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. 2025 Feb 3;15(1):4122.
doi: 10.1038/s41598-024-71547-4.

Environmental and health risk assessment of polycyclic aromatic hydrocarbons and toxic elements in the red sea using Monte Carlo simulation

Affiliations

Environmental and health risk assessment of polycyclic aromatic hydrocarbons and toxic elements in the red sea using Monte Carlo simulation

F Alshaima Sayed et al. Sci Rep. .

Abstract

This research evaluates the environmental and health risks linked to potentially toxic elements (PTEs) and PAHs along the western coast of the Gulf of Suez, Egypt. This study investigated the concentration of 16 PAH compounds in the Suez Gulf, revealing significantly higher levels than the EU (0.20 µg/L) and US (0.030 µg/L) standards. The average total PAH concentration across eight locations was significantly higher, with the Suez area having the highest concentration at 479 µg/L. Pyrene (Pyr) was the dominant PAH with a concentration of 443 µg/L in Suez, while acenaphthylene (Ace) had the lowest concentration at 0.120 µg/L in Northern Zaafarana. Carcinogenic PAHs (CAR) ranged from 8.67 µg/L at Ras Gharib to 29.62 µg/L at Suez, highlighting the urgent need for regulatory measures. Confirmatory ratios pointed to industrial and shipping influences as petrogenic sources. Elevated total organic carbon (TOC) levels in Suez Bay indicated aggravated organic pollution, exacerbated by oil rigs and refineries. The ecological risk assessment highlighted substantial risks, particularly in Suez, necessitating immediate interventions to combat PAH contamination and preserve the environmental balance of the Red Sea. The dominant metals in water samples were arranged in descending order as follows: Pb > Fe > Cr > Cu > Zn > Mn > Cd > Ni. The study evaluated environmental and human health risks using a multifaceted approach, including cluster analysis, principal component analysis, and various indices (HPI, RI, MI, HQ, HI, and CR). Most water samples exhibited high pollution risks, surpassing permissible limits for HPI (> 100) and MI (> 6). Notably, HI oral values indicated significant non-carcinogenic risks for adults and children. While HI values for adults suggested low-risk dermal contact, those for children showed a substantial proportion in the high-risk category. Most water samples displayed CR values exceeding 1 × 10-4 for Cd, Cr, and Pb, indicating vulnerability to carcinogenic effects in both age groups. Monte Carlo simulations reinforced these findings, revealing a significant carcinogenic impact on children and adults. The identified clusters, reflective of industrial, petroleum-related, and urban runoff contamination sources, were consistently validated and clarified through PCA, enhancing the reliability of the findings. In light of these results, urgent and comprehensive water treatment measures are imperative to mitigate carcinogenic and non-carcinogenic health risks. These insights provide a foundation for implementing targeted management strategies to effectively address the challenges of heavy metal contamination in the Red Sea.

Keywords: Carcinogenic and non-carcinogenic risk; Monte Carlo simulation; PAHs; PTE pollution indices; Python code; Red Sea.

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Conflict of interest statement

Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Location map for the area of study.
Fig. 2
Fig. 2
The ecological risk index (a), heavy metals pollution index (b), and metal index (c) calculated from 18 locations of the GOS.
Fig. 3
Fig. 3
Box plot of HQ oral in adult (a), child (b), HQ dermal in adult (c), and child (d).
Fig. 4
Fig. 4
Box plot of HI (oral & dermal) index in children and adults.
Fig. 5
Fig. 5
Box plot of CR (children and adults) index through oral contact (a) and dermal contact (b).
Fig. 6
Fig. 6
The predicted HQ oral in adult (a), child (b), HQ dermal in adult (c), and child (d).
Fig. 7
Fig. 7
The predicted CR oral value with 5% and 95% of the datasets in adult (a), child (b), HQ oral in adult (c), and child (d).
Fig. 8
Fig. 8
Cluster analysis (dendrogram) of the heavy metals in the collected samples.
Fig. 9
Fig. 9
PCA extracted from (a) scree plot and its plotting on 3D diagram (b).

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