Feras Essam Balkhi

INDOOR AIR QUALITY, MITIGATING CO2 CONCENTRATION IN CLASSROOMS USING ADJACENT CORRIDORS AND ATRIUMS FERAS ESSAM MOHAMMED BALKHI

Master of Architecture (Second semester) Supervisor: 1Dr. Mustafa Sabbagh, 2Dr-ing. Mohannad Bayoumi

Department of Architecture (KAUARCH) Faculty of Architecture and planning King Abdulaziz University

CONTENT 01. INTRODUCTION 1.1 Problem statement 1.2 Objective 1.3 Literature review 1.3.1 IAQ in classrooms 1.3.2 Standards for CO2 concentration 02. METODOLOGY 2.1 Study method 2.2 Field measurment 03. ANALYSIS 3.1 Maintaining Thermal Comfort study 3.2 CO2 study 3.2.1 Validation 04. MODELING 4.1 Occupants densities in the classroom 4.2 Simplifying the study case 4.3 Occupancy schedule 4.3.1 Results 4.4 Applying the air exchange 4.6 Comparing scenarios 05. CONCLUSION 5.1 Conclusion and Recommendations 06. REFERENCES 02

01. INTRODUCTION

1.1 Problem statement 1.2 Objective 1.3 Literature review 1.3.1 IAQ in classrooms 1.3.2 Standards for CO2 concentration

03

01. INTRODUCTION

1.1 Problem statement Indoor air quality (IAQ) is an essential factor that decides occupants’ level of satisfaction and performance. Classroom are more critical due to typically high occupancy density. The over-crowdedness of classroom is a serious and quite common issue.

Can be studying to find approach using the total air supply entering the building of Constant Air Volume (CAV) system, reducing CO2 concentration in classrooms, without affecting the thermal comfort ?

The larger the classroom, the greater the dilution of levels of carbon dioxide (CO2) and pollutants, and the longer good air quality can be maintained. In an average size classroom with a volume of 181 cubic meters, 30 occupants and no ventilation, the air quality becomes poor in just 30 minutes [1].

1.2 Objective

This paper aims to test the viability of air exchanging between the classrooms and other adjacent indoor spaces, to enhance the overall levels of CO2 concentration, as a quick solution for an overcrowded classrooms.

Ventilation can be the most important factor affecting IAQ, as confined air in closed space without renewal can be contaminated by several pollutants, including: Radon, CO2, carbon dioxide, bacteria and other volatile chemical particles [3].

Occupants are the main indoor source of CO2. The CO2 is easy to measure as a surrogate for indoor pollutants. Indoor CO2 levels are a good indicator of ventilation efficiency witch directly indicate to the quality of the indoor air [3].

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01. INTRODUCTION 1.3 Literature review

1.3.1 IAQ in classrooms

Classrooms has a large occupancy density. Where classroom occupants, on daily bases spend most of there active day within it. This space creating an interactive and educational environment that must be reviewed and assessed by the IAQ conditions.

In particular, the greater number of occupants with one unchanged space, which leads to the classroom spaces.

O

C

%

Thermal comfort affecting CO2 concentration in classrooms

Several studies indicated CO2 as a factor of evaluation for air quality in space. Maintaining the temperature and relative humidity as effects of CO2 concentration.

The correlated with relevant environmental parameters is humidity, radiant temperature, air velocity. CO2 concentrations and temperatures are important factors within buildings, it's affecting the occupant performance and particularly cognitive performance regarding all mental activities such as thinking, reasoning, and remembering [4].

The evaluating of CO2 concentrations as indicator of air quality, maintaining temperature, and relative humidity are the common and related factors that affect the IAQ in the classrooms.

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01. INTRODUCTION 1.3 Literature review

1.3.1 IAQ in classrooms Bad IAQ influences on occupants in classrooms

IAQ in schools is often very low. and the indoor air pollutants have an impact on occupants' health, comfort, and productivity [5].

Building-related symptoms were significantly and positively associated with the concentration of colony-forming units of molds in floor dust: eye irritation, throat irritation, headache, concentration problems, and dizziness [7].

Investigations have proven the effectiveness of evaluating and improving IAQ may enhance the educational space and the Comprehension of students.

Decreasing classrooms’ temperature from 25°C to 23°C, and also increasing temperature from 20°C to 23°C whilst decreasing CO2 levels from 1800 ppm and/or 1000 ppm to 600 ppm significantly improved the performance of adult students in a memory and attention tasks [4].

Cold, hot and warm sensations can negatively affect mental performance for memory and attention tasks while mild cooling sensation can improve mental alertness [4].

Low rates of ventilation in classrooms significantly reduce pupils’ attention and vigilance, and negatively affect memory and concentration and the physical environment. Therefore, affects teaching and learning [6].

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01. INTRODUCTION 1.3 Literature review

1.3.1 IAQ in classrooms Importance of ventilation affecting CO2

Classrooms have a higher level above 1000 ppm. A. S. Hassan Abdallah found the reason of this problem was because teachers close the doors and depend on mechanical fans and single side ventilation from windows for ventilation without continuous airflow of fresh air. Also found CO2 level decreases during the school break in 30 minutes due to the opening door without student occupation [8].

In study showed that the energy demand in school buildings was reduced by 38% for a CO2-DCV compared with an CAV system. [9] In study, the DCV system was able to deliver and maintain a good IAQ, even at reduced air flow rates. The VAV dampers or extract fans respond well to predefined set points of CO2 concentration and tempera- ture. Even at low air flow rates, it was noticed that the ventila- tion efficiency was not affected. This shows that demand controlled ventilation is effective in distributing the air even at reduced air flow rates. [10]

1.3.1 Standards for CO2 concentration

CO2 levels and potential health problems are indicated below: Table 1 [11].

Concentration (ppm)

Effects

400-1000

Typical level found in occupied spaces with good air exchange

1000-2000

Complaints of drowsiness and poor air

2000-5000

Headaches, sleepiness and stagnant, poor concentration, loss of attention

5000

Workplace exposure limit (as 8-hour TWA) in most jurisdictions

40000

May lead to serious oxygen deprivation resulting in permanent brain damage, even death

Table 1, Influences of CO2 concentrations FERAS ESSAM BALKHI - IAQ, Mitigating CO2 concentration in classrooms using adjacent corridors and atriums - 01. INTRODUCTION

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02. METODOLOGY

2.1 Study method 2.2 Study structure 2.3 Field measurment

FERAS ESSAM BALKHI - IAQ, Mitigating CO2 concentration in classrooms using adjacent corridors and atriums - 02. METHODOLOGY

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02. METHODOLOGY 2.1 Study method

This study investigates a prototype classroom building in Jeddah, as case study. The study involved maintaining the thermal comfort and evaluating CO2 concentration.

The case windows condition is not designed with natural ventilation systems (no opining windows). In set of mechanically air-conditioned space using CAV system.

Study simulating a combined approach by exchanging the air-conditioned adjacent common spaces (i.e. corridors and atriums) with the classrooms. Also, should not ignore the over crowdedness issue of classrooms, by reconsidering the occupancy schedule and number of occupants, which causes a high level of CO2 concentration. The reason of high CO2 concentrations was the low intensity of ventilation and a high number of occupants during the lecture time in one closed space [7].

Selecting and study one classroom as a case sample. Using the field measurement devices will set up the device in the middle of the classroom with a height of 1.1m for the level of the occupants breathe, to evaluate the IAQ of the space.

The measuring device used to evaluate the relative humidity and temperature of the study sample to calculate the thermal comfort effect. Validate using the collected data. Field observations such as space dimensions and occupants’ number of the space to get the full current condition of the case sample.

Maintaining thermal comfort. Then, simulating CO2 as an indicator of air quality, occupancy density, and mechanical system type, using software (IDA ICE).

Reviewing the occupants densities and typical scheduling of the classrooms. Studying and applying the occupancy scheduling of adjacent spaces to simulate the study case.

Discussing influences of any change may cause by one classroom to reach a quick solution of space efficiency with the lowest potential losses of change space.

Then comparing the scenarios and results. aiming to upgrade the IAQ of space in Saudi Arabia classrooms to confirm the findings and scale the problem size which may lead to new policy and refurbishment of schools.

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02. METHODOLOGY 2.2 Study structure

Evaluate CO2

Validation

Classroom Occupants

Applying

Schedule Results

Selecting sample

Current condition

Modeling and siumaltion

Suggested solution Scenarios

Measurement

Maintaining thermal comfort

Research sample

Simplifying

Conclusion and Recommendations

Schedule

Corridors and atriums

Comparing

Analyze

FERAS ESSAM BALKHI - IAQ, Mitigating CO2 concentration in classrooms using adjacent corridors and atriums - 02. METHODOLOGY

Findings

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02. METHODOLOGY

2.3 Field measurment Installing CO2 sensors as a parameter of the IAQ condition in the classroom. Also, promoted conscious ventilation in each classroom by involving the teachers to manage the manual airing and suggests frequent and short periods of window openings [9].

Measurements devices were installed in one of the buildings of the current preparatory year in educational classroom to measure the IAQ using (HOBO onset data logger U10-003) Specific for measure CO2 concentration in air, temperature and relative humidity of these enclosed spaces as shown in the drawing. The designed occupation capacity of the classroom is 40 occupants (Figure 1).

Monitoring in more than one period depending on the space condition in terms of use. Install accurate measuring devices that detect and record measurements of temperature and relative humidity within the case sample (Figure 2,3,4).

Figure 1, Field measurment

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02. METHODOLOGY 2.3 Study tools

MEASUREMENT

SIMULATION

HOBO onset data logger U10-003

IDA ICE

Specific for measure CO2 concentration in air, temperature and relative humidity

Specific for measure CO2 concentration in air, temperature and relative humidity

Measurements devices were installed in one of the buildings of the current preparatory year (No.535) in educational classroom to measure the quality determinants of these enclosed spaces as shown in the drawings.

The variables were monitored in more than one period depending on the space condition in terms of use.

IDA Indoor Climate and Energy (IDA ICE) is a Building performance simulation (BPS) software. IDA ICE is a simulation application for the multi-zonal and dynamic study of indoor climate phenomenas as well as energy use. The implemented models are state of the art, many studies show that simulation results and measured data compare well.

FERAS ESSAM BALKHI - IAQ, Mitigating CO2 concentration in classrooms using adjacent corridors and atriums - 02. METHODOLOGY

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02. METHODOLOGY

2.3 Field measurment

1.06 m

9.14 m

1.06 m

1.06 m

7.50 m

Figure 3, Classroom plan MEASUREMENT TOOL SPOT HEIGHT 1.10 m

3.00 m

Figure 2, Case sample (classroom) Space volume: 205.5 m3

Figure 4, Classroom section

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03. ANALYSIS

3.1 Thermal Comfort study 3.2 CO2 study 3.2.1 Validation

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03. ANALYSIS

3.1 Thermal comfort study The two most important variables affecting the thermal comfort in the classroom is temperature and relative humidity. The data average readings were shown on the Psychrometric chart to determine whether the results were within the range of thermal comfort zone or not. As shown in the diagram (Figure 5), data average is placed in the comfort zone.

Relativ e humidity (%)100

90

80

70

60

Absolute humidity (kg/kg) 50 40

30

0.0550

0.0500

40 0.0450

Data average

0.0400

Temperature: 22.25 C Relative humidity: 66.5% o

35

0.0350 20

Data taken at 2019.Oct.13

0.0300

Dry bulb temperature Absolute humidity Relative humidity Wet bulb temperature Comfort zone

30

COMFORT ZONE

0.0250

DATA AVERAGE

0.0200

25 10

0.0150 20

0.0100

15 10

0.0050

5 0

Wet bulb temperature (°C) -10 -40 -35 -30 Dry bulb temperature (°C)

-25

-20

-15

-10

-5 -5

0

5

10

15

20

25

30

35

40

45

50

55

60

65

0.0000

Figure 5, Psychrometric chart of the classroom

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03. ANALYSIS

3.1 Maintaining thermal comfort study

1.06 m

9.14 m

1.06 m

1.06 m

7.50 m

Figure 7, Classroom exterior edge plan

Figure 6, Classroom exterior edge

Because of the hot climate of Jeddah, the exterior edge facade of the classroom is exposed to high temperatures that may affect the indoor thermal comfort (Figure 6,7) The study trying to find a quick solution without effecting the thermal comfort in classrooms.

Considering this condition rate maintained and not negatively affected, as it is related to CO2, which may affect the study solutions.

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03. ANALYSIS

3.2 CO2 Study

CO2 monitored in two different days, one on a day off and the other due workday where occupants are in the classroom.

According to the typical scheduling of the classroom, it is divided into two periods. The first period has the general studying subjects, which contains a larger number of occupancy and almost getting to the full capacity of the classroom. And its starting from 8:00 a.m. until 12:00 p.m. The chart shows a high increase in CO2 concentrations in the lecture due to the classroom.

Consequently, CO2 emissions due to student’s congestion increase to a concentration level of 1270 ppm (Table 2), which is above the standard. Although the accumulation of CO2 in the last few hours, the second period comes after one hour of lunch break with no occupancy inside the classroom.

Therefore, the chart showing a drop in CO2 concentration. Continuously, Starting the second period at 13:00 p.m., until 16:00 p.m. This period has specialized subject courses, which contains less number of occupancy than the morning period. Clearly, the chart showing a good continuous result of the evening period.

Because of the low number occupancy which often being less than the space half design capacity (Figure 4).

MAX

AVG

MED

MIN

1270

855

890

434

Table 2, CO2 Measurements data due workday

Starting PEAK 9:50 am. 1270 ppm 10:30 am.

1400

End 12:00 am.

CO2 CONCENTRATION (ppm)

ppm

1200 ppm

1000 ppm

800 ppm

600 ppm

400 ppm

200 ppm

0

17

:0 0

ppm

DAY TIME CLASS OFF

CO2 STANDARD

WORKDAY CO2 LEVEL

DAYOFF CO2 LEVEL

Figure 8, CO2 Concentration FERAS ESSAM BALKHI - IAQ, Mitigating CO2 concentration in classrooms using adjacent corridors and atriums - 03. ANALYSIS

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03. ANALYSIS

3.2.1 Validation Depending on the typical schedule of the classroom and using the lowest point as zero occupancies, it found that the line reaches the peak point with an of 34 occupancies. Also, the evening period is getting in between 23-26 occupants in the classroom. caused by a lower number of occupancy than the designed space capacity.

It leads to the designed space capacity that does not match 40 occupants per classroom as it designed. Taking the measurements and comparing them with the simulation result measurements from the simulation program while entering the same values of the timing and duration of the break times and the number of occupants. A slight difference in the results of the measurements does not exceed -2.75% or +2.75% as a margin of error between the reality and the simulations (Figure 9).

1800 ppm 1600 ppm 1400 ppm 1200 ppm 1000 ppm 800 ppm 600 ppm 400 ppm 200 ppm

0

Field measurment

Validation

Figure 9, Validation FERAS ESSAM BALKHI - IAQ, Mitigating CO2 concentration in classrooms using adjacent corridors and atriums - 03. ANALYSIS

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04. MODELING

4.1 Occupants densities in the classroom 4.2 Simplifying the study case 4.3 Occupancy schedule 4.3.1 Results 4.4 Evaluating the current condition CO2 concentrations 4.5 Applying the air exchange 4.6 Comparing scenarios

FERAS ESSAM BALKHI - IAQ, Mitigating CO2 concentration in classrooms using adjacent corridors and atriums - 04. MODELING

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04. MODELING

4.1 Occupants densities in the classroom

9.14 m

4.1 A

1.06 m

1.06 m

7.50 m

According to the standard, in the simulation the occupants number was reduced to 30 occupants in the classroom to fits the designed space. A good decrease in the CO2 concentration level by 12.5% can make a good help to reduce the CO2 concentration in classroom. (Figure 11)

1.06 m

03

CO2 concentration can be reduced by reducing the number of occupants in the classroom. The large number of occupants in one closed space such as the classroom, increases the rates of CO2 concentration. This classroom contains a high number of occupants above the standard by 40 occupancies for 68.5m2 with furniture in rows and freely arranged. Each occupant needs a space of 1.8 - 2.0 m2 in the classroom [12]. (Figure 10)

Students: 30 - Area: 68.5

Figure 11, Occupants in classroom

1600 ppm

1400 ppm

1200 ppm

1000 ppm

800 ppm

600 ppm

400 ppm

200 ppm

0

Current condition (40 Occupants)

Proposed solution (30 Occupants)

Figure 10, Comparing occupants densities FERAS ESSAM BALKHI - IAQ, Mitigating CO2 concentration in classrooms using adjacent corridors and atriums - 04. MODELING

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04. MODELING

Atrium zone Space volume: 5,484.8 m3

4.2 Simplifying the study case 4.2 A

Corridors zone Space volume: 1346 m3

Using Simulation to simplify the study case, sizing down the space proportionality of the corridor and atrium to the classroom. By allocating a space volume form corridor and atrium for each classroom (Figure 12,13,15). The classroom space was filled with the same number of occupants of this space under the real circumstances and opining all the three spaces classroom, corridor and, atrium to each other. As a result, the simulation shows the decrease in the concentration of CO2 reaches 946.23 ppm at its highest point (Figure 14). In this case, it is a priority to reconsider the proportionality between these areas by increasing the classroom space or reducing the adjacent spaces.

That is a costly solution that may lead to a redesign of the built spaces or to find another quick solution.

Figure 12, Space volume allocating 01

Classroom zone Space volume: 205.5 m3

Classroom zone Space volume: 210 m3

PEAK 946.23 ppm 10:20 am.

1400 1200

Atrium zone Space volume: 52.67 m3

1000 800

Corridors zone Space volume: 51.77 m3

600 400 200

7

0

CO2 standard

Field measurment

SimpliďŹ ed the study case

Figure 14, CO2 Concentration in allocated classroom

Figure 13, Space volume allocating 02

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04. MODELING

4.2 Simplifying the study case 4.2 B

Using Simulation to simplify the study case, sizing down the space proportionality of the corridor and atrium to the classroom. By allocating a space volume form corridor and atrium for each classroom (Figure 12,13,15). The classroom space was filled with the same number of occupants of this space under the real circumstances and opining all the three spaces classroom, corridor and, atrium to each other. As a result, the simulation shows the decrease in the concentration of CO2 reaches 946.23 ppm at its highest point (Figure 14). In this case, it is a priority to reconsider the proportionality between these areas by increasing the classroom space or reducing the adjacent spaces.

That is a costly solution that may lead to a redesign of the built spaces or to find another quick solution.

PEAK 946.23 ppm 10:20 am.

1400

03 Atrium

Classroom open to atrium Classroom open to corridor

PEAK 793.50 ppm 15:00 am.

1200 1000 800

Corridor

600 400 200

7

0

CO2 standard

Field measurment

Classroom open to atrium

Figure 15, Floor spaces allocating

Classroom open to corridor

Figure 14, CO2 Concentration in allocated classroom

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04. MODELING

4.3 Occupancy schedule

CURRENT CONDETION

4.3 B

First semester 2020 - Student classes schedule

A. Classroom schedule

According to the typical scheduling of the classroom (Figure 16), it is divided into two periods. The first period has the general studying subjects, which contains a larger number of occupancy and almost getting to the full capacity of the classroom. And its starting from 8:00 a.m. until 12:00 p.m.

The last few hours, the second period comes after one hour of lunch break with no occupancy inside the classroom. (Figure 17)

Figure 16, Typical classroom schedule

Occupancy time Without occupancies

Classrooms schedule 10 min. break DURING WORKDAY

60Min.

50Min.

01

02

OFF

7:00

10Min.

WORKDAY START

10Min.

03

CLASS

8:00

50Min.

10Min.

04

CLASS

9:00

50Min.

10Min.

05

CLASS

10:00

50Min.

10Min.

06

CLASS

11:00

50Min.

10Min.

07

BREAK

12:00

50Min.

10Min.

08

CLASS

13:00

50Min.

09

CLASS

14:00

60Min.

50Min.

10

CLASS

15:00

Figure 17, Simplifying classroom schedule

FERAS ESSAM BALKHI - IAQ, Mitigating CO2 concentration in classrooms using adjacent corridors and atriums - 04. MODELING

OFF

16:00

WORKDAY END

17:00

23

04. MODELING

4.3 Occupancy schedule 4.3 B

B. Interspersed brakes time schedule

Interspersed brakes time schedules reviewed and simulated in three scenarios. proposed 01 (current condition) as 10 minutes break times in between each class session. proposed 02 as the same current condition instead of 10 minutes it's going to be 15 minutes. The proposed 03 is a different case with 5 min. break - 30 min. break to test the CO2 affecting by Interspersed breaks. The graph showing that the third proposal is worst than the current condition. The proposed 02 is in a slight difference from the current condition by 3%.

1800 ppm 1600 ppm 1400 ppm 1200 ppm 1000 ppm 800 ppm 600 ppm 400 ppm 200 ppm 0

10 min. break (current condition)

15 min. break (proposed 01)

5 min. break - 30 min. break (proposed 02)

Figure 18, Comparing proposed Interspersed brakes time schedules FERAS ESSAM BALKHI - IAQ, Mitigating CO2 concentration in classrooms using adjacent corridors and atriums - 04. MODELING

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04. MODELING

4.3 Occupancy schedule 4.3 C

C. Corridors and atriums schedule

Based on the classroom schedule, a high number of occupants is using the classroom eight times as a period for 50 minutes.

Interpose these classroom periods 10 minutes break time after each class. The adjacent indoor spaces such as corridors and atriums have the opposite schedule of occupancy (Figure 18).

Occupancy time Without occupancies

Corridors and atriums schedule HOURS DURING WORKDAY 60Min.

50Min.

01

02

OFF

7:00

10Min.

WORKDAY START

10Min.

03

OFF

8:00

50Min.

10Min.

04

OFF

9:00

50Min.

10Min.

05

OFF

10:00

50Min.

10Min.

06

OFF

11:00

50Min.

10Min.

07

ON

12:00

50Min.

10Min.

08

OFF

13:00

50Min.

09

OFF

14:00

60Min.

50Min.

10

OFF

15:00

Figure 19, Corridors and atriums schedule

FERAS ESSAM BALKHI - IAQ, Mitigating CO2 concentration in classrooms using adjacent corridors and atriums - 04. MODELING

OFF

16:00

WORKDAY END

17:00

25

04. MODELING

4.3 Occupancy schedule 4.3 D

D. Using the indoor edge of the classroom

1.06 m 1.06 m 1.06 m

Classroom adjacent spaces (i.e. corridors and atriums) tend to have better CO2 levels due to its occupancy schedule/density.

Taking advantage of the total fresh air entering the building from the CAV system. The adjacent common spaces have a large space of unused fresh air compared to the closed classroom spaces (Figure 20).

9.14 m

CORRIDOR

Figure 21, Utilizing adjacent common spaces

Figure 20, Classroom indoor edge

By exchanging the air between these spaces, it can make utilization of the adjacent common spaces as a reserve of fresh air, to mitigate the CO2 accumulate concentrations in the closed and fully occupied classrooms. This approach is not impacting the energy consumption by using a new fresh air. Because it's using the fresh air that is already inside the building. Moreover, not impacting the thermal comfort of using outdoor ventilation in the hot climate. Aiming to reach the lowest potential losses of building physical change (Figure 19).

FERAS ESSAM BALKHI - IAQ, Mitigating CO2 concentration in classrooms using adjacent corridors and atriums - 04. MODELING

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04. MODELING

4.4 Evaluating the current condition CO2 in classrooms

CO2 concentration

Scenario 01 (current condition)

Entering the data collected of the field measurements into the simulation software for an entire floor of the building based on maximum capacity of the educational spaces, scheduling and duration of the break times is equal to 10 minutes between every two classes and one our break after 12:00 pm.

30

31

56

zone 06

49

48

Atr. 36

zone 04

52

zone 02

42

41

40

39

zone 17

Atr. 24

32

54

51

zone 09

38

33

34

zone 16 zone 19

zone 07

44

46

53

zone 15

45

50 zone 01

zone 05

47

zone 11

55

zone 08 zone 14

As evaluation of the current condition. The simulation results Shows the IAQ suffocation of the classrooms due to CO2 accumulatio (Figure 22). All the classrooms showing a high level of CO2 concentration above 1000 ppm. The classrooms 45 and 48 got the highest levels of CO2 concentration reaches above 2000 ppm, because of the high number of occupants, and with the smallest designed classroom spaces.

As shown the adjacent corridors and atriums have the lowest concentrations of CO2, because the occupation schedule of this spaces is usually low. Examining the previous of exchanging the fresh air between these spaces and classrooms to mitigate the CO2 levels.

Max. 2000 ppm

Min. 400 ppm

zone 18

43 35

37

Figure 22, CO2 Current condition (scenario 01) FERAS ESSAM BALKHI - IAQ, Mitigating CO2 concentration in classrooms using adjacent corridors and atriums - 04. MODELING

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04. MODELING

4.5 Applying the air inďŹ ltration Applying the proposed solution by using the simulation software. All the spaces on one of the building floors, opened to each other to verify the effectiveness. By opening a rectangular aperture in each classroom to infiltration the classroom air to the adjacent space with the high unused fresh air to mitigate the CO2 accumulate concentrations (Figure 23).

OUTSIDE AIR

30 90% Occupied

31

Air infiltration CO2 sensor in classroom

zone 06

49

48

zone 04

42

41

40

39

zone 17

Atr. 24

32

54

52

51

zone 09

38

33

34

zone 16 zone 19

zone 07

Figure 24, CAV system with openings

Atr. 36

zone 02

CLASSROOM INDOOR AIR

53

zone 15

44

46 50% Occupied

45

50 zone 01

47

zone 05

ATRIUM

zone 11

55

zone 08 zone 14

CORRIDOR

10% Occupied

56

zone 18

43 35

37

Figure 23, Openings in the classrooms with adjacent areas

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04. MODELING

4.5 Applying the air inďŹ ltration CO2 concentration

Scenario 02 (CAV with air inďŹ ltration)

Due to the simulation, by opening a rectangular aperture in each classroom allowing to air infiltration to adjacent spaces finding a decrease in the highest value of the CO2 concentration in classroom number 48 by 29.6%, from 2008 ppm to 1414 ppm (Figure 25).

30

31

56

zone 06

Atr. 36

zone 04

52

zone 02

42

41

40

39

zone 17

Atr. 24

32

54

51

zone 09

38

33

34

zone 16 zone 19

zone 07

44

46

53

zone 15

45

50 zone 01

47

zone 11

55

zone 08 zone 14

49

48 zone 05

CO2 response Average values of CO2 concentration in classrooms generally decreased by 13.1%.

In scenario 01, the total average CO2 in classrooms was 1513 ppm, decreased to 1314 ppm after applying the scenario 02.

Seeking to drop the CO2 concentrations nearly to 1000 ppm. Noticing an increase in CO2 concentration levels at the corridors and atriums caused by the accumulate of CO2 in adjacent classrooms. In scenario 01, the average CO2 for corridors and atriums was 880 ppm. But, the scenario 02 increased that average CO2 concentrations to 1026 ppm. That is not making a problem like the ones in the classrooms, because it contains a high occupancy rate while in its counterpart (Figure 26).

Max. 2000 ppm

Min. 400 ppm

zone 18

43 35

37

Figure 25, Applying air exchange with indoor openings (scenario 02) FERAS ESSAM BALKHI - IAQ, Mitigating CO2 concentration in classrooms using adjacent corridors and atriums - 04. MODELING

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04. MODELING

4.6 Comparing scenarios CO2 concentration Max. 2000 ppm

Min. 400 ppm

CO2 level (ppm) 2100 2000 1900 1800 1700 Average scenario 01 (1513 ppm)

1500 1400

Average scenario 02 (1314 ppm)

1300 1200 1100 1000 900

Classrooms

1600

Average scenario 02 (1026ppm)

Standard CO2 level

Average scenario 01 (880 ppm)

800 700 600

30 31 32 33 34 35 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 01 02 04 05 06 07 08 09 10 11 14 15 16 17 18 19 24 36 Atr.Atr.

Zone number (classrooms)

Zone number (corridors and atriums)

Scenario 01 (current condition) Scenario 02 (CAV with air inďŹ ltration)

Figure 26, Comparing scenarios

FERAS ESSAM BALKHI - IAQ, Mitigating CO2 concentration in classrooms using adjacent corridors and atriums - 04. MODELING

Corridors and atriums

500 Outdoor ambient CO2 level (400)

Zone 30 31 32 33 34 35 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 01 02 04 05 06 07 08 09 10 11 14 15 16 17 18 19 Atr. 24 Atr. 36

Scenario 01 Scenario 02 1455 1150 1455 1277 1446 1182 1455 1317 1455 1318 1455 1318 1455 1318 1455 1300 1455 1299 1455 1299 1455 1299 1513 1418 1513 1419 1455 1287 1840 1509 1653 1459 1653 1459 2008 1414 1455 1274 1455 1147 1455 1303 1455 1200 1455 1208 1455 1290 1513 1402 1455 1297 796.6 796.7 727.9 846.4 804.2 978.4 933.2 922.8 805.7 729.8 979.4 1006 1017 1076 1015 965.3 732.1 706.3

974 1064 981 1123 1037 1087 1087 1109 1092 953.8 1088 1127 1113 1193 1111 1056 961.4 945.2

Table 3, Comparing scenarios zones 30 28

04. MODELING

4.7 Demand controlled ventilation system Scenario 02 (DCV with air exchange) Demand controlled ventilation (DCV) is a feedback control method to maintain indoor air quality that automatically adjusts the ventilation rate provided to space in response to changes in conditions such as occupant number or indoor pollutant concentration.

In this case, applying the DCV system could be more efficient because of the building condition of the high intensity of occupation and the low space's area of classrooms.

CAV system with CO2 sensor in extract air

Installing the CO2 sensor in the extract duct. The concentration of CO2 is continuously measuring and represents the mean value in the building. Due to the feedback control, an increase of the CO2 concentration leads to an increased flow rate. (Figure, 24) The system checks the air quality in the extract duct every 30 min and increases the airflow according to the sensor signal. The systems start in idle mode with fans turned off. Every 30 min, the CO2 concentration is checked after the systems was operated on basic flow rate for 5 min. If the concentration is below 600 ppm, the system goes to idle again, if it is above 600 ppm, the basic flow rate is activated for 30 min. Then, the concentration is checked again. If the value is then still above 600 ppm, the systems goes to the nominal flow rate until concentrations are below 600 ppm again. If it has decreased and is now below 600 ppm again, the system goes to idle mode. [13]

Ventilation off check CO2 concentration every 30 min. for 5 min. basic flow rate

CO2 > 600 ppm ?

No

Yes Basic flow rate for 30 min. then check CO2 concentration Yes

CO2 > 600 ppm ?

No

Nominal flow rate for 30 min. then check CO2 concentration Yes

CO2 > 600 ppm ?

No

Table 4, Operating levels for the airflow rate: Off

Basic flow

Nominal flow

0 m3/h

115 m3/h

145 m3/h

Figure 27, Control of CAV system with CO2 sensor in extract.

FERAS ESSAM BALKHI - IAQ, Mitigating CO2 concentration in classrooms using adjacent corridors and atriums - 04. MODELING

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04. MODELING

4.8 Applying air exchange Scenario 03 (DCV with air exchange) The decrease in the highest value of the CO2 concentration in classroom 48 from 2008 ppm to 880.8 ppm. Also, the average values of CO2 concentration generally decreased by 49.3%. The decreasing point for classrooms scenario 01 compared with scenario 03 decreased by 746 ppm. Comparing scenario 03 with the current condition into adjacens spaces, the CO2 concentration is almost the same.

OUTSIDE AIR

90% Occupied

30

Air exchange CO2 Sensor in extract

31

56

zone 06

49

48

zone 11

55

zone 08

50

53

54

Figure 28, DCV system with openings

zone 04

42

41

40

39

zone 17

Atr. 24

32

52

zone 02

CLASSROOM INDOOR AIR

Atr. 36

51

zone 09

38

33

34

zone 16 zone 19

zone 07

44

46 50% Occupied

45

zone 01

zone 05

47

zone 15

ATRIUM 10% Occupied

zone 14

CORRIDOR

zone 18

43 35

37

Figure 29, DCV system with openings in the classrooms

FERAS ESSAM BALKHI - IAQ, Mitigating CO2 concentration in classrooms using adjacent corridors and atriums - 04. MODELING

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04. MODELING

4.9 Comparing scenarios CO2 concentration Max. 2000 ppm

Min. 400 ppm

CO2 level (ppm) 2100 2000 1900 1800 1700 Average scenario 01 (1513 ppm)

1500 1400

Average scenario 02 (1314 ppm)

1300 1200 1100 1000 900

Average scenario 02 (1026ppm)

Standard CO2 level

Average scenario 01 (880 ppm)

800 700 600

Classrooms

1600

Average scenario 03 (767 ppm)

Average scenario 03 (777 ppm)

30 31 32 33 34 35 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 01 02 04 05 06 07 08 09 10 11 14 15 16 17 18 19 24 36 Atr.Atr.

Zone number (classrooms)

Zone number (corridors and atriums)

Scenario 01 (current condition) Scenario 02 (CAV with air inďŹ ltration) Scenario 03 (DCV with air exchange)

Figure 30, Comparing scenarios

FERAS ESSAM BALKHI - IAQ, Mitigating CO2 concentration in classrooms using adjacent corridors and atriums - 04. MODELING

Corridors and atriums

500 Outdoor ambient CO2 level (400)

Zone 30 31 32 33 34 35 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 01 02 04 05 06 07 08 09 10 11 14 15 16 17 18 19 Atr. 24 Atr. 36

Scenario 01 Scenario 02 Scenario 03 1455 1150 669 1455 1277 773 1446 1182 686 789 1455 1317 1455 1318 789 1455 1318 789 1455 1318 788 787 1455 1300 1455 1299 787 1455 1299 787 804 1455 1299 1513 1418 804 1513 1419 787 1455 1287 720 1840 1509 789 669 1653 1459 799 1653 1459 853 2008 1414 749 1455 1274 723 1455 1147 736 1455 1303 748 1455 1200 1455 1208 748 710 1455 1290 819 1513 1402 1455 1297 819 796.6 796.7 727.9 846.4 804.2 978.4 933.2 922.8 805.7 729.8 979.4 1006 1017 1076 1015 965.3 732.1 706.3

974 1064 981 1123 1037 1087 1087 1109 1092 953.8 1088 1127 1113 1193 1111 1056 961.4 945.2

874 666 797 788 799 791 791 796 804 789 741 777 831 774 770 721 674 789

Table 3, Comparing scenarios zones 33 28

05. CONCLUSION

5.1 Conclusion and Recommendations

FERAS ESSAM BALKHI - IAQ, Mitigating CO2 concentration in classrooms using adjacent corridors and atriums - 05. CONCLUSION

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05. CONCLUSION

5.1 Conclusion and Recommendations In conclusion, Although the natural ventilation is important to the classroom design should consider the windows able to open. But maintaining thermal comfort in the space in a good condition, aiming to find a quick solution with fewer losses in the meantime can be able by Allowing more fresh air in the classrooms.

Taking advantage of the total fresh air entering the building form the CAV system, using the adjacent spaces can be modified to exchange the unused fresh air with fully occupied classrooms to reduce the total pollution of CO2 concentration.

The results showing the effectiveness of opening a rectangular aperture in each classroom allowing to air infiltration between classrooms and adjacent spaces. This approach is not impacting the energy consumption by using new fresh air. Because it's using the fresh air that is already stored inside the building.

Installing CO2 sensors in the spaces that expected more occupancies to control each space needed more fresh air such as the fully occupied classrooms comparing it to the rest of the adjacent spaces in the building. The openings can be manually controlled by the teacher classroom monitoring the CO2 sensors informing of the IAQ condition.

In the current condition is an accumulation of CO2 concentrations in classrooms with the CAV system in closed spaces.

As a quick solution, scenario 02 can be a proper proposal for this case. because it's keeping the same condition without much changing at the building. Although, it's reducing the general average of CO2 levels in classrooms by 200 ppm as average. in corridors, it's going above 1000 ppm at a slight level which is fine for the common spaces.

Applying the VAV-DCV system is the optimum approach in case of a long term solution. The simulation shows a generally decreased CO2 levels by 49% comparing scenario 03 with the current condition.

CO2-sensors monitor CO2 level in the air in the indoor spaces.

An air-handling system that employs data from the sensors to regulate the amount of supply air. The VAV dampers or extract fans respond well to predefined set points of CO2 concentration.

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06. REFERENCES

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[Accessed: 26-Feb-2020].

[3] Sick Classrooms Caused by Rising CO2 Levels. 2014.

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[8] A. S. Hassan Abdallah, “Thermal Monitoring and Evaluation of Indoor CO2 Concentration in Classrooms of Two Primary Governmental Schools in New Assiut City, Egypt,” Procedia Eng., vol. 205, pp. 1093–1099, 2017.

[9] M. Mysen , S. Berntsen , P Nafstad , P.G Shild , Occupancy density and benefits of demand-controlled ventilation in Norwegian primary schools , Energy Build. 37 (2005) 1234–1240 .

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