Retrieval of the Depolarization Ratio of Graphite Particles Using an Aerosol Chamber

Park, Gahyeon; Kim, Dukhyeon; Noh, Youngmin; Cho, Gangnam

doi:10.5194/egusphere-2026-2900

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https://doi.org/10.5194/egusphere-2026-2900

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10 Aug 2026

| 10 Aug 2026

Status: this preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).

Retrieval of the Depolarization Ratio of Graphite Particles Using an Aerosol Chamber

Gahyeon Park, Dukhyeon Kim, Youngmin Noh, and Gangnam Cho

Abstract. This study derives the intrinsic depolarization ratio of graphite particles using a custom-built near-field polarization light detection and ranging (LiDAR) system combined with an aerosol chamber. To minimize the inherent geometric overlap problem in typical LiDAR systems, the receiver and chamber were separated by 30 m and signals were acquired at ultrahigh spatial resolution (0.03 m). Pure graphite particles and fugitive graphite particles collected from a steel plant were individually injected into a standardized chamber using a dust feeder. Parallel and perpendicular polarized backscatter signals were then measured at a wavelength of 532 nm. Background aerosol signals in the acquired raw data were eliminated through signal preprocessing and a correction algorithm. Ultimately, the intrinsic depolarization ratio was calculated as 0.15 ± 0.01 for pure graphite and 0.16 ± 0.03 for mixed particles collected from the steel plant. The results are statistically consistent (within the margin of error). The derived optical indicators provide a scientific foundation for the future development of remote monitoring technologies that can measure fugitive dust originating from steel plants in real time.

Received: 21 May 2026 – Discussion started: 10 Aug 2026

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Gahyeon Park, Dukhyeon Kim, Youngmin Noh, and Gangnam Cho

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RC1:
'Comment on egusphere-2026-2900', Anonymous Referee #1, 26 Aug 2026 reply
The authors present measurements of the particle linear depolarisation ratio of graphite particles performed with a novel experimental setup that combines a lidar system with an aerosol chamber. In principle, the work is of interest to the readers of AMT. However, there are a number of issues that have to be addressed in a major revision before this work could be considered for publication.
Major issues:
I strongly recommend that the authors consider using community-approved names and signs for the considered parameters as it is not always clear what they are referring to. This matters as the depolarisation ratio is a parameter that demands very specific information. Please consult Freudenthaler et al. (2009, https://doi.org/10.1111/j.1600-0889.2008.00396.x) as a standard reference. In my understanding, the total mixed depolarisation ratio is what's known as volume linear depolarisation ratio and the intrinsic depolarisation ratio is the particle linear depolarisation ratio (PLDR). In any case I didn't double-check the equations in Section 2.3 because of the irritating nomenclature.

I am missing a discussion of relevance. Specifically, I would be interested about the size range and concentration of fugitive dust from steel plants. Don't they have measures for depositing most of this material? Is whatever is actually emitted comparable to the size distribution and concentration generated in the aerosol chamber? This matters for assessing the use of the chamber measurements for atmospheric application.

I generally like the setup that the authors have developed for this study. However, I would actually expect that a novel setup is tested in a series of measurements to assess performance: Does an empty chamber reproduce the PLDR of the outside air? Does a measurement with spherical particles give a PLDR of zero? Can you reproduce literature values when feeding mineral dust into the chamber? It's somewhat audacious to present new findings with an unverified setup.

Minor issues:
line 40: a PLDR of unity means that the reflected light is completely unpolarised and this doesn't really happen. Note that PLDR gives an indication of sphericity or nonsphericity and that "completely nonspherical particles" is a meaningless designation.

Section 2: I suggest to remove subsubsections and restructure as 2.1 Experimental setup, 2.2 Lidar instrument, 2.3 PLDR calculation

Figure 2 could be omitted. The only relevant information is the distance between lidar and chamber (which could be added to Figure 1) and that measurements were performed outside.

line 108: Is this an open chamber or are there windows on the sides that could affect the depolarisation measurement? Do you have any measurements of particle size distributions or concentration? Have you checked that the particles are properly mobilised and homogeneously distributed in the chamber?

Line130 and subsequent equations: I am missing the effect of the molecules in the air. The mixed depolarisation ratio (if it's the same as VLDR) should include molecules, graphite, and all the other ambient aerosols. The latter two contribute to PLDR which then needs to be disentangles for graphite and the rest.

Line 138 and line 150: Applying a background value and a correction factor seems a lot like you are doing a relative calibration of the PLDR. If that's the case, please state it so that readers understand what you are doing. Also, couldn't you perform an absolute calibration of the PLDR?

Figures 4 and 5: Not sure if both are needed. There is certainly too little text to warrant both.

Table 2: explain the meaning of the parameters in the table header.

Figure 7: This is nice to see but the information is the same as in Figure 8. So maybe omit or move to appendix?

Figure 8: What do the error bars represent? Are they the standard deviation of the mean of the values in Figure 7? If that's the case, do you also have an estimate of the absolute error? An absolute calibration of the PLDR or measurements along the lines of major comment 3 could be of help here.

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Citation: https://doi.org/10.5194/egusphere-2026-2900-RC1

Gahyeon Park, Dukhyeon Kim, Youngmin Noh, and Gangnam Cho

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Short summary

Steel plants release harmful graphite dust that is hard to track. To solve this, we used a custom light-based remote sensing system and a controlled chamber to measure how graphite reflects light. We discovered that graphite has a unique optical fingerprint, reflecting light differently than natural dust or other pollution. This distinct signature allows us to remotely identify and track graphite pollution in real time, helping to improve industrial air quality monitoring and public health.


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