High Resolution Models of Groundwater Metal Exposures

项目1摘要 长期的强心研究记录了本地人尿砷(As)和铀(U)的高水平 相对于美国总人口的美国部落研究地点。暴露于金属和类金属的增加 (下称金属)可能导致影响部落和其他农村地区的心脏代谢性疾病的流行。 美国的社区。在北部平原的农村社区，饮用水通常来自 来自相同含水层的不受监管和基本上不受监测的私人水井或公共供水系统。 大部分砷和铀的暴露可能是由于地下水来源中金属水平的升高造成的。然而， 农村社区，特别是部落地区的地下水数据相对稀缺，因此很难 确定地下水危害，并减轻其暴露。哥伦比亚大学北方分校项目1 平原超级基金研究计划(CUNP-SRP)使用双管齐下的方法来解决我们的 了解包括原住民在内的农村地区地下水污染和暴露的分布 美国部落地区。首先，我们将整合现有的和新的地下水成分数据测量 与先前的大型矿物学和化学形态数据集。第二，我们将结合使用 井中地下水成分及遥感水文等变量开发机 基于学习的家庭尺度地下水污染物水平预测模型--基础 暴露评估所需的数据。我们有三个具体目标。目标1将分析来自 CUNP-SRP实地区域以确定和更好地了解As和U的动员机制 喝水。Aim 2将开发基于过程的模型，预测As和U的饮用水浓度 整个北部平原的家庭规模。AIM 3将开发和验证AS和U饮用水 强心脏砷和铀终身(SAUL)队列(项目3)的暴露概况 水中金属浓度、用水和详细住宅的空间和时间变异性和趋势 来自所有Shaul地点的部落参与者的尿液接触史。我们还将评估 政策干预对饮用水砷和铀暴露的影响，包括因水变化造成的影响 关于CWSS中污染物浓度的AS MCL的来源和使用，以及实施 使用点过滤。综合起来，我们的数据和模型将提供对环境的更好理解 CUNP-SRP将有害金属混合物的健康影响联系起来所需的暴露 (项目3和4)，确定清洁水的缓解途径(项目5)，并允许社区 参与和管理核心，使环境数据及其解释可供 这些部落社区。归根结底，这些努力在数据收集、建模和其他数据方面的结果 分析将有助于识别高危人群并制定有效的干预措施，以减少潜在的危险 在北部平原及其他地区暴露于受污染的饮用水。

Project 1 Summary The long-running Strong Heart Study documented high urinary arsenic (As) and uranium (U) levels in Native American tribal study sites relative to the general US population. Elevated exposures to metals and metalloids (hereafter metals) potentially contribute to the epidemic of cardiometabolic disease affecting tribal and other rural communities in the US. In rural communities of the Northern Plains, drinking water is commonly derived from unregulated and largely unmonitored private wells or public water systems that draw from the same aquifers. Much of the As and U exposure likely results from elevated levels of metals in groundwater sources. However, groundwater data are relatively scarce for rural communities, especially from tribal regions, making it difficult to identify groundwater hazards, and to mitigate their exposures. Project 1 of the Columbia University Northern Plains Superfund Research Program (CUNP-SRP) uses a two-pronged approach to address a critical gap in our understanding of the distribution of groundwater contamination and exposure across rural areas including Native American tribal areas. First, we will integrate existing and new measurements of groundwater composition data with prior large mineralogical and chemical speciation data sets. Second, we will use a combination of groundwater composition in wells and remotely sensed hydrological and other variables to develop machine learning-based predictive models of groundwater contaminant levels at the household scale—the foundational data needed for exposure assessment. We have 3 specific aims. Aim 1 will analyze drinking water sources from the CUNP-SRP field areas to identify and better understand the mobilization mechanisms of As and U into drinking water. Aim 2 will develop process-based models that predict As and U drinking water concentrations at the household scale across the Northern Plains. Aim 3 will develop and validate As and U drinking water exposure profiles for the Strong Heart Arsenic and Uranium Lifelong (SHAUL) cohort (for Project 3) by comparing spatial and temporal variability and trends in water metal concentrations, water use, and detailed residential histories with urinary-based exposures for tribal participants from all SHAUL locations. We will also evaluate the impact of policy interventions on drinking water As and U exposures, including those from changes in water sources and use, implementation of As MCL on contaminant concentrations in CWSs, and implementation of point-of-use filtration. Combined, our data and models will provide improved understanding of environmental exposures that is needed for the CUNP-SRP to contextualize the health effects of hazardous metal mixtures (Projects 3 and 4), to identify mitigation pathways to clean water (Project 5), and to allow the Community Engagement and Administrative Cores to make the environmental data and their interpretations accessible to these tribal communities. Ultimately, the results of these efforts in data collection, modeling, and additional data analysis will help identify at-risk populations and develop effective interventions to reduce potentially dangerous exposures to contaminated drinking water in the Northern Plains and beyond.