the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 07 Jan 2025 | Subsequently updated
Modelling the impact of anthropogenic aerosols on CCN concentrations over a rural boreal forest environment
Abstract. The radiative properties of clouds depend partially on the cloud droplet number concentration, which is determined by the concentration of cloud condensation nuclei (CCN) when the clouds are formed. In turn, CCN concentrations are determined by the atmospheric particle size distribution and their chemical composition. We use a novel Lagrangian modelling framework to examine the origins and history of gas and aerosol components observed at the boreal forest measurement site SMEAR II, and their potential to act as CCN. This framework combines: a) global emission datasets, b) backward trajectories from the FLEXible PARTicle dispersion model (FLEXPART) airmass dispersion model, c) a detailed description of atmospheric chemistry and aerosol dynamics from the Model to Simulate the Concentration of Organic Vapours, Sulphuric Acid and Aerosol Particles (SOSAA). We apply this SOSAA-FP (FP standing for FLEXPART) framework to simulate a period from March to October 2018 with one hour time resolution, focusing on the concentrations of CCN between 0.1–1.2 % maximum supersaturation as calculated by the κ-Köhler theory (with respective dry particle diameter of activation ca. 175–35 nm). We find that the model PM1 fraction of primary particles, sulfates and secondary organic aerosol correlate well with the observed organic aerosol and sulfate trends and explain most of the observed organic aerosol and sulfate PM1 mass. Our results show that primary particle emissions play a considerable role in CCN concentrations even at a rural site such as SMEAR II. Changes in atmospheric cluster formation rates had a relatively weak impact on the CCN concentrations in the sensitivity runs. Enhanced cluster formation increased (decreased) the CCN concentrations for the highest (lowest) maximum supersaturation. Without any cluster formation our modelled median CCN concentrations changed by –48 % and +23 % for supersaturations of 1.2 % and 0.1 %, respectively, whereas omitting primary particle emissions had a decreasing effect in all calculated CCN supersaturation classes (–82 % and –33 % decrease in median CCN of 1.2 % and 0.1 % supersaturation, respectively). While the enhancing effect of cluster formation to high supersaturation (i.e., small diameter) CCN concentrations is unsurprising, the weak sensitivity to cluster formation rates and the decreasing effect to lowest supersaturation CCN was unexpected, as was the strong influence of anthropogenic primary emissions. The Lagrangian model framework showed its power, as it was possible to trace down the causes behind the unexpected outcomes by comparing how the particle population evolved along the trajectories in different sensitivity tests.
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Version 3 | 20 Feb 2025
RC1: 'Comment on egusphere-2025-39', Anonymous Referee #1, 16 Jul 2025-
AC1:
'Reply on RC1', PETRI CLUSIUS, 18 Nov 2025
We would like to thank both reviewers for your constructive and valuable comments on our manuscript. in light of the comments, we have revised the text considerably. As the questions and comments from the two reviewers are sometimes related, and our edits address multiple points, the included attachment shows our response to both reviewers.
-
AC1:
'Reply on RC1', PETRI CLUSIUS, 18 Nov 2025
-
RC2:
'Comment on egusphere-2025-39', Anonymous Referee #2, 25 Aug 2025
This study employs a novel Lagrangian modeling framework to investigate the origins and history of gas and aerosol components observed at the boreal forest measurement site, and their potential to act as CCN. I am impressed by the efforts the authors made for very detailed analysis and evaluation of the simulation results, with hourly, diurnal, and also seasonal variations. This study is methodologically rigorous, supported by extensive data, and provides significant scientific insights, particularly in understanding the relative contributions of anthropogenic and biogenic emissions to CCN formation. I recommend the publication of this work once the authors address my comments below.
Major Comments:
Page 10, Line 260-263, for the parameterizations estimating the volatility of organic compounds, as there are several other methods, such as Li et al., (2016) and Yang et al., (2023), I am curious why the authors picked the method of Stolzenburg et al. (2022)? Isaacman-Vanwertz and Aumont (2021) concluded that considering the average and distribution of error, the combined Daumit-Li method (modified to consider nitrates) represented a nearly optimal approach to estimating vapor pressure from a molecular formula. In addition, did the simulated organic compounds in the model in this study include CHOS compounds? If CHOS compounds were available, I recommend the authors re-examine whether Stolzenburg et al. (2022) could predict the volatility of compounds containing sulfur.
Minor comments:
(1) The manuscript is written very long. I recommend the authors could somehow shorten it and highlight the significance of this study. For Section 4, the Discussion and Conclusions, I recommend separate discussion and conclusions. Section 4 is too long and too detailed. The readers would like to have a more straight conclusion and significance/ implication of this study.
(2) In the discussion, the authors had emphasized the importance of the heterogeneous chemistry and particle-phase chemistry in CCN formation. Besides it, the phase state of organic aerosols may also play an important role in CCN formation pathways (Reid et al., 2018; Shiraiwa et al., 2017), and online simulation of organic aerosol phase state has been coupled in several chemical transport models (Rasool et al., 2021; Zhang et al., 2024) which could be applied to examine its effect in CCN. The potential effect of phase state on cluster formation or gas-particle partitioning is recommended to be discussed.
(3) Page 25, Line 521, supersaturation classes of 0.4 % should be 0.6 % as Figure 9 showed.References:
1. Isaacman-VanWertz, G. and Aumont, B.: Impact of organic molecular structure on the estimation of atmospherically relevant physicochemical parameters, Atmos. Chem. Phys., 21, 6541-6563, 10.5194/acp-21-6541-2021, 2021.
2. Li, Y., Pöschl, U., and Shiraiwa, M.: Molecular corridors and parameterizations of volatility in the chemical evolution of organic aerosols, Atmos. Chem. Phys., 16, 3327-3344, 10.5194/acp-16-3327-2016, 2016.
3. Rasool, Q. Z., Shrivastava, M., Octaviani, M., Zhao, B., Gaudet, B., and Liu, Y.: Modeling Volatility-Based Aerosol Phase State Predictions in the Amazon Rainforest, ACS Earth and Space Chemistry, 5, 2910-2924, 10.1021/acsearthspacechem.1c00255, 2021.
4. Reid, J. P., Bertram, A. K., Topping, D. O., Laskin, A., Martin, S. T., Petters, M. D., Pope, F. D., and Rovelli, G.: The viscosity of atmospherically relevant organic particles, Nat. Commun., 9, 956, 10.1038/s41467-018-03027-z, 2018.
5. Shiraiwa, M., Li, Y., Tsimpidi, A. P., Karydis, V. A., Berkemeier, T., Pandis, S. N., Lelieveld, J., Koop, T., and Pöschl, U.: Global distribution of particle phase state in atmospheric secondary organic aerosols, Nat. Commun., 8, 15002, 10.1038/ncomms15002, 2017.
6. Yang, X., Ren, S., Wang, Y., Yang, G., Li, Y., Li, C., Wang, L., Yao, L., and Wang, L.: Volatility Parametrization of Low-Volatile Components of Ambient Organic Aerosols Based on Molecular Formulas, Environmental Science & Technology, 57, 11595-11604, 10.1021/acs.est.3c02073, 2023.
7. Zhang, Z., Li, Y., Ran, H., An, J., Qu, Y., Zhou, W., Xu, W., Hu, W., Xie, H., Wang, Z., Sun, Y., and Shiraiwa, M.: Simulated phase state and viscosity of secondary organic aerosols over China, Atmos. Chem. Phys., 24, 4809-4826, 10.5194/acp-24-4809-2024, 2024.Citation: https://doi.org/10.5194/egusphere-2025-39-RC2 -
AC2:
'Reply on RC2', PETRI CLUSIUS, 18 Nov 2025
We would like to thank both reviewers for your constructive and valuable comments on our manuscript. in light of the comments, we have revised the text considerably. As the questions and comments from the two reviewers are sometimes related, and our edits address multiple points, the included attachment shows our response to both reviewers.
-
AC2:
'Reply on RC2', PETRI CLUSIUS, 18 Nov 2025
-
Version 2 | 24 Jan 2025
-
Version 1 | 07 Jan 2025
Status: closed
-
Version 3 | 20 Feb 2025
RC1: 'Comment on egusphere-2025-39', Anonymous Referee #1, 16 Jul 2025The study employs a novel Lagrangian modeling framework (SOSAA-FP) to investigate the impact of anthropogenic aerosols on cloud condensation nuclei (CCN) concentrations in a boreal forest environment. By combining global emission datasets, backward trajectories, and detailed aerosol dynamics, the work provides insights into the relative contributions of primary emissions and secondary aerosol formation to CCN, highlighting the importance of anthropogenic influences even in rural settings. This approach advances understanding of aerosol-cloud interactions and their implications for climate modeling. Yet several questions should be clarified before its publication.
Major:
- Mechanisms Behind Weak Sensitivity to Cluster Formation Rates: The study finds that changes in atmospheric cluster formation rates have a relatively weak impact on CCN concentrations, which is unexpected given the importance of new particle formation (NPF) in aerosol dynamics. What specific mechanisms or feedbacks within the model could explain this weak sensitivity? For instance, how do the interactions between primary particles and newly formed clusters influence the overall CCN population? Understanding these mechanisms is crucial for refining models and improving predictions of aerosol impacts on climate.
- Role of Primary Emissions in CCN Formation: The results indicate that primary particle emissions play a substantial role in CCN concentrations even in a rural environment like SMEAR II. How do these findings reconcile with previous studies that emphasize the importance of secondary organic aerosols (SOA) in CCN formation? Specifically, what are the potential trade-offs between primary and secondary sources in different environmental conditions, and how might these findings influence the development of emission reduction strategies?
- Impact of BVOC Emissions on CCN Seasonality: The study demonstrates that BVOC emissions significantly affect CCN concentrations, especially during the growing season. However, the sensitivity of CCN to BVOC emissions is found to be highest in the largest CCN sizes. What are the implications of this finding for the role of BVOCs in cloud formation and climate feedback mechanisms? Additionally, how do seasonal variations in BVOC emissions influence the overall aerosol size distribution and CCN activity, and what are the potential feedbacks on regional climate?
- While the model shows reasonable agreement with observations for some components (e.g., organic aerosols and sulfates), significant discrepancies exist for others (e.g., nucleation-mode particles and gas-phase species like SO₂ and H₂SO₄). The paper does not thoroughly address the potential sources of these biases, such as uncertainties in emission inventories, simplified deposition schemes, or missing chemical pathways (e.g., aromatic oxidation). A more rigorous discussion of model limitations and their impact on CCN predictions is needed.
Minor:
- The text mentions the use of Welch’s t-test and Mood’s median test, but the results (e.g., p-values) are not included. Please provide the specific p-values or significance levels in the text to support the conclusions drawn from these tests.
- The color scheme used in Figure 7 for different supersaturation levels is not very distinct. Please use a more contrasting color palette to enhance readability.
- The reference list includes some inconsistencies in formatting (e.g., some references have full journal names while others are abbreviated). Please standardize the reference formatting to ensure consistency.
- Line 565: please change “backed with” to “supported by”.
Citation: https://doi.org/10.5194/egusphere-2025-39-RC1 -
AC1:
'Reply on RC1', PETRI CLUSIUS, 18 Nov 2025
We would like to thank both reviewers for your constructive and valuable comments on our manuscript. in light of the comments, we have revised the text considerably. As the questions and comments from the two reviewers are sometimes related, and our edits address multiple points, the included attachment shows our response to both reviewers.
-
RC2:
'Comment on egusphere-2025-39', Anonymous Referee #2, 25 Aug 2025
This study employs a novel Lagrangian modeling framework to investigate the origins and history of gas and aerosol components observed at the boreal forest measurement site, and their potential to act as CCN. I am impressed by the efforts the authors made for very detailed analysis and evaluation of the simulation results, with hourly, diurnal, and also seasonal variations. This study is methodologically rigorous, supported by extensive data, and provides significant scientific insights, particularly in understanding the relative contributions of anthropogenic and biogenic emissions to CCN formation. I recommend the publication of this work once the authors address my comments below.
Major Comments:
Page 10, Line 260-263, for the parameterizations estimating the volatility of organic compounds, as there are several other methods, such as Li et al., (2016) and Yang et al., (2023), I am curious why the authors picked the method of Stolzenburg et al. (2022)? Isaacman-Vanwertz and Aumont (2021) concluded that considering the average and distribution of error, the combined Daumit-Li method (modified to consider nitrates) represented a nearly optimal approach to estimating vapor pressure from a molecular formula. In addition, did the simulated organic compounds in the model in this study include CHOS compounds? If CHOS compounds were available, I recommend the authors re-examine whether Stolzenburg et al. (2022) could predict the volatility of compounds containing sulfur.
Minor comments:
(1) The manuscript is written very long. I recommend the authors could somehow shorten it and highlight the significance of this study. For Section 4, the Discussion and Conclusions, I recommend separate discussion and conclusions. Section 4 is too long and too detailed. The readers would like to have a more straight conclusion and significance/ implication of this study.
(2) In the discussion, the authors had emphasized the importance of the heterogeneous chemistry and particle-phase chemistry in CCN formation. Besides it, the phase state of organic aerosols may also play an important role in CCN formation pathways (Reid et al., 2018; Shiraiwa et al., 2017), and online simulation of organic aerosol phase state has been coupled in several chemical transport models (Rasool et al., 2021; Zhang et al., 2024) which could be applied to examine its effect in CCN. The potential effect of phase state on cluster formation or gas-particle partitioning is recommended to be discussed.
(3) Page 25, Line 521, supersaturation classes of 0.4 % should be 0.6 % as Figure 9 showed.References:
1. Isaacman-VanWertz, G. and Aumont, B.: Impact of organic molecular structure on the estimation of atmospherically relevant physicochemical parameters, Atmos. Chem. Phys., 21, 6541-6563, 10.5194/acp-21-6541-2021, 2021.
2. Li, Y., Pöschl, U., and Shiraiwa, M.: Molecular corridors and parameterizations of volatility in the chemical evolution of organic aerosols, Atmos. Chem. Phys., 16, 3327-3344, 10.5194/acp-16-3327-2016, 2016.
3. Rasool, Q. Z., Shrivastava, M., Octaviani, M., Zhao, B., Gaudet, B., and Liu, Y.: Modeling Volatility-Based Aerosol Phase State Predictions in the Amazon Rainforest, ACS Earth and Space Chemistry, 5, 2910-2924, 10.1021/acsearthspacechem.1c00255, 2021.
4. Reid, J. P., Bertram, A. K., Topping, D. O., Laskin, A., Martin, S. T., Petters, M. D., Pope, F. D., and Rovelli, G.: The viscosity of atmospherically relevant organic particles, Nat. Commun., 9, 956, 10.1038/s41467-018-03027-z, 2018.
5. Shiraiwa, M., Li, Y., Tsimpidi, A. P., Karydis, V. A., Berkemeier, T., Pandis, S. N., Lelieveld, J., Koop, T., and Pöschl, U.: Global distribution of particle phase state in atmospheric secondary organic aerosols, Nat. Commun., 8, 15002, 10.1038/ncomms15002, 2017.
6. Yang, X., Ren, S., Wang, Y., Yang, G., Li, Y., Li, C., Wang, L., Yao, L., and Wang, L.: Volatility Parametrization of Low-Volatile Components of Ambient Organic Aerosols Based on Molecular Formulas, Environmental Science & Technology, 57, 11595-11604, 10.1021/acs.est.3c02073, 2023.
7. Zhang, Z., Li, Y., Ran, H., An, J., Qu, Y., Zhou, W., Xu, W., Hu, W., Xie, H., Wang, Z., Sun, Y., and Shiraiwa, M.: Simulated phase state and viscosity of secondary organic aerosols over China, Atmos. Chem. Phys., 24, 4809-4826, 10.5194/acp-24-4809-2024, 2024.Citation: https://doi.org/10.5194/egusphere-2025-39-RC2 -
AC2:
'Reply on RC2', PETRI CLUSIUS, 18 Nov 2025
We would like to thank both reviewers for your constructive and valuable comments on our manuscript. in light of the comments, we have revised the text considerably. As the questions and comments from the two reviewers are sometimes related, and our edits address multiple points, the included attachment shows our response to both reviewers.
-
AC2:
'Reply on RC2', PETRI CLUSIUS, 18 Nov 2025
-
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The study employs a novel Lagrangian modeling framework (SOSAA-FP) to investigate the impact of anthropogenic aerosols on cloud condensation nuclei (CCN) concentrations in a boreal forest environment. By combining global emission datasets, backward trajectories, and detailed aerosol dynamics, the work provides insights into the relative contributions of primary emissions and secondary aerosol formation to CCN, highlighting the importance of anthropogenic influences even in rural settings. This approach advances understanding of aerosol-cloud interactions and their implications for climate modeling. Yet several questions should be clarified before its publication.
Major:
Minor: