A comprehensive characterisation of natural aerosol sources in the high Arctic during the onset of sea ice melt

A comprehensive characterisation of natural aerosol sources in the high Arctic during the onset of sea ice melt† Gabriel Pereira Freitas, ‡ ab Julia Kojoj, ‡ ab Camille Mavis, c Jessie Creamean, c Fredrik Mattsson, ab Lovisa Nilsson, d Jennie Spicker Schmidt, e Kouji Adachi, f Tina ˇ Santl-Temkiv, e Erik Ahlberg, d Claudia Mohr, abgh Ilona Riipinen ab and Paul Zieger ‡* ab Received 2nd October 2024, Accepted 25th November 2024 DOI: 10.1039/d4fd00162a The interactions between aerosols and clouds are still one of the largest sources of uncertainty in quantifying anthropogenic radiative forcing. To reduce this uncertainty, we must first determine the baseline natural aerosol loading for different environments. In the pristine and hardly accessible polar regions, the exact nature of local aerosol sources remains poorly understood. It is unclear how oceans, including sea ice, control the aerosol budget, influence cloud formation, and determine the cloud phase. One critical question relates to the abundance and characteristics of biological aerosol particles that are important for the formation and microphysical properties of Arctic mixed-phase clouds. Within this work, we conducted a comprehensive analysis of various potential local sources of natural aerosols in the high Arctic over the pack ice during the ARTofMELT expedition in May–June 2023. Samples of snow, sea ice, seawater, and the sea surface microlayer (SML) were analysed for their microphysical, chemical, and fluorescent properties immediately after collection. Accompanied analyses of ice nucleating properties and biological cell quantification were performed at a later stage. We found that increased biological activity in seawater and the SML during the late Arctic spring led to higher emissions of fluorescent primary biological a Department of Environmental Science, Stockholm University, Stockholm, Sweden. E-mail: paul.zieger@aces. su.se b Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden c Department of Atmospheric Science, Colorado State University, USA d Department of Physics, Lund University, Sweden e Department of Biology, Aarhus University, Denmark f Department of Atmosphere, Ocean, and Earth System Modeling Research, Meteorological Research Institute, Tsukuba, Japan g PSI Center for Energy and Environmental Sciences, Paul Scherrer Institute, Villigen, Switzerland h Department of Environmental Systems Science, ETH Zurich, Zürich, Switzerland †Electronic supplementary information (ESI) available. See DOI: https://doi.org/10.1039/d4fd00162a ‡Contributed equally to this work. 120 |Faraday Discuss.,2025,258,120–146 This journal is © The Royal Society of Chemistry 2025 Faraday Discussions Cite this: Faraday Discuss.,2025,258,120 PAPER Open Access Article. Published on 25 November 2024. Downloaded on 10/31/2025 11:48:49 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. View Article Online View Journal | View Issue aerosol particles (fPBAPs) and other highly fluorescent particles (OHFPs, here organiccoated sea salt particles). Surprisingly, the concentrations of ice nucleating particles (INPs) in the corresponding liquid samples did not follow this trend. Gradients in OHFPs, fPBAPs, and black carbon indicated an anthropogenic pollution signal in surface samples especially in snow but also in the top layer of the sea ice core and SML samples. Salinity did not affect the aerosolisation of fPBAPs or sample ice nucleating activity. Compared to seawater, INP and fPBAP concentrations were enriched in sea ice samples. All samples showed distinct differences in their biological, chemical, and physical properties, which can be used in future work for an improved source apportionment of natural Arctic aerosol to reduce uncertainties associated with their representation in models and impacts on Arctic mixed-phase clouds. 1 Introduction Climate change is manifested most in the rapidly changing Arctic. Here, the observed temperature increase is almost four times higher than the global average with local amplication of up to six or even seven times. 1 This rapid warming, known as Arctic amplication, 2 is interlinked with the Earth's climate system and has consequences on global weather systems 3 and the climate within and outside the Arctic. 4 Aerosols, suspended liquid or solid particles in the air, are known to inuence the Arctic climate by affecting solar radiation, cloud formation, and atmospheric composition (see Fig. 1). These particles can either be directly emitted into the atmosphere (primary aerosols) or formed from gaseous precursors (secondary Fig. 1 Sources of natural primary aerosol particles over the high Arctic Ocean during the onset of sea ice melt. Primary particles can be lofted to the atmosphere via wind stress on surfaces (e.g., blowing snow, wave breaking) and bubble bursting (e.g., in leads or melt ponds). Once in the atmosphere, particles can interact with solar radiation and influence cloud properties by acting as cloud condensation nuclei (CCN) or ice nucleating particles (INP). Paper Faraday Discussions Thisjournalis©TheRoyalSocietyofChemistry2025 Faraday Discuss.,2025,258,120–146 | 121 Open Access Article. Published on 25 November 2024. Downloaded on 10/31/2025 11:48:49 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. View Article Online aerosols). In winter and spring, the Arctic aerosol population is dominated by long-range transport of particles from lower latitudes, including biomass burning 5 or pollution aerosols from anthropogenic sources. 6 This phenomenon is also known as Arctic haze. 7,8 In late spring, the shiin atmospheric dynamics induced by the increase in solar radiation blocks northward aerosol transport to a large degree, and local aerosol sources instead drive changes in the aerosol population. 9–12 Summertime sources include secondary aerosols, 13–15 such as the oxidation of dimethyl sulphide, common in marine environments. In addition, aerosols from the free troposphere and entrainment from above the stable boundary layer could contribute to aerosol particles in the high Arctic during summer. 16 Primary aerosols are also signicant in the Arctic, dened here as the region above the Arctic Ocean's pack-ice, including the biologically active marginal ice zone (MIZ). Key sources during the summer are sea spray from breaking waves in open water 17,18 and terrestrial emissions from the northern continental regions or islands in the Arctic. 19–21 Blowing snow is another signi- cant polar primary aerosol source, 22,23 but it is more prominent during winter. 24 A crucial category of primary aerosols are those of biological origin –spores, bacteria, pollen, viruses, or algae –found in the ocean, sea ice, or snow. These are known as primary biological aerosol particles (PBAPs) and are vital to the Earth's biosphere, climate system, and hydrological cycle. 25–28 Clouds signicantly affect the surface energy budget in the Arctic, 29,30 inuencing the melting and freezing of sea ice. 31–34 Unlike mid-latitude or subtropical clouds, which generally cool the climate, with the exception of the middle of summer, low-level Arctic mixed-phase clouds (AMPCs) warm the surface 35,36 and can persist throughout the year for days or weeks at a time. 37 The impacts of AMPC radiative properties on sea ice albedo is further inuenced by aerosol particles, both natural and anthropogenic, which act as cloud condensation nuclei (CCN) or ice nucleating particles (INPs). 38–40 The inherently complex AMPCs have proven particularly difficult to accurately reproduce in models, 37,41,42 and the relevant sources of natural aerosols, and understanding their interactions with clouds, remain incomplete pieces of the puzzle. 38,43,44 In fact, on a global scale, natural aerosol sources and properties are the largest source of uncertainty in estimates of the cloud radiative forcing induced by aerosols. 45 In summer, high Arctic low-level clouds are oen optically thin due to fewer, larger droplets or ice crystals. 46 This is linked to the pristine air with very low CCN concentrations, as anthropogenic inuence is limited. 47,48 Consequently, marine particles from the marginal ice zone and further north serve as CCN. 13,49,50 INP observations in the Arctic are more limited than CCN, yet recent studies have targeted evaluation of their quantities and sources, including over the full sea ice annual cycle. 51 Despite the known importance of CCN and INPs for cloud processes, and the body of recent work focusing on CCN and INPs, their abundance, sources, atmospheric transformations, and sinks in the Arctic remain insufficiently understood, 15,52,53 yet are critical for climate prediction. 54 The interface between the ocean and atmosphere, known as the sea surface microlayer (SML), is enriched in biogenic organic material, including different and distinct microbial communities, 55,56 which can be released through bubble bursting via sea spray. 57–59 Sea spray is composed of inorganic sea salt particles, which can be coated by water-dissolved organics and/or accompanied by primary biological particles. 60 The biological and organic composition of sea spray aerosol Faraday Discussions Paper 122 |Faraday Discuss.,2025,258,120–146 This journal is © The Royal Society of Chemistry 2025 Open Access Article. Published on 25 November 2024. Downloaded on 10/31/2025 11:48:49 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. View Article Online is thus linked to the ocean's physico-chemical and biological state, with biological particles such as marine gels potentially acting as a signicant source of CCN. 61,62 In a marine and Arctic environment, PBAPs may serve as a signicant source of INPs, 21,51,63–66 thus playing a signicant role in modulating cloud radiative properties and precipitation formation. 67–69 Snowfall effectively removes PBAPs from the atmosphere, 70 but some microorganisms may survive and potentially grow within the snow-pack, 71 and possibly be re-suspended through blowing snow 23,72 although this has yet to be conrmed by observations. Microorganisms are also trapped in sea ice, 73 where they can thrive, and are released into seawater or melt ponds when the ice melts, 74 where they are possibly emitted as aerosols through bubble bursting or wave breaking. 75 Non-wind driven mechanisms such as algae respiration bubbles 76 and bubble inclusion releases in the ice 77 were discussed by Beck et al. in 2024, 72 but the extent of their contribution is hard to quantify. Recent studies suggest PBAPs are a dominant source of high-temperature INPs (i.e., INPs that can form cloud ice at temperatures $−15 °C) in the Arctic, 21,72 contributing to uncertainties in INP predictions and cloud properties in models. 78 Creamean et al. 79 found a seasonal increase in airborne biological INPs during the high Arctic summer, coinciding with high melt pond and lead fractions in the sea ice, pointing to a biological INP source in the marginal ice zone (MIZ). Further support comes from uorescent particle observations, which also peaked during this period, indicating a local marine source. 72 Close to Arctic land masses, the vegetation and soil seem to be the main sources for PBAPs and INPs, 21,80 but it is unclear how much they contribute to their high Arctic respective populations. Thus, one way to assess the ratio between local and transported sources is rst characterising the local aerosol sources. To incorporate biological INPs into models, sources and emission processes must be claried. 68,78 Open-water features within sea ice, such as leads and melt ponds, are potential sources, with biological activity inuenced by the age and thickness of sea ice and snow, 81,82 and the formation of leads. 83 However, differentiating between various sources of PBAPs and INPs –sea ice, seawater, or snow – requires more specic characterisation. 72 The purpose of this study is to analyse key potential natural sources of aerosols in the high Arctic, focusing on sea ice, snow, and seawater, during the transition from spring to summer (i.e., up to the melt onset). As sea ice retreats and as the melt season is lengthened, new natural aerosol sources will emerge, making it crucial to understand their origins and properties for more accurate climate predictions in the Arctic. By studying the biological, physical, and chemical characteristics of these aerosols, we aim to gain deeper insights into their role in Arctic climate processes, particularly in poorly understood areas such as aerosol– cloud interactions. 2 Methods 2.1 The ARTofMELT expedition The ARTofMELT (atmospheric rivers and the onset of sea ice melt) expedition on board the Swedish icebreaker I/B Oden took place from May 7th to June 15th 2023. One main scientic goal of the expedition was to study the various atmospheric, sea ice and ocean processes that are important during the onset of the sea ice melt season, including, among others, the role of aerosols and clouds. “Source” Paper Faraday Discussions Thisjournalis©TheRoyalSocietyofChemistry2025 Faraday Discuss.,2025,258,120–146 | 123 Open Access Article. Published on 25 November 2024. Downloaded on 10/31/2025 11:48:49 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. View Article Online samples were taken throughout the expedition at two dedicated ice oe camps, where Oden was moored to an ice oe, and predominantly from remote ice stations accessed by helicopter. The sites were chosen in order to obtain samples from different areas with a range of sea ice thickness, open water sources (leads), and snow coverage (see Fig. S1 and Table S1 in the ESI†). 2.2 Source sampling Samples of seawater from leads, sea ice cores, snow, and the sea surface microlayer (SML) were retrieved simultaneously at various sampling sites throughout the expedition. Sea ice cores (7.25 cm in diameter) were collected using a Kovacs Mark III Ice Coring System, permeating the measured thickness of the sea ice at the sampling location (see Fig. S1†). Segments of 10–20 cm were cut from the top, middle, and bottom of the ice cores. Each segment was placed in a separate WhirlPak® bag. Snow samples were collected by digging snow pits near the ice coring locations from the top of the snowpack to the sea ice surface (see Table S2†for depths). Temperature proles were measured every 10–20 cm. Snow was collected in separate containers for each analytical method directly from the top 10 cm and bottom 10 cm of the snow pit (if deep enough). Lead water samples were collected in individual containers at the surface and at 5 or 10 m depth using a horizontal water sampler (Pentair), then poured into containers that were triple-rinsed with lead water. When present, “slush”in the open leads, or porous sea ice broken offfrom the oe edge and/or refrozen surface ocean water, was also skimmed from the surface and collected into containers. Water samples were stored frozen on Oden until analysis. SML samples were collected by submerging a 28 ×52 cm glass plate vertically through the SML and slowly retracting it (5 cm s −1 ), allowing the SML to adhere to the glass surface. 84 The adhered SML was then scraped offinto individual containers. The glass plate was cleaned before and aer sampling by rinsing with 70% ethanol and ultra-pure water (MilliQ, Direct Q3, Merck). Ice cores remained frozen on Oden until analysis, when they were melted at room temperature then partitioned in separate containers for the various analyses described below. All other samples that were collected in their separate containers at each ice station were stored frozen on board Oden and successively analysed within 1–2 days using the aerosol in situ instruments installed in the Stockholm University Department of Environmental Science (ACES) mobile laboratory. Duplicates of the same samples were stored and transported frozen for biological characterisation and ice nucleating particle analysis aer the expedition ended at Aarhus University and Colorado State University, respectively. 2.3 Source sample analyses 2.3.1 Aerosol generation for analyses on-board Oden.On-board analyses of melted samples took place 1–2 days aer collection, whereby aerosols were generated via atomisation, and measurements were taken using a multiparameter bioaerosol spectrometer (MBS), scanning electrical mobility spectrometer (SEMS), soot particle aerosol mass spectrometer (SP-AMS), single particle soot photometer (SP2), and a transmission electron microscopy analysis (TEM) grid sampler. Faraday Discussions Paper 124 |Faraday Discuss.,2025,258,120–146 This journal is © The Royal Society of Chemistry 2025 Open Access Article. Published on 25 November 2024. Downloaded on 10/31/2025 11:48:49 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. View Article Online An aerosol generator (Model ATM 228, Topas GmbH, Germany) was used to atomise particles from the melted samples. The particle stream was diluted with particle-free air and dried using a Naon dryer (Model MD-700, Perma Pure, USA) to a relative humidity of RH =22 ±3.2% before being split into the different aerosol samplers (see Fig. 2). The sampling bottles of the aerosol generator were thoroughly cleaned before and aer each experiment using isopropanol and ultrapure water (MilliQ, Direct Q3, Merck) and rinsed several times with ultra-pure water. Leak and background tests were performed regularly by injecting particle-free air and running the atomiser with an empty rinsed bottle. The atomiser operates by creating a differential pressure between the air in the sample bottle and the incoming particle-free air that enters through the nozzle of the aerosol generator, which is submerged in the liquid sample. This creates a negative pressure at a sample inlet in the nozzle, causing the sample to ow into it and converge into droplets that exit the nozzle and rise to the surface of the sample inside bubbles. The aerosolised sample is released through bursting bubbles at the sample surface, thus to some extent mimicking natural sea spray. 85 The particle concentration produced depends on the differential nozzle pressure set, which determines the air ow. In this work, we were primarily interested in characterising uorescent primary biological aerosol particles (fPBAPs) in the coarse mode, as they are most likely to be relevant as INPs, and because this is the size range where they can be detected online with the MBS. Therefore, the pressure setting of the atomiser was regulated to generate rates of particles above >0.8 mm in diameter that were sufficient for detection, while keeping the pressure as low as possible to achieve as gentle and realistic atomisation as possible. Due to the large variation in salinity between source types, the pressure had to be adjusted for each sample. Samples with higher salinity like seawater from the leads reached appropriate particle rates at lower pressures, while it had to be increased for samples with lower salinity like snow (see Fig. S2†). For samples of the same source type (e.g., all snow samples), the nozzle pressure was constant throughout the entire set of experiments. To ensure that aerosolising the samples at different pressures did not have unexpected effects on the generated particle concentration in the ne or coarse mode, respectively, we ran two experiments with the sample types with lowest Fig. 2 Set-up of the experiment. Aerosol particles were atomised using an atomiser, the aerosols were diluted with dry particle-free air and successively analysed using the multiparameter bioaerosol spectrometer (MBS), soot-particle aerosol mass spectrometer (SP-AMS), single-particle soot photometer (SP2) and scanning electrical mobility spectrometer (SEMS), and using filter sampling with transmission electron microscopy (TEM) analyses performed after the expedition. The relative humidity was monitored at the inlet of the SEMS. Paper Faraday Discussions Thisjournalis©TheRoyalSocietyofChemistry2025 Faraday Discuss.,2025,258,120–146 | 125 Open Access Article. Published on 25 November 2024. Downloaded on 10/31/2025 11:48:49 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. View Article Online salinity, sea ice and snow, with the atomiser pressure increased step-wise to cover the entire range of settings used during all experiments (see Fig. S2†). The air ow from the atomiser to the instrumental setup was kept constant by the pumps behind the instruments, and an added make-up ow of dry particle-free air (see Fig. 2). The total sample ow rate between the atomiser and all sampling instruments was 3.7 L min −1 . 2.3.2 The multiparameter bioaerosol spectrometer (MBS). An MBS (University of Hertfordshire, UK) was used to determine the size, shape and uorescence characteristics of particles above D> 0.8 mm (optical diameter) on a single-particle basis. A UV-ashlight was used to excite uorescence at 280 nm wavelength and the emitted uorescence was measured at eight different channels between 305 and 655 nm using a spectrometer. Using a lowand a high-power infrared laser, the MBS also determines the optical diameter and 2D-scattering pattern. The latter holds information on the morphology of the detected particle. More technical details can be found in Ruske et al. 86 The MBS was specically designed to detect biological particles using uorescence. The classication of uorescent particles follows a decision tree described by Freitas et al. 59 in 2022. In summary, each uorescence emission channel is treated individually and assigned two thresholds. The rst threshold (3 times the background signal, measured every 30 000 particles and before the actual measurement started) classies particles as uorescent particles (FP), while the second (9 times the background) classies them as highly uorescent particles. These particles are assigned a spectral class based on the channels where their signal exceeds the second threshold, represented by letter combinations (A–H, for each channel). Particles with the highest signal in channel B (364 nm) are classied as uorescent primary biological aerosol particles (fPBAPs), while others are grouped as other highly uorescent particles (OHFPs). The MBS's channel B specically detects tryptophan uorescence, a marker for microorganisms. fPBAP spectral classes B, BC, ABC, and ABCD are referred to as fPBAP types I–IV, with other classes grouped as type V. The average uorescence spectra for fPBAPs and the most abundant OHFPs are shown in Fig. S3†(see also Freitas et al. 21 ). 2.3.3 The scanning electrical mobility spectrometer (SEMS). The sub-micron particle number size distributions were measured using a SEMS (Model 2100, Brechtel Inc. USA). The particle stream passed through an impactor to remove particles above 1 mm (round jet impactor, model 8009, Brechtel Inc. USA) before being charged using a Ni-63 bi-polar charger. A differential mobility analyser (DMA) and a mixing condensation particle counter (MCPC, model 1720, Brechtel Inc. USA) were then used to scan the size distributions between 0.005 and 1 mm (electrical mobility diameter) every 1 min. The multiple charge and loss correction within the SEMS was performed with the provided manufacturer's soware. A second MCPC (Model 1720, Brechtel Inc. USA) was used in parallel to measure the total concentration of sub-micrometre particles. The total sampling ow rate of the SEMS and MCPC was 0.76 L min −1 . The sizing of the SEMS was veried using polystyrene latex spheres of known sizes (100 nm and 269 nm, respectively). 2.3.4 The soot particle aerosol mass spectrometer (SP-AMS). A SP-AMS (Aerodyne Inc., USA) was deployed to determine the chemical composition of sub-micron particles. The SP-AMS was alternating between a laser on and a laser offmode. During laser on, an intra-cavity Nd:YAG laser (1064 nm) was used to Faraday Discussions Paper 126 |Faraday Discuss.,2025,258,120–146 This journal is © The Royal Society of Chemistry 2025 Open Access Article. Published on 25 November 2024. Downloaded on 10/31/2025 11:48:49 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. View Article Online vaporise the soot particles. In laser offmode, only the standard tungsten vaporiser, set to 600 °C, was used to measure the non-refractory composition. The aerosol components were ionised, using 70 eV electron ionisation, and subsequently entered the mass spectrometer in order to detect their chemical composition in real-time. More technical details can be found in Onasch et al. 87 Within this work, only the non-size-resolved laser offdata was used. It includes the mass concentration of non-refractory material such as organics, nitrate, chloride, ammonium and sulphate. All SP-AMS data were processed and analysed with soware packages SQUIRREL 1.66 and PIKA 1.26. Mono-disperse 300 nm (using the DMA from the SEMS) ammonium nitrate particles were used for the calibration of the ionisation efficiency. 2.3.5 The single particle soot photometer (SP2). A SP2 (Droplet Measurement Technology, Boulder, USA) was used to determine the refractory black carbon (rBC) mass of single particles. More technical details can be found in Schwarz et al. 88 and Stephens et al. 89 In the SP2, single particles cross a continuous wave intracavity laser (Nd:YAG,1064 nm) carried by a sample ow (0.12 L min −1 ) and constrained by a sheath ow. Absorbing particles, such as soot, are brought to incandescence, which yields a signal related to the single-particle mass. Here, the SP2 incandescence detectors were calibrated with Aquadag® and recalculated to a fullerene soot equivalent following Laborde et al. 90 The SP2 can determine the rBC mass between 0.3–117 fg corresponding to a volume equivalent diameter of 70–500 nm (assuming a density of 1.8 g cm −3 ). However, below 0.9 fg, the detection efficiency is reduced below 100%. 90 2.3.6 Transmission electron microscopy (TEM) analysis. Coarseand nemode particles with aerodynamic diameters larger and smaller than 0.7 mm, respectively, were sampled on transmission electron microscopy (TEM) grids using an impactor sampler (AS-24W, Arios Inc., Tokyo, Japan). The morphology and composition of individual particles from selected coarse-mode TEM samples (one sample of sea ice and lead water and two samples of snow) and the morphology of all ne-mode samples were analysed using a transmission electron microscope (JEM-1400, JEOL, Tokyo, Japan) equipped with an energy dispersive Xray spectrometer (EDS; X-Max 80, Oxford Instruments, Tokyo, Japan). The technical details of the TEM sampling and analysis are described in Adachi et al. 91 2.3.7 DNA extraction and quantitative polymerase chain reaction. DNA was extracted from a selection of source samples following the DNeasy® PowerSoil® Pro Kit protocol (HB-2495-002 ©2018, Qiagen). Two modications were applied to the protocol. In step 2, the PowerBead Pro Tube was vortexed in a TissueLyzer (Qiagen) for 10 min at a speed of 40 Hz. In step 16, 50 mL of solution C6 was added to the lter membrane, followed by 10 min of incubation to ensure a higher DNA yield from the extraction. To quantify the amount of bacterial 16S rRNA and eukaryotic 18S rRNA gene copies, a quantitative Polymerase Chain Reaction (qPCR) was performed on a 2 mL DNA template. Samples were run on a MX3005p qPCR instrument (Agilent, Santa Clara, CA, United States). To target the 16S rRNA gene sequence, the universal primers Bac908F (50-AAC TCA AAK GAA TTG ACG GG-30) and Bac1075R (50-CAC GAG CTG ACGACA RCC-30) were used following the methods described by Lever et al. 92 Some modications were applied to the qPCR protocol, including (1) 95 °C polymerase activation for 15 min, followed by (2) 40 PCR cycles, (3) elongation for 15 s and (4) acquisition for 15 s. The number 18S rRNA gene copies were quantied using primers Euk345F (50Paper Faraday Discussions Thisjournalis©TheRoyalSocietyofChemistry2025 Faraday Discuss.,2025,258,120–146 | 127 Open Access Article. Published on 25 November 2024. Downloaded on 10/31/2025 11:48:49 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. View Article Online AAGGAAGGCAGCAGGCG-30) and Euk499R (50CACCAGACTTGCCCTCYAAT-30) following the methods described by Zhu et al. 93 2.3.8 Ice nucleating particle analysis. All samples were processed on the Colorado State University Ice Spectrometer (IS) 94 5–14 months aer collection. Details of processing source samples are found in Barry et al., 95 but are described briey here. The solutions were prepared by thawing the collected samples at room temperature without further processing. The IS contains two 96-well temperature-controlled aluminium blocks tted with disposable clean PCR trays that enable the analysis of two samples at a time (11-, 121and 1331-fold, and occasionally in higher dilutions of 20-, 400-, and 8000-fold dilutions plus a 0.01 mL-ltered deionized water blank). For each sample, aliquots of 50 mL were dispensed into the PCR tray wells in a laminar ow clean hood, the trays were placed in the aluminium blocks in the IS, the blocks were covered with a plexiglass window, and the head space purged with cooled, dry, particle-free N 2 . Frozen wells were counted at each 0.5 °C interval as the temperature was lowered at ∼0.33 °C min −1 to ∼−30 °C. The cumulative concentrations of INPs per mL of sample were calculated using the equation from Vali 96 in 1971. In total, 37(15) ice core segments, 23(11) snow, 31(18) lead water, and 8(6) SML samples were analysed (analysed) on the IS (see also Table S1†). 2.3.9 Supporting analyses and data. The Oden is equipped with a FerryBox I system (-4H-JENA engineering GmbH, Jena, Germany) for the continuous analysis of key underway seawater properties such as temperature, salinity or turbidity. The water intake is at approximately 8 to 9 m below sea level (depending on the current draught of the ship). Here, we used the chlorophyll-adata measured using a WetLabs ECO FLNTU(RT) sensor within the FerryBox I system. Since the absolute calibration of the sensor was lacking, we show the normalised signal in conjunction with chlorophyll-avalues from discrete lter samples from a fully calibrated uorometer (see next paragraph). The source samples were also probed for their chlorophyll-aconcentrations. Chlorophyll-awas measured using a benchtop laboratory uorometer (Trilogy, Turner Designs, Inc.) with a chlorophyll-anon-acidication module. For preparation, at least 500 mL (up to 2000 mL) of each source sample were ltered through borosilicate glass grade GF/F lter discs (Whatman®, 0.7 mm pore size) through a ltration assembly (PYREX 47 mm microltration all-glass assembly) under vacuum. Each lter was added to 2.5 mL of 90% acetone and stored in 15 mL centrifuge tubes at −20 °C in the dark for 24 hours. Aer 24 hours, the suspension was thawed in the dark at room temperature, aer which the lters were compressed at the bottom of the tube with an acetone-cleaned spatula. The supernatant was extracted with a 5 mL pipette into a 12 ×75 mm borosilicate test tube (Fisher). The tube was placed into a tube adapter in the Trilogy® and analysed for chlorophyll-aconcentration (mgL −1 ). Aer analysis, the glass tubes were triple rinsed with acetone for reuse. Salinity was measured by rst recovering the conductivity of the source samples using a EXTECH ExStikII EC400 TDS/Conductivity/Salinity Pen and using the practical salinity scale (PSS-78) with Hill-86 modication. 97 Faraday Discussions Paper 128 |Faraday Discuss.,2025,258,120–146 This journal is © The Royal Society of Chemistry 2025 Open Access Article. Published on 25 November 2024. Downloaded on 10/31/2025 11:48:49 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. View Article Online measured INP concentrations of about 100 mL −1 at −15 °C in seawater in the Canadian Arctic, both during the summer season. The INP concentrations we obtained are comparable to previous measurements of seawater in the North Atlantic in the early fall. 116 This could indicate that the Arctic region in which we sampled was highly inuenced by water inow from the North Atlantic Ocean, or it simply reects the season, and INP concentration would have been higher in the water in the end of summer. In Fig. 5A and B, some samples are not shown on the logarithmic scatter plot due to an INP concentration of 0. As expected, at the lower temperature of T=−20 °C, INP concentrations increase in magnitude and range from 1 to 10 3 mL −1 , but no relationship or correlation to the fPBAP contribution can be observed. The INP concentrations shown come from the samples in their liquid state, not from the aerosol they produce. Therefore, the lack of correlation could be due to selective aerosolisation, either caused by the applied aerosol generation method or by the particles themselves. At both freezing temperatures, the INP concentrations (and their spread) are similar across sources. When aerosolised, sea ice samples consistently had a much higher fPBAP contribution, oen 100 to 1000 times more than lead water samples. It is known that sea-derived INPs around the Arctic oen come from heat-labile sources. 79 Despite similar concentrations of INPs, melted sea ice is likely a more efficient INP aerosol source than lead water. During the Arctic melt season, melt ponds cover a signicant portion of the Arctic surface 117,118 and thus may contribute signicantly to the fPBAP and INP populations when aerosolisation mechanisms (e.g. wind) are present. The aerosolisation process will depend on the salinity of the source sample since the salinity impacts the concentration and size of the salt particles produced. 109,119,120 The interplay between lm, jet and spume drops 17,121 within the aerolisation will determine the size-dependent chemical 122–124 and physical 125,126 composition of the released salt particles, which in turn may impact how the biological and organic material will re-distribute among the produced particles. In this work, the mean coarse-mode size scales quasi-linearly with sample salinity (see Fig. S7†). However, for the contribution of fPBAPs, no correlation between the salinity of the samples was observed (see Fig. 5C). Even within the different subsamples –sea ice, lead water or snow –the salinity did not impact the amount of released fPBAPs, conrming that the actual biological content of the sample and not the salinity is driving the amount of released fPBAPs. Interestingly, the snow samples showed the largest variation in fPBAPs, even at generally low salinity, reecting the nature of snow that is produced by precipitation, with its content primarily inuenced by air mass composition and scavenging of the aerosol as snow falls 70 and subsequent microbial growth. 71 These ndings point towards blowing snow as a potential source for fPBAPs and INPs, especially since snow could easily be re-suspended and not depend on the formation of melt ponds rst. However, this process will likely also depend on the season 24 and the actual microphysical properties of the snow. As mentioned above, the sea ice samples showed the highest fPBAP contributions. These contributions were notuniformly distributed along the thickness of the sea ice core, but rather showed a clear gradient with the fPBAP contributions increasing from the bottom to the top of the sea ice core (see Fig. 5D). The top of the sea ice core in the liquid phase also had signicantly higher concentrations of INPs. Interestingly, the cell counts showed counter-intuitive behaviour compared to the Paper Faraday Discussions Thisjournalis©TheRoyalSocietyofChemistry2025 Faraday Discuss.,2025,258,120–146 | 135 Open Access Article. Published on 25 November 2024. Downloaded on 10/31/2025 11:48:49 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. View Article Online INP and fPBAP values, with higher cell counts at the bottom of the sea ice core compared to the top. This is due to the migration and growth of microorganisms in brine channels that form at the interface of sea ice and seawater. 127 These results indicate that the microbial communities in lead seawater have signicantly different ice nucleating properties than those found in sea ice. Since we do see a covariation between cell counts in the liquid-phase lead water samples and fPBAP contribution to the aerosolised coarse mode (see Fig. 3), the opposite relation between cell counts and fPBAPs throughout the ice cores does not mean that we cannot detect the cells as fPABPs. However, it could corroborate the suggestion that microorganisms living on the sea ice surface are more likely to be aerosolised. The higher concentrations of fPBAPs at the top of the sea ice core reect differences in the abundance of microorganisms found along the ice core. 128,129 These ndings point to possible evolutionary traits acquired by these organisms. In future work, differences in the composition of the microbial community 130 will be further investigated using sequencing techniques. 4 Conclusions During the ARTofMELT expedition, Arctic sea ice, snow, and seawater samples were collected at the start of the melt season to investigate their physical, chemical and biological properties. Our study found notable differences in aerosol properties between these aerosol sources, with sea ice contributing the highest concentrations of uorescent primary biological aerosol particles (fPBAPs) and other highly uorescent particles (OHFPs). The observed increase in biological activity in seawater and the sea surface microlayer coincided with a rise in fPBAP and OHFP emissions; however, this increase in biological activity did not translate into an increase in ice nucleating particle (INP) concentrations within the water samples. The higher OHFP concentration was also linked to an increased organic mass fraction within the analysed particles. The enrichment of black carbon in the upper layers of the surface, particularly in snow, indicated a detectable anthropogenic inuence even in the pristine Arctic environment. This could also be the reason for the increase in the organic mass fraction within the upper snow samples. The counter-intuitive results regarding cell counts and aerosol emissions of melted sea ice samples highlight the importance of aerosolisation mechanisms that need to be taken into account when interpreting results of controlled or discrete sample analysis. Salinity did not appear to have a signicant impact on fPBAP aerosolisation or ice nucleating activity. However, the enrichment of INPs and fPBAPs in sea ice samples, increasing toward the surface, points to melt ponds as a potential important source of INPs, although the exact aerosolisation process remains unclear. This rich data set provides a valuable foundation for future research, offering the opportunity for detailed source-apportionment of natural aerosols and enhancing our understanding of aerosol–cloud interactions in the Arctic. Data availability The data of this study can be found at Kojoj et al. (2025) 131 provided at the Data Centre of the Bolin Centre for Climate Research, Sweden. Faraday Discussions Paper 136 |Faraday Discuss.,2025,258,120–146 This journal is © The Royal Society of Chemistry 2025 Open Access Article. Published on 25 November 2024. Downloaded on 10/31/2025 11:48:49 AM. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. View Article Online Author contributions The original concept of the study was developed by PZ. GF, JK, FM, LN, JC, CM, JS, and PZ were responsible for the acquisition of the main observational data. GF and JK performed the main data analysis and visualisation. GF, JK, FM, LN, CM, JS, KA, EA, and JC performed pre-processing and supporting data analysis. The manuscript text was written by PZ, GF, and JK, with input, contributions, and edits from all co-authors. Conflicts of interest The authors declare that they have no conict of interest. Acknowledgements This work is part of the ARTofMELT (Atmospheric rivers and the onset of Arctic melt) project. The ARTofMELT expedition was supported and organised by the Swedish Polar Research Secretariat (SPRS) on the Swedish research icebreaker Oden in spring 2023 under the SWEDARCTIC program. Support also came from the Swedish Council for Research Infrastructures (Grant 2021-00153) and the Knut and Alice Wallenberg Foundation (Grant 2016-0024). This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 101003826 via project CRiceS (Climate Relevant interactions and feedbacks: the key role of sea ice and Snow in the polar and global climate system) and the European Research Council (Consolidator grant INTEGRATE No. 865799). Funding for this study was provided by the European Union's Horizon Europe project “CleanCloud”(Grant agreement No. 101137639). Further funding was provided by the Carl Tryggers Foundation (CTS 22:2148), Ymer-80foundation, the Bolin Centre for Climate Research (RA2) and the Ivar Bendixsons scholarship. JMC and CM were funded by the U.S. National Science Foundation Arctic Natural Sciences (ANS) program (grant number OPP-2226864). This research was co-funded by the Novo Nordisk Foundation (NNF19OC0056963), Carlsberg Foundation (CF24-1911) and the Villum Foundation (23175 and 37435). LN and EA acknowledge the funding by the Swedish Research Council, project-ID 2019-05062 and by MERGE Short Research Project “ARTofMELT Arctic Ocean icebreaker expedition 2023”. The authors are grateful to the co-Chief Scientists Michael Tjernström and Paul Zieger, the SPRS coordinator Åsa Lindgren and the SPRS support team, and to Captain Mattias Petersson and the crew on Oden. 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