Research Article Assessment of Copper and Zinc in Soils of a...

Hindawi Publishing CorporationApplied and Environmental Soil ScienceVolume 2013 Article ID 790795 10 pageshttpdxdoiorg1011552013790795

Research ArticleAssessment of Copper and Zinc in Soils of a VineyardRegion in the State of Satildeo Paulo Brazil

Glaacuteucia Ceciacutelia Gabrielli dos Santos1 Gustavo Souza Valladares2 Cleide Aparecida Abreu1

Otaacutevio Antocircnio de Camargo1 and Ceacutelia Regina Grego3

1 Instituto Agronomico de Campinas Avenida Barao de Itapura 1481 13012-970 Campinas SP Brazil2 UFCCCA Departament de Ciencias do Solo Campus do Pici Bloco 807 12168 60021-970 Fortaleza CE Brazil3 Embrapa Monitoramento por Satelite Avenida Soldado Passarinho 303 Fazenda Chapadao 13070-115 Campinas SP Brazil

Correspondence should be addressed to Cleide Aparecida Abreu cleideiacspgovbr

Received 7 March 2013 Revised 16 July 2013 Accepted 20 August 2013

Academic Editor Marıa Cruz Dıaz Alvarez

Copyright copy 2013 Glaucia Cecılia Gabrielli dos Santos et alThis is an open access article distributed under the Creative CommonsAttribution License which permits unrestricted use distribution and reproduction in any medium provided the original work isproperly cited

This soil acidification may increase the bioavailability of copper (Cu) and zinc (Zn) in soilsThe objective of this study was to verifythe concentrations of Cu and Zn in soils of a vineyard region including sample acidification to simulate acid rain The study wasdeveloped in an area of vineyard cultivation with an adjacent land having other crops grown in the state of Sao Paulo BrazilSoil samples were collected and GPS located under different uses and coverings The extracted solutions used to determine theavailable Cu and Zn forms were diethylenetriaminepentaacetic acid (DTPA) pH 73 and calcium chloride 001M The total formswere obtained by HNO

3digestion The amounts of Cu and Zn extracted using DTPA were considered high in most of the samples

and were greater in the areas cultivated with vineyards that had received fungicide applications for several decadesThe total formswere higher in vineyard soils The amounts of Cu and Zn extracted using CaCl

2did not have good correlation with vineyards or

with other metalsrsquo formsThe results confirmed that the soil was enriched with Cu and Zn due to the management of the vineyardswith chemicals for several decades

1 Introduction

Soil conservation is fundamental for the sustainable develop-ment and preservation of ecosystems and biodiversity Thesoil is exposed to contamination through several anthropicactivities mainly agriculture The contamination of soil byheavy metals results in a high risk of its productive capacityand of the balance of the ecosystems [1]

Soil has a diverse heavy-metal concentration that is depe-ndent on the parent material from which it is formed theformation processes and the composition and proportion ofthe components of the solid phase [2] This concentrationmay be affected by several anthropic activities includingirrigation fertilizer and chemical applications and industrialor urban sewage incorporation [3 4] Moreover the concen-tration distribution and bioavailability of heavy metals inthe environment are influenced by the soil type topographygeology and erosive processes [5]

Cultivation may cause soil contamination by heavy met-als specifically copper in vineyard areas [1 6 7]The intensiveuse of agrochemicals with Cu and Zn in their compositionmay pollute the soil [8ndash10] Historical and current applica-tions have resulted in Cu accumulation in the soil and totalCu quantities have been measured in vineyards worldwideHigh concentrations of fungicide-derived copper in orchardand vineyard soils have been reported from around theworld for example Brazil 36ndash3215mg kgminus1 [11] Cham-pagneFrance 100ndash1500mg kgminus1 [12] India 29ndash131mg kgminus1[13] and Australia 1ndash223mg kgminus1 [14] It has been suggestedthat areas with greater humidity and precipitation such asBrazil or Champagne France exhibit higher Cu concentra-tions than dry environments due to higher Cu use [10]

The acidification of soil and surface water is a seriousconcern in society today [15ndash17] The acid rain and resultingsoil acidification are a real problem in Sao Paulo state due to

2 Applied and Environmental Soil Science

Table 1 Descriptive statistics of soil attributes in the vineyard and other uses in the region studied

Variable Unit Vineyard Other usesMinimum Maximum Average STD Minimum Maximum Average STD

Organic matter g Lminus1 170 550 344 109 130 820 330 142CEC cmolc Lminus1 607 312 122 649 455 151 805 264Base saturation 370 950 675 168 100 930 429 210Clay g kgminus1 150 313 223 418 125 450 254 669Silt g kgminus1 750 226 142 387 740 243 154 417Sand g kgminus1 562 729 635 419 346 788 591 829CuT mg kgminus1 100 405 207 841 465 803 134 117ZnT mg kgminus1 143 243 534 430 648 225 457 402pH CaCl2 420 650 516 062 370 640 470 063pH CaCl2 after acidified 363 697 496 092 333 660 431 070CuDTPA mg kgminus1 280 155 679 327 130 154 269 218CuDTPA after acidified mg kgminus1 259 221 911 489 126 200 347 282ZnDTPA mg kgminus1 480 250 118 563 140 248 539 475ZnDTPA after acidified mg kgminus1 502 299 137 647 097 280 564 537CuCaCl mg kgminus1 001 012 008 003 001 061 006 010CuCaCl after acidified mg kgminus1 003 008 005 001 002 123 007 019ZnCaCl mg kgminus1 001 258 073 073 001 897 117 167ZnCaCl after acidified mg kgminus1 001 311 137 111 003 454 109 105STD standard deviation

the intense industrialization [18] and the soils in the regionstudied here are considered themost sensitive to acidificationin Brazil [19]

Statistical and geostatistical techniques can assist in theinterpretation of research in soil pollution by heavy metals[1 20 21]

The objective of this study was to verify the concentra-tions of Cu and Zn in the soils of a vineyard region inclu-ding the acidification of the samples with the objective ofsimulating acid rain

2 Materials and Methods

The study was performed in a 598 ha catchment area inJundiaı Sao Paulo state Brazil (23∘111015840 S 46∘531015840 W) whichis occupied by 29 ha vineyard (Figure 1) that is ten to sixtyyears old has natural vegetation pastures and other typesof orchards in the vicinity and is 672ndash755m altitude Thelandscape is rolling and hilly in a geomorphological provincethat is dominated by a ldquohalf-orangerdquo type of relief The soiltypes in the area are inceptisols ultisols and oxisols [22] andthe main original rock is the schist The descriptive statisticsof soil attributes are presented in Table 1

The spatial datawere uniformmade andwereGPS locatedbased on satellite images with high-spatial resolution Aninterpretation of land use and cover was made with detailedfield checking based on an IKONOS II mosaic (orbital point159539 on July 4 2001 at 1319 PM and on November 082001 at 1324 PM) The land useland cover map and thetopographic data were utilized to plan the soil samplingultimately establishing a total of one hundred sample pointsThese points were georeferenced and integrated in a vectorialformat in the geographic information system (GIS)

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VineyardsNatural vegetation

Figure 1 Area of study in a vineyard region of Sao Paulo state Brazil

At this stage the area was traversed With the help of anauger 67 georeferenced perturbed soil samples at 0ndash015mdepth were collected including 37 from the vineyard and 30from the land under other crops grownThe samples were airdried crushed and passed through a 2mm sieve

The 67 soil samples (100 g each) after being driedand sieved were assembled in glass percolation columnsand treated with 20mL of HNO

301mol Lminus1 and 100mL of

Applied and Environmental Soil Science 3

deionized water to eliminate the H+ excess and alter theirpH as described by Camargo and Raij [23]The samples wereincubated for 15 days for a complete acidification reactionand were then dried sieved and chemically analyzed forthe bioavailability of Cu and Zn The CuT and ZnT conce-ntrations were determined using HNO

3according to the

procedure described in the US EPA 3051 method [24] theavailable formwas determined using DTPA pH 73 (CuDTPAand ZnDTPA) [25] and CaCl

2001mol Lminus1 (CuCaCl and

ZnCaCl) [6 26] extractions The Cu and Zn levels in thedigestion extracts were determined by ICP-OES

A descriptive statistical analysis was used for calculationThe discriminate analysis (DA) is a method of dependenceanalysis and is a special case of canonical correlation Inthis study the DA was first used to reveal whether the landuse patterns differed significantly in terms of Cu and Znconcentrations To analyze the spatial variability the geosta-tistical analysis [27 28] was used through the elaborationand adjustment of semivariograms and data interpolation bykriging for mapping

3 Results and Discussion

31 General Soil Characteristics The physicochemical char-acteristics and element contents are summarized in Table 1The selected soils were naturally acidic to slightly acidic(1MCaCl

2pH range 37ndash65) with an average value of 51

with textures that varied from loam (common in soilsdeveloped from schist or slate) to sandy loam (typical forgranite soils) The soil samples taken in this region had largesand contents (346ndash788 g kgminus1) and the loam or sandy loamtextures that are typical of soils were developed over granites

Cation exchange capacities (CEC) ranged from 607 to312 cmolcL

minus1 (Table 1)The highest values of CECwere foundin vineyard soil

Soil organic matter contents were generally high butvaried widely ranging from 13 to 82 g Lminus1 (Table 1) The soilorganic matter content is useful to give an idea of the textureof the soil with values up to 15 g Lminus1 for sandy soils between16 and 30 g Lminus1 for medium texture and 31ndash60 g Lminus1 for claysoils Values above 60 g Lminus1 indicate the accumulation oforganic matter in the soil generally by poor drainage or highacidity The highest values of organic matter were found inforest soils (82 g Lminus1) and vineyard soils (55 g Lminus1)

32 Total Cu and Zn Concentrations The total Cu contentin the vineyard and in soil under other uses in the regionvaried between 10 and 405mg kgminus1 and between 47 and803mg kgminus1 respectively (Table 1)

The total Cu values are generally higher than or similar tothose reported by Kabata-Pendias and Pendias [29] for natu-ral soils whose typical values ranged from 13 to 24mg kgminus1depending on the soil type On the other hand the total Cuvalues are generally lower than or similar to those reportedby Brun et al [26] in Southern France (30 to 250mg kgminus1)and by Fernandez-Calvino et al [7] in the Northwest IberianPeninsula (25 to 666mg kgminus1) The differences could reflect

different application rates as well as different physical andchemical parameters in the soils but we do not have enoughinformation to discern diverse possibilities

The total Zn content in the vineyard and in soil underother uses in the region varied between 143 and 243mg kgminus1and between 648 and 225mg kgminus1 respectively (Table 1)Thetotal Zn values are generally higher than or similar to thosereported by Alloway [30] for natural soils whose typicalvalues ranged from 10 to 300mg kgminus1 depending on the soiltype Only 25 of samples exceeded the average Zn concen-trations reported by Alloway [30] for soils (50mg kgminus1) Thetotal Zn values are generally higher than or similar to thosereported by Fernandez-Calvino et al [31] in vineyard soils (60to 149mg kgminus1)

The total concentrations of Cu and Zn in the area com-pared to the soil reference values (mg kgminus1) from SaoPaulo state range from 35 to 60mg kgminus1 and from 60 to300mg kgminus1 [32] respectively It was observed that only threetopsoil samples (3) had a concentration higher than thereference value for Cu and that only one sample presented aconcentration higher than the prevention values The highertotal Cu concentrations were observed in soils under vine-yard palm and Typha The area with palm had previouslybeen cultivated with vineyards for decades and the soilunder Typha vegetation represents a wetland that is in alower altitude position of the study area which most likelyreceived contaminated sediments from the higher parts ofthe landscape These results clearly demonstrate the riskof contaminating the adjacent areas and the power of Cupermanency in the soil

Because many vineyards are located on steep slopesintensive erosion furtherly influences Cu mobility in thesesoils and thus increases the risks associated with groundwatercontamination

The effect of landscape on copper levels in soils is unclearSediments in Galicia (Spain) river valley were found to havehigher copper levels than nearby vineyard soils [33] Rusjanet al [34] found that amongst plains plateaus and terracescopper levels were highest on terraces

The copper content in vineyard soils is attributed to fac-tors such as frequency of pesticide application and local cli-matic conditions Studies from France and Italy demonstratethat vineyard soils in wet regions contain more copper thanin dry regions [26 35] Deluisa et al [35] attributed this effectto differences in soil type and precipitation the latter encour-aging greater use of copper However Pietrzak and McPhail[36] did not see a difference in copper application betweenhumid regions and drier regions The vineyards situatedin the region where humid climate dominates (Gippslandregion) generally do not receive greater annual applicationof copper-based fungicides than vineyards located in sub-humid conditions (Rutherhglan region) The local factors ofeach vineyard (eg slope exposure amount of sun receivedsurrounded vegetation and wind breakers) play importantroles in controlling any outbreaks of diseases and at the sametime influence the use of fungicides Other authors havesuggested that erosion leaching and plowing are the maindeterminants [37]


For the Zn total concentration 14 topsoil samples (21)presented concentrations higher than the reference valuesin both vineyard and soil used to grow pears These resultsindicate that agricultural management contributed to soilcontamination with Cu and Zn

33 Available Cu and Zn Concentrations and Soil AttributesAlthough the total Cu and Zn soil concentrations are afair indication of availability including deficiency or over-supply they do not provide conclusive information aboutthe environmental impact of this availability The Cu andZn availability to the biota when used as nutrients ortoxic elements and their mobility are important factors toconsider when investigating the effect of these metals on theenvironment In this context the available concentrations ofCu and Zn seem to be the best indicator to make inferencesabout the potential environment impacts of these elements

The concentrations of Cu and Zn extracted using DTPAmay provide information about the elementsrsquo availabilityfor plant nutrition [38] and their potential to pollute thesoil [39] The Cu concentration in topsoil varied from13 to 155mg kgminus1 with a mean of 43mg kgminus1 (CuD-TPA) and from 001 to 061mg kgminus1 with a mean of006mg kgminus1 (CuCaCl) (Table 1) The highest concentrationsof Cu extracted using DTPA occurred in soils under thesame use as that used to obtain the total Cu Howeverfor Cu extraction with CaCl

2 the highest Cu concentration

which occurred in soils under experimental vineyards differsfrom the highest total and DTPA Cu concentrations whichoccurred in experimental and commercial vineyards

The Zn concentration in topsoil varied from 14 to250mg kgminus1 with a mean of 81mg kgminus1 (ZnDTPA) andfrom 001 to 897mg kgminus1 with a mean of 10mg kgminus1(ZnCaCl) (Table 1) The higher concentration of available Znoccurred in soils under vineyards and natural vegetationindicating that the high available Zn concentration may beexplained by anthropogenic pollution Despite the applica-tion of agrochemicals the same finding was observed for thetotal Zn that is the natural concentration of the element onceit also occurs in some natural vegetation land uses (Table 1)

According to Studentrsquos 119905-test (119875 lt 005) topsoils invineyards had higher concentrations of the total formofCu aswell as that extracted by DTPA and CaCl

2than did the other

land uses The same result was observed for Zn extractedby DTPA but not for Zn extracted by CaCl

2or for its total

form These results show a reasonable soil contamination invineyard areas by Cu and a probable elevation in the availableZn concentration

The average concentrations of available forms of Cu andZn in vineyard soils tend to be higher than the concentrationsobserved in soils under other uses with exception of CaCl

2-

extractableCu andZnwhere the highermean concentrations(123 and 454mg kgminus1) were observed in soils under naturalvegetation (Table 1)

Generally the vineyard soils have higher pH and CECthan what is observed in soils under other uses High CECencourages metals to bind with soil aggregates depending onthe organic matter and the clay content of the soil High pH

enhances the dissociation of organic acids and therefore theformation of complexeswithmetals alteringmetal speciationand reducing bioavailability [40]

34 Available Forms of Cu and Zn after Acidification Consid-ering all of the surface samples acidified (Table 1) there is aslight increase in Cu content in the soil which ranged from126 to 221mg kgminus1 with a mean of 57mg kgminus1 (CuDTPA)and from 002 to 123mg kgminus1 with a mean of 006mg kgminus1(CuCaCl) As observed in the natural nonacid samplesthe maximum values of Cu were found in areas that wereoccupied by vineyards and Typha

The soil acidification revealed higher concentrations ofDTPA-extractable Cu and Zn which were not observed forCaCl2-extractable Cu and Zn These results indicate that the

DTPA method was more sensitive to soil acidification forsimulating acid rain than was CaCl

2 These results disagree

with those obtained by Brun et al [26] that indicated theCaCl2extractant as the best for the available forms of Cu

in vineyard soils Such disagreement is probably due todifferences between the original pHs of these soil regions

The statistical method used to compare the Cu and Znconcentrations extracted both with and without acidificationwas linear regression (119884 = 1198870 + 1198871119883) as suggested by J CMiller and J N Miller [41] The null hypotheses were thatthe declivity (b1) would not be different from one (1) and thatthe intercept (b0) would not be different from zero (0)Thesehypotheses were tested by calculating the confidence limits at95 for both coefficients The results were also submitted toan analysis of variance (F-test) and to correlation

According to the regression analyses of Cu and Znextracted by DTPA the intercept is equal to zero (0) andthe angular coefficient is higher than the unit (1) Theseresults indicate that the acidification promoted more metalextraction (Table 2)Then the soil acidification increased theavailability of Cu and Zn thus increasing the risk of environ-mental contamination Moreover in Jundiai an undulatedrelief is predominant [22 42] and the soil erosion potentialis high which is reflected by the slope and in some cases thetexture gradient of the ultisols In this landscape erosionmaythus transport sediments that have been contaminated withCu to the lower regions thus increasing the environmentalimpact of Cu contamination Excessive amounts of hydrogenions introduced into the soil by acid rain or fertilization canrelease Cu through cation exchange The metal mobilized inthe soil can thus eventually enter aquatic systems throughrainwater or can enter groundwater rivers and lakes Riversdraining cultivated areas with high soil Cu concentrationscan also have high Cu concentrations [43] In the case ofvineyard soils which are the most easily eroded cultivatedsoils [44] applied Cu can reach water bodies not only inwater-soluble forms but also due to erosion in colloid-bound forms that can accumulate below the water bodyin sediments In vine growing areas evaluating the riskof water quality that is posed by the use of copper-basedfungicides therefore requires determining the Cu levels andthe distribution of Cu among its more and less bioavailableforms in both vineyard soils and the sediments of local waterbodies


Table 2 Regression coefficients for the available forms of Cu and Zn extracted by DTPA and CaCl2 natural (independent variable) andacidified (dependent variable) samples

Elementmethod 1199032

Intercept119875

Angular coefficient119875

Min Average Max Min Average MaxCuDTPA 095 minus061 minus018 024 039 129 137 144 lt001ZnDTPA 094 minus088 minus017 053 062 106 113 120 lt001CuCaCl 015 0028 0033 0038 lt001 0053 0126 0200 lt001ZnCaCl 059 0401 0611 0820 lt001 0480 0605 0730 lt001

Table 3 Correlation coefficients between forms of Cu and Zn and other soil attributes

CuT ZnT CuDTPAacidified

ZnDTPAacidified

CuCaClacidified ZnCaCl acidified

Organicmatter 049lowast 015 027 057lowast 012 minus028

pH 037lowast minus009 033 minus025 minus001 minus087lowast

CEC 052lowast 008 022 minus001 010 minus060lowast

Basessaturation 045lowast minus005 035 minus006 000 minus088lowast

CuDTPA 072lowast 052lowast 097lowast 044lowast 014 minus018ZnDTPA 049lowast 063lowast 047lowast 094lowast 006 025CuCaCl 000 minus001 minus049lowast 012 020 025ZnCaCl minus016 022 minus025 037 011 088lowast

CuT 100 054lowast 070lowast 044lowast 020 minus029ZnT 100 047lowast 063lowast minus001 021CuDTPAacidified 100 033 011 minus027

ZnDTPAacidified 100 006 023

CuCaClacidified 100 minus002

Clay 045lowast minus017 minus024 minus018Silt minus030 001 026 020Sand minus017 016 minus001 minus001lowast119875 lt 005

The regression analyses of Cu and Zn extracted byCaCl2show that the intercepts are higher than zero (0) and

that the angular coefficients are lower than one (1) Theseresults indicate a dual behavior in the samples Converselyin samples with low metal concentrations the acidificationincreases the concentration of the metals and in sampleswith high concentrations the acidification promoted lessextraction

The Cu concentration extracted by CaCl2was compared

to soils under either vineyard or other land uses usingStudentrsquos 119905-test For both acidified and nonacidified soils theCuCaCl

2concentration was higher in vineyard soils though

the difference was greater among the nonacidified soils witha mean of 0076mg kgminus1 in vineyard soils and a mean of0041mg kgminus1 in soil under other uses For the acidified soilsthe mean in vineyard soils was 0046mg kgminus1 and it was0037mg kgminus1 for soil under other uses the results weresignificant at the 005 level For Zn extracted by CaCl

2 the

results showed no difference between soils under vineyard

or other uses These results indicate that the CaCl2method

could not efficiently show Zn contamination by agriculturalmanagement the higher concentrations of Zn extracted byCaCl2occurred in soils under natural vegetation which differ

from the Zn concentrations determined by total Zn and Znextracted by DTPA

35 Relationship between Cu and Zn and Soil AttributesTable 3 presents the correlation coefficients obtained betweenthe Cu and Zn total and acidified forms and for the other soilproperties in 27 samples of vineyard topsoilThe total Cu wascorrelated with soil organic matter (119903 = 049) pH (119903 = 037)cation exchange capacity (CEC) (119903 = 052) base saturation(119903 = 045) CuDTPA (119903 = 072) ZnDTPA (119903 = 049) andtotal Zn (119903 = 054) whereas total Zn was correlated only withCuDTPA (119903 = 052) and ZnDTPA (119903 = 063)

Brun et al [26] comparing various soil extractors obse-rved that Cu extracted by 001mol Lminus1 CaCl

2was correlated

well with the soil pH (ie it was decreased with increasing


Table 4 Confusion matrix of land use classifications based on discriminant analysis

Land use To natural vegetation To nonvineyard To vineyard Sum

From natural vegetation 3 2 0 560 40 000 100

From nonvineyard 0 32 2 340 94 6 100

From vineyard 0 2 25 27000 7 93 100

Sum 3 36 27 66

soil pH) which is an important property controlling thebioavailability of Cu However Cu extracted by DTPA at pH73 was correlated only with the CEC

High positive correlation between CuDTPA andZnDTPA content pH organic matter and base saturationwas found in the same area by Valladares et al [45] (ie theCu content increases with increasing pH organic matter andbase saturation)

Copper in soils is strongly immobilized by the composi-tion of the soil sorption complex [10 46] (ie organic matterFe-Mn-oxyhydroxides and nature of the humic substances)Soluble humic and fulvic acidsmay increase the solubility andmobility of the elements once in a neutral to alkaline reactionenvironment they form stable complexes with the carboxylhydroxyl and amino groups of these compounds [46 47]

The acidified forms of Cu andZn extracted byDTPAwerehighly correlated with total Cu and Zn whereas Zn DTPAshowed a higher correlation with soil organic matter than didCu These results differ from those observed in the literature[46 47] which correlates Cu with soil organic matter Theacidified Cu DTPA was correlated with clay content

Unlike the Cu and Zn forms extracted by DTPA thebehaviors of the acidified forms of Cu and Zn that wereextracted by CaCl

2were very different The acidified Cu

extracted by CaCl2was not correlated with other soil

attributes this result should reflect the Cu forms that werereleased by the weathering of shale because the soils arepoorly developed in the vineyards (inceptisols) No cor-relation between acidified and nonacidified Cu extractedby CaCl

2was observed The acidified and nonacidified Zn

extracted by CaCl2had good intercorrelation and were high-

negatively correlated with pH CEC and base saturationIn order to determine whether the three different land

uses native vegetation vineyard and other agricultureactivities differed significantly in terms of Cu and Zn soilconcentrations before and after acidification discriminateanalysiswas used In thisway the three landuseswere enteredin the calculations as the grouping variables and the soil Cuand Zn concentration forms were entered as the independentvariables

Thediscriminate analysis results are displayed in Figure 2which present the groups of land uses formed according tothe Cu and Zn concentrations in soil The obtained resultsindicate that the three land uses had different levels ofCu and Zn concentrations in the top layer of soil bothbefore and after acidification For each extracted elementconcentration a high degree of between-groups variation

0

2

4

6

8

0 2 4 6 8

F2 (1

5 9

5)

F1 (84 05)

Natural vegetationNonvineyardVineyard

minus8

minus6

minus4

minus2

minus8 minus6 minus4 minus2

Figure 2 Factors of discriminant analysis showing land use groupsformed according to Cu and Zn concentrations in soil

Table 5 Factor loadings generated by discriminant analysis

Variable 1198651

1198652

CuDTPA 0798 minus0206ZnDTPA 0510 minus0642CuCaCl 0427 minus0242ZnCaCl minus0301 minus0853CuT 0661 minus0087ZnT 0124 0172CuDTPA acidified 0768 minus0209ZnDTPA acidified 0559 minus0586CuCaCl2 acidified 0369 minus0083ZnCaCl2 acidified 0057 minus0621

exists with canonical correlation values varying between063 and 088 The Wilksrsquo lambda statistics indicate that thedifference among the land uses is significant at 119875 = 005The statistically significant results also show a very highpercentage of correct classification ranging from 60 to 94(Table 4) The analysis of Mahalanobis distances indicates a


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Cu (mg kgminus1)1ndash33ndash6

6ndash1010ndash16

b

(a)

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6ndash1010ndash25

b

(b)

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Zn (mg kgminus1)1ndash44ndash8

8ndash1212ndash25

b

(c)

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8ndash1212ndash30

b

(d)

b

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15ndash2020ndash40

(e)

b

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40ndash6060ndash2434

(f)

Figure 3 Continued


b

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(g)Figure 3 Spatial distributions of the Cu and Zn extracted by DTPA and CaCl

2in natural and acidified samples and the total content of Cu

and Zn in natural soil samples (a) and (c) Cu and Zn extracted by DTPA in natural samples (b) and (d) Cu and Zn extracted by DTPA inacidified soil samples (e) and (f) total content of Cu and Zn in soil (g) Cu extracted by CaCl

2in natural samples

Table 6 Semivariograms parameters for spatial distributions of Cu and Zn in soils from a vineyard region of Sao Paulo state nugget effect(1198620) sill (119862) range (119860) and dependency degree (GD)

Variable 1198620

119862 119860 (m) GD () ModelCuDTPA 094 685 1258 86 SphericalCuDTPA acidified 236 1280 1256 82 SphericalZnDTPA 2200 5934 9660 63 GaussianZnDTPA acidified 2970 10740 12040 72 ExponentialCuT 5166 10218 2905 49 SphericalZnT 89000 589000 16660 85 GaussianCuCaCl 00008 00026 8540 69 SphericalCuCaCl acidified 00002 00002 mdash mdash Nugget effectZnCaCl 064 064 mdash mdash Nugget effectZnCaCl acidified 013 013 mdash mdash Nugget effect

highly significant probability of differences among the landuses varying from 00001 to 0003 though vineyard differedfrom the other land uses more significantly

Eigenvalues explained 8405 of variance in the first fac-tor (Figure 2) Factor loadings generated by the discriminateanalysis are presented in Table 5 which shows the groupsformed by the metalsrsquo forms indicating correlation amongthemThefirst groupwith high values for factor 1 is formed bythe two forms of Cu extracted by DTPA and by the total CuA second group is formed by the two forms of Zn extractedby DTPA These groups indicate the high contaminations ofCu and Zn in the vineyard soils Other forms of the metalsdid not have good correlations andmay thus describe naturalhigh concentrations of thesemetalsThese results confirm thelow correlation between the acidified and nonacidified formsof Cu and Zn extracted by CaCl

2

Discriminate analysis shows strong differences betweenthe Cu and Zn concentrations in the investigated land usesand that the behaviors of the forms are variable

36 Spatial Distribution of Cu and Zn Copper and Zincconcentrations extracted by DTPA which was obtained from67 topsoil georeferenced samples both natural and acidifiedwere analyzed to determine their spatial dependence usinggeostatistical and semivariograms analyses (Table 6) kriginginterpolation of data and map building isolines The spatialdependence of the samples was strong for Cu and moderatefor Zn according to the ratio of spatial dependence (GD)(Table 6) Spherical model for Cu had a good adjustmentwith a nugget effect near 0 (zero) For Zn the nonacidifiedsoil had the best adjustment using the Gaussian model andthe acidified soil had better adjustment in the exponentialmodel

A change occurred in the spatial behavior of the Cuand Zn concentrations extracted by DTPA in natural andacidified samples (Figures 3(a) 3(b) 3(c) and 3(d)) indi-cating that an occurrence of acid rain or an acid fertilizerreaction would increase the amount of copper available inthe areaThis effect is even more pronounced in the vineyard


soils where an increased Cu concentration (Figure 1) wasobserved

High total Cu concentration coincides with the areasunder vines (Figures 1 and 3(e))Thus a risk of contaminationmay be occurring in these areas Considering such factorsas high Cu concentrations in vineyard soils soil acidifica-tion and slope erosion effects may contaminate the lowerlands in the landscape The total Zn concentration coincideswith vineyards and natural vegetation indicating a natu-ral high concentration and contamination in the vineyard(Figure 3(f))

Analyzing spatial dependence of Cu and Zn extractedby CaCl

2 only nonacidified Cu had moderate dependence

and displayed good adjustment to the spherical model(Figure 3(g)) Acidified extraction of the Cu and Zn formsdid not show spatial dependence and had verified the ldquonuggeteffectrdquo The forms extracted by CaCl

2did not have a spatial

correlation with the DTPA and total forms and insteadshowed different behaviors These results suggest that CaCl

2

extraction was less efficient than DTPA in representing thebioavailability of Cu and Zn

4 Conclusions

The results confirmed the enrichment of the soil with Cu andZn due to the use and management of the vineyards withchemicals for several decades

Acknowledgment

Thanks to CNPq for the PHD grant to the first author

References

[1] A Facchinelli E Sacchi and L Mallen ldquoMultivariate statisticaland GIS-based approach to identify heavy metal sources insoilsrdquo Environmental Pollution vol 114 no 3 pp 313ndash324 2001

[2] L R F Alleoni R B Borba and O A Camargo ldquoMetais pesa-dos da cosmogenese aos solos brasileirosrdquo Topicos em Cienciado Solo vol 4 pp 1ndash42 2005

[3] F A Nicholson S R Smith B J Alloway C Carlton-Smithand B J Chambers ldquoAn inventory of heavy metals inputs toagricultural soils in England and Walesrdquo Science of the TotalEnvironment vol 311 no 1ndash3 pp 205ndash219 2003

[4] V Simeonov J A Stratis C Samara et al ldquoAssessment of thesurface water quality in Northern GreecerdquoWater Research vol37 no 17 pp 4119ndash4124 2003

[5] J F G P Ramalho N M B Amaral Sobrinho and A C XVelloso ldquoContaminacao da microbacia de Caetes com metaispesados pelo uso de agroquımicosrdquo Pesquisa AgropecuariaBrasileira vol 35 pp 1289ndash1303 2000

[6] G R Nachtigall R C Nogueirol L R F Alleoni and M ACambri ldquoCopper concentration of vineyard soils as a functionof pH variation and addition of poultry litterrdquoBrazilianArchivesof Biology and Technology vol 50 no 6 pp 941ndash948 2007

[7] D Fernandez-Calvino J C Novoa-Munoz M Diaz-RavinaandM Arias-Estevez ldquoCooper accumulation and fractionationin vineyard soils from temperate humid zone (NW IberianPenninsula)rdquo Geoderma vol 153 no 1-2 pp 119ndash129 2009

[8] M C Ramos and M Lopez-Acevedo ldquoZinc levels in vineyardsoils from the Alt Penedes-Anoia region (NE Spain) aftercompost applicationrdquo Advances in Environmental Research vol8 no 3-4 pp 687ndash696 2004

[9] S K Gaw A L Wilkins N D Kim G T Palmer and P Robin-son ldquoTrace element and ΣDDT concentrations in horticulturalsoils from the Tasman Waikato and Auckland regions of NewZealandrdquo Science of the Total Environment vol 355 no 1ndash3 pp31ndash47 2006

[10] M Komarek E Cadkova V Chrastny F Bordas and JBollinger ldquoContamination of vineyard soils with fungicides areview of environmental and toxicological aspectsrdquo Environ-ment International vol 36 no 1 pp 138ndash151 2010

[11] N Mirlean A Roisenberg and J O Chies ldquoMetal contami-nation of vineyard soils in wet subtropics (southern Brazil)rdquoEnvironmental Pollution vol 149 no 1 pp 10ndash17 2007

[12] E Besnard C Chenu and M Robert ldquoInfluence of organicamendments on copper distribution among particle-size anddensity fractions in Champagne vineyard soilsrdquo EnvironmentalPollution vol 112 no 3 pp 329ndash337 2001

[13] B R Prasad S Basavaiah A Subba Rao and I V Subba RaoldquoForms of copper in soils of grape orchardsrdquo Journal of theIndian Society of Soil Science vol 32 pp 318ndash322 1984

[14] A M Wightwick S A Salzman S M Reichman G Allinsonand NWMenzies ldquoInter-regional variability in environmentalavailability of fungicide derived copper in vineyard soils anAustralian case studyrdquo Journal of Agricultural and Food Chem-istry vol 58 no 1 pp 449ndash457 2010

[15] K Ito Y Uchiyama N Kurokami K Sugano and Y NakanishildquoSoil acidification and decline of trees in forests within theprecincts of shrines in Kyoto (Japan)rdquo Water Air and SoilPollution vol 214 no 1ndash4 pp 197ndash204 2011

[16] Y Zhao L Duan J Xing T Larssen C P Nielsen and JHao ldquoSoil acidification in China is controlling SO

2emissions

enoughrdquo Environmental Science and Technology vol 43 no 21pp 8021ndash8026 2009

[17] C J Stevens N B Dise and D J Gowing ldquoRegional trendsin soil acidification and exchangeable metal concentrations inrelation to acid deposition ratesrdquo Environmental Pollution vol157 no 1 pp 313ndash319 2009

[18] M C Forti A Carvalho A J Melfi and C RMontes ldquoDeposi-tion patterns of SO

4

2minus NO3

minus and H+ in the Brazilian territoryrdquoWater Air and Soil Pollution vol 130 no 1ndash4 pp 1121ndash11262001

[19] A J Melfi C R Montes A Carvalho and M C Forti ldquoUse ofpedological maps in the identification of sensitivity of soilsto acidic deposition application to Brazilian soilsrdquo Anais daAcademia Brasileira de Ciencias vol 76 no 1 pp 139ndash145 2004

[20] A Qishlaqi F Moore and G Forghani ldquoCharacterization ofmetal pollution in soils under two landuse patterns in theAngouran region NW Iran a study based on multivariate dataanalysisrdquo Journal of HazardousMaterials vol 172 no 1 pp 374ndash384 2009

[21] D Fernandez-Calvino B Garrido-Rodrıguez J E Lopez-Periago M Paradelo and M Ariaz-Estevez ldquoSpatial distribu-tion of copper fractions in a vineyard soilrdquo Land Degradation ampDevelopment 2011

[22] J Valadares I F Lepsch and A Kupper ldquoLevantamentopedologico detalhado da Estacao Experimental de Jundiaı SPrdquoBragantia vol 30 no 2 pp 337ndash386 1971

[23] O A Camargo and B V Raij ldquoMovimento do gesso emamostras de Latossolos com diferentes propriedades eletroquı-


micasrdquo Revista Brasileira de Ciencia do Solo vol 13 no 3 pp275ndash280 1989

[24] USEPA ldquoEnvironmental Protection Agency Method 3052Microwave assisted acid digestion of siliceous and organicallybasedmatricesWashington 1 CD-ROMrdquo 1996 httpwwwepagovSW-846pdfs3052pdf

[25] B V Raij J C Andrade H Cantarella and J A QuaggioAnal-ise Quımica Para Avaliacao da fertilidade de Solos TropicaisInstituto Agronomico de Campinas Campinas Brazil 2001

[26] L A Brun J Maillet J Richarte P Herrmann and J C RemyldquoRelationships between extractable copper soil properties andcopper uptake by wild plants in vineyard soilsrdquo EnvironmentalPollution vol 102 no 2-3 pp 151ndash161 1998

[27] R M Srivastava ldquoDescribing spatial variability using geostatis-tics analysisrdquo in Geostatistics for Environmental and Geotechni-cal Applications RM Srivastava S Rouhani andMVCromerEds pp 13ndash19 American Society for Testing and MaterialsWest Conshohocken Pa USA 1996

[28] S R Vieira ldquoGeoestatıstica em estudos de variabilidade espacialdo solordquo in Topicos em Ciencia do Solo R F Novais V H Alva-res Schaefer and C E G R Eds pp 1ndash54 Sociedade Brasileirade Ciencia do Solo Vicosa Brasil 2000

[29] A Kabata-Pendias and H Pendias Trace Elements in Soils andPlants CRCPress LLC Boca Raton Fla USA 3rd edition 2001

[30] B J Alloway ldquoBioavailability of elements in soilsrdquo in Essential ofMedical Geology O Selinus B J Alloway A R Centeno et alEds pp 347ndash372 Springer AmsterdamTheNetherlands 2005

[31] D Fernandez-Calvino M Pateiro-Moure J C Novoa-MunozB Garrido-Rodrıguez andMArias-Estevez ldquoZinc distributionand acid-base mobilisation in vineyard soils and sedimentsrdquoScience of the Total Environment vol 414 pp 470ndash479 2012

[32] Sao Paulo Environmental Agency ldquoReport on standard valuesfor soils and groundwater in the Sao Paulo State Cetesb Brazilrdquo2005 httpwwwcetesbspgovbrSolorelatoriostabelavalores 2005pdf

[33] D Fernandez-CalvinoM Pateiro-Moure E Lopez-PeriagoMArias-Estevez and J C Novoa-Munoz ldquoCopper distributionand acid-base mobilization in vineyard soils and sedimentsfromGalicia (NW Spain)rdquo European Journal of Soil Science vol59 no 2 pp 315ndash326 2008

[34] D Rusjan M Strlic D Pucko and Z Korosec-Koruza ldquoCop-per accumulation regarding the soil characteristics in Sub-Mediterranean vineyards of Sloveniardquo Geoderma vol 141 no1-2 pp 111ndash118 2007

[35] A Deluisa P Giandon M Aichner et al ldquoCopper pollution initalian vineyard soilsrdquoCommunications in Soil Science and PlantAnalysis vol 27 no 5ndash8 pp 1537ndash1548 1996

[36] U Pietrzak andD CMcPhail ldquoCopper accumulation distribu-tion and fractionation in vineyard soils of Victoria AustraliardquoGeoderma vol 122 no 2ndash4 pp 151ndash166 2004

[37] K A Mackie T Muller and E Kandeler ldquoRemediation ofcopper in vineyards-a mini reviewrdquo Environmental Pollutionvol 167 pp 16ndash26 2012

[38] C A Abreu A S Lopes andG C G Santos ldquoMicronutrientesrdquoin Fertilidade do Solo R F NNovais VH Alvarez N F BarrosR L F Fontes R B Cantarutti and J C L Neves Eds pp 645ndash736 Sociedade Brasileira de Ciencia do Solo Vicosa Brazil2007

[39] C A Abreu B V Raij M F Abreu and A P GonzalezldquoRoutine soil testing to monitor heavy metals and boronrdquoScientia Agricola vol 62 no 6 pp 564ndash571 2005

[40] R Maier I Pepper and C Gerba Environmental MicrobiologyAcademic Press San Diego Calif USA 2000

[41] J C Miller and J N Miller Statistics for Analytical ChemistryEllis Horwood New York NY USA 3rd edition 1993

[42] J B Oliveira M N CamargoM Rossi and B Calderano FilhoMapa Pedologico do Estado de Sao Paulo Instituto AgronomicoCampinas Brazil 1999

[43] H Xue L Sigg and R Gachter ldquoTransport of Cu Zn and Cdin a small agricultural catchmentrdquo Water Research vol 34 no9 pp 2558ndash2568 2000

[44] G Pardini and M Gispert ldquoImpact of land abandonment onwater erosion in soils of the Eastern Iberian Peninsulardquo Agro-chimica vol 50 no 1-2 pp 13ndash24 2006

[45] G S Valladares E C Azevedo O A Camargo C R GregoandM C S Rastoldo ldquoVariabilidade espacial e disponibilidadede cobre e zinco em solos de vinhedo e adjacenciasrdquo Bragantiavol 68 no 3 pp 733ndash742 2009

[46] J Wu L J West and D I Stewart ldquoEffect of humic substanceson Cu(II) solubility in kaolin-sand soilrdquo Journal of HazardousMaterials vol 94 no 3 pp 223ndash238 2002

[47] M Schnitzer and S U Khan Humic Substances in the Environ-ment Marcel Dekker New York NY USA 1972

Submit your manuscripts athttpwwwhindawicom

Forestry ResearchInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental and Public Health

Journal of



EcosystemsJournal of


MeteorologyAdvances in

EcologyInternational Journal of


Marine BiologyJournal of


Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

Advances in


Environmental Chemistry

Atmospheric SciencesInternational Journal of



Waste ManagementJournal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal of

Geophysics


Geological ResearchJournal of

EarthquakesJournal of


BiodiversityInternational Journal of


ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OceanographyInternational Journal of


The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014


ClimatologyJournal of


Table 1 Descriptive statistics of soil attributes in the vineyard and other uses in the region studied

Variable Unit Vineyard Other usesMinimum Maximum Average STD Minimum Maximum Average STD

Organic matter g Lminus1 170 550 344 109 130 820 330 142CEC cmolc Lminus1 607 312 122 649 455 151 805 264Base saturation 370 950 675 168 100 930 429 210Clay g kgminus1 150 313 223 418 125 450 254 669Silt g kgminus1 750 226 142 387 740 243 154 417Sand g kgminus1 562 729 635 419 346 788 591 829CuT mg kgminus1 100 405 207 841 465 803 134 117ZnT mg kgminus1 143 243 534 430 648 225 457 402pH CaCl2 420 650 516 062 370 640 470 063pH CaCl2 after acidified 363 697 496 092 333 660 431 070CuDTPA mg kgminus1 280 155 679 327 130 154 269 218CuDTPA after acidified mg kgminus1 259 221 911 489 126 200 347 282ZnDTPA mg kgminus1 480 250 118 563 140 248 539 475ZnDTPA after acidified mg kgminus1 502 299 137 647 097 280 564 537CuCaCl mg kgminus1 001 012 008 003 001 061 006 010CuCaCl after acidified mg kgminus1 003 008 005 001 002 123 007 019ZnCaCl mg kgminus1 001 258 073 073 001 897 117 167ZnCaCl after acidified mg kgminus1 001 311 137 111 003 454 109 105STD standard deviation

the intense industrialization [18] and the soils in the regionstudied here are considered themost sensitive to acidificationin Brazil [19]

Statistical and geostatistical techniques can assist in theinterpretation of research in soil pollution by heavy metals[1 20 21]

The objective of this study was to verify the concentra-tions of Cu and Zn in the soils of a vineyard region inclu-ding the acidification of the samples with the objective ofsimulating acid rain

2 Materials and Methods

The study was performed in a 598 ha catchment area inJundiaı Sao Paulo state Brazil (23∘111015840 S 46∘531015840 W) whichis occupied by 29 ha vineyard (Figure 1) that is ten to sixtyyears old has natural vegetation pastures and other typesof orchards in the vicinity and is 672ndash755m altitude Thelandscape is rolling and hilly in a geomorphological provincethat is dominated by a ldquohalf-orangerdquo type of relief The soiltypes in the area are inceptisols ultisols and oxisols [22] andthe main original rock is the schist The descriptive statisticsof soil attributes are presented in Table 1

The spatial datawere uniformmade andwereGPS locatedbased on satellite images with high-spatial resolution Aninterpretation of land use and cover was made with detailedfield checking based on an IKONOS II mosaic (orbital point159539 on July 4 2001 at 1319 PM and on November 082001 at 1324 PM) The land useland cover map and thetopographic data were utilized to plan the soil samplingultimately establishing a total of one hundred sample pointsThese points were georeferenced and integrated in a vectorialformat in the geographic information system (GIS)

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 3030007442

600

7442

800

7443

000

7443

200

7443

400

7443

600

7442

600

7442

800

7443

000

7443

200

7443

400

7443

600

VineyardsNatural vegetation

Figure 1 Area of study in a vineyard region of Sao Paulo state Brazil

At this stage the area was traversed With the help of anauger 67 georeferenced perturbed soil samples at 0ndash015mdepth were collected including 37 from the vineyard and 30from the land under other crops grownThe samples were airdried crushed and passed through a 2mm sieve

The 67 soil samples (100 g each) after being driedand sieved were assembled in glass percolation columnsand treated with 20mL of HNO

301mol Lminus1 and 100mL of



3according to the




























2than did the other


2or for its total



2-















Intercept119875





ZnDTPAacidified

















2 the







2was correlated







From vineyard 0 2 25 27000 7 93 100

Sum 3 36 27 66














0

2

4

6

8

0 2 4 6 8

F2 (1

5 9

5)

F1 (84 05)


minus8

minus6

minus4

minus2




Variable 1198651

1198652




301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


6ndash1010ndash16

b

(a)

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


6ndash1010ndash25

b

(b)

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


8ndash1212ndash25

b

(c)

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


8ndash1212ndash30

b

(d)

b

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


15ndash2020ndash40

(e)

b

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600



(f)

Figure 3 Continued


b

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600






2in natural samples


Variable 1198620




2












2


4 Conclusions


Acknowledgment


References

















2emissions




4

2minus NO3





































Journal of












Volume 2014

Advances in









Geophysics
















3according to the




























2than did the other


2or for its total



2-















Intercept119875





ZnDTPAacidified

















2 the







2was correlated







From vineyard 0 2 25 27000 7 93 100

Sum 3 36 27 66














0

2

4

6

8

0 2 4 6 8

F2 (1

5 9

5)

F1 (84 05)


minus8

minus6

minus4

minus2




Variable 1198651

1198652




301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


6ndash1010ndash16

b

(a)

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


6ndash1010ndash25

b

(b)

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


8ndash1212ndash25

b

(c)

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


8ndash1212ndash30

b

(d)

b

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


15ndash2020ndash40

(e)

b

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600



(f)

Figure 3 Continued


b

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600






2in natural samples


Variable 1198620




2












2


4 Conclusions


Acknowledgment


References

















2emissions




4

2minus NO3





































Journal of












Volume 2014

Advances in









Geophysics






















2than did the other


2or for its total



2-















Intercept119875





ZnDTPAacidified

















2 the







2was correlated







From vineyard 0 2 25 27000 7 93 100

Sum 3 36 27 66














0

2

4

6

8

0 2 4 6 8

F2 (1

5 9

5)

F1 (84 05)


minus8

minus6

minus4

minus2




Variable 1198651

1198652




301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


6ndash1010ndash16

b

(a)

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


6ndash1010ndash25

b

(b)

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


8ndash1212ndash25

b

(c)

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


8ndash1212ndash30

b

(d)

b

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


15ndash2020ndash40

(e)

b

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600



(f)

Figure 3 Continued


b

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600






2in natural samples


Variable 1198620




2












2


4 Conclusions


Acknowledgment


References

















2emissions




4

2minus NO3





































Journal of












Volume 2014

Advances in









Geophysics

















Intercept119875





ZnDTPAacidified

















2 the







2was correlated







From vineyard 0 2 25 27000 7 93 100

Sum 3 36 27 66














0

2

4

6

8

0 2 4 6 8

F2 (1

5 9

5)

F1 (84 05)


minus8

minus6

minus4

minus2




Variable 1198651

1198652




301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


6ndash1010ndash16

b

(a)

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


6ndash1010ndash25

b

(b)

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


8ndash1212ndash25

b

(c)

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


8ndash1212ndash30

b

(d)

b

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


15ndash2020ndash40

(e)

b

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600



(f)

Figure 3 Continued


b

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600






2in natural samples


Variable 1198620




2












2


4 Conclusions


Acknowledgment


References

















2emissions




4

2minus NO3





































Journal of












Volume 2014

Advances in









Geophysics



















From vineyard 0 2 25 27000 7 93 100

Sum 3 36 27 66














0

2

4

6

8

0 2 4 6 8

F2 (1

5 9

5)

F1 (84 05)


minus8

minus6

minus4

minus2




Variable 1198651

1198652




301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


6ndash1010ndash16

b

(a)

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


6ndash1010ndash25

b

(b)

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


8ndash1212ndash25

b

(c)

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


8ndash1212ndash30

b

(d)

b

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


15ndash2020ndash40

(e)

b

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600



(f)

Figure 3 Continued


b

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600






2in natural samples


Variable 1198620




2












2


4 Conclusions


Acknowledgment


References

















2emissions




4

2minus NO3





































Journal of












Volume 2014

Advances in









Geophysics















301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


6ndash1010ndash16

b

(a)

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


6ndash1010ndash25

b

(b)

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


8ndash1212ndash25

b

(c)

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


8ndash1212ndash30

b

(d)

b

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600


15ndash2020ndash40

(e)

b

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600



(f)

Figure 3 Continued


b

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600






2in natural samples


Variable 1198620




2












2


4 Conclusions


Acknowledgment


References

















2emissions




4

2minus NO3





































Journal of












Volume 2014

Advances in









Geophysics















b

301800 302000 302200 302400 302600 302800 303000

301800 302000 302200 302400 302600 302800 303000

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600

7442

800

7442

600

7443

000

7443

200

7443

400

7443

600






2in natural samples


Variable 1198620




2












2


4 Conclusions


Acknowledgment


References

















2emissions




4

2minus NO3





































Journal of












Volume 2014

Advances in









Geophysics






















2


4 Conclusions


Acknowledgment


References

















2emissions




4

2minus NO3





































Journal of












Volume 2014

Advances in









Geophysics












































Journal of












Volume 2014

Advances in









Geophysics














Research Article Assessment of Copper and Zinc in Soils of a...

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Transcript of Research Article Assessment of Copper and Zinc in Soils of a...