GAINS data update including primary PM25

.buildlibrary

@@ -1,4 +1,4 @@
-ValidationKey: '15503740'
+ValidationKey: '15696130'
 AcceptedWarnings:
 - 'Warning: package ''.*'' was built under R version'
 - 'Warning: namespace ''.*'' is not available and has been replaced'

.gitignore

@@ -3,3 +3,6 @@
 .RData
 .Ruserdata
 fe_variables.csv
+.github/workflows/lucode2-check.yaml
+.buildlibrary
+

.zenodo.json

@@ -1,6 +1,6 @@
 {
   "title": "mrremind: MadRat REMIND Input Data Package",
-  "version": "0.82.0",
+  "version": "0.83.0",
   "description": "<p>The mrremind packages contains data preprocessing for the REMIND model.<\/p>",
   "creators": [
     {

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: mrremind
 Type: Package
 Title: MadRat REMIND Input Data Package
-Version: 0.82.0
-Date: 2021-10-07
+Version: 0.83.0
+Date: 2021-10-11
 Authors@R: c(person("Lavinia", "Baumstark", email = "lavinia@pik-potsdam.de", role = c("aut","cre")),
              person("Renato", "Rodrigues", role = "aut"),
              person("Antoine", "Levesque", role = "aut"),

R/calcGAINSEmi.R

@@ -1,101 +1,99 @@
 #' Calculate air pollution emissions and emission factors from GAINS data
-#' 
+#'
 #' Provides input data for exoGAINSAirpollutants.R
-#' 
-#' 
+#'
+#'
 #' @return Emissions and emission factors
 #' @author Sebastian Rauner
 #' @param subtype "emission_factors", "emissions","emissions_starting_values"
 #' @seealso \code{\link{calcOutput}}
 #' @examples
-#' 
-#' \dontrun{ 
+#' \dontrun{
 #' calcOutput("calcGAINSEmi")
 #' }
+#'
+calcGAINSEmi <- function(subtype = "emissions") {
 
+  if (!(subtype %in% c("emission_factors", "emissions", "emissions_starting_values"))) stop('subtype must be in c("emission_factors", "emissions","emissions_starting_values")')
+
+  if (subtype == "emissions") {
+  emi_gains_ext_in <- calcOutput("GAINS", subtype = "emissions", sectoral_resolution = "extended", aggregate = FALSE) # in Mt
+  emi_gains_agg_in <- calcOutput("GAINS", subtype = "emissions", sectoral_resolution = "aggregated", aggregate = FALSE) # in Mt
 
-calcGAINSEmi <- function(subtype="emissions") {
-
-  if (!(subtype %in% c("emission_factors", "emissions","emissions_starting_values"))) stop('subtype must be in c("emission_factors", "emissions","emissions_starting_values")')
-
-  if(subtype=="emissions") {
-  emi_gains_ext_in <- calcOutput("GAINS",subtype = "emissions",sectoral_resolution="extended",aggregate=FALSE) # in Mt
-  emi_gains_agg_in <- calcOutput("GAINS",subtype = "emissions",sectoral_resolution="aggregated",aggregate=FALSE) # in Mt
 
-
   # mainly: combine extended and aggregated GAINS data by appending
   # waste sectors from extended to aggregated and then using
   # aggregated only
-  
+
   # construct mappings: add waste from extended mapping to aggregated mapping
-  map_mix <- toolGetMapping(type = "sectoral", name = "mappingGAINSmixedtoREMIND17activities.csv")
-  map_waste <- map_mix[map_mix$GAINS %in% c("Waste_Solid_Industrial","Waste_Solid_Municipal","Waste_Water_Industrial","Waste_Water_Municipal"),]
-  
+  map_mix <- read.csv(toolGetMapping("mappingGAINSmixedtoREMIND17activities.csv", type = "sectoral"), stringsAsFactors = FALSE)
+  map_waste <- map_mix[map_mix$GAINS %in% c("Waste_Solid_Industrial", "Waste_Solid_Municipal", "Waste_Water_Industrial", "Waste_Water_Municipal"), ]
+
   # append waste ef and emi from extended to aggregated
-  emi_gains <- mbind(emi_gains_agg_in,emi_gains_ext_in[,,map_waste$GAINS])
-  
+  emi_gains <- mbind(emi_gains_agg_in, emi_gains_ext_in[, , map_waste$GAINS])
+
   # many of the 2005 values seem to be outliers
   warning("GAINS data for 2005 was set to 2010 values (for emi and ef) because 2005 often seems to be an outlier!!!\n")
-  emi_gains[,2005,] <- setYears(emi_gains[,2010,]) 
-  
+  emi_gains[, 2005, ] <- setYears(emi_gains[, 2010, ])
+
   x <- emi_gains
-  unit = 'Mt'
-  description = 'Emissions from GAINS for all CEDS setors execpt aviation and shipping'
-  weight = NULL
-  
+  unit <- "Mt"
+  description <- "Emissions from GAINS for all CEDS setors execpt aviation and shipping"
+  weight <- NULL
+
                             }
-  
-  if(subtype=="emission_factors") {
-  ef_gains_ext_in  <- calcOutput("GAINS",subtype = "emission_factors",sectoral_resolution="extended",aggregate=FALSE) # in Tg/TWa
-  ef_gains_agg_in  <- calcOutput("GAINS",subtype = "emission_factors",sectoral_resolution="aggregated",aggregate=FALSE) # in Tg/TWa
-  emi_gains_ext_in <- calcOutput("GAINS",subtype = "emissions",sectoral_resolution="extended",aggregate=FALSE) # in Mt
-  emi_gains_agg_in <- calcOutput("GAINS",subtype = "emissions",sectoral_resolution="aggregated",aggregate=FALSE) # in Mt
-  
+
+  if (subtype == "emission_factors") {
+  ef_gains_ext_in  <- calcOutput("GAINS", subtype = "emission_factors", sectoral_resolution = "extended", aggregate = FALSE) # in Tg/TWa
+  ef_gains_agg_in  <- calcOutput("GAINS", subtype = "emission_factors", sectoral_resolution = "aggregated", aggregate = FALSE) # in Tg/TWa
+  emi_gains_ext_in <- calcOutput("GAINS", subtype = "emissions", sectoral_resolution = "extended", aggregate = FALSE) # in Mt
+  emi_gains_agg_in <- calcOutput("GAINS", subtype = "emissions", sectoral_resolution = "aggregated", aggregate = FALSE) # in Mt
+
   # mainly: combine extended and aggregated GAINS data by appending
   # waste sectors from extended to aggregated and then using
   # aggregated only
-  
+
   # construct mappings: add waste from extended mapping to aggregated mapping
-  map_mix <- toolGetMapping(type = "sectoral", name = "mappingGAINSmixedtoREMIND17activities.csv")
-  map_waste <- map_mix[map_mix$GAINS %in% c("Waste_Solid_Industrial","Waste_Solid_Municipal","Waste_Water_Industrial","Waste_Water_Municipal"),]
-  
+  map_mix <- read.csv(toolGetMapping("mappingGAINSmixedtoREMIND17activities.csv", type = "sectoral"), stringsAsFactors = FALSE)
+  map_waste <- map_mix[map_mix$GAINS %in% c("Waste_Solid_Industrial", "Waste_Solid_Municipal", "Waste_Water_Industrial", "Waste_Water_Municipal"), ]
+
   # append waste ef and emi from extended to aggregated
-  ef_gains  <- mbind(ef_gains_agg_in,  ef_gains_ext_in[,,map_waste$GAINS])
-  emi_gains <- mbind(emi_gains_agg_in,emi_gains_ext_in[,,map_waste$GAINS])
-  
-  
+  ef_gains  <- mbind(ef_gains_agg_in,  ef_gains_ext_in[, , map_waste$GAINS])
+  emi_gains <- mbind(emi_gains_agg_in, emi_gains_ext_in[, , map_waste$GAINS])
+
+
   # many of the 2005 values seem to be outliers
   warning("GAINS data for 2005 was set to 2010 values (for emi and ef) because 2005 often seems to be an outlier!!!\n")
-  ef_gains[,2005,]  <- setYears(ef_gains[,2010,])
-  emi_gains[,2005,] <- setYears(emi_gains[,2010,]) 
-  
+  ef_gains[, 2005, ]  <- setYears(ef_gains[, 2010, ])
+  emi_gains[, 2005, ] <- setYears(emi_gains[, 2010, ])
+
   w <- emi_gains
- 
-  
+
+
   x <- ef_gains
-  unit = 'Mt/TWa'
-  description = 'Emission factors from GAINS for all CEDS setors execpt aviation and shipping'
-  weight=w
-     
+  unit <- "Mt/TWa"
+  description <- "Emission factors from GAINS for all CEDS setors execpt aviation and shipping"
+  weight <- w
+
   }
-
 
-  if(subtype=="emissions_starting_values") {
-
-
-    start_value_REMIND_regions <- readSource(type="REMIND_11Regi", subtype="AP_starting_values", convert = TRUE)
-
+
+  if (subtype == "emissions_starting_values") {
+
+
+    start_value_REMIND_regions <- readSource(type = "REMIND_11Regi", subtype = "AP_starting_values", convert = TRUE)
+
     x <- start_value_REMIND_regions
-    unit = 'Mt'
-    description = 'AP starting values for the first iteration of REMIND'
-    weight = NULL
-    
+    unit <- "Mt"
+    description <- "AP starting values for the first iteration of REMIND"
+    weight <- NULL
+
   }
-  
-  
-  return(list(x=x,
-              weight=weight,
-              unit=unit,
-              description=description))
-  
+
+
+  return(list(x = x,
+              weight = weight,
+              unit = unit,
+              description = description))
+
 }