This manuscript presents a comprehensive investigation of net ozone production rate (P(O₃)ₙₑₜ) and ozone formation sensitivity (OFS) through the integration of in situ field observations using a novel dual-channel reaction chamber system (NPOPR) and detailed box model simulations based on MCM v3.3.1. The study is of high relevance and scientific value, particularly in addressing long-standing issues of underestimation in modeled ozone production. The work also has practical implications for improving model-based OFS diagnosis and VOC pollution control strategies. However, several major issues must be addressed in the manuscript.

1. In your study, observed OVOC concentrations are used to constrain the box model. However, many OVOCs (e.g., formaldehyde, acetaldehyde, ketones) are not only emitted directly but also formed via secondary photochemical reactions from VOC precursors. Directly constraining their concentrations may mask deficiencies in the model’s chemical mechanism and artificially suppress diagnostic signals of missing secondary formation pathways.

1. Why were NO and NOx changed between the two methods to diagnose O3 sensitivity, respectively?

1. The manuscript attributes the model–measurement discrepancy (P(O₃)net_Missing) entirely to missing reactive VOCs or underrepresented chemical pathways. However, box models by design do not account for horizontal or vertical transport, which may play a significant role in shaping the measured ozone production rate—especially during periods with strong advection or mixing layer evolution, such as early morning or late afternoon. You should clarify why transport processes are neglected and whether their influence is truly negligible.

1. Although the manuscript includes substantial observation–model comparisons and compensatory mechanisms for missing reactivity, the concluding section does not clearly state what is new in this work compared to existing studies, please clearly emphasize the innovation points and boundaries of this study in the conclusion section and explain its promoting role in the research of the formation mechanism of ozone pollution.

Lines 29-31: You mentioned “the only approach to fill the gag was to add unmeasured VOCs” appears too strong. It implies that no other explanations or methods could be relevant, which may not be justified. Consider softening this to reflect that unmeasured OVOCs were the most effective compensating factor in this study, rather than the only one possible.

Line 43: “precursor” should be “precursors”.

Line 46: “equation” should be “equations”.

Lines 205-206: It is unclear what magnitude of precursor perturbation was applied, please provide a more explicit description of the model configuration used for the sensitivity analysis.

Lines 278-281: The confidence interval of 68.3% is relatively conservative, please provide additional analysis.

Line 306: The reported p-value (P < 0.5) does not indicate statistical significance, and the analysis doesn’t hold.

Lines 305-307：The statement that the mechanisms added in Case D1 “are not the main cause” of the bias may overstate the conclusion. The remaining discrepancy could still be partly due to uncertainties in those mechanisms, parameterization, site-specific variability and transportation etc. A more cautious wording would improve clarity and avoid giving a false sense of certainty.

Lines 328-329: The statement that “P(O₃)net_Missing increases significantly at higher O₃ precursor concentrations” (based on r² = 0.4-0.5) may overstate the strength of the relationship. A moderate correlation should not be equated with a strong or significant increase unless supported by statistical testing.

Lines 389-391: You use an empirical relationship between k_OH and P(O₃)net to get k_OH_Missing, and then adjust VOC concentrations to match this value. However, this method assumes a direct linear relationship without showing how real chemical reactions support this assumption. Please explain why this approach is reasonable, and whether it reflects actual atmospheric chemistry.

Lines 396-397: In Case E2, ethylene was amplified to 5.9-85.6 times the original concentration, far exceeding the limit emission levels in the conventional urban atmosphere. The lack of emission inventories or observational data support may cause the simulation results to deviate from reality. More discussion on the rationality of these magnifications is required.

Line 485: It is not necessary to add legends to every subgraph in Fig.6. Simplification can be considered.

Lines 519-521: The conclusion repeatedly emphasizes the role of OVOCs in O₃ formation and compensation, yet it assumes these are mainly anthropogenic in origin. As noted earlier, many OVOCs are also formed secondarily. It is recommended that you should distinguish between primary and secondary OVOC contributions or clearly state the limitation of their current attribution.