Subsurface heat island across the Chicago Loop district: Analysis of localized drivers
Subsurface heat island across the Chicago Loop district: Analysis of localized drivers
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DOI：
10.1016/j.uclim.2022.101211
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发表时间：
2022-07
期刊：
影响因子：
6.4
通讯作者：
A. F. Rotta Loria;Anjali Thota;A. Thomas;Nathan Friedle;Justin M. Lautenberg;Emily C. Song
中科院分区：
文献类型：
--
作者：
A. F. Rotta Loria;Anjali Thota;A. Thomas;Nathan Friedle;Justin M. Lautenberg;Emily C. Song
全球城市地区的地下正在变暖，导致所谓的地下城市热岛。尽管进行了许多调查，但对来源的了解有限（例如，局部驱动因素）的地下城市热岛。本文介绍了一个前所未有的物联网设施，以揭示地下城市石楠岛的本地化驱动因素的关键特征：一个由超过150个无线温度传感器组成的网络，部署在整个芝加哥环路区的地表和地下环境中。通过这个设施，该研究揭示了环路中的地下城市热岛，并指出了这种地下气候变化的局部驱动因素的显著和高度异质的温度。表征所监测的地下热岛的局部驱动器的温度可以超过地面温度>25 °C，涉及朝向该介质的连续热传递。这些司机的温度在整个研究区域可以进一步相差>15 °C，不仅当检查不同的司机时，而且当考虑同一司机内的不同位置时。地下城市热岛的本地化驱动程序的识别功能可以说是世界各地的许多城市的特点，需要足够的建模方法和不确定性量化在未来的模拟研究，这种普遍的现象。
The subsurface beneath urban areas worldwide is warming up, leading to so-called subsurface urban heat islands. Despite many investigations, limited knowledge is available on the sources (e.g., localized drivers) of subsurface urban heat islands. This paper presents an unprecedented Internet of Things facility to unravel key features characterizing localized drivers of subsurface urban heath islands: a network composed of >150 wireless temperature sensors deployed in surface and subsurface environments across the Chicago Loop district. Through this facility, the study unravels a subsurface urban heat island in the Loop and indicates marked and highly heterogeneous temperatures for localized drivers of such underground climate change. The temperatures of localized drivers characterizing the monitored subsurface heat island can exceed by >25 °C the ground temperature, involving a continuous heat transfer towards this medium. The temperatures of such drivers can further differ by >15 °C across the studied district, not only when different drivers are examined, but also when different locations within the same driver are considered. The identified features of localized drivers of subsurface urban heat islands arguably characterize many cities worldwide, requiring adequate modeling approaches and uncertainty quantifications in future simulation studies on such pervasive phenomena.