Horizon Europe Projects
Department of Environmental Sciences, Informatics and Statistics

The global denim industry, producing over 3 billion pairs of jeans annually, is one of the most chemically intensive sectors in textiles. Conventional indigo dyeing relies on fossil-derived synthetic indigo and toxic reducing agents such as sodium hydrosulfite, resulting in widespread water pollution, hazardous working conditions, and high energy and chemical input. GREENDIGO aims to revolutionise this process by developing the first fully enzymatic, biobased dyeing method for denim that is scalable, safe, and sustainable. The project will replace conventional indigo with a water-soluble precursor, which can be adsorbed onto cotton fibres under mild aqueous conditions. A specific enzyme will catalyse its in-situ conversion to indigo directly on the fabric, eliminating the need for harmful reductants and enabling a cleaner, circular textile value chain. GREENDIGO will combine cutting-edge enzyme engineering, synthetic biology, and textile chemistry with advanced sustainability assessment to ensure the process is economically viable, environmentally safe, and aligned with planetary boundaries. UNIVE’s research groups, coordinator of the project will apply the EC’s Safe and Sustainable by Design (SSbD) framework from the outset, integrating life cycle analysis, ecotoxicity testing, and absolute sustainability modelling. Outcomes will be benchmarked against current practices, with particular attention to emissions, resource use, and scalability.

SurftoGreen aims to develop a new portfolio of fully bio-based surfactants for key applications.
By using renewable biomass-derived building blocks sourced from EU agricultural and forest side streams, the project seeks to create surfactants with over 95% bio-based content, overcoming the current performance and production throughput constraints. Thus, SurftoGreen seeks to provide environmentally friendly alternatives to conventional, petroleum-based products, thereby contributing to a more sustainable future.
The project will validate the effectiveness, sustainability and safety of its bio-based formulations in industrial demonstrators for home and personal care, textile enhancement, and agriculture.
Thanks to the collaboration between major market players and small businesses, SurfToGreen aims to gain significant market share and compete against existing products, to ensure a paradigm shift towards more environmentally friendly practices.
It brings together 18 partners from 10 different countries. Among them, UNIVE is responsible for WP5 “Sustainability integration”, leading the implementation of the EC SSbD (Safe and Sustainable by Design) framework for the innovative solutions being developed in the project.

BioSusTex is a project financed by the Horizon Europe Programme involving 13 international partners with the main objective of improving chemical safety and sustainability of bio-based products in the textile sector. Focusing on cotton and cellulosic textiles BioSusTex targets increased recycling rates and substitution of harmful compounds by (i) delivering an optimized cellulosic fiber recycling process for dope-dyed man-made cellulosics, (ii) develop efficient and sustainable pre-processing techniques for removal of elastane, dyes, and impurities from post-consumer blended cellulosic textile, while avoiding potential toxic degradation products during processing (iii) develop a biobased PFAS-free water-repellent coating based on an innovative methodology with temporary surfactants and (iv) developing removable biobased, PVC-free print formulations. Significant improvements in these key technologies, in accordance with the Safe and Sustainable by design (SSbD) framework, are expected to notably improve the sustainability of the textile value chain. Further, BioSusTex will not only yield technical solutions but respond to the industry needs of rapid assessments methods by (v) further developing analytical methods and prediction tools related to toxicity evaluation (vi) building a novel Decision Support software tool implementing the SSbD methodology; and (vii) creating a database compiling all the data generated in the previous stages, which ultimately supports systemic sustainable innovation in the textile value chain as a whole.

The SUNRISE project (acronym for "Safe and Sustainable by Design: integrated approaches for impact assessment of advanced materials”) aims to develop an integrated assessment of potential impacts on human health and the environment from innovative commercial products consisting of advanced materials (AdMa), including nanomaterials. As defined by the Organization for Economic Cooperation and Development (OECD), AdMa are defined as those materials that exhibit innovative or improved properties compared to conventional materials, such that they bring new performance and/or functionality. Life cycle analysis of such innovative products (from the raw materials required for product synthesis to the disposal and end-of-life phases) will be the cornerstone for the development and application of an integrated assessment of their safety (for the environment and for workers’ and consumers’ health) and of their environmental, economic and social sustainability. This integrated assessment will be implemented taking into account the Safe and Sustainable by Design (SSbD) approach, recently promoted by the European Commission, in order to support the design and development of innovative products, ensuring their safety and sustainability. SUNRISE envisions the involvement of several key stakeholders along the entire value chain in a co-creative process that balances the perspectives and interests of stakeholders from industry (including SMEs), regulation, policy, consultants (and CROs), academia, and the civil society.

Lack of interoperability between building datasets is a key issue MODERATE aims to address by developing an open marketplace where data can be reliably shared between data owners. In a next step, the platform will allow for users to make use of different services to analyse the available data, gain insights on the building stock and create a long-term impact for the management of buildings.

The Bauhaus defined the role of design in the 20th century by combining art and architecture with industry and construction embedded in a political, economic and social vision of the world. The New European Bauhaus (NEB), promoted by the European Commission, aims at raising a movement towards implementing the Green Deal based on sustainability, social inclusion, and beauty. 
This means realising regenerative approaches inspired by nature that enrich our experiences through creativity, art, and culture, embracing diversity to promote inclusive, accessible spaces where the dialogue between diverse cultures, disciplines, genders, ethnicities, and ages becomes an opportunity to imagine a better future for all. 
In response to the challenge of the climate crisis, the Bauhaus of the Seas (BoS) proposes a NEB mobilisation around the most important natural space in the EU and the world: the sea.
The BoS aims to demonstrate solutions for climate neutrality with a particular focus on coastal cities and will offer opportunities to engage with communities for an environmentally sustainable, socially fair, and aesthetically appealing transition. 
Seven lighthouse demonstrators will be located in different aquatic ecosystems: the Atlantic Tagus River Estuary (Lisbon/Oeiras), the Lagoon in the Adriatic (Venice), the Gulf of Genoa (Genoa), the Atlantic Rhine–Scheldt Delta (Rotterdam), the Öresund Strait (Malmö) and North Sea / Elbe River (Hamburg). They will serve as pilots for the broader implementation of the NEB under the vision of the BoS.

GREENART is a Horizon Europe funded project which involves 28 international partners. The project aims at identifying and producing safe and effective solutions for the conservation and restoration of works of art based on materials with a low environmental impact derived from renewable natural source or from recycled waste. The project proposes new solutions based on green and sustainable materials and methods:

1. protective coatings based on green materials from waste and plant proteins;
2. foams and packaging materials made by biodegradable/compostable polymers from renewable sources;
3. consolidants based on natural polymers from renewable sources;
4. gels and cleaning fluids inspired by the most advanced systems currently available to conservators, improving them according to green and circular economy;
5. green tech solutions for monitoring cultural heritage assets non-invasively against pollutants and environmental oscillations.

The safe-by-design approach will be used from the early design stages to verify the product safety.
In addition, product performance will be evaluated throughout the entire life cycle, in line with Life Cycle Assessment principles, which will be used to assess both environmental sustainability and economic feasibility.

Ca' Foscari, within the AiCE project, will research and develop artificial intelligence and computer vision models to segment and recognize particular patterns within ice cores. Given the increasing availability of data, this will allow for the automation and speeding up of ice core analysis, which are crucial for progress in polar science research. Furthermore, generative AI models will be used to reduce the amount of acquired data, hence speeding up the analysis.

The research project, funded by the Horizon Europe programme with an ERC starting grant, tackles the problem of organizing big and structured data sets in order to reduce their space usage and accelerate searches inside them. On a high level, the idea is very similar to the functioning of a common dictionary: it is much easier to search a term in a dictionary rather than in a book because, in the former, terms are sorted alphabetically. The REGINDEX project extends this simple idea to much more complex data: labeled graphs (or, equivalently, regular languages). While sentences in a book are formed by consecutive words, in a labeled graph “jumps” between (even very distant) words are permitted. Even if this makes the problem of searching sentences in a graph much more complicated, the project will show that the idea of sorting still applies. The developed techniques will find immediate applications in the design of algorithms for searching mutations inside sets of genomes. The DNA of two human beings is never perfectly identical. As a matter of fact, the differences existing among all human genomes can be modeled as a very large labeled graph: a pangenomic graph. The problem of searching for a particular mutation in the data set translates to that of searching a “sentence” (a path) inside this graph.

Cross-Modal Alignment for Semantic Processing and Effective Representation (CASPER) bridges the gap between artificial intelligence (AI) and human cognition by creating multimodal systems capable of reasoning similarly to humans. Although large language models (LLMs) excel in text processing, they often struggle with seamlessly integrating diverse modalities like audio, images, videos, and neural signals. CASPER addresses this limitation by combining deep learning, graph neural networks (GNNs), and neuroscience within a unified architecture. Inputs across modalities are encoded into embeddings and structured as nodes within a semantic graph. GNNs fuse these nodes into abstract concepts aligned with the semantic token space of an LLM. This integration empowers the LLM to perform multimodal reasoning, enabling tasks such as audiovisual question answering or image captioning. CASPER also uniquely decodes neural signals (fMRI, EEG, MEG) into this shared semantic space, allowing neural activity to directly reconstruct sensory experiences via generative models. Supported by interdisciplinary expertise from Ca’ Foscari University, EPFL, and the University of Geneva, CASPER significantly advances multimodal AI and brain-computer interfaces.

The IMAGICS project aims to significantly enhance the resolution of isotopic analyses of ice cores, in order to detect rapid and abrupt climate signals recorded in isotopic patterns. This will be achieved by acquiring images of the isotopic composition of ice samples coupling the Cavity Ring-Down Spectroscopy (CRDS) and the Laser Ablation (LA) techniques. The objectives and activities planned at DAIS are the following:

1. Optimizing the production of water vapor pulses from synthetic ice using LA, suitable for CRDS analysis.
2. Developing a method to produce isotopically homogeneous synthetic ice with known isotopic composition, to be used as a standard for LA-CRDS.
3. Creating a library of functions for automated extraction and analysis of isotopic images obtained through LA-CRDS.
4. Testing the LA-CRDS technique on real ice core samples, focusing on periods marked by high climate variability.

The results of the project will provide a new tool to the glaciology and paleoclimate communities for studying past rapid climate changes. The project also serves as the groundwork for interfacing LA with other gas analyzers for applications in different climate archives or planetary science.

MESMERISE will build on the latest advances in the laser ablation inductively coupled plasma mass spectrometry 2D Imaging technique to retrieve climatic information from the three Greenlandic ice cores NGRIP, NEEM, and RECAP covering the last warm period, the Eemian. The results will lead to a better understanding of the current warm period while improving our interpretation of the climate signal stored in the deepest parts of polar ice cores. This will be highly relevant for other projects such as the quest for the Oldest Ice in Antarctica. Nicolas Stoll will conduct his research at the Department of Environmental Sciences, Informatics, and Statistics of Ca' Foscari with Prof. Carlo Barbante. Further research will be carried out at the Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research in Bremerhaven, Germany, with Prof. Pascal Bohleber and at the Physics of Ice, Climate and Earth section of the University of Copenhagen with Assist. Prof. Anders Svensson.

Estimating the ice volume of Earth's glaciers is a grand challenge of Earth System science. Besides being a critical parameter to model their evolution, knowledge of glacier volumes is fundamental to quantify both global sea level rise and available freshwater resources. Under anthropogenic forcing, shrinking glaciers impacts water availability for almost 2 billion people, and contributes to more than 20% of sea level rise. Improving glacier ice volume estimates is now a top-priority for humans both for the present time and for the future climate scenarios. Today, the amount of satellite data is increasing at such a rate that it cannot be efficiently exploited by traditional processing pipelines. The goal of SKYNET is to develop AI deep learning models capable of exploiting the huge amount of available satellite data to predict and refine the ice volumes of all Earth’s glaciers, from continental glaciers to polar glaciers, including those in the periphery of Greenland and Antarctica. SKYNET will be jointly developed by Ca’ Foscari University of Venice, the University of California Irvine and the Jet Propulsion Laboratory.

The EXPEDITE project addresses the urgent need for advanced multi-hazard risk assessments and resilience measures to enhance decision-making for risk management in the EU and globally. Traditional risk assessments often rely on static models, which fail to capture the dynamic and complex nature of climate hazards. This leads to inadequate information for timely decision-making. The project aims to overcome barriers such as data availability, computational costs, and the integration of multiple hazards. By leveraging artificial intelligence technology, EXPEDITE will develop a prototype climate service to provide actionable intelligence to various end-users, including governments and private sectors. The project will focus on creating innovative, cost-effective, and practical solutions that go beyond the current state of the art, aiming to deliver more efficient climate risk and resilience assessments.

A 30cm sea level rise could damage most of the world's beaches by 2100. Data shows 1500 more km of eroding beaches compared to stable beaches along the Italian Mediterranean coast. Sandy beaches vital for hospitality dominate Italy's coasts but are deteriorating. Although crucial for tourism, projected beach losses from climate change are often excluded from strategies, potentially limiting their effectiveness. The SEA-LIMITHS project assesses the economic and environmental impacts of sea-level rise on the coastal hospitality sector using AI, adding to limited research on climate change effects. This project fills a critical gap by analyzing the consequences of sea level rise on sandy beaches and beach hospitality losses from erosion and flooding in two key coastal regions, Veneto, and Emilia-Romagna. Hosted by the prestigious Department of Environmental Sciences, Computer Science and Statistics at Ca' Foscari University of Venice, the study is supervised by renowned professor Francesco Bosello, an expert in the field and coordinator of the Climate Change Economic Analysis of Climate Impacts and Policy division at the Euro-Mediterranean Center on Climate Change. The research provides necessary evidence on sea level rise impacts to inform coastal management and climate change adaptation in the hospitality sector.

Increased frequencies of natural disasters (droughts, flooding, and eutrophication) due to global warming and related resources scarcities necessitate timely and pro-active actions of mitigation, adaptation, and recycling. Due to occasional and unexpected occurrence of the catastrophes and accumulative adverse effects of disturbing environmental systems which come into surface in the long run, short-sighted financial and investment policies that are considered for 5-10 years often overlook these effects. Unexpected flooding in spring and temperature anomalies during summer in Europe, increased forest fires in tropical areas within the last years also indicated unpreparedness of the financial and infrastructure systems to cope with such disruptions. Within the SIMARIS project, we aim at developing a long-term macro-economic growth model integrated with water-land-energy systems. This model allows for analyzing strategic investments to improve water, land and energy use efficiency and strengthen resilience of the infrastructural systems to deal with resource scarcities and natural catastrophes. The model will be implemented to the case of Central Asia where water and energy scarcity and degradation of lands are major issues that threaten livelihoods and prevent sustainable economic growth. In addition to numerous contributions to water-economic modeling field, this project therefore effectively contributes to improve environmental protection and investment policy making in the study region and beyond.