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Commit 63c406ac authored by Marianna Rottoli's avatar Marianna Rottoli
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Reporting script updates and small bugfixes.

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scripts/output/single/notebook_templates/EDGETransportReport.Rmd
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View file @ 63c406ac
...@@ -18,7 +18,10 @@ require(magclass) ...@@ -18,7 +18,10 @@ require(magclass)
require(quitte) require(quitte)
require(ggpubr) require(ggpubr)
require(gridExtra) require(gridExtra)
require(edgeTrpLib) #require(edgeTrpLib)
require(devtools)
load_all("../../../../../../edgetrplib/")
``` ```
...@@ -52,10 +55,11 @@ demand_ej <- readRDS(datapath(fname = "demandF_plot_EJ.RDS")) ## detailed final ...@@ -52,10 +55,11 @@ demand_ej <- readRDS(datapath(fname = "demandF_plot_EJ.RDS")) ## detailed final
vintcomp <- readRDS(datapath(fname = "vintcomp.RDS")) vintcomp <- readRDS(datapath(fname = "vintcomp.RDS"))
newcomp <- readRDS(datapath(fname = "newcomp.RDS")) newcomp <- readRDS(datapath(fname = "newcomp.RDS"))
shares <- readRDS(datapath(fname = "shares.RDS")) shares <- readRDS(datapath(fname = "shares.RDS"))
inco_tech <- readRDS(datapath(fname = "inco_costs.RDS")) pref <- readRDS(datapath(fname = "pref.RDS"))
EF_shares <- readRDS(datapath(fname = "EF_shares.RDS")) EF_shares <- readRDS(datapath(fname = "EF_shares.RDS"))
annual_sales <- readRDS(datapath(fname = "annual_sales.RDS")) annual_sales <- readRDS(datapath(fname = "annual_sales.RDS"))
mj_km_data <- readRDS(datapath(fname = "mj_km_data.RDS")) mj_km_data <- readRDS(datapath(fname = "mj_km_data.RDS"))
stations <- readRDS(datapath(fname = "stations.RDS"))
name_mif = list.files(pattern = "REMIND_generic", full.names = F) name_mif = list.files(pattern = "REMIND_generic", full.names = F)
name_mif = name_mif[!grepl("withoutPlu", name_mif)] name_mif = name_mif[!grepl("withoutPlu", name_mif)]
...@@ -122,22 +126,47 @@ p ...@@ -122,22 +126,47 @@ p
```{r, echo=FALSE, warning=FALSE} ```{r, echo=FALSE, warning=FALSE}
p=ggplot()+ plotinconv = function(inco_tech, iso_plot, vehicle_type){
geom_bar(data = inco_tech[iso == iso_plot & subsector_L1 == "trn_pass_road_LDV_4W" & vehicle_type == "Large Car and SUV" & year<=2100 & year>=2010], aes(x = as.character(year), y = pinco, group = technology, fill = technology), position = position_stack(), stat = "identity")+ p=ggplot()+
geom_bar(data = inco_tech[iso == iso_plot & subsector_L1 == "trn_pass_road_LDV_4W" & vehicle_type == vehicle_type & year<=2100 & year>=2010], aes(x = as.character(year), y = value, group = logit_type, fill = logit_type), position = position_stack(), stat = "identity")+
facet_grid(~technology)+ facet_grid(~technology)+
theme_minimal()+ theme_minimal()+
scale_fill_manual(values = cols)+ # scale_fill_manual(values = cols)+
expand_limits(y = c(0,0.8))+ expand_limits(y = c(0,0.8))+
scale_x_discrete(breaks = c(2015,2050,2100))+ scale_x_discrete(breaks = c(2015,2050,2100))+
theme(axis.text.x = element_text(angle = 90, vjust = +0.1), theme(axis.text.x = element_text(angle = 90, vjust = +0.1),
legend.position = "none",
strip.background = element_rect(color = "grey"))+ strip.background = element_rect(color = "grey"))+
labs(x = "", y = "Inconvenience cost [$/pkm]", title = paste0("Example of ", iso_plot)) labs(x = "", y = "Inconvenience cost [$/pkm]", title = paste0("Example of ", iso_plot))
p return(p)
}
plotinconv(inco_tech = pref$FV_final_pref[subsector_L1 == "trn_pass_road_LDV_4W"], iso_plot = "DEU", vehicle_type = "Large Car and SUV")
plotinconv(inco_tech = pref$FV_final_pref[subsector_L1 == "trn_pass_road_LDV_4W"], iso_plot = "USA", vehicle_type = "Large Car")
plotinconv(inco_tech = pref$FV_final_pref[subsector_L1 == "trn_pass_road_LDV_4W"], iso_plot = "JPN", vehicle_type = "Large Car")
plotinconv(inco_tech = pref$FV_final_pref[subsector_L1 == "trn_pass_road_LDV_4W"], iso_plot = "CHN", vehicle_type = "Large Car")
plotinconv(inco_tech = pref$FV_final_pref[subsector_L1 == "trn_pass_road_LDV_4W"], iso_plot = "IND", vehicle_type = "Large Car")
``` ```
# Share of stations
```{r, echo=FALSE, warning=FALSE}
stationsplot = function(stations, iso_plot){
p = ggplot()+
geom_line(data = stations[iso == iso_plot], aes(x= year, y = fracst))+
facet_grid(~technology)+
theme_minimal()+
labs(title = paste0("Stations for each fuel, ", iso_plot))
return(p)
}
stationsplot(stations, iso_plot)
```
# Endogenous intensity for Liquids # Endogenous intensity for Liquids
```{r, echo=FALSE, message=FALSE, warning=FALSE} ```{r, echo=FALSE, message=FALSE, warning=FALSE}
...@@ -181,11 +210,11 @@ salesplot = function(annual_sales){ ...@@ -181,11 +210,11 @@ salesplot = function(annual_sales){
annual_sales <- annual_sales[,.(shareFS1=sum(shareFS1)),by=c("iso","technology","year")] annual_sales <- annual_sales[,.(shareFS1=sum(shareFS1)),by=c("iso","technology","year")]
p = ggplot()+ p = ggplot()+
geom_bar(data = annual_sales[year<=2050 & year>=2015 & iso == iso_plot], aes(x=as.numeric(as.character(year)),y=shareFS1, group = technology, fill = technology), position = position_stack(), stat = "identity")+ geom_bar(data = annual_sales[year <= 2100 & year >= 2020 & iso == iso_plot], aes(x=as.numeric(as.character(year)),y=shareFS1, group = technology, fill = technology), position = position_stack(), stat = "identity")+
theme_minimal()+ theme_minimal()+
scale_fill_manual("Technology", values = cols)+ scale_fill_manual("Technology", values = cols)+
expand_limits(y = c(0,1))+ expand_limits(y = c(0,1))+
scale_x_continuous(breaks = c(2015,2030,2050))+ scale_x_continuous(breaks = c(2020, 2030, 2050, 2100))+
theme(axis.text.x = element_text(angle = 90, vjust = +0.1), theme(axis.text.x = element_text(angle = 90, vjust = +0.1),
strip.background = element_rect(color = "grey"), strip.background = element_rect(color = "grey"),
legend.position = "none")+ legend.position = "none")+
...@@ -210,13 +239,11 @@ demandEJplotf = function(demandEJ){ ...@@ -210,13 +239,11 @@ demandEJplotf = function(demandEJ){
demandEJ[, aggr_mode := ifelse(subsector_L3 %in% c("Passenger Rail", "HSR", "International Aviation", "Domestic Aviation"), "Pass non LDV", aggr_mode)] demandEJ[, aggr_mode := ifelse(subsector_L3 %in% c("Passenger Rail", "HSR", "International Aviation", "Domestic Aviation"), "Pass non LDV", aggr_mode)]
demandEJ[, aggr_mode := ifelse(subsector_L2 %in% c("trn_pass_road_bus", "Bus"), "Pass non LDV", aggr_mode)] demandEJ[, aggr_mode := ifelse(subsector_L2 %in% c("trn_pass_road_bus", "Bus"), "Pass non LDV", aggr_mode)]
demandEJ[, aggr_mode := ifelse(is.na(aggr_mode), "Freight", aggr_mode)] demandEJ[, aggr_mode := ifelse(is.na(aggr_mode), "Freight", aggr_mode)]
demandEJ[, veh := ifelse(vehicle_type %in% c("Truck (0-1t)", "Truck (0-3.5t)", "Truck (0-2.7t)", "Truck (0-2t)"), "Trucks (<3.5t)", NA)] demandEJ[, veh := ifelse(grepl("Large|SUV|Midsize|Multipurpose Vehicle|Van|3W Rural", vehicle_type), "Large Cars", NA)]
demandEJ[, veh := ifelse(vehicle_type %in% c("Truck (16-32t)", "Truck (3.5-16t)", "Truck (6-15t)", "Truck (4.5-12t)", "Truck (2.7-4.5t)", "Truck (4.5-15t)"), "Trucks (3.5t-16)", veh)]
demandEJ[, veh := ifelse(vehicle_type %in% c("Truck (>15t)", "Truck (16-32t)", "Truck (>32t)" ), "Trucks (>16)", veh)]
demandEJ[, veh := ifelse(grepl("Large|SUV|Midsize|Multipurpose Vehicle|Van|3W Rural", vehicle_type), "Large Cars", veh)]
demandEJ[, veh := ifelse(grepl("Subcompact|Compact|Mini|Three-Wheeler", vehicle_type), "Small Cars", veh)] demandEJ[, veh := ifelse(grepl("Subcompact|Compact|Mini|Three-Wheeler", vehicle_type), "Small Cars", veh)]
demandEJ[, veh := ifelse(grepl("Motorcycle|Moped|Scooter", vehicle_type), "Motorbikes", veh)] demandEJ[, veh := ifelse(grepl("Motorcycle|Moped|Scooter", vehicle_type), "Motorbikes", veh)]
demandEJ[, veh := ifelse(grepl("bus|Bus", vehicle_type), "Bus", veh)] demandEJ[, veh := ifelse(grepl("bus|Bus", vehicle_type), "Bus", veh)]
demandEJ[, veh := ifelse(grepl("Truck", vehicle_type) & vehicle_type != "Light Truck and SUV", "Truck", veh)]
demandEJ[, veh := ifelse(grepl("Freight Rail_tmp_vehicletype", vehicle_type), "Freight Rail", veh)] demandEJ[, veh := ifelse(grepl("Freight Rail_tmp_vehicletype", vehicle_type), "Freight Rail", veh)]
demandEJ[, veh := ifelse(grepl("Passenger Rail|HSR", vehicle_type), "Passenger Rail", veh)] demandEJ[, veh := ifelse(grepl("Passenger Rail|HSR", vehicle_type), "Passenger Rail", veh)]
demandEJ[, veh := ifelse(subsector_L3 == "Domestic Ship", "Domestic Shipping", veh)] demandEJ[, veh := ifelse(subsector_L3 == "Domestic Ship", "Domestic Shipping", veh)]
...@@ -226,12 +253,12 @@ demandEJplotf = function(demandEJ){ ...@@ -226,12 +253,12 @@ demandEJplotf = function(demandEJ){
demandEJ[, veh := ifelse(is.na(veh), vehicle_type, veh)] demandEJ[, veh := ifelse(is.na(veh), vehicle_type, veh)]
demandEJ = demandEJ[,.(demand_EJ = sum(demand_EJ)), by = c("iso", "year", "aggr_mode", "veh")] demandEJ = demandEJ[,.(demand_EJ = sum(demand_EJ)), by = c("iso", "year", "aggr_mode", "veh")]
demandEJ[, vehicle_type_plot := factor(veh, levels = c("LDV","Freight Rail", "Trucks (<3.5t)", "Trucks (3.5t-16)", "Truck (>12t)", "Trucks (>16)", "Trucks","Domestic Shipping", "International Shipping", demandEJ[, vehicle_type_plot := factor(veh, levels = c("LDV","Freight Rail", "Truck","Domestic Shipping", "International Shipping",
"Motorbikes", "Small Cars", "Large Cars", "Van", "Motorbikes", "Small Cars", "Large Cars", "Van",
"Domestic Aviation", "International Aviation", "Bus", "Passenger Rail", "Domestic Aviation", "International Aviation", "Bus", "Passenger Rail",
"Freight", "Freight (Inland)", "Pass non LDV", "Pass non LDV (Domestic)"))] "Freight", "Freight (Inland)", "Pass non LDV", "Pass non LDV (Domestic)"))]
legend_ord <- c("Freight Rail", "Trucks (<3.5t)", "Trucks (3.5t-16)", "Truck (>12t)", "Trucks (>16)", "International Shipping","Domestic Shipping", "Trucks", legend_ord <- c("Freight Rail", "Truck", "International Shipping","Domestic Shipping",
"Motorbikes", "Small Cars", "Large Cars", "Van", "Motorbikes", "Small Cars", "Large Cars", "Van",
"International Aviation", "Domestic Aviation","Bus", "Passenger Rail", "International Aviation", "Domestic Aviation","Bus", "Passenger Rail",
"Freight", "LDV", "Pass non LDV", "Freight (Inland)", "Pass non LDV (Domestic)") "Freight", "LDV", "Pass non LDV", "Freight (Inland)", "Pass non LDV (Domestic)")
...@@ -313,31 +340,30 @@ demandpkmplotf = function(demandpkm){ ...@@ -313,31 +340,30 @@ demandpkmplotf = function(demandpkm){
demandpkm[, aggr_mode := ifelse(sector %in% c("trn_freight", "trn_shipping_intl"), "Freight", aggr_mode)] demandpkm[, aggr_mode := ifelse(sector %in% c("trn_freight", "trn_shipping_intl"), "Freight", aggr_mode)]
demandpkm[, aggr_mode := ifelse(sector %in% c("trn_aviation_intl"), "Pass. non LDV", aggr_mode)] demandpkm[, aggr_mode := ifelse(sector %in% c("trn_aviation_intl"), "Pass. non LDV", aggr_mode)]
demandpkm[, aggr_mode := ifelse(subsector_L2 %in% c("trn_pass_road_bus", "HSR_tmp_subsector_L2", "Passenger Rail_tmp_subsector_L2", "Cycle_tmp_subsector_L2", "Walk_tmp_subsector_L2", "Domestic Aviation_tmp_subsector_L2", "Bus") | subsector_L1 %in% c("trn_pass_road_LDV_2W"), "Pass. non LDV", aggr_mode)] demandpkm[, aggr_mode := ifelse(subsector_L2 %in% c("trn_pass_road_bus", "HSR_tmp_subsector_L2", "Passenger Rail_tmp_subsector_L2", "Cycle_tmp_subsector_L2", "Walk_tmp_subsector_L2", "Domestic Aviation_tmp_subsector_L2", "Bus") | subsector_L1 %in% c("trn_pass_road_LDV_2W"), "Pass. non LDV", aggr_mode)]
demandpkm[, veh := ifelse(grepl("Large|SUV|Midsize|Multipurpose Vehicle|Van|3W Rural", vehicle_type), "Large Cars", NA)]
demandpkm[, veh := ifelse(vehicle_type %in% c("Truck (0-1t)", "Truck (0-3.5t)"), "Trucks (<3.5t)", "Trucks (<3.5t)")]
demandpkm[, veh := ifelse(vehicle_type %in% c("Truck (16-32t)", "Truck (3.5-16t)", "Truck (6-15t)"), "Trucks (3.5t-16)", veh)]
demandpkm[, veh := ifelse(vehicle_type %in% c("Truck (>15t)", "Truck (16-32t)", "Truck (>32t)" ), "Trucks (>16)", veh)]
demandpkm[, veh := ifelse(grepl("Large|SUV|Midsize|Multipurpose Vehicle|Van|3W Rural", vehicle_type), "Large Cars", veh)]
demandpkm[, veh := ifelse(grepl("Subcompact|Compact|Mini|Three-Wheeler_tmp_vehicletype", vehicle_type), "Small Cars", veh)] demandpkm[, veh := ifelse(grepl("Subcompact|Compact|Mini|Three-Wheeler_tmp_vehicletype", vehicle_type), "Small Cars", veh)]
demandpkm[, veh := ifelse(grepl("Motorcycle|Moped|Scooter", vehicle_type), "Motorbikes", veh)] demandpkm[, veh := ifelse(grepl("Motorcycle|Moped|Scooter", vehicle_type), "Motorbikes", veh)]
demandpkm[, veh := ifelse(grepl("bus|Bus", vehicle_type), "Bus", veh)] demandpkm[, veh := ifelse(grepl("bus|Bus", vehicle_type), "Bus", veh)]
demandpkm[, veh := ifelse(grepl("Truck", vehicle_type) & vehicle_type != "Light Truck and SUV", "Truck", veh)]
demandpkm[, veh := ifelse(subsector_L3 == "Domestic Aviation", "Domestic Aviation", veh)] demandpkm[, veh := ifelse(subsector_L3 == "Domestic Aviation", "Domestic Aviation", veh)]
demandpkm[, veh := ifelse(subsector_L3 == "International Aviation", "International Aviation", veh)] demandpkm[, veh := ifelse(subsector_L3 == "International Aviation", "International Aviation", veh)]
demandpkm[, veh := ifelse(grepl("Freight Rail", vehicle_type), "Freight Rail", veh)] demandpkm[, veh := ifelse(grepl("Freight Rail", vehicle_type), "Freight Rail", veh)]
demandpkm[, veh := ifelse(grepl("Passenger Rail|HSR", vehicle_type), "Passenger Rail", veh)] demandpkm[, veh := ifelse(grepl("Passenger Rail|HSR", vehicle_type), "Passenger Rail", veh)]
demandpkm[, veh := ifelse(grepl("Ship", vehicle_type), "Shipping", veh)] demandpkm[, veh := ifelse(grepl("Ship", vehicle_type), "Shipping", veh)]
demandpkm[, veh := ifelse(grepl("Cycle|Walk", subsector_L3), "Non motorized", veh)] demandpkm[, veh := ifelse(grepl("Cycle|Walk", subsector_L3), "Non motorized", veh)]
demandpkm[, veh := ifelse(is.na(veh), vehicle_type, veh)]
demandpkm = demandpkm[,.(demand_F = sum(demand_F)), by = c("iso", "year", "aggr_mode", "veh")] demandpkm = demandpkm[,.(demand_F = sum(demand_F)), by = c("iso", "year", "aggr_mode", "veh")]
setnames(demandpkm, old = "veh", new = "vehicle_type") setnames(demandpkm, old = "veh", new = "vehicle_type")
demandpkm[, vehicle_type_plot := factor(vehicle_type, levels = c("LDV","Truck",
demandpkm[, vehicle_type_plot := factor(vehicle_type, levels = c("LDV","Freight Rail", "Trucks (<3.5t)", "Trucks (3.5t-16)", "Trucks (>16)", "Trucks", "Freight Rail",
"Motorbikes", "Small Cars", "Large Cars", "Van", "Motorbikes", "Small Cars", "Large Cars", "Van",
"Domestic Aviation", "International Aviation","Bus", "Passenger Rail", "Domestic Aviation", "International Aviation","Bus", "Passenger Rail",
"Freight", "Non motorized", "Shipping"))] "Freight", "Non motorized", "Shipping"))]
demandpkm[, mode := ifelse(vehicle_type %in% c("Freight", "Freight Rail", "Trucks", "Trucks (3.5t-16)", "Trucks (>16)", "Shipping"),"freight", "pass")] demandpkm[, mode := ifelse(vehicle_type %in% c("Freight", "Freight Rail", "Truck", "Shipping"),"freight", "pass")]
demandpkm = merge(demandpkm, REMIND2ISO_MAPPING, by = "iso") demandpkm = merge(demandpkm, REMIND2ISO_MAPPING, by = "iso")
demandpkm = demandpkm[, .(demand_F = sum(demand_F)), by = c("region", "year", "vehicle_type_plot", "aggr_mode", "mode")] demandpkm = demandpkm[, .(demand_F = sum(demand_F)), by = c("region", "year", "vehicle_type_plot", "aggr_mode", "mode")]
...@@ -416,6 +442,7 @@ CO2km_intensity_newsalesplotf = function(annual_sales, mj_km_data, sharesVS1, sh ...@@ -416,6 +442,7 @@ CO2km_intensity_newsalesplotf = function(annual_sales, mj_km_data, sharesVS1, sh
totalemi = totalemi[,.(gCO2_km_ave = sum(gCO2_km_ave)), by = c("year", "iso", "vehicle_type")] totalemi = totalemi[,.(gCO2_km_ave = sum(gCO2_km_ave)), by = c("year", "iso", "vehicle_type")]
totalemi = merge(totalemi, sharesVS1, all.x = TRUE, by = c("iso", "year", "vehicle_type")) totalemi = merge(totalemi, sharesVS1, all.x = TRUE, by = c("iso", "year", "vehicle_type"))
totalemi = totalemi[year %in% unique(sharesVS1$year)]
totalemi = totalemi[,.(gCO2_km_ave = sum(gCO2_km_ave*share)), by = c("iso", "year", "subsector_L1")] totalemi = totalemi[,.(gCO2_km_ave = sum(gCO2_km_ave*share)), by = c("iso", "year", "subsector_L1")]
......
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