simschul / uncertainty_ghg_accounts

This is the code for reproducing the results for our study on “Estimating the uncertainty of the greenhouse gas emission accounts in Global Multi-Regional Input-Output analysis” submitted to the Journal of Earth Systems Science Data (ESSD).

Estimating the uncertainty of the greenhouse gas emission accounts in Global Multi-Regional Input-Output analysis

This is the code for reproducing the results for our study on “Estimating the uncertainty of the greenhouse gas emission accounts in Global Multi-Regional Input-Output analysis” submitted to the Journal of Earth Systems Science Data (ESSD).

The article is available as preprint here: https://essd.copernicus.org/preprints/essd-2023-473/

Data required

To reproduce the results and run the scripts you need to download the following data:

• EXIOBASE V3.8.2 IOT_2015_ixi.zip and MRSUT_2015.zip from here: https://zenodo.org/records/5589597
• UNFCCC country-submitted greenhouse gas emissions data until 2020-10-25 from here: https://zenodo.org/record/4199622
• EDGAR v5.0 time series data for CO$_2$, CH$_4$ and N$_2$O from here: https://edgar.jrc.ec.europa.eu/dataset_ghg50
• UNFCCC uncertainty data from here: https://zenodo.org/record/10037714
• Correspondence table between UNFCCC CRF and EXIOBASE industry sectors from here: https://zenodo.org/record/10046372
• Supplementary material 2 from Selin et al. (2021): https://doi.org/10.1088/1748-9326/abec02 (The link to the file is a bit hidden below the abstract)

The uncertainty data from Solazzo et al. (2021) (https://acp.copernicus.org/articles/21/5655/2021/) is already part of this repository (./data/tot_GHG_2015_Tier1_sector_countrytotal_cat_.csv).

How to run the scripts

1. Clone the repository to create a local copy on you computer.

2. Open the project by clicking on uncertainty_GHG_accounts.Rproj.

3. renv will automatically bootstrap itself, downloading and installing the appropriate version of renv. It will also ask you if you want to download and install all the packages it needs by running renv::restore().

4. Once the packages are installed, open the file __main__.qmd.

5. Run the code junks one by one.

The scripts need to be run according to the order indicated (which the __main__.qmd does). The dependency graph of the individual scripts is depicted here:

The code was tested with the following setup:

platform       x86_64-pc-linux-gnu         
arch           x86_64                      
os             linux-gnu                   
system         x86_64, linux-gnu           
status                                     
major          4                           
minor          3.1                         
year           2023                        
month          06                          
day            16                          
svn rev        84548                       
language       R                           
version.string R version 4.3.1 (2023-06-16)
nickname       Beagle Scouts 

In case of problems, please raise an issue or contact me.