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Pull request #208: Sjs/feature/CEDS Release April21
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Merge in JGCRI/gcam-core from sjs/feature/CEDS_Release_April21 to master

* commit '544eff9f93a1e79e157f93a9fc7b3232696ae2f0':
  Update \data and \man files
  Empty commit
  Revert "Updated Source"
  Updated Source
  Update two output / input names to be clearer
  Aggregate international shipping emissions
  Regenerate the prebuilt data
  Added a new prebuilt data output of international shipping emissions
  Update sysdata.rda
  data/ files updated with prebuilt data based off of new CEDS update
  Update constants.R to change CEDS years to 1970:2019
  Update L201.en_nonco2 and related batch script to remove L201.OutputEmissCoeff_elec
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@pralitp
pralitp committed Jul 11, 2021
2 parents deae9d8 + 544eff9 commit 3d51cdd
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Showing 14 changed files with 104 additions and 104 deletions.
2 changes: 1 addition & 1 deletion input/gcamdata/R/constants.R
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Original file line number Diff line number Diff line change
Expand Up @@ -622,7 +622,7 @@ emissions.EPA.scaling.threshold <- 50 # EPA emissions/ CEDS emission, used to ch
emissions.EPA.scaling.threshold.combustion <- 20 # check scaling outliers in L112 chunk for combustion sector

# Time
emissions.CEDS_YEARS <- 1971:2019 # Year coverage for CEDS inventory.
emissions.CEDS_YEARS <- 1970:2019 # Year coverage for CEDS inventory.
emissions.CTRL_BASE_YEAR <- 1975 # Year to read in pollution controls
emissions.DEFOREST_COEF_YEARS <- c(2000, 2005)
emissions.EDGAR_YEARS <- 1971:2008
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32 changes: 17 additions & 15 deletions input/gcamdata/R/zchunk_L102.nonco2_ceds_R_S_Y.R
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@
#' @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{L102.ceds_nonco2_tg_R_S_F}.
#' the generated outputs: \code{L102.ceds_nonco2_tg_R_S_F}, \code{L102.ceds_int_shipping_nonco2_tg_S_F}.
#' @details Calculates emissions using CEDS and CMIP data.
#' @importFrom assertthat assert_that
#' @importFrom dplyr filter mutate select
Expand All @@ -34,7 +34,8 @@ module_emissions_L102.nonco2_ceds_R_S_Y <- function(command, ...) {
FILE = "emissions/CEDS/ceds_fuel_map",
"L154.IEA_histfut_data_times_UCD_shares"))
} else if(command == driver.DECLARE_OUTPUTS) {
return(c("L102.ceds_GFED_nonco2_tg_R_S_F"))
return(c("L102.ceds_GFED_nonco2_tg_R_S_F",
"L102.ceds_int_shipping_nonco2_tg_S_F"))
} else if(command == driver.MAKE) {

# Silence package checks
Expand Down Expand Up @@ -63,7 +64,6 @@ module_emissions_L102.nonco2_ceds_R_S_Y <- function(command, ...) {
CMIP_unmgd_emissions <- get_data(all_data, "emissions/CEDS/GFED-CMIP6_LUC_emissions") %>%
gather_years(value_col = "emissions")
CMIP_sector_map <- get_data(all_data, "emissions/CEDS/LULUC_to_sector_Mapping")
Int_shipping_IEA_EIA <- get_data(all_data, "L154.IEA_histfut_data_times_UCD_shares") %>% filter(UCD_category=="trn_international ship")

# If the (proprietary) raw CEDS datasets are available, go through the full computations below
# If not, use the pre-saved summary file (i.e., the output of this chunk!) assuming it's available
Expand Down Expand Up @@ -140,15 +140,7 @@ module_emissions_L102.nonco2_ceds_R_S_Y <- function(command, ...) {
filter(CEDS_agg_sector=="trn_intl_ship",CEDS_agg_fuel =="refined liquids") %>%
gather_years %>%
filter(year %in% emissions.CEDS_YEARS) %>%
filter(year <= max(HISTORICAL_YEARS), emissions > 0) %>%
right_join(Int_shipping_IEA_EIA %>% select(iso,year,value) %>% filter(year <= max(HISTORICAL_YEARS)), by=c("year")) %>%
mutate(emissions=if_else(is.na(emissions),0,emissions)) %>%
group_by(Non.CO2,year,sector,fuel) %>%
mutate(share_in_global_ship= value/sum(value)) %>%
ungroup() %>%
# Converts kt(gg) to Teragrams. Multiply by iso's share in international shipping consumption.
mutate(emissions = (emissions * CONV_GG_TG)*share_in_global_ship) %>%
select(-share_in_global_ship,-value)->CEDS_int_shipping
filter(year <= max(HISTORICAL_YEARS), emissions > 0)->CEDS_int_shipping


CEDS_allgas %>%
Expand All @@ -164,8 +156,7 @@ module_emissions_L102.nonco2_ceds_R_S_Y <- function(command, ...) {
gather_years %>%
filter(year %in% emissions.CEDS_YEARS) %>%
# Converts kt(gg) to Teragrams
mutate(emissions = emissions * CONV_GG_TG) %>%
bind_rows(CEDS_int_shipping)->L102.CEDS
mutate(emissions = emissions * CONV_GG_TG)->L102.CEDS


# Aggregate by region, GHG, and CEDS sector
Expand All @@ -192,19 +183,30 @@ module_emissions_L102.nonco2_ceds_R_S_Y <- function(command, ...) {
"L154.IEA_histfut_data_times_UCD_shares") ->
L102.ceds_GFED_nonco2_tg_R_S_F

CEDS_int_shipping %>%
add_title("CEDS international shipping non-CO2 emissions by CEDS sector / fuel / historical year",overwrite = TRUE) %>%
add_units("Tg") %>%
add_precursors("emissions/CEDS/BC_total_CEDS_emissions","emissions/CEDS/OC_total_CEDS_emissions","emissions/CEDS/CO_total_CEDS_emissions",
"emissions/CEDS/NH3_total_CEDS_emissions","emissions/CEDS/NMVOC_total_CEDS_emissions","emissions/CEDS/NOx_total_CEDS_emissions",
"emissions/CEDS/SO2_total_CEDS_emissions","emissions/CEDS/ceds_sector_map","emissions/CEDS/ceds_fuel_map",
"emissions/CEDS/CH4_total_CEDS_emissions") ->
L102.ceds_int_shipping_nonco2_tg_S_F

# verify the calculated data matches the prebuilt version if not a warning
# will be generated and should only be ignored if the underly CEDS data
# actually changed
verify_identical_prebuilt(L102.ceds_GFED_nonco2_tg_R_S_F)
verify_identical_prebuilt(L102.ceds_int_shipping_nonco2_tg_S_F)


}
else {
# raw CEDS datasets not available, so we will use the prebuilt version
L102.ceds_GFED_nonco2_tg_R_S_F <- prebuilt_data("L102.ceds_GFED_nonco2_tg_R_S_F")
L102.ceds_int_shipping_nonco2_tg_S_F <- prebuilt_data("L102.ceds_int_shipping_nonco2_tg_S_F")
}

return_data(L102.ceds_GFED_nonco2_tg_R_S_F)
return_data(L102.ceds_GFED_nonco2_tg_R_S_F, L102.ceds_int_shipping_nonco2_tg_S_F)
} else {
stop("Unknown command")
}
Expand Down
68 changes: 48 additions & 20 deletions input/gcamdata/R/zchunk_L112.ceds_ghg_en_R_S_T_Y.R
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Original file line number Diff line number Diff line change
Expand Up @@ -41,6 +41,7 @@ module_emissions_L112.ceds_ghg_en_R_S_T_Y <- function(command, ...) {
FILE="emissions/CEDS/gains_iso_sector_emissions",
FILE="emissions/CEDS/gains_iso_fuel_emissions",
"L102.ceds_GFED_nonco2_tg_R_S_F",
"L102.ceds_int_shipping_nonco2_tg_S_F",
"L122.LC_bm2_R_HarvCropLand_C_Yh_GLU",
"L101.in_EJ_R_en_Si_F_Yh",
"L107.an_Prod_Mt_R_C_Sys_Fd_Y",
Expand All @@ -60,9 +61,9 @@ module_emissions_L112.ceds_ghg_en_R_S_T_Y <- function(command, ...) {
FILE = "emissions/GCAM_EPA_CH4N2O_energy_map"))
} else if(command == driver.DECLARE_OUTPUTS) {
return(c("L111.nonghg_tg_R_en_S_F_Yh",
"L111.nonghg_tgej_R_en_S_F_Yh",
"L111.nonghg_tgej_R_en_S_F_Yh_infered_combEF_AP",
"L112.ghg_tg_R_en_S_F_Yh",
"L112.ghg_tgej_R_en_S_F_Yh",
"L112.ghg_tgej_R_en_S_F_Yh_infered_combEF_AP",
"L113.ghg_tg_R_an_C_Sys_Fd_Yh",
"L115.nh3_tg_R_an_C_Sys_Fd_Yh",
"L121.nonco2_tg_R_awb_C_Y_GLU",
Expand Down Expand Up @@ -95,7 +96,34 @@ module_emissions_L112.ceds_ghg_en_R_S_T_Y <- function(command, ...) {


#Get CEDS_GFED data
L112.CEDS_GCAM <- get_data(all_data, "L102.ceds_GFED_nonco2_tg_R_S_F")
L112.CEDS_GCAM_no_intl_shipping <- get_data(all_data, "L102.ceds_GFED_nonco2_tg_R_S_F")

#Get CEDS international shipping data
L112.CEDS_intl_shipping <- get_data(all_data, "L102.ceds_int_shipping_nonco2_tg_S_F")
Int_shipping_IEA_EIA <- get_data(all_data, "L154.IEA_histfut_data_times_UCD_shares") %>% filter(UCD_category=="trn_international ship")

# Load required inputs
iso_GCAM_regID <- get_data(all_data, "common/iso_GCAM_regID")

#Process data for international shipping to disaggregate to the GCAM regions
L112.CEDS_intl_shipping %>%
right_join(Int_shipping_IEA_EIA %>% select(iso,year,value) %>% filter(year <= max(HISTORICAL_YEARS)), by=c("year")) %>%
mutate(emissions=if_else(is.na(emissions),0,emissions)) %>%
group_by(Non.CO2,year,sector,fuel) %>%
mutate(share_in_global_ship= value/sum(value)) %>%
ungroup() %>%
# Converts kt(gg) to Teragrams. Multiply by iso's share in international shipping consumption.
mutate(emissions = (emissions * CONV_GG_TG)*share_in_global_ship) %>%
select(-share_in_global_ship,-value) %>%
left_join_error_no_match(iso_GCAM_regID, by = "iso") %>%
group_by(GCAM_region_ID, Non.CO2, CEDS_agg_sector, CEDS_agg_fuel, year) %>%
summarise(emissions = sum(emissions)) %>%
ungroup() %>%
na.omit()->CEDS_int_shipping

#Combine emissions from all other CEDS sectors with emissions from international shipping
L112.CEDS_GCAM_no_intl_shipping %>%
bind_rows(CEDS_int_shipping)->L112.CEDS_GCAM

#In case of tanker loading emissions which are classified as process emissions, transfer them to refined liquids. Same for processs industrial energy emissions
L112.CEDS_GCAM %>%
Expand All @@ -116,7 +144,6 @@ module_emissions_L112.ceds_ghg_en_R_S_T_Y <- function(command, ...) {

# Load required inputs
GCAM_region_names <- get_data(all_data, "common/GCAM_region_names")
iso_GCAM_regID <- get_data(all_data, "common/iso_GCAM_regID")

#Get GAINS sector and fuel emissions by iso. Also get IEA energy data by iso.
GAINS_sector <- get_data(all_data,"emissions/CEDS/gains_iso_sector_emissions")
Expand Down Expand Up @@ -865,14 +892,14 @@ module_emissions_L112.ceds_ghg_en_R_S_T_Y <- function(command, ...) {
L112.nonco2_tgej_R_en_S_F_Yh %>%
filter(Non.CO2 %in% c("CH4", "N2O")) %>%
select(GCAM_region_ID, Non.CO2, supplysector, subsector, stub.technology, year, value = emfact) %>%
bind_rows(GAINS_NG_em_factors %>% filter(Non.CO2 %in% c("CH4", "N2O")) %>% select(-energy))->L112.ghg_tgej_R_en_S_F_Yh
bind_rows(GAINS_NG_em_factors %>% filter(Non.CO2 %in% c("CH4", "N2O")) %>% select(-energy))->L112.ghg_tgej_R_en_S_F_Yh_infered_combEF_AP


L112.nonco2_tgej_R_en_S_F_Yh %>%
filter(!(Non.CO2 %in% c("CH4", "N2O", "CO2"))) %>%
select(GCAM_region_ID, Non.CO2, supplysector, subsector, stub.technology, year, value = emfact) %>%
bind_rows(GAINS_NG_em_factors %>% filter(!(Non.CO2 %in% c("CH4", "N2O"))) %>% select(-energy))->
L111.nonghg_tgej_R_en_S_F_Yh
L111.nonghg_tgej_R_en_S_F_Yh_infered_combEF_AP


# Animal NH3 emissions
Expand Down Expand Up @@ -1002,7 +1029,7 @@ module_emissions_L112.ceds_ghg_en_R_S_T_Y <- function(command, ...) {
# Scale CH4 and N2O emissions to EPA 2019 mitigation report (BAU scenario)
# Source: https://www.epa.gov/global-mitigation-non-co2-greenhouse-gases
# The following tables will be updated by the order below:
# 1) L112.ghg_tgej_R_en_S_F_Yh (resource production emission factors)
# 1) L112.ghg_tgej_R_en_S_F_Yh_infered_combEF_AP (resource production emission factors)
# 2) L131.nonco2_tg_R_prc_S_S_Yh (industrial processes and urban processes input emissions)
# 3) L113.ghg_tg_R_an_C_Sys_Fd_Yh (agriculture livestock - input emissions)
# 4) L121.nonco2_tg_R_awb_C_Y_GLU (agriculture waster burning - input emissions)
Expand Down Expand Up @@ -1077,7 +1104,7 @@ module_emissions_L112.ceds_ghg_en_R_S_T_Y <- function(command, ...) {
select(-EPA_sector, -emscaler)
}

# Part 1: L112.ghg_tgej_R_en_S_F_Yh (resource production emission factors)
# Part 1: L112.ghg_tgej_R_en_S_F_Yh_infered_combEF_AP (resource production emission factors)
#---------------------------------------------------------------------------------------------------------------


Expand Down Expand Up @@ -1125,8 +1152,8 @@ module_emissions_L112.ceds_ghg_en_R_S_T_Y <- function(command, ...) {
select(-upper, -value_median) ->
L112.ghg_tgej_R_en_S_F_Yh_adj_noOutlier

# 4) update L112.ghg_tgej_R_en_S_F_Yh for resource production
L112.ghg_tgej_R_en_S_F_Yh %>%
# 4) update L112.ghg_tgej_R_en_S_F_Yh_infered_combEF_AP for resource production
L112.ghg_tgej_R_en_S_F_Yh_infered_combEF_AP %>%
# produce NA on purpose, since the original data also contain combustion related emission factors
# we just update resource emission factors
left_join(L112.ghg_tgej_R_en_S_F_Yh_adj_noOutlier,
Expand All @@ -1137,7 +1164,7 @@ module_emissions_L112.ceds_ghg_en_R_S_T_Y <- function(command, ...) {


# update the original table
L112.ghg_tgej_R_en_S_F_Yh <- L112.ghg_tgej_R_en_S_F_Yh_update
L112.ghg_tgej_R_en_S_F_Yh_infered_combEF_AP <- L112.ghg_tgej_R_en_S_F_Yh_update

# Part 2: L131.nonco2_tg_R_prc_S_S_Yh (industrial processes and urban processes input emissions)

Expand Down Expand Up @@ -1351,43 +1378,44 @@ module_emissions_L112.ceds_ghg_en_R_S_T_Y <- function(command, ...) {
add_comments("Compute unscaled non-ghg emissions by country and technology, and CEDS emissions by region and sector.") %>%
add_comments("and finally calculate non-ghg emission totals by GCAM sector, fuel, technology, and driver type for CEDS historical years.") %>%
add_legacy_name("L111.nonghg_tg_R_en_S_F_Yh") %>%
add_precursors("L102.ceds_GFED_nonco2_tg_R_S_F","emissions/CEDS/ceds_sector_map","emissions/CEDS/ceds_fuel_map", "common/GCAM_region_names",
add_precursors("L102.ceds_GFED_nonco2_tg_R_S_F", "L102.ceds_int_shipping_nonco2_tg_S_F", "emissions/CEDS/ceds_sector_map","emissions/CEDS/ceds_fuel_map", "common/GCAM_region_names",
"common/iso_GCAM_regID","energy/mappings/UCD_techs","energy/calibrated_techs","energy/calibrated_techs_bld_det",
"emissions/mappings/Trn_subsector","emissions/CEDS/CEDS_sector_tech_combustion","emissions/mappings/Trn_subsector_revised",
"emissions/mappings/CEDS_sector_tech_proc","emissions/mappings/calibrated_outresources","emissions/mappings/CEDS_sector_tech_proc_revised",
"L101.in_EJ_R_en_Si_F_Yh","emissions/CEDS/CEDS_sector_tech_combustion_revised","emissions/mappings/UCD_techs_emissions_revised","L154.IEA_histfut_data_times_UCD_shares",
"emissions/CEDS/gains_iso_sector_emissions","emissions/CEDS/gains_iso_fuel_emissions") ->
L111.nonghg_tg_R_en_S_F_Yh

L111.nonghg_tgej_R_en_S_F_Yh %>%
L111.nonghg_tgej_R_en_S_F_Yh_infered_combEF_AP %>%
na.omit() %>%
add_title("Non-ghg emission total shares by GCAM sector, fuel, technology, and driver type for CEDS historical years.") %>%
add_units("Tg/EJ") %>%
add_comments("Use non-ghg emission totals by GCAM sector, fuel, technology, and driver type for CEDS historical years to derive emission shares.") %>%
add_legacy_name("L111.nonghg_tgej_R_en_S_F_Yh") %>%
same_precursors_as("L111.nonghg_tg_R_en_S_F_Yh") ->
L111.nonghg_tgej_R_en_S_F_Yh
L111.nonghg_tgej_R_en_S_F_Yh_infered_combEF_AP

L112.ghg_tg_R_en_S_F_Yh %>%
add_title("GHG emissions by energy sector, gas, region, and historical year") %>%
add_units("Tg") %>%
add_comments("Emissions calculated with CEDS totals") %>%
add_legacy_name("L112.ghg_tg_R_en_S_F_Yh") %>%
add_precursors("L102.ceds_GFED_nonco2_tg_R_S_F","emissions/CEDS/ceds_sector_map","emissions/CEDS/ceds_fuel_map", "common/GCAM_region_names",
add_precursors("L102.ceds_GFED_nonco2_tg_R_S_F","L102.ceds_int_shipping_nonco2_tg_S_F","emissions/CEDS/ceds_sector_map","emissions/CEDS/ceds_fuel_map", "common/GCAM_region_names",
"common/iso_GCAM_regID","energy/mappings/UCD_techs","energy/calibrated_techs","energy/calibrated_techs_bld_det",
"emissions/mappings/Trn_subsector","emissions/CEDS/CEDS_sector_tech_combustion","emissions/mappings/calibrated_outresources",
"L101.in_EJ_R_en_Si_F_Yh", "emissions/mappings/Trn_subsector_revised", "emissions/EPA/EPA_2019_raw", "emissions/EPA_CH4N2O_map",
"emissions/CEDS/CEDS_sector_tech_combustion_revised","emissions/mappings/UCD_techs_emissions_revised","L154.IEA_histfut_data_times_UCD_shares",
"emissions/CEDS/gains_iso_sector_emissions","emissions/CEDS/gains_iso_fuel_emissions") ->
L112.ghg_tg_R_en_S_F_Yh

L112.ghg_tgej_R_en_S_F_Yh %>%
L112.ghg_tgej_R_en_S_F_Yh_infered_combEF_AP %>%
add_title("GHG emissions factors by energy sector, gas, region, and historical year") %>%
add_units("Tg/EJ") %>%
add_comments("Emissions calculated with CEDS emissions factors.") %>%
add_comments("Then, emissions factors computed by dividing calculated emissions by energy data") %>%
add_legacy_name("L112.ghg_tgej_R_en_S_F_Yh") %>%
add_precursors("L102.ceds_GFED_nonco2_tg_R_S_F",
"L102.ceds_int_shipping_nonco2_tg_S_F",
"emissions/CEDS/ceds_sector_map",
"emissions/CEDS/ceds_fuel_map",
"common/GCAM_region_names",
Expand All @@ -1406,7 +1434,7 @@ module_emissions_L112.ceds_ghg_en_R_S_T_Y <- function(command, ...) {
"emissions/EPA_country_map",
"emissions/CEDS/CEDS_sector_tech_combustion_revised",
"emissions/mappings/UCD_techs_emissions_revised") ->
L112.ghg_tgej_R_en_S_F_Yh
L112.ghg_tgej_R_en_S_F_Yh_infered_combEF_AP

L113.ghg_tg_R_an_C_Sys_Fd_Yh %>%
add_title("Animal GHG emissions (CH4 and N2O) by GCAM region / sector / technology / historical year") %>%
Expand All @@ -1417,7 +1445,7 @@ module_emissions_L112.ceds_ghg_en_R_S_T_Y <- function(command, ...) {
add_comments("Fourth: compute CEDS emissions by region and sector") %>%
add_comments("Fifth: scale EPA emissions by tech to match CEDS") %>%
add_legacy_name("L113.ghg_tg_R_an_C_Sys_Fd_Yh") %>%
add_precursors("L102.ceds_GFED_nonco2_tg_R_S_F","emissions/CEDS/ceds_sector_map","emissions/CEDS/ceds_fuel_map", "common/GCAM_region_names",
add_precursors("L102.ceds_GFED_nonco2_tg_R_S_F","L102.ceds_int_shipping_nonco2_tg_S_F","emissions/CEDS/ceds_sector_map","emissions/CEDS/ceds_fuel_map", "common/GCAM_region_names",
"common/iso_GCAM_regID","emissions/CEDS/CEDS_sector_tech_combustion", "emissions/CEDS/CEDS_sector_tech_combustion_revised",
"emissions/mappings/CEDS_sector_tech_proc", "L107.an_Prod_Mt_R_C_Sys_Fd_Y","emissions/mappings/CEDS_sector_tech_proc_revised",
"L103.ghg_tgmt_USA_an_Sepa_F_2005") ->
Expand All @@ -1429,7 +1457,7 @@ module_emissions_L112.ceds_ghg_en_R_S_T_Y <- function(command, ...) {
add_units("Tg") %>%
add_comments("Annual animal NH3 emissions is computed using CEDS emissions and FAO animal production.") %>%
add_legacy_name("L115.nh3_tg_R_an_C_Sys_Fd_Yh") %>%
add_precursors("L102.ceds_GFED_nonco2_tg_R_S_F","emissions/CEDS/ceds_sector_map","emissions/CEDS/ceds_fuel_map", "common/GCAM_region_names",
add_precursors("L102.ceds_GFED_nonco2_tg_R_S_F","L102.ceds_int_shipping_nonco2_tg_S_F","emissions/CEDS/ceds_sector_map","emissions/CEDS/ceds_fuel_map", "common/GCAM_region_names",
"common/iso_GCAM_regID","emissions/CEDS/CEDS_sector_tech_combustion","emissions/CEDS/CEDS_sector_tech_combustion_revised",
"L107.an_Prod_Mt_R_C_Sys_Fd_Y","L107.an_Prod_Mt_R_C_Sys_Fd_Y") ->
L115.nh3_tg_R_an_C_Sys_Fd_Yh
Expand Down Expand Up @@ -1546,7 +1574,7 @@ module_emissions_L112.ceds_ghg_en_R_S_T_Y <- function(command, ...) {
) ->
L131.nonco2_tg_R_prc_S_S_Yh

return_data(L111.nonghg_tg_R_en_S_F_Yh, L111.nonghg_tgej_R_en_S_F_Yh, L112.ghg_tg_R_en_S_F_Yh, L112.ghg_tgej_R_en_S_F_Yh, L113.ghg_tg_R_an_C_Sys_Fd_Yh, L115.nh3_tg_R_an_C_Sys_Fd_Yh, L121.nonco2_tg_R_awb_C_Y_GLU,
return_data(L111.nonghg_tg_R_en_S_F_Yh, L111.nonghg_tgej_R_en_S_F_Yh_infered_combEF_AP, L112.ghg_tg_R_en_S_F_Yh, L112.ghg_tgej_R_en_S_F_Yh_infered_combEF_AP, L113.ghg_tg_R_an_C_Sys_Fd_Yh, L115.nh3_tg_R_an_C_Sys_Fd_Yh, L121.nonco2_tg_R_awb_C_Y_GLU,
L121.AWBshare_R_C_Y_GLU, L122.ghg_tg_R_agr_C_Y_GLU, L122.EmissShare_R_C_Y_GLU, L124.nonco2_tg_R_grass_Y_GLU, L124.nonco2_tg_R_forest_Y_GLU, L124.deforest_coefs,
L131.nonco2_tg_R_prc_S_S_Yh,L125.bcoc_tgbkm2_R_grass_2000,L125.bcoc_tgbkm2_R_forest_2000,L125.deforest_coefs_bcoc)
} else {
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