Nursanto et al. utilize three months of observations collected in Cabauw, Netherlands, to investigate what aerosols control new particle formation (NPF). Using an Aerosol Chemical Speciation Monitor (ACSM) and scanning mobility particle sizer (SMPS) with positive matrix factorization (PMF), the authors found four distinct factors associated with the start and growth of new particles and two factors associated with background, large particles. The factors found by the authors were generally similar across the three different months. They generally found sulfate was associated with the beginning of an NPF event and nitrate was observed during the condensational growth. Further, organics were both associated with NPF and condensation. The authors also associate the events with different relative chemical composition of aerosol (organic rich, nitrate rich, sulfate rich, ammonium rich) and back trajectories for where the air masses originated.

Though this article is potentially of interest to the ACP community, and the authors have done a good job in setting up the scientific quesiton and premise, there are many technical aspects and analysis that either needs further discussion and/or evaluation, which are detailed below, prior to publication to ACP.

Major

1) In general, much more details are needed in the measurements. There are many key details that are necessary in evaluating the science that have not been addressed. These include:

1.1) What size particle lens was used? It is not clear if a PM1 or PM2.5 particle lens was used, which is both important in the flow rates for the cyclone and the aerosol diameter cut-offs (further discussed below).

1.2) What was the flow rate throughout the system? Was there an external pull for the ACSM to reduce residence times? What type of tubing was used? Was the inlet heated or not? Any concern about temperature gradients between inlet outside and instrument inside?

1.3) Were the SMPS and ACSM on same or different inlets? If different, how far apart were the two inlets?

1.4) Was a drier used for either or both instruments?

1.5) More information needs to be included about the SMPS, as it is one of the key instruments. This includes type of DMA and CPC, resolution, type of column, software for analysis, type of neutralizer source, etc.

1.6) What are the limits of detection for everything? E.g., were any of the measurements at or below LOD for when trying to investigate NPF?

2) Some further discussion or details also needs to be included for PMF. This includes:

2.1) Why were the total mass concentration for the inorganics instead of their ions used?

2.2) Why was potassium used? It is generally related with surface ionization of the vaporizer. Evidence that the potassium was from aerosols and not surface ionization should be included in the SI.

2.3) Why were the 18 bins selected for the SMPS? Was this due to the software, or did this provide the optimal data for analysis? Would fewer bins be better or worse? Further, some more discussion about the weighting of the SMPS data and errors in the SI would be beneficial.

3) Looking at the PMF organic profiles for all seasons, many of the profiles look very similar and/or like they are split solutions. E.g., in Fig. 3, the mass spectra for organics for solution F6, F4, F2, and F1 look nearly identical, and there are mass spectra for organics that look nearly identical in the SI. Should these solutions be combined? Also, the profiles are generally surprising looking as they do not look like profiles expected for ambient aerosol. Since there can be a potential bias in the CO2+ signal from CV, was m/z 44 (and associated ions) downweighted the similar amount as is typical for SV or downweighted more? Inclusion of the time series of each profile and SMPS data associated with that factor in the SI would also be extremely beneficial here in further evaluating and understanding if each solution is unique and real. 

4) One very large concern is what aerosol diameters are being observed with the ACSM. If it is using a PM1 lens, any aerosol below 40 nm is not observed, and aerosol between 40 and 70 to 100 nm is only fractionally observed (e.g., approximate linear growth in the amount of aerosol observed with diameter to 70 - 100 nm). However, if it is PM2.5 lens, the ACSM will only observe 100% of aerosol for diameter > 110 nm. Thus, any aerosol observed for most of the solutions/modes for NPF are very surprising. Since many of the figures show potential contribution of "large" particles (>100 nm diameter) showing small contribution to the factor, how much volume is the small, large particle, contribution adding? E.g., is the volume large enough that that is what is leading to the aerosol being observed by the ACSM?

5) Looking at the progession of the NPF with the ACSM data is very surprising and needs further discussions. Some specific questions that need to be addressed are listed below:

5.1) How does the composition shift entirely from sulfate to organics or sulfate/organics to nitrate between F6 to F5? What happened to the sulfate? Looking at the solutions, it appears that F6 --> F4 and may be F5 --> F3; however, as it is presented and discussed, it appears the NPF event goes from F6 --> F5 --> F4 --> F3.

5.2) Similarly, what happened to f(CO2)? Highly oxyenated material may be necessary for the initiation of NPF; however, it should not completely disappear as compounds with higher volatility, lower f(CO2) condenses onto the aeorosol.

6) Looking at the time series of SMPS number concentration vs time (Fig 5 & SI), it is not clear what has lead to some events being specifically selected as NPF and other times where there is what appears to be rapid particle formation not being selected as an NPF. For example, in Fig. 5, why was the third event selected as it appears it only went to 30-40 nms and stoppped but later times (after 5/30) not selected?

7) Fig 6 and associated figures in SI, it is surprising how the normalized mass spans what appears to be a larger time frame than the NPF event. E.g., Fig. S4 shows that the events are ~ 4 - 6 hours; however, looking at Fig. 6 (and associated figures), it seems that it takes a full 12 hrs to go from F6 --> F3. Clairification in how this figure/results are related to NPF needs to be further detailed.

8) Section S2. Further clarification needs to be added in this section to discuss the thermodynamics vs kinetics that may be controlling NPF and the aerosol composition in general. It is recommended that Weber et al. (2016) and Pye et al. (2020) are reviewed and incoporated in the discussions here, for the following reasons. 

8.1) Are the values 0.99 and 0.98 statistically different, considering the overall uncertainties with the ACSM?

8.2) It is nearly impossible to say anything about aerosol acidity in the boundary layer just with charge balance calculated with the ACSM/AMS. E.g., it was not until the ammonium balance dropped below 0.65 could aerosol acidity be directly related to the charge balance measured on the AMS (ACSM) (Schueneman et al., 2021).

8.3) Though NO3 and SO4 would be with other cations, generally, both the cations and anions would be not easily observable due to the higher boiling point and the aerosol being more refractory. It would be recommended to say that both the cations and anions from these salts would be slowly detected and not "not detected." (Line 939 SI).

8.4) Line 945 - 950. This needs to be rephrased as both the association of sulfate with a base is both kinetically and thermodynamically controlled (see Weber et al., 2016 and Pye et al., 2020). Sulfuric acid will first react with a base (either ammonia or an amine) very quickly; then, it will more slowly form the ammonium sulfate or double-amine sulfate. E.g., > 100 ug m^-3 NH3 was estimated to be needed to make pure ammonium sulfate. Instead, it will be a combination of ammonium sulfate and bisulfate in the aerosol phase. Further, a combination of factors (temperature, relative humidity, ammonia, and ammonium) will play in the role to start having ammonium nitrate in the aerosol phase, which is best explained with a thermodynamic model. Even at "low" pH (~2), ammonium nitrate will be present even though the sulfate is not pure ammonium sulfate. Thus, it is not as straightforward that all the ammonia reacts with sulfate to form ammonium sulfate and the remainder then reacts with nitrate.

8.5) The terms "nitrate excess" and "sulfate-rich" also are hard to follow for the reasons discussed in 8.4.

9) What does an "orgnaic-rich" period mean, in that it was related to ammonium? Why was ammonium used to normalize and determine organic rich vs poor? Clarification in what this chemically means should be addressed.

Minor

1) Line 333, believe September should be fall instead of summer?

2) line 364, what is quiet NPF?

3) Sect 3.3 Title should be F6, F5, F4, F3 and not F7, F6, F5, F4

4) Line 225. A discussion about what happened to the sulfate and why it is suddenly poor in Sept should be included

References:

Pye et al. The Acidity of Atmospheric Particles and Clouds. Atmos. Chem. Phys. 20, 4809 - 4888. doi:10.5194/acp-20-4809-2020, 2020.

Schueneman et al. Aerosol pH Indicator and Organosulfate Detectability from Aerosol Mass Spectrometry Measurements. Atmos. Meas. Tech. 4, 2237 - 2260. doi:10.5194/amt-14-2237-2021, 2021.

Weber et al. High Aerosol Acidity Despite Declining Atmospheric Sulfate Concentrations Over the Past 15 Years. Nature Geosci. 9, 282-285. doi:10.1038/ngeo2665

Nursanto et al. provided insights in new particle formation of different chemical species by combining organic aerosol mass spectrum, inorganic mass concentration from ACSM, and 18 particle size bins from SMPS. It suggests that the small-size particles are related to the transport of SOx, NH3, and some organic precursors. Moreover, nitrate plays an important role while particle size grows. However, there are still some fundamental questions that need to be addressed to draw such conclusions.

General comments:

1. PM_2.5 inlet of ACSM is subject to a significant loss for particles that have a small size, do you believe SMPS and ACSM are measuring the same thing? Do you believe these small particles in F6 were actually measured by ACSM?
2. A more detailed description of how to balance the estimated error from different instruments is required (in this case, since mass conc. of inorganic were used, it’s like combining three different datasets).
3. A more detailed description of the number of factor decisions is required.
4. Why only up to m/z 100 were used? ToF-ACSM has data up to m/z 200 that potentially can increase the capability of better PMF factor separations.
5. The PMF solutions, especially the OA factors are not convincing, even with CV-ACSM, literature has shown successful PMF analyses with reasonable solutions in both China and Atalanta. The PMF factors are not well-separated and seems like the authors define the factors heavily based on the SMPS data. Authors need to show that factors are not mixed from time series, diurnal, and mass spectrums. Currently, the mass spectrum from OA suggests they are mixed. In addition, bootstrap should be conducted to demonstrate that current results are robust and stable.
6. How do PMF results look like when you only use the OA mass spectrum? Does it also provide a 6-factor solution that supports your current conclusions (e.g., K related to biomass burning)

Specific comments:

Line 101: Would be great if you can provide the average temperature of May when you say it was characterized as moderate spring temperatures in the text. Same for the highest temperature for June and the warm temperature for Sep.

Line 124: These citations are rather for collection efficiency correction based on SV. I feel like it’s better if you can explain the CE in your word instead of citing this literature since you are not using their methods to apply CE correction.

Line 129: Please cite James Allen’s paper for the fragmentation table you used.

Line 133: How confident are you about your potassium signals from ToF-ACSM, I’ve barely seen any of the other studies report it. Did you also conduct RIE calibration for it?

Line 146: mass-to-charge ratio?

Line 153: It’s great that the authors considered balancing the variables from the different instruments, but the detailed description and how well the weighting should be discussed in this study. Because it is the key to ensuring the quality of the results.

Line 161: As the most subjective part of the PMF, it would need more detailed descriptions and illustrations to justify your selection of the number of factors. Also, did you bootstrap your final solution to make sure your results are stable? This step is also important to make sure the solution is representative and robust.

Line 198-199: This statement of lower f44 and higher f43 is often referred to as HOA is simply false. There are lots of primary sources that could have this feature. Please rephrase.

Line 200-203: There are quite a few studies of PMF using CV ACSM already, therefore, I think the authors cannot simply say that your results are not comparable with other works e.g., Joo et al., 2021 and Zheng et al., 2020. I’m still convinced that the CV ACSM should provide sufficient information to resolve reasonable PMF factors based on literature and some ongoing studies.

Line 258-259: I have a hard time believing that OA correlates with K signal leads to biomass burning origin, not to mention how trustworthy the K signal is from the ACSM. If the K signal is so pronounced and you believe it is from biomass burning, you shall be able to resolve a biomass burning OA factor in Sep. I wonder if that’s the case, otherwise, it is difficult to believe your statement.

Figure 3, S1 and S2:

The diurnal plots for each factor shall be displayed side by side with the factor profiles for all three months to have a better comparison among factors to conclude F1 seems to be aged.

Figure 1:

Perhaps it’s better to combine Fig 1 and 2 to have a better visualization of where the wind comes from.

References

Joo, T., Chen, Y., Xu, W., Croteau, P., Canagaratna, M. R., Gao, D., Guo, H., Saavedra, G., Kim, S. S., Sun, Y., Weber, R., Jayne, J., & Ng, N. L. (2021). Evaluation of a New Aerosol Chemical Speciation Monitor (ACSM) System at an Urban Site in Atlanta, GA: The Use of Capture Vaporizer and PM 2.5 Inlet. ACS Earth and Space Chemistry, 5(10), 2565–2576. https://doi.org/10.1021/acsearthspacechem.1c00173

Zheng, Y., Cheng, X., Liao, K., Li, Y., Li, Y. J., Huang, R.-J., Hu, W., Liu, Y., Zhu, T., Chen, S., Zeng, L., Worsnop, D. R., & Chen, Q. (2020). Characterization of anthropogenic organic aerosols by TOF-ACSM with the new capture vaporizer. Atmospheric Measurement Techniques, 13(5), 2457–2472. https://doi.org/10.5194/amt-13-2457-2020