| 27 Aug 2025
Validation of TROPOMI and WRF-Chem NO2 across seasons using SWING+ and surface observations over Bucharest
Abstract. Nitrogen oxides (NOx) are key pollutants involved in ozone and particulate matter formation, with strong spatial variability near urban sources. Accurate monitoring of tropospheric nitrogen dioxide (NO2) is essential for air quality management and relies on validated chemistry transport models and multi-scale observations. This study evaluates the WRF-Chem model v4.5.1, run at 1 km resolution over Bucharest, Romania, using in situ meteorological data and surface chemical measurements, as well as airborne NO2 columns from 17 SWING+ flights conducted between 2021 and 2022. The model successfully captures key atmospheric processes and NO2 variability across all but one observation period. Our results indicate that anthropogenic NOx emissions from CAMS-REG v7.0 are underestimated, with satisfactory agreement with observations achieved when the emissions are scaled by a factor of 1.5. We also assess TROPOMI tropospheric NO2 columns v2.4.0 using SWING+ as reference, with WRF-Chem used as an intercomparison platform to account for differences in sampling and vertical sensitivity. TROPOMI biases range from +20 % at low concentrations (1015 molec. cm-2) to –13 % at higher levels (15 × 1015 molec. cm-2). Additionally, we provide seasonal diagnostics, a detailed treatment of uncertainty estimates, and contextualize our findings through a review of recent TROPOMI NO2 validation studies.
Review of the study „Validation of TROPOMI and WRF-Chem NO2 across seasons using SWING+ and surface observations over Bucharest“ by Antoine Pasternak et al.
The study focuses on validating a high-resolution chemistry-transport model and satellite retrievals of tropospheric nitrogen dioxide (NO₂) over the urban region of Bucharest. The authors run the WRF‑Chem model with 1 km resolution over the Bucharest region for 17 two-day time series in 2021 and 2022 across the different seasons, and compare its output with ground-based in situ meteorological and chemical observations as well as airborne column measurements from the SWING+ instrument (17 flights between 2021–2022). They evaluate the satellite-based TROPOMI tropospheric NO₂ column product (v2.4.0) using the airborne SWING+ data as reference, and WRF-Chem as an intercomparison. The main findings are the different biases for different concentration ranges and the seasonality of the results. Results are compared to existing TROPOMI validation studies. They show that NOx emissions from the CAMS-REF inventory need to be scaled.
General comments:
The paper presents valuable and comprehensive validation work for both TROPOMI and WRF-Chem NO₂ data over the Bucharest region. It provides detailed comparisons combining satellite, model, airborne, and surface observations over an urban area with complex emission patterns. The analysis across different seasons and atmospheric conditions adds further strength.
I think it needs discussion, if not only a scaling of the CAMS-REG, but a seasonal dependent scaling is necessary. Can you also comment on how region-dependent your scaling factor is? I think the seasonal dependency in the validation results should, in general, be more highlighted in the abstract and conclusion.
I think section 4 would benefit from being less of a review and including more explicit comparisons of this study's results with previous validation studies.
Overall, this is a well-structured, technically sound paper, and its results are relevant to the air quality satellite and modelling community. I recommend publication after minor adjustments.
Specific comments:
L23: Missing reference.
L53: Add a reference for the lifetime information.
L55: Add a reference for the expected seasonality.
L101: What is this highest resolution available?
L103: Which ERA5 variables have been used?
L110: Instead of “each chemical species” maybe better “several chemical species”. Which have you used?
L113: How do the monthly factors vary by season for the main sectors contributing to the emissions over Bucharest? Do you know how these factors are determined?
Table 2: I would suggest putting this table in the attachment. How is the NO/NO2 ratio determined for the mapping of CAMS-REG NOx into MOZART-4 NO and NO2 and how is this influencing your results?
L160: “The first data point is recorded at 01:00 LT.” Why is this different from the meteorology comparison?
Equation 1: How were the composition and ratios determined?
L216: Just to clarify, with these errors, you mean the AMF, SCDre, and DSCDs errors?
L226: You are integrating over the troposphere, but SWING+ only measured below 3km, is this correct?
L318-320: Do you mean, it is expected to see a morning, a late afternoon and an evening peak? Because you see two peaks (morning and evening), which I thought are both related to the rush hour. But if I understand your discussion correctly, you expect an late afternoon rush hour peak? What is causing the evening peak?
L331: This might be because the second day is always the flight day, so usually a clear-sky day.
L373-376: Move “It also provides statistics per season and for the entire dataset. For two dates, reported in the table, we truncate data associated with the beginning of the flight for reasons explained in Sect. 3.2.2.” to L373 after “for each separate flight.”.
Which is the other truncated day? Selecting 13:24 LT instead of what time?
L385: Be careful in the discussion, and remind the reader that some seasonal biases might compensate each other.
Table 7: Do you have an idea why the agreement is so different between the days?
Line 471: Do you have any ideas why this day you have excluded is not working well?
Line 481: …span from 2019 to 2025, cover several TROPOMI product versions and focus…
L487: and the upper bound from 10^16 to 1.5x10^16.
L558: See general comments. Please comment if seasonal scaling would be better and how region-dependent your factor might be.
L577/578 Connect this to what you have found. How much seasonality was studied in these evaluations of the TROPOMI product? Might this be something that should be investigated further?
Technical corrections:
L6/7: Split the sentence into two: …are underestimated. Satisfactory agreement with observations is achieved …
L29: like the Global Ozone …
L120: A preliminary evaluation …
Fig.3: stationary instead of staionnary for sector C
L142: …for the first 15 of the 17 SWING+ dates…
L143/144: Move the sentence “When available, …” to the end of this subsection.
Table 3: I would replace the 0 with “-“, since the meaning is not that there are 0 overpasses but just no O3 measurements at these stations
L156: including NO and NO2, and for some of them also O3.
L201: Typical and typically so close to each other doesn’t read very well.
L204: remove with
L237: DOAS was already introduced.
L245: and the offline product instead of and offline products
L252: To avoid confusions: Does “for its” refer to SWING+ or WRF-Chem?
L326: Add …modeled outputs, separated by seasons, defined as summer (June, July, August), …
L367: Thereafter, the modeled columns correlate…
L433: precision of the regression method
L476&478: For better readability you can try to add the seasons directly after each bias: -6+/-25% (summer), …
L504/505: Hard to read, check rewriting.
L537: We assess the WRF-Chem performance…