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 21 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 (almost 5 years ago)
- Default Branch: master
- Last Synced: 2025-04-21T06:37:23.670Z (7 days ago)
- Stars: 2
- Forks: 0
- Open Issues: 3
- Releases: 0
https://gitlab.com/ibarraespinosa/vein/blob/master/
# VEIN 
- build: [](https://ci.appveyor.com/project/ibarraespinosa/vein)
[](https://codecov.io/github/atmoschem/vein?branch=master)
- cran:
[](http://cran.rstudio.com/web/packages/vein/index.html)
[](http://cran.r-project.org/web/packages/vein)
[](http://cran.r-project.org/package=vein)
[](https://www.tidyverse.org/lifecycle/#maturing)
- doi:
[](https://zenodo.org/badge/latestdoi/88201850)
- github: [](https://github.com/atmoschem/vein)
[](https://github.com/atmoschem/vein/actions)
# **V**ehicular **E**missions **IN**ventories (VEIN)
### 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$ldv)
plot(PC_E25_1400)
#> Weighted mean = 11.17
```
If you want to know the vehicles per street and by age of use, just add
the net. Age functions now returns ‘sf’ objects if the net argument is
present.
``` r
PC_E25_1400net <- age_ldv(
x = net$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()
```
- [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
```
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()
```
 \#### 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))
```
#### 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()
```
#### 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
)
```
#### 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
[](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: .
### 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)
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Dependencies
DESCRIPTION
cran
- R >= 3.5.0 depends
- cptcity * imports
- data.table * imports
- dotCall64 * imports
- fields * imports
- grDevices * imports
- graphics * imports
- sf >= 1.0.1 imports
- stats * imports
- units * imports
- knitr * suggests
- rmarkdown * suggests
- testthat * suggests
Score: 2.3025850929940455