Read NetCDF data from global inventories

Read data from global inventories. Several files can be read to produce one emission output and/or can be splitted into several species

Usage

read(
  file = file.choose(),
  version = NA,
  coef = rep(1, length(file)),
  spec = NULL,
  year = 1,
  month = 1,
  hour = 1,
  categories,
  reproject = TRUE,
  as_raster = TRUE,
  skip_missing = FALSE,
  verbose = TRUE
)

Source

Read abbout EDGAR at http://edgar.jrc.ec.europa.eu and MACCITY at http://accent.aero.jussieu.fr/MACC_metadata.php

More info for EDGARv8.1 https://edgar.jrc.ec.europa.eu/dataset_ap81 for short live species and https://edgar.jrc.ec.europa.eu/dataset_ghg80 for GHG

Arguments

file

file name or names (variables are summed)

version

Character; One of of the following:

argument	tested	region	resolution	projection
EDGAR	4.32 and 5.0	Global	0.1 x 0.1 °	longlat
EDGAR_HTAPv2	2.2	Global	0.1 x 0.1 °	longlat
EDGARv8m	8.1	Global	0.1 x 0.1 °	longlat
GAINS	v5a	Global	0.5 x 0.5 °	longlat
RCP	RCP3PD Glb	Global	0.5 x 0.5 °	longlat
MACCITY	2010	Global	0.5 x 0.5 °	longlat
FFDAS	2.2	Global	0.1 x 0.1 °	longlat
ODIAC	2020	Global	1 x 1 °	longlat
VULCAN-y	3.0	US	1 x 1 Km	lcc
VULCAN-h	3.0	US	1 x 1 Km	lcc
ACES	2020	NE US	1 x 1 km	lcc

coef

coefficients to merge different sources (file) into one emission

spec

numeric speciation vector to split emission into different species

year

scenario index (only for GAINS and VULCAN-y)

month

the desired month of the inventory (MACCITY and ODIAC)

hour

hour of the emission (only for ACES and VULCAN-h)

categories

considered categories (for MACCITY/GAINS variable names), empty for use all

reproject

to project the output to "+proj=longlat" needed for emission function (only for VULCAN and ACES)

as_raster

return a raster (default) or matrix (with units)

skip_missing

return a zero emission and a warning for missing files/variables

verbose

display additional information

Value

Matrix or raster

Note

for EDGAR (all versions), GAINS, RCP and MACCTITY, please use flux (kg m-2 s-1) NetCDF file.

References

Janssens-Maenhout, G., Dentener, F., Van Aardenne, J., Monni, S., Pagliari, V., Orlandini, L., ... & Wankmüller, R. (2012). EDGAR-HTAP: a harmonized gridded air pollution emission dataset based on national inventories. European Commission Joint Research Centre Institute for Environment and Sustainability. JRC 68434 UR 25229 EUR 25229, ISBN 978-92-79-23123-0.

Lamarque, J.-F., Bond, T. C., Eyring, V., Granier, C., Heil, A., Klimont, Z., Lee, D., Liousse, C., Mieville, A., Owen, B., Schultz, M. G., Shindell, D., Smith, S. J., Stehfest, E., Van Aardenne, J., Cooper, O. R., Kainuma, M., Mahowald, N., McConnell, J. R., Naik, V., Riahi, K., and van Vuuren, D. P.: Historical (1850-2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: methodology and application, Atmos. Chem. Phys., 10, 7017-7039, doi:10.5194/acp-10-7017-2010, 2010.

Z Klimont, S. J. Smith and J Cofala The last decade of global anthropogenic sulfur dioxide: 2000–2011 emissions Environmental Research Letters 8, 014003, 2013

Gurney, Kevin R., Jianming Liang, Risa Patarasuk, Yang Song, Jianhua Huang, and Geoffrey Roest (2019) The Vulcan Version 3.0 High-Resolution Fossil Fuel CO2 Emissions for the United States. Nature Scientific Data.

See also

rasterSource and gridInfo

species

Examples

# \donttest{
dir.create(file.path(tempdir(), "EDGARv432"))
folder <- setwd(file.path(tempdir(), "EDGARv432"))

url <- "http://jeodpp.jrc.ec.europa.eu/ftp/jrc-opendata/EDGAR/datasets/v432_AP/NOx"
file <- 'v432_NOx_2012.0.1x0.1.zip'

download.file(paste0(url,'/TOTALS/',file), file)

unzip('v432_NOx_2012.0.1x0.1.zip')

nox  <- read(file    = dir(pattern = '.nc'),
             version = 'EDGAR',
             spec    = c(E_NO  = 0.9 ,   # 90% of NOx is NO
                         E_NO2 = 0.1 ))  # 10% of NOx is NO2
#> reading EDGAR emissions, output unit is g m-2 s-1 ...
#> from v432_NOx_2012.0.1x0.1.nc emi_nox x 1.000000 
#> using the following speciation:
#> E_NO = 0.9
#> E_NO2 = 0.1
setwd(folder)
# creating a color scale
cor <- colorRampPalette(colors = c(c("#031057", "#0522FC",
                                     "#7E0AFA", "#EF0AFF",
                                     "#FFA530", "#FFF957")))
raster::plot(nox$E_NO,xlab="Lat", ylab="Lon",
             col = cor(12),zlim = c(-6.5e-7,1.4e-5),
             main="NO emissions from EDGAR (in g / m2 s)")


d1  <- gridInfo(paste(system.file("extdata", package = "EmissV"),"/wrfinput_d01",sep=""))
#> Grid information from: /home/runner/work/_temp/Library/EmissV/extdata/wrfinput_d01 
NO  <- emission(grid = d1, inventory = nox$E_NO, pol = "NO", mm = 30.01, plot = TRUE)
#> Using raster from inventory for NO ...
#> Grid output: 99 columns 93 rows

# }