A Thermal Comfort Investigation of a Facility Department of a Hospital in Hot-Humid Climate: Correlation between Objective and Subjective Measurements

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1 Case Study Paper Indoor and Built Indoor Built Environ 2013;22;5: Accepted: August 12, 2012 Environment A Thermal Comfort Investigation of a Facility Department of a Hospital in Hot-Humid Climate: Correlation between Objective and Subjective Measurements F. Azizpour S. Moghimi C. H. Lim S. Mat E. Salleh K. Sopian Solar Energy Research Institute, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia Key Words Hot-humid region E Neutral temperature E Predicted mean vote (PMV) E Thermal comfort E Thermal sensation vote (TSV) Abstract A field study on assessing thermal comfort has been performed on one of the large-scale hospitals in Malaysia, a country where the climate is classified as hot-humid. The main objective of this study was to examine the comfort criteria by American Society of Heating, Air conditioning & Refrigeration Engineers, US (ASHRAE) standards in hot-humid regions and also to find the correlation between predicted mean vote (PMV) according to Fanger s theory and thermal sensation vote (TSV) according to occupant votes. Therefore, both objective and subjective data was collected in this hospital, and this study s results have confirmed that the preferred temperature is not necessarily in compliance with a neutral temperature, and people in hothumid areas would prefer cooler environment to neutral temperature. In addition, by analyzing linear regression, a strong correlation between PMV and TSV was found while R 2 ¼ 0.950, and also the neutral temperature point in this field study was around þ0.75 on the seven-point ASHRAE thermal sensation scale. Introduction Appropriate indoor air quality (IAQ) is necessary for a healthy environment [1]. Several short-term and long-term problems regarding health and productivity are associated to poor IAQ including temperature, humidity, air velocity, lighting, noise and CO 2 [2,3]. A comfortable indoor environment is an essential condition for any building type. So far, a lot of studies have been done on climate, adaptive and behavioural factors relating to and affecting thermal comfort, HVAC and control systems [4,5]. ß The Author(s), Reprints and permissions: DOI: / X Accessible online at Figures 1 4 appear in colour online F. Azizpour, Solar Energy Research Institute (SERI), Universiti Kebangsaan Malaysia (UKM), 43600, Malaysia. Tel. þ , Fax þ , fa.azizpour@gmail.com

2 These are all important issues that must be considered by architects and engineers when designing and retrofitting buildings. As such, significant opportunities are regained regarding saving energy, reducing emissions and providing appropriate thermal conditions in buildings [2,6,7]. Hospitals in particular face these issues more critically than other buildings due to their unique characteristics and requirements [8,9]. Hospitals operate around the clock, and their micro climate can significantly affect both patients and staffs. Patients thermal requirements are not only due to physical weakness but can also affect the healing process and the length of stay in hospital [10,11]. There are an increasing number of studies that show how workers satisfaction with their work environment including thermal conditions could greatly influence their productivity [12,13]. Furthermore, the high correlation between environmental factors, health, productivity and satisfaction with the work environment could decrease absenteeism amongst staff [14,15]. The first scientific studies on thermal comfort began in 1950s. Then, Fanger s theory based on a fully controlled climate chamber opened the way for researchers to evaluate thermal comfort. In recent years, researchers interest in the adaptive theory of thermal comfort has led to qualifying and improving thermal environment, subjectively and objectively [16,17]. Fundamentally, the adaptive theory implies that humans can play a key role in thermal comfort, meaning that people can create thermal conditions in which they would prefer, consciously or unconsciously, given the opportunity to modify their ambient thermal environment such as changing metabolic rate, posture and clothing [18]. There are many standards for describing thermal comfort in indoor environments. The two most frequently used standards are American Society of Heating, Air conditioning & Refrigeration Engineers, US (ASHRAE) standard [19] and ISO 7730:2005 [20]. Also, some researchers are focusing on thermal comfort in hot-humid climates and have found some differences to the predicted mean vote (PMV) model as prescribed by the standards. Studies show that not all of the above standards are totally suitable for hot-humid region conditions [21,22]. The main objectives of this study are as follows:. To evaluate the thermal sensation vote (TSV) through a field study based on subjective data collection.. To evaluate the predicted mean vote (PMV) in the field study according to objective data collection.. To find the relationship between TSV and PMV and examine the ASHRAE thermal comfort criteria in a hot-humid region.. To evaluate IAQ in the field study based on objective measurements. Research Methodology Climate Background and Site Description Malaysia is a hot and humid tropical country, lying between Latitude 18 and 78 north and Longitude 1008 and 1208 east. Malaysia has a yearly mean temperature of 268C to 278C, high day time temperatures of 298Cto348C and a relative humidity (RH) of 70% to 90% throughout the year [23]. The assessment of thermal comfort was conducted at University Kebangsaan Malaysia Medical Center s (UKMMC) facility department built on 240,000 m 2 and situated in Cheras, Selongor. The facility department is a three-story building located in the west of UKMMC and was established in More information on this building is listed in Table 1. Data Collection The facility department of UKMMC is divided into 5 thermal zones according to different thermal conditions and activity. The 5 thermal zones are lobby, office, praying room, kindergarten and catering area. The lobby, kindergarten and catering areas are located on the ground floor while the praying room and office are on the first floor. The total number of occupants in all 5 zones is around 200. In this study, which investigates thermal comfort, Table 1. Information regarding the field study (facility department of UKMMC) Structure of roof Steep roof, clay tile Structure of external wall Normal brick þ 2-layer plaster Total volume (m 3 ) m 3 Total floor area (m 2 ) 5957 m 2 Max. no. of occupants 250 Cooling system Air conditioned Ext. wall area (m 2 ) 4010 m 2 Ext. opening area (m 2 ) 853 m 2 UKMMC: University Kebangsaan Malaysia Medical Center. A Thermal Comfort Investigation in Hot-Humid Climate Indoor Built Environ 2013;22:

3 both objective and subjective measurements were performed in May and June Objective Measurement Physical data for determining the level of thermal comfort and IAQ was measured with the Thermal Comfort Solar Energy Research Institute (SERI). This equipment can measure ambient temperature, mean radiant temperature (MRT), RH, air velocity (V), lux level, noise and CO 2. All measurements were taken at a height of 1.0 m above the ground and calibration was done prior to measurement. The first step was to evaluate the thermal comfort. There are six physical factors affecting human thermal comfort. The four environmental factors which were measured are air temperature, MRT, humidity, air velocity and the two personal factors of clothing insulation value (CLO) and activity level (MET), which are estimated in accordance with ASHRAE [24,25]. The personal factors of the personnel of each thermal zone monitored by this study are presented in Table 2. In all thermal zones, the Clo-value (thermal resistance) was set at 0.6 according to staff uniforms at UKMMC since this study focused on staffs other than in the praying room where the Clo was estimated to be 0.7 due to additional cover while praying. Regarding different activities observed in different zones, the MET value for the lobby was 1.5 (walking), for the office it was 1.2 (sedentary activity), for the praying room it was 1.4 (praying), for the kindergarten it was 1.2 (sedentary activity) and for the catering area it was 2.0 due to more active activity compared to the other zones. In the second step, to briefly evaluate the IAQ, all environmental factors including temperature, humidity, air velocity, CO 2, light level and noise were compared to the standards given, namely ASHRAE 62.1, Singapore Indoor Air Quality Guidelines (SIAQG), World Health Organization (WHO) and Malaysian Standard (MS) [26 29]. Table 2. The estimated values of CLO and MET NO Thermal zone CLO MET (W/m 2 ) 1 Lobby Office Praying room Kindergarten Catering area CLO: clothing insulation value; MET: metabolic rate. Subjective Measurement This study focused on hospital staff. For the subjective survey, a sample size of 110 filled out questionnaires, were provided by staffs in the different thermal zones. The questionnaire for this survey is given in the Appendix, including the following information: (A) (B) (C) (D) (E) (F) Demographic information Thermal sensation Thermal preference Thermal acceptance Thermal tolerance Control ability of thermal conditions The sampled gender distribution was 24.5% male and 75.5% female, while age distribution was 5.5% below 20 years old, 60% between 20 and 30, 21% between 30 and 40 and 13.5% older than 40. Clearly, the majority of respondents were 20- to 30-year-old females. Results and Discussion Evaluating the TSV Two questionnaire questions were used to evaluate the TSV, as follows: 1. How do you feel about the temperature at this moment? 2. How would you like to feel? The first question regards thermal sensation and the answers comprised seven points on the ASHRAE scale (i.e. cold, cool, slightly cool, neutral, slightly warm, warm and hot). The second question regards thermal preference and there were 5 possible answers: much cooler than now, a little cooler than now, no change, a little warmer than now and much warmer than now. A sample size of 110 subjects, all staff, took part in the survey. Tables 3 and 4 show the descriptive statistical analysis in SPSS. According to Table 5, in the cumulative percent column, 70.9% of respondents voted on the neutral and cool side on the 7-point scale, while according to Table 3, the cumulative percent of those who preferred cooler than now was 60%. However, Table 4 illustrates that among 71% of respondents voting within the three central categories of the ASHRAE thermal sensation scale preferred to feel cooler than now. The results obtained by comparing simultaneous votes on both thermal sensation and thermal preference as shown in Tables 3 5 suggest that neutral thermal 838 Indoor Built Environ 2013;22: Azizpour et al.

4 Table 3. Thermal preference vote Frequency Percentage Valid percentage Cumulative percentage Valid Much cooler than now A little cooler than now No change A little warmer than now Total Table 4. Cross tabulation of thermal sensation and thermal preference Cold cool Feel three scale Warm hot Total Slightly cool neutral slightly warm Thermal preference Cooler than now 6 47 (71%) No change Warmer than now Total Table 5. Thermal sensation vote on the 7-point ASHRAE scale Frequency Percentage Valid Cumulative percentage percentage Valid Cold Cool Slightly cool Neutral Slightly warm Warm Hot Total ASHRAE: American Society of Heating, Air conditioning & Refrigeration Engineers, US. Table 6. Value calculation according to Fanger s theory for five thermal zones in UKMMC Zone OP PMV PPD % MET CLO Lobby Office Praying room Kindergarten Catering area UKMMC: University Kebangsaan Malaysia Medical Center; OP: operative temperature; PMV: predictive mean value; PPD: predicted percentage of dissatisfied; MET: metabolic rate; CLO: clothing insulation value. sensations are not always the preferred thermal state. de Dear (1998) believes that thermal preference temperature is more suited than thermal neutral temperature to serve as the criterion for thermal comfort [16]. It has also been revealed that UKMMC occupants prefer cooler than neutral temperature since the significance level in this test was This finding is in agreement with a study on classrooms in China done by Zhang et al. in 2007 [30] and in workplaces and residences in Taiwan [21]. Furthermore, it echoes Humphreys hypothesis [31]. Moreover, it aligns well with McIntryre s studies of 1980 [32]. McIntryre realized that people in hothumid regions would prefer a slightly cool environment, while people in cold regions would prefer a slightly warm environment [18]. Evaluating Thermal Comfort Index PMV and predicted percentage of dissatisfied people (PPD) were calculated in this field study (UKMMC) according to Fanger s formula for all 5 thermal zones. The results are presented in Table 6 and Figure 1. The personal factor values used in the calculation are taken from Table 2. As shown in Table 6 and Figure 1, the PMV, PPD and OP are calculated based on Fanger s model in all thermal zones. In the lobby at C operative temperature (OP), the PMV value was 1.5 and that 48.4% of occupants were dissatisfied with their environment. In the office, the PMV value was 0.1 and 5.1% of people were dissatisfied. In the praying room, the mean vote was predicted to be 0.8 with 17.2% dissatisfied. In the kindergarten, the PMV value A Thermal Comfort Investigation in Hot-Humid Climate Indoor Built Environ 2013;22:

5 Predicted Percentage of Dissatisfied (PPD) lobby 52.9% % kinder garden % catering area 30 office % praying room % Predicted Mean Vote (PMV) Fig. 1. Predictive mean value (PMV) versus predicted percentage of dissatisfaction (PPD) in five thermal zones. Table 7. A profile of TSV and calculated PMV and PPD values for each investigated thermal zone Zone OP TSV on ASHRAE scale Mean TSV PMV PPD Cool ¼ 3 Cold ¼ 2 Slightly cold ¼ 1 Neutral ¼ 0 Slightly warm ¼þ1 Lobby þ1.08 þ % Office þ % Praying room þ % Kindergarten % Catering þ0.61 þ % ASHRAE: American Society of Heating, Air conditioning & Refrigeration Engineers, US; OP: operative temperature; PMV: predictive mean value; PPD: predicted percentage of dissatisfaction; TSV: thermal sensation vote. Warm ¼þ2 Hot ¼þ3 was in the negative and was equal to 1.5 with 52.9% PPD. Finally, in the catering area, the calculated PMV and PPD were 1.5 and 48.2%, respectively. Correlation between Subjective and Objective Measurements A comparison between two kinds of data collection was conducted to clarify an important question in this field: Is there any correlation between TSV and PMV in hothumid regions? To answer the question, the mean actual vote in the 5 thermal zones was considered. Table 7 provides a comparison of the TSV, PMV and PPD values. As presented in Table 7, in all thermal zones, the calculated PMV value was higher than mean TSV. It can be inferred that people in Malaysia are well acclimatized and accustomed to hot-humid weather and would tolerate higher temperatures. This finding is in agreement with many studies that have emphasized the role of adaptation to climate on thermal comfort evaluation [4,21,31]. By analyzing the linear regression between TSV and PMV, a strong relation (R 2 ¼ 0.950) was found with equation y ¼ 0.982x þ (Figure 2), while the new PMV limit corresponding to the neutrality range in this field study was 0.22 and þ1.73 as opposed to 1 and þ1 as suggested by Fanger s model. In addition, the neutrality point was þ0.75 and not 0 as acclaimed by Fanger s model, meaning that the neutrality point for people in hothumid regions would be closer to slightly warm on the seven-point ASHRAE scale. Correlation between OP and TSV Figure 3 depicts the correlation between the mean TSV with OP in each investigated thermal zone within the operative C temperature range. 840 Indoor Built Environ 2013;22: Azizpour et al.

6 2 y = 0.982x predicted mean vote (PMV) R² = Fig thermal sensation vote (TSV) Linear regression on predictive mean value (PMV) with thermal sensation vote (TSV). Fig y = 0.487x R² = Operative Temperature (OP) Linear regression on thermal sensation vote (TSV) with operative temperature (OP). Thermal Sensation Vote (TSV) The neutral OP estimated by the regression line for TSV equal to 0 was 26.88C, and the strong relationship was indicated in Figure 3 as R 2 ¼ The regression line slope in Figure 3 is equal to 0.487/8C, which means more than a 28C variation of OP can cause the result to equal 1 as variation of TSV. Figure 4 shows the relationship between OP and calculated PMV with R 2 ¼ and the slope of this regression line is exactly the same as the slope of the linear regression model relating TSV with OP. The neutral OP derived from the PMV regression analysis is equal to 258C, nearly 1.88C lower than the regression result of mean thermal sensation vote. Table 8 shows the comparison between the results obtained from this study are similar to previous thermal comfort studies [30,33 36]. Evaluating the IAQ To evaluate IAQ, six environmental factors were measured in 5 thermal zones as listed in Table 9. The factors were compared with set standards including ASHRAE, SIAGE, WHO and MS. Table 9 illustrates the average of six environmental factors measures by thermal comfort in five different thermal zones. ASHRAE defines the range of comfort temperature between 228C and 248C [26], while the A Thermal Comfort Investigation in Hot-Humid Climate Indoor Built Environ 2013;22:

7 Fig. 4. Predicted Mean Vote(PMV) y = 0.487x R² = Operative temperature Linear regression on predictive mean value (PMV) with operative temperature (OP). Table 8. Regression formulas from similar studies Author Location Regression formula R 2 References de Dear 1985 Australia TSV ¼ TO [33] Donnini, 1997 Cold climate TSV ¼ TO [34] Cena, 1999 Hot humid TSV ¼ 0.21 TO 4.28 (summer) [35] TSV ¼ 0.27 TO 6.29 (winter) Hwang, 2006 Taiwan TSV ¼ ET* [36] Observed, 2011 Malaysia TSV ¼ TO TSV: thermal sensation vote. Table 9. Comparison of environmental factors to set standards in five thermal zones Zone Temperature (8C) Humidity (%) Air velocity (m/s) CO 2 (ppm) Lux (lumen/m 2 ) Noise (dba) Av M ASHRAE SIAGE Av M ASHRAE SIAGE Av M WHO Av M ASHRAE Av M MS Av M WHO SIAGE SIAGE Lobby Office Praying room Kindergarten Catering area Av M: average of measured data; ASHRAE: American Society of Heating, Air conditioning & Refrigeration Engineers, US; SIAQG: Singapore Indoor Air Quality Guidelines, WHO: World Health Organization; MS: Malaysian Standard. SIAGE comfort temperature ranges between 22.58C and 25.58C [27]. According to both standards, the lobby, praying room, kindergarten and catering area were not in the comfort range. The averages of the second factor, humidity, according to the ASHRAE standard [26], all zones were out of range except the Kindergarten; according to SIAGE [27], all were within range except the catering area. Air velocity, the third factor, exceeded the threshold in all zones by 0.25 m.s 1. As Table 9 demonstrates, CO 2 in all zones except the Office was below 842 Indoor Built Environ 2013;22: Azizpour et al.

8 the threshold of ASHRAE [26] and SIAGE [27] set at 1000 ppm. In the office, this would be the case due to the number of occupants, which was affecting the level of CO 2, 1074 ppm was measured. The lighting level standard may vary from zone to zone due to different activity being carried out in each particular zone. According to the Malaysian standard 1525, proper lighting levels would be 100 lux for the Lobby, lux for the office, 200 lux for the praying room and kindergarten and lux for the catering area [29]. Thus, all zones in this study were below the range. The recommended WHO standards on the last factor, which is the noise level, are 70 dba in the lobby, around 40 dba in the office and praying room, dba in the kindergarten and 70 dba in the catering area [28]. According to these standards, the noise level in the office, praying room and kindergarten exceeded the acceptable range [26,37]. Conclusions The most important findings of this field study on thermal comfort of staff working in a hospital department in a hot-humid climate region, such as Malaysia, were derived by examining the thermal comfort criteria given by ASHRAE standards. Objective measurements and subjective surveys were both conducted to identify the relationship between PMV and actual mean vote (TSV). In addition, the IAQ of the case study was briefly evaluated and the conditions were compared with several standards.. Through descriptive statistical analysis performed in SPSS, it was found that 70.9% of staff voted on neutral and cool on the seven-point thermal sensation ASHRAE scale, while the percentage of those who preferred cooler than now was 60%. On the other hand, 71% of staff who voted within the three central categories of the ASHRAE scale preferred to feel cooler than now indicating that the neutral temperature is not always preferred.. In addition, it was clarified that people in this field study from a hot-humid area would prefer the lower temperature to the neutral.. In all 5 thermal zones (lobby, office, praying room, kindergarten and catering area) the PMV was higher than the TSV, revealing that participants in this survey are acclimatized to the hot-humid weather.. TSV regression models on PMV indicated a strong correlation between PMV and actual mean vote.. Moreover, by analyzing the linear regression between TSV and PMV, neutrality in this field study was found to be around þ0.75 rather than 0 as given in Fanger s model.. TSV and PMV regression models on OP showed that the neutral temperature was 26.88C and 258C, respectively; meaning that neutral temperature in this field study according to Fanger s theory (PMV) was 1.88C lower than actual mean vote (TSV). The slope of these two regressions were exactly the same and equal to 0.487/8C, meaning that the 28C OP variation would cause the result to equal 1 as variation of both TSV and PMV.. The CO 2 level in the office was higher than the standard range due to the number of occupants. The lighting level in all 5 zones was lower than the criteria given by the standards mentioned above. The noise level in the office and praying room where the occupants need to concentrate exceeded the WHO standards and will require appropriate remediation to be decided by the decision makers of the hospital. Acknowledgement The authors would like to express their gratitude to the Solar Energy Research Institute (SERI), Universiti Kebangsaan Malaysia, the Ministry of Science, Technology and Innovation Malaysia for sponsoring the work under the project Science fund UKM-DLP Thanks as well to Malika Mouhdi and the UKMMC staff for their valuable assistance in this project. References 1 Yu CWF, Kim JT: Building environmental assessment schemes for rating of IAQ in sustainable buildings: Indoor Built Environ 2011;20(1): Kumar S, Mahdavi A: Integrating thermal comfort field data analysis in a case-based building simulation environment: Build Environ 2001;36: Department of Occupational Safety and Health, Ministry of Human Resources, Malaysia: Code of Practice on Indoor Air Quality. Malaysia, Department of Occupational Safety and Health, Ministry of Human Resources, Nicol JF, Humphreys MA: Adaptive thermal comfort and sustainable thermal standards for buildings: Energy Build 2002;34: Buratti C, Ricciardi P: Adaptive analysis of thermal comfort in university classroom: correlation between experimental data and mathematical models: Build Environ 2009;44: De Dear R: Thermal comfort in practice: Indoor Air 2004;14: A Thermal Comfort Investigation in Hot-Humid Climate Indoor Built Environ 2013;22:

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10 Appendix: Questionnaire Synthesis A Thermal Comfort Investigation in Hot-Humid Climate Indoor Built Environ 2013;22: