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Accelerate pm25

Source: R/accelerate_hpop.R
accelerate_pm25.Rd

Accelerate pm25 by picking the best value between business as usual, and linear change of -2% * 2018 value_col per year.

Usage

accelerate_pm25(
  df,
  ind_ids = billion_ind_codes("hpop"),
  scenario_col = "scenario",
  value_col = "value",
  default_scenario = "default",
  bau_scenario = "historical",
  scenario_name = "acceleration",
  ...
)

Arguments

df

Data frame in long format, where 1 row corresponds to a specific country, year, and indicator.

ind_ids

Named vector of indicator codes for input indicators to the Billion. Although separate indicator codes can be used than the standard, they must be supplied as a named vector where the names correspond to the output of billion_ind_codes().

scenario_col

Column name of column with scenario identifiers. Useful for calculating contributions on data in long format rather than wide format.

value_col

Name of the column containing indicator value in df.

default_scenario

name of the default scenario.

bau_scenario

name of scenario to be used for business as usual. Default is historical.

scenario_name

name of scenario

...

additional parameters to be passed to scenario function

Details

Runs:

  • scenario_bau(df, small_is_best = TRUE,...)

  • scenario_linear_change(df, linear_value = df$value_col[df$"year" == 2018] * -0.02, small_is_best = TRUE,...)

Then picks the best result between the two scenarios.

See also

HPOP acceleration scenarios accelerate_adult_obese(), accelerate_alcohol(), accelerate_child_obese(), accelerate_child_viol(), accelerate_devontrack(), accelerate_fuel(), accelerate_hpop_sanitation_rural(), accelerate_hpop_sanitation_urban(), accelerate_hpop_sanitation(), accelerate_hpop_tobacco(), accelerate_ipv(), accelerate_overweight(), accelerate_road(), accelerate_stunting(), accelerate_suicide(), accelerate_transfats(), accelerate_wasting(), accelerate_water_rural(), accelerate_water_urban(), accelerate_water()