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Interlaboratory validation of thirteen qPCR methods to quantify adulterants in culinary spices and herbs
No full textCulinary spices and herbs are vulnerable to fraudulent practices adulterating or substituting their authentic composition. Recently, we conducted in-house validation of thirty real-time quantitative polymerase chain reaction (qPCR) methods aiming at detecting and quantifying the top five adulterants of six commonly consumed spices and herbs: paprika/chilli, turmeric, saffron, cumin, oregano and black pepper. The thirteen qPCR methods meeting all the in-house validation criteria have been tested in an interlaboratory trial including fifteen European laboratories for each method. For each method the participants received DNA templates of binary mixtures for five standard samples together with five test samples of unknown adulterant concentration. Interlaboratory validation parameters included repeatability, reproducibility and trueness. Measurement uncertainties, limit of detection and limit of quantification were also determined. After data examination and outlier removal, relative repeatability standard deviation ranged from 4 % to 25 %, relative reproducibility standard deviation ranged from 6 % to 25 % and trueness bias ranged from -11 % to 27 %. The thirteen qPCR methods are therefore fully validated and may be included in international standards for deployment in official control laboratories.JRC.F.4 - Food Integrit
Transition to Electric Vehicles
No full textThe European Union (EU) automotive industry is facing challenges as Chinese electric vehicles (EVs) are increasingly gaining market share due to lower prices and perceived higher quality. In the last decade, the industry's reliance on foreign components has increased slightly (from 8% to 11%), but this modest increase masks the heterogeneity of EV and internal combustion engine (ICE) manufacturing. The distinction between EVs and ICEs is particularly important for inputs where the EU lacks a comparative advantage, such as batteries. Using a new methodology developed under the SMILE EU project, we disaggregate the automotive sector to separately assess technological differences and foreign dependencies for ICEs, EVs, and vehicle parts. Our analysis reveals that EVs have a significantly higher reliance on foreign components than ICEs (29% vs 13%, respectively). We find that this disparity is largely attributed to global value chain (GVC) strategies, rather than a domestic technological shortfall. These findings underscore the need for policy initiatives at an EU-wide level aimed at reducing outsourcing through GVCs and boosting European competitiveness in EV manufacturing.JRC.B.6 - Industrial strategy, skills and technology transfe
The Futures Balance Tool: Supporting Forward-Looking Policy Analysis
No full textThe Futures Balance Tool introduces an AI-based, user-friendly solution that supports policymakers’ decision-making across the Impact Assessment (IA) process. It is developed by the United Nations Beyond Lab in collaboration with JRC Decision Analysis Lab and EU Policy Lab.JRC.S.3 - Science for Modelling, Monitoring and Evaluatio
Fiscal drag in theory and in practice: A European perspective
No full textThis paper presents a comprehensive characterization of “fiscal drag”—the increase in tax revenue that occurs when nominal tax bases grow but nominal parameters of progressive tax legislation are not updated accordingly—across 21 European countries using a microsimulation approach. First, we estimate tax-to-base elasticities, showing that the progressivity built in each country’s personal income tax system induces elasticities around 1.7–2 for many countries, indicating a potential for large fiscal drag effects. We unpack these elasticities to show stark heterogeneity in their underlying mechanisms (tax brackets or tax deductions and credits), across income sources (labor, capital, self-employment, public benefits), and across the individual income distribution. Second, we extend the analysis beyond these elasticities to study fiscal drag in practice between 2019 and 2023, incorporating observed income growth and legislative changes. We quantify the actual impact of fiscal drag and the extent to which government policies have offset it, either through indexation or other reforms. Our results provide new insights into the fiscal and distributional effects of fiscal drag in Europe, as well as useful statistics for modeling public finances.JRC.B.2 - Fiscal Policy Analysi
Analysing the Effects of Inflation on the SME Definition
No full textIn recent years, events such as the COVID-19 pandemic and the ongoing conflict in Ukraine have disrupted global markets and supply chains, causing price fluctuations across multiple sectors. This situation raises concerns about the relevance of the current set of financial thresholds that define SMEs. The analysis considers a various methods and data sources to estimate the impact of inflation on the number of enterprises excluded from the SME category. Overall, the affected SME population is relatively small. At the EU level, approximately 0.06% of enterprises were affected in 2023. Despite this small percentage, there is a noticeable trend across nearly all Member States, with the proportion increasing over time.JRC.S.3 - Science for Modelling, Monitoring and Evaluatio
Job quality and the platformisation of regular work: A cross-country analysis of digital monitoring and algorithmic management in the EU
No full textDigitalisation and the increasing use of digital platforms for the coordination of work processes in an algorithmic way can have deep implications for the world of work. While digital monitoring and algorithmic management have been a paradigmatic feature of work in the gig economy, they are increasingly permeating the regular economy across sectors and occupations, a phenomenon that can be termed the 'platformisation' of regular work. Besides potential efficiency gains, these new data-driven managerial and control structures can have implications for workers' well-being. The AIM-WORK survey, conducted by the European Commission’s Joint Research Centre in 2024-2025 in all EU Member States, is currently the most comprehensive representative survey on the issue. This paper uses this novel evidence to examine the implications of the platformisation of work for job quality across EU countries. Our findings show that some forms of platformisation are associated with reduced worker autonomy and work intensification. In contrast to intellectual jobs, platformised workers performing manual routine tasks are more commonly routinised and monitored. These negative associations are almost exclusively concentrated in Central-Eastern Member States, with Western EU countries generally showing neutral job quality outcomes. We argue that this stark contrast suggests that labour market institutions are key in preventing detrimental effects of platformisation of regular work on European labour markets.JRC.B.6 - Industrial strategy, skills and technology transfe
Towards a Unified Framework for Measuring Sustainable and Inclusive Wellbeing in the EU
No full textThere is a growing recognition that relying on traditional economic indicators such as GDP and its growth, is inadequate for tackling the current and emerging global societal challenges. Beyond better measurement, there is a need for policy objectives that can address these fundamental issues in a different way. A shift is underway towards wellbeing as an explicit policy objective. To enable the existing multitude of beyond GDP measurement frameworks to support such a shift, the notion of sustainable and inclusive wellbeing is emerging as a new consensus term and approach. In this context, this paper presents the main ingredients of the European Commission’s related initiative, which aims to develop sustainable and inclusive wellbeing metrics, to progressively complement GDP with wellbeing indicators in EU policymaking. Our conceptual and measurement framework builds on the multidimensional approach of the first Stiglitz report and the OECD wellbeing framework, integrating the key dimensions of current and future wellbeing, inclusion, and sustainability. To make it useful for policies and align with EU political priorities and processes, we made three important contributions. (1) We implemented several refinements in the OECD approach: most importantly, we strengthened the role of resilience and redefined the treatment of nature. Rather than classifying this latter solely as one of the four capitals, we assigned it a transversal role. (2) We designed the conceptual structure in a way that it enables us to ‘catalogue’ existing EU frameworks, working towards their streamlining, identifying gaps in their coverage and arriving at a lean yet comprehensive indicator set. (3) We followed a consensus-based expert selection method for the indicators, ensuring that the eventual list is comprehensive, aligned with political priorities, and balanced in terms of size and scope. An important application of our framework is to introduce ‘directionality’ into the competitiveness discourse: to use resources efficiently in order to deliver wellbeing to people in a sustainable and inclusive way. If a country allocates a greater share of its resources to dimensions of societal wellbeing not reflected in GDP than another one, then a purely GDP-based comparison may provide a misleading picture. It is therefore essential to systematically identify and appropriately value these dimensions, enabling countries to make informed choices and to address current challenges more effectively.JRC.B.1 - Economic and Financial Resilienc
Structural and chemical insights on the incorporation of americium into zircaloy-derived monoclinic zirconia
No full textMonoclinic zirconia (m-ZrO2) forms on the internal surface of nuclear fuel Zircaloy cladding, acting as a critical barrier against radionuclide release at the fuel-cladding interface. However, the incorporation of minor actinide elements like americium in m-ZrO2 and resultant structural chemistry remains poorly understood. Using a combination of diffraction and high-resolution X-ray spectroscopic techniques, we have examined m-ZrO2 with 5mol%Am doping. We show Am enters m-ZrO2 tetravalently, where its solubility is approximately 1.0 mol%, m-(Am4+
0.011(7)Zr4+0.989(7))O2, attributed to the large Am4+ cation,where excess Am, that is predominantly trivalent, adopts a C-type (Am4+/3+1-xZr4+x)2O3+x phase in space group Ia-3. The known reversible high temperature phase transformation of m-ZrO2 to tetragonal is further shown to be reduced from 1150 oC to 1050 oC via Am4+ incorporation. The investigation provides critical insight into the chemical reactivity and speciation of minor actinide elements with nuclear fuel cladding related m-ZrO2.JRC.G.5 - Nuclear Science and Innovation for Energy and Healt
SuperDove radiometric data assessment in coastal and inland waters
No full textThe use of high-resolution data in aquatic applications increased significantly in the last decade with the launch of decametre-scale optical sensors. More recently, commercial very-high resolution (VHR) sensors, offering finer spatial and temporal resolutions, have shown the potential of complementing data from high-resolution missions. Planet SuperDove (SD), with a band-setting similar to the Copernicus Sentinel-2 MultiSpectral Instrument (S2-MSI), a 3-m spatial resolution and quasi-daily revisiting time, show the potential for widening water monitoring applications to smaller water basins, and finer-scale phenomena. However, the uncertainties in SD products need to be quantified, to assess their fitness-for-purpose for these applications. This work aims to provide uncertainty estimates for SD-derived aquatic remote sensing reflectance (RRS) in different water types, benefitting from the radiometric measurements of the AERONET-OC network. RRS was derived from both Surface Reflectance (SR) products, distributed by Planet, or from data processed with ACOLITE. The comparability between SD and S2-MSI products was also assessed comparing RRS and Rayleigh-corrected reflectance (RRC) from S2-MSI and SD. The results indicate generally low performance across all bands for both SD RRS products, except in the most turbid waters, and highlight the lack of a publicly available robust atmospheric correction processor for SD data for most optical water types. The comparison to S2-MSI shows promising results only when comparing RRC values, but differences still suggest issues associated with calibration and radiometry of the SD sensors. The results also highlight the need for a harmonization strategy to ensure consistent integration of these datasets within multi-source monitoring systems.JRC.D.2 - Ocean and Wate
Evaluating visible near-infrared spectroscopy in context of a repeated sampling survey across the European Union
No full textVisible near-infrared spectroscopy (VNIRS) has potential to fulfill the increasing need for soil organic carbon (SOC) data to support more cost-effective monitoring. However, VNIRS predictions for large-scale repeated surveys have not yet been systematically compared to the laboratory measurement error from dry-combustion. This study assessed 15,134 SOC pan-European predictions by VNIRS for a second campaign, LUCAS 2015, based on the LUCAS 2009 survey. Models performed well considering the mean prediction metrics (e.g. RMSE: 26–27 g C kg−1, CCC: 0.94) with marginal differences between approaches. However, relative differences between model approaches performance changed when assessed based on the confidence interval coverage probability (CICP). The CICP assesses whether VNIRS predictions lie within the confidence interval of measured SOC given the laboratory error. Furthermore, we quantified with a loss function how the cost-effectiveness of VNIRS depends on both the laboratory measurement error and the tolerated error in SOC predictions. Depending on the confidence interval considered, the best-case scenario for VNIRS would equate to estimated cost savings between 14–31 k (€) by replacing dry-combustion in the second campaign of a repeated survey on SOC. Overall, prior information from the first survey led to modest to large improvements of VNIRS SOC predictions, depending on the metric considered. Our results showed how mean prediction metrics, the CICP and the loss function can lead to variable interpretations of model performance and ideally should not be evaluated in isolation. Our results further indicated that future research is warranted on calibration models that are interpretable and allow for adequate uncertainty quantification.JRC.D.3 - Sustainable Supply Chains and Bioeconom