R/zchunk_L262.dac.R
In JGCRI/gcamdata: Build the GCAM Input Datasets
Defines functions
module_energy_L262.dac
Documented in
module_energy_L262.dac
# Copyright 2019 Battelle Memorial Institute; see the LICENSE file.
#' module_energy_L262.dac
#'
#' Compute a variety of final energy keyword, sector, share weight, and technology information for dac-related GCAM inputs.
#'
#' @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{L262.SectorLogitTables[[ curr_table ]]$data}, \code{L262.Supplysector_dac}, \code{L262.FinalEnergyKeyword_dac},
#' \code{L262.SubsectorLogitTables[[ curr_table ]]$data}, \code{L262.SubsectorLogit_dac}, \code{L262.SubsectorShrwtFllt_dac},
#' \code{L262.SubsectorInterp_dac}, \code{L262.StubTech_dac}, \code{L262.GlobalTechShrwt_dac}, \code{L262.GlobalTechCoef_dac},
#' \code{L262.GlobalTechCost_dac}, \code{L262.GlobalTechCapture_dac}, \code{L262.StubTechProd_dac}, \code{L262.StubTechCalInput_dac_heat},
#' \code{L262.StubTechCoef_dac}, \code{L262.PerCapitaBased_dac}, \code{L262.BaseService_dac}, \code{L262.PriceElasticity_dac}, \code{object}.
#' The corresponding file in the original data system was \code{L262.dac.R} (energy level2).
#' @details The chunk provides final energy keyword, supplysector/subsector information, supplysector/subsector interpolation information, global technology share weight, global technology efficiency, global technology coefficients, global technology cost, price elasticity, stub technology information, stub technology interpolation information, stub technology calibrated inputs, and etc for dac sector.
#' @importFrom assertthat assert_that
#' @importFrom dplyr arrange bind_rows distinct filter if_else group_by lag left_join mutate pull select
#' @importFrom tidyr complete nesting
#' @author JF March 2021
module_energy_L262.dac <- function(command, ...) {
TECH_PARAMETRIZATION_OUTPUTS <- paste0("ssp", 1:5)
if(command == driver.DECLARE_INPUTS) {
return(c(FILE = "common/GCAM_region_names",
FILE = "energy/calibrated_techs_cdr",
FILE = "energy/A62.PrimaryFuelCCoef",
FILE = "energy/A62.sector",
FILE = "energy/A62.subsector_interp",
FILE = "energy/A62.subsector_logit",
FILE = "energy/A62.subsector_shrwt",
FILE = "energy/A62.globaltech_coef_ssp1",
FILE = "energy/A62.globaltech_coef_ssp2",
FILE = "energy/A62.globaltech_coef_ssp3",
FILE = "energy/A62.globaltech_coef_ssp4",
FILE = "energy/A62.globaltech_coef_ssp5",
FILE = "energy/A62.globaltech_cost_ssp1",
FILE = "energy/A62.globaltech_cost_ssp2",
FILE = "energy/A62.globaltech_cost_ssp3",
FILE = "energy/A62.globaltech_cost_ssp4",
FILE = "energy/A62.globaltech_cost_ssp5",
FILE = "energy/A62.globaltech_shrwt_ssp1",
FILE = "energy/A62.globaltech_shrwt_ssp2",
FILE = "energy/A62.globaltech_shrwt_ssp3",
FILE = "energy/A62.globaltech_shrwt_ssp4",
FILE = "energy/A62.globaltech_shrwt_ssp5",
FILE = "energy/A62.globaltech_co2capture",
FILE = "energy/A62.demand",
FILE = "energy/A62.globaltech_retirement",
"L162.out_Mt_R_dac_Yh"))
} else if(command == driver.DECLARE_OUTPUTS) {
return(c("L262.CarbonCoef_dac",
"L262.Supplysector_dac",
"L262.FinalEnergyKeyword_dac",
"L262.SubsectorLogit_dac",
"L262.SubsectorShrwtFllt_dac",
"L262.SubsectorInterp_dac",
"L262.GlobalTechCost_dac",
"L262.GlobalTechCost_dac_ssp1",
"L262.GlobalTechCost_dac_ssp2",
"L262.GlobalTechCost_dac_ssp3",
"L262.GlobalTechCost_dac_ssp4",
"L262.GlobalTechCost_dac_ssp5",
"L262.StubTech_dac",
"L262.GlobalTechShrwt_dac",
"L262.GlobalTechShrwt_dac_ssp1",
"L262.GlobalTechShrwt_dac_ssp2",
"L262.GlobalTechShrwt_dac_ssp3",
"L262.GlobalTechShrwt_dac_ssp4",
"L262.GlobalTechShrwt_dac_ssp5",
'L262.GlobalTechCoef_dac',
"L262.GlobalTechCoef_dac_ssp1",
"L262.GlobalTechCoef_dac_ssp2",
"L262.GlobalTechCoef_dac_ssp3",
"L262.GlobalTechCoef_dac_ssp4",
"L262.GlobalTechCoef_dac_ssp5",
"L262.GlobalTechCapture_dac",
"L262.PerCapitaBased_dac",
"L262.PriceElasticity_dac",
"L262.StubTechProd_dac",
"L262.BaseService_dac",
"L262.GlobalTechSCurve_dac",
"L262.GlobalTechProfitShutdown_dac"))
} else if(command == driver.MAKE) {
all_data <- list(...)[[1]]
# Load required inputs
GCAM_region_names <- get_data(all_data, "common/GCAM_region_names")
calibrated_techs <- get_data(all_data, "energy/calibrated_techs_cdr")
A62.PrimaryFuelCCoef <- get_data(all_data, "energy/A62.PrimaryFuelCCoef", strip_attributes = TRUE)
A62.sector <- get_data(all_data, "energy/A62.sector", strip_attributes = TRUE)
A62.subsector_interp <- get_data(all_data, "energy/A62.subsector_interp", strip_attributes = TRUE)
A62.subsector_logit <- get_data(all_data, "energy/A62.subsector_logit", strip_attributes = TRUE)
A62.subsector_shrwt <- get_data(all_data, "energy/A62.subsector_shrwt", strip_attributes = TRUE)
A62.globaltech_co2capture <- get_data(all_data, "energy/A62.globaltech_co2capture")
A62.demand <- get_data(all_data, "energy/A62.demand", strip_attributes = TRUE)
A62.globaltech_retirement <- get_data(all_data, "energy/A62.globaltech_retirement", strip_attributes = TRUE)
L162.out_Mt_R_dac_Yh <- get_data(all_data, "L162.out_Mt_R_dac_Yh", strip_attributes = TRUE)
#load ssp parametrizations
A62.globaltech_coef_ssp1 <- get_data(all_data, "energy/A62.globaltech_coef_ssp1")%>% gather_years %>% mutate(scenario=paste0("ssp1"))
A62.globaltech_coef_ssp2 <- get_data(all_data, "energy/A62.globaltech_coef_ssp2")%>% gather_years %>% mutate(scenario=paste0("ssp2"))
A62.globaltech_coef_ssp3 <- get_data(all_data, "energy/A62.globaltech_coef_ssp3")%>% gather_years %>% mutate(scenario=paste0("ssp3"))
A62.globaltech_coef_ssp4 <- get_data(all_data, "energy/A62.globaltech_coef_ssp4")%>% gather_years %>% mutate(scenario=paste0("ssp4"))
A62.globaltech_coef_ssp5 <- get_data(all_data, "energy/A62.globaltech_coef_ssp5")%>% gather_years %>% mutate(scenario=paste0("ssp5"))
A62.globaltech_cost_ssp1 <- get_data(all_data, "energy/A62.globaltech_cost_ssp1")%>% gather_years %>% mutate(scenario=paste0("ssp1"))
A62.globaltech_cost_ssp2 <- get_data(all_data, "energy/A62.globaltech_cost_ssp2")%>% gather_years %>% mutate(scenario=paste0("ssp2"))
A62.globaltech_cost_ssp3 <- get_data(all_data, "energy/A62.globaltech_cost_ssp3")%>% gather_years %>% mutate(scenario=paste0("ssp3"))
A62.globaltech_cost_ssp4 <- get_data(all_data, "energy/A62.globaltech_cost_ssp4")%>% gather_years %>% mutate(scenario=paste0("ssp4"))
A62.globaltech_cost_ssp5 <- get_data(all_data, "energy/A62.globaltech_cost_ssp5")%>% gather_years %>% mutate(scenario=paste0("ssp5"))
A62.globaltech_shrwt_ssp1 <- get_data(all_data, "energy/A62.globaltech_shrwt_ssp1")%>% gather_years %>% mutate(scenario=paste0("ssp1"))
A62.globaltech_shrwt_ssp2 <- get_data(all_data, "energy/A62.globaltech_shrwt_ssp2")%>% gather_years %>% mutate(scenario=paste0("ssp2"))
A62.globaltech_shrwt_ssp3 <- get_data(all_data, "energy/A62.globaltech_shrwt_ssp3")%>% gather_years %>% mutate(scenario=paste0("ssp3"))
A62.globaltech_shrwt_ssp4 <- get_data(all_data, "energy/A62.globaltech_shrwt_ssp4")%>% gather_years %>% mutate(scenario=paste0("ssp4"))
A62.globaltech_shrwt_ssp5 <- get_data(all_data, "energy/A62.globaltech_shrwt_ssp5")%>% gather_years %>% mutate(scenario=paste0("ssp5"))
# ===================================================
# 0. Give binding for variable names used in pipeline
year <- value <- GCAM_region_ID <- sector <- fuel <- year.fillout <- to.value <-
technology <- supplysector <- subsector <- minicam.energy.input <- coefficient <-
remove.fraction <- minicam.non.energy.input <- input.cost <- PrimaryFuelCO2Coef.name <-
PrimaryFuelCO2Coef <- calibration <- calOutputValue <- subs.share.weight <- region <-
calibrated.value <- . <- scenario <- temp_lag <- base.service <- energy.final.demand <-
value.x <- value.y <- parameter <- half.life <- median.shutdown.point <-
L262.GlobalTechCoef_dac_ssp1 <- L262.GlobalTechCoef_dac_ssp2 <-L262.GlobalTechCoef_dac_ssp3 <-L262.GlobalTechCoef_dac_ssp4 <-L262.GlobalTechCoef_dac_ssp5 <-
L262.GlobalTechCost_dac_ssp1 <- L262.GlobalTechCost_dac_ssp2 <- L262.GlobalTechCost_dac_ssp3 <- L262.GlobalTechCost_dac_ssp4 <- L262.GlobalTechCost_dac_ssp5 <-
L262.GlobalTechShrwt_dac_ssp1 <- L262.GlobalTechShrwt_dac_ssp2 <- L262.GlobalTechShrwt_dac_ssp3 <- L262.GlobalTechShrwt_dac_ssp4 <- L262.GlobalTechShrwt_dac_ssp5 <- NULL
# ===================================================
# 1. Perform computations
# Prelim - carbon coefficient (emissions factor)
A62.PrimaryFuelCCoef %>%
write_to_all_regions(c(LEVEL2_DATA_NAMES[["CarbonCoef"]]), GCAM_region_names = GCAM_region_names, has_traded = TRUE) -> L262.CarbonCoef_dac
# 1a. Supplysector information
# L262.Supplysector_dac: Supply sector information for CO2 removal sector containing dac subsectors and technologies
A62.sector %>%
write_to_all_regions(c(LEVEL2_DATA_NAMES[["Supplysector"]], LOGIT_TYPE_COLNAME), GCAM_region_names) ->
L262.Supplysector_dac
# L262.FinalEnergyKeyword_dac: Supply sector keywords for CO2 removal sector
A62.sector %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["FinalEnergyKeyword"]], GCAM_region_names) %>%
na.omit ->
L262.FinalEnergyKeyword_dac
# 1b. Subsector information
# L262.SubsectorLogit_dac: Subsector logit exponents of CO2 removal sector
A62.subsector_logit %>%
write_to_all_regions(c(LEVEL2_DATA_NAMES[["SubsectorLogit"]], LOGIT_TYPE_COLNAME), GCAM_region_names) ->
L262.SubsectorLogit_dac
# and L262.SubsectorShrwtFllt_dac: Subsector shareweights of CO2 removal sector
A62.subsector_shrwt %>%
filter(!is.na(year.fillout)) %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["SubsectorShrwtFllt"]], GCAM_region_names) ->
L262.SubsectorShrwtFllt_dac
# L262.SubsectorInterp_dac: Subsector shareweight interpolation of CO2 removal sector
A62.subsector_interp %>%
filter(is.na(to.value)) %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["SubsectorInterp"]], GCAM_region_names) ->
L262.SubsectorInterp_dac
# 1c. Technology information
# L262.StubTech_dac: Identification of stub technologies of dac
# Note: assuming that technology list in the shareweight table includes the full set (any others would default to a 0 shareweight)
A62.globaltech_shrwt <- bind_rows(A62.globaltech_shrwt_ssp1,A62.globaltech_shrwt_ssp2,A62.globaltech_shrwt_ssp3,A62.globaltech_shrwt_ssp4,A62.globaltech_shrwt_ssp5)
A62.globaltech_shrwt %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["Tech"]], GCAM_region_names) %>%
rename(stub.technology = technology) ->
L262.StubTech_dac
# L262.GlobalTechShrwt_dac: Shareweights of global dac technologies
A62.globaltech_shrwt %>%
gather_years %>%
complete(nesting(supplysector, subsector, technology,scenario), year = c(year, MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)) %>%
arrange(supplysector, subsector, technology, scenario,year) %>%
group_by(scenario,supplysector, subsector, technology) %>%
mutate(share.weight = approx_fun(year, value, rule = 1)) %>%
ungroup %>%
filter(year %in% c(MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)) %>%
rename(sector.name = supplysector,
subsector.name = subsector) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechYr"]], "share.weight","scenario") ->
L262.GlobalTechShrwt_dac
#L262.GlobalTechCoef_dac: Energy inputs and coefficients of dac technologies
#concatenate tables of all ssps into one table for later filtering
A62.globaltech_coef <- bind_rows(A62.globaltech_coef_ssp1,A62.globaltech_coef_ssp2,A62.globaltech_coef_ssp3,A62.globaltech_coef_ssp4,A62.globaltech_coef_ssp5)
A62.globaltech_coef %>%
gather_years %>%
complete(nesting(supplysector, subsector, technology, minicam.energy.input,scenario), year = c(year, MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)) %>%
arrange(supplysector, subsector, technology, minicam.energy.input, scenario,year) %>%
group_by(scenario,supplysector, subsector, technology, minicam.energy.input) %>%
mutate(coefficient = approx_fun(year, value, rule = 1),
coefficient = round(coefficient, energy.DIGITS_COEFFICIENT)) %>%
ungroup %>%
filter(year %in% c(MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)) %>%
rename(sector.name = supplysector,
subsector.name = subsector) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechCoef"]],'scenario') ->
L262.GlobalTechCoef_dac
# Carbon capture rates for dac.
# L262.GlobalTechCapture_dac: defines CO2 capture fractions for dac (by definition 1, as all inputs are defined per tonne C removed from the atmosphere),
# as well as a separately-defined process heat dac sector, which has slightly lower capture rates for natural gas combustion emissions.
# This allows separate consideration of the capture fraction of any combustion emissions resulting from the process heat input
# No need to consider historical periods here
A62.globaltech_co2capture %>%
gather_years %>%
complete(nesting(supplysector, subsector, technology), year = c(year, MODEL_FUTURE_YEARS)) %>%
arrange(supplysector, subsector, technology, year) %>%
group_by(supplysector, subsector, technology) %>%
mutate(remove.fraction = approx_fun(year, value, rule = 1),
remove.fraction = round(remove.fraction, energy.DIGITS_REMOVE.FRACTION)) %>%
ungroup %>%
filter(year %in% MODEL_FUTURE_YEARS) %>%
rename(sector.name = supplysector,
subsector.name = subsector) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechYr"]], "remove.fraction") %>%
mutate(storage.market = energy.CO2.STORAGE.MARKET) ->
L262.GlobalTechCapture_dac
# L262.GlobalTechCost_dac: Non-energy costs of global dac technologies
#first we concatenate all the ssp cost parametrizations into one table, for later filtering
A62.globaltech_cost <- bind_rows(A62.globaltech_cost_ssp1,A62.globaltech_cost_ssp2,A62.globaltech_cost_ssp3,A62.globaltech_cost_ssp4,A62.globaltech_cost_ssp5)
A62.globaltech_cost %>%
gather_years %>%
complete(nesting(supplysector, subsector, technology, minicam.non.energy.input,scenario), year = c(year, MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)) %>%
arrange(supplysector, subsector, technology, minicam.non.energy.input, scenario,year) %>%
group_by(scenario,supplysector, subsector, technology, minicam.non.energy.input) %>%
mutate(input.cost = approx_fun(year, value, rule = 1),
input.cost = round(input.cost, energy.DIGITS_COST)) %>%
ungroup %>%
filter(year %in% c(MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)) %>%
rename(sector.name = supplysector,
subsector.name = subsector) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechCost"]],'scenario') ->
L262.GlobalTechCost_dac # intermediate tibble
L262.GlobalTechCapture_dac %>%
pull(remove.fraction) %>%
mean -> dac_CO2_capture_frac
L262.GlobalTechCoef_dac %>%
filter(minicam.energy.input == "airCO2") %>%
pull(coefficient) %>%
mean ->
coef_mean # temporary value
#Calibration and region-specific data
# L262.StubTechProd_dac: calibrated CO2 removal (cdr) production (arbitrarily high value met entirely by no-capture technology in history)
calibrated_techs %>%
filter(calibration == "output") %>% # Only take the tech IDs where the calibration is identified as output
select(sector, supplysector, subsector, technology) %>%
distinct ->
calibrated_techs_export # temporary tibble
L162.out_Mt_R_dac_Yh %>%
filter(year %in% MODEL_BASE_YEARS) %>%
mutate(calOutputValue = round(value, energy.DIGITS_CALOUTPUT)) %>%
left_join_error_no_match(GCAM_region_names, by = "GCAM_region_ID") %>%
left_join_error_no_match(calibrated_techs_export, by = "sector") %>%
mutate(stub.technology = technology,
share.weight.year = year,
subs.share.weight = if_else(calOutputValue > 0, 1, 0),
tech.share.weight = subs.share.weight) %>%
select(LEVEL2_DATA_NAMES[["StubTechProd"]]) ->
L262.StubTechProd_dac
# L262.PerCapitaBased_dac: per-capita based flag for dac exports final demand. Note that this should be zero as the amount of DAC shouldn't be explicitly tied to population
A62.demand %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["PerCapitaBased"]], GCAM_region_names) ->
L262.PerCapitaBased_dac
# L262.BaseService_dac: base-year service output of dac (arbitrarily high)
L262.StubTechProd_dac %>%
select(region, year, base.service = calOutputValue) %>%
mutate(energy.final.demand = A62.demand[["energy.final.demand"]]) ->
L262.BaseService_dac
# L262.PriceElasticity_dac: price elasticity (zero to represent the backstop nature of dac technology)
A62.demand %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["PriceElasticity"]][LEVEL2_DATA_NAMES[["PriceElasticity"]] != "year"], GCAM_region_names) %>%
repeat_add_columns(tibble(year = MODEL_FUTURE_YEARS)) %>%
select(LEVEL2_DATA_NAMES[["PriceElasticity"]]) ->
L262.PriceElasticity_dac
# Retirement information
A62.globaltech_retirement %>%
set_years %>%
mutate(year = as.integer(year)) %>%
rename(sector.name = supplysector, subsector.name = subsector) ->
A62.globaltech_retirement_with_years
# Copy the data in the last base year period through to the end year
A62.globaltech_retirement_with_years %>%
filter(year == max(MODEL_BASE_YEARS)) ->
A62.globaltech_retirement_max_baseyear
A62.globaltech_retirement_with_years %>%
filter(year == min(MODEL_FUTURE_YEARS)) %>%
select(-year) %>%
repeat_add_columns(tibble(year = MODEL_FUTURE_YEARS)) %>%
bind_rows(A62.globaltech_retirement_max_baseyear) ->
L262.globaltech_retirement
# Retirement may consist of any of three types of retirement function (phased, s-curve, or none)
# All of these options have different headers, and all are allowed
# L262.GlobalTechSCurve_dac: Global tech lifetime and s-curve retirement function
L262.globaltech_retirement %>%
filter(!is.na(half.life)) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechYr"]], "lifetime", "steepness", "half.life") ->
L262.GlobalTechSCurve_dac
# L262.GlobalTechProfitShutdown_dac: Global tech profit shutdown decider.
L262.globaltech_retirement %>%
filter(!is.na(median.shutdown.point)) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechYr"]], "median.shutdown.point", "profit.shutdown.steepness") ->
L262.GlobalTechProfitShutdown_dac
# ===================================================
# Produce outputs
# Extract SSP data and assign to separate tables
for(sce in TECH_PARAMETRIZATION_OUTPUTS) {
L262.GlobalTechCost_dac %>%
filter(scenario == sce) %>%
select(-c(scenario))%>%
add_title(paste("Cost coefficients of dac -", sce)) %>%
add_units("1975$/kg for supplysector dac; 1975$/GJ for supplysector process heat dac") %>%
add_comments(sce) %>%
add_comments("Includes non-energy related capture costs only per kgC captured from the atmosphere. Storage costs will be computed endogenously through the carbon storage markets. Additional non-energy cost of process heat dac assumed zero.") %>%
add_legacy_name(paste0("L262.GlobalTechCost_dac_", tolower(sce))) %>%
add_precursors(paste0("energy/A62.globaltech_cost_", tolower(sce))) ->
x
assign(paste0("L262.GlobalTechCost_dac_", tolower(sce)), x)
}
for(sce in TECH_PARAMETRIZATION_OUTPUTS) {
L262.GlobalTechCoef_dac %>%
filter(scenario == sce) %>%
select(-c(scenario))%>%
add_title(paste("Tech coefficients of dac -", sce)) %>%
add_units("airCO2 input is unitless (Mt airCO2 per Mt dac); all others are GJ per kg (EJ of energy per Mt of dac)") %>%
add_comments(sce) %>%
add_comments("For dac sector, the energy use coefficients from A62.globaltech_coef are interpolated into all model years") %>%
add_legacy_name(paste0("L262.GlobalTechCoef_dac_", tolower(sce))) %>%
add_precursors(paste0("energy/A62.globaltech_coef_", tolower(sce))) ->
x
assign(paste0("L262.GlobalTechCoef_dac_", tolower(sce)), x)
}
for(sce in TECH_PARAMETRIZATION_OUTPUTS) {
L262.GlobalTechShrwt_dac %>%
filter(scenario == sce) %>%
select(-c(scenario))%>%
add_title("Shareweights of global dac technologies") %>%
add_units("Unitless") %>%
add_comments("For dac sector, the share weights from A62.globaltech_shrwt are interpolated into all base years and future years") %>%
add_legacy_name(paste0("L262.GlobalTechShrwt_dac_",tolower(sce))) %>%
add_precursors(paste0("energy/A62.globaltech_shrwt_",tolower(sce))) ->
x
assign(paste0("L262.GlobalTechShrwt_dac_", tolower(sce)), x)
}
L262.CarbonCoef_dac %>%
add_title("Assumed carbon coefficient of air-derived CO2") %>%
add_units("Unitless C/C ratio") %>%
add_comments("Set in exogenous data table A62.PrimaryFuelCCoef") %>%
add_precursors("energy/A62.PrimaryFuelCCoef", "common/GCAM_region_names") ->
L262.CarbonCoef_dac
L262.Supplysector_dac %>%
add_title("Supply sector information for CO2 removal sector") %>%
add_units("NA") %>%
add_comments("For dac sector, the supply sector information (output.unit, input.unit, price.unit, logit.year.fillout, logit.exponent) from A62.sector is expended into all GCAM regions") %>%
add_legacy_name("L262.Supplysector_dac") %>%
add_precursors("energy/A62.sector", "common/GCAM_region_names") ->
L262.Supplysector_dac
L262.FinalEnergyKeyword_dac %>%
add_title("Supply sector keywords for dac sector") %>%
add_units("NA") %>%
add_comments("For dac sector, the supply sector final energy keywords from A62.sector are expended into all GCAM regions") %>%
add_legacy_name("L262.FinalEnergyKeyword_dac") %>%
add_precursors("energy/A62.sector", "common/GCAM_region_names") ->
L262.FinalEnergyKeyword_dac
L262.SubsectorLogit_dac %>%
add_title("Subsector logit exponents of dac sector") %>%
add_units("Unitless") %>%
add_comments("For dac sector, the subsector logit exponents from A62.subsector_logit are expanded into all GCAM regions") %>%
add_legacy_name("L262.SubsectorLogit_dac") %>%
add_precursors("energy/A62.subsector_logit", "common/GCAM_region_names") ->
L262.SubsectorLogit_dac
L262.SubsectorShrwtFllt_dac %>%
add_title("Subsector shareweights of dac sector") %>%
add_units("unitless") %>%
add_comments("For dac sector, the subsector shareweights from A62.subsector_shrwt are expanded into all GCAM regions") %>%
add_legacy_name("L262.SubsectorShrwtFllt_dac") %>%
add_precursors("energy/A62.subsector_shrwt", "common/GCAM_region_names") ->
L262.SubsectorShrwtFllt_dac
L262.SubsectorInterp_dac %>%
add_title("Subsector shareweight interpolation of dac sector") %>%
add_units("NA") %>%
add_comments("For dac sector, the subsector shareweight interpolation function infromation from A62.subsector_interp is expanded into all GCAM regions") %>%
add_legacy_name("L262.SubsectorInterp_dac") %>%
add_precursors("energy/A62.subsector_interp", "common/GCAM_region_names") ->
L262.SubsectorInterp_dac
L262.StubTech_dac %>%
add_title("Identification of stub technologies of dac") %>%
add_units("NA") %>%
add_comments("For dac sector, the stub technologies from A62.globaltech_shrwt are expanded into all GCAM regions") %>%
add_legacy_name("L262.StubTech_dac") %>%
add_precursors("energy/A62.globaltech_shrwt_ssp1", "energy/A62.globaltech_shrwt_ssp2","energy/A62.globaltech_shrwt_ssp3","energy/A62.globaltech_shrwt_ssp4","energy/A62.globaltech_shrwt_ssp5",
"common/GCAM_region_names") ->
L262.StubTech_dac
L262.GlobalTechShrwt_dac %>%
add_title("Shareweights of global dac technologies") %>%
add_units("Unitless") %>%
add_comments("For dac sector, the share weights from A62.globaltech_shrwt are interpolated into all base years and future years") %>%
add_precursors("energy/A62.globaltech_shrwt_ssp1","energy/A62.globaltech_shrwt_ssp2","energy/A62.globaltech_shrwt_ssp3","energy/A62.globaltech_shrwt_ssp4","energy/A62.globaltech_shrwt_ssp5") ->
L262.GlobalTechShrwt_dac
L262.GlobalTechCoef_dac %>%
add_title("Energy inputs and coefficients of dac technologies") %>%
add_units("airCO2 input is unitless (Mt airCO2 per Mt dac); all others are GJ per kg (EJ of energy per Mt of dac)") %>%
add_comments("For dac sector, the energy use coefficients from A62.globaltech_coef are interpolated into all model years") %>%
add_precursors("energy/A62.globaltech_coef_ssp1","energy/A62.globaltech_coef_ssp2","energy/A62.globaltech_coef_ssp3","energy/A62.globaltech_coef_ssp4","energy/A62.globaltech_coef_ssp5") ->
L262.GlobalTechCoef_dac
L262.GlobalTechCost_dac %>%
add_title("Non-energy costs of global dac manufacturing technologies") %>%
add_units("1975$/kg for supplysector dac; 1975$/GJ for supplysector process heat dac") %>%
add_comments("Includes non-energy related capture costs only per kgC captured from the atmosphere. Storage costs will be computed endogenously through the carbon storage markets. Additional non-energy cost of process heat dac assumed zero.") %>%
add_precursors("energy/A62.globaltech_cost_ssp1","energy/A62.globaltech_cost_ssp2","energy/A62.globaltech_cost_ssp3","energy/A62.globaltech_cost_ssp4","energy/A62.globaltech_cost_ssp5") ->
L262.GlobalTechCost_dac
L262.GlobalTechCapture_dac %>%
add_title("CO2 capture fractions from global dac production technologies with CCS") %>%
add_units("Unitless") %>%
add_comments("For dac sector, the remove fractions from A62.globaltech_co2capture are interpolated into all model years") %>%
add_legacy_name("L262.GlobalTechCapture_dac") %>%
add_precursors("energy/A62.globaltech_co2capture") ->
L262.GlobalTechCapture_dac
L262.PerCapitaBased_dac %>%
add_title("per-capita based flag for dac exports final demand") %>%
add_units("NA") %>%
add_comments("Per-capita based flags for dac from A62.demand are expanded into all GCAM regions") %>%
add_legacy_name("L262.PerCapitaBased_dac") %>%
add_precursors("energy/A62.demand", "common/GCAM_region_names") ->
L262.PerCapitaBased_dac
L262.PriceElasticity_dac %>%
add_title("price elasticity for dac") %>%
add_units("Unitless") %>%
add_comments("The elasticity values from A62.demand are expanded into all GCAM_regions") %>%
add_legacy_name("L262.PriceElasticity_dac") %>%
add_precursors("energy/A62.demand", "common/GCAM_region_names") ->
L262.PriceElasticity_dac
L262.StubTechProd_dac %>%
add_title("calibrated cdr values") %>%
add_units("Mt") %>%
add_comments("Values are calculated using L162.out_Mt_R_dac_Yh then added GCAM region information and supplysector, subsector, and technology information") %>%
add_legacy_name("L262.StubTechProd_dac") %>%
add_precursors("energy/calibrated_techs_cdr", "L162.out_Mt_R_dac_Yh", "common/GCAM_region_names") ->
L262.StubTechProd_dac
L262.BaseService_dac %>%
add_title("base-year service output of dac") %>%
add_units("Mt") %>%
add_comments("Transformed from L262.StubTechProd_dac by adding energy.final.demand from A62.demand") %>%
add_legacy_name("L262.BaseService_dac") %>%
add_precursors("energy/A62.demand", "energy/calibrated_techs_cdr", "L162.out_Mt_R_dac_Yh", "common/GCAM_region_names") ->
L262.BaseService_dac
L262.GlobalTechSCurve_dac %>%
add_title("Global tech lifetime and s-curve retirement function") %>%
add_units("year for lifetime and halflife; Unitless for steepness") %>%
add_comments("The values are extracted from L262.globaltech_retirement for entries that half life value is not NA") %>%
add_legacy_name("L262.GlobalTechSCurve_dac") %>%
add_precursors("energy/A62.globaltech_retirement") ->
L262.GlobalTechSCurve_dac
L262.GlobalTechProfitShutdown_dac %>%
add_title("Global tech profit shutdown decider") %>%
add_units("Unitless") %>%
add_comments("The values are extracted from L262.globaltech_retirement for entries that median shutdown point is not NA") %>%
add_legacy_name("L262.GlobalTechProfitShutdown_dac") %>%
add_precursors("energy/A62.globaltech_retirement") ->
L262.GlobalTechProfitShutdown_dac
return_data(L262.CarbonCoef_dac,
L262.Supplysector_dac, L262.FinalEnergyKeyword_dac, L262.SubsectorLogit_dac,
L262.SubsectorShrwtFllt_dac, L262.SubsectorInterp_dac,
L262.GlobalTechCost_dac,
L262.GlobalTechCost_dac_ssp1,L262.GlobalTechCost_dac_ssp2,L262.GlobalTechCost_dac_ssp3,L262.GlobalTechCost_dac_ssp4,L262.GlobalTechCost_dac_ssp5,
L262.StubTech_dac,
L262.GlobalTechShrwt_dac_ssp1,L262.GlobalTechShrwt_dac_ssp2,L262.GlobalTechShrwt_dac_ssp3,L262.GlobalTechShrwt_dac_ssp4,L262.GlobalTechShrwt_dac_ssp5,
L262.GlobalTechShrwt_dac,
L262.GlobalTechCoef_dac,
L262.GlobalTechCoef_dac_ssp1, L262.GlobalTechCoef_dac_ssp2, L262.GlobalTechCoef_dac_ssp3, L262.GlobalTechCoef_dac_ssp4, L262.GlobalTechCoef_dac_ssp5,
L262.GlobalTechCapture_dac,
L262.PerCapitaBased_dac,
L262.PriceElasticity_dac,L262.StubTechProd_dac,L262.BaseService_dac,L262.GlobalTechSCurve_dac,
L262.GlobalTechProfitShutdown_dac)
} else {
stop("Unknown command")
}
}
JGCRI/gcamdata documentation built on March 21, 2023, 2:19 a.m.
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Defines functions module_energy_L262.dac
Documented in module_energy_L262.dac
# Copyright 2019 Battelle Memorial Institute; see the LICENSE file.
#' module_energy_L262.dac
#'
#' Compute a variety of final energy keyword, sector, share weight, and technology information for dac-related GCAM inputs.
#'
#' @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{L262.SectorLogitTables[[ curr_table ]]$data}, \code{L262.Supplysector_dac}, \code{L262.FinalEnergyKeyword_dac},
#' \code{L262.SubsectorLogitTables[[ curr_table ]]$data}, \code{L262.SubsectorLogit_dac}, \code{L262.SubsectorShrwtFllt_dac},
#' \code{L262.SubsectorInterp_dac}, \code{L262.StubTech_dac}, \code{L262.GlobalTechShrwt_dac}, \code{L262.GlobalTechCoef_dac},
#' \code{L262.GlobalTechCost_dac}, \code{L262.GlobalTechCapture_dac}, \code{L262.StubTechProd_dac}, \code{L262.StubTechCalInput_dac_heat},
#' \code{L262.StubTechCoef_dac}, \code{L262.PerCapitaBased_dac}, \code{L262.BaseService_dac}, \code{L262.PriceElasticity_dac}, \code{object}.
#' The corresponding file in the original data system was \code{L262.dac.R} (energy level2).
#' @details The chunk provides final energy keyword, supplysector/subsector information, supplysector/subsector interpolation information, global technology share weight, global technology efficiency, global technology coefficients, global technology cost, price elasticity, stub technology information, stub technology interpolation information, stub technology calibrated inputs, and etc for dac sector.
#' @importFrom assertthat assert_that
#' @importFrom dplyr arrange bind_rows distinct filter if_else group_by lag left_join mutate pull select
#' @importFrom tidyr complete nesting
#' @author JF March 2021
module_energy_L262.dac <- function(command, ...) {
TECH_PARAMETRIZATION_OUTPUTS <- paste0("ssp", 1:5)
if(command == driver.DECLARE_INPUTS) {
return(c(FILE = "common/GCAM_region_names",
FILE = "energy/calibrated_techs_cdr",
FILE = "energy/A62.PrimaryFuelCCoef",
FILE = "energy/A62.sector",
FILE = "energy/A62.subsector_interp",
FILE = "energy/A62.subsector_logit",
FILE = "energy/A62.subsector_shrwt",
FILE = "energy/A62.globaltech_coef_ssp1",
FILE = "energy/A62.globaltech_coef_ssp2",
FILE = "energy/A62.globaltech_coef_ssp3",
FILE = "energy/A62.globaltech_coef_ssp4",
FILE = "energy/A62.globaltech_coef_ssp5",
FILE = "energy/A62.globaltech_cost_ssp1",
FILE = "energy/A62.globaltech_cost_ssp2",
FILE = "energy/A62.globaltech_cost_ssp3",
FILE = "energy/A62.globaltech_cost_ssp4",
FILE = "energy/A62.globaltech_cost_ssp5",
FILE = "energy/A62.globaltech_shrwt_ssp1",
FILE = "energy/A62.globaltech_shrwt_ssp2",
FILE = "energy/A62.globaltech_shrwt_ssp3",
FILE = "energy/A62.globaltech_shrwt_ssp4",
FILE = "energy/A62.globaltech_shrwt_ssp5",
FILE = "energy/A62.globaltech_co2capture",
FILE = "energy/A62.demand",
FILE = "energy/A62.globaltech_retirement",
"L162.out_Mt_R_dac_Yh"))
} else if(command == driver.DECLARE_OUTPUTS) {
return(c("L262.CarbonCoef_dac",
"L262.Supplysector_dac",
"L262.FinalEnergyKeyword_dac",
"L262.SubsectorLogit_dac",
"L262.SubsectorShrwtFllt_dac",
"L262.SubsectorInterp_dac",
"L262.GlobalTechCost_dac",
"L262.GlobalTechCost_dac_ssp1",
"L262.GlobalTechCost_dac_ssp2",
"L262.GlobalTechCost_dac_ssp3",
"L262.GlobalTechCost_dac_ssp4",
"L262.GlobalTechCost_dac_ssp5",
"L262.StubTech_dac",
"L262.GlobalTechShrwt_dac",
"L262.GlobalTechShrwt_dac_ssp1",
"L262.GlobalTechShrwt_dac_ssp2",
"L262.GlobalTechShrwt_dac_ssp3",
"L262.GlobalTechShrwt_dac_ssp4",
"L262.GlobalTechShrwt_dac_ssp5",
'L262.GlobalTechCoef_dac',
"L262.GlobalTechCoef_dac_ssp1",
"L262.GlobalTechCoef_dac_ssp2",
"L262.GlobalTechCoef_dac_ssp3",
"L262.GlobalTechCoef_dac_ssp4",
"L262.GlobalTechCoef_dac_ssp5",
"L262.GlobalTechCapture_dac",
"L262.PerCapitaBased_dac",
"L262.PriceElasticity_dac",
"L262.StubTechProd_dac",
"L262.BaseService_dac",
"L262.GlobalTechSCurve_dac",
"L262.GlobalTechProfitShutdown_dac"))
} else if(command == driver.MAKE) {
all_data <- list(...)[[1]]
# Load required inputs
GCAM_region_names <- get_data(all_data, "common/GCAM_region_names")
calibrated_techs <- get_data(all_data, "energy/calibrated_techs_cdr")
A62.PrimaryFuelCCoef <- get_data(all_data, "energy/A62.PrimaryFuelCCoef", strip_attributes = TRUE)
A62.sector <- get_data(all_data, "energy/A62.sector", strip_attributes = TRUE)
A62.subsector_interp <- get_data(all_data, "energy/A62.subsector_interp", strip_attributes = TRUE)
A62.subsector_logit <- get_data(all_data, "energy/A62.subsector_logit", strip_attributes = TRUE)
A62.subsector_shrwt <- get_data(all_data, "energy/A62.subsector_shrwt", strip_attributes = TRUE)
A62.globaltech_co2capture <- get_data(all_data, "energy/A62.globaltech_co2capture")
A62.demand <- get_data(all_data, "energy/A62.demand", strip_attributes = TRUE)
A62.globaltech_retirement <- get_data(all_data, "energy/A62.globaltech_retirement", strip_attributes = TRUE)
L162.out_Mt_R_dac_Yh <- get_data(all_data, "L162.out_Mt_R_dac_Yh", strip_attributes = TRUE)
#load ssp parametrizations
A62.globaltech_coef_ssp1 <- get_data(all_data, "energy/A62.globaltech_coef_ssp1")%>% gather_years %>% mutate(scenario=paste0("ssp1"))
A62.globaltech_coef_ssp2 <- get_data(all_data, "energy/A62.globaltech_coef_ssp2")%>% gather_years %>% mutate(scenario=paste0("ssp2"))
A62.globaltech_coef_ssp3 <- get_data(all_data, "energy/A62.globaltech_coef_ssp3")%>% gather_years %>% mutate(scenario=paste0("ssp3"))
A62.globaltech_coef_ssp4 <- get_data(all_data, "energy/A62.globaltech_coef_ssp4")%>% gather_years %>% mutate(scenario=paste0("ssp4"))
A62.globaltech_coef_ssp5 <- get_data(all_data, "energy/A62.globaltech_coef_ssp5")%>% gather_years %>% mutate(scenario=paste0("ssp5"))
A62.globaltech_cost_ssp1 <- get_data(all_data, "energy/A62.globaltech_cost_ssp1")%>% gather_years %>% mutate(scenario=paste0("ssp1"))
A62.globaltech_cost_ssp2 <- get_data(all_data, "energy/A62.globaltech_cost_ssp2")%>% gather_years %>% mutate(scenario=paste0("ssp2"))
A62.globaltech_cost_ssp3 <- get_data(all_data, "energy/A62.globaltech_cost_ssp3")%>% gather_years %>% mutate(scenario=paste0("ssp3"))
A62.globaltech_cost_ssp4 <- get_data(all_data, "energy/A62.globaltech_cost_ssp4")%>% gather_years %>% mutate(scenario=paste0("ssp4"))
A62.globaltech_cost_ssp5 <- get_data(all_data, "energy/A62.globaltech_cost_ssp5")%>% gather_years %>% mutate(scenario=paste0("ssp5"))
A62.globaltech_shrwt_ssp1 <- get_data(all_data, "energy/A62.globaltech_shrwt_ssp1")%>% gather_years %>% mutate(scenario=paste0("ssp1"))
A62.globaltech_shrwt_ssp2 <- get_data(all_data, "energy/A62.globaltech_shrwt_ssp2")%>% gather_years %>% mutate(scenario=paste0("ssp2"))
A62.globaltech_shrwt_ssp3 <- get_data(all_data, "energy/A62.globaltech_shrwt_ssp3")%>% gather_years %>% mutate(scenario=paste0("ssp3"))
A62.globaltech_shrwt_ssp4 <- get_data(all_data, "energy/A62.globaltech_shrwt_ssp4")%>% gather_years %>% mutate(scenario=paste0("ssp4"))
A62.globaltech_shrwt_ssp5 <- get_data(all_data, "energy/A62.globaltech_shrwt_ssp5")%>% gather_years %>% mutate(scenario=paste0("ssp5"))
# ===================================================
# 0. Give binding for variable names used in pipeline
year <- value <- GCAM_region_ID <- sector <- fuel <- year.fillout <- to.value <-
technology <- supplysector <- subsector <- minicam.energy.input <- coefficient <-
remove.fraction <- minicam.non.energy.input <- input.cost <- PrimaryFuelCO2Coef.name <-
PrimaryFuelCO2Coef <- calibration <- calOutputValue <- subs.share.weight <- region <-
calibrated.value <- . <- scenario <- temp_lag <- base.service <- energy.final.demand <-
value.x <- value.y <- parameter <- half.life <- median.shutdown.point <-
L262.GlobalTechCoef_dac_ssp1 <- L262.GlobalTechCoef_dac_ssp2 <-L262.GlobalTechCoef_dac_ssp3 <-L262.GlobalTechCoef_dac_ssp4 <-L262.GlobalTechCoef_dac_ssp5 <-
L262.GlobalTechCost_dac_ssp1 <- L262.GlobalTechCost_dac_ssp2 <- L262.GlobalTechCost_dac_ssp3 <- L262.GlobalTechCost_dac_ssp4 <- L262.GlobalTechCost_dac_ssp5 <-
L262.GlobalTechShrwt_dac_ssp1 <- L262.GlobalTechShrwt_dac_ssp2 <- L262.GlobalTechShrwt_dac_ssp3 <- L262.GlobalTechShrwt_dac_ssp4 <- L262.GlobalTechShrwt_dac_ssp5 <- NULL
# ===================================================
# 1. Perform computations
# Prelim - carbon coefficient (emissions factor)
A62.PrimaryFuelCCoef %>%
write_to_all_regions(c(LEVEL2_DATA_NAMES[["CarbonCoef"]]), GCAM_region_names = GCAM_region_names, has_traded = TRUE) -> L262.CarbonCoef_dac
# 1a. Supplysector information
# L262.Supplysector_dac: Supply sector information for CO2 removal sector containing dac subsectors and technologies
A62.sector %>%
write_to_all_regions(c(LEVEL2_DATA_NAMES[["Supplysector"]], LOGIT_TYPE_COLNAME), GCAM_region_names) ->
L262.Supplysector_dac
# L262.FinalEnergyKeyword_dac: Supply sector keywords for CO2 removal sector
A62.sector %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["FinalEnergyKeyword"]], GCAM_region_names) %>%
na.omit ->
L262.FinalEnergyKeyword_dac
# 1b. Subsector information
# L262.SubsectorLogit_dac: Subsector logit exponents of CO2 removal sector
A62.subsector_logit %>%
write_to_all_regions(c(LEVEL2_DATA_NAMES[["SubsectorLogit"]], LOGIT_TYPE_COLNAME), GCAM_region_names) ->
L262.SubsectorLogit_dac
# and L262.SubsectorShrwtFllt_dac: Subsector shareweights of CO2 removal sector
A62.subsector_shrwt %>%
filter(!is.na(year.fillout)) %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["SubsectorShrwtFllt"]], GCAM_region_names) ->
L262.SubsectorShrwtFllt_dac
# L262.SubsectorInterp_dac: Subsector shareweight interpolation of CO2 removal sector
A62.subsector_interp %>%
filter(is.na(to.value)) %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["SubsectorInterp"]], GCAM_region_names) ->
L262.SubsectorInterp_dac
# 1c. Technology information
# L262.StubTech_dac: Identification of stub technologies of dac
# Note: assuming that technology list in the shareweight table includes the full set (any others would default to a 0 shareweight)
A62.globaltech_shrwt <- bind_rows(A62.globaltech_shrwt_ssp1,A62.globaltech_shrwt_ssp2,A62.globaltech_shrwt_ssp3,A62.globaltech_shrwt_ssp4,A62.globaltech_shrwt_ssp5)
A62.globaltech_shrwt %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["Tech"]], GCAM_region_names) %>%
rename(stub.technology = technology) ->
L262.StubTech_dac
# L262.GlobalTechShrwt_dac: Shareweights of global dac technologies
A62.globaltech_shrwt %>%
gather_years %>%
complete(nesting(supplysector, subsector, technology,scenario), year = c(year, MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)) %>%
arrange(supplysector, subsector, technology, scenario,year) %>%
group_by(scenario,supplysector, subsector, technology) %>%
mutate(share.weight = approx_fun(year, value, rule = 1)) %>%
ungroup %>%
filter(year %in% c(MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)) %>%
rename(sector.name = supplysector,
subsector.name = subsector) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechYr"]], "share.weight","scenario") ->
L262.GlobalTechShrwt_dac
#L262.GlobalTechCoef_dac: Energy inputs and coefficients of dac technologies
#concatenate tables of all ssps into one table for later filtering
A62.globaltech_coef <- bind_rows(A62.globaltech_coef_ssp1,A62.globaltech_coef_ssp2,A62.globaltech_coef_ssp3,A62.globaltech_coef_ssp4,A62.globaltech_coef_ssp5)
A62.globaltech_coef %>%
gather_years %>%
complete(nesting(supplysector, subsector, technology, minicam.energy.input,scenario), year = c(year, MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)) %>%
arrange(supplysector, subsector, technology, minicam.energy.input, scenario,year) %>%
group_by(scenario,supplysector, subsector, technology, minicam.energy.input) %>%
mutate(coefficient = approx_fun(year, value, rule = 1),
coefficient = round(coefficient, energy.DIGITS_COEFFICIENT)) %>%
ungroup %>%
filter(year %in% c(MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)) %>%
rename(sector.name = supplysector,
subsector.name = subsector) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechCoef"]],'scenario') ->
L262.GlobalTechCoef_dac
# Carbon capture rates for dac.
# L262.GlobalTechCapture_dac: defines CO2 capture fractions for dac (by definition 1, as all inputs are defined per tonne C removed from the atmosphere),
# as well as a separately-defined process heat dac sector, which has slightly lower capture rates for natural gas combustion emissions.
# This allows separate consideration of the capture fraction of any combustion emissions resulting from the process heat input
# No need to consider historical periods here
A62.globaltech_co2capture %>%
gather_years %>%
complete(nesting(supplysector, subsector, technology), year = c(year, MODEL_FUTURE_YEARS)) %>%
arrange(supplysector, subsector, technology, year) %>%
group_by(supplysector, subsector, technology) %>%
mutate(remove.fraction = approx_fun(year, value, rule = 1),
remove.fraction = round(remove.fraction, energy.DIGITS_REMOVE.FRACTION)) %>%
ungroup %>%
filter(year %in% MODEL_FUTURE_YEARS) %>%
rename(sector.name = supplysector,
subsector.name = subsector) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechYr"]], "remove.fraction") %>%
mutate(storage.market = energy.CO2.STORAGE.MARKET) ->
L262.GlobalTechCapture_dac
# L262.GlobalTechCost_dac: Non-energy costs of global dac technologies
#first we concatenate all the ssp cost parametrizations into one table, for later filtering
A62.globaltech_cost <- bind_rows(A62.globaltech_cost_ssp1,A62.globaltech_cost_ssp2,A62.globaltech_cost_ssp3,A62.globaltech_cost_ssp4,A62.globaltech_cost_ssp5)
A62.globaltech_cost %>%
gather_years %>%
complete(nesting(supplysector, subsector, technology, minicam.non.energy.input,scenario), year = c(year, MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)) %>%
arrange(supplysector, subsector, technology, minicam.non.energy.input, scenario,year) %>%
group_by(scenario,supplysector, subsector, technology, minicam.non.energy.input) %>%
mutate(input.cost = approx_fun(year, value, rule = 1),
input.cost = round(input.cost, energy.DIGITS_COST)) %>%
ungroup %>%
filter(year %in% c(MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)) %>%
rename(sector.name = supplysector,
subsector.name = subsector) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechCost"]],'scenario') ->
L262.GlobalTechCost_dac # intermediate tibble
L262.GlobalTechCapture_dac %>%
pull(remove.fraction) %>%
mean -> dac_CO2_capture_frac
L262.GlobalTechCoef_dac %>%
filter(minicam.energy.input == "airCO2") %>%
pull(coefficient) %>%
mean ->
coef_mean # temporary value
#Calibration and region-specific data
# L262.StubTechProd_dac: calibrated CO2 removal (cdr) production (arbitrarily high value met entirely by no-capture technology in history)
calibrated_techs %>%
filter(calibration == "output") %>% # Only take the tech IDs where the calibration is identified as output
select(sector, supplysector, subsector, technology) %>%
distinct ->
calibrated_techs_export # temporary tibble
L162.out_Mt_R_dac_Yh %>%
filter(year %in% MODEL_BASE_YEARS) %>%
mutate(calOutputValue = round(value, energy.DIGITS_CALOUTPUT)) %>%
left_join_error_no_match(GCAM_region_names, by = "GCAM_region_ID") %>%
left_join_error_no_match(calibrated_techs_export, by = "sector") %>%
mutate(stub.technology = technology,
share.weight.year = year,
subs.share.weight = if_else(calOutputValue > 0, 1, 0),
tech.share.weight = subs.share.weight) %>%
select(LEVEL2_DATA_NAMES[["StubTechProd"]]) ->
L262.StubTechProd_dac
# L262.PerCapitaBased_dac: per-capita based flag for dac exports final demand. Note that this should be zero as the amount of DAC shouldn't be explicitly tied to population
A62.demand %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["PerCapitaBased"]], GCAM_region_names) ->
L262.PerCapitaBased_dac
# L262.BaseService_dac: base-year service output of dac (arbitrarily high)
L262.StubTechProd_dac %>%
select(region, year, base.service = calOutputValue) %>%
mutate(energy.final.demand = A62.demand[["energy.final.demand"]]) ->
L262.BaseService_dac
# L262.PriceElasticity_dac: price elasticity (zero to represent the backstop nature of dac technology)
A62.demand %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["PriceElasticity"]][LEVEL2_DATA_NAMES[["PriceElasticity"]] != "year"], GCAM_region_names) %>%
repeat_add_columns(tibble(year = MODEL_FUTURE_YEARS)) %>%
select(LEVEL2_DATA_NAMES[["PriceElasticity"]]) ->
L262.PriceElasticity_dac
# Retirement information
A62.globaltech_retirement %>%
set_years %>%
mutate(year = as.integer(year)) %>%
rename(sector.name = supplysector, subsector.name = subsector) ->
A62.globaltech_retirement_with_years
# Copy the data in the last base year period through to the end year
A62.globaltech_retirement_with_years %>%
filter(year == max(MODEL_BASE_YEARS)) ->
A62.globaltech_retirement_max_baseyear
A62.globaltech_retirement_with_years %>%
filter(year == min(MODEL_FUTURE_YEARS)) %>%
select(-year) %>%
repeat_add_columns(tibble(year = MODEL_FUTURE_YEARS)) %>%
bind_rows(A62.globaltech_retirement_max_baseyear) ->
L262.globaltech_retirement
# Retirement may consist of any of three types of retirement function (phased, s-curve, or none)
# All of these options have different headers, and all are allowed
# L262.GlobalTechSCurve_dac: Global tech lifetime and s-curve retirement function
L262.globaltech_retirement %>%
filter(!is.na(half.life)) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechYr"]], "lifetime", "steepness", "half.life") ->
L262.GlobalTechSCurve_dac
# L262.GlobalTechProfitShutdown_dac: Global tech profit shutdown decider.
L262.globaltech_retirement %>%
filter(!is.na(median.shutdown.point)) %>%
select(LEVEL2_DATA_NAMES[["GlobalTechYr"]], "median.shutdown.point", "profit.shutdown.steepness") ->
L262.GlobalTechProfitShutdown_dac
# ===================================================
# Produce outputs
# Extract SSP data and assign to separate tables
for(sce in TECH_PARAMETRIZATION_OUTPUTS) {
L262.GlobalTechCost_dac %>%
filter(scenario == sce) %>%
select(-c(scenario))%>%
add_title(paste("Cost coefficients of dac -", sce)) %>%
add_units("1975$/kg for supplysector dac; 1975$/GJ for supplysector process heat dac") %>%
add_comments(sce) %>%
add_comments("Includes non-energy related capture costs only per kgC captured from the atmosphere. Storage costs will be computed endogenously through the carbon storage markets. Additional non-energy cost of process heat dac assumed zero.") %>%
add_legacy_name(paste0("L262.GlobalTechCost_dac_", tolower(sce))) %>%
add_precursors(paste0("energy/A62.globaltech_cost_", tolower(sce))) ->
x
assign(paste0("L262.GlobalTechCost_dac_", tolower(sce)), x)
}
for(sce in TECH_PARAMETRIZATION_OUTPUTS) {
L262.GlobalTechCoef_dac %>%
filter(scenario == sce) %>%
select(-c(scenario))%>%
add_title(paste("Tech coefficients of dac -", sce)) %>%
add_units("airCO2 input is unitless (Mt airCO2 per Mt dac); all others are GJ per kg (EJ of energy per Mt of dac)") %>%
add_comments(sce) %>%
add_comments("For dac sector, the energy use coefficients from A62.globaltech_coef are interpolated into all model years") %>%
add_legacy_name(paste0("L262.GlobalTechCoef_dac_", tolower(sce))) %>%
add_precursors(paste0("energy/A62.globaltech_coef_", tolower(sce))) ->
x
assign(paste0("L262.GlobalTechCoef_dac_", tolower(sce)), x)
}
for(sce in TECH_PARAMETRIZATION_OUTPUTS) {
L262.GlobalTechShrwt_dac %>%
filter(scenario == sce) %>%
select(-c(scenario))%>%
add_title("Shareweights of global dac technologies") %>%
add_units("Unitless") %>%
add_comments("For dac sector, the share weights from A62.globaltech_shrwt are interpolated into all base years and future years") %>%
add_legacy_name(paste0("L262.GlobalTechShrwt_dac_",tolower(sce))) %>%
add_precursors(paste0("energy/A62.globaltech_shrwt_",tolower(sce))) ->
x
assign(paste0("L262.GlobalTechShrwt_dac_", tolower(sce)), x)
}
L262.CarbonCoef_dac %>%
add_title("Assumed carbon coefficient of air-derived CO2") %>%
add_units("Unitless C/C ratio") %>%
add_comments("Set in exogenous data table A62.PrimaryFuelCCoef") %>%
add_precursors("energy/A62.PrimaryFuelCCoef", "common/GCAM_region_names") ->
L262.CarbonCoef_dac
L262.Supplysector_dac %>%
add_title("Supply sector information for CO2 removal sector") %>%
add_units("NA") %>%
add_comments("For dac sector, the supply sector information (output.unit, input.unit, price.unit, logit.year.fillout, logit.exponent) from A62.sector is expended into all GCAM regions") %>%
add_legacy_name("L262.Supplysector_dac") %>%
add_precursors("energy/A62.sector", "common/GCAM_region_names") ->
L262.Supplysector_dac
L262.FinalEnergyKeyword_dac %>%
add_title("Supply sector keywords for dac sector") %>%
add_units("NA") %>%
add_comments("For dac sector, the supply sector final energy keywords from A62.sector are expended into all GCAM regions") %>%
add_legacy_name("L262.FinalEnergyKeyword_dac") %>%
add_precursors("energy/A62.sector", "common/GCAM_region_names") ->
L262.FinalEnergyKeyword_dac
L262.SubsectorLogit_dac %>%
add_title("Subsector logit exponents of dac sector") %>%
add_units("Unitless") %>%
add_comments("For dac sector, the subsector logit exponents from A62.subsector_logit are expanded into all GCAM regions") %>%
add_legacy_name("L262.SubsectorLogit_dac") %>%
add_precursors("energy/A62.subsector_logit", "common/GCAM_region_names") ->
L262.SubsectorLogit_dac
L262.SubsectorShrwtFllt_dac %>%
add_title("Subsector shareweights of dac sector") %>%
add_units("unitless") %>%
add_comments("For dac sector, the subsector shareweights from A62.subsector_shrwt are expanded into all GCAM regions") %>%
add_legacy_name("L262.SubsectorShrwtFllt_dac") %>%
add_precursors("energy/A62.subsector_shrwt", "common/GCAM_region_names") ->
L262.SubsectorShrwtFllt_dac
L262.SubsectorInterp_dac %>%
add_title("Subsector shareweight interpolation of dac sector") %>%
add_units("NA") %>%
add_comments("For dac sector, the subsector shareweight interpolation function infromation from A62.subsector_interp is expanded into all GCAM regions") %>%
add_legacy_name("L262.SubsectorInterp_dac") %>%
add_precursors("energy/A62.subsector_interp", "common/GCAM_region_names") ->
L262.SubsectorInterp_dac
L262.StubTech_dac %>%
add_title("Identification of stub technologies of dac") %>%
add_units("NA") %>%
add_comments("For dac sector, the stub technologies from A62.globaltech_shrwt are expanded into all GCAM regions") %>%
add_legacy_name("L262.StubTech_dac") %>%
add_precursors("energy/A62.globaltech_shrwt_ssp1", "energy/A62.globaltech_shrwt_ssp2","energy/A62.globaltech_shrwt_ssp3","energy/A62.globaltech_shrwt_ssp4","energy/A62.globaltech_shrwt_ssp5",
"common/GCAM_region_names") ->
L262.StubTech_dac
L262.GlobalTechShrwt_dac %>%
add_title("Shareweights of global dac technologies") %>%
add_units("Unitless") %>%
add_comments("For dac sector, the share weights from A62.globaltech_shrwt are interpolated into all base years and future years") %>%
add_precursors("energy/A62.globaltech_shrwt_ssp1","energy/A62.globaltech_shrwt_ssp2","energy/A62.globaltech_shrwt_ssp3","energy/A62.globaltech_shrwt_ssp4","energy/A62.globaltech_shrwt_ssp5") ->
L262.GlobalTechShrwt_dac
L262.GlobalTechCoef_dac %>%
add_title("Energy inputs and coefficients of dac technologies") %>%
add_units("airCO2 input is unitless (Mt airCO2 per Mt dac); all others are GJ per kg (EJ of energy per Mt of dac)") %>%
add_comments("For dac sector, the energy use coefficients from A62.globaltech_coef are interpolated into all model years") %>%
add_precursors("energy/A62.globaltech_coef_ssp1","energy/A62.globaltech_coef_ssp2","energy/A62.globaltech_coef_ssp3","energy/A62.globaltech_coef_ssp4","energy/A62.globaltech_coef_ssp5") ->
L262.GlobalTechCoef_dac
L262.GlobalTechCost_dac %>%
add_title("Non-energy costs of global dac manufacturing technologies") %>%
add_units("1975$/kg for supplysector dac; 1975$/GJ for supplysector process heat dac") %>%
add_comments("Includes non-energy related capture costs only per kgC captured from the atmosphere. Storage costs will be computed endogenously through the carbon storage markets. Additional non-energy cost of process heat dac assumed zero.") %>%
add_precursors("energy/A62.globaltech_cost_ssp1","energy/A62.globaltech_cost_ssp2","energy/A62.globaltech_cost_ssp3","energy/A62.globaltech_cost_ssp4","energy/A62.globaltech_cost_ssp5") ->
L262.GlobalTechCost_dac
L262.GlobalTechCapture_dac %>%
add_title("CO2 capture fractions from global dac production technologies with CCS") %>%
add_units("Unitless") %>%
add_comments("For dac sector, the remove fractions from A62.globaltech_co2capture are interpolated into all model years") %>%
add_legacy_name("L262.GlobalTechCapture_dac") %>%
add_precursors("energy/A62.globaltech_co2capture") ->
L262.GlobalTechCapture_dac
L262.PerCapitaBased_dac %>%
add_title("per-capita based flag for dac exports final demand") %>%
add_units("NA") %>%
add_comments("Per-capita based flags for dac from A62.demand are expanded into all GCAM regions") %>%
add_legacy_name("L262.PerCapitaBased_dac") %>%
add_precursors("energy/A62.demand", "common/GCAM_region_names") ->
L262.PerCapitaBased_dac
L262.PriceElasticity_dac %>%
add_title("price elasticity for dac") %>%
add_units("Unitless") %>%
add_comments("The elasticity values from A62.demand are expanded into all GCAM_regions") %>%
add_legacy_name("L262.PriceElasticity_dac") %>%
add_precursors("energy/A62.demand", "common/GCAM_region_names") ->
L262.PriceElasticity_dac
L262.StubTechProd_dac %>%
add_title("calibrated cdr values") %>%
add_units("Mt") %>%
add_comments("Values are calculated using L162.out_Mt_R_dac_Yh then added GCAM region information and supplysector, subsector, and technology information") %>%
add_legacy_name("L262.StubTechProd_dac") %>%
add_precursors("energy/calibrated_techs_cdr", "L162.out_Mt_R_dac_Yh", "common/GCAM_region_names") ->
L262.StubTechProd_dac
L262.BaseService_dac %>%
add_title("base-year service output of dac") %>%
add_units("Mt") %>%
add_comments("Transformed from L262.StubTechProd_dac by adding energy.final.demand from A62.demand") %>%
add_legacy_name("L262.BaseService_dac") %>%
add_precursors("energy/A62.demand", "energy/calibrated_techs_cdr", "L162.out_Mt_R_dac_Yh", "common/GCAM_region_names") ->
L262.BaseService_dac
L262.GlobalTechSCurve_dac %>%
add_title("Global tech lifetime and s-curve retirement function") %>%
add_units("year for lifetime and halflife; Unitless for steepness") %>%
add_comments("The values are extracted from L262.globaltech_retirement for entries that half life value is not NA") %>%
add_legacy_name("L262.GlobalTechSCurve_dac") %>%
add_precursors("energy/A62.globaltech_retirement") ->
L262.GlobalTechSCurve_dac
L262.GlobalTechProfitShutdown_dac %>%
add_title("Global tech profit shutdown decider") %>%
add_units("Unitless") %>%
add_comments("The values are extracted from L262.globaltech_retirement for entries that median shutdown point is not NA") %>%
add_legacy_name("L262.GlobalTechProfitShutdown_dac") %>%
add_precursors("energy/A62.globaltech_retirement") ->
L262.GlobalTechProfitShutdown_dac
return_data(L262.CarbonCoef_dac,
L262.Supplysector_dac, L262.FinalEnergyKeyword_dac, L262.SubsectorLogit_dac,
L262.SubsectorShrwtFllt_dac, L262.SubsectorInterp_dac,
L262.GlobalTechCost_dac,
L262.GlobalTechCost_dac_ssp1,L262.GlobalTechCost_dac_ssp2,L262.GlobalTechCost_dac_ssp3,L262.GlobalTechCost_dac_ssp4,L262.GlobalTechCost_dac_ssp5,
L262.StubTech_dac,
L262.GlobalTechShrwt_dac_ssp1,L262.GlobalTechShrwt_dac_ssp2,L262.GlobalTechShrwt_dac_ssp3,L262.GlobalTechShrwt_dac_ssp4,L262.GlobalTechShrwt_dac_ssp5,
L262.GlobalTechShrwt_dac,
L262.GlobalTechCoef_dac,
L262.GlobalTechCoef_dac_ssp1, L262.GlobalTechCoef_dac_ssp2, L262.GlobalTechCoef_dac_ssp3, L262.GlobalTechCoef_dac_ssp4, L262.GlobalTechCoef_dac_ssp5,
L262.GlobalTechCapture_dac,
L262.PerCapitaBased_dac,
L262.PriceElasticity_dac,L262.StubTechProd_dac,L262.BaseService_dac,L262.GlobalTechSCurve_dac,
L262.GlobalTechProfitShutdown_dac)
} else {
stop("Unknown command")
}
}
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