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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,111 @@ | ||
| #' Reads NPI policy database with technology capacity target from the Policy data base (v4 August 2024) | ||
| #' by PBL that translate the high impact policies of https://climatepolicydatabase.org/. | ||
| #' @description Reads excel sheet with NPi (National Policies Implemented) | ||
| #' data on different policy targets (capacity) with different variations: unconditional for minimal and conditionnal for maximum targets. | ||
| #' NPI targets only include targets that are based on implemented policy instruments. | ||
| #' @details Country name is ISO coded. Capacity/Additional Capacity targets are in GW. | ||
| #' @return magpie object | ||
| #' @author Rahel Mandaroux, Léa Hayez, Falk Benke | ||
| #' @param subtype Capacity_2025_uncond (or cond) for capacity target | ||
| #' @importFrom readxl read_xlsx | ||
| #' @importFrom dplyr select | ||
|
|
||
| ############# | ||
| #for testing | ||
| #setwd("C:/Users/rahelma/remind/sources/NewClimate") | ||
| #NPIfile <- "NPi_2025-02-03.xlsx" | ||
| ############# | ||
|
|
||
| readNewClimate <- function(subtype) { | ||
| # browser() | ||
|
|
||
| if (grepl("2025", subtype, fixed = TRUE)) { #keep structure to compare when new versions (NPi target updates) are generated | ||
| NPIfile <- "NPi_2025-02-03.xlsx" | ||
| } else { | ||
| NPIfile <- "NPi_2025-02-03.xlsx" | ||
| if (!grepl("2025", subtype, fixed = TRUE)) { | ||
| warning("\nNo data for year in ", subtype, " available. Choose default: ", NPIfile) | ||
| } | ||
| } | ||
|
|
||
| if (grepl("Capacity", subtype, fixed = TRUE)) { | ||
| # Capacity/Additional Capacity targets are in GW. | ||
| NPI <- read_excel(NPIfile, sheet = "Capacity_target_PBL_2025", | ||
| col_types = c("text", "skip", "numeric", "text", "text", "numeric", | ||
| "numeric", "numeric", "numeric", "numeric", "numeric","numeric", | ||
| "numeric","numeric","numeric","numeric","numeric", "skip", "skip", "skip")) | ||
| x <- as.magpie(NPI, spatial = 1, temporal = 2, datacol = 3) | ||
| } | ||
|
|
||
| if (grepl("Emissions", subtype, fixed = TRUE)) { | ||
| input <- read_xlsx(NPIfile, sheet = "EmissionTargets", skip = 3, na = c("?", "")) | ||
| # select the relevant columns to work upon | ||
| input2 <- select(input, 2, 7:14) | ||
| # rename columns | ||
| colnames(input2) <- c("ISO_Code", "Reference_Year", "BAU_or_Reference_emissions_in_MtCO2e", "Target_Year", | ||
| "Type", "Unconditional", "Conditional", "Uncond2", "Cond2") | ||
| # if no entry in first two quantitative columns, use data from 3rd and 4th | ||
| bothcolumns <- input2$ISO_Code[(! is.na(input2$Unconditional) & ! is.na(input2$Uncond2)) | | ||
| (! is.na(input2$Conditional) & ! is.na(input2$Cond2))] | ||
| if (length(bothcolumns) > 0) { | ||
| warning("readNewClimate with subtype=", subtype, " has values in more than one Uncond/Cond column in: ", | ||
| paste(bothcolumns, collapse = ", ")) | ||
| } | ||
| # check consistency of Type. Note: this has to be identical to the definition in calcEmiTarget.R | ||
| allowedType <- c("GHG-Absolute", "GHG", "GHG/GDP", "CO2/GDP", "GHG-fixed-total", "GHG/CAP") | ||
| if (FALSE %in% (input2$Type %in% allowedType)) { | ||
| warning("Unknown data type used in ", NPIfile, ": ", | ||
| paste(unique(input2$Type)[!unique(input2$Type) %in% allowedType], collapse = ", "), | ||
| ". Please use: ", paste(allowedType, collapse = " or "), ".") | ||
| } | ||
| # check that correct columns are used for relative and Mt stuff | ||
| if (! grepl("Emissions_20(18|21)", subtype)) { | ||
| colRelative <- is.na(input2$Uncond2) & is.na(input2$Cond2) & | ||
| input2$Type %in% c("GHG", "GHG/GDP", "CO2/GDP", "GHG/CAP") | ||
| colAbsolute <- is.na(input2$Unconditional) & is.na(input2$Conditional) & | ||
| input2$Type %in% c("GHG-Absolute", "GHG-fixed-total") | ||
| colInconsistent <- ! (colRelative | colAbsolute) | ||
| if (any(colInconsistent)) { | ||
| warning("readNewClimate with subtype=", subtype, " noticed that the target column used does not ", | ||
| "correspond to the type used for: ", paste(input2$ISO_Code[colInconsistent], collapse = ", ")) | ||
| } | ||
| } | ||
|
|
||
| # drop extra columns | ||
| input2[is.na(input2$Unconditional), ]$Unconditional <- input2[is.na(input2$Unconditional), ]$Uncond2 | ||
| input2[is.na(input2$Conditional), ]$Conditional <- input2[is.na(input2$Conditional), ]$Cond2 | ||
| input2$Uncond2 <- NULL | ||
| input2$Cond2 <- NULL | ||
|
|
||
| # if conditional is empty, fill with unconditional | ||
| input2[is.na(input2$Conditional), ]$Conditional <- input2[is.na(input2$Conditional), ]$Unconditional | ||
|
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||
| # in case a country has two or more types of targets for same year, use GHG-Absolute targets | ||
| # note: the only remaining country in 2021 is MGD Madagascar based on its 2016 submission | ||
| input2 <- input2[!(input2$ISO_Code %in% input2[duplicated(input2[c(1, 4)]), ]$ISO_Code | ||
| & input2$Target_Year %in% input2[duplicated(input2[c(1, 4)]), ]$Target_Year | ||
| & input2$Type != "GHG-Absolute"), ] | ||
|
|
||
| # check whether conditional is more stringent than unconditional | ||
| condTrumpsUncond <- (input2$Conditional <= input2$Unconditional) | is.na(input2$Unconditional) | ||
| if (any(! condTrumpsUncond)) { | ||
| warning("readNewClimate with subtype=", subtype, ": unconditional target more stringent than conditional in: ", | ||
| paste(input2$ISO_Code[! condTrumpsUncond], collapse = ", ")) | ||
| } | ||
|
|
||
| # warning if emission changes have no reference year or BAU reference | ||
| ref4change <- input2$ISO_Code[input2$Reference_Year %in% c("no", NA) & | ||
| input2$Type %in% c("GHG", "CO2/GDP", "GHG/GDP", "GHG-Absolute")] | ||
| if (length(ref4change) > 0) { | ||
| warning("readNewClimate with subtype=", subtype, " has no entry in column reference year in:", | ||
| paste(ref4change, collapse = ", ")) | ||
| } | ||
| # as magclass can only cover numerical values well, transform: in column 2 BAU into -1, and Type into number based on allowedType | ||
| input2[2] <- as.numeric(unlist(rapply(input2[2], function(x) | ||
| ifelse(x == "BAU", -1, ifelse(x == "no", -2, x)), how = "replace"))) | ||
| input2[5] <- as.numeric(unlist(rapply(input2[5], function(x) match(x, allowedType), how = "replace"))) | ||
| # sort with c(1,4,2,3,5,6,7) to get region into first and years into second column | ||
| x <- as.magpie(input2[c(1, 4, 2, 3, 5, 6, 7)], spatial = 1, temporal = 2, datacol = 3) | ||
| } | ||
| return(x) | ||
| } |
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