighted_average +
- TIV_CH4_domestic_weighted_average +
- TIV_CH4_noncombustion_gas_domestic_weighted_average +
- TIV_CH4_noncombustion_oil_domestic_weighted_average +
- TIV_CH4_noncombustion_anthracite_domestic_weighted_average +
- TIV_CH4_noncombustion_bituminouscoal_domestic_weighted_average +
- TIV_CH4_noncombustion_cokingcoal_domestic_weighted_average +
- TIV_CH4_noncombustion_lignite_domestic_weighted_average +
- TIV_CH4_noncombustion_subbituminouscoal_domestic_weighted_average +
- TIV_CH4_noncombustion_oilrefinery_domestic_weighted_average +
- TIV_CH4_agriculture_domestic_weighted_average +
- TIV_CH4_waste_domestic_weighted_average +
- TIV_N2O_domestic_weighted_average +
- TIV_N2O_agriculture_domestic_weighted_average +
- TIV_SF6_domestic_weighted_average +
- TIV_HFC_domestic_weighted_average +
- TIV_PFC_domestic_weighted_average),
- co2eq_europe_kg = fd_me*((TIV_CO2_europe_weighted_average +
- TIV_CO2_noncombustion_cement_europe_weighted_average +
- TIV_CO2_noncombustion_lime_europe_weighted_average + TIV_CO2_agriculture_peatdecay_europe_weighted_average +
- TIV_CO2_waste_biogenic_europe_weighted_average + TIV_CO2_waste_fossil_europe_weighted_average +
- TIV_CH4_europe_weighted_average +
- TIV_CH4_noncombustion_gas_europe_weighted_average +
- TIV_CH4_noncombustion_oil_europe_weighted_average +
- TIV_CH4_noncombustion_anthracite_europe_weighted_average +
- TIV_CH4_noncombustion_bituminouscoal_europe_weighted_average +
- TIV_CH4_noncombustion_cokingcoal_europe_weighted_average +
- TIV_CH4_noncombustion_lignite_europe_weighted_average +
- TIV_CH4_noncombustion_subbituminouscoal_europe_weighted_average +
- TIV_CH4_noncombustion_oilrefinery_europe_weighted_average +
- TIV_CH4_agriculture_europe_weighted_average +
- TIV_CH4_waste_europe_weighted_average +
- TIV_N2O_europe_weighted_average +
- TIV_N2O_agriculture_europe_weighted_average +
- TIV_SF6_europe_weighted_average +
- TIV_HFC_europe_weighted_average +
- TIV_PFC_europe_weighted_average) -
- (TIV_CO2_domestic_weighted_average +
- TIV_CO2_noncombustion_cement_domestic_weighted_average +
- TIV_CO2_noncombustion_lime_domestic_weighted_average + TIV_CO2_agriculture_peatdecay_domestic_weighted_average +
- TIV_CO2_waste_biogenic_domestic_weighted_average + TIV_CO2_waste_fossil_domestic_weighted_average +
- TIV_CH4_domestic_weighted_average +
- TIV_CH4_noncombustion_gas_domestic_weighted_average +
- TIV_CH4_noncombustion_oil_domestic_weighted_average +
- TIV_CH4_noncombustion_anthracite_domestic_weighted_average +
- TIV_CH4_noncombustion_bituminouscoal_domestic_weighted_average +
- TIV_CH4_noncombustion_cokingcoal_domestic_weighted_average +
- TIV_CH4_noncombustion_lignite_domestic_weighted_average +
- TIV_CH4_noncombustion_subbituminouscoal_domestic_weighted_average +
- TIV_CH4_noncombustion_oilrefinery_domestic_weighted_average +
- TIV_CH4_agriculture_domestic_weighted_average +
- TIV_CH4_waste_domestic_weighted_average +
- TIV_N2O_domestic_weighted_average +
- TIV_N2O_agriculture_domestic_weighted_average +
- TIV_SF6_domestic_weighted_average +
- TIV_HFC_domestic_weighted_average +
- TIV_PFC_domestic_weighted_average)),
- energy_use_TJ = fd_me*(TIV_energy_weighted_average),
- energy_use_domestic_TJ = fd_me*(TIV_energy_domestic_weighted_average),
- energy_use_europe_TJ = fd_me*(TIV_energy_europe_weighted_average -
- TIV_energy_domestic_weighted_average))
-
-# direct from FD - to go back to results without direct FD fp, do not run this next chunk and do not bind_rows with 'results'
-
-env_ac_pefasu_no_TR = read_csv(paste0(data_dir_income_stratified_footprints, "/data/env_ac_pefasu_1_Data.csv")) %>%
- filter(TIME == 2015) %>%
- mutate(geo = dplyr::recode(GEO,"Austria" = "AT",
- "Belgium" = "BE",
- "Cyprus" = "CY",
- "Czechia" = "CZ",
- "Denmark" = "DK",
- "Estonia" = "EE",
- "Finland" = "FI",
- "France" = "FR",
- "Germany (until 1990 former territory of the FRG)" = "DE",
- "Greece" = "EL",
- "Hungary" = "HU",
- "Ireland" = "IE",
- "Italy" = "IT",
- "Latvia" = "LV",
- "Lithuania" = "LT",
- "Luxembourg" = "LU",
- "Malta" = "MT",
- "Netherlands" = "NL",
- "Norway" = "NO",
- "Poland" = "PL",
- "Portugal" = "PT",
- "Romania" = "RO",
- "Slovakia" = "SK",
- "Slovenia" = "SI",
- "Spain" = "ES",
- "Sweden" = "SE",
- "United Kingdom" = "UK",
- "Bulgaria" = "BG",
- "Croatia" = "HR")) %>%
- select(NACE_R2,geo,Value) %>%
- mutate(Value = parse_number(Value),
- Value = as.numeric(Value)) %>%
- spread(NACE_R2,Value) %>%
- clean_names() %>%
- mutate(HH_HEAT = heating_cooling_activities_by_households/total_activities_by_households,
- HH_TRA = transport_activities_by_households/total_activities_by_households,
- HH_OTH = other_activities_by_households/total_activities_by_households) %>%
- select(geo,HH_HEAT,HH_TRA,HH_OTH)
-
-
-env_ac_pefasu_TR = env_ac_pefasu_no_TR %>%
- filter(geo == "BG") %>%
- mutate(geo = dplyr::recode(geo,
- "BG" = "TR"))
-
-env_ac_pefasu = rbind(env_ac_pefasu_no_TR,env_ac_pefasu_TR) %>%
- gather(sector,share_of_total_energy,-geo)
-
-env_ac_ainah_r2 = read_csv(paste0(data_dir_income_stratified_footprints, "/data/env_ac_ainah_r2_1_Data.csv")) %>%
- filter(TIME == 2015) %>%
- mutate(geo = dplyr::recode(GEO,"Austria" = "AT",
- "Belgium" = "BE",
- "Cyprus" = "CY",
- "Czechia" = "CZ",
- "Denmark" = "DK",
- "Estonia" = "EE",
- "Finland" = "FI",
- "France" = "FR",
- "Germany (until 1990 former territory of the FRG)" = "DE",
- "Greece" = "EL",
- "Hungary" = "HU",
- "Ireland" = "IE",
- "Italy" = "IT",
- "Latvia" = "LV",
- "Lithuania" = "LT",
- "Luxembourg" = "LU",
- "Malta" = "MT",
- "Netherlands" = "NL",
- "Norway" = "NO",
- "Poland" = "PL",
- "Portugal" = "PT",
- "Romania" = "RO",
- "Slovakia" = "SK",
- "Slovenia" = "SI",
- "Spain" = "ES",
- "Sweden" = "SE",
- "Turkey" = "TR",
- "United Kingdom" = "UK",
- "Bulgaria" = "BG",
- "Croatia" = "HR")) %>%
- select(NACE_R2,AIRPOL,geo,Value) %>%
- mutate(Value = parse_number(Value),
- Value = as.numeric(Value)) %>%
- spread(NACE_R2,Value) %>%
- clean_names() %>%
- mutate(HH_HEAT = heating_cooling_activities_by_households/total_activities_by_households,
- HH_TRA = transport_activities_by_households/total_activities_by_households,
- HH_OTH = other_activities_by_households/total_activities_by_households) %>%
- select(geo,airpol,HH_HEAT,HH_TRA,HH_OTH)
-
-
-env_ac_ainah_r2_co2 = env_ac_ainah_r2 %>%
- filter(airpol == "Carbon dioxide") %>%
- select(-airpol) %>%
- gather(sector,share_of_total_co2,-geo)
-
-env_ac_ainah_r2_ch4 = env_ac_ainah_r2 %>%
- filter(airpol == "Methane") %>%
- select(-airpol) %>%
- gather(sector,share_of_total_ch4,-geo)
-
-env_ac_ainah_r2_n2o = env_ac_ainah_r2 %>%
- filter(airpol == "Nitrous oxide") %>%
- select(-airpol) %>%
- gather(sector,share_of_total_n2o,-geo)
-
-direct_FD_fp_long = national_fp %>%
- filter(fd_category == "Final consumption expenditure by households",
- geo %in% c("AT",
- "BE", "BG", "CY", "CZ",
- "DE" , "DK" , "EE" ,
- "ES" , "FI" , "FR" ,
- "UK", "EL", "HR" ,
- "HU" , "IE" , "IT" ,
- "LT" , "LU" , "LV" ,
- "MT" , "NL" , "PL" ,
- "PT" , "TR" , "SK" ,
- "SI" , "SE" , "RO" ,
- "NO")) %>%
- select(year,geo,fd_category,direct_FD_co2,
- direct_FD_co2_noncombustion_cement,
- direct_FD_co2_noncombustion_lime,
- direct_FD_co2_agriculture_peatdecay,
- direct_FD_co2_waste_biogenic,
- direct_FD_co2_waste_fossil,
- direct_FD_ch4,
- direct_FD_ch4_noncombustion_gas,
- direct_FD_ch4_noncombustion_oil,
- direct_FD_ch4_noncombustion_anthracite,
- direct_FD_ch4_noncombustion_bituminouscoal,
- direct_FD_ch4_noncombustion_cokingcoal,
- direct_FD_ch4_noncombustion_lignite,
- direct_FD_ch4_noncombustion_subbituminouscoal,
- direct_FD_ch4_noncombustion_oilrefinery,
- direct_FD_ch4_agriculture,
- direct_FD_ch4_waste,
- direct_FD_n2o,
- direct_FD_n2o_agriculture,
- 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) %>%
- slice(rep(1:n(), each = 3))
-
-sector = rep(c("HH_HEAT","HH_TRA","HH_OTH"), nrow(direct_FD_fp_long)/3)
-
-direct_FD_fp_long_disagg = cbind(sector,direct_FD_fp_long) %>%
- mutate(coicop = ifelse(sector == "HH_TRA","CP072",
- ifelse(sector == "HH_HEAT","CP045","CP05")),
- five_sectors = ifelse(sector == "HH_TRA", "transport",
- ifelse(sector == "HH_HEAT", "shelter", "manufactured goods"))) %>%
- left_join(env_ac_ainah_r2_co2, by = c("geo","sector")) %>%
- left_join(env_ac_ainah_r2_ch4, by = c("geo","sector")) %>%
- left_join(env_ac_ainah_r2_n2o, by = c("geo","sector")) %>%
- left_join(env_ac_pefasu, by = c("geo","sector")) %>%
- mutate(direct_FD_co2 = (direct_FD_co2 +
- direct_FD_co2_noncombustion_cement +
- direct_FD_co2_noncombustion_lime +
- direct_FD_co2_agriculture_peatdecay +
- direct_FD_co2_waste_biogenic +
- direct_FD_co2_waste_fossil)*share_of_total_co2,
- direct_FD_ch4 = (direct_FD_ch4 +
- direct_FD_ch4_noncombustion_gas +
- direct_FD_ch4_noncombustion_oil +
- direct_FD_ch4_noncombustion_anthracite +
- direct_FD_ch4_noncombustion_bituminouscoal +
- direct_FD_ch4_noncombustion_cokingcoal +
- direct_FD_ch4_noncombustion_lignite +
- direct_FD_ch4_noncombustion_subbituminouscoal +
- direct_FD_ch4_noncombustion_oilrefinery +
- direct_FD_ch4_agriculture +
- direct_FD_ch4_waste)*share_of_total_ch4,
- direct_FD_n2o = (direct_FD_n2o +
- direct_FD_n2o_agriculture)*share_of_total_n2o,
- direct_FD_energy = direct_FD_energy*share_of_total_energy) %>%
- left_join(shares, by = c("year","geo","coicop")) %>%
- mutate(disaggregated_direct_FD_co2 = direct_FD_co2*share,
- disaggregated_direct_FD_ch4 = direct_FD_ch4*share,
- disaggregated_direct_FD_n2o = direct_FD_n2o*share,
- disaggregated_direct_FD_energy = direct_FD_energy*share) %>%
- select(year,geo,sector, quintile,
- coicop, five_sectors,
- disaggregated_direct_FD_co2,
- disaggregated_direct_FD_ch4,
- disaggregated_direct_FD_n2o,
- disaggregated_direct_FD_energy)
-
-direct_FD_co2 = direct_FD_fp_long_disagg %>%
- select(year,geo,sector,quintile,coicop,five_sectors,disaggregated_direct_FD_co2) %>%
- spread(quintile,disaggregated_direct_FD_co2) %>%
- rename(q1_co2 = QUINTILE1,
- q2_co2 = QUINTILE2,
- q3_co2 = QUINTILE3,
- q4_co2 = QUINTILE4,
- q5_co2 = QUINTILE5) %>%
- mutate(q1_co2_domestic = q1_co2,
- q2_co2_domestic = q2_co2,
- q3_co2_domestic = q3_co2,
- q4_co2_domestic = q4_co2,
- q5_co2_domestic = q5_co2,
- co2_total = q1_co2+q2_co2+q3_co2+q4_co2+q5_co2,
- co2_total_domestic = q1_co2_domestic+
- q2_co2_domestic+q3_co2_domestic+
- q4_co2_domestic+q5_co2_domestic)
-
-direct_FD_ch4 = direct_FD_fp_long_disagg %>%
- select(year,geo,sector,quintile,coicop,five_sectors,disaggregated_direct_FD_ch4) %>%
- spread(quintile,disaggregated_direct_FD_ch4) %>%
- rename(q1_ch4 = QUINTILE1,
- q2_ch4 = QUINTILE2,
- q3_ch4 = QUINTILE3,
- q4_ch4 = QUINTILE4,
- q5_ch4 = QUINTILE5) %>%
- mutate(q1_ch4_domestic = q1_ch4,
- q2_ch4_domestic = q2_ch4,
- q3_ch4_domestic = q3_ch4,
- q4_ch4_domestic = q4_ch4,
- q5_ch4_domestic = q5_ch4,
- ch4_total = q1_ch4+q2_ch4+q3_ch4+q4_ch4+q5_ch4,
- ch4_total_domestic = q1_ch4_domestic+
- q2_ch4_domestic+q3_ch4_domestic+
- q4_ch4_domestic+q5_ch4_domestic)
-
-
-direct_FD_n2o = direct_FD_fp_long_disagg %>%
- select(year,geo,sector,quintile,coicop,five_sectors,disaggregated_direct_FD_n2o) %>%
- spread(quintile,disaggregated_direct_FD_n2o) %>%
- rename(q1_n2o = QUINTILE1,
- q2_n2o = QUINTILE2,
- q3_n2o = QUINTILE3,
- q4_n2o = QUINTILE4,
- q5_n2o = QUINTILE5) %>%
- mutate(q1_n2o_domestic = q1_n2o,
- q2_n2o_domestic = q2_n2o,
- q3_n2o_domestic = q3_n2o,
- q4_n2o_domestic = q4_n2o,
- q5_n2o_domestic = q5_n2o,
- n2o_total = q1_n2o+q2_n2o+q3_n2o+q4_n2o+q5_n2o,
- n2o_total_domestic = q1_n2o_domestic+
- q2_n2o_domestic+q3_n2o_domestic+
- q4_n2o_domestic+q5_n2o_domestic)
-
-direct_FD_energy = direct_FD_fp_long_disagg %>%
- select(year,geo,sector,quintile,coicop,five_sectors,disaggregated_direct_FD_energy) %>%
- spread(quintile,disaggregated_direct_FD_energy) %>%
- rename(q1_energy = QUINTILE1,
- q2_energy = QUINTILE2,
- q3_energy = QUINTILE3,
- q4_energy = QUINTILE4,
- q5_energy = QUINTILE5) %>%
- mutate(q1_energy_domestic = q1_energy,
- q2_energy_domestic = q2_energy,
- q3_energy_domestic = q3_energy,
- q4_energy_domestic = q4_energy,
- q5_energy_domestic = q5_energy,
- energy_total = q1_energy+q2_energy+q3_energy+q4_energy+q5_energy,
- energy_total_domestic = q1_energy_domestic+
- q2_energy_domestic+q3_energy_domestic+
- q4_energy_domestic+q5_energy_domestic)
-
-
-direct_FD_fp_wide = direct_FD_co2 %>%
- left_join(direct_FD_ch4, by = c("year","geo",
- "sector","coicop",
- "five_sectors")) %>%
- left_join(direct_FD_n2o, by = c("year","geo",
- "sector","coicop",
- "five_sectors")) %>%
- left_join(direct_FD_energy, by = c("year","geo",
- "sector","coicop",
- "five_sectors")) %>%
- mutate(country_of_production = geo) %>%
- mutate(q1_co2eq = q1_co2 + q1_ch4 + q1_n2o,
- q2_co2eq = q2_co2 + q2_ch4 + q2_n2o,
- q3_co2eq = q3_co2 + q3_ch4 + q3_n2o,
- q4_co2eq = q4_co2 + q4_ch4 + q4_n2o,
- q5_co2eq = q5_co2 + q5_ch4 + q5_n2o,
- co2eq_total = q1_co2eq +
- q2_co2eq + q3_co2eq +
- q4_co2eq + q5_co2eq,
- q1_co2eq_domestic = q1_co2_domestic + q1_ch4_domestic + q1_n2o_domestic,
- q2_co2eq_domestic = q2_co2_domestic + q2_ch4_domestic + q2_n2o_domestic,
- q3_co2eq_domestic = q3_co2_domestic + q3_ch4_domestic + q3_n2o_domestic,
- q4_co2eq_domestic = q4_co2_domestic + q4_ch4_domestic + q4_n2o_domestic,
- q5_co2eq_domestic = q5_co2_domestic + q5_ch4_domestic + q5_n2o_domestic,
- co2eq_total_domestic = q1_co2eq_domestic +
- q2_co2eq_domestic + q3_co2eq_domestic +
- q4_co2eq_domestic + q5_co2eq_domestic) %>%
- select(-q1_ch4,
- -q2_ch4,
- -q3_ch4,
- -q4_ch4,
- -q5_ch4,
- -ch4_total,
- -q1_ch4_domestic,
- -q2_ch4_domestic,
- -q3_ch4_domestic,
- -q4_ch4_domestic,
- -q5_ch4_domestic,
- -ch4_total_domestic,
- -q1_n2o,
- -q2_n2o,
- -q3_n2o,
- -q4_n2o,
- -q5_n2o,
- -n2o_total,
- -q1_n2o_domestic,
- -q2_n2o_domestic,
- -q3_n2o_domestic,
- -q4_n2o_domestic,
- -q5_n2o_domestic,
- -n2o_total_domestic)
-
-direct_FD_fp_wide_all = direct_FD_fp_wide %>%
- clean_names() %>%
- select(year,geo,coicop,q1_co2:q5_co2,
- q1_co2_domestic:q5_co2_domestic,
- q1_co2eq:q5_co2eq,
- q1_co2eq_domestic:q5_co2eq_domestic,
- q1_energy:q5_energy,
- q1_energy_domestic:q5_energy_domestic)
-
-## extract co2 and pivot long
-cols_co2 = c("q1_co2", "q2_co2", "q3_co2", "q4_co2", "q5_co2")
-tmp_co2 = direct_FD_fp_wide_all %>%
- select(year, geo, coicop, cols_co2) %>%
- pivot_longer(cols = cols_co2,
- names_to = "quintile",
- values_to = "co2_kg") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-## extract co2 domestic and pivot long
-cols_co2_domestic = c("q1_co2_domestic", "q2_co2_domestic", "q3_co2_domestic", "q4_co2_domestic", "q5_co2_domestic")
-tmp_co2_domestic = direct_FD_fp_wide_all %>%
- select(year, geo, coicop, cols_co2_domestic) %>%
- pivot_longer(cols = cols_co2_domestic,
- names_to = "quintile",
- values_to = "co2_domestic_kg") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-## extract co2eq and pivot long
-cols_co2eq = c("q1_co2eq", "q2_co2eq", "q3_co2eq", "q4_co2eq", "q5_co2eq")
-tmp_co2eq = direct_FD_fp_wide_all %>%
- select(year, geo, coicop, cols_co2eq) %>%
- pivot_longer(cols = cols_co2eq,
- names_to = "quintile",
- values_to = "co2eq_kg") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-## extract co2eq domestic and pivot long
-cols_co2eq_domestic = c("q1_co2eq_domestic", "q2_co2eq_domestic", "q3_co2eq_domestic", "q4_co2eq_domestic", "q5_co2eq_domestic")
-tmp_co2eq_domestic = direct_FD_fp_wide_all %>%
- select(year, geo, coicop, cols_co2eq_domestic) %>%
- pivot_longer(cols = cols_co2eq_domestic,
- names_to = "quintile",
- values_to = "co2eq_domestic_kg") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-## extract energy use and pivot long
-cols_energy = c("q1_energy","q2_energy","q3_energy","q4_energy","q5_energy")
-tmp_energy = direct_FD_fp_wide_all %>%
- select(year, geo, coicop, cols_energy) %>%
- pivot_longer(cols = cols_energy,
- names_to = "quintile",
- values_to = "energy_use_TJ") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-## extract energy domestic and pivot long
-cols_energy_domestic = c("q1_energy_domestic","q2_energy_domestic","q3_energy_domestic","q4_energy_domestic","q5_energy_domestic")
-tmp_energy_domestic = direct_FD_fp_wide_all %>%
- select(year, geo, coicop, cols_energy_domestic) %>%
- pivot_longer(cols = cols_energy_domestic,
- names_to = "quintile",
- values_to = "energy_use_domestic_TJ") %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile)
-
-direct_FD_fp_wide_recombined = tmp_co2 %>%
- left_join(tmp_co2_domestic, by=c("year", "geo", "coicop", "quint")) %>%
- left_join(tmp_co2eq, by=c("year", "geo", "coicop", "quint")) %>%
- left_join(tmp_co2eq_domestic, by=c("year", "geo", "coicop", "quint")) %>%
- left_join(tmp_energy, by=c("year", "geo", "coicop", "quint")) %>%
- left_join(tmp_energy_domestic, by=c("year", "geo", "coicop", "quint")) %>%
- clean_names() %>%
- mutate(year = as.numeric(year))
-
-
-
-# something is wrong with 'bah' (don't think so anymore) - the expenditures match the german and now the
-#shares match the german, but some countries are clearly wrong - with almost 100% shares in CP04, whereas some look
-#relatively normal - have to figure this out - huge TIVS in the CP045 sector for those weird countries. likely some weird
-#sector that has a huge TIV but not much expenditure to it so need to do a weighted average - was the case, now have done
-#with weighted TIV. some eastern european countries like Bulgaria still have huge CP04 emission shares - might be correct
-#if their electricity is extremely dirty - need to look at the intensities of each country individually
-
-results = ok %>%
- filter(!(geo %in% c("EA","EA12","EA13","EA17",
- "EA18","EA19","EEA28","EEA30_2007",
- "EFTA","EU15","EU25",
- "EU27_2007", "EU27_2020",
- "EU28","XK", "RS",
- "MK", "ME")),
- !(quintile %in% c("TOTAL","UNK")),
- !(year %in% c(1988,1994,1999))) %>%
- group_by(geo,quintile,year,coicop) %>%
- summarise(fd_me = sum(fd_me, na.rm = TRUE),
- co2_kg = sum(co2_kg, na.rm = TRUE),
- co2_domestic_kg = sum(co2_domestic_kg, na.rm = TRUE),
- co2_europe_kg = sum(co2_europe_kg, na.rm = TRUE),
- co2eq_kg = sum(co2eq_kg, na.rm = TRUE),
- co2eq_domestic_kg = sum(co2eq_domestic_kg, na.rm = TRUE),
- co2eq_europe_kg = sum(co2eq_europe_kg, na.rm = TRUE),
- energy_use_TJ = sum(energy_use_TJ, na.rm = TRUE),
- energy_use_domestic_TJ = sum(energy_use_domestic_TJ, na.rm = TRUE),
- energy_use_europe_TJ = sum(energy_use_europe_TJ, na.rm = TRUE)) %>%
- ungroup() %>%
- mutate(year = as.numeric(year)) %>%
- na.omit()
-
-results_formatted = results %>%
- clean_names() %>%
- mutate(quint = parse_number(quintile)) %>%
- select(-quintile) %>%
- filter(coicop %in% c("CP011",
- "CP012",
- "CP02",
- "CP03",
- "rent",
- "CP043",
- "CP044",
- "CP045",
- "CP05",
- "CP06",
- "CP071",
- "CP072",
- "CP073",
- "CP08",
- "CP09",
- "CP10",
- "CP11",
- "CP12"))
-
-results_formatted_with_direct_FD_fp = bind_rows(results_formatted,direct_FD_fp_wide_recombined)
-
-
-write.csv(results_formatted_with_direct_FD_fp, paste0(data_dir_income_stratified_footprints, "/results_formatted_method2_ixi_pps_hh_no_rent.csv"))</code></pre>
</div>
<div id="european-exp-deciles" class="section level1">
<h1>European exp deciles</h1>
-<pre class="r"><code>knitr::opts_chunk$set(echo = FALSE, message=FALSE)
-
-if (!require("pacman")) install.packages("pacman")
-pacman::p_load(tidyverse,
- janitor,
- here,
- wbstats,
- ISOcodes,
- viridis,
- imputeTS,
- hrbrthemes,
- wesanderson,
- glue)
-
-target_eu_ntiles = 10
-
-source(here("code", "helper_functions.R"))
-
-
-# 1) load MRIO result file
-dat_results_raw = read_rds(here("data", "results_formatted_method1_ixi_pps_hh_no_rent.rds")) %>%
- ungroup() %>%
- mutate(year= strtoi(year)) %>%
- rename(iso2 = geo)
-
-# get iso3 country codes to join with hh data
-country_codes = ISOcodes::ISO_3166_1 %>%
- select(iso2 = Alpha_2, iso3 = Alpha_3) %>%
- # resolve inconsistency between Eurostat and ISO for Greece and UK/Great Britain
- mutate(iso2 = if_else(iso2=="GR", "EL", iso2)) %>%
- mutate(iso2 = if_else(iso2=="GB", "UK", iso2))
-
-# 2) load Eurostat household data - should show how I get to 'total_private_households.csv' - see code chunk in SI - move to here.
-hh_data = read_csv(here("data", "total_private_households.csv")) %>%
- mutate(imputed = if_else(is.na(total_private_households), TRUE, FALSE)) %>%
- rename(iso2 = geo) %>%
- group_by(iso2) %>%
- # impute households with next available neighbour
- mutate(hh = na_locf(total_private_households)) %>%
- left_join(country_codes, by="iso2") %>%
- select(-total_private_households)
-
-#3) Eurostat mean expenditures per household income quintile per household and per adult equivalent
-df_expenditure_long = read_csv(here("data",
- "mean_expenditure_by_quintile_long.csv"),
- na = ":") %>%
- #filter(year >=2010, geo != "IT") %>%
- #filter(year >=2005, geo != "IT") %>%
- #decide here
- filter(year >=2005) %>%
- mutate(imputed = if_else(is.na(mean_expenditure), TRUE, FALSE)) %>%
- group_by(geo,unit,quintile) %>%
- mutate(value = na_locf(mean_expenditure)) %>%
- select(-mean_expenditure) %>%
- ungroup()
-
-
-# df_expenditure_2005 = df_expenditure_long %>%
-# filter(year == 2010) %>%
-# mutate(year = 2005,
-# imputed = TRUE)
-#
-# df_expenditure_long = df_expenditure_long %>%
-# bind_rows(df_expenditure_2005)
-
-## Calculate adult equivalents per household
-df_adult_e_p_hh = df_expenditure_long %>%
- rename(iso2 = geo) %>%
- pivot_wider(id_cols = c(iso2, year, quintile, imputed),
- names_from = unit,
- values_from = value) %>%
- clean_names() %>%
- mutate(adult_e_p_hh = pps_hh/pps_ae) %>%
- left_join(country_codes, by="iso2") %>%
- mutate(iso3 = if_else(iso2 == "XK", "XKX", iso3),
- quint = parse_number(quintile))
-
-
-# add quintile population data
-mrio_results_with_adult_eq_all = dat_results_raw %>%
- filter(year %in% c(2005, 2010, 2015)) %>%
- left_join(hh_data, by=c("iso2", "year")) %>%
- mutate(hh_quintile = hh/5) %>% # population per country quinitle
- select(-hh) %>%
- rename(hh_imputed = imputed) %>%
- left_join(df_adult_e_p_hh %>%
- select(iso2, year, quint, imputed_ae = imputed, adult_e_p_hh),
- by=c("iso2", "year", "quint")) %>%
- mutate(ae_quintile = hh_quintile * adult_e_p_hh) %>%
- select(-c(hh_quintile, adult_e_p_hh))
-
-
-#### ONLY COUNTRIES THAT HAVE DATA FOR 2005, 2010, and 2015
-## TODO: maybe make a bit less dirty =)
-complete_countries = mrio_results_with_adult_eq_all %>%
- group_by(year, iso2) %>%
- summarise(co2_kg = sum(co2_kg)) %>%
- ungroup() %>%
- filter(co2_kg>0) %>%
- select(iso2, year, co2_kg) %>%
- pivot_wider(id_cols = c(iso2), names_from = year, values_from = co2_kg) %>%
- drop_na() %>%
- select(iso2) %>%
- pull()
-
-
-hh_data %>%
- filter(iso2 %in% complete_countries, year<=2015, year>=2005) %>%
-ggplot(aes(x=year, y=hh*0.000001)) +
- geom_line() +
- geom_point(data=hh_data %>%
- filter(iso2 %in% complete_countries,
- year<=2015,
- year>=2005,
- imputed), color="red") +
- theme_ipsum() +
- scale_x_continuous(labels = scales::label_number(accuracy = 1, big.mark = "")) +
- labs(x="", y="Total number of households (mio)") +
- facet_wrap(~iso3, scales="free_y", ncol = 4) +
- theme(legend.position = "bottom",
- axis.text.x = element_text(angle = 90))
-
-#ggsave(here("figures", "household_size.png"), plot = p, width = 8, height = 14)
-
-pal <- wes_palette("Cavalcanti1", 5, type = "discrete")
-pal = pal[c(1,2,5)]
-
-df_adult_e_p_hh %>%
- filter(iso2 %in% complete_countries, year<=2015, year>=2005) %>%
- mutate(quint = parse_number(quintile)) %>%
- ggplot(aes(x=quint, y=adult_e_p_hh, color=factor(year))) +
- geom_line(alpha=0.5) +
- theme_ipsum() +
- scale_color_manual(name = "Year", values = pal) +
- labs(x="", y="Adult equivivalents per household") +
- facet_wrap(~iso3, ncol = 4) +
- theme(legend.position = "bottom",
- axis.text.x = element_text(angle = 90))
-
-#ggsave(here("figures", "adult_eq_per_household.png"), plot = p, width = 8, height = 14)
-
-df_adult_e_p_hh %>%
- filter(iso2 %in% complete_countries, year<=2015, year>=2005) %>%
- mutate(quint = parse_number(quintile)) %>%
- write_csv(here("data", "adult_eq_per_household.csv"))
-
-
-# calculate EU expenditure tiles based on loaded mrio result file and adult equivalents.
-# returns country quintiles mapped to EU ntile rank and EU ntile boundaries
-# helper function called by function below
-calculate_eu_ntiles <- function(pyear, pquantile_count=10) {
-
- country_data_annual_sorted = summary_country_fd %>%
- ungroup() %>%
- filter(year==pyear) %>%
- arrange(fd_pae_e) %>%
- mutate(idx = 1:n(),
- eu_q_rank = 0) # later to be filled with euro quintile rank
-
- # total EU adult equivalents (of included countries) in year
- total_ae_in_year = sum(country_data_annual_sorted$ae_quintile)
-
- # quantile target ae population
- eu_decile_adult_eq = total_ae_in_year/pquantile_count
-
- # country quinitles must be split to allocate ae population accorting to eu quantile target ae population
- # filtering by condition that cant be fulfilled is a lazy way to create an empty dataframe
- # of the same structure as country_data_annual_sorted
- additional_rows = country_data_annual_sorted %>%
- filter(year==1)
-
- # store quantile split values
- eu_quantile_boundaries = data.frame(euro_q_rank = 1:pquantile_count, p = 0)
-
- ## can't think of a non-loop way to do this, sorry
- ## loops through the ordered dataset, assignes euro quantile rank
- ## and splits quintiles where necessary
- eu_ae_current = 0
- euro_q_rank_current = 1
- for (row_idx in 1:nrow(country_data_annual_sorted)) {
- row = country_data_annual_sorted[row_idx,]
- if (row["ae_quintile"] + eu_ae_current <= eu_decile_adult_eq) {
- eu_ae_current = eu_ae_current + row["ae_quintile"]
- country_data_annual_sorted[row_idx, "eu_q_rank"] = euro_q_rank_current
- } else {
- ae_diff = eu_decile_adult_eq - eu_ae_current
- ## write rest of this eu decile (split country quintile)
- new_row = country_data_annual_sorted[row_idx, ]
- new_row[1, "eu_q_rank"] = euro_q_rank_current
- new_row[1, "ae_quintile"] = ae_diff
- ## record eu quantile boundary
- eu_quantile_boundaries[eu_quantile_boundaries$euro_q_rank==euro_q_rank_current, "p"] =
- country_data_annual_sorted[row_idx, "fd_pae_e"]
- ## put first part of population in overflow dataframe
- additional_rows = additional_rows %>%
- bind_rows(new_row)
- ## classify rest of country quinitle population to next euro quantile
- country_data_annual_sorted[row_idx, "ae_quintile"] =
- country_data_annual_sorted[row_idx, "ae_quintile"] - (ae_diff+0.0001)
- euro_q_rank_current = euro_q_rank_current + 1
- country_data_annual_sorted[row_idx, "eu_q_rank"] = euro_q_rank_current
- eu_ae_current = country_data_annual_sorted[row_idx, "ae_quintile"]
-
- }
- }
-
- country_data_eu_quantiles = country_data_annual_sorted %>%
- bind_rows(additional_rows) %>%
- arrange(fd_pae_e, eu_q_rank) %>%
- mutate(idx = 1:n())
-
- #ad zeroth and nth quantile (min and max)
- eu_quantile_boundaries[pquantile_count, "p"] = max(country_data_eu_quantiles$fd_pae_e)
- #tmp = data.frame(euro_q_rank = 0, p = min(country_data_eu_quantiles$fd_pae_e)) %>%
- # bind_rows(eu_quantile_boundaries)
-
-
- list("df_q_data" = country_data_eu_quantiles, "df_q_boundaries" = eu_quantile_boundaries)
-}
-
-# maps MRIO results to EU ntile ranks, returns mapping and ntile EU boundaries
-map_mrio_results_to_eu_ntiles <- function(pyear, ptarget_ntiles) {
-
- df_eu_ntiles = calculate_eu_ntiles(pyear, pquantile_count = ptarget_ntiles)
- df_eu_ntiles_data = df_eu_ntiles$df_q_data
- #df_eu_ntiles_p = df_eu_ntiles$df_q_boundaries
-
- sector_mapping = mrio_results_with_adult_eq %>%
- group_by(sector_id) %>%#
- summarise(sector_agg_id = first(sector_agg_id)) %>%
- ungroup()
-
- df_mapped_data = mrio_results_with_adult_eq %>%
- select(year,
- iso2,
- quint,
- sector_id,
- fd_me,
- co2_kg,
- co2_domestic_kg,
- co2_europe_kg,
- co2eq_kg,
- co2eq_domestic_kg,
- co2eq_europe_kg,
- energy_use_TJ,
- energy_use_domestic_TJ,
- energy_use_europe_TJ,
- ae_quintile) %>%
- filter(year==pyear) %>%
- # calc per adult aequivalent values in quintiles
- mutate(fd_pae_e = fd_me*1000000/ae_quintile,
- co2_pae_kg = co2_kg/ae_quintile,
- co2_pae_dom_kg = co2_domestic_kg/ae_quintile,
- co2_pae_eu_kg = co2_europe_kg/ae_quintile,
- co2eq_pae_kg = co2eq_kg/ae_quintile,
- co2eq_pae_dom_kg = co2eq_domestic_kg/ae_quintile,
- co2eq_pae_eu_kg = co2eq_europe_kg/ae_quintile,
- energy_use_pae_tj = energy_use_TJ/ae_quintile,
- energy_use_dom_pae_tj = energy_use_domestic_TJ/ae_quintile,
- energy_use_eu_pae_tj = energy_use_europe_TJ/ae_quintile) %>%
- # remove totals
- select(-c(fd_me,
- co2_kg,
- co2_domestic_kg,
- co2_europe_kg,
- co2eq_kg,
- co2eq_domestic_kg,
- co2eq_europe_kg,
- energy_use_TJ,
- energy_use_domestic_TJ,
- energy_use_europe_TJ,
- year, ae_quintile)) %>%
- full_join(df_eu_ntiles_data %>%
- rename(fd_pae_e_quint_tmp = fd_pae_e), by=c("iso2", "quint")) %>%
- rename(adult_eq = ae_quintile) %>% # country quintile and their split fraction population
- # recalc totals
- mutate(fd_me = fd_pae_e*adult_eq/1000000,
- co2_kg = co2_pae_kg*adult_eq,
- co2_dom_kg = co2_pae_dom_kg*adult_eq,
- co2_eu_kg = co2_pae_eu_kg*adult_eq,
- co2eq_kg = co2eq_pae_kg*adult_eq,
- co2eq_dom_kg = co2eq_pae_dom_kg*adult_eq,
- co2eq_eu_kg = co2eq_pae_eu_kg*adult_eq,
- energy_use_tj = energy_use_pae_tj*adult_eq,
- energy_use_dom_tj = energy_use_dom_pae_tj*adult_eq,
- energy_use_eu_tj = energy_use_eu_pae_tj*adult_eq
- ) %>%
- left_join(sector_mapping, by="sector_id")
-
- list("df_mapped_data" = df_mapped_data, "df_ntile_boundaries" = df_eu_ntiles$df_q_boundaries)
-
-}
-
-
-### Filter only countries with complete info for years 2005, 2010, 2015
-mrio_results_with_adult_eq = mrio_results_with_adult_eq_all %>%
- filter(iso2 %in% complete_countries)
-
-## summarize final demand per adult equvalent per quintile across all sectors as basis for eurodeciles for complete countries
-summary_country_fd = mrio_results_with_adult_eq %>%
- group_by(iso2, year, quint) %>%
- summarise(ae_quintile = first(ae_quintile),
- fd_pae_e = sum(fd_me*1000000)/(ae_quintile))
-
-## summarize final demand per adult equvalent per quintile across all sectors as basis for eurodeciles for all countries
-summary_country_fd_all = mrio_results_with_adult_eq_all %>%
- group_by(iso2, year, quint) %>%
- summarise(ae_quintile = first(ae_quintile),
- fd_pae_e = sum(fd_me*1000000)/(ae_quintile))
-
-
-df_mapped_result_2005 = map_mrio_results_to_eu_ntiles(2005, target_eu_ntiles)
-df_mapped_result_2005_data = df_mapped_result_2005$df_mapped_data
-df_mapped_result_2005_ntiles = df_mapped_result_2005$df_ntile_boundaries
-
-df_mapped_result_2010 = map_mrio_results_to_eu_ntiles(2010, target_eu_ntiles)
-df_mapped_result_2010_data = df_mapped_result_2010$df_mapped_data
-df_mapped_result_2010_ntiles = df_mapped_result_2010$df_ntile_boundaries
-
-df_mapped_result_2015 = map_mrio_results_to_eu_ntiles(2015, target_eu_ntiles)
-df_mapped_result_2015_data = df_mapped_result_2015$df_mapped_data
-df_mapped_result_2015_ntiles = df_mapped_result_2015$df_ntile_boundaries
-
-df_mapped_result_data = df_mapped_result_2005_data %>%
- bind_rows(df_mapped_result_2010_data) %>%
- bind_rows(df_mapped_result_2015_data)
-
-write_csv(df_mapped_result_data,
- here(paste0("data/mrio_results_eu_ntile_mapped_n_", target_eu_ntiles, ".csv")))
-
-df_mapped_result_ntiles =
- df_mapped_result_2005_ntiles %>% mutate(year=2005) %>%
- bind_rows(df_mapped_result_2010_ntiles %>% mutate(year=2010)) %>%
- bind_rows(df_mapped_result_2015_ntiles %>% mutate(year=2015))
-
-write_csv(df_mapped_result_ntiles,
- here(paste0("data/eu_ntiles_n_", target_eu_ntiles, ".csv")))
-
-######
-
-knitr::opts_chunk$set(echo = FALSE, message=FALSE)
-
-if (!require("pacman")) install.packages("pacman")
-pacman::p_load(tidyverse,
- janitor,
- here,
- wbstats,
- ISOcodes,
- viridis,
- imputeTS,
- hrbrthemes,
- wesanderson,
- glue)
-
-target_eu_ntiles = 10
-
-source(here("code", "helper_functions.R"))
-
-dat_results_raw = read_rds(here("data", "results_formatted_method1_pxp_pps_hh_no_rent.rds")) %>%
- ungroup() %>%
- mutate(year= strtoi(year)) %>%
- rename(iso2 = geo)
-
-# get iso3 country codes to join with hh data
-country_codes = ISOcodes::ISO_3166_1 %>%
- select(iso2 = Alpha_2, iso3 = Alpha_3) %>%
- # resolve inconsistency between Eurostat and ISO for Greece and UK/Great Britain
- mutate(iso2 = if_else(iso2=="GR", "EL", iso2)) %>%
- mutate(iso2 = if_else(iso2=="GB", "UK", iso2))
-
-# 2) load Eurostat household data
-hh_data = read_csv(here("data", "total_private_households.csv")) %>%
- mutate(imputed = if_else(is.na(total_private_households), TRUE, FALSE)) %>%
- rename(iso2 = geo) %>%
- group_by(iso2) %>%
- # impute households with next available neighbour
- mutate(hh = na_locf(total_private_households)) %>%
- left_join(country_codes, by="iso2") %>%
- select(-total_private_households)
-
-#3) Eurostat mean expenditures per household income quintile per household and per adult equivalent
-df_expenditure_long = read_csv(here("data",
- "mean_expenditure_by_quintile_long.csv"),
- na = ":") %>%
- #filter(year >=2010, geo != "IT") %>%
- #filter(year >=2005, geo != "IT") %>%
- #decide here
- filter(year >=2005) %>%
- mutate(imputed = if_else(is.na(mean_expenditure), TRUE, FALSE)) %>%
- group_by(geo,unit,quintile) %>%
- mutate(value = na_locf(mean_expenditure)) %>%
- select(-mean_expenditure) %>%
- ungroup()
-
-# df_expenditure_2005 = df_expenditure_long %>%
-# filter(year == 2010) %>%
-# mutate(year = 2005,
-# imputed = TRUE)
-#
-# df_expenditure_long = df_expenditure_long %>%
-# bind_rows(df_expenditure_2005)
-
-## Calculate adult equivalents per household
-df_adult_e_p_hh = df_expenditure_long %>%
- rename(iso2 = geo) %>%
- pivot_wider(id_cols = c(iso2, year, quintile, imputed),
- names_from = unit,
- values_from = value) %>%
- clean_names() %>%
- mutate(adult_e_p_hh = pps_hh/pps_ae) %>%
- left_join(country_codes, by="iso2") %>%
- mutate(iso3 = if_else(iso2 == "XK", "XKX", iso3),
- quint = parse_number(quintile))
-
-
-# add quintile population data
-mrio_results_with_adult_eq_all = dat_results_raw %>%
- filter(year %in% c(2005, 2010, 2015)) %>%
- left_join(hh_data, by=c("iso2", "year")) %>%
- mutate(hh_quintile = hh/5) %>% # population per country quinitle
- select(-hh) %>%
- rename(hh_imputed = imputed) %>%
- left_join(df_adult_e_p_hh %>%
- select(iso2, year, quint, imputed_ae = imputed, adult_e_p_hh),
- by=c("iso2", "year", "quint")) %>%
- mutate(ae_quintile = hh_quintile * adult_e_p_hh) %>%
- select(-c(hh_quintile, adult_e_p_hh))
-
-
-#### ONLY COUNTRIES THAT HAVE DATA FOR 2005, 2010, and 2015
-## TODO: maybe make a bit less dirty =)
-complete_countries = mrio_results_with_adult_eq_all %>%
- group_by(year, iso2) %>%
- summarise(co2_kg = sum(co2_kg)) %>%
- ungroup() %>%
- filter(co2_kg>0) %>%
- select(iso2, year, co2_kg) %>%
- pivot_wider(id_cols = c(iso2), names_from = year, values_from = co2_kg) %>%
- drop_na() %>%
- select(iso2) %>%
- pull()
-
-hh_data %>%
- filter(iso2 %in% complete_countries, year<=2015, year>=2005) %>%
-ggplot(aes(x=year, y=hh*0.000001)) +
- geom_line() +
- geom_point(data=hh_data %>%
- filter(iso2 %in% complete_countries,
- year<=2015,
- year>=2005,
- imputed), color="red") +
- theme_ipsum() +
- scale_x_continuous(labels = scales::label_number(accuracy = 1, big.mark = "")) +
- labs(x="", y="Total number of households (mio)") +
- facet_wrap(~iso3, scales="free_y", ncol = 4) +
- theme(legend.position = "bottom",
- axis.text.x = element_text(angle = 90))
-
-#ggsave(here("figures", "household_size.png"), plot = p, width = 8, height = 14)
-
-pal <- wes_palette("Cavalcanti1", 5, type = "discrete")
-pal = pal[c(1,2,5)]
-
-df_adult_e_p_hh %>%
- filter(iso2 %in% complete_countries, year<=2015, year>=2005) %>%
- mutate(quint = parse_number(quintile)) %>%
- ggplot(aes(x=quint, y=adult_e_p_hh, color=factor(year))) +
- geom_line(alpha=0.5) +
- theme_ipsum() +
- scale_color_manual(name = "Year", values = pal) +
- labs(x="", y="Adult equivivalents per household") +
- facet_wrap(~iso3, ncol = 4) +
- theme(legend.position = "bottom",
- axis.text.x = element_text(angle = 90))
-
-#ggsave(here("figures", "adult_eq_per_household.png"), plot = p, width = 8, height = 14)
-
-df_adult_e_p_hh %>%
- filter(iso2 %in% complete_countries, year<=2015, year>=2005) %>%
- mutate(quint = parse_number(quintile)) %>%
- write_csv(here("data", "adult_eq_per_household.csv"))
-
-# calculate EU expenditure tiles based on loaded mrio result file and adult equivalents.
-# returns country quintiles mapped to EU ntile rank and EU ntile boundaries
-# helper function called by function below
-calculate_eu_ntiles <- function(pyear, pquantile_count=10) {
-
- country_data_annual_sorted = summary_country_fd %>%
- ungroup() %>%
- filter(year==pyear) %>%
- arrange(fd_pae_e) %>%
- mutate(idx = 1:n(),
- eu_q_rank = 0) # later to be filled with euro quintile rank
-
- # total EU adult equivalents (of included countries) in year
- total_ae_in_year = sum(country_data_annual_sorted$ae_quintile)
-
- # quantile target ae population
- eu_decile_adult_eq = total_ae_in_year/pquantile_count
-
- # country quinitles must be split to allocate ae population accorting to eu quantile target ae population
- # filtering by condition that cant be fulfilled is a lazy way to create an empty dataframe
- # of the same structure as country_data_annual_sorted
- additional_rows = country_data_annual_sorted %>%
- filter(year==1)
-
- # store quantile split values
- eu_quantile_boundaries = data.frame(euro_q_rank = 1:pquantile_count, p = 0)
-
- ## can't think of a non-loop way to do this, sorry
- ## loops through the ordered dataset, assignes euro quantile rank
- ## and splits quintiles where necessary
- eu_ae_current = 0
- euro_q_rank_current = 1
- for (row_idx in 1:nrow(country_data_annual_sorted)) {
- row = country_data_annual_sorted[row_idx,]
- if (row["ae_quintile"] + eu_ae_current <= eu_decile_adult_eq) {
- eu_ae_current = eu_ae_current + row["ae_quintile"]
- country_data_annual_sorted[row_idx, "eu_q_rank"] = euro_q_rank_current
- } else {
- ae_diff = eu_decile_adult_eq - eu_ae_current
- ## write rest of this eu decile (split country quintile)
- new_row = country_data_annual_sorted[row_idx, ]
- new_row[1, "eu_q_rank"] = euro_q_rank_current
- new_row[1, "ae_quintile"] = ae_diff
- ## record eu quantile boundary
- eu_quantile_boundaries[eu_quantile_boundaries$euro_q_rank==euro_q_rank_current, "p"] =
- country_data_annual_sorted[row_idx, "fd_pae_e"]
- ## put first part of population in overflow dataframe
- additional_rows = additional_rows %>%
- bind_rows(new_row)
- ## classify rest of country quinitle population to next euro quantile
- country_data_annual_sorted[row_idx, "ae_quintile"] =
- country_data_annual_sorted[row_idx, "ae_quintile"] - (ae_diff+0.0001)
- euro_q_rank_current = euro_q_rank_current + 1
- country_data_annual_sorted[row_idx, "eu_q_rank"] = euro_q_rank_current
- eu_ae_current = country_data_annual_sorted[row_idx, "ae_quintile"]
-
- }
- }
-
- country_data_eu_quantiles = country_data_annual_sorted %>%
- bind_rows(additional_rows) %>%
- arrange(fd_pae_e, eu_q_rank) %>%
- mutate(idx = 1:n())
-
- #ad zeroth and nth quantile (min and max)
- eu_quantile_boundaries[pquantile_count, "p"] = max(country_data_eu_quantiles$fd_pae_e)
- #tmp = data.frame(euro_q_rank = 0, p = min(country_data_eu_quantiles$fd_pae_e)) %>%
- # bind_rows(eu_quantile_boundaries)
-
-
- list("df_q_data" = country_data_eu_quantiles, "df_q_boundaries" = eu_quantile_boundaries)
-}
-
-# maps MRIO results to EU ntile ranks, returns mapping and ntile EU boundaries
-map_mrio_results_to_eu_ntiles <- function(pyear, ptarget_ntiles) {
-
- df_eu_ntiles = calculate_eu_ntiles(pyear, pquantile_count = ptarget_ntiles)
- df_eu_ntiles_data = df_eu_ntiles$df_q_data
- #df_eu_ntiles_p = df_eu_ntiles$df_q_boundaries
-
- sector_mapping = mrio_results_with_adult_eq %>%
- group_by(sector_id) %>%#
- summarise(sector_agg_id = first(sector_agg_id)) %>%
- ungroup()
-
- df_mapped_data = mrio_results_with_adult_eq %>%
- select(year,
- iso2,
- quint,
- sector_id,
- fd_me,
- co2_kg,
- co2_domestic_kg,
- co2_europe_kg,
- co2eq_kg,
- co2eq_domestic_kg,
- co2eq_europe_kg,
- energy_use_TJ,
- energy_use_domestic_TJ,
- energy_use_europe_TJ,
- ae_quintile) %>%
- filter(year==pyear) %>%
- # calc per adult aequivalent values in quintiles
- mutate(fd_pae_e = fd_me*1000000/ae_quintile,
- co2_pae_kg = co2_kg/ae_quintile,
- co2_pae_dom_kg = co2_domestic_kg/ae_quintile,
- co2_pae_eu_kg = co2_europe_kg/ae_quintile,
- co2eq_pae_kg = co2eq_kg/ae_quintile,
- co2eq_pae_dom_kg = co2eq_domestic_kg/ae_quintile,
- co2eq_pae_eu_kg = co2eq_europe_kg/ae_quintile,
- energy_use_pae_tj = energy_use_TJ/ae_quintile,
- energy_use_dom_pae_tj = energy_use_domestic_TJ/ae_quintile,
- energy_use_eu_pae_tj = energy_use_europe_TJ/ae_quintile) %>%
- # remove totals
- select(-c(fd_me,
- co2_kg,
- co2_domestic_kg,
- co2_europe_kg,
- co2eq_kg,
- co2eq_domestic_kg,
- co2eq_europe_kg,
- energy_use_TJ,
- energy_use_domestic_TJ,
- energy_use_europe_TJ,
- year, ae_quintile)) %>%
- full_join(df_eu_ntiles_data %>%
- rename(fd_pae_e_quint_tmp = fd_pae_e), by=c("iso2", "quint")) %>%
- rename(adult_eq = ae_quintile) %>% # country quintile and their split fraction population
- # recalc totals
- mutate(fd_me = fd_pae_e*adult_eq/1000000,
- co2_kg = co2_pae_kg*adult_eq,
- co2_dom_kg = co2_pae_dom_kg*adult_eq,
- co2_eu_kg = co2_pae_eu_kg*adult_eq,
- co2eq_kg = co2eq_pae_kg*adult_eq,
- co2eq_dom_kg = co2eq_pae_dom_kg*adult_eq,
- co2eq_eu_kg = co2eq_pae_eu_kg*adult_eq,
- energy_use_tj = energy_use_pae_tj*adult_eq,
- energy_use_dom_tj = energy_use_dom_pae_tj*adult_eq,
- energy_use_eu_tj = energy_use_eu_pae_tj*adult_eq
- ) %>%
- left_join(sector_mapping, by="sector_id")
-
- list("df_mapped_data" = df_mapped_data, "df_ntile_boundaries" = df_eu_ntiles$df_q_boundaries)
-
-}
-
-### Filter only countries with complete info for years 2005, 2010, 2015
-mrio_results_with_adult_eq = mrio_results_with_adult_eq_all %>%
- filter(iso2 %in% complete_countries)
-
-## summarize final demand per adult equvalent per quintile across all sectors as basis for eurodeciles for complete countries
-summary_country_fd = mrio_results_with_adult_eq %>%
- group_by(iso2, year, quint) %>%
- summarise(ae_quintile = first(ae_quintile),
- fd_pae_e = sum(fd_me*1000000)/(ae_quintile))
-
-## summarize final demand per adult equvalent per quintile across all sectors as basis for eurodeciles for all countries
-summary_country_fd_all = mrio_results_with_adult_eq_all %>%
- group_by(iso2, year, quint) %>%
- summarise(ae_quintile = first(ae_quintile),
- fd_pae_e = sum(fd_me*1000000)/(ae_quintile))
-
-df_mapped_result_2005 = map_mrio_results_to_eu_ntiles(2005, target_eu_ntiles)
-df_mapped_result_2005_data = df_mapped_result_2005$df_mapped_data
-df_mapped_result_2005_ntiles = df_mapped_result_2005$df_ntile_boundaries
-
-df_mapped_result_2010 = map_mrio_results_to_eu_ntiles(2010, target_eu_ntiles)
-df_mapped_result_2010_data = df_mapped_result_2010$df_mapped_data
-df_mapped_result_2010_ntiles = df_mapped_result_2010$df_ntile_boundaries
-
-#df_mapped_result_2015 = map_mrio_results_to_eu_ntiles(2015, target_eu_ntiles)
-#df_mapped_result_2015_data = df_mapped_result_2015$df_mapped_data
-#df_mapped_result_2015_ntiles = df_mapped_result_2015$df_ntile_boundaries
-
-df_mapped_result_data = df_mapped_result_2005_data %>%
- bind_rows(df_mapped_result_2010_data) #%>%
- #bind_rows(df_mapped_result_2015_data)
-
-write_csv(df_mapped_result_data,
- here(paste0("data/mrio_results_eu_ntile_mapped_n_", target_eu_ntiles, "_pxp.csv")))
-
-df_mapped_result_ntiles =
- df_mapped_result_2005_ntiles %>% mutate(year=2005) %>%
- bind_rows(df_mapped_result_2010_ntiles %>% mutate(year=2010)) #%>%
- #bind_rows(df_mapped_result_2015_ntiles %>% mutate(year=2015))
-
-write_csv(df_mapped_result_ntiles,
- here(paste0("data/eu_ntiles_n_", target_eu_ntiles, "_pxp.csv")))
-
-######
-
-knitr::opts_chunk$set(echo = FALSE, message=FALSE)
-
-if (!require("pacman")) install.packages("pacman")
-pacman::p_load(tidyverse,
- janitor,
- here,
- wbstats,
- ISOcodes,
- viridis,
- imputeTS,
- hrbrthemes,
- wesanderson,
- glue)
-
-target_eu_ntiles = 10
-
-source(here("code", "helper_functions.R"))
-
-# 1) load MRIO result file
-dat_results_raw = read_rds(here("data", "results_formatted_method2_ixi_pps_hh_no_rent.rds")) %>%
- ungroup() %>%
- mutate(year= strtoi(year)) %>%
- rename(iso2 = geo)
-
-# get iso3 country codes to join with hh data
-country_codes = ISOcodes::ISO_3166_1 %>%
- select(iso2 = Alpha_2, iso3 = Alpha_3) %>%
- # resolve inconsistency between Eurostat and ISO for Greece and UK/Great Britain
- mutate(iso2 = if_else(iso2=="GR", "EL", iso2)) %>%
- mutate(iso2 = if_else(iso2=="GB", "UK", iso2))
-
-# 2) load Eurostat household data
-hh_data = read_csv(here("data", "total_private_households.csv")) %>%
- mutate(imputed = if_else(is.na(total_private_households), TRUE, FALSE)) %>%
- rename(iso2 = geo) %>%
- group_by(iso2) %>%
- # impute households with next available neighbour
- mutate(hh = na_locf(total_private_households)) %>%
- left_join(country_codes, by="iso2") %>%
- select(-total_private_households)
-
-#3) Eurostat mean expenditures per household income quintile per household and per adult equivalent
-df_expenditure_long = read_csv(here("data",
- "mean_expenditure_by_quintile_long.csv"),
- na = ":") %>%
- #filter(year >=2010, geo != "IT") %>%
- #filter(year >=2005, geo != "IT") %>%
- #decide here
- filter(year >=2005) %>%
- mutate(imputed = if_else(is.na(mean_expenditure), TRUE, FALSE)) %>%
- group_by(geo,unit,quintile) %>%
- mutate(value = na_locf(mean_expenditure)) %>%
- select(-mean_expenditure) %>%
- ungroup()
-
-# df_expenditure_2005 = df_expenditure_long %>%
-# filter(year == 2010) %>%
-# mutate(year = 2005,
-# imputed = TRUE)
-#
-# df_expenditure_long = df_expenditure_long %>%
-# bind_rows(df_expenditure_2005)
-
-## Calculate adult equivalents per household
-df_adult_e_p_hh = df_expenditure_long %>%
- rename(iso2 = geo) %>%
- pivot_wider(id_cols = c(iso2, year, quintile, imputed),
- names_from = unit,
- values_from = value) %>%
- clean_names() %>%
- mutate(adult_e_p_hh = pps_hh/pps_ae) %>%
- left_join(country_codes, by="iso2") %>%
- mutate(iso3 = if_else(iso2 == "XK", "XKX", iso3),
- quint = parse_number(quintile))
-
-
-# add quintile population data
-mrio_results_with_adult_eq_all = dat_results_raw %>%
- filter(year %in% c(2005, 2010, 2015)) %>%
- left_join(hh_data, by=c("iso2", "year")) %>%
- mutate(hh_quintile = hh/5) %>% # population per country quinitle
- select(-hh) %>%
- rename(hh_imputed = imputed) %>%
- left_join(df_adult_e_p_hh %>%
- select(iso2, year, quint, imputed_ae = imputed, adult_e_p_hh),
- by=c("iso2", "year", "quint")) %>%
- mutate(ae_quintile = hh_quintile * adult_e_p_hh) %>%
- select(-c(hh_quintile, adult_e_p_hh))
-
-
-#### ONLY COUNTRIES THAT HAVE DATA FOR 2005, 2010, and 2015
-## TODO: maybe make a bit less dirty =)
-complete_countries = mrio_results_with_adult_eq_all %>%
- group_by(year, iso2) %>%
- summarise(co2_kg = sum(co2_kg)) %>%
- ungroup() %>%
- filter(co2_kg>0) %>%
- select(iso2, year, co2_kg) %>%
- pivot_wider(id_cols = c(iso2), names_from = year, values_from = co2_kg) %>%
- drop_na() %>%
- select(iso2) %>%
- pull()
-
-hh_data %>%
- filter(iso2 %in% complete_countries, year<=2015, year>=2005) %>%
-ggplot(aes(x=year, y=hh*0.000001)) +
- geom_line() +
- geom_point(data=hh_data %>%
- filter(iso2 %in% complete_countries,
- year<=2015,
- year>=2005,
- imputed), color="red") +
- theme_ipsum() +
- scale_x_continuous(labels = scales::label_number(accuracy = 1, big.mark = "")) +
- labs(x="", y="Total number of households (mio)") +
- facet_wrap(~iso3, scales="free_y", ncol = 4) +
- theme(legend.position = "bottom",
- axis.text.x = element_text(angle = 90))
-
-#ggsave(here("figures", "household_size.png"), plot = p, width = 8, height = 14)
-
-pal <- wes_palette("Cavalcanti1", 5, type = "discrete")
-pal = pal[c(1,2,5)]
-
-df_adult_e_p_hh %>%
- filter(iso2 %in% complete_countries, year<=2015, year>=2005) %>%
- mutate(quint = parse_number(quintile)) %>%
- ggplot(aes(x=quint, y=adult_e_p_hh, color=factor(year))) +
- geom_line(alpha=0.5) +
- theme_ipsum() +
- scale_color_manual(name = "Year", values = pal) +
- labs(x="", y="Adult equivivalents per household") +
- facet_wrap(~iso3, ncol = 4) +
- theme(legend.position = "bottom",
- axis.text.x = element_text(angle = 90))
-
-#ggsave(here("figures", "adult_eq_per_household.png"), plot = p, width = 8, height = 14)
-
-df_adult_e_p_hh %>%
- filter(iso2 %in% complete_countries, year<=2015, year>=2005) %>%
- mutate(quint = parse_number(quintile)) %>%
- write_csv(here("data", "adult_eq_per_household.csv"))
-
-# calculate EU expenditure tiles based on loaded mrio result file and adult equivalents.
-# returns country quintiles mapped to EU ntile rank and EU ntile boundaries
-# helper function called by function below
-calculate_eu_ntiles <- function(pyear, pquantile_count=10) {
-
- country_data_annual_sorted = summary_country_fd %>%
- ungroup() %>%
- filter(year==pyear) %>%
- arrange(fd_pae_e) %>%
- mutate(idx = 1:n(),
- eu_q_rank = 0) # later to be filled with euro quintile rank
-
- # total EU adult equivalents (of included countries) in year
- total_ae_in_year = sum(country_data_annual_sorted$ae_quintile)
-
- # quantile target ae population
- eu_decile_adult_eq = total_ae_in_year/pquantile_count
-
- # country quinitles must be split to allocate ae population accorting to eu quantile target ae population
- # filtering by condition that cant be fulfilled is a lazy way to create an empty dataframe
- # of the same structure as country_data_annual_sorted
- additional_rows = country_data_annual_sorted %>%
- filter(year==1)
-
- # store quantile split values
- eu_quantile_boundaries = data.frame(euro_q_rank = 1:pquantile_count, p = 0)
-
- ## can't think of a non-loop way to do this, sorry
- ## loops through the ordered dataset, assignes euro quantile rank
- ## and splits quintiles where necessary
- eu_ae_current = 0
- euro_q_rank_current = 1
- for (row_idx in 1:nrow(country_data_annual_sorted)) {
- row = country_data_annual_sorted[row_idx,]
- if (row["ae_quintile"] + eu_ae_current <= eu_decile_adult_eq) {
- eu_ae_current = eu_ae_current + row["ae_quintile"]
- country_data_annual_sorted[row_idx, "eu_q_rank"] = euro_q_rank_current
- } else {
- ae_diff = eu_decile_adult_eq - eu_ae_current
- ## write rest of this eu decile (split country quintile)
- new_row = country_data_annual_sorted[row_idx, ]
- new_row[1, "eu_q_rank"] = euro_q_rank_current
- new_row[1, "ae_quintile"] = ae_diff
- ## record eu quantile boundary
- eu_quantile_boundaries[eu_quantile_boundaries$euro_q_rank==euro_q_rank_current, "p"] =
- country_data_annual_sorted[row_idx, "fd_pae_e"]
- ## put first part of population in overflow dataframe
- additional_rows = additional_rows %>%
- bind_rows(new_row)
- ## classify rest of country quinitle population to next euro quantile
- country_data_annual_sorted[row_idx, "ae_quintile"] =
- country_data_annual_sorted[row_idx, "ae_quintile"] - (ae_diff+0.0001)
- euro_q_rank_current = euro_q_rank_current + 1
- country_data_annual_sorted[row_idx, "eu_q_rank"] = euro_q_rank_current
- eu_ae_current = country_data_annual_sorted[row_idx, "ae_quintile"]
-
- }
- }
-
- country_data_eu_quantiles = country_data_annual_sorted %>%
- bind_rows(additional_rows) %>%
- arrange(fd_pae_e, eu_q_rank) %>%
- mutate(idx = 1:n())
-
- #ad zeroth and nth quantile (min and max)
- eu_quantile_boundaries[pquantile_count, "p"] = max(country_data_eu_quantiles$fd_pae_e)
- #tmp = data.frame(euro_q_rank = 0, p = min(country_data_eu_quantiles$fd_pae_e)) %>%
- # bind_rows(eu_quantile_boundaries)
-
-
- list("df_q_data" = country_data_eu_quantiles, "df_q_boundaries" = eu_quantile_boundaries)
-}
-
-# maps MRIO results to EU ntile ranks, returns mapping and ntile EU boundaries
-map_mrio_results_to_eu_ntiles <- function(pyear, ptarget_ntiles) {
-
- df_eu_ntiles = calculate_eu_ntiles(pyear, pquantile_count = ptarget_ntiles)
- df_eu_ntiles_data = df_eu_ntiles$df_q_data
- #df_eu_ntiles_p = df_eu_ntiles$df_q_boundaries
-
- sector_mapping = mrio_results_with_adult_eq %>%
- group_by(coicop) %>%#
- summarise(coicop = first(coicop)) %>%
- ungroup()
-
- df_mapped_data = mrio_results_with_adult_eq %>%
- select(year,
- iso2,
- quint,
- coicop,
- fd_me,
- co2_kg,
- co2_domestic_kg,
- co2_europe_kg,
- co2eq_kg,
- co2eq_domestic_kg,
- co2eq_europe_kg,
- energy_use_tj,
- energy_use_domestic_tj,
- energy_use_europe_tj,
- ae_quintile) %>%
- filter(year==pyear) %>%
- # calc per adult aequivalent values in quintiles
- mutate(fd_pae_e = fd_me*1000000/ae_quintile,
- co2_pae_kg = co2_kg/ae_quintile,
- co2_pae_dom_kg = co2_domestic_kg/ae_quintile,
- co2_pae_eu_kg = co2_europe_kg/ae_quintile,
- co2eq_pae_kg = co2eq_kg/ae_quintile,
- co2eq_pae_dom_kg = co2eq_domestic_kg/ae_quintile,
- co2eq_pae_eu_kg = co2eq_europe_kg/ae_quintile,
- energy_use_pae_tj = energy_use_tj/ae_quintile,
- energy_use_dom_pae_tj = energy_use_domestic_tj/ae_quintile,
- energy_use_eu_pae_tj = energy_use_europe_tj/ae_quintile) %>%
- # remove totals
- select(-c(fd_me,
- co2_kg,
- co2_domestic_kg,
- co2_europe_kg,
- co2eq_kg,
- co2eq_domestic_kg,
- co2eq_europe_kg,
- energy_use_tj,
- energy_use_domestic_tj,
- energy_use_europe_tj,
- year, ae_quintile)) %>%
- full_join(df_eu_ntiles_data %>%
- rename(fd_pae_e_quint_tmp = fd_pae_e), by=c("iso2", "quint")) %>%
- rename(adult_eq = ae_quintile) %>% # country quintile and their split fraction population
- # recalc totals
- mutate(fd_me = fd_pae_e*adult_eq/1000000,
- co2_kg = co2_pae_kg*adult_eq,
- co2_dom_kg = co2_pae_dom_kg*adult_eq,
- co2_eu_kg = co2_pae_eu_kg*adult_eq,
- co2eq_kg = co2eq_pae_kg*adult_eq,
- co2eq_dom_kg = co2eq_pae_dom_kg*adult_eq,
- co2eq_eu_kg = co2eq_pae_eu_kg*adult_eq,
- energy_use_tj = energy_use_pae_tj*adult_eq,
- energy_use_dom_tj = energy_use_dom_pae_tj*adult_eq,
- energy_use_eu_tj = energy_use_eu_pae_tj*adult_eq
- ) #%>%
- #left_join(sector_mapping, by="sector_id")
-
- list("df_mapped_data" = df_mapped_data, "df_ntile_boundaries" = df_eu_ntiles$df_q_boundaries)
-
-}
-
-### Filter only countries with complete info for years 2005, 2010, 2015
-mrio_results_with_adult_eq = mrio_results_with_adult_eq_all %>%
- filter(iso2 %in% complete_countries)
-
-## summarize final demand per adult equvalent per quintile across all sectors as basis for eurodeciles for complete countries
-summary_country_fd = mrio_results_with_adult_eq %>%
- group_by(iso2, year, quint) %>%
- summarise(ae_quintile = first(ae_quintile),
- fd_pae_e = sum(fd_me*1000000)/(ae_quintile))
-
-## summarize final demand per adult equvalent per quintile across all sectors as basis for eurodeciles for all countries
-summary_country_fd_all = mrio_results_with_adult_eq_all %>%
- group_by(iso2, year, quint) %>%
- summarise(ae_quintile = first(ae_quintile),
- fd_pae_e = sum(fd_me*1000000)/(ae_quintile))
-
-df_mapped_result_2005 = map_mrio_results_to_eu_ntiles(2005, target_eu_ntiles)
-df_mapped_result_2005_data = df_mapped_result_2005$df_mapped_data
-df_mapped_result_2005_ntiles = df_mapped_result_2005$df_ntile_boundaries
-
-df_mapped_result_2010 = map_mrio_results_to_eu_ntiles(2010, target_eu_ntiles)
-df_mapped_result_2010_data = df_mapped_result_2010$df_mapped_data
-df_mapped_result_2010_ntiles = df_mapped_result_2010$df_ntile_boundaries
-
-df_mapped_result_2015 = map_mrio_results_to_eu_ntiles(2015, target_eu_ntiles)
-df_mapped_result_2015_data = df_mapped_result_2015$df_mapped_data
-df_mapped_result_2015_ntiles = df_mapped_result_2015$df_ntile_boundaries
-
-df_mapped_result_data = df_mapped_result_2005_data %>%
- bind_rows(df_mapped_result_2010_data) %>%
- bind_rows(df_mapped_result_2015_data)
-
-write_csv(df_mapped_result_data,
- here(paste0("data/mrio_results_eu_ntile_mapped_n_", target_eu_ntiles, "_method2_ixi.csv")))
-
-df_mapped_result_ntiles =
- df_mapped_result_2005_ntiles %>% mutate(year=2005) %>%
- bind_rows(df_mapped_result_2010_ntiles %>% mutate(year=2010)) %>%
- bind_rows(df_mapped_result_2015_ntiles %>% mutate(year=2015))
-
-write_csv(df_mapped_result_ntiles,
- here(paste0("data/eu_ntiles_n_", target_eu_ntiles, "_method2_ixi.csv")))</code></pre>
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