ef_wear | R Documentation |
ef_wear
estimates wear emissions.
The sources are tyres, breaks and road surface.
ef_wear(
wear,
type,
pol = "TSP",
speed,
load = 0.5,
axle = 2,
road = "urban",
verbose = FALSE
)
wear |
Character; type of wear: "tyre" (or "tire"), "break" (or "brake") and "road" |
type |
Character; type of vehicle: "2W", "MC", "Motorcycle", "PC", "LCV", 'HDV", "BUS", "TRUCKS" |
pol |
Character; pollutant: "TSP", "PM10", "PM2.5", "PM1" and "PM0.1" |
speed |
Data.frame of speeds |
load |
Load of the HDV |
axle |
Number of axle of the HDV |
road |
Type of road "urban", "rural", "motorway". Only applies when type is "E6DV" or "BEV" |
verbose |
Logical to show more information. Only applies when type is "E6DV" or "BEV" |
emission factors grams/km
Ntziachristos and Boulter 2016. Automobile tyre and break wear and road abrasion. In: EEA, EMEP. EEA air pollutant emission inventory guidebook-2009. European Environment Agency, Copenhagen, 2016
When type is "E6DV" or "BEV": Tivey J., Davies H., Levine J., Zietsman J., Bartington S., Ibarra-Espinosa S., Ropkins K. 2022. Meta Analysis as Early Evidence on the Particulate Emissions Impact of EURO VI to Battery Electric Bus Fleet Transitions. Paper under development.
{
data(net)
data(pc_profile)
pc_week <- temp_fact(net$ldv+net$hdv, pc_profile)
df <- netspeed(pc_week, net$ps, net$ffs, net$capacity, net$lkm, alpha = 1)
ef <- ef_wear(wear = "tyre", type = "PC", pol = "PM10", speed = df)
ef_wear(wear = "tyre",
type = c("E6DV"),
pol = "PM10",
verbose = TRUE)
ef_wear(wear = "tyre",
type = c("E6DV"),
pol = "PM10",
verbose = FALSE)
}
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