Tracking the Dynamics of Individual Ship Plumes Using Ground-Based Imaging DOAS

Ships contribute significantly to global NOx emissions. Especially in coastal cities they can become a relevant source of air pollution. Established approaches of monitoring ship emissions often rely on in-situ or LP-DOAS measurements and are subject to different limitations like spatial coverage. Therefore, emission estimates derived from such measurements are typically based on simplified transport models and do not fully account for the actual shape and movement of exhaust plumes.Remote sensing techniques, such as imaging DOAS (iDOAS) measurements, can help to overcome these limitations. In this study, we present several months of iDOAS measurements of NO2 (nitrogen dioxide) plumes from individual ships at a major shipping lane near the harbor of Hamburg, using the instrument IMPACT (Imaging MaPper for AtmospheriC observaTions, Peters et al., 2019). The measurements were carried out within the framework of the SEICOR measurement campaign (Ship Emission Inspection with Calibration-free Optical Remote sensing), which started in April 2025.By supplementing the measurements with Automatic Identification System (AIS) data containing information on passing ships, the NO2-column enhancements within the emission plume are detected reliably and calculated from the measured dSCDs in several hundred cases. The high spatial and temporal resolution of the dataset nicely enables a detailed view on plume structure, transport, and dispersion under varying meteorological conditions. The large number of observed plumes allows us to systematically relate plume shape and evolution to key meteorologic parameters (e.g. stability and boundary layer height). The dataset demonstrates that Gaussian plume modeling of single measurements typically is not sufficient to describe the development and emission strength of ship plumes accurately. At the same time, we show that in many cases a mass-balance approach can be used to quantify ship NOx emissions, which are in good agreement with previous studies.