Spatial patterns of metals and metal mixtures in drinking water
饮用水中金属和金属混合物的空间格局
基本信息
- 批准号:10559491
- 负责人:
- 金额:$ 16.75万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-02-21 至 2025-01-31
- 项目状态:未结题
- 来源:
- 关键词:5 year oldAddressAffectArchivesArsenicBiomedical ResearchBrainCadmiumChildChromiumCognitiveCognitive agingColoradoConsumptionCountryDataDatabasesDevelopmentDiagnosisEffectivenessElderlyElementsExposure toGeographic LocationsGeological SurveyGoalsGuidelinesHealthHeavy MetalsHybridsImmunosuppressionIn VitroIndividualInformation SystemsLeadLinkLocationMalignant NeoplasmsManganeseMapsMeasurementMetal exposureMetalsMethodsModelingMunicipalitiesNurses&apos Health StudyOrganoidsOxidation-ReductionPatternPersonsPoisonPopulationPrivatizationProcessPropertyProspective cohortPublic HealthRegulationResearchResearch PriorityRiskRisk AssessmentRoleSamplingSeleniumSiteSoilSourceSuperfundSurfaceSystemTechnologyTestingTimeToxicity TestsTrace metalTrainingTreatment EffectivenessUnited StatesWaterWater PollutantsWater SupplyWomanWorkcommunity engagementcontaminated drinking watercontaminated waterdisease registrydrinking waterearly life exposureeffectiveness evaluationexposed human populationgeochemistryground waterhigh riskimprovedinnovative technologiesinsightland usemachine learning algorithmneurodevelopmentnovelremediationrisk mitigationsuperfund sitetoolwater qualitywater samplingwater treatment
项目摘要
PROJECT SUMMARY/ABSTRACT
In 2016, approximately 15 million people lived within one mile of Superfund sites, including approximately 5% of
all children in the United States (US) under 5 years of age. Lead (Pb), arsenic (As), and cadmium (Cd) are
among the top ten contaminants on the Agency for Toxic Substances and Disease Registry’s 2017 Substances
Priorities List for Superfund sites. These and other metals/metalloids can contaminate surface waters and
groundwater systems, leading to elevated exposures through drinking water. Across the US, tens of millions of
individuals consume drinking water with concentrations of heavy metals in excess of regulatory guidelines.
Exposures to heavy metals have been associated with many negative impacts on public health, including impacts
on neurodevelopment and cognitive aging. However, the contribution of different Superfund sites to this
contamination problem remains poorly characterized on a national scale. This is important because regulations
for drinking water contaminants and risk mitigation actions are often undertaken at the federal level, but most
prior work has focused on site-specific studies. Proximity to Superfund sites may be associated with higher risk
of contamination by heavy metal mixtures in tap water. This relationship is likely more prominent in private wells
than in municipal drinking water supplies, where the finished water quality is influenced by water treatment
technologies. Across different geographic areas, there are considerable differences in municipal water treatment
technology and continuous development of innovative technologies, but little information is available on how this
affects spatial patterns of metal concentrations in tap water. In Aim 1, we will characterize the role of Superfund
sites across the country for heavy metals in private wells by developing novel hybrid mechanistic-empirical
models for heavy metals across the US using a large database of measurements in groundwater from the USGS,
locations of point sources such as Superfund sites, and hydrogeological features/predictors that affect the fate
and transport of trace metals. For Aim 2, we will use new measurements and models to identify the spatial co-
occurrence of different metal mixtures relevant to human exposures from drinking water. This analysis will be
used to identify the composition of metal mixtures for in vitro toxicity tests on brain organoids in Project 2. Aim 3
will leverage >28 million measurements of heavy metals from municipal water supplies to field-evaluate the role
of different treatment technologies. This will provide insights into the effectiveness of treatment technologies and
can help inform Project 4 as well as Superfund site managers responsible for remediation. This project provides
a link between biomedical research in the MEMCARE Center, human exposures, and potential benefits of
remediation technology being developed in Project 4.
项目摘要/摘要
2016年,约有1500万人居住在超级基金网站一英里以内,其中约5%
美国所有5岁以下的儿童。铅(铅)、砷(砷)和镉(镉)
有毒物质和疾病登记局2017年物质排名前十的污染物
超级基金网站的优先事项列表。这些金属和其他金属/类金属会污染地表水和
地下水系统,导致通过饮用水暴露的增加。在美国各地,数千万人
个人饮用的饮用水中重金属浓度超过了规定的标准。
暴露于重金属会对公众健康产生许多负面影响,包括影响
关于神经发育和认知老化。然而,不同的超级基金网站对此的贡献
污染问题在全国范围内仍然没有得到很好的描述。这一点很重要,因为法规
对于饮用水污染物和风险缓解行动,通常是在联邦一级采取的,但大多数
之前的工作主要集中在特定地点的研究上。靠近超级基金网站可能与更高的风险相关
自来水中重金属混合物的污染。这种关系在私人油井中可能更加突出。
在城市饮用水供应中,成品水的质量受水处理的影响
技术。在不同的地理区域,城市水处理存在相当大的差异
技术和创新技术的不断发展,但关于这一点如何实现的信息很少
影响自来水中金属浓度的空间模式。在目标1中,我们将描述超级基金的角色
通过开发新的混合机制-经验方法,在全国各地的私人油井中寻找重金属
使用美国地质勘探局地下水测量的大型数据库对全美各地的重金属进行建模,
点源的位置,如超级基金地点,以及影响命运的水文地质特征/预测因素
以及痕量金属的运输。对于目标2,我们将使用新的测量和模型来识别空间协同
与人体从饮用水中暴露有关的不同金属混合物的出现。这一分析将是
用于确定项目2中用于脑有机化合物体外毒性试验的金属混合物的组成。目标3
将利用来自市政供水的2800万个重金属测量数据来现场评估这一角色
不同的处理技术。这将提供对处理技术和
可以帮助告知项目4以及负责补救的Superfund站点经理。该项目提供了
MEMCARE中心的生物医学研究、人类暴露和
项目4中正在开发的补救技术。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Elsie Mareca Sunderland其他文献
Elsie Mareca Sunderland的其他文献
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{{ truncateString('Elsie Mareca Sunderland', 18)}}的其他基金
Spatial patterns of metals and metal mixtures in drinking water
饮用水中金属和金属混合物的空间格局
- 批准号:
10332731 - 财政年份:2020
- 资助金额:
$ 16.75万 - 项目类别:
Spatial patterns of metals and metal mixtures in drinking water
饮用水中金属和金属混合物的空间格局
- 批准号:
10112927 - 财政年份:2020
- 资助金额:
$ 16.75万 - 项目类别:
Assessing the Contribution of Polyfluoroalkyl Precursors to Diverse PFAS Exposures near Contaminated Sites
评估多氟烷基前体对污染场地附近各种 PFAS 暴露的影响
- 批准号:
10352510 - 财政年份:2017
- 资助金额:
$ 16.75万 - 项目类别:
Assessing the Contribution of Polyfluoroalkyl Precursors to Diverse PFAS Exposures near Contaminated Sites
评估多氟烷基前体对污染场地附近各种 PFAS 暴露的影响
- 批准号:
10704007 - 财政年份:2017
- 资助金额:
$ 16.75万 - 项目类别:
Sources, Transport, Exposure and Effects of PFASs (STEEP)
PFAS 的来源、传输、暴露和影响 (STEEP)
- 批准号:
9904670 - 财政年份:
- 资助金额:
$ 16.75万 - 项目类别:
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