Methods on prevention of double-counting and constructing characterization factors were taken from:
Cabernard, L., Pfister, S., & Hellweg, S. (2019). A new method for analyzing sustainability performance of global supply chains and its application to material resources. Science of The Total Environment, 684, 164–177. https://doi.org/10.1016/j.scitotenv.2019.04.434
Matlab Tool:
https://data.mendeley.com/datasets/nddmgkm3cc/1
This R-package provides various methods for environmentally-extended multi-regional input–output (EE-MRIO) analysis. It offers different methods for calculating EEMRIO matrices and includes a set of diverse characterization factors.
- supports EXIOBASE3 and Eora
- characterization factors:
- biodiversity loss
"bl"
(currently only for Exiobase) - blue water consumption
"bw"
- climate change impacts
"cc"
- energy demand
"en"
- land use
"lu"
- material footprint
"mf"
- water stress
"ws"
(currently only for Exiobase)
- biodiversity loss
- calculate:
- production to demand matrix
"pd"
- production to target demand matrix
"no-double-pt"
- target to final supply matrix
"no-double-ts"
- target to final demand matrix
"no-double-td"
- production to final demand matrix
"no-double-pd"
- production to demand matrix
- create country dyads
install.packages("remotes")
remotes::install_github("dvp17/mrio")
Before you begin, set your working directory to the path where you store your Eora and Exiobase files:
e.g. setwd("C:/Data/Exiobase")
or setwd("C:/Data/Eora")
setwd("C:/Data/Exiobase")
exio_cc <- mrio::exioloop(1995:2000, "cc", "pd")
utils::View(exio_cc[1:100,])
Please be aware that the process of calculating the matrices will take some time.
setwd("C:/Data/Exiobase")
exio_cc_dyad <- mrio::dyads(1995:1996, exio_cc)
utils::View(exio_cc_dyad[1:100,])
Attention: The construction of dyads can be time-consuming. Please notice that no progress bar or estimated time for process completion is given before.
For additional information on which extensions are included for which environmental impact, have a look on the characterization factors listed in the package. Notice that calculation of water stress and biodiversity loss is a little more complex, which makes it difficult to provide a simple list on those CFs.
utils::View(mrio::cf_eora)
utils::View(mrio::cf_eora[mrio::cf_eora$cf_cc > 0,])
- added processing of pxp-matrices for EXIOBASE3
- add WIOD data
- add
bl
andws
for Eora - add
bl
for pxp-matrices - include social indicators
- structural path calculation?
- implement function to download data automatically