Maritime ship traffic is globally increasing with 90% of the world trade being carried over the ocean. The emissions of the maritime traﬃc are a severe threat to the marine environment and coastal population, especially in ports and along shipping lanes with dense populations. Therefore MATE (Maritime Traffic Emissions: A monitoring network) aims to develop a complete monitoring network to allow for continuous monitoring of ship emissions in the atmosphere and in the water, including black carbon, oil residues, sulphur oxides and plastic debris. The MATE-Hyper project will focus on the development of a novel sensor system for soot (black carbon) and plastic debris on the sea surface. We´re developing an integrated, artificial intelligence based system, combining visible and infrared video camera information with guided hyperspectral spot-data designed for buoy and static platforms. Automated extraction of information from this complex data through machine learning techniques will support probabilistic models for pollution characteristics. Combining this data in an intelligent way with other environmental observations will eventually lead to the integration of sensor information towards a reliable holistic situational awareness of marine ecosystem health.