Housing as a critical determinant of heat vulnerability and health.

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Title: Housing as a critical determinant of heat vulnerability and health.
Authors: Samuelson, Holly1 (AUTHOR) hsamuelson@gsd.harvard.edu, Baniassadi, Amir1 (AUTHOR), Lin, Anne2,3 (AUTHOR), Izaga González, Pablo1 (AUTHOR), Brawley, Thomas1,4,5 (AUTHOR), Narula, Tushar1,4 (AUTHOR)
Source: Science of the Total Environment. Jun2020, Vol. 720, pN.PAG-N.PAG. 1p.
Abstract: Municipalities use Heat Vulnerability Indices (HVIs) to quantify and map relative distribution of risks to human health in the event of a heatwave. These maps ostensibly allow public agencies to identify the highest-risk neighborhoods, and to concentrate emergency planning efforts and resources accordingly (e.g., to establish the locations of cooling centers). The method of constructing an HVI varies by municipality, but common inputs include demographic variables such as age and income – and to some extent, metrics such as land cover. However, taking demographic data as a proxy for heat vulnerability may provide an incomplete or inaccurate assessment of risk. A critical limitation in HVIs may be a lack of focus on housing characteristics and how they mediate indoor heat exposure. To provide an objective assessment of this limitation, we first reviewed HVIs in the literature and those published or commissioned by municipalities. We subsequently verified that most of these HVIs excluded housing factors. Next, to scope the potential consequences, we used physics-based simulations of housing prototypes (46,000 housing permutations per city) to estimate the variation in indoor heat exposure within high-vulnerability neighborhoods in Boston and Phoenix. The results show that by excluding building-level determinants of exposure, HVIs fail to capture important components of heat vulnerability. Moreover, we demonstrate how these maps currently overlook important nuances regarding the impact of building age and air conditioning functionality. Finally, we discuss the challenges of implementing housing stock characteristics in HVIs and propose methods for overcoming these challenges. Unlabelled Image • Most Heat Vulnerability Indices exclude housing characteristics. • Excluding housing characteristics results in an incomplete account of vulnerability. • Simulations show substantial temperature variation attributable to housing. • Past assumptions about housing age and AC functionality are not accurate. • We propose solutions for overcoming lack of spatially granular data on housing. [ABSTRACT FROM AUTHOR]
Copyright of Science of the Total Environment is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Housing as a critical determinant of heat vulnerability and health.
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  Data: <searchLink fieldCode="JN" term="%22Science+of+the+Total+Environment%22">Science of the Total Environment</searchLink>. Jun2020, Vol. 720, pN.PAG-N.PAG. 1p.
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Municipalities use Heat Vulnerability Indices (HVIs) to quantify and map relative distribution of risks to human health in the event of a heatwave. These maps ostensibly allow public agencies to identify the highest-risk neighborhoods, and to concentrate emergency planning efforts and resources accordingly (e.g., to establish the locations of cooling centers). The method of constructing an HVI varies by municipality, but common inputs include demographic variables such as age and income – and to some extent, metrics such as land cover. However, taking demographic data as a proxy for heat vulnerability may provide an incomplete or inaccurate assessment of risk. A critical limitation in HVIs may be a lack of focus on housing characteristics and how they mediate indoor heat exposure. To provide an objective assessment of this limitation, we first reviewed HVIs in the literature and those published or commissioned by municipalities. We subsequently verified that most of these HVIs excluded housing factors. Next, to scope the potential consequences, we used physics-based simulations of housing prototypes (46,000 housing permutations per city) to estimate the variation in indoor heat exposure within high-vulnerability neighborhoods in Boston and Phoenix. The results show that by excluding building-level determinants of exposure, HVIs fail to capture important components of heat vulnerability. Moreover, we demonstrate how these maps currently overlook important nuances regarding the impact of building age and air conditioning functionality. Finally, we discuss the challenges of implementing housing stock characteristics in HVIs and propose methods for overcoming these challenges. Unlabelled Image • Most Heat Vulnerability Indices exclude housing characteristics. • Excluding housing characteristics results in an incomplete account of vulnerability. • Simulations show substantial temperature variation attributable to housing. • Past assumptions about housing age and AC functionality are not accurate. • We propose solutions for overcoming lack of spatially granular data on housing. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Science of the Total Environment is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Jun2020
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