This study provides valuable insights into wintertime VOC composition, their sources, and contribution to secondary sulfur chemistry in wintertime during the 2022 ALPACA campaign in Fairbanks (Alaska). The paper is well written and clearly structured even though the choices of figures could be improved (see Major comments).

The authors show that VOC concentrations were dominated by alcohols, aromatics, and carbonyls.  Positive matrix factorization (PMF) identified 9 distinct sources, with traffic-related emissions accounting for majority of measured VOCs (approximately 56%), while residential heating sources such as wood burning and heating oil contributed a smaller, yet significant fraction. The analysis further highlights elevated formaldehyde levels observed downtown during cold stagnation periods. An interesting aspect of the study is the discussion of S(IV) species, dominated by hydroxymethanesulfonate (HMS), whose formation appears linked to ammonia and formaldehyde emissions linked to gasoline and diesel sources. Most of the results are based on correlations alone which limits the interpretations.

Regarding novelty, the manuscript would benefit from a clearer positioning relative to the work by Ketcherside et al. (2025), which discussed similar findings combining VOC and aerosol source apportionment measurements in Fairbanks. Additional discussion is needed to better emphasize the unique contribution of the present study, particularly given its stronger reliance on PTR-MS observations. The interpretation of the links between S(IV) species and their potential precursors or emission sources could be further expanded, especially to clarify the relative roles of SO₂, formaldehyde, ammonia, and traffic-related emissions in controlling HMS formation under subarctic winter conditions.

Major comments:

Section 3.3 compares the results with another VOC source apportionment study conducted in Fairbanks. For readers unfamiliar with the VOC source apportionment study by Ketcherside et al. (2025) and the PM source apportionment study by Ijaz et al. (2024), including a figure (e.g., Fig. S14 and S15 alongside a corresponding figure from Ijaz et al.) or a summary table highlighting the main differences between the PMF results (CTC versus residential site) would strengthen the discussion and improve readability.

Beyond describing the differences in VOC sources observed at two sites within the same city, it would add value to further discuss, either at the end of this section or in the conclusion, the potential implications for SOA and ozone formation, as well as the variability occurring at such a local scale. Are the observed differences significant enough to affect secondary pollutant formation?

Furthermore, only a few of the 9 scatter plots presented in Figure 3 appear directly relevant to the discussion. I would suggest replacing them with the Pearson correlation heatmap shown in Fig. S16, which provides more comprehensive information supporting the overall interpretation. Although this figure is discussed in the Supplementary Information, including correlations with external factors in the main manuscript would better support the source attribution analysis.

The wiper fluid factor accounts for 28% of the measured VOCs, exceeding the combined contributions from traffic and diesel sources. Does this interpretation seem reasonable? This factor also appears highly site-specific, as it was not observed at the Fairbanks residential site. If the number of factors were reduced, would methanol and ethanol instead be redistributed into other sources?

Minor comments:

Page 3, line 72: It would be useful to provide quantitative values after “a significant fraction of PM_2.5 in Fairbanks” to better emphasize the importance of investigating their sources and formation pathways.

Was no cooking-related factor identified?

For the VCP factor, were no siloxane fragments observed?

Both the VCP and wiper fluid factors appear to increase with warmer temperatures (Fig. S25 and Fig. S29). Do the authors have a possible explanation for this behavior?

Technical corrections: 

Page 17 – line 457: “This is large difference likely due”, please rephrase.

Page 19 – line 495-496: ”Ijaz et al. (2024) contribute about 1.6% (0.06 μg/m³) of measured OA to traffic […] we contribute”, here “attribute” may be more appropriate than “contribute.”

Recommendation: Major revisions

This manuscript presents PTR-ToF-MS measurements of VOCs in downtown Fairbanks during the ALPACA 2022 campaign, resolves nine sources with positive matrix factorization (PMF), and compares the factors to total ammonium and PILS S(IV) to suggest a link between vehicle emissions and wintertime hydroxymethanesulfonate (HMS) formation. The dataset is useful, the downtown site adds to the residential measurements of Ketcherside et al. (2025), the non-ethanol-blended-fuel and extreme-cold context is new, and the heating-oil aromatic result is interesting.

However, the main quantitative claims currently go beyond what the evidence shows, and several key analysis choices are described too briefly to be reproduced or checked. The factor solution is not justified against the neighbouring solutions; two pairs of factors seem to be over-split; the main “vehicle-related” fraction depends on putting non-combustion sources into the vehicle category; the formaldehyde treatment is not well reconciled with its known humidity dependence; and the S(IV)/HMS conclusion is based on weak correlations without ammonia measurements. None of these problems is fatal, and the data can support a strong paper, but they need major revision before the conclusions, especially those in the abstract, can be defended. My major comments follow, then specific comments by section, then technical points.

1. Justification of the PMF factor solution. No section explains why the nine-factor solution is chosen over the neighbouring solutions. The wood-heating and heating-oil factors look like a split of a single space-heating factor, and the aged-air and vertical-mixing factors are almost the same, with shared secondary signatures. The supplement only notes that Q/Qexp decreased monotonically and that the solution was chosen for its interpretability, while the bootstrap criteria (Table S6) test each factor against the same tracer used to define it, which is circular. Please add a clear, solution-by-solution explanation (ideally in a dedicated section; this is currently placed in S2 and would be better as S1), state whether the factor pairs above merge at lower factor numbers, and report the rotational and statistical uncertainty of the factor contributions, because the paper depends strongly on exact apportionment percentages.
2. Interpretation and naming of the secondary factors. “Vertical mixing” is a meteorology-based name for a factor whose chemical composition (mostly formic acid, maleic anhydride, formaldehyde, and several CxHyO3 species) is clearly secondary/aged. The authors also show that the factor depends on wind direction, which points to transport rather than only vertical exchange. The vertical-mixing and aged-air factors share strong secondary-chemistry and transport signatures; please justify keeping them separate, or merge them into secondary-chemistry factor(s) and discuss the primary emissions that feed them. The attribution would be much stronger with wind-rose plots for each factor and back-trajectory analysis showing the factor origins.
3. Reliability of source attribution. Three points. (a) The diesel toluene/benzene ratio of zero is used as a diagnostic, but a zero assigned by PMF is an artifact, not a real emission ratio; the claim that gasoline/diesel differences explain a four-order-of-magnitude carbonyl/aromatic contrast should be checked against a mass-based source comparison, because the roughly two-fold difference suggested by Table S3 cannot explain it and more likely shows that PMF has difficulty separating these sources. (b) Windshield wiper fluid is, by definition, a volatile chemical product and not a tailpipe emission (Coggon et al., 2018, on in-cabin D5 siloxane, which is still classified as a VCP even though it is vehicle-associated); the “vehicle-related ≈56%” framing therefore mixes use behaviour with combustion emissions and should be revised. The acetic-acid factor, assigned to “old vehicles” based on indirect evidence and a “may be related to vehicle emissions” argument, is also included in the vehicle total and needs a sensitivity range. (c) The analysis reports the species that dominate each factor; it would be more useful to also identify tracer masses whose signal is mostly explained by a single factor, for all factors, which would test how well PMF separated the sources.
4. Make fuller use of the PTR-ToF-MS data. Although the PMF used over 300 ions, the interpretation in the main text is based on a small set of species, and the full chemical range of the solution is never shown. Plots of the factors in O/C–H/C and OSC–log C space, and stacked views of intensity by carbon number and oxygen content, would show what contributes to each factor across the spectrum and would clearly improve the source naming. A low individual signal does not mean low information content.
5. Inter-campaign comparison should be shown, not left to the reader. Several parts of the text ask the reader to compare the manuscript’s figures with those of other papers; showing these differences quantitatively is the job of this paper. Please give factor-profile correlations against Ketcherside et al. (2025) and bring the main comparison into the main text. The current main-text figures are few and not very informative. Where time resolution or the inclusion of external species (O3, NOX) is suggested as the reason for the difference with Ketcherside et al. (lines 484–487), this can be tested directly by running PMF with those species included; explaining the difference by a factor that was deliberately left out, without testing it, is not convincing. Related to this, please state whether cooking tracers such as long-chain aldehydes (e.g. Coggon et al., 2024; Klein et al., 2019) were included, given that Ijaz et al. (2024) resolved a cooking factor in the same airshed but this study did not.
6. Formaldehyde treatment and the S(IV)/HMS conclusion. The PTR formaldehyde is about four times lower than the MIRA and COFFEE instruments and is corrected by a single constant scale factor. Because the stated cause is a humidity-dependent back-reaction, a constant factor cannot correct a bias that changes with time, and the reported r² of 0.69–0.81 together with a four-fold offset is consistent with—not evidence against—such a dependence. Please clarify whether the scaled or the unscaled formaldehyde series was used as PMF input (a constant scale keeps the percentages unchanged but biases the shape of the time series), and discuss the humidity dependence directly, because formaldehyde is the basis of the diesel-source and HMS arguments. Finally, the abstract states that vehicle-related ammonia and formaldehyde “likely play a key role” in HMS formation; this causal claim is based on weak correlations (R² ≈ 0.4) among combustion factors that vary together and without any ammonia measurement (as the authors admit). The careful wording used in the body (“this first look seems to indicate”) should also be used in the abstract and conclusions.

Introduction and site description

• Lines 91, 102–103, 114–116: The campaign location and naming are introduced in a confusing way. The residential site of the earlier ALPACA publications (≈3 km away) and the downtown site of this study should be named, dated, and clearly separated early in the text, since both are called “ALPACA.” As written, lines 102–103 read as if PMF was done for the campaign in general rather than only for the downtown site.
• Lines 105–106: The claim of being “the first study to have two sets of PTR-MS measurements under the same airshed” is a weak novelty claim and is weakened by the 2.6 km separation, the different instruments, and the different time resolution. Consider starting instead with the truly new aspects (non-ethanol fuel, extreme cold, the VOC–S(IV) link).

Methods

• Lines 33, 135–136: PTR identification of compound categories is sensitive to fragmentation. Please describe how possible fragmentation interferences were handled, especially for masses that are known to be affected, both in the compound identification and in the mixing-ratio conversion.
• Time resolution is inconsistent. The Methods describe 2-minute averaging (lines 124, 433), the Conclusions state one-minute resolution (line 543), and line 118 describes a 15-minute-per-hour duty cycle that is not explained. Please make these consistent and clarify the sampling scheme and how it feeds into the diurnal cycles and the PMF input.
• Lines 139–141: The ethanol mixing ratios are corrected by a factor of nine for fragmentation, based on post-campaign laboratory calibration. As ethanol is the second-largest species and feeds the wiper-fluid and VCP factors, please report the uncertainty of this correction.
• Line 189 and throughout: Please report uncertainties (e.g. standard deviation of the mean) on the campaign averages. In addition, the 0.05 ppb campaign-mean threshold is reasonable for the overview, but it may remove short, source-specific plumes whose campaign mean is below the cutoff but which still represent a separate source; it would be useful to check for such cases.
• Short-chain alkanes (<C8) are undetected by PTR. The manuscript itself notes that ethane, propane, and butane can represent a large fraction of carbon (7.5–37% in other campaigns). This unmeasured, vehicle-heavy pool is a caveat for every reported apportionment percentage and should be stated clearly wherever fractions are given.

Results and discussion

• Line 149–150: See Major Comment 6 on the formaldehyde–humidity tension.
• Line 290: Please clarify that values such as benzene (65.8%), toluene (82.6%), etc., are the fraction of the total measured amount of each compound that is assigned to that factor.
• Lines 345–346: Several statements about temperature dependence (e.g. the warm/cold ratios of wiper fluid, VCP, wood heating) would be supported by showing factor–temperature correlations.
• Supplement (diesel section): See Major Comment 3(a) on the toluene/benzene = 0 diagnostic and the mass-based check.
• Supplement (wiper fluid): Did the authors observe glycols associated with these emissions? Their presence or absence would help support the wiper-fluid assignment.
• Line 358: See Major Comment 3(b) on the VCP-versus-traffic categorisation of wiper fluid.

Figures

• Figure 1: A stacked bar chart would show the category concentrations directly and allow error bars, instead of using pie charts that hide the absolute values.
• Figure 3: Factor names are not consistent with the text (e.g. a panel labelled “Methanol” for the wiper-fluid factor), and the panels do not have clear axis labels and units. Please also report correlations for physically reasonable factor combinations (gasoline + diesel, wiper fluid + VCP, wood heating + heating oil) against total ammonium and consider whether diurnal-cycle comparisons are more informative than the scatter correlations, which are all weak.

• Lines 24 and 70: Define S(IV) at first use.
• Line 255: Correct to “Europe.”