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Build the livestock energy-use CO2 footprint extension (meat only).

Source: R/energy_co2_extension.R
build_energy_co2_extension.Rd

Aggregate GLEAM 3.0 on-farm (direct) and feed-production (embedded) energy use into a footprint extension keyed by (year, area_code, item_cbs_code), expressed in kilograms of carbon-dioxide equivalent (CO2e). This is the energy slice of the livestock greenhouse-gas basket and is designed to be summed with build_livestock_ghg_extension() (enteric and manure CH4/N2O), which keys on the same live-animal sectors.

The GLEAM energy emission factors are expressed per kilogram of live weight (see gleam_energy_use_ef), which is well defined for meat but not for milk or eggs, so the extension covers meat only: bovine (item_cbs_code 961 non-dairy cattle and 946 buffalo), sheep (976) and goat (1016), pig (1049 and 1051) and broiler-chicken (1053) meat. Milk and eggs keep their CH4/N2O but get no energy CO2.

For each meat group the live weight produced is recovered from FAOSTAT carcass production divided by a GLEAM dressing fraction (gleam_dressing_percentages), multiplied by a per-country energy intensity (embedded + direct), and then attributed to the contributing live-animal sectors in proportion to their slaughtered head counts. Because GLEAM reports its factors by production system and climate zone but the package has no country-level system or climate shares, the intensities are collapsed to one value per country by an unweighted mean across systems and climate zones; this choice is recorded in method_energy. A meat group with carcass output but no slaughtered-head counts keeps its energy CO2e, split equally across the group's live-animal sectors, and triggers a warning.

gleam_geographic_hierarchy is the country universe of the whole extension, so a reporting area absent from it gets no energy intensity and its meat production leaves the extension. That affects both the aggregate reporting buckets (polity_area_code 999 "Rest of World" and the continental residuals 901-906) and the dissolved entities GLEAM's present-day country table cannot carry (USSR, Czechoslovakia, Yugoslavia, Belgium-Luxembourg, Serbia and Montenegro). The size of that loss is now reported on every build rather than left to be inferred, and three opt-in treatments recover it instead of losing it: unclassified = "polity_region" groups the live reporting areas GLEAM omits (today Nauru and Tuvalu) from the polity crosswalk, unclassified = "historical_region" additionally groups the dissolved entities from the membership they themselves held while they existed, and unclassified = "global_mean" prices every unclassifiable area at the world-mean GLEAM intensity. The default keeps the historical behaviour; see whep#415, whep#492 and whep#553.

Usage

build_energy_co2_extension(
  method = c("gleam"),
  data = list(),
  unclassified = c("drop", "polity_region", "historical_region", "global_mean"),
  example = FALSE
)

Arguments

method

Estimation method. Only "gleam" (default), the GLEAM 3.0 per-live-weight factors, is currently available.

data

Optional named list of pre-loaded inputs to avoid remote reads: primary_prod (the get_primary_production() output). It falls back to its reader when absent.

unclassified

How to treat reporting areas gleam_geographic_hierarchy has no row for, and which therefore get no country energy intensity. "drop" (default) keeps the historical behaviour: their meat production leaves the extension, and a warning says how much. "polity_region" gives the live, self-reporting ones among them a grouping derived from their polity in polity_area_crosswalk, running GLEAM's own scheme rules on that continent, and marks those rows "GLEAM_3.0_energy_meat_polity_region"; the aggregate buckets and dissolved entities still drop. "historical_region" does everything "polity_region" does and also groups the dissolved entities (USSR, Czechoslovakia, the Yugoslav SFR, Belgium-Luxembourg, Serbia and Montenegro, the Netherlands Antilles) from the OECD and EU membership they held while they existed, marking those rows "GLEAM_3.0_energy_meat_historical_region". "global_mean" instead prices every unclassifiable area at the unweighted world mean of the published GLEAM factors, marking those rows "GLEAM_3.0_energy_meat_global_mean".

example

If TRUE, return a small fixture instead of reading remote data. Defaults to FALSE.

Value

A tibble with columns year, area_code, item_cbs_code, impact_u (energy-use emissions in kilograms CO2e) and method_energy ("GLEAM_3.0_energy_meat", "GLEAM_3.0_energy_meat_polity_region" for rows grouped from the polity crosswalk, "GLEAM_3.0_energy_meat_historical_region" for dissolved entities grouped from their own era's memberships, or "GLEAM_3.0_energy_meat_global_mean" for rows priced at the world mean), plus the polity columns below.

Polity columns

Every area-keyed output carries the polity its area_code resolves to in that row's year:

  • polity_area_code: The numeric key rows are AGGREGATED on, for the matrix workflows. It is a bucket, not an identity: use reporting_polity_code to say which territory a row belongs to.

  • reporting_polity_code: The polity itself, e.g. ESP-1846-1914. It is year-aware, so the same area_code resolves to different polities in different years, which is the point of the crosswalk.

  • reporting_polity_name: Its name. It can differ from the area's own name where the area folds into an aggregate.

  • reporting_polity_has_geometry: Whether the polity has a polygon in the WHEP polity database, for callers that need to map or intersect it. FALSE is a documented gap upstream, not an error.

Rows whose area_code resolves to no polity keep the columns with NA rather than being dropped, so a gap is visible instead of silent.

Rows before the back-cast anchor year resolve to the polity live in that anchor year rather than to the polity live in the row's own year, because WHEP's pre-anchor series are back-cast onto the anchor-year territory. See add_polity_code() for the reasoning. Where that polity is not live in the row's own year – 41.5% of the pre-1961 (area, year) cells – add_polity_code() says so as mapping_status == "backcast_anchor", and polity_coverage_gaps() reports it as gap_kind == "backcast_anchor". These columns do not say so either way.

A row whose year no mapped period covers is resolved to the NEAREST period of the same area instead, so reporting_polity_code can name a polity that did not exist in that row's year – FAOSTAT bucket 206 "Sudan (former)" keeps reporting after SUD-1956-2011 ends, and its post-2011 rows carry that code. These columns do not say so: add_polity_code() reports such a row as mapping_status == "out_of_span", and that column is dropped here so that adding it does not change the schema of every area-keyed output at once. polity_coverage_gaps() reports the stand-in rows of a built table, and options(whep.polity_mapping_status = "flag") (or "status") carries the signal on the outputs themselves. Both are opt-in; the default is no extra column.

Examples

build_energy_co2_extension(example = TRUE)
#> # A tibble: 8 × 9
#>    year area_code polity_area_code reporting_polity_code reporting_polity_name  
#>   <int>     <int>            <int> <chr>                 <chr>                  
#> 1  2010        21               21 BRA-1909-2025         Brazil                 
#> 2  2010        21               21 BRA-1909-2025         Brazil                 
#> 3  2010       231              231 USA-1959-2025         United States of Ameri…
#> 4  2010       231              231 USA-1959-2025         United States of Ameri…
#> 5  2010       231              231 USA-1959-2025         United States of Ameri…
#> 6  2010       231              231 USA-1959-2025         United States of Ameri…
#> 7  2010       231              231 USA-1959-2025         United States of Ameri…
#> 8  2010       231              231 USA-1959-2025         United States of Ameri…
#> # ℹ 4 more variables: reporting_polity_has_geometry <lgl>, item_cbs_code <int>,
#> #   impact_u <dbl>, method_energy <chr>