Understanding thermal justice and systemic cooling poverty from the margins: intersectional perspectives from Rio de Janeiro

Antonella Mazzonea Oxford Martin School, Future of Cooling Programme, University of Oxford, Oxford, UK;b Department of Anthropology and Archaeology, University of Bristol, Bristol, UK;d The New Institute Centre for Environmental Humanities (NICHE), University of Venice, Venice, ItalyCorrespondence[email protected]

https://orcid.org/0000-0003-2352-1362 View further author information

Enrica De Cianc Department of Economics, University of Venice, Venice, Italy;d The New Institute Centre for Environmental Humanities (NICHE), University of Venice, Venice, Italy;e Euro-Mediterranean Center on Climate Change (CMCC), Lecce, ItalyView further author information

Elias de Paulaf Independent Researcher, Rio de Janeiro, BrazilView further author information

Andreia Ferreiraf Independent Researcher, Rio de Janeiro, BrazilView further author information

Radhika Khoslaa Oxford Martin School, Future of Cooling Programme, University of Oxford, Oxford, UK;g Smith School of Enterprise and the Environment, School of Geography and the Environment, University of Oxford, Oxford, UKView further author information

Understanding thermal justice and systemic cooling poverty from the margins: intersectional perspectives from Rio de Janeiro

Table 1. Factors that contribute to cooling poverty in Rio de Janeiro.

Table 2. Multidimensional systemic cooling poverty and socio-economic characteristics. Mean values computed across the 32 respondents. High-income individuals are those declaring more than the minimum salary. Number of respondents in parentheses.

Table 3. Linear probability model for cooling strategies adoption. Robust standard errors in parenthesis.

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Understanding thermal justice and systemic cooling poverty from the margins: intersectional perspectives from Rio de Janeiro

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Table 1. Factors that contribute to cooling poverty in Rio de Janeiro.

Table 2. Multidimensional systemic cooling poverty and socio-economic characteristics. Mean values computed across the 32 respondents. High-income individuals are those declaring more than the minimum salary. Number of respondents in parentheses.

Table 3. Linear probability model for cooling strategies adoption. Robust standard errors in parenthesis.

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