projects/ecuador_td_hot_month/scripts/evaporatives.R

In ibarraespinosa/vein: Vehicular Emissions Inventories

file.remove("emi/evaporatives.csv")
# temperature
te <- met$Temperature
bb <- (0 + 15) / 2
cc <- (10 + 25) / 2
dd <- (20 + 35) / 2

tem <- ifelse(
  te <= bb, "0_15",
  ifelse(
    te > bb & te <= cc, "10_25",
    "20_35"
  )
)

nmonth <- ifelse(nchar(seq_along(te)) < 2,
  paste0(0, seq_along(te)),
  seq_along(te)
)

# filtrando veiculos otto
meta_ev <- metadata[metadata$fuel != "D", ]
veh_ev <- meta_ev$vehicles

# checks name
type_emis <- c("Diurnal", "Running Losses", "Hot Soak")
name_file_evap <- c("/DIURNAL_", "/RUNNING_LOSSES_", "/HOT_SOAK_")

ef_d <- paste0("D_", tem)
ef_rl <- paste0("R_", tem)
ef_hs <- paste0("S_", tem)

# plot
n_PC <- metadata[metadata$family == "PC", ]$vehicles
n_LCV <- metadata[metadata$family == "LCV", ]$vehicles[1:4]
n_MC <- metadata[metadata$family == "MC", ]$vehicles

ns <- c(
  "PC", "LCV", "MC",
  "PC", "LCV", "MC",
  "PC", "LCV", "MC"
)
ln <- list(
  n_PC, n_LCV, n_MC,
  n_PC, n_LCV, n_MC,
  n_PC, n_LCV, n_MC
)
laby <- c(
  "g/day", "g/day", "g/day",
  "g/trip", "g/trip", "g/trip",
  "g/trip", "g/trip", "g/trip"
)
ev <- c(
  "DIURNAL", "DIURNAL", "DIURNAL",
  "RUNNING_LOSSES", "RUNNING_LOSSES", "RUNNING_LOSSES",
  "HOT_SOAK", "HOT_SOAK", "HOT_SOAK"
)


# plotting
switch(language,
  "portuguese" = cat("Plotando EF\n"),
  "english" = cat("Plotting EF\n"),
  "spanish" = cat("Plotando EF\n")
)

for (i in seq_along(ns)) {
  dl <- lapply(
    seq_along(ef_d), function(j) {
      data.frame(
        ef_cetesb(
          p = ef_d[j],
          veh = ln[[i]],
          year = year,
          scale = scale,
          agemax = 40,
          verbose = verbose
        ),
        month = nmonth[j]
      )
    }
  )

  dl <- rbindlist(dl)
  df <- wide_to_long(
    df = dl,
    column_with_data = ln[[i]],
    column_fixed = "month"
  )

  df$age <- 1:40
  setDT(df)
  names(df) <- c("ef", "month", "veh", "age")
  p <- ggplot(
    df[df$ef > 0, ],
    aes(x = age, y = ef, colour = veh)
  ) +
    geom_line() +
    facet_wrap(~month) +
    ylim(0, NA) +
    labs(y = laby[i], title = ev[i]) +
    # scale_y_log10() +
    theme_bw()

  png(
    filename = paste0("images/EF_", ev[i], "_", ns[i], ".png"),
    width = 2100, height = 1500, units = "px", pointsize = 12,
    bg = "white", res = 300
  )
  print(p)
  dev.off()
}

switch(language,
  "portuguese" = message("\nFiguras em /images\n"),
  "english" = message("\nFigures in /image\n"),
  "spanish" = message("\nFiguras en /images\n")
)

# Diurnal  ####
switch(language,
  "portuguese" = cat("\nEmissões evaporativas diurnal\n"),
  "english" = cat("\nEvaporative diurnal emissions\n"),
  "spanish" = cat("\nEmisiones evaporativas diurnal\n")
)

for (i in seq_along(veh_ev)) {
  cat(
    "\n", veh_ev[i],
    rep("", max(nchar(veh_ev) + 1) - nchar(veh_ev[i]))
  )


  x <- readRDS(paste0("veh/", veh_ev[i], ".rds"))

  lef <- lapply(seq_along(te), function(j) {
    cat(nmonth[j], " ")
    ef_cetesb(
      p = ef_d[j],
      veh = veh_ev[i],
      year = year,
      scale = scale,
      agemax = ncol(x),
      # diurnal: g/day* day/km= g/km
      verbose = verbose
    ) / (mileage[[veh_ev[i]]] / 365) # mean daily mileage
  })
  lef <- EmissionFactors(as.data.frame(do.call("rbind", lef)))

  # muda NaNaN para 0
  lef[is.na(lef)] <- 0

  array_x <- emis_hot_td(
    veh = x,
    lkm = mileage[[veh_ev[i]]],
    ef = lef,
    pro_month = pmonth[[veh_ev[i]]],
    fortran = TRUE,
    nt = check_nt() / 2,
    verbose = verbose,
    params = list(
      veh = veh_ev[i],
      size = meta_ev$size[i],
      fuel = meta_ev$fuel[i],
      pollutant = "NMHC",
      type_emi = "Evaporatives",
      subtype_emi = "Diurnal",
      baseyear = year
    )
  )

  fwrite(array_x, "emi/evaporatives.csv", append = TRUE)
}
cat("\n")


# Running Losses ####
switch(language,
  "portuguese" = cat("\nEmissões evaporativas running-losses\n"),
  "english" = cat("\nEvaporative running-losses emissions\n"),
  "spanish" = cat("\nEmisiones evaporativas running-loses\n")
)

for (i in seq_along(veh_ev)) {
  cat(
    "\n", veh_ev[i],
    rep("", max(nchar(veh_ev) + 1) - nchar(veh_ev[i]))
  )


  x <- readRDS(paste0("veh/", veh_ev[i], ".rds"))

  lef <- lapply(seq_along(te), function(j) {
    cat(nmonth[j], " ")
    ef_cetesb(
      p = ef_rl[j],
      veh = veh_ev[i],
      year = year,
      scale = scale,
      agemax = ncol(x),
      # g/trip * trip/day * day/km = g/km
      verbose = verbose
    ) * meta_ev$trips_day[i] / (mileage[[veh_ev[i]]] / 365)
  })
  lef <- EmissionFactors(as.data.frame(do.call("rbind", lef)))


  # muda NaNaN para 0
  lef[is.na(lef)] <- 0

  array_x <- emis_hot_td(
    veh = x,
    lkm = mileage[[veh_ev[i]]],
    ef = lef,
    pro_month = pmonth[[veh_ev[i]]],
    fortran = TRUE,
    nt = check_nt() / 2,
    verbose = verbose,
    params = list(
      veh = veh_ev[i],
      size = meta_ev$size[i],
      fuel = meta_ev$fuel[i],
      pollutant = "NMHC",
      type_emi = "Evaporatives",
      subtype_emi = "Running Losses",
      baseyear = year
    )
  )

  fwrite(array_x, "emi/evaporatives.csv", append = TRUE)
}

cat("\n")


# Hot Soak ####
switch(language,
  "portuguese" = cat("\nEmissões evaporativas hot-soak\n"),
  "english" = cat("\nEvaporative hot-soak emissions\n"),
  "spanish" = cat("\nEmisiones evaporativas hot-soak\n")
)

for (i in seq_along(veh_ev)) {
  cat(
    "\n", veh_ev[i],
    rep("", max(nchar(veh_ev) + 1) - nchar(veh_ev[i]))
  )


  x <- readRDS(paste0("veh/", veh_ev[i], ".rds"))

  lef <- lapply(seq_along(te), function(j) {
    cat(nmonth[j], " ")
    ef_cetesb(
      p = ef_hs[j],
      veh = veh_ev[i],
      year = year,
      agemax = ncol(x),
      verbose = verbose
    ) * meta_ev$trips_day[i] / (mileage[[veh_ev[i]]] / 365) # quilometragem medio diario
  })
  lef <- EmissionFactors(as.data.frame(do.call("rbind", lef)))

  # muda NaNaN para 0
  lef[is.na(lef)] <- 0

  array_x <- emis_hot_td(
    veh = x,
    lkm = mileage[[veh_ev[i]]],
    ef = lef,
    pro_month = pmonth[[veh_ev[i]]],
    fortran = TRUE,
    nt = check_nt() / 2,
    verbose = verbose,
    params = list(
      veh = veh_ev[i],
      size = meta_ev$size[i],
      fuel = meta_ev$fuel[i],
      pollutant = "NMHC",
      type_emi = "Evaporatives",
      subtype_emi = "Hot Soak",
      baseyear = year
    )
  )

  fwrite(array_x, "emi/evaporatives.csv", append = TRUE)
}
cat("\n")


switch(language,
  "portuguese" = message("\n\nArquivos em: /emi/evaporatives.csv:"),
  "english" = message("\n\nFiles in: /emi/evaporatives.csv"),
  "spanish" = message("\n\nArchivos en: /emi/evaporatives.csv")
)


switch(language,
  "portuguese" = message("Limpando..."),
  "english" = message("Cleaning..."),
  "spanish" = message("Limpiando...")
)
suppressWarnings(
  rm(
    i, mileage, meta_ev, veh_ev, year,
    diurnal_ef, hot_soak_ef, running_losses_ef
  )
)
# deberiamos ter al menos: "composition" "net"         "veh"         "year"
ls()
invisible(gc())