simulate_ams_iig_dataset.RdGenerates synthetic monitoring observations for AMS-II.G projects, including baseline and project biomass consumption, non-renewable fractions, emission factors, leakage placeholders, and monitoring metadata.
simulate_ams_iig_dataset(
n_sites = 5,
n_periods = 4,
start_year = 2024,
start_month = 1,
seed = NULL,
baseline_consumption_mean = 14,
efficiency_gain = 0.45,
baseline_fraction_mean = 0.85,
project_fraction_mean = 0.4
)Number of project sites or households to simulate.
Number of monitoring periods per site.
Starting calendar year for the monitoring periods.
Starting month for the monitoring periods (1-12).
Optional random seed for reproducibility.
Mean baseline biomass consumption per period (tonnes).
Expected fractional reduction in biomass consumption due to efficiency improvements (0-1).
Mean baseline non-renewable fraction.
Mean project non-renewable fraction.
A tibble containing monitoring metadata and the columns required by estimate_emission_reductions_ams_iig().
simulate_ams_iig_dataset(n_sites = 2, n_periods = 3, seed = 123)
#> # A tibble: 6 × 17
#> site_id period year month day monitoring_date monitoring_label
#> <chr> <int> <dbl> <dbl> <int> <date> <chr>
#> 1 site_01 1 2024 1 15 2024-01-15 2024-01
#> 2 site_01 2 2024 2 19 2024-02-19 2024-02
#> 3 site_01 3 2024 3 14 2024-03-14 2024-03
#> 4 site_02 1 2024 1 3 2024-01-03 2024-01
#> 5 site_02 2 2024 2 10 2024-02-10 2024-02
#> 6 site_02 3 2024 3 18 2024-03-18 2024-03
#> # ℹ 10 more variables: baseline_biomass_consumption_tonnes <dbl>,
#> # baseline_non_renewable_fraction <dbl>,
#> # baseline_net_calorific_value_mj_per_tonne <dbl>,
#> # baseline_emission_factor_tco2_per_mj <dbl>,
#> # project_biomass_consumption_tonnes <dbl>,
#> # project_non_renewable_fraction <dbl>,
#> # project_net_calorific_value_mj_per_tonne <dbl>, …