Assess AMS-II.F applicability conditions collectively

Bundles the individual applicability checks into a single helper that returns a tidy summary of whether each criterion is satisfied. This wrapper is useful for pre-screening project concepts prior to detailed calculations. [check_applicability_energy_intensity_iif()]. [check_applicability_fuel_switching_iif()]. [check_applicability_monitoring_iif()].

assess_ams_iif_applicability(baseline_data,
                                         project_data,
                                         monitoring_data,
                                         intensity_args = list(),
                                         fuel_switch_args = list(),
                                         monitoring_args = list())

Arguments

baseline_data

Tibble containing baseline inputs.

project_data

Tibble containing project inputs.

monitoring_data

Tibble containing monitoring dataset.

intensity_args

Optional list of arguments passed to

fuel_switch_args

Optional list of arguments passed to

monitoring_args

Optional list of arguments passed to

Value

A tibble with the columns `criterion` and `is_met`.

Examples

baseline <- tibble::tibble(
  baseline_total_energy_mwh = 220,
  service_level_indicator = 420,
  baseline_thermal_energy_gj = 320,
  baseline_thermal_emission_factor_tco2_per_gj = 0.072
)
project <- tibble::tibble(
  project_total_energy_mwh = 150,
  service_level_indicator = 420,
  project_thermal_energy_gj = 220,
  project_thermal_emission_factor_tco2_per_gj = 0.045
)
monitoring <- tibble::tibble(
  project_total_energy_mwh = 12.5,
  service_level_indicator = 0.35,
  operating_hours = 220
)
assess_ams_iif_applicability(baseline, project, monitoring)
#> # A tibble: 3 × 2
#>   criterion        is_met
#>   <chr>            <lgl> 
#> 1 energy_intensity TRUE  
#> 2 fuel_switching   TRUE  
#> 3 monitoring       TRUE