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Global dataset of regions at the frontlines of cooling poverty risk

Documentation:
This global dataset of regions at the frontlines of cooling poverty risk includes five different files:
(1) Global cooling demand in People-CDDs at ~1 km resolution (GeoTIFF), quantifying population-weighted cooling degree days by combining climate observations with gridded population data;
(2) Global ability to access cooling in $/CDD per capita (PPP-adjusted) at ~10 km resolution (geoTIFF), estimating the economic capacity of populations to afford cooling by integrating GDP per capita with heat exposure;
Population at the frontlines of cooling poverty risk at ~10 km resolution (geoTIFF), with two separate maps that identify populations (3) at high risk and (4) at extreme risk of cooling poverty by combining cooling demand, affordability constraints, and electricity costs;
and (5) Summary of results by country in Excel, providing aggregated national-level indicators including total People-CDDs, economic capacity to afford cooling, and the population at high and extreme risk.
Together, these datasets provide a global, spatially detailed estimate of cooling poverty risk under present-day climate conditions.
Further information regarding the data sources and methods used to produce these datasets is available in the corresponding scientific article.

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Authors/Creators

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Institution:
University of Oxford
Division:
SSD
Department:
SOGE
Sub department:
Smith School
Oxford college:
Somerville College
Role:
Creator
ORCID:
0009-0004-2386-6445
More by this author/creator
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Creator
ORCID:
0000-0002-1802-5017
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Institution:
University of Oxford
Division:
MSD
Department:
Primary Care Health Sciences
Role:
Creator
More by this author/creator
Institution:
University of Oxford
Division:
SSD
Department:
SOGE
Sub department:
Smith School
Role:
Creator
ORCID:
0000-0002-7730-8041


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Funder identifier:
https://ror.org/0439y7842
Grant:
2892710


Publisher:
University of Oxford
Publication date:
2025


Language:
English
Keywords:
Pubs id:
2281921
Local pid:
pubs:2281921
Deposit date:
2025-08-18
ARK identifier:

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