Improving evaluation of NO2 emission from ships using spatial association on TROPOMI satellite data

Kurchaba, S.; Vliet, J. van; Meulman, J. J.; Verbeek F.J.; Veenman C.J. (2021)

Article in monograph or in proceedings

As of 2021, more demanding NOx emission requirements entered into force for newly built ships operating on the North and Baltic Sea. Even though various methods are used to assess ships’ pollution in ports and off the coastal areas, monitoring over the open sea has been infeasible until now. In this work, we present a novel automated method for evaluation of NO2 emissions produced by individual seagoing ships. We use the spatial association statistic local Moran’s 𝐼 in order to improve the distinguishability between the plume and the background. Using the Automatic Identification Signal (AIS) data of ship locations as well as incorporated uncertainties in wind speed and wind direction, we automatically associate the detected plumes with individual ships. We evaluate the quality of ship-plume matching by calculating the Pearson correlation coefficient between the values of a model-based emission proxy and the estimated NO2 concentrations. For five of the six analyzed areas, our method yields results that are an improvement over the baseline approach used in a previous study.

• TROPOMI
• NO2
• Ships
• Moran’s I
• Spatial Association
• AIS
• Wind

• All authors: Kurchaba, S.; Vliet, J. van; Meulman, J. J.; Verbeek F.J.; Veenman C.J.
• Editor(s): Meng, X.; Wang, F.; Lu, C.T.; Huang, Y.; Shekhar, S.; Xie, X.
• Date: 2021-11-04
• Title of host publication: Proceedings of the 29th International Conference on Advances in Geographic Information Systems
• Pages: 454 - 457
• ISBN (electronic): 9781450386647
• DOI: doi:10.1145/3474717.3484213
• Link: https://dl.acm.org/doi/10.1145/3474717.3484213