Small scale variability of chlorinated POPs in the river Elbe floodplain soils (Germany)

Small scale variability of chlorinated POPs in the river Elbe floodplain soils (Germany)

Chemosphere 79 (2010) 745–753 Contents lists available at ScienceDirect Chemosphere journal homepage: www.elsevier.com/locate/chemosphere Small sca...

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Chemosphere 79 (2010) 745–753

Contents lists available at ScienceDirect

Chemosphere journal homepage: www.elsevier.com/locate/chemosphere

Small scale variability of chlorinated POPs in the river Elbe floodplain soils (Germany) Kristian Kiersch a,*, Gerald Jandl a, Ralph Meissner b, Peter Leinweber a a b

Institute for Land Use, University of Rostock, Justus-von-Liebig-Weg 6, D-18051 Rostock, Germany UFZ – Helmholtz Centre for Environmental Research, Department of Soil Physics, Lysimeter Station, Dorfstrasse 55, D-39615 Falkenberg, Germany

a r t i c l e

i n f o

Article history: Received 7 September 2009 Received in revised form 18 January 2010 Accepted 21 February 2010 Available online 26 March 2010 Keywords: Pesticides Persistent organic pollutants Fluvisol Phytoremediation MASE

a b s t r a c t The long-time use of persistent organic pollutants (POPs) led to a world-wide contamination of environmental compartments. Although, bans of numerous POPs reduced the POP input to rivers. Floodplain soils are still highly contaminated, because they are sinks for these compounds, which restrict their agricultural use. Hence, the intention of this study was the determination of 29 relevant POPs in two soil depths (0–10 cm and 10–20 cm) of a field experiment to get a survey on the small-scale spatial variability of the experimental site and to establish a baseline for phytoremediation experiments. The POP concentrations ranged from 0.1 lg kg1 to 160 lg kg1 and showed an increase of dieldrin, endrin, endosulfan I, endosulfan II, heptachlor, p,p0 -DDE, o,p0 -DDE and methoxychlor concentrations on average in the river Elbe floodplains between the years 1998 and 2007. However, there was a pronounced small-scale spatial variability of POP concentrations in vertical and horizontal direction. The latter was estimated by comparing the relative standard deviations (RSDs) of the POP concentrations in sample sets located at sites of increasing distance from <1 m to >10 000 m. Ó 2010 Elsevier Ltd. All rights reserved.

1. Introduction The widespread use of persistent organic pollutants (POPs) led to a ubiquitous contamination of all environmental compartments (Cotham and Bidleman, 1991). Main pathways to soil are the dry and wet deposition of gaseous and particular materials (Himel et al., 1990; Cotham and Bidleman, 1991). Floodplain soils may be contaminated by the deposition of POP enriched sediments which originate from particulate matter in river water (Götz et al., 1994). Enrichment of POPs in floodplain soils and their ability for biomagnification restrict the agricultural use for arable or grassland (Faroon et al., 2000). Therefore, techniques are required to remediate contaminated floodplain soils and possible approaches are the complete removal of the contaminated soil (Hourdakis et al., 2000) or the bioremediation by crops, i.e., phytoremediation (Saier and Trevors, 2010; Wenzel, 2008). For experimental or practical remediation projects detailed knowledge of the concentrations and the spatial distribution of the numerous POPs are essential prerequisites. The floodplain soil of the river Elbe is one of the most strongly contaminated in Central Europe because of agriculture, forestry, mining, pulp and chemical industry activities in the river Elbe catchment (Thieken, 2001). Especially the chemical industry increased the contamination by the input of by-products of the synthesis of dichlorodiphenyltrichloroethane (DDT) and hexachlorocyclohex* Corresponding author. Tel.: +49 381 498 3190; fax: +49 381 498 3122. E-mail address: [email protected] (K. Kiersch). 0045-6535/$ - see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.chemosphere.2010.02.041

ane (HCH), which led to high POP concentrations in the river Elbe sediments (Kalbitz and Popp, 1999; Thieken, 2001; Franke et al., 2005). Previous investigations showed POP concentrations on single points along the river Elbe catchment (Witter et al., 1998, 2003; Thieken, 2001; Franke et al., 2005; Götz et al., 2006). However, the concentrations of individual POPs reported in these publications varied by factor up to 430. Furthermore, Witter et al. (2003) reported decreased POP concentrations downwards the soil profile at one site and the opposite in the soil 44 km away along the river Elbe. It can be hypothesised that spatial variability at the small- and medium-scale may be one reason for the differences in POP concentrations reported so far. Detailed knowledge of the small scale variability is also a precondition for the planning and setup of phytoremediation field experiments. Therefore, the objective of the present study was to determine the concentrations of 29 relevant POPs in experimental plots of a floodplain soil of the river Elbe at soil depths of 0–10 cm and 10– 20 cm as a prerequisite for subsequent success control of phytoremediation experiments.

2. Materials and methods 2.1. Site and sampling The experimental site Schönberg, Deich is situated near the town Wittenberge (Brandenburg, Germany) between river Elbe

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kilometer 435 and 440 in a flood channel running parallel to the river Elbe in a distance of 100 m (Fig. 1). The soil was classified as Norm-Vega according to the German Classification System (AG Boden, 2008) and as Fluvisol according to the World Reference Base for Soil Resources (FAO/UNESCO, 1998). The annual mean (1977–2006) of temperature was 8.5 °C and the mean of precipitation was 588 mm. The experimental site is periodical flooded ones to twice per year for up to two months and 2 m water head with sedimentation rates of up to 405 g cm2 (Krüger et al., 2005, 2006). The experimental site is divided in eight subsequently following plots of each 3  3 m. These are grown

with grass, and different clones of willows and poplar were planted in autumn 2005 for a phytoremediation experiment. Four samples were taken per plot at depths of 0–10 cm and 10–20 cm. The samples were collected in spring 2007, immediately air-dried for 48 h and sieved to <2 mm (Hüttig et al., 2004; Mamontov et al., 2004). 2.2. Texture and chemical analyses The soil texture was determined by wet-sieving and sedimentation according to the Koehn-Pipette method (Schlichting et al., 1995). The concentrations of C, N and S were determined by an

Fig. 1. Map of the river Elbe catchment and the scale-up of the sampling site (insert lower left), which is located between two flood abandoned channels. The sampling site is flooded once or twice a year in spring and autumn.

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elemental analyzer (Vario EL Fa. Foss Heraeus, Hanau, Germany). The soil pH was determined in 0.01 M CaCl2 at a soil:solution ratio of 1:2.5. For extraction of the POPs, 25 mL n-hexane/acetone (1:1, v/v) were added to 5 g of soil sample for microwave accelerated solvent extraction (MASE) (Molins et al., 1997). The MASE was done at 800 W by heating from ambient temperature to 110 °C in 20 min, holding this temperature for 15 min and cooling down to ambient temperature in 30 min as described in the US EPA-Method 3546 adapted for the Mars Xpress microwave (CEM, Kamp-Lintfort, Germany). The filtered extracts were treated with a tetrabutylammonium sulfite reagent to clean the extracts from elemental S (Jensen et al., 1977). For the clean-up of the matrix components a solid phase extraction (SPE) with a Florisil phase was used (Le Calvez et al., 2002). The POPs were determined using a G1530A (Agilent Technologies, Santa Clara, USA) gas chromatograph with two parallel capillary columns with different polarities, each equipped with an electron capture detector (ECD). The capillary columns DB-1701P (0.25 lm of 14% cyanopropylphenyl- and 86% dimethylpolysiloxane) with 60 m length and an inner diameter of 0.25 mm and the DB-5MS (0.25 lm of 5% diphenyl- and 95% dimethylpolysiloxane) with 60 m length and an inner diameter of 0.25 mm were used. The gas chromatograph was equipped with a pulsed split/splitless – injector at 280 °C. The pulsed pressure mode of the carrier gas helium 5.0 operated at 350 kPa for 3 min was followed by a reduction to a constant pressure of 200 kPa to complete the analysis. The ECDs at 280 °C (DB-1701P) and 325 °C (DB-5MS) worked both with nitrogen as make-up gas with a volumetric flow of 20 mL min1. The temperature program started at 150 °C for 1 min, than ramped to 240 °C at 3 °C min1, held for 5 min and finally ramped to 280 °C at 4 °C min1 with a final hold of 44 min. All POPs were identified and calibrated with external standards from ULTRA SCIENTIFIC (Kingstown, USA) in the range from 0.0001 lg mL1 to

0.1 lg mL1. The POPs were quantified after separation by both used columns, whereas the lower resulting concentrations of each compound were selected to exclude co-elutions. The amounts of the known on-column degradation of DDT and endrin were quantified by single standard analyses. The resulting degradation product were quantified and considered for the quantification of the POPs. The limit of quantification (LOQ) was calculated for each POP depending on the standard deviation of the blank and displayed in Table 3. Spiking experiments with 2 mL of 0.1 lg mL1 of each POP to the appropriate mass of soil (5 g) for the extraction resulted in recoveries from 42% (p,p0 -DDT) to 110% (cis-chlordan), with an average of 80%. This agreed with the described completeness of the MASE extraction from 81% to 116% of fresh and aged soil samples (Lopez-Avila et al., 1995). A subset of samples was analysed by GC/MS (Trace GC Ultra/ DSQ, Thermo Fisher Scientific, Waltham, USA). The DB-5MS capillary column with 60 m length and an inner diameter of 0.25 mm was used. The injection was done with a split ratio of 1:10 at 280 °C and a constant flow of 1.5 mL min1 during the whole measurement. The temperature program started at 50 °C for 1 min, than ramped to 120 °C at 40 °C min1 and finally ramped to 280 °C at 4 °C min1 with a final hold of 25 min. Single masses for the identification of the POPs in the SIM mode, as described by Arend (2002), Esteve-Turrillas et al. (2005) and Yagoh et al. (2006), were completed by a second characteristic mass for each compound chosen from library mass spectra: HCHs: m/z 217, 219; PCB 28: m/z 256, 258; PCB 52: m/z 290, 292; PCB 101: m/z 324, 326; PCB 138 and PCB 153: m/z 360, 362; PCB 180: 394, 396; aldrin: m/z 263, 293; dieldrin: m/z 263, 277; endrin: m/z 263, 281; endosulfan I and endosulfan II: m/z 277, 339; endosulfan sulfate: m/z 272, 387; cis- and trans-chlordan: m/z 373, 375; heptachlor and mirex: m/z 272, 274; DDTs and DDDs: m/z 235, 237; DDEs: m/z 246, 248; HCB: m/z 284, 286; quintozene: m/z 237, 295; methoxychlor: m/z 227, 229. Thus, GC/MS confirmed the identification of the 29 POPs obtained by the dual column GC/ECD. 2.3. Statistical data evaluation

Table 1 Soil texture at two sampling depths and their relative standard deviations (RSDs). Plot

Clay (<0.002 mm) (%)

Silt (0.002–0.063 mm) (%)

Sand (0.063–2 mm) (%)

0–10 cm 10–20 cm 0–10 cm

10–20 cm

0–10 cm 10–20 cm

39 39 39 37 34 38 29 30

39 30 29 22 23 25 24 34

50 50 46 47 46 44 48 56

46 34 43 31 27 33 32 35

11 11 15 16 20 18 23 15

15 36 28 47 50 42 45 31

RSD (%) 12

22

7.8

18

27

32

P1 P2 P3 P4 P5 P6 P7 P8

Linear regression between the concentrations of C, N, S, pH, clay, silt, sand and the POP were established. The significance of the regression is indicated as follows: p 6 0.05, p 6 0.01,  p 6 0.001) (STATISTICA 6.0, StatSoft Inc., 2001). 3. Results and discussion 3.1. Basic soil characteristics On average of all samples, the soil texture (Table 1) at the depth of 0–10 cm consisted of (36 ± 4.0)% clay, (48 ± 3.5)% silt and (16 ± 4.1)% sand. At the depth of 10–20 cm the soil had on average

Table 2 Concentrations of organic C, total N, total S and the pH values in the plots under study and their RSDs. Plot

Organic C (g kg1)

N (g kg1)

S (g kg1)

pH

0–10 cm

10–20 cm

0–10 cm

10–20 cm

0–10 cm

10–20 cm

0–10 cm

10–20 cm

P1 P2 P3 P4 P5 P6 P7 P8

82 85 80 79 70 67 81 87

68 40 37 26 27 27 26 32

6.6 6.7 6.2 6.2 5.9 5.2 6.3 6.6

4.9 3.3 3.1 2.4 2.9 2.3 2.2 2.6

2.2 2.3 2.1 2.2 1.6 1.7 2.1 3.0

2.0 1.3 1.3 0.9 0.7 0.7 0.7 0.8

5.5 5.6 5.4 5.5 5.5 5.4 5.4 5.6

5.7 5.8 5.7 5.8 5.7 5.7 5.7 5.8

RSD (%)

8.8

40

7.9

30

19

43

1.6

0.9

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Table 3 Individual POP concentrations and limits of quantification (LOQ) in the plots at the sampling depth 0–10 cm at the experimental sites Schönberg, Deich in comparison with published data from other river Elbe floodplains. POP (lg kg1)

a-HCH b-HCH c-HCH d-HCH PCB 28 PCB 52 PCB 101 PCB 138 PCB 153 PCB 180 Aldrin Dieldrin Endrin cis-Chlordane trans-Chlordane Heptachlor p,p0 -DDT p,p0 -DDD p,p0 -DDE o,p0 -DDT o,p0 -DDD o,p0 -DDE HCB Mirex Endosulfan I Endosulfan II Endosulfan sulfate Quintozene Methoxychlor

LOQ (lg kg1)

0.022 0.017 0.052 0.11 0.050 0.052 0.032 0.057 0.048 0.064 0.022 0.033 0.12 0.027 0.025 0.052 0.27 0.076 0.035 0.346 0.041 0.037 0.013 0.021 0.033 0.047 0.088 0.019 0.80

Schönberg, Deich

Elbe

1

2

3

4

5

6

7

8

Min.

Max.

9.5 17 4.4 6.6 5.5 4.6 1.6 27 16 8.9 3.0 1.8 0.89 1.6 1.5 17 25 99 25 60 84 16 96 1.8 1.6 10 6.4 3.0 53

6.0 14 3.1 5.1 3.5 5.1 1.2 15 14 5.8 1.9 2.2 1.4 0.93 0.90 13 15 85 19 35 68 12 84 1.2 1.2 8.6 5.2 24 22

11 15 3.6 6.9 3.4 4.9 1.3 22 17 6.5 3.9 3.3 2.2 1.3 1.6 8.1 27 99 22 31 87 18 79 1.3 1.3 4.9 4.7 9.2 23

9.8 17 2.7 3.8 3.5 4.1 1.4 17 18 8.9 2.3 1.4 1.6 1.4 1.7 8.8 31 110 24 36 110 19 85 1.1 1.3 6.5 6.2 4.9 15

8.7 13 2.9 4.6 3.7 4.4 1.2 18 15 7.0 2.7 2.4 3.5 1.2 1.0 14 19 82 20 44 86 16 85 1.7 1.1 9.8 4.1 2.1 16

6.0 16 2.0 2.8 3.8 4.1 1.3 20 16 8.4 2.5 1.4 1.7 1.4 0.099 16 34 92 22 45 89 17 83 1.6 1.1 9.1 4.2 3.3 25

10 14 2.3 4.7 3.6 4.7 1.2 10 17 8.2 2.9 2.2 1.9 1.5 1.2 12 20 85 21 16 96 15 83 0.64 0.79 8.1 1.0 3.1 10

11 15 1.2 5.4 4.3 4.8 1.2 13 15 7.9 3.5 1.8 2.5 1.2 0.68 7.1 53 110 21 28 110 16 82 0.47 0.55 12 1.5 2.0 14

<1a <1a <1a,b <1a <1b,c 1.0b 2.0b 4.0b 4.0b 2.0b <1b <1b <1b n.d.a. n.d.a. <1b <1c 6.0b 2.0b n.d.a. 5.0b <1b 7.0b n.d.a. <1b <1b n.d.a. n.d.a. <1b

52c 92c 9.0c 25c 10b 21b 10b 40c 20c 36c 4.0b n.d.a. n.d.a. n.d.a. n.d.a. n.d.a. 430c 460c 17b n.d.a. 96b n.d.a. 810b n.d.a. n.d.a. 7.0b n.d.a. n.d.a. n.d.a.

n.d.a. – no data available. a Götz et al. (2006). b Witter et al. (1998). c Witter et al. (2003).

less clay (28 ± 5.7)% and silt (35 ± 6.0)% but more sand (37 ± 11)% than at the upper depth. The pH (Table 2) was on average slightly but significant lower at 0–10 cm (5.5 ± 0.1) than at 10–20 cm (5.7 ± 0.1). The acidity of soil at both depths confirmed the absence of carbonate so that the concentrations of total C corresponded to the concentrations of Corg (Table 2), which were (79 ± 6.9) g kg1 at 0–10 cm and (35 ± 14) g kg1 at 10–20 cm. Comparable concentrations of Corg were determined by Witter et al. (2003) at soil depths of 0– 10 cm (from 20 g kg1 to 103 g kg1) and 10–20 cm (from 20 g kg1 to 54 g kg1) at other sites of the river Elbe floodplains, which were investigated for POPs. The average N concentrations (Table 2) were larger at 0–10 cm (6.2 ± 0.5) g kg1 than at 10–20 cm (3.0 ± 0.9) g kg1. Furthermore, the S concentration (Table 2) was (2.2 ± 0.4) g kg1 at 0–10 cm and decreased to (1.0 ± 0.5) g kg1 at 10–20 cm. The constantly larger organic C, total N and total S concentrations at the upper depth indicated an enrichment of soil organic matter (SOM) in the topsoil. 3.2. Concentrations of persistent organic pollutants (POPs) Most of the POP concentrations were below 20 lg kg1 at both depths, except for most DDX, HCB and methoxychlor. The POP concentrations ranged from 0.099 lg kg1 (trans-chlordan, plot 6) to 110 lg kg1 (p,p0 -DDD, plot 8) at 0–10 cm (Table 3). Among the concentrations of the 29 POPs (Table 3), just PCB 138 (r = 0.759), endosulfan I (r = 0.881), endosulfan sulfate (r = 0.905) and mirex (r = 0.738) were correlated significantly with the clay content at 0–10 cm (correlations are not shown). Exclusively, the concen-

tration of PCB 52 was significantly correlated with organic C (r = 0.713) and N (r = 0.719) concentrations, no other significant correlations of the POPs appeared with the soil texture, organic C, N, S concentrations at this depth. The concentrations of the 29 determined POPs ranged from 0.065 lg kg1 (trans-chlordan, plot 5) to 160 lg kg1 (p,p0 -DDD, plot 1) at 10–20 cm (Table 4). The concentrations of 19 POPs (Table 4) were significantly correlated with clay, 20 POPs with silt, 17 POPs with the organic C, 16 with the N and 20 with the S concentrations at 10–20 cm. The 20 individual POPs correlated significantly with the silt content and negative significantly with the sand content, which proves the decrease of the POP contamination with an increasing sand content in soil. The determined significant correlations of the POP concentrations with the clay and silt contents could be caused by the emplacement of the POPs into the micropores of the clay and silt particles or microaggregates (Alexander, 1995; Lopez-Avila et al., 1995). The larger number of significant correlations at 10–20 cm indicated a more finished sedimentation of the POPs and bonding to the SOM than at 0–10 cm. The significant correlations between the POPs and the Corg, N and S concentrations at the lower depth agreed with the published increased POP concentrations by increasing Corg concentrations in the river Elbe and its corresponding floodplain soils (Witter et al., 2003). The differences between the significant correlations of the individual POP concentrations with the contents of the inorganic and organic soil characteristics at both sampling depths can be explained by the higher microbial activity in the upper depth. During this decomposition and building-up of SOM, a fixing of the POPs is hindered or excluded. The responsible humic compounds of the SOM with their huge number

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Table 4 Individual POP concentrations in the plots at the sampling depth 10–20 cm at the experimental sites Schönberg, Deich in comparison with published data from other river Elbe floodplains. POP (lg kg1)

a-HCH b-HCH c-HCH d-HCH PCB 28 PCB 52 PCB 101 PCB 138 PCB 153 PCB 180 Aldrin Dieldrin Endrin cis-Chlordane trans-Chlordane Heptachlor p,p0 -DDT p,p0 -DDD p,p0 -DDE o,p0 -DDT o,p0 -DDD o,p0 -DDE HCB Mirex Endosulfan I Endosulfan II Endosulfan sulfate Quintozene Methoxychlor

Schönberg, Deich

Elbe

1

2

3

4

5

6

7

8

Min.

Max.

13 25 4.5 7.1 3.9 6.1 1.8 10 17 7.9 2.8 2.8 3.0 2.0 2.5 18 35 158 47 66 140 16 100 1.9 1.8 6.4 8.6 5.3 17

8.1 17 4.2 3.9 3.4 3.7 1.3 17 13 3.1 1.8 2.8 0.61 1.4 2.1 5.2 27 110 21 47 100 20 91 2.9 1.3 3.6 14 8.2 21

6.9 12 5.1 4.7 2.1 3.5 1.4 17 14 4.5 2.9 4.2 0.80 1.3 0.59 9.7 25 97 18 45 93 16 110 4.5 1.4 5.7 15 3.6 32

5.3 10 2.7 3.0 1.4 1.0 0.62 10 7.2 3.4 1.6 1.1 0.76 0.62 2.0 6.1 16 74 13 31 70 12 50 1.7 0.62 2.4 14 4.4 13

3.6 6.5 0.23 2.5 2.0 2.3 0.47 4.8 6.3 2.9 1.4 1.0 0.41 0.47 0.065 5.7 30 42 9.1 17 43 8.1 60 1.4 0.46 3.9 7.4 2.0 14

3.6 8.7 3.3 1.9 1.1 2.6 0.45 6.4 7.3 3.3 1.5 1.6 0.80 0.49 0.64 6.7 19 41 9.6 20 44 6.7 70 3.9 0.44 4.9 7.9 6.2 13

3.4 9.1 0.96 1.9 1.0 2.4 0.62 4.9 6.6 4.2 1.4 1.4 1.1 0.62 0.48 2.5 16 10 9.9 11 17 4.6 54 1.3 0.62 3.7 1.1 1.0 15

5.8 12 3.5 3.5 1.8 4.4 1.0 9.4 8.4 4.5 2.3 2.1 0.75 1.0 1.3 4.6 49 90 21 48 89 17 81 2.2 1.0 5.9 7.8 1.3 29

<1c <1c <1a 1.0b <1c <1c 6.0b 5.0b 4.0b 2.0b 1.0b 1.0b 2.0b n.d.a. n.d.a. <1b <1c 3.0c <1a n.d.a. 7.0b 3.0b 6.0c n.d.a. <1b <1b n.d.a. n.d.a. <1b

52c 170a 21c 110c 21b 8.0b 17c 42b 16b 23c 5.0b 3.0b 15b n.d.a. n.d.a. 2.0b 430a 1100a 41b n.d.a. 550a 24b 750c n.d.a. 2.0b 17b n.d.a. n.d.a. n.d.a.

n.d.a. – no data available. a Götz et al. (2006). b Witter et al. (1998). c Witter et al. (2003).

of functional groups and their macromolecular structure are able to build bonds to different POPs (Li et al., 2003). Schulten et al. (2001) and Sutton et al. (2005) proved this in modeling experiments. 3.2.1. HCHs The individual a-, b-, c- and d-HCH concentrations ranged from 1.2 lg kg1 to 17 lg kg1 at 0–10 cm (Table 3) and from 0.23 lg kg1 to 25 lg kg1 at 10–20 cm (Table 4). These ranges confirm Witter et al. (2003), who determined HCH concentrations from <1 lg kg1 to 92 lg kg1 at 0–10 cm and Götz et al. (2006), who determined from <1 mg kg1 to 170 lg kg1 at 10–20 cm at other floodplains of the river Elbe. At both depths c-HCH had the smallest and b-HCH the largest concentrations among the isomers, in agreement with Götz et al. (2006) and Witter et al. (1998, 2003). However, this disagrees to the composition of technical HCH if applied as insecticide composed of 60–70% a-HCH, 5–12% b-HCH, 10–15% c-HCH and 6–10% d-HCH (Walker et al., 1999; Manickham et al., 2006) and of purified lindane with >90% c-HCH (Li et al., 2003). These origins would result in larger concentrations of the c-isomer than of the other isomers. Thus, theoretically the aHCH should have the highest concentrations of the HCHs, because it was spread in largest quantity. Most likely, the different ratios of the HCH isomers result from redistribution and degradation. The low c-HCH concentrations could result from its higher mobility and biodegradability, compared to a-, b- and d-HCH (Phillips et al., 2005). The high b-HCH concentrations seem to be best explained by the higher persistence of this isomer (Manickham et al., 2006).

3.2.2. PCBs The concentrations of the summed PCB congeners 28, 52, 101, 138, 153 and 180 ranged from 45 lg kg1 to 64 lg kg1 at 0– 10 cm (Table 3) and from 19 lg kg1 to 47 lg kg1 at 10–20 cm (Table 4). Our data confirmed Witter et al. (1998), who published for the upper depth a range from 15 lg kg1 to 110 lg kg1 and for the lower depth from 20 lg kg1 to 110 lg kg1. The higher concentrations of PCB 138, 153 and 180 are a result of a higher chlorination, which induce a less polarity and a higher persistence, when compared to the lower chlorinated PCBs 28, 52 and 101 (Hernandez et al., 1995). 3.2.3. Cyclodienes The concentrations of the cyclodienes aldrin, dieldrin and endrin ranged from 0.89 lg kg1 to 3.9 lg kg1 at 0–10 cm (Table 3) and from 0.41 lg kg1 to 4.2 lg kg1 at 10–20 cm (Table 4). Witter et al. (1998) published for floodplains of the river Elbe a range from <1 lg kg1 to 4 lg kg1 at 0–10 cm and from 1.0 lg kg1 to 15 lg kg1 at 10–20 cm. The concentrations of endosulfan I, II and sulfate varied from 0.55 lg kg1 to 12 lg kg1 at 0–10 cm and from 0.44 lg kg1 to 15 lg kg1 at 10–20 cm. This confirms the published data from Witter et al. (1998), who found similar concentrations from <1 lg kg1 to 7 lg kg1 at 0–10 cm and from <1 lg kg1 to 17 lg kg1 at 10–20 cm. The higher concentrations at the upper depth (Table 3) could be explained by the permanent use of endosulfan I and II as insecticide till today. The determined cis- and trans-chlordane concentrations ranged from 0.099 lg kg1 to 1.7 lg kg1 at 0–10 cm and from 0.065 lg kg1 to 2.5 lg kg1 at 10–20 cm. The heptachlor concentrations ranged from 7.1 lg kg1

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to 17 lg kg1 at 0–10 cm and from 2.5 lg kg1 to 18 lg kg1 at 10– 20 cm. These results exceeded the data published by Witter et al. (1998) at 0–10 cm (<1 lg kg1) by a factor up to 17 and at 10– 20 cm (from <1 lg kg1 to 2 lg kg1) by factor up to 9. This higher concentration in 2007 could be induced by an input of heptachlor after the determination in 1998 (Witter et al., 1998). 3.2.4. DDX The determined concentrations of the DDX ranged from 12 lg kg1 to 110 lg kg1 at 0–10 cm (Table 3) and from 4.6 lg kg1 to 160 lg kg1 at 10–20 cm (Table 4). These results confirm the published data ranged from <1 lg kg1 to 460 lg kg1 at 0–10 cm (Witter et al., 2003) and from <1 lg kg1 to 1100 lg kg1 at 10–20 cm (Götz et al., 2006). The insecticide DDT was first applied as technical grade, with the major compounds of 77.1% p,p0 -DDT, 14.9% o,p0 -DDT, 4% p,p0 DDE, and minor proportions of 0.1% o,p0 -DDE, 0.3% p,p0 -DDD, 0.1% o,p0 -DDD and 3.5% other compounds. The determined DDTs in the sediments showed that the concentrations of o,p0 -DDT

were larger in six plots at the depth 0–10 cm and in four plots at the depth 10–20 cm than the respective p,p0 -DDT concentrations. Such a changed p,p0 -DDT:o,p0 -DDT-ratio, when compared to the composition of the above described technical DDT, indicated a degradation of p,p0 -DDT to the other DDX or to other unidentified compounds. This degradation is also emphasised by the near unique p,p0 -DDD:o,p0 -DDD- and p,p0 -DDE: o,p0 -DDEratios at both depths. Furthermore, the degradation of p,p0 -DDT is indicated by the decreased proportion on the summed DDX of up to 6.4% (0–10 cm) and 7.4% (10–20 cm). The nearly similar percentage of o,p0 -DDT to the technical product suggests, that the decrease of p,p0 -DDT resulted in the transformation to the isomers of DDD and DDE. This is supported by the extreme increase of p,p0 -DDD (0–10 cm: up to 36%, 10–20 cm: up to 34%), o,p0 -DDD (0–10 cm: up to 38%, 10–20 cm: up to 32%), p,p0 -DDE (0–10 cm: up to 8.3%, 10–20 cm: up to 14%), and o,p0 -DDE (0– 10 cm: up to 6.3%, 10–20 cm: up to 6.7%). Such a transformation of DDT to DDD and DDE also was described by Tiedje et al. (1993).

Fig. 2. Summed concentrations of HCHs, PCBs, cyclodienes, DDX (lg kg1) and Corg concentrations (g kg1) in the plots at the depths 0–10 cm and 10–20 cm.

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3.2.5. HCB, quintozene, mirex and methoxychlor The concentrations of HCB ranged from 79 lg kg1 to 96 lg kg1 at 0–10 cm (Table 3) and from 50 lg kg1 to 110 lg kg1 at 10–20 cm (Table 4). This data agrees with the range of 7.0 lg kg1 to 810 lg kg1 at 0–10 cm (Witter et al., 1998) and of 6.0–750 lg kg1 at 10–20 cm (Witter et al., 2003). The concentrations of quintozene and mirex ranged from 0.47 lg kg1 to 24 lg kg1 at 0–10 cm and from 1.0 lg kg1 to 8.2 lg kg1 at 10– 20 cm. The methoxychlor concentrations ranged from 10 lg kg1 to 53 lg kg1 at 0–10 cm and from 13 lg kg1 to 32 lg kg1 at 10–20 cm. Witter et al. (1998) published a methoxychlor concentration of <1 lg kg1 at both depths, which were exceeded by factor >53 at 0–10 cm and by factor >32 at 10–20 cm. This indicates a continuous input since 1998. The direct comparison of the average concentrations of individual POPs with literature data (Witter et al., 1998) showed higher values for dieldrin, endrin, endosulfan I, endosulfan II, heptachlor, p,p0 -DDE, o,p0 -DDE and methoxychlor at 0–10 cm in the present study. At 10–20 cm exclusively heptachlor and methoxychlor exceeded data published by Witter et al. (1998). Thus our data showed a larger increase of the POP concentrations at 0–10 cm than at 10–20 cm, which could be explained by the input of contaminated particulate matter during floods in the last years. 3.2.6. Spatial variability A pronounced spatial variability was indicated by the comparison of data for the two sampling depths, for the individual plots and for different sampling sites over small to medium distances. The comparison of the relative standard deviations (RSDs) of the soil basic characteristics showed larger variations of the clay, silt, sand contents, concentrations of organic C, total N and total S at 10–20 cm than at 0–10 cm sampling depth (Tables 1 and 2). Except for p,p0 -DDT, quintozene and methoxychlor, this was also true for the individual POP concentrations (not shown). To visualise small-scale vertical (sampling depth) and horizontal (sequence of plots) variations, the summed concentrations of HCHs, PCBs, cyclodienes and DDX (Stockholm Convention on POPs) were displayed for each individual plot and sampling depth in Fig. 2. The RSD of the HCH concentrations of 12% around an average of 8 lg kg1 at 0–10 cm (PCBs: cyclodienes: 3.9 lg kg1 ± 14%; DDX: 8.5 lg kg1 ± 12%; 1 48 lg kg ± 13%) indicated a smaller spatial variability than at 10–20 cm (HCHs: 6.3 lg kg1 ± 47%; PCBs: 5.1 lg kg1 ± 37%; cyclodienes: 3.3 lg kg1 ± 37%; DDX: 42 lg kg1 ± 52%). The larger horizontal variability of the summed POP concentrations in the deeper soil layer was confirmed by the Corg concentrations which had an average of 79 g kg1 and 8.8% RSD at 0–10 cm and an average of 35 g kg1 and 40% RSD at 10–20 cm (Fig. 2 and Table 2). The smaller RSDs of the soil texture data (Table 1), C, N, S (Table 2) and summed POP concentrations (Fig. 2) at 0–10 cm than at 10–20 cm can be explained by the effects of the phytostabilization (Joner and Leyval, 2003). This means a closer and homogeneously root penetration of the comprehensive sod at

the upper depth, which stronger fixed the soil particles with the adsorbed POPs and SOM. Furthermore, this could be explained by the so-called ‘‘hydraulic control” of the sod roots at the upper depth, which could inhibit the migration of POPs with the water away from the roots by a permanent flow to them and decreased the elution by capillary and leakage water (Joner and Leyval, 2003). The pronounced larger POP concentrations in the first three plots at 10–20 cm soil depth compared to 0–10 cm and the average decrease to plot seven could be explained with the soil texture of the lower soil layer (10–20 cm) (Fig. 2). The first three plots had the finest soil texture in this soil layer, which suggest that in former times there was a depression with the deepest point at plot one, which had been filled up by fine sediment until today. It is very likely that these clay sized sediment particles were loaded with POPs because of their large specific surfaces, thereby explaining the higher POP contamination of plots and sampling depth. This agrees with Götz et al. (1994), who proved that the POPs in the water of the river Elbe are bound predominantly to the suspended particulate matter. Large differences in sedimentation rates in river Elbe floodplains were reported by Büttner et al. (2006) and Baborowski et al. (2007). In the light of these differences in sedimentation conditions, increases (Witter et al., 1998, 2003; Götz et al., 2006) as well as decreases (Witter et al., 2003) in POP concentrations with profile depth in floodplain soils at different sampling sites along the river Elbe appear not implausible. Table 5 shows a comparison of the RSDs of mean POP concentrations from the present study and from comparable publications with data arranged according to increasing distance between sampling points. Data in the first line represent the variability among four single samplings at one plot which were averaged to obtain representative concentrations for plots in Tables 3 and 4. At the sampling depth of 0–10 cm, the minimum RSDs of POP concentrations increased with increasing distance between sampling points. These minimum values of RSDs can be grouped into <1  100% (first two groups of data, 1 m < x < 7 m distance), 100–101% (1 m < x < 28 m distance) and 101–102% (45  103 m to 210  103 m). These three groups indicated that increasing the distance between samplings to be compared by four (inclusion of data from Witter et al. (1998)) to five orders of magnitude (inclusion of data from Witter et al. (1998)) resulted only in a moderate increase of minimum RSD by one order of magnitude. At the second sampling depth, the same order of magnitude of minimum RSDs of POP concentrations derived from the data by Witter et al. (1998, 2003) was obtained in the present study already when the distance between sampling points was as low as 1 m < x < 28 m. Moreover, there was no increase in the maximum RSDs and only a small increase in the average RSDs of POP concentrations with increasing distance between sampling points (Table 5). These data and comparisons do not qualify for geostatistics, which mathematically describes the spatial dependence of data (Nielsen and Wendroth, 2003). This comparison enables some interesting insights into the scale-dependency of variation in POP concentrations. Surprisingly, the variability of

Table 5 Comparison of the minimal, maximal and average relative standard deviations (RSDs) of POP concentrations in relation to the distances between sampling points from the present study and literature data. Distances between sampling points along the river Elbe

Sampling depth, 0–10 cm

Sampling depth, 10–20 cm

1 m < x < 1.5 m, replicate samplings in one plot 1 m < x < 7 m, between adjacent plots 1 m < x < 28 m, between all eight plots 45  103 m, between sites from Witter et al. (2003) 210  103 m, between sites from Witter et al. (1998)

0.7–170%, average 37% 0.1–120%, average 20% 5.9–120%, average 28% 67–170%, average 102% 43–140%, average 94%

1.2–130%, average 51% 0.5–130%, average 32% 30–80%, average 50% 94–180%, average 130% 42–140%, average 110%

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POP concentrations at both sampling depths was large at a small scale of a few meters which is often considered as one sampling point. The previous discussions indicated that small scale differences in relief and sedimentation conditions governed the POP concentrations at this scale. Furthermore, the small increase in the RSDs with increasing distance over three to four orders of magnitude indicated that larger-scale differences in POP inputs (e.g., various sources) or sedimentation and translocation processes had a much smaller influence on the POP concentrations than the small scale sedimentation conditions. Moreover, without sufficient replicates at each sampling point and detailed analyses of the small scale variability, data on POP concentrations reported in the literature could be suspected to be accidental, at least to a certain extent. 4. Conclusions (1) Recoveries and LOQs of GC/ECD, supported by GC/MS results showed that the chosen analytical approach was suitable for the quantification of the 29 selected relevant POPs in trace concentrations in a plot experiment established in the Elbe river floodplain soils. The spectrum of determined POPs had been expanded in comparison to previous studies. Compared with literature data an increase of eight POP concentrations at the depth of 0–10 cm and two at 10–20 cm was proved between the years 1998 and 2007. Thus, a baseline was established to investigate possible effects of phytoremediation on the concentrations of POPs. (2) A pronounced small-scale spatial variability of POP concentrations in the horizontal and vertical directions was explained partly by the sedimentation conditions which governed texture and organic matter distribution. Since the variability in POP concentrations did not increase much from the 101 m to 104 m scale, single sampling point measurements along the river Elbe must be complemented by systematic investigations of the small- to medium-scale spatial variability to obtain a valid picture of contaminant distribution at the catchment-scale and its possible changes, e.g., due to closing of point sources, flood events and remediation processes.

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