the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 05 Mar 2025
Improved detection of global NOx emissions from shipping in Sentinel-5P TROPOMI data
Abstract. Shipping is an important source of nitrogen oxide (NOx) emissions worldwide, contributing to air pollution and negatively affecting marine environments, ecosystems, and biodiversity. TROPOMI (TROPOspheric Monitoring Instrument) aboard the Sentinel-5 Precursor (S5P) has significantly enhanced the ability to detect ship emissions from space due to its low measurement noise levels and high spatial resolution of 5.5 x 3.5 km2. This study uses the TROPOMI tropospheric NO2 slant column density (tSCD) to identify global shipping routes. Preprocessing techniques, including iterative high-pass and Fourier filtering, markedly improve the detection of shipping lanes, revealing previously undetectable routes. Our analysis examines the impact of high-pass filter box sizes, demonstrating that smaller sizes enhance the visibility of narrow shipping features, while larger box sizes increase overall NO2 signals. Additionally, we investigate various flagging criteria that affect NO2 signal distribution, highlighting the critical importance of careful selection for accurate emission monitoring. Filtered TROPOMI NO2 tSCDs over oceans show a strong correlation with shipping activities, as confirmed by comparison with the CAMS-GLOB-SHIP (Copernicus Atmospheric Monitoring Service for Global Shipping) inventory, and also reveal unknown shipping routes in regions such as the Bering Sea. Furthermore, TROPOMI effectively captures NO2 emissions from offshore oil and gas platforms, with NO2 hotspots in the TROPOMI data aligning well with locations of offshore installations listed in the OSPAR (Oslo and Paris Commission) and BOEM (Bureau of Ocean Energy Management) inventories. Lastly, the filtered TROPOMI NO2 tropospheric vertical column densities (tVCDs) are compared with the tVCDs from the CAMS (Copernicus Atmospheric Monitoring Service) model, which has a coarse spatial resolution of 0.4°. While both data sets effectively identify global shipping lanes, the CAMS NO2 tVCDs are significantly higher compared to the filtered TROPOMI tVCDs, with differences of up to a factor of 100 in the South Atlantic Ocean.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Atmospheric Measurement Techniques.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.- Preprint
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2025-107', Anonymous Referee #4, 27 Mar 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-107/egusphere-2025-107-RC1-supplement.pdf
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AC1: 'Reply on RC1', Miriam Latsch, 02 Jun 2025
We want to thank Referee #4 for the positive feedback, helpful comments, and advice on our manuscript. Detailed responses to the reviewer’s comments can be found in the attached document. We hope that we have incorporated all suggestions and comments in a satisfactory way.
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AC1: 'Reply on RC1', Miriam Latsch, 02 Jun 2025
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RC2: 'Comment on egusphere-2025-107', Anonymous Referee #1, 27 Apr 2025
The manuscript presents a worldmap of patterns of enhanced NO2 over oceans that can be attributed to ship tracks or oil rigs, based on high-pass filtered NO2 measurements from TROPOMI. The paper is well generally well written, and the resulting ship tracks are impressive by the presented detail.
I have the following general concerns:
- The paper presents patterns in a rather qualitative way (tSCDs), while in the title as well as in some instances in the text it sounds as if the study aims to quantify ship emissions. This should be avoided.
- The methodology should be clarified and the individual retrieval/filtering steps should be illustrated for real measurements.
- The comparison to CAMS VCDs is problematic, as this dataset has not been high-pass filtered. This should be modified, or discussed properly.
- The outlook/next steps should be discussed in more depth. Obviously, it would be desirable to quantify NOx emissions for the detected ship tracks. How to do this, which problems have to be solved? (impact on filter settings, AMFs, ...)
Detailed comments:Title: The title is misleading, as it suggests that this study is about quantifying ship emissions. Please consider modifying this, especially in the manuscript, for instance in line 149: I would expect to read a number at the end of the section with such a headline.
A statement like that in line 382 should already be made in the abstract.Line 4, line 49: This TROPOMI pixel size only holds for nadir. Towards the swath edges, pixels are considerably larger.
Line 90: I agree that the tSCD allows the detection of ship NOx without bias from a-priori knowledge used for the AKs in the operational product. However, as soon as NOx emissions should be quantified, the tSCDs need to be converted to tVCDs by an (appropriate) AMF.
Please clarify.Lines 93-104: I think a short modification sentence would be helpful: The tSCD is provided in the operational product (or could easily be calculated by subtracting V_strat*AMF_strat from total SCD), but this quantity turned out to be affected by a simplification in the operational processor: ...
Line 106: What does "approximately" mean?
Line 109: How far is this a "saturation"? What is saturated?
Filtering: The iterative filter approach seems complex, and Fig. 1 does not really help. I would propose to have a sketch showing the effect of the individual steps on real data instead.
Fig. 2 shows the result of the iterative filter process. I do not understand how the values here can exceed 4e13, when in a previous step everything above 3e13 has been skipped. Please clarify.Line 149: Even with stating the disadvantages of applying filters, one might think that all the discussed filters are applied below. A statement should be added that, as default, they are *not*, with reference to later discussion why not.
Line 157: except the model used for assimilating strat. NO2...
Fig. 3: The map of resulting ship tracks is quite impressive, and the benefit of 1° over 0.25° quite prominent. However, this is a result of the high-pass filter, and this will inevitably cause *negative* tSCDs next to the shipping lines. This would have to be taken into account for quantification of emissions. I thus think that the figures should also show the negative values to create awareness for this effect - this might not look as nice, but more honest.
CAMS comparison:
Are the CAMS tVCDs high-pass filtered as well? If not, they should for a more meaningful comparison.Line 421: and avoiding artificial ship tracks just introduced by the a-priori profiles?
Fig. C1: This comparison is not appropriate, since the TROPOMI data has been high-pass filtered, but the CAMS data not. At least this aspect needs to be clearly discussed.
A statement on data availability is missing. I would encourage the authors to make their results available on a data repository so that future studies could reference this dataset with a doi.
Citation: https://doi.org/10.5194/egusphere-2025-107-RC2 -
AC2: 'Reply on RC2', Miriam Latsch, 02 Jun 2025
We want to thank Referee #1 for the feedback and helpful comments on our manuscript. Detailed responses to the reviewer’s comments can be found in the attached document. We hope that we have incorporated all suggestions and comments in a satisfactory way.
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AC2: 'Reply on RC2', Miriam Latsch, 02 Jun 2025
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