Wang et al. investigate the monthly and spatial variability of ozone (O₃) formation in the Guanzhong Basin and discuss implications for mitigating O₃ and secondary aerosol pollution. The study combines in situ observations with WRF-Chem simulations and includes analyses of EKMA regimes and source contributions. Overall, the approach is sound and the analyses are carefully conducted. I recommend minor revision before publication.

My first comment is about the application of EKMA isopleth profiles to MDA8 O₃. EKMA analyses are most commonly applied to O₃ production rates, with the goal of quantifying the sensitivity of local photochemical O₃ production to local NOₓ and VOC emissions. In this study, EKMA is applied directly to MDA8 O₃, which includes not only local chemical production but also the effects of transport and advection. It would be helpful for the authors to discuss the extent to which transport and advection may influence the EKMA results, and to clarify why this approach is appropriate for MDA8 O₃ in the present context.

My second comment relates to the source attribution methodology. It is unclear whether the O₃ attributed to individual source sectors is calculated by completely removing the corresponding emission source and comparing against the base case, or by incrementally reducing emissions. Additional discussion of how chemical nonlinearity in O₃ formation may affect the source attribution would strengthen this part of the analysis.

Finally, the structure of the Results section, particularly Section 3.3, could be improved for clarity. While the descriptions of individual figures are thorough, the section is quite dense. In particular, a clearer separation of the roles of local meteorology (largely uncontrollable) versus emissions (policy-relevant factors) across different cities and months would help readers better follow the key messages.

This manuscript investigates the sub-seasonal and spatial variability of ozone and secondary aerosol formation regimes in the Guanzhong Basin from May to August 2022 based on WRF-Chem simulations and EKMA curves. The key finding is a sub-seasonal progression in O₃ sensitivity (VOC-limited --> transitional --> NO_x-limited) and policy implications for month- and city-specific controls. While the novelty of the approach is somewhat limited, the analysis of sub-seasonal regime shifts is timely and carries important policy relevance for regional air quality management. The manuscript is generally well written, and the methods are sound. I recommend publication after the following major and minor issues are addressed.

1. The policy implications of this study are largely based on simulations for a single year (2022). However, 2022 was one of the warmest years in China since 1961, characterized by intense heatwaves and drought, and emissions in 2022 may also differ from other years (e.g., 2019 or 2024) due to COVID-related impacts. Given the strong sensitivity of ozone formation to both meteorology and emissions, it is unclear whether the diagnosed regime shifts and associated policy implications are representative of other years. The authors are encouraged to discuss the robustness of their conclusions to interannual variability in meteorology and emissions. Where feasible, additional support using observations combined with indicator-based methods or box-model analyses could help verify the ozone formation regimes in 2022 and assess their consistency with other recent years.
2. The manuscript discusses the interactions between PM_2.5 and O₃, including aerosol radiative effects and heterogeneous uptake of HO₂ on O₃ production, but these interactions are not considered in the interpretation of ozone and secondary aerosol formation regimes. It would be helpful to discuss to what extent the substantial reduction in PM_2.5 mass from 2014–2024 may have contributed to changes in O₃ pollution, whether aerosol chemical and radiative effects affect the diagnosed sub-seasonal O₃ regimes, and how this might inform coordinated co-control strategies.
3. Other minor comments:

# 19: dominate should be dominant

# 216–222: These sentences are repeated.

# 277–289: This paragraph reads more like background rather than results.

# 300: Table 4 should be Table 3.

Section 3.5: The discussion of secondary aerosol formation regimes is largely descriptive. Additional explanation of the chemical or meteorological processes driving variability in SA regimes would improve the interpretation.

Figure S4: The x-axis time label is incorrectly marked as 2018.