emission_model: Emission model

Description

Estimate hot-exhaust emissions of public transport systems. This function must be used together with transport_model.

Usage

emission_model(
  tp_model,
  ef_model,
  fleet_data,
  pollutant,
  reference_year = 2020,
  process = "hot_exhaust",
  heightfile = NULL,
  parallel = TRUE,
  ncores = NULL,
  output_path = NULL,
  continue = FALSE,
  quiet = TRUE
)

Value

A list with emissions estimates or NULL with output files saved locally at output_path.

Arguments

tp_model: sf_linestring object or a character path the to sf_linestring objects. The tp_model is the output from transport_model, or the path in which the output files from the transport_model are saved.
ef_model: character. A string indicating the emission factor model to be used. Options include ef_usa_moves, ef_usa_emfac,ef_europe_emep, ,ef_brazil_cetesb, and ef_brazil_scaled_euro (scale ef_brazil_cetesb() based on ef_scaled_euro()).
fleet_data: data.frame. A data.frame with information the fleet characteristics. The required columns depend on the ef_model selection. See @examples for input.
pollutant: character. Vector with one or more pollutants to be estimated. Example: c("CO", "CO2", "PM10", "NOx"). See the documentation to check which pollutants are available for each emission factor model (ef_usa_moves, ef_usa_emfac, ef_europe_emep, or ef_brazil_cetesb).
reference_year: numeric. Year of reference considered to calculate the emissions inventory. Defaults to 2020. This argument is only required when the ef_model parameter is ef_usa_moves or ef_usa_emfac.
process: character; Emission process, classified in "hot_exhaust" (Default), and wear processes (identified as "tyre","brake" and/or "road" wear). Note that wear processes are only available when the ef_europe_emep is selected in the @param ef_model. Details on wear emissions are presented in emi_europe_emep_wear.
heightfile: character or raster data. The raster file with height data, or its filepath, used to estimate emissions considering the effect of street slope. This argument is used only when ef_brazil_scaled_euro or ef_europe_emep are selected. Default is NULL. Details are provided in slope_class_europe_emep.
parallel: logical. Decides whether the function should run in parallel. Defaults is TRUE.
ncores: integer. Number of cores to be used in parallel execution. This argument is ignored if parallel is FALSE. Default (NULL) selects the total number of available cores minus one.
output_path: character. File path where the function output is exported. If NULL (Default), the function returns the output to user.
continue: logical. Argument that can be used only with output_path When TRUE, it skips processing the shape identifiers that were already saved into files. It is useful to continue processing a GTFS file that was stopped for some reason. Default value is FALSE.
quiet: Logical; Display messages from the emissions or emission factor functions. Default is 'TRUE'.

Details

The fleet_data must be a data.frame organized according to the desired ef_model. The required columns is organized as follows (see @examples for real data usage).

veh_type: character; Bus type, classified according to the @param ef_model . For ef_emep_europe, use "Ubus Midi <=15 t","Ubus Std 15 - 18 t", "Ubus Artic >18 t", "Coaches Std <=18 t" or "Coaches Artic >18 t"; For ef_usa_moves or ef_usa_emfac, use "BUS_URBAN_D"; For ef_brazil_cetesb, use "BUS_URBAN_D", "BUS_MICRO_D", "BUS_COACH_D" or "BUS_ARTIC_D".
type_name_eu: character; Bus type, used only for @param ef_model ef_scaled_euro are selected. The classes can be "Ubus Midi <=15 t","Ubus Std 15 - 18 t", "Ubus Artic >18 t", "Coaches Std <=18 t" or "Coaches Artic >18 t".
reference_year: character; Base year of the emission factor model input. Required only when ef_usa_moves or ef_usa_emfac are selected.
tech: character; After treatment technology. This is required only when emep_europe is selected. Check ?ef_emep_europe for details.
euro: character; Euro period of vehicle, classified in "Conventional", "I", "II", "III", "IV", "V", "VI", and "EEV". This is required only when ef_emep_europe is selected. Check ef_europe_emep for details.
fuel: character; Required when ef_usa_moves, ef_usa_emfac and ef_europe_emep are selected.
fleet_composition: Numeric. Scaled composition of fleet. In most cases, the user might not know which vehicles run on each specific routes. The composition is used to attribute a probability of a specific vehicle to circulate in the line. The probability sums one. Required for all emission factors selection. Users can check the gtfs2emis fleet data vignette, for more examples.

Based on the input height data, the function returns the slope class between two consecutive bus stop positions of a LineString Simple Feature (transport model object). The slope is given by the ratio between the height difference and network distance from two consecutive public transport stops. The function classifies the slope into one of the seven categories available on the European Environmental Agency (EEA) database, which is -0.06, -0.04,-0.02, 0.00, 0.02, 0.04, and 0.06.

Examples

Run this code

# \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_cetesb <- progressr::with_progress(emission_model(
                tp_model = tp_model,
                ef_model = "ef_brazil_cetesb",
                fleet_data = fleet_data_ef_cetesb,
                pollutant = c("CO","PM10","CO2","CH4","NOx")
                ))
                            
# Example using European emission model and fleet
fleet_data_ef_europe <- data.frame(  veh_type = c("Ubus Midi <=15 t",
                                                  "Ubus Std 15 - 18 t",
                                                  "Ubus Artic >18 t")
                                   , euro = c("III","IV","V")
                                   , fuel = rep("D",3)
                                   , tech = c("-","SCR","SCR")
                                   , fleet_composition = c(0.4,0.5,0.1))
                                   
emi_emep <- progressr::with_progress(emission_model(tp_model = tp_model
                          , ef_model = "ef_europe_emep"
                          , fleet_data = fleet_data_ef_europe
                          , pollutant = c("PM10","NOx")))
emi_emep_wear <- progressr::with_progress(emission_model(tp_model = tp_model
                          , ef_model = "ef_europe_emep"
                          , fleet_data = fleet_data_ef_europe
                          , pollutant = "PM10"
                          , process = c("tyre","road","brake")))
raster_cur <- system.file("extdata/bra_cur-srtm.tif", package = "gtfs2emis")                           
emi_emep_slope <- progressr::with_progress(emission_model(tp_model = tp_model
                          , ef_model = "ef_europe_emep"
                          , fleet_data = fleet_data_ef_europe
                          , heightfile = raster_cur
                          , pollutant = c("PM10","NOx")))  
                                                  
# Example using US EMFAC emission model and fleet
fleet_data_ef_moves <- data.frame(  veh_type = "BUS_URBAN_D"
                                  , model_year = 2010:2019
                                  , fuel = "D"
                                  , reference_year = 2020
                                  , fleet_composition = rep(0.1,10))
                                  
fleet_data_ef_emfac <- data.frame(  veh_type =  "BUS_URBAN_D"
                                  , model_year = 2010:2019
                                  , fuel = "D"
                                  , reference_year = 2020
                                  , fleet_composition = rep(0.1,10))
                                  
# Example using US MOVES emission model and fleet
emi_moves <- emission_model(tp_model = tp_model
                          , ef_model = "ef_usa_moves"
                          , fleet_data = fleet_data_ef_moves
                          , pollutant = c("CO","PM10","CO2","CH4","NOx")
                          , reference_year = 2020)
                          
emi_emfac <- emission_model(tp_model = tp_model
                          , ef_model = "ef_usa_emfac"
                          , fleet_data = fleet_data_ef_emfac
                          , pollutant = c("CO","PM10","CO2","CH4","NOx")
                          , reference_year = 2020)
}
# }