This study presents a comprehensive dataset of ice-nucleating particle (INP) concentrations measured during the Arctic Century Expedition (August–September 2021) across the Barents, Kara, and Laptev Seas. The authors combine online (HINC) and offline (DRINCZ) immersion freezing measurements with aerosol chemical and physical analyses to examine INP abundance, sources, and variability in the Eurasian Arctic. The work expands observational coverage in a remote and data-scarce region and provides insights into the local versus long-range sources of Arctic INPs.

The manuscript is well structured and clearly written, with a logical flow from methods to results and interpretation. The inclusion of a focused case study contrasting low and high INP periods adds significant value by integrating aerosol measurements, chemical tracers, meteorology, and air mass origin to support the broader conclusions. This is a well-executed and much-needed observational study in a remote and understudied Arctic region. I recommend publication after minor revisions to address the points below.

1. The use of 2-day back trajectories in Figure 7 provides useful context for identifying short-range influences but may be insufficient to fully assess the role of long-range transport, particularly for mineral dust or aged aerosols that can persist in the atmosphere for several days. While the authors conclude that local sources dominate INP variability, this conclusion may partly reflect the limited temporal scope of the trajectory analysis. Extending the trajectory duration could potentially reveal additional source regions or transport pathways not captured in the current analysis, such as high-latitude terrestrial dust or recirculated Arctic aerosols. As it stands, the statement of limited long-range influence, though plausible, remains somewhat constrained by the methodology. A brief discussion of this limitation and consideration of longer trajectory timescales would be welcome.
2. The weak correlations between INP and chemical tracers in Figure 4 limit the strength of source attribution to mineral dust or marine biogenic components. While the observed trends, such as modest associations with AlSiCa or sulfur, are directionally consistent with expected sources, the low correlation coefficients and lack of statistical significance in many cases suggest that the chemical composition data alone are insufficient to differentiate dominant INP types. This highlights the need for either more specific tracers (e.g., molecular markers) or multivariate approaches to better resolve complex and potentially co-varying source contributions.
3. The use of coarse elemental proxies (e.g., AlSiCa) without complementary biological markers (e.g., DNA, lipids) constrains the ability to resolve source types (marine vs terrestrial biogenic).
4. The discrepancy between impinger and PM10 filter data is well noted in Appendix A, but two important methodological issues remain unaddressed. First, the vertical offset between sampling inlets (2nd vs 6th deck) could introduce a height-related bias, particularly under stratified conditions where aerosol concentrations may vary significantly with altitude. Second, the potential for contamination from the ship’s own exhaust emissions is not discussed, despite the low ambient aerosol background and proximity of the sampling locations to possible emission sources.
5. The weak to moderate correlations between INP concentrations and aerosol surface area shown in Figure 3 suggest that existing parameterizations may not fully capture the complexity of INP behavior in this environment. It would be helpful if the authors could expand the discussion to explore possible contributing factors, such as the potential diluting effect of non-IN-active sea salt particles or the presence of mixed aerosol types. A brief reflection on these mechanisms would strengthen the interpretation.

Minor comments:

1. Table 1, please clarify that CPC measures particle number concentrations.
2. In Figure 2, the yellow circles, grey open triangles, blue bars, and pink diamonds all correspond to data at the same temperature points, but this is not immediately clear to the reader. Adding a guiding arrow or visual connector between the temperature axis and the symbol legend would help direct the eye and improve interpretability.

Li et al. present valuable findings on INP measurements in the Eurasian sector of the Arctic Ocean during late summer 2021. These are paired with colocated aerosol size and composition data, supported by reanalysis and air mass trajectory analysis from shipborne observations. The inclusion of measurements from this sector is particularly notable, given the region's proximity to Russia and the general scarcity of INP and aerosol data from this area. This region is especially important as it serves as a key site for sea ice formation after the sea ice minimum in September. The case study highlighted in the paper is especially intriguing, with a well-supported connection between air mass history, wind speed, and aerosol composition suggesting potential fluvial-marine sources. I believe this manuscript merits publication following consideration of the comments outlined below.

General comment:

My primary concern with the analysis is the lack of discussion regarding the removal of ship exhaust contamination from the online aerosol and HINC measurements. Ship stack emissions are a well-known source of interference in aerosol datasets and must be carefully filtered out, even when the vessel is in motion, since recirculated air can still impact measurements taken fore of the stacks. While previous studies have shown that ship emissions do not significantly affect offline, immersion-mode INP concentrations, the same cannot be assumed for online measurements. I strongly recommend that the authors apply an established method, such as the one developed by Beck et al. (2022), to identify and exclude periods potentially influenced by ship exhaust. Implementing such quality control steps may also improve correlations with the offline INP data.

Specific comments:

Line 16: “...which is a decrease in cloud albedo upon glaciation…” While this precise statement is true, generally a decrease in cloud cover would lead to less surface warming on average, since MPCs contribute to surface warming most of the year except for a short period in the middle of summer (Intrieri et al., 2002). Thus, while cloud albedo decreases due to glaciation, cloud thinning reduces the stronger downwelling longwave effects from MPCs. May want to consider reframing this statement in light of the first sentence of the paragraph. 

Line 43: The authors could consider citing Creamean et al. (2022) and Wex et al. (2019) to support the statement regarding the seasonal cycle, particularly for elevated INP concentrations during summer months.

Line 47: The authors could replace Hall (2004) with more updated citations on Arctic amplification, such as Yoshimori et al. (2025) and/or Rantanen et al. (2022).

Line 48: Define MBA as marine biogenic aerosol.

Figure 1: The ship track is incomplete, as it does not extend to Murmansk at the end. Additionally, it would be helpful to indicate the location of the ship’s exhaust stack in panel b, as this is relevant for evaluating potential contamination in the aerosol measurements.

Line 86: Out of curiosity, why are samples stored in the fridge overnight prior to analysis?

Line 178: It is intriguing that the authors note their results are comparable to those of Hartmann et al. (2021), despite the fact that Hartmann's measurements were taken in early summer (during the onset of sea ice melt and primary productivity) whereas the present study occurs in late summer, following the peak in productivity and during the period of the annual sea ice minimum. It would be interesting for the authors to elaborate on why they consider these datasets comparable, given the seasonal and biogeochemical differences between the two time periods.

Figure 2: Why are the Welti, Bigg, and Creamean datasets only presented at –15 °C? Additionally, what datasets do the bright purple and orange boxes at –15 °C represent? The visibility of the Welti, and Bigg and Leck data could be improved for clarity. The authors may also consider incorporating more recent INP data from the MOSAiC expedition (Barry et al., 2025), which includes observations in a similar region west of Svalbard, as well as data from Irish et al. (2014), which, although from the Canadian Archipelago, could provide a useful spatial comparison for July and August. Note that Barry et al. (2025) is currently available as a preprint: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-128/.

Line 232: Why did the authors choose 2-day back trajectories rather than longer ones that might capture long-range transport? Also, was the boundary layer height obtained from ERA5?

Lines 241-243: These statements are supported by Nieto-Caballero et al. (2025) and Weiber et al. (2025). The authors could consider including these citations.

Line 272: The authors may wish to highlight that, despite the substantial presence of melt ponds covering up to 20–30% of the sea ice surface (Webster et al., 2015), the peak of primary productivity has already passed (e.g., Ardyna et al., 2020). Consequently, local biological sources of warm-temperature INPs are likely to be minimal during this period.

References:

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