Integrated risk assessment of heavy metals in marine sediments from Salwa Bay, Qatar using pollution indices and multivariate analysis
Bibliographic record
Abstract
This study investigates the concentration, contamination status, and ecological risk of HMs in surface sediments collected from 44 coastal sites in Salwa Bay, Qatar. Concentrations of Zn, Cd, Cr, As, Co, Mn, Al, and Fe were measured and assessed using contamination indices including Enrichment Factor (EF), Contamination Factor (CF), Geoaccumulation Index (Igeo), and Potential Ecological Risk Index (PERI). Multivariate statistical tools such as Pearson correlation matrix and Principal Component Analysis (PCA) were applied to explore inter-element relationships and potential sources. The results revealed significant enrichment and contamination by Cd and Cr, with 43 samples classified as extremely enriched in Cd and 40 as significantly enriched in Cr based on EF. The CF and Igeo indices confirmed Cd as the most concerning element, with 19 samples showing very high CF (≥6) and 18 samples classified as moderately to strongly contaminated (Igeo 2-3). Comparisons with Canadian Sediment Quality Guidelines (ISQGs and PEL) and the SQGs of the National Oceanic and Atmospheric Administration (ERL and ERM) indicated that 100 % of samples for Zn, Cr, and As were below PEL/ERM thresholds, but over 56 % of samples for Cd exceeded ISQGs and ERLs, suggesting potential biological risks. PCA extracted two principal components explaining 75.56 % of the total variance, highlighting probable anthropogenic sources for Co, Cr, Fe, Cd, and Zn, and a mixed geogenic and anthropogenic origin for As. The semi-enclosed bay's hydrodynamic retention zones and localized point-source contributions are likely reflected in the contamination hotspots found by spatial analysis at stations 14, 26, 35, and 39. In addition to ecological hazards, the results raise concerns about dietary exposure concerns because Cd can bioaccumulate in fish and benthic organisms, which may have an impact on human health. These results highlight the need for more stringent Cd emission limits, biomonitoring initiatives, and hydrodynamic modeling to predict pollutant movement, as well as for regionally coordinated monitoring and policy responses throughout the Arabian Gulf. These findings underscore the need for continued monitoring and regulatory attention in Salwa Bay, particularly concerning cadmium pollution. Although no direct local anthropogenic sources were observed within the Qatari part of Salwa Bay, the enrichment of some HMs indicates possible transport from external sources within the Arabian Gulf and subsequent accumulation due to the bay's semi-enclosed hydrodynamic setting.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".