Surface heat assessment for developed environments: Optimizing urban temperature monitoring
Surface heat assessment for developed environments: Optimizing urban temperature monitoring
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DOI：
10.1016/j.buildenv.2018.05.059
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发表时间：
2018-08
影响因子：
7.4
通讯作者：
C. Malings;M. Pozzi;K. Klima;M. Berges;E. Bou‐Zeid;P. Ramamurthy
中科院分区：
文献类型：
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作者：
C. Malings;M. Pozzi;K. Klima;M. Berges;E. Bou‐Zeid;P. Ramamurthy
由于气候变化导致的平均地表温度上升加剧了城市热岛效应，可能对城市人口产生不利影响。城市内极端高温风险时空分布的精细分辨率建模可以改进用于减轻这种风险的策略，例如向城市居民发布有针对性的高温警报。在本文中，我们将最近开发的城市温度概率建模方法与先前开发的脆弱性评估相结合，然后实施传感器放置优化技术来指导城市地区的温度监测。使用各种指标来优化温度测量的位置，以最佳地支持监测和应对极端高温风险的决策。这种最佳传感器放置方法在宾夕法尼亚州匹兹堡市进行了演示，基于所调查的各种传感器性能指标，产生了几种拟议的温度监测方案。我们定量和定性地比较这些方案，以确定每个提议的度量的相对优点。
The urban heat island effect, exacerbated by rising average surface temperatures due to climate change, can lead to adverse impacts on city populations. Fine resolution modeling of the spatial and temporal distribution of extreme heat risk within a city can improve the strategies used to mitigate this risk, such as the issuance of targeted heat advisories to city residents. In this paper, we combine a recently developed method for probabilistic modeling of urban temperatures with previously developed vulnerability assessments, and then implement sensor placement optimization techniques to guide temperature monitoring in urban areas. A variety of metrics are used to optimize the placement of temperature measures to best support decision-making for monitoring and responding to extreme heat risk. This optimal sensor placement methodology is demonstrated for the city of Pittsburgh, PA, resulting in several proposed temperature monitoring schemes based on the various sensor performance metrics investigated. We quantitatively and qualitatively compare these schemes to identify the relative merits of each proposed metric.