Read emission estimates generated by the emission_model or from emission factor functions (e.g. ef_brazil_cetesb) and convert them into a data.table format.

emis_to_dt(
  emi_list,
  emi_vars = "emi",
  veh_vars = "veh_type",
  pol_vars = "pollutant",
  process_vars = "process",
  segment_vars = NULL
)

Arguments

emi_list

list. A list of emission estimates

emi_vars

character. data.frame names of 'emi_list' object attributed to emissions or emission factors. Default is 'emi'.

veh_vars

character. data.frame names of 'emi_list' object attributed to vehicle characteristics. Default is 'veh_type'.

pol_vars

character. data.frame names of 'emi_list' object attributed to pollutants. Default is 'pollutant'.

process_vars

character. data.frame names of 'emi_list' object attributed to the emission processes. Default is 'process'.

segment_vars

character. data.frame names of 'emi_list' object attributed to the road segments. Default is NULL.

Value

data.table.

See also

Other emission analysis: emis_grid(), emis_summary()

Examples

# \donttest{
 if (requireNamespace("gtfstools", quietly=TRUE)) {

# read GTFS
gtfs_file <- system.file("extdata/bra_cur_gtfs.zip", package = "gtfs2emis")
gtfs <- gtfstools::read_gtfs(gtfs_file) 

# keep a single trip_id to speed up this example
gtfs_small <- gtfstools::filter_by_trip_id(gtfs, trip_id ="4451136")
  
# run transport model
tp_model <- transport_model(gtfs_data = gtfs_small,
                            min_speed = 2,
                            max_speed = 80,
                            new_speed = 20,
                            spatial_resolution = 100,
                            parallel = FALSE)

# Example using Brazilian emission model and fleet
fleet_data_ef_cetesb <- data.frame(veh_type = "BUS_URBAN_D",
                                   model_year = 2010:2019,
                                   fuel = "D",
                                   fleet_composition = rep(0.1,10)
                                   )
                                   
emi_list <- emission_model(
                tp_model = tp_model,
                ef_model = "ef_brazil_cetesb",
                fleet_data = fleet_data_ef_cetesb,
                pollutant = c("CO","PM10","CO2","CH4","NOx")
                )

# convert emission list to data.table
dt <- emis_to_dt(emi_list)
}
#> Converting shapes to sf objects
#> Processing the data
#> Constant emission factor along the route
# }