Heavy metals and radioactivity assessment of the coastal sediments at Abu Ghusun, southern Red Sea, Egypt
Bibliographic record
Abstract
Coastal sediments act as both sinks and secondary sources of pollutants, making their assessment essential for understanding ecological and human health risks in sensitive marine environments. This study evaluated the concentrations of nine trace metals and natural radionuclides in surface sediments from Abu Ghusun, south Red Sea to assess their ecological, radiological, and health implications. Sediment texture, organic matter, and metal concentrations were analyzed, followed by application of international sediment quality guidelines and multiple ecological risk indices. The results showed that Pb, Cr, Ba, Cu, and Ni exceeded the Effect Range Median (ERM) thresholds, suggesting potential adverse effects on benthic organisms. Cr and V also surpassed Canadian soil quality guidelines and global upper crust values. Enrichment Factor analysis indicated significant enrichment of Pb and Ni, while contamination indices revealed considerable to elevated contamination for most metals, particularly Zn and Pb. Geo-accumulation (Igeo) values > 5 identified areas of severe contamination. Despite this, the Potential Ecological Risk Index (PERI) indicated low ecological threat (<150), though the mean ERM quotient suggested a medium–high priority risk. Toxicological risk assessment showed moderate toxicity potential, while human health evaluation revealed negligible non-carcinogenic and carcinogenic risks. The activity concentrations of 232Th (12.1 ± 6.42 Bq/kg), 226Ra (24.53 ± 5.65 Bq/kg), and 40K (337.06 ± 64.98 Bq/kg) were below gobal safety limits, indicating no radiological hazards. This study offers the first integrated assessment of trace metals and radionuclides in Abu Ghusun sediments, combining ecological, radiological, and health risk indices to reveal localized Pb, Ni, and Zn enrichment. Continuous monitoring is recommended to track pollutant inputs, particularly from anthropogenic activities. Remediation strategies and stricter regulation of potential metal sources should be implemented to protect the Red Sea ecosystem.
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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 | 0.002 | 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".