English(EN) Quantifying the Threat: A Bayesian Probabilistic Framework for Heavy Metal Health Risks among Children in the Densu Basin, Ghana

贝叶斯框架量化加纳地下水重金属健康风险

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-21 04:00

研究人员开发了一个贝叶斯概率框架，用于评估地下水中重金属污染对儿童的健康风险，重点关注加纳登苏河流域的儿童。这种新方法通过纳入不确定性、协同暴露和空间变异性，改进了先前的方法。研究发现，铅、砷和镉构成最大的累积风险，约31%的采样点显示超过危害指数1的概率大于0.5。该框架的发现强调，高风险区域通常以多种金属的中度协同暴露为特征，而不是单一元素的极端污染，这为数据有限地区的公共卫生规划提供了宝贵的见解。 AI

排序理由这是一篇研究论文，详细介绍了一种新的风险评估统计框架。[lever_c_demoted from research: ic=1 ai=0.1]

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · T. Ansah-Narh, G. Y. Afrifa, J. B. Tandoh, E. N. N. Nortey, D. Adjei, R. Opoku-Sarkordie, R. Davis · 2026-10-21 04:00

量化威胁：加纳登苏盆地儿童重金属健康风险的贝叶斯概率框架

arXiv:2610.28064v1 Announce Type: cross Abstract: Groundwater in Ghana's Densu River Basin remains a key domestic water source, but multi-metal contamination threatens children's health. Previous deterministic hazard index assessments provide limited treatment of uncertainty, co-…

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报道来源 [1]

量化威胁：加纳登苏盆地儿童重金属健康风险的贝叶斯概率框架

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