title: Wet-bulb globe temperature index estimation using meteorological data from São Paulo State, Brazil.
abstract: It is well known that excessive heat exposure causes heat disorders and can lead to death in some situations. Evaluation of heat stress on workers performing indoor and outdoor activities is, nowadays, conducted worldwide by wet-bulb globe temperature (WBGT) index, which calculation parameters are dry-bulb, natural wet-bulb, and globe temperatures, which must be measured at the same time and in location where the worker is conducting his/her activities. However, for some activities performed in large outdoor areas such as those of agricultural ones, it is not feasible to measure directly those temperatures in all work periods and locations where there are workers. Taking this into account, this work aims to introduce a WBGT index estimation using atmospheric variables observed by automatic meteorological stations. In order to support our estimation method, we used, as a test-bed, data recorded in the State of São Paulo (SP), Brazil. By adding the cloudiness factor in the calculation through measurement of solar radiation, the algorithm proved to be as efficient as those mentioned in this work. It was found that this method is viable, with WBGT-estimated values obtained from meteorological data measured by stations with a distance of less than 80 km. This estimate can be used for monitoring heat stress in real time as well as to investigate heat-related disorders and agricultural work.
authors: Fundacentro, Florianopolis, SC, Brazil.
authors: Paulo Alves
authors: PA
authors: Maia
authors: Fundacentro, Florianopolis, SC, Brazil.
authors: Álvaro Cézar
authors: ÁC
authors: Ruas
authors: Fundacentro, Florianopolis, SC, Brazil. daniel.bitencourt@pq.cnpq.br.
authors: Daniel Pires
authors: DP
authors: Bitencourt
mesh_terms: D000465:Algorithms; D001938:Brazil; D004784:Environmental Monitoring; D055904:Meteorology / Q000379:methods*; D008962:Models, Theoretical; D014887:Weather
keywords: Heat disorders; Heat stress; Meteorological data; Outdoor activities
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