Ice-nucleating particles (INPs) initiate ice formation in
supercooled clouds, typically starting in western Europe at a few kilometres above the
ground. However, little is known about the concentration and composition of
INPs in the lower free troposphere (FT). Here, we analysed INPs active at -10∘C (INP-10) and -15 ∘C (INP-15) that were collected
under FT conditions at the high-altitude observatory Jungfraujoch between
January 2019 and March 2021. We relied on continuous radon measurements to
distinguish FT conditions from those influenced by the planetary boundary
layer. Median concentrations in the FT were 2.4 INP-10 m-3 and 9.8 INP-15 m-3, with a multiplicative standard deviation of 2.0 and
1.6 respectively. A majority of INPs were deactivated after exposure to 60 ∘C; thus, they probably originated from certain epiphytic bacteria or
fungi. Subsequent heating to 95 ∘C deactivated another 15 % to
20 % of the initial INPs, which were likely other types of fungal INPs that might have been
associated with soil organic matter or with decaying leaves. Very few
INP-10 withstood heating to 95 ∘C, but on average 20 % of
INP-15 in FT samples did so. This percentage doubled during Saharan
dust intrusions, which had practically no influence on INP-10. Overall,
the results suggest that aerosolised epiphytic microorganisms, or parts
thereof, are responsible for the majority of primary ice formation in
moderately supercooled clouds above western Europe.
Introduction
The free troposphere (FT) refers to a part of the troposphere that is only
occasionally in exchange with the Earth's surface, whereas the planetary
boundary layer (PBL) continuously exchanges particles with surface sources
and sinks. Consequently, the FT integrates particle emissions over a much
larger area compared with the PBL. For example, in the PBL, a community of airborne microorganisms is mainly composed of organisms emitted from sources
within a distance of several tens of kilometres around an observation point
(Tignat-Perrier et al., 2019). In contrast, particle populations sampled at
a high-altitude mountain station under FT conditions constitute a mixture of
many sources and sinks active on a continental scale (Herrmann et al., 2015,
Sun et al., 2021). A special kind of aerosol particle, so-called
ice-nucleating particles (INPs), is relevant for primary ice formation in
mid-level clouds (Findeisen, 1938). Ice formation in clouds above lowlands
in western Europe starts at a few kilometres altitude at around -5 ∘C (Kanitz et al., 2011). However, FT air masses have been little
explored in terms of the INPs that they carry, let alone the INPs active >-15∘C. For recent summaries of INP studies in the FT, see Lacher
et al. (2018) and He et al. (2021). Under FT conditions at the high-altitude
observatory Jungfraujoch (3580 m a.s.l.) in the Swiss Alps, Lacher et al. (2018) found similar concentrations of INPs active at -31 ∘C
(INP-31) as had been reported for the FT in other regions of the world
(summarised in Table 2 and Fig. 6 in Lacher et al., 2018) as well as little
seasonal variation. Later, continuous measurements by Brunner et al. (2021b)
found the monthly median of INP-30 in the FT background to peak in
April and to be lowest in December. Brunner et al. (2021a, b) found that most
INP-30 at Jungfraujoch occurred during Saharan dust intrusions, by far
exceeding any background concentration. However, in the PBL and at more moderate
supercooling (here, ≥-15∘C), biological particles seemed to
constitute the majority of the INP population as revealed by heat tests
(Hill et al., 2016). Heat deactivates biological INPs but leaves mineral INPs
largely unaffected (Hill et al., 2016). During dust
events sampled in Beijing, Chen et al. (2021) found that 70 % of INPs active at ≥-15, ∘C (INP-15) were heat sensitive. Observed heat-sensitive
fractions of INP-15 in the PBL of agricultural areas in the USA
(Suski et al., 2018) and in Argentina (Testa et al., 2021) were even larger
(>90 %). These findings contrast with a small biological
fraction detected among ice particle residuals collected at Jungfraujoch
from mixed-phase clouds and classified by physico-chemical analyses (Mertes
et al., 2007) or by laser ablation mass spectrometry (Schmidt et al., 2017;
Lacher et al., 2021). Not every ice particle residual has initiated as INP
the formation of the ice particle it was recovered from, in particular not
when it was recovered from a secondary ice particle. An ice particle
residual recovered from a primary ice particle and classified by mass
spectrometry as mineral dust may have been activated at moderate
supercooling by a minor, ice nucleation active biological component sticking
to its surface (Augustin-Bauditz et al., 2016). A heat test, which
specifically targets the ice nucleation active component, would have
classified the same assembly as a biological INP.
Aerosolisation of biological particles from vegetated land to the PBL is
intensified during rainfall (Huffman et al. 2013; Prenni et al., 2013; Iwata
et al., 2019). Subsequent transport from the PBL to the FT may happen
through mixing in frontal systems, cloud convection, or by mountain venting
(Henne et al., 2005). Here, we investigate whether biological INPs, as
classified by heat tests, also contribute the majority of the INP population
in the FT. Our objectives were to quantify INPs active at moderate
supercooling in the FT and to narrow down the likely composition of these INPs
and how this composition might change during Saharan dust intrusions (SDIs). We will also compare INP concentrations in the FT with those of air masses influenced by
the PBL as presented in earlier studies.
Material and methodsSampling and analysis
For our investigation, we relied on archived samples of particulate matter
(PM10) collected between January 2019 and March 2021 (Table A1) on
quartz-fibre filters at the high-altitude observatory Jungfraujoch
(07∘59′02′′ E, 46∘32′53′′ N; 3580 m a.s.l.), which is
part of the Swiss national air quality monitoring network. PM10 sampling and INP analysis at the site have been described in previous work (Conen et
al., 2012). Units of air volume throughout this paper are normalised to
standard pressure. Briefly, air was sampled at a rate of 720 m3 d-1 through a heated inlet, followed by a PM10 cut-off, onto a
150 mm diameter quartz-fibre filter (Pallflex Tissuquartz 2500-UP) with a 140 mm diameter of active area. Every day at midnight a new filter was exposed
to the continuous air stream for 24 h. From each selected filter, we took
72 punches with a 2 mm diameter each; all 72 punches together contained
aerosol particles from a total of 10.6 m-3. Each punch was placed into
a 0.5 mL Eppendorf safe-lock tube, and 0.1 mL of ultra-pure water
(Sigma-Aldrich, W4502-1L) was added. The tubes were then immersed in a
cooling bath and exposed to a temperature ramp from -5 to -15 ∘C (0.3 ∘C min-1). After each 1 ∘C
step, the number of frozen tubes was counted by eye, and the cumulative
concentration of INPs was calculated according to Vali (1971). After the
first such freezing assay, the tubes were placed in a water bath
at 60 ∘C for 10 min before the freezing assay was repeated. This was followed
by a second 10 min heat treatment at 95 ∘C and a third freezing
assay. Loss of INPs active <-10 ∘C due to the repeated
freezing is unlikely in this study. Although Polen et al. (2016)
observed some loss of INPs active
>-5∘C throughout five repeated freezing assays, little had changed in INPs active <-5∘C (see Fig. 6 in Polen et al., 2016). A more extensive set of
tests was conducted by Vali (2008) on a soil sample. After 55 refreezing
cycles, an increasingly larger fraction of INPs had been lost above -10 ∘C toward the warmer end of the freezing spectrum, but the
concentration of INPs active <-10∘C had remained
practically the same (Fig. 1c in Vali, 2018).
Probably the largest uncertainty in these assays is related to the often
small number of INPs assessed. The 68 % confidence interval (±1σ) of a determined INP number concentration is roughly proportional
to the square root of the INPs in an assay. In this study, an assay contained
particles collected from 10.6 m3 of air. Hence, a concentration of 1 INP m-3 was represented by a total of 10 or 11 INPs in the assay and is
associated with an uncertainty of around ±0.3 INP m-3 (√11/11×1 INP m-3). Two blank (background) assays were done with
punches from 5 mm wide fringes of sample filters. This part of a filter is
covered by the clamp rings holding it in place during sampling. Thus,
sampled air does not pass through it, and it remains clean. However, some particles may get smeared from the active filter
area onto this narrow fringe during
handling and transport. Consequently, these blank values are a
conservative (upper) estimate of a field blank. Each of these blanks was
composed of punches from four filters. Sample values were corrected for
blank values by subtracting the average of both blanks, which on average was
7 % of a sample value. We calculated by difference the number
concentration of heat-sensitive INPs (INPs active before any heat treatment - INPs active after 60 ∘C treatment) and moderately heat-tolerant
INPs (INPs active after 60 ∘C treatment - INPs active after 95 ∘C treatment). What remained active after the 95 ∘C treatment was termed heat tolerant. In one sample (6 February 2021), the assay was
completely frozen at -15 ∘C and was repeated with smaller punches
(1 mm diameter).
Probability density function of the log-transformed hourly mean radon
concentration observed during the years from 2016 to 2020 at Jungfraujoch (black
line). The sum of two fitted and weighed log-normal distributions (grey
dotted line) closely matches the observed distribution. The fitted
distributions most likely represent the distribution of free tropospheric
air masses (blue continuous line) and that of air masses influenced by the
planetary boundary layer (red line). Ninety percent of the values below the
dashed vertical line belong to the fitted “free troposphere” distribution
(figure adapted from Conen et al., 2021).
Identification of free tropospheric conditions
A key issue in our study is the distinction between FT and PBL-influenced
air masses. For this purpose, we routinely monitor radon (222Rn) at
Jungfraujoch with a dual-loop two-filter detector (Whittlestone and
Zahorowski, 1998). Radon is emitted relatively homogenously in space and
time from land surfaces. Its only sink in the atmosphere is radioactive
decay. Because of its short half-life (3.82 d), the concentration
difference is large between the FT and the PBL, making radon a useful tracer
to discriminate between these two types of air masses (Herrmann et al.,
2015; Chambers et al., 2016). The probability density function of all hourly
mean radon concentrations measured over the past 5 years is well
reproduced by the sum of two log-normal distributions (Fig. 1), most likely
representing FT- and PBL-influenced air masses (Conen et al., 2021, Brunner
et al., 2021a). Although FT conditions prevailed 41.5 % of the time, it
was only on 1 in 13 d in 2019 and 2020 that such conditions applied to every
hour of a full 24 h PM10 sampling period. Here, we consider a
24 h PM10 sampling period as representative of the FT when all 24
values of the hourly mean radon concentration during the sampling period were
below 1.05 Bq m-3. Ninety percent of all values below 1.05 Bq m-3
belong to the distribution representing FT conditions (Fig. 1). Two-thirds
of the FT samples defined that way were collected in the months of January,
February, and March. We selected 28 such samples from
between January 2019 and March 2021 for INP analysis, making sure to have samples from each
month of the year for which they were available. In addition, from the filter archive, we selected
an additional seven samples with high PM10
loads and a yellow-brown (ochre) colour resulting from SDIs
(Collaud Coen et al., 2004) .
Ensemble of 7 d backward trajectories ending at Jungfraujoch
at noon local time on days for which we analysed INPs under free tropospheric
conditions. The trajectories were calculated using the HYSPLIT model (NOAA Air Resources Laboratory;
https://www.ready.noaa.gov/HYSPLIT.php (last access: 30 July 2021).
The median radon concentration in the FT distribution is only 0.28 times
that of the PBL-influenced distribution (Fig. 1); hence, PBL injections in
the FT may have a median age of about 7 d. Thus, the airshed from
which the INPs in FT air masses sampled at Jungfraujoch might have originated is
roughly indicated by 7 d backward trajectories calculated using the
HYSPLIT model (Fig. 2). One trajectory was calculated for each day, ending
at 13:00 UTC at 500 m a.g.l., which is 1500 m a.s.l. for Jungfraujoch in the model surface. The model was run with the following
settings: the meteorology was from the Global Data Assimilation System (GDAS; 1∘, global); the vertical motion calculation
method was model vertical velocity; and the location coordinates were 46∘32′53′′ N, 07∘59′02′′ E.
The INP concentration found in the free troposphere (FT) and during
Saharan dust intrusions (SDIs), categorised according to heat sensitivity.
The median and multiplicative standard deviation are shown. Use of the
multiplicative standard deviation (s*) is appropriate because multiplicative
processes determine the concentration of biological particles in the
atmosphere (Limpert et al., 2001, 2008). It was estimated from the upper
(Q3) and lower (Q1) quartiles of a distribution: s*= (Q3/Q1)0.741
(Limpert et al., 2001). It was not estimated when the lower quartile was
below the detection limit (<0.095 INP m-3). INPs were designated as heat sensitive if they had lost their activity after exposure to 60 ∘C; INPs were termed moderately heat tolerant if they had retained their
activity after exposure to 60 ∘C but had lost it after exposure
to 95 ∘C; and heat-tolerant INPs were those that were still active
after both heat treatments.
Results and discussionConcentration and likely composition of ice-nucleating particles in free
tropospheric air
The observed range of the INP concentration in FT air masses was 1.0 to
5.6 m-3 for INPs active at -10 ∘C (INP-10) and 4.1 to 16.3 m-3 for INPs active at -15 ∘C
(INP-15). These values are within the lower range of INP concentrations
observed in other contexts (Petters and Wright, 2015). The INPs sampled at
Jungfraujoch under FT conditions likely originated from the northern part
of western Europe and from the North Atlantic (Fig. 2). The latter influence was
probably minor. McCluskey et al. (2018) found a mean of 1.1 INP-15 m-3 in pristine marine air masses arriving at the west coast of
Ireland, which was 1/10 of the median that we found at Jungfraujoch. A majority of
INP-10 (83 %) and INP-15 (57 %) species in the FT were heat sensitive
and lost their activity after exposure to a temperature of 60 ∘C (Table 1; for INPs
active at other temperatures between -8 and -15 ∘C,
see Table A3). Possible contributors to this category include the bacteria
Erwinia herbicola (Phelps et al., 1986) and Pseudomonas sp. (Pouleur et al., 1992) as well as heat-sensitive spores of several fungal species (Table 2). These microorganisms
live on plant surfaces from where they, or parts of them, are emitted to the
atmosphere (Lindow et al., 1978; Lindemann et al., 1982; Hirno and Upper,
2000; Huffman et al., 2013). Further potential sources include other fungi,
such as Fusarium graminearum (Vujanovic et al., 2012; Keller et al., 2014) and Puccinia sp. (Morris et al.,
2013). However, we do not know whether these species lose their ice
nucleation activity at 60 ∘C or between 60 and 95 ∘C, as heat stress tests were only done at around 95 ∘C, which is why they are not included in Table 2.
Reported heat sensitivity of INPs active at moderate supercooling.
Indicated is the temperature range in which at least 90 % of a specific
type of INPs active ≥15∘C was found to be deactivated,
although a smaller fraction of the same INPs may already have been
deactivated at a lower temperature. For example, soil particles analysed by
Conen and Yakutin (2018) had lost half of their INP-10 after exposure to 60 ∘C but more than 98 % after exposure to 95 ∘C.
These particles are assigned a deactivation temperature between 60
and 95 ∘C. Note that studies where INPs were found to be
deactivated after a single heat treatment ∼95∘C
are not listed because deactivation might already have happened <60∘C.
TypeDeactivation temperature Reference<60∘C60–95 ∘C>95∘CBacteriaErwinia herbicolaPhelps et al. (1986)Pseudomonas sp.Pouleur et al. (1992)Lysinibacillus sp.Failor et al. (2017)FungiAcremonium implicatumPummer et al. (2015)Isaria farinosaPummer et al. (2015)Fusarium acuminatumKunert et al. (2019)Fusarium langsethiaeKunert et al. (2019)Fusarium armeniacumKunert et al. (2019)Fungal symbiont in lichenKieft (1988)Mortierella alpinaFröhlich-Nowoisky et al. (2015)Fusarium avenaceumPouleur et al. (1992)Others MixedLeaf-derived ice nucleiSchnell and Vali (1973)Soil particlesHill et al. (2016)Soil particlesConen and Yakutin (2018)OrganicPollenDiehl et al. (2002), Pummer et al. (2012)LigninBogler and Borduas-Dedekind (2020)MineralK-feldsparsDaily et al. (2021)MontmorilloniteConen et al. (2011)IlliteO'Sullivan et al. (2015)KaoliniteDaily et al. (2021)
Between 15 % and 20 % of the INPs that we found in the FT were moderately heat
tolerant (deactivated between 60 and 95 ∘C). This
deactivation temperature matches the profile of Mortierella alpina, a saprophytic fungus
associated with decaying leaf litter (Vasebi et al., 2019) and with soil
particles (Fröhlich-Nowoisky et al., 2015; Conen and Yakutin, 2018).
Other potential sources of moderately heat-tolerant INPs include fungal
symbionts in lichen (Kieft, 1988), Fusarium avenaceum (Pouleur et al., 1992), and the other
above-mentioned fungi for which the deactivation temperature is not clearly
defined. The sum of heat-sensitive and moderately heat-sensitive INP-15
in a FT sample was on average 80 % (SD = 9 %) of its
total INP-15 content, which was slightly smaller than the combined fractions of
fungal and bacterial INP-15 (92 %) estimated in a case study over
Amazonia (Patade et al., 2021).
Heat-tolerant INPs (not deactivated at 95 ∘C) constituted a
negligibly small fraction of all INP-10, but they
contributed as much as the moderately heat-tolerant INPs to INP-15. The fraction of heat-tolerant INP-15 should substantially increase during SDIs if mineral dust, in particular K-feldspar, is their main
component (Vergara-Temprado et al., 2017), which is an issue addressed in the next
section.
The effect of Saharan dust intrusions
Mineral dust has by far the largest contribution to INPs activated at
around -30 ∘C at Jungfraujoch (Larcher et al., 2018, 2021;
Brunner et al., 2021a, b). Most INPs in airborne mineral dust are
probably K-feldspars, some of which are already activated at temperatures
above -10 ∘C (Boose et al., 2016; Harrison et al., 2019). Here,
we analysed seven samples collected during SDIs (Appendix Table A1),
but we excluded one sample from further analysis (6 February 2021) in which INPs had
substantially increased at -15 ∘C after each heat treatment. A
similar reaction to heating was previously observed by Boose et al. (2019),
and it was explained by the removal of secondary organic coatings that had masked
ice nucleation active sites before the heat treatment. In the remaining six
samples, the median PM10 concentration was 19 times as large as in FT
samples. Surprisingly, the median concentration of heat-tolerant INP-15
during SDIs was larger by only a factor of 4 compared with the
FT (Table 1). Hence, mineral dust cannot be the main heat-tolerant
INP-15 in the FT, as SDIs, which consist mainly of
mineral dust, would have led to an increase in the heat-tolerant fraction
of INP-15 that is roughly proportional to the increase in dust load.
This assumption is based on the finding that a large fraction of the particle
volume (i.e. mass) during an SDI event at Jungfraujoch falls into the size
range of particles >0.5µm in optical diameter (Schwikowski
et al., 1995), which is a good predictor of atmospheric INP-15 (DeMott
et al., 2010; Mignani et al., 2021). As we found no peak in heat-tolerant
INP-15 during the main pollen season in spring, pollen and pollen
fragments (Diehl et al., 2002; Pummer et al., 2012) are also an unlikely
source of these particles. (Note that Burkart et al. (2021) recently found convincing
evidence that ice nucleation activity in birch pollen is related to a
protein. Therefore, it probably is also heat sensitive, contrarily to
earlier conclusions.) More likely candidates of the heat-tolerant fraction
in the FT include soil organic material, stabilised through bonding to
minerals surfaces against deactivation by heat (Perkins et al., 2020), or
lignin, not necessarily bound to mineral surfaces (Bogler and
Borduas-Dedekind, 2020). Such organic compounds are more abundant in fertile soils in the mid-latitudes compared with desert soils and could explain the
comparatively small effect of SDIs on heat-tolerant INP-15
observed at Jungfraujoch.
Further, the medians of heat-sensitive and of moderately heat-tolerant
INP-15 were a factor of 1.6 and 2.3 larger during SDIs
respectively (Table 1). Their increase may be due to a concurrent influence
of the PBL with all SDIs, as suggested by enhanced radon
concentrations (Table A1). Overall, SDIs and the
associated PBL influence doubled the median concentration of INP-15
and doubled the average fraction of heat-tolerant INP-15 in a sample
but had no discernable effect on the median concentration of INP-10
(Table 1).
Comparison with other studies in the Swiss Alps
Mignani et al. (2021) made a large number of impinger-based INP-15
measurements (n=124, each integrating over 20 min) in February and March
2019 at Weissfluhjoch, a mountain station 145 km east of Jungfraujoch and
at a 909 m lower elevation (2671 m a.s.l.). This station was increasingly influenced by air from the PBL throughout the
day (Wieder et al., 2021). The
median of all observations, excluding those influenced by SDIs (n=11), was
15.5 m-3 (s*=4.0 m-3). This value is about a factor of 2
larger than the median of the four FT samples collected at Jungfraujoch
during the same months, February and March 2019 (8.9 m-3 with a range of 5.5 to 13.0 m-3). A factor of 2 decrease with an increase of
1000 m in altitude has already been observed for INP-8 in Switzerland (Conen
et al., 2017). Similar to the present study, SDIs at Weissfluhjoch
enhanced the median INP-15 concentration by much less than the
concurrent increase in particle number concentration.
The concentration of INP-10 when free tropospheric conditions
prevailed at Jungfraujoch throughout a full day (open squares) and for days
not selected for this criterion (crosses); data are from Conen et al. (2015) (see
Table A2).
A surprising feature of INP-10 in FT samples is their narrow
distribution (1.0 to 5.6 m-3) throughout the year (Fig. 3), which is
in contrast to what we had found earlier at Jungfraujoch for filters not
selected for FT conditions that covered a range of 3 orders of magnitude
(Conen et al., 2015). Those filters were sampled between June 2012 and May
2013 and analysed using the same method described in this study, although without the
heat treatments. Generally, the influence of the PBL on Jungfraujoch is
largest in summer and smallest in winter (Collaud Coen et al., 2011;
Griffith et al., 2014). Hence, if samples are not explicitly selected for FT
conditions, the majority of them will have at least some PBL influence, in
particular during summer (Brunner et al., 2021b). Therefore, the concentration
of INP-10 on filters not selected for FT conditions occasionally
exceeded that of filters selected for FT conditions, in particular during
summer (Fig. 3). However, the opposite was true for winter. Especially
during January and February, the concentration of INP-10 was 1 or 2 orders of magnitude smaller in the randomly selected samples from the year
2013 compared with the FT samples for the years 2019, 2020, and 2021. A
plausible explanation for this difference could be that a
substantially larger fraction of INP-10 had been activated and
deposited before reaching Jungfraujoch in 2013 compared with the later years.
Indeed, mean air temperature during sampling in January and February 2013 at
Jungfraujoch was -16.2 ∘C (SD 5.3 ∘C), which is 6.4 ∘C colder than during sampling in January and February 2019,
2020, and 2021 (-9.8 ∘C; SD 4.6 ∘C). However, high relative humidity and low temperature does not always result in a
particularly low number concentration of INP-10 being recorded at
Jungfraujoch. On 14 March 2021 an exceptionally strong storm from the north-west
passed Jungfraujoch, with gusts of up to 122 km h-1 and a mean daily
wind speed of 51.5 km h-1. Daily mean values of relative humidity and
temperature were 98 % and -18.8 ∘C respectively.
Nevertheless, we found a non-negligible concentration of INP-10 (0.7 m-3) on the PM10 filter from that day. The updraught velocity at
Jungfraujoch can reach a 6 min mean value of 8 m s-1 under
north-westerly wind conditions (Hammer et al., 2014). An INP-10 activated 1350 m
below Jungfraujoch at -10 ∘C would grow for about 3 min ((18.8–10.0 ∘C)/6.5 ∘C km-1/8 m s-1=169 s) into a crystal with a fall velocity of 5 cm s-1
(Fukuta and Takahashi, 1999). As such, it could still enter the heated inlet
of the sampler, which takes in droplets up to a size of about 40 µm
(Weingartner et al., 1999); evaporate; and let the INP-10 pass the
PM10 cut-off and be collected on the filter. At a lower wind speed, the growth
time increases, and activated INP-10 species are more likely to either settle or
become too large to enter the heated inlet, eventually leading to very
low concentrations; this might explain our earlier observations in 2013. In
an increasingly warmer climate, seasonality in the sink term of INPs active
under moderately supercooled conditions above the Alps may fade.
In summary, the results of this study suggest that epiphytic microorganisms
contribute the majority of INPs to ice formation in moderately supercooled
clouds above the northern part of western Europe, whereas the impact of
Saharan dust is negligible at -10 ∘C and still limited at -15 ∘C.
Number concentration of ice-nucleating particles active at -10 ∘C (INP-10) and at -15 ∘C (INP-15) at
Jungfraujoch, determined for free tropospheric conditions and during Saharan
dust intrusions. The same sample material was analysed three times. A first
freezing assay was followed by a heat treatment (10 min at 60 ∘C)
and second freezing assay, followed by a second heat treatment (10 min at 95 ∘C) and a third freezing assay. All steps were carried out in an
uninterrupted operation. Blank values were subtracted from raw measured
values. Three categories of INPs were derived by calculating the difference between the INP number concentration before and after each heat treatment, resulting in
negative values if the INP concentration had increased after a heat
treatment. Meteorological data are from MeteoSwiss, and PM10 data are from
the Swiss National Air Pollution Monitoring Network (NABEL).
DateINP-10 (m-3)INP-15 (m-3)TmeanFraction of hoursRadon PM10(dd.mm.yyyy)with RH >95 %Deactivation temperature (∘C) Deactivation temperature (∘C) MinMaxMean<6060–95>95<6060–95>95(∘C)(Bq m-3)(µg m-3)Free tropospheric conditions 06.01.20191.60.30.05.10.71.1-13.10.000.320.480.390.526.01.20191.10.30.13.81.51.6-11.10.000.200.400.290.705.02.20191.50.20.04.30.10.7-9.60.000.300.620.460.803.03.20193.81.20.110.41.71.3-8.40.040.300.820.540.908.03.20192.30.80.16.62.63.6-13.80.040.450.860.660.827.03.20191.20.20.03.9-0.21.3-8.70.000.220.480.341.307.05.20192.20.10.16.31.82.0-7.70.000.370.920.581.914.05.20192.90.30.27.01.85.6-70.000.291.010.512.303.09.20192.61.60.05.62.91.61.30.000.350.750.481.412.09.20191.71.40.03.13.64.31.20.130.210.990.481.116.10.20193.31.10.05.32.22.1-4.90.130.430.690.560.628.12.20193.30.30.17.31.32.0-70.000.430.940.640.730.12.20191.60.40.02.90.11.1-2.40.000.381.010.680.405.01.20201.70.50.17.50.11.2-7.50.000.260.780.430.514.01.20204.00.60.010.51.41.0-6.10.000.540.840.681.116.02.20204.20.60.28.91.32.0-0.90.000.230.660.490.820.02.20204.90.70.011.41.63.3-10.10.000.190.510.341.710.03.20201.40.10.17.40.31.4-8.40.080.160.960.452.602.05.20200.70.30.01.91.61.0-8.80.000.481.040.790.503.05.20203.90.50.09.83.03.4-9.20.040.220.880.500.907.07.20202.42.20.13.96.16.30.30.000.501.000.731.331.10.20201.80.30.24.92.51.8-0.90.000.480.980.660.701.11.20201.70.50.26.82.60.6-1.30.420.260.640.460.622.11.20200.90.50.04.40.90.7-2.30.000.310.960.560.722.12.20202.2-0.10.05.50.11.8-70.000.150.350.220.419.01.20214.10.00.012.8-0.11.6-130.000.340.640.491.614.02.20210.70.20.15.70.90.9-170.000.300.620.400.514.03.20210.50.50.11.52.30.4-18.80.830.570.900.751.7Saharan dust intrusions 25.01.20202.4-0.10.55.71.02.1-11.00.002.104.993.0120.803.02.20201.50.90.14.51.95.1-5.90.001.172.311.688.721.03.20204.80.30.113.95.19.4-8.80.001.245.032.7116.522.03.20201.20.20.013.09.95.6-9.20.000.465.143.609.608.11.20202.3-0.10.012.71.56.8-4.30.001.374.062.3613.806.02.20211.51.20.4-25.1-37.8116.0-7.20.001.153.912.47147.103.03.20210.40.50.1-0.26.812.4-7.10.001.252.401.5861.5
Number concentration of ice-nucleating particles active at -10 ∘C (INP-10) at Jungfraujoch, determined from randomly selected
PM10 filter samples. Each sample was collected throughout a full
calender day, for which the local mean air temperature and the fraction of hours
with relative humidity above 95 % are shown. The INP data are from the
study by Conen et al. (2015), and meteorological data are from MeteoSwiss.
Assays of INPs that showed no freezing at all at -10 ∘C were set
to a value of 0.01 INP-10 m-3 to be displayable on the
log scale in Fig. 2.
DateINP-10TmeanFraction of hoursDateINP-10TmeanFraction of hours(dd.mm.yyyy)(m-3)(∘C)with RH >95 %(dd.mm.yyyy)(m-3)(∘C)with RH >95 %06.06.20122.23-1.70.1704.12.20121.00-16.60.0813.06.20120.78-8.10.5407.12.20120.36-18.10.0016.06.20126.432.20.0008.12.20120.43-21.10.0023.06.20123.611.20.0014.12.20120.50-9.90.0027.06.20128.781.70.1724.12.20120.50-3.70.0030.06.20126.944.40.0828.12.20123.19-13.70.4203.07.201219.501.70.2501.01.20130.71-10.70.2108.07.20128.780.70.0811.01.20130.57-16.20.0411.07.20123.73-1.10.0419.01.20130.09-9.50.0413.07.20124.07-0.90.1720.01.20130.03-11.90.1316.07.20122.05-50.2522.01.20130.01-18.80.0028.07.201215.3820.1726.01.20130.01-14.20.0001.08.20125.503.20.1701.02.20130.92-9.50.5403.08.201220.741.80.0006.02.20130.85-21.30.9610.08.20122.60-0.80.1709.02.20130.03-26.80.5415.08.20125.9530.1711.02.20130.16-17.40.0018.08.20123.957.40.0021.02.20130.01-200.1320.08.20126.105.80.1326.02.20130.01-180.0003.09.20124.55-0.90.2104.03.20130.93-10.60.0015.09.20122.140.60.0006.03.20130.10-10.80.2519.09.20121.80-70.7513.03.20130.23-15.50.0021.09.20121.39-0.90.0414.03.20130.36-25.41.0025.09.201212.03-3.90.1318.03.20130.10-16.30.0030.09.20124.68-2.90.7931.03.20130.30-17.90.0004.10.20122.32-4.40.2910.04.20130.78-11.80.0011.10.20122.05-4.30.0411.04.20130.50-6.30.0012.10.20123.29-6.10.2914.04.20131.16-2.30.0016.10.20120.64-80.0019.04.20132.79-7.60.4623.10.20122.141.80.0023.04.20130.36-4.50.0028.10.20120.03-16.50.0029.04.20130.43-4.10.9202.11.20123.51-10.60.0005.05.20131.88-5.90.0010.11.20129.02-7.10.5817.05.20130.86-5.20.5013.11.20121.88-4.30.0022.05.20130.03-9.10.0014.11.201211.31-20.0025.05.20130.50-15.50.6721.11.20120.23-5.80.0028.05.20131.80-70.6326.11.20120.86-6.90.6329.05.20130.30-12.40.33
Median number concentration of ice-nucleating particles
active between -8 and -15∘C at Jungfraujoch,
determined for free tropospheric conditions and during Saharan dust
intrusions, and the average of two assays with blank filter material. The blank
values have been subtracted from the sample values before calculating the
medians shown in the table.
Temperature (∘C)-8-9-10-11-12-13-14-15CategoryINPs in the free troposphere (m-3)All0.81.72.43.44.46.08.79.8Heat sensitive0.61.42.02.53.44.14.95.6Moderately heat tolerant0.30.30.40.50.60.91.21.5Heat tolerant0.00.00.00.20.30.50.91.6CategoryINPs in Saharan dust intrusions (m-3)All0.61.32.43.25.17.813.420.0Heat sensitive0.51.01.92.74.55.16.99.2Moderately heat tolerant0.30.20.20.20.71.01.93.5Heat tolerant0.00.00.10.30.51.13.36.2CategoryINPs in blank filter material (m-3)All0.00.00.10.10.20.30.40.6Heat sensitive0.00.00.00.00.00.20.20.2Moderately heat tolerant0.00.00.10.10.10.00.00.1Heat tolerant0.00.00.00.00.00.10.10.4Data availability
All data used in this paper are given in Tables A1, A2, and A3 in the Appendix.
Author contributions
FC and CM conceived the study. CH organised the particle collection and
provided the samples, and AE carried out the freezing assays. FC prepared the paper
with contribution from all co-authors.
Competing interests
The contact author has declared that neither they nor their co-authors have any competing interests.
Disclaimer
Publisher’s note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Acknowledgements
We thank the International Foundation of the High Altitude Research Stations
Jungfraujoch and Gornergrat (HFSJG), 3012 Bern, Switzerland, for making it
possible for us to work and to operate instruments at the high-altitude
observatory Jungfraujoch. We thank Claudia Zellweger and Stefan Reimann at Empa for helping us with the selection of PM10 filter
samples and for generously sending sections of them to Basel. We are
grateful to Alastair Williams and his group at Australian Nuclear Science and Technology Organisation (ANSTO) for the ongoing collaboration as the supplier and supporter of the radon detection system.
The radon observations are supported by the Swiss National Science
Foundation (SNSF) as a contribution to the pan-European Integrated Carbon
Observation System (ICOS; https://www.icos-ri.eu, last access: 2 August 2021). The authors acknowledge MeteoSwiss, for the uncomplicated provision of meteorological data through its data portal IDAweb, and the Air Resources Laboratory at NOAA, for providing access to its HYSPLIT model.
Financial support
This study was done with in-house means. We have not received funding specifically dedicated to this study. The support from SNSF as a contribution to ICOS, as mentioned in the acknowledgements, satisfies the demands ICOS makes to users of its open-access data.
Review statement
This paper was edited by Allan Bertram and reviewed by two anonymous referees.
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