Aggregate monitoring periods for AMS-III.D datasets

Roll up period-level monitoring data to the grouping level used in AMS-III.D calculations.

aggregate_monitoring_periods_iiid(
  data,
  group_cols,
  sum_cols = c("volatile_solids_kg_per_day", "methane_recovered_m3", "leakage_emissions_tco2e", "days_in_period"),
  mean_cols = c("methane_potential_m3_per_kg_vs", "baseline_mcf_fraction", "project_mcf_fraction", "capture_efficiency_fraction", "destruction_efficiency_fraction"),
  na_rm = TRUE
)

Arguments

data

Tibble containing period-level monitoring data.

group_cols

Character vector of grouping columns (e.g. "farm_id").

sum_cols

Numeric columns to sum across monitoring periods.

mean_cols

Numeric columns to average across monitoring periods.

na_rm

Logical indicating whether to remove missing values during aggregation.

Value

Tibble aggregated to the specified grouping columns.

Examples

monitoring <- tibble::tibble(
  farm_id = rep("A", 2),
  monitoring_period = c(1, 2),
  volatile_solids_kg_per_day = c(40, 42),
  methane_recovered_m3 = c(1200, 1300),
  days_in_period = c(30, 30),
  methane_potential_m3_per_kg_vs = c(0.23, 0.24),
  project_mcf_fraction = c(0.6, 0.58)
)
aggregate_monitoring_periods_iiid(monitoring, group_cols = "farm_id")
#> # A tibble: 1 × 6
#>   farm_id volatile_solids_kg_per_day methane_recovered_m3 days_in_period
#>   <chr>                        <dbl>                <dbl>          <dbl>
#> 1 A                               82                 2500             60
#> # ℹ 2 more variables: methane_potential_m3_per_kg_vs <dbl>,
#> #   project_mcf_fraction <dbl>