Accepted Manuscript

Title: The influence of soil composition on the leachability ofselected hydrophobic organic compounds (HOCs) from soilsusing a batch leaching test

Author: <ce:author id="aut0005"> Silviu-LaurentiuBadea<ce:author id="aut0010"> Staffan Lundstedt<ce:authorid="aut0015"> Per Liljelind<ce:author id="aut0020"> MatsTysklind

PII: S0304-3894(13)00195-7DOI: http://dx.doi.org/doi:10.1016/j.jhazmat.2013.03.019Reference: HAZMAT 14986

To appear in: Journal of Hazardous Materials

Received date: 17-11-2012Revised date: 6-3-2013Accepted date: 8-3-2013

Please cite this article as: S.-L. Badea, S. Lundstedt, P. Liljelind, M. Tysklind, Theinfluence of soil composition on the leachability of selected hydrophobic organiccompounds (HOCs) from soils using a batch leaching test, Journal of HazardousMaterials (2013), http://dx.doi.org/10.1016/j.jhazmat.2013.03.019

This is a PDF file of an unedited manuscript that has been accepted for publication.As a service to our customers we are providing this early version of the manuscript.The manuscript will undergo copyediting, typesetting, and review of the resulting proofbefore it is published in its final form. Please note that during the production processerrors may be discovered which could affect the content, and all legal disclaimers thatapply to the journal pertain.

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The influence of soil composition on the leachability of 1

selected hydrophobic organic compounds (HOCs) from 2

soils using a batch leaching test3

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5

Silviu-Laurentiu Badea *1, Staffan Lundstedt1, Per Liljelind1, Mats Tysklind16

1Department of Chemistry, Umeå University, SE-901 87, Umeå, Sweden7

8

*Corresponding author:9

Silviu-Laurentiu Badea10

E-mail: silviu.badea@chem.umu.se11

Phone: +46-90-786 932312

Fax: +46-90-786765513

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Abstract14

The influence of soil composition (peat and clay content) on the leachability was investigated in batch 15

leaching experiments for chemically diverse hydrophobic organic compounds (HOCs: PCP, PAHs, 16

HCB, HCHs, PCBs, and TCDD/Fs). An experimental design was applied to generate 8 diverse soil 17

matrices, and the results were evaluated by orthogonal projections to latent structures (OPLS), as well as 18

compound specific response surface models. Overall, the distribution coefficients (log Kd) of model 19

HOCs were in the range of approx. 2.0 – 5.7. The Kd-values of HCHs, phenanthrene and PCP were 20

positively correlated with the peat content. Kd-values of benzo(a)anthracene, HCB, and PCB 47 were 21

positively correlated with both peat and clay content. The Kd-values of 1,3,6,8-TCDD and 1,3,6,8-22

TCDF were positively correlated with peat content but negatively correlated with clay content, while for 23

PCB 153 and PCB 155 the correlations were reversed. The correlation between the Kd-values and the 24

compounds’ Kow-values was linearly for compounds with log Kow <6. For HOCs with log Kow > 6, the 25

Kd-values were leveling off, possibly due to small particles in the leachates. Our study demonstrated 26

how complex interaction between both the organic matter and clay components influences the 27

leachability of HOCs in a compound-specific manner.28

Keywords: Contaminated soil; Hydrophobic organic compounds; Leaching tests; Distribution 29

coefficient; 30

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1. Introduction37

Contaminated soils may function as secondary sources of hazardous compounds in the environment and 38

organic contaminants may be spread through evaporation, particle migration and leaching from soil to 39

groundwater. Consequently, in order to perform thorough risk assessments of contaminated sites all 40

these distribution pathways must be considered and estimated. Leaching tests may be useful tools to 41

estimate the mobility of contaminants via the water phase and thereby the risk for groundwater and 42

surface water contamination [1]. The leachability of the compounds is dependent on the inherent 43

physico-chemical properties of the compounds, the soil type, the presence of other contaminants, as well 44

as the age of the contamination.45

Soil is composed of many different components, of which clays, oxides and organic matter are reported 46

to be the primary constituents responsible for the sorption of organic contaminants [2]. Organic matter 47

has a high affinity for many non-polar compounds and is considered to have a dominating influence on 48

the sorption. For soils and sediments with low organic matter content, clay minerals may have a more 49

important role [3]. When it comes to the properties of the contaminants, their solubility as well as their 50

partitioning behavior between water and organic phases, often described by the octanol-water partition 51

coefficient (Kow), are thought to be the most important [4]. The most hydrophobic compounds (Kow > 6) 52

are unlikely to leach, due to their low water solubility and high affinity for particle surfaces. In contrast, 53

less hydrophobic compounds (Kow < 6) are generally weakly sorbed and will leach to varying degrees 54

depending on their solubility. In response to the need for leaching tests, methods for organic compounds 55

have been recently developed [5-15]. Generally, all leaching tests aim to determine the fraction of 56

contaminants that are loosely bound and therefore may be mobilized into the water phase. Leaching tests 57

may be performed in the form of equilibrium column tests or batch tests. In the batch tests, the soil is 58

agitated in the leachate for a fixed time to obtain equilibrium between contaminants in solution and 59

contaminants in the soil. The distribution of the contaminants between the soil and leachates are usually 60

calculated as soil-water distribution coefficients (Kd), which are widely used in modeling of 61

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environmental behavior of contaminants in soils. Hydrophobic organic compounds (HOCs), often 62

present in the contaminated soils, including a wide array of compounds, such as organochlorine 63

pesticides (OCs), polychlorinated benzenes (PCBz), polycyclic aromatic hydrocarbons (PAHs), 64

polychlorinated biphenyls (PCBs), polychlorinated dibenzofurans (PCDFs) and polychlorinated 65

dibenzo-p-dioxins (PCDDs). These compounds are often toxic, persistent in the environment and can 66

bioaccumulate [16-19]. The mobility of HOCs is generally low mainly because to their strong 67

association with the organic matter in soils [4, 6, 20, 21], but their mobility may also be limited by other 68

constituents of the soil, e.g. small particles of clay and active oxide surfaces [2]. On the other hand, 69

dissolved organic carbon (DOC) and fine particles may be transported through the soil profile as 70

colloids [22] and thereby function as carriers for HOCs, which then may increase the mobility [23-25]. 71

The objective of this study was to investigate the influence of the soil composition (proportion of peat, 72

clay and sand) on the leachability of a wide range of HOCs, focusing on similarities and differences 73

between the compounds.74

2. Experimental75

The leachability of HOCs was studied in a series of batch leaching experiments according to an 76

experimental design, which was evaluated by orthogonal projections to latent structures (OPLS). Spiked 77

artificial soils were used to control the parameters of interest, such as the soil and contaminant 78

compositions [26].79

2.1. Soil samples80

OECD standard soil, containing 70% sand, 20% kaolin clay and 10% sphagnum peat [27], was used as a 81

reference soil during the batch leaching experiments. Kaolinite (Al2Si2O5(OH)4) was identified as the 82

main mineral in the clay, as determined by X-ray Diffraction (Rietveld's method) [28], while the quartz 83

(SiO2) was identified as the main mineral in the sand. In order to identify the moieties in the organic 84

matter responsible for interaction with the HOCs, the peat used in the preparation of the soils was 85

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investigated by X-ray photoelectron spectroscopy (XPS) [20] (see S.M.). Five chemical states of carbon 86

were identified and quantified in the C1s spectra: 285.0 eV (representing aliphatic C-C and C-H bonds),87

285.7 (C-COOH, C-CON), 286.7 eV (C-O-C, C-OH, C-N), 288.2 eV (O-C-O, C=O) and 289.3 eV 88

(COOH bonds). The uncertainty of atomic concentrations determinations was approximately ±8 atomic 89

%. In addition to the OECD soil, seven other artificial soils, with different proportions of the same 90

constituents were prepared in duplicates (see Table 1 for their composition), in accordance with a D-91

optimal experimental design.92

2.2. Model compounds and soil spiking 93

Technical hexachlorocyclohexane (HCH) containing 69.3% α-HCH, 15.0% β-HCH, 9.0 % γ-HCH, 6.5 94

% -HCH, pentachlorophenol (PCP), hexachlorobeneze (HCB), phenanthrene (Phe), benzo(a)anthracene 95

(BaA), were all purchased from Sigma-Aldrich (Munich, Germany), while the polychlorinated 96

biphenyls: PCB 47, PCB 153, and PCB 155, 1,3,6,8-tetrachloro dibenzo-p-dioxin (1,3,6,8-TCDD) and 97

1,3,6,8-tetrachloro dibenzofuran (1,3,6,8-TCDF), were purchased from LGC Standards (Borås, 98

Sweden). The 13 HOCs, selected as representative soil contaminants of general concern, were spiked in 99

the soils using a high solvent volume method similar to the methods previously described [29, 30]. The 100

high solvent volume spiking method was chosen since it is likely to provide a homogenously 101

distribution of the target compounds in the soils [30] compared with low solvent volume spiking 102

methods. The homogeneity of the spiked soils was tested by analysis of triplicate samples prior to the 103

start leaching tests. Briefly, about 320 g of OECD soil and 200 g of each of the other soils were 104

transferred to brown glass bottles and homogenized. The soils were spiked with an acetone solution (50 105

mL per 100 g of soil) of the above mentioned compounds to reach a final concentration in the soils of: 106

402 ng/g for PCP, 1060 ng/g for Phe, 1010 ng/g for BaA, 2000 ng/g for HCB, 6930 ng/g for α-HCH, 107

1500 ng/g for β-HCH, 900 ng/g for γ-HCH, 650 ng/g for -HCH, 5.0 ng/g for PCB 47, 4.0 ng/g for PCB 108

153, 5.3 ng/g for PCB 155, 1.0 ng/g for 1,3,6,8-TCDD, and 1.0 ng/g for 1,3,6,8-TCDF. The above 109

mentioned spiked concentrations were designed to be environmentally relevant and to mimic the 110

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contamination at industrial sites. The spiked soils were homogenized with glass rods and the solvent 111

was allowed to evaporate for one week leaving the bottles opened. The soils were mixed regularly with 112

the glass rods to accelerate the solvent’s evaporation. The soils were stored at +4ºC for four weeks in 113

order to let the contaminants migrate somewhat into the soil particles (age) before the leaching tests. 114

2.3. Batch leaching test115

The batch leaching tests were performed using 100 g aliquots of the soils, triplicates of the OECD soil 116

and duplicates of the other seven soils. A blank consisting of 100 g clean OECD soil (with no spiked 117

contaminants) was run in parallel. The tests were performed in 0.5 L Schott Duran bottles (screw capped 118

glass, 45 mm screw thread, 78 mm side wide and 181 mm height)_at a liquid to solid ratio (L/S) of 5 119

L/kg, which was reached by adding 0.5 L of an aqueous solution containing 0.001 M CaCl2 and 0.2 g/L 120

NaN3 to each bottle (ionic strength of 0.012 mol/L). The bottles (18 in total) were placed in a horizontal 121

shaker, and rotated at 120 rpm for 24 hours to obtain equilibrium between the contaminants in solution 122

and contaminants in the soil. The leachates were then separated from the soil by filtration, using a 123

cellulose filter followed by vacuum filtration through a glass fiber filter with pore diameters of about 0.7 124

μm (Sartorius Stedim Biotech GmbH, Gottingen, Germany).125

2.4. Extraction of soil leachates126

After separation, the leachates were spiked with an internal standard (IS) solution containing 13C-labeled 127

PCP, γ-HCH (IS for all HCHs), PCB 52 (IS for PCB 47), and PCB 153 (IS for PCBs 153 and 155), 2H-128

labeled Phe and BaA and 37Cl-2,3,7,8-TCDD (IS for 1,3,6,8-TCDD and 1,3,6,8-TCDF), all from LGC 129

Standards (Borås, Sweden). The leachates were extracted by liquid-liquid extraction using three portions 130

of 50 mL dichloromethane (DCM) each. The first round was performed in 1L Schott Duran bottles on 131

the horizontal shaker for 24 hours, and the following two rounds in separatory funnels. The organic 132

extracts were collected and evaporated using a rotavapor, and were then dried on columns of anhydrous 133

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sodium sulfate (Na2SO4) and divided into three aliquots for cleanup and analysis of 1) PCDDs/Fs and 134

PCBs, 2) PCP and 3) PAHs, HCHs and HCB, respectively. 135

2.5. Extraction of soil samples 136

Samples (5 g dry weight) of the spiked soils and clean OECD soil were transferred in duplicates to pre-137

washed Soxhlet thimbles. The samples were spiked with similar IS-solutions as the ones used for the 138

leachates (ten times more concentrated), after which they were extracted with toluene using Soxhlet 139

Dean-Stark extractors for 24 hours. The resulting extracts were divided into four aliquots: one retained 140

as a precaution, and the others for determinations of 1) PCDDs/Fs and PCBs, 2) PCP and 3) PAHs, 141

HCHs and HCB, respectively. The extraction procedure for the soil particles trapped on the filter was 142

identical to that for the soil samples.143

2.6. Clean-up and analysis of PAHs, HCHs and HCB 144

The aliquots of the extracts intended for analysis of PAHs, HCHs and HCBs were purified on columns, 145

consisting of 4 g of silica gel deactivated with 10% water (w/w) packed in 16 mm i.d. glass columns, 146

with a ca. 1 cm layer of anhydrous Na2SO4 on top. The target compounds were eluted with 60 mL of 147

cyclopentane [31]. About 1 ml of toluene was added to the eluates and the cyclopentane was evaporated. 148

Recovery standard (RS), consisting of 2H-labeled fluoranthene was added before GC/MS analysis. An 149

Agilent 6890 N gas chromatograph (GC) coupled to Agilent 5975 inert mass selective detector (MSD) 150

(Agilent Technology, Palo Alto, USA) was used for the analysis, in the selected ion monitoring (SIM) 151

mode. The GC was equipped with a 30 m x 0.25 mm x 0.25 μm i.d., SLB-5ms column (Supelco, 152

Bellefonte, Pennsylvania, USA), and a HP PTV injector operated in splitless mode. Helium was used as 153

carrier gas at a flow of 1.3 mL/min. The temperature program for the GC oven was: 80 °C for 1.8 min, 154

rising by 8 °C/min to 180 °C, and then by 12°C/min to 310°C and held for 10 min. 155

2.7. Clean-up and analysis of PCP156

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The aliquots of the extracts intended for PCP analysis were diluted with 2 mL of n-hexane, then the PCP 157

was separated from other hydrophobic sample components by liquid-liquid extraction with 3 x 1 mL 158

0.5M NaOH solution. The aqueous phase, containing the sodium phenolate of PCP, was collected in 159

new vials. The PCP was acetylated by adding 1mL of acetic acid anhydride to the aqueous phase [31]. 160

After 10 min, 0.5 mL of 18.5 % HCl was added. Acetylated PCP was then extracted with 3 x 2mL of 161

cyclopentane. The extract was dried on a column containing 1 g of anhydrous Na2SO4, 0.1 to 1 mL of 162

toluene was added, and the cyclopentane was evaporated. An RS, consisting of 2H-dibenzofuran was 163

added before GC/MS analysis. Here too, the same 6890 N GC-5975 MSD was used, equipped with the 164

same SLB-5ms column but using a slightly different temperature program in the GC: 90 °C for 2 min, 165

increase by 15 °C/min to 220 °C, and then by 30°C to 310°C and held for 2 min.166

2.8. Clean-up and analysis of PCBs and PCDDs/Fs 167

The aliquots of the extracts intended for PCB and PCDD/F analysis were spiked with 50 μL of 168

tetradecane. After evaporation, the residual extracts were dissolved in 2-3 mL n-hexane and transferred 169

to multi layer silica columns for clean up [31]. The columns consisted of, 16 mm i.d. glass columns 170

packed with the following components from top to bottom: 1cm layer of Na2SO4, 4cm of H2SO4 acidified silica 171

gel, 4 cm of neutral silica gel, 4 cm of KOH alkaline silica gel and a plug of glass wool. The PCBs and 172

PCDD/Fs were eluted with 50 mL of n-hexane, the eluate was collected in round flasks and evaporated 173

again until near dryness (the residual volume of 50μL tetradecane). The PCDD/Fs were separated from 174

the PCBs on carbon columns [31]. The PCBs were eluted from the column with 50 mL of a mixture of 175

DCM/n-Hexane (50:50), after which the columns were turned upside-down and the PCDD/Fs were 176

eluted with 50 mL toluene. The PCB fractions were spiked with 40 μL tetradecane, and 40 μL of an RS 177

solution containing 13C-labeled PCBs 97 and 188, while the PCDD/F fractions were spiked with 30 μL 178

tetradecane and 40 μL of an RS-solution containing 13C-labeled 1,2,3,4-TCDD, 1,2,3,4,6-PeCDF, 179

1,2,3,4,6,9-HxCDF, and 1,2,3,4,6,8,9-HpCDF. Both fractions were evaporated until only the tetradecane 180

remained and then transferred to 200 μL GC-vials for analysis. 181

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The PCBs and PCDD/Fs were analyzed using an Agilent 6890N gas chromatograph (Agilent 182

Technology, Palo Alto, USA) coupled to a Waters Autospec Ultima NT 2000D high resolution mass 183

spectrometer (Milford, USA), the latter with a mass resolution of 10000. The mass spectrometer was 184

operated in SIM mode. Analyses were performed on non-polar DB-5 column (60 m x 0.25 mm x 0.25 185

μm J&W Scientific, CA, USA). The temperature program for PCDD/Fs started at 200°C for 2 min, then 186

increased by 3 °C/min to 278 °C, followed by 10 °C/min to 315 °C, which was held for 5 min. The 187

temperature program for PCBs started at 190°C for 2 min, then increased by 3 °C/min to 278 °C, then 6 188

°C/min to 304 °C, no hold time. 189

2.9. Total organic carbon analysis190

Total and dissolved organic carbon was determined using a Shimadzu TOC-5000 high temperature 191

catalytic oxidation instrument with a non-dispersive infrared (NDIR) detection. Samples were acidified 192

and sparged prior to analysis. Calculation of carbon concentrations was made with potassium hydrogen 193

phtalate as standard substance.194

2.10. Calculation of distribution coefficients195

The distribution of the contaminants between the solid and liquid phases were expressed as soil-water 196

distribution coefficients (Kd), calculated using the following equation:197

w

sd

C

CK 198

where Cs and Cw are the concentrations of a given compound in the soil and aqueous phase, respectively. 199

Since spiked soils were used, the Kd was calculated using measured concentration of the aqueous phase 200

only, while the soil concentrations were based on the spiked levels. The concentrations in the soils 201

before and after the leaching were verified for one of the soils, i.e. the M2 soil (see Table S2 202

Supplementary Material (S.M.). Some experimental concentrations in the after-leaching M2 soil (BaA 203

and Phe) appears to be slightly lower than the concentrations calculated according to the mass balance 204

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(see S.M.) and these slightly lower concentrations might be explained by sorption of above mentioned 205

compounds on the cellulose filters during pre-filtration.206

2.11. Multivariate data analysis207

To evaluate the relationships between proportions of sand, clay and peat in the soil and the leachability 208

of the model compounds (log Kd values) an orthogonal partial least square model (O-PLS) was 209

established using the SIMCA-P+12.0 multivariate statistical software package (Umetrics, Umeå, 210

Sweden). A two-dimensional model with N=8 observations and K=16 variables (X=13, Y=3) was used. 211

The quality of the model is described by the R2X, R2Y and Q2 values. R2X and R2Y are defined as the 212

proportion of variance in the data explained by the models and indicates goodness of fit, while Q2 is 213

defined as the proportion of variance in the data predictable by the model and indicates predictability 214

[32].215

Furthermore, in order to evaluate the relation between the soil composition (% sand, clay and peat, 216

respectively) and the concentration of the model compounds, a screening model was developed with the 217

MODDE 9.0 software (Umetrics, Umeå, Sweden). The D-optimal experimental design was generated 218

for three factors (% sand, clay and peat, respectively), with 8 experiments, to produce a model with 219

linear terms for all of the factors, and no interaction terms included. The relationships between the 220

factors and response (concentration) were analyzed using multiple-linear regression (MLR) [33].221

3. Results and Discussion222

3.1. Multivariate analysis of the distribution coefficients. Variation of leachability in relation to soil 223

composition.224

The logarithmic values of the distribution coefficients (log Kd) for all compounds are summarized in 225

Table 1. Overall, the log Kd varied between 2.04±0.04 for α-HCH in the soil with 90% sand, 5% clay 226

and 5% peat (M2), and 5.69±0.05 for PCB 155, the compound with the highest log Kow value (7.2), in 227

the soil with 30% sand, 60% clay and 10% peat (M6). For the compounds with low hydrophobicity 228

(described as log Kow), i.e. the HCHs, PCP, Phe and PCB 47, the highest Kd-values were recorded for 229

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the soil with the highest proportion of organic matter (M4 with 20% sand, 20% clay and 60 % peat). For 230

most of the model compounds (HCHs, PCP, HCB, PCB 47 and PCB 155), the lowest Kd-values were 231

recorded for the soils with the lowest peat and clay contents (soils M1 and M2). While the log Kd-values 232

of Phe from Table 1 are similarly with the one recorded by Enell et al. [5] (5.18) in a column leaching 233

test with aged soil (16 % organic matter), van Hattum et al. [34] obtained similarly values of the log Kd234

values both for BaA (log Kd 4.5–6.9, average 5.6 ± 0.7) and Phe (log Kd 3.6–6.3, average 4.4 ± 0.9) for 235

their partition between water and lake and river sediments with organic carbon contents between 0.9 and 236

22%. Comparing results from van Hattum et al. [34] with the lower variation of the Kd-values both for 237

BaA and Phe recorded in our study (although involving a large variation in soil composition), one 238

possible explanation could be higher variation of field data comparing with the data obtained from 239

controlled reference experiments performed with spiked soils [26].240

In order to efficiently investigate the relation between the soil composition (% sand, clay and peat, 241

respectively), the physico-chemical properties of the model compounds, and the leachability of the same 242

compounds (log Kd values), the results were also explored with OPLS. The R2X and R2Y obtained were 243

0.811 and 0.961 respectively, while the Q2 was 0.834 indicating that the model could explain most of 244

the variations within the data set. The resulting OPLS scatter plot (Fig. 1) shows the degree to which the 245

Kd values for each compound were influenced by the soil constituents, and also which of the compounds 246

that behaved similarly as well as those that behaved differently. Also compound specific response 247

surfaces were calculated using screening models calculated with MODDE 9.0 software. The resulting 248

contour plots show how the leachate concentrations of the compounds varied with the soil composition249

(see Figs. 2, 3, 4, and 5).250

The OPLS loading scatter plot (Fig. 1) indicate four groups of compounds with different interactions 251

with the soil matrix. For the first group (group A in Fig. 1), consisting of HCHs, Phe and PCP, the Kd252

values had a relatively strong positive correlation with the peat content, while the correlation with the 253

clay and the sand was weaker. Thus, the leachability of these compounds was mainly controlled by the 254

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peat, showing decreasing leachability with increasing peat content, while they were less affected by the 255

variations in the clay and the sand content (see also the contour plots of from Fig. 2A, 2B and 2C). The 256

contour plot from Fig. 2A show that the concentration of α-HCH in the leachate is decreasing about 13 257

times, as the peat content increases from 0 to 60%. A similar behavior was also seen for the other 258

compounds of group A, for example the other HCHs, not shown in Fig.2, see S1A (S.M.). This behavior 259

of HCHs is also similarly with the one reported in other studies, as the log Kd values for all HCHs from 260

Tab. 1 fell in the same range as those reported by Toul et al. [35] for sorption of γ-HCH on dusty fine-261

grained sandstone (1.1 % organic carbon; log Kd 3.18) and fine-grained sandstone (0.28 % organic 262

carbon; log Kd 3.54) in sorption batch tests. The contour plot from Fig. 2B show that the concentration 263

of PCP in the leachate is decreasing about 6 times, as the peat content increases from 0 to 60%, 264

indicating a relatively strong retention of PCP in soils with the organic matter contents higher than 10 % 265

(see also S1B, S.M.). Nevertheless, this decrease cannot be entirely attributed to the hydrophobic 266

interactions since the pH of the leachates (measured in a separate DOC availability test using the same 267

liquid to solid ratio (L/S) of 5 L/kg) was decreasing from 7.70 in the case of M2 leachate (5 % peat) to 268

4.61 in the case of M4 leachate (60%). In the case of slightly alkaline M2 leachate, the sorption of 269

phenolate ion and the formation and sorption of the neutral metal-phenolate ion pair must be taken into 270

account [36]. This correlation was found also by Wahlström et al. [37], who observed a high 271

leachability of chlorophenols in sandy soils, while it was much lower in humus rich soils. The relative 272

high concentration of PCP in all the leachate samples, in the present study, might be associated with its 273

relatively high water solubility (0.857 mg/L), which is drastically increased as the phenol is dissociated 274

into its phenolate ion (PCP-), occurring at pH 7 and above [36, 37]. The contour plot from Fig. 2C 275

shows that the concentration of Phe in the leachate is decreasing about 454 times to 3.22 ± 1.45 ng/mL, 276

as the peat content increases from 0 to 60% (see also S1C, S.M.). Both Fig. 2C and Fig. 1 show that the 277

leachability of Phe is only weakly correlated with the clay content, as compared to the influence of the 278

peat content. Quantitatively, the log Kd-values of Phe from Tab. 1 are similarly with the one recorded by 279

Enell et al. [5] (5.18) in a column leaching test with aged soil (16 % organic matter). By XPS analysis, 280

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the following moieties were found: C-C, C-H, COOH, C-CON, C-O-C, C-OH, C-N, O-C-O, C=O. 281

Among them, the aliphatic moieties identified at 285.0 eV (C-C and C-H bonds) have the highest atomic 282

concentrations (AC), 41.91 %, followed by the components identified at the binding energy of 286.7 eV 283

(C-OH, C-N and C-O-C bonds) with 20.5 %. The high presence of aliphatic moieties in the peat 284

combined with the high influence of the peat content on the Kd values of HCHs, Phe and PCP suggests 285

that alkyl-C moieties, in addition to aromatic moieties, can act as sorption domains for HOCs in soil 286

organic matter. The alkyl-C moieties can sorb too appreciable amounts of HOCs, in some cases with 287

even higher affinity than aromatic-rich sorbents [38].288

The second group of compounds (group B in Fig. 1) consists of 1,3,6,8-TCDD and 1,3,6,8-TCDF. Their 289

Kd values were positively correlated with the peat content, but negatively correlated with the clay 290

content. Thus, 1,3,6,8-TCDD and 1,3,6,8-TCDF levels in the leachates decreased with increasing peat 291

content in the soil, but increased with increasing clay content. This is an interesting finding showing that 292

the leachability of 1,3,6,8-TCDD and 1,3,6,8-TCDF might be enhanced in the soils with high clay 293

content. The blocking of the sorption sites during the expansion of the clay [39] and also the colloidal 294

transport of the 1,3,6,8-TCDD and 1,3,6,8-TCDF on the clay particles [40] might explain their enhanced 295

leachability. This behavior for the 1,3,6,8-TCDD and 1,3,6,8-TCDF can also be seen in the contour plots 296

for these compounds (Figs. 3A and 3B) respectively. The contour plots are similar, indicating that these 297

two compounds have similar leaching behavior, and that they are affected similarly by the studied soil 298

components. 299

For the 3rd group of compounds (group C in Fig. 1), consisting of BaA, HCB and PCB 47, the Kd values 300

were positively correlated with both the peat and the clay content, meaning that the leachate 301

concentrations of these compounds were decreasing as both the peat and the clay content increased. 302

However, compared to group A the correlation with the peat content was weaker for group C, and for 303

BaA even the correlation with clay was weak. The contour plot presented in Fig. 4 combined with Fig. 304

1 shows that the concentration of HCB in leachates is increasing with the decrease of both peat and clay 305

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content of the soil as we are moving from the bottom of plot (high content of clay and peat) to the top 306

(low content of clay and peat). Quantitatively, the variability of Kd values for HCB is similar with the 307

one reported by Toul et al. [35], i.e. a log Kd between 3.07 for sorption of HCB on dusty fine-grained 308

sandstone (1.1 % organic carbon) and 3.66 for sorption of HCB on lake sediment (2.85 % organic 309

matter). The contour plot presented in Fig. 5A combined also with the Fig. 1 shows that the 310

concentration of PCB 47 in leachates increased with the decrease of peat and very weakly with the 311

decrease of clay content of the soil, as we are moving from the bottom of plot (high content of clay and 312

peat) to the top (low content of clay and peat). Compared with the Phe, the Kd values of BaA are weakly 313

correlated both with peat and the clay content, suggesting that the soil composition had a low influence 314

on this compound. Nevertheless, van Hattum et al. [34] recorded variable but similarly log Kd values 315

both for BaA (log Kd 4.5–6.9, average 5.6 ± 0.7) and Phe (log Kd 3.6–6.3, average 4.4 ± 0.9) for their 316

partition between water and lake and river sediments with organic carbon contents between 0.9 and 317

22%, indicating a higher variation of field data comparing with the data obtained from controlled 318

reference experiments performed with spiked soils [26].319

The 4th group of compounds (group D in Fig. 1), consisting of PCB 153 and PCB 155, showed Kd values 320

that, according to the OPLS-model, were positively correlated with the clay content while being 321

negatively correlated with the peat content. Although the Kd values of PCB 153 appears to be slightly 322

positively correlated with the sand content while the Kd values of PCB 155 appears to be slightly 323

negatively correlated with the sand content (this it is apparently true for all the other compounds 324

excepting 1,3,6,8-TCDD which is very weak positively correlated with the sand content), it is probable 325

that this mainly is an affect of the change in the clay and peat content. This means that these compounds 326

would be expected to show higher leachability as the clay content decreased, but also as the peat content 327

increased. For PCB 153, this agrees well with what the contour plot shows, but for PCB 155 it is 328

somewhat different (Fig. 5). For this compound the concentration in the leachate seem to increase both 329

as the peat and clay decreases. This apparent difference between predictions of the OPLS-model and the 330

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response surface model was probably due to the low significance of the correlation between peat and 331

PCB 155’s leachability. 332

3.2. Variation of the distribution coefficients with hydrophobicity of the compounds333

Since it is generally suggested that the leaching of organic compounds from soil is controlled mainly by 334

the compounds’ hydrophobicity, the log Kd-values of all compounds calculated for OECD soil as well 335

for the soils with the highest amount of peat (M4) and clay (M6), respectively, were plotted against their 336

log Kow (See Fig. 6). The data from the log Kd vs. log Kow plot for OECD soil (Fig. 6A) were fitted 337

linearly and also quadratic, and the slope of the linear curve was calculated to 1.02 ± 0.18 (Eqn. 1 from 338

Fig.6A), close to the value of 1, as expected for sorption processes that are driven by hydrophobic 339

interactions [41]. However, for the more hydrophobic compounds (log Kow>6) the measured Kd-values 340

deviated from the linear relationship, which also the regression coefficient (R2), calculated to 0.71, 341

indicate. Excluding the Kd values for the four most hydrophobic compounds (PCB 153 and PCB 155, 342

1,3,6,8-TCDD and 1,3,6,8-TCDF) a better linear relationship was calculated (R2 = 0.85), while the slope 343

of the linear curve was 1.34 ± 0.19 (Eqn.2 from Fig.6A). According to Booij et al. (1993) [42], a plot log 344

Kd vs. log Kow using ’true’ Kd values (based on truly dissolved concentrations) should result in a linear 345

relationship with a slope close to 1, but due to the colloids present in the leachates the apparent Kd346

values for the hydrophobic compounds are deviating from the linearity. The above mentioned study [42]347

estimated that the differences between true and apparent Kd values were negligible for compounds with 348

log Kow <6, and were up to 1 log unit for more hydrophobic compounds. The log Kd vs. log Kow plots 349

for the more extreme soils in terms of peat and clay content M4 and M6 soils shown in Figs. 6B and 6C, 350

indicate an even more complex relationship. Excluding the Kd values for the four most hydrophobic 351

compounds (PCB 153 and PCB 155, 1,3,6,8-TCDD and 1,3,6,8-TCDF), the linearity of the curves were 352

R2 = 0.58 for M4 soil and R2 = 0.90 for the M6 soil respectively. The linear fitting of the all Kd data for 353

both M4 and M6 soils was resulting much more low R2 values (data not shown) than the one calculated 354

with all Kd data for OECD soil (R2 = 0.71). The slopes of the curves for log Kd vs. log Kow plots for the 355

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M4 and M6 soils were 0.65 ± 0.18 for M4 and 1.47 ± 0.17 for M6 respectively, clearly deviating from 356

the suggested value of 1 [41]. Thus the sorption in these two soils might be driven by other factors than 357

hydrophobic interactions (dissolution, the presence of dissolved organic matter and colloids, transport 358

via particles). The amount of DOC released from the spiked soil was estimated in a separate DOC 359

availability test using the same liquid to solid ratio (L/S) of 5 L/kg. The high values obtain for total 360

organic carbon (between 49.9 and 323 mg/L leachates) show that the colloid-facilitated transport of the 361

four most hydrophobic compounds (PCB 153 and PCB 155, 1,3,6,8-TCDD and 1,3,6,8-TCDF) might 362

explain the above mentioned deviation from the linearity. In order to describe the effect of small 363

colloidal particles that escape phase separation, Gschwend et al. [43] developed the ‘non-settling 364

particles model’ (NPL-model ), demonstrating that the apparent Kd values of highly hydrophobic 365

compounds are lower than the ‘true Kd values’ (based on truly dissolved concentrations) [41]. Thus log 366

Kd vs. log Kow plots from Fig. 6 indicated that the apparent Kd values show a deviation from the “true Kd367

values” for highly hydrophobic compounds (PCB 153 and PCB 155, 1,3,6,8-TCDD and 1,3,6,8-TCDF). 368

Similar trends, with logarithmic values of the organic carbon distribution coefficient (Koc)) diverging 369

from a linear relationship at log Kow > 6, was found by Burgess et al. [44] in a study on distribution of 370

PCBs in a colloidal system, and they suggested that the divergence was due to the lack of equilibrium 371

between colloidal and dissolved phases in the system. Possible mechanisms might include contaminant 372

diffusion rates, colloid transport dynamics, steric hindrance and colloid instability.373

Conclusions374

The results of this study indicate that the leachability of moderately hydrophobic compounds, such as 375

HCHs, PCP and Phe, is correlated mainly with the peat content of soil, and their leachability decreases 376

as the peat content increases, while the correlation with the clay content is much weaker. For slightly 377

more hydrophobic compounds, such as BaA, HCB and PCB 47, there are correlations with both peat and 378

clay contents implying that their leachability decreases as the proportions of either of these soil 379

constituents increases, although the correlations for BaA are weak. For the highly hydrophobic 380

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compounds the correlation was less consistent. For the PCDDs/Fs, i.e. 1,3,6,8-TCDD and 1,3,6,8-381

TCDF, the leachability was negatively correlated with the peat content but positively correlated with the 382

clay content, while for the highly chlorinated PCBs, i.e. PCB 153 and PCB 155, the correlations were 383

the reversed, i.e. the leachability was positively correlated with the peat content but a negatively 384

correlated with the clay content. Thus, while leachability of moderately hydrophobic compounds, such 385

as HCHs, PCP and Phe is mainly influenced by organic matter content, the clay content may also 386

influence the leachability of highly hydrophobic compounds (Kow > 6), positively for co-planar 387

compounds (1,3,6,8-TCDD and 1,3,6,8-TCDF), and negatively for non-planar compounds (PCB 153 388

and PCB 155). 389

Overall, the leaching behavior of α-HCH and PCP seem to be quite similar despite the different 390

chemical nature of these two compounds. The low log Kd values recorded for HCHs and PCP were 391

similar with those recorded in previous studies [35, 37] in which they both were estimated to have high 392

leachability at contaminated sites. On the contrary, the BaA’s retention in the soil, was not influenced 393

significantly by the increasing proportions of organic matter in the soil matrix. The relationship log Kd394

vs. log Kow investigated in our study shows that the apparent log Kd values for highly hydrophobic 395

compounds, such as PCB 153 and PCB 155, 1,3,6,8-TCDD and 1,3,6,8-TCDF, may deviate from the 396

linear relationship seen for the less hydrophobic compounds due to colloids, present in the leachate, 397

acting as carriers for the highly hydrophobic compounds. If colloid-facilitated transport is not taken into 398

account, the concentration of dissolved contaminants in the water phase will be somewhat 399

overestimated, and the apparent Kd lower than the true value. Furthermore, for soils with very high 400

content of organic material or clay, our results show that the relation between log Kd and log Kow is less 401

linear for all compounds. Also our study demonstrated that beside the organic matter content of the soil, 402

the clay content may also influence the leachability of HOCs, especially for highly hydrophobic 403

compounds (Kow > 6). Our study demonstrated how complex interaction between both the organic 404

matter and clay components influences the leachability of highly hydrophobic compounds in a 405

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compound-specific manner. Therefore this study can be a step forward in the understanding and 406

assessment of mobility of organic contaminants in contaminated soil sites.407

Acknowledgements 408

The research of Silviu-Laurentiu Badea is funded by Umeå University. The work was performed within 409

the frame of the Northern Sweden Soil Remediation Center (MCN). The authors are gratefully to Dr. 410

Rui Climaco Pinto from BILS (Bioinformatics Infrastructure for Life Sciences) for his support with 411

multivariate analysis and to Dr. Andrey Shchukarev for his support with XPS analysis.412

413

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Table Captions413

Table 1. Summary of the distribution coefficients (log Kd values) determined for the model compounds 414

in the test soils.415

Figure Captions416

Fig. 1. OPLS loading scatter plots of Kd values for the model compounds.417

Fig. 2. Contour plots showing the variation of concentrations in leachates of α-HCH (A), PCP (B) and 418

Phe (C) vs. proportions of clay and peat in the artificial soils . The R2 values obtained from the MODDE 419

screening models were 0.80 for α-HCH, 0.51 for PCP and 0.30 for Phe respectively.420

Fig. 3. Contour plots showing the variation of concentrations in leachates of 1,3,6,8-TCDD (A) and 421

1,3,6,8-TCDF (B) vs. proportions of clay and peat in the artificial soils. The R2 values of the MODDE 422

screening models were 0.68 for 1,3,6,8-TCDD and 0.68 for 1,3,6,8-TCDF respectively.423

Fig. 4. Contour plots showing the variation of concentrations in leachates of HCB vs. proportions of 424

clay and peat in the artificial soils. The R2 values of the MODDE screening model was 0.69.425

Fig. 5. Contour plots showing the variation of concentrations in leachates of PCB 47 (A) PCB 153 (B) 426

and PCB 155 (C) vs. proportions of clay and peat in the artificial soils. The R2 values of the MODDE 427

screening models were 0.55 for PCB 47 and 0.36 for PCB 153 and 0.43 for PCB 155 respectively.428

Fig. 6. Log Kd values for the target compounds vs. their log Kow values, calculated for OECD standard 429

soil (A), M4 soil (20% sand, 20% clay and 60 % peat) (B) and M6 soil (30 % sand, 60 % clay, 10% 430

peat) (C). The OECD data were fitted linearly (black curve for all data and green curve excluding431

compounds 10 to 13) and quadratically (red curve for all data) (A). Eqns. (1) and (2) describe the linear 432

fits of all data and data excluding compounds 10 to 13, respectively (A). The target compounds were -433

HCH (1), -HCH (2), -HCH (3), -HCH (4), PCP (5), HCB (6), BaA (7), Phe (8), PCB 47 (9), PCB 434

153 (10), PCB 155 (11), 1,3,6,8-TCDF (12) and 1,3,6,8-TCDD (13).435

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Table 1. Summary of the distribution coefficients (log Kd values) determined for the model compounds in the test soils.

Compound Log Kd

OECDLog Kd M1 Log Kd M2 Log Kd M3 Log Kd M4 Log Kd M5 Log Kd M6 Log Kd M7 Log

Kow

[45]

-HCH 2.44±0.02 2.05±0.02 2.04±0.04 2.73±0.29 3.19±0.09 2.23±0.01 2.36±0.09 2.98±0.03 3.8

-HCH 3.15±0.01 3.04±0.17 2.70±0.003 3.41±0.20 3.96±0.01 2.97±0.05 2.95±0.03 3.56±0.11 3.78

-HCH 2.59±0.03 2.15±0.01 2.11±0.03 2.88±0.24 3.35±0.12 2.36±0.03 2.49±0.10 3.15±0.02 3.72

-HCH 3.23±0.03 2.99±0.03 2.87±0.07 3.49±0.07 3.95±0.08 3.05±0.07 3.05±0.04 3.87±0.01 4.14

5 PCP 3.46±0.11 2.84±0.02 2.68±0.06 3.32±0.03 3.46±0.10 2.84± 0.07 2.92±0.15 3.50±0.11 5.01

6 HCB 4.52±0.21 4.19±0.25 3.92±0.01 5.12±0.27 5.16±0.13 4.54±0.06 4.69±0.05 5.29±0.12 5.73

7 Benzo(a)anthracene 5.37±0.01 5.09±0.07 5.32±0.09 5.23±0.002 5.30±0.12 5.27±0.05 5.27±0.01 5.23±0.002 5.61

8 Phenanthrene 3.17±0.008 2.53±0.21 3.79±0.03 3.72±0.07 5.17±0.06 2.89±0.06 3.16±0.02 3.71±0.05 4.45

9 PCB 47 4.67±0.02 4.70±0.09 4.41±0.07 4.87±0.03 4.89±0.04 4.83±0.19 4.86±0.01 4.83±0.03 5.17

10 PCB 153 4.46±0.07 4.44±0.01 4.19±0.07 4.69±0.04 4.11±0.001 4.61±0.14 4.47±0.08 4.38±0.09 6.9

11 PCB 155 5.22±0.26 5.00±0.12 4.81±0.03 5.02±0.05 5.05±0.20 4.88±0.30 5.69±0.05 5.29±0.04 7.2

12 1,3,6,8-TCDF 4.65±0.15 5.24±0.07 4.77±0.09 5.66±0.08 5.40±0.19 4.29 4.41±0.03 4.60±0.10 5.92

13 1,3,6,8-TCDD 4.58±0.02 4.76±0.08 4.58±0.13 5.03±0.03 4.84±0.006 4.23 4.29±0.01 4.31±0.10 6.57

Sand % 70 85 90 50 20 50 30 10

Clay % 20 10 5 20 20 40 60 45

Composition of the artificial soils

Peat % 10 5 5 30 60 10 10 45

549

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-0.9

-0.8

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0.0

0.1

0.2

0.3

0.4

0.5

0.6

-0.7 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

pq[2

]

pq[1]

a-HCH

b-HCH

g-HCHd-HCH

PCP

HCB

BaA

Phe

PCB-47PCB-153

PCB-155

TCDFTCDD

Sand %

Clay %

Peat %

D

B

A

C

549 Fig. 1. OPLS loading scatter plots of Kd values for the model compounds.550

551

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A

B

C

551

Fig. 2. Contour plots showing the variation of concentrations in leachates of α-HCH (A), PCP (B) and 552

Phe (C) vs. proportions of clay and peat in the artificial soils . The R2 values obtained from the MODDE 553

screening models were 0.80 for α-HCH, 0.51 for PCP and 0.30 for Phe respectively.554

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A

B

555

Fig. 3. Contour plots showing the variation of concentrations in leachates of 1,3,6,8-TCDD (A) and 556

1,3,6,8-TCDF (B) vs. proportions of clay and peat in the artificial soils. The R2 values of the MODDE 557

screening models were 0.68 for 1,3,6,8-TCDD and 0.68 for 1,3,6,8-TCDF respectively.558

559

560

561

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561

Fig. 4. Contour plots showing the variation of concentrations in leachates of HCB vs. proportions of 562

clay and peat in the artificial soils. The R2 values of the MODDE screening model was 0.69.563

564

565

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A

B

C

565

Fig. 5. Contour plots showing the variation of concentrations in leachates of PCB 47 (A) PCB 153 (B) 566

and PCB 155 (C) vs. proportions of clay and peat in the artificial soils. The R2 values of the MODDE 567

screening models were 0.55 for PCB 47 and 0.36 for PCB 153 and 0.43 for PCB 155 respectively.568

569

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3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5

1.52.02.53.03.54.04.55.05.56.06.5

1

2

3

4

5

6789

10

1112

13

By = 0.6578x + 1.4665R2=0.58

log

Kd

log Kow

3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5

1.52.02.53.03.54.04.55.05.56.06.5

1

2

3

4 5

6

7

8

910

11

12 13

Cy = 1.4793x - 2.97163R2=0.90

log

Kd

log Kow

3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5

1.52.02.53.03.54.04.55.05.56.06.5

1

2

3

45

6

7

8

910

11

12 13

Ay = 1.0266x - 1.0291 (1)R2=0.71y = 1.3478x - 2.4133 (2)R2=0.85

log

Kd

log Kow

569

Fig. 6. Log Kd values for the target compounds vs. their log Kow values, calculated for OECD standard 570

soil (A), M4 soil (20% sand, 20% clay and 60 % peat) (B) and M6 soil (30 % sand, 60 % clay, 10% 571

peat) (C). The OECD data were fitted linearly (black curve for all data and green curve excluding 572

compounds 10 to 13) and quadratically (red curve for all data) (A). Eqns. (1) and (2) describe the linear 573

fits of all data and data excluding compounds 10 to 13, respectively (A). The target compounds were -574

HCH (1), -HCH (2), -HCH (3), -HCH (4), PCP (5), HCB (6), BaA (7), Phe (8), PCB 47 (9), PCB 575

153 (10), PCB 155 (11), 1,3,6,8-TCDF (12) and 1,3,6,8-TCDD (13).576

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Highlights577

Kd-values were determined for 13 HOCs in batch tests with varying soil composition.578

Log Kd-values (ranged from 2 to 5.7) were lowest for α-HCH and highest for PCB 155.579

The clay content may influence significantly the leachability of HOCs with Kow > 6.580

581