Geoderma xxx (2010) xxx–xxx

GEODER-10554; No of Pages 12

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Geoderma

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Geochemistry and spatial distribution of heavy metals in Oxisols in a mineralizedregion of the Brazilian Central Plateau

Diego Lang Burak a, Mauricio P.F. Fontes b,⁎, Nerilson Terra Santos c, Lena Virginia Soares Monteiro d,Eder de Sousa Martins e, Thierry Becquer f

a Universidade Federal do Espírito Santo, Departamento de Produção Vegetal, 29500-000 Alegre-ES, Brazilb Universidade Federal de Viçosa, Departamento de Solos, 36570-000, Viçosa-MG, Brazilc Universidade Federal de Viçosa, Departamento de Estatistica, 36570-000, Viçosa-MG, Brazild Universidade Estadual de Campinas, Instituto de Geociências, 13083-970, Campinas-SP, Brazile Embrapa Cerrados, Caixa Postal 08223, 73010-970 Planaltina-DF, Brazilf IRD, UMR 210 Eco&Sols, INRA/SupAgro, 2 Place Viala, F-34060 Montpellier Cedex 2, France

⁎ Corresponding author. Currently, Visiting SchoEnvironmental Earth Science System, Stanford, CA, 94

E-mail addresses: dlburak@hotmail.com (D.L. Burak)(M.P.F. Fontes), nsantos@ufv.br (N.T. Santos), lena@ige.eder@cpac.embrapa.br (E.S. Martins), thierry.becquer@i

0016-7061/$ – see front matter © 2010 Elsevier B.V. Aldoi:10.1016/j.geoderma.2010.08.007

Please cite this article as: Burak, D.L., et al.,Brazilian Central Plateau, Geoderma (2010

a b s t r a c t

a r t i c l e i n f o

Article history:Received 11 January 2010Received in revised form 8 August 2010Accepted 23 August 2010Available online xxxx

Keywords:Trace elementsMetals dispersionGeomorphologyGeologyMineral deposits

The majority of the soils of the Central Plateau of Brazil are product of long time development over stablesurfaces, usually associated with erosion and re-deposition cycles. In this context, to successfully study thegeochemistry and spatial distribution of heavy metals, it is essential to understand the geology as well as thegeomorphology of the landscape and the properties of the metals related to their mobility. The main objectiveof this work was to evaluate contents of naturally occurring heavy metals (Co, Cu, Mn, Ni, Pb and Zn) in somehighly weathered tropical soils as related to their geochemistry, geology and geomorphology. Additionally, itwas aimed to interpret the spatial distribution patterns of these metals and of major elements (Al, Fe, Ti andMg), evaluating the association and taking the influence of the geology and geomorphology intoconsideration. In geo-referenced sites, ranging from 480 to 1040 m in altitude, samples were collected attwo depths (0–20 and 60–80 cm), ground, sieved, and prepared for analysis. Heavymetals andmajor elementcontents were determined by extraction with aqua regia. Descriptive statistics, Pearson correlationcoefficients, Principal Components Analysis (PCA) and spatial variability analyses were conducted and soilmetal concentrations for the whole area were predicted by kriging (interpolation). A close associationbetween Pb, Zn, and Mn was observed using PCA and Pearson's correlation. Highest concentrations of Pb, Zn,and Mn were determined in soils between 650 and 550 m altitude surrounding the dolomite massif hills andAmbrósia and Fagundes mineral deposits. Copper and Fe were found to be geochemically associated withhighest concentrations observed in soils formed from carbonaceous phyllite with quartzite layers. Cobalt andNi concentrations were associated with areas characterized geomorphologically as alluvial–colluvial depositsat the lowest altitudes within the region. Although there is a marked dispersive action of tropical weatheringonmetal distribution in the region, Cu, Pb, and Znwere found spatially associated with their geological source.This probably happens because of greater affinity of those metals to Fe and Mn oxides formed predominantlyunder tropical conditions and present in higher concentrations near to the sources of these heavy metals. Onthe other hand, both the low affinity of Ni and Co for these oxide minerals and the region's geomorphologyallowed for their migration towards the drainage network to the regions of sediment accumulation at loweraltitudes during the landscape's evolution.

lar, University of Stanford,305, USA., mpfontes@ufv.brunicamp.br (L.V.S. Monteiro),rd.fr (T. Becquer).

l rights reserved.

Geochemistry and spatial distribution of hea), doi:10.1016/j.geoderma.2010.08.007

© 2010 Elsevier B.V. All rights reserved.

1. Introduction

Geogenic heavy metal contents in soils are dependent initially onthe geological sources. However, important discrepancies in heavy

metal contents between the soils and the underlying bedrocks in thesame area are possible due to the geochemical processes acting onheavy metal distribution within the landscape. Metal distribution inthe landscape should be analyzed based on the geomorphology, andhydrology (Miller, 1997) that control the mobility of metals insolution (Kabata-Pendias and Pendias, 2005) and on factors that canact as geochemical barriers controlling the mobility of metals(Perel'man, 1986).

The region of Unaí-Paracatu-Vazante, in the northwest part ofMinas Gerais State, Brazil, hosts several mineral deposits, notably the

vy metals in Oxisols in a mineralized region of the

2 D.L. Burak et al. / Geoderma xxx (2010) xxx–xxx

largest Zn–Pb district in South America (Dardenne, 1979, 2000;Monteiro et al., 2006, 2007). The Zn–(Pb) deposits are found in theVazante Group (Dardenne et al., 1998) and include different types ofores (Monteiro et al., 2006, 2007). In spite of the large extent of thesedeposits, rendering this region to be naturally prone to the occurrenceof high levels of heavy metals in the soils, research at regional scale ofheavy metal content in soils are, practically, inexistent. As theagriculture rapidly expands in this region, geochemical studies arenecessary to evaluate the potential risk of heavy metal on cropproduction and human health.

The most important soils for agricultural production in the regionare the Latosols, the equivalent to the Oxisols in the US Soil Taxonomyand the Ferralsols in the FAO Soil Classification System. The Latosolsare product of long time development on stable surfaces and areamong the oldest and most weathered soils of the Earth's surface(Vasconcelos et al., 1994). As a consequence of different weatheringcycles, erosion and re-deposition, polygenetic and polycyclic char-acteristics were developed in these soils, as well as an expressivethickness and complexity of their saprolites (Muggler and Buurman,2000). Knowledge of the spatial distribution of heavy metals in thesoil is an important tool for identification of contaminated areas andfor support of soil uses as well as identification of the factorsresponsible for high heavy metal concentrations, helping to under-stand anthropogenic sources for metals in soils and the pedogeo-chemical background. This latter is a first step for heavy metalmonitoring on a local scale for contaminated soils. In this context, thedevelopment of distribution maps through prediction of metalcontents has been accomplished successfully via geostatistical inter-polators (Goovaerts, 1997; Critto et al., 2003; Reimann and de Caritat,2005; Liu et al., 2006). Nevertheless, regional studies using informa-tion on physical processes such as altitude, slope and the hydro-graphic network, important for the interpretation of spatial heavymetal distribution in the landscape, are scarce in tropical regions. Suchinformation can be obtained by Digital Elevation Models (DEM) andGeographical Information Systems (GIS), that are tools used tointroduce determinism within the stochastic concepts of geostatistics(McBratney et al., 2003).

To test the hypothesis that the metal distribution in soils of thismineralized region of the Brazilian Central Plateau is related to thegeology, the geomorphological evolution of the landscape andgeochemical characteristics of the metals, the objective of this studywas to investigate the spatial distribution patterns of the naturallyoccurring metals Co, Cu, Ni, Mn, Pb, and Zn and their association withthemajor elements (Al, Fe, Ti andMg) in the Oxisols developed on theflat surfaces of the Unaí-Paracatu-Vazante region, Minas Gerais, Brazil.

2. Study area

2.1. Geology

The study region has a total area of 15,700 km2 and is located inthe northwest part of Minas Gerais State, Brazil (Unai-Paracatu-Vazante region) and in the eastern part of the Brasília Fold Belt (BFB)(Dardenne, 2000) that, together with the Araguaia and Paraguai FoldBelt, forms the Tocantins Province (Fig. 1) (Almeida, 1967). Thisprovince results from important orogenic events which occurredduring the Neoproterozoic in consequence of the convergence andcollision of the Amazônico, São Francisco-Congo and Paraná cratonblocks (Dardenne, 2000), during the amalgamation of the Gondwanasupercontinent.

The BFB is characterized as an unstable tectonic unit that sufferedsuccessive reactivations resulting in a history of metamorphism anddeformations. The main stages of the tectonic evolution of BFB arerelated to two collision events, one related to amagmatic arc–continentcollision (ca. 0.79 Ga) and the other associated with a continent–continent collision (0.63–0.61 Ga). The Neoproterozoic Vazante Group

Please cite this article as: Burak, D.L., et al., Geochemistry and spatial dBrazilian Central Plateau, Geoderma (2010), doi:10.1016/j.geoderma.20

lies on the western border of the São Francisco Craton and represents ameta-sedimentary unit of the southern segment of the Brasília Fold Belt(Fig. 1). Several Zn and Pb mineral deposits in the Vazante Group wereformed as a result of hydrothermal events, which have been related tothick marine pelitic–dolomitic sequence affected by low greenschistfacies metamorphism related to the metamorphic-deformationalhistory of the BFB resulting in several carbonate-hosted zinc oredeposits. These primary ore types in the district differ mainly in relativesulfide abundance, which is a notable feature of the Morro Agudo,Ambrosia and Fagundes deposits, but is subordinate to willemitic ore(Zn2SiO4) in the Vazante deposit (Monteiro et al, 2006, 2007) (Fig. 1c).The tectonic evolution, geology, and characteristics of the mineraldeposits existents in the VazanteGroup have beendescribed in detail byDardenne (2000), Pimentel et al. (2001),Misi et al. (2005) andMonteiroet al. (2006, 2007).

The Canastra Group (1.2 Ga) (Dardenne, 1979, 2000) is represen-tative of the deposition during the evolution of the passive margin ofthe west border of the São Francisco craton (Dardenne, 2000) (Fig. 1).The deposition of these sequences would have occurred in aplatformal environment of shallow waters to the east, favoring theformation of superior carbonatic sequences (e.g. the Serra do LandimFormation), and inferior sequences rich in carbon, sulfides andterrigenous sediments on the west side (e.g. the Paracatu Formation).In this region anoxic conditions in the depositional paleoenvironmentmay have favored precipitation of these metals as sulfides (chalco-pyrite and pyrite) (Fuck et al., 1993). Due the compression event andthe inversion of the sequences formed, the Vazante group istectonically directly overlaid by carbonaceous phyllites of theParacatu Formation of the Canastra Group.

2.2. Geomorphology

As far as the geomorphology is concerned, the region ischaracterized by a remaining South American geomorphic surfaceat altitudes of 900 to 1100 m i.e., the oldest surface in the region.During the Tertiary, tectonic uplift and sea regression initiatederosion and carved new valleys, exposing older underlying rocks toweathering and/or deep saprolites to erosion, resulting in newerosion surface cycles called Velhas I and Velhas II (King, 1956;Lepsch and Buol, 1988). In the studied region the Vazante Groupcarbonate rocks facilitated a lowered relief at 480 to 750 m altitudesurrounded by the topographically higher Central Plateau of Brazil(Fig. 2). Within the lowered region, the soils from the higherelevations (550 to 750 m) developed over Neo-proterozoic units ofthe Vazante Group and the Paracatu Formation. In the lowerelevations (480 and 550 m) the soils developed over detritic–lateriticcover deposits from elluvial/colluvial origin and unconsolidatedsediment deposits from alluvial and colluvial origin formed duringthe Tertiary/Quaternary period (Fig. 2). In the lowest elevationregion, processes of fluvial deposits, terraces, floodplains, and fluvialplains were of wider occurrence during the geomorphologicevolution (Naime and Motta, 1998). The area constitutes a drainagesystem that flows in a west–east direction.

The soils developed on the flat landscape of the South Americanand Velhas geomorphic surfaces are predominantly Oxisols thatcorrespond to 64.2% of the total area of the region studied. The soilsformed over the higher geomorphic surface (South American) aremore weathered with higher gibbsite contents than those of theVelhas surfaces (480 to 750 m altitude) (Naime and Motta, 1998).

3. Materials and methods

3.1. Sampling

Soils were sampled in the South American and Velhas geomor-phologic surfaces. Sampling was done in two depths (0–20 and 60–

istribution of heavy metals in Oxisols in a mineralized region of the10.08.007

Fig. 1. (A) Location map of the Brasília Fold Belt and the São Francisco Craton (Dardenne, 2000); (B) Geological map of the southern segment of the Brasília Fold Belt (Dardenne,2000): (1) Phanerozoic basins; (2) Bambuí Group, Três Marias Formation; (3) Bambuí Group, Paraopeba Subgroup; (4) Ibiá Formation; (5) Araxá Group; (6) Felsic and maficgranulites and orthogneisses; (7) Vazante Group; (8) Paranoá Group; (9) Canastra Group. (C) Detailed Geological map of study region: (1) Canastra Group (Superior Member Serrado Anta); (2) Paracatu Formation (carbonaceous phyllite with quartzite layers); (3) Vazante Group (slates, phosphorites and quartzites) (4) Vazante Group (dolomites, cherts,metapelites and phosphorites); (5) Detritic–lateritic, detritic and elluvial/colluvial cover deposits in peneplanation surfaces; (6) Paranoá Group (quartzites, pelites, limestones,dolomites, cherts and conglomerates).; (7) Unconsolidated Sediments (alluvial–colluvial origin deposits).

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80 cm) within the Oxisol soil units according to the soil map of Naimeand Motta (1998). Such depths were chosen to best represent the Aand B horizons in the Oxisols. Approximately one sample point/54 km2 was selected on an irregular grid, resulting in a total of 237geo-referenced sites. Sampling was avoided in areas near to potentialsources of heavy metals (near roads, railroads, mining areas) andstainless steel equipments were used for collection and samplepreparation. Natural environments were preferred over pastures orcropped land, but unavoidably some soils were sampled in these areasdue to the increasing extensive agriculture and cattle farmswithin theregion's Oxisols.

3.2. Chemical analysis

Initially the samples were dried and sieved in 10 mesh and afterthat a soil sample was crushed and sieved in 100 mesh. Heavy metalswere measured following digestion of soil with aqua regia (3 HCl:1HNO3). The analyses were performed in random sequences and the Al,Fe, Ti, Mg, Mn, Cu, Pb, Zn, Ni and Co analyses were determined byinductively coupled plasma atomic emission spectrometry (ICP-AES).The accuracy of the analytical determinations was evaluated using thecertified reference samples Buffalo River Sediment (SRM 2704), SanJoaquin Soil (SRM2 700), Lake Sediment (LKSD-1) after a tri-acid

Please cite this article as: Burak, D.L., et al., Geochemistry and spatial diBrazilian Central Plateau, Geoderma (2010), doi:10.1016/j.geoderma.20

digestion (HCl, H2SO4, HF) in a microwave oven. All glassware andmaterials were cleaned for metal analysis. Certified analytical gradereagents were used throughout. Analytical grade HCl and HNO3 wereused for digestion. Blanks were run through all experiments to detectany contamination.

3.3. Statistical and geostatistical analyses

For each of the sample sets under study, the anthropic influencewasevaluated using the Top Enrichment Factor (TEF) (Facchinelli et al,2001), defined as the heavy metals concentration ratio between theupper layer (0–20 cm) and the underlying layer (60–80 cm).

Conventional descriptive statistical analyses of the samples wereperformed as a first approach for the evaluation of metal contents.Skewness and kurtosis indices were calculated to test the normality ofthe distribution of the data. The relationships between the elementswere analysed by using Pearson's correlation coefficients andPrincipal Components Analysis (PCA). The PCA allows for theidentification of the components responsible for the total variationof the data as well as the variable groups that explain these variations,which cannot be obtained by Pearson correlations.

The spatial correlation of samples was analyzed by the experi-mental semivariograms, to which the mathematical models were

stribution of heavy metals in Oxisols in a mineralized region of the10.08.007

Fig. 2. Digital Elevation Model (DME) with the samples used, mineral deposits and drainage network of the Unaí-Paracatu-Vazante region.

4 D.L. Burak et al. / Geoderma xxx (2010) xxx–xxx

fitted. This becomes necessary for the determination of the structureof the spatial variation of the variables studied and to obtain inputparameters for kriging interpolation. The mathematical models testedwere the exponential, spherical, and Gaussian. Since the anisotropicfeature (north–south and east–west) was not clearly identified inthese semivariograms, the unidirectional semivariograms werecomputed. The fitness of the semivariogram model was evaluatedby a cross validation technique and R2 values (Goovaerts, 1997;Webster and Oliver, 2007). The software used was the SAS system®(SAS, 1998) and the geostatistical analyst extension of ArcGIS 9.0®and GIS+® (version 7.0).

With the concentrations results for Al, Fe, Ti, Mn, Mg, Cu, Co, Ni, Pband Zn, maps were generated using ordinary kriging as interpolator.The variables Pb, Zn and Mn were logarithmically transformed since

Please cite this article as: Burak, D.L., et al., Geochemistry and spatial dBrazilian Central Plateau, Geoderma (2010), doi:10.1016/j.geoderma.20

the data for them presented an accentuated asymmetry. Thesetransformations render the semivariograms more robust and betterestimates are obtained in the kriging (Goovaerts, 2001; Webster andOliver, 2007).

4. Results

4.1. Descriptive statistics of raw data set

Heavy metals concentration results (statistics presented in Table 1)were obtained using aqua regia which is a digestion procedure used toassess soil quality as far as the extraction of trace elements is concerned(ISO 14466, 1995). Aqua regia procedure is considered adequate foranalyzing total-recoverable heavy metals in soils of certain regions

istribution of heavy metals in Oxisols in a mineralized region of the10.08.007

Table 1Summary of the descriptive statistics of the raw data.

Metals Mean Median Minimum Maximum S.D. CV (%) Skewness Kurtosis Percentage exceedingguide value

Enrichment ratio

Preventiona Interventionb Cerrado soilsc

Al (g kg−1) 100.30 93.50 5.60 229.70 49.40 49.30 0.38 −0.63 – – –

Fe (g kg−1) 61.30 60.80 4.50 145.40 22.10 36.10 0.36 1.15 – – –

Ti (g kg−1) 0.72 0.65 0.13 2.21 0.40 55.20 1.48 2.88 – – –

Mg (g kg−1) 0.63 0.61 0.08 2.19 0.37 57.60 1.04 1.53 – – –

Mn (mg kg−1) 190 130 10 1860.0 222.0 114.60 4.89 29.76 – – 0.42Log (Mn) 4.93 4.90 2.45 7.53 0.74 15.08 0.18 1.69 – – –

Pb (mg kg−1) 40.34 31.61 1.99 465.32 43.27 107.30 5.93 47.92 7.14 2.8 1.55Log (Pb) 3.70 3.76 0.74 6.14 0.71 19.21 −0.74 3.87 – – –

Zn (mg kg−1) 44.97 27.58 6.75 556.26 78.17 173.80 5.01 26.07 2.38 1.9 1.73Log (Zn) 3.38 3.32 1.91 6.32 0.72 21.23 1.76 5.16 – – –

Cu (mg kg−1) 35.66 32.48 7.71 157.67 21.87 61.30 2.64 10.01 6.19 0 0.94Ni (mg kg−1) 22.16 21.30 3.41 66.88 9.02 40.70 1.14 2.68 17.62 0 1.58Co (mg kg−1)) 5.40 4.94 1.23 23.50 3.22 59.60 2.28 8.46 0 0 1.08

S.D.: standard deviation; C.V.: coefficient of variation.a Prevention values according to CETESB (2005) of: 25 mg kg−1 for Co; 30 mg kg−1 for Ni; 60 mg kg−1 for Cu; 72 mg kg−1 for Pb; and 300 mg kg−1 for Zn.b Intervention values according to CETESB (2005) of: 35 mg kg−1 for Co; 70 mg kg−1 for Ni; 200 mg kg−1 for Cu; 180 mg kg−1 for Pb; and 450 mg kg−1 for Zn.c Average concentration ratios obtained in this study divided by the average concentrations (n=61) of the Cerrado soils in the Planalto Central obtained by Marques et al. (2004).

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(Chen and Ma, 2001) and sometimes, it is also used for guidelinescomparison. The aqua regia extraction is the standard method used byCompany of Environmental Sanitary Technology from the Office ofEnvironment of São Paulo State, Brazil (CETESB) to evaluate heavymetal concentrations in Brazilian soils (CETESB, 2001, 2005).

The top enrichment factor (TEF) was calculated for each samplingpoint and 27 sample points with TEF greater than 1.5 were discardedfrom the statistical and geostatistical analyses. According to Fachinelliet al. (2001), who studied soils from temperate regions, a naturalpedogenetic enrichment is unlikely to produce TEF values exceeding2, while higher values point to an important anthropic input from thetop. Therefore, TEF values greater than 2 indicate an importantanthropic addition. In our study, soil samples that showed TEF valuesgreater than 1.5were considered TEF-outliers for evaluation of naturalheavy metal contents and were eliminated from the data set. Theselection of the 1.5 value instead of 2 is justified because of the greaterdegree of weathering, leaching and pedological homogeneity atdepths to which the soils of tropical climates are naturally subjected.For the remainder of the samples, the mean of the two depths wasused in statistical and geostatistical analyses. Table 1 presents thedescriptive statistics for the 10 metals analyzed in the present study,after removing TEF-outliers.

The skewness and kurtosis coefficients show that the Al, Fe, Ti, Mg,Cu, Ni, and Co concentrations have a symmetrical and shapedistribution similar to normal distributions. However, the distributionfor Mn, Pb, and Zn exhibited a strong positive skewness. Furthermore,the coefficients of variation of these three metals were greater than forother metals, suggesting that their contents varied more from soil tosoil. The high skewness, kurtosis and standard deviation values of thedata could indicate the occurrence of geochemical anomalies in ageochemical prospection (Gonçalves et al., 1998). The kurtosis andskewness values for Mn, Pb and Zn decreased after the raw data setswere logarithmically transformed and analyzed (Table 1). Spatialanalyses were carried out using logarithmically transformed values.According to Webster and Oliver (2007), when the raw data setpresents skewness coefficients above 0.5, logarithmic transformationbecomes necessary.

The mean metal contents of the soils were 5.4 (Co), 35.7 (Cu), 22.2(Ni), 40.3 (Pb) and 45 (Zn) mg kg−1, (Table 1). The values obtainedfor Pb, Zn and Ni are 1.5 to 1.7 times higher, whereas the values of Cuand Co are quite similar and Mn is lower than those obtained in soilsfrom the Central Plateau of Brazil by Marques et al. (2004), whoanalyzed total contents of trace elements by wavelength-dispersiveX-ray fluorescence spectroscopy (WD-XRF).

Please cite this article as: Burak, D.L., et al., Geochemistry and spatial diBrazilian Central Plateau, Geoderma (2010), doi:10.1016/j.geoderma.20

Only the Ni and Pb mean contents were slightly higher than theReference Values (Ni=13; Pb=17 mg kg−1), i.e. the natural contentsof these elements for a non-contaminated soil as proposed by CETESB(Company of Environmental Sanitary Technology from the Office ofEnvironment of São Paulo State, Brazil), a Brazilian State Agency thatproposed the first tabulation of guidance values for heavy metals toidentify maximum acceptable values of contamination in Braziliansoils (CETESB, 2001, 2005). Besides the Reference Values, CETESB(2005) also proposed Prevention and Intervention Values. Heavymetal contents above the Prevention Values suggest the existence ofsoil quality alteration and a potential risk to human health, requiringcontrol of additional heavy metal introduction for example, viafertilizers, sewage sludge etc., and a real risk to human health alreadyexists if the heavy metals contents are above the Intervention Values.All the heavy metals studied, except Co, had a small percentage (2–18%) of the samples with concentrations above the Prevention Values(Table 1). For Pb and Zn, some samples (2–3%) were above theIntervention Values demonstrating the need for environmentalmonitoring of the more contaminated areas represented by thesesamples.

4.2. Relationships between heavy metals and major elements

Pearson's correlation coefficients between pairs of metal concen-trations are presented in Table 2. A significant and positive correlationcoefficient suggests a similar geochemical behavior and/or a commonsource material of these elements.

A significant positive correlation was verified for Al with Fe and Tishowing that these elements have a similar geochemical behavior,being very immobile. Fe and Al have similar behavior by formingsecondary minerals as oxides such as hematite, goethite and gibbsite,which are typical of Oxisol mineralogy (Fontes and Weed, 1991).Titanium has geochemical similarities with Al and Fe because inOxisols it normally forms secondaryminerals such as anatase which isvery resistant to weathering (Milnes and Fitzpratick, 1989). Anotherpositive and significant correlation was found between Fe and Mgindicating a common source for both elements but a negativeassociation was found for Mg and Al suggesting that these elementshave neither a common source nor similar geochemical behavior. Thecorrelations of Fe with Pb and Cu seem to be related to the formationof secondary iron oxides that have the capacity to strongly adsorbthese two heavy metals, as already described in the literature (Gomeset al., 2001; Sipos et al., 2008; Serrano et al., 2009).

stribution of heavy metals in Oxisols in a mineralized region of the10.08.007

Table 2Correlation coefficientsa obtained between all the elements studied.

Al Fe Ti Mg Mn Pb Zn Cu Ni Co

Al 1Fe 0.31*** 1Ti 0.37*** 0.30*** 1Mg −0.43*** 0.19** −0.13 1Mn −0.15 0.17 0.20** 0.38*** 1Pb −0.02 0.19** 0.26*** 0.13 0.60*** 1Zn −0.20** 0.02 0.10 0.29*** 0.75*** 0.64*** 1Cu −0.09 0.52*** 0.04 0.39*** 0.20** 0.16 0.14 1Ni −0.12 0.04 −0.20** 0.46*** 0.19** 0.03 0.13 0.38*** 1Co −0.28*** 0.06 −0.03 0.36*** 0.37*** 0.13 0.25*** 0.38*** 0.71*** 1

a Pearson correlation: **pb0.01 ***pb0.001.

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Among the heavy metals, very strong and significant correlationswere obtained between Zn, Pb and Mn, which is explained by theircommon source (Dardenne et al., 1998). Significant correlations werealso observed for Mg with Zn, Cu, Ni, and Co probably due to theirgeochemical behavior as far as adsorption processes are concerned.Magnesium, Zn, Ni and Co are known to be predominantly boundelectrostatically to colloidal surfaces in tropical soils (Matos et al.,2001; Fontes e Gomes, 2003; Covelo et al., 2007).

To better quantify the relationships among the variables understudy and to identify the group of geochemically similar samples,Principal Component Analysis was performed, and the first threeprincipal components (PCs) were chosen based on the eigenvaluesbeing greater than 1. Fig. 3 shows the main results from the principalcomponent analysis (PCA) conducted. The first three PCs explained68.4% of the total variation of the data. The relationships between thePCs and environmental factors, such as pedological, biogeochemicaland anthropogenic factors have been successful explored with PCA(Facchinelli et al, 2001; Critto et al., 2003; Liu et al., 2006).

All the elements, except Al, were negatively correlated with thefirst Principal Component (PC1), whereas Al was positively correlatedwith PC1 and PC2, indicating its poor associationwith the othermetals(Fig. 3A). The soil sample scores in the CanastraGroup seemed to have alarger contribution to the positive correlation of Al with PC1 and PC2.With the second and third Principal Components it was possible toobtain three groups of variables with better relationship among them,i.e., their data points appeared closer in PCA graph (Fig. 3C): Zn, Mn andPb were positively correlated with PC2 and PC3; Mg, Co and Ni werenegatively correlated with PC2 and PC3; and Ti, Al, Fe and Cu werenegatively correlatedwith PC3 and positively correlatedwith PC2. It canbe observed for the first group (Zn, Mn and Pb) a better contribution ofsoil sample scores of Vazante Group; in the second group (Ti, Al, Fe andCu) a better contribution of soil sample scores of Paracatu Formationbelow 800 m; and in the third group (Mg, Co and Ni) a bettercontribution of soil sample scores from the detritic–lateritic-Tertiarycover/unconsoli-dated sediment below 550 m (Fig. 3D).

Therefore, with the PCA analysis it was possible to separategeochemically similar sub-regions: a sub-region in altitudes above900 m developed over the higher geologic members of Canastra Group,including part of the Paracatu Formation, associated mainly with Al; asub-region in altitudes below 800 m over the Paracatu Formationassociated mainly with Fe and Cu; a sub-region developed over theVazante Group in altitudes between 600 and 700 m associated mainlywith Mn, Pb and Zn; and a sub-region developed over detritic-lateritic-Tertiary cover and unconsolidated sediments of alluvial–colluvial originat altitudes below 550 m, associated with Mg, Ni and Co.

4.3. Characterization of the spatial variability

The geostatistical method attempts to extract the structural andprobabilistic characteristics of a given regionalized phenomenon from

Please cite this article as: Burak, D.L., et al., Geochemistry and spatial dBrazilian Central Plateau, Geoderma (2010), doi:10.1016/j.geoderma.20

an apparent randomness of the data collected, i.e. a spatial correlationbetween the values situated in a certain neighbourhood within thesampled area (Goovaerts, 1997; Webster and Oliver, 2007).

Table 3 shows the best theoretical models fitted and the estimatedparameters of the experimental semivariograms for the majorelements and the heavy metals. The semivariograms were computedaccording to exponential, spherical, and Gaussian models and thecross validation results are also presented in Table 3. The Gaussianmodel was used for Al, Mn and Co, the spherical model for Fe, Pb, Zn,Cu and Ni, and the exponential model for Ti. All the theoretical modelsgave a good fit to the experimental semivariograms; the values for theroot-mean-square standardized errors are close to one and those ofthe mean standardized errors are close to zero as well as thedetermination coefficients, R2, are close to one (Goovaerts, 2001;Webster and Oliver, 2007).

The nugget effect was analyzed by means of its percentage on thesill (C0/C0+C1) with the objective of evaluating the degree of spatialdependence (Cambardella et al., 1994) (Table 3). The nugget effects(C0) corresponded to field variation at a much smaller distance thanthat used in the sampling scale (Goovaerts, 1997; Webster and Oliver,2007).

Additionally, on the regional scale, weaker spatial dependence canbe attributed to extrinsic factors (soil management practices, such asfertilization) and higher spatial dependence of soil properties can beattributed to intrinsic factors (soil formation factors, such as soil parentmaterials and relief) (Cambardella et al., 1994). A high degree of spatialdependence was only verified for Zn and Cu (C0/C0+C1b25%). Theother metals studied presented a moderate degree of spatial depen-dence 25%bC0/C0+C1b75%).

None of the metals showed a weak degree of spatial dependence.The range (a value) is the distance at which spatial autocorrelationbetween pairs of data points ceases. Its variation between 33 and100 km implies that the distance of the spatial autocorrelation islonger than the average distance of 7.4 km between samples,indicating that the sample framework used was adequate to representthe spatial structure so that geostatistical interpolation maps of goodquality will be obtained (McGrath et al., 2004). Among the heavymetals, Mn, Cu, Pb, and Zn presented the smaller range values than Niand Co.

4.4. Regional distribution of the heavy metals in soils

The spatial distribution pattern of the heavy metals and theirrelationship to the geological setting and altitude levels, were evaluatedby the geostatistical maps of the Co, Cu, Mn, Ni, Pb and Zn contents andrelated to the geological setting and altitude levels (Fig. 4). Lead and Znpresented similar spatial distribution patterns, in which the regions ofhigher contents occurred within the metapelitic–dolomitic unit of theVazante Group. Regions with contents above 72 mg kg−1 for Pb and300 mg kg−1 for Zn (Prevention Values – CETESB, 2005) and samples

istribution of heavy metals in Oxisols in a mineralized region of the10.08.007

-4

-2

0

2

4

CP

3:

16,1

1 %

CP 2 : 20,15 %

D

CP 1 : 32,14 %-4

CP

2:

20,1

5%

-4

-2

0

2

4 B

Al

Fe

TiMg

Mn

Cu

Zn

NiCo

Pb

PC 2: 20,15%

-1,0

-0,5

0,0

0,5

1,0

PC

3:

16,1

1%

C

AlFe

Ti

Mg

Mn

Cu

Zn

Ni Co

Pb

-1,0PC 1: 32,14%

-1,0

-0,5

0,0

0,5

1,0

PC

2:

20,1

5%

A

CANASTRA GROUP + PARACATU FORMATION soil samples upper 900 m

DETRITIC-LATERITIC COVER, ELUVIAL DEPOSITS and PARANOA GROUP soil samples upper 550 m

DETRITIC-LATERITIC COVER, ELUVIAL DEPOSITS soils samples lower 550 m

VAZANTE GROUP soils samples betwenn 700 e 600 m

PARACATU FORMATION soils samples lower 800 m

UNCONSOLIDATE SEDIMENTS (alluvial-colluvial origin deposits) lower 550 m

-0,5 0,0 0,5 1,0 -1,0 -0,5 0,0 0,5 1,0

-2 0 2 4 -4 -2 0 2 4

Fig. 3. Graph of the PCA and their respective correlations with the variables studies (A and C); plots of samples scores, identifying their respective geologic groups (B and D) for thefirst and the second principal component (A and B); and the second and third Principal Components (C and D).

7D.L. Burak et al. / Geoderma xxx (2010) xxx–xxx

above the Intervention Values for these metals occurred close to thedolomite massifs near to the Ambrósia and Fagundes deposits. Inthe Paracatu Formation, the zonewith highest Pb contents occurs in thesouthern part of this geologic unit. The areas with contents above

Table 3Theoretical models and estimated parameters of the experimental semivariograms and the

Metala Model Parametersb

C0 C0+C1 C0/(

Al Gaussian 879 3125 28Fe Spherical 181 567.5 31Ti Exponential 891 1852 48Mg Gaussian 606 1545 39Mne Gaussian 0.059 0.124 47Pbe Spherical 0.049 0.101 48,5Zne Spherical 0.007 0.133 1Cu Spherical 32 548 5Ni Spherical 34.5 105.4 32Co Gaussian 7.45 14.9 50

a Al, Fe in g kg−1; Ti and Mg in dag kg−1; Mn, Pb, Zn, Cu, Ni, and Co in mg kg−1.b C0=nugget effect; C0+C1=sill; a=range.c Cross validation evaluated with the Mean Standardized Errors (MSE) and the Root-Mead Spatial dependence (%) classified as: b25%=strong; between 25 and 75%=moderatee For Mn. Zn and Pb the concentrations were transformed to their logarithms.

Please cite this article as: Burak, D.L., et al., Geochemistry and spatial diBrazilian Central Plateau, Geoderma (2010), doi:10.1016/j.geoderma.20

the Prevention Values made up 0.87% of the studied area for Zn and6.68% for Pb, i.e. 136 and 1036 km2, respectively. Lower contents forthese metals are detected at the lower altitudes, indicating a weakdispersion along the landscape decline.

ir cross validation statistics.

Cross validationc

C0+C1)d a R2 RMSSE MSE

.1 91.4 0,956 1.009 0.003

.8 74.3 0,939 1.001 0.001

.1 47.4 0,745 0.941 0.004

.2 42.6 0,949 1.053 0.004

.5 58.0 0,953 1.010 0.00438.2 0,914 1.062 0.006

.60 52.0 0,869 1.051 0.006

.2 33.3 0,966 1.139 0.016

.7 100.4 0,945 1.011 0.006

.0 79.4 0,920 0.952 −0.010

n-Square Standardized Errors (RMSSE) (Goovaerts, 2001).and N75%=weak (Cambardella et al., 1994).

stribution of heavy metals in Oxisols in a mineralized region of the10.08.007

Fig. 4. Spatial distribution of Mn, Pb, Zn, Cu, Ni, and Co contents by geostatistical interpolation using ordinary kriging. Geology Legend: CG (Canastra Group – Serra do Anta Member).PF (Paracatu Formation). VG (Vazante Group). DLed (Detritic lateric eluvial/coluvial deposits). ACds (alluvial and colluvial sediment deposits). Mineral Deposits Legend: 1 =Fagundes, 2 = Ambrósia, 3 = Morro Agudo, 4 = Vazante.

8 D.L. Burak et al. / Geoderma xxx (2010) xxx–xxx

High Cu contents were determined in soils on the flat surfaces atapproximately 650 to 750 m altitude, where phyllites and carbona-ceous phyllites with quartzite layers occur, belonging to the ParacatuFormation. Copper contents above Prevention Value, 60 mg kg−1,(CETESB, 2005) corresponded to 5.08% of the total area under study,i.e., 797 km2. These contents were not observed exclusively in theParacatu Formation and Cu contents from 20 to 40 mg kg−1 occurredat lower altitudes.

The highest Mn contents occur exclusively close to the Ambrósiaand Fagundes deposits within the Vazante Group. The origin of Mn inthe region, as well as that of Pb and Zn, could be hydrothermal, relatedto the genesis of the zinc–lead ore bodies of the Ambrósia deposit(Monteiro et al. 2006, 2007). Although Mn does not have yet aguidance Reference Value in the CETESB (2005) tabulation, it is arelevant heavy metal and its distribution is very important for heavymetal contamination and pollution monitoring. There are reports of

Please cite this article as: Burak, D.L., et al., Geochemistry and spatial dBrazilian Central Plateau, Geoderma (2010), doi:10.1016/j.geoderma.20

higherMn contents in other studies in Brazilian Central Plateau region(Marques et al., 2004). In general, manganese contaminationproblems are relatively minor, and toxicity levels are found almostonly in plants grown in environments subjected to flooding. Thespatial distribution of Ni and Co was similar and higher content ofthese metals were detected in soils developed on detritic–lateritic-Tertiary cover and unconsolidated Sediments of alluvial–colluvialorigin at the lowest altitudes. Nickel contents exceeded the Preven-tion Value of 30 mg kg−1 (CETESB, 2005) in 5.82% of the total areaunder study, corresponding to 911 km2, and the contents of Co werebelow the Prevention Value (CETESB, 2005).

4.5. Regional distribution of major elements (Al, Fe, Mg and Ti) in soils

Aluminum, Fe, Ti and Mg were evaluated by the geostatisticalmaps and related to the geological setting and altitude levels (Fig. 5).

istribution of heavy metals in Oxisols in a mineralized region of the10.08.007

Fig. 5. Spatial distribution of Al, Fe, Ti, and Mg contents by geostatistical interpolation using ordinary kriging. Geology legend: CG (Canastra Group – Serra do Anta Member). PF(Paracatu Formation). VG (Vazante Group). DLed (detritic lateric elluvial/coluvial deposits). ACds (alluvial and colluvial sediments deposits). Mineral deposits legend: 1= Fagundes,2 = Ambrósia, 3 = Morro Agudo, 4 = Vazante.

9D.L. Burak et al. / Geoderma xxx (2010) xxx–xxx

In general, the high Al and Ti contents were observed above 800 m,corresponding to the upper geological units of the Canastra Group(Serra do Anta Members). Since this surface is the oldest in the regionand has undergone a high degree of weathering, the soils developedhave higher concentrations of Al and Ti extracted with aqua regia, dueto the occurrence of secondary Al- and Ti-bearing minerals, such asgibbsite and anatase. The highest Fe contents were related to the soilsformed on the Paracatu Formation and the lowest contents occurredin the soils at lower altitudes. Magnesium contents are distributedalong the Vazante Group and over the Paranoá Group. The dolomiterock is the main source of Mg, with the element distributed along thelower altitudes indicating a weak dispersion pattern for this metal.

5. Discussion

5.1. Heavy metal sources and relationship to the geological setting

The Brasília Belt includes in its eastern part a thick pile ofsediments deposited along the western margin of the São Franciscocraton. Several lithostratigraphic units are identified (e.g. Paranoá,Vazante, Canastra, and Bambuí Groups) and have been interpreted as

Please cite this article as: Burak, D.L., et al., Geochemistry and spatial diBrazilian Central Plateau, Geoderma (2010), doi:10.1016/j.geoderma.20

part of a Meso- to Neoproterozoic passive margin of the São Franciscocontinent, with shallow water platformal sediments in the east, anddeeper-water turbiditic sediments in the west (Dardenne, 1979;Pimentel et al., 2001).

The Canastra Group is characterized at its base by green carbonatephyllite of the Serra do Landim Formation (Mandalosso, 1980) andimmediately above this by carbonaceous phyllites enriched with Cuand Fe of the Paracatu Formation. The carbonaceous phyllites areformed by low-grade metamorphism of black shales, i.e. sedimentaryrocks well known as concentrators of many metals (Starostin andYapaskurt, 2007). The Serra do Landim Formation composed by greencarbonate phyllite presents high Cu contents associated withmalachite [Cu2CO3(OH)], a secondary mineral formed by Cu super-gene accumulating processes from oxidation of the primary mineralchalcopyrite from the Paracatu Formation (Viviani et al., 2001).

Therefore, greater Cu and Fe contents are detected in soils abovethe Paracatu and Serra do Landim formations developed below 800 m,where the carbonaceous phyllites and green carbonate phyllite weremore exposed to weathering (Figs. 4 and 5). The statistical distribu-tions of the Cu and Fe contents, the most abundant metals in thisregion, are closer to the normal distribution, and do not show an

stribution of heavy metals in Oxisols in a mineralized region of the10.08.007

10 D.L. Burak et al. / Geoderma xxx (2010) xxx–xxx

accentuated asymmetry (Table 1), suggesting that a concentrationmineralizing event (hydrothermal, e.g.) affecting a small region didnot occur. This geochemical behavior (normal distribution) suggests asupergenic enrichment that happened in more recent geologicalperiods during the rock weathering and relief development. Althoughpresent in lower contentswhen comparedwith the Vazante Group, Znand Pb are also detected in the Paracatu Formation and the occurrenceof these metals would also be associated with the same geneticprocess verified for Cu (Zini et al., 1988).

The Pelitic-dolomitic sequences of the Vazante Group contain thelargest Pb–Zn deposits in Brazil (Vazante, Morro Agudo, Fagundes andAmbrósia deposits) (Misi et al., 2005; Monteiro et al., 2006, 2007). Thegenesis of such deposits is hydrothermal, associated with large scalemigration of hot saline fluids that have leached metals from thesedimentary sequence of the Vazante Group. Themetal deposits occuras sulfides (sphalerite, galena and pyrite in Morro Agudo, Ambrósiaand Fagundes) or silicates (willemite in Vazante) associated withcarbonate rocks which are exposed as dolomite outcrops in the region(Monteiro et al., 2006, 2007).

The results of this study indicate that, regardless of the large scaleinteraction of the Vazante Group rocks with metalliferous fluidsresulting in various mineral bodies, higher soil metal contents arerestricted to the areas close to the Ambrósia and Fagundes deposits(Fig. 4). These deposits are characterized as gossans, i.e. intenselyweathered ore deposits corresponding to the upper and exposed partof the sulfide-rich ore bodies. In Vazante and Morro Agudo deposits,the ore bodies occur more deeply, where weathering did not reachyet. The statistical distribution of Pb, Zn and Mn contents indicates astrong skewness (Table 1) which is characteristic of geochemicalanomalies and of metal-concentrating geochemical events (Gonçalveset al., 1998) such as hydrothermal processes. The dolomites associatedwith the Ambrósia deposit also have a higher Mn content than theother deposits (Monteiro et al., 2006, 2007).

High Co contents in soil occur in regions close to the Ambrósia andFagundes deposits (Fig. 4), and for Ni, higher contents are found inother areas of the Vazante Group and both metals are also found atlower altitudes. The origin of Ni and Co in the Unaí-Paracatu-Vazanteregion may be related to mafic intrusion in the metapelitic–dolomiticunits of the Vazante Group, as mafic dikes have been identified in theregion (Babinski et al., 2005). These metals, when not associated withmafic rocks, may be associated with sulfides such as pyrite (FeS2),pyrrotite (FeS), chalcopyrite (CuFeS2) and arsenopyrite (AsFeS2)(Wedepohl, 1978; Ure and Berrow, 1982).

5.2. Metal dispersion in the landscape

Metal distribution in the landscape is dependent upon thegeomorphology and hydrology, which influence metal dispersion, andthe geochemical barriers, i.e. the soil constituents that scavenge or sorbheavymetals, and that prevent itswider dispersion in the environment.

In the Central Plateau of Brazil from the end of the Proterozoic tothe Upper Ordovician Superior a stable cratonic domain wasconsolidated and, being associated with a tropical climate, promotedintensive chemical weathering, forming deep saprolites. This inten-sive weathering is an important process for the generalized planationand the formation of the South American Surface (SAS), according tothe etchplanation theory (Thomas, 1994). King (1956) reported thetablelands (chapadas) 900 to 1200 m high of Central Brazil (Fig. 2) ascorresponding to remnants of the SAS. These older geomorphologicalsurfaces at higher altitudes are enriched with metals of 3+ or highervalences (Ti, Cr, La, V) due to the presence of resistant materials or theincorporation of these metals into secondary minerals such asgoethite, hematite, gibbsite and kaolinite (Marques et al, 2004). Onthese surfaces, divalent elements such as Co, Ni, Cu, Pb, Mn and Znwere initially lost at a higher rate due to the intense leaching favoredby their higher position in the landscape. During weathering of the

Please cite this article as: Burak, D.L., et al., Geochemistry and spatial dBrazilian Central Plateau, Geoderma (2010), doi:10.1016/j.geoderma.20

primary minerals, the solubilized heavy metals were leached orprecipitated, together with other metals (Al, Fe, Ti and Mn) as afunction of their mobility. Due to the intenseweathering, tropical soilshave expressive mineral oxides contents, such as hematite, goethiteand gibbsite (Fontes and Weed, 1991), the residual minerals from thetropical weathering.

Several studies have shown that secondary iron and manganeseoxides are themain scavengers of tracemetals in soils (Singh andGilkes,1992; Becquer et al., 2006). Theseoxides andhydroxides are amphotericminerals (Fontes et al., 2001) that occur as discrete phases and/orassociated with other minerals as coatings (Axe and Trivedi, 2002).Because these oxides possess large surface areas (N400 m2 g−1),microporous structures and an abundance of binding sites, they havea significant impact on contaminant mobility, distribution and attenu-ation (Axe and Trivedi, 2002). The Mn oxides (for Pb and Zn) and Feoxides (for Cu and Pb) become very efficient geochemical barriers thatlimited the Pb and Cu dispersion in the studied region (Figs. 4 and 5).Especially in areas close to the dolomite outcrops where higher pHvalues are found (data not shown), due to the presence of carbonates,Mn becomes less soluble facilitating the manganese oxide formation(Kabata-Pendias and Pendias, 2005).

Heavy metal adsorption on Fe and Mn oxides has been studied byseveral researchers and in general the studies have suggested thefollowing order of adsorption of heavy metal ions on these oxides:PbNCuNMnNCoNZnNNi for the Mn oxides (McKenzie, 1989); CuNPbNZnNCoNNi for goethite (Fischer et al., 2007), PbNCuNZnNCoNNiand PbNCuNZnNNiNCo for hematite and amorphous Fe, respectively(Ross, 1994). For soils, specially the highlyweathered ones, the order hasbeen, generally, CrNPbNCuNCdNZnNNi (Matos et al., 1996; Fontes et al.,2000; Gomes et al., 2001; Fontes and Gomes, 2003). The preferentialsorption of Pb over Zn in these soils is highlighted by comparing thePb/Zn metals contents ratio between parent rock and soil of theregion. Results from Monteiro (2002), from chemical analyses ofparent rocks, i.e. the dolomites mineralized by hydrothermal fluids inthe deposits of Ambrósia and Fagundes, found Pb/Zn ratios between0.005 and 0.023. In this study, the soils near the Ambrósia andFagundes deposits, the Pb/Zn ratios varied between 0.35 and 1.5,suggesting that, although these heavy metals originate from the samesource, there is greater Pb enrichment in these soils. Some Zn wasexported out of these soils due the more efficient adsorption of Pb onMn and Fe oxides, i.e. the main geochemical barriers in these soils. Thehigh Mn contents near the Ambrósia and Fagundes deposits (Fig. 4)can explain the geochemical anomalies of Pb and Zn in soils close to theore bodies. As far as Cu is concerned, enrichment occurs in soils withhigher Fe contents, such as those formed over the Paracatu Formationwhere iron oxides act as principal geochemical barrier (Fig. 4).

Conversely, the metals with lower affinity toward Fe and Mnoxides, such as Co and Ni, were preferentially transported to theregions of sedimentary deposits, where they accumulated. Thisaccumulation was favored by adsorption in fine-grain sediments atlower altitudes of the alluvial–colluvial unconsolidated sedimentaryregion. In lower altitude as floodplain depositional environmentscharacterized by lower energy and fine-grained sedimentary particlestend to exhibit higher metal concentrations than those characterizedby higher energy and coarse grains of channel deposits (Miller, 1997).This is showed in this work by higher Co and Ni contents in the clay-loamy texture Oxisols (Naime and Motta, 1998) over unconsolidatedsediments below 550 m and the lowest concentrations of all metalsstudied in the coarse textured oxisols (Naime and Motta, 1998) above550 m in unconsolidated sediments.

In general, the relative affinity of heavy metals for the oxides isinversely related to the range (a value from Table 3) calculated fromthe semivariograms: Cu (33.3 km)bPb (38.2 km)bZn (42.6 km)bCo(79.4 km)bNi (100.4 km). This result suggest that the range can beused as an estimate of the element's mobility and dispersioncapacities, since the dispersion from a regional source decreases

istribution of heavy metals in Oxisols in a mineralized region of the10.08.007

11D.L. Burak et al. / Geoderma xxx (2010) xxx–xxx

gradually with the distance between samples until finally there is nospatial correlation. Lead and Zn as well as Ni and Co originate frompoint geological sources, the former from mineralized dolomites andthe latter from ultramafic dicks, however Pb and Zn had lower range(a) values than Ni and Co, showing a smaller mobility and dispersioncapacity for Pb an Zn in the tropical environment as compared to Niand Cowhich showed the highest range values. Themetals' dispersionpattern in the form of geochemical halos close to the source is typicalof tropical regions and flat topography (Anand and Paine, 2002).Trofimuk (1978) studying the geochemical halos resulting frommetaldispersion due to Au-rich sulfide mineralizations, also detecteddifferent types of geochemical halos, and Pb, Zn, Cu, Ag, and Mnwere the elements closest to the mineralized bodies, whereas Co, Ni,Mo, and Bi were farther away, in regions of lower altitude.

6. Conclusions

Geochemical studies of highly developed soils of the northwesternpart of Minas Gerais State, (Unaí, Paracatu, Vazante regions) in theCentral Plateau of Brazil, are described. They show the abundance ofZn and Pb in the soils over the Vazante Group, especially near thedolomite massif influenced by Zn–Pb mineralization events of theAmbrósia and Fagundes ore bodies. High concentrations of Cu werefound in soils on the Paracatu Formation, formed by carbonaceousphyllites, as well as of Ni and Co in soils at lower altitudes in the regionformed by unconsolidated sedimentary deposits.

Despite the dispersive effect of the climatic conditions of the tropicalenvironments, Pb and Zn were less dispersed, depending on thegeomorphology and drainage network. This is due to the higher affinityof thesemetals to the oxides, especially Fe andMn oxides that aremainlyfound in the Zn and Pb neighborhood-sources and in tropical conditions.Copperpresents lowdispersion, following the samegeochemical behavioras Pb andZn, and the lower transport fromhigher to lower altitudes is dueto the higher association with Fe oxides, also present in soils on theParacatu Formation. Conversely, the low Ni and Co affinity for the Fe andMn oxides and the geomorphology of the region promoted their migra-tion along the drainage network from their points of origin in the regionswithin the VazanteGroup to the regions of sediment accumulation.

The range (a value) obtained from the semivariograms seemed tobe a very good estimate of the heavy metal´s mobility and dispersioncapacity. Although Pb, Zn, Ni and Co originate from point sources, Pband Zn have a smaller range as compared to Ni and Co, showing amuch smaller mobility and dispersion capacity.

The concentrations of heavy metals studied, except Co, exceededthe Prevention Values tabulated by the Brazilian State Agency asguidance values to identify maximum acceptable values of heavymetals contamination for Brazilian soils. The highest concentrations ofPb and Zn exceeded the Intervention Values.

Acknowledgments

This work was supported by the CNPq (Conselho Nacional deDesenvolvimento Científico e Tecnológico, Brazil), Project No 475623/2003-7 and by Productivity Research Fellowships to the 2nd, 4th and5th authors; and by CAPES-COFECUB (Brazilian–French CooperationProgram) under Project Number 514-05. This research is also part ofthe project EMBRAPA Cerrados/IRD no 0203205 (Mapping of theBiome Cerrado Landscape and Functioning of Representative Soils).

References

Almeida, F. F. M., 1967. Origem e evolução da plataforma brasileira. Boletim DNPM.(In Portuguese).

Anand, R.R., Paine, M., 2002. Regolith geology of the Yilgarn Craton, Western Australia:implications for exploration. Australian Journal of Earth Science 49, 3–162.

Please cite this article as: Burak, D.L., et al., Geochemistry and spatial diBrazilian Central Plateau, Geoderma (2010), doi:10.1016/j.geoderma.20

Axe, L., Trivedi, P., 2002. Intraparticle surface diffusion of metal contaminants and theirattenuation in microporous amorphous Al, Fe, and Mn oxides. Journal of Colloidand Interface Science 247, 259–265.

Babinski, M., Monteiro, Fetter, L.V.S.A.H., Bettencourt, J., Oliveira, T.F., 2005. Isotopegeochemistry of the mafic dykes from the Vazante nonsulfide zinc deposit, Brazil.J. South American Earth Science 18, 293–304.

Becquer, T., Quantin, C., Rottécapet, S., Ghanbaja, J., Mustin, C., Herbillon, A.J., 2006.Sources of trace metals in Ferralsols in New Caledonia. European Journal of SoilScience 57, 200–213.

Cambardella, C.A., Moorman, T.B., Novak, J.M., Parkin, T.B., Karlen, D.L., Turco, R.F.,Konopka, A.E., 1994. Field-scale variability of soils properties in central Iowa soils.Soil Science Society of America Journal 58, 1501–1511.

CETESB, 2001. Relatório de estabelecimento de Valores Orientadores para Solos e ÁguasSubterrâneas no Estado de São Paulo. CETESB. (In Portuguese).

CETESB, 2005. Decisão de diretoria nº 195–2005- Aprovação dos Valores Orientadorespara Solos e Águas Subterrâneas no Estado de São Paulo – CETESB, São Paulo, 2005.(In Portuguese).

Chen, M., Ma, L.Q., 2001. Comparison of three aqua regia digestion methods for twentyFlorida soils. Soil Science Society of America Journal 65, 491–499.

Covelo, E.F., Vega, F.A., Andrade, M.L., 2007. Simultaneous sorption and desorption ofCd, Cr, Cu, Ni, Pb and Zn in acid soils II: soil ranking and influence of soilcharacteristics. Journal of Hazardous Materials 147, 862–870.

Critto, A., Carlon, C., Marcomini, A., 2003. Characterization of contaminated soil andgroundwater surrounding an illegal landfill (S. Giuliano, Venice, Italy) by principalcomponent analysis and kriging. Environmental Pollution 122, 235–244.

Dardenne M.A., 1979. Les minéralisations de plomb, zinc, fluor du proterozoïquesupérieur dans le Brésil central. Ph. D. thesis, Université Paris VI. (In French withEnglish Summary).

Dardenne, M.A., 2000. The Brasília fold belt. In: Cordani, U.G., Thomaz Filho, A.,Campos, D.A. (Eds.), Tectonic evolution of South America. International GeologicalCongress, Rio de Janeiro, pp. 231–263.

Dardenne, M.A., Freitas-Silva, F.H., Souza, J.C.F., Campos, J.E.G., 1998. Evolução tectono-sedimentar do Grupo Vazante no contexto da Faixa de Dobramentos Brasília.Congresso brasileiro de geologia. Sociedade Brasileira de Geologia, Belo Horizonte.

Facchinelli, A., Sacchi, E.,Mallen, L., 2001.Multivariate statistical andGIS-based approachto identify heavy metal sources in soils. Environmental Pollution 114, 313–324.

Fischer, L., Brümmer, G.W., Barrow, N.J., 2007. Observations and modelling of thereactions of 10 metals with goethite: adsorption and diffusion processes.European Journal of Soil Science 58, 1304–1315.

Fontes, M.P.F., Gomes, P.C., 2003. Simultaneous competitive adsorption of heavymetals by the mineral matrix of tropical soils. Applied Geochemistry 18, 795–804.

Fontes, M.P.F., Weed, S.B., 1991. Iron oxides in selected Brazilian Oxisols: I. Mineralogy.Soil Science Society of America Journal 55, 1143–1149.

Fontes, M.P.F., Matos, A.T., Costa, L.M., Neves, J.C.L., 2000. Competitive adsorption ofzinc, copper, and lead in three highly-weathered Brazilian soils. Communications inSoil Science and Plant Analysis 31, 2939–2958.

Fontes, M.P.F., de Camargo, O.A., Sposito, G., 2001. Electrochemistry of colloidalparticles and its relationship with the mineralogy of highly weathered soils.Scientia Agricola 58, 627–646 In Portuguese, with English Summary.

Fuck, R.A., Jardim De Sá, E.F., Pimentel, M.M., Dardenne, M.A., Soares, A.C.P., 1993. Asfaixas de dobramento marginais do Craton do São Francisco. In: Dominguez, J.M.L.,Misi, A. (Eds.), O Craton do São Francisco. SBG/SGM/CNPq, Sociedade Brasileira deGeologia. In Portuguese.

Gomes, P.C., Fontes, M.P.F., Silva, A.G., Mendonça, E.S., Netto, A.R., 2001. Selectivitysequence and competitive adsorption of heavy metals by Brazilian soils. SoilScience Society of America Journal 65, 1115–1121.

Gonçalves, M.A., Vairinho, M., Oliveira, V., 1998. Study of geochemical anomalies inMombeja area using a multifractal methodology and geostatistics. In: Buccianti, A.,Nardi, G., Potenza, R. (Eds.), Proceedings of the IV IAMG'98. Part 2, pp. 590–595.

Goovaerts, P., 1997. Geostatistics for Natural Resources Evaluation. Oxford UniversityPress, New York.

Goovaerts, P., 2001. Geostatistical modelling of uncertainty in soil science. Geoderma103, 3–26.

ISO 14466, 1995. Soil quality – extraction of trace elements soluble in aqua regia.International Organization for Standardization, Geneve, Switzerland.

Kabata-Pendias, A., Pendias, H., 2005. Trace elements in soils and plants, 3rd ed. CRCPress, Boca Raton.

King, L.C., 1956. A Geomorfologia do Brasil Oriental. Revista Brasileira de Geografia 18,147–265 In Portuguese, with English Summary.

Lepsch, I.F., Buol, S.W., 1988. Oxisol–landscape relationships in Brazil. International SoilClassification Workshop, 8., Rio de Janeiro, 1986. Proceedings. Embrapa-SNLCS, Riode Janeiro, pp. 174–189.

Liu, X., Wu, J., Xu, J., 2006. Characterizing the risk assessment of heavy metals andsampling uncertainty analysis in paddy field by geostatistics and GIS. EnvironmentalPollution 141, 257–264.

Mandalosso, A., 1980. Aspectos da diagênese dos carbonatos do grupo Bambuí na regiãode Paracatu (MG). Congresso Brasileiro de Geologia. SBG, Camburiú, pp. 2069–2081.In Portuguese, with English Summary.

Marques, J.J., Schulze, D.G., Curi, N., Mertzman, S.A., 2004. Trace element geochemistryin Brazilizan Cerrado soils. Geoderma 121, 31–43.

Matos, A.T., Fontes, M.P.F., Jordão, C.P., Costa, L.M., 1996. Mobility and retention forms ofheavy metals in a Red-Yellow Latosol. Revista Brasileira de Ciência do Solo 20,379–386 In Portuguese, with English Summary.

Matos, A.T., Fontes, M.P.F., Costa, L.M., Martinez, M.A., 2001. Mobility of heavy metals asrelated to soil chemical and mineralogical characteristics of Brazilian soils.Environmental Pollution 111, 429–435.

stribution of heavy metals in Oxisols in a mineralized region of the10.08.007

12 D.L. Burak et al. / Geoderma xxx (2010) xxx–xxx

McBratney, A.B., Mendonça Santos, M., Minasmy, A., 2003. On digital soil mapping.Geoderma 117, 3–52.

Mcgrath, D., Zhang, C., Carton, O.T., 2004. Geostatistical analyses and hazard assessmenton soil lead in Silvermines area, Ireland. Environmental Pollution 127, 239–248.

McKenzie, R.M., 1989. Manganese oxides and hydroxides. In: Dixon, J.B., Weed, S.B.(Eds.), Minerals in soil environments. Soil Science Society of America, pp. 439–465.

Miller, J.R., 1997. The role of fluvial geomorphic processes in the dispersal of heavymetals from mine sites. Journal of Geochemical Exploration 58, 101–118.

Milnes, A.R., Fitzpatrick, R.W., 1989. Titanium and zirconium minerals. In: Dixon, J.B.,Weed, S.B. (Eds.), Minerals in soil environments, 2nd ed. Soil Science Society ofAmerica, Madison, pp. 1131–1205.

Misi, A., Iyer, S.S.S., Coelho, C.E.S., Tassinari, C.C.G., Franca-Rocha, W.J.S., Cunha, I.A.,Gomes, A.S.R., Oliveira, T.F., Teixeira, J.B.G., Filho, V.M.C., 2005. Sediment hostedlead–zinc deposits of the Neoproterozoic Bambuí Group and correlative sequences,São Francisco Craton, Brazil: a review and a possible metallogenetic evolutionmodel. Ore Geology Reviews 26, 263–304.

Monteiro, L.V.S., 2002. Modelamento metalogenético dos depósitos de zinco deVazante, Fagundes e Ambrósia, associados ao Grupo Vazante, Minas Gerais. Ph D.Thesis, Universidade de São Paulo. (In Portuguese, with English Summary)

Monteiro, L.V.S., Bettencourt, J.S., Juliani, C., Oliveira, T.F., 2006. Geology, petrography,and mineral chemistry of the Vazante, Ambrósia, and Fagundes Neoproterozoiccarbonate-hosted Zn–(Pb) deposits, Minas Gerais, Brazil. Ore Geology Reviews 28,201–234.

Monteiro, L.V.S., Bettencourt, J.S., Juliani, C., Oliveira, T.F.O., 2007. Nonsulfide andsulfide-rich zinc mineralizations in the Vazante, Ambrósia and Fagundes deposits,Minas Gerais, Brazil: mass balance and stable isotope characteristics of thehydrothermal alterations. Gondwana Research 11, 362–381.

Muggler, C.C., Buurman, P., 2000. Erosion, sedimentation and pedogenesis inpolygenetic Oxisol sequences from Minas Gerais, Brazil. Catena 41, 3–17.

Naime, U.J., Motta, P.E.F., 1998. Levantamento de reconhecimento demédia intensidadedos solos e avaliação da aptidão agrícola das terras da Região Geoeconômica deBrasília – Minas Gerais. EPAMIG/EMBRAPA, 1998. 213 p. (In Portuguese).

Perel'man, A.I., 1986. Geochemical barriers: theory and practical applications. AppliedGeochemistry 1, 669–680.

Pimentel, M.M., Dardenne, M.A., Fuck, R.A., Viana, M.G., Junges, S.L., Fischel, D.P., Seer, H.J.,Dantas, E.L., 2001. Nd isotopes and the provenance of detrital sediments of theNeoproterozoic Brasılia Belt, central Brazil. Journal of South America Earth Science 14,571–585.

Please cite this article as: Burak, D.L., et al., Geochemistry and spatial dBrazilian Central Plateau, Geoderma (2010), doi:10.1016/j.geoderma.20

Reimann, C., De Caritat, P., 2005. Distinguishing between natural and anthropogenicsources for elements in the environment: regional geochemical surveys versusenrichment factors. Science of the Total Environment 337, 91–107.

Ross, S.M., 1994. Toxic metals in soil–plant systems. John Willey & Sons, West Sussex.SAS Institute. SAS – Statistical Analysis System. SAS Institute, Inc. v. 4.10 for Windows.

1998. USA.Serrano, S., O'Day, P.A., Vlassopoulos, D., Garcia-Gonzalez, M.T., Garrido, F.A., 2009.

Surface complexation and ion exchange model of Pb and Cd competitive sorptionon natural soils. Geochemica et Cosmochemica Acta 73, 543–558.

Singh, B., Gilkes, R.J., 1992. Properties and distribution of iron oxides and theirassociation with minor elements in the soils of south-western Australia. Journal ofSoil Science 43, 77–98.

Sipos, P., Németh, T., Kis, V., Mohai, I., 2008. Sorption of copper, zinc and lead on soilmineral phases. Geoderma 73, 461–469.

Starostin, V.I., Yapaskurt, O.V., 2007. Aspects of genetic formational typification ofmetalliferous highly carbonaceous sedimentary complexes. Moscow UniversityGeological Bulletin 62, 131–142.

Thomas, M.F., 1994. Geomorphology in the tropics: a study of weathering anddenudation in low latitudes. John Wiley & Sons, New York.

Trofimuk, N.N., 1978. Halos of wide disseminated elements in the presence ofpolimetallic bodies. Okhrana Nedr 4, 25–29.

Ure, A.M., Berrow, M.L., 1982. The elemental constituents of soils. In: Bowen, H.J.M. (Ed.),Environmental chemistry. Royal Society of Chemistry, London, pp. 94–204.

Vasconcelos, P.M., Renne, P.R., Brimhall, G.H., Becker, T.A., 1994. Direct dating ofweathering phenomena by 40Ar/39Ar and K–Ar analysis of supergene K–Mnoxides. Geochimica et Cosmochimica Acta 58, 1635–1665.

Viviani, C., Almeida, D.R., Romagna, G., Lopes, J.A., De Souza, J.C.F., De Oliveira, T.F.,Bessa, V., 2001. The Vazante and Morro Agudo Zn–Pb mines, MG, Brazil. In: Misi, A.,Teixeira, J.B. (Eds.), Proterozoic Base Metal of Africa and South America. CNPq andUNESCO/IUGS, Belo Horizonte, pp. 115–132.

Webster, R., Oliver, M.A., 2007. Geostatistics for Environmental Scientists, SecondEdition. John Wiley & Sons, West Sussex, England.

Wedepohl, K.H., 1978. Handbook of Geochemistry, vol. II-2. Springer-Verlag,Heidelberg.

Zini, A., Forlim, R., Andreazza, P., Souza, A., 1988. Depósito doMorro doOuro Paracatu,MG.In: Schobbenhaus, C., Coelho, C.E.S. (Eds.), Principais depósitos minerais do Brasil:Metais básicos não ferrosos, ouro e alumínio. DNPM, v.3, Brasília, pp. 479–489. InPortuguese.

istribution of heavy metals in Oxisols in a mineralized region of the10.08.007