Profiling PBDE emissions from coastal landfills: Impact of waste management practices
Bibliographic record
Abstract
• PBDE-driven landfill management is crucial for marine protection. • Seasonal waste spikes substantially increase PBDE levels. • BDE-47 dominates PBDE profiles in landfill leachate. • Prioritize policies for advanced leachate treatment and recycling in coastal landfills. This study investigates the influence of landfill management practices on the release of polybrominated diphenyl ethers (PBDEs) from coastal landfills in Newfoundland, Canada. By comparing PBDE congener profiles in leachate from a modern landfill with advanced treatment systems and a legacy landfill with limited infrastructure, we demonstrate the critical role of modern waste management practices in mitigating PBDE contamination. Both sites showed PBDE contamination, but the legacy landfill exhibited greater variability in congener types and concentrations. BDE-47 emerged as the predominant congener at both sites, with episodic spikes at the legacy landfill reaching 14.39 ng/L, alongside the presence of congeners like BDE-77, BDE-100, and BDE-183. GIS analysis revealed PBDE dispersion into nearby surface waters, posing risks to marine ecosystems. Landfill operator surveys provided insights into operational challenges, including limited e-waste diversion, fire risks from batteries, and inadequate leachate treatment at the legacy site, contributing to its vulnerability. This study underscores the need for proactive PBDE management in coastal landfills. The adoption of modern landfill technologies and enhanced e-waste diversion programs is vital for reducing contamination and protecting marine environments. These findings highlight the importance of sustainable waste management practices in safeguarding coastal ecosystems.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".