The session aims to:
• Highlight the strategic objectives of various projects, networks, and partnerships in promoting sustainable, socially, and environmentally responsible resource management and innovation.
• Showcase collaborative actions and cross-project synergies, including technology, industry, environment, society, and policies.
• Present notable outcomes as well as industrial, societal, and environmental impacts that contribute to the EU’s vision for a low-carbon, circular economy.
• Discuss future directions and plans for scaling innovations and enhancing sustainability throughout the value chain at different scales.
Special attention will be given to cross-sector collaborations and initiatives that promote the integration of research, industry, society, and policy efforts. These collaborations focus on fostering sustainable development, enhancing the resource efficiency of the raw materials sector, and contributing to the EU’s strategic goals for circularity and economic resilience.
This session aims to facilitate collaboration and knowledge exchange among projects, networks, and partnerships, serving as an entry point for more specialised sessions on specific aspects of the raw material value chain and sustainability. By promoting a cross-project perspective, the session ensures that the outcomes of various initiatives are widely disseminated within the EGU community, fostering a holistic approach to sustainable resource development.
This session is co-organised by
Horizon Europe projects AGEMERA, MultiMiner, EIS, GoldenRAM, AVANTIS, LITHOS, EXCEED
Finnish projects: JTF Development of the Extractive Industry in the Lapland, Northern Ostrobothnia and Kainuu (KAKE); ERDF Lapland Mining hub
The AGEMERA project (Agile Exploration and Geo-Modelling for European Critical Raw Materials), funded under the Horizon Europe programme and recognised as a Horizon Europe Technology Success Story (European Commission: European Health and Digital Executive Agency, 2024), supports the EU's green and digital transitions by addressing challenges in the supply of critical raw materials (CRMs) (European Commission, 2024).
AGEMERA advances CRM exploration by integrating geological, technological, and social strategies. It enhances understanding of mineral deposit models through systematic research approaches, including data collection, synthesis, and modelling. By refining mineral system models, AGEMERA aims to identify overlooked CRM deposits and promote sustainable mining practises in the EU (Holma et al., 2022)
From a technological perspective, AGEMERA employs non-invasive methods such as muography, ambient noise seismology (Romero and Schimmel, 2018), and drone-based electromagnetic surveys (Pirttijärvi et al., 2014) to minimise environmental and societal impacts. These methodologies are supported by the AGEMERA AI engine, a cloud-based platform that integrates diverse datasets through AI Knowledge Packs (Stimac Tumara and Matselyukh, 2024). The platform facilitates efficient data processing, targeting, and visualisation via a natural language interface.
The project emphasizes social local (non)acceptance and the integration of community perspectives in mining practices through tools like surveys and participatory methods. Educational initiatives, including university courses, public events, and an online game, aim to increase awareness of CRMs’ societal importance and encourage responsible resource management.
Key deliverables include:
- Enhanced models for CRM exploration.
- Non-invasive geophysical methodologies.
- AI-driven data integration platforms.
- Tools to evaluate and address community acceptance of mining.
- Educational resources to support sustainability awareness.
Aligned with the EU’s Critical Raw Materials Act (European Commission, 2024), AGEMERA promotes sustainable CRM supply chains and reduces reliance on imports. By integrating geological, technological, and societal dimensions, AGEMERA contributes to Europe’s transition to a low-carbon, circular economy.
Acknowledgements
The project receives funding from the Horizon Europe programme (Grant agreement ID: 101058178).
References
European Commission: Regulation (EU) 2024/1252 of the European Parliament and of the Council of 11 April 2024 establishing a framework for ensuring a secure and sustainable supply of critical raw materials and amending Regulations (EU) No 168/2013, (EU) 2018/858, (EU) 2018/1724 and (EU) 2019/1020Text with EEA relevance., 2024.
European Commission: European Health and Digital Executive Agency: An insight into successful raw materials projects – EU Horizon technology success stories – Vol. 4, Publications Office of the European Union, https://doi.org/doi/10.2925/8174788, 2024.
Holma, M., Korteniemi, J., Casini, G., Saura, E., Šumanovac, F., Kapuralić, J., and Tornos, F.: Agile Exploration and Geo-modelling for European Critical Raw Materials - Introduction to the AGEMERA project, 51–54, 2022.
Pirttijärvi, M., Zaher, M. A., and Korja, T.: Combined Inversion of Airborne Electromagnetic and Static Magnetic Field Data., Geophysica, 50, 2014.
Romero, P. and Schimmel, M.: Mapping the basement of the Ebro Basin in Spain with seismic ambient noise autocorrelations, J Geophys Res Solid Earth, 123, 5052–5067, 2018.
Stimac Tumara, B. and Matselyukh, T.: AGEMERA AI: Innovative AI solution for responsible resource exploration, in: EGU General Assembly Conference Abstracts, 628, 2024.
How to cite: Joutsenvaara, J., Niinikoski, E.-R., Holma, M., Suopajärvi, L., Islam, M. A., Meissner, G., Saartenoja, A., Štimac Tumara, B., Nemethy, A., Vrabie, C., and Käär, K.: AGEMERA: Integrating Non-Invasive Geophysical Technologies, AI, and Social Strategies for Sustainable Critical Raw Material Exploration in Europe, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5708, https://doi.org/10.5194/egusphere-egu25-5708, 2025.
The Exploration Information System (EIS) is an initiative focused on advancing mineral systems modelling and mineral prospectivity mapping through open-source tools. This 36-month project is a collaboration among 17 partners across six EU member states and beyond, integrating expertise from academia, research institutes, industry, and service providers. The EIS project is funded by the European Union’s Horizon 2020 Europe research and innovation program under grant agreement no. 1010557357.
EIS addresses the EU’s need for critical raw materials (CRMs) by developing innovative data analysis and modelling tools. Central to the project are the "EIS Toolkit" and "EIS QGIS Wizard," open-source platforms designed to enhance exploration efficiency, reduce environmental footprints, and strengthen sustainable resource management. These tools leverage advanced methodologies, including machine learning and artificial intelligence, to refine prospectivity analysis and predictive mapping across diverse mineral systems, such as VMS (Volcanogenic Massive Sulphide), granite-related lithium-tin-tantalum-tungsten, and IOCG (Iron Oxide Copper-Gold).
This presentation will showcase the EIS project’s objectives, methodologies, and key achievements, such as the development of the mineral systems library, software tools and selected case studies. Furthermore, it will discuss the project’s contributions to the EU’s Critical Raw Materials Act goals, emphasizing cross-sector collaboration and open-access innovation. By aligning research, industry, and societal goals, EIS demonstrates how EU-funded projects can foster sustainability, economic resilience, and resource efficiency in the raw materials sector.
How to cite: Nykänen, V., Munia, H., Bauer, T., Knobloch, A., Bertrand, G., Kaija, J., and Cremesty, J.: Integrating Mineral System Modelling and Mineral Prospectivity Mapping with Open-Source Tools: Insights from the EIS Horizon Europe Project, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10000, https://doi.org/10.5194/egusphere-egu25-10000, 2025.
Earth Observation (EO), as a tool to improve efficiency of mineral exploration and mine site monitoring, requires easily accessible robust highly automated data processing algorithms. The Horizon Europe funded Research and Innovation Action project “Multi-source and Multi-scale Earth observation and Novel Machine Learning Methods for Mineral Exploration and Mine Site Monitoring” (MultiMiner, 2023–2036) develops innovative machine learning solutions to support the critical raw material (CRM) independency of EU. We develop and utilize self-supervised or weakly supervised machine learning solutions which require a low number of in situ reference data. This presentation showcases the recent advancements of the MultiMiner project and highlights of application of the novel machine learning algorithms in selected case studies for mineral exploration and mine site monitoring.
In the MultiMiner project, robust, transferable, scalable and automated tools are developed for mineral exploration. These tools are based on multi-source EO data at multiple data scales and platforms and are implemented into a stand-alone software. The tools include a Mineral Mapping Algorithm (MMA) to perform an automatic spectral feature extraction from deposit-type related reference spectra from a customized reference mineral spectral library. Additionally, workflows to perform automated machine learning interpretation of the multiscale EO data mapping results are developed to produce value added mineral maps of alteration zone or proxy minerals. Finally, a Mineral Prospectivity Wizard GUI is developed, facilitating multi-scale mineral mapping and automatic data interpretation in a guided step-by-step process to analyse EO data even usable for non-remote sensing experts. The developed algorithms are expected to improve accuracy and time-efficiency of direct mineral identification of CRMs and other raw materials.
To reduce disruptions to mining operations and monitor environmental aspects of operating and closed mine sites, MultiMiner creates timely mine site monitoring methods. A novel Generic Mine Site Monitoring (GMSM) algorithm, capable of combining multi-source EO data at various temporal, spatial and spectral resolutions, and requiring only a limited amount of in situ data, is developed. The GMSM algorithm leverages EO foundation models for different modalities, and includes support of temporal information as well. The GMSM algorithm can automatically monitor impacts of mining on the environment, such as water quality and acid mine drainage mapping, or combined monitoring of atmospheric and surface dust. Furthermore, success of rehabilitation activities, including monitoring the revegetation status and Tailings Storage Facility (TSF) dismantling are researched. EO-based solutions for improving mining safety and mitigating operational risks are proposed in terms of ground moisture monitoring and open pit and TSF dam stability monitoring.
To unlock the potential of EO data, including Copernicus Sentinel-1 and Sentinel-2, EnMAP, drone-borne hyperspectral, radiometric and multiband SAR as well as in situ collected spectral data, we present case studies to demonstrate and validate the use of the MultiMiner machine learning -based algorithms at five test sites in Europe. The acquired field data are harmonized following project-specific guidelines and subsequently, the metadata of the thus acquired field data are safeguarded in a project database. In the presentation, we give a brief overview of the guidelines and the database.
How to cite: Middleton, M., Liwata-Kenttälä, P., Schlok, M., Molinier, M., Laakso, K., and L'Haridon, J.: MultiMiner: New Earth Observation data processing algorithms for mineral exploration and mine site monitoring, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12558, https://doi.org/10.5194/egusphere-egu25-12558, 2025.
The European Commission´s Critical Raw Materials Act (CRMA) sets multiple benchmarks
for reducing Europe’s dependency on a few third countries for strategic/critical raw
materials. Vanadium (V) and titanium (Ti) have received less attention than other CRMs
such as the battery raw materials, or the light/heavy rare-earth elements that have been
central to many previously funded projects. However, the situation for vanadium and
titanium is no different to that of the popular CRMs: there is no domestic vanadium or
(refined) titanium metal production in the EU, making the EU critically dependent on
imports. To help achieve the benchmark of 10% domestic extraction in CRMA, AVANTIS
will develop a low-carbon, multi- grade under/unexploited, vanadium-bearing
titanomagnetite (Ti-V-Fe-(P)) deposits and mining wastes.
Europe has a multitude of unexploited, low-grade V-bearing titanomagnetite deposits in
Finland, Sweden, Greenland, Norway, Poland and Ukraine. However, these deposits have
a complex “spiderweb-like” mineral assemblage. Without selective blasting, selective
fragmentation and pre-concentration technologies to separate the Ti-rich ilmenite grains
from the V-bearing magnetite, these deposits are not economically viable. Supported by a
bespoke forensic geometallurgy, AVANTIS develops a novel selective blasting approach
that allows for rock excavation in view of increased mineral liberation at the blasting stage,
and reduced energy demand in the crushing and grinding stages. In addition, AVANTIS
designs tailored, water-free and water-lean pre-concentration technologies that can
produce two distinct pre-concentrates: (1) ilmenite-rich, Ti-pre-concentrate and (2)
ilmenite-free, V-pre-concentrate. The water-lean method is also tailored to process V/Ti-
bearing mining wastes from historical/on-going operations. It is expected that the resulting
flowsheets have a low net water consumption and reduced GHG intensity of extraction.
AVANTIS strengthens the “responsible mining in Europe”-paradigm, increasing society’s
trust in domestic CRM production.
How to cite: Luukkanen, S.: AVANTIS - Sustainable, decarbonised vanadium, titanium and iron extraction from Europe’s low-grade vanadium-bearing titanomagnetite deposits , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-21197, https://doi.org/10.5194/egusphere-egu25-21197, 2025.
The SEMACRET project aims to develop socially and environmentally responsible exploration methods for green transition (Critical) Raw Materials (PGE, Co, V, Ti, Ni, Cu, Cr) hosted by ultramafic-mafic orthomagmatic mineral systems. The primary focus is on refining ore deposit models following the mineral systems approach, optimising regional-scale exploration targeting, and developing efficient local scale exploration methods. There are 4 reference sites serving as case studies for testing these methodologies, including Lapland in Finland, the Beja area in Portugal, the Ransko area in the Czech Republic, and the Suwalki and Sleza areas in Poland.
The project has refined multiple geochemical proxies to identify the key source (mantle) component and degree of melting for generating metal rich magmas, in both rift and orogenic belts settings. Using computational modelling, magma transportation on a whole-crustal scale and within the upper crust have been modelled. High temperature experimental studies and thermodynamic modelling have been applied to constrain the metal precipitation mechanisms. All these provide fundamental clues for guiding mineral exploration in both regional and local-scale exploration.
Regional exploration targeting for orthomagmatic mineral deposits involves the compilation of mineral system models for Ni-Cu-rich conduit-type and PGE-Cr-V-rich layered mafic intrusion systems, supplemented by the insights gained from geological modelling. We applied new deep penetration geodata as predictor proxy in the modelling. These predictor maps are then integrated using a knowledge-driven approach for prospectivity modelling. The implication for future upscaling is to build up a GIS based deep penetration geophysical database across Europe from dispersed sources, as part of the European Geological Data Infrastructure, to facilitate the utilization of these data for guiding mineral exploration. In addition, an innovative outliner detection method has been developed which can be applied for identifying occurrence of mineral deposits.
Local-scale exploration focuses on creating an integrated solution that combines innovative methods to identify high potential areas at the deposit scale to be applied in brownfield exploration. The project developed innovative geophysical inversion methods. These include 3D inversion for electromagnetic (EM) data of sulfide ores taking into account induced polarization (IP), and joint inversion of EM and ground IP data in QGIS plug-in, advanced modelling algorithms of full tensor magnetic gradiometry (FTMG) data and 3-component passive seismic modelling. Novel environmentally friendly surficial geochemistry tools based on upper soil horizons and plant geochemistry are also being explored. In addition, machine learning-based resource modelling and 3D prospectivity modelling are under development. Many of these technologies have potential for future upscaling. Different technologies can be integrated and combined with litho-geochemical modelling, for an optimized solution for the best practice on different mineralization styles.
Sustainable mineral exploration needs to promote social awareness on the significance of raw materials. In SEMACRET, social community events, interview and machine learning based social media analyses have been carried out to understand the attitudes towards exploration and mining from different stakeholders. Mineral source data on key raw materials hosted in orthomagmatic mineral systems have been collected across Europe, and conversion to UNFC code is on going.
How to cite: Yang, S., Jesus, A., and Consortium, S.: Sustainable exploration for orthomagmatic ore deposits, progress of the HEU SEMACRET project, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-21282, https://doi.org/10.5194/egusphere-egu25-21282, 2025.
The combination of mineralogical, geochemical, and spectroscopy data in the visible, near-infrared, and shortwave infrared (VNIR-SWIR) wavelength ranges provides the determination of mining spectral signatures. These signatures enable the identification and classification of geological materials present in a specific mineral deposit. Beyond their use in remote sensing studies focused on the studied area, mining spectral signatures have broader applications in exploration and extraction processes. They provide a rapid, cost-effective way to classify samples according to ore content, without the need for reagents or harmful chemicals.
This paper presents the methodology and the results of the determination and validation of the mining spectral signatures during a pilot study conducted in the Aramo Plateau (northern of the Iberian Peninsula), included in the S34I project (Secure and Sustainable Supply of Raw Materials for EU Industry). Mineralization of Co, Cu, and Ni in this area have been known since the last century, associated with the alteration of carbonates due to fluid circulation linked to tectonic activity in the region.
Through the analysis of 133 samples, 11 mineralogical associations were identified. Of these, 9 (7 corresponding to rocks and 2 to soils) were distinguishable from one another using VNIR-SWIR spectroscopy, so each association was assigned a characteristic spectral signature. Three of these groups were related to the higher Co content. These spectral signatures were subsequently validated through X-ray diffraction analysis of the samples. The validated spectral signatures enabled the fast mineralogical characterization of 550 samples and their classification according to their Co, Cu and Ni content.
The methodology developed here is easily transferable to other mineral resource exploration studies.
How to cite: Suarez, M., Santamaría, Á., Ramírez, J. D., Morales, J., and Williams, V.: Mining spectral signatures for mineral resource exploration. Results from the EU S34I Project., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-21362, https://doi.org/10.5194/egusphere-egu25-21362, 2025.
The GoldenRAM (G-RAM) project will provide easy exchange of accurate information on Raw Materials in the European Union and partnering countries for organizations engaged in the mining industry and public stakeholders. The project will develop an Earth Observation Platform (G-RAM platform) leveraging novel Artificial Intelligence (AI) Natural Language processing in combination with advanced, proprietary Artificial Intelligence Knowledge Packs (AIKPs) which simplify complex computation workflows and provide seamless access to a unique and validated combination of geological and remote sensing data, domain expertise, and multipurpose mapping technologies for geological and mining industry stakeholders. Especially, the introduction of AIKPs plays an important role in advancing the TRL of state-of-the-art solutions and enabling their wider adoption among the industry and stakeholders. The G-RAM platform will be demonstrated in 6 field trials creating a compelling value proposition for implementation across the mining industry value chains and improving responsible and sustainable supply of CRMs to Europe.
How to cite: Paavola, M.: GOLDENRAM - EO Platform supporting critical raw materials industry in Europe, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15265, https://doi.org/10.5194/egusphere-egu25-15265, 2025.
The growing demand for critical raw materials, such as rare earth elements, cobalt, and lithium, is driven by their indispensable role in renewable energy technologies, battery systems, and advanced electronics. As near-surface deposits of these materials are increasingly depleted, the focus of mineral exploration is shifting to concealed and deep-seated deposits, which present significant challenges in both detection and extraction. This study presents a comprehensive, interdisciplinary approach to advancing surface-based geochemical exploration techniques, enabling more precise targeting of hidden mineral resources while minimising environmental impact and maximising sustainability.
Central to this research is the integration of advanced exploration technologies with innovative geochemical methods. The project emphasises the development of refined surface geochemical techniques to identify subtle anomalies in elemental composition that signal the presence of deep ore systems. By combining geochemical data with geophysical evidence, the study aims to provide a holistic understanding of ore-forming processes and their surface expression. Recent advances include the application of ultra-high-resolution analytical chemistry, cost-effective and efficient sampling strategies, and the exploration of new phyto-geochemical media. Furthermore, UAV-assisted biogeochemical sampling introduces an innovative dimension, enhancing the accessibility and precision of data collection in challenging terrains.
A key feature of the project is the incorporation of artificial intelligence (AI)-assisted 3D mineral prospectivity modeling, which enables the integration of diverse datasets to produce highly accurate predictive models. This technological synergy not only improves the resolution of mineral targeting but also significantly reduces exploration costs and environmental impacts by optimizing sampling strategies and minimizing invasive practices.
The DeepBEAT project also addresses the broader societal and environmental dimensions of mineral exploration. By focusing on sustainable methodologies, the research prioritizes minimizing ecological disruption while fostering transparency and acceptance among stakeholders. The outcomes of this study contribute to advancing global capabilities for securing critical raw materials, which are essential for achieving a sustainable, technology-driven future.
Overall, this work pushes the boundaries of surface geochemical exploration by uniting state-of-the-art analytical, geophysical, and data-processing technologies. The results provide a transformative framework for the precise and sustainable detection of deep-seated mineral systems, laying the foundation for a responsible and resilient raw materials supply chain.
How to cite: Wollenberg, A., Pospiech, S., and Birtel, S.: DeepBEAT - Innovative Geochemical Approaches for Sustainable Exploration of Deep-Seated Mineral Resources, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20971, https://doi.org/10.5194/egusphere-egu25-20971, 2025.
The new “environmental technologies,” such as electric vehicles, batteries, and wind turbines—essential for reducing greenhouse gas emissions and achieve the EU goal to be climate-neutral by 2050 —will require over 400% more Critical and Strategic Raw Materials (CRM and SRM, respectively) by 2050 compared to today. However, EU’s domestic supply of primary CRM and SRM —including basic metals, industrial minerals, and aggregates—accounts for less than 3%. This creates a significant supply risk, as Europe depends on third countries for the green transition.
To achieve European resource security, actions must be taken to diversify supply from primary and secondary CRM and SRM sources and enhance resource independence, efficiency, and circularity, including sustainable product design. However, despite advances in exploration technology, the discovery rate of ore deposits continues to decline, while the supply from shallow deposits is nearing depletion. Under these circumstances, new ore models based on sophisticated deep-land exploration techniques, analysis, and interpretation, are becoming increasingly important.
DEXPLORE aims to reduce Europe’s reliance on non-EU countries for CRM and SRM by developing an advanced surface-to-subsurface exploration package including innovative techniques, such as geochemical and optical methods, mineral UAV-assisted detector, Earth Observation tools, and deep-land geophysics capable of exploring up to 600 meters deep.
With three pilot zones — fluorite mineralization at northern Spain, VSHMS deposits of the Iberian Pyrite Belt (Cu, Ni, Zn), and graphitic and sulfide-bearing gneisses of the N-E Estonian Precambrian basement (Cu, Ni, Zn, Pb, Mo)— DEXPLORE aims to develop updated ore models. This will be achieved through an advanced surface-to-subsurface exploration package and an extended reality (XR) platform that integrates geological, remote sensing, and geophysical data. The project seeks to enhance decision-making, increase public awareness of the critical role of CRMs in the green transition, and promote sustainable resource sourcing.
DEXPLORE brings together 13 partners—11 beneficiaries and 2 affiliated entities—from 4 European countries: Spain, Greece, Estonia, and Italy. Each partner contributes top-notch expertise in their field, playing a distinct role in the project, which reflects its multidisciplinary nature of the project.
How to cite: Hernandez-Moreno, C., Montes-González, M., Tsiakos, V., Tsimiklis, G., Ricci, P. C., Mourmouri, R., Hand, T., Yakoumis, I., Olona Allué, J., García, B., Soesoo, A., García-Nieto, J., and Villa, L.: DEXPLORE: Recognizing European potential for hosting deep land primary CRM by combining new mineral models and advanced exploration and visualization techniques, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16884, https://doi.org/10.5194/egusphere-egu25-16884, 2025.
The global transition towards clean energy, electrification of transport, and sustainable development relies heavily on strategic and critical raw materials. In Europe, increasing self-sufficiency in raw material production has become crucial to securing the industrial foundation for the green transition. Eastern and Northern Finland have intensified collaboration among regional, national, and international actors to promote sustainable raw material use. At the regional level, Mining Hubs spearhead the development of the mineral industry, while Finland’s new mineral strategy is focusing on advancing the mineral and battery cluster, fostering a circular economy, and enabling clean and digital transitions. At the European level, the Critical Raw Materials Act seeks to ensure a secure, diversified, and sustainable supply chain while strengthening the EU's strategic autonomy.
In this multi-level framework, research and innovation (R&I) and training organizations play a pivotal role in fostering cooperation. Key institutions in Eastern and Northern Finland, including the Geological Survey of Finland, the University of Oulu, and Kajaani University of Applied Sciences, have united under the project “Development of the mining sector in Lapland, Northern Ostrobothnia, and Kainuu”. A two-year project, launched in September 2024, will promote competence development, R&I innovation, and corporate engagement to strengthen the regional mining sector and its contributions to sustainable development. To achieve the project's objectives, various workshops will be held, and participation in conferences and events at both national and international levels has been and will be undertaken to develop networks and cooperation. Activities will include, among others, organizing a Super Cluster event to bring together actors and projects from mining sector, alongside the OECD Mining Regions and Cities event in June 2025 in Rovaniemi, Finland.
The project has been part-funded by the European Union Just Transition Fund (JTF) in collaboration with the participating organizations. Total budget is approximately 517 000€ and implementation period from September 2024 to August 2026.
How to cite: Pihlaja, J., Kupila, J., Kaija, J., and Panttila, H.: Enhancing Sustainable Raw Material Use: A Collaborative Approach to Developing the Mineral Sector in Eastern and Northern Finland, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12572, https://doi.org/10.5194/egusphere-egu25-12572, 2025.
The Euorpean Union's Horizon program has recently funded the SEMACRET project for the sustainable exploration of critical raw materials. This is of particular importance as the EU seeks to increase its energy and mineral self-sufficiency and decrease its dependence on an external and potentially volitile supply chain. Among the technical challenges of novel resource identification and development, there are also many social aspects of exploration that must be understood and appreciated if the social license to explore is to be gained and resource exploration projects are to move forward. Understanding stakeholder perspectives, concerns, priorities, and values is crucial to developing policies and programs that will result in the accomplishment of these goals. That is why SEMACRET has a working package dedicated to exploring these facets of resource development within member states, local communities, and in social media. In particular, attitudes expressed on social media can be difficult to understand due to the volume of information, the ambiguous status of users as stakeholders, and the semi-anonymous nature of social media interactions. To address these challenges, researchers from SEMACRET's social science working package have worked to develop a machine learning application that uses natural language processing techniques to identify, differentiate, and understand perspectives on local mineral exploration expressed on social media. This presentation explains the methodology (latent Dirichlet allocation) and shows results from the four EU member states (Poland, Portugal, Czech Republic and Finland) that are the focus of SEMACRET's exploration research.
How to cite: Bahr, K.: Social Media Attitudes about Mining for the Green Transition in Europe Using Machine Learning Techniques, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18372, https://doi.org/10.5194/egusphere-egu25-18372, 2025.
Acid Mine Drainage (AMD) poses significant environmental challenges, especially in mining-disturbed areas where sulfide-rich rocks oxidize, releasing acidic water with high concentrations of metals and sulfates. This issue underscores the urgent need for innovative and sustainable approaches to monitor and mitigate its effects on water quality and ecosystems.
To address these challenges, we integrated drone-derived multispectral data with machine learning (ML) techniques to predict key AMD indicators, including iron concentration, pH, and sulfate content. This approach enables efficient, high-resolution environmental monitoring, offering a scalable alternative to traditional resource-intensive methods. Our study, conducted in the Outokumpu mining area of Finland, demonstrates the potential of combining advanced technologies with strategic environmental management.
Given the limited availability of field-measured water quality samples (10 samples from three AMD-affected lakes and one non-AMD lake), we employed a novel data augmentation strategy. This included a window-based spatial data expansion method and the Synthetic Minority Oversampling Technique (SMOTE), significantly enhancing dataset variability and model robustness. These innovations align with the EU’s vision of leveraging cutting-edge technology for environmental resilience and sustainability.
Our findings highlight how integrating drone technology, ML, and data augmentation fosters a sustainable and efficient monitoring framework for AMD-affected regions. This approach aligns with the broader goals of the European raw material value chain, contributing to environmentally responsible resource management and innovation. By promoting cross-sector collaboration and showcasing the applicability of advanced monitoring techniques, our work supports the EU’s strategic objectives for a circular economy and sustainable development.
Acknowledgments: This work is part of the Secure and Sustainable Supply of Raw Material for EU
Industry (S34I) project, n.101091616, funded by European Health and Digital Executive Agency
(HADEA).
How to cite: Farahnakian, F. and Luodes, N.: Predicting Acid Mine Drainage Indicators Using Drone Data andMachine Learning Techniques, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15740, https://doi.org/10.5194/egusphere-egu25-15740, 2025.
The transition to a circular economy (CE) signifies a profound shift in the manner by which global environmental challenges are addressed. Rather than adhering to the conventional linear model characterized by "take, make, dispose," the CE frameworks prioritize resource efficiency, waste reduction, and regenerative processes, thereby requiring systemic transformations across value chains and production systems. Although CE frameworks present substantial opportunities for advancing sustainable development, their implementation is often impeded by various constraints, including institutional inertia, fragmented value chains, and inadequate collaboration among various stakeholders.
This study examines the critical role of stakeholder engagement in surmounting these challenges. Stakeholders—including policymakers, industry leaders, consumers, and non-governmental organizations—are essential for aligning diverse interests and promoting collaborative strategies. Employing a mixed-methods design that integrates a systematic review of existing CE literature with semi-structured interviews of both internal and external stakeholders, the research identifies pivotal drivers for CE adoption, such as regulatory incentives, heightened consumer demand for sustainable products, and technological innovations.
Building on the study’s findings, an accessible stakeholder engagement framework was developed to facilitate collaboration and communication across interdisciplinary and cross-cultural teams. This framework comprises three primary modules: stakeholder identification, collaboration strategies, and performance evaluation. It facilitates the systematic mapping of stakeholder roles, offers practical strategies for fostering partnerships, and introduces explicit metrics to assess environmental, social, and economic outcomes. Preliminary assessments suggest that this effectively addresses knowledge gaps and reinforces stakeholder engagement across diverse industries and regions.
By recognizing the multifaceted nature of the circular economy (CE) and emphasizing inclusivity, this study provides a comprehensive and pragmatic perspective on CE implementation. Its findings offer actionable guidance for organizations endeavouring to embed CE principles within their operational practices, thereby enhancing international cooperation and furthering sustainable development on a global scale.
How to cite: Chou, Y.-Y., Tung, C.-P., and Chiou, C.-R.: Designing a Tool for Identifying and Integrating Stakeholders in the Circular Economy, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11174, https://doi.org/10.5194/egusphere-egu25-11174, 2025.
This paper revisits the challenges and opportunities artisanal and small-scale mining (ASM) may pose for an evolving supply-web for mineral raw materials seen as critical for the EU. Artisanal and small-scale mining operations are often associated with poor operational health & safety (OHS), lasting environmental impacts, and poor governance, if not criminality. ASM is also characterised by a high degree of externalisation of environmental and social costs and risks due to its largely opportunistic nature. To the contrary, one of the overarching policy-goals of the EU is to ensure a fair, responsible, sustainable and sustained supply of critical raw materials. A wide variety of minerals have attained economic importance only in recent years, but are not found in economic quantities in Europe. The globally increasing demand for them means that not only precious metal, diamonds and gem-stones are of interest to ASM anymore, but also the less rich fringes of occurrences mined by large-scale mining (LSM) companies. Thus, we can expect to see more ASM mined critical raw materials in the EU supply-webs.
In order to not leave such mine products to less scrupulous competitors on the market, EU downstream actors and policy-makers have to consider how to align ASM with our environmental, social and governance (ESG) expectations while recognising the motivations of people for engaging in ASM activities. An extensive review of the literature on ASM in Africa in particular and of relevant aid and donor programmes has been undertaken to better understand motivations, constraints and ‘business models’ used with a view to reduce their degree of externalisation of costs and risks.
Key findings include: a) Formalisation of ASM should be seen as an end goal rather than a starting point, b) Acknowledging that ASM is a subsistence activity that does not fit into the business development philosophy of traditional money lenders and donor agencies, c) Sustainable ASM business models require real and sustained economic incentives aligned with ESG improvements, an d) Re-thinking of risk assessment and management by traditional money-lenders and training of ASM to better understand their concerns and constraints, as lack of funding is a major constraint.
Three ‘business models’ seem to be most promising strategies to integrate ASM activities into the EU value-webs while maintaining our ESG expectations: a) Fostering symbioses between LSM and ASM with a view to constructive collaboration, b) Fostering the association of ASM operators to increase collective bargaining power and collective improvement, and c) Building up of mineral raw materials clusters that covers more elements of the value-webs and associated economic activities, including the construction of supporting infrastructure.
How to cite: Falck, E., Correia, V., Komac, M., and Awases, Z.: Artisanal and Small-Scale Mining (ASM) in Africa and the Supply of Critical Raw Materials CRM to European Markets, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19058, https://doi.org/10.5194/egusphere-egu25-19058, 2025.
