Persistent Problem: Global Challenges to Managing PCBs
Bibliographic record
Abstract
Polychlorinated biphenyls (PCBs), "famous" as persistent organic pollutants (POPs), have been managed nationally since the 1970s and globally under the Stockholm Convention on POPs since 2004, requiring environmentally sound management (ESM) of PCBs by 2028. At most, 30% of countries are on track to achieve ESM by 2028. Globally over 10 million tonnes of PCB-containing materials remain, mostly in countries lacking the ability to manage PCB waste. Canada (Ontario) and Czechia, both parties to the Stockholm Convention, are close to achieving the 2028 goal, having reduced their stocks of pure PCBs by 99% in the past 10 years. In contrast, the USA, not a party to the Stockholm Convention, continues to have a substantial but poorly inventoried stock of PCBs and only ∼3% decrease in mass of PCBs since 2006. PCB management, which depends on Stockholm Convention support and national compliance, portends major challenges for POP management. The failure to manage global PCB stocks >30 years after the end of production highlights the urgent need to prioritize reducing production and use of newer, more widely distributed POPs such as chlorinated paraffins and per- and polyfluorinated alkyl substances, as these management challenges are unlikely to be resolved in the coming decades.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.020 | 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".