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Abstract

Ice nucleating particles (INPs) in the atmosphere are necessary to generate ice crystals in mixed-phase clouds, a crucial component for precipitation development. The sources and composition of INPs are varied: from mineral dust derived from continental erosion to bioaerosols resulting from bubble bursting at the ocean surface. The performance of a home-built droplet freezing assay (DFA) device for quantifying the ice nucleating abilities of water samples via immersion freezing has been validated against both published results and analyses of samples from sea surface microlayer (SML) and bulk surface water (BSW) from the Gulf of Mexico (GoM) and Saanich Inlet, off Vancouver Island (VI), Canada. Even in the absence of phytoplankton blooms, all the samples contained INPs at moderate concentrations, ranging from 6.0x10^1 to 1.1x10^5 L-1 water. The freezing temperatures (i.e., T50, the temperature at which 50% of the droplets freeze) of the samples decreased in order of VI SML > GoM BSW > GoM SML, indicating that the higher latitude coastal waters have a greater potential to initiate cloud formation and precipitation.
© 2022 Universidad Nacional Autónoma de México, Instituto de Ciencias de la Atmósfera y Cambio Climático.
This is an open access article under the CC BY-NC License (http://creativecommons.org/licenses/by-nc/4.0/).
Atmósfera 35(1), 127-141 (2022)
https://doi.org/10.20937/ATM.52938
The UNAM-droplet freezing assay: An evaluation of the ice nucleating
capacity of the sea-surface microlayer and surface mixed layer in tropical
and subpolar waters
Luis A. LADINO1*, Javier JUARÉZ-PÉREZ1, Zyanya RAMÍREZ-DÍAZ1,2, Lisa A. MILLER3, Jorge HERRERA4,
Graciela B. RAGA1, Kyle G. SIMPSON3, Giuliana CRUZ3, Diana L. PEREIRA1 and Fernanda CÓRDOBA1
1Instituto de Ciencias de la Atmósfera y Cambio Climático, Universidad Nacional Autónoma de México, Ciudad de
México, México.
2Department of Geosciences, Texas Tech University, Lubbock, Texas, USA.
3Centre for Ocean Climate Chemistry, Institute of Ocean Sciences, Fisheries and Oceans Canada, Sidney, British
Columbia, Canada.
4Departamento de Recursos del Mar, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico
Nacional, 97310 Mérida, Yucatán, México.
*Corresponding author; email: luis.ladino@atmosfera.unam.mx
Received: June 30, 2020; accepted: October 8, 2020
RESUMEN
Los núcleos de glaciación (INP, por su sigla en inglés) presentes en la atmósfera intervienen en la formación de
cristales de hielo, los cuales son indispensables para el desarrollo de precipitación en nubes mixtas. Las fuentes
y la composición de los INP son muy variadas: desde el polvo mineral derivado de la erosión de los suelos en
los continentes hasta el bioaerosol emitido en la supercie del océano. El dispositivo denominado ensayo de
congelación de gotas (DFA) se construyó recientemente para cuanticar la eciencia de nucleación de hielo en
muestras líquidas mediante la congelación por inmersión. Su funcionamiento se validó comparando los resultados
con reportes en la literatura y con los análisis de muestras de la microcapa supercial del océano (SML) y de
muestras obtenidas a 1 m de profundidad (BSW) en el Golfo de México (GoM) y en Saanich, frente a la Isla
de Vancouver (VI), Canadá. Todas las muestras analizadas contenían INP en concentraciones moderadas, entre
6.0 × 101 y 1.1 × 105 L–1 de agua, incluso en ausencia de oraciones de toplancton. Se estimó la temperatura a
la cual se congela el 50% de las gotas (T50) en cada una de las muestras. El valor de T50 fue mayor en muestras
de VI SML, seguido por muestras del GoM BSW y del GoM SML, lo que indica que las aguas costeras en
latitudes altas tienen un mayor potencial para iniciar la formación de nubes y precipitación.
ABSTRACT
Ice nucleating particles (INPs) in the atmosphere are necessary to generate ice crystals in mixed-phase clouds,
a crucial component for precipitation development. The sources and composition of INPs are varied: from
mineral dust derived from continental erosion to bioaerosols resulting from bubble bursting at the ocean
surface. The performance of a home-built droplet freezing assay (DFA) device for quantifying the ice nu-
cleating abilities of water samples via immersion freezing has been validated against both published results
and analyses of samples from sea surface microlayer (SML) and bulk surface water (BSW) from the Gulf of
Mexico (GoM) and Saanich Inlet, off Vancouver Island (VI), Canada. Even in the absence of phytoplankton
blooms, all the samples contained INPs at moderate concentrations, ranging from 6.0 × 101 to 1.1 × 105 L–1
water. The freezing temperatures (i.e., T50, the temperature at which 50% of the droplets freeze) of the samples
decreased in order of VI SML > GoM BSW > GoM SML, indicating that the higher-latitude coastal waters
have a greater potential to initiate cloud formation and precipitation.
Keywords: sea surface microlayer, ice nucleation, Gulf of Mexico, mixed-phase clouds, droplet freezing assay.
128 L. A. Ladino et al.
1. Introduction
Two thirds of the Earth’s surface is covered by
oceans, providing a well-known source of aerosol
particles that have the potential to nucleate cloud
droplets and ice crystals, inuencing cloud albedo
and precipitation, and hence, climate. Although
marine aerosol particles are ubiquitous in the atmo-
sphere, their physical and chemical properties are
poorly understood (Bigg and Leck, 2001; Heint-
zenberg et al., 2004; Gantt and Meskhidze, 2013).
The major components of primary marine aerosol
are inorganic sea salt and organic matter. The latter
can be cellular (e.g., bacteria, phytoplankton, and
diatoms) and extracellular (e.g., exopolymeric sub-
stances; EPS) (Yoon et al., 2007; Vignati et al., 2010).
While organic matter is highly concentrated in the
sea surface microlayer (SML), the sea salt content is
rather constant for a few meters below the surface.
Sea salt particles are injected into the atmosphere
together with marine organic matter by sea spray as a
result of bubble bursting and wave activity (Facchini
et al., 2008; Gantt and Meskhidze, 2013). Vignati
et al. (2010) estimated the global sea salt emissions
to be 24 Tg year–1, whereas the sub-micron organic
matter emissions from sea spray were found to be
8.2 Tg year–1.
Marine aerosol particles can inuence mixed-
phase and cirrus cloud formation because a fraction
of them are able to act as ice nucleating particles
(INPs), facilitating ice crystal formation via different
heterogeneous ice nucleation pathways (e.g., Bigg,
1973; Schnell and Vali, 1975; Schnell, 1975, 1977,
1982; Rosinski et al., 1987, 1988; Mason et al.,
2015; DeMott et al., 2016; McCluskey et al., 2017,
2018; Welti et al., 2018; Creamean et al., 2018; Si
et al., 2018; Ladino et al., 2019; Gong et al., 2020).
As summarized by Burrows et al. (2013), marine
microorganisms, EPS aggregates, glassy organics,
and crystalline hydrated NaCl are types of aerosol
particles that have the potential to nucleate ice in
marine environments. However, whether the marine
INPs are dominated by a specic aerosol type, and
under what conditions, remains unclear due to the
limited number of eld and laboratory studies (Kanji
et al., 2017).
Recent studies have addressed some of the
aforementioned gaps in knowledge. For example,
laboratory studies have shown that crystalline salts
(e.g., Instant Ocean and NaCl), organic matter (e.g.,
amorphous sucrose), and a variety of marine mi-
croorganisms (e.g., Nanochloris atomus, Emiliania
huxleyi, Vibrio harveyi, and Prochlorococcus) can
efciently nucleate ice via deposition nucleation at
temperatures below –40 ºC (e.g., Wise et al., 2012;
Wagner and Mohler, 2013; Schill and Tolbert, 2014;
Ladino et al., 2016; Wolf et al., 2019). At warmer
temperatures, Knopf et al. (2011) and Wilson et al.
(2015) found that the planktonic diatom species
Thalassiosira pseudonana (and their exudates) was
able to efciently nucleate ice via immersion freez-
ing, with freezing temperatures as high as –23 ºC. In
mesocosm studies, Wang et al. (2015) and McClus-
key et al. (2017) found that the concentration of INPs
was signicantly enhanced during a phytoplankton
bloom. The authors suggest that higher INP concen-
trations are linked to the presence of heterotrophic
bacteria and organic species in the sea spray aerosol.
More recently, Tesson and Šantl-Temkiv (2018)
found that the marine aquatic microalgae Polarella
glacialis was able to nucleate ice via immersion
freezing at temperatures close to –6 ºC. As shown by
Creamean et al. (2019), biological INPs in the Arctic
can be emitted into the atmosphere by marine waters
as a result of phytoplankton blooms during summer.
In both Arctic (Wilson et al., 2015; Irish et al., 2017)
and tropical (Gong et al., 2020) waters, INP concen-
trations have been observed to be either enriched and
depleted in the SML in comparison to bulk surface
water (BSW) samples, likely dependent on complex
interactions between biological, oceanographic, and
meteorological conditions.
Burrows et al. (2013) and Yun and Penner (2013)
used global climate models to investigate the po-
tential impacts of marine aerosol on the Earth’s
radiative balance and the hydrological cycle. Both
studies predicted a signicant inuence of marine
organic aerosol (MOA) on cloud properties in the
Southern Ocean, remote from terrestrial aerosol
sources. In remote areas, MOA could also contrib-
ute to the INP concentration signicantly where the
presence of mineral dust is limited, as is the case
for continental biological aerosol (Pratt et al., 2009;
Prenni et al., 2009; Pöschl et al., 2010). Recent
studies by Wilson et al. (2015), Vergara-Temprado
et al. (2017), and McCluskey et al. (2019) reached
similar conclusions.
129
The UNAM-droplet freezing assay
Burrows et al. (2013) and Yun and Penner (2013)
mentioned the urgent need to conduct eld studies in
marine environments as well as laboratory studies,
using marine aerosol particles to reduce uncertainties
in global climate predictions. Most notably, there is
a limited number of experimental studies focusing
on INPs from airborne particles and SML waters in
tropical latitudes. Therefore, the currently available
parametrizations to model marine INPs may under-
estimate the role that marine tropical oceans play in
the global distribution of INPs.
With the aim to contribute to the understanding of
the ice nucleating properties of the marine aerosol in
tropical latitudes, a device to quantify the ice nucle-
ating abilities from different types of aerosol samples
has been constructed by the Micro and Mesoscale
Interactions Group at the Instituto de Ciencias de la
Atmósfera y Cambio Climático of the Universidad
Nacional Autónoma de México (UNAM). Samples
collected from the SML and BSW in the Gulf of
Mexico (GoM) and Saanich Inlet (Vancouver Island,
Canada), were analyzed using the new device.
2. Methods
2.1 Sampling locations
Two different sampling locations were chosen for this
study: (i) Saanich Inlet, off Vancouver Island (VI), Can-
ada; and (ii) the southern GoM. Sampling at VI took
place in Patricia Bay (48º 39’ N, 123º 28’ W) as shown
in Figure 1a. SML samples (ca. 25 mL) were collected
on two different days (March 21 and 22, 2018) and at
three different stations using a glass plate (section 2.2).
The sampling locations (A, B, and C in Fig. 1a) were
approximately 1 km apart, with location A about 1 km
from the dock at the Institute of Ocean Sciences. The
samples were collected in triplicate and kept frozen
(ca. –4 ºC) while transported from Canada to Mexico.
Sampling in the GoM took place at Dzilam de
Bravo (21º 23’ N, 88º 52’ W) on the Yucatan Penin-
sula (Fig. 1b) as part of the African Dust and Biomass
Burning Over Yucatan (ADABBOY) project. Dzilam
de Bravo is 107 km away from Merida (the capital and
most populated city in the Yucatan state) and 79 km
from Progreso (one of the largest harbors in the state).
Samples from the SML and BSW were collected (in
triplicate) on April 17, 2018 at 10 different stations,
separated by 1 km as shown in Figure 1b. A cold front
affected the region on April 17, and therefore wave
activity was signicant in comparison to previous
days and also in comparison to conditions in the
protected bay off VI. The samples were kept frozen
(ca. –4 ºC) while transported to Mexico City.
A total of 48 SML and 10 BSW samples were
collected as summarized in Table I. At each sampling
station, both at VI and in the GoM, the sea surface
temperature (SST), and the salinity were measured
with a YSI 85 multiparameter probe.
a
b
Mexico
Patricia
Bay
Canada
Sidney
Sidney
Institute of Ocean
Sciences
B
CA
Mexico
2
3
4
1
Dzilam de Bravo
5
6
7
8
9
10
Fig. 1. Sampling sites: (a) at Saanich Inlet, Vancouver
Island (VI), and (b) Dzilam de Bravo, Gulf of Mexico
(GoM) (Google Earth, 2019). At both locations, individual
stations were separated by approximately 1 km.
Table I. Summary of the SML and BSW samples collected
in the Gulf of Mexico and off Vancouver Island.
Collected samples
Gulf of Mexico Vancouver Island
SML: 30 BSW: 10 SML: 18
130 L. A. Ladino et al.
2.2 Sampling methods
A glass plate, an old and simple but very useful tool to
collect SML samples, was used in this study (Harvey
and Burzell, 1972; Cunliffe and Wurl, 2014). We used
a 30 × 20 cm plate of tempered glass with a thickness
of 4 mm (Fig. 2a). To collect a sample from the SML,
the glass plate (previously rinsed at least three times
with deionized water on both sides) was vertically
immersed into the sea surface and then lifted slowly
at a constant rate (Cunliffe and Wurl, 2014). As the
glass plate was lifted, the SML adhered to it, so it
was removed from the glass plate with the help of a
neoprene squeegee as shown in Figure 2b. The SML
samples were collected in high-density polyethylene
(HDPE) amber bottles and stored at –20 ºC prior
to their analysis. Note that the temperature of the
samples was –4 ºC during their transport to Mexico
City, where the DFA analysis were performed. The
thickness of the collected SML (h in mm) can be
calculated following Eq. (1) from Cunliffe and Wurl
(2014):
h
=104
V
A·N
(1)
where V is the sample volume in cm3, A the total area
of the immersed glass plate in cm2 (i.e., the area of
both sides), and N the number of dips per sample
(dimensionless). BSW samples were only collected
in the GoM (Fig. 2c) at a depth of approximately 1 m
using a Niskin bottle (Seabird Coastal).
2.3 The UNAM-droplet freezing assay (UNAM-
DFA)
The droplet freezing assay (DFA) has been widely
used to study the ice nucleating abilities of different
aerosol types (Vali and Stansbury, 1966; Vali, 1971;
Lindow, 1983; Conen et al., 2011; Attard et al., 2012;
Wright and Petters, 2013; Stopelli et al., 2014; Hill
et al., 2014; Budke and Koop, 2015; Whale et al.,
2015; David et al., 2019). This method specically
studies the immersion freezing mode, which has been
recognized as the most important pathway to form ice
crystals in mixed-phase clouds (Murray et al., 2012).
Ice formation via immersion freezing occurs when a
liquid droplet with an aerosol immersed is exposed
to decreasing temperatures. As a consequence of the
lower temperature, an ice germ forms at the surface
of the aerosol particle causing the droplet to freeze
(Murray et al., 2012; Kanji et al., 2017). The UN-
AM-DFA (Fig. 3) is based on the design by David et
al. (2019) and consists of: (i) a thermostat (LAUDA
PRO-RP 1090) lled with polydimethylsiloxane as
recirculating-cooling liquid; (ii) an aluminum sample
holder to support the V-bottom Enzyme-Linked Im-
munosorbent Assay (ELISA) plate (Corning 3896);
(iii) a light-emitting diode (LED) system, and (iv) a
video camera (ATVIO, HD 1080P, WDV800SA) to
record the freezing experiments.
Using an eight-tip micropipette (EPPENDORF
300), 50 µL of sample (i.e., SML or BSW) were
transferred into each of the 96 wells of a sterile
ab c
SML
SSW
30 cm
20 cm
In Out
Fig. 2. (a) Glass plate used in the present study, (b) sea surface microlayer (SML) sample collection
procedure, and (c) bulk surface water (BSW) sample collection procedure.
131
The UNAM-droplet freezing assay
ELISA plate (Fig. 3a). The plate was then covered
with a transparent lm to seal the plate and to avoid
any interaction between the sample and the ambient
laboratory air. The 50 µL in each well corresponds
to the volume of a liquid drop with a diameter of ca.
4.4 mm. The loaded ELISA plate was placed into the
cooling bath where the temperature decreased from 0
to –40 ºC at a cooling rate of 2.66 ºC min–1 (Fig. 3c).
While the temperature decreased, the freezing of
each well was monitored and recorded with the video
camera. The freezing of each well was determined
by the change in its opacity while transitioning from
liquid to solid (Fig. 4). The temperature was assumed
to be the same in all of the 96 wells at a given time
during the temperature ramp and was recorded from
the thermostat with an uncertainty of ± 0.01 ºC.
Given that the volume of the polydimethylsiloxane
decreases as a function of temperature due to thermal
contraction, the depth of the ELISA plates was man-
ually controlled with the help of adjustable screws on
either side of the metallic support (Fig. 3b).
A video and a le of the temperature as a function
of time were obtained from each experiment. The
frozen fraction (f) at 1 ºC intervals was obtained
combining both information sources following
Eq. (2):
f =
N
f
N
(2)
where Nf is the number of frozen droplets at a specic
temperature and N the total droplets of the ELISA
Fig. 3. Diagram showing the main components of the UNAM-droplet freezing assay (UN-
AM-DFA). (a) Sample preparation; (b) sample holder, Enzyme-Linked Immunosorbent
Assay (ELISA) plate, video camera arrangement, and (c) cross section view of the full setup.
(a)
ELISA plate
12
11
10
9
8
7
6
5
4
3
2
1
ABCDEF
ELISA plate
Cooling bath
(LAUDA, PRO RP 1090)
ELISA plate
–15,41°C
LAUDA ECO SILVER
–35,00°C Tset
2
Polydimethylsiloxane
LED lamp
light
Camera
Metallic
support
Adjustable
screws
Micropipette
Adjustable
screws
(b) (c)
Tint
Fig. 4. Example of an Enzyme-Linked Immunosorbent
Assay (ELISA) plate with liquid (red circles) and frozen
(yellow circles) wells differentiated according to their
appearance.
132 L. A. Ladino et al.
plate (i.e., 96). The cumulative INP concentration
(L–1) is derived following Eq. (3) (Yadav et al., 2019):
C
INP (T) =
–ln (F
uf
)
Vdrop
(3)
where Fuf is the fraction of unfrozen droplets (di-
mensionless) at temperature T (ºC), and Vdrop is the
drop volume (L).
3. Results and discussion
3.1 UNAM-DFA performance
We performed homogeneous freezing experiments
with MilliQ water (18.2 MΩ cm) to assess the per-
formance and limits of the UNAM-DFA. As shown in
Figure 5a, the homogeneous freezing curve obtained
with the UNAM-DFA is close to the one reported
by Tobo (2016). However, the liquid droplets from
the present results were found to freeze at lower
temperatures than those found in previous studies
(e.g., Whale et al., 2015; Irish et al., 2017; Yadav et
al., 2019). The variability between the homogeneous
freezing curves shown in Figure 5a is not surprising
given that the spontaneous freezing of liquid droplets
is inuenced by its size, the cooling rate, and the
details of the method used (i.e., suspended droplets
vs. droplets placed on cold stages), among other
factors. The homogeneous freezing curve serves as
a zero. Any freezing event at higher temperatures is
attributed to the presence of impurities, such as aero-
sol ice nucleating particles (INPs), immersed in the
droplets and categorized as heterogeneous freezing.
Arizona Test Dust (ATD) was utilized in a sec-
ondary experiment to further assess the performance
of the UNAM-DFA. ATD can be considered a proxy
for natural mineral dust and its ice nucleating abilities
in different ice nucleation modes are well known
(Kanji et al., 2008; Kanji and Abbatt, 2010; Welti et
al., 2009; DeMott et al., 2011; Niemand et al., 2012;
Hader et al., 2014; Steinke et al., 2015; Yadav et
al., 2019). An aqueous solution of 0.1% w/w ATD
(ISO 12103-1; Powder Technology, Inc; A1 ultraf-
ine) in MilliQ water was prepared and analyzed in
the UNAM-DFA. Figure 5b shows the relationship
between INP concentration (in the form of ATD
particles) and freezing temperature. Although the
INP concentrations in our samples were lower than
those observed by Yadav et al. (2019), the trend with
freezing temperature in both data sets is consistent.
The small difference found in the concentration range
where these two studies overlap can be attributed to
the grain size of the ATD, i.e., ultrane (A1) in the
present study versus coarse (A4) used by Yadav et
al. (2019).
1
0.9
106
105
104
103
102
Irish et al. (2017)
Tobo et al. (2016)
Whale et al. (2015)
Yadav et al. (2019)
Hom. Fre. (run 1)
Hom. Fre. (run 2)
Hom. Fre. (run 3)
Hom. Fre. (run 4)
UNAM-DFA
Yadav et al. (2019)
Standard deviation
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
–40 –35 –30 –25 –20
INP concentrations (L–1)
–15 –10 –5 –25 –20 –15
Temperature (°C)
–10
Fig. 5. (a) Homogeneous freezing activation curves, and (b) ice nucleating particles
(INP) concentration calculated for Arizona Test Dust (ATD) samples. The error bars
are the representative average variability associated to the homogeneous freezing
experiments.
133
The UNAM-droplet freezing assay
3.2 Ice nucleating properties of the SML: Gulf of
Mexico vs. Vancouver Island
Figure 6 shows an intercomparison of the frozen frac-
tion of the SML samples collected off VI and in the
GoM within 3 km of shore. The two sets of samples
are clearly distinguishable, with the GoM samples
closer to the homogeneous freezing line. Therefore,
the SML samples from VI were more efcient at nu-
cleating ice. Note that the variability between stations
in the ice nucleating abilities of the SML samples
from the GoM is greater than those from VI. While
the activation curves of the VI samples range from
–9.5 to –18.5 ºC, the GoM samples vary from –21.5
to –35.5 ºC. This is consistent with the VI stations
being conned to a relatively enclosed inlet, whereas
the GoM stations extended more directly away from
the coast into open water.
Another way to quantify the ice nucleating ability
of a given sample is by the temperature at which
50% of the droplets freeze, denoted as T50. Figure 7a
shows that the median T50 values for the VI and GoM
SML samples were –13.5 and –28.7 ºC, respective-
ly. Therefore, both the activation scans and the T50
clearly show that the SML samples from VI were
signicantly more efcient at nucleating ice than
those collected in the GoM.
Given that the same person collected the sam-
ples and that the instrumentation used to collect
the samples and to analyze them were identical, the
differences observed in the results are likely related
to the different characteristics of the composition of
the SML in the GoM and the mid-latitude Saanich
Inlet. Table II shows that the average salinity and sea
surface temperature (SST) measured in the GoM are
signicantly higher than those measured at VI. The
lower salinity in the waters off VI is a direct result
of the high volumes of river waters delivered to the
ocean in that area. Irish et al. (2019) also found higher
INP concentrations associated with riverine waters in
the Arctic Ocean. While crystalline sea salt particles
are very inefcient INPs, via immersion freezing,
due to their high solubility (e.g., Kanji et al., 2017),
organic aerosol particles of marine origin have been
shown to be efcient INPs (e.g., Schnell, 1975;
Wilson et al., 2015; DeMott et al., 2016; Irish et al.,
2017; Creamean et al., 2018; Gong et al., 2020). Van
de Poll et al. (2013) showed how lower SST values
positively correlate with the availability of nutrients
required for marine production. They found that low-
er SST values are linked with higher chlorophyll-a.
Figure 7 shows that the T50 values in our samples
were inversely related to the SST measured at each
sampling site.
3.3 Ice nucleating capacity of the Gulf of Mexico
samples: SML vs. BSW
Given that SML and BSW samples were collected at
each of the 10 sampling stations in the GoM, it was
Temperature (°C)
-40 –35 –30 –25 –20–15 –10–
50
Frozen Fraction
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
GoM, 1 km
GoM, 2 km
GoM, 3 km
VI, 1 km
VI, 2 km
VI, 3 km
Hom. Fre. (run 1)
Hom. Fre. (run 2)
Hom. Fre. (run 3)
Hom. Fre. (run 4)
Fig. 6. Frozen fraction curves for the sea surface microlayer (SML) samples collected
in the Gulf of Mexico (greenish lines) and off Vancouver Island (reddish lines). The
black symbols denote the homogeneous freezing curves, and the error bars are the
representative average variability (Fig. 5).
134 L. A. Ladino et al.
possible to conduct a direct comparison of the ice nucle-
ating abilities of these two types of samples. Figure 8a
shows that the BSW samples were more efcient
at nucleating ice as their freezing temperatures are
closer to 0 ºC. This is also shown by the T50 values,
where the BSW samples had higher T50 values than
the SML samples by 4.2 ºC (Fig. 8b).
Although the present results are in agreement with
those reported by Irish et al. (2017) from SML and
BSW samples collected in the Arctic, Wilson et al.
(2015), Chance et al. (2018), Irish et al. (2019), and
Zeppenfeld et al. (2019) found higher ice nucleation
efciencies in the SML in comparison to deeper wa-
ters. More recently, Gong et al. (2020) reported the
absence of a clear trend between the INP concentra-
tions in the SML and BSW samples collected off Cape
Verde, in the Atlantic Ocean (at 16-24º N). Organic
matter and hence INPs can be concentrated in the
SML. As mentioned above, during the sampling in
the GoM a cold front affected the region. This caused the
generation of medium to strong waves, which can
enhance organic matter enrichment in the SML
(Cunliffe et al., 2013). Additionally, as highlighted
by Irish et al. (2017) and Wurl and Obbard (2004),
the SML sampling method can play an important role
in the thickness of the collected SML and therefore
in its observed physicochemical properties. Note that
in Irish et al. (2017) and in the present study, a glass
–10
–15
–20
T50(°C)
–25
–30
Gulf of Mexico Vancouver Isand
a
26
24
22
18
SST (°C)
14
10
Gulf of Mexico Vancouver Isand
b
8
12
16
20
Fig. 7. Box plots for (a) T50 values of the Gulf of Mexico (GoM) and Vancouver Island (VI)
sea surface microlayer (SML) samples within 3 km of shore, and (b) the sea surface tem-
perature (SST) measured in the GoM and off VI. Ten GoM and six VI observations were used
to build each panel. The top and bottom limits of each box are the 25th and 75th percentiles of
the samples, respectively. The median of the samples is represented by the line in the middle
of each box. The top and bottom whiskers on each box indicate the maximum and minimum
values, respectively.
Table II. Summary of the average physicochemical characteristics of the samples collected* in the Gulf of
Mexico (GoM) and off Vancouver Island (VI).
Variable GoM SD Number of
measurements
VI SD Number of
measurements
Sea Surface temperature (ºC) 25.88 0.03 10 8.74 0.05 6
Salinity (psu) 34.25 7.39 10 27.94 0.13 6
SD; standard deviation.
*Samples from both sites were collected during the local morning.
135
The UNAM-droplet freezing assay
plate was used to collect the SML. On the other hand,
Wilson et al. (2015), Chance et al. (2018), and Irish
et al. (2019) used a rotating drum. Overall, there is a
hint that the sampling method and hence the thick-
ness of the sampled SML can impact the measured
ice nucleating activity. This potential bias deserves
further study.
3.4 Small-scale spatial variability in ice nucleating
activity
The ice nucleating activity of the SML and BSW
samples collected in the GoM was evaluated as a
function of the distance from shore, as shown in
Figure 9. The minimum T50 was observed 2 km from
shore for both the SML and SBW samples. Beyond
3 km, the T50 values for the BSW were relatively
constant (–21.2 ± 0.7 ºC); however, the SML sam-
ples showed a higher variability (–25.2 ± 1.7 ºC).
Therefore, although a small effect of the coast on
the ice nucleating abilities of the SML and BSW
waters was observed, this seems to be very local and
likely caused by different anthropogenic activities at
the coast (e.g., the presence of boats). Although the
T50 values from the BSW samples and the distance
from the shore did not correlate (r = 0.25, p = 0.48),
the T50 values from the SML sample were found to
moderately correlate with the distance from the shore
(r = 0.52); however, the correlation is not statistically
signicant (p = 0.11). It was found that the T50 values
Temperature (°C)
–40 –30 –20 –10 0
Frozen Fraction
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
a
SML
BSW
Hom. Fre. (run 1)
Hom. Fre. (run 2)
Hom. Fre. (run 3)
Hom. Fre. (run 4)
SML BSW
T 50 (ºC)
–30
–28
–26
–24
–22
–20
b
+
Fig. 8. a) Frozen fraction curves for the sea surface microlayer (SML; red lines) and
bulk surface water (BSW; blue lines) samples collected at the Gulf of Mexico, and (b)
box plot of the T50 from the SML and BSW. The error bars in (a) are the representative
average variability associated to the homogeneous freezing experiments. On panel (b),
the tops and bottoms of each box are the 25th and 75th percentiles of the samples, re-
spectively. The median of the samples is represented by the line in the middle of each
box. The top and bottom whiskers on each box indicate the maximum and minimum
values, respectively. The red cross indicates an outlier value.
–18
–20
–22
–24
–26
T
50
(°C)
–28
–30
–32 1234 5
Distance (km)
6789
10
BSW
SML
Fig. 9. T50 values as a function of the distance from shore
for the sea surface microlayer (SML) and bulk surface
water (BSW) samples collected in the Gulf of Mexico.
The error bars depict the representative average variability.
136 L. A. Ladino et al.
of the SML and BSW, as a function of the distance
from the shore, have a good correlation (r = 074, p <
0.05). This indicates that the properties of the SML
and BSW from the GoM may be driven by similar
processes such as water mass characteristics (i.e.,
freshwater fractions) and ecosystem structure.
Although the small-scale (i.e., 10 km) spatial
distribution of the INPs around Dzilam de Bravo
is not constant, the observed variability is not very
large. As shown by Wilson et al. (2015) and Irish et
al. (2017), signicant changes can be found when
samples are collected over large distances, much
larger than 10 km.
3.5 INP concentrations
Using the frozen fractions shown in Figures 6 and
8a and following Eq. (3), the INP concentrations for
the entire data set were calculated and are shown in
Figure 10. Although the INP concentrations of the
VI and the GoM samples are on the same order of
magnitude, the INP activities in the VI samples were
found at much higher temperatures than those of the
GoM samples. The INP concentrations in the VI
SML samples varied from 2.1 × 102 to 9.1 × 104 L–1
water at temperatures ranging from –10.5 to –18.5 ºC.
Likewise, the SML and BSW samples from the
GoM contained INPs in concentrations from 6.0 ×
101 to 1.1 × 105 L–1 water at temperatures below
–16.5 ºC. Although the INP concentrations from the
VI samples are in agreement with those reported by
Wilson et al. (2015) and Irish et al. (2017), the INP
concentrations from the GoM samples are two or
three orders of magnitude lower, possibly because of
the lower overall biological productivity of tropical
versus polar and subpolar waters.
4. Conclusions
A droplet freezing assay device, denoted as UN-
AM-DFA, was built at the Universidad Nacional
Autónoma de México to study mixed-phase cloud
formation via the immersion freezing mode. The re-
sults obtained with the UNAM-DFA are in agreement
with those reported by similar DFAs built elsewhere.
Given the current lack of data on the ice nucleating
abilities of aerosol particles emitted in tropical lati-
tudes, the UNAM-DFA will be very useful to ll the
gaps in the current knowledge of how the oceanic
emissions may impact atmospheric chemistry and
cloud formation.
Samples from the sea-surface microlayer of the
GoM were found to be less efcient (lower T0 and T50
values by 12 ºC and 15 ºC, respectively) at nucleating
ice than comparable samples collected off VI, on the
west coast of Canada. This is likely related to the
physicochemical characteristics, including freshwa-
ter inuences and overall biological productivity, of
the GoM and VI waters. Given that neither the GoM
nor the VI samples were collected under the inuence
of coincident phytoplankton blooms, it would be in-
teresting to collect samples during active blooms in
the GoM (i.e., October-November) to assess whether
the ice nucleating abilities of the SML are higher
under such conditions than those observed here.
The bulk surface waters from the GoM were
found to have higher ice nucleating activities than
the corresponding SML samples, as the T50 values
in the bulk waters were 4.2 ºC higher. Although this
can be considered somewhat unusual, similar results
have also been found in the high Arctic (Irish et al.,
2017). The conditions and processes that lead to en-
richment of ice-nucleating activity in the sea-surface
microlayer deserve further investigation.
Fig. 10. Ice nucleating particles (INP) concentrations as
a function of temperature for the Gulf of Mexico (GoM)
and Vancouver Island (VI) samples.
105
104
103
102
–35 –30 –25 –20
Temperature (°C)
INPs concentration (L–1 water)
–15
GoM SML
GoM BSW
VI SML
–10–
50
137
The UNAM-droplet freezing assay
For the most part, there was not a clear pattern in
the spatial distribution of ice nucleating activity of
the SML and BSW samples either in the GoM or off
VI. However, more information is required to assess
possible causes of the minimum T50 values found 2 km
from shore in the GoM. The good correlation between
the SML T50 and BSW T50 as a function of the distance
from the shore suggests that the properties of both types
of samples may be driven by similar processes such as
water mass characteristics (i.e., freshwater fractions)
and ecosystem structure. It would be interesting to
collect SML and BSW samples out in the open Pacic
Ocean and further into the central GoM to evaluate
whether their ice nucleating abilities differ signicantly
from those found closer to shore.
Finally, the INP concentrations in the GoM (6.0 ×
101 to 1.1 × 105 L-1 water) and VI (2.1 × 102 to 9.1
× 104 L–1 water) samples agreed well with literature
data at different locations, with the exception of the
SML samples from the GoM, which were substan-
tially lower than other observations. The high INP
concentrations found at high temperatures in the VI
samples suggest that these waters have the potential
to signicantly affect mixed-phase cloud formation
on a local scale.
Acknowledgments
The authors thank W. Gutierrez†, M. García, A.
Rodríguez, E. Salinas, and L. Martínez for their
invaluable help. This study was nancially sup-
ported by DGAPA (Dirección General de Asuntos
del Personal Académico) and CONACYT (Consejo
Nacional de Ciencia y Tecnología) through grants
PAPIIT IA108417, PAPIIT IN111120, and FC-2164,
respectively, and by Fisheries and Oceans Canada.
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... More recently, the ice nucleating abilities of particles present in the Arctic sea surface microlayer (Wilson et al., 2015;Irish et al., 2017Irish et al., , 2019 and the Arctic ambient aerosol were evaluated Creamean et al., 2018;Wex et al., 2019). Similar studies were performed over the eastern Mediterranean by Gong et al. (2019), over the Southern Ocean by McCluskey et al. (2018) and Welti et al. (2020), over the North Atlantic by Wilbourn et al. (2020), and over the tropical Atlantic by , Welti et al. (2018), Ladino et al. (2019), Ladino et al. (2020), and Gong et al. (2020a). Welti et al. (2020) presented an analysis of the INP concentrations on ship-based measurements for different zones in the Arctic, Atlantic, Pacific, and Southern oceans. ...
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