Surface temperatures in New York City: Geospatial data enables the accurate prediction of radiative heat transfer
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s41598-018-19846-5.pdf
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1.76 MB
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Author(s)
Ghandehari, Masoud
Aghamohamadnia, Milad
Emig, Thorsten
Date Issued
February 2018
Journal
Scientific Reports
Publisher
Nature Publishing Group
Citation
Ghandehari, Masoud et al. “Surface Temperatures in New York City: Geospatial Data Enables the Accurate Prediction of Radiative Heat Transfer.” Scientific Reports 8, 1 (February 2018): 2224 © 2018 The Author(s)
Version
Final published version
Abstract
Despite decades of research seeking to derive the urban energy budget, the dynamics of thermal exchange in the densely constructed environment is not yet well understood. Using New York City as a study site, we present a novel hybrid experimental-computational approach for a better understanding of the radiative heat transfer in complex urban environments. The aim of this work is to contribute to the calculation of the urban energy budget, particularly the stored energy. We will focus our attention on surface thermal radiation. Improved understanding of urban thermodynamics incorporating the interaction of various bodies, particularly in high rise cities, will have implications on energy conservation at the building scale, and for human health and comfort at the urban scale. The platform presented is based on longwave hyperspectral imaging of nearly 100 blocks of Manhattan, in addition to a geospatial radiosity model that describes the collective radiative heat exchange between multiple buildings. Despite assumptions in surface emissivity and thermal conductivity of buildings walls, the close comparison of temperatures derived from measurements and computations is promising. Results imply that the presented geospatial thermodynamic model of urban structures can enable accurate and high resolution analysis of instantaneous urban surface temperatures.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
MIT Energy Initiative
Terms of Use
Attribution 4.0 International (CC BY 4.0)
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DOI of Published Version
https://doi.org/10.1038/s41598-018-19846-5
