| 24 Jul 2026
Assessing the Representativeness of Surface Atmospheric Ammonia Observations for Satellite Data Interpretation
Abstract. Atmospheric ammonia (NH₃) is a major precursor of secondary fine particulate matter and is predominantly emitted by agricultural activities. However, the representativeness and complementarity of satellite and surface NH₃ observations remain insufficiently characterized. This study evaluates the consistency between IASI satellite observations and surface NH₃ measurements across the three largest NH₃ emitting regions of France (Brittany, Grand Est, and Auvergne–Rhône-Alpes), representing 44 % of national emissions. A network of 24 monitoring sites, equipped with Radiello passive samplers and Picarro analyzers, operates from June 2024 to June 2025. Surface measurements show higher and more variable NH₃ concentrations at agricultural sites than at background sites, whereas traffic-influenced urban locations exhibit intermediate levels. IASI NH₃ columns reproduce surface regional patterns and seasonal variability, with spring and summer maxima consistent with agricultural emissions. Satellite–surface agreement is assessed across multiple spatial and temporal scales. Strong correlations (R ≥ 0.7) are obtained at biweekly to seasonal timescales when averaging IASI observations within 20–40 km of the monitoring sites, demonstrating its capability to characterize regional NH₃ variability. In contrast, correlations remain weaker at daily and sub-daily timescales, highlighting the limited ability of polar-orbiting satellites to capture localized variability. These findings demonstrate that satellite observations are well suited for long-term NH₃ monitoring and trend analysis, whereas dense surface networks remain essential for resolving fine-scale variability. The forthcoming IRS geostationary mission should improve NH₃ monitoring through enhanced temporal and spatial sampling.
This study presents a comparison between IASI satellite NH₃ retrievals and ground-based observations across three highly agricultural regions of France between June 2024 and June 2025, using a combination of Radiello passive samplers and high-resolution Picarro analyzers. The objective is to assess how representative satellite observations are of surface measurements and to determine under which conditions satellite data can complement, or potentially substitute for, ground-based monitoring while still capturing the spatial and temporal variability of atmospheric NH₃.
Overall, the manuscript is well written, concise, easy to read and addresses an important and timely topic. Accurate measurements of atmospheric ammonia remain relatively scarce and are subject to several measurement artefacts that vary depending on the sampling technique employed. Therefore, studies that evaluate the consistency and complementarity of satellite and surface observations are highly valuable to both the atmospheric chemistry and air quality communities. I think this paper is ready to be published, once minor comments related to the readability of figures, and more details on certain parts of the paper, mostly addressing details of the number of data used for the comparisons and the QA/QC of the ground measurements.
Specific comments
Introduction
Line 78: Instead of Radiello instruments, I suggest using Radiello passive samplers, as referring to them as instruments is somewhat misleading. In addition, I recommend citing the more recent study by Martin et al. (2019), which addresses the uncertainties and biases associated with both Radiello body types. This reference would complement the Puchalski et al. study and provide a more comprehensive assessment of sampler performance.
Martin, N. A., Ferracci, V., Cassidy, N., Hook, J., Battersby, R. M., di Meane, E. A., Tang, Y. S., Stephens, A. C. M., Leeson, S. R., Jones, M. R., Braban, C. F., Gates, L., Hangartner, M., Stoll, J.-M., Sacco, P., Pagani, D., Hoffnagle, J. A., and Seitler, E.: Validation of ammonia diffusive and pumped samplers in a controlled atmosphere test facility using traceable Primary Standard Gas Mixtures, Atmospheric Environment, 199, 453-462, https://doi.org/10.1016/j.atmosenv.2018.11.038, 2019.
Line 82: I think citing Gu et al. (2021) after Sutton et al. (2003) would strengthen this statement by providing more recent evidence on the importance of ammonia mitigation. The full reference is:
Gu, B., Zhang, L., Van Dingenen, R., Vieno, M., Van Grinsven, H. J., Zhang, X., Zhang, S., Chen, Y., Wang, S., Ren, C., Rao, S., Holland, M., Winiwarter, W., Chen, D., Xu, J., and Sutton, M. A.: Abating ammonia is more cost-effective than nitrogen oxides for mitigating PM2.5 air pollution, Science, 374, 758-762, https://doi.org/10.1126/science.abf8623, 2021.
Methodology: 2.1 Ground based measruements
Macé, T., Iturrate-Garcia, M., Pascale, C., Niederhauser, B., Vaslin-Reimann, S., and Sutour, C.: Air pollution monitoring: development of ammonia (NH3) dynamic reference gas mixtures at nanomoles per mole levels to improve the lack of traceability of measurements, Atmospheric Measurement Techniques, 15, 2703-2718, https://doi.org/10.5194/amt-15-2703-2022, 2022.
Results
Sections 3.1 to 3.3
It would be useful to provide information on the data capture rates of the ground-based measurements. Again, if this information is available in a separate publication, a citation would likely be sufficient. Readers would benefit from knowing what proportion of the seasonal or annual dataset remained after QA/QC procedures. This information is also important when comparing the ground-based measurements with the IASI observations. I assume that the datasets presented here meet a minimum data completeness criterion (e.g., >75% of the sampling period), but this should be explicitly stated.
Figure 3 is a key figure in the manuscript; however, the axis labels and legend are extremely difficult to read. I recommend either splitting the figure into multiple panels or increasing the font sizes substantially to improve readability. A similar issue exists in Figure 4, although it is less critical than in Figure 3.
Figure 5: Please remove the light grey borders at the top of the graph. In addition, the colour legend should either be included directly in the figure or described more clearly in the caption.
Section 3.4
In Line 36, this statement " Comparison between the campaign period and the longer-term record indicates similar distributions, suggesting that the campaign observations are representative of multi-year variability"; do you have any reference or additional figure that supports this statement?
Section 3.5
Technical comments
-Line 18: change operates to operated from....
-Line 51: The Pope et al 2009 reference is not in the reference list, please add it to the reference list.
-Line 60: Change pollutant to pollutants, such as suphur...
Line 96: The start of the sentence "To prevent from the lack..." does not make sense; If I understand correctly, the phrase should start something like "To overcome the lack of surface of measurement...."
Table 1: Passive sampler and Analyzer with caps at the beggining
Line 252: Please superindex μg m-3 in both numbers in this line.
Line 295: Separate 15km to 15 km
Line 378: Please remove the "numbers" after the "number of IASI pixels.
Line 446: Change uniformed to uniform enhancements linked to..
I would like to thank the editor for the opportunity to review this paper and to the authors for putting together this nice manuscript.
Best of luck!