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GFC2020: a global map of forest land use for year 2020 to support the EU Deforestation Regulation
No full textRemote sensing-based observations are used to map tree cover extent, estimate canopy height, detect disturbances, and classify land cover and land use. However, comprehensive global information on forest cover, capturing both physical characteristics and land use components as defined by the United Nations Food and Agriculture Organization (FAO), remains limited. Here, we present a harmonized and globally consistent map of forest presence or absence at 10 m spatial resolution for the year 2020, hereafter referred to as GFC2020. Our approach combines multiple spatial datasets, primarily derived from Earth observation (EO), to harness their complementary strengths within a transparent, flexible, and open science framework. GFC2020 maps 4562 million hectares (Mha) of forests globally, which is 9.5 % more than the estimate from latest FAO Global Forest Resources Assessment (FRA) for 2020. GFC2020 forest area does not include 578 Mha of tree cover (11 % of the global tree cover area) because these areas do not meet the height threshold or occur on agricultural or urban land. Conversely, around 0.6 % (∼ 25 Mha) of the area classified as forest in GFC2020 is unstocked, due to forest management practices or natural disturbances such as fire. Based on the reinterpretation of a previously collected reference set of 21 752 sample units, GFC2020 achieves an overall accuracy of 91 %, with a commission error of 18 % and an omission error of 8 % for forest. Improvements in EO products, such as better detection of trees in dry and open landscapes, distinguishing natural from human drivers of forest disturbance, mapping tree crops at high spatial resolution or identifying agroforestry systems, will contribute to enhancing future versions of GFC2020. The shift from tree cover to forest cover mapping is not only essential for ecological and climate-related applications but also provides new opportunities to support policy needs. GFC2020 is one of many tools to inform the deforestation risk assessments under supply chain oriented regulations such as the European Union's Deforestation Regulation (EUDR). Even though this map follows the EUDR's definition of forest, it is a non-exclusive, non-mandatory, and not legally binding source. The data availability is as follows: GFC2020 (Bourgoin et al., 2024a, http://data.europa.eu/89h/e554d6fb-6340-45d5-9309-332337e5bc26) and the validation dataset (Colditz et al., 2025a, http://data.europa.eu/89h/8fbace34-a2fe-47b9-ad82-3e9226b7a9a6).JRC.D.1 - Land and Climat
Chemical activity-based carbon-deposition risk maps for solid oxide fuel cell systems with off-gas recirculation
No full textHere, we present a methodology for the generalized quantification of the carbon (C)-formation risk in hydrocarbon mixtures based on the normalized chemical activity. An open-source computational thermodynamics tool is coupled to a solid oxide fuel cell (SOFC) stack model to apply and validate this approach with literature data based on methane-fueled SOFC systems with anode off-gas recirculation. Two- and three-dimensional C-formation risk maps valid for all C-H-O mixtures are proposed for a practical, accurate, and meaningful assessment of the trade-off between C-deposition risk and SOFC performance. Compared to conventional risk evaluation methods such as steam-to-carbon ratio (SCR), oxygen-to-carbon ratio (OCR), or C-H-O ternary-phase diagrams, this approach allows a system-agnostic evaluation of different designs operated at varying conditions at a constant C-formation risk margin. The generalized formulation allows integration into process optimization workflows to obtain high-performance system designs with extended stack operating windows.JRC.G.4 - Reactor Safety and Component
Doing more with less: Cutting food loss and waste in the EU and its impact on food security
No full textIn September 2025, the European Parliament and Council signed the law of the Revision of the EU waste framework directive, which includes also reductions for food loss and waste (FLW). This comes at a time of concern over the EU's strategic autonomy for its agrifood sector. Taking a cradle-to-grave approach, this paper combines official FLW statistics with recent advances in simulation modelling to quantify the impacts of two FLW cuts scenarios on EU food availability, affordability, and stability. Compared with a business-as-usual baseline, average EU household per capita food budget savings and self-sufficiency of up to €192 and 0.82\%, respectively, are observed, accompanied by falling average EU food production of up to 2\%. With the inclusion of FLW behavioural market adjustment costs (taxes), average EU food producer price falls of up to 1\% are lower than reported in previous studies, whilst in a handful of member states, consumer food prices rise marginally. This hitherto unforeseen outcome is a signal for anticipating and ensuring adequately tailored social protection schemes for the most vulnerable.JRC.D.4 - Economics of Food System
Mapping Montenegro’s potential in the context of Smart Specialisation
Full text linkThe Smart Specialisation Strategy (S3) is a place-based economic agenda that Montenegro, as the first non-EU country to adopt a strategy based on this framework, is now updating for the 2026–2031 period. This new iteration elevates S3 to a national ‘umbrella’ strategy, utilizing comprehensive quantitative and qualitative mapping to identify the country’s economic, scientific, and innovative strengths. The resulting report serves as an analytical foundation for the upcoming Entrepreneurial Discovery Process (EDP), where stakeholders collaborate to finalize Montenegro’s strategic priority domains. The analysis identifies five preliminary priority areas for Montenegro’s 2026–2031 S3 strategy: Construction, Energy and Sustainable Environment, Sustainable Agriculture and Food, Digital Innovation and Transformation, and Innovative and Sustainable Tourism. While sectors like Construction and Energy are highlighted for their roles in infrastructure and green transitions, the ICT and Tourism sectors stand out as high-growth pillars, contributing significantly to GDP and export potential.JRC.B.3 - Territorial Developmen
Integrated governance in data ecosystems: A conceptual framework consolidating collaborative and data governance
No full textThe potential benefits deriving from inter-organizational data sharing have increased over time, leading to an intensified interest in data ecosystems. The governance of these endeavors depends on both collaborative and data governance dimensions. However, previous research has often treated these dimensions separately, creating silos that hinder the capacity to deliver value considering their socio-technical nature. Addressing this gap, this study investigates the intertwined relationship between these two dimensions within data ecosystems. It does so by questioning which existing and most relevant relationships exist between them, as well as the nature of these relationships. To this end, we adopt a multiple case study approach, analyzing five data ecosystems. The research led to the development of a conceptual framework for Integrated Governance, highlighting the need for a holistic socio-technical approach that addresses collaborative and data governance dimensions as intertwined. The framework unveils 24 core relationships between these dimensions in data ecosystems and provides insights on the nature of the relationships, distinguishing among causal, explanatory, concurrent, chronological, and overlapping ones. This work introduces a new perspective in the academic discourse on data sharing providing actionable insights for practitioners and enabling them to design and manage data ecosystems more effectively.JRC.T.4 - Digital and Data Sovereignt
Transforming Cities
Full text linkThis report examines barriers and enablers shaping the role of cities in the EU green transition pathway. It presents the outcomes of an international expert workshop organised by the Joint Research Centre (JRC) of the European Commission in collaboration with Politecnico di Torino, Italy. The workshop is part of a series of JRC exploratory research activities applying innovative methods to co-create shared visions for system transitions across the EU food, urban, and green innovation domains.
During the workshop, experts from academia, architectural and landscape firms, policymaking institutions, major urban networks, living labs, the European Committee of the Regions, and non-governmental organisations identified enablers and local good practices to strengthen the implementation of selected European Green Deal targets at the urban level and to address structural challenges hampering transformative change.
Seven enabling conditions emerged as critical for advancing urban green transitions: strengthened and systematic community and citizen engagement; upgrading urban infrastructure and uptake of nature-based solutions; innovative governance and policymaking; sustainability education and skills; coupled energy and digital transitions; adequate financial resources and public-private cooperation; and transparent communication and information sharing.
A central element of the workshop was ShapeEUrbe, a science-based board game specifically designed for this event. Through the game, participants explored policy gaps, good practices, barriers and enablers for achieving the European Green Deal targets and envisioning urban futures towards the EU’s 2050 climate neutrality ambition.JRC.D.3 - Sustainable Supply Chains and Bioeconom
Escaping the Inactivity Trap? The Work Incentive of the Spanish Minimum Income
No full textThe Spanish Minimum Income scheme, introduced in 2020, offers beneficiaries a unique national guaranteed income as a last-resort benefit. However, the scheme’s design featured a lack of work incentives for low earners, potentially leading to inactivity traps. To address this flaw the Spanish government introduced an earnings disregard in 2022, enabling beneficiaries to keep all or part of the benefit when their earnings increase up to a certain limit. This paper provides an ex ante assessment of this reform, looking into its expected fiscal, distributional and labour market effects using the tax–benefit microsimulation model EUROMOD, and the behavioural labour supply model EUROLAB. Our results show that the reform has the potential to incentivise work for very low earners, particularly lone parents, mainly by promoting part-time employment. The reform and its subsequent employment effects are also expected to slightly reduce inequality and poverty. While this is a step in the right direction, we discuss some avenues for improvement.JRC.B.2 - Fiscal Policy Analysi
Identification of essential variables for the estimation of energy demand in buildings at European scale
No full textAccurate European scale building energy modelling remains challenging due to fragmented data, yet it is essential for assessing policy scenarios. This study proposes a data-driven methodology to identify a minimal set of essential variables for a reduced-form model capable of accurately predicting energy demand across European buildings. Using Random Forest machine learning applied to two complementary datasets: (1) a cross-country database of building typologies across the Member States of the European Union (EU), and (2) the French Energy Performance Certificate (EPC) database—the analysis identifies five key variables that reduce mean absolute percentage error by 10 percentage points compared to using all 18 original available attributes. These variables are: living floor area, height, construction year, climatic conditions, and building functionality, while construction materials and other architectural features show limited predictive relevance. The study fills a gap in the literature by rigorously establishing essential variables required for EU-scale energy modelling, complementing previous work that either lacks cross-country generalization or focuses on single-country assessments. The main novelty lies in demonstrating that competitive predictive accuracy can be still achieved using standardized, widely available features, challenging the assumption that detailed physical data are required for robust models. This approach prioritizes scalability and cost-effectiveness, enabling wider development across Europe towards the creation of a detailed EU Digital Building Stock Model for energy-related purposes. As key variables can be derived from Earth Observation, cadastral records, and machine-learning-based inference, the findings support harmonised, building-level energy estimation and facilitate applications such as identifying worst-performing buildings, prioritizing renovation actions, and informing decarbonization strategies.JRC.C.2 - Energy Efficiency and Renewable
Assessing the impact of Energy Efficiency on the EU Energy Consumption in 2010-2023
Full text linkThis report examines the determinants of changes in primary and final energy consumption at EU27 and Member State levels over the period 2010 to 2023 to track and understand the progress towards 2030 energy efficiency targets and beyond. Energy consumption trends are driven by several factors beyond energy efficiency improvements, which can have a profound effect in the aggregate energy use, irrespective of the impact of energy efficiency policies and measures. To understand the latest energy consumption trends in the EU, the Logarithmic-Mean Divisia Index
(LMDI) approach, a widely used Index Decomposition Analysis (IDA) method, was applied to study both aggregated and sectoral energy consumption changes at EU and Member State levels over the examined period and quantify the impact of factors such as economic activity, demographics, productivity, lifestyle and weather changes. The results suggest significant energy efficiency gains from 2010 to 2023, without which the progress achieved towards 2030 EU energy efficiency targets would have been difficult to attain. However, any analysis for the recent years should be considered with caution as they have been significantly influenced by exceptional external factors. In 2020, the COVID-19 pandemic led to a drop in energy consumption, followed by a rebound effect once the restrictions were raised. Starting in 2022, the Russia’s war of aggression against Ukraine (was preceded from and) resulted in an increase in energy prices (especially for gas) with strong interventions by the EU and Member States to limit energy consumption. With the aim to investigate the evolution of the determinant factors of energy consumption, an analysis of the energy consumption projections for selected sectors (i.e., industry, services, agriculture and residential) up to 2050 at the European level has been carried out.JRC.C.2 - Energy Efficiency and Renewable
JRC-IDEES-2023: the Integrated Database of the European Energy System
Full text linkThe Joint Research Centre's Integrated Database of the European Energy System (JRC-IDEES) incorporates in a single database a rich set of information allowing for highly granular analyses of the dynamics of the European energy system, so as to better understand the past and create a robust basis for future policy assessments. JRC-IDEES provides a consistent set of disaggregated energy-economy-emissions data for each Member State of the European Union, covering all sectors of the energy system for the 2000-2023 period. This data complies with Eurostat energy balances while providing a plausible decomposition of energy consumption into specific processes and end uses. In each sector, JRC-IDEES uses a vintage-specific approach to quantify the characteristics of the energy-using equipment in operation, along with the average operation of the equipment stock. It accordingly identifies different drivers and provides insights on their role by sector while accounting for structural differences across countries. JRC-IDEES therefore supports several key applications for energy modelling, research, and policy analysis, such as parameterizing energy models and assessing past and prospective policies.
JRC-IDEES is freely accessible to the general public since 2018 and can be downloaded through the JRC Data Catalogue. This report documents the 2025 release (JRC-IDEES-2023), which incorporates several new data sources and methodological improvements while extending the time coverage of the database until 2023. As such, the report is a revision of the previous JRC-IDEES-2021 technical report and describes key changes where relevant. The report also includes general minor revisions to clarify assumptions and data sources.JRC.C.6 - Economics of Climate Change, Energy and Transpor