R/calcEmiPollutantExo.R

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

#' calcEmiPollutantExo
#' calculate EmiPollutantExo based on RCP data
#'
#' @return magpie object
#' @author Julian Oeser
#' @param subtype Either 'Waste' or 'AviationShipping'
#' @param aviationshippingsource Defines source for aviation and shipping emissions. Either 'RCP' or 'LeeGAINS'.
#' @seealso \code{\link{calcOutput}}
#' @examples
#' \dontrun{ a <- calcOutput(type="EmiPollutantExo")
#' }
#'
calcEmiPollutantExo <- function(subtype, aviationshippingsource = "RCP") {

  if (!subtype %in% c("Waste", "AviationShipping")) {
    stop("Invalid subtype. Must be 'Waste' or 'AviationShipping'")
  }
  if (!aviationshippingsource %in% c("RCP", "AviationShipping")) {
    stop("Invalid aviationshippingsource. Must be 'RCP' or 'LeeGAINS'")
  }

  if (subtype == "Waste") {
    x <- readSource("RCP", subtype = "Waste")
    # EDGAR and CEDS IDs of interest
    eIds <- c("6A", "6B", "6C", "6D")
    cIDs <- c("5A_Solid-waste-disposal", "5C_Waste-incineration", "5D_Wastewater-handling", "5E_Other-waste-handling")
  }

  if (subtype == "AviationShipping") {
    if (aviationshippingsource == "RCP") {
      x <- readSource("RCP", subtype = "AviationShipping", convert = FALSE)
    }
    if (aviationshippingsource == "LeeGAINS") {
      shipping <- readSource("ECLIPSE", subtype = "shipping.emi", convert = FALSE)
      avi <- readSource("Lee", subtype = "emi")
      x <- mbind(shipping, avi)
      getSets(x) <- c("region", "year", "source", "type", "scenario")
      dimnames(x)[[3]] <- gsub("CH4", "ch4", dimnames(x)[[3]])
      dimnames(x)[[3]] <- gsub("BC", "bc", dimnames(x)[[3]])
      dimnames(x)[[3]] <- gsub("SO2", "so2", dimnames(x)[[3]])
    }
    # EDGAR and CEDS IDs of interest
    eIds <- c("1C1", "1C2")
    cIDs <- c("1A3ai_International-aviation", "1A3di_International-shipping")
  }

  # Get EDGAR and CEDS data used to scale
  ch4 <- readSource("EDGAR", subtype = "ch4_history")[, 2005, eIds]
  so2 <- readSource("EDGAR", subtype = "SO2")[, 2005, eIds]
  co  <- readSource("EDGAR", subtype = "CO")[, 2005, eIds]
  voc <- readSource("EDGAR", subtype = "VOC")[, 2005, eIds]
  nox <- readSource("EDGAR", subtype = "NOx")[, 2005, eIds]
  bc <- readSource("CEDS", subtype = "BC")[, 2005, cIDs] %>% collapseNames() %>% setNames(eIds)
  oc  <- readSource("CEDS", subtype = "OC")[, 2005, cIDs] %>% collapseNames() %>% setNames(eIds)
  getSets(bc) <- getSets(ch4)
  getSets(oc) <- getSets(ch4)

  ch4 <- add_dimension(ch4, dim = 3.1, "type", "ch4")
  so2 <- add_dimension(so2, dim = 3.1, "type", "so2")
  bc  <- add_dimension(bc,  dim = 3.1, "type", "bc")
  oc  <- add_dimension(oc,  dim = 3.1, "type", "oc")
  co  <- add_dimension(co,  dim = 3.1, "type", "CO")
  voc <- add_dimension(voc, dim = 3.1, "type", "VOC")
  nox <- add_dimension(nox, dim = 3.1, "type", "NOx")

  # Convert from Gg or kt to Tg
  scale_data <- collapseNames(mbind(ch4, so2, bc, oc, co, voc, nox)) / 1000

  if (subtype == "Waste") {
    scale_data <- dimSums(scale_data, dim = 3.2)
    getSets(scale_data)  <- c("region","year","type")
  }
  if (subtype == "AviationShipping") {
    scale_data <- dimSums(scale_data, dim = 1)
    getSets(scale_data) <- c("region", "year", "type", "source")
    getNames(scale_data) <- gsub("1C1", "Aviation", getNames(scale_data))
    getNames(scale_data) <- gsub("1C2", "InternationalShipping", getNames(scale_data))
  }

  getYears(scale_data) <- NULL
  x <- complete_magpie(x, fill = 0)
  scale_x <- x[, 2005, ]
  getYears(scale_x) <- NULL

  x <- x * scale_data / scale_x
  x[is.na(x)] <- 0

  # interpolate time
  y <- getYears(x, as.integer = TRUE)
  required_year <- seq(2000, 2150, by = 5)
  interpolated_year <- required_year[!(required_year %in% y)]
  out <- time_interpolate(x, interpolated_year, TRUE, extrapolation_type = "constant")

  getSets(out) <- getSets(x)

  list(x = out,
       weight = NULL,
       unit = "Tg/yr",
       description = "Emissions from Aviation and International Shipping from 2000 to 2150")
}