Seediscussions,stats,andauthorprofilesforthispublicationat:http://www.researchgate.net/publication/257673746

MethodsforExtractingHeavyMetalsinSoilsfromtheSouthwesternAmazon,BrazilARTICLEinWATERAIRANDSOILPOLLUTIONFEBRUARY2013ImpactFactor:1.69DOI:10.1007/s11270-012-1430-z

DOWNLOADS22

VIEWS74

2AUTHORS:

SabrinaNovaesdosSantos-AraujoUniversityofSoPaulo4PUBLICATIONS35CITATIONS

SEEPROFILE

LuisAlleoniUniversityofSoPaulo121PUBLICATIONS575CITATIONS

SEEPROFILE

Availablefrom:SabrinaNovaesdosSantos-AraujoRetrievedon:23June2015

Methods for Extracting Heavy Metals in Soilsfrom the Southwestern Amazon, Brazil

Sabrina Novaes dos Santos &Lus Reynaldo Ferracci Alleoni

Received: 20 August 2012 /Accepted: 18 December 2012 /Published online: 19 January 2013# Springer Science+Business Media Dordrecht 2013

Abstract Heavy metals occur naturally in soil, atconcentrations that depend on the parent material fromwhich the soil was formed, the processes of formation,and the composition and the proportion of the compo-nents of its solid phase. Quantifying these concentra-tions is important for environmental studies of soilcontamination and pollution, and choosing the meth-ods for doing so is a key step in establishing heavymetal contents in soil samples. We evaluated twodigestion methods (aqua regia and EPA 3051, bothmicrowave oven-assisted) for assessing pseudo-totalconcentrations of Cd, Co, Cr, Cu, Ni, Pb and Zn inthe surface layer (020 cm) of soil samples from theBrazilian agricultural frontier in the southwesternAmazon. Nineteen composite samples of the mostrepresentative soil classes for the states of MatoGrosso and Rondnia were collected under nativevegetation undisturbed by human intervention.Canonical discriminant analysis and principal compo-nent analysis were used for multivariate exploration ofthe data. Aqua regia extracted higher amounts of Co,

Ni, Pb, and Zn than EPA 3051, while levels of Cr andCu did not differ between methods. In general, aquaregia recovered more of the metals when compared toreference soil samples.

Keywords Aqua regia . EPA 3051 . Backgroundconcentrations . Soil contamination . Acid extractors

1 Introduction

Heavy metals occur naturally in soils, at concentra-tions that depend on the soil parent material, on theprocesses by which the soil formed, and on the com-position and proportion of the components of its solidphase. Quantifying these concentrations is importantfor studies of environmental pollution, and a key steptowards establishing soil quality reference values.

Environmental agencies require reference indica-tors in order to monitor environmental impacts anddetermine pollution levels, as part of their mandate toenforce environmental legislation. These indicatorsare obtained by comparing concentrations of toxicelements in soils with those observed in natural(nonpolluted) soils, or with reference values.

To date, a number of studies have been carried outto quantify natural concentrations and reference back-ground values of heavy metals in Brazilian soils.However, no studies have described natural concen-trations of heavy metals in the soils of Mato Grossoand Rondnia, Brazilian states in the southwestern

Water Air Soil Pollut (2013) 224:1430DOI 10.1007/s11270-012-1430-z

S. N. dos Santos (*)Graduate Student in Soil Science and Plant Nutrition,University of Sao Paulo (ESALQ/USP),Av. Pdua Dias, 11, C.P. 9,Piracicaba, So Paulo 13418-900, Brazile-mail: sabrinanovaes@usp.br

L. R. F. AlleoniDepartment of Soil Science, ESALQ/USP,Av. Pdua Dias, 11, C.P. 9,Piracicaba, So Paulo 13418-900, Brazil

Amazon, which represent one of the largest agricul-tural frontiers on Earth.

Deciding which method to prepare and extract con-centrations of elements in soil samples is a crucial stepin the process of describing the environmental condi-tions of a given area. There are several different meth-ods of acidic digestion, ranging from aqua regia (AR)(3:1 HCl/HNO3, v/v), with varying quantities of acidsand various digestion times and temperatures, in anopen system, and sometimes even hydrofluoric acid isused in a closed system. This latter digestion is con-sidered total, due to the destruction of the silicatematrices (Chen and Ma 1998; Caires 2009).

A large number of studies (e.g., Akker and Delft1991; Chen and Ma 1998; Tam and Yao 1999; Chenand Ma 2001; Campos et al. 2003; Tighe et al. 2004;Chander et al. 2008; Caires 2009; Nemati et al. 2010)have documented marked differences in the amountsof metals extracted by these different methods. Thismeans that government agencies must establish normsregarding methods to extract naturally occurring con-centrations in soils, in order to permit rigorous com-parisons with pre-established values.

In Brazil, the analytic methods adopted in legislationfor quantifying total concentrations of inorganic substan-ces (apart frommercury) in soil samples are twomethodsof the United States Environmental Protection Agency(USEPA), known as 3050B (HNO3 + H2O2) and 3051(HNO3) (USEPA, 2007a, b, c), which are widely used todigest samples of soils, sediments, and wastes.

In the 3051 method, the oxidation of organic matteris performed by nitric acid without the solubilizationof the silicate fraction (pseudo-total). Conversely, inthe 3052 method the use of nitric and hydrofluoricacids promotes a full dissolution of the sample.However, hydrofluoric acid requires very careful han-dling, because it can cause severe burns in contactwith skin (Costa et al. 2008). It can also damageanalytical instruments (e.g., it attacks silicate materi-als, especially glass) and promote undesirable forma-tion of insoluble fluoride precipitation with Al, Ca, Fe,and Mg, and coprecipitation with Rb, Sr, Y, Cs, Ba,Pb, Th, and U (Yokoyama et al. 1999; Vieira et al.2005). The use of the 3052 method is hardly justifiedin highly weathered tropical soils because mineralreserves are not impressive and their silicate fractioncontains low amounts of heavy metals.

Microwave ovens have been used in soil chemistrylaboratories since the 1980s (Jassie and Kingston

1988) and provide fast, secure, and efficient digestion(Chen and Ma 2001).

Microwave heating is employed in the 3050B,3051, and 3052 methods. Its advantages include ashorter sample digestion, a more complete dissolutionof samples, and a smaller loss of volatile elements, inaddition to a lower risk of contamination than othermethods (Abreu et al. 2006).

AR is also very efficient at extracting pseudo-totalcontents of heavy metals in soils. It is the standardmethod for certifying soil samples in Britain andFrance (Prez et al. 1997). Nitric acid oxidizes hydro-chloric acid, giving rise to various oxidation productssuch as molecular chlorine and nitrosyl chloride (3HCl +HNO3 = 2H2O + Cl2 + NOCl) (Chen and Ma 2001).This property, along with the presence of chloride(complexing), makes AR a highly efficient extractor fordissolving heavy metals (Costa et al. 2008).

In this study we assessed the AR and EPA 3051methods of pseudo-total digestion for extracting Cd,Co, Cr, Cu, Ni, Pb, and Zn. Concentrations weresubsequently correlated with physical and chemicalproperties of soils from the states of Mato Grossoand Rondnia, in Brazils southwestern Amazonregion.

2 Materials and Methods

The territories of Mato Grosso and Rondnia stateswere first divided into 11 ecoregions or biogeoclimaticmacrozones intended to reflect large-scale similaritiesand differences in soil, climatic, and managementconditions. This classification was performed with anArcView 9.0 Geographical Information System bysuperimposing maps of soil conditions (scale of 1:5million), native vegetation, geology, climate, and to-pography, with the goal of identifying homogeneousareas that would allow our measurements of soil attrib-utes at the study sites to be extrapolated across theentire region (Maia et al. 2009). These homogeneouszones illustrate biogeoclimatic conditions free of an-thropogenic disturbances such as deforestation, agri-culture, or ranching (Table 1).

Soils were sampled in June and July 2007. Twotownships in each of the regions were selected atrandom, for a total of 19 townships. These yielded19 soil samples, with three replicates each, collect-ed under native vegetation free of anthropogenic

1430, Page 2 of 16 Water Air Soil Pollut (2013) 224:1430

disturbance and considered to be representative ofsoils in Mato Grosso and Rondnia. Within eachtownship ranches with areas of native vegetationin which to collect soils were selected (Fig. 1).

Compound samples were formed from samplestaken at five collection sites within a 100100 mplot at each ranch: one site at the center of theplot and the other four on the square corners.Samples were collected at a depth of 020 cm.After being collected, samples were air-dried, ho-mogenized, and sieved through 2-mm mesh. Mostof the soils collected belonged to the followingorders: Oxisols (74 %), Inceptsols (16 %), andEntisols (10 %). More details regarding the studyare found in the work of Santos and Alleoni(2012).

The contents of available phosphorus and potassi-um were extracted with Mehlich-I (Mehlich 1953),and calcium and magnesium were extracted with1 M KCl (Anderson and Ingram 1992). Phosphoruscontent was determined by colorimetry, Ca and Mgwere quantified in an atomic absorption spectropho-tometer (AAS), and K in a flame photometer.Exchangeable aluminum was removed with 1 moll1

KCl (Anderson and Ingram 1992), and determined bytitration with 0.025 moll1 NaOH. Total acidity (H +Al) was extracted with a 1 M calcium acetate (pH7buffered) solution and determined by titration with0.025 M ammonium hydroxide.

pH was determined potentiometrically for suspen-sions of air-dried fine earth in 1 M KCl, H2O, and0.01 M CaCl2 1:2.5 (Anderson and Ingram 1992). The

Table 1 Characteristics of macroregions in the states of Mato Grosso and Rondnia, southwestern Amazon region, Brazil(Mello, 2007)

Region Topography Soil Climate and averageannual rainfall (mm)

Vegetation

Alto Xingu Flat with large plateaus Oxisols Amia (1,7502,250) Seasonal semi-deciduousforest to open Amazonforest

Paran Basin Flat with large plateaus Oxisols Quartzipsamments Am,b Cwac (1,2501,750) Cerrado sensu stricto

Parecis Plateau Flat with large plateaus Quartzipsamments Oxisols Ami (1,5002,250) Cerrado sensu stricto andseasonal semi-deciduousforest

Araguaia Depression Flat areas and rollinghills; frequentlywaterlogged

Entisols AquentEntisols

Ami (1,2502,000) Open cerrado (dominatedby grasses) and cerradosensu stricto

Cuiab Depression Flat areas and rolling hills Inceptisols Entisols Am (1,5001,750) Cerrado sensu stricto

Guapor Depression Mostly flat Oxisols, UltisolsEntisols

Ami (1,7502,250), Ami,Am (1,5001,750)

Open Amazon forest(north) and seasonalsemi-deciduous forestto Cerrado (south)

NortheasternMato Grosso

Irregular with rolling hills Ultisols Amid (2,0002,500) Cerrado to seasonalsemi-deciduous forest

NorthernMato Grosso

Irregular with rolling hills Ultisols, OxisolsInceptisols

Awi, Ami (2,0002,750) Open Amazon forest toseasonal semi-deciduousforest

Northern Rondnia Predominately flat Oxisols Awi (2,0002,500) Open Amazon forest

Central Rondnia Varies between flatareas and rolling hills

Ultisols, Oxisols Awi, Ami (1,7502,250) Open Amazon forest

Pantanal Mostly flat; frequentlywaterlogged

Entisols, Alfisols Am (1,5001,750) Open Cerrado and seasonalsemi-deciduous forest

a Ami = very hot tropical monsoon climateb Am = tropical monsoon climatec Cwa = wet subtropical climated Awi = tropical savanna climate

Water Air Soil Pollut (2013) 224:1430 Page 3 of 16, 1430

difference between pH1 M KCl and H2O was used toverify the sign of the net charge (Mekaru and Uehara1972). Based on the contents of exchangeable cations,the sum of exchangeable bases, the cation exchangecapacity (CEC) at pH7.0, and base and Al saturationswere then calculated. Granulometric analysis was per-formed by the densimeter method (Gee and Or 2002)and organic carbon was determined with a LECO CN-2000 dry combustion elemental analyzer.

The oxides (expressed as SiO2, Al2O3, Fe2O3,TiO2, and MnO) were extracted using 9 M H2SO4.Contents of Fe, Mn and Al were determined usingatomic absorption spectrophotometry (AAS), Ti bycolorimetry (Vettori 1969), and Si by gravimetry.The Ki weathering index was calculated by the molarrelation method where Ki = (%SiO2/60)/(%Al2O3/102). Sodium citratebicarbonatedithionite (Na-CBD) solution was used to extract the free iron oxides(Mehra and Jackson 1960) and the concentration ofthe poorly crystalline oxides of Fe, Al, and Mn were

determined by the method described by Loeppert andInskeep (1996).

Pseudo-total concentrations of metals wereobtained via digestion by (1) the AR method(Mcgrath and Cunliffe 1985) and (2) with concentrat-ed acid in a microwave oven, under controlled tem-perature and pressure, following the EPA 3051 method(USEPA, 1996).

AR: 0.5 g of samples sieved through 100 mesh wastransferred to Teflon tubes. Each tube received 9 ml ofconcentrated HCl (32 %) and 3 ml of concentratedHNO3 (65 %) (3:1) of analytical-level purity, and themixture was left undisturbed for 12 h of pre-digestion.The tubes were subsequently placed in a closed systemin a microwave oven (Mars Xpress, CEM Corporation)for 20 min at 180 C subsequently passing the temper-ature ramp. After cooling, samples were transferred tocertified 25-ml flasks (NBR ISO/IEC), the flask volumewas completed with ultrapure water, and the extractswere filtered. All analyses were carried out with three

Fig. 1 Map of southwestern Amazonian Brazil, showing townships selected for soil sampling (RO Rondnia, MT Mato Grosso)

1430, Page 4 of 16 Water Air Soil Pollut (2013) 224:1430

replicates. Analysis quality control was performed withcertified soil samples (NIST SRM 2709 San Joaquinsoil and DO65-540 Metals in Soil EnvironmentalResource Associates).

Calibration curves to determine metal concen-trations were prepared based on 1,000 mg l1

standards (TITRISOL, Merck), using ultrapurewater for dilution, cleaning, and decontaminationof the glassware, which was kept in 10 % nitricacid solution for 24 h and rinsed with distilledwater and ultrapure water. Concentrations of Co,Cr, Cu, Ni, Pb, and Zn were determined via atom-ic absorption spectrophotometry (FAAS) and Cdconcentrations in a graphite oven.

The AR method is normally carried out with diges-tion in an open system. However, methods in which aclosed system is heated with a microwave oven arewell established and widely employed (Nieuwenhuizeet al. 1991; Chen and Ma 1998, 2001; Nemati et al.2010; Sakan et al. 2011). The advantages of the closedsystem compared to other methods are: (1) ashorter digestion time for samples, (2) a lower riskof pollution, (3) a more complete dissolution ofsamples, and (4) lower losses of volatile elements(Sakan et al. 2011).

EPA 3051: 0.5 g of samples sieved through 100mesh was transferred to Teflon tubes, to which 10 mlof concentrated HNO3 (65 %) of analytical purity wereadded. Samples were placed in a closed system micro-wave oven (Mars Xpress, CEM Corporation) for4 min and 30 s at 175 C, subsequently passingthe temperature ramp. After cooling, samples weretransferred to certified 25-ml flasks (NBR ISO/IEC), with flask volume completed with ultrapurewater, and the extracts were filtered with slowfilter paper. All analyses were carried out in threereplicates, and sample blanks were performed si-multaneously. Analysis quality control was per-formed with certified soils (NIST SRM 2709 SanJoaquin soil and DO65-540 Metals in Soil Environmental Resource Associates). The NISTrecommends comparing methods that do not usehydrofluoric acid (3050, 3051, and their updatedversions) with recovery based on leachable con-centrations (NIST, 2002), since certified concentrationsare determined based on methods to determine totalconcentrations. Calibration curves and the determi-nation of metal concentrations were carried out asdescribed in the previous paragraph.

Results were examined via analysis of variance(ANOVA) (F Cu. The rangesof recovery were within those recommended for theelements under study (USEPA, 1996).

Water Air Soil Pollut (2013) 224:1430 Page 5 of 16, 1430

3.2 Digestion Methods

The two methods of pseudo-total digestion yieldeddifferent levels of naturally occurring heavy metalsin soils of Mato Grosso and Rondnia (Table 4). Ingeneral, pseudo-total concentrations of metalsobtained via digestion by both methods were wellbelow the maximum levels considered acceptable forsoils worldwide (Alloway 1990; Reimann et al. 2000).Mean concentrations observed in soils of Rondnia

and Mato Grosso were also generally lower than thosereported in the literature for other Brazilian states andfor other countries (MINEROPAR 2005; Salonen andKorkka-Niemi 2007; Paye et al. 2010; Caires 2009;Bini et al. 2011; Shah et al. 2012).

The low natural levels obtained by the two methodsmay be related to the physical and chemical soil attrib-utes and to the parent material of soils in the region.Oxisols and Ultisols are highly weathered soils, andtheir clay fraction is dominated by kaolinite, gibbsite,

Table 3 Average contents ofheavy metals recovered for cer-tified reference materials (Biondi2010)

aValue of metal content for bothcertified soilsbPercentage of metals recoveredfor DO65 and percentage of met-als recovered in relation to theleachate 2709acUsed to extract metals with ex-tractor EPA 3051dUsed to extract metals with theaqua regia extractor

Element Certified soil Recovery level(mg kg1)

Certified valuea

(mg kg1)Recovery(determined)b (%)

Leachrecovery (%)

Cd 2709ac 0.3 0.370.002 104 110

DO65d 84.7 91.0 93

Co 2709a 9.3 12.800.2 73 81

DO65 174.4 190.0 91.8

Cr 2709a 52.0 130.09.0 40 41

DO65 140.4 144.0 97

Cu 2709a 24.4 33.90.5 72 81

DO65 251.9 237.0 106

Ni 2709a 59.5 852 70 77

DO65 214.0 200.0 107

Pb 2709a 8.1 17.30.1 47 53

DO65 111.2 104.0 107

Zn 2709a 71.0 1034 69 77

DO65 314.4 341.0 107

Table 2 Selected physical andchemical attributes of soil sam-ples from the states of Rondoniaand Mato Grosso, Brazil (n=19)

CECe effective cation exchangecapacity, CECt totalcation ex-change capacity, V base satura-tion, m saturation for aluminum

Variable Mean Minimum Maximum Standard Deviation

pH (H2O) 4.6 3.5 7.4 0.9

pH (0.01 M CaCl2) 4.3 3.2 7.2 0.9

pH (1 M KCl) 4.2 3.2 6.9 0.9

mmolc kg1

CECe 19.0 2.3 96.4 17.9

CECt 55.4 17.8 158.0 29.0

%

V 24 0.2 99 26.9

m 46 0.1 98 34.6

g kg1

Org. C 13.3 4.4 35.1 7.1

Sand 654 271 953 189

Silt 38 10 92 21

Clay 307 25 651 174

1430, Page 6 of 16 Water Air Soil Pollut (2013) 224:1430

goethite, and iron and aluminum oxides (Fontes andWeed 1991). They are also typically acidic (pH in H2Ovarying from 4.3 to 6.2) and have very low concen-trations of heavy metals. Parent material is one of theprincipal determinants in the distribution of heavymetals in soils. Even under severe weathering condi-tions (pedogenesis) such as those present in the wettropics, parent material may play an important role indetermining a large part of the heavy metal content ofsoils (Baize and Sterckeman 2001).

Cd concentrations were below the detection levelfor both methods. Co concentrations varied from 7.2to 38.9 mgkg1 for digestion with AR and from 16.6to 39.0 mgkg1 for EPA 3051 digestion. Mean Coconcentrations were higher for the EPA 3051 extrac-tion than for AR. Mean Cr concentrations were higherfor the AR digestion (47.9 mgkg1) than for EPA 3051(39.4 mgkg1). However, there was significant varia-tion within methods, with AR showing results from20.4 to 142.1 mgkg1 and EPA 3051 from 19.2 to98.8 mgkg1. Mean Cu concentrations were similarfor the two methods: 18.3 and 16.6 mgkg1 for ARand EPA 3051, respectively.

AR extracted much higher quantities of Ni, Pb, andZn than EPA 3051. Mean values varied from 0.2, 5.2,and 1.2 mgkg1 to 24.3, 25.9, and 100.9 mgkg1 forthe AR method, and from 0, 2.7, and 0 mgkg1 to 5.6,15.8, and 69.6 mgkg1 for the EPA 3051 method,respectively. The methods did not differ (p

especially so for elements that are involved in thesilicate matrix, such as Cr, Ni, and Pb. The variationin Ni, Pb and Zn contents in this study probablyoccurred because the amount and the nature of thealuminosilicate matrix also varied.

AR is a mixture of the acids HNO3 and HCl.They react to form nitrosyl chloride (NOCl) andmolecular chlorine (Cl2), which are highly reac-tive, have a high oxidizing power, and are capableof dissolving even noble metals, but do not totallydissolve silicates. In the European Union, AR isthe most commonly used solution for extractingmetals from polluted soils (Gleyzes et al. 2002;Grotti et al. 2002; Quevauviller 2002), and is thestandard method for certifying soil samples inGreat Britain and France (Sakan et al. 2011).The EPA 3051 method uses nitric acid (HNO3),an oxidizing agent commonly used to extract met-als, which are converted into soluble nitrates.Hydrogen peroxide is used as an auxiliary agentin the oxidation of samples with a high content oforganic carbon, which reacts to produce H2O.Oliveira et al. (2008) evaluated the effectivenessof three methods of extracting total metal concen-trations (AR, EPA 3051, and EPA 3052), andconcluded that AR was the most appropriate.Although it does not extract total concentrationsof heavy metals, AR does provide a reasonableestimate of the maximum amount that can poten-tially become available to plants or be leachedinto groundwater (Diaz-Barrientos et al. 1991).

In our study, AR was also the most effective meth-od for extracting naturally occurring heavy metals.This may be due to the association of nitric acid andhydrochloric acid in a closed system, creating a dis-solving mixture that is extremely efficient for heavymetals (Costa et al. 2008) and increases the extractionpower of AR. Extraction procedures with strong acidssuch as AR with HNO3 and/or HCl typically seek toreflect a pollutants potential availability and mobility,factors which are related to its transfer from soils toplants (Rauret 1998). While it did not extract higherconcentrations of heavy metals from Mato Grosso andRondnia soils, the EPA 3051 method is widely usedin the United States and by many environmental agen-cies worldwide, and its use is mandated underBrazilian law by CONAMA.

The CDA model explained the variation betweenthe methods, with Canonical Discriminant Function

(CDF1) (AR) responsible for 100 % of the difference(Fig. 3). One important insight provided by the CDAis the value of the parallel discrimination rate (PDR),which is the product of the standardized canonicalcoefficients (SCC) and the correlation (r). The param-eter r provides univariate information for each metal(i.e., its individual contribution), independent of themethod used. The PDR is more efficient when theresearcher wants to discriminate between areas(Cruz-Castillo et al. 1994; Baretta et al. 2005) ormethods, as in this study. Positive values of thePDR coefficient indicate a separation effect be-tween the methods, while negative values indicatesimilarities between methods for a given attribute(Baretta et al. 2005).

Within the CDF1 the methods varied depending onthe heavy metals studied (Table 3). According to thePDR values within the CDF1, Co, Ni, Pb, and Zn werethe elements that contributed the most to distinguish-ing between the digestion methods (0.21, 0.27, 0.37,and 0.17, respectively), and showed excellent po-tential as indicators (Fig. 3 and Table 5). Pbshowed the highest PDR and was the element thatcontributed the most to distinguishing between themethods. In the CDF2, Ni had the highest PDRvalue (0.26) of all the heavy metals analyzed. Cuwas less sensitive, had a lower PDR value, andcontributed less (0.04 and 0.06, respectively) inthe two functions (CDF1 and CDF2) to distin-guishing between the areas studied (Table 5).

Fig. 3 Relationship between the first and second discriminantcanonical function (DCF1 and DCF2) on the mean (centroid) ofthe standardized canonical coefficients (SCC) for Zn, Ni, Pb, Cr,Co, and Cu in soils of Mato Grosso and Rondnia, Brazil

1430, Page 8 of 16 Water Air Soil Pollut (2013) 224:1430

3.3 Correlations

Correlations between the heavy metal concentrationsin the 19 soil samples and the 34 physical and chem-ical attributes of those soils are presented in Table 6.Metal concentrations extracted with AR, which had ahigher extraction power of the pseudo-total concen-trations of heavy metals, were used in the correlations.With the exception of Cr, there was generally a posi-tive correlation between the concentrations of Co, Cu,Ni, Pb, and Zn (Table 6). Biondi (2010) reportedsimilar results in a study of soils from Pernambuco,Brazil, where Cu concentrations were positively cor-related with concentrations of Zn (r=0.78; r=0.81),Co (r=0.81; r=0.76), and Ni (r=0.73; r=0.71) in thesurface and subsurface horizons, respectively (p0.7*). Lee et al. (1997)studied soils in Oklahoma, USA collected nearthe parent material, underlying sedimentary rocks and concluded that the most influential attribute in thedistribution of heavy metals in the soil profile was thesum of silt and clay contents. In our study, that sumwas also positively correlated with metal concentra-tions, independent of extraction method, and showed acorrelation coefficient varying from 0.31 to 0.73.

In general, Fe and Mn oxides were the variablesthat showed the strongest correlations with heavy met-als. Various authors have noted the importance of ironoxides as determinants of heavy metal mobility insoils under a tropical climate (Fontes et al. 2000;Fontes and Weed 1991; Alloway 1990; Covelo et al.2007). Oxides have varying capacities for adsorbingmetallic cations. For a given type of oxide, the capac-ity for adsorbing cations varies with the degree ofcrystallization of the oxide, and can vary as the weath-ering process causes changes in the form of the crystal,in the surface area, and in the chemical properties ofthe surface of the oxides (Yu 1997). In general, poorlycrystallized substances have a large specific surfacearea and a high capacity for adsorbing metals. Bycontrast, the activity of well-crystallized substancesis comparatively lower (Yu 1997).

Mn oxides and hydroxides are rare in soils and, forthis reason, less studied than Fe oxides. Nonetheless,they are efficient sorbents of heavy metals because oftheir small size and large specific surface area(McKenzie 1979). Like Fe oxides, Mn oxides are verystable (i.e., they have low levels of solubility; Stummand Morgan 1996), their surfaces are highly reactive,and they precipitate as tiny poorly crystallized oramorphous crystals (Fortin et al. 1993; Tessier et al.1996).

CO concentrations were not correlated with theconcentrations of any metal in this study (p

Table6

Pearson

correlationmatrixbetweennaturallevelsof

heavymetals(aquaregiamethod)

andsoilattributes,with

significantvalues

(p