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1 Energy and Buildings 41 (2009) Contents lists available at ScienceDirect Energy and Buildings journal homepage: A comparative analysis of urban and rural residential thermal comfort under natural ventilation environment Jie Han a, Wei Yang a, Jin Zhou a, Guoqiang Zhang a, *, Quan Zhang a, Demetrios J. Moschandreas b a Key Lab of Building Safety and Energy Efficiency, Ministry of Education, China, College of Civil Engineering, Hunan University, Changsha , China b Department of Civil, Architectural and Environmental Engineering, Illinois Institute of Technology, Chicago, IL, USA ARTICLE INFO ABSTRACT Article history: Received 25 May 2008 Received in revised form 30 July 2008 Accepted 2 August 2008 Keywords: Comparative analysis Urban thermal comfort Rural thermal comfort Thermal sensation The paper presents a field study of occupants thermal comfort and residential thermal environment conducted in an urban and a rural area in Hunan province, which is located in central southern China. The study was performed during the cold winter Twenty-eight naturally ventilated urban residences and 30 also naturally ventilated rural residences were investigated. A comparative analysis was performed on results from urban and rural residences. The mean thermal sensation vote of rural residences is approximately 0.4 higher than that of urban residences at the same operative temperature. Thermal sensation votes calculated by Fanger s PMV model did not agree with these obtained directly from the questionnaire data. The neutral operative temperature of urban and rural residences is 14.0 and C, respectively. Percentage of acceptable votes of rural occupants is higher than that of urban occupants at the same operative temperature. It suggests that rural occupants may have higher cold tolerance than urban occupants for their physiological acclimatization, or have relative lower thermal expectation than urban occupants because of few air-conditioners used in the rural area. The research will be instrumental to researchers to formulate thermal standards for naturally ventilated buildings in rural areas. ß 2008 Elsevier B.V. All rights reserved. 1. Introduction In recent years, many researchers studied residential thermal environment and occupant comfort in urban residences of different climatic zones [1 7]. Specifically, in China, such field studies have been conducted in large cities, such as Beijing, Harbin, Shanghai, Changsha, Xi an, Hong Kong, Guangzhou and Shenzhen [8 15]. However, China is a developing country, the majority of Chinese live in rural areas rather than in urban areas. In order to improve people s living conditions in rural areas, the Chinese government is now promoting new rural constructions all over the country. This study seeks responses to the following questions: what is the difference of occupants thermal comfort between urban and rural residences, and should we provide the same residential thermal environment for rural and urban residences? It is well known that the lifestyle and economic status of individuals in rural areas are different from those in urban areas in China. For example, air-conditioning in rural areas is less popular than in urban areas, which leads to occupants * Corresponding author. Tel.: ; fax: address: gqzhang@188.com (G. Zhang). living in rural areas to expect less thermal comfort than those living in urban areas. Fanger and Toftum [16] have introduced an expectancy factor to explain the difference between non-airconditioned buildings in regions where the weather is warm only during the summer where there are none or few buildings with air-conditioning and regions with same or similar environmental conditions but widespread use of air-conditioning. The expectancy factor is with few air-conditioned buildings and where there are many air-conditioned buildings. Moreover, thermal adaptive theory indicates that behavioral adjustment, past thermal history and expectation influence occupants thermal comfort [17]. It is evident that there are many differences between urban and rural occupants comfort because of their different economic condition, lifestyle, context factors, physiological acclimatization and expectation. However, to the best of our knowledge, there is little information available concerning the occupant s comfort and residential thermal environment in the rural area. Thus, two purposes of this study were proposed, firstly this paper provides the information of occupant s thermal comfort and residential thermal environment in the rural area through field studies, secondly, a comparative and statistical analysis of urban and rural occupants thermal comfort was conducted, which will be assistant /$ see front matter ß 2008 Elsevier B.V. All rights reserved. doi: /j.enbuild

2 140 J. Han et al. / Energy and Buildings 41 (2009) to recommend the sustainable thermal standards for buildings in the rural area in China in the future. 2. Research methods 2.1. Building types, envelop characteristics and possible use of heating Changsha, which represents conditions of typical hot summer and cold winter zone of central southern China, is the capital of Hunan province. Changsha was selected as the urban area site for our study. Yuping, a village about 150 km away from Changsha, was selected as the rural area site. The outdoor meteorological conditions of the two areas are very similar: cold winters and hot summers. The surveys were performed in both Changsha and Yuping in the cold winter of There are two common types of buildings in the rural area: earth and brick-masonry buildings. The envelopes of earth buildings are rammed earth walls made of yellow earth and sand. The envelopes of brick-masonry buildings are cavity walls made of brick and cement mortar. Reinforced-concrete buildings are usually in the urban area. The envelopes of reinforced-concrete buildings are filled wall which are made of aerated concrete block or hollow brick. During the winter months, occupants of naturally ventilated buildings without heating and cooling systems warm themselves using basins in which charcoal is burnt, while urban occupants warm themselves using electric heaters. In summer, the majority of rural and urban occupants make use of oscillating fans for cooling occupied areas of naturally ventilated buildings. All residences both in the rural and the urban areas were investigated by this study without installing central HVAC systems or any mechanical ventilated systems. The size of rural residences is usually larger than urban residences Subjects A sample size of 103 subjects in 58 different residences of the urban and rural areas participated in the study, occupants of 28 residences in urban Changsha and 30 in rural Yuping responded to the winter surveys. The subjects participating in the survey were composed of 51 females (49.5%) and 52 males (50.5%). The average age of all respondents is 37.5 years old, ranging from 10 to 70. The questionnaire covered several areas including demographics (sex, gender, height, weight, age, etc.), years of living in their current places, economic condition, educational level and measures for improving residential thermal environment and advancing occupants thermal comfort level. The questionnaire also includes the traditional scales of thermal sensation and thermal preference, current clothing garment and metabolic activity checklists. The thermal sensation scale was the ASHRAE seven-point scale of warmth ranging from cold ( 3) to hot (+3) with neutral (0) in the middle. The thermal preference scale is a three-point scale with the following options: (1) want warmer, (2) no change and (3) want cooler. Intrinsic clothing insulations were estimated using the garment values published in ISO Metabolic rates were assessed by a checklist of residential activities databases published in ASHRAE Standard Summary of the background characteristic of the subjects are represented in Table 1. Table 1 Summary of the subjects of residential occupants and personal thermal variables Place Urban area Rural area Sample size (male/female) 53 (21/32) 50 (31/19) Mean age (year) Mean, standard deviation 34.8, , 13.9 Minimum, maximum 10, 67 12, 70 Mean height (m) Mean, standard deviation 1.63, , 0.09 Minimum, maximum 1.35, , 1.76 Mean weight (kg) Mean, standard deviation 59.3, , 11.2 Minimum, maximum 32, 90 25, 76 Mean years living in local address Mean, standard deviation 7, , 19.6 Minimum, maximum 0.5, 50 3, 70 Mean metabolism (met) (58.2 W/m 2 = 1 met) Mean, standard deviation 1.25, , 0.5 Minimum, maximum 1, 2 1, 2 Mean clothing insulation Mean, standard deviation 2.0, , 0.46 Minimum, maximum 0.92, , 2.89 Swema 3000, multi-purpose test system for professional measurements in indoor climate, was utilized in this study. The multi-purpose Swema 3000 is ideal in a broad range of applications, including indoor climate, thermal comfort, airconditioning and ventilation. Moreover, Swema 3000 incorporates powerful built-in calculation and documentation features that vastly simplify field study. Three probes are equipped with Swema 3000, Swa03 probe measures air velocity and temperature with sensory accuracy of 0.3 m/s, 0.3 8C, respectively. Hygroclip S probe measures relative humidity (RH) and temperature with sensory accuracy of 1.6%, 0.3 8C, respectively. SWAT probe measures globe temperature with sensor accuracy of 0.3 8C. The test system is shown in Fig. 1. Three points were measured in a room along the diagonal. The field investigator measured thermal comfort variables (ambient air temperature, relative humidity, velocity and globe temperature) at the 0.1, 0.6 and 1.1 m heights while each respondent filled in the questionnaire. Operative temperature (T 0 ) was calculated as the average of air temperature and mean radiant temperature Measurement of indoor climate Fig. 1. Swema 3000 test system.

3 J. Han et al. / Energy and Buildings 41 (2009) Calculation of thermal comfort indices Following the same approach as that used by previous studies such as ASHRAE research project RP-884 [18], the environmental and comfort indices were calculated with the Fountain model of thermal sensation [19] and a thermal comfort index calculator available on online ( using data from the survey questionnaire responses and thermal variable measurements obtained by this field study were used as input data to the model and calculator tool. Chair insulation was not considered in the study for its minor influence in the winter. 3. Results and discussion 3.1. Outdoor and indoor climate environments During the investigation period, the mean daily maximum temperature for both the urban and rural areas was in the range of C. Meanwhile, the mean daily maximum relative humidity was in the range of %. Outdoor climatic variables (air temperature, relative humidity and air velocity) are measured by climatic station. Table 2 provides statistical summaries of the indoor measurements and comfort indices for the residences of the urban area and the rural areas in the 2006 winter season samples. Mean air and radiant temperature (averaged across the three heights of 0.1, 0.6, and 1.1 m) generally fell between 7 and 17 8C in urban residences and 6 and 11 8C in rural residences. Mean RH values were in the range of % urban residences and % in rural residences. The mean air velocity (average over the three heights) was 0.05 m/s in both places. Operative temperatures fell within the C range. The predicted mean vote (PMV) fell within 2.23 to 0.96 in urban residences and 1.78 to 0.74 in rural residences. The PMV value is increased by 0.17 and 0.46 for each degree increase of the operative temperature in the urban and rural residences, which were obtained from a linear regression. Mean predicted percentage of dissatisfied (PPD) fell in the range of % in urban residences and % in rural residences. Table 2 Statistical summary of indoor climatic and comfort indices Place Urban area Rural area Fig. 2. Cumulative frequency distribution of the indoor and ambient temperature in the rural area Cumulative frequency distribution of the indoor and ambient temperature Figs. 2 and 3 give the cumulative frequency distribution of the indoor and ambient temperature in the rural and urban areas, respectively. A comparative analysis of the cumulative frequency distribution of the indoor and ambient temperature in both areas was gained from the two figures. As Fig. 2 shows in rural residences, the indoor temperature of the 50th percentile value of the distribution is close to C, while for the ambient temperature it is C for a difference of one centigrade between the indoor and ambient temperatures. As Fig. 3 shows in urban residences, the indoor temperature of the 50th percentile value of the distribution is close to C, while for the ambient temperature it is C for approximately no difference in indoor and ambient temperatures at the 50th percentile value of the distribution. Mean air temperature (8C) Mean, standard deviation 12.1, , 1.22 Minimum, maximum 7.67, , Mean radiant temperature (8C) Mean, standard deviation 11.94, , 1.25 Minimum, maximum 7.2, , Mean operative temperature (8C) Mean, standard deviation 12, , 1.23 Minimum, maximum 7.43, , Mean relative humidity (%) Mean, standard deviation 62.59, , 4.34 Minimum, maximum 30.77, , Mean air velocity area (m/s) Mean, standard deviation 0.06, , 0.04 Minimum, maximum 0.02, , 0.17 Predicted mean vote (PMV) Mean, standard deviation 0.62, , 0.82 Minimum, maximum 2.23, , 0.74 Predicted percent of dissatisfied (PPD) (%) Mean, standard deviation 24.85, , 18.1 Minimum, maximum 5.2, , 66.2 Fig. 3. Cumulative frequency distribution of the indoor and ambient temperature in the urban area.

4 142 J. Han et al. / Energy and Buildings 41 (2009) Fig. 4. Frequency of thermal sensation vote Thermal comfort and the questionnaire Thermal sensation urban and rural residence The frequency distribution of thermal sensation votes of the urban and rural area is given in Fig. 4. The mean thermal sensation votes of urban and rural area, range from 1 (slightly cool) to 0 (neutral), are 77.3 and 80%, respectively; most of thermal sensation votes were equal to zero. Mean thermal sensation votes (MTSV) obtained directly from questionnaires and PMV calculated by Fanger PMV model [20] both the urban and rural areas have been plotted against operative temperature in Figs. 5 and 6, respectively. Fig. 5 shows the mean ASHRAE thermal sensation votes and PMV for each half-degree operative temperature bin in the urban residence. The regression line of MTSV fitted to the bin means was highly significant (Prob < , R 2 = 0.82) and a standard error on the regression coefficient was The fitted MTSV and PMV equations are: MTSV ¼ 0:21T 0 2:93 (1) PMV ¼ 0:17T 0 2:42 ðprob < 0:0001; R 2 ¼ 0:89Þ (2) The regression relationships indicate that MTSV does not agree with PMV. MTSV is higher than PMV when the operative temperature exceeded C. Whereas, MTSV is lower than PMV Fig. 6. MTSV and PMV of the rural residence. when the operative temperature under C. The linear slope of MTSV is higher than that of PMV. Fig. 6 shows the mean ASHRAE thermal sensation votes and PMV for each half-degree operative temperature bin in the rural residence. The regression line of MTSV fitted to the bin means was highly significant (Prob < , R 2 = 0.86) and standard error on the regression coefficient was The fitted MTSV and PMV equations are: MTSV ¼ 0:22T 0 2:53 (3) PMV ¼ 0:46T 0 4:16 ðprob < 0:0001; R 2 ¼ 0:94Þ (4) The figure indicates the linear slope of PMV is higher than that of MTSV. MTSV is higher than PMV when the operative temperature exceeded 6.8 8C. Whereas, MTSV is lower than PMV when the operative temperature over 6.8 8C Thermal preference urban and rural residence Thermal preference is assessed directly according to the answers of the question: at the present time, would you prefer to want warmer, no change or want cooler? The frequency distribution of thermal preference of the urban and rural residence is given in Fig. 7. Among the urban occupants 67.9 and 32.1% voted Fig. 5. MTSV and PMV of the urban residence. Fig. 7. Frequency of thermal preference.

5 J. Han et al. / Energy and Buildings 41 (2009) Fig. 8. Comparison of thermal acceptability between rural and urban residence. for want warmer and no change, respectively. Importantly, no respondent voted for want cooler. Among the rural occupants 62 and 36% voted for want warmer and no change. It shows that the percentage of the rural occupants voting no change is a little more than the percentage of the urban occupants Thermal acceptability urban and rural residences Thermal acceptability is a quite controversial aspect of thermal comfort because it can be defined with reference to different scales. Four acceptability ratings based on different scales are compared by Fato et al. [7]. Thermal acceptability for this paper is obtained directly from the occupants who answered acceptable to the questionnaire when asked whether their thermal conditions were acceptable or not. The percentage of actual unacceptable votes for each half-degree operative temperature bin was plotted as a function of the operative temperature. Fig. 8 shows the comparative results of thermal acceptability between the rural and urban residences. Results indicate that the percentage of unacceptable votes of urban residences is higher than the rural residence at the same operative temperature. The percentage of acceptable votes of rural occupants is higher than the urban occupants at the same operative temperature, which indicates the cold tolerance of the rural occupants is higher than the urban occupants. In addition, Fig. 10. Comparison of thermal sensation vote between the rural and urban residence. the frequency distribution of thermal acceptability of the urban and rural residence is given in Fig. 9. Urban occupant vote is 68 and 32% for acceptable and unacceptable, respectively. Rural occupants vote is 78 and 22% for acceptable and unacceptable, respectively Thermal sensation vote urban residence vs. rural residences MTSV for half-degree operative temperature bin in the urban and rural residence was obtained directly from the questionnaires according to ASHRAE seven-point scale. Fig. 10 compares mean thermal sensation vote between the urban and rural area. The figure indicates that the mean MTSV of the rural area is approximately 0.4 higher than that of the urban area at the same operative temperature. The neutrality is derived by solving Eqs. (1) and (3) for a mean sensation of zero and the neutral operative temperature for the urban and rural residences are 14.0 and C, respectively. The mean MTSV of the rural area is higher than that of the urban area at the same operative temperature, and the neutral operative temperature for rural residences is lower than that of urban residences. One possible reason is that the occupants in the rural area have stronger ability to tolerate cold than those in the urban area because of their physiological acclimatization or past thermal history. The other reason that expectations of the rural area occupants is lower than that of the urban area occupants considering their economic level. Statistical data from questionnaires shows that the occupants incomes of the rural area are far below that of the urban area, which leads to the following conclusion: occupants of the rural area have relative low expectation for their thermal comfort. This agrees with Fanger s study, who has introduced an expectancy factor in non-airconditioned buildings in warm climates [16] Relationship between MTSV and PMV Fig. 9. Frequency of thermal acceptability. MTSV for half-degree operative temperature bin in the urban and rural residences was obtained directly from the questionnaires. PMV for half-degree operative temperature bin in the urban and rural residence was calculated by Fanger s PMV model. The relationship between MTSV and PMV is given in Fig. 11. The linear regression line of MTSV and PMV was significant (Prob < , R 2 = 0.75) and standard error on the regression coefficient was

6 144 J. Han et al. / Energy and Buildings 41 (2009) Fig. 11. Relationship between MTSV and PMV The fitted equation was: MTSV ¼ 0:78PMV 0:11 ð 3 PMV 0Þ (5) An interesting phenomenon is observed from this equation. If PMV equals to 1, the MTSV is MTSV is higher than PMV, which implies that Fanger s PMV heat balance model with six key parameters does not describe exactly occupants thermal sensation under natural ventilated environment. Thermal adaptability such as context factors, expectations, behavioral adjustments and so on should be considered at the same time Personal environmental control and indoor air quality (IAQ) The availability and appropriate use of controls in a building allows occupants to modify the internal environment. In naturally ventilated buildings, control over indoor temperature and ventilation can be obtained by applying typical strategies/controls suchasopeningwindows,doors,ventilators,etc.however,for extreme conditions in winter, hibachis, air-conditioners or electric furnaces may be used to improve indoor thermal environment. The data of the study show that 94% of rural residence occupants make use of hibachi, and the rest use electric furnaces. However, only 18% occupants in the urban area use hibachis, while others use air-conditioners and electric furnaces. The different percent of improving thermal environmental methods indicates that the electric energy consumed by the urban area is much more than that by the rural area. Indoor air quality problems between the rural and urban residences are quite different. The indoor air pollution source in rural areas is fuel burning but indoor air pollution sources in urban areas include outdoor pollution from industrial sources and traffic and building and decoration materials. The main contaminants in urban areas are volatile organic compounds (VOCs), formaldehyde, benzene, etc. But the main pollutant in rural areas is particulate matter (PM), carbon dioxide (CO 2 ), carbonic oxide (CO), sulfur dioxide (SO 2 ) and so on, Wang et al. [21]. In the rural area, carbon dioxide (CO 2 ) concentrations of all rooms were lower than the national standard, but PM and SO 2 concentrations in many rooms are higher than the standard because of the pollutant source of charcoal basins Possible improvements of the housing thermal environment Because of increased use of air-conditioning consuming plenty of electric energy and creating a serious peak electricity load problem, people are seeking passive techniques to improve indoor thermal environment and occupants thermal comfort. Santamouris et al. [22] have summarized the recent progress on passing cooling technique in the residences of low-income households. As a rule, passive cooling techniques include: (1) improving urban microclimate techniques, (2) solar and heat protection techniques and (3) heat dissipation techniques. Improving urban microclimate techniques may involve increasing green spaces in urban environments, planting roof and wall for an ecologic way to improve the indoor thermal environment, and using reflective or cooling materials. Solar and heat protection may involve switchable glazing technology, using reflective coatings on the roofs, solar control and shading of building surface, thermal insulation, etc. Heat dissipation techniques include ground cooling system, natural ventilation techniques, hybrid ventilation systems, night ventilation, wind tower, using oscillating or ceiling fans, etc. In China, the commonly used passive techniques in the summer are increasing green area in the urban, planting roof and wall, thermal insulation, natural ventilation, oscillating or ceiling fans, etc. In winter, the commonly used passive techniques are wall insulations, using carbon basins and electric heaters, etc. In addition, airconditioners for cooling and heating are far more popular in the urban area than in the rural area Comparisons with previous thermal comfort studies under natural ventilated environment In this study, the neutral operative temperature for the urban residences is C in winter under natural ventilated environment, which is 6.8 8C lower than that of the city of Ilam in western Iran [6] and 6.7 8C lower than that of Bari in southern Italy [7] in natural ventilated buildings during the winter season. The difference may be contributed to clothing insulation. The mean clothing insulation in this study is 2.0 clo, which is higher than that of Iran (1.5 clo) and Italy (0.88 clo). Thermal experience may be another reason. The indoor mean operative temperature in this study is 12 8C, which is lower than that of Iran (21.9 8C) and Italy (28 8C). It indicates that people who used to experience lower temperature environment will have lower neutral temperature, which is in accordance with thermal adaptive theory. The linear regression coefficient of MTSV in half-degree operative temperature is 0.22, which is similar to that of Italy (0.28). 4. Conclusions This study investigates thermal environment and comfort of residences between the urban and rural area in Hunan province, which is located in central southern China. A total of 103 occupants from 53 residences from the urban area of Changsha and the rural area of Yuping in Hunan province of China provided thermal perception data in the cold winter in Occupant thermal sensation responses in houses of the urban area are different from those in residences of the rural area. Mean thermal sensation vote of the rural area is 0.4 higher than that of the urban area at the same operative temperature. Moreover, the percentage of acceptable votes of rural occupants is higher than the urban occupants. The difference is attributed to the occupants of the rural area having relative lower expectation than the occupants of the urban area. The other possible reason is that the occupants of the rural area have stronger ability to tolerate cold than the occupants of the urban area because of their physiological acclimatization or past thermal history. Low expectation and ability to tolerate cold temperatures by the rural subjects may explain the observed differences. The mean PMV calculated by

7 J. Han et al. / Energy and Buildings 41 (2009) Fanger s model is higher than the MTSV obtained from the questionnaire data. The difference is attributed to the different combination of the objective and subjective conditions that have not been considered in Fanger s model. The comparative results of this field survey can be helpful to recommend the sustainable thermal standards for buildings of the rural area in the future for central southern China. Acknowledgements The authors would like to thank Ms. Ping Wang, Wen Lin and Mr. Peng Zhang for assisting field experiments. The work of this paper is financially supported by the Natural Science Foundation of China (No ) and the 11th Five Year National Science and Technology Support Key Project of China (Nos. 2006BAJ02A05, 2006BAJ04B04) References [1] J.F. Bush, A tale of two populations: thermal comfort in air-conditioned and naturally ventilated offices in Thailand, Energy and Buildings 18 (1992) [2] R.J. De dear, M.E. Fountain, Field experiments on occupant comfort and office thermal environments in a hot-humid climate, ASHRAE Transactions 100 (2) (1994) [3] R.J. De dear, A global database of thermal comfort field experiments, ASHRAE Transactions 104 (1b) (1998) [4] J.F. Nicol, I.A. Raja, A. Allaudim, G.N. Jamy, Climatic variations in comfortable temperatures: the Pakistan projects, Energy and Buildings 30 (1999) [5] M.A. Ealiwa, A.H. Taki, A.T. Howarth, M.R. Seden, An investigation into thermal comfort in the summer season of Ghadames, Libya, Building and Environment 36 (2001) [6] S. Heidari, S. Sharples, A comparative analysis of short-term and long-term thermal comfort surveys in Iran, Energy and Buildings 34 (2002) [7] I. Fato, F. Martellotta, C. Chiancarella, Thermal comfort in the climatic conditions of southern Italy, ASHRAE Transactions 110 (2) (2004) [8] Y.Z. Xia, R.Y. Zhao, Y. Jiang, Thermal comfort in naturally ventilated houses in Beijing, HV&AC 29 (2) (1999) 1 5 (in Chinese). [9] Z.J. Wang, G. Wang, L.M. Lian, A field study of the thermal environment in residential buildings in Harbin, ASHRAE Transactions 109 (2) (2003) [10] X.J. Ye, Z.P. Zhou, Z.W. Lian, et al., Field study of a thermal environment and adaptive model in Shanghai, Indoor Air 16 (2006) [11] J. Han, G. Zhang, Q. Zhang, et al., Field study on occupant s thermal comfort and residential thermal environment in a hot-humid climate of China, Building and Environment 42 (2007) [12] H. Yoshino, S. Guan, Y.F. Lun, et al., Indoor thermal environment of urban residential buildings in China: winter investigation in five major cities, Energy and Buildings 36 (2004) [13] H. Yoshino, Q. Zhang, A. Mochida, et al., Indoor thermal environment and energy saving for urban residential buildings in China, Energy and Buildings 38 (2006) [14] G. Zhang, C. Zheng, W. Yang, et al., Thermal comfort investigation of naturally ventilated classrooms in a subtropical region, Indoor and Built Environment 16 (2) (2007) [15] W. Yang, G. Zhang, Thermal comfort in naturally ventilated and air-conditioned buildings in humid subtropical climate zone in China, International Journal of Biometeorology 52 (2008) [16] P.O. Fanger, J. Toftum, Extension of the PMV model to non-air-conditioned buildings in warm climates, Energy and Buildings 34 (2002) [17] G.S. Brager, R.J. De dear, Thermal adaptation in the built environment: a literature review, Energy and Buildings 27 (1998) [18] R.J. De dear, G.S. Brager, Developing an adaptive model of thermal comfort and preference, ASHRAE Transactions 104 (1998) [19] M.E. Fountain, C. Huizenga, A thermal comfort prediction tool, ASHRAE Journal 38 (9) (1996) [20] P.O. Fanger, Thermal Comfort: Analysis and Applications in Environmental Engineering, McGraw-Hill Inc., New York, [21] K. Wang, Q. Zhang, G.Q. Zhang, et al., Airflow and indoor air quality of residence heating by charcoal basin in rural region, Journal of Central South University of Technology 14 (2007) [22] M. Santamouris, K. Pavlou, A. Synnefa, K. Niachou, D. Kolokotsa, Recent progress on passive cooling techniques: advanced technological developments to improve survivability levels in low-income households, Energy and Buildings 39 (2007)