Sorption behavior of 20 wastewater originated micropollutants in groundwater — Column experiments with pharmaceutical residues and industrial agents

Journal of Contaminant Hydrology 154 (2013) 29–41

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Sorption behavior of 20 wastewater originated micropollutants in groundwater — Column experiments with pharmaceutical residues and industrial agents Victoria Burke a,⁎, Svantje Treumann a, Uwe Duennbier b, Janek Greskowiak a, Gudrun Massmann a a Carl von Ossietzky Universität Oldenburg, Institute of Biology and Environmental Sciences, Working Group Hydrogeology and Landscape Hydrology, D-26111 Oldenburg, Germany b Berliner Wasserbetriebe, Department of Laboratories, D-10864 Berlin, Germany

a r t i c l e

i n f o

Article history: Received 11 December 2012 Received in revised form 9 August 2013 Accepted 13 August 2013 Available online 27 August 2013 Keywords: Psychoactive drugs Phenazone-type compounds β-Blocker Retardation Octanol/water partition coefficient

a b s t r a c t Since sorption is an essential process with regard to attenuation of organic pollutants during subsurface flow, information on the sorption properties of each pollutant are essential for assessing their environmental fate and transport behavior. In the present study, the sorption behavior of 20 wastewater originated organic micropollutants was assessed by means of sediment column experiments, since experimentally determined data for these compounds are not or sparsely represented in the literature. Compounds investigated include various psychoactive drugs, phenazone-type pharmaceuticals and β-blockers, as well as phenacetine, N-methylphenacetine, tolyltriazole and para-toluenesulfonamide. While for most of the compounds no or only a low sorption affinity was observed, an elevated tendency to sorb onto aquifer sand was obtained for the β-blockers atenolol, propranolol and metoprolol. A comparison between experimental data and data estimated based on the octanol/water partition coefficient following the QSAR approach demonstrated the limitations of the latter to predict the adsorption behavior in natural systems for the studied compounds. © 2013 Elsevier B.V. All rights reserved.

1. Introduction Organic pollutants derived from wastewater may enter groundwater by infiltration from wastewater influenced surface waters or due to leakage of sewer systems. Besides the process of biodegradation, sorption plays a substantial role as an attenuation process during subsurface flow. Thus, sorption properties are mandatory for assessing the environmental behavior of the pollutants in general and, particularly, to assess their potential to leach into the groundwater which is often used for drinking water supply. Sorption processes can be driven by diverse mechanisms, including physisorption, chemisorption and mechanical inclusion (von Oepen et al., 1991). Depending on the characteristics of both sorbent and sorbate various intermolecular interactions ⁎ Corresponding author. Tel.: +49 441 7984683; fax: +49 441 7983769. E-mail address: [email protected] (V. Burke). 0169-7722/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.jconhyd.2013.08.001

(e.g. van der Waals interactions, hydrophobic bonding) result in bindings with varying binding energies. Further, total sorption may be combining different sorption mechanisms (von Oepen et al., 1991) and it is quite difficult to identify the contribution of each of them to the total (Boyd, 1982). Based on the quantitative structure–activity relationship (QSAR) the sorption properties of a pollutant can be approximated from the octanol–water partition coefficient (Kow), which indicates the hydrophobicity of a compound. A number of previous studies addressed the sorption properties of selected organic pollutants (e.g. Drillia et al., 2005; Loeffler et al., 2005; Maeng et al., 2011; Schaffer et al., 2012; Yamamoto et al., 2009), and most found deviations in the sorption coefficient estimates from those derived by their Kow values. This indicates that mechanisms other than hydrophobic interactions have to be considered (Yamamoto et al., 2009). Maeng et al. (2011) quoted the example of electrostatic interactions as one limitation of assessing the distribution behavior based on the

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Kow value, if pollutants occur in acidic form. Thus, experimental investigations are additionally necessary in order to obtain reliable and more realistic data on the sorption of environmental pollutants. Several authors reported laboratory experiments investigating the sorption behavior of numerous organic pollutants, including batch (Deitsch et al., 2000; Hart et al., 2004) and column experiments (Patterson et al., 2010). However, sorption data of most of the compounds addressed within this study have not been reported in the literature before. The batch method is the simplest experimental setup, however, it is limited by requiring inappropriate solid/ solution ratios or in meeting the hydrodynamic conditions in natural porous media (Limousin et al., 2007). Limousin et al. (2007) concluded that sorption parameters derived from batch experiments are hardly transferable to porous media, and hence column experiments are preferred. Similar results were observed by Benker et al. (1998). Column experiments can also be used to investigate kinetic dependencies by adjusting the hydraulic residence time (Limousin et al., 2007). Moreover, recently published studies indicated that sorption obtained in batch experiments is consistently overestimated compared to that obtained in column experiments (Murillo-Torres et al., 2012; Piatt et al., 1996), potentially caused by contact times and solid/solution ratios. We performed sorption column experiments on 20 organic trace pollutants, which are frequently detected within the urban water cycle of Berlin, Germany. According to the concept of a semi-closed water cycle, the drinking water production in Berlin relies on the indirect reuse of treated wastewater via managed aquifer recharge such as bank filtration. Since this concept is not unique to Berlin but also applied in other metropolitan municipalities, the investigated compounds are potentially of general importance. Our study included several pharmaceutical compounds classified as psychoactive drugs, phenazone-type pharmaceuticals and two other analgesics as well as beta adrenergic antagonists (β-blockers). Moreover we investigated two industrial compounds — the anticorrosive additive tolyltriazole and the sulfonamide para-toluenesulfonamide. Table 1 provides chemical structures and physicochemical properties of the selected organic contaminants. The investigated psychoactive drugs are the tranquilizers meprobamate, diazepam and oxazepam, the hypnotic/sedative pyrithyldione, the antiepileptic primidone as well as its metabolite phenylethylmalonamide (PEMA). The compounds have already been intensively studied by Hass et al. (2012a) due to their omnipresence within the Berlin water cycle. Moreover, some of them were found to be persistent under certain aquifer conditions (Hass et al., 2012b). Another set of compounds addressed within the present study is a group summarized here as phenazone-type pharmaceuticals. Included are the analgesics phenazone and propyphenazone, and the phenazone-type metabolites 1-acetyl1-methyl-2-dimethyl-oxamoyl-2-phenylhydrazide (AMDOPH), 1-acetyl-1-methyl-2-phenylhydrazide (AMPH), acetylaminoantipyrine (AAA) and formylaminoantipyrine (FAA). All of them were previously detected in surface water and groundwater in the range of tens to several hundred nanograms per liter (e.g. de Jongh et al., 2012; Massmann et al., 2008). Reddersen et al. (2002) determined average phenazone concentrations

of 3 μg L− 1 in groundwater samples at contaminated areas in Berlin, Germany. Moreover, phenazone and AMPH were also encountered in Dutch drinking water obtained from river bank filtrates in maximum concentrations of 35 ng L− 1 and 19 ng L− 1, respectively (de Jongh et al., 2012). Though the mentioned concentrations are far below the provisional drinking water guideline values provided by de Jongh et al. (2012) concerning the toxicological relevance for human health, their occurrence in nearly all compartments of the water cycle raises concerns. Sorption experiments have been carried out solely for propyphenazone, resulting in retardation coefficients between 1.6 and 2.5 (Mersmann et al., 2003; Scheytt et al., 2004, 2006), and for phenazone (Benotti and Brownawell, 2009), indicating that sorption was negligible. Pharmaceutically active compounds from the β-blocker group are mainly applied for the treatment of hypertension and cardiac dysfunction. Purchased volumes show an increasing trend over the last years, with metoprolol by far as the main applicant (BLAC, 2003). As different β-blockers commonly feature the same mode of toxic action (Escher et al., 2006), additive effects increase the environmental risk of this therapeutic group (Maurer et al., 2007). For our sorption studies we selected four β-blockers, namely metoprolol, atenolol, sotalol and propranolol, due to their frequent occurrence and high persistence within the aquatic environment (Bendz et al., 2005; BLAC, 2003). Phenacetine was introduced in the 1890s as an antipyretic and since 1900 commonly an element of analgesic mixtures. Several decades later its toxicity for humans became obvious and its application in medical care was strongly reduced (Carro-Ciampi, 1978). N-methylphenacetine, probably a metabolite of phenacetine, was detected in Berlin groundwater at concentrations up to several hundred nanograms per liter (Heberer et al., 1997). Apart of the pharmaceutically active compounds, we included two industrial agents in the present study — tolyltriazole and para-toluenesulfonamide (p-TSA). Both contaminants are used in a wide variety of applications (e.g. Reemtsma et al., 2010; Richter et al., 2007) and regularly discharged with municipal wastewaters. Tolyltriazole, a mixture of the isomers 4- and 5-methylbenzotriazole, is commonly used as an anticorrosive additive in industrial and commercial fluids. Among several other applications it is added to aircraft deicing fluids in order to reduce flammability hazards (Cornell et al., 2000). As pointed out by Cornell et al. (2000), it inhibits biodegradation and is toxic to a number of microorganisms. Its widespread use and the fact that tolyltriazole is frequently detected in surface waters, groundwater and even drinking water (Giger et al., 2006; Janna et al., 2011; Reemtsma et al., 2010) in high concentrations underline the importance of investigating its transport behavior. The industrial agent p-TSA is used as a plasticizer, an intermediate for pesticides and drugs, as a fungicide in paints and coatings and is also the primary degradation product of the disinfectant Chloramine-T (Meffe et al., 2010; Richter et al., 2007). Since p-TSA was found to be ubiquitous in the aquatic environment of Berlin (Meffe et al., 2010; Richter et al., 2007), a number of studies have already been carried out investigating its environmental fate and behavior (e.g. Meffe et al., 2012; Richter et al., 2008b, 2009). However, previous work has failed to address its sorption behavior.

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Table 1 Physical and chemical properties of the investigated compounds. MWa (g/mol)

pKab

log Dowb at pH 8.3

284.07

2.92

3.08

Oxazepam C15H11ClN2O2 604–75–1

286.05

12.47

2.92

Meprobamate C9H18N2O4 57–53–4

218.13

15.63

0.93

Primidone C12H14N2O2 125–33–7

218.11

11.6

1.12

PEMA C11H14N2O2 7206–76–0

206.11

n.a.

0.73

Pyrithyldione C9H13NO2 77–04–3

167.09

13.04

1.56

188.09

0.37

1.22

230.14

0.76

2.35

Substance Formula CAS-RN Psychoactive drugs Diazepam C16H13ClN2O 439–14–5

Phenazone-type pharmaceuticals Phenazone C11H12N2O 60–80–0

Propyphenazone C14H18N2O 479–92–5

Structure

(continued on next page)

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Table 1 (continued) MWa (g/mol)

pKab

log Dowb at pH 8.3

AMDOPH C13H17N3O3 519–65–3

263.13

n.a.

0.09

AMPH C9H12N2O 38604–70–5

164.09

n.a.

1.3

AAA C13H15N3O2 83–15–8

245.12

15.52

0.15

FAA C12H13N3O2 1672–58–8

231.10

12.66

0.11

266.16

9.67

−0.95

Propranolol C16H21NO2 525–66–6

259.16

9.67

1.20

Sotalol C12H20N2O3S 3930–20–9

272.12

9.35

−1.28

Metoprolol C15H25NO3 37350–58–6

267.18

9.67

0.38

Substance Formula CAS-RN

β-Blockers Atenolol C14H22N2O3 29122–68–7

Structure

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Table 1 (continued) MWa (g/mol)

pKab

log Dowb at pH 8.3

171.04

10.46

1.09

Tolyltriazole C7H7N3

133.06

8.93c, 8.87d

1.73c/1.71d

Phenacetine C10H13NO2 62–44–2

179.09

n.a.

1.41

N-methylphenacetine C11H15NO2 7298–73–9

193.11

n.a.

1.27

Substance Formula CAS-RN

Structure

Others p-TSA C7H9NO2S 70–55–3

a b c d

Monoisotopic mass. Calculated with ChemAxon software (Marvin 5.9.4., http://chemaxon.com). 4-Methyl-1H-benzotriazole. 5-Methyl-1H-benzotriazole.

The objective of the present study was to quantify the sorption behavior of the mentioned contaminants in terms of linear distribution coefficients Kd and Koc in typical aquifer sediment under near-natural groundwater conditions. 2. Materials and methods 2.1. Sediment and column influent water Aquifer sediment used in the column was collected from a bank filtration site in Berlin, Germany. Particle size distribution of the sandy sediment determined by sieving analysis was N630 μm (13%); 630–200 μm (75%); 200–63 μm (10%); 63–20 μm (1%) and b20 μm (1%). The organic matter content determined by loss of ignition was 0.20% (w/w). Prior to use the sediment was sterilized by autoclavation (121 °C, 1 bar and 15 min). Previous studies gave evidence that this kind of pre-treatment is considered to slightly affect some physical sediment properties (Lotrario et al., 1995) and might thus influence sorption rates (Hildebrand et al., 2006). However, Stang et al. (1992) and Lotrario et al. (1995) reported on negligible differences with regard to the sorption caused by autoclavation. Also Ball and Roberts (1991) stated, that autoclavation has no effect on sorption as long the sediment can cool quickly afterwards.

Two different column influent waters were used. Column influent “A” consisted of tap water containing 15 mmol L−1 sodium azide, which was added in order to inhibit biological activity in the water and on the sediment. Column influent “B” consisted, equal to influent water “A”, of tap water containing 15 mmol L−1 sodium azide, but was additionally spiked with the conservative tracer sodium chloride (50 mg L−1) and a standard solution enclosing all organic compounds investigated in the course of the study. Previously, single stock solutions were prepared by dissolving each compound in methanol, respectively. Mixing of these stock solutions resulted in the used standard solution containing 5 μg mL−1 of each compound. Adding the standard solution to influent water “B” led, based on its nominal concentration, to final concentrations of 0.8 μg L−1. 2.2. Chemicals High purity standards of sotalol, metoprolol, atenolol, propranolol, phenazone, primidone, FAA and AMPH were purchased from Sigma-Aldrich (Steinheim, Germany). The reference compounds diazepam, meprobamate and oxazepam were obtained from Cerilliant (Round Rock, TX, USA) and PEMA from Toronto Research Chemicals (Toronto, ON, Canada). Phenacetine, N-methylphenacetine, propyphenazone

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and AAA were purchased from Sigma-Aldrich (St. Louis, MO, USA). Pyrithyldione was provided by the Institute of Doping Analysis and Sports Biochemistry Dresden and AMDOPH was commercially synthesized by Witega Laboratorien Berlin-Adlershof GmbH (Berlin, Germany). A sodium chloride standard solution (Merck) was used as a conservative tracer. Sodium azide was sourced from Sigma-Aldrich (Steinheim, Germany). 2.3. Column setup A stainless steel column was packed with the sterilized aquifer sediment as uniformly as possible. The sediment was carefully filled from above while the column was flooded from the bottom with tap water in order to avoid air entrapment and grain size separation due to gravity. Simultaneously, the sediment was compacted by vibrating the column with an oscillating machine. A stainless steel net with a mesh size of 63 μm was placed at the top and the bottom of the column in order to prevent sediment losses. The entire tubing and tube connections used during the experiment were made of polytetrafluoroethylene (PTFE). A sketch of the experimental setup is presented in Fig. 1. While pH, temperature and the electrical conductivity (EC) were determined in the column effluent using external probes (Hach®), oxygen (O2) was measured in a flow cell, using oxygen probes connected to a fiber optic oxygen transmitter (Fibox 3, PreSens). The oxygen probes were constructed according to Hecht and Kölling (2001), but based on 2 mm plastic optical fibers. O2 measurements were performed on both column influent and effluent. The column was conditioned with column influent “A” until constant values regarding pH, temperature, EC and O2 concentration were obtained. After conditioning, influent water “B” containing the conservative tracer and the target compounds was passed through the column for five days, since this duration was assumed to enable breakthrough of all compounds. Samples of the column effluent were collected by the use of an automatic fraction collector, which accumulated the entire column effluent over each hour. After five days the column influent was switched back to reservoir “A” and the sampling interval of 1 h was maintained for another seven days. Table 2 summarizes column dimensions, hydraulic parameters and experimental conditions in the study. Since it was aimed to reproduce conditions as they are prevalent in the main Berlin aquifer, which is a typical glaciofluvial sand, adjustable parameters were correspondingly set. Actual values describing the transport properties (effective porosity, mean pore water velocity and hydrodynamic dispersivity) were derived from the conservative tracer test. 2.4. Sampling and sample analysis Measurements for pH, temperature, EC and O2 were carried out once a day as described above. In order to record the breakthrough of the conservative tracer, the chloride concentration was quantified in intervals of 4 h. Therefore, samples were filtered using 0.45 μm cellulose acetate filters (Sartorius Minisart®) and analyzed by ion chromatography with a Basic IC plus (Metrohm) according to DIN EN ISO 14911.

Fig. 1. Schematic sketch of the experimental setup.

Quantification of the organic target compounds was done every 30 h. This was done to obtain at least one value on the increasing part of the breakthrough curve for all retarded compounds (based on the breakthrough of the conservative tracer). The starting point was the first appearance of the conservative tracer. Aliquots of 10 ml of the respective water samples were filled into glass containers and stored at 4 °C until analysis. Measurements were carried out in the laboratories of the Berliner Wasserbetriebe by application of high-performance liquid chromatography (ACCELA, Thermo Scientific, USA) coupled to high resolution mass spectrometry (Orbitrap, Exactive™, Thermo Fisher Scientific, Germany). The limits of quantification were 20 ng L−1 for the phenazone-type pharmaceuticals and tolyltriazole, 25 ng L−1 for the β-blockers and 50 ng L−1 for the psychoactive compounds, phenacetine, N-methylphenacetine and p-TSA. The analytical method is described in detail in Wode et al. (2012).

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the organic carbon content (foc) of the aquifer sediment yielding Koc:

Table 2 Information on column characteristics and experimental conditions. Parameter

Unit

Value

Column height Column inner diameter Effective porosity Flow rate Pore water velocity Hydrodynamic dispersion Temperature Oxygen saturation pH

m m – m3/s m/s m2/s °C % –

0.3 0.1 0.45 5.6 × 10−9 1.7 × 10−6 7 × 10−9 21 100 8.3

K oc ¼

Kd : f oc

ð4Þ

Further, the first-order sorption rate constant α can be transformed into a “sorption half-life time” t50, i.e. the time needed to attain 50% of sorption equilibrium in a corresponding batch system. Thus, the “sorption half-life time” indicates the degree of sorption disequilibrium for a given time scale. It can be derived from a simple closed-form solution of Eq. (3) for S(t =0) = S0 and Sðt→∞Þ ¼ S∞ ¼ 0

2.5. Data analysis The estimation of the sorption parameters of the investigated trace organic compounds occurred in two steps. In step one, the physical transport parameters, i.e. the coefficient of hydrodynamic dispersion and the pore velocity were estimated by simulating the conservative breakthrough of the sodium chloride tracer with a one-dimensional advection– dispersion model described by the following formulation:

θ

∂C ∂2 C ∂C ¼ θD 2 −θv ∂t ∂x ∂x

ð1Þ

where x is the length of the column (L), t the time (T), C is the aqueous concentration (M L−3) at x and t, v the mean pore water velocity [L T−1], θ is the porosity (dimensionless) and D the coefficient of hydrodynamic dispersion [L2 T−1]. Once D and v were estimated, the trace organic concentrations in the column effluent were simulated in the second step applying a one-dimensional advection–dispersion and one-site kinetic linear sorption model (e.g. Nkedi-Kizza et al., 1984) described by the following formulations:

θ

δC δ2 C δC ¼ θ D 2 −θv −α ρb ðK d C−SÞ δt δx δx

∂S ¼ α ðK d C−SÞ ∂t

ρb θ Kd ρ

1þ θb K d

S0 and S0 ¼ Sðt Þþ ρθ C ðt Þ: b

1

ρb ρb K d S0 K d S0 B C −α t ð1þρθb KdÞ S¼ θ ρ þ @S0 − θ ρ : Ae 1 þ b Kd 1 þ b Kd θ θ

ð5Þ

By setting Sðt 50 Þ ¼ 12 ðS0 þ S∞ Þ Eq. (5) yields: ln 2 t 50 ¼ ρ : b K þ1 α θ d

ð6Þ

In order to compare the applicability of the QSAR approach to our findings, log Koc values were calculated according to the classical Karickhoff's (1979) empirical formula (Eq. (7)). Due to the fact that some of the investigated compounds occur charged at pH 8.3 (prevalent during the experiment), the pH dependent octanol–water partition coefficient log Dow instead of log Kow for the neutral form was used for calculation. log Dow values used are given in Table 1. Previously, different other equations were developed in order to assess sorption coefficients based on the octanol–water partition coefficient (e.g. Binetin and Devillers, 1994; Schwarzenbach and Westall, 1981), but that from Karickhoff et al. (1979) is the most common one and has been noted throughout the literature (Hart et al., 2004). logK oc ¼ logK ow −0:21:

ð7Þ

ð2Þ 3. Results and discussion 3.1. Linear distribution coefficients ð3Þ

where ρb is the bulk density (M L−3), Kd is the linear distribution coefficient (L3 M−1), S is the adsorbed concentration (M M−1) and α is the first-order sorption rate constant (T−1). Note that for ad- and desorption individual sorption rate constants were estimated, i.e., the rate constant in Eq. (3) was set to α = αads for adsorption (KdC — S N 0) and α = αdes for desorption (KdC — S b 0), respectively. All simulations were carried out with the PHREEQC-2 code (Parkhurst and Appelo, 1999). For the simulation of the organic compounds, the hydrodynamic dispersion coefficient as well as the pore water velocity was adopted unchanged from the conservative tracer test. Thus, only Kd and α were adjusted to reproduce the observed concentrations of the organic compounds. The Kd value identified in this manner was normalized according to

The nonreactive tracer was first detected after 36 h (see Fig. 2a). Fitting the analytical approach to the measured values revealed a hydrodynamic dispersion coefficient of 7 × 10−9 m2 s−1 and a pore water velocity of 1.7 × 10−6 m s−1, resulting in a hydraulic retention time of approximately two days (49 h) within the column. Retardation due to sorption was observed for nine out of the 20 investigated organic contaminants. Breakthrough curves similar to those of the nonreactive tracer were obtained for the remaining 11 compounds, indicating that these compounds were not subject to retardation. The entire compound class of the phenazone-type pharmaceuticals, including phenazone, propyphenazone, AAA, FAA, AMPH and AMDOPH, were transported similar to the nonreactive tracer, resulting in linear distribution coefficients of Kd = 0 L/kg and, accordingly, retardation coefficients of Rf = 1. The observed breakthrough curves, showing almost

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Fig. 2. Observed values (circles) and simulated breakthrough curves (solid lines) of the conservatively behaving compounds chloride (a), phenazone (b), propyphenazone (c), AAA (d), FAA (e), AMDOPH (f), AMPH (g), p-TSA (h), meprobamate (i), primidone (j), PEMA (k) and pyrithyldione (l).

constant concentrations after 65 h, are illustrated in Fig. 2b–g. Regarding propyphenazone our results differ slightly from those of Scheytt et al. (2004) and Mersmann et al. (2003), who observed retardation factors between 1.6 and 2.0 by means of column experiments. However, batch experiments performed by Zuehlke et al. (2007) gave no evidence that sorption occurs to propyphenazone or phenazone. A negligible sorption affinity concerning phenazone was also obtained by Benotti and Brownawell (2009), who investigated its adsorption behavior in suspended solutions. So far, information on retardation coefficients of AAA, FAA, AMPH and AMDOPH were not reported in the literature. The sulfonamide p-TSA also showed conservative transport behavior (Kd = 0 L/kg) as depicted in Fig. 2h. This result is in line with findings of Richter et al. (2008a), who suspected sorption of p-TSA to be negligible after analyzing

p-TSA residues on filter sludge samples in the course of raw water treatment. Explicit sorption experiments for p-TSA had, however, previously never been conducted. Similarly, the psychoactive drugs meprobamate, pyrithyldione, primidone and PEMA were not subject to retardation due to sorption. Their breakthrough curves agree well with that of the nonreactive tracer (Fig. 2i–l). With regard to meprobamate and primidone, our results are supported by those of Lin et al. (2011). For primidone, Yu et al. (2009) also made similar observations, investigating its sorption characteristics by means of batch experiments with three natural soils. Reference values for pyrithyldione and PEMA are unavailable, owing to the limited number of studies addressed to them. Elevated concentrations of oxazepam and diazepam were firstly measured after 65 h and maximum concentrations

V. Burke et al. / Journal of Contaminant Hydrology 154 (2013) 29–41

were observed after 125 h (Fig. 3a, b). Both breakthrough curves showed a distinct tailing indicating non-equilibrium sorption. The best data fit was achieved with adsorption rates of 4 × 10− 5 s− 1 and 7 × 10− 5 s− 1 for oxazepam and diazepam, respectively, and desorption rates of 4 × 10−5 s−1. Mechanism leading to slow desorption compared to preceding adsorption were described by Pignatello and Xing (1995). The resulting distribution coefficients for oxazepam and diazepam are 0.19 L/kg and 0.25 L/kg, respectively. These values are consistent with their similar hydrophobicity (log Dow = 2.92 and 3.08 for diazepam and oxazepam, respectively). In contrast to our findings, diazepam showed a higher sorption

Fig. 3. Observed values (circles) and simulated breakthrough curves (solid lines) of oxazepam (a), diazepam (b), phenacetine (c), methylphenacetine (d), tolyltriazole (e), sotalol (f) and atenolol (g) in comparison to the breakthrough curve of the nonreactive tracer (dashed line).

37

affinity to different soils and sediments during laboratory studies by Lin et al. (2011) and Oppel et al. (2004). Lin et al. (2011) studied its sorption behavior by means of batch experiments, which are occasionally overestimating the sorption affinity (Murillo-Torres et al., 2012; Piatt et al., 1996). Oppel et al. (2004), however, addressed the leaching potential for diazepam using soil columns filled with three different soils covering a wide range of pH values (2.9–7.0). They found diazepam sorption to be strong in all cases and concluded that the organic carbon content of the sediment seems to be the main factor influencing the sorption behavior of diazepam. However, Lin et al. (2011) used soils with organic carbon contents similarly low than those of the aquifer sediment used within this study and found an exceedingly strong sorption at least for one of the soils, indicating that the organic carbon content may not be the sole controlling factor. By investigating their sorption behavior within water/sediment systems, Loeffler et al. (2005) also suggested sorption to be a relevant process concerning diazepam, but not for oxazepam. Phenacetine (Fig. 3c) and N-methylphenacetine (Fig. 3d) exhibited almost no sorption. Due to slight deviations of their breakthrough curves from that of the conservative tracer Kd values of 0.03 L/kg have been fitted. Concerning phenacetine these results are in agreement with those of Maeng et al. (2011) who found sorption to be less important than biodegradation. The sorption behavior of N-methylphenacetine has, to our knowledge, so far never been investigated. A higher retardation coefficient and thus lower mobility was obtained for the industrial agent tolyltriazole. Elevated concentrations were firstly measured after 95 h. The maximum was achieved after 185 h, leading to a Kd value of 0.56 L/kg (Fig. 3e). The sorption process was found to be rate limited. Both adsorption and desorption were restricted to 5 × 10−5 s−1. Prior investigations described the sorption tendency of tolyltriazole to be minimal, both during treatment (Tham and Kennedy, 2005) and during residence in the subsurface environment (Jia et al., 2007). However, by conducting batch experiments Reemtsma et al. (2010) observed a moderate affinity to adsorb onto activated carbon. Altogether, these experimental values and the fact that tolyltriazole is frequently encountered in the aquatic environment (Giger et al., 2006; Janna et al., 2011; Reemtsma et al., 2010) and was even detected in drinking water (Janna et al., 2011) point towards an elevated environmental mobility. Comparably high sorption affinities were observed for the β-blockers atenolol, propranolol and metoprolol. While sotalol retarded moderately and appeared first in the sample taken after 95 h (Fig. 3f), atenolol was not detected until the sampling event after 215 h (Fig. 3g). Concerning sotalol, adsorption (6 × 10−4 s−1) proceeded significantly faster than desorption (3 × 10−5 s−1) and a Kd value of 0.43 L/kg was observed. Due to the fact that atenolol concentrations did not reach their maximum until the end of the study, the retardation can only be estimated to be approximately greater than 6. No breakthrough throughout the entire study was observed for propranolol and for metoprolol, indicating distribution coefficients N2.47 L/kg and, correspondingly, retardation coefficients N9. Investigations of Kibbey et al. (2007) resulted in retardation factors of 42 and 16 for propanolol

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V. Burke et al. / Journal of Contaminant Hydrology 154 (2013) 29–41

and metoprolol, respectively, supporting our observations. Likewise, other authors indicated a high sorption tendency of propranolol to soil (Drillia et al., 2005; Lin et al., 2010). Lin et al. (2010) suggested that sorption of propranolol is due to ion bond formations. Due to the incomplete breakthrough of atenolol, metoprolol and propranolol, the calculated Kd values have to be considered as “minimum values” and sampling should have been continued to achieve precise values. Accordingly, Kd values available in the literature are significantly higher than these (Lin et al., 2010). In turn, the Koc values obtained from Ramil et al. (2010) and Yamamoto et al. (2009) are in the order of magnitude of minimum values given. A high mobility within aquifers can be expected for nearly all of the investigated compounds (assuming similar aquifer characteristics). As a result, a potential for rapid leaching into the groundwater exists and has to be considered. Exceptions are the β-blockers atenolol, propranolol and metoprolol, for which retardation coefficients N6 were observed. Their mobility may be comparably low, however, their omnipresence in the aquatic environment continues to provide evidence of their environmental relevance. Rate limited sorption was observed for tolyltriazole, oxazepam, diazepam and sotalol. Calculated “sorption half-

life times” ranged between t50 = 0.1 h (sotalol) and t50 = 3.0 h (oxazepam) for the adsorption process and t50 = 1.4 h (tolyltriazole) and t50 = 6.0 h (oxazepam) with regard to the desorption process. Transferring these dimensions to field scale conditions, which are commonly characterized by significantly longer travel times, rate limitations are assumed to be insignificant in the field for these four compounds. 3.2. Comparison to QSAR derived and literature values Experimentally determined distribution coefficients (Kd) were used to calculate organic carbon normalized distribution coefficients (Koc) according to Eq. (4). For atenolol, propranolol and metoprolol, for which the breakthrough was not completed during the investigation period, minimum distribution coefficients assessed within this study were assumed (Kd N 1.54 L/kg for atenolol and Kd N 2.47 L/kg for propranolol and metoprolol). Except for the non-retarded compounds (for which Kd = 0 L/kg), Kd values from 0.03 L/kg (phenacetine, N-methylphenacetine) to N2.47 L/kg (propranolol, metoprolol) were obtained (Table 3). Normalizing these distribution values to the organic carbon content of the test sediment (foc = 0.20%) gives log Koc values from 1.18 L/kg to N3.09 L/kg (Table 3).

Table 3 Values for Rf, Kd and log Koc (estimated based on log Dow, experimentally determined and literature data). Substance

Estimateda Rf

Experimental Kd

log Koc

Rf

(L/kg)

From literature

Kd

log Koc

1.0 1.1 1.0 1.1 1.0 1.9

0 0.03 0 0.02 0 0.28

−0.12 1.09 −0.10 1.01 −0.06 2.14

1.0 1.0 1.0 1.0 1.0 1.0

Atenolol

1.0

0

−1.16

N6.0

N1.54

N2.89

Metoprolol Sotalol Propranolol

1.0 1.0 1.1

0 0 0.02

0.17 −1.49 0.99

N9.0 2.4 N9.0

N2.47 0.43 N2.47

N3.09 2.33 N3.09

Primidone Meprobamate Pyrithyldione PEMA Oxazepam Diazepam

1.1 1.0 1.1 1.0 4.3 5.8

0.02 0.01 0.05 0.01 1.03 1.48

0.91 0.72 1.35 0.52 2.71 2.87

1.0 1.0 1.0 1.0 1.6 1.8

0 0 0 0 0.19 0.25

1.97 2.09

Tolyltriazole p-TSA Phenacetine N-Methylphenacetine

1.2 1.0 1.1 1.1

0.08 0.01 0.03 0.02

1.51 0.88 1.20 1.06

2.8 1.0 1.1 1.1

0.56 0.00 0.03 0.03

b c d e f g h i j k

Calculated based on log Dow values given in Table 1. Scheytt et al. (2004). Scheytt et al. (2005). Mersmann et al. (2003). Yamamoto et al. (2009). Ramil et al. (2010). Kibbey et al. (2007). Lin et al. (2010). Yu et al. (2009). Loeffler et al. (2005). Lin et al. (2011).

Kd

log Koc

(L/kg)

AMDOPH AMPH FAA Phenazone AAA Propyphenazone

a

Rf

(L/kg) 0 0 0 0 0 0

1.6b 2.0d

2.44 1.18 1.18

1.81c 1.3–8.1e

16g 42g

2.2–160e 270h 0.02–0.75i

2.2j 3j 6k

1.85–2.05f 2.5–3.2e 1.75–2.22f 1.41–1.94f 2.43–4.55f 3.5–4e −0.04–1.07i

2.28j 2.18j

V. Burke et al. / Journal of Contaminant Hydrology 154 (2013) 29–41

39

Fig. 4. Kd values estimated based on ph dependent octanol–water partition coefficient log Dow vs. experimental determined Kd values. Plotted in brackets are Kd values calculated based on minimum retardation coefficients determined within this study.

To compare our findings with QSAR derived sorption parameters, organic carbon-referenced distribution coefficients (log Koc) and subsequently linear distribution coefficients (Kd) were estimated according to Eqs. (7) and (4), respectively, using octanol–water partition coefficients given in Table 1. The calculated values were plotted against those determined experimentally within this study and the result is given in Fig. 4. QSAR significantly underestimated Kd values for metoprolol, propranolol and atenolol, even though experimental values were only minimum values. It overestimated Kd values for oxazepam and diazepam. The herein applied QSAR approach uses the Karickhoff et al. (1979) formulae which is based on investigations on largely hydrophobic compounds. Hence, it may often fail in predicting the sorption behavior of polar and ionic compounds (Carballa et al., 2008). This likely explains the mentioned underestimations concerning the β-blockers, which are mainly positively charged at the ambient pH of 8.3 (pKa N 9). Since oxazepam and diazepam are uncharged at pH 8.3, other interactions than electrostatic ones seem responsible for the deviations. Altogether, the presented data confirm suggestions already made by other authors (Maeng et al., 2010; Maurer et al., 2007; Schaffer et al., 2012; Yamamoto et al., 2009) concerning some limitations of the Kow/Dow based QSAR approach. 4. Conclusions • No or only low tendencies to sorb onto the glaciofluvial sandy test sediment were found for most of the investigated compounds, indicating a high mobility of the contaminants within the aquifer. • A moderate sorption affinity was observed for the β-blocker sotalol and the anticorrosive agent tolyltriazole, while high sorption affinities were determined for the β-blockers atenolol, propranolol and metoprolol. • Sorption was found to be rate limited for tolyltriazole, oxazepam, diazepam and sotalol. Nevertheless, sorption rates observed for these compounds revealed sorption

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