A Pooled Data Analysis to Determine the Relationship between Selected Metals and Arsenic Bioavailability in Soil

Kaihong Yan, Ravi Naidu, Yanju Liu, Ayanka Wijayawardena, Luchun Duan and Zhaomin Dong
Additional contact information
Kaihong Yan: Global Centre for Environmental Remediation, the Faculty of Science and Information Technology, University of Newcastle, University Drive, Callaghan, NSW 2308, Australia
Ravi Naidu: Global Centre for Environmental Remediation, the Faculty of Science and Information Technology, University of Newcastle, University Drive, Callaghan, NSW 2308, Australia
Yanju Liu: Global Centre for Environmental Remediation, the Faculty of Science and Information Technology, University of Newcastle, University Drive, Callaghan, NSW 2308, Australia
Ayanka Wijayawardena: Global Centre for Environmental Remediation, the Faculty of Science and Information Technology, University of Newcastle, University Drive, Callaghan, NSW 2308, Australia
Luchun Duan: Global Centre for Environmental Remediation, the Faculty of Science and Information Technology, University of Newcastle, University Drive, Callaghan, NSW 2308, Australia
Zhaomin Dong: Global Centre for Environmental Remediation, the Faculty of Science and Information Technology, University of Newcastle, University Drive, Callaghan, NSW 2308, Australia

IJERPH, 2018, vol. 15, issue 5, 1-10

Abstract: Chronic exposure to arsenic (As) is a global concern due to worldwide exposure and adverse effects, and the importance of incorporating bioavailability in the exposure assessment and risk assessment of As is increasing acknowledged. The bioavailability of As is impacted by a number of soil properties, such as pH, clay and metal concentrations. By retrieving 485 data from 32 publications, the aim of this study was to determine the relationship between selected metals (Fe and Al) and As bioavailability. In present study, the bioaccessibility (BAC) data measured by in vitro approaches were converted into bioavailability data based on the previously determined relationship between BAC and bioavailability. The As relative bioavailability (RBA) was summarized to be 24.36 ± 18.49%, which is in the range previously reported. A significant association between Fe concentration and the bioavailability of As was observed while this association varied for different types of RBA data. This disparity may suggest a non-reliable association between Fe and As bioavailability. The correlations between logarithmically transformed total content of Fe + Al and As bioavailability is then outlined: RBA = (−8.40 ± 1.02) × Ln(Fe + Al) + (58.25 ± 4.09), R 2 = 0.25, p < 0.001, n = 212. Jackknife resampling was also applied to validate the relation between total content of (Fe + Al) and As bioavailability, which suggested that the relation is robust. This is the first pooled study to address the relations between selected metal concentrations and As bioavailability, which may provide some implications to establish soil properties-based RBA prediction for As.

Keywords: arsenic; bioavailability; soil properties; pooled study (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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