the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Thirty Years of Arctic Primary Marine Organic Aerosols: Patterns, Seasonal Dynamics, and Trends (1990–2019)
Abstract. Changing Arctic climate patterns have led to sea ice retreat, impacting ocean and atmospheric dynamics as well as marine ecosystems. Reduced sea ice cover likely enhances emissions of primary marine aerosols (sea salt and organic matter) via bubble bursting, potentially amplifying aerosol-cloud interactions. Moreover, primary marine organic aerosol (PMOA) production is closely linked to variations in marine biological productivity. This study examines the emission patterns, seasonality, and historical trends of key biomolecule groups (dissolved carboxylic acid-containing polysaccharides (PCHO), dissolved combined amino acids (DCAA), and polar lipids (PL)) within the Arctic Circle from 1990 to 2019. Surface ocean concentrations of these groups are derived from a biogeochemistry model and used as input to the aerosol-climate model ECHAM-HAM. Results indicate that the strong seasonality in biomolecule concentrations and PMOA emissions is driven by marine productivity and sea salt emissions. These quantities peak from May to September, coinciding with the phytoplankton bloom and seasonal sea ice minimum. Accumulated aerosol emissions and burdens over the Arctic increased by at least 7 % and 4 %, respectively, between the first and second halves of the study period. Summer trend analysis (June–August) reveals a strong reduction in sea ice that correlates with rising concentrations of organic groups in seawater in the inner Arctic. Positive emission anomalies have become more frequent over the past 15 years, indicating an overall upward trend. Average PMOA production has increased by 0.8 % per year since 1990. However, changes vary across biomolecular types and Arctic subregions, with PCHO showing the largest relative increase.
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RC1: 'Comment on egusphere-2025-2829', Anonymous Referee #1, 23 Jul 2025
The authors have undergone an extensive modeling study to understand the impact of several factors (sea ice extent, wind speed, SST) on the emission of speciated PMOA over the last several decades. They have done the analysis on a regional basis and searched for trends relating decreases in sea ice area to increases in PMOA emissions. As they discuss in section 5, all of this is very difficult to do considering the lack of PMOA seawater and atmospheric aerosol data, especially speciated, in the Arctic. Given the lack of data and the many uncertainties involved, the paper advances the understanding of factors controlling the emission, seasonality, and trends in Arctic PMOA.
Lines 184 – 185: Were open leads and melt ponds considered in estimating PMOA concentrations?
Table 1: Is an analysis of annually averaged data justified since there is so much seasonality in the factors controlling emission flux, burden and deposition?
Lines 318: Is there a reference for the SST correction factor for the SS emission flux?
Figure 5: The order of figures for e) and f) is different than what is stated in the caption.
Lines 339 – 341: It is stated on lines 301 – 302 that SS emissions from the model are a sum of both the accumulation and coarse modes. Earlier in the paper it says that PMOA fluxes are based on SS fluxes which are based on temperature. Yet it is stated here (lines 339 – 341) that the SST correction factor used in SS model simulations remains relatively similar for the accumulation mode. Is only the SST correction for the accumulation mode used for the speciated PMOA fluxes? It seems confusing if the speciated PMOA fluxes are coming from size independent (accumulation + coarse modes) SST emissions but size a dependent (accumulation mode only) SST correction.
Figure 8: Should this be Beaufort Sea for (b)?
Line 611: Change “along” to “alone”.
Citation: https://doi.org/10.5194/egusphere-2025-2829-RC1 -
RC2: 'Comment on egusphere-2025-2829', Anonymous Referee #2, 28 Jul 2025
- Abstract: what you mean by accumulated aerosol burden? It has not been introduced before so reader might find it difficult to understand what you mean by accumulated
- Abstract: These two lines almost say the same thing. Why you need both? “These quantities peak from May to September, coinciding with the phytoplankton bloom and seasonal sea ice minimum” and “Summer trend analysis (June–August) reveals a strong reduction in sea ice that correlates with rising concentrations of organic groups in seawater in the inner Arctic.”
- Abstract: This line says the rate of increase has decreased from 7 to 4% in the second half of the study. “ Accumulated aerosol emissions and burdens over the Arctic increased by at least 7% and 4%, respectively, between the first and second halves of the study period.”.
But this line says emission have become more frequent in last 15 years. “Positive emission anomalies have become more frequent over the past 15 years”
I think its contradicting as your trends say the emission rate has rather decreased from 7 to 4%
- Discuss why the rate of increase has decreased from 7% to 4%
- Abstract: “PCHO showing the largest relative increase” mention a number here
- Is the ‘peak’ season constant in a particular month for all the years? Mention this in the abstract if its changing or staying constant. Pernov (2022) mentioned peak MSA concentration will shift its peak month in next 50 years. It would be interesting to see if this shift in peak in other parameters has started showing in long term data already
- Line 43: “and the relevance of PMOA for cloud formation in the Arctic”: add citations
- Line 63: Cite Russell for carbohydrates. Also mention some literature on lipids.
- Line 88: Any particular reason why only polysaccharides, amino acids and lipids were chosen as components to represent PMOA? How much fraction of PMOA does each represent? “highly abundant” mention number here if possible
- Line 113: add citations about the accuracy of HAM model with the given assumptions. Do organics have large uncertainty in representation? If so, then taking results from this model and using them as input for another model will only lead to uncertainties. Its important to quantify this or at least cite.
- Line 6322; is it PMOA? Or POMA?
- Line 655: “This represents a relative change of 1.1, 1 and 0.8 %yr−1 for each group.” The group order mentioned is as follows: PLaer, DCAAaer and PCHOaer. So PCHO relative change is 0.8% which is less then PL and DCAA. Then why In line 662, it is mentioned that PCHO has the most prominent relative change?
- It would be nice to include how much % change in CCN or INP do you think these relative changes in PMOA will cause. I ask this because the relative increase is around 1% which seems pretty small. So I want to get an idea if this small change will affect CCN/INP significantly
- Line 585. Agreed but it would be nice if you could also add these observational data points wherever and whenever available with a different symbol in your figures. That way we get an idea of how accurate your model estimates are.
- Line 620: typo: remove ‘?’
- Figure 1: add different observation stations in the Arctic (for reader to get a clearer picture)
- Figure 3b. May be add residual as well to indicate how much fraction of total OMF is contributed by these three? Try including a stacked bar plot with errorbars for each month? Its nice when all components of OMF sums to 1.
- Line 250. What are your thoughts about SST? Why don’t you see how emissions at a particular location has changed with SST in the last 30 years? Add SST to Figure 8
19. Why not add years till 2024 to make the data more up-to-date, since it's modelling and doesnot require observation data availability?
Citation: https://doi.org/10.5194/egusphere-2025-2829-RC2
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