Dynamic Source Distribution and Emission Inventory of a Persistent, Mobile, and Toxic (PMT) Substance, Melamine, in China
Bibliographic record
Abstract
Persistent, mobile, and toxic (PMT) substances are affecting the safety of drinking water and are threatening the environment and human health. Many PMT substances are used in industrial processing or consumer products, but their sources and emissions mostly remain unclear. This study presents a long-term source distribution and emission estimation of melamine, a high-production-volume PMT substance of emerging global concern. The results indicate that in China, approximately 1858.7 kilotonnes (kt) of melamine were released into the water (∼58.9%), air (∼27.0%), and soil systems (∼14.1%) between 1995 and 2020, mainly from its production and use in the decorative panels, textiles, and paper industries. The textile and paper industries have the highest emission-to-consumption ratios, with more than 90% emissions per unit consumption. Sewage treatment plants are the largest source of melamine in the environment for the time being, but in-use products and their wastes will serve as significant melamine sources in the future. The study prompts priority action to control the risk of PMT substances internationally.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".