The authors have certainly made a major effort to address the comments from the first round, and the resulting manuscript is certainly a lot clearer now. I have a few small comments on the response, detailed below. I have also reread the manuscript and I added a few minor comments that mostly address readability. Overall, I think this manuscript will be ready for publication once these comments are addressed.
- The clarification regarding the multiple valve switching nature of the sampler is appreciated. One additional question comes to mind, which is a) what is the minimum sampling interval the software could do (and why?) and b) is that interval (2s per L328?) really desirable/appropriate for ambient sampling?. On the latter point, each valve switch introduces the possibility of either sample contamination (from stuff absorbed on the valve ball) and sample volatilization (from turbulence introduced by the pressure fluctuations). Both of these are admittedly very hard to quantify, but I would be curious what the authors' thoughts are on this subject.
- Regarding the discussion of volatilization of the analyte, I suppose what the authors are trying to say is that at worst it will lead to biased partitioning data (although given the complications in the calibration of gases and aerosols, these are likely not distinguishable in the data from the "true" partitioning). So this could be stated explicitly. Furthermore (and I might be overinterpreting the author's intentions here, this is just my reading of it), typically (e.g. see the recent Tong et al, 2022 paper) it is a given that the results from the molecular technique are not really used for absolute quantification, but for molecular ID'ing. Advanced statistical techniques (e.g. constrained PMF in the Tong et al example) can then be used to further constrain the actual sensitivity/quantification on a molecular PMF basis, bypassing to a large extent the need for single molecule calibrations as requested by Reviewer #2. Up to the authors if they want to make this case explicitly in the paper, but realistically it seems that routine analysis of AERTRACC sampled TD-CIMS data is probably going to be handled in a similar fashion, and that hence both absolute sensitivities and, to a lesser extent, the aforementioned quantification biases can be addressed that way.
- Having said that, I am not clear how you determined that "oligomerization...was not observed in this study". A comparison of the CIMS TD profile with other volatility methods (e.g. bulk TD) would be required for this, and I do not think these data were recorded. It is probably ok to write that "the effect of oligomerization appears minor in our testing", but everything beyond that seems unsupported.
- While adding the programing language of the control software is appreciated, I believe it would still be appropriate to mention, either in the paper or in the data availability statement, if the software is publicly available. If so, it would be good to specify under which license and if not, if there are plans to make it available in the future.
- L241: I used 10 ug sm3 as a (US-centric) typical number in my review. You could use something more typical of West German urban conditions, and add a reference to support it. Regardless, your subsequent statement covers it.
- L425: DL=3xsigma Background is a conservative DL definition by some practitioners' standards, so overall it does look like all your compounds were actually roughly above DL. The large SD of the TDT, however, is notable. Is this an issue with the much higher concentration of these compounds in the background, or rather was less material collected on the TDTs compared to the filters? As noted by Reviewer, a little bit more detail on how exactly the combined error bars in Figure 4 come about would be helpful.
- Revised Figure 5: This is very nice, thank you for making it! Please consider adding a vertical grid, the plot is pretty busy and this might improve readability. I would also note that the S/B for the AMS cases might improve if you ever chose to operate the AMS at 0.5 Hz or something like that.
- While again exact quantification is not the goal, in my view, I wonder, also in the context of the PM1/PM10 comparisons, if adding a gravimetric filter analysis of both denuders and filters as a routine step prior to the thermal desorption would be a helpful addition for general QC of the data.
- The SI does not seem to have been revised; hence, I have not reviewed it.
L21: Replace "(PM1 and PM10)" with "(with PM1 and PM10 cutoffs, respectively)"
L30: is "permanent" necessary here?
L42: Consider "are generally classified into" instead of "consist"
L45: Citation needed. Nault 2021 or Southerland 2022 could be used, there are others.
L73: Citation needed for EC/OC sampler
L92: "and quick online methods do not provide in-depth chemical analysis capability". Not sure what "quick" is trying to qualify here, but in terms of "capability" the EESI or CHARON (or VIA) will provide it, I suppose the question is how cumbersome both ops and analysis are... So at a minimum please replace "quick" with "most". The authors could add a half-sentence about offline methods typically providing more detail regardless, and hence being preferred.
L106: "probing the emission of a pizza oven"
L132: Please rephrase: "up to either 10 um (PM10) or". More generally, it would probably read better if you removed this detail up here (could replace with "variable aerosol size cuts") and discussed the size cuts in detail further down. Also, both here and below, it seems that adding "nominal" in front of PM10 would be advisable. I mean, the fact that the plumbing can pass PM10 does still not mean that at say, 60 km/h in turbulent urban BL conditions PM10 sampling can really be achieved...And you write in Section 3.1 (which should probably explicitly be referenced here) that you have calculated significant plumbing losses above 3.5 um. So something like "nominal PM10, in practice PM4-PM5" would seem appropriate.
L285: I assume you “thune” when needed, since for a stationary instrument anything else would seem like overkill, so consider clarifying if you are describing your SOP or just the conditions of the text experiment.
L299: It is unclear how the concentration of individual species would be size-corrected if needed.
L375: Replace "occurrence in literature references" with "previous mention in the literature"
L376: Consider adding the single calibration compound you are using for scaling in parenthesis
L502: The standard reference for f60 use in the AMS is Cubison et al, 2011, suggest adding it here.
L578: "An in-house developed software package" would be clearer, not obvious who the "self" here is...
L582: Consider specifying the effective size range here again.
Tong, Y., Qi, L., Stefenelli, G., Wang, D. S., Canonaco, F., Baltensperger, U., Prévôt, A. S. H., and Slowik, J. G.: Quantification of primary and secondary organic aerosol sources by combined factor analysis of extractive electrospray ionisation and aerosol mass spectrometer measurements (EESI-TOF and AMS), Atmos. Meas. Tech., 15, 7265–7291, https://doi.org/10.5194/amt-15-7265-2022, 2022
B. A. Nault, D. S. Jo, B. C. McDonald, P. Campuzano-Jost, D. A. Day, W. Hu, J. C. Schroder, J. Allan, D. R. Blake, M. R. Canagaratna, H. Coe, M. M. Coggon, P. F. DeCarlo, G. S. Diskin, R. Dunmore, F. Flocke, A. Fried, J. B. Gilman, G. Gkatzelis, J. F. Hamilton, T. F. Hanisco, P. L. Hayes, D. K. Henze, A. Hodzic, J. Hopkins, M. Hu, L. G. Huey, B. T. Jobson, W. C. Kuster, A. Lewis, M. Li, J. Liao, M. O. Nawaz, I. B. Pollack, J. Peischl, B. Rappenglück, C. E. Reeves, D. Richter, J. M. Roberts, T. B. Ryerson, M. Shao, J. M. Sommers, J. Walega, C. Warneke, P. Weibring, G. M. Wolfe, D. E. Young, B. Yuan, Q. Zhang, J. A. de Gouw, J. L. Jimenez, Secondary organic aerosols from anthropogenic volatile organic compounds contribute substantially to air pollution mortality. Atmos. Chem. Phys. 21, 11201–11224 (2021).
V. A. Southerland, M. Brauer, A. Mohegh, M. S. Hammer, A. van Donkelaar, R. V. Martin, J. S. Apte, S. C. Anenberg, Global urban temporal trends in fine particulate matter (PM2·5) and attributable health burdens: estimates from global datasets. Lancet Planet Health. 6, e139–e146 (2022).
M. J. Cubison, a. M. Ortega, P. L. Hayes, D. K. Farmer, D. Day, M. J. Lechner, W. H. Brune, E. Apel, G. S. Diskin, J. a. Fisher, H. E. Fuelberg, A. Hecobian, D. J. Knapp, T. Mikoviny, D. Riemer, G. W. Sachse, W. Sessions, R. J. Weber, a. J. Weinheimer, A. Wisthaler, J. L. Jimenez, Effects of aging on organic aerosol from open biomass burning smoke in aircraft and laboratory studies. Atmos. Chem. Phys. 11, 12049–12064 (2011).