R/calcValidEmissionsAFOLU.R

In pik-piam/mrvalidation: madrat data preparation for validation purposes

#' @title ValidEmissionsAFOLU
#' @description validation for total and cumulative AFOLU emissions in CO2eq
#' @author Michael Crawford
#'
#' @param datasource current options are "FAO" and "EDGAR_LU"
#' @param cumulative cumulative from y2000
#'
#' @return MAgPIE object with emissions in CO2eq
#'
#' @examples
#' \dontrun{
#'    calcOutput("ValidEmissionsAFOLU")
#' }

calcValidEmissionsAFOLU <- function(datasource = "FAO", cumulative = FALSE) {

   .convertGWP100AR6 <- function(x, old, conversion) {
        x <- x * conversion

        getNames(x) <- stringr::str_replace(getNames(x), old, "GWP100AR6")
        getNames(x) <- stringr::str_replace(getNames(x), paste0("Mt ", old, "/yr"), "Mt CO2e/yr")

        return(x)
    }

    if (datasource == "FAO") {

        #  FAO agricultural emissions (inclusive of the burning of crop residues)
        faoAg <- calcOutput("ValidEmissions", datasource = "FAO_EmisAg", aggregate = FALSE, warnNA = FALSE)
        faoAg <- faoAg[, , "historical"]

        # FAO emissions from land-use change
        faoLUC <- calcOutput("ValidEmissions", datasource = "FAO_EmisLUC", aggregate = FALSE, warnNA = FALSE)

        # Reduce to only years present for both datasets
        yearsPresent <- Reduce(f = intersect, x = Map(getYears, list(faoAg, faoLUC)))

        # These emissions, if summed, represent total emissions from FAO
        n2o <- faoAg[, yearsPresent, c("Emissions|N2O|Land|Biomass Burning|+|Burning of Crop Residues (Mt N2O/yr)",
                                       "Emissions|N2O|Land|+|Agriculture (Mt N2O/yr)")]

        ch4 <- faoAg[, yearsPresent, c("Emissions|CH4|Land|Biomass Burning|+|Burning of Crop Residues (Mt CH4/yr)",
                                       "Emissions|CH4|Land|+|Agriculture (Mt CH4/yr)")]

        co2 <- faoLUC[, yearsPresent, "Emissions|CO2|Land|+|Land-use Change (Mt CO2/yr)"]

        n2o <- .convertGWP100AR6(n2o, "N2O", 273)
        ch4 <- .convertGWP100AR6(ch4, "CH4", 27)
        co2 <- .convertGWP100AR6(co2, "CO2", 1)

        ag <- n2o + ch4 # these emissions now have the same names (i.e., in CO2e), and can thus be simply summed

        total <- mbind(ag, co2)

    } else if (datasource == "EDGAR_LU") {

        edgar <- calcOutput("LandEmissions", datasource = "EDGAR_LU", aggregate = FALSE)

        n2o <- .convertGWP100AR6(edgar[, , "Emissions|N2O|Land|+|Agriculture (Mt N2O/yr)"],     "N2O", 273)
        ch4 <- .convertGWP100AR6(edgar[, , "Emissions|CH4|Land|+|Agriculture (Mt CH4/yr)"],     "CH4", 27)
        co2 <- .convertGWP100AR6(edgar[, , "Emissions|CO2|Land|+|Land-use Change (Mt CO2/yr)"], "CO2", 1)

        ag <- n2o + ch4

        total <- mbind(ag, co2)

    }

    total <- dimSums(total, dim = 3) * 0.001 # Mt to Gt CO2e
    getSets(total)["d3.1"] <- "variable"
    getNames(total) <- "Emissions|GWP100AR6|Land (Gt CO2e/yr)"

    # Calculate cumulative emissions since y2000
    if (cumulative) {
        yearsFrom2000 <- seq(from = 2000, max(getYears(total, as.integer = TRUE)))
        total <- total[, yearsFrom2000, ] # Align historical time series to MAgPIE's accumulation start date
        total[, "y2000", ] <- 0

        total <- as.magpie(apply(total, c(1, 3), cumsum))

        getNames(total, dim = "variable") <- "Emissions|GWP100AR6|Land|Cumulative (Gt CO2e)"
    }

    total <- add_dimension(total, dim = 3.1, add = "scenario", nm = "historical")
    total <- add_dimension(total, dim = 3.2, add = "model", nm = datasource)

    return(list(x           = total,
                weight      = NULL,
                unit        = "CO2eq",
                description = paste0("Historical global GHG emissions, calculated by ", datasource)))

}