Occurrence and Ecological Risks of Typical POPs in Surface Sediments from the Taizhou River System
Bibliographic record
Abstract
In order to investigate the possible changes of enviromental persistent organic pollutant( POPs) pollution properties during the industrial restructuring in typical e-waste dismantling areas,dioxins( PCDD/Fs),co-planar polychlorinated biphenyls( dl-PCBs) and polybrominated diphenyl ethers( PBDEs) in surface sediments from streams in Taizhou were sampled and analyzed with gas chromatography/high resolution mass spectrometry( GC/HRMS). In addition,the possible sources were also investigated by principal component analysis( PCA). The mean concentrations in Jiaojiang River and Jinqingzha Harbor were 3. 18 and 1. 91 ng/kg( WHO2005-TEQ) for 2378-PCDD/Fs,0. 26 and 0. 62 ng/kg( WHO2005-TEQ) for dl-PCBs,22. 5 and 19. 7 μg/kg for PBDEs,which were at the medium level of POPs in surface sediments in China and the world,and much lower than those in heavily polluted places as other e-waste dismantling sites. The results show that PCDD/Fs in surface sediment in Taizhou mainly originate from coal burning.dl-PCBs can be attributed to the residue of technical PCB products in the history or e-waste dismantling activities. PBDEs sources include the use of technical PBDEs products and the e-wastedismantling activities. YTZ site is close to a discharge port of a chemical engineering industrial zone; its PCDD/Fs and dl-PCBs concentrations were as high as 6. 54 × 104 and 7. 84 × 103ng/kg,respectively. The possible sources are the secondary metallurgy or chemical waste recycling. This implies that new POPs emission sources may appear,and much more attention should be paid during industrial restructuring in the e-waste dismantling area. Some surface sediments have total toxic equivalent quantities exceeding the interim sediment quality guidelines( ISQGs) suggested by Canadian Environmental Council and United States Environmental Protection Agency,indicating ecological risks in Taizhou.
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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 | 0.001 | 0.002 |
| 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) | 0.000 | 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".