Trace metal levels of the Odaw river sediments at the Agbogbloshie e-waste recycling site
Bibliographic record
Abstract
The lack of appropriate infrastructure and legislation regarding the proper way of handling ewastes has encouraged informal recycling as in the case of the Agbogbloshie e-waste site. The burning and dumping of these wastes at the bank of the Odaw River eventually end up in the river. To ascertain the level of trace metal contamination in the Odaw River, 15 sediment samples collected from five different locations were analyzed for their trace metals. The locations were chosen to represent areas near to heavy e-waste activities and areas with no apparent ewaste activities, and analysis carried out using Atomic Absorption Spectrophotometry. The results indicated that mean concentrations of the trace metals (Cu, Cd, Pb, Fe, Cr and Ni) were highest at locations near burning and dumping sites (L1 and L2 respectively). This was attributed to the result of e-waste activities and the configuration of the river. With the exception of Cu and Cd at L1, the rest of the metals were below the recommended Canadian interim sediment quality guideline (ISQG) while none was above the Probable Effect Level (PEL), an indication that the levels of trace metal contamination were below the concentration at which frequent adverse effects are expected to occur. The results have confirmed that e-waste recycling activities along the banks of the Odaw River contribute to the contamination of the river.Keywords: E-waste, sediment, metal, contamination, recycling
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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) | 0.001 | 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".