the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 01 Sep 2025
An innovative approach to measuring hygroscopic light scattering enhancement using a humidified single-nephelometer system
Abstract. Most atmospheric aerosol particles are hygroscopic, meaning they absorb water from the surrounding air, altering their size, shape, overall chemistry, refractive index, and thus light-scattering properties – an effect with important implications for Earth's radiative balance. The scattering enhancement factor, f(RH), and backscattering enhancement factor, f(RH)bsp, quantify the increase in light scattering under elevated relative humidity (RH). These parameters are typically measured using two nephelometers operating under dry (RH < 40 %) and humidified (RH > 80 %) conditions, a method prone to interinstrument uncertainties. This study presents a novel single-nephelometer system that reduces measurement uncertainty and studies aerosol hygroscopic behavior in the inadequately represented European urban environment. The system was deployed at a suburban site in Prague, Suchdol, Czech Republic, from November 2022 to August 2023. Results revealed low aerosol hygroscopicity, likely due to a well-mixed aerosol population dominated by black and brown carbon. Both enhancement factors peaked in spring, possibly influenced by favorable conditions for new particle formation and changes in aerosol composition, size distribution, and meteorological conditions. In contrast, low values in summer reflected a composition shift toward black carbon-dominated aerosols from traffic emissions, with particle growth being disrupted, potentially due to the structural compaction of black carbon aggregates under high RH. While f(RH) and f(RH)bsp generally increased with decreasing concentrations of light-absorbing particles, organic carbon, particularly its most volatile fractions, significantly enhanced aerosol hygroscopicity in the urban environment. Despite low aerosol hygroscopicity, increased RH significantly influenced aerosol climate-relevant variables.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2025-3800', Anonymous Referee #1, 19 Oct 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-3800/egusphere-2025-3800-RC1-supplement.pdfCitation: https://doi.org/
10.5194/egusphere-2025-3800-RC1 -
RC2: 'Comment on egusphere-2025-3800', Anonymous Referee #2, 25 Nov 2025
Summary:
The manuscript presents measurements of particle hygroscopicity in the form of scattering enhancement factor derived from a single RH-switched nephelometer. A new instrument was developed and operated for approximately nine months at a suburban site outside of Prague, Czech Republic. Data are presented both for a traditional hemispheric scattering measurement and also for backscatter-specific hygroscopicity. Results suggest a dominance of low-hygroscopicity, highly-absorbing aerosol at the site, and correlations with other aerosol properties are discussed. Inclusion of backscatter f(RH) measurements is a nice unique addition to the literature and could be emphasized more throughout the manuscript. Still, major revisions are necessary before publication to address concerns regarding the validity of the approach when conditions are changing on sub-hour timescales, and the validity of highly absorbing aerosol observations.
Major critiques:
- The manuscript focuses on a self-described “innovative approach” or “novel” system to measure ambient aerosol hygroscopicity (i.e., f(RH)). But in my opinion, the method that is presented is at best functionally the same as previous work, or depending on your application it is less robust. The novel aspect of the new approach is utilizing a single nephelometer and automatically switching the sample pre-treatment systematically back and forth from dry to humid relative humidity. This switching is done at 1-hour frequency, resulting in an f(RH) calculation once every 3 hours (i.e., every dry-humid-dry or humid-dry-humid cycle). For comparison, aircraft-based hygroscopicity measurements are done utilizing multiple instruments in parallel, thus producing dry and wet datasets simultaneously (i.e., Brock et al. [2015] or Ziemba et al. [2013]). Clearly ground-based measurements do not require the same fast time-response, but the manuscript does not adequately describe the merits of using a single instrument. For example, the abstract claims (Line-17, also Line-63) that the new system “reduces measurement uncertainty” but does not justify this improvement. Can this improvement in measurement uncertainty be quantified? The authors should add text to provide more clarity. Additionally, at least one study already employs a single-nephelometer-based f(RH) measurement (Orozco et al., 2016) and should be cited.
- Another result of this work is the dominance of low-hygroscopicity and highly-absorbing aerosol in the region. Table 1 reports seasonal SSA values of 0.65-0.76. These are extremely low for ambient aerosols and require more explanation. For example, SSA values globally are typically greater than 0.9 (Devi and Satheesh, 2022), even in regions dominated by biomass burning. Part of this concern is the lack of discussion regarding aethalometer-based absorption corrections (of which SSA values are based). Aethalometer observations are filter-based, and typically require correction for scattering from the filter media directly or from the aerosols collected on the filter (e.g., Virkkula et al. [2010]). Backman et al. [2017] report a correction factor of 3.45 for Arctic sampling. Coen et al. [2010] also describe numerous correction schemes developed for aethalometers. Given such low SSA values, a more in-depth discussion and scrutiny of the reported absorption data is critically important.
Specific Comments:
Line Comment
TITLE I’m not sure that “innovative approach” should be highlighted in the title, since the I don’t think the method is really the focus of the paper. I suggest revising to something emphasizing seasonal variability for hemispheric and backscatter hygroscopicity.
74 How is instrument exhaust treated and are you able to verify that exhaust never contaminates the sample line?
85 Please add additional instrumental details for the instrument, including:
- Nafion dryer model number for the common dried line,
- Nafion dryer model for the humidifier stage,
- theoretical (or preferably experimental) size-dependent particle losses in each of the Nafion dryers,
- theoretical (or preferably experimental) size-dependent particle losses in the 4-way valve, and
- typical water temperature used for humidification, and whether there is any heating of sample air in the system
145 Please provide a description and references for any corrections applied to the aethalometer data.
150 Please provide the mass absorption efficiency used to convert absorption to BC mass. Was this conversion factor wavelength dependent?
167 Why do you have to assume the dew-point is preserved when you are directly measuring both the inlet and outlet temperature and RH? From that data, did you have to filter any of the dataset for instances when the RH dramatically changed inside the nephelometer?
180 When enhancement factors are calculated, are they referenced specifically to RH = 40% and RH = 80%? If the RH control varied or drifted, was the data corrected back to 40 and 80% for calculation of the enhancement factor? For example, if the dry RH was actually controlled at 32%, was this scattering data corrected to 40% or simply assumed to be “dry”? Similarly for the humidified sample, how did you treat data when the control RH deviated from 80%?
188 Are the conditioning periods shown in Figure 3? Can those periods be marked in the figure to assess stability in the system?
188 This looks like a rather ideal period for calculating the 50-minute averages, but how does your method handle periods when dry scattering changes significantly during the 3-hour period? Gradual changes, but more likely fast changes associated with frontal passages or airmass changes, will could result in incorrect f(RH) calculations. How is this flagged or filtered in your method?
235 How are new particle formation events relevant to this work? This section seems outside the scope of the paper and should be removed.
288 It’s not clear that f(RH) truly “varies with seasons”, since only Fall is inconsistent. Likewise, it is very difficult to assess whether the different Fall slope is real or just a statistical anomaly (the yellow points are very hard to see). You may want to consider 4 separate panels, one for each season.
284 It appears that some fraction of datapoints show f(RH) and f(RH)bsp values below 1. Interestingly, the data do not converge at f(RH) AND f(RH)bsp = 1, with potentially more backscatter data below 1. Can you comment on the interpretation of these sub-1 data, and why backscatter might behave differently? Do you think a soot restructuring process is occurring similar to Shingler et al. [2016]?
303 The slopes from Figure 4 seem very different from the values stated here. Can you comment on the cause of the difference?
411 This discussion of hygroscopicity variability as a function of OC/POC/SOC is challenging without knowledge of the aerosol sulfate content. Could most of the f(RH) variability be driven by the organic mass fraction, and be less sensitive to relative contributions of different organic species? Please comment on the importance of sulfate (or nitrate) for interpreting hygroscopicity.
424 Similar comment. Most literature shows that hygroscopicity increases as organic mass fraction decreases (contrary to your statement), e.g., Massoli et al. [2009]. Please comment.
420 The y-axix of this plot is difficult to understand. Can you update the axis label to be more explicit with how you calculated “normalized log levels”?
451 Again, NPF correlation does not seem causal or robust, and should be removed, including Figures 12 and 13.
References:
Brock [2015] = doi.org/10.5194/acp-16-4987-2016
D and S [2022] = doi.org/10.5194/acp-22-5365-2022
Massoli [2009] = doi.org/10.1029/2008JD011604
Orozco [2016] = doi.org/10.1002/2015JD023971
Shingler [2016] = doi.org/10.1002/2016JD025471
Virkkula [2010] = doi.org/10.1080/02786826.2010.482110
Ziemba [2013] = doi.org/10.1029/2012GL054428
Citation: https://doi.org/10.5194/egusphere-2025-3800-RC2
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