R/zchunk_L2112.ag_nonco2_IRR_MGMT.R

In rohmin9122/gcam-korea-release: Build the GCAM-Korea Input Datasets

#' module_emissions_L2112.ag_nonco2_IRR_MGMT
#'
#' Disaggregate non-CO2 agricultral emissions by production technology
#'
#' @param command API command to execute
#' @param ... other optional parameters, depending on command
#' @return Depends on \code{command}: either a vector of required inputs,
#' a vector of output names, or (if \code{command} is "MAKE") all
#' the generated outputs: \code{object}, \code{L2112.AWBEmissions}, \code{L2112.AGREmissions}. The corresponding file in the
#' original data system was \code{L2112.ag_nonco2_IRR_MGMT.R} (emissions level2).
#' @details Disaggregates agricultural emissions the basis of production by scaling emissions by a technology factor
#' @importFrom assertthat assert_that
#' @importFrom dplyr filter mutate select
#' @importFrom tidyr gather spread
#' @author KD July 2017
module_emissions_L2112.ag_nonco2_IRR_MGMT <- function(command, ...) {
  if(command == driver.DECLARE_INPUTS) {
    return(c("L2111.AGREmissions",
             "L2111.AGRBio",
             "L2111.AWB_BCOC_EmissCoeff",
             "L2111.nonghg_max_reduction",
             "L2111.nonghg_steepness",
             "L2111.AWBEmissions",
             "L2012.AgProduction_ag_irr_mgmt"))
  } else if(command == driver.DECLARE_OUTPUTS) {
    return(c("L2112.AGRBio", "L2112.AWB_BCOC_EmissCoeff", "L2112.nonghg_max_reduction",
             "L2112.nonghg_steepness", "L2112.AWBEmissions", "L2112.AGREmissions"))
  } else if(command == driver.MAKE) {

    all_data <- list(...)[[1]]

    AgProductionTechnology <- level <- year <- region <- AgSupplySector <- AgSupplySubsector <-
      AgProductionTechnology_nolvl <- calOutputValue <- AgProductionTechnology_lvl <- total <-
      share_tech <- input.emissions <- Non.CO2 <- NULL  # silence package check notes

    # Load required inputs
    L2111.AWBEmissions <- get_data(all_data, "L2111.AWBEmissions")
    L2111.AGREmissions <- get_data(all_data, "L2111.AGREmissions")
    L2111.AGRBio <- get_data(all_data, "L2111.AGRBio")
    L2111.AWB_BCOC_EmissCoeff <- get_data(all_data, "L2111.AWB_BCOC_EmissCoeff")
    L2111.nonghg_max_reduction <- get_data(all_data, "L2111.nonghg_max_reduction")
    L2111.nonghg_steepness <- get_data(all_data, "L2111.nonghg_steepness")
    L2012.AgProduction_ag_irr_mgmt <- get_data(all_data, "L2012.AgProduction_ag_irr_mgmt")

    # ===================================================
    # For all of the animal emission tables add high and low management level
    L2111.AGRBio %>%
      repeat_add_columns(tibble(level = c("hi", "lo"))) %>%
      unite(AgProductionTechnology, AgProductionTechnology, level, sep = "_") ->
      L2112.AGRBio

    L2111.AWB_BCOC_EmissCoeff %>%
      repeat_add_columns(tibble(level = c("hi", "lo"))) %>%
      unite(AgProductionTechnology, AgProductionTechnology, level, sep = "_") ->
      L2112.AWB_BCOC_EmissCoeff

    L2111.nonghg_max_reduction %>%
      repeat_add_columns(tibble(level = c("hi", "lo"))) %>%
      unite(AgProductionTechnology, AgProductionTechnology, level, sep = "_") ->
      L2112.nonghg_max_reduction

    L2111.nonghg_steepness %>%
      repeat_add_columns(tibble(level = c("hi", "lo"))) %>%
      unite(AgProductionTechnology, AgProductionTechnology, level, sep = "_") ->
      L2112.nonghg_steepness


    # For the tables whose emissions are read as quantities rather than rates,
    # disaggregate emissions on the basis of production.

    # First calculate the total emissions for each region, supply sector, subsector,
    # technology level in the most recent model base year. This total will latter be
    # used to  calculate share weights.
    L2012.AgProduction_ag_irr_mgmt %>%
      filter(year == max(MODEL_BASE_YEARS)) %>%
      mutate(AgProductionTechnology_nolvl = gsub("_hi|_lo", "", AgProductionTechnology)) %>%
      group_by(region, AgSupplySector, AgSupplySubsector, AgProductionTechnology_nolvl, year) %>%
      summarise(total = sum(calOutputValue)) %>%
      ungroup() ->
      L2112.AgProduction_ag_irr_nomgmt_aggergate

    # Now subset the table of agricultural production for the most recent model base year
    # and format the data frame so that so that the AgProductionTechnology_level column
    # will match the column in the aggeregated data frame.
    L2012.AgProduction_ag_irr_mgmt %>%
      filter(year == max(MODEL_BASE_YEARS)) %>%
      select(region, AgSupplySector, AgSupplySubsector, AgProductionTechnology_lvl = AgProductionTechnology, year, calOutputValue) %>%
      mutate(AgProductionTechnology_nolvl = gsub("_hi|_lo", "", AgProductionTechnology_lvl)) ->
      L2112.AgProduction_ag

    # Calculate the share weights or the fraction of emissions for each region, sector, subsector,
    # technology and level for the using the aggrated total emissions determined above.
    # Eventually these emission shares will be used as a factor to disaggregate the emissions input.
    L2112.AgProduction_ag %>%
      left_join_error_no_match(L2112.AgProduction_ag_irr_nomgmt_aggergate,
                               by = c("region", "AgSupplySector", "year", "AgSupplySubsector", c("AgProductionTechnology_nolvl"))) %>%
      mutate(share_tech = calOutputValue / total) ->
      L2112.AgProduction_ag_share


    # Combine non agricultural waste burning emissions and agricultural waste burning
    # emissions into a single data frame. Add management level information to production
    # technology column.
    L2111.AWBEmissions %>%
      bind_rows(L2111.AGREmissions) %>%
      repeat_add_columns(tibble(level = c("hi", "lo"))) %>%
      unite(AgProductionTechnology_lvl, AgProductionTechnology, level, sep = "_", remove = FALSE) ->
      L2112.awb_agr_emissions

    # Match the shares(fraction of emissions) to the data frames containing
    # emissions quantities for the agricultural water burning and agricultural
    # non waste burning emissions.
    L2112.AgProduction_ag_share %>%
      select(-year, -AgSupplySubsector) %>%
      left_join(L2112.awb_agr_emissions, by = c("region", "AgSupplySector", "AgProductionTechnology_lvl")) ->
      L2112.awb_agr_emissions


    # Where shares allocated to lo/hi are NA but emissions are positive, split it 50/50 between
    # the techs. For all others, set share to zero. Then scale the input emissions by the emission
    # shares.
    L2112.awb_agr_emissions %>%
      mutate(share_tech = if_else(is.na(share_tech) & input.emissions > 1e-6, 0.5, share_tech)) %>%
      replace_na(list(share_tech = 0)) %>%
      mutate(input.emissions  = input.emissions * share_tech) %>%
      select(region, AgSupplySector, AgProductionTechnology = AgProductionTechnology_lvl, AgSupplySubsector,
             year, Non.CO2, input.emissions, level) ->
      L2112.awb_agr_emissions_disag

    # The disaggregated agricultural waste burning emissions.
    L2112.awb_agr_emissions_disag %>%
      filter(grepl("AWB", Non.CO2)) ->
      L2112.AWBEmissions

    # The disaggregated non agricultural waste burning emissions.
    L2112.awb_agr_emissions_disag %>%
      filter(!grepl("AWB", Non.CO2)) ->
      L2112.AGREmissions

    # ===================================================
    # Produce outputs
    L2112.AGRBio %>%
      add_title("Bio N2O Coefficients by region, technology, and management level ") %>%
      add_units("kg N2O per GJ bioenergy") %>%
      add_comments("L211.AGRBio repeated by IRR and RFD technologies") %>%
      add_legacy_name("L2112.AGRBio") %>%
      add_precursors("L2111.AGRBio") ->
      L2112.AGRBio

    L2112.AWB_BCOC_EmissCoeff %>%
      add_title("Agricultural Waste Burning BC/OC Emissions Coefficients by management") %>%
      add_units("kt/Mt") %>%
      add_comments("L2111.AWB_BCOC_EmissCoeff repeated high and low management") %>%
      add_legacy_name("L2112.AWB_BCOC_EmissCoeff") %>%
      add_precursors("L2111.AWB_BCOC_EmissCoeff") ->
      L2112.AWB_BCOC_EmissCoeff

    L2112.nonghg_max_reduction %>%
      add_title("Non-GHG maximum emissions coefficient reduction by agricultural technology and management") %>%
      add_units("Percent reduction from base-year emissions coefficient") %>%
      add_comments("L2111.nonghg_max_reduction repeated by high and low management") %>%
      add_legacy_name("L2112.nonghg_max_reduction") %>%
      add_precursors("L2111.nonghg_max_reduction") ->
      L2112.nonghg_max_reduction

    L2112.nonghg_steepness %>%
      add_title("Steepness of non-GHG emissions reduction for agricultural technologies") %>%
      add_units("Unitless") %>%
      add_comments("L2111.nonghg_steepness repeated by high and low management level") %>%
      add_legacy_name("L2112.nonghg_steepness") %>%
      add_precursors("L2111.nonghg_steepness") ->
      L2112.nonghg_steepness

    L2112.AWBEmissions %>%
      add_title("Input table of agricultural waste burning emissions by production") %>%
      add_units("Tg") %>%
      add_comments("Production share weights are set for irrigated vs. rainfed, same for high and low management.") %>%
      add_legacy_name("L2112.AWBEmissions") %>%
      add_precursors("L2111.AWBEmissions", "L2012.AgProduction_ag_irr_mgmt") ->
      L2112.AWBEmissions

    L2112.AGREmissions %>%
      add_title("Input table for the agricultural emissions by production") %>%
      add_units("Tg") %>%
      add_comments("Production share weights are set for irrigated vs. rainfed, same for high and low management.") %>%
      add_legacy_name("L2112.AGREmissions") %>%
      add_precursors("L2111.AGREmissions", "L2012.AgProduction_ag_irr_mgmt") ->
      L2112.AGREmissions

    return_data(L2112.AGRBio, L2112.AWB_BCOC_EmissCoeff, L2112.nonghg_max_reduction, L2112.AWBEmissions,
                L2112.nonghg_steepness, L2112.AGREmissions)

  } else {
    stop("Unknown command")
  }
}