Add targets for CO2 emissions per unit production at the portfolio level, using the SDA approach

This function calculates targets of CO2 emissions per unit production at the portfolio-level, otherwise referred to as "emissions factors". It uses the sectoral-decarbonization approach (SDA) to calculate these targets.

Usage

target_sda(
  data,
  abcd,
  co2_intensity_scenario,
  use_credit_limit = FALSE,
  by_company = FALSE,
  region_isos = r2dii.data::region_isos
)

Arguments

data

A dataframe like the output of r2dii.match::prioritize().

abcd

An asset-level data frame like r2dii.data::abcd_demo.

co2_intensity_scenario

A scenario data frame like r2dii.data::co2_intensity_scenario_demo.

use_credit_limit

Logical vector of length 1. FALSE defaults to using the column loan_size_outstanding. Set to TRUE to instead use the column loan_size_credit_limit.

by_company

Logical vector of length 1. FALSE defaults to outputting weighted_production_value at the portfolio-level. Set to TRUE to output weighted_production_value at the company-level.

region_isos

A data frame like r2dii.data::region_isos (default).

Value

A tibble including the summarized columns emission_factor_metric and emission_factor_value. If by_company = TRUE, the output will also have the column name_abcd.

Handling grouped data

This function ignores existing groups and outputs ungrouped data.

See also

Other functions to calculate scenario targets: target_market_share()

Examples

library(r2dii.match)
library(r2dii.data)

loanbook <- head(loanbook_demo, 150)
abcd <- head(abcd_demo, 100)

matched <- loanbook %>%
  match_name(abcd) %>%
  prioritize()

# Calculate targets at portfolio level
matched %>%
  target_sda(
   abcd = abcd,
   co2_intensity_scenario = co2_intensity_scenario_demo,
   region_isos = region_isos_demo
   )
#> Warning: Removing rows in abcd where `emission_factor` is NA
#> Warning: Found no match between loanbook and abcd.
#> # A tibble: 0 × 4
#> # ℹ 4 variables: sector <chr>, year <int>, emission_factor_metric <chr>,
#> #   emission_factor_value <dbl>

# Calculate targets at company level
matched %>%
  target_sda(
   abcd = abcd,
   co2_intensity_scenario = co2_intensity_scenario_demo,
   region_isos = region_isos_demo,
   by_company = TRUE
   )
#> Warning: Removing rows in abcd where `emission_factor` is NA
#> Warning: Found no match between loanbook and abcd.
#> # A tibble: 0 × 4
#> # ℹ 4 variables: sector <chr>, year <int>, emission_factor_metric <chr>,
#> #   emission_factor_value <dbl>