Fix scen selection

pik-piam · Feb 19, 2025 · 8c78faf · 8c78faf
1 parent c6b966a
commit 8c78faf
Showing 1 changed file with 15 additions and 18 deletions.
diff --git a/R/calcEmiTarget.R b/R/calcEmiTarget.R
@@ -6,10 +6,6 @@ calcEmiTarget <- function(subtype, scenario) {
   if (!subtype %in% c("Ghgshare2005", "Ghgfactor", "Ghghistshare")) {
     stop("Unknown 'subtype' argument")
   }
-  # Make sure SSP2 is included in the scenarios. Required for the computations.
-  if (! "SSP2" %in% scenario) {
-    scenario <- c(scenario, "SSP2")
-  }
 
   # Import historical emi needed for the calculations
   ## Historical emissions for 1990-2015 - co2 (excl LU),ch4,n2o (so far no Fgas historic time series)
@@ -36,32 +32,31 @@ calcEmiTarget <- function(subtype, scenario) {
   globGhg <- dimSums(ghg, dim = 1)
   ghg <- toolCountryFill(ghg, fill = 0, verbosity = 2)
 
+  # Make sure SSP2 is included in the ghgFactor scenarios. Required for the computations.
+  subsetScen <- unique(c(scenario, "SSP2"))
   # Get ghgfactor
   listGhgfactors <- list(
-    "2018_cond"   = readSource("UNFCCC_NDC", subtype = "Emissions_2018_cond", subset = scenario),
-    "2018_uncond" = readSource("UNFCCC_NDC", subtype = "Emissions_2018_uncond", subset = scenario),
-    "2021_cond"   = readSource("UNFCCC_NDC", subtype = "Emissions_2021_cond", subset = scenario),
-    "2021_uncond" = readSource("UNFCCC_NDC", subtype = "Emissions_2021_uncond", subset = scenario),
-    "2022_cond"   = readSource("UNFCCC_NDC", subtype = "Emissions_2022_cond", subset = scenario),
-    "2022_uncond" = readSource("UNFCCC_NDC", subtype = "Emissions_2022_uncond", subset = scenario),
-    "2023_cond"   = readSource("UNFCCC_NDC", subtype = "Emissions_2023_cond", subset = scenario),
-    "2023_uncond" = readSource("UNFCCC_NDC", subtype = "Emissions_2023_uncond", subset = scenario),
-    "2024_cond"   = readSource("UNFCCC_NDC", subtype = "Emissions_2024_cond", subset = scenario),
-    "2024_uncond" = readSource("UNFCCC_NDC", subtype = "Emissions_2024_uncond", subset = scenario)
+    "2018_cond"   = readSource("UNFCCC_NDC", subtype = "Emissions_2018_cond", subset = subsetScen),
+    "2018_uncond" = readSource("UNFCCC_NDC", subtype = "Emissions_2018_uncond", subset = subsetScen),
+    "2021_cond"   = readSource("UNFCCC_NDC", subtype = "Emissions_2021_cond", subset = subsetScen),
+    "2021_uncond" = readSource("UNFCCC_NDC", subtype = "Emissions_2021_uncond", subset = subsetScen),
+    "2022_cond"   = readSource("UNFCCC_NDC", subtype = "Emissions_2022_cond", subset = subsetScen),
+    "2022_uncond" = readSource("UNFCCC_NDC", subtype = "Emissions_2022_uncond", subset = subsetScen),
+    "2023_cond"   = readSource("UNFCCC_NDC", subtype = "Emissions_2023_cond", subset = subsetScen),
+    "2023_uncond" = readSource("UNFCCC_NDC", subtype = "Emissions_2023_uncond", subset = subsetScen),
+    "2024_cond"   = readSource("UNFCCC_NDC", subtype = "Emissions_2024_cond", subset = subsetScen),
+    "2024_uncond" = readSource("UNFCCC_NDC", subtype = "Emissions_2024_uncond", subset = subsetScen)
   )
   listYears <- lapply(listGhgfactors, getItems, dim = "year") %>% unlist() %>% unique() %>% sort()
   ghgfactor <- purrr::map(listGhgfactors,
                            ~ add_columns(.x, listYears[!listYears %in% getItems(.x, dim = "year")], 2)) %>%
     mbind()
   ghgfactor <- ghgfactor[, sort(getYears(ghgfactor)), ]
 
-  # Get gdp and pop scenarios (make sure to always get SSP2)
-  gdp <- calcOutput("GDP", scenario = scenario, aggregate = FALSE)
-
   # create 1/0 dummy for calculation of regional share covered by quantitative target, per TarYear.
   # Note that 0 implies no goal, net zero targets have ghgfactor of 0 but dummy of 1
   dummy1 <- 1 * !is.na(ghgfactor[, , "SSP2", drop = TRUE])
-
+  ghgfactor <- mselect(ghgfactor, "data" = scenario)
 
   if (subtype == "Ghgfactor") {
     # in order to calculate the share of regional emissions coming from countries with quantitative target
@@ -75,6 +70,8 @@ calcEmiTarget <- function(subtype, scenario) {
   }
 
   if (subtype == "Ghgshare2005") {
+    # Get gdp scenarios
+    gdp <- calcOutput("GDP", scenario = scenario, aggregate = FALSE)
     # calculate growth for GDP weight for GHG emission share
     # assuming constant relative emission intensities across countries of one region
     gdpWeight <- new.magpie(getItems(dummy1, dim = "iso3c"), getItems(dummy1, dim = "year"), getNames(ghgfactor))