Housing as a critical determinant of heat vulnerability and health
Housing as a critical determinant of heat vulnerability and health
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DOI：
10.1016/j.scitotenv.2020.137296
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发表时间：
2020-06-10
影响因子：
9.8
通讯作者：
Narula, Tushar
中科院分区：
文献类型：
--
作者：
Samuelson, Holly;Baniassadi, Amir;Narula, Tushar
市政当局使用热脆弱性指数（HVIs）来量化和绘制热浪发生时人类健康风险的相对分布。这些地图表面上允许公共机构识别风险最高的社区，并相应地集中应急计划的努力和资源（例如，建立冷却中心的位置）。构建人类健康指数的方法因城市而异，但共同的输入包括人口统计变量，如年龄和收入——在某种程度上，还包括土地覆盖等指标。然而，将人口统计数据作为热脆弱性的代理可能提供不完整或不准确的风险评估。HVIs的一个关键限制可能是缺乏对住房特征以及它们如何调节室内热暴露的关注。为了对这一局限性进行客观评估，我们首先回顾了文献和已出版或由市政当局委托的艾滋病毒感染者。我们随后证实，大多数这些HVIs排除了住房因素。接下来，为了确定潜在的后果，我们使用基于物理的住房原型模拟（每个城市46,000个住房排列）来估计波士顿和凤凰城高脆弱性社区室内热暴露的变化。结果表明，通过排除建筑层面的暴露决定因素，HVIs未能捕获热脆弱性的重要组成部分。此外，我们还展示了这些地图目前如何忽略了建筑年龄和空调功能影响的重要细微差别。最后，我们讨论了在HVIs中实施住房存量特征所面临的挑战，并提出了克服这些挑战的方法。(C) 2020 Elsevier B.V.版权所有
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. (C) 2020 Elsevier B.V. All rights reserved.