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Surface temperatures in New York City: Geospatial data enables the accurate prediction of radiative heat transfer

TitleSurface temperatures in New York City: Geospatial data enables the accurate prediction of radiative heat transfer
Publication TypeJournal Article
Year of Publication2018
AuthorsGhandehari M, Emig T, Aghamohamadnia M
JournalScientific Reports
Volume8
Pagination Article Number 2224
Date PublishedFeb-02-2018
KeywordsENERGY-BALANCE; URBAN; STORAGE; MODEL; ALBEDO; FLUX
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.

URLhttp://www.nature.com/articles/s41598-018-19846-5
DOI10.1038/s41598-018-19846-5
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