Full text of DOI:10.1080/10473289.2000.10464212

This article was downloaded by: [University Of Maryland]
On: 17 October 2014, At: 03:22
Publisher: Taylor & Francis
Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer
House, 37-41 Mortimer Street, London W1T 3JH, UK
Journal of the Air & Waste Management Association
Publication details, including instructions for authors and subscription information:
http://www.tandfonline.com/loi/uawm20
Impact of Microenvironmental Nitrogen Dioxide
Concentrations on Personal Exposures in Australia
Kiyoung Lee a b , Wonho Yang b & Neville D. Bofinger c
a Department of Epidemiology and Preventive Medicine , University of California at
Davis
b Center for Public Health Research, School of Public Health , Queensland University
of Technology , Brisbane , Queensland , Australia
c School of Natural Resource Sciences , Queensland University of Technology ,
Brisbane , Queensland , Australia
Published online: 27 Dec 2011.
To cite this article: Kiyoung Lee , Wonho Yang & Neville D. Bofinger (2000) Impact of Microenvironmental Nitrogen
Dioxide Concentrations on Personal Exposures in Australia, Journal of the Air & Waste Management Association, 50:10,
1739-1744, DOI: 10.1080/10473289.2000.10464212
To link to this article: http://dx.doi.org/10.1080/10473289.2000.10464212
PLEASE SCROLL DOWN FOR ARTICLE
Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained
in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no
representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose
of the Content. Any opinions and views expressed in this publication are the opinions and views of the
authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should
not be relied upon and should be independently verified with primary sources of information. Taylor
and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses,
damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection
with, in relation to or arising out of the use of the Content.
This article may be used for research, teaching, and private study purposes. Any substantial or systematic
reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any
form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http://
www.tandfonline.com/page/terms-and-conditions

TECHNICAL PAPER
ISSN 1047-3289 J. ALire&eW,aYstae nMgan,aagen. AdssoBc.o5f0in:1g73e9r-1744
Copyright 2000 Air & Waste Management Association
Impact of Microenvironmental Nitrogen Dioxide Concentrations
on Personal Exposures in Australia
Kiyoung Lee
Department of Epidemiology and Preventive Medicine, University of California at Davis, and Center for
Public Health Research, School of Public Health, Queensland University of Technology, Brisbane,
Queensland, Australia
Wonho Yang
Center for Public Health Research, School of Public Health, Queensland University of Technology, Brisbane,
Queensland, Australia
Neville D. Bofinger
School of Natural Resource Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
ABSTRACT
to the error of prediction of personal exposure was con-
firmed in the regression analysis using the multinational
study database.
Indoor and outdoor NO2 concentrations were measured
and compared with simultaneously measured personal
exposures of 57 office workers in Brisbane, Australia.
House characteristics and activity patterns were used
to determine the impacts of these factors on personal
exposure. Indoor NO2 levels and the presence of a gas
range in the home were significantly associated with
personal exposure. The time-weighted average of per-
sonal exposure was estimated using NO2 measurements
in indoor home, indoor workplace, and outdoor home
levels. The estimated personal exposures were closely
correlated, but they significantly underestimated the
measured personal exposures. Multiple regression analy-
sis using other nonmeasured microenvironments indi-
cated the importance of transportation in personal
exposure models. The contribution of transportation
INTRODUCTION
NO2 is a byproduct of high-temperature fossil fuel com-
bustion. Abundant indoor and outdoor combustion
sources make NO2 one of the most ubiquitous pollut-
ants in the urban environment. Despite wide distribu-
tion of sources, indoor NO2 concentration is the
dominant risk factor of personal exposure. Individuals
were found to spend ~90% of their days indoors and
about two-thirds of the day inside their homes.1,2 When
personal NO2 exposures were measured for 568 subjects
from 18 cities in 15 countries, indoor concentration was
responsible for 75% of the variation in the total personal
exposure of office workers.3 The relation between indoor
levels and personal exposures was associated with geo-
graphical conditions, indoor sources, and other demo-
graphic characteristics.
IMPLICATIONS
The significance of indoor sources on personal exposure
to NO2 has been determined in many previous studies.
This study demonstrates the relative importance of in-
door sources in Australia. A microenvironmental model
with three dominant environments (i.e., residential indoor,
residential outdoor, and workplace indoor) significantly
underestimated personal exposure. Regression analysis
showed that transportation was a major contributor of
the error in prediction of personal exposure. This was also
confirmed in the multinational study database. The find-
ing suggests a need for exposure assessment during
transportation to construct accurate personal exposure
models.
The presence of a gas range has been identified as
one of the major factors contributing to indoor and per-
sonal NO2 exposures. Significantly higher NO2 concen-
trations were measured in homes with gas ranges; mean
two-day personal NO2 exposures were 34.8 ppb and 20.5
ppb in homes with and without gas ranges, respectively.3
The use of a gas range provided a mean indoor/outdoor
(I/O) NO2 ratio of 1.19, compared with 0.69 for those
homes without gas ranges. In the multinational study,
the association between gas ranges and indoor NO2 expo-
sure was independent of country-specific parameters.
Volume 50 October 2000
Journal of the Air & Waste Management Association 1739

Lee, Yang, and Bofinger
In addition to residential indoor NO2 sources, traffic
emission has been associated with respiratory health ef-
fects.4 Pollutants from traffic emission include various
toxic chemicals, and they can affect not only ambient
levels but also indoor levels in homes in heavy traffic ar-
eas. The distance between home and traffic road is im-
portant, especially for children, due to their limited travel
distance from home. For the working population, com-
muting may be a significant source of personal exposure.
In Australia, personal exposure to NO2 has not been
characterized. Based on a few published studies, large geo-
graphical variations were found. In a study in Perth, West-
ern Australia, the indoor mean four-day average level was
found to be 28 ppb, slightly higher than outdoor levels of
24 ppb.5 In the Latrobe Valley, Victoria, the annual mean
indoor level was 8 ppb.6 The Victoria study documented
higher NO2 concentrations in kitchens than in living
rooms and bedrooms and reported seasonal variation, with
higher levels measured during winter.
In this study, indoor, outdoor, and personal NO2 con-
centrations were measured by a protocol identical to that
used in the multinational study.3 An identical question-
naire for housing characteristics and an activity diary also
were used, allowing direct comparison between the present
study and values reported by Levy et al.3 In addition, a
personal exposure model was used to estimate the impact
of commuting in the working population.
residential indoor exposure, workplace indoor exposure,
and residential outdoor exposure according to eq 1
Pi = (IHi • Ii + OHi • Oi + WIi • Wi)/T
(1)
where Pi is estimated time-weighted average personal NO2
exposure for participant i, IHi is number of hours spent
inside the home for participant i during the sampling
period, OHi is number of hours spent outside the home
for participant i during the sampling period, WIi is num-
ber of hours spent inside the workplace for participant i
during the sampling period, Ii is measured average resi-
dential indoor NO2 concentration for participant i, Oi is
measured average outside home NO2 concentration for
participant i, Wi is measured average workplace indoor
NO2 concentration for participant i, and T is total expo-
sure time.
Since not all microenvironments were measured, the
personal exposures from eq 1 were significantly lower than
the measured personal exposures. Differences between the
measured personal exposure (P) and the personal expo-
sure estimated by eq 1 (Pi) could be explained by
nonmeasured microenvironments. The concentrations at
different microenvironments were estimated as the regres-
sion coefficient b in eq 2
P – Pi = bIO • FIO + b(WO+OO) • F(WO+OO) + bT • FT
(2)
METHODS
where P is measured personal NO2 exposure (ppb), FIO is
fraction of hours spent inside other than at home and
workplace, F(WO+OO) is fraction of hours spent outside other
than near home (including outside workplace and other
outdoors), and FT is fraction of hours spent on transpor-
tation.
The impact of transportation in personal exposure
was also determined using the database of the multina-
tional study.3 In the analysis, cities with a sample size of
less than 20 (i.e., Bombay, Manila, Zagreb, and Sosnowiec)
were excluded. Data from Mexico were excluded due to
possible sampling error. The multiregression analysis was
conducted after the data were combined into country or
area. The data were combined into eight regions: (1) North
American cities (Boston and Ottawa), (2) Scandinavian
cities (Kjeller and Kuopio), (3) Western European cities
(Berlin, Erfurt, and Geneva), (4) United Kingdom (Lon-
don and Watford), (5) Korea (Seoul and Taejon), (6) Japan
(Sapporo and Tokushima), (7) China (Beijing), and (8)
Australia (Brisbane).
Residential indoor, residential outdoor, and workplace
indoor NO2 concentrations and personal NO2 exposures
were measured for 57 subjects from six offices located in
Brisbane, Queensland, Australia. The NO2 concentrations
were simultaneously measured during a 2-day period in
June 1999. Winter was chosen because active combustion
in winter tends to elevate both indoor and outdoor NO2
concentrations. Participants filled out an activity diary
and a questionnaire about their homes and their surround-
ings during the course of the study. The study proposal
was identical to the multinational study. Details of the
study protocol are explained in a paper by Levy et al.3
Each site had a coordinator who recruited up to 10
office workers and provided them with all sampling ma-
terials. All NO2 concentrations were measured by passive
filter badges.7 Quality was assured by blanks from each
site to account for differences in sealing quality and lag
time before analysis. Once sampling was completed, the
NO2 passive badges were analyzed by a spectrophotom-
eter (Beckman Model DU640).
Personal exposure can be approximated as the time-
weighted average of microenvironmental concentrations.
Although not all microenvironments were measured in
this study, personal NO2 exposure was estimated using
RESULTS
A total of 58 subjects were recruited from six organiza-
tions located in Brisbane, Queensland, Australia. Personal
exposure data from one subject were excluded, since the
1740 Journal of the Air & Waste Management Association
Volume 50 October 2000

Lee, Yang, and Bofinger
Table 2. NO2 concentrations (ppb) and I/O ratio.
subject did not place indoor and outdoor samplers. The
house characteristic information is shown in Table 1. The
mean number of bedrooms in all houses was 3.2. The av-
erage number of family members was 2.9. Eighteen houses
had gas ranges. None of the houses had pilot lights or
kerosene or coal heaters. Even though the monitoring was
conducted in June (winter in the southern hemisphere),
windows were open in ~89% of the houses at some time
during the sampling period. The NO2 concentrations and
the mean I/O NO2 ratio are shown in Table 2.
Mean
Standard Deviation
Minimum
Maximum
Indoor
10.5
14.5
18.2
15.0
0.78
5.6
5.8
1.2
2.0
31.1
35.0
23.3
31.3
3.62
Outdoor
Workplace
Personal
I/O Ratio
5.0
10.1
5.7
5.2
0.55
0.29
The presence of a gas range had the most statistically
significant influence on indoor concentrations, as shown
in Table 3. The mean indoor concentration in homes with
gas ranges was 13.6 ppb, compared with 9.1 ppb for homes
without gas ranges. The presence of gas ranges provided a
mean I/O ratio of 1.03, compared with a mean I/O ratio
of 0.67 for those without gas ranges. When participants
lived in homes with a smoker, indoor concentrations were
significantly higher. “Single detached house” and “pres-
ence of gas water heater” factors increased indoor NO2
concentrations slightly.
Table 3. House characteristics associated with indoor NO2 concentrations.
Characteristics
Mean Indoor NO2
with Characteristic
(ppb)
Mean Indoor NO2
without Characteristic
(ppb)
p-value
Gas range
13.6 6.2
14.9 7.7
9.1 4.7
9.9 5.0
9.9 5.0
9.8 5.5
0.004
0.025
0.054
0.059
Presence of smoker
Single detached house
Gas water heater
13.6 7.4
13.2 5.1
Outdoor NO2 concentrations were associated signifi-
cantly with the number of bedrooms, residential area, and
house type. Mean outdoor concentration in homes with
one or two bedrooms was 18.5 ppb, compared with 13.6
ppb in homes with three or more bedrooms. Outdoor NO2
levels were higher when the house was in a nonresiden-
tial area or a single detached house. The presence of gas
ranges and gas water heaters was the most significant fac-
tor contributing to personal NO2 exposure. Average per-
sonal exposure in homes with gas ranges was 17.9 ppb,
compared with 13.7 ppb for houses without gas ranges.
Personal exposures were significantly higher when par-
ticipants lived in homes with one or two bedrooms.
Fifty-five participants completed an activity diary
during the sampling period. The participants spent the
majority of their time indoors. The fraction of total
indoor time was 88 6%. Participants spent 54 12% of
their time in homes. Participants stayed inside the work-
place for 29 10% of the time. The fraction of total out-
door time was 4 4%. About one-half of the outdoor time
was spent near the workplace. Transportation time ac-
counted for 7.1 3.4%.
A simple personal exposure model estimated personal
exposure using eq 1. The estimated personal NO2 expo-
sure was significantly associated with the measured per-
sonal exposure, with a Spearman correlation coefficient
of 0.58, as shown in Figure 1. However, the estimated
personal NO2 exposure of 11.2 4.0 ppb was significantly
lower than the measured personal exposures of 15.2 5.3
ppb (paired t test, p < 0.001).
The difference between the measured level and the
estimated level was used to determine concentrations at
other nonmeasured microenvironments. When the mul-
tiple regression was conducted using indoor other than
home and workplace, outside workplace, outside other than
workplace and home, and transportation, only the regres-
sion coefficient for transportation was statistically signifi-
cant. The results for Brisbane are shown in Table 4. Time
spent outside workplace and other than home and work-
place were only 1.9% and 1.1%, respectively. Therefore,
outside workplace and outside other than home and work-
place were combined into one microenvironment in eq 2.
When personal exposures in the multinational data-
base were estimated by eq 1, the estimated personal NO2
exposure of 22.5 15.7 ppb was significantly lower than
the measured personal exposures of 28.8 18.1 ppb.
Table 1. House characteristics in study dwellings and commuting (n = 57).
Number of Houses Number of Houses
with House
without House
Characteristic
Characteristic
House Type (single detached house)
Number of Bedrooms (1 or 2)
Attached Garage
47
11
19
7
10
46
38
50
39
45
6
Presence of Smoker
Gas Range
18
12
51
48
34
Gas Water Heater
Window Open
Commuting with Car
Commuting Time per Day (<60 min)
9
23
Volume 50 October 2000
Journal of the Air & Waste Management Association 1741

Lee, Yang, and Bofinger
in the seven regions is shown in
Figure 2.
DISCUSSION
Average indoor and outdoor NO2
levels were 10.5 and 14.5 ppb,
respectively. The NO2 measure-
ments in this study were relatively
low compared with the levels in
the multinational study with 18
cities. These low levels were ob-
served in only four cities (i.e.,
Kuopio, Finland; Erfurt, Ger-
many; Kjeller, Norway; and
Geneva, Switzerland). These lev-
els were significantly lower than
levels reported in Perth, western
Australia.4 However, the indoor
levels were slightly higher than
the levels observed in Latrobe
Figure 1. Association between measured personal NO2 exposure and estimated personal exposure
by microenvironmental model.
Using the multinational study database, NO2 concentra-
tions in other nonmeasured microenvironments were es-
timated by eq 2. The results in eight regions are shown in
Table 5. Regression coefficients for transportation were
significant for all countries or areas, except China. It is
significant that 19 subjects among the 43 participants in
China did not commute during the sampling period. Re-
gression coefficients for other microenvironments were
not consistently significant.
Valley, Victoria.5 The indoor levels in Latrobe Valley were
reported as annual average.
The average ratio of indoor to outdoor levels was 0.78.
Previous studies in the United States reported that I/O
NO2 ratios were higher in winter than in summer. The
annual indoor level is estimated to be ~60% of the out-
door level in homes without gas ranges.9 Considering 18
out of 57 houses in this study had gas ranges, the I/O
ratio is slightly lower than expected, possibly due to the
fact that 89% of participants opened windows during the
sampling period.
The presence of gas ranges increased personal expo-
sure by 4 ppb in this study, significantly lower than the
increase of 15 ppb reported by Levy et al.3 for homes with
a gas range. Unlike the multinational study, no house in
this study had a pilot light. Considering the absence of a
pilot light, the increase was comparable to the study in
the United States; personal exposure in homes with gas
ranges without a pilot light was 6 ppb higher than in those
with electric ranges.2
NO2 exposure during transportation was not mea-
sured in this study. The estimated NO2 levels in transpor-
tation were compared with residential outdoor levels. The
NO2 level in transportation was ~3 times higher than the
residential outdoor level in Korea and Japan. In western
Europe, North America, and Brisbane, the ratio of NO2 in
transportation to residential outdoor level was ~2. The
ratio was ~1 in Scandinavian cities and the United King-
dom. The relationship between average residential out-
door levels and the estimated NO2 levels in transportation
The impact of indoor NO2 on personal exposure can
be affected by activity patterns. The participants (all of-
fice workers) spent 88% of their time indoors and an
average of 7.1% of their time on transportation. While
the recruitment of office workers allowed for direct com-
parison with the multinational study, it is acknowledged
that office workers may spend the least amount of time
outdoors, and consequently, the impact of residential
NO2 on personal exposure in this study and the multi-
national study may not be applicable to different popu-
lation groups.
Table 4. Estimated NO2 concentrations and fraction of time in four microenviron-
ments in Brisbane.
Regression Coefficient
SE (ppb)
Fraction
Sig
of Time (%)
Indoor other than
Home and Workplace
Outside Workplace
Outside other than
Home and Workplace
Transportation
–14.4 10.4
–8.9 24.8
4.9 2.6
1.9 2.6
0.176
0.720
36.0 24.9
32.0 13.2
1.1 2.3
7.1 3.4
0.151
0.019
Personal exposure was estimated by eq 1. The
Spearman correlation coefficient between the measured
1742 Journal of the Air & Waste Management Association
Volume 50 October 2000

Lee, Yang, and Bofinger
Table 5. Estimated NO2 concentrations in microenvironments from multinational measurements.
Country
Regression Coefficient
SE for Other
Regression Coefficient
SE for Outdoors
Regression Coefficient
Sample Number
SE for Transportation (ppb)
Indoors (ppb)
other than Home (ppb)
North America (Boston and Ottawa)
96.0 27.1a
20.3 21.5
27.0 16.8
39.0 9.6a
66.9 31.6b
33.3 44.5
32.4 16.3
34.0 16.4b
28.3 7.1a
13.5 9.8
16.9 8.7
35.8 8.6a
33.2 6.4a
28.5 32.5
48.1 23.3b
5.4 9.8
60.8 16.2a
43.8 15.1a
35.3 11.9a
16.1 6.4b
134.9 48.0a
71.9 20.0a
36.2 12.2a
18.6 37.0
59.3 9.2a
48
89
57
56
66
88
55
43
502
Western Europe (Berlin, Erfurt, and Geneva)
UK (London and Wartford)
Scandinavian (Kjeller and Kuopio)
Korea
Japan
Brisbane
Chinac
Total
42.1 30.5
49.6 9.3a
ap < 0.01; bp < 0.05; c19 of 43 subjects did not spend any time on transportation.
personal exposure and the estimated personal exposure
was less than the coefficient of 0.81 reported by Levy et
al.3 It should be noted that the denominator of the model
in this study was different from the denominator in the
study by Levy et al.3 When personal exposure was calcu-
lated with a total of the three microenvironments (resi-
dential indoor, residential outdoor, and workplace
indoor), as in the multinational study, the estimated
personal exposure in Brisbane was 13.2 4.4 ppb. The
estimated personal exposures showed better correlation.
When personal exposure was estimated by the equation
with total sampling time, the model provided personal
exposure of 11.2 ppb.
indicates that there are other environmental factors sig-
nificantly contributing to personal exposure. Multiple
regression using other nonmeasured microenvironments
showed that personal exposure could be significantly af-
fected by the NO2 level during transportation.
The importance of transportation on the personal
exposure model was confirmed in separate regressions of
eight regions from the multinational data. Regression
coefficients for transportation were significant in all re-
gions, except China. The results in China may be due to
the large number of noncommuters (19 noncommuters
among 43 subjects). This is another piece of indirect evi-
dence for this methodology. The difference from the per-
sonal exposure model may be caused by various errors.
The passive sampler can produce a measurement error of
less than 20%.8,9 The activity diary was determined with a
resolution of 1/2-hr intervals. Considering the measure-
ment errors, the finding can conclude
Although eq 1 does not include all possible microen-
vironments, it accounts for 85% of the exposure period.
However, the underestimation by the model was greater
than the missing sampling time. The underestimation
that exposure during transportation is
significant for the working population
that commutes.
The methodology using eq 2
demonstrated consistent results in the
large database from the multinational
study. However, the results of the analy-
sis could not be independently verified
due to lack of separate measurement of
NO2 exposure during transportation.
Most previous studies measured expo-
sure to traffic-related air pollutants with
control of routes and transport type.10,11
Personal exposure to the air pollutant,
often higher than concentrations at
nearby stationary monitors, was
strongly associated with transport
Figure 2. Relationship between estimated NO2 level during transportation and average outdoor
mode, route, and city. The higher
level.
Volume 50 October 2000
Journal of the Air & Waste Management Association 1743

Lee, Yang, and Bofinger
4. Brunekreef, B.; Janssen, N.A.H.; deHartog, J.; Harssema, H.; Knape,
M.; vanVliet, P. Epidemiology 1997, 8, 298-303.
5. Dingle, P.; Murray, F.; Jiang, X.Y. In Proceedings of the 11th Interna-
tional Conference of the Clean Air Society of Australia and New Zealand;
Brisbane, Queensland, Australia, 1992.
6. Garrett, M.H.; Hooper, M.A.; Hooper, B.M. J. Air &Waste Manage. Assoc.
1999, 49, 76-81.
7. Yanagisawa, Y.; Nishimura, H. Environ. Int. 1982, 8, 235-242.
8. Lee, K.; Yanagisawa, Y.; Spengler, J.D.; Billick, I.H. J. Expos. Anal.
Environ. Epidemiol. 1992, 2, 207-219.
concentration during transportation is better shown from
continuous CO measurements.12 The estimated NO2 con-
centrations in transportation were equal to or higher than
the average residential outdoor level in all seven regions.
Further measurement of exposure during transportation
is needed to verify the impact of transportation on total
personal exposure.
9. Berglund, M.; Vahter, M.; Bylin, G. J. Expos. Anal. Environ. Epidemiol.
1992, 2, 295-307.
10. Chan, C.C.; Ozkaynak, H.; Spengler, J.D.; Sheldon, L. Environ. Sci.
Technol. 1991, 25, 964-972.
11. van Wijnen J.H.; Verhoeff, A.P.; Jans, H.W.; Bruggen, M. Int. Arch.
Occup. Environ. Health 1995, 67 (3), 187-193.
CONCLUSIONS
This study demonstrated that the presence of gas ranges
was the predominant factor affecting indoor concentra-
tions and personal exposures to NO2 in Brisbane, Austra-
lia. Personal exposure by a microenvironmental model
was closely correlated with the measured personal expo-
sure. However, the estimated personal exposure was sig-
nificantly lower than the measured personal exposure.
Although the difference may be contributed by measure-
ment error and other nonmeasured microenvironments,
regression analysis with nonmeasured microenvironments
strongly suggested that transportation is a major contribu-
tor to the difference. The importance of transportation in
the prediction of personal exposure was confirmed using
the database of the multinational study. The findings con-
clude that exposure during transportation needs to be
considered for better personal exposure models.
12. Akland, G.G.; Hartwell, T.D.; Johnson, T.R.; Whitmore, R.W. Environ.
Sci. Technol. 1985, 19, 911-918.
ACKNOWLEDGMENTS
About the Authors
This study was partially supported by a Queensland Uni-
versity of Technology researcher development grant and
a Commonwealth Government of Australia Australia–
Korea fellowship. The authors wish to thank Gary
Golding, David Grantham, Beno Groothoff, Robin
Ormerod, Claire Richardson, and Ralph Riese, who aided
with data collection, and all study participants.
Kiyoung Lee (corresponding author) was a lecturer of envi-
ronmental and occupational health at the School of Public
Health, Queensland University of Technology, Australia, at
the time of this study. He is currently an assistant professor
at the Department of Epidemiology and Preventive Medi-
cine, University of California at Davis in Davis, CA. Wonho
Yang was an Australia–Korea fellow at the School of Public
Health, Queensland University of Technology, Australia, and
is currently a doctoral candidate at the School of Public
Health, Seoul National University, Korea. Neville D. Bofinger
is a senior lecturer at School of Natural Resource Sciences,
Queensland University of Technology, Australia. To contact
Lee, write Department of Epidemiology and Preventive
Medicine, School of Medicine, University of California, One
Shields Avenue, Davis, CA 95616 (phone: 530-754-8164;
fax: 530-752-5047; e-mail: lee@ucdavis.edu).
REFERENCES
1. Quackenboss, J.J.; Spengler, J.D.; Kanarek, M.S.; Letz, R.; Duffy, C.P.
Environ. Sci. Technol. 1986, 20, 775-789.
2. Spengler, J.D.; Schwab, M.; Ryan, P.B.; Colome, S.; Wilson A.L.; Billick,
I.H.; Becker, E. J. Air & Waste Manage. Assoc. 1994, 44, 39-47.
3. Levy, J.I.; Lee, K.; Spengler, J.D.; Yanagisawa, Y.; Bischof, W.; Braathen,
O.; Chung, Y.; Coward, S.; Gutschmidt, K.; Jin, K.; Korenaga, T.;
Ohkoda, Y.; Pastuszka, J.; Patil, R.S.; Qing, X.; Raizenne, M.; Romieu,
I.; Salonen, R.; Sega, K.; Seifert, B.; Shah, S.; Torres, E.; Yoon, D.; Zhang,
X. J. Air & Waste Manage. Assoc. 1998, 48, 553-560.
1744 Journal of the Air & Waste Management Association
Volume 50 October 2000