Vehicular Emissions INventory (VEIN) model.

What is VEIN ?

Vehicular Emissions Inventories. An R package to estimate vehicular emissions. It currently covers the following pollutants in speed functions:

Criteria: “CO”, “NOx”, “HC”, “PM”, “CH4”, “NMHC”, “CO2”, “SO2”, “Pb”, “FC” (Fuel Consumption).
PAH and POP: “indeno(1,2,3-cd)pyrene”, “benzo(k)fluoranthene”, “benzo(b)fluoranthene”, “benzo(ghi)perylene”, “fluoranthene”, “benzo(a)pyrene”, “pyrene”, “perylene”, “anthanthrene”, “benzo(b)fluorene”, “benzo(e)pyrene”, “triphenylene”, “benzo(j)fluoranthene”, “dibenzo(a,j)anthacene”, “dibenzo(a,l)pyrene”, “3,6-dimethyl-phenanthrene”, “benzo(a)anthracene”, “acenaphthylene”, “acenapthene”, “fluorene”, “chrysene”, “phenanthrene”, “napthalene”, “anthracene”, “coronene”, “dibenzo(ah)anthracene”
Dioxins and Furans: “PCDD”, “PCDF”, “PCB”.
Metals: “As”, “Cd”, “Cr”, “Cu”, “Hg”, “Ni”, “Pb”, “Se”, “Zn”.
NMHC:
ALKANES: “ethane”, “propane”, “butane”, “isobutane”, “pentane”, “isopentane”, “hexane”, “heptane”, “octane”, “TWO_methylhexane”, “nonane”, “TWO_methylheptane”, “THREE_methylhexane”, “decane”, “THREE_methylheptane”, “alcanes_C10_C12”, “alkanes_C13”.
CYCLOALKANES: “cycloalcanes”.
ALKENES: “ethylene”, “propylene”, “propadiene”, “ONE_butene”, “isobutene”, “TWO_butene”, “ONE_3_butadiene”, “ONE_pentene”, “TWO_pentene”, “ONE_hexene”, “dimethylhexene”.
ALKYNES:“ONE_butine”, “propine”, “acetylene”.
ALDEHYDES: “formaldehyde”, “acetaldehyde”, “acrolein”, “benzaldehyde”, “crotonaldehyde”, “methacrolein”, “butyraldehyde”, “isobutanaldehyde”, “propionaldehyde”, “hexanal”, “i_valeraldehyde”, “valeraldehyde”, “o_tolualdehyde”, “m_tolualdehyde”, “p_tolualdehyde”.
KETONES: “acetone”, “methylethlketone”.
AROMATICS: “toluene”, “ethylbenzene”, “m_p_xylene”, “o_xylene”, “ONE_2_3_trimethylbenzene”, “ONE_2_4_trimethylbenzene”, “ONE_3_5_trimethylbenzene”, “styrene”, “benzene”, “C9”, “C10”, “C13”.

Also, Brazilian emission factors and speciations for WRF-Chem runs:

e_eth e_hc3 e_hc5 e_hc8 e_ol2 e_olt e_oli e_iso e_tol e_xyl e_c2h5oh e_ald e_hcho e_ch3oh e_ket E_SO4i E_SO4j E_NO3i E_NO3j E_MP2.5i E_MP2.5j E_ORGi E_ORGj E_ECi E_ECj

BONUS: I’ve added the CETESB Emissio Factors 2016!

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.

Packages needed

After installing system dependencies, you will need these packages:

In order to run the demo, this package is also needed:

ggplot2

Installation

VEIN can be installed via CRAN or github

library(devtools) 
install_github("atmoschem/vein")
library(vein)
demo(VEIN)

install.packages("vein")
library(vein)
demo(VEIN)

What is new? (v0.5.2)

grid_emis To allocate gridded emissions to streets by grid cell.
ef_ive International Vehicular Emission Model - Base Emission Factors IVE.
ef_whe to account for high emitters emission factor on fleet.
ef_im emission factors by used vehicles with normal deterioration, depending on accumulated mileage.
ef_cetesb Emission factors of the Environmental Agency of São Paulo State, Brazil.
vein_notes To generates .txt files which includes specification of the machine.
emis_source to source vein scripts.
emis_dist function to distribute top-down emissions into ‘sf’ objects by feature, specifically, ir returns a vector of lines (streeets).
Check the NEWS

future steps

More tests!
Parallelism. I’ve done some tests already with good results.
RCPP integration. I would like to do it, specifically in emis.
Estimation of evaporative emissions with Copert Tier 3.
More speciations.
A draft book already published https://bookdown.org/zergioibarra/veinbook/ and source here: https://github.com/ibarraespinosa/VEINBOOK.

How does it work?

VEIN consist of: “Elaboration of vehicular emissions inventories, consisting in four stages:

pre-processing activity data,
preparing emissions factors,
estimating the emissions and
post-processing of emissions in maps and databases."

This implies the use of several functions in a coordinates ans structured way, therefore it is added the new function inventory which creates a structured set of directories and scripts to run VEIN. Please, open the file ‘main.R’ and run each line to understand VEIN. Remember, if you have doubts with any function, just type ‘?’ with the name of the function. For intance: ?inventory.

Using inventory

library(vein)
inventory(name = file.path(tempdir(), "YourCity"), show.dir = T,
          show.scripts = T)

## files at /tmp/RtmpIbtREd/YourCity

## Directories:
##  [1] "/tmp/RtmpIbtREd/YourCity"             
##  [2] "/tmp/RtmpIbtREd/YourCity/ef"          
##  [3] "/tmp/RtmpIbtREd/YourCity/emi"         
##  [4] "/tmp/RtmpIbtREd/YourCity/emi/BUS_01"  
##  [5] "/tmp/RtmpIbtREd/YourCity/emi/HGV_01"  
##  [6] "/tmp/RtmpIbtREd/YourCity/emi/LCV_01"  
##  [7] "/tmp/RtmpIbtREd/YourCity/emi/MC_01"   
##  [8] "/tmp/RtmpIbtREd/YourCity/emi/PC_01"   
##  [9] "/tmp/RtmpIbtREd/YourCity/est"         
## [10] "/tmp/RtmpIbtREd/YourCity/images"      
## [11] "/tmp/RtmpIbtREd/YourCity/network"     
## [12] "/tmp/RtmpIbtREd/YourCity/post"        
## [13] "/tmp/RtmpIbtREd/YourCity/post/df"     
## [14] "/tmp/RtmpIbtREd/YourCity/post/grids"  
## [15] "/tmp/RtmpIbtREd/YourCity/post/streets"
## [16] "/tmp/RtmpIbtREd/YourCity/profiles"    
## [17] "/tmp/RtmpIbtREd/YourCity/veh"         
## Scripts:
## [1] "est/BUS_01_input.R" "est/HGV_01_input.R" "est/LCV_01_input.R"
## [4] "est/MC_01_input.R"  "est/PC_01_input.R"  "main.R"            
## [7] "post.R"             "traffic.R"

Please, read the examples in the documentation of each function and run the demo.

1) Examples with traffic data:

age functions:

data("net")
PC_E25_1400 <- age_ldv(x = net$ldv, name = "PC_E25_1400")

## Average age of PC_E25_1400 is 11.17

## Number of PC_E25_1400 is 1946.95 * 10^3 veh

plot(PC_E25_1400, xlab = "age of use")

## 
## Average =  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, name = "PC_E25_1400", net = net)

## Average age of PC_E25_1400 is 11.17

## Number of PC_E25_1400 is 1946.95 * 10^3 veh

sp::spplot(as(PC_E25_1400net, "Spatial"),
       c("PC_E25_1400_1", "PC_E25_1400_9"),
       main = "PC by age of use", scales = list(draw = T),
       col.regions = rev(cptcity::cpt()))

- temp_fact - netspeed

temporal factors and netspeed

data("net")
data("pc_profile")
pc_week <- temp_fact(net$ldv+net$hdv, pc_profile)
dfspeed <- netspeed(pc_week, net$ps, net$ffs, net$capacity, net$lkm, alpha = 1.5)
class(dfspeed)

## [1] "Speed"      "data.frame"

plot(dfspeed, xlab = "Hours", ylab = "Speed [km/h]")

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

dfspeednet <- netspeed(pc_week, net$ps, net$ffs, net$capacity, net$lkm,
                       alpha = 1.5, net = net)
sp::spplot(as(dfspeednet, "Spatial"),
       c("S1", "S9"), scales = list(draw = T),
       col.regions = rev(cptcity::cpt()))

2) Emission Factors

V <- 0:150
ef1 <- ef_ldv_speed(v = "PC",t = "4S", cc = "<=1400", f = "G", eu = "PRE",
p = "CO")
efs <- EmissionFactors(ef1(1:150))
plot(Speed(1:150), efs, xlab = "speed[km/h]", type = "b", pch = 16)

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)

## Number of columns of 'veh' is different than length of 'ef'

## adjusting length of ef to the number of colums of 'veh'

## 139727.29 kg emissions in 24 hours and 7 days

plot(E_CO, xlab = "Hours", ylab = "[g/h]")

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")
E_CO_STREETS <- emis_post(arra = E_CO, pollutant = "CO", by = "streets_wide")

Grids

make_grid.

You can use this function in two ways

when spobj is “character”, it is a path to wrfinput file and then runs eixport::wrf_grid to create a grid based on a wrf_input file.

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(net, 1/102.47/2) #500m in degrees

## Number of lon points: 23
## Number of lat points: 19

E_CO_g <- emis_grid(spobj = E_CO_STREETSnet, g = g, sr= 31983)

## Transforming spatial objects to 'sr'

## Sum of street emissions 139727288.63
## Sum of gridded emissions 139727288.63

sp::spplot(as(E_CO_g, "Spatial"),
       c("V1", "V9"), scales = list(draw = T),
       col.regions = rev(cptcity::cpt()))

At this step, you can feed you grid with emissions from other sources!

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.

eixport::wrf_create(wrfinput_dir = "PathToWrfInput", wrfchemi_dir = "OutputPathWrfChemInput")
gwrf <- eixport::wrf_grd("PathToWrfInput")
E_CO_gwrf <- emis_grid(spobj = E_CO_STREETSnet, g = gwrf)
gr <- GriddedEmissionsArray(E_CO_gwrf, rows = 19, cols = 23, times = 168, T)
eixport::wrf_put(file = "Path/To/WRFChemInputFile, 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 emis_wrf to create a data.frame the specifications for AS4WRF.ncl.
Export the output of emis_wrf to a text file without header. Recall that AS4WRF requires all the lumped species.
Contact the developer of AS4WRF Angel Vara alvv1986@gmail.com 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://www.geosci-model-dev.net/11/2209/2018/},
doi = {10.5194/gmd-11-2209-2018}
}

Communications, doubts etc

Drop me an email sergio.ibarra@usp.br
You can ask on Eart Science Stackoverflow,.
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 sergio.ibarra@usp.br.

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.

VEIN model

Sergio Ibarra-Espinosa

19 de Octubre de 2016