data-raw/create_constants.R
In MatthewHeun/IEATools: Tools for Working with International Energy Agency Data
# This script creates constants and saves them in the right locations.
# If there are any changes to these constants,
# source this script before building the package.
library(magrittr)
library(IEATools)
#
# Define the valid IEA release years for which this package will work
#
valid_iea_release_years <- c(2021, 2022)
usethis::use_data(valid_iea_release_years, overwrite = TRUE)
#
# Give the column names of IEA data frames in typical left-to-right order.
#
iea_cols <- list(country = "Country",
method = "Method",
energy_type = "Energy.type",
last_stage = "Last.stage",
year = "Year",
ledger_side = "Ledger.side",
flow_aggregation_point = "Flow.aggregation.point",
flow = "Flow",
product = "Product",
unit = "Unit",
e_dot = "E.dot")
usethis::use_data(iea_cols, overwrite = TRUE)
#
# Country concordance table columns
#
country_concordance_cols <- list(pfu_code = "PFU.code",
iea_name = "IEA.name")
usethis::use_data(country_concordance_cols, overwrite = TRUE)
#
# Default override data frame for 3-letter country codes.
# This constant is used in the use_iso_countries() function.
# The second column is the name in the IEA extended energy balance database.
# The first column is the 3-letter code we will use in the PFU database.
# This data frame is how we handle non-standard country names
# as well as IEA-only countries and aggregations.
#
override_iso_codes_df <- tibble::tribble(
~a, ~b,
"WRLD", "World",
"CHNM", "People's Republic of China",
"HKG", "Hong Kong (China)",
"SUN", "Former Soviet Union (if no detail)",
"WMBK", "World marine bunkers",
"WABK", "World aviation bunkers",
"YUG", "Former Yugoslavia (if no detail)") %>%
magrittr::set_names(c(country_concordance_cols$pfu_code,
country_concordance_cols$iea_name))
usethis::use_data(override_iso_codes_df, overwrite = TRUE)
#
# Give names for matrix meta information columns
#
mat_meta_cols <- list(matnames = "matnames",
matvals = "matvals",
rownames = "rownames",
colnames = "colnames",
rowtypes = "rowtypes",
coltypes = "coltypes")
usethis::use_data(mat_meta_cols, overwrite = TRUE)
#
# Give names for PSUT meta information columns
#
sut_meta_cols <- list(country = iea_cols$country,
method = iea_cols$method,
energy_type = iea_cols$energy_type,
last_stage = iea_cols$last_stage,
year = iea_cols$year)
usethis::use_data(sut_meta_cols, overwrite = TRUE)
#
# Give the column names of data frames with PSUT data
#
psut_cols <- list(resources = "R",
R = "R",
use = "U",
U = "U",
U_feed = "U_feed",
U_eiou = "U_EIOU",
r_eiou = "r_EIOU",
make = "V",
V = "V",
final_demand = "Y",
Y = "Y",
B = "B",
s_units = "S_units",
matvals = "matvals",
Y_fu_details = "Y_fu_details",
U_eiou_fu_details = "U_EIOU_fu_details")
usethis::use_data(psut_cols, overwrite = TRUE)
#
# Give names of columns in FU allocation and eta_fu templates
#
template_cols <- list(ef_product = "Ef.product",
machine = "Machine",
eu_product = "Eu.product",
destination = "Destination",
quantity = "Quantity",
maximum_values = "Maximum.values",
C_eiou = "C_EIOU",
C_Y = "C_Y",
C_perc = "C.perc [%]",
e_dot_max = "E.dot_max",
e_dot_perc = "E.dot [%]",
e_dot_dest = "E.dot_dest",
e_dot_machine = "E.dot_machine",
e_dot_machine_tot = "E.dot_machine_tot",
e_dot_machine_perc = "E.dot_machine [%]",
e_dot_machine_max_perc = "E.dot_machine_max [%]",
eta_fu = "eta.fu",
phi_pf = "phi.pf",
phi_u = "phi.u",
phi = "phi",
c_source = "C.source",
eta_fu_source = "eta.fu.source",
phi_source = "phi.source",
.values = ".values")
usethis::use_data(template_cols, overwrite = TRUE)
#
# FU analysis file information
#
fu_analysis_file_info <- list(fu_analysis_file_suffix = " FU Analysis.xlsx",
fu_allocation_tab_name = "FU Allocations",
eta_fu_tab_name = "FU etas")
usethis::use_data(fu_analysis_file_info, overwrite = TRUE)
#
# Give row and column types
#
row_col_types <- list(industry = "Industry",
resource = "Industry",
sector = "Industry",
product = "Product",
unit = "Unit")
usethis::use_data(row_col_types, overwrite = TRUE)
#
# Coal and coal products
#
primary_coal_products <- list(hard_coal_if_no_detail = "Hard coal (if no detail)",
brown_coal_if_no_detail = "Brown coal (if no detail)",
anthracite = "Anthracite",
coking_coal = "Coking coal",
other_bituminous_coal = "Other bituminous coal",
sub_bituminous_coal = "Sub-bituminous coal",
lignite = "Lignite")
usethis::use_data(primary_coal_products, overwrite = TRUE)
coal_and_coal_products <- list(primary_coal_products,
patent_fuel = "Patent fuel",
coke_oven_coke = "Coke oven coke",
gas_coke = "Gas coke",
coal_tar = "Coal tar",
bkb = "BKB",
gas_works_gas = "Gas works gas",
coke_oven_gas = "Coke oven gas",
blast_furnace_gas = "Blast furnace gas",
other_recovered_gases = "Other recovered gases") %>%
unlist() %>%
as.list()
usethis::use_data(coal_and_coal_products, overwrite = TRUE)
secondary_coal_products <- setdiff(coal_and_coal_products, primary_coal_products) %>%
unlist() %>%
as.list()
usethis::use_data(secondary_coal_products, overwrite = TRUE)
#
# Peat and peat products
#
primary_peat_products <- list(peat = "Peat")
usethis::use_data(primary_peat_products, overwrite = TRUE)
peat_and_peat_products <- list(primary_peat_products,
peat_products = "Peat products") %>%
unlist() %>%
as.list()
usethis::use_data(peat_and_peat_products, overwrite = TRUE)
secondary_peat_products <- setdiff(peat_and_peat_products, primary_peat_products) %>%
unlist() %>%
as.list()
usethis::use_data(secondary_peat_products, overwrite = TRUE)
#
# Oil and oil products
#
primary_oil_products <- list(crude_ngl_feedstocks_if_no_detail = "Crude/NGL/feedstocks (if no detail)",
crude_oil = "Crude oil",
natural_gas_liquids = "Natural gas liquids",
additives_blending_components = "Additives/blending components",
other_hydrocarbons = "Other hydrocarbons",
oil_shales_and_oil_sands = "Oil shale and oil sands")
usethis::use_data(primary_oil_products, overwrite = TRUE)
oil_and_oil_products <- list(primary_oil_products,
refinery_feedstocks = "Refinery feedstocks",
refinery_gas = "Refinery gas",
ethane = "Ethane",
liquefied_petroleum_gases_lpg = "Liquefied petroleum gases (LPG)",
motor_gasoline_excl_biofuels = "Motor gasoline excl. biofuels",
aviation_gasoline = "Aviation gasoline",
gasoline_type_jet_fuel = "Gasoline type jet fuel",
kerosene_type_jet_fuel_excl_biofuels = "Kerosene type jet fuel excl. biofuels",
other_kerosene = "Other kerosene",
gas_diesel_oil_excl_biofuels = "Gas/diesel oil excl. biofuels",
fuel_oil = "Fuel oil",
naptha = "Naphtha",
white_spirit_SBP = "White spirit & SBP",
lubricants = "Lubricants",
bitumen = "Bitumen",
paraffin_waxes = "Paraffin waxes",
petroleum_coke = "Petroleum coke",
other_oil_products = "Other oil products") %>%
unlist(recursive = TRUE) %>%
as.list()
usethis::use_data(oil_and_oil_products, overwrite = TRUE)
secondary_oil_products <- setdiff(oil_and_oil_products, primary_oil_products) %>%
unlist() %>%
as.list()
usethis::use_data(secondary_oil_products, overwrite = TRUE)
#
# Natural gas
#
primary_gas_products <- list(natural_gas = "Natural gas") %>%
unlist() %>%
as.list()
usethis::use_data(primary_gas_products, overwrite = TRUE)
#
# Renewables
#
renewable_products <- list(geothermal = "Geothermal",
hydro = "Hydro",
solar_photovoltaics = "Solar photovoltaics",
solar_thermal = "Solar thermal",
tide_wave_and_ocean = "Tide, wave and ocean",
wind = "Wind",
other_sources = "Other sources")
usethis::use_data(renewable_products, overwrite = TRUE)
#
# Biofuels
#
biofuels_and_waste_products <- list(industrial_waste = "Industrial waste",
municipal_waste_renewable = "Municipal waste (renewable)",
municipal_waste_nonrenewable = "Municipal waste (non-renewable)",
primary_solid_biofuels = "Primary solid biofuels",
biogases = "Biogases",
biogasoline = "Biogasoline",
biodiesels = "Biodiesels",
bio_jet_kerosene = "Bio jet kerosene",
other_liquid_biofuels = "Other liquid biofuels",
non_specified_primary_biofuels_and_waste = "Non-specified primary biofuels and waste",
charcoal = "Charcoal")
usethis::use_data(biofuels_and_waste_products, overwrite = TRUE)
#
# Electricity
#
electricity_products <- list(electricity = "Electricity")
usethis::use_data(electricity_products, overwrite = TRUE)
#
# Non-energy
#
nonenergy_products <- list(additives_blending_components = "Additives/blending components",
bitumen = "Bitumen",
lubricants = "Lubricants",
naphtha = "Naphtha",
paraffin_waxes = "Paraffin waxes",
refinery_feedstocks = "Refinery feedstocks",
white_spirit_and_sbp = "White spirit & SBP"
# The following products were removed from the
# nonenergy_products constant by MKH on 3 Nov 2023
# after extensive discussion among
# PB, EA, and MKH.
# The decision was made to follow the IEA directly.
# The IEA does not consider the following products
# to be NEU, so we do the same.
# We will now be allocating these products correctly
# in Country-specific (and WRLD) allocation
# spreadsheets.
# coal_tar = "Coal tar",
# crude_ngl_feedstocks_if_no_detail = "Crude/NGL/feedstocks (if no detail)",
# crude_oil = "Crude oil",
# natural_gas_liquids = "Natural gas liquids",
# oil_shale_and_oil_sands = "Oil shale and oil sands",
# other_hydrocarbons = "Other hydrocarbons",
# other_oil_products = "Other oil products"
)
usethis::use_data(nonenergy_products, overwrite = TRUE)
#
# Flow types
#
tpes_flows <- list(resources = "Resources",
production = "Production",
imports = "Imports",
exports = "Exports",
international_marine_bunkers = "International marine bunkers",
international_aviation_bunkers = "International aviation bunkers",
# Added new "exports_to_" tpes flows on 15 July 2021 as part of treating
# World bunkers correctly.
# These new flows will ultimately replace
# international_marine_bunkers and international_aviation_bunkers
# after all IEA data are specified.
exports_to_world_marine_bunkers = "Exports to World marine bunkers",
exports_to_world_aviation_bunkers = "Exports to World aviation bunkers",
stock_changes = "Stock changes")
usethis::use_data(tpes_flows, overwrite = TRUE)
#
# Primary energy flows used to calculate domestic primary energy consumption using
# Recca::primary_aggregates()
#
prim_agg_flows <- tpes_flows
prim_agg_flows <- prim_agg_flows[!(prim_agg_flows %in% c(tpes_flows$production,
tpes_flows$exports,
tpes_flows$international_marine_bunkers,
tpes_flows$international_aviation_bunkers,
tpes_flows$exports_to_world_marine_bunkers,
tpes_flows$exports_to_world_aviation_bunkers
))]
usethis::use_data(prim_agg_flows, overwrite = TRUE)
tfc_compare_flows <- list(total_primary_energy_supply = "Total primary energy supply",
total_energy_supply = "Total energy supply",
transfers = "Transfers",
statistical_differences = "Statistical differences",
transformation_processes = "Transformation processes",
energy_industry_own_use = "Energy industry own use",
losses = "Losses")
usethis::use_data(tfc_compare_flows, overwrite = TRUE)
transformation_processes <- list(main_activity_producer_electricity_plants = "Main activity producer electricity plants",
autoproducer_electricity_plants = "Autoproducer electricity plants",
main_activity_producer_CHP_plants = "Main activity producer CHP plants",
autoproducer_CHP_plants = "Autoproducer CHP plants",
main_activity_producer_heat_plants = "Main activity producer heat plants",
autoproducer_heat_plants = "Autoproducer heat plants",
heat_pumps = "Heat pumps",
electric_boilers = "Electric boilers",
chemical_heat_for_electricity_production = "Chemical heat for electricity production",
blast_furnaces = "Blast furnaces",
gas_works = "Gas works",
coke_ovens = "Coke ovens",
patent_fuel_plants = "Patent fuel plants",
bkb_peat_briquette_plants = "BKB/peat briquette plants",
oil_refineries = "Oil refineries",
petrochemical_plants = "Petrochemical plants",
coal_liquefaction_plants = "Coal liquefaction plants",
gas_to_liquid_gtl_plants = "Gas-to-liquids (GTL) plants",
for_blended_natural_gas = "For blended natural gas",
charcoal_production_plants = "Charcoal production plants",
nuclear_indsutry = "Nuclear industry",
non_specified_transformation = "Non-specified (transformation)",
# 2019
non_specified_energy = "Non-specified (energy)")
usethis::use_data(transformation_processes, overwrite = TRUE)
main_act_plants <- list(main_act_prod_elect_plants = "Main activity producer electricity plants",
main_act_prod_chp_plants = "Main activity producer CHP plants",
main_act_prod_heat_plants = "Main activity producer heat plants",
autoprod_elect_plants = "Autoproducer electricity plants",
autoprod_heat_plants = "Autoproducer heat plants",
autoprod_chp_plants = "Autoproducer CHP plants")
usethis::use_data(main_act_plants, overwrite = TRUE)
eiou_flows <- list(bkb_peat_briquette_plants = "BKB/peat briquette plants",
blast_furnaces = "Blast furnaces",
charcoal_plants = "Charcoal production plants",
coal_liquefaction_plants = "Coal liquefaction plants",
coal_mines = "Coal mines",
coke_ovens = "Coke ovens",
gas_works = "Gas works",
gas_to_liquids_plants = "Gas-to-liquids (GTL) plants",
gasification_plants = "Gasification plants for biogases",
liquefaction_regasification_plants = "Liquefaction (LNG) / regasification plants",
non_specified_eiou = "Non-specified (energy)",
nuclear_industry = "Nuclear industry",
oil_and_gas_extraction = "Oil and gas extraction",
# "Oil and gas extraction" is split in the specification process.
# So we need "Oil extraction" and "Natural gas extraction".
oil_extraction = "Oil extraction",
natural_gas_extraction = "Natural gas extraction",
oil_refineries = "Oil refineries",
own_use_elect_chp_heat_plants = "Own use in electricity, CHP and heat plants",
# In the specification process,
# we route "Own use in electricity, CHP and heat plants" to
# main activity plants for electricity, CHP, and heat.
# So we need to include those plants here.
main_activity_producer_electricity_plants = "Main activity producer electricity plants",
main_activity_producer_chp_plants = "Main activity producer CHP plants",
main_activity_producer_heat_plants = "Main activity producer heat plants",
patent_fuel_plants = "Patent fuel plants",
pumped_storage_plants = "Pumped storage plants")
usethis::use_data(eiou_flows, overwrite = TRUE)
tfc_flows <- list(industry = "Industry",
transport = "Transport",
other = "Other",
non_energy_use = "Non-energy use")
usethis::use_data(tfc_flows, overwrite = TRUE)
manufacturing_flows <- list(iron_and_steel = "Iron and steel",
chemical_and_petrochemical = "Chemical and petrochemical",
non_ferrous_metals = "Non-ferrous metals",
non_metallic_minerals = "Non-metallic minerals",
transport_equipment = "Transport equipment",
machinery = "Machinery",
food_and_tobacco = "Food and tobacco",
# 2018
paper_pulp_and_print = "Paper, pulp and print",
# 2019
paper_pulp_and_printing = "Paper, pulp and printing",
wood_and_wood_products = "Wood and wood products",
textile_and_leather = "Textile and leather")
usethis::use_data(manufacturing_flows, overwrite = TRUE)
industry_flows <- list(mining_and_quarrying = "Mining and quarrying",
construction = "Construction",
manufacturing = "Manufacturing",
manufacturing_flows,
# 2018
non_specified_industry = "Non-specified (industry)",
# 2019
industry_not_elsewhere_specified = "Industry not elsewhere specified",
# Extra flows that arise after specification
coal_mines = "Coal mines",
oil_and_gas_extraction = "Oil and gas extraction",
oil_extraction = "Oil extraction",
natural_gas_extraction = "Natural gas extraction") %>%
unlist() %>%
as.list()
usethis::use_data(industry_flows, overwrite = TRUE)
# A constant containing non-eiou industry flows
industry_net_flows <- industry_flows[!(industry_flows %in% c("Coal mines", "Oil and gas extraction"))]
usethis::use_data(industry_net_flows, overwrite = TRUE)
transport_flows <- list(domestic_navigation = "Domestic navigation",
world_marine_bunkers = "World marine bunkers",
international_navigation = "International navigation",
domestic_aviation = "Domestic aviation",
world_aviation_bunkers = "World aviation bunkers",
international_aviation = "International aviation",
road = "Road",
rail = "Rail",
pipeline_transport = "Pipeline transport",
# 2019
non_specified_transport = "Non-specified (transport)",
# 2020
transport_not_elsewhere_specified = "Transport not elsewhere specified")
usethis::use_data(transport_flows, overwrite = TRUE)
# A constant containing domestic transport flows. This constant is the same as
# transport flows except it does not contain "World marine bunkers" or
# "World aviation bunkers"
transport_domestic_flows <- transport_flows[!(transport_flows %in% c(tpes_flows$world_aviation_bunkers,
tpes_flows$world_marine_bunkers))]
usethis::use_data(transport_domestic_flows, overwrite = TRUE)
other_flows <- list(residential = "Residential",
commercial_and_public_services = "Commercial and public services",
agriculture_forestry = "Agriculture/forestry",
fishing = "Fishing",
# 2018
non_specified_other = "Non-specified (other)",
# 2019
final_consumption_not_elsewhere_specified = "Final consumption not elsewhere specified")
usethis::use_data(other_flows, overwrite = TRUE)
non_energy_flows <- list(non_energy_use_industry_transformation_energy = "Non-energy use industry/transformation/energy",
non_energy_use_in_transport = "Non-energy use in transport",
non_energy_use_in_other = "Non-energy use in other")
usethis::use_data(non_energy_flows, overwrite = TRUE)
#
# Memo: Non-energy use in xxxxxx flows
#
memo_non_energy_flows <- list(memo_non_energy_use_in_industry = "Memo: Non-energy use in industry",
memo_non_energy_use_in_construction = "Memo: Non-energy use in construction",
memo_non_energy_use_in_mining_quarrying = "Memo: Non-energy use in mining and quarrying",
memo_non_energy_use_in_iron_steel = "Memo: Non-energy use in iron and steel",
memo_non_energy_use_in_chemical_petrochemical = "Memo: Non-energy use in chemical/petrochemical",
memo_non_energy_use_in_non_ferrous_metals = "Memo: Non-energy use in non-ferrous metals",
memo_non_energy_use_in_non_metallic_minerals = "Memo: Non-energy use in non-metallic minerals",
memo_non_energy_use_in_transport_equipment = "Memo: Non-energy use in transport equipment",
memo_non_energy_use_in_machinery = "Memo: Non-energy use in machinery",
memo_non_energy_use_in_food_beverages_tobacco = "Memo: Non-energy use in food/beverages/tobacco",
memo_non_energy_use_in_paper_pulp_printing = "Memo: Non-energy use in paper/pulp and printing",
memo_non_energy_use_in_wood_and_wood_products = "Memo: Non-energy use in wood and wood products",
memo_non_energy_use_in_textiles_leather = "Memo: Non-energy use in textiles and leather",
memo_non_energy_use_in_industry_not_elsewhere_specified = "Memo: Non-energy use in industry not elsewhere specified")
usethis::use_data(memo_non_energy_flows, overwrite = TRUE)
#
# Aggregations
#
aggregation_flows <- list(total_primary_energy_supply = tfc_compare_flows$total_primary_energy_supply,
# In 2020, IEA changed the name of TPES to TES.
total_energy_supply = tfc_compare_flows$total_energy_supply,
total_final_consumption = "Total final consumption",
transformation_processes = "Transformation processes",
energy_industry_own_use = "Energy industry own use",
tfc_compare = "TFC compare",
industry = "Industry",
manufacturing = "Manufacturing",
transport = "Transport",
other = "Other",
non_energy_use = "Non-energy use")
usethis::use_data(aggregation_flows, overwrite = TRUE)
#
# Default names for columns in aggregate data frames
#
aggregate_cols <- list(aggregate_primary = "EX.p",
aggregate_final = "EX.f",
aggregate_useful = "EX.u",
net_aggregate_demand = "EX.fd_net",
gross_aggregate_demand = "EX.fd_gross")
usethis::use_data(aggregate_cols, overwrite = TRUE)
memo_aggregation_flow_prefixes <- list(memo = "Memo: ",
electricity_output_GWh = "Electricity output (GWh)",
heat_output = "Heat output")
usethis::use_data(memo_aggregation_flow_prefixes, overwrite = TRUE)
memo_aggregation_product_prefixes <- list(memo = "Memo: ",
total = "Total")
usethis::use_data(memo_aggregation_product_prefixes, overwrite = TRUE)
#
# Interfaces
#
interface_industries <- list(imports = tpes_flows$imports,
exports = tpes_flows$exports,
international_aviation_bunkers = tpes_flows$international_aviation_bunkers,
international_marine_bunkers = tpes_flows$international_marine_bunkers,
exports_to_world_aviation_bunkers = tpes_flows$exports_to_world_aviation_bunkers,
exports_to_world_marine_bunkers = tpes_flows$exports_to_world_marine_bunkers,
stock_changes = tpes_flows$stock_changes)
usethis::use_data(interface_industries, overwrite = TRUE)
#
# Aggregation regions
#
# Note: Greenland, Palestinian Authority, and Uganda are NOT
# aggregation regions.
#
aggregation_regions <- list(world = "World",
oecd_americas = "OECD Americas",
oecd_asia_oceana = "OECD Asia Oceania",
oecd_europe = "OECD Europe",
africa = "Africa",
non_oecd_americas = "Non-OECD Americas",
non_oecd_asia_excluding_china = "Non-OECD Asia (excluding China)",
middle_east = "Middle East",
non_oecd_europe_and_eurasia = "Non-OECD Europe and Eurasia",
memo_equatirlai_guinea = "Memo: Equatorial Guinea",
# memo_greenland = "Memo: Greenland",
memo_lao_peoples_democratic_republic = "Memo: Lao People's Democratic Republic",
memo_mali = "Memo: Mali",
# memo_palestinian_authority = "Memo: Palestinian Authority",
memo_uganda = "Memo: Uganda",
memo_africa_un = "Memo: Africa (UN)",
memo_americas_un = "Memo: Americas (UN)",
memo_asia_un = "Memo: Asia (UN)",
memo_europe_un = "Memo: Europe (UN)",
memo_oceania_un = "Memo: Oceania (UN)",
memo_oecd_total = "Memo: OECD Total",
memo_non_oecd_total = "Memo: Non-OECD Total",
memo_iea_total = "Memo: IEA Total",
memo_iea_and_accession_association_countries = "Memo: IEA and Accession/Association countries",
memo_european_union_28 = "Memo: European Union-28",
memo_fsu_15 = "Memo: FSU 15",
memo_former_yugoslavia = "Memo: Former Yugoslavia",
memo_opec = "Memo: OPEC",
memo_asean = "Memo: ASEAN",
memo_g7 = "Memo: G7",
memo_g8 = "Memo: G8",
memo_g20 = "Memo: G20",
memo_china_pr_of_china_and_hong_kong_china = "China (P.R. of China and Hong Kong, China)"
# As of 14 July 2021, we are treating
# these bunkers as their own country,
# so they should no longer be listed as an aggregation region.
# world_aviation_bunkers = "World aviation bunkers",
# world_marine_bunkers = "World marine bunkers"
)
usethis::use_data(aggregation_regions, overwrite = TRUE)
#
# Sort orders
#
# We want to replace this code with other code to read a concordance table
# for country names.
# ---MKH, 20 July 2021
countries <- countrycode::codelist %>%
dplyr::select(iso3c) %>%
dplyr::filter(!is.na(iso3c)) %>%
unlist() %>%
unname()
countries <- append(countries, c("WAB", "WMB"))
usethis::use_data(countries, overwrite = TRUE)
# See
# T. Sousa, P. E. Brockway, J. M. Cullen, S. T. Henriques, J. Miller, A. C. Serrenho, and T. Domingos.
# The need for robust, consistent methods in societal exergy accounting. Ecological Economics, 141:11–21, Nov 2017.
# for details
methods <- list(pcm = "PCM", # Physical content method (used by IEA)
rcm = "RCM", # Resource content method
psm = "PSM") # Partial substitution method (used by EIA and BP)
usethis::use_data(methods, overwrite = TRUE)
energy_types <- list(e = "E", # Energy
x = "X") # Exergy
usethis::use_data(energy_types, overwrite = TRUE)
all_stages <- list(primary = "Primary",
final = "Final",
useful = "Useful",
services = "Services")
usethis::use_data(all_stages, overwrite = TRUE)
last_stages <- all_stages
last_stages$primary <- NULL
usethis::use_data(last_stages, overwrite = TRUE)
ledger_sides <- list(supply = "Supply",
consumption = "Consumption")
usethis::use_data(ledger_sides, overwrite = TRUE)
# Defining the row order for IEA-style data frames is tricky and requires some manual intervention.
# In the first step, we use the data frame created from load_tidy_iea_df,
# creating a united column from Flow.aggregation.point and Flow.
fap_flows <- load_tidy_iea_df(remove_zeroes = FALSE) %>%
tidyr::unite(col = Flow.aggregation.point_Flow, Flow.aggregation.point, Flow, sep = "_", remove = TRUE) %>%
dplyr::select(Flow.aggregation.point_Flow) %>%
unique() %>%
unlist() %>%
unname() %>%
# Then we insert a few items manually.
# Coal mines and Oil and gas extraction are created in specify_primary_production().
insert_after(after = "Total primary energy supply_Production",
values = c("Total primary energy supply_Coal mines", "Total primary energy supply_Oil and gas extraction")) %>%
# We we have Resources, Coal mines and Oil and gas extraction are Transformation processes.
# Add entries for those, too.
insert_after(after = "TFC compare_Statistical differences",
values = c("Transformation processes_Coal mines", "Transformation processes_Oil and gas extraction")) %>%
# Inserting Nuclear industry as a transformation process
insert_after(after = "Transformation processes_Oil and gas extraction",
values = "Transformation processes_Nuclear industry") %>%
# Energy industry own use_Own use in electricity, CHP and heat plants,
# Pumped storage plants, and Nuclear industry is reassigned to Main activity producer electricity plants in specify_tp_eiou()
insert_after(after = "Energy industry own use_Nuclear industry",
values = "Energy industry own use_Main activity producer electricity plants") %>%
# Inserting Main activity producer CHP plants and Main activity producer heat plants as EIOU flows
insert_after(after = "Energy industry own use_Main activity producer electricity plants",
values = c("Energy industry own use_Main activity producer CHP plants", "Energy industry own use_Main activity producer heat plants")) %>%
insert_after(after = "Energy industry own use_Main activity producer heat plants",
values = c("Energy industry own use_Oil extraction", "Energy industry own use_Natural gas extraction")) %>%
# Add combinations for international bunkers.
insert_after(after = "Transport_Domestic navigation",
values = "Transport_International navigation") %>%
insert_after(after = "Transport_Domestic aviation",
values = "Transport_International aviation") %>%
# Pick up several "not elsewhere specified" flows.
# These enable sorting for years besides the latest year.
insert_after(after = "Transport_Transport not elsewhere specified",
values = "Transport_Non-specified (transport)") %>%
insert_after(after = "Industry_Industry not elsewhere specified",
values = "Industry_Non-specified (industry)") |>
# Insert several specific non-energy use flows.
# These flows are used when we specify Non-energy use flows by industry (where available).
insert_after(after = "Non-energy use_Non-energy use industry/transformation/energy",
values = c("Non-energy use_Non-energy use in construction",
"Non-energy use_Non-energy use in mining and quarrying",
"Non-energy use_Non-energy use in iron and steel",
"Non-energy use_Non-energy use in chemical/petrochemical",
"Non-energy use_Non-energy use in non-ferrous metals",
"Non-energy use_Non-energy use in non-metallic minerals",
"Non-energy use_Non-energy use in transport equipment",
"Non-energy use_Non-energy use in machinery",
"Non-energy use_Non-energy use in food/beverages/tobacco",
"Non-energy use_Non-energy use in paper/pulp and printing",
"Non-energy use_Non-energy use in wood and wood products",
"Non-energy use_Non-energy use in textiles and leather",
"Non-energy use_Non-energy use in industry not elsewhere specified"))
usethis::use_data(fap_flows, overwrite = TRUE)
products <- load_tidy_iea_df(remove_zeroes = FALSE) %>%
dplyr::select(Product) %>%
unique() %>%
unlist() %>%
unname() %>%
# Insert a few items manually.
# In specify_primary_production(), some Products are renamed to account for the fact that they come from a different industry.
insert_after(after = primary_coal_products[length(primary_coal_products)],
# values = paste0(primary_coal_products, from_notation[["suff_start"]], "Coal mines", from_notation[["suff_end"]])) %>%
values = RCLabels::paste_pref_suff(pref = primary_coal_products, suff = "Coal mines", notation = RCLabels::bracket_notation)) %>%
insert_after(after = primary_oil_products[length(primary_oil_products)],
# values = paste0(primary_oil_products, from_notation[["suff_start"]], "Oil and gas extraction", from_notation[["suff_end"]])) %>%
values = RCLabels::paste_pref_suff(pref = primary_oil_products, suff = "Oil and gas extraction", notation = RCLabels::bracket_notation)) %>%
insert_after(after = "Natural gas",
# values = paste0("Natural gas", from_notation[["suff_start"]], "Oil and gas extraction", from_notation[["suff_end"]]))
values = RCLabels::paste_pref_suff(pref = "Natural gas", suff = "Oil and gas extraction", notation = RCLabels::bracket_notation))
usethis::use_data(products, overwrite = TRUE)
#
# Pull the non-specified flows together
#
non_specified_flows <- list(non_specified_transformation = transformation_processes$non_specified_transformation,
non_specified_energy = "Non-specified (energy)",
non_specified_transport = transport_flows$non_specified_transport,
# 2018
non_specified_industry = industry_flows$non_specified_industry,
# 2019
industry_not_elsewhere_specified = industry_flows$industry_not_elsewhere_specified,
non_specified = "Non-specified",
# 2020
non_specified_transport = transport_flows$transport_not_elsewhere_specified)
usethis::use_data(non_specified_flows, overwrite = TRUE)
#
# Final demand sectors for use by Recca::finaldemand_aggregates()
#
fd_sectors <- c(eiou_flows,
industry_net_flows,
transport_domestic_flows,
other_flows,
non_energy_flows,
gsub(memo_aggregation_flow_prefixes$memo, "", memo_non_energy_flows))
usethis::use_data(fd_sectors, overwrite = TRUE)
#
# Names and constants associated with constant phi value tables.
#
phi_constants_names <- list(phi_constants_tab_name = "phi_constants",
product_colname = "Product",
phi_colname = "phi",
phi_source_colname = "phi.source",
is_useful_colname = "is.useful")
usethis::use_data(phi_constants_names, overwrite = TRUE)
MatthewHeun/IEATools documentation built on Feb. 6, 2024, 3:29 p.m.
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# This script creates constants and saves them in the right locations.
# If there are any changes to these constants,
# source this script before building the package.
library(magrittr)
library(IEATools)
#
# Define the valid IEA release years for which this package will work
#
valid_iea_release_years <- c(2021, 2022)
usethis::use_data(valid_iea_release_years, overwrite = TRUE)
#
# Give the column names of IEA data frames in typical left-to-right order.
#
iea_cols <- list(country = "Country",
method = "Method",
energy_type = "Energy.type",
last_stage = "Last.stage",
year = "Year",
ledger_side = "Ledger.side",
flow_aggregation_point = "Flow.aggregation.point",
flow = "Flow",
product = "Product",
unit = "Unit",
e_dot = "E.dot")
usethis::use_data(iea_cols, overwrite = TRUE)
#
# Country concordance table columns
#
country_concordance_cols <- list(pfu_code = "PFU.code",
iea_name = "IEA.name")
usethis::use_data(country_concordance_cols, overwrite = TRUE)
#
# Default override data frame for 3-letter country codes.
# This constant is used in the use_iso_countries() function.
# The second column is the name in the IEA extended energy balance database.
# The first column is the 3-letter code we will use in the PFU database.
# This data frame is how we handle non-standard country names
# as well as IEA-only countries and aggregations.
#
override_iso_codes_df <- tibble::tribble(
~a, ~b,
"WRLD", "World",
"CHNM", "People's Republic of China",
"HKG", "Hong Kong (China)",
"SUN", "Former Soviet Union (if no detail)",
"WMBK", "World marine bunkers",
"WABK", "World aviation bunkers",
"YUG", "Former Yugoslavia (if no detail)") %>%
magrittr::set_names(c(country_concordance_cols$pfu_code,
country_concordance_cols$iea_name))
usethis::use_data(override_iso_codes_df, overwrite = TRUE)
#
# Give names for matrix meta information columns
#
mat_meta_cols <- list(matnames = "matnames",
matvals = "matvals",
rownames = "rownames",
colnames = "colnames",
rowtypes = "rowtypes",
coltypes = "coltypes")
usethis::use_data(mat_meta_cols, overwrite = TRUE)
#
# Give names for PSUT meta information columns
#
sut_meta_cols <- list(country = iea_cols$country,
method = iea_cols$method,
energy_type = iea_cols$energy_type,
last_stage = iea_cols$last_stage,
year = iea_cols$year)
usethis::use_data(sut_meta_cols, overwrite = TRUE)
#
# Give the column names of data frames with PSUT data
#
psut_cols <- list(resources = "R",
R = "R",
use = "U",
U = "U",
U_feed = "U_feed",
U_eiou = "U_EIOU",
r_eiou = "r_EIOU",
make = "V",
V = "V",
final_demand = "Y",
Y = "Y",
B = "B",
s_units = "S_units",
matvals = "matvals",
Y_fu_details = "Y_fu_details",
U_eiou_fu_details = "U_EIOU_fu_details")
usethis::use_data(psut_cols, overwrite = TRUE)
#
# Give names of columns in FU allocation and eta_fu templates
#
template_cols <- list(ef_product = "Ef.product",
machine = "Machine",
eu_product = "Eu.product",
destination = "Destination",
quantity = "Quantity",
maximum_values = "Maximum.values",
C_eiou = "C_EIOU",
C_Y = "C_Y",
C_perc = "C.perc [%]",
e_dot_max = "E.dot_max",
e_dot_perc = "E.dot [%]",
e_dot_dest = "E.dot_dest",
e_dot_machine = "E.dot_machine",
e_dot_machine_tot = "E.dot_machine_tot",
e_dot_machine_perc = "E.dot_machine [%]",
e_dot_machine_max_perc = "E.dot_machine_max [%]",
eta_fu = "eta.fu",
phi_pf = "phi.pf",
phi_u = "phi.u",
phi = "phi",
c_source = "C.source",
eta_fu_source = "eta.fu.source",
phi_source = "phi.source",
.values = ".values")
usethis::use_data(template_cols, overwrite = TRUE)
#
# FU analysis file information
#
fu_analysis_file_info <- list(fu_analysis_file_suffix = " FU Analysis.xlsx",
fu_allocation_tab_name = "FU Allocations",
eta_fu_tab_name = "FU etas")
usethis::use_data(fu_analysis_file_info, overwrite = TRUE)
#
# Give row and column types
#
row_col_types <- list(industry = "Industry",
resource = "Industry",
sector = "Industry",
product = "Product",
unit = "Unit")
usethis::use_data(row_col_types, overwrite = TRUE)
#
# Coal and coal products
#
primary_coal_products <- list(hard_coal_if_no_detail = "Hard coal (if no detail)",
brown_coal_if_no_detail = "Brown coal (if no detail)",
anthracite = "Anthracite",
coking_coal = "Coking coal",
other_bituminous_coal = "Other bituminous coal",
sub_bituminous_coal = "Sub-bituminous coal",
lignite = "Lignite")
usethis::use_data(primary_coal_products, overwrite = TRUE)
coal_and_coal_products <- list(primary_coal_products,
patent_fuel = "Patent fuel",
coke_oven_coke = "Coke oven coke",
gas_coke = "Gas coke",
coal_tar = "Coal tar",
bkb = "BKB",
gas_works_gas = "Gas works gas",
coke_oven_gas = "Coke oven gas",
blast_furnace_gas = "Blast furnace gas",
other_recovered_gases = "Other recovered gases") %>%
unlist() %>%
as.list()
usethis::use_data(coal_and_coal_products, overwrite = TRUE)
secondary_coal_products <- setdiff(coal_and_coal_products, primary_coal_products) %>%
unlist() %>%
as.list()
usethis::use_data(secondary_coal_products, overwrite = TRUE)
#
# Peat and peat products
#
primary_peat_products <- list(peat = "Peat")
usethis::use_data(primary_peat_products, overwrite = TRUE)
peat_and_peat_products <- list(primary_peat_products,
peat_products = "Peat products") %>%
unlist() %>%
as.list()
usethis::use_data(peat_and_peat_products, overwrite = TRUE)
secondary_peat_products <- setdiff(peat_and_peat_products, primary_peat_products) %>%
unlist() %>%
as.list()
usethis::use_data(secondary_peat_products, overwrite = TRUE)
#
# Oil and oil products
#
primary_oil_products <- list(crude_ngl_feedstocks_if_no_detail = "Crude/NGL/feedstocks (if no detail)",
crude_oil = "Crude oil",
natural_gas_liquids = "Natural gas liquids",
additives_blending_components = "Additives/blending components",
other_hydrocarbons = "Other hydrocarbons",
oil_shales_and_oil_sands = "Oil shale and oil sands")
usethis::use_data(primary_oil_products, overwrite = TRUE)
oil_and_oil_products <- list(primary_oil_products,
refinery_feedstocks = "Refinery feedstocks",
refinery_gas = "Refinery gas",
ethane = "Ethane",
liquefied_petroleum_gases_lpg = "Liquefied petroleum gases (LPG)",
motor_gasoline_excl_biofuels = "Motor gasoline excl. biofuels",
aviation_gasoline = "Aviation gasoline",
gasoline_type_jet_fuel = "Gasoline type jet fuel",
kerosene_type_jet_fuel_excl_biofuels = "Kerosene type jet fuel excl. biofuels",
other_kerosene = "Other kerosene",
gas_diesel_oil_excl_biofuels = "Gas/diesel oil excl. biofuels",
fuel_oil = "Fuel oil",
naptha = "Naphtha",
white_spirit_SBP = "White spirit & SBP",
lubricants = "Lubricants",
bitumen = "Bitumen",
paraffin_waxes = "Paraffin waxes",
petroleum_coke = "Petroleum coke",
other_oil_products = "Other oil products") %>%
unlist(recursive = TRUE) %>%
as.list()
usethis::use_data(oil_and_oil_products, overwrite = TRUE)
secondary_oil_products <- setdiff(oil_and_oil_products, primary_oil_products) %>%
unlist() %>%
as.list()
usethis::use_data(secondary_oil_products, overwrite = TRUE)
#
# Natural gas
#
primary_gas_products <- list(natural_gas = "Natural gas") %>%
unlist() %>%
as.list()
usethis::use_data(primary_gas_products, overwrite = TRUE)
#
# Renewables
#
renewable_products <- list(geothermal = "Geothermal",
hydro = "Hydro",
solar_photovoltaics = "Solar photovoltaics",
solar_thermal = "Solar thermal",
tide_wave_and_ocean = "Tide, wave and ocean",
wind = "Wind",
other_sources = "Other sources")
usethis::use_data(renewable_products, overwrite = TRUE)
#
# Biofuels
#
biofuels_and_waste_products <- list(industrial_waste = "Industrial waste",
municipal_waste_renewable = "Municipal waste (renewable)",
municipal_waste_nonrenewable = "Municipal waste (non-renewable)",
primary_solid_biofuels = "Primary solid biofuels",
biogases = "Biogases",
biogasoline = "Biogasoline",
biodiesels = "Biodiesels",
bio_jet_kerosene = "Bio jet kerosene",
other_liquid_biofuels = "Other liquid biofuels",
non_specified_primary_biofuels_and_waste = "Non-specified primary biofuels and waste",
charcoal = "Charcoal")
usethis::use_data(biofuels_and_waste_products, overwrite = TRUE)
#
# Electricity
#
electricity_products <- list(electricity = "Electricity")
usethis::use_data(electricity_products, overwrite = TRUE)
#
# Non-energy
#
nonenergy_products <- list(additives_blending_components = "Additives/blending components",
bitumen = "Bitumen",
lubricants = "Lubricants",
naphtha = "Naphtha",
paraffin_waxes = "Paraffin waxes",
refinery_feedstocks = "Refinery feedstocks",
white_spirit_and_sbp = "White spirit & SBP"
# The following products were removed from the
# nonenergy_products constant by MKH on 3 Nov 2023
# after extensive discussion among
# PB, EA, and MKH.
# The decision was made to follow the IEA directly.
# The IEA does not consider the following products
# to be NEU, so we do the same.
# We will now be allocating these products correctly
# in Country-specific (and WRLD) allocation
# spreadsheets.
# coal_tar = "Coal tar",
# crude_ngl_feedstocks_if_no_detail = "Crude/NGL/feedstocks (if no detail)",
# crude_oil = "Crude oil",
# natural_gas_liquids = "Natural gas liquids",
# oil_shale_and_oil_sands = "Oil shale and oil sands",
# other_hydrocarbons = "Other hydrocarbons",
# other_oil_products = "Other oil products"
)
usethis::use_data(nonenergy_products, overwrite = TRUE)
#
# Flow types
#
tpes_flows <- list(resources = "Resources",
production = "Production",
imports = "Imports",
exports = "Exports",
international_marine_bunkers = "International marine bunkers",
international_aviation_bunkers = "International aviation bunkers",
# Added new "exports_to_" tpes flows on 15 July 2021 as part of treating
# World bunkers correctly.
# These new flows will ultimately replace
# international_marine_bunkers and international_aviation_bunkers
# after all IEA data are specified.
exports_to_world_marine_bunkers = "Exports to World marine bunkers",
exports_to_world_aviation_bunkers = "Exports to World aviation bunkers",
stock_changes = "Stock changes")
usethis::use_data(tpes_flows, overwrite = TRUE)
#
# Primary energy flows used to calculate domestic primary energy consumption using
# Recca::primary_aggregates()
#
prim_agg_flows <- tpes_flows
prim_agg_flows <- prim_agg_flows[!(prim_agg_flows %in% c(tpes_flows$production,
tpes_flows$exports,
tpes_flows$international_marine_bunkers,
tpes_flows$international_aviation_bunkers,
tpes_flows$exports_to_world_marine_bunkers,
tpes_flows$exports_to_world_aviation_bunkers
))]
usethis::use_data(prim_agg_flows, overwrite = TRUE)
tfc_compare_flows <- list(total_primary_energy_supply = "Total primary energy supply",
total_energy_supply = "Total energy supply",
transfers = "Transfers",
statistical_differences = "Statistical differences",
transformation_processes = "Transformation processes",
energy_industry_own_use = "Energy industry own use",
losses = "Losses")
usethis::use_data(tfc_compare_flows, overwrite = TRUE)
transformation_processes <- list(main_activity_producer_electricity_plants = "Main activity producer electricity plants",
autoproducer_electricity_plants = "Autoproducer electricity plants",
main_activity_producer_CHP_plants = "Main activity producer CHP plants",
autoproducer_CHP_plants = "Autoproducer CHP plants",
main_activity_producer_heat_plants = "Main activity producer heat plants",
autoproducer_heat_plants = "Autoproducer heat plants",
heat_pumps = "Heat pumps",
electric_boilers = "Electric boilers",
chemical_heat_for_electricity_production = "Chemical heat for electricity production",
blast_furnaces = "Blast furnaces",
gas_works = "Gas works",
coke_ovens = "Coke ovens",
patent_fuel_plants = "Patent fuel plants",
bkb_peat_briquette_plants = "BKB/peat briquette plants",
oil_refineries = "Oil refineries",
petrochemical_plants = "Petrochemical plants",
coal_liquefaction_plants = "Coal liquefaction plants",
gas_to_liquid_gtl_plants = "Gas-to-liquids (GTL) plants",
for_blended_natural_gas = "For blended natural gas",
charcoal_production_plants = "Charcoal production plants",
nuclear_indsutry = "Nuclear industry",
non_specified_transformation = "Non-specified (transformation)",
# 2019
non_specified_energy = "Non-specified (energy)")
usethis::use_data(transformation_processes, overwrite = TRUE)
main_act_plants <- list(main_act_prod_elect_plants = "Main activity producer electricity plants",
main_act_prod_chp_plants = "Main activity producer CHP plants",
main_act_prod_heat_plants = "Main activity producer heat plants",
autoprod_elect_plants = "Autoproducer electricity plants",
autoprod_heat_plants = "Autoproducer heat plants",
autoprod_chp_plants = "Autoproducer CHP plants")
usethis::use_data(main_act_plants, overwrite = TRUE)
eiou_flows <- list(bkb_peat_briquette_plants = "BKB/peat briquette plants",
blast_furnaces = "Blast furnaces",
charcoal_plants = "Charcoal production plants",
coal_liquefaction_plants = "Coal liquefaction plants",
coal_mines = "Coal mines",
coke_ovens = "Coke ovens",
gas_works = "Gas works",
gas_to_liquids_plants = "Gas-to-liquids (GTL) plants",
gasification_plants = "Gasification plants for biogases",
liquefaction_regasification_plants = "Liquefaction (LNG) / regasification plants",
non_specified_eiou = "Non-specified (energy)",
nuclear_industry = "Nuclear industry",
oil_and_gas_extraction = "Oil and gas extraction",
# "Oil and gas extraction" is split in the specification process.
# So we need "Oil extraction" and "Natural gas extraction".
oil_extraction = "Oil extraction",
natural_gas_extraction = "Natural gas extraction",
oil_refineries = "Oil refineries",
own_use_elect_chp_heat_plants = "Own use in electricity, CHP and heat plants",
# In the specification process,
# we route "Own use in electricity, CHP and heat plants" to
# main activity plants for electricity, CHP, and heat.
# So we need to include those plants here.
main_activity_producer_electricity_plants = "Main activity producer electricity plants",
main_activity_producer_chp_plants = "Main activity producer CHP plants",
main_activity_producer_heat_plants = "Main activity producer heat plants",
patent_fuel_plants = "Patent fuel plants",
pumped_storage_plants = "Pumped storage plants")
usethis::use_data(eiou_flows, overwrite = TRUE)
tfc_flows <- list(industry = "Industry",
transport = "Transport",
other = "Other",
non_energy_use = "Non-energy use")
usethis::use_data(tfc_flows, overwrite = TRUE)
manufacturing_flows <- list(iron_and_steel = "Iron and steel",
chemical_and_petrochemical = "Chemical and petrochemical",
non_ferrous_metals = "Non-ferrous metals",
non_metallic_minerals = "Non-metallic minerals",
transport_equipment = "Transport equipment",
machinery = "Machinery",
food_and_tobacco = "Food and tobacco",
# 2018
paper_pulp_and_print = "Paper, pulp and print",
# 2019
paper_pulp_and_printing = "Paper, pulp and printing",
wood_and_wood_products = "Wood and wood products",
textile_and_leather = "Textile and leather")
usethis::use_data(manufacturing_flows, overwrite = TRUE)
industry_flows <- list(mining_and_quarrying = "Mining and quarrying",
construction = "Construction",
manufacturing = "Manufacturing",
manufacturing_flows,
# 2018
non_specified_industry = "Non-specified (industry)",
# 2019
industry_not_elsewhere_specified = "Industry not elsewhere specified",
# Extra flows that arise after specification
coal_mines = "Coal mines",
oil_and_gas_extraction = "Oil and gas extraction",
oil_extraction = "Oil extraction",
natural_gas_extraction = "Natural gas extraction") %>%
unlist() %>%
as.list()
usethis::use_data(industry_flows, overwrite = TRUE)
# A constant containing non-eiou industry flows
industry_net_flows <- industry_flows[!(industry_flows %in% c("Coal mines", "Oil and gas extraction"))]
usethis::use_data(industry_net_flows, overwrite = TRUE)
transport_flows <- list(domestic_navigation = "Domestic navigation",
world_marine_bunkers = "World marine bunkers",
international_navigation = "International navigation",
domestic_aviation = "Domestic aviation",
world_aviation_bunkers = "World aviation bunkers",
international_aviation = "International aviation",
road = "Road",
rail = "Rail",
pipeline_transport = "Pipeline transport",
# 2019
non_specified_transport = "Non-specified (transport)",
# 2020
transport_not_elsewhere_specified = "Transport not elsewhere specified")
usethis::use_data(transport_flows, overwrite = TRUE)
# A constant containing domestic transport flows. This constant is the same as
# transport flows except it does not contain "World marine bunkers" or
# "World aviation bunkers"
transport_domestic_flows <- transport_flows[!(transport_flows %in% c(tpes_flows$world_aviation_bunkers,
tpes_flows$world_marine_bunkers))]
usethis::use_data(transport_domestic_flows, overwrite = TRUE)
other_flows <- list(residential = "Residential",
commercial_and_public_services = "Commercial and public services",
agriculture_forestry = "Agriculture/forestry",
fishing = "Fishing",
# 2018
non_specified_other = "Non-specified (other)",
# 2019
final_consumption_not_elsewhere_specified = "Final consumption not elsewhere specified")
usethis::use_data(other_flows, overwrite = TRUE)
non_energy_flows <- list(non_energy_use_industry_transformation_energy = "Non-energy use industry/transformation/energy",
non_energy_use_in_transport = "Non-energy use in transport",
non_energy_use_in_other = "Non-energy use in other")
usethis::use_data(non_energy_flows, overwrite = TRUE)
#
# Memo: Non-energy use in xxxxxx flows
#
memo_non_energy_flows <- list(memo_non_energy_use_in_industry = "Memo: Non-energy use in industry",
memo_non_energy_use_in_construction = "Memo: Non-energy use in construction",
memo_non_energy_use_in_mining_quarrying = "Memo: Non-energy use in mining and quarrying",
memo_non_energy_use_in_iron_steel = "Memo: Non-energy use in iron and steel",
memo_non_energy_use_in_chemical_petrochemical = "Memo: Non-energy use in chemical/petrochemical",
memo_non_energy_use_in_non_ferrous_metals = "Memo: Non-energy use in non-ferrous metals",
memo_non_energy_use_in_non_metallic_minerals = "Memo: Non-energy use in non-metallic minerals",
memo_non_energy_use_in_transport_equipment = "Memo: Non-energy use in transport equipment",
memo_non_energy_use_in_machinery = "Memo: Non-energy use in machinery",
memo_non_energy_use_in_food_beverages_tobacco = "Memo: Non-energy use in food/beverages/tobacco",
memo_non_energy_use_in_paper_pulp_printing = "Memo: Non-energy use in paper/pulp and printing",
memo_non_energy_use_in_wood_and_wood_products = "Memo: Non-energy use in wood and wood products",
memo_non_energy_use_in_textiles_leather = "Memo: Non-energy use in textiles and leather",
memo_non_energy_use_in_industry_not_elsewhere_specified = "Memo: Non-energy use in industry not elsewhere specified")
usethis::use_data(memo_non_energy_flows, overwrite = TRUE)
#
# Aggregations
#
aggregation_flows <- list(total_primary_energy_supply = tfc_compare_flows$total_primary_energy_supply,
# In 2020, IEA changed the name of TPES to TES.
total_energy_supply = tfc_compare_flows$total_energy_supply,
total_final_consumption = "Total final consumption",
transformation_processes = "Transformation processes",
energy_industry_own_use = "Energy industry own use",
tfc_compare = "TFC compare",
industry = "Industry",
manufacturing = "Manufacturing",
transport = "Transport",
other = "Other",
non_energy_use = "Non-energy use")
usethis::use_data(aggregation_flows, overwrite = TRUE)
#
# Default names for columns in aggregate data frames
#
aggregate_cols <- list(aggregate_primary = "EX.p",
aggregate_final = "EX.f",
aggregate_useful = "EX.u",
net_aggregate_demand = "EX.fd_net",
gross_aggregate_demand = "EX.fd_gross")
usethis::use_data(aggregate_cols, overwrite = TRUE)
memo_aggregation_flow_prefixes <- list(memo = "Memo: ",
electricity_output_GWh = "Electricity output (GWh)",
heat_output = "Heat output")
usethis::use_data(memo_aggregation_flow_prefixes, overwrite = TRUE)
memo_aggregation_product_prefixes <- list(memo = "Memo: ",
total = "Total")
usethis::use_data(memo_aggregation_product_prefixes, overwrite = TRUE)
#
# Interfaces
#
interface_industries <- list(imports = tpes_flows$imports,
exports = tpes_flows$exports,
international_aviation_bunkers = tpes_flows$international_aviation_bunkers,
international_marine_bunkers = tpes_flows$international_marine_bunkers,
exports_to_world_aviation_bunkers = tpes_flows$exports_to_world_aviation_bunkers,
exports_to_world_marine_bunkers = tpes_flows$exports_to_world_marine_bunkers,
stock_changes = tpes_flows$stock_changes)
usethis::use_data(interface_industries, overwrite = TRUE)
#
# Aggregation regions
#
# Note: Greenland, Palestinian Authority, and Uganda are NOT
# aggregation regions.
#
aggregation_regions <- list(world = "World",
oecd_americas = "OECD Americas",
oecd_asia_oceana = "OECD Asia Oceania",
oecd_europe = "OECD Europe",
africa = "Africa",
non_oecd_americas = "Non-OECD Americas",
non_oecd_asia_excluding_china = "Non-OECD Asia (excluding China)",
middle_east = "Middle East",
non_oecd_europe_and_eurasia = "Non-OECD Europe and Eurasia",
memo_equatirlai_guinea = "Memo: Equatorial Guinea",
# memo_greenland = "Memo: Greenland",
memo_lao_peoples_democratic_republic = "Memo: Lao People's Democratic Republic",
memo_mali = "Memo: Mali",
# memo_palestinian_authority = "Memo: Palestinian Authority",
memo_uganda = "Memo: Uganda",
memo_africa_un = "Memo: Africa (UN)",
memo_americas_un = "Memo: Americas (UN)",
memo_asia_un = "Memo: Asia (UN)",
memo_europe_un = "Memo: Europe (UN)",
memo_oceania_un = "Memo: Oceania (UN)",
memo_oecd_total = "Memo: OECD Total",
memo_non_oecd_total = "Memo: Non-OECD Total",
memo_iea_total = "Memo: IEA Total",
memo_iea_and_accession_association_countries = "Memo: IEA and Accession/Association countries",
memo_european_union_28 = "Memo: European Union-28",
memo_fsu_15 = "Memo: FSU 15",
memo_former_yugoslavia = "Memo: Former Yugoslavia",
memo_opec = "Memo: OPEC",
memo_asean = "Memo: ASEAN",
memo_g7 = "Memo: G7",
memo_g8 = "Memo: G8",
memo_g20 = "Memo: G20",
memo_china_pr_of_china_and_hong_kong_china = "China (P.R. of China and Hong Kong, China)"
# As of 14 July 2021, we are treating
# these bunkers as their own country,
# so they should no longer be listed as an aggregation region.
# world_aviation_bunkers = "World aviation bunkers",
# world_marine_bunkers = "World marine bunkers"
)
usethis::use_data(aggregation_regions, overwrite = TRUE)
#
# Sort orders
#
# We want to replace this code with other code to read a concordance table
# for country names.
# ---MKH, 20 July 2021
countries <- countrycode::codelist %>%
dplyr::select(iso3c) %>%
dplyr::filter(!is.na(iso3c)) %>%
unlist() %>%
unname()
countries <- append(countries, c("WAB", "WMB"))
usethis::use_data(countries, overwrite = TRUE)
# See
# T. Sousa, P. E. Brockway, J. M. Cullen, S. T. Henriques, J. Miller, A. C. Serrenho, and T. Domingos.
# The need for robust, consistent methods in societal exergy accounting. Ecological Economics, 141:11–21, Nov 2017.
# for details
methods <- list(pcm = "PCM", # Physical content method (used by IEA)
rcm = "RCM", # Resource content method
psm = "PSM") # Partial substitution method (used by EIA and BP)
usethis::use_data(methods, overwrite = TRUE)
energy_types <- list(e = "E", # Energy
x = "X") # Exergy
usethis::use_data(energy_types, overwrite = TRUE)
all_stages <- list(primary = "Primary",
final = "Final",
useful = "Useful",
services = "Services")
usethis::use_data(all_stages, overwrite = TRUE)
last_stages <- all_stages
last_stages$primary <- NULL
usethis::use_data(last_stages, overwrite = TRUE)
ledger_sides <- list(supply = "Supply",
consumption = "Consumption")
usethis::use_data(ledger_sides, overwrite = TRUE)
# Defining the row order for IEA-style data frames is tricky and requires some manual intervention.
# In the first step, we use the data frame created from load_tidy_iea_df,
# creating a united column from Flow.aggregation.point and Flow.
fap_flows <- load_tidy_iea_df(remove_zeroes = FALSE) %>%
tidyr::unite(col = Flow.aggregation.point_Flow, Flow.aggregation.point, Flow, sep = "_", remove = TRUE) %>%
dplyr::select(Flow.aggregation.point_Flow) %>%
unique() %>%
unlist() %>%
unname() %>%
# Then we insert a few items manually.
# Coal mines and Oil and gas extraction are created in specify_primary_production().
insert_after(after = "Total primary energy supply_Production",
values = c("Total primary energy supply_Coal mines", "Total primary energy supply_Oil and gas extraction")) %>%
# We we have Resources, Coal mines and Oil and gas extraction are Transformation processes.
# Add entries for those, too.
insert_after(after = "TFC compare_Statistical differences",
values = c("Transformation processes_Coal mines", "Transformation processes_Oil and gas extraction")) %>%
# Inserting Nuclear industry as a transformation process
insert_after(after = "Transformation processes_Oil and gas extraction",
values = "Transformation processes_Nuclear industry") %>%
# Energy industry own use_Own use in electricity, CHP and heat plants,
# Pumped storage plants, and Nuclear industry is reassigned to Main activity producer electricity plants in specify_tp_eiou()
insert_after(after = "Energy industry own use_Nuclear industry",
values = "Energy industry own use_Main activity producer electricity plants") %>%
# Inserting Main activity producer CHP plants and Main activity producer heat plants as EIOU flows
insert_after(after = "Energy industry own use_Main activity producer electricity plants",
values = c("Energy industry own use_Main activity producer CHP plants", "Energy industry own use_Main activity producer heat plants")) %>%
insert_after(after = "Energy industry own use_Main activity producer heat plants",
values = c("Energy industry own use_Oil extraction", "Energy industry own use_Natural gas extraction")) %>%
# Add combinations for international bunkers.
insert_after(after = "Transport_Domestic navigation",
values = "Transport_International navigation") %>%
insert_after(after = "Transport_Domestic aviation",
values = "Transport_International aviation") %>%
# Pick up several "not elsewhere specified" flows.
# These enable sorting for years besides the latest year.
insert_after(after = "Transport_Transport not elsewhere specified",
values = "Transport_Non-specified (transport)") %>%
insert_after(after = "Industry_Industry not elsewhere specified",
values = "Industry_Non-specified (industry)") |>
# Insert several specific non-energy use flows.
# These flows are used when we specify Non-energy use flows by industry (where available).
insert_after(after = "Non-energy use_Non-energy use industry/transformation/energy",
values = c("Non-energy use_Non-energy use in construction",
"Non-energy use_Non-energy use in mining and quarrying",
"Non-energy use_Non-energy use in iron and steel",
"Non-energy use_Non-energy use in chemical/petrochemical",
"Non-energy use_Non-energy use in non-ferrous metals",
"Non-energy use_Non-energy use in non-metallic minerals",
"Non-energy use_Non-energy use in transport equipment",
"Non-energy use_Non-energy use in machinery",
"Non-energy use_Non-energy use in food/beverages/tobacco",
"Non-energy use_Non-energy use in paper/pulp and printing",
"Non-energy use_Non-energy use in wood and wood products",
"Non-energy use_Non-energy use in textiles and leather",
"Non-energy use_Non-energy use in industry not elsewhere specified"))
usethis::use_data(fap_flows, overwrite = TRUE)
products <- load_tidy_iea_df(remove_zeroes = FALSE) %>%
dplyr::select(Product) %>%
unique() %>%
unlist() %>%
unname() %>%
# Insert a few items manually.
# In specify_primary_production(), some Products are renamed to account for the fact that they come from a different industry.
insert_after(after = primary_coal_products[length(primary_coal_products)],
# values = paste0(primary_coal_products, from_notation[["suff_start"]], "Coal mines", from_notation[["suff_end"]])) %>%
values = RCLabels::paste_pref_suff(pref = primary_coal_products, suff = "Coal mines", notation = RCLabels::bracket_notation)) %>%
insert_after(after = primary_oil_products[length(primary_oil_products)],
# values = paste0(primary_oil_products, from_notation[["suff_start"]], "Oil and gas extraction", from_notation[["suff_end"]])) %>%
values = RCLabels::paste_pref_suff(pref = primary_oil_products, suff = "Oil and gas extraction", notation = RCLabels::bracket_notation)) %>%
insert_after(after = "Natural gas",
# values = paste0("Natural gas", from_notation[["suff_start"]], "Oil and gas extraction", from_notation[["suff_end"]]))
values = RCLabels::paste_pref_suff(pref = "Natural gas", suff = "Oil and gas extraction", notation = RCLabels::bracket_notation))
usethis::use_data(products, overwrite = TRUE)
#
# Pull the non-specified flows together
#
non_specified_flows <- list(non_specified_transformation = transformation_processes$non_specified_transformation,
non_specified_energy = "Non-specified (energy)",
non_specified_transport = transport_flows$non_specified_transport,
# 2018
non_specified_industry = industry_flows$non_specified_industry,
# 2019
industry_not_elsewhere_specified = industry_flows$industry_not_elsewhere_specified,
non_specified = "Non-specified",
# 2020
non_specified_transport = transport_flows$transport_not_elsewhere_specified)
usethis::use_data(non_specified_flows, overwrite = TRUE)
#
# Final demand sectors for use by Recca::finaldemand_aggregates()
#
fd_sectors <- c(eiou_flows,
industry_net_flows,
transport_domestic_flows,
other_flows,
non_energy_flows,
gsub(memo_aggregation_flow_prefixes$memo, "", memo_non_energy_flows))
usethis::use_data(fd_sectors, overwrite = TRUE)
#
# Names and constants associated with constant phi value tables.
#
phi_constants_names <- list(phi_constants_tab_name = "phi_constants",
product_colname = "Product",
phi_colname = "phi",
phi_source_colname = "phi.source",
is_useful_colname = "is.useful")
usethis::use_data(phi_constants_names, overwrite = TRUE)
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