Estimate emission reductions under AMS-I.B

Composes the AMS-I.B equation helpers to estimate emission reductions for a dataset describing fossil fuel consumption displaced by a renewable mechanical energy system.

estimate_emission_reductions_ams_ib(
  fuel_data,
  consumption_col = "fuel_consumption",
  ncv_col = "net_calorific_value",
  group_cols = NULL,
  emission_factor,
  project_energy_col = NULL,
  project_emission_factor = 0
)

Arguments

fuel_data

Tibble containing baseline fuel consumption data.

consumption_col

Name of the column with baseline fuel consumption (e.g. litres or kg).

ncv_col

Name of the column with net calorific value in MJ per unit of fuel.

group_cols

Optional character vector specifying grouping columns (e.g. machine identifiers).

emission_factor

Baseline emission factor in tCO2e/MJ.

project_energy_col

Optional column name containing residual project fossil energy in MJ.

project_emission_factor

Project emission factor in tCO2e/MJ (default 0).

Value

A tibble containing baseline energy, baseline emissions, project energy, project emissions, and emission reductions.

Examples

fuel <- tibble::tibble(machine_id = c("pump-1", "pump-1", "mill-3"),
                       fuel_consumption = c(200, 180, 150),
                       net_calorific_value = c(43, 43, 42))
estimate_emission_reductions_ams_ib(fuel, emission_factor = 0.00007)
#> # A tibble: 1 × 5
#>   baseline_energy_mj baseline_emissions_tco2e project_energy_mj
#>                <dbl>                    <dbl>             <dbl>
#> 1              22640                     1.58                 0
#> # ℹ 2 more variables: project_emissions_tco2e <dbl>,
#> #   emission_reductions_tco2e <dbl>