Sediment evaluation indices point to cadmium and selenium contamination: A simultaneous analysis of potentially toxic elements in the water and sediment along the upper and middle Awash River, Ethiopia
Bibliographic record
Abstract
This study presents a simultaneous analysis of potentially toxic elements (PTEs) in the water and sediment of the upper and middle Awash River for the first time. We used standard field and laboratory procedures, sediment assessment indices and guidelines, and multivariate statistical methods to analyze PTEs and assess their possible sources. Water and sediment samples were collected from nine sampling sites, and PTEs were analyzed using the Inductively Coupled Plasma Optical Emission Spectrometer. The PTEs concentrations arranged in descending order in water were Fe>Mn>B>Zn>Cr>Ni>Pb>Cu, ranging between 4.14 ± 2.093 mg L 1 and 0.074 ± 0.016 mg L 1. The level of PTEs in the sediment varied between 24,493.6 ± 16,640.3 mg kg-1 and 0.4 ± 0.2 mg kg-1 and follows the order: Fe>Mn>Cr>Zn>Pb>Ni>B>Se>Co>Cu>Cd>Hg>As. The river-mouth of the upper Awash had the highest concentrations of Mn, Ni, Cr, and Cu in water and Fe, Mn, Cr, Ni, Pb, Co, Se, Cu, Cd, and AS in the sediment. Contamination factor, enrichment factor, and geo-accumulation index showed a very high level of contamination of Se and Cd. The ecological risk index, Nemerow pollution index, and pollution load index also indicated a high ecological risk and pollution by PTEs in the river. The levels of Fe, Pb, Ni, Mn, B, and Cr in the water surpassed Ethiopian/WHO's drinking water guidelines, while the levels of Cd, Hg, and Cr in the sediment exceeded Canadian/Ontario's probable/severe effect levels. This study revealed the presence of ecological degradation at the downstream sites of the upper and middle Awash. The most likely sources of contaminants were identified as small-scale agricultural pollution, residential and commercial waste from towns like Addis Ababa, Merti, and Metehara, and the inflow of Lake Beseka. We recommend an integrated management plan for the Awash River to ensure sustainable use of the water, guarantee the well-being of wildlife, and reduce public health risks.
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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 | 0.001 | 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".