the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 29 Nov 2023
Sources of organic gases and aerosol particles and their roles in nighttime particle growth at a rural forested site in southwest Germany
Abstract. The composition, sources and chemical transformation of volatile organic compounds (VOCs) and organic aerosol (OA) particles were investigated during July–August 2021 at a rural forested site in southwest Germany. VOCs and semi-volatile OA particles were measured with a proton-transfer-reaction mass spectrometer coupled with a particle inlet (CHARON-PTR-MS). The CHARON-measured OA mass accounted on average for 63 ± 18 % of the total OA mass (4.2 ± 2.8 μg m-3) concurrently measured by an aerosol mass spectrometer (AMS). The total concentrations of measured VOCs ranged from 7.6 to 88.9 ppb with an average of 31.2 ± 13.4 ppb. Positive matrix factorization (PMF) was used to identify major source factors of VOCs and OA. Three factors of oxygenated VOC (OVOC), namely aromatic-OVOCs, biogenic-OVOCs and aged-OVOCs contributed on average 11 % ± 9 %, 37 % ± 29 %, 29 % ± 21 % of total VOC concentrations, respectively. The results of AMS-PMF indicated substantial contributions of oxygenated organic compounds to OA particle mass. Consistently, three secondary OA (SOA) factors determined by CHARON-PMF analysis, namely aromatic-SOA (5 % ± 7 %), daytime-biogenic SOA (17 % ± 17 %), nighttime-biogenic SOA (28 % ± 21 %), showed high contributions to total CHARON-measured OA mass. Nighttime particle growth was observed regularly at this area, which was mainly attributed by the semi-volatile organic compounds and organic nitrates formed from the oxidation of monoterpenes and sesquiterpenes. This study presents major sources, real-time transformations of VOCs and OA, and nighttime particle formation characteristic for central European forested areas.
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RC1: 'Comment on egusphere-2023-2255', Anonymous Referee #1, 14 Jan 2024
This paper presents an analysis of VOCs and organic aerosol (OA) that were present at a site in Germany, using online measurements from a variety of mass spectrometric techniques. In particular, online PTR-MS measured VOCs, and CHARON PTR-MS and AMS assessed particle composition. PMF was applied to each of these data sets. A central tenet of the paper is that the additional molecular information provided by PTR enhances the identification of sources relative to what can be learned with the AMS. The relatively weak correlation of some AMS PMF factors with CHARON PMF factors supports this claim. A strength of this paper is that PMF is applied to both gas and particle measurements using PTR-MS. Whereas PMF has been applied to AMS data extensively, there are only a few examples where it has been applied to PTR data, and fewer still (any?) that use PTR to assess both gas and particle composition. A second strength is the clear demonstration of nighttime OA growth via NO3 chemistry (up to a few nm/hour), as seen in the CHARON (and AMS) data sets. This is especially important to illustrate for a mixed use environment, where large populations (and their pollution) are located close to forests. For these reasons I strongly support publication and have only a few critical comments.
- General: Although the title is strictly correct that the measurements are at a forested location, I was surprised to read in the paper that a large city, a very large coal-fired power plant, and a refinery are only a few km away. My recommendation would be to give a new title to the paper because my first impression was that this was going to be a paper on data from a relatively remote site, dominated by only biogenic emissions. This is clearly not the case with the large, for example, aromatic input, along with the important role of NO3 chemistry.
- Line 223. Small point that PTR does detect alkenes.
- Line 299. Delete “with”. Otherwise, this paper was very clearly written with almost no typos.
- Line 300 and thereabouts. Although the authors mention this, I think more emphasis should be given to the extremely low probability that highly oxygenated species will be detected, both with the heat of the CHARON source and with PTR ionization, i.e., the spectrum is invariably “contaminated” or impacted by oxygenated fragment ions. Does this affect the PMF solutions and intepretation?
- The authors identify a primary traffic factor with a strong aromatic character and an aromatic oxygenated factor. Why refer to one as a traffic factor and not the other? In terms of source attribution, they both arise from traffic, only one is more aged than the other.
- I think it is notable that the MOOA factor is so significant, a long way from the coast. We don’t hear much about marine input in continental regions, and so I would recommend to emphasize this more, e.g. in the Abstract.
- I am surprised that the cooking factor only shows a peak at lunchtime. This is unlike behavior observed in cities with large evening signals. Why is this? In particular, is this an indication of only a very local source, e.g. from cafeterias on the site? If so, it reduces its importance as likely it will have little regional impact. This may be the reason that the AMS COA factor was not observed. Regardless, it is interesting and valuable to illustrate that it can be observed using palmitic acid as a tracer.
- Line 541 and thereabouts. It is valuable that the NO3 production rate was calculated but why not try to estimate the concentration of NO3, if the major sinks of NO3 are indeed with biogenics (which were measured)? This would be useful for others to be able to frame how likely nighttime biogenic SOA may form in their settings, which may have a different NO3 concentration.
- How do the authors handle a size-dependent enrichment factor (Figure S1) when calculating the total aerosol mass observed by CHARON?
- It appears that the authors are attributing all of C5H9+ to isoprene. How good an assumption is this?
Citation: https://doi.org/10.5194/egusphere-2023-2255-RC1 -
AC1: 'Reply on RC1', Junwei Song, 11 Mar 2024
Thanks to all reviewers for their evaluation and constructive comments on the manuscript. We tried to answer all questions and revised our manuscript and supplement accordingly. Point-to-point responses are displayed in blue text and changes in both revised manuscript and supplement are highlighted in red text.
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RC2: 'Comment on egusphere-2023-2255', Anonymous Referee #2, 19 Jan 2024
Review of Song et al., https://doi.org/10.5194/egusphere-2023-2255
The manuscript by Song et al. investigates the chemical composition and sources of VOC and OA, as well as contribution of OVOC and CHON to nighttime OA mass and particle growth events in a rural forested area in Germany in summer, by the deployment of advanced mass spectrometry techniques, very extensive source apportionments (for several datasets for both gas and particle phase) and air mass back trajectory analysis.
In this study they have found that the CHARON-measured OA mass accounted on average for 63 ± 18% of the total OA mass (4.2 ± 2.8 μg m-3) concurrently measured by an aerosol mass spectrometer (AMS). After the source apportionment done by the PMF they also have found three factors of oxygenated VOC (OVOC), namely aromatic-OVOCs, biogenic-OVOCs and aged-OVOCs contributed on average 11% ± 9%, 37% ± 29%, 29% ±21% of total VOC concentrations, respectively.
Finally, they have also observed regularly nighttime particle growth, which they attributed to the semi-volatile organic compounds and organic nitrates formed from the oxidation of biogenic VOC. This is a very interesting phenomenon.
The study is well designed, the manuscript is well written, and the data are well presented with very impressive efforts. I would therefore recommend its publication on ACP.
Below few comments for the authors.
Specific:
Line 220-222. What’s the fraction of these 98 VOC ions to the total VOC signal/concentration detected by PTR-MS? Is the total VOC shown in Figure 2d the sum of these 98 VOC ions or all detected VOC ions including excluded ones? Would be nice to show the time series of total 98 VOC ions and total VOC ions in SI.
Line 294-296. The authors attributed the low mass range of detected ions mainly to the fragmentation of larger masses, instead of other potential reasons like low oxygenated VOC there. Probably the mass spectra of FIGAERO-CIMS could help to support this attribution if the FIGAERO mass spectra show higher mass range ions.
Line 299 and 482. It seems the dominating ion for CxHyO2+ group is C3H5O2+ (methylglyoxal/acrylic acid) from Table S2 and S3. Why is it so high? It seems to be present both in aged-OVOC factor in gas phase and F5/6 factor in particle phase from CHARON-PTR-MS PMF results. This ion seems to be related to the long range transported Atlantic air masses as discussed in Line 379? Does the F5/6 factor correlate with MOOA factor or MSA (similar to the MOOA factor with MSA fragment ion (CH3SO2+) from AMS-PMF in Fig 5b)?
Line 308. The authors attributed the correlation of CxHy+ with CxHyO1-2+ mainly to the fragmentation of larger masses. Li et al. (2020) have also reported similar observations that CxHyO1-2+ species followed more the CxHy+ trends. How about the role of nighttime chemistry and decreased PBL here, considering higher monoterpenes/sesquiterpenes (Line 266 and Fig S5b) and SV-OOA1 factor (Line 404 and Fig 5c) at night as well as SV-OOA1 factor correlates with VOC terpene factor (Line 403) and nighttime-BSOA factor (Line 469)?
Line 328-330. Ethanol is a relatively long-lived compound and could have contributions from regional transport or lab solvent usage. Could the authors exclude this contribution e.g. via air mass trajectory results? If not, the reviewer may suggest to remove these two sentences and make the point directly about correlations between traffic VOC with ethanol.
Line 367-373. The biogenic OVOC factor with smaller OVOC. Does it correlate with monoterpene or sesquiterpene SOA markers detected by CHARON or FIGAERO? Probably this could be utilized to support the factor attribution.
Line 379-382. Considering the high fractions of this factor from the marine air mass clusters, have the authors tried to correlate this factor with MOOA factor or MSA (similar to the MOOA factor with MSA fragment ion (CH3SO2+) from AMS-PMF in Fig 5b)?
Line 395-397. Maybe also partially due to the PBL dilution as shown in Fig 5c?
Line 443. This factor also contains quite high C7H9+ in addition to the fatty acid peaks. Is it from toluene or fragment ion from monoterpenes/sesquiterpenes? Have the authors tried to correlate this factor with MOOA factor or MSA (similar to the MOOA factor with MSA fragment ion (CH3SO2+) from AMS-PMF in Fig 5b), or check the air mass trajectories? Fatty acids like palmitic acid can also have marine sources (Mashayekhy Rad et al., 2018). Also higher fractions of biogenic-OVOC from long range transported marine air masses was shown in Line 492.
Minor technical details:
Line 107. Use either “western” or “central”.
Line 145. Add “respectively” after “100 °C”.
Line 150. Add “Th” after “398”.
Line 287. The percentage is slightly different from the values in the abstract in Line 21. Please double check.
Line 416. Please keep consistent for “R” or “r” in the text, also in all plots if it means the same such as Fig S6.
Line 536. Typo for SV-OOA1?
Fig 9 and 10. Would be nicer to change to horizontal plot for better visualization. Also type of “ug -3” in Fig 10.
Fig S5. Please change the axis color of wind speeds or BLH to be consistent with their marker color.
References:
Li, H., Riva, M., Rantala, P., Heikkinen, L., Daellenbach, K., Krechmer, J. E., Flaud, P.-M., Worsnop, D., Kulmala, M., Villenave, E., Perraudin, E., Ehn, M., and Bianchi, F.: Terpenes and their oxidation products in the French Landes forest: insights from Vocus PTR-TOF measurements, Atmos. Chem. Phys., 20, 1941–1959, https://doi.org/10.5194/acp-20-1941-2020, 2020.
Mashayekhy Rad, F., Leck, C., Ilag, L. L., and Nilsson, U.: Investigation of ultrahigh-performance liquid chromatography/travelling-wave ion mobility/time-of-flight mass spectrometry for fast profiling of fatty acids in the high Arctic sea surface microlayer, Rapid Commun. Mass Spectrom., 32, 942–950, https://doi.org/10.1002/rcm.8109, 2018.
Citation: https://doi.org/10.5194/egusphere-2023-2255-RC2 -
AC2: 'Reply on RC2', Junwei Song, 11 Mar 2024
Thanks to all reviewers for their evaluation and constructive comments on the manuscript. We tried to answer all questions and revised our manuscript and supplement accordingly. Point-to-point responses are displayed in blue text and changes in both revised manuscript and supplement are highlighted in red text.
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AC2: 'Reply on RC2', Junwei Song, 11 Mar 2024
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RC3: 'Comment on egusphere-2023-2255', Anonymous Referee #3, 26 Jan 2024
Review report – egusphere-2023-2255
The manuscript proposed by Junwei Song et al. entitled “Sources of organic gases and aerosol particles and their roles in nighttime particle growth at a rural forested site in southwest Germany “ deals with the chemical characterisation of Volatile Organic Compounds (VOCs) and organic aerosol (OA) at the molecular level, and the relation with particle growth events at a rural forested site in southwest Germany during summer 2021. The study used a combination of state-of-the-art measurement and advanced statistical tools (i.e. PMF) to evidence sources contribution to VOCs and OA. The authors interestingly show an important contribution of different biogenic SOA factors to OA, while traditional AMS-PMF approach was not able to distinguish the different processes contributing to SOA, highlighting the need for molecular level characterization. They hypothesise that BVOC oxidation with ozone and NO3 radicals produced semi and low volatile compounds that participate to nighttime particle growth events. The paper is of excellent quality and well written, it reads quite well. However I have some points that are worth to be clarified, even if it does not question the quality of the study. The paper is of great interest for the scientific community, and consequently I recommend the publication of the paper after the authors address the following points:
Main comments
L. 184: Does the 18.4 enrichment factor used as a constant value during the entire campaign? The authors have particle size distribution measurements (SMPS), why not using these data to calculate an enrichment factor for each time point of the field campaign based on size distribution (in mass), and the enrichment factor response as a function of particle diameter? This maybe can help to increase the agreement between AMS and Charon.
L. 142-144 and text S1 It is a good approach to remove the first 290 s of each CHARON measurement, but I am wondering why such a specific timing (why not 5 min / 300 sec?). Then, the authors did not exclude the same 290 sec in gas phase mode, which is questioning. Indeed, some sticky semi volatile species that are highly concentrated in particle phase (or, at least, more concentrated in gas phase concentrated in particle than in gas phase) will take time to re equilibrate to gas phase or background concentration. This could lead to an overestimated gas phase concentration of these compounds. Is there an obvious reason for not applying such an exclusion on gas phase? Maybe the authors can show in the supplement one or two time series as examples of gas/particle (and particle gas) transition of sticky compounds to support their approach.
L. 287 290: Are AMS and Charon really comparable in this study? The authors wrote the AMS measured NR.PM2.5, while the ADL in the CHARON only extracts PM1. In addition, only masses above 60 are included in the CHARON analysis, while some compounds might significantly fragment at masses below this threshold (m/ 41 or 43 for example can be important fragments, see Leglise et al., (2019), cited in the manuscript).
L.320: Is traffic the right name for this factor or anthropogenic primary emission would more appropriate? The diurnal cycle of BTEX (figure S5) is more pronounced based on a night/day basis rather than peaking during rush hours (e.g. benzene and toluene peaked at nighttime)
L. 337: Why does C6H9+ ion is attributed to monoterpene fragment rather than isoprene, while it is explained that a correction factor has been applied to this ion accounting for isoprene fragmentation? I do not understand the logic here.
L. 374 382: I agree with the fifth VOC factor is long range transport and it should be noted that O/C ratio of this factor is higher than others, supporting this hypothesis.
3.2.1 : I think the analysis in this section could be supported by polar plot analysis (concentration as function of wind speed and direction; see for example the fig 7 in the paper of Languille et al., 2019). All factors should have a preferential wind direction (biogenic from east, anthropogenic southwest, etc.)
L390-397: As for VOCs, not sure HOA is only traffic, considering the moderate correlation to BC. And that diurnal cycle is not mainly driven by rush hours. In addition, refineries and coal fire plant might contribute to this factor. In general, it would be good to check whether these industrial sources at source west affect both VOCs and OA.
3.2.3 The reasons explaining why a 6 factors solution has been selected should be clarified (why for CHARON-PMF there is not the same plots (fig S8 and S9) as for AMS and VOCs in the supplementary?). From what I see, factors 5 and 6 seems to be anticorrelated with a nearly similar mass spectrum. So the combination of both will probably result in rather flat signal, that can potentially be attributed to some kind of background or something else (it seems like one factor that has been split in half)? Both factors are mainly attributed to C3H5O2+ and altogether they explain 42 % of the OA, which is quite high (I guess this is the highest ion at m/z 73 on fig S7, that is really high based on table S3)! Can this be due to a contamination in the set up (filter, lines material, etc.)? Another option would be to exclude this ion from the analysis, if this can be a contamination or if it biases the analysis? In that sense, a five factors solution summing the 2 last factors should be suitable too.
L. 443. I fully agree with the assignment of factor 1 CHARON OA to cooking OA, but I have 2 remarks. First the ion C16H33O2 is not the only significant one, there is another important one that can be a long chain fatty acid C16H35O3+. The second one is the C7H9+ peak, commonly attributed to toluene in gas phase, which is for sure not the case in OA. Where does this ion may come from (also seen in factor 2).
It is also interesting to note that COA contributes to 9 % of OA according to CHARON PMF, but it is not reported in AMS-PMF while it has been already identified in urban AMS-PMF studies. How can that be explained?
L. 497: High contribution of traffic VOC factor is observed for cluster C3. But Figure 1 showed that it is more long-range transport rather than local cluster. The VOC traffic factor is thus probably not only pure traffic.
L.525: Please details what are the calculations made here.
L. 541-543: The NO3 production term should include temperature dependant rate constant (kO3.NO2 = 1.4 × 10−13 exp.(−2470/T) cm3 molecule−1 s−1 (Vrekoussis et al., (2004)). A rough evaluation of the sink for NO3 due to NO should be evaluated to see if N-oxidation products are less concentrated the night NO concentration was higher.
L.557- 590: I am in line with the authors hypothesis of nighttime contribution of BVOC oxidation to SOA and growth. But I see here two limits in the approach, the first one being that most of aerosol shown in the particle size distribution that depict a growth were not detected neither by AMS nor by the CHARON due to their low diameter. Making the link between these growth events and the aerosol chemical composition should be done with high caution, as this is not a direct link. The second limit is that nights when no growth were observed, the terpenes and related oxidation products should be lower. This case is not shown by the author but could strengthen their hypothesis if verified (maybe include an additional figure in the supplement).
Minor comments:
L. 115: “The site is mainly composed of pine trees”. Please precise which pine are dominating the forest as BVOC emissions can differ from one pine species to another. It is important as the authors claim that pine trees are dominating BVOC emissions.
References :
Languille, B., Gros, V., Petit, J.-E., Honoré, C., Baudic, A., Perrussel, O., Foret, G., Michoud, V., Truong, F., Bonnaire, N., Sarda-Estève, R., Delmotte, M., Feron, A., Maisonneuve, F., Gaimoz, C., Formenti, P., Kotthaus, S., Haeffelin, M., Favez, O., 2019. Wood burning: A major source of Volatile Organic Compounds during wintertime in the Paris region. Sci. Total Environ. 135055. https://doi.org/10.1016/j.scitotenv.2019.135055
Leglise, J., Müller, M., Piel, F., Otto, T., Wisthaler, A., 2019. Bulk Organic Aerosol Analysis by Proton-Transfer-Reaction Mass Spectrometry: An Improved Methodology for the Determination of Total Organic Mass, O:C and H:C Elemental Ratios, and the Average Molecular Formula. Anal. Chem. 91, 12619–12624. https://doi.org/10.1021/acs.analchem.9b02949
Vrekoussis, M., Kanakidou, M., Mihalopoulos, N., Crutzen, P.J., Lelieveld, J., Perner, D., Berresheim, H., Baboukas, E., 2004. Role of the NO<sub>3</sub> radicals in oxidation processes in the eastern Mediterranean troposphere during the MINOS campaign. Atmospheric Chem. Phys. 4, 169–182. https://doi.org/10.5194/acp-4-169-2004Citation: https://doi.org/10.5194/egusphere-2023-2255-RC3 -
AC3: 'Reply on RC3', Junwei Song, 11 Mar 2024
Thanks to all reviewers for their evaluation and constructive comments on the manuscript. We tried to answer all questions and revised our manuscript and supplement accordingly. Point-to-point responses are displayed in blue text and changes in both revised manuscript and supplement are highlighted in red text.
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AC3: 'Reply on RC3', Junwei Song, 11 Mar 2024
Status: closed
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RC1: 'Comment on egusphere-2023-2255', Anonymous Referee #1, 14 Jan 2024
This paper presents an analysis of VOCs and organic aerosol (OA) that were present at a site in Germany, using online measurements from a variety of mass spectrometric techniques. In particular, online PTR-MS measured VOCs, and CHARON PTR-MS and AMS assessed particle composition. PMF was applied to each of these data sets. A central tenet of the paper is that the additional molecular information provided by PTR enhances the identification of sources relative to what can be learned with the AMS. The relatively weak correlation of some AMS PMF factors with CHARON PMF factors supports this claim. A strength of this paper is that PMF is applied to both gas and particle measurements using PTR-MS. Whereas PMF has been applied to AMS data extensively, there are only a few examples where it has been applied to PTR data, and fewer still (any?) that use PTR to assess both gas and particle composition. A second strength is the clear demonstration of nighttime OA growth via NO3 chemistry (up to a few nm/hour), as seen in the CHARON (and AMS) data sets. This is especially important to illustrate for a mixed use environment, where large populations (and their pollution) are located close to forests. For these reasons I strongly support publication and have only a few critical comments.
- General: Although the title is strictly correct that the measurements are at a forested location, I was surprised to read in the paper that a large city, a very large coal-fired power plant, and a refinery are only a few km away. My recommendation would be to give a new title to the paper because my first impression was that this was going to be a paper on data from a relatively remote site, dominated by only biogenic emissions. This is clearly not the case with the large, for example, aromatic input, along with the important role of NO3 chemistry.
- Line 223. Small point that PTR does detect alkenes.
- Line 299. Delete “with”. Otherwise, this paper was very clearly written with almost no typos.
- Line 300 and thereabouts. Although the authors mention this, I think more emphasis should be given to the extremely low probability that highly oxygenated species will be detected, both with the heat of the CHARON source and with PTR ionization, i.e., the spectrum is invariably “contaminated” or impacted by oxygenated fragment ions. Does this affect the PMF solutions and intepretation?
- The authors identify a primary traffic factor with a strong aromatic character and an aromatic oxygenated factor. Why refer to one as a traffic factor and not the other? In terms of source attribution, they both arise from traffic, only one is more aged than the other.
- I think it is notable that the MOOA factor is so significant, a long way from the coast. We don’t hear much about marine input in continental regions, and so I would recommend to emphasize this more, e.g. in the Abstract.
- I am surprised that the cooking factor only shows a peak at lunchtime. This is unlike behavior observed in cities with large evening signals. Why is this? In particular, is this an indication of only a very local source, e.g. from cafeterias on the site? If so, it reduces its importance as likely it will have little regional impact. This may be the reason that the AMS COA factor was not observed. Regardless, it is interesting and valuable to illustrate that it can be observed using palmitic acid as a tracer.
- Line 541 and thereabouts. It is valuable that the NO3 production rate was calculated but why not try to estimate the concentration of NO3, if the major sinks of NO3 are indeed with biogenics (which were measured)? This would be useful for others to be able to frame how likely nighttime biogenic SOA may form in their settings, which may have a different NO3 concentration.
- How do the authors handle a size-dependent enrichment factor (Figure S1) when calculating the total aerosol mass observed by CHARON?
- It appears that the authors are attributing all of C5H9+ to isoprene. How good an assumption is this?
Citation: https://doi.org/10.5194/egusphere-2023-2255-RC1 -
AC1: 'Reply on RC1', Junwei Song, 11 Mar 2024
Thanks to all reviewers for their evaluation and constructive comments on the manuscript. We tried to answer all questions and revised our manuscript and supplement accordingly. Point-to-point responses are displayed in blue text and changes in both revised manuscript and supplement are highlighted in red text.
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RC2: 'Comment on egusphere-2023-2255', Anonymous Referee #2, 19 Jan 2024
Review of Song et al., https://doi.org/10.5194/egusphere-2023-2255
The manuscript by Song et al. investigates the chemical composition and sources of VOC and OA, as well as contribution of OVOC and CHON to nighttime OA mass and particle growth events in a rural forested area in Germany in summer, by the deployment of advanced mass spectrometry techniques, very extensive source apportionments (for several datasets for both gas and particle phase) and air mass back trajectory analysis.
In this study they have found that the CHARON-measured OA mass accounted on average for 63 ± 18% of the total OA mass (4.2 ± 2.8 μg m-3) concurrently measured by an aerosol mass spectrometer (AMS). After the source apportionment done by the PMF they also have found three factors of oxygenated VOC (OVOC), namely aromatic-OVOCs, biogenic-OVOCs and aged-OVOCs contributed on average 11% ± 9%, 37% ± 29%, 29% ±21% of total VOC concentrations, respectively.
Finally, they have also observed regularly nighttime particle growth, which they attributed to the semi-volatile organic compounds and organic nitrates formed from the oxidation of biogenic VOC. This is a very interesting phenomenon.
The study is well designed, the manuscript is well written, and the data are well presented with very impressive efforts. I would therefore recommend its publication on ACP.
Below few comments for the authors.
Specific:
Line 220-222. What’s the fraction of these 98 VOC ions to the total VOC signal/concentration detected by PTR-MS? Is the total VOC shown in Figure 2d the sum of these 98 VOC ions or all detected VOC ions including excluded ones? Would be nice to show the time series of total 98 VOC ions and total VOC ions in SI.
Line 294-296. The authors attributed the low mass range of detected ions mainly to the fragmentation of larger masses, instead of other potential reasons like low oxygenated VOC there. Probably the mass spectra of FIGAERO-CIMS could help to support this attribution if the FIGAERO mass spectra show higher mass range ions.
Line 299 and 482. It seems the dominating ion for CxHyO2+ group is C3H5O2+ (methylglyoxal/acrylic acid) from Table S2 and S3. Why is it so high? It seems to be present both in aged-OVOC factor in gas phase and F5/6 factor in particle phase from CHARON-PTR-MS PMF results. This ion seems to be related to the long range transported Atlantic air masses as discussed in Line 379? Does the F5/6 factor correlate with MOOA factor or MSA (similar to the MOOA factor with MSA fragment ion (CH3SO2+) from AMS-PMF in Fig 5b)?
Line 308. The authors attributed the correlation of CxHy+ with CxHyO1-2+ mainly to the fragmentation of larger masses. Li et al. (2020) have also reported similar observations that CxHyO1-2+ species followed more the CxHy+ trends. How about the role of nighttime chemistry and decreased PBL here, considering higher monoterpenes/sesquiterpenes (Line 266 and Fig S5b) and SV-OOA1 factor (Line 404 and Fig 5c) at night as well as SV-OOA1 factor correlates with VOC terpene factor (Line 403) and nighttime-BSOA factor (Line 469)?
Line 328-330. Ethanol is a relatively long-lived compound and could have contributions from regional transport or lab solvent usage. Could the authors exclude this contribution e.g. via air mass trajectory results? If not, the reviewer may suggest to remove these two sentences and make the point directly about correlations between traffic VOC with ethanol.
Line 367-373. The biogenic OVOC factor with smaller OVOC. Does it correlate with monoterpene or sesquiterpene SOA markers detected by CHARON or FIGAERO? Probably this could be utilized to support the factor attribution.
Line 379-382. Considering the high fractions of this factor from the marine air mass clusters, have the authors tried to correlate this factor with MOOA factor or MSA (similar to the MOOA factor with MSA fragment ion (CH3SO2+) from AMS-PMF in Fig 5b)?
Line 395-397. Maybe also partially due to the PBL dilution as shown in Fig 5c?
Line 443. This factor also contains quite high C7H9+ in addition to the fatty acid peaks. Is it from toluene or fragment ion from monoterpenes/sesquiterpenes? Have the authors tried to correlate this factor with MOOA factor or MSA (similar to the MOOA factor with MSA fragment ion (CH3SO2+) from AMS-PMF in Fig 5b), or check the air mass trajectories? Fatty acids like palmitic acid can also have marine sources (Mashayekhy Rad et al., 2018). Also higher fractions of biogenic-OVOC from long range transported marine air masses was shown in Line 492.
Minor technical details:
Line 107. Use either “western” or “central”.
Line 145. Add “respectively” after “100 °C”.
Line 150. Add “Th” after “398”.
Line 287. The percentage is slightly different from the values in the abstract in Line 21. Please double check.
Line 416. Please keep consistent for “R” or “r” in the text, also in all plots if it means the same such as Fig S6.
Line 536. Typo for SV-OOA1?
Fig 9 and 10. Would be nicer to change to horizontal plot for better visualization. Also type of “ug -3” in Fig 10.
Fig S5. Please change the axis color of wind speeds or BLH to be consistent with their marker color.
References:
Li, H., Riva, M., Rantala, P., Heikkinen, L., Daellenbach, K., Krechmer, J. E., Flaud, P.-M., Worsnop, D., Kulmala, M., Villenave, E., Perraudin, E., Ehn, M., and Bianchi, F.: Terpenes and their oxidation products in the French Landes forest: insights from Vocus PTR-TOF measurements, Atmos. Chem. Phys., 20, 1941–1959, https://doi.org/10.5194/acp-20-1941-2020, 2020.
Mashayekhy Rad, F., Leck, C., Ilag, L. L., and Nilsson, U.: Investigation of ultrahigh-performance liquid chromatography/travelling-wave ion mobility/time-of-flight mass spectrometry for fast profiling of fatty acids in the high Arctic sea surface microlayer, Rapid Commun. Mass Spectrom., 32, 942–950, https://doi.org/10.1002/rcm.8109, 2018.
Citation: https://doi.org/10.5194/egusphere-2023-2255-RC2 -
AC2: 'Reply on RC2', Junwei Song, 11 Mar 2024
Thanks to all reviewers for their evaluation and constructive comments on the manuscript. We tried to answer all questions and revised our manuscript and supplement accordingly. Point-to-point responses are displayed in blue text and changes in both revised manuscript and supplement are highlighted in red text.
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AC2: 'Reply on RC2', Junwei Song, 11 Mar 2024
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RC3: 'Comment on egusphere-2023-2255', Anonymous Referee #3, 26 Jan 2024
Review report – egusphere-2023-2255
The manuscript proposed by Junwei Song et al. entitled “Sources of organic gases and aerosol particles and their roles in nighttime particle growth at a rural forested site in southwest Germany “ deals with the chemical characterisation of Volatile Organic Compounds (VOCs) and organic aerosol (OA) at the molecular level, and the relation with particle growth events at a rural forested site in southwest Germany during summer 2021. The study used a combination of state-of-the-art measurement and advanced statistical tools (i.e. PMF) to evidence sources contribution to VOCs and OA. The authors interestingly show an important contribution of different biogenic SOA factors to OA, while traditional AMS-PMF approach was not able to distinguish the different processes contributing to SOA, highlighting the need for molecular level characterization. They hypothesise that BVOC oxidation with ozone and NO3 radicals produced semi and low volatile compounds that participate to nighttime particle growth events. The paper is of excellent quality and well written, it reads quite well. However I have some points that are worth to be clarified, even if it does not question the quality of the study. The paper is of great interest for the scientific community, and consequently I recommend the publication of the paper after the authors address the following points:
Main comments
L. 184: Does the 18.4 enrichment factor used as a constant value during the entire campaign? The authors have particle size distribution measurements (SMPS), why not using these data to calculate an enrichment factor for each time point of the field campaign based on size distribution (in mass), and the enrichment factor response as a function of particle diameter? This maybe can help to increase the agreement between AMS and Charon.
L. 142-144 and text S1 It is a good approach to remove the first 290 s of each CHARON measurement, but I am wondering why such a specific timing (why not 5 min / 300 sec?). Then, the authors did not exclude the same 290 sec in gas phase mode, which is questioning. Indeed, some sticky semi volatile species that are highly concentrated in particle phase (or, at least, more concentrated in gas phase concentrated in particle than in gas phase) will take time to re equilibrate to gas phase or background concentration. This could lead to an overestimated gas phase concentration of these compounds. Is there an obvious reason for not applying such an exclusion on gas phase? Maybe the authors can show in the supplement one or two time series as examples of gas/particle (and particle gas) transition of sticky compounds to support their approach.
L. 287 290: Are AMS and Charon really comparable in this study? The authors wrote the AMS measured NR.PM2.5, while the ADL in the CHARON only extracts PM1. In addition, only masses above 60 are included in the CHARON analysis, while some compounds might significantly fragment at masses below this threshold (m/ 41 or 43 for example can be important fragments, see Leglise et al., (2019), cited in the manuscript).
L.320: Is traffic the right name for this factor or anthropogenic primary emission would more appropriate? The diurnal cycle of BTEX (figure S5) is more pronounced based on a night/day basis rather than peaking during rush hours (e.g. benzene and toluene peaked at nighttime)
L. 337: Why does C6H9+ ion is attributed to monoterpene fragment rather than isoprene, while it is explained that a correction factor has been applied to this ion accounting for isoprene fragmentation? I do not understand the logic here.
L. 374 382: I agree with the fifth VOC factor is long range transport and it should be noted that O/C ratio of this factor is higher than others, supporting this hypothesis.
3.2.1 : I think the analysis in this section could be supported by polar plot analysis (concentration as function of wind speed and direction; see for example the fig 7 in the paper of Languille et al., 2019). All factors should have a preferential wind direction (biogenic from east, anthropogenic southwest, etc.)
L390-397: As for VOCs, not sure HOA is only traffic, considering the moderate correlation to BC. And that diurnal cycle is not mainly driven by rush hours. In addition, refineries and coal fire plant might contribute to this factor. In general, it would be good to check whether these industrial sources at source west affect both VOCs and OA.
3.2.3 The reasons explaining why a 6 factors solution has been selected should be clarified (why for CHARON-PMF there is not the same plots (fig S8 and S9) as for AMS and VOCs in the supplementary?). From what I see, factors 5 and 6 seems to be anticorrelated with a nearly similar mass spectrum. So the combination of both will probably result in rather flat signal, that can potentially be attributed to some kind of background or something else (it seems like one factor that has been split in half)? Both factors are mainly attributed to C3H5O2+ and altogether they explain 42 % of the OA, which is quite high (I guess this is the highest ion at m/z 73 on fig S7, that is really high based on table S3)! Can this be due to a contamination in the set up (filter, lines material, etc.)? Another option would be to exclude this ion from the analysis, if this can be a contamination or if it biases the analysis? In that sense, a five factors solution summing the 2 last factors should be suitable too.
L. 443. I fully agree with the assignment of factor 1 CHARON OA to cooking OA, but I have 2 remarks. First the ion C16H33O2 is not the only significant one, there is another important one that can be a long chain fatty acid C16H35O3+. The second one is the C7H9+ peak, commonly attributed to toluene in gas phase, which is for sure not the case in OA. Where does this ion may come from (also seen in factor 2).
It is also interesting to note that COA contributes to 9 % of OA according to CHARON PMF, but it is not reported in AMS-PMF while it has been already identified in urban AMS-PMF studies. How can that be explained?
L. 497: High contribution of traffic VOC factor is observed for cluster C3. But Figure 1 showed that it is more long-range transport rather than local cluster. The VOC traffic factor is thus probably not only pure traffic.
L.525: Please details what are the calculations made here.
L. 541-543: The NO3 production term should include temperature dependant rate constant (kO3.NO2 = 1.4 × 10−13 exp.(−2470/T) cm3 molecule−1 s−1 (Vrekoussis et al., (2004)). A rough evaluation of the sink for NO3 due to NO should be evaluated to see if N-oxidation products are less concentrated the night NO concentration was higher.
L.557- 590: I am in line with the authors hypothesis of nighttime contribution of BVOC oxidation to SOA and growth. But I see here two limits in the approach, the first one being that most of aerosol shown in the particle size distribution that depict a growth were not detected neither by AMS nor by the CHARON due to their low diameter. Making the link between these growth events and the aerosol chemical composition should be done with high caution, as this is not a direct link. The second limit is that nights when no growth were observed, the terpenes and related oxidation products should be lower. This case is not shown by the author but could strengthen their hypothesis if verified (maybe include an additional figure in the supplement).
Minor comments:
L. 115: “The site is mainly composed of pine trees”. Please precise which pine are dominating the forest as BVOC emissions can differ from one pine species to another. It is important as the authors claim that pine trees are dominating BVOC emissions.
References :
Languille, B., Gros, V., Petit, J.-E., Honoré, C., Baudic, A., Perrussel, O., Foret, G., Michoud, V., Truong, F., Bonnaire, N., Sarda-Estève, R., Delmotte, M., Feron, A., Maisonneuve, F., Gaimoz, C., Formenti, P., Kotthaus, S., Haeffelin, M., Favez, O., 2019. Wood burning: A major source of Volatile Organic Compounds during wintertime in the Paris region. Sci. Total Environ. 135055. https://doi.org/10.1016/j.scitotenv.2019.135055
Leglise, J., Müller, M., Piel, F., Otto, T., Wisthaler, A., 2019. Bulk Organic Aerosol Analysis by Proton-Transfer-Reaction Mass Spectrometry: An Improved Methodology for the Determination of Total Organic Mass, O:C and H:C Elemental Ratios, and the Average Molecular Formula. Anal. Chem. 91, 12619–12624. https://doi.org/10.1021/acs.analchem.9b02949
Vrekoussis, M., Kanakidou, M., Mihalopoulos, N., Crutzen, P.J., Lelieveld, J., Perner, D., Berresheim, H., Baboukas, E., 2004. Role of the NO<sub>3</sub> radicals in oxidation processes in the eastern Mediterranean troposphere during the MINOS campaign. Atmospheric Chem. Phys. 4, 169–182. https://doi.org/10.5194/acp-4-169-2004Citation: https://doi.org/10.5194/egusphere-2023-2255-RC3 -
AC3: 'Reply on RC3', Junwei Song, 11 Mar 2024
Thanks to all reviewers for their evaluation and constructive comments on the manuscript. We tried to answer all questions and revised our manuscript and supplement accordingly. Point-to-point responses are displayed in blue text and changes in both revised manuscript and supplement are highlighted in red text.
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AC3: 'Reply on RC3', Junwei Song, 11 Mar 2024
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