PMV model is insufficient to capture subjective thermal response from Indians

https://doi.org/10.1016/j.ergon.2014.01.005Get rights and content

Highlights

  • A laboratory simulation study on adaptive thermal response from Indians is proposed.

  • PMV overestimates actual Subjective thermal sensation (TSV) response from Indians.

  • A new asymmetric TSV-PPD relation is developed, different from PMV-PPD relation.

  • Thermal comfort zone and optimum temperature for Indians are estimated.

  • Study highlights the limitation of adopting PMV model in Indian context.

Abstract

A controlled laboratory experiment was carried out on forty Indian male college students for evaluating the effect of indoor thermal environment on occupants' response and thermal comfort. During experiment, indoor temperature varied from 21 °C to 33 °C, and the variables like relative humidity, airflow, air temperature and radiant temperature were recorded along with subject's physiological parameters (skin (Tsk) and oral temperature (Tc)) and subjective thermal sensation responses (TSV). From Tsk and Tc, body temperature (Tb) was evaluated. Subjective Thermal Sensation Vote (TSV) was recorded using ASHRAE 7-point scale. In PMV model, Fanger's Tsk equation was used to accommodate adaptive response. Stepwise regression analysis result showed Tb was better predictor of TSV than Tsk and Tc. Regional skin temperature response, suppressed sweating without dipping, lower sweating threshold temperature and higher cutaneous threshold for sweating were observed as thermal adaptive responses. These adaptive responses cannot be considered in PMV model. To incorporate subjective adaptive response, mean skin temperature (Tsk) is considered in dry heat loss calculation. Along with these, PMV-model and other two methodologies are adopted to calculate PMV values and results are compared. However, recent literature is limited to measure the sweat rate in Indians and consideration of constant Ersw in PMV model needs to be corrected. Using measured Tsk in PMV model (Method1), thermal comfort zone corresponding to 0.5 ≤ PMV ≤ 0.5 was evaluated as (22.46–25.41) °C with neutral temperature of 23.91 °C, similarly while using TSV response, wider comfort zone was estimated as (23.25–26.32) °C with neutral temperature at 24.83 °C, which was further increased to with TSV-PPDnew relation. It was observed that PMV-model overestimated the actual thermal response. Interestingly, these subjects were found to be less sensitive to hot but more sensitive to cold. A new TSV-PPD relation (PPDnew) was obtained from the population distribution of TSV response with an asymmetric distribution of hot-cold thermal sensation response from Indians. The calculations of human thermal stress according to steady state energy balance models used on PMV model seem to be inadequate to evaluate human thermal sensation of Indians.

Relevance to industry

The purpose of this paper is to estimate thermal comfort zone and optimum temperature for Indians. It also highlights that PMV model seems to be inadequate to evaluate subjective thermal perception in Indians. These results can be used in feedback control of HVAC systems in residential and industrial buildings.

Introduction

A comfortable thermal environment encourages the productivity, satisfaction and well-being of the building occupants. Thermal sensation refers to subjective feeling about the level of warmth of the environment like warm, hot, neutral, cold etc., and the feeling of comfort is not a direct sense of air temperature. Thermal comfort is defined as the condition of mind which expresses satisfaction with the thermal environment (ASHRAE, 1992, ASHRAE, 2005). Assessment of thermal comfort is one of the important requirements of HVAC (heating, ventilation, and air conditioning) design engineers to create a thermally satisfied environment for the occupants inside buildings or other enclosures. To access physiological strain of an occupant in a thermal environment, different heat stress indices have been derived using environmental ambient parameters. Among them, Effective Temperature (ET), Wet-Bulb Globe Temperature (WBGT), Predicted Four Hour Sweat Rate (P4SR) etc. are most commonly used. Compared to these indices, Fanger (1972) has first developed thermal index based on steady-state heat balance between the body and the environment, and assigned a sensation vote to the physiological strain, which makes results more comprehensible. More recently, international standards such as ISO 7730 (2005) and the ASHRAE Standard 55–92 (ASHRAE, 2005) adopted this Fanger's method to estimate subjective thermal sensation based on Predicted Mean Vote (PMV) model in a ASHRAE 7-points scale, that categories as cold (−3), cool (−2), slightly cool (−1), neutral (0), slightly warm (+1), warm (+2), and hot (+3). Similarly, Thermal Sensation Vote (TSV) or Actual Mean Vote indicates subjective thermal sensation recorded directly from them. From this subjective response (either calculated or directly recorded), thermally comfortable condition is evaluated. The thermal comfort temperature range is decided with at least 90% occupants feel thermally satisfied i.e. [−0.5 ≤ PMV ≤ 0.5] and the optimum temperature denotes as the corresponding ambient temperature at PMV = 0. This PMV model is the most representative thermal comfort model and used worldwide. According to the international standards, the optimum temperature during winter and summer seasons is suggested as 22 °C (with acceptable range of 20–23 °C) and 24.5 °C (with acceptable range of 23–26 °C) respectively, with following environmental and human parameters: relative humidity of 50%; mean relative air velocity of <0.15 m s−1; mean radiation temperature is equal to air temperature; metabolic rate is 1.2 met and clothing insulation for winter and for summer are considered as 0.9 clo and 0.5 clo respectively. In Fanger's equation, PMV values are directly calculated from environmental parameters as it assumes that thermal sensation experienced by a person, a passive response which is a function of physiological strain imposed on him by the environment, and it does not clarify how people respond physiologically and subjectively to the thermal environment. However, thermal adaptation is a natural tendency of people to accommodate in changing climate for better fit and is of mainly three types – 1. Physiological 2. Behavioral (personal, cultural, environmental or technical) and 3. Psychological (habituation or expectation) (Brager and de Dear, 1998). Physiological adaptation occurs in response to repeated stress application, either through gradual diminution of the organism's response to repeated environmental stimulation or increasing the efficiency of the other responses, which will help to prevent or moderate the potential damages or cope with the consequences with relative ease. Researchers have reported that the thermal steady state approach in PMV model causes the failure of estimating thermal comfort effectively (Humphreys and Nicol, 2002, Jones, 2002), whereas other groups of researchers have questioned on the limitation of the experimental conditions, calculation of clothing insulation and the sensitivity of PMV equations (Humphreys and Nicol, 2002, Peeters et al., 2009, Brager and de Dear, 1998). According to the published data, these PMV or PPD indices do not include the effect of personal adaptation like psychological adaptation, physiological adaptation and behavioral thermoregulation (Peeters et al., 2009, Brager and de Dear, 1998, Humphreys and Hancock, 2007, Holmes and Hacker, 2007, Baker and Standeven, 1996), as thermal adaptation is region specific, which modifies subject's thermal preference beyond mere passive experience of body's thermal balance and profoundly influenced by local climatic condition and socio-cultural set-up, food habit, clothing etc.

ASHRAE 55 also includes the adaptive comfort concept supported by large number of field experiments studies in ASHRAE RP 884 databases (de Dear and Brager, 2002). Several authors have reported that especially the people living in the tropical regions, having higher optimum temperature than those in the cold regions due to the adaptation (Wong et al., 2002, Nicol, 2004, Wijewardane and Jayasinghe, 2008, Hwang et al., 2009, Yao et al., 2009, de Dear and Brager, 1998). India is having tropical climate and a large variation in environmental conditions in different regions (Singh et al., 2008). Sharma and Ali (1986) have assessed thermal sensation for Indians and developed “Tropical Summer Index (TSI)” and identified Indian thermal sensations as “slightly cool”, “comfortable” and “slightly warm” at 19–25 °C (with optimum at 22 °C), 25–30 °C (with optimum at 27.5 °C) and 30–34 °C (with optimum at 32 °C) respectively. Bangladesh is also having similar type of outdoor environmental conditions. Thermal comfort zone for Bangladeshi people is reported as air temperature range of 24–32 °C with relative humidity ranging between 50 and 90% and without or in little air movement (Mallick, 1996). From a field study at Hyderabad, India, Indraganti (2010) has estimated the comfort band for Indians to be (26–32.45) °C with the neutral temperature at 29.23 °C. However, the National Building Code of India (BIS, 2005) advocates the use of two indoor temperature ranges for summer (23–26) °C and winter (21–23) °C for all the climatic zones, which is similar to ASHRAE recommendation but far above than the earlier reported results. For better prediction of thermal response in Indians, it is required to quantify human perception of different thermal conditions and how it is correlated with the physiological parameters. Both skin-surface (Tsk) and core (Tc) temperatures are known afferent inputs to the thermoregulatory system, and contribute about equally toward determining thermal comfort (Bulaco et al., 2000). Hence, both skin and core temperatures are potential physiological parameters for objective evaluation of human thermal sensation experienced by the surrounding environment. Skin temperature initiates thermoregulatory response before activating stronger autonomic and metabolic responses controlled by core temperature to maintain the body temperature. Estimation of Tsk is relatively easy, while measuring Tc is always challenging. Rectal temperature is regarded as the most valid core temperature index but it is impractical, invasive and expensive for everyday clinical use. Therefore, oral temperature (recording from sublingual pocket) is one of the common index for Tc as it's measurements are easy and reliable. No literature is available on thermal response studies in Indian climate on their natives, and researchers have concluded for the requirement of further study. In this context, a laboratory study is conducted to investigate how mean skin temperature, oral temperature and body temperature are correlated with TSV responses at different thermal environments and any adaptive variations in objective measurement. A new relation is aimed to establish on TSV and the number of responder at different air temperatures, similar to Predicted Percentage Dissatisfied (PPD) in PMV model to highlight the thermal adaptive response of Indians. This study also aims to evaluate indoor thermal comfort condition for Indians from this TSV-PPD response, and compare the result with PMV-PPD model estimated result.

Section snippets

Subjects

Forty young male university students having age-(25.18 ± 2.4)years, weight-(68.6 ± 8.46)kg and height-(1.71 ± 0.05)m participated in this study as volunteers. They were originally from different part of the country and none of them were professional athletes. The Body Mass Index (BMI) was calculated as ratio of body weight (kg) and square of body height (m) and obtained as 23.38 ± 2.03. Body Surface Area (BSA) of individual participant was calculated using following DuBois and DuBois (1916)

Variation of regional skin temperature, Tsk and Tcore

Variations of regional skin temperatures at different ta are plotted in Fig. 3 and corresponding changes of mean skin temperature (Tsk), core temperature (Tcore) and body temperature are plotted in Fig. 4. Analysis of the variance (ANOVA) results show that the regional skin temperature, mean skin temperature (Tsk) and core temperature at different ta are significantly different (alpha-0.001). In present study, it is observed that regional temperatures changes systematically with ta, which

Conclusion

This study gives an overview of adaptive thermal response from Indian subjects based on laboratory simulation experiment. Determination of subjective thermal sensation using PMV model based on steady state energy balance seems to be inadequate for Indian population. Interestingly, mean skin temperature (Tsk) response shows different slope in higher and lower ta regions, which indicates asymmetric thermal sensation response in Indians. PMV overestimates the actual subjective thermal sensation

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