1. Air Pollutants and Health Risks:
A Case Study of Sick Building Syndrome
(SBS) in an Underground Metro Station
Platform Area in Tropical Region
Lee Voth-Gaeddert
Yiseul Kim
David Melton
Stephanie Stumpos
Mentors: Dr. Mukesh Khare & Dr. Hernando Perez

2. Indo or Air Pollution and
Sick Building Syndrome
— The Chandi Chowk “Moonlit Market” Metro, built in
2005, is one of 35 underground stations that serve the
National Capital Region of India
— Due to building characteristics and a large number of
daily commuters, there is concern for workers who spend
their entire shifts working in the underground station and
their health
— This case study will focus on the quantification of
exposures to a unique set of stressors and the mitigation
of these events which are associated with SBS and
microbial infection

5. Hazard Identification
Pollutant
Suspended
Particulate Matter
PM10
PM2.5
Source
•
•
•
•
Volatile Organic
Compounds
•
•
shedding
mechanical
abrasion
natural
anthropogenic
automobile
emissions
cleaning materials
Effect
•
•
•
•
•
•
•
Bio-aerosols
•
organic dust
•
microbes
Carbon dioxide
•
living organisms
•
•
•
occupants
•
Aggravated
asthma
Decreased lung
functioning
Respiratory
irritation
Sensory irritation
headaches
nausea
allergic skin
reactions
allergies
respiratory
irritation
Indicator of poor
ventilation

6. Exposure Assessment: Pollutants
Sick Building Syndrome is a discomfort caused by
poor air quality, and only exists while the sufferer
inhabits the building or container in question.

7. Exposure Assessment: Pollutants
In contrast to microbial infection, sick
building syndrome exists only while the
sufferer inhabits the container of interest.
This suggests that the substance of
interest is not a microbial but rather a
chemical hazard.

8. Exposure Assessment Tasks
Pathway
Amount
Duration

9. Pathway: Source Receptor Model

10. Pathway
•
•
•
•
A source of carbon dioxide is biological
activities of humans
Airspeed is unknown but average is 0.3 m/s.
Contact with human is through inhalation
Particulate matter generated by processes
within the station or flowing in from external
source
Bio-aerosol emissions are not well documented
and further testing is necessary to identify
precisely the source

11. Amount
•
•
•
Concentrations of each pollutant were recorded over eight hour monitoring cycles.
Disturbances that may decrease/elevate the volumes of suspended particulate matter
were not provided in the data
Activity changes throughout the course of the day that may affect the concentration
levels should be taken into consideration
Acceptable levels

12. Duration
•
•
If concentration is assumed to be uniform, the
duration of exposure is the length of time the
person inhabits the building.
If concentrations of the pollutants fluctuate
throughout the day due to external
disturbances, the duration of exposure
becomes difficult to quantify, as the contact
with the substance could be sporadic.

13. Dose-Response: Pollutants and SBS
— Unfortunately, a dose-response relationship could not be established
due to data gaps
— SBS scoring is a valuable epidemiologic too that can provide
prevalence data and elucidate associations between pollutant levels
and symptoms
Needs
— We need to establish a temporal relationship between pollutant
concentrations and symptoms (SBS scores)
— A complete data set is needed
— Larger number of observations are needed across all demographic
categories
— Gather post-shift questionnaires to assess any reduction in symptoms
— record time of interview

14. SBS Questionnaire Data
Sometimes
0.5
Always
1
Age under 20
Age between 20- 39
Age between 40-59
Male (12) Female (10) Male (23) Female (15)
Male (9)
Age above 59
Female (3)
Female
(0)
Male (1)
19%
31%
16%
43%
23%
37%
24%
23%
18%
29%
14%
25%
14%
21%
41%
49%
63%
49%
25%
43%
53%
58%
37%
65%
52%
27%
61%
72%
27%
56%
55%
52%
75%
81%
42%
78%
100%
100%
100%
-
12
10
23
15
9
3
1
0.10
0.16
0.16
0.22
0.23
0.19
0.24
0.23
0.18
0.29
0.14
0.13
0.07
0.11
0.21
0.49
0.32
0.49
0.13
0.22
0.27
0.58
0.37
0.65
0.52
0.14
0.31
0.72
0.14
0.28
0.55
0.26
0.38
0.81
0.21
0.39
Total
1.04
1.21
1.68
2.21
2.10
2.60
2.50
Rank
6
5
4
2
3
1
-
Irritation in the eyes (%)
Irritation in the nose (%)
Dryness in mucous (%)
Lethargy/drowsiness/tiredness (%)
Dryness on the face/hands (%)
Headache (%)
0.50
1.00
1.00

15. SBS Questionnaire Data continued

16. Hazard Identification (Microbial)
Data given
Days
Concentration (cfu/m3)
Average
01
02
03
04
05
06
1.
2.
3.
1586
962
1103
990
810
1025
S.D.
93.599
75.139
84.602
88.682
55.643
141.860
E. coli
Bacterial types
Bacillus
Staphylococcus
32%
28%
19%
20%
30%
13%
40%
36%
35%
26%
38%
50%
15%
10%
29%
20%
15%
18%
Data gaps
Concentration of microorganisms of each monitoring cycle
Ambiguity of identification of bacterial type (species and
strains)
Exposure parameters for lung infection
- Exposure rate
- Exposure frequency
- Exposure duration

17. Escherichia coli (E. coli)
— A large and diverse group of bacteria
— Gram-negative, facultative anaerobic, and rod-shaped
— Commonly found in the lower intestine of warm-blooded
organisms
— Used as markers for water contamination
— Most strains of E. coli are harmless
Centers for Disease Control and Prevention

18. Escherichia coli (E. coli)
— At present, 190 serogroups are known.
— Six pathotypes are associated with diarrhea.
- Shiga toxin-producing E. coli (STEC)
- Enterotoxigenic E. coli (ETEC)
- Enteropathogenic E. coli (EPEC)
- Enteroaggregative E. coli (EAEC)
- Enteroinvasive E. coli (EIEC)
- Diffusely adherent E. coli (DAEC)
Centers for Disease Control and Prevention

19. Exposure Assessment
• Concentrations of E.coli (cfu/m3):
• 50% of microbes inhaled will be ingested
• 1 in 100,000 of E. coli inhaled are pathogenic
• Inhalation rates (u=5.0E m3/min) *multiplied by
-03
480min/shift

20. Dose-Response
—Exposure parameters: Apply available dose response
model from QMRA wiki.
- Best fit model: beta-Poisson
- Optimized parameters:
α = 1.55E
-01,
N50 = 2.11E+06
- LD50/ID50: 2.11E+06
- Host type: Human

21. Pearson-Tukey Method
— Decision Tree model based
— Allows analysis of three different scenarios;
— Best
— Worst
— Average
μ+
1
.6
4Ϭ
Best
μ-1
. 64
μ
Ϭ
Average
Worst

22. Tukey Test
Day 1
Day 2
Day 3
Day 4
Day 5
Day 6
High
594.8751008 334.1625188 270.540551 263.0420656 292.9821591 216.8045679
Medium
508
269
210
198
243
133
Low
421.1248992 182.1248992 123.1248992 111.1248992 156.1248992 46.1248992
1/100,000 chance of pathogic e coli
cfu/m3
Day 1
Day 2
Day 3
Day 4
Day 5
Day 6
High
0.005948751 0.003341625 0.002705406 0.002630421 0.002929822 0.002168046
Medium
0.00508
0.00269
0.0021
0.00198
0.00243
0.00133
Low
0.004211249 0.001821249 0.001231249 0.001111249 0.001561249 0.000461249
50% of microbes inhaled will be ingested
cfu/m3
Day 1
Day 2
Day 3
Day 4
Day 5
Day 6
High
0.002974376 0.001670813 0.001352703 0.00131521 0.001464911 0.001084023
Medium
0.00254 0.001345
0.00105
0.00099
0.001215
0.000665
Low
0.002105624 0.000910624 0.000615624 0.000555624 0.000780624 0.000230624
Taking into account breathing rate of 2.4 m3/8hrs
shift = 8 hours
Day 1
Day 2
Day 3
Day 4
Day 5
Day 6
High
0.007138501 0.00400995 0.003246487 0.003156505 0.003515786 0.002601655
Medium
0.006096 0.003228
0.00252
0.002376
0.002916
0.001596
Low
0.005053499 0.002185499 0.001477499 0.001333499 0.001873499 0.000553499

23. Systematic Sampling Method
— Pearson-Tukey Method was used
— The beta-Poisson model was used
— Each of the six days of data given was assessed for risk
— Data in table is probability of one person getting ill out of
the number given
1 out of how many will get sick
Day 1
Day 2
Day 3
Day 4
Day 5
Day 6
High
22039682.64 39234973.26 48461708.4 49843196.09 44749677.99 60473158.43 44133732.8
Medium 25808775.77 48739246.11 62432652.65 66216449.28 53954144.54 98577869.81 59288189.69
Low
31132943.74 71988272.21 106484201.2 117983069 83976719.55 284246827.4 115968672.2

24. Risk Management
— ASHRAE Ventilation standards
— Between 15 and 60 cubic ft./m of outdoor air per person
— Filtration devices; increased air exchange
— Installation of monitoring systems
— Conducting emission inventory
— Cost benefit analysis: compare productivity lost to sick days and the
cost of improvements to station

25. Risk Communication
Employer
Regulatory agencies
Employer
Employee

26. References
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27. Chart Reference