Heavy metal contamination and assessment of radioactivity in coastal sediments: a case study from the El Qulaan area, southern Red Sea, Egypt
Bibliographic record
Abstract
This study investigated the concentrations, spatial distribution, and associated ecological and health risks of nine metals in the sediments of the El Qulaan region along the Red Sea coast in southern Egypt. The levels of barium (Ba), lead (Pb), chromium (Cr), nickel (Ni), and vanadium (V) exceeded both the Canadian soil quality guidelines and the Earth’s average shale composition. Nickel concentrations surpassed the Effect Range Median (ERM), while Pb, Cr, and Ni levels exceeded the Probable Effect Level (PEL), suggesting potential adverse effects on local marine organisms. Factor analysis revealed three main factors: the first factor (F1), accounting for 24% of the variance, included Ba, Co, Cr, V, Fe, pH, and total organic matter (TOM%); the second (F2, 20%) comprised Cu, Ni, and Zn; and the third (F3, 19%) included Pb, Gravel%, Sand%, and Mud%. Contamination factor (CF) values indicated varying degrees of pollution: low for Co and Cu, moderate for Pb, Zn, and Fe, considerable for Cr, Ni, and V, and high for Ba. The geo-accumulation index classified all metals as contributing to extreme contamination. The potential ecological risk index (PERI) ranged from 49 to 81, indicating a low ecological risk (PERI <150). Other indices, including the mean effects range-median quotient, toxic risk index, and modified hazard quotient, pointed to moderate toxicity and contamination severity. Non-carcinogenic risk assessments revealed no long-term health concerns, and cancer risk values remained below internationally accepted safety thresholds. Natural radioactivity levels in the sediments were also mapped and analyzed. The mean activities of 232 Th, 226 Ra, and 40 K were 25.43 ± 7.54, 19.99 ± 6.84, and 294.92 ± 77.86 Bq/kg, respectively, all falling below global safety limits. The findings highlight the pressing need for targeted mitigation efforts and policy measures to manage metal contamination in the region’s coastal environments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".