atmoschem / vein Goto Github PK

R+Fortran+OpenMP package to estimate Vehicular Emissions INventories VEIN.

Home Page: https://atmoschem.github.io/vein/

License: Other

R 98.73% Fortran 0.92% C 0.27% Shell 0.08%

atmospheric-science atmospheric-sciences vein vehicular-emissions-inventories emissions atmoschem atmospheric-chemistry emissions-model

vein's Introduction

VEIN

build:
cran:
doi:
github:

Vehicular Emissions INventories (VEIN)

vein

TODO

Include speed functions with Fortran
Include CB6
Add EF from HBEFA?
See issues GitHub

System requirements

vein imports functions from spatial packages listed below. In order to install these packages, firstly the user must install the requirements mentioned here.

Installation

CRAN

VEIN can be installed via CRAN or github

install.packages("vein")

GitHub

remotes::install_github("atmoschem/vein")

or if you have a 32 bits machine

install_github("atmoschem/vein",
INSTALL_opts = "--no-multiarch")

demo

Then, if you want, run the demo

library(vein) 
demo(VEIN)

Approaches

1. get a project (easier)

At the moment, most of the projects covers Brazilian regions, but I will include China, Europe or USA approaches as soon as I can.

Use the function get_project and read the documentation, there you can see more projects as well.

Check the projects here: (https://atmoschem.github.io/vein/reference/get_project.html)[https://atmoschem.github.io/vein/reference/get_project.html]

library(vein)
?get_project
get_project(directory = "awesome_city")

The structure of the new directory “awesome_city” is:

awesome_city
├── config
│   ├── clean.R
│   ├── config.R
│   ├── inventory.xlsx
│   └── packages.R
├── main.R
├── main.Rproj
├── network
│   ├── net.gpkg
│   └── net.rds
├── scripts
│   ├── evaporatives.R
│   ├── exhaust.R
│   ├── fuel_eval.R
│   ├── net.R
│   ├── pavedroads.R
│   ├── plots.R
│   ├── post.R
│   ├── traffic.R
│   └── wrf.R
└── wrf
└── wrfinput_d02

You have to open the file main.Rproj with Rstudio and then open and run main.R

To run main.R you will need these extra packages:

ggplot2
readxl
eixport (If you plan to generate WRF Chem emissions file)

If you do not have them already, you can install:

install.packages(c("ggplot2", "readxl", "eixport"))

Too complicated? Watch a YouTube

English

Portuguese

2. Use inventory (a bit not so easy)

Read the instruction of inventory

?inventory

1) Examples with traffic data:

If you know the distribution of the vehicles by age of use , use: my_age
If you know the sales of vehicles or better the registry of new vehicles, use age to apply a survival function.
If you know the theoretical shape of the circulating fleet and you can use age_ldv, age_hdv or age_moto. For instance, you dont know the sales or registry of vehicles, but somehow you know the shape of this curve.
You can use/merge/transform/adapt any of these functions.

library(vein)
data("net")
PC_E25_1400 <- age_ldv( x = net$ldv)

plot(PC_E25_1400)
#> Weighted mean =  11.17

If you want to know the vehicles per street and by age of use, just add the net. Age functions now returns ‘sf’ objects if the net argument is present.

PC_E25_1400net <- age_ldv(
  x = net$ldv, 
  net = net
)
plot(PC_E25_1400net, 
  key.pos = 4, 
  pal = cptcity::cpt(
    colorRampPalette = T, 
    rev = T))
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> Warning: plotting the first 9 out of 50 attributes; use max.plot = 50 to plot
#> all
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()

temporal factors and netspeed

data("net")
data("pc_profile")
pc_week <- temp_fact(
  net$ldv + net$hdv, 
  pc_profile
)
dfspeed <- netspeed(
  q = pc_week, 
  ps = net$ps, 
  ffs = net$ffs, 
  cap = net$capacity, 
  lkm = net$lkm, 
  alpha = 1.5
)
plot(dfspeed)
#> Weighted mean =  44.16

If you want ot check the speed at different hours by street, just add net:

dfspeednet <- netspeed(
  q = pc_week, 
  ps = net$ps, 
  ffs = net$ffs, 
  cap = net$capacity, 
  lkm = net$lkm,
  alpha = 1.5, 
  net = net
)
plot(
  dfspeednet[, c("S1", "S9")], 
  key.pos = 4, 
  pal = cptcity::cpt(colorRampPalette = T, 
                     rev = T), 
  axes = T
)
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()

#### 2) Emission Factors

V <- 0:150
ef1 <- ef_ldv_speed(
  v = "PC",
  t = "4S", 
  cc = "<=1400", 
  f = "G",
  eu = "PRE",
  p = "CO"
)
ef2 <- ef_ldv_speed(
  v = "PC",
  t = "4S", 
  cc = "<=1400", 
  f = "G",
  eu = "III",
  p = "CO"
)

ef1 <- EmissionFactors(ef1(1:150))
ef2 <- EmissionFactors(ef2(1:150))
colplot(data.frame(PRE = ef1, III = ef2))

3) Estimation of emissions

emis

euro <- c(
  rep("V", 5), 
  rep("IV", 5), 
  rep("III", 5), 
  rep("II", 5),
  rep("I", 5), 
  rep("PRE", 15)
)
lef <- lapply(1:40, function(i) {
  ef_ldv_speed(
    v = "PC", 
    t = "4S",
    cc = "<=1400", 
    f = "G",
    eu = euro[i], 
    p = "CO", 
    show.equation = FALSE
  ) 
})
E_CO <- emis(
  veh = PC_E25_1400, 
  lkm = net$lkm, 
  ef = lef, 
  speed = dfspeed,
  profile = pc_profile
)

4) Post Emissions

emis_post
When the argument by = “veh” the emissions are aggregated by age and hour.
When the argument by = “streets_wide”, aggregated the emissions by street. In this cae, if you add the argument net with the respective streets, it returns an spatial net with the hourly emissions.

E_CO_DF <- emis_post(
  arra = E_CO,  
  veh = "PC", 
  size = "<1400", 
  fuel = "G",
  pollutant = "CO", 
  by = "veh", 
  type_emi = "exhaust"
)
E_CO_STREETS <- emis_post(
  arra = E_CO, 
  pollutant = "CO", 
  by = "streets", 
  net = net
)
plot(
  E_CO_STREETS[, c("V1", "V9")], 
  key.pos = 4, 
  pal = cptcity::cpt(colorRampPalette = T, 
                     rev = T), 
  axes = T)
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()

Grids

make_grid.

Create a grid using make_grid.The spobj is the spatial net. The size of the grid has the size of the net. You have to specify the grid spacing.
Create a grid using a path to wrfinput file instead a net. The grid will have the size of the wrf_input. You don’t have to specify the grid spacing.

data(net)
E_CO_STREETSnet <- emis_post(
  arra = E_CO, 
  pollutant = "CO",
  by = "streets_wide",
  net = net
)
g <- make_grid(
  spobj = net, 
  width = 1/102.47
)
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> Number of lon points: 12
#> Number of lat points: 10
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
E_CO_g <- emis_grid(
  spobj = E_CO_STREETSnet, 
  g = g, 
  sr= 31983
)
#> Your units are:
#> g
#> Transforming spatial objects to 'sr'
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> Sum of street emissions 148791715.29
#> Sum of gridded emissions 148791715.29
na <- paste0("V", 1:168)
for(i in 1:168) E_CO_g[[na[i]]] <- E_CO_g[[na[i]]] * units::set_units(1, "1/h")
plot(
  E_CO_g[, c("V1", "V9")], 
  key.pos = 4, 
  pal = cptcity::cpt(colorRampPalette = T, 
                     rev = T,
                     pal = "mpl_viridis"), 
  axes = T, 
  lty = 0
)

Creating a WRFChem Input file using eixport:

Create a grid using make_grid and a wrfinput file
Run emis_grid to grid your emissions.
Create a GriddedEmissionsArray.
Create a wrfchem input file [eixport::wrf_create](https://atmoschem.github.io/eixport/reference/wrf_create.html.
Put the GriddedEmissionsArray into the wrf chem input file using eixport::wrf_put.

library(eixport)
dir.create(file.path(tempdir(), "EMISS"))
wrf_create(wrfinput_dir         = system.file("extdata", package = "eixport"),
wrfchemi_dir         = file.path(tempdir(), "EMISS"),
domains              = 2,
frames_per_auxinput5 = 1, #hours
auxinput5_interval_m = 60,
verbose              = TRUE)
path_to_wrfi <- paste0(system.file("extdata", package = "eixport"), "/wrfinput_d02")
path_to_wrfc <- list.files(file.path(tempdir(), "EMISS"), full.names = TRUE)[1]
gwrf <- eixport::wrf_grid(path_to_wrfi)
E_CO_gwrf <- emis_grid(spobj = E_CO_STREETSnet, g = gwrf)
gr <- GriddedEmissionsArray(E_CO_gwrf, rows = 51, cols = 63, times = 1)
eixport::wrf_put(file = path_to_wrfc, name = "E_CO", POL = gr)

Creating a WRFChem Input file using AS4WRF

Create a grid using make_grid and your net.
Run emis_grid to grid your emissions.
Run eixport::to_as4wrf to create a data.frame the specifications for AS4WRF.ncl.
Export data.frame to a text.file. Recall that AS4WRF requires all the lumped species.
Contact the developer of AS4WRF Angel Vara [email protected] to get a copy and run AS4WRF.ncl.

Thanks and enjoy VEIN!

Citation

If you use VEIN, please, cite it (BIBTEX, ENDNOTE):

Ibarra-Espinosa, S., Ynoue, R., O’Sullivan, S., Pebesma, E., Andrade, M. D. F., and Osses, M.: VEIN v0.2.2: an R package for bottom-up vehicular emissions inventories, Geosci. Model Dev., 11, 2209-2229, https://doi.org/10.5194/gmd-11-2209-2018, 2018.

@article{gmd-11-2209-2018,
author = {Ibarra-Espinosa, S. and Ynoue, R. and O'Sullivan, S. and Pebesma, E. and Andrade, M. D. F. and Osses, M.},
title = {VEIN v0.2.2: an R package for bottom--up vehicular emissions inventories},
journal = {Geoscientific Model Development},
volume = {11},
year = {2018},
number = {6},
pages = {2209--2229},
url = {https://gmd.copernicus.org/articles/11/2209/2018/},
doi = {10.5194/gmd-11-2209-2018}
}

Special thanks to all the contributors

Communications, doubts etc

Earth-Sciences on Stackoverflow, tag vein-r-package
Drop me an email [email protected] or [email protected] (你好**朋友 - Hello Chinese friends!)
Check the group on GoogleGroups Group.
Check the project on ResearchGate.

Issues

If you encounter any issues while using VEIN, please submit your issues to: https://github.com/atmoschem/vein/issues/ If you have any suggestions just let me know to [email protected].

Contributing

Please, read this guide. Contributions of all sorts are welcome, issues and pull requests are the preferred ways of sharing them. When contributing pull requests, please follow the Google’s R Style Guide. This project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.

Note for non-english and anaconda users

Sometimes you need to install R and all dependencies and a way for doing that is using anaconda. Well, as my system is in portuguese, after installing R using anaconda it changed the decimal character to ‘,’. In order to change it back to english meaning decimal separator as ‘.’, I added this variable into the .bashrc

nano ~/.bashrc
export Lang=C

More details on StackOverflow

vein's People

Contributors

Stargazers

Watchers

Forkers

edzer salvatirehbein pedro-andrade-inpe gitter-badger joaobazzo aadler knut11 yingw1014 quishqa xenos-code schuch666 raisantana iaradasilva karlropkins ramespada

vein's Issues

emis_wrf should change times based on attr()

emis_wrf should return dataframe with local and UTC time. Local time should be converted based on attr()

improve time in emis_wrf and change name?

time in wmis_wrf should use attr(x, "tzone") <- "tz". Therefore, the argument "utc" is not necesary anymore. Also, the name 'wrf' it is no t necessary because it could be used with different models. This function l probably will be deprecated once it is ready the package eix, which will export emissions to different, models, including WRF.

hours emis_post wrong when veh is list of Vehicles data-frame

hours are incorrectly assigned in output of emis_post when veh is a list of vehicles data-frame.

pc_profile

I was wondering why the emissions profile does not add 24 * 7 = 168.
I always thought that the sum of the emissions of all hours of the day of the week should add up to the total emissions for that week with a uniform profile.
Thanks in advance,
Mel

add emis_topdown

This function would allow estimating top-down vehicular emissions. Possible features:

It allows estimations with mileage by age of use.
Read spatial polygons with fleet by type of vehicle and/or mileage by age of use.
If it is used average hourly mileage, it could be used directly inside emis.
Reads emission factors for n pollutants
Produces an EmissionsArray which could be processed with emis_post to produce a data-base.

EmissionsArray, maybe 3 dimensions??

An EmissionsArray has 4 dimensions, number of streets, the category of vehicles, hours and days. However, as the last two dimensions represent time, maybe it could be better to eliminate the last dimension and the third dimensions could be only the total number of hours.

Add split between HC and CH4

Needs #30

add Warning when unit of lkm is 'm' in emis

this can reduce alot of future pŕoblems

Print sum of emissions when estimating

age_* and my_age function message sum of vehicles with few digits

now message rounds sums of 110^6 vehicles with 2 digits. It should be sum of 110^3 vehicles

vein should not depend on sp

According to Writting R Extensions, in DESCRIPTION, the field Depends should be nowadays used rarely, only for packages which are intended to be put on the search path to make their facilities available to the end user, for instance, latticeExtra depends on *lattice. In the case of vein, few times sp functions are called therefore it is not justified.

add flexibility in age functions

Age functions allow producing age distribution of vehicles in circulation. The functions are base on scrapping functions of the National Emissions Inventory for Brazil, 1996 and 2001. These functions can be restrictive and need to be updated. The goal is to have functions that can represent on average, a specific vehicular market.

Support for sf

sf is an R package of spatial features. VEIN needs to migrate its dependencies from sp to sf

inventory

linha 46 e 47 deveria ter deparse para o tipo de veiculo

adt?

Average Daily Traffic (ADT) is a common metric in transportation studies, used also as input for estimating emissions. It should be included

Add speciation of PM

Needs #30

Add summary in emis_wrf output

The user must convert the emissions from grams to mol before using emis_wrf. It would be convenient to add a summary of the output when using emis_wrf.

The output of emis_wrf is in wrong order

The output of emis_wrf is:
LONG, LAT, ID, ....
and it should be
ID, LONG, LAT, ....

Add message of sum of vehicles in age functions

This feature would provide a quick check if vehicles distributions are consistent

Add option to show messages in age* functions and plot.Vehicles

The age* functions (age_ldv, age_hdv, age_moto and my_age) return a message with a total number of vehicles and average age. It would be good to add an option to shows or not these messages

Required new set of profiles for topdown emissions

normalized hourly profiles are not equal than the resulting profiles after estimating emissions. Hence, it is necessary to add hourly emissions profiles to temporally distribute top-down emissions

Message with sum in emis

It would be a good idea print a message with sum of emissions in emis functions

make_grid would message characteristics of grid

This could be good when for constructing grid with WP in WRF

mechanism for emis_wrf need to be updated

emis_Wrf depends on AAS4WRF (Vera, 2015) configuration. This configuration has changed. Now it is for mechanism CBMZ. The pollutants 36 species. The output of emis_wrf should contain one column per pollutant and in the case that there are no emissions, the column should have filled with 0.
Compounds:

"E_SO2"
"E_NO"
"E_ALD"
"E_HCHO"
"E_ORA2"
"E_NH3"
"E_HC3"
"E_HC5"
"E_HC8"
"E_ETH"
"E_CO"
"E_OL2"
"E_OLT"
"E_OLI"
"E_TOL"
"E_XYL"
"E_KET"
"E_CSL"
"E_ISO"
"E_NO2"
"E_CH3OH"
"E_C2H5OH"
"E_PM25I"
"E_PM25J"
"E_SO4I"
"E_SO4J"
"E_NO3I"
"E_NO3J"
"E_ORGI"
"E_ORGJ"
"E_ECI"
"E_ECJ"
"E_SO4C"
"E_NO3C"
"E_ORGC"
"E_ECC"

linha 42 de input.R repete x_DF

speciate IAG needs to be fixed

the updated speciation of IAG excluded CH3OH and KET incorrectly added. This implies to change the function speciate.

dataframe for storing emi_post df outputs?

It would be good to include an argument in emis_post that point to a path with a data-frame to rbind newer results. This can wotk like a data-base with newer dependencies, only base.

speciate is not working properly

speciate does not produce mol/h

Add speciation of NMHC

Needs #30

Deberia emis_post incluir otra clasificación?

los argumentos de emis_post son:

args(emis_post)
function (arra, veh, size, fuel, pollutant, by = "veh")

veh, size, fuel y pollutant son strings para generar una base de datos clasificada. Sin embargo, podria ser mejor incluir una classificación desde lo mas general a lo mas particular:

fam (family): PC, LCV, HGV, Bus o MC
subfam: HGV-A (A de Articulado), HGV-R (R de Rigido), Coach.
fuel: fuel
size: cilindradas del motor o peso bruto del camión
vehcomp: nombre compuesto de la composición vehicular. Por ejemplo: PC_E25_1400.

Generará una base de datos mas pesada pero mejor clasificada.

Documentation of vein::inventory

Missing description of est directory.

Message with sum of emissions needs improvement

The message needs to separate letters and round the sum of emissions

Output of emis_wrf according to 6 hours meteorological data

When running WRF-Chem or other atmospheric models it is necessary meteorological data as input. This data has different temporal resolution and must match with UTC hourly emissions, in general.
A common database is NCAR/UCAR Global Forcast System https://rda.ucar.edu/datasets/ds335.0 but time resolution is each 6 hours. There are other datasets of 3 hours time resolution. Therefore, it would be convenient to have an argument in emis_wrf to match the hours of the emissions to the hours UTC of the meteorological data.

add suport for list of vehicles data-frames for vkm

VEIN reads list of Vehicle data-frame but vkm it is not updated

Error in new table of iag speciation

There is an error in table of speciation for painting

Should I delete by streets_narrow in emis_post?

I've never used this option

emis_wrf should convert automatically spatial bject with WGS84 lat lon coordinates

If emis_wrf uses projected emissions grids the output will be projected coordinates. This function automatically should reproject the output to WGS84 lat lon

Improve plots

Plots should be spatial and temporal. These plots will be improved after migrating to sf

emis_merge

Emissions are estimated for each type of vehicle, street different hour. Also, emis_post generates
three type of files. At the end there are a lot of files. Hence, an emis_merge function would be useful. This function will not be related with the base::merge functions, but, it will load all emissions according to an specific format and mergte,rbind,cbind them (see #36).

It is important to preserve any spatial attribute, so this function would work better with sf objects (see #5 )

name argument in age functions

argument name in age functions should have a default value

Fix mileage functions so that they are positive

some mileage functions return negative values some ages.

https://www.researchgate.net/publication/261870923_Curvas_de_intensidade_de_uso_por_tipo_de_veiculo_automotor_da_frota_da_cidade_de_Sao_Paulo?el=1_x_2&enrichId=rgreq-ce74b752-7df5-4db6-a7f2-658fe7d6eb47&enrichSource=Y292ZXJQYWdlOzI2MTg3MDkyMztBUzoxMDEwNDc1MDY4MzM0MTVAMTQwMTEwMzAxMTU2MQ%3D%3D

Light Flex vehicles only

emis_post assumes that estimation is for 7 days of the week

emis_posts with by = "veh" assumes a 7 days of the week estimation.

ef_* accepts vectorized arguments

ed_* emission factors functions are useful but when integrating into a street reality, lacks flexibility. For instance, there are arguments to account for load and gradient but one at the time. It would be good that these functions accept vectorized values, for example:
gradient <- c(0, 0.2, 0.4, 0.6) Representing streets with gradient 0, 0.2, 0.4 and 0.6. The length of this vectorized arguments should be equal to the number of streets. This function should allow having different values at different hours, for example, for evaluating the hourly variation of load in urban buses or trucks.

Function to work with units in data.frames

Sometimes it is necessary to convert to units or unclass several columns of dataframes. In other occasions, it is necessary to add units. It would be convenient to create a function to do that.

Improve estimation of evaporative emissions

currently Evaporative emissions are based on tier 2 EEA emission guidelines. The improvement includes hourly distribution and Tier 3

skeleton function needed

It is needed an 'skeleton' function to create folders fir i/o in a known structure, or skeleton. This functons could be named vein::vein and will use dir.create and other file functions.

This functions must be flexible in order to produce folders and/or files.

data.table?

VEIN functions could include the dependency on data.table functions so that it produces faster estimations. This could imply in modification in all function but these modifications should be only internal, they must preserve the same arguments

NMHC Speciation IAG incorrect

The speciation of NMHC from tunnel studie of IAG/USP is incorrect. There is no emissions of methanol. New table will be fixed in next commit

filter by na in my_age?

if
veh <- veh$PC <- c(0, 0, 0, 1, 2, 3 , NA, NA)
0 means that vehicles produced at first and second age (index). Last two NA indicates that the didnt exist vehicles at age 7 and 8. For instance, these type of vehicles started being produced at age 6 but the data already includes the last two NA.

Maybe, it could be a good idea include a filter for excluding NA in this parameter

veh$PC[!is.na(veh$PC)]

ef_nitro error form some categories

ef_nitro presents an error when filtering for some parameters. The problem is that there are still some values "ALL" that need to be changed at internal data.

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