MULTI-PATHWAY HUMAN EXPOSURE TO HEAVY METALS IN TWO URBAN RIVERS OF SOUTHERN NIGERIA: A DETERMINISTIC AND MONTE CARLO RISK ASSESSMENT

Heavy metal contamination of freshwater systems poses significant public health concerns in urbanizing regions where rivers provide food and domestic water. This study assessed human health risks associated with Pb, Cd, Mn, Fe, Cu, Zn, and Ni in water, sediment, and fish from Ogba and Ikpoba Rivers, Nigeria, using integrated deterministic and probabilistic approaches. Exposure through fish consumption, water ingestion, and incidental sediment ingestion was evaluated for adults and children using Estimated Daily Intake (EDI), Hazard Quotient (HQ), Hazard Index (HI), and Monte Carlo simulation (10,000 iterations). Metal concentrations generally followed the pattern sediment > fish > water, indicating sediment retention with transfer into edible biota. Fish consumption was the dominant exposure pathway in both rivers, while sediment ingestion contributed minimally. Children consistently showed higher exposure and risk than adults due to lower body weight. All mean deterministic HI values were below 1, indicating no immediate non-carcinogenic risk under average exposure assumptions. However, upper-tail probabilistic estimates for child fish consumers approached levels of concern, particularly in Ogba River. Sensitivity analysis identified fish ingestion rate and metal concentration as the strongest drivers of risk variability. These findings show that average deterministic estimates may underestimate risk for high-exposure groups. Continuous monitoring, child-focused risk management, and fish consumption guidance are recommended for river-dependent communities.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-16
DOI
https://doi.org/10.5281/zenodo.20220053
Primary Topic
Heavy metals in environment
Type
article
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article

MULTI-PATHWAY HUMAN EXPOSURE TO HEAVY METALS IN TWO URBAN RIVERS OF SOUTHERN NIGERIA: A DETERMINISTIC AND MONTE CARLO RISK ASSESSMENT

O. Ogbeide, G. Ogbeide
Zenodo (CERN European Organization for Nuclear Research)
Heavy metals in environment
article

MULTI-PATHWAY HUMAN EXPOSURE TO HEAVY METALS IN TWO URBAN RIVERS OF SOUTHERN NIGERIA: A DETERMINISTIC AND MONTE CARLO RISK ASSESSMENT

O. Ogbeide, G. Ogbeide
article en

Abstract

Heavy metal contamination of freshwater systems poses significant public health concerns in urbanizing regions where rivers provide food and domestic water. This study assessed human health risks associated with Pb, Cd, Mn, Fe, Cu, Zn, and Ni in water, sediment, and fish from Ogba and Ikpoba Rivers, Nigeria, using integrated deterministic and probabilistic approaches. Exposure through fish consumption, water ingestion, and incidental sediment ingestion was evaluated for adults and children using Estimated Daily Intake (EDI), Hazard Quotient (HQ), Hazard Index (HI), and Monte Carlo simulation (10,000 iterations). Metal concentrations generally followed the pattern sediment > fish > water, indicating sediment retention with transfer into edible biota. Fish consumption was the dominant exposure pathway in both rivers, while sediment ingestion contributed minimally. Children consistently showed higher exposure and risk than adults due to lower body weight. All mean deterministic HI values were below 1, indicating no immediate non-carcinogenic risk under average exposure assumptions. However, upper-tail probabilistic estimates for child fish consumers approached levels of concern, particularly in Ogba River. Sensitivity analysis identified fish ingestion rate and metal concentration as the strongest drivers of risk variability. These findings show that average deterministic estimates may underestimate risk for high-exposure groups. Continuous monitoring, child-focused risk management, and fish consumption guidance are recommended for river-dependent communities.

Zenodo (CERN European Organization for Nuclear Research)
University of Science and Technology of Benin (BJ)
Sustainable cities and communities
Openalex Percentile: Top 9%
Heavy metals in environment
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