Measurement report: Cloud Processes and the Transport of Biological Emissions Regulate Southern Ocean Particle and Cloud Condensation Nuclei Concentrations

Long-range transport of biogenic emissions from the coast of Antarctica, precipitation scavenging, and cloud processing are the main processes that influence the observed variability in Southern Ocean (SO) marine boundary layer (MBL) condensation nuclei (CN) and cloud condensation nuclei (CCN) concentrations during the austral summer. Airborne particle measurements on the HIAPER GV from north-south transects between Hobart, Tasmania and 62°S during the Southern Ocean 20 Clouds, Radiation Aerosol Transport Experimental Study (SOCRATES) were separated into four regimes comprising combinations of high and low concentrations of CCN and CN. In 5-day HYSPLIT back trajectories, air parcels with elevated CCN concentrations were almost always shown to have crossed the Antarctic coast, a location with elevated phytoplankton emissions relative to the rest of the SO. The presence of high CCN concentrations was also consistent with high cloud fractions over their trajectory, suggesting there was substantial growth of biogenically formed particles through cloud processing. Cases 25 with low cloud fraction, due to the presence of cumulus clouds, had high CN concentrations, consistent with previously reported new particle formation in cumulus outflow regions. Measurements associated with elevated precipitation during the previous 1.5-days of their trajectory had low CCN concentrations indicating CCN were effectively scavenged by precipitation. A course-mode fitting algorithm was used to determine the primary marine aerosol (PMA) contribution which accounted for < 20% of CCN (at 0.3% supersaturation) and cloud droplet number concentrations. Vertical profiles of CN and large particle 30 concentrations (Dp > 0.07μm) indicated that particle formation occurs more frequently above the MBL; however, the growth of recently formed particles typically occurs in the MBL, consistent with cloud processing and the condensation of volatile compound oxidation products. https://doi.org/10.5194/acp-2020-731 Preprint. Discussion started: 11 September 2020 c © Author(s) 2020. CC BY 4.0 License.

Over the southeRn Ocean (CAPRICORN-2) campaign. The CAPRICORN-2 study was conducted from 10 January to 21 February 2018, overlapping the SOCRATES study. The R/V Investigator covered a north-south transect over the SO, starting at Hobart, Tasmania (43°S) and reaching approximately 66°S, and then returning to Hobart. In this study, CCN measurements collected on the R/V Investigator were measured with a commercially-available streamwise CCN counter (CCN-100, Droplet Measurement Technologies, Boulder, CO) that measured CCN concentration between 0.25 and 1.05% supersaturation with a 170 step-wise scan. Each CCN spectrum took approximately one hour to complete. R/V Investigator CCN at 0.35% are analyzed and compared to the GV HIAPER CCN0.3 measurements.

HYSPLIT-GDAS
In this study, HYSPLIT hourly five-day back trajectories were performed with the Global Data Assimilation System (GDAS,175 ftp://arlftp.arlhq.noaa.gov/pub/archives/gdas0p5/) (Rolph et al., 2017;Stein et al., 2015) at 0.5 degree resolution for each CCN spectrum in the MBL leg (below the cloud layer if clouds are present). The average latitude, longitude and altitude (50-500 m) of the MBL legs on the GV HIAPER were used as starting points for the back trajectories. Antarctica is the only continent over which back trajectories passed; none of the airborne aerosol measurements in the MBL were influenced by continental Australia; the only anthropogenic influences were potentially ship tracks and research stations in Antarctica, which we assume 180 to have a negligible impact in this study.

ECMWF ReAnalysis (ERA5)
ERA5 is the 5th generation of a climate reanalysis dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF)(Copernicus Climate Change Service (C3S), 2017). The ERA5 model assimilates satellite, ground and airborne measurements to archive the state of the weather and climate. The ERA5 total precipitation and low-level cloud fraction was 185 used for the time period covering the SOCRATES campaign to identify the role of clouds and precipitation in changing CN and CCN concentrations. The ERA5 time resolution is hourly, and spatial resolution is 0.25 degrees.

Primary Marine Aerosol (PMA) Fitting Algorithm
The PMA concentration was determined by fitting the UHSAS distribution of particles greater than 0.2 µm diameter to a single lognormal mode. A single lognormal mode has been found to represent PMA in ambient measurements (Modini et al., 2015;190 Quinn et al., 2017;Saliba et al., 2019). While this method was previously used on dry particle number size distributions ranging from 0.02 to 5.0 µm (Saliba et al., 2019), the UHSAS measures the particle number size distribution between 0.07 and 1.0 µm diameter. In addition, UHSAS particles in the SOCRATES campaign were not fully dried and a relatively narrow deliquesced mode (GSD =1.44±0.25) is present at approximately 0.6 µm diameter, similar to previous measurements of optically derived particle distributions at high relative humidity (Strapp et al., 1992). This 0.6 µm deliquescent mode was consistently fit by the 195 algorithm. The deliquesced UHSAS particles affect the mode diameter of the fitted PMA size distribution but not the retrieved https://doi.org/10.5194/acp-2020-731 Preprint. Discussion started: 11 September 2020 c Author(s) 2020. CC BY 4.0 License.
PMA (and CCN0.3) number concentrations. The concentration of particles in this fitted mode correlated moderately with wind speed (Section 3.5), similar to previous measurements of PMA estimated with this method (Modini et al., 2015;Quinn et al., 2017;Saliba et al., 2019), indicating the fitted mode is a viable approximation of PMA concentrations. The estimated PMA mode sizes are consistent with sea salt (from PMA) observed on size-resolved particles collected in the marine boundary layer 200 during SOCRATES and analysed with transmission electron microscopy (TEM). The TEM analysis shows almost all particles > 0.2 µm in diameter consist of sea salt; and sea salt particles account for 25% to 100% of particle number concentrations at particle diameters > 0.4 µm (Saliba et al. submitted).

Particle Regimes 205
MBL CN and CCN0.3 measured on the GV HIAPER MBL legs ranged from 116-1153 cm -3 and 17-264 cm -3 and averaged 540±246 cm -3 and 123±58 cm -3 , respectively. Figure 1b shows the CN and CCN0.3 concentrations averaged over each CCN spectra scan during GV HIAPER MBL legs throughout the SOCRATES field project (with the exception of RF 14 when the scanning CCN counter malfunctioned). To determine which atmospheric processes drove the variability of nearly an order of magnitude in CN and CCN0.3, the measurements were divided into four regimes. The regime thresholds were selected based 210 on the bimodality of observed CN and CCN0.3 concentrations shown by the histograms and kernel density functions in Figure   1a,c. Figure 1a,c also shows the kernel density estimate based on a normal kernel function. Using this approach, rather than grouping all values into a single bin, each measurement is represented by a normal distribution and integrated to produce the kernel density estimate. The optimal kernel density estimate bandwidth was found to be 28 and 91 for CCN0.3 and CN, respectively, and calculated using the "ksdensity" function from Matlab (2019), derived from theory developed by Bowman 215 and Azzalini (1997). The Hartigan's Dip test (Hartigan and Hartigan, 1985) determined that the distribution was not unimodal (P-value <0.01) for both CN and CCN0.3, thereby validating the use of a bimodal distribution for this analysis. The bimodal distribution minima correspond to 125 cm -3 and 750 cm -3 for CCN0.3 and CN, respectively. Even though only CCN0.3 was used to determine the particle regimes, Figure 2a illustrates the systematic differences between the averaged CCN spectra and CN concentrations for each of the regimes. The bimodal CCN0.3 and CN regimes were combined for a total of four regimes. Table  220 1 shows the average CCN0.3 and CN concentrations for each of the four regimes, which are distinguished by permutations of high and low CCN0.3 and CN concentrations.
To differentiate the four regimes in the text, we have given them each abbreviated descriptive names based on their CN and CCN0.3 concentrations, where the regime with high CN and CCN concentrations is referred to as "Recent particle formation (RPF) + Aged", the regime with low CN and CCN concentrations is referred to as "Scavenged", the regime with low CN and 225 high CCN concentrations is referred to as "Aged", and finally the regime with high CN and low CCN concentrations is referred to as "RPF + Scavenged". The classification of each regime is based on the relative concentration of Aitken-mode particles (CN) and accumulation-mode particles (CCN), with a naming convention that describes the expected airmass history. Similar https://doi.org/10.5194/acp-2020-731 Preprint. Discussion started: 11 September 2020 c Author(s) 2020. CC BY 4.0 License.
to analyses in previous studies, the relative contribution of the accumulation-mode and the Aitken-mode are used to identify recent particle formation (RPF) events and growth of Aitken-mode particles to accumulation-mode or CCN sizes (Kalivitis et 230 al., 2015;Kleinman et al., 2012;Williamson et al., 2019). The Scavenged regime is named based on evidence indicating the removal of CCN-sized particles through precipitation scavenging (Section 3.3). The Aged regime represents cases in which accumulation-mode is prominent and CCN particle concentrations are relatively high, likely due to atmospheric processes that increase particle size over time such as the condensation of VOC oxidation products or cloud processing (Section 3.2 and 3.3, respectively). The RPF regime exhibits a large Aitken-mode with high concentrations of CN, indicative of recent particle 235 formation (Section 3.2).

Back Trajectories
Previous studies have shown long-range transport of particles and VOCs can affect locally observed particle concentrations and chemical properties (Dzepina et al., 2015;Korhonen et al., 2008). In addition, atmospheric processes affecting particle 240 concentrations upstream of the measurement location reduces the correlation of particle properties to individual (or discrete) processes, such as precipitation, cloud processing, and new particle formation (Albrecht, 1989;Bates et al., 1998b;Russell et al., 2009;Sanchez et al., 2018;Stevens and Feingold, 2009;Stevens and Seifert, 2008;Vallina et al., 2006;Wood et al., 2015).
Lagrangian HYSPLIT back trajectories initiated at MBL leg altitudes (50-500 m) were used to determine the path travelled by the parcel of air for the previous five days for each of the MBL legs ( Figure 3). Consistent patterns are apparent for each of 245 the particle regimes. Specifically, the back trajectories for the Aged particle regime ( Figure 3d) are consistently from the south along the Antarctic coast, which is associated with the elevated ocean surface emissions of DMS and other VOCs produced by phytoplankton activity (Alroe et al., 2019;Humphries et al., 2016;Kim et al., 2019;O'shea et al., 2017;Odowd et al., 1997;Weller et al., 2018). In contrast, the high CN regimes (RPF and RPF + Scavenged) exhibit back trajectories generally from the west from the SO. The scavenged regime consists of back trajectories from both the west and the south, signifying atmospheric 250 process rather than the parcel path and origin influence the observed CN and CCN concentrations.

Cloud Processing
Relating the identified regimes to the observed cloud processes provides insight on how cloud processes affect CN and CCN concentrations. Figure 2c shows CCN0.3 and CDNC correlated moderately (r = 0.75), the highest correlation of CCN concentrations relative to other supersaturations, indicating that CCN0.3 is a good proxy for CDNC, and similar to previous 255 estimates of marine cloud effective supersaturations (Martin et al., 1994;Snider et al., 2003). For this comparison, the 90th percentile of CDNC from vertical profiles are matched to the nearest below-cloud MBL leg CCN concentration. As expected, the Aged particle regime accounted for cases with the highest CDNCs (192±100), while the scavenged particle regime accounted for the lowest observed CDNC (111±72). Few CDNC measurements are associated with the RPF (high CN) regimes, suggesting fewer clouds are associated with this regime. Figure 2b shows the cloud effective supersaturation and its relationship to the CDNC. The cloud effective supersaturation is calculated as the supersaturation where the CCN concentration was equal to the 90th percentile of the measured CDNC. Typically, clouds contain a range of peak supersaturations, controlled by the strength of the updraft and the cloud droplet number concentration (Hudson and Svensson, 1995;Pawlowska and Grabowski, 2006;Siebert and Shaw, 2017). The effective supersaturation accounts for the CCN that have activated adiabatically near cloud base and subsequently dried through sub-adiabatic mixing processes (Sanchez et al., 265 2017). In general, the observed CDNC weakly correlate to the effective supersaturation (Figure 2b, r = 0.47). The two regimes with aged particles (high CCN) consistently had higher CDNCs than the other regimes, highlighting the role of CCN concentrations on impacting CDNC. It is also important to note, CDNC can still be relatively high (~200 cm -3 ) in regimes with low CCN under conditions of high in-cloud supersaturations generated by strong updrafts, or with relatively low PMA concentrations which also allows the generation of higher in-cloud supersaturations (Fossum et al., 2020). 270 To identify the effect of precipitation on CCN concentrations, CCN0.3 is compared to the total precipitation (obtained from ERA5) integrated over a 35-hour back trajectory, shown in Figure 4a. As expected, the two scavenged regimes (with lower CCN0.3 concentrations) corresponded to higher total precipitation. Figure 4b shows the Pearson correlation coefficient comparing the base 10 logarithm of the integrated total precipitation over back trajectory times of 0 to 120 hours and CCN concentrations between 0.1% and 0.8% supersaturation. The Pearson's coefficient r-value peaked for 35-hour back trajectories 275 at CCN supersaturations ranging from 0.3-0.5% (similar to effective in-cloud supersaturations, Figure 4b), indicating air parcel history, particularly in the last 1.5 days, is important for determining atmospheric processes that affect CCN concentration.
The Pearson's coefficient for CCN0.1 was consistently the lowest, likely because CCN0.1 is associated with PMA, which is quickly replenished in the MBL through sea spray emissions. Similarly, the Pearson's coefficient for CCN0.87 was also low, likely because this CCN size is associated with RPF particles that are replenished in the FT and subsequently grow to larger 280 sizes (and lower supersaturation CCN). Figure 4c shows the MBL cloud fraction (obtained from ERA5) over the 120-hour back trajectory averaged for each particle regime. The two regimes with RPF (RPF and RPF + scavenged; high CN) are associated with lower cloud fraction (< 0.6), which suggests the presence of cumulus clouds. New particle formation has previously been observed in cumulus cloud outflow regions (Bates et al., 1998b;Clarke et al., 1999;Cotton et al., 1995;Perry and Hobbs, 1994) and is likely the main 285 source of CN in these RPF regimes. In contrast, the "Aged" particle regimes correspond to high MBL cloud fraction (> 0.6), which is consistent with stratus and stratocumulus clouds. Stratus and stratocumulus clouds typically include less precipitation, allowing more cloud processing of CN to CCN sizes (Flossmann and Wobrock, 2019;Hoppel et al., 1990;Hudson et al., 2015;Neubauer et al., 2014). In addition, the concentration of ultrafine particles (Dp < 30 nm) also decreases through Brownian scavenging of interstitial particles onto cloud droplets (Croft et al., 2010), so that higher cloud fractions further reduce CN 290 concentrations. The back trajectories associated with the Aged regime (Figure 3d) typically originate from SO storm tracks to the south, which is consistent with the elevated cloud fraction shown in Figure 4c. The storm track frequency peaks around 60°S (Patoux et al., 2009), suggesting parcels of air entering the storm track from the south have also been influenced by https://doi.org/10.5194/acp-2020-731 Preprint. Discussion started: 11 September 2020 c Author(s) 2020. CC BY 4.0 License.
coastal Antarctic biogenic DMS and other VOC emissions, eventually leading to increases in CCN concentrations via cloud processing and in the absence of precipitation. The trajectories associated with the RPF and the RPF + Aged regimes are 295 typically from the west, and have fewer clouds. While these regimes have elevated CN concentrations, they are not linked to Antarctic coastal sources within the last 120 hours (Figure 3a,b). Long-range transport of aerosol particles and their precursors for more than five days is possible in the absence of major sinks (i.e., precipitation) (Feichter and Leisner, 2009). The existence of both Aged and RPF in the same regime suggests particles have experienced some cloud processing as well as input from a recent particle formation event. The cloud fraction for the aged + RPF regime is significantly lower than the aged regime 300 (Figure 4c).

Latitudinal Gradient
Both the airborne GV HIAPER and shipborne R/V Investigator measurements showed latitudinal (North-South) gradients in CCN concentrations, although differences in the sampling strategies between the two platforms does result in slight differences in the observed latitudinal gradients (discussed in detail below). Both sets of measurements showed high CCN concentrations 305 near Antarctica (Figure 5a The presence of a latitudinal gradient in aerosol concentrations (Dp > 0.07 μm) and a weak gradient in the GV HIAPER CCN 315 implies a north-south gradient in particle composition (i.e., hygroscopicity) across the SO. Figure 5d shows the hygroscopicity parameter (κ) for Dp > 0.07 μm derived at each MBL leg. The smaller κ (less hygroscopic aerosol) at high latitudes is consistent with the aerosol particles originating from biogenic emissions which have lower hygroscopicity values (κ = 0.6-0.9 for sulfates and κ < 0.2 for organics) relative to sea salt (κ = 1.3) (Kreidenweis and Asa-Awuku, 2014; Petters and Kreidenweis, 2007).
As PMA (mostly comprised of sea salt) is present all over the SO, relatively high κ values (κ ~1.0 ) are 320 found north of ~ 55°S where there are fewer biologically-derived organic and sulfate particles. The latitudinal trend of decreasing κ (i.e., more hygroscopic chemical composition toward the lower latitudes) implies particles further south in the SO will need higher in-cloud supersaturations to activate particles of the same size compared to mid regions of the SO where there are fewer biologically derived particles. Alternatively, particle growth and aging enhances the particle's ability to be CCN active even with a low hygroscopicity and initial small size. Despite the lower observed hygroscopicity of particles at high latitudes based on the airborne measurements, there are a greater number of CCN available (Figure 5b) to increase cloud droplet number and potentially enhance cloud reflectivity at higher latitudes.
Measurements from the R/V Investigator during the CAPRICORN-2 study show minima in CCN concentrations around 60°S (Figure 5a), which corresponds to the maximum in SO storm track activity (Patoux et al., 2009); however, this minima in CCN is not observed from the GV measurements and is not as pronounced in similar ship measurements at the same time (Humphries 330 et al.,in prep.). As expected, based on the GV measurements, there are elevated CCN concentrations to the south of 60°S High concentrations of aerosol particles in the MBL can be formed during new particle formation events in the free troposphere and subsequently entrained downward into the MBL (Bates et al., 1998a;Clarke et al., 1996Clarke et al., , 2013Korhonen et al., 2008;Pirjola et al., 2000;Reus et al., 2000;Russell et al., 1998;Sanchez et al., 2018;Thornton et al., 1997;Yoon and Brimblecombe, 360 2002). The nucleation of new aerosol particles often occurs in the free troposphere owing to the low total condensational sink and cold temperatures (Raes et al., 1997;Yue and Deepak, 1982). It has traditionally been thought that the SO is a possible exception to this trend because the SO MBL is a pristine environment with few anthropogenic sources, relatively low particle concentrations (condensational sink), and low temperatures compared to other MBLs around the world (Covert et al., 1992;Humphries et al., 2015;Pirjola et al., 2000;Yue and Deepak, 1982). To determine if the SO MBL truly is an exception to the 365 trend, we compare the concentrations of recently formed and aged particles. CN (Dp > 0.01 µm) and UHSAS (Dp > 0.07 µm) concentrations in the MBL (CNMBL; UHSASMBL) and above the MBL inversion (CNInv; UHSAS Inv) in Figure 7d Figures 7a and 7c show profiles of CN concentrations when CNMBL/ CNInv > 1 (consistent with particle formation occurring in the MBL) and CNMBL/ CNInv < 1 (consistent with particle formation in the free troposphere or decoupled layer). When CNMBL/ CNInv ~ 1, particle formation has not recently occurred in either the MBL or above the inversion (Figure 7b), and mixing across the inversion homogenizes the aerosol concentrations between the free troposphere and MBL. During this study, the CNInv is generally greater CNMBL, which suggests particle formation occurs more frequently 375 above the MBL inversion, either in the free troposphere or a decoupled layer above the marine boundary layer. This is also shown in the histogram of the CNMBL / CNInv ratio (Figure 9a), which typically has a value of less than unity. These results are consistent with previous findings that the observed long-range transport of particles and their precursors from phytoplankton blooms (Figure 3d) typically occurs above the MBL (Hudson et al., 1998;Korhonen et al., 2008;Meskhidze and Nenes, 2006;Russell et al., 1998;Sanchez et al., 2018;Thornton et al., 1997;Williamson et al., 2019;Yoon and Brimblecombe, 2002). 380 Similarly, Figure 8 compares UHSAS concentrations (Dp > 0.07 µm) in the MBL to those above the MBL inversion. As the UHSAS provided vertical profiles of the aerosol, we use the UHSAS to complement the static CCN measurements to assess the vertical extent of cloud-active aerosol. CCN0.3 and CCN0.4 correlate well with UHSAS (Dp > 0.07 µm) concentrations (r = 0.94). Contrary to the vertical extent of CN, UHSAS (Dp > 0.07 µm) and CCN0.43 concentrations are generally greater in the MBL compared to above the MBL inversion (Figure 7a-c, Figure 9b), which suggests high MBL UHSAS concentrations 385 resulted from the growth of Aitken mode particles to CCN sizes through cloud processing (Section 3.2.2) (Hudson et al., 1998) or gas-to-particle phase condensation in the MBL (Pirjola et al., 2004;Russell et al., 2007;Sanchez et al., 2018), and consequently associated with the Aged regime ( Figure 8). Precipitation also likely played a role in depleting UHSAS and CCN-sized particles (Dp > 0.07 µm) for the Scavenged regimes.
GV HIAPER airborne measurements collected during the Southern Ocean Clouds, Radiation Aerosol Transport Experimental Study (SOCRATES) of CN and CCN over the Southern Ocean (SO) during the austral summer were separated into four regimes based on back trajectories and CN-to-CCN ratios. Airborne CCN measurements were also compared to shipborne measurements on the R/V Investigator collected on the second Clouds, Aerosols, Precipitation, Radiation and atmospheric Composition Over the southeRn Ocean (CAPRICORN-2) campaign. The airborne measurements on the GV HIAPER show a 395 weak gradient in CCN at 0.3% supersaturation (CCN0.3) with increasing CCN concentrations to the south between 44°S to 62.1°S, which may be caused by aerosol precursors from Antarctic coastal biological emissions. Shipborne CCN measurements on the R/V Investigator also show gradients between 44°S to 67°S with a minimum around 60°S where the peak frequency of SO storm tracks occurs (Patoux et al., 2009). Enhanced ship-based CCN concentrations north of 50°S are likely from Australia, enhanced biogenic activity near the Australian coast, or even long-range transport from Antarctic coastal emissions. Elevated 400 CCN concentrations to the south of 60°S originate from biogenic emissions from the Antarctic coastal area. The differences in the observed trends between airborne and shipborne CCN concentrations is likely due to the different sampling strategies.
The particle regimes from the GV measurements were determined from the observed bimodal distributions in CN and CCN0.3 concentrations, with minimum values at 750 cm -3 and 125 cm -3 , respectively. These minima were used as thresholds to identify different particle regimes. and CCN concentrations, as well as a gradient in particle composition (inferred from hygroscopicity). The hygroscopicity gradient was derived from aerosol size distributions (UHSAS) and CCN spectra and resulted in less hygroscopic aerosol (lower κ) to the south, indicating CCN contained more biogenic sulfate and organics, relative to those further north, which likely 415 contained a larger fraction of more hygroscopic sea salt. Biogenic emissions from coastal Antarctic areas accounted for most of the CCN and CDNC concentrations in the SO during the austral summer, while PMA only accounted for about 20% of observed CCN and CDNC.
Precipitation over the ~1.5-day trajectory inversely correlates with CCN concentrations, indicating precipitation scavenging is a major sink of CCN in the SO. The boundary layer cloud fraction was highest for the aged (high CCN) regime, suggesting 420 cloud processing significantly enhanced CCN concentrations (CCN0.3 = 185±38 cm -3 for the Aged regime) in non-precipitating clouds. High CN concentrations (Dp > 0.01 µm), characteristic of recent particle formation (RPF) corresponded to cases with low cloud fractions, which is consistent with particle formation in cumulus outflow, also found in previous studies (Bates et https://doi.org/10.5194/acp-2020-731 Preprint. Discussion started: 11 September 2020 c Author(s) 2020. CC BY 4.0 License. al., 1998b;Clarke et al., 1999;Cotton et al., 1995;Perry and Hobbs, 1994). RPF is the main eventual source of CCN number concentration in the SO. In addition, CN concentrations were typically lower in the MBL relative to concentrations above the 425 MBL, suggesting that RPF typically occurred above the MBL inversioneither in the free troposphere or a decoupled layer.
In contrast, CCN and particle concentrations with Dp > 0.07 µm (UHSAS) were higher in the MBL, suggesting growth of recently formed particles to CCN sizes occurred after mixing into the MBL and subsequent aging through gas-to-particle conversion and cloud processing.
Due to the remoteness of the SO, biogenic Antarctic coastal emissions appear to be the main CCN source to the SO MBL.