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The impact of ventilation and daylight on learning in schools – a summary
of the actual state of knowledge
Susanne Urlaub1,2*, Gunnar Grün2,3, Peter Foldbjerg4, Klaus Peter Sedlbauer2,5
1 University of Stuttgart, Germany
2 Fraunhofer Institute for Building Physics, Stuttgart and Valley, Germany
3 Technische Hochschule Nürnberg, Germany
4 VELUX A/S, Hørsholm, Denmark
4 Technical University of Munich, Germany
*Corresponding email: susanne.urlaub@lbp.uni-stuttgart.de
SUMMARY
The physical environment in schools is a very essential parameter of the learning progress of
the pupils. This work gives an overview about the actual state of knowledge on the
relationship between ventilation and daylight in a classroom and the learning outcomes of
pupils. A higher ventilation rate promotes a higher working speed while errors seem to be
unaffected. High levels of CO2 influenced the reaction time in attention tests. Additionally,
high CO2-concentrations seem to promote absence. A very small amount of research has been
done to the relationship between daylight and learning performance. Nevertheless, more
daylight in a classroom appears to increase pupils’ learning progress. Indeed, the present
amount of research does not allow to derive an optimum value of ventilation or daylight as the
conditions in the studies are very broad.
PRACTICAL IMPLICATIONS
A good learning environment is essential for a successful later academic achievement and for
the innovation power of a society. A sufficient indoor air quality and an adequate amount of
daylight support the learning progress; on the other hand insufficient physical conditions
promote distraction and absence.
KEYWORDS
ventilation rate, CO2, learning, absenteeism, pupils’ performance
1 INTRODUCTION
Children spend an affordable amount of their daily time in a classroom and should learn
things that are important for their later achievement in education and finally in their
profession. Classrooms should therefore provide an optimal environment to support the
learning behaviour of the pupils. One part of this environment is the physical indoor climate.
The learning progress should not be hindered by e.g. a high noise level, overheated rooms or
an unhealthy or stuffy air. In reality, many schools failed to provide these optimal
environmental conditions as the ventilation rate is often too low, CO2 values too high (e.g.
Umweltbundesamt 2004) and the classrooms are frequently too warm in the summer months.
As about 18 % of the total European population (this corresponds to approximately 95 million
persons) can be considered as being a pupil or student (Eurostat 2015), the socio-economic
impact of the indoor climate in classrooms needs to be reflected. This work aims at showing
the actual state of knowledge about the influence of ventilation and daylight on learning
(directly by performance measures and indirectly by absenteeism). This is an important first
step to estimate the meaning of a good indoor climate for the European society.
2 METHODS
An extensive literature search has been done to find and include the available studies. The
following databases were searched: ISI Web of Science, Sciencedirect, PubMed, ERIC,
Google Scholar and the WorldCat catalogue. Additionally, the proceedings of the following
conferences were searched by hand: Indoor Air, Healthy Buildings, CLIMA, IAQ and
Roomvent as well as the following journals: Indoor Air, Building and Environment, Energy
and Buildings, Lighting Research and Technology and Environmental Health Perspectives. In
a next step, the references from identified publications (studies and reviews) were checked for
additional material.
To cover the indoor environmental aspects of the studies, the following search terms were
used: CO2, carbon dioxide, indoor air quality, ventilation rate and ventilation. For the learning
outcome the following key words were utilized: learning, learning behavio(u)r, performance,
(academic) achievement, absenteeism, attendance. In total, this search leaded to over 200
different publications, indeed most of them were not relevant as they have a focus different to
this review. The amount of useful studies is indicated in each section.
3 RESULTS
Type of ventilation system and learning behaviour
The literature search identified only one study (Tøftum et al. 2015) for this part. This study
compares classrooms with three different ventilation systems: natural ventilation, ventilation
with mechanical exhaust and balanced mechanical ventilation (supply and exhaust). Learning
performance was measured with a standardized test which is an official measurement for the
quality of primary school education. In total, data from 264 schools were eligible for this
study. In the schools with natural ventilation, pupils had a significantly lower achievement
indicator than in schools with balanced mechanical ventilation. Additionally, indoor air
quality was judged poorer than in mechanically ventilated schools. The highest achievement
was measured in schools with mechanical exhaust systems.
Ventilation rate and learning behaviour
The literature search yielded seven original studies that focus on the influence of different
ventilation rates on the performance of children at their schoolwork. The main limitation of
these studies is that the ventilation rates are mainly below the ASHRAE-recommended value
of 7.4 l/s per person (ASHRAE 62.1, 2013) and findings are hence limited to this range of
ventilation. What happens if ventilation rate is raised above the recommended value is
unknown yet. Table 1 shows the most important characteristics of the identified studies.
Table 1. Characteristics of the identified studies on the relationship between ventilation rate
and learning
Study
Number of subjects
Performance tests
Bakó-Biró et al. 2007, 2008 and 2012
Haverinen-Shaughnessy et al. 2011
Haverinen-Shaughnessy et al. 2015
Mendell et al. 2015
Petersen et al. 2015
Shaughnessy et al. 2006
Wargocki & Wyon, 2007
332 pupils
100 classrooms
3109 pupils
150 classrooms
4 classrooms
54 schools
2 classrooms
9 different tests
Standardized math and reading tests
Standardized math and reading tests
Standardized math and English tests
4 different tests
Standardized math and reading tests
7 different tests
The conditions, i.e. the ventilation rates are different in each study as well as the tests to
measure the learning behaviour. Nevertheless, it seems that mainly working speed is affected
by a low ventilation rate, as it is shown in three studies (Bakó-Biró et al. 2007, 2008 and 2012
and Wargocki and Wyon, 2007 and Petersen et al. 2015).
Another study (Shaughnessy et al. 2006) used standardized math and reading tests. The
results of the performance tests indicated an increase in performance with increasing
ventilation rate. Significance is given for math results, but not for reading. An extension
(Haverinen-Shaughnessy et al. 2011) of this study investigates 100 classrooms of which 87
had ventilation rates below the ASHRAE-recommended value of 7.4 l/s per person. The
statistical analysis of the tests via regression modelling shows a linear increase in
performance of 2.9 % for math and 2.7 % for reading with every increase of ventilation rate
by 1 l/s per person in the range of 0.9 to 7.4 l/s per person.
A more recent study (Haverinen-Shaughnessy et al. 2015) aims at identifying some
underlying confounding variables to illustrate the mere influence of ventilation rate and
temperature on learning outcomes. After considering the influence of possible confounders,
math scores improve in sum about 0.5 % or eleven points on the test scale for every increase
of 1 l/s per person in the range of 0.9 up to 7.1 l/s per person. This is a smaller increase than
in previous studies from these authors (Haverinen-Shaughnessy et al. 2011), this may be
explained by eliminating confounding variables that are included in the former studies.
Another experiment (Mendell et al. 2015) analyzed the performance of 3rd, 4th and 5th grade
pupils in an English and a math test. Ventilation rates and were in most rooms below the re-
commended value of 7.4 l/s per person. For every 10% increase in ventilation rate test scores
in the English test improved about 0.6 points. The results of the math test were not significant.
Figure 1 shows the results of almost all discussed studies with their respective conditions. The
study of Mendell et al. (2015) is not displayed in this figure as they used a prior-30-day-
ventilation-rate which is not the same metric as in the other studies (where ventilation rates
from a spot measurement were used).
Figure 1. Overview about the influence of ventilation rate on learning outcomes.
CO2-concentration and learning behaviour
The literature search has leaded to five publications; the characteristics are shown in Table 2.
Table 2. Characteristics of the identified studies on the relationship between CO2-
concentration and learning
Study
Number of subjects
Performance tests
Coley et al. 2007
Lee et al. 2012
Myhrvold et al. 1996
Ribic 2008
Twardella et al. 2012
18 pupils
312 students
About 550 pupils
152 pupils
417 pupils
Cognitive Drug Research Test
Self-estimated performance
Concentration Test
Concentration Test
Concentration Test
One study (Coley et al. 2007) investigates the influence of CO2 on attention. As a result, the
reaction times of 3 out of 4 tests increase with high CO2-levels. Accuracy was not affected.
The authors concluded that high levels of CO2 hinder the children to focus their attention
which is a confirmation of an older field study (Myhrvold et al. 1996), where the same
tendency was found. In another study (Ribic, 2008), the condition of high CO2 values was far
beyond the recommended guidelines (almost 4000 ppm). Results showed that the
performance of an attention test was considerably decreased in this condition.
A more recent experiment (Twardella et al. 2012) was conducted in 20 classrooms with a
mechanical ventilation system. Results showed a significant increase in error rates at the
higher concentrations. The difference to the other studies is that in the worst condition the
CO2 concentration is about 2100 ppm which is considerably lower as in the other studies; this
may lower the magnitude of the effect on performance.
The study of Lee et al. (2012) differs from the aforementioned ones. Students report their
subjectively estimated learning performance. The CO2 concentration ranged from 500 to
about 1660 ppm which is considerably better than in all other studies. Thus, IAQ measured
with CO2 concentrations shows no influence on self-estimated learning performance.
Figure 2 shows the results of the four studies with objective performance measures..
Figure 2. Overview about the influence of CO2-concentration on learning outcomes.
Ventilation and absenteeism
Although absence is not a direct performance metric, it is obvious that learning progress
suffers if pupils are ill or absent. Four studies were identified for this research field.
The study of Shendell et al. (2004) focuses on the influence of CO2 on the attendance of
students in 435 classrooms. Almost all of them have a mechanical ventilation system. The
statistical analysis shows a 10-20 % increase in absence over a year, when CO2 concentration
rises by an interval of 1000 ppm.
A recent experiment (Mendell et al., 2013) investigates the possible relationship between
ventilation rate in the classroom and daily illness absence of pupils. In many classrooms, the
observed range of ventilation rates is below the ASHRAE-recommended value of 7.1 l/s per
person. Within this range, the data show that an increase in 1 l/s per person leads to
remarkable decreases in absence rate, but the relationship is not linear. While at very low
ventilation rates an increase would result in 3-5 % decrease of illness absence, the reduction is
much bigger at higher ventilation rates. When increasing the ventilation rate from 7.1 to 15 l/s
per person, illness caused absence would be reduced about 11-17 %.
Simons et al. (2010) reports findings from a cross-sectional survey of 2751 schools. In
contrast to the aforementioned studies, no measurements of the physical environment had
been conducted. The main outcomes were ventilation problems (e.g. air intakes near pollution
sources or bad condition of air filters) and absenteeism. The results are indicated as odds
ratios (OR) and ventilation problems are a main risk factor for an increased absence,
especially if air intakes are near a pollution source (OR 2.90) and if outside air is not
sufficiently supplied into the room (OR 2.89).
In a study from Scotland (Gaihre et al. 2014), the authors stated that with every 100 ppm-
increase of CO2-concentration attendance is reduced by 0.2 %. Attendance was not affected
by temperature or relative humidity. Academic attainment, i.e. the percentage of pupils that
attained the knowledge level expected for that age group, was not affected by CO2-
concentration.
Daylight in schools and learning
The literature search identified four studies, but there is no single study that focuses clearly on
the natural illumination in the classrooms. The first study (Stone and Irwin, 1994) investigates
the influence of windows in general, and thus also daylight, on performance. Participants
were students who were seated in either a windowed or windowless room and performed
several tasks. The windowed condition was separated into direct view and indirect view
conditions. Surprisingly, no significant differences of performance between windowed and
windowless rooms could be observed. The only influence was the type of view on the creative
task. Participants with a direct view completed more items on this task.
The next study (Nicklas et al. 1996) compares three newly built daylit schools with other new
schools built in the same district of North Carolina, USA. The daylit schools were designed to
maximize the amount of daylight in the classrooms. Normalized tests were evaluated from the
county school system. As a result, the authors stated that pupils that attended daylit schools
performed 5 to 14 % better within one year than those not visiting such a school. When the
pupils were compared over a longer time, the effect is even larger. On average the learning
progress has been found 14 % better in daylit schools than in common schools.
A huge study was conducted in California, USA with over 21,000 pupils (Heschong, 2003).
They used, like Nicklas et al. (1996), standardized tests that were passed by the pupils at the
end and on the half of a school year and they compared the learning progress under different
lighting situations (windows, skylights, windows and skylights, none). They stated that pupils
in classrooms with the most daylight performed about 20% better on math tests and 26% on
reading tests than those with the smallest amount of daylight over a period of one year. Pupils
in classroom with the largest window areas progressed 15% faster in math and 23% in reading
compared with pupils in classrooms with the lowest amount of window area. Classrooms with
skylights allow children to progress about 20% faster than children in a classroom without
skylights. Other schools in this study show a 7 to 18% higher performance in those
classrooms with the most daylight compared to those classrooms with the lowest amount of
daylight.
A very old study (Larson et al. 1965) reports contradictory results compared to the other two
studies mentioned above. The focus of this study is the influence of windows in the classroom
on learning and absenteeism. The windowless condition and the window-condition lasted
each one year. They also used standardized tests that pupils pass every year to evaluate the
learning progress. The results showed a high variability and therefore the authors drew the
conclusion that the presence or absence of windows has no effect on the learning progress of
children. Additionally, teachers indicated that the pupils were less distracted in windowless
environments. The conclusions from this study are consequently, that windows are not really
necessary in classrooms but instead they should have a good artificial lighting and air-
conditioning system.
4 DISCUSSION
Ventilation seems to have an influence on the learning behaviour of children; both ventilation
rate and CO2-concentration appear to change the performance. Nevertheless, the conditions
which are compared are mostly very broad and an optimum value in the sense of a threshold
level, as e.g. 1000 or 1200 ppm, being more supportive for learning could not be derived. In
terms of ventilation rate, the knowledge is limited to the range below the recommended
values in ventilation standards and it is known that an air change rate near this value is better
for learning. It is unknown yet, if ventilation rates above the guideline values can even
improve performance. With regard to the performance metric, it seems that ventilation rate
affects mainly working speed, but not errors, whereas higher CO2 values seem to reduce
attention, but not all results are consistent (e.g. math results are significant in one study but
not in another) and confounding factors like language proficiency appear to play a role which
test score is achieved.
With regard to daylight, the empirical evidence is small. None of the studies focuses on the
single influence of daylight. Nevertheless, the presence of windows (and therefore daylight)
seems to improve the learning progress, at least if the most extreme conditions are compared.
But, like in the field of ventilation, the conditions in the studies are very broad (and often not
even indicated) and no knowledge is available yet what happens at an intermediate level of
daylight illumination and if there is an optimal value of daylight for learning performance.
5 CONCLUSIONS
Academic achievement is an essential parameter for later earnings in life which are not only
important on the personal level with regard to the achievable quality of life but also in a
public dimension in form of greater tax revenues. For example, the benefits of tertiary
education exceed the costs on average by a factor of three (OECD, 2013). On the other hand,
the indoor environment seems to be a parameter which plays a role in reaching a certain
academic achievement, but knowledge on how to support optimally the learning in schools
with adequate indoor environmental quality is limited to rather extreme values (very low or
very high). The research agenda for the next years has to keep in mind this fact and needs to
focus on the development of optimal indoor environmental quality for learning behavior in
order to be able to give substantiated advice to the design and operation of schools.
Quantifications may also been done if ranges for best possible learning are known, which
could be put into relation with e.g. energy need and consumption of the school building on the
one side and with socio-economic factors like higher income tax revenues.
ACKNOWLEDGEMENT
The authors express their gratitude to the graduate program “People Inside” at the Chair of
Building Physics, University Stuttgart, Germany and Velux A/S, Denmark for a fruitful
cooperation and support of this study. This work is benefitting from the research project
Building I conducted at the Energy Campus Nuremberg, funded by the Bavarian State
Government.
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