Remote sensing of aerosol water fraction, dry size distribution and soluble fraction using multi-angle, multi-spectral polarimetry

van Diedenhoven, Bastiaan; Hasekamp, Otto P.; Cairns, Brian; Schuster, Gregory L.; Stammes, Snorre; Shook, Michael A.; Ziemba, Luke D.

doi:https://doi.org/10.5194/egusphere-2022-670

Preprints

https://doi.org/10.5194/egusphere-2022-670

Preprints

22 Aug 2022

| 22 Aug 2022

Remote sensing of aerosol water fraction, dry size distribution and soluble fraction using multi-angle, multi-spectral polarimetry

Bastiaan van Diedenhoven, Otto P. Hasekamp, Brian Cairns, Gregory L. Schuster, Snorre Stammes, Michael A. Shook, and Luke D. Ziemba

Abstract. A framework to infer volume water fraction, soluble fraction and dry size distributions of fine mode aerosol from multi-angle, multi-spectral polarimetry retrievals of column-averaged ambient aerosol properties is presented. The method is applied to observations of the Research Scanning Polarimeter (RSP) obtained during two NASA aircraft campaigns, namely the Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) and the Cloud, Aerosol, and Monsoon Processes-Philippines Experiment (CAMP²Ex). All aerosol retrievals are statistically evaluated using in situ data. Volume water fraction is inferred from the retrieved ambient real part of the refractive index, assuming a dry refractive index of 1.54 and by applying a volume mixing rule to obtain the effective ambient refractive index. The uncertainties in inferred volume water fraction resulting from this simplified model are discussed and estimated to be lower than 0.2 and decreasing with increasing volume water fraction. The daily mean retrieved volume water fractions correlate well with the in situ values with a mean absolute difference of 0.09. Polarimeter-retrieved ambient effective radius for daily data is shown to increase as a function of volume water fraction as expected. Furthermore, the effective variance of the size distributions also increases with increasing effective radius, which we show is consistent with an external mixture of soluble and insoluble aerosol. The relative variations of effective radius and variance over an observation period are then used to estimate the soluble fraction of the aerosol. Daily results of soluble fraction correlate well with in situ observed sulfate mass fraction with a correlation coefficient of 0.79. Subsequently, inferred water and soluble fractions are used to derive dry fine-mode size distributions from their ambient counterparts. While dry effective radii obtained in situ and from RSP show similar ranges, in situ values are generally substantially smaller during the ACTIVATE deployments, which may be due to biases in RSP retrievals or in the in situ observations, or both. Both RSP and in situ observations indicate the dominance of aerosol with low hygroscopicity during the ACTIVATE and CAMP²Ex campaigns. Furthermore, RSP indicates a high degree of external mixing of particles with low and high hygroscopicity. These retrievals of fine mode water volume fraction and soluble fraction may be used for the evaluation of water uptake in atmospheric models. Furthermore, the framework allows to estimate the variation in the concentration of fine-mode aerosol larger than a specific dry radius limit, which can be used as a proxy for the variation in cloud condensation nucleus concentrations. This framework may be applied to multi-angle, multi-spectral satellite data expected to be available in the near future.

Received: 19 Jul 2022 – Discussion started: 22 Aug 2022

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Journal article(s) based on this preprint

22 Dec 2022

Remote sensing of aerosol water fraction, dry size distribution and soluble fraction using multi-angle, multi-spectral polarimetry

Bastiaan van Diedenhoven, Otto P. Hasekamp, Brian Cairns, Gregory L. Schuster, Snorre Stamnes, Michael Shook, and Luke Ziemba

Atmos. Meas. Tech., 15, 7411–7434, https://doi.org/10.5194/amt-15-7411-2022,https://doi.org/10.5194/amt-15-7411-2022, 2022

Short summary

Bastiaan van Diedenhoven, Otto P. Hasekamp, Brian Cairns, Gregory L. Schuster, Snorre Stammes, Michael A. Shook, and Luke D. Ziemba

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2022-670', Anonymous Referee #2, 13 Sep 2022
Review

This study “Remote sensing of aerosol water fraction, dry size distribution and soluble fraction using multi-angle, multi-spectral polarimetry” by Diedenhoven et al. present a framework to infer volume water fraction, soluble fraction and dry size distributions of fine mode aerosol from multi-angle, multi-spectral polarimetry retrievals of column-averaged ambient aerosol properties. The results showed that the retrieved volume water fractions, particle radius and soluble fraction all correlated well with the in situ values. Futhermore, the uncertainties in inferred volume water fraction resulting from this simplified model are estimated to be lower than 0.2 and decreasing with increasing volume water fraction.

The manuscript addresses the issue of retrieved aerosol water fraction, dry size distribution and soluble fraction which are important to air quality and climate. These retrievals of fine mode water volume fraction and soluble fraction may be used for the evaluation of water uptake in atmospheric models. Thus, there are some minor comments need to be addressed before published.

Specific comments:

Line 150: The authors assumed the size distributions of the insoluble component and the dry soluble component of the mixture are the same. Is there any back up reference?

Line 254:Why only data over ocean are used in this manuscript? Please specify.

Section 4.1: The Figure 5 showed that the water volume fractions derived from the retrieved refractive indices show a larger peak at zero for all three campaigns, corresponding to κ = 0. Why the retrieved aerosol hygroscopicity can equal to zero? As I understand, even the even the water-insoluble particles will be somewhat hygroscopic rather than absolutely not hygroscopic.

Line 448: Why is there no difference in the retrieved results assuming different f values? This is confused. Because the solube aerosol fraction has lagre effect on aerosol hygroscopicity and thus influence particle size distribution.

Section 5: Same above. the authors assume that the aerosol consists of externally mixed soluble (κ > 0) and insoluble (κ = 0) components with equal dry size distributions. This will lead to large uncertainty in retrieved results. I suggest the uncertainty analysis about this assumption are needed.
Citation: https://doi.org/10.5194/egusphere-2022-670-RC1
- AC1: 'Reply on RC1', Bastiaan van Diedenhoven, 11 Nov 2022
  
  We thank the reviewer for the for the positive feedback and helpful comments. Comments are repeated below in italic script, followed by our responses.
  
  Line 150: The authors assumed the size distributions of the insoluble component and the dry soluble component of the mixture are the same. Is there any back up reference?
  Little information is available. We added a discussion on this assumption and a sensitivity study at line 183 and further. In the discussion we include the sentence:
  “Some observations, such as from Holmgren et al. (2014) and Kim et al. (2020), suggest that hygroscopicity increases with particle size.”
  Please also see our reply to comment 5.
  
  Line 254:Why only data over ocean are used in this manuscript? Please specify.
  To specify we added the following to the text at line 275:
  “The majority of the data during these campaigns were collected over ocean. Furthermore, the RSP aerosol retrieval algorithm (section 3.2) is currently limited to ocean surfaces. Hence, only data over ocean are used here.”
  
  Section 4.1: The Figure 5 showed that the water volume fractions derived from the retrieved refractive indices show a larger peak at zero for all three campaigns, corresponding to κ = 0. Why the retrieved aerosol hygroscopicity can equal to zero? As I understand, even the even the water-insoluble particles will be somewhat hygroscopic rather than absolutely not hygroscopic.
  Petters and Kreidenweis (2007) define kappa as equal or greater than 0 (e.g., see their Fig 1). Note that these insoluble particles can be wettable at supersaturation above 1, as discussed by Petters & Kreidenweis: “As kappa approaches zero, the particle becomes nonhygroscopic and the slope approaches that expected for an insoluble but wettable particle as predicted by the Kelvin equation, i.e. –1.”
  Since we already refer to Petters and Kreidenweis (2007) for our definition of kappa, no changes were made to the manuscript related to this comment.
  
  Line 448: Why is there no difference in the retrieved results assuming different f values? This is confused. Because the solube aerosol fraction has lagre effect on aerosol hygroscopicity and thus influence particle size distribution.
  The reviewer is correct that soluble fraction has a large effect on the aerosol growth as a function of relative humidity. However, note that we derive dry effective radius and variance from the ambient values using the simulated relationship between r_e and v_e and water fraction in combination with the retrieved water fraction. Figure 1 shows that the relationship between r_e and water fraction is rather similar for f_sol values >0.05. The relationship between v_e and water fraction varies somewhat more with f_sol, but this variation is still limited for f_sol between about 0.1 and 0.7.
  To further clarify, we added the following to the text at line 473:
  “Since the variation of re,mix and ve,mix with fw vary relatively weakly for 0.1 < fsol < 0.6 (Fig. 1), no noticeable difference in the histogram is seen if a different value fsol is assumed within this range.”
  
  Section 5: Same above. the authors assume that the aerosol consists of externally mixed soluble (κ > 0) and insoluble (κ = 0) components with equal dry size distributions. This will lead to large uncertainty in retrieved results. I suggest the uncertainty analysis about this assumption are needed.
  According to the reviewer’s suggestion we added a sensitivity study to the supplement (section S2) and summarize the results in the main text. The following was added to the text starting at line 183 and further:
  “To derive Eqs. 18–21, we assumed that the size distributions of the insoluble component and the dry soluble component of the mixture are the same. Some observations, such as from Holmgren et al. (2014) and Kim et al. (2020), suggest that hygroscopicity increases with particle size. To test the impact on assuming the same dry particle distribution of insoluble and soluble aerosols, we simulated re,mix and ve,mix as a function of fsol for a range of fw and for an aerosol with a soluble component with re,dry = 0.15 μm and an insoluble component that is ∆re smaller. For both components we assume ve,dry = 0.15. Using these simulations as our dataset, we subsequently infer fsol, re,dry and ve,dry while assuming an aerosol mixture with equal soluble and insoluble components. The differences between the inferred fsol, re,dry and ve,dry and the true values in the simulations yield an estimated sensitivity to ∆re. Detailed results are given in the Supplement. For a ∆re of 0.03 μm, maximum underestimations of fsol, re,dry and ve,dry are 0.23, 9% and 17%, respectively, occurring at true fsol values of 0.65, 0.28 and 0.16, respectively. These biases scale approximately linearly with ∆re. Hence, especially retrieved fsol and ve,dry are quite sensitive to our assumption of the same dry particle distribution of insoluble and soluble aerosols. However, a realistic estimate of the range of ∆re is not available.”
  
  Citation: https://doi.org/10.5194/egusphere-2022-670-AC1
RC2:
'Comment on egusphere-2022-670', Anonymous Referee #1, 08 Oct 2022

This study provides a novel method to derive aerosol water volume fraction, dry size distribution, and soluble fraction of fine mode aerosol although some assumptions are needed. This exploration is encouraged to enhance people’s understanding of aerosol physicochemical properties. This study is within the scope of the journal. I would suggest this paper be published, and I also have comments below for the authors to address.

Line 110. How low is the ð and how small is the radii for ignoring the Kelvin term? What is uncertainty?

Line 125. The authors should indicate the uncertainty of aerosol hygroscopicity for 150 nm particles if omitting the Kelvin term.

Line 130. It is not reasonable to classify aerosol as soluble and insoluble particles according to whether the aerosol hygroscopicity parameter (ð) is 0. Actually, the ð of many organics is larger than 0 but they are insoluble. Here can be considered hygroscopic (ð>0) and non-hygroscopic (ð=0).

Line 250. More information about RSP is needed, such as the instrument configuration, detection ability, measurement uncertainty, and so on.

Line 435. Whether sulfate is the principal chemical component. The authors can provide the mass fractions of aerosol chemical species measured by AMS.

Figure 3. According to the ð_ext, the hygroscopicity of particles is very weak. If divided by 0.56 using Eq. 28, the ð of most particles is below 0.1, indicating a large number of organics with weak hygroscopicity. It may be inappropriate for the author to assume that soluble components are represented by sulfate in Line 320.

Figure 5, 6, 9, 11, 12, 14. Some in situ data were used to compare, but the measurement instruments were not introduced in the paper. This information can be added to the supplement. What’s the uncertainty of these in situ measurements?

Figure 8. The scatter is not well consistent with the model line in (a) and (b). What’s the reason?

Technical advice:

Line 330. “Therefor” should be “Therefore”

Citation: https://doi.org/10.5194/egusphere-2022-670-RC2
- AC2: 'Reply on RC2', Bastiaan van Diedenhoven, 11 Nov 2022
  
  We thank the reviewer for the for the positive feedback and helpful comments. The comments are repeated below in italic script, followed by our replies.
  Line 110. How low is the kappa and how small is the radii for ignoring the Kelvin term? What is uncertainty? Line 125. The authors should indicate the uncertainty of aerosol hygroscopicity for 150 nm particles if omitting the Kelvin term.
  At line 110, we now cite Wex et al. (2008) and Ruehl et al. (2010) for a discussion on the effects of the Kelvin effect. The remark that the Kelvin effect “is only substantial for very low kappa” was from the perspective of a given growth factor, where lowering kappa implies increasing RH. To be more consistent with conclusions of Wex et al. 2008 and Ruehl et al. 2010, we now state that
  “In practice, the Kelvin term is often ignored as its effect is only substantial for RH close to 100% and/or small radii (Wex et al., 2008; Ruehl et al., 2010)”
  Furthermore, as suggested we indicate the uncertainty of the growth factor for the example shown in Fig 1 and added the sentence (line 127):
  “To further justify neglecting the Kelvin effect in our analysis, we note that for a typical value of κ of 0.15, ignoring the Kelvin effect (Eq. 8) leads to an underestimation of the growth factor of less than 3% at a fw = 0.9.”
  
  Line 130. It is not reasonable to classify aerosol as soluble and insoluble particles according to whether the aerosol hygroscopicity parameter (Kappa) is 0. Actually, the kappa of many organics is larger than 0 but they are insoluble. Here can be considered hygroscopic (kappa>0) and non-hygroscopic (kappa=0).
  The terminology used in the literature is a bit muddled and the terms soluble/insoluble and hygroscopic/non-hygroscopic or hydrophilic/hydrophobic are often used exchangeable (see for example papers cited in line 133). In line 132, we defined our definition of insoluble as particles with kappa=0. Here, we can refer to Petters & Kreidenweis 2007 who state (referring to a plot of critical supersaturation against dry size) state: “As kappa approaches zero, the particle becomes nonhygroscopic and the slope approaches that expected for an insoluble but wettable particle as predicted by the Kelvin equation, i.e. –1.”
  Since we already define the terms “insoluble” and “soluble” in line 132, no changes were made to the manuscript related to this comment.
  
  Line 250. More information about RSP is needed, such as the instrument configuration, detection ability, measurement uncertainty, and so on.
  Quite some information on RSP is given already in lines 291 and further. About its accuracy we added the sentence (line 293):
  “Accuracy of the measured intensity and degree of polarization is generally better than 3% and 0.2%, respectively.”
  And also (line 300):
  “Uncertainties in the derived water fraction, soluble fraction and dry size distributions resulting from measurement uncertainties (see e.g., Knobelspiesse et al., 2012) are expected to be substantially smaller than those arising from the assumptions made in these derivations, as discussed in sections 2, 4 and 5.”
  
  Line 435. Whether sulfate is the principal chemical component. The authors can provide the mass fractions of aerosol chemical species measured by AMS.
  The mass fractions of organics, ammonium and nitrate are now added to the table S3 in the supplement. We added the following to the text at line 445:
  “Mass fractions of ammonium, nitrate and organics are given in table S3. Generally, the majority of the mass other than sulfate is composed of organics.”
  
  Figure 3. According to the kappa_ext, the hygroscopicity of particles is very weak. If divided by 0.56 using Eq. 28, the kappa of most particles is below 0.1, indicating a large number of organics with weak hygroscopicity. It may be inappropriate for the author to assume that soluble components are represented by sulfate in Line 320.
  Daily average kappa values derived from f(RH) are given in table S3 and range from 0.05 to 0.3. Indeed, these kappa values are low because of the large contribution of organics with low hygroscopicity. That is exactly our interpretation. Note that these are single values for bulk aerosol that is generally internally and externally mixed and sampled at 1 Hz. Hence, we do not expect to observe values of kappa representing pure sulfate aerosol for example.
  To further clarify this, to line 367 we added:
  “Note that the f (80%, 20%) and κext values represent the hygroscopicity of bulk aerosol observed at 1 Hz.“
  
  Figure 5, 6, 9, 11, 12, 14. Some in situ data were used to compare, but the measurement instruments were not introduced in the paper. This information can be added to the supplement. What’s the uncertainty of these in situ measurements?
  The in situ data are described in quite some detail already in section 3.3. Related to the previous comment, we added the data sampling resolution:
  “Data are reported at 1 Hertz resolution.”
  Uncertainty of the water fraction derived from the in situ probes was also discussed already in lines 332 and further. We added a line with estimated uncertainties of the LAS probe to derived sizes and number concentrations at line 343:
  “Uncertainty of the LAS data is estimated at 20%.”
  
  Figure 8. The scatter is not well consistent with the model line in (a) and (b). What’s the reason?
  Possible reasons were already discussed in the paper at line 420 and further:
  “The spread in the data may be attributable to natural variation of aerosol dry size distributions during the observation period, as well as uncertainties in effective radius retrievals and water fraction estimates. “
  We did not make changes to the paper related to this comment.
  
  Line 330. “Therefor” should be “Therefore”
  Thank you for catching the error. It is corrected.
  
  Citation: https://doi.org/10.5194/egusphere-2022-670-AC2

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2022-670', Anonymous Referee #2, 13 Sep 2022
Review

This study “Remote sensing of aerosol water fraction, dry size distribution and soluble fraction using multi-angle, multi-spectral polarimetry” by Diedenhoven et al. present a framework to infer volume water fraction, soluble fraction and dry size distributions of fine mode aerosol from multi-angle, multi-spectral polarimetry retrievals of column-averaged ambient aerosol properties. The results showed that the retrieved volume water fractions, particle radius and soluble fraction all correlated well with the in situ values. Futhermore, the uncertainties in inferred volume water fraction resulting from this simplified model are estimated to be lower than 0.2 and decreasing with increasing volume water fraction.

The manuscript addresses the issue of retrieved aerosol water fraction, dry size distribution and soluble fraction which are important to air quality and climate. These retrievals of fine mode water volume fraction and soluble fraction may be used for the evaluation of water uptake in atmospheric models. Thus, there are some minor comments need to be addressed before published.

Specific comments:

Line 150: The authors assumed the size distributions of the insoluble component and the dry soluble component of the mixture are the same. Is there any back up reference?

Line 254:Why only data over ocean are used in this manuscript? Please specify.

Section 4.1: The Figure 5 showed that the water volume fractions derived from the retrieved refractive indices show a larger peak at zero for all three campaigns, corresponding to κ = 0. Why the retrieved aerosol hygroscopicity can equal to zero? As I understand, even the even the water-insoluble particles will be somewhat hygroscopic rather than absolutely not hygroscopic.

Line 448: Why is there no difference in the retrieved results assuming different f values? This is confused. Because the solube aerosol fraction has lagre effect on aerosol hygroscopicity and thus influence particle size distribution.

Section 5: Same above. the authors assume that the aerosol consists of externally mixed soluble (κ > 0) and insoluble (κ = 0) components with equal dry size distributions. This will lead to large uncertainty in retrieved results. I suggest the uncertainty analysis about this assumption are needed.
Citation: https://doi.org/10.5194/egusphere-2022-670-RC1
- AC1: 'Reply on RC1', Bastiaan van Diedenhoven, 11 Nov 2022
  
  We thank the reviewer for the for the positive feedback and helpful comments. Comments are repeated below in italic script, followed by our responses.
  
  Line 150: The authors assumed the size distributions of the insoluble component and the dry soluble component of the mixture are the same. Is there any back up reference?
  Little information is available. We added a discussion on this assumption and a sensitivity study at line 183 and further. In the discussion we include the sentence:
  “Some observations, such as from Holmgren et al. (2014) and Kim et al. (2020), suggest that hygroscopicity increases with particle size.”
  Please also see our reply to comment 5.
  
  Line 254:Why only data over ocean are used in this manuscript? Please specify.
  To specify we added the following to the text at line 275:
  “The majority of the data during these campaigns were collected over ocean. Furthermore, the RSP aerosol retrieval algorithm (section 3.2) is currently limited to ocean surfaces. Hence, only data over ocean are used here.”
  
  Section 4.1: The Figure 5 showed that the water volume fractions derived from the retrieved refractive indices show a larger peak at zero for all three campaigns, corresponding to κ = 0. Why the retrieved aerosol hygroscopicity can equal to zero? As I understand, even the even the water-insoluble particles will be somewhat hygroscopic rather than absolutely not hygroscopic.
  Petters and Kreidenweis (2007) define kappa as equal or greater than 0 (e.g., see their Fig 1). Note that these insoluble particles can be wettable at supersaturation above 1, as discussed by Petters & Kreidenweis: “As kappa approaches zero, the particle becomes nonhygroscopic and the slope approaches that expected for an insoluble but wettable particle as predicted by the Kelvin equation, i.e. –1.”
  Since we already refer to Petters and Kreidenweis (2007) for our definition of kappa, no changes were made to the manuscript related to this comment.
  
  Line 448: Why is there no difference in the retrieved results assuming different f values? This is confused. Because the solube aerosol fraction has lagre effect on aerosol hygroscopicity and thus influence particle size distribution.
  The reviewer is correct that soluble fraction has a large effect on the aerosol growth as a function of relative humidity. However, note that we derive dry effective radius and variance from the ambient values using the simulated relationship between r_e and v_e and water fraction in combination with the retrieved water fraction. Figure 1 shows that the relationship between r_e and water fraction is rather similar for f_sol values >0.05. The relationship between v_e and water fraction varies somewhat more with f_sol, but this variation is still limited for f_sol between about 0.1 and 0.7.
  To further clarify, we added the following to the text at line 473:
  “Since the variation of re,mix and ve,mix with fw vary relatively weakly for 0.1 < fsol < 0.6 (Fig. 1), no noticeable difference in the histogram is seen if a different value fsol is assumed within this range.”
  
  Section 5: Same above. the authors assume that the aerosol consists of externally mixed soluble (κ > 0) and insoluble (κ = 0) components with equal dry size distributions. This will lead to large uncertainty in retrieved results. I suggest the uncertainty analysis about this assumption are needed.
  According to the reviewer’s suggestion we added a sensitivity study to the supplement (section S2) and summarize the results in the main text. The following was added to the text starting at line 183 and further:
  “To derive Eqs. 18–21, we assumed that the size distributions of the insoluble component and the dry soluble component of the mixture are the same. Some observations, such as from Holmgren et al. (2014) and Kim et al. (2020), suggest that hygroscopicity increases with particle size. To test the impact on assuming the same dry particle distribution of insoluble and soluble aerosols, we simulated re,mix and ve,mix as a function of fsol for a range of fw and for an aerosol with a soluble component with re,dry = 0.15 μm and an insoluble component that is ∆re smaller. For both components we assume ve,dry = 0.15. Using these simulations as our dataset, we subsequently infer fsol, re,dry and ve,dry while assuming an aerosol mixture with equal soluble and insoluble components. The differences between the inferred fsol, re,dry and ve,dry and the true values in the simulations yield an estimated sensitivity to ∆re. Detailed results are given in the Supplement. For a ∆re of 0.03 μm, maximum underestimations of fsol, re,dry and ve,dry are 0.23, 9% and 17%, respectively, occurring at true fsol values of 0.65, 0.28 and 0.16, respectively. These biases scale approximately linearly with ∆re. Hence, especially retrieved fsol and ve,dry are quite sensitive to our assumption of the same dry particle distribution of insoluble and soluble aerosols. However, a realistic estimate of the range of ∆re is not available.”
  
  Citation: https://doi.org/10.5194/egusphere-2022-670-AC1
RC2:
'Comment on egusphere-2022-670', Anonymous Referee #1, 08 Oct 2022

This study provides a novel method to derive aerosol water volume fraction, dry size distribution, and soluble fraction of fine mode aerosol although some assumptions are needed. This exploration is encouraged to enhance people’s understanding of aerosol physicochemical properties. This study is within the scope of the journal. I would suggest this paper be published, and I also have comments below for the authors to address.

Line 110. How low is the ð and how small is the radii for ignoring the Kelvin term? What is uncertainty?

Line 125. The authors should indicate the uncertainty of aerosol hygroscopicity for 150 nm particles if omitting the Kelvin term.

Line 130. It is not reasonable to classify aerosol as soluble and insoluble particles according to whether the aerosol hygroscopicity parameter (ð) is 0. Actually, the ð of many organics is larger than 0 but they are insoluble. Here can be considered hygroscopic (ð>0) and non-hygroscopic (ð=0).

Line 250. More information about RSP is needed, such as the instrument configuration, detection ability, measurement uncertainty, and so on.

Line 435. Whether sulfate is the principal chemical component. The authors can provide the mass fractions of aerosol chemical species measured by AMS.

Figure 3. According to the ð_ext, the hygroscopicity of particles is very weak. If divided by 0.56 using Eq. 28, the ð of most particles is below 0.1, indicating a large number of organics with weak hygroscopicity. It may be inappropriate for the author to assume that soluble components are represented by sulfate in Line 320.

Figure 5, 6, 9, 11, 12, 14. Some in situ data were used to compare, but the measurement instruments were not introduced in the paper. This information can be added to the supplement. What’s the uncertainty of these in situ measurements?

Figure 8. The scatter is not well consistent with the model line in (a) and (b). What’s the reason?

Technical advice:

Line 330. “Therefor” should be “Therefore”

Citation: https://doi.org/10.5194/egusphere-2022-670-RC2
- AC2: 'Reply on RC2', Bastiaan van Diedenhoven, 11 Nov 2022
  
  We thank the reviewer for the for the positive feedback and helpful comments. The comments are repeated below in italic script, followed by our replies.
  Line 110. How low is the kappa and how small is the radii for ignoring the Kelvin term? What is uncertainty? Line 125. The authors should indicate the uncertainty of aerosol hygroscopicity for 150 nm particles if omitting the Kelvin term.
  At line 110, we now cite Wex et al. (2008) and Ruehl et al. (2010) for a discussion on the effects of the Kelvin effect. The remark that the Kelvin effect “is only substantial for very low kappa” was from the perspective of a given growth factor, where lowering kappa implies increasing RH. To be more consistent with conclusions of Wex et al. 2008 and Ruehl et al. 2010, we now state that
  “In practice, the Kelvin term is often ignored as its effect is only substantial for RH close to 100% and/or small radii (Wex et al., 2008; Ruehl et al., 2010)”
  Furthermore, as suggested we indicate the uncertainty of the growth factor for the example shown in Fig 1 and added the sentence (line 127):
  “To further justify neglecting the Kelvin effect in our analysis, we note that for a typical value of κ of 0.15, ignoring the Kelvin effect (Eq. 8) leads to an underestimation of the growth factor of less than 3% at a fw = 0.9.”
  
  Line 130. It is not reasonable to classify aerosol as soluble and insoluble particles according to whether the aerosol hygroscopicity parameter (Kappa) is 0. Actually, the kappa of many organics is larger than 0 but they are insoluble. Here can be considered hygroscopic (kappa>0) and non-hygroscopic (kappa=0).
  The terminology used in the literature is a bit muddled and the terms soluble/insoluble and hygroscopic/non-hygroscopic or hydrophilic/hydrophobic are often used exchangeable (see for example papers cited in line 133). In line 132, we defined our definition of insoluble as particles with kappa=0. Here, we can refer to Petters & Kreidenweis 2007 who state (referring to a plot of critical supersaturation against dry size) state: “As kappa approaches zero, the particle becomes nonhygroscopic and the slope approaches that expected for an insoluble but wettable particle as predicted by the Kelvin equation, i.e. –1.”
  Since we already define the terms “insoluble” and “soluble” in line 132, no changes were made to the manuscript related to this comment.
  
  Line 250. More information about RSP is needed, such as the instrument configuration, detection ability, measurement uncertainty, and so on.
  Quite some information on RSP is given already in lines 291 and further. About its accuracy we added the sentence (line 293):
  “Accuracy of the measured intensity and degree of polarization is generally better than 3% and 0.2%, respectively.”
  And also (line 300):
  “Uncertainties in the derived water fraction, soluble fraction and dry size distributions resulting from measurement uncertainties (see e.g., Knobelspiesse et al., 2012) are expected to be substantially smaller than those arising from the assumptions made in these derivations, as discussed in sections 2, 4 and 5.”
  
  Line 435. Whether sulfate is the principal chemical component. The authors can provide the mass fractions of aerosol chemical species measured by AMS.
  The mass fractions of organics, ammonium and nitrate are now added to the table S3 in the supplement. We added the following to the text at line 445:
  “Mass fractions of ammonium, nitrate and organics are given in table S3. Generally, the majority of the mass other than sulfate is composed of organics.”
  
  Figure 3. According to the kappa_ext, the hygroscopicity of particles is very weak. If divided by 0.56 using Eq. 28, the kappa of most particles is below 0.1, indicating a large number of organics with weak hygroscopicity. It may be inappropriate for the author to assume that soluble components are represented by sulfate in Line 320.
  Daily average kappa values derived from f(RH) are given in table S3 and range from 0.05 to 0.3. Indeed, these kappa values are low because of the large contribution of organics with low hygroscopicity. That is exactly our interpretation. Note that these are single values for bulk aerosol that is generally internally and externally mixed and sampled at 1 Hz. Hence, we do not expect to observe values of kappa representing pure sulfate aerosol for example.
  To further clarify this, to line 367 we added:
  “Note that the f (80%, 20%) and κext values represent the hygroscopicity of bulk aerosol observed at 1 Hz.“
  
  Figure 5, 6, 9, 11, 12, 14. Some in situ data were used to compare, but the measurement instruments were not introduced in the paper. This information can be added to the supplement. What’s the uncertainty of these in situ measurements?
  The in situ data are described in quite some detail already in section 3.3. Related to the previous comment, we added the data sampling resolution:
  “Data are reported at 1 Hertz resolution.”
  Uncertainty of the water fraction derived from the in situ probes was also discussed already in lines 332 and further. We added a line with estimated uncertainties of the LAS probe to derived sizes and number concentrations at line 343:
  “Uncertainty of the LAS data is estimated at 20%.”
  
  Figure 8. The scatter is not well consistent with the model line in (a) and (b). What’s the reason?
  Possible reasons were already discussed in the paper at line 420 and further:
  “The spread in the data may be attributable to natural variation of aerosol dry size distributions during the observation period, as well as uncertainties in effective radius retrievals and water fraction estimates. “
  We did not make changes to the paper related to this comment.
  
  Line 330. “Therefor” should be “Therefore”
  Thank you for catching the error. It is corrected.
  
  Citation: https://doi.org/10.5194/egusphere-2022-670-AC2

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

AR by Bastiaan van Diedenhoven on behalf of the Authors (11 Nov 2022) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (14 Nov 2022) by Jing Wei

RR by Anonymous Referee #2 (21 Nov 2022)

RR by Anonymous Referee #1 (01 Dec 2022)

ED: Publish as is (01 Dec 2022) by Jing Wei

AR by Bastiaan van Diedenhoven on behalf of the Authors (02 Dec 2022)

Journal article(s) based on this preprint

22 Dec 2022

Remote sensing of aerosol water fraction, dry size distribution and soluble fraction using multi-angle, multi-spectral polarimetry

Bastiaan van Diedenhoven, Otto P. Hasekamp, Brian Cairns, Gregory L. Schuster, Snorre Stamnes, Michael Shook, and Luke Ziemba

Atmos. Meas. Tech., 15, 7411–7434, https://doi.org/10.5194/amt-15-7411-2022,https://doi.org/10.5194/amt-15-7411-2022, 2022

Short summary

Bastiaan van Diedenhoven, Otto P. Hasekamp, Brian Cairns, Gregory L. Schuster, Snorre Stammes, Michael A. Shook, and Luke D. Ziemba

Supplement

https://doi.org/10.5194/egusphere-2022-670-supplement

Bastiaan van Diedenhoven, Otto P. Hasekamp, Brian Cairns, Gregory L. Schuster, Snorre Stammes, Michael A. Shook, and Luke D. Ziemba

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The strong variability in the chemistry of atmospheric particulate matter affects the amount of water they absorb and their effect on climate. We present a remote sensing method to determine the amount of water in particulate matter. Its application to airborne instruments indicates that the observed aerosols have rather low water contents and low fractions of soluble particles, which agrees well with in situ measurements. Future satellites will be able to yield global aerosol water uptake data.


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