Emissions of persistent organic pollutants and eight candidate POPs from UNECE-Europe in 2000, 2010 and 2020 and the emission reduction resulting from the implementation of the UNECE POP protocol:
Bibliographic record
Abstract
An emission inventory for persistent organic pollutants (POP) is made for the year 2000 based on submissions of emission data from the Parties to the Convention on LRTAP. The inventory covers the UNECE territory except Canada and the United States. For the countries, sources or compounds lacking in official submissions, default emission estimates have been prepared and applied to complete the inventory. An indicative comparison of the year 2000 emissions with the 1990 emission levels from a previous study is presented as well as emission projections for 2010, 2015, 2020 based on activity scenarios developed in the framework of the EU CAFE programme. The key source analysis of the projected emissions assuming full implementation of the UNECE protocols allows identification of remaining source strengths which subsequently are briefly discussed in terms of their potential for (further) reduction. A number of chemicals are currently being investigated for inclusion on the UN/ECE POPs protocol list of priority compounds but for these substances emission estimation methodologies are scarce or non-existent. For eight of these substances (dicofol, edosulfan, hexachlorobutadiene (HBU), pentabromodiphenyl ether (PBDE), pentachlorobenzene (PCBe), pentachlorophenol (PCP), polychloronated naftalenes (PCN) and short chained chlorinated paraffins (SCCPs)) an emission estimation methodology is proposed and a preliminary emission inventory for the year 2000 is presented. © 2007 Elsevier Ltd. All rights reserved.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".