Journal of Hazardous Materials 243 (2012) 223–231

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Journal of Hazardous Materials
journal homepage: www.elsevier.com/locate/jhazmat

Modeling ﬁeld-scale vertical movement of zinc and copper in a pig
slurry-amended soil in Brazil
Fábio Joel Kochem Mallmann a,∗ , Danilo Rheinheimer dos Santos a , Carlos Alberto Ceretta a ,Cesar Cella a , Jirka Šimůnek b , Folkert van Oort caDepartamento de Solos, Universidade Federal de Santa Maria, CEP 97.105-900, Santa Maria, Rio Grande do Sul, Brazil
Department of Environmental Sciences, University of California Riverside, Riverside, CA 92521, USAc
INRA, UR 251, Pessac, RD10, F-78026 Cedex, Franceb

h i g h l i g h t s
 We performed a model validation of Zn and Cu settings in a pig-slurry amended soil.
 A two-site model with reduced kinetic constants present the best ﬁt with ﬁeld data.
 Future 50-years scenarios related to the pig slurry applications were simulated.
 Downward Zn and Cu solute ﬂuxes will not present risk to groundwater pollution.
 Continuous pig slurry amendments will lead to a high Cu accumulation on soil surface.

a r t i c l e

i n f oArticle history:
Received 11 May 2012
Received in revised form
27 September 2012
Accepted 14 October 2012
Available online 23 October 2012
Keywords:
Two-site sorption model
Solute movement
Hydrus-2D
Trace metals
Groundwater pollutiona b s t r a c t
Organic amendments often represent a source of trace metals (TMs) in soils, which may partly leachinto the groundwater. The objectives of this study were (1) to validate Hydrus-2D for modeling thetransport of Zn and Cu in an Alﬁsol amended with pig slurry (PS) by comparing numerical simulations
and experimental ﬁeld data, and (2) to model the next 50 years of TM movements under scenarios ofsuspended or continued PS amendments. First, between 2000 and 2008, we collected detailed Zn and Cu
data from a soil proﬁle in Santa Maria, Brazil. Two hypotheses about Zn and Cu reactivity with the solid
phase were tested, considering physical, hydraulic, and chemical characteristics of six soil layers. Usinga two-site sorption model with a sorption kinetic rate adjusted based on laboratory EDTA extractions,Hydrus simulations of the vertical TM transport were found to satisfactorily describe the soil Zn and
Cu concentration proﬁles. Second, the long-term fate of Zn and Cu in the soil was assessed using thevalidated parameterized model. Numerical simulations showed that Zn and Cu did not present risks
for groundwater pollution. However, future Cu accumulation in the surface soil layer would exceed theBrazilian threshold for agricultural soils.
© 2012 Elsevier B.V. All rights reserved.

1. Introduction
Soil amendment with organic waste is a common practice inagriculture worldwide. In different regions of Brazil, large-scale animal production generates large amounts of manure. These regions
are often characterized by the predominance of family farming, inwhich each farmer has only a small land area to grow crops. The fertilizing value of organic waste, such as animal manure, is generally
recognized, but its quality may vary widely. For example, pig slurry(PS) often has a relatively low nutrient content, making it uneconomical to transport over long distances. Hence, PS disposal criteria∗ Corresponding author. Tel.: +55 55 32208108; fax: +55 55 32208256.
E-mail address: fabiojkmallmann@gmail.com (F.J.K. Mallmann).
0304-3894/$ – see front matter © 2012 Elsevier B.V. All rights reserved.
http://dx.doi.org/10.1016/j.jhazmat.2012.10.022

are primarily guided by a limited space, increasing risks of soil pollution by nitrate, phosphorus, and trace metals (TMs), notably zinc(Zn) and copper (Cu).
Regulatory agencies in many countries have established environmental guidelines for soil organic waste amendments [1–4].
Basically, such guidelines restrict, or ban, applications of organic
waste to soils where the total TM content exceeds the maximal
allowed values. Brazilian laws currently allow for the maximum
TM values, which are generally higher than those adopted in
the European Union. The Companhia de Tecnologia de Saneamento Ambiental (CETESB) [3], and speciﬁcally the state of Sao
Paulo, authorizes 2800 and 1500 kg ha−1 of Zn and Cu, respectively, as maximum loads that can be applied in a particular area.
Moreover, the maximum soil TM content, when further applications of amendments to agricultural soils are prohibited, are 450

224

F.J.K. Mallmann et al. / Journal of Hazardous Materials 243 (2012) 223–231

and 200 mg kg−1 for Zn and Cu, respectively [5]. For comparison,
the European Union [1] allows the addition of 30 kg Zn ha−1 and
12 kg Cu ha−1 based on a 10-years average. The maximum allowed
soil concentrations when further amendments are restricted are
150–300 mg kg−1 for Zn and 50–140 mg kg−1 for Cu, depending
on soil pH. Brazil’s federal legislation was expanded in the 1990s,
based on the experiences of other countries. It was recognizedthat the total TM levels are not good environmental indicators formaking decisions, and that the type of soil management needs
to be taken into consideration. For example, the maximum TM
levels established by the Brazilian legislation refer to any layerof the soil proﬁle. In southern Brazil, about 50% of agriculturaloperations (almost 8.5 million hectares) are managed under notillage practices. Consequently, the organic waste applied on thesoil surface is not incorporated deeper into the soil proﬁle, thus
enhancing a rapid increase of TM concentrations in the surface
layer.
Soil water movement varies in time and space and determines
to a large extent the spatial distribution of TMs in soils. Mathematical modeling of the fate of metals in soils in terms of their retention
and transport is helpful to assess their environmental impacts [6].
Mathematical models, simulating water ﬂow and transport andreactions of TMs in soils, provide additional information on risksof the transfer of TMs to the groundwater. Such transfer mainly
depends on the amount of water moving through a particular typeof soil and on the mobility of TMs in the soil solution. On the one
hand, theoretical mathematical models require many parameters
to describe complex processes of TMs reactivity with functionalgroups of the solid phase. On the other hand, empirical models
often insufﬁciently consider physical and chemical soil characteristics or biological activity since such models merely rely on
adsorption/desorption data. However, such adsorption/desorption
processes are often inﬂuenced by various soil factors, which are
difﬁcult to measure or individually control.
The Hydrus software package [7] has been widely used to simulate the fate and transport of TMs in soils [8–12]. Hydrus includes
mathematical modules that simulate variably-saturated water ﬂow
and solute transport in porous media. Recently, Mallmann et al. [13]demonstrated the effectiveness of the Hydrus two-site sorption
sub-model [14] by simulating changes in Zn and Pb concentration proﬁles in metal contaminated soils over one century. Similar
modeling by Rheinheimer et al. [15] predicted that Zn and Pb concentrations in the soil solution will not exceed the reference water
quality values of the Council of the European Communities (CEC) [1]during the next 50 years. Additionally, Seuntjens [16] used Hydrus
to simulate two remediation scenarios for a soil contaminated withcadmium (Cd). He concluded that Cd concentrations in the soil
solution were reduced after adding an organic material and/or an
acidity corrector to the soil. He also predicted a decreasing Cd loss
from the soil. Moradi et al. [17] simulated Cd movement in a soil
amended with a sewage sludge under an arid climate. While they
noted that there is little risk of groundwater contamination byleached Cd, they observed an accumulation of TM in the soil surface
layer, and an increased risk for TM absorption by plant roots and/or
removal by surface runoff.
Here, we use Hydrus-2D to model the past and future movements of Zn and Cu in a Brazilian Alﬁsol, contaminated by repetitive
applications of PS, and compare the obtained results with a
non-amended soil. First, we simulate changes in Zn and Cu concentration proﬁles in the soil using known metal inputs via PS
amendments during 8 years. We consider two hypotheses for interactions between the soil solid phase and the soil solution, i.e., either
a complete instantaneous equilibrium or a two-site sorption modelwith both equilibrium and kinetic sorption. The model’s validity isassessed by comparing simulated and measured ﬁeld TM distributions in 2008. Second, we predict the movement of Zn and Cu, using

the adopted hypothesis, for the next 50 years under two scenariosof discontinued and continued PS applications.
2. Materials and methods
2.1. Experimental site, soil, and other characteristics
The study was conducted on experimental ﬁelds of the campus of the Federal University of Santa Maria in the state of Rio
Grande do Sul in Brazil (29◦ 42 52 S and 53◦ 42 10 W, 90 m altitude) and involved repetitive applications of PS. Soils, classiﬁed asa Typic Hapludalf [18], are well drained, and show a strong verticalclay gradient in the proﬁle. The parent material is upper Triassic
sandstone, locally referred to as the Santa Maria Formation [19].
The soil mineralogical composition includes interstratiﬁed illitesmectite, kaolinite-smectite, hydroxy-aluminum vermiculite andkaolinite clay minerals [20]. The climate is subtropical (Cfa 2, Köppen classiﬁcation), with mean annual rainfall of 1600 mm and meanannual temperature of 19 ◦ C. The experiment lasted from May 2000
to January 2008 on plots of 4 m × 3 m. The cultivated soil was underno-tillage since 1992. Four treatments were tested with PS doses
of 0, 20, 40, and 80 m3 ha−1 applied on the soil surface in each cultivation cycle. Experiments involved 19 PS applications, totaling
1520 m3 ha−1 for the plot with the highest dose, i.e., 70,000 kg of dry
organic matter, 83.4 kg of Zn and 67.1 kg of Cu per ha. The total plant
dry matter produced during the 8-year experiment was 57,870 and
147,260 kg ha−1 for the 0 and 80 m3 ha−1 plots, respectively [21].
2.2. Soil sample collection and processing
Two plots with 0 and 80 m3 ha−1 treatments were selected forthis study. In January 2008, three disturbed and three undisturbed
soil samples were collected from each of six layers of both plots
at 0–5, 5–10, 10–25, 25–35, 35–50, and 50–60-cm depths. On
disturbed samples we determined soil texture, a part of the soil
water retention curve (SWRC) corresponding to the soil moisturepressures larger than 500 kPa, pHH2 O , organic carbon content (OC),and the total concentrations and desorption curves of Zn and Cu.
On undisturbed samples, we measured the saturated soil hydraulicconductivity (Ks ), bulk density, and a part of the SWRC for the soil
water pressure smaller than 100 kPa.
2.3. Soil physical and chemical analysis
The Ks was determined using a falling head permeameter [22].
For establishing SWRC, undisturbed samples were saturated for
48 h and then successively submitted to tensions of 1, 4, 6, and
10 kPa in a sand column [23] and to 33 and 100 kPa in a pressure
cooker. Gravimetric water contents at higher tensions (500, 1000
and 1500 kPa) were determined with the dew point potentiometeron disturbed soil samples. The soil bulk density was determinedon soil cylinders and the soil texture was measured following the
USDA procedure [24].
Soil pHH2 O and OC contents were determined according toTedesco et al. [25] and EMBRAPA [26], respectively. Total Zn and Cu
concentrations were measured after total sample digestion according to Tessier et al. [27]. Desorption isotherm curves for Zn andCu were generated using Ethylene diamine tetraacetic acid (EDTA)
extractions at 0.05 mol l−1 (pH 6.0); soil-solution ratio 1:10 [28] at
5, 10, 15, 20, 25, 30, 60, 120, 240, 360, 480, 600, and 1440 min.
2.4. Water ﬂow and solute transport simulations
Hydrus-2D [7] was used to simulate one-dimensional unsaturated water ﬂow and Zn and Cu transport in a vertical
rectangular domain. The analytical models of van Genuchten and of

F.J.K. Mallmann et al. / Journal of Hazardous Materials 243 (2012) 223–231

van Genuchten–Mualem were used to describe water retention
curves and unsaturated hydraulic conductivity functions, respectively [29]. Soil residual ( r ) and saturated ( s ) water contents,
and parameters ˛ and n for each soil layer were obtained by ﬁtting the van Genuchten model to retention data determined in
the laboratory using the SWRC software [30]. The pore connectivity/tortuosity factor (l) used in simulations was set to 0.5 for all
soil layers. This value was recommended by Mualem [31] and is a
default value used for soils in Hydrus modeling studies.
The initial soil and soil solution Zn and Cu concentrations withineach soil layer, used in the Hydrus-2D simulations (starting on
01/01/2000), were based on values measured in the plot without PS
applications. For the total TM contents we used the total concentrations measured in the laboratory. For soil solution concentrationsof Zn and Cu, we used multiple regression equations proposed by
Sauvé et al. [32] and tested by Mallmann et al. [13]:log Znsolution (␮g l−1 ) = 3.68 − 0.55pH + 0.94 log Zn (mg kg−1 )− 0.34 log OC(%),(1)

log Cusolution (␮g l−1 ) = 1.37 − 0.21pH + 0.93 log Cu (␮g kg−1 )− 0.21 log OC (%),

(2)

The Freundlich nonlinear isotherm equations were developed
from these total and solution TM concentrations. The Freundlich
exponent n of 0.65 was used for Zn [33,34] and 0.85 for Cu [35],corresponding to average values from literature dealing with modeling studies on soils with comparable properties. Different values
for Zn and Cu are based on the premise that Cu has a great binding strength with soil constituents [36] and, consequently, a low
mobility in the soil proﬁle.
Desorption Zn and Cu curves were ﬁtted using the kinetic modelof Fangueiro et al. [37]:Q = Q1 (1 − e−kt ) + Q2 (1 − e−t )(3)where Q (mg kg−1 ) is TM desorbed at time t; Q1 (mg kg−1 ) is the easily extractable TM fraction, associated with the constant desorption
kinetic rate k (h−1 ); and Q2 (mg kg−1 ) is the slowly extractable TM
fraction, associated with the kinetic desorption constant  (h−1 ).
The non-extractable TM fraction by EDTA (Q3 ) is calculated as thedifference between the total TM (QT ) and Q at t = 24 h.
In simulations of the vertical transport of Zn and Cu in the soil,
the fraction Q1 represented sorption sites with the instantaneous
equilibrium sorption [37], because of the high value of k. This value
led to the calculation of the ˇ value (equation 4), which is the fraction of sorption sites with instantaneously adsorbed TMs to thefunctional groups (at equilibrium) and is required by Hydrus-2D:
ˇ=

Q1
QT

(4)

The Q2 and Q3 TM fractions were considered to be adsorbed
to functional groups according to a kinetics adsorption/desorption
model [37], using the kinetic constant (). Since it is impossible
to determine the real  value in the ﬁeld, and considering thatthe strong extractant character of EDTA signiﬁcantly overestimate
rates that occur in soils [38], we reduced the sorption rates in theHydrus-2D simulations, following Mallmann et al. [13]. Mallmann
et al. [13] reproduced the vertical distributions of Zn and Pb concentrations using Hydrus-2D after reducing EDTA-determined rates by
1:144,000 (considering that one minute of the EDTA extraction represents one day in the ﬁeld and an additional reduction by a factorof 100), leading to a satisfactory ﬁtting of observed proﬁles of metal
concentrations in real soil situations. All physical and chemical
characteristics and initial TM concentrations for the plot without

225

PS applications that are required to run Hydrus-2D are listed inTable 1.
Numerical solutions of the Richards equation, describing
variably-saturated water ﬂow, and the convection–dispersion
equation, describing solute transport, require speciﬁcation of initial and boundary conditions. The atmospheric boundary condition
was considered in Hydrus-2D simulations at the soil surface. Daily
precipitation data 01/01/2000–01/01/2008 were obtained from
Sistema Irriga® (UFSM). Since a water loss by surface runoff wasmeasured during 8 years of the experiment [39], rainfall was corrected by subtracting a water runoff loss. Daily evapotranspiration
rates for crops cultivated on the experimental plots were obtained
from the Sistema Irriga’s® irrigation management program, whichcalculates the crop’s maximum evapotranspiration (ETm ) using thePenman–Monteith combination equation [40]. Average amountsof annual rainfall, runoff (from the area without the PS application), and evapotranspiration were 1678, 548, and 921 mm year−1 ,respectively.
The total amounts of Zn and Cu added to the soil via PS amendments were determined as a difference between the TM massbalance in the plot with applied PS and the one without, evaluated over a depth of 60 cm (Table 2). Furthermore, there was asigniﬁcant loss of TMs from the soil proﬁle from depths larger than
60 cm due to leaching during simulations. To maintain the balance
between the results of the simulations with the plot that received
PS, these quantities were also added to the amounts applied to thesoil during the simulations. Thus, the total amounts of TMs added
to the soil in Hydrus simulations were 76.5 and 56.5 kg ha−1 of Zn
and Cu, respectively (Fig. 1). These quantities differ slightly fromthose added in ﬁeld experiments during 19 PS applications (83.4
and 67.1 kg ha−1 , respectively). These differences are attributed
mainly to the TM loss due to runoff, and to a lesser extent, theTM removal with harvested crops. The cumulative removal of TMs
by harvested crops from 2001 till 2008 was very small, representing only about 0.33 and 1.13% of the total Zn mass in the 0–60-cm
soil depth (Table 2) for the 0 and 80 m3 ha−1 plots, respectively,
and about 0.05 and 0.12% of the total Cu mass, respectively. These
removed amounts were calculated based on the crop production
data (for corn for years 2001, 2002, 2004, 2005, and 2007, andfor beans for years 2003 and 2006) and the TM concentrations incrop grains [41,42]. The amounts of TMs added to the soil in PS
applications were proportional to the measured TM contents in theamendments during the ﬁeld experiment (Fig. 1). In the Hydrus2D simulations, the Zn and Cu quantities were applied at the soil
surface diluted in rainwater (assuming an instantaneous 100% solubility). This strategy was selected for two reasons: (a) to increase thedownward movement of TMs since the TM transfer associated withorganic or mineral particles (the so-called colloid-facilitated solutetransport [43]) was not considered and (b) the kinetic approachthat was used was responsible for retarding the initial sorptionof the input Zn and Cu amounts to the soil sorption sites, which
reproduces a non-complete solubility of the pig slurry’s TMs. Using
parameters listed in Table 1, we simulated the vertical transport ofZn and Cu between 01/01/2000 and 01/01/2008 while considering
two hypotheses about the TM reactivity:– hypothesis A: 100% of the total TM concentrations in each soil
layer is in instantaneous chemical equilibrium with the soil solution,– hypothesis B: the total TM concentrations in soil can be divided
into an instantaneous chemical equilibrium fraction and a kinetic
fraction, determined by the EDTA extraction. The kineticallyadsorbed fraction reacts with the solution according to the rate constant, deﬁned by the two-site kinetic sorption equation
proposed by Fangueiro et al. [37]. In this equation, the kinetic

F.J.K. Mallmann et al. / Journal of Hazardous Materials 243 (2012) 223–231

12

60

8

40

4

20

0
2000

2002

2004

2006

16

COPPER ADDITIONS

80

12

60

8

40

4

20

0
2008

0
2000

Time, year

2002

2004

2006

Cumulative Cu, kg ha -1

Zn, kg ha-1

80

Cu, kg ha-1

ZINC ADDITIONS

16

Cumulative Zn, kg ha-1

226

0
2008

Time, year

Fig. 1. Actual and cumulative zinc and copper applications used in Hydrus-2D simulations between 2000 and 2008, corresponding to 19 pig slurry applications during theexperiment.
Table 1
Physical and chemical parameters of the soil in the plot without the application of pig slurry, required for simulations with Hydrus-2D.
Parametera

Soil layer (cm)
1
(0–5)

2
(5–10)

3(10–25)4(25–35)5(35–50)6(50–60)

Soil
pH
Clay, g kg−1
Silt, g kg−1
Sand, g kg−1
OC, g kg−1
Bd, g cm−3
Ks , cm d−1
 s , cm3 cm−3
 r , cm3 cm−3
˛VG , cm−1
n1
LLD, cmTD, cm

5.29
141
365
494
12.3
1.53
81.1
0.367
0.116
0.06961.4297
0.5
2.5
0.2

5.34
163
349
488
9.4
1.61
20.3
0.404
0.137
0.35641.3249
0.5
2.5
0.2

5.50
165
347
488
8.7
1.69
12.5
0.405
0.139
0.07081.4455
0.5
2.5
0.2

5.50
179
356
465
9.4
1.49
32.8
0.419
0.147
0.27161.3330
0.5
2.5
0.2

5.42
177
368
455
7.8
1.46
205.6
0.365
0.144
0.18091.3297
0.5
2.5
0.2

5.42
188
371
441
6.1
1.41
250.8
0.410
0.128
0.49891.3603
0.5
2.5
0.2

Zinc
Total, mg kg−1
Solution, ␮g l−1ˇ, 10−3 d−1
KF
n

15.30
71.32
0.56
4.29
1.76
0.65

15.30
73.44
0.29
4.13
1.72
0.65

15.15
61.33
0.14
3.04
1.92
0.65

20.04
77.78
0.04
1.82
2.18
0.65

22.08
100.13
0.04
1.44
2.03
0.65

18.91
93.73
0.02
2.82
1.82
0.65

CopperTotal, mg kg−1
Solution, ␮g l−1ˇ, 10−3 d−1
KF
n

5.33
9.27
0.61
6.87
54.28
0.85

5.33
9.58
0.46
4.17
52.78
0.85

9.04
15.31
0.21
2.61
60.05
0.85

10.89
18.15
0.13
2.49
62.61
0.85

12.01
21.59
0.07
1.83
59.53
0.85

14.23
26.91
0.06
3.10
58.52
0.85

a
OC = organic carbon; Bd = bulk density; Ks = saturated hydraulic conductivity;  s = saturated water content;  r = residual water content; ˛VG and n1 = retention parameters;
L = pore-connectivity factor; LD and TD = longitudinal and transverse dispersivities, respectively; ˇ = fraction of sorption sites with instantaneous sorption of the heavy metals;
 = kinetic constant for sorption sites 1-␤; KF and n = parameters of the Freundlich isotherm for the ˇ sites, calculated with total and solution concentrations in mol g−1 andmol l−1 , respectively.

Table 2
Zinc and copper amounts measured in different soil layers of experimental plots with and without pig slurry applications.
Soil layer (cm)

1 (0–5)2 (5–10)
3 (10–25)
4 (25–35)
5 (35–50)
6 (50–60)
Total (0–60)

Zinc, kg ha−1

Copper, kg ha−1

Plot without pig slurry

Plot with pig slurry

Plot without pig slurry

Plot with pig slurry

11.7
12.4
38.4
30.0
48.4
26.7
167.6

53.0
32.2
57.6
24.4
41.6
30.4
239.2

4.1
4.3
22.9
16.3
26.3
20.1
94.0

45.4
18.4
30.4
11.6
26.4
17.0
149.2

F.J.K. Mallmann et al. / Journal of Hazardous Materials 243 (2012) 223–231

sorption sites react with the soil solution at a rate that is a fractionof the  measured value, as discussed above.

227

transport mechanisms occurring in soils that were neglected inour study may be responsible for differences between simulated and measured Cu concentrations. Additional processes that
may contribute to the TM transport in soil are bioturbation,
mainly by earthworms [44–46], and the colloid-facilitated transport [43,47,48]. Being very difﬁcult to parameterize, such processes
were not taken into account in our simulations.
Simulated Zn concentrations ﬁtted better the measured Zn values when hypothesis B was used, partly due to larger Zn solution
concentrations throughout the simulation (Fig. 2). Consequently,
the transfer of Zn to subsurface layers occurred earlier when the
two-site sorption model was used. Increased Zn concentrations in
the 5–10 cm soil layer were observed as early as 2001. The slower
adsorption rate to the soil kinetic sorption sites, compared to theequilibrium sites, prolongs the presence of TM in the soil solution,
favoring its transfer to deeper soil layers. Improved correspondenceof simulated and measured concentrations when a two-site sorption model with reduced EDTA kinetic rate constants is used wasrecently demonstrated by Mallmann et al. [13].
Similar delay was also observed for Cu when sorption according
to hypothesis B was considered (Fig. 2). Nevertheless, Cu concentrations in the soil solution during simulations were much
lower than observed for Zn, explaining its limited leaching in thesoil, compared to Zn. Although simple, the Freundlich sorption
isotherm, describing the adsorption/desorption process in the sorption sub-model used in Hydrus-2D, was adequate to account fordifferences between the two TMs. Both the distribution coefﬁcient (KF ), describing the equilibrium sorption, and the fractionof the equilibrium sorption sites (ˇ) were higher for Cu (Table 1),
indicating lower ratios of Cu in the soil solution compared to Zn
and a lower susceptibility of Cu to transport via water ﬂow. It is
important to emphasize that, in our work, soil water retention andhydraulic conductivity data were all measured directly on samples collected in situ, and used to obtain parameters for the van
Genuchten–Mualem model [29], describing soil hydraulic properties. Consequently, there was no need to use empirical pedotransfer
functions to estimate soil hydraulic parameters.
Finally, by comparing simulated and measured Zn and Cu concentrations, the usefulness of water ﬂow and solute transportmodels implemented in Hydrus for estimating the transport anddistribution of TMs in soils was demonstrated. In addition to being
efﬁcient in reproducing the distribution of Zn and Pb concentrations in arable soils affected by a metallurgical fallout deposition

After validating the model by comparing model predictions andexperimental ﬁeld data of Zn and Cu concentration proﬁles for
2000–2008, we simulated the movement of Zn and Cu for the next
50 years. These simulations included estimations of TM quantities transported to soil layers below a depth of 60 cm. To performthese simulations, precipitation, runoff, and evapotranspiration
data between 2000 and 2008 were repeated successively until thecompletion of the desired 50-year period. Two scenarios were evaluated concerning the future applications of PS to the soil. While in
Scenario I the future applications of PS were discontinued, in Scenario II the PS applications continued during 2008–2058 at dosesof 80 m3 ha−1 prior to cultivation, i.e., there was an additional inputof 478 and 353 kg ha−1 of Zn and Cu, respectively.
3. Results and discussion
3.1. Simulation of Zn and Cu transport in the soil between 2000
and 2008
Simulations with hypothesis A (100% instantaneous equilibrium) produced a strong Zn and Cu retention in the soil surface
layer (0–5 cm), although increasing TM contents were observedin the ﬁeld down to a depth of about 25 cm (Table 3). In particular, about 97% of added Cu remained in the top 0–5 cm soil layer.
Large differences between simulated and measured TM concentrations clearly indicate that the model based on hypothesis A cannot
describe observed ﬁeld metal concentration proﬁles.
Simulations with hypothesis B (a two-site sorption model witha reduced sorption rate) produced more realistic distributions of
Zn and Cu when compared to measured ﬁeld values (R2 = 0.982
and 0.919, respectively). Simulated and observed Zn concentrations
were fairly similar in the surface soil layer. Also, simulations indicated transport of Zn down to a depth of about 25 cm. In 2008,
differences between measured and simulated Zn concentrations
did not exceed 4.1 mg kg−1 in any soil layer (Table 3). The model
based on hypothesis B also predicted an increased transfer of Cu in
the soil. Yet, estimated and observed Cu concentrations in 2008 still
diverged (Table 3). Although the transport and sorption–desorption
processes considered in our simulations in general represent themain factors governing the TM movement in soils [6], other

Table 3
Total zinc and copper concentrations in soil layers of experimental plots with pig slurry applications. Initial and ﬁnal values are for 2000 and 2008, respectively. Simulated
values are for 2008 (using Hydrus-2D run under hypotheses A and B.
Soil layer

Zinc

CopperDifference
mg kg−1%

Initial (2000)
mg kg−1

Final (2008)
mg kg−1

Simulated (2008)
mg kg−1

Differencea
mg kg−1%

Hypothesis A: 100% equilibrium sorption model
15.3
69.4
83.6
1 (00–05)
15.3
39.9
38.7
2 (05–10)
15.2
22.7
16.0
3 (10–25)
20.0
16.3
19.7
4 (25–35)
22.1
19.0
21.5
5 (35–50)
6 (50–60)
18.9
21.5
19.1

14.2
−1.2
−6.8
3.4
2.5
−2.4

20.5
−2.9
−29.7
20.6
13.2
−11.2

5.3
5.3
9.0
10.9
12.0
14.2

59.4
22.8
12.0
7.7
12.0
12.0

77.1
6.9
8.9
10.9
12.0
13.9

17.8
−15.9
−3.1
3.2
−0.1
1.8

29.9
−69.7
−26.1
40.9
−0.5
15.3

Hypothesis B: two-site sorption model with reduced  values
1 (00–05)
15.3
69.4
65.4
15.3
39.9
39.2
2 (05–10)
15.2
22.7
20.7
3 (10–25)
20.0
16.3
20.4
4 (25–35)
22.1
19.0
21.9
5 (35–50)
18.9
21.5
18.7
6 (50–60)

−4.0
−0.7
−2.1
4.1
2.9
−2.8

−5.7
−1.7
−9.2
24.9
15.3
−12.9

5.3
5.3
9.0
10.9
12.0
14.2

59.4
22.8
12.0
7.7
12.0
12.0

73.6
9.9
8.9
10.9
12.0
14.0

14.2
−12.9
−3.1
3.2
−0.1
2.0

23.9
−56.5
−25.9
40.8
−0.6
16.3

cm

a

Initial (2000)
mg kg−1

Final (2008)
mg kg−1

Simulated (2008)–ﬁnal (2008).

Simulated (2008)
mg kg−1aF.J.K. Mallmann et al. / Journal of Hazardous Materials 243 (2012) 223–231

2.5

Zn concentration, mg l-1

2.0

ZINC

1.5

1.0

0.5

0.0
2000

2002

2004

2006

COPPER400

0-5 cm, two-site sorption
5-10 cm, two-site sorption
10-25 cm, two-site sorption
0-5 cm, 100% equilibrium
5-10 cm, 100% equilibrium
10-25 cm, 100% equilibrium

Cu concentration, µg l-1

228

2008

Time, year

300

200

100

0
2000

2002

2004

2006

2008

Time, year

Fig. 2. Zinc and copper concentrations in the soil solution between 2000 and 2008 in the upper three soil layers, estimated with Hydrus-2D for two hypotheses: 100%
chemical equilibrium and a two-site sorption with a reduced sorption rate. Note that different concentration scales are used on the Y-axis.

in Northern France [13], the model based on hypothesis B was also
shown to be a successful tool for assessing the movement of Zn,
and somewhat less of Cu, in PS amended soils in Southern Brazil,
under very different pedoclimatic conditions.

mentioned that the amounts of heavy metals extracted from thesoil by EDTA closely coincided with the anthropogenic metal pool.
Hence, EDTA extractions are indicative for long-term predictions ofmetal migration at different depths in soils.

3.2. Predictive simulations of Zn and Cu concentrations between
2008 and 2058

3.2.2. Scenario II: continued PS applications
After an additional 50 years of PS applications, Zn concentrations in the soil solution in 2058 would increase in all soil layers
compared to 2008, notably at depths below 20 cm (Fig. 3). The twosite sorption model predicted a transfer of 208 kg Zn ha−1 (43.6% of
Zn added between 2008 and 2058) to depths below 60 cm. Such
results are consistent with the ﬁndings of Abollino et al. [52], who
also reported a higher TM mobility in contaminated soils than in
uncontaminated soils. However, they concluded that such contaminants were potentially more environmentally damaging. Ourmodel’s estimates for 2058 indicate maximum Zn levels in the soil
solution of 1.7 mg l−1 at a depth of 5 cm and less than 1.0 mg l−1
at a depth of 60 cm. Such Zn concentrations are clearly below thethreshold value of 5.0 mg l−1 established by the Brazilian Health
Ministry [53] for drinking water. In addition, although consistently
larger total Zn contents were predicted for the 60-cm soil proﬁle in
2058 (508 kg Zn ha−1 ) than in 2008 (240 kg Zn ha−1 ), the threshold
Zn concentrations set by CETESB [5] for agricultural areas (AA) were
not exceeded. The maximum Zn concentration of 97.6 mg kg−1
observed in the upper soil layer (Fig. 3) did not exceed either theprevention value (PV-AA: 300 mg kg−1 ) or the intervention value(IV-AA: 450 mg kg−1 ). Hydrus-2D simulations of the impacts ofcontinuous PS applications did not reveal risks of groundwaterpollution by Zn leaching, nor of exceeding the threshold Zn concentration in any soil layer.
Predicted variations in Cu concentrations in the soil solutionof all soil layers were much smaller than for Zn. Higher Cu concentrations occurred at depths above 35 cm (Fig. 3). An estimatedCu transfer to depths below 60 cm during 50 years was low(7.0 kg ha−1 ) and equal to the amount predicted for scenario I, representing 12.4% of the total Cu mass added to the soil between 2000
and 2008, but only 2.0% of the total Cu mass added between 2008
and 2058. This suggests that until 2058, Cu inputs from PS will
not reach depths below 60 cm and that such outputs are primarily controlled by water ﬂow through the soil and the TM solution
concentration in the 50–60-cm soil layer (26.9 ␮g l−1 , Table 1).
However, in 2058 the contamination plume of Cu in the soil solution would penetrate deeper in the soil proﬁle than in 2008 (Fig. 3).

3.2.1. Scenario I: discontinued PS applications
Hydrus-2D simulations, considering hypothesis B, predictedthat water ﬂow in the soil proﬁle was sufﬁcient in lowering the Zn
solution concentrations to levels comparable with those observedin the non-amended soil (Fig. 3). About 45% of Zn retained in theupper 25 cm of the soil proﬁle in 2008 was desorbed and moved
to depths below 25 cm. In addition, a loss of 48.4 kg Zn ha−1 fromthe upper 60 cm was estimated, representing 63% of the total Zn
mass added to the soil between 2000 and 2008. Although Zn concentrations in the soil solution were similar to those observed in
the non-amended soil, the observed increased retention of Zn in
deeper layers of the soil was related to higher adsorption capabilities (higher KF ) and especially to a higher fraction of kinetic sorption
sites (1-ˇ), from which desorption is very slow. Kandpal et al. [49]also highlighted the existence of the kinetic sorption sites in the soil,
showing that the Zn desorption curve in the soil demonstrates thepresence of a labile and another, less labile fraction. For this reason,
the use of the two-site sorption model is more suitable to accountfor such phenomenon. Moreover, the activation energy necessary
for TM desorption was reported to be higher than for adsorption[50], i.e., desorption rates are slower than adsorption rates. This
indicates that, over the long-term, metal contaminants such as Zn
will slowly migrate to greater soil depths and their surface concentrations will decrease.
Movement of Cu in the soil was different than movement of
Zn. After suspending PS applications, the downward movementof Cu slowed, leading to a slight increase in the total Cu concentrations in the upper 25 cm, whereas Zn concentrations increasedslightly in all soil layers (Fig. 3). Studying ﬁeld experiments involving soil applications of sewage sludge, Han et al. [51] mentionedthat at low doses, TMs were transported and repartitioned among
the solid soil constituents very slowly and, with time, concentrations would return to an equilibrium state of un-amended soils. In
our work, the use of EDTA extractions efﬁciently determined levelsof Zn and Cu sorbed to kinetic sites of the soil. Labanowski et al. [38]

F.J.K. Mallmann et al. / Journal of Hazardous Materials 243 (2012) 223–231

Zn total, mg kg-1

Zn solution, mg l -1
0.5

1.0

1.5

0

2.0

0

0

10

10

20

20

Depth, cm

Depth, cm

0.0

30

40

20

2000
2008
2058 (i)2058 (ii)

60

80

100

250

300

30

50

60

60

Cu solution, mg l-1
0.2

0.4

0.6

0.8

Cu total, mg kg-1
1.0

1.2

0

0

0

10

10

20

20

30

Depth, cm

Depth, cm

40

40

50

0.0

229

50

100

150

200

30

40

40

50

50

60

60

Fig. 3. Zinc (top) and copper (bottom) solution concentrations (left) and total concentrations (right) in the soil proﬁle at 2000, 2008, and 2058 for two scenarios: (i)discontinued and (ii) continued pig slurry applications; simulated with Hydrus-2D using the hypothesis of a two-site sorption model with a reduced sorption rate. Note thatdifferent concentration scales are used on the X-axis.

Therefore, if applications of PS were maintained, the transfer of
Cu to groundwater would be likely to increase signiﬁcantly after
2058. Yet, the Cu concentrations remain below the threshold value
for drinking water in Brazil [53] (2.0 mg l−1 ), and 50-years of continued PS applications would not represent a risk of groundwaterCu pollution.
However, the total Cu soil concentrations are likely to represent
environmental risk in case of continued PS applications. Simulated
Cu concentrations in 2058 increased to 259 mg kg−1 at a depthof 1 cm (compared to 108 mg kg−1 in 2008) and to 207 mg kg−1
at a depth of 5 cm. According to CETESB [5], such concentrations
exceed the IV-AA value of 200 mg Cu kg−1 . In such a case, the regulatory agency highlights direct and indirect potential risks to humanhealth under the Agricultural Exposure Scenario. Moreover, in 2058
elevated Cu concentrations (180–100 mg kg−1 ) were also predicted
at a 5–10-cm depth (Fig. 3), representing environmental risk if PS
applications were continued after 2058. At depths of 15–20 cm,
simulated soil Cu concentrations remained below the Prevention
Value (60 mg Cu kg−1 , [5]), referring to the soil’s capacity to sustain
its primary functions, such as protecting the ecological receptors
and the quality of the groundwater. For soil depths below 25 cm, Cu

concentrations did not exceed 35.0 mg kg−1 , the Quality Reference
Value [5], presenting no environmental risk.
Our predictive modeling of the fate of TMs revealed risks ofstrong Cu accumulation at the soil surface, notably in the upper
10 cm. Mechanical homogenization by mixing top soil layers
and thus incorporating Cu to greater depths may represent an
efﬁcient management strategy to lower such too high surface
TM concentrations. Soil management in regions where organic
residues with potential hazardous impacts are disposed should
be different than in regions with the traditional agricultural
production under no-tillage systems. Even in unique agricultural
production systems, temporary turning of soil under no-tillage isan alternative strategy not to be ignored [54]. Yet, lowering thesurface TM concentration by mechanical tillage does not reduce
the total accumulated metal mass.
4. Conclusion
We used Hydrus-2D with a two-site sorption model with areduced kinetic rate constant and with measured soil hydrauliccharacteristics to reproduce vertical distributions of Zn and Cu

230

F.J.K. Mallmann et al. / Journal of Hazardous Materials 243 (2012) 223–231

measured in an experimental plot soil proﬁle after 8 years of
repeated pig slurry applications. We considered the satisfactory
correspondence between simulated and ﬁeld-observed TM distributions to represent a direct model validation. We then used thevalidated model to predict Zn and Cu movements during the future
50 years. If PS applications are discontinued, estimated TM concentration levels, notably of Zn, would considerably decrease in surface
layers. However, if PS applications continue, the model estimateda much higher Zn transfer to depths below 60 cm than for the scenario of discontinued PS applications. In addition, Cu transfer below
the 60-cm depth was similar for both scenarios. Nevertheless, thetransport of Zn and Cu by percolating water did not present risks
in the future for polluting groundwater. Yet, a continuous application of pig slurry would lead to consistent Cu accumulation in thesoil surface layer, exceeding the Brazilian threshold for copper inagricultural soils.
Acknowledgements
F.J.K. Mallmann acknowledges CAPES for postgraduate scholarship. The authors thank Reimar Carlesso and Mirta Petry (Sistema
Irriga® ) for providing daily evapotranspiration and local atmospheric data. They express their special gratitude to Maria AliceSantanna for her relevant contributions to the discussion.
References[1] CEC, Council of the European Communities, Council Directive 86/278/EEC of 12
June 1986 on the protection of the environment, and in particular of the soil,
when sewage sludge is used in agriculture, Ofﬁcial J. 181 (1986) 6–18.
[2] USEPA, United States Environmental Protection Agency, 40 CFR–Part 503 Standards for the use and disposal of sewage sludge, F. R. Washington, 58 (1993)
9387–9415.
[3] CETESB, Companhia de Tecnologia de Saneamento Ambiental, Relatório deEstabelecimento de Valores Orientadores para Solos e Águas Subterrâneas, SãoPaulo, 2001.
[4] CONAMA, Conselho Nacional do Meio Ambiente, Resolução no. 375/2006, de
29/8/2006.
[5] CETESB, Companhia de Tecnologia de Saneamento Ambiental, Decisão de diretoria No. 195-2005-E, de 23-11-2005.
[6] R. Carrillo-Gonzàlez, J. Šimůnek, S. Sauvé, D. Adriano, Mechanisms and pathways of trace element mobility in soils, Adv. Agron. 91 (2006) 111–178.
[7] J. Šimůnek, M.T.H. Van Genuchten, M. Šejna, Development and applications of
the HYDRUS and STANMOD software packages, and related codes, Vadose Zone
J. 7 (2008) 587–600.
[8] L. Bahaminyakamwe, J. Šimůnek, J. Dane, J.F. Adams, J.W. Odom, Copper mobility in soils as affected by sewage sludge and low molecular weight organic
acids, Soil Sci. 171 (2006) 29–38.
[9] F. Degryse, E. Smolders, Mobility of Cd and Zn in polluted and unpolluted
spodosols, Eur. J. Soil Sci. 57 (2006) 122–133.
[10] M.N. Ngoc, S. Dultz, J. Kasbohm, Simulation of retention and transport of copper,
lead and zinc in a paddy soil of the Red River Delta Vietnam, Agric. Ecosyst.
Environ. 129 (2009) 8–16.
[11] J.-H. Huang, G. Ilgen, E. Matzner, Fluxes and budgets of Cd, Zn, Cu, Cr and
Ni in a remote forested catchment in Germany, Biogeochemistry 103 (2001)
59–70.
[12] S. Chotpantarat, S.K. Ong, C. Sutthirat, K. Osathaphan, Effect of pH on transportof Pb2+ , Mn2+ , Zn2+ and Ni2+ through lateritic soil: column experiments andtransport modeling, J. Environ. Sci. 23 (2011) 640–648.
[13] F.J.K. Mallmann, D. Rheinheimer dos Santos, P. Cambier, J. Labanowski, I. Lamy,
M.A. Santanna, D. Tessier, F. van Oort, Using a two site-reactive model for simulating one century changes of Zn and Pb concentration proﬁles in soils affectedby metallurgical fallout, Environ. Pollut. 162 (2012) 294–302.
[14] M.T.H. Van Genuchten, R.J. Wagenet, Two-site/two-region models for pesticidetransport and degradation: theoretical development and analytical solutions,
Soil Sci. Soc. Am. J. 53 (1989) 1303–1310.
[15] D. Rheinheimer dos Santos, P. Cambier, F.J.K. Mallmann, J. Labanowski, I. Lamy,
D. Tessier, F. van Oort, Prospective modeling with Hydrus-2D of 50 years Zn andPb movement in low and moderately metal contaminated agricultural soils, J.
Contam. Hydrol. (submitted for publication).
[16] P. Seuntjens, Field-scale cadmium transport in a heterogeneous layered soil,
Water Air Soil Pollut. 140 (2002) 401–423.
[17] A. Moradi, K.C. Abbaspour, M. Afyuni, Modeling ﬁeld-scale cadmium transport
below the root zone of a sewage sludge amended soil in an arid region in Central
Iran, J. Contam. Hydrol. 79 (2005) 187–206.
[18] Soil Survey Staff, Keys to Soil Taxonomy, ninth ed., Natural Resources Conservation Service, USDA, Washington, DC, 2003.

[19] J.L.S. Silva, Estudo dos processos de siliciﬁcação e calciﬁcacão em Rochas Sedimentares Mesozóicas do Rio Grande do Sul, Brasil, Ph.D. Thesis, University
Federal do Rio Grande do Sul, Porto Alegre, Brazil, 1997.
[20] E.C. Bortoluzzi, B. Velde, M. Pernes, J.C. Dur, D. Tessier, Vermiculite, withhydroxy-aluminium interlayer, and kaolinite formation in a subtropical sandy
soil from south Brazil, Clay Min. 43 (2008) 185–193.
[21] C.R. Lourenzi, C.A. Ceretta, L.S. Silva, G. Trentin, E. Girotto, F. Lorensini,
T.L. Tiecher, G. Brunetto, Soil chemical properties related to acidity
under successive pig slurry applications, Rev. Bras. Ciênc. Solo 35 (2011)
1827–1836.
[22] P.I. Gubiani, D.J. Reinert, J.M. Reichert, N.S. Gelain, J.P.G. Minella, Permeâmetrode carga decrescente associado a programa computacional para a determinaçãoda condutividade hidráulica do solo saturado, Rev. Bras. Ciênc. Solo 34 (2010)
993–997.
[23] D.J. Reinert, J.M. Reichert, Coluna de areia para medir a retenção de água nosolo: protótipos e teste, Ciênc. Rural 36 (2006) 1931–1935.
[24] USDA, United States Department of Agriculture; Soil Conservation Service, Soil
Survey Investigations, Report, no. 1, Washington, 1972.
[25] M.J. Tedesco, C. Gianello, C.A. Bissani, H. Bohnen, S.J. Volkenweiss, Análise desolo, plantas e outros materiais, Porto Alegre, Dep. de Solos, UFRGS (1995).
[26] EMBRAPA, Centro Nacional de Pesquisa de Solos, Manual de métodos de análise
de solo, second ed., Rio de Janeiro, 1997.
[27] A. Tessier, P.G.C. Campbell, M. Bisson, Sequential extraction procedure
for the speciation of particulate trace metals, Anal. Chem. 51 (1979)
844–850.
[28] A. Bermond, I. Yousﬁ, J.P. Ghestem, Kinetic approach to the chemical speciationof trace metals in soils, Analyst 123 (1998) 785–789.
[29] M.T.H. Van Genuchten, A closed-form equation for predicting thehydraulic conductivity of unsaturated soils, Soil Sci. Soc. Am. J. 44 (1980)
892–898.
[30] D. Dourado Neto, D.R. Nielsen, J.W. Hopmans, K. Reichardt, O.O.S. Bacchi, Programa computacional para modelagem de curvas de retenção de água no solo
(SWRC, versão 2.00), Scientia Agric. 57 (2000) 191–192.
[31] Y. Mualem, A new model for predicting the hydraulic conductivity of unsaturated porous media, Water Resour. Res. 12 (1976) 513–522.
[32] S. Sauvé, W. Hendershot, H.E. Allen, Solid-solution partitioning of metals incontaminated soils: dependence on pH, total metal burden, and organic matter,
Environ. Sci. Technol. 34 (2000) 1126–1131.
[33] M. Arias, C. Perez-Novo, F. Osorio, E. Lopez, B. Soto, Adsorption and desorptionof copper and zinc in the surface layer of acid soils, J. Colloid Interface Sci. 288(2005) 21–29.
[34] G.J. Lair, M.H. Gerzabek, G. Haberhauer, M. Jakusch, H. Kirchmann, Response of
the sorption behaviour of Cu, Cd, and Zn to different soil management, J. Plant
Nutr. Soil Sci. 169 (2006) 60–68.
[35] B. Buchter, B. Davidoff, M.C. Amacher, C. Hinz, I.K. Iskandar, H.M. Selim, Correlation of Freundlich Kd and n retention parameters with soils and elements,
Soil Sci. 148 (1989) 370–379.
[36] J.C. Echeverria, M.T. Morera, C. Mazkiarin, J.J. Garrido, Competitive sorption ofheavy metal by soils: isotherms and fractional factorial experiments, Environ.
Pollut. 101 (1998) 275–284.
[37] D. Fangueiro, A. Bermond, E. Santos, H. Carapuça, A. Duarte, Kinetic approachto heavy metal mobilization assessment in sediments: choose of kinetic
equations and models to achieve maximum information, Talanta 66 (2005)
844–857.
[38] J. Labanowski, F. Monna, A. Bermond, P. Cambier, C. Fernandez, I. Lamy, F.
van Oort, Kinetic extractions to assess mobilization of Zn, Pb, Cu, and Cd
in a metal-contaminated soil: EDTA vs. citrate, Environ. Pollut. 152 (2008)
693–701.
[39] C.A. Ceretta, E. Girotto, C.R. Lourenzi, G. Trentin, R.C.B. Vieira, G. Brunetto,
Nutrients transfer by runoff under no tillage in a soil treated with successive
applications of pig slurry, Agric. Ecosyst. Environ. 139 (2010) 689–699.
[40] R.G. Allen, L.S. Pereira, D. Raes, M. Smith, Crop evapotranspiration: guidelines
for computing crop water requirements, FAO Rome (1998).
[41] E. Girotto, Cobre e zinco no solo sob uso intensivo de dejeto líquido de suínos,Masters Dissertation, Federal University of Santa Maria, Santa Maria, Brazil,
2007.
[42] E.C.B. Andrade, A.M. Barros, A.C.P. Magalhães, L.L.C. Castro, I. Takasei,
Comparação dos teores de cobre e zinco em leguminosas cruas e após serem
processadas termicamente em meio salino e aquoso, Ciênc. Tecnol. Aliment. 24(2004) 316–318.
[43] J. Šimůnek, C. He, J.L. Pang, S.A. Bradford, Colloid-facilitated transport invariably-saturated porous media: numerical model and experimental veriﬁcation, Vadose Zone J. 5 (2006) 1035–1047.
[44] J. Nahmani, P. Lavelle, E. Lapied, F. van Oort, Effects of heavy metal soil pollution
on earthworm communities in the north of France, Pedobiologia 47 (2003)
663–669.
[45] C. Fernandez, J. Labanowski, A.G. Jongmans, A. Bermond, P. Cambier, I. Lamy,
F. van Oort, Fate of airborne metal pollution in soils as related to agricultural management: 2. assessing the role of biological activity in micro-scale
Zn and Pb distributions in A, B and C horizons, Eur. J. Soil Sci. 61 (2010)
514–524.
[46] N.J. Jarvis, A. Taylor, M. Larsbo, A. Etana, K. Rosén, Modelling the effects of bioturbation on the re-distribution of 137 Cs in an undisturbed grassland soil, Eur.
J. Soil Sci. 61 (2010) 24–34.
[47] L. Citeau, I. Lamy, F. van Oort, F. Elsass, Colloidal facilitated transfer of metals
in soils under different land use, Colloids Surf. A 217 (2003) 11–19.

F.J.K. Mallmann et al. / Journal of Hazardous Materials 243 (2012) 223–231[48] F. van Oort, A.G. Jongmans, L. Citeau, I. Lamy, P. Chevallier, Metal transport
dynamics in soils as revealed by microscale zinc and lead distribution patterns
in subsurface horizons, Eur. J. Soil Sci. 57 (2006) 154–166.
[49] G. Kandpal, P.C. Srivastava, B. Ram, Kinetics of desorption of heavy metals from
polluted soils: inﬂuence of soil type and metal source, Water Air Soil Pollut.
161 (2005) 353–363.
[50] M.B. McBride, Environmental Chemistry of Soils, Oxford University Press, New
York, 1994.
[51] F.X. Han, A. Banin, W.L. Kingery, G.B. Triplett, L.X. Zhou, S.J. Zheng, W.X. Ding,
New approach to studies of heavy metal redistribution in soil, Adv. Environ.
Res. 8 (2003) 113–120.

231[52] O. Abollino, M. Aceto, M. Malandrino, E. Mentasti, C. Sarzanini, R.
Barberis, Distribution and mobility of metals in contaminated sites. Chemometric investigation of pollutant proﬁles, Environ. Pollut. 119 (2002)
177–193.
[53] BRAZIL, Portaria N(518/GM de 25 de março de 2004, Controle e vigilância daqualidade da água para consumo humano e seu padrão de potabilidade, Ministério da Saúde, 2004.
[54] A.L. Marcolan, I. Anghinoni, T.I. Fraga, J.G.B. Leite, Recuperação de atributos físicos de um Argissolo em função do seu revolvimento e do tempo de semeadura
direta, Rev. Bras. Ciênc. Solo 31 (2007) 571–579.