R/zchunk_L231.proc_sector.R
In rohmin9122/gcam-korea-release: Build the GCAM-Korea Input Datasets
Defines functions
module_emissions_L231.proc_sector
Documented in
module_emissions_L231.proc_sector
#' module_emissions_L231.proc_sector
#'
#' Writes urban & industrial processing sector outputs.
#'
#' @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{L231.UnlimitRsrc}, \code{L231.UnlimitRsrcPrice}, \code{L231.FinalDemand_urb}, \code{L231.SectorLogitTables[[ curr_table ]]$data}, \code{L231.Supplysector_urb_ind}, \code{L231.SubsectorLogitTables[[ curr_table ]]$data}, \code{L231.SubsectorLogit_urb_ind}, \code{L231.SubsectorShrwt_urb_ind}, \code{L231.SubsectorShrwtFllt_urb_ind}, \code{L231.SubsectorInterp_urb_ind}, \code{L231.SubsectorInterpTo_urb_ind}, \code{L231.StubTech_urb_ind}, \code{L231.GlobalTechShrwt_urb_ind}, \code{L231.GlobalTechEff_urb_ind}, \code{L231.GlobalTechCoef_urb_ind}, \code{L231.GlobalTechCost_urb_ind}, \code{L231.RegionalTechCalValue_urb_ind}, \code{L231.IndCoef}. The corresponding file in the
#' original data system was \code{L231.proc_sector.R} (emissions level2).
#' @details For urban processes and industrial processes, produces global technology coefficients,
#' costs, efficiencies, and shareweights by interpolating assumption file data. For urb & ind. processing subsectors
#' and supplysectors, produces logit, shareweights, and interpolation files by writing assumption file data to all regions.
#' Writes out coefficients and prices for misc emissions sources from assumption file data.
#' Outputs urban processing demand using constants. StubTech mapping file created from assumption mappings.
#' Regional technology calibration values created with constant. Industry input-output coefficient file created.
#' @importFrom assertthat assert_that
#' @importFrom dplyr filter mutate select
#' @importFrom tidyr gather spread
#' @author RLH July 2017
module_emissions_L231.proc_sector <- function(command, ...) {
if(command == driver.DECLARE_INPUTS) {
return(c(FILE = "common/GCAM_region_names",
FILE = "emissions/A_regions",
FILE = "emissions/A31.rsrc_info", # Units and source
FILE = "emissions/A31.sector", # source
FILE = "emissions/A31.subsector_logit", # source
FILE = "emissions/A31.subsector_shrwt", # source
FILE = "emissions/A31.subsector_interp", # source
FILE = "emissions/A31.globaltech_shrwt", # source
FILE = "emissions/A31.globaltech_eff", # Units and source
FILE = "emissions/A31.globaltech_cost", # Units and source
FILE = "emissions/A31.globaltech_coef", # Units and source
FILE = "energy/A32.globaltech_eff", # Units and source
"L1322.in_EJ_R_indfeed_F_Yh",
"L1322.in_EJ_R_indenergy_F_Yh"))
} else if(command == driver.DECLARE_OUTPUTS) {
return(c("L231.UnlimitRsrc",
"L231.UnlimitRsrcPrice",
"L231.FinalDemand_urb",
"L231.Supplysector_urb_ind",
"L231.SubsectorLogit_urb_ind",
"L231.SubsectorShrwt_urb_ind",
"L231.SubsectorShrwtFllt_urb_ind",
"L231.SubsectorInterp_urb_ind",
"L231.SubsectorInterpTo_urb_ind",
"L231.StubTech_urb_ind",
"L231.GlobalTechShrwt_urb_ind",
"L231.GlobalTechEff_urb_ind",
"L231.GlobalTechCoef_urb_ind",
"L231.GlobalTechCost_urb_ind",
"L231.RegionalTechCalValue_urb_ind",
"L231.IndCoef"))
} else if(command == driver.MAKE) {
# Silence package checks
year <- value <- share.weight <- efficiency <- input.cost <- coefficient <-
year.fillout <- to.value <- supplysector <- subsector <- technology <- minicam.energy.input <-
minicam.non.energy.input <- region <- sector.name <- subsector.name <- calibrated.value <-
market <- resource_type <- resource <- `output-unit` <- `price-unit` <- capacity.factor <-
secondary.output <- GCAM_region_ID <- service <- ind_proc_input <- ind_output <- NULL
all_data <- list(...)[[1]]
# Load required inputs
GCAM_region_names <- get_data(all_data, "common/GCAM_region_names")
A_regions <- get_data(all_data, "emissions/A_regions")
A31.rsrc_info <- get_data(all_data, "emissions/A31.rsrc_info") %>%
gather_years
A31.sector <- get_data(all_data, "emissions/A31.sector")
A31.subsector_logit <- get_data(all_data, "emissions/A31.subsector_logit")
A31.subsector_shrwt <- get_data(all_data, "emissions/A31.subsector_shrwt")
A31.subsector_interp <- get_data(all_data, "emissions/A31.subsector_interp")
A31.globaltech_shrwt <- get_data(all_data, "emissions/A31.globaltech_shrwt") %>%
gather_years(value_col = "share.weight")
A31.globaltech_eff <- get_data(all_data, "emissions/A31.globaltech_eff") %>%
gather_years(value_col = "efficiency")
A31.globaltech_cost <- get_data(all_data, "emissions/A31.globaltech_cost") %>%
gather_years(value_col = "input.cost")
A31.globaltech_coef <- get_data(all_data, "emissions/A31.globaltech_coef") %>%
gather_years(value_col = "coefficient")
A32.globaltech_eff <- get_data(all_data, "energy/A32.globaltech_eff") %>%
gather_years
L1322.in_EJ_R_indfeed_F_Yh <- get_data(all_data, "L1322.in_EJ_R_indfeed_F_Yh")
L1322.in_EJ_R_indenergy_F_Yh <- get_data(all_data, "L1322.in_EJ_R_indenergy_F_Yh")
# ===================================================
# L231.FinalDemand_urb: Final demand information for urban processes sector
L231.FinalDemand_urb <- tibble(region = A_regions$region,
energy.final.demand = "urban processes",
perCapitaBased = 1,
income.elasticity = 0,
base.service = 0.004,
aeei = 0 # Autonomous Energy Efficiency Improvement
) %>%
repeat_add_columns(tibble(year = MODEL_BASE_YEARS))
# L231.Supplysector_ind: Supply sector information for urban & industrial processes sectors
L231.Supplysector_urb_ind <- A31.sector %>%
write_to_all_regions(c(LEVEL2_DATA_NAMES[["Supplysector"]], LOGIT_TYPE_COLNAME), GCAM_region_names = GCAM_region_names )
# 2b. Subsector information
# L231.SubsectorLogit_urb_ind: Subsector logit exponents of urban & industrial processes sectors
L231.SubsectorLogit_urb_ind <- A31.subsector_logit %>%
write_to_all_regions(c(LEVEL2_DATA_NAMES[["SubsectorLogit"]], LOGIT_TYPE_COLNAME), GCAM_region_names = GCAM_region_names)
# L231.SubsectorShrwt_urb_ind and L231.SubsectorShrwtFllt_urb_ind: Subsector shareweights of urban & industrial processes sectors
if(any(!is.na(A31.subsector_shrwt$year))) {
L231.SubsectorShrwt_urb_ind <- A31.subsector_shrwt %>%
filter(!is.na(year)) %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["SubsectorShrwt"]], GCAM_region_names = GCAM_region_names)
}
if(any(!is.na(A31.subsector_shrwt$year.fillout))) {
L231.SubsectorShrwtFllt_urb_ind <- A31.subsector_shrwt %>%
filter(!is.na(year.fillout)) %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["SubsectorShrwtFllt"]], GCAM_region_names = GCAM_region_names)
}
# L231.SubsectorInterp_urb_ind and L231.SubsectorInterpTo_urb_ind: Subsector shareweight interpolation of urban & industrial processes sector
if(any(is.na(A31.subsector_interp$to.value))) {
L231.SubsectorInterp_urb_ind <- A31.subsector_interp %>%
filter(is.na(to.value)) %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["SubsectorInterp"]], GCAM_region_names = GCAM_region_names)
}
if(any(!is.na(A31.subsector_interp$to.value))) {
L231.SubsectorInterpTo_urb_ind <- A31.subsector_interp %>%
filter(!is.na(to.value)) %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["SubsectorInterpTo"]], GCAM_region_names = GCAM_region_names)
}
# Technology information
# L231.StubTech_urb_ind: Identification of stub technologies of urban & industrial processes sectors
# Note: assuming that technology list in the shareweight table includes the full set (any others would default to a 0 shareweight)
L231.StubTech_urb_ind <- A31.globaltech_shrwt %>%
select(supplysector, subsector, technology) %>%
distinct %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["Tech"]] , GCAM_region_names = GCAM_region_names) %>%
rename(stub.technology = technology)
# L231.GlobalTechShrwt_urb_ind: Shareweights of global urban & industrial processes sector technologies
L231.GlobalTechShrwt_urb_ind <- A31.globaltech_shrwt %>%
select(supplysector, subsector, technology) %>%
distinct %>%
# Interpolate to all years
repeat_add_columns(tibble(year = c(HISTORICAL_YEARS, MODEL_FUTURE_YEARS))) %>%
left_join(A31.globaltech_shrwt, by = c("supplysector", "subsector", "technology", "year")) %>%
mutate(share.weight = approx_fun(year, value = share.weight, rule = 1)) %>%
filter(year %in% MODEL_YEARS) %>%
select(sector.name = supplysector, subsector.name = subsector, technology, year, share.weight)
# L231.GlobalTechEff_urb_ind: Energy inputs and coefficients of global urban & industrial processes technologies
L231.GlobalTechEff_urb_ind <- A31.globaltech_eff %>%
select(-year, -efficiency) %>%
distinct %>%
# Interpolate to all years
repeat_add_columns(tibble(year = c(HISTORICAL_YEARS, MODEL_FUTURE_YEARS))) %>%
left_join(A31.globaltech_eff, by = c("supplysector", "subsector", "technology", "year", "minicam.energy.input")) %>%
mutate(efficiency = approx_fun(year, value = efficiency, rule = 1)) %>%
filter(year %in% MODEL_YEARS) %>%
select(sector.name = supplysector, subsector.name = subsector, technology, year, minicam.energy.input, efficiency)
# Coefficients on global industry sector technologies (not energy-use or feedstocks)
# L231.GlobalTechCoef_urb_ind: Energy inputs and coefficients of global urban & industrial processes technologies
L231.GlobalTechCoef_urb_ind <- A31.globaltech_coef %>%
select(-year, -coefficient) %>%
distinct %>%
# Interpolate to all years
repeat_add_columns(tibble(year = c(HISTORICAL_YEARS, MODEL_FUTURE_YEARS))) %>%
left_join(A31.globaltech_coef, by = c("supplysector", "subsector", "technology", "year", "minicam.energy.input")) %>%
mutate(coefficient = approx_fun(year, value = coefficient, rule = 1)) %>%
filter(year %in% MODEL_YEARS) %>%
select(sector.name = supplysector, subsector.name = subsector, technology, year, minicam.energy.input, coefficient)
# Costs of global technologies
# L231.GlobalTechCost_urb_ind: Capital costs of global urban & industrial processes technologies
L231.GlobalTechCost_urb_ind <- A31.globaltech_cost %>%
select(-year, -input.cost) %>%
distinct %>%
# Interpolate to all years
repeat_add_columns(tibble(year = c(HISTORICAL_YEARS, MODEL_FUTURE_YEARS))) %>%
left_join(A31.globaltech_cost, by = c("supplysector", "subsector", "technology", "year", "minicam.non.energy.input")) %>%
mutate(input.cost = approx_fun(year, value = input.cost, rule = 1)) %>%
filter(year %in% MODEL_YEARS) %>%
select(sector.name = supplysector, subsector.name = subsector, technology, year, minicam.non.energy.input, input.cost)
# Calibration and region-specific data
# L231.StubTechCalInput_calvalue: calibrated input of urban & industrial processes technologies
L231.RegionalTechCalValue_urb_ind <- L231.GlobalTechCost_urb_ind %>%
filter(year %in% MODEL_BASE_YEARS) %>%
select(-minicam.non.energy.input, -input.cost) %>%
# Assign values to all regions
repeat_add_columns(tibble(region = A_regions$region)) %>%
mutate(minicam.energy.input = "misc emissions sources",
calibrated.value = 0.001) %>%
select(region, sector.name, subsector.name, technology, year, minicam.energy.input, calibrated.value)
# Resource Information
# Interpolate to specified historical years, as necessary
L231.rsrc_info <- A31.rsrc_info %>%
select(-year, -value) %>%
distinct() %>%
# Interpolate to all years
repeat_add_columns(tibble(year = HISTORICAL_YEARS)) %>%
left_join(A31.rsrc_info, by = c("resource", "resource_type",
"market", "output-unit", "price-unit", "capacity.factor", "year")) %>%
mutate(value = approx_fun(year, value, rule = 1)) %>%
filter(year %in% MODEL_YEARS) %>%
repeat_add_columns(GCAM_region_names) %>%
mutate(market = replace(market, market == "regional", region[market == "regional"]))
# L231.UnlimitRsrc: output unit, price unit, and market for unlimited resources
L231.UnlimitRsrc <- L231.rsrc_info %>%
filter(resource_type == "unlimited-resource") %>%
select(-year, - value) %>%
distinct %>%
select(region, unlimited.resource = resource, output.unit = `output-unit`, price.unit = `price-unit`, market, capacity.factor)
# L231.UnlimitRsrcPrice: prices for unlimited resources
L231.UnlimitRsrcPrice <- L231.rsrc_info %>%
filter(resource_type == "unlimited-resource") %>%
select(region, unlimited.resource = resource, year, price = value)
# L231.IndCoef: coefficient on industrial processes as an input to the industry sector
# Coefficient = 0.008 / change in industry output from 1990 (0.008 is the sum of calvalue)
# First, interpolate A32.globaltech_eff efficiency values to all years
Ind.globaltech_eff <- A32.globaltech_eff %>%
select(-year, -value) %>%
repeat_add_columns(tibble(year = c(HISTORICAL_YEARS, MODEL_FUTURE_YEARS))) %>%
left_join(A32.globaltech_eff, by = c("supplysector", "subsector", "technology", "minicam.energy.input",
"secondary.output", "year")) %>%
group_by(supplysector, subsector, technology, minicam.energy.input,
secondary.output) %>%
mutate(value = round(approx_fun(year, value, rule = 1), 3)) %>%
ungroup %>%
filter(year %in% MODEL_YEARS) %>%
select(sector = supplysector, fuel = subsector, year, efficiency = value) %>%
distinct()
# Now combine input energy info and join with efficiency values
L231.IndCoef <- bind_rows(L1322.in_EJ_R_indenergy_F_Yh %>%
mutate(sector = "industrial energy use"),
L1322.in_EJ_R_indfeed_F_Yh %>%
mutate(sector = "industrial feedstocks")) %>%
left_join_keep_first_only(Ind.globaltech_eff, by = c("sector", "fuel", "year")) %>%
# Calculate service as energy * efficiency
mutate(service = value * efficiency) %>%
na.omit() %>%
group_by(GCAM_region_ID, year) %>%
summarise(ind_output = sum(service)) %>%
ungroup() %>%
mutate(ind_proc_input = 0.008,
coefficient = ind_proc_input / ind_output,
supplysector = "industry",
subsector = "industry",
technology = "industry",
minicam.energy.input = "industrial processes") %>%
left_join_error_no_match(GCAM_region_names, by = "GCAM_region_ID")
# Interpolate coefficients to model years
L231.IndCoef <- L231.IndCoef %>%
select(-year, -coefficient, -ind_output, -ind_proc_input) %>%
distinct %>%
repeat_add_columns(tibble(year = MODEL_YEARS)) %>%
left_join(L231.IndCoef, by = c("GCAM_region_ID", "region", "supplysector", "subsector", "technology", "minicam.energy.input", "year")) %>%
group_by(region, technology) %>%
mutate(coefficient = approx_fun(year, coefficient, rule = 2)) %>%
ungroup() %>%
select(region, supplysector, subsector, technology, year, minicam.energy.input, coefficient)
# ===================================================
# Produce outputs
L231.UnlimitRsrc %>%
add_title("Processing Resource Capacity Factors") %>%
add_units("Unitless") %>%
add_comments("Data from A31.rsrc_info") %>%
add_legacy_name("L231.UnlimitRsrc") %>%
add_precursors("emissions/A31.rsrc_info") ->
L231.UnlimitRsrc
L231.UnlimitRsrcPrice %>%
add_title("Processing Resource Prices") %>%
add_units("units") %>%
add_comments("Interpolated data from A31.rsrc_info") %>%
add_legacy_name("L231.UnlimitRsrcPrice") %>%
add_precursors("emissions/A31.rsrc_info") ->
L231.UnlimitRsrcPrice
L231.FinalDemand_urb %>%
add_title("Urban Processes Final Energy Demand") %>%
add_units("units") %>%
add_comments("Constants for base service, income elasticity, and aeei") %>%
add_legacy_name("L231.FinalDemand_urb") %>%
add_precursors("emissions/A_regions") ->
L231.FinalDemand_urb
L231.Supplysector_urb_ind %>%
add_title("Urban and Industrial Processes Supplysector Logit Info") %>%
add_units("Unitless") %>%
add_comments("A31.sector written to all regions") %>%
add_legacy_name("L231.Supplysector_urb_ind") %>%
add_precursors("emissions/A31.sector", "common/GCAM_region_names") ->
L231.Supplysector_urb_ind
L231.SubsectorLogit_urb_ind %>%
add_title("Urban and Industrial Processes Subsector Logit Info") %>%
add_units("Unitless") %>%
add_comments("A31.subsector_logit written to all regions") %>%
add_legacy_name("L231.SubsectorLogit_urb_ind") %>%
add_precursors("emissions/A31.subsector_logit", "common/GCAM_region_names") ->
L231.SubsectorLogit_urb_ind
if(exists("L231.SubsectorShrwt_urb_ind")) {
L231.SubsectorShrwt_urb_ind %>%
add_title("Urban and Industrial Processes Subsector Shareweights") %>%
add_units("Unitless") %>%
add_comments("A31.subsector_shrwt written to all regions") %>%
# This was a mistake in the old data system - the wrong name was assigned, but because it didn't exist, no error was thrown
add_legacy_name("L231.SubsectorShrwt_ind") %>%
add_precursors("emissions/A31.subsector_shrwt", "common/GCAM_region_names") ->
L231.SubsectorShrwt_urb_ind
} else {
missing_data() %>%
add_legacy_name("L231.SubsectorShrwt_ind") ->
L231.SubsectorShrwt_urb_ind
}
if(exists("L231.SubsectorShrwtFllt_urb_ind")) {
L231.SubsectorShrwtFllt_urb_ind %>%
add_title("Urban and Industrial Processes Subsector Shareweights") %>%
add_units("Unitless") %>%
add_comments("A31.subsector_shrwt written to all regions") %>%
add_legacy_name("L231.SubsectorShrwtFllt_urb_ind") %>%
add_precursors("emissions/A31.subsector_shrwt", "common/GCAM_region_names") ->
L231.SubsectorShrwtFllt_urb_ind
} else {
missing_data() %>%
add_legacy_name("L231.SubsectorShrwtFllt_urb_ind")->
L231.SubsectorShrwtFllt_urb_ind
}
if(exists("L231.SubsectorInterp_urb_ind")) {
L231.SubsectorInterp_urb_ind %>%
add_title("Urban and Industrial Processes Subsector Shareweight Interpolation") %>%
add_units("NA") %>%
add_comments("A31.subsector_interp written to all regions") %>%
add_legacy_name("L231.SubsectorInterp_urb_ind") %>%
add_precursors("emissions/A31.subsector_interp", "common/GCAM_region_names") ->
L231.SubsectorInterp_urb_ind
} else {
missing_data() %>%
add_legacy_name("L231.SubsectorInterp_urb_ind") ->
L231.SubsectorInterp_urb_ind
}
if(exists("L231.SubsectorInterpTo_urb_ind")) {
L231.SubsectorInterpTo_urb_ind %>%
add_title("Urban and Industrial Processes Subsector Shareweight Interpolation") %>%
add_units("NA") %>%
add_comments("A31.subsector_interp written to all regions") %>%
add_legacy_name("L231.SubsectorInterpTo_urb_ind") %>%
add_precursors("emissions/A31.subsector_interp", "common/GCAM_region_names") ->
L231.SubsectorInterpTo_urb_ind
} else {
missing_data() %>%
add_legacy_name("L231.SubsectorInterpTo_urb_ind") ->
L231.SubsectorInterpTo_urb_ind
}
L231.StubTech_urb_ind %>%
add_title("Urban and Industrial Processes Stub Technology Map") %>%
add_units("NA") %>%
add_comments("A31.globaltech_shrwt filtered and written to all regions") %>%
add_legacy_name("L231.StubTech_urb_ind") %>%
add_precursors("emissions/A31.globaltech_shrwt", "common/GCAM_region_names") ->
L231.StubTech_urb_ind
L231.GlobalTechShrwt_urb_ind %>%
add_title("Urban and Industrial Processes Global Technology Shareweights") %>%
add_units("Unitless") %>%
add_comments("A31.globaltech_shrwt interpolated to model years") %>%
add_legacy_name("L231.GlobalTechShrwt_urb_ind") %>%
add_precursors("emissions/A31.globaltech_shrwt") ->
L231.GlobalTechShrwt_urb_ind
L231.GlobalTechEff_urb_ind %>%
add_title("Urban and Industrial Processes Global Technology Efficiency") %>%
add_units("Unitless") %>%
add_comments("A31.globaltech_eff interpolated to model years") %>%
add_legacy_name("L231.GlobalTechEff_urb_ind") %>%
add_precursors("emissions/A31.globaltech_eff")->
L231.GlobalTechEff_urb_ind
L231.GlobalTechCoef_urb_ind %>%
add_title("Urban and Industrial Processes Global Technology Coefficients") %>%
add_units("units") %>%
add_comments("A31.globaltech_coef interpolated to model years") %>%
add_legacy_name("L231.GlobalTechCoef_urb_ind") %>%
add_precursors("emissions/A31.globaltech_coef") ->
L231.GlobalTechCoef_urb_ind
L231.GlobalTechCost_urb_ind %>%
add_title("Urban and Industrial Processes Global Technology Costs") %>%
add_units("units") %>%
add_comments("A31.globaltech_cost interpolated to model years") %>%
add_legacy_name("L231.GlobalTechCost_urb_ind") %>%
add_precursors("emissions/A31.globaltech_cost") ->
L231.GlobalTechCost_urb_ind
L231.RegionalTechCalValue_urb_ind %>%
add_title("Urban and Industrial Processes Global Technology Calibrated Values") %>%
add_units("units") %>%
add_comments("A31.globaltech_cost interpolated to base years and written to all regions") %>%
add_legacy_name("L231.RegionalTechCalValue_urb_ind") %>%
add_precursors("emissions/A31.globaltech_cost", "emissions/A_regions") ->
L231.RegionalTechCalValue_urb_ind
L231.IndCoef %>%
add_title("Industrial Processes Input-Output Coefficients") %>%
add_units("units") %>%
add_comments("Coefficients equal to constant input value divided by calculated output value") %>%
add_legacy_name("L231.IndCoef") %>%
add_precursors("energy/A32.globaltech_eff",
"L1322.in_EJ_R_indfeed_F_Yh",
"L1322.in_EJ_R_indenergy_F_Yh",
"common/GCAM_region_names") ->
L231.IndCoef
return_data(L231.UnlimitRsrc, L231.UnlimitRsrcPrice, L231.FinalDemand_urb, L231.Supplysector_urb_ind, L231.SubsectorLogit_urb_ind,
L231.SubsectorShrwt_urb_ind, L231.SubsectorShrwtFllt_urb_ind, L231.SubsectorInterp_urb_ind, L231.SubsectorInterpTo_urb_ind,
L231.StubTech_urb_ind, L231.GlobalTechShrwt_urb_ind, L231.GlobalTechEff_urb_ind, L231.GlobalTechCoef_urb_ind,
L231.GlobalTechCost_urb_ind, L231.RegionalTechCalValue_urb_ind, L231.IndCoef)
} else {
stop("Unknown command")
}
}
rohmin9122/gcam-korea-release documentation built on Nov. 26, 2020, 8:11 a.m.
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Defines functions module_emissions_L231.proc_sector
Documented in module_emissions_L231.proc_sector
#' module_emissions_L231.proc_sector
#'
#' Writes urban & industrial processing sector outputs.
#'
#' @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{L231.UnlimitRsrc}, \code{L231.UnlimitRsrcPrice}, \code{L231.FinalDemand_urb}, \code{L231.SectorLogitTables[[ curr_table ]]$data}, \code{L231.Supplysector_urb_ind}, \code{L231.SubsectorLogitTables[[ curr_table ]]$data}, \code{L231.SubsectorLogit_urb_ind}, \code{L231.SubsectorShrwt_urb_ind}, \code{L231.SubsectorShrwtFllt_urb_ind}, \code{L231.SubsectorInterp_urb_ind}, \code{L231.SubsectorInterpTo_urb_ind}, \code{L231.StubTech_urb_ind}, \code{L231.GlobalTechShrwt_urb_ind}, \code{L231.GlobalTechEff_urb_ind}, \code{L231.GlobalTechCoef_urb_ind}, \code{L231.GlobalTechCost_urb_ind}, \code{L231.RegionalTechCalValue_urb_ind}, \code{L231.IndCoef}. The corresponding file in the
#' original data system was \code{L231.proc_sector.R} (emissions level2).
#' @details For urban processes and industrial processes, produces global technology coefficients,
#' costs, efficiencies, and shareweights by interpolating assumption file data. For urb & ind. processing subsectors
#' and supplysectors, produces logit, shareweights, and interpolation files by writing assumption file data to all regions.
#' Writes out coefficients and prices for misc emissions sources from assumption file data.
#' Outputs urban processing demand using constants. StubTech mapping file created from assumption mappings.
#' Regional technology calibration values created with constant. Industry input-output coefficient file created.
#' @importFrom assertthat assert_that
#' @importFrom dplyr filter mutate select
#' @importFrom tidyr gather spread
#' @author RLH July 2017
module_emissions_L231.proc_sector <- function(command, ...) {
if(command == driver.DECLARE_INPUTS) {
return(c(FILE = "common/GCAM_region_names",
FILE = "emissions/A_regions",
FILE = "emissions/A31.rsrc_info", # Units and source
FILE = "emissions/A31.sector", # source
FILE = "emissions/A31.subsector_logit", # source
FILE = "emissions/A31.subsector_shrwt", # source
FILE = "emissions/A31.subsector_interp", # source
FILE = "emissions/A31.globaltech_shrwt", # source
FILE = "emissions/A31.globaltech_eff", # Units and source
FILE = "emissions/A31.globaltech_cost", # Units and source
FILE = "emissions/A31.globaltech_coef", # Units and source
FILE = "energy/A32.globaltech_eff", # Units and source
"L1322.in_EJ_R_indfeed_F_Yh",
"L1322.in_EJ_R_indenergy_F_Yh"))
} else if(command == driver.DECLARE_OUTPUTS) {
return(c("L231.UnlimitRsrc",
"L231.UnlimitRsrcPrice",
"L231.FinalDemand_urb",
"L231.Supplysector_urb_ind",
"L231.SubsectorLogit_urb_ind",
"L231.SubsectorShrwt_urb_ind",
"L231.SubsectorShrwtFllt_urb_ind",
"L231.SubsectorInterp_urb_ind",
"L231.SubsectorInterpTo_urb_ind",
"L231.StubTech_urb_ind",
"L231.GlobalTechShrwt_urb_ind",
"L231.GlobalTechEff_urb_ind",
"L231.GlobalTechCoef_urb_ind",
"L231.GlobalTechCost_urb_ind",
"L231.RegionalTechCalValue_urb_ind",
"L231.IndCoef"))
} else if(command == driver.MAKE) {
# Silence package checks
year <- value <- share.weight <- efficiency <- input.cost <- coefficient <-
year.fillout <- to.value <- supplysector <- subsector <- technology <- minicam.energy.input <-
minicam.non.energy.input <- region <- sector.name <- subsector.name <- calibrated.value <-
market <- resource_type <- resource <- `output-unit` <- `price-unit` <- capacity.factor <-
secondary.output <- GCAM_region_ID <- service <- ind_proc_input <- ind_output <- NULL
all_data <- list(...)[[1]]
# Load required inputs
GCAM_region_names <- get_data(all_data, "common/GCAM_region_names")
A_regions <- get_data(all_data, "emissions/A_regions")
A31.rsrc_info <- get_data(all_data, "emissions/A31.rsrc_info") %>%
gather_years
A31.sector <- get_data(all_data, "emissions/A31.sector")
A31.subsector_logit <- get_data(all_data, "emissions/A31.subsector_logit")
A31.subsector_shrwt <- get_data(all_data, "emissions/A31.subsector_shrwt")
A31.subsector_interp <- get_data(all_data, "emissions/A31.subsector_interp")
A31.globaltech_shrwt <- get_data(all_data, "emissions/A31.globaltech_shrwt") %>%
gather_years(value_col = "share.weight")
A31.globaltech_eff <- get_data(all_data, "emissions/A31.globaltech_eff") %>%
gather_years(value_col = "efficiency")
A31.globaltech_cost <- get_data(all_data, "emissions/A31.globaltech_cost") %>%
gather_years(value_col = "input.cost")
A31.globaltech_coef <- get_data(all_data, "emissions/A31.globaltech_coef") %>%
gather_years(value_col = "coefficient")
A32.globaltech_eff <- get_data(all_data, "energy/A32.globaltech_eff") %>%
gather_years
L1322.in_EJ_R_indfeed_F_Yh <- get_data(all_data, "L1322.in_EJ_R_indfeed_F_Yh")
L1322.in_EJ_R_indenergy_F_Yh <- get_data(all_data, "L1322.in_EJ_R_indenergy_F_Yh")
# ===================================================
# L231.FinalDemand_urb: Final demand information for urban processes sector
L231.FinalDemand_urb <- tibble(region = A_regions$region,
energy.final.demand = "urban processes",
perCapitaBased = 1,
income.elasticity = 0,
base.service = 0.004,
aeei = 0 # Autonomous Energy Efficiency Improvement
) %>%
repeat_add_columns(tibble(year = MODEL_BASE_YEARS))
# L231.Supplysector_ind: Supply sector information for urban & industrial processes sectors
L231.Supplysector_urb_ind <- A31.sector %>%
write_to_all_regions(c(LEVEL2_DATA_NAMES[["Supplysector"]], LOGIT_TYPE_COLNAME), GCAM_region_names = GCAM_region_names )
# 2b. Subsector information
# L231.SubsectorLogit_urb_ind: Subsector logit exponents of urban & industrial processes sectors
L231.SubsectorLogit_urb_ind <- A31.subsector_logit %>%
write_to_all_regions(c(LEVEL2_DATA_NAMES[["SubsectorLogit"]], LOGIT_TYPE_COLNAME), GCAM_region_names = GCAM_region_names)
# L231.SubsectorShrwt_urb_ind and L231.SubsectorShrwtFllt_urb_ind: Subsector shareweights of urban & industrial processes sectors
if(any(!is.na(A31.subsector_shrwt$year))) {
L231.SubsectorShrwt_urb_ind <- A31.subsector_shrwt %>%
filter(!is.na(year)) %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["SubsectorShrwt"]], GCAM_region_names = GCAM_region_names)
}
if(any(!is.na(A31.subsector_shrwt$year.fillout))) {
L231.SubsectorShrwtFllt_urb_ind <- A31.subsector_shrwt %>%
filter(!is.na(year.fillout)) %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["SubsectorShrwtFllt"]], GCAM_region_names = GCAM_region_names)
}
# L231.SubsectorInterp_urb_ind and L231.SubsectorInterpTo_urb_ind: Subsector shareweight interpolation of urban & industrial processes sector
if(any(is.na(A31.subsector_interp$to.value))) {
L231.SubsectorInterp_urb_ind <- A31.subsector_interp %>%
filter(is.na(to.value)) %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["SubsectorInterp"]], GCAM_region_names = GCAM_region_names)
}
if(any(!is.na(A31.subsector_interp$to.value))) {
L231.SubsectorInterpTo_urb_ind <- A31.subsector_interp %>%
filter(!is.na(to.value)) %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["SubsectorInterpTo"]], GCAM_region_names = GCAM_region_names)
}
# Technology information
# L231.StubTech_urb_ind: Identification of stub technologies of urban & industrial processes sectors
# Note: assuming that technology list in the shareweight table includes the full set (any others would default to a 0 shareweight)
L231.StubTech_urb_ind <- A31.globaltech_shrwt %>%
select(supplysector, subsector, technology) %>%
distinct %>%
write_to_all_regions(LEVEL2_DATA_NAMES[["Tech"]] , GCAM_region_names = GCAM_region_names) %>%
rename(stub.technology = technology)
# L231.GlobalTechShrwt_urb_ind: Shareweights of global urban & industrial processes sector technologies
L231.GlobalTechShrwt_urb_ind <- A31.globaltech_shrwt %>%
select(supplysector, subsector, technology) %>%
distinct %>%
# Interpolate to all years
repeat_add_columns(tibble(year = c(HISTORICAL_YEARS, MODEL_FUTURE_YEARS))) %>%
left_join(A31.globaltech_shrwt, by = c("supplysector", "subsector", "technology", "year")) %>%
mutate(share.weight = approx_fun(year, value = share.weight, rule = 1)) %>%
filter(year %in% MODEL_YEARS) %>%
select(sector.name = supplysector, subsector.name = subsector, technology, year, share.weight)
# L231.GlobalTechEff_urb_ind: Energy inputs and coefficients of global urban & industrial processes technologies
L231.GlobalTechEff_urb_ind <- A31.globaltech_eff %>%
select(-year, -efficiency) %>%
distinct %>%
# Interpolate to all years
repeat_add_columns(tibble(year = c(HISTORICAL_YEARS, MODEL_FUTURE_YEARS))) %>%
left_join(A31.globaltech_eff, by = c("supplysector", "subsector", "technology", "year", "minicam.energy.input")) %>%
mutate(efficiency = approx_fun(year, value = efficiency, rule = 1)) %>%
filter(year %in% MODEL_YEARS) %>%
select(sector.name = supplysector, subsector.name = subsector, technology, year, minicam.energy.input, efficiency)
# Coefficients on global industry sector technologies (not energy-use or feedstocks)
# L231.GlobalTechCoef_urb_ind: Energy inputs and coefficients of global urban & industrial processes technologies
L231.GlobalTechCoef_urb_ind <- A31.globaltech_coef %>%
select(-year, -coefficient) %>%
distinct %>%
# Interpolate to all years
repeat_add_columns(tibble(year = c(HISTORICAL_YEARS, MODEL_FUTURE_YEARS))) %>%
left_join(A31.globaltech_coef, by = c("supplysector", "subsector", "technology", "year", "minicam.energy.input")) %>%
mutate(coefficient = approx_fun(year, value = coefficient, rule = 1)) %>%
filter(year %in% MODEL_YEARS) %>%
select(sector.name = supplysector, subsector.name = subsector, technology, year, minicam.energy.input, coefficient)
# Costs of global technologies
# L231.GlobalTechCost_urb_ind: Capital costs of global urban & industrial processes technologies
L231.GlobalTechCost_urb_ind <- A31.globaltech_cost %>%
select(-year, -input.cost) %>%
distinct %>%
# Interpolate to all years
repeat_add_columns(tibble(year = c(HISTORICAL_YEARS, MODEL_FUTURE_YEARS))) %>%
left_join(A31.globaltech_cost, by = c("supplysector", "subsector", "technology", "year", "minicam.non.energy.input")) %>%
mutate(input.cost = approx_fun(year, value = input.cost, rule = 1)) %>%
filter(year %in% MODEL_YEARS) %>%
select(sector.name = supplysector, subsector.name = subsector, technology, year, minicam.non.energy.input, input.cost)
# Calibration and region-specific data
# L231.StubTechCalInput_calvalue: calibrated input of urban & industrial processes technologies
L231.RegionalTechCalValue_urb_ind <- L231.GlobalTechCost_urb_ind %>%
filter(year %in% MODEL_BASE_YEARS) %>%
select(-minicam.non.energy.input, -input.cost) %>%
# Assign values to all regions
repeat_add_columns(tibble(region = A_regions$region)) %>%
mutate(minicam.energy.input = "misc emissions sources",
calibrated.value = 0.001) %>%
select(region, sector.name, subsector.name, technology, year, minicam.energy.input, calibrated.value)
# Resource Information
# Interpolate to specified historical years, as necessary
L231.rsrc_info <- A31.rsrc_info %>%
select(-year, -value) %>%
distinct() %>%
# Interpolate to all years
repeat_add_columns(tibble(year = HISTORICAL_YEARS)) %>%
left_join(A31.rsrc_info, by = c("resource", "resource_type",
"market", "output-unit", "price-unit", "capacity.factor", "year")) %>%
mutate(value = approx_fun(year, value, rule = 1)) %>%
filter(year %in% MODEL_YEARS) %>%
repeat_add_columns(GCAM_region_names) %>%
mutate(market = replace(market, market == "regional", region[market == "regional"]))
# L231.UnlimitRsrc: output unit, price unit, and market for unlimited resources
L231.UnlimitRsrc <- L231.rsrc_info %>%
filter(resource_type == "unlimited-resource") %>%
select(-year, - value) %>%
distinct %>%
select(region, unlimited.resource = resource, output.unit = `output-unit`, price.unit = `price-unit`, market, capacity.factor)
# L231.UnlimitRsrcPrice: prices for unlimited resources
L231.UnlimitRsrcPrice <- L231.rsrc_info %>%
filter(resource_type == "unlimited-resource") %>%
select(region, unlimited.resource = resource, year, price = value)
# L231.IndCoef: coefficient on industrial processes as an input to the industry sector
# Coefficient = 0.008 / change in industry output from 1990 (0.008 is the sum of calvalue)
# First, interpolate A32.globaltech_eff efficiency values to all years
Ind.globaltech_eff <- A32.globaltech_eff %>%
select(-year, -value) %>%
repeat_add_columns(tibble(year = c(HISTORICAL_YEARS, MODEL_FUTURE_YEARS))) %>%
left_join(A32.globaltech_eff, by = c("supplysector", "subsector", "technology", "minicam.energy.input",
"secondary.output", "year")) %>%
group_by(supplysector, subsector, technology, minicam.energy.input,
secondary.output) %>%
mutate(value = round(approx_fun(year, value, rule = 1), 3)) %>%
ungroup %>%
filter(year %in% MODEL_YEARS) %>%
select(sector = supplysector, fuel = subsector, year, efficiency = value) %>%
distinct()
# Now combine input energy info and join with efficiency values
L231.IndCoef <- bind_rows(L1322.in_EJ_R_indenergy_F_Yh %>%
mutate(sector = "industrial energy use"),
L1322.in_EJ_R_indfeed_F_Yh %>%
mutate(sector = "industrial feedstocks")) %>%
left_join_keep_first_only(Ind.globaltech_eff, by = c("sector", "fuel", "year")) %>%
# Calculate service as energy * efficiency
mutate(service = value * efficiency) %>%
na.omit() %>%
group_by(GCAM_region_ID, year) %>%
summarise(ind_output = sum(service)) %>%
ungroup() %>%
mutate(ind_proc_input = 0.008,
coefficient = ind_proc_input / ind_output,
supplysector = "industry",
subsector = "industry",
technology = "industry",
minicam.energy.input = "industrial processes") %>%
left_join_error_no_match(GCAM_region_names, by = "GCAM_region_ID")
# Interpolate coefficients to model years
L231.IndCoef <- L231.IndCoef %>%
select(-year, -coefficient, -ind_output, -ind_proc_input) %>%
distinct %>%
repeat_add_columns(tibble(year = MODEL_YEARS)) %>%
left_join(L231.IndCoef, by = c("GCAM_region_ID", "region", "supplysector", "subsector", "technology", "minicam.energy.input", "year")) %>%
group_by(region, technology) %>%
mutate(coefficient = approx_fun(year, coefficient, rule = 2)) %>%
ungroup() %>%
select(region, supplysector, subsector, technology, year, minicam.energy.input, coefficient)
# ===================================================
# Produce outputs
L231.UnlimitRsrc %>%
add_title("Processing Resource Capacity Factors") %>%
add_units("Unitless") %>%
add_comments("Data from A31.rsrc_info") %>%
add_legacy_name("L231.UnlimitRsrc") %>%
add_precursors("emissions/A31.rsrc_info") ->
L231.UnlimitRsrc
L231.UnlimitRsrcPrice %>%
add_title("Processing Resource Prices") %>%
add_units("units") %>%
add_comments("Interpolated data from A31.rsrc_info") %>%
add_legacy_name("L231.UnlimitRsrcPrice") %>%
add_precursors("emissions/A31.rsrc_info") ->
L231.UnlimitRsrcPrice
L231.FinalDemand_urb %>%
add_title("Urban Processes Final Energy Demand") %>%
add_units("units") %>%
add_comments("Constants for base service, income elasticity, and aeei") %>%
add_legacy_name("L231.FinalDemand_urb") %>%
add_precursors("emissions/A_regions") ->
L231.FinalDemand_urb
L231.Supplysector_urb_ind %>%
add_title("Urban and Industrial Processes Supplysector Logit Info") %>%
add_units("Unitless") %>%
add_comments("A31.sector written to all regions") %>%
add_legacy_name("L231.Supplysector_urb_ind") %>%
add_precursors("emissions/A31.sector", "common/GCAM_region_names") ->
L231.Supplysector_urb_ind
L231.SubsectorLogit_urb_ind %>%
add_title("Urban and Industrial Processes Subsector Logit Info") %>%
add_units("Unitless") %>%
add_comments("A31.subsector_logit written to all regions") %>%
add_legacy_name("L231.SubsectorLogit_urb_ind") %>%
add_precursors("emissions/A31.subsector_logit", "common/GCAM_region_names") ->
L231.SubsectorLogit_urb_ind
if(exists("L231.SubsectorShrwt_urb_ind")) {
L231.SubsectorShrwt_urb_ind %>%
add_title("Urban and Industrial Processes Subsector Shareweights") %>%
add_units("Unitless") %>%
add_comments("A31.subsector_shrwt written to all regions") %>%
# This was a mistake in the old data system - the wrong name was assigned, but because it didn't exist, no error was thrown
add_legacy_name("L231.SubsectorShrwt_ind") %>%
add_precursors("emissions/A31.subsector_shrwt", "common/GCAM_region_names") ->
L231.SubsectorShrwt_urb_ind
} else {
missing_data() %>%
add_legacy_name("L231.SubsectorShrwt_ind") ->
L231.SubsectorShrwt_urb_ind
}
if(exists("L231.SubsectorShrwtFllt_urb_ind")) {
L231.SubsectorShrwtFllt_urb_ind %>%
add_title("Urban and Industrial Processes Subsector Shareweights") %>%
add_units("Unitless") %>%
add_comments("A31.subsector_shrwt written to all regions") %>%
add_legacy_name("L231.SubsectorShrwtFllt_urb_ind") %>%
add_precursors("emissions/A31.subsector_shrwt", "common/GCAM_region_names") ->
L231.SubsectorShrwtFllt_urb_ind
} else {
missing_data() %>%
add_legacy_name("L231.SubsectorShrwtFllt_urb_ind")->
L231.SubsectorShrwtFllt_urb_ind
}
if(exists("L231.SubsectorInterp_urb_ind")) {
L231.SubsectorInterp_urb_ind %>%
add_title("Urban and Industrial Processes Subsector Shareweight Interpolation") %>%
add_units("NA") %>%
add_comments("A31.subsector_interp written to all regions") %>%
add_legacy_name("L231.SubsectorInterp_urb_ind") %>%
add_precursors("emissions/A31.subsector_interp", "common/GCAM_region_names") ->
L231.SubsectorInterp_urb_ind
} else {
missing_data() %>%
add_legacy_name("L231.SubsectorInterp_urb_ind") ->
L231.SubsectorInterp_urb_ind
}
if(exists("L231.SubsectorInterpTo_urb_ind")) {
L231.SubsectorInterpTo_urb_ind %>%
add_title("Urban and Industrial Processes Subsector Shareweight Interpolation") %>%
add_units("NA") %>%
add_comments("A31.subsector_interp written to all regions") %>%
add_legacy_name("L231.SubsectorInterpTo_urb_ind") %>%
add_precursors("emissions/A31.subsector_interp", "common/GCAM_region_names") ->
L231.SubsectorInterpTo_urb_ind
} else {
missing_data() %>%
add_legacy_name("L231.SubsectorInterpTo_urb_ind") ->
L231.SubsectorInterpTo_urb_ind
}
L231.StubTech_urb_ind %>%
add_title("Urban and Industrial Processes Stub Technology Map") %>%
add_units("NA") %>%
add_comments("A31.globaltech_shrwt filtered and written to all regions") %>%
add_legacy_name("L231.StubTech_urb_ind") %>%
add_precursors("emissions/A31.globaltech_shrwt", "common/GCAM_region_names") ->
L231.StubTech_urb_ind
L231.GlobalTechShrwt_urb_ind %>%
add_title("Urban and Industrial Processes Global Technology Shareweights") %>%
add_units("Unitless") %>%
add_comments("A31.globaltech_shrwt interpolated to model years") %>%
add_legacy_name("L231.GlobalTechShrwt_urb_ind") %>%
add_precursors("emissions/A31.globaltech_shrwt") ->
L231.GlobalTechShrwt_urb_ind
L231.GlobalTechEff_urb_ind %>%
add_title("Urban and Industrial Processes Global Technology Efficiency") %>%
add_units("Unitless") %>%
add_comments("A31.globaltech_eff interpolated to model years") %>%
add_legacy_name("L231.GlobalTechEff_urb_ind") %>%
add_precursors("emissions/A31.globaltech_eff")->
L231.GlobalTechEff_urb_ind
L231.GlobalTechCoef_urb_ind %>%
add_title("Urban and Industrial Processes Global Technology Coefficients") %>%
add_units("units") %>%
add_comments("A31.globaltech_coef interpolated to model years") %>%
add_legacy_name("L231.GlobalTechCoef_urb_ind") %>%
add_precursors("emissions/A31.globaltech_coef") ->
L231.GlobalTechCoef_urb_ind
L231.GlobalTechCost_urb_ind %>%
add_title("Urban and Industrial Processes Global Technology Costs") %>%
add_units("units") %>%
add_comments("A31.globaltech_cost interpolated to model years") %>%
add_legacy_name("L231.GlobalTechCost_urb_ind") %>%
add_precursors("emissions/A31.globaltech_cost") ->
L231.GlobalTechCost_urb_ind
L231.RegionalTechCalValue_urb_ind %>%
add_title("Urban and Industrial Processes Global Technology Calibrated Values") %>%
add_units("units") %>%
add_comments("A31.globaltech_cost interpolated to base years and written to all regions") %>%
add_legacy_name("L231.RegionalTechCalValue_urb_ind") %>%
add_precursors("emissions/A31.globaltech_cost", "emissions/A_regions") ->
L231.RegionalTechCalValue_urb_ind
L231.IndCoef %>%
add_title("Industrial Processes Input-Output Coefficients") %>%
add_units("units") %>%
add_comments("Coefficients equal to constant input value divided by calculated output value") %>%
add_legacy_name("L231.IndCoef") %>%
add_precursors("energy/A32.globaltech_eff",
"L1322.in_EJ_R_indfeed_F_Yh",
"L1322.in_EJ_R_indenergy_F_Yh",
"common/GCAM_region_names") ->
L231.IndCoef
return_data(L231.UnlimitRsrc, L231.UnlimitRsrcPrice, L231.FinalDemand_urb, L231.Supplysector_urb_ind, L231.SubsectorLogit_urb_ind,
L231.SubsectorShrwt_urb_ind, L231.SubsectorShrwtFllt_urb_ind, L231.SubsectorInterp_urb_ind, L231.SubsectorInterpTo_urb_ind,
L231.StubTech_urb_ind, L231.GlobalTechShrwt_urb_ind, L231.GlobalTechEff_urb_ind, L231.GlobalTechCoef_urb_ind,
L231.GlobalTechCost_urb_ind, L231.RegionalTechCalValue_urb_ind, L231.IndCoef)
} else {
stop("Unknown command")
}
}
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