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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.

Note

These may be moving to vein at some point...

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