Size-Resolved Atmospheric Ice Nucleating Particles during East Asian Dust Events

. Asian dust is an important source of atmospheric ice nucleating particles (INPs). However, the freezing activity of airborne Asian dust, especially its sensitivity to particle size, is poorly understood. In this study we report the first INP measurement of size-resolved airborne mineral dust collected during East Asian dust events. The measured total INP concentrations in the immersion mode ranged from 10 -2 to 10 2 L -1 in dust events at temperatures between -25 and -5 ℃. The average contributions of heat-sensitive INPs at three temperatures, -10, -15, and -20 ℃, were 81 ± 12%, 70 ± 15%, and 38 ± 15 21%, respectively, suggesting that proteinaceous biological materials have a substantial effect on the ice nucleation properties of Asian atmospheric mineral dust at warm temperatures. The dust particles which originated from China’s northwest deserts are more efficient INPs compared to those from northern regions. There was no significant difference in the ice nucleation properties between East Asian dust particles and other regions in the world. An explicit size dependence of both INP concentration and surface ice active density was observed. The nucleation efficiency of dust particles increased with increasing 20 particle size, while the INP concentration first increased rapidly and then levelled, due to the significant decrease in the number concentration of larger particles. A new set of parameterizations for INP activity based on size-resolved nucleation properties of Asian mineral dust particles were developed over an extended temperature range (-35 ~ -6 ℃). These size-dependent parameterizations require only particle size distributions as input, and Uniform Deposit Impactor (MOUDI, MSP Corporation, USA). An 8-stage inertia impactor (Model 100-R) was used to collect size-resolved aerosol samples during dust events in the spring of 2018 and 2019. Size-resolved 90 stages from 1 to 8 of the MOUDI with cut-points ( 𝐷 50 ) ranging from 10 to 0.18 μm in aerodynamic diameters, at a flow rate of 30 L min -1 were detected in this study (Marple et al., 1991). The sizes of collected particles in a given stage are set in a size bin, which is presented as the cut-point ( 𝐷 50 ) in the following text. For example, most of the particles with an aerodynamic diameter less than 10 μm and larger than 5.6 μm will be collected on stage 𝐷 50 = 5.6 𝜇𝑚 , therefore the size range between 5.6 and 10 μm will be presented here as cut-point 𝐷 50 = 5.6 𝜇𝑚 . Fourteen sets of MOUDI samples were collected: 8 in 2018, and 95


Introduction 25
Ice formation in tropospheric clouds significantly impacts the microphysical processes and lifetime of clouds, thereby determining radiative forcing, precipitation, and the hydrological cycle (Lohmann and Feichter, 2005;Boucher et al., 2014;Lohmann et al., 2016). Mineral dust particles can act as ice nucleating particles (INPs) that trigger heterogeneous ice nucleation at relatively high temperatures and low relative humidities by efficiently lowering the energy barrier to form the critical ice embryo (Pruppacher and Klett, 1997). Up to 2000 Tg of mineral dust are emitted from arid and semiarid areas into where is the total volume of sampled air per droplet converted to standard conditions (0 ℃ and 1013 hPa) during each particle collection period. To quantify and compare the ice nucleation activity of different size samples, the cumulative ice 125 nucleation active site density (Connolly et al., 2009;Hoose and Mohler, 2012;Niemand et al., 2012), i.e., the number of active sites per unit surface area of INPs (Vali et al., 2015), is converted from the INP concentration and calculated using: where is the total surface area of the particles per unit volume of sampled air per droplet, based on the particulate matter information derived from size distribution measurements of the particles (see Section 2.3 below).
The uncertainty of the experimental results arises mainly from the representativeness of testing droplets for the total suspension. 130 The population number of INPs present in the washing suspension is usually small, and the number of examined droplets is limited (90 droplets). Therefore, confidence intervals for the number of ice nucleating particles per unit sample volume (per droplet) should be considered. Using O'Sullivan's method (O'Sullivan et al., 2018;Barker, 2002), the confidence intervals are calculated in Eq. (4): between the size distribution instruments and the MOUDI stages was applied, which was based on the particle cut-off characteristics of each stage and inter-stage particle losses reported in Marple et al. (1991).
Compared with the transformation matrix used by Reicher et al. (2019), the method adopted in this study has two optimizations.
Firstly, the size distribution instruments (SMPS and APS) have more sampling channels (64 channels). The more data points 155 corresponding to each sampling particle size range the instruments measure, the higher accuracy for total surface area calculated. Secondly, according to the particle collection efficiency curves in Marple et al. (1991), narrowing the intervals of the transformation matrix better reflects the real distribution.

Air mass back trajectory analysis
Back trajectories of air mass arriving at the sampling site were calculated using the HYSPLIT 4 (Hybrid Single-Particle 160 Lagrangian Integrated Trajectory) model of the NOAA Air Resources Laboratory (Stein et al., 2015). When computing archive trajectories, the GDAS (Global Data Assimilation System, 1 degree, global) was selected as meteorological input data. The 72-hour back trajectories were initiated at the beginning of each sampling period, and started a new trajectory every 1 or 2 hours until the end of the sampling period. MeteoInfoMap, a GIS application that enables the user to visualize and analyze the spatial and meteorological data with multiple data formats (Wang, 2014) was used for final analysis and mapping. 165

INP Concentrations
Detailed sampling and measurement information for the 14 sets of samples collected in 2018 and 2019 are given in Table 1. The total sampled volumes and PM10 mass concentrations during the sampling periods determine the particle collection quantities, and affect the INP concentrations. Two weather condition scenarios, dust and non-dust events, were defined, based 170 on PM10 mass concentration (larger than 200 μg m -3 lasting more than 2 hours for dust events), the volume concentration of coarse mode particles (mean concentration higher than 75 μm 3 cm -3 for dust events; Wu et al., 2009), phenomenological dust storm observations operated by China Meteorological Administration (CMA, being reported as the largescale dust events), and the concentration of aluminium (Al) element (see Supplementary Information, referred to as SI from here on, Table S1).
Sample M4 was classified as a non-dust event. Sampling started at the end of a continuous dust storm period (M1, M2, and 175 M3), and the air mass passed through the Bohai Sea before arriving in Beijing, therefore it was not dominated by mineral dust (see the SI, Fig. S1).
Results of all freezing curves containing airborne dust particles at various particle size classes are presented in pale yellow in Fig. 1. Each curve corresponds to one sampled filter. Freezing was observed from -5 to -25 ℃ for ambient filters, while blank filters froze between -20 and -30 ℃. The freezing temperature range of the blank filters is similar to that of distilled water, far 180 lower than that of ambient samples, indicating a low contribution of contaminants from the filters. Frozen fraction curves from event M1 are also shown in Fig. 1, and each colour depicts a different size class ranging from 0.18 to 10.0 μm. Droplets https://doi.org/10.5194/acp-2020-678 Preprint. Discussion started: 15 September 2020 c Author(s) 2020. CC BY 4.0 License.
containing different size classes froze at different temperatures. Large particles froze at higher temperatures, while smaller particles froze at lower temperatures, indicating differentiated ice nucleating abilities. This will be discussed in more detail below. 185 The total concentrations of INPs ( ) as a function of temperature of all 14 samples, including 13 dust events and 1 nondust condition (M4), are shown in Fig. 2 (a), marked by different colors. These results were obtained from the data in Fig. 1 using Eq.
(2). In the sampling process, the eight-stage MOUDI collected particles in nine filters simultaneously. Each filter had a corresponding INP concentration, and each line in Fig. 2 (a) represents the sum of INP concentrations from 0.18 to 10 μm in each sample. On the whole, the measured total spanned 4 orders of magnitude from 10 -2 to 10 2 L -1 of standard air, 190 and freezing was measured between -5 and -25 ℃ for dust events and between -15 and -28 ℃ for non-dust event. The total INP concentrations and freezing temperatures during dust and non-dust periods were significantly different, and the concentration increased by approximately 2 orders of magnitude during dust events at a given temperature, indicating that mineral dust particles are very efficient INPs in the immersion mode. For mineral dust particles, their freezing temperatures were similar. However, the variations in concentration between the samples were up to two orders of magnitude at a given 195 temperature. The difference in INP concentrations was caused by dust particle properties including particle composition, particle loading, and the sample volume. The trend of with temperature and particle size in mineral dust-dominated samples is depicted in Fig. 2 (b), where the size-resolved ranged from 10 -2 to 10 1 L -1 of standard air (see Table S2 in the SI). For each particle size, INP concentrations increased significantly with decreasing temperature. From another perspective, at a given temperature, increased rapidly 205 and then levelled when the particle size increased from 0.18 to 10 μm. This is explained by the fact that depends not only on the activity of particles in a specific size range, but also on the total number concentration of the same size particles.

Difference of INPs between two Transport Pathways
In Fig. 3 (a), two distinct transport pathways, the northwest and north pathways, were identified during the sampling periods, based on air mass back trajectory analysis. These trajectories are consistent with the prevailing mineral dust transport pathways 210 that affect the Beijing region (Huang et al., 2010;Sun et al., 2005). Combined with the geographical distributions of deserts, the northwest pathway passes through Gobi Desert and Kubuqi sandy desert in northwest China, while the north route passes through Hunshadake, Horqin and Hulun Buir sandy lands in north-eastern China. These two pathways shown in Fig were from the northern area. Sample D7 is not included in Fig. 3 (c) because the size distribution data are partially missing, 215 and surface area could not be fully derived.
It is clearly shown in Fig. 3 (b) that the total INP concentrations of samples that followed the same pathway were very similar in their freezing behavior. Although the concentrations in the two pathways have similar initial and final freezing temperatures, there was a significant difference of an order of magnitude in the intermediate temperatures (-16 ~ -11 ℃).
To compare the ice nucleation activity of different samples, ice active site density, ( ), was calculated and is shown in Fig.  220 3 (c). Similar to in Fig. 3 (b), the gross ( ) values were similar in trajectories that followed the same route, but differed in trajectories between the two major pathways. This suggests that the mineral components differed between the different source regions; the ice nucleation activity of particles from the northwest was higher than that from the northern region. The surface area concentrations of the coarse mode particles ( ≥ 1.0 μm ) were also higher in the northwest pathway (see Fig.   S2 in the SI). 225 Both and ( ) in the northwest pathway were higher than those in north route, suggesting that dust from northwest China deserts has a higher freezing efficiency. Previous studies have shown that Chinese deserts have distinct zoning characteristics; The north-western deserts are characterized by relatively higher amount of feldspars, while in the northern sandy lands, quartz mineral is more common (Zhao, 2015). The two dust sources in this study are consistent with these two desert regions. The higher INP activity of the northwest pathway may be related to higher content of feldspar mineral, which 230 is known as an important nucleator when temperatures higher than -20 ℃ (Atkinson et al., 2013). reported airborne ice nucleating particles in the dusty tropical Atlantic, which is near the Sahara Desert in Africa (referred to as P18 from here on). Reicher et al. (2019) characterized the properties of size-segregated mineral dust sampled during dust events in the Eastern Mediterranean (referred to as R19 from here on), and found that the ( ) values increased with particle size. 240

Surface Ice Active Site Density of Dust Particles
The gross ( ) values of most samples in this study are in agreement with P18, although a few samples are more active than P18 at higher temperatures (above -15 ℃). The measured temperature-dependency in this study is consistent with that observed in R19 in four size classes. The difference in the freezing temperature range between the two studies, higher in this study (-25 to -5 ℃) than in R19 (-35 to -20 ℃), is due to the droplets' volume (0.5 nL in R19, in contrast to 1 μL in the present study).
Larger droplets tend to freeze at higher temperatures because they contain a broader spectrum of nucleation active sites 245 (O'Sullivan et al., 2014). Overall, we demonstrated that despite the fact that the mineral dust originated from different sources, https://doi.org/10.5194/acp-2020-678 Preprint. Discussion started: 15 September 2020 c Author(s) 2020. CC BY 4.0 License. and experienced varying atmospheric transport and aging processes, both the gross and size-resolved ice nucleation activity showed great similarities over a wide range of temperatures (-25 ~ -5 ℃), which is consistent with the conclusions of previous studies (Niemand et al., 2012;DeMott et al., 2015;Kaufmann et al., 2016;Price et al., 2018;Reicher et al., 2019).
There are three possible explanations why some samples in this study were more active than the measurements in the two other 250 studies presented in Fig. 4 (a)

Contribution of Heat-Sensitive INPs
Previous studies have suggested that biological materials may attach to or mix with dust particles and play an important contribution to INP populations during dust events (Pratt et al., 2009;Creamean et al., 2013;Boose et al., 2016a;Mazar et al., 270 2016;Gat et al., 2017). Because biological ice nucleation is mainly induced by proteinaceous components, inactivation by heat treatment is considered as a common way to identify biological nucleation activity (Christner et al., 2008a;Christner et al., 2008b;Garcia et al., 2012;O'Sullivan et al., 2014). In this study, heat-resistant INPs represent those particles that can initiate freezing after heat treatment (heated to 95 ℃ for 30 min). The suspensions of five size classes ( 50 = 10, 5.6, 3.2, 1.8 1.0 μm) were measured before and after heat treatment to calculate original and heat-resistant , 275 respectively. We subtracted heat-resistant from the original concentration to evaluate the contribution of heat-sensitive INPs, which are mainly considered to be proteinaceous biological materials at warm temperatures. with 81 ± 12% at -10 ℃ and 70 ± 15% at -15 ℃. At -20 ℃, heat-resistant INPs increased to 62 ± 21%, in comparison with 19 280 ± 12% at -10 ℃ (see Table S3 in the SI). In general, the contribution of heat-sensitive INPs is similar for different particle size classes at a given temperature (see Table S4). This proportion is related to the balance of biological materials and active mineral dust. Microorganisms may be more common in larger particles due to larger surface area (Gong et al., 2020). On the other hand, larger particles may contain more efficient mineral species, such as feldspars (Margaret et al., 1994), which are expected to be heat-resistant. 285 Figure 6 compares the freezing properties before and after heat treatment, based on those samples (with 50 ≥ 1.0 μm) originated from northwest and north pathways. The most prominent INP type above -10 ℃ were lost completely in north and northwest samples upon heating. In north samples, these INPs were less common than in northwest samples to begin with, a difference that extended to almost an order of magnitude in some of the cases. For example, near temperature at -10 ℃.
This is probably the reason why samples from the north pathway were less sensitive to heat treatment in general. It is then 290 interesting to compare ( ) curves of north and northwest samples in Fig. 6 (b), which demonstrated similar nucleation activity (within an order of magnitude, see Fig. S3 in the SI) after heating. This may suggest that after heat-sensitive INPs was removed, the two transport pathways are now dominated by similar material, which is probably mineral dust.
Overall, heat-sensitive components dominated the freezing at higher temperatures (above -15 ℃), and their contribution decreased pronouncedly at lower temperatures. Recently, Harrison et al. (2019) found that some quartz samples are sensitive 295 to aging in aqueous suspension. We can't rule out the presence of quartz, or determine the fraction of specific quartz in heatsensitive INPs at -20 ℃. The higher proportion of heat-sensitive INPs at 50 = 1.0 μm at -20 ℃ may be attributed to the inactivation of quartz. However, quartz cannot be activated at -10 ℃, and we can therefore conclude that a great proportion of INPs originated from heat-sensitive sites, mostly attributed to proteinaceous biological materials. The assumption of biological contribution for higher nucleation activity above -15 ℃ was verified also in Sect. 3.3. 300

Parameterizations of Size-Resolved Ice Nucleation Active Site Densities
By combining the observational dataset in our study with those in R19, the new ( ) parameterizations for size-resolved ice nucleation active site densities of dust particles are calculated by an exponential function: Where is the temperature in Celsius, and are coefficients given in Table 2. These new parameterizations broaden the temperature range spanning from -35 to -6 ℃. 305 Four sizes, 50 = 5.6, 3.2, 1.8 1.0 μm , measured in both studies were considered for parameterization. The parameterizations for size-resolved dust particles are displayed in Fig. 7 (a) and their coefficients are given in Table 2. Here, the submicron fit line, marked in Fig. 7 (a) by the solid blue line, was derived from the dataset of 50 = 0.6, 0.3 μm in R19 and 50 = 0.56, 0.32, 0.18 μm in this study, representing the ( ) of submicron desert dust. Note that we only present here the cases dominated by mineral dust rather than all the data.
An explicit size dependent freezing efficiency was observed. The difference between the fit line of 50 = 5.6 μm and the submicron line were approximately 1 to 2 orders of magnitude, while the three fit lines of 50 = 3.2, 1.8 1.0 μm were almost overlapping, and located between the first two lines. In this case, the 50 = 3.2, 1.8 1.0 μm lines were integrated into one, 1.0 ~ 3.2 μm fit line, shown in Fig. 7 (b).
A comparison between the newly calculated parameterizations and those from previous studies (Niemand et al., 2012;Atkinson 315 et al., 2013;Niedermeier et al., 2015;Reicher et al., 2019;Harrison et al., 2019) is presented in Fig. 7 (b). The parameterization in Niemand et al. (2012) is consistent with the 5.6 μm fit line (solid red line), and is close to the 1.0 ~ 3.2 μm fit line (solid green line) for temperatures lower than -17 ℃. The size of the surface-collected dust samples added into the chamber they used was less than 1 to 5 μm. Moreover, following a milling or sieving process, surface-collected samples may lead to higher The parameterizations for supermicron and submicron particle size ranges in the lower temperature range (< -20 ℃) developed by R19 used the same data points as the present study. However, no size-resolved information for the higher temperature range was available. Combined with our dataset, a set of representative size-resolved parameterizations with a wide and atmospherically relevant temperature range (-35 to -6 ℃) were derived, highlighting the importance of INPs size data. 330 The airborne particles, which were collected during dust-dominated events are composed of a complex mixture of various mineral components (e.g. feldspar, quartz, clay, and calcite), varying particle sizes, biological materials, and anthropogenic fine particulate matter. Its ice nucleation activity is determined by all components, and dominated by the most active substance.
That is why these new parameterizations located between the K-feldspar and quartz parameterizations are more active at temperatures higher than about -10 ℃. Overall, our new parameterizations can efficiently reflect actual atmospheric conditions. 335

Conclusions
The ice nucleation activities of size-resolved airborne East Asian dust particles in the immersion mode were investigated for the first time. Compared to non-dust event, the total INP concentrations during the East Asian dust events increased by approximately two orders of magnitude, and ranged between 10 -2 and 10 2 L -1 of standard air at temperatures between -25 and -5 ℃. The gross surface ice active site density, ( ), spanned 4 orders of magnitude from 10 4 to 10 8 m -2 at the temperature 340 range of -25 ℃ to -5 ℃. Based on air mass back trajectory analysis, dust particles transported from China's northwest and https://doi.org/10.5194/acp-2020-678 Preprint. Discussion started: 15 September 2020 c Author(s) 2020. CC BY 4.0 License. northern deserts have different ice nucleation efficiencies, indicating that dust particles from the northwest deserts may contain more active minerals.
An explicit size dependence of both INP concentration and surface ice active density was observed for Asian dust samples.
The nucleation efficiency of dust particles increased with increasing particle size, while the concentration first increased rapidly 345 with particle size, and then levelled. This is due to the dependence of on the common effect of the activity of individual size particles and the total number concentration of same size particles.
The gross and size-resolved ( ) values were derived, and compared with recent studies. The results suggest that both the population and size-resolved ice nucleation activities of natural mineral dust particles from East Asia, North Africa, and Eastern Mediterranean are relatively uniform, implying that the freezing properties of dust particles from global deserts are similar, as 350 was found in previous studies (Boose et al., 2016b;Kaufmann et al., 2016;Price et al., 2018;Reicher et al., 2019).
During the East Asian dust events, the average contributions of heat-sensitive INPs at three temperatures, -10, -15, and -20 ℃, were 81 ± 12%, 70 ± 15%, and 38 ± 21%, respectively. This result not only emphasizes the important role of biological materials during Asian dust transport, but also explains the phenomenon of higher INP activity at relatively warm temperatures (above -15 ℃) compared with the measurement closer to the desert source (P18). In addition, we found that the contribution 355 of heat-sensitive INPs in different particle size classes was similar, which could be attributed to the abundance of adherent biological materials and active mineral components in the dust particles.
A new set of size-resolved parameterizations based on the field observations in this study and R19 were developed, which are valid in an extended temperature range spanning from -35 to -6 ℃, characterizing the ice nucleation properties of size-resolved mineral dust particles. The size of the particles controls their atmospheric lifetime, transport distance, and interactions with 360 clouds, as larger particles sediment more quickly. Supermicron particles detected at high altitudes are much more abundant than expected by sedimentation theory alone (Ryder et al., 2018), emphasizing the importance of larger particles. Larger particles are more active INPs, as particle size reflects the mineral composition to a large extent. In both field observations and laboratory experiments it is easier to obtain particle size distributions than mineralogical compositions. Due to the single requirement of particle size distributions as input for our model, the new particle size-based parametrizations can be widely 365 applied in models, and help better characterize and predict INP concentrations related to natural mineral dust, especially related to long-range transport.

Data availability.
The data presented in this article can be accessed through the corresponding author Z. Wu (zhijunwu@pku.edu.cn).

Supplementary Information 370
The Supplementary Information related to this article is available online https://doi.org/10.5194/acp-2020-678 Preprint.     this study and those for desert dust (Niemand et al., 2012;Reicher et al., 2019) and single mineral dust components (Atkinson