Investigating whether the inclusion of humid heat metrics improves estimates of AC penetration rates

A case study of Southern California

Bibliographic Data

ID15547602
AuthorsMcKenna Peplinski (0000-0002-6353-6211, University of Southern California), P Kalmus (0000-0001-7557-8614, Jet Propulsion Laboratory), Kelly T Sanders (0000-0003-4466-0054, University of Southern California, corresponding author)
Year2023
Volume18
Issue10
Pages104054-104054
Publication date2023-09-20
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEnvironmental Research Letters (JOURNAL)
Journal identifiersISSN: 1748-9326 • E-ISSN: 1748-9326
PublisherIOP Publishing (PUBLISHER • GB)
DOI10.1088/1748-9326/acfb96
OpenAlexW4386881094
LanguageEN
Citations received1
References cited60

Global cooling capacity is expected to triple by 2050, as rising temperatures and humidity levels intensify the heat stress that populations experience. Although air conditioning (AC) is a key adaptation tool for reducing exposure to extreme heat, we currently have a limited understanding of patterns of AC ownership. Developing high resolution estimates of AC ownership is critical for identifying communities vulnerable to extreme heat and for informing future electricity system investments as increases in cooling demand will exacerbate strain placed on aging power systems. In this study, we utilize a segmented linear regression model to identify AC ownership across Southern California by investigating the relationship between daily household electricity usage and a variety of humid heat metrics (HHMs) for ~160000 homes. We hypothesize that AC penetration rate estimates, i.e. the percentage of homes in a defined area that have AC, can be improved by considering indices that incorporate humidity as well as temperature. We run the model for each household with each unique heat metric for the years 2015 and 2016 and compare differences in AC ownership estimates at the census tract level. In total, 81% of the households were identified as having AC by at least one heat metric while 69% of the homes were determined to have AC with a consensus across all five of the heat metrics. Regression results also showed that the r 2 values for the dry bulb temperature (DBT) (0.39) regression were either comparable to or higher than the r 2 values for HHMs (0.15–0.40). Our results suggest that using a combination of heat metrics can increase confidence in AC penetration rate estimates, but using DBT alone produces similar estimates to other HHMs, which are often more difficult to access, individually. Future work should investigate these results in regions with high humidity

Economics · Electricity · Geography · Humidity · Linear regression · Meteorology · Metric (unit · Operations management · Physics · Relative humidity · Statistics · Wet-bulb globe temperature · Building Energy and Comfort Optimization · Climate Change and Health Impacts · Environmental Science · Mathematics · Urban Heat Island Mitigation

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