R/calcGAINSEmi.R

In pik-piam/moinput: Model Operations Input Data Library

#' 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{ 
#' 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

  
  # 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 <- read.csv(toolMappingFile("sectoral", "mappingGAINSmixedtoREMIND17activities.csv"), 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])
  
  # 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,]) 
  
  x <- emi_gains
  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
  
  # 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 <- read.csv(toolMappingFile("sectoral", "mappingGAINSmixedtoREMIND17activities.csv"), 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])
  
  
  # 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,]) 
  
  w <- emi_gains
 
  
  x <- ef_gains
  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)
    
    x <- start_value_REMIND_regions
    unit = 'Mt'
    description = 'AP starting values for the first iteration of REMIND'
    weight = NULL
    
  }
  
  
  return(list(x=x,
              weight=weight,
              unit=unit,
              description=description))
  
}