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The long-term objective of this research project is to characterize multi-pollutant (arsenic, lead, cadmium, and chromium) human exposures by linking sources to biomarkers using a multi-scale (individual level, county level) hierarchical Bayesian model (HBM) that describes how multi-media pathways contribute to direct routes of exposure. Our approach is to use a statistical model that has explicit stages for pollutant sources, global and local environmental levels, personal exposures, and biomarkers. By analyzing these stages simultaneously, we provide an analysis of exposure pathways from the sources of toxic substances in the environment to biomarker levels observed in individuals. The complexity of our approach, in terms of levels of hierarchy, variety of (misaligned) data sources, and computational requirements, illustrates what is now possible using hierarchical Bayesian models. Our HBM draws on individual-specific measurements from the National Human Exposure Assessment Survey (NHEXAS) Phase I, supplemented by arsenic concentration measurements in topsoil and stream sediments. We focus on arsenic and its air, soil, water, and food pathways of exposure for individuals in the U.S. Environmental Protection Agency's Region 5 -Illinois, Indiana, Michigan, Minnesota, Ohio, and Wisconsin. After fitting the HBM, we report on the relative importance of the different pathways of arsenic exposure. In addition, we provide a discussion of generalizations to more complicated pathways, other regions, and a multivariate model.

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In this paper we present a proposed semi-quantitative approach for assessing the integrity of active and retired oil and gas wells in example study areas for siting geologic carbon storage repositories. The approach makes use of readily available wellbore information and is illustrated with study areas in Ohio and Michigan. Results help depict wellbore integrity issues in a region that has numerous oil and gas wells dating back to the 1800s. We first reviewed readily available sources of information and identified three key well condition indicators that might be expected to impact wellbore integrity -wellbore age, depth and status. Each of these indicators was then coded for each available well with a simple scale representing increasing levels of expected wellbore integrity and combined to form a composite integrity score. The resulting composite indicators provide a useful tool to help identify areas where existing wells tend to be newer, shallower, and plugged and abandoned-all of these being conditions more favorable for repository siting. When considered in combination with maps showing the depth of targeted geologic confining layers and maps indicating the density of existing wells (i.e., the number of existing wells per 1 km 2 grid cell), the maps of wellbore integrity provide a more complete evaluation of different areas for repository siting. Study areas in Ohio and Michigan were evaluated and pros and cons of each area are discussed to help illustrate the utility of this proposed wellbore integrity approach. The approach proposed here makes use of reasonably extensive and readily available information, and combines it in a systematic and objective way, creating an intuitive tool to assist with repository siting.