1 Background, aim, and scope

Plastics have benefits in a wide range of areas including technology, energy savings and improved consumer health. The packaging industry uses the most plastic, 18 million tons corresponding to 40.1% (Plastics Europe 2010). Polyethylene (PE) is about one third of the Europe plastics demand among other resin types (Plastics Europe 2010). Recently, PE devices have been applied for measuring polycyclic aromatic hydrocarbons (PAHs) in aquatic environments (Mueller et al. 2001; Booij et al. 2003; Adams et al. 2007; Cornelissen et al. 2008; Hale et al. 2010; Smedes et al. 2009).

Plastic debris in aquatic ecosystems is a rapidly increasing long-term and widespread threat that represents a great challenge for remediation (Zarfl et al. 2011). Since the early 1970s, plastic debris has become widespread in marine habitats, in sediment and in the surface waters of coastal areas and oceans throughout the world (Goldberg 1997; Mato et al. 2001; Derraik 2002; Rios et al. 2007; Sheavly and Register 2007; Moore 2008; Barnes et al. 2009; Ryan et al. 2009; Browne et al. 2010). PE is one of the primary synthetic polymers found in the oceans (Mato et al. 2001).

PE is classified into several different categories based mostly on its density and branching. In terms of sold volumes, the most economically important grades are high density polyethylene (HDPE) and low density polyethylene (LDPE) that account for 12% and 17%, respectively, of the total European plastic materials demand (Plastics Europe 2010).

PAHs are a class of hydrophobic organic chemicals (HOC) that occur all over the world in seawater (Da Silva et al. 2007; Arias et al. 2009; Ren et al. 2010). It has been reported that pre-processing plastic pellets and fragments of consumer products in ocean environments are contaminated with PAHs (Rios et al. 2007). Organic pollutants associated with plastics have been identified as one of the hazards related to plastic debris in the marine environment (Betts 2008). Zarfl and Matthies (2010) reported that HOC with octanol–water partitioning coefficients (log K OW) >6.5 have an enhanced mobility because of their sorption to buoyant microplastic material. Plastic debris floating on the surface of the ocean can be ingested by seabirds (USEPA 1990; Ryan et al. 1988; Blight and Burger 1997; Moser and Lee 1992; Spear et al. 1995; McCauley and Bjorndal 1999; Provencher et al. 2009) and hazards from a subsequent transfer of sorbed contaminants must be considered.

Environmental hazards associated with sorbed PAHs to microplastics in the aquatic environment were assessed theoretically assuming thermodynamic equilibrium (Gouin et al. 2011). Although results suggested microplastic being of low importance as a vector of substances to aquatic organisms in comparison with other exposure pathways, the authors identified a need to better understand the influence of material properties on the Fickian diffusion of a chemical through the polymeric material. For instance, a decreased diffusivity for several hydrocarbons was observed with increasing polymer crystallinity (Vittoria 1995; Luetzow et al. 1999). In the study of Karapanagioti and Klontza (2008), a slower diffusion of phenanthrene into plastic-eroded pellets compared to virgin materials was attributed to an increase in crystallinity due to weathering. Although several sorption studies of PAHs were performed with PE passive samplers, powder and pellets (Booij et al. 2003; Adams et al. 2007; Teuten et al. 2007; Cornelissen et al. 2008; Karapanagioti and Klontza 2008; Smedes et al. 2009; Hale et al. 2010), the influence of different types of PE on the sorption behaviour of PAHs has been addressed rarely. In Mueller et al. (2001), the hypothesis that different types of PE passive samplers have different sampling properties was not definitely answered.

The objective of the present study was to investigate the diffusivity of several PAHs in LDPE and HDPE. Batch sorption experiments were performed with acenaphthylene, acenaphthene, fluorene, phenanthrene, anthracene and fluoranthene and with LDPE and HPDE pellets, respectively.

2 Materials and methods

2.1 Chemicals and sorbents

A ‘PAH Mix’ standard solution was purchased from Neochema (Bodenheim, Germany), containing acenaphthylene (ACY), acenaphthene (ACE), fluorene (FLN), phenanthrene (PHE), anthracene (ANT) and fluoranthene (FLT) in acetone with a concentration of 50 ng μL−1 of each PAH. Acetone (HPLC grade) was purchased from Sigma Aldrich (Seelze, Germany). Ultrapure water was taken from a Sartorius Arium 611VF water purification system (Goettingen, Germany). PAH stock solutions with final concentrations of each PAH of 60 and 100 ng L−1 were produced by adding 3 and 5 μL, respectively, of the ‘PAH Mix’ standard solution to 2.5 L of ultrapure water. All PAHs were <0.01% saturation. The stock solution of 100 ng L−1 was diluted proportionately with ultrapure water to levels between 1 and 100 ng L−1. A mixture of deuterated PAHs containing D10-ACE and D10-PHE with a concentration of each compound of 500 ng μL−1 was purchased from Dr. Ehrensdorfer GmbH (Augsburg, Germany). A stock solution with a concentration of 50 pg μL−1 was prepared with acetone and used as an internal standard (IS).

LPDE pellets (Lupolen 1840 D, LyondellBasell) and HDPE pellets (Hostalen ACP 9255 Plus, LyondellBasell) were used as sorbents. The densities of LPDE and HPDE were given in the product data sheets at 0.919 (LyondellBasell 2007a) and 0.957 g cm−3 (LyondellBasell 2007b), respectively. The mean measured mass (n = 10) was 14 ± 2 mg for LDPE and 34 g ± 3 mg for HDPE. The measured mean sizes (n = 6) were 4.0 × 4.4 × 2.0 mm (width × length × height) for LDPE and 4.2 × 4.7 × 2.8 mm for HDPE.

2.2 Batch experiments

One plastic pellet and 7 mL of the PAH stock solution containing ACY, ACE, FLN, PHE, ANT and FLT (60 ng L−1 of each PAH) were added to a 10-mL glass vial (Gerstel, Muelheim, Germany). The vial was sealed with a magnetic crimp cap equipped with a Teflon-faced silicone septum (Gerstel, Muelheim, Germany) wrapped with aluminium foil. Samples were shaken in the dark at 20 ± 1°C for 16 time intervals within one week in a reciprocating shaker at 300 rpm. After being shaken, the cap was opened, the pellet and the aluminium foil were quickly removed with tweezers, 9 μL of the IS stock solution were added and the caps were closed immediately.

To assess compound loss from additional removal processes, e.g. sorption to the glass wall and/or volatilization, controls (7 mL PAH stock solution, 60 ng L−1) were shaken for similar time periods. The analytical loss was taken into account in the mass balance equation used in the calculation of the diffusion coefficients. For all of the sorption experiments, procedural blanks (ultrapure water, pellet) were shaken daily and weekly, respectively. All samples were performed in triplicates.

The influence of time (t) on the ratio between the mean concentrations in the aqueous phase of the sorption samples (Caq) and the controls (Caq,c) (n = 3) was tested by an analysis of variance (ANOVA) with IBM SPSS Statistics 15.0 assuming a significance level (p) of 0.01. A triplicate sample was considered to reach equilibrium when the last two measurements (24 h and one week) were statistically the same.

For determination of sorption distribution coefficients (K PE,24h), one LDPE pellet was shaken for 24 h in a reciprocating shaker at 300 rpm in 7 mL of the PAH solution using eight concentrations of PAHs in the initial concentrations range of 1–100 ng L−1. All concentration levels were repeated in triplicates. Controls were also performed at each concentration level in triplicates. Sorption isotherms were generated using a linear model. The slope of the plot Caq,24h against the solid-phase concentration CPE,24h (nanogrammes per kilogramme) represented KPE,24h. Therefore, CPE,24h denotes the PAH concentration in the pellet after 24 h calculated from Caq,24h assuming mass balance after correction by the control concentration in solution after 24 h (Caq,c,24h) as described in Section 2.4.

2.3 Chemical analysis

The concentrations of PAHs in the aqueous phase were determined by solid-phase microextraction (SPME) using a 65-μm polydimethylsiloxane–divinylbenzene fibre (PDMS/DVB) (Supelco, Seelze, Germany) and gas chromatography–mass spectrometry (GC–MS). The method was described in detail in Kukučka et al. (2010). In brief, extraction temperature and time were 60°C and 60 min, respectively. Agitating speed was 250 rpm. Before extraction, the fibre was pre-baked for 15 min at 270°C in a separate needle heater. Desorption from the fibre was carried out in the GC inlet at 270°C for 5 min in splitless mode. GC analyses were performed on a 6890N GC system coupled with a 5973 inert mass selective detector (Agilent Technologies, Santa Clara, USA). A HP-5MS capillary column (5% diphenyl–95% dimethylpolysiloxane), 30 m × 0.25 mm i.d., 0.25 μm film thickness (Agilent Technologies, Santa Clara, USA) was used for chromatographic separation. The GC programme was as follows: 80°C (5 min hold), then at 15°C min−1 to 180°C followed by 5°C min−1 to 310°C (5 min hold). Helium was used as the carrier gas with a flow rate of 1.5 mL min−1. MS with electron impact ionisation (EI) at 70 eV was operated in selected ion monitoring mode. The limits of detection (LODs) were between 0.1 ng L−1 (ANT) and 5.14 ng L−1 (FLT). Values of Caq in blank samples were all below LOD.

2.4 Sorption model

Kinetic sorption of organic substances to plastic pellets can be described by the diffusion model based on Fick’s second law in spherical coordinates (Karapanagioti et al. 2010) simulating the change of the solute concentration CPE (in nanogrammes per kilogramme) in the pellet over time t (in seconds) and assuming the pellet to be spherical with a radius r (in centimetres)

$$ \frac{{\partial {C_{\text{PE}}}}}{{\partial t}} = \frac{{{D_{\text{PE}}}}}{{{x^2}}}\frac{\partial }{{\partial x}}\left( {{x^2}\frac{{\partial {C_{\text{PE}}}}}{{\partial x}}} \right) $$
(1)

where D PE (in centimetres per second) is the constant diffusion coefficient in the pellet and x (in centimetres) is the distance from the centre of the plastic pellet with 0 ≤ x ≤ r. As described above, sorption experiments were conducted in batches in keeping with tried and tested procedures for batch experiments used to analyse sorption of organic compounds to soil and sediment (OECD 1996).

According to Grathwohl (1998), the following assumptions were made: (1) the solid phase is free of solute at the beginning of the experiment (C PE  = 0 at t = 0 and for all x with 0 ≤ x ≤ r), and (2) in the long run, the concentration in the solid phase reaches equilibrium (\( C_{\text{PE}}^{*} \)) at the surface (\( {C_{\text{PE}}} = C_{\text{PE}}^{*} \) at t = ∞ and for x = r), and (3) in the centre (x = 0), the solute concentration does not change in space after the beginning of the experiment (\( \frac{{\partial {C_{\text{PE}}}}}{{\partial x}} = 0 \) for x = 0 and t > 0).

Under these initial and boundary conditions and according to Crank (1986), the diffusion equation was solved analytically as formulated by Grathwohl (1998). For the analytical solution, a short-term approximation exists

$$ {m_{\text{PE}}}(t) = 6 \cdot m_{\text{PE}}^{*} \cdot \left( {\frac{{m_{\text{PE}}^{*}}}{{m_w^{*}}} + 1} \right) \cdot \sqrt {{\frac{{{D_{\text{PE}}} \cdot t}}{{\pi \cdot {r^2}}}}} $$
(2)

where m PE (t) (in milligrammes) is the substance mass in the plastic pellet at time t, and \( m_{\text{PE}}^{ * } \) and \( m_w^{ * } \) (both given in milligrammes) represent the substance mass at equilibrium in the pellet and in solution, respectively.

In order to determine diffusion coefficients by linear regression the short-term approximation was converted to the linear pattern \( y = m \cdot x + b \)

$$ {C_{\text{PE}}}(t) = \sqrt {{{D_{\text{PE}}}}} \cdot 6 \cdot C_{\text{PE}}^{*} \cdot \left( {{K_{\text{PE}}} \cdot \frac{{{M_{\text{PE}}}}}{{{V_w}}} + 1} \right) \cdot \sqrt {{\frac{t}{{\pi \cdot {r^2}}}}} $$
(3)

where K PE (in litres per kilogramme) is the equilibrium sorption coefficient, M PE is the mean pellet mass (in milligrammes) and V w is the volume (in millilitres) of liquid phase in the batches. In this way, C PE(t) are the given y-values, the whole term \( 6 \cdot C_{\text{PE}}^{*} \cdot \left( {{K_{\text{PE}}} \cdot \frac{{{M_{\text{PE}}}}}{{{V_w}}} + 1} \right) \cdot \sqrt {{\frac{t}{{\pi \cdot {r^2}}}}} \) represents the x-values which can be calculated from the given parameters, b is zero, and \( \sqrt {{{D_{\text{PE}}}}} \) is the slope of the line which was determined by linear regression.

Assuming a spherical plastic pellet the radius r was calculated from M PE and pellet density ρ PE (in grammes per centimetre):

$$ r = 3 \sqrt{{\frac{{3 \cdot {M_{\text{PE}}}}}{{4 \cdot \pi \cdot {\rho_{\text{PE}}}}}}} $$
(4)

C PE(t) denotes the PAH concentration in the pellet at times t calculated from C aq assuming mass balance after correction by Caq,c (derivation of the equation is given in the SI).

$$ {C_{\text{PE}}}(t) = \left( {{C_{{aq,c}}}(t) - {C_{{aq}}}(t)} \right) \cdot \frac{{{V_w}}}{{{M_{\text{PE}}}}} $$
(5)

The distribution coefficient K PE between a plastic pellet and water can be estimated in different ways: First of all, the well-established Karickhoff approximation was applied to estimate the distribution coefficient K OC (in litres per kilogramme) between organic carbon and water from the substance’s octanol–water distribution coefficient K OW (in litres per kilogramme) and the organic carbon content (f oc) of the plastic pellet (Karickhoff 1981)

$$ {K_{\text{OC}}} = 0.411 \cdot {K_{\text{OW}}} $$
(6)
$$ \Rightarrow {K_{{{\text{PE - OC}}}}} = {f_{\text{oc}}} \cdot 0.411 \cdot {K_{\text{OW}}} $$
(7)

Furthermore, regressions have been developed to directly describe PAH partitioning between PE passive samplers and water without explicit relation to the organic carbon content. These are given by Adams et al. (2007)

$$ \log {K_{{{\text{PE - OW}}07}}} = 1.2 \cdot \log {K_{\text{OW}}} - 0.97 $$
(8)

and Smedes et al. (2009)

$$ \log {K_{{PE - OW10}}} = 1.48 \cdot \log {K_{{OW}}} - 2.45 $$
(9)
$$ \log {K_{{PE - MW}}} = 0.0307 \cdot MW - 1.19 $$
(10)

where MW is the molecular weight (grammes per mole) of PAHs. Adams et al. (2007) derived their regression equations from eight PAHs at 24°C, and are dependent on the log K OW. Smedes et al. (2009) proposed their estimation method based on sorption investigations on 26 PAHs and finally concluded that correlation of the equilibrium partition coefficient with molecular weight (Eq. 10) might be a more appropriate descriptor for equilibrium sorption than K OW.

Using these estimation methods to calculate K PE, the substance concentration in the plastic particle at equilibrium \( C_{\text{PE}}^{ * } \) was calculated based on the total substance mass (M total given in milligrammes) admitted to the experimental setup (derivation of the equation is given in the SI):

$$ C_{\text{PE}}^{*} = \frac{1}{{\frac{{{V_w}}}{{{K_{\text{PE}}} \cdot {M_{\text{PE}}}}} + 1}} \cdot \frac{{{M_{\text{total}}}}}{{{M_{\text{PE}}}}} $$
(11)

Linear regressions with Eq. 3 and K PE-MW as a reference scenario but also with alternative K PE estimates (K PE-OC, K PE-OW07, K PE-OW10) to consider the possible range were finally conducted using the least squares method and resulted in diffusion coefficients D PE. According to Tinsley (1979), diffusion coefficients of the investigated PAHs i were normalised arbitrarily to FLT by the normalisation factor (MWi/MWFLT)0.5. Based on the derived values D PE, the time t 90 to reach 90% of equilibrium was calculated by Eq. 12 (derivation of the equation is given in the SI):

$$ {t_{{90}}} = \frac{{\pi \cdot {r^2}}}{{{D_{\text{PE}}}}} \cdot {\left( {\frac{{0.9}}{{6 \cdot \left( {{K_{\text{PE}}} \cdot \frac{{{M_{\text{PE}}}}}{{{V_w}}} + 1} \right)}}} \right)^2} $$
(12)

The period t 90 was calculated from the deduced diffusion coefficients. These values are helpful for the future design of equilibrium batch experiments of PAH sorption into different plastic particles.

3 Results and discussion

3.1 Sorption kinetics

Mean values of \( {C_{\text{aq}}} C_{{{\text{aq,c}}}}^{{ - 1}} \) with minimum and maximum values obtained from batch experiments with LDPE and HDPE pellets and different PAHs were plotted versus time t (Fig. 1). Values of C aq C aq,c −1 decreased with time for both pellet types indicating sorption of all investigated PAHs. The physicochemical properties of PAHs are shown in Table SI-1 in the Electronic supplementary material. Values of C aq C aq,c −1 fell more quickly as log K OW values of PAHs increased. Results of the ANOVA demonstrated that a triplicate did not reach equilibrium for all PAHs after 24 h under the experimental conditions because the last two measurements (24 h and one week) were not statistically the same (0.014 ≤ p ≤ 0.320). In Fig. 2, the values of K PE,24h obtained from the sorption isotherms using a linear model were compared to the K PE–MW values calculated from Eq. 10. The lower values of measured K PE,24h than of calculated K PE-MW verified the fact that equilibrium was not reached in batches under the experimental conditions.

Fig. 1
figure 1

Plots of mean values of C aq C aq,c −1 versus time for LDPE and HDPE (error bars reflect minimum and maxium values)

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Fig. 2
figure 2

Comparison of values of K PE,24h for ACY, ACE, FLN, PHE, ANT and FLT obtained from the sorption isotherms using a linear model with KPE-MW values calculated from the regression given by Smedes et al. (2009)

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3.2 Equilibrium sorption coefficients

Since sorption equilibrium was not achieved in the kinetic batch experiments, the equilibrium sorption coefficients K PE were estimated as reported above. Calculated K PE values ranged from 382 L kg−1 (NAP) to 12E + 06 L kg−1 (BEP). Since K OW increased by raising the molecular weight of the PAH (except for ACY), equilibrium sorption described by K PE simultaneously indicated this positive correlation, which was represented by all of the four proposed regressions (Fig. 3). Figure 3 also displays measured K PE values available from the literature for sorption of PAHs to PE passive samplers with mean and minimum–maximum ranges (Mueller et al. 2001; Booij et al. 2003; Adams et al. 2007; Cornelissen et al. 2008; Hale et al. 2010; Smedes et al. 2009). The regression assuming the K OC concept (K PE-OC, Eq. 7) represented a lower boundary for all predicted K PE of most of the PAHs (log K OW > 4.1). Moreover, measured K PE data of the PAHs were generally higher than was estimated by the K OC concept. Thus, equilibrium sorption of PAHs seemed to be driven by parameters other than, or in addition to, organic carbon. In comparison with the measured K PE data, the correlation with molecular weight actually seemed to be the most appropriate one and was therefore used for the diffusion model as a benchmark. Nevertheless, the alternative estimates for K PE (K PE-OC, K PE-OW07, K PE-OW10, see Eq. 7–9) were also applied to identify the sensitivity of the diffusion coefficient on the equilibrium constant.

Fig. 3
figure 3

Measured literature data (black diamonds mean and minimum–maximum range) (Mueller et al. 2001; Booij et al. 2003; Adams et al. 2007; Cornelissen et al. 2008; Hale et al. 2010; Smedes et al. 2009) and regression results for equilibrium sorption coefficient log K PE of PAHs with different log K OW. Lines represent regressions based on a correlation between K PE and K OW both given in litres per kilogramme [eq 7 K PE-OC (Karickhoff 1981), eq 8 K PE-OW07 (Adams et al. 2007), eq 9 K PE-OW07 (Smedes et al. 2009)]. Black squares indicate regression results derived from molecular weight (K PE-MW, Smedes et al. 2009) of those PAHs which can also be characterised by available measured data (black diamonds) for KPE

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3.3 Diffusion coefficients

For the investigated time periods, the condition given by Grathwohl (1998) was confirmed, i.e. values of the mass Fourier number D PE·t/r 2 were smaller than 0.01, and the short-term approximation (Eq. 2) could be applied. Estimated diffusion coefficients of PAHs into LDPE and HDPE investigated in our experiments are summarised in Table 1. For comparison of our diffusion coefficients with already existing data, a review of the literature revealed only a few diffusion coefficients for PAHs and PE. Karapanagioti et al. (2010) observed diffusion of PHE into PE pellets with a radius of 0.14 cm and a respective logarithmic diffusion coefficient of −11 cm2 s−1 which corresponds to our result of −11 cm2 s−1 (within a range of −11.22 to 10.45 cm2 s−1) for PHE diffusion into HDPE. Hale et al. (2010) reported logarithmic diffusion coefficients for PHE and ANT of −9.10 and −8.73 cm2 s−1 into PE membranes of 26 and 51 μm thicknesses, respectively. Simko et al. (1999) calculated a log D PE of −10.85 cm2 s−1 for the diffusion of FLT into PE sheets. These values are higher than diffusion coefficients in this study which may be attributable to the difference in the size of sorbents (pellets versus membranes or sheets).

Table 1 Log D PE and t 90 (reference scenario, range given in brackets and resulting from alternative K PE estimations (K PE-OC, K PE-OW07, K PE-OW10, K PE-MW)) for investigated PAHs
Full size table

In Table 1, benchmark values are supplied, which were based on equilibrium sorption coefficients K PE-MW calculated from molecular weight (Eq. 10) as well as the respective range of diffusion coefficients resulting from simulations with alternative K PE estimates (K PE-OC, K PE-OW07, K PE-OW10). In general, for both plastic types, LDPE and HDPE, diffusion coefficients decreased by about a hundred times, while MW of the PAHs increased by 50% (152.2–202.3 g mol−1) which indicates a hindered diffusion through the matrix as a result of a larger molecule size. This correlation has also been observed by Hale et al. (2010) and Simko et al. (1999) for diffusion of organochlorine pesticides and PAHs into PE membranes and for PAHs into PE sheets, respectively.

Normalised diffusion coefficients should be equal for all PAHs in the same medium (i.e. LDPE or HDPE, respectively) (Tinsley 1979). Diffusion coefficients still differed within 1 to 2 orders of magnitude since the normalisation factor based on the molecular weight ranges from 0.867 for ACY to 0.939 for ANT and is not able to cut all diffusion coefficients down to the same order of magnitude. Nevertheless, the uncertainty range also covers about one order of magnitude for most of the PAHs (Table 1).

Diffusion coefficients of PAHs into LDPE were larger than respective coefficients in HDPE (Table 1) indicating that material properties of PE play a role in the velocity of the uptake of PAHs. The difference in the individual compounds’ diffusion velocity, however, decreased with increasing MW indicating that the negative influence of the density on sorption became less important.

It took longer to reach 90% of equilibrium concentration in HDPE pellets than in LDPE pellets for all investigated PAHs apart from FLT, which was already implied by the deduced diffusion coefficients. The difference between the diffusion coefficients of FLT in the two plastic types was the smallest while the estimated K PE-MW was ten times higher than even for ANT (Table 2). Thus, the higher radius of the HDPE pellet gained importance in Eq. 12 and led to a shorter t90 in HDPE than in LDPE.

Table 2 K PE-MW values for the reference scenario estimated by Eq. 12 for investigated PAHs and ratio between C PE and C aq at t 90
Full size table

Finally, 90% of equilibrium was attained in 24 h for sorption of all of the investigated PAHs in LDPE and of FLN, PHE, ANT and FLT in HDPE. Therefore, we calculated the ratio between PAH concentration in the pellet (CPE) and in the solution (Caq) at 90% of the equilibrium which could be expected to be close to the equilibrium concentration ratio K PE-MW. However, this ratio was still far from the equilibrium ratio K PE-MW (Table 2). This was also stated by Ahn et al. (2005) who reported results of batch experiments investigating diffusion of PHE into polyoxymethylene (POM) pellets, a rubbery polymer, with 2.0 to 2.8 mm diameters. After 10 weeks, the concentration profile of PHE determined by microscope laser–desorption laser ionisation mass spectroscopy revealed that the diffusion front had not yet reached the centre of the pellet and still remained in the outer 0.6 mm of the POM. This is in the same order of magnitude as the diffusion distances of 0.15–0.68 mm calculated with the Einstein–Smoluchowski equation assuming the diffusion coefficients deduced for PHE in LDPE and HDPE. This means that the time between 90% of equilibrium and equilibrium is long enough to alter the concentration ratio CPE/Caq significantly. Thus, experiments reaching 90% of equilibrium are not sufficient to determine equilibrium distribution coefficients. Consequently, batch sorption experiments aiming to describe equilibrium partitioning of organic compounds into polymer material should adjust their equilibration time and the ratio of sorbent mass to solution volume in order to obtain measurable differences in sorbent concentration between the time only 90% of equilibrium concentration is reached and equilibrium itself.

4 Conclusions

A comparison of predicted and measured equilibrium distribution coefficients between PE and water reported in the literature indicate that equilibrium sorption of PAHs seemed to be driven by parameters other than, or in addition to, organic carbon. Our findings demonstrated that the diffusion coefficients for PAHs are different for LDPE and HDPE. The lower the density of the PE, the higher was the diffusivity. According to our results, equilibrium time could be shortened during passive sampling by using a polymer with a lower density. In some areas, marine ecosystems may not be in equilibrium with respect to concentrations of organic contaminants and abundance of marine plastic debris. In such cases, various densities of polymers must be considered in risk assessments. Considering the variety of polymer types, the polymer density should be taken into account when assessing the hazard of PAHs in marine environments. Further studies are needed to investigate the influence of other polymer characteristics, e.g. crystallinity on the sorption behaviour of PAHs to PE.