R/calcFoodWasteAndSewage.R

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

#recycling of food waste and sewage?
calcFoodWasteAndSewage<-function(historic=TRUE){
  past<-findset("past") 
  mb<-calcOutput("FAOmassbalance",aggregate = FALSE)
  demand<-collapseNames(mb[,,"households"][,,c("nr")])
  getSets(demand)[[3]]<-"ItemCodeItem"
  
  # food waste should be estimated without using demand projections
  
  scenarios=readSource("Bodirsky2018",subtype="scenarios")
  scenarios<-toolHoldConstantBeyondEnd(scenarios)
  intake_shr = collapseNames(scenarios[,,"Intake (kcal/capita/day)"]/scenarios[,,"Demand for food (kcal/capita/day)"])
  intake_shr[intake_shr>1] <- 1
  
  if(historic){
    intake_shr=collapseNames(intake_shr[,getYears(demand),"SSP2"])
  } else {
    
    ###demand calculation could also move into a specific function.
    
    kap=findset("kap")
    processed=c("sugar","oils","alcohol")
    kst=findset("kst")
    future=setdiff(getYears(scenarios), getYears(demand))
    lastyear <- paste0("y",max(getYears(demand,as.integer = TRUE)))
    
    demand=add_dimension(demand,dim = 3.1,add = "scenario",nm="SSP2")
    demand=add_columns(demand, dim = 3.1,addnm = c("SSP1","SSP3","SSP4","SSP5"))
    demand[,,]=demand[,,"SSP2"]
    demand<-toolHoldConstantBeyondEnd(demand)
    
    
    demand[,future,kap]      = demand[,future,kap]            *collapseNames(scenarios[,future,"Demand for animal source foods (kcal/capita/day)"]/setYears(scenarios[,lastyear,"Demand for animal source foods (kcal/capita/day)"],NULL))
    demand[,future,processed]= demand[,future,processed]      *collapseNames(scenarios[,future,"Demand for empty calories (kcal/capita/day)"]/setYears(scenarios[,lastyear,"Demand for empty calories (kcal/capita/day)"],NULL))
    demand[,future,kst]      = demand[,future,kst]            *collapseNames(scenarios[,future,"Demand for food (kcal/capita/day)"]/setYears(scenarios[,lastyear,"Demand for food (kcal/capita/day)"],NULL))
    demand[,future,"others"] = demand[,future,"others"]       *collapseNames(scenarios[,future,"Demand for vegetables fruits and nuts (kcal/capita/day)"]/setYears(scenarios[,lastyear,"Demand for vegetables fruits and nuts (kcal/capita/day)"],NULL))
    
  }
  
  # assuming N:P ratio of 10:1 based on Moree et al (2013)
  #Moree, A. L., A. H. W. Beusen, A. F. Bouwman, and W. J. Willems. 2013. “Exploring Global Nitrogen and Phosphorus Flows in Urban Wastes during the Twentieth Century.” Global Biogeochemical Cycles 27 (3): 836–46. doi:10.1002/gbc.20072.
  demand<-mbind(add_dimension(demand,dim=3.1,nm="nr"),add_dimension(demand,dim=3.1,nm="p")/10)
  # not differentiated by product
  demand<-dimSums(demand,dim="ItemCodeItem")
  
  #waste_shr<-calcOutput("Demand",aggregate = FALSE)
  #waste_shr<-collapseNames(waste_shr[,,"waste_shr"][,past,"SSP2"])
  
  #urine:80% of intake for N, 62% for P (moree)
  urine<-new.magpie("GLO",NULL,c("nr","p"))
  urine[,,"nr"]<-0.8
  urine[,,"p"]<-0.62
  
  out<-mbind(
    add_dimension(demand*(1-intake_shr),dim = 3.1,nm = "hh_food_waste"),
    add_dimension(demand*(intake_shr)*urine,dim = 3.1,nm = "urine"),
    add_dimension(demand*(intake_shr)*(1-urine),dim = 3.1,nm = "feces")
  )
  
  # add recycling as feed, fertilizer
  
  return(list(x=out,
              weight=NULL,
              unit="Mt Nr, P",
              description="Further destiny of food")
  )    
}