Particles sampled from the main and auxiliary ship diesel engine exhausts during a measurement campaign aboard a cargo ship are studied by SEM and energy-dispersive X-ray (EDX) microanalysis. Cluster analysis (CA) is applied to characterize the particles by separating them into distinct groups of similar morphology and chemical composition, representative of the particle types in the exhaust from the main and auxiliary engines. Raman microspectroscopy, Fourier transform infrared (FTIR) spectroscopy, inductively coupled plasma mass spectrometry and ion chromatography provide the criteria for the clustering of a large data set of individual particles. To identify chemical and morphological features of heavy and distillate fuel oil-derived PM emissions, micromarkers discriminating between the different types of emitted particles are proposed. These micromarkers could enable the classification of multicomponent aerosols according to a source type. This characterization of complex multicomponent aerosols emitted by ship diesel engines improves the quantification of the contribution of shipping to ambient air particulates, and can help to identify a source type in apportionment studies.