Surface temperatures in New York City: Geospatial data enables the accurate prediction of radiative heat transfer
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...
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| Format: | Article |
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Nature Publishing Group
2018
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| Online Access: | http://hdl.handle.net/1721.1/115212 |
| _version_ | 1826212532698742784 |
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| author | Ghandehari, Masoud Aghamohamadnia, Milad Emig, Thorsten |
| author2 | Massachusetts Institute of Technology. Department of Civil and Environmental Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Civil and Environmental Engineering Ghandehari, Masoud Aghamohamadnia, Milad Emig, Thorsten |
| author_sort | Ghandehari, Masoud |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T15:24:19Z |
| format | Article |
| id | mit-1721.1/115212 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T15:24:19Z |
| publishDate | 2018 |
| publisher | Nature Publishing Group |
| record_format | dspace |
| spelling | mit-1721.1/1152122022-09-29T14:37:22Z Surface temperatures in New York City: Geospatial data enables the accurate prediction of radiative heat transfer Ghandehari, Masoud Aghamohamadnia, Milad Emig, Thorsten Massachusetts Institute of Technology. Department of Civil and Environmental Engineering MIT Energy Initiative Emig, Thorsten 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. 2018-05-03T17:21:49Z 2018-05-03T17:21:49Z 2018-02 2017-08 2018-04-27T17:43:11Z Article http://purl.org/eprint/type/JournalArticle 2045-2322 http://hdl.handle.net/1721.1/115212 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) http://dx.doi.org/10.1038/s41598-018-19846-5 Scientific Reports Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/ application/pdf Nature Publishing Group Scientific Reports |
| spellingShingle | Ghandehari, Masoud Aghamohamadnia, Milad Emig, Thorsten Surface temperatures in New York City: Geospatial data enables the accurate prediction of radiative heat transfer |
| title | Surface temperatures in New York City: Geospatial data enables the accurate prediction of radiative heat transfer |
| title_full | Surface temperatures in New York City: Geospatial data enables the accurate prediction of radiative heat transfer |
| title_fullStr | Surface temperatures in New York City: Geospatial data enables the accurate prediction of radiative heat transfer |
| title_full_unstemmed | Surface temperatures in New York City: Geospatial data enables the accurate prediction of radiative heat transfer |
| title_short | Surface temperatures in New York City: Geospatial data enables the accurate prediction of radiative heat transfer |
| title_sort | surface temperatures in new york city geospatial data enables the accurate prediction of radiative heat transfer |
| url | http://hdl.handle.net/1721.1/115212 |
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