Indoor air quality vulnerability along the urban-rural continuum: A neighbourhood classification of exposure for England and Wales

Lenka Hasova, Caitlin Robinson and Lin Zhang

Environment and Planning B, 2026, vol. 53, issue 3, 710-725

Abstract: People living in the Global North spend most of their time indoors in the built environment, especially their homes. Indoor air pollution has therefore become a major health concern, particularly in urban environments. Both exposure to poor-quality indoor environments, as well as vulnerability to adverse effects on health and well-being, have a unique geography, varying socially, spatially and temporally. Yet to date, the measurement of indoor air quality is relatively technical in focus, failing to account for the ways in which indoor environments are complex and varied, shaped by the physical environment, housing stock, policies, household dynamics, incomes and cultural norms. This paper aims to better understand the complex social and spatial drivers of vulnerability to poor indoor air quality. This is done by establishing a conceptual framing and building a new classification of vulnerability to indoor air pollution at the neighbourhood scale across England and Wales. First, the paper builds three separate indices utilising a spectrum of open-source data: environmental, structural and human-related. Second, it uses cluster analysis to generate indoor air quality profiles for neighbourhoods, identifying key patterns and drivers of vulnerability that typify different geographies. The findings allow for national, regional and local comparisons of vulnerability, which can be useful to a diverse range of stakeholders to assess potential exposure and guide intervention. Moreover, it highlights the dramatically different relationship between structural, environmental and human dimensions of vulnerability, encouraging indoor air quality exposure to be understood from multiple perspectives, not solely focused on low incomes.

Keywords: Indoor air quality; spatial inequalities; cluster analysis; urban analytics; ambient environment (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:sae:envirb:v:53:y:2026:i:3:p:710-725

DOI: 10.1177/23998083251344678

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