the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 12 Oct 2023
Aerosol hygroscopicity over the South-East Atlantic Ocean during the biomass burning season: Part I – From the perspective of scattering enhancement
Abstract. Aerosol hygroscopicity plays a vital role in aerosol radiative forcing. One key parameter describing hygroscopicity is the scattering enhancement factor, f (RH), defined as the ratio of the scattering coefficient at humidified relative humidity (RH) to its dry value. Here, we utilize the f (80 %) from ORACLES 2016 and 2018 airborne measurements to investigate the hygroscopicity of aerosols, its vertical distribution, its relationship with chemical composition, and its sensitivity to organic aerosol (OA) hygroscopicity over the South-East Atlantic (SEA) Ocean during the biomass burning (BB) season.
We found that aerosol hygroscopicity remains steady above 2 km, with a mean f (80 %) of 1.40±0.17. Below 2 km, aerosol hygroscopicity increases with decreasing altitude, with a mean f (80 %) of 1.51±0.22, consistent with higher values of BB hygroscopicity found in the literature. The hygroscopicity parameter of OA (κOA) is retrieved from the Mie model with a mean value of 0.11±0.08, which is in the middle to upper range compared to literature. Higher OA hygroscopicity is related to aerosols that are more aged, oxidized, and present at lower altitudes. The enhanced BBA hygroscopicity at lower altitudes is mainly due to a lower OA fraction, increased sulphate fraction, and greater κOA at lower altitudes.
We propose a parameterization that quantifies f (RH) with chemical composition and κOA based on Mie simulation of internally mixed OA-(NH4)2SO4-BC mixture. The good agreement between the predictions and the ORACLES measurements implies that the aerosols in the SEA during the BB season can be largely represented by the OA-(NH4)2SO4-BC internal mixture with respect to the f (RH) prediction. The sensitivity of f (RH) to κOA indicates that applying a constant κOA is only suitable when the OA fraction is low and κOA shows limited variation. However, in situations deviating these two criteria, κOA can notably impact scattering coefficients and aerosol radiative effect; therefore, accounting for κOA variability is recommended.
- Preprint
(4018 KB) - Metadata XML
-
Supplement
(644 KB) - BibTeX
- EndNote
Status: final response (author comments only)
-
RC1: 'Comment on egusphere-2023-2199', Anonymous Referee #1, 21 Nov 2023
Review of Zhang et al for egusphere (ACP?) 2023.
This paper describes the vertical profile of aerosol hygroscopicity from the African continent during biomass burning season and the sensitivity of the observed hygroscopicity to aerosol chemical composition. The primary measurements used were made during two airborne field campaigns in 2016 and 2018. A main point of the paper is that when considering aerosol hygroscopicity it is import to realize that organic aerosol may have different water uptake values.
I think this paper is a useful addition to the hygroscopicity literature - however it would benefit from some more details about the measurements in order to better make their point. There is also some key information that should be mentioned sooner (e.g., PNSD was not important for f(RH) for this study, coarse mode was not important for this study.)
Comments/questions
line 80 - Suggests that organics can have 'kappa>1'? should this say '...kappa approaching 1.0'?
line 113 - What was size cut for nephelometers? Were nephelometer measurements corrected for truncation? Truncation corrections can be large when coarse mode aerosol are sampled.
line 116-117 - Where were RH sensors for RR neph located? Were they calibrated? (see, for example, description of RH sensor locations and calibration in manuscript cited reference Day et al., 2006).
line 119 - Provide a probability distribution plot of ref RH and wet RH (it could go in supplemental).
line 124 - What is largest diameter measured by AMS? did AMS provide a measure of sea salt?
Line 129-132 - Did you perform a scattering closure study using the PNSD, refractive index from chemistry and the nephelometer measurements?
line 145 - Approximately 134 flight hours - is that before or after the constraints (dryRH<30%, scat>10 Mm-1 and f60 > 0.003 are applied? What was the final number of data points/hours studied?
line 159 - This would be a good place to show that scattering closure was obtained for dry scattering and the PNSD. (it could go in supplemental materials). Relatedly - is assumed PNSD similar to measured PNSD - can you show that (e.g., a plot in supplemental materials).
line 162-163 - 'particles beyond pm1 not included in calculation' - does this mean APS data is not used since UHSAS size range goes up to 1um? or was some sort of merging of the two size distributions done (for example, as described in Hand and Kreidenweis, 2002). Perhaps show plot(s) of full size distribution in supplement so can refer reader to it when say super-um particles made minimal contribution.
line 168 - Is there no information on contribution of sea salt? It seems like sea salt should be considered since over ocean and/or discuss why it's ok not to consider it. Later on (line 201) mentions the marine boundary layer so it seems there would be some influence of sea salt on the measurements
Figure 2 - There appears to be an inverse relationship between OA/BC and plume age. Could/should note this when discussing the figure.
line 195 - Sentence refers to 'figure 1a' --> change to figure 1 because there is only 1 pane in figure 1.
line 195 - Is there something in figure 1 that indicates subsidence? Please elaborate! Also please label countries so when refer to Namibian coast reader can see where you are talking about.
line 196 &197 - Do you have a citation for the cloud top height information? Please provide.
line 211 - The authors note that the OA/BC ratio 'removes the dilution effect during transport'. but they should also note that it's useful for looking at because it can indicate something about processing as discussed later - e.g., gas phase organics condensing on existing particles or loss of hygroscopic particles due to wet scavenging.
line 218 - Mentions Figure 3 only considers measurements above 1.4 km to minimize marine influence. Why is 1.4 km the chosen altitude for that? Should all analyses/plots use that altitude constraint? Figure 2 goes down to 1 and 0.5 km for the two different years. Should a line be added to figure 2 at 1.4 km with a note indicating above that height is considered above the MBL?
Figure 5 - Perhaps say shading indicates 10 and 90 percentiles rather than dashed lines since the line for 2016 mean is also dashed. Also, you should NOT combine mean with percentiles - that is mixing statistical parameters. Either use median and percentiles or mean and standard deviation! Are the f(RH) values (and gamma values) above and below 2km statistically different (e.g. can you use something like a student t-test or some other appropriate statistical test to say how different they are at what level of confidence)?
line 290 Change 'diameter' --> 'value' (in both places on the line)
lines 296-313 - Put comparisons in a table and/or do similar figure as figure 3 in Titos et al. (2016) rather than this paragraph which is rather long and hard to follow.
line 324-325 - Pearson correlation coefficient of -0.35. so R2 ~ 0.13. Is this statistically significant?
Fig 6 - I don't see dotted gray lines (except for gridlines). There is also too much information on this plot. I suggest making two plots one with measurement points and one with model results maybe with ACE-Asia fit on both plots for ease of comparability.
line 376 "was calculated following the lognormally distribution" I'm not sure what you are saying here. I think you mean assuming the PNSD is lognormally distributed? Do the assumed values of Dg and sigma match the measured PNSD?
line 377 - Caption for figure 6 says sigma=1.5, this line says sigma=1.6
lines 381-382 How much variation was there in the measured PNSD temporally and spatially (horizontal and vertical)? How does assuming a constant size distribution affect your results? Very possibly I am missing something, but it seems like if a constant size distribution is assumed, then by definition the hygroscopicity will depend on composition. It might be good to discuss in methods section more about the size distribution - characteristics such as Dg and sigma as well as spatial/temporal changes.
line 398 - Has sigma=1.6 also instead of 1.5. Use consistent sigma for all calculations or explain why not doing so?
line 399 - How do results change if RHref = 30% is used? What is the median value of the RHref of your measurements?
line 401 Change 'all with a span of 0.02' --> 'all in increments of 0.02'
line 424-425 - This is the first time it is mentioned that the effect of PNSD on f(RH) is small. That should be mentioned much sooner and perhaps with a little more detail in the main text.
line 405-415 - Do the 2nd and 5th order polynomials have a physical interpretation? Do you expect such equations to be widely applicable or only for the special case (BBA over SEA) studied here?
line 448 - How is the deviation of f(80%) calculated? Why is the deviation always positive?
line 455 - Change 'As well' --> 'Additionally'
line 463-468 - The discussion of the North China Plain data doesn't add anything. You've already made the point that KappaOA and Fo need to represent the actual data to get a good f(RH) value. I would remove this data and discussion.
line 495 - Give median to go with percentiles.
Line 512 - Change 'Sensitivity study' --> 'A sensitivity study'
Hand, J.L., Kreidenweis, S.M., 2002. A new method for retrieving particle refractive index and effective density from aerosol size distribution data. Aerosol Science & Technology, 36:10, 1012-1026.
Citation: https://doi.org/10.5194/egusphere-2023-2199-RC1 -
RC2: 'Comment on egusphere-2023-2199', Anonymous Referee #2, 27 Feb 2024
This paper presents an assessment of the controls of aerosol hygroscopicity for well-aged biomass burning aerosol over the South-East Atlantic ocean during ORACLES 2016 and 2018. Measurements of f(RH) and chemical composition ratios are shown in order to derive the hygroscopicity of organic aerosol specifically. A complicated parameterization is developed that depends on organic/sulfate ratio, black carbon mass fraction, and organic aerosol hygroscopicity, and is shown to reproduce the measured data. The conclusions are important: variability of the organic hygroscopicity of biomass burning can significantly alter the overall hygroscopicity of particles.
The manuscript is generally well-written and organized. More measurement detail is needed in the paragraph at line 111. Please include a description about how the relative humidity (RH) sensor for the humidified nephelometer was calibrated, and if this is the basis for the stated 3% uncertainty. Also, please include a description of how the sample was humidified, or include a reference for the approach. For what size range are the nephelometers measuring scattering coefficient? Is this governed by the aircraft inlet or by internal tubing limitations? Are there any losses in the humidification system that would complicate a quantitative comparison of dry vs. humid scattering?
Additionally, only mass fractions of aerosol components are presented. Without presenting absolute concentrations, it is difficult to assess what components are driving changes in mass fraction, and if low concentrations are driving increased uncertainty in the derived ratios. Please consider including profiles with actual mass concentrations for the AMS components and BC.
131 How was the UHSAS calibrated? PSL or at another refractive index?
134 What particles are assumed to dominate the coarse mode to justify a spherical assumption? Sea-salt or dust?
135 What do the subscripts “i" and “X” represent in the equation? Are you assuming kappa values for BC, and what kappa values are assumed for inorganic components? Please include a better description of Equation (3), which is vital to the paper results.
182 Since you are assessing hygroscopicity, and invoking the SO4/OA ratio to explain variability, can you plot the vertical distribution of SO4/OA?
191 You reference a pressure but are plotting altitude. Please be consistent.
194 The airmass age at the surface from Fig2 seems very similar between years. Both 10-12 days. Please confirm this statement. The biggest difference seems to be that the 2018 data looks less aged aloft.
248 You are plotting and interpreting the dependence on ambient temperature; how does that temperature relate to the temperature directly at the AMS? During the description of the dry Nephelometer, you note that drying occurs because of heating inside the aircraft cabin, so does this also apply to the AMS measurements? Does the measurement temperature vary with the ambient temperature significantly?
265 Is the AMS sensitive to sea-salt sulfate using a standard vaporizer temperature of 600C? Was the AMS operated at 600C?
285 I do not see any plots to assess the vertical variability of SO4/OA to assess this statement.
293 What is the typical MBL height during measurements? Is there a measurement to corroborate this statement?
Citation: https://doi.org/10.5194/egusphere-2023-2199-RC2
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 315 | 88 | 27 | 430 | 40 | 20 | 19 |
- HTML: 315
- PDF: 88
- XML: 27
- Total: 430
- Supplement: 40
- BibTeX: 20
- EndNote: 19
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
