Relating soil geochemical properties to arsenic bioaccessibility through hierarchical modeling (original) (raw)

2018, Journal of Toxicology and Environmental Health

Interest in improved understanding of relationships among soil properties and arsenic (As) bioaccessibility has motivated the use of regression models for As bioaccessibility prediction. However, limits in the numbers and types of soils included in previous studies restrict the usefulness of these models beyond the range of soil conditions evaluated, as evidenced by reduced predictive performance when applied to new data. In response, hierarchical models that consider variability in relationships among soil properties and As bioaccessibility across geographic locations and contaminant sources were developed to predict As bioaccessibility in 139 soils on both a mass fraction (mg/kg) and percent basis. The hierarchical approach improved the estimation of As bioaccessibility in study soils. Additionally, the number of soil elements identified as statistically significant explanatory variables increased when compared to previous studies. Specifically, total soil Fe, P, Ca, Co and V were significant explanatory variables in both models, while total As, Cd, Cu, Ni and Zn were also significant in the mass fraction model and Mg was significant in the percent model. The hierarchical approach developed in this study provides a novel tool to explore relationships between soil properties and As bioaccessibility across a broad range of soil types and As contaminant sources encountered in the environment and identifies areas of future mechanistic research to better understand the complexity of interactions between soil properties and As bioaccessibility.

The Link between Soil Geochemistry in South-West England and Human Exposure to Soil Arsenic

Minerals

The aim of this research is to use the whole soil geochemistry and selected bioaccessibility measurements, using the BioAcessibility Research Group of Europe (BARGE) method, on the same soils to identify the geochemical controls on arsenic (As) bioaccessibility and to gain an understanding of its spatial distribution in south-west England. The total element concentrations of 1154 soils were measured with As concentrations ranging from 4.7–1948 mg·kg−1, with the bioaccessible As of 50 selected soils ranging from 0.6–237 mg·kg−1. A Self Modelling Mixture Resolution approach was applied to the total soil element chemistry to identify the intrinsic soil constituents (ISCs). The ISCs were used as predictor variables and As bioaccessibility as the dependant variables in a regression model for the prediction of As bioaccessibility at all soil locations to examine its regional spatial distribution. This study has shown that bioaccessibility measurements can be directly linked to the geochem...

Independent Data Validation of an in Vitro Method for the Prediction of the Relative Bioavailability of Arsenic in Contaminated Soils

Environmental science & technology, 2015

In vitro bioaccessibility (IVBA) assays estimate arsenic (As) relative bioavailability (RBA) in contaminated soils to improve accuracy in human exposure assessments. Previous studies correlating soil As IVBA with RBA have been limited by the use of few soil types and sources of As, and the predictive value of As IVBA has not been validated using an independent set of As-contaminated soils. In this study, a robust linear model was developed to predict As RBA in mice using IVBA, and the predictive capability of the model was independently validated using a unique set of As-contaminated soils. Forty As-contaminated soils varying in soil type and contaminant source were included in this study, with 31 soils used for initial model development and nine soils used for independent model validation. The initial model reliably predicted As RBA values in the independent data set, with a mean As RBA prediction error of 5.4%. Following validation, 40 soils were used for final model development, ...

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