R/zchunk_L253.emission_controls.R
In JGCRI/gcamdata: Build the GCAM Input Datasets
Defines functions
module_emissions_L253.emission_controls
Documented in
module_emissions_L253.emission_controls
# Copyright 2019 Battelle Memorial Institute; see the LICENSE file.
#' module_emissions_L253.emission_controls
#'
#' Allow user to specify NSPS and existing vintage retrofits for regions
#'
#' @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{L253.EF_retrofit}, \code{L253.EF_NSPS_new_vintage},
#' \code{L253.Retrofit_off}, \code{L253.delete_gdp_control},
#' \code{L253.user_EF_retrofit}, \code{L253.user_EF_NSPS_new_vintage},
#' \code{L253.user_Retrofit_off}, \code{L253.user_delete_gdp_control},
#' \code{L253.EF_retrofit_USA}, \code{L253.EF_NSPS_new_vintage_USA},
#' \code{L253.Retrofit_off_USA}, \code{L253.delete_gdp_control_USA},
#' \code{L253.user_EF_retrofit_USA}, \code{L253.user_EF_NSPS_new_vintage_USA},
#' \code{L253.user_Retrofit_off_USA}, \code{L253.user_delete_gdp_control_USA},
#' @author ENL August 2021
module_emissions_L253.emission_controls <- function(command, ...) {
# Get list of files from user drop folder, which will become inputs
list.files("inst/extdata/emissions/user_emission_controls", "*.csv", full.names = TRUE) %>%
sub('inst/extdata/', '', .) ->
user_em_control_files
names(user_em_control_files) <- rep("FILE", length(user_em_control_files))
if(command == driver.DECLARE_INPUTS) {
# List of all data that we need, either from csv input or another chunk
return(c(FILE = "common/GCAM_region_names",
FILE = "emissions/A_regions",
FILE = "gcam-usa/states_subregions",
FILE = "emissions/emission_controls/A53.em_ctrl_param_china_industry",
FILE = "emissions/emission_controls/A53.em_ctrl_param_intl_shipping",
FILE = "emissions/emission_controls/A53.em_ctrl_param_dom_shipping",
user_em_control_files, # All files in user_emission_controls folder
"L102.pcgdp_thous90USD_Scen_R_Y",
"L201.nonghg_steepness",
"L223.StubTechEff_elec",
"L223.GlobalTechEff_elec",
"L224.Supplysector_heat"))
} else if(command == driver.DECLARE_OUTPUTS) {
return(c("L253.EF_retrofit",
"L253.EF_NSPS_new_vintage",
"L253.Retrofit_off",
"L253.delete_gdp_control",
"L253.user_EF_retrofit",
"L253.user_EF_NSPS_new_vintage",
"L253.user_Retrofit_off",
"L253.user_delete_gdp_control",
"L253.EF_retrofit_USA",
"L253.EF_NSPS_new_vintage_USA",
"L253.Retrofit_off_USA",
"L253.delete_gdp_control_USA",
"L253.user_EF_retrofit_USA",
"L253.user_EF_NSPS_new_vintage_USA",
"L253.user_Retrofit_off_USA",
"L253.user_delete_gdp_control_USA"))
} else if(command == driver.MAKE) {
# Silencing package checks
. <- year <- supplysector <- MAC_region <- state <- state_name <-
scenario <- value <- SO2_name <- region <- NULL
all_data <- list(...)[[1]]
# Load required inputs
GCAM_region_names <- get_data(all_data, "common/GCAM_region_names")
non_co2_region_info <- get_data(all_data, "emissions/A_regions")
states_subregions <- get_data(all_data, "gcam-usa/states_subregions")
pcGDP_MER <- get_data(all_data, "L102.pcgdp_thous90USD_Scen_R_Y", strip_attributes = TRUE)
L201.nonghg_steepness <- get_data(all_data, "L201.nonghg_steepness", strip_attributes = TRUE)
base_year_eff <- get_data(all_data, "L223.StubTechEff_elec", strip_attributes = TRUE)
future_year_eff <- get_data(all_data, "L223.GlobalTechEff_elec", strip_attributes = TRUE) %>%
filter(year %in% MODEL_FUTURE_YEARS)
dist_heat_regions <- get_data(all_data, "L224.Supplysector_heat", strip_attributes = TRUE) %>%
select(region, supplysector)
# Load all inputs that contains A53. We do this to simplify the process of moving data
# from the user drop folder to the core. To move data to the core, the user just has to
# name them containing "A53" and include the files in driver.DECLARE_INPUTS
em_ctrl_inputs <- names(all_data[grep("A53", names(all_data))])
lapply(em_ctrl_inputs, function(name, all_data) {
get_data(all_data, name, strip_attributes = TRUE)
}, all_data) %>% bind_rows() -> em_ctrl_parameters
# Load user data from drop folder
lapply(user_em_control_files, function(name, all_data) {
get_data(all_data, name, strip_attributes = TRUE)
}, all_data) %>% bind_rows() -> user_em_ctrl_parameters
# Create mapping between meta region and GCAM-region for all cases listed below
# Users can specify MAC regions (specified in emissions/A_regions.csv) which will then be applied to all corresponding GCAM regions,
# USA state names or abbreviations which will be applied to GCAM-USA states,
# or, global pararamters "All" for all GCAM regions, and "All states" for all GCAM-USA states.
non_co2_region_info %>%
select(region, MAC_region) %>%
rename(GCAM_region = region,
meta_region = MAC_region) -> meta_region_map
states_subregions %>%
select(state, state_name) %>%
rename(GCAM_region = state,
meta_region = state_name) -> gcamusa_region_map
gcamusa_region_map %>%
bind_rows(mutate(gcamusa_region_map, meta_region = "All states")) -> gcamusa_region_map
meta_region_map %>%
bind_rows(mutate(meta_region_map, meta_region = "All"), gcamusa_region_map) -> meta_region_map
# Join GDP data with GCAM region by the region ID, and filter to only include data we need
# Convert GDP data to 2015$ to be consistent with the units expected in the emission control input files
# The scenario can be switched to another by substituting the new scenario with "gSSP2" here
pcGDP_MER %>%
filter(scenario == "gSSP2",
year %in% MODEL_YEARS) %>%
left_join_error_no_match(non_co2_region_info, by = "GCAM_region_ID") %>%
select(year, value, region) %>%
mutate(value = value * gdp_deflator(2015, 1990)) %>%
spread(year, value) -> pcGDP_MER
# Get regional SO2 species names
# SO2 names for GCAM-USA states are the same as the name for USA region in global GCAM
non_co2_region_info %>%
select(region, SO2_name) -> so2_reg_names_global
states_subregions %>% select(state) %>%
rename(region = state) %>%
mutate(SO2_name = so2_reg_names_global[[which(so2_reg_names_global$region == "USA"), "SO2_name"]]) -> so2_reg_names_states
bind_rows(so2_reg_names_global, so2_reg_names_states) -> so2_reg_names
# Function that processes emission control data
process_em_control_data <- function(em_control_data) {
# Silence package checks
GCAM_region <- supplysector <- region <- Non.CO2 <- SO2_name <-
tail <- pcGDP_start_NSPS <- NSPS_start_year <- NSPS_em_coeff <- year <- GDP <-
id <- retrofit_start_year <- pcGDP_start_retrofit <- subsector <-
stub.technology <- linear.control <- retrofit_time <- retrofit_vintage <-
retrofit_em_coeff <- start.year <- final.emissions.coefficient <- emiss.coef <-
head <- period <- end.year <- efficiency.y <- efficiency.x <- efficiency <-
gdp.control <- disable.em.control <- NULL
# Only run if there is emission control data
if(length(em_control_data) > 0){
# Combine emission control data with region mapping. If data has meta region mapping, keep corresponding GCAM region
# Otherwise, keep original region.
# Using left_join instead of left_join_error_no_match because not all regions have meta region mapping
em_control_data %>%
left_join(meta_region_map, by = c("region" = "meta_region")) %>%
filter(GCAM_region %in% dist_heat_regions$region |
!supplysector %in% dist_heat_regions$supplysector) %>%
mutate(region = if_else(is.na(GCAM_region), region, GCAM_region)) %>%
semi_join(L201.nonghg_steepness,
by = c("region", "supplysector", "subsector", "stub.technology")) %>%
select(-GCAM_region) -> em_control_data
# Stop if regions aren't valid regions
all_GCAM_regions <- all(em_control_data$region %in% c(GCAM_region_names$region, states_subregions$state))
if(!all_GCAM_regions){
stop("Emission control regions not valid GCAM or MAC regions")
}
# Name linear control based on the non-CO2 and replace SO2s with corresponding regional SO2 name
em_control_data %>%
mutate(linear.control = paste0(Non.CO2, "_control_retrofits")) %>%
left_join_error_no_match(so2_reg_names, by = "region") %>%
mutate(Non.CO2 = if_else(Non.CO2 == "SO2" & !region %in% states_subregions$state, SO2_name, Non.CO2)) %>%
select(-SO2_name) -> em_control_data
# Model years, including the last base year, that retrofits can be applied
# Note NSPS can be applied to all model future years which is already defined
retrofit_years <- c(tail(MODEL_BASE_YEARS, n=1), MODEL_FUTURE_YEARS)
# RETROFITS
# Extract only the data we need for retrofits from emission control data. Use row number to keep track of order.
# Join in regional GDP data and filter for retrofit years. If there is no user-inputted retrofit start year,
# we calculate it by finding all years where GDP is at least the inputted start GDP value, and keep the first
# occurrence, which is the year at which each region reaches pcGDP of the "pcGDP_start_retrofit" value
em_control_data %>%
mutate(id = row_number()) %>%
select(-c(pcGDP_start_NSPS, NSPS_start_year, NSPS_em_coeff, 'Notes and sources')) %>%
left_join_error_no_match(pcGDP_MER, by = "region") %>%
tidyr::gather(year, GDP, as.character(MODEL_YEARS)) %>%
arrange(id) %>%
filter(year %in% retrofit_years) %>%
mutate(retrofit_start_year = if_else(is.na(retrofit_start_year) & GDP >= pcGDP_start_retrofit,
as.numeric(year), retrofit_start_year)) %>%
select(-year, -GDP, -id) %>%
drop_na(retrofit_start_year) %>%
distinct(region, supplysector, subsector, stub.technology, Non.CO2,
linear.control, pcGDP_start_retrofit, retrofit_time,
retrofit_vintage, retrofit_em_coeff, .keep_all = TRUE) -> L253.EF_retrofit
# Rename to GCAM input names and calculate end year by adding retrofit time to start year
# If a region doesn't have retrofits (emissions coefficient of -1), remove row
L253.EF_retrofit %>%
rename(final.emissions.coefficient = retrofit_em_coeff,
start.year = retrofit_start_year) %>%
mutate(retrofit_time = as.numeric(retrofit_time),
end.year = start.year + retrofit_time) %>%
filter(final.emissions.coefficient != -1) -> L253.EF_retrofit
# NSPS
# Similar approach for NSPS
# Select NSPS data, get NSPS start year from either user-inputted data or calculated from GDP data
em_control_data %>%
mutate(id = row_number()) %>%
select(-c(pcGDP_start_retrofit, retrofit_start_year, retrofit_time, retrofit_vintage, retrofit_em_coeff, 'Notes and sources')) %>%
left_join_error_no_match(pcGDP_MER, by = "region")%>%
tidyr::gather(year, GDP, as.character(MODEL_YEARS)) %>%
arrange(id) %>%
filter(year %in% MODEL_FUTURE_YEARS) %>%
mutate(NSPS_start_year = if_else(is.na(NSPS_start_year) & GDP >= pcGDP_start_NSPS,
as.numeric(year), NSPS_start_year)) %>%
select(-year, -GDP, -id) %>%
drop_na(NSPS_start_year) %>%
distinct(region, supplysector, subsector, stub.technology, Non.CO2,
linear.control, pcGDP_start_NSPS, NSPS_em_coeff, .keep_all = TRUE) -> L253.EF_NSPS_new_vintage
# Rename to GCAM input names and remove regions without an NSPS
L253.EF_NSPS_new_vintage %>%
rename(emiss.coef = NSPS_em_coeff,
period = NSPS_start_year) %>%
filter(emiss.coef != -1) -> L253.EF_NSPS_new_vintage
# Remove the default generic control since more specific control is in place
em_control_data %>%
select(region, supplysector, subsector, stub.technology, linear.control, Non.CO2) %>%
mutate(period = head(MODEL_YEARS, n=1),
gdp.control = "GDP_control") -> L253.delete_gdp_control
# If there are multiple controls on same emissions and technologies within regions, keep latest data.
# distinct() keeps first occurrence, but we want to keep the last, so we reverse all rows,
# remove duplicates, and then reverse back to original order
L253.EF_retrofit %>% arrange(desc(row_number())) %>%
distinct(region, supplysector, subsector, stub.technology, Non.CO2,
retrofit_vintage, linear.control, .keep_all = TRUE) %>%
arrange(desc(row_number())) -> L253.EF_retrofit
L253.EF_NSPS_new_vintage %>% arrange(desc(row_number())) %>%
distinct(region, supplysector, subsector, stub.technology, Non.CO2,
linear.control, period, .keep_all = TRUE) %>%
arrange(desc(row_number())) -> L253.EF_NSPS_new_vintage
# Define a utility function that returns the next model year.
# Because we vectorize the function, the argument can be a vector (or column) of years
# If year passed in is last model year, return last model year
get_next_model_year <- Vectorize(function(year) {
if(!year %in% MODEL_YEARS) {
stop("Year is not a GCAM model year")
}
else if(year != tail(MODEL_YEARS, n = 1)){
MODEL_YEARS[which(MODEL_YEARS == year)+1]
}
else {return(year)}
})
# Turn off retrofits after end year of the last retrofit for that emission/technology/region
L253.EF_retrofit %>%
arrange(desc(retrofit_vintage)) %>%
distinct(region, supplysector, subsector, stub.technology, Non.CO2,
pcGDP_start_retrofit, start.year, retrofit_time, final.emissions.coefficient,
linear.control, end.year, .keep_all = TRUE) %>%
mutate(period = get_next_model_year(retrofit_vintage),
start.year = period,
end.year = tail(MODEL_FUTURE_YEARS, n=1),
disable.em.control = 1) -> L253.Retrofit_off
# Convert emission factors relative to the output unit where needed
# Divide by efficiency for electricity technologies which have output drivers
# Using left_join instead of left_join_error_no_match because not all sectors use output drivers
# Currently the only other sector that uses output drivers is the resource sector which we do not deal with
L253.EF_retrofit %>%
left_join(base_year_eff, by = c("region", "supplysector", "subsector", "stub.technology",
"retrofit_vintage" = "year")) %>%
left_join(future_year_eff, by = c("supplysector" = "sector.name", "subsector" = "subsector.name",
"stub.technology" = "technology", "retrofit_vintage" = "year")) %>%
# For techs without efficiencies, we divide by 1 (no change)
mutate(efficiency.y = if_else(is.na(efficiency.y), 1, efficiency.y),
final.emissions.coefficient = if_else(is.na(efficiency.x), final.emissions.coefficient/efficiency.y,
final.emissions.coefficient/efficiency.x)) -> L253.EF_retrofit_2
# We do the same for NSPS, but since NSPS can only be applied in future model years, we only join in future efficiency data
L253.EF_NSPS_new_vintage %>%
left_join(future_year_eff, by = c("supplysector" = "sector.name", "subsector" = "subsector.name",
"stub.technology" = "technology", "period" = "year")) %>%
mutate(efficiency = if_else(is.na(efficiency), 1, efficiency),
emiss.coef = emiss.coef/efficiency) -> L253.EF_NSPS_new_vintage
# Select/order only the relevant columns
# Note that although some sectors have different column names (eg tranSubsector instead of subsector in transportation)
# the C++ won't check for name mismatches so using these column names is fine
L253.EF_retrofit <- select(L253.EF_retrofit, region, supplysector, subsector, stub.technology, retrofit_vintage, Non.CO2, linear.control, start.year, end.year, final.emissions.coefficient)
L253.EF_NSPS_new_vintage <- select(L253.EF_NSPS_new_vintage, region, supplysector, subsector, stub.technology, period, Non.CO2, emiss.coef)
L253.delete_gdp_control <- select(L253.delete_gdp_control, region, supplysector, subsector, stub.technology, period, Non.CO2, gdp.control)
L253.Retrofit_off <- select(L253.Retrofit_off, region, supplysector, subsector, stub.technology, period, Non.CO2, linear.control, start.year, end.year, disable.em.control)
# Separate out US State emission controls
L253.EF_retrofit_USA <- filter(L253.EF_retrofit, region %in% states_subregions$state)
L253.EF_NSPS_new_vintage_USA <- filter(L253.EF_NSPS_new_vintage, region %in% states_subregions$state)
L253.delete_gdp_control_USA <- filter(L253.delete_gdp_control, region %in% states_subregions$state)
L253.Retrofit_off_USA <- filter(L253.Retrofit_off, region %in% states_subregions$state)
L253.EF_retrofit <- filter(L253.EF_retrofit, !region %in% states_subregions$state)
L253.EF_NSPS_new_vintage <- filter(L253.EF_NSPS_new_vintage, !region %in% states_subregions$state)
L253.delete_gdp_control <- filter(L253.delete_gdp_control, !region %in% states_subregions$state)
L253.Retrofit_off <- filter(L253.Retrofit_off, !region %in% states_subregions$state)
# Produce outputs
# If there is no user data, we set input list to NA and it will be filtered out during add_precursors
if(length(user_em_control_files) == 0){
user_em_control_files <- NA
}
# Create empty output if there is no data
if(exists("L253.EF_retrofit")) {
L253.EF_retrofit %>%
add_title("Emission Control Retrofits") %>%
add_units("Various") %>%
add_comments("Retrofit emission controls") -> L253.EF_retrofit
# Add precursors. Using do.call to add precursors from vectors
L253.EF_retrofit_precursors <- list(L253.EF_retrofit)
precursors <- na.omit(c("common/GCAM_region_names",
"emissions/A_regions",
user_em_control_files,
em_ctrl_inputs,
"L102.pcgdp_thous90USD_Scen_R_Y",
"L201.nonghg_steepness",
"L223.StubTechEff_elec",
"L223.GlobalTechEff_elec",
"L224.Supplysector_heat"))
L253.EF_retrofit_precursors[precursors] <- precursors
do.call(add_precursors, L253.EF_retrofit_precursors) -> L253.EF_retrofit
} else {
missing_data() -> L253.EF_retrofit
}
if(exists("L253.EF_NSPS_new_vintage")) {
L253.EF_NSPS_new_vintage %>%
add_title("NSPS Emission Controls") %>%
add_units("Various") %>%
add_comments("New Source Performance Standard Emission controls") %>%
same_precursors_as(L253.EF_retrofit) -> L253.EF_NSPS_new_vintage
} else {
missing_data() -> L253.EF_NSPS_new_vintage
}
if(exists("L253.Retrofit_off")) {
L253.Retrofit_off %>%
add_title("Retrofit Off") %>%
add_units("Various") %>%
add_comments("Turn off retrofit") -> L253.Retrofit_off
L253.Retrofit_off_precursors <- list(L253.Retrofit_off)
precursors <- na.omit(c("common/GCAM_region_names",
"emissions/A_regions",
user_em_control_files,
em_ctrl_inputs,
"L102.pcgdp_thous90USD_Scen_R_Y"))
L253.Retrofit_off_precursors[precursors] <- precursors
do.call(add_precursors, L253.Retrofit_off_precursors) -> L253.Retrofit_off
} else {
missing_data() -> L253.Retrofit_off
}
if(exists("L253.delete_gdp_control")) {
L253.delete_gdp_control %>%
add_title("Delete GDP Control") %>%
add_units("Various") %>%
add_comments("Delete GDP control because new control is in place") %>%
same_precursors_as(L253.Retrofit_off) -> L253.delete_gdp_control
} else {
missing_data() -> L253.delete_gdp_control
}
if(exists("L253.EF_retrofit_USA")) {
L253.EF_retrofit_USA %>%
add_title("U.S. States Emission Control Retrofits") %>%
add_units("Various") %>%
add_comments("U.S. states retrofit emission controls") -> L253.EF_retrofit_USA
L253.EF_retrofit_USA_precursors <- list(L253.EF_retrofit_USA)
precursors <- na.omit(c("common/GCAM_region_names",
"emissions/A_regions",
"gcam-usa/states_subregions",
user_em_control_files,
em_ctrl_inputs,
"L102.pcgdp_thous90USD_Scen_R_Y",
"L201.nonghg_steepness",
"L223.StubTechEff_elec",
"L223.GlobalTechEff_elec",
"L224.Supplysector_heat"))
L253.EF_retrofit_USA_precursors[precursors] <- precursors
do.call(add_precursors, L253.EF_retrofit_USA_precursors) -> L253.EF_retrofit_USA
} else {
missing_data() -> L253.EF_retrofit_USA
}
if(exists("L253.EF_NSPS_new_vintage_USA")) {
L253.EF_NSPS_new_vintage_USA %>%
add_title("U.S. States NSPS Emission Controls") %>%
add_units("Various") %>%
add_comments("U.S. states New Source Performance Standard Emission controls") %>%
same_precursors_as(L253.EF_retrofit_USA) -> L253.EF_NSPS_new_vintage_USA
} else {
missing_data() -> L253.EF_NSPS_new_vintage_USA
}
if(exists("L253.Retrofit_off_USA")) {
L253.Retrofit_off_USA %>%
add_title("U.S. States Retrofit Off") %>%
add_units("Various") %>%
add_comments("Turn off retrofit in U.S. states") -> L253.Retrofit_off_USA
L253.Retrofit_off_USA_precursors <- list(L253.Retrofit_off_USA)
precursors <- na.omit(c("common/GCAM_region_names",
"emissions/A_regions",
"gcam-usa/states_subregions",
user_em_control_files,
em_ctrl_inputs,
"L102.pcgdp_thous90USD_Scen_R_Y"))
L253.Retrofit_off_USA_precursors[precursors] <- precursors
do.call(add_precursors, L253.Retrofit_off_USA_precursors) -> L253.Retrofit_off_USA
} else {
missing_data() -> L253.Retrofit_off_USA
}
if(exists("L253.delete_gdp_control_USA")) {
L253.delete_gdp_control_USA %>%
add_title("U.S. States Delete GDP Control") %>%
add_units("Various") %>%
add_comments("Delete GDP control in U.S. states because new control is in place") %>%
same_precursors_as(L253.Retrofit_off_USA) -> L253.delete_gdp_control_USA
} else {
missing_data() -> L253.delete_gdp_control_USA
}
} else {
# There is no emissions control data, so we set missing data to each output
missing_data() -> L253.EF_retrofit
missing_data() -> L253.EF_NSPS_new_vintage
missing_data() -> L253.Retrofit_off
missing_data() -> L253.delete_gdp_control
missing_data() -> L253.EF_retrofit_USA
missing_data() -> L253.EF_NSPS_new_vintage_USA
missing_data() -> L253.Retrofit_off_USA
missing_data() -> L253.delete_gdp_control_USA
} # end ifelse
# Get all outputs from function into list
out <- list(L253.EF_retrofit = L253.EF_retrofit,
L253.EF_NSPS_new_vintage = L253.EF_NSPS_new_vintage,
L253.Retrofit_off = L253.Retrofit_off,
L253.delete_gdp_control = L253.delete_gdp_control,
L253.EF_retrofit_USA = L253.EF_retrofit_USA,
L253.EF_NSPS_new_vintage_USA = L253.EF_NSPS_new_vintage_USA,
L253.Retrofit_off_USA = L253.Retrofit_off_USA,
L253.delete_gdp_control_USA = L253.delete_gdp_control_USA)
return(out)
} # end process_em_control_data
# Run function twice, one for core emissions control data and one for user emissions control data
outputs <- process_em_control_data(em_ctrl_parameters)
outputs_user <- process_em_control_data(user_em_ctrl_parameters)
# Get specific outputs from outputs list
L253.EF_retrofit <- outputs$L253.EF_retrofit
L253.EF_NSPS_new_vintage <- outputs$L253.EF_NSPS_new_vintage
L253.Retrofit_off <- outputs$L253.Retrofit_off
L253.delete_gdp_control <- outputs$L253.delete_gdp_control
L253.user_EF_retrofit <- outputs_user$L253.EF_retrofit
L253.user_EF_NSPS_new_vintage <- outputs_user$L253.EF_NSPS_new_vintage
L253.user_Retrofit_off <- outputs_user$L253.Retrofit_off
L253.user_delete_gdp_control <- outputs_user$L253.delete_gdp_control
L253.EF_retrofit_USA <- outputs$L253.EF_retrofit_USA
L253.EF_NSPS_new_vintage_USA <- outputs$L253.EF_NSPS_new_vintage_USA
L253.Retrofit_off_USA <- outputs$L253.Retrofit_off_USA
L253.delete_gdp_control_USA <- outputs$L253.delete_gdp_control_USA
L253.user_EF_retrofit_USA<- outputs_user$L253.EF_retrofit_USA
L253.user_EF_NSPS_new_vintage_USA <- outputs_user$L253.EF_NSPS_new_vintage_USA
L253.user_Retrofit_off_USA <- outputs_user$L253.Retrofit_off_USA
L253.user_delete_gdp_control_USA <- outputs_user$L253.delete_gdp_control_USA
return_data(L253.EF_retrofit,
L253.EF_NSPS_new_vintage,
L253.Retrofit_off,
L253.delete_gdp_control,
L253.user_EF_retrofit,
L253.user_EF_NSPS_new_vintage,
L253.user_Retrofit_off,
L253.user_delete_gdp_control,
L253.EF_retrofit_USA,
L253.EF_NSPS_new_vintage_USA,
L253.Retrofit_off_USA,
L253.delete_gdp_control_USA,
L253.user_EF_retrofit_USA,
L253.user_EF_NSPS_new_vintage_USA,
L253.user_Retrofit_off_USA,
L253.user_delete_gdp_control_USA)
} else {
stop("Unknown command")
}
}
JGCRI/gcamdata documentation built on March 21, 2023, 2:19 a.m.
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Defines functions module_emissions_L253.emission_controls
Documented in module_emissions_L253.emission_controls
# Copyright 2019 Battelle Memorial Institute; see the LICENSE file.
#' module_emissions_L253.emission_controls
#'
#' Allow user to specify NSPS and existing vintage retrofits for regions
#'
#' @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{L253.EF_retrofit}, \code{L253.EF_NSPS_new_vintage},
#' \code{L253.Retrofit_off}, \code{L253.delete_gdp_control},
#' \code{L253.user_EF_retrofit}, \code{L253.user_EF_NSPS_new_vintage},
#' \code{L253.user_Retrofit_off}, \code{L253.user_delete_gdp_control},
#' \code{L253.EF_retrofit_USA}, \code{L253.EF_NSPS_new_vintage_USA},
#' \code{L253.Retrofit_off_USA}, \code{L253.delete_gdp_control_USA},
#' \code{L253.user_EF_retrofit_USA}, \code{L253.user_EF_NSPS_new_vintage_USA},
#' \code{L253.user_Retrofit_off_USA}, \code{L253.user_delete_gdp_control_USA},
#' @author ENL August 2021
module_emissions_L253.emission_controls <- function(command, ...) {
# Get list of files from user drop folder, which will become inputs
list.files("inst/extdata/emissions/user_emission_controls", "*.csv", full.names = TRUE) %>%
sub('inst/extdata/', '', .) ->
user_em_control_files
names(user_em_control_files) <- rep("FILE", length(user_em_control_files))
if(command == driver.DECLARE_INPUTS) {
# List of all data that we need, either from csv input or another chunk
return(c(FILE = "common/GCAM_region_names",
FILE = "emissions/A_regions",
FILE = "gcam-usa/states_subregions",
FILE = "emissions/emission_controls/A53.em_ctrl_param_china_industry",
FILE = "emissions/emission_controls/A53.em_ctrl_param_intl_shipping",
FILE = "emissions/emission_controls/A53.em_ctrl_param_dom_shipping",
user_em_control_files, # All files in user_emission_controls folder
"L102.pcgdp_thous90USD_Scen_R_Y",
"L201.nonghg_steepness",
"L223.StubTechEff_elec",
"L223.GlobalTechEff_elec",
"L224.Supplysector_heat"))
} else if(command == driver.DECLARE_OUTPUTS) {
return(c("L253.EF_retrofit",
"L253.EF_NSPS_new_vintage",
"L253.Retrofit_off",
"L253.delete_gdp_control",
"L253.user_EF_retrofit",
"L253.user_EF_NSPS_new_vintage",
"L253.user_Retrofit_off",
"L253.user_delete_gdp_control",
"L253.EF_retrofit_USA",
"L253.EF_NSPS_new_vintage_USA",
"L253.Retrofit_off_USA",
"L253.delete_gdp_control_USA",
"L253.user_EF_retrofit_USA",
"L253.user_EF_NSPS_new_vintage_USA",
"L253.user_Retrofit_off_USA",
"L253.user_delete_gdp_control_USA"))
} else if(command == driver.MAKE) {
# Silencing package checks
. <- year <- supplysector <- MAC_region <- state <- state_name <-
scenario <- value <- SO2_name <- region <- NULL
all_data <- list(...)[[1]]
# Load required inputs
GCAM_region_names <- get_data(all_data, "common/GCAM_region_names")
non_co2_region_info <- get_data(all_data, "emissions/A_regions")
states_subregions <- get_data(all_data, "gcam-usa/states_subregions")
pcGDP_MER <- get_data(all_data, "L102.pcgdp_thous90USD_Scen_R_Y", strip_attributes = TRUE)
L201.nonghg_steepness <- get_data(all_data, "L201.nonghg_steepness", strip_attributes = TRUE)
base_year_eff <- get_data(all_data, "L223.StubTechEff_elec", strip_attributes = TRUE)
future_year_eff <- get_data(all_data, "L223.GlobalTechEff_elec", strip_attributes = TRUE) %>%
filter(year %in% MODEL_FUTURE_YEARS)
dist_heat_regions <- get_data(all_data, "L224.Supplysector_heat", strip_attributes = TRUE) %>%
select(region, supplysector)
# Load all inputs that contains A53. We do this to simplify the process of moving data
# from the user drop folder to the core. To move data to the core, the user just has to
# name them containing "A53" and include the files in driver.DECLARE_INPUTS
em_ctrl_inputs <- names(all_data[grep("A53", names(all_data))])
lapply(em_ctrl_inputs, function(name, all_data) {
get_data(all_data, name, strip_attributes = TRUE)
}, all_data) %>% bind_rows() -> em_ctrl_parameters
# Load user data from drop folder
lapply(user_em_control_files, function(name, all_data) {
get_data(all_data, name, strip_attributes = TRUE)
}, all_data) %>% bind_rows() -> user_em_ctrl_parameters
# Create mapping between meta region and GCAM-region for all cases listed below
# Users can specify MAC regions (specified in emissions/A_regions.csv) which will then be applied to all corresponding GCAM regions,
# USA state names or abbreviations which will be applied to GCAM-USA states,
# or, global pararamters "All" for all GCAM regions, and "All states" for all GCAM-USA states.
non_co2_region_info %>%
select(region, MAC_region) %>%
rename(GCAM_region = region,
meta_region = MAC_region) -> meta_region_map
states_subregions %>%
select(state, state_name) %>%
rename(GCAM_region = state,
meta_region = state_name) -> gcamusa_region_map
gcamusa_region_map %>%
bind_rows(mutate(gcamusa_region_map, meta_region = "All states")) -> gcamusa_region_map
meta_region_map %>%
bind_rows(mutate(meta_region_map, meta_region = "All"), gcamusa_region_map) -> meta_region_map
# Join GDP data with GCAM region by the region ID, and filter to only include data we need
# Convert GDP data to 2015$ to be consistent with the units expected in the emission control input files
# The scenario can be switched to another by substituting the new scenario with "gSSP2" here
pcGDP_MER %>%
filter(scenario == "gSSP2",
year %in% MODEL_YEARS) %>%
left_join_error_no_match(non_co2_region_info, by = "GCAM_region_ID") %>%
select(year, value, region) %>%
mutate(value = value * gdp_deflator(2015, 1990)) %>%
spread(year, value) -> pcGDP_MER
# Get regional SO2 species names
# SO2 names for GCAM-USA states are the same as the name for USA region in global GCAM
non_co2_region_info %>%
select(region, SO2_name) -> so2_reg_names_global
states_subregions %>% select(state) %>%
rename(region = state) %>%
mutate(SO2_name = so2_reg_names_global[[which(so2_reg_names_global$region == "USA"), "SO2_name"]]) -> so2_reg_names_states
bind_rows(so2_reg_names_global, so2_reg_names_states) -> so2_reg_names
# Function that processes emission control data
process_em_control_data <- function(em_control_data) {
# Silence package checks
GCAM_region <- supplysector <- region <- Non.CO2 <- SO2_name <-
tail <- pcGDP_start_NSPS <- NSPS_start_year <- NSPS_em_coeff <- year <- GDP <-
id <- retrofit_start_year <- pcGDP_start_retrofit <- subsector <-
stub.technology <- linear.control <- retrofit_time <- retrofit_vintage <-
retrofit_em_coeff <- start.year <- final.emissions.coefficient <- emiss.coef <-
head <- period <- end.year <- efficiency.y <- efficiency.x <- efficiency <-
gdp.control <- disable.em.control <- NULL
# Only run if there is emission control data
if(length(em_control_data) > 0){
# Combine emission control data with region mapping. If data has meta region mapping, keep corresponding GCAM region
# Otherwise, keep original region.
# Using left_join instead of left_join_error_no_match because not all regions have meta region mapping
em_control_data %>%
left_join(meta_region_map, by = c("region" = "meta_region")) %>%
filter(GCAM_region %in% dist_heat_regions$region |
!supplysector %in% dist_heat_regions$supplysector) %>%
mutate(region = if_else(is.na(GCAM_region), region, GCAM_region)) %>%
semi_join(L201.nonghg_steepness,
by = c("region", "supplysector", "subsector", "stub.technology")) %>%
select(-GCAM_region) -> em_control_data
# Stop if regions aren't valid regions
all_GCAM_regions <- all(em_control_data$region %in% c(GCAM_region_names$region, states_subregions$state))
if(!all_GCAM_regions){
stop("Emission control regions not valid GCAM or MAC regions")
}
# Name linear control based on the non-CO2 and replace SO2s with corresponding regional SO2 name
em_control_data %>%
mutate(linear.control = paste0(Non.CO2, "_control_retrofits")) %>%
left_join_error_no_match(so2_reg_names, by = "region") %>%
mutate(Non.CO2 = if_else(Non.CO2 == "SO2" & !region %in% states_subregions$state, SO2_name, Non.CO2)) %>%
select(-SO2_name) -> em_control_data
# Model years, including the last base year, that retrofits can be applied
# Note NSPS can be applied to all model future years which is already defined
retrofit_years <- c(tail(MODEL_BASE_YEARS, n=1), MODEL_FUTURE_YEARS)
# RETROFITS
# Extract only the data we need for retrofits from emission control data. Use row number to keep track of order.
# Join in regional GDP data and filter for retrofit years. If there is no user-inputted retrofit start year,
# we calculate it by finding all years where GDP is at least the inputted start GDP value, and keep the first
# occurrence, which is the year at which each region reaches pcGDP of the "pcGDP_start_retrofit" value
em_control_data %>%
mutate(id = row_number()) %>%
select(-c(pcGDP_start_NSPS, NSPS_start_year, NSPS_em_coeff, 'Notes and sources')) %>%
left_join_error_no_match(pcGDP_MER, by = "region") %>%
tidyr::gather(year, GDP, as.character(MODEL_YEARS)) %>%
arrange(id) %>%
filter(year %in% retrofit_years) %>%
mutate(retrofit_start_year = if_else(is.na(retrofit_start_year) & GDP >= pcGDP_start_retrofit,
as.numeric(year), retrofit_start_year)) %>%
select(-year, -GDP, -id) %>%
drop_na(retrofit_start_year) %>%
distinct(region, supplysector, subsector, stub.technology, Non.CO2,
linear.control, pcGDP_start_retrofit, retrofit_time,
retrofit_vintage, retrofit_em_coeff, .keep_all = TRUE) -> L253.EF_retrofit
# Rename to GCAM input names and calculate end year by adding retrofit time to start year
# If a region doesn't have retrofits (emissions coefficient of -1), remove row
L253.EF_retrofit %>%
rename(final.emissions.coefficient = retrofit_em_coeff,
start.year = retrofit_start_year) %>%
mutate(retrofit_time = as.numeric(retrofit_time),
end.year = start.year + retrofit_time) %>%
filter(final.emissions.coefficient != -1) -> L253.EF_retrofit
# NSPS
# Similar approach for NSPS
# Select NSPS data, get NSPS start year from either user-inputted data or calculated from GDP data
em_control_data %>%
mutate(id = row_number()) %>%
select(-c(pcGDP_start_retrofit, retrofit_start_year, retrofit_time, retrofit_vintage, retrofit_em_coeff, 'Notes and sources')) %>%
left_join_error_no_match(pcGDP_MER, by = "region")%>%
tidyr::gather(year, GDP, as.character(MODEL_YEARS)) %>%
arrange(id) %>%
filter(year %in% MODEL_FUTURE_YEARS) %>%
mutate(NSPS_start_year = if_else(is.na(NSPS_start_year) & GDP >= pcGDP_start_NSPS,
as.numeric(year), NSPS_start_year)) %>%
select(-year, -GDP, -id) %>%
drop_na(NSPS_start_year) %>%
distinct(region, supplysector, subsector, stub.technology, Non.CO2,
linear.control, pcGDP_start_NSPS, NSPS_em_coeff, .keep_all = TRUE) -> L253.EF_NSPS_new_vintage
# Rename to GCAM input names and remove regions without an NSPS
L253.EF_NSPS_new_vintage %>%
rename(emiss.coef = NSPS_em_coeff,
period = NSPS_start_year) %>%
filter(emiss.coef != -1) -> L253.EF_NSPS_new_vintage
# Remove the default generic control since more specific control is in place
em_control_data %>%
select(region, supplysector, subsector, stub.technology, linear.control, Non.CO2) %>%
mutate(period = head(MODEL_YEARS, n=1),
gdp.control = "GDP_control") -> L253.delete_gdp_control
# If there are multiple controls on same emissions and technologies within regions, keep latest data.
# distinct() keeps first occurrence, but we want to keep the last, so we reverse all rows,
# remove duplicates, and then reverse back to original order
L253.EF_retrofit %>% arrange(desc(row_number())) %>%
distinct(region, supplysector, subsector, stub.technology, Non.CO2,
retrofit_vintage, linear.control, .keep_all = TRUE) %>%
arrange(desc(row_number())) -> L253.EF_retrofit
L253.EF_NSPS_new_vintage %>% arrange(desc(row_number())) %>%
distinct(region, supplysector, subsector, stub.technology, Non.CO2,
linear.control, period, .keep_all = TRUE) %>%
arrange(desc(row_number())) -> L253.EF_NSPS_new_vintage
# Define a utility function that returns the next model year.
# Because we vectorize the function, the argument can be a vector (or column) of years
# If year passed in is last model year, return last model year
get_next_model_year <- Vectorize(function(year) {
if(!year %in% MODEL_YEARS) {
stop("Year is not a GCAM model year")
}
else if(year != tail(MODEL_YEARS, n = 1)){
MODEL_YEARS[which(MODEL_YEARS == year)+1]
}
else {return(year)}
})
# Turn off retrofits after end year of the last retrofit for that emission/technology/region
L253.EF_retrofit %>%
arrange(desc(retrofit_vintage)) %>%
distinct(region, supplysector, subsector, stub.technology, Non.CO2,
pcGDP_start_retrofit, start.year, retrofit_time, final.emissions.coefficient,
linear.control, end.year, .keep_all = TRUE) %>%
mutate(period = get_next_model_year(retrofit_vintage),
start.year = period,
end.year = tail(MODEL_FUTURE_YEARS, n=1),
disable.em.control = 1) -> L253.Retrofit_off
# Convert emission factors relative to the output unit where needed
# Divide by efficiency for electricity technologies which have output drivers
# Using left_join instead of left_join_error_no_match because not all sectors use output drivers
# Currently the only other sector that uses output drivers is the resource sector which we do not deal with
L253.EF_retrofit %>%
left_join(base_year_eff, by = c("region", "supplysector", "subsector", "stub.technology",
"retrofit_vintage" = "year")) %>%
left_join(future_year_eff, by = c("supplysector" = "sector.name", "subsector" = "subsector.name",
"stub.technology" = "technology", "retrofit_vintage" = "year")) %>%
# For techs without efficiencies, we divide by 1 (no change)
mutate(efficiency.y = if_else(is.na(efficiency.y), 1, efficiency.y),
final.emissions.coefficient = if_else(is.na(efficiency.x), final.emissions.coefficient/efficiency.y,
final.emissions.coefficient/efficiency.x)) -> L253.EF_retrofit_2
# We do the same for NSPS, but since NSPS can only be applied in future model years, we only join in future efficiency data
L253.EF_NSPS_new_vintage %>%
left_join(future_year_eff, by = c("supplysector" = "sector.name", "subsector" = "subsector.name",
"stub.technology" = "technology", "period" = "year")) %>%
mutate(efficiency = if_else(is.na(efficiency), 1, efficiency),
emiss.coef = emiss.coef/efficiency) -> L253.EF_NSPS_new_vintage
# Select/order only the relevant columns
# Note that although some sectors have different column names (eg tranSubsector instead of subsector in transportation)
# the C++ won't check for name mismatches so using these column names is fine
L253.EF_retrofit <- select(L253.EF_retrofit, region, supplysector, subsector, stub.technology, retrofit_vintage, Non.CO2, linear.control, start.year, end.year, final.emissions.coefficient)
L253.EF_NSPS_new_vintage <- select(L253.EF_NSPS_new_vintage, region, supplysector, subsector, stub.technology, period, Non.CO2, emiss.coef)
L253.delete_gdp_control <- select(L253.delete_gdp_control, region, supplysector, subsector, stub.technology, period, Non.CO2, gdp.control)
L253.Retrofit_off <- select(L253.Retrofit_off, region, supplysector, subsector, stub.technology, period, Non.CO2, linear.control, start.year, end.year, disable.em.control)
# Separate out US State emission controls
L253.EF_retrofit_USA <- filter(L253.EF_retrofit, region %in% states_subregions$state)
L253.EF_NSPS_new_vintage_USA <- filter(L253.EF_NSPS_new_vintage, region %in% states_subregions$state)
L253.delete_gdp_control_USA <- filter(L253.delete_gdp_control, region %in% states_subregions$state)
L253.Retrofit_off_USA <- filter(L253.Retrofit_off, region %in% states_subregions$state)
L253.EF_retrofit <- filter(L253.EF_retrofit, !region %in% states_subregions$state)
L253.EF_NSPS_new_vintage <- filter(L253.EF_NSPS_new_vintage, !region %in% states_subregions$state)
L253.delete_gdp_control <- filter(L253.delete_gdp_control, !region %in% states_subregions$state)
L253.Retrofit_off <- filter(L253.Retrofit_off, !region %in% states_subregions$state)
# Produce outputs
# If there is no user data, we set input list to NA and it will be filtered out during add_precursors
if(length(user_em_control_files) == 0){
user_em_control_files <- NA
}
# Create empty output if there is no data
if(exists("L253.EF_retrofit")) {
L253.EF_retrofit %>%
add_title("Emission Control Retrofits") %>%
add_units("Various") %>%
add_comments("Retrofit emission controls") -> L253.EF_retrofit
# Add precursors. Using do.call to add precursors from vectors
L253.EF_retrofit_precursors <- list(L253.EF_retrofit)
precursors <- na.omit(c("common/GCAM_region_names",
"emissions/A_regions",
user_em_control_files,
em_ctrl_inputs,
"L102.pcgdp_thous90USD_Scen_R_Y",
"L201.nonghg_steepness",
"L223.StubTechEff_elec",
"L223.GlobalTechEff_elec",
"L224.Supplysector_heat"))
L253.EF_retrofit_precursors[precursors] <- precursors
do.call(add_precursors, L253.EF_retrofit_precursors) -> L253.EF_retrofit
} else {
missing_data() -> L253.EF_retrofit
}
if(exists("L253.EF_NSPS_new_vintage")) {
L253.EF_NSPS_new_vintage %>%
add_title("NSPS Emission Controls") %>%
add_units("Various") %>%
add_comments("New Source Performance Standard Emission controls") %>%
same_precursors_as(L253.EF_retrofit) -> L253.EF_NSPS_new_vintage
} else {
missing_data() -> L253.EF_NSPS_new_vintage
}
if(exists("L253.Retrofit_off")) {
L253.Retrofit_off %>%
add_title("Retrofit Off") %>%
add_units("Various") %>%
add_comments("Turn off retrofit") -> L253.Retrofit_off
L253.Retrofit_off_precursors <- list(L253.Retrofit_off)
precursors <- na.omit(c("common/GCAM_region_names",
"emissions/A_regions",
user_em_control_files,
em_ctrl_inputs,
"L102.pcgdp_thous90USD_Scen_R_Y"))
L253.Retrofit_off_precursors[precursors] <- precursors
do.call(add_precursors, L253.Retrofit_off_precursors) -> L253.Retrofit_off
} else {
missing_data() -> L253.Retrofit_off
}
if(exists("L253.delete_gdp_control")) {
L253.delete_gdp_control %>%
add_title("Delete GDP Control") %>%
add_units("Various") %>%
add_comments("Delete GDP control because new control is in place") %>%
same_precursors_as(L253.Retrofit_off) -> L253.delete_gdp_control
} else {
missing_data() -> L253.delete_gdp_control
}
if(exists("L253.EF_retrofit_USA")) {
L253.EF_retrofit_USA %>%
add_title("U.S. States Emission Control Retrofits") %>%
add_units("Various") %>%
add_comments("U.S. states retrofit emission controls") -> L253.EF_retrofit_USA
L253.EF_retrofit_USA_precursors <- list(L253.EF_retrofit_USA)
precursors <- na.omit(c("common/GCAM_region_names",
"emissions/A_regions",
"gcam-usa/states_subregions",
user_em_control_files,
em_ctrl_inputs,
"L102.pcgdp_thous90USD_Scen_R_Y",
"L201.nonghg_steepness",
"L223.StubTechEff_elec",
"L223.GlobalTechEff_elec",
"L224.Supplysector_heat"))
L253.EF_retrofit_USA_precursors[precursors] <- precursors
do.call(add_precursors, L253.EF_retrofit_USA_precursors) -> L253.EF_retrofit_USA
} else {
missing_data() -> L253.EF_retrofit_USA
}
if(exists("L253.EF_NSPS_new_vintage_USA")) {
L253.EF_NSPS_new_vintage_USA %>%
add_title("U.S. States NSPS Emission Controls") %>%
add_units("Various") %>%
add_comments("U.S. states New Source Performance Standard Emission controls") %>%
same_precursors_as(L253.EF_retrofit_USA) -> L253.EF_NSPS_new_vintage_USA
} else {
missing_data() -> L253.EF_NSPS_new_vintage_USA
}
if(exists("L253.Retrofit_off_USA")) {
L253.Retrofit_off_USA %>%
add_title("U.S. States Retrofit Off") %>%
add_units("Various") %>%
add_comments("Turn off retrofit in U.S. states") -> L253.Retrofit_off_USA
L253.Retrofit_off_USA_precursors <- list(L253.Retrofit_off_USA)
precursors <- na.omit(c("common/GCAM_region_names",
"emissions/A_regions",
"gcam-usa/states_subregions",
user_em_control_files,
em_ctrl_inputs,
"L102.pcgdp_thous90USD_Scen_R_Y"))
L253.Retrofit_off_USA_precursors[precursors] <- precursors
do.call(add_precursors, L253.Retrofit_off_USA_precursors) -> L253.Retrofit_off_USA
} else {
missing_data() -> L253.Retrofit_off_USA
}
if(exists("L253.delete_gdp_control_USA")) {
L253.delete_gdp_control_USA %>%
add_title("U.S. States Delete GDP Control") %>%
add_units("Various") %>%
add_comments("Delete GDP control in U.S. states because new control is in place") %>%
same_precursors_as(L253.Retrofit_off_USA) -> L253.delete_gdp_control_USA
} else {
missing_data() -> L253.delete_gdp_control_USA
}
} else {
# There is no emissions control data, so we set missing data to each output
missing_data() -> L253.EF_retrofit
missing_data() -> L253.EF_NSPS_new_vintage
missing_data() -> L253.Retrofit_off
missing_data() -> L253.delete_gdp_control
missing_data() -> L253.EF_retrofit_USA
missing_data() -> L253.EF_NSPS_new_vintage_USA
missing_data() -> L253.Retrofit_off_USA
missing_data() -> L253.delete_gdp_control_USA
} # end ifelse
# Get all outputs from function into list
out <- list(L253.EF_retrofit = L253.EF_retrofit,
L253.EF_NSPS_new_vintage = L253.EF_NSPS_new_vintage,
L253.Retrofit_off = L253.Retrofit_off,
L253.delete_gdp_control = L253.delete_gdp_control,
L253.EF_retrofit_USA = L253.EF_retrofit_USA,
L253.EF_NSPS_new_vintage_USA = L253.EF_NSPS_new_vintage_USA,
L253.Retrofit_off_USA = L253.Retrofit_off_USA,
L253.delete_gdp_control_USA = L253.delete_gdp_control_USA)
return(out)
} # end process_em_control_data
# Run function twice, one for core emissions control data and one for user emissions control data
outputs <- process_em_control_data(em_ctrl_parameters)
outputs_user <- process_em_control_data(user_em_ctrl_parameters)
# Get specific outputs from outputs list
L253.EF_retrofit <- outputs$L253.EF_retrofit
L253.EF_NSPS_new_vintage <- outputs$L253.EF_NSPS_new_vintage
L253.Retrofit_off <- outputs$L253.Retrofit_off
L253.delete_gdp_control <- outputs$L253.delete_gdp_control
L253.user_EF_retrofit <- outputs_user$L253.EF_retrofit
L253.user_EF_NSPS_new_vintage <- outputs_user$L253.EF_NSPS_new_vintage
L253.user_Retrofit_off <- outputs_user$L253.Retrofit_off
L253.user_delete_gdp_control <- outputs_user$L253.delete_gdp_control
L253.EF_retrofit_USA <- outputs$L253.EF_retrofit_USA
L253.EF_NSPS_new_vintage_USA <- outputs$L253.EF_NSPS_new_vintage_USA
L253.Retrofit_off_USA <- outputs$L253.Retrofit_off_USA
L253.delete_gdp_control_USA <- outputs$L253.delete_gdp_control_USA
L253.user_EF_retrofit_USA<- outputs_user$L253.EF_retrofit_USA
L253.user_EF_NSPS_new_vintage_USA <- outputs_user$L253.EF_NSPS_new_vintage_USA
L253.user_Retrofit_off_USA <- outputs_user$L253.Retrofit_off_USA
L253.user_delete_gdp_control_USA <- outputs_user$L253.delete_gdp_control_USA
return_data(L253.EF_retrofit,
L253.EF_NSPS_new_vintage,
L253.Retrofit_off,
L253.delete_gdp_control,
L253.user_EF_retrofit,
L253.user_EF_NSPS_new_vintage,
L253.user_Retrofit_off,
L253.user_delete_gdp_control,
L253.EF_retrofit_USA,
L253.EF_NSPS_new_vintage_USA,
L253.Retrofit_off_USA,
L253.delete_gdp_control_USA,
L253.user_EF_retrofit_USA,
L253.user_EF_NSPS_new_vintage_USA,
L253.user_Retrofit_off_USA,
L253.user_delete_gdp_control_USA)
} else {
stop("Unknown command")
}
}
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