METHODS TO IMPROVE INDOOR ENVIRONMENTAL QUALITY (IEQ) IN CLASSROOMS IN HOT CLIMATES. 03

Page 1

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

Supervisor: Dr-Ing. Mohannad Bayoumi Master of Architecture (Design + Research) Department of Architecture (KAUARCH) Faculty of Architecture and planning King Abdulaziz University


CONTENT 01. BACKGROUND 1.1 Introduction 1.2 Research problem 1.3 Research objective

05. DESIGN ALTERNATIVES 5.1 Investigation variables 5.2 Scenarios 5.3 Compare and analyze

02. LITERATURE REVIEW 2.1 Indoor air quality 2.2 CO2 2.3 Standards 2.4 Sick building syndrome 2.5 Conclusion and Notes

06. RESULTS 6.1 Table of design proposals 6.2 Recommendations

03. RESEARCH METHODS 3.1 Research factors 3.2 Methodology 04. CASE ANALYSIS 4.1 Study framework 4.2 Research sample 4.3 Measurement and Simulation tools 4.4 Measurement analysis 4.5 Observations 4.6 Research question

07. REFERENCES


01. BACKGROUND

1.1 Introduction 1.2 Research problem 1.3 Research objective

13.OCT.2019 WORKDAY TIME 7:00 7:10 7:20 7:30 7:40

TEMP. 22.011 21.819 21.772 21.676 21.628

RH. 62.17 62.769 63.239 63.684 64.008

CO2 475 464 445 456 434


01. BACKGROUND 1.1 Introduction

This paper focuses on studying the classrooms indoor air quality of the preparatory year at King Abdulaziz University in Saudi Arabia. One of them is a classroom in an existing building in Jeddah that was taken as a research sample. the variables affecting the indoor air quality were measured and analyzed it by installing sensors to measure and record these variables in this classroom. After that research was done to determine the optimal range of these variables and compare them to check whether these results were within the optimal range of each variable or not. The results show that it is important to propose improvement measures to reduce CO2 concentrations and ensure thermal comfort. Users need to realize that the quality of the internal environment is important for their health, comfort and performance and efficiency.

FERAS ESSAM BALKHI - INDOOR ENVIRONMENTAL QUALITY - 01. BACKGROUND

1.2 Problem statement

While spaces have a great impact on the lives of the people that occupied them, the climate of those spaces is an undeniable essential factor that decides their level of satisfaction and thus performance. - While the targeted teacher-student ratio is 1:17, some schools in high-density areas will have to occupy up to 45 students per classroom. - People spend up to 90-95% of their time indoors, and most people realize that outdoor air pollution can affect their health, but indoor air pollution can have significant and harmful health effects that may be two to five times higher of outdoor pollution levels.


01. BACKGROUND 1.3 Objective

Improve the indoor air quality of classrooms, by Mitigating CO2 concentration. Achieving guidelines to upgrade the quality of educational classrooms indoor spaces.

Keywords

-Air quality -CO2 influences -Space efficiency -Function of indoor spaces -Students performance FERAS ESSAM BALKHI - INDOOR ENVIRONMENTAL QUALITY - 01. BACKGROUND


02. LITERATURE REVIEW

2.1 Peer reviewed research articles 2.2 Research question 2.3 Standards


02. LITERATURE REVIEW

2.1 Indoor Air Quality (IAQ)

- Indoor Air Quality (IAQ) refers to the air quality within and around buildings and structures, especially as it relates to the health and comfort of building occupants (1). - The most important factor that affects the indoor air quality is the ventilation, as the air conďŹ ned to a closed space without renewal, it can be contaminated by several pollutants, including: Radon, carbon monoxide, carbon dioxide, bacteria and other volatile chemical particles (2).


02. LITERATURE REVIEW 2.2 (CO2)

- humans by there nature are the main indoor source of carbon dioxide in most buildings. Carbon dioxide (CO2) is easy to measure as a surrogate for indoor pollutants. Indoor CO2 levels are a good indicator of ventilation efďŹ ciency wetch directly indicate to the quality of the indoor air (3).


02. LITERATURE REVIEW 2.3 Standards

Carbon dioxide levels and potential health problems are indicated below: (4)

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


02. LITERATURE REVIEW 2.5 Conclusion and Notes

- The poor indoor air quality has large effect on the space occupants health and comfort. - The indoor air quality can be indicated by measuring the CO2 concentration levels - The larger is the space, the greater is the dilution of carbon dioxide concentration levels and pollutants and the longer good air quality can be maintained. - In anaverage size classroom with a volume of 181 cubic metres, 30 students and no natural ventilation, the air quality becomes poor in just 30 minutes (7).


03. RESEARCH METHODS 3.1 Research factors 3.2 Methodology


03. RESEARCH METHODS 3.1 Research factors

3.1.1 Management related 3.1.1 A

Schedule timeline The current CO2 ratios, classroom occupancy times should be reconsidered by adjusting the sessions schedule of break timeline between classes, as break times reduce the CO2 concentration.

3.1.1 B

Occupants number CO2 concentration can be reduced by reducing the number of students in the classroom, the large number of occupants in the indoor spaces increases the rates of CO2 concentration.

3.1.2 Design related 3.1.2 C

Space volume The size of the existing study spaces can be reviewed to be larger in size so that the space can accommodate higher oxygen ratios and less carbon dioxide.

3.1.2 D

Mechanical systems Redistribute the air inside the building during the working hours, by adding extensions linking the indoor public spaces in the building with classrooms to increase the control of the distribution of CO2 ratios.


03. RESEARCH METHODS 3.2 Methodology

Evaluate

Students performance

Management variables Occupants

Discussion

Schedule Scenarios

Current condition

Aimed condition

Suggested alternatives

Results Scenarios

Measurement

Space efficiency

Research sample

Space volume

Conclusion and Recommendations

Mechanical

Design variables

Analyze

Observations

Findings


04. CASE ANALYSIS 4.1 4.2 4.3 4.4 4.5 4.6

Study framework Research sample Measurement and Simulation tools Measurement analysis Observations Research question


03. RESEARCH METHODS 3.1 Study framework

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. Install accurate measuring devices that detect and record environmental quality variables at indoor spaces where they measure temperature and relative humidity within the case zone.


03. RESEARCH METHODS 3.1 Research sample

1.06 m

7.50 m

1.06 m

1.06 m

Classroom building 535 King Abdulaziz university Space volume: 205.5 m 3

9.14 m

PLAN MEASUREMENT TOOL SPOT HEIGHT 1.10 m

3.00 m

SECTION FERAS ESSAM BALKHI - INDOOR ENVIRONMENTAL QUALITY - 02. LITERATURE REVIEW


03. RESEARCH METHODS

3.2 Measurement and Simulation 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.


04. CASE ANALYSIS

4.1 Measurement (thermal analysis)

RELATIVE HUMIDITY CLASSROM ANALYSIS

TEMPERATURE CLASSROM ANALYSIS TEMPERATURE(C)

RELATIVE HUMIDITY (%)

O

70%

26C

O

68%

25 C

66%

24 C

64%

23 C

62%

22 C

60%

21 C

58%

20 C

O

O

O

O

O

:0 0 17

17

:0 0

O

DAY TIME

DAY TIME

COMFORT TEMPERATURE

RELATIVE HUMIDITY HIGHEST LEVEL STANDARD

RELATIVE HUMIDITY (%)

TEMPERATURE(C)

CLASS OFF


04. CASE ANALYSIS

4.1 Measurement (thermal analysis) Psychrometric chart

The two most important variables affecting the thermal comfort in the classroom 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.

Relativ e humidity (%)100

90

80

70

60

Absolute humidity (kg/kg) 50 40

30

0.0550

0.0500

40 0.0450

Observations

As shown the in the diagram, data avearge is placed in the comfort zone.

0.0400

35

0.0350 20

Data average

0.0300

Temperature: 22.25 C Relative humidity: 66.5% o

30 0.0250

COMFORT ZONE

Data taken 13.OCT.2019

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) Dry bulb temperature

-25

-20

Absolute humidity

-15

-10

Relative humidity

-5 -5

0

5

Wet bulb temperature Comfort zone

10

15

20

25

30

35

40

45

50

55

60

65

0.0000


04. CASE ANALYSIS

4.1 Measurement analysis CO2 Concentration

Observations

The charts show a high increase in CO2 concentrations in the working day due to the classroom is full by students. Consequently, the carbon dioxide emissions due to students congestion increase to a concentration level of 1270 ppm, which causes complaints of drowsiness and poor air. 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

TIME 7:00 7:10 7:20 7:30 7:40 7:50 8:00 8:10 8:20 8:30 8:40 8:50 9:00 9:10 9:20 9:30 9:40 9:50 10:00 10:10 10:20 10:30 10:40 10:50 11:00 11:10 11:20 11:30 11:40 11:50

TEMP. 22.011 21.819 21.772 21.676 21.628 21.557 21.533 21.461 21.461 21.437 21.413 21.461 21.533 21.652 21.843 22.082 22.178 22.345 22.369 22.441 22.753 22.753 22.872 22.848 22.729 22.8 22.824 22.824 22.92 22.872

RH. 62.17 62.769 63.239 63.684 64.008 64.307 64.563 64.844 65.131 65.442 65.759 66.101 66.455 66.76 67.133 67.505 67.743 67.493 67.194 67.035 66.882 66.65 66.302 65.674 65.039 64.832 64.648 64.453 64.764 64.984

8:10 8:20 8:30 8:40 8:50 9:00 9:10 9:20 9:30 9:40 9:50 10:00 10:10 10:20 10:30 10:40 10:50 BUILDING 535 11:00 13.OCT.2019 11:10 11:20 WORKDAY 11:30 11:40 CO2 TIME 11:50 12:00 475 12:10 464 12:20 445 12:30 456 12:40 434 12:50 459 13:00 444 13:10 448 13:20 457 13:30 461 13:40 442 13:50 518 14:00 561 14:10 680 14:20 805 14:30 959 14:40 997 14:50 1004 15:00 1004 15:10 1104 15:20 1191 15:30 1270 15:40 1237 15:50 1230 16:00 1115 16:10 1143 16:20 1183 16:30 1189 16:40 1171 16:50 1040

21.461 21.461 21.437 21.413 21.461 21.533 21.652 21.843 22.082 22.178 22.345 22.369 22.441 22.753 22.753 22.872 22.848 22.729 22.8 22.824 22.824 22.92 TEMP. 22.872 22.705 22.609 22.561 22.489 22.441 22.369 22.321 22.345 22.417 22.489 22.561 22.537 22.513 22.489 22.489 22.465 22.489 22.465 22.489 22.465 22.441 22.417 22.417 22.561 22.465 22.417 22.513 22.489 22.465 22.441

64.844 65.131 65.442 65.759 66.101 66.455 66.76 67.133 67.505 67.743 67.493 67.194 67.035 66.882 66.65 66.302 65.674 65.039 64.832 64.648 64.453 64.764 RH. 64.984 65.167 65.247 65.369 65.387 65.424 65.607 65.906 66.26 66.705 67.133 67.523 67.834 68.03 68.079 68.176 68.317 68.555 68.799 68.848 68.86 68.829 68.738 68.579 68.512 68.524 68.506 68.524 68.457 68.427 68.378

448 457 461 442 518 561 680 805 959 997 1004 1004 1104 1191 1270 1237 1230 1115 1143 1183 1189 1171 CO2 1040 971 938 871 852 834 805 861 891 925 946 975 917 908 929 913 867 910 877 943 883 886 889 889 876 877 904 925 898 883 871


04. CASE ANALYSIS

4.1 Measurement analysis CO2 Concentration VeriďŹ cation

After taking the physical measurements and comparing them with the simulation result measurements from the simulation program - while entering the same values of the variables (the timing and duration of the break times - the number of students) - we notice 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.

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

0

Physical measurment

Simulation


04. CASE ANALYSIS 4.2 Observations

The educational space was studied in two different days, one on a day off and the other due workday where students are in the classroom. According to data analysis, there is an increase in the concentration of CO2 above average at the workday, causing students' complaints of drowsiness and poor air quality. The classroom is in good condition of humidity average 66.75% and temperature below the average by 21.87 ° C in the thermal comfort zone, but the best Thermal comfort is between 23° to 25 ° C. This causes increased cost and waste in building energy consumption.

4.3 Research question

What is the optimum approach for the reduction of CO2 concentration in classrooms, without affecting the thermal comfort?


05. DESIGN ALTERNATIVES 5.1 Investigation variables 5.2 Scenarios 5.3 Compare and analyze


05. DESIGN ALTERNATIVES 5.1 Investigation variables

Management related (Schedule timeline) 3.1.1 A

CURRENT CONDETION

First semester 2020 - Student classes schedule


05. DESIGN ALTERNATIVES 5.2 Scenarios

Current condition 10 min. break

Management related (Schedule timeline) 3.1.1 A

01

CLASSROOM SCHEDULE PHYSICAL MEASUREMENT DURING WORKDAY 60Min.

50Min.

01

02

OFF

7:00

Scanning and analyze When entering the first variable (the students number) equal the maximum capacity of the classroom -40 students- and the second variable (timing and duration of the break time) equal the real situation -10 minutes between every two sessions in the simulation program, the results are shown as following graphs below.

1800 ppm

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.

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

200 ppm 0

Scenario 01

10Min.

08

CLASS

13:00

50Min.

60Min.

09

CLASS

14:00

50Min.

10

CLASS

15:00

OFF

16:00

WORKDAY END

17:00


05. DESIGN ALTERNATIVES 5.2 Scenarios

Scenario 02 15 min. break

Management related (Schedule timeline) 3.1.1 A

02

CLASSROOM SCHEDULE SIMULATION DURING WORKDAY 60Min.

50Min.

01

02

OFF

7:00

extending the break time to 15 minutes When entering the first variable (student number) equal the maximum class capacity 40 students - and the second variable (timing and duration of the break time) equal 15 minutes between evrey two sessions in the simulation program, the results are shown as graphs below. We notice a decrease in the area under the curve by 3%, which means that the levels of carbon dioxide concentration are 3% lower than the current situation.

1800 ppm

15Min.

WORKDAY START

15Min.

50Min.

03

CLASS

8:00

50Min.

50Min.

04

CLASS

9:05

15Min.

50Min.

05

CLASS

10:00

15Min.

50Min.

06

CLASS

11:00

15Min.

13:00

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

Scenario 02

15Min.

50Min.

08

CLASS

1600 ppm

Scenario 01

50Min.

07

BREAK

12:00

15Min.

09

CLASS

14:00

60Min.

10

CLASS

15:00

OFF

16:00

WORKDAY END

17:00


05. DESIGN ALTERNATIVES 5.2 Scenarios

Scenario 03 5 min. break - 30 min. break

Management related (Schedule timeline) 3.1.1 A

03

CLASSROOM SCHEDULE SIMULATION DURING WORKDAY 60Min.

50Min.

01

02

OFF

7:00

customizing the break time to 5 minutes followed by 30 minutes in a row When entering the first variable (student number) the maximum class capacity - 40 students - and the second variable (timing and duration of the break time)50 minutes session time then 5 minutes break time then 50 minutes session time followed by 30 minutes one after one in the simulation program, the results are shown as graphs. We notice an increase in the area under the curve equivalent to 4.5%, which means that the levels of carbon dioxide concentration rise by 4.5% from the current situation.

5Min.

03

CLASS

8:00

WORKDAY START

50Min.

CLASS

8:55

5Min.

5Min.

30Min.

04

BREAK

9:45

10:15

50Min.

5Min.

05

50Min.

06

CLASS

BREAK

11:10

5Min.

5Min.

30Min.

04

BREAK

12:00 12:30

50Min.

5Min.

08

09

CLASS

CLASS

13:25

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

Scenario 01

50Min.

Scenario 03

5Min.

5Min.

30Min.

04

BREAK

14:15 14:45

50Min.

5Min.

08

CLASS

50Min.

60Min.

09

10

CLASS

15:40

OFF

16:30

WORKDAY END

17:30


05. DESIGN ALTERNATIVES 5.2 Comparing scenarios

Management related (Schedule timeline) 3.1.1 A

03

When comparing the alternatives, we find that the second scenario is the best option, as CO2 concentration levels are 3% lower than the current situation.

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

Scenario 01

Scenario 02

Scenario 03


05. DESIGN ALTERNATIVES

9.14 m

5.2 Scenarios

1.06 m

Management related (Occupants number) 3.1.1 B

1.06 m

7.50 m

02

1.06 m

CO2 concentration can be reduced by reducing the number of students in the classroom, the large number of occupants in the indoor spaces increases the rates of CO2 concentration.

Standard.(5)

Students: 30 - Area: 68.5

Classroom square or rectangular 65m2 with furniture in rows and freely arranged fits for 30 - 36 students (which means 1.8 - 2.0 m2 for each student). 1600 ppm

According to the standard, the student number was reduced to 30 students in the classroom, we can notice a slight decrease in the CO2concentration level by 12.5%.

1400 ppm

1200 ppm

1000 ppm

800 ppm

600 ppm

400 ppm

200 ppm

0

Current condition 01

Scenario 02


05. DESIGN ALTERNATIVES 5.2 Scenarios

Design related (Space volume) 3.1.2 C

01

Floor area 4420m2 Solid and unventilated area 1346m2 Free ventileted area 3047m2 Classrooms area 1700m2 30

31

56

zone 06

50

53

Atr. 36

32

52

zone 02

42

41

40

39

zone 17

Atr. 24

51

zone 09

38

33

34

zone 16 zone 19

zone 07

zone 04

54 zone 15

All free spaces 3047m2 100% Classrooms area 1820m2 55.80% Corridors area 1346m2 44.20%

45 44

46

zone 11

zone 01

47

zone 05

57.5%

49

48

zone 14

42.5%

55

zone 08

zone 18

43 35

37


05. DESIGN ALTERNATIVES 5.2 Scenarios

Design related (Space volume) 3.1.2 C Atrium 01

Space volume: 2742.4m3 All vertical space: 5,484.8m3

Current situation Corridors and atriums CORRIDORS SCHEDULE

HOURS DURING WORKDAY 60Min.

50Min.

01

02

OFF

7:00

10Min.

03

CLASS

8:00

WORKDAY START

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.

10Min.

60Min.

09

CLASS

14:00

50Min.

10

CLASS

15:00

OFF

16:00

WORKDAY END

17:00


05. DESIGN ALTERNATIVES 5.2 Scenarios

Design related (Space volume)

Atrium zone Space volume: 5,484.8 m3

Corridors zone Space volume: 1346 m3

3.1.2 C Atrium 01

Scanning and analyze

The total atriums volume in the building = 5484.8 m3. The floors number in the building = 4 floors. The allocated volume of the atriums for each floor = 5484.8 / 4 = 1371.2 m3.

Classroom zone Space volume: 205.5 m3

The corridors volume in each floor = 1346 m3. The total volume of the atriums per floor + the volume of corridors = 1371.2 + 1346 = 2717.2 m3. Number of classes per floor = 26 classrooms. Average class volume = 210 m3. The allocated volume from the corridors and the atriums for each classroom = 2717.2 / 26 = 104.5 m3.

33%

67%

Total Mixed Volume Classroom Volume Allocated volume from corridors and atrium for each classroom

FERAS ESSAM BALKHI - INDOOR ENVIRONMENTAL QUALITY - 01. BACKGROUND

Atrium zone

Corridor zone

Classroom zone

Section diagram


05. DESIGN ALTERNATIVES

Classroom zone Space volume: 210 m3

5.2 Scenarios

Design related (Space volume) 3.1.2 C Atrium 02

Scenario 02 Using the Ida-Ace program, three spaces are allocated (classroom space,allocated space from the corridors for each classroom and allocated space from the atrium for each classroom). The classroom space was filled with the same number of users of this space under the real circumstances then I opened all of the three spaces to each other. The results are shown as shown in the diagram below. We observe a decrease in the concentration CO2 it reach 946.23 ppm at its highest concentration point.

Atrium zone Space volume: 52.67 m3 Corridors zone Space volume: 51.77 m3

PEAK 946.23 ppm 10:20 am.

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

CALIBRATION

FERAS ESSAM BALKHI - INDOOR ENVIRONMENTAL QUALITY - 01. BACKGROUND

SCENARIO 01


05. DESIGN ALTERNATIVES 5.2 Scenarios

New classroom zone Space volume: 313.65 m3

Design related (Space volume) 3.1.2 C Atrium 03

Scenario 03 If the classroom space is fully integrated with the allocated space from the corridors and the atrium,and considered it as one whole space then occupied it by the same number of users under real circumstances. The results of the CO2 concentration in this case are shown in the graph below. PEAK 882.48 ppm 10:20 am.

We observe a decrease in the concentration of CO2 it reach 882.48 ppm at its highest concentration point.

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

CALIBRATION

FERAS ESSAM BALKHI - INDOOR ENVIRONMENTAL QUALITY - 01. BACKGROUND

SCENARIO 01

SCENARIO 02


05. DESIGN ALTERNATIVES Comparing and analyze

Design related (Space volume) 3.1.2 C

03

Atrium

Classroom 53

Scenario 02

1400

1200

1000

800

600

400

Corridor 200

0

7:00 7:20 7:40 8:00 8:20 8:40 9:00 9:20 9:40 10:00 10:20 10:40 11:00 11:20 11:40 12:00 12:20 12:40 13:00 13:20 13:40 14:00 14:20 14:40 15:00 15:20 15:40 16:00 16:20 16:40 �ΔϠγϠγ

CALIBRATION

FERAS ESSAM BALKHI - INDOOR ENVIRONMENTAL QUALITY - 07.RESULTS

�ΔϠγϠγ

SCENARIO 01

�ΔϠγϠγ

�ΔϠγϠγ

CLASSROOM 53


05. DESIGN ALTERNATIVES 5.2 Scenarios

9.14 m

7.50 m

1.06 m

01

1.06 m

3.1.2 D

1.06 m

Design related (Mechanical system)

PLAN

Scenario 01

The basic concept of reducing the CO2 concentration in the interior spaces is to replace the air in the contaminated space with unpolluted air, but the problem is that if the indoor air is replaced by the air from outdoor the internal temperature will increase which affects the thermal comfort of the occupants.


05. DESIGN ALTERNATIVES 5.2 Scenarios

Design related (Mechanical system) 3.1.2 D

02

Taking advantage of the cold air in low-density of interior spaces

Since there are low users densities in some of the internal spaces such as the corridors and atriums, the problem can be avoided by using the air switch between the spaces are usually occupied only for short times (breaktimes period) and spaces with high intensity of use (as the classrooms). This will achieve the goal of reducing CO2 pollution without increasing electrical energy consumption by conditioning outdoor air.

Scenario 02 (Corridors and atriums) 15 min. break CLASSROOM SCHEDULE

HOURS DURING WORKDAY 60Min.

50Min.

01

02

OFF

7:00

10Min.

03

OFF

8:00

WORKDAY START

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.

10Min.

09

OFF

14:00

60Min.

50Min.

10

OFF

15:00

OFF

16:00

WORKDAY END

17:00


05. DESIGN ALTERNATIVES 5.2 Scenarios

9.14 m

1.06 m

02

1.06 m

3.1.2 D

1.06 m

Design related (Mechanical system)

CORRIDOR

PLAN

Since there are low users densities in some of the internal spaces such as the corridors and atriums, the problem can be avoided by using the air switch between the spaces are usually occupied only for short times (breaktimes period) and spaces with high intensity of use (as the classrooms). This will achieve the goal of reducing CO2 pollution without increasing electrical energy consumption by conditioning outdoor air.


05. DESIGN ALTERNATIVES 5.2 Scenarios

Design related (Mechanical system) 3.1.2 D

02

Applying the proposed solution idea by using the simulation program 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

Using the simulation software, all the spaces on one of the building oors will be opened to each other to verify the effectiveness of the proposed solution.

zone 18

43 35

37


CO2 concentration

05. DESIGN ALTERNATIVES 5.2 Scenarios

Min. 400 ppm

Max. 2000 ppm

Design related (Mechanical system) 3.1.2 D

01

Current condition

56

49

48

45

53

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

50

zone 15

47

zone 11

55

zone 08

zone 01

We notice the highest value of CO2 concentration levels in educational spaces reach 2008 ppm.

31 zone 06

zone 05

Observation

30

zone 14

When entering the variables into the simulation program for an entire oor of the building based on the following data (the maximum capacity of the educational spaces - the timing and duration of the break times is equal to 15 minutes between every two sessions) the results appear as follows.

Scenario 01 Space CO2 30 1455 31 1455 32 1446 33 1455 34 1455 35 1455 37 1455 38 1455 39 1455 40 1455 41 1455 42 1513 43 1513 44 1455 45 1840 46 1653 47 1653 48 2008 49 1455 50 1455 51 1455 52 1455 53 1455 54 1455 55 1513 56 1455 Zone 01 796.6 Zone 02 796.7 Zone 04 727.9 Zone 05 846.4 Zone 06 804.2 Zone 07 978.4 Zone 08 933.2 Zone 09 922.8 Zone 10 805.7 Zone 11 729.8 Zone 14 979.4 Zone 15 1006 Zone 17 1076 Zone 16 1017 Zone 18 1015 Zone 19 965.3 Atr. 24 732.1 Atr. 36 706.3

zone 18

43 35

37


CO2 concentration

05. DESIGN ALTERNATIVES 5.2 Scenarios

Min. 400 ppm

Max. 2000 ppm

Design related (Mechanical system) 3.1.2 D

02

56

49

48

45

53

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

50

zone 15

47

zone 11

55

zone 08

zone 01

We notice a decrease in the highest value of the CO2 concentration in educational spaces from 2008 ppm to 1509 ppm, and this is a good improvement. Looking at the average values of CO2 concentration levels in educational spaces, we ďŹ nd that it's generally decreased by 13.2%.

31 zone 06

zone 05

Observation

30

zone 14

When applying the idea in the simulation program to an entire oor of the building and opening the spaces to each other according to the following variables data (the maximum capacity of the educational spaces - the timing and duration of break times equal 15 minutes between each two sessions) the results are shown to us as follows

Scenario 02 Space CO2 30 1150 31 1277 32 1182 33 1317 34 1318 35 1318 37 1318 38 1300 39 1299 40 1299 41 1299 42 1418 43 1419 44 1287 45 1509 46 1459 47 1459 48 1414 49 1274 50 1147 51 1303 52 1200 53 1208 54 1290 55 1402 56 1297 Zone 01 974 Zone 02 1064 Zone 04 981 Zone 05 1123 Zone 06 1037 Zone 07 1087 Zone 08 1087 Zone 09 1109 Zone 10 1092 Zone 11 953.8 Zone 14 1088 Zone 15 1127 Zone 17 1193 Zone 16 1113 Zone 18 1111 Zone 19 1056 Atr. 24 961.4 Atr. 36 945.2

zone 18

43 35

37


CO2 concentration

05. DESIGN ALTERNATIVES 5.2 Scenarios

Min. 400 ppm

Max. 2000 ppm

Design related (Mechanical system) 3.1.2 D

03

31

56

zone 06

49

48

50

53

Atr. 36

32

52

zone 02

42

41

40

39

zone 17

Atr. 24

51

zone 09

38

33

34

zone 16 zone 19

zone 07

zone 04

54 zone 15

45 44

46

zone 11

55

zone 08

zone 01

47

zone 05

We notice a decrease in the highest value of the CO2 concentration in educational spaces from 2008 PPM to 880.8 ppm, and this is a very good improvement. Looking at the average values of CO2 concentration levels in educational spaces, we ďŹ nd that it's generally decreased by 49.3%, as we can notice a slight increase in CO2 concentration levels at the corridors spaces (the highest reach 1088 ppm) which is acceptable.

30

zone 14

When applying the idea in the simulation program to an entire oor of the building and opening the spaces to each other according to the following variables data (the maximum capacity of the educational spaces - the timing and duration of break times equal 15 minutes between each two sessions) after that if we add some mechanical solutions (As an example CO2 sensors & VAV HVAC systems) the results are shown as follows

Scenario 04 Space CO2 30 799.3 31 794.1 32 788.6 33 798 34 798.3 35 798.3 37 798.3 38 793.7 39 793.7 40 793.7 41 793.7 42 804.2 43 805 44 797.3 45 854.2 46 826.7 47 826.7 48 880.8 49 795 50 787.2 51 798.1 52 791.1 53 797.2 54 795.1 55 806.2 56 800.8 Zone 01 795.4 Zone 02 802.2 Zone 04 751.6 Zone 05 829.1 Zone 06 807.7 Zone 07 964.5 Zone 08 908.5 Zone 09 869.6 Zone 10 793 Zone 11 747.2 Zone 14 988.4 Zone 15 1015 Zone 17 1024 Zone 16 1088 Zone 18 1009 Zone 19 965.1 Atr. 24 750 Atr. 36 735.6

zone 18

43 35

37


06. RESULTS

6.1 Table of design proposals 6.2 Recommendations


06. RESULTS

6.2 Recommendations In conclusion, the following recommendations are presented based on the above research, study and analysis: 1- Taking into account during the design that the Spaces should be designed with dimensions and sizes commensurate with their uses. 2- Changing the scheduling of students ’sessions times and break times. 3- Reducing the number of students in the single educational space, in proportion to its size. 4- Improving the mechanical systems of building conditioning and ventilation to allow more fresh air to enter the air conditioning cycle. 5- Adding windows between the interior spaces of the building that allows air exchange between educational spaces and general corridor spaces when the indoor air quality decreases to reduce energy waste when opening the external windows.


05. REFRENCES (1). U.S. Environmental Protection Agency (2). Sick Classrooms Caused by Rising CO2 Levels - the energy alliance group of north america - Kerry Kilpatrick - publication date 13/01/2014 - Acces Date 09/11/2019. (4). Occupational Health And Safety, Steve Bonino -2016 (5) Neufert architects data 3rd edition - Ernst Neufert. (6). Clements-Croome, 2004 (7) BUILDING BETTER SCHOOLS - VELUX Modular Skylight - Unknown Author - Unknown publication date - Acces Date 09/11/2019. (8) Indoor Air Quality (IAQ) - U.S. Environmental Protection Agency - Unknown Author - Unknown publication date - Acces Date 09/11/2019.


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