the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 05 Aug 2026
Seasonal Evolution of Thermal, Dynamic, and Material Boundary Layers and their impacts on air pollution in the Megacity Beijing
Abstract. Urban planetary boundary layer height (PBLH) regulates the exchange of heat, momentum, moisture, aerosols, and pollutants between the surface and free troposphere, yet a single PBLH estimate cannot represent the multiple physical interfaces controlling turbulent mixing in complex megacities. This study investigates the seasonal co-evolution of thermal, dynamic, and material PBLHs in Beijing using the parcel, Richardson number (Ri), and gradient methods. Dynamic PBLH dominated during winter, with a mean of 828 m exceeding thermal (666 m) and material (625 m) PBLHs. In spring, material (918 m) and dynamic (871) PBLHs also exceeded the thermal PBLH (657 m). Summer exhibited the deepest daytime PBLH growth, with median peak thermal, dynamic and material PBLHs of 1397 m, 1402 m, and 1464 m, respectively. Autumn showed a transition regime, with mean thermal (685 m), dynamic (591 m) and material (709 m) PBLHs. In winter, pollutant concentrations were negatively correlated with dynamic PBLH (ρ= -0.47 to -0.74). Weak thermal buoyancy suppressed vertical mixing and restricted the upward transport of pollutants into the free atmosphere, favouring local pollution accumulation except during strong cold-air advection. In summer and autumn, thermal and material PBLHs exceeded the dynamic PBLH. Strong thermal buoyancy lifted particulate matter and other primary pollutants above the dynamic PBL top, facilitating long range dispersion. In contrast, ozone exhibited positive correlations with all PBLH metrics, consistent with active photochemical production and vigorous convective mixing. Collectively, these results demonstrate that adopting multiple definitions of BLH provides a comprehensive understanding of the processes controlling atmospheric pollution.
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Status: open (until 09 Nov 2026)
- RC1: 'Comment on egusphere-2026-4121', Anonymous Referee #1, 12 Oct 2026 reply
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- 1
Review of Jinyuan Xin et al., 2026: “Seasonal Evolution of Thermal, Dynamic, and Material Boundary Layers and their impacts on air pollution in the Megacity Beijing”
The authors present an interesting investigation into the variability of Beijing’s planetary boundary layer and air pollution through a range of metrics. Their analysis is rigorous and thorough. They find the expected relationships between air pollutants and boundary layer behaviour without delving deeply into new mechanisms, methods or scientific insights. I therefore conclude that this paper is marginally suitable for ACP, but some revisions should be undertaken first.
The two major things to be addressed are:
In addition, below are a range of minor revisions to be considered:
Line 44: should be “a diverse range of ABL…”
Line 93: for those not directly in the field, can you please outline in more detail (or provide a reference) why " Data with a carrier-to-noise ratio below -26 dBZ were discarded”.
Lines 99-100: For this statement, “both microwave radiometer and wind lidar exhibit a strong correlation with the measurement taken from the 325-m meteorological tower” Please comment briefly on exactly what measurement have been compared here. Are there radiometer or lidar measurements on the tower? Or is the validation through comparison of different measurement types indicating good agreement in BL structure?
Line 146-147: Instead of saying “reflected back by the cloud’s lower boundary” I think you want to clarify that the backscatter can come from cloud or aerosol.
Lines 148-149: “Assuming that the mixed layer has a relatively uniform aerosol concentration that is significantly higher than that of the air above” – how does the BLH detection algorithm hold up when this assumption isn’t true (which there are a few examples of in Figures 2-4)
Lines 156-157: The font size goes small here for some reason
Line 159: Hourly average pollutant concentration data, or values measured on the hour?
Figure 1: Can you please put on the map the location and names of the air pollution stations you obtained data from?
Line 167: You say “representative periods from four seasons were selected”. Can you please explain why you chose the periods you did and how you know they are seasonally representative?
Figures 2-4 (and subsequent figures): Can you clarify whether periods of cloud have been filtered out, or whether periods of exceptionally high backscatter (e.g. 00:00, 18/12/11) represent cloud? Also, in your captions you should identify the season, and not have identical captions for each one.
Figure 6: Are the values presented means for the whole months noted, or the mean diurnal cycle in the case study periods in each month? You should clarify in the caption. Also, importantly, I think you should show the standard deviation of the diurnal cycle as error bars on these plots to help the reader interpret whether variability between methods and months are significant. The large variability noted in your mean values in the text suggests the difference is probably not really significant. This should cause you to be cautious with statements like in Line 311 where you say “The three PBLHs showed distinct seasonality” – are they really distinct within uncertainty?
Figure 7: The uncertainty analysis here is better and allows the significance to be assessed well. Good idea still to include the uncertainty bars in the diurnal plot though so we can see how the variability sits hour to hour.
Line 352: “reflecting enhanced warm-season photochemical production” – yes, and also higher NO titration of O3 in winter.
Lines 360-361: “SO2 peak during daytime in April, July, and September, indicating potential influences from regional transport or the downward dispersion of increased industrial emissions” – can you help those unfamiliar with the region understand why peaking in daytime in April, July and September indicates the conclusions you list about the SO2 source? Same with the following sentence. Why does low warm season SO2 specifically indicate changes in coal combustion?
Line 365: you refer to “dominance of photochemical O3” – it is not clear what you mean by dominance. It’s not the most abundant pollution all the time.
Line 376-377: The “This implies that…” sentence needs revising
Line 390-391: “The positive correlations between ozone and PBLH in this study likely reflect the combined effects of stronger convective mixing and enhanced in situ ozone formation under deeper boundary-layer conditions” – I think you need some more analysis here. It is well known that NO and O3 are anticorrelated because NO titrates O3. Therefore as NOx goes up in a reducing boundary layer, O3 goes down. So what you’re seeing in the PBLH-O3 relationship is likely driven by PBLH-NOx relationships, but you should investigate a little deeper whether that is expected in Beijing (e.g. through whether the O3 production is expected to be NOx- or VOC-driven there).
Line 399: define A2 (and other similar names, are they the time periods of interest?)