Global gridded scenarios of residential cooling energy demand to 2050

# ggACene (global gridded Air Conditioning energy) projections

### Output AC and AC electricity gridded data

This repository hosts output data for SSPs126, 245, 370 and 585 on the estimated and future projected ownership of residential air conditioning (% of households), the related energy consumption (TWh/yr.), and the underlying population counts (useful to quantify the per-capita average consumption or the headcount of people affected by the cooling gap). These data are contained in the multi-layer .nc (NCDF) files, which can be opened and processed in any GIS software/library, or visualised in softwares such as Panoply.

### Input data and analysis replication

The repository also hosts input data to replicate the entire data generating process. A twin Github repository hosts code (https://github.com/giacfalk/ggACene) to run the model generating the ggACene (global gridded Air Conditioning energy) projections dataset.

## InstructionsTo reproduce the model and generate the dataset from scratch, please refer to the following steps:- Download input data "replication_package_input_data.7z" by cloning the repository- Decompress the folder using 7-Zip (https://www.7-zip.org/download.html)- Open RStudio and adjust the path folder in the sourcer.R script- Run the sourcer.R script to train the ML model, make projections, and represent result files

### Figures replication package

Finally, the source_code_data_replication_figures.zip archive contains an R script and processed input data to replicate all the figures contained in the manuscript.

### ReferenceFalchetta, G., De Cian, E., Pavanello, F., & Wing, I. S. Inequalities in global residential cooling energy use to 2050. Nature Communications. https://www.nature.com/articles/s41467-024-52028-8