EURAMET project 21GRD09 MetroPOEM: Metrology for the harmonisation of measurements of environmental pollutants in Europe
Bibliographic record
Abstract
The MetroPOEM project is funded by EURAMET under the European Green Deal and the underlying ambition for zero pollution. The project aligns directly with global target 7 of the Kunming-Montreal Global Biodiversity Framework (GBF), which aims to ‘…reduce pollution risks and the negative impact of pollution from all sources by 2030…’To support target 7 of the GBF requires the development of highly sensitive techniques to detect ultra-low levels of pollutant elements identified as environmental stressors, and to determine their isotope ratios, which are key parameters in the identification and attribution of sources of such pollutants.Mass spectrometry is a key method for determination quantities of non-radioactive polluting elements and long-lived radionuclides as well as the isotope ratios of such elements, and the MetroPOEM project bridges the traceability gap between activity and mass-based measurements – particularly estimation of mass bias.Underlying studiesSI-traceable high-precision methods were developed for isotope ratio determination of Li, B, Cr, Cd, Ni, Sb, Pb, and U in environmental matrices, focused on seawater as the model solution. Method development encompassed manual and automated methods for separating analytes from the matrix, evaluating different calibration approaches and instrumental isotope fractionation corrections, and estimating uncertainty budgets. Various single and multi-collector ICP-MS systems, as well as accelerator mass spectrometry, were used and their performances compared.These findings support the development of methods for stable and radioactive isotope determination.Radioactive standard solutions (90Sr, 237Np, 234,236U, 239,240Pu, 241Am) were distributed to partner laboratories for measurement. The results and data analysis were compiled as a comparison report, leading to a peer-reviewed publication draft.Reference materialsA 250 litre of sea water sample was taken from the German EEZ (North Sea) for the development of two certified reference materials. This material was subjected to processing, including spiking with additional elements based on preliminary analysis and homogenisation.Part of this candidate reference material was characterised for isotope ratios of Li, B, Cr, Cd, Ni, Sb, Pb, and U to generate a reference material with SI traceability for isotope ratios. Additionally, ~50×0,5L liquid RM aliquots of sea water were prepared, spiked with natural U, 237Np, 239,240Pu and 241Am.A solid silica-based reference material, produced by sol-gel synthesis spiked with 234,235,236,238U, 237Np, 239,240Pu and 241Am, as well as ~10 kg of an inactive material for testing dissolution procedures.These materials were characterised in accordance with the requirements of ISO 17034 by interlaboratory studies between the project partners, using techniques developed in the project, and will be available to the wider scientific community for method development and validation.OutputsCertified reference materials from the project will be available to the wider scientific community for method development and validation.To support end users interested in developing or upgrading their capabilities. two Good Practice Guides on (i) measurement of radioactivity by mass spectrometric techniques, and (ii) sample treatment, uncertainties and mass bias quantification, are being drafted for issue by the end of the project.Project outcomes thus support the aims of the GBF global target 5 by improving traceability of measurement.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.032 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".