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A new portable sampler to monitor pollen at street level in the
environment of patients
Letty A. de Weger
a,
⁎,Frank Molster
b
, Kevin de Raat
a
, Jeffrey den Haan
a
,Johan Romein
b
, Willem van Leeuwen
c
,
Hans de Groot
d
, Marijke Mostert
c
,Pieter S. Hiemstra
a
a
Department of Pulmonology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, the Netherlands
b
Leidse Instrumentmakers School, Einsteinweg 61, 2333 CC Leiden, the Netherlands
c
University of Applied Sciences, Zernikedreef 11, 2333 CK Leiden, the Netherlands
d
Department of Allergology, Reinier de Graaf Gasthuis, Reinierde Graafweg5, 2625 AD Delft, the Netherlands
HIGHLIGHTS
•An easy-to-use portable pollen sampler
is developed and validated
•At street level grass and birch pollen is
distributed unevenly throughout a city
•Grass/birch pollen is detected weeks
earlier at street- compared to
rooftop level
GRAPHICAL ABSTRACT
abstractarticle info
Article history:
Received 27 March 2020
Received in revised form 28 May 2020
Accepted 19 June 2020
Available online 20 June 2020
Editor: Pavlos Kassomenos
Keywords:
Pollen monitoring
Personal sampling
Street level
Portable sampler
Hay fever
Allergic rhinitis
Allergic rhinitis caused by pollen exposure is one of the most common allergic diseases. Therefore monitoring
pollen levels in ambient air is an important tool in research and healthcare. Most European monitoring stations
collect airborne pollen at rooftop levels for measurements in the larger surrounding of the sampling station, and
not in the direct environment of sensitized subjects. Here we present the development and evaluation of a por-
table pollen sampler, called “Pollensniffer”, that was designed to collect pollen in the immediate environment of
allergic subjects. Validation of the Pollensniffer against the standard volumetricpollen sampler showed for most
pollen types high correlations between the number of pollen collected by those two devices (Spearman's Corre-
lation Coefficient N0.8); the Pollensniffer appeared to collect on average 5.8 times more pollen per hour than the
static sampler. Pollen monitoring was performed using this Pollensniffer at street level at 3 different locations in
the city of Leiden during 22 weeks in 2017 and 21 weeks in 2018, during three 15-min periods a day and at one
day in the week.The results showed that thepollen levels for birch and grass pollen can significantly differ from
location tolocation and per time of day. Furthermore, the Pollensniffermeasurements at street level showed that
birch and grass pollen grains were detected 1 1/2 and 2–3 weeks, respectively, before detection at rooftop level.
The street measurements show that allergicsubjects can encountervarying pollen levels throughout the city and
that they canbe exposed to grass and birchpollen and may experiencehay fever symptoms, evenbefore the sam-
pler at rooftop level registers these pollen.
© 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://
creativecommons.org/licenses/by/4.0/).
Science of the Total Environment 741 (2020) 140404
⁎Corresponding author at: Dr. L.A. de Weger, Department of Pulmonology, Leiden University Medical Center, P.O. Box 9600,2300 RC Leiden, the Netherlands.
E-mail address: l.a.de_weger@lumc.nl (L.A. de Weger).
https://doi.org/10.1016/j.scitotenv.2020.140404
0048-9697/© 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Contents lists available at ScienceDirect
Science of the Total Environment
journal homepage: www.elsevier.com/locate/scitotenv
1. Introduction
Thirty to forty percent of the Europeans suffers from the symptoms
of allergic rhinitis (Blomme et al., 2013), and although sometimes trivi-
alized, it is considered as a major health problem. The most common
symptoms of allergic rhinitis are itchy or runny nose, sneezing, blocked
nose and commonly co-existing non-nasalsymptoms such as itchy and
watery eyes; importantly, also quality of life, sleep and work productiv-
ity is affected (Bousquet et al., 2006). Although these symptoms are
bothersome, about 10% of the patients never consult their doctor for
their problems, and most patients treat their symptoms by self-
medication (Maurer and Zuberbier, 2007). Yet, it is known that inade-
quate treatment of allergic rhinitis can trigger the development of
asthma (Bousquet et al., 2008).
Besides these medical and social aspects, also the economic impact
of allergic rhinitis is considerable: the total mean of health care and in-
direct costs (absenteeism and presenteeism) amounts to €2326,70 per
allergic rhinitis patient-year (Colas et al., 2017).
Pollen exposure is a major trigger for allergic rhinitis symptoms.
For both patients and their treating physicians, it is relevant to
know when allergenic pollen is in the air. Therefore, more than 500
pollen monitor stations in Europe monitor the pollen grains that
are present in the air on a daily basis (Buters et al., 2018). The pollen
samplers are located at a height of 10–30 m above ground level to
collect the different pollen types that are released by the plants pres-
ent in the region and is thus representative for the larger surround-
ings. Monitoring pollen at this height is justified since sampling at
near ground level would favour the collection of more locally pro-
duced pollen and would show more daily fluctuations, while at
10 m and higher above ground level the pollen concentrations are
more stable (Galán et al., 2014;Rojo et al., 2019). However, patients
are mostly exposed at street level, and knowledge on the d istribution
of aero-allergens at this level is limited. Some studies monitored pol-
len at different height levels and compared the street level measure-
ment using a stationary sampler with the same kind of sampler
located at rooftop level. Most of these studies showed that the pollen
concentrations at rooftop level correlate well with the pollen con-
centrations monitored at street level, although in general the con-
centrations were higher at street level (Bastl et al., 2019;Rantio-
Lehtimäki et al., 1991;Rojo et al., 2019;Spieksma et al., 2000). One
studyshowedthatatsocalled‘street canyon environments’in
urban areas, grass pollen concentrations tended to be lower (Peel
et al., 2014a). Studies on the pollen distribution at street level in cit-
ies are limited. In these studies different sampling methods have
been used, but they all indicate that highly variable pollen concen-
trations exist at different locations within cities at street level
(Ishibashi et al., 2008;Katz and Carey, 2014;Skjøth et al., 2013;
Werchan et al., 2017).
In order to be able to monitor pollen at different locations, easy-to-
use, portable samplers are needed. Furthermore, such samplers can be
used to monitor pollen or other allergens in the direct environment of
the patient. Fiorina et al. (Fiorina et al., 2003)describedthataerobiolog-
ical sampling in the direct environment of two asthmatic patients, for
whom the causative allergen was difficult to identify, revealed the re-
sponsible allergen. In that pilot study, a battery operated portable sam-
pler (PARTRAP) was used (Fiorina et al., 1997). In the past decades
several other personal samplers have been described, but –to our
knowledge- these devices, including the PARTAP, are not commercially
available (Peel et al., 2013;Renstrom et al., 2002;Werchan et al., 2018;
Yamamoto et al., 2015). Furthermore, the user-friendliness and the effi-
cacy of these devices varies; nasal samplers (Renstrom et al., 2002)are
placed in the nostrils of the nose and depend on breathing, and the Per-
sonal AeroAllergen Sampler (PAAS) (Yamamoto et al., 2007)relieson
passive pollen collection and is carried around the neck for a longer pe-
riod, which both may not be very comfortable. The currently available
transportable samplers (Peel et al., 2014b) are made for installation on
the floor, but not specifically for portable use and furthermore has a
lower efficiency than a static 7-day recording sampler.
Therefore, in this paper we developed a portable sampler, that is
ease-to-use to collect allergens at different locations, especially in the
environment of allergic patients. Although the constructed device,
called Pollensniffer, can also collect other bioaerosols like fungal spores,
in this study we focussed on pollen. The Pollensniffer was validated by
comparison to a standard Hirst type pollen sampler (Hirst, 1952), and
used to study the distribution of birch and grass pollen at street level,
since here the patients will come into contact with the pollen. In the
analysis of the data we focussed on issues that are relevant for the aller-
gic rhinitis patients such as (i) the differences in pollen levels at differ-
ent locations in the city; and (ii) the timing of exposure to the first
pollen grains of the season at street level.
Fig. 1. a. Pollensnifferwith the conicalinlet (A) and the aluminium closingof the opening for thesample holder (B).A connector cableconnects a power bank(C) to a micro-USB connector
(D) in the Pollensnifffer.The airstream generated by the ventilator insidethe Pollensnifferleaves the Pollensniffer at openingsat the rear end (not shown)and at three backsides (e.g.E). b.
The Pollensniffer (PS1) mounted on the rain cover of the static sampler on the roof of the LUMC.
2L.A. de Weger et al. / Science of the Total Environment 741 (2020) 140404
2. Materials and methods
2.1. Description of the Pollensniffer
The Pollensniffer isa portable device to monitor airborne pollen with
the following dimensions: diameter 6 cm; length 15 cm; weight 408 g
(Pollensniffer) + 205 g (power bank). The body of this low-volume
Pollensniffer (Fig. 1a) consists of four elements that were printed in a
3D printer using POM (polyoxymethylene). The technical drawings
are shown in Supplementary Fig. S1.Three elements at the back
(Fig. S1, b, d and e) were connected using 4 long thin bolts. The inlet is
placed onto the body via a bayonet mount. The inlet (Fig. S1,a) has a
conical shape and behind the inlet, a static sample holder is inserted.
This sample holder can be placed into the Pollensniffer via an opening
on the side. This opening is secured by an aluminium handle (Fig. 1a,
arrow B).
The static sample holder contains a 4 cm-long, 2.5 cm-wide carrier
glass-slide on which a Vaseline-coated Melinex strip (Burkard
Manufacturing Co. Limited, UK) is mounted to collect the pollen, that
passed the inlet. Behind thesample holder, a ventilator generates an air-
stream into the Pollensniffer. Pollen grains that are drawn in, are
trapped onto the Vaseline strip. The air stream passes through the
Pollensniffer and escapes via openings at the rear end (Fig. 1a, arrow
E). Electronics to power the ventilator are located behind the ventilator.
Using a connector cable, a power bank (Fig. 1a, C; Intenso S10000,
Germany) is connected to the Pollensniffer via a micro-USB connector
(Fig. 1a, D). The ventilator generates an airflow through the inlet
(10 mm) and the pollen grains are drawn inwards and collide with
the Vaseline-coated Melinex tape and stick into the Vaseline. Although
an estimated 90% of the pollen grains are deposited on the Vaseline
tape in an approximate 12 mm circle behind the inlet, also all pollen
grains collected on the tape outside this circle are counted (see also
later).
To measure the air flow that passed through the Pollensniffer an
electronic flow cell (Honeywell AWM5102 VN airstream sensor, North
Carolina, USA) was air-tightly connected to the conical inlet of the
Pollensniffer via a funnel. The flow appeared to be constant during the
whole operating time of the power bank, i.e. 5–6h.
The Pollensniffer was evaluated for its user-friendliness by partici-
pants of a local theatre and music festival in Schipborg, Netherlands
(FestiValderAa, 7–9 July 2017). Fifteen random, voluntary participants
used the Pollensniffer by holding it in their hand during a short walk
and completed a small questionnaire on the user-friendliness of the
device.
2.2. Validation of the Pollensniffer
On the roof of the 6th floor of the Leiden University Medical Center
(LUMC; west part of the Netherlands), approx. 22 m above ground
level two static traps (Burkard Manufacturing Co. Limited, UK) were
present. One sampler was used for the routinely monitoring of the
daily pollen concentrations (see later), while on the other sampler the
firstly constructed Pollensniffer (PS1) was mounted on the rain-cover.
The inlets of the Pollensniffer and the static sampler were both facing
the wind guided by the wind vane of the static sampler (Fig. 1b). As
shown in Fig. S1 the inlet of the Pollensniffer has a conical shape and a
round inlet with a 10 mm diameter. The static sampler has a standard
rectangular inlet of 14 × 2 mm. Both devices collected pollen during 1
or 2 h periods from February 28th to April 4th 2017. Forty-one samples
for each of the devices were collected on warm, dry days, anticipating
high levels of pollen.
Following manufacturing of the first Pollensniffer (PS1), another
four Pollensniffers (PS2, PS3, PS4, and PS5) were constructed. The per-
formance of these Pollensniffers was compared among each other. To
this end, the five Pollensniffers were mounted on a rack (15 cm height)
at a distance of 20 cm from each other on the roof of the LUMC. They
were allowed to collect pollen for 30 min periods on June 13th and
19th, 2017, resulting in 8 different samples for each of the five
Pollensniffers. In this period mainly Poaceae and Urticaceae pollen
were present and used for the analysis. All Poaceae and Urticaceae pol-
len presenton the slides were counted.
2.3. Pollen monitoring at street- and rooftop level
Rooftop level pollen samples were collected with one of the static 7-
day volumetric spore trap continuously. At street level, pollen were col-
lected by the Pollensniffer from April 6th to September 5th in 2017 and
February 7th to June 29th in 2018. Three locations in the city of Leiden
were selected (Fig. 2): (i) in a main shopping street in Leiden (=City
Center) without any plants or trees, except for Linden trees (Tilia)in
the side way; (ii) on an open space in a park within the city canal
boundaries (Huigpark) with a stretch of grass and a diversity of trees,
like Aesculus, Salix, Betula, Platanus, Populus, Sorbus, and Taxodium
distichum; and (iii) on an open space in a park more at the border of
the city (Kweeklust) with a small grass area and several trees like
Platanus, Populus, Salix, Taxodium distichum, and bushes like Corylus.
The birch tree species in the surroundings of the monitoring locations
are mapped and shown in Supplementary Fig. S2. An overview of the
birch species present in an approximately 500 m circle around the mon-
itor locations is as follows: for the City Center location only a few Betula
species are present in a 500 m circle, i.e. B. pendula (8 trees),
B. papyfrifera (6 trees) and B. ermanii (6 trees). For the Huigpark location
hardly any Betula species are present at the south side of the park, but at
the north side several B. pendula species are found e.g. B. pendula (60
trees), B. papyrifera (15 trees), B. ermanii (6 trees), B. nigra (30 trees)
and B. utilis (17 trees). In the surroundings of Kweeklust (within a
500 m circle) at the north side of the city, hardly any Betula trees are
present but in the streets on the other sides different Betula species
can be found, i.e. B. pendula (43 trees), B. ermanii (4 trees), B. papyrifera
(5 trees), B. utilis (2 trees), B. pubescens (8 trees) and B. nigra (3 trees).
When focussing on grass in the surroundings of the monitoring loca-
tions it is clear that for the City Center very little grass is present except
for some well-maintained grass areas at approx. 400 m from the loca-
tion. Also at the locations in the parks, the grass areas are well main-
tained. Only close to Kweeklust there are some grass banks that are
mowed only twice a year (early July and half September).
At each location, pollen were sampled for 15 min in the morning
(9–10.30 h), in the early afternoon (12.30–14.00 h) and early evening
(16.30–17.00 h) during one day in the week. The Pollensniffer was
hand-held by a standing person, resulting in a measuring height of ap-
proximately 1 to 1.20 m. For the street level measurements Pollensniffer
PS1 was used. The day varied depending on the weather; especially dry,
sunny days were selected for measurements unless this was not possi-
ble. At each location weather parameters like temperature, wind
speed and rain were recorded.
In the static sampler as well as in the Pollensniffer, the pollen grains
were collected on a Melinex strip covered with Vaseline. The strip was
stainedbysafranin(0.002%w/v) solution and mounted on a micro-
scopic slide (Galán et al., 2014).
For the daily pollen concentrations the microscopic slides from the
static sampler (rooftop level counts) were scanned in three longitudinal
bands corresponding to 1 m
3
collected air in 24 h, to obtain daily pollen
concentrations (grains/m
3
,24h)(de Weger et al., 2013;Galán et al.,
2017). On the strips of the Pollensniffer, all pollen collected were micro-
scopically differentially counted.
For the validation experiments, the start and the end of each mea-
surement with the static sampler was marked on the Vaseline strip. In
contrast to the analysis of daily pollen concentrations where defined
areas are being counted, in this analysis all pollen present on the strip
between these marks were counted. So in the validation experiment
all pollen collected on the tape in the static sampler were compared to
all pollen collected on the tape in the Pollensniffer. For the validation
3L.A. de Weger et al. / Science of the Total Environment 741 (2020) 140404
experiments, the results obtained from the Pollensniffer samples and
the static sampler were expressed as pollen counts and not as pollen
concentrations, since the counts were not related to the sample volume.
The samplevolume is dependent on the flow rate of the device and we
could not use the same device to measure the flow rate in the static
sampler and the Pollensniffer since the inlets are different. Furthermore,
Fig. 2. a. Map of the city of Leiden showing the location ofthe roof top level static sampler and the locations of the street level measurements. b. The three locations of the street level
measurements, City Center, Huigpark and Kweeklust.
4L.A. de Weger et al. / Science of the Total Environment 741 (2020) 140404
Oteros et al. (Oteros et al., 2017) showed that there is a large variation in
flow rates measured in routinely used Hirst type samplers. Since we
used different devices and comparing flow rates was not possible due
to technical restrictions, we carefully standardized sample collection
by using a strict protocol concerning duration and time of collection,
height at which pollen were collected, and position of collection by
directing the inlet of the Pollensniffer facing the current wind direction.
Subsequently all pollen present in the sample were microscopically
counted and compared.
An overview of the different experiments is provided in Table S1.
2.4. Analysis of data
For the analysis of the validation experiments a correlation analysis
was performed to assess the strength of the relationship between the
pollen collected by the Pollensniffer and the static pollen sampler.
Since a Shapiro-Wilk test showed that neither the original nor the log-
transformed pollen data of both samplers were normally distributed,
Spearman's correlation coefficient was used. Differences and correla-
tions were considered statistically significant at pb.05. For the calcula-
tion of the average difference between the pollen collected by the
Pollensniffer and the static sampler, a regression analysis was per-
formed using the counts of all individual pollen types.
For the comparison of the 5 individual Pollensniffers the mean and
standard deviations of the 8 measurements were calculated. A one
way analysis of variance (ANOVA) was performed on the log trans-
formed data, since the log transformed data of this experiment were
normally distributed according to the Shapiro-Wilk test.
For the comparison between rooftop level and street level measure-
ments, the daily concentrations of the static sampler were compared to
the sum of the street level measurements of the three locations in the
morning, the early afternoon and the early evening (the sum of 9 mea-
surements per day). In order to compare the timing of the first seasonal
pollen collected by the roof top static sampler and of the first seasonal
pollen collected by Pollensniffer at street level, we compared the day
at which more than 3 grains/m
3
were collected by the static sampler
and when more than 3 grains were collected by the Pollensniffer. This
is an arbitrary threshold with the rationale that 1 or 2 pollen can be co-
incidental and a count of 4 pollen or more is more robust.
All statistical analyses were performed using the statistical software
package STATA 14.2 (StataCorp, TX, USA).
3. Results
3.1. General use of the Pollensniffer
The air flow through the Pollensniffers appeared to be very stable
during the operating time of the power bank (5–6 h). Using an elec-
tronic air flow sensor, the air flow was measured in 5 individual
Pollensniffers (Supplement Table S2.) The air flow appeared to depend
on the shape of sample holder used. The sample holder was slightly
modified in Pollensniffers PS2-PS5 resulting in an increase in air flow
through the device from 7.5 l/min to 8.3–9.2 l/min.
The user-friendliness of the Pollensniffer was evaluated by a panel of
volunteers in the northern part of the Netherlands. None of participants
considered the Pollensniffer was complicated; 81% said it was easy to
learn how to use the Pollensniffer and 50% indicated they would like
to use the Pollensniffer more often. The major concerns on the
Pollensniffer were related to the noise produced during operation (too
much; 50% of participants), the size (too large; 14%) and the weight
(too heavy; 28%).
3.2. Validation of the Pollensniffer in comparison to the static sampler
When the Pollensniffer PS1 was mounted on top of the rain cover of
the static sampler, the number of pollen grains collected by the
Fig. 3. Scatterplotsof the pollen counts per hourof different pollenspecies from the staticsampler and thePollensniffer.For presentationpurposes the countswere log transformed.In each
plot Spearman's correlation coefficient (SCC) between the counts of different pollen types collected by the two samplers are shown. All correlation coefficients are significant (pb.05).
5L.A. de Weger et al. / Science of the Total Environment 741 (2020) 140404
Pollensniffer and the static sampler correlated significantly for all pollen
types analysed (Fig. 3). For most types the Spearman's correlation coef-
ficient was strong (N0.8) but for Cupressaceae, Salix and Corylus, this
was moderate (0.64–0.75). This experiment showed that for all types
the Pollensniffer collected more pollen grains than the static sampler.
To assess the magnitude of the difference between the two samplers,
a regression analysis between the pollen counts by the Pollensniffer
(PS) and by the static sampler (BU) was performed. This resulted in
the equation: PS = 5.766 BU + 2.721 (R
2
= 0.788). This regression
equation indicates that the counts of the Pollensniffer are on average
5.8 times per hour higher than those in the static sampler.
Validation of the 5 individual Pollensniffers.
Five individual Pollensniffers (PS1-PS5) were placed on the same
roof as the static sampler and were set up to collect eight 1 h-samples,
each at the same time. The individual Pollensniffers (PS2-PS5) were
comparedto the validated Pollensniffer PS1. The Spearman's correlation
coefficients between the pollen counts of the Pollensniffers PS2-PS5 and
Pollensniffer PS1 were all significant (pb.05) and higher than 0.80.
(Supplement Fig. S3). The percentage standard deviation of the mean
values of the measurements with these five Pollensniffers varied be-
tween 9.3 and 27.4% resulting in a 15.5% average variability (Supple-
ment Table S3). A one way analysis of variance (ANOVA) showed that
the pollen collected by the different Pollensniffers did not significantly
differ[(F55,47) = 0.93, p=.601)].
Grass and birch pollen collected at different locations.
At three locations in the city of Leiden pollen were collected for
15 min using the Pollensniffer in the morning, the early afternoon and
the early evening. Concerning the variation in pollen counts (dynamics)
during the day and the variation in number of pollen counts at large,
similar results were observed for the three location on most days, al-
though there are some notable differences. The peak values for birch
pollen at the three locations were reached on the same monitoring
day, but the number of pollen collected at these three locations varied
notably on that day (Fig. 4a and b) i.e. in week 15, 2017 102 birch pollen
grains (square rooted value [RV] 10.1) in Kweeklust, 28 pollen grains
(RV 5.3) in the City Center and 39 pollen grains (RV 6.2) in Huigpark.
In 2018, these values were much higher; e.g. on April 18th (week 16)
2338 pollen grains (RV 48.4) in Huigpark and 556 (RV 23.6) in
Kweeklust and 312 (RV 17.6) in the City Center. This large difference
in peak values between the years was also reflected in the annual pollen
integral of the rooftop birch pollen, which amounted to 4398 pollen
day/m
3
in 2018 compared to only 995 in 2017. Strikingly, in the City
Center without any birch trees in the street or close by, the pollen counts
were in the same range as collected in the parks, although as mentioned
before, the highest numbers of pollen were collected in the parks.
Also for grass pollen (Fig. 4c and d) the levels were similar in the City
Center to those in the parks although again the peak values were
reached in the parks: 174 in 2017 in the Huigpark week 22 (June 2nd)
and 209 in 2018 in Kweeklust week 23 (June 6th).
For grass pollen counts, the variations between the three locations
were observed more frequently than for birch pollen; e.g. in 2017,
week 22, a high number of grass pollen was collected in the Huigpark
(174) in the morning with low numbers in Kweeklust (33). In the
early evening it was the other way around: high numbers in Kweeklust
(105) and low numbers in Huigpark (39). In contrast to birch pollen,
peak values for grasses were not reached in the same week on the var-
ious locations: the Huigpark reached its peak value (178) in week 22
(June 1st) and Kweeklust (peak value 209) in week 23 (June 6th),
which was 5 days apart.
During rain periods the number of birch or grass pollen that were
collected at street level were usually low (see arrows in Fig. 4).
Comparison between street level and rooftop level pollen counts
in time.
For a comparison between the rooftop level and street level pollen,
we compared the daily pollen concentrations measured by the static
sampler on the roof of the LUMC (as pollen/m
3
) with the sum of the
pollen collected at three 15-min periods of the day and from three loca-
tions in the city (sum of 9 measurements). Fig. 5 shows that the pollen
counts at street level follow at large the rooftop level pollen concentra-
tions: on days with high pollen concentrations measured at rooftop
level also the street level pollen counts are high and vice versa. Never-
theless, exceptions can be found: e.g. April 12th 2017 (week 15)
shows high street level birchpollen counts while the rooftop concentra-
tions were low (Figs. 4aand5a).
We studied the timing of the first pollen grains to be collected at
rooftop level and street level for birch pollen and grass pollen. In 2017,
this could not be studied for birch since the birch pollen season was al-
ready started before our series of measurements took off. In 2018, the
first significant (≥4) number of birch pollen grains was collected on
March 26th (19 birch pollen, see asterisk in Fig. 5b), while at rooftop
the pollen concentration reached a significant level (≥4 pollen grains/
m
3
) on April 6th (6 pollen grains/m
3
). So at street level birch pollen
are detected 11 days earlier than on rooftop level (Fig. 5b).
For grass pollen at rooftop level (week 18) 7 pollen/m
3
were re-
corded on April 30th 2017, while at street level 18 days earlier: 15 pol-
len were collected on April 12th (week 15) (see asterisk in Fig. 5c). In
2018, the first significant number of pollen were collected at rooftop
level on May 2nd (4 pollen/ m
3
, 24 h), while 19 days earlier (13th
April, week 15) 5 pollen were collected at street level (see the asterisk
in Fig. 5d). This indicates that birch pollen and grass pollen can be de-
tected at street level 1 1/2 weeks and 2–3 weeks, respectively, earlier
than at rooftop level.
4. Discussion
Here we describe the developmentand validation of a portable sam-
pler, called Pollensniffer, which can be used to collect pollen in the di-
rect environment of patients. In this study we have used the
Pollensniffer to monitor grass and birch pollen grains present at street
level in the city of Leiden and we show large differences in quantities
between the three locations on different days and during the day. We
also show that birch pollen and grass pollen are present 1 1/
2–3 weeks earlier at street level (approximately 1 to 1.20 m)compared
to rooftop level (22 m), which is the monitoring height for daily pollen
monitoring with the static sampler.
First the Pollensniffer was validated in an experimental set up where
the Pollensniffer was mounted on top of the rain cover of the static sam-
pler. We showed that for most pollen types, the number collected by the
Pollensniffer and the static sampler correlated significantly. The
Pollensniffer appeared to be very efficient, since it collected on average
5.8 times more pollen per hour than the static sampler. An explanation
for the high efficiency of the Pollensniffer compared to the static sam-
pler might be found in the shape of the inlet. A pollen grain passing in
an air streamline just above the inlet of the static sampler may not be
drawn into the static sampler, while the wider conical inlet of the
Pollensniffer may still collect this pollen grain.
Several devices for personalized allergen measurements have been
described (Fiorina et al., 1997;Peel et al., 2014b;Renstrom et al.,
2002;Werchan et al., 2018;Yamamoto et al., 2007)buttheuser-
friendliness and the efficacy of these devices varies. Therefore, we de-
veloped the portable Pollensniffer in such a way that it can be carried,
and, if required, can also be mounted onto the steering wheel of a bicy-
cle, which will be described in another paper. Furthermore, the easily
replaceable power bank generates a constant flow which can be main-
tained for 5–6 h. The measurements were performed with theinlet fac-
ing the current wind direction. This is a relevant instruction since this
will help to generate a good flow into the sampler.
We asked 15 volunteers to evaluate our Pollensniffers, and the ma-
jority (81%) thought it was an easy-to-use device, which they would
like to use more often (50%). The test panel suggested some improve-
ments: (i) to reduce the noise during use (50%); (ii) to reduce the size
6L.A. de Weger et al. / Science of the Total Environment 741 (2020) 140404
(14%); and (iii) to reduce the weight (28%). These suggestions will be
used when a next generation of Pollensniffers will be produced.
The pollen collected by the Pollensniffer and the static sampler at the
same location correlate significantly and for most types the correlation
is strong (SCC N0.8). For Corylus, Cupressaceae and Salix this correlation
was moderate (SCC =0.64, 0.74, resp.). For Corylus, the pollen counts in
the static sampler were very low (b0–7 pollen) (Fig. 3) which will affect
the correlation. Molina et al. (Molina et al., 2010) found in a similar ex-
perimentalso a low correlation for Cupressaceae pollenbetween a per-
sonal sampler and a continuous sampler (both from Burkard). The
lower correlation for Cupressaceae and Salix might be caused by the
fact that both these grains form clumps (Cupressaceae especially
when they are broken) more often than other pollen types. These
clumps may introduce a bias in the counts.
Comparison of five individual Pollensniffers shows that the number
of pollen collected bythe 5 devices are strongly correlated (Supplement
Fig. S3). Furthermore, the average standard deviation between the mea-
surements with the five Pollensniffers was 15.5%, which is comparable
to the variation reported in 3 Hirst-type samplers placed 5 m apart, i.e.
20% of the pollen count (Buters et al., 2015). This shows that, although
the measurements of the flow through the devices may slightly differ
among the Pollensniffers, their performance in pollen collection is
similar.
The first use of the Pollensniffers was to study the distribution of
grass and birch pollen in the environment of the patients and we choose
three locations at street level in the city of Leiden. One location in the
shopping street (City Center), one in a park within the boundaries
formed by the canals (Huigpark) and one more at the border of the
city (Kweeklust). The total daily pollen counts for birch and grasses fol-
low the pollen concentrations measured by the static sampler at rooftop
level, although exceptions occur e.g. April 12th 2017 (week 15) with
high pollen counts at street level and low pollen concentrations at roof-
top level. Higher birchpollen counts at street level may be caused by the
fact that in a 500 m circle around all three locations birch trees are pres-
ent. When these treesare blooming their pollen may be dispersed better
at street level and collected less at rooftop level.
The peak values for both birch and grass pollen were recorded in the
parks, but on most days the pollen counts were in the same order of
magnitude for the City Center and the parks, which may be striking
for the City Center location since in this shopping street no grasses or
birch trees were present. Only a few birch trees or well-maintained
grass areas were present within a circle of 500 m. This indicates that
birch and grass pollen can disperse very well within a city.
For birch trees, the temporal differences between the three locations
are very similar, although the number of pollen collected at the various
sites can differ markedly (Figs. 4a and b). The most striking differences
Fig. 4. Pollencounts in 2017 and 2018 at the different locations in the city of Leiden: City Center, Huigparkand Kweeklust. The numbers 123 indicatemorning (1), early afternoon (2) and
early evening (3). The numbers 14–26 indicate the week number of the measurement. Arrows indicate the incidence of rain during the pollen collection. For presentation purposes the
birch pollen counts are rooted. Note that scale of the vertical axes is different. Figs. 4a and b represent birch pollen counts and Figs. 4c and d grass pollen.
7L.A. de Weger et al. / Science of the Total Environment 741 (2020) 140404
are found between the parks; there are days with very high pollen
counts in one park and much lower pollen counts at the other 2 loca-
tions (Fig. 4a, week 15, 2017 and Fig. 4b, week 16, 2018). In 2017,
highest values of birch pollen were collected in Kweeklust, while in
2018 the highest values were collected in Huigpark. This may be due
to the fact that we only collected pollen one day in the week. Maybe
in 2017, most birch trees in Kweeklust were ready to bloom on the col-
lection day, while in 2018 the day of collection may have been the
blooming day of most birches near Huigpark.
Also for grasses the temporal differences are similar for the different
locations, althoughthe three locations showmore variation in time than
the birch pollen. Pollen counts can be high in Kweeklust and low in
Huigpark, but the other week it can be the other way around (Fig. 4d,
week 22 and 23). Or pollen counts are increasing during the day in
Kweeklust and decreasing in Huigpark during the day (e.g. Fig. 4c,
week 22). These marked differences in pollen counts between the loca-
tions may be caused by the fact that different grass species are present
near the Huigpark and Kweeklust, which may cause different dynamics
in pollen production. Another explanation may be that the mowing re-
gime differs among the different regions. Large differences in grass pol-
len distribution within a city has also been described by others (Hjort
et al., 2016;Skjøth et al., 2013). The grass pollen will be produced by
local urban sources, but since in the surroundings of Leiden also rural
and recreation areas are present, it cannot be excluded that also these
areas could be a source for the grass pollen detected in the city. How-
ever, several recent studies on street level measurements indicate that
mainly local sources affect the pollen levels in the city domain and
that during intense flowering the grass pollen level is a local scale phe-
nomenon (Skjøth et al., 2013;Werchan et al., 2017).
These differences in pollen levels within a city may explain in part
the diversity in symptom severity among allergic patients and it will
hamper the development of accurate local p ollen forecasts. It will be im-
possible with currenttechniques to take these local differences into ac-
count for pollen forecasts, but knowledge about the uneven dispersion
of pollen in a city is relevant (Werchan et al., 2017).
The daily pollen monitoring takes place at rooftop level which is jus-
tified since the measurements should give an overview of the airborne
pollen types within a larger area. These rooftop level measurements
are used in most countries to inform the patients on the current pollen
levels. We donot question the relevance of these data, however it is also
important to know how these rooftop pollen concentrations relate to
the pollen counts at street level. This study shows that at street level
birch pollen was collected 1 1/2 week and grass pollen 2–3 weeks be-
fore those pollen types were collected at rooftop level.
In 1991, Rantio-Lethimäki was the first to describe that detection of
grass pollen at street level occurs 2 weeks earlier than rooftop level
(Rantio-Lehtimäki et al., 1991). Bastl et al. found a longer duration of
the grass pollen season at street level compared to rooftop level (29
and 34 days in 2015 and 2016, respectively; (Bastl et al., 2019)). These
results indicate that patients may be affected by the pollenbefore pollen
are detected by the samplers at rooftop level. The pollen collected at the
street level locations in the early season were quite low (see results),
Fig. 5. At rooftoplevel daily pollen concentrationswere monitored duringthe whole year (blue line).At street level the pollen weremonitored once a week on variable days and theyare
shown as the sum of the collected pollen at the tree locations during the morning, early afternoon and early evening (red bars). Green triangles indicate the day at which a street level
measurement was performed. Asterisks indicate days with more than 4 pollen collected at streetlevel before pollen are detected at rooftop levelby the static sampler. Figs. 5a and b
represent birch pollen in 2017 and 2018 respectively. The street level counts of 2018 are rooted for presentation purposes. Figs. 5c and d represent grass pollen in 2017 and 2018
respectively. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
8L.A. de Weger et al. / Science of the Total Environment 741 (2020) 140404
but we have to realize that pollen were collected during only 15 min at
each location. Nevertheless, patients for instance going by bike or on
foot to work or doing exercise in the parksthat stay out for a longer pe-
riod, may inhale sufficient pollen to develop symptoms. Allergic pa-
tients report to their physician or allergist that they experience
symptoms before the pollen are reported by the daily pollen concentra-
tions (Pfaar et al., 2017)
5. Conclusions
A new portable pollen sampler, called Pollensniffer, has been devel-
oped, validated against the static pollen sampler and which is approxi-
mately 5–6 times more efficient in collecting pollen. This Pollensniffer
has been used to monitor birch and grass pollen at street level. The pol-
len levels correlate well with the pollen levels at rooftop, but there can
be large differences in pollen levels in a city between different locations
and different 15-minute periods during the day. Furthermore, at the
start of the birch and the grass pollen season, pollen were collected 1
1/2 to 2–3 weeks respectively earlier at street level compared to rooftop
level, explaining why patients can have symptoms before the pollen
season officially has started as defined by pollen counts in the rooftop
sampler.
CRediT authorship contribution statement
Letty A. de Weger:Conceptualization, Methodology, Formal analysis,
Writing - original draft, Writing - review & editing.Frank Molster:Writ-
ing - review & editing, Conceptualization. Kevin de Raat:Investigation,
Writing - review & editing.Jeffrey den Haan:Investigation, Writing - re-
view & editing.Johan Romein:Writing - review & editing, Conceptuali-
zation. Willem van Leeuwen:Conceptualization, Supervision, Writing
- review & editing.Hans de Groot:Conceptualization, Writing - review
& editing.Marijke Mostert:Conceptualization, Supervision, Project ad-
ministration, Writing - review & editing.Pieter S. Hiemstra:Conceptual-
ization, Supervision, Writing - review & editing.
Declaration of competing interest
The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influ-
ence the work reported in this paper.
Acknowledgements
The study was supported in part by a grant from Generade (grant
2016002D12) and from Taskforce for Applied Research (RAAK
PUB03.045), and the testing of the Pollensniffers on Festivalderaa was
supported by an Innofest grant. Wewould like to acknowledge the help
of Dennis Hengst, Martijn Tenge,en Stefan Elfering for their work on the
development of the Pollensniffer, Sam Luijben and Raheel Gill for tech-
nical assistance and pollen sampling. Roel Schellandfor his support dur-
ing the grant application, and Kenji Miki from Kyoto University, Kyoto
for advising us on the aerobiological properties of the Pollensniffer.
We thank Emiel Hilgersom from the Leiden Municipality for the infor-
mation on the birch tree species and the maintenance of roadsides
and meadows.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.
org/10.1016/j.scitotenv.2020.140404.
References
Bastl, M., Bastl, K., Karatzas, K., Aleksic, M., Zetter, R., et al., 2019. The evaluation of pollen
concentrations withstatistical and computationalmethods on rooftop andon ground
level in Vienna –how to include daily crowd-sourced symptom data. World Allergy
Org. J. 12, 100036.
Blomme, K., Tomassen, P., Lapeere, H., Huvenne, W.,Bonny, M., et al., 2013. Prevalence of
allergic sensitization versus allergic rhinitis symptoms in an unselected population.
Int. Arch. Allergy Immunol. 160, 200–207.
Bousquet, J., Neukirch, F., Bousquet, P.J., Gehano, P., Klossek, J.M., et al.,2006. Severity and
impairment of allergic rhinitis in patients consulting in primary care. J. Allergy Clin.
Immunol. 117, 158–162.
Bousquet, J., Khaltaev, N., Cruz, A.A., Denburg,J., Fokkens, W.J., etal., 2008. Allergic rhinitis
and its impact on asthma (ARIA) 2008 update (in collaboration with the World
Health Organization, GA(2)LEN and AllerGen). Allergy 63 (Suppl. 86), 88–160.
Buters, J., Prank, M., Sofiev, M., Pusch, G., Albertini, R., et al.,2015. Variation of the group 5
grass pollen allergencontent of airborne pollen in relation to geographic location and
time in season. J. Allergy Clin. Immunol. 136, 87–95.e86.
Buters, J.T.M., Antunes, C., Galveias, A., Bergmann, K.C., Thibaudon, M., et al., 2018. Pollen
and spore monitoring in the world. Clin Transl Allergy 8, 9.
Colas, C., Brosa, M., Anton, E., Montoro, J., Navarro, A., et al., 2017. Estimate of the total
costs of allergic rhinitis in specialized care based on real-world data: the FERIN
study. Allergy 72, 959–966.
de Weger, L.A., Beerthuizen, T., Hiemstra, P.S., Sont, J.K., 2013. Development and valida-
tion of a 5-day-ahead hay fever forecast for patients with grass-pollen-induced aller-
gic rhinitis. Int. J. Biometeorol. 58, 1047–1055.
Fiorina, A., Scordamaglia, A., Mincarini, M., Fregonese, L., Canonica, G.W., 1997.
Aerobiologic particlesampling by a new personalcollector (PartrapFA52) in compar-
ison to the Hirst (Burkard) sampler. Allergy 52, 1026–1030.
Fiorina, A., Scordamaglia, A., Fumagalli, F., Canonica, G.W., Passalacqua, G., 2003. Aerobio-
logical diagnosis of respiratory allergy by a personal sampler: two case reports. J
Investig Allergol Clin Immunol 13, 284–285.
Galán, C., Smith, M., Thibaudon, M., Frenguelli, G., Oteros, J., et al., 2014. Pollen monitoring:
minimum requirements and reproducibility of analysis. Aerobiologia 30, 385–395.
Galán, C.,Ariatti, A., Bonini,M., Clot, B., Crouzy,B., et al., 2017. Recommended terminology
for aerobiological studies. Aerobiologia 33, 293–295.
Hirst, J.M., 1952. An automatic volumetric spore trap. Ann. Appl. Biol. 39, 257–265.
Hjort, J., Hugg, T.T., Antikainen, H., Rusanen, J., Sofiev, M., et al., 2016. Fine-scale exposure
to allergenic pollen in the urban environment: evaluation of land use regression ap-
proach. Environ. Health Perspect. 124, 619–626.
Ishibashi, Y., Ohno, H., Oh-ishi, S., Matsuoka, T., Kizaki, T., et al.,2008. Characterization of
pollen dispersion in the neighborhood of Tokyo, Japan in the springof 2005 and 2006.
Int. J. Environ. Res. Public Health 5, 76–85.
Katz, D.S.W., Carey, T.S., 2014. Heterogeneity in ragweed pollen exposure is determined
by plant composition at small spatial scales. Sci. Total Environ. 485–486, 435–440.
Maurer, M., Zuberbier, T., 2007. Undertreatment of rhinitis symptoms in Europe: findings
from a cross-sectional questionnaire survey. Allergy 62, 1057–1063.
Molina, R.T., Palacios, I.S., Garijo, Á.G., Muñoz Rodríguez, A.F., Rodríguez, S.F., et al., 2010.
Use of personal sporetraps to complement continuous aerobiological monitoring.
Grana 49, 134–141.
Oteros, J., Buters, J., Laven, G., Röseler, S., Wachter, R., et al., 2017. Errors in determining
the flow rate of Hirst-type pollen traps. Aerobiologia 33, 201–210.
Peel, R.G., Hertel, O., Smith, M., Kennedy, R., 2013. Personal exposure to grass pollen: re-
lating inhaled dose to background concentration. Ann.Allergy Asthma Immunol.111,
548–554.
Peel, R.G., Kennedy, R., Smith, M., Hertel, O., 2014a. Do urban canyons influence street
level grass pollen concentrations? Int. J. Biometeorol. 58, 1317–1325.
Peel,R.G.,Kennedy,R.,Smith,M.,Hertel,O.,2014b.Relative efficiencies of the Burkard 7-
day, Rotorod and Burkardpersonal samplersfor Poaceae and Urticaceae pollenunder
field conditions. Ann Agric Environ Med 21, 745–752.
Pfaar, O., Bastl, K., Berger, U., Buters, J., Calderon, M.A., et al., 2017. Defining pollen expo-
sure times for clinical trials of allergen immunotherapy for pollen-induced
rhinoconjunctivitis –an EAACI position paper. Allergy 72, 713–722.
Rantio-Lehtimäki,A.,Koivikko,A.,Kupias,R.,Mäkinen,Y.,Pohjola,A.,1991.Significance of
sampling height of airborne particles for aerobiological information. Allergy 46, 68–76.
Renstrom, A., Karlsson, A.S., Tovey, E., 2002. Nasal air samplingused for the assessment of
occupational allergen exposure and the efficacy of respiratory protection. Clin. Exp.
Allergy 32, 1769–1775.
Rojo, J., Oteros, J., Perez-Badia, R., Cervigon, P., Ferencova, Z., et al., 2019. Near-ground ef-
fect of height on pollen exposure. Environ. Res. 174, 160–169.
Skjøth, C., Ørby, P.V., Becker, T., Geels, C., Schlünssen, V., et al., 2013. Identifying urban
sources as cause of elevated grass pollen concentrations using GIS and remote sens-
ing. Biogeosciences 10, 541–554.
Spieksma, F.T.M., van Noort, P., Nikkels, H., 2000. Influence of nearby stands of Artemisia
on street-level versus roof-top-level ratio’s of airborne pollen quantities. Aerobiologia
16, 21–24.
Werchan, B., Werchan, M., Mucke, H.G.,Gauger, U., Simoleit, A., et al., 2017. Spatial distri-
bution of allergenic pollen through a large metropolitan area. Environ. Monit. Assess.
189, 169.
Werchan, M., Sehlinger, T., Goergen, F., Bergmann, K.-C., 2018. The pollator: a personal
pollen sampling device. Allergo J. Int. 27, 1–3.
Yamamoto,N., Matsuki, H., Yanagisawa, Y., 2007. Application of the personal aeroallergen
sampler to assess personal exposures to Japanese cedar and cypress pollens. J Expo.
Sci. Environ. Epidemiol. 17, 637–643.
Yamamoto, N., Matsuki, Y., Yokoyama, H., Matsuki, H., 2015. Relationships among indoor,
outdoor,and personal airborne Japanesecedar pollen counts.PLoS One 10, e0131710.
9L.A. de Weger et al. / Science of the Total Environment 741 (2020) 140404
