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add prep_emissions_trajectory() #26

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add prep_emissions_trajectory() #26

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92 changes: 75 additions & 17 deletions main.R
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Original file line number Diff line number Diff line change
Expand Up @@ -395,6 +395,66 @@ prep_key_bars_portfolio <-
}


# -------------------------------------------------------------------------
# prep_emissions_trajectory ------------------------------------------------------
# based on pacta.portfolio.report:::prep_emissions_trajectory, but does not
# filter by scenario and scenario source

prep_emissions_trajectory <-
function(equity_results_portfolio,
bonds_results_portfolio,
portfolio_name,
pacta_sectors,
year_span,
start_year
) {
emissions_units <-
c(
Automotive = "tons of CO\U00002082 per km per cars produced",
Aviation = "tons of CO\U00002082 per passenger km per active planes",
Cement = "tons of CO\U00002082 per tons of cement",
Coal = "tons of CO\U00002082 per tons of coal",
`Oil&Gas` = "tons of CO\U00002082 per GJ",
Power = "tons of CO\U00002082 per MWh",
Steel = "tons of CO\U00002082 per tons of steel"
)
Comment on lines +411 to +420
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NB/ unrelated to this PR but.... this seems very likely to fall out of sync 😅

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Agreed, but I'm not sure where to put it. It was baked-in to pacta.portfolio.report:::prep_emissions_trajectory(), so ported over here, unless/until it's available somewhere in a better format.


list(`Listed Equity` = equity_results_portfolio,
`Corporate Bonds` = bonds_results_portfolio) %>%
bind_rows(.id = "asset_class") %>%
filter(.data$portfolio_name == .env$portfolio_name) %>%
filter(.data$scenario_geography == "Global") %>%
select(
"asset_class",
"allocation",
"equity_market",
sector = "ald_sector",
"year",
plan = "plan_sec_emissions_factor",
scen = "scen_sec_emissions_factor",
"scenario",
"scenario_source"
) %>%
distinct() %>%
filter(!is.nan(.data$plan)) %>%
pivot_longer(c("plan", "scen"), names_to = "plan") %>%
unite("name", "sector", "plan", remove = FALSE) %>%
mutate(disabled = !.data$sector %in% .env$pacta_sectors) %>%
mutate(unit = .env$emissions_units[.data$sector]) %>%
group_by(.data$asset_class) %>%
filter(!all(.data$disabled)) %>%
mutate(equity_market = case_when(
.data$equity_market == "GlobalMarket" ~ "Global Market",
.data$equity_market == "DevelopedMarket" ~ "Developed Market",
.data$equity_market == "EmergingMarket" ~ "Emerging Market",
TRUE ~ .data$equity_market)
) %>%
filter(.data$year <= .env$start_year + .env$year_span) %>%
arrange(.data$asset_class, factor(.data$equity_market, levels = c("Global Market", "Developed Market", "Emerging Market"))) %>%
ungroup()
}


# input and output directories -------------------------------------------------

input_dir <- "./inputs"
Expand Down Expand Up @@ -665,23 +725,7 @@ pacta.portfolio.report:::prep_trajectory_alignment(
jsonlite::write_json(path = file.path(output_dir, "data_trajectory_alignment.json"))


# data_emissions.json ----------------------------------------------------------

pacta.portfolio.report:::prep_emissions_trajectory(
equity_results_portfolio = equity_results_portfolio,
bonds_results_portfolio = bonds_results_portfolio,
investor_name = investor_name,
portfolio_name = portfolio_name,
select_scenario_other = select_scenario_other,
select_scenario = select_scenario,
pacta_sectors = pacta_sectors,
year_span = year_span,
start_year = start_year
) %>%
pacta.portfolio.report:::translate_df_contents("data_emissions", dictionary) %>%
jsonlite::write_json(path = file.path(output_dir, "data_emissions.json"))

# data_exposure_stats.json
# data_exposure_stats.json -----------------------------------------------------

prep_exposure_stats(
audit_file = audit_file,
Expand Down Expand Up @@ -731,3 +775,17 @@ prep_key_bars_portfolio(
) %>%
pacta.portfolio.report:::translate_df_contents("data_key_bars_portfolio", dictionary) %>%
jsonlite::write_json(path = file.path(output_dir, "data_techexposure_company_portfolio.json"))


# data_emissions.json ----------------------------------------------------------

prep_emissions_trajectory(
equity_results_portfolio = equity_results_portfolio,
bonds_results_portfolio = bonds_results_portfolio,
portfolio_name = portfolio_name,
pacta_sectors = pacta_sectors,
year_span = year_span,
start_year = start_year
) %>%
pacta.portfolio.report:::translate_df_contents("data_emissions", dictionary) %>%
jsonlite::write_json(path = file.path(output_dir, "data_emissions.json"))