Sustainable educational buildings

Sustainable educational buildings A proposal for changes to investment evaluation policies in Chile through the incorporation of thermal comfort and air quality criteria JAIME SOTO-MUÑOZ1, MAUREEN TREBILCOCK2, ALEXIS PÉREZ-FARGALLO3

1

Universidad del Bío-Bío, Departamento de Ciencias de la Construcción, Collao 1202, Concepción, Chile, [email protected] 2 Universidad del Bío-Bío, Departamento de Teoría y Diseño de la Arquitectura, Collao 1202, Concepción, Chile, [email protected] 3 Universidad de Sevilla, Departamento de Construcciones Arquitectónicas II, Avda. Reina Mercedes, 4 A, 41012Sevilla. España, [email protected]

The constructive configuration of an educational institution influences its indoor comfort variables; while at the same time comfort variables have an effect on the metabolism and stress of students and teachers. In turn, each architectural project depends on the factors that define its design. When the investment is assessed, costs are determined to compare alternative architectural strategies for the project. However, public policies in most countries in Latin America do not consider factors related to thermal comfort or air quality in their educational indicators since it has not been possible to gauge the effect of physical variables on school outcomes in the Southern Cone. This study addresses the current constructive reality of public schools located in different geographic areas of Chile. Data was obtained on temperature, humidity, CO2 concentration and other indicators of environmental conditions using sensors installed in 4th-grade classrooms in summer and winter. Fieldwork demonstrated that the quality of the indoor environment in schools is deficient and therefore it is necessary to establish strategies for economic evaluation when heating and cooling systems are not present. Taking into consideration this information, Chilean state policies and methods of investment evaluation were reviewed. Mandatory criteria were determined and a proposal for public policy improvements was developed that integrates indicators and monitoring of student productivity and energy efficiency variables based on the data collected. This has the potential to encourage energy savings and increase understanding of the value of an optimal indoor environment that includes thermal comfort and air quality as factors conducive to better learning. If these comfort parameters are adequate, they will positively influence the development of education in regards to student productivity and learning.

Keywords: educational buildings, sustainability, energy and environmental policies, educational indicators, indoor environmental comfort.

14th International Conference on Sustainable Energy Technologies – SET 2015 25th - 27th of August 2015, Nottingham, UK

INTRODUCTION Sustainability has been considered as a way forward since the United Nations Conference on Environment and Development held in Rio de Janeiro in 1992. As a result, the energy performance of buildings has become especially relevant in the international arena in order to reduce consumption and CO 2 emissions. Accordingly, sustainable schools take into consideration the integration of social, economic and environmental concepts; under this logic, educational buildings use resources during construction and operation in more efficient and less polluting manners than buildings that meet minimum construction requirements. They also use more natural light, and have better air quality and generally superior indoor comfort conditions; thus, these buildings contribute to better learning and student health, thereby improving the productivity of classroom activities (Wargocki & Wyon, 2013). However, in most Latin American countries, policies on the social evaluation of public investment projects for new building or renovation have not changed to include the value of sustainable construction. These social evaluation policies give evidence of different criteria using methodological manuals with specific procedures. According to Candia, Perrotti and Aldunate (2015), in 2010, the Network of National Public Investment Systems (SNIP Network) was created to improve the management of public investment in 15 countries and has subsequently made contributions to different national systems. In Chile, the social evaluation of projects is understood as the act of determining whether to execute a project from the perspective of society as a whole, considering the positive and negative effects the project has on other economic agents. Although the procedures for the evaluation of investment in building projects do not take into consideration sustainability issues, in recent decades there has been a public effort incorporate the value of energy efficiency and indoor environmental quality into the design, construction and life cycle of buildings. In this sense, the weaknesses in the evaluation of investment in design strategies and their incorporation into building designs require changes in the way benefits are valued by the population. For example, in the case of educational buildings, students and teachers require the inclusion of thermal comfort and air quality in classroom design and construction. Thermal comfort is defined as satisfaction with the thermal environment and is a subjective decision (ASHRAE, 2010). In this regard, in Chile, Supreme Decree 548 is the main document governing educational infrastructure; it establishes the different areas within an educational establishment and gives requirements for both the design and construction of these buildings. This decree establishes the minimum standards of comfort for educational institutions, but makes no mention of how these requirements should be tested or 3 verified. In particular, CO2 concentration levels in classrooms are not established, only the requirement of 3 m of air per person, which is only partially complied with in the country. In 2012, terms of reference were developed by the Chilean 2 Energy Efficiency Agency that modify the criteria to an airflow greater than 5 l/s/pp or 0.6 l/s/m . References such as the British Building Bulletin 101: Ventilation of School Buildings (BB 101) and the American ASHRAE standard 62.1-2013, Ventilation for Acceptable Indoor Air Quality are used, but informally. Previously, international studies have detected amounts of up to 5,000 ppm in classrooms, in comparison with the average outdoor CO 2 level worldwide of just 360 ppm (Mumovi, 2009). CO2 concentrations above 1,000 ppm can produce negative effects on humans such as decreased attention span and reaction times (Bako-Biro, 2012). However, temperature is the most influential variable in the sensation of comfort in an enclosed area according to studies by Lee (2012). Men and women are affected in distinct manners and cold and hot ambient temperatures produce different effects. Heat decreases overall performance in activities and produces the physiological response of perspiration, while cold causes a reduction in motor skills and in the speed of task completion. To calculate temperature, there are two complementary approaches: adaptive thermal limits and the Fanger method (de Dear & Brager, 2002). Thermal comfort has gained a position in the country as a result of the emergence of environmental conditioning techniques. In the case of educational buildings, said techniques translate into more comfortable classrooms. However, models are not used to evaluate the performance of thermal comfort or air quality in schools. From Yaglou (1923) through Fanger (1970), these physical variables have come to be recognized in buildings, and only now in the present are there methods for evaluating the variables that influence man-environment thermal exchanges. This assessment makes it possible to identify wellbeing and measure the costs/benefits of an investment project in educational building. Nevertheless, in Chile, the Ministry of Social Development's Division of Social Evaluation (MIDESO), when using the National Investment System (SNI) in order to make a decision on investment or the technical-economic convenience of executing a project, does not establish sustainability criteria in its public profitability procedures, such as saving energy by including energy efficiency in passive strategies in the envelope or having better air quality inside classrooms. Internationally, advanced tools exist and are used to quantify the impact of the incorporation of energy efficiency in buildings. Almost without exception, these use two methodologies currently recognized to be universal, as a base to define their objectives, criteria, standards, databases, and assessment procedures, among others. The first is referred to as Life Cycle Assessment (LCA), which mainly focuses on the study of environmental impact throughout the life of a product, from the cradle to the grave; the second, called Life Cycle Cost (LCC), is used more in the assessment of the total cost of an asset over time, including its acquisition, operation, maintenance and deconstruction costs. Their use is supported by scientific backing and standards from recognized international bodies such as the International Organization for Standardization (ISO) and the American Society for Testing and Materials (ASTM). Countries are organized and their policies made based on observations of reality, and the observable evolution of quality of life and sustainability indicators. The existence of psychological, cultural and social factors in Latin American schools suggests that concepts of well-being in the classroom and not just corporate-economic principles should be taken into consideration. This is directly related to the obligations assumed by Latin American states in the Declaration of the Rights of the Child (1959) and updated in the 2002 special session of the United Nations "A World Fit for Children". In this regard, the social vulnerability factor in Chilean schools is taken into consideration with the School Vulnerability Index SOTO MUÑOZ, TREBILCOCK, PEREZ FARGALLO_342 2


(IVE) indicator. This is part of the National System for the Equitable Allocation of Scholarships from the National Student Aid and Scholarship Board (JUNAEB), which was created in the 1960s to support educational efforts in the country. The IVE does not explain vulnerability, but rather each year generates information for educational support programs. For example, these include access to free meals in the most vulnerable schools throughout the academic year, which is a factor directly associated with the ability to use memory, and therefore collaborative learning. Then, the IVE can be used as a benchmark for the development of environmental and social policies regarding design criteria and the incorporation of architectural strategies in public education buildings, while studies have found that most classrooms do not meet the minimum standards of comfort (AChEE, 2012). The effect of air quality in classrooms and thermal comfort in the most vulnerable schools is the opportunity to take into account the difficult reality faced by students and therefore their teachers, when trying to learn content, procedures and attitudes for their future development.

1. OBJECTIVES Chile has a total of 12,116 educational establishments that are divided into: 5,820 public institutions; 5,536 governmentsubsidized establishments; 681 private institutions; and 70 establishments managed by business associations or private corporations, with public financing (Espinoza, 2012). The aim of this study is to analyse the importance of the effect of indoor climate conditions in Chilean public schools when faced with other determinants such as student social level. This involves analysing the relationship that may exist between academic performance, social factors and the comfort of learning spaces, in order to determine the factors that have a greater impact on the productivity of students. It aims to establish a logical foundation for the development of government policies related to the evaluation of public investments for the consideration of sustainable strategies that favour the improvement of learning in the classroom.

2. METHODOLOGY Research primarily involved obtaining information in order to carry out an objective analysis of the aspects that most greatly influence the academic performance of students. To this end, 15 public schools in Chile were selected based on: geographical location according to the climatic zoning in Chilean Standard NCh1079; urban location; and an enrolment of more than 30 students per classroom. The selected schools were in the cities of Iquique in northern Chile, Puerto Montt in the south, and the Metropolitan Region of Santiago in the centre of the country. Also, these three urban centres are located in different climatic zones, 1NL, 3NVT and 4CL, and a high percentage of the country's population resides within the analysed zones. A second factor taken into account in sample selection was the previously mentioned School Vulnerability Index (IVE). A high vulnerability value index implies a low socio-economic level and vice versa. The IVEs of the sample range from 37.6% to 93.10%, thus including all socio-economic levels in order to analyse the relationship with academic performance as a starting point in public schools (see Table 1). Table 1: Classroom data used in the study School

Municipality

Climatic zone

IVE

Attendance

SIMCE

Pass rate

IQ1

Iquique

1NL

71.30%

78.23%

222

80.49%

IQ2

Iquique

1NL

79.10%

86.52%

224

86.52%

IQ3

Iquique

1NL

80.60%

80.92%

237

84.00%

PM1

Puerto Montt

4CL

67.40%

91.75%

235

97.78%

PM2

Puerto Montt

4CL

71.80%

84.07%

243

93.75%

PM3

Puerto Montt

4CL

92.40%

84.62%

232

88.89%

PM4

Puerto Montt

4CL

93.10%

86.70%

249

86.44%

SC1

La Florida

3NVT

62.13%

84.40%

253

96.06%

SC2

La Granja

3NVT

75.83%

80.91%

232

84.08%

SC3

La Granja

3NVT

83.31%

81.20%

231

80.70%

SC4

Ñuñoa

3NVT

37.6%

87.22%

313

93.68%

SC5

Providencia

3NVT

41.56%

82.59%

264

91.01%

SC6

Providencia

3NVT

43.3%

87.25%

268

95.50%

SC7

Quinta Normal

3NVT

80.0%

84.33%

276

91.49%

SC8

Renca

3NVT

68.81%

90.51%

233

91.30%

SOTO MUÑOZ, TREBILCOCK, PEREZ FARGALLO_342 3


Table 2: Data on thermal comfort and indoor air quality in classrooms Winter

Summer

School

T °C

PPM CO2

PMV

PPD

T °C

PPM CO2

PMV

PPD

IQ1

21.19

1,461.57

-0.014

31.01%

24.38

892.48

0.42

37.42%

IQ2

17.37

657.94

-0.42

22.01%

22.19

920.68

0.55

34.50%

IQ3

19.11

1,384.11

0.25

43.57%

21.89

1,404.56

0.46

41.71%

SC1

17.99

2,023.91

0.14

27.29%

20.46

1,402.07

0.48

24.51%

SC2

17.92

1,592.73

0.22

27.76%

19.43

1,311.41

0.05

22.03%

SC3

14.42

1,834.74

-0.23

42.74%

18.85

1,311.66

0.25

22.17%

SC4

15.33

1,519.28

-0.062

25.59%

18.39

1,184.51

0.10

28.89%

SC5

12.53

1,539.29

-0.27

42.76%

25.34

652.20

1.15

60.42%

SC6

12.23

1,363.87

0.03

19.81%

24.34

693.11

0.57

38.43%

SC7

11.77

1,343.95

-0.31

29.29%

26.04

560.26

0.72

53.21%

SC8

13.95

1,874.14

-0.27

28%

25.047

524.59

0.128

31.2%

PM1

12.98

1,027.91

-0.022

19.57%

24.48

590.73

0.71

42.67%

PM2

13.65

1,326.47

-0.2

22%

26.03

648.75

0.34

27.23%

PM3

13.58

1,766.44

-0.02

43%

24.69

879.49

0.63

40.26%

PM4

11.23

1,858.20

-0.56

21.53%

22.83

1,191.56

0.15

21.43%

Fieldwork was conducted to characterize the buildings using monitoring equipment installed for 4-day periods. Measurements of air temperature, radiant temperature, relative humidity, wind speed and CO 2 concentrations in PPM were taken in winter and summer (see Table 2). Data collection made it possible to characterize each educational building and show its unique features, such as: envelope composition and equipment, and resources, among others. Likewise, through daily perception surveys for students and teachers, information to estimate thermal comfort was collected using the Fanger method. Data was obtained on activities done before the survey, thereby providing information about metabolic rate. Both students and teachers were asked about the type of clothing they were wearing when responding to the survey. The above-mentioned information was used to obtain CLO and MET data. In turn, these data were used to obtain the PMV and PPD indices (see Table 2). Finally, data on academic performance, student pass rate, performance on the System for the Measurement Educational Quality (SIMCE) test, and attendance were collected (see Table 1).

3. DATA ANALYSIS 3.1. Relationship between attendance, IVE and performance Nationally, recent studies indicate that school dropout rates in primary education are negligible; in the study sample, dropout rates range from 1.11% to 11.40%. However, Espinoza (2012) indicates that for the 1992-2002 period the dropout rate is directly related to socio-economic level and ranges from 1.5% to 6.5%, the latter corresponding to the poorest fifth of Chilean society. Therefore, at first glance it could be said that this percentage is not randomly distributed, but rather it is the poorest groups that suffer to a greater extent due to this problem (Espíndola and Leon, 2002). From an educational and policymaking standpoint, it seems appropriate to indicate that there should be a direct relationship between poverty, vulnerability, exclusion, school dropout, school attendance and academic performance. In the sample under study in this research, it was found that there was no direct relationship between the dropout rate and the vulnerability index of students; instead, there was a correlation between the percentage of attendance and dropout, with lower student dropout rates in educational establishments with higher attendance. Also, it could be expected that attendance rate and vulnerability index are linked. As can be seen in Figure 1, it is not possible to corroborate this claim, as no such trend exists in the data. On the other hand, it can be said that in the classrooms analysed there is no evidence that dropout and school performance are directly related to the socio-economic status of the students. However, there is a relationship between the passing rate, the dropout percentage and attendance, with better results in both areas in those schools where attendance is higher (see Figures 1 and 2).



Figure 1: Relation between IVE, attendance and pass rate

Most studies on academic performance formulate hypotheses about socio-economic levels and pedagogical practices and mainly indicate that students at risk of social exclusion need special programs to increase academic performance. This suggests that low performance and grade repetition are related to living in poverty or social exclusion, thus indicating a higher chance of school failure (Román, 2003). The SIMCE is the National Education Quality Measurement System that consists of a set of standardized tests to measure the level achieved in different content areas and is administered in grades four, eight and ten. Upon observing Figure 2, in which student SIMCE results in the classrooms studied are related with attendance, it can be seen that there is a general trend in which attendance relates to test value; as described previously, attendance is not linked to socioeconomic level. Therefore, it can be affirmed that academic results are not directly related either.

Figure 2: Relationship between attendance and SIMCE results

3.2. Relationship between attendance and comfort The concept of thermal comfort has emerged fairly recently in the discussion on the design of public schools in Chile. It is understood to be the subjective manifestation of conformity or satisfaction with the existing thermal environment (Passive design manual, 2012), depending on the perception of four physical variables (air temperature, radiant wall temperature, relative humidity, air velocity) and two personal variables (clothing insulation (CLO) and metabolic rate) (Fanger, 1970; ASHRAE 55-2013; ISO 7730: 2005). The assessment of thermal comfort was born out of the new climate control techniques; the heating the cooling of an enclosed area is intended to make people feel comfortable and for this reason methods were developed to measure user satisfaction. Currently, there are two theories to define thermal comfort; both have their limits and potentials. On the one hand, there is the theory of heat balance and on the other, adaptive theory. Adaptive theory is applicable to field work. As such, it was used in this research. Proposed by Povl Ole Fanger in 1973, this theory involves calculating two indices called the Predicted Mean Vote (PMV) and the Predicted Percentage of Dissatisfied individuals (PPD) based on the evaluation of one's dress, metabolic rate, air temperature, mean radiant temperature, air speed and relative humidity. Nevertheless, it cannot be ignored that the thermal comfort criterion is in turn linked to culture and weather conditions, lifestyle and even socio-economic level. From the previous, the theory of adaptive thermal comfort was born. Its mission is to analyse the real acceptability of thermal environments according to their context, in this case the nation's schools; the performance of the building during the school year; and student expectations. Adaptive theory argues that people create their own thermal preferences based on their interaction with the environment, and modify their behaviour or gradually adapt themselves (Brager & de Dear, 1998). Three categories of adaptation can be created: adjustment of



behaviour, physiological (occurs in extreme situations and therefore not in buildings) and psychological (altered perception). For an initial analysis of comfort, the PPD was associated with the PMV and with the percentage of class attendance. As can be seen in Figures 3 and 4, a relationship was not observed between student attendance and classroom comfort conditions due to the great dispersion of data in both summer and winter. Due to the above, the decision was made to perform an analysis to relate average classroom temperatures with student attendance.

Figure 3: Relationship between attendance and PPD.

Figure 4: Relationship between attendance and PMV.

It has been demonstrated that there are limitations to the evaluation methods used to calculate thermal comfort. Some authors have obtained errors of close to 15% regarding the estimation of individual metabolic rate, which translates into a variation of approximately 0.3 in PMV (Havenith et al. 2002). Of the values used for obtaining the PMV, that which shows greater relevance is metabolic rate since it determines the level of an individual's clothing insulation (Gauthier & Shipworth, 2012). These values are tabulated by ISO standard 8996:2004, based on adults averaging 30 years of age, weighing 60 to 70 kg and having body surface area of 1.6 to 1.8 m². As the present study is on primary school children, whose age is between 9 and 11 years, and whose weight and body surface values do not correspond to those tabulated to obtain metabolic levels, it is quite possible that there is an approximation error in the values obtained for the evaluation of thermal comfort. For this reason, it is possible that the PMV and PPD values from young individuals are not sufficiently accurate for analysis. More exact values of metabolic rate would have to be obtained to minimize error. Schofield (1985) designed a series of equations to calculate the basal metabolic rate (BMR) of individuals based on data from a representative sample. Equation 1: BMR calculation for boys between 3 and 10 years old. Equation 2: BMR calculation for boys between 10 and 18 years old. Equation 3: BMR calculation for girls between 3 and 10 years old. Equation 4: BMR calculation for girls between 10 and 18 years old.

BRM  0,095w  2,11 BRM  0,074w  2,754 BRM  0,085w  2,033 BRM  0,056w  2,898

Where: 

w = weight of the individual (kg)



It was observed that even with Schofield's suggested corrections to the BMR calculation, there is no relationship between attendance and thermal comfort as seen in Figures 3 and 4; therefore, it was decided to directly carry out an analysis of student attendance and average classroom temperature. In Figure 6, student attendance and average classroom temperature are correlated. Here, it can be observed that the dispersion of data is large and thus it is not possible to say that there is a link between classroom temperature conditions and attendance. However, if the values obtained from the schools located in the colder climates (Santiago, Puerto Montt) are analysed (see Figure 6), it can be seen that there is a tendency of greater attendance the higher the classroom temperature in winter. It should be mentioned that the temperatures in Iquique in winter correspond to summer weather in the other two populations, as this city has a warmer climate. Therefore, it was important to take this information into consideration in the study.

Figure 5: Relationship between attendance and classroom dry bulb temperature in winter by location

Figure 6: Relationship between attendance and classroom dry bulb temperature in winter

Regarding summer temperatures (see Figure 8), it was noted that even with some dispersion among the values, the lower the classroom temperature, the greater the student attendance; although, winter temperatures (see Figure 7) are the most grouped values. The relationship between temperature and winter attendance is related to the rise in temperatures from internal gains due to higher classroom occupancy; an increase in indoor temperature results from greater attendance, which translates into greater thermal comfort. This phenomenon is more difficult to observe in the summer temperatures since the opening of windows makes the relationship between temperature and attendance not so linear. This is largely due to the fact that its value will depend on the amount of ventilation surface area and whether there is cross ventilation. For this reason, the values are more dispersed. However, it is still possible to observe that at a lower classroom temperature there is a relatively higher percentage of attendance.

Figure 7: Relationship between attendance and classroom temperature in summer



Therefore, it became clear that the PMV and PPD values of the children were unrelated to attendance and as such are not valid indicators for analysis; whereas, average classroom temperatures apparently do correlate with attendance.

3.3. Relationship between attendance and air quality Air quality is measured by the level of pollutants in a space that positively influence or negatively affect or even cause health problems for occupants (Passive Design Manual, 2012). The assessment of air quality in classrooms was directly linked to the concentration of parts per million of CO 2 measured during classroom occupancy hours. Through the process of respiration, living beings convert oxygen into carbon dioxide. Nevertheless, there are also other environmental pollutants such as formaldehyde, organic vapours, dust or fibres. These are due to multiple factors, amongst which construction materials stand out and were not measured in the present research. Various studies indicate that CO2 concentrations in occupied spaces with little or no ventilation can reach more than 5,000 ppm, which is well above the permissible range for humans (1,000-1,500 ppm) (Bakó-Biro, 2012). High concentrations of carbon dioxide can significantly lower reaction speed and reasoning ability, thereby decreasing the academic performance of students under this circumstance by approximately 30% (Wargocky, 2013). It was observed that the phenomenon of high CO2 concentration in classrooms is perceived by students as a consequence of raising the room temperature, although some teachers did perceive the situation and eventually took action to ventilate by briefly opening windows.

Figure 8: Relationship between attendance and CO2 concentration (ppm).

With respect to CO2 concentrations (see Figure 8), it was observed that even with some dispersion in the values, in winter the higher the attendance, the greater the concentration of carbon dioxide in classrooms. The relationship between CO2 concentration and attendance in winter is related to greater room occupancy; hence, the increase in carbon dioxide emissions results in poorer air quality. In summer, this phenomenon is more difficult to observe because the opening of windows causes the relationship between carbon dioxide concentration and attendance to be not so linear. This value largely depends on the amount of surface area for ventilation and if there is any cross ventilation. Consequently, the values are more dispersed.

3.4. Public investments in state-managed schools Accordingly, how should the factors discussed be considered in decision making for public investments? First, by defining social assessment strategies, such as for example the achievement of national learning and curriculum aims linked to the concept of educational space in the classroom. In this analysis, it was observed that there are differences between an area referred to as a "classroom" and an educational space. As reflected in the data collected, it is possible to distinguish that there exist classrooms that are actually enclosed spaces that do not take into consideration visual, auditory or other perceptive factors that favour a suitable environment for mental concentration. Ideally, the environmental factors of educational spaces decrease student stress and promote health by minimizing disturbances, such as for example, lower incidence of respiratory diseases with proper management of fresh air and temperature conditions that promote immunity to sickness. With that said, it is logical to develop an academic productivity indicator based on elements such as the relationship between the degree of inclusion of sustainable strategies in the building, physical-environmental variables, student health and academic performance. This indicator must be able to measure physiological and behavioural changes in students resulting from an inadequate environment. Thus, when making an initial investment or investing in renovations, the incorporation of passive strategies that favour an educational space will be valued (see Figure 9). SOTO MUÑOZ, TREBILCOCK, PEREZ FARGALLO_342 8


Figure 9: New considerations for policies on the evaluation of public investment in educational buildings

The proposal involves the modification of the Ministry of Social Development's project evaluation procedures and policies, by making information available that enables formulators and analysts of initiatives for investment in public buildings to consider costs and benefits in their design or analysis. This relates to the implementation of measures to promote a better quality of student learning in the classroom, including greater opportunities for development throughout their primary and secondary education.

4. CONCLUSIONS In the search for a logical foundation for new government policies on investments in educational building in Chile that includes sustainable strategies for transforming a classroom into a better educational space, the previously described methodology was employed. From this research, evidence emerged demonstrating that in Chilean public schools thermal comfort and air quality conditions are not satisfactory for the welfare and academic performance of students. Regarding the difficulties in obtaining valid data, primarily related to the PMV and PPD values, the young individuals are apparently inconsistent in their analysis of environmental conditions in the classroom thereby causing difficulties in applying the Fanger method. Also, unlike other authors mentioned in the study, no direct relationship was found between the dropout rate and the vulnerability index IVE, exclusion or the poverty rate; but rather, was more related to the percentage of attendance. Therefore, there is no evidence that dropout rates and school performance are directly related to the socio-economic status of students in the classrooms analysed; likewise, the connection between the pass rate and attendance also emerged from this research. This made it possible to determine that the percentage of attendance was the factor most closely related to thermal comfort and air quality conditions. Concerning the analysis of PPD and PMV, it was found that even after making the corrections recommended by Schofield for the calculation of BMR, there was no relationship between the factors analysed; hence, it was decided to carry out a direct analysis between student attendance and average classroom temperature. It should be noted that adequate procedures still do not exist for assessing the thermal comfort values established by Fanger with children. In the analysis of attendance and average classroom temperature, it was observed that the dispersion of data was very wide due to the inclusion of a region (Iquique) where the winter weather corresponded to the summer weather in the other populations (Santiago, Puerto Montt). However, from the data obtained from schools located in the colder climates it was found that there is indeed a trend of increasing classroom temperature in winter, the higher the attendance; this circumstance may be due to greater internal gains, but implies more comfort and even lower risk of sicknesses related to low temperatures. With regard to summer temperatures, it was observed that there was still some dispersion of the values, which is explained by the natural ventilation in classrooms. Nevertheless, it was possible to relate lower classroom temperature with higher student attendance. Accordingly, it can be concluded that it is necessary to obtain indoor classroom temperatures in both winter and summer that promote lower student absenteeism and thus increase productivity in educational institutions. The comfort conditions described above strongly affect indoor air quality because as it has been demonstrated, a higher level of attendance implies a greater concentration of carbon dioxide in classroom air; in winter a large number of classrooms exceed concentrations of 1,500 ppm when attendance surpasses 84%. Consequently, it follows that increasing the standard classroom temperature will increase occupancy and therefore mechanisms should be installed to help achieve indoor air quality for optimum student performance. It can be concluded that classroom temperature should be between 18 and 21 degrees Celsius to increase attendance rates and consequently lower the dropout rate and increase student performance. In this way, a drop-out rate close to 1% and a pass rate of close to 98% could be achieved. It can also be stated that students from more vulnerable socioSOTO MUÑOZ, TREBILCOCK, PEREZ FARGALLO_342 9


economic groups acquire a better attitude toward classroom temperatures, in this way increasing their comfort range compared to students from less vulnerable socio-economic groups. The absence of systematic evidence involving data on physical-environmental variables in classrooms makes it impossible analyse the problem of lack of comfort and poor air quality. Considering the absence of systems to monitor environmental conditions in classrooms and recognizing the variability of these factors according to the different climates in Chile, it is necessary to include temperature, humidity and CO 2 concentration sensors in the design of educational buildings. Finally, a method of evaluation of public investment exists in the country. However, it does not take into consideration the learning opportunities generated for students by including strategies that produce educational spaces in Chilean schools. Therefore, there is an opportunity to develop policies in this respect and foster the development of a standard for better education in the future.

5. ACKNOWLEDGMENTS The authors belong to the Sustainable Architecture and Construction Research Group (GACS) at the University of the Bío-Bío and would like to acknowledge that this paper is part of the FONDECYT research project 1130596 “Methodology for the dynamic analysis of thermal comfort during the design process of school buildings” funded by the Chilean National Commission for Research in Science and Technology.

6. REFERENCES ASHRAE, 2013. Standard 55-2013 -- Thermal Environmental Conditions for Human Occupancy ASHRAE, 2013. Standard 62.1-2013 - Ventilation for Acceptable Indoor Air Quality BAKÓ-BIRÓ, Zs., CLEMENTS-CROOME, D.J., KOCHHAR, N., AWBI, H.B., & WILLIAMS, M.J., 2012. Ventilation rates in schools and pupils’ performance, Building and Environment, 48, p. 215-223. BRAGER, Gail, & DE DEAR, Richard, 1998. Thermal adaptation in the built environment: a literature review. Energy and buildings, 27(1), p.83–96 CANDIA, Jorge, PERROTTI, Daniel E., ALDUNATE, E., 2015. Evaluación social de proyectos Un resumen de las principales metodologías oficiales utilizadas en América Latina y el Caribe. 1ed. Santiago de Chile: Cepal. 1 CITEC UBB, & DECON UC, 2012. Manual de Diseño Pasivo y Eficiencia Energética en Edificios Públicos, p. 112. Santiago de Chile DE DEAR, R, & BRAGER, G. 2002. Thermal comfort in naturally ventilated buildings: revisions to ASHRAE Standard 55, Energy and Buildings. Volume 34, Issue 6, July 2002, p. 549–561 EDUCATION FUNDING AGENCY, 2014. Building Bulletin 101: ventilation for school buildings ESPINOZA, O., CASTILLO, D., GONZÁLEZ, L.E. & LOYOLA, J., 2012. Factores familiares asociados a la deserción escolar en Chile: un estudio de caso. Revista de Ciencias Sociales. ESPÍNDOLA, E. y LEÓN, A. (2002). La deserción escolar en América Latina: Un tema prioritario para la agenda regional. Revista Iberoamericana de Educación, 30, 39-62. FANGER, P.O., 1970. Thermal comfort: analysis and applications in environments engineering, Danish Technical Press Copenhagen INSTITUTO NAICONAL DE LA NORMALIZACIÓN, 2008. Nch 1079/Of 2008: Arquitectura y construcción - Zonificación climático habitacional para Chile y recomendaciones para el diseño arquitectónico ISO, 2006. Standard 7730:2006- Ergonomía del ambiente térmico: Determinación analítica e interpretación del bienestar térmico mediante el cálculo de los índices PMV y PPD y los criterios de bienestar térmico local MUMOVI, D. & SANTAMOURIS, M. eds, 2009. A Handbook of Sustainable Building Design and Engineering ROMÁN, M. 2003. Resultados IV Encuesta Actores Sistema Educacional Chileno. Santiago de Chile: CIDE WARGOCKI, P., & WYON, D.P., 2013. Providing better thermal and air quality conditions in school classrooms would be cost-effective. Building and Environment, 59(0), 581–589
