Jay H. Arehart
A New Estimate of Building Floor Space in North America
Arehart, Jay H.; Pomponi, Francesco; D'Amico, Bernardino; Srubar III, Wil V.
Authors
Prof Francesco Pomponi F.Pomponi2@napier.ac.uk
Visiting Professor
Dr Bernardino D'Amico B.D'Amico@napier.ac.uk
Associate Professor
Wil V. Srubar III
Abstract
Floor space is a key variable used to understand the energy and material demands of buildings. Using recent datasets of building footprints, we employ a random forest regression model to estimate the floor space of the North American building stock. Our estimate for floor space in 2016 is 88,033 (+15,907 / -21,861) million m2—which is 2.9 times higher than current estimates from national statistics offices. We also show how floor space per capita (m2 cap-1) is not constant across the North American region, highlighting the heterogeneous nature of building stocks. As a critical variable in integrated assessment models to project energy and material demands, this result suggests the following: (1) the North American building stock is more energy efficient than previously realized, suggesting that buildings are underutilized, (2) the embodied environmental impacts of buildings have been underestimated in comparison to operational impacts, and (3) the near-term demand for floor space and, consequently, the future demand for materials and energy have been largely underestimated.
Citation
Arehart, J. H., Pomponi, F., D'Amico, B., & Srubar III, W. V. (2021). A New Estimate of Building Floor Space in North America. Environmental Science and Technology, 55(8), 5161-5170. https://doi.org/10.1021/acs.est.0c05081
Journal Article Type | Article |
---|---|
Acceptance Date | Mar 18, 2021 |
Online Publication Date | Mar 30, 2021 |
Publication Date | 2021-04 |
Deposit Date | Mar 19, 2021 |
Publicly Available Date | Mar 31, 2022 |
Journal | Environmental Science & Technology |
Print ISSN | 0013-936X |
Electronic ISSN | 1520-5851 |
Publisher | American Chemical Society |
Peer Reviewed | Peer Reviewed |
Volume | 55 |
Issue | 8 |
Pages | 5161-5170 |
DOI | https://doi.org/10.1021/acs.est.0c05081 |
Keywords | floor space; building stock; North America; machine learning |
Public URL | http://researchrepository.napier.ac.uk/Output/2754147 |
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