Skip to content
Snippets Groups Projects
Commit 43d7954b authored by Marianna Rottoli's avatar Marianna Rottoli
Browse files

Reporting EDGE-T compare scenarios adjusted to regional aggregation and cleaned.

parent 418128d7
No related branches found
No related tags found
1 merge request!300Updated cache; reporting adapted to regional EDGE-T.
Expand all Hide whitespace changes
Inline Side-by-side
scripts/output/comparison/EDGEcomparison.R
+ 88
− 513
View file @ 43d7954b
This diff is collapsed.
scripts/output/comparison/notebook_templates/EDGETransportComparison.Rmd
+ 87
− 45
View file @ 43d7954b
......@@ -36,15 +36,13 @@ EJroad_all = readRDS("EJroad_all.RDS")
fleet_all = readRDS("fleet_all.RDS")
salescomp_all = readRDS("salescomp_all.RDS")
ESmodecap_all = readRDS("ESmodecap_all.RDS")
CO2km_int_newsales_all = readRDS("CO2km_int_newsales_all.RDS")
EJpass_all = readRDS("EJfuelsPass_all.RDS")
EJfrgt_all = readRDS("EJfuelsFrgt_all.RDS")
EJModeFuel_all = readRDS("EJModeFuel_all.RDS")
emidem_all = readRDS("emidem_all.RDS")
elecdem_all = readRDS("elecdem_all.RDS")
costs_all = readRDS("costs_all.RDS")
pref_FV_all = readRDS("pref_FV_all.RDS")
dempkm_cap_all = readRDS("demgdpcap_all.RDS")
setConfig(forcecache=T)
cols <- c("NG" = "#d11141",
......@@ -110,26 +108,28 @@ cols <- c("NG" = "#d11141",
"FE|Transport" = "#1e90ff",
"FE|Buildings" = "#d2b48c",
"FE|Industry" = "#919191",
"ElecEra" = "#00b159",
"ElecEraWise" = "#68c6a4",
"HydrHype" = "#00aedb",
"HydrHypeWise" = "#o3878f",
"ConvCase" = "#113245",
"ConvCaseWise" = "#d11141",
"NDC" = "#d11141",
"NPi_IC" = "#f6ab6c",
"Budg_BE" = "#00b159",
"Budg_IC" = "#113245",
"Budg_ICsyn" = "orchid",
"Budg_FC" = "#00aedb",
"Budg_BE-LS" = "#68c6a4",
"Budg_IC-LS" = "#d11141",
"SynSurge" = "orchid")
"LDVs Electricity" = "#00b159",
"Bus+Rail Electricity" = "#7cfc00",
"Road+Rail freight Electricity" = "#68c6a4",
"LDVs Hydrogen" = "#00aedb",
"Bus+Rail Hydrogen" = "#00bfff",
"Road+Rail freight Hydrogen" = "#035aa6",
"Domestic Aviation Hydrogen" = "#a5d7f1",
"LDVs Hydrocarbons" = "#8c8c8c",
"Bus+Rail Hydrocarbons" = "#b2b2b2",
"Road+Rail freight Hydrocarbons" = "#787f77",
"Domestic Aviation Hydrocarbons" = "#d7d7d7",
"Domestic Shipping Hydrocarbons" = "#978888",
"International Aviation Hydrocarbons" = "#474847",
"International Shipping Hydrocarbons" = "#53515b")
legend_ord_modes <- c("Freight Rail", "Truck", "Shipping", "International Shipping", "Domestic Shipping", "Trucks",
"Motorbikes", "Small Cars", "Large Cars", "Van",
"International Aviation", "Domestic Aviation","Bus", "Passenger Rail",
"Freight", "LDV", "Pass non LDV", "Freight (Inland)", "Pass non LDV (Domestic)", "Non motorized")
legend_ord_modes_fuel <- c("LDVs Electricity", "Bus+Rail Electricity", "Road+Rail freight Electricity",
"LDVs Hydrogen", "Bus+Rail Hydrogen", "Road+Rail freight Hydrogen", "Domestic Aviation Hydrogen",
"LDVs Hydrocarbons", "Bus+Rail Hydrocarbons", "Road+Rail freight Hydrocarbons", "Domestic Aviation Hydrocarbons", "Domestic Shipping Hydrocarbons", "International Aviation Hydrocarbons", "International Shipping Hydrocarbons")
legend_ord_fuels <- c("BEV", "Electricity", "Hybrid Electric", "FCEV", "Hydrogen", "Hybrid Liquids", "Liquids", "Oil", "Biodiesel", "Synfuel", "Synfuels", "Gases","NG")
......@@ -137,7 +137,7 @@ legend_ord_costs <- c("Inconvenience", "Risk", "Charging", "Model availability",
legend_ord_emissions <- c("Emi|CO2|Industry|Gross", "Emi|CO2|Buildings|Direct", "Emi|CO2|Transport|Demand", "Emi|CO2|Energy|Supply|Gross", "Emi|CO2|Land-Use Change","Emi|CO2|CDR|BECCS")
legend_ord = c(legend_ord_modes, legend_ord_fuels, legend_ord_costs)
legend_ord = c(legend_ord_modes, legend_ord_fuels, legend_ord_costs, legend_ord_modes_fuel)
regionplot = "EUR"
......@@ -168,7 +168,7 @@ vintcomparisonpf = function(dt){
aes(x=scenario, y=value, group=interaction(variable, technology),
fill = technology, alpha = factor(alphaval), width=.75), position="stack", stat = "identity", width = 0.5, color = "black", size=0.05)+
guides(fill = guide_legend(reverse=TRUE))+
facet_grid(year~region) +
facet_grid(year~region, scales = "free") +
theme2use +
scale_alpha_discrete(breaks = c(1,0), name = "Status", labels = c("Vintages","New additions")) +
guides(linetype=FALSE,
......@@ -293,33 +293,54 @@ ESmodecappf = function(dt, rp){
p = ESmodecappf(ESmodecap_all)
```
## CO2 intensity of new sales
## Final energy, by fuel
```{r, echo=FALSE, message=FALSE, warning=FALSE, fig.width=14, fig.height=12}
## all modes by fuel and mode
EJfuelsMod_pf = function(dt_all){
dt_all = dt_all[year>=2020]
dt_all[veh %in% c("Small Cars", "Large Cars", "Motorbikes"), veh := "LDVs"]
dt_all[veh %in% c("Bus", "Passenger Rail"), veh := "Bus+Rail"]
dt_all[veh %in% c("Truck", "Freight Rail"), veh := "Road+Rail freight"]
dt_all[technology %in% c("NG", "Liquids"), technology := "Hydrocarbons"]
dt_all[technology %in% c("BEV", "Electric"), technology := "Electricity"]
dt_all[technology %in% c("FCEV"), technology := "Hydrogen"]
dt_all = dt_all[, techmode := paste0(veh, " ", technology)]
dt_all[, techmode := factor(techmode, levels = legend_ord)]
dt_all_b = dt_all[, .(demand_EJ = sum(demand_EJ)), by = c("techmode", "year", "region", "scenario")]
dt_all_nob = dt_all[! veh %in% c("International Aviation", "International Shipping")][, .(demand_EJ = sum(demand_EJ)), by = c("techmode", "year", "region", "scenario")]
plot_b_lo = ggplot()+
geom_area(data = dt_all_b, aes(x=year, y=demand_EJ, group = techmode, fill = techmode), color="black", size=0.05, position= position_stack())+
labs(x = "", y = "[EJ]", title = "All transport demand by fuel")+
facet_grid(scenario~region, scales = "free")+
scale_fill_manual("Transport mode",values = cols, breaks = legend_ord)+
expand_limits(y = c(0,1))+
scale_x_continuous(breaks = c(2020, 2030,2050, 2100)) +
theme2use
CO2km_int_newsalespf = function(dt){
dt = dt[!is.na(gCO2_km_ave)]
plot = ggplot()+
geom_line(data = dt[year >= 2020], aes(x = year, y = gCO2_km_ave, group = scenario, color = scenario))+
labs(title = expression(paste(CO["2"], " intensity of LDVs new additions")), y = expression(paste("[", gCO["2"], "/km]")), x = "")+
plot_nb_lo = ggplot()+
geom_area(data = dt_all_nob, aes(x=year, y=demand_EJ, group = techmode, fill = techmode), color="black", size=0.05, position= position_stack())+
labs(x = "", y = "[EJ]", title = "All transport demand by fuel, no bunkers")+
facet_grid(scenario~region, scales = "free")+
scale_fill_manual("Transport mode",values = cols, breaks = legend_ord)+
expand_limits(y = c(0,1))+
scale_x_continuous(breaks = c(2020, 2030, 2050, 2100))+
facet_grid(~region)+
guides(linetype = FALSE) +
scale_x_continuous(breaks = c(2020, 2030,2050, 2100)) +
theme2use
plot = list(plot_b_lo = plot_b_lo, plot_nb_lo = plot_nb_lo)
return(plot)
}
CO2km_int_newsalespf(CO2km_int_newsales_all)
EJfuelsMod_pf(dt_all = EJModeFuel_all)
```
## Final energy, by fuel
```{r, echo=FALSE, message=FALSE, warning=FALSE, fig.width=14, fig.height=12}
## passenger by fuel
## by fuel, transport aggregated
EJfuels_pf = function(dt_p, dt_f){
dt_p = dt_p[year >= 2020]
dt_p = dt_p[, .(demand_EJ = sum(demand_EJ)), by = c("subtech", "year", "region", "scenario")]
dt_p = dt_p[, .(demand_EJ = sum(demand_EJ)), by = c("subtech", "year", "region", "scenario", "sector")]
plotp = ggplot()+
geom_area(data = dt_p, aes(x=year, y=demand_EJ, group = subtech, fill = subtech), color="black", size=0.05, position= position_stack())+
labs(x = "", y = "[EJ]", title = "Passenger transport FE demand by fuel")+
......@@ -330,7 +351,7 @@ EJfuels_pf = function(dt_p, dt_f){
theme2use
dt_f = dt_f[year >= 2020]
dt_f = dt_f[, .(demand_EJ = sum(demand_EJ)), by = c("subtech", "year", "region", "scenario", "sector")]
plotf_lo = ggplot()+
geom_area(data = dt_f[sector == "trn_shipping_intl"], aes(x=year, y=demand_EJ, group = subtech, fill = subtech), color="black", size=0.05, position= position_stack())+
labs(x = "", y = "[EJ]", title = "International freight FE demand by fuel")+
......@@ -348,8 +369,29 @@ EJfuels_pf = function(dt_p, dt_f){
expand_limits(y = c(0,1))+
scale_x_continuous(breaks = c(2020, 2030,2050, 2100)) +
theme2use
dt_all = rbind(dt_f, dt_p)
dt_all_b = dt_all[, .(demand_EJ = sum(demand_EJ)), by = c("subtech", "year", "region", "scenario")]
plot_all = ggplot()+
geom_area(data = dt_all_b, aes(x=year, y=demand_EJ, group = subtech, fill = subtech), color="black", size=0.05, position= position_stack())+
labs(x = "", y = "[EJ]", title = "FE demand by fuel, all transport modes")+
facet_grid(scenario~region)+
scale_fill_manual("Technology",values = cols, breaks=legend_ord)+
expand_limits(y = c(0,1))+
scale_x_continuous(breaks = c(2020, 2030,2050, 2100)) +
theme2use
dt_all_nob = dt_all[sector %in% c("trn_pass", "trn_freight")][, .(demand_EJ = sum(demand_EJ)), by = c("subtech", "year", "region", "scenario")]
plot_all_nobunkers = ggplot()+
geom_area(data = dt_all_nob, aes(x=year, y=demand_EJ, group = subtech, fill = subtech), color="black", size=0.05, position= position_stack())+
labs(x = "", y = "[EJ]", title = "FE demand by fuel, all transport modes")+
facet_grid(scenario~region)+
scale_fill_manual("Technology",values = cols, breaks=legend_ord)+
expand_limits(y = c(0,1))+
scale_x_continuous(breaks = c(2020, 2030,2050, 2100)) +
theme2use
plot = list(plotf_lo = plotf_lo, plotf_sm = plotf_sm, plotp = plotp)
plot = list(plotf_lo = plotf_lo, plotf_sm = plotf_sm, plotp = plotp, plot_all = plot_all, plot_all_nobunkers = plot_all_nobunkers)
return(plot)
}
......@@ -378,10 +420,10 @@ emidem_pf(emidem_all)
demcapgdpcap_pf = function(dt) {
dt = dt[year >= 2005]
dt = dt[, year := as.character(year)]
dtsec = unique(dt[, c("region", "year", "demsec", "sector", "gdpcap", "scenario")])
dtsec = unique(dt[, c("region", "year", "demsec", "sector", "GDP_cap", "scenario")])
psec = ggplot()+
geom_line(data = dtsec, aes(x = gdpcap, y = demsec, color = region, group = interaction(region, scenario), linetype = scenario))+
geom_point(data = dtsec[year %in% c("2020", "2030", "2050", "2070", "2100")], aes(x = gdpcap, y = demsec, shape = year, group = interaction("region", "scenario"), color = region))+
geom_line(data = dtsec, aes(x = GDP_cap, y = demsec, color = region, group = interaction(region, scenario), linetype = scenario))+
geom_point(data = dtsec[year %in% c("2020", "2030", "2050", "2070", "2100")], aes(x = GDP_cap, y = demsec, shape = year, group = interaction("region", "scenario"), color = region))+
facet_wrap(~sector, scales = "free") +
theme2use +
theme(axis.text.x = element_text(angle = 90, hjust = 1),
......@@ -392,10 +434,10 @@ psec = ggplot()+
dtappl = unique(dt[, c("region", "year", "demappl", "appl", "gdpcap", "scenario")])
dtappl = unique(dt[, c("region", "year", "demappl", "appl", "GDP_cap", "scenario")])
pappl = ggplot()+
geom_line(data = dtappl, aes(x = gdpcap, y = demappl, color = region, group = interaction(region, scenario), linetype = scenario))+
geom_point(data = dtappl[year %in% c("2020", "2030", "2050", "2070", "2100")], aes(x = gdpcap, y = demappl, shape = year, group = region, color = region))+
geom_line(data = dtappl, aes(x = GDP_cap, y = demappl, color = region, group = interaction(region, scenario), linetype = scenario))+
geom_point(data = dtappl[year %in% c("2020", "2030", "2050", "2070", "2100")], aes(x = GDP_cap, y = demappl, shape = year, group = region, color = region))+
facet_wrap(~appl, scales = "free") +
theme2use +
theme(axis.text.x = element_text(angle = 90, hjust = 1),
......@@ -405,10 +447,10 @@ pappl = ggplot()+
labs(y = "Per capita demand [km/capita]", x="GDP per capita [$/person]")
dttype = unique(dt[, c("region", "year", "demtype", "type", "gdpcap", "scenario")])
dttype = unique(dt[, c("region", "year", "demtype", "type", "GDP_cap", "scenario")])
ptype = ggplot()+
geom_line(data = dttype, aes(x = gdpcap, y = demtype, color = region, group = interaction(region, scenario), linetype = scenario))+
geom_point(data = dttype[year %in% c("2020", "2030", "2050", "2070", "2100")], aes(x = gdpcap, y = demtype, shape = year, group = region, color = region))+
geom_line(data = dttype, aes(x = GDP_cap, y = demtype, color = region, group = interaction(region, scenario), linetype = scenario))+
geom_point(data = dttype[year %in% c("2020", "2030", "2050", "2070", "2100")], aes(x = GDP_cap, y = demtype, shape = year, group = region, color = region))+
facet_wrap(~type, scales = "free") +
theme2use +
theme(axis.text.x = element_text(angle = 90, hjust = 1),
......
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment