vein

An R package to estimate Vehicular Emissions INventories.
https://gitlab.com/ibarraespinosa/vein
Category: Emissions
Sub Category: Emission Observation and Modeling
Keywords from Contributors

atmospheric-modelling atmospheric-science
Last synced: about 11 hours ago
JSON representation
Repository metadata

Host: gitlab.com
URL: https://gitlab.com/ibarraespinosa/vein
Owner: ibarraespinosa
License: other
Created: 2020-05-09T01:23:33.840Z (over 5 years ago)
Default Branch: master
Last Synced: 2025-12-14T17:13:48.190Z (11 days ago)
Stars: 2
Forks: 0
Open Issues: 3
Releases: 0
https://gitlab.com/ibarraespinosa/vein/blob/master/

          



# VEIN 

- build: [![AppVeyor Build
  Status](https://ci.appveyor.com/api/projects/status/github/ibarraespinosa/vein?branch=master&svg=true)](https://ci.appveyor.com/project/ibarraespinosa/vein)
  [![Coverage
  Status](https://img.shields.io/codecov/c/github/atmoschem/vein/master.svg)](https://codecov.io/github/atmoschem/vein?branch=master)
- cran:
  [![](http://cranlogs.r-pkg.org/badges/vein)](http://cran.rstudio.com/web/packages/vein/index.html)
  [![CRAN_Status_Badge](http://www.r-pkg.org/badges/version/vein)](http://cran.r-project.org/web/packages/vein)
  [![CRAN
  Downloads](http://cranlogs.r-pkg.org/badges/grand-total/vein?color=orange)](http://cran.r-project.org/package=vein)
  [![Package
  Status](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://www.tidyverse.org/lifecycle/#maturing)
  ![CRAN/METACRAN](https://img.shields.io/cran/l/vein?style=plastic)
- doi:
  [![DOI](https://zenodo.org/badge/88201850.svg)](https://zenodo.org/badge/latestdoi/88201850)
- github: [![Github
  Stars](https://img.shields.io/github/stars/atmoschem/vein.svg?style=social&label=Github)](https://github.com/atmoschem/vein)
  ![GitHub code size in
  bytes](https://img.shields.io/github/languages/code-size/atmoschem/vein)
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  ![GitHub commit
  activity](https://img.shields.io/github/commit-activity/y/ibarraespinosa/vein)
  [![R build
  status](https://github.com/atmoschem/vein/workflows/R-CMD-check/badge.svg)](https://github.com/atmoschem/vein/actions)



# **V**ehicular **E**missions **IN**ventories (VEIN)

![vein](https://user-images.githubusercontent.com/27447280/234115392-b1c891ff-474d-40a3-b9a7-e816ded9bc70.gif)

### TODO

- get_project with Chinese EF
- Include speed functions with Fortran
- Include CB6
- Add EF from HBEFA?
- See issues [GitHub](https://github.com/atmoschem/vein/issues) and
  [GitLab](https://gitlab.com/ibarraespinosa/vein/-/issues)

### 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](https://www.github.com/r-spatial/sf).

### Installation

#### CRAN

VEIN can be installed via CRAN or github

``` r
install.packages("vein")
```

#### GitHub

``` r
remotes::install_github("atmoschem/vein")
```

or if you have a **32 bits** machine

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

------------------------------------------------------------------------

#### demo

Then, if you want, run the demo

``` r
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](https://atmoschem.github.io/vein/reference/get_project.html)
and read the documentation, there you can see more projects as well.

Check the projects here:
()\[\]

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

The structure of the new directory “awesome_city” is:

``` r
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:

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

## Too complicated? Watch a YouTube




[English](https://www.youtube.com/embed/tHSWIjg26vg)




[Portuguese](https://www.youtube.com/watch?v=6-07Y0Eimng)

### 2. Use inventory (a bit not so easy)

Read the instruction of inventory

``` r
?inventory
```

#### 1) Examples with traffic data:

1.  If you know the distribution of the vehicles by age of use , use:
    [my_age](https://atmoschem.github.io/vein/reference/my_age.html)
2.  If you know the sales of vehicles or better the registry of new
    vehicles, use
    [age](https://atmoschem.github.io/vein/reference/age.html) to apply
    a survival function.
3.  If you know the theoretical shape of the circulating fleet and you
    can use
    [age_ldv](https://atmoschem.github.io/vein/reference/age_ldv.html),
    [age_hdv](https://atmoschem.github.io/vein/reference/age_hdv.html)
    or
    [age_moto](https://atmoschem.github.io/vein/reference/age_moto.html).
    For instance, you dont know the sales or registry of vehicles, but
    somehow you know the shape of this curve.
4.  You can use/merge/transform/adapt any of these functions.

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

plot(PC_E25_1400)
#> Weighted mean =  11.17
```

![](man/figures/unnamed-chunk-3-1.png)

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.

``` r
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()
```

![](man/figures/unnamed-chunk-4-1.png)

- [temp_fact](https://atmoschem.github.io/vein/reference/temp_fact.html)
- [netspeed](https://atmoschem.github.io/vein/reference/netspeed.html)

temporal factors and netspeed

``` r
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
```

![](man/figures/unnamed-chunk-5-1.png)

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

``` r
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()
```

![](man/figures/unnamed-chunk-6-1.png) \#### 2) Emission Factors

- [ef_ldv_speed](https://atmoschem.github.io/vein/reference/ef_ldv_speed.html)
- [ef_hdv_speed](https://atmoschem.github.io/vein/reference/ef_hdv_speed.html)
- [ef_ldv_scaled](https://atmoschem.github.io/vein/reference/ef_ldv_scaled.html)
- [ef_hdv_scaled](https://atmoschem.github.io/vein/reference/ef_hdv_scaled.html)
- [EmissionFactors](https://atmoschem.github.io/vein/reference/EmissionFactors.html)
- [EmissionFactorsList](https://atmoschem.github.io/vein/reference/EmissionFactorsList.html)

``` r
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))
```

![](man/figures/unnamed-chunk-7-1.png)

#### 3) Estimation of emissions

- [emis](https://atmoschem.github.io/vein/reference/emis.html)

``` r
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](https://atmoschem.github.io/vein/reference/emis_post.html)
- 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.

``` r
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()
```

![](man/figures/unnamed-chunk-9-1.png)

#### Grids

- [make_grid](https://atmoschem.github.io/vein/reference/make_grid.html).

1)  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.
2)  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.

``` r
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
)
```

![](man/figures/unnamed-chunk-10-1.png)

#### Creating a WRFChem Input file using [eixport](https://atmoschem.github.io/eixport/):

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

``` r
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

1.  Create a grid using
    [make_grid](https://atmoschem.github.io/vein/reference/make_grid.html)
    and your net.
2.  Run
    [emis_grid](https://atmoschem.github.io/vein/reference/emis_grid.html)
    to grid your emissions.
3.  Run
    [eixport::to_as4wrf](https://atmoschem.github.io/eixport/reference/to_as4wrf.html)
    to create a data.frame the specifications for AS4WRF.ncl.
4.  Export data.frame to a text.file. Recall that AS4WRF requires all
    the lumped species.
5.  Contact the developer of AS4WRF Angel Vara  to
    get a copy and run AS4WRF.ncl.

Thanks and enjoy VEIN!

## Citation

If you use VEIN, please, cite it
([BIBTEX](https://gmd.copernicus.org/articles/11/2209/2018/gmd-11-2209-2018.bib),
[ENDNOTE](https://gmd.copernicus.org/articles/11/2209/2018/gmd-11-2209-2018.ris)):

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,
, 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

[![Contributors](https://contrib.rocks/image?repo=atmoschem/vein)](https://github.com/atmoschem/vein/graphs/contributors)

## Communications, doubts etc

- Earth-Sciences on Stackoverflow, tag
  [vein-r-package](https://earthscience.stackexchange.com/questions/tagged/vein-r-package)
- Drop me an email  or 
  (你好中国朋友 - Hello Chinese friends!)
- Check the group on GoogleGroups
  [Group](https://groups.google.com/d/forum/veinmodel).
- Check the project on
  [ResearchGate](https://www.researchgate.net/project/VEIN-An-R-package-for-vehicular-emissions-inventories).

## Issues

If you encounter any issues while using VEIN, please submit your issues
to:  If you have any
suggestions just let me know to .

### Contributing

Please, read
[this](https://github.com/atmoschem/vein/blob/master/CONTRIBUTING.md)
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](https://google.github.io/styleguide/Rguide.xml). This project is
released with a [Contributor Code of
Conduct](https://github.com/atmoschem/vein/blob/master/CODE_OF_CONDUCT.md).
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](https://stackoverflow.com/questions/13575180/how-to-change-language-settings-in-r)