the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 25 Jul 2025
Characteristics of Legacy and Emerging Per- and Polyfluoroalkyl Substances in Atmospheric Total Suspended Particulate from The Coastal Areas in China
Abstract. Per- and polyfluoroalkyl substances (PFASs) could be attached to particles and transported in the atmosphere, it is necessary to investigate the characteristics of legacy and emerging PFASs in atmospheric particulates in relatively clean, low pollution open ocean in China to reveal the transport mechanism of PFASs in the atmosphere. Concentration characteristics of 30 legacy and emerging in total suspended particulate (TSP, particles with aerodynamic diameters < 100 μm) from Laoshan in Shandong and Xisha Islands in the South China Sea were analyzed. ∑PFASs in TSP ranged in 5.65–80.1 pg/m3 and 3.59–18.2 pg/m3 for Laoshan and Xisha Islands, respectively. Generally, the long-chained PFASs were the most detected PFAS, with the detection frequency of 73.1 % and 72.0 %. Perfluorooctanoic acid (PFOA) were the main PFAS, with the profiles of 57.1 % and 21.0 %, respectively. Principal component analysis and multiple linear regression (PCA-MLR) showed that the Laoshan was dominated by fluoropolymer manufacturing (46.9 %) and metal electroplating/electrochemical processes (36.3 %), while the Xisha islands exhibited primary contributions from textile treatment sources (53.4 %) and precious metal sources (42.2 %). The backward trajectory clusters for 24 h/120 h showed that air masses in the Laoshan primarily originated from northern (23 %) and southeastern (28 %), the Xisha Islands were predominantly sourced from the northeastern (80 %), overlapping transport paths of air masses between the two regions within the same altitude range. This suggests that that the similarity of PFAS distribution characteristics between Laoshan and Xisha may be related to long-distance atmospheric transport between the two regions.
- Preprint
(1499 KB) - Metadata XML
-
Supplement
(1008 KB) - BibTeX
- EndNote
Status: open (until 08 Oct 2025)
-
RC1: 'Comment on egusphere-2025-3127', Anonymous Referee #1, 01 Sep 2025
reply
General Comments:
The authors collected particulate matter from Laoshan (along the coast of the East China Sea) and from the Xisha Islands (in the South China Sea) and tested for 30 PFAS. They quantified 19 PFAS at Laoshan and 14 at Xisha. As in other studies, long-chain PFCAs were most prevalent, so this result is not particularly surprising. Among the emerging PFAS tested, HFPO-DA, 6:2 Cl-PFESA, and PFOSA were detected at Laoshan only; DONA at Xisha Islands only; and 6:2 FTSA at both sites. It is intriguing to see the spike of DONA on March 15-17, though not explored much in the manuscript.
The scientific approach is generally appropriate. The authors describe QA/QC measures, but they should include more details about blanks to demonstrate full scientific rigor, as described in more detail below. I also caution against over-interpreting the sectors of PFAS sources identified from PCA-MLR. With the current selection of figures in the manuscript, it is not easy for the reader to make direct comparison between measured PFAS concentrations at the two sampling sites. See below for suggested changes.
Specific Comments:
(1) Lines 16-18 of Abstract: What do the authors mean by “the similarity of PFAS distribution characteristics”? The distribution characteristics of Figures S1 vs S2 do not look similar to me, nor do the pie charts in Fig 5.
(2) Lines 41-42: I question the authors’ statement that few studies have focused on atmospheric PFAS in China. They cite at least 8 works in the manuscript published between 2015-2019. There are also multiple papers published more recently. As most relevant, the authors should recognize the coastal and marine measurements from southeastern China by Yamazaki et al. (DOI 10.1016/j.chemosphere.2021.129869).
(3) Line 102: Some of the target analytes lacked a corresponding isotopically labelled standard. Were the concentrations of 6:2 Cl-PFESA, HFPO-DA, and DONA corrected by the percent recoveries in Table S4? If yes, please specify. If no, I recommend to acknowledge that detections and absolute quantitations of 6:2 Cl-PFESA, HFPO-DA, and DONA are likely to be underestimates because of analyte loss during sample prep, e.g., from sorption to the nylon filter.
(4) Lines 106-108: It seems misleading to say that PFAS levels in all blanks were either not detected or below MDLs because the MDLs were defined based on blank concentrations. Could the authors please clarify? I recommend to add blanks to the data tables in the SI for full transparency. For example, it seems counterintuitive for the MDL for 6:2 FTS to be so low when its percent recovery is >> 100, suggesting background contamination.
(5) Figures 2 and 3: If the goal is to compare PFAS profiles at Laoshan and Xisha Islands, then I suggest that the authors make Figures 2 & 3 two-panel figures with one panel for each site. Otherwise it’s hard to make a visual comparison of concentrations when the Laoshan data in Fig 2 are displayed in a different format from the Xisha Islands data in Fig 3.
(6) Figure 3: Is the daily average concentration of PFAS integrated over a full 24-hour period?
(7) Sample Collection for Xisha Islands: In lines 197-205, the authors hypothesize that day vs night differences occur because the ship was sailing in the day and stationary at night. I find the discussion somewhat confusing.
(a) What can the authors learn from the exceptions, i.e., night samples when the ship was in motion (XS-02 and XS-22)?
(b) I have a related clarifying question: In lines 199-202, the authors write, “The daytime concentration was the highest on the 16th, and the difference between day and night concentration was significant, mainly because the day and night samples were collected when the ship was stationary and sailing.” Are the two halves of this sentence connected? In other words, are the authors specifically stating that there was a significant difference between day and night concentrations on March 16? Based on my interpretation of Table S2, the day and night samples associated with 20210316 are XS-21 and XS-22, and the ship was sailing for both and stationary for neither.
(c) It could be helpful if the authors number the sampling sites in Figure 1 to connect them to the samples in Table S2.(8) Lines 225-239: I caution that the authors are unlikely to find significant and strong correlations for the emerging PFAS given that the data set is heavily censored (lots of n.d.’s and <MDL’s).
(9) Section 3.3, Source Apportionment: How distinct are the different groupings? An individual PFAS has many uses, and in addition to direct emissions, PFCAs can also form from atmospheric degradation of FTOHs.
(10) Lines 278-290: PCA-MLR provides evidence but not proof. I suggest the authors use conditional language for their conclusions. For example, “The main sources of PFASs in Laoshan area may be...” or something similar.
(11) Figure 6: I do not understand the display of dual-source backward trajectory clusters. The caption says that (c) and (d) show different sampling time periods. When are the periods?
(12) Tables S5 and S6: It would be helpful to add row(s) with some summary statistics like min-max range, average and standard deviation.
Technical Corrections:
(1) Line 210: ADONA is misspelled.
(2) Figure 3: The x axis is missing a title (date in March 2021). The figure caption should indicate that the red line goes with the right axis.
(3) I advise the authors to use the acronym LC-PFCAs for long chain PFCAs because L-PFCAs could be misinterpreted as linear PFCAs.
(4) What type of correlation analysis did the authors conduct? Line 118 says Spearman, but line 225 says Pearson.
(5) TOC art: There is a lot of information in this figure. It will likely be difficult to interpret at scale.
(6) Text S1, third line of first paragraph: Internal standard mix should be MPFAC-MXA.
Citation: https://doi.org/10.5194/egusphere-2025-3127-RC1
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 297 | 42 | 11 | 350 | 22 | 5 | 10 |
- HTML: 297
- PDF: 42
- XML: 11
- Total: 350
- Supplement: 22
- BibTeX: 5
- EndNote: 10
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1