emis_hot_td: Estimation of hot exhaust emissions with a top-down approach

Description

emis_hot_td estimates cold start emissions with a top-down appraoch. This is, annual or monthly emissions or region. Especifically, the emissions are estimated for the row of the simple feature (row of the spatial feature).

In general was designed so that each simple feature is a region with different average monthly temperature. This function, as others in this package, adapts to the class of the input data. providing flexibility to the user.

Usage

emis_hot_td(
  veh,
  lkm,
  ef,
  pro_month,
  params,
  verbose = FALSE,
  fortran = FALSE,
  nt = ifelse(check_nt() == 1, 1, check_nt()/2)
)

Value

Emissions data.frame

Arguments

veh: "Vehicles" data-frame or spatial feature, where columns are the age distribution of that vehicle. and rows each simple feature or region.
lkm: Numeric; mileage by the age of use of each vehicle.
ef: Numeric or data.frame; emission factors. When it is a data.frame number of rows can be for each region, or also, each region repeated along 12 months. For instance, if you have 10 regions the number of rows of ef can also be 120 (10 * 120). when you have emission factors that varies with month, see ef_china.
pro_month: Numeric or data.frame; monthly profile to distribute annual mileage in each month. When it is a data.frame, each region (row) can have a different monthly profile.
params: List of parameters; Add columns with information to returning data.frame
verbose: Logical; To show more information
fortran: Logical; to try the fortran calculation.
nt: Integer; Number of threads which must be lower than max available. See check_nt. Only when fortran = TRUE

Details

List to make easier to use this function.

`pro_month` is data.frame AND rows of `ef` and `veh` are equal.
`pro_month` is numeric AND rows of `ef` and `veh` are equal.
`pro_month` is data.frame AND rows of `ef` is 12X rows of `veh`.
`pro_month` is numeric AND rows of `ef` is 12X rows of `veh`.
`pro_month` is data,frame AND class of `ef` is 'units'.
`pro_month` is numeric AND class of `ef` is 'units'.
NO `pro_month` AND class of `ef` is 'units'.
NO `pro_month` AND `ef` is data.frame.
`pro_month` is numeric AND rows of `ef` is 12 (monthly `ef`).

Examples

Run this code

if (FALSE) {
# Do not run
euros <- c("V", "V", "IV", "III", "II", "I", "PRE", "PRE")
efh <- ef_ldv_speed(
  v = "PC", t = "4S", cc = "<=1400", f = "G",
  eu = euros, p = "CO", speed = Speed(34)
)
lkm <- units::as_units(c(20:13), "km") * 1000
veh <- age_ldv(1:10, agemax = 8)
system.time(
  a <- emis_hot_td(
    veh = veh,
    lkm = lkm,
    ef = EmissionFactors(as.numeric(efh[, 1:8])),
    verbose = TRUE
  )
)
system.time(
  a2 <- emis_hot_td(
    veh = veh,
    lkm = lkm,
    ef = EmissionFactors(as.numeric(efh[, 1:8])),
    verbose = TRUE,
    fortran = TRUE
  )
) # emistd7f.f95
identical(a, a2)

# adding columns
emis_hot_td(
  veh = veh,
  lkm = lkm,
  ef = EmissionFactors(as.numeric(efh[, 1:8])),
  verbose = TRUE,
  params = list(paste0("data_", 1:10), "moredata")
)

# monthly profile (numeric) with numeric ef
veh_month <- c(rep(8, 1), rep(10, 5), 9, rep(10, 5))
system.time(
  aa <- emis_hot_td(
    veh = veh,
    lkm = lkm,
    ef = EmissionFactors(as.numeric(efh[, 1:8])),
    pro_month = veh_month,
    verbose = TRUE
  )
)
system.time(
  aa2 <- emis_hot_td(
    veh = veh,
    lkm = lkm,
    ef = EmissionFactors(as.numeric(efh[, 1:8])),
    pro_month = veh_month,
    verbose = TRUE,
    fortran = TRUE
  )
) # emistd5f.f95
aa$emissions <- round(aa$emissions, 8)
aa2$emissions <- round(aa2$emissions, 8)
identical(aa, aa2)

# monthly profile (numeric) with data.frame ef
veh_month <- c(rep(8, 1), rep(10, 5), 9, rep(10, 5))
def <- matrix(EmissionFactors(as.numeric(efh[, 1:8])),
  nrow = nrow(veh), ncol = ncol(veh), byrow = TRUE
)
def <- EmissionFactors(def)
system.time(
  aa <- emis_hot_td(
    veh = veh,
    lkm = lkm,
    ef = def,
    pro_month = veh_month,
    verbose = TRUE
  )
)
system.time(
  aa2 <- emis_hot_td(
    veh = veh,
    lkm = lkm,
    ef = def,
    pro_month = veh_month,
    verbose = TRUE,
    fortran = TRUE
  )
) # emistd1f.f95
aa$emissions <- round(aa$emissions, 8)
aa2$emissions <- round(aa2$emissions, 8)
identical(aa, aa2)

# monthly profile (data.frame)
dfm <- matrix(c(rep(8, 1), rep(10, 5), 9, rep(10, 5)),
  nrow = 10, ncol = 12,
  byrow = TRUE
)
system.time(
  aa <- emis_hot_td(
    veh = veh,
    lkm = lkm,
    ef = EmissionFactors(as.numeric(efh[, 1:8])),
    pro_month = dfm,
    verbose = TRUE
  )
)
system.time(
  aa2 <- emis_hot_td(
    veh = veh,
    lkm = lkm,
    ef = EmissionFactors(as.numeric(efh[, 1:8])),
    pro_month = dfm,
    verbose = TRUE,
    fortran = TRUE
  )
) # emistd6f.f95
aa$emissions <- round(aa$emissions, 2)
aa2$emissions <- round(aa2$emissions, 2)
identical(aa, aa2)

# Suppose that we have a EmissionsFactor data.frame with number of rows for each month
# number of rows are 10 regions
# number of columns are 12 months
tem <- runif(n = 6 * 10, min = -10, max = 35)
temp <- c(rev(tem[order(tem)]), tem[order(tem)])
plot(temp)
dftemp <- celsius(matrix(temp, ncol = 12))
dfef <- ef_evap(
  ef = c(rep("eshotfi", 8)),
  v = "PC",
  cc = "<=1400",
  dt = dftemp,
  show = F,
  ca = "small",
  ltrip = units::set_units(10, km),
  pollutant = "NMHC"
)
dim(dfef) # 120 rows and 9 columns, 8 ef (g/km) and 1 for month
system.time(
  aa <- emis_hot_td(
    veh = veh,
    lkm = lkm,
    ef = dfef,
    pro_month = veh_month,
    verbose = TRUE
  )
)
system.time(
  aa2 <- emis_hot_td(
    veh = veh,
    lkm = lkm,
    ef = dfef,
    pro_month = veh_month,
    verbose = TRUE,
    fortran = TRUE
  )
) # emistd3f.f95
aa$emissions <- round(aa$emissions, 2)
aa2$emissions <- round(aa2$emissions, 2)
identical(aa, aa2)
plot(aggregate(aa$emissions, by = list(aa$month), sum)$x)

# Suppose that we have a EmissionsFactor data.frame with number of rows for each month
# monthly profile (data.frame)
system.time(
  aa <- emis_hot_td(
    veh = veh,
    lkm = lkm,
    ef = dfef,
    pro_month = dfm,
    verbose = TRUE
  )
)
system.time(
  aa2 <- emis_hot_td(
    veh = veh,
    lkm = lkm,
    ef = dfef,
    pro_month = dfm,
    verbose = TRUE,
    fortran = TRUE
  )
) # emistd4f.f95
aa$emissions <- round(aa$emissions, 8)
aa2$emissions <- round(aa2$emissions, 8)
identical(aa, aa2)
plot(aggregate(aa$emissions, by = list(aa$month), sum)$x)
}