Urban heat island (UHI) is the best acknowledged climate-change related phenomenon also because it affects population health conditions in dense urban areas, even exacerbated during heat waves. While most of field studies are performed by means of permanent weather stations, this paper presents an intra-urban microclimate analysis through wearable sensing techniques for monitoring and characterizing granular peculiarities as perceived by urban pedestrians. The study is implemented in four areas of New York City presenting already mitigation techniques. These strategies are specifically analyzed from the pedestrians' perspective, who may walk along parks and sidewalks, to better study real boundary conditions responsible for thermal perception, even in those areas where vehicles are not allowed. A novel cluster analysis procedure is then carried out to perform data-driven identification of urban microclimate peculiarities in relation to its morphology (e.g. urban canyons etc.). Results show a non-negligible dependency from urban configuration both in winter and in summer. Measurements in the high-packed district winter daytime show a drop off of 0.6 °C in air temperature close to small parks. The packed low-rise district presents highest values of CO2, with respect to the other monitored areas both in winter and in summer. The same areas are automatically recognized through the data-driven clustering process. The data-driven approach may be therefore successfully integrated into classic measurements to investigate UHI and heat stress in dense anthropized areas.

Human-centric microclimate analysis of Urban Heat Island: Wearable sensing and data-driven techniques for identifying mitigation strategies in New York City

Pioppi B.;Pigliautile I.;Pisello A. L.
2020

Abstract

Urban heat island (UHI) is the best acknowledged climate-change related phenomenon also because it affects population health conditions in dense urban areas, even exacerbated during heat waves. While most of field studies are performed by means of permanent weather stations, this paper presents an intra-urban microclimate analysis through wearable sensing techniques for monitoring and characterizing granular peculiarities as perceived by urban pedestrians. The study is implemented in four areas of New York City presenting already mitigation techniques. These strategies are specifically analyzed from the pedestrians' perspective, who may walk along parks and sidewalks, to better study real boundary conditions responsible for thermal perception, even in those areas where vehicles are not allowed. A novel cluster analysis procedure is then carried out to perform data-driven identification of urban microclimate peculiarities in relation to its morphology (e.g. urban canyons etc.). Results show a non-negligible dependency from urban configuration both in winter and in summer. Measurements in the high-packed district winter daytime show a drop off of 0.6 °C in air temperature close to small parks. The packed low-rise district presents highest values of CO2, with respect to the other monitored areas both in winter and in summer. The same areas are automatically recognized through the data-driven clustering process. The data-driven approach may be therefore successfully integrated into classic measurements to investigate UHI and heat stress in dense anthropized areas.
2020
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1492723
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