During the project, Canadian and Norwegian SME and research teams were collaborating to develop a sensor system for remote monitoring of SO2 emissions from ship exhaust and deduce the fuel sulphur content. Maritime traffic is steadily raising SO2 emissions with negative impacts on environment and health. Since 2020, International Maritime Organization (IMO) decision entered into force for global fuel sulphur limit of 0.50%. Current maritime authorities’ practices include using staff on ships entering the port to collect and analyse fuel samples (which is labour intensive) stationary sniffers at checkpoints (that are not reliable as most ships can switch off the engine while passing on the momentum below sniffers) or drones with sensor payloads flying through the ship flumes.
The overall ambition of REMON-SO2 project was to facilitate maritime authorities to enforce environmental regulations by establishing and demonstrating a system to remotely detect, identify and quantify SO2 emissions in real-time.
The key results in the project are: 1) We developed a compact hyperspectral camera (less weight and power consumption) with improved sensitivity for LWIR hyperspectral imaging; 2) We utilized the hyperspectral camera to monitor emissions from passing ships, with ground truth data collected using a drone-mounted sniffer; 3) We successfully implemented ship detection in hyperspectral images, which enables more efficient background analysis and storage conservation; 4) We developed automatic detection for the areas of interest for the plume and the reference. The plume contains the exhaust plumes of the ship, the pixels of which are to be analyzed to quantify the various gases. The reference is a homogeneous hot area (the chimney) that is used to determine the atmosphere between the camera and the plume; 5) The Fuel Sulfur Content (FSC) of the ships fuel is computed from the plume hyperspectral data and the atmospheric parameters. This is done via spectral unmixing: a constrained optimization algorithm fitting the spectra of the various constituents to the observed spectra. The ratio of SO2 to CO2 can be used to determine the FSC per scene. The statistics of the various scenes are used as the final FSC report. This completes a fully automated data processing chain from the acquisition of a series of scenes by the spectral camera, to a report on the FSC of the ship’s fuel; the whole system was tested on pilot in Norway with hyperspectral images collected from passing ships and supported by ground truth measurements using a drone.
For NORCE, this project has enhanced the company’s knowledge and capabilities in exhaust emission detection, strengthening its competitiveness in this field. As a maritime nation, Norway places great importance on environmental protection. The company's ability in emission detection can meet the demands of the country, contributing to both the economy and environmental protection.
For Telops, this project enables a fully automated verification process of the Fuel Sulfur Content of passing vessels, enhancing the detection efficiency. In addition, automatic ship detection also makes it possible to eliminate data redundancy and save on data storage.
For Aersea, this project gave the company the knowledge and the experience in exhaust emission detection. Through the project the company succeeded in acquiring the highest drone operator license in Europe (LUC), a VLOS (visual line of sight) license for the unmanned helicopter and gained a foothold in the emission detection business area.
Besides maritime surveys, chemical and industrial plants, this technology, and knowledge can be applied in any other area where the need for detecting gas emissions exists.
Maritime traffic is steadily raising SO2 emissions with negative impacts on environment and health. Since 2020, International Maritime Organization (IMO) decision entered into force for global fuel sulphur limit of 0.50%. Currently the maritime authorities use staff on ships entering the port to collect and analyse fuel samples (which is labour-intensive), stationary sniffers at checkpoints (that are not reliable as most ships can switch off the engine while passing on the momentum below sniffers) or drones with sensor payloads flying through the ship flumes.
The overall ambition of the project is to facilitate maritime authorities’ law enforcement work by establishing and demonstrating a system that will be able to remotely detect, identify and quantify SO2 emissions in real-time and identify the corresponding sulphur content.
The overall goal of this project is to design and develop a compact sensor system that can detect, identify, and quantify SO2 emissions in real-time at a remote distance of few kms along the line of sight from port areas. The project has the ambition to lead to a product that can remotely and continuously monitor for ship fuel sulphur compliance and law enforcement using a stationary installation in ports or using mobile aerial scanning for covering larger area.