Risk Transmission of Hg/MeHg from Aquatic Environments to Dietary Exposure Through Aquatic Products: Network-Based Pathway Identification and a Framework Toward Probabilistic Early Warning

Mercury (Hg) and methylmercury (MeHg) can be transferred from aquatic environments through food webs to edible fishery products and ultimately contribute to human dietary exposure. This structured narrative review synthesizes 99 sources to examine the continuous risk-transmission process from environmental Hg/MeHg dynamics to dietary exposure and to evaluate the roles of network analysis, Bayesian networks (BNs), and Monte Carlo simulation in related risk assessment. Three main findings emerge. First, concentrations in a single environmental medium are insufficient to characterize risk transmission because MeHg formation, bioavailability, trophic transfer, and accumulation depend on interacting environmental and ecological processes. Second, food-web structure and transfer pathways are critical for identifying the biological groups and links that contribute most strongly to MeHg movement toward edible products. Third, network analysis, BNs, and Monte Carlo simulation provide complementary functions for pathway identification, probabilistic updating, and exposure-uncertainty analysis, respectively. Based on these findings, we propose a conceptual Network–BN–Monte Carlo framework linking pathway identification, probabilistic inference, and dietary-exposure uncertainty within a common analytical approach. The framework currently serves primarily to organize existing evidence; practical risk assessment and early warning will require empirical parameterization and independent validation using real monitoring data.

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Publication Details

Journal
Foods
Published
2026-10-29
DOI
https://doi.org/10.3390/foods15213879
Primary Topic
Mercury impact and mitigation studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Risk Transmission of Hg/MeHg from Aquatic Environments to Dietary Exposure Through Aquatic Products: Network-Based Pathway Identification and a Framework Toward Probabilistic Early Warning

Zhiyao Zhao, Xiaozheng Cui, Li Wang, Yingxin Zhang et al.
1 links
Foods
Mercury impact and mitigation studies
article

Risk Transmission of Hg/MeHg from Aquatic Environments to Dietary Exposure Through Aquatic Products: Network-Based Pathway Identification and a Framework Toward Probabilistic Early Warning

Zhiyao Zhao, Xiaozheng Cui, Li Wang, Yingxin Zhang, Jiabin Yu
article en

Abstract

Mercury (Hg) and methylmercury (MeHg) can be transferred from aquatic environments through food webs to edible fishery products and ultimately contribute to human dietary exposure. This structured narrative review synthesizes 99 sources to examine the continuous risk-transmission process from environmental Hg/MeHg dynamics to dietary exposure and to evaluate the roles of network analysis, Bayesian networks (BNs), and Monte Carlo simulation in related risk assessment. Three main findings emerge. First, concentrations in a single environmental medium are insufficient to characterize risk transmission because MeHg formation, bioavailability, trophic transfer, and accumulation depend on interacting environmental and ecological processes. Second, food-web structure and transfer pathways are critical for identifying the biological groups and links that contribute most strongly to MeHg movement toward edible products. Third, network analysis, BNs, and Monte Carlo simulation provide complementary functions for pathway identification, probabilistic updating, and exposure-uncertainty analysis, respectively. Based on these findings, we propose a conceptual Network–BN–Monte Carlo framework linking pathway identification, probabilistic inference, and dietary-exposure uncertainty within a common analytical approach. The framework currently serves primarily to organize existing evidence; practical risk assessment and early warning will require empirical parameterization and independent validation using real monitoring data.

FoodsVol. 15(21)
Beijing Technology and Business University (CN)
National Natural Science Foundation of China, Beijing Technology and Business University, National Center for Research and Development
Openalex Percentile: Top 18%
Mercury impact and mitigation studies
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