INDOOR ENVIRONMENTAL QUALITY IN CHILEAN CLASSROOM by MARIA ISABEL RIVERA A DISSERTATION Presented to the Department Architecture and the Graduate School of the University of Oregon in partial fulfillment of the requirements for the degree of Doctor of Philosophy September 2019 DISSERTATION APPROVAL PAGE Student: María Isabel Rivera Title: Indoor Environmental Quality in Chilean Classroom This dissertation has been accepted and approved in partial fulfillment of the requirements for the Doctor of Philosophy degree in the Department of Architecture by: Alison Kwok Chairperson Kevin Van Den Wymelenberg Core Member Charles Martinez Core Member Alexandra Rempel Institutional Representative and Janet Woodruff-Borden Vice Provost and Dean of the Graduate School Original approval signatures are on file with the University of Oregon Graduate School. Degree awarded September 2019 ii © 2019 María Isabel Rivera iii DISSERTATION ABSTRACT María Isabel Rivera Doctor of Philosophy Department of Architecture September 2019 Title: Indoor Environmental Quality in Chilean Classrom Recently, there has been a growing concern about poor thermal comfort and air quality conditions that can have a negative effect on children’s health and academic performance. Research in the U.S. and Europe has shown high classroom indoor temperatures and CO2 concentrations, and low ventilation rates. Little is known about classroom conditions in developing countries like Chile, where there is no adherence to environmental standards. Additionally, there is limited knowledge about students’ and teachers’ perceptions of environmental conditions in primary schools. Furthermore, studies have shown that current thermal comfort standards criteria might not be applicable to children. This thesis aims to advance our understanding of students’ and teachers’ perceptions of thermal comfort and indoor air quality in primary school settings. Moreover, this dissertation intends to identify other factors that may influence thermal and air quality comfort. The research questions are: 1) What are the physical conditions of classrooms in Chilean primary schools?; 2) What is the relationship between physical conditions of classrooms among the three types of schools (public, private–subsidized, and private non– subsidized) commonly found in Chile?; 3) Do expectations of thermal comfort and air quality differ between students and teachers?; and 4) Do subjective perceptions of iv classroom environmental qualities differ between the types of schools that represent different social/economic backgrounds? Two field studies were conducted in nine free-running classrooms in the city of Concepción, Southern Chile. Various methods were implemented to collect data, based on previous studies on children: survey questionnaires, physical measurements, interviews, behavioral observations, and statistical analysis. Approximately 880 students, aged 10-14 years old, and 80 teachers were surveyed twice a day in the fall and winter season of 2018. Overall, the results show that students and teachers were comfortable, despite low indoor temperatures and poor air quality conditions, outside the comfort zone limits of the ASHRAE–55 standard adaptive model. Analyses from subjective responses reveal 80% of comfort acceptability, thanks to personal adaptations. A statistically significant difference (p<0.001) in students’ thermal perception was found between private-subsidized and public schools, and between private-subsidized and private-nonsubsidized schools. This dissertation includes previously published and unpublished co-authored material. v CURRICULUM VITAE NAME OF AUTHOR: María Isabel Rivera GRADUATE AND UNDERGRADUATE SCHOOLS ATTENDED: University of Oregon, Eugene, United States University of Washington, Seattle, United States Universidad de Concepción, Concepción, Chile DEGREES AWARDED: Doctor of Philosophy, Architecture, 2019, University of Oregon Master of Architecture, 2009, University of Washington Professional Degree of Architect (Título), 2006, Universidad de Concepción Bachelor of Architecture, 2004, Universidad de Concepción AREAS OF SPECIAL INTEREST: Sustainable Architecture and passive design Indoor environment quality and effects on comfort, well-being and health Energy effeciency in Buildings Low carbon and low embodied energy materials in buildings Pedagogy in Architecture PROFESSIONAL EXPERIENCE: Graduate Research Assistant, Cross Laminated Timber Research NetZED Lab, Department of Architecture, Eugene, Oregon, United States, 2018-2019 Conference Coordinator, Reynolds Symposium: Education by Desing, Department of Architecture, Eugene, Oregon, United States, 2018-2019 Graduate Teaching and Research fellow, Department of Architecture, Eugene, Oregon, United States, 2015-2016 Assistant Professor, Department of Architecture, Universidad de Concepción, Concepción, Chile, since 2012 Adjunct Professor, Department of Architecture, Universidad de Concepción, Chile, 2010–2012 Principal, María Isabel Rivera Architect, Concepción, Chile, since 2006 vi GRANTS, AWARDS, AND HONORS: Architectural Research Centers Consortium (ARCC) King Student Medal for Excellence in Architectural and Environmental Design Research, University of Oregon, 2019 Anthony Wong Scholarship for Research in Sustainable Design, University of Oregon, 2019, 2017 Student Retreat Scholarship, Society of Building Science Educators (SBSE), 2017, 2016 SBSE Jeffrey Cook Student Scholarship, for PLEA Conference, 2017 SBSE Student Scholarship, for PLEA Conference, 2016 Becas Chile – scholarship for doctoral degree outside Chile, CONICYT, 2016–2019 Beca Universidad de Concepción – scholarship for doctoral degree , 2015–2019 Presidential scholarship for Master degree outside Chile – CONICYT, 2007–2009 Augusto Iglesias Barrios, best graduate architect from the class of 2006 PUBLICATIONS: Schweiker, M., Abdul-Zahra, A., Afonso de André, M., Al-Atrash, F., Al-Khatri, R., Kwok, A., …Rivera, M.I. (2019). The Scales Project: a cross-national dataset on the interpretation of thermal perception scales.. Occupant Behaviour in Buildings. Scientific Data. In press. DOI 10.17605/OSF.IO/9P2GQ Rivera, M.I., and Kwok, A. (2019). Thermal Comfort and Air Quality in Chilean Schools, Perceptions of Student and Teachers. Proceedings from the ARCC Spring Research Conference, Toronto, Canada, May 29–June 1, 2019. Retrieved from https://www.arcc- repository.org/index.php/repository/article/view/632 Kwok, A., Tjahjana, N., & Rivera, M.I. (2017). Campus Audit Squads for Energy (CASE): understanding behavioural patterns and energy use of plug loads. Proceedings from PLEA Conference, Edinburgh, Scotland, July 2–5, Vol. I. Building Performance Evaluation (pp. 756–763) Retrieved from https://plea2017.net/ Delpino, M., and Rivera, M.I. (2017). Architectural Design Studio as a tool to promote University Social Responsibility (USR) in the improvement of urban environments. Proceedings from PLEA Conference, Edinburgh, Scotland, July 2–5. Vol. II. Education and Training (pp. 2259–2266). Retrieved from https://plea2017.net/ vii Elzeyadi, I., Abboushi, B., Hadipour, H., and Rivera, M.I. (2016). High– Performance Facades: Measuring the Impacts of Dynamic Shading Prototypes on Indoor Environmental Quality Using Yearly Simulations and Field Test. Proceedings from PLEA Conference, Los Angeles, California, United States, July 11–13. Vol. II. Strategies, tools, and simulation methods (pp. 1004–1013). Agurto, L., Espinosa, P., Rivera, M.I., & Merino, L. (2015). Develop of a set of criteria and sustainability indicators as a digital tool to assist the design at neighborhood scale on the Chilean context. Proceedings from Organized by the Center and Faculty of Environmental Science, University of Concepción, Chile, March. Delpino, M., Rivera, M.I. (2013). Sustainable Construction: Recycle, reinterpret, rehabilitate as an exploration and experience in architectural and urban improvement. Proceedings from 5th International Congress of Architecture and Environment, University of Concepción, Chile, November. Rivera, M.I. (2010). Chaitén Rebuilding from the Ashes: Sustainable Housing Prototype for an eco-village in southern Chile. International Symposium: Sustainability and City Development, La Serena, Chile, October 2009. Cuadernos de Investigación Urbanística, 0(70). Retrieved from http://polired.upm.es/index.php/ciur/article/view/1180 viii ACKNOWLEDGMENTS I wish to express my sincere appreciation to my dissertation committee composed by Professors Alison Kwok, Alexandra Rempel, Kevin Van Den Wymelenberg, and Charles Martinez for the precious time, assistance, feedback, knowledge, and encouragement in the preparation of this manuscript. Additionally, I would like to thank Professor Lauren Lindstrom, for her guidance and feedback provided in the exam questions and early stages of my research. Professor Alison Kwok has been my trusted advisor and mentor throughout these four years. I have learned immensely from her, particularly how to spark in students their thirst for sustainable design, passive architecture, and building science. She has inspired and encouraged me to actively participate in promoting healthy sustainable design, getting to know great educators and experts in this field. I feel very fortunate that our paths did cross, and I would not be where I am today without her help, guidance, and support. This research would have not been possible without the assistance of the Department of Education and Infrastructure of Municipalities of Concepción and San Pedro de la Paz, particularly architects and colleagues Javier Canales, Francisco Brito, Felipe Perez, and Angeline Arriata. Additionally, I thank all the students and teachers involved in this study for their patience, time, and generosity. I would also like to thank all the administration staff of the different schools who allowed me access to the different classrooms, provided feedback, and helped immensely in my fieldwork, in particular: Roberto Riquelme, Jose Vilche, Dory Zepeda , Leyla Acevedo, Flavia Molina, Gastón Torres, Maria Lourdes Alid, María Graciela Escárate, Gonzalo Sepúlveda, Susana Cabrera, Juan Pablo Duran, José Quezada, Gabriel Beguiristian, Domingo Seguel, and Víctor Viveros. My heartfelt appreciation to my students, Fresdly Lizama, Ignacio Galindo, and Sebastian Galindo, who assisted me during my fieldwork and gave me their commitment, patience and great learning moments. And also to my friend and teacher, ix Pamela Toledo, for her time, encouragement, and support that was instrumental during surveys and follow-up interviews. I am indebted to Universidad de Concepción for its financial support through the Universidad de Concepción scholarship, and to my current Dean, Leonel Perez, and former Dean Bernardo Suazo who encouraged me to pursue my Ph.D. My Ph.D. studies could have not been possible without the financial support from the Department of Architecture of the University of Oregon, during my first year, and from the National Commission for Scientific and Technological Research (CONICYT) through the Becas Chile–scholarship, during the next three consecutive years. Additionally, I very much appreciate the support from the Anthony Wong Scholarship for Research in Sustainable Design, the Ph.D. Architecture Fund, and the Society of Building Science Educators (SBSE) through their Student Retreat and Conference Scholarships, and the Jeffrey Cook Student Travel Scholarship. I am very grateful to my great friend and colleague Lyndsey Deaton, for her constant support, advise, and therapeutic talks during the Ph.D. program. Thank you for making this process memorable! Last but not least, my infinite gratitude to my extended family and friends, who have supported me from the beginning. To my family editors, Cathi, Paul, Doug, and Ricardo, for all those extra-long hours you help me “translate” and proofread my ideas. To my parents, for their prayers and encouragement that helped me to persevere. To Ricardo, for this crazy four-year journey we did together, your support, patience, knowledge, and generosity. This has been inspiring and kept me going throughout a successful achievement. I am forever grateful. Gracias totales! x To all the childrens in Chile and in the rest of world, who deserve better learning environments. xi TABLE OF CONTENTS Chapter Page I. INTRODUCTION ..................................................................................................... 17 Research Problem ....................................................................................... 20 Research Objectives ................................................................................... 21 Research Questions .................................................................................... 21 Approach ................................................................................................... 22 Significance ................................................................................................ 24 Scope & Limitations ................................................................................... 26 Organization of the Dissertation ................................................................. 28 II. BACKGROUND ....................................................................................................... 30 Indoor Environment .................................................................................... 30 Defining the Meaning of Thermal Comfort and Indoor Air Quality ............. 32 Thermal Comfort and Indoor Air Quality Parameters .................................. 36 Research on Thermal Comfort .................................................................... 38 Models of Thermal Comfort ........................................................................ 40 International Standards for Thermal Comfort .............................................. 50 Approaches in IAQ Assessment .................................................................. 60 International Standards and Guidelines for Indoor Air Quality .................... 61 Chapter Summary ....................................................................................... 66 III. LITERATURE REVIEW ............................................................................................... 67 Thermal Comfort Studies in Schools ........................................................... 68 Indoor Air Quality Studies in Schools ......................................................... 78 IEQ Effects on Students’ Health and Performance ....................................... 82 Thermal Comfort and IAQ Field Studies in Primary Schools in Chile .......... 88 Chapter Summary ....................................................................................... 93 IV. RESULTS: THERMAL COMFORT AND AIR QUALITY IN CHILEAN SCHOOLS, PERCEPTIONS OF STUDENTS AND TEACHERS ...................................................... 98 Introduction ............................................................................................... 98 Methodology ............................................................................................ 100 Data Collection ........................................................................................ 103 Results ...................................................................................................... 106 Conclusions ............................................................................................. 111 V. RESULTS: INFLUENCE OF SOCIAL BACKGROUND AND CLASSROOM CONDITIONS ON PERCEPTIONS OF INDOOR AIR QUALITY IN CHILEAN SCHOOLS .............................................................................................................. 115 Introduction ............................................................................................. 115 Methodology ............................................................................................ 119 Results ...................................................................................................... 135 Discussion ................................................................................................ 154 Conclusions ............................................................................................. 157 xii Chapter Page VI. CONCLUSIONS ..................................................................................................... 159 Future Work ............................................................................................. 166 APPENDICES ................................................................................................................. 168 A. INSULATION CALCULATIONS ..................................................................... 168 B. INSULATION CALCULATIONS ..................................................................... 169 C. INSULATION CALCULATIONS ..................................................................... 170 D. INDOOR AIR QUALITY PROFILE MEASUREMENT ....................................... 171 E. INDOOR AIR QUALITY PROFILE MEASUREMENT ........................................ 172 F. IRB APPROVALS ............................................................................................ 173 G. IRB APPROVALS ........................................................................................... 176 H. QUESTIONNAIRE ......................................................................................... 178 REFERENCES CITED ....................................................................................................... 186 xiii LIST OF FIGURES Figure Page Figure 2.1: Comparison between the adaptive model and the “static” model ................... 48 Figure 2.2 Adaptive comfort zone chart. .......................................................................... 53 Figure 2.3. Acceptable limits of operative temperature ranges for free-running, naturally conditioned spaces. ......................................................................................................... 56 Figure 2.4 Correlation between indoor CO2 concentration levels and ventilation rates in naturally and mechanically ventilated classrooms ............................................................ 62 Figure 3.1 Comparative graph of the percentage of number of studies of different thermal comfort approaches in different educational stages. ............................................ 70 Figure 4.1. ASHRAE 55–2017 adaptive comfort zone for naturally ventilated spaces fall and winter season. ......................................................................................................... 108 Figure 4.2. Student thermal sensation vote in fall and winter .......................................... 109 Figure 4.3. Teacher thermal sensation vote in fall and winter. ........................................ 110 Figure 4.4. Comparison of students thermal sensation votes (TSVs). ............................... 112 Figure 4.5. Comparison of teachers thermal sensation votes (TSVs). ............................... 113 Figure 5.1. Map of Chile ................................................................................................ 122 Figure 5.2. Concepción weather. ................................................................................... 123 Figure 5.3. Case study of school classrooms surveyed .................................................... 127 Figure 5.4. Indoor climate measurement equipment.. ..................................................... 129 Figure 5.5. Fieldwork set-up ........................................................................................... 132 Figure 5.6. Indoor operative and prevailing mean outdoor temperatures for fall and winter in all classrooms.. ............................................................................................... 140 Figure 5.7. ASHRAE–55 psychrometric chart with comfort zone for 1 Clo and 0.50 Clo. ........................................................................................................................ 141 Figure 5.8 School uniforms across different types of schools. ......................................... 142 xiv Figure Page Figure 5.9. Distribution of thermal sensation votes for all students and teachers across all schools.. ......................................................................................................... 144 Figure 5.10. Thermal Sensation Votes of students and teacher per school type during fall season.. .................................................................................................................... 146 Figure 5.11. Student thermal sensation across different classrooms and in all public schools during fall surveys. ............................................................................................ 147 Figure 5.12. Cross-tabulation between thermal sensation (ASHRAE) and thermal preference votes of students in fall season. ..................................................................... 149 Figure 5.13. Distribution of Air Quality Perception Votes for students and teachers in the fall season.. .......................................................................................................... 152 Figure 5.14. Crosstabulation of the relationship between Air quality sensation vote (AQV) and Air Movement Preference Vote (AMP) for students during fall surveys.. ........ 153 xv LIST OF TABLES Table Page Table 2.1. ASHRAE thermal sensation scale (ASHRAE55, 2017) ....................................... 42 Table 2.2. Thermal comfort standards in applicable to classroom spaces ......................... 51 Table 2.3 Recommended categories and their associated acceptable temperature ranges for mechanically conditioned (PMV-PPD) and free-running buildings, based on ISO 7730 (2005) .............................................................................................................. 57 Table 2.4 WHO guidelines of maximum acceptable levels of indoor pollutants ............... 63 Table 2.5 Summary of international air quality standards and guidelines for PM 2.5, ......... 65 Table 4.1 Summary of classroom visits, building details, sample size, and number of surveys for different seasons ........................................................................................... 108 Table 5.1 Summary of participating schools, surveys, and subjects ................................ 126 Table 5.2. Summary of questionnaire items, scales and numerical coding used in the analysis .......................................................................................................................... 134 Table 5.3 Fieldwork physical measurements for fall ....................................................... 136 Table 5.4 Fieldwork physical measurements for winter .................................................. 137 Table 5.5. Mean values of outdoor and indoor temperature and thermal sensation vote of students in each school in fall season ......................................................................... 138 Table 5.6. Mean values of outdoor and indoor temperature and thermal sensation vote of students in each school in winter season .................................................................... 139 Table 5.7 Cross-tabulation between thermal sensation (ASHRAE) and thermal preference ...................................................................................................................... 149 Table 5.8. Cross-tabulation between thermal sensation (ASHRAE) and thermal preference ...................................................................................................................... 150 Table 5.9. Cross-tabulation of number of votes and their percentages between air quality sensation and air movement preference .............................................................. 153 Table 5.10 Pearson correlation matrix, between physical measurements and subjective perceptions, with their significance ................................................................................ 155 xvi CHAPTER I: INTRODUCTION School learning environments are one of the most critical spaces where different aspects of sustainability research can be integrated, such as: indoor environmental quality, energy efficiency, performance, behavior, health, and well-being, and the effects it can have on occupants when these are poorly integrated or not considered at all in the design. Additionally, it is widely acknowledged that children spend a significant amount of time indoors, 80–90% between home and school (Klepeis et al., 2001), during their developmental years, from early childhood to adolescence. In virtually no other setting do people spend extended periods in such close quarters; the average school has an occupant density that can be somewhere between those of prisons and commercial planes (Frumkin, 2006). Learning activities demand high levels of concentration, since students learn new topics and advance in their thinking skills; therefore, classroom design characteristics should provide a stimulating environment that promotes the learning process (De Giuli, Da Pos, & De Carli, 2012; Mishra & Ramgopal, 2013; Turunen et al., 2014). Studies have shown that high classroom indoor temperatures, (de Dear et al., 2013; Mendell & Heath, 2005; Wargocki & Wyon, 2007, 2013a) high CO2 concentration levels, and low ventilation rates (Bakó-Biró, Clements-Croome, Kochhar, Awbi, Williams, 2012; Cui, Cao, Park, Ouyang, & Zhu, 2013a; Haverinen-Shaughnessy & Shaughnessy, 2015; Mendell et al., 2013) can have a negative impact on student performance and well-being. This is of particular concern in developing countries, such as Chile, where unfavorable 17 environmental conditions (i.e., high CO2 concentrations, high and low temperatures, and high RH) have been identified in schools (Soto, Trebilcock, & Pérez, 2015), and where there is no adherence to indoor environmental quality standards, or ordinances that can regulate minimum requirements. Closer attention to the indoor environmental quality (hereafter IEQ) conditions needs to be considered in order to promote health and performance enhancements. As noted by Mendell & Heath (2005), young children are more susceptible to environmental pollutants than adults, because their developing lungs breathe more than twice the air compared to their bodies. Currently, many cities in the south of Chile, including Concepción city, have been declared saturated zones since 2015 for fine particles PM2.5 (Ministerio del Medio Ambiente de Chile (MMA), 2015), due to high air pollution from wood-burning heating systems typical of this region. These high concentrations are a concern because of the health impacts they can have on children in short- and long-term exposure. Additionally, looking at the building stock of current school design in Chile, the majority are free-running buildings (i.e., without heating or ventilation systems). Operable windows or doors are the only means of ventilation for providing fresh air in classrooms. Closer attention needs to be paid to the existing indoor climate of classrooms and its relationship to outdoor air pollutants, to promote comfort and well- being that support academic performance and user satisfaction. Providing thermal comfort for occupants in a given environment not only depends on physical conditions but also on the interaction of physiological, psychological, emotional, cultural, and social factors of people (Fabbri, 2013, 2015). Current standards 18 such as: ASHRAE–55 (2017); EN15251 (2007); ISO 10551 (1995); ISO 7726 (2001); and ISO 7730 (2005), define acceptable ranges of operative temperature based on heat balance and the adaptive thermal comfort models, from studies done in climate chambers simulating office environments with adult occupants only. Due to the absence of standards that deal specifically with indoor environmental quality in educational buildings and classroom spaces at different grade levels, architects and engineers must use current standards. Recent studies have shown that children’s perceptions and thermal preferences might differ from those of adults, because of physiological characteristics, and also because of the physical activities that children do in school buildings being different from sedentary ones in office settings (e.g., playground time, classroom presentations, and PE classes) (Mendell & Heath, 2005; Mors, Hensen, Loomans, & Boerstra, 2011; Zomorodian, Tahsildoost, & Hafezi, 2016b). Limited studies (Kwok, 1997) exist in which the perspectives of children and teachers regarding their perception of their indoor environment are combined in a single study. Understanding how their perceptions differ or compare can help our understanding of how to provide comfortable spaces for all of them. Additionally, some studies (Montazami, Gaterell, Nicol, Lumley, & Thoua, 2017b; Trebilcock, Soto-Muñoz, Yañez, & Figueroa-San Martin, 2017a) suggest that children's perceptions and preferences of thermal comfort might be influenced by other factors such as different social backgrounds. In adaptive thermal comfort theory, Brager and de Dear (de Dear & Brager, 1998) argue that, “occupants are deemed as active agents in creating ideal indoor thermal 19 conditions” (as cited in Kim and de Dear 2018) through adaptive strategies such as opening windows. In classrooms, however, school children have no control over windows, unless directed by a teacher. Studies have shown (De Giuli et al., 2012; Kim & de Dear, 2018b) that students in primary schools are less outspoken in expressing their desire to modify classroom environment to their teacher than older students in secondary schools. Additionally, school dress code policies, like the ones in Chilean schools, require students to wear school uniforms, limiting the opportunities to modify clothing during the day or to wear other clothing items that are not part of the uniform (Shamila Haddad, Osmond, & King, 2019). Therefore, more research is required in school buildings, particularly in the primary classroom level, to understand what adaptations are permissible between students and teachers in these settings. 1.1. Research Problem The research gap this work address is understanding the degree to which school children and teachers can practice personal adaptive behaviors and how they interact with available opportunities to control their classroom environments is essential to understand the perceptions and expectations towards thermal comfort and indoor air quality acceptable to them. Additionally, we investigate how cultural and socio-economic background can play a role in a student's thermal comfort perceptions. Limited research has been conducted in this area (Montazami et al., 2017b; Trebilcock et al., 2017a), however both studies suggest that a strong relationship might exist between the socio- economic background of children and their thermal perceptions of classroom temperatures and home conditions. Children coming from more vulnerable backgrounds were more comfortable at lower temperatures than those considered less vulnerable (Trebilcock et al., 20 2017a). However, the study by Trebilcock et al. (2017a), only looks at public schools, and its scope is limited. 1.2. Research Objectives Overall, this dissertation aims to advance our understanding of students’ and teachers’ perceptions of and sensations towards thermal comfort and indoor air quality in primary school settings. Moreover, this dissertation intends to identify other factors that may influence thermal and air quality comfort conditions in primary schools. Therefore, there are four objectives this study will address: • To characterize the physical conditions of thermal and air quality (e.g. air temperature, relative humidity, air velocity, radiant temperature, CO2 and particulate matter PM2.5, PM10) of school classrooms during different seasons, and compare them with thresholds from existing international standards and guidelines; • To compare the thermal and air quality physical conditions between the three types of schools commonly found in Chile (public, private–subsidized, and private-nonsubsidized); • To evaluate thermal comfort and indoor air quality perceptions and sensations of students and teachers in naturally ventilated classrooms; • To evaluate whether perceptions of students of thermal and air quality comfort are related to their socio-economic background (the type of school, vulnerability index and home conditions). 1.3. Research Questions To achieve these aims, this dissertation expands from the previous body of research by including comfort perceptions and sensations of both students and teachers in naturally–ventilated primary schools in Southern Chile. This study looks at contextual factors such as socio-economic background (the type of school, vulnerability index, and 21 home conditions) that can influence the subject's perceptions of classroom environments. The primary research questions this dissertation asks are: 1. What are the physical conditions of classrooms in Chilean primary schools? 2. How do physical conditions compare to international standards, such as ASHRAE-55? 3. What is the relationship between physical conditions of classrooms and the three types of schools (public, private–subsidized, and private non–subsidized) commonly found in Chile? 4. Do expectations of thermal comfort and air quality differ between students and teachers? 5. Do subjective perceptions of classroom environmental qualities differ between the types of schools that represent different social/economic backgrounds? 1.3.1. Hypothesis or Hypotheses Three hypotheses inform this dissertation: 1. Primary school students perceive physical conditions of thermal comfort and air quality of their classrooms as unacceptable. 2. Classroom conditions would be unacceptable under international standards, such as ASHRAE-55 and EN15251. 3. There is a significant difference of students’ thermal sensation perceptions between public and private schools. In public schools, TSVs fall on the colder side of the ASHRAE-55 7-point scale as compared to private schools. 1.4. Approach This study focuses on a longitudinal survey approach consisting of real-time subjective responses with simultaneous physical measurements of thermal comfort and air quality in naturally–ventilated classrooms of nine primary school buildings, in the city of Concepcion, Chile. 22 Measurement protocols and data collection were based on ASHRAE-55-2017 Protocol I for thermal comfort and indoor air quality field studies which characterize the physical indoor environment while obtaining subjective responses. As it is evidenced in the literature review, field studies are more appropriate for observing and evaluating students’ responses to naturally–ventilated environments. Multiple approaches were implemented to collect and analyze data such as: physical measurements, survey questionnaires, interviews, observations, and statistical analysis commonly used in thermal comfort studies. However, this dissertation only reports on the results of quantitative data; (at this time, no qualitative analysis is presented from the results of teacher and student's interviews). General approaches • To characterize the physical conditions of thermal and air quality (e.g., air temperature, relative humidity, air velocity, radiant temperature, CO2 and particulate matter PM2.5, PM10) of school classrooms during two seasonal regimes: fall and winter season. • To compare measured physical conditions with comfort thresholds of the adaptive model of standard ASHRAE-55 (2017), WHO indoor air quality guidelines (WHO, 2010), and (ASHRAE-62.1, 2016) for classroom and school type. • To evaluate and compare thermal comfort and indoor air quality perceptions and sensations responses of students and teachers to criteria specified in ASHRAE-55 (2017), using different comfort scales and environmental indices. • To analyze whether students’ perceptions of thermal and air quality comfort are related to their socio-economic background (the type of school, vulnerability index, and home conditions) through statistical analysis of variance and correlations. 23 • To compare the results with findings from other thermal comfort and air quality studies. Preliminary approaches prior to the field study included: 1) assembly of participating schools and subject samples through a two-phase recruitment; 2) pilot studies with university students and teachers to test and check electronic survey questionnaires using tablets. 1.5. Significance Classroom spaces are where children spend more time, other than home, during the developmental years of their life, up to one–third of the day (de Dear, Kim, Candido, & Deuble, 2015). It is known that environmental conditions that are not acceptable, due to poor ventilation, increased classroom temperatures, poor air quality, high levels of RH, can affect the comfort, health, and performance of children (de Dear et al., 2015; Kwok, 1997; Zeiler & Boxem, 2009). Thermal discomfort diverts attention; for example, cold conditions decrease finger temperatures, thus affecting manual dexterity (Chen, Shih, & Chi, 2010; Enander & Hygge, 1990; van Maanen et al., 2019; Willem, 2006). On the other hand, warm temperatures lower arousal (the state of activation of an individual), decreasing children’s attention and affecting timing and choice of behavior (Pawel Wargocki & Wyon, p. 361, 2016; Willem, 2006). However there is little understanding of what are comfortable conditions for children, since all current standard criteria, e.g., (ASHRAE–55, 2017; EN15251, 2007; ISO 7730, 2005) for the evaluation of thermal comfort are based on studies on adults. 24 As evidenced from the literature, there is a significant need for research studies that can contribute to a better understanding of how to provide a comfortable indoor environment for school children. There are few thermal comfort field studies that include students aged 10–14 years old, from primary school level. There are even fewer studies that include perceptions of students and teachers on thermal comfort and indoor air quality through survey questionnaires designed for their age group. This study will contribute significantly to knowledge in this area. Additionally, there is a dearth of studies performed in developing countries from South America, with different climate and cultural backgrounds, like Chile, where there is no legislation for indoor environmental quality standards. Furthermore, cities in the southern part of Chile have high outdoor air pollution that occurs during winter due to wood-burning heating systems. The latter has more significant implications because most school designs in Chile are naturally ventilated buildings, where operable windows, doors, or envelope filtrations are the only means of fresh air ventilation and minimal provision of heating systems. A deeper understanding of the physical conditions of classroom environments across different school types (public, private–subsidized, and private non– subsidized) and the level of air pollutant concentrations students and teachers are exposed to is sorely needed. This study will shed light on these issues as well as assist in the design process and operations of schools. Additionally, it can inform teachers and parents about adaptive strategies, and school administrators and policymakers about the decision-making of new policies, and eventually educate lawmakers for ordinances that can improve IEQ. 25 1.6. Scope & Limitations Scope: The scope of this study encompasses field measurements of physical conditions of IEQ in classroom with subjective responses through survey questionnaires. Specifically, the study evaluates thermal comfort and indoor air quality parameters (e.g., air temperature, relative humidity, air velocity, radiant temperature, CO2 and particulate matter PM2.5, PM10) of middle school classroom grade levels (6th to 8th grade). Subjective responses included: 1) “right–here–right–now” type of questions on current status of thermal comfort, air movement, and air quality using multiple voting scales; 2) general personal satisfaction and perception about home and classroom environmental conditions, and health-related symptoms experienced in the past; 3) house conditions; 4) personal perception of impacts of classroom environmental parameters on class work; and 5) general demographic information, gender, age, nationality, and anthropometrics of height and weight were collected. Limitations: This study acknowledges the importance of studying the effects and relationships between poor air quality on performance and health-related symptoms, on students and teachers in classroom environments — for example, the effects of CO2 concentrations on absenteeism, and health symptoms. However, this study did not include such evaluations of the effects of thermal and air quality comfort on students’ and teachers’ performance and health. The original design for this study included measurements of two distinct temperature regimes (i.e., summer and winter season). However, due to a delay in the 26 import of fieldwork equipment, the start of data collection was delayed a month from what was initially anticipated. Because of this delay, it was only possible to collect measurements during fall (a transitional season) and winter season. Additionally, this delay affected the schedule planning for the second field campaign during winter, affecting the sample size for this assessment. Therefore, it was only possible to assess four school buildings instead of the original nine from the first field campaign because of the winter break holiday schedule of schools. During fieldwork assessment in the fall season, measurements evidenced a variation of the daily mean outdoor temperature, showing a difference of 6.4ºC between the highest outdoor daily mean temperature value measured at the beginning of the field study (April 23rd) and the lowest outdoor daily mean temperature value at the end of the campaign (May 30th), as seen in Table 5.5. This unfortunately influences the calculation for comfort temperatures by being outside of the comfort range permissible by the adaptive model in (ASHRAE–55, 2017) standard. The range allowed for prevailing mean outdoor temperatures is >10ºC and < 33.5ºC. Although these limitations can have an impact on the accuracy of the results, the methodology and data analysis have accounted for such variations of these unexpected events. 27 1.7. Organization of the Dissertation The dissertation is organized in a series of chapters that explores the different topics related to the study aims. This dissertation includes previously published and unpublished co-authored material. Committee members have contributed to these papers, hence they are listed as co–authors. The following outlines the main topics and research questions addressed by each chapter. Chapter 1: introduces the research topic and research problem, structure, and significance of the research. It states the research aims, questions, scope and its limitations, and outlines the research design and approaches for the development of this thesis. Chapter 2: provides background information of definitions of thermal comfort and indoor air quality parameters, approaches commonly used in the literature to evaluate thermal comfort and air quality, and international standards. Chapter 3: provides a literature review on current research on comfort and indoor air quality of school fieldwork studies carried out internationally as well as locally in Chile, and research studies on effects of temperature and air quality on students' health and performance. Chapter 4: seeks to answer the first and third research questions of the thesis. This chapter presents results of previously published co-authored material from the conference proceeding for the Architectural Research Centers Consortium (ARCC) 2019 International Conference: Future Praxis Applied Research as a Bridge Between Theory and Practice. 28 Chapter 5: seeks to answer questions two and four of the thesis. This chapter presents the results of an unpublished article that is planned to be submitted to the international journal Building and the Environments. Chapter 6: conclusions and future work 29 2. CHAPTER II: BACKGROUND 2.1. Indoor Environment Providing a good indoor environment is essential for the success of building design, not only because it is seeking occupants' comfort, but also the significant impact on energy consumption and thus its influence on sustainability. Today's standards that define acceptable indoor environments should address all these factors (Nicol & Humphreys, 2002). The indoor environment can be defined as dynamic interactions of spatial, social, and physical factors which affect productivity, health, and comfort (Clements-Croome, 2018). The condition of comfort in an environment "is the result of the interaction of physical exchanges, physiological, psychological, social and cultural rights, it depends on the architecture, the clothing, the eating, and the climate" (Fabbri, 2015, p. 8). Therefore, the assessment of Indoor Environmental Quality (IEQ hereafter) does not depend solely on the physical parameters of the environment (i.e., temperature, humidity, air velocity, acoustics, and lighting), but also the human body's physiological and psychological responses to them. The human body, through its physiological systems, will respond to the different environmental variables through a dynamic interaction, which can result in successful or unsuccessful response to the outside world. Unsuccessful responses can lead to death, due to conditions beyond survivable limits, whereas our goal is the successful response of the 30 body as it uses its resources to maintain an optimum state. The assessment of comfort in an indoor environment, which can help us make the judgment of the conditions of well- being, comes under four categories: 1) Thermal Comfort, 2) Indoor Air Quality, 3) Lighting Comfort, and 4) Acoustic Comfort. Thermal environment can help determine if a person is too hot, too cold or in thermal comfort (Parsons, 2003). Evidence has shown, that human beings react differently to the indoor environment, for example, children in school versus adults in office settings. Children move around into different classroom spaces during a school day and have different activities that can change their metabolic rate and therefore, their thermal perception (Havenith, 2007; Kim & de Dear, 2018b). On the other hand, adults in an office are mostly sitting in the same space and performing similar 3working activities resulting in a long-term sedentary position. Parsons, in 2003 noted that, there are four principal methods that can assess human responses to the environment: 1) Subjective Methods; 2) Objective Measures; 3) Behavioral Methods, and 4) Modeling Methods. This study addresses children/teachers’ interaction with classroom environments, through the first two methods via fieldwork data collection. The following chapter focuses on the contributions of past field studies of thermal comfort and indoor air quality, and the applicability of the adaptive model in school settings. The literature background is divided into four main sections: 1) definitions of comfort and parameters, 2) models of thermal comfort, 3) international standards, and 4) studies on thermal comfort and indoor air quality in school settings. 31 2.2. Defining the Meaning of Thermal Comfort and Indoor Air Quality Thermal comfort is linked to how our bodies need to maintain a constant internal temperature (balance of heat), and it depends on the environment we are in or the amount of heat we produce. This internal temperature of our bodies is maintained in the range of 37 °C when conditions allow our human body to achieve a temperature balance with the environment, which is vital for our health and well-being (Nicol, Humphreys and Roaf, 2012). The thermal interaction between the human body and the environment in maintaining this stability is a process that Nicol et al., (2012), called "thermoregulation", which is complex and involves research on multiple disciplines such as psychology, physiology, physics, and sociology. Nicol et al., (2012), describe that sociologists analyze the way occupants react to the environment, physiologists study how we use and produce heat, and psychologists interpret conscious feeling about the environment. On the other hand, design builders should consider all of these factors by providing a design that best meets occupants’ comfort needs. For example, thermal comfort standards can help architects, engineers, and building constructors design buildings that can provide an indoor environment that more than 80% of their occupants will find thermally comfortable, which is an overall acceptability specified in many standards such as ASHRAE-55 (2017). However, the dissatisfaction of the remaining 20% raises the question: are we supposed to ignore their discomfort? (ASHRAE–55, 2017) Researchers have provided multiple definitions of thermal comfort in the literature. In the field of architecture, Olgyay (1953) was probably the first to formalize the concept of thermal comfort through his bioclimatic approach (as cited in Shamila Haddad, 2016, p. 16). Lisa Heschong’s Thermal Delight in Architecture (Heschong, 1979), describes that 32 there is an underlying assumption that the best thermal environment is the one that goes unnoticed and that once objectively "comfortable" all of our thermal needs have been met. Heschong notes this is the ideal approach by the heating and cooling engineers: “The steady-state approach to the thermal environment assumes that any degree of thermal stress is undesirable” (Heschong, 1979, p. 21). Benzinger (1979) and Hensen (1991) agrees with this assumption of what thermal comfort should be, by describing it as: "a state in which there are no driving impulses to correct the environment by behavior." The ideal approach imposed by engineers that Heschong describes, is the concept of uniformity or static conditions, providing the same temperature across multiple spaces within a building, which in turn requires a great effort and energy for engineers to maintain. These static conditions are utterly unnatural to what happens outdoors or in naturally-ventilated spaces in which physical variations occur. Heschong argues: “When thermal comfort is a constant condition, constant in both space and time, it becomes so abstract that it loses its potential to focus affection” (Heschong, 1979, p. 36) It has been assumed that providing a constant temperature can prevent people from being distracted or making adjustments to the internal conditions to reach a comfortable thermal state. However, studies have shown that people seemed to enjoy a range of temperatures, "in spite of extra physiological effort required to adjust to thermal stimuli" (Heschong, 1979, p. 21). Providing a fixed set temperature, particularly in indoor environments that are naturally ventilated, many times is not a possible solution for occupants. There is an underlying notion, as noted by Fitch (1972) that humans might 33 subconsciously need thermal variations (Spengler, McCarthy, & Samet, Chapter 15, 2001). Heschong (1979) suggests that we should look for more than just a simple comfort in a building, but through our thermal sense we can not only find satisfaction but under certain conditions, we can produce delight. The American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE hereafter) provides the definition that is most accepted for the thermal comfort, which defines it as: “that condition of mind that expresses satisfaction with the thermal environment and is assessed by subjective evaluation” (ANSI/ASHRAE 55, 2017, p. 3). This definition leaves open what is meant by "condition of mind" or "satisfaction," but it does emphasize that judgment of comfort is a cognitive process which involves different interactions influenced by physical exchanges, physiological, psychological, and other processes (ASHRAE Hanbook, 2017). Comfort also depends on behaviors that are consciously or unconsciously guided by thermal and moisture sensations to reduce discomfort. Examples of such adaptive behaviors include: altering clothing, opening a window, changing posture or location, changing thermostat settings, or leaving the space (ASHRAE Hanbook, 2017). The purpose behind the science of thermal comfort is to provide user satisfaction, health, delight, and energy conservation strategies as noted by Nicol, Humphreys, and Roaf (Nicol, Humphreys, & Roaf, 2012). Indoor Air Quality (IAQ hereafter), refers to the air quality within and around buildings and structures, especially as it relates to the health and comfort of building 34 occupants (EPA, 2019). Understanding and controlling common pollutants found indoors can help us reduce the risk of indoor health concerns. In “Building Breathing Space” by Steven Connor (Academie, 2006, Chapter 2, p. 118), the author describes that "buildings sweat, age, excrete and they respire." Research studies have helped us understand that one of the significant concerns of indoor air quality is the off-gassing of building materials, in addition to occupant odors as well as occupant breathing (Passe & Battaglia, 2015). Therefore, ventilation is required to adjust humidity levels as a result of exhaled air by occupants or interior conditions, as well as, to remove excess heat, body odors, and materials' emissions (e.g., volatile organic compounds, VOC), which are major health concerns. As described by Passe & Battaglia (2015), ventilation has two primary goals. First, to provide cooling air through the reduction of temperature or cooling by evaporation through the increase of air velocity. Second, to maintain air exchange rates that can help keep a proper composition of air, by avoiding stale or nauseating conditions, due to little oxygen or to many pollutants such as VOC, or CO2. As addressed by Olli Seppänen (Seppänen, 2006), ventilation and natural ventilation can help remove or dilute pollutants that can cause health-related issues such as (in Santamouris & Wouters, 2006, Chapter 9, p. 247 as presented in Passe & Battaglia (2015) : 1. Infectious diseases caused by airborne viruses or bacteria; 2. Growth of microorganisms in humid air, for example, mold within the building envelope construction 3. Allergies and asthma caused by exposure to mold that thrives at high humidity indoors; 4. Lung cancer caused by exposure to tobacco smoke and radon decay products; 5. Cancer and skin irritation as well as allergies caused by VOCs and formaldehyde in the air 6. Dizziness and nausea caused by odors, which can lead to dissatisfaction with the indoor environment; 35 7. Sick building syndrome (SBS). Indoor humidity is considered a widespread cause of respiratory diseases among children, due to the fact that high indoor air humidity promotes mold growth. Particular care must be taken in high-density classroom environments, and leaky building envelopes, which can lead to internal condensation on walls and colder surfaces. Therefore, the removal of humidity through ventilation is of great importance to reduce health-related risk due to mold growth. On the other hand, if too much humidity is removed other detrimental problems like respiratory issues can be created due to the dry air (Passe & Battaglia, 2015). Careful consideration needs to be taken for the appropriate ventilation rates to provide a healthy environment. This topic is still debatable today in terms of energy savings, and the type of equipment required to condition the air. 2.3. Thermal Comfort and Indoor Air Quality Parameters Providing comfortable conditions depends on factors that affect occupants’ perception and experience of thermal comfort. Currently, indoor thermal comfort is influenced by four parameters of the thermal environment, including air temperature, relative humidity, mean radiant temperature (i.e., the temperature of surrounding surfaces), and air velocity. Additionally, these parameters are combined with two personal factors: clothing (i.e., thermal resistance) and activity level (i.e., metabolic rate) of occupants. It is also important to consider temperature stratification and the temperature difference over the entire body, and surface temperatures of adjacent walls near the occupant, which can have an impact on the perception of comfort. Human beings react differently to 36 comfortable conditions due to psychological and physiological factors, which makes it difficult to satisfy everyone. In school settings, the temperature is considered to be one of the most important indoor environmental parameters, as higher temperatures can negatively impact performance (Pawel Wargocki & Wyon, 2007). On the other hand, for IAQ, one of the “most important validation parameters (next to temperature and humidity)” is air change rates for ventilation strategies (Passe & Battaglia, 2015, p.62). However, providing a ventilation strategy can only be implemented in a continuous mode of air change rate in naturally-ventilated buildings. Therefore, the rate in question becomes the minimum rate for natural ventilation strategy, which is driven by dynamic and not continuous homogeneous forces (Passe & Battaglia, 2015, p.62). Ventilation rates that provide healthy IAQ are determined by the following factors: the number of people occupying the space, their activity level, the volume, and the area of the space. In recent findings, little evidence exists that supports the tenet that higher ventilation rates [2.5 versus 26 cfm (1.2 versus 12.3 L/s) per person as evidenced in Seppanen, Fisk, and Mendell, (1999)] provide healthier indoor environments (Holladay, M. 2013, as cited in Passe & Battaglia, 2015). However, the perception of air quality and ventilation rates have shown a connection in studies by Seppänen et al., (1999) and also have been correlated with performance by Wargocki et al., (Pawel Wargocki, Wyon, Sundell, Clausen, & Fanger, 2000). 37 Other IAQ parameters are PM2.5 and PM10, that refer to particulate matter with particle diameters up to 2.5 µm and 10 µm, respectively, and are amongst the most hazardous of air pollutants for human health. Smaller particles < 2.5 µm are the most harmful because they penetrate deep into the lungs and are difficult to remove from the air (Santamouris & Wouters, 2006, p. 254). These types of particles can cause various health- related issues, such as cardiovascular diseases or asthma attacks due to pollen or airborne dust. Carbon dioxide (CO2) is also an essential parameter of IAQ and can be an indicator of other pollutants in the air and for ventilation rates. CO2 concentrations depend on occupancy, ventilation rate, and room volume (Santamouris & Wouters, 2006, p. 256). School environments, in general, tend to be particularly highly polluted due to the following reasons: crowded classrooms, low ventilation rates, multiple activities that can increase children's metabolic rate and indoor temperature, inadequacy in providing fresh air, bringing pollutants in from the outdoors after break times, or due to inappropriate selection for site location; e.g. near heavy-traffic streets or highways as evidenced in the literature review studies (Chatzidiakou, Mumovic, & Summerfield, 2012; W. J. Fisk, 2017). Further careful consideration of these IAQ parameters and their effect on health, comfort, and performance of children and possible negative impacts is required. 2.4. Research on Thermal Comfort An extensive volume of research, based on studies on adults in office settings, has focused on defining commonly accepted criteria and parameters of thermal comfort that have been distilled into different international standards. In the USA, thermal comfort considerations are guided by ASHRAE standard 55, in the UK by CIBSE, and in Europe by 38 standard EN ISO 7730 (ASHRAE–55, 2017; CIBSE, 2006; ISO 7730, 2005). Over the last 50 years, two distinct research methodologies have been used for evaluating indoor thermal comfort and the interaction between the human body and the surrounding environment based on questionnaire surveys: 1) laboratory-based studies (climate chambers) and 2) field-based studies (real-world settings). Climate chamber studies are based on the theory of the heat balance of the human body, in which thermal comfort can be achieved through strictly controlled conditions of the building's indoor climate engineering systems (e.g., air-conditioned) (Richard. de Dear, 2004; Halawa & Van Hoof, 2012). In these settings as de Dear describes, occupants are "passive thermal comfort sensors," occupants are not expected to change or intervene, and there is a specific expectation of what the environmental conditions should be, and any departure from that would be evaluated as unfavorably (de Dear, 2004, p. 33). Instead, field-based studies rely on thermal comfort sensations of occupants measured in situ (i.e., while they are doing their daily activities) together with simultaneous physical measurements of the environment. In these real settings, a holistic person- environment systems approach in which the occupant is an active agent, or interactive with the building, informs by implementing adaptive opportunities available to create a thermally comfortable indoor environment for themselves combined with controlled conditions of the building's indoor climate (de Dear, 2004). 39 2.5. Models Thermal Comfort From these two research methodologies, two main model approaches of thermal comfort have been developed and adopted in international standards: 1) the heat-balance model (Fanger, 1970), and 2) the adaptive comfort model (de Dear, 1998; Humphreys & Nicol, 2002a). The latter has been incorporated only sparingly over the last decade. The two models use very different algorithms for calculating comfort zone prescriptions, but also differ significantly about the way buildings are designed and how the environments are controlled (Spengler et al., 2001, p. 15.12). One of the most relevant differences between models is their potential for energy savings in todays’ buildings and the impacts of greenhouse emissions on climate change. 2.5.1. The Heat Balance or Steady-State (Rational) Model The heat balance model, for calculating the steady state of thermal comfort, is the result from an extensive research done inside air-conditioned climate chambers developed by Ole Fanger’s research team in the 1960s and 1970s. In this model, thermal comfort can be reached when the heat balance of the body is neutral, that is, there is a balance between heat production and heat dissipation, as seen in the following equation 2.1 (Fanger, 1970, p. 22). H – Ed – Esw –Ere – L = K = R + C (2.1) Where: H = the internal heat production in the human body Ed = the heat loss by water vapor diffusion through the skin Esw = the heat loss by evaporation of sweat from the surfaces of the skin Ere = the latent respiration heat loss L = the dry respiration heat loss 40 K = the heat transfer from the skin to the outer surface of the clothed body (conduction through the clothing) R = the heat loss by radiation from the outer surface of the clothed body C = the heat loss by convection from the outer surface of the clothed body Based on thermoregulation and heat balance theories, the human body employs physiological processes (e.g., sweating, shivering, regulating blood flow to the skin) in order to reach that thermal balance (Charles K. E, 2003, p. 5). Humans gain heat from metabolism and often from the surrounding environment, and they release heat through convection, radiation, evaporation, and conduction. Humans cannot tolerate a wide range of core temperatures, as cold-blooded reptiles do, so in a short period, heat gains must be balanced with heat losses (Spengler et al., Chapter 15, 2001). In the heat balance or static model of thermal comfort, the model views occupants as passive recipients of thermal stimuli, and the effects of a given thermal environment are mediated exclusively by the physics of heat transfer of their bodies and automatic physiological responses (de Dear & Brager, 1998). Using the heat balance equation (2.6.1), Fanger obtained the comfort equation by inserting comfort expressions for skin temperature and sweat rates from experiments by using American college-aged persons exposed to an environment under steady conditions (Fanger, 1970, p. 42). The comfort equation included four environmental parameters and two personal factors (as mentioned in section 2.4). Thus, combining these parameters would create optimal thermal comfort for occupants under steady state conditions. However, this equation does not take into account people’s thermal sensation, which does not satisfy the equation (Shamila Haddad, 2016). Therefore, Fanger did further studies in 41 which he asked people about their thermal sensation at different temperature conditions in controlled environments. In these studies, participants, mostly male adults wearing office garments, were exposed to various thermal conditions while performing standardized office activities. The researchers chose physical conditions while thermal responses were collected from subjects by asking their thermal sensation vote (TSV) on a psycho-physical ASHRAE seven- point scale, as seen in Table 2.1. In other studies, subjects were able to adjust the thermal environment themselves, adjusting the temperature until they felt thermally 'neutral' (i.e., neither hot nor cold, voting 0 on the scale) (Charles, 2003, p. 5). Table 2.1. ASHRAE thermal sensation scale (ASHRAE55, 2017) Thermal Cold Cool Slightly Neutral Slightly Warm Hot sensation cool warm descriptor Point scale -3 -2 -1 0 1 2 3 The aim of Fanger’s model was to predict the mean thermal sensation vote of a group of people and their respective percentage of dissatisfaction with their thermal environment through the use of indices such as: 1) the Predicted Mean Vote Index (PMV), and 2) the Percentage of Dissatisfaction Index (PPD) (Rupp, Vásquez, & Lamberts, 2015). The PMV index is calculated through the four parameters of the thermal environment (air temperature, mean radiant temperature, air velocity, and humidity) and with two personal variables (metabolic rate and clothing insulation) that influence on thermal comfort. Therefore, the PMV index predicts the mean thermal sensation vote of a group (on ASHRAE seven-point scale) of people at any given combination of the four environmental 42 parameters and the physical activity and clothing worn by occupants. According to Fanger (1970), dissatisfied votes are those that fall within -2 (cool), -3 (cold), + 2 (warm), or +3 (hot), while comfortable votes are within -1 (slightly cool), 0 (neutral), and +1 (slightly warm) on the ASHRAE scale. Calculating these indices are complicated, and their calculation by hand is hardly possible, as seen in ISO 7730. Therefore, computer code programs (Schweiker, 2016), datalogger instruments with built-in software (e.g., Testo 480) or web application tools for ASHRAE 55 (Schiavon, Hoyt, & Piccioli, 2014) are used to calculate PMV-PPD indices. For these applications, indices can be calculated as a function of metabolic rate (W/m2), clothing insulation (clo), air temperature (°C), mean radiant temperature (°C), relative humidity (%), and air velocity (m/s). For input quantities for clothing insulation or metabolic rate, values are obtained from different standards such as ASHRAE–55, 2017; ISO 7730, 2005; ISO 8996, 2004. The PMV method is the basis of international standards that are still currently used today, such as EN15251, 2007; ISO 7730, 2005; and ASHRAE– 55, 2017. Due to the nature of PMV studies (i.e., based on laboratories), numerous studies have investigated the appropriateness of heat balance indices in real-world situations and have questioned its validity. Field studies of thermal comfort are conducted in actual buildings under normal conditions of occupancy, and many times involved a much larger sample size with "real" occupants as opposed to "paid college-age subjects" (de Dear, 2004). As noted in Nicol et al., (2012, p. 49), the model is unable to take into account the social and climatic factors that exist in real-world field surveys. Humphreys and Nicol 43 (2002a) argue that exposure to a large group of people to a single thermal space, wearing the same clothing insulation, and having the same level of activity rarely occurs in real- world settings. Additionally, the applicability and validity of the whole index in other geographic contexts, different types of buildings, and model input parameters such as clothing and metabolic rate, have also been questioned in multiple studies, arguing that a single model cannot be applicable to different settings (Halawa & Van Hoof, 2012; Van Hoof, Mitja Mazej, 2010; Humphreys & Nicol, 2002; Van Hoof, 2008). Studies have also shown that PMV differs from an occupant's vote, particularly in naturally ventilated spaces in which the range that occupants find comfortable in field studies is much broader than the steady-state model allows (De Dear & Brager, 2002; Humphreys & Nicol, 2002). The latter has been the subject of intensive research in field studies, in which the differences can be explained by the concept of "behavioral adaptation," i.e., adjustment to climatic conditions in which the field studies took place. This has led to the adaptive model described below. 2.5.2. Adaptive Comfort Model Looking at climate in addition to thermoregulatory responses, the adaptive model takes into account a range of responses (i.e., behavioral, physiological, and psychological adjustments) that occupants might take in order to achieve thermal comfort (Spengler et al., Chapter 15, 2001). These adaptations are not considered in the heat balance model as occupants are viewed as "passive recipients" of thermal stimuli as noted by de Dear (2004). Instead, in the adaptive model occupants are active agents of their thermal environment. The underlying principle of the adaptive model as described by Humphreys and Nicol: 44 “If a change occurs such as to produce discomfort, people react in ways that tend to restore their comfort” (Humphreys, Nicol, 1998). The adaptive principle sees occupants as active participants in making adjustments to their environment, e.g., opening windows, changing the thermostat or making adjustments to themselves, i.e., adding or removing clothing, changing posture in a process of dynamic equilibrium with the thermal environment. In contrast to the climate chamber approach, in which indoor conditions are controlled for research, the adaptive model relies on field studies in which thermal sensation votes of occupants were collected in situ while they were doing their routine activities (de Dear, 2004) in order to evaluate existing conditions that occupants are exposed to. The origins of the adaptive model are based on field studies in naturally ventilated buildings by Nicol and Humphreys (Humphreys, Nicol, 1998; 2002a; 2010), Auliciems (Auliciems, 1981), and de Dear, Brager, and Cooper (de Dear, Brager, & Cooper, 1997; de Dear & Brager, 1998). From these field studies, relationships between indoor operative temperatures (acceptable ranges) and prevailing outdoor air temperatures were determined through linear regressions such that higher outdoor temperatures allow for higher indoor temperatures (Rupp et al., 2015), thus, ultimately shifting the paradigm of Fanger's theories and steady–state model. Additionally, the adaptive model considers contextual factors and past thermal history, which can influence occupants’ thermal expectations and preferences (de Dear & Brager, 1998). People who live in warm climates would prefer and tolerate higher indoor temperatures, in contrast to people in cold climate zones who would prefer and tolerate lower indoor temperatures, which is the opposite assumption underlying the PMV-model. As noted by de Dear, “the context of a person-environment interaction 45 includes not just environmental context but also cognitive and even emotional context” (de Dear, 2004). Human thermal adaptation can be classified into three categories as described in de Dear and Brager (de Dear & Brager, 1998) and referenced by other authors (Rupp et al., 2015; Spengler et al., 2001): 1) behavioral adjustment; 2) physiological; and 3) psychological. 1) Behavioral adjustment: includes all modifications a person might do consciously or unconsciously, to achieve thermal comfort. These adjustments can be classified into personal (e.g., adding or removing a clothing item), environmental (e.g., turning on an air conditioning/heater, opening a window), and cultural responses (e.g., having a siesta in the heat of the day, or drinking hot liquids like "mate" in cold days). 2) Physiological adaptation: the body's acclimatization for long-term exposure to thermally stressful environments (hot or cold). Physiological adaptations are changes in the internal settings at which thermoregulatory response occur, such as shivering, sweating, vasodilation, and vasoconstriction. Physiological adaptations can be divided into genetic (intergenerational) adaptation and climatization (within the individual's lifetime) 3) Psychological adaptation: are complex combinations of factors outside the realm of thermal environmental parameters. Thermal perceptions might be directly and significantly attenuated by one’s past thermal experiences and 46 expectations of what buildings offer in terms of architectural design and technological features of environmental control systems (e.g., HVAC). In field studies of the adaptive model, particularly in naturally ventilated buildings, occupants are more aware of outdoor weather conditions than in centrally-controlled HVAC buildings. Windows provide a strong link between indoor and outdoor conditions. By using the ASHRAE RP-884 database de Dear, Brager and Cooper (de Dear & Brager, 1998; de Dear et al., 1997; de Dear & Brager, 2002), found an agreement between comfort temperature (preferred indoor temperatures) in HVAC buildings and the predicted temperature of PMV. On other hand, in naturally ventilated buildings, the same conclusion could not be drawn; the PMV model was not able to predict the broader range of temperatures that occupants preferred as seen in Figure 2.1. In such buildings, occupants seem capable to adapt to a much wider range of conditions and accept higher indoor temperatures than predicted by PMV-PPD models (Richard. de Dear, 2004). According to de Dear and Brager, the PMV model is not applicable in naturally ventilated buildings, because the model only partially accounts for thermal adaptation to the indoor environment. 47 Figure 2.1: Comparison between the adaptive model and the “static” model (based on PMV predictions) applied to naturally ventilated buildings, from the data based off RP-884, source (de Dear et al., 1997) The adaptive model, from field studies research, has shown strengths and weaknesses that are worthy of noting. The model provides an opportunity that can be translated into energy savings, due to the broader ranges of acceptable conditions in naturally ventilated buildings which allows for higher acceptable operative temperature as the outdoor temperatures increase (de Dear & Brager, 1998). The reason behind this is due to the higher levels of personal control occupants have in these buildings, thanks to design opportunities for access to operable windows (de Dear et al., 2013). The notion of energy savings is also pointed out by Nicol and Humphreys (Nicol & Humphreys, 2009): the adaptive approach provides an opportunity for comfort in buildings which can also be compatible for low-carbon buildings. The latter, however, requires buildings to offer the ability for more active occupants through integrated design that can maximize the use of passive architectural strategies which can reduce its dependence on mechanical control systems for heating/cooling. 48 Despite the strengths of the adaptive model, weaknesses have been identified by researchers. Due to the nature of the statistical analysis of the adaptive approach, it is difficult to generalize the results from one survey to those from another survey even when the conditions are similar (Humphreys & Nicol, 2002a). Another criticism is this notion that the model is a "black box" based on empirical observations due to the interpretation that the adaptive mechanisms are hidden, not fully defined, and not quantified or related to measurements (Nicol, Humphreys, & Roaf, 2012, p. 30). However, as noted in Nicol et al., (2012) one way to address this criticism is by developing models of usage patterns of occupants' individual adaptation mechanisms (i.e., opening windows, turning on a fan, pulling down blinds, or turning on the heat) that can occur inside buildings. The following work by Fergus Nicol, Humphreys, & Olesen, 2004; Yun & Steemers, 2007; and Rijal, Tuohy, Humphreys, Nicol, 2012 have developed such models and algorithms. However, such predictions of adaptive behaviors and usage are hard to predict and generalize, due to the particular nature of different building types, social context, and occupants' expectations. More research is required in this area. Finally, the model also has been scrutinized by its simple approach of only considering operative temperature to calculate the comfort temperatures based on outdoor temperatures, and by overlooking the environmental and personal parameters which have influenced PMV (Toftum & Ole Fanger, 2002). The latter has been raised by Humphreys and Nicol (Humphreys & Nicol, 2002b) and de Dear et al., (2013) by arguing that comfort temperatures are clearly a function of more than just outdoor temperatures, people’s clothing, or building controls; they are dependent on outdoor conditions, like outdoor temperature. Therefore, there is feedback between climate and adaptive actions, which 49 translates to only considering outdoor temperature for real situations like free-running buildings (Humphreys & Nicol, 2002a). Air temperature or operative temperature are sufficient indices for thermal comfort and including other variables can create biases in the assessment of thermal environment, as noted by Humphreys and Nicol. However, it is not clear what biases Humphreys refers to or how they can impact the overall adaptive thermal comfort. The adaptive model has also ignored the effects of humidity and air movement on comfort, which were not captured in the ASHRAE-55-2004 standard version and only in the recent revision of ASHRAE 55-2010, which incorporated air movement as a way to stretch the warmer comfort zone, from 0.8 m/s to 1.2m/s. This change came after more than 20 years of supporting evidence that more air movement can allow comfort at higher indoor temperatures (de Dear et al., 2013). On the other hand, in cold climate zones, the use of more clothing insulation has not been acknowledged as a way to broaden the comfort zone towards a colder side (< 10°C) and potentially reducing energy use through heating. Further studies are necessary to look at this alternative for cold climates where occupants can be more adaptive to cold temperatures. Even though the model presents limitations and has been subject to scrutiny, its incorporation in international standards is a significant step forward in recognizing the vital role occupants exert on their indoor environment. 2.6. International Standards for Thermal Comfort Currently, there are three well-known and widely used international standards: ASHRAE Standard 55 (2017), ISO Standard 7730 (2005), and CEN Standard EN15251 50 (2007). These standards are used to determine design values for operative temperature, and comfort equations based on the steady-state heat balance or the adaptive thermal comfort models, as seen in Table 2.2. Table 2.2. Thermal comfort standards in applicable to classroom spaces Standard Thermal comfort Operative temperature Clothing insulation approach range (°C) Winter Summer Winter Summer ISO 7730 heat balance/steady-state (2005) –0.51.0). Additionally, one-way ANOVA was run to compare the mean TSVs among teachers across school types in fall. No statistically significant difference was reported, (F(2,59) = 3.01, p = .057). Figure 5.12 shows the crosstabulation between TSV in relation to their Thermal Preference Vote (TPV) across a three-point scale suggested by McIntyre, for students in fall. It can be seen that as the thermal sensation increases (i.e., from cold to hot), percentage students of votes increase for wanting “cooler” temperatures. On the other hand, as thermal sensation increases towards the cooler side, votes increase for “warmer” temperatures. The distribution seems almost symmetrical. However, inconsistent responses occurred towards the warm side; for example, 37% of the students who felt hot (thermal sensation of +3) prefer warmer temperatures. This suggests that students might not have fully understood right-here right-now phrase. However, the total percentage of inconsistent votes only represents 3.9% (13 votes) as seen in Table 5.7 from the total number of votes (1542), a minimal percentage, demonstrating that the majority of the students did indeed understand the questionnaire and what was asked. 148 Figure 5.12. Cross-tabulation between thermal sensation (ASHRAE) and thermal preference votes of students in fall season. As move towards the warmer side of scale, the preference for cooler temperature increases. In other hand, as students votes move towards de cold side of the scale, thermal preference for warmer temperatures increases. Table 5.7 Cross-tabulation between thermal sensation (ASHRAE) and thermal preference Thermal Sensation Votes (TSV) Thermal Preference -3 -2 -1 0 +1 +2 +3 Total Cooler (1) 4 (1.1%) 10 (2.7%) 33 (8.8%) 124 (33.2%) 127 (34.0%) 56 (15.0%) 20 (5.3%) 374 (100.%) No Change (2) 10 (1.2%) 38 (4.6%) 144 (17.2%) 445(53.3%) 163(19.5%) 33 (4.0%) 2 (0.2%) 835 (100.%) Warmer (3) 26 (7.8%) 50 (15.0%) 101 (30.3%) 74 (22.2%) 55 (16.5%) 14 (4.2%) 13 (3.9%) 333 (100.%) Total 40 (2.6%) 98 (6.4%) 278 (18.0%) 643 (41.7%) 345 (22.4%) 103 (6.7%) 35 (2.3%) 1542 (100%) Cross-tabulation between thermal sensation (ASHRAE) and thermal preference, n = number of votes (percentage with respect to number of votes) 149 Another way of looking at this relation of votes in the data is the question of “neutral” thermal state. Studies have suggested (Kwok & Chun, 2003, Wong & Khoo, 2003) that this is not always the preferred option. Table 5.8 crosstabulation grouped the central three categories of thermal sensation and extreme ends of dissatisfaction [-3, -2 & +2, +3]. Of the students that voted within the three main categories, 48.8% prefer no change in the temperatures of their classroom. However, those that felt slightly cooler, 18.3% voted to want cooler temperatures and in the slightly warmer scale, 14.9% prefer warmer temperatures, corroborating previous studies. Table 5.8. Cross-tabulation between thermal sensation (ASHRAE) and thermal preference Thermal Sensation Votes (TSV) Thermal Preference (-3, -2) (-1, 0, +1) (+2, +3) Total Cooler (1) 14 (0.9%) 284 (18.3%) 76 (4.9%) 374 (24.1%) No Change (2) 48 (3.1%) 752 (48.8%) 35 (2.2%) 835 (54.1%) Warmer (3) 76 (4.9%) 230 (14.9%) 27 (1.7%) 333 (21.5%) Total 138 (8.9%) 1266 (83%) 138 (8.8%) 1542 (100%) Cross-tabulation between thermal sensation (ASHRAE) and thermal preference, n = number of votes (percentage with respect to number of votes) The survey also asked subjects about their preference of air movement and the air quality sensation vote (AQV) of their classroom. Figure 5.13 shows the distribution of votes from the question How do you find Air Quality right now in this classroom? in a seven- point scale based on a previous study (Kwok, 1997) for students and teachers in the fall season. Votes fell within the three central categories of the scale: slightly stale, neutral, and slightly fresh [-1, 0, +1], with very small differences around them as seen by the 95% confidence interval error bars. A small tendency can be seen towards the slightly stale side of the scale, a total of 28% of the votes for students versus 39% for teachers, suggesting that teachers are a bit more sensitive at perceiving the air quality of the classroom than 150 students. The average mean AQV for students is -0.121 (SD = 1.42) and -0.18 (SD = 1.45) for teachers. Figure 5.14 shows the crosstabulation between AQV in relation to their Air Movement Preference Vote (AMP) a three-point scale (more air movement, no change, and less air movement) similar to McIntyre thermal preference, for students in fall. Note that as air quality is perceived to be more stale (i.e., from neutral to very stale), the percentage of student votes increased towards “more air movement.” On the other hand, as the air quality votes increase towards the fresh side of the scale (i.e., from neutral to very fresh), votes are very divided between wanting more air movement or no change. Inconsistent responses occurred towards the fresh side of the scale, for example, 57% of the students who felt the air was fresh (air quality vote of +3) preferred more air movement, suggesting that air movement is a preferred condition for children in their classroom environment. However, this sample only represents 1.6% (24 votes) from the total number of votes. This result can also be evidenced in Table 5.9, a crosstabulation that looks at the relation between air quality sensation vote and air movement preference vote, by grouping the three central categories and extreme ends [-3, -2 & +2, +3]. The left side of the scale assumes votes of dissatisfaction of the air quality sensation. Of the students that voted within the three central categories, 40.5% prefer more air movement, 25% no change and 5.6 less air movement. 151 a) Students Mean = -0.12 Std. Dev = 1.42 Std. EM = 0.03 N = 1542 b) Teachers Mean = -0.21 Std. Dev = 1.05 Std. EM = 0.13 N = 62 C) TEACHER S Figure 5.13. Distribution of Air Quality Perception Votes for students (a) and teachers (b) in the fall season. 75% of the votes for children fall within the central three categories of the scale, with 28% on slightly stale. For teachers, 91% of the votes are within the three central categories. The distribution of students votes is slightly skewed towards the more stale side of the scale, in comparison with teacher votes, 47% of the votes was towards the slightly stale to moderately stale. 152 Percentage of Vote (%) Percentage of Vote (%) Figure 5.14. Crosstabulation of the relationship between Air quality sensation vote (AQV) and Air Movement Preference Vote (AMP) for students during fall surveys. Higher preference vote for more air movement is observed at stale conditions. However, students’ prefer more air movement even at very fresh perceived conditions. In general, this confirms that students prefer more air movement in their classroom, consistent with the low air velocities measured in the classroom. Table 5.9. Cross-tabulation of number of votes and their percentages between air quality sensation and air movement preference Air quality sensation vote (AQV) Air Movement Preference (-3, -2) (-1, 0, +1) (+2, +3) Total Less air movement (1) 33 (2.1%) 87 (5.6%) 25 (1.6%) 145 (9.4%) No Change (2) 19 (1.3%) 385 (25%) 73 (4.7%) 477 (30.9%) More air movement (3) 209 (13.6%) 625 (40.5%) 86 (5.6%) 920 (59.7%) Total 261 (17%) 1097 (71.2%) 184 (11.9%) 1542 (100%) Cross-tabulation between air quality sensation and air movement preference, n = number of votes (percentage with respect to number of votes) 153 A Pearson Correlation analysis was performed between subjective votes and physical measurements as seen in Table 5.10. Subjects air movement preference votes with CO2 concentrations shows a weak, negative correlation of r = -0.006, n= 1542, p= 0.800 as seen in Table 5.10. 5.4. Discussion Participating subjects included middle school students and teachers. Overall, primary school children, aged 10–14, were capable of understanding thermal sensation and preference rating scales, and their responses are similar to responses from teachers. This is further supported by the fact that there were very few conflicted discrepancies when looking at TSV and TPV. Despite very cold classroom conditions, classroom occupants found those conditions comfortable, as oppose to those specified in ASHRAE-55. Votes for TSV and TPV were found to be similarly related to environmental conditions, as seen in Table 5.9. This suggests that the environmental variables are effective indicators of students’ thermal response. A negative correlation (r(1542) = -0.322, p=0.01) was identified between TSV and TPV during fall from student surveys. However, there were discrepancies between children’s responses, such as feeling warm and wanting warmer temperatures. Evaluating the air quality perceptions, students voted within the three central categories of the scale: slightly stale, neutral, and slightly fresh. Teacher votes were skewed towards the slightly stale conditions, suggesting they were a bit more sensitive at perceiving classroom conditions than students. This might be explained by the fact that 154 Table 5.10 Pearson correlation matrix, between physical measurements and subjective perceptions, with their significance Correlations Subjective Perceptions Votes Personal Parameter Indoor environmental variables Tpma( Ta(out) Va CO2 Top TA TPV AMP AQV Clo Age Gender out) ºC ºC Tg ºC Ta (ºC) Rhi (%) (m/s) (ppm) (ºC) Subjective Perceptions Votes Thermal Sensation Vote -0.004 -.322** .180** -.102** -.107** -.083** .080** .179** .123** .233** .266** -.115** 0.023 -.132** .254** (TSV) 0.871 0.000 0.000 0.000 0.000 0.001 0.002 0.000 0.000 0.000 0.000 0.000 0.365 0.000 0.000 Thermal Acceptability (TA) 1 0.011 -0.007 .254** -0.032 -.080** .093** -0.006 0.018 0.031 0.046 0.004 0.042 0.024 0.037 0.674 0.770 0.000 0.205 0.002 0.000 0.804 0.483 0.221 0.072 0.869 0.098 0.353 0.149 Thermal Preference Vote 1 -.242** .198** .074** 0.049 0.000 -.079** -0.005 -.166** -.202** .134** -0.031 .050* -.183** (TPV) 0.000 0.000 0.004 0.056 0.994 0.002 0.833 0.000 0.000 0.000 0.221 0.049 0.000 Air Movement Preference 1 -.193** -0.019 0.022 -0.010 0.042 -0.049 .112** .141** -.123** 0.024 -0.006 .125** (AMP) 0.000 0.455 0.395 0.707 0.102 0.055 0.000 0.000 0.000 0.351 0.800 0.000 Indoor Air Quality Vote 1 -0.014 -0.043 .107** -0.045 .103** -.076** -.109** .105** .052* -0.010 -.087** (AQV) 0.579 0.088 0.000 0.078 0.000 0.003 0.000 0.000 0.039 0.708 0.001 Personal Parameter Cloth insulation (Clo) 1 -0.007 -.215** 0.041 .111** -.055* -.134** .147** -0.009 .064* -.077** 0.777 0.000 0.111 0.000 0.031 0.000 0.000 0.725 0.011 0.002 Age (yrs) 1 -0.005 -.092** -0.017 -.155** -.102** -0.005 0.019 -.100** -.149** 0.836 0.000 0.504 0.000 0.000 0.835 0.463 0.000 0.000 Gender (male/female) 1 0.047 .153** .100** .061* 0.035 0.045 0.036 .098** 0.067 0.000 0.000 0.016 0.167 0.077 0.163 0.000 Indoor environmental variables Prevailing mean outdoor Temperature Tpma(out) 1 .434** .628** .626** -.357** .069** -.241** .665** 0.000 0.000 0.000 0.000 0.007 0.000 0.000 Mean daily Outdoor Air Temperature Ta(out) 1 .139** .122** .467** .074** -0.043 .147** 0.000 0.000 0.000 0.003 0.094 0.000 Indoor Globe Temperature (Tg) Correlation coefficient range 1 .692** -.491** -0.019 -.159** .984** 0.51 to 1.0 0.000 0.000 0.463 0.000 0.000 Indoor Air Temperature (Ta) 0.31 to 0.5 1 -.595** .070** -.205** .806** 0.1 to 0.3 0.000 0.006 0.000 0.000 Indoor Relative Humidity 0.0 1 -.143** .452** -.544** (Rhi) –0.1 to 0.3 0.000 0.000 0.000 Indoor Air Velocity (Va) –0.31 to 0.5 1 -.056* 0.029 –0.51 to 1.0 0.029 0.255 Indoor Carbon Dioxide 1 -.181** (CO2) 0.000 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). Top = Pearson Correlation BMoitdtodmle = = S iSgi g(2. -(t2a-ilteadil)e d) Bottom = number of observations 155 students are longtime residents to their classroom, spending most of their day in the same classroom while teachers moved to different classrooms throughout the day. The preference for more air movement was across all school types, even for the votes falling on the fresh side of the scale. While collecting the different surveys, the author experienced very stale/stuffy classroom environments in all school types and attributed this to high levels of CO2, PM10, and PM2.5. Even though student votes for indoor air quality might not be as effective in the “right-here-right-now” type of questions in the survey itself, their overall perception when asked in focus group interviews described deplorable air conditions. Indoor air quality in all classrooms had high levels of CO2 (>4,000), PM10 (>135), and PM2.5. (>50). Some of the factors that might explain these conditions: a) high density of occupants in the classrooms; b) little air movement which limited air ventilation rates (i.e., windows were mostly closed due to low outdoor temperatures); c) predominantly wood- burning for heat during the winter in these localities. A medium positive correlation was identified between CO2 and RH, r(1542) = 0.467, p=0.01. Students reported feeling tired and have difficulty concentrating. Also, the relative humidity was high (e.g., ranging from 60% to 75%) in all school types, presence of mold in walls and ceilings, as well as condensation in walls and windows were observed in classrooms visits. In some cases, mold can have a more significant impact on health and well-being of students and teachers (Philomena M Bluyssen, 2012; Chatzidiakou et al., 2012; Daisey, Angell, & Apte, 2003b), thus suggesting new strategies need to be implemented through better architectural design, that can improve indoor classroom conditions. 156 5.5. Conclusions Student and teachers votes fall within the comfortable ranges of acceptability of ASHRAE-7 point scale, as seen in the normal distributions of thermal sensation with higher votes concentrated in neutral and thermal preference votes in no change, despite very cold conditions when compared to international standards. Students and teachers utilized adaptive mechanisms such as adding clothing such as scarfs, parkas, coats, mittens, and other pieces of clothing. Additionally, students during break times, increasing metabolic activity, shivering, huddling, and bringing in hot drinks to their classroom. Classroom environmental parameters, such as humidity is negatively correlated with indoor temperature (r = -0.595, p = 0.001) and positively correlated CO2 concentrations (r = 0.452, p = 0.001). Prevailing mean outdoor temperature is positively correlated with indoor air temperature (r = 0.626, p = 0.001). Indoor air quality conditions are very deficient by ASHRAE-62.1. The latter can be explained by low ventilation rates (airspeed average of 0.09m/s in all school) due to little use of windows (because of outside noises, and cold outdoor temperatures), and crowded classrooms. Additionally, high concentration (by guidelines of WHO 2010, and ASHRAE- 62.1) of particulate matter is due to dust, soil that children bring from the outside, windows located close to outside traffic streets, and high concentrations of fine particle PM2.5 due to domestic heating systems (i.e., wood-burning heaters). Subjects indoor air quality perceptions (AQV) and thermal preference vote (TPV) have a median positively correlation, r = 0.198, p = 0.001, suggesting that the perceptions 157 of air quality conditions may influence thermal preference. Additionally, AQV is negatively correlated with air movement preference (AMP), r = -0.193, p = 0.001. The results of this study contribute information regarding student and teachers perceptions and preferences of their classroom environments, to the body of knowledge that was previously lacking. 158 CHAPTER VI 6. CONCLUSIONS This thesis investigated thermal comfort and indoor air quality conditions in primary school settings, through field surveys, during fall and winter season in the city of Concepción, Chile. The overall aim is to advance our understanding of students’ and teachers’ sensations towards thermal comfort and indoor air quality, specifically, to identify other factors that might influence their perceptions of thermal comfort and air quality conditions. The main conclusion of this study is that students and teachers in free-running classrooms feel comfortable in and accept cold and poor air quality conditions, outside the ranges of comfort zone specified by the adaptive model of the ASHRAE–55 (2017) standard, and thresholds of indoor air quality guidelines by WHO (2010) and ASHRAE – 62.1 (2016). Occupants in this climate zone have found personal ways to adapt themselves to outdoor temperatures lower (<10ºC) than those specified by ASHRAE-55 adaptive model in free-running environments (i.e., limited heating in winter). Prevailing mean outdoor temperature ranges for this study were between 8ºC and 11ºC in fall, and 6 and 9ºC in winter. 159 The fact that occupants in this cultural and climate region can adapt to comfort in free-running classrooms, with limited opportunities to change indoor environmental conditions, suggests opportunities to expand the adaptive comfort zones to broader ranges of colder outdoor temperatures for school buildings. This offers an excellent possibility for schools to save energy with well-designed characteristics of naturally–ventilated environments that can promote health, performance, and well-being. This chapter discusses key conclusions drawn from the study based on the research question asked and it suggests further work. 1. Physical conditions, such as air temperature, relative humidity, particulate matter, air velocity, CO2 levels, inside learning spaces are deficient (i.e., high CO2 and particulate matter concentrations, low indoor operative temperatures, and high RH), which confirms results from previous studies in Chilean primary schools (Armijo, Whitman, 2011; Soto et al., 2015; Trebilcock et al., 2017a). However, this study contributes with new knowledge on these conditions, which were seen across all three main types of schools present in the Chilean educational system (i.e., public, private-subsidized, and private–nonsubsidized schools). This evidences the need to incorporate new standards and guidelines that can help to set minimum thresholds for school building design currently unavailable, similar to what developed countries have defined, to provide better indoor conditions in classroom spaces for their occupants. Concerning measurements of high CO2 concentrations in all schools, these are likely the result of poor ventilation rates (on average 0.09 m/s in both seasons) and 160 crowded environments, thus limiting the possibilities to remove air pollutants and provide clean air inside the classrooms. CO2 concentrations average 1600 ppm in fall and 1900 ppm in winter, exceeding the maximum threshold of 1,000 ppm in densely occupied spaces according to EPA and ASHRAE Standard 62.1-2016. Similarly, high particle concentrations for particulate matter PM10 were observed. Average concentration in all classroom were 105 μg/m3 and 117 μg/m3 in fall and winter, respectively. Average concentrations of PM2.5 were 38 μg/m3 and 56 μg/m3 in fall and winter, respectively, thus exceeding WHO 2010 guidelines of 20 μg/m3 at eight hour mean for PM10 and 10 μg/m3 at eight hour mean for PM2.5. These alarming conditions must be address soon because of the effects they can have on children’s developmental years, particularly because of the extended hours that children spend indoor. Further research is required in this area, particularly on the effects it can have on health and performance on students and teachers. 2. Differences between schools were seen as shown in Figure 5.7. High levels of RH (between 65% and 80% on average) and low indoor temperatures (between 15ºC and 24ºC) were measured in public schools compared to both types of private schools. The social background does have an impact on the current physical conditions measured in the field study; public schools have minimal operational funds administered by municipalities compared to private schools that have more resources due to students tuitions. Construction systems in public schools are mostly outdated compared to private ones. Public schools have basic construction solutions, no insulation, leaky envelopes, many have not been re-conditioned since they were built in the ’90s. Little improvements 161 over time and declining enrollment over the years have led parents to consider those public institutions as unfavorable places to send their kids to. Thermal perceptions and preferences among students and teachers fall within 80% to 90% acceptability (i.e., when asked directly and indirectly through votes calculations) and were mainly distributed within the three central categories of ASHRAE–7 point scale. Their thermal sensation votes had similar normal distributions, with no major differences among their means, except for teacher’s votes been skewed to the slightly cool side of the scale, during winter. As evidenced in the study, their thermal sensation votes do respond to outdoor conditions, i.e., when outdoor temperatures were lower, their votes move to the slightly cold part of the scale. This was more evident at the end of the fieldwork when outdoor temperatures were even lower. The latter proves that adaptation is related to outdoor conditions and that children, as well as adults, are aware of weather condition, as the adaptive model defines it. Even though outdoor and indoor temperatures are low compared to other studies, students (or their parents) and teachers in Chilean schools do accommodate for comfort, through clothing adaptations. Even with strict dress code policies, such as school uniforms, it was evident that their clothing values were significantly higher than in previous studies. Clo values from this study ranged between 0.95 and 1.24 in fall and winter for both students and teachers. However, as evidenced during the campaigns, many students and teachers wore parkas inside the classroom, scarves, mittens, and in some cases wool hats, in which clo values could reach as high as 1.66 to 1.86. 162 Another potential explanation for why students found thermal conditions comfortable, as noted in the literature, is that students have high metabolic rates and are involved in active school activities in which they are continually interacting with the outdoor environment, making them more aware of those conditions that are much different from those of an office setting where an adult is mostly in sedentary positions. As observed in fieldwork, students would instead prefer to feel a bit colder or cold, in order to get fresh outdoor air circulation to accommodate slightly stale or stale indoor air, due to their crowded classrooms and low ventilation rates. It was also acknowledged in the interviews that many teachers withstand cold thermal conditions in the classroom to accommodate for their students' thermal sensation, meaning, they will tolerate cold temperature by opening a window in cold days, so their students would not be feeling warm or hot, and the stuffiness of the environment would be reduced. This has not been evidenced in the literature, and it has been argued that classroom conditions are predominantly controlled and changed based on teachers' thermal sensation. However, this cannot be generalized for all the schools surveyed in this study. Nonetheless, it evidences the awareness that teachers have on their student's comfort and well-being. Perceptions of IAQ did show some differences between students and teachers. Study results showed that teachers are more sensitive to stuffy/stale conditions than children. This may result from children being permanent residents of their classroom environments. As mentioned before, primary school students in Chilean classrooms are 163 taught the majority of the subjects in the same classroom all day, for an entire year. Therefore, students get acclimated to unsatisfactory conditions, or as other authors have noted, children are not able to perceive or acknowledge poor conditions such as high CO2 concentration (Fisk, 2017; P. Wargocki & Da Silva, 2015). The latter raises even more concerns due to high concentrations to which they are exposed, and the fact that children might not always be able to report. Further research is required in this area to better understand the consequences on children of long-term exposure to poor IAQ conditions. On the other hand, teachers move around from one environment to another, thus explaining their sensitivity and awareness to poor air quality and also indoor temperatures. 3. Perceptions of children between school types do differ. Differences were observed between private-subsidize and public schools, and also between private-subsidize and private-nonsubsidized schools. These can be explained by the more modern construction solutions on the private-subsidized schools compare to the other schools and also by the available environmental opportunities to control classroom spaces. In terms of environmental adaptations, students, as well as teachers, have minimal opportunities to control their indoor classroom conditions, due to the lack of adaptive design strategies of school design. They are only limited to open or close windows and doors, to provide fresh air or change indoor temperatures. In all public schools, heating systems are not installed or in working condition to accommodate for cold winter temperatures. However, this was different in most private schools since they all have heating systems available in each classroom. As evidenced in 164 the field visits, heating systems, for the most part, are centrally controlled so teachers and students could not change the thermostat. Additionally, many schools heating system were not working correctly or were providing heat when it was no longer needed. The heating systems were very inefficient and affected the thermal perception of occupants. From focus group interviews and field observations, private school students were more outspoken about their classroom conditions than public school students and would ask the teacher to open/close windows, as well as, to make personal adaptations of clothing, or to bring hot drinks to their classroom to keep themselves warm. On the other hand, public school students were less outspoken about their classroom conditions to their teachers. This might be explained by their experience of emotional deprivation of childhood, due to their low–income social background as compared to the middle and high social backgrounds, which can be seen in both private schools. The latter needs to be further investigated to determine other factors that can influence their perception, as well as, their different means of adaptation. Overall, the methods implemented to survey this age group of children proved to be successful. Particularly, the use of tablets and measuring equipment helped to get students engaged in the survey activity. Data collection of physical measurements and surveys became a teaching moment for primary school children, especially in deprived backgrounds as these devices are not typical for children to see. Thus, field surveys became a great break and distraction to their regular classroom routine. However, as evidenced in the field campaigns, certain concepts and terminology can still be better improved. Children many times did not understand the concept of air movement, or 165 neutral. To answer these questions, the author provided feedback and explanation during the surveys, to help students to understand what was asked. 6.1. Future work Work in this area may be expanded in different ways. There are three suggestions that emerge and that I would like to pursue further from this research. Future work can evaluate classroom conditions in warmer outdoor temperature regimes, i.e., end of spring or end of the summer season, to determine what are the indoor classroom conditions and the different methods of adaptations that students and teacher take?. Because this study only looked at relatively cold outdoor temperatures, questions arise for what it could be the thermal sensation and preferences for students and teacher in warmer conditions. Would they respond the same as they did for this study?. The literature review suggests that children are more sensitive to warmer temperatures, but still manage to adapt to warmer outdoor temperatures, particularly in hot arid climate zones like the middle east. Deficient IAQ was found in all classrooms spaces, across all different school types. It raises questions about the concerning effects is can have on students’ performance, health, and well–being as evidenced in the literature. Future research should look at the effects of high particle and CO2 concentrations on students’ attendances and task performance to determine if associations exist, and what type of effects has on students and teacher. Due to the 2015 national declaration of a saturated zone for fine particle outdoor concentrations in the city of Concepción, a new plan for decontamination would be put in 166 place at the end of this year 2019. Therefore, it would be essential to provide a baseline to evaluate the impact of existing classroom conditions have on performance and health before this plan is put into place, to evaluate later how the implementation of the new plan can impact or not classroom conditions. As evidenced in the literature as well as in this study, indoor classroom conditions need re-conditioning and retrofitting. School building stock is outdated in terms of classroom design, with layouts from the '70s, that does not incorporate new teaching pedagogies, passive strategies that can provide better and efficient indoor conditions. From this study, new research can look at retrofitting strategies that can integrate all different environmental parameters. The integration of passive and active energy-efficient strategies should be further explored in classroom environments to provide solutions for how we can improve existing school buildings. The development of recommendations for new policy solutions that can address design and building operation of schools should take place. My intension is that this study and my future involvement in this matter can help to move forward to healthier, efficient Chilean schools. 167 APPENDIX A INSULATION CALCULATIONS Calculations of insulation cloth values of students’ uniforms 168 APPENDIX B INSULATION CALCULATIONS Calculations of insulation cloth values of students’ uniforms 169 APPENDIX C INSULATION CALCULATIONS Calculations of insulation cloth values of students’ uniforms 170 APPENDIX D INDOOR AIR QUALITY PROFILE MEASUREMENT Indoor Air quality profile measurements of CO2, during one school day school in the fall. 171 APPENDIX E INDOOR AIR QUALITY PROFILE MEASUREMENT Indoor Air quality profile measurements of PM2.5, and PM10 during one school day school in fall. 172 APPENDIX F IRB APPROVALS Notice of IRB Review and Approval, from the Committee for Protection of Human Subjects (CPHS), the University of Oregon Institutional Review Board (IRB). 173 174 175 APPENDIX G IRB APPROVALS Notice of IRB Review and Approval, from the Ethics Committee “Comité de Etica, Bioetica y Bioseguridad” of the Vicerrectoria de Investigación y Desarrollo, University of Concepción. 176 177 APPENDIX H QUESTIONNAIRE Student questionnaire example. 178 179 180 181 182 183 184 185 REFERENCES CITED Academie, J. V. E. (2006). Going aerial: air, art, architecture. (M. Bakkle, Ed.). Ahmed Abdul–Wahab, S. A., En, S. C. F., Elkamel, A., Ahmadi, L., & Yetilmezsoy, K. (2015). A review of standards and guidelines set by international bodies for the parameters of indoor air quality. Atmospheric Pollution Research, 6(5), 751–767. https://doi.org/10.5094/APR.2015.084 Al-hemoud, A. M. (2017). International Guidelines and Standards Pertaining to Indoor Air Quality, (April). Amato, F., Rivas, I., Viana, M., Moreno, T., Bouso, L., Reche, C., … Querol, X. (2014). Sources of indoor and outdoor PM2.5 concentrations in primary schools. Science of the Total Environment, 490, 757–765. https://doi.org/10.1016/j.scitotenv.2014.05.051 ASHRAE, ANSI/ASHRAE Standard 55-2004. Thermal Environmental Conditions for Human Occupancy. American Society of Heating, Refrigerating, and Air-Conditioning Engineers, Inc.: Atlanta, GA). ASHRAE, ANSI/ASHRAE Standard 55-2017. Thermal Environmental Conditions for Human Occupancy. American Society of Heating, Refrigerating, and Air-Conditioning Engineers, Inc.: Atlanta, GA). ASHRAE, ANSI/ASHRAE Standard 62.1-2016. Ventilation for acceptable indoor air quality. American Society of Heating, Refrigerating, and Air-Conditioning Engineers, Inc.: Atlanta, GA. ASHRAE, ANSI/ASHRAE 2017 ashrae handbook (Inch-pound ed., Vol. , fundamentals) [Inch-pound edition.]. Atlanta, GA: ASHRAE, 2017 ASHRAE-IWEC. (2001). International Weather for Energy Calculations (IWEC) Users Manual and CD-ROM. Atlanta: ASHRAE. Armijo, Whitman, C. (2011). Post-occupancy evaluation of state schools in 5 climatic zones of Chile. Gazi University Journal of Science, 24(2), 365–374. Auliciems, A. (1981). Towards a psycho-physiological model of thermal perception. International Journal of Biometeorology, 25(2), 109–122. https://doi.org/10.1007/BF02184458 Baker, L. (2011). Center for the Built Environment UC Berkeley. UC Berkeley. https://doi.org/10.1016/j.enbuild.2013.06.009.Keywords 186 Bakó-Biró, Z., Clements-Croome, D. J., Kochhar, N., Awbi, H. B., & Williams, M. J. (2012). Ventilation rates in schools and pupils’ performance. Building and Environment, 48(1), 215–223. https://doi.org/10.1016/j.buildenv.2011.08.018 Benzinger, T. (1979). The physiological basis for thermal comfort. Indoor Climate, 441– 476. Retrieved from https://scholar.google.com/scholar_lookup?title=The physiological basis for thermal comfort&publication_year=1979&author=T.H. Benzinger Bernstein, J. A., Alexis, N., Bacchus, H., Bernstein, I. L., Fritz, P., Horner, E., … Tarlo, S. M. (2008). The health effects of nonindustrial indoor air pollution. Journal of Allergy and Clinical Immunology, 121(3), 585–591. https://doi.org/10.1016/j.jaci.2007.10.045 Bluyssen, P. M., Roda, C., Mandin, C., Fossati, S., Carrer, P., de Kluizenaar, Y., … Bartzis, J. (2016). Self-reported health and comfort in “modern” office buildings: First results from the European OFFICAIR study. Indoor Air, 26(2), 298–317. https://doi.org/10.1111/ina.12196 Bluyssen, Philomena M. (2012). The Indoor Environment Handbook. Proceedings of the ICE - Engineering Sustainability (Vol. 165). https://doi.org/10.1680/ensu.10.00054 Brager, G., & Baker, L. (2009). Occupant satisfaction in mixed-mode buildings. Building Research and Information, 37(4), 369–380. https://doi.org/10.1080/09613210902899785 Brager, G. S., & de Dear, R. J. (1998). Thermal adaptation in the built environment: a literature review. Energy and Buildings, 27(1), 83–96. https://doi.org/10.1016/S0378- 7788(97)00053-4 Charles K. E. (2003). Fanger ’ s Thermal Comfort and Draught Models IRC Research Report RR-162. October. Ottawa. Chatzidiakou, L., Mumovic, D., & Dockrell, J. (2014). The Effects of Thermal Conditions and Indoor Air Quality on Health, Comfort and Cognitive Performance of Students Commissioned by: London. Chatzidiakou, L., Mumovic, D., & Summerfield, A. J. (2012). What do we know about indoor air quality in school classrooms? A critical review of the literature. [Online]. Available: http://www.tandfonline.com/doi/abs/10.1080/17508975.2012.725530, 4(4), 228–259. https://doi.org/10.1080/17508975.2012.725530 Chen, W. L., Shih, Y. C., & Chi, C. F. (2010). Hand and finger dexterity as a function of skin temperature, EMG, and ambient condition. Human Factors, 52(3), 426–440. https://doi.org/10.1177/0018720810376514 187 CIBSE. (2006). Environment Design. Freelancer’s Guide to Corporate Event Design: From Technology Fundamentals to Scenic and Environmental Design. https://doi.org/10.1016/B978-0-240-81224-3.00016-9 Clements-Croome, D. (2018). Creating the productive workplace : places to work creatively (Third ed.). London: Routledge, Taylor & Francis Group. Cui, W., Cao, G., Park, J. H., Ouyang, Q., & Zhu, Y. (2013a). Influence of indoor air temperature on human thermal comfort, motivation and performance. Building and Environment, 68, 114–122. https://doi.org/10.1016/j.buildenv.2013.06.012 Cui, W., Cao, G., Park, J. H., Ouyang, Q., & Zhu, Y. (2013b). Influence of indoor air temperature on human thermal comfort, motivation and performance. Building and Environment, 68, 114–122. https://doi.org/10.1016/j.buildenv.2013.06.012 Daisey, J. M., Angell, W. J., & Apte, M. G. (2003a). Indoor air quality, ventilation and health symptoms in schools: an analysis of existing information. Indoor Air, 13(1), 53– 64. https://doi.org/10.1034/j.1600-0668.2003.00153.x Daisey, J. M., Angell, W. J., & Apte, M. G. (2003b). Indoor air quality, ventilation and health symptoms in schools: an analysis of existing information. Indoor Air, 13(1), 53– 64. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/12608926 de Dear, & Brager. (1998). Developing an Adaptive Model of Thermal Comfort and Preference -RP 884 final report. ASHRAE Transactions, 104(March), 1–18. Retrieved from https://escholarship.org/content/qt4qq2p9c6/qt4qq2p9c6.pdf de Dear, R. J., Akimoto, T., Arens, E. A., Brager, G., Candido, C., Cheong, K. W. D., … Zhu, Y. (2013). Progress in thermal comfort research over the last twenty years. Indoor Air, 23(6), 442–461. https://doi.org/10.1111/ina.12046 de Dear, R, Brager, G., & Cooper, D. (1997). Developing an adaptive model of thermal comfort and preference - Final Report on RP-884. ASHRAE Transactions, 104(Part 1), 1–18. Retrieved from http://sydney.edu.au/architecture/documents/staff/richard_de_dear/RP884_Final_Repo rt.pdf%0Ahttp://escholarship.org/uc/item/4qq2p9c6.pdf de Dear, R, Kim, J., Candido, C., & Deuble, M. (2015). Adaptive thermal comfort in australian school classrooms. Building Research and Information, 43(3), 383–398. https://doi.org/10.1080/09613218.2015.991627 de Dear, R. (2004). Thermal comfort in practice. Indoor Air, 14(Suppl 7), 32-39. de Dear, R. (1998). A global database of thermal comfort field experiments. Field studies of thermal comfort and adaptation. ASHRAE Technical Data Bulletin 14, (January 1998), 15–26. 188 de Dear, R., & Brager, G. (2002). Thermal comfort in naturally ventilated buildings: revision to ASHRAE standards 55. Journal of Energy and Buildings, 34, 549–561. https://doi.org/10.1016/S0378-7788(02)00005-1 De Giuli, V., Da Pos, O., & De Carli, M. (2012). Indoor environmental quality and pupil perception in Italian primary schools. Building and Environment, 56, 335–345. https://doi.org/10.1016/j.buildenv.2012.03.024 EN15251, B. E. 15251:2007. (2007). EN 15251 - Indoor environmental input parameters for design and assessment of energy performance of buildings addressing indoor air quality, thermal environment, lighting and acoustics (Vol. 3). Enander, A. E., & Hygge, S. (1990). Thermal stress and human performance. Scandinavian Journal of Work, Environment and Health, 16(SUPPL. 1), 44–50. https://doi.org/10.5271/sjweh.1823 EPA. (2016). NAAQS Table. Retrieved August 28, 2019, from https://www.epa.gov/criteria- air-pollutants/naaqs-table Fabbri, K. (2013). Thermal comfort evaluation in kindergarten: PMV and PPD measurement through datalogger and questionnaire. Building and Environment, 68, 202–214. https://doi.org/10.1016/j.buildenv.2013.07.002 Fabbri, K. (2015). Indoor thermal comfort perception : a questionnaire approach focusing on children. Berlin : Springer. Falk, B. (1998). Effects of thermal stress during rest and exercise in the paediatric population. Sports Medicine, 25(4), 221–240. Fanger, P. O. (1970). Thermal comfort: Analysis and applications in environmental engineering. Applied Ergonomics. Danmarks Tekniske Høojskole, McGraw Hill Book Company, USA. https://doi.org/10.1016/s0003-6870(72)80074-7 Fisk, W. J. (2017). The ventilation problem in schools: Literature review. Indoor Air, (June), 1–13. https://doi.org/10.1111/ina.12403 Fisk, W. (2002). How IEQ affects health, productivity. ASHRAE Journal, 44(5), 56–58. Frumkin, H. (2006). Safe and healthy school environments. Oxford University Press. Griffiths, I. D. (1991). Thermal comfort in buildings with passive solar features : field studies. (C. of the E. Communities, Ed.). Euratom publications - eur, 13431. Retrieved from https://uolibraries.on.worldcat.org/search?queryString=no%3A+59990090#/oclc/5999 0090 189 Haddad, S., King, S., Osmond, P., & Heidari, S. (2012). Questionnaire Design to Determine Children’s Thermal Sensation, Preference and Acceptability in the Classroom. Proceedings of 28th PLEA Conference, 1(November), 2. Haddad, Shamila. (2016). Thermal Comfort in Naturally Ventilated Schools. The University of New South Wales. Haddad, Shamila, Osmond, P., & King, S. (2013). Metabolic rate estimation in the calculation of the pmv for children. 47th International Conference of the Architectural Science Association, 241–250. Haddad, Shamila, Osmond, P., & King, S. (2017a). Revisiting thermal comfort models in Iranian classrooms during the warm season. Building Research and Information, 45(4), 457–473. https://doi.org/10.1080/09613218.2016.1140950 Haddad, Shamila, Osmond, P., & King, S. (2017b). Revisiting thermal comfort models in Iranian classrooms during the warm season. Building Research and Information, 45(4), 457–473. https://doi.org/10.1080/09613218.2016.1140950 Haddad, Shamila, Osmond, P., & King, S. (2019). Application of adaptive thermal comfort methods for Iranian schoolchildren. Building Research and Information, 47(2), 173– 189. https://doi.org/10.1080/09613218.2016.1259290 Halawa, E., & Van Hoof, J. (2012). The adaptive approach to thermal comfort: A critical overview. Energy and Buildings, 51, 101–110. https://doi.org/10.1016/j.enbuild.2012.04.011 Havenith, G. (2007). Metabolic rate and clothing insulation data of children and adolescents during various school activities. Ergonomics, 50(10), 1689–1701. https://doi.org/10.1080/00140130701587574 Haverinen-Shaughnessy, U., & Shaughnessy, R. J. (2015). Effects of classroom ventilation rate and temperature on students’ test scores. PLoS ONE, 10(8), 1–14. https://doi.org/10.1371/journal.pone.0136165 Haverinen-Shaughnessy, U., Shaughnessy, R. J., Cole, E. C., Toyinbo, O., & Moschandreas, D. J. (2015). An assessment of indoor environmental quality in schools and its association with health and performance. Building and Environment, 93(P1), 35–40. https://doi.org/10.1016/j.buildenv.2015.03.006 Hensen, J. L. M. (1991). On the thermal interaction of building structure and heating and ventilation system - (Dissertation) - Technische Universiteit Eindhoven, Netherlands. Heschong, L. (1979). Thermal delight in architecture. Cambridge, Mass: MIT Press. Humphreys, Michael, F. N. (1998). Understandng the adaptive approach to Thermal Comfort. ASHRAE Transactions, 1–14. 190 Humphreys, M. A., & Nicol, J. F. (2002a). Adaptive thermal comfort and sustainable thermal standards for buildings. Energy and Buildings, 34(6), 563–572. https://doi.org/10.1016/S0378-7788(02)00006-3 Humphreys, M. A., & Nicol, J. F. (2002b). The validity of ISO-PMV for predicting comfort votes in every-day thermal environments. Energy and Buildings, 34(6), 667–684. Humphreys, M. A., Rijal, H. B., & Nicol, J. F. (2013). Updating the adaptive relation between climate and comfort indoors; new insights and an extended database. Building and Environment, 63, 40–55. https://doi.org/10.1016/j.buildenv.2013.01.024 Hussein, I, & Rahman, M. H. A. (2009). Field study on thermal comfort in Malaysia. European Journal of Scientific Research, 37(1), 134–152. Retrieved from https://www.scopus.com/inward/record.uri?eid=2-s2.0- 70449090056&partnerID=40&md5=108f979d4c4d7f32bc1cd09a9e0895a7 Hussein, Ibrahim, Rahman, M. H. A., & Maria, T. (2009). Field studies on thermal comfort of air-conditioned and non air-conditioned buildings in Malaysia. ICEE 2009 - Proceeding 2009 3rd International Conference on Energy and Environment: Advancement Towards Global Sustainability, (December), 360–368. https://doi.org/10.1109/ICEENVIRON.2009.5398622 ISO 10551. (1995). ISO 10551 Ergonomics of the thermal environment–Assessment of the influence of the thermal environment using subjective judgement scales, 1–20. ISO 7726. (2001). ISO 7726 Ergonomics of the thermal environment — Instruments for measuring physical quantities. Bs En Iso 7726:2001, (1), 1–62. https://doi.org/10.3403/02509505 ISO 7730. (2005). ISO 7730 Ergonomics of the thermal environment - analytical determination and interpretation of thermal comfort using calculation of the PMV and PPD indices and local thermal comfort criteria. ISO 8996. (2004). ISO 8996: 2004(E) Ergonomics of the thermal environment — Determination of metabolic rate, 1–21. https://doi.org/10.1016/j.jssc.2008.03.003 Joost van Hoof, Mitja Mazej, J. L. M. H. (2010). Thermal comfort: research and practice. Frontiers in Bioscience, 15(2), 765–788. Kim, J., & de Dear, R. (2018a). Thermal comfort expectations and adaptive behavioural characteristics of primary and secondary school students. Building and Environment, 127(September), 13–22. https://doi.org/10.1016/j.buildenv.2017.10.031 Kim, J., & de Dear, R. (2018b). Thermal comfort expectations and adaptive behavioural characteristics of primary and secondary school students. Building and Environment, 127(October), 13–22. https://doi.org/10.1016/j.buildenv.2017.10.031 191 Klepeis, N. E., Nelson, W. C., Ott, W. R., Robinson, J. P., Tsang, A. M., Switzer, P., … Engelmann, W. H. (2001). The National Human Activity Pattern Survey. Lawrence Berkeley National Laboratory, 11(3), 231–252. https://doi.org/10.1038/sj.jea.7500165 T4 - A resource for assessing exposure to environmental pollutants Y3 - 20/2/2017 U6 - 10.1038/sj.jea.7500165 M4 - Citavi Korsavi, S. S., & Montazami, A. (2019). Developing a valid method to study adaptive behaviours with regard to IEQ in primary schools. Building and Environment, 153(February), 1–16. https://doi.org/10.1016/j.buildenv.2019.02.018 Kosonen, R., & Tan, F. (2004). Assessment of productivity loss in air-conditioned buildings using PMV index. Energy and Buildings, 36(10 SPEC. ISS.), 987–993. https://doi.org/10.1016/j.enbuild.2004.06.021 Kovats, R. S., & Hajat, S. (2008). Heat Stress and Public Health: A Critical Review. Annual Review of Public Health, 29(1), 41–55. https://doi.org/10.1146/annurev.publhealth.29.020907.090843 Kwok, A. G. (1997). Thermal comfort in naturally-ventilated and air-conditioned classrooms in the tropics. UC Berkeley. Lan, L., Wargocki, P., & Lian, Z. (2011). Quantitative measurement of productivity loss due to thermal discomfort. Energy and Buildings, 43(5), 1057–1062. https://doi.org/10.1016/j.enbuild.2010.09.001 Leeuw, E. D. de. (2001). Reducing Missing Data in Surveys: An Overview of Methods. Quality and Quantity, 35(2), 147–160. https://doi.org/10.1023/A:1010395805406 Lundgren, K., Kuklane, K., Gao, C., & Holmér, I. (2013). Effects of Heat Stress on Working Populations when Facing Climate Change. Industrial Health, 51(1), 3–15. https://doi.org/10.2486/indhealth.2012-0089 Mansour, S. (2014). Indoor Air Quality in Schools: An investigation of the impact of outdoor air quality, school layout, and room type. The University of Texas at Arlington, University of Texas at Arlington, United States. McCartney K, J., & Nicol J, F. (2002). Developing an adaptive control algorithm for {Europe}: results of the {SCATs} {Project}. Energy and Buildings, 34, 623. Mendell, M., Eliseeva, E., Davies, M, Spears, M., Lobscheid, A., Fisk, W., & Apte, M. (2013). Association of classroom ventilation with reduced illness absence: a prospective study in California elementary schools. Indoor Air, 23, 515–528. https://doi.org/IO.IIII/illu.12042 192 Mendell, M. J., Eliseeva, E. A., Davies, M. M., & Lobscheid, A. (2016). Do classroom ventilation rates in California elementary schools influence standardized test scores? Results from a prospective study. Indoor Air, 26(4), 546–557. https://doi.org/10.1111/ina.12241 Mendell, M. J., Eliseeva, E. A., Davies, M. M., Spears, M., Lobscheid, A., Fisk, W. J., & Apte, M. G. (2013). Association of classroom ventilation with reduced illness absence: A prospective study in California elementary schools. Indoor Air, 23(6), 515–528. https://doi.org/10.1111/ina.12042 Mendell, M. J., & Heath, G. A. (2005). Do indoor pollutants and thermal conditions in schools influence student performance? A critical review of the literature. Indoor Air, 15(1), 27–52. https://doi.org/10.1111/j.1600-0668.2004.00320.x MINEDUC. (2016). OECD Review of Policies to Improve the Effectiveness of Resource Use in Schools: Country Background Report for Chile, 3(3), 317. https://doi.org/10.1787/9789264256729-en Ministerio del Medio Ambiente de Chile (MMA). (2015). Declara Zona Saturada Por Material Particulado Fino Respirable Mp2,5 Como Concentración Diaria, A Las Comunas De Lota, Coronel, San Pedro De La Paz, Hualqui, Chiguayante, Concepción, Penco, Tomé, Hualpén Y Talcahuano. Https://Doi.Org/10.1145/1542130.1542154 Mishra, A. K., & Ramgopal, M. (2013). Field studies on human thermal comfort - An overview. Building and Environment, 64, 94–106. https://doi.org/10.1016/j.buildenv.2013.02.015 Mohammadyan, M., Alizadeh-Larimi, A., Etemadinejad, S., Latif, M. T., Heibati, B., Yetilmezsoy, K., … Dadvand, P. (2017). Particulate air pollution at schools: Indoor- outdoor relationship and determinants of indoor concentrations. Aerosol and Air Quality Research, 17(3), 857–864. https://doi.org/10.4209/aaqr.2016.03.0128 Montazami, A., Gaterell, M., Nicol, F., Lumley, M., & Thoua, C. (2017a). Developing an algorithm to illustrate the likelihood of the dissatisfaction rate with relation to the indoor temperature in naturally ventilated classrooms. Building and Environment, 111, 61–71. https://doi.org/10.1016/j.buildenv.2016.10.009 Montazami, A., Gaterell, M., Nicol, F., Lumley, M., & Thoua, C. (2017b). Impact of social background and behaviour on children’s thermal comfort. Building and Environment, 122, 422–434. https://doi.org/10.1016/j.buildenv.2017.06.002 Montazami, A., Gaterell, M., Nicol, F., Lumley, M., & Thoua, C. (2017c). Impact of social background and behaviour on children’s thermal comfort. Building and Environment, 122, 422–434. https://doi.org/10.1016/j.buildenv.2017.06.002 193 Mors, T., Hensen, Loomans, & Boerstra. (2011). Adaptive thermal comfort in primary school classrooms: Creating and validating PMV-based comfort charts. Building and Environment, 46(12), 2454–2461. https://doi.org/10.1016/j.buildenv.2011.05.025 Mors ter, S., Hensen, J. L. M., Loomans, M. G. L. C., & Boerstra, A. C. (2011). Adaptive thermal comfort in primary school classrooms: Creating and validating PMV-based comfort charts. Building and Environment, 46(12), 2454–2461. https://doi.org/10.1016/j.buildenv.2011.05.025 Nicol, F., & Humphreys, M. (2010). Derivation of the adaptive equations for thermal comfort in free-running buildings in European standard EN15251. Building and Environment, 45(1), 11–17. https://doi.org/10.1016/j.buildenv.2008.12.013 Nicol, F., Humphreys, M. A. (Michael A., & Roaf, S. (2012). Adaptive thermal comfort : principles and practice. London ; Routledge. Retrieved from https://uolibraries.on.worldcat.org/search?databaseList=638&queryString=Adaptive+T hermal+Comfort%3A+Principles+and+Practice%2C+by+Fergus+Nicol%2C+Michael +Humphreys%2C+Susan+Roaf+#/oclc/730403966 Nicol, & Humphreys. (2002). Adaptive thermal comfort and sustainable thermal standards for buildings. Energy and Buildings, 34(6), 563–572. https://doi.org/10.1016/S0378- 7788(02)00006-3 Nicol, J. F., & Humphreys, M. A. (2009). New standards for comfort and energy use in buildings. Building Research and Information, 37(1), 68–73. https://doi.org/10.1080/09613210802611041 Nicol, J. Fergus, Humphreys, M. A., & Olesen, B. (2004). A stochastic approach to thermal comfort - Occupant behavior and energy use in buildings. ASHRAE Transactions, 110 PART I(January), 554–568. Pagels, P., Raustorp, A., Guban, P., Fröberg, A., & Boldemann, C. (2016). Compulsory school in- and outdoors—implications for school children’s physical activity and health during one academic year. International Journal of Environmental Research and Public Health, 13(7). https://doi.org/10.3390/ijerph13070699 Park, J. (2015). Are Humans Good Sensors? Using Occupants as Sensors for Indoor Environmental Quality Assessment and for Developing Thresholds that Matter. Carnegie Mellon University, Research Showcase CMU, 2016. Parsons, K. C. (Kenneth C. . (2003). Human thermal environments : the effects of hot, moderate, and cold environments on human health, comfort, and performance (2nd ed). London: Taylor & Francis. Parsons, K. C. (Kenneth C. . (2014). Human thermal environments : the effects of hot, moderate, and cold environments on human health, comfort, and performance (Third). Taylor & Francis. 194 Passe, U., & Battaglia, F. (2015). Designing spaces for natural ventilation : an architect’s guide (1st ed.). Routledge, Taylor & Francis Group. Petersen, S., Jensen, K. L., Pedersen, A. L. S., & Rasmussen, H. S. (2016). The effect of increased classroom ventilation rate indicated by reduced CO2 concentration on the performance of schoolwork by children. Indoor Air, 26(3), 366–379. https://doi.org/10.1111/ina.12210 Pierpaoli, M., & Ruello, M. (2018). Indoor Air Quality: A Bibliometric Study. Sustainability, 10(11), 3830. https://doi.org/10.3390/su10113830 Qualtrics. (2005). Qualtrics. Provo, Utah, USA. Rijal, Tuohy, Humphreys, Nicol, and S. (2012). Considering the impact of situation- specific motivations and constraints in the design of naturally ventilated and hybrid buildings. Architectural Science Review, 55(1), 1–71. Rovelli, S., Cattaneo, A., Nuzzi, C. P., Spinazzè, A., Piazza, S., Carrer, P., & Cavallo, D. M. (2014). Airborne particulate matter in school classrooms of northern Italy. International Journal of Environmental Research and Public Health, 11(2), 1398–1421. https://doi.org/10.3390/ijerph110201398 Rupp, R. F., Vásquez, N. G., & Lamberts, R. (2015). A review of human thermal comfort in the built environment. Energy and Buildings, 105, 178–205. https://doi.org/10.1016/j.enbuild.2015.07.047 Salthammer, T., Uhde, E., Schripp, T., Schieweck, A., Morawska, L., Mazaheri, M., … Kumar, P. (2016). Children’s well-being at schools: Impact of climatic conditions and air pollution. Environment International, 94, 196–210. https://doi.org/10.1016/j.envint.2016.05.009 Santamouris, M., & Wouters, P. (2006). Building ventilation : the state of the art. London: Earthscan. Santiago, P., Fiszbein, A., García Jaramillo, S., & Radinger, T. (2017). OECD Reviews of School Resources: Chile 2017. https://doi.org/10.1787/9789264285637-en Schiavon, S., Hoyt, T., & Piccioli, A. (2014). Web application for thermal comfort visualization and calculation according to ASHRAE Standard 55. Building Simulation, 7(4), 321–334. https://doi.org/10.1007/s12273-013-0162-3 Schweiker, M. (2016). comf: An R Package for Thermal Comfort Studies. The R Journal, 8(2), 341–351. https://doi.org/10.32614/rj-2016-050 195 Seppanen, Fisk, and M. (1999). Association of ventilation rates and CO2 concentrations with health and other responses in commercial and institutional buildings. Indoor Air, (9), 226–255. Retrieved from https://www.pdx.edu/green- building/sites/www.pdx.edu.green-building/files/Seppanen association between ventilation and co2.pdf Seppänen, O., Fisk, M. (1999). Association of Ventilation Rates and CO2 Concentrations with Health and Other Responses in Commercial and Institutional Buildings. Indoor Air, 9, 226–252. Seppänen, O. (2006). The Effect of Ventilation on Health and Other Human Responses. Routledge. Retrieved from https://www.taylorfrancis.com/books/e/9781849770620/chapters/10.4324/97818497 70620-12 Seppänen, O., Fisk, W. J., & Lei, Q. H. (2005). Ventilation and performance in office work. Indoor Air, 16(1), 28–36. https://doi.org/10.1111/j.1600-0668.2005.00394.x Shaughnessy, R. J., Haverinen-Shaughnessy, U., Nevalainen, A., & Moschandreas, D. (2006). A preliminary study on the association between ventilation rates in classrooms and student performance. Indoor Air, 16(6), 465–468. https://doi.org/10.1111/j.1600- 0668.2006.00440.x Shendell, D. G., Prill, R., Fisk, W. J., Apte, M. G., Blake, D., & Faulkner, D. (2004). Associations between classroom CO2 concentrations and student attendance in Washington and Idaho. Indoor Air, 14(5), 333–341. https://doi.org/10.1111/j.1600- 0668.2004.00251.x Smedje, G., & Norbäck, D. (2000). New Ventilation Systems at Select Schools in Sweden—Effects on Asthma and Exposure. Archives of Environmental Health, 55(1), 18–25. https://doi.org/10.1080/00039890009603380 Soto, J., Trebilcock, M., & Pérez, A. (2015). 342 : Sustainable educational buildings A proposal for changes to investment evaluation policies in Chile through the incorporation of thermal comfort and air quality criteria. In 14th International Conference on Sustainable Energy Technologies (pp. 1–10). Nottingham. Spengler, J. D., McCarthy, J. F., & Samet, J. M. (2001). Indoor air quality handbook. McGraw-Hill. Teli, D. (2013). Thermal performance and occupant comfort in naturally ventilated UK junior schools outside the heating season. University of Southampton. Teli, D., James, P. A. B., & Jentsch, M. F. (2013). Thermal comfort in naturally ventilated primary school classrooms. Building Research and Information, 41(3), 301–316. https://doi.org/10.1080/09613218.2013.773493 196 Teli, D., James, P. A. B., & Jentsch, M. F. (2015). Investigating the principal adaptive comfort relationships for young children. Building Research and Information, 43(3), 371–382. https://doi.org/10.1080/09613218.2015.998951 Teli, D., Jentsch, M. F., & James, P. A. B. (2012). Naturally ventilated classrooms: An assessment of existing comfort models for predicting the thermal sensation and preference of primary school children. Energy and Buildings, 53, 166–182. https://doi.org/10.1016/j.enbuild.2012.06.022 Teli, D., Jentsch, M. F., James, P. A. B., & Bahaj, A. S. (2012). Field study on thermal comfort in a UK primary school. 7th Windsor Conference, 7730(April), 12–15. Toftum, J., & Ole Fanger, P. (2002). Extension of the PMV model to non-air-conditioned buildings in warm climates. Energy and Buildings, 34(6), 533–536. https://doi.org/10.1016/S0378-7788(02)00003-8 Trebilcock, M., Bobadilla, A., Piderit, B., Figueroa, R., Muñoz, C., Sanchez, R., … Hernández, J. (2012). Environmental Performance of Schools in Areas of Cultural Sensitivity. PLEA2012 - 28th Conference, Opportunities, Limits & Needs Towards an Environmentally Responsible Architecture, (November), 7–12. Trebilcock, M., Piderit, B., Diaz, M., Hatt, T., Figueroa, R., Besser, D., … Arriagada, R. (2013). Parametric Analysis of School Classroom Typologies ’ Energy Performance. PLEA2013 - 29th Conference, Sustainable Architecture for a Renewable Future, (September). Trebilcock, M., Piderit, B., Soto, J., & Figueroa, R. (2016). A parametric analysis of simple passive strategies for improving thermal performance of school classrooms in Chile. Architectural Science Review, 8628(March), 1–15. https://doi.org/10.1080/00038628.2016.1150251 Trebilcock, M., Soto-Muñoz, J., Yañez, M., & Figueroa-San Martin, R. (2017a). The right to comfort: A field study on adaptive thermal comfort in free-running primary schools in Chile. Building and Environment, 114, 455–469. https://doi.org/10.1016/j.buildenv.2016.12.036 Trebilcock, M., Soto-Muñoz, J., Yañez, M., & Figueroa-San Martin, R. (2017b). The right to comfort: A field study on adaptive thermal comfort in free-running primary schools in Chile. Building and Environment, 114, 455–469. https://doi.org/10.1016/j.buildenv.2016.12.036 Trebilcock, M., Soto, J., & Figueroa, R. (2012). Thermal comfort in primary schools : a field study in Chile. Proceedings of 8th Windsor Conference: Counting the Cost of Comfort in a Changing World Cumberland Lodge, Windsor, UK, 10-13 April 2014, (April 2014), 10–13. 197 Turunen, M., Toyinbo, O., Putus, T., Nevalainen, A., Shaughnessy, R., & Haverinen- shaughnessy, U. (2014). International Journal of Hygiene and Indoor environmental quality in school buildings , and the health and wellbeing of students, 217, 733–739. US EPA. (n.d.). Introduction to Indoor Air Quality. Retrieved June 8, 2019, from https://www.epa.gov/indoor-air-quality-iaq/introduction-indoor-air-quality Van Hoof, J. (2008). Forty years of Fanger’s model of thermal comfort: Comfort for all? Indoor Air, 18(3), 182–201. https://doi.org/10.1111/j.1600-0668.2007.00516.x Van Kann, D., De Vries, S., Schipperijn, J., De Vries, N., Jansen, M., & Kremers, S. (2016). Schoolyard characteristics, physical activity, and sedentary behavior: Combining gps and accelerometry. Journal of School Health, 86(12), 913-921. doi:10.1111/josh.12459 van Maanen, L., van der Mijn, R., van Beurden, M. H. P. H., Roijendijk, L. M. M., Kingma, B. R. M., Miletić, S., & van Rijn, H. (2019). Core body temperature speeds up temporal processing and choice behavior under deadlines. Scientific Reports, 9(1), 1– 12. https://doi.org/10.1038/s41598-019-46073-3 Wargocki, P., & Da Silva, N. A. F. (2015). Use of visual CO2 feedback as a retrofit solution for improving classroom air quality. Indoor Air, 25(1), 105–114. https://doi.org/10.1111/ina.12119 Wargocki, Pawel, & Wyon, D. P. (2006). Effects of HVAC on student performance. ASHRAE Journal, 48(10), 22–28. Wargocki, Pawel, & Wyon, D. P. (2007). The Effects of Outdoor Air Supply Rate and Supply Air Filter Condition in Classrooms on the Performance of Schoolwork by Children. HVAC&R Research, 13(March 2007), 165–191. https://doi.org/10.1080/10789669.2007.10390950 Wargocki, Pawel, & Wyon, D. P. (2013a). Providing better thermal and air quality conditions in school classrooms would be cost-effective. Building and Environment, 59, 581–589. https://doi.org/10.1016/j.buildenv.2012.10.007 Wargocki, Pawel, & Wyon, D. P. (2013b). Providing better thermal and air quality conditions in school classrooms would be cost-effective. Building and Environment, 59, 581–589. https://doi.org/10.1016/j.buildenv.2012.10.007 Wargocki, Pawel, & Wyon, D. P. (2016). Ten questions concerning thermal and indoor air quality effects on the performance of office work and schoolwork. Building and Environment, 112, 2–9. https://doi.org/10.1016/j.buildenv.2016.11.020 198 Wargocki, Pawel, Wyon, D. P., Sundell, J., Clausen, G., & Fanger, P. O. (2000). The effects of outdoor air supply rate in an office on perceived air quality, sick building syndrome (SBS) symptoms and productivity. Indoor Air, 10(4), 222–236. https://doi.org/10.1034/j.1600-0668.2000.010004222.x WHO. (2005). Air Quality Guidelines - Particulate matter, ozone, nitrogen dioxide and sulfur dioxide. World Health Organization, (4), 1–483. WHO. (2010). WHO Guidelines for indoor air quality, selected pollutants. World Health Organization, 2(1), 1–444. https://doi.org/10.1177/156482658000200103 Willem, H. C. (2006). Thermal and indoor air quality effects on physiological responses, perception and performance of tropically acclimatized people. National University of Singapore. World Health Organization, & WHO Regional Office for Europe. (2010). WHO guidelines for indoor air quality. Nutrition Journal, 484. https://doi.org/10.1186/2041-1480-2-S2- I1 Yun, G. Y., & Steemers, K. (2007). Time-dependent occupant behaviour models of window control in summer. Building and Environment, 43(9), 1471–1482. https://doi.org/10.1016/j.buildenv.2007.08.001 Zeiler, W., & Boxem, G. (2009). Effects of thermal activated building systems in schools on thermal comfort in winter. Building and Environment, 44(11), 2308–2317. https://doi.org/10.1016/j.buildenv.2009.05.005 Zhang, F., & de Dear, R. (2017). University students’ cognitive performance under temperature cycles induced by direct load control events. Indoor Air, 27(1), 78–93. https://doi.org/10.1111/ina.12296 Zomorodian, Z. S., Tahsildoost, M., & Hafezi, M. (2016a). Thermal comfort in educational buildings: A review article. Renewable and Sustainable Energy Reviews, 59, 895–906. https://doi.org/10.1016/j.rser.2016.01.033 Zomorodian, Z. S., Tahsildoost, M., & Hafezi, M. (2016b). Thermal comfort in educational buildings: A review article. Renewable and Sustainable Energy Reviews, 59, 895–906. https://doi.org/10.1016/j.rser.2016.01.033 199