| 18 Aug 2026
Measurement report: Long-term 2D MAX-DOAS observations of HONO vertical distributions in a rice–wheat rotation agricultural region in Shouxian, China
Abstract. Nitrous acid (HONO) photolysis is an important source of hydroxyl radicals (OH) in the atmospheric boundary layer, but long-term observations of HONO vertical distributions and their responses to agricultural activities remain limited. We conducted nearly 2 years (2022–2023) of two-dimensional multi-axis differential optical absorption spectroscopy (2D MAX-DOAS) observations in a rice–wheat rotation region in Shouxian, China. Retrieval reliability and stability were assessed through an intercomparison between two synchronized systems, spectral fit quality, degrees of freedom for signal (DOFS), and averaging-kernel analysis. Meteorological data, farming records, backward trajectories, potential source contribution function (PSCF) analysis, and Tropospheric Ultraviolet and Visible (TUV) calculations were integrated to investigate HONO variability, fertilization effects, and potential OH production. HONO was concentrated below 0.5 km, with morning and late-afternoon peaks and a noon minimum. Seasonal means followed the order winter > autumn > spring > summer. In spring and summer, near-surface HONO decreased toward midday, whereas HONO increased aloft, suggesting possible radiation-associated replenishment in elevated layers. During the 10 d following fertilization on 15 March 2023, HONO concentrations at 0.05, 0.20, and 0.50 km increased by factors of 5.3, 3.7, and 2.5, respectively, relative to the preceding 10 d. Near-site PSCF values suggested local and short-range agricultural influences. At 0.05 km, potential OH production from HONO photolysis increased after fertilization by 710 % under clear-sky conditions and by 86 % under cloudy conditions. These findings demonstrate the importance of resolving HONO vertical structure and agricultural-event responses when evaluating its photochemical relevance in agricultural regions.
Hu et al. present a two-year study of HONO in a rice–wheat agricultural region in China, using two MAX-DOAS systems. The study primarily focuses on the vertical profiles of HONO retrieved using the PRiAM profiling algorithm to investigate its temporal and vertical variability and identify potential sources. To support this analysis, the authors examine HONO alongside NO2, AOD, and meteorological parameters. They further assess the implications of the observed HONO levels for atmospheric oxidation by analyzing OH radical production rates and HONO photolysis frequencies, providing additional insights into the potential sources and temporal evolution of HONO.
As HONO is typically present at low atmospheric concentrations, its reliable retrieval using DOAS can be challenging. Therefore, studies that improve our understanding of HONO measurements are valuable. In particular, investigating HONO emissions from rice–wheat agricultural regions via remote sensing is of considerable interest, as these environments remain relatively understudied despite their growing importance for understanding regional atmospheric chemistry.
General Comments
The overall concept of this study is convincing, and the methods employed are generally appropriate for the objectives of the manuscript. However, the main limitation is the extremely low HONO concentrations observed during the measurement period at the study site, which substantially challenges the reliability of the retrieved HONO profiles. The authors state that "the adopted fitting settings adequately reproduced the major absorption features" (L250) and "the averaging-kernel patterns, DOFS values, and differences between the retrieved and a priori profiles support the reliability of the main retrieved lower-atmospheric feature" (L273). Unfortunately, I do not believe that the results presented adequately support either of these claims. In particular, the spectral fit shown in Fig. 4 raises serious concerns about the reliability of the HONO retrieval at the observed concentrations. In my experience, the fit is unusually poor compared with what I would typically expect from a published HONO retrieval study. Furthermore, degrees of freedom (DOF) values below 2 generally indicate limited vertical information content, although the implications depend on the specific retrieval setup. In this case, the low DOFS values raise substantial concerns about the extent to which the retrieved vertical profiles are constrained by the measurements rather than by the a priori assumptions. Consequently, the interpretation of the retrieved vertical structure is not sufficiently substantiated.
For these reasons, I cannot recommend final publication of the manuscript in its current form. Nevertheless, I would encourage the authors to consider submitting a substantially restructured manuscript that focuses on the HONO vertical column densities (VCDs) rather than the retrieved vertical profiles.
I believe that the underlying dataset may still be of considerable scientific value, provided that the limitations of the spectral fitting and the information content of the measurements are clearly acknowledged and the conclusions are revised accordingly.
Specific Comments to preprint version
Abstract and throughout the manuscript: Please do not abbreviate day as d
L96: Please add information on the spectrometers and CCDs
L102: Please provide a reference for PRiAM
Table 2: Why was H2O only included in one fit? Why did you use a different approach for the Intensity Offset?
L147-148: Please add cities and countries for the institutes
2.2.3 Please add a priori information. Which profile shapes, aerosol parameterizations, etc., were used?
L175: What does this mean? "The altitude range constrained by the measurements was further evaluated by comparing the retrieved and a priori profiles"
L191: Please explain your interpolation and smoothing approach.
Fig. 4: There are almost no visible spectral features of HONO! Also, the optical depth of HONO is of the same order of magnitude as the RMS, indicating that you are close to or even below the detection limit.
Fig. 5: Please add information regarding the a priori profiles (see comment above). It would be better if the profiles matched the fitting example above. If not, please explain why you chose to show these profiles.
Fig. 6: Why is there a larger deviation for higher HONO values?
Was any cloud filtering applied? Since you discuss results with and without clouds below, it would be good to add details about your cloud treatment somewhere in the manuscript.
Fig. 7: HONO shows a clear diurnal variation. What is the point of averaging over a full month? The temporal evolution would be better discussed using a time series.
Fig. 8: This looks to me as if it were just a scaling of exponential profiles, probably due to the limited information content!
Furthermore, there seems to be a small background concentration close to the surface in all seasons. This again indicates that there is too much forcing towards the a priori profile.
L319–320: "Relatively elevated" sounds as if there were a HONO distribution at higher altitudes, detached from the surface. I cannot see such a layer. If there is one, perhaps changing the colour scale would improve this figure.
L339: "Elevated HONO": Please rephrase this so that it is clear that you mean higher concentrations and not a detached concentration layer.
Here, I was also wondering how many data points went into these plots. As there are typically fewer measurements in winter due to less sunlight, and the measurements tend to be more strongly affected by clouds and aerosols,
this might impact the data quality, statistics, and discussion.
Fig. 10: The impact of humidity is not as clear to me from this figure as it is discussed in this section. If there is a relevant correlation, please add supporting information.
Section 3.3.1: Since you discuss the PBL, it would be worth adding some information on the PBL height, either in numbers or by adding another (sub)figure.
Fig. 11: Please add information about the typical prevailing wind directions for each season, if there are any.
What is the minimum number of data points per wind direction? Why are higher HONO concentrations observed at higher wind speeds in the NE direction in spring?
Fig. 13: In my view, a time series of VCDs (or near-surface concentrations) would already explain most of the findings. Since I have little confidence in the full profiles, I would recommend simplifying this plot.
Fig. 14: Why is there a period between September and October during which the NO2 background values seem to be much lower than during the other periods?
Fig. 15: Please discuss your findings using VCDs only.
Fig. 16: I do not really see the point of discussing post-to-pre-fertilization ratios. The temporal development of HONO can already be seen in time series or even in the contour plots.
Either shorten this section or highlight the benefits of this analysis and how it supports your findings.
L503: "Plotting resolution": If the resolution is insufficient, please increase it.
Section 3.4: This is the first section in which you discuss findings with and without clouds. However, there is no information about your cloud treatment.
Furthermore, since clouds strongly affect radiative transfer, all profiling results that have not been cloud-filtered have extremely high uncertainties.
Please add a section discussing the impact of clouds, including information on how clouds are treated throughout the manuscript.