Fixed a big in data loading

Emission_factors/N2_N20_emission.R

@@ -5,8 +5,7 @@ easypackages::packages(c("tidyverse", "readxl", "openxlsx", "rio", "xlsx", "sf",
                          "BBmisc", "quanteda", "Ryacas"))
 
 # Load data  --------------------------------------------------------------
-dat_n2 = read_csv("Input_data/N2_N20_ratio.csv")
-
+dat_n2 = read_csv("Input_data/N2_N20_ratio_input.csv")
 # functions ---------------------------------------------------------------
 # converting letters to numbers for indexing
 # letter2number = function(x) {utf8ToInt(x) - utf8ToInt("a") + 1L}
@@ -46,7 +45,7 @@ ratio_grass_forest = as.numeric(dat_shrt$ratio_N2O_to_N2O_N2[351])
 # the soil types were mapped based on websites (perfereably university databases/articles/etc.)
 # sources are indicated in the dataset 
 
-dat_soilmap = read_csv("Input_data/soil_type_map.csv") %>%  
+dat_soilmap = read_csv("Input_data/soil_type_map.csv") #%>%  
   dplyr::select(soil_type:Cifos_soil)