the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Mixing state, spatial distribution, sources and photochemical enhancement to sulfate formation of black carbon particles in the Arctic Ocean during summer
Abstract. Black carbon heats the atmosphere by absorbing solar radiation and regulates the radiation balance of the Earth. Specifically in the Arctic region, black carbon accelerates Arctic warming by simultaneously altering surface albedo. Nonetheless, assessing the climatic impacts of black carbon aerosols in the Arctic is challenging due to their considerable variability in temporal and spatial distribution, sources, and chemical composition. Black carbon particles (0.2–2 μm) in the Arctic Ocean were investigated using a ship-based single particle aerosol mass spectrometer from July to August 2017. In the central Arctic Ocean, near the Norwegian Sea-Iceland and the North Atlantic, biomass combustion is the predominant source of black carbon particles, constituting over 50 %, with a particularly high contribution exceeding 70 % in the central Arctic Ocean. Within the Chukchi Sea region, terrestrial transport from mid and low latitudes emerges as the primary source of black carbon particles, representing over 50 %, with biomass combustion and anthropogenic pollution sources each contributing around 25 %. Near Svalbard, biomass combustion sources and terrigenous transport stand out as the primary sources of black carbon particles, with their contributions being comparable. Furthermore, the ratio of sulfate to nitrate in black carbon particles was notably higher compared to that in sea salt particles. This ratio increased with elevated black carbon content and sunlight intensity, suggesting that Arctic black carbon particles substantially facilitated sulfate formation through photochemical processes. Such interactions could potentially modify the mixing state of Arctic black carbon particles and their radiative impacts.
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RC1: 'Comment on egusphere-2024-2706', Anonymous Referee #1, 12 Nov 2024
This study used single particle mass spectrometry to investigate the aerosol particles measured in a research cruise in the Arctic. The dataset was used in previous studies by Wang et al. (2022) and Su et al. (2024), focusing on iodine-containing and organic aerosol (OA) particles, respectively. The novelty of this study is intended to be the focus of black carbon (BC) particles. However, the BC identification is unconvincing: certain sub-types exhibit overlapping features with OA particles. For instance, the K-lev and K-Ni-CN are very similar to the OC-K and OC-S, respectively, as identified in Su et al. (2024). Additionally, Ni should show at m/z 58+ rather than 59+. Furthermore, the K-CN and Ca-NO3 should be classified as independent types, respectively. Consequently, classifying these particles as BC is inappropriate, and related analyses and discussions are therefore not valid.
Beyond these concerns, I have additional comments and suggestions on the interpretation and discussion of results. The conclusions on BC sources are difficult to support based solely on current findings, and further analysis, supplementary results, and/or additional references are needed. The discussion on photochemical processes is unconvincing. A positive relationship between SNR and SWGDN alone does not suggest the critical role of photochemistry; all daytime activities should be considered and discussed.
The potential contribution of this study falls within the scope of ACP; however, the current manuscript does not yet meet publication standards. Based on the comments above, a thorough rewrite is recommended before resubmission.
Ref:
Su, B., Zhang, G., Song, C., Liang, Y., Wang, L., Li, L., Zhou, Z., Yan, J., Wang, X., and Bi, X.: Submicron Organic Aerosol Types in the Summertime Arctic: Mixing State, Geographic Distribution, and Drivers, JGR Atmospheres, 129, e2024JD041061, https://doi.org/10.1029/2024JD041061, 2024.
Wang, L., Yan, J., Saiz-Lopez, A., Jiang, B., Yue, F., Yu, X., and Xie, Z.: Mixing state and distribution of iodine-containing particles in Arctic Ocean during summertime, Science of The Total Environment, 834, 155030, https://doi.org/10.1016/j.scitotenv.2022.155030, 2022.
Citation: https://doi.org/10.5194/egusphere-2024-2706-RC1 -
RC2: 'Comment on egusphere-2024-2706', Anonymous Referee #2, 14 Feb 2025
Wang et al. used a Single Particle Aerosol Mass Spectrometer (SPAMS) to sample Artic aerosol particles on R/V Xuelong. They focused on analyzing black carbon particles, as well as their mixing state and spatial distribution. They also claim that black carbon plays a role in promoting sulfate formation. While the data set is of high interest, the current analysis lacks details and is not technically sound. The authors should provide a more rigorous analysis and detailed interpretation in the revised manuscript. The manuscript requires major revision before it can be considered for publication.
Major Comment
- Summary of SPAMS measurements: The SPAMS have been deployed many times on R/V Xuelong for the Chinese Arctic Research Expedition. There are a handful of papers about the SPAMS measurement, not limited to Wang et al. (2022) and Su et al. (2024). I am unsure if black carbon measurement using SPAMS has been reported before. I suggest the author first summarize what has been done using SPAMS on R/V Xuelong in a table in the supplement and then outline the novelty of the work in the Introduction. This will greatly help the readers understand the progress of similar work using SPAMS.
- Mass spectra of particles: My understanding of the mass spectra in Figure 2 is that each of them represented the average mass spectra of particles clustered by ART-2a. If that is the case, error bars should be included to indicate the ranges of the ions for individual ions shown in the mass spectra. When grouping the ions, did the authors exclude what has been reported in Wang et al. (2022) and Su et al. (2024)? However, it appears to me that this is not the case. By visually comparing the mass spectra from this study with those in the Wang et al. (2022) and Su et al. (2024), I suspect there are some overlaps between the presented mass spectra:
- Fig 2b in Wang et al. (2022) looks like the mix of Fig 2a, f in this study;
- Fig 2a in Wang et al. (2022) has some degrees of similarities to Fig 2b in this study;
- Fig 2g OC-S in Su et al. (2024) is like the Fig 2c in this study;
- Fig 2d OC-K in Su et al. (2024) is like the Fig 2f in this study
More details should be provided about how black-carbon-containing particles were defined. In addition, the mass spectra in this study should be quantitatively compared with those reported in Wang et al. (2022) and Su et al. (2024), with the aid of contrast angle.
- What is the size distribution of the detected particles? What is the size-resolved distribution of the observed aerosol types?
- Section 3.2: The current analysis lacks details and is descriptive. The message presented in Figs 3 and 4 is too generalized. There is no information about the backward air mass trajectories. It is important to know the time spent on open water, land, and sea ice as well as the time spent within the mixing layers. Readers would be interested in the source region of individual aerosol types in each leg. Such analysis can be carried out using potential source contribution function (PSCF) or concentration-weighted trajectory (CWT). In addition, the information about the size-resolved aerosol types should be included, similar to those in Su et al. (2024)
- Section 3.3: The author speculates the high SNR was due to the sulfur-containing gases from marine organisms. Did the MSA signal coincide with the high SNR values?
- Lines 330 – 332: How did you exclude the anthropogenic sources? What were the major aerosol types left for the analysis?
Minor Comment
- Line 155: What was the in-line RH after the Nafion dryer?
- Section 2.2: How many particles have been sampled? I found two different numbers in Wang et al. (2022) and Su et al. (2024), which used the same data set as this study, i.e., “More than 2,000,000 particles” vs. “over 2.25 million particles”.
- Section 2.2: How was the influence of ship exhaust from the research vessel removed? I am concerned if the measurement has been affected by the ship exhaust from the research vessel, which can emit black carbon. I also don’t see any details about detecting ship exhaust in Wang et al. (2022) and Su et al. (2024).
- Figure 2: I will suggest the authors use different colors to differentiate different groups of ions (e.g., C-only ions, oxygenated C ions, metal ions)
- Section 3.3: Could you include a histogram illustrating the SNR?
- Lines 312 – 315: Could you please include the mass spectra of sea salt particles in the supplement?
- Line 334: What should be the SNR we should expect for aerosol types associated with biomass combustion air masses?
- Figure 5: Please color the data point left after excluding the anthropogenic sources (line 331). In addition, the correlation analysis should be carried out only with the data points after excluding the influence of anthropogenic sources.
- Figure 6: For certain groups, the hollow squares are outside the interquartile ranges. What does it mean? This may happen when there are a few very large values in a small sample size. Could you please clean the data properly before making the analysis? In addition, it will be better to use violin plots to visualize the distribution of the data and list the number of particles for the two particle types in each SWGDN group.
Technical Comment
- Line 109: higher and longer compared to what?
References:
Su, B., Zhang, G., Song, C., Liang, Y., Wang, L., Li, L., Zhou, Z., Yan, J., Wang, X., and Bi, X.: Submicron organic aerosol types in the summertime arctic: Mixing state, geographic distribution, and drivers, Journal of Geophysical Research: Atmospheres, 129, e2024JD041061, 2024.
Wang, L., Yan, J., Saiz-Lopez, A., Jiang, B., Yue, F., Yu, X., and Xie, Z.: Mixing state and distribution of iodine-containing particles in arctic ocean during summertime, Science of The Total Environment, 834, 155030, 2022.
Citation: https://doi.org/10.5194/egusphere-2024-2706-RC2
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