Analysis of Indoor Air Pollutants and Guidelines for Space and Physical Activities in Multi-Purpose Activity Space of Elementary Schools

Abstract

Owing to the recent increase in the number of warning reports and alerts on the dangers of fine dusts, there has been an increasing concern over fine dusts among citizens. In spaces with poor ventilation, the occupants are forced to open the window to initiate natural ventilation via the direct introduction of the outside air; however, this may pose a serious challenge if the external fine-dust concentration is high. The lack of natural ventilation increases the indoor carbon dioxide (CO2) concentration, thus necessitating the installation of mechanical ventilation systems. This study analyzed the frequency of the application of mechanical ventilation systems in the Multi-purpose activity space of elementary schools, which are spaces where children require a higher indoor air quality than adults owing to the rapid increase in the CO2 concentration of the Multi-purpose activity space during activities. In addition, the architectural and equipment factors of the Multi-purpose activity spaces of nine elementary schools were characterized. The results revealed that five out of the nine elementary schools installed mechanical ventilation systems, whereas the remaining four schools installed jet air turnover systems. The indoor air quality of the Multi-purpose activity space of D elementary school, which had the minimum facility volume among the schools investigated in this study (564.2 m3), with up to 32 participants for each activity, was investigated. The results revealed that the ultrafine-dust (PM2.5) concentration of the facility was as high as 4.75 µg/m3 at a height of 1.2 m, and the CO2 concentration was as high as 3183 ppm. The results of the analysis of three elementary schools with different volumes were compared and analyzed using CONTAM simulation. This study determined the required volume per occupant and the optimum number of occupants for a given volume and presented guidelines for the optimum number of occupants, activities, and volume to reduce the high concentration of pollutants in the analyzed Multi-purpose activity space. The guideline proposed in this study is aimed at maintaining the CO2 concentration of the Multi-purpose activity space below 1000 ppm, as prescribed by the Indoor Air Quality Control in Public-Use Facilities, Etc. Act in South Korea.

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Citation: Lee, Y.-K.; Kim, Y.I.
Analysis of Indoor Air Pollutants and
Guidelines for Space and Physical
Activities in Multi-Purpose Activity
Space of Elementary Schools. Energies
2022,15, 220. https://doi.org/
10.3390/en15010220
Academic Editor: Boris Igor Palella
Received: 15 November 2021
Accepted: 22 December 2021
Published: 29 December 2021
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energies
Article
Analysis of Indoor Air Pollutants and Guidelines for Space
and Physical Activities in Multi-Purpose Activity Space of
Elementary Schools
Yeo-Kyung Lee 1and Young Il Kim 2,*
1
Department of Architectural Engineering, Graduate School, Seoul National University of Science and Technology,
Seoul 01811, Korea; dldurud9004@naver.com
2School of Architecture, Seoul National University of Science and Technology, Seoul 01811, Korea
*Correspondence: yikim@seoultech.ac.kr
Abstract:
Owing to the recent increase in the number of warning reports and alerts on the dangers
of fine dusts, there has been an increasing concern over fine dusts among citizens. In spaces with
poor ventilation, the occupants are forced to open the window to initiate natural ventilation via
the direct introduction of the outside air; however, this may pose a serious challenge if the external
fine-dust concentration is high. The lack of natural ventilation increases the indoor carbon dioxide
(CO
2
) concentration, thus necessitating the installation of mechanical ventilation systems. This study
analyzed the frequency of the application of mechanical ventilation systems in the Multi-purpose
activity space of elementary schools, which are spaces where children require a higher indoor air
quality than adults owing to the rapid increase in the CO
2
concentration of the Multi-purpose activity
space during activities. In addition, the architectural and equipment factors of the Multi-purpose
activity spaces of nine elementary schools were characterized. The results revealed that five out of
the nine elementary schools installed mechanical ventilation systems, whereas the remaining four
schools installed jet air turnover systems. The indoor air quality of the Multi-purpose activity space
of D elementary school, which had the minimum facility volume among the schools investigated
in this study (564.2 m
3
), with up to 32 participants for each activity, was investigated. The results
revealed that the ultrafine-dust (PM2.5) concentration of the facility was as high as 4.75
µ
g/m
3
at
a height of 1.2 m, and the CO
2
concentration was as high as 3183 ppm. The results of the analysis
of three elementary schools with different volumes were compared and analyzed using CONTAM
simulation. This study determined the required volume per occupant and the optimum number
of occupants for a given volume and presented guidelines for the optimum number of occupants,
activities, and volume to reduce the high concentration of pollutants in the analyzed Multi-purpose
activity space. The guideline proposed in this study is aimed at maintaining the CO
2
concentration
of the Multi-purpose activity space below 1000 ppm, as prescribed by the Indoor Air Quality Control
in Public-Use Facilities, Etc. Act in South Korea.
Keywords:
activity; carbon dioxide; jet air turnover system; CONTAM; elementary school; fine dust;
indoor air quality; Multi-purpose activity space (MPA-space); student
1. Introduction
1.1. Background and Objectives of Research
Currently, in Korea, the number of warnings due to fine dust is increasing every year.
The domestic fine-dust measurement data are divided into PM10 and PM2.5. According
to ‘Fine, Ultrafine, and Yellow Dust: Emerging Health Problems in Korea’ [
1
], PM10 with
a diameter of less than 10
µ
m is classified as fine dust, and PM2.5 with a diameter of less
than 2.5
µ
m is classified as ultrafine dust. In the case of PM2.5, the dust is deposited in the
alveolar region and has a worse effect on health than PM10 (fine dust) [
1
,
2
]. In particular,
Energies 2022,15, 220. https://doi.org/10.3390/en15010220 https://www.mdpi.com/journal/energies

Energies 2022,15, 220 2 of 21
when comparing the concentration of ultrafine dust in Seoul and five major overseas cities
for 6 years, from 2014 to 2019, as analyzed using the domestic air environment annual data
and the China Environmental Observation Center data [
3
], the ultrafine particles in Seoul
are gradually increasing each year, a trend contrary to other major populated cities, as
shown in Figure 1. The dust concentration of Seoul was measured to be the second highest
after Beijing. Compared to the four cities of LA, Tokyo, Paris, and London, it can be seen
that the concentration of ultrafine dust in Seoul is measured as being twice as high [4].
Energies 2022, 14, x FOR PEER REVIEW 2 of 23
alveolar region and has a worse effect on health than PM10 (fine dust) [1,2]. In particular,
when comparing the concentration of ultrafine dust in Seoul and five major overseas cities
for 6 years, from 2014 to 2019, as analyzed using the domestic air environment annual
data and the China Environmental Observation Center data [3], the ultrafine particles in
Seoul are gradually increasing each year, a trend contrary to other major populated cities,
as shown in Figure 1. The dust concentration of Seoul was measured to be the second
highest after Beijing. Compared to the four cities of LA, Tokyo, Paris, and London, it can
be seen that the concentration of ultrafine dust in Seoul is measured as being twice as high
[4].
(a) (b)
Figure 1. (a) Annual ultrafine-dust (PM2.5) concentration in the major cities of the world [4]; (b)
annual fine-dust (PM10) concentration in Korea [4].
In addition, the ‘Annual Report of Air Quality in Korea 2019’ revealed that the
concentration of ultrafine dusts in Seoul was approximately twice as high as those of Los
Angeles, Tokyo, Paris, and London [5]. In China, wher e the high conc entration of fine dust
has posed a serious environmental threat, the fine-dust concentration has been decreasing
annually, whereas that of South Korea has been increasing. In addition, in the ‘2019 World
Air Quality Report’ of IQAir, an international air-pollutant protection technology
organization, South Korea was ranked first in the ultrafine-dust concentration among
OECD member states [5]. In addition, a report on the Chungnam region, which is located
in the center of South Korea, revealed that the increase in fine-dust concentration is a
major cause of the deterioration in the public health of this region. This could be attributed
to the significantly high emission of air pollutants in the Chungnam region owing to the
industries which greatly rely on combustion processes in this region [6]. According to the
‘fine dust alert status report’ of the Chungnam Institute of Health and Environment, as of
6 May 2017 the average hourly fine-dust concentration in the Chungnam area was
measured to be higher than 300 µg/m3 during the hours of 13:00 to 18:00 [6,7]. In the
Chungnam region, the annual average number of asthma patients per 100,000 people is
6259, and correlation analysis results on the identification of the effects of air pollutants,
such as fine dust, revealed that this number increases with an increase in the emissions of
suspended particulates and fine dusts [5]. In addition, a high incidence of respiratory
diseases was observed among the residents in Incheon, which exhibits a relatively high
concentration of air pollutants [8]. Children are more vulnerable to the adverse effects of
fine dusts compared to adults owing to their body structure, behavior, and developmental
characteristics [9]. Furthermore, the “High-concentration Fine Dust Response Manual for
Protection of the Vulnerable Class” describes that infants and children inhale more air
pollutants than adults because of their higher respiratory rate per unit weight [10,11]. Air
pollutants have an adverse effect on human health and are particularly dangerous for
infants and children with underdeveloped lungs [12]. There is an increasing awareness
about the protection of elementary school students from exposure to external fine dusts
Figure 1. (a) Annual ultrafine-dust (PM2.5) concentration in the major cities of the world [4]; (b) an-
nual fine-dust (PM10) concentration in Korea [4].
In addition, the ‘Annual Report of Air Quality in Korea 2019’ revealed that the concen-
tration of ultrafine dusts in Seoul was approximately twice as high as those of Los Angeles,
Tokyo, Paris, and London [
5
]. In China, where the high concentration of fine dust has posed
a serious environmental threat, the fine-dust concentration has been decreasing annually,
whereas that of South Korea has been increasing. In addition, in the ‘2019 World Air Quality
Report’ of IQAir, an international air-pollutant protection technology organization, South
Korea was ranked first in the ultrafine-dust concentration among OECD member states [
5
].
In addition, a report on the Chungnam region, which is located in the center of South Korea,
revealed that the increase in fine-dust concentration is a major cause of the deterioration in
the public health of this region. This could be attributed to the significantly high emission
of air pollutants in the Chungnam region owing to the industries which greatly rely on
combustion processes in this region [
6
]. According to the ‘fine dust alert status report’ of
the Chungnam Institute of Health and Environment, as of 6 May 2017 the average hourly
fine-dust concentration in the Chungnam area was measured to be higher than 300
µ
g/m
3
during the hours of 13:00 to 18:00 [
6
,
7
]. In the Chungnam region, the annual average
number of asthma patients per 100,000 people is 6259, and correlation analysis results
on the identification of the effects of air pollutants, such as fine dust, revealed that this
number increases with an increase in the emissions of suspended particulates and fine
dusts [
5
]. In addition, a high incidence of respiratory diseases was observed among the
residents in Incheon, which exhibits a relatively high concentration of air pollutants [
8
].
Children are more vulnerable to the adverse effects of fine dusts compared to adults owing
to their body structure, behavior, and developmental characteristics [
9
]. Furthermore, the
“High-concentration Fine Dust Response Manual for Protection of the Vulnerable Class”
describes that infants and children inhale more air pollutants than adults because of their
higher respiratory rate per unit weight [
10
,
11
]. Air pollutants have an adverse effect on
human health and are particularly dangerous for infants and children with underdeveloped
lungs [
12
]. There is an increasing awareness about the protection of elementary school
students from exposure to external fine dusts owing to the increasing concerns about the
direct adverse effects of air pollutants on human health, and the increasing reports on the
dangers of fine dust. However, the lack of attention to the importance of proper ventila-

Energies 2022,15, 220 3 of 21
tion in daily life has resulted in occupants devoting little time to opening windows and
ventilating their indoor space [
13
,
14
]. Insufficient natural ventilation results in an increase
in the indoor carbon dioxide (CO
2
) concentration, thus necessitating the installation of a
mechanical ventilation system [
15
]. Thus, this study aimed to analyze the frequency of the
application of mechanical ventilation systems in the MPA-spaces of elementary schools, as
well as the characteristics of the pollutants in spaces with high activity levels of children.
1.2. Scope and Methodology of Research
This study examined various comprehensive measures and legal standards imple-
mented by the government in elementary school facilities with an increase in the concen-
tration of fine dust, and further analyzed the frequency of the installation of mechanical
ventilation systems in the indoor MPA-spaces of elementary schools with high activity
levels of elementary school students. In addition, the CO
2
concentration and the fine-dust
concentration were measured as a function of the activity levels of elementary school stu-
dents, using Testo 160 IAQ and Sensirion SPS, respectively. The airtightness of the facilities
was measured using a blower door test, as shown in Figure 2.
Energies 2022, 14, x FOR PEER REVIEW 3 of 23
owing to the increasing concerns about the direct adverse effects of air pollutants on
human health, and the increasing reports on the dangers of fine dust. However, the lack
of attention to the importance of proper ventilation in daily life has resulted in occupants
devoting little time to opening windows and ventilating their indoor space [13,14].
Insufficient natural ventilation results in an increase in the indoor carbon dioxide (CO2)
concentration, thus necessitating the installation of a mechanical ventilation system [15].
Thus, this study aimed to analyze the frequency of the application of mechanical
ventilation systems in the MPA-spaces of elementary schools, as well as the characteristics
of the pollutants in spaces with high activity levels of children.
1.2. Scope and Methodology of Research
This study examined various comprehensive measures and legal standards
implemented by the government in elementary school facilities with an increase in the
concentration of fine dust, and further analyzed the frequency of the installation of
mechanical ventilation systems in the indoor MPA-spaces of elementary schools with high
activity levels of elementary school students. In addition, the CO2 concentration and the
fine-dust concentration were measured as a function of the activity levels of elementary
school students, using Testo 160 IAQ and Sensirion SPS, respectively. The airtightness of
the facilities was measured using a blower door test, as shown in Figure 2.
Through the experimental results and graph analysis, the indoor-air-pollutant
concentration increase over time, with respect to the number of occupants and activities
and the correlation between the space volume and the pollutant concentration, can be
found. The rate of increase in air pollutants as a function of the activity levels of
elementary school students was measured using experimental results, and the change in
pollutant concentrations at three elementary schools with different MPA-space volumes
was compared using CONTAM (W. Stuart Dols, Brian J. Polidoro, Gaithersburg, US)
simulation. In addition, the required volume per occupant and the permissible number of
occupants in a facility was derived using CONTAM simulation to determine the
conditions necessary to reduce the concentration of air pollutants in these MPA-spaces to
below the minimum acceptable level and to provide guidelines on the optimum number
of people, activities, and volume [16,17].
(a) (b)
Figure 2. (a) Sealing of windows, doors, diffusers, air conditioners, and other openings before the
blower door test; (b) blower door test of the MPA-space of D Elementary school.
The CONTAM simulation results were verified by comparing the root mean square
error (RMSE) and the mean absolute percentage error (MAPE) of the simulation and
measurement results. For the design guidelines and for suggesting the proper level of
activities in indoor physical spaces and the correlations between activity types, the
number of people, the space, the activity time, and the CO2 concentration were derived in
Figure 2.
(
a
) Sealing of windows, doors, diffusers, air conditioners, and other openings before the
blower door test; (b) blower door test of the MPA-space of D Elementary school.
Through the experimental results and graph analysis, the indoor-air-pollutant concen-
tration increase over time, with respect to the number of occupants and activities and the
correlation between the space volume and the pollutant concentration, can be found. The
rate of increase in air pollutants as a function of the activity levels of elementary school
students was measured using experimental results, and the change in pollutant concentra-
tions at three elementary schools with different MPA-space volumes was compared using
CONTAM (W. Stuart Dols, Brian J. Polidoro, Gaithersburg, US) simulation. In addition, the
required volume per occupant and the permissible number of occupants in a facility was
derived using CONTAM simulation to determine the conditions necessary to reduce the
concentration of air pollutants in these MPA-spaces to below the minimum acceptable level
and to provide guidelines on the optimum number of people, activities, and volume [
16
,
17
].
The CONTAM simulation results were verified by comparing the root mean square
error (RMSE) and the mean absolute percentage error (MAPE) of the simulation and
measurement results. For the design guidelines and for suggesting the proper level of
activities in indoor physical spaces and the correlations between activity types, the number
of people, the space, the activity time, and the CO
2
concentration were derived in order
to maintain a CO
2
concentration in indoor space below 1000 ppm. If the indoor physical
spaces were operated using these correlations, the indoor-air-quality environment was
affected positively and enhanced the effectiveness of student physical activities and the
indoor occupants’ health [9–11].

Energies 2022,15, 220 4 of 21
2. Domestic System and Class Status of the MPA-Space of Elementary Schools
This study investigated the standards and comprehensive measures implemented
by the government to respond to the annually increasing concentration of fine dusts in
the MPA-spaces of elementary schools and the guidelines of the Ministry of Education on
the “watch” and “warning messages” of the domestic fine-dust warning systems of the
physical education activities of elementary schools.
2.1. Comprehensive Measures for Reducing the Concentration of Fine Dusts in South Korea
The South Korean Government has recognized the increasing tendency and hazard of
fine dusts and has been preparing various comprehensive measures and legal standards.
As a part of these efforts, the South Korean Government recently included provisions on
air quality in the School Health Act in 2019, which is the most closely related provision
for elementary schools. Furthermore, the Ministry of Environment recently announced
the standards for facilities used by the vulnerable class, and the Office of Education on
metropolitan and provincial levels distributed practical manuals on the response to high-
concentration fine dusts in order to prepare the rules that should be adhered to by school
facilities in responding to the occurrence of high-concentration fine dusts. These include
the replacement of outdoor physical education classes with indoor classes or the reduction
in the duration of outdoor activities when “watch” or “preliminary/emergency reduction
measures” messages on the fine dusts are issued [
18
]. In summary, national comprehensive
measures and standards are being established to address the increase in the concentration
of fine dusts in South Korea, and regulations on outdoor activities are being strengthened.
2.2. Current Status of Physical Education Classes According to the Domestic System in Response
to Fine Dusts
The “watch” or “preliminary/emergency reduction measures” messages on fine dust,
from the standards on national comprehensive measures and the practical manual of
the Office of Education on metropolitan and provincial levels, restrict outdoor physical
education classes [
18
]. According to a previous study on the “Effects of Elementary School
Students” Awareness of Fine Dust, Respiratory-Related Subjective Symptoms, and Level of
Physical Activities on Health Promotion Behavior,” [
19
] children’s physical activity at school
and at home decreased as the concentration of fine dust increased. In addition, according
to “A Qualitative Case Study on Physical Education Classes for Efforts to Overcome Fine
Dust,” [
20
] the importance of indoor physical education classes is increasing. However,
because of the insufficient analyses and studies on the quantity of fine dusts in indoor
MPA-spaces, compared to that of regular classrooms, it is difficult to identify the exact
characteristics of the MPA-space owing to insufficient data on the aging MPA-spaces of
schools. Therefore, this study analyzed the architectural and equipment factors of the
MPA-space of elementary schools, as well as the change in the concentration of fine dusts
and CO2as a function of the activities during physical education class.
3. Current Status of Indoor MPA-Spaces in Elementary Schools
This study analyzed the architectural and equipment factors of the MPA-space in
elementary schools to examine the current indoor environment of these facilities.
3.1. Architectural Factors of the Indoor MPA-Space in the Elementary Schools
This study analyzed the architectural factors of the MPA-space in nine elementary
schools using architectural drawings of these facilities. The data on the required area
per student, which were obtained using the average floor area of the MPA-space and the
information on the school alert site, were analyzed [
21
]. The analysis of the size of the
MPA-space in the nine elementary schools revealed that the average floor area and ceiling
height of the facilities was 609.82 m2and 9.96 m, respectively (Table 1).

Energies 2022,15, 220 5 of 21
Table 1. Height, area, and volume of the MPA-space of the nine elementary schools.
Name of School Ceiling Height (m) Floor Area (m2) Space Volume (m3)
A 10.4 616.14 6407.9
B 10.8 677.16 7313.3
C 10.6 751.20 7962.7
D 3.64 155 564.2
E 10.6 562.8 5965.7
F 11.5 570.72 6563.3
G 12.1 725.4 8777.3
H 9.46 652.4 6171.7
I 10.5 777.6 8164.8
Average 9.96 609.82 6073.8
The required area of 0.4 m
2
per person, which is the stipulated required auditorium
area in the school facility planning and design guidelines of the Seoul Metropolitan Office
of Education, and in the general applications of domestic building plans, was compared to
the floor area of the nine elementary schools (Table 2). The results revealed that the actual
floor area of the MPA-space of eight out of the nine analyzed elementary schools satisfied
the criterion; however, the D Elementary School, which was established in 1965, did not
meet the criterion [22,23].
Table 2. Required area for the MPA-space of the elementary schools.
Name of School Number of Classes Number of Students Required Area
(Number of Students ×0.4 m2)
A 28 729 291.56
B 28 889 355.6
C 24 579 231.6
D 25 445 178
E 28 1224 489.6
F 32 1062 424.8
G 28 850 340
H 29 1263 505.2
I 22 823 329.2
Average 26.64 854.73 341.9
3.2. Equipment Factors of the Indoor MPA-Space in the Elementary Schools
The current status of the air purification systems in the MPA-space of the nine ele-
mentary schools was analyzed, and the results revealed that air conditioning systems were
installed in all the MPA-spaces (Table 3). The air conditioning and heating devices used in
these schools included a gas-engine-driven heat pump (GHP) and an electric heat pump
(EHP). Jet air turnover systems are beneficial in seasons with poor air stream for reducing
the temperature difference between the upper and lower temperatures in the room. In this
study, jet air turnover systems were installed in four out of the nine elementary schools [
24
].
In addition, poorly operating diffusers were observed in the D elementary school;
however, an energy recovery ventilation (ERV) system was installed in the MPA-space
of the school. These results suggest that the distribution of air conditioners in the indoor
MPA-spaces in these schools is insufficient, and some of the mechanical ventilation systems
in these schools were in poor operation and required immediate improvement.
Therefore, this study further investigated the indoor air quality of the D elementary
school to analyze the effects of the required area on the indoor air quality, as well as the
concentration of the indoor air pollutants requiring mechanical ventilation application.

Energies 2022,15, 220 6 of 21
Table 3. Status of the air conditioners and air purifiers in the analyzed elementary schools.
Name of School Air Conditioning and Heating Device Air Purifier
A GHP Jet air turnover system
B EHP Jet air turnover system
C GHP X
D GHP ERV
E GHP Jet air turnover system
F EHP Jet air turnover system
G EHP X
H EHP Fan
I GHP Fan
4. Analysis of the Indoor Air Quality Characteristics Based on the Volume of the
MPA-Space
Indoor air quality was measured to analyze the indoor environmental characteristics
that change according to students’ activities at indoor physical education facilities in
elementary schools. The experiment measured the indoor temperature, which affects the
comfort of the occupants, and the concentration of CO
2
that adversely affects the human
body as the concentration increases, in addition to the concentration of fine dusts.
The D Elementary School was established in 1965, and its MPA-space is located on the
second floor. In the case of the MPA-space, as shown in Figure 3, the floor area is 155 m
2
,
the ceiling height is 3.64 m, and the volume is 564.2 m
3
. The space is heated and cooled by
EHP with an ERV and air purifier installed.
Energies 2022, 14, x FOR PEER REVIEW 6 of 23
In addition, poorly operating diffusers were observed in the D elementary school;
however, an energy recovery ventilation (ERV) system was installed in the MPA-space of
the school. These results suggest that the distribution of air conditioners in the indoor
MPA-spaces in these schools is insufficient, and some of the mechanical ventilation
systems in these schools were in poor operation and required immediate improvement.
Table 3. Status of the air conditioners and air purifiers in the analyzed elementary schools.
Name of School Air Conditioning and Heating Device Air Purifier
A GHP Jet air turnover system
B EHP Jet air turnover system
C GHP X
D GHP ERV
E GHP Jet air turnover system
F EHP Jet air turnover system
G EHP X
H EHP Fan
I GHP Fan
Therefore, this study further investigated the indoor air quality of the D elementary
school to analyze the effects of the required area on the indoor air quality, as well as the
concentration of the indoor air pollutants requiring mechanical ventilation application.
4. Analysis of the Indoor Air Quality Characteristics Based on the Volume of the
MPA-Space
Indoor air quality was measured to analyze the indoor environmental characteristics
that change according to students’ activities at indoor physical education facilities in
elementary schools. The experiment measured the indoor temperature, which affects the
comfort of the occupants, and the concentration of CO2 that adversely affects the human
body as the concentration increases, in addition to the concentration of fine dusts.
The D Elementary School was established in 1965, and its MPA-space is located on
the second floor. In the case of the MPA-space, as shown in Figure 3, the floor area is 155
m2, the ceiling height is 3.64 m, and the volume is 564.2 m3. The space is heated and cooled
by EHP with an ERV and air purifier installed.
(a) (b)
Figure 3. (a) Floor plan of the MPA-space of the D elementary school and (b) indoor-air-quality
measurement experiment.
4.1. Indoor Air Quality Experiment of the MPA-Space
The indoor air quality factors, including temperature, humidity, CO2, PM10, and
PM2.5 from 30 January 2020 to 4 February 2020, were measured. The concentration of fine
Figure 3.
(
a
) Floor plan of the MPA-space of the D elementary school and (
b
) indoor-air-quality
measurement experiment.
4.1. Indoor Air Quality Experiment of the MPA-Space
The indoor air quality factors, including temperature, humidity, CO
2
, PM10, and
PM2.5 from 30 January 2020 to 4 February 2020, were measured. The concentration of
fine dust, the temperature, and the CO
2
concentration were measured using the Sensirion
SPS30, which is certified by the Monitoring Certification Scheme (MCERTS), a monitoring
certification of the UK Environment Agency, and the Testo 400, respectively. The MPA-
space of the D Elementary School is utilized for various physical education activities, such
as club activities, small soccer, badminton, and playing catch.
As shown in Figure 3, the ultrafine-dust measurement points were measured at two
measurement points with heights of 0.8 m, 1.2 m, and 1.6 m, respectively. For the outdoor
air data, the ‘Ambient air information around our school’ measurement data provided by
the Korea Environment Corporation was used [
25
]. Figure 4shows the result of the fine-
dust concentration measured on January 30, when various activities were being performed

Energies 2022,15, 220 7 of 21
in the facility. On January 30, the MPA-space was ventilated by teachers for 5 to 10 min
before the elementary school students started their activities (Table 4).
Energies 2022, 14, x FOR PEER REVIEW 7 of 23
dust, the temperature, and the CO2 concentration were measured using the Sensirion
SPS30, which is certified by the Monitoring Certification Scheme (MCERTS), a monitoring
certification of the UK Environment Agency, and the Testo 400, respectively. The MPA-
space of the D Elementary School is utilized for various physical education activities, such
as club activities, small soccer, badminton, and playing catch.
As shown in Figure 3, the ultrafine-dust measurement points were measured at two
measurement points with heights of 0.8 m, 1.2 m, and 1.6 m, respectively. For the outdoor
air data, the ‘Ambient air information around our school’ measurement data provided by
the Korea Environment Corporation was used [25]. Figure 4 shows the result of the fine-
dust concentration measured on January 30, when various activities were being
performed in the facility. On January 30, the MPA-space was ventilated by teachers for 5
to 10 min before the elementary school students started their activities (Table 4).
Table 4. Activity schedule of the MPA-space of D elementary school on 30 January 2020.
Time Activity Type
Number of
Occupants Air Purifier Ventilation
before Activity
08:00–08:50 Extracurricular activity 32 On O
09:00–09:40 Catch play 25 On O
09:50–10:30 Catch play 24 On O
11:30–12:10 Catch play 24 On O
13:10–13:50 Catch play 25 On O
14:35–15:10 After-school activity 12 Off O
15:30–15:55 After-school activity 12 Of
f
X
Figure 4. Measurement of ultrafine-dust (PM2.5) concentration in the MPA-space of D elementary
school on 30 January 2020 as a function of the physical activities.
The measurement of the ultrafine-dust concentration revealed that the number of
occupants and activities had no significant effect on the ultrafine-dust concentration;
however, the concentration drastically decreased when the operation of the air purifier
was initiated at 8:00 am (Figure 4). In contrast, the indoor ultrafine-dust concentration
gradually increased from 14:00 when the air purifier was not in operation. Nevertheless,
the concentration of ultrafine dust in the facility was maintained at a significantly lower
concentration than 35µg/m3, which is the standard concentration in ‘Annex 2 Maintenance
Standards’ of the Enforcement Rule of the Domestic Indoor Air Quality Control Act [1].
Figure 4.
Measurement of ultrafine-dust (PM2.5) concentration in the MPA-space of D elementary
school on 30 January 2020 as a function of the physical activities.
Table 4. Activity schedule of the MPA-space of D elementary school on 30 January 2020.
Time Activity Type Number of
Occupants Air Purifier Ventilation
before Activity
08:00–08:50 Extracurricular activity 32 On O
09:00–09:40 Catch play 25 On O
09:50–10:30 Catch play 24 On O
11:30–12:10 Catch play 24 On O
13:10–13:50 Catch play 25 On O
14:35–15:10 After-school activity 12 Off O
15:30–15:55 After-school activity 12 Off X
The measurement of the ultrafine-dust concentration revealed that the number of
occupants and activities had no significant effect on the ultrafine-dust concentration; how-
ever, the concentration drastically decreased when the operation of the air purifier was
initiated at 8:00 am (Figure 4). In contrast, the indoor ultrafine-dust concentration gradually
increased from 14:00 when the air purifier was not in operation. Nevertheless, the concen-
tration of ultrafine dust in the facility was maintained at a significantly lower concentration
than 35
µ
g/m
3
, which is the standard concentration in ‘Annex 2 Maintenance Standards’ of
the Enforcement Rule of the Domestic Indoor Air Quality Control Act [1].
However, the trend in the effect of the activities of the occupants on the CO
2
concen-
trations was significantly different from that of the fine-dust concentration. Despite the
ventilation initiated by the teachers for 5–10 min prior to the physical education class, the
data measured at 1 min intervals at a height of 1.2 m and analyzed for an average of 5 min,
revealed that the maximum CO
2
concentration for each activity was as high as 3183 ppm.
In particular, the number of occupants and activities had a significant effect on the increase
in the CO
2
concentrations (Figure 5), which exceeded the domestic concentration limit
of the Enforcement Rules of the Indoor Air Quality Control in Public-Use Facilities, Etc.
Act [26,27].

Energies 2022,15, 220 8 of 21
Energies 2022, 14, x FOR PEER REVIEW 8 of 23
However, the trend in the effect of the activities of the occupants on the CO2
concentrations was significantly different from that of the fine-dust concentration. Despite
the ventilation initiated by the teachers for 5–10 min prior to the physical education class,
the data measured at 1 min intervals at a height of 1.2 m and analyzed for an average of 5
min, revealed that the maximum CO2 concentration for each activity was as high as 3183
ppm. In particular, the number of occupants and activities had a significant effect on the
increase in the CO2 concentrations (Figure 5), which exceeded the domestic concentration
limit of the Enforcement Rules of the Indoor Air Quality Control in Public-Use Facilities,
Etc. Act [26,27].
Figure 5. Result of the carbon dioxide (CO2) concentration by physical activity in MPA-space in D
elementary school on 30 January 2020.
To analyze the CO2 concentration, which is the most problematic in this type of space,
this study analyzed the effect of the physical activities and the number of occupants on
the CO2 concentration using CONTAM simulation. In addition, the airtightness of the
MPA-space was measured using a blower door test [28].
The airtightness test was conducted using a blower door (Minneapolis Blower
Door™ System, TEC, USA). To measure the airtightness, first each opening element
affecting the airtightness of the applicable space was sealed, after which the sealing
materials were removed sequentially. As shown in Table 5, the opening elements included
the windows in the MPA-space, the supply and exhaust ducts, an indoor EHP, and a door.
Pressurization and depressurization methods (EN 13829) were employed during the
blower door test to seal the exterior- and corridor-side window systems, which were
expected to be major intrusion paths for fine dust, and to remove the plastic pasted during
the sealing of each element until the pressure difference between indoor and outdoor
environment was –10–65 Pa [29–31].
Figure 5.
Result of the carbon dioxide (CO
2
) concentration by physical activity in MPA-space in D
elementary school on 30 January 2020.
To analyze the CO
2
concentration, which is the most problematic in this type of space,
this study analyzed the effect of the physical activities and the number of occupants on
the CO
2
concentration using CONTAM simulation. In addition, the airtightness of the
MPA-space was measured using a blower door test [28].
The airtightness test was conducted using a blower door (Minneapolis Blower Door
™
System, TEC, USA). To measure the airtightness, first each opening element affecting the
airtightness of the applicable space was sealed, after which the sealing materials were
removed sequentially. As shown in Table 5, the opening elements included the windows in
the MPA-space, the supply and exhaust ducts, an indoor EHP, and a door. Pressurization
and depressurization methods (EN 13829) were employed during the blower door test
to seal the exterior- and corridor-side window systems, which were expected to be major
intrusion paths for fine dust, and to remove the plastic pasted during the sealing of
each element until the pressure difference between indoor and outdoor environment was
−10–65 Pa [29–31].
Table 5. Leakage area of the MPA-space.
Element Cumulative EqLA
(cm2)
Cumulative Surface Area
(cm2/m2)
EqLA
(cm2)
Surface Area
(cm2/m2)
1 Element sealing 1941.9 3.98 1941.90 3.98
2 Small window 2011.5 4.12 69.60 0.14
3 Supply air diffuser 2286.5 4.69 129.80 0.27
4 Exhaust air diffuser 2387.3 4.89 100.80 0.20
5 EHP 2410.9 4.94 23.60 0.05
6 Large window 2589.7 5.31 178.1 0.37
7 Door 2913.5 5.97 323.80 0.66
The airtight performance measured using the blower door test can be represented
using several units, such as ACH (Air Change per Hour) and ELA (Effective Leakage Area).
In this study, the measured airtight performance was represented using Equivalent Leakage
Area (EqLA), as shown in Table 5. The EqLA corresponded to the amount of leaked air
as a function of the area when the pressure difference between the inside and outside
environment of a building was 10 Pa [32].

Energies 2022,15, 220 9 of 21
Furthermore, the results of the analysis of the natural ventilation rate using the air
volume ranging from 10 to 65 Pa are represented in the trend line shown in Table 6. The
amount of natural ventilation at 2 Pa, which is the standard pressure difference for installing
natural ventilation facilities according to the Annex Tables 1–3of the Rules on Equipment
Standards for Domestic Buildings, was significantly high (1.58 per hour) [
33
]. This result
indicates that the external air exchange in this facility was active.
Table 6. Change in the air flow rate per hour of the MPA-space of D elementary school.
Energies 2022, 14, x FOR PEER REVIEW 9 of 23
Table 5. Leakage area of the MPA-space.
Element
Cumulative EqLA
(cm2)
Cumulative Surface Area
(cm2/m2)
EqLA
(cm2)
Surface Area
(cm2/m2)
1 Element sealing 1941.9 3.98 1941.90 3.98
2 Small window 2011.5 4.12 69.60 0.14
3 Supply air diffuser 2286.5 4.69 129.80 0.27
4 Exhaust air diffuser 2387.3 4.89 100.80 0.20
5 EHP 2410.9 4.94 23.60 0.05
6 Large window 2589.7 5.31 178.1 0.37
7 Door 2913.5 5.97 323.80 0.66
The airtight performance measured using the blower door test can be represented
using several units, such as ACH (Air Change per Hour) and ELA (Effective Leakage
Area). In this study, the measured airtight performance was represented using Equivalent
Leakage Area (EqLA), as shown in Table 5. The EqLA corresponded to the amount of
leaked air as a function of the area when the pressure difference between the inside and
outside environment of a building was 10 Pa [32].
Furthermore, the results of the analysis of the natural ventilation rate using the air
volume ranging from 10 to 65 Pa are represented in the trend line shown in Table 6. The
amount of natural ventilation at 2 Pa, which is the standard pressure difference for
installing natural ventilation facilities according to the Annex Tables 1–3 of the Rules on
Equipment Standards for Domestic Buildings, was significantly high (1.58 per hour) [33].
This result indicates that the external air exchange in this facility was active.
Table 6. Change in the air flow rate per hour of the MPA-space of D elementary school.
Pressure
Difference
(Pa)
Air Flow
Rate
(m3/h)
Exponent
(n)
Air Change
per Hour
(1/h)
50 7629.73
0.67
13.52
4 1416.80 2.51
2 892.57 1.58
4.2. Simulation Analysis of the MPA-Space
To determine the effect of the number of occupants and the leakage area conditions
on the change in the CO2 concentration of the MPA-space of D elementary school, with a
change in the volume of the facility during the same activity, the change in the CO2
concentration of three elementary schools with different facility volumes was simulated
using CONTAM. The results presented in Table 1 indicate that the D elementary school
exhibits the worst physical activity facility conditions because of its large number of
occupants per unit volume and the poor operation of its facility in introducing outdoor
air due to aging.
In contrast, the analysis of the architectural drawings of the A and H elementary
schools, which corresponded to Cases 2 and 3, revealed that their MPA-spaces were good
as their floor area and height were on an average level. Cases 2 and 3 were selected
because their data can be used for standard model analysis in future studies, and the
results will be highly useful in designs for improving indoor air quality. The CONTAM
simulation analysis of the MPA-space was performed by calculating the amount of CO2
Pressure
Difference
(Pa)
Air Flow
Rate
(m3/h)
Exponent
(n)
Air Change
per Hour
(1/h)
50 7629.73
0.67
13.52
4 1416.80 2.51
2 892.57 1.58
4.2. Simulation Analysis of the MPA-Space
To determine the effect of the number of occupants and the leakage area conditions
on the change in the CO
2
concentration of the MPA-space of D elementary school, with
a change in the volume of the facility during the same activity, the change in the CO
2
concentration of three elementary schools with different facility volumes was simulated
using CONTAM. The results presented in Table 1indicate that the D elementary school
exhibits the worst physical activity facility conditions because of its large number of
occupants per unit volume and the poor operation of its facility in introducing outdoor air
due to aging.
In contrast, the analysis of the architectural drawings of the A and H elementary
schools, which corresponded to Cases 2 and 3, revealed that their MPA-spaces were good
as their floor area and height were on an average level. Cases 2 and 3 were selected because
their data can be used for standard model analysis in future studies, and the results will
be highly useful in designs for improving indoor air quality. The CONTAM simulation
analysis of the MPA-space was performed by calculating the amount of CO
2
generated per
person per hour (g/s) for each activity. To calculate this, Equations (1)–(3) were utilized.
The rate of increase in the CO
2
generated per person per hour for an activity, the mole
number of the CO
2
generated per person per hour for an activity, and the amount of CO
2
generated per person per hour for each activity were derived sequentially. First, using
the experimental results for each activity, the rate of increase in the CO
2
concentration
generated per person per hour for each activity was calculated using Equation (1), which
was proposed by Cho et al. [34,35].
The CO
2
generation rate per person based on an activity can be expressed using
Equation (1).
.
CCO2,P=(C2−C1)
∆tV(1)
where
.
CCO2,P
is the amount of CO
2
generated after the activity of one person per hour
(ppm·m3/min).
C2is the CO2concentration at the end of the activity (ppm).
C1is the CO2concentration at the beginning of the activity (ppm).
Vis the volume of the activity space volume (m3).

Energies 2022,15, 220 10 of 21
∆tis the activity duration (min).
The number of moles of CO
2
generated per person per hour for each activity was
derived by multiplying the number of moles of air and CO
2
by the rate of increase in the
CO
2
concentration per person per hour for each activity, as shown in Equation (2) [
36
–
38
].
The increase in the concentration of CO
2
generated per person per hour for each
activity can be calculated using Equation (2).
.
nCO2,P=.
CCO2,P
1
Vm(2)
where
.
nCO2,P
is the increase in moles of the CO
2
generated by the activity of one person per
hour (kmol/s).
.
CCO2,P
is the increase rate of the concentration of CO
2
generated by the activity of one
person per hour at a given volume (ppm·m3/min).
Vm: The volume of 1 mole of an ideal gas in the standard state, 22.4 L/mol.
The number of moles of CO
2
per hour for each activity was multiplied by the molecular
weight to derive the “the amount of CO
2
generated per person for each activity”, as shown
in Equation (3).
The increase in the CO2concentration per hour per activity can be calculated using:
.
mCO2,P=.
nCO2,PMCO2(3)
where
.
mCO2,Pis the amount of CO2per person per hour for each activity (g/s).
.
nCO2,P
is the molar amount of CO
2
generated per person per hour for each activity
(kmol/s).
MCO2is the molecular weight of CO2(kg/kmol).
Table 7shows the amount of CO
2
generated per person per hour for each activity in
the MPA-space derived using the appropriate equation.
Table 7. CO2generation per person per hour for each physical activity in D Elementary School.
Activity Type Volume of CO2Generated per Person
(ppm·m3/min·Person)
Mass of CO2Generated per Person per Hour
(g/s Person)
Extracurricular Activities 367.64 0.0120
Catch play (09:00~09:40) 515.22 0.0169
Catch play (09:50~10:30) 483.84 0.0158
Catch play (11:30~12:10) 417.63 0.0137
Catch play (13:10~13:50) 603.38 0.0198
After-school activity 328.26 0.0107
The amount of CO
2
generated per person per hour during the stretching and catch
activities, which require rapid movements and a large range of activity per person in the
applicable space, was higher than that generated per person during club and after-school
activities. In addition, the amount of CO
2
generated per person during the same type of
activity varied with a change in the duration of the activity, the change in temperature
according to the duration, and before and after lunch time [
14
,
39
]. To verify the accuracy
of the derived equation and determine the optimum number of occupants, the types
of activities, and the area to be presented in the guidelines, the CO
2
concentration was
predicted using the CONTAM program.
The CONTAM simulation was performed as shown in Figure 6, based on the amount
of CO
2
generated per person per hour for each activity, the initial concentration analyzed
in the ventilation and measurement experiments using the leakage area, the number of
occupants, and the architectural factor information presented in Table 5[40].

Energies 2022,15, 220 11 of 21
Energies 2022, 14, x FOR PEER REVIEW 11 of 23
Table 7. CO2 generation per person per hour for each physical activity in D Elementary School.
Activity Type Volume of CO2 Generated per Person
(ppm∙m3/min∙Person)
Mass of CO2 Generated per Person
per Hour (g/s Person)
Extracurricular Activities 367.64 0.0120
Catch play (09:00~09:40) 515.22 0.0169
Catch play (09:50~10:30) 483.84 0.0158
Catch play (11:30~12:10) 417.63 0.0137
Catch play (13:10~13:50) 603.38 0.0198
After-school activity 328.26 0.0107
The amount of CO2 generated per person per hour during the stretching and catch
activities, which require rapid movements and a large range of activity per person in the
applicable space, was higher than that generated per person during club and after-school
activities. In addition, the amount of CO2 generated per person during the same type of
activity varied with a change in the duration of the activity, the change in temperature
according to the duration, and before and after lunch time [14,39]. To verify the accuracy
of the derived equation and determine the optimum number of occupants, the types of
activities, and the area to be presented in the guidelines, the CO2 concentration was
predicted using the CONTAM program.
The CONTAM simulation was performed as shown in Figure 6, based on the amount
of CO2 generated per person per hour for each activity, the initial concentration analyzed
in the ventilation and measurement experiments using the leakage area, the number of
occupants, and the architectural factor information presented in Table 5 [40].
(a)
1
Figure 6.
(
a
) Zone, pollutants, flow path, and corridor input conditions for the CONTAM simulation;
(b) CONTAM simulation result of CO2concentration.
To examine the effect of the facility volume on the CO
2
generation, a CONTAM
simulation was performed by applying the same occupant and activity conditions used
in Case 1 to three different volumes. Case 1 was formulated by applying the architectural
factors of the D elementary school, which were analyzed and compared to the actual
measurement values. The accuracy of the CONTAM data applied to Case 1 was verified
by calculating the RMSE of the square of the difference and MAPE [
41
]. The accuracy
of the CONTAM data increased with a decrease in the RMSE [
42
–
44
]. MAPE refers to
the percentage of the absolute error representing the accuracy of the simulation value
in statistics [
42
]. The RMSE and MAPE were calculated using Equations (4) and (5),
respectively:
RMSE =r1
n∑n
i=1(yi−ˆ
yi)2(4)
MAPE =100
n∑n
i=1



yi−ˆ
yi
yi



(5)
where
RMSE is the Root mean square error (ppm).
MAPE is the Mean absolute percentage error (%).

Energies 2022,15, 220 12 of 21
nis the number of data.
yiis the measured CO2concentration (ppm).
ˆ
yiis the CO2concentration estimated by the CONTAM simulation (ppm).
To verify the RMSE and MAPE results, the measured values and the CONTAM results
were converted to five-minute unit data. The calculated RMSE was 123.37 ppm, and
the RMSE-percent, which was calculated by dividing the percentage of the RMSE by the
average concentration, was 6.02%. The calculated MAPE was 5.50%9 (Table 8), which is a
relatively low error rate. In addition, A elementary school and H elementary school, which
belong to the average of the architectural and facility factors in Table 1, were selected as
Case 2 and Case 3, respectively, and the CONTAM simulation was performed [45].
Table 8.
Root mean square error (RMSE) and mean accuracy percentage error (MAPE) of the
CONTAM simulation results of the CO2concentration in D Elementary School.
RMSE (ppm) RMSE-Percent (%) MAPE (%)
123.37 6.02 5.50
To increase the accuracy of the CONTAM simulation analysis, the experimental data
measured every minute were converted to five-minute average data and plotted as shown
in Figure 7.
Energies 2022, 14, x FOR PEER REVIEW 13 of 23
Table 8. Root mean square error (RMSE) and mean accuracy percentage error (MAPE) of the
CONTAM simulation results of the CO2 concentration in D Elementary School.
RMSE (ppm) RMSE-Percent (%) MAPE (%)
123.37 6.02 5.50
To increase the accuracy of the CONTAM simulation analysis, the experimental data
measured every minute were converted to five-minute average data and plotted as shown
in Figure 7.
The results revealed that the CO2 concentration gradient varied with a change in
activity. The D elementary school with a Case 1 volume of 564.2 m3 exhibited a drastic
change when the amount of CO2 for each activity was applied. Although the same leakage
area of each element compared to the space volume was applied as the CONTAM
simulation input condition for Cases 1, 2, and 3, the natural reduction in CO2
concentration was higher in Case 1 than in Cases 2 and 3, which were large spaces
containing stagnant air. [46–49].
In addition, the CO2 concentration in Cases 2 and 3 was maintained at concentrations
below 1000 ppm, which is the standard concentration of the “Enforcement Rules of the
Indoor Air Quality Control in Public-Use Facilities, Etc. Act [1]”, after all activities and
below 875 ppm after 14:00 when the number of occupants was relatively low owing to
after-school activities.
To verify the reliability of the previously analyzed data, the indoor-air-quality
measurement and CONTAM simulation analysis according to the activity were
performed in the A elementary school (Case 2) with a large space.
Figure 7. CONTAM simulation of the CO2 concentration of three cases, with similar conditions as
that of the MPA-space of D elementary on January 30th.
4.3. Verification of the Indoor Air Quality of the MPA-Space
To verify the effect of the size of the facility on the properties of the indoor air quality
of the facility for each activity, the indoor air quality of A elementary school was
measured. The ultrafine-dust concentration and the CO2 concentration of A elementary
school were measured using the same method used to calculate that of D elementary
school. The floor area and ceiling height of the medium-sized MPA-space of A elementary
Figure 7.
CONTAM simulation of the CO
2
concentration of three cases, with similar conditions as
that of the MPA-space of D elementary on 30 January.
The results revealed that the CO
2
concentration gradient varied with a change in activ-
ity. The D elementary school with a Case 1 volume of 564.2 m
3
exhibited a drastic change
when the amount of CO
2
for each activity was applied. Although the same leakage area
of each element compared to the space volume was applied as the CONTAM simulation
input condition for Cases 1, 2, and 3, the natural reduction in CO
2
concentration was higher
in Case 1 than in Cases 2 and 3, which were large spaces containing stagnant air. [46–49].
In addition, the CO
2
concentration in Cases 2 and 3 was maintained at concentrations
below 1000 ppm, which is the standard concentration of the “Enforcement Rules of the
Indoor Air Quality Control in Public-Use Facilities, Etc. Act [
1
]”, after all activities and
below 875 ppm after 14:00 when the number of occupants was relatively low owing to
after-school activities.

Energies 2022,15, 220 13 of 21
To verify the reliability of the previously analyzed data, the indoor-air-quality mea-
surement and CONTAM simulation analysis according to the activity were performed in
the A elementary school (Case 2) with a large space.
4.3. Verification of the Indoor Air Quality of the MPA-Space
To verify the effect of the size of the facility on the properties of the indoor air quality
of the facility for each activity, the indoor air quality of A elementary school was measured.
The ultrafine-dust concentration and the CO
2
concentration of A elementary school were
measured using the same method used to calculate that of D elementary school. The floor
area and ceiling height of the medium-sized MPA-space of A elementary school were
616.14 m
2
and 10.4 m, respectively. This facility was equipped with an EHP for heating
and cooling, and a jet air turnover system was installed among the air purification systems;
however, an air purifier that could directly improve fine dusts had not been installed.
Thus, the characteristics of the indoor air quality of the MPA-space of A elementary school,
which has a larger volume than D elementary school, were investigated using experimental
analysis and CONTAM simulations [
50
,
51
]. Figure 8shows an image of the experiment
performed in the MPA-space of A elementary school on 18 November 2020 using the
fine-dust sensor that was utilized in D elementary school. A 160 IAQ, which measures the
indoor and outdoor CO
2
concentration, was installed to consider the effect of the outdoor
air. In addition, the concentration of ultrafine dusts was measured at points A and B, at
heights of 0.6 and 1.2 m.
Energies 2022, 14, x FOR PEER REVIEW 14 of 23
school were 616.14 m2 and 10.4 m, respectively. This facility was equipped with an EHP
for heating and cooling, and a jet air turnover system was installed among the air
purification systems; however, an air purifier that could directly improve fine dusts had
not been installed. Thus, the characteristics of the indoor air quality of the MPA-space of
A elementary school, which has a larger volume than D elementary school, were
investigated using experimental analysis and CONTAM simulations [50,51]. Figure 8
shows an image of the experiment performed in the MPA-space of A elementary school
on 18 November 2020 using the fine-dust sensor that was utilized in D elementary school.
A 160 IAQ, which measures the indoor and outdoor CO2 concentration, was installed to
consider the effect of the outdoor air. In addition, the concentration of ultrafine dusts was
measured at points A and B, at heights of 0.6 and 1.2 m.
The results revealed that the number of occupants and the type of activities had no
significant effect on the ultrafine-dust concentration of the MPA-space of A elementary
school (Figure 9). In addition, the maximum ultrafine-dust concentration at points A and
B at a height of 1.2 m was 11.76µg/m3, and the corresponding outdoor air concentration
was 31.55 µg/m3. To analyze the effects of the activities of the occupants in a space on the
concentration of fine dusts, additional measurements were obtained when the windows
were opened and closed and when the doors were opened and closed [52–54]. Despite the
increase in the concentration of ultrafine dusts in the outside air, the CO2 concentration in
the MPA-space of A elementary school was maintained below 12 µg/m3 without any
change in the concentrations of the ultrafine dusts. In contrast, there was a sharp increase
in the CO2 concentration between 10:15 and 11:45 when the activity started (Figure 10).
Figure 8. Floor plan of the MPA-space of A elementary school.
Figure 8. Floor plan of the MPA-space of A elementary school.
The results revealed that the number of occupants and the type of activities had no
significant effect on the ultrafine-dust concentration of the MPA-space of A elementary
school (Figure 9). In addition, the maximum ultrafine-dust concentration at points A and
B at a height of 1.2 m was 11.76
µ
g/m
3
, and the corresponding outdoor air concentration
was 31.55
µ
g/m
3
. To analyze the effects of the activities of the occupants in a space on the
concentration of fine dusts, additional measurements were obtained when the windows
were opened and closed and when the doors were opened and closed [
52
–
54
]. Despite the
increase in the concentration of ultrafine dusts in the outside air, the CO
2
concentration
in the MPA-space of A elementary school was maintained below 12
µ
g/m
3
without any
change in the concentrations of the ultrafine dusts. In contrast, there was a sharp increase
in the CO2concentration between 10:15 and 11:45 when the activity started (Figure 10).

Energies 2022,15, 220 14 of 21
Energies 2022, 14, x FOR PEER REVIEW 15 of 23
Figure 9. Measurement of the ultrafine-dust concentration (PM2.5) according to activities and
window/door openings in the MPA-space of A elementary school on 18 November 2020.
Figure 10. Change in the CO2 concentration as a function of physical activities and window/door
openings in the MPA-space of A elementary school on 18 November 2020.
Furthermore, the measurement results of placing the CO2 concentration meter
outdoors, and at points A and B, revealed that the indoor CO2 concentration was
approximately 200 ppm lower than that of the outside air at the beginning of the activity
(Figure 10). However, the CO2 concentration increased sharply from 10:15 am when 15
occupants started their activities and continued to increase to 441 ppm (Table 9), which
resulted in values similar to the outdoor CO2 concentration (Figure 10) [55,56]. The
measured indoor CO2 concentration in A elementary school was maintained below the
standard concentration of the “Enforcement Rules of the Indoor Air Quality Control in
Public-Use Facilities, Etc. Act.” To analyze the concentration of CO2 generated during each
activity in A elementary school as a function of the facility volume, a CONTAM
simulation of the CO2 concentration for each activity was performed.
Figure 9.
Measurement of the ultrafine-dust concentration (PM2.5) according to activities and
window/door openings in the MPA-space of A elementary school on 18 November 2020.
Energies 2022, 14, x FOR PEER REVIEW 15 of 23
Figure 9. Measurement of the ultrafine-dust concentration (PM2.5) according to activities and
window/door openings in the MPA-space of A elementary school on 18 November 2020.
Figure 10. Change in the CO2 concentration as a function of physical activities and window/door
openings in the MPA-space of A elementary school on 18 November 2020.
Furthermore, the measurement results of placing the CO2 concentration meter
outdoors, and at points A and B, revealed that the indoor CO2 concentration was
approximately 200 ppm lower than that of the outside air at the beginning of the activity
(Figure 10). However, the CO2 concentration increased sharply from 10:15 am when 15
occupants started their activities and continued to increase to 441 ppm (Table 9), which
resulted in values similar to the outdoor CO2 concentration (Figure 10) [55,56]. The
measured indoor CO2 concentration in A elementary school was maintained below the
standard concentration of the “Enforcement Rules of the Indoor Air Quality Control in
Public-Use Facilities, Etc. Act.” To analyze the concentration of CO2 generated during each
activity in A elementary school as a function of the facility volume, a CONTAM
simulation of the CO2 concentration for each activity was performed.
Figure 10.
Change in the CO
2
concentration as a function of physical activities and window/door
openings in the MPA-space of A elementary school on 18 November 2020.
Furthermore, the measurement results of placing the CO
2
concentration meter out-
doors, and at points A and B, revealed that the indoor CO
2
concentration was approximately
200 ppm lower than that of the outside air at the beginning of the activity (Figure 10). How-
ever, the CO
2
concentration increased sharply from 10:15 am when 15 occupants started
their activities and continued to increase to 441 ppm (Table 9), which resulted in values
similar to the outdoor CO
2
concentration (Figure 10) [
55
,
56
]. The measured indoor CO
2
concentration in A elementary school was maintained below the standard concentration of
the “Enforcement Rules of the Indoor Air Quality Control in Public-Use Facilities, Etc. Act”.
To analyze the concentration of CO
2
generated during each activity in A elementary school
as a function of the facility volume, a CONTAM simulation of the CO
2
concentration for
each activity was performed.

Energies 2022,15, 220 15 of 21
Table 9. Activity schedule of the MPA-space of A elementary school on 18 November 2020.
Time Activity Type Number of
Occupants
Ventilation
before Activity
10:15–10:41 Stretching, rope jump 15 X
10:42–11:45 Badminton 15 X
13:00–14:00 Window open 2 -
14:30–15:00 Hallway door open 2 -
4.4. Simulation Verification Analysis of the MPA-Space
For the CONTAM simulation analysis of the MPA-space of A elementary school, the
amount of CO
2
generated per hour (g/s) per person per activity was calculated using
Equation (3) (Table 10) [
54
]. The amount of CO
2
generated per person per hour for each
physical activity in the MPA-space of A elementary school was significantly higher than that
generated in D elementary school (Table 10). Most of the students in A elementary school
engaged in running-related physical activities, and their scope of activity was significantly
wider than that of the students in the D elementary school, which can be attributed to the
larger space of the MPA-space of A elementary school. The as-calculated amount of CO
2
was utilized to perform the CONTAM simulation analysis by designating D, A, and H
elementary schools as Cases 1, 2, and 3, respectively, as shown in Figure 11. The results
revealed that the CO
2
concentrations of Cases 2 and 3 were maintained below 430 ppm
with no notable change. In contrast, the CO
2
concentrations of the D elementary school
(Case 1) increased sharply to 2500 ppm in 1 h and 30 min owing to its small volume [
55
,
56
].
Table 10. CO2generation per person per hour for each physical activity in A Elementary school.
Activity Type Rate of Increase in CO2Concentration per Person
(ppm·m3/min)
CO2Generation per Person
(g/s Person)
Stretching, rope jump 768.94 0.0252
Badminton 987.29 0.0323
Energies 2022, 14, x FOR PEER REVIEW 17 of 23
Figure 11. CONTAM Simulation of carbon dioxide concentration according to activity type in MPA-
space in A elementary school.
The verification of the experimental results and the CONTAM simulation analysis
revealed that despite the wide scope of activity and the high level of activities, the
concentrations of both D and A elementary schools were maintained below 25 µg/m3,
which is the standard value for the ultrafine-dust concentration prescribed by the WHO.
In addition, the CO2 concentration of A elementary school, which has a larger volume than
D elementary school, was maintained below the standard for the CO2 concentration
prescribed by the “Enforcement Rules of the Indoor Air Quality Control in Public-Use
Facilities, Etc. Act”, which is currently enforced by the South Korean Government.
Therefore, to maintain indoor air quality in an MPA-space with the high respiratory and
activity levels of elementary school students, it is essential to determine the optimum
number of occupants for a particular space size to maintain the CO2 concentration below
the acceptable concentration, as well as the average required size per occupant for indoor
physical education activities and the measures for reducing fine dusts [57].
5. Measures against Increase in Indoor CO2 Concentration Due to Physical Education
Activities
Regardless of the measures currently implemented by the South Korean Government
to reduce fine dusts, the indoor CO2 concentration negatively affected the indoor air
quality of A and D elementary schools. To develop a strategy to maintain the indoor CO2
concentration, which exhibited a high concentration, below 1000 ppm, which is the
domestic concentration limit prescribed by the “Enforcement Rules of the Indoor Air
Quality Control in Public-Use Facilities, Etc. Act”, this study proposed a guideline for
maintaining the optimum average volume required per occupant during indoor physical
education activities, as well as the optimum number of occupants per volume for each
physical education activity [57–60].
5.1. Optimum Volume per Occupant for Each Physical Eduction Activity
The volume required per occupant for each activity to maintain the CO2
concentration below 1000 ppm was derived based on the analysis of the amount of CO2
per person per hour for each physical activity using CONTAM simulation. The
experimental data of D elementary school, including leakage area, initial indoor CO2
concentration, and initial indoor temperature, were utilized [57,59,60].
The results revealed that the minimum required volume for badminton activities was
approximately 133 m3, and the average required volume per person for each activity was
approximately 88 m3 (Table 12). Thus, based on the class presented in Table 2, if 35
Figure 11.
CONTAM Simulation of carbon dioxide concentration according to activity type in
MPA-space in A elementary school.
The accuracy of the CONTAM simulation for the analysis of the CO
2
concentration in
A elementary school was verified using the same method used to verify that of D elementary
school by calculating the RMSE and MAPE, an