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Pore-water carbonate and phosphate as predictors of arsenate toxicity in soil Dane Lamb, Mohammed Kader, Liang Wang, Girish Choppala, Mohammad Mahmudur Rahman, Mallavarapu Megharaj, and Ravi Naidu Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b03195 • Publication Date (Web): 31 Oct 2016 Downloaded from http://pubs.acs.org on November 1, 2016

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Pore-water carbonate and phosphate as predictors of arsenate toxicity in soil

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Dane T Lamb1,2*, Mohammed Kader1,2, Liang Wang1,2, Girish Choppala3, Mohammad Mahmudur Rahman1,2, Mallavarapu Megharaj1,2, Ravi Naidu1,2

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Global Centre for Environmental Research (GCER), Faculty of Science and Information Technology, The University of Newcastle, Callaghan, Advanced Technology Building, NSW, 2308, Australia.

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Cooperative Research Centre for Contamination Assessment and Remediation of the Environment(CRC CARE), University of South Australia, Mawson Lakes, Bld X, SA 5095, Australia.

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Southern CrossGeoscience Southern Cross University, Lismore, NSW 2480, Australia.

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* Email: [email protected] Phone: +61 2 4913 8733

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Abstract

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Phytotoxicity of inorganic contaminants is influenced by the presence of competing ions at the site of uptake. In this study, interaction of soil pore-water constituents with arsenate toxicity was investigated in cucumber (Cucumis sativa L) using 10 contrasting soils. Arsenate phytotoxicity was shown to be related to soluble carbonate and phosphate. The data indicated that dissolved phosphate and carbonate had an antagonistic impact on arsenate toxicity to cucumber. To predict arsenate phytotoxicity in soils with a diverse range of soil solution properties, both carbonate and phosphate were required. The relationship between arsenic and pore-water toxicity parameters was established initially using multiple regression. In addition, based on the relationship with carbonate and phosphate we successively applied a terrestrial biotic ligand-like model (BLM) including carbonate and phosphate. Estimated effective concentrations from the BLM-like parameterisation were strongly correlated to measured arsenate values in pore-water (R2 =0.76, P < 0.001). The data indicates that an ion interaction model similar to the BLM for arsenate is possible, potentially improving current risk assessments at arsenic and co-contaminated soils.

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Key words: arsenate, biotic ligand model, BLM, anionic, toxicity, bioavailability

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Introduction

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Arsenic (As) is a major soil-borne toxicant globally and is well known to impact directly on

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human and ecological health 1. Many of the world’s greatest problems associated with As are

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due to mobilisation of As due to changes in hydrogeological conditions (e.g Bangladesh,

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West Bengal in India). Arsenic contaminated soil exists as a result of anthropogenic inputs

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from lead, zinc, arsenic, gold and silver mines, use as a pesticide in orchids and cattle dips,

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smelter fallout from processing metalliferous ore and from wood preservatives

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impact of As contamination in soil is known to be influenced by a range of biological and soil

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factors, including organism, species, and a range of soil properties.

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. The

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Despite As ecotoxicity being of significant research interest 3, our ability to model and

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predict As toxicity in terrestrial systems is lacking. This translates into inconsistencies in

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environmental guidance and management of contaminated sites. For example, a recent

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modification of the Australian regulatory soil quality guideline values has witnessed an

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increase from the previous 20 mg kg-1 As to between 40 and 160 mg kg-1, expressed on a

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total metal(loid) basis 40 and 160 mg kg-1 are for sensitive ecological and industrial areas,

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respectively). However, recently, EC10 values ranging from 23 – 395 and 5.5 to 330 mg kg-1

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to Lactuca sativa and Vibrio fischeri, respectively, have been reported 4. Similarly, in

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Australian soils, Kader et al. 5 reported EC20 and EC50 values of 7.8-160 and 17-440 mg kg-

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1

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values. The latter studies both reported a clear interaction with soil properties, which

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ultimately govern As toxicity in surficial soil layers via modification of solubility in soil

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solution. Risk assessment and soil guidance data should reflect the properties of soil

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influencing the bioavailability of As.

after 3 months ageing in a range of soils, with most soils falling below the new guideline

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Metal(loid) bioavailabilty to plants is influenced qualitatively by the presence of other

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potentially competing ions in soil solution 6. It has been demonstrated that the toxicity of

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cationic metals such as Cu2+, Zn2+ and Ni2+ from the aqueous phase are influenced by

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solution pH surrounding the root7-9. The biotic ligand model (BLM) interprets the variation as

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changes in H+ competition for binding sites at the site of toxicity. Similarly, modifications to

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toxicity and uptake are reported for other major cations, such as Ca2+ and Mg2+ due to

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competition. Developed BLMs are increasingly employed for cationic contaminants in an

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attempt to account for co-contaminated waters in terrestrial and aquatic systems

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. In

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aquatic systems, BLMs have been reported for Chlamydomonas reinhardtii , Chlorella spp.

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species (e.g. Hordeum vulgare L. and Lactuca sativa L.) for copper, zinc, nickel and silver

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have been reported using root elongation as the toxicity end point6, 14, 18, 19.

and Pseudokirchneriella subcapitata 13, 17. Similarly, BLMs for several terrestrial plants

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Arsenate uptake in algae and higher plants is influenced by the presence of phosphate

.

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The influence of other anions is less clear. In terms of adsorption processes, phosphate,

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sulfate and carbonate have been demonstrated to compete with arsenate at the solid-solution

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interface

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sulfur containing functional groups in peat

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However, organic-arsenic binding constants and BLM-like models are rare29,

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comparison to cationic counterparts, such as Pb, As toxicity from solution culture has not

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been shown to be strongly dependent on pH. WHAM (Windermere Humic Aqueous Model)

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is a speciation software which primarily is used for modelling cation binding with humic

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substances. Recently, WHAM has been applied to toxicity modelling31. WHAM utilises

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binding constants relating to Humic and Fulvic acids and has been applied primarily to

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aquatic organisms. However, as there are presently no binding constants included in the

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WHAM speciation software for As and dissolved organic carbon, there are significant

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limitations in the application of biotic ligand or the WHAM-based Ftox models31 at

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contaminated sites. Since arsenate is taken up via the phosphate cotransport system, ions able

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to influence phosphate uptake may similarly influence arsenate (e.g. carbonate) 32. To the best

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of our knowledge, there are no empirical or mechanistic models reporting arsenate toxicity in

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a complex multi-ion terrestrial systems, particularly phosphate and carbonate.

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. Arsenic binding to organic solid substrates has been shown to occur with 26

, cysteine

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and proteinaceous biowastes 30

.

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.

In

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In this study, we related measured soil pore-water As toxicology and the influence of

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phosphate and carbonate from the pore-water of 10 contrasting soils. The role of soil pore-

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water parameters on As bioavailability to the test organism, Cucumis sativa L. (cucumber),

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was investigated in detail and a BLM-like model is reported.

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Materials and Methods

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Soil collection and spiking

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Soils (10) from different parts of Australia (specifically South Australia, Victoria, New South

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Wales and Queensland) were sampled from the top 0-0.2m of each profile, air-dried and

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sieved through 2 mm stainless steel sieves. The experimental soils represent a wide range of

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soil properties (e.g. clay content (7 to 62%), soil pH (4.5 to 8.1) and organic carbon (1.1 to

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8.4%)) and soil types found across Australia9. After air drying, all soils were spiked with

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arsenate [As (V)] (Na2HAsO4 ) by spraying As solution to a thin layer of soil with continuous

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mixing using a trowel in a plastic tray. The soils were spiked with up to 1,000 mg As/kg.

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Spiked soils were placed in 12 L plastic containers and mixed again with a mechanical mixer

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for 5-10 minutes. All 10 soils were incubated for approximately 3 months with a water

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content of approximately 60-70% (w/w) of field capacity at room temperature. Additionally,

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three soils (MG, TA, PB) were spiked on a separate occasion and incubated for 4 weeks.

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Calculation of a F-test to test whether there was a significant difference between toxicity

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batches indicates no significant difference in any of the three soils 33. This indicates a good

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level of reproducibility within the procedure applied in this study. Prior to our toxicity

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experiments, soils were again air dried, sieved (2 mm) and mixed 34. Soluble orthophosphate

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was determined in a 1:1 extract (16 h) by the Automated Flow Injection Analysis and

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molybdate blue colour reaction method.

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Phytotoxicity assay

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Each soil treatment was replicated 3 times for the pot study. Air-dried soil was transferred to

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0.5 L plastic pots lined with fine nylon mesh, as previously reported5. Each pot was placed

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within a plastic collecting tray to prevent excess leachate watering. Plants were watered by

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weight using Milli-Q water (18.2 MΩ.cm) to maintain approximately 70-100% of field

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capacity throughout the study. Cucumber (Cucumis sativa L.) was chosen based on

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sensitivity to metal(loid)s from a screening study of several plant species. In every pot 10-12

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cucumber seeds were sown initially to ensure sufficient germination. Ten days later seedlings

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were thinned to 5 plants per pot. Pots were randomised every second day to minimise the

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variability of condition effects. After 4 weeks under greenhouse conditions (~16 - 25˚C),

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plants were harvested and plant shoots were first washed with tap water and then rinsed

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several times with Milli-Q water. Washed shoot samples were then dried in an oven at 60˚C

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for 72 h. Dry weight was measured and shoots were homogenised for measurement of As

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content in shoots by acid digestion35.

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After harvesting, Milli-Q water was added to approximately each pot’s ‘field’ capacity. Pore-

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water was collected using Rhizon samplers as previously reported

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sample was then sub-divided for analysis (pH, DOC, anionic and cationic composition). For

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analysis of pore-water samples for As and dissolved cations, samples for total aqueous

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analysis were acidified (pH