Vol.1, No.4, 330-331 (2009) Health
doi:10.4236/health.2009.14054
SciRes
Copyright © 2009 Openly accessible at http://www.scirp.org/journal/HEALTH/
Airborne particles and asthma: a biophysical model
Ming Yang, Yixing Wang
Department of Botany, Oklahoma State University, 104 Life Sciences East, Stillwater, Oklahoma 74078, USA;
ming.yang@okstate.edu
Received 9 October 2009 revised 10 November 2009; accepted 12 November 2009.
ABSTRACT
Airborne particles can trigger asthma when
reaching certain threshold concentrations that
vary by a few to several thousand times among
different particles. The underlying mechanism
for the variation is unknown. Here, based on
common knowledge and observations, we pro-
pose that the potency of an airborne particle in
causing asthma correlates positively with the
weight of the particle and inversely with the
friction coefficient between the particle and the
airway epithelium. This model may lead to new
approaches for investigating the asthma phe-
nomenon, and to practical applications for re-
ducing the prevalence of asthma.
Keywords: Pollen; Spores, Allergens; Surface
roughness; Environment
1. INTRODUCTION
It is known that different species of pollens and mold
spores differ greatly in their ability to trigger asthma, as
profoundly represented by the scale of pollen and mold
spore count developed by the National Allergy Bureau
(hereafter referred to as the NAB scale) [1]. Given that
pollens and mold spores, at least within their own re-
spective categories, are similar in chemical composition,
it remains unexplained why such variation occurs.
Induction of asthma by airborne particles involves
both biophysical and biochemical responses. The earliest
response is that the ciliated airway epithelial cells
physically move the particles out of the respiration sys-
tem upon the particle invasion. The lateral motion of the
particles relative to the epithelium can be envisioned as a
physical process relying on friction between two solid
surfaces separated by a layer of liquid (also called lubri-
cated friction). Of two particles having the same friction
coefficient with the airway epithelium, the heavier one is
expected to be less efficiently removed than the lighter
one. Extending from this argument, a particle with a
larger friction coefficient will be more efficiently re-
moved than a particle of the same weight but with a
smaller friction coefficient. In other words, a particle
with smooth surface may tend to slip off the cilia of the
epithelium.
2. THE MODEL
It is proposed that the physical (excluding chemical)
potency (P) of an airborne particle in inducing asthma is
a function of the particle count (n) in a unit space, the
weight of the particle (w), and the friction coefficient (µ)
between the airway epithelial cells and the particle,
which can be expressed by the following equation.
P = nw/µ (1)
3. EVIDENCE SUPPORTING THE
MODEL
The NAB scale indicates that, for mold spores to be a
significant trouble-maker, the count should be about
13,000-49,999 per cubic meter, whereas it is about
20-199, 50-499, and 90-1499 per cubic meter for grass
pollens, weed pollens, and tree pollens, respectively.
These numbers suggest that the abilities of these parti-
cles in causing allergy and asthma vary by several to
about 10 times within a class and several to several
thousand times between classes. It is known that mold
spores are usually about 3-5 µm in diameter and airborne
pollens are usually about 20-90 µm in diameter, which
can be translated into a few dozens to several thousand
times differences in weight between mold spores and
pollens, a range consistent with the range of variations in
the ability to cause allergy and asthma between mold
spores and pollens. Moreover, within each class of the
particles, the diameter variation is estimated to be typi-
cally in the range of one to several times, which are
translated into single to double-digit fold differences in
weight. Therefore, the differences in particle size could,
to a large extent, account for the variation in the ability
to cause allergy and asthma within each class of parti-
cles.
To estimate the ranges of pollen size in different plant
M. Yang et al. / HEALTH 1 (2009) 330-331
SciRes Copyright © 2009 Openly accessible at http://www.scirp.org/journal/HEALTH/
331
331
Table 1. Correspondence between NAB pollen count scales
and pollen sizes.
Grasses Weeds Trees
Pollen count scale as
high for allergy2 20-199 50-499 90-1499
Pollen size range (µm)
(90% of the species) 20-95a 18-90 18-90
Mean pollen size (µm)
± standard deviation
57 ± 29a
(n = 113)
43 ± 30
(n = 267)
40 ± 22
(n = 142)
aMonocot species including eight grass species
groups as the first test of Eq.1, we analyzed the pollen
sizes (lengths) [2] of 114, 267, and 142 species of mono-
cots (including eight grass species), weeds (herbaceous
species), and trees, respectively. Here the data for all the
available monocot species are used to represent the data
for grass species because the sizes are known only for
eight grass species. The results are summarized in Table
1. First, 90% of species in each of the three groups fall in
the pollen size range of 20-95 µm or 18-90 µm. Second,
the monocot species have the largest mean pollen size,
the weeds the second largest, and the trees smallest. The
differences in mean pollen size, after multiplication to
the power of three, represent the differences in pollen
weight, i.e., the ratio in weight is (57:43:40)3 2.9:1.2:1.
These values to a large extent correspond to the differ-
ences in the NAB pollen counts for the three groups of
species, consistent with the model indicated by Eq.1.
However, the variation in weight alone does not fully
explain the differences in the particle count scale be-
tween the pollen classes (e.g. the NAB scale differences
between grass pollens and tree pollens range from 4.5
folds to 7.5 folds whereas the mean pollen weight dif-
ference is 2.9 folds). If particle weight is a factor under-
lying the major differences in the NAB scale, it is rea-
sonable to assume that a related physical factor, the fric-
tion coefficient in the particle-airway epithelium system,
also contributes to the differences in the NAB scale, es-
pecially between pollen classes, i.e., the NAB scale dif-
ferences may be partially accounted for by the differ-
ences in surface features between the pollen classes. The
friction coefficient factor, to some extent, is also ex-
pected to contribute to even smaller differences within
each particle class of both pollens and mold spores.
Although the friction coefficients between human
airway epithelium and airborne particles remain to be
experimentally determined, a survey of scanning elec-
tron microscopy studies of 16 pollen species frequently
linked to asthma indicates that, in general, grass pollens
have the smoothest surfaces, followed by somewhat
rougher pollens of some weed and tree species, and the
roughest pollens of other tree species [3-5]. The levels of
roughness of these pollens inversely correlate well with
their documented abilities to cause asthma. Interestingly,
ragweed, a famously potent weed pollen species in in-
ducing allergy and asthma, is ranked among the
smoothest ones; its surface spines are far apart from one
another and thus are predicted to contribute little to the
roughness (friction coefficient) at a microscopic scale.
Even subtle differences among the pollens with interme-
diate levels of surface roughness seem to inversely cor-
relate with their potencies in inducing asthma [5]. A
similar correlation seems likely to exist for mold spores
as they too vary in surface roughness [6]. These results
suggest that the particle surface structure, the only vari-
able determinant of friction coefficient in the system
involving the airway epithelium and airborne particles, is
an important factor affecting asthma induction, in addi-
tion to the weight factor.
Besides n, w and µ in Eq.1 may be subjective to ma-
nipulation for the reduction or elimination of the effect
of airborne particles on asthma induction. Controlled
environmental conditions that render airborne particles
light and their surface rough may help achieve a satis-
factory goal in asthma prevention or treatment.
REFERENCES
[1] http://www.aaaai.org/nab/index.cfm?p=reading_charts.
[2] http://www-saps.plantsci.cam.ac.uk/pollen/index.htm.
[3] Lewis, W.H. and Imber, W.E. (1975) Allergy epidemiol-
ogy in the St. Louis, Missouri, area. III. Trees. Ann Al-
lergy, 35, 113-119.
[4] D'Amato, G. and Lobefalo, G. (1989) Allergenic pollens
in the southern Mediterranean area. J Allergy Clin Im-
munol, 83, 116-122.
[5] http://www.vcbio.science.ru.nl/en/virtuallessons/pollenpl
ants.
[6] Rydjord, B., Namork, E., Nygaard, U.C., Wiker, H.G. and
Hetland, G. (2007) Quantification and characterisation of
IgG binding to mould spores by flow cytometry and
scanning electron microscopy. J Immunol Methods, 323,
123-131.