the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 16 Jul 2025
Long-range transported dust enhances ice nucleating particles abundance and cloud formation in the North China Plain
Abstract. Ice-nucleating particles (INPs) are critical in cloud formation and precipitation, particularly in continental regions where dust aerosols are prevalent. However, the long-term contributions of transported dust and other sources to INPs remain poorly understood. In this study, we analyzed precipitation samples collected at the summit of Mount Tai (1534 m a.s.l.), a background site in the North China Plain (NCP), from February 24 to November 29 in 2021. The cumulative INP number concentrations per volume of air (NINP_air) ranged from 0.4 × 10-2 to 1.8 L−1, aligning with INP spectra from precipitation and cloud water samples under diverse global conditions. During the observation period, NINP_air were highest in spring, approximately 2.3±1.4 times higher than those in other seasons. The seasonal enhancement was primarily attributed to the longrange transport of dust aerosols, supported by the frequent occurrence of dust events and the highest Dust Aerosol Optical Depth (DAOD) during spring. Additionally, interactions between biological materials and mineral dust appeared to enhance the ice- nucleating activity, triggering freezing at relatively higher temperatures and further increasing INP concentrations during spring. Using a Positive Matrix Factorization (PMF) model, we identified mineral dust contributed 43.6 % of the annual average NINP_air, and the contribution increasing markedly to 71.7 % in spring. Satellite observations further revealed that the long-range transport of dust in spring promotes large-scale cloud formation by forming ice crystals over the NCP. These findings highlight the vital role of transported dust in modulating INP abundance and provide new insights into aerosol-cloud interactions over the continental regions.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Atmospheric Chemistry and Physics.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.- Preprint
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RC1: 'Comment on egusphere-2025-2855', Anonymous Referee #1, 24 Jul 2025
This paper describes measurements of rainwater samples collected on Mount Tai in eastern China. INP concentrations with and without heat treatment were measured alongside ions in rainwater. INP concentrations in air were estimated based on an assumed cloud water content. Variation of INP concentrations is briefly examined across the seasons measured. An attempt is made to use PMF analysis to describe the aerosol populations associated with INP concentrations, though this piece of the work is critically flawed in my opinion, described in more detail below. Due to the lack of formal error analysis of the INP data and the flaws with the PMF analysis and interpretation, I do not believe this manuscript is publishable in it’s current form. More rigorous analysis could be done with the dataset described and a heavily changed version could be considered for a future submission.
Major comments:
Section 2.2 – There is no discussion of error analysis. There will be large errors associated with counting uncertainties in the INP measurements and the assumption of cloud water content. Additionally, field blanks should have been performed in order to assess the cleanliness of handling procedures of the rainwater samples. If dilutions were performed additional analysis of dilution water must be performed. INP concentrations would then need to be corrected for background INPs in field blanks and dilution water (if used), with uncertainties propagated. My understanding is that incorporating these uncertainties into the PMF analysis could drastically change the results of the manuscript.
Figure 3 and lines 249-258: The source profiles of many of your PMF factors are so similar that the identities of the different sources are extremely unclear. “mineral dust”, “soil dust”, “industrial emissions”, and “industrial emissions + biomass burning” are all very similar, and the differences between them are not significant enough to identify them with any confidence. The main quantities that could be used to identify many of these factors have not been measured, such as total organic content to distinguish “mineral dust” and “soil dust”, or levoglucosan to identify “biomass burning”.
Beyond these critical and related issues, there is a larger problem applying PMF analysis to INP concentrations. INP do not necessarily correlate with any of the major components measured. If this is the case, PMF analysis will distribute INP randomly across sources, and the interpretation of INP within the source profiles will be meaningless. Rigorous error analysis of PMF assignment uncertainties would be required to show that any interpretation of INP results within PMF analysis is meaningful.
Minor comments:
Line 45: Hoose 2010 reference is wildly mis-characterized, this statement needs to be reworked or removed. Something akin to “Simulations performed by Hoose et al., 2010, found that model outputs were broadly consistent with experimental measurements of INP concentrations when initialized with 77% mineral INP composition.” would be acceptable.
Lines 62-65: the assertation that background dust is overlooked as an INP source is easily refuted by many of your other citations in the introduction…
Line 67-68: many anthropogenic aerosols are very poor INPs, this unsupported claim should probably be removed.
Section 2.1: give sampling site coordinates and elevation.
Line 97-98: referencing WBF is odd here… glass slide is probably more important for preventing evaporation/condensation with room air. I recommend reworking.
Line 116: should be either “using ion chromatography” or using an ion chromatograph”
Line 141-142: justification of this treatment of missing data should be provided.
Line 143: “Q ratio” needs to be discussed prior to this in order for it to make sense. Also do you mean “As the number of PMF factors increase” instead of “As the PMF factor increases?”
Line 216: HR and HS aren’t defined acronyms, so while I understand which quantities they refer to it makes further discussion using these terms difficult to follow.
Figure 1.b) you only have two winter samples, the data isn’t really meaningful, I would recommend removing it.
Figure 2.b): is this calculated as mean(HR/HS) or as mean(HR)/mean(HS)? They would have different interpretations so clarification is required. Additionally, the uncertainties with these ratios will be very large and cannot be ignored.
Figure 3: Y axis on these figures has no units.
Citation: https://doi.org/10.5194/egusphere-2025-2855-RC1 -
RC2: 'Reply on RC1', Anonymous Referee #1, 24 Jul 2025
A small note after thinking on this further - a more rigorous way to tie together INP measurements with PMF factors would be to do the factorization excluding the INP measurements, then to calculate correlation coefficients between the factors and the INP measurements. Additionally, you may get different results depending on the INP activation temperature chosen, but correlations could be calculated for several temperatures. I suspect correlations will be limited and of low statistical significance, but this method is at least more robust.
Citation: https://doi.org/10.5194/egusphere-2025-2855-RC2
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RC2: 'Reply on RC1', Anonymous Referee #1, 24 Jul 2025
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RC3: 'Comment on egusphere-2025-2855', Anonymous Referee #2, 04 Aug 2025
This paper explores the significant role of long-range transported dust in influencing ice-nucleating particles (INPs) and cloud formation within the North China Plain. The authors analyzed precipitation samples from Mount Tai, a background site, over several months in 2021, revealing that INP concentrations were highest in spring. This seasonal increase was primarily linked to mineral dust transported from distant arid regions, a finding supported by satellite data and chemical analyses using a Positive Matrix Factorization model. The study concludes that this transported dust is a dominant factor in INP abundance, driving large-scale ice cloud formation and impacting aerosol-cloud interactions in continental areas.
This reviewer has several major and minor comments. While the study addresses an important topic relevant to the journal, the paper currently lacks sufficient empirical evidence, methodological detail, and analytical rigor to fully support its central claims regarding the dominant role of long-range transported dust in INP concentrations and cloud formation. Significant revisions, particularly in addressing the methodological gaps, substantiating claims with clearer data correlations, and refining the seasonality analysis, are deemed necessary before considering publication in ACP.
Major comments:
[1] How do the authors assess the background contribution of aerosols dry and wet depositions in precipitation samples during each sampling interval? How about the influence of evaporation? Is it accounted in total rainwater amount and estimation in Ninp? This reviewer finds the Milli-Q water background spectrum of the authors’ freezing assay in the supplemental material, but not the field blank background. These background data need to be presented in the main manuscript.
[2] Does the precipitation type (or intensity) have any influences on Ninp? Some previous studies of precipitation INP report it. Discussion should be provided in the main manuscript.[3] Seasonality analysis is thin in winter as there are only two samples analyzed, and this reviewer does not feel comfortable to see anyone claims seasonality with such a low number of samples.
[4] How does the authors segregate the local dust aerosol contribution from long-range ones? The approach should be explicitly clarified in the method section.
[5] L196-201: This part sounds very speculative. What evidence that the authors have to specify it’s biological? Heat labile INP analysis? Then, why heat sensitivity is not the highest in spring? Also, what evidence can the authors offer to refer to the feldspar involvement?
[6] L242-244: If dust is truly responsible for INP propensity, present the correlation between (long-range-transported) dust conc and Ninp in some ways. The authors can keep everything simple this way… If they cannot, please explain why not.
[7] Fig. 3: This paper does not describe how the composition of INPs was measured. L279- states the inclusion of mineral INP active at -16 dC. It could be biogenic or organic that come with minerals, right? Isn’t it misleading to cite Tobo et al.?[8] L276-280: This reviewer agrees with the statements. Then, the tile could be misleading. It could be local biogenic materials mixed with long-range-transported dust act as INPs, correct? What proof the authors have to explicitly say it’s long-range-transported dust in the title and elsewhere in the manuscript? The same applies to L313-315 – the authors may need to rephrase these parts.
[9] Sect. 3.4 is speculative and substantial revision seems necessary.
Minor comments:
L37-38: A reference is missing.
L78-80: Do the author mean aerosol composition? Or INP composition? How do they segregate and measure the INP of different sources, such as organic, biological, and minerals. If it’s really INP composition, please clarify the approach in the method section. Also, there are only two winter samples that the authors analyzed, and the sample size is too small to validate seasonality statistically. This reviewer highly recommends the author to rephrase seasonal variations and/or seasonality here and elsewhere applicable.
L89-93: The winter sample is poorly represented. Why? Please provide justifications. Less precipitation in winter? Logistics reason? Also, please clarify what the authors used for sampling intervals for individual samples. How did you preserve rainwater without impact of evaporation and dry/wet depositions?
L109-111: This seems a big assumption. Can the authors provide any evidence that CWC can be considered a constant for their sampling location and conditions throughout the year?
L115-116: How about water insoluble components? Most INPs are assumed to be water insoluble, providing surface for ice embryo to form. This circles back to the reviewer’s question listed above – have the authors looked into aerosol or INP composition?
L189 & Fig. 1 caption: Please rephrase urban to rural here and elsewhere the revision applies. The study location in Vepuri et al. is indeed a rural area. Also, rephrase “our measurements” to our Ninp measurements.
L213-: The method of heat application test needs to be described in Sect. 2.2.
L217- & Fig. 2a: It’s hard to interpret the data since Fig. 2a looks so busy. +/- 2.4 dC seems pretty substantial uncertainties. Absolutely, no exception is involved? The authors might revisit their data (hard to assess from the figure).
L226-227: Why in summer not spring? Sounds contradicting to L192-198 about the spring Ninp peak.
L276-280 (& L315): Polysaccharides or polymers (insoluble lignin and cellulose INPs)? Cite proper references if the latter is the case.
Fig. 4 & L286: The authors might want to offer individual sample interval specific data (definitely not monthly average unless there is strong justification that conditions are stable through a month).Citation: https://doi.org/10.5194/egusphere-2025-2855-RC3 -
RC4: 'Comment on egusphere-2025-2855', Anonymous Referee #3, 20 Aug 2025
Overview of data presented: The authors report on the collection of 69 precipitation samples at Mount Tai in the North China Plain from Feb to Nov 2021. The authors then report measurements of ice nucleation using a drop freezing technique GIGINA which uses 1 microL droplets. The freezing temperatures obtained were then converted to INPs in water and INPs in air, and subsequently correlated with ICP-MS and IC data from the precipitation. The authors ran a PMF model to source apportion the origin of the metals and ions in the precip samples.
Gaps to be addressed prior to publication:
It would be important to normalize the frozen fraction curves determined by the authors beyond dividing by the volume of the droplet (Eq 2). They authors could normalize to an ion or a metal they measured in their ICP-MS and IC dataset (like Fe to see enhancements?). The goal here is to understand the role of concentration in the reported INP measurements. Are the lower freezing samples simply more dilute (more rain)? Or because of fewer INPs? Another normalization for the authors to run would be to divide their Poisson distribution (similar to Eq 2) by the amount of water collected from the precipitation sample. Alternatively, can the authors run OC/EC or TOC measurements to have another measure to normalize to?
The PMF methodology is sound and well reported, however, I didn’t understand how the PMF analysis was then related to the INP results. How did the authors determine which INP was linked to which PMF factor? In other words, the precip sample analyzed are used for PMF, but each sample has one frozen fraction curve. How then are the sources of INP assigned? Did the authors assume that the same fraction of factors was to be applied to each sample/frozen fraction? If that’s the case, then I doubt this method is accurate as we know that INPs are not representative of bulk properties (Alden et al., 2025; Chen et al., 2018; Roy et al., 2021; Wu et al., 2019).
How is the seasonality of precipitation disentangled from the reported seasonality of INPs? In other words, is the seasonality of INPs reported in this manuscript simply the observation of precip seasonality at the site? (specifically related to the statement on lines 203-204)
Additional feedback to address on the methodology section:
Show all data collected in the SI. This request includes adding all the ICP-MS and IC data as well as the list the frozen fractions as a function of temperature plotted (Which is in any case a requirement for ACP).
Show all calibrations for the ICP-MS and the IC in the SI.
Line 90: 2 samples in the winter is difficult to extrapolate to seasonality, and box-and-whisker plots as well standard deviations cannot be made on 2 points, so this result would need to be revised throughout the manuscript. The authors could show just the 2 points for winter in their plots, but shouldn’t create statistics on these points. (Especially since the 2 frozen fractions for the winter time collection are about 5 degree different (Figure S5).
comment on whether the precipitation was rain or snow and how how much was collected, since dilution of the INPs could be impacting the results.
For GIGINA, is the freezing temperature identified before or after the pixel has changed colour? And why was that choice made?
Line 110: Fcloud-air) is 4 × 10−7 m3 needs a reference
Figure S4: the y-axis could be renamed “number of samples” instead of data number to be more precise.
Feedback to address on the results section:
Lines 179-181: could the authors explain what the importance of highlighting the onset of freezing is? How likely is the onset due to contamination?
Line 210-211-212 needs references
Line 212-213 about the heat treatment, see and discuss (Daily et al., 2022)
Line 215 also needs multiple references to support/authenticate.
Line 217-218 why did the authors focus on reporting the onset freezing temperature as a difference, is that onset due to contaminants instead of the population of INPs?
Section 3.3 would require more details on how the factors were named/assigned including additional references. Factor 1 and 2 need to be better described and supported. Industrial activities also need to be more precise (also considering the wealth of knowledge on Chinese PM source apportionment).
Paragraph starting at line 267 – I don’t understand how this analysis (PMF assigned to INP) was accomplished (see my criticism above).
Line 272 can benefit from additional soil references like (Alden et al., 2025; Knackstedt et al., 2018; Suski et al., 2018)
Figure 2a – the authors should check the math of their Poisson statistics when f_ice approaches 1 as there seems to be a cut off of the data in these plots. There are also two curves at -10 and -13oC that appear vertical (likely a data plotting mistake).
Figure 2c – data number should be replaced by sample number of FF curve to be more precise.
Figure 3 – it would be useful for the authors to highlight in this figure which elements/ions were used to assign the name of each factor.
References:
Alden, K. A., Bieber, P., Miller, A. J., Link, N., Murray, B. J., and Borduas-Dedekind, N.: The role of surface-active macromolecules in the ice-nucleating ability of lignin, Snomax, and agricultural soil extracts, Atmospheric Chem. Phys., 25, 6179–6195, https://doi.org/10.5194/acp-25-6179-2025, 2025.
Chen, J., Wu, Z., Augustin-Bauditz, S., Grawe, S., Hartmann, M., Pei, X., Liu, Z., Ji, D., and Wex, H.: Ice-nucleating particle concentrations unaffected by urban air pollution in Beijing, China, Atmospheric Chem. Phys., 18, 3523–3539, https://doi.org/10.5194/acp-18-3523-2018, 2018.
Daily, M. I., Tarn, M. D., Whale, T. F., and Murray, B. J.: An evaluation of the heat test for the ice-nucleating ability of minerals and biological material, Atmospheric Meas. Tech., 15, 2635–2665, https://doi.org/10.5194/amt-15-2635-2022, 2022.
Knackstedt, K. A., Moffett, B. F., Hartmann, S., Wex, H., Hill, T. C. J., Glasgo, E. D., Reitz, L. A., Augustin-Bauditz, S., Beall, B. F. N., Bullerjahn, G. S., Fröhlich-Nowoisky, J., Grawe, S., Lubitz, J., Stratmann, F., and McKay, R. M. L.: Terrestrial Origin for Abundant Riverine Nanoscale Ice-Nucleating Particles, Environ. Sci. Technol., 52, 12358–12367, https://doi.org/10.1021/acs.est.8b03881, 2018.
Roy, P., Mael, L. E., Hill, T. C. J., Mehndiratta, L., Peiker, G., House, M. L., DeMott, P. J., Grassian, V. H., and Dutcher, C. S.: Ice Nucleating Activity and Residual Particle Morphology of Bulk Seawater and Sea Surface Microlayer, ACS Earth Space Chem., 5, 1916–1928, https://doi.org/10.1021/acsearthspacechem.1c00175, 2021.
Suski, K. J., Hill, T. C. J., Levin, E. J. T., Miller, A., DeMott, P. J., and Kreidenweis, S. M.: Agricultural harvesting emissions of ice-nucleating particles, Atmospheric Chem. Phys., 18, 13755–13771, https://doi.org/10.5194/acp-18-13755-2018, 2018.
Wu, S., He, Z., Zang, J., Jin, S., Wang, Z., Wang, J., Yao, Y., and Wang, J.: Heterogeneous ice nucleation correlates with bulk-like interfacial water, Sci. Adv., 5, eaat9825, https://doi.org/10.1126/sciadv.aat9825, 2019.
Citation: https://doi.org/10.5194/egusphere-2025-2855-RC4
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