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How to Perform a Thermal Comfort Analysis

Image of Laura Miller
Laura Miller

Fred Betz implements initiatives to promote sustainability at healthcare facilities around the world. He also helps develop compliance documentation for the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE). His work relies on the “predicted mean vote” (PMV), a thermal comfort model used to anticipate the temperatures people consider comfortable based on climate, culture, and how people dress. 

To illustrate how this works, Betz described his experience at a recent ASHRAE summer meeting in Houston: 

Ambient temperatures (were) above 30˚C (86˚F) and relative humidity levels above 60 percent. Most attendees dressed appropriately for the weather and froze inside the buildings. There were several complaints that it was too cold inside. Texans showed up to the meetings in full suits and had an appropriately high CLO value to keep themselves warm. They knew their culture of keeping buildings at (approximately) 20˚C (68˚F) in the summer. Outsiders such as myself spent four days being cold indoors and sweating outside. The irony of this is that it took place at an event for an industry that provides thermal comfort.

The local Texans in this case considered the venue to have achieved optimal thermal comfort, whereas the visitors from elsewhere found the indoor environment too cold. 

Betz’s account reveals just how complex creating comfortable indoor environments can be. But the information gained from such an analysis can be invaluable as you seek to create safer and more comfortable indoor spaces.

How to Measure Thermal Comfort

Analyzing thermal comfort involves studying the perception of temperature variations and other environmental variables on the human body. According to a study to be released in the August 2021 issue of the Journal of Building Engineering, there are seven primary indices of thermal comfort that can be applied to built environments:

Predictive Mean Vote 

Developed at Kansas State University and in cooperation with the Technical University of Denmark, the concept of the predicted mean vote (PMV) looks empirically at how humans perceive thermal comfort. The analysis uses a seven-point scale that predicts the average vote of large groups. 

The PMV scale:

  • +3 = hot
  • +2 = warm
  • +1 = slightly warm
  • 0 = neutral
  • -1 = slightly cool
  • -2 = cool
  • -3 = cold

This allows you to estimate the predicted percent of dissatisfied people (PPD). 

Wet Bulb Globe Temperature 

Wet bulb globe temperature (WBGT) instruments measure the temperatures of wet and dry bulbs, along with a black globe, to estimate stress due to high temperatures in a work environment. It seeks to calculate conditions that could lead to heat-related health issues and alerts workers so they can mitigate these effects.

The equation used to determine WBGT in indoor environments is: 

WBGT = 0.7 x WB + 0.3 x BG

WB is the wet bulb temperature, BG is the 6-inch Vernon Black Globe temperature


Measuring conditions both indoors and outdoors, this index is particularly relevant for building occupants engaged in strenuous activities indoors, especially in areas where ventilation and air conditioning are uneven, as is often the case in warehouse or factory settings. 

Discomfort Index 

Discomfort index values are calculated by determining WBGT but looks more specifically at building design, including ventilation and orientation in relation to the sun. 

Cooling Power Index 

Though originally used to convey the effects of wind speed and outdoor temperatures on thermal comfort, a 2019 article in Applied Energy examined its application in relation to energy use and conditions moderated by passive or hybrid cooling systems. It considers the following cooling factors: 

  • Air temperature
  • Humidity
  • Movement of air/ventilation

Devices called Kata thermometers help measure cooling power, with a wet Kata reading above 20 indicating thermal comfort. 


Relative humidity levels indoors should be a part of any thermal comfort analysis. But its impact goes beyond comfort.

Relative humidity can impact indoor air quality, which in turn can affect respiratory conditions and allergies in building occupants. 

  • Studies have shown that infectious airborne viruses and bacteria are minimized when exposed to relative humidity levels between 40-70 percent. 
  • Relative humidity affects allergenic mites, which reach maximum size at 80 percent relative humidity, and fungi, most of which require relativity levels of at least 60 percent to grow. 
  • Relative humidity affects formation of nitrogen and sulfur dioxide, off-gassing of formaldehyde from indoor materials, and ozone formation. 

Keeping indoor humidity levels between 40-60 percent would minimize most adverse health effects

Standard Effective Temperature

Thermal comfort analysis using standard effective temperature (SET) measurements look at temperature in an imaginary environment where radiant temperature equals air temperature, with relative humidity at 50 percent and airspeed at less than 0.1 meters per second (just under 4 inches per second). This measurement examines the heat loss from skin while occupants conduct normal activities dressed in pants and long-sleeved shirts. As such, SET relies on criteria similar to those of the cooling power index. 

Universal thermal climate index 

The universal thermal climate index (UTCI) looks at conditions immediately surrounding built environments, which ultimately affect thermal conditions indoors. This correlates strongly with other thermal comfort analyses—such as PMV, SET, or WBGT—and is designed to produce accurate readings in all climates and during any season. 

Going Beyond Thermal Comfort Analysis

Thermal comfort analysis can be more easily achieved with an intelligent building automation system (BAS) that includes IoT devices and an advanced analytics layer with machine learning capabilities, such as onPoint. 

Reliable sensor data is essential to all thermal comfort indices. But with advanced analytics, it can also become actionable. By collecting, organizing, and analyzing environmental data, onPoint offers deep visibility into building conditions and can correlate multiple variables to elucidate relationships between conditions and building systems. Heating, cooling, and ventilation can then be automatically adjusted based on real-time and historical temperature, humidity, occupancy, and weather data, as well as season. As more data is gathered over time, responses become better, helping you achieve optimal thermal comfort even in changing conditions. Meanwhile, advanced fault detection and diagnostics streamlines maintenance and simplifies troubleshooting, which means faster fixes and fewer complaints from uncomfortable occupants. 

With customizable reporting and powerful automation capabilities, onPoint can help building owners and facilities managers develop a comprehensive plan for thermal comfort and enhance the everyday lives of occupants. 

Buildings IOT offers the services and technologies you need to perform a thermal comfort analysis and create better occupant experiences. Contact our expert team to learn more.



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