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Estimate direct soil N2O emissions from applied nitrogen.

Source: R/n_balance_losses.R
calculate_soil_n2o.Rd

Four emission-factor regimes for direct nitrous oxide from nitrogen applied to soil, n2o_direct_n_t = n_input_t * ef.

"ipcc2019" (the default) is the IPCC 2019 Tier 1 wet/dry disaggregation, keyed on each row's moisture_regime ("wet" or "dry"), with every factor read from ipcc_2019_soil_n_ef:

  • EF1 (IPCC 2019 Refinement Vol 4 Ch 11 Table 11.1 (Updated) p. 11.13): 0.016 for synthetic fertiliser and 0.006 for every other N input in wet climates, 0.005 for all N inputs in dry climates. Stamped "ipcc2019_wet_dry".

  • EF1FR (same table): 0.004, the aggregated flooded-rice factor, on every rice row in both moisture and both water regimes. No drainage layer exists for its continuous-flooding (0.003) versus drained (0.005) split, and upland rice, which the table prices with EF1, has no layer of its own either. Rice rows are those whose item_cbs_code is the CBS item of a production item classed Crop_irrig == "Rice" in items_prod_full (2807, rice and products). Stamped "ipcc2019_ef1fr".

  • EF3PRP (same table) on excreta deposited by grazing animals, as the N-weighted blend excreta_cpp_share * EF3PRP,CPP + (1 - excreta_cpp_share) * EF3PRP,SO, with EF3PRP,CPP 0.006 wet and 0.002 dry for cattle, poultry and pigs and EF3PRP,SO 0.003 for sheep and other animals. Excreta keep this factor on a rice row too: Equation 11.1 prices urine and dung deposited by grazing animals apart from the N applied to the crop. A row labelled by species reads its share from the label: 1 on "Excreta_cattle_monog", 0 on "Excreta_other". Stamped "ipcc2019_ef3prp_blend".

  • Excreta labelled so only as the fallback of a manure-type split (method_excreta_species == "fallback_label_no_species") is collected manure applied to the land, not grazing deposition: it takes the factor of applied manure on its row (EF1 for other N inputs, EF1FR on a rice item), whatever its missing species mix. Stamped "ipcc2019_fallback_applied_manure".

"ipcc2019_atl_med" is the earlier IPCC 2019 Tier 1 option keyed on the Atlantic/Mediterranean climate instead: the n2o_efs_disaggregated table's two climate-level rows (irrig_type == "Tier_1" for ATL, irrig_type == "Med_average" for MED, 0.010 and 0.005), whatever the input. "aguilera" is a finer Mediterranean-calibrated disaggregation (Cayuela et al. 2017), selectable where its irrig_type/fert_type granularity is available and its regional emission factors apply: ef * mf, ef from n2o_efs_disaggregated on (irrig_type, climate), mf from fertiliser_n2o_modifiers on (fert_type, climate). An "Excreta" row, whose species are carried as a share rather than in its label, takes excreta_cpp_share * mf(Excreta_cattle_monog) + (1 - excreta_cpp_share) * mf(Excreta_other), stamped "aguilera_excreta_blend"; a fallback-labelled "Excreta" row, which is collected manure applied to the land and not grazing deposition, takes mf(Solid) (0.38 on MED, 0.60 on ATL), stamped "aguilera_fallback_applied_manure". "ipcc2006" uses the n2o_efs_ipcc2006 table (IPCC 2006 Tier 1 defaults, flat 0.010 except flooded rice 0.003), keyed like "aguilera" on (irrig_type, climate) with no mf.

Usage

calculate_soil_n2o(
  x,
  method = c("ipcc2019", "ipcc2019_atl_med", "aguilera", "ipcc2006"),
  example = FALSE
)

Source

IPCC (2019) 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Vol 4, Ch 11, Table 11.1 (Updated), p. 11.13.

Arguments

x

A tibble with n_input_t. method = "ipcc2019" requires fert_type ("Synthetic", "Solid", "Liquid", "Human", "Recycling", "SOM" or an excreta label: "Excreta", "Excreta_cattle_monog", "Excreta_other"), item_cbs_code and moisture_regime, plus excreta_cpp_share on "Excreta" rows. "ipcc2019_atl_med" requires climate. "aguilera" and "ipcc2006" require climate and irrig_type, and aguilera fert_type (and excreta_cpp_share on "Excreta" rows).

method

"ipcc2019" (default, IPCC 2019 Tier 1 wet/dry), "ipcc2019_atl_med" (IPCC 2019 Tier 1 on ATL/MED), "aguilera" (Mediterranean-calibrated) or "ipcc2006" (IPCC 2006 Tier 1).

example

If TRUE, return a small fixture instead of computing from x. Defaults to FALSE.

Value

x with n2o_direct_n_t and method_soil_n2o appended. method_soil_n2o names the factor each row took: the method name, or for "ipcc2019" one of "ipcc2019_wet_dry", "ipcc2019_ef1fr", "ipcc2019_ef3prp_blend", "ipcc2019_fallback_applied_manure", and for "aguilera" "aguilera_excreta_blend" on blended excreta rows and "aguilera_fallback_applied_manure" on fallback-labelled ones.

Details

method = "ipcc2019" aborts when moisture_regime is absent (whep_missing_moisture_regime), missing on any row (whep_moisture_regime_na, naming the count) or neither "wet" nor "dry" (whep_moisture_regime_value): which class a row belongs to is decided where the drivers are built, not here. An excreta row carrying N without an excreta_cpp_share aborts (whep_excreta_share_missing), as does a share outside 0 to 1 (whep_excreta_share_invalid) and a share on a species-labelled row that contradicts its label (whep_excreta_share_label_conflict); a row with no excreta N emits nothing whatever its mix. A fert_type with no direct factor in Equation 11.1 ("BNF", "Deposition") aborts (whep_soil_n2o_fert_type).

Examples

calculate_soil_n2o(example = TRUE)
#> # A tibble: 4 × 7
#>   n_input_t fert_type item_cbs_code moisture_regime excreta_cpp_share
#>       <dbl> <chr>             <int> <chr>                       <dbl>
#> 1        10 Synthetic          2511 wet                          NA  
#> 2        10 Solid              2511 dry                          NA  
#> 3        10 Synthetic          2807 wet                          NA  
#> 4        10 Excreta            3000 wet                           0.5
#> # ℹ 2 more variables: n2o_direct_n_t <dbl>, method_soil_n2o <chr>