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update weighting for the Aggregate score based on WEO2023 (#327)
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* update weighting for the Aggregate score based on WEO2023

* Anonymize path and point to azure location

* Refactor

* Update calculations and comment

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Co-authored-by: Monika Furdyna <[email protected]>
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Antoine-Lalechere and MonikaFu authored May 30, 2024
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55 changes: 45 additions & 10 deletions data-raw/remaining_carbon_budgets.R
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# styler: off
remaining_carbon_budgets <- tibble::tribble(
~scenario_source, ~ald_sector, ~remaining_carbon_budget, ~unit, ~weighting_factor,
"GECO2021", "coal", 84934.79, "Mt CO2 (2019)", 0.25,
"GECO2021", "oil", 82987.79, "Mt CO2 (2019)", 0.24,
"GECO2021", "gas", 49094.21, "Mt CO2 (2019)", 0.14,
"GECO2021", "power", 91121.17, "Mt CO2 (2019)", 0.27,
"GECO2021", "steel", 10746.03, "Mt CO2 (2019)", 0.03,
"GECO2021", "automotive", 11338.9, "Mt CO2 (2019)", 0.03,
"GECO2021", "hdv", 7388.01, "Mt CO2 (2019)", 0.02,
"GECO2021", "aviation", 5963.32, "Mt CO2 (2019)", 0.02
# The Extended file data for WEO 2023 is stored here:
# https://portal.azure.com/#view/Microsoft_Azure_FileStorage/FileShareMenuBlade/~/browse/storageAccountId/%2Fsubscriptions%2Ffeef729b-4584-44af-a0f9-4827075512f9%2FresourceGroups%2FRMI-SP-PACTA-PROD%2Fproviders%2FMicrosoft.Storage%2FstorageAccounts%2Fpactarawdata/path/scenario-sources/protocol/SMB
# The specific file is 'weo_2023-20240222/WEO2023 extended data/WEO2023_Extended_Data.xlsx'
# Please download the file and replace the dummy path in variable 'file_scenario_emissions_data'
# to the path on your computer before running the code.
file_scenario_emissions_data <- "PATH/TO/WEO2023/SCENARIO/EXTENDED/DATA"
carbon_emissions <- readxl::read_xlsx(file_scenario_emissions_data,
sheet = "World CO2 Emissions",
range = "J7:AP45") %>%
filter(!row_number() %in% c(12, 13, 14, 18, 19, 20)) %>%
rename(
sector = "...1",
emissions_2022 = "2022...25",
emissions_2030 = "2030...26",
emissions_2035 = "2035...27",
emissions_2040 = "2040...28",
emissions_2045 = "2045...29",
emissions_2050 = "2050...30",
) %>%
select(c("sector", "2010", "2015", "2021", "emissions_2022", "emissions_2030", "emissions_2035", "emissions_2040", "emissions_2045", "emissions_2050")) %>%
filter(sector %in% c("Coal", "Oil", "Natural gas", "Electricity and heat sectors", "Iron and steel**", "Cement**", "Passenger cars", "Aviation")) %>%
mutate(
scenario_source = "WEO2023",
unit = "Mt CO2 (2022)"
)

remaining_carbon_budgets <- carbon_emissions %>%
mutate(
# Remaining carbon budget for a sector is the sum of scenario emissions from 2022 until 2030.
# We interpolate the emissions linearly between points for which we have scenario values (2022 and 2030).
# The sum of 7 linearly interpolated points between x and y (including x and y) is equal to 4x + 5y:
# x + 7*x + ((1 + 2 + 3 + 4 + 5 + 6 + 7)/7)*(y-x) + y = 8x + 5y - 4x = 4x + 5y
remaining_carbon_budget = emissions_2022 * 4 + emissions_2030 * 5,
weighting_factor = remaining_carbon_budget/ sum(remaining_carbon_budget)
) %>%
mutate(ald_sector = case_when(
sector == "Coal" ~ "coal",
sector == "Oil" ~ "oil",
sector == "Natural gas" ~ "gas",
sector == "Electricity and heat sectors" ~ "power",
sector == "Iron and steel**" ~ "steel",
sector == "Passenger cars" ~ "automotive",
sector == "Aviation" ~ "aviation",
sector == "Cement**" ~ "cement"
)) %>%
select("scenario_source", "unit", "remaining_carbon_budget", "weighting_factor", "ald_sector")
# styler: on

usethis::use_data(remaining_carbon_budgets, overwrite = TRUE)
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