Secondary Organic Aerosols in PM2.5 in Bengbu, a Typical City in Central China: Concentration, Seasonal Variation and Sources
Round 1
Reviewer 1 Report
In manuscript ID Atmosphere-1242213, entitled "Secondary organic aerosols in PM2.5 in Bengbu, a typical city in Central China: concentration, seasonal variation and sources", the authors analyzed the concentrations of organic carbon, elemental carbon, water-soluble organic carbon and organic tracers in the seasonal PM2.5 samples at one urban and one suburban site. In general, the work is of interest, but I believe that due to the numerous analyzes performed, the manuscript is quite difficult to read. In this regard, I suggest rewriting at least the conclusions, as well as the abstract. I also suggest better define the conclusion of this study: how this information can be used for a comprehensive understanding of China's air pollution? How can this study contribute to the development of air pollution control strategies?
- Introduction: In my opinion, the first part of the introduction (lines 33-61) is a bit confusing, and I think the concepts reported can be rewritten more clearly.
- Introduction: I suggest better specifying in this session the objectives of the work. In addition, due to the numerous analyzes performed, I suggest specifying how the paper is structured (referring to the results section in particular), to facilitate reading.
- Line 67: How can it be defined as “representative”?
- Line 69: I suggest adding a citation regarding “Moreover, air 68 quality in Bengbu is still poor especially in autumn and winter”.
- Figure 1: I suggest making this image clearer: for example, I suggest reporting the station names as they are shown in the text. In addition, I believe that Hefei has never been mentioned before (I see a reference only later in the text): I suggest explaining its importance in the text or to eliminate it from the figure.
- Paragraph 2.2. I suggest reporting some more LOD information.
- Line 90: I suggest adding a reference to "baked at 500 oC for more than 4 h before usage."
- Line 127: Has the number of motor vehicles been determined in any way? From literature?
- Line 128-130: What statistical tests were used to evaluate these differences?
- Line 134-137: I believe that the impact of meteorological variables on OC and EC concentrations should be better discussed, also reporting bibliographic references.
- Line 154: For completeness, I suggest also reporting the intercept value.
- Line 247: If I am not mistaken it has not been previously specified how the temperature data were acquired: I suggest specifying it.
Author Response
Please see the attachment.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
This paper was very difficult to read. Initially, I had edited a bit for english, but that became tedious. The results are difficult to read through because there are frequently unsupported and highly speculative interpretations of the data. Additionally, the lack of variability and reported uncertainties made it difficult to assess the quality of the speculation. Also, there are often correlations that are referred to, but they are not shown. From table 3 below there are presumably very large uncertainties, and the authors make reference to the uncertainty, but it is not reported in the paper. For me, this is the crucial failing of the paper, because I am unable to assess the merits of the conclusions being drawn. Overall, the paper has a feeling of a report that has been turned into a publication. I would like to see more of the data rather than tables reporting seasonal averages and a better connection to more recent publications. I cannot recommend publication until there are details regarding the uncertainties including error propagation through the whole analysis.
Major comments:
Table 1 should include the variability in the measurements. (the variability is mentioned beginning on line 148) Please include other variables from the sites (e.g. RH, T, etc…)
Lines 135 – 145: “The main reason for the high winter concentration and the observed seasonal variation of OC and EC should be the seasonal difference of meteorological conditions (such as temperature, wind direction and atmospheric mixing height)…
Then beginning of the next paragraph: Higher OC/EC ratio was found in summer than other seasons (Table 1), in accordance with the higher formation rate of SOA under the higher temperature and stronger solar radiation in summer”
Doesn’t this mean the season variation is also dependent upon other things that meterological conditions? Because the SOA sources vary dramatically with season (as you show later). The discussion about seasonal variation should be revised.
Line 141: “It could also be found from Table 1 that the OC/EC ratio at WH was significantly higher than that of HBJ, indicating the stronger influence of SOA and secondary photochemical reaction at WH.»
The absolute scale of OC from both sites is identical for the summer. This statement is not correct, the OC/EC depends mostly on the small concentration of EC present, not any significant difference in SOA production.
Lines 153-155: why does this mean it is characteristic of regional pollution? Provide more detail. There is also a disconnect with line 144 where the opposite thing is said (external transport is said to be important).
Line 166-168: this is not supported by any data shown so far. What if it is just the absence of biogenic emissions?
Table 2 should include the variability in the measurements.
Lines 255 - 257: Studies showed 255 that α-pinene was first oxidized to pinic acid in the atmosphere, and then further oxidized 256 to form SOA [36].
- This implies that pinic acid is not low enough volatility to form SOA. This is not true (even based on the citation).
Table 3: I am unable to assess the error or variability present in the numbers shown in Table 3. Is this statistically significant? I can’t comment on section 3.3.2 as a result. This error will be compounded in the following section for Table 4.
Line 410: Despite the large uncertainties in the estimation of SOC concentration, the tracer based method could give important information on the sources of SOA in PM2.5 in Bengbu and their seasonal variations (Table 4).
- No uncertainty is reported! The rest of the paper builds upon SOC values that presumably have large uncertainties. This will create a scenario where the further reported values will have even larger uncertainties.
Other comments:
Line 143: either go further in depth and try to connect the transport with where it comes from or leave this out. It is too nebulous to say this with any certainty beyond the presented speculation.
Line 212 “stronger solar radiation in summer promoted the photochemical oxidation of isoprene»
Is this to say that the amount of isoprene oxidation is products is limited by the oxidants present, and not the presence of isoprene?
Lines 220-222: This is expected because the alkene triols are an artefact from the decomposition of higher order oligomers from IEPOX chemistry (see comment above)
Lines 223-240: There is a significant discussion about low NOx vs. High NOx, but there is no information about the NOx conditions in the area until this paragraph. Considering the isoprene concentrations will also vary dramatically with temperature, couldn’t methyl glyceric acid be coming from a different source? And if it is from a different source, then it will partition more readily into the particle phase at lower temperatures. Without information about NOx or isoprene concentrations, this is significant speculation.
Lines 241 – 252: Again, the presence of isoprene is an essential part of this argument it requires the only source of MGA to come from isoprene.
Lines 261 – 263: provide an average value from the cited literature for comparison.
Lines 263-265: How will different techniques impact these numbers?
Lines 284: The seasonal differences could be attributed to the use of human cosmetic products. Find the right citations here. Typically limonene is used in cosmetic products, while aPinene is more characteristic of biogenic emissions.
Line 289: Isn’t this more true for isoprene than monoterpenes (the dependence on meterological conditions)?
Lines 299 – 307: Show more here. If you want to make the connections between BBOA and sesquiterpenes then show it. Saying something about the temporal variation with strong biomass burning events and not showing it, is meaningless in the text. What are the concentrations during the event…? Anything else about this is important.
Lines 317-320: Provide a connection to other measurements…
Line 420: How important are these sugars?
Line 423: This is really the first mention of soil. What provides evidence of this determination? Uncertainties
Minor editing comments:
Line 21: MGA and MTL are not defined.
Line 24 & 25: PMF is not defined
Line 25: is SOC supposed to be WSOC?
Line 36: I would like references after each point.
Line 38 BTEX is not defined.
Line 38: Many studies… not researches.
Line 41: C5-Alkene triols may be considered a tracer for isoprene / IEPOX chemistry, but it should be noted that it is most likely an artefact coming from the decomposition of higher order oligomers. (DOI: 10.5194/acp-19-11253-2019)
Line 55: I am hesistant to say that SO4-2 is only an anthropogenic pollutant because there are also significant natural sources of SO2 in the atmosphere.
Line 62: add a reference here
Line 64: existing studies… have mainly been conducted …
Line 65: change to: … while SOA studies in central inland areas of China …
Line 69: Can a reference be provided to support the poor air quality.
Line 69: There, studies …
Line 81: are densely distributed.
Line 132: An obvious …
Lines 150 – 152: I don’t know what this sentence means.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Reviewer 3 Report
There is no significant novelty from this paper. Lots of papers on the same topic discuss this issue. I provide a 'major correction' recommendation before this paper can be published.
- The author did not explain how they did data processing. Is there any missing value?
- To explain any spatial differences. Use the Gini index or Moran's I. Yet, The authors do not have a test that can be used to justify spatial differences [1]–[3]. Correlation does not imply causation.
- Add analysis on the impact of PM2.5 PM10 on health, and other aspects [4]–[9]. Explain what recommendations can be produced, for example, the Penta-Helix collaboration [10], [11].
Additional references
[1] K. Winarso and H. Yasin, “Modeling of air pollutants SO2 elements using geographically weighted regression (GWR), geographically temporal weighted regression (GTWR) and mixed geographically temporalweighted regression (MGTWR),” ARPN J. Eng. Appl. Sci., vol. 11, no. 13, pp. 8080–8084, 2016.
[2] T. Ren, Z. Long, R. Zhang, and Q. Chen, “Moran’s I test of spatial panel data model - Based on bootstrap method,” Econ. Model., vol. 41, pp. 9–14, 2014, doi: 10.1016/j.econmod.2014.04.022.
[3] F. Jin and L. F. Lee, “On the bootstrap for Moran’s i test for spatial dependence,” J. Econom., vol. 184, no. 2, pp. 295–314, 2015, doi: 10.1016/j.jeconom.2014.09.005.
[4] N. A. H. Janssen, P. Fischer, M. Marra, C. Ameling, and F. R. Cassee, “Short-term effects of PM 2.5 , PM 10 and PM 2.5-10 on daily mortality in the Netherlands,” Sci. Total Environ., 2013, doi: 10.1016/j.scitotenv.2013.05.062.
[5] N. Masseran and M. A. M. Safari, “Modeling the transition behaviors of PM10 pollution index,” Environ. Monit. Assess., vol. 192, no. 7, pp. 1–15, 2020, doi: 10.1007/s10661-020-08376-1.
[6] F. Tsai, J. Y. Tu, S. C. Hsu, and W. N. Chen, “Case study of the Asian dust and pollutant event in spring 2006: Source, transport, and contribution to Taiwan,” Sci. Total Environ., vol. 478, no. 2014, pp. 163–174, 2014, doi: 10.1016/j.scitotenv.2014.01.072.
[7] R. E. Caraka, R. C. Chen, H. Yasin, Y. Lee, and B. Pardamean, “Hybrid Vector Autoregression Feedforward Neural Network with Genetic Algorithm Model for Forecasting Space-Time Pollution Data,” Indones. J. Sci. Technol., vol. 6, pp. 243–266, 2021.
[8] R. Y. Chen, K. F. Ho, G. B. Hong, and K. J. Chuang, “Houseplant, indoor air pollution, and cardiovascular effects among elderly subjects in Taipei, Taiwan,” Sci. Total Environ., vol. 705, no. 135770, pp. 1–4, 2020, doi: 10.1016/j.scitotenv.2019.135770.
[9] R. D. Brook et al., “Particulate matter air pollution and cardiovascular disease: An update to the scientific statement from the american heart association,” Circulation. 2010, doi: 10.1161/CIR.0b013e3181dbece1.
[10] R. E. Caraka, M. Noh, R. C. Chen, Y. Lee, P. U. Gio, and B. Pardamean, “Connecting Climate and Communicable Disease to Penta Helix Using Hierarchical Likelihood Structural Equation Modelling,” Symmetry (Basel)., vol. 13, no. 657, pp. 1–21, 2021.
[11] K. Sudiana, E. T. Sule, I. Soemaryani, and Y. Yunizar, “The development and validation of the Penta Helix construct,” Bus. Theory Pract., vol. 21, no. 1, pp. 136–145, 2020, doi: 10.3846/btp.2020.11231.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
The authors modified the text following my suggestions: I believe that the manuscript can be considered suitable for publication.
Reviewer 3 Report
The author did not make significant revisions and some suggestions were also not completed. There is no novelty that is significant enough to be published in this study. Many papers have been published discussing the same issue.
