Run the AMS-II.F emission reduction workflow

Orchestrates the numbered equations for AMS-II.F to compute annual emission reductions from agricultural energy efficiency or fuel switching projects. The meta-function wires together [calculate_baseline_agricultural_emissions()], [calculate_project_agricultural_emissions()], [calculate_leakage_emissions_iif()], and [calculate_emission_reductions_iif()] while allowing optional fine-tuning via argument lists. electricity use. electricity use. grouping structure of the baseline/project data. datasets. [calculate_baseline_agricultural_emissions()]. [calculate_project_agricultural_emissions()]. [calculate_leakage_emissions_iif()]. [calculate_emission_reductions_iif()]. `group_cols` is injected automatically. totals by the requested grouping structure.

estimate_emission_reductions_ams_iif(baseline_data,
                                                 project_data,
                                                 leakage_data = NULL,
                                                 group_cols = NULL,
                                                 baseline_args = list(),
                                                 project_args = list(),
                                                 leakage_args = list(),
                                                 reduction_args = list())

Arguments

baseline_data

Tidy baseline dataset describing counterfactual fuel and

project_data

Tidy project dataset describing monitored fuel and

leakage_data

Optional tibble of leakage components aligned with the

group_cols

Character vector of grouping columns common to the supplied

baseline_args

Optional list of additional arguments passed to

project_args

Optional list of additional arguments passed to

leakage_args

Optional list of additional arguments passed to

reduction_args

Optional list of arguments forwarded to

Value

A tibble containing baseline, project, leakage, and emission reduction

Examples

baseline <- tibble::tibble(
  facility_id = "rice_mill_1",
  baseline_fuel_energy_gj = 960,
  baseline_fuel_emission_factor_tco2_per_gj = 0.072,
  baseline_electricity_mwh = 180,
  baseline_electricity_emission_factor_tco2_per_mwh = 0.61
)
project <- tibble::tibble(
  facility_id = "rice_mill_1",
  project_fuel_energy_gj = 520,
  project_fuel_emission_factor_tco2_per_gj = 0.03,
  project_electricity_mwh = 150,
  project_electricity_emission_factor_tco2_per_mwh = 0.61
)
estimate_emission_reductions_ams_iif(baseline, project, group_cols = "facility_id")
#> # A tibble: 1 × 2
#>   facility_id emission_reductions_tco2e
#>   <chr>                           <dbl>
#> 1 rice_mill_1                      71.8