Project 6: Optimizing Sampling and Statistical Analysis for Hazardous Waste Site

项目6：危废场优化采样及统计分析

• 批准号: 7932380
• 负责人: Brent Andrew Coull
• 金额: $ 11.55万
• 依托单位: HARVARD SCHOOL OF PUBLIC HEALTH
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-04-12 至 2014-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7932380
• 关键词: Accounting; Area; Arsenic; Biological Markers; Biological Monitoring; Budgets; Cadmium; Communities; Data; Epidemiologist; Exposure to; Goals; Hazardous Waste Sites; Health; Heterogeneity; Individual; Investigation; Lead; Manganese; Measurement; Measures; Metal exposure; Methods; Modeling; Oklahoma; Outcome; Proxy; Risk; Risk Assessment; Sampling; Site; Software Tools; Soil; Statistical Methods; Statistical Models; Superfund; Tars; Uncertainty; Water; Work; Zinc; base; cost; design; improved; interest; model design; remediation; software development; superfund site; tool; wasting

Site assessment is a key aspect of understanding the risks of and planning remediafion of hazardous waste sites. Budget constraints, site heterogeneity and uncertainties in assessing exposure complicate assessment. The ideal approach also varies according to the purpose. From a regulatory perspective, goals include general characterization of a site, estimating mean levels for risk assessment, planning remediation, and assessing compliance. In contrast, environmental epidemiologists are interested in estimating individual exposures as accurately as possible to study associations with health outcomes. The objective of this project is to provide statistical design and analysis tools to improve the accuracy and reliability of site and exposure assessment for Superfund hazardous waste sites. Our approach is based on statistical modeling, along with optimal design considerations that maximize prediction accuracy while minimizing cost and accounting for practical considerations. Building on the basic spatial kriging model, our spatial model-based approach to design and analysis will be compared to existing design-based approaches that do not account for spatial correlation. We will extend these to complicated real-worid settings, including the use of previous targeted samples and non-detect, proxy and composite samples, which may allow a reduction in sampling costs. At the megasite scale, we will relate soil concentrations to biomarker levels in the Tar Creek Superfund site, and develop spatial measurement error models for relating environmental concentrations to exposure as measured by biomarkers? thus, accounting for incomplete environmental sampling. We will clarify under what circumstances a spatial model-based approach provides real benefits in pracfice, reducing cost and uncertainty. To make spatial-model based methods accessible to the site-assessment community, we will develop software tools for use by EPA and site professionals.

场地评估是了解危险废物风险和规划危险废物补救措施的一个关键方面 网站.预算限制、场地异质性和暴露评估的不确定性使情况复杂化 考核理想的方法也因目的而异。从监管角度看，目标 包括场地一般特性、估计风险评估的平均水平、规划补救措施， 并评估遵守情况。与此相反，环境流行病学家感兴趣的是估计个人 尽可能准确地研究暴露与健康结果的关系。的目的 项目的目的是提供统计设计和分析工具，以提高网站的准确性和可靠性， 超级基金危险废物场址的接触评估。我们的方法是基于统计建模， 沿着最佳设计考虑，最大化预测精度，同时最小化成本， 考虑到实际情况。在基本空间克里金模型的基础上，我们基于空间模型的 设计和分析的方法将与现有的基于设计的方法进行比较，这些方法不考虑 空间相关性。我们将把这些扩展到复杂的现实世界的设置，包括使用以前的 目标样本和非检测样本、替代样本和复合样本，这可能会减少采样 成本在巨岩点尺度上，我们将把焦油溪的土壤浓度与生物标志物水平联系起来 建立空间测量误差模型，将环境浓度与 通过生物标志物测量的暴露量？因此，说明环境取样不完整。我们将 澄清在何种情况下，基于空间模型的方法在实践中提供了真实的好处， 成本和不确定性。为了使基于空间模型的方法为场地评估界所利用， 我们将开发软件工具供EPA和现场专业人员使用。