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Decompose urban nitrogen losses into population, per-capita, and recycling drivers

Source: R/decomposition_analysis.R
decompose_urban_losses.Rd

Decomposes the year-on-year change in non-recycled human excreta nitrogen (N) into three multiplicative drivers, computed at the national level: population, per-capita excreted N (approximated by per-capita food N consumption, since intake is approximately equal to excretion), and the non-recycled fraction of excreted N.

Only the population_food destiny is used as the excretion proxy. population_other_uses (non-food industrial use, e.g. cotton/tobacco) is deliberately excluded even though .create_wastewater_surplus_df() in grafs_plot_df.R includes it: that material is not ingested, so it cannot be assumed to leave the body as excreta, breaking the intake-approximates-excretion logic this compartment relies on.

Food waste is not included: the commodity-balance sheets underlying n_prov_destiny carry Food/Feed/Seed/Other-uses/Export/Import destinies but no separate consumer food-waste line, so this loss is excreta-only. Whether the urban/People recycling flows already folded in some food waste from the original source is unconfirmed.

Usage

decompose_urban_losses(
  n_prov_destiny = NULL,
  population_yg = NULL,
  by_period = FALSE,
  example = FALSE
)

Arguments

n_prov_destiny

Nitrogen flows tibble from create_n_prov_destiny(). If NULL, loaded automatically.

population_yg

Population tibble from whep_read_file("population_yg"). If NULL, loaded automatically.

by_period

If TRUE, compares each reference period (each averaged across its ten years) against the immediately preceding one — 1860-1870 -> 1920-1930 -> 1960-1970 -> 2010-2020 — plus one extra transition spanning the full analysis window, 1860-1870 straight to 2010-2020 (the total change) — instead of chaining year on year.

example

If TRUE, return a small hardcoded output without downloading remote data. Default is FALSE.

Value

A tibble from calculate_lmdi() with columns period, period_years, factor_label, component_type, additive, multiplicative, and multiplicative_log.

Examples

decompose_urban_losses(example = TRUE)
#> # A tibble: 8 × 7
#>   period    period_years factor_label     component_type additive multiplicative
#>   <chr>            <dbl> <chr>            <chr>             <dbl>          <dbl>
#> 1 1860-1861            1 Population       factor            393.           1.00 
#> 2 1860-1861            1 Per-capita excr… factor           -388.           0.996
#> 3 1860-1861            1 Non-recycled fr… factor            -17.5          1.000
#> 4 1860-1861            1 Urban N loss     target            -12.6          1.000
#> 5 1861-1862            1 Population       factor            391.           1.00 
#> 6 1861-1862            1 Per-capita excr… factor           -387.           0.996
#> 7 1861-1862            1 Non-recycled fr… factor            -17.5          1.000
#> 8 1861-1862            1 Urban N loss     target            -12.6          1.000
#> # ℹ 1 more variable: multiplicative_log <dbl>