options(encoding = "UTF-8")
library(vein) # vein
library(sf) # spatial data
library(cptcity) # 7120 colour palettes
library(ggplot2) # plots
library(eixport) # create wrfchemi
library(data.table) # faster data.frames
sessionInfo()
# 0 Configuration
language <- "english" # spanish portuguese
path <- "config/inventory.xlsx"
readxl::excel_sheets(path)
metadata <- readxl::read_xlsx(path = path, sheet = "metadata")
mileage <- readxl::read_xlsx(path = path, sheet = "mileage")
tfs <- readxl::read_xlsx(path = path, sheet = "tfs")
veh <- readxl::read_xlsx(path = path, sheet = "fleet")
fuel <- readxl::read_xlsx(path = path, sheet = "fuel")
pmonth <- readxl::read_xlsx(path = path, sheet = "pmonth")
met <- readxl::read_xlsx(path = path, sheet = "met")
im_ok <- readxl::read_xlsx(path = path, sheet = "im_ok")
im_co <- readxl::read_xlsx(path = path, sheet = "im_co")
im_hc <- readxl::read_xlsx(path = path, sheet = "im_hc")
im_nox <- readxl::read_xlsx(path = path, sheet = "im_nox")
im_pm <- readxl::read_xlsx(path = path, sheet = "im_pm")
year <- 2018
scale <- "tunnel2018"
theme <- "black" # dark clean ing
delete_directories <- TRUE
source("config/config.R", encoding = "UTF-8")
# 1) Network ####
net <- sf::st_read("network/net.gpkg")
crs <- 31983
source("scripts/net.R", encoding = "UTF-8")
# 2) Traffic ####
net <- readRDS("network/net.rds")
metadata <- readRDS("config/metadata.rds")
categories <- c("pc", "lcv", "trucks", "bus", "mc") # in network/net.gpkg
veh <- readRDS("config/fleet_age.rds")
k_D <- 1/2.482039
k_E <- 1/5.708199
k_G <- 1/5.866790
verbose <- FALSE
year <- 2018
theme <- "black" # dark clean ink
survival <- TRUE
source("scripts/traffic.R", encoding = "UTF-8")
# 3) Estimation ####
language <- "portuguese" # english chinese spanish portuguese
metadata <- readRDS("config/metadata.rds")
mileage <- readRDS("config/mileage.rds")
veh <- readRDS("config/fleet_age.rds")
net <- readRDS("network/net.rds")
pmonth <- readRDS("config/pmonth.rds")
met <- readRDS("config/met.rds")
verbose <- FALSE
year <- 2019
# fuel calibration with fuel consumption data
fuel <- readRDS("config/fuel.rds")
pol <- "FC"
source("scripts/fuel_eval.R", encoding = "UTF-8")
# Exhaust
pol <- c("CO", "HC", "NMHC", "NOx", "CO2",
"PM", "NO2", "NO", "SO2")
IM <- FALSE
im_ok <- readRDS("config/im_ok.rds")
im_co <- readRDS("config/im_co.rds")
im_hc <- readRDS("config/im_hc.rds")
im_nox <- readRDS("config/im_nox.rds")
im_pm <- readRDS("config/im_pm.rds")
scale <- "tunnel2018"
source("scripts/exhaust.R", encoding = "UTF-8")
# Evaporative
source("scripts/evaporatives.R", encoding = "UTF-8")
# Paved Roads
metadata <- readRDS("config/metadata.rds")
mileage <- readRDS("config/mileage.rds")
year <- 2019
pol <- c("PM25RES", "PM10RES")
source("scripts/ressuspensao.R", encoding = "UTF-8")
# distribute emissions into OSM roads ####
# To download OpenStreetMap data...
# Read and edit the file osm.R
# Then run manually
#download_osm <- TRUE
#OSM_region <- "sudeste"
#"scripts/osm.R"
# I already included OSM hre network/roads.rds
# 4) Post-estimation ####
language <- "spanish" # english chinese spanish portuguese
net <- readRDS("network/net.rds")
roads <- st_transform(readRDS("network/roads.rds"), 31983) # I already included OSM
months_subset <- 8 #10:11 for instance
g <- st_transform(eixport::wrf_grid(
paste0(system.file("extdata",
package = "eixport"),
"/wrfinput_d01")), 31983)
# Number of lat points 99
# Number of lon points 149
crs <- 31983
osm_name <- "fclass" #OSM column for type of road (motorway, trunk...)
source("scripts/post.R", encoding = "UTF-8")
# plots
metadata <- readRDS("config/metadata.rds")
tfs <- readRDS("config/tfs.rds")
veh <- readRDS("config/fleet_age.rds")
pol <- c("CO", "HC", "NOx", "CO2", "PM", "NMHC")
year <- 2018
bg <- "white"
pal <- "mpl_viridis" # procura mais paletas com ?cptcity::find_cpt
breaks <- "quantile" # "sd" "quantile" "pretty"
tit <- "Emissões veiculares em São Paulo [t/ano]"
source("scripts/plots.R", encoding = "UTF-8")
# MECH ####
language <- "portuguese" # english spanish
months_subset <- "08" #only one month each time
g <- eixport::wrf_grid(paste0(system.file("extdata",
package = "eixport"),
"/wrfinput_d01"))
aer <- "pmneu2" # "pmiag", "pmneu"
# option 1 (if cb05-=> ecb05_opt1)
mech <- "iag_cb05" # "iag_cb05v2", "neu_cb05", "iag_racm"
pol <- c("CO", "NO", "NO2", "SO2", "CO2")
mol <- c(12, 14+16, 14+16*2, 32+16*2, 12+16*2)
source('scripts/mech.R', encoding = 'UTF-8')
# option 2 (if cb05-=> ecb05_opt2)
# mech <- "CB05" # "CB4", "CB05", "S99", "S7","CS7", "S7T", "S11", "S11D","S16C","S18B","RADM2", "RACM2","MOZT1"
# source('scripts/mech2.R', encoding = 'UTF-8')
# # remove some pollutant?
# file.remove("post/spec_grid/E_BENZENE.rds")
# WRF CHEM
language <- "portuguese" # english spanish
# hourly distribution for NOx with HDV
# hourly distribution for other than NOX with PC
tfs <- readRDS("config/tfs.rds")
remove_pol <- "E"
year <- 2018
days <- 30 #days of month
cols <- 99 # da grade
rows <- 149 # da grade
wrf_times <- 24 # ?
data("emis_opt")# names(emis_opt)
emis_option <- gsub(".rds", "", list.files(path = "post/spec_grid"))
pasta_wrfinput <- system.file("extdata",
package = "eixport")
pasta_wrfchemi <- "wrf"
wrfi <- paste0(system.file("extdata",
package = "eixport"),
"/wrfinput_d01")
domain <- 1
wrf_times <- 24
offset_hours <- 0
source("scripts/wrf.R", encoding = "UTF-8")
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