Applicability of H14 Protocol for Sediments in Order to Consider Their Valorization: Limits and Benefits
Bibliographic record
Abstract
Community and national regulations impose to do not discharge harbor sediments into the sea without first measured the level of pollution and assessed the risk of impacts on the marine environment by the use of ecotoxicity tests on marine species. If the immersion is impossible, sediment has to be directed to inland areas where they have the status of waste. Then, it must identify whether the waste is hazardous or not.The H14 "ecotoxic" property of the EU Waste Directive, which is conventionally used for the characterization of hazardous waste in case of multiple contaminations, can be applied to sediments. In case of strong positive response to ecotoxicity tests on terrestrial species, the sediment must be managed as a hazardous waste and it must be oriented to regulated waste storage sites. For sediments that do not have a significant toxicity, two alternatives are available for the decision makers: the deposit of sediment in landfills or the valorization of sediments as secondary raw materials (SRM).The SEDIVALD project aimed to test the application of H14 protocol on a set of marine, lake and river sediments where the main regularly pollutants were dosed. The results of these tests showed first a large variability in levels of sediment pollution, which was fairly predictable because of the types of activities for the concerned ports and watersheds.In numerous cases, the H14 protocol was effective for characterizing the level of hazard of sediment and seemed correlated with the levels of pollutants measured. In contrast, other sediments were identified as ecotoxic by the H14 protocol without that the dosed pollution left it supposed. According to classical chemical analyzes, sediments appeared not to be polluted and logically should not have to meet H14 protocol. The origin of the pollution (pesticides or other) must be sought because these hazardous wastes could be used in beach nourishment.The SEDIVALD project has demonstrated the applicability of the H14 protocol to characterize the hazard level of sediments from the ecotoxicological point of view, but it also showed the importance of further investigations to detect contaminants that are not usually taken into account. This is particularly important because the sediments managed in land should be treated by physicochemical and biological processes to enable their valorization as SRM.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".