R/calcEmissions.R
In pik-piam/moinput: Model Operations Input Data Library
Defines functions
calcEmissions
#' @importFrom magclass setNames getNames<-
#' @importFrom utils read.csv2
#' @importFrom dplyr filter_ mutate_
calcEmissions <- function(datasource="CEDS16") {
if (datasource == "CEDS16") {
# read CEDS emissions data from sources
bc <- readSource("CEDS",subtype="BC")
ch4 <- readSource("CEDS",subtype="CH4")
co <- readSource("CEDS",subtype="CO")
co2 <- readSource("CEDS",subtype="CO2")#,convert = FALSE)
n2o <- readSource("CEDS",subtype="N2O")
nh3 <- readSource("CEDS",subtype="NH3")
nox <- readSource("CEDS",subtype="NOx")
nmvoc <- readSource("CEDS",subtype="NMVOC")
oc <- readSource("CEDS",subtype="OC")
so2 <- readSource("CEDS",subtype="SO2")
y <- Reduce(intersect,list(getYears(bc),
getYears(ch4),
getYears(co),
getYears(co2),
getYears(n2o),
getYears(nh3),
getYears(nox),
getYears(nmvoc),
getYears(oc),
getYears(so2)))
emi <- mbind(bc[,y,],ch4[,y,],co[,y,],co2[,y,],n2o[,y,],nh3[,y,],nox[,y,],nmvoc[,y,],oc[,y,],so2[,y,]) / 1000 # kt -> Mt
rm(bc,ch4,co,co2,n2o,nh3,nox,nmvoc,oc,so2)
if (any(!emi[,,"6B_Other-not-in-total"]==0)) cat("CEDS59 sector 6B_Other-not-in-total was removed although it contains data! Please check CEDS source files.\n")
emi <- emi[,,"6B_Other-not-in-total",invert=TRUE]
# aggregate and rename CEDS59 sectors to CEDS16 sectors
map_CEDS59_to_CEDS16 <- read.csv(toolMappingFile("sectoral", "mappingCEDS59toCEDS16.csv"), stringsAsFactors=FALSE)
tmp <- toolAggregate(x=emi,weight = NULL, dim=3.1, rel = map_CEDS59_to_CEDS16, from="CEDS59",to="CEDS16")
# rename emissions according to map
map <- c(BC="BC",CH4="CH4",CO="CO",CO2="CO2",N2O="N2O",NH3="NH3",NOx="NOx",NMVOC="VOC",OC="OC",SO2="SO2")
getNames(tmp,dim=2) <- map[getNames(tmp,dim=2)]
# remove third entry "kt" in data dimension
tmp <- collapseNames(tmp,collapsedim = 3)
} else if (datasource == "CEDS2REMIND") {
# read CEDS emissions data from sources
bc <- readSource("CEDS",subtype="BC")
ch4 <- readSource("CEDS",subtype="CH4")
co <- readSource("CEDS",subtype="CO")
co2 <- readSource("CEDS",subtype="CO2")#,convert = FALSE)
n2o <- readSource("CEDS",subtype="N2O")
nh3 <- readSource("CEDS",subtype="NH3")
nox <- readSource("CEDS",subtype="NOx")
nmvoc <- readSource("CEDS",subtype="NMVOC")
oc <- readSource("CEDS",subtype="OC")
so2 <- readSource("CEDS",subtype="SO2")
y <- Reduce(intersect,list(getYears(bc),
getYears(ch4),
getYears(co),
getYears(co2),
getYears(n2o),
getYears(nh3),
getYears(nox),
getYears(nmvoc),
getYears(oc),
getYears(so2)))
emi <- mbind(bc[,y,],ch4[,y,],co[,y,],co2[,y,],n2o[,y,],nh3[,y,],nox[,y,],nmvoc[,y,],oc[,y,],so2[,y,]) / 1000 # kt -> Mt
rm(bc,ch4,co,co2,n2o,nh3,nox,nmvoc,oc,so2)
if (any(!emi[,,"6B_Other-not-in-total"]==0)) cat("CEDS59 sector 6B_Other-not-in-total was removed although it contains data! Please check CEDS source files.\n")
emi <- emi[,,"6B_Other-not-in-total",invert=TRUE]
# aggregate and rename CEDS59 sectors to CEDS16 sectors
map_CEDS59_to_CEDS16 <- read.csv(toolMappingFile("sectoral", "mappingCEDS59toREMINDreporting.csv"), stringsAsFactors=FALSE)
emi <- toolAggregate(x=emi,weight = NULL, dim=3.1, rel = map_CEDS59_to_CEDS16, from="CEDS59",to="REMIND")
# rename emissions according to map (currently only relevant for VOC)
map <- c(BC="BC",CH4="CH4",CO="CO",CO2="CO2",N2O="N2O",NH3="NH3",NOx="NOx",NMVOC="VOC",OC="OC",SO2="SO2")
getNames(emi,dim=2) <- map[getNames(emi,dim=2)]
# remove third entry "kt" in data dimension
emi <- collapseNames(emi,collapsedim = 3)
# sectoral sums
emi <- add_columns(emi,"Energy|Demand|Transportation",dim=3.1)
emi[,,"Energy|Demand|Transportation"] <- emi[,, "Energy|Demand|Transportation|Aviation"] +
emi[,,"Energy|Demand|Transportation|Ground Transportation"] +
emi[,,"Energy|Demand|Transportation|International Shipping"]
emi <- add_columns(emi,"Energy|Supply",dim=3.1)
emi[,,"Energy|Supply"] <- emi[,,"Energy|Supply|Electricity"] +
emi[,,"Energy|Supply|Heat"] +
emi[,,"Energy|Supply|Fuel Production"]
emi <- add_columns(emi,"Energy|Demand",dim=3.1)
emi[,,"Energy|Demand"] <- emi[,,"Energy|Demand|Transportation"] +
emi[,,"Energy|Demand|Residential and Commercial"] +
emi[,,"Energy|Demand|Industry"]
emi <- add_columns(emi,"Energy",dim=3.1)
emi[,,"Energy"] <- emi[,,"Energy|Demand"] +
emi[,,"Energy|Supply"]
emi <- add_columns(emi,"Energy Supply and Demand",dim=3.1)
emi[,,"Energy Supply and Demand"] <- emi[,,"Energy"]
emi <- add_columns(emi,"Energy and Industrial Processes",dim=3.1)
emi[,,"Energy and Industrial Processes"] <- emi[,,"Energy"] +
emi[,,"Industrial Processes"]
emi <- add_columns(emi,"Land Use",dim=3.1)
emi[,,"Land Use"] <- emi[,,"Land Use|Agriculture and Biomass Burning"] +
emi[,,"Land Use|Forest Burning"] +
emi[,,"Land Use|Grassland Burning"]
emi <- add_columns(emi,"Total",dim=3.1)
emi[,,"Total"] <- emi[,,"Energy"] +
emi[,,"Industrial Processes"] +
emi[,,"Land Use"] +
emi[,,"Solvents"] +
emi[,,"Waste"]
# get variables names right
emi[,,"N2O"] <- emi[,,"N2O"] * 1000 # Mt -> kt
# change order, add "Emissions|", and reduce to a single dimension by replacing dots: Waste.SO2.harm -> Emissions|SO2|Waste|harm
tmp <- gsub("^([^\\.]*)\\.(.*$)","Emi|\\2|\\1 (Mt \\2/yr)",getNames(emi))
# remove "Total" from variable name
tmp <- gsub("\\|Total","",tmp)
tmp <- gsub("Mt N2O","kt N2O",tmp)
tmp <- gsub("\\|SO2\\|","\\|Sulfur\\|",tmp)
# Add full scenario name
getNames(emi) <- tmp
getSets(emi) <- c("region","year","variable")
tmp <- emi
# } else if (datasource == "EDGAR") {
# # Allocation to sectors the same for all pollutants
# # read EDGAR emissions from sources
# co <- readSource("EDGAR",subtype="CO")
# co <- add_dimension(co, dim=3.2, add="em",nm="CO")
# voc <- readSource("EDGAR",subtype="VOC")
# voc <- add_dimension(voc, dim=3.2, add="em",nm="VOC")
# nox <- readSource("EDGAR",subtype="NOx")
# nox <- add_dimension(nox, dim=3.2, add="em",nm="NOx")
# nh3 <- readSource("EDGAR",subtype="NH3")
# nh3 <- add_dimension(nh3, dim=3.2, add="em",nm="NH3")
# so2 <- readSource("EDGAR",subtype="SO2")
# so2 <- add_dimension(so2, dim=3.2, add="em",nm="SO2")
# pm10 <- readSource("EDGAR",subtype="PM10")
# pm10 <- add_dimension(pm10, dim=3.2, add="em",nm="PM10")
#
# edgar <- mbind(co,nox,so2,voc,nh3,pm10) / 1000 # kt = Gg -> Mt
#
# map <- c(CO="CO",NOx="NOx",SO2="Sulfur",VOC="VOC",NH3="NH3",PM10="PM10")
# tmp <- NULL
# for (i in getNames(edgar,dim=2)) {
# vars <- c("1A2","2A1","2A2","2A7","2B","2C","2D","2E","2F1","2F2","2F3","2F4","2F5","2F7","2F8","2F9","2G")
# tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Industry (Mt/yr)")))
# vars <- c("1A4")
# tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Residential and Commercial (Mt/yr)")))
# #vars <- c("1C1","1A3a", "1A3b", "1A3c", "1A3d", "1A3e","1C2")
# #tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Transportation (Mt/yr)")))
# vars <- c("1C1")
# tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Transportation|Aviation (Mt/yr)")))
# vars <- c("1A3a", "1A3b", "1A3c", "1A3d", "1A3e")
# tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Transportation|Ground Transportation (Mt/yr)")))
# vars <- c("1C2")
# tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Transportation|International Shipping (Mt/yr)")))
# vars <- c("1A1a","1A1bc","1B1","1B2")
# tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Supply (Mt/yr)")))
# vars <- c("4F")
# tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Land Use|Agricultural Waste Burning (Mt/yr)")))
# vars <- c("4A","4B","4C","4D1","4D2","4D3","4D4")
# tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Land Use|Agriculture (Mt/yr)")))
# vars <- c("5A", "5D", "5F", "5F2")
# tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Land Use|Forest Burning (Mt/yr)")))
# vars <- c("3A", "3B", "3C", "3D")
# tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Solvents (Mt/yr)")))
# vars <- c("6A","6B","6C","6D")
# tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Waste (Mt/yr)")))
# }
#
} else if (datasource == "EDGAR") {
# read EDGAR emissions from sources
co <- readSource("EDGAR",subtype="CO")
co <- add_dimension(co, dim=3.2, add="em",nm="CO")
voc <- readSource("EDGAR",subtype="VOC")
voc <- add_dimension(voc, dim=3.2, add="em",nm="VOC")
nox <- readSource("EDGAR",subtype="NOx")
nox <- add_dimension(nox, dim=3.2, add="em",nm="NOx")
nh3 <- readSource("EDGAR",subtype="NH3")
nh3 <- add_dimension(nh3, dim=3.2, add="em",nm="NH3")
so2 <- readSource("EDGAR",subtype="SO2")
so2 <- add_dimension(so2, dim=3.2, add="em",nm="SO2")
pm10 <- readSource("EDGAR",subtype="PM10")
pm10 <- add_dimension(pm10, dim=3.2, add="em",nm="PM10")
edgar <- mbind(co,nox,so2,voc,nh3,pm10) / 1000 # kt = Gg -> Mt
# Allocation of pollutants to sectors: special treatment for solvents
map <- c(CO="CO",NOx="NOx",SO2="Sulfur",VOC="VOC",NH3="NH3",PM10="PM10")
tmp <- NULL
for (i in names(map)) {
vars <- c("1A4")
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Residential and Commercial (Mt/yr)")))
#vars <- c("1C1","1A3a", "1A3b", "1A3c", "1A3d", "1A3e","1C2")
#tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Transportation (Mt/yr)")))
vars <- c("1C1")
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Transportation|Aviation (Mt/yr)")))
vars <- c("1A3a", "1A3b", "1A3c", "1A3d", "1A3e")
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Transportation|Ground Transportation (Mt/yr)")))
vars <- c("1C2")
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Transportation|International Shipping (Mt/yr)")))
vars <- c("1A1a","1A1bc","1B1","1B2")
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Supply (Mt/yr)")))
vars <- c("4F")
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Land Use|Agricultural Waste Burning (Mt/yr)")))
vars <- c("4A","4B","4C","4D1","4D2","4D3","4D4")
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Land Use|Agriculture (Mt/yr)")))
vars <- c("5A", "5D", "5F", "5F2")
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Land Use|Forest Burning (Mt/yr)")))
vars <- c("6A","6B","6C","6D")
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Waste (Mt/yr)")))
}
# no extrawurst for voc
map <- c(VOC="VOC")
for (i in names(map)) {
vars <- c("1A2","2A1","2A2","2A7","2B","2C","2D","2E","2F1","2F2","2F3","2F4","2F5","2F7","2F8","2F9","2G")
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Industry (Mt/yr)")))
vars <- c("3A", "3B", "3C", "3D")
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Solvents (Mt/yr)")))
}
# extrawurst for everything but voc: industry = industry + solvents
map <- c(CO="CO",NOx="NOx",SO2="Sulfur",NH3="NH3",PM10="PM10")
for (i in names(map)) {
vars <- c("1A2","2A1","2A2","2A7","2B","2C","2D","2E","2F1","2F2","2F3","2F4","2F5","2F7","2F8","2F9","2G","3A", "3B", "3C", "3D")
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Industry (Mt/yr)")))
# add zero dummy or Solvents
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1)*0, paste0("Emissions|",map[i],"|Solvents (Mt/yr)")))
}
} else if (datasource == "LIMITS") {
# read LIMITS emissions from sources
em_limits <- readSource("LIMITS", subtype="emissions")
em_limits <- collapseNames(em_limits[,,"kt"][,,"CLE"][,,"Unattributed", invert=TRUE])
getNames(em_limits, dim=2)[which(getNames(em_limits, dim=2) == "NOX")] <- "NOx"
map <- read.csv2(toolMappingFile("sectoral", "mappingLIMITSsectorstoREMINDsectors.csv"), stringsAsFactors=TRUE)
em_limits[is.na(em_limits)] <- 0.0
tmp <- NULL
for (kap in getNames(em_limits, dim=2)) {
tmp_limits <- collapseNames(em_limits[,,kap])
tmp_map <- map %>%
filter_(~limits_sector %in% getNames(tmp_limits, dim=1)) %>%
mutate_(remind_sector = ~paste(sub("POLLUTANT", kap, remind_sector), "(Mt/yr)"))
tmp <- mbind(tmp, toolAggregate(tmp_limits, tmp_map, dim=3.1))
}
tmp <- tmp / 1000 # kt = Gg -> Mt
#tmp <- tmp[,2005,]
} else if (datasource == "ECLIPSE") {
# read ECLIPSE emissions from sources
em_eclipse <- readSource("ECLIPSE", subtype="emissions.aggregated")
em_eclipse <- collapseNames(em_eclipse[,,"CLE"])
#map <- read.csv(toolMappingFile("sectoral", "mappingECLIPSEtoAggREMINDsectors.csv"), stringsAsFactors=TRUE)
map <- read.csv2(toolMappingFile("sectoral", "mappingECLIPSEsectorstoREMINDsectors.csv"), stringsAsFactors=TRUE)
em_eclipse[is.na(em_eclipse)] <- 0.0
tmp <- NULL
for (kap in getNames(em_eclipse, dim=2)) {
tmp_eclipse <- collapseNames(em_eclipse[,,kap])
tmp_map <- map %>%
filter_(~eclipse_sector %in% getNames(tmp_eclipse, dim=1)) %>%
mutate_(remind_sector = ~paste(sub("POLLUTANT", kap, remind_sector), "(Mt/yr)"))
tmp <- mbind(tmp, toolAggregate(tmp_eclipse, tmp_map, dim=3.1))
}
tmp <- tmp / 1000 # kt = Gg -> Mt
#tmp <- tmp[,2005,]
} else if (datasource == "GFED") {
data <- readSource("GFED")
# aggregate gfed sectors to sectors of all other data
emi_subset <- c("SO2","OC","NOx","NH3","CO","BC")
tmp <- new.magpie(getRegions(data),getYears(data),c("agriwaste","forest","savannah"))
tmp <- add_dimension(tmp,add="emi",dim=3.1,nm=emi_subset)
tmp[,,"savannah"] <- data[,,"savanna"][,,emi_subset]
tmp[,,"agriwaste"] <- data[,,"agricultural_waste"][,,emi_subset]
tmp[,,"forest"] <- (data[,,"boreal"] + data[,,"temperate"] + data[,,"peat"] + data[,,"deforestation"])[,,emi_subset]
tmp[,,"CO"] <- tmp[,,"CO"] / 10 # 1E11g -> Mt
tmp[,,c("NH3","SO2","BC")] <- tmp[,,c("NH3","SO2","BC")] / 1000 # 1E9g -> Mt
tmp[,,c("NOx","OC")] <- tmp[,,c("NOx","OC")] / 100 # 1E10g -> Mt
getNames(tmp,dim=2)<- gsub("SO2","Sulfur",getNames(tmp,dim=2)) # rename SO2 -> Sulfur
} else if (datasource == "CDIAC") {
data <- readSource("CDIAC")
# omitting "PerCap"
map <- c(FFIC ="Fossil Fuels and Industry", # <--- old name. New name wil be: "Energy and Industrial Processes",
Solids ="Energy|Solids",
Liquids ="Energy|Liquids",
Gases ="Energy|Gases",
Cement ="Industrial Processes|Cement",
Flaring ="Energy|Flaring",
Bunker ="Energy|Bunkers")
tmp <- NULL
for (i in names(map)) {
tmp <- mbind(tmp, setNames(data[,,i],paste0("Emissions|CO2|",map[i]," (Mt/yr)")))
}
tmp <- tmp * 44/12 /1000 # from ktC -> MtCO2
}
return(list(x=tmp,
weight=NULL,
unit="Mt",
description="historic emissions in 1970-2014"))
}
pik-piam/moinput documentation built on June 9, 2020, 12:23 p.m.
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Defines functions calcEmissions
#' @importFrom magclass setNames getNames<-
#' @importFrom utils read.csv2
#' @importFrom dplyr filter_ mutate_
calcEmissions <- function(datasource="CEDS16") {
if (datasource == "CEDS16") {
# read CEDS emissions data from sources
bc <- readSource("CEDS",subtype="BC")
ch4 <- readSource("CEDS",subtype="CH4")
co <- readSource("CEDS",subtype="CO")
co2 <- readSource("CEDS",subtype="CO2")#,convert = FALSE)
n2o <- readSource("CEDS",subtype="N2O")
nh3 <- readSource("CEDS",subtype="NH3")
nox <- readSource("CEDS",subtype="NOx")
nmvoc <- readSource("CEDS",subtype="NMVOC")
oc <- readSource("CEDS",subtype="OC")
so2 <- readSource("CEDS",subtype="SO2")
y <- Reduce(intersect,list(getYears(bc),
getYears(ch4),
getYears(co),
getYears(co2),
getYears(n2o),
getYears(nh3),
getYears(nox),
getYears(nmvoc),
getYears(oc),
getYears(so2)))
emi <- mbind(bc[,y,],ch4[,y,],co[,y,],co2[,y,],n2o[,y,],nh3[,y,],nox[,y,],nmvoc[,y,],oc[,y,],so2[,y,]) / 1000 # kt -> Mt
rm(bc,ch4,co,co2,n2o,nh3,nox,nmvoc,oc,so2)
if (any(!emi[,,"6B_Other-not-in-total"]==0)) cat("CEDS59 sector 6B_Other-not-in-total was removed although it contains data! Please check CEDS source files.\n")
emi <- emi[,,"6B_Other-not-in-total",invert=TRUE]
# aggregate and rename CEDS59 sectors to CEDS16 sectors
map_CEDS59_to_CEDS16 <- read.csv(toolMappingFile("sectoral", "mappingCEDS59toCEDS16.csv"), stringsAsFactors=FALSE)
tmp <- toolAggregate(x=emi,weight = NULL, dim=3.1, rel = map_CEDS59_to_CEDS16, from="CEDS59",to="CEDS16")
# rename emissions according to map
map <- c(BC="BC",CH4="CH4",CO="CO",CO2="CO2",N2O="N2O",NH3="NH3",NOx="NOx",NMVOC="VOC",OC="OC",SO2="SO2")
getNames(tmp,dim=2) <- map[getNames(tmp,dim=2)]
# remove third entry "kt" in data dimension
tmp <- collapseNames(tmp,collapsedim = 3)
} else if (datasource == "CEDS2REMIND") {
# read CEDS emissions data from sources
bc <- readSource("CEDS",subtype="BC")
ch4 <- readSource("CEDS",subtype="CH4")
co <- readSource("CEDS",subtype="CO")
co2 <- readSource("CEDS",subtype="CO2")#,convert = FALSE)
n2o <- readSource("CEDS",subtype="N2O")
nh3 <- readSource("CEDS",subtype="NH3")
nox <- readSource("CEDS",subtype="NOx")
nmvoc <- readSource("CEDS",subtype="NMVOC")
oc <- readSource("CEDS",subtype="OC")
so2 <- readSource("CEDS",subtype="SO2")
y <- Reduce(intersect,list(getYears(bc),
getYears(ch4),
getYears(co),
getYears(co2),
getYears(n2o),
getYears(nh3),
getYears(nox),
getYears(nmvoc),
getYears(oc),
getYears(so2)))
emi <- mbind(bc[,y,],ch4[,y,],co[,y,],co2[,y,],n2o[,y,],nh3[,y,],nox[,y,],nmvoc[,y,],oc[,y,],so2[,y,]) / 1000 # kt -> Mt
rm(bc,ch4,co,co2,n2o,nh3,nox,nmvoc,oc,so2)
if (any(!emi[,,"6B_Other-not-in-total"]==0)) cat("CEDS59 sector 6B_Other-not-in-total was removed although it contains data! Please check CEDS source files.\n")
emi <- emi[,,"6B_Other-not-in-total",invert=TRUE]
# aggregate and rename CEDS59 sectors to CEDS16 sectors
map_CEDS59_to_CEDS16 <- read.csv(toolMappingFile("sectoral", "mappingCEDS59toREMINDreporting.csv"), stringsAsFactors=FALSE)
emi <- toolAggregate(x=emi,weight = NULL, dim=3.1, rel = map_CEDS59_to_CEDS16, from="CEDS59",to="REMIND")
# rename emissions according to map (currently only relevant for VOC)
map <- c(BC="BC",CH4="CH4",CO="CO",CO2="CO2",N2O="N2O",NH3="NH3",NOx="NOx",NMVOC="VOC",OC="OC",SO2="SO2")
getNames(emi,dim=2) <- map[getNames(emi,dim=2)]
# remove third entry "kt" in data dimension
emi <- collapseNames(emi,collapsedim = 3)
# sectoral sums
emi <- add_columns(emi,"Energy|Demand|Transportation",dim=3.1)
emi[,,"Energy|Demand|Transportation"] <- emi[,, "Energy|Demand|Transportation|Aviation"] +
emi[,,"Energy|Demand|Transportation|Ground Transportation"] +
emi[,,"Energy|Demand|Transportation|International Shipping"]
emi <- add_columns(emi,"Energy|Supply",dim=3.1)
emi[,,"Energy|Supply"] <- emi[,,"Energy|Supply|Electricity"] +
emi[,,"Energy|Supply|Heat"] +
emi[,,"Energy|Supply|Fuel Production"]
emi <- add_columns(emi,"Energy|Demand",dim=3.1)
emi[,,"Energy|Demand"] <- emi[,,"Energy|Demand|Transportation"] +
emi[,,"Energy|Demand|Residential and Commercial"] +
emi[,,"Energy|Demand|Industry"]
emi <- add_columns(emi,"Energy",dim=3.1)
emi[,,"Energy"] <- emi[,,"Energy|Demand"] +
emi[,,"Energy|Supply"]
emi <- add_columns(emi,"Energy Supply and Demand",dim=3.1)
emi[,,"Energy Supply and Demand"] <- emi[,,"Energy"]
emi <- add_columns(emi,"Energy and Industrial Processes",dim=3.1)
emi[,,"Energy and Industrial Processes"] <- emi[,,"Energy"] +
emi[,,"Industrial Processes"]
emi <- add_columns(emi,"Land Use",dim=3.1)
emi[,,"Land Use"] <- emi[,,"Land Use|Agriculture and Biomass Burning"] +
emi[,,"Land Use|Forest Burning"] +
emi[,,"Land Use|Grassland Burning"]
emi <- add_columns(emi,"Total",dim=3.1)
emi[,,"Total"] <- emi[,,"Energy"] +
emi[,,"Industrial Processes"] +
emi[,,"Land Use"] +
emi[,,"Solvents"] +
emi[,,"Waste"]
# get variables names right
emi[,,"N2O"] <- emi[,,"N2O"] * 1000 # Mt -> kt
# change order, add "Emissions|", and reduce to a single dimension by replacing dots: Waste.SO2.harm -> Emissions|SO2|Waste|harm
tmp <- gsub("^([^\\.]*)\\.(.*$)","Emi|\\2|\\1 (Mt \\2/yr)",getNames(emi))
# remove "Total" from variable name
tmp <- gsub("\\|Total","",tmp)
tmp <- gsub("Mt N2O","kt N2O",tmp)
tmp <- gsub("\\|SO2\\|","\\|Sulfur\\|",tmp)
# Add full scenario name
getNames(emi) <- tmp
getSets(emi) <- c("region","year","variable")
tmp <- emi
# } else if (datasource == "EDGAR") {
# # Allocation to sectors the same for all pollutants
# # read EDGAR emissions from sources
# co <- readSource("EDGAR",subtype="CO")
# co <- add_dimension(co, dim=3.2, add="em",nm="CO")
# voc <- readSource("EDGAR",subtype="VOC")
# voc <- add_dimension(voc, dim=3.2, add="em",nm="VOC")
# nox <- readSource("EDGAR",subtype="NOx")
# nox <- add_dimension(nox, dim=3.2, add="em",nm="NOx")
# nh3 <- readSource("EDGAR",subtype="NH3")
# nh3 <- add_dimension(nh3, dim=3.2, add="em",nm="NH3")
# so2 <- readSource("EDGAR",subtype="SO2")
# so2 <- add_dimension(so2, dim=3.2, add="em",nm="SO2")
# pm10 <- readSource("EDGAR",subtype="PM10")
# pm10 <- add_dimension(pm10, dim=3.2, add="em",nm="PM10")
#
# edgar <- mbind(co,nox,so2,voc,nh3,pm10) / 1000 # kt = Gg -> Mt
#
# map <- c(CO="CO",NOx="NOx",SO2="Sulfur",VOC="VOC",NH3="NH3",PM10="PM10")
# tmp <- NULL
# for (i in getNames(edgar,dim=2)) {
# vars <- c("1A2","2A1","2A2","2A7","2B","2C","2D","2E","2F1","2F2","2F3","2F4","2F5","2F7","2F8","2F9","2G")
# tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Industry (Mt/yr)")))
# vars <- c("1A4")
# tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Residential and Commercial (Mt/yr)")))
# #vars <- c("1C1","1A3a", "1A3b", "1A3c", "1A3d", "1A3e","1C2")
# #tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Transportation (Mt/yr)")))
# vars <- c("1C1")
# tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Transportation|Aviation (Mt/yr)")))
# vars <- c("1A3a", "1A3b", "1A3c", "1A3d", "1A3e")
# tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Transportation|Ground Transportation (Mt/yr)")))
# vars <- c("1C2")
# tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Transportation|International Shipping (Mt/yr)")))
# vars <- c("1A1a","1A1bc","1B1","1B2")
# tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Supply (Mt/yr)")))
# vars <- c("4F")
# tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Land Use|Agricultural Waste Burning (Mt/yr)")))
# vars <- c("4A","4B","4C","4D1","4D2","4D3","4D4")
# tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Land Use|Agriculture (Mt/yr)")))
# vars <- c("5A", "5D", "5F", "5F2")
# tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Land Use|Forest Burning (Mt/yr)")))
# vars <- c("3A", "3B", "3C", "3D")
# tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Solvents (Mt/yr)")))
# vars <- c("6A","6B","6C","6D")
# tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Waste (Mt/yr)")))
# }
#
} else if (datasource == "EDGAR") {
# read EDGAR emissions from sources
co <- readSource("EDGAR",subtype="CO")
co <- add_dimension(co, dim=3.2, add="em",nm="CO")
voc <- readSource("EDGAR",subtype="VOC")
voc <- add_dimension(voc, dim=3.2, add="em",nm="VOC")
nox <- readSource("EDGAR",subtype="NOx")
nox <- add_dimension(nox, dim=3.2, add="em",nm="NOx")
nh3 <- readSource("EDGAR",subtype="NH3")
nh3 <- add_dimension(nh3, dim=3.2, add="em",nm="NH3")
so2 <- readSource("EDGAR",subtype="SO2")
so2 <- add_dimension(so2, dim=3.2, add="em",nm="SO2")
pm10 <- readSource("EDGAR",subtype="PM10")
pm10 <- add_dimension(pm10, dim=3.2, add="em",nm="PM10")
edgar <- mbind(co,nox,so2,voc,nh3,pm10) / 1000 # kt = Gg -> Mt
# Allocation of pollutants to sectors: special treatment for solvents
map <- c(CO="CO",NOx="NOx",SO2="Sulfur",VOC="VOC",NH3="NH3",PM10="PM10")
tmp <- NULL
for (i in names(map)) {
vars <- c("1A4")
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Residential and Commercial (Mt/yr)")))
#vars <- c("1C1","1A3a", "1A3b", "1A3c", "1A3d", "1A3e","1C2")
#tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Transportation (Mt/yr)")))
vars <- c("1C1")
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Transportation|Aviation (Mt/yr)")))
vars <- c("1A3a", "1A3b", "1A3c", "1A3d", "1A3e")
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Transportation|Ground Transportation (Mt/yr)")))
vars <- c("1C2")
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Transportation|International Shipping (Mt/yr)")))
vars <- c("1A1a","1A1bc","1B1","1B2")
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Supply (Mt/yr)")))
vars <- c("4F")
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Land Use|Agricultural Waste Burning (Mt/yr)")))
vars <- c("4A","4B","4C","4D1","4D2","4D3","4D4")
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Land Use|Agriculture (Mt/yr)")))
vars <- c("5A", "5D", "5F", "5F2")
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Land Use|Forest Burning (Mt/yr)")))
vars <- c("6A","6B","6C","6D")
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Waste (Mt/yr)")))
}
# no extrawurst for voc
map <- c(VOC="VOC")
for (i in names(map)) {
vars <- c("1A2","2A1","2A2","2A7","2B","2C","2D","2E","2F1","2F2","2F3","2F4","2F5","2F7","2F8","2F9","2G")
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Industry (Mt/yr)")))
vars <- c("3A", "3B", "3C", "3D")
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Solvents (Mt/yr)")))
}
# extrawurst for everything but voc: industry = industry + solvents
map <- c(CO="CO",NOx="NOx",SO2="Sulfur",NH3="NH3",PM10="PM10")
for (i in names(map)) {
vars <- c("1A2","2A1","2A2","2A7","2B","2C","2D","2E","2F1","2F2","2F3","2F4","2F5","2F7","2F8","2F9","2G","3A", "3B", "3C", "3D")
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1), paste0("Emissions|",map[i],"|Energy Demand|Industry (Mt/yr)")))
# add zero dummy or Solvents
tmp <- mbind(tmp, setNames(dimSums(edgar[,,i][,,vars],dim=3.1)*0, paste0("Emissions|",map[i],"|Solvents (Mt/yr)")))
}
} else if (datasource == "LIMITS") {
# read LIMITS emissions from sources
em_limits <- readSource("LIMITS", subtype="emissions")
em_limits <- collapseNames(em_limits[,,"kt"][,,"CLE"][,,"Unattributed", invert=TRUE])
getNames(em_limits, dim=2)[which(getNames(em_limits, dim=2) == "NOX")] <- "NOx"
map <- read.csv2(toolMappingFile("sectoral", "mappingLIMITSsectorstoREMINDsectors.csv"), stringsAsFactors=TRUE)
em_limits[is.na(em_limits)] <- 0.0
tmp <- NULL
for (kap in getNames(em_limits, dim=2)) {
tmp_limits <- collapseNames(em_limits[,,kap])
tmp_map <- map %>%
filter_(~limits_sector %in% getNames(tmp_limits, dim=1)) %>%
mutate_(remind_sector = ~paste(sub("POLLUTANT", kap, remind_sector), "(Mt/yr)"))
tmp <- mbind(tmp, toolAggregate(tmp_limits, tmp_map, dim=3.1))
}
tmp <- tmp / 1000 # kt = Gg -> Mt
#tmp <- tmp[,2005,]
} else if (datasource == "ECLIPSE") {
# read ECLIPSE emissions from sources
em_eclipse <- readSource("ECLIPSE", subtype="emissions.aggregated")
em_eclipse <- collapseNames(em_eclipse[,,"CLE"])
#map <- read.csv(toolMappingFile("sectoral", "mappingECLIPSEtoAggREMINDsectors.csv"), stringsAsFactors=TRUE)
map <- read.csv2(toolMappingFile("sectoral", "mappingECLIPSEsectorstoREMINDsectors.csv"), stringsAsFactors=TRUE)
em_eclipse[is.na(em_eclipse)] <- 0.0
tmp <- NULL
for (kap in getNames(em_eclipse, dim=2)) {
tmp_eclipse <- collapseNames(em_eclipse[,,kap])
tmp_map <- map %>%
filter_(~eclipse_sector %in% getNames(tmp_eclipse, dim=1)) %>%
mutate_(remind_sector = ~paste(sub("POLLUTANT", kap, remind_sector), "(Mt/yr)"))
tmp <- mbind(tmp, toolAggregate(tmp_eclipse, tmp_map, dim=3.1))
}
tmp <- tmp / 1000 # kt = Gg -> Mt
#tmp <- tmp[,2005,]
} else if (datasource == "GFED") {
data <- readSource("GFED")
# aggregate gfed sectors to sectors of all other data
emi_subset <- c("SO2","OC","NOx","NH3","CO","BC")
tmp <- new.magpie(getRegions(data),getYears(data),c("agriwaste","forest","savannah"))
tmp <- add_dimension(tmp,add="emi",dim=3.1,nm=emi_subset)
tmp[,,"savannah"] <- data[,,"savanna"][,,emi_subset]
tmp[,,"agriwaste"] <- data[,,"agricultural_waste"][,,emi_subset]
tmp[,,"forest"] <- (data[,,"boreal"] + data[,,"temperate"] + data[,,"peat"] + data[,,"deforestation"])[,,emi_subset]
tmp[,,"CO"] <- tmp[,,"CO"] / 10 # 1E11g -> Mt
tmp[,,c("NH3","SO2","BC")] <- tmp[,,c("NH3","SO2","BC")] / 1000 # 1E9g -> Mt
tmp[,,c("NOx","OC")] <- tmp[,,c("NOx","OC")] / 100 # 1E10g -> Mt
getNames(tmp,dim=2)<- gsub("SO2","Sulfur",getNames(tmp,dim=2)) # rename SO2 -> Sulfur
} else if (datasource == "CDIAC") {
data <- readSource("CDIAC")
# omitting "PerCap"
map <- c(FFIC ="Fossil Fuels and Industry", # <--- old name. New name wil be: "Energy and Industrial Processes",
Solids ="Energy|Solids",
Liquids ="Energy|Liquids",
Gases ="Energy|Gases",
Cement ="Industrial Processes|Cement",
Flaring ="Energy|Flaring",
Bunker ="Energy|Bunkers")
tmp <- NULL
for (i in names(map)) {
tmp <- mbind(tmp, setNames(data[,,i],paste0("Emissions|CO2|",map[i]," (Mt/yr)")))
}
tmp <- tmp * 44/12 /1000 # from ktC -> MtCO2
}
return(list(x=tmp,
weight=NULL,
unit="Mt",
description="historic emissions in 1970-2014"))
}
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