R/convertEDGARghg.R

In pik-piam/mrcommons: MadRat commons Input Data Library

convertEDGARghg <- function(x) {

  # rename regions
  getItems(x, dim = 1) <- sub(pattern = "ANT", replacement = "SXM",
                              x = getItems(x, dim = 1))
  getItems(x, dim = 1) <- sub(pattern = "SCG", replacement = "SRB",
                              x = getItems(x, dim = 1))

  # Analog to convertCEDS: shipping and aviation data is global only
  # We want to distribute it evenly across all countries.
  # Therefore, save global data because it will be removed by toolCountryfill

  # sum all sub-sectors of int. aviation and shipping per pollutant
  air <- dimSums(x["AIR", , ], dim = 3.2, na.rm = TRUE) %>%
    add_dimension(dim = 3.2, add = "variable", nm = "Aviation")
  getItems(air, dim = 1) <- "GLO"

  sea <- dimSums(x["SEA", , ], dim = 3.2, na.rm = TRUE) %>%
    add_dimension(dim = 3.2, add = "variable", nm = "Shipping")
  getItems(sea, dim = 1) <- "GLO"

  x <- x[c("AIR", "SEA"), , invert = TRUE]

  # combine bunker data
  bunkers <- mbind(air, sea)

  # fills missing ISO countries and remove unknown ISO countries and bunkers
  x <- toolCountryFill(x, fill = 0, verbosity = 2)

  # create weight 1 for bunkers
  w <- new.magpie(getItems(x, dim = 1),
                  getItems(x, dim = 2),
                  getItems(bunkers, dim = 3),
                  fill = 1)

  # create mapping of each country to GLO
  m <- data.frame(from = getItems(x, dim = 1), to = "GLO")

  # spread global shipping and aviation data evenly across countries and
  # save it to regions of x
  x <- add_columns(x, addnm = c("Aviation", "Shipping"), dim = 3.2, fill = NA)
  x[, , getItems(bunkers, dim = 3)] <- toolAggregate(bunkers, m, weight = w)

  return(x)
}