Calibration of the Physiological Equivalent Temperature (PET) index range for outside spaces in a tropical climate city

Highlights

• (PET) thermal comfort index is frequently used in studies on thermal comfort.

• It is considered one of the most important indices for analyzing thermal conditions in urban areas.

• This study aimed to calibrate the PET index for Cuiabá-MT, a tropical climate city.

• The findings contribute to clarifying issues related to thermal perception.

Abstract

This study aimed to calibrate the physiological equivalent temperature (PET) index range for Cuiabá-MT, a city with a tropical climate, for which PET calibration was not previously conducted. The air temperature, relative humidity, globe temperature, wind speed, and direction were measured in three scenarios: arboreal shading (S1), artificial shading with parasol (S2), and sun exposure (S3). Questionnaires were administered to a group of 30 people to verify the preferences, perceptions, and levels of thermal comfort of respondents with data processing, using RayMan software. The values with the greatest differences were between S1 (wooded) and S3 (sun exposure). Five categories of the PET index were adapted: slightly cold, comfortable, slightly hot, hot, and very hot. The comfortable range was found to be between 23.01 and 34.64 °C. When performing the correlation of the users' responses regarding their thermal perceptions and preferences in the different scenarios, it was found that in S1, the percentage of thermal comfort was the highest and in S3, the percentage of thermal discomfort was the highest, reinforcing the significance of afforestation in thermal comfort. The findings of this study contribute to the clarification of issues related to thermal perception and comfort in open spaces in tropical climate.

Introduction

Studies on human thermal sensation and comfort in outdoor environments have recently received attention from urban climatologists, human biometeorologists, and bioclimatologists (Park et al., 2014).

According to Potchter et al. (2018), the PET index was first applied to thermal perception and sensation in 2003, and has been in constant use since 2006. Furthermore, its use became predominant from 2012.

According to Krüger et al. (2018), the PET is an index based on the Munich Energy-balance Model for Individuals (MEMI), which is based on the energy balance of an individual, that uses climatic variables (temperature, air humidity and wind) and the radiant temperature which is based on the human thermal balance equation.

PET is one of the most important indices for analyzing bioclimatic thermal conditions in urban areas. For example, in the studies conducted in Brazil and Cuba, simulations with PET and meteorological data showed that, in shaded settings and increased wind speed, the thermal bioclimate can be substantially improved in tropical cities (Abreu-Harbich et al., 2015; Algeciras and Matzarakis, 2015).

The PET thermal comfort index is widely used to determine outdoor thermal comfort conditions in different climatic zones, such as, mediterranean (Csa) (Tsitoura et al., 2014), wet tropical (Af) (Silva and Alvarez, 2015), continental / wet subtropical (Dwa/Cwa) (Jeong et al., 2016), wet subtropical (Cfa) (Liu et al., 2016), desert and arid (BWh) (Elnabawi et al., 2016), hot-humid (Aw) (Ndetto and Matzarakis, 2017), and semi-arid desert (BWh) (Middel et al., 2017).

The neutrality range may vary in different locations, for example, for the state of Arizona, USA, it was 19.1–38.1 °C (Middel et al., 2017) and for the cities, Changsha and Shanghai, in China, the ranges were 15.0–22.0 °C and 15.0–29.0 °C, respectively (Chen et al., 2015), being necessary to determine this range for tropical climates.

As noted by Krüger et al. (2018), there is no consensus among researchers about which strategy to use in PET index calibrations, making comparisons difficult.

The PET thermal comfort index calibration method used by the majority of researchers was linear regression (Kántor et al., 2012; Krüger et al., 2017). Silva and Alvarez (2015) used the frequency-analysis method. Hirashima et al. (2016) used ordinal regression analysis.

The need to make several calibrations is associated with differences between countries, climatic and cultural contexts, and different thermal requirements, reinforcing the argument of Johansson et al. (2014) for the standardization of protocols and methods in outdoor comfort research.

Thus, to define adequate predictive indices of thermal comfort, there is a need to develop local calibration models.

Therefore, the calibration of the PET index needs to consider the physical and physiological aspects (which influence the heat balance of the human body) and the adaptive factors with regard to local climatic conditions, thus justifying the need to collect subjective data related to index values.