R/zchunk_L243.bio_trade_input.R
In JGCRI/gcamdata: Build the GCAM Input Datasets
Defines functions
module_aglu_L243.bio_trade_input
Documented in
module_aglu_L243.bio_trade_input
# Copyright 2019 Battelle Memorial Institute; see the LICENSE file.
#' module_aglu_L243.bio_trade_input
#'
#' Establish regionally differentiated trade structure for bioenergy.
#'
#' @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{L243.DeleteInput_RegBio}, \code{L243.SectorLogitTables[[
#' curr_table ]]$data}, \code{L243.TechCoef_RegBio}, \code{L243.Supplysector_Bio},
#' \code{L243.SectorUseTrialMarket_Bio}, \code{L243.SubsectorLogitTables[[ curr_table ]]$data},
#' \code{L243.SubsectorLogit_Bio}, \code{L243.SubsectorShrwt_TotBio}, \code{L243.SubsectorShrwtFllt_TradedBio},
#' \code{L243.GlobalTechCoef_TotBio}, \code{L243.GlobalTechShrwt_TotBio}, \code{L243.StubTech_TotBio},
#' \code{L243.StubTechShrwt_TotBio}, \code{L243.StubTechCoef_ImportedBio}, \code{L243.StubTechCoef_DomesticBio},
#' \code{L243.TechCoef_TradedBio}, \code{L243.TechShrwt_TradedBio}, \code{L243.SubsectorShrwt_TotBio_SSP4},
#' \code{L243.SubsectorShrwtFllt_TradedBio_SSP4}, \code{L243.SubsectorShrwt_TotBio_SSP3},
#' \code{L243.StubTechShrwt_TotBio_SSP3}, \code{L243.Supplysector_reg_SSP4}, \code{L243.SubsectorInterpTo_tra_SSP4}.
#' The corresponding file in the original data system was \code{L243.bio_trade_input.R} (aglu level2).
#' @details This chunk sets up a structure for regionally differentiated bioenergy trade. Each
#' region consumes a blend of domestic and international bioenergy. Regions can supply to either
#' the domestic or international market. Share weights in the default case depend on the amount of
#' cropland a region has, with the largest region having a share weight of 1. Share weights in SSP3
#' and SSP4 are adjusted to reflect the trade frictions in the SSP storylines.
#' @importFrom assertthat assert_that
#' @importFrom dplyr bind_rows filter full_join if_else group_by left_join mutate select summarize
#' @importFrom tidyr replace_na
#' @author KVC July 2017
module_aglu_L243.bio_trade_input <- function(command, ...) {
if(command == driver.DECLARE_INPUTS) {
return(c(FILE = "common/GCAM_region_names",
FILE = "aglu/A_bio_supplysector",
FILE = "aglu/A_bio_subsector_logit",
FILE = "aglu/A_bio_subsector",
FILE = "aglu/A_agRegionalSector",
FILE = "aglu/A_agTradedSubsector",
"L120.LC_bm2_R_LT_Yh_GLU",
"L102.pcgdp_thous90USD_Scen_R_Y"))
} else if(command == driver.DECLARE_OUTPUTS) {
return(c("L243.DeleteInput_RegBio",
"L243.TechCoef_RegBio",
"L243.Supplysector_Bio",
"L243.SectorUseTrialMarket_Bio",
"L243.SubsectorLogit_Bio",
"L243.SubsectorShrwt_TotBio",
"L243.SubsectorShrwtFllt_TradedBio",
"L243.GlobalTechCoef_TotBio",
"L243.GlobalTechShrwt_TotBio",
"L243.StubTech_TotBio",
"L243.StubTechShrwt_TotBio",
"L243.StubTechCoef_ImportedBio",
"L243.StubTechCoef_DomesticBio",
"L243.TechCoef_TradedBio",
"L243.TechShrwt_TradedBio",
"L243.SubsectorShrwt_TotBio_SSP4",
"L243.SubsectorShrwtFllt_TradedBio_SSP4",
"L243.SubsectorShrwt_TotBio_SSP3",
"L243.StubTechShrwt_TotBio_SSP3",
"L243.Supplysector_reg_SSP4",
"L243.SubsectorInterpTo_tra_SSP4"))
} else if(command == driver.MAKE) {
all_data <- list(...)[[1]]
region <- traded <- subsector.name <- sector.name <- technology <- year <- subsector <-
share.weight <- supplysector <- MORE <- market.name <- Land_Type <- GCAM_region_ID <-
value <- Cropland <- year.fillout <- trade.region <- NULL # silence package check notes
# Load required inputs
GCAM_region_names <- get_data(all_data, "common/GCAM_region_names", strip_attributes = TRUE)
A_bio_supplysector <- get_data(all_data, "aglu/A_bio_supplysector", strip_attributes = TRUE)
A_bio_subsector_logit <- get_data(all_data, "aglu/A_bio_subsector_logit", strip_attributes = TRUE)
A_bio_subsector <- get_data(all_data, "aglu/A_bio_subsector")
A_agRegionalSector <- get_data(all_data, "aglu/A_agRegionalSector", strip_attributes = TRUE)
A_agTradedSubsector <- get_data(all_data, "aglu/A_agTradedSubsector", strip_attributes = TRUE)
L120.LC_bm2_R_LT_Yh_GLU <- get_data(all_data, "L120.LC_bm2_R_LT_Yh_GLU")
L102.pcgdp_thous90USD_Scen_R_Y <- get_data(all_data, "L102.pcgdp_thous90USD_Scen_R_Y")
# Note: I'm pulling out all of the hard-coded GCAM sector names used in this file to the top so it is clearer
OLD.REGIONAL.BIOMASS.NAME <- "regional biomass"
NEW.REGIONAL.BIOMASS.NAME <- "total biomass"
TRADED.BIOMASS.NAME <- "traded biomass"
BIOMASS.NAME <- "biomass"
BIOMASS.TRADE.REGION <- gcam.USA_REGION
DOMESTIC.BIOMASS.NAME <- "domestic biomass"
INTERNATIONAL.BIOMASS.NAME <- "imported biomass"
# First, create a table to delete existing regional biomass input (this needs to include region/sector/subsector/technology/input for all regions & years)
GCAM_region_names %>%
select(region) %>%
mutate(supplysector = OLD.REGIONAL.BIOMASS.NAME, subsector = OLD.REGIONAL.BIOMASS.NAME, technology = OLD.REGIONAL.BIOMASS.NAME) %>%
repeat_add_columns(tibble(year = MODEL_YEARS)) %>%
mutate(minicam.energy.input = BIOMASS.NAME) ->
L243.DeleteInput_RegBio
# Set up all of the new supply sectors.
# Copy sector information to each region.
# Note that "traded biomass" only goes in the BIOMASS.TRADE.REGION
A_bio_supplysector %>%
repeat_add_columns(tibble(region = GCAM_region_names$region)) %>%
mutate(region = if_else(traded == 1, BIOMASS.TRADE.REGION, region),
logit.year.fillout = min(MODEL_YEARS)) %>%
select(-traded) ->
L243.Supplysector_Bio
# Now, create new regional biomass with input called "total biomass" with a input-output coefficient of 1 (i.e., a pass through sector)
L243.DeleteInput_RegBio %>%
mutate(minicam.energy.input = NEW.REGIONAL.BIOMASS.NAME,
coefficient = 1,
market.name = region) ->
L243.TechCoef_RegBio
# Set up the technologies for the new regional biomass sector ("total biomass")
# This sector will include a domestic component and an international component. The domestic component
# consumes "biomass" directly, while the international consumes "traded biomass".
# These technologies have input-output coefficients of 1 (i.e., pass through sectors)
tibble(sector.name = NEW.REGIONAL.BIOMASS.NAME) %>%
repeat_add_columns(tibble(subsector.name = c(DOMESTIC.BIOMASS.NAME, INTERNATIONAL.BIOMASS.NAME))) %>%
mutate(technology = subsector.name) %>%
repeat_add_columns(tibble(year = MODEL_YEARS)) %>%
mutate(minicam.energy.input = if_else(subsector.name == DOMESTIC.BIOMASS.NAME, BIOMASS.NAME, TRADED.BIOMASS.NAME),
coefficient = 1) ->
L243.GlobalTechCoef_TotBio
# Add share-weights to the global technologies
L243.GlobalTechCoef_TotBio %>%
select(sector.name, subsector.name, technology, year) %>%
# note the competition between import and domestic happens at the subsector nest
# so share weights are not consequential here
mutate(share.weight = 1.0) ->
L243.GlobalTechShrwt_TotBio
# Set up stub-technologies
tibble(supplysector = NEW.REGIONAL.BIOMASS.NAME) %>%
repeat_add_columns(tibble(subsector = c(DOMESTIC.BIOMASS.NAME, INTERNATIONAL.BIOMASS.NAME))) %>%
mutate(stub.technology = subsector) %>%
repeat_add_columns(tibble(region = GCAM_region_names$region)) ->
L243.StubTech_TotBio
# Share weights for the regional biomass technologies
L243.StubTech_TotBio %>%
repeat_add_columns(tibble(year = MODEL_YEARS)) %>%
mutate(share.weight = 1) ->
L243.StubTechShrwt_TotBio
# Stub technologies for the regional biomass technologies
L243.StubTech_TotBio %>%
filter(subsector == INTERNATIONAL.BIOMASS.NAME) %>%
repeat_add_columns(tibble(year = MODEL_YEARS)) %>%
mutate(minicam.energy.input = TRADED.BIOMASS.NAME,
coefficient = 1,
market = BIOMASS.TRADE.REGION) ->
L243.StubTechCoef_ImportedBio
# Stub technologies for the regional biomass technologies
L243.StubTech_TotBio %>%
filter(subsector == DOMESTIC.BIOMASS.NAME) %>%
repeat_add_columns(tibble(year = MODEL_YEARS)) %>%
mutate(minicam.energy.input = BIOMASS.NAME,
coefficient = 1,
market = region) ->
L243.StubTechCoef_DomesticBio
# The traded markets tend to be a good candidate to solve explicitly since they tie together many solved markets.
# Set flag so traded biomass uses trial markets
A_bio_supplysector %>%
filter(traded == 1) %>%
select(supplysector) %>%
mutate(region = BIOMASS.TRADE.REGION, use.trial.market = 1) ->
L243.SectorUseTrialMarket_Bio
# Set up all of the new subsectors.
# Copy subsector information to each region.
# Note that "traded biomass" only goes in the BIOMASS.TRADE.REGION, but the subsector name includes the original region name
A_bio_subsector_logit %>%
repeat_add_columns(tibble(region = GCAM_region_names$region)) %>%
mutate(subsector = if_else(traded == 1, paste(region, subsector), subsector),
region = if_else(traded == 1, BIOMASS.TRADE.REGION, region),
logit.year.fillout = min(MODEL_YEARS)) %>%
select(-traded) ->
L243.SubsectorLogit_Bio
# Share weights for the regional biomass subsectors
L243.StubTech_TotBio %>%
select(region, supplysector, subsector) %>%
repeat_add_columns(tibble(year=MODEL_YEARS)) %>%
# expecting NAs for all the years that need to be filled in
left_join(gather_years(A_bio_subsector, "share.weight"), by = c("supplysector", "subsector", "year")) %>%
group_by(region, supplysector, subsector) %>%
mutate(share.weight = approx_fun(year, share.weight)) %>%
ungroup() ->
L243.SubsectorShrwt_TotBio
# Input name, market, coeff for traded biomass
tibble(region = BIOMASS.TRADE.REGION, supplysector = TRADED.BIOMASS.NAME) %>%
mutate(minicam.energy.input = BIOMASS.NAME,
coefficient = 1) %>%
repeat_add_columns(tibble(market.name = GCAM_region_names$region)) %>%
repeat_add_columns(tibble(year = MODEL_YEARS)) %>%
mutate(subsector = paste(market.name, TRADED.BIOMASS.NAME),
technology = subsector) ->
L243.TechCoef_TradedBio
# Compute share weights for subsectors based on cropland area. Largest region gets shareweight of 1.
# This will mean that international biomass supply is roughly proportional to
# cropland area (larger regions produce more biomass).
L120.LC_bm2_R_LT_Yh_GLU %>%
filter(Land_Type == "Cropland", year == max(HISTORICAL_YEARS)) %>%
group_by(GCAM_region_ID) %>%
summarize(Cropland = sum(value)) %>%
ungroup() %>%
mutate(share.weight = Cropland / max(Cropland)) %>%
full_join(GCAM_region_names, by = "GCAM_region_ID") %>% # Using full join to ensure regions without cropland show up
replace_na(list(share.weight = 0)) %>% # Assign regions without land a shareweight of 0 (i.e., they won't contribute to international bio supply)
select(-GCAM_region_ID, -Cropland) %>%
mutate(supplysector = TRADED.BIOMASS.NAME,
subsector = paste(region, TRADED.BIOMASS.NAME),
region = BIOMASS.TRADE.REGION,
year.fillout = min(MODEL_YEARS)) ->
L243.SubsectorShrwtFllt_TradedBio
# Set share weights for technologies in the traded biomass sector to 1
# This is because competition is handled at the subsector level
L243.SubsectorShrwtFllt_TradedBio %>%
mutate(technology = subsector, share.weight = 1) %>%
select(-year.fillout) %>%
repeat_add_columns(tibble(year = MODEL_YEARS)) ->
L243.TechShrwt_TradedBio
# Set share weights for total biomass in SSP4 low income regions.
# SSP4 assumes limited trade with low income regions; so, share weights are set to 0.1
# See Calvin et al. (2017) for documentation. https://doi.org/10.1016/j.gloenvcha.2016.06.010
L243.SubsectorShrwt_TotBio %>%
filter(region %in% get_ssp_regions(L102.pcgdp_thous90USD_Scen_R_Y, GCAM_region_names, "low"),
subsector == "imported biomass") %>%
mutate(share.weight = if_else(year >= aglu.BIO_TRADE_SSP4_YEAR_FILLOUT, 0.1, share.weight)) ->
L243.SubsectorShrwt_TotBio_SSP4_lo
L243.SubsectorShrwtFllt_TradedBio %>%
mutate(trade.region = gsub(" traded biomass", "", subsector)) %>%
filter(trade.region %in% get_ssp_regions(L102.pcgdp_thous90USD_Scen_R_Y, GCAM_region_names, "low")) %>%
mutate(year.fillout = aglu.BIO_TRADE_SSP4_YEAR_FILLOUT, share.weight = 0.1) %>%
select(-trade.region) ->
L243.SubsectorShrwtFllt_TradedBio_SSP4
# Set share weights for total biomass in SSP4 high and medium income regions.
# SSP4 assumes free trade within high income regions; so, subsector share weights are set to 0.5
# (tech shareweights are not relevant as there is only one tech per subsector)
# See Calvin et al. (2017) for documentation. https://doi.org/10.1016/j.gloenvcha.2016.06.010
L243.SubsectorShrwt_TotBio %>%
filter(region %in% c(get_ssp_regions(L102.pcgdp_thous90USD_Scen_R_Y, GCAM_region_names, "high"),
get_ssp_regions(L102.pcgdp_thous90USD_Scen_R_Y, GCAM_region_names, "medium")),
subsector == "imported biomass") %>%
mutate(share.weight = if_else(year >= aglu.BIO_TRADE_SSP4_YEAR_FILLOUT, 0.5, share.weight)) ->
L243.SubsectorShrwt_TotBio_SSP4_hi
# Bind SSP4 share weights for all regions into single data frames
bind_rows(L243.SubsectorShrwt_TotBio_SSP4_hi, L243.SubsectorShrwt_TotBio_SSP4_lo) ->
L243.SubsectorShrwt_TotBio_SSP4
# Set share weights for total biomass in SSP3.
# SSP3 assumes limited trade across regions; so, share weights are set to 0.1
# See Calvin et al. (2017) for documentation. https://doi.org/10.1016/j.gloenvcha.2016.06.010
L243.SubsectorShrwt_TotBio %>%
filter(subsector == "imported biomass") %>%
mutate(share.weight = if_else(year >= aglu.BIO_TRADE_SSP4_YEAR_FILLOUT, 0.1, share.weight)) ->
L243.SubsectorShrwt_TotBio_SSP3
L243.StubTechShrwt_TotBio %>%
filter(subsector == "imported biomass", year >= aglu.BIO_TRADE_SSP3_YEAR_FILLOUT) %>%
mutate(share.weight = 0.1) ->
L243.StubTechShrwt_TotBio_SSP3
# SSP4 ag trade - reduce the logit exponents for the decision between imports and consumption of domestic
# production, in low income regions
SSP4_AG_LOGIT_IMPORT_LOW <- -1.5
L243.Supplysector_reg_SSP4 <- mutate(A_agRegionalSector, logit.year.fillout = min(MODEL_BASE_YEARS)) %>%
write_to_all_regions(c(LEVEL2_DATA_NAMES[["Supplysector"]], "logit.type"),
filter(GCAM_region_names, region %in% get_ssp_regions(L102.pcgdp_thous90USD_Scen_R_Y, GCAM_region_names, "low"))) %>%
mutate(logit.exponent = SSP4_AG_LOGIT_IMPORT_LOW)
# SSP4 ag trade, cont'd - for the export market (sharing regions), decrease the share-weights from their base-year
# calibrated values towards zero in some year beyond the analysis window
SSP4_ZERO_EXPORT_YEAR_LOW <- 2150
A_agTradedSubsector_SSP4 <- mutate(A_agTradedSubsector, to.value = 0,
to.year = SSP4_ZERO_EXPORT_YEAR_LOW,
interpolation.function = "linear")
L243.SubsectorInterpTo_tra_SSP4 <- write_to_all_regions(A_agTradedSubsector_SSP4,
LEVEL2_DATA_NAMES[["SubsectorInterpTo"]],
filter(GCAM_region_names, region %in% get_ssp_regions(L102.pcgdp_thous90USD_Scen_R_Y, GCAM_region_names, "low")),
has_traded = TRUE) %>%
mutate(region = gcam.USA_REGION) # need to manually set the region name to gcam.USA_REGION, where the traded commodities are housed
# Produce outputs
L243.DeleteInput_RegBio %>%
add_title("Table of regional biomass sector/subsector/technology/year for deletion") %>%
add_units("NA") %>%
add_comments("List all region/year combinations for the regional biomass sector/subsector/technology") %>%
add_comments("We need to rename the input from 'biomass' to 'total biomass' so we can separate trade.") %>%
add_comments("We also want to change the market from global to regional.") %>%
add_comments("The only way to do this in the model is to delete these technologies and re-add them with the right input and market-name.") %>%
add_legacy_name("L243.DeleteInput_RegBio") %>%
add_precursors("common/GCAM_region_names") ->
L243.DeleteInput_RegBio
L243.TechCoef_RegBio %>%
add_title("Table creating new 'traded biomass' sector/subsector/technology coefficients") %>%
add_units("Unitless") %>%
add_comments("Copy the L243.DeleteInput_RegBio table. Update the name of the input to 'total biomass'.") %>%
add_comments("Add the input-output coefficient (equals 1 since this is a pass through sector).") %>%
add_comments("Add the market name (equal to the region name since trade is no longer global).") %>%
add_legacy_name("L243.TechCoef_RegBio") %>%
same_precursors_as(L243.DeleteInput_RegBio) ->
L243.TechCoef_RegBio
L243.Supplysector_Bio %>%
add_title("Units and logit exponents for bio trade supply sectors") %>%
add_units("NA") %>%
add_comments("Copy bio trade assumption file to all regions") %>%
add_comments("Replace region name for 'traded biomass' with the trade region (currently USA).") %>%
add_legacy_name("L243.Supplysector_Bio") %>%
add_precursors("common/GCAM_region_names", "aglu/A_bio_supplysector") ->
L243.Supplysector_Bio
L243.SectorUseTrialMarket_Bio %>%
add_title("Table flagging traded biomass sector to use trial markets") %>%
add_units("NA") %>%
add_comments("Create a table with the traded biomass sector and a boolean (1) for use.trial.markets") %>%
add_legacy_name("L243.SectorUseTrialMarket_Bio") %>%
add_precursors("aglu/A_bio_supplysector") ->
L243.SectorUseTrialMarket_Bio
L243.SubsectorLogit_Bio %>%
add_title("Logit exponents for bio trade subsectors") %>%
add_units("unitless") %>%
add_comments("Copy bio trade subsector assumption file to all regions") %>%
add_comments("Modify subsector name to include the region for the 'traded biomass' sectors.") %>%
add_comments("Replace region name for 'traded biomass' with the trade region (currently USA).") %>%
add_legacy_name("L243.SubsectorLogit_Bio") %>%
add_precursors("common/GCAM_region_names", "aglu/A_bio_subsector_logit") ->
L243.SubsectorLogit_Bio
L243.SubsectorShrwt_TotBio %>%
add_title("Subsector share weights for the total biomass sector") %>%
add_units("unitless") %>%
add_comments("Map the share weights specified in the assumption file to all subsectors") %>%
add_precursors("aglu/A_bio_subsector") %>%
same_precursors_as("L243.StubTech_TotBio") ->
L243.SubsectorShrwt_TotBio
L243.SubsectorShrwtFllt_TradedBio %>%
add_title("Subsector shareweights for traded biomass sector") %>%
add_units("unitless") %>%
add_comments("Use cropland area in the final historical year to calculate shareweights.") %>%
add_comments("Share weights are proportional to cropland area, with the region with") %>%
add_comments("the largest cropland area assigned a share weight of 1.") %>%
add_legacy_name("L243.SubsectorShrwtFllt_TradedBio") %>%
add_precursors("common/GCAM_region_names", "L120.LC_bm2_R_LT_Yh_GLU") ->
L243.SubsectorShrwtFllt_TradedBio
L243.GlobalTechCoef_TotBio %>%
add_title("Total biomass technology coefficients") %>%
add_units("unitless") %>%
add_comments("Create table with 'domestic' and 'international' biomass subsectors.") %>%
add_comments("Set minicam.energy.input for both types of subsector.") %>%
add_comments("Set input-output coefficients to 1.") %>%
add_comments("Copy to all model years.") %>%
add_legacy_name("L243.GlobalTechCoef_TotBio") ->
L243.GlobalTechCoef_TotBio
L243.GlobalTechShrwt_TotBio %>%
add_title("Share weights for domestic and imported biomass") %>%
add_units("unitless") %>%
add_comments("Copy L243.GlobalTechCoef_TotBio. Set share weights based on an assumption file") %>%
add_legacy_name("L243.GlobalTechShrwt_TotBio") %>%
same_precursors_as("L243.GlobalTechCoef_TotBio") ->
L243.GlobalTechShrwt_TotBio
L243.StubTech_TotBio %>%
add_title("Stub technologies for the 'total biomass' sector") %>%
add_units("NA") %>%
add_comments("Copy technology names to all regions") %>%
add_legacy_name("L243.StubTech_TotBio") %>%
add_precursors("common/GCAM_region_names") ->
L243.StubTech_TotBio
L243.StubTechShrwt_TotBio %>%
add_title("Share weights for the total biomass sector") %>%
add_units("NA") %>%
add_comments("Set share weight for 'total biomass' technologies equal to 1 in all regions") %>%
add_legacy_name("L243.StubTechShrwt_TotBio") %>%
same_precursors_as("L243.StubTech_TotBio") ->
L243.StubTechShrwt_TotBio
L243.StubTechCoef_ImportedBio %>%
add_title("Input-output coefficients for imported biomass technologies") %>%
add_units("unitless") %>%
add_comments("Filter L243.StubTech_TotBio for the imported biomass sector") %>%
add_comments("Set coefficients to 1 and market name to the traded region (currently USA)") %>%
add_legacy_name("L243.StubTechCoef_ImportedBio") %>%
same_precursors_as("L243.StubTech_TotBio") ->
L243.StubTechCoef_ImportedBio
L243.StubTechCoef_DomesticBio %>%
add_title("Input-output coefficients for domestic biomass technologies") %>%
add_units("unitless") %>%
add_comments("Filter L243.StubTech_TotBio for the domestic biomass sector") %>%
add_comments("Set coefficients to 1 and market name to region name") %>%
add_legacy_name("L243.StubTechCoef_DomesticBio") %>%
same_precursors_as("L243.StubTech_TotBio") ->
L243.StubTechCoef_DomesticBio
L243.TechCoef_TradedBio %>%
add_title("Input-Output coefficients for traded biomass technologies") %>%
add_units("unitless") %>%
add_comments("Assign coefficient of 1 to all traded biomass technologies in all years") %>%
add_legacy_name("L243.TechCoef_TradedBio") %>%
add_precursors("common/GCAM_region_names") ->
L243.TechCoef_TradedBio
L243.TechShrwt_TradedBio %>%
add_title("Technology shareweights for the traded biomass sector") %>%
add_units("unitless") %>%
add_comments("Use the region & subsector names from 'L243.SubsectorShrwtFllt_TradedBio") %>%
add_comments("Set all share weights to 1 since competition is handled at subsector level.") %>%
add_legacy_name("L243.TechShrwt_TradedBio") %>%
same_precursors_as("L243.SubsectorShrwtFllt_TradedBio") ->
L243.TechShrwt_TradedBio
L243.SubsectorShrwt_TotBio_SSP4 %>%
add_title("Subsector shareweights for total bioenergy in SSP4") %>%
add_units("unitless") %>%
add_comments("Uses the structure of L243.SubsectorShrwt_TotBio") %>%
add_comments("Replace shareweights with assumed coefficients (0.1 for low income, 0.5 for high income)") %>%
same_precursors_as("L243.SubsectorShrwt_TotBio") %>%
add_precursors("common/GCAM_region_names", "L102.pcgdp_thous90USD_Scen_R_Y") ->
L243.SubsectorShrwt_TotBio_SSP4
L243.SubsectorShrwtFllt_TradedBio_SSP4 %>%
add_title("Subsector shareweights for traded bioenergy in SSP4") %>%
add_units("unitless") %>%
add_comments("Uses the structure of L243.SubsectorShrwtFllt_TradedBio") %>%
add_comments("Replace shareweights with assumed coefficients (0.1 for low income, 0.5 for high income)") %>%
add_legacy_name("L243.SubsectorShrwtFllt_TradedBio_SSP4") %>%
same_precursors_as("L243.SubsectorShrwtFllt_TradedBio") %>%
add_precursors("common/GCAM_region_names", "L102.pcgdp_thous90USD_Scen_R_Y") ->
L243.SubsectorShrwtFllt_TradedBio_SSP4
L243.SubsectorShrwt_TotBio_SSP3 %>%
add_title("Subsector shareweights for total bioenergy in SSP3") %>%
add_units("unitless") %>%
add_comments("Uses the structure of L243.SubsectorShrwt_TotBio") %>%
add_comments("Replace shareweights with assumed coefficients (0.1)") %>%
same_precursors_as("L243.SubsectorShrwt_TotBio") ->
L243.SubsectorShrwt_TotBio_SSP3
L243.StubTechShrwt_TotBio_SSP3 %>%
add_title("Technology shareweights for total bioenergy in SSP3") %>%
add_units("unitless") %>%
add_comments("Uses the structure of L243.StubTechShrwt_TotBio") %>%
add_comments("Replace shareweights with assumed coefficients (0.1)") %>%
add_legacy_name("L243.StubTechShrwt_TotBio_SSP3") %>%
same_precursors_as("L243.StubTechShrwt_TotBio") ->
L243.StubTechShrwt_TotBio_SSP3
L243.Supplysector_reg_SSP4 %>%
add_title("Supplysector info for regional crop markets w modified logits for SSP4") %>%
add_units("unitless") %>%
add_comments("Only applies to low-income regions") %>%
add_precursors("common/GCAM_region_names", "aglu/A_agRegionalSector") ->
L243.Supplysector_reg_SSP4
L243.SubsectorInterpTo_tra_SSP4 %>%
add_title("Subsector interpolation info for traded crop markets w modified share-weights for SSP4") %>%
add_units("unitless") %>%
add_comments("Only applies to low-income regions") %>%
add_precursors("common/GCAM_region_names", "aglu/A_agTradedSubsector") ->
L243.SubsectorInterpTo_tra_SSP4
return_data(L243.DeleteInput_RegBio,
L243.TechCoef_RegBio,
L243.Supplysector_Bio,
L243.SectorUseTrialMarket_Bio,
L243.SubsectorLogit_Bio,
L243.SubsectorShrwt_TotBio,
L243.SubsectorShrwtFllt_TradedBio,
L243.GlobalTechCoef_TotBio,
L243.GlobalTechShrwt_TotBio,
L243.StubTech_TotBio,
L243.StubTechShrwt_TotBio,
L243.StubTechCoef_ImportedBio,
L243.StubTechCoef_DomesticBio,
L243.TechCoef_TradedBio,
L243.TechShrwt_TradedBio,
L243.SubsectorShrwt_TotBio_SSP4,
L243.SubsectorShrwtFllt_TradedBio_SSP4,
L243.SubsectorShrwt_TotBio_SSP3,
L243.StubTechShrwt_TotBio_SSP3,
L243.Supplysector_reg_SSP4,
L243.SubsectorInterpTo_tra_SSP4)
} else {
stop("Unknown command")
}
}
JGCRI/gcamdata documentation built on March 21, 2023, 2:19 a.m.
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Defines functions module_aglu_L243.bio_trade_input
Documented in module_aglu_L243.bio_trade_input
# Copyright 2019 Battelle Memorial Institute; see the LICENSE file.
#' module_aglu_L243.bio_trade_input
#'
#' Establish regionally differentiated trade structure for bioenergy.
#'
#' @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{L243.DeleteInput_RegBio}, \code{L243.SectorLogitTables[[
#' curr_table ]]$data}, \code{L243.TechCoef_RegBio}, \code{L243.Supplysector_Bio},
#' \code{L243.SectorUseTrialMarket_Bio}, \code{L243.SubsectorLogitTables[[ curr_table ]]$data},
#' \code{L243.SubsectorLogit_Bio}, \code{L243.SubsectorShrwt_TotBio}, \code{L243.SubsectorShrwtFllt_TradedBio},
#' \code{L243.GlobalTechCoef_TotBio}, \code{L243.GlobalTechShrwt_TotBio}, \code{L243.StubTech_TotBio},
#' \code{L243.StubTechShrwt_TotBio}, \code{L243.StubTechCoef_ImportedBio}, \code{L243.StubTechCoef_DomesticBio},
#' \code{L243.TechCoef_TradedBio}, \code{L243.TechShrwt_TradedBio}, \code{L243.SubsectorShrwt_TotBio_SSP4},
#' \code{L243.SubsectorShrwtFllt_TradedBio_SSP4}, \code{L243.SubsectorShrwt_TotBio_SSP3},
#' \code{L243.StubTechShrwt_TotBio_SSP3}, \code{L243.Supplysector_reg_SSP4}, \code{L243.SubsectorInterpTo_tra_SSP4}.
#' The corresponding file in the original data system was \code{L243.bio_trade_input.R} (aglu level2).
#' @details This chunk sets up a structure for regionally differentiated bioenergy trade. Each
#' region consumes a blend of domestic and international bioenergy. Regions can supply to either
#' the domestic or international market. Share weights in the default case depend on the amount of
#' cropland a region has, with the largest region having a share weight of 1. Share weights in SSP3
#' and SSP4 are adjusted to reflect the trade frictions in the SSP storylines.
#' @importFrom assertthat assert_that
#' @importFrom dplyr bind_rows filter full_join if_else group_by left_join mutate select summarize
#' @importFrom tidyr replace_na
#' @author KVC July 2017
module_aglu_L243.bio_trade_input <- function(command, ...) {
if(command == driver.DECLARE_INPUTS) {
return(c(FILE = "common/GCAM_region_names",
FILE = "aglu/A_bio_supplysector",
FILE = "aglu/A_bio_subsector_logit",
FILE = "aglu/A_bio_subsector",
FILE = "aglu/A_agRegionalSector",
FILE = "aglu/A_agTradedSubsector",
"L120.LC_bm2_R_LT_Yh_GLU",
"L102.pcgdp_thous90USD_Scen_R_Y"))
} else if(command == driver.DECLARE_OUTPUTS) {
return(c("L243.DeleteInput_RegBio",
"L243.TechCoef_RegBio",
"L243.Supplysector_Bio",
"L243.SectorUseTrialMarket_Bio",
"L243.SubsectorLogit_Bio",
"L243.SubsectorShrwt_TotBio",
"L243.SubsectorShrwtFllt_TradedBio",
"L243.GlobalTechCoef_TotBio",
"L243.GlobalTechShrwt_TotBio",
"L243.StubTech_TotBio",
"L243.StubTechShrwt_TotBio",
"L243.StubTechCoef_ImportedBio",
"L243.StubTechCoef_DomesticBio",
"L243.TechCoef_TradedBio",
"L243.TechShrwt_TradedBio",
"L243.SubsectorShrwt_TotBio_SSP4",
"L243.SubsectorShrwtFllt_TradedBio_SSP4",
"L243.SubsectorShrwt_TotBio_SSP3",
"L243.StubTechShrwt_TotBio_SSP3",
"L243.Supplysector_reg_SSP4",
"L243.SubsectorInterpTo_tra_SSP4"))
} else if(command == driver.MAKE) {
all_data <- list(...)[[1]]
region <- traded <- subsector.name <- sector.name <- technology <- year <- subsector <-
share.weight <- supplysector <- MORE <- market.name <- Land_Type <- GCAM_region_ID <-
value <- Cropland <- year.fillout <- trade.region <- NULL # silence package check notes
# Load required inputs
GCAM_region_names <- get_data(all_data, "common/GCAM_region_names", strip_attributes = TRUE)
A_bio_supplysector <- get_data(all_data, "aglu/A_bio_supplysector", strip_attributes = TRUE)
A_bio_subsector_logit <- get_data(all_data, "aglu/A_bio_subsector_logit", strip_attributes = TRUE)
A_bio_subsector <- get_data(all_data, "aglu/A_bio_subsector")
A_agRegionalSector <- get_data(all_data, "aglu/A_agRegionalSector", strip_attributes = TRUE)
A_agTradedSubsector <- get_data(all_data, "aglu/A_agTradedSubsector", strip_attributes = TRUE)
L120.LC_bm2_R_LT_Yh_GLU <- get_data(all_data, "L120.LC_bm2_R_LT_Yh_GLU")
L102.pcgdp_thous90USD_Scen_R_Y <- get_data(all_data, "L102.pcgdp_thous90USD_Scen_R_Y")
# Note: I'm pulling out all of the hard-coded GCAM sector names used in this file to the top so it is clearer
OLD.REGIONAL.BIOMASS.NAME <- "regional biomass"
NEW.REGIONAL.BIOMASS.NAME <- "total biomass"
TRADED.BIOMASS.NAME <- "traded biomass"
BIOMASS.NAME <- "biomass"
BIOMASS.TRADE.REGION <- gcam.USA_REGION
DOMESTIC.BIOMASS.NAME <- "domestic biomass"
INTERNATIONAL.BIOMASS.NAME <- "imported biomass"
# First, create a table to delete existing regional biomass input (this needs to include region/sector/subsector/technology/input for all regions & years)
GCAM_region_names %>%
select(region) %>%
mutate(supplysector = OLD.REGIONAL.BIOMASS.NAME, subsector = OLD.REGIONAL.BIOMASS.NAME, technology = OLD.REGIONAL.BIOMASS.NAME) %>%
repeat_add_columns(tibble(year = MODEL_YEARS)) %>%
mutate(minicam.energy.input = BIOMASS.NAME) ->
L243.DeleteInput_RegBio
# Set up all of the new supply sectors.
# Copy sector information to each region.
# Note that "traded biomass" only goes in the BIOMASS.TRADE.REGION
A_bio_supplysector %>%
repeat_add_columns(tibble(region = GCAM_region_names$region)) %>%
mutate(region = if_else(traded == 1, BIOMASS.TRADE.REGION, region),
logit.year.fillout = min(MODEL_YEARS)) %>%
select(-traded) ->
L243.Supplysector_Bio
# Now, create new regional biomass with input called "total biomass" with a input-output coefficient of 1 (i.e., a pass through sector)
L243.DeleteInput_RegBio %>%
mutate(minicam.energy.input = NEW.REGIONAL.BIOMASS.NAME,
coefficient = 1,
market.name = region) ->
L243.TechCoef_RegBio
# Set up the technologies for the new regional biomass sector ("total biomass")
# This sector will include a domestic component and an international component. The domestic component
# consumes "biomass" directly, while the international consumes "traded biomass".
# These technologies have input-output coefficients of 1 (i.e., pass through sectors)
tibble(sector.name = NEW.REGIONAL.BIOMASS.NAME) %>%
repeat_add_columns(tibble(subsector.name = c(DOMESTIC.BIOMASS.NAME, INTERNATIONAL.BIOMASS.NAME))) %>%
mutate(technology = subsector.name) %>%
repeat_add_columns(tibble(year = MODEL_YEARS)) %>%
mutate(minicam.energy.input = if_else(subsector.name == DOMESTIC.BIOMASS.NAME, BIOMASS.NAME, TRADED.BIOMASS.NAME),
coefficient = 1) ->
L243.GlobalTechCoef_TotBio
# Add share-weights to the global technologies
L243.GlobalTechCoef_TotBio %>%
select(sector.name, subsector.name, technology, year) %>%
# note the competition between import and domestic happens at the subsector nest
# so share weights are not consequential here
mutate(share.weight = 1.0) ->
L243.GlobalTechShrwt_TotBio
# Set up stub-technologies
tibble(supplysector = NEW.REGIONAL.BIOMASS.NAME) %>%
repeat_add_columns(tibble(subsector = c(DOMESTIC.BIOMASS.NAME, INTERNATIONAL.BIOMASS.NAME))) %>%
mutate(stub.technology = subsector) %>%
repeat_add_columns(tibble(region = GCAM_region_names$region)) ->
L243.StubTech_TotBio
# Share weights for the regional biomass technologies
L243.StubTech_TotBio %>%
repeat_add_columns(tibble(year = MODEL_YEARS)) %>%
mutate(share.weight = 1) ->
L243.StubTechShrwt_TotBio
# Stub technologies for the regional biomass technologies
L243.StubTech_TotBio %>%
filter(subsector == INTERNATIONAL.BIOMASS.NAME) %>%
repeat_add_columns(tibble(year = MODEL_YEARS)) %>%
mutate(minicam.energy.input = TRADED.BIOMASS.NAME,
coefficient = 1,
market = BIOMASS.TRADE.REGION) ->
L243.StubTechCoef_ImportedBio
# Stub technologies for the regional biomass technologies
L243.StubTech_TotBio %>%
filter(subsector == DOMESTIC.BIOMASS.NAME) %>%
repeat_add_columns(tibble(year = MODEL_YEARS)) %>%
mutate(minicam.energy.input = BIOMASS.NAME,
coefficient = 1,
market = region) ->
L243.StubTechCoef_DomesticBio
# The traded markets tend to be a good candidate to solve explicitly since they tie together many solved markets.
# Set flag so traded biomass uses trial markets
A_bio_supplysector %>%
filter(traded == 1) %>%
select(supplysector) %>%
mutate(region = BIOMASS.TRADE.REGION, use.trial.market = 1) ->
L243.SectorUseTrialMarket_Bio
# Set up all of the new subsectors.
# Copy subsector information to each region.
# Note that "traded biomass" only goes in the BIOMASS.TRADE.REGION, but the subsector name includes the original region name
A_bio_subsector_logit %>%
repeat_add_columns(tibble(region = GCAM_region_names$region)) %>%
mutate(subsector = if_else(traded == 1, paste(region, subsector), subsector),
region = if_else(traded == 1, BIOMASS.TRADE.REGION, region),
logit.year.fillout = min(MODEL_YEARS)) %>%
select(-traded) ->
L243.SubsectorLogit_Bio
# Share weights for the regional biomass subsectors
L243.StubTech_TotBio %>%
select(region, supplysector, subsector) %>%
repeat_add_columns(tibble(year=MODEL_YEARS)) %>%
# expecting NAs for all the years that need to be filled in
left_join(gather_years(A_bio_subsector, "share.weight"), by = c("supplysector", "subsector", "year")) %>%
group_by(region, supplysector, subsector) %>%
mutate(share.weight = approx_fun(year, share.weight)) %>%
ungroup() ->
L243.SubsectorShrwt_TotBio
# Input name, market, coeff for traded biomass
tibble(region = BIOMASS.TRADE.REGION, supplysector = TRADED.BIOMASS.NAME) %>%
mutate(minicam.energy.input = BIOMASS.NAME,
coefficient = 1) %>%
repeat_add_columns(tibble(market.name = GCAM_region_names$region)) %>%
repeat_add_columns(tibble(year = MODEL_YEARS)) %>%
mutate(subsector = paste(market.name, TRADED.BIOMASS.NAME),
technology = subsector) ->
L243.TechCoef_TradedBio
# Compute share weights for subsectors based on cropland area. Largest region gets shareweight of 1.
# This will mean that international biomass supply is roughly proportional to
# cropland area (larger regions produce more biomass).
L120.LC_bm2_R_LT_Yh_GLU %>%
filter(Land_Type == "Cropland", year == max(HISTORICAL_YEARS)) %>%
group_by(GCAM_region_ID) %>%
summarize(Cropland = sum(value)) %>%
ungroup() %>%
mutate(share.weight = Cropland / max(Cropland)) %>%
full_join(GCAM_region_names, by = "GCAM_region_ID") %>% # Using full join to ensure regions without cropland show up
replace_na(list(share.weight = 0)) %>% # Assign regions without land a shareweight of 0 (i.e., they won't contribute to international bio supply)
select(-GCAM_region_ID, -Cropland) %>%
mutate(supplysector = TRADED.BIOMASS.NAME,
subsector = paste(region, TRADED.BIOMASS.NAME),
region = BIOMASS.TRADE.REGION,
year.fillout = min(MODEL_YEARS)) ->
L243.SubsectorShrwtFllt_TradedBio
# Set share weights for technologies in the traded biomass sector to 1
# This is because competition is handled at the subsector level
L243.SubsectorShrwtFllt_TradedBio %>%
mutate(technology = subsector, share.weight = 1) %>%
select(-year.fillout) %>%
repeat_add_columns(tibble(year = MODEL_YEARS)) ->
L243.TechShrwt_TradedBio
# Set share weights for total biomass in SSP4 low income regions.
# SSP4 assumes limited trade with low income regions; so, share weights are set to 0.1
# See Calvin et al. (2017) for documentation. https://doi.org/10.1016/j.gloenvcha.2016.06.010
L243.SubsectorShrwt_TotBio %>%
filter(region %in% get_ssp_regions(L102.pcgdp_thous90USD_Scen_R_Y, GCAM_region_names, "low"),
subsector == "imported biomass") %>%
mutate(share.weight = if_else(year >= aglu.BIO_TRADE_SSP4_YEAR_FILLOUT, 0.1, share.weight)) ->
L243.SubsectorShrwt_TotBio_SSP4_lo
L243.SubsectorShrwtFllt_TradedBio %>%
mutate(trade.region = gsub(" traded biomass", "", subsector)) %>%
filter(trade.region %in% get_ssp_regions(L102.pcgdp_thous90USD_Scen_R_Y, GCAM_region_names, "low")) %>%
mutate(year.fillout = aglu.BIO_TRADE_SSP4_YEAR_FILLOUT, share.weight = 0.1) %>%
select(-trade.region) ->
L243.SubsectorShrwtFllt_TradedBio_SSP4
# Set share weights for total biomass in SSP4 high and medium income regions.
# SSP4 assumes free trade within high income regions; so, subsector share weights are set to 0.5
# (tech shareweights are not relevant as there is only one tech per subsector)
# See Calvin et al. (2017) for documentation. https://doi.org/10.1016/j.gloenvcha.2016.06.010
L243.SubsectorShrwt_TotBio %>%
filter(region %in% c(get_ssp_regions(L102.pcgdp_thous90USD_Scen_R_Y, GCAM_region_names, "high"),
get_ssp_regions(L102.pcgdp_thous90USD_Scen_R_Y, GCAM_region_names, "medium")),
subsector == "imported biomass") %>%
mutate(share.weight = if_else(year >= aglu.BIO_TRADE_SSP4_YEAR_FILLOUT, 0.5, share.weight)) ->
L243.SubsectorShrwt_TotBio_SSP4_hi
# Bind SSP4 share weights for all regions into single data frames
bind_rows(L243.SubsectorShrwt_TotBio_SSP4_hi, L243.SubsectorShrwt_TotBio_SSP4_lo) ->
L243.SubsectorShrwt_TotBio_SSP4
# Set share weights for total biomass in SSP3.
# SSP3 assumes limited trade across regions; so, share weights are set to 0.1
# See Calvin et al. (2017) for documentation. https://doi.org/10.1016/j.gloenvcha.2016.06.010
L243.SubsectorShrwt_TotBio %>%
filter(subsector == "imported biomass") %>%
mutate(share.weight = if_else(year >= aglu.BIO_TRADE_SSP4_YEAR_FILLOUT, 0.1, share.weight)) ->
L243.SubsectorShrwt_TotBio_SSP3
L243.StubTechShrwt_TotBio %>%
filter(subsector == "imported biomass", year >= aglu.BIO_TRADE_SSP3_YEAR_FILLOUT) %>%
mutate(share.weight = 0.1) ->
L243.StubTechShrwt_TotBio_SSP3
# SSP4 ag trade - reduce the logit exponents for the decision between imports and consumption of domestic
# production, in low income regions
SSP4_AG_LOGIT_IMPORT_LOW <- -1.5
L243.Supplysector_reg_SSP4 <- mutate(A_agRegionalSector, logit.year.fillout = min(MODEL_BASE_YEARS)) %>%
write_to_all_regions(c(LEVEL2_DATA_NAMES[["Supplysector"]], "logit.type"),
filter(GCAM_region_names, region %in% get_ssp_regions(L102.pcgdp_thous90USD_Scen_R_Y, GCAM_region_names, "low"))) %>%
mutate(logit.exponent = SSP4_AG_LOGIT_IMPORT_LOW)
# SSP4 ag trade, cont'd - for the export market (sharing regions), decrease the share-weights from their base-year
# calibrated values towards zero in some year beyond the analysis window
SSP4_ZERO_EXPORT_YEAR_LOW <- 2150
A_agTradedSubsector_SSP4 <- mutate(A_agTradedSubsector, to.value = 0,
to.year = SSP4_ZERO_EXPORT_YEAR_LOW,
interpolation.function = "linear")
L243.SubsectorInterpTo_tra_SSP4 <- write_to_all_regions(A_agTradedSubsector_SSP4,
LEVEL2_DATA_NAMES[["SubsectorInterpTo"]],
filter(GCAM_region_names, region %in% get_ssp_regions(L102.pcgdp_thous90USD_Scen_R_Y, GCAM_region_names, "low")),
has_traded = TRUE) %>%
mutate(region = gcam.USA_REGION) # need to manually set the region name to gcam.USA_REGION, where the traded commodities are housed
# Produce outputs
L243.DeleteInput_RegBio %>%
add_title("Table of regional biomass sector/subsector/technology/year for deletion") %>%
add_units("NA") %>%
add_comments("List all region/year combinations for the regional biomass sector/subsector/technology") %>%
add_comments("We need to rename the input from 'biomass' to 'total biomass' so we can separate trade.") %>%
add_comments("We also want to change the market from global to regional.") %>%
add_comments("The only way to do this in the model is to delete these technologies and re-add them with the right input and market-name.") %>%
add_legacy_name("L243.DeleteInput_RegBio") %>%
add_precursors("common/GCAM_region_names") ->
L243.DeleteInput_RegBio
L243.TechCoef_RegBio %>%
add_title("Table creating new 'traded biomass' sector/subsector/technology coefficients") %>%
add_units("Unitless") %>%
add_comments("Copy the L243.DeleteInput_RegBio table. Update the name of the input to 'total biomass'.") %>%
add_comments("Add the input-output coefficient (equals 1 since this is a pass through sector).") %>%
add_comments("Add the market name (equal to the region name since trade is no longer global).") %>%
add_legacy_name("L243.TechCoef_RegBio") %>%
same_precursors_as(L243.DeleteInput_RegBio) ->
L243.TechCoef_RegBio
L243.Supplysector_Bio %>%
add_title("Units and logit exponents for bio trade supply sectors") %>%
add_units("NA") %>%
add_comments("Copy bio trade assumption file to all regions") %>%
add_comments("Replace region name for 'traded biomass' with the trade region (currently USA).") %>%
add_legacy_name("L243.Supplysector_Bio") %>%
add_precursors("common/GCAM_region_names", "aglu/A_bio_supplysector") ->
L243.Supplysector_Bio
L243.SectorUseTrialMarket_Bio %>%
add_title("Table flagging traded biomass sector to use trial markets") %>%
add_units("NA") %>%
add_comments("Create a table with the traded biomass sector and a boolean (1) for use.trial.markets") %>%
add_legacy_name("L243.SectorUseTrialMarket_Bio") %>%
add_precursors("aglu/A_bio_supplysector") ->
L243.SectorUseTrialMarket_Bio
L243.SubsectorLogit_Bio %>%
add_title("Logit exponents for bio trade subsectors") %>%
add_units("unitless") %>%
add_comments("Copy bio trade subsector assumption file to all regions") %>%
add_comments("Modify subsector name to include the region for the 'traded biomass' sectors.") %>%
add_comments("Replace region name for 'traded biomass' with the trade region (currently USA).") %>%
add_legacy_name("L243.SubsectorLogit_Bio") %>%
add_precursors("common/GCAM_region_names", "aglu/A_bio_subsector_logit") ->
L243.SubsectorLogit_Bio
L243.SubsectorShrwt_TotBio %>%
add_title("Subsector share weights for the total biomass sector") %>%
add_units("unitless") %>%
add_comments("Map the share weights specified in the assumption file to all subsectors") %>%
add_precursors("aglu/A_bio_subsector") %>%
same_precursors_as("L243.StubTech_TotBio") ->
L243.SubsectorShrwt_TotBio
L243.SubsectorShrwtFllt_TradedBio %>%
add_title("Subsector shareweights for traded biomass sector") %>%
add_units("unitless") %>%
add_comments("Use cropland area in the final historical year to calculate shareweights.") %>%
add_comments("Share weights are proportional to cropland area, with the region with") %>%
add_comments("the largest cropland area assigned a share weight of 1.") %>%
add_legacy_name("L243.SubsectorShrwtFllt_TradedBio") %>%
add_precursors("common/GCAM_region_names", "L120.LC_bm2_R_LT_Yh_GLU") ->
L243.SubsectorShrwtFllt_TradedBio
L243.GlobalTechCoef_TotBio %>%
add_title("Total biomass technology coefficients") %>%
add_units("unitless") %>%
add_comments("Create table with 'domestic' and 'international' biomass subsectors.") %>%
add_comments("Set minicam.energy.input for both types of subsector.") %>%
add_comments("Set input-output coefficients to 1.") %>%
add_comments("Copy to all model years.") %>%
add_legacy_name("L243.GlobalTechCoef_TotBio") ->
L243.GlobalTechCoef_TotBio
L243.GlobalTechShrwt_TotBio %>%
add_title("Share weights for domestic and imported biomass") %>%
add_units("unitless") %>%
add_comments("Copy L243.GlobalTechCoef_TotBio. Set share weights based on an assumption file") %>%
add_legacy_name("L243.GlobalTechShrwt_TotBio") %>%
same_precursors_as("L243.GlobalTechCoef_TotBio") ->
L243.GlobalTechShrwt_TotBio
L243.StubTech_TotBio %>%
add_title("Stub technologies for the 'total biomass' sector") %>%
add_units("NA") %>%
add_comments("Copy technology names to all regions") %>%
add_legacy_name("L243.StubTech_TotBio") %>%
add_precursors("common/GCAM_region_names") ->
L243.StubTech_TotBio
L243.StubTechShrwt_TotBio %>%
add_title("Share weights for the total biomass sector") %>%
add_units("NA") %>%
add_comments("Set share weight for 'total biomass' technologies equal to 1 in all regions") %>%
add_legacy_name("L243.StubTechShrwt_TotBio") %>%
same_precursors_as("L243.StubTech_TotBio") ->
L243.StubTechShrwt_TotBio
L243.StubTechCoef_ImportedBio %>%
add_title("Input-output coefficients for imported biomass technologies") %>%
add_units("unitless") %>%
add_comments("Filter L243.StubTech_TotBio for the imported biomass sector") %>%
add_comments("Set coefficients to 1 and market name to the traded region (currently USA)") %>%
add_legacy_name("L243.StubTechCoef_ImportedBio") %>%
same_precursors_as("L243.StubTech_TotBio") ->
L243.StubTechCoef_ImportedBio
L243.StubTechCoef_DomesticBio %>%
add_title("Input-output coefficients for domestic biomass technologies") %>%
add_units("unitless") %>%
add_comments("Filter L243.StubTech_TotBio for the domestic biomass sector") %>%
add_comments("Set coefficients to 1 and market name to region name") %>%
add_legacy_name("L243.StubTechCoef_DomesticBio") %>%
same_precursors_as("L243.StubTech_TotBio") ->
L243.StubTechCoef_DomesticBio
L243.TechCoef_TradedBio %>%
add_title("Input-Output coefficients for traded biomass technologies") %>%
add_units("unitless") %>%
add_comments("Assign coefficient of 1 to all traded biomass technologies in all years") %>%
add_legacy_name("L243.TechCoef_TradedBio") %>%
add_precursors("common/GCAM_region_names") ->
L243.TechCoef_TradedBio
L243.TechShrwt_TradedBio %>%
add_title("Technology shareweights for the traded biomass sector") %>%
add_units("unitless") %>%
add_comments("Use the region & subsector names from 'L243.SubsectorShrwtFllt_TradedBio") %>%
add_comments("Set all share weights to 1 since competition is handled at subsector level.") %>%
add_legacy_name("L243.TechShrwt_TradedBio") %>%
same_precursors_as("L243.SubsectorShrwtFllt_TradedBio") ->
L243.TechShrwt_TradedBio
L243.SubsectorShrwt_TotBio_SSP4 %>%
add_title("Subsector shareweights for total bioenergy in SSP4") %>%
add_units("unitless") %>%
add_comments("Uses the structure of L243.SubsectorShrwt_TotBio") %>%
add_comments("Replace shareweights with assumed coefficients (0.1 for low income, 0.5 for high income)") %>%
same_precursors_as("L243.SubsectorShrwt_TotBio") %>%
add_precursors("common/GCAM_region_names", "L102.pcgdp_thous90USD_Scen_R_Y") ->
L243.SubsectorShrwt_TotBio_SSP4
L243.SubsectorShrwtFllt_TradedBio_SSP4 %>%
add_title("Subsector shareweights for traded bioenergy in SSP4") %>%
add_units("unitless") %>%
add_comments("Uses the structure of L243.SubsectorShrwtFllt_TradedBio") %>%
add_comments("Replace shareweights with assumed coefficients (0.1 for low income, 0.5 for high income)") %>%
add_legacy_name("L243.SubsectorShrwtFllt_TradedBio_SSP4") %>%
same_precursors_as("L243.SubsectorShrwtFllt_TradedBio") %>%
add_precursors("common/GCAM_region_names", "L102.pcgdp_thous90USD_Scen_R_Y") ->
L243.SubsectorShrwtFllt_TradedBio_SSP4
L243.SubsectorShrwt_TotBio_SSP3 %>%
add_title("Subsector shareweights for total bioenergy in SSP3") %>%
add_units("unitless") %>%
add_comments("Uses the structure of L243.SubsectorShrwt_TotBio") %>%
add_comments("Replace shareweights with assumed coefficients (0.1)") %>%
same_precursors_as("L243.SubsectorShrwt_TotBio") ->
L243.SubsectorShrwt_TotBio_SSP3
L243.StubTechShrwt_TotBio_SSP3 %>%
add_title("Technology shareweights for total bioenergy in SSP3") %>%
add_units("unitless") %>%
add_comments("Uses the structure of L243.StubTechShrwt_TotBio") %>%
add_comments("Replace shareweights with assumed coefficients (0.1)") %>%
add_legacy_name("L243.StubTechShrwt_TotBio_SSP3") %>%
same_precursors_as("L243.StubTechShrwt_TotBio") ->
L243.StubTechShrwt_TotBio_SSP3
L243.Supplysector_reg_SSP4 %>%
add_title("Supplysector info for regional crop markets w modified logits for SSP4") %>%
add_units("unitless") %>%
add_comments("Only applies to low-income regions") %>%
add_precursors("common/GCAM_region_names", "aglu/A_agRegionalSector") ->
L243.Supplysector_reg_SSP4
L243.SubsectorInterpTo_tra_SSP4 %>%
add_title("Subsector interpolation info for traded crop markets w modified share-weights for SSP4") %>%
add_units("unitless") %>%
add_comments("Only applies to low-income regions") %>%
add_precursors("common/GCAM_region_names", "aglu/A_agTradedSubsector") ->
L243.SubsectorInterpTo_tra_SSP4
return_data(L243.DeleteInput_RegBio,
L243.TechCoef_RegBio,
L243.Supplysector_Bio,
L243.SectorUseTrialMarket_Bio,
L243.SubsectorLogit_Bio,
L243.SubsectorShrwt_TotBio,
L243.SubsectorShrwtFllt_TradedBio,
L243.GlobalTechCoef_TotBio,
L243.GlobalTechShrwt_TotBio,
L243.StubTech_TotBio,
L243.StubTechShrwt_TotBio,
L243.StubTechCoef_ImportedBio,
L243.StubTechCoef_DomesticBio,
L243.TechCoef_TradedBio,
L243.TechShrwt_TradedBio,
L243.SubsectorShrwt_TotBio_SSP4,
L243.SubsectorShrwtFllt_TradedBio_SSP4,
L243.SubsectorShrwt_TotBio_SSP3,
L243.StubTechShrwt_TotBio_SSP3,
L243.Supplysector_reg_SSP4,
L243.SubsectorInterpTo_tra_SSP4)
} else {
stop("Unknown command")
}
}
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