R/readRCP.R

In pik-piam/mrremind: MadRat REMIND Input Data Package

#' Read RCP
#' Read in RCP data
#'
#' @return magpie object of the RCP data
#' @author Julian Oeser
#' @seealso \code{\link{readSource}}
#' @examples
#'
#' \dontrun{ a <- readSource(type="RCP", subtype="Waste")
#' }
#'
#' @param subtype Either 'Waste' or 'AviationShipping'
#'
#' @importFrom readxl read_excel
#' @importFrom dplyr filter_ mutate_ rename_ select_ recode
#' @importFrom tidyr gather_ separate_
#' @importFrom stats complete.cases

readRCP <- function(subtype) {


  dat <- as.data.frame(do.call(rbind, lapply(list.files(pattern = ".xls$"), read_excel)))

  if (subtype == "Waste") {
    dat <- dat %>%
      filter(.data$Region %in% c("R5ASIA", "R5LAM", "R5MAF", "R5OECD", "R5REF"),
             grepl("Waste", .data$Variable)) %>%
      pivot_longer(cols = matches('^[0-9]*$'), names_to = 'year',
                   names_transform = list(year = as.numeric)) %>%
      separate("Variable", c("type", "source"), sep = " - ") %>%
      select(region = 'Region', 'year', scenario = 'Scenario', 'type', 'source',
             'value') %>%
      mutate(region = sub('^R5', '', .data$region))

  } else if (subtype == "AviationShipping") {
    dat <- dat %>%
      filter(.data$Region == "World",
             grepl("Aviation|Shipping", .data$Variable)) %>%
      pivot_longer(cols = matches('^[0-9]*$'), names_to = 'year',
                   names_transform = list(year = as.numeric)) %>%
      mutate(Region = "GLO") %>%
      separate("Variable", c("type", "source"), sep = " - ") %>%
      select(region = 'Region', 'year', scenario = 'Scenario', 'type', 'source',
             'value')
  } else {
    stop("Invalid subtype. Must be 'Waste' or 'AviationShipping'")
  }

  dat$scenario <- recode(dat$scenario,
                         `IMAGE - RCP3-PD (2.6)`="rcp26",
                         `MiniCAM - RCP 4.5` = "rcp45",
                         `AIM - RCP 6.0` = "rcp60",
                         `MESSAGE - RCP 8.5` = "rcp85")

  dat$source <- recode(dat$source,
                        `Waste (landfills, wastewater, non-energy incineration)`="Waste",
                        `International Shipping`="InternationalShipping")

  dat$type <- recode(dat$type,
                      `CH4 emissions`="ch4",
                      `Sulfur emissions`="so2",
                      `Black Carbon emissions`="bc",
                      `Organic Carbon Emissions`="oc",
                      `CO emissions`="CO",
                      `NOx emissions`="NOx",
                      `VOC emissions`="VOC",
                      `NH3 emissions`="nh3")

  dat <- dat[complete.cases(dat),]

  out <- as.magpie(dat, spatial=1 ,datacol=6)

  return(out)

}