Environ. Sci. Technol. 1999, 33, 217-222
Ozone Measurement with Passive
Samplers: Validation and Use for
Ozone Pollution Assessment in
Montpellier, France
NADINE L. BERNARD,
MARIETTE J. GERBER,*
CECILE M. ASTRE, AND
MONIQUE J. SAINTOT
Groupe d'Epidémiologie Métabolique, Cancer Research Center,
INSERM - CRLC, 34298 Montpellier Cedex 5, France
The objective of this pilot study was to determine a way
of assessing personal exposure to ozone (O3) for use in a
study of O3 effects on health. Passive samplers (Passam,
AG) were used to measure pollution levels in Montpellier,
France. They were standardized using an O3 analyzer. Blanks
and duplicates were tested to evaluate sensitivity (6.6 µg/
m3) and imprecision (2 µg/m3). They were validated by
comparing on-site measurements with those of the automatic
UV absorption analyzers of the regional air quality
network (AMPADI-LR). The correlation coefficient was r
) 0.9, p < 10-3, and the regression coefficient was close to
1. The on-site measurements provided information
about local pollution. Distance from NO2 sources (urban
traffic) and sunlight intensity were identified as environmental
determinants of O3 pollution. Residential microenvironmental
concentrations and personal exposure were measured
for 110 subjects. The indoor/outdoor ratio is higher than
in Mexico City and higher than in Toronto in summer but
comparable with that in Toronto in winter. The relationship
between personal exposure and indoor home measurements
is closer than that between personal exposure and
outdoor home environment measurements. This is especially
true for the spring and summer months, when the
correlation between indoor and outdoor measurements is
low (r ) 0.23, p < 0.05). At the workplace, on the
other hand, there is a close correlation between indoor
and outdoor ozone measurements in summer (r ) 0.80, p
< 0.001), as there is between personal exposure and
outdoor measurements (r ) 0.60, p < 0.001).
Introduction
Tropospheric ozone (O3) is a major pollutant produced by
various sources, among them urban traffic through photochemical transformation of nitrogen oxides, carbon monoxide, and volatile organic compounds. It is the major source
of O3 pollution in Montpellier, France. O3 pollution is usually
assessed by air quality network analyzers, but for studies
examining the relationship between O3 exposure and health,
it is better to measure personal exposure to O3 (1). Few O3
passive samplers have been described (2-7), and the sampler
presented in this study was previously used for microenvironmental measurements, e.g., for fixed-site measurements
in a defined environment (8).
* Corresponding author phone: (33) 67.61.30.05; fax: (33)
67.52.29.01; e-mail: [email protected].
10.1021/es971140k CCC: $18.00
Published on Web 12/03/1998
 1999 American Chemical Society
The work reported here is a pilot study for an epidemiological project on the health effects of O3. It had three
objectives: (1) to validate O3 passive samplers in closed
environment measurements and for the assessment of
personal exposure, (2) to assess O3 pollution in the areas of
the city where the potential subjects of the epidemiological
study live and/or work, and (3) to study O3 concentration
and distribution with regard to the main determinants:
sunlight and NO2 sources. This paper presents the results
of this pilot study.
Materials and Methods
Passive Samplers. The passive O3 samplers were provided
by PASSAM AG (Switzerland). As supplied by the firm, the
tubes are protected from sunlight by an opaque cylindrical
box. They cannot be used in this form for personal exposure
assessment and were therefore covered with self-adhesive
aluminum foil and black poly(vinyl chloride) (PVC) film. The
passive samplers consisted of 4.9-cm long calibrated tubes
with an inside diameter of 0.9 cm, within which air diffuses
by molecular diffusion. The sampling period was 5 days.
1,2-Di(4-pyridyl)ethylene solution (DPE) was deposited on
a glass filter, supported by a grid, and fixed the O3. The other
end was left open for air diffusion (Figure 1). Addition of
MBTH (3-methyl-2-benzothiazolinone hydrazone hydrochloride) reactant (5) produced a colored complex, which
was measured in a spectrophotometer at 442 nm after
stabilization in a 30 °C water bath for 1 h. The reaction was
specific to O3, and there was no interference from NO2
(information from the manufacturer).
The diffusion coefficient for O3 is unknown and the O3induced alteration to DPE is not stoichiometric. The samplers
were therefore calibrated using a UV photometric ozone
analyzer: three samplers protected by aluminum foil and
PVC film were placed at the air intake of the analyzer. The
cumulated O3 measured by the analyzer over 5 days was
used as the reference measurement. The procedure was
repeated four times. We determined an F factor expressing
the O3 measurement by passive sampler expressed in µg/
m3/h, using the equation:
Ca ) F × Qe
where Ca is the mean for hourly O3 concentrations measured
in µg/m3/h by analyzer over 5 days and Qe the mean O3 for
the three tubes expressed as µg/tube/h (mean of (Q1 + Q2
+ Q3)/(exposure time, in hours)).
The reliability of the passive sampler equipment was
evaluated using blanks (closed passive samplers) on the
selected sites for 5 days. In addition, O3 concentration was
measured using pairs of passive samplers placed open in the
same environmental conditions for the same period of time
(5 days). This was repeated 20 times to evaluate imprecision
of measurement (Sc) according to the equation: Sc ) SD(diff)/x2 (9). The difference between each pair of values
was computed and the standard deviation [SD(diff)] of these
differences calculated.
Sixteen subjects were asked to wear a pair of O3 passive
samplers, to test the reproducibility of personal exposure
measurement using passive samplers. A special device was
used to avoid the absorption effect of fabrics (10): the
samplers were fixed on a black PVC plate (9 × 6 cm) hooked
onto the wearer’s belt. Variation and correlation coefficients
were computed for the 16 pairs of tubes.
NO2 exposure was assessed with Palmes tubes, previously
validated in the same conditions of use (11).
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FIGURE 1. Scheme of ozone passive sampler.
Analyzers. O3 in the urban road network is monitored by
the regional agency AMPADI-LR, using O3 41M UV absorption
analyzers (Environnement SA). These have a detection limit
of 2 µg/m3 (2 µg/m3 ) 1 ppb) and are accurate to (1% in the
0-2000 µg/m3 range. The analyzers are maintained in
accordance with the manufacturer’s instructions and checked
by AMPADI-LR, which belongs to a national group for the
standardization of air pollution measurements set up by the
Central Air Quality Control Laboratory. We obtained continuous O3 measurements from four permanent stations and
one temporary one.
Study Site Characteristics. Meteorology. Montpellier has
a subhumid Mediterranean climate: hot, dry summers with
a high level of sunlight (2700 h/year) and mild winters. Rainfall
is irregular and heavy, with an average of 800 mm/year (12).
Wind is a very important feature of the local climate. The
annual mean recorded over the last 15 years shows that 37%
of the winds are >4 m‚s-1. Prevailing winds come from the
northwest, with a speed of >4 m‚s-1, and to a minor extent
from the southeast. The latter are humid sea breezes with
a speed of <4 m‚s-1.
Meteorological data for the region were provided by the
Montpellier office of Météo France. The AMPADI-LR measurement stations on sites 29 and 61 recorded temperature,
hygrometry, and wind direction.
Local Atmospheric Pollution. All data were provided by
AMPADI-LR. Sulfur dioxide (SO2) concentrations in Montpellier are low, with a mean annual background level of 10
µg/ m3. The air quality surveillance network does not provide
information on hydrocarbon concentrations. On the other
hand, urban NO2 pollution caused by motor vehicle traffic
and other combustion installations reaches a mean annual
background level of 50 µg/m3 and a mean annual level of
80 µg/m3 when measurements are taken close to busy
roads. The data on O3 concentrations were provided by the
AMPADI-LR stations at sites 19, 29, 25, and 61, three of which
(19, 25, 29) are in the city center. The mean hourly concentration of O3 was 53 µg/m3 in summer (May to October)
and 30 µg/m3 in winter (November to April). The hourly
maximum was 180 µg/m3 (calculated over a 2-year period,
1994-1996).
Motor Vehicle Traffic. The urban area road network of
Montpellier is depicted in Figures 2 and 3. Traffic density
in Montpellier is above the national average. The number
of vehicles at the main entrances and exits of the city was
estimated in 1994 as approximately 200 000/day (Mairie de
Montpellier, 1994). The average number of vehicles at the
toll plaza of the A9 expressway in the same year was 43 000/
day and 72 000/day during the summer holiday period
(Autoroutes du Sud de la France, 1994). Over 800 000
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vehicles/day passed through the city in 1997 (Mairie de
Montpellier, 1997). The center of Montpellier is characterized
by dense housing and narrow streets, with an intricate
network of pedestrianized streets and streets still open to
traffic. The area is surrounded by major thoroughfares with
heavy flows of cars and buses. Outside the city center the
urban pattern is more open, with a large number of urban
freeways and the A9 expressway to the south of the city.
Sampling Sites. These are indicated in Figure 3; 48 sites
over 100 m from busy roads and other identified potential
NO2 sources (heating plants, restaurants, air vents, etc.) had
been studied in a previous NO2 measurement survey (11).
We retained 21 such sites, distributed throughout the entire
urban area; 10 blanks were set up at each of 10 sites. Four
sites (sites 19, 25, 29, and 61) were selected because air quality
surveillance network analyzers were located there. All sites
except site 25 measured background pollution. NO2 and O3
were measured simultaneously at all sites.
At the analyzer sites, passive samplers were attached to
the sampling tubes of the analyzers. At all other sites, the
samplers were set up vertically 2.5 m (the height of the
sampling tube of the analyzer) from the ground on freestanding poles over 2 m from any other vertical surfaces.
These samplers were placed on wooden blocks which kept
them 80 mm from the sides of the support, thus allowing air
to circulate freely around them, but sheltered from prevailing
winds. Each tube was left in position for 5 days, with the
open end facing downward to avoid rain penetration. The
PVC coating of the tubes allowed humidity to run off. The
periods studied were in 1995 and 1996.
Statistics and Graphical Representation. Statistical
analysis was carried out using SAS software (SAS Institute,
SAS/STAT User’s Guide, version 6; SAS Institute, Inc., Cary,
NC). Pearson correlations were computed when variables
showed a normal distribution. Spearman nonparametric
tests were used when variables were skewed. Sunshine
intensity was expressed in W/m2, and temperature in °C.
Distance of measurement site from the city center was
calculated in km using site 23 (in the middle of the city
center) as a reference point. Distance from the expressway
was calculated using the minimum distance between the
relevant site and the expressway. The distances were grouped
into four classes (<1, 1-2, 2-3, and >3 km) for use in a
linear regression model and to estimate the effects of distance
on atmospheric O3 concentrations. The mean atmospheric
O3 concentration was computed for each class.
IDRISI (Microsoft Corp. IDRISI for Windows) and Paintbrush software were used for graphical representation of O3
concentrations over the urban area.
Results and Discussion
Validation of O3 Passive Samplers. The mean O3 measurement of 10 blanks on 10 different sampling sites over 5 days
was 9.2 ( 2.2 µg/m3/h. Three standard deviations (6.6 µg/
m3/h) set the detection limit.
The detection limit for passive samplers using a nitritecoated filter was approximately 17 ppb for a 12-h period and
8 ppb for a 24-h period (1 ppb ) 2 µg/m3) (3). Another
passive sampler using different reagents (6) showed higher
detection limits than the samplers using nitrite-coated filters
(30 ppb/day, 4.3 ppb/week, 1 ppb/month).
The imprecision of 20 pairs of passive samplers was
estimated as 2 µg/m3/h. This result was comparable to that
available with other methods.
Sixteen volunteers were asked to wear two passive
samplers simultaneously for 5 days (in October 1995). The
variation coefficient was 5%. The correlation coefficient for
16 duplicates was r ) 0.9, p < 10-3. This test indicated the
good reproducibility of the personal exposure measurement
FIGURE 2. Distribution of hourly ozone concentration in Montpellier, France, during November 13-20, 1995.
using passive samplers but did not assess the influence of
air movement on the final measurement, as was done by
Scheeren and Adema (7).
Linear regression analysis was used to compare O3
measurement by passive sampler and by O3 41 M analyzer.
The equation gave a slope close to 1 (1.13 ( 0.08 µg/m3), and
the y-intercept was not different from zero. The correlation
coefficient for 40 measurements was r ) 0.9, p < 10-3.
These results enabled the PASSAM O3 passive samplers
to be validated on site. They indicated satisfactory reproducibility and precision of measurement, and in addition,
the samplers were validated by comparison with a monitoring analyzer: the correlation coefficient between the
two measurement techniques was comparable to the
findings of previous studies, in which the same model of
sampler was tested against analyzers in urban and periurban
areas (13, 14).
Microenvironmental Measurements on Urban Sites.
The measurement survey on urban sites was conducted over
5-day periods between June 1995 and October 1996. We
selected two measurement periods, one in summer and the
other in winter.
The mean temperatures recorded for the periods June 29,
1995 to July 3, 1995 and November 13-20, 1995 were 22.2
and 11.2 °C, respectively, while sunshine intensity reached
467 and 279 W/m2. There were slight southeasterlies and
southerly sea breezes during the first period (<1 m/s). During
the second period, the northwest wind, which is usually rather
strong (>4 m/s), was moderate (ca. 2 m/s).
As expected, the mean O3 concentrations were higher in
summer than in winter, as a result of the climatic conditions.
The mean O3 levels at the 22 sites used for both of the
measurement periods were 97.3 ( 24.6 µg/m3 for summer
and 42.2 ( 12.9 µg/m3 for winter.
The distribution of O3 levels over the city is given in Figure
2 for winter and in Figure 3 for summer. O3 concentrations
were low in the city center in both seasons: 20.1 µg/m3/h
for site 25 in winter and 26.5 ( 2.1 µg/m3 for sites 25 and 23
in summer. Site 25, measuring proximity pollution by NOx,
had the lowest O3 levels. Low O3 concentrations were noted
in areas with dense traffic, possibly the result of O3 being
trapped by NO (17). Concentrations therefore increased with
distance from the city center and were highest in periurban
areas.
As expected, winter concentrations were always lower
than summer ones. Site 8 shows a low O3 concentration on
the winter map. This site is close to a large hospital and to
a university, and motor vehicle traffic was high at this period
of the year (data from Mairie de Montpellier, 1997). The
low-O3 concentration area therefore extends to this site, which
is some distance from the city center. In the northwest of
the city, the section covering sites 2 and 51 has lower O3
levels than sites 4 and 50, although the former sites are further
from the city center. This might be explained by the fact
that sites 2 and 51 are close to a busy road. O3 precursors
such as NOx produced by the nearby road may have modified
the O3 concentration gradients as a result of the complex
physical and chemical processes (15) inherent in the dynamic
NO2-O3 cycle.
Personal Exposure and Related Microenvironmental
Exposure. We assessed the O3 personal exposure and the
home indoor and outdoor O3 concentrations of all 110
subjects between June 1995 and September 1996. Indoor
and outdoor measurements were taken at the workplace for
these 110 subjects between June 1996 and September 1996.
A wide range of concentrations is shown in Table 1. The
maximum outdoor values are close to the alarm thresholds,
although the means are lower than in rural suburban areas
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FIGURE 3. Distribution of hourly ozone concentration in Montpellier, France, during June 29, 1996 to July 30, 1996.
TABLE 1. Hourly O3 Concentrations (µg/m3) Assessed by
Passive Samplers in 110 Subjects Over 1 Year
personal
outdoor
indoor
mean
SD
median
min
max
34.3
65.6
31.0
17.6
26.5
18.5
30.1
62.8
29.0
6.5
8.8
6.0
88.0
130.1
79.0
TABLE 2. Winter Hourly O3 Concentrations (µg/m3) Assessed
by Passive Samplers in 40 Subjects
personal
outdoor
indoor
mean
SD
median
min
max
15.4
52.8
19.9
7.7
25.4
10.9
13.7
49.7
16.9
6.5
8.8
6.0
39.6
89.5
65.2
(16), 50 µg/m3, and lower than the November-June means
for Mexico City, 124 µg/m3 (17).
The indoor/outdoor ratio, 0.41, is twice as high as in
Mexico City (17). There is a moderate but significant correlation between personal exposure and indoor concentration
(0.54, p < 0.001) and weaker correlations between personal
exposure and outdoor concentration (0.24, p < 0.05) and
between outdoor and indoor concentrations (0.28, p < 0.01).
Winter and summer measurements were analyzed separately. The winter concentrations are shown in Table 2. These
figures are higher than those measured in Toronto in 1992
by Ogawa’s passive samplers and reported by Liu et al. (18),
especially for indoor measurement. This results in a very
low indoor/outdoor ratio in Toronto: 0.07 versus 0.31 in
Montpellier. In our study, the correlation coefficients are
high and significant: 0.71, p < 0.001 between personal
exposure and indoor concentrations; 0.61, p < 0.001 between
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TABLE 3. Summer Hourly O3 Concentrations (µg/m3) Assessed
by Passive Samplers in 70 Subjects
personal
outdoor home
indoor home
outdoor work
indoor work
mean
SD
median
min
max
44.1
70.1
34.9
81.1
36.2
18.2
34.5
17.1
30.5
18.8
42.4
69.6
32.7
78.9
33.5
10.6
9.2
8.3
10.1
9.8
88.0
130.1
79.0
136.2
82.5
personal exposure and outdoor concentrations; 0.62, p <
0.01 between indoor and outdoor measurements.
The summer concentrations are shown in Table 3. Again,
figures are higher than those measured in Toronto by Liu et
al. (18). However, the indoor/outdoor ratios are close: 0.40
in the Toronto study and 0.46 in our study. Correlations of
personal exposure with home indoor measurements and with
indoor and outdoor work measurements are generally much
higher in our study (0.30, 0.70, and 0.60, respectively) than
in the study of Liu et al. (18) showing no correlation between
personal exposure and indoor measurement at home and at
work. Their best coefficient of correlation was for personal
exposure with outdoor measurements at home (0.20),
whereas our study showed no correlation between these sets
of measurements in summer. The time activity pattern of
subjects in Montpellier differed from the time activity pattern
of subjects in Toronto mostly by the fractions of time spent
at work (36 ( 8% versus 23 ( 31%) and by a much lower
variation among subjects (fraction of time spent at home 41
( 4% in Montpellier and 45 ( 32% in Toronto).
Environmental Determinants of O3 Concentrations. O3
measurements were taken over 10 5-day periods between
June 1995 and June 1996, to study the effect of meteorological
factors, temperature, and sunshine. The meteorological data
TABLE 4. Mean Hourly O3 Concentrations (µg/m3/h) in
Relation to Distance from the City Center for Two Seasons in
1995
distance
(d) from
city center
winter period:
Nov 13-20, 1995
mean O3 ( SD
summer period:
June 29, 1995
to July 30, 1995
mean O3 ( SD
d < 1 km
1 km e d <
2 km
2 km e d <
3 km
d > 3 km
(N ) 3) 25.0 ( 4.3a-c
(N ) 5) 40.5 ( 2.2a,d
(N ) 5) 50.6 ( 24.1f-h
(N ) 6) 84.8 ( 9.1f,i,j
(N ) 6) 43.0 ( 6.4b,e
(N ) 9) 103.8 ( 15.3g,i
(N ) 3) 61.9 ( 6.6c-e
(N ) 5) 120.0 ( 9.8h,j
Significance:
f,ip
< 0.05; ap < 0.01;
b,e,jp
< 0.001;
c,d,g,hp
) 0.0001.
for sites 29 and 61 were recorded by AMPADI-LR. There is
a strong significant correlation between O3 concentrations
and sunlight: r ) 0.96, p < 10-3, site 29; r ) 0.87, p <
0.001, site 61. The correlation between O3 concentration
and temperature is weaker: r ) 0.74, p < 0.05, site 29; r )
0.66, p < 0.05, site 61. When we computed a partial
correlation between O3 concentration and temperature
taking sunlight intensity into account, the correlation between O3 levels and temperature became nonsignificant.
The partial correlation between O3 concentration and sunlight taking temperature into account modified the correlation coefficient only slightly: r ) 0.95, p < 10-3, site 29; r )
0.77, p < 0.01, site 61. This confirms that temperature has
no or very little effect on the O3 production cycle. Temperature is a covariable of sunlight (r ) 0.85, p ) 0.001), and
the causal relationship exists only between sunlight and O3
concentration.
With regard to the relationship between NO2 concentration and O3 concentration, we first compared NO2 and O3
levels measured with passive samplers at fixed sites and times.
We studied the association between NO2 and O3 for the
10 periods between June 1995 and June 1996 on a limited
number of sites. There was an inverse correlation between
hourly levels of NO2 and O3 at four sites (sites 19, 25, 29, and
61): r ) -0.74, p < 10-3. These sites were selected because
there were air quality surveillance network analyzers located
there, and a comparison between the two measurement
methods was therefore possible.
We studied the association between O3 and NO2 for one
period only (November 13-20, 1995) on 17 sites. The
correlation coefficient between O3 and NO2 measurements
was r ) -0.96, p < 0.01. There was likewise an inverse
correlation between distance from city center and the NO2
level (r ) -0.74, p < 10-3 during winter 1995; r ) -0.88, p
< 10-3 during summer 1995); a positive correlation was
observed between distance from city center and the O3 level
(r ) 0.77, p < 10-3 during winter 1995; r ) 0.78, p < 10-3
during summer 1995).
However, whereas there was an inverse correlation
between the minimum distance of the measurement sites
from the expressway and the NO2 levels, (r ) -0.63, p < 10-3
in winter 1995; r ) -0.73, p < 10-3 in summer 1995), the
positive correlation coefficient between the minimum distance of the measurement sites from the expressway and the
O3 levels was not significant, indicating the possible influence
of the two NO2 sources, city center and expressway, on O3
generation.
We determined the relationship of O3 and NO2 concentrations using a four-class classification of distance from city
center (Table 4). The O3 means in summer were higher than
those in winter, but both periods showed increasing concentrations as distance from the city center increased. The
lowest level was observed at a distance of <1 km. Significant
thresholds were found at distances of <1 and >3 km in winter
and at distances of <1 km and between 1 and 2 km in summer,
indicating that increased sunlight tends to increase O3
concentrations in areas closer to the city center in summer
than is the case in winter.
Statistical analysis enabled us to assess the potential
influence of the main sources of O3 precursors during the
different climatic periods. The effect of the city center
appeared to be important in both winter and summer, but
to differing degrees. The expressway did not appear to have
a significant effect on O3 concentrations during the periods
studied. Because it is located to the south of the city center,
the expressway may only have an effect when there is a
southerly blowing and dispersing pollutants. We could not
determine any potential influence of the expressway, because
the southerly was very weak during the summer period
studied.
The NO2 measurements were in agreement with previous
results (11). The findings on the relationships between NO2
sources and concentrations and between NO2 and O3
concentrations not only confirm our knowledge of the kinetics
of O3 generation but also, because they are consistent,
indirectly validate our O3 and NO2 measurements by passive
sampler.
The findings of our study are in agreement with what is
generally known about the environmental conditions for O3
pollution, namely, the importance of sunlight and of motor
vehicle traffic. We were able to verify that these conditions
were relevant to the Montpellier situation.
We now possess a cartographic representation of O3
distribution in Montpellier, even if this representation is
influenced by the choice of sampling sites. It has enabled
us to determine the mean O3 levels for all the districts in
which our study groups live and/or work. This finding, in
conjunction with the factors influencing O3 levels, can be
used to establish an exposure index to assess the level of
personal exposure of city dwellers to atmospheric pollution
(19).
Acknowledgments
This study was supported by the Environment Ministry
(Contract 94246), the Environment and Energy Conservation Agency (ADEME, Contract 9593019), and the Ligue
départementale de l’Hérault contre le cancer. We thank
Bernard Vuillot, Murielle Ducaté, Corinne Favier, Joumana
Michalou, and Robert Goulevitch for their assistance in
this research.
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Received for review December 31, 1997. Revised manuscript
received September 14, 1998. Accepted October 15, 1998.
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