the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Two years of Volatile Organic Compounds online in-situ measurements at SIRTA (Paris region, France) using Proton-Transfer-Reaction Mass Spectrometry
- 1Laboratoire des Sciences du Climat et de l’Environnement, Orme des Merisiers, 91190 Gif-sur-Yvette, France
- 2Institut National de l’Environnement Industriel et des Risques, Parc Technologique ALATA, 60550 Verneuil-en-Halatte, France
- anow at: Laboratoire Rhéologie et Procédés, 38610 Gières, France
- 1Laboratoire des Sciences du Climat et de l’Environnement, Orme des Merisiers, 91190 Gif-sur-Yvette, France
- 2Institut National de l’Environnement Industriel et des Risques, Parc Technologique ALATA, 60550 Verneuil-en-Halatte, France
- anow at: Laboratoire Rhéologie et Procédés, 38610 Gières, France
Abstract. Volatile Organic Compounds (VOCs) have direct influences on air quality and climate. They indeed play a key role in atmospheric chemistry, as precursors of secondary pollutants, such as ozone (O3) and secondary organic aerosols (SOA). To this respect, long-term datasets of in-situ atmospheric measurements are crucial to characterize the variability of atmospheric chemical composition, its sources and trends. The on-going establishment of the Aerosols, Cloud, and Trace gases Research InfraStructure (ACTRIS) allows implementing the collection and provision of such high-quality datasets. In this context, online and continuous measurements of O3, nitrogen oxides (NOX) and aerosols have been carried out since 2012 at the SIRTA observatory, located in the Paris region, France. Within the last decade, VOC measurements have been conducted offline at SIRTA, until the implementation of a real-time monitoring which started in January 2020, using a Proton-Transfer- Reaction Quadrupole Mass-Spectrometer (PTR-Q-MS).
The dataset acquired during the first two years of online VOC measurements provides insights on their seasonal and diurnal variabilities. The additional long-term datasets obtained from co-located measurements (NOX, aerosol physical and chemical properties, meteorological parameters) are used to better characterize the atmospheric conditions and to further interpret the obtain results. Results also include insights on VOC’s main sources and the influence of meteorological conditions and air mass origin on their levels, in the Paris region. Due to the COVID-19 pandemic, the year 2020 notably comprised a quasi-total lockdown in France in Spring, and a lighter one in Autumn. Therefore, a focus is made on the impact of these lockdowns on the VOC variability and sources. A change in the behaviour of VOC markers for anthropogenic sources was observed during the first lockdown, reflecting a change in human activities. This dataset could be further used as input for atmospheric models and can be found under https://doi.org/10.14768/f8c46735-e6c3-45e2-8f6f-26c6d67c4723 (Simon et al, 2022).
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Leïla Simon et al.
Status: final response (author comments only)
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RC1: 'Comment on essd-2022-406', Anonymous Referee #1, 04 Jan 2023
General Comments
Simon and coauthors present a two-year long PTRMS dataset of VOCs in the Paris region. Data was collected across seasons and before and during COVID-19 lockdowns and will be very helpful for models and other interpretations of urban VOC measurements. The authors do a good job of presenting what the dataset is and guide the reader through points of interest and further study in the data set while presenting some of their own conclusions. However, the quality of the dataset is questionable only because a large amount of detail on calibrations and quality control is left out. Major revisions are required to add this detail in and are outlined in the comments below. I have many other minor comments that are needed to communicate some conclusions and for the presentation of this data set.
Specific Comments
Line 137-139: I think the kinetic approach needs a little more justification for your system. It’s not clear that this will work for your full range of k. This could be a figure of k*(transmission) vs. measured sensitivity in the supplement and then you overlay a few species of estimated sensitivity over a broad k range.
Line 149: You should briefly describe the implications of having a higher humidity in the drift tube.
Line 157: It is unclear what “sensibility” is used for here.
Line 159: Explain why it is advantageous to have a cycle of <15 minutes.
Line 171-175: You should include a supplement table for the sensitivities of select species across the different standards. Also do you propagate this uncertainty into your measurements? If not, you should and state how you do it.
Line 174-175: Include the NPL standard species in Table S2.
Line 175-177: It is very unclear what this lab test was. What specifically was done to “infer the repeatability of measurements over 3 days”?
Line 177-179: It is surprising that for a quadrupole PTRMS the sensitivities changed on average by 3% from an RH of 30% to 90%. There should be a supplement figure showing sensitivity vs. RH or the ratio of water dimer to monomer for a few ions to support this claim.
Line 180-181: State what reagent ions you are calibrating to and what the normalization factor is. Also there needs to be more detail on how you applied humidity corrections. Did you gather sensitivity vs. humidity curves and then apply them? Which species did you calibrate for/which standard cylinder did you use and what did you do for a humidity correction for species with no standard calibration? The low humidity influence in general is questionable without supporting figures.
Section 2.3.4: To support the quality of this dataset this section needs a lot more detail. In addition to the above comments, you should state in the main text how many species were directly calibrated for and for what fraction of the measurement period (since you changed standards) had direct calibrations. Since you only calibrate once a month you should state how much the sensitivities are changing and include a supplement time series for select species of the sensitivity vs. time. This would also be a good place to overlay calculated sensitivities when cylinders changed.
Line 186-187: Specifically what measurements are you referring to here? Which ions/metrics are you tracking? Are these ions species you would assume are stable over two years in an air cylinder? Also you mention that you check instrument parameters but do not comment on their stability. There needs to be more detail on these tests.
Line 207: It looks like you could not perform zeros for most of the PTR-ToF measurement time due to lockdowns. Can you show that the zeros are robust over a long period of time? Were you able to calibrate during this time too?
Line 208: There needs to be more discussion on how the PTR-ToF is calibrated if you are going to use it for assigning species fractions to isobaric peaks. Is the internal dilution system the calibration system for the PTR-Q-MS or a different one? How frequent were the calibrations and what was in your calibration standard?
Line 220-221: These guidelines need to be summarized here. The quality of this data cannot be supported without explaining your detection limit and error determination.
Line 223-224: You need to explain what these internal and external quality control checks are.
Line 226: define what Ebas is and include a DOI citation for the dataset in the text.
Table 1: It is unclear what the mean error is and what quality checked by ACTRIS means.
Line 258: This sentence for isoprene is for global BVOC and you are looking at an urban region. Unless you have literature to support this, it is not necessarily expected that isoprene will be very high in this region relative to monoterpenes. You should remove this or reword it.
Line 259: Briefly explain what is meant by this. Are you saying the median monoterpene concentration is high because of a wintertime contribution?
Line 261-270: The purpose of figure 3 needs to be articulated more or figure 3 should be removed. The supporting paragraph preceding figure 3 does not explain what the figure means but rather states the concentrations of some classes in each bin. Is there some takeaway about sourcing at lower or higher concentrations that uses this figure rather than the other sourcing details later in the paper? There is a brief portion on comparison to particles but no data to compare.
Line 290: How many hours back do the back trajectories go? This would be important for estimating chemical and transport lifetimes. Also are these trajectories sourced and stay near the surface for the duration of the trajectory?
Line 308: is the NO2+ signal included in your “N-containing” species and if so what fraction does it compose of that class? Since it could be part of reagent ion chemistry I would be cautious of using m/z 46 unless you have a strong calibration and zero to prove that it is not generated in the instrument.
Line 315: How was mixed layer height measured?
Figure 6: This figure needs more detail in the caption explaining what the distributions are and what the lines are. The title (or legend?) should be consistent with the naming convention in the rest of the paper (N containing instead of n_containing).
Figure 8: A suggestion: I think a comparison of diel cycles during different seasons for select species would be very valuable and support your month average plots of Figure 7 and could be included. For example, your differences in monoterpene concentrations in the summer and autumn could be highlighted in the supplement and could add to your claims of changes in lifetime against oxidation and sourcing across the seasons.
SI Line 51-53: What fractions of m/z 69 are isoprene and furan?
Technical Corrections
Line 38: secondary organic aerosols and ozone should not be capitalized.
Line 63-64: non-methane hydrocarbons and oxygenated VOCs should not be capitalized.
Line 97-98: Is “important” here used to describe the frequency and intensity of traffic? If so, I would suggest replacing “important” with “heavy”.
Figure 1 caption: Change “South-West” to “southwest”
Line 116: Specify that the AE33 model is an aethalometer. I would just place it in your parenthesis before “Magee Scientific”.
Line 186: You should replace instances of “bottle” with “cylinder” if you are referring to a gas standard. Unless it really is a bottle, then my apologies.
Line 198: “While isoprene is an abundant biogenic VOC…”
Line 239: VOC has already been defined. You do not have to define it again here.
Line 262: In general, remove any contractions (e.g., don’t) from the text.
Line 263: use a · instead of . in your units.
Figure 3: x axis needs units
Line 290: define h
Line 298: Be consistent in naming conventions. Earlier it is “oceanic 1” but here it is “Oceanic 1”.
Line 302: “…Figure 5b.” You should use this notation for other instances.
Line 326: “… to the temperature…”
Line 361: This variable is defined as Bff earlier on. Stay consistent with names.
Figure 9: define NR-PM1
Line 445: remove “seem to have”
Figure 10: Replace “During” and “Lockdown_2” with “Spring Lockdown” and “Autumn Lockdown”, respectively. This is consistent with you caption and text. Also use subscripts with your BC variables to be consistent.
Should “CRediT” in the authorship statement be “Credit”?
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RC2: 'Comment on essd-2022-406', Anonymous Referee #2, 20 Jan 2023
This work shows a two year long PTRMS data set in SIRTA, and it is very valuable to the community, particularly modelling community, as it captures COVID 19 lock down as well as other very interesting and contrasting atmospheric chemistry periods. I think it is well written and the paper should be published, but, much more information needs to be provided on data methodology and analysis. Therefore I suggest major revisions mostly on methodological process.
2.1.2. I would remove this section or put it later as this is not your main objective and the data is only for comparison purposes.
I also do not see information on temperature, pressure and par measurements which you use for concentration calculations and show it on graphs. I need info on sensors and methodology.
2.3.1.
Line 126: Please state the period of PTRMS measurements
Line 134: from where do you get the clean air, how clean is this?
Lines 137-139: the transmission calculation needs to be better explained. How is the transmission curve? How did you calculate it? How often did you calculate it? How do you interpolate transmission curves over time? Please state k rates for each compound. Why 3 instead of 2 for unknown k rates? Can you provide a reference for this? Which standards you use for transmission, how did you take into account fragmentation of compounds. But to me the most critical thing is to see if you have calculated several transmission curves or only one (the latter would not be correct then).
2.3. I need a longer explanation on inlet set up. How it is? A picture would be very explanatory. Is the line isolated? How are you heating the line? How tall is the SIRTA station, because 6 m for 15 m above ground is confusing. What is the OD and ID of the PFA lines. How this may be affecting compounds such as dichlorobenzene for stickiness? What is a Valco valve? Explain more on what is this and which material is done, how many connections you have.. etc..
2.3.2.
You say tdrift is 60ºC in the text but it says 40ºC in table S1
What do you mean by regularly adjusted…. How is this done, how often, do you calibrate for each change? You need to state better how calibrations are done, but we will get there.
2.3.3.
Did you have equal dwell time for all compounds? It is not the same to measure acetone and sesquiterpenes for instance, and a dwell time of 10 s for compounds such as acetone, seems too long… although not necessarily wrong. But let me get this straight, you only get a value per compounds every 15 minutes? This may decrease the power of online measurements… but again not necessarily wrong. I understand calibrations were done with the exact dwell time of measurements, right?
How this lower sensitivity with 5 s has been observed? Can you explain in time when changes were done? Also can you show this decrease in sensitivity?
Also can you explain why a resolution of 15m is better than 22m?
Line 160: Can you show your scan mode measurements? Which previous studies you used?
Line 166-168: This lines seem to contradict what you say in 156-159. Please rephrase and make it consistent.
I suggest including a table with all monitored masses, compound assignment, possible fragmentation, k rates, calibration factors, LOD and uncertainty……. (basically an updated table 1)
2.3.4.
This is the most critical part to me
How did you perform blanks with the gas calibration unit. Did you have n2? Synthetic air, catalytic converter? If the latter at which temperature? Also how is your blank for compounds such as acetic acid?
Did you find a drift in your calfactors over time? Somehow it may seem one month per doing calibrations is too long. I would like to see a list of calibrations and how these change when ptr parameters are changed.
Please show cal factors (ncps/ppbv) per each compound and how they drift with time and with cal gas. This also adds to the comment on transmission. Add the NPL cal gas, and please show how did you account for the variations in calgas. This is very important for the compounds used to calculate the transmission curve. Please also state which compounds are those.
Line 175-179: please rephrase…. This is very confusing. When did you do these tests?
About humidity in calibrations, did you perform humid calibrations or not? How did you apply this effect?
How did you interpolate sensitivities? Did you interpolate humidity effect over time? Also I guess the impact of humidity is totally different depending the compounds. Please show.
2.4.1.
What is stable ambient air? Can you please rephrase this part? What do you mean check the stability?
2.4.2.
Line 205: please state inner diameter, as this is the same residence time as expressed in line 143, however with a different flow. Thus Both ptr system sample from different lines? Please restate to make it clear.
Line 206 ohh so here is the catalytic converter. Only performed once per two days? This is too long, it changes with time.. even 13hrs may be too long…..
Line 209: how are these calibrations done with the internal standard?
2.4.3.
S3 text
If you cant calibrate for formaldehyde, drop it…
The main source for acetaldehyde is not biomass burning (or not only). There is photochemistry and even biogenic. Please rephrase and show references.
m/z 46 how can you calibrate for them two with transmission only?the same goes for m57
you say corresponds when I think the word here is we have assigned this mass to this compound. Please change.
2.4.4.
Please state how did you calculate the statistical error, the systematic error, and how did you use the theory of error propagation. This information is totally missing. Also how did you calculate the LOD.
I think you cant cite ACTRIS guidelines, because they are not ready yet. On the other hand please state which are those guidelines.
Line 223 what do you mean by internal quality check by carefully verifying? How is the quality check by ACTRIS, please state. What is ebas database, please state.
3.1 I suggest using statistics (like correlations or heatmap) to group compounds, as in the city you have many different sources, and perhaps what is expected may not be the reality. And also have you considered doing a positive matrix factorization? This could really help on source identification.
Line 242: this statement about methanol and acetone is inconsistence with Figure 4, oxygenated compounds have even higher yaxis.
Line 246. I really do not understand why you pass to concentrations when comparing ppb across other literarture could be valuable. The only thing I need to know is that you indeed use real temp and atm pressure data to calculate this, per point. Correct?
Line 258: you keep saying isoprene is the most important biogenic compound, and this is not true. It may be the most copiously emitted, but there are species who do not emit isoprene. So rephrase these statements.
Why are monoterpene concentrations important during winter? And why only in winter, if it is a source from the city, (i.e. perfumery, or cleaning products industry) wouldn’t it be all over the year?
Despite im not really happy with a figure 2 because it does not give you much info as it is averaged over summer and winter and day and night, so I expect a huge variability, I do not know what is the purpose of figure 3. Please rephrase the purpose of the figure or remove.
3.2.
Are the trajectories more dominant in particular seasons? Please also state this.
3.3
Line 381:where does the 77% comes from?
4.
Explain what flags are
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EC1: 'Comment on essd-2022-406', Tobias Gerken, 31 Jan 2023
Both reviewers have made important comments about technical aspects of the dataset such as instrument calibration and processing of the data. The authors are encouraged to carefully review and respond to the reviewers' comments to ensure that the data-set is as trustworthy as possible.
Leïla Simon et al.
Data sets
PTR-MS measurements in 2020-2021 Leïla Simon, Valérie Gros https://doi.org/10.14768/f8c46735-e6c3-45e2-8f6f-26c6d67c4723
Leïla Simon et al.
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