Flexibilization of the currency unit in accordance with mrdrivers

.buildlibrary

@@ -1,4 +1,4 @@
-ValidationKey: '1561560'
+ValidationKey: '1602080'
 AutocreateReadme: yes
 AcceptedWarnings:
 - 'Warning: package ''.*'' was built under R version'

CITATION.cff

@@ -2,8 +2,8 @@ cff-version: 1.2.0
 message: If you use this software, please cite it using the metadata from this file.
 type: software
 title: 'mrtransport: Input data generation for the EDGE-Transport model'
-version: 0.7.8
-date-released: '2024-10-24'
+version: 0.8.0
+date-released: '2024-10-30'
 abstract: The mrtransport package contains data preprocessing for the EDGE-Transport
   model.
 authors:

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: mrtransport
 Title: Input data generation for the EDGE-Transport model
-Version: 0.7.8
+Version: 0.8.0
 Authors@R: c(
     person("Johanna", "Hoppe", , "[email protected]", role = c("aut", "cre"),
            comment = c(ORCID = "0009-0004-6753-5090")),
@@ -26,4 +26,4 @@ Imports:
     magrittr,
     quitte,
     data.table
-Date: 2024-10-24
+Date: 2024-10-30

R/calcEdgeTransportSAinputs.R

@@ -8,14 +8,16 @@
 #' @importFrom madrat readSource calcOutput
 #' @importFrom magclass time_interpolate
 
-calcEdgeTransportSAinputs <- function(subtype, SSPscen = "SSP2EU", IEAharm = TRUE) { # nolint: cyclocomp_linter
+calcEdgeTransportSAinputs <- function(subtype, SSPscen = "SSP2", IEAharm = TRUE) { # nolint: cyclocomp_linter
 
   temporal <- spatial <- present <- period <- region <- technology <-
     univocalName <- gdppc <- speed <- altTech <- variable <- value <-
     regionCode12 <- multiplier <- time_interpolate <- setNames <-
     capex <- untilPrice <- untilPrice2 <- purchasePriceSubsidy <-
     purchasePriceSubsidy2 <- NULL
 
+  monUnit <- gsub(".*?(\\d{4}).*", "US$\\1", mrdrivers::toolGetUnitDollar())
+
   lowResYears <- data.table(temporal = "all", period = c(
     1990,
     seq(2005, 2060, by = 5),
@@ -171,7 +173,7 @@ calcEdgeTransportSAinputs <- function(subtype, SSPscen = "SSP2EU", IEAharm = TRU
 
     },
     "annualMileage" = {
-      unit <- "vehkm/veh/yr"
+      unit <- "vehkm/veh yr"
       description <- "Annual mileage on technology level. Sources: TRACCS, UCD"
       weight <- calcOutput("GDP", average2020 = FALSE, aggregate = FALSE) |> time_interpolate(highResYears)
       weight <- weight[, , paste0("gdp_", SSPscen)]
@@ -197,7 +199,7 @@ calcEdgeTransportSAinputs <- function(subtype, SSPscen = "SSP2EU", IEAharm = TRU
 
       # Add annual mileage of zero for active modes
       activeModes <- completeDataSet[univocalName %in% c("Cycle", "Walk")]
-      activeModes[, unit := "vehkm/veh/yr"][, variable := "Annual mileage"][, value := 0][, check := NULL]
+      activeModes[, unit := "vehkm/veh yr"][, variable := "Annual mileage"][, value := 0][, check := NULL]
       annualMileage <- rbind(annualMileage, activeModes)
 
       annualMileage <- annualMileage[, c("region", "period", "univocalName", "technology",
@@ -345,17 +347,17 @@ calcEdgeTransportSAinputs <- function(subtype, SSPscen = "SSP2EU", IEAharm = TRU
       quitteobj <- loadFactor
     },
     "CAPEXtrackedFleet" = {
-      unit <- "US$2017/veh"
+      unit <- paste0(monUnit, "/veh")
       description <- "CAPEX for vehicle types that feature fleet tracking (cars, trucks and busses).
                       Sources: UCD, PSI"
       weight <- calcOutput("GDP", average2020 = FALSE, aggregate = FALSE) |> time_interpolate(highResYears)
       weight <- weight[, , paste0("gdp_", SSPscen)]
 
       # read PSI CAPEX
       CAPEXPSI <- toolPreparePSI(readSource("PSI", "CAPEX"))
-      # read UCD CAPEX given in US$2017/vkt and US$2017/veh
+      # read UCD CAPEX given in US$/vehkm and US$/veh
       CAPEXUCD <- toolPrepareUCD(readSource("UCD", "CAPEX"), "CAPEX")
-      # For some modes UCD offers only a combined value for CAPEX and non-fuel OPEX given in US$2017/vehkm
+      # For some modes UCD offers only a combined value for CAPEX and non-fuel OPEX given in US$/vehkm
       CAPEXcombinedUCD <- toolPrepareUCD(readSource("UCD", "CAPEXandNonFuelOPEX"), "CAPEXandNonFuelOPEX")
       # Operating subsidies for Freight Rail, Passenger Rail, HSR (+ Bus not used here) are partially attributed to CAPEX
       # otherwise negative values in OPEX
@@ -385,7 +387,7 @@ calcEdgeTransportSAinputs <- function(subtype, SSPscen = "SSP2EU", IEAharm = TRU
       # PSI CAPEX for 4 Wheelers feature only purchase costs - take other capital costs from UCD for EUR regions
       CAPEXraw <- rbind(PSIpurchaseCosts, CAPEXUCD4W, CAPEXcombinedUCD, data$operatingSubsidyUCD)
 
-      GDPpcMERmag <- calcOutput("GDPpc", aggregate = FALSE, unit = "constant 2017 US$MER") |> time_interpolate(highResYears)
+      GDPpcMERmag <- calcOutput("GDPpc", aggregate = FALSE, unit = mrdrivers::toolGetUnitDollar()) |> time_interpolate(highResYears)
       GDPpcMERmag <- GDPpcMERmag[, , paste0("gdppc_", SSPscen)]
 
       GDPpcMER <- magpie2dt(GDPpcMERmag, yearcol = "period", regioncol = "region", valcol = "gdppc")[, variable := NULL]
@@ -424,15 +426,15 @@ calcEdgeTransportSAinputs <- function(subtype, SSPscen = "SSP2EU", IEAharm = TRU
       quitteobj <- CAPEX
     },
     "nonFuelOPEXtrackedFleet" = {
-      unit <- "US$2017/veh/yr"
+      unit <- paste0(monUnit, "/veh yr")
       description <- "Non-fuel OPEX on technology level for vehicle types that feature fleet tracking
                      (cars, trucks, busses). Sources: UCD, PSI"
       weight <- calcOutput("GDP", average2020 = FALSE, aggregate = FALSE) |> time_interpolate(highResYears)
       weight <- weight[, , paste0("gdp_", SSPscen)]
 
       nonFuelOPEXUCD <- toolPrepareUCD(readSource("UCD", "nonFuelOPEX"), "nonFuelOPEX")
       nonFuelOPEXUCD <- nonFuelOPEXUCD[univocalName %in% filterEntries$trn_pass_road_LDV_4W]
-      # For trucks and busses UCD offers only a combined value for CAPEX and non-fuel OPEX given in US$2017/vehkm
+      # For trucks and busses UCD offers only a combined value for CAPEX and non-fuel OPEX given in US$/vehkm
       nonFuelOPEXcombinedUCD <- toolPrepareUCD(readSource("UCD", "CAPEXandNonFuelOPEX"), "CAPEXandNonFuelOPEX")
       nonFuelOPEXcombinedUCD <- nonFuelOPEXcombinedUCD[univocalName %in% filterEntries$trn_freight_road
                                                        | univocalName == "Bus"]
@@ -483,17 +485,17 @@ calcEdgeTransportSAinputs <- function(subtype, SSPscen = "SSP2EU", IEAharm = TRU
       quitteobj <- nonFuelOPEX
     },
     "CAPEXother" = {
-      unit <- "US$2017/vehkm"
+      unit <- paste0(monUnit, "/vehkm")
       description <- "CAPEX (purchase costs) for vehicle types that do not feature fleet tracking
                       (all other than cars, trucks and busses). Sources: UCD"
       weight <- calcOutput("GDP", average2020 = FALSE, aggregate = FALSE) |> time_interpolate(lowResYears)
       weight <- weight[, , paste0("gdp_", SSPscen)]
 
-      # read UCD CAPEX given in US$2017/vkt and US$2017/veh
+      # read UCD CAPEX given in US$/vehkm and US$/veh
       # non fuel OPEX include Domestic Aviation, International Aviation, Moped, Motorcycle (50-250cc), Motorcycle (>250cc) (+4W not used here)
       CAPEXUCD <- toolPrepareUCD(readSource("UCD", "CAPEX"), "CAPEX")
       CAPEXUCD <- CAPEXUCD[!univocalName %in% filterEntries$trn_pass_road_LDV_4W]
-      # For some modes UCD offers only a combined value for CAPEX and non-fuel OPEX given in US$2017/vehkm
+      # For some modes UCD offers only a combined value for CAPEX and non-fuel OPEX given in US$/vehkm
       # combined CAPEX and OPEX include Domestic Ship, Freight Rail, HSR, International Ship, Passenger Rail
       CAPEXcombinedUCD <- toolPrepareUCD(readSource("UCD", "CAPEXandNonFuelOPEX"), "CAPEXandNonFuelOPEX")
       CAPEXcombinedUCD <- CAPEXcombinedUCD[!(univocalName %in% filterEntries$trn_freight_road | univocalName == "Bus")]
@@ -507,7 +509,7 @@ calcEdgeTransportSAinputs <- function(subtype, SSPscen = "SSP2EU", IEAharm = TRU
                      c("region", "univocalName", "technology",
                        "variable", "unit"), extrapolate = TRUE)
 
-      # Data for two wheelers is given in US$2017/veh and needs to be converted to US$2017/vehkm
+      # Data for two wheelers is given in US$/veh and needs to be converted to US$/vehkm
       # with the help of annuity and annual mileage
 
       # UCD applied interest rate of 10% and uniform vehicle lifetime of 15 yrs
@@ -527,12 +529,12 @@ calcEdgeTransportSAinputs <- function(subtype, SSPscen = "SSP2EU", IEAharm = TRU
       CAPEXUCD <- merge.data.table(data$CAPEXUCD, AMUCD2W, by = c("region", "univocalName", "technology", "period"),
                                    all.x = TRUE)
       CAPEXUCD[univocalName %in% filterEntries$trn_pass_road_LDV_2W, value := (value * annuityFactor)/ annualMileage]
-      CAPEXUCD[univocalName %in% filterEntries$trn_pass_road_LDV_2W, unit := "US$2017/vehkm"][, annualMileage := NULL]
+      CAPEXUCD[univocalName %in% filterEntries$trn_pass_road_LDV_2W, unit := paste0(monUnit, "/vehkm")][, annualMileage := NULL]
 
       # merge.data.table data
       CAPEXraw <- rbind(CAPEXUCD, data$CAPEXcombinedUCD, data$operatingSubsidyUCD)
 
-      GDPpcMERmag <- calcOutput("GDPpc", aggregate = FALSE, unit = "constant 2017 US$MER") |> time_interpolate(lowResYears)
+      GDPpcMERmag <- calcOutput("GDPpc", aggregate = FALSE, unit = mrdrivers::toolGetUnitDollar()) |> time_interpolate(lowResYears)
       GDPpcMERmag <- GDPpcMERmag[, , paste0("gdppc_", SSPscen)]
 
       GDPpcMER <- magpie2dt(GDPpcMERmag, yearcol = "period", regioncol = "region", valcol = "gdppc")[, variable := NULL]
@@ -578,16 +580,16 @@ calcEdgeTransportSAinputs <- function(subtype, SSPscen = "SSP2EU", IEAharm = TRU
       quitteobj <- CAPEX
     },
     "nonFuelOPEXother" = {
-      unit <- "US$2017/vehkm"
+      unit <- paste0(monUnit, "/vehkm")
       description <- "Non fuel OPEX on technology level for vehicle types that do not feature fleet tracking
                      (other than cars, trucks, busses). Sources: UCD, PSI"
       weight <- calcOutput("GDP", average2020 = FALSE, aggregate = FALSE) |> time_interpolate(lowResYears)
       weight <- weight[, , paste0("gdp_", SSPscen)]
-      # read UCD non fuel given in US$2017/vkt and US$2017/veh/yr
+      # read UCD non fuel given in US$/vehkm and US$/veh/yr
       # non fuel OPEX include Domestic Aviation, International Aviation, Moped, Motorcycle (50-250cc), Motorcycle (>250cc) (+4W not used here)
       nonFuelOPEXUCD <- toolPrepareUCD(readSource("UCD", "nonFuelOPEX"), "nonFuelOPEX")
       nonFuelOPEXUCD <- nonFuelOPEXUCD[!univocalName %in% filterEntries$trn_pass_road_LDV_4W]
-      # For some modes UCD offers only a combined value for CAPEX and non-fuel OPEX given in US$2017/vehkm
+      # For some modes UCD offers only a combined value for CAPEX and non-fuel OPEX given in US$/vehkm
       # combined CAPEX and OPEX include Domestic Ship, Freight Rail, HSR, International Ship, Passenger Rail
       nonFuelOPEXcombinedUCD <- toolPrepareUCD(readSource("UCD", "CAPEXandNonFuelOPEX"), "CAPEXandNonFuelOPEX")
       nonFuelOPEXcombinedUCD <- nonFuelOPEXcombinedUCD[!univocalName %in% c(filterEntries$trn_freight_road,
@@ -604,7 +606,7 @@ calcEdgeTransportSAinputs <- function(subtype, SSPscen = "SSP2EU", IEAharm = TRU
       data <- lapply(data, approx_dt, lowResYears, "period", "value",
                      c("region", "univocalName", "technology", "variable", "unit"), extrapolate = TRUE)
 
-      # Data for two wheelers is given in US$2017/veh and needs to be converted to US$2017/vehkm
+      # Data for two wheelers is given in US$/veh and needs to be converted to US$/vehkm
       # with the help of annual mileage
       AMUCD2W <- toolPrepareUCD(readSource("UCD", "annualMileage"), "annualMileage")
       AMUCD2W <- AMUCD2W[univocalName %in% filterEntries$trn_pass_road_LDV_2W]
@@ -616,7 +618,7 @@ calcEdgeTransportSAinputs <- function(subtype, SSPscen = "SSP2EU", IEAharm = TRU
                                                                          "univocalName", "technology"),
                                          all.x = TRUE)
       nonFuelOPEXUCD[univocalName %in% filterEntries$trn_pass_road_LDV_2W, value := value / annualMileage]
-      nonFuelOPEXUCD[univocalName %in% filterEntries$trn_pass_road_LDV_2W, unit := "US$2017/vehkm"][, annualMileage
+      nonFuelOPEXUCD[univocalName %in% filterEntries$trn_pass_road_LDV_2W, unit := paste0(monUnit, "/vehkm")][, annualMileage
                                                                                                     := NULL]
 
       # merge.data.table data
@@ -758,7 +760,7 @@ calcEdgeTransportSAinputs <- function(subtype, SSPscen = "SSP2EU", IEAharm = TRU
       quitteobj <- VOT
     },
     "timeValueCosts" = {
-      unit <- "US$2017/pkm"
+      unit <- paste0(monUnit, "/pkm")
       description <- "Time value costs for passenger transport modes.
                       Sources: GCAM"
       weight <- calcOutput("GDP", average2020 = FALSE, aggregate = FALSE) |> time_interpolate(highResYears)
@@ -776,7 +778,7 @@ calcEdgeTransportSAinputs <- function(subtype, SSPscen = "SSP2EU", IEAharm = TRU
                                          valcol = "multiplier")[, c("variable", "unit") := NULL]
       setkey(valueOfTimeMultiplier, region, period, univocalName, technology)
 
-      GDPpcMERmag <- calcOutput("GDPpc", aggregate = FALSE, unit = "constant 2017 US$MER") |> time_interpolate(highResYears)
+      GDPpcMERmag <- calcOutput("GDPpc", aggregate = FALSE, unit = mrdrivers::toolGetUnitDollar()) |> time_interpolate(highResYears)
       GDPpcMERmag <- GDPpcMERmag[, , paste0("gdppc_", SSPscen)]
 
       GDPpcMER <- magpie2dt(GDPpcMERmag, yearcol = "period", regioncol = "region", valcol = "gdppc")[, variable := NULL]
@@ -787,11 +789,11 @@ calcEdgeTransportSAinputs <- function(subtype, SSPscen = "SSP2EU", IEAharm = TRU
       timeValueCosts <- merge(timeValueCosts, GDPpcMER)
       weeksPerYear <- 50
       hoursPerWeek <- 40
-      timeValueCosts[, value := gdppc                   ## [US$2017/person/year]
-                     * multiplier                        ## [US$2017/person/year]
-                     / (hoursPerWeek * weeksPerYear) /     ## [US$2017/h]
-                       speed]                            ## [US$2017/pkm]
-      timeValueCosts[, variable := "Time value costs"][, unit := "US$2017/pkm"]
+      timeValueCosts[, value := gdppc                   ## [US$/person/year]
+                     * multiplier                        ## [US$/person/year]
+                     / (hoursPerWeek * weeksPerYear) /     ## [US$/h]
+                       speed]                            ## [US$/pkm]
+      timeValueCosts[, variable := "Time value costs"][, unit := paste0(monUnit, "/pkm")]
       timeValueCosts <- timeValueCosts[, c("region", "univocalName", "technology",
                                            "variable", "unit", "period", "value")]
       timeValueCosts <- timeValueCosts[(univocalName %in% highResUnivocalNames
@@ -820,7 +822,7 @@ calcEdgeTransportSAinputs <- function(subtype, SSPscen = "SSP2EU", IEAharm = TRU
       quitteobj <- timeValueCosts
     },
     "PurchasePriceSubsidies" = {
-      unit <- "US$2017/veh"
+      unit <- paste0(monUnit, "/veh")
       description <- "Subsidies for individuals purchasing alternative technology LDVs.
                       If untilPrice is not NA, then the subsidies only apply if the purchase price (CAPEX)
                       is smaller than or equal to the untilPrice."
@@ -844,7 +846,7 @@ calcEdgeTransportSAinputs <- function(subtype, SSPscen = "SSP2EU", IEAharm = TRU
 
       # merge subsidies with CAPEX data to obtain purchase price and calculate subsidies
       data <- merge(data, CAPEXapprox, all.y = TRUE, by = intersect(names(data), names(CAPEXapprox)))
-      data$unit <- "US$2017/veh"
+      data$unit <- paste0(monUnit, "/veh")
 
       # calculate subsidies based on purchase price and untilPrice values
       calculateSubsidies <- function(period, price, subsidy, untilPrice, subsidy2,

R/convertPSI.R

@@ -32,15 +32,15 @@ convertPSI <- function(x, subtype) {
     subtype,
     "CAPEX" = {
 
-      # PSI CAPEX need to be transformed from EUR 2017 to USD 2017
+      # PSI CAPEX need to be transformed from EUR 2017 to USD
       x <- GDPuc::toolConvertGDP(
         gdp = x,
         unit_in = "constant 2017 EUR",
         unit_out = mrdrivers::toolGetUnitDollar(),
         replace_NAs = "with_USA"
       )
-
-      getItems(x, dim = "unit") <- "US$2017/veh"       # nolint: object_usage_linter
+      monUnit <- gsub(".*?(\\d{4}).*", "US$\\1", mrdrivers::toolGetUnitDollar())
+      getItems(x, dim = "unit") <- paste0(monUnit, "/veh")       # nolint: object_usage_linter
     },
     "energyIntensity" = {
       #PSI energy intensity needs to be transformed to MJ/vehkm

R/convertUCD.R

@@ -37,15 +37,15 @@ convertUCD <- function(x, subtype) {
 
     x <- toolAggregate(x, rel = UCD2iso)
 
-    # convert US$2005 to US$20217
     x <- GDPuc::toolConvertGDP(
       gdp = x,
       unit_in = "constant 2005 US$MER",
       unit_out = mrdrivers::toolGetUnitDollar(),
       replace_NAs = "with_USA"
     )
 
-    magclass::getNames(x) <- gsub("US\\$2005", "US$2017", magclass::getNames(x))
+    monUnit <- gsub(".*?(\\d{4}).*", "US$\\1", mrdrivers::toolGetUnitDollar())
+    magclass::getNames(x) <- gsub("US\\$2005", monUnit, magclass::getNames(x))
 
   } else {
     x <- toolAggregate(x, rel = UCD2iso)

R/readTRACCS.R

@@ -155,7 +155,7 @@ readTRACCS <- function(subtype = c("fuelEnDensity", "roadFuelConsumption", "ener
         }))
       mpobj <- data[
         , .(country_name, TRACCS_category, TRACCS_vehicle_type,
-          TRACCS_technology, variable = "Annual mileage", unit = "vehkm/veh/yr", period, value)] %>%
+          TRACCS_technology, variable = "Annual mileage", unit = "vehkm/veh yr", period, value)] %>%
         as.magpie(spatial = "country_name", temporal = "period")
       return(mpobj)
     },

R/readUCD.R

@@ -42,7 +42,7 @@ readUCD <- function(subtype = c(
     "annualMileage" = {
       dt <- UCD[variable == "annual travel per vehicle"]
       dt[, variable := "Annual mileage"]
-      dt[, unit := "vehkm/veh/yr"]
+      dt[, unit := "vehkm/veh yr"]
     },
     "nonMotorizedDemand" = {
       dt <- UCD[variable == "service output"]
@@ -68,7 +68,7 @@ readUCD <- function(subtype = c(
                                 "Operating costs (tolls)", "Operating costs (total non-fuel)")]
 
       dt[unit == "2005$/vkt", unit := "US$2005/vehkm"]
-      dt[unit == "2005$/veh/yr", unit := "US$2005/veh/yr"]
+      dt[unit == "2005$/veh/yr", unit := "US$2005/veh yr"]
     },
     "CAPEXandNonFuelOPEX" = {
       dt <- UCD[variable %in% c("CAPEX and non-fuel OPEX")]

R/toolAdjustAnnualMileage.R

@@ -28,12 +28,13 @@ toolAdjustAnnualMileage <- function(dt, completeData, filter, ariadneAdjustments
   # Non-motorized modes do not get an annual mileage (no fleet tracking possible for walking/
   # not planned for non-motorized cycling)
   completeData <- completeData[!univocalName %in% c("Cycle", "Walk")]
+  mileageUnit <- unique(dt$unit)
   dt <- merge.data.table(completeData, dt, all = TRUE)
   # For some regions an annual mileage is provided for certain vehicle types, but no demand.
   # These values need to be deleted
   dt <- dt[!is.na(check)]
   # update variable and unit for introduced NAs
-  dt[, unit := "vehkm/veh/yr"][, variable := "Annual mileage"][, check := NULL]
+  dt[, unit := mileageUnit][, variable := "Annual mileage"][, check := NULL]
 
   # Average first within regions over technologies -> e.g. BEV gets the same value as other technologies
   # Take min over technologies for BEV

R/toolAdjustCAPEXother.R

@@ -105,7 +105,7 @@ toolAdjustCAPEXother <- function(dt, ISOcountries, yrs, completeData, GDPpcMER,
   missingMoped[is.na(value), value := twoW250][, twoW250 := NULL]
 
   missing2W <- rbind(missing50, missing250, missingMoped)
-  missing2W[, unit := "US$2017/vehkm"][, variable := "Capital costs (total)"]
+  missing2W[, unit := unique(dt[!(is.na(value))]$unit)][, variable := "Capital costs (total)"]
 
   dt <- rbind(dt[!(is.na(value) & univocalName %in% filter$trn_pass_road_LDV_2W)], missing2W)
   dt[, check := NULL]