the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 22 Mar 2024
Characterizing water solubility of fresh and aged secondary organic aerosol in PM2.5 with the stable carbon isotope technique
Abstract. The investigation of the water-soluble characteristics of secondary organic carbon (SOC) is essential for a more comprehensive understanding of its climate effects. However, due to the limitations of the existing source apportionment methods, the water solubility of different types of SOC remains uncertain. This study analyzed stable carbon isotope and mass spectra signatures of total carbon (TC) and water-soluble organic carbon (WSOC) in ambient PM2.5 samples for one year and established stable carbon isotope profiles of fresh and aged SOC. Furthermore, the Bayesian stable isotope mixing (BSIM) model was employed to reveal the water solubility characteristics of fresh and aged SOC in a coastal megacity of China. WSOC was dominated by secondary sources, with fresh and aged SOC contributing 28.1 % and 45.2 %, respectively. Water-insoluble organic carbon (WIOC) was dominated by primary sources, to which fresh and aged SOC contributed 23.2 % and 13.4 %. We also found the aging degree of SOC has considerable impacts on its water solubility due to the much higher water-soluble fraction of aged SOC (76.5 %) than fresh SOC (54.2 %). Findings of this study may provide a new perspective for further investigation of the hygroscopicity effects of SOC with different aging degrees on light extinction and climate change.
-
Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
-
Preprint
(1252 KB)
-
Supplement
(786 KB)
-
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(1252 KB) - Metadata XML
-
Supplement
(786 KB) - BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-736', Anonymous Referee #1, 10 Apr 2024
Investigating the water solubility of SOA is a highly significant topic, because it has a significant impact on its climatic effects. This work utilized carbon isotopic techniques and mass spectrometry method to evaluate the water solubility of SOA with varying degrees of aging, basing on one-year ambient PM2.5 data and established stable carbon isotope profiles of fresh and aged SOA. This work found that SOA has high water solubility, and the solubility of aged SOA is higher than that of fresh SOA. The finding of this work is of great significance for us to deeply understand the climatic effects of SOA. There are certain issues that need to be addressed before considering this work for publication.
- The source apportionment based on offline data involves water-soluble ions and heavy metal components. The relevant analysis methods should be briefly introduced in the main text and described in detail in the Supplementary Information (SI). Quality control should also be briefly explained.
- The results of the PMF model should be explained in greater detail, including the explanation of the source profiles identified by PMF and the evaluation of the model results.
- The uncertainty assessment of the Bayesian model is crucial, it is better to move Figure S5 to the main text.
- To ensure consistency and clarity, it is advisable to arrange the various sources in Figure 4(a) in a uniform order.
- Lines 305-306, the meanings of "[c]water-soluble" and "[c]water-insoluble" should be clearly explained to avoid any ambiguity.
- Figure 5(c) appears redundant as it overlaps with Figure 5(b) in terms of information presented. To streamline the content, it is advisable to include the slope information within Figure 5(b).
- Line 38, the full name of CCN should be clearly listed at the first mention in the main text.
Citation: https://doi.org/10.5194/egusphere-2024-736-RC1 -
AC1: 'Reply on RC1', Xing Peng, 09 May 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-736/egusphere-2024-736-AC1-supplement.pdf
-
RC2: 'Comment on egusphere-2024-736', Anonymous Referee #2, 15 Apr 2024
The manuscript analyzed the water-soluble and water insoluble organic carbon in a coastal megacity of China. The sources and contributions of WSOC and WIOC to PM2.5 were explored with Bayesian stable isotope mixing model, and the water solubility of fresh and aged SOC in the coastal megacity of China were revealed. The study is important and meaningful, while there are still some questions need to be clarified to improve the manuscript.
Specific comments:
- I am confused about how the BSIM and PMF model used in the source apportionment of the TC and WSOC. The author should re-organize section 2.3 to make it clear.
As described in section 2.3, The four sources, including traffic, biomass burning, the fresh SOC and aged SOC were resolved by PMF model. The author also obtained the stable carbon isotope fingerprints by traffic emission samples collected in tunnels, fresh SOC simulated through petrol vehicle bench tests, aged SOC samples collected at a background monitoring station and biomass burning samples simulated through laboratory experiment.
Did the fingerprint above were used as prior information in the BSIM model? What about the δ13C/‰ values of the four sources? How could the author verify the representation of the four source fingerprints and that they can be properly used in Shenzhen?
- This study firstly employed BSIM model to quantify the contributions of fresh and aged SOC to WSOC and WIOC. The author claimed the consistence of the results form BSIM and PMF model. My question about the method used in this study is what is the advantages of the BSIM model compared with PMF model? Why was the result of BSIM model used for the final analysis?
- Line137-138, the SOC was divided into fresh SOC and aged SOC based on the oxidation state, what is theexact values of the average oxidation state of carbon (OSc) orO/C of the two SOC sources?
- Line 162, table 1 showed the δ13C/‰ values of the four sources in TC and WSOC, I noticed that the value of δ13C/‰ for different OC showed obvious overlap, for example, the values of fresh SOC in WSOC and TC were lower and higher than that of traffic source, respectively? How did the sources were determined being clearly separated by the values of δ13C with the existence of the obvious overlap of the δ13C/‰?
- Line332, the meaning of the dots and lines in Figure 5a should be added.
- Line 338-339, the reference has been listed in the legend of figure 5, so it doesn’t need to be listed in the caption here.
- The subdivided OOAs were name as fresh SOC and aged SOC in the manuscript, while they were named MO-OOA and LO-OOA in Figure S4. Please make the names of these items consistency through the manuscript or add some statement of the difference.
Citation: https://doi.org/10.5194/egusphere-2024-736-RC2 -
AC2: 'Reply on RC2', Xing Peng, 09 May 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-736/egusphere-2024-736-AC2-supplement.pdf
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-736', Anonymous Referee #1, 10 Apr 2024
Investigating the water solubility of SOA is a highly significant topic, because it has a significant impact on its climatic effects. This work utilized carbon isotopic techniques and mass spectrometry method to evaluate the water solubility of SOA with varying degrees of aging, basing on one-year ambient PM2.5 data and established stable carbon isotope profiles of fresh and aged SOA. This work found that SOA has high water solubility, and the solubility of aged SOA is higher than that of fresh SOA. The finding of this work is of great significance for us to deeply understand the climatic effects of SOA. There are certain issues that need to be addressed before considering this work for publication.
- The source apportionment based on offline data involves water-soluble ions and heavy metal components. The relevant analysis methods should be briefly introduced in the main text and described in detail in the Supplementary Information (SI). Quality control should also be briefly explained.
- The results of the PMF model should be explained in greater detail, including the explanation of the source profiles identified by PMF and the evaluation of the model results.
- The uncertainty assessment of the Bayesian model is crucial, it is better to move Figure S5 to the main text.
- To ensure consistency and clarity, it is advisable to arrange the various sources in Figure 4(a) in a uniform order.
- Lines 305-306, the meanings of "[c]water-soluble" and "[c]water-insoluble" should be clearly explained to avoid any ambiguity.
- Figure 5(c) appears redundant as it overlaps with Figure 5(b) in terms of information presented. To streamline the content, it is advisable to include the slope information within Figure 5(b).
- Line 38, the full name of CCN should be clearly listed at the first mention in the main text.
Citation: https://doi.org/10.5194/egusphere-2024-736-RC1 -
AC1: 'Reply on RC1', Xing Peng, 09 May 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-736/egusphere-2024-736-AC1-supplement.pdf
-
RC2: 'Comment on egusphere-2024-736', Anonymous Referee #2, 15 Apr 2024
The manuscript analyzed the water-soluble and water insoluble organic carbon in a coastal megacity of China. The sources and contributions of WSOC and WIOC to PM2.5 were explored with Bayesian stable isotope mixing model, and the water solubility of fresh and aged SOC in the coastal megacity of China were revealed. The study is important and meaningful, while there are still some questions need to be clarified to improve the manuscript.
Specific comments:
- I am confused about how the BSIM and PMF model used in the source apportionment of the TC and WSOC. The author should re-organize section 2.3 to make it clear.
As described in section 2.3, The four sources, including traffic, biomass burning, the fresh SOC and aged SOC were resolved by PMF model. The author also obtained the stable carbon isotope fingerprints by traffic emission samples collected in tunnels, fresh SOC simulated through petrol vehicle bench tests, aged SOC samples collected at a background monitoring station and biomass burning samples simulated through laboratory experiment.
Did the fingerprint above were used as prior information in the BSIM model? What about the δ13C/‰ values of the four sources? How could the author verify the representation of the four source fingerprints and that they can be properly used in Shenzhen?
- This study firstly employed BSIM model to quantify the contributions of fresh and aged SOC to WSOC and WIOC. The author claimed the consistence of the results form BSIM and PMF model. My question about the method used in this study is what is the advantages of the BSIM model compared with PMF model? Why was the result of BSIM model used for the final analysis?
- Line137-138, the SOC was divided into fresh SOC and aged SOC based on the oxidation state, what is theexact values of the average oxidation state of carbon (OSc) orO/C of the two SOC sources?
- Line 162, table 1 showed the δ13C/‰ values of the four sources in TC and WSOC, I noticed that the value of δ13C/‰ for different OC showed obvious overlap, for example, the values of fresh SOC in WSOC and TC were lower and higher than that of traffic source, respectively? How did the sources were determined being clearly separated by the values of δ13C with the existence of the obvious overlap of the δ13C/‰?
- Line332, the meaning of the dots and lines in Figure 5a should be added.
- Line 338-339, the reference has been listed in the legend of figure 5, so it doesn’t need to be listed in the caption here.
- The subdivided OOAs were name as fresh SOC and aged SOC in the manuscript, while they were named MO-OOA and LO-OOA in Figure S4. Please make the names of these items consistency through the manuscript or add some statement of the difference.
Citation: https://doi.org/10.5194/egusphere-2024-736-RC2 -
AC2: 'Reply on RC2', Xing Peng, 09 May 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-736/egusphere-2024-736-AC2-supplement.pdf
Peer review completion
Journal article(s) based on this preprint
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 329 | 69 | 30 | 428 | 45 | 37 | 21 |
- HTML: 329
- PDF: 69
- XML: 30
- Total: 428
- Supplement: 45
- BibTeX: 37
- EndNote: 21
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
Fenghua Wei
Xing Peng
Liming Cao
Mengxue Tang
Ning Feng
Xiaofeng Huang
Lingyan He
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(1252 KB) - Metadata XML
-
Supplement
(786 KB) - BibTeX
- EndNote
- Final revised paper