Ecotoxicology and Environmental Safety 139 (2017) 102–108
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Rates and equilibria of perfluorooctanoate (PFOA) sorption on soils from different regions of China
MARK
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Yu Miaoa, Xuetao Guoa,b, , Dan Pengc, Tingyu Fana, Chen Yangb a b c
School of Earth and Environment, Anhui University of Science and Technology, Huainan 232001, China Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control (SCUT), Guangzhou 510006, China School of Traffic and Environment,Shenzhen Institute of Information Technology, Shenzhen 518172, China
A R T I C L E I N F O
A B S T R A C T
Keywords: Perfluorooctanoate Sorption Soil Organic carbon Mineral
Understanding sorption of PFOA on soil particles is crucial to evaluate its environmental risk. Here, sorption of PFOA onto ten agricultural soils was examined. The influence of soil physico-chemical properties on PFOA sorption was investigated. The sorption rate of PFOA followed a pseudo-second-order kinetics. Isotherm data of PFOA sorption was fitted with both Freundlich and linear models and the latter fitted better. The sorptiondesorption of PFOA onto ten soil samples depended on soil organic carbon content and composition of soil minerals. The sorption and desorption isotherms of PFOA on ten soils were linear, except for the sorption of PFOA onto a few soils, which was described by the Freundlich equation with the parameter N > 1. The main sorption mechanism of PFOA was hydrophobic interaction between the perfluorinated carbon chain and the organic matter of soil, as evidenced by the correlation between the solid-liquid distribution coefficient and the fraction of soil organic carbon. The sorption of PFOA in soils was highly irreversible.
1. Introduction Persistent organic pollutants (POPs) have attracted broad attention because of their toxicity stability, bioaccumulation, and wide distribution. Perfluorooctanoate (PFOA) has been categorized as one of the POPs in 2009, which is extensively used in different areas until being partially restricted very recently (Milinovic et al., 2016; Yu et al., 2009; Zhou et al., 2013a). However, PFOA is still unreplaceable in some special industrial and commercial areas, such as firefighting, electroplating and etc (Deng et al., 2012; Ololade et al., 2016; Xu et al., 2015). The extreme chemical stability and non-degradability originate from the high-energy carbon-fluorine (C-F) bonds in PFOA, which induce their resistance to hydrolysis and to thermal, microbiological and photolytic degradation (Milinovic et al., 2015b). Owing to the previous abuse usage and the stability, PFOA is ubiquitously existed at ng/L levels in sediment, soils, water and sewage sludge (Liu et al., 2015; Milinovic et al., 2015b; Zhao et al., 2014; White et al., 2015). Exact data on the concentrations of perfluoroalkyl substances (PFASs) in soils are scarce in the literature. PFASs were found in some soil samples from several countries (China, Japan and USA), with the highest concentrations of 10 and 30 ng/g, which were found for PFOS and PFOA, respectively (Strynar et al., 2012). Analyzing the soil samples from Shanghai (China) gave similar PFOS and PFOA contamination levels
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attributed to the manufacturing and usage of perfluoro-containing products (Li et al., 2010). The case is getting worse as they are still allowed to be used in diverse fields in China (Wang et al., 2013, 2010). Here, we can also compared China with North America, Europe, Africa, Australia, South America and Antarctica (Rankin et al., 2016). Therefore, a thorough understanding of the fate of PFOA in soils is important for evaluating, their ecological and environment harmfulness. As mentioned above, PFOA is difficult to be decomposed in ambient environments (Vecitis et al., 2009; Zhou et al., 2010a). Sorption of PFOA to soils is a crucial process that determines its fate, transport, and transformation in the environment. Thus, not only the total concentration of PFOA in the soil, but also the sorption mechanism between the soil components and PFOA needs to be considered to better evaluate their risk (Milinovic et al., 2015a). The sorption behavior of PFAAs on soils/sediments has been studied previously (Wang et al., 2015). For example, Milinovic et al. (2015b) investigated sorption of PFOS, PFOA and PFBS on six soil samples with a significant amount of soil organic carbon content, which indicated that the hydrophobicity mainly controlled their sorption behavior in soils. Comparatively, Li et al. (2012) reported the sorption parameters such as the solid-liquid distribution coefficient (Kd) of PFOA in Yangtze River sediments, which revealed that the sorption is mainly depended on the organic carbon
Corresponding author at: School of Earth and Environment, Anhui University of Science and Technology, Huainan 232001, China. E-mail address:
[email protected] (X. Guo).
http://dx.doi.org/10.1016/j.ecoenv.2017.01.022 Received 22 August 2016; Received in revised form 11 January 2017; Accepted 12 January 2017 0147-6513/ © 2017 Elsevier Inc. All rights reserved.
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content of the sediments. Overall, the organic carbon (OC) content of soils plays a significant role in influencing the sorption behavior of PFASs. Although there is some literature studying the sorption of PFOA in river and marine sediments, there are still no systematic studies on the sorption-desorption behavior of PFOA in soils (mineral soils and pure soils); Only a few previous studies focused on the sorption and desorption behavior of PFOS in soils (Milinovic et al., 2015b). Here, we systematically studied the sorption behavior of PFOA in ten different soils with varied physical and/or chemical properties, particularly to identify the influence of the different parameters of the soil on the interaction process with PFOA and further to evaluate their behavior once being incorporated into the soil as a consequence of the repeated addition of sewage sludge to agricultural soils. The sorption kinetics of the PFOA on the ten soil samples with a broad range of soil organic carbon content was summarized. The sorption and desorption isotherms were obtained for PFOA in a wide range of concentrations, and the Kd values were derived from fitting the isotherms to appropriate simple models (Freundlich and linear). The sorption mechanism was explained based on to the physicochemical properties of PFOA and the properties of different soils. At last, the sorption reversibility of each compound was determined.
Fig. 1. Distribution of the sampling sites in China.
was higher than 10% in all soil samples reflected from the particle size analysis. According to USDA criteria, S03, S05, S06, S07 and S08 soils had the higher silt percentage, in the form of silt loam texture. S04, S09 and S10 soils with different OC contents, were sandy loam soils. S01 and S02 soils, with the highest OC content of the soils studied, were clay loam and loam soils, respectively.
2. Materials and methods 2.1. Reagents and standards
2.3. Sorption procedure
PFOA of analytical standard was purchased from Sigma-Aldrich Corporation (St Louis, MO). The water solubility of PFOA was 3.4 g/L with a very low pKa values (pKa =−0.2). Therefore, it tends to be dissociated into anionic species in the aqueous solution, whose pH value is usually higher than 4.0 (Li et al., 2012; Zhou et al., 2010b). The octanol-water partition coefficient (KOW) of PFOA differs significantly in previous studies, owing to the determination methods of this parameter for hydrophobic organic compounds is quite different (Milinovic et al., 2015c). Acetonitrile and formic acid (HPLC grade, Merck Chemicals Co. AQ5) were used as received. Pure water was prepared by a Milli-Q® water machine (Millipore Co., Huainan, China). All the other chemicals were of analytical reagent grade and were used without further purification. PFOA was dissolved into acetonitrile at 1000 mg/L and stored at 4 °C for a maximum of 1 month. The stock solution was diluted at desired times using Milli-Q® water to prepare work solutions at different concentrations. All solutions were stored at 4 °C in 20 mL glass vials with polyethylene caps (Sigma-Aldrich, Germany).
The PFOA’s sorption kinetics on soils was studied with the acetonitrile containing a certain concentration (250 μg/L) of PFOA with a pH value of 6.8. And the pH of the solution was adjusted to 6.8 by adding HNO3 or KOH. Briefly, 0.05g of the soil and 20 mL of PFOA solution were added to 25 mL of Teflon-lined centrifuge tubes and in the cap we added aluminum foil to avoid the effect of the concentrations of PFOA in the solution. At the same time, 0.01 M KNO3 and 0.001 M of NaN3 were added to maintain a constant ionic strength and depress microbial activities, respectively (Li et al., 2015). After vortexmixing for 30 s, the solution was shaken at 250 rpm and 25 ± 2 °C for 0–48 h before centrifuging at 4000 rpm for 10 min. Consequently, 1 mL of the supernatant was transferred to a pre-weight 1.5 mL amber glass vial for chemical analyses. At each concentration level, the experiments were run in three parallels. The adsorbed mass of PFOA in soils was calculated based on the concentration difference, which can be expressed as:
qt = (C0 −Ct )V / m
2.2. Soil characterization
(1)
where qt is the concentration (mg/kg) of PFOA in soils at sampling time t. C0, Ct, V, and m are the initial PFOA concentration (ug/L), PFOA concentration (ug/L) in solution at sampling time, total solution volume (mL), and soils mass (g), respectively. The sorption experiments were conducted using a batch equilibrium technique at 25 °C with a pH value of 6.8. The initial PFOA concentrations were set from 10 to 500 μg/L, including 10 μg/L, 100 μg/L, 250 μg/L, 300 μg/L and 500 μg/L. The background solution containing 0.001 M NaN3 to minimize the bioactivity and 0.01 M KNO3 was to adjust the ionic strength. The initial aqueous solution with different amounts of different soils were vigorously mixed in a batch reactor system (CMBR) and mixed for sorption equilibrium on a shaker at 150 rpm. The sorption equilibrium time for PFOA were 24 h. After the sorption experiments, the screw cap vials were centrifuged at 4000 rpm for 30 min, then 1 mL of the supernatant was transferred into a preweight 1.5 mL amber glass vial for chemical analyses. At each concentration level, the experiments were performed for three times. KOH or HNO3 solutions were used for adjusting the pH value of the solution.
Ten agricultural soil samples (named as S01, S02, S03, S04, S05, S06, S07, S08, S09 and S10) were selected from different provinces of China with prominently contrasting characteristics. Details of the location for all sampling sites are listed in Fig. 1. The soil samples were taken from the top layer (0–10 cm depth), and then air-dried and sieved through a 2 mm mesh. Prior to analysis, the soil samples were homogenized with a roller table and stored at room temperature. The organic carbon, cation exchange capacity (CEC), and the pH of the soils were measured according to previously reported soil testing procedures (Maszkowska et al., 2015; Milinovic et al., 2015a; Xiang et al., 2016). The other characteristics of the soil samples were evaluated: the iron and aluminum oxides, texture (sand, silt, and clay) was obtained by a Bruker phaser diffractometer system using the whole sample procedure (randomly oriented mounts) and the spectra were analyzed using PAN anlytical X′Pert High Score software. Detailed information on sampling and measurement procedures are available elsewhere (Soares and Alleoni, 2008). The main physicochemical characteristics of the ten soils investigated here were summarized in Table 1. The clay content 103
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Table 1 Physicochemical properties of soils from different sources of China. Soil
S01 S02 S03 S04 S05 S06 S07 S08 S09 S10
Location
HaErBin HuaiNan BeiJing ZhuMaDian XiaMen ShangHai YingTan YanAn HaiKou GuangZhou
pH
6.96 8.02 8.78 5.07 7.65 7.43 4.84 8.59 7.08 5.86
CEC (cmol/k)
25.3 12.5 7.62 8.50 9.44 14.2 11.8 9.41 7.26 10.3
OC (%)
5.76 5.06 4.80 3.61 3.02 2.47 1.70 1.48 1.05 0.52
(% wrt mineral content) Clay (%)
Silt (%)
Sand (%)
46.2 37.1 19.2 16.4 25.1 18.7 22.7 11.5 10.7 35.4
30.3 29.8 42.1 37.2 40.8 51.2 39.7 58.2 29.9 27.7
23.6 33.1 38.7 46.4 34.1 30.1 37.6 30.3 59.5 36.9
SiO2 (%)
Fe2O3 (%)
Al (OH)3 (%)
63.1 64.3 68.9 76.0 73.9 65.5 65.9 67.0 58.8 74.4
4.34 5.33 3.75 2.55 2.67 5.59 6.45 4.45 8.31 3.21
13.3 13.8 12.0 10.3 11.4 14.0 16.0 12.1 21.4 11.8
Linear (Eq. (5)) and Freundlich (Eq. (6)) models were used to fit the equilibrium sorption data (Guo et al., 2015b, 2016) :
Desorption experiments were performed with a single cycle decant refill technique. In brief, after completion of the sorption test, each CMBR was weighed. Subsequently, the supernatant in each reactor was emptied with a pipette and then the reactor with the precipitates was weighed to calculate the amount of PFOA free background aqueous solution. Then, it replaced with the same volume of a solution that contained the same background solution but free of PFOA. Afterwards, the reactor was reweighed, capped, and placed in the shaker for the desorption experiments. After mixing at the same conditions, the tubes were centrifuged and set upright for 24 h. The supernatant was withdrawn from each reactor to quantify PFOA in the solution phase.
qe = Kd⋅Ce qe =
K F⋅Cen
(5) (6)
Where Ce (mg/L) and qe (mg/kg) are the equilibrium concentration of PFOA in the liquid phase and solid phase, respectively; The distribution coefficient of solute between soil and water is Kd (L/kg). The capacity affinity parameter is KF (µg/g)/(mg/L)n. n (dimensionless) is the exponential parameter. Parameters were estimated by nonlinear regression weighted by the dependent variable.
2.4. Sorption models 2.5. Chemical analysis The sorption kinetics data was fitted by pseudo-first-order (Eq. (2)), pseudo-second order (Eq. (3)),and the intraparticle diffusion models (Eq. (4)). Time intervals were 15, 30, 45 min, and 1, 2, 3, 5, 7, 12, 24, 36, 48 h. The models can be described using the equations written as follows (Guo et al., 2015a):
log(qe − qt ) = log q e−
k1t 2.303
The concentration of PFOA was determined using a Hitachi (Japan) LC-2000 HPLC equipped with a CDD- 10Avp conductivity detector. 20 μL of the samples were injected into the HPLC system. A TC-C18 column (4.6×250 mm; 5 µm) purchased from Phenomenex (U.S.) was used. Methanol/0.03 M NaH2PO4 (75/25) was used as the mobile phase at a flow rate of 0.8 mL/min. Linear calibration curves (R2 > 0.99) were fitted for all experiments.
(2)
t 1 t = + qt qe k 2qe2
(3)
qt = kit 0.5 + Constant
(4)
3. Results and discussion 3.1. Sorption kinetics of PFOA onto ten soil samples The sorption kinetics of PFOA on tested soils are shown in Fig. 2(a). In general, three stages of the sorption process of PFOA to the soils could be revealed. First, significant sorption occurred at the initial 7 h. Then, the sorption gradually increased at a much slower rate and
Where qt and qe are the amounts of sorption PFOA at time t and at equilibrium respectively. The first-order, second-order and intraparticle diffusion model apparent sorption rate constants are k1, k2 and ki, respectively.
Fig. 2. Sorption kinetics of PFOA in soils: (a) Relationships between the contacting time and the PFOA concentration in soils and (b) the pseudo-second order model fit to PFOA sorption kinetics data.
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eventually saturated after nearly 24 h for all of the ten soil samples, indicating that the dynamic equilibrium was reached. Our results are similar to those of (Higgins, 2006), who reported that the sorption kinetic process of PFOS on soils was a rapid initial transfer into the near surface boundary layer of the soil aggregate. As shown in Fig. 2(a), for all of the ten soil samples, the maximum sorption capacity follows the order: S01 > S02 > S03 > S04 > S05 > S06 > S07 > S08 > S09 > S10, which is consistent with the order of their soil organic carbon content. Therefore, our study supports that the hydrophobicity plays a key role in determining the PFOA sorption onto ten soil samples (Milinovic et al., 2015c). To further understand the sorption kinetics, pseudo-first-order, pseudo-second-order and intraparticle diffusion models were applied to analyze the sorption kinetics data. As seen from SI Table 1 the estimated correlation coefficient (R2) demonstrated that the pseudosecond-order rate model could perfectly fit the sorption rate data over the entire period of experiment (R2 > 0.99), as shown in Fig. 2(b). According to the pseudo-second-order rate equation, the rate constant k2 is positively related to the sorption rate, which is theoretically determined by the property of the sorbate for a given sorbent (Dai et al., 2013). As seen from the fitted k2 values in SI Table 1, the sorption rate on different soil samples is most likely related to the mineral substance content in soils (Zhao et al., 2014; Zhou et al., 2010a). The relationship between k2 and the mineral substance content in soils, including SiO2, Al2O3 and Fe2O3 were displayed in Fig. 3. The SiO2 was extracted by hot concentrated acid digestion, while Al2O3 and Fe2O3 were extracted by dithionite. The dependence between k2 and the mineral content is negatively associated with the content of silica and positively associated with the content of Al2O3 and Fe2O3 (Johnson et al., 2007; Wang and Shih, 2011; Zhou et al., 2013b). The k2 of the PFOA sorption onto soil samples was increased as the content of the Al2O3 and Fe2O3 increased, while decreased with the increasing content of silica, indicating a faster sorption rate of PFOA onto soils with the higher content of Fe oxide minerals. For the soils, the sorption rate is mainly determined by the available sorption sites for the sorbent, typically exhibiting a positive correlation (Ololade et al., 2016). In the present study, the alumina and iron oxide have more sorption sites available for the sorbent, which may have the interactions with PFOA via electrostatic forces (Johnson et al., 2007; Wang and Shih, 2011). Tang et al. (2010) reported that PFOS sorption onto the silica surface was primarily driven by the strong electrostatic repulsion between the charged sulfonate head groups and the silica surface and the hydrophobic interaction between the perfluoroalkyl tails and the hydrophobic moieties on the silica surface. Similarly, Johnson et al. (2007) hypothesized that the sorption of PFOS on iron oxide surfaces might be dominated by the electrostatic attraction between the negatively charged head groups and the positively charged mineral surfaces. Wang et al. (2012) found that the sorption of PFOA onto [Al(OH)3] surface was related to the formation of hydroxyl groups, which can facilitate the PFOA sorption.
Fig. 4. Sorption kinetics of PFOA on soils fitted by intraparticle diffusion model.
The intraparticle diffusion model was adopted to fit the sorption kinetics instead of the pseudo-second-order, because the latter cannot provide a definite process for sorption. The model illustrates that a good linear relationship should be obtained from the plot of sorbate uptake (qt) vs. the square root of time (t0.5) if intra-sorbent diffusion is the exclusive rate-controlling factor in a given system. Moreover, and the fitted line should also pass through the origin. As shown in Fig. 4, the intraparticle diffusion model could fit the sorption data of PFOA onto ten soil samples, but the plots did not pass through the origin, implying that the boundary layer diffusion might have been a rate-controlling step. The sorption rate might also be influenced by other factors, including the morphology and the natural properties of the soils, the concentration of the PFOA, and its affinity to the sorbent (Cheung et al., 2007). As seen in Fig. 4, the nonlinear plots throughout the experiments suggest that more than one factors can affect the sorption process. The sorption process of PFOA onto soils can be separated into three possible steps. The initial linear portion demonstrated a rapid sorption event containing two steps: (1) PFOA diffusion into the liquid phase; (2) external mass transfer to the soil particles’ surface. The later stage is the equilibrium stage, namely intra-sorbent diffusion onto the sorption sites. In addition to the remaining amount of PFOA in the solution, the morphology and the structure of the soil particles can also influence the sorption kinetics. The sorption slope of the ten soil samples was decreased as the content of the soil organic carbon content decreased. Therefore, the diffusion and sorption of PFOA onto soils require a long time while to achieve a greater sorption capacity. This three-stage sorption process is similar to the results reported from previous studies (Cheung et al., 2007; Yu et al., 2009). 3.2. Sorption and desorption isotherm of PFOA onto ten soil samples Fig. 5 shows the sorption isotherms of PFOA onto ten soil samples.
Fig. 3. The relationship between the k2 and the mineral substance content in soils.
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Fig. 5. Sorption and desorption isotherms of PFOA onto ten soils.
There is a linear relationship between the sorption pattern of Ce vs. qe for all PFOA-soil combinations at the concentration ranges studied, which was also confirmed by the nearly constant Kd values as a function
of Ce changes. Regarding the PFOA, the Ce vs. qe plots followed a linear relationship, as confirmed by the N parameter of the Freundlich model, which approached 1 except for S01, S02 and S10 (SI Table 2) . The
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of 2.0–3.2 for PFOA from similar experiments, but agrees well with the value obtained from soil samples with a higher OC content (5.76) (Chen et al., 2013; Milinovic et al., 2016). Although individual KOC values could be obtained for each soil, a KOC derived from the correlation would be more representative of a series of soils with a broad range of OC content, which is the case of the present study. This is because the soils with an extremely low OC content might lead to overestimation of the KOC value (Milinovic et al., 2015b). The KOC obtained from adsorption experiments, even after being normalized to the organic matter content, still varies as a function of the nature of the type of solid phase considered (Zareitalabad et al., 2013). In view of this, the KOC values obtained in this work for ten different soil samples with very different compositions, agrees with the mean value reported for different matrices at different experimental conditions, with KOC of 2.1 for PFOA (Zareitalabad et al., 2013).
Fig. 6. Correlation between Kd and organic carbon fraction for PFOA sorption onto ten soils.
linearity of sorption isotherms was consistent with previously reported results for PFOA sorption. Sorption is promoted predominantly by Van der Waals interactions between solute molecules and soil organic matter for nonpolar hydrophobic compounds such as PFOA according to previous studies (Enevoldsen and Juhler, 2010; Milinovic et al., 2015c). The Kd values obtained from the slope of the linear isotherms for all of the soil samples in the concentration range from 0.487 to 1.477 mL/g were similar to the KF alues in the range of 1.602–8.846 mL/g. Considering that both parameters were highly correlated (R2 > 0.92), both models were suitable for describing PFOA sorption in soils. Both parameters were in a sequence of increasing values, which is in consistent with the increase in OC content. But for S01, S02 and S10 the N parameter of the Freundlich model was larger than 1. Two possibilities might induce this behavior: (1) solute-solute interactions through vertical packing of alkyl chains, which may cause cooperative sorption (Milinovic et al., 2016); (2) interactions with sorption sites of different nature (hydrophobic interaction with organic matter and hydrophilic interaction with clay) (Droge et al., 2009; Jeon et al., 2011; Yu et al., 2012). Only in three soil samples with N > 1 suggests that the solutesolute interaction is unlikely the main reason. Taking into account that N > 1 was observed for S01 and S02 with the highest OC ratios, as well as the fact that PFOA is polar in nature (logKOW 4.59), it is most likely that the OC in the solid phase dominate the PFOA adsorption process.
4. Conclusions The sorption behavior of PFOA onto different soils with different organic content is systematically studied. The sorption kinetics of PFOA followed pseudo-second-order kinetics. Isotherm data of PFOA sorption was fitted with both Freundlich and Linear models with the latter one more reasonable. The sorption-desorption behavior of PFOA onto ten soil samples depended not only on the physico-chemical properties of the studied compound, but also on the soil characteristics, particularly the soil organic carbon content and the soil mineral composition. In general, sorption and desorption isotherms of PFOA on ten soil samples were all linear, except for the sorption of PFOA onto SO1, S02 and S10 soil samples, which was described by the Freundlich equation with N > 1. The main sorption process of PFOA was attributed to the hydrophobic interaction between the perfluorinated carbon chain and the organic component of the soil, as evidenced by the correlation between the solid–liquid distribution coefficient and the fraction of the organic carbon. Overall, the sorption of PFOA in soils is highly irreversible, which is favourable in remediation of the PFOA contaminated agricultural soils through the repeated addition of sewage sludge by immovilization. Acknowledgements
3.3. Correlation of Kd with physico-chemical properties of ten soil samples
The study was financially supported by the China National Science Fund Program (No. 41503095), the Natural Science Foundation of Universities of Anhui Province (KJ2015A016), Shenzhen Science and Technology Planning Research (JCYJ20150417094158012), the China Postdoctoral Science Foundation funded project (No. 2016M601994), the PhD Fund of Anhui University of Science and Technology (ZY540) and the Key Science Foundation for Young Teachers of Anhui University of Science and Technology (QN201507).
As OC played a major role on the sorption and desorption parameters of PFOA onto soils, the relationship between Kd and the fraction of the organic carbon in soil was further explored. The Kd of organic compounds in soils can be expressed as a sum of two originations. In a simplistic approach, a soil can be considered as a mixture of two main components, the organic and the mineral part. Thus, the solid-liquid distribution coefficient of a compound in a soil can be expressed as (Milinovic et al., 2015c):
Kd = Kd,ORG + Kd, MIN = Koc⋅Foc + Kd, MIN Koc =
Kd, MIN 1 Kd − FOC FOC
Appendix A. Supporting information
(7)
Supplementary data associated with this article can be found in the online version at doi:10.1016/j.ecoenv.2017.01.022.
(8)
References
Where Kd, ORG can be expressed as the product of the solid-liquid distribution coefficient of the compound in the organic fraction (referred to the weight of organic carbon), fOC, and the fraction of organic carbon in the soil, FOC, expressed as grams of organic carbon per gram of soil. Therefore, the KOC value can be calculated from the slope of the Kd vs. FOC relationship obtained for ten soils for a given compound. Fig. 6 plotted the correlations investigated in this study for PFOA. The strong dependence between the Kd values and the soil organic carbon for PFOA (R2 =0.977) allowed us to deduce KOC values from the slope of the curves, which showed that a KOC =5.615 mL/g for PFOA. The deduced KOC values for PFOA (5.61) is higher than the reported values
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