Functions to estimate vehicle weight-based non-exhaust PM2.5 and PM10 emission factors based on methods of Beddows and Harrison.
Usage
ef_beddows_nee_pm(
veh.wt,
em.type = c("pm2.5", "pm10"),
em.source = c("brake", "tyre", "road", "resusp"),
brk.regen = FALSE,
route.def = c("urban", "rural", "motorway"),
route.source = "uk naei",
verbose = FALSE,
...
)
ef_beddows_brake_pm2.5(em.type, em.source, ...)
ef_beddows_brake_pm10(em.type, em.source, ...)
ef_beddows_tyre_pm2.5(em.type, em.source, ...)
ef_beddows_tyre_pm10(em.type, em.source, ...)
ef_beddows_road_pm2.5(em.type, em.source, ...)
ef_beddows_road_pm10(em.type, em.source, ...)
ef_beddows_resusp_pm2.5(em.type, em.source, ...)
ef_beddows_resusp_pm10(em.type, em.source, ...)
Arguments
- veh.wt
(numeric, required) vehicle weight (in kg).
- em.type
(character) type of emissions to predict, by default PM2.5 and PM10.
- em.source
(character) emission source, by default brake, tyre, road and resuspension, but can be any combination.
- brk.regen
vehicle regenerative braking, default
FALSE
means not installed/used or a numeric (0-1) for efficiency if installed/used, e.g. 0.25 = 25% efficient (equivalent to a 75% of a conventional non-regenerative brake contribution).- route.def
(character) route definitions, by default urban, rural and motorway.
- route.source
(character) route sources, must be UK NAEI.
- verbose
(logical) If TRUE, include model parameters and methods details when reporting EF predictions.
- ...
other arguments, often passed on.
Value
These functions build data.frames of urban, rural and motorway emission
factors for non-exhaust PM2.5 and PM10. ef_beddows_nee_pm
is the main
function, and others are wrappers for single source and type emissions factors.
References
These functions are based on methods developed and reported by:
Beddows, D.C. and Harrison, R.M., 2021. PM10 and PM2.5 emission factors for non-exhaust particles from road vehicles: Dependence upon vehicle mass and implications for battery electric vehicles. Atmospheric Environment, 244, p.117886. https://doi.org/10.1016/j.atmosenv.2020.117886