BackgroundDietary exposure from food to toxic inorganic arsenic (iAs) in the general U.S. population has not been well studied.ObjectivesThe goal of this research was to quantify dietary As exposure and analyze the major contributors to total As (tAs) and iAs. Another objective was to compare model predictions with observed data.MethodsProbabilistic exposure modeling for dietary As was conducted with the Stochastic Human Exposure and Dose Simulation–Dietary (SHEDS-Dietary) model, based on data from the National Health and Nutrition Examination Survey. The dose modeling was conducted by combining the SHEDS-Dietary model with the MENTOR-3P (Modeling ENvironment for TOtal Risk with Physiologically Based Pharmacokinetic Modeling for Populations) system. Model evaluation was conducted via comparing exposure and dose-modeling predictions against duplicate diet data and biomarker measurements, respectively, for the same individuals.ResultsThe mean modeled tAs exposure from food is 0.38 μg/kg/day, which is approximately 14 times higher than the mean As exposures from the drinking water. The mean iAs exposure from food is 0.05 μg/kg/day (1.96 μg/day), which is approximately two times higher than the mean iAs exposures from the drinking water. The modeled exposure and dose estimates matched well with the duplicate diet data and measured As biomarkers. The major food contributors to iAs exposure were the following: vegetables (24%); fruit juices and fruits (18%); rice (17%); beer and wine (12%); and flour, corn, and wheat (11%). Approximately 10% of tAs exposure from foods is the toxic iAs form.ConclusionsThe general U.S. population may be exposed to tAs and iAs more from eating some foods than from drinking water. In addition, this model evaluation effort provides more confidence in the exposure assessment tools used.

High dimensional model representation is under active development as a set of quantitative model assessment and analysis tools for capturing high-dimensional input-output system behavior based on a hierarchy of functions of increasing dimensions. The HDMR component functions are optimally constructed from zeroth order to higher orders step-by-step. This paper extends the definitions of HDMR component functions to systems whose input variables may not be independent. The orthogonality of the higher order terms with respect to the lower order ones guarantees the best improvement in accuracy for the higher order approximations. Therefore, the HDMR component functions are constructed to be mutually orthogonal. The RS-HDMR component functions are efficiently constructed from randomly sampled input-output data. The previous introduction of polynomial approximations for the component functions violates the strictly desirable orthogonality properties. In this paper, new orthonormal polynomial approximation formulas for the RS-HDMR component functions are presented that preserve the orthogonality property. An integrated exposure and dose model as well as ionospheric electron density determined from measured ionosonde data are used as test cases, which show that the new method has better accuracy than the prior one.

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Copper is an essential trace element and adverse health effects can potentially be associated with both very low and very high intakes. Accurate estimates of inhalation and ingestion (food and drinking water) exposures are therefore needed in order to realistically assess any effects of the distribution of copper intakes within the general population. The work presented here demonstrates an application of a customized subset of the MENTOR/SHEDS-4M computational system (Modeling ENvironment for TOtal Risk studies, employing the Stochastic Human Exposure and Dose Simulation approach, for Multimedia, Multipathway, Multiroute exposures to Multiple co-occurring contaminants. The application utilized data from the National Human Exposure Assessment Survey (NHEXAS) for USEPA Region V as well as from a variety of other available databases. The case study, using a statistical population-based modeling framework, was performed for Eaton County, MI. The results of the simulations, aggregated for six age subgroups of the general population, suggest that food intake is the major pathway for total copper exposure, while drinking water can have significant contributions at the tail of the distribution of intakes. Specifically, it was estimated that over 80% of the county population received potential doses of copper from food that were lower than the Institute of Medicine (IOM) Recommended Dietary Allowance (RDA) value of 900 microg/day. Furthermore, the total combined potential dose from food and water was only about two times greater than the recommended value only for individuals with intakes in the range above the 99th percentile of both food and water intakes. The values were well below the upper tolerable intake value of 10,000 microg/day. The inhalation route consistently acted as only a minor contributor to the total exposure.

In this article, we present a critical review of the reported performance of reverse osmosis (RO) and capacitive deionization (CDI) for brackish water (salinity < 5.0 g/L) desalination from the aspects of engineering, energy, economy and environment. We first illustrate the criteria and the key performance indicators to evaluate the performance of brackish water desalination. We then systematically summarize technological information of RO and CDI, focusing on the effect of key parameters on desalination performance, as well as energy-water efficiency, economic costs and environmental impacts (including carbon footprint). We provide in-depth discussion on the interconnectivity between desalination and energy, and the trade-off between kinetics and energetics for RO and CDI as critical factors for comparison. We also critique the results of technical-economic assessment for RO and CDI plants in the context of large-scale deployment, with focus on *Manuscript Click here to view linked References 2 lifetime-oriented consideration to total costs, balance between energy efficiency and clean water production, and pretreatment/post-treatment requirements. Finally, we illustrate the challenges and opportunities for future brackish water desalination, including hybridization for energy-efficient brackish water desalination, co-removal of specific components in brackish water, and sustainable brine management with innovative utilization. Our study reveals that both RO and CDI should play important roles in water reclamation and resource recovery from brackish water, especially for inland cities or rural regions.