Spatial characteristics, sources and exposure risk of polychlorinated biphenyls in dusts and soils from an urban environment in the Niger Delta of Nigeria
Bibliographic record
Abstract
Chlorinated organic compounds, such as polychlorinated biphenyls (PCBs), are a threat to both humans and the environment because of their toxicity, persistence, and capacity for long-range atmospheric transport . The concentrations of 28 PCB congeners, including 12 dioxin-like and seven indicator PCBs, were investigated in soils, and indoor and outdoor dusts from Port Harcourt city, Nigeria, in order to evaluate the characteristic distribution patterns in these media, their sources, and possible risk. The PCB concentrations varied from 4.59 to 116 ng g −1 for soils, and from 1.80 to 23.0 ng g −1 and 2.73 to 57.4 ng g −1 for indoor and outdoor dusts respectively. The sequence of PCB concentrations in these matrices was soil > outdoor dust > indoor dust. The composition of PCBs in these matrices indicated the prevalence of lower chlorinated PCBs in indoor and outdoor dusts, while the higher chlorinated congeners were dominant in soils. Di-PCBs were the predominant homologues in indoor dusts, while deca-PCBs were the most prevalent homologues in outdoor dusts and soils. The TEQ values of dioxin-like PCBs in 60 % of the soils, 100 % of the indoor dust, and 30 % of the outdoor dust were above the indicative value of 4 pg TEQ g −1 established by the Canadian authority. The hazard index (HI) values for exposure of adults and children to PCBs in these media were mostly greater than one, while the total cancer risk (TCR) values exceeded the acceptable risk value of 10 −6 , which indicate probable non-carcinogenic and carcinogenic risks resulting from exposure to PCBs in these media. Source analysis for PCBs in these matrices shows that they originated from diverse sources.
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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 | 0.001 |
| 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".