Chapter 6 Advances in Isotopic Dilution Techniques in Trace Element Research

C H A P T E R

S I X

Advances in Isotopic Dilution Techniques in Trace Element Research: A Review of Methodologies, Benefits, and Limitations Rebecca E. Hamon,* David R. Parker,† and Enzo Lombi‡ Contents 290 293 306 306 308 309 310 313 314 314 315 317

1. Introduction 2. The Isotopic Dilution Principle 3. Methodologies 3.1. Choice of isotope 3.2. Isotope ‘‘spiking’’ 3.3. Choice of suspension matrix in E-value determinations 3.4. Equilibration time 3.5. L-value determinations 4. Uncertainties and Sources of Errors 4.1. Accuracy and precision 4.2. Spike-derived artifacts 4.3. Error propagation 4.4. Uncertainties and sources of error specific to L-value determination 4.5. Colloidal interferences 4.6. Changes in oxidation state 5. Interpretation of E-Values 6. Interpretation of L-Values 7. Future Applications Acknowledgments References * {

{

318 320 321 325 327 335 336 337

Plant Chemistry Section, Agricultural and Environmental Chemistry Institute, Faculty of Agricultural Sciences, Universita` Cattolica del Sacro Cuore, Via Emilia Parmense 84, I-29100, Piacenza, Italy Soil and Water Sciences Section, Department of Environmental Sciences, University of California, Riverside, California 92521 Plant and Soil Science Laboratory, Department of Agricultural Science, Faculty of Life Sciences, University of Copenhagen, Thorvaldsensvej 40, 1871 Frederiksberg C, Denmark

Advances in Agronomy, Volume 99 ISSN 0065-2113, DOI: 10.1016/S0065-2113(08)00406-9

#

2008 Elsevier Inc. All rights reserved.

289

290

Rebecca E. Hamon et al.

Abstract New insights into factors controlling element bioavailability and mobility in soils have been achieved through the use of isotopic dilution methods. With the advent of robust and relatively simple analytical techniques able to accurately determine stable isotope ratios, the future use of isotopic dilution methods is expected to continue to expand. In both theory and practice, the E- and L-value isotopic dilution methods appear relatively simple to apply. However, this simplicity is deceptive: in reality, there exist a number of pitfalls that can result in collection of flawed data or inappropriate data interpretation. With a focus on trace elements, this chapter reviews studies that have applied isotopic dilution techniques to examine various aspects of soil chemistry and bioavailability, provides guidance on conducting isotopic dilution experiments, and discusses potential future applications for these techniques. The various pitfalls that may be encountered, including precipitation artifacts, colloidal interferences, and labile redox state effects, as well as how to identify and avoid such pitfalls, are also described.

1. Introduction Trace elements, including both metals and metalloids which are the focus of this chapter, are present in soils in a variety of chemical and physical forms and, for some elements, in multiple oxidation states. These diverse forms are the combined result of the geochemical origins of each element in conjunction with its chemical interactions with highly heterogeneous soil systems. Significant research effort over the last 50 years has been devoted to improving our understanding of the various forms, or pools, in which trace elements exist in soils, as this is a key determinant of their bioavailability and mobility. The chemical techniques that have been developed to investigate trace element pools in soils can be divided into five main categories: fractionation, adsorption, desorption, spectroscopic, and isotopic dilution methods. Fractionation methods involve the use of one (batch extraction) or more (sequential extraction) extractants, ranging from water to neutral salt solutions to chelating agents and even Coca ColaÒ (Schnug et al., 1996), to extract trace elements from different chemical pools in soil. The pools that are so extracted are almost always operationally defined (Ahnstrom and Parker, 2001) because the quantity extracted depends on the strength and effectiveness of the extractant used as a solvent for a particular trace element–soil substrate combination; few, if any extractants are highly specific for a particular trace element–soil substrate combination. Extractants also typically alter the chemistry of the system they are extracting; this can sometimes lead to measurable redistribution of elements among the putative

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geochemical pools (Ahnstrom and Parker, 2001; Gleyzes et al., 2002). Fractionation studies can therefore provide broad information regarding the nature of the chemical environment in which the trace element is hosted within the soil, but caution is required to avoid overinterpretation of the results due to the lack of extractant specificity and the possibility of redistribution. A further aim of many fractionation studies has been to identify a ubiquitous extractant, able to act as a bioavailability surrogate across a number of soil types, sources of contamination, environmental endpoints, and for multiple elements. This quest has so far proven largely unsuccessful (Menzies et al., 2007). Adsorption methods assess the strength of binding of trace elements to soils (or soil components) by measuring the concentration remaining in solution following additions of the element of interest to soil suspensions, with the aqueous phase typically being water or a dilute, neutral salt. Plots of sorbed element versus solution concentration at incremental additions of the element can be used to generate adsorption isotherms and, when linear, to estimate the partitioning coefficient, Kd, and thus the soil buffering capacity for a given element (Allen et al., 2001). Correlations between different soil properties and the Kd can provide information on which soil components are important sorbents for trace elements ( Janssen et al., 1997). However, adsorption studies are labor intensive. They also require addition of sufficient additional analyte to register measurable increases in the trace element concentration in solution; hence, the data obtained reflect a perturbation of the original chemical equilibrium of the system. Adsorption studies also implicitly assume that the analyte measured in solution is present in a form that is available to bind to solid-phase sorption sites. However, there is increasing evidence from isotope dilution studies (see Section 4.5) that a significant proportion of analyte in the aqueous phase of soil suspensions may be bound in a nonexchangeable form to soil colloids, which are so small that they can pass through a 0.2 mm filter. Few adsorption studies to date have, prior to measurement, filtered the analyte solution using filters with pore size smaller than 0.2 mm. Inadvertent inclusion of a nonexchangeable form of analyte in Kd determinations results in an underestimate of the Kd, that is an underestimate of the true capacity for the soil to sorb the analyte. Moreover, colloids may also provide binding sites for the introduced analyte, further increasing the apparent solution-phase concentration and thus further contributing to the underestimation of Kd. We believe that the conclusions of at least some of the numerous adsorption studies conducted to date may in fact be compromised by the presence of variable quantities of colloids in the measured solutions. Desorption methods assess the ability of the soil solid phase to retain previously sorbed analytes, and when the results are correlated against different soil properties, can also provide information on the chemical pools that host the trace elements and on the soil factors that influence

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their bioavailability and mobility. Different types of desorption methods include column desorption (Allen et al., 1995), repeated resuspension in fresh electrolyte (Gray et al., 1999), batch desorption with resins (Mason et al., 2008), and diffusion gradients in thin films (DGT) (Zhang et al., 1998). As with adsorption methods, the column and batch desorption methods are labor intensive and may be subject to interferences from colloids. Each of the desorption methods also perturbs the chemical equilibrium of the system. However, the perturbation that occurs during desorption may be similar to the localized depletion that is induced by biotic uptake of trace elements from soils and hence investigation of this (i.e., the rate of resupply of elements from the solid phase) can provide further insights into soil factors affecting bioavailability. Indeed, this is a key premise of the DGT method (Zhang et al., 1998). An in-depth discussion of the DGT method is beyond the scope of this chapter, but it should be noted that this technique, which provides an integrated measure of the soil solution concentration and the rate of resupply, is showing great promise as a tool to predict the bioavailability of trace elements to plants across a wide range of soil types (Nolan et al., 2005). A number of spectroscopic techniques have been applied to the investigation of metal distribution, surface reactions, and solid-phase speciation at the molecular level. Using these methods, the physical and chemical forms and distribution of contaminants in soil and sediments can be investigated in situ. The spectrum of techniques available has increased significantly in the last few decades, and ranges from conventional methods such as X-ray diffraction to more sophisticated techniques such as X-ray microanalyses (EDXA, PIXE), Fourier-transform infrared, nuclear magnetic and paramagnetic resonance, secondary ion mass spectroscopy, and X-ray absorption (XAS) spectroscopy. For instance, X-ray microanalysis allows quantitative investigation of the distribution of an element in samples with a volume as small as a few femtoliters or with a spatial resolution of a few micrometers [for review, see Van Steveninck and Van Steveninck (1991)]. More recently, synchrotron-based techniques such as XAS have greatly improved our ability to gain information regarding oxidation and coordination states, number and type of near neighbors, and bond distances of the elements of interest (Sparks, 2001). XAS techniques have been used to assess solid-phase speciation of a number of soil metals and metalloids such as As, Co, Cr, Ni, Pb, and Zn. These techniques provide powerful tools for the assessment of metal speciation at the microscale. However, translating this detailed assessment into environmentally relevant information in terms of metal toxicity and bioavailability still represents a significant challenge. Also, accessibility to these spectroscopic techniques is still limited so that routine use is problematic. Isotopic dilution techniques have been employed in soil science for more than 50 years and are the focus of the remainder of this chapter. In essence, the isotope dilution technique allows differentiation of trace

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element pools on the basis of the kinetics of exchange of the trace elements with the soil solid phase. While in reality, the kinetics of exchange of elements within the soil represents a continuum, it can be useful and convenient to delineate kinetic boundaries. For example, results obtained during an isotopic dilution study of metal-contaminated soil prompted Hamon et al. (2002a) to propose that soil contaminants be placed into three risk classes based on the kinetics of their association with the soil solid phase, namely, (1) labile, (2) chemically labile, and (3) nonlabile. Labile forms were defined as the solution and readily (within 1–3 days) exchangeable pools of contaminant that pose a current risk and whose bioavailability can be measured, for example, by monitoring concentrations of the contaminant in plants growing in the soil. Nonlabile forms were defined as those that remain in chemically inert pools (i.e., do not readily participate in an exchange equilibrium) despite environmental perturbations, and hence pose little risk either now or in the future. The chemically labile form of contaminant was defined as that which is ‘‘fixed’’ in a nonexchangeable (and nonavailable) pool under current conditions, but which can be released to the available pool if the environmental conditions change, for example, through soil acidification or changes in redox status. The same definitions of labile, chemically labile, and nonlabile forms are used throughout the remainder of this chapter. It should be emphasized from the beginning that the isotopic dilution approach does not aim to directly measure trace element bioavailability but, both separately and in combination with the other methods described above, can provide useful information toward the understanding of various soil processes that influence bioavailability.

2. The Isotopic Dilution Principle The isotopic dilution principle is based on the premise that when a small amount of an isotope of an element of interest is introduced in a soil, it will readily redistribute itself among the solution and exchangeable phases (which are in dynamic equilibrium) in the same way as the other isotopes of the same element. Therefore:

a
sol Msol ¼
aexch Mexch

ð1Þ

where sol and exch represent the activity (a
) of the isotope, or the concentration of the metal (M ), in the solution phase and exchangeably adsorbed on the soil solid phase, respectively. When a
sol (Bq liter1) is converted to the same units as a
exch (Bq kg1) by taking into account the dilution factor for the suspension, D (D ¼ solution volume in liter/soil mass

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in kg), the sum of a
sol and a
exch is equal to the total quantity of tracer isotope introduced (abbreviated hereafter as A
); similarly, the sum of Msol (mg liter1) and Mexch (mg kg1) is equal to the total labile or exchangeable metal pool after multiplying Msol by D to convert to the appropriate units. Sampling and analysis of the solution phase allows determination of isotope distribution between the solution and solid phases. In this case, the labile pool has traditionally been termed an E-value (where E signifies ‘‘exchangeable’’) and it can be calculated by rearranging Eq. (1) and taking into account the dilution factor, D:

E ¼ ðD  Msol þ Mexch Þ ¼

Msol  A
 D
asol

ð2Þ

It is important to note that Eqs. (1) and (2) can only be valid under the following conditions: 1. The small quantity of isotope introduced in the system has not perturbed the equilibrium of the system, and consequently the isotope has no access to any nonlabile metal pool through processes such as (co) precipitation; 2. The introduced isotope behaves exactly as the natural element in the soil; 3. All metal species measured in solution (Msol) are isotopically exchangeable; 4. The introduced isotope has physically mixed with the entire labile metal pool. It should also be noted here that the dilution of the introduced isotope within the preexisting pool of the same element in soil is time-dependent. In theory, at infinite time, the isotope would mix uniformly with the entire soil metal pool (Tiller et al., 1972). Generally, the equilibration time is operationally limited to a few days (usually 1–3 days, see Section 3.4). As pointed out by Hamon et al. (2002b), the determination of an Evalue not only allows the measurement of the total exchangeable pool of an element in soil (E-value or Ea) but also the assessment of the pool present on the soil solid phase in an exchangeable form (Ee ¼ EaDMsol). In many cases, these two E-values are not very different; exceptions occur when the soil buffering capacity is low (Hamon et al., 2002b). Alternatively, plants grown in an isotopically labeled soil can be used to sample the exchangeable pool. In this case, the labile pool is called an L-value (Larsen, 1952). After growing the plants in the labeled soil, the shoot is harvested and the concentration/activity of the isotopes in the plant is measured. The L-value is calculated as follows:

L¼

Mshoot  Mseed  A
a
shoot

ð3Þ

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where shoot indicates the activity (a
) of the isotope, or the concentration of the metal (M), in the plant shoot and Mseed is the contribution of metal from the seed to the metal concentration in the shoot; as before, A
is the total amount of isotope used to label the soil. Since in this case, a living organism is used to sample the soil solution, the L-value can be considered as representative of the potentially bioavailable pool for that organism. In other words, it is the metal pool that the organism can draw from as the most accessible forms (e.g., solution species) are depleted over time, which may include both labile and chemically labile forms of the element. However, it should be noted that the actual bioavailability of this metal pool is controlled by a number of chemical parameters (such as pH, competing ions, ligands in solution) as well as by physiological processes. The procedural frameworks used for the determination of E- and Lvalues are depicted in Fig. 1, and a compendium of the literature that has made use of isotopic dilution techniques to investigate trace elements in soil is given in Table 1.

L-value

Soil spiking

E-value

Shoot harvesting Soil suspension (24/72 h equilibration)

Isotope measurement L-value calculation Soil

Centrifugation filtering < 0.2 mm

Isotope measurement E-value calculation

Non-labile

Labile

Figure 1 Schematic representation of E- and L-value procedures. In the Lvalue procedure, stars denote the added isotope whereas dots represent the native metal.

296

Table 1 Compendium of the literature on isotopic dilution techniques (E- and L-values) used to assess the exchangeable pool of heavy metals and metalloids in soil

Year

Authors

Cadmium 1986 Fujii and Corey

Isotope

Other elements Soil No.

Equilibration Total mg kg1 Equilibration medium Time

109

Cd

Zn

4

na

Pb

2

0.16, 0.29

0.01 M Ca (NO3)2þ1 M EDTA

16 h–3 days

E (%)

Dalenberg and Van Driel

109

Cd

1990

109

Cd

5

0.04–0.22

–

na

–

109

Cd

33

0.7–2040

0.01 M CaCl2

24 h

3–102

1994

Jensen and Mosbaek Nakhone and Young Riise et al.

109

Cd

2

<1

Modified Tessier

5 min–221 days

~25

1997

Hamon et al.

109

Cd

1

0.2

1998 1998

Hamon et al. Pandeya et al.

109

Cd Cd

1 10

0.03–0.4 na

1999

Gabler et al.

114

Cd

2

0.25, 0.76

1999 2000

Smolders et al. Gerard et al.

109

Cd Cd

10 4

0.3–6.5 0.6–25

115

109

Zn

Cu, Cr, Ni, Pb, Zn Zn

6 months–4 years

0.005 M DTPA, 0.01 M CaCl2, 0.1 M Na-ac. Water, EDTA, NH4NO3 0.01 M CaCl2 Water

L (%)

na

1990

1993

Plant species used for L-values

L. multiflorum, S. oleracea, T. aestivum, D. carota L. sativa

~62–86

B. napus, A. calendula, T. subterraneum, L. sativa, B. vulgaris, L. perenne, T. aestivum, T. turgidum T. turgidum

20–36

na

50–80

48 h

na

2–24 h

~65

7 days IEK

62–90 T. aestivum 55–109 41–66 L. perenne, L. sativa, na (30 days) T. caerulescens

2000

Hutchinson et al.

109

Cd

2000 2000

Stanhope et al. Young et al.

109

Cd Cd

2001

111

2001 2001 2002a

Ahnstrom and Parker Almas and Singh Stacey et al. Hamon et al.

Cd Cd 109 Cd

2003

Ayoub et al.

114

2003 2003 2003 2003

Collins et al. Degryse et al. Gray et al. Lombi et al.

109

2003 2003 2004

Scheifler et al. Tye et al. Degryse et al.

109

2004 2004 2004

Gray et al. Hutchinson et al. Sterckeman et al.

109

2005 2005

Nolan et al. Sappin-Didier et al. Sterckeman et al.

109

2005

109

109 109

Cd

Cd Cd Cd 109 Cd 109

Cd Cd 109 Cd

67–261

48 6–103

4

22–34

0.1 M Ca (NO3)2 48 h 0.1 M Ca (NO3)2 or 48 h CaCl2 0.1 M Sr (NO3)2 2 h–14 days

Zn Zn Zn

2 3 5

0.17, 1.9 0.03–1.06 90

24 h 3 days

6.4–33 1.5–3.2

Zn

2

0.18, 33.8

0.01 M Ca (NO3)2 Water (acidification) Water

1 h–50 days

86 (3 days)

Cu, Zn

2 74 20 8

18.7, 20.3 0.5–118 0.6–3.8 19–42

24 h 16 h–3 days 24 h 3 days

19–73 18–92 33–84 22–63

Zn Zn

1 39 80

20.3 0.03–384 0.6–414

IEK 2 days 16 h–3 days

50 (14 days) Helix aspersa (snail) Na 9–92 (3 days)

20 1 7

0.19–3.0 135 0.13–7

Diluted ligands 0.01 M CaCl2 0.05 M Ca (NO3)2 Waterresin (acidification) Water 0.1 M Ca (NO3)2 0.01 M CaCl2 and 0.1 mM EDTA Water 0.1 M Ca (NO3)2 Water

IEK 48 h IEK

13 2

0.11–86 2.3, 2.4

0.1 M Ca (NO3)2

24 days

43–54 (24 h) 39 59–74 (79 days) na

2

19.5, 19.9

0.01 M CaCl2

Zn

Cd Cd 109 Cd

109

T. caerulescens, T. officinale, H. vulgare

59 Na

109

109

~20–47 40–83

1 66

111

109

L. multiflorum T. aestivum

0.1 M Ca (NO3)2

Cd

Cd Cd

Cu, Zn

Cd

Zn

4.9–49

6–50

59–770

Zn

48 h

T. caerulescens (6 pop), L. heterophullum B. juncea

6

13–49 (14 days)

N. tabacum (2 lines) 7 days

44

35–74

58

86–100

297

L. perenne, L. sativa, 37–76 T. caerulescens, T. pratense, B. napus, A. thaliana

(continued)

Table 1 (continued) 298

Authors

Isotope

Other elements Soil No.

Total mg kg

Equilibration Equilibration medium Time

E (%)

Zn Zn

23 12

3–4 0.01–0.94

0.1 M Ca (NO3)2 0.01 M CaCl2

48 h 3 days

na 50–108

2006

Crout et al. Degryse and Smolders Geebelen et al.

109

7

31

IEK

5–32 (7 days)

2006 2007

Zhang et al. Gabler et al.

109

Water ( acidification) 0.1 M Ca (NO3)2 0.01 M Ca (NO3)2

48 h 24 h

na 4–99

Lopez and Graham

24 h–5 days

na

1972

0.005 M DTPA, 0.10 M Naac.þ0.01 M CaCl2 or 0.01 M LaCl3 0.005 M DTPA, 0.01 M CaCl2, 0.1 M Na-ac. at different pH 0.05 M CaCl2þcarrier 0.005 M DTPA, 0.01 M CaCl2, 0.1 M Na-ac. 0.005 M DTPA, 0.01 M CaCl2, 0.1 M Na-ac. 0.005 M DTPA, 0.01 M CaCl2, 0.1 M Na-ac. at different pH

48 h

na

1–15 days

Year

2006 2006

Cd Cd

109

109

Cd

Zn 17 Cr, Cu, Mo, 115 Ni, Pb, Tl, Zn

3–4 0.04–1.3

65

Cu, Fe, Mn

3

na

Lopez and Graham

65

Co, Cu, Fe, Mn

6

na

1972

Tiller et al.

65

25

4–183

1973

Lopez and Graham

65

Fe, Mn

6

na

1976

Rule and Graham

65

Fe, Mn

4

na

1977

Sinha et al.

65

21

na

Zinc 1970

Cd Cd

1

114

Zn

Zn

Zn Zn

Zn

Zn

Plant species used for L-values

L (%)

T. subterraneum

~3–15

48 h

~4–212 (7 days) na

T. repens

na

48 h

na

T. repens, F. elatior

na

48 h

na

Z. mays, T. aestivum na

1982

Ganai et al.

65

1986 1987

65

1997

Fujii and Corey Sanders and El Kherbawy Hamon et al.

1999

Zn

4

100–1500

Cd

4 26

na 37–224

65

Cd

1

80

Gabler et al.

68

Cd, Cr, Cu, Ni, Pb

2

51

1999

Sinaj et al.

65

11

42–987

1999 2000

Smolders et al. Young et al.

65

Cd Cd

6 25

50–311 na

2001 2001 2002a 2003

Almas and Singh Stacey et al. Hamon et al. Ayoub et al.

65

Cd Cd Cd Cd

2 3 5 2

68, 168 28–214 18540 65, 1231

2003 2003 2003

Collins et al. Degryse et al. Lombi et al.

65 65

Cd Cd, Cu

2 74 8

1400, 3250 53–34100 1756–2920

2003 2004

Tye et al. Degryse et al.

65

Cd Cd

39 109

29–28500 8–35800

Zn Zn

65

Zn

Zn Zn Zn Zn

65

Zn Zn 65 Zn 67 Zn 65

Zn Zn 65 Zn Zn Zn

65

0.005 M DTPA, 0.01 M CaCl2, 0.1 M Na-ac. at different pH 0.01 M Ca (NO3)2 0.01 M CaCl2 þ carrier

Water, EDTA, NH4NO3 Water

48 h

9–96

16 h–3 days na

na na

2–24 h

~5–10

IEK

4–44 (15 days) 23–50 6–48

0.01 M CaCl2 7 days 0.1 M Ca (NO3)2 or 48 h CaCl2

299

0.01 M Ca (NO3)2 Water Water

24 h 3 days 1 h–50 days

0.12–24 1.2–5.9 13–65 (25 days)

Diluted ligands 0.01 M CaCl2 Water, resin ( acidification) 0.1 M Ca (NO3)2 0.01 M CaCl2, 0.1 mM EDTA.

24 h 16 h–3 days 3 days

16–59 5–68 18–53

48 h 16 h–3 days

na 3–72 (3 days)

B. napus, A. calendula, T. subterraneum, L. sativa, B. vulgaris, L. perenne, T. aestivum, T. turgidum

12

T. aestivum

24–74

L. multiflorum T. aestivum

10–28 20–72

T. caerulescens, T. officinale, H. vulgare

11–60

(continued)

Table 1 300 Year

(continued) Authors

Isotope

2004 2004

Sarret et al. ScottFordsmand et al.

65

2004 2005 2005

Sinaj et al. Nolan et al. Sterckeman et al.

65

2006 2006

Crout et al. Degryse and Smolders Zhang et al. Gabler et al.

65

Lopez and Graham

1972

1974

2006 2007

Copper 1970

Other elements Soil No.

Zn Zn

Total mg kg

1

Equilibration Equilibration medium Time

E (%)

3 1

21000 15

0.001 M Ca (NO3)2 48 h 36, 42 days

54–92

Cd, Cu Cd

7 13 2

na 28–21300 1538–3362

Water 0.1 M Ca (NO3)2 0.01 M CaCl2

IEK 48 h 7 days

na na 9–49

Cd Cd

23 12

300–500 4.5–70.7

0.1 M Ca (NO3)2 0.01 M CaCl2

48 h 3 days

na 11–49

Cd 17 Cd, Cr, Cu, 115 Mo, Ni, Pb, Tl

300–500 4.2–163

0.1 M Ca (NO3)2 0.01 M Ca (NO3)2

48 h 24 h

na 0.2–94

64

Fe, Mn, Zn

3

na

Lopez and Graham

64

Co, Fe, Mn, Zn

6

na

McLaren and Crawford

64

24

4.4–64

0.005 M DTPA, 48 h 0.10 M Naac.þ0.01 M CaCl2 or 0.01 M LaCl3 48 h 0.005 M DTPA, 0.01 M CaCl2, 0.1 M Na-ac. at different pH 0.05 M CaCl2 24 h

65

Zn 65 Zn 65 Zn

Zn Zn

65

65

Zn Zn

68

Cu

Cu

Cu

Plant species used for L-values

Eisenia andrei (earthworm)

na

na

2–21

L. sativa L. multiflorum

L (%)

55–60

na

L. perenne., L. sativa, 28–66 T. caerulescens, T. pratense, B. napus, A. thaliana

1999

Gabler et al.

65

2003

Lombi et al.

64

2004

Lombi et al.

64

2004 2005 2006a

Nolan et al. Nolan et al Ma et al.

64,65

2006b 2006c 2006

Ma et al. Ma et al. Oliver et al.

64,65

2007

Gabler et al.

65

Nickel 1998 1999

Echevarria et al. Gabler et al.

63

2002

Denys et al.

2002

Cu

Cd, Cr, Ni, Pb, Zn Cd, Zn

2

13

4

1245

As

7

1058

Cd, Zn

12 13 21

7–432 7–602 12–40000

19 46 6

12–2400 12–2400 84–1058

Water, EDTA, NH4NO3 Water, resin ( acidification) Water, resin ( acidification) Watercarrier 0.1 M Ca (NO3)2 Water, resin, 0.01 M CaCl2 Water Water Water

Cd, Cr, Mo, 89 Ni, Pb, Tl, Zn

0.6–46.1

2 2

33, 35 16

63

7

10–862

Staunton et al.

63

2

20, 45

2003

Pinel et al.

63

2

19, 35

2004

Massoura et al.

63

4

26–863

Cu Cu

Cu Cu 64 Cu 64

Cu Cu Cu

64 65

Cu

Ni Ni

62

Ni Ni Ni

Ni

Cd, Cr, Cu, Pb, Zn

2–24 h

~24

24 h

28–40

24 h 24 h 24 days 24 h

34 (control soil) 3.7–52 na 5–100

24 h 24 h 24 h

30–110 11–100 58–74

0.01 M Ca (NO3)2

24 h

na

Water Water, EDTA, NH4NO3 Water

IEK 2–24 h IEK

Water or 0.01 M CaCl2

24 h

Water

IEK

S. lycopersicum, L. multiflorum

63–81

15–40 ~15

T. pratense

7–36

~8–57 (90 days) na

T. aestivum, T. na pratense A. murale

30–60 (90 days)

T. alexandricum, F. na ovina, F. rubra, R. sativus, B. napus, L. perenne, L. esculentum T. aestivum, T. 30–60 pratense A. murale

301

(continued)

Table 1

(continued)

302 Year

Authors

Isotope

2006

Echevarria et al.

63

Ni

2006

Massoura et al.

63

Ni

2007 2007 2007

Bani et al. Chardot et al. Gabler et al.

63

Manganese 1970 Lopez and Graham

Ni Ni 62 Ni

Total mg kg

Equilibration Equilibration medium Time

E (%)

100

19–12000

Water

IEK

na

16

154–12000

Water

IEK

1 9 115

3440 125–2507 <3–49.9

Water Water 0.01 M Ca (NO3)2

IEK IEK 24 h

~0.1–50 (3 months) 6 (24 h) >50 na

0.005 M DTPA, 0.10 M Naac.þ0.01 M CaCl2 or 0.01 M LaCl3 0.005 M DTPA, 0.01 M CaCl2, 0.1 M Na-ac. at different pH 0.005 M DTPA, 0.01 M CaCl2, 0.1 M Na-ac. 0.005 M DTPA, 0.01 M CaCl2, 0.1 M Na-ac. 0.1 N H3PO4 0.05 M CaCl2 or 0.005 M DTPA 0.05 M CaCl2 or 0.005 M DTPA

24 h–5 days

na

48 h

na

48 h

na

T. repens

na

48 h

Na

T. repens, F. elatior

na

3 days 7–97 up to 5 days ~3–46

S. vulgare

2–17

na

H. vulgare

Other elements Soil No.

63

Cd, Cr, Cu, Mo, Pb, Tl, Zn

1

54

Mn

Cu, Fe, Zn

3

na

1972

Lopez and Graham

54

Mn

Co, Cu, Fe, Zn

6

na

1973

Lopez and Graham

54

Mn

Fe, Zn

6

na

1976

Rule and Graham

54

Mn

Fe, Zn

2

na

1979 1984

Salcedo and Ellis Goldberg and Smith Goldberg and Smith

54

Mn Mn

12 10

96–655 49–1275

Mn

3

na

1985

54

54

na

Plant species used for L-values

T. caerulescens, T. pratense A. murale

L (%)

na

Iron 1970

Lopez and Graham

59

Cu, Mn, Zn

3

na

1972

Lopez and Graham

59

Co, Cu, Mn, Zn

6

na

1973

Lopez and Graham

59

Zn, Mn

6

na

1976

Rule and Graham

59

Mn, Zn

4

na

1985

Dyanand and Sinha

59

22

na

Tye et al.

73

102

4–17200

P

27

13–1080

2004 2004

De Brouwere et al. Hamon et al. Lombi et al.

73

Cu

8 1

Lead 1979

Tjell et al.

210

3

Arsenic 2002 2004

Fe

Fe

Fe

Fe

Fe

As As

73

As As

73

Pb

0.005 M DTPA, 0.10 M Naac.þ0.01 M CaCl2 or 0.01 M LaCl3 0.005 M DTPA, 0.01 M CaCl2, 0.1 M Na-ac. at different pH 0.005 M DTPA, 0.01 M CaCl2, 0.1 M Na-ac. 0.005 M DTPA, 0.01 M CaCl2, 0.1 M Na-ac. 0.005 M DTPA, 0.01 M CaCl2, 0.1 M Na-ac.

24 h–5 days

48 h

na

48 h

na

T. repens

na

48 h

na

T. repens, F. elatior

na

48 h

na

S. vulgare

na

L. multiflorum

na

0.005 M (NH4) 48 h H2PO4 0.005 M Ca (NO3)2 40 h

0.4–60

725–4770 4772

Water Water, resin ( acidification

2–73 3.7 (control soil)

11–17

1:1 HNO3, or 0.02 na M EDTA, or 1 M NH4-ac.

48 h 2 days

1.2–19

na

303

(continued)

304

Table 1

Year

(continued) Authors

Isotope

1989

Mosbaek et al.

210

1990

Dalenberg and Van Driel

210

1999

Gabler et al.

207

2005

Tongtavee et al.

207

2007

Gabler et al.

207

2007

Degryse et al.

208

Cobalt 1969

Tiller et al.

60

Gille and Graham Lopez and Graham

60

McLaren et al.

1971 1972

1986

Selenium 1994 He et al.

Other elements Soil No.

Pb Pb

Pb

1

Total mg kg

2

7–15

Cd

2

4.7, 20.1

Cd, Cr, Cu, Ni, Zn

2

37

5

Equilibration Equilibration medium Time

1:1 HNO3, or 1 M NH4-ac.

>2 years

E (%)

Plant species used for L-values

Na

Na L. multiflorum, S. oleracea, T. aestivum, D. carota

6 months–4 years 2–24 h

~61

21–246

Water, EDTA, NH4NO3 Water

IEK

40–64 (24 h) T. aestivum

<4–80

0.01 M Ca (NO3)2

24 h

na

16–14436

0.01 M CaCl2

3 days

45–>89

25

0.18–97

7–14 days

~0.6–111

1

na

0.05 M CaCl2carrier various

Na

na

6

na

48 h

na

60

20

3–15

0.005 M DTPA, 0.01 M CaCl2, 0.1 M Na-ac. at different pH 0.5 M CaCl2

48 h

1–11

75

3

32–256

0.01 M 24 h CaCl2KH2PO4

37–79

Pb Pb

Pb

Cd, Cr, Cu, 115 Mo, Ni, Tl, Zn 21

Co Co

60

Co

Co Se

Cu, Fe, Mn, Zn

S. vulgare

L (%)

~80– 170 ~100– 2000

~54– 868

na

2003

Goodson et al.

75

Se

5

2–20

0.1 M KCl

2006

Collins et al.

78,76

9

3–1130

Water

24 h

3–78

55

Water, EDTA, NH4NO3 0.01 M Ca (NO3)2

24 h

~0.06

24 h

Na

4 weeks–6 months 24 h

Na

<2–5 Mo

1 M HNO3, 1 MNH4-ac. 0.01 M Ca (NO3)2

na

0.01 M Ca (NO3)2

24 h

Na

Chromium 1999 Gabler et al. 2007

Gabler et al.

Se

53

Cr

53

Cr

Cd, Cu, Ni, 2 Zn, Pb Cd, Cu, Mo, 115 Ni, Pb, Tl, Zn

Molybdenum, Thallium, and Mercury 203 Hg 1988 Mosbaek et al. 2007

Gabler et al.

97

2007

Gabler et al.

203

Mo

Tl

1

Cd, Cr, Cu, 115 Ni, Pb, Tl, Zn Cd, Cr, Cu, 115 Mo, Ni, Pb, Zn

<3–171 Cr

0.2–0.3

4–73

A. bisulcatus, A. 2–37 canadensis, B. juncea, S. airoides, S. pinnata

L. multiflorum, L. sativa, R. sativus

na

Na

E (%) and L (%) refer to the isotopically exchangeable pool (E- and L-values) as percentage of the total soil content. The symbol ‘‘~’’ indicates values that have been calculated from published data. When different amendments were added to the same soil, these treatments were compiled in the table as different soils.

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3. Methodologies 3.1. Choice of isotope Typically, radioactive isotopes of metals and metalloids have been used. Available radioisotopes include 109Cd, 60Co, 64Cu, 59Fe, 203Hg, 54Mn, 63Ni, 210Pb, 75Se, and 65Zn. However, as shown in Table 2, some of these isotopes have very short half-lives (e.g., 64Cu) that limits their use in longer term studies, or have relatively long half-lives (e.g., 63Ni) that can cause a disposal problem once the study is completed. Use of certain radioisotopes may also pose a significant risk due to the nature of the radiation emitted (e.g., 210Pb). Therefore, the use of enriched stable isotopes (Table 3) has gained some favor, driven in part by the availability of sensitive analytical techniques such as inductively coupled plasma mass spectrometry (ICP-MS) (Ahnstrom and Parker, 2001; Gabler et al., 1999; Gray et al., 2003; Nolan et al., 2004; Tongtavee et al., 2005). Even though the use of stable isotopes is analytically more demanding than in the case of radioisotopes, it opens the way to the study of elements for which appropriate radioisotopes are not available (or affordable), and offers the additional Table 2

Some useful radioisotopes for the determination of E- and L-values

Isotope

Half-life

Decay modea

Detectionb

51

Cr Mn 55 Fe 59 Fe 57 Co 63 Ni 64 Cu

28 days 312 days 2.7 years 45 days 272 days 100 years 12.7 h

g 320 keV (100) g 835 keV (100) b 231 keV (100) g 1100 keV (57) g 22 keV (17) b 67 keV (100) g 1346 keV (100)

65

Zn As 75 Se 109 Cd 110m Ag

244 days 80 days 120 days 461 days 250 days

EC!51V EC!54Cr EC!55Mn b!59Co EC!57Fe b!63Cu b, EC!64Zn, 64 Ni EC!65Cu EC!73Ge EC!75As EC!109Ag b!110Cd

113

115 days 47 days

EC!113In b!203Tl

54

73

Sn Hg

203 a

g 115 keV (51) g 53 keV (10) g 265 keV (59) g 88 keV (3.7) g 657 keV (94) or b 83 keV (67) g 392 keV (64) g 279 keV (100)

EC¼electron capture. For g - and b-ray spectrometry, the energy of the strongest emission is given in keV, along with the percent relative intensity in parentheses. Note that the unusually long and short half-lives of 63Ni and 64Cu, respectively, can make their use problematic. b

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Table 3 Some potentially useful stable isotopes for the determination of E- and L-values, typically using ICP-MS for isotope-ratio determinations Element

Number of isotopes

Suggested tracera,b

Suggested referenceb

B Cr Fe Ni Cu Zn Se Mo Ag Cd Sn Hg Pb

2 4 4 5 2 5 6 7 2 8 10 7 4

10

11

53

52

B (20%) Cr (9.5%) 57 Fe (2.2%) 62 Ni (3.6%) 65 Cu (31%) 68 Zn (19%) 77 Se (7.6%) 95 Mo (16%) 109 Ag (48%) 111 Cd (13%) 118 Sn (24%) 201 Hg (13%) 206 Pb (24%)

B Cr 56 Fe 60 Ni 63 Cu 66 Zn 78 Se 97 Mo 107 Ag 114 Cd 120 Sn 202 Hg 207 Pb

a

Natural atomic abundance is shown in parentheses. Many of these isotopes are subject to potential interferences from polyatomic (molecular) species such as 40Ar16OH (amu ¼ 57). Increasingly, these problems are readily overcome through the use of newer ICP-MS instruments with collision/reactor cell technology, most typically in He collision mode. Note that with B and Mo, no radioisotopes are available. b

advantage of an indefinite ‘‘shelf-life’’; the feasibility of in-field isotopic dilution studies is another possible benefit. The measurement of a labile pool (E-value) using stable isotopes requires the accurate knowledge or determination of three isotope ratios: the natural abundance ratio of the isotopes (IRnat), the ratio of the isotopes in the spike solution (IRsp), and the measured isotope ratio in solution after spiking (IRmeas). These isotopic ratios are then used to calculate the labile pool using equations such as the following developed by Nolan et al. (2004) for Cu:

E¼R

AWðMnat Þ IRsp  IRmeas  ðIRnat þ 1Þ AWðM
Þ IRmeas  IRnat

ð4Þ

where, R is the total concentration of the isotope in the spike and AW is the atomic weight of the isotopes in their natural abundance (Mnat) and in the spike (M
). Note that although most isotope ratios were until relatively recently considered invariable in nature (with the exception of a few elements such as Pb or B), high resolution techniques such as multicollector ICP-MS are now showing that many elements exhibit natural massdependent variations in isotope composition (Halliday et al., 1998; Vance and Thirlwall, 2002). Therefore, it is recommended that the natural isotope ratio is measured in each soil tested and the measured value is used in the calculation of E- and L-values.

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3.2. Isotope ‘‘spiking’’ When a radioisotope is used to assess either an E- or an L-value, the soil must be spiked with an amount of isotope that will allow accurate detection of the activity in the solution extracted from the soil or in plants. It is difficult to generalize as to the total activity needed for a given experiment because this will depend on the soil characteristics controlling the partitioning of the radioisotope (such as pH, organic matter), the half-life and counting efficiency of the isotope, and, in the case of L-values, the ability of the organism to accumulate that element. Moreover, the propensity of the element of interest to partition to the soil must be considered, for example, for a given soil, the Kd of Pb is typically larger than that of Cd. Hence, at a given spike rate, less of a Pb spike will be found in solution where it can be counted in comparison to a Cd spike. In the literature, activities varying from much less than 1kBqg1 (e.g., in the case of 63Ni in sandy soil; Echevarria et al., 1998) to over 1MBqg1 (e.g., for the shortlived 64Cu; Lombi et al., 2003) are reported. Generally, the isotope used is virtually ‘‘carrier free’’ radioisotope [i.e., has a high specific activity (MBqmg1 metal)] and the amount of ‘‘cold’’ element added in the spike is negligible and can be ignored. In cases where carrier (‘‘cold’’ element) is deliberately added (e.g., Tiller et al., 1972), or the specific activity is low such that a significant quantity of cold element is added with the radioisotope, this needs to be accounted for during the calculation of E- or L-values. Since the total amount of radioisotope added to the soil is generally extremely small, its addition does not significantly perturb the equilibrium of the system. Consequently, the decrease of radioactivity in solution is due to a homoionic exchange between the added radioisotope and the stable isotope(s) of the same element present as free ions in solution, or as reversibly sorbed ion bound to solution- or solid-phase ligands (Sinaj et al., 1999). In contrast, when a stable isotope is used for the determination of an Eor L-value the amount of metal added to the system must be sufficiently large to cause a quantifiable change in the isotopic ratio of the spiked soil in comparison to the natural isotopic ratio of the system (i.e., IRsp and IRmeas in Eq. (4) must be significantly different). Nolan et al. (2004) used the mean standard deviation of 63Cu/65Cu measurements between replicates and the difference between IRsp and IRmeas to assess the error associated with different amount of 65Cu spiking. The data showed that an addition equivalent to 5% of the E-value produced an acceptably low uncertainty (<5%) in the E-value determination. But when the E-value is unknown, the amount of isotope to add can be estimated from the total elemental concentration in soil, or from a reasonable proxy for the E-value, such as a 1M CaCl2 extraction in the case of Cd (Young et al., 2000). Nolan et al. (2004) suggested an addition of 65Cu equivalent to approximately 1% of total Cu in

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soil, as did Ahnstrom and Parker (2001) using 111Cd. The isotopic natural abundance is also a consideration in determining which isotope to use and the amount of spike to add, with the lower the natural abundance of the spike relative to the natural abundance of the other isotopes, the lower amount of spike that can be added. Hence, in contrast to studies with Cu, Gray et al. (2003) could achieve reliable measurements by adding 111Cd equivalent to ca. 0.1% of the total Cd concentration partly because 111Cd accounts for only 12.8% of the total Cd in natural systems whereas 65Cu represents 30.8% of the isotopic abundance of Cu isotopes. Gabler et al. (2007) added an amount of spike equivalent to one-third of the EDTAextractable metal content and repeated the measurements with an optimized spike addition if the original amount added to the sample was less than 5% of the isotopically exchangeable amount [which is in agreement with the suggestion made by Nolan et al. (2004)]. In case of Pb, Degryse et al. (2007) added 208Pb in a relatively large amount (between 4% and 12% of the total soil Pb concentration) and it is possible that as a consequence, their results may overestimate Pb lability in some soils (see Section 4.2).

3.3. Choice of suspension matrix in E-value determinations Early studies aiming to assess micronutrient lability in soil used a mixture of DTPA, CaCl2, and Na-acetate at different pH (e.g., Lopez and Graham, 1970, 1972; Sinha et al., 1977) as the isotopic equilibration medium. This choice of suspension matrix was probably based on the use of DTPA to assess micronutrient availability. However, it is likely that such a solution, especially when the pH of the soil suspension was modified, could result in dissolution/desorption of nonexchangeable metals from the chemically labile pool, and this should be considered when interpreting the results of these experiments. More recently, either deionized water or a dilute electrolyte solution such as 0.1 M or 0.01 M CaCl2 or Ca(NO3)2 (Smolders et al., 1999; Young et al., 2000) has been used in E-value determination of metals. In case of As, water (Hamon et al., 2004), 5 mM (NH4)H2PO4 (Tye et al., 2002), and 5 mM Ca(NO3)2 (De Brouwere et al., 2004) have all been used. The dilute salt solutions have the advantage of increasing the concentration of the analyte in the extracts due to displacement of the ion of interest from the adsorption sites. In case of CaCl2, used to mimic the Ca concentration in the soil solution, the Cd concentration in solution could also be enhanced by the complexation of Cd by Cl (Young et al., 2000). These aspects are of importance when the concentrations of the analytes in solution are close to their analytical detection limits because increased concentrations usually translate to more accurate measurements. Dilute divalent cation salt solutions also offer the advantage of decreasing the presence of colloids in solution that facilitates filtration of the samples and lessens the potential for colloidal interferences (see Section 4.5). Care is

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needed, however, to ensure that the suspension matrix does not cause precipitation of the analyte of interest that, if it occurs prior to the addition of isotope, will usually result in an underestimation of the labile pool. For example, if the goal is to assess E-values for Ag or As, it would be best to avoid use of salt solutions containing Cl or Ca, respectively, due to the potential risk of precipitation of AgCl or insoluble calcium arsenate salts. There may also be interest in assessing the E-values of cations and anions simultaneously in a soil, and here water may provide the most useful alternative. However, use of water can enhance colloid dispersion and colloids may lead to an overestimation of the E-values (see Section 4.5). To avoid this problem, a resin purification method was originally developed for phosphorus E-values by Hamon and McLaughlin (2002), and subsequently adapted for trace metals by Lombi et al. (2003; Fig. 2). This method also allows quantification of the fraction of colloidal metals that are not isotopically exchangeable and therefore not readily bioavailable. Another advantage of this resin step is that it concentrates the metals (and isotopes) and provides a constant analyte matrix, and therefore allows a more reliable determination of the E-values when metal concentrations and isotope activities in the filtrates are close to detection limits. Generally, if colloidal interferences are resolved using the resin method, differences in E-values measured using either water or CaCl2 are small for elements such as Cd and Zn (unpublished data). However, a recent study found that for Cu, significantly different E-values were obtained using water with the resin purification procedure compared to using CaCl2 (Ma et al., 2006a). In this case, the E-values measured with 0.01M CaCl2 were 30% smaller than those measured in water (þresin). In soils, Cu is more strongly associated with organic matter than either Cd or Zn, and changes in soil organic matter conformation due to an increase in the ionic strength of the soil suspension when CaCl2 was employed may have caused Cu to be sequestered in nonexchangeable form within organic colloids.

3.4. Equilibration time A distinction must be made between the equilibration time for E-values calculated, as discussed above [Eq. (2)], and the isotopically exchangeable kinetic (IEK) method. The latter uses an empirically derived function of time that was originally developed for P (Fardeau and Marini, 1968), and then adapted for other elements (Echevarria et al., 1998; Frossard and Sinaj, 1997), to assess exchangeable pools. When an isotope is added to an equilibrated soil suspension its activity in solution decreases over time. Jose and Krishnamoorthy (1972) suggested that the initial fast process is due to equilibration with soil surface sites with different absorption energies and exchange kinetics. After this initial fast process, the activity in solution slowly decreases over time probably due to

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Soil spiking

Soil suspension (24/72 h equilibration)

Soil

Centrifugation filtering < 0.2 mm

Calculation of labile metals (E-value)

+ Chelex 100 (Ca form)

Calculation of labile metals (Er-value)

Supernatant

Supernatant + colloids

Resin elution 0.5 M HNO3

Supernatant + colloids + resin (24 h equilibration)

Figure 2 Schematic representation of a conventional E-value procedure and of an E-value procedure including a resin purification step to minimize colloidal interferences [after Hamon and McLaughlin (2002) and Lombi et al. (2003)].

diffusion processes (McAuliffe et al., 1948; Tiller et al., 1972). Due to the continued reaction of the isotope with the soil system, an operationally defined equilibration time is chosen when the E-values are calculated using Eq. (2). This equilibration time is generally 1–3 days, and is intended to be long enough for the fast reaction processes to be completed, so that an increase in the equilibration time would have little further influence on the measured E-value. For instance, Young et al. (2000) reported very little change in Cd E-values after 48 h of isotope equilibration, and suggested 2 days as standard for equilibration. Other authors have found that after 2–3 days, the activity in solution stabilizes and remains almost constant for several days or weeks (Goldberg and Smith, 1984; Oliver et al., 2006;

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Tiller et al., 1972; Tongtavee et al., 2005). This indicates that, even though the choice of the equilibration time is operationally defined, in practice most published data suggest that a reasonably distinct labile pool is distinguishable when a 2–3 day equilibration time is used (Young et al., 2000). It should be noted, however, that very few studies have been of sufficient duration to allow any quantification of the more sluggish exchange kinetics that are operative on a months-to-years timescale. Ahnstrom and Parker (2001) showed that E-values for Cd (expressed as a percentage of total soil Cd) increased anywhere from 5% to 20% over 57 weeks of incubation. This slow migration of tracer into marginally labile pools would be almost impossible to detect if only monitored for a few days or weeks. When using the IEK approach, the labile pool is estimated at different equilibration times. In this case, short-term equilibration kinetics (1–100 min) are used to extrapolate E-values at longer equilibration times (Et), generally up to 90 days. These values are calculated with an equation effectively identical to Eq. (2) (Gray et al., 2004):

Et ¼ D  Msol

A
a
t

ð5Þ

where D is the soil:solution ratio, A
is the total amount of radioactivity introduced in the system, and a
t is the activity in solution at time (t). However, in this case instead of being measured directly, the term a
t is estimated from a measurement of the radioactivity remaining in the soil solution after 1 min (a
1 ) using an empirical equation (Fardeau, 1996):

"

1=n #n a
t a
1 a1 a
1 ¼ t þ þ A
A
A
A


ð6Þ

where a
1 is the radioactivity remaining in solution after an infinite exchange time and n is a parameter describing the rate of disappearance of the isotope from the solution for times longer than 1 min of exchange. The ratio a
1 =A
is the maximum possible dilution of the isotope and can be approximated by the ratio of water-soluble metal to the total soil metal concentration (Fardeau, 1996). In practice, this term is approximated by a measurement of the water-soluble metal over the total soil metal at equilibrium (Echevarria et al., 1998; Fardeau, 1996).

a
1 Msol ¼ A
Mtot

ð7Þ

Isotopic lability of Zn as predicted by the IEK method was compared to E-values measured at different equilibration times by Sinaj et al. (1999), and the agreement was very good (r2 ¼ 0.997) for equilibration times of 1–15 days.

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However, it should be noted that Sinaj et al. (1999) used 2M HNO3-extractable Zn rather than total soil Zn as the input parameter for Mtot in Eq. (7). Gray et al. (2004) investigated whether isotopically exchangeable Cd from exchange intervals up to 18 days could be predicted by the IEK method. Their results showed that for 4 of the 6 soils investigated, the IEK method could only predict Cd lability up to 24 h after which the predictions significantly overestimated the measured E-values. One of the fundamental assumptions of IEK (and isotopic dilution in general) is that at infinite time, all soil elements are potentially exchangeable. Gray et al. (2004) speculated that their results (i.e., inability of IEK to predict measured E-values) might indicate that this fundamental assumption is unrealistic and supported this conjecture with the observation that when EDTA-extractable Cd instead of total Cd was used in Eq. (7), IEK could correctly predict E-values for all soils. However, we would argue that their results are in fact a good demonstration that short-term exchange kinetics do not necessarily provide a valid model for exchange processes occurring in the longer term. For example, there is no a priori reason as to why the kinetics of exchange occurring in more recalcitrant pools such as within crystal lattices should be predictable from much more rapid surface-exchange kinetics. It is therefore not surprising that limiting the metal pool under consideration during the IEK calculation (e.g., 2-M HNO3-extractable or EDTA-extractable metal), to one which is more likely to have exchange kinetics similar to the pool sampled in the first few minutes, yields an IEK calculation that compares more favorably with measured E-values. In the first comprehensive investigation of E- and L-values for Pb, Tongtavee et al. (2005) also compared Pb lability using short-term IEK and measured E-values. These authors found that short-term IEK data could not predict the Pb E-values measured (up to 15 days) in the investigated soils. Tongtavee et al. (2005) attributed this to a lack of precision in the values used for time (t). As they pointed out, for short equilibrations, the length of time taken to separate the solution from the soil by centrifugation and filtration could have introduced substantial errors into the first two data points (usually taken at 1 and 10min). As a consequence of both of the issues described above, we would recommend that a great deal of caution be exercised when extrapolating results from very short-term exchange experiments (minutes) to quantify pools of elements that are labile in the medium/longer term (days/months).

3.5. L-value determinations L-value determinations are based on the exposure of a selected organism (traditionally a higher plant) to a soil spiked with an isotope of the element of interest. After exposure, the isotopic ratio between the introduced and native isotope is measured in the organism and the L-value is calculated as

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described in Eq. (2) (for a radioisotope). In addition to the methodological issues described above, which are common to both E- and L-values, some additional methodological aspects have to be considered in the case of L-value determinations. The first issue is related to the need to use a larger amount of soil for L-value determination because the soil has to host the biological organism used in the assessment. This causes L-values to be more labor intensive and require the addition of more isotope than for E-values. When radioisotopes are used, this also means an increased exposure to radioactivity for the experimentalist. From practical point of view, it is also more difficult to homogenize the isotope in a larger amount of dry or moist soil than in the case of an E-value determination where a small amount of soil is used in a batch system involving a soil slurry. However, a homogeneous distribution of the isotope is essential for the correct measurement of L-values (see Section 4.4). An additional issue is the period of exposure that is largely a function of the growth rate and life cycle of the organism of choice. It should be long enough so that quantifiable amounts of both trace and reference isotopes can accumulate in the organisms. This is particularly important in order to minimize errors because of the presence of the element of interest in the seeds (or juveniles) used for the L-value determination (see Section 4.4). In any case, the exposure time is generally much longer than the equilibration time (a few minutes to a few days) used for E-value determination. Therefore, the choice of the isotope for an L-value measurement may occasionally be more problematic than in the case of E-values. An example is provided by Cu wherein the radioisotope 64Cu has a half-life (12.4 h) that is suitable for E-value determinations, but far too short for the assessment of Cu lability using L-values. Therefore, in this case, the choice of the isotope is restricted to the stable isotope 65Cu. L-values using stable isotopes can be calculated using the same equation used for stable isotope E-value determination [Eq. (4)]. However, in this case, IRnat is the natural abundance ratio of the isotopes in plants grown in an unspiked soil (from control pots), and IRmeas is the measured abundance ratio of the metal in plants grown on the labeled soil (Oliver et al., 2006).

4. Uncertainties and Sources of Errors 4.1. Accuracy and precision It is clear from the equations presented above that the determination of an Eor L-value is the end result of a number of independent measurements. Consequently, any error in a single measurement is propagated through the calculation of the labile pool. In the case of E-value determinations made using a radioisotope, three independent measurements are needed: (1) the total

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activity of the tracer isotope added to the system, (2) the activity of the isotope in the solution after equilibration, and (3) the total concentration of the element in the equilibrated solution. Activities of the radioisotopes are assessed using standard methods for g- or b-radiation. These analytical techniques are usually both accurate and precise, providing spectral interferences (e.g., interference of 65Zn on 109Cd) and quenching issues have been accounted for, and if the recorded counts are sufficiently greater than the background levels. Note that appropriate decay correction is also an important consideration, especially for short-lived radioisotopes. The total amount of radioisotope added is usually analyzed in acidified ‘‘blank’’ solutions spiked with the radioisotope, but without the soil. Acidification of the solution is essential to avoid loss of isotope due to sorption to glassware and filters, especially if it is added ‘‘carrier-free’’ whereby the total number of atoms per liter in the spiking solution is very low. In the case of L-values, the total amount of radioisotope added is measured either in a digest of the labeled soil (Smolders et al., 1999) or in the stock solution used to spike the soil (Hutchinson et al., 2000). The accuracy/ precision of measurements of the analyte concentration in solutions depends on the analytical technique used and is beyond the scope of this chapter. It is, however, an important consideration in assessing the overall accuracy of a calculated E- or L-value (see Section 4.3). Generally, the use of dilute salt solutions, or a deionized water extract in conjunction with a resin purification step, both increases the concentration of the analyte in solution (thus improving accuracy) and reduces the problem of colloidal interferences (see Section 4.5).

4.2. Spike-derived artifacts When E- or L-values are determined using stable isotopes, a single instrument (usually an ICP-MS) is used for all measurements. In addition to errors due to isobaric interferences (which vary depending on the instrument utilized and are not discussed here), a significant source of uncertainty can arise from the amount of the isotope added. In fact, the decision regarding the amount of added isotope is a balancing act between two contrasting needs: on the one hand, the statistical errors of the measurements are minimized if the number of added spike atoms equals the number of isotopically exchangeable atoms in the sample (Heumann, 1988) but on the other hand, a large amount of added isotope may cause changes in the speciation of the element investigated. Moreover, if a large amount of isotope is added, some of the isotope may undergo precipitation reactions, thereby not participating in isotopic exchange. This violates one of the conditions for isotope dilution (viz ‘‘the isotope introduced in the system has not perturbed the equilibrium of the system’’) and results in an overestimation of the isotopic exchangeability. Artifacts arising from precipitation of the spike can be tested by examining the effect of an increasing spike

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concentration on measured E-values; if all of the assumptions of isotopic dilution are valid, then the E-value should be independent of the amount of spike added. Figure 3 shows the effect of increasing 206Pb spike (added at 1, 2, 5, 10, 20, 50, and 100% of total soil Pb) on the determination of the Pb E-value in two soils. The results obtained for Soil 1 show an increasing Evalue with increasing amounts of added isotope. This indicates that the E-value is already overestimated at relatively low additions of spike (<2% total soil Pb), which can be attributed to precipitation of the added spike. Note that the E-value may also be overestimated in Soil 1 at the lowest spike addition (1% total soil Pb); however, detection limit issues precluded the addition of a lower amount of isotope to assess this. The solubility of Pb in soils is much lower than the solubility of many other metals, and it would be expected that this would be reflected in a relatively small labile pool of Pb as a proportion of the total soil Pb content. In contrast, Degryse et al. (2007) remarked on the high lability of Pb found in their study in comparison to documented lability for other metals, and other studies have similarly reported relatively large values for the labile Pb pool (Table 1). We hypothesize that precisely because Pb solubility in soils is low, E- and L-value results for this element are more likely to be compromised by precipitation artifacts, resulting in an overestimation of the actual lability, unless great care is taken to prevent this.

1600 Soil 1 Soil 2

E-value (mg kg−1)

1400

1200

1000

800

600 10

100

1000

10,000

Amount of isotope added (mg kg−1)

Figure 3 Lead (Pb) E-values in two soils as a function of increasing amounts of spiked 206 Pb (Hamon and Nolan, unpublished data).

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In contrast, one concern about E- or L-values determined using radioisotopes, discussed at length in the early literature (Tiller et al., 1972), was irreversible binding of the isotope to vacant sites on the soil surface, coined ‘‘isotope fixation’’. This theory was originally proposed to try to explain severe overestimates (i.e., E-value>total soil element) of E-values that were frequently observed in soils where the E-values were expected to be low (e.g., in the case of Zn: soils with high pH and low total Zn content). The essence of this theory is that in some circumstances, isotopic exchange is impeded by the existence of vacant binding sites that instantaneously sequester and ‘‘fix’’ the introduced trace atoms, hence circumventing the exchange process because there are no atoms of native element already present at the sites to exchange with. It was thought that this problem was exacerbated by the small number of tracer atoms added during E-value determination such that a small number of these vacant sites would nonetheless cause a large, positive error in the calculated E-value. Indeed, preequilibrating the soil with carrier (with the aim being to ‘‘saturate’’ any such vacant sites, making them no longer accessible to the added tracer atoms) did yield lower E-values (Tiller et al., 1972). However, it seems thermodynamically implausible that a system that hosts a measurable (if low) concentration of isotopically exchangeable native element in solution would simultaneously host vacant sites that do not bind the soluble native element already present, but which nevertheless can selectively and irreversibly bind radioisotope or other tracer atoms added in a very small amount. One exception would be if the chemistry of the added isotope is sufficiently different from the native element that major isotopic discrimination occurs (i.e., violating the condition that ‘‘the introduced isotope behaves exactly as the natural element’’). This seems unlikely for most metals/metalloids that have a high enough atomic mass that a difference of a few neutrons is of little overall significance, though more investigation may be needed (see Section 4.4). Hamon et al. (2002b) have provided an alternative explanation to account for the results of Tiller et al. (1972) that does not invoke vacant sites. Moreover, other credible candidates that could explain reported overestimates of E-values determined in high pH or uncontaminated soils include the susceptibility of measurements made in such soils to colloidal interferences (see Section 4.5), and the fact that any measurement of analytes near their detection limit is inherently subject to analytical difficulties. Finally, changes in lability can arise if the added spike solution contains components that acidify or otherwise alter the overall sample (Gabler et al., 2007).

4.3. Error propagation Errors in the determination of E- and L-values might arise simply from experimental error, as the values depend on several exacting analyses. Excepting the early work of Tiller et al. (1972), there have been few

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systematic analyses of sources of error and uncertainty in the determination of E- and L-values. As a simple example, consider the determinations of E- and L-values made by Goodson et al. (2003) using 75Se. The quantification of the radioisotope involves two separate g-counter measurements, one for the background and one for the sample. Because the net activity is derived from the difference between the sample counts and the background counts, the overall uncertainty is calculated using standard conventions for the propagation of indeterminate errors (Wang et al., 1975):

Stracer ¼ ðs2total þ s2background Þ2

ð8Þ

where Stracer is the absolute uncertainty in the measured net radioactivity (in cpm) and stotal and sbackground are the standard deviations for the sample and background measurements, respectively (and typically taken to be the square root of the measured count rate). The uncertainty in the measurement of the ‘‘cold’’ Se can be estimated from the standard deviation of several replicate readings of a single sample using HVG-AAS, typically about 0.3 mg liter1 Se in our laboratories (¼Sreference). Then, because E- and L- values are both derived from the quotient of ‘‘cold’’ Se to isotopic tracer, the overall, relative uncertainty is given by

"
%SrðEorLÞ ¼

Stracer
Se

2


þ

Sreference ½Se

2 # 2
100

ð9Þ

where
Se is the measured, background-corrected 75Se activity in cpm and [Se] is the measured solution Se concentration in mg liter1. This uncertainty is depicted in Fig. 4 for representative values of 75Se counting and Se analysis by HVG-AAS as employed by Goodson et al. (2003). The figure suggests that, to achieve overall accuracies to within 5%, data collection should be restricted to cases where (1) total 75Se activity exceeds about 2000 cpm and (2) ‘‘cold’’ Se exceeds about 9mg liter1.

4.4. Uncertainties and sources of error specific to L-value determination In the calculation of L-values [Eq. (3)], the elemental content of the seeds should be subtracted from the total metal content of the plant. Similarly, in the case of labile pools determined using different biological systems such as earthworms or snails, the amount of metal in the juvenile invertebrates should be subtracted from the metal present in the organism at the end of the experiment. However, the seed/juvenile contribution is often negligible if the seed/juvenile size is small, and if the plants/invertebrates are allowed to

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6500 6000

Relative error in E- or L-value (%)

75Se

activity, cpm

5500 5000

32

4500

28

4000

24 20

3500

16 3000

12

2500

8

2000

4

1500

0

1000 1

3

5

7

9

11

13

15

Aqueous [Se], mg L-1

Figure 4 Relative uncertainty in the calculated E- or L-value as a function of the counting rate for 75Se by g-counting and the ‘‘cold’’ Se in solution as determined by HVG-AAS. Background count rate is taken to be constant at 495 cpm. Assumed uncertainty in the HVG-AAS determination of Se is 0.3 mg liter1.

grow to a reasonable size (Tiller and Wassermann, 1972). For instance, Hamon et al. (1997) showed that for the plants in their study, the seed contribution to the total metal content of the shoot could be minimized to <5% if the plants were left to grow for several weeks. Scott-Fordsmand et al. (2004) calculated that the Zn content of juvenile earthworms could lead to a maximum error of 10%. Scheifler et al. (2003) accounted for the initial amount of Cd in snails and the Cd contribution of the food source (lettuce) by subtracting the amount of Cd accumulated in snails grown in an uncontaminated soil from that of snails grown in a contaminated one. Oliver et al. (2006) reported that, under their experimental conditions, seed contribution to Cu L-values was not significant when tomato seeds were used because of their small size and small Cu content. In contrast, when ryegrass was used there was a significant impact on the Lvalues determined, and they had to be corrected for the seed Cu content. This contribution was determined by germinating the seeds in petri dish for 10 days and measuring the Cu content in the seedling shoots. Therefore, seed contribution is not a factor that can be discounted a priori, and care must be taken to avoid overestimation of L-values due to the seed contribution. Another consideration in the determination of L-values is possible discrimination of the isotopes during uptake. One of the key assumptions of any

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L-value determination is that all the isotopes of an element of interest, which are in equilibrium in the labile pool, are taken up and assimilated with equal ease by the organism under study. However, Weiss et al. (2005) have reported isotopic discrimination of Zn in higher plants. In particular, they observed a preferential uptake of the lighter 64Zn isotope over 66Zn when plants were grown in nutrient solutions. The extent of this discrimination is limited (0.13% to 0.26% per atomic mass unit) and as such would not have a significant effect on the determination of the labile pool, but information in this regard is scarce and more investigation is needed. One procedural aspect that is extremely important in the determination of correct L-values is the mixing of the isotope with the soil. As we discussed in Section 1 of this chapter, one of the fundamental assumptions of the isotopic dilution principle is that the introduced isotope has physically mixed with the entire labile metal pool. This condition is obviously easier to achieve in the determination of E-values, which is generally conducted using a batch system and dilute slurry (Fig. 1), than for L-values where the isotope has to be manually or mechanically mixed into the soil in which the plants will be grown (Fig. 1). Because plant roots may only sample an incomplete proportion of the soil (especially in the early stages of growth), any heterogeneity in the distribution of the introduced isotope, as well as the metal present in the soil, will have an effect on the L-values (Hamon et al., 1998). For instance, if the isotope is not homogeneously distributed and the plant roots grow in areas where the introduced isotope is not present, the L-value will be overestimated. The opposite result can occur (L-values underestimated) if the root system grows into areas where the introduced isotope is accumulated. It is therefore imperative that the soil used is homogenized and the added isotope is thoroughly mixed with the soil. The best way to achieve a thorough mixing will depend on the nature of the soil (clay soils are more difficult as they tend to form aggregates when wet) and the isotope used (mechanical mixing, for safety reasons, should be preferred when radioisotopes are used). When a large amount of soil is to be spiked for L-value determinations, adding the isotope diluted in an appropriate amount of water (rather than using a few microliters of concentrated solution) helps to ensure a more thorough mixing.

4.5. Colloidal interferences If nonisotopically exchangeable colloidal metals (Mcol) are present in the filtered solutions (Msol), then the unlabeled metal concentrations, and consequently the E-values, are overestimated as can be deduced from the following equations:

E¼

Msol Msol þ Mcol
 A  D <  A
 D

asol asol

ð10Þ

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As mentioned previously, a resin purification step was developed to remove this interference (Hamon and McLaughlin, 2002; Lombi et al., 2003). Briefly, after equilibration of the isotope with the soil suspension, the liquid phase is separated from the soil by filtration through a 0.45 or 0.2 mm filter. An ion exchange resin is used to separate the element of interest (and the isotope) from any nonlabile colloidal forms present in the filtered extract (Fig. 2). The metals and/or metalloids of interest are then eluted from the resin and their concentration and radioactivity measured. Colloidal interferences generally increase with increased pH and can lead to overestimations of the labile pool that are very significant. For example, overestimations of up to 60% for Cd, Zn, Cu, and As were found by Lombi et al. (2003, 2004). The resin purification method also allows additional information to be obtained during the determination of labile pools, specifically, an assessment of the presence of nonisotopically exchangeable metals/metalloids associated with the colloids. Sinaj et al. (1999, 2004) proposed the use of ion chromatography to assess Msol. This method should avoid colloidal interferences but is less sensitive than other analytical techniques. In addition, if Msol is measured using ion chromatography then a
sol also needs to be measured in the eluant obtained by ion chromatography and not on the original solution. Otherwise, the E-values will be most likely underestimated due to relative isotopic enrichment of the original solution as a result of isotope sorption to surface exchange sites on any colloids that are present in the original solution.

4.6. Changes in oxidation state In the case of redox-labile elements such as As, Co, Cr, Fe, Mn, and Se, there is the potential to incur large errors during E-value determination if the introduced isotope changes redox state during the equilibration period and this is not accounted for (Hamon et al., 2004). In other words, if the isotope changes redox state, and the E-value of the system is determined by the standard procedure of simply measuring the concentration and isotopic activity of the element in solution, hence ignoring the solution-phase speciation of the element and isotope, hidden within the calculated E-value are multiple components (Eq. (11)) and the result of this calculation may be incorrect (Hamon et al., 2004):

PIE ¼

Mox1 þ Mox2 a
ox1 þ a
ox2

!

!  ðA
ox1 þ A
ox2 Þ D

ð11Þ

where PIE is the potentially incorrect E-value; Mox1 and Mox2 are the solution concentrations of the two oxidation states; a
ox1 and a
ox2 are the activities of the isotope with two oxidation states in solution; A
ox1 and A
ox2 equals the total activity, A
, initially added to the system; and D, as before, is

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the dilution factor. In contrast, the correct equation for calculating the total E-value (Etot) for an element having two oxidation states can be written as follows (Hamon et al., 2004):

! Etot ¼

Mox1  A
ox1 a
ox1

!! þ

Mox2  A
ox2 a
ox2

D

ð12Þ

Hamon et al. (2004) observed that the function Etot will be equal to PIEvalue when one of the two oxidation states is not present or, for soils containing appreciable quantities of element in both oxidation states, when the Kd for the two oxidation states are equal. These authors investigated changes in As lability in two soils under different redox conditions. Arsenic exists in two oxidation states, As(V) and As(III), and it can be expected that the Kd for the two states will be very different with As(V) larger than that of As(III) (Smith et al., 1999). Preliminary experiments showed that irrespective of whether it was introduced to the soils as As(V) or As(III), a portion of the isotope converted to the alternate species during the equilibration period. Hence, Hamon et al. (2004) considered that the PIE-value (which to calculate, only requires knowledge of the total amount of isotope added, and the combined solution concentration and activity of cold and radioactive species, respectively) could not be substituted as a measure of Etot in their system. The latter (i.e., Etot) requires much more information in order to calculate, namely, knowledge of the solution concentration and activity of cold and radioactive As(V) and solution concentration and activity of cold and radioactive As(III) as well the Kd of one of the redox species. Hamon et al. (2004) solved this problem by coupling the isotopic dilution technique with a speciation of both the stable and the radioisotope by HPLC-ICP-MS and HPLC-g-counting. In addition, the Kd for the As(III) species was determined after repeated extractions with 0.1 M NH4H2PO4 followed by HPLC-ICP-MS analysis that enabled assessment of the total amount of 73As(III) in the system. However, we have realized that the function Etot will also be equal to PIE-value when the specific activities of the species in solution are the same, that is, when:

a
ox1 a
¼ ox2 Mox1 Mox2

ð13Þ

This observation potentially greatly simplifies the determination of Etot in systems with different redox states because if a determination of the solution concentration and activity of the different species shows that their specific activities are the same, then the extractive step to establish the Kd of one of

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the species is not necessary, as Etot can be calculated using the PIE-value equation. Note further that, in this case, the E-values for the individual redox states can also be determined as follows:

!

Mox1  A
ox1 a
ox1

PIE ¼ Etot ¼

!!

þ

Mox2  A
ox2 a
ox2

D

ð14Þ

and

A
¼ A
ox1 þ A
ox2 Hence,

! Mox1  A
ox1
aox1

þ

!! Mox2

 ðA  Aox1 Þ D ¼ PIE a
ox2

ð15Þ

ð16Þ

Assuming the specific activity of the two redox species has been measured, then the only unknown factor in Eq. (16) is A
ox1 , which can therefore be determined, allowing also the determination of A
ox2 , and thus, the E-values for both the oxidation states, Eox1 , and Eox2 :

Eox1 ¼

Eox2 ¼

! Mox1  A
ox1 D a
ox1

ð17Þ

! Mox2  A
ox2 D a
ox2

ð18Þ

Furthermore, if the specific activities of the species in solution are not the same, this in fact indicates that the system has not yet reached a state of (pseudo) equilibrium. One theoretical corollary of this observation is that it should be possible to achieve identical solution-specific activities for the two species by increasing the equilibration time. We would recommend that as a first step an assessment be made as to whether this is likely to occur for the system under investigation because, as will be seen from the discussion below, this would be the simplest approach toward determining the E-value in systems containing different redox species where the initial measurement gives different specific activities. However, in many cases, it may not be feasible to increase the equilibration time due to practical constraints associated with maintaining a relatively constant redox status in a batch system, which can be very difficult to achieve over longer time periods. Hence, in practical terms, it may never be possible to

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achieve a state of (pseudo) equilibrium for some redox-labile systems. For systems where a (pseudo) equilibrium has not been achieved, the introduced isotope is still being converted to the other redox state. Hence, the size of A
ox1 is either continuing to decrease or continuing to increase depending, respectively, on whether the isotope was added in the same form as A
ox1 or was added as the other redox species; the size of A
ox2 is also changing but in the opposite direction. Whether a reasonable estimate of the E-value is achievable under these circumstances can be tested by comparing E-values obtained following addition of either the A
ox1 or the A
ox2 form of the isotope as follows. Note that here determination of the E-value requires that the total amount of one of the redox forms of the isotope remaining in the system at equilibrium can be measured, for example, by using the extraction method employed in Hamon et al. (2004) for assessing the total 73As(III); the total amount of the other form is determined by difference. When the A
ox1 form of the isotope is used, the value of A
ox1 measured at the end of the equilibration period will be an underestimate compared to the actual average size of A
ox1 that has contributed to exchange with the labile A
ox1 pool because the size of A
ox1 has continually decreased since the beginning of the equilibration period by being converted to the other redox form. In contrast, when the A
ox2 form of the isotope is used, the measured value of A
ox1 will be an overestimate compared to the actual average size of A
ox1 because there was no A
ox1 present at the beginning of the experiment, A
ox1 has only accumulated in the system by being converted from A
ox2 . The degree to which the two Eox1 values calculated from the two measured A
ox1 values also underestimate and overestimate the ‘‘true’’ E-value, and thus, the degree to which they differ from each other, depends on how rapidly the A
ox1 form of the isotope is able to redistribute across the labile pool in response to incremental changes in the amount of A
ox1 in the system during the equilibration period. If, for example, we imagine a system that at all times during the equilibration period responds to changes in A
ox1 with an instantaneous redistribution, then, despite being based on an underestimate and an overestimate of A
ox1 , both of the Eox1 values calculated from measurements taken at time t would exactly match the true (by definition) E-value at time t. In reality, the rate of redistribution is not instantaneous and may change with time (and may differ between redox states so the alternate case relevant to A
ox2 should also be checked), so the two Eox1 (Eox2 ) values will differ, but they provide a boundary within which the ‘‘true’’ E-value is located. Hamon et al. (2004) calculated both the Etot and PIE-values, and found that the PIE-value overestimated Etot by up to more than an order of magnitude in samples that contained high amounts of As(III) relative to As(V). This indicates that for those samples, the system had not yet reached a state of (pseudo) equilibrium. This consequently invalidates both the hypothesis presented by Hamon et al. (2004) that equilibrium of the oxidation states of the isotope would be rapid because only small quantities of the radioisotope were added, and also, therefore, the presumed test of this

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hypothesis [i.e., the same Etot values for each species were obtained irrespective of whether the introduced isotope was in the As(V) or As(III) form]. However, the fact that this hypothesis was invalid fortunately is not a significant problem in terms of the results obtained in that study because the E-values for both redox species were similar irrespective of the form of the isotope that was introduced and hence, as discussed above, the reported Etot values are a good approximation of the actual E-values. A similar issue was tackled by Collins et al. (2006) when investigating the E-values of Se in soils and sediments. Using a double-labeling technique in combination with HPLC-ICP-MS, these authors were able to demonstrate that, in contrast to As, the introduced isotope did not change oxidation state in their soils during their equilibration period (24 h). This facilitated the determination of E-values of selenite and selenate because, in this case, only the solution-phase speciation of the Se isotopes needed to be performed. To our knowledge, these are the only two examples where speciation of redox sensitive species has been taken into account in E-value determination. The approaches used by Hamon et al. (2004) and Collins et al. (2006) were successful in determining the lability of different oxidation species of As and Se, respectively. Any other study conducted on redox-sensitive elements (e.g., Table 1) should be viewed with caution if the speciation of the element of interest has not been considered. This issue is likely to be much more challenging in the case of cationic metals such as Co, Fe, and Mn that are often present in the soil in multiple oxidation states, are strongly sorbed, and/or readily form insoluble oxidation products and/or coprecipitates. As discussed above, if isotope introduced in the soil undergoes a change in oxidation state over the equilibration period (as in the case of As but not Se), but does not attain a state of (pseudo) equilibrium, the isotopic Kd for at least one of the oxidation states needs to be measured to estimate Etot. This was possible, without disturbing the soil equilibrium, for As(III) due to its weak sorption by soil, but may be problematic in the case of strongly sorbed ions such as Co, Fe, and Mn. An early recognition of this problem was suggested by Lopez and Graham (1970) who investigated the lability of Mn, Fe, Zn, and Cu in soil. These authors reported that E-values for Mn and Fe were dependent on the composition and pH of the extracted solutions whereas those for Cu and Zn were not, and suggested that this was due to ‘‘the oxidation–reduction properties of the element concerned.’’

5. Interpretation of E-Values E-values have been compared to elemental concentrations of organisms, or to growth responses, to assess their use for predicting bioavailability (e.g., Ganai et al., 1982; McBeal et al., 2007; Nolan et al., 2005; Pandeya

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et al., 1998). This use may be motivated by the fact that E-values have some commonality with definitions used to describe bioavailability. For instance, Sposito (1989) stated that a chemical element is bioavailable, specifically to terrestrial plants, if it is present as, or can be readily transformed to, the aqueous free ion; if it can move to plant roots on a timescale that is relevant to plant growth and development; and if once absorbed by the root, it affects the life cycle of the plant. However, the E-value is an empirical measure based on soil—solution partitioning of an isotopic tracer within the exchangeable pool, and is not designed to measure bioavailability per se. In other words, while the E-value may quantify the potentially reactive pool of an element over a specified length of time (Tye et al., 2002), there is no reason that this should reflect actual element uptake by, or toxicity to, an organism because these factors are not controlled directly by the size of the labile pool. A simple case to demonstrate this is as follows: one can envision three different soils that have the same sized labile pool (i.e., identical E-values) for a given metal, but in the first soil, most of the labile metal is partitioned to exchange sites on the soil solid phase (high Kd). In the second soil, more of the labile metal is free in the solution phase (low Kd), while in the third soil, the solution-phase metal is exchangeably complexed by various soluble ligands. For example, Collins et al. (2003) clearly showed that decreasing the pH and addition of organic ligands greatly affected the Kd for Cd in an acidic soil, but at the same time had no significant effect on the lability of Cd (E-value) in that soil. Despite the three identical E-values, organisms growing in these three soils will typically exhibit different responses in terms of metal uptake or toxicity. This is because these responses are strongly influenced by the concentration (activity) and speciation of the metal in solution (Campbell, 1995; Parker and Pedler, 1997), which, as can be seen from the foregoing example, bears no direct relation to the E-value per se. Using the IEK method, Fardeau and Jappe (1978) introduced the index r (1)/R [equivalent to a
1 /A in Eq. (6)] to estimate the P-buffering capacity of different soils. Theoretical problems with this approach are discussed elsewhere (Hamon et al., 2002b). More recently, Gray et al. (2004) used the same index to assess the soil-buffering capacity of Cd and argued that the higher the ratio, the less readily the ion is removed from the solution, and hence the more highly buffered the soil is. However, we disagree with this assertion and draw attention to the fact that, in an acidic soil for example, an isotope of a metal could remain in solution simply because the Kd for that metal is small (e.g., as a consequence of a low cation exchange capacity in conjunction with protons). In this case, the system would not be well buffered (the small sorbed pool could not replenish the large pool in solution) but the r(1)/R would nevertheless be large. The aforementioned considerations are important in the proper interpretation of E-values. In particular, we would like to emphasize that there is

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no direct linkage between the labile pool and the amount of metal taken up by an organism. Nonetheless, E-values can provide valuable information and have been employed to: (1) investigate various management options such as in situ remediation using soil amendments (Hamon et al., 2002a; Lombi et al., 2003, 2004); (2) assess the specificity and selectivity of sequential extraction procedures (Ahnstrom and Parker, 1999); (3) investigate the aging process for soil metals (Crout et al., 2006; Ma et al., 2006b,c; Nakhone and Young, 1993; Smolders et al., 1999; Young et al., 2001); (4) predict solubility and free-ion activity of contaminants in soils as a function of soil characteristics (Tye et al., 2002, 2003), and as a result of environmental changes (Hamon et al., 2004). Moreover, in combination with L-value measurements, E-values have been used to assess whether plants (e.g., Denys et al., 2002; Gerard et al., 2000; Goodson et al., 2003; Hammer et al., 2006; Hutchinson et al., 2000), snails (Scheifler et al., 2003), or earthworms (Scott-Fordsmand et al., 2004) can mobilize metals or metalloids from soil (see Section 6). When a comparison of E- and L-values is conducted, it should be remembered that the isotopically exchangeable pool is an operationally defined assay, whose value depends upon equilibration time (Echevarria et al., 1998; Young et al., 2005). This should be taken into account in the measurement of L-values, where contact between the isotope and soil may extend to several weeks or months. In this case, unless a comparable equilibration time is used, E-values measured or estimated by IEK may be lower than the L-value simply due to different equilibration times rather than to any other factor. However, this may not be a serious problem because, as discussed in Section 3.4, E-values seem to be reasonably constant if the equilibration time is long enough to fully embrace the rapid exchange reactions (2–3 days).

6. Interpretation of L-Values Plants and other organisms living in soil absorb ions from the soil solution. (Possible exceptions include earthworms that may additionally sorb ions more ‘‘directly’’ from the solid phase, through the action of gut fluids.) As a consequence of this uptake, exchangeable ions are released from the solid phase into the solution, and this exchangeable pool can be labeled using an isotope. Hence, organisms that access metals or metalloids from only the exchangeable pool will have the same specific activity as the soil solution (assuming free of colloidal interferences) and, for a given soil, E- and L-values should be identical. This is true as long as the contribution from seed/juveniles/food sources can be quantified or is negligible, providing there is no isotopic discrimination during uptake, providing the equilibration times are effectively equivalent, and as long as the isotope is

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physically and homogeneously mixed with the entire exchangeable pool, and the other conditions of isotope dilution are independently met for both the E- and the L-value systems (see Sections 3 and 4). However, plant roots may have the ability to mobilize nutrients in the rhizosphere and access nonexchangeable nutrients [for review, see Hinsinger (2001)]. Therefore, E- and L-values have been used in combination to assess whether organisms can access nonlabile pools of metals and metalloids. It should be noted that, in theory, L-values can only be equal to or larger than corresponding E-values. This statement is based on the assumption that the metal pool in soil that is the most available to plants, which can be assumed to be the free ions in solution, is completely isotopically exchangeable. Therefore, Lvalues smaller than E-values have presumably been obtained as a result of analytical or procedural errors, including the nonhomogeneous distribution of the isotope in soils used for L-value assessment, or colloidal interference in determining E-values. A further reason (S. Young, personal communication) may be due to the fact that the E-value provides a snapshot of the system at a given time, whereas the L-value is an integration of the uptake of isotopes over the whole life of the plant. Thus, in the event of a slow rate of reaction between the isotope and the soil, the L-value may be smaller than an E-value that has been measured (or estimated by IEK) after an equilibration time equal to the plant growth period because when the plant started growing, the L-value was smaller (as was the E-value at that time) than at the final sampling time. In practice, however, because the major reaction processes between the introduced isotope and the soil are typically completed before a sown plant starts to take up significant quantities of the analyte of interest, the probability of the L-value being significantly lower than the E-value due to this reason can be considered very low. A list of studies showing where E- and L-value comparisons have been done can be seen within Table 1 and numerical data from the available literature has been compiled in Fig. 5. The experimental data from seven publications reporting both E- and Lvalues for Cd and eight publications for Zn have been compiled in Fig. 5A and B. The investigations of Ayoub et al. (2003) and Hutchinson et al. (2000) both tried to assess whether the Cd and Zn hyperaccumulator plant Thlaspi caerulescens could access a larger pool of Cd than nonaccumulator plants. The results indicated that all the plant species accessed the same pool. In the former study, the Cd and Zn E-values were generally larger than the L-values. As suggested by the authors, this was probably due to heterogeneity in the distribution of the isotope in the soil used for the L-value experiment; Gerard et al. (2000) explained their results similarly (Fig. 5A and B). The results of Hutchinson et al. (2000) were more variable, and the authors concluded that the E- to L-value ratio was very close to unity. Sterckeman et al. (2005) conducted a similar investigation with Cd and Zn using both an acid and a calcareous soil. Cadmium E- and L-values were

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A 100

L-values (mg kg-1)

Cd

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Ayoub et al. 2003 Hutchinson et al. 2000 Scheifler et al. 2003 Smolders et al. 1999 Stacey et al. 2001 Sterckeman et al. 2005 Gerard et al. 2000

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0.1 0.1

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Ayoub et al. 2003 Sinaj et al. 2004 Sinha et al. 1977 Smolders et al. 1999 Stacey et al. 1999 Sterckeman et al. 2005 Tiller et al. 1972 Rule and Graham 1976

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Figure 5 (Continued )

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C 1000 Cu, Ni, Pb, Se

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Cu: Oliver et al. 2006 Ni: Echevarria et al. 1998 Ni: Massoura et al. 2004 Pb: Tongtavee et al. 2005 Se: Goodson et al. 2003

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Figure 5 Relations between experimentally measured L- and E-values for different soils, plants, and metals: (A) Cd (N ¼ 79); (B) Zn (N ¼ 140); (C) Cu (N ¼ 6), Ni (N ¼ 26), Pb (N ¼ 5), and Se (N ¼ 16); (D) Mn (N ¼ 48) and Fe (N ¼ 16).

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similar in the acid soils for all species investigated. In the calcareous soil, L-values for Cd were larger than E-values for all species, with the exception of the hyperaccumulator plant. In contrast, Zn L-values were always larger than E-values in both soils and for all plant species. Among the plant species investigated, ryegrass (Lolium perenne) showed the largest L-values. This result was interpreted according to the view that the Graminaceae may excrete phytometallophores that have a rather general affinity for transition metals (Parker et al., 2005; Welch, 1995), which could mobilize metals in the rhizosphere (i.e., access the chemically labile pool). Smolders et al. (1999) and Sinaj et al. (2004) also compared E- and L-values using graminaceous species. Smolders et al. (1999) found consistent, albeit only marginally, greater L- than E-values for both Cd and Zn. However, Sinaj et al. (2004) did not find any difference between E- and L-values for Zn using ryegrass. Tiller et al. (1972) investigated Zn E- and L-values in 25 different soils using Trifolium spp. No differences were observed in soils with pH < 7 whereas, with calcareous soils, a detailed investigation demonstrated that E-values were overestimated due to methodological problems. The results reported by Stacey et al. (2001) show very large differences between E- and L-values that the authors attributed to the different isotope equilibration times in their determinations. While it is likely that this may be a contributing factor, because the isotopic equilibration time for the E-value determination was only 24 h, the differences appear too large to be solely caused by this experimental parameter. Finally, the results obtained by Sinha et al. (1977) and Rule and Graham (1976) for Zn show a general agreement between E- and L-values but it should be noted that a pH-buffered DTPA solution was used in the E-value determination. Thus, the overall consensus with respect to E- versus L-values in the case of Cd and Zn is that, if these metals are mobilized from nonexchangeable (chemically labile) pools by plants at all, this only occurs to a very limited extent and is species- and soil-specific, with graminaceous plants more likely to mobilize metals than dicotyledonous species (including the Cd and Zn hyperaccumulators). This is reinforced by the observation that the root exudates of the hyperaccumulator T. caerulescens were much less able to mobilize Cd and Zn when compared to the root exudates of Fe- or Zndeficient wheat (Triticum aestivum) (Zhao et al., 2001). Comparisons of E- and L-values for Cu, Ni, Pb, and Se show a generally good agreement between the two techniques (Fig. 5C). An exception is provided with Ni by Echevarria et al. (1998), who presented data showing E-values, which in most cases exceeded L-values by twofold. This may be due to heterogeneous mixing of the isotope in the soil used for the L-value determination (Gerard et al., 2000; Hamon et al., 1998), or to overestimation of the E-values, which were estimated using the IEK technique, for reasons discussed above (see Section 3.4). The Pb data are derived from the study of Tongtavee et al. (2005) who used a stable Pb isotope for

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determination of the E- and L-values. The data show a good agreement between E- and L-values with the exception of the uncontaminated soil where the L-value was clearly erroneous because it was much larger than the total soil Pb content. The authors suggested that this may be due to rapid ‘‘fixation’’ of the introduced Pb isotope. However, this would also be expected to affect E-values determined in the same soil, but that was not the case (Fig. 5C). More likely, either nonhomogeneous mixing of the spike during the L-value determinations or a substantial, unaccounted for contribution of Pb from the seed caused this discrepancy. It is important to emphasize that overestimates of the labile pool arising from precipitation of the added spike, which as previously discussed (Section 4.2) is a particular consideration in studies done with stable Pb isotopes, would not necessarily be revealed by a comparison of E- and L-values, as the precipitation artifact would erroneously inflate both the E- and L-values similarly. Comparison of E- and L-values for Mn and Fe (Fig. 5D) shows large and inconsistent differences. This may be due to several reasons including the fact that E-values were determined using either pH-buffered 5-mM EDTA solutions or a 0.1-M H3PO4 solution (see Table 1). Furthermore, as suggested by Lopez and Graham (1970), both Fe and Mn were added as divalent cations and the isotope added could have been oxidized in the soil and therefore precipitate as oxyhydroxides, as recognized by Dyanand and Sinha (1985), or, as discussed above, could be due to the problems associated with performing isotope dilution experiments on elements that commonly exhibit more than one oxidation state in ambient conditions. Two studies have recently assessed whether soil invertebrates can access nonexchangeable (chemically labile) pools of metals. Scott-Fordsmand et al. (2004) reported that the earthworm Eisenia andrei accessed the same soil Zn pool as lettuce, and that this pool is the isotopically exchangeable Zn. In contrast, Scheifler et al. (2003) suggested that snails could access a part of the nonlabile Cd pool. In this study, the Cd E-value, estimated using IEK, was 10.08 (1.27) mg kg1 whereas the labile Cd measured using the snail was 11.85 (0.40) mg kg1. This difference, even if statistically significant, is rather modest considering the large number of independent measurements required in this experiment (see Section 4.3). This is apparent when the results of Scheifler et al. (2003) are viewed in the context of the other studies investigating Cd mobilization using E- and L-values (Fig. 5A). The variability observed in Fig. 5A–D, and the potential sources of error when comparing E- and L-values, suggests that comparing these two independent measurements is difficult, and that care should be taken when discussing the findings. Perhaps a simpler alternative is to assess whether a specific plant (or invertebrate) can mobilize nonexchangeable (chemically labile) forms of metals in a given soil via a direct comparison of the L-values of different species. This approach was used by Hamon et al. (1997) who investigated the uptake of Cd and Zn by seven plant species and found that,

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with the exception of Cd uptake by canola, all plants seemed to access the same metal pool. A similar approach has been also adopted by several other authors in the last few years (see Table 1), and generally the results yielded small and rarely significant differences between the species investigated. L-values have also been used to assess ageing processes of metals in soils (Hamon et al., 1998) and, in studies conducted in the field, to infer the contribution of atmospheric deposition to the total plant content of metals (e.g., Dalenberg and Vandriel, 1990; Jensen and Mosbaek, 1990; Mosbaek et al., 1988, 1989). Conclusions about deposition rates from some of these studies may need revision as they were not necessarily designed to recognize, or control for one or more of the range of artifacts described above (e.g., contribution of metal from the seed, nonhomogeneous mixing of the isotope with the soil, and so on) that, as well as atmospheric deposition, could also give rise to the inflated L-value, which in these studies was attributed solely to atmospheric deposition. For example, recalculation of data from Dalenberg and Vandriel (1990) shows L-values for Pb for plants grown in a filtered air chamber (where atmospheric deposition should be minimal) that range from 100% to more than 2000% of the total soil Pb. The authors ascribed the lower than expected specific activity in these plants to contaminated air leaking into the chamber, though it is equally if not more likely that one or more of the previously mentioned artifacts was responsible. However, these studies also serve as a reminder that surface contamination can lead to an overestimation of the L-value and hence steps should be taken to prevent this from compromising results. In theory, the isotope dilution E- and L-value methods are simple to use. In practice, however, it is clear from the above discussion that these methods are subject to a number of both theoretical and methodological pitfalls that can easily result in erroneous conclusions being drawn from the data that is generated. Table 4 summarizes the potential methodological sources of error that we have discussed, and aims to provide a troubleshooting guide and check list to help researchers who may be using these methods for the first time. However, it should be noted that these pitfalls are not necessarily intuitive, and many of them have emerged only with the benefit of hindsight and/or through a process of trial-and-error, which is still ongoing. For example, similar issues as occur with redox-sensitive species may exist for elements that are present in significant amounts in solutions as complexes/compounds that can partition to the solid phase, and that are exchangeable with the isotope, but that are only slowly exchangeable such that they do not undergo complete exchange during the equilibration period. In fact, decreased exchangeability of organically complexed Cu arising from condensation of the complexes in Ca electrolyte could contribute to the differences found between E-values determined by Ma et al. (2006a) for Cu using the waterþresin method versus CaCl2 (see section 3.3). However, more investigation is required to assess this issue. Hence,

Table 4 Troubleshooting guide and checklist for E- and L-value determinations Checklist

E > tot

Result status Analytical accuracy and precision poor Precipitation of added isotope Spike solution too acidic/corrosive Reactive suspension matrix for analyte of interest Isotope discrimination occurring Preexisting metal in organism or food unaccounted for Contamination by, e.g., atmospheric deposition Nonhomogeneous mixing of added isotope Colloidal interferences Multiple oxidation states present but not accounted for Spike equilibration time not consistent between E- and L-value method



E < tot

p

L > tot



L < tot

p

E>L



E¼L

E
p

p

 

c co co cu

 

c co co



c co co

c co co cu



c

 

c co



c

c co



co



c



n

c





 

n

co,cu*

n

n

c

n

n

 



co,cu*

co





tot ¼ total concentration of the element of interest in soil. p ¼ Results highly likely to be acceptable. However, possible hidden interferences arising from problems identified in same column should never be completely discounted unless they have been shown to be insignificant.  ¼ Results probably unacceptable.  ¼ Possible sole explanation for unacceptable result. c ¼ Could cause either over- or underestimate of labile pool. co ¼ Will only cause overestimate of labile pool. cu ¼ Will only cause underestimate of labile pool. * ¼ Depends on method used (refer to text). n ¼ Problem possible but unlikely in this circumstance using standard methods.

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while we have endeavored to provide a comprehensive guide in Table 4, it will likely be subject to revisions in the future.

7. Future Applications The future use of isotopic dilution techniques is likely to expand due to the development of robust and relatively simple analytical techniques that are able to accurately determine stable isotope ratios. The use of enriched stable isotopes will not only permit the study of elements for which radioisotopes are not available, too expensive, short lived, or dangerous to use, but may further allow application of isotopic dilution techniques in field studies. In recent years, isotopic dilution techniques have been recognized as an extremely flexible set of tools to investigate a variety of processes related to bioavailability and mobility of micronutrients and contaminants. Moreover, new methodologies and approaches have led to the use of these techniques to investigate new area of research. For instance, new insights on colloidalfacilitated transport of metals have been achieved using the resin technique described previously (Hamon and McLaughlin, 2002; Lombi et al., 2003) as well as by combining the principle of isotopic dilution with ultrafiltration methods (Sivry et al., 2006). The next step forward in this direction could focus on the coupling of isotopic dilution and Field Flow Fractionation (FFF)-ICP-MS. For instance, FFF has been recently employed to separate engineered Zn oxide nanoparticles in soil suspension (Gimbert et al., 2007) and, when combined with isotopic dilution techniques, could provide a powerful tool in the emerging area of environmental risk assessment of nanomaterials. As pointed out by Tye et al. (2003) and Young et al. (2007), isotopic dilution techniques may also provide an ideal starting point for whole soil modeling of metal speciation and partitioning. Solution equilibrium models such as GEOCHEM (Parker et al., 1995), NICA (Gooddy et al., 1995), or WHAM (Tipping, 1994) are being complemented by models based on adsorption on specific solid phases to simulate whole-soil behavior of metals and metalloids. Since these models are based on the assumption that all the elements are free to rapidly equilibrate, situations in which this assumption is invalid can create serious problems in the modeling exercise. This assumption clearly cannot be met in a soil system where a significant part of the metal/metalloid of interest may be entrapped in the crystal lattice of minerals or in precipitates. We have demonstrated that the same problem could be present in soil solution due to the presence of nonexchangeable forms of metals/metalloids associated with colloids (Lombi et al., 2003). As discussed previously, the isotopic dilution principle is based on the dilution

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of the introduced isotope in the exchangeable pool, which is consequently determined. Therefore, this reactive/exchangeable pool represents the ideal starting point for modeling. In our opinion, the use of isotopic dilution technique in combination with speciation techniques (such as HPLC-ICP-MS, secondary ion mass spectroscopy, or synchrotron spectroscopy) has a tremendous potential in terms of investigating soil processes such as metal/metalloids aging or mobilization. For instance, Hamon et al. (2004) combined isotopic dilution with a chromatographic/mass spectroscopic As speciation method to simultaneously determine the labile pools of arsenite and arsenate. Application of this method identified a suite of mechanisms controlling mobility and speciation of As in contaminated soils subjected to changes in microbial activity, pH, and redox conditions. A current limitation of isotopic dilution techniques is a lack of molecular understanding of the chemistry of the labile metal pool associated with the soil solid phase, with only a few studies investigating this aspect (e.g., Bailey et al., 2005; Lamm et al., 1963). Synchrotron-based techniques, which allow characterization of the chemical environment surrounding the solid-phase metal, are ideal to complement, and provide a molecular underpinning for isotopic dilution. This coupling was demonstrated by Sarret et al. (2004) who investigated Zn speciation in soil using isotopic dilution, micro X-ray fluorescence, and extended X-ray absorption fine structure spectroscopy. A similar approach was employed by Bailey et al. (2005) to investigate time-dependent changes in lability of Cd. Similar studies in which different techniques are combined with isotopic dilution methods are likely to become more numerous in the future. Further afield, the analytical progress made in terms of detection of isotopic ratios has opened the door to novel and exciting applications of isotopic dilution techniques to new areas of research. For instance, using stable isotopic dilution, Maddaloni et al. (1998) investigated bioavailability of soil-borne Pb in humans. Sander and Pignatello (2005) developed an isotopic dilution technique using 14C-naphthalene to assess true hysteresis (i.e., irreversible sorption) of this compound to organic matter. We expect that the use of isotopic dilution techniques in the investigation of the behavior of xenobiotics in the environment will increase rapidly in the near future.

ACKNOWLEDGMENTS The authors would like to thank Prof. Scott Young, Nottingham University, for valuable comments on the manuscript.

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