Global gridded scenarios of residential cooling energy demand to 2050
- 1. CMCC, IIASA
- 2. Università di Bologna
- 3. UNIVE, CMCC
- 4. Boston University
Description
# 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, its energy consumption, and the underlying population (useful to quantify the per-capita average consumption or the headcount of people affected by the cooling gap).
### Input data and analysis replication
The repository also hosts input data to replicate the 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.
## Instructions
To 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
### References
Falchetta, G., De Cian, E., Pavanello, F., & Wing, I. S. Inequalities in global residential cooling energy use to 2050. Forthcoming at Nature Communications
Files
Files
(3.9 GB)
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md5:ad6254a0b51728e08b4638d4169aaabc
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3.7 MB | Download |
md5:7399c5a1a5ca16656e1887df62990252
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3.7 MB | Download |
md5:801e61361c9d6120945a59a632546c58
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3.5 MB | Download |
md5:54844830a59fd492ad62395ccae20946
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3.9 GB | Download |
Additional details
Software
- Repository URL
- https://github.com/giacfalk/ggACene
- Programming language
- R