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Tytuł:
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Methods for Estimating Wet Bulb Globe Temperature From Remote and Low-Cost Data: A Comparative Study in Central Alabama.
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Autorzy:
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Carter AW; Department of Earth and Planetary Sciences Johns Hopkins University Baltimore MD USA.
Zaitchik BF; Department of Earth and Planetary Sciences Johns Hopkins University Baltimore MD USA.
Gohlke JM; Department of Population Health Sciences Virginia Polytechnic Institute and State University Blacksburg VA USA.
Wang S; Department of Population Health Sciences Virginia Polytechnic Institute and State University Blacksburg VA USA.
Richardson MB; Division of Preventive Medicine University of Alabama at Birmingham Birmingham AL USA.
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Źródło:
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GeoHealth [Geohealth] 2020 May 21; Vol. 4 (5), pp. e2019GH000231. Date of Electronic Publication: 2020 May 21 (Print Publication: 2020).
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Typ publikacji:
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Journal Article
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Język:
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English
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Imprint Name(s):
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Original Publication: Hoboken, NJ : Wiley Periodicals, Inc., [2017]-
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References:
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Geohealth. 2020 May 21;4(5):e2019GH000231. (PMID: 32490302)
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Contributed Indexing:
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Keywords: WBGT; health; heat stress
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Entry Date(s):
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Date Created: 20200604 Latest Revision: 20240328
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Update Code:
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20240329
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PubMed Central ID:
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PMC7240860
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DOI:
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10.1029/2019GH000231
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PMID:
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32490302
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Heat stress is a significant health concern that can lead to illness, injury, and mortality. The wet bulb globe temperature (WBGT) index is one method for monitoring environmental heat risk. Generally, WBGT is estimated using a heat stress monitor that includes sensors capable of measuring ambient, wet bulb, and black globe temperature, and these measurements are combined to calculate WBGT. However, this method can be expensive, time consuming, and requires careful attention to ensure accurate and repeatable data. Therefore, researchers have attempted to use standard meteorological measurements, using single data sources as an input (e.g., weather stations) to calculate WBGT. Building on these efforts, we apply data from a variety of sources to calculate WBGT, understand the accuracy of our estimated equation, and compare the performance of different sources of input data. To do this, WBGT measurements were collected from Kestrel 5400 Heat Stress Trackers installed in three locations in Alabama. Data were also drawn from local weather stations, North American Land Data Assimilation System (NLDAS), and low cost iButton hygrometers. We applied previously published equations for estimating natural wet bulb temperature, globe temperature, and WBGT to these diverse data sources. Correlation results showed that WBGT estimates derived from all proxy data sources-weather station, weather station/iButton, NLDAS, NLDAS/iButton-were statistically indistinguishable from each other, or from the Kestrel measurements, at two of the three sites. However, at the same two sites, the addition of iButtons significantly reduced root mean square error and bias compared to other methods.
Competing Interests: The authors declare no conflicts of interest relevant to this study.
(© 2020. The Authors.)