## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>") ## ----------------------------------------------------------------------------- library(gtfs2emis) emi_europe_emep_wear(dist = units::set_units(1,"km"), speed = units::set_units(30,"km/h"), pollutant = c("PM10","TSP","PM2.5"), veh_type = "Ubus Std 15 - 18 t", fleet_composition = 1, load = 0.5, process = c("tyre"), as_list = TRUE) ## ----message = FALSE---------------------------------------------------------- emi_europe_emep_wear(dist = units::set_units(1,"km"), speed = units::set_units(30,"km/h"), pollutant = c("PM10","TSP","PM2.5"), veh_type = "Ubus Std 15 - 18 t", fleet_composition = 1, load = 0.5, process = c("brake"), as_list = TRUE) ## ----message = FALSE---------------------------------------------------------- emi_europe_emep_wear(dist = units::set_units(1,"km"), speed = units::set_units(30,"km/h"), pollutant = c("PM10","TSP","PM2.5"), veh_type = "Ubus Std 15 - 18 t", fleet_composition = 1, load = 0.5, process = c("road"), as_list = TRUE) ## ----message = FALSE,fig.height=3, fig.width=8-------------------------------- library(units) library(ggplot2) emis_list <- emi_europe_emep_wear(dist = units::set_units(rep(1,100),"km"), speed = units::set_units(1:100,"km/h"), pollutant = c("PM10","TSP","PM2.5"), veh_type = c("Ubus Std 15 - 18 t"), fleet_composition = c(1), load = 0.5, process = c("brake","tyre","road"), as_list = TRUE) ef_dt <- gtfs2emis::emis_to_dt(emis_list,emi_vars = "emi" ,segment_vars = "speed") ggplot(ef_dt)+ geom_line(aes(x = as.numeric(speed),y = as.numeric(emi),color = pollutant))+ facet_wrap(facets = vars(process))+ labs(x = "Speed (km/h)",y = "Emissions (g)")+ theme_minimal() ## ----message = FALSE---------------------------------------------------------- library(gtfstools) library(sf) # 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, spatial_resolution = 100, parallel = FALSE) # Fleet data, using Brazilian emission model and fleet fleet_data_ef_emep <- data.frame(veh_type = "Ubus Std 15 - 18 t", fleet_composition = 1, euro = "V", # for hot-exhaust emissions fuel = "D", # for hot-exhaust emissions tech = "SCR") # for hot-exhaust emissions # Emission model (hot-exhaust) emi_list_he <- emission_model( tp_model = tp_model, ef_model = "ef_europe_emep", fleet_data = fleet_data_ef_emep, pollutant = "PM10" ) # Emission model (non-exhaust) emi_list_ne <- emi_europe_emep_wear( dist = tp_model$dist, speed = tp_model$speed, pollutant = "PM10", veh_type = c("Ubus Std 15 - 18 t"), fleet_composition = c(1), load = 0.5, process = c("brake","tyre","road"), as_list = TRUE) emi_list_ne$tp_model <- tp_model ## ----message = FALSE---------------------------------------------------------- # create spatial grid grid <- sf::st_make_grid( x = sf::st_make_valid(tp_model) , cellsize = 0.25 / 200 , crs= 4326 , what = "polygons" , square = FALSE ) # grid (hot-exhaust) emi_grid_he <- emis_grid( emi_list_he,grid,time_resolution = 'day' ,aggregate = TRUE) setDT(emi_grid_he) pol_names <- setdiff(names(emi_grid_he),"geometry") emi_grid_he_dt <- melt(emi_grid_he,measure.vars = pol_names,id.vars = "geometry") emi_grid_he_dt <- sf::st_as_sf(emi_grid_he_dt) # grid (non-exhaust) emi_grid_ne <- emis_grid( emi_list_ne,grid,time_resolution = 'day' ,aggregate = TRUE) setDT(emi_grid_ne) pol_names <- setdiff(names(emi_grid_ne),"geometry") emi_grid_ne_dt <- melt(emi_grid_ne,measure.vars = pol_names,id.vars = "geometry") emi_grid_ne_dt <- sf::st_as_sf(emi_grid_ne_dt) # bind grid emi_grid_dt <- data.table::rbindlist(l = list(emi_grid_he_dt,emi_grid_ne_dt)) emi_grid_sf <- sf::st_as_sf(emi_grid_dt) ## ----message = FALSE,fig.height=3, fig.width=6-------------------------------- # plot library(ggplot2) ggplot(emi_grid_sf) + geom_sf(aes(fill= as.numeric(value)), color=NA) + geom_sf(data = tp_model$geometry,color = "black")+ scale_fill_continuous(type = "viridis")+ labs(fill = "PM10 (g)")+ facet_wrap(facets = vars(variable),nrow = 1)+ theme_void() ## ----message = FALSE,fig.height=3, fig.width=6-------------------------------- # Emissions by time emi_time_he <- emis_summary(emi_list_he,by = "time") emi_time_ne <- emis_summary(emi_list_ne,by = "time") emi_time <- data.table::rbindlist(l = list(emi_time_he,emi_time_ne)) ggplot(emi_time)+ geom_col(aes(x = process,y = as.numeric(emi),fill = as.numeric(emi)))+ scale_fill_continuous(type = "viridis")+ labs(fill = "PM10 level",y = "Emissions (g)")+ theme_minimal()