the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 11 Jul 2024
Technical note: Quantified organic aerosol subsaturated hygroscopicity by a simple optical scatter monitor system through field measurements
Abstract. The hygroscopicity of organic aerosol (κOA) plays a crucial role in cloud droplet activation and aerosol-radiation interactions. This study investigated the viability of an optical scatter monitor system, featuring two nephelometric monitors (pDR-1500), to determine κOA, after knowing the aerosol chemical composition. This system was operated during a mobile lab deployment on Long Island in the summer of 2023, which was executed to coordinate with the Atmospheric Emissions and Reactions Observed from Megacities to Marine Areas (AEROMMA) field campaign. The derived κOA under subsaturated high humidity conditions (RH between 85 % and 95 %) were categorized based on different aerosol sources, including wildfire aerosol, urban aerosol, and aerosol from rural conditions. The κOA and the OA O:C ratio exhibited linear positive relationships for the urban aerosol and the aerosol from rural conditions, with a much higher slope (0.50 vs. 0.24) for the latter. However, there was no clear relationship between κOA and the OA O/C ratio observed during each period affected by wildfire plumes. The system proposed here could be widely applied alongside the current aerosol component measurement systems, providing valuable insights into the large-scale spatial and temporal variations of OA hygroscopicity.
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RC1: 'Comment on egusphere-2024-1390', Anonymous Referee #1, 26 Jul 2024
This paper reports on the use of what the authors claim is a simplified experimental system based on two nephelometers to determine the hygroscopicity parameter (Kappa) of ambient PM1 organic aerosol (Kappa_OA) for RH in the range of 85-95%. The system is essential two relatively low price nephelometers that are used to measure aerosol mass concentration, both measuring ambient air one at close to ambient conditions the other is dried. The results are contrasted for different aerosol sources and include comparison to the AMS-measured O/C ratio. The nephelometers also report mass concentration and so difference in the wet and dry nephs reported particle mass concentrations are interpreted as equal to the liquid water concentration due to the differences in the RH of the two nephs. There are some limitations noted by the authors, such as differences in particle size ranges when comparing masses from the dry neph to the AMS, that the AMS is not a comprehensive measurement of even PM1 mass, and uncertainty in the calibration of the nephs for converting scattering to mass. Furthermore, the sampling is done within an (I assume) airconditioned trailer which will result in biases when trying to determine actual ambient particle water concentrations, although that is not the goal of this study. For someone who has not read the first Zang et al paper on the pDRs, what these instruments actually are is not clear. Maybe a photo in the Supp, or a small description of what they are typically used for and stating the cost ($10k) early in the manuscript, not just in the Conclusions, would help to explain why this is claimed to be a simple method early in reading the paper.
One major issue lacking in this paper is a discussion comparing the specific method used here to the f(RH) method to infer particle water. Both use a wet and dry neph. The f(RH) method has a substantial history, yet is never noted in this work (see description in Guo et al and a list of references therein; www.atmos-chem-phys.net/15/5211/2015/ )
Overall, the paper is of interest and suitable for publication in ACP but there are unclear sections in this paper that need to be addressed.
Specific comments
In section 2.2 System setup, lines 93 to 100 where particle losses in sample lines are discussed it would be useful to add the flow Reynolds numbers. For line 99, what particle sizes does this less than 1% loss apply to?
Line 91, is RH of 45% sufficient to assume that particles do not contain water, which is, I believe, the assumption here in this calculation?
Line 118, what about the fact that the AMS only measures non-refractory species, so it is not a comprehensive measurement of particle mass concentration, not even considering the size of particles sampled. Ie, this should also be noted in this part of the paper, since it is also discussed later on, along with the PM1 vs PM2.5 issue.
Line 140, why is the chemical composition data not used to estimate density of OA instead of assuming a constant value of 1.4 g/cm3.
Line 145, note that if these data are used to estimate ambient air LWC in this study there are issues with the ambient measurements (wet) being made indoors. This is why many past studies on using HTDMA or f(RH) run the ambient (wet) instrument outdoors.
Line 150, what is the basis for assuming a constant fine/coarse mode mass ratio? Doesn’t the fine and coarse mode chemical composition vary? Not sure how one assesses the impact of this assumption. The reasoning in lines 149 to 152 (“ By simply assuming a constant …”) is not clear. My interpretation is that the authors assume that the chemical composition of the coarse and fine modes is the same and invariant throughout the study and so the ratio of particle water in the fine and coarse modes will equal the ratio of fine and coarse mode dry mass concentration. This assumes no nonlinearities, such as the Kelvin effect.
Line 163, the standard deviation is given as 0.08, but this is somewhat meaningless without knowing the typical (mean) Kappa_OA. Maybe the range in the standard deviation divided by the mean could be given for all the bins to get an idea of the relative error estimated by this method.
In Fig 2b define what the given ratios are (slope?). The associated text is not clear (lines 172-174, ie what is the 2.5 referring to, and [24].
Fig 3, the x-axis has no label. This is somewhat stated in the fig caption but seems poor form. What is the year? Are the data shown in Fig 3 added (stacked) or each (ALW_OA and ALW_IOA) go to zero on the y axis?
Line 195, is derived Kappa_OA from equation 3, if so state it.
Typo in line 200 ,,
Line 196 and Fig 4b, define mass concentration, ie is it dry PM1? (Not sure what total mass concentration means).
Line 214 to 216. Doesn’t burning conditions, smoldering/flaming affect Kappa_OA, or is this washed out the in highly averaged nature of smoke transported over long distances?
Would it be useful to plot Kappa_OA to Mass_ALWOA? They are related by equation 3.
Line 237 starting with “ It also shows…. What is being referred to, Fig 5b? (change to: It shows to Fig 5b shows…?
First line of Conclusions, why not call them inexpensive single wavelength nephelometers instead of optical scattering systems, the latter could include a single particle optical particle counter, which these are not (I assume).
Line 263, not only is the slope different but the magnitude is significantly different between urban and rural (the curves are nowhere near overlapping). Doesn’t this have implications for using O/C to estimate Kappa_OA.
Line 279, typo, varication?
A final comment: It is curious to me why one does not compare water soluble organic carbon to Kappa_OA.
Lines 277 and on where it is noted that there the measurements were not continuous…. This is not clear. The schematic shows that the wet measurement was straight ambient. It then seems that the gaps in the data are due to only periods of high ambient RH were analyzed in this study. So the authors are suggesting that adding a humidification system to the ambient leg to maintain an RH in a specific range, such as 85-95% would allow continuous measurements – is this the point?
Citation: https://doi.org/10.5194/egusphere-2024-1390-RC1 -
AC2: 'Reply on RC1', Jie Zhang, 01 Oct 2024
We thank the reviewer #1 for the detailed, helpful, and overall supportive comments. We have revised the manuscript to account for each comment. Responses to the individual comments are provided below. The supplement is our point-by-point response to each comment. Author responses are in Bold black. Modifications to the manuscript are in our normal font. Line numbers in the response correspond to those in the revised manuscript text file (tracked version).
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AC2: 'Reply on RC1', Jie Zhang, 01 Oct 2024
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CC1: 'Comment on egusphere-2024-1390', Paul Zieger, 26 Jul 2024
This is an interesting approach to study and determine the hygroscopic growth of organic aerosol. The authors do a good job in using field observation of AMS and nephelometer data to determine kappa values for organic aerosol, and I enjoyed reading the manuscript. However, there is one major shortcoming which should be addressed in a revised version: The current work (here published as a technical note) misses a solid calibration and error analysis (see e.g., Titos et al., 2016 and Zieger et al., 2013). This should include a calibration with substances of known hygroscopic growth (e.g., Fierz et al., 2010), including organic substances which are studied here. Otherwise there is the risk that the retrieved kappa values, although they nicely correlate with the O:C ratio, just remain estimates.
Fierz-Schmidhauser, R., Zieger, P., Wehrle, G., Jefferson, A., Ogren, J.A., Baltensperger, U. and Weingartner, E., 2010. Measurement of relative humidity dependent light scattering of aerosols. Atmospheric Measurement Techniques, 3(1), pp.39-50.Titos, G., Cazorla, A., Zieger, P., Andrews, E., Lyamani, H., Granados-Muñoz, M.J., Olmo, F.J. and Alados-Arboledas, L., 2016. Effect of hygroscopic growth on the aerosol light-scattering coefficient: A review of measurements, techniques and error sources. Atmospheric Environment, 141, pp.494-507.Zieger, P., Fierz-Schmidhauser, R., Weingartner, E. and Baltensperger, 2013. Effects of relative humidity on aerosol light scattering: results from different European sites. Atmospheric Chemistry and Physics, 13(21), pp.10609-10631.Citation: https://doi.org/10.5194/egusphere-2024-1390-CC1 -
AC4: 'Reply on CC1', Jie Zhang, 01 Oct 2024
Dear Dr. Zieger,
Thank you so much for your comments, and we totally agree that lab calibration and verification of this method using the substances with known hygroscopic parameters is critical important. We proposed a potential design for this type of test, but it could not be realized in our lab at this time due to limited resources. To made up this to some extent, we add more detailed discussion in the text with all reference being cited and including the proposed instruments set-up, as shown in the supplement.
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AC4: 'Reply on CC1', Jie Zhang, 01 Oct 2024
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RC2: 'Comment on egusphere-2024-1390', Anonymous Referee #2, 29 Jul 2024
General comments:
This manuscript presents and discusses results obtained via a relatively low-cost method for quantifying the hygroscopicity of organic aerosol. Two pDRs (a single wavelength nephelometer-like instrument) are operated along with an AMS to estimate the mass of water taken up by submicron organic aerosol particles. By assuming a density of the organics (among other assumptions), the hygroscopicity of the organics (K_OA) is estimated. K_OA is evaluated and discussed in the context of O:C ratio as well as for air masses of different origin.
Overall the paper is easy to follow and concise. The analysis is enjoyable to read. It is suitable for publication in ACP, and there are just a handful of assumptions that I would like to see discussed and/or explained in greater detail.
Specific comments:
Line 91 - I was a bit surprised to see 45% RH used as a "dry" humidity where the pDR_dry and pDR_wet were compared (well, really just < 45% conditions... but RH is not measured below this value). I know of a few organic acids that do not display deliquescence and gradually take up water with increasing RH (e.g., Pope et al., 2010), and there are likely other organics I am not aware of. Do you have a reason to believe <45% RH was sufficient for the comparison you were after? Was the composition mostly dominated by inorganic species that would deliquesce at RH values > 45%? Perhaps you might want to discuss this possibility for organics to take up a certain amount of water with increasing RH and how that may affect this comparison between the pDRs.
Line 101 - I'm unfamiliar with the pDR and would appreciate a bit more discussion. I see that it uses 880 nm as the wavelength. That's pretty high considering that you are interested in using it to study the hygroscopicity of submicron particles, right? Furthermore, it seems that the instrument was originally calibrated with Arizona Road Dust, which sounds like it would consist of relatively large particles (mostly > 1um?) , although that's just a guess/assumption I'm making. Anyway, due to the larger wavelength it would be great if you could briefly discuss the challenges and/or any previously determined competence of the pDR for analyzing submicron particles. Have results from the pDR ever been compared to those from a nephelometer operating at a comparable wavelengthg and size range of particles?
Fig. 1: Small thing, but it says "calibrate factor" in the figure, whereas in the text it is always referred to as "calibration factor." I suggest being consistent if you can!
Line 127 - I am trying to wrap my brain around the application of the fine mode calibration factor (determined by the ratio of masses measured by the pDR_dry and AMS) to the dry and wet pDR mass concentrations. Maybe a bit more discussion would help me (and potentially others). The calibration factor is based on a difference in dry aerosol mass between the pDR and the AMS, which will most likely have a density > 1 g cm-3 and refractive index greater than 1.33. However, it sounds like much of the mass measured by the pDR_wet can come from water, which has a lower density (1 g cm-3) and refractive index (1.33) than most dry aerosol components. I'm curious if the calibration factor is robust in situations when much of the mass measured by the pDR_wet is from water? I understand you need some way to correct pDR_wet, but maybe you could discuss how the calibration factor is based on dry aerosol and may not apply perfectly when needing to correct a mass measurement (from pDR_wet) that is potentially largely composed of water. And if it is not as big of a deal as I am making it please help me understand why, thanks.
Line 136 - I see that you assume a single density for the organic species. I understand you have to assume a density because you do not have size-resolved information about your submicron organic aerosols. As you showed in your study, properties of organic aerosol can be largely different depending on the source, and I'm sure organic densities are subject to this variation (don't have citations off the top of my head, but I'm sure they are out there). Perhaps you can at least mention the organic density likely spanned a range and explain why you chose 1.4 g cm-3 (i.e., at least provide a citation as I don't believe there is one now).
Line 149-152 - I was a little confused by this stated assumption: "By simply assuming a constant mass ratio for the chemical composition of fine-mode and coarse-mode particles, the ratio of MALW associated with fine-mode particles to that associated with coarse-mode particles will correspond to the dry aerosol mass concentration of each mode."
Perhaps I am not following, but I thought this study was focused solely on submicron mass because the pDR_dry mass is corrected to be equal that measured by the AMS, which is certainly submicron. And then pDR_wet is also corrected by that same correction factor, although the pDR_wet understandably samples up to 2.5 microns to be able to capture the hygroscopic growth of dry submicron particles (sampled by the pDR_dry and AMS). So how would the coarse mode be represented in this study? I was thinking it got "corrected out" by aligning everything to the AMS mass...
Second, this assumption makes me nervous: "the ratio of MALW associated with fine-mode particles to that associated with coarse-mode particles will correspond to the dry aerosol mass concentration of each mode."
I would expect the fine and coarse mode to take up water differently, largely because they are typically composed of different chemical components. For example, see Fig. 10B in AzadiAghdam et al. (2019), where derived kappa values are not consistent with particle size and are largely sensitive to the presence of sea salt and certain inorganic species, which are typically found in varying amounts between the fine and coarse mode.
That all being said, can you provide more insight into why you believe the assumption you are making is a good one? What is it founded upon? Can you provide a reference or justification? Thanks.
Line 189 - Small thing, but it would be clearer for me if you explicitly wrote "percentile" with the [25%-75%] or some other explanation for what this range is referring to.
Line 196-197 - I was curious about your categorization of the different HYPSLIT back-trajectories. Was this totally subjective or was there more of a process to it? I ask since the lowest-level back-trajectory (red line) on 06 July 2023 in Fig. S3 appears to stay near large metropolitan areas for much of the time before eventually moving out into a more (relatively) rural part of New York. I'm just curious if back-trajectories heading in the northwest direction (or from over the Atlantic Ocean as in panel for 25 August 2023) from the measurement site were considered rural no matter what or if there were more criteria to the classifications?
Line 279 - The fact that you were not able to calibrate with particles of known composition (and therefore known kappa values) seems like a big deal to me and significant limitation to the study, especially as you are trying to present an alternative and lower-cost method to what has been often used in the past. I find it interesting that the inability to calibrate was not mentioned until the Conclusions section. I would strongly suggest moving this information to the Methods section where you previously were discussing the various limitations associated with the proposed method (the paragraphs right before the Results and Discussion). I appreciate that you propose an alternative instrument set-up where the lab calibration would be possible.
Also is "varication" supposed to be "verification" in Line 279?
Citations for works mentioned above:
Pope, F. D., Dennis-Smither, B. J., Griffiths, P. T., Clegg, S. L., & Cox, R. A. (2010). Studies of single aerosol particles containing malonic acid, glutaric acid, and their mixtures with sodium chloride. I. Hygroscopic growth. The Journal of Physical Chemistry A, 114(16), 5335-5341.
AzadiAghdam, M., Braun, R. A., Edwards, E. L., Bañaga, P. A., Cruz, M. T., Betito, G., ... & Sorooshian, A. (2019). On the nature of sea salt aerosol at a coastal megacity: Insights from Manila, Philippines in Southeast Asia. Atmospheric Environment, 216, 116922.
Citation: https://doi.org/10.5194/egusphere-2024-1390-RC2 -
AC1: 'Reply on RC2', Jie Zhang, 01 Oct 2024
We sincerely thank the reviewer #2 for his/her thorough and thoughtful comments that helped improve our manuscript substantially. We have read all comments carefully and have responded to them each in turn. The supplement is our point-by-point responses to reviewer #2 comments. Author responses are in bold black. Modifications to the manuscript are in normal front. Line numbers in the response correspond to those in the revised manuscript text file (tracked version).
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AC1: 'Reply on RC2', Jie Zhang, 01 Oct 2024
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CC2: 'Comment on egusphere-2024-1390', Ye Kuang, 30 Jul 2024
This is a nice try using a cost-effective optical method for studying aerosol hygroscopicity, not the relatively more expensive multiwavelength nephelometer system.
Using measurements of dry and wet neph to infer aerosol liquid water content (Guo et al., 2015;Kuang et al., 2018), hygroscopicity (Kuang et al., 2017) as well as organic hygroscopicity (Kuang et al., 2020;Kuang et al., 2021) are already done and fully discussed before. The method proposed in this manuscript is interesting and differ a little bit with previous studies, a discussion comparing the specific method used here with previous studies should be included, however, never noted in this work. Also, the concept of using the ambient air as the sample air of wet neph is also introduced in Qiao et al. (2024). Optical methods are promising and cost-effective methods in investigating aerosol water and hygroscopicity, however, error analysis should be included.
Guo, H., Xu, L., Bougiatioti, A., Cerully, K. M., Capps, S. L., Hite Jr, J. R., Carlton, A. G., Lee, S. H., Bergin, M. H., Ng, N. L., Nenes, A., and Weber, R. J.: Fine-particle water and pH in the southeastern United States, Atmos. Chem. Phys., 15, 5211-5228, 10.5194/acp-15-5211-2015, 2015.
Kuang, Y., Zhao, C., Tao, J., Bian, Y., Ma, N., and Zhao, G.: A novel method for deriving the aerosol hygroscopicity parameter based only on measurements from a humidified nephelometer system, Atmos. Chem. Phys., 17, 6651-6662, 10.5194/acp-17-6651-2017, 2017.
Kuang, Y., Zhao, C. S., Zhao, G., Tao, J. C., Xu, W., Ma, N., and Bian, Y. X.: A novel method for calculating ambient aerosol liquid water content based on measurements of a humidified nephelometer system, Atmospheric Measurement Techniques, 11, 2967-2982, 10.5194/amt-11-2967-2018, 2018.
Kuang, Y., He, Y., Xu, W., Zhao, P., Cheng, Y., Zhao, G., Tao, J., Ma, N., Su, H., Zhang, Y., Sun, J., Cheng, P., Yang, W., Zhang, S., Wu, C., Sun, Y., and Zhao, C.: Distinct diurnal variation in organic aerosol hygroscopicity and its relationship with oxygenated organic aerosol, Atmos. Chem. Phys., 20, 865-880, 10.5194/acp-20-865-2020, 2020.
Kuang, Y., Huang, S., Xue, B., Luo, B., Song, Q., Chen, W., Hu, W., Li, W., Zhao, P., Cai, M., Peng, Y., Qi, J., Li, T., Wang, S., Chen, D., Yue, D., Yuan, B., and Shao, M.: Contrasting effects of secondary organic aerosol formations on organic aerosol hygroscopicity, Atmos. Chem. Phys., 21, 10375-10391, 10.5194/acp-21-10375-2021, 2021.
Qiao, H., Kuang, Y., Yuan, F., Liu, L., Zhai, M., Xu, H., Zou, Y., Deng, T., and Deng, X.: Unlocking the Mystery of Aerosol Phase Transitions Governed by Relative Humidity History Through an Advanced Outdoor Nephelometer System, Geophysical Research Letters, 51, e2023GL107179, https://doi.org/10.1029/2023GL107179, 2024.
Citation: https://doi.org/10.5194/egusphere-2024-1390-CC2 - AC3: 'Reply on CC2', Jie Zhang, 01 Oct 2024
Status: closed
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RC1: 'Comment on egusphere-2024-1390', Anonymous Referee #1, 26 Jul 2024
This paper reports on the use of what the authors claim is a simplified experimental system based on two nephelometers to determine the hygroscopicity parameter (Kappa) of ambient PM1 organic aerosol (Kappa_OA) for RH in the range of 85-95%. The system is essential two relatively low price nephelometers that are used to measure aerosol mass concentration, both measuring ambient air one at close to ambient conditions the other is dried. The results are contrasted for different aerosol sources and include comparison to the AMS-measured O/C ratio. The nephelometers also report mass concentration and so difference in the wet and dry nephs reported particle mass concentrations are interpreted as equal to the liquid water concentration due to the differences in the RH of the two nephs. There are some limitations noted by the authors, such as differences in particle size ranges when comparing masses from the dry neph to the AMS, that the AMS is not a comprehensive measurement of even PM1 mass, and uncertainty in the calibration of the nephs for converting scattering to mass. Furthermore, the sampling is done within an (I assume) airconditioned trailer which will result in biases when trying to determine actual ambient particle water concentrations, although that is not the goal of this study. For someone who has not read the first Zang et al paper on the pDRs, what these instruments actually are is not clear. Maybe a photo in the Supp, or a small description of what they are typically used for and stating the cost ($10k) early in the manuscript, not just in the Conclusions, would help to explain why this is claimed to be a simple method early in reading the paper.
One major issue lacking in this paper is a discussion comparing the specific method used here to the f(RH) method to infer particle water. Both use a wet and dry neph. The f(RH) method has a substantial history, yet is never noted in this work (see description in Guo et al and a list of references therein; www.atmos-chem-phys.net/15/5211/2015/ )
Overall, the paper is of interest and suitable for publication in ACP but there are unclear sections in this paper that need to be addressed.
Specific comments
In section 2.2 System setup, lines 93 to 100 where particle losses in sample lines are discussed it would be useful to add the flow Reynolds numbers. For line 99, what particle sizes does this less than 1% loss apply to?
Line 91, is RH of 45% sufficient to assume that particles do not contain water, which is, I believe, the assumption here in this calculation?
Line 118, what about the fact that the AMS only measures non-refractory species, so it is not a comprehensive measurement of particle mass concentration, not even considering the size of particles sampled. Ie, this should also be noted in this part of the paper, since it is also discussed later on, along with the PM1 vs PM2.5 issue.
Line 140, why is the chemical composition data not used to estimate density of OA instead of assuming a constant value of 1.4 g/cm3.
Line 145, note that if these data are used to estimate ambient air LWC in this study there are issues with the ambient measurements (wet) being made indoors. This is why many past studies on using HTDMA or f(RH) run the ambient (wet) instrument outdoors.
Line 150, what is the basis for assuming a constant fine/coarse mode mass ratio? Doesn’t the fine and coarse mode chemical composition vary? Not sure how one assesses the impact of this assumption. The reasoning in lines 149 to 152 (“ By simply assuming a constant …”) is not clear. My interpretation is that the authors assume that the chemical composition of the coarse and fine modes is the same and invariant throughout the study and so the ratio of particle water in the fine and coarse modes will equal the ratio of fine and coarse mode dry mass concentration. This assumes no nonlinearities, such as the Kelvin effect.
Line 163, the standard deviation is given as 0.08, but this is somewhat meaningless without knowing the typical (mean) Kappa_OA. Maybe the range in the standard deviation divided by the mean could be given for all the bins to get an idea of the relative error estimated by this method.
In Fig 2b define what the given ratios are (slope?). The associated text is not clear (lines 172-174, ie what is the 2.5 referring to, and [24].
Fig 3, the x-axis has no label. This is somewhat stated in the fig caption but seems poor form. What is the year? Are the data shown in Fig 3 added (stacked) or each (ALW_OA and ALW_IOA) go to zero on the y axis?
Line 195, is derived Kappa_OA from equation 3, if so state it.
Typo in line 200 ,,
Line 196 and Fig 4b, define mass concentration, ie is it dry PM1? (Not sure what total mass concentration means).
Line 214 to 216. Doesn’t burning conditions, smoldering/flaming affect Kappa_OA, or is this washed out the in highly averaged nature of smoke transported over long distances?
Would it be useful to plot Kappa_OA to Mass_ALWOA? They are related by equation 3.
Line 237 starting with “ It also shows…. What is being referred to, Fig 5b? (change to: It shows to Fig 5b shows…?
First line of Conclusions, why not call them inexpensive single wavelength nephelometers instead of optical scattering systems, the latter could include a single particle optical particle counter, which these are not (I assume).
Line 263, not only is the slope different but the magnitude is significantly different between urban and rural (the curves are nowhere near overlapping). Doesn’t this have implications for using O/C to estimate Kappa_OA.
Line 279, typo, varication?
A final comment: It is curious to me why one does not compare water soluble organic carbon to Kappa_OA.
Lines 277 and on where it is noted that there the measurements were not continuous…. This is not clear. The schematic shows that the wet measurement was straight ambient. It then seems that the gaps in the data are due to only periods of high ambient RH were analyzed in this study. So the authors are suggesting that adding a humidification system to the ambient leg to maintain an RH in a specific range, such as 85-95% would allow continuous measurements – is this the point?
Citation: https://doi.org/10.5194/egusphere-2024-1390-RC1 -
AC2: 'Reply on RC1', Jie Zhang, 01 Oct 2024
We thank the reviewer #1 for the detailed, helpful, and overall supportive comments. We have revised the manuscript to account for each comment. Responses to the individual comments are provided below. The supplement is our point-by-point response to each comment. Author responses are in Bold black. Modifications to the manuscript are in our normal font. Line numbers in the response correspond to those in the revised manuscript text file (tracked version).
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AC2: 'Reply on RC1', Jie Zhang, 01 Oct 2024
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CC1: 'Comment on egusphere-2024-1390', Paul Zieger, 26 Jul 2024
This is an interesting approach to study and determine the hygroscopic growth of organic aerosol. The authors do a good job in using field observation of AMS and nephelometer data to determine kappa values for organic aerosol, and I enjoyed reading the manuscript. However, there is one major shortcoming which should be addressed in a revised version: The current work (here published as a technical note) misses a solid calibration and error analysis (see e.g., Titos et al., 2016 and Zieger et al., 2013). This should include a calibration with substances of known hygroscopic growth (e.g., Fierz et al., 2010), including organic substances which are studied here. Otherwise there is the risk that the retrieved kappa values, although they nicely correlate with the O:C ratio, just remain estimates.
Fierz-Schmidhauser, R., Zieger, P., Wehrle, G., Jefferson, A., Ogren, J.A., Baltensperger, U. and Weingartner, E., 2010. Measurement of relative humidity dependent light scattering of aerosols. Atmospheric Measurement Techniques, 3(1), pp.39-50.Titos, G., Cazorla, A., Zieger, P., Andrews, E., Lyamani, H., Granados-Muñoz, M.J., Olmo, F.J. and Alados-Arboledas, L., 2016. Effect of hygroscopic growth on the aerosol light-scattering coefficient: A review of measurements, techniques and error sources. Atmospheric Environment, 141, pp.494-507.Zieger, P., Fierz-Schmidhauser, R., Weingartner, E. and Baltensperger, 2013. Effects of relative humidity on aerosol light scattering: results from different European sites. Atmospheric Chemistry and Physics, 13(21), pp.10609-10631.Citation: https://doi.org/10.5194/egusphere-2024-1390-CC1 -
AC4: 'Reply on CC1', Jie Zhang, 01 Oct 2024
Dear Dr. Zieger,
Thank you so much for your comments, and we totally agree that lab calibration and verification of this method using the substances with known hygroscopic parameters is critical important. We proposed a potential design for this type of test, but it could not be realized in our lab at this time due to limited resources. To made up this to some extent, we add more detailed discussion in the text with all reference being cited and including the proposed instruments set-up, as shown in the supplement.
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AC4: 'Reply on CC1', Jie Zhang, 01 Oct 2024
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RC2: 'Comment on egusphere-2024-1390', Anonymous Referee #2, 29 Jul 2024
General comments:
This manuscript presents and discusses results obtained via a relatively low-cost method for quantifying the hygroscopicity of organic aerosol. Two pDRs (a single wavelength nephelometer-like instrument) are operated along with an AMS to estimate the mass of water taken up by submicron organic aerosol particles. By assuming a density of the organics (among other assumptions), the hygroscopicity of the organics (K_OA) is estimated. K_OA is evaluated and discussed in the context of O:C ratio as well as for air masses of different origin.
Overall the paper is easy to follow and concise. The analysis is enjoyable to read. It is suitable for publication in ACP, and there are just a handful of assumptions that I would like to see discussed and/or explained in greater detail.
Specific comments:
Line 91 - I was a bit surprised to see 45% RH used as a "dry" humidity where the pDR_dry and pDR_wet were compared (well, really just < 45% conditions... but RH is not measured below this value). I know of a few organic acids that do not display deliquescence and gradually take up water with increasing RH (e.g., Pope et al., 2010), and there are likely other organics I am not aware of. Do you have a reason to believe <45% RH was sufficient for the comparison you were after? Was the composition mostly dominated by inorganic species that would deliquesce at RH values > 45%? Perhaps you might want to discuss this possibility for organics to take up a certain amount of water with increasing RH and how that may affect this comparison between the pDRs.
Line 101 - I'm unfamiliar with the pDR and would appreciate a bit more discussion. I see that it uses 880 nm as the wavelength. That's pretty high considering that you are interested in using it to study the hygroscopicity of submicron particles, right? Furthermore, it seems that the instrument was originally calibrated with Arizona Road Dust, which sounds like it would consist of relatively large particles (mostly > 1um?) , although that's just a guess/assumption I'm making. Anyway, due to the larger wavelength it would be great if you could briefly discuss the challenges and/or any previously determined competence of the pDR for analyzing submicron particles. Have results from the pDR ever been compared to those from a nephelometer operating at a comparable wavelengthg and size range of particles?
Fig. 1: Small thing, but it says "calibrate factor" in the figure, whereas in the text it is always referred to as "calibration factor." I suggest being consistent if you can!
Line 127 - I am trying to wrap my brain around the application of the fine mode calibration factor (determined by the ratio of masses measured by the pDR_dry and AMS) to the dry and wet pDR mass concentrations. Maybe a bit more discussion would help me (and potentially others). The calibration factor is based on a difference in dry aerosol mass between the pDR and the AMS, which will most likely have a density > 1 g cm-3 and refractive index greater than 1.33. However, it sounds like much of the mass measured by the pDR_wet can come from water, which has a lower density (1 g cm-3) and refractive index (1.33) than most dry aerosol components. I'm curious if the calibration factor is robust in situations when much of the mass measured by the pDR_wet is from water? I understand you need some way to correct pDR_wet, but maybe you could discuss how the calibration factor is based on dry aerosol and may not apply perfectly when needing to correct a mass measurement (from pDR_wet) that is potentially largely composed of water. And if it is not as big of a deal as I am making it please help me understand why, thanks.
Line 136 - I see that you assume a single density for the organic species. I understand you have to assume a density because you do not have size-resolved information about your submicron organic aerosols. As you showed in your study, properties of organic aerosol can be largely different depending on the source, and I'm sure organic densities are subject to this variation (don't have citations off the top of my head, but I'm sure they are out there). Perhaps you can at least mention the organic density likely spanned a range and explain why you chose 1.4 g cm-3 (i.e., at least provide a citation as I don't believe there is one now).
Line 149-152 - I was a little confused by this stated assumption: "By simply assuming a constant mass ratio for the chemical composition of fine-mode and coarse-mode particles, the ratio of MALW associated with fine-mode particles to that associated with coarse-mode particles will correspond to the dry aerosol mass concentration of each mode."
Perhaps I am not following, but I thought this study was focused solely on submicron mass because the pDR_dry mass is corrected to be equal that measured by the AMS, which is certainly submicron. And then pDR_wet is also corrected by that same correction factor, although the pDR_wet understandably samples up to 2.5 microns to be able to capture the hygroscopic growth of dry submicron particles (sampled by the pDR_dry and AMS). So how would the coarse mode be represented in this study? I was thinking it got "corrected out" by aligning everything to the AMS mass...
Second, this assumption makes me nervous: "the ratio of MALW associated with fine-mode particles to that associated with coarse-mode particles will correspond to the dry aerosol mass concentration of each mode."
I would expect the fine and coarse mode to take up water differently, largely because they are typically composed of different chemical components. For example, see Fig. 10B in AzadiAghdam et al. (2019), where derived kappa values are not consistent with particle size and are largely sensitive to the presence of sea salt and certain inorganic species, which are typically found in varying amounts between the fine and coarse mode.
That all being said, can you provide more insight into why you believe the assumption you are making is a good one? What is it founded upon? Can you provide a reference or justification? Thanks.
Line 189 - Small thing, but it would be clearer for me if you explicitly wrote "percentile" with the [25%-75%] or some other explanation for what this range is referring to.
Line 196-197 - I was curious about your categorization of the different HYPSLIT back-trajectories. Was this totally subjective or was there more of a process to it? I ask since the lowest-level back-trajectory (red line) on 06 July 2023 in Fig. S3 appears to stay near large metropolitan areas for much of the time before eventually moving out into a more (relatively) rural part of New York. I'm just curious if back-trajectories heading in the northwest direction (or from over the Atlantic Ocean as in panel for 25 August 2023) from the measurement site were considered rural no matter what or if there were more criteria to the classifications?
Line 279 - The fact that you were not able to calibrate with particles of known composition (and therefore known kappa values) seems like a big deal to me and significant limitation to the study, especially as you are trying to present an alternative and lower-cost method to what has been often used in the past. I find it interesting that the inability to calibrate was not mentioned until the Conclusions section. I would strongly suggest moving this information to the Methods section where you previously were discussing the various limitations associated with the proposed method (the paragraphs right before the Results and Discussion). I appreciate that you propose an alternative instrument set-up where the lab calibration would be possible.
Also is "varication" supposed to be "verification" in Line 279?
Citations for works mentioned above:
Pope, F. D., Dennis-Smither, B. J., Griffiths, P. T., Clegg, S. L., & Cox, R. A. (2010). Studies of single aerosol particles containing malonic acid, glutaric acid, and their mixtures with sodium chloride. I. Hygroscopic growth. The Journal of Physical Chemistry A, 114(16), 5335-5341.
AzadiAghdam, M., Braun, R. A., Edwards, E. L., Bañaga, P. A., Cruz, M. T., Betito, G., ... & Sorooshian, A. (2019). On the nature of sea salt aerosol at a coastal megacity: Insights from Manila, Philippines in Southeast Asia. Atmospheric Environment, 216, 116922.
Citation: https://doi.org/10.5194/egusphere-2024-1390-RC2 -
AC1: 'Reply on RC2', Jie Zhang, 01 Oct 2024
We sincerely thank the reviewer #2 for his/her thorough and thoughtful comments that helped improve our manuscript substantially. We have read all comments carefully and have responded to them each in turn. The supplement is our point-by-point responses to reviewer #2 comments. Author responses are in bold black. Modifications to the manuscript are in normal front. Line numbers in the response correspond to those in the revised manuscript text file (tracked version).
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AC1: 'Reply on RC2', Jie Zhang, 01 Oct 2024
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CC2: 'Comment on egusphere-2024-1390', Ye Kuang, 30 Jul 2024
This is a nice try using a cost-effective optical method for studying aerosol hygroscopicity, not the relatively more expensive multiwavelength nephelometer system.
Using measurements of dry and wet neph to infer aerosol liquid water content (Guo et al., 2015;Kuang et al., 2018), hygroscopicity (Kuang et al., 2017) as well as organic hygroscopicity (Kuang et al., 2020;Kuang et al., 2021) are already done and fully discussed before. The method proposed in this manuscript is interesting and differ a little bit with previous studies, a discussion comparing the specific method used here with previous studies should be included, however, never noted in this work. Also, the concept of using the ambient air as the sample air of wet neph is also introduced in Qiao et al. (2024). Optical methods are promising and cost-effective methods in investigating aerosol water and hygroscopicity, however, error analysis should be included.
Guo, H., Xu, L., Bougiatioti, A., Cerully, K. M., Capps, S. L., Hite Jr, J. R., Carlton, A. G., Lee, S. H., Bergin, M. H., Ng, N. L., Nenes, A., and Weber, R. J.: Fine-particle water and pH in the southeastern United States, Atmos. Chem. Phys., 15, 5211-5228, 10.5194/acp-15-5211-2015, 2015.
Kuang, Y., Zhao, C., Tao, J., Bian, Y., Ma, N., and Zhao, G.: A novel method for deriving the aerosol hygroscopicity parameter based only on measurements from a humidified nephelometer system, Atmos. Chem. Phys., 17, 6651-6662, 10.5194/acp-17-6651-2017, 2017.
Kuang, Y., Zhao, C. S., Zhao, G., Tao, J. C., Xu, W., Ma, N., and Bian, Y. X.: A novel method for calculating ambient aerosol liquid water content based on measurements of a humidified nephelometer system, Atmospheric Measurement Techniques, 11, 2967-2982, 10.5194/amt-11-2967-2018, 2018.
Kuang, Y., He, Y., Xu, W., Zhao, P., Cheng, Y., Zhao, G., Tao, J., Ma, N., Su, H., Zhang, Y., Sun, J., Cheng, P., Yang, W., Zhang, S., Wu, C., Sun, Y., and Zhao, C.: Distinct diurnal variation in organic aerosol hygroscopicity and its relationship with oxygenated organic aerosol, Atmos. Chem. Phys., 20, 865-880, 10.5194/acp-20-865-2020, 2020.
Kuang, Y., Huang, S., Xue, B., Luo, B., Song, Q., Chen, W., Hu, W., Li, W., Zhao, P., Cai, M., Peng, Y., Qi, J., Li, T., Wang, S., Chen, D., Yue, D., Yuan, B., and Shao, M.: Contrasting effects of secondary organic aerosol formations on organic aerosol hygroscopicity, Atmos. Chem. Phys., 21, 10375-10391, 10.5194/acp-21-10375-2021, 2021.
Qiao, H., Kuang, Y., Yuan, F., Liu, L., Zhai, M., Xu, H., Zou, Y., Deng, T., and Deng, X.: Unlocking the Mystery of Aerosol Phase Transitions Governed by Relative Humidity History Through an Advanced Outdoor Nephelometer System, Geophysical Research Letters, 51, e2023GL107179, https://doi.org/10.1029/2023GL107179, 2024.
Citation: https://doi.org/10.5194/egusphere-2024-1390-CC2 - AC3: 'Reply on CC2', Jie Zhang, 01 Oct 2024
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