Global gridded scenarios of residential cooling energy demand to 2050

Falchetta, G. ORCID: https://orcid.org/0000-0003-2607-2195, Pavanello, F., De Cian, E., & Sue Wing, I. (2023). Global gridded scenarios of residential cooling energy demand to 2050. 10.5281/zenodo.7845125.

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Abstract

# ggACene (global gridded Air Conditioning energy) projections

This data 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).

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.

## Running the model
To reproduce the model and generate the dataset from scratch, please refer to the following steps:
- Download input data by cloning the repository
- Adjust the path folder in the sourcer.R script
- Run the sourcer.R script to train the ML model and make projections

## References
Falchetta, G., De Cian, E., Pavanello, F., & Wing, I. S. Inequalities in global residential cooling energy use to 2050 *Under review*

Item Type:	Data
Additional Information:	Restricted
Uncontrolled Keywords:	adaptation, air conditioning, climate change, heat exposure
Research Programs:	Energy, Climate, and Environment (ECE) Energy, Climate, and Environment (ECE) > Integrated Assessment and Climate Change (IACC)
Depositing User:	Luke Kirwan
Date Deposited:	18 Dec 2023 16:45
Last Modified:	18 Dec 2023 16:45
URI:	https://pure.iiasa.ac.at/19305

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