Preprints
https://doi.org/10.5194/egusphere-2025-107
https://doi.org/10.5194/egusphere-2025-107
05 Mar 2025
 | 05 Mar 2025
Status: this preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).

Improved detection of global NOx emissions from shipping in Sentinel-5P TROPOMI data

Miriam Latsch, Andreas Richter, John P. Burrows, and Hartmut Bösch

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.
Share
Miriam Latsch, Andreas Richter, John P. Burrows, and Hartmut Bösch

Status: open (until 09 Apr 2025)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Miriam Latsch, Andreas Richter, John P. Burrows, and Hartmut Bösch
Miriam Latsch, Andreas Richter, John P. Burrows, and Hartmut Bösch

Viewed

Total article views: 104 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
87 14 3 104 2 3
  • HTML: 87
  • PDF: 14
  • XML: 3
  • Total: 104
  • BibTeX: 2
  • EndNote: 3
Views and downloads (calculated since 05 Mar 2025)
Cumulative views and downloads (calculated since 05 Mar 2025)

Viewed (geographical distribution)

Total article views: 98 (including HTML, PDF, and XML) Thereof 98 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 18 Mar 2025
Download
Short summary
This study presents our advanced methods to better detect ship-related nitrogen dioxide (NO2) emissions in TROPOMI satellite data. By applying filtering techniques, we identify numerous global shipping routes, including previously undetectable ones, and emissions from offshore platforms. Additionally, we compare the filtered satellite data with CAMS global model data to estimate the differences between observed and modelled NO2 emissions.
Share