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Could bridging science and the arts be the key to better policies?
No full textIn an era marked by increasingly complex global challenges, the need for interdisciplinary collaboration has never been more pressing. This is particularly true at the intersection of science, art, and policy, where different modes of thinking and understanding can drive innovation and reshape societal perspectives. The SciArt project , launched by the Joint Research Centre (JRC) of the European Commission in 2016, stands as a testament to the potential of bridging these traditionally siloed domains. Rooted in the success of a pilot project at the 2015 Milan World Expo, SciArt has evolved into a seminal initiative that fosters deep connections between scientists, artists, and policymakers to address urgent global issues. By focusing on the nexus of art, science, and policy, SciArt not only supports the EU’s evidence-based policymaking but also creates new ways of engaging the public and policy-makers in complex scientific debates, making them both relatable and meaningful.JRC.S.4 - Scientific Development Programme
Citizen-engaged screening of 230 pesticides in the Lake Naivasha catchment, Kenya, using stir bar sorptive extraction and GC-QToF-HRMS
No full textThe presence of pesticides in surface water samples from the Lake Naivasha catchment area in Kenya was investigated using Stir Bar Sorptive Extraction (SBSE) and Gas Chromatograph with Quadruple Time-Of-Flight High Resolution Mass Spectrometry (GC-QToF-HRMS). A total of 56 pesticides were detected, belonging to different classes including fungicides (48.2%), insecticides (17.9%), herbicides (12.5%), and other categories. The most frequently detected pesticides were the fungicides boscalid, fluopyram, hexachlorobenzene, tebuconazole, herbicide metolachlor, and insecticides bromopropylate, chlorpyrifos, diazinon, and the synergist piperonyl butoxide. The site with the highest pesticides detections was adjacent to Lake Naivasha, near a wastewater treatment plant discharge. Toxicological risk assessments revealed that the acute toxic unit threshold for crustaceans (TU = 0.01) was exceeded in several samples, primarily due to the presence of chlorpyrifos and diazinon. Notably, chlorpyrifos, banned for all agricultural purposes in Kenya in 2024, was detected in several samples. These findings highlight the presence of pesticides in Kenyan water bodies, posing potential risks to aquatic ecosystems and underscore a need for stricter regulation, ongoing monitoring, and the adoption of sustainable agricultural practices to minimise the impact of pesticides on the environment.JRC.D.2 - Ocean and Wate
GHG emissions of all world countries
Get PDFThe Emissions Database for Global Atmospheric Research (EDGAR) provides greenhouse gas (GHG) emissions time series for all countries and for all anthropogenic sectors from 1970 until 2024, including emissions and removals from land use and forestry. The report contributes to the Paris Agreement process with an independent quantitative overview of global GHG emissions, based on the IEA-EDGAR CO2, EDGAR CH4, EDGAR N2O and EDGAR F-gases version EDGAR_2025_GHG (2025).JRC.C.5 - Clean Air and Climat
Lehren aus der Corona-Pandemie: Staatliche Beihilfen unterstützten vor allem kleine Unternehmen bei der Krisenbewältigung [Lessons from the Covid-19 pandemic: State aid supported small businesses in withstanding the crisis]
No full textDie Europäische Union überwacht staatliche Beihilfen für Unternehmen streng, reagierte jedoch in Krisenzeiten in der Vergangenheit mit der Einführung eines sogenannten befristeten Rahmens, um die Beihilferegeln vorübergehend zu lockern. Im Zuge der Covid-19-Pandemie wurde ein befristeter Rahmen geschaffen, der umfangreiche staatliche Beihilfen zur Stabilisierung der Wirtschaft ermöglichte. Die vorliegende Studie untersucht die Wirksamkeit dieser Maßnahmen in Spanien und Italien, zwei von der Pandemie besonders betroffenen Ländern. In diesen Ländern wurden die Unternehmen in erheblichem Umfang mit staatlichen Beihilfen unterstützt. Um die Wirkung der Beihilfen zu analysieren, werden Unternehmen, die staatliche Beihilfen erhielten, mit nicht unterstützten Unternehmen verglichen. Die Ergebnisse zeigen, dass die Unterstützung insbesondere Mikro- und Kleinunternehmen half, Umsatzeinbrüche abzufedern und Investitionen förderte. Der Bausektor profitierte dabei in besonderem Maße. Die Studie betont die wichtige Rolle von staatlicher, zeitlich begrenzter Unterstützung für das Überleben und die Entwicklung von kleinen Unternehmen in Krisenzeiten. Vorsicht ist indes geboten, wenn derartige Instrumente im Rahmen des Green Industrial Deals auf große Unternehmen ausgeweitet und nicht nur vorübergehend eingesetzt werden sollten. Dies könnte zu starken Verzerrungen des Wettbewerbs führen.JRC.S.3 - Science for Modelling, Monitoring and Evaluatio
Strengths and Limitations of Word-Based Task Explainability in Vision Language Models: a Case Study on Biological Sex Biases in the Medical Domain
No full textVision-language models (VLMs) can achieve high accuracy in medical applications but can retain demographic biases from training data. While multiple works have identified the presence of these biases in many VLMs, it remains unclear how strong their impact at the inference level is. In this work, we study how well a task-level explainability method based on linear combinations of words can detect multiple types of biases, with a focus on medical image classification. By manipulating the training datasets with demographic and non-demographic biases, we show how the adopted approach can detect explicitly encoded biases but fails with implicitly encoded ones, particularly biological sex. Our results suggest that such a failure likely stems from misalignment between sex-describing features in image versus text modalities. Our findings highlight limitations in the evaluated explainability method for detecting implicit biases in medical VLMs.JRC.F.7 - Digital Healt
Statistical atlas of European agriculture: gridded data from the agricultural census 2020 and the spatial distribution of CAP contextual indicators
No full textInternational organizations have voiced the need to integrate geographical information from agricultural holdings into official statistics to gain a better understanding of the spatial dynamics of the European agricultural sector. This paper presents a set of thematic maps based on the European 2020 agricultural census to explore the major structural differences between regions and countries. To comply with the confidentiality requirements associated with the census data, we applied a multi-resolution gridded approach by varying the resolution of the grid cells as a function of the density, dominance, and quality of individual observations. The datasets contain a mixture of grid resolutions ranging from 1 to 40 km, preserving a hierarchical structure where higher-resolution grid cells are aggregated into lower resolutions until the statistical disclosure requirements are met. The variables presented here correspond to the Contextual Indicators of the Performance Monitoring and Evaluation Framework of the Common Agricultural Policy and are divided into three broad categories: structural components (i.e., agricultural holdings, land use, livestock patterns, and labor input); the demographics of farmers (i.e., age, gender, and skills); and agricultural production methods (i.e., irrigation and organic farming). Our exploratory analysis indicates that high farm density occurs in plains, lowlands, and fertile soil in valleys; that high shares of organic farming tend to be concentrated in certain areas with high proportions of grassland; and that agricultural holdings managed by young farmers are located in a belt stretching from France through to Switzerland, Austria, Czechia, Slovakia, and Poland. These novel datasets are highly versatile, not only allowing policies to evaluate funding schemes at more local levels, but also offering researchers new opportunities to draw causal spatial inference from the multi-resolution gridded data. The dataset is the first attempt to create an unprecedented harmonized view of European agriculture with high spatial resolution and is available at https://doi.org/10.5281/zenodo.14852709 (Eurostat, 2025).JRC.D.5 - Food Securit
Continental Scale Soil Monitoring: A Proposed Multi-Scale Framing of Soil Quality
No full textGlobally, soils are subjected to various management practices and stressors which can lead to degradation. This makes their protection essential for sustaining many functions and services as well as maintaining the overall life support system of Earth. National monitoring programmes are increasingly implemented to evaluate the state and trend of soils, a move which has been advocated by the Mission Soil in Europe. In soil science, frameworks have been established to interpret and communicate soil monitoring results, concentrating on the concept of quality, a term which can be interpreted in many ways. This paper explores the multifaceted meaning of soil quality, addressing its implications for future soil health assessments. It achieves this by focusing on the context of the Mission Soil. Soil health is a holistic concept embracing emergence, complexity and highlighting long-term vitality and resilience. In contrast, soil quality is often viewed through the lens of its capacity to meet specific human needs and functions, typically in a shorter timeframe. The concept of quality is assessed through indicators where the choice of framework significantly influences selection and interpretation. However, selecting appropriate soil indicators across Europe is challenging due to diverse climate, topography, geology and soil types, resulting in varied soil processes. Therefore, establishing clear principles and criteria for soil indicator selection is essential. Our paper identifies four distinct frameworks for soil quality assessment: ‘Fitness for Purpose’, ‘Free from Degradation’, ‘External Benchmarking’ and ‘Value Assessment’, with each possessing a unique role and application. Notably, the ‘Free from Degradation’ framework is emphasised for its alignment with soil protection efforts and its relevance to soil threats. This makes it particularly suitable for pan-European assessments conducted by the European Union Soil Observatory (EUSO).JRC.D.3 - Land Resources and Supply Chain Assessment
Pan-European monitoring of local forest fragmentation
Get PDFThis document describes the design process, definitions, and algorithmic implementation for a panEuropean assessment of forest fragmentation. This study is a preceding presentation of the indicator 4.7 in the State of Europe’s Forests 2025 report, published by FOREST EUROPE. Forest cover is derived from the Copernicus High Resolution Forest Type dataset for the year 2021 at a spatial resolution of 10 meters. Forest fragmentation is assessed within a local neighbourhood of 500 hectare. Spatially explicit maps and statistical summaries are derived for 44 reporting units: the entire map coverage, European regions, the EU27, and the EEA38 countries.JRC.D.1 - Forests and Bio-Econom
Combining MFA and LCA models to unveil the EU plastic value chain impacts
No full textPlastics value chains are complex, due to different feedstocks, sectors of applications and variety of end-use products. Material Flow Analysis and Life Cycle Assessment can be integrated to map the life cycle impacts associated with material flows along the plastic value chain. In this study, the environmental impacts of the entire European Union plastic value chain were evaluated for 9 sectors, from production to end-of-life with polymers-specific granular details and addressing 16 environmental impact categories. In the baseline scenario, Climate Change impacts due to the EU plastic value chains amounted to 279 Mt CO2 eq., with plastic production contributing to 124 Mt CO2 eq. Sensitivity scenarios explored variations in flows and production volumes and implementation of cleaner energy mixes along the plastic life cycle, decreasing Climate Change up to 28 %. Results proved how combined improvements along the value chain or plastic production reductions are necessary to enable significant impacts’ savings.JRC.D.3 - Sustainable Supply Chains and Bioeconom
Non-linearity correction for variable signal analysis in mass spectrometry using discrete ion counters
No full textThe response of a discrete ion counter is not perfectly linear due to count loss caused by dead time and pulse pileup. As a result, the output rate of the counter does not scale linearly with the input rate of ions reaching the detector. The value of a stable input rate can be determined from the measured output rate by inverting the throughput formula of the ion counter. However, when the input rate varies during the measurement, a mismatch between the average input rate and the average output rate becomes apparent. The resulting bias can be particularly significant when measuring transient signals. A correction procedure is proposed to calculate a better estimate of the average input rate from the observed mean and variance of the output rate. Implementation of this refined throughput formula is recommended to improve accuracy of mass spectrometry utilising discrete ion counters.JRC.G.6 - Nuclear Data and Measurement Standard