Contamination of wetland soils and floodplain sediments from agricultural activities in the Cerrado Biome (State of Minas Gerais, Brazil)

Catena 128 (2015) 203–210

Contents lists available at ScienceDirect

Catena journal homepage: www.elsevier.com/locate/catena

Contamination of wetland soils and floodplain sediments from agricultural activities in the Cerrado Biome (State of Minas Gerais, Brazil) Vania Rosolen a,⁎, Alfredo Borges De-Campos b, José Silvio Govone c, Cleonice Rocha d a

Department of Petrology and Metallogeny (DPM), University of State of São Paulo (UNESP), Av. 24A, 1515, Bela Vista, Rio Claro, SP CEP: 13506-900, CP: 178, Brazil Institute of the Geoscience (IG), University of Campinas (UNICAMP), R. João Pandiá Calógeras, 51, Campinas, SP CEP: 13083-870, Brazil Department of Statistics, Applied Mathematics and Computation (DEMAC), University of State of São Paulo (UNESP), Av. 24A, 1515, Bela Vista, Rio Claro, SP CEP: 13506-900, Brazil d Department of Mathematics and Physics (MAF), Pontifical Catholic University of Goiás (PUCGoiás), Av. Universitária, 1440, Setor Universitário, Goiânia, GO CEP: 74605-010, Brazil b c

a r t i c l e

i n f o

Article history: Received 13 May 2014 Received in revised form 29 January 2015 Accepted 2 February 2015 Available online xxxx Keywords: Wetland soils Floodplain sediments Contamination index Ecological risk

a b s t r a c t The expansion and intensification of agriculture are responsible for the increase in nonpoint pollution and the release of chemical considered toxic to flora, fauna and human health. Since 1970s, the Cerrado Biome in the State of Minas Gerais (Brazil) has been converted to agriculture. This land use change has not been accompanied by research to evaluate pollution levels associated with inorganic elements in natural wetlands and river sediments. In this study samples were collected in natural wetlands and river sediments recently deposited in floodplain areas to determine the total concentration of inorganic compounds that can be considered potentially toxic and to perform risk assessment. The total concentration of 18 elements (As, Ba, Ca, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, P, Pb, Sr, Ti, V, Zn and Zr) and oxides present at the organic soil layer (0–30 cm) and at the mineral subsurface horizon (30–60 cm) of the wetlands in the upper oxidized layer (0–10 cm) of sediments was determined by ICPOES and XRF. Contamination levels were determined and a risk assessment performed by comparing the obtained values with those proposed by the Guidelines for Agricultural Soils of Brazil (CONAMA no. 420) as well as the pedogeochemical background for soils formed from sandstone. The results showed high average concentrations of As, Cr and Cu in soils and floodplain sediments (as well as of Ba, Pb and Ni in some samples) with values exceeding (p significant at 5%) the pedogeochemical background and the threshold value for clean soil established by CONAMA. The concentrations of As and Cr in the soil were above the threshold level in 100% and 60% of samples, respectively, which may impact the environment and living organisms. The calculated contamination index (Pi) indicates that the wetlands exhibit moderate contamination (2 b Pi ≤ 3) by As N Cr N Cu in the topsoil and in the sub-superficial horizons whereas the floodplain sediments exhibit either no contamination (Pi ≤ 1) or low level of contamination (1 b Pi ≤ 2). When compared with sediments, the results suggest that the Cerrado wetland soils have a tendency to acquire pollutants and thus store agrochemicals. This poses a real risk to the environment and living organisms if no BMP are established. © 2015 Elsevier B.V. All rights reserved.

1. Introduction Crop expansion and intensification are the two pathways used to increase production and productivity in agriculture and both have environmental impacts. According to Foley et al. (2011), contemporary agriculture faces two enormous challenges: (i) increasing production to address a rising world population and (ii) addressing environmental concerns. In the modern agriculture model, crops have often been associated with the generation of nonpoint source pollution which may become an environmental issue (Carpenter et al., 1998). In the Cerrado Biome (Brazilian savannah) the widespread distribution of nonpoint source pollution is a crucial problem related to the expansion and ⁎ Corresponding author. E-mail addresses: [email protected] (V. Rosolen), [email protected] (A.B. De-Campos), [email protected] (J.S. Govone), [email protected] (C. Rocha).

http://dx.doi.org/10.1016/j.catena.2015.02.007 0341-8162/© 2015 Elsevier B.V. All rights reserved.

intensification of agriculture (Laabs et al., 2000). In recent years, intensive agricultural development of soybean, maize and cotton, as well as improved pasture and sugar cane for biofuels occurred in the plateau areas of Minas Gerais State after massive deforestation of the Cerrado native vegetation. In the beginning of the agriculture intensification, only dry and well drained soils (Oxisols) were converted to farmland. However, agribusiness growth required increased amounts of land, and the expansion eventually exceeded the geographical limits of Oxisols to encompass wetland soils found in vereda and murundu wetland types. Vereda and murundu are regional terms, similar to dambo in Africa (von der Heyden and New, 2003), and both correspond to surface topographic depressions located on flat plateaus that are permanently or temporarily waterlogged. In many countries, wetlands are considered priority areas for preservation because they provide several environmental services, e.g., wildlife habitat, storage and regulation of water, carbon stocks, recharge and

204

V. Rosolen et al. / Catena 128 (2015) 203–210

discharge of groundwater and retention of sediments, nutrients and toxic substances (Matiza, 1994; Zedler and Kercher, 2005). Wetlands are also considered an important sink for heavy metals due to the variety of physical–chemical processes that are responsible for the control and stabilization of trace elements (Williams et al., 1994; Bai et al., 2011). Their intrinsic characteristics related to soils (topsoil with high organic matter content), topographic position in the landscape (topographic depression) and hydrology (flow patterns) contribute to the wetland ecosystem to the concentration of residual agrochemicals. Despite the economic importance of agribusiness in the study area and the fact that wetlands are considered priority areas for environmental preservation by the Brazilian Forest Code (Rosolen et al., 2014), less attention has been paid to the influence of agriculture on Cerrado wetlands. In previous studies conducted in a small catchment located near the studied area, Laabs et al. (1999, 2000) detected atrazine (0.05–0.13 μg L−1) in the water, cyhalothrin (4.0 μg kg−1) and simazine (3.2 μg kg−1) in river sediments and high concentrations of simazine, atrazine and chlorpyrifos (80–180 μg kg−1) in addition to metolachlor, cyanazine and trifluralin (2–15 μg kg−1) in Oxisol samples from maize fields. These results indicate that pesticides can accumulate in the soils and may leach into rivers, leading to the pollution of water resources. In the studied area, wetlands are not isolated ecosystems but are functionally connected to river channels and watershed catchment areas. Chemical loadings in the wetland soils and river sediments are expected because farms surround both. It is known that wetlands transport and store not only excess of water but also potential pollutants (Hill and Robinson, 2012). Pollution of wetland soils and floodplain sediments by agriculture is thus of great concern. Despite the importance of this issue, there is a lack of knowledge on the chemical loading of

major and trace elements in wetlands and floodplain sediments as influenced by agriculture in the Cerrado Biome. This is critical because it is known that chemicals released to the environment by agriculture may show different levels of toxicity, are persistent and could be incorporated in the food chain, thus leading to serious public health concerns (Adriano et al., 2004; Ewing et al., 2012; Myers et al., 2013; Gao et al., 2013). This research aims to determine the current status of Cerrado wetland soils and floodplain sediments regarding pollutant metal accumulation from agriculture. The objectives are to (1) assess the total concentration of inorganic chemical contaminants in Cerrado wetland soils, emphasizing the differential concentration shown in the organic and mineral horizons of Gleysols; (2) assess the total concentration of inorganic chemical contaminants in sediments recently deposited in floodplains; and (3) evaluate the degree of impacts of agricultural practices and their environmental implications using the range of chemical concentrations established by the Brazilian Agricultural Soil guidelines (CONAMA, 2009) and the contamination index proposed by Bai et al. (2010).

2. Material and methods The study area is comprised of the Uberabinha catchment (18° 56′ to 19° 26′ S and 47° 50′ to 48° 9′ W), which is located in the western region of Minas Gerais State, Brazil, near the city of Uberlândia, on sedimentary flat plateau area (Fig. 1). This plateau is a branch of the Brazilian Central Plateau, which was originally covered by Cerrado Biome vegetation. The studied area covers an area of 728.43 km2 and encompasses the upper stream of the catchment.

Fig. 1. Localization, land-use and locations of collecting samples of soils and sediments in the Uberabinha catchment (MG, Brazil).

V. Rosolen et al. / Catena 128 (2015) 203–210

The area is at an elevation of 1050 m, with a climate characterized by pronounced dry season (from May to October) and rainfall season (from November to April). The average annual rainfall is 1516 mm, and the average annual temperature is 23 °C. The geology of the Uberabinha catchment is characterized by sandstones of the Marília Formation, Bauru Group (Upper Cretaceous) (Nishiyama, 1989). The soil cover is composed of yellow-reddish Oxisol in well-drained parts of the plateau and Gleysol in imperfectly drained areas corresponding to vereda and murundu wetland types. Murundu corresponds to vegetated micromounds, with circular or elliptical shape, located in the headwaters inside the woodland Cerrado (Cerrado strictu sensus). Vereda is a hillside marsh wetland located in riparian stream zones. The soils of these wetlands may be permanently or temporarily waterlogged, according to the rise and fall of the groundwater level following the alternating wet and dry seasons, which causes the release of water to rivers during dry periods. Grass dominates in anoxic soil conditions. The wetland soils have high levels of organic matter or peat, low pH (near 5) and iron depleted horizons. Chemically poor soils – both Oxisols and Gleysols in the study area – undergo desilicification and are composed of kaolinite, gibbsite and residual quartz, and the contents of hematite and goethite reach 12% and 5%, respectively (Corrêa, 1989). The wetlands are surrounded by soybean and maize crops and their borders (at the transition zone between dry and wet soils) were converted to agricultural tillage after removal of the original herbaceous and shrubby vegetation. 2.1. Soil and sediment sampling and analytical procedures The sampled wetlands correspond to open topographic depressions that are temporally waterlogged and connected to river channels. The topographic slope from the wetland border to the central axis is in the range of 3–4 m. Soil samples were collected in triplicate at the organic topsoil (0–30 cm depth) and the mineral sub-superficial horizon (50–60 cm depth) at five wetlands (sites P1, P2, P3, P4 and P5) (Fig. 1). Only in P1 was the Gleysol drained to increase the area for cultivation (the date of construction is uncertain but personal communication suggests the 1980s). Samples of sediments recently deposited at eight floodplains areas (sites P6, P7, P8, P9, P10, P11, P12 and P13) were collected at 0–10 cm depth along the river channel of the Uberabinha River (Fig. 1). The sediment samples contain material from the upper oxidized layer and are representative of the pollution situation in the last few years, especially related to river deposits (Förstner, 2003). Traces of agrochemicals used in crops in the studied area from 1970s were expected to be found. In the laboratory, soil and sediment samples were homogenized and oven dried at 50 °C then sieved (through a nylon mesh) to obtain the fraction of b63 μm (silt and clay fractions). Particles under this size are nearly equivalent to the size of material carried in suspension by rivers, which usually bind pollutants (Förstner, 2003). Total oxides were determined by X-ray fluorescence (XRF) (Lab. Geosol, LTDA, Brazil) in the sieved samples. The detection limits were in the order of 0.1 g kg−1 for SiO2, Al2O3 and Fe2O3 and in the order of 0.01 g kg−1 for MgO, CaO, P2O5, Na2O, K2O, and TiO. For the analyses of As, Ba, Ca, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, P, Pb, Sr, Ti, V, Zn and Zr, the soil and sediment samples were digested with Aqua Regia (HCl/HNO3) and analyzed using inductively coupled plasma optical emission spectroscopy (ICP-OES, Thermo Jarrel Ash, ICAP 61E). Quality control was verified by using the International Reference Material (ICPREF20), Lab. Geosol, LTDA, Brazil, with recovery rates of 95–100%. The samples from each field site were prepared in triplicate to check the analytical precision of the data. The total organic carbon (OC%) was determined by the TOC equipment (SSM-5000A Shimadzu Corporation). The soil and sediment pH values were measured using a pH meter (soil:water = 1:5).

205

2.2. Statistical analysis The data of trace elements failed to meet the assumption of normality (Shapiro–Wilk test) for parametric statistical analysis, so nonparametric tests (Hollander and Wolfe, 1973) were applied. The comparison between the relative concentration of metals present in the organic topsoil and mineral horizons was made by applying Friedman's test (significant if at p b 0.05), which considered no independency between variables. The Wilcoxon test for nonparametric data (significant if at p b 0.05) was used to determine if the mean of each element concentration in soil and sediments was higher or smaller than those proposed by the contamination guiding values of CONAMA (2009). 2.3. Contamination index (Pi) Determining contamination levels in the wetland soils and floodplain sediments and the risk assessment were made by comparing the concentrations of inorganic chemicals obtained in this study with guiding values established by CONAMA (National Environmental Council, Resolution no. 420 of 2009) for agriculture soils. Additionally, the results were compared with pedogeochemical background values determined for soils from sandstones present in the same region of the study area (Marques et al., 2004a). However, both reference values are related to soils developed in oxidic conditions because there are no established geochemical background or chemical threshold values for waterlogged soils found in the wetlands or floodplain sediments from Central Brazil. Considering the need to adopt numerical criteria to evaluate the impacts of agriculture practices and their environmental implications, the ranges of chemical concentration values applicable to all classes of agricultural soils and pedogeochemical background values were used. Accordingly, the soil quality guideline index VQR, which indicates the background values for clean soil, was used for analyzing the collected data. In the VQR index, the class background value indicates the natural expected value whereas the class VP (threshold effect level) is the concentration of determined substance above which the quality of soil and groundwater becomes low, and the class VI (potential effect level) is the concentration of determined compound in the soil above which there is a potential direct or indirect risk to the environment and human health. The contamination index (Pi) was calculated for the heavy metals following the approach proposed by Bai et al. (2010), which is expressed by the equations: Pi ¼

Ci ; Xa

if C i ≤ X a

C i −X a ; X b −X a C −X b Pi ¼ 2 þ i ; X c −X b C i −X c Pi ¼ 3 þ ; X c −X b Pi ¼ 1 þ

if X a b C i ≤ X b if X b b C i ≤ X c if C i N X c

where Pi = contamination index; Ci = determined values; Xa = no contaminated threshold; Xb = low contaminated threshold; and Xc = high contaminated threshold. The contamination index is described by the following categories: Pi ≤ 1, no contamination; 1 b Pi ≤ 2, low contamination; 2 b Pi ≤ 3, moderate contamination; and Pi N 3, high contamination. The integrated contamination index (P) is expressed by: vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi !ffi u n u 1X t P P ¼ maxðP i Þ  n i¼1 i where P i is the average contamination index of each heavy metal and n is the heavy metal number. P ≤ 1 indicates no contamination; 1 b P ≤ 2,

206

V. Rosolen et al. / Catena 128 (2015) 203–210

low contamination; 2 b P ≤ 3, moderate contamination; and P N 3, high contamination. Threshold values (Xa, Xb and Xc) were established according to CONAMA (2009).

OC concentration mainly because a decrease in the solubility of organic matter linked to a decrease in the particle dispersion occurs along with the repulsion of both organic matter and soil inorganic solid surfaces at low pH (You et al., 1999).

3. Results and discussion 3.2. Assessment of heavy metals in wetland soils and floodplain sediments 3.1. Elemental composition of wetland soils and floodplain sediments The total oxide concentration values obtained in this study reflect the typical regolith composition developed in a humid tropical climate (Table 1). In the wetland soils, SiO2 and Al2O3 dominated, followed by Fe2O3 and TiO2. The oxides of Ca, Mg, Na, K and Mn are present in very small amounts or below the detection limit, indicating intense leaching. Losses of Fe2 O 3 were determined in the sub-superficial horizons, which are consistent with iron depletion in temporally hydromorphic environment (Vepraskas and Caldwell, 2008; Ewing et al., 2012). High levels of Fe oxides in topsoil can be related to Febinding organominerals created by temporary Fe-oxidation (Fe3 +) from reductible-Fe2 + by biological respiration (Schwertmann and Taylor, 1989). The geochemical composition of the floodplain sediments is similar to that of the wetland soils (Table 1), with a high amount of SiO2, Al2O3 and Fe2O3 and with low CaO, Na2O, K2O, MgO and MnO. It was observed in the field that the higher SiO 2 content in the sediments compared with the soil samples is due to the presence of thinner fragmented grains of quartz transported and deposited in the floodplains by river pulses. The source of sediments is the material deposited from the erosion of sandstones and lateritic soils, and both are widespread in the catchment. The range of OC content in the topsoil varies from 3.2 to 11.6% whereas it varies from 2.3 to 2.8% in the subsurface horizons (Table 1). Organic carbon concentrations in the sediments are lower than 1.4 g kg − 1 . As expected, the wetland soils store more soil organic carbon than the sediments, and this is due to the soil formation under anaerobic conditions which restricts the decomposition of organic matter (Page et al., 2011). The pH in the topsoil was slightly more acidic than in the sub-superficial horizons (Table 1). The lower pH values at the topsoil are related to the larger amount of OC near surface. Usually, low pH values (b 5) are accompanied by high

3.2.1. Heavy metal pollution Comparing our results (Table 2) with the pedogeochemical background (Marques et al., 2004a) and the threshold values for soil quality (CONAMA, 2009), all values gathered in this study for heavy metals are smaller than the reference values, except for Cr. It is expected that soils developed after long-term chemical weathering in sandstone are composed mostly by quartz and present low concentration of heavy metals when compared with weathered basic and ultrabasic rocks. Geogenic heavy metal content in soils is dependent initially on the geological sources, while their distribution in the landscape is dependent upon geomorphology and hydrology (Miller, 1997; Burak et al., 2010). In the flat and old plateaus of the Central Brazil, soils are enriched by secondary residual products of weathering such as goethite, hematite, gibbsite and kaolinite and by heavy metals with 3+ valences (Ti, Cr, La and V) due to the presence of resistant materials or secondary minerals (Marques et al., 2004a,b). This explains the high concentration values gathered for Cr in our study. Table 2 shows the mean concentrations of As, Ba, Pb, Cu, Cr, Ni, V and Zn in the topsoil and the sub-superficial horizons of wetland soils and floodplain sediments in the study area. Overall, the heavy metals in the soil samples showed higher concentrations than those determined from the pedogeochemical background for As and Cu (all samples) and for Pb, Cr, Ni, V and Zn (with some samples). In the floodplain sediments, high concentrations of As, Ba and Cu were observed for all samples, and high concentrations of Pb, Cr, Ni and Zn were determined at some samples. Compared with the soil quality guidelines (Table 2), 100% of the soil samples showed As concentration above the threshold value (VP) whereas one sample (P3) exceeded the intervention values. Forty percent of samples exceeded the threshold values for Cu and 60% for Cr, whereas 40% of samples were above the background values for Pb, 60% for Cu, 100% for Cr and 20% for Ni. In the floodplain sediments, 100% of samples showed concentrations of As above the background

Table 1 Total oxides, organic carbon and pH determined in the topsoil (0–30 cm) and subsurface (50–60) samples of the studied wetlands and in the sediment samples of the floodplains (0–10 cm) of the Uberabinha River. Sample

Wetlands/horizon type

Depth (cm)

Total Oxides (%)a SiO2

Al2O3

Fe2O3

CaO

MgO

TiO2

P2O5

Na2O

K2O

MnO

pH

OC (%)

P1 P1 P2 P2 P3 P3 P4 P4 P5 P5

Topsoil Subsurface Topsoil Subsurface Topsoil Subsurface Topsoil Subsurface Topsoil Subsurface

0–30 50–60 0–30 50–60 0–30 50–60 0–30 50–60 0–30 50–60

43.3 46.4 23.9 27.7 21.2 26.6 22.0 38.8 – –

27.8 33.4 36.8 38.3 33.7 36.9 32.5 36.3 – –

3.2 2.0 11.5 8.6 17.2 10.3 17.3 4.0 – –

n.d. n.d. 0.07 0.01 0.09 0.02 0.03 n.d. – –

n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. – –

2.51 2.74 2.6 2.6 2.3 2.6 1.9 2.8 – –

0.09 0.04 0.11 0.09 0.13 0.10 0.15 0.06 – –

n.d. n.d. n.d. n.d. n.d. n.d. n.d. n.d. – –

0.04 0.03 0.05 0.03 0.06 0.03 0.08 0.03 – –

n.d. n.d. 0.02 n.d. n.d. n.d. n.d. n.d. – –

4.8 5.1 4.7 5.8 4.8 5.0 4.5 5.3

3.2 2.5 3.9 2.3 7.4 3.3 11.6 2.8 – –

Sediments P6 P7 P8 P9 P10 P11 P12 P13

Surface Surface Surface Surface Surface Surface Surface Surface

0–10

74.4 – 69.4 76.6 77.8 70.5 – –

10.9 – 10.0 6.1 4.9 8.8 – –

3.5 – 8.3 9.3 9.3 10.4 – –

0.05 – 1.33 0.21 0.16 0.19 – –

n.d. – 0.4 0.1 0.1 0.1 – –

3.3 – 1.9 3.4 3.9 4.0 – –

0.08 – 0.21 0.14 0.12 0.18 – –

n.d. – 0.12 n.d. n.d. n.d. – –

0.03 – 0.25 0.07 0.06 0.09 – –

0.03 – 0.08 0.08 0.1 0.09 – –

5.3

1.2 – 1.4 0.5 0.5 0.5 – –

a

– 0–10 0–10 0–10 0–10 0–10 0–10

Average of three samples; n.d. = not detectable, under detection limit of the method; – = no data available; OC = organic carbon.

5.1 5.3 5.3 5.3

12.6 13 99.6 39 n.d. 8 45.6 30 155 122 16.6 8.3 111 97.3 38 27.3

P13

n.d. 190.3 20.3 32.6 120 19.3 19.6 42.6

P12

14.3 61 8 36 17.6 7.3 29.6 15.6

P11

13.5 64.3 10.6 49 39.6 15 53.3 26.6

P10

10 49 10 15.8 28.3 7 27.6 15.3 20 21.6 n.d. 31.6 111 7.3 250.6 26.3

mg·kg−1

12 48.3 17.3 28.6 31 11.3 34 18.3

15 50 n.d. 64.6 36 12.3 44 20.6

P9 P8

n.d. 19 30 20 9 15 11.3 11.6 n.d. 34.6 50.3 n.d. 46.6 36.6 85.3 30.6 145.6 43.6 58.6 113 7 17.3 11.3 8 178 113.3 151.6 235.6 5 35.3 22.6 23.3 23.6 35 n.d. 45.6 118.3 7.3 291.6 36.3 22.3 24.3 n.d. 36 118 8 272 35 mg·kg−1

n.d. = not detectable, under detection limit of the method. a CONAMA (2009). b Marques et al. (2004a,b). c Wetlands and sediments.

As Ba Pb Cu Cr Ni V Zn

mg·kg−1

3.5 75 17 35 40 13 275 60

(VP)

15 150 100 60 75 30 – 300

(VI)

25 300 200 100 300 50 – 500

n.d. 33 ± 38 9±6 10 ± 8 118 ± 76 8±5 175 ± 79 22 ± 9

16.6 19.6 15.6 14.3 33.6 14.6 18.3 12.1 81 55.6 72.1 88 96 99.5 63.6 6 9 15.3 139 150.6 104 9.3 18.3 21.6

P7 P6

Sediments

P5 P4 P3 P2 P1

Subsurface

P5 P4 P3 P2 Topsoil

P1

Determined valuesc

Pedogeochemical backgroundc Intervention Valuesb Threshold valuesb Elementsa Background valuesb

Table 2 Guiding values for agricultural soils for Brazil established by CONAMA (2009), background values of the trace element geochemistry for soil from sandstone of the study area region as proposed by Marques et al. (2004a,b), and medium values determined in the topsoils and subsurface of the wetlands (samples from P1 to P5) and floodplains (samples from P6 to P14) of the study area region.

V. Rosolen et al. / Catena 128 (2015) 203–210

207

level, 10% for Ba, 40% for Cu (one sample in P8 exceeded the threshold value) and 50% for Ni. The threshold level was exceeded in approximately 30% of samples for Ni. The VP contamination level indicates that for samples with heavy metal concentration above the VP value, significant effects are expected on the majority of soil and sedimentdwelling organisms. As the first estimation of the level of soil toxicity, the concentrations of As, Cr and Cu in the studied soil samples indicate major environmental and ecological risks. The high values for these metals can be associated with agrochemical inputs (Stigliani, 1988; Ahlf and Förstner, 2001; Gao et al., 2013; Xiao et al., 2013). These studies show that usually agricultural soil and river sediments usually receive and store large amount of heavy metals and organic pesticides, which are present as insoluble products or as sorbed entities on the surfaces of soil substrates. In Europe, for instance, heavy metals commonly found in agricultural soils include Cd, Cr, Cu, Hg, Ni, Pb and Zn (Stigliani, 1988). The associated ecological risk due to the presence of these heavy metals is well documented (Pedersen et al., 1998; Bai et al., 2010; Xiao et al., 2013). Applying the nonparametric Wilcoxon's test (p significant at 5% indicates the concentrations obtained in soil and sediment samples are higher than the quality guideline values), the elements As, Cu and Cr showed significant differences when compared with the quality guideline reference values (Table 3). As and Cu exceed the background reference values for all samples, and Cr exceeded the background value only in the topsoil. These metals have been added to pesticides and phosphate fertilizers which are applied to fields (Bjerregaard and Andersen, 2007; Kelepertzis, 2014) therefore agriculture is indeed the source of these heavy metals. It should be stressed that As and Cr are heavy metals that are not essential to living organisms and are of particular concern as soil pollutants (Adriano et al., 2004). Normally, the presence of As and Cr in soils and sediments is due to their high affinity for binding to organic chelators, such as humic and fulvic substances and clay minerals (Bjerregaard and Andersen, 2007). Arsenic may be present in organometallic forms, which are an active ingredient in pesticides added to soils through the use of synthetic fertilizers and As-based pesticides (Campos, 2007). Additionally, other mineralogical and chemical characteristics of soils and sediments contribute to their ability to fix heavy metals. The presence of Fe and Al (hydr)oxides-bearing minerals (e.g., goethite, hematite and gibbsite) in the soil and floodplain sediment samples (Table 1) can lead to the formation of insoluble and stable Fe and Al-heavy metal complex, as reported by Schwertmann and Taylor (1989). The above explanation helps to clarify the high amounts of these two heavy metals in collected samples. Comparison between our results and literature values was made (Table 4), showing that the mean concentration of heavy metals for the floodplain sediment samples was all below the average concentration values for a number of case studies around the world. The same trend was observed for the topsoil samples, except for Cr and Cu which showed mean concentration values above the average concentration values calculated for other locations. This comparison indicates Table 3 Nonparametric Wilcoxon's test comparing the trace elements in the topsoil and the subsurface horizons in the wetlands and in the floodplain sediments with the guiding values of CONAMA (2009). Elementsa

Wetland — topsoil

Wetland — subsurface

Sediment

As (3.5) Ba (75) Pb (17) Cu (35) Cr (40) Ni (13) V (275) Zn (60)

p = 0.001⁎ p=1 p = 0.46 p = 0⁎

p = 0.0011⁎ p=1 p = 0.46 p = 0⁎

p = 0.0075⁎ p = 0.87 p=1 p = 0.0455⁎

p = 0.2676 p = 0.9918 p=1 p=1

p = 0.1379 p = 0.7852 p=1 p=1

p = 0.0019⁎ p = 0.9861 p = 0.99 p=1

a Background reference. ⁎ Significant at 5%.

208

V. Rosolen et al. / Catena 128 (2015) 203–210

Table 4 Mean value of heavy metal concentration (mg·kg−1) in soil and sediment samples from different locations. Region

As

Ba

Cr

Cu

Ni

Pb

V

Zn

References

Soil 1. Yilong Lake, China 2. Pearl River Estuary, China 3. Baiyangdin Lake, China Average Uberabinha catchment, Brazil

16.12 – 38.37 27.25 19.54

– – – – 24.36

– 91.42 81.33 86.38 98.96

34.25 47.44 43.02 41.57 59.46

– 41.16 43.85 42.51 9.12

38.87 44.86 30.72 38.15 37.13

– – – – 191.44

82.71 158.83 128.76 123.43 24.1

Bai et al. (2010) Bai et al. (2011) Gao et al. (2013)

Sediment 1. Luan River, China 2. Baiyangdin wetland ecosystem, China 3. Yangtze River basin, China 4. Campania region, Italy 5. Nile River, Egypt 6. Ganges River, India Average Uberabinha catchment, Brazil

5.15 24.8 25.86 7.18 – – 15.75 12.5

– – – 193.31 – – – 49.75

71.47 84.00 77.19 24.18 191.00 176 103.97 92.80

47.98 35.00 59.06 38.90 25.00 60.33 44.38 38.33

– – – 23.21 34.00 47.33 34.85 11.00

22.11 30.00 37.75 31.69 – 30.33 30.38 8.66

– – – 47.61 246.00 – 146.81 63.00

78.22 112.00 148.81 89.27 59.00 119 101.05 38.00

indeed that Cr and Cu pose risk to soil contamination and confirms the risk of contamination detected by comparing our results with the soil quality guideline values (Table 2). 3.2.2. Comparative distribution of heavy metals in topsoil and sub-subsurface horizons of wetlands Table 5 indicates significant accumulation (p b 0.05) of Ba, Ca, Cu, Fe, K, Mg, P, Sr, Ti, Zn and Zr in the topsoil samples. Among these elements, P, K, Ca, Mg, Cu, Fe and Zn are usually added to the soil as macro- and micro-nutrients for plants (van Raij, 2011). Thus their high concentrations in the topsoil samples are attributed to mineral fertilization. Most of these elements can be fixed in soil organic matter (SOM) which has a direct impact on element uptake (Bai et al., 2011; Chrastný et al., 2012). Thus the concentration of these elements should have increased in the topsoil in association with SOM. On the other hand, our results suggest that As, Cr, Mn, Ni and V partially migrated from the topsoil to the sub-superficial mineral horizon through soil solution therefore these metals were not strongly fixed by insoluble soil organic matter. This may be explained by the mobility of metals which is influenced by complexation reactions with organic ligands. The complexation reactions can either increase or decrease metal sorption on mineral surfaces (Güngör and Bekbölet, 2010). At low pH (b 5), the predominant DOM fraction is fulvic acid (You et al., 1999), which is able to form more soluble and mobile metal complexes due to its high content of the carboxylic functional group (Benedetti et al., 1996). Therefore, the solubility of organic matter fractions and associated heavy metals at low pH conditions explains the migration of As, Cr, Mn, Ni and V down the soil profile. Although this explanation is likely, Bai et al. (2011) and Gao et al. (2013) report that there is no evidence of linkage between heavy metals present in soils and sediment and soil organic matter. So, further investigation on the association between heavy metals and SOM is needed to better understand the behavior of heavy metals in the environment. In addition to SOM, other soil properties such as pH, the capacity of sorption of the clay minerals and ionic strength, should be considered (Güngör and Bekbölet, 2010). If it accounts for the role of kaolinite (predominant secondary mineral in the study area), its sorption capacity of heavy metals increases with increasing pH (up to pH 5.7 and 6.0 for Cu

Present study

Liu et al. (2009) Su et al. (2011) Yi et al. (2011) Albanese et al. (2007) Devok et al. (1977) Singh et al. (2003) Present study

and Pb; and pH 7.3 and 8.0 for Zn and Cd in the single-element systems, respectively) (Srivastava et al., 2005). This is an interesting finding as reducing conditions dominate in wetland soils which usually lead to an increase of pH and thus sorption of heavy metals onto kaolinite. 3.2.3. Contamination index (Pi) for heavy metals One possible way for estimating the environmental hazard associated with heavy metals in soils is the use of a contamination index. Overall the wetland soils presented moderate levels of contamination (2 b Pi ≤ 3) ranked As N Cr N Cu in the topsoil as well as in the sub-superficial horizons. In the floodplain sediments, no contamination (Pi ≤ 1) or low level of contamination (1 b Pi ≤ 2) was observed, except for As and Cr at site P8 and Cr at sites P11, P12 and P13, which showed a moderate level of contamination (Table 6). The observed increase in the level of contamination is related to agriculture practices. Pesticides and fertilizers are usually applied at least twice a year in the study area. It is well known from extensive literature that wetlands have the tendency to be an initial barrier for nutrient and toxic elements that come from agrochemicals (e.g., Gathumbi et al., 2005). The results from this study support the assumption that tropical wetland soils are a sink for agrochemicals, particularly heavy metals. Our findings for the contamination indices were compared with the work done by Bai et al. (2010), which applied the same methodology for calculating the contamination index (Pi). Overall we found higher contamination indices than those reported by Bai et al. (2010) (Table 7). Despite the differences between the two study areas, the comparison indicates that the Cerrado wetlands have been negatively influenced by agricultural practices and this poses an environmental concern. 4. Conclusion The wetland soils examined exhibit an increase in integrated contamination indices when compared with the floodplain sediments. This finding suggests that the wetland soils are preferential areas for trapping and storing agrochemical residues. The studied wetland soils function as a sink for metals, and the concentration of As, Cr and Cu

Table 5 Comparative concentration of the chemical elements obtained in the topsoil and the subsurface horizons of the wetlands. Elements

Elements

As

Ba

Ca

0.4386

0.0001⁎

0.0201⁎

Na

Ni

P

Pb

Sr

Ti

V

Zn

Zr

1

0.7963

0.0098⁎

0.4386

0.0045⁎

0.0389⁎

0.7963

0.0045⁎

0.0389⁎

⁎ p b 0.05 indicates significant difference between horizons.

Cr

Cu

Fe

K

Mg

Mn

0.1967

0.0045⁎

0.0001⁎

0.0003⁎

0.0201⁎

0.1213

V. Rosolen et al. / Catena 128 (2015) 203–210 Table 6 Background, threshold and intervention values (Xa, Xb and Xc) for heavy metals in agriculture soil according CONAMA (2009) and the contamination index (Pi) calculated for topsoils and subsurface horizons of the soils of the wetlands and the sediments. Elements (mg·kg−1)

As

Ba

Pb

Cu

Cr

Ni

V

Zn

Xa Xb Xc

3.5 3.5 15

75 75 150

17 17 100

35 35 60

40 40 75

13 13 30

275 275 275

60 60 300

Pi topsoil P1 P2 P3 P4 P5

2.1 2.4 2.0 2.7 2.8

0.1 0.4 0.1 0.3 0.4

1.0 0.7 1.7 – –

1.8 2.3 2.7 1.0 1.4

2.0 2.1 1.6 2.1 2.1

0.4 0.6 1.1 0.6 0.5

0.5 0.5 0.3 0.9 –

0.1 0.1 0.3 0.5 0.6

Pi subsurface P1 P2 P3 P4 P5

0.0 2.4 3.5 2.5 2.5

0.1 0.2 0.2 0.2 0.3

0.0 1.2 1.4 0.0 0.0

1.5 1.1 2.6 0.9 0.9

2.3 1.1 1.5 2.2 2.2

0.5 1.3 0.9 0.6 0.6

0.6 0.4 0.6 0.9 0.9

0.1 0.6 0.4 0.4 0.4

Pi floodplain P6 P7 P8 P9 P10 P11 P12 P13

1.6 1.7 2.0 1.9 1.9 0.0 1.8 1.8

0.7 0.6 0.7 0.9 0.8 2.3 1.3 0.5

0.6 1.0 0.0 0.6 0.5 1.0 0.0 0.5

0.5 0.8 2.1 1.6 1.0 0.9 1.4 0.9

0.7 0.8 0.9 1.0 0.4 2.2 2.4 2.2

0.5 0.9 0.9 1.1 0.6 1.4 1.2 0.6

0.1 0.1 0.2 0.2 0.1 0.1 0.4 0.4

0.3 0.3 0.3 0.4 0.3 0.7 0.6 0.5

exceeded the pedogeochemical background and threshold effect level of the soil quality guideline reference values. This result is of great concern for wetland soils surrounded by agricultural fields, and it represents a major environmental risk for most wetlands found in the Cerrado Biome. Acknowledgments The authors wish to thank FAPEMIG (Fundação de Apoio à Pesquisa do Estado de Minas Gerais — Proc. no. CRA-APQ-01103-11) and FAPESP (Fundação de Amparo à Pesquisa do Estado de São Paulo — Proc. no. 24/ 03111-4) for supporting this work. References Adriano, D.C., Wenzel, W.W., Vangronsveld, J., Bolan, N.S., 2004. Role of assisted natural remediation in environmental cleanup. Geoderma 122, 121–142. Ahlf, W., Förstner, U., 2001. Managing contaminated sediments. Part I: improving chemical and biological criteria. J. Soils Sediments 2 (1), 30–36. Albanese, S.B.D., Lima, A., Cicchella, D., 2007. Geochemical background and baseline values of toxic elements in stream sediments of Campania region (Italy). J. Geochem. Explor. 93, 21–34. Bai, J., Yang, Z., Cui, B., Gao, H., Ding, Q., 2010. Some heavy metals distribution in wetland soils under different land use types along a typical plateau lake, China. Soil Tillage Res. 106, 344–348. Bai, J., Xiao, R., Cui, B., Zhang, K., Wang, O., Liu, X., Gao, H., Huang, L., 2011. Assessment of heavy metal pollution in wetland soils from the young and old reclaimed regions in the Pearl River Estuary, South China. Environ. Pollut. 159, 817–824. Benedetti, M.F., Van Riemsdijk, W.H., Koopal, L.K., 1996. Humic substances considered as a heterogeneous donnan gel phase. Environ. Sci. Technol. 30, 1805–1813. Bjerregaard, P., Andersen, O., 2007. Ecotoxicology of metals: sources, transport, and effects in the ecosystem. In: Nordberg, G.F., Vouk, V.B. (Eds.), Handbook on the Toxicology of Metals. Elsevier, California, pp. 251–280. Burak, D.L., Fontes, M.P.F., Santos, N.T., Monteriro, L.V.S., Martins, E.S., Becquer, T., 2010. Geochemistry and spatial distribution of heavy metals in Oxisols in a mineralized region of the Brazilian Central Plateau. Geoderma 160, 131–142.

209

Campos, V., 2007. Solubility and phytoextraction of arsenic from soil by two different fern species. In: Letcher, T.M. (Ed.), Thermodynamics, Solubility and Environmental Issues. Elsevier Science & Technology, pp. 229–243. Carpenter, S.R., Caraco, N.F., Correll, D.L., Howarth, R.W., Sharpley, A.N., Smith, V.H., 1998. Nonpoint pollution of surface waters with phosphorus and nitrogen. Ecol. Appl. 8, 559–568. Chrastný, V., Komárek, M., Procházka, J., Pechar, L., Vaněkd, A., Penížekd, V., Farkaš, J., 2012. 50 years of different landscape management in fluencing retention of metals in soils. J. Geochem. Explor. 115, 59–68. CONAMA — National Environmental Council, 2009. Resolução n° 420 de 2009. Critérios e valores orientadores de qualidade do solo agrícola quanto à presença de substâncias químicas e estabelece diretrizes para o gerenciamento ambiental de áreas contaminadas por essas substâncias em decorrência de atividades antrópicas. Eletronic update 2014. http://www.mma.gov.br/port/conama/ legiabre.cfm?codlegi=620. Corrêa, G.F., 1989. Les microreliefs “murundus” et leur environment pedologique dans l'ouest du Minas Gerais, region du plateau central bresilian. (Ph.D. Thesis). Université de Nancy I., France. Devok, V.M., Komy, Z., Araújo, F., Put, A.V., Grieken, R.V., 1977. Chemical composition of sediments, suspended matter, river water and ground water of the Nile (Aswan– Sohag traverse). Sci. Total Environ. 201, 195–210. Ewing, J.M., Vepraskas, M.J., Broome, S.W., White, J.G., 2012. Changes in wetland soil morphological and chemical properties after 15, 20, and 30 years of agricultural production. Geoderma 179, 73–80. Foley, J.A., Ramankutty, N., Brauman, K.A., Cassidy, E.S., Gerber, J.S., Johnston, M., Mueller, N.D., O'Conell, C., Ray, D.K., West, P.C., Balzer, C., Bennett, E.M., Carpenter, S.R., Hill, J., Monfreda, C., Polasky, S., Rockstron, J., Sheen, J., Siebert, S., Tilman, D., Zaks, D.P.M., 2011. Solutions for a cultivated planet. Nature 478, 337–342. Förstner, U., 2003. Geochemical techniques on contaminated sediments — river basin view. Part I: integrated water quality management: river basin approach. Environ. Sci. Pollut. Res. 10, 58–62. Gao, H., Bai, J., Xiao, R., Liu, P., Jiang, W., Wang, J., 2013. Levels, sources and risk assessment of trace elements in wetland soils of a typical shallow freshwater lake, China. Stoch. Env. Res. Risk A. 27, 275–284. Gathumbi, S.M., Bohlen, P.J., Graetz, D.A., 2005. Nutrient enrichment of wetland vegetation and sediments in subtropical pasture. Soil Sci. Soc. Am. J. 69, 539–548. Güngör, E.B.Ö., Bekbölet, M., 2010. Zinc release by humic and fulvic acid as influenced by pH, complexation and DOC sorption. Geoderma 159, 131–138. Hill, C.R., Robinson, J.S., 2012. Phosphorus flux from wetland ditch sediments. Sci. Total Environ. 437, 315–322. Hollander, M., Wolfe, D.A., 1973. Nonparametric Statistical Methods. Wiley, New York, p. 501. Kelepertzis, E., 2014. Accumulation of heavy metals in agricultural soils of Mediterranean: insights from Argolida basin, Peloponnese, Greece. Geoderma 221–222, 82–90. Laabs, V., Amelung, W., Zech, W., 1999. Pesticides in soil, sediments and water samples from a small microbasin in the Brazilian Cerrados. In: Thomas, R., Ayarza, M.A. (Eds.), Sustainable Land Management for the Oxisol of the Latin American Savannas: Dynamics of Soil Organic Matter and Indicators of Soil Quality. CIAT Publication 132, pp. 203–214 (Colombia). Laabs, V., Amelung, W., Pinto, A., Altstaed, A., Zech, W., 2000. Leaching and degradation of corn and soybean pesticides in an Oxisol of the Brazilian Cerrados. Chemosphere 14, 1441–1449. Liu, J., Li, Y., Zhang, B., Cao, J., Cao, Z., Domagalski, D., 2009. Ecological risk of heavy metals in sediments of the Luan River source water. Ecotoxicology 18, 748–758. Marques, J.J., Schulze, D.G., Curi, N., Mertzman, S.A., 2004a. Trace elements geochemistry in Cerrado soils. Geoderma 121, 31–43. Marques, J.J., Schulze, D.G., Curi, N., Mertzman, S.A., 2004b. Major element geochemistry and geomorphic relationships in Brazilian Cerrado soils. Geoderma 119, 179–195. Matiza, T., 1994. Wetlands in Zimbabwe: an overview. In: Matiza, T., Crafter, S.A. (Eds.), Wetlands Ecology and Priorities for Conservation in Zimbabwe: Proceedings of a Seminar on Wetlands of Zinbabwe. The IUCN Wetlands Programme. IUCN, Switzerland, pp. 3–10. Miller, J.R., 1997. The role of fluvial geomorphic processes in the dispersal of heavy metals from mine sites. J. Geochem. Explor. 58, 101–118. Myers, S.C., Clarkson, B.R., Reeves, P.N., Clarkson, B.D., 2013. Wetland management in New Zealand: are current approaches and policies sustaining wetland ecosystems in agricultural landscapes? Ecol. Eng. 56, 107–120. Nishiyama, L., 1989. Geologia de Uberlândia e arredores. Soc. Nat. 1, 9–16. Page, S.E., Rieley, J.O., Banks, C.J., 2011. Global and regional importance of the tropical peatland carbon pool. Glob. Chang. Biol. 17, 798–818. Pedersen, F., Sj Brnestad, E., Andersen, H.V., Kj Lholt, J., Poll, C., 1998. Characterization of sediments from Copenhagen harbour by use of biotests. Water Sci. Technol. 37, 233–240. Rosolen, V., Oliveira, D.A., Bueno, G.T., 2014. Vereda and murundu wetlands and changes in Brazilian environmental laws: challenges to conservation. Wetl. Ecol. Manag. http://dx.doi.org/10.1007/s11273-014-9380-4 (Online First).

Table 7 Comparison between soil contamination indices calculated for two different locations. Region

As

Ba

Cr

Cu

Ni

Pb

V

Zn

References

1. Yilong Lake, China 2. Uberabinha catchment, Brazil

Low Moderate

– No

– Moderate

No Moderate

– No

No Low

– No

No No

Bai et al. (2010) Present study

210

V. Rosolen et al. / Catena 128 (2015) 203–210

Schwertmann, U., Taylor, R.M., 1989. Iron oxides. In: Dixon, J.B., Weed, S.B. (Eds.), Minerals in Soil Environments. Soil Sci Soc Am, Madison, pp. 379–438. Singh, K.P., Mohan, D., Singh, D.K., Malik, A., 2003. Studies on distribution and fractionation of heavy metals in Gomti river sediments—a tributary of the Ganges, India. J. Hydrol. 312, 14–27. Srivastava, P., Singh, B., Angove, M., 2005. Competitive adsorption behavior of heavy metals on kaolinite. J. Colloid Interface Sci. 290, 28–38. Stigliani, W.M., 1988. Changes in valued “capacities” of soil and sediments as indicators of non-linear and time-delayed environmental effects. Environ. Monit. Assess. 10, 245–307. Su, L., Liu, J., Christensen, P., 2011. Spatial distribution and ecological risk assessment of metals in sediments of Baiyangdian wetland ecosystem. Ecotoxicology 20, 1107–1116. van Raij, B., 2011. Fertilidade dos solos e manejo de nutrientes. IPNI, Piracicaba, p. 420. Vepraskas, M.J., Caldwell, P.V., 2008. Interpreting morphological features in wetland soils with a hydrologic model. Catena 73, 153–165.

von der Heyden, C.J., New, M.G., 2003. The role of a dambo in the hydrology of a catchment and the river network downstream. Hydrol. Earth Syst. Sci. 7, 339–357. Williams, T.P., Bubb, J.M., Lester, J.N., 1994. Metal accumulation within salt marsh environments: a review. Mar. Pollut. Bull. 28, 277–290. Xiao, R., Bai, J., Huang, L., Zhang, H., Cui, B., Liu, X., 2013. Distribution and pollution, toxicity and risk assessment of heavy metals in sediments from urban and rural rivers of the Pearl River delta in southern China. Ecotoxicology 22, 1564–1575. Yi, Y., Yang, Z., Zhang, S., 2011. Ecological risk assessment of heavy metals in sediment and human health risk assessment of heavy metals in fishes in the middle and lower reaches of the Yangtze River basin. Environ. Pollut. 159, 2575–2585. You, S.J., Yin, Y., Allen, H.E., 1999. Partitioning of organic matter in soils: effects of pH and water/soil ratio. Sci. Total Environ. 227, 155–160. Zedler, J.B., Kercher, S., 2005. Wetland resources: status, trends, ecosystem services, and restorability. Annu. Rev. Environ. Resour. 30, 39–74.