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Fix issue when subsector variables not available #474

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Fix issue when subsector variables not available #474

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8e110c9
Explicit flag for when subsectors not available
gabriel-abrahao Sep 22, 2023
e3ad1e9
Fix logic and extend handling to CCS variables
gabriel-abrahao Sep 22, 2023
4556151
Added name
gabriel-abrahao Sep 22, 2023
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2 changes: 2 additions & 0 deletions CITATION.cff
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Original file line number Diff line number Diff line change
Expand Up @@ -65,6 +65,8 @@ authors:
given-names: Jessica
- family-names: Verpoort
given-names: Philipp
- family-names: Abrahao
given-names: Gabriel
license: LGPL-3.0
repository-code: https://github.com/pik-piam/remind2

183 changes: 96 additions & 87 deletions R/reportEmi.R
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Original file line number Diff line number Diff line change
Expand Up @@ -138,10 +138,17 @@ reportEmi <- function(gdx, output = NULL, regionSubsetList = NULL, t = c(seq(200
vm_demFeSector <- readGDX(gdx, "vm_demFeSector", field = "l", restore_zeros = F)[, t, ]
# set NA values to 0,
vm_demFeSector[is.na(vm_demFeSector)] <- 0
# FE demand per industry subsector
o37_demFeIndSub <- readGDX(gdx, "o37_demFeIndSub", restore_zeros = F)[, t, ]
if (!is.null(o37_demFeIndSub)) {
# FE demand per industry subsector. First read without subsetting to check if
# is was actually written
# o37_demFeIndSub <- readGDX(gdx, "o37_demFeIndSub", restore_zeros = F)[, t, ]
o37_demFeIndSub <- readGDX(gdx, "o37_demFeIndSub", restore_zeros = F)
# Does subsector information exist?
if (length(o37_demFeIndSub) != 0) {
hassubsectors <- TRUE
o37_demFeIndSub <- o37_demFeIndSub[,t,]
o37_demFeIndSub[is.na(o37_demFeIndSub)] <- 0
} else {
hassubsectors <- FALSE
}

# secondary energy production
Expand Down Expand Up @@ -174,95 +181,97 @@ reportEmi <- function(gdx, output = NULL, regionSubsetList = NULL, t = c(seq(200
vm_co2CCS <- readGDX(gdx, "vm_co2CCS", field = "l", restore_zeros = F)[, t, ]


# CO2 captured by industry sectors
vm_emiIndCCS <- readGDX(gdx, "vm_emiIndCCS", field = "l", restore_zeros = T)[, t, ]
getSets(vm_emiIndCCS)[3] <- "secInd37" # relabel subsector dimension to match with other parameters

# CO2 released by CCU
vm_co2CCUshort <- readGDX(gdx, "vm_co2CCUshort", field = "l", restore_zeros = F)[, t, ]
# helper variable to release captured CO2 in no CCU capacities are standing anymore to take the captured CO2
v_co2capturevalve <- readGDX(gdx, "v_co2capturevalve", field = "l", restore_zeros = F)[, t, ]

# CO2 captured per industry subsector
# NOTE: The parameter pm_IndstCO2Captured was calculated without taking into
# account the different emission factors of energy carriers, so we recalculate
# it here. Might load it again when we are reasonably sure we won't process
# any gdxes with the faulty parameter any more.
vm_emiIndCCS_tibble <- vm_emiIndCCS[,,emiInd37_fuel] %>%
as_tibble() %>%
select(t = 'ttot', regi = 'all_regi', emiInd37 = 'secInd37',
vm_emiIndCCS = 'value') %>%
left_join(secInd37_2_emiInd37, 'emiInd37') %>%
select(-'emiInd37')

o37_demFeIndSub_tibble <- o37_demFeIndSub %>%
as_tibble() %>%
select(t = 'ttot', regi = 'all_regi', sety = 'all_enty',
fety = 'all_enty1', 'secInd37', 'emiMkt' = 'all_emiMkt',
o37_demFEindsub = 'value')

pm_emifac_tibble <- pm_emifac %>%
mselect(mutate(se2fe, all_enty2 = 'co2')) %>%
as_tibble() %>%
select(t = 'tall', regi = 'all_regi', fety = 'all_enty1',
pm_emifac = 'value') %>%
# extend fossil emission factors to biomass and synfuels
left_join(
se2fe %>%
distinct(sety = .data$all_enty, fety = .data$all_enty1),

by = 'fety',

relationship = 'many-to-many'
)
# CO2 captured by industry sectors
vm_emiIndCCS <- readGDX(gdx, "vm_emiIndCCS", field = "l", restore_zeros = T)[, t, ]
getSets(vm_emiIndCCS)[3] <- "secInd37" # relabel subsector dimension to match with other parameters

# CO2 released by CCU
vm_co2CCUshort <- readGDX(gdx, "vm_co2CCUshort", field = "l", restore_zeros = F)[, t, ]
# helper variable to release captured CO2 in no CCU capacities are standing anymore to take the captured CO2
v_co2capturevalve <- readGDX(gdx, "v_co2capturevalve", field = "l", restore_zeros = F)[, t, ]

if (hassubsectors) {
# CO2 captured per industry subsector
# NOTE: The parameter pm_IndstCO2Captured was calculated without taking into
# account the different emission factors of energy carriers, so we recalculate
# it here. Might load it again when we are reasonably sure we won't process
# any gdxes with the faulty parameter any more.
vm_emiIndCCS_tibble <- vm_emiIndCCS[,,emiInd37_fuel] %>%
as_tibble() %>%
select(t = 'ttot', regi = 'all_regi', emiInd37 = 'secInd37',
vm_emiIndCCS = 'value') %>%
left_join(secInd37_2_emiInd37, 'emiInd37') %>%
select(-'emiInd37')

o37_demFeIndSub_tibble <- o37_demFeIndSub %>%
as_tibble() %>%
select(t = 'ttot', regi = 'all_regi', sety = 'all_enty',
fety = 'all_enty1', 'secInd37', 'emiMkt' = 'all_emiMkt',
o37_demFEindsub = 'value')

pm_emifac_tibble <- pm_emifac %>%
mselect(mutate(se2fe, all_enty2 = 'co2')) %>%
as_tibble() %>%
select(t = 'tall', regi = 'all_regi', fety = 'all_enty1',
pm_emifac = 'value') %>%
# extend fossil emission factors to biomass and synfuels
left_join(
se2fe %>%
distinct(sety = .data$all_enty, fety = .data$all_enty1),

by = 'fety',

relationship = 'many-to-many'
)

subsector_total_emissions <- inner_join(
o37_demFeIndSub_tibble,
pm_emifac_tibble,
subsector_total_emissions <- inner_join(
o37_demFeIndSub_tibble,
pm_emifac_tibble,

c('t', 'regi', 'sety', 'fety')
) %>%
group_by(.data$t, .data$regi, .data$secInd37) %>%
summarise(
subsector_total_emissions = sum(.data$o37_demFEindsub * .data$pm_emifac),
.groups = 'drop')
c('t', 'regi', 'sety', 'fety')
) %>%
group_by(.data$t, .data$regi, .data$secInd37) %>%
summarise(
subsector_total_emissions = sum(.data$o37_demFEindsub * .data$pm_emifac),
.groups = 'drop')

subsector_emissions <- inner_join(
o37_demFeIndSub_tibble,
pm_emifac_tibble,

subsector_emissions <- inner_join(
o37_demFeIndSub_tibble,
pm_emifac_tibble,
c('t', 'regi', 'sety', 'fety')
) %>%
group_by(.data$t, .data$regi, .data$secInd37, .data$sety, .data$fety,
.data$emiMkt) %>%
summarise(
subsector_emissions = sum(.data$o37_demFEindsub * .data$pm_emifac),
.groups = 'drop')

c('t', 'regi', 'sety', 'fety')
) %>%
group_by(.data$t, .data$regi, .data$secInd37, .data$sety, .data$fety,
.data$emiMkt) %>%
summarise(
subsector_emissions = sum(.data$o37_demFEindsub * .data$pm_emifac),
.groups = 'drop')
pm_IndstCO2Captured <- subsector_emissions %>%
full_join(
inner_join(
vm_emiIndCCS_tibble,

pm_IndstCO2Captured <- subsector_emissions %>%
full_join(
inner_join(
vm_emiIndCCS_tibble,
subsector_total_emissions,

subsector_total_emissions,
c('t', 'regi', 'secInd37')
) %>%
mutate(subsector_capture_share = .data$vm_emiIndCCS
/ .data$subsector_total_emissions) %>%
select(-'vm_emiIndCCS', -'subsector_total_emissions'),

c('t', 'regi', 'secInd37')
) %>%
mutate(subsector_capture_share = .data$vm_emiIndCCS
/ .data$subsector_total_emissions) %>%
select(-'vm_emiIndCCS', -'subsector_total_emissions'),

c('t', 'regi', 'secInd37')
) %>%
mutate(
value = .data$subsector_emissions * .data$subsector_capture_share) %>%
select(-'subsector_emissions', -'subsector_capture_share') %>%
select(ttot = 't', all_regi = 'regi', all_enty = 'sety', all_enty1 = 'fety',
'secInd37', all_emiMkt = 'emiMkt', 'value') %>%
as.magpie(spatial = 2, temporal = 1, data = ncol(.)) %>%
ifelse(is.finite(.), ., 0) # replace NaN by 0

rm(vm_emiIndCCS_tibble, subsector_total_emissions, pm_emifac_tibble)
mutate(
value = .data$subsector_emissions * .data$subsector_capture_share) %>%
select(-'subsector_emissions', -'subsector_capture_share') %>%
select(ttot = 't', all_regi = 'regi', all_enty = 'sety', all_enty1 = 'fety',
'secInd37', all_emiMkt = 'emiMkt', 'value') %>%
as.magpie(spatial = 2, temporal = 1, data = ncol(.)) %>%
ifelse(is.finite(.), ., 0) # replace NaN by 0

rm(vm_emiIndCCS_tibble, subsector_total_emissions, pm_emifac_tibble)
}

# utility functions ----
# Convert a mixer table into a list that can be passed to mselect() to
Expand Down Expand Up @@ -555,7 +564,7 @@ reportEmi <- function(gdx, output = NULL, regionSubsetList = NULL, t = c(seq(200


# reporting if FE per industry subsector o37_demFeIndSub exists
if (!is.null(o37_demFeIndSub)) {
if (hassubsectors) {

# relabel industry energy CC from CCS sectors to industry sectors
vm_emiIndCCS_Mapped <- toolAggregate(
Expand Down Expand Up @@ -1154,7 +1163,7 @@ reportEmi <- function(gdx, output = NULL, regionSubsetList = NULL, t = c(seq(200
)

### report industry captured CO2 ----
if (!is.null(pm_IndstCO2Captured)) {
if (ifelse(exists("pm_IndstCO2Captured"),!is.null(pm_IndstCO2Captured),FALSE) & hassubsectors) {
variable_prefix <- 'Carbon Management|Carbon Capture|Industry Energy|'
variable_postfix <- ' (Mt CO2/yr)'

Expand Down Expand Up @@ -1231,7 +1240,7 @@ reportEmi <- function(gdx, output = NULL, regionSubsetList = NULL, t = c(seq(200
mbind())
} else {

if (!is.null(o37_demFeIndSub)) {
if (hassubsectors) {


# calculate bioenergy shares in industry solids, liquids and gases per subsector
Expand Down Expand Up @@ -2392,7 +2401,7 @@ reportEmi <- function(gdx, output = NULL, regionSubsetList = NULL, t = c(seq(200
"Emi|CO2|Gross|Energy|Demand|+|Transport (Mt CO2/yr)")

# TODO: remove this if clause once the below variable are there for industry subsectors
if ((module2realisation["industry", 2] == "fixed_shares") | (!is.null(o37_demFeIndSub))) {
if ((module2realisation["industry", 2] == "fixed_shares") | hassubsectors) {
# Note: this assumes that all bunker fuels are liquids
emi.vars.wBunkers <- c(emi.vars.wBunkers, "Emi|CO2|Energy|Demand|Transport|+|Liquids (Mt CO2/yr)", "Emi|CO2|Energy|Demand|++|Liquids (Mt CO2/yr)")

Expand Down