Please see the attached review.

Review of “Impact of particulate matter reductions on aerosol HO₂ uptake and rising surface ozone pollution in India”

The study by Gopikrishnan et al. reports the effect of HO₂ uptake on aerosols in the years 2018 (high aerosol year) and 2022 (low aerosol year) in the entire India region using the GEOS-Chem model. In 2022, during winter and post-monsoon seasons, HO₂ uptake on aerosols reduced ozone while this is reversed during the monsoon season due to lower aerosols. Based on NO_x reduction scenarios, 80 % of the increase in ozone due to HO₂ uptake on aerosols can be resolved through NO_x mitigation. Overall, the study reports important results on the impact of this new chemical regime and the following revisions are suggested for improvement.

Major comments:

The modeled to observed O₃ discrepancies seem significant in Figure S1. The authors provide several factors (lines 176 to 183) that could cause model to obs discrepancies such as uncertainties in the precursor emissions, ozone sinks, and the coarse resolution of the model. However, the modeled O₃ is significantly higher than observations in all the ground station reported values shown in Figure S1 throughout the entire year. The model overestimates the obs by up to ~75 ppb (assuming that the y-axis is in µg/m³) and in many periods ~ 50 ppb which seems way too high compared to previous literature on GEOS-Chem model studies in Asia. Since the paper mainly discusses about different chemical regimes (NO_x- vs VOC- vs aerosol-limited) it seems worthwhile to confirm that the emissions have been set up properly in the model. More details on the model setup should be added in section 2.2. (e.g., meteorology and emission inventory used).

Similar to Ivatt et al. (2022), it would be useful to add sensitivity tests by adjusting the HO₂ uptake coefficient as this number has a wide reported range (0.08-0.4) and could change the relative importance of each chemical regime.

There are details on the entire region of India that doesn’t seem highly relevant to the main point of the paper which makes the paper difficult to read. Throughout sections 3.1.1, 3.1.2, and 3.1.3, the authors describe trends in PM10 or ozone for each region/year/season and provide previous literature studies to derive causations of the modeled trend. In section 4.1 this continues describing a figure in the supporting information. This level of detail can be useful for the interested readers but not necessarily needed for the discussion. I suggest leaving only relevant information in the main text and moving the rest to the supporting information.

Minor comments:

(lines 37 – 41) The statements about NO_x-limited and VOC-limited seem reversed. In a NO_x-limited regime, radical-radical termination reactions dominate, and higher levels of VOCs won’t lead to significant O₃ increase. In a VOC-limited environment, loss through NO₂ + OH dominates and reducing VOCs will be more efficient in lowering O₃. Also, NO_x “concentrations” are not directly compared to VOC “concentrations” so I would revise “concentration of NO_x is low compared to VOCs”.

Line 49 Add definition for “MDA-8”

Line 51 How many days of ozone exceedances were reported for the 2018 base year?

Line 51 Should 100 ppb be 100 µg/m³?

Figure 1 Colors for NW and Central are too similar. Suggest changing the color of one of them. Northeast India is shown as “NE” in the figure legend but “NEI” in the caption.

Figure S1 Suggest adding units on the y-axis.

Line 300 The relationship between PM₁₀ and ozone is not always inverse. Should clarify.

Line 354 western -> Western

Figure 6 The color scale is a little difficult to see especially the blue and red gradations. Suggest adjusting.

Lines 406-410 If the peroxy-radical self-reactions dominate, it is the VOCs that suppress ozone through the self-reactions.

Line 512 “Furthermore, scaling down the NO_x emissions in the model simulations by 25 and 50 % shows a reduction of about 5-10 and 10-15 µg/m³ of surface ozone in India” Are these numbers referring to the bottom graph in Figure 8? It seems more like 1-4 µg/m³ for a 25 % and 4-8 µg/m³ for a 50 % reduction.