Calculate emissions based on arithmetic means

TBD

Usage

fct_arithmetic_mean(.ad, .cs, .usr, .time)

Arguments

.ad

Activity Data input table for the shiny app (AD_lu_transitions)

.cs

Carbon Stock input table for the shiny app (c_stocks)

.usr

User inputs' table for the shiny app (user_inputs). Contains the number of iterations of the MCS, carbon fraction if needed and if truncated PDFs should be used when necessary.

.time

the 'time' table from the tool input file (see template)

Value

A data frame with arithmetic mean of CO2 emissions for each land use transition, REDD+ activity or emission reductions level.

Examples

library(readxl)
library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union
library(mocaredd)

path <- system.file("extdata/example2-with-sims.xlsx", package = "mocaredd")

cs <- read_xlsx(path = path, sheet = "c_stocks", na = "NA")
ad <- read_xlsx(path = path, sheet = "AD_lu_transitions", na = "NA")
usr <- read_xlsx(path = path, sheet = "user_inputs", na = "NA")
time <- read_xlsx(path = path, sheet = "time_periods", na = "NA")

time_clean <- time |> dplyr::mutate(nb_years = year_end - year_start + 1)

res <- fct_arithmetic_mean(.ad = ad, .cs = cs, .usr = usr, .time = time_clean)
head(res$emissions)
#> # A tibble: 2 × 6
#>   period_type year_start year_end nb_years sim_no    E_sim
#>   <chr>            <dbl>    <dbl>    <dbl>  <int>    <dbl>
#> 1 REF               2016     2020        5      1 21036471
#> 2 MON1              2021     2022        2      1  7621570
res$gg_emissions