Thermal Comfort in Outdoor Environment

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of outdoor comfort indices, however, SET*, PMV and PET have proven suitable for ... Key words: comfort index, outdoor, PET, PMV, SET*, thermal comfort. 1.
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Thermal Comfort in Outdoor Environment Tsuyoshi HONJO Faculty of Horticulture, Chiba University 648 Matsudo, Matsudo-shi, Chiba 271-8510, Japan e-mail: [email protected]

Abstract Relatively few studies on thermal comfort for outdoor environments have been done compared to indoor environments, although the importance of the former is increasingly recognized with changing climate and increase of heat stress in cities. The difficulty in assessing thermal outdoor conditions is that the climatic variables are much more diverse than in indoor settings. Indices such as SET*, PMV and PET are the most broadly used not only as indoor indices but also as outdoor comfort indices. In the present study, applications of these indices to outdoor conditions are reviewed. There remain problems in the assessment of outdoor comfort indices, however, SET*, PMV and PET have proven suitable for application at the current state of the art. Key words: comfort index, outdoor, PET, PMV, SET*, thermal comfort

1. Introduction During the last decade, interest in the assessment of thermal comfort has increased because of climate changes and increased heat stress in cities. But there have been relatively small numbers of studies on thermal comfort for outdoor environment (Swaid et al. 1993; Nikolopoulou et al. 2001; Givoni et al. 2003; Spagnolo & de Dear, 2003). On the other hand, many studies have been done on thermal comfort especially for indoor environment. Climatic chambers became available more frequently after 1960 which permitted to analyze separately the influences of the 4 main climatic parameters: 1) ambient air temperature, 2) radiant (i.e., wall) temperature, 3) air humidity and 4) airstream velocity (Mayer & Höppe, 1987) on thermal comfort. They enabled extensive studies to establish indices for indoor thermal comfort and discomfort. Gagge et al. (1971) promoted the concepts of New Effective Temperature (ET*) or, respectively, standard Effective Temperatures (SET*) by taking into account: 5) different degrees of insulation measured by “clo” and 6) levels of activity measured by “met” as additional factors. Fanger (1972) provided an extensive set of comfort diagrams from which – for given conditions of “clo” and “met” – Predicted Mean Values (PMV) of comfort or discomfort were derived by obtaining a rating scale from large samples of individuals for subjectively felt (dis-)comfort as a useful tool to establish comfortable indoor conditions by air conditioning, depending on clothing and physical activity. Theoretically, the indices developed for indoor Global Environmental Research 13/2009:43-47 printed in Japan

conditions can also be applied to outdoor environments. However, Spagnolo and de Dear (2003) pointed out for SET* that it cannot be used outdoors without modification. The main problem for assessing thermal outdoor conditions is that the climatic variables may be much more diverse than in indoor settings. To account for this problem, the Physiological Equivalent Temperature (PET) was developed (Mayer & Höppe, 1987) with the aim to obtain a better estimate of outdoor conditions. Proceeding from thermophysiological considerations and taking into account the above-mentioned climatic parameters, PET, as an index, is similar in definition to ET* (i.e., its dimension is °C) and presents an outdoor equivalent to a typical indoor setting, e. g., heat balance of a human subject at light activity (80 W) and indoor clothing (0.9 clo). Apart from SET*, PMV and PET, as the most frequently used indices, climatic outdoor conditions have been further characterized by less complex indices such as the discomfort index (Thom, 1959), wind-chill index (Steadman, 1971) and apparent temperature (Steadman, 1979). While indoor environment can be easily changed by air conditioning, methods for making an outdoor environment comfortable are very limited. For the outdoor environment, the indoor comfort indices were sometimes applied. Spagnolo and de Dear (2003) reviewed the studies on thermal comfort of outdoor conditions and questioned that the theory developed for an indoor environment can be applied to an outdoor environment without modification. The outdoor comfort indices based on energy balance of the human body should also use meteorological variables (air temperature, humidity, ©2009 AIRIES

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radiation, and wind speed) and human factors (clothing and metabolism). But broader ranges of meteorological variables and of human factors pose greater difficulties when assessing outdoor comfort indices compared to indices for an indoor environment. Currently, in recent studies on outdoor thermal comfort SET*, PMV and PET are the most broadly used indices. In the present study applications to outdoor conditions of the indices SET*, PMV and PET are reviewed. Specifically compared by presenting examples are the prediction values of PMV and PET in two different outdoor settings.

2. Energy Balance of the Human Body In the thermal indices which consider the thermal physiology, energy balance of the human body is important to evaluate the thermal comfort. Equation of the energy balance, which is the basis for the comfort indices, is expressed as follows (Höppe, 1999). M+W+R+C+ED+ERe+ESw+S = 0, where M is the metabolic rate, W is the physical work output, R is the net radiation of the body, C is the convective heat flux, ED is the latent heat flux diffusing through the skin, ERe is of heat flux by the respiration, ESw is the heat flux due to evaporation of sweat, and S is the storage heat flow for heating or cooling the body mass. These terms in this equation have positive signs if they gain energy for the body (M is always positive, W, ED and ESw are always negative). The individual terms are mainly influenced by the meteorological parameters. C and ERe are affected by air temperature, ED, ERe, ESw are affected by humidity, Ultrasonic anemometer

Pyrgeometer

Pyranometer

Thermometer/ hygrometer

Globe thermometer

Data logger

Fig. 1 Photograph Showing the Setup of Meteorological Instruments for the Measurement of Outdoor Comfort Indices. Relations between factor and senser are shown below. Factor Air temperature Globe temperature Relative humidity Wind speed Incoming short-wave radiation Incoming long-wave radiation (according to Thorsson et al., 2007)

Sensor Thermometer Globe thermometer Hygrometer Ultrasonic anemometer Pyranometer Pyrgeometer

C and ESw are affected by wind velocity and R is calculated as the exchange between environment and human body by short wave and long wave radiation. A typical setup of meteorological instruments to assess these environmental variables is shown in Fig. 1. In a sedentary condition we feel comfortable when sweat production is small or ESw is near zero. At higher levels of activity, comfort is attained at modest levels of sweating or skin wettedness. That means that combinations of skin temperature and the body’s core temperature indicating the comfortable range are activitydependent. The other important condition for the comfort is that changes of S do not exceed a certain small value, i.e., the amount of metabolic heat generated in the body (M +W) is approximately equal to the amount of heat lost from the body.

3. Outdoor Comfort Indices and Their Application 3.1 SET* The new effective temperature (ET*) is based on human energy balance and two-node model (Gagge et al., 1971). With ET* the thermal conditions can be compared to the conditions in a standardized room with a mean radiant temperature equal to air temperature and a constant relative humidity of 50%. Gagge et al. (1986) improved ET* and proposed the new standard effective temperature (SET*) which is used frequently both as indoor and outdoor comfort index. Ishii et al. (1988) compared several thermal comfort indices and concluded that SET* is better suited in evaluating outdoor comfort. Kinouchi (2001) also found that SET* can be used as an index for the outdoor environment. Pickup and Dear (1999) improved the SET* and developed thermal indices especially for outdoor conditions OUTSET*. Many CFD (Computational Fluid Dynamics) models have been used in the analysis of outdoor thermal environment (Bruse & Fleer, 1998; Tominaga et al., 2004; Stathopoulos, 2006). In recent studies, distribution of SET* is used as an output of CFD model (Lin et al., 2008). Chen et al. (2004) measured the outdoor environment of apartment blocks and simulated the effects of changes in the outdoor thermal design on calculated SET*. With the CFD model and Genetic Algorithm (GA) Ooka et al. (2008) simulated the optimum arrangement of trees and Chen et al. (2008) simulated the influence of the arrangement of buildings on the outdoor thermal environment. Both studies show the distribution of SET* at the pedestrian level. To calculate the convective heat flux C in the equation of human energy balance, a single value of convective heat transfer coefficient has been mostly used. Ono et al. (2008) divided the human body into nine parts and measured the coefficient of each part by wind tunnel experiments using a thermal manikin. The values of the coefficients were compared with the CFD model and used for the calculation of SET* distribution.

Thermal Comfort in Outdoor Environment

3.2 PMV Fanger (1972) developed PMV (predicted mean vote) for indoor climates with the aim to provide an index for ratings of thermal (dis-)comfort at various states of activity and clothing insulation. PMV is also used as ISO 7730 (ISO, 1994). In Table 1, the relation of PMV value with thermal perception and physiological stress level is shown for low activity and normal indoor clothing. To apply PMV to outdoor conditions, Jendritzky and Nübler (1981) added complex outdoor radiation (Fig. 2) and the model is known as Klima-Michel Model (KMM). As an application of KMM model, Jendritzky and Nübler (1981) showed the distribution map of PMV in Freiburg from which effects of buildings and heat islands are obvious. Matzarakis and Mayer (1997) calculated PMV to develop a high-resolution map that presents the average annual number of days with strong heat stress (PMV>3.0), using Greece as an example. They selected PMV as the index because PMV with KMM is a wellsuited measure for assessing the thermal environment of different outdoor-climates. In this study, PMV was calculated with the meteorological data obtained at 12 Greek stations for the years 1980 to 1989. The map shows quite broad areas which have to be considered as areas of high heat stress. From meteorological measurement in a nearby park, Vu et al. (1998) calculated PMV and found that inside the park, the PMV for a walking person is 2.6. The PMV for the same person in the upwind direction of the park is 3.2 and the corresponding value of PMV in the downwind direction of the park is 2.8. In this study, the PMV value itself is not in the comfortable range but the decrease in PMV, due to the presence of the park, indicates a improvement of the thermal environment. Thorsson et al. (2004) studied the relationship between the thermal environment and behavioral patterns in an urban park located in Goteborg, Sweden by structured interviews, observations of the behavior and measurements of PMV. In Fig. 3, comparison between the thermal perception of the interviewees and the PMV indicated some discrepancy between PMV and actual perception vote (ASV). 41% of calculated PMV of the interviewees were outside the range of Fanger’s model (3). Nikolopoulou et al. (2001) also presented similar results. Hodder and Parsons (2007) investigated the effect of quantity and quality of solar radiation on thermal comfort. They set a semi-outdoor arrangement like a seat of a car, and changed the intensity of solar radiation, spectral contents with same intensity of solar radiation and material of the glass through which solar radiation came in. PMV was kept 0±0.5 where there was no direct radiation. Increase in the total intensity of solar radiation was the critical factor affecting thermal comfort.

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Table 1 Ranges of PMV and physiological equivalent temperature PET for different grades of thermal perception and physiological stress; internal heat production: 80 W, heat transfer resistance of the clothing: 0.9 clo (according to Matzarakis & Mayer, 1997). PMV

PET (°C)

–3.5 –2.5 –1.5 –0.5 0.5 1.5 2.5 3.5

4 8 13 18 23 29 35 41

Thermal perception Very cold Cold Cool Slightly cool Comfortable Slightly warm Warm Hot Very hot

Grade of physiological stress Extreme cold stress Strong cold stress Moderate cold stress Slight cold stress No thermal stress Slight heat stress Moderate heat stress Strong heat stress Extreme heat stress

Fig. 2 The components of the human radiant energy budget. short-wave radiation (0.28-4um): I = direct solar radiation, H = diffuse solar radiation, (I+H)refl = reflected short-wave radiation. long-wave radiation (4-100um): Eu = atmospheric counter radiation, EA = long-wave emissions of the surroundings, W = radiation from the man’s surface. (according to Jendritzky & Nübler, 1981)

Fig. 3 Percentage frequency distribution for thermal perception assessed by the predicted mean vote (PMV) index and the thermal perception of the interviewees (ASV) (according to Thorsson et al., 2004).

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3.3 PET PET was developed as an index which takes into account all basic thermoregulatory processes (Höppe, 1993) and is based on a thermo-physiological heat balance model called Munich energy balance model for individuals (MEMI) (Höppe, 1984; 1999). According to Mayer and Höppe (1987) and Höppe (1999), PET is defined as the equivalent air temperature at which, in a typical indoor condition heat balance of the human body exists (work metabolism 80 W of light activity, and clothing of 0.9 clo). The following assumptions are made for the indoor reference climate: Mean radiant temperature equals air temperature (Tmrt=Ta). Air velocity is set to 0.1 m/s. Water vapour pressure is set to 12 hPa (approximately equivalent to a relative humidity of 50% at Ta=20°C). Although PET is the equivalent temperature under a virtual indoor condition, it is applicable to a wide range of real outdoor conditions. PET is one of the recommended indices in new German guidelines for urban and regional planners (VDI, 1998) and is used for the prediction of changes in the thermal component of urban or regional climates. By using the Software named RayMan developed by Matzarakis et al. (2007), PET can be calculated easily. The comparison of PMV with PET is shown in Table 1. The range of thermal perception and physiological stress of both indices are also shown. As applications of PET: Matzarakis et al. (1999)

determined PET for heat stress in Greece proceeding from the data used by Matzarakis and Mayer (1997) for evaluation of PMV. Svensson et al. (2003) presented the distribution map of PET in Goteborg by using the geographic information system. Gulyás et al. (2006) evaluated thermal comfort in Szeged, Hungary. Ali-Toudert and H. Mayer (2006) studied the effects of aspect ratio and orientation of an urban street canyon. Bouyer et al. (2007) evaluated the thermal comfort of a stadium by using wind tunnel experiments and PET. Alexandri and Jones (2008) analyzed the effect of greening of walls and roofs of urban canyons in a simulation model and based evaluation of thermal comfort on PET. Thorsson et al. (2007) studied the relation between the thermal comfort and outdoor activities in a satellite city near Tokyo, Japan. Comparison of the results of structured interviews and of PET evaluation in an urban park and a square are shown in Fig. 4. PET shows good agreement with the perception of interviewees. It is superior to that shown Fig. 3 where PMV was used as an the comfort index. Further studies will be necessary to decide which index is more suitable for indicating outdoor comfort, depending on the particular environmental conditions.

4. Conclusions Although there remain problems in the assessment of outdoor comfort indices, SET*, PMV and PET have proven suitable for application at the current state of the art. Outdoor and indoor comfort zones may differ from each other. There may be larger influences of psychological aspects when we stay in outdoor than in indoor environments. Adaptation or acclimatization to the outdoor environment should be studied. We do not have enough knowledge about the influence of regional differences on the comfort zone. An Universal Thermal Comfort Index (UTCI) is now being developed (Höppe, 2002) but for an improved assessment of outdoor thermal comfort much more measurements and consideration of additional aspects will be necessary. References

Fig. 4 Percentage Frequency Distribution of Thermal Perception of the Interviewees and Calculated Physiological Equivalent Temperature (PET) at (a) Matsudo Station Square and (b) Matsudo Central Park (according to Thorsson et al., 2007).

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Tsuyoshi HONJO Tsuyoshi HONJO is a professor in Faculty of Horticulture at Chiba University, Japan. One of his interests is urban meteorology especially the effect of urban vegetation. He is also interested in visualization of landscape by computer graphics and various area of computer application in agriculture.

(Received 15 January 2009, Accepted 23 March 2009)