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Uncertainty in the design of the measurement frameworks underlying GIS-based human health risk assessment models.

机译:基于GIS的人类健康风险评估模型的度量框架的设计不确定性。

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摘要

GIS-based human health risk assessment (GIS-based HHRA) refers to the integration of GIS with risk assessment modeling for purposes of generating spatially-differentiated risk estimates for specific receptor populations. The use of GIS-based HHRA models allow more representative individual and population risk estimates to be generated due to the explicit consideration for the spatial distribution of chemical concentrations in impacted media as well as the spatial distribution of receptor populations across study areas. Having more representative and spatially-refined estimates of individual and population risk can improve risk-based decision making by decreasing the degree of uncertainty associated with these estimates thereby increasing confidence in the risk-based decisions that are made. Despite the potential of GIS-based HHRA models to enhance environmental and public health decision making, little research has been conducted into the design of these models including the impact that different model designs can have on risk results and risk-based decision making.; Research presented in this dissertation examines this issue of GIS-based HHRA model design and more specifically, the design of the GIS-based measurement frameworks underlying these models. These measurement frameworks are responsible for integrating spatial data coverages and generating spatially-explicit risk estimates for modeled receptor populations. This research demonstrates that, under certain circumstances, the design of the measurement frameworks can significantly impact risk results and the risk-based decisions made using these models. These findings point to the importance of considering measurement framework design uncertainty along with other sources of uncertainty in designing and using GIS-based HHRA models to support environmental decision making. This dissertation research was conducted using five hazardous waste combustion (HWC) test case facilities.
机译:基于GIS的人类健康风险评估(基于GIS的HHRA)是指GIS与风险评估模型的集成,目的是生成特定受体群体的空间差异化风险估计。基于GIS的HHRA模型的使用,由于明确考虑了受影响介质中化学浓度的空间分布以及整个研究区域中受体种群的空间分布,因此可以生成更具代表性的个人和种群风险估计。对个人和人口风险进行更具代表性和空间优化的估计,可以通过降低与这些估计相关的不确定性程度,从而提高对基于风险的决策的信心,从而改善基于风险的决策。尽管基于GIS的HHRA模型具有增强环境和公共卫生决策的潜力,但对这些模型的设计却很少进行研究,包括不同模型设计可能对风险结果和基于风险的决策产生的影响。本文提出的研究探讨了基于GIS的HHRA模型设计的问题,更具体地说,研究了基于这些模型的基于GIS的测量框架的设计。这些测量框架负责整合空间数据覆盖范围,并为建模的受体群体生成空间明确的风险估计。这项研究表明,在某些情况下,度量框架的设计会显着影响风险结果以及使用这些模型做出的基于风险的决策。这些发现表明,在设计和使用基于GIS的HHRA模型来支持环境决策时,必须考虑测量框架设计不确定性以及其他不确定性来源。本论文的研究是利用五个危险废物燃烧(HWC)测试案例设施进行的。

著录项

  • 作者

    Pekar, Zachary.;

  • 作者单位

    The University of North Carolina at Chapel Hill.;

  • 授予单位 The University of North Carolina at Chapel Hill.;
  • 学科 Environmental Sciences.; Health Sciences Public Health.
  • 学位 Ph.D.
  • 年度 2003
  • 页码 161 p.
  • 总页数 161
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 环境科学基础理论;预防医学、卫生学;
  • 关键词

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