Interconnected soil iron and arsenic speciation effects on arsenic bioaccessibility and bioavailability: a scoping review

Abstract

Extensive research has examined arsenic (As) bioavailability in contaminated soils and is routinely assessed using in vitro bioaccessibility (IVBA) assays. Analysis of differences in bioaccessibility measurements across IVBA assays and phases is expected to provide valuable insights into geochemical mechanisms controlling soil As bioaccessibility and bioavailability. Soil iron (Fe) content and As speciation are expected to significantly influence IVBA gastric and intestinal phases due to fluctuations in precipitation-dissolution chemistry and sorption reactivity as pH and assay chemical complexity changes. The aim of this review was to examine these relationships by 1) conducting a meta-analysis (n = 47 soils) determining the influence of total Fe on As bioaccessibility measurements and 5 IVBA assays and 2) investigating the effect of As speciation on gastric/intestinal phase IVBA and in vitro-in vivo correlations. Our findings indicate that soil Fe content and As speciation heterogeneity are important in elucidating variability of bioaccessibility measurements across IVBA assays and gastrointestinal phases. Greater focus on coupled As speciation and Fe precipitation chemistry may (1) improve our understanding of soil geochemical factors and assay constituents that influence As in vitro-in vivo correlations and (2) resolve variability in the precision of oral relative bioavailability (RBA) estimated using IVBA assays for soils possessing heterogenous As speciation and Fe composition.

Keywords: Arsenic; bioaccessibility; bioavailability; coprecipitation; iron; meta-analysis; sorption; speciation.

Figure 1.

Box and whisker plots showing variability in mean (x), median (horizontal line), lower and upper quartile (end of boxes) and extreme (whiskers) % in vitro bioaccessibility (IVBA) values (by assay and phase), and % relative bioavailability (RBA) measurements for the 47 soils included in the meta-analysis. All IVBA assays shown include data for the gastric (-G) and intestinal (-I) assay phases

Figure 2.

Conceptual model showcasing expected bioaccessibility of As phases ranging from least to greatest based on current literature (left, middle; adapted from Meunier et al. 2010). We then compare this to a range of processes that may facilitate changes in bioaccessibility measurements (right) but require further investigation

Figure 3.

Magnitude and pH-dependency of As(V) (arsenate – ∆) and as(III) (arsenite – ○) adsorption to ferrihydrite (green) and goethite (yellow) at an initial concentration of 100 mM (7.5 g As/L) as (data taken from Dixit and Hering 2003). Sorbent concentration was 0.03 g L⁻¹ hydrous ferric oxide and 0.5 g L⁻¹ goethite compared to the IVBA pH ranges of the gastric and intestinal phases

Figure 4.

Change in % IVBA from gastric to intestinal phase across the 5 IVBA assays evaluated (n = 47 soil for SBRC, IVG, PBET, and DIN; n = 35 soils for UBM). Positive values represent an increase in IVBA from gastric to intestinal phase within an assay, whereas negative values represent a decrease

Figure 5.

Relationship between total soil Fe (x-axis) and relative percent difference (RPD) in As IVBA from gastric to intestinal phase (y-axis) by assay

Figure 6.

Relationship between total soil Fe (x-axis) and coefficient of variation (CoV) in measured soil as IVBA (y-axis) across 10 IVBA assays/phases (5 assays x 2 phases per assay) for a) gastric and intestinal phases (GP and IP, respectively) combined, b) gastric only assays, and c) intestinal only assays)

Figure 7.

In vitro – in vivo correlation (IVIVC) residuals in (a) gastric and (b) intestinal phase IVBA assays reported by Juhasz et al. (2014) (n = 10 soils) for each of the five assays. Soils labeled 1 through 5 contain As(V) only, whereas soils 6 through 10 contain a mixture of As(V) and As(III). Residuals, in this context, represent the difference between the directly measured % IVBA value for a given soil and the predicted value based on the fitted linear regression line. Generally, the closer to zero the residual, the more accurate the prediction of RBA for that particular soil and assay