38796 research outputs found
Sort by
Global near real-time 500 m 10-day FPAR dataset from MODIS and VIIRS for operational agricultural monitoring and crop yield forecasting
No full textClimate change and extreme weather events pose challenges to food security, emphasizing the need for reliable and timely monitoring of crop and rangeland conditions. For this purpose, long-term consistent Earth Observation datasets on vegetation conditions are typically used in early warning and crop yield forecast systems. However, the near-real-time (NRT) production of high quality datasets and the need to guarantee long-term records present various challenges. To address these, we present a NRT global dataset of Fraction of Photosynthetically Active Radiation (FPAR) at 500 m resolution, optimized for agricultural applications. Our dataset combines MODIS-FPAR (Collection 6.1) and VIIRS-FPAR (Collection 2) data, ensuring continuity from 2000 to well beyond 2030. We applied a robust filtering approach based on the Whittaker smoother to produce reliable FPAR estimates in NRT, accounting for sparse and irregular spaced observations due to cloud cover. The dataset is composed of two 10 d filtered timeseries: (1) MODIS-FPAR for 2000 to 2023, being the reference dataset, and (2) intercalibrated VIIRS-FPAR for 2018 onward. While several methods can effectively smooth and gap-fill FPAR data (i.e., using observations before and after the estimation date), our method is designed for optimal filtering in NRT (i.e., using only prior observations). Our approach yields six successive estimates of the same FPAR data point with increasing quality: an inital estimate immediately after the 10 d reference period, four subsequent estimates every 10 d using new observations, and a final consolidated estimate 90 d later. The implemented filtering ingests the available FPAR observations and their original quality assessment (QA) layers. To avoid unrealistic extrapolation when observations are sparse, we impose constraints, season and location specific, to FPAR estimates. We then intercalibrated the VIIRS-FPAR with the MODIS-FPAR filtered timeseries, using a mean difference correction approach, to ensure consistency between both series. This paper describes the filtering and intercalibration method used, the quality assessment of resulting timeseries, and details the obtained products and the corresponding QA layers. The NRT FPAR dataset is publicly available through the Joint Research Centre Data Catalogue, https://doi.org/10.2905/1aac79d8-0d68-4f1c-a40f-b6e362264e50JRC.D.5 - Food Securit
The influence of homogeneity on the stability assessment of reference materials
No full textAccurate estimation of the uncertainty of stability is crucial for certified reference materials (CRMs), as it forms a component of the overall uncertainty budget. In case of between-unit heterogeneity, results obtained on the same unit of a CRM are not independent which leads to a bias in the estimated uncertainty of stability when used ordinary least squares. This bias depends on the ratio of between-unit heterogeneity to method repeatability and the number of replicate analyses performed per unit and can reach nearly 50 % for as few as three replicates per unit. A study on actual certified values shows that this bias can influence the certified values. The study shows that employing linear mixed-effects models (LME) with restricted maximum likelihood (REML) for parameter estimation provides consistent estimate of uncertainty of stability, even in the presence of significant between-unit heterogeneity. Simpler, alternative approaches for specific scenarios, such as well-balanced datasets are also provided.JRC.G.II.6 - Nuclear Data and Measurement Standard
European Market Surveillance of Pollutant Emissions from Light- and Heavy-Duty Vehicles
Get PDFThis report presents the results of the work conducted by the Joint Research Centre (JRC) as the European Commission contribution to market surveillance on pollutant emissions of Light- and Heavy-duty Vehicles in 2024. It encompasses experimental data and compliance assessments relative to the measurement of pollutant emissions from internal combustion engine vehicles available on the European market. In 2024, twenty-five Light- (LDVs) and two Heavy-duty Vehicles (HDVs) were tested.
The LDVs were tested on standard laboratory Type 1 (Worldwide harmonized Light-duty Testing Procedure; WLTP), on-road Type 1a (Real Driving Emissions; RDE), Type 4 evaporative emission, Type 5 durability, and Type 6 low-temperature tests. No non-compliances were detected for Type 1, 1a, and 4, while a low risk of non-compliance was found for Type 6 testing. One gasoline Off-Vehicle Charging Hybrid Electric Vehicle (OVC-HEV) showed a high risk of non-compliance to Type 5 durability tests.
Higher emissions were found under non-regulated testing conditions (e.g. at low or high temperatures or under dynamic driving conditions) for some gasoline vehicles (for CO), likely linked to fuel enrichment, and three diesel and one gasoline vehicle (for NOx). These high emissions were attributed to Auxiliary Emissions Strategies (AES) that were not in all cases declared by the manufacturers and approved by the relevant national Authorities.
For HDVs, one N3 category Euro VId diesel truck and one N2 category Euro VIe CNG delivery rigid truck were tested. Both vehicles were tested on the road and in laboratory conditions under regulatory and non-regulatory conditions to assess compliance with the Euro VI emissions standard and to evaluate the potential presence of AES and defeat devices. Emissions of regulated pollutants of both vehicles were below the applicable limits on the regulatory In-Service Conformity (ISC) tests performed on-road with Portable Emission Measurement System (PEMS).JRC.C.4 - Sustainable, Smart and Safe Mobilit
Sustainable Finance Taxonomy Mapper Methodology
Get PDFThe proliferation of more than 50 green taxonomies has shown the increasing interest of policymakers worldwide to foster green capital flows and counteract greenwashing. The Sustainable Finance Taxonomy Mapper (SFTM) aims to foster interoperability across taxonomies worldwide through mapping taxonomy design features as well as technical screening criteria across economic activities substantially contributing to climate or wider environmental objectives. The paper lays out the methodology adopted in the SFTM to map an initial set of 11 taxonomies.JRC.B.1 - Economic and Financial Resilienc
Interoperability Approaches for environmental data sharing and reuse in the European Union
Get PDFData Interoperability is essential to effective usage of data and to building a working data economy for public and private stakeholders across the European Union. Achieving interoperability requires agreement and substantial investments. Over time, there have been a wide range of policy initiatives to improve interoperability, such as sector-specific regulations like INSPIRE –environmental purpose driven – or, more recently, general legal frameworks like the Interoperable Europe Act. However, efforts and benefits were not always balanced optimally, which lead to incomplete, heterogeneous or delayed interoperability.
This report provides a framework to determine what kind of policies and approaches effectively contribute to achieving data interoperability taking into account the lessons learnt from past data sharing initiatives, with a focus on high-value datasets from the geospatial and environmental domain. Furthermore, it includes a set of prospective interoperability approaches that could potentially be applied to Common European Data Spaces, but which are mainly proposed for their consideration in the Green Deal Data Space.JRC.T.4 - Data Governance and Service
Product-as-a-Service as an essential enabler for circular economy in the EU
Get PDFThe Product-as-a-Service (PaaS) model offers potential to accelerate the EU’s transition to a circular economy (CE). Scientific assessment of a PaaS is essential, because not all PaaS offerings and features may contribute to a CE.
The assessment of an example of PaaS offering for home appliances in the EU market shows positive contributions to the efficient use of critical raw materials (CRMs).
Business leaders in the EU are recommended to investigate the potential of PaaS with inherent complexity of a PaaS in mind, including resource efficiency and sustainability potentials.
EU policymakers are recommended to investigate possible policies for facilitating PaaS offerings of higher resource efficiency on the EU market, also for critical raw materials, for instance through providing fair assessment and labelling schemes to end users.JRC.D.3 - Land Resources and Supply Chain Assessment
Data protection, interoperability and governance assessment tool: results from a proof-of-concept survey
No full textBackground
The Collaborative Health Information European Framework (CHIEF) supports consistent monitoring of quality of care and outcomes, through the definition of a cohesive information infrastructure aligned with legal and ethical standards, to ensure preparedness to the European Health Data Space (EHDS). We aimed to define, develop and apply a practical solution to help data controllers and data holders of disease registries and health information systems navigate the increasingly complex and rapidly evolving legal conditions for the governance of health data.
Methods
We designed a tool for data protection, interoperability and governance assessment (DIGA) as a modular, self-assessment questionnaire with an integrated scoring system. The tool enables the application of a mixed-methods approach, combining quantitative and qualitative analytics to assess the level of institutional compliance with EU data protection laws, governance standards, and the EHDS Regulation. The tool has been designed to enhance usability and flexible implementation, allowing institutions to focus on sections that are considered most relevant for their operational purposes. A proof-of-concept survey was run to test and validate the capability of the tool in the field.
Results
The pilot study demonstrated the ability of the tool to capture real-world practices and help data controllers and data holders identify both strengths and critical gaps. The results of the survey showed that participating centres have already established solid foundations in several key areas of data protection. Participating centres showed a moderate-to-high ability to support the secondary use of health data for both research and public health purposes, reflecting an encouraging level of preparedness to the EHDS Regulation. The user feedback collected alongside the pilot study confirmed the relevance and usability of the tool.
Conclusions
We developed an ad-hoc tool to monitor and improve DIGA, as a strategic resource for disease registries and health information systems. The application on field showed that the DIGA tool can support institutional self-assessment, to foster regulatory readiness and generate meaningful insights on how to guide implementation of national and EU-level policies. Further studies are needed to assess the reliability of the tool under broader conditions and refine it accordingly for large-scale implementation. Validation across multiple networks and disease domains within CHIEF will allow strengthening its role in preparation of the EHDS.JRC.F.1 - Disease Preventio
Aligning EU policies to address biological invasions: assessing invasion impacts across sectors
No full textInvasive alien species (IAS) affect various policy sectors, including environment, trade, and agriculture. In Europe, each of these sectors is usually regulated under different European Union legislation, but IAS is not prioritised in most sectors, and this may hinder effective tackling of biological invasions. Greater policy coherence is needed to align relevant sectors for better management of biological invasions. Engaging policymakers by sharing information on IAS impacts can help them understand the multisectoral nature of the problem and develop effective strategies. We reviewed 602 IAS in Europe, impacting nine policy sectors and 25 domains (i.e. specific policies within a broader policy sector, each addressing particular issues and activities related to that sector portfolio). Findings were presented at the NeoBiota workshop in Lisbon on the 3rd of September 2024, attended by 54 participants, including policymakers and researchers. The workshop featured presentations and interactive sessions where participants tested the review methodology on 49 species, identifying areas for improvement, such as assessing impact scale and refining sector domains. Confusion matrices showed moderate to substantial agreement between organisers and participants in evaluating affected domains, types of impact, and confidence levels. This study shows the crucial need for interaction and synergy between research and policy, which are essential for tackling effectively IAS in Europe.JRC.D.2 - Ocean and Wate
Methodology for Sample Size Reduction in Uncertainty Analysis with High-Fidelity Fuel Performance Tools
No full textThis paper presents an efficient computational approach for modeling the propagation of uncertainties in input variables to output variables in fuel rod thermal-mechanical simulations. Our primary goal was to develop a methodology to identify a reduced sample size capable of providing information on uncertainties and sensitivities while remaining cost effective for computation-intensive high-fidelity three-dimensional simulations or full-core calculations.
Our method uses the best-estimate code TRANSURANUS (TU), which is equipped with a built-in Monte Carlo engine. This framework allows for the introduction of uncertainties into the selected input parameters through minor modifications in the input file used for the reference case. We applied this methodology to analyze a representative fuel rod proposed for use in the conceptual molten-salt fluoride-cooled high-temperature reactor (FHR), adapted to the geometry of the advanced gas-cooled reactor (AGR).
The computational efficiency of our approach lies in the reduced number of input/output operations. Consequently, we can execute numerous TU runs, enabling a comprehensive comparison of the results generated with a smaller number of statistical runs. To support statistical postprocessing, we developed the TUPython tool. With this tool, we can quantitatively assess both temporal and spatial variations as well as the sensitivity of fuel behavior model responses. The study showed that the sample size of 153, defined by the fourth-order Wilks’ method, can be used to economically model uncertainty propagation and perform sensitivity analyses in this specific case.JRC.G.I.5 - Nuclear Science and Innovation for Energy and Healt
Internet Standards: Domain Name System Security Extensions (DNSSEC) standards - an analysis of uptake in the EU
Get PDFA high level of adoption of Domain Name System Security Extensions (DNSSEC) is essential to protect
20 the integrity of the Domain Name System (DNS) Internet infrastructure to ensure the interoperability and
security of the global cyberspace. This report provides an analysis of the level of DNSSEC adoption for Q3
2025 across EU Member States and globally. The report also presents an analysis of the usage of DNS
resolvers in the EU and globally. Overall, the average DNSSEC validation rate in the EU is still low (49.4%),
but is superior to the global one (35.4%).JRC.T.2 - Cybersecurity and Digital Technologie