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Respiratory Protection Provided by N95 Filtering Facepiece Respirators Against Airborne Dust and Microorganisms in Agricultural Farms


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A new system was used to determine the workplace protection factors (WPF) for dust and bioaerosols in agricultural environments. The field study was performed with a subject wearing an N95 filtering facepiece respirator while performing animal feeding, grain harvesting and unloading, and routine investigation of facilities. As expected, the geometric means (GM) of the WPFs increased with increasing particle size ranging from 21 for 0.7-1 microm particles to 270 for 5-10 microm particles (p < 0.001). The WPF for total culturable fungi (GM = 35) was significantly greater than for total culturable bacteria (GM = 9) (p = 0.01). Among the different microorganism groups, the WPFs of Cladosporium, culturable fungi, and total fungi were significantly correlated with the WPFs of particles of the same sizes. As compared with the WPFs for dust particles, the WPFs for bioaerosols were found more frequently below 10, which is a recommended assigned protection factor (APF) for N95 filtering facepiece respirators. More than 50% of the WPFs for microorganisms (mean aerodynamic diameter < 5 microm) were less than the proposed APF of 10. Even lower WPFs were calculated after correcting for dead space and lung deposition. Thus, the APF of 10 for N95 filtering facepiece respirators seems inadequate against microorganisms (mean aerodynamic size < 5 microm). These results provide useful pilot data to establish guidelines for respiratory protection against airborne dust and microorganisms on agricultural farms. The method is a promising tool for further epidemiological and intervention studies in agricultural and other similar occupational and nonoccupational environments.
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Journal of Occupational and Environmental Hygiene,2:577–585
ISSN: 1545-9624 print / 1545-9632 online
2005 JOEH, LLC
DOI: 10.1080/15459620500330583
Respiratory Protection Provided by N95 Filtering Facepiece
Respirators Against Airborne Dust and Microorganisms in
Agricultural Farms
Shu-An Lee, Atin Adhikari, Sergey A. Grinshpun, Roy McKay,
Rakesh Shukla, Haoyue Li Zeigler, and Tiina Reponen
University of Cincinnati, Department of Environmental Health, Cincinnati, Ohio
Anew system was used to determine the workplace pro-
tection factors (WPF) for dust and bioaerosols in agricultural
environments. The field study was performed with a subject
wearing an N95 filtering facepiece respirator while performing
animal feeding, grain harvesting and unloading, and routine
investigation of facilities. As expected, the geometric means
(GM) of the WPFs increased with increasing particle size
ranging from 21 for 0.7–1 µm particles to 270 for 5–10 µm
particles (p < 0.001). The WPF for total culturable fungi
(GM = 35) was significantly greater than for total culturable
bacteria (GM = 9) (p = 0.01). Among the different microor-
ganism groups, the WPFs of Cladosporium, culturable fungi,
and total fungi were significantly correlated with the WPFs of
particles of the same sizes. As compared with the WPFs for dust
particles, the WPFs for bioaerosols were found more frequently
below 10, which is a recommended assigned protection factor
(APF) for N95 filtering facepiece respirators. More than 50%
of the WPFs for microorganisms (mean aerodynamic diameter
<5 µm) were less than the proposed APF of 10. Even lower
WPFs were calculated after correcting for dead space and lung
deposition. Thus, the APF of 10 for N95 filtering facepiece
respirators seems inadequate against microorganisms (mean
aerodynamic size <5 µm). These results provide useful pilot
data to establish guidelines for respiratory protection against
airborne dust and microorganisms on agricultural farms.
The method is a promising tool for further epidemiological
and intervention studies in agricultural and other similar
occupational and nonoccupational environments.
Keywords agricultural farms, airborne dust, airborne microorgan-
isms, respirators, workplace protection factor, WPF
Address correspondence to: Tiina Reponen, University of
Cincinnati, Department of Environmental Health, P.O. Box 670056,
Cincinnati, OH 45267-0056; e-mail:
armers are at high risk of exposure to airborne dust
and microorganisms. These exposures can cause
respiratory diseases.
According to the U.S.
Bureau of Labor Statistics,
around 13 million
people gain some earnings from farming in the United States.
Of these, 6 million people are family members living and
working on the farms.
The application of engineering controls for preventing
farmers and their family members from exposure to airborne
particles, including microorganisms, is limited because of
the diverse nature of the dust and bioaerosol sources in
agricultural settings. Personal protection by respirators is
often the only feasible option for farmers to minimize their
exposure to airborne dust and microorganisms. However, the
Respiratory Protection Standard (29 CFR Part 1910.134) is not
applicable to many agricultural environments,
and there is
limited guidance for respiratory protection against biological
Respirators used by agricultural workers should be certified
by NIOSH in accordance with 42 CFR Part 84.
Under these
certification guidelines, N95 filtering facepiece respirators
have the filtration efficiency of at least 95% for the most
penetrative particle size of 0.3 µm. These respirators have
been recommended by the Centers for Disease Control and
Prevention (CDC) for health care workers to protect them
from infectious aerosols, which can cause diseases such as
SARS (severe acute respiratory syndrome) and tuberculosis.
Qian et al.
found that the filtration efficiency of some
N95 filtering facepiece respirators is 99.5% or higher for
the NaCl and PSL particles in the size range of 0.75 to
1 µmaswell as for Bacillus subtilis (the mean aerodynamic
diameter = 0.8 µm) and Bacillus megatherium (the mean
aerodynamic diameter = 1.2 µm). The aerodynamic sizes of
most bacteria and fungal spores are between 0.7 and 10 µm
and thus the filtration efficiency by N95 filtering facepiece
respirators should be even higher than 99.5%. However, these
contaminants enter the respirator cavity not only through the
filter material but also through the faceseal leaks, which is
the primary pathway for contaminants to penetrate inside
negative pressure respirators (especially those that have poor
respirator fit). N95 filtering facepiece respirators are relatively
comfortable for workers because they are lightweight and
do not obstruct vision or hinder communication as much as
Journal of Occupational and Environmental Hygiene November 2005 577
elastomeric respirators. Therefore, in the present study, the
N95 filtering facepiece respirator was investigated for its field
performance in protecting farmers against airborne dust and
The workplace protection factor (WPF) is commonly used
to assess respirator performance in the workplace. The WPF,
which is defined as a ratio of the particle concentration outside
the respirator to that inside the respirator, is a measure of the
protection provided in the workplace under the conditions
of that workplace, by a properly selected, fit tested, and
functioning respirator that is correctly worn and used.
In our previous study,
we developed a new personal
sampling system for determining the protection provided by
respirators against airborne dust and microorganisms. This
personal system was tested for its capability of measuring and
reflecting the nearly instant changes in the aerosol concen-
trations inside and outside the respirator through laboratory
and field evaluation.
Both laboratory and field studies
showed this system to be a promising tool in determining
the protection provided by respirators against particles and
microorganisms. The objective of the current study was to use
the newly developed personal sampling system in agricultural
environments to determine the protection provided to farmers
by N95 filtering facepiece respirators against airborne dust
and microorganisms of different particle size ranges. Our
concurrent article
will characterize exposures, whereas this
article focuses on respiratory protection.
Field Study Design
Field samples were collected using a personal sampling
system previously described in detail by Lee et al.
short, the sampling system consisted of two sampling lines
(in-facepiece and ambient sampling lines) that were used to
collect particle samples inside and outside the respirator. N95
filtering facepiece respirators (model 8210, 8110S; 3M, St.
Paul, Minn.) were used in the field experiments. Airborne
dust and microorganisms were sampled through the sampling
probes at a flow rate of 10 L/min and drawn through Tygon
tubing to a metal sampling chamber at the end of each
sampling line. A portion of each aerosol flow (2.8 L/min) was
sampled from the chamber into an optical particle counter
(OPC, model HHPC-6; ARTI Inc., Grants Pass, Ore.) for
dust measurement. The rest of the aerosol flow (7.2 L/min)
passed through a filter sampler that collected the airborne
The selected flow rate of 10 L/min is five times the conven-
tional in-facepiece sampling flow rate used for fit testing. As
described in Lee et al.,
a higher flow rate was selected to
decrease the respirator purge time and the potential sampling
bias for nonhomogenous distributions of the particle concen-
tration inside the respirator. In addition, the high flow rate
decreases the detection limit of particle measurements when
measuring for a specific sampling period, which is especially
important for evaluating the respirator performance against
low concentrations of airborne microorganisms. This high
flow rate, however, may lead to the overestimation of particle
penetration into the mask particularly at low respiration flow
Our field measurements were conducted in six farms—three
types of animal confinements (swine, poultry, and dairy), and
three grain farms. Detail information on farming activities and
farm characteristics, as well as on the methods for enumeration
of airborne dust and microorganisms, are presented in Lee
et al.
All subjects recruited in the study had to pass the medical
clearance evaluation and fit test before participating in field
testing. The medical clearance evaluation was conducted using
the questionnaire, specified in OSHA standard 1910.134,
Appendix C.
The medical clearance was authorized by
a licensed physician. Before starting the field test, subjects
signed an Institutional Review Board consent form, where the
possible risks of the field test were addressed. All study subjects
were required not to have beard or stubble on their face and
not to smoke 1 hour before the test.
The respirator fit test was performed once for each subject
prior to his or her involvement in the field testing. Before
fit testing, each subject was trained and instructed to wear
the respirator properly. The instructions followed the man-
ufacturer’s guidance on the use of the respirator. Fit testing
was conducted with a TSI Portacount Plus in connection with
N95 companion (TSI, Inc., St. Paul, Minn.) in compliance
with the 6-exercise protocol.
With the quantitative fit
test, a fit factor of 100 or above constituted a pass. The
subject then donned the respirator equipped with the personal
sampling system. In each farming environment, one to four
subjects were involved in the experiment that lasted for 30
to 60 min. The testing time covered the time it took the
subject to complete the specific work task under investigation.
Subjects were recruited primarily from agricultural farms,
while students and staff of the University of Cincinnati also
Correction on WPF Data Based on the Respirator
Dead Space and Lung Retention
Several studies have shown that respirator dead space and
lung retention decrease the concentration inside the respirator
during inhalation, resulting in the overstating of the WPF.
Hinds and Bellin
developed a model to predict the average
true concentration inside the respirator after accounting for
the effects of lung retention and respirator dead space. In their
study, the ratio of an average full breathing cycle concentration
to an average inhalation concentration (C
)was related
to the ratio of the respirator dead volume to the tidal volume
). The association was described in detail for five values
of fractional particle depositions in the respiratory tract (F
in the absence of faceseal leakages. Based on the information
obtained for V
and F
in our study, the ratio of C
can be interpolated from a figure presented in Hinds and
Bellin’s paper.
Thus, the corrected WPF (WPF
) can be
578 Journal of Occupational and Environmental Hygiene November 2005
calculated as following:
= WPF ×
where the WPF value is measured during the full breathing
To use this model, information is needed on the respirator
dead space volume, tidal volume, and fractional deposition
of particles in the respiratory tract. For an N95 filtering
facepiece respirator, the respirator dead volume was measured
by immersing a human face into an N95 respirator filled with
water and measuring the remaining water volume inside the
respirator. The average of three repeats was of 123 mL. Tidal
volume of 1250 mL was selected to represent an adult male
performing light work.
The respiratory deposition of particles was calculated using
an existing computer-based deposition model.
These cal-
culations were performed separately for each microorganism
group/species and for dust particles in the five OPC particle
size classes. All of the physiological data, which were required
for the respiratory deposition model, were specified for an
average height of American adult male (176 cm) under light
Data Analysis
The data analysis was performed by analysis of variance
(ANOVA), t-test, and correlation model by Statistical Analysis
System (SAS) version 8.0 (SAS Institute Inc., Cary, N.C.).
P-values of <0.05 were considered significant. Intra- and
intersubject variability in WPFs was investigated by repeated
measure analysis using PROC MIXED procedure in SAS.
Two different models were considered for both dust and
microorganisms. The first model was one-way random effect
model used to examine the between-subject and within-subject
variability without including the covariate of particle size and
microbial type in the model. The second model was a two-
factor mixed-effect model, in which one additional covariate
(particle size for nonbiological particles, and microbial type
for biological particles) was included. Particle size had two
levels: 0.7–2 µm and 2–10 µm, and microbial type had two
levels: culturable fungi and culturable bacteria.
The between-subject and within-subject variability were es-
timated by the restricted maximum likelihood (REML) method
due to the unbalanced nature of data. In addition, the difference
in mean WPFs among five particle sizes as well as among
the predominant fungal spores were examined by ANOVA
followed by pair-wise comparison using Tukey’s studentized
range (HSD) test. The t-test was used to examine the difference
in the protection factors for biological and nonbiological
particles, specifically comparisons between culturable fungi
and culturable bacteria and comparisons between two particle
size ranges: 0.7–2 µm (bacteria) versus 2–10 µm (fungi). The
correlation coefficient was obtained to examine the association
between the WPF for airborne microorganisms and the WPF
for dust of similar particle sizes. All WPF data used for
statistical analyses were log-transformed to achieve normal
distribution. When the concentration inside the respirator was
undetectable, one-half of the detection limit was used to
calculate the WPF.
igure 1 presents the percentile and mean values of the
WPFs, determined as a ratio of the concentration outside
the respirator to that inside the respirator. The WPFs provided
by N95 filtering facepiece respirators against airborne dust
were found to be associated with the particle size. The
geometric means (GM) of the WPFs were 24 for the particles in
the range of 0.7 to 2 µm and 75 for the particles of 2 to 10 µm.
With specific size fractions, GM = 21 for 0.7–1 µm particles,
28 for 1–2 µm particles, 51 for 2–3 µm particles, 115 for 3–5
µm particles, and 270 for 5–10 µm particles. The difference
in WPFs for particles in the five size classes was statistically
significant (p < 0.001). The WPF for the particle size fraction
of 2–10 µm, representing the size of most airborne fungi, was
significantly higher than that for 0.7–2 µm, representing the
size of most bacteria (p = 0.01). Correspondingly, the WPF for
total culturable fungi (GM = 35) was significantly greater than
for total culturable bacteria (GM = 9; p = 0.01).
For the most common fungal genera or groups, the geomet-
ric means of the WPFs were 5 for Aspergillus/Penicillium,6
for Ascospores, 15 for Basidiospores, 68 for Cladosporium,
15 for smut spores, 15 for Epicoccum, and 22 for Alternaria.
Their corresponding calculated mean aerodynamic sizes were
3.7, 5.6, 6.8, 8.1, 9.7, 14.5, and 18.9 µm.
Thus, similarly to
the situation with nonbiological particles, the WPF increased
with an increase in the microorganism size with the exception
of Cladosporium.
When the individual fungal genera and groups were inves-
tigated, Cladosporium had a wide range of WPF values com-
pared with other fungi. The large variability in the spore size
of Cladosporium can explain this phenomenon. The physical
size and aerodynamic size of Cladosporium cladosporioides
are 3.6 ± 0.7 µm and 1.8 ± 0.7 µm, respectively, as reported
by Reponen et al.
The size of Cladosporium spp. measured
in our study ranged from 7.8–16.6 µminlength and 4.3–
9.2 µminwidth, while Ellis
reported wider ranges of
the spore size (3–40 µm [in length] × 2–13 µm [in width])
that reflect different species of Cladosporium.Inaddition, the
agglomeration of the Cladosporium was observed under the
microscope for the air samples. The abovementioned factors
were attributed to a decrease in the penetration of Cladospo-
rium through the faceseal leaks and a greater variation in the
Fungal spores as large as Cladosporium are not able to
remain suspended in the air for a long time. Most of them
will settle down on the ground before they reach the sampling
probe. The concentration of spores in the air may not rise
to considerable levels as long as there is no continuous
aerosolization source in the environment. As reported in our
concurrent study,
most of the concentrations of individual
fungal genera and groups outside the respirator were close to
Journal of Occupational and Environmental Hygiene November 2005 579
the detection limit in animal confinements. This caused the
concentration of these spores inside the respirator to remain
below detection limit in several cases. In these cases, the WPFs
were calculated by using one-half of the detection limit for the
concentration inside the respirator. This might introduce a bias
in estimating the respiratory protection against fungal spores
as large as Cladosporium.
In addition, if the leak size is close to particle size, the
shape of the fungal spores, as well as the shape and size of
faceseal leaks, might affect the penetration of spores through
the faceseal leaks. For example, nonspherical fungal spores,
such as Cladosporium, penetrate differently when the large
end of a spore encounters a small faceseal leak, compared with
when it encounters a large faceseal leak. Likewise, penetration
is different when the large end of a spore encounters a slit
shape faceseal leak compared with a circular faceseal leak.
FIGURE 1. Percentile and mean values of workplace protection factor (without correction for respirator dead space and lung retention)
against dust and microorganisms. The boxplot shows the following: geometric mean; vertical lines from left represent 5%, 25%, 50%, 75%,
95% percentiles; n represents the number of observations; n
represents number of those observations, in which the in-facepiece concentrations
were below LOD. Legend: FF = fit factor; APF = assigned protection factor.
Thus, large variation in the WPF was expected for nonspherical
fungal spores.
Figure 1 also shows the proposed assigned protection factor
(APF) and the pass/fail criterion for N95 filtering facepiece
respirators, which are 10
and 100,
respectively, for N95
filtering facepiece respirators. Among 19 observations, 68%
of the WPFs for particles in the lowest size range of 0.7–1 µm
were above 10, whereas for large particles, this percentage
was greater. However, more than 50% of the WPFs for
microorganisms, such as culturable bacteria (62%), cultur-
able actinomycetes (64%), Aspergillus/Penicillium (65%), and
Ascospores (64%), were below 10. The mean aerodynamic
diameter of these microorganisms was estimated to be below
5 µm. Most of the WPF values for larger fungal spores
were higher as discussed above: 59% of smut spores, 78%
of Alternaria, and 67% of Epicoccum in WPF values were
580 Journal of Occupational and Environmental Hygiene November 2005
above 10. Although the WPF for dust and microorganisms
showed similar increasing trend with increasing particle size,
the WPF for particles were found to be higher than that for
microorganisms of the same size range. This might be due
to differences in the particle losses occurring in the faceseal
leaks due to different shape and density of biological and
nonbiological particles.
Another reason could be related to the measurement bias of
the OPC in size-selective count of dust particles. The optical
particle counter operates by projecting light on particles and
detecting light scattering from particles; thus, factors such
as shape and color of particles interfering light scattering
can affect the instrumental measurement on particles. When
the air samples were analyzed under the microscope, dust
particles with irregular shape and different colors were ob-
served. Unlike the dust particles, fungal spores have close-
to-regular shapes. The difference in reflective index and
shape of the dust particles is expected to cause significant
variability of the measured particle sizes and number con-
centrations in a specific environment when using the OPC.
Furthermore, the irregular shape of dust particles increases
particle losses through the faceseal leaks due to the interception
The density of particles may also play a role. The aerody-
namic sizes of dust particles and fungal spores were calculated
based on the assumption that ρ = 1 g/cm
.However, the density
of dust particles, such as sand and clay, can be higher than
1 g/cm
whereas for many fungal spores the density is smaller
than 1 g/cm
This is likely to result in the underestimation
of the aerodynamic size of dust particles and the overestimation
TABLE I. WPF Correlations
Dust Particle Size Fractions Within the 0.7–10 µm Range
Five Fractions Two Fractions
Microorganism 0.7–1 µm 1–2 µm 2–3 µm 3–5 µm 5–10 µm 0.7–2 µm 2–10 µm
0.7–10 µm
(n = 17) 0.34 0.43 0.46 0.37 0.35
0.37 0.41 0.37
(n = 12) 0.05 0.23 0.19 0.03 0.14
0.13 0.17 0.21
(n = 7) 0.36 0.38 0.15 0.19 0.08
0.39 0.15 0.44
(n = 15) 0.58 0.58 0.57 0.52 0.61
0.59 0.57 0.61
(p = 0.02) (p = 0.02) (p = 0.03) (p = 0.05) (p = 0.02) (p = 0.02) (p = 0.03) (p = 0.02)
Smut spores
(n = 14) 0.05 0.06 0.05 0.22 0.22
0.06 0.07 0.09
(n = 8) 0.13 0.22 0.28 0.28 0.29 0.17 0.32 0.28
(n = 12) 0.24 0.28 0.30 0.33 0.34 0.25 0.29 0.22
Total fungal
(n = 18)
0.40 0.47
(p = 0.05)
(p = 0.04)
0.44 0.51
(p = 0.04)
0.44 0.50
(p = 0.03)
(p = 0.03)
Culturable fungal
spores (n = 18)
(p = 0.04)
(p = 0.02)
(p = 0.01)
(p = 0.02)
(p = 0.001)
(p = 0.03)
(p = 0.01)
(p = 0.01)
Culturable bacteria (n = 18) 0.17 0.23 0.20 0.09 0.11
0.20 0.19 0.25
Notes: Values denote Pearson correlation coefficients (R) for log-transformed WPFs. Significant correlations in bold;anentry in the parentheses indicates the p
values; n = number of observations.
Based on the microscopic analysis.
For some microorganism, one observation was lost.
of the aerodynamic size of fungal spores. Following this logic,
the aerodynamic sizes of dust particles may be underestimated
whereas those for fungal spores may be overestimated. When
the physical sizes of dust particles and fungal spores are about
the same and their Stokes numbers are close to 1, even small
variation in the density of particles can have a pronounced
effect on the dust particle losses in the faceseal leaks due to the
impaction mechanism. The concentration of the dust particles
inside the respirator was lower than that of the fungal spores,
resulting in the higher protection factor. These findings deserve
further research. Since there are no OSHA required guide-
lines for respiratory protection against biaerosols, and OSHA
has proposed to change the APF for filtering facepieces,
the results obtained in this study provide important pre-
liminary information to consider for respiratory protection
against airborne dust and microorganisms in agricultural
Nearly all the WPF studies used to justify the APF = 10
for half-mask respirators have involved particulate contami-
nants, and many of these studies have been done with large
particles. However, large particles, which comprise most of
the total mass, were found to be less penetrative than small
ones. Thus, by determining the total mass concentration
inside and outside respirator, one may lead to underestimate
the WPF values for small particles, which would result in
the overestimation of the APF values. Our data show that the
particle size should be taken into account when assigning APF
Since the WPF for both airborne dust and microorgan-
isms was found to be associated with the particle size, we
Journal of Occupational and Environmental Hygiene November 2005 581
investigated whether the WPF of airborne microorganisms
and the WPF of dust of the same size range correlate with
each other. Table I shows the correlation between the WPF of
dust and the WPF of fungal spores for predominant groups
and genera. The WPF for Cladosporium, total fungi, and
culturable fungi showed a significant association with the WPF
for total dust (0.7–10 µm) as well as with the WPF of dust
in the corresponding size range: 5–10 µm for Cladosporium
(r = 0.61, p = 0.02), 2–10 µm for total fungal spores (r = 0.50,
p = 0.03) and culturable fungal spores (r = 0.61, p = 0.01).
Although the WPF of Aspergillus/Penicillium did not signif-
icantly correlate with the WPF of dust, the best correlation
between the WPF for Aspergillus/Penicillium and dust was
observed with the particles in the size range of 2–3 and 3–5
µm, which coincides with the size of Aspergillus/Penicillium
spores. The WPFs obtained for other microorganisms were
found to have much lower correlation with those obtained for
the particles.
As mentioned above, the variation in the shape and re-
flection index of nonbiological particles may play a role in
the measurement of their size and may explain the poor
correlation between the WPF of airborne microorganisms and
the WPF of dust. In addition, the mean aerodynamic size of
Alternaria (14.5 µm) and Epicoccum (18.9 µm) were greater
than 10 µm, which exceeded the upper limit of the particle
sizes that the OPC can measure at about 10% efficiency. Thus,
for further study involving these two large fungi or similar
ones, the OPC should be customized to measure particle sizes
up to 20 µm. Moreover, the sampling losses through the
sampling line should be carefully addressed for these large
Figure 2 presents the regression plots for the associations
that were found to be significant: WPF of Cladosporium,
total fungi, and culturable fungi vs. the WPF of dust particles
for the corresponding size range. The equations provided
in Figure 2 can be used to estimate the WPF of these
microorganisms when only dust measurement is performed.
It means the WPFs of microbes can be obtained by import-
ing the WPFs of particles of the same aerodynamic size
in the equation. Considerable time and expense could be
saved for the microbiological analysis. However, as we found
significant correlations for only a few microbial types, our
data indicate that the WPFs for most of the microorganism
genus/groups cannot be estimated utilizing WPFs measured for
Several subjects recruited among students and staff at the
University of Cincinnati repeated the experiment in different
farming environments. This allowed us to investigate the
difference in WPFs between and within subjects. Table II
shows the variability of the WPFs between subjects and within
subjects for airborne dust and microorganisms. The Appendix
shows the raw data used in these calculations. The first model
(without covariates) shows that the between-subject variability
was 1.08 for dust and 0.13 for microorganisms, while the
within-subject variability was 1.43 and 3.9, respectively. This
demonstrates that the within-subject variability in WPFs was
FIGURE 2. Correlation between the WPF for microorganisms
and the WPF for particles of corresponding particle size: (A)
Cladosporium vs. 5–10 µm particles, (B) total fungi vs. 2–10 µm
particles, and (C) culturable fungi vs. 2–10 µm particles. y = log
(the WPF for microorganisms); x = log (the WPF for particles).
greater than the between-subject variability for half-mask
respirators when there were no other covariates included in
the model. The findings support the results presented by Nicas
and Neuhaus.
However, when the covariate, such as particle size or
microbial type, was included in the model, the within-subject
variability decreased as seen in Table II. This may result
582 Journal of Occupational and Environmental Hygiene November 2005
TABLE II. Variability of WPFs Between Subjects (σ
) and Within Subjects (σ
)for Dust and Microorganisms
Reduction for Within-Subject
Variation Compared with Model
with No Covariates (%)
No covariates 1.08 1.43 0.43 2.83 3.31
Size only 1.18 1.07 0.52 2.96 2.81 25
No covariates 0.13 3.9 0.03 1.43 7.21
Type only 0.18 3.49 0.05 1.53 6.48 11
= between-subject geometric standard deviation.
= within-subject geometric standard deviation.
in the within-subject variability being equal to or smaller
than the between-subject variability at least for nonbiological
particles. Table II also shows that the fraction of the between-
subject variability versus the total variability for dust increased
from 43% to 52% when the particle size was accounted for
in the model. Note that the between-subject variability in
microorganisms was much smaller than the within-subject
variability. Also, the latter for biological particles was two to
three times larger than that for nonbiological ones. It is likely
that different farming activities involved different particle size
distributions, different microbial composition, and different
faceseal leakage.
TABLE III. Differences in WPF Data Before and After Accounting for Lung Deposition and Respirator Dead
Mean Aerodynamic
Size (µm)
(%) C
Bias E (%)
0.7–1 µm0.9390.82 92 76 22
1–2 µm1.5700.68 146 99 47
2–3 µm2.5920.59 343 202 69
3–5 µm4.0960.57 932 531 75
5–10 µm7.5890.60 2563 1538 67
Fungal spores
Aspergillius/Penicillium 3.7950.57 3 2 75
Ascospores 5.6930.58 5 3 72
Basidiospores 6.8920.59 240 142 69
Cladosporium 8.1870.61 406 248 64
Smut spores 9.7840.62 60 37 61
Alternaria 14.5720.67 256 172 49
Epicoccum 18.9630.71 90 64 41
Mean aerodynamic size is the same as that presented in authors’ concurrent paper.
: fractional deposition of particles in the respiratory tract.
: ratio of an average concentration measured during the full breathing cycle to that measured during inhalation.
: WPF corrected after accounting for lung deposition and respirator dead volume (WPF
= WPF × C
Bias: [WPF-WPF
] × 100%, calculated with nonrounded numbers.
When comparing the within-subject and between-subject
variability in WPFs for airborne dust and microorganisms,
other covariates such as particle size, microbial types, and
farming activities should be carefully addressed, and the effect
of these factors on WPF measurements in agricultural envi-
ronments should be further investigated. From our small-scale
study results, it appears that the WPF distributions between
biological and nonbiological particles are very different from
each other. Therefore, more detailed research will help to better
characterize WPFs.
Previous studies showed that respirator dead space and
lung retention decrease the concentration inside the respirator
Journal of Occupational and Environmental Hygiene November 2005 583
during inhalation, resulting in overestimation of the WPF.
So far, only a few WPF studies have investigated the effects
of respirator dead space and lung retention because the
information on the distribution of the particle size inside the
respirator was not readily available. In this study, the OPC
provided the size distribution of particles inside the respirator
for five different size fractions in the particle size range of 0.7
to 10 µm. In addition, the size information for fungal spores
was obtained from the data presented by Lee et al.
Table III presents the differences in the WPF data before
and after accounting for the lung deposition and respirator
dead volume. As seen from the table, the total deposition
in human respiratory tract (F
) ranged from 39 to 96%
for particles in the size range of 0.7 to 10 µm, and from
63% to 95% for fungal spores, which cover the particle
size range from 3.7 to 18.9 µminmean aerodynamic size.
The measured WPF values were corrected by accounting
for respirator dead space and lung retention using Hind and
Bellin’s approach.
The bias was calculated by dividing
the difference between the protection factors before (WPF)
and after correction (WPF
)bythe protection factor after
correction. For particles in the size range of 0.7 to 10 µm,
the WPFs before correction were overestimated by 22% to
75%. For fungal spores in the mean aerodynamic size of
3.7 to 18.9 µm, the protection factors before correction
resulted in the overestimation ranging from 41% to 75%.
This information provided the possible bias caused by res-
pirator dead space and lung retention when we evaluated
the respiratory protection against airborne dust and microor-
ganisms in agricultural farms. As compared with the WPF
values presented in Figure 1, the percentage of WPF values
less than 10 would be increased after correction for dead
respirator space and lung retention. For example, the percent-
age of WPF values less than 10 for Aspergillus/Penicillium
was increased from 65% to 71% resulting from the
he protection provided by N95 filtering facepiece respira-
tors against dust and airborne microorganisms varied with
particle size, shape, and density. The WPFs for microorganisms
were smaller than those for nonbiological (dust) particles of
the same size range measured by OPCs. This may be due
to pronouncedly irregular shape and higher density of dust
particles as compared to biological particles. More than 50% of
the measured WPFs for microorganisms (mean aerodynamic
size <5 µm) were less than the proposed APF of 10. Even
lower WPFs were calculated after correcting for respirator dead
space and lung deposition. As a consequence, the APF of 10
for N95 filtering facepiece respirators against microorganisms
(mean aerodynamic size <5 µm) seems to be inadequate for
more than 50% of wearings. Our data shows that particle
size and the nature of particles (nonbiological/biological)
should be taken into account when computing APF values
for particulate respirators. In order to establish respiratory
protection guidelines against airborne microorganisms in
agricultural farms, more field data must be obtained. The
present results provide preliminary data toward developing
such guidelines, and the method developed can be used for
further epidemiological and intervention studies in agricul-
tural and other environments with considerable bioaerosol
he authors are grateful to farm owners for providing access
and help in field measurements.
The authors also thank students and staff members who
volunteered to be human subjects in the field testing when
Special thanks go to Mike Brugger and LingYing Zhao
(Ohio State University) for helping us find field sites.
This research was supported by the National Institute for
Occupational Safety and Health (NIOSH R01 OH04085) and
through the Pilot Project Research Training Program of the
University of Cincinnati Education and Research Center.
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APPENDIX I. Relicated WPF Values of Airborne
Dust and Microorganisms
0.7–2 µm 2–10 µm
Subject 1 17.6
45.3 337.754.03.1
Subject 2 27.0 194.958.09.0
34.3 269.2 400.02.2
35.3 145.7 2575.01.6
55.1 414.1 520.6 116.7
Subject 3 74.3 258.8 192.0 709.5
Subject 4 40.3 232.370.025.3
Subject 5 160.7 712.578.12.5
39.4 145.8 293.57.5
115.3 612.6 262.5 169.2
Subject 6 4.37.921.462.4
Journal of Occupational and Environmental Hygiene November 2005 585
... This leads to a higher estimate of the infection risk than that with w < 4. We have measured the TIL in this study on human subjects, as the available data in literature are mostly based on measurements on manikins (30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40), and little or no information regarding the dependency of leakage on particle size is known for human subjects (41)(42)(43)(44)(45)(46)(47)(48). The few studies with human subjects that present size-dependent data (49)(50)(51)(52) are performed with different types of face masks, and none of these covers a representative particle size range necessary for risk calculations considered here. For the lack of a reliable measurement method on human subjects and since data from the literature are inconclusive, we assume the TOL to be the same as TIL (see Total inward leakage and Total outward leakage for more details). ...
... The shaded regions represent the range of leakage values from the worstperforming to the best-performing mask/subject combination. The total inward leakage decreases for all mask wearing cases i to v with particle size for particles larger than 300 nm, which agrees well with the literature (30,32,33,35,(49)(50)(51). The best mask fit, that is, least leakage, is found in case iv, in which the face seal leakage at the nose is eliminated by using double-sided adhesive tape 3M-1509 as explained in Total inward leakage. ...
Full-text available
There is ample evidence that masking and social distancing are effective in reducing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. However, due to the complexity of airborne disease transmission, it is difficult to quantify their effectiveness, especially in the case of one-to-one exposure. Here, we introduce the concept of an upper bound for one-to-one exposure to infectious human respiratory particles and apply it to SARS-CoV-2. To calculate exposure and infection risk, we use a comprehensive database on respiratory particle size distribution; exhalation flow physics; leakage from face masks of various types and fits measured on human subjects; consideration of ambient particle shrinkage due to evaporation; and rehydration, inhalability, and deposition in the susceptible airways. We find, for a typical SARS-CoV-2 viral load and infectious dose, that social distancing alone, even at 3.0 m between two speaking individuals, leads to an upper bound of 90% for risk of infection after a few minutes. If only the susceptible wears a face mask with infectious speaking at a distance of 1.5 m, the upper bound drops very significantly; that is, with a surgical mask, the upper bound reaches 90% after 30 min, and, with an FFP2 mask, it remains at about 20% even after 1 h. When both wear a surgical mask, while the infectious is speaking, the very conservative upper bound remains below 30% after 1 h, but, when both wear a well-fitting FFP2 mask, it is 0.4%. We conclude that wearing appropriate masks in the community provides excellent protection for others and oneself, and makes social distancing less important.
... Most studies that investigate the efficiency of RPD focus on the filtering efficiency of the material from which the RPD devices are made [14][15][16][17][18][19][20][21]. This is often done by fitting the mask border airtight to the surface of a manikin; human test subjects are not typically used in such studies. ...
Full-text available
Since aerosol inhalation is the most common mechanism for COVID-19 infection, the respiratory protective devices (RPDs) have the highest importance in personal protection. The aim of this study was to assess the efficiency of 10 different RPDs in shortening the travelling distance of exhaled air by range measurement using the schlieren imaging technique. When a RPD is worn by a person resting in a seated position, the expired air does not exceed the human convective boundary layer (CBL). Instead, the CBL lifts the expired aerosols vertically up. Thus, they have a prolonged travelling time in the surrounding air and become less harmful by several mechanisms of virus content decay. Coughing as well as expiration valves can cause far reaching expiration air clouds that cross horizontally the human CBL by opening leakage airway corridors into different directions. Measured by the range of expired air an FFP2 mask provided high security under all conditions tested. A non-vented full-face mask with two viral filters performed even better because of its airtight fit and the excellent filtering capacity of the viral filters during inspiration and expiration, even during cough manoeuvres.
... These biologically hazardous substances or bioaerosols might be transferred through the air, and they could cause severe health effects because of their ability to incubate, grow, multiply, and produce toxic substances 138 . The efficient inhaled air filtration and cleaning off such hazardous particles, as well as the destruction of the inhibition of that bioaerosol development, are the matter of respiratory protection systems made of nonwovens filters. ...
Full-text available
Protective masks – worn properly - have become the key to wither away the COVID-19 pandemic. Nowadays, the vast majority of these masks are made of nonwoven fabrics. High-quality products have mainly melt-blown filtering layers of nano/microfiber. Melt blowing produces very fine synthetic nonwovens from a wide range of polymers and allows a fair control of the fiber structure and morphology that makes it ideal for filtration purposes. Melt blowing has a high throughput, and the low price of the filter makes these products widely available for civil use. Although melt-blown fiber applications were rapidly growing in the last three decades, we still have limited knowledge on the processing parameters. In this regard, we detailed the melt blowing parameters to obtain a filter media with high particle capturing efficiency and a low-pressure drop. We summarized the melt-blown fiber mat characteristics with specific attention to the pore size, the porosity, the fiber diameter, the fiber packing density and the air permeability desired for highly efficient filtration. Even though we cannot estimate the future social effects and the trauma caused by the current pandemic, and protective masks might remain a part of everyday life for a long while. That also implies that near-future investments in wider manufacturing capacities seem inevitable. This paper also aims to facilitate masks' production with improved filtration efficiency by reviewing the recent developments in melt blowing, the related applications, the effects of processing parameters on the structure and performance of the nonwoven products focusing on the filtration efficiency via knowledge.
... The aerosol size distribution measurement captured by the Mini-WRAS confirms the importance of using N95 respirators, as used by the participant in figure 1, and has been corroborated in various studies (Lee et al., 2007;Janssen et al. 2013). Therefore, our findings support the continued use of N95 respirators to protect farmers. ...
Highlights The OPC-N3, developed by Alphasense, may be useful in measuring occupational exposure in agricultural settings based on the agreement with mass concentrations measured by gravimetrical filter analysis. The AirBeam2 is better suited for environmental exposure measurements rather than occupational measurements. Particle sizing by the GRIMM Mini-WRAS 1371 and the OPC-N3 show many aerosols that agricultural workers are exposed to follow a bimodal curve and are above 0.1 µm, thereby the respirator used as personal protective equipment is effective in filtering out aerosols in this occupation. Abstract . Prolonged exposure to dust has been shown to have adverse health effects in agricultural workers, primarily with the development of respiratory diseases. Low-cost sensors may be cost-effective tools for farmers to determine when they are exposed to harmful levels of dust during their workday. The purpose of this study was to identify low-cost sensors that may be reliably used in occupational settings to help workers and employers identify respirable particle matter exposure. The study utilized two different low-cost optical particle counters (OPCs) to collect data on dust exposure, which were worn on a belt by the participant: the OPC-N3 developed by Alphasense and the AirBeam2 developed by HabitatMap. Additionally, an AirChek TOUCH air sampling pump fit with a respirable dust aluminum cyclone allowed for the collection of respirable particulate matter (PM4) to determine the true concentration of exposure. Results show that the PM4 measurements made by the OPC-N3 are similar to the gravimetrical filter measurement at concentrations of < 50 µg/m3. In addition, the data analysis suggests that the AirBeam2 may be significantly underestimating the amount of particulate matter that farmworkers are exposed to and therefore may not be suitable for occupational exposure measurements compared to the OPC-N3. Keywords: Aerosols, Agriculture, AirBeam2, Dust, Exposure, Low-cost, Occupational, Optical particle counter, OPC-N3.
... Standard surgical masks provide some level of protection [45,46], but they are far less effective filters than N95 respirators (a factor of 2-10 for surgical masks, and 8-80 for N95s) [47]. N95 masks have been demonstrated to be effective in preventing COVID-19 in a hospital setting [48], but benefiting from them requires proper fit and user compliance [49,50,51,52,53], which suggests that widespread use is likely to be ineffective [54,55]. ...
The COVID-19 pandemic has brought into sharp focus the need to understand respiratory virus transmission mechanisms. In preparation for an anticipated influenza pandemic, a substantial body of literature has developed over the last few decades showing that the short-range aerosol route is an important, though often neglected transmission path. We develop a simple mathematical model for COVID-19 transmission via aerosols, apply it to known outbreaks, and present quantitative guidelines for ventilation and occupancy in the workplace.
... Staff at many workplaces may be exposed to harmful aerosols [1][2][3][4][5]. A characteristic feature of biological hazards is their variability over time. ...
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Studies on the functionalization of materials used for the construction of filtering facepiece respirators (FFRs) relate to endowing fibers with biocidal properties. There is also a real need for reducing moisture content accumulating in such materials during FFR use, as it would lead to decreased microorganism survival. Thus, in our study, we propose the use of superabsorbent polymers (SAPs), together with a biocidal agent (biohalloysite), as additives in the manufacturing of polypropylene/polyester (PP/PET) multifunctional filtering material (MFM). The aim of this study was to evaluate the MFM for stability of the modifier’s attachment to the polymer matrix, the degree of survival of microorganisms on the nonwoven, and its microorganism filtration efficiency. Scanning electron microscopy (SEM) and Fourier transform infrared (FTIR) spectroscopy were used to test the stability of the modifier’s attachment. The filtration efficiency was determined under conditions of dynamic aerosol flow of S. aureus bacteria. The survival rates (N%) of the following microorganisms were assessed: Escherichia coli and Staphylococcus aureus bacteria, Candida albicans yeast, and Aspergillus niger mold using the AATCC 100-2004 method. FTIR spectrum analysis confirmed the pre-established composition of MFM. The loss of the active substance from MFM in simulated conditions of use did not exceed 0.02%, which validated the stability of the modifier’s attachment to the PP/PET fiber structure. SEM image analysis verified the uniformity of the MFM structure. Lower microorganism survival rates were detected for S. aureus, C. albicans, and E. coli on the MFM nonwoven compared to control samples that did not contain the modifiers. However, the MFM did not inhibit A. niger growth. The MFM also showed high filtration efficiency (99.86%) against S. aureus bacteria.
During 2001-2002, the National Institute for Occupational Safety and Health (NIOSH), at the United States Centers for Disease Control and Prevention, collaborated with the Bureau of Labor Statistics (BLS) at the United States Department of Labor to conduct a voluntary survey of U.S. employers regarding the use of respiratory protective devices. In 2003, the survey results were jointly published by NIOSH and BLS. This study highlights and evaluates the scientific impact of the 2001-2002 survey by using Science Impact Framework that provides a historical tracking method with five domains of influence. The authors conducted interviews with original project management as well as a thorough document review and qualitative content analysis of published papers, books, presentations, and other relevant print media. A semi-structured and cross-vetted coding was applied across the five domains: Disseminating Science, Creating Awareness, Catalyzing Action, Effecting Change, and Shaping the Future. The 2001-2002 survey findings greatly enhanced understanding and awareness of respirator use in occupational settings within the United States. It also led to similar surveys in other countries, regulatory initiatives by the Occupational Safety and Health Administration and Mine Safety and Health Administration, and ultimately to a renewed partnership between NIOSH and BLS to collect contemporary estimates of respirator use in the workplace within the United States.
Although measuring the workplace protection factor (WPF) is important to verify the performance of particulate respirators in a real work environment, there are no reports of such measurements in Japan. The aim of this study was to measure the WPF of a replaceable particulate respirator (RPR) and a powered air-purifying respirator (PAPR). Eight participants were subjected to three conditions: wearing a RPR correctly (C-RPR), wearing a RPR as usual (but incorrectly) (U-RPR), and wearing a PAPR in the same way as U-RPR (PAPR). Subjects performed dust-generating tasks for 15 min, during which the WPF was measured. The WPF was calculated by dividing the concentration of particles outside the particulate respirator (Co) by that inside the particulate respirator (Ci). A fit testing instrument was used to measure the number of particles. Ci was measured by inserting the test guide into the face piece, and Co was measured by fixing the test guide near the breathing area of the subjects. The WPF geometric mean values (standard deviations) for C-RPR, U-RPR, and PAPR were 17.7 (2.59), 27.0 (3.86), and 117.3 (5.25), respectively. It is important to generate knowledge about the performance of particulate respirators to prevent occupational respiratory diseases.
Full-text available
Background: This study aims to assess whether the TSI PortaCount (Model 8020) is a measuring instrument comparable with the flame photometer. This would provide an indication for the suitability of the PortaCount for determining the workplace protection factor for particulate filtering facepiece respirators. Methods: The PortaCount (with and without the N95-Companion™) was compared with a stationary flame photometer from Moores (Wallisdown) Ltd (Type 1100), which is a measuring instrument used in the procedure for determining the total inward leakage of the particulate filtering facepiece respirator in the European Standard. Penetration levels of sodium chloride aerosol through sample respirators of two brands (A and B) were determined by the two measuring systems under laboratory conditions. For each brand, thirty-six measurements were conducted. The samples were split into groups according to their protection level, conditioning before testing, and aerosol concentration. The relationship between the gauged data from two measuring systems was determined. In addition, the particle size distribution inside the respirator and outside the respirator was documented. Linear regression analysis was used to calculate the association between the PortaCount (with and without the N95-Companion™) and the flame photometer. Results: A linear relationship was found between the raw data scaled with the PortaCount (without N95-Companion™) and the data detected by the flame photometer (R2 = 0.9704) under all test conditions. The distribution of particle size was found to be the same inside and outside the respirator in almost all cases. Conclusion: Based on the obtained data, the PortaCount may be applicable for the determination of workplace protection factor.
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Different methods available for size measurements of fungal and actinomycete spores were compared for four fungal species (Penicillium brevicompactum, Penicillium melinii, Cladosporium cladosporioides, and Aspergillus versicolor) and two actinomycete species (Streptomyces albus and Thermoactinomyces vulgaris). The physical size of spores was measured with three microscopic methods: with an optical microscope from stained (wet) slides, with an optical microscope from unstained (dry) slides and with an environmental scanning electron microscope (SEM) directly from the microbial culture. The aerodynamic diameter, da, of airborne spores was measured with an aerodynamic particle sizer. The respiratory deposition of spores was calculated with a computer-based model. The environmental SEM measurements indicated larger size for fungal spores than the optical microscope, whereas for actinomycete spores, both microscopes gave comparable results. Optical microscopic measurements showed that the stained fungal spores were 1.1-1.2 times larger than the unstained ones, which was attributed to the different hydration status of spores. There was no clear trend in the relationship between the da and the physical diameter measured with any of three tested microscopic methods. For example, the physical diameter of Cladosporium cladosporioides spores was larger than the da by a factor ranging from 2.0 to 2.2, whereas the da of Streptomyces albus spores was larger than the physical diameter by a factor of 1.3-1.5. Thus, the aerodynamic diameter of microbial spores cannot be accurately estimated solely based on the physical diameter but needs information on the density of the spores that may vary considerably. The results on the spore size were utilized to calculate respiratory deposition of spores. The errors in the size measurement were found to result in overestimation of the respiratory deposition of C. cladosporioides spores by a factor of 1.2-1.8, and underestimation of the respiratory deposition of S. albus spores by a factor of 0.6-0.7. These errors in the size measurement cause bias in the exposure assessment and in the estimation of the efficiency of control devices. More research is needed to standardize the method for particle diameter estimates applicable for airborne spores.
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The efficiency of respirators is usually determined by the protection factor, which is the ratio of the particle concentration outside the respirator to that inside the respirator. Most studies on workplace protection factors (WPF) of respirators have focused on the measurement of total mass concentrations, ignoring the effect of particle size. Furthermore, there appear to be no previous studies on protection factors against biological particles. In this study, a prototype personal sampling setup was developed for determining the protection provided by respirators against non-biological and biological particles in the size range of 0.7 – 10 µm. The range covers respirable and thoracic dust particles as well as most bacterial and fungal spores. The setup is compatible for field use in workplace environments and was optimized by minimizing particle losses in its aerosol transmission system. Theoretical modeling, laboratory tests, and field tests were performed for design optimization. After accounting for aerosol deposition mechanisms due to gravity, inertia, and turbulence affecting aerosol transmission through the straight and bending sections of specialized tubing, the theoretical data showed best agreement with the laboratory and field data for a tube diameter of ½ inch (~1.27 cm) among the three tested diameters. Tubing of this diameter also had the least amount of particle losses, and can be directed either above the ear or above the shoulder of the person whose respiratory protection is being evaluated. In addition, the ability of the setup to measure the WPF when a human subject donned a respirator was demonstrated successfully during soybean unloading. This study suggests that the new setup is a promising tool for future studies on evaluating respiratory protection against airborne dusts and microorganisms in occupational environments.
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The aim of this study was to determine the size distribution of bacteria and fungi occurring in the air of human dwellings. The concentration and size distribution of particulate aerosol, Gram-positive mesophilic bacteria, Gram-negative mesophilic bacteria and fungi were examined in 60 flats situated in the Upper Silesia conurbation, southern Poland. The investigated flats comprised three quantitatively equal (20 flats each) groups: flats without additional emission sources of particulate aerosol and microorganisms (Group I), flats with persons who smoke at least one packet of cigarettes per day (Group II), and flats located near steelworks (Group III). The concentrations of four fractions of particulate aerosol were measured by Harvard impactors (PM 2.5 and PM 10) as well as by cyclone HD and 37 mm filter disc holder (PM 5 and TSP). The concentrations of bacteria and fungi were measured by a particle-sizing six-stage Graseby-Andersen impactor. It was found that the concentrations of particulate aerosol in examined flats were below 0.6 mg/m.(3) and the concentrations of microorganisms were below the level of 10(4) cfu/m.(3). The dominant bacteria present in the air of examined dwellings (Micrococcus/Kocuria spp., Staphylococcus spp., Bacillus spp., Pseudomonadaceae, Aeromonas spp., Nocardia spp.) occurred mostly as single particles in the dwellings without additional emission sources, while in the air of dwellings inhabited by tobacco smokers, they often formed aggregates composed of bacterial and dust particles. The fungi dominant in the air of examined dwellings (Penicillium spp., Aspergillus spp., yeasts) occurred mostly as single particles.
In 1984, the International Commission on Radiological Protection (ICRP) appointed a task group of Committee 2 to review and revise, as necessary, the ICRP Dosimetric Model for the Respiratory System. The model was originally published in 1966, modified slightly in Publication No. 19, and again in Publication No. 30 (in 1979). The task group concluded that research during the past 20 y suggested certain deficiencies in the ICRP Dosimetric Model for the Respiratory System. Research has also provided sufficient information for a revision of the model. The task group's approach has been to review, in depth, morphology and physiology of the respiratory tract; deposition of inhaled particles in the respiratory tract; clearance of deposited materials; and the nature and specific sites of damage to the respiratory tract caused by inhaled radioactive substances. This review has led to a redefinition of the regions of the respiratory tract for dosimetric purposes. The redefinition has a morphologic and physiological basis and is consistent with observed deposition and clearance of particles and with resultant pathology. Regions, as revised, are the extrathoracic (E-T) region, comprising the nasal and oral regions, the pharynx, larynx, and upper part of the trachea; the fast-clearing thoracic region (T[f]), comprising the remainder of the trachea and bronchi; and the slow-clearing thoracic region (T[s]), comprising the bronchioles, alveoli, and thoracic lymph nodes. A task group report will include models for calculating radiation doses to these regions of the respiratory tract following inhalation of representative alpha-, beta-, and gamma-emitting particulate and gaseous radionuclides. The models may be implemented as a package of computer codes available to a wide range of users. This should facilitate application of the revised human respiratory tract model to worldwide radiation protection needs. (C)1989Health Physics Society
Assessing the role of bioaerosols in residence-related symptoms involves (1) determining that symptoms are related to the residence by medical examination and careful questioning, (2) connecting reported symptoms with known or hypothesized effects of bioaerosols, (3) examining the residence for bioaerosol risk factors such as overcrowding/poor ventilation, inappropriate outdoor air intrusion, and dampness/standing water, (4) and finally, if no obvious risk factors are present, air sampling. Air sampling should always be a last resort and should use a reliable volumetric method. Particulate samplers, such as the Burkard personal spore trap, are inexpensive alternatives to viable particle samplers and will provide data on most organisms implicated in hypersensitivity diseases. Interpretation of residential bioaerosol sample data requires both qualitative and quantitative comparison with adjacent outdoor air and examination of aerosol changes related to domestic activities. Recommendations that should lead to a decrease in indoor bioaerosols include the use of air conditioning to allow limitation of outdoor aerosols, prevention of dampness or moisture intrusion, and discouraging the use of humidifying devices other than steam. Bioaerosol assessment in the workplace is often more complex than for residences. Because the symptomatic subjects are not in charge of the environment, such situations often lead to difficult employee/management relations and occasionally to litigation. It is essential that each step in workplace bioaerosol assessment be defensible and that the best possible methods are used. The approach is similar to the approach used for residences, but on a larger scale. Symptom assessment must include stress and ergonomic factors. Air sampling, if this is necessary, must usually be extensive with controls for ventilation rates, occupancy, and spatial variation.
Numerous reports document significant worldwide increases in asthma morbidity and mortality from the late 1970s to the early 1990s. Various social and environmental factors, including exposure to indoor and outdoor pollutants and allergens, have been postulated as partial explanations of increasing asthma trends. Although air pollution concentrations have not generally increased over this period, other factors, including increases in poverty and decreases in regular medical care, may render individuals more susceptible to effects from exposures. There is a substantial literature linking exposure to several gaseous air pollutants with respiratory effects in asthmatics. Since the chemical composition and size distribution of airborne particles vary markedly with time and location, the impact of these heterogeneous mixtures on asthmatics is difficult to study in controlled exposure studies. Epidemiologic studies, however, have repeatedly demonstrated associations of particulate matter (PM) with exacerbations of asthma in ecological time-series analyses of emergency room visits and hospital admissions, as well as in panel studies examining associations with peak flow, medication use, and symptoms. In this article we briefly review asthma pathophysiology and potential pathways through which inhaled particles may affect the respiratory status of asthmatics. We also summarize the quantitative results from epidemiologic studies linking ambient PM to several measures of asthma exacerbations. Our analysis indicates that mean levels of PM occurring in urban areas of North America and Europe may be associated with increases of 2 to 5 percent for hospital admissions for asthma, from 5 to 10 percent for emergency room visits, and up to 60 percent for asthma symptoms.
In 1984 the ICRP appointed a Task Group of its Committee 2, led by Dr W J Bair, to review the respiratory tract model which had been used for dosimetric purposes in ICRP Publication 30 and to propose an updated model. The new model was to reflect the greatly increased knowledge which was available concerning lung physiology; particle clearance and the biological effects of inhaled radioactive particles as well as the increased needs of present day radiation protection. The Task Group set out to provide a respiratory tract model which would meet the following five criteria: 1. permit dose calculations for workers, and for individual members of populations of all ethnic groups; 2. be useful for predictive dose assessments, as well as for setting limits on intake; 3. take account of the influences of smoking, air pollutants and respiratory tract diseases; 4. permit estimates of dose to the respiratory tract from bioassay data; and 5. be equally applicable to radioactive gases and vapours as well as to particles. The 480 pages of the volume under review indicate the success of this massive task. In brief the new model, which applies explicitly to workers and to all members of the general public inhaling gases, vapour or particles, permits the evaluation of dose per unit intake or exposure as well as the interpretation of bioassay data. There is a fundamental difference in approach from the old model, the latter computed only average dose to the whole lung. The new model considers the respiratory tract as five regions, two extrathoracic, the anterior nose or , and the posterior nasal passages, larynx, pharynx and mouth ; the bronchial region (BB); the bronchiolar region (bb), and the alveolar - interstitial region (AI), each of which is assumed to have a different radiosensitivity. These regions differ widely in the radiation doses they may receive, and the model computes specific tissue doses. The model readily permits the insertion of subject specific data, such as age, activity levels, smoking habits and health status. The main features of the model and of the underlying physiology and radiobiology aspects are presented in the first 100 or so pages of the book. The rest being taken up by 8 Annexes, each authored by groups of Task Group members, which contain all the detailed arguments and information on which the report is based, together with large tabulations of valuable physiological and physical data. Specific annexes deal with anatomy and morphology, respiratory physiology, radiation effects on the respiratory tract, deposition of inhaled particles, particle clearance, reference values for regional deposition, specific absorbed fractions of photon energy and absorbed fractions for alpha, beta and electron radiations. This is a detailed and comprehensive model of the human respiratory tract and a very complex one in relation to its predecessor. However, it is versatile and appears to meet all the criteria required of it. For some, its complexity may appear rather daunting and it appears to require major computer programs, such a LUDEP developed by NRPB, to enable it to be used. However, this impression is misleading, if the model is clearly understood it is still possible to make simple dose evaluations without the aid of a computer. This volume provides a wealth of information on the human respiratory tract and its physiology and its appeal should spread far beyond the radiation protection community. This is a valuable working manual as well as a reference book, it is, therefore, a pity that the publishers have not chosen to offer it in a durable hard bound format.
Exposure to airborne fungal spores may cause respiratory symptoms. The hygroscopicity of airborne spores may significantly affect their aerodynamic diameter, and thus change their deposition pattern in the human respiratory tract. We have investigated the change in aerodynamic diameter of five different fungal species as a function of relative humidity. Liquid and dry dispersion methods were explored for the aerosolization of the fungal spores. A new system that produces non-aggregated spore aerosol directly from a moldy surface was designed and found suitable for this study. The spores were aerosolized from a mold growth on agar by ducting dry air over the surface, and spore chains in the flow were broken up by passing the entire flow through a critical orifice. Size-spectrometric measurements with an Aerodynamic Particle Sizer showed that the aerodynamic diameter of the tested fungal spores does not change significantly when the relative humidity increases from 30% to 90%. A more distinct spore size increase was found at a relative humidity of ∼ 100%. The highest change of the aerodynamic diameter was found with Cladosporium cladosporioides: it increased from 1.8 μm to 2.3 μm when the relative humidity increased from 30% to ∼ 100%. The size increase corresponds to an approximate doubling of the particle volume. In order to estimate the effect of hygroscopic growth on the respiratory deposition of spores, the mean depositions in the human respiratory tract were calculated for fungal spores with various size changes due to hygroscopic growth. A recently developed model of the International Commission of Radiological Protection was used for the respiratory deposition calculations. We found that the 27% increase in Cladosporium size results in a 20–30% increase in the respiratory deposition of these spores. We conclude that most fungal spores are only slightly hygroscopic and the hygroscopic increase does not significantly affect their respiratory deposition. Our calculations show that for bioaerosol particles, ranging from 0.1 to 10 μm in diameter, the greatest change in the respiratory deposition due to hygroscopic size changes occurs in the particle size range of 0.5–2 μm.