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1 Supporting Information Quantifying the Effects of Temperature and Salinity on Partitioning of Hydrophobic Organic Chemicals to Silicone Rubber Passive Samplers Michiel T.O. Jonker 1 *, Stephan A. van der Heijden 1, Marcel Kotte 2, Foppe Smedes 3,4, 1 Institute for Risk Assessment Sciences, Utrecht University; P.O. Box 80177, 3508 TD Utrecht, the Netherlands. 2 Rijkswaterstaat, Water, Transport and Environment, P.O. Box 17, 8200 AA, Lelystad, the Netherlands 3 Deltares, PO. Box 85467, 3508 AL Utrecht, the Netherlands. 4 Masaryk University, RECETOX, Kamenice 753/5, 62500, Brno, Czech Republic * Corresponding author m.t.o.jonker@uu.nl; phone: ; fax: Number of pages (including this one) : 25 Number of Tables : 8 Number of Figures : 7 S1

2 Table S1. Salts and their concentrations used in media produced to study the effects of salinity on K sr-w. Concentration (g/l or ) NaCl Na 2 SO KCl KBr Na 2 B 4 O 7 10H 2 O MgCl 2.6H 2 O CaCl 2.2H 2 O SrCl 2.6H 2 O NaHCO NaN Total salinity (g/l) Table S2. Concentrations of the test compounds in the spike solution (mg/l acetone). Phenanthrene 1.35 PCB Anthracene 1.65 PCB Fluoranthene 2.06 PCB Pyrene 1.37 PCB Benz[a]anthracene 1.58 PCB Chrysene 1.26 PCB Benzo[e]pyrene 1.45 PCB Benzo[b]fluoranthene 1.22 PCB Benzo[k]fluoranthene 1.43 PCB Benzo[a]pyrene 1.39 PCB Benzo[ghi]perylene 1.46 PCB Dibenz[ah]anthracene 1.55 PCB Indeno[123,cd]pyrene 1.79 PCB PCB PCB PCB HCBD 3.39 PCB HCB 4.04 PCB S2

3 Table S3. Log K sr-w values (average ± standard deviation) determined at different temperatures and salinities. 4 ºC 12 ºC Phenanthrene 4.09 ± ± ± ± ± ± 0.02 Anthracene 4.22 ± ± ± ± ± ± 0.02 Fluoranthene 4.62 ± ± ± ± ± ± 0.01 Pyrene 4.68 ± ± ± ± ± ± 0.01 Benz[a]anthracene 5.29 ± ± ± ± ± ± 0.02 Chrysene 5.20 ± ± ± ± ± ± 0.02 Benzo[e]pyrene 5.73 ± ± ± ± ± ± 0.07 Benzo[b]fluoranthene 5.74 ± ± ± ± ± ± 0.08 Benzo[k]fluoranthene 5.83 ± ± ± ± ± ± 0.08 Benzo[a]pyrene 5.82 ± ± ± ± ± ± 0.08 Benzo[ghi]perylene 6.09 ± ± ± ± ± ± 0.10 Dibenz[ah]anthracene 6.11 ± ± ± ± ± ± 0.09 Indeno[123,cd]pyrene 6.19 ± ± ± ± ± ± 0.21 S3

4 Table S3 - continued. 20 ºC 30 ºC Phenanthrene 3.93 ± ± ± ± ± ± 0.02 Anthracene 4.06 ± ± ± ± ± ± 0.02 Fluoranthene 4.42 ± ± ± ± ± ± 0.01 Pyrene 4.46 ± ± ± ± ± ± 0.01 Benz[a]anthracene 5.04 ± ± ± ± ± ± 0.01 Chrysene 4.95 ± ± ± ± ± ± 0.01 Benzo[e]pyrene 5.43 ± ± ± ± ± ± 0.01 Benzo[b]fluoranthene 5.54 ± ± ± ± ± ± 0.01 Benzo[k]fluoranthene 5.57 ± ± ± ± ± ± 0.01 Benzo[a]pyrene 5.53 ± ± ± ± ± ± 0.02 Benzo[ghi]perylene 5.98 ± ± ± ± ± ± 0.03 Dibenz[ah]anthracene 6.17 ± ± ± ± ± ± 0.09 Indeno[123,cd]pyrene 6.10 ± ± ± ± ± ± 0.04 S4

5 Table S3 - continued. 4 ºC 12 ºC HCBD 4.77 ± ± ± ± ± ± 0.05 HCB 5.05 ± ± ± ± ± ± 0.05 PCB ± ± ± ± ± ± 0.02 PCB ± ± ± ± ± ± 0.02 PCB ± ± ± ± ± ± 0.01 PCB ± ± ± ± ± ± 0.04 PCB ± ± ± ± ± ± 0.05 PCB ± ± ± ± ± ± 0.03 PCB ± ± ± ± ± ± 0.22 PCB ± ± ± ± ± ± 0.05 PCB ± ± ± ± ± ± 0.07 PCB ± ± ± ± ± ± 0.12 PCB ± ± ± ± ± ± 0.24 PCB ± ± ± ± ± ± 0.22 PCB ± ± ± ± ± ± 0.11 PCB ± ± ± ± ± ± 0.24 PCB ± ± ± ± ± ± 0.21 PCB ± ± ± ± ± ± 0.26 PCB ± ± ± ± ± ± 0.18 PCB ± ± ± ± ± ± 0.25 S5

6 Table S3 - continued. 20 ºC 30 ºC HCBD 4.68 ± ± ± ± ± ± 0.01 HCB 4.93 ± ± ± ± ± ± 0.01 PCB ± ± ± ± ± ± 0.01 PCB ± ± ± ± ± ± 0.01 PCB ± ± ± ± ± ± 0.01 PCB ± ± ± ± ± ± 0.02 PCB ± ± ± ± ± ± 0.02 PCB ± ± ± ± ± ± 0.02 PCB ± ± ± ± ± ± 0.02 PCB ± ± ± ± ± ± 0.03 PCB ± ± ± ± ± ± 0.03 PCB ± ± ± ± ± ± 0.04 PCB ± ± ± ± ± ± 0.02 PCB ± ± ± ± ± ± 0.02 PCB ± ± ± ± ± ± 0.06 PCB ± ± ± ± ± ± 0.05 PCB ± ± ± ± ± ± 0.02 PCB ± ± ± ± ± ± 0.01 PCB ± ± ± ± ± ± 0.04 PCB ± ± ± ± ± ± 0.07 S6

7 Table S4. Log K sr-w values determined under standard conditions (20 ºC; no salt) in the present study, as compared with the values reported by Smedes et al. 1 and SPARC-derived log K ow values. logk ow (SPARC) logk sr-w this study logk sr-w Smedes et al. Phenanthrene ± ± 0.01 Anthracene ± ± 0.01 Fluoranthene ± ± 0.02 Pyrene ± ± 0.02 Benz[a]anthracene ± ± 0.03 Chrysene ± ± 0.02 Benzo[e]pyrene ± ± 0.04 Benzo[b]fluoranthene ± ± 0.04 Benzo[k]fluoranthene ± ± 0.04 Benzo[a]pyrene ± ± 0.02 Benzo[ghi]perylene ± ± 0.05 Dibenz[ah]anthracene 7.22 a 6.17 ± ± 0.05 Indeno[123,cd]pyrene ± ± 0.08 HCBD ± b HCB ± ± 0.02 PCB ± ± 0.03 PCB ± ± 0.02 PCB ± ± 0.03 PCB ± 0.03 PCB ± 0.01 PCB ± ± 0.02 PCB ± ± 0.03 PCB ± ± 0.03 PCB ± 0.02 PCB ± ± 0.03 PCB ± ± 0.03 PCB ± ± 0.03 PCB ± 0.02 PCB ± ± 0.06 PCB ± ± 0.04 PCB ± ± 0.06 PCB ± 0.04 PCB ± ± 0.06 a The SPARC-derived value for dibenz[ah]anthracene was unrealistically high. Based on HPLC retention times (C 18 column) the value was set equal to that of benzo[ghi]perylene. b Unpublished value. S7

8 Table S5. Temperature dependency factors (± standard errors) derived at different salinity levels (unbiased values for 18 and 36 systems only) Phenanthrene ± ± ± Anthracene ± ± ± Fluoranthene ± ± ± Pyrene ± ± ± Benz[a]anthracene ± ± ± Chrysene ± ± ± Benzo[e]pyrene ± Benzo[b]fluoranthene ± Benzo[k]fluoranthene ± Benzo[a]pyrene ± Benzo[ghi]perylene ± Dibenz[ah]anthracene ± Indeno[123,cd]pyrene ± HCBD ± ± ± HCB ± ± ± PCB ± ± ± PCB ± ± ± PCB ± ± ± PCB ± ± PCB ± PCB ± PCB ± PCB ± PCB ± PCB ± PCB ± PCB ± PCB ± PCB ± PCB ± PCB ± PCB ± PCB ± Bold values differ significantly (F-test) from the other values in the same row. S8

9 Table S6. Thermodynamic parameters (± standard errors) describing partitioning of the test compounds from 0 water to silicone rubber at 293 K: changes in Gibbs free energy ( G), enthalpy ( H), and entropy (T S). Values for PDMS (from Muijs and Jonker 4 ) are included for comparison. Silicone rubber (this study) PDMS (Muijs & Jonker, 2009) G H T S G H T S (kj/mol) (kj/mol) (kj/mol) (kj/mol) (kj/mol) (kj/mol) Phenanthrene ± ± ± ± ± ± 1.70 Anthracene ± ± ± ± ± ± 1.53 Fluoranthene ± ± ± ± ± ± 1.39 Pyrene ± ± ± ± ± ± 1.40 Benz[a]anthracene ± ± ± ± ± ± 1.38 Chrysene ± ± ± ± ± ± 1.40 Benzo[e]pyrene ± ± ± ± ± ± 1.57 Benzo[b]fluoranthene ± ± ± ± ± ± 1.70 Benzo[k]fluoranthene ± ± ± ± ± ± 1.75 Benzo[a]pyrene ± ± ± ± ± ± 1.58 Benzo[ghi]perylene ± ± ± ± ± ± 3.98 Dibenz[ah]anthracene ± ± ± 3.66 Indeno[123,cd]pyrene ± ± ± ± ± ± 4.62 HCBD ± ± ± 1.15 HCB ± ± ± 1.01 PCB ± ± ± 0.97 PCB ± ± ± 0.60 PCB ± ± ± 0.78 PCB ± ± ± 1.52 PCB ± ± ± 2.21 PCB ± ± ± 1.14 PCB ± ± ± 4.53 PCB ± ± ± 1.51 PCB ± ± ± 2.10 PCB ± ± ± 14.5 PCB ± ± ± 3.35 PCB ± ± ± 4.27 PCB ± ± ± 3.67 PCB ± ± ± 4.63 PCB ± ± ± 3.49 PCB ± ± ± 5.34 PCB ± ± ± 11.6 PCB ± ± ± 5.15 S9

10 Table S7. Salinity dependency factors (± standard errors) derived for the less hydrophobic compounds (unbiased values) at different temperatures. 4 ºC 12 ºC 20 ºC 30 ºC Phenanthrene ± ± ± ± Anthracene ± ± ± ± Fluoranthene ± ± ± ± Pyrene ± ± ± ± Benz[a]anthracene ± ± Chrysene ± ± HCBD ± ± ± ± HCB ± ± ± ± PCB ± ± ± ± PCB ± ± ± ± PCB ± ± ± ± PCB ± ± PCB ± ± PCB ± ± PCB ± ± PCB ± PCB ± Bold values differ significantly (F-test) from the other values in the same row. S10

11 Table S8. Equations to calculate temperature- and salinity-specific silicone rubber-water partition coefficients. Phenanthrene Anthracene Fluoranthene Pyrene Benz[a]anthracene Chrysene Benzo[e]pyrene Benzo[b]fluoranthene Benzo[k]fluoranthene Benzo[a]pyrene Benzo[ghi]perylene Dibenz[ah]anthracene Indeno[123,cd]pyrene HCBD HCB PCB-18 PCB-28 PCB-52 PCB-72 PCB-103 PCB-66 PCB-155 PCB-101 PCB-77 PCB-118 PCB-153 PCB-138 PCB-126 PCB-187 PCB-156 PCB-180 PCB-169 PCB-170 log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S log K sr-w (T,S) = (T-20) S S11

12 Figure S1. Comparison between logksr-w values determined under standard conditions (20 ºC, no salt) in the present study and those reported in the literature for AlteSil silicone rubber.1-3 Panels A and C show data for PAHs; panels B, D, and E for PCBs (and HCB, HCBD in panel B). S12

13 Comparison between logk sr-w values in the present study with the ones from Smedes et al. (2009), both determined under standard conditions. When comparing the logk sr-w values in the present study with the ones from Smedes et al. 1 (i.e., the most comprehensive and overlapping data set), it appears that the current values generally are lower by about 0.15 to 0.3 log units (see Figure S1A,B and Table S4). For the most hydrophobic PAHs, the current values are however practically identical to the values from Smedes et al., 1 whereas for the most hydrophobic PCBs, the values determined in the present study are higher (see Figure S1B). The cause of this discrepancy may be related to (i) the characteristics of the silicone rubber and/or (ii) the experimental approach followed to determine the partition coefficients. The present experiments were performed with a rubber sheet that was produced many years after the one used by Smedes et al. 1 In case the composition of the rubber meanwhile would have changed, the sorption characteristics could have as well. However, additional recent experiments (Van der Heijden and Jonker, unpublished data) with a sheet from exactly the same batch as used by Ter Laak et al. 3 (obtained in 2007) demonstrated that, at least for PAHs, the sorption characteristics of the present AlteSil rubber are not different from those of the batch from 2007: logk sr-w values determined with the 2007 sheet are very similar to the ones presented in this study (see Figure S2 below). The alternative explanation for the differences between the present results and those from Smedes et al. 1 would be related to the experimental approach. The experimental setup of the present study was different from the one by Smedes and coworkers. 1 The first concerned spiking a pure water phase in batchshake experiments, whereas the latter applied spiking via loaded silicone rubber and cosolvent experiments with water/methanol mixtures. It should also be noted that the concentration levels applied by Smedes et al. 1 were a factor of about 500 lower than in the present study. Still, it is unclear which experimental differences exactly may have caused the observed differences in the K sr-w values, as experimental artifacts in either of the setups expectedly would have resulted in a pattern different from the currently-observed one. S13

14 Figure S2. LogK sr-w values for PAHs determined in the present study against values determined recently for an AlteSil silicone rubber sheet obtained in 2007 (Van der Heijden and Jonker; unpublished results), both at 20 ºC. S14

15 Figure S3. LogK sr-w values determined at different temperatures and salinities (indicated) against SPARC logk ow values. Open circles represent PAHs; solid squares PCBs. S15

16 8 Flu at Vlissingen no correction T and S correction Flu at Grevelingen meer no correction T and S correction Flu at Waddenzee midden no correction T and S correction S16

17 BaP at Vlissingen no correction T and S correction BaP at Grevelingen meer no correction T and S correction BaP at Waddenzee midden no correction T and S correction S17

18 PCB052 at Vlissingen no correction T and S correction PCB052 at Grevelingen meer no correction T and S correction PCB052 at Waddenzee midden no correction T and S correction S18

19 PCB153 at Vlissingen no correction T and S correction PCB153 at Grevelingen meer no correction T and S correction PCB153 at Waddenzee midden no correction T and S correction Figure S4. Aqueous concentrations (ng/l) of 2 PAHs (fluoranthene and benzo[a]pyrene) and 2 PCBs (52 and 153) at three saline Dutch locations, determined with silicone rubber passive samplers. Calculations were performed with and without adjusting the K sr-w values for the effects of salinity and temperature. S19

20 Figure S5. Effect of temperature on the sampling rate (R s ) at location Vlissingen without (left panel) and with (right panel) adjusting K sr-w values for the effects of temperature and salinity during sampling. S20

21 Figure S6. Frequency distribution of the ratios of aqueous concentrations calculated without and with adjusting K sr-w values for the effects of temperature and salinity during sampling. S21

22 Figure S7. Average ratios of aqueous concentrations calculated without and with adjusting K sr-w values for the effects of temperature and salinity during sampling, as a function of logk ow. Open circles represent data for PAHs, closed squares for PCBs. Figure A presents data as obtained by applying the modeling/calculation approach used for the Dutch passive sampling monitoring; Figure B presents the average ratios calculated using the method as applied in e.g. ref 5, assuming the averaged (marine/estuarine) conditions in the field data base (i.e., 8 C and 30 g/l salinity). S22

23 Details on the calculation of freely dissolved concentrations from the Dutch passive sampling field monitoring work. Several Dutch waters are monitored by using passive sampling with silicone rubber (coastal waters since 2001 and inland surface waters since 2009). Until 2006, silicone material from Rubber BV (the Netherlands) was used. From then on, sampling continued with Altesil silicone rubber ( i.e., the same material as used in the present study. Continuity of the results was assured however by determining K sr,w values for a wide range of (target and PRC) compounds with both materials within the same experiment. 1 The methods of sampling were described and evaluated after the first five years of monitoring. 6 At the start of the program, duplicate samplers were exposed. The data showed that the variability in the uptake was at the level of analytical performance. In addition to the uptake of target compounds, release of PRCs was monitored and was used to express the kinetics resulting from the transport resistance through the aqueous boundary layer in terms of the sampling rate (R s ). The average R s value was determined from the release of the individual PRCs and was used to derive the freely dissolved concentrations of the target compounds, according to methods described in ref 6. Based on field experience, the selection of PRCs was adapted over the course of time, in order to more accurately determine the R s. Presently, the chemicals used as PRC are biphenyl-d 10 and the PCBs 1, 2, 3, 10, 14, 21, 30, 50, 55, 78, 104, 145, and 204. As transport through the aqueous boundary layer surrounding the silicone rubber is related to the aqueous diffusion coefficient, theory predicts R s to decrease for bulkier molecules, i.e. higher molecular weight (or K OW ) compounds. For SPMDs 7 and Chemcatcher, 8 curved relationships between R s and logk OW were found, which were not compatible with the decrease in diffusion. For silicone rubbers, an empirical relationship of sampling rates with D 0.47 w was therefore determined that closely followed relationships predicted from chemical engineering. 9 The use of the relationship to derive information on R s from the release of PRCs was optimised by fitting this release to the model by non-linear least squares regression (NLS), using an adjustable parameter (FA) to represent the average turbulence that is controlling the thickness of the aqueous boundary layer. 10 Ref 10 includes a thorough discussion on how variability in e.g. K sr,w can influence the results and the NLS procedure provides an error estimate. A discussion on repeatability, analytical considerations, and blank levels during the sampling procedure can be found in ref 6. S23

24 The above-described procedure was reworked into a guideline for the use of silicone rubber for passive sampling of PCBs and PAHs. It includes the equations needed to derive C w from the uptake of target compounds and the release of PRCs. 11 In the present study, the above guideline was applied to retrospectively derive C w values from the raw data of 10 years of monitoring. Briefly, the calculations successively involved (1) calculation of the remaining PRC fractions in the sheets; (2) calculation of the flow factor (FA; representing the aqueous boundary layer thickness) and the sampling rate (R s ), based on the remaining PRC fractions; (3) calculation of the degree of (non) equilibrium for each target compound, based on FA and the K sr-w of the target compounds; (4) calculation of the freely dissolved concentrations in water, based on the degree of equilibrium and the K sr-w values of the target compounds. The calculations were performed with the different K sr,w values for the two materials that had been used over the years. For this, the data set generated by Smedes 1 was used, and not the data from the present paper, because the latter did not include the PRCs applied and were not valid for the silicone rubber used during the first 5 years of monitoring. The entire calculation procedure was first performed with these K sr,w values determined at 20 C in pure water. Subsequently, the calculations were repeated using location-specific (temperature and salinity-adjusted) K sr,w values, as obtained by applying the equations derived in the present study (Table S8). From the difference in the two resulting data sets, the influence of adjusting the K sr,w values for temperature and salinity could be quantified. The estimates for the variation coefficient of FA provided by the NLS were on average 7 and 12% (n = 250) using the original and adjusted K sr,w values, respectively. Adopting a long term analytical error of 10%, the final variation in the passive sampling results would range around 15% (well above LOQ). This estimate does not include the systematic errors that might occur from the bias in the K sr,w s. S24

25 Literature Cited 1. Smedes, F.; Geertsma, R. W.; Van Der Zande, T.; Booij, K. Polymer-water partition coefficients of hydrophobic compounds for passive sampling: Application of cosolvent models for validation. Environ. Sci. Technol. 2009, 43 (18), Yates, K.; Davies, I.; Webster, L.; Pollard, P.; Lawton, L.; Moffat, C. Passive sampling: Partition coefficients for a silicone rubber reference phase. J. Environ. Monitor. 2007, 9 (10), Ter Laak, T. L.; Busser, F. J. M.; Hermens, J. L. M. Poly(dimethylsiloxane) as passive sampler material for hydrophobic chemicals: Effect of chemical properties and sampler characteristics on partitioning and equilibration times. Anal. Chem. 2008, 80 (10), Muijs, B.; Jonker, M. T. O. Temperature-dependent bioaccumulation of polycyclic aromatic hydrocarbons. Environ. Sci. Technol. 2009, 43 (12), Perron, M. M.; Burgess, R. M.; Suuberg, E. M.; Cantwell, M. G.; Pennell, K. G. Performance of passive samplers for monitoring estuarine water column concentrations: 1. Contaminants of concern. Environ. Toxicol. Chem. 2013, 32 (10), Smedes, F. Monitoring of chlorinated biphenyls and polycyclic aromatic hydrocarbons by passive sampling in concert with deployed mussels. In Comprehensive Analytical Chemistry; Greenwood, R., Mills, G. A., Vrana, B., Eds.; Elsevier Science and Technology Books: Oxford, 2007; Vol Huckins, J. N.; Petty, J. D.; Booij, K. Monitors of Organic Chemicals in the Environment: Semipermeable Membrane Devices; Springer: New York, MA, Vrana, B.; Mills, G. A.; Kotterman, M.; Leonards, P.; Booij, K.; Greenwood, R. Modelling and field application of the Chemcatcher passive sampler calibration data for the monitoring of hydrophobic organic pollutants in water. Environ. Pollut. 2007, 145 (3), Rusina, T. P.; Smedes, F.; Koblizkova, M.; Klanova, J. Calibration of silicone rubber passive samplers: Experimental and modeled relations between sampling rate and compound properties. Environ. Sci. Technol. 2010, 44 (1), Booij, K.; Smedes, F. An improved method for estimating in situ sampling rates of nonpolar passive samplers. Environ. Sci. Technol. 2010, 44 (17), Smedes, F.; Booij, K. Guidelines for passive sampling of hydrophobic contaminants in water using silicone rubber samplers; Techniques in Marine Environmental Sciences; International Council for the Exploration of the Sea (ICES): Copenhagen, Denmark, 2012; vironmental%20sciences%20(times)/times52/120621%20times%2052%20final.pdf. S25

Dorothea Gilbert, Espen Eek, Naiara Berrojalbiz, Amy MP Oen and Hans Peter H. Arp. Norwegian Geotechnical Institute, Oslo

Innovative passive sampling techniques at the sediment-water and air-water interface for monitoring the presence and fluxes of hydrophobic organic contaminants Dorothea Gilbert, Espen Eek, Naiara Berrojalbiz,