General Comments

This manuscript analyzes long-term changes in the ozone season, percentile concentrations, exposure time, and ozone generation/consumption rates in Beijing based on ground-level ozone observations from 2013 to 2023. The topic is of some practical relevance. However, the current manuscript has clear shortcomings in terms of scientific focus, depth of mechanistic analysis, and methodological rigor. Overall, the paper remains at the level of descriptive statistical analysis and lacks quantitative investigation of the drivers of ozone variability, making it difficult to support its central claim regarding the impacts of human activities and environmental management policies. In addition, several key concepts are not rigorously defined, parts of the methods are unclear or non-standard, and some interpretations of the results involve logical leaps or overstatement. Taken together, the manuscript does not currently meet the standard for publication and should make a major revision.

Specific Comments

1. The manuscript introduces the concept of the “Ozone Season”; however, this concept largely overlaps with previously defined terms such as the “warm season” or “pollution season,” and thus offers limited novelty. Although the authors attempt to define it based on MDA8 pollution days, they do not sufficiently justify the advantages or necessity of this definition compared to existing approaches. Moreover, the manuscript fails to demonstrate the added value of this concept in terms of mechanistic understanding or policy evaluation.
2. The abstract and introduction repeatedly emphasize the influence of human activities and pollution control policies. However, the main text relies solely on qualitative interpretations of temporal trends, without incorporating any supporting evidence such as emission inventories (e.g., NOx, VOCs) or model simulations. Specific issues include: no use of emission inventory data, no separation of meteorological and emission-driven contributions, no sensitivity or attribution analysis. Therefore, the key conclusions (e.g., attributing observed changes to NOx emission reductions) are not directly supported by evidence and remain largely speculative.
3. The definition and calculation of ozone exposure time are not sufficiently clear. The authors are encouraged to provide a more explicit description and move this definition to the Methods section to improve clarity and reproducibility.
4. In Section 3.5, the ozone variation rate is defined as . This method essentially represents the net change in concentration and may be influenced by transport and boundary layer processes, rather than purely reflecting chemical production or loss. The authors should clarify the applicability of this approach and provide appropriate references to support its use.
5. Several trends (e.g., changes in peak values and percentile concentrations) are reported without statistical significance testing. The authors are encouraged to include statistical metrics to strengthen the robustness of the conclusions.
6. The manuscript frequently refers to the impacts of NOx, VOCs, and climate change; however, these discussions remain largely qualitative and lack sufficient scientific rigor. Specifically, the study does not include the quantitative analysis, the model-based support or the process-level decomposition. Therefore, the mechanistic interpretation presented in the manuscript resembles an empirical summary rather than a rigorous scientific analysis, and therefore does not adequately support the conclusions drawn.

Technical Comments

1. Lines 205–207: Fig. 7 is introduced immediately after Fig. 5, which disrupts the logical flow. The order of figure presentation should be revised.
2. Figure 8 contains too many lines, making it difficult to interpret. The authors are encouraged to simplify the figure, for example by averaging over multiple years (e.g., every two years) or grouping the data.
3. There are large blank spaces on several pages, which affect the overall layout. The manuscript formatting should be improved.

This study analyzes long‑term (2013–2023) changes in ozone pollution in Beijing, focusing on the Ozone Season. The authors document an earlier onset and later end of the Ozone Season, increased low‑percentile MDA8 concentrations, delayed diurnal ozone exposure, reduced diurnal peak ozone and generation rates, and increased nighttime/trough concentrations. The topic is relevant given Beijing’s air quality policies. However, the manuscript suffers from critical methodological and interpretational flaws that severely undermine its scientific contribution. I recommend major revision before the manuscript can be considered for acceptance.

Major comments

1. The title and abstract repeatedly claim that observed changes are “due to policy and human activity”. However, the study only presents descriptive trends. No emission time series (NOx, VOCs), no meteorological contribution separated. The authors exclude days with precipitation (>0 mm) or wind speed >5 m/s for >2 hours to obtain “typical” days. This crude filtering does not remove variability from temperature, humidity, cloud cover, or boundary layer height. So discussions referred to the control policy could be bias or need to more quantitative analysis to support it.
2. The paper reports numerous trends (e.g., first pollution day advances by 1.38 days/year; MDA8 mean increases by 0.94 µg/m³/year; peak ozone decreases by 3.6 µg/m³/year; Ozone Season lengthens by 2.0 days/year). No p‑values, confidence intervals, or trend tests (e.g., Mann‑Kendall) are provided. Given the strong interannual variability (e.g., 2021 as an outlier), many of these trends may not be statistically significant.
3. The Ozone Season is defined as the period from the first to the last MDA8 > 160 µg/m³ day of the year. This definition is highly sensitive to isolated early or late pollution events caused by unusual meteorology (e.g., a single hot day in March). The authors do not test robustness.
4. The average advancement of the first pollution day (1.38 days/year) and delay of the last pollution day (0.63 days/year) are derived from only 11 years with high interannual variability. No significance testing is provided, and these averages mix real trends with random meteorological fluctuations. It is misleading to calculate the change rate X days/year.
5. The authors claim a significant upward trend in mean MDA8 (0.94 µg/m³/year). However, the data show strong interannual fluctuations (e.g., 2021 mean is nearly as low as 2013). Without a Mann‑Kendall test and sensitivity analysis (excluding 2021 or 2023), the trend is not credible. The increase in low percentiles is well known and not novel.
6. According to the authors’ figure 5, the apparent “delay” in ozone exposure start time (t1) is driven almost entirely by the unusually early t1 in 2013. For 2014–2023, t1 values are similar. Therefore, the claimed “shifting to later over the years” is not a trend but seems a single anomaly.
7. Vi = Pᵢ – Pᵢ₋₁ is a net change rate that includes horizontal/vertical transport, not just photochemical production/loss. The authors repeatedly refer to “generation rate” and “consumption rate” without acknowledging the influence of transport. This is misleading.
8. The cold season (October–March) contains very few ozone pollution days (mostly in October and March; November–February rarely have MDA8 > 160). The reported t1 distributions for the cold season are based on extremely small sample sizes, making year‑to‑year comparisons unreliable.
9. The study period includes the COVID‑19 pandemic years (2020–2022), during which anthropogenic emissions (especially NOx) dropped dramatically in Beijing. These short‑term changes can strongly affect ozone metrics and may confound the long‑term trend attributed to policy. The authors need to perform sensitivity analysis (e.g., excluding 2020–2022) nr discuss how the pandemic might have influenced their results.
10. The discussion speculates that NOx reduction weakens nighttime titration and VOC reduction lowers daytime peaks. However, no time series of ambient NO₂ or VOC concentrations (or emissions) in Beijing are presented. Without these data, the attribution remains speculative.

Minor Comments

• Several sentences are awkward or unclear. Examples: “the overall exposure time to ozone has shifted to later over the years”  to “has shifted to later in the day”. A professional language edit is recommended.
• Table 1: The effective rate of “typical” days after weather filtering ranges from 54% to 77%. The low rates (e.g., 54% in 2021) raise concerns about representativeness. Discuss potential bias.
• Figure 4: The y‑axis is time of day, but the caption is unclear. Clarify that colors represent frequency or concentration. Add units.
• Figure 5: why there are hot colors at 1:00 am.

• As temperatures rise, this exposure window shifts, with the duration extending from 14:00 to 21:00 during the months of April to September. 14:00 to 21:00 seems not match the figure.

• How the data in some of figures are not clearly explained. Many figure captions are not self-explanatory.
• Some citations are incomplete or inconsistent (e.g., “Beijing Municipal Bureau of Ecology and Environment, 2024” should be formatted as a proper reference). Check journal guidelines.
• In the conclusion, the statement “The decrease in peak concentrations benefits from coordinated emission reduction policies for regional VOCs and NOx (Wang et al., 2022)” includes a citation. Citations are generally not recommended in the conclusion section, as conclusions should summarize findings without introducing new references.