High Resolution Models of Groundwater Metal Exposures

地下水金属暴露的高分辨率模型

• 批准号: 10707888
• 负责人: Steven N. Chillrud
• 金额: $ 30.35万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-21 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10707888
• 关键词: Address; Affect; Area; Arsenic; Cardiometabolic Disease; Chemicals; Cheyenne; Cohort Studies; Communities; Dangerousness; Data; Data Analyses; Data Collection; Data Set; Development; Environmental Exposure; Environmental Pollution; Environmental Risk Factor; Epidemic; Evaluation; Exposure to; Filtration; Future; Goals; Health; Heart; Household; Individual; Intervention; Isotopes; Length; Location; Measurement; Measures; Metal exposure; Metals; Methods; Modeling; Native Americans; Nitrates; Northern Plains Tribe; Oxidation-Reduction; Participant; Pathway interactions; Policies; Population; Populations at Risk; Privatization; Probability; Process; Publications; Recording of previous events; Research; Resolution; Resources; Role; Running; Rural Community; Sioux Indians; Site; Source; South Dakota; Southeastern Asia; Spatial Distribution; Superfund; Surface; Surveys; System; Testing; Time trend; Toxicology; Tribes; Universities; Uranium; Water; Water Supply; anthropogenesis; cohort; community engagement; contaminated drinking water; cooking; density; drinking; drinking water; effective intervention; geochemistry; ground water; hazard; hydrology; improved; interest; machine learning model; machine learning prediction; member; meter; northern Native American; oxidation; predictive modeling; programs; remediation; remote sensing; rural area; trend; tribal community; urinary; water quality

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.

项目1摘要 长期的强心研究记录了高尿砷（As）和铀（U）水平， 美国部落研究地点相对于美国一般人口。金属和类金属暴露增加 （以下简称金属）可能导致影响部落和其他农村地区的心脏代谢疾病流行。 美国的社区。在北方平原的农村社区，饮用水通常来自 不受管制和基本上不受监测的私人威尔斯井或从同一含水层取水的公共供水系统。 大部分的砷和铀接触可能是由于地下水源中金属含量升高。然而，在这方面， 农村社区，特别是部落地区的地下水数据相对缺乏， 查明地下水危害，并减轻其风险。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）采用双管齐下的方法来解决我们的关键差距， 了解农村地区地下水污染的分布和暴露情况，包括土著居民 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 与之前的大型矿物学和化学形态数据集。第二，我们将结合使用 地下水成分在威尔斯和遥感水文和其他变量开发机 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将分析饮用水源， * CUNP-SRP外地领域，以确定和更好地了解A和U的动员机制， 饮用水目标2将开发基于过程的模型，预测As和U饮用水浓度， 整个北方平原的家庭规模。目标3将开发和验证砷和铀饮用水 强心砷和铀终身（SHAUL）队列（项目3）的暴露概况， 水金属浓度、水利用和详细的居住区的空间和时间变化和趋势 来自所有SHAUL地点的部落参与者的尿液暴露史。我们还将评估 政策干预对饮用水砷和铀暴露的影响，包括来自水变化的影响 污染物的来源和使用，实施关于化学武器系统中污染物浓度的As MCL，以及实施 使用点过滤。结合起来，我们的数据和模型将提供更好的理解环境 CUNP-SRP所需的暴露，以了解有害金属混合物对健康的影响 （项目3和4），确定清洁水的缓解途径（项目5），并允许社区 参与和行政核心，使环境数据及其解释易于访问 这些部落社区。最终，这些努力在数据收集、建模和附加数据方面的成果 分析将有助于识别风险人群，并制定有效的干预措施，以减少潜在的危险 在北方平原和更远的地方暴露于受污染的饮用水。