Selective chemical extraction of heavy metals in tailings and soils contaminated by mining activity:...

Selective chemical extraction of heavy metals in tailings and soils contaminated bymining activity: Environmental implications

Paulo J.C. Favas a,d,⁎, João Pratas b,d, M. Elisa P. Gomes a,d, V. Cala c

a Departamento de Geologia, Escola de Ciências da Vida e do Ambiente, Universidade de Trás-os-Montes e Alto Douro, Apartado 1013, 5001–801 Vila Real, Portugalb Departamento de Ciências da Terra, Faculdade de Ciências e Tecnologia, Universidade de Coimbra, Largo Marquês de Pombal, 3001–401 Coimbra, Portugalc Departamento de Geología y Geoquímica, Facultad de Ciencias, Universidad Autónoma de Madrid, 28049 Madrid, Spaind Centro de Geociências da Universidade de Coimbra, Portugal

a b s t r a c ta r t i c l e i n f o

Article history:

Received 3 September 2010Accepted 28 April 2011Available online 6 May 2011

Keywords:

Trace element mobilityGeochemical speciationSequential extractionMining soilsErvedosa mine

Total concentrations of chemical elements in soils may not be enough to understand the mobility andbioavailability of the elements. It is important to characterise the degree of association of chemical elements indifferent physical and chemical phases of soil. Another geochemical characterisation methodology is to applysequential selective chemical extraction techniques. A seven-step sequential extraction procedure was usedto investigate the mobility and retention behaviour of Al, Fe, Mn, Cu, Zn, Pb, Cr, Co, Ni, Mo, Cd, Bi, Sn, W, Ag, Asand U in specific physical–chemical and mineral phases in mine tailings and soils in the surroundings of theabandoned Ervedosa mine. The soil geochemical data show anomalies associated with mineralised veins orinfluenced by mining. Beyond the tailings, the highest recorded concentrations for most elements are in soilssituated in mineralised areas or under the influence of tailings. The application of principal componentsanalysis allowed recognition of (a) element associations according to their geochemical behaviour and(b) distinction between samples representing local geochemical background and samples representingcontamination. Some metal cations (Mn, Cd, Cu, Zn, Co, Cr, Ni) showed important enrichment in the mostmobilisable and bioavailable (i.e., water-soluble and exchangeable) fractions due likely to the acidicconditions in the area. In contrast, oxy-anions such as Mo and As showed lower mobility because ofadsorption to Fe oxy-hydroxides. The residual fraction comprised largest proportions of Sn and Al and to alesser extent Zn, Pb, Ni, Cr, Bi, W, and Ag, which are also present at low concentrations in the bioavailablefractions. The elements in secondarymineral phases (mainly Fe, Mn, Cu, Zn, Cd, Pb,W, Bi, Mo, Cr, Ni, Co, As andU) as well as in organic matter and sulphides are temporarily withheld, suggesting that they may be releasedto the environment by changes in physico-chemical conditions.

© 2011 Elsevier B.V. All rights reserved.

1. Introduction

Investigations of the partitioning of metals in soils, sediments andwaste allow better understanding of metal behaviour than studies oftotal metal concentrations, which provide limited information on themobility and bioavailability of the metals being studied. Sequentialchemical extractions use a series of successively aggressive reagents toextract metals associated with specific fractions of sediments (Bogleand Nichol, 1981; Cappuyns et al., 2007; Tessier et al., 1979), soils(Cohen et al., 1998; Hirner, 1992; Li and Thornton, 2001; Pueyo et al.,2008) or mine wastes (Dold, 2003; Fanfani et al., 1997). Sequentialextraction procedures are greatly influenced, however, by experimentalfactors such as choice of reagents, extraction time and weight ratio ofsample to volume of solution. There are many criticisms of theseprocedures including the lack of specificity of reagents, the possibility of

re-adsorption of released metals to remaining fractions (Belzille et al.,1989; Hass and Fine, 2010) and the potential alteration of phases duringextraction (Li and Thornton, 2001). Selective extractionmethods allow,nevertheless, discrimination between the different sources (i.e.,geogenic and/or anthropogenic sources) of element concentrations insamples. Therefore, the ability to simulate different environmentalconditions (i.e., acidic, alkaline, oxidising or reducing) in contact withthe solid phase of soils, sediments and wastes makes the methods ofselective extraction veryuseful in characterising the chemical behaviour(i.e.,mobility, solubility, bioavailability and toxicity) of trace elements inthe environment.

Mine tailings often contain high concentrations of potentially toxicelements whose mobility may pose an environmental hazard forsurrounding ecosystems. The objective of the present study was toevaluate the mobility and retention behaviour of Al, Fe, Mn, Cu, Zn, Pb,Cr, Co, Ni, Mo, Cd, Bi, Sn, W, Ag, As and U in specific physical–chemicalandmineral phases inmine tailings and soils in the surrounding area ofthe abandoned Ervedosa mine (N Portugal) by applying a seven-stepsequential extraction procedure.

Journal of Geochemical Exploration 111 (2011) 160–171

⁎ Corresponding author. Tel.: +351 259 350 220; fax: +351 259 350 480.E-mail address: [email protected] (P.J.C. Favas).

0375-6742/$ – see front matter © 2011 Elsevier B.V. All rights reserved.doi:10.1016/j.gexplo.2011.04.009

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2. The study area

2.1. Geological setting

The Ervedosa mine (also known as the Tuela mine) in northeasternPortugal is situated in the schistose domain of the Galiza-Trás-os-Montes Zone of the Iberian Terrane (Fig. 1). Muscovite–biotite andmuscovite granites intruded into Silurian phyllites and quartzites andCarboniferous biotite granitoids at Ervedosamine (Fig. 1b). The Silurianmetasediments are cut by Sn-bearing quartz veins (Beetsma, 1995). Themineralisation is associated with the muscovite granite and wasprobably derived from the late stages of fractional crystallisation ofthe granite suite because magmatic differentiation was responsible forthe increase in Sn content of granites and theirmicas (Gomes andNeiva,2002). In the mine, Sn-bearing quartz veins are hosted in fracturesrelated to a dextral N30°W-trending ductile shear zone (Fig. 1b).Cassiterite is the main ore mineral. It is associated with varioussulphides (arsenopyrite, pyrite, sphalerite, pyrrhotite, chalcopyriteand stannite), matildite, bismuthinite, native bismuth and otherminerals (Gomes and Neiva, 2001).

The Ervedosa mine, exploited in the past by the Phoenicians andthe Romans, was in intermittent operation in the 1928–1969 period.The lastmining operationwas underground, which continued upwardinto two large open pits. Cassiterite and sulphides were exploited for,respectively, Sn and arsenic trioxide (As2O3). Alluvial placers ofcassiterite were also exploited. However, there has been no mining inthe area since 1969 and the mine was abandoned without anyenvironmental remediation. The rock waste and tailings, which stillcontain metals, were deposited on the ground and are currentlypartially covered by natural vegetation. Exposure of these materialsto air and water produces acidic water from the abandoned minegalleries and tailings, facilitating the release of contaminants tosurrounding environments (Gomes and Favas, 2006).

2.2. Climate, soils and land use

Topographic elevations in the Ervedosa mine area vary between350 m and 650 m. The area is characterised by cold winters and hotsummers, and the temperature varies between 2.0 °C and 31.6 °C. Inthe period 1968–1998, the average annual precipitation was 816 mmand the average annual temperature was 14.2 °C. In recent years, theannual precipitation in the area varied from aminimum of 18.5 mm inAugust to a maximum of 110.5 mm in December (SNIRH, 2011).

The dominant soil unit of the area is the Leptosol type, whichconsists of soils whose principal characteristic is the presence ofbedrock at 20 cm below the surface (Agroconsultores and COBA, 1991).These soils are divided into a distric (acid) sub-unit associated with themetasedimentary rocks and an umbric (acid and organic-rich) sub-unitassociated with granitic rocks.

Soils in the study area are uncultivated and are occupied bylocal spontaneous vegetation, mainly herbs and shrubs. The mostrepresentative species are Lavandula stoechas, Thymus mastichina,Cistus ladanifer, Pterospartum tridentatum, Cistus salvifolius, Rosacanina, Rosa micrantha, Cytisus sp., Genista sp., Arbutus unedo, Ericaarborea, Erica umbellata, Erica australis and Halimium allyssoides

(Agroconsultores and COBA, 1991; Dinis and Ribeiro, 1988).

3. Material and methods

3.1. Field sampling and sample preparation

Samples of mine tailings and/or soils were collected from four linetransects in the surrounding area of the Ervedosa mine (Fig. 1b and c).Line transect 1 (LT1), along which 14 samples were collected, islocated in an area outside the influence of mining although itintercepts mineralised veins. Line transect 2 (LT2), along which 15

sampleswere collected, includesmine tailings and soils. Line transects3 and 4 (LT3, LT4), along which 12 and 10 samples were collected,respectively, are located downhill and affected by runoff from themining area. Each soil or tailings sample weighs about 5 kg and is acomposite of 4–5 partial samples collected from 0 cm to 20 cm depth.Samples of soil and tailings were oven-dried at a constant temper-ature of 40 °C, manually homogenised and quartered. Two equivalentfractions were obtained from each quartered sample. One fractionwas used for the determination of physico-chemical properties, andthe other fraction was used for chemical analysis. The samples forchemical analysis were sieved first using a 2 mm mesh sieve, toremove plant matter, and subsequently screened to pass 250 μm(Brooks, 1983).

3.2. Analysis of physico-chemical properties

The main physico-chemical properties of the samples (b2 mmfraction) were characterised at the UTAD Soil Analysis Laboratory(Portugal) using the following methods: pH was determined in waterextracts (1:2.5 v/v); organic carbonwas determinedwith the elementalanalyser (Primacs SCN Analyser, Skalar); a conversion factor of 1.724was used to convert organic carbon to organic matter based on theassumption that organic matter contains 58% organic C (Nelson andSommers, 1996); exchangeable acidity (H++Al3+) was extractedwith1 M KCl (Barnhisel and Bertsch, 1982); and exchangeable bases wereextracted with 1 M NH4OAc at a pH of 7.0 (Rhoades, 1982). The cationswere measured using atomic absorption spectrophotometry (SoilSurvey Laboratory, 1992). Particle size analysis was determined usingthe pipette method (Soil Survey Laboratory, 1992). Available P and Kcontents were determined using the Egner–Riechm method (Egneret al., 1960).

3.3. Analysis of total element contents

The determination of total element contents was performed usingtri-acid digestion (HF-HNO3-HClO4 concentrations) (Dold and Fontboté,2001; Lucas and Sequeira, 1971;Walsh et al., 1997) followed by ICP-MS(inductively coupled plasma-mass spectrometry) analysis using an Elan6000 Perkin-Elmer spectrometer (Interdepartmental Research Service,SIDI, ofUniversidadAutónomadeMadrid, Spain). The analyticalmethodfor total metal concentrations was assessed using the 2711 SRMreference material (Montana Soil, from LGC Promochem, Barcelona,Spain), which was included in the triplicate analyses. The agreementsbetween the certified reference values and those determined by theanalytical method were in the range 82.7% to 110.5%.

3.4. Sequential extraction procedure

Samples for sequential chemical extraction analysis were selectedsuch that they reasonably represent the various materials and linetransects sampled (Fig. 1c). Two samples were selected from LT1:sample 7 was collected near a mineralised vein and reflects a situationin which the soils are naturally contaminated; sample 14 wascollected away from the mineralised vein and is representative ofnon-contaminated soil. Samples 5, 7 and 9 selected from LT2represent tailings. Samples 4 and 8 selected from LT3 represent soilsdownhill from the mining area that are possibly contaminated by acidmine drainage.

The selective chemical extraction sequence followed in this studywas adopted from Dold and Fontboté (2001). This seven-step methodwas initially developed for Cu mine tailings in order to evaluate theretention behaviour of trace elements by specific secondary mineralsor minerals groups. This scheme has been applied to the speciationstudy of metal cations and metalloids like arsenic that prevail inanionic forms in soils and mine tailings (Dold and Fontboté, 2001;Ramos and Siebe, 2007). Besides the typical fractions, this method

161P.J.C. Favas et al. / Journal of Geochemical Exploration 111 (2011) 160–171

allows the extraction of primary sulphides. This is important for thiswork because of the existence of various sulphides (arsenopyrite,pyrite, sphalerite, pyrrhotite, chalcopyrite and stannite) in miner-alised veins at the mining area (Favas, 2008; Gomes and Favas, 2006;Gomes and Neiva, 2001).

The procedure involved the addition of 1 g of dried soil or tailingssample to 50 ml Teflon centrifuge tubes, followed by the reactionsequence summarised in Table 1. Fraction 1 (FI) consisted of water-

soluble metals. Fraction 2 (FII) consisted of exchangeable metalsand/or those soluble in slightly acidic conditions. For the purpose ofthe current work, the “mobilisable and bioavailable fraction” is definedas that portion of the total solid-phase metal concentration that isextracted bywater plus the exchangeable fractions recovered in thefirsttwo steps of the sequential extraction scheme (i.e., FI and FII). Fraction 3(FIII) (easily reducible fraction) represents metals bound to short-range-order Fe, Al and Mn (oxy)hydroxides and poorly-crystallised

Fig. 1. The Ervedosa mine area: (a) location in Portugal; (b) simplified geological map; and (c) simplified topographical mapwith soil and tailings sampling points. 1—Silurian peliticmetasedimentary rocks; 2—Silurian quartzites; 3—medium to coarse-grained porphyritic biotite-muscovite granitoids; 4—medium-grained slightly porphyritic muscovite–biotitegranite; 5—fine to medium-grained muscovite granite; 6—alluvium; 7—quartz veins; 8—mining limit; 9—drainage lines; 10—access routes; 11—topographic elevation contours;12—mine gallery; 13—sample numbers.

162 P.J.C. Favas et al. / Journal of Geochemical Exploration 111 (2011) 160–171

ferric hydroxysulfates. Fraction 4 (FIV) (moderately reducible fraction)represents metals bound to long-range-order Fe, Al and Mn (oxy)hydroxides and well-crystallised ferric hydroxysulfates. FIII and FIVrepresent the fractions of metals that can be released if environmentalconditions change from an oxic to anoxic state. Fraction 5 (FV)represents metals associated with organic matter and secondarysulphides. Fraction 6 (FVI) consists of metals bound to primarysulphides. Metals liberated from fractions V and VI may be releasedunder oxidising conditions. Fraction 7 (FVII) represents metals stronglyassociated with crystalline structures of minerals and remainingresistant fractions that are unlikely to be released under the normallyencountered conditions.

The concentrations of elements in all the extracts from thesequential extraction were also determined by ICP-MS. Blanks of thedifferent extractants were analysed in triplicate. Calibration solutionswere made with the appropriate extraction solutions. The accuracy ofthe sequential chemical extraction was determined by comparing thesum of the concentrations obtained at different stages of extractionwith the contents obtained by total decomposition (Cuong andObbard, 2006). The accuracy values ranged between 70% and 110%,which are of the same order as those obtained by other researchers(e.g., Cuong and Obbard, 2006; Fonseca and Martin, 1986; Li andThornton, 2001; Umoren et al., 2007).

3.5. Statistical testing

Descriptive statistics of the data were obtained using SPSS (v. 16.0)software (SPSS Inc., Chicago, USA). The distribution of the data wastested for normality using the Kolmogorov–Smirnov (K–S) test. Weapplied principal components analysis (PCA) to interpret the data. Theaim of PCA is to reduce the data dimensionality while preserving thevariance–covariance structure of the data. The analysis starts with prandom variables X1, X2, …, Xp where no assumption of multivariatenormality is required. If the principal components are derived frommultivariate normal random variables, they have a noteworthygeometric property. The axes of the constant density ellipsoidscorrespond to the principal components (Pereira et al., 2003). In thepresent study, PCA was performed using AnDad (v. 7.10) software (C.V.R.M., 2002). The data matrix used in the analysis consisted of 51samples and 18 variables (pH, Al, Fe, Mn, Cu, Zn, Pb, Cr, Co, Ni, Mo, Cd,Bi, Sn, W, Ag, As and U).

4. Results and discussion

4.1. Physico-chemical properties of soil and tailings

Soils and tailings in the Ervedosa mine area are acidic (Table 2).Soils and tailings along LT1, LT2 and LT3 have loamy sand or sandyloam texture. Soils along LT4 are silty loam. The particle sizedistribution shows that the soils have very low clay contents. Thisimplies that the topography and scarce vegetation in the area haveexposed the very fine particles in the soils to hydrolytic erosion andremoval by runoff water. Exchangeable Ca concentrations were below

the critical value of 1.5 cmol+/kg (Buol et al., 1975). ExchangeableMgconcentrations were less than 0.16 cmol+/kg. According to Coppinand Bradshaw (1982), there is a severe deficiency of Mg below0.16 cmol+/kg. The low cation exchange capacity of the soils (rangingfrom 1.91 cmol+/kg to 5.80 cmol+/kg) can be explained by the lowpercentage of organic matter and low negative charge due to theacidity as well as the low clay contents of the samples (Table 2).

4.2. Distributions of total element concentration data

Some of the studied elements such as Ag, Cd and, to a lesser degreeMo, Co and Bi are present at lower concentrations compared withmost of the other elements. The concentrations of these mentionedelements in the soils have narrower variances compared to those ofthe other metals, suggesting that their concentrations are controlledprimarily by factors other than contamination induced bymineralisedveins and mining. The concentrations of the other elements arecharacterised by large variances and show the presence of “outliers.”The distributions of concentrations of individual elements are notsymmetric about the mean values, and most of the data showed longtails to the high concentration side. Statistical tests indicate that thedata generally fit well a lognormal distribution.

4.3. Element associations

Thefirstfive principal components explainmore than 80%of the totalvariance in thedata (Fig. 2). Thefirst principal component (axis 1),whichexplains 39.2% of the total data variance, defines a Cr-Ni-Fe-Co-Mnassociation with positive loadings and a Sn-U-W-Bi-Cu-Pb associationhighnegative loadings. The secondcomponent (axis 2), explaining 16.6%of the total data variance, reveals a Ag-As association with positiveloadings. TheZn ismainly explainedby axis 3. TheCd ismainly explainedby axis 4, as opposed to Pb. Mo is best explained by axis 5. The Al is onlyexplainedwell by axis 7. However, this axis has an eigenvalue less than 1and, thus, are not discussed here.

Thus, the data of total element concentrations mainly show twoelement associations. The Cr-Ni-Fe-Co-Mn association exists becauseof the similar geochemical behaviours and interdependence of theseelements (i.e., in geochemical cycles, the behaviours of Co, Cr and Niresemble those of Fe and/or Mn), which keep them closely correlatedwith the soil conditions as fundamentally controlled by pH (Adriano,2001; Bartlett and James, 1979; Smith and Paterson, 1995; Yaronet al., 1996). These elements show great mobility within the range ofpH values recorded in the soil samples (Table 3) such that they formextensive secondary dispersion haloes (Adriano, 2001; Bloomfieldand Pruden, 1980; Kabata-Pendias and Pendias, 2001; McBride, 1994;McGrath, 1995). In contrast, the Sn-U-W-Bi-Cu-Pb association, whichis inversely correlated with pH, reflects the presence of mineralisedveins in the area.

The PCA also highlight sample “populations,” which are more-or-less distinct from one another (Fig. 3). “Populations” A and B, whichreflect geochemical anomalies representing the mineralised veins,consist of some samples from LT1 and LT3 andmany samples from LT2(including all tailings samples). “Population” A is primarily linked to aSn-U-W-Bi-Cu-Pb association, with affinities to other elements suchas As and Ag. “Population” B is primarily associated with a Cr-Ni-Fe-Co-Mn association but also with As, Ag and Cd. “Population” C consistsof samples that can be considered to have geochemical backgroundvalues. “Population” D, consisting of the remaining samples, seems toestablish the transition between the anomalous and backgroundpopulations.

4.4. Geochemical background

Total concentrations of heavy metals in soils and tailings havepresumably low biological significance because such concentrations

Table 1

Sequential extraction technique applied in this study.

Fraction Experimental conditions

(I) Deionised water, 25 °C, shake for 1 hour(II) 1 M NH4 acetate pH 4.5, 25 °C, shake for 2 hours(III) 0.2 M NH4 oxalate pH 3.0 (in dark), shake for 1 hour(IV) 0.2 M NH4 oxalate pH 3.0 (in light), heath in water bath for 2 hours(V) 35% H2O2, heat in water bath for 1 hour. 1 MNH4 acetate pH 4.5 shake for

30 min.(VI) Combination of KClO3 and 12 M HCl (25 °C, 30 min.). 4 M HNO3 (90 °C,

20 min.)(VII) HF+HNO3+HClO4 digestion in open Teflon vessels


provide very limited information on themobility and bioavailability ofthe elements. However, assessment of the hazards associated withheavymetal levels occurring in polluted sites may be accomplished bycomparing the reported concentrations to a set of toxicity threshold

values or background data. Currently, there are no regional guidelinevalues established for heavy metals in the region where the Ervedosamine is located. However, based on the distinction of samples derivedfromresults of thePCA, the followingempirical (local) background levels

Table 2

Physico-chemical characteristics of the selected soil and tailings samples from each line transect (LT).

LT1 LT2 LT3 LT4

Sample 7(soil)

Sample 14(soil)

Sample 5(tailings)

Sample 7(tailings)

Sample 9(tailings)

Sample 4(soil)

Sample 8(soil)

Sample 1(soil)

Sample 7(soil)

Sieve analysis (%)Coarse sand 43.7 32.1 49.5 51.1 61.4 47.1 36.4 21.6 22.4Fine sand 30.2 49.4 26.2 27.8 29.1 26.2 35.3 35.3 26.2Silt 20.5 18.1 22.0 20.1 10.4 22.9 25.6 39.9 47.5Clay 5.5 0.4 2.3 1.0 0.1 3.8 2.7 3.2 3.9Texture Sandy loam Loamy sand Loamy sand Loamy sand Sand Sandy loam Sandy loam Silty loam Silty loamExchangeable complexExchangeable bases (cmol+/kg)Ca2+ 0.24 0.38 0.14 0.21 0.86 0.34 1.25 0.30 1.20Mg2+ 0.11 0.24 0.11 0.32 0.24 0.19 1.36 0.16 1.32K+ 0.09 0.21 0.07 0.08 0.08 0.08 0.19 0.06 0.16Na+ 0.08 0.08 0.08 0.04 0.08 0.10 0.11 0.08 0.10Exchangeable bases sum 0.52 0.91 0.41 0.65 1.27 0.70 2.91 0.60 2.78Exchangeable acidity (cmol+/kg)H+ 0.06 0.22 0.05 0.09 0.10 0.06 0.05 0.05 0.05Al3+ 1.36 1.74 0.70 0.90 0.57 1.43 0.79 1.43 2.97Cation exchange capacity (cmol+/kg) 1.95 2.87 1.16 1.63 1.94 2.19 3.75 2.08 5.80Base saturation (%) 26.7 31.8 35.1 39.6 65.4 32.0 77.6 28.8 47.9Organic matter (%) 1.00 5.48 2.21 0.02 0.74 2.43 3.57 4.46 4.48pH 4.4 4.4 4.8 5.0 4.7 4.6 5.1 4.6 4.7Available P, K (mg/kg)P2O5 7 26 138 40 240 180 202 179 198K2O 44 76 48 36 40 52 76 50 74

Fig. 2. Projection of the variables in the first four factorial plans of the PCA.


in the studied area could be defined per element: Al=5.77%, Fe=2.36%,Mn=394mg/kg, Cu=139 mg/kg, Zn=216 mg/kg, Pb=53.4 mg/kg,Cr=33.8 mg/kg, Co=7.9 mg/kg, Ni=21.5 mg/kg, Mo=2.67 mg/kg,Cd=1.22 mg/kg, Bi=4.79 mg/kg, Sn=15 mg/kg, W=10.7 mg/kg,Ag=1.37 mg/kg, As=218 mg/kg, U=13.9 mg/kg. Each of these valuescorresponds to the arithmetical mean of concentrations of each elementin “Population” C samples distinguished in the results of the PCA.According to the statistical summaries of total concentrations perelement, most of the soil and tailings samples have concentrations of As,Sn, U, W, Bi and Cu (Table 3) exceeding the background levels for sandysoils (Kabata-Pendias and Pendias, 2001). The Cu background definedabove exceeds the accepted toxicity threshold value for Cu (100 mg/kg)(Kabata-Pendias and Pendias, 2001). The As background defined aboveexceeds the accepted toxicity threshold value for As (40 mg/kg)(Sheppard, 1992).

4.5. Fractions of element concentrations in soils and tailings

The analytical results obtained in various steps of the fractionationtechnique used to determine the metal-bearing phases of Al, Fe, Mn,Cu, Zn, Pb, Cr, Co, Ni, Mo, Cd, Bi, Sn,W, Ag, As and U in soils and tailingsare shown in the graphs of Figs. 4, 5 and 6.

Iron is shared by all the mineralogical phases, but is prevalent inmoderately reducible fractions (30.2–49.7%), residual fractions (21.6–52.5%), primary sulphides (6.4–26.9%) and easily reducible fractions(3.5–17.1%). A significant fraction of Fe is linked to more resistantmineralogical phases, such as crystalline Fe oxides and residualsilicate phases, to which the percentages associated with primarysulphides (arsenopyrite, pyrite, chalcopyrite, pyrrhotite, sphaleriteand stannite) and Fe and Mn oxy-hydroxides should be added.However, not all the Fe in fraction VI is necessarily due to thedissolution of primary sulphides. Chao and Sanzolone (1977) reportedthat the reagents used in this step (ClO3K+HCl+HNO3) can alsoattack silicates and release some Fe. On the other hand, Mikutta et al.(2005) evaluated methods used to remove organic matter andconcluded that H2O2 allows only partial dissolution of the organicmatter. Therefore, some residual organic matter may be extractedwith the subsequent phase.

The main source of Al in the soil and tailings samples is theweathering of aluminosilicates. The majority of Al (77.4–92.6%) existsin the residual fraction of all the samples (Figs. 4–6). Thus, Al ispresent in the samples mainly in the form of primary and secondarysilicate minerals. The second most abundant fraction of Al is bound toprimary sulphides (FVI) (2.4–9.5%). Like Fe, the Al extracted in thisstep could have been overestimated, however, in view of the accuracyof analyses. Aluminium bound to reducible phases was mainlyassociated with the crystalline ferric oxide fraction (FIV) (2.7–8.1%),possibly due to co-precipitation or substitution with the secondaryferric phases and to amorphous Fe and Mn oxy-hydroxides fraction(FIII) (0.8–4.1%), possibly due to hydrolysis of gibbsite. Only a smallpercentage of Al was extracted in the more exchangeable fraction(1.1–3.1%) and the organic fraction (0.03–0.6%).

The geochemical behaviour of Mn shows some similarities withthat of Fe. There are significant concentrations of Mn in theexchangeable fraction (12.9–24.0%) of most samples (Figs. 4–6).Thus, Mn shows higher availability than Fe in most samples, but itsconcentrations in the bioavailable fraction are significantly lowerbecause the total concentrations are also low.

Copper is distributed by various reagents in the sequence, but lessin water and hydrogen peroxide. It appears to be preferentiallyassociated with the residual fraction (8.0–51.9%), exchangeablefraction (1.6–26.9%) and reducible fractions (4.6–22.3% in fraction IIIand 14.8–48.2% in fraction IV) (Figs. 4–6), reflecting its affinity to beadsorbed and co-precipitated with Fe oxy-hydroxides (Adriano, 2001;James and Barrow, 1981). These fractions are more noticeable in thesamples of tailings (LT2) and contaminated soils (LT3). There are alsoT

able

3

Statisticals

ummariesof

pHva

lues

andtotalc

oncentration

sof

stud

iedelem

ents

insoils

andtailing

ssamples

perlin

etran

sect

(LT).E

lemen

tco

ncen

trations

inmg/kg

,exc

eptthoseforAla

ndFe

arein

%.S

D=

stan

dard

deviation;

ND=

not

detected

. LT1(n

=14

)LT

2(n

=15

)LT

3(n

=12

)LT

4(n

=10

)

Mea

nMed

Min

Max

SDMea

nMed

Min

Max

SDMea

nMed

Min

Max

SDMea

nMed

Min

Max

SD

pH4.5

4.4

4.4

4.8

0.13

4.7

4.7

4.5

5.0

0.19

4.8

4.7

4.5

5.1

0.23

4.6

4.6

4.5

4.7

0.06

Al

9.21

9.44

5.83

11.6

1.94

8.03

7.59

5.82

13.0

2.17

7.35

7.37

5.10

10.2

1.72

4.77

4.89

3.46

6.08

0.88

Fe2.26

2.12

1.43

3.83

0.79

3.12

2.91

1.11

5.85

1.45

2.90

3.05

1.65

3.69

0.63

4.19

4.03

3.10

5.66

0.97

Mn

306

245

184

706

165

686

522

390

1495

333

846

748

384

1475

388

783

831

531

1053

196

Cu26

129

933

.653

415

414

717

675

.922

052

211

223

88.1

309

7713

313

629

.820

060

Zn16

714

874

.828

269

378

349

243

576

122

278

261

163

429

9123

024

191

.232

079

Pb10

864

.141

.332

896

.772

.769

.337

.114

930

.179

.271

.244

.712

826

.829

.128

.218

.043

.68.1

Cr36

.232

.29.16

74.7

26.4

61.1

58.2

5.55

126

36.9

86.0

91.5

16.5

140

36.2

171

183

104

237

50Co

7.55

5.48

2.69

23.3

6.49

12.9

8.89

2.94

26.6

8.67

15.2

14.3

3.21

27.4

8.7

22.7

21.0

19.4

28.4

3.3

Ni

20.2

13.4

6.00

64.4

18.8

33.9

34.0

7.83

56.9

14.2

33.9

31.8

17.3

60.5

15.9

85.0

83.0

65.4

109

15.3

Mo

2.12

1.75

1.06

4.89

1.05

5.91

2.95

1.68

24.3

7.29

7.24

6.03

2.63

16.1

4.64

0.21

0.00

ND

0.99

0.39

Cd0.64

0.40

0.03

1.90

0.65

1.84

2.26

0.38

3.28

1.07

3.18

2.04

0.80

7.35

2.37

3.75

4.18

0.25

6.05

1.98

Bi16

.921

.01.00

29.7

12.1

3.55

2.96

0.51

7.81

2.64

5.78

4.63

1.18

12.4

3.31

5.86

1.91

0.32

14.3

6.35

Sn80

.079

.38.91

159

50.3

43.0

35.3

12.5

85.7

27.2

39.3

41.3

2.16

79.5

23.0

9.47

11.6

4.75

13.7

3.7

W53

.438

.212

.111

737

.014

.614

.88.00

18.8

3.5

10.8

9.68

2.32

20.9

5.09

4.73

3.56

1.89

8.51

2.77

Ag

1.35

1.27

0.55

2.54

0.66

1.05

0.98

0.70

1.35

0.21

1.76

1.39

1.08

3.42

0.83

1.08

0.86

0.36

2.01

0.70

As

409

330

56.2

1996

479

313

241

108

679

207

533

427

310

1323

311

507

116

12.9

1282

586

U60

.277

.9ND

105

38.2

42.7

27.5

12.8

100

30.1

42.5

45.0

ND

73.6

21.1

10.4

9.24

4.60

17.1

4.23


significant concentrations of Cu in the fraction of primary sulphides(5.4–30.3%).

The highest concentrations of Zn are associated with the residualfraction (55.1–83.7%) (Figs. 4–6). Zinc is also present in significant

amounts in the primary sulphides fraction (3.7–23.1%) and moderatelyreducible fraction (4.7–26.0%), thus reflecting the dissolution ofsulphides (sphalerite) and adsorption and co-precipitation with Feoxides. The exchangeable fraction also shows significant amounts of Zn

Fig. 3. Projection of the samples in the first factorial plan of the PCA.

Fig. 4. Fractions of element concentrations in selected soil and tailings samples in LT1 (I=water-soluble; II=exchangeable; III=easily reducible; IV=moderately reducible;V=organic matter; VI=primary sulphides; VII=residual).


in the tailings samples (1.2–9.7%). It is known that in anacidmedium,Zntends to be adsorbed by clay minerals and organic matter by cationexchange processes, whereas co-precipitation with Fe and Mn oxy-hydroxides is a minor process (Adriano, 2001; McBride, 1994; Sposito,1989). However, Fonseca et al. (1999) emphasised that ammoniumacetate (NH4OAc) behaves as an extremely aggressive reagent in thepresence of samples containing Pb and Zn minerals, and thus theexchangeable fraction may contain Zn resulting from the partialdissolution of sphalerite.

The Pb appears to be associated with the residual (25.6–70.0%),primary sulphides (18.2–30.5%), moderately reducible (6.1–30.2%),easily reducible (1.8–8.6%) and exchangeable (1.1–7.6%) fractions(Figs. 4–6). The increase of Pb in the reducible fractions shows its

known tendency to be adsorbed (mainly by clay minerals, organicmatter and Fe, Mn, and Al oxides) and co-precipitated with Fe and Mnoxides. The percentage of Pb associated with the exchangeable fractionis higher in sample 14 along LT1, so its potential bioavailability is greaterin that area. Like the assumption for Zn, part of the exchangeablefraction of Pb may be due to the partial extraction of sulphides throughthe action of NH4OAc.

The concentrations of Cd determined in the different stages ofselective extraction show that it appears mainly in the exchangeable(9.1–69.6%), easily reducible (3.1–13.8%) and moderately reducible(13.7–46.0%) fractions (Figs. 4–6). It is also present in the fraction ofprimary sulphides (1.8–40.6%) as a result of the dissolution ofsphalerite and in association with organic matter (2.5–11.3%). The

Fig. 5. Fractions of element concentrations in selected soil and tailings samples in LT2 (I=water-soluble; II=exchangeable; III=easily reducible; IV=moderately reducible;V=organic matter; VI=primary sulphides; VII=residual).


Cd is marked in the samples by a high potential bioavailability,especially in samples with high total concentration (tailings), whereCd is more soluble. According toMcBride (1994), Cd2+ tends to have ahigh mobility in well-drained acid soils because it is weakly adsorbedto the organic matter and to clay and oxide minerals when the pHis below 6. However, part of the Cd of the exchangeable fractionmay result from the partial extraction of sphalerite by the action ofNH4OAc.

The Ni is largely represented in the residual fraction (27.0–70.8%)because it probably exists in the silicates (Figs. 4–6). The importance ofthis fractionmay be due to, according to Sposito (1989), the presence ofNi by isomorphous substitution of Fe and Al in the spinel groupminerals or as inclusions in silicate networks of smectite and illite. Theamounts of Ni in the primary sulphides (3.5–24.2%) may be due to theattack on silicates (as explained for Fe above). The remaining fractions(exchangeable and reducible) are a result of adsorption to claymineralsand Fe and Mn oxy-hydroxides and co-precipitation with thesesecondary phases.

The Co yields significant amounts in the exchangeable (9.2–37.2%),easily reducible (7.9–51.6%) and moderately reducible (14.7–21.4%)fractions (Figs. 4–6), for reasons identical to those discussed for Ni.Cobalt is also important constituents of the primary sulphide andresidual fractions.

Thus, bivalent cations (i.e., Mn, Pb, Cd, Ni, Co) exhibit similarbehaviours in the mine area. The exchangeable fraction, withreducible fractions, reflects the importance of pH on the adsorptionto clay minerals and secondary phases of Fe, Al and Mn, as well as thediffusion in crystalline systems and its co-precipitation with second-ary minerals (Adriano, 2001; Dold and Fontboté, 2001; Holmstrom

and Ohlander, 2001; Moncur et al., 2005; Romero et al., 2007).Consequently, Fe-precipitates and clay minerals are considered as themain solid-phases' that control the mobility of potentially toxicelements in tailings and soils.

Concentrations of Cr are mainly represented in the residualfraction (36.1–90.2%) (Figs. 4–6), for reasons similar to that discussedfor Ni, which results in its low content in the bioavailable fractions.There are also, as a secondary trend, concentrations of Cr in thereducible fractions by associationwith Fe andMn oxy-hydroxides andthe sulphides fraction. The Cr extracted from the exchange fraction insample 7 of LT2 reaches to 23.8% and from the organic matter fractionin sample 7 of LT1 reaches to 29.3%.

In contrast to the bivalent cations (i.e., Mn, Pb, Cd, Ni, Co), whichare mobile under acidic conditions, oxy-anions such as Mo (V, VI) andAs (V) show increasing adsorption with Fe oxy-hydroxides withdecreasing pH (Dzombak and Morel, 1990). This behaviour is clearlyvisible in the samples studied because themost significant incrementsof Mo and As occur in the reducible fractions (Figs. 4–6). The contentsof Mo in the easily reducible fraction represent 5.8–100% of the totalextracted, and the extracted contents in the moderately reduciblefraction represent 0.0–80.1%. Molybdenum also exists in the primarysulphides (0.0–43.76%), organic matter (0.0–7.1%) and residual (0.0–19.9%) fractions. The easily and moderately reducible fractionsrepresent, respectively, 12.1–43.9% and 39.1–62.3% of the total Asextracted. There is also significant As in the fraction of the primarysulphides due to dissolution of arsenopyrite.

Bismuth is associatedmainlywith the residual fraction (33.5–100%),followedby theeasily reducible fraction (0.0–42.9%) and themoderatelyreducible fraction (0.0–22.2%) (Figs. 4–6). These results reflect the

Fig. 6. Fractions of element concentrations in selected soil and tailings samples LT3 (I=water-soluble; II=exchangeable; III=easily reducible; IV=moderately reducible;V=organic matter; VI=primary sulphides; VII=residual).


adsorption of Bi to clayminerals and secondary phases of Fe andMnandthe co-precipitation with these secondary minerals. Bismuth also existsin the fraction of primary sulphides (0.0–16.6%) due to dissolution ofmatildite, bismuthinite and native bismuth (included in arsenopyrite).All the Bi in sample 14 along LT1 was drawn into the exchangeablefraction,with 89.9%, and the organicmatter fraction,with the remaining10.1%. This sample is associated with a low pH, high electricalconductivity and organic matter.

The Sn appears mostly represented in the residual fraction (87.6–99.0%) and, to amuch lesser extent, in the reducible fractions (Figs. 4–6)due to its dominant presence in resistant minerals (cassiterite). Thisdetermines that this element has a low content in more bioavailablefractions.

TheW is divided into various reagents of the sequence. It is presentin important amounts in the residual (13.2–75.3%), moderatelyreducible (11.9–59.7%), organic matter (2.4–45.4%), easily reducible(1.3–16.1%), and primary sulphides (0.8–11.9%) fractions (Figs. 4–6).

Most of the Ag is associated with the residual (25.0–100%) andprimary sulphides (0.0–43.9%) fractions (Figs. 4–6) due to thedissolution of matildite. There are some important Ag contents in theeasily reducible fraction (0.0–19.4%) and moderately reducible fraction(0.0–16.5%) thatmay indicate co-precipitation with Fe oxy-hydroxides.The tendency for complexation by the organicmatter is also reflected inthe contents extracted from fraction V,which can reach15.5% of total Agextracted.

The U is extracted at various stages of selective extraction. HigherU concentrations are found in the residual (4.7–42.9%), exchange(6.0–36.5%), reducible (11.8–26.1% in fraction III and 9.7–36.5% infraction IV) and primary sulphides (5.1–14.7%) fractions (Figs. 4–6).

4.6. Bioavailability of metals

The elements extracted from the so-called exchangeable fractions,which in this study were leached through the use of NH4OAc, are animportant part of the potentially available elements and can beconsidered as an estimate of bioavailability (Adriano, 2001; Ernst,1996; González et al., 2007; Kabata-Pendias, 2004; Kidd et al., 2007;Walter et al., 2006). In a recent critical review work, Hass and Fine(2010) highlight the selectivity problems of various reagents,including ammonium acetate (NH4OAc) used in this work to extractthe exchangeable fraction. Several authors have reported a lack ofselectivity of acetate because of its ability to dissolve carbonates(Tessier et al., 1979), oxyhydroxide coatings (Gibbs, 1973) and a widerange of soil minerals (Berti and Jacobs, 1996; Miller et al., 1986;

Stover et al., 1976). However, because the procedure adopted in thisstudy allows the separation of the water-soluble fraction, theextracted chemical elements must be considered highly bioavailablebecause they are easily mobilised (cf. Meers et al., 2007; Seguin et al.,2004).

The absorption of chemical elements by plants depends on theirbioavailability in the soil (bioavailable fraction) and on theirreplacement by less bioavailable fractions (McGrath et al., 1997).The dynamic equilibrium established between the different fractionsof soil determines the mobility and bioavailability of elements. ThepH, Eh and amount and type of soil colloids (organic matter, clays andoxides) are the most important edaphic factors that controlconcentrations. Additionally, plants can modify the conditions of therhizosphere through processes like the production of root exudates orchanging of the pH (Adriano, 2001; Cattani et al., 2006). Under naturalconditions, the chemical elements associated with resistant soilfractions such as oxy-hydroxides, organic matter and sulphides mayalso be released into solution if environmental conditions are altered(Li and Thornton, 2001; Polkowska-Motrenko et al., 2000; Rauret,1998; Tessier et al., 1979).

4.7. Environmental risk

In order to estimate the environmental risk associated with heavymetal pollution in the study area, the soil and tailings samples wereclassified according to a risk assessment code (RAC) based on thestrength of the bond between metals and the different geochemicalfractions in soils and the ability of the metals to be released and enterinto the food chain (Rodríguez et al., 2009). The RAC, expressed as apercentage, is defined by taking the ratio of the FI+FII fractions(water soluble and exchangeable fractions) to the total concentrationof elements in the soil (Table 4). According to the several studies thatshowed good correlations between FI+FII fractions and the simpleextraction using EDTA/acetic acid (i.e., usual procedure employed tocharacterise the bioavailable fractions of metals) as well as thecontents accumulated in various plant species (e.g., Abollino et al.,2006; Ernst, 1996; Lin et al., 2010; Meers et al., 2007), the FI+FIIfractions can be used as good estimates of bioavailability. According toRodríguez et al. (2009), there is no risk when FI+FII fractionsrepresent lower than 1% of the total concentrations, low risk for 1–10%RAC, medium risk for 11–30% RAC, a high risk for 31–50% RAC, and avery high risk for higher percentages of RAC.

In general, tailings samples showed a higher risk than the soilsamples (Table 4) probably due to the deficient physico-chemical

Table 4

Sums of element concentrations (mg/kg) in the water-soluble and exchangeable fractions and their ratios (expressed as a percentage) to the total element concentration.Abbreviations: LT=line transect; s=sample; ND=not detected.

Water-soluble fraction+Exchangeable fraction (mg/kg)

Samples Al Fe Mn Cu Zn Pb Cr Co Ni Mo Cd Bi Sn W Ag As U

LT1 s7 967 186 51.1 17.6 2.7 9.0 3.9 0.8 0.7 ND 0.18 0.5 0.003 0.261 ND 63.9 30.9LT1 s14 1170 75 23.4 6.9 1.2 5.0 0.3 0.4 0.2 ND 0.01 18.2 0.094 0.157 ND 4.5 16.5LT2 s5 547 325 151 5.1 2.9 1.8 1.7 7.4 1.3 0.042 0.24 0.1 ND 0.004 ND 6.5 7.2LT2 s7 637 207 88.9 18.9 24.1 0.3 17.3 1.5 3.5 ND 1.63 0.1 0.005 0.016 0.07 10.9 5.4LT2 s9 440 384 121 53.2 43.3 4.0 0.3 2.3 5.5 0.004 1.36 1.0 0.036 0.012 0.04 17.4 21.9LT3 s4 770 177 89.8 31.8 3.0 1.0 1.3 2.7 0.7 ND 0.44 0.2 0.007 0.013 ND 15.3 10.8LT3 s8 718 236 111 5.2 4.1 0.8 1.7 5.5 0.9 0.022 0.17 ND 0.006 0.004 0.03 11.5 1.3

(Water-soluble fraction+Exchangeable fraction)/Total concentration (%)

Samples Al Fe Mn Cu Zn Pb Cr Co Ni Mo Cd Bi Sn W Ag As U

LT1 s7 1.4 0.5 24.8 3.3 0.9 4.8 6.4 28.3 4.1 - 9.5 3.0 0.0 0.3 - 3.2 29.4LT1 s14 1.1 0.5 10.9 1.9 1.6 8.0 2.7 9.6 2.5 - 30.2 69.5 0.1 0.2 - 1.5 19.0LT2 s5 0.8 0.6 15.8 2.7 1.1 2.5 1.3 27.6 2.3 0.2 9.1 4.0 - 0.1 - 1.8 12.0LT2 s7 1.0 0.5 19.1 16.3 4.2 0.8 21.3 16.8 10.3 - 74.5 3.6 - 0.1 6.8 4.3 36.8LT2 s9 0.3 3.2 17.7 28.4 8.0 4.1 4.9 35.4 19.7 0.2 51.5 14.2 - 0.1 4.2 7.9 29.7LT3 s4 0.9 0.6 14.5 14.6 1.1 1.4 1.3 23.1 2.7 - 25 5.2 - 0.1 - 3.2 25.1LT3 s8 1.1 0.7 16.0 5.1 2.1 1.2 1.2 27.5 2.5 0.1 21 - 0.1 0.1 2.7 2.9 5.8


properties of tailings (i.e., very low clay and organic matter contents,sandy texture) that influence processes of interaction with heavymetals. The soil and tailings samples collected from the area showedhigh total concentrations of As, Sn, U, W, Bi and Cu. However, the riskassessment based on those elements suggested that potentialdangerous situation in the area can be derived mainly from Upollution because most of the analysed samples suggest medium tohigh risk based on U concentrations. The soil samples suggest low riskfor As, due to a consequence of the strong adsorption of As on thesecondary ferric phases at the acidic pH of the samples.

5. Conclusions

The tailings in the Ervedosa mine area are characterised by lowproductivity in the strict edaphic sense because of their reduced organicmatter content, low cation exchange capacity and sharp acidity valuesassociated with typically sandy textures. The geochemical soil datahighlight some anomalies associated with mineralised veins or relatedto themining influence. Beyond the tailings, the highest concentrationsformost of the elements studies are recorded in the soils collected in thenearby surroundings of mineralised veins or in the soils influenced bythe tailings.

The application of principal components analysis to the data of totalelement concentrationsmainly showed element associations accordingto their geochemical behaviour. The element associations recognisedare consistent with field observations and were used to discriminatesoils of local geochemical background from contaminated soils. Ingeneral, soil samples further away from the tailings have high localgeochemical background concentrations of certain elements such as As,Sn, U, W, Bi and Cu. Moreover, most samples of tailings and soils reflectthe mineralisation geochemical anomalies.

Despite the usual operational and experimental problems ofsequential extractions, the procedure used in this study is consideredsuitable to study the behaviour of metals and the mechanisms ofmetal release under variable environmental conditions. Based on theavailable data, heavy metal speciation showed notable differenceslargely depending on the acidity of soils and tailings and the presenceof Fe oxyhidroxides formed via pyrite oxidation. Oxyanions such asMo and As show lower mobility through adsorption to Fe, whereasmetal cations such as Mn, Cd, Cu, Zn, Co, Cr, Ni and U revealedsignificant enrichments in the water soluble and exchangeablefractions. Tin and Al exist principally in the more residual fractions.The ability of this sequential procedure adopted in this study todistinguish between associations with organic matter, secondarysulphides and primary sulphides is highly desirable from anenvironmental perspective. For the Ervedosa mine area, the lowpool of metals (with the exception of Cr and W) bound to sulphidesoxidised using hydrogen peroxide implies a slower rate of oxidationas these soils and tailings are exposed to open atmospheric conditions.

Data obtained using the sequential extraction procedure describedin this study lend to assessment of risk associatedwith the presence ofheavy metals in soils and tailings. Despite high total concentrations ofAs, Sn, U, W, Bi and Cu, the risk assessment code (ratio of the watersoluble and exchangeable fractions to the total concentration ofelements) only suggests potential dangerous situation in the Ervedosamine area mainly in the form of U pollution.

Acknowledgements

The authors gratefully acknowledge the instrumental support of theGeosciences Centre at Coimbra University and the financial supportfrom FCT (Portuguese Foundation for Science and Technology)presented as a PhD Fellowship to P.J.C. Favas and as a grant (ProjectPTDC/CTE-GEX/66710/2006). Finally, we would like to thank theanonymous reviewers and John Carranza (guest editor of this specialissue) for their constructive comments and helpful suggestions.

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