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Quantitative Source Attribution and Health Risk Probabilities for Heavy Metals in Bizerte Coastline Sediments

Domain:

environment and energyhealthcare

Record type:

dataset
Creator:
AbdJelSinRan
Host:avatar

Substantial amounts of heavy metals (HMs) enter coastal environments through diverse natural and anthropogenic activities, posing significant ecological and human health concerns. This study provides a comprehensive assessment of the contamination levels of HMs (Fe, Zn, Pb, Co, Cu, Ni, Mn, Cd, and Cr) in surface sediments collected from the Bizerte coastline (Tunisia) and evaluates potential human health risks. Probabilistic modeling using Monte Carlo simulations quantified carcinogenic and non-carcinogenic risks for adults and children through ingestion, dermal contact, and inhalation exposure routes. Average heavy metal concentrations in sediments were found in the descending order (mg/kg): Fe (384) >Pb (4.7) >Zn (2.6) >Mn (2.3) >Cu (1.1) >Cr (0.63) >Ni (0.48) >Co (0.1) >Cd (0.05). Source apportionment using positive matrix factorization (PMF), complemented by Pearson correlation analysis and Self-Organizing Maps (SOM), identified four predominant sources: industrial activities (28.5%), geogenic sources (27.3%), sewage discharge (23.4%), and agricultural run- off (20.8%). The PMF and risk modeling highlighted Pb as the primary contributor to non-carcinogenic risk and Cr as the primary contributor to carcinogenic risk. Although TCR remained below the safety threshold of 1×10−4, children exhibited approximately an order of magnitude higher risk, with 29.4% samples exceeding the 1×10−6 risk level.

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Tags

BiotechnologySociologyImmunologyEnvironmental Sciences not elsewhere classifiedBiological Sciences not elsewhere classifiedPotentially toxic elementsMonte Carloself-organizing mappositive matrix factorizationhazard index+1

Licenses

CC BY 4.0

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