The objective of CU 3.2 is to develop a forecasting system capable of predicting the transport and transformation of oil spills in marine environments. By integrating satellite data and meteocean models and data, this system will generate accurate simulations of oil slick movement over time. The predictions will support authorities such as the Guardia Costiera, ISPRA and MASE in their efforts to respond swiftly to oil spill incidents, ensuring timely mitigation and minimizing environmental damage.

The goal of CU 3.3 is to monitor and predict the dispersion of produced water slicks or eventual oil slicks resulting from offshore oil extraction activities. This CU aims to improve pollution tracking by implementing machine learning and artificial intelligence models, combined with traditional water quality modeling, thus enhancing the detection and tracking of oil-contaminated water. By providing a continuous monitoring system and real-time risk assessment capabilities, CU 3.3 will contribute to reducing the environmental impact of offshore discharges while supporting authorities in offshore pollution management.

The objective of CU 3.5 is to generate risk maps that assess the potential impact of oil spills. These maps will combine environmental, socio-economic and predictive modeling data to visualize high-risk areas, supporting strategic decision-making by quickly providing a statistical analysis from a number of combined simulations. Through a GIS-based platform, stakeholders will be able to dynamically analyze risk levels, integrate pollution hazard data with marine ecosystem information and improve coordination for emergency response efforts.

CMCC role
The project is built on a strong multi-sectoral partnership, bringing together leading research institutions, governmental agencies and technology providers to develop an integrated monitoring and forecasting system for environmental protection.
CMCC’s contribution in the Vertical 3 is focused on monitoring marine and coastal pollution. The primary goal is to establish an advanced surveillance system that ensures real-time monitoring and early detection of pollution sources, allowing for rapid intervention and mitigation of environmental damage. CMCC is actively involved in this initiative, contributing its expertise in climate modeling, data analysis and marine ecosystem assessment.

CMCC’s role in Vertical 3 includes:

• developing predictive models to assess and forecast the impact of pollutants on marine ecosystems, leveraging high-resolution climate and oceanographic data;
• enhancing early warning systems for pollution events, including oil spills, improving rapid response capabilities;
• supporting policy and decision-making by providing data-driven insights to governmental agencies, environmental organizations and coastal communities;
• promoting sustainable management strategies to protect marine biodiversity and ensure cleaner coastal environments.

Activities
Within CU 3.2, the key activities involve the development of predictive models for oil spill drift and transformation. An open-source simulation system, based on models such as MEDSLIK-II, is implemented to predict oil movement and its evolution at sea. The system integrates satellite data, meteorological and oceanographic models and information to generate drift forecast maps up to 10 days in the future. An on-demand forecasting system allows authorized operators to simulate oil spill evolution in real time, either based on detected spills from satellite imagery or manually inputted scenarios.

For CU 3.3, activities focus on continuous monitoring and predictive simulation of produced water slicks and oil spills originating from offshore oil extraction. The system processes satellite images and in-situ data to track slick evolution, utilizing machine learning and artificial intelligence algorithms to enhance detection and forecasting capabilities. A core component is the 72-hour forecast model, which continuously updates every six hours to predict the transport and dispersion of produced water contaminants. The system integrates real-time meteorological and oceanographic data to refine these predictions, ensuring that authorities receive the most accurate information possible. All results are visualized through an interactive GIS-based platform, allowing decision-makers to assess the environmental risks posed by produced water discharges in offshore areas.

The activities in CU 3.5 center on the generation of risk maps that combine predictive spill models with environmental and socio-economic data. These maps are created through a systematic process that overlays pollution hazard data with marine ecosystem characteristics, maritime traffic intensity and economic activity zones. Using stochastic simulations, the system assesses long-term exposure risks based on historical spill patterns and environmental conditions. The Web-GIS platform developed within CU 3.5 allows users to interact with risk maps, analyze specific locations and integrate data layers for a comprehensive assessment. The platform supports customized risk evaluations, enabling decision-makers to tailor risk assessments based on factors such as spill volume, weather conditions and geographic vulnerability. Through these activities, CU 3.5 ensures that stakeholders have access to precise, dynamic and actionable risk information for oil spill and produced water slick management.

Expected results
The expected outcomes of CU 3.2 include a more precise and timely forecasting system for oil spill evolution, significantly improving emergency response strategies. Authorities will benefit from accurate trajectory predictions, enabling rapid deployment of mitigation actions to contain and remove oil slicks before they cause severe environmental damage. By integrating real-time satellite observations, meteorological forecasts and oceanographic models, CU 3.2 will ensure that oil spill evolution is monitored with high accuracy, reducing uncertainty in decision-making.

For CU 3.3, the main expected result is the reduction of offshore pollution risks by improving the monitoring and prediction of produced water slicks and oil spills from oil extraction activities. The integration of AI-based detection systems will allow for earlier identification of contamination events, leading to quicker response times and better containment strategies. The forecast model will provide real-time insights into the movement of produced water slicks, helping authorities assess potential environmental risks and enforce stricter pollution control measures. Additionally, the GIS-based visualization platform will offer an interactive and comprehensive overview of offshore pollution risks, allowing decision-makers to take proactive steps in environmental management.

The expected outcomes of CU 3.5 include the generation of high-resolution risk maps, offering a detailed assessment of oil spill and produced water slick threats in marine environments. These maps will enable the precise identification of high-risk areas, considering both environmental vulnerabilities (e.g., marine protected zones, fisheries and coral habitats) and socioeconomic impacts (e.g., tourism and coastal industries). By combining predictive modeling with stochastic simulations, CU 3.5 will facilitate long-term risk assessments, helping policymakers and environmental agencies anticipate potential pollution events and implement preventative measures. The Web-GIS platform will enhance access to risk data, allowing stakeholders to analyze and customize risk assessments based on different parameters, such as spill location, volume and dispersion patterns.

Partners
DXC Technology, Enterprise Services Italia S.r.l., Datamanagement Italia S.p.A., Digitouch Technologies
S.r.l., DS Tech S.r.l., Eustema S.p.A., Exprivia S.p.A., Key Partner S.r.l., Links Management and Technology S.p.A., Lutech S.p.A., Parsec 3.26 S.r.l.

Stakeholders:
Capitanerie di Porto, Guardia Costiera, ISPRA- Istituto Superiore per la Protezione e la Ricerca Ambientale, ENEA- Agenzia nazionale per le nuove tecnologie, l’energia e lo sviluppo sostenibile, IIM- Istituto Idrografico della Marina Militare (Ministero della Difesa), AM– Aeronautica Militare, MIC– Ministero della Cultura, MASE – Ministero dell’Ambiente e della Sicurezza Energetica, DPC RegionePuglia, Autorità di Bacino Distrettuale dell’Appennino Meridionale.