emis estimates vehicular emissions as the product of the vehicles on a road, length of the road, emission factor avaliated at the respective speed. \(E = VEH*LENGTH*EF(speed)\)

emis(veh, lkm, ef, speed, agemax = ifelse(is.data.frame(veh), ncol(veh),
  ncol(veh[[1]])), profile, simplify = FALSE, hour = nrow(profile),
  day = ncol(profile), array = TRUE, verbose = FALSE)



"Vehicles" data-frame or list of "Vehicles" data-frame. Each data-frame as number of columns matching the age distribution of that ype of vehicle. The number of rows is equal to the number of streets link. If this is a list, the length of the list is the vehicles for each hour.


Length of each link in km


List of functions of emission factors


Speed data-frame with number of columns as hours. The default value is 34km/h


Age of oldest vehicles for that category


Dataframe or Matrix with nrows equal to 24 and ncol 7 day of the week


Logical; to determine if EmissionsArray should les dimensions, being streets, vehicle categories and hours or default (streets, vehicle categories, hours and days). Default is FALSE to avoid break old code, but the recommendation is that new estimations use this parameter as TRUE


Number of considered hours in estimation. Default value is number of rows of argument profile


Number of considered days in estimation


Deprecated! emis_cold returns only arrays. When TRUE and veh is not a list, expects a profile as a dataframe producing an array with dimensions (streets x columns x hours x days)


Logical; To show more information


If the user applies a top-down approach, the resulting units will be according its own data. For instance, if the vehicles are veh/day, the units of the emissions implicitly will be g/day.


Hour and day will be deprecated because they can be infered from the profile matrix.


if (FALSE) { # Do not run data(net) data(pc_profile) data(profiles) data(fe2015) data(fkm) PC_G <- c(33491,22340,24818,31808,46458,28574,24856,28972,37818,49050,87923, 133833,138441,142682,171029,151048,115228,98664,126444,101027, 84771,55864,36306,21079,20138,17439, 7854,2215,656,1262,476,512, 1181, 4991, 3711, 5653, 7039, 5839, 4257,3824, 3068) veh <- data.frame(PC_G = PC_G) pc1 <- my_age(x = net$ldv, y = PC_G, name = "PC") # Estimation for morning rush hour and local emission factors speed <- data.frame(S8 = net$ps) lef <- EmissionFactorsList(fe2015[fe2015$Pollutant=="CO", "PC_G"]) E_CO <- emis(veh = pc1,lkm = net$lkm, ef = lef, speed = speed, profile = 1) # Estimation for 168 hour and local factors pcw <- temp_fact(net$ldv+net$hdv, pc_profile) speed <- netspeed(pcw, net$ps, net$ffs, net$capacity, net$lkm, alpha = 1) lef <- EmissionFactorsList(fe2015[fe2015$Pollutant=="CO", "PC_G"]) E_CO <- emis(veh = pc1, lkm = net$lkm, ef = lef, speed = speed, profile = profiles$PC_JUNE_2014) summary(E_CO) lpc <- list(pc1, pc1) E_COv2 <- emis(veh = lpc,lkm = net$lkm, ef = lef, speed = speed) # top down veh <- age_ldv(x = net$ldv[1:4], name = "PC_E25_1400", agemax = 4) mil <- fkm$KM_PC_E25(1:4) ef <- ef_cetesb("COd", "PC_G")[1:4] emis(veh, units::set_units(mil, "km"), ef) # group online bus1 <- age_hdv(30, agemax = 4) veh = bus1 lkm = units::set_units(400, "km") speed = 40 efco <- ef_cetesb("COd", "UB", agemax = 4) lef <- ef_hdv_scaled(dfcol = as.numeric(efco), v = "Ubus", t = "Std", g = ">15 & <=18", eu = rep("IV", 4), gr = 0, l = 0.5, p = "CO") for(i in 1:length(lef)) print(lef[[i]](10)) emis(veh = bus1, lkm = lkm, speed = 40, ef = lef, verbose = T) emis(veh = bus1, lkm = lkm, ef = efco, verbose = T) }