Department of Earth Sciences, Faculty of Natural Sciences, University of Tabriz, 29 Bahman Boulevard, Tabriz, East Azerbaijan, Iran.
Institute of Environment, University of Tabriz, Tabriz, East Azerbaijan, Iran.
Environ Sci Pollut Res Int. 2021 Apr;28(15):18702-18724. doi: 10.1007/s11356-020-11853-2. Epub 2021 Jan 21.
A capability for aggregating risks to aquifers is explored in this paper for cases with sparse data exposed to anthropogenic and geogenic contaminants driven by poor/non-existent planning/regulation practices. The capability seeks 'Total Information Management' (TIM) under sparse data by studying hydrogeochemical processes, which is in contrast to Human Health Risk Assessment (HHRA) by the USEPA for using sample data and a procedure with prescribed parameters without deriving their values from site data. The methodology for TIM pools together the following five dimensions: (i) a perceptual model to collect existing knowledge-base; (ii) a conceptual model to analyse a sample of ion-concentrations to determine groundwater type, origin, and dominant processes (e.g. statistical, graphical, multivariate analysis and geological survey); (iii) risk cells to contextualise contaminants, where the paper considers nitrate, arsenic, iron and lead occurring more than three times their permissible values; (iv) 'soft modelling' to firm up information by learning from convergences and/or divergences within the conceptual model; and (v) study the processes within each risk cell through the OSPRC framework (Origins, Sources, Pathways, Receptors and Consequence). The study area comprises a series of patchy aquifers but HHRA ignores such contextual data and provides some evidence on both carcinogenic and non-carcinogenic risks to human health. The TIM capability provides a greater insight for the processes to unacceptable risks from minor ions of anthropogenic nitrate pollutions and from trace ions of arsenic, iron and lead contaminants.
本文探讨了在数据稀疏的情况下，针对人为和地质污染物暴露的情况，对含水层风险进行综合评估的能力。这种能力通过研究水文地球化学过程来寻求“全面信息管理”（TIM），这与美国环保署（USEPA）的人类健康风险评估（HHRA）形成了对比，后者使用样本数据和规定参数的程序，而不从现场数据中推导出其值。TIM 方法汇集了以下五个方面：（i）感知模型，用于收集现有知识库；（ii）概念模型，用于分析离子浓度样本，以确定地下水类型、来源和主导过程（例如统计、图形、多元分析和地质调查）；（iii）风险单元，用于将污染物置于上下文中，本文考虑了硝酸盐、砷、铁和铅的浓度超过允许值三倍以上的情况；（iv）“软建模”，通过从概念模型中的收敛和/或发散中学习来加强信息；（v）通过 OSPRC 框架（起源、来源、途径、受体和后果）研究每个风险单元中的过程。研究区域包括一系列零星的含水层，但 HHRA 忽略了这种上下文数据，并提供了一些关于人类健康的致癌和非致癌风险的证据。TIM 能力提供了对人为硝酸盐污染的次要离子和砷、铁和铅污染物的痕量离子引起不可接受风险的过程的更深入了解。
