Relating soil geochemical properties to arsenic bioaccessibility through hierarchical modeling

ABSTRACT

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 % basis. The hierarchical approach improved the estimation of As bioaccessibility in studied soils. In addition, the number of soil elements identified as statistically significant explanatory variables increased when compared to previous investigations. 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 % model. This developed hierarchical approach provides a novel tool to (1) explore relationships between soil properties and As bioaccessibility across a broad range of soil types and As contaminant sources encountered in the environment and (2) identify areas of future mechanistic research to better understand the complexity of interactions between soil properties and As bioaccessibility.

KEYWORDS:

• soil
• arsenic
• bioaccessibility
• hierarchical modeling
• properties

Acknowledgments

The US Environmental Protection Agency (U.S. EPA), through its Office of Research and Development, funded and performed this research. This article has been reviewed in accordance with the policy of the National Exposure Research Laboratory, U.S. EPA, and approved for publication. The views expressed in this paper are those of the authors and do not necessarily represent the views or policies of the Agency. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.

Supplementary Material

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