Dear authors, congratulations for the work carried out and presented in this manuscript. A lot of details are given in the document and the comparative approach of the different calibration methods using the Taylor diagram is very well explained and used.

I nevertheless have few comments or suggestions listed below:

Line 10, “The correlation coefficient R”: only a question at this stage of the review, is it really the R or the R2?

Line 18: What does a.g.l. mean?

Line 20: do you have some data to illustrate the "almost constant"?

Line 57: What is the range of temperature?

“Figure 3” (Barret et al., 2024, p. 8) Figure 3: If the period without data is not usefull, I would advice the author to use some cut in the time series, or multiple graphs in order to maximise the visibility instead of leaving a third of the space empty.

Line 227, “the addition of voltages from the NO sensor in equ. 2.5.2”: What is equ.2.5.2, do you mean equation (1) at the top of the page ?

Line 237, “correlation coefficient R.”: In relation to the comment in the abstract, it is maybe a good idea to write down the formula.

Figure 5: it is not easy to see the difference in color of the dot in the legend (printed or pdf), I would advice to increse the size of the symbol.

Figure 6(b): could you give some info about the 2 line (I guess red = linear regression, blu = unity)

Figure 7: I think some words are missing, "Same caption as Figure 5 but for NO2 (MLP100 calibration function)."

Figure 9: Same comment as for Figure 7.

This study investigates surface distributions and vertical profiles of trace gases in Arctic wintertime using low-cost sensors. The MICROMEGAS instrument, equipped with EGSs, was deployed at a downtown calibration site, onboard a vehicle, and on a tethered balloon at the city’s edge. Regarding sensor calibration, results indicate that manufacturer-provided parameters were sufficient for CO, while a Multi-Layer Perceptron neural network yielded the best results for NO, NO₂, and O₃. MICROMEGAS demonstrated effectiveness in capturing surface and vertical variability in gas concentrations. Overall, the manuscript presents interesting findings. However, I have several major comments:

General comments:

1. Based on the manuscript flow, consider modifying the title to: “Surface Distributions and Vertical Profiles of Trace Gases (CO, O₃, NO, NO₂) in the Arctic Wintertime Boundary Layer Using Low-Cost Sensors During ALPACA-2022”.
2. The study emphasizes the novelty of deploying EGS in cold environments, but the impacts of temperature and relative humidity on sensor performance are not discussed. Please address this in the manuscript.
3. Line 95 mentions SO₂ measurement, but no data is presented. Either provide detailed discussion of SO₂ data or remove its mention.
4. Cross-interference: In lines 225–230, what contributions do NO and NO₂ concentrations have on O₃ sensor calibration under cold conditions? Would these impacts vary with temperature changes?
5. Lines 145–150: Discuss whether vehicle emissions would influence sensor detection. Was the detection of the sensors based on gas diffusion, or was there an air pump? If a pump was used, what was its flow rate? If based on diffusion, would sensor response vary at different vehicle speeds? For example, if the vehicle speed is too fast, the sensor response may not be fast enough to capture the rapid change of ambient concentration. Please discuss.
6. Lines 152–155: What were the vertical profiles of temperature, RH, and pressure during balloon ascents? How did rapid changes in these parameters affect sensor performance?
7. Lines 152-155: In the balloon measurements, have the authors compared EGS data with high-accuracy instruments (e.g., for CO and O₃) to validate the sensor’s vertical profiling capabilities?
8. Figure 3: Why not randomly separate the training and testing datasets? This approach might be more robust and objective.
9. Lines 202–205: Add a brief description of the HGBT and RF parameterization methods used.
10. Line 259: Include a brief explanation of how to interpret the Taylor diagram.
11. Lines 259–271: Until the end of the manuscript, I realized that Figure 4b presents the information of the raw data, and the raw data for CO was used in this study without any correction. This information should be clearly stated here. 
12. Lines 292–296: Could the relatively worse performance of HGBT and RF models result from the data selection process? Consider discussing whether a 10-fold cross-validation or random data selection could improve predictions.
13. Line 296: What is meant by the term “raw calibration method”? Does it refer to using raw data directly or applying a linear correction to the raw data?
14. Line 305: The manuscript lacks information on Ox calibration. Please include this.
15. Line 327: Define what is meant by “systematic bias.”
16. Figure 15: Was the time resolution of sensor data consistent with that of the reference instrument? If not, could observed spikes in sensor data be due to its higher time resolution?
17. Section 4: Discuss the limitations of this study and please provide suggestions for future research on low-cost sensors in cold environments.

Technical comments:

1. Line 57: Extremely, not extreme.
2. Line 142: Correct "ouside" to "outside."
3. Line 208: Figure 7 is referenced before Figure 6. Correct the order.
4. Line 227: Replace "Equ." with "Eqn. 2.5.2."
5. Figure 15: Trace gas, not trace gaz, in the caption. For better visualization, consider using a different symbol instead of dark circles.