Fate of Pharmaceuticals and Their Transformation Products in Four

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Fate of Pharmaceuticals and their Transformation Products in four small European Rivers receiving treated Wastewater Zhe Li, Anna Sobek, and Michael Radke Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.5b06327 • Publication Date (Web): 06 May 2016 Downloaded from http://pubs.acs.org on May 6, 2016

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Environmental Science & Technology

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Fate of Pharmaceuticals and their Transformation

2

Products in four Small European Rivers receiving

3

treated Wastewater

4

Zhe Li*, Anna Sobek, Michael Radke*,†

5

Department of Environmental Science and Analytical Chemistry (ACES), Stockholm University,

6

10691 Stockholm, Sweden

7

ABSTRACT

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Considerable knowledge gaps exist with respect to the fate and environmental relevance of

9

transformation products (TPs) of polar organic micropollutants in surface water. To narrow this

10

gap we investigated the fate of 20 parent compounds (PCs) and 11 characteristic TPs in four

11

wastewater-impacted rivers. Samples were obtained from time-integrated active sampling as well

12

as passive sampling using polar organic chemical integrative samplers (POCIS). Seventeen out

13

of the 20 PCs were detected in at least one of the rivers. All the PCs except acesulfame,

14

carbamazepine and fluconazole were attenuated along the studied river stretches, with the largest

15

decrease found in the smallest river with intense surface water-pore water exchange. Seven TPs

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were detected, all of which were already present directly downstream of the WWTP outfall, thus

17

suggesting that the WWTPs were a major source of TPs to the recipients. For anionic

ACS Paragon Plus Environment

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compounds, attenuation was the highest in the two rivers with the lowest discharge, while the

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pattern was not as clear for neutral or cationic compounds. For most compounds the results

20

obtained from active sampling were not significantly different from those using POCIS,

21

demonstrating that the cost and labor efficient POCIS is suitable to determine the attenuation of

22

organic micropollutants in rivers.

23

24

INTRODUCTION

25

Recent research has highlighted the importance of investigating biotic and abiotic attenuation

26

processes of pharmaceuticals in rivers.1-5 These processes are substance specific and highly

27

dependent on environmental conditions such as redox status, solar irradiation, microbial

28

communities etc.6-9 To deepen our process-understanding and to identify relevant drivers and

29

constraints of micropollutant transformation in rivers, field studies focusing on a common set of

30

compounds and using comparable sampling strategies are necessary. Moreover, currently there

31

are very few datasets on such a common set of compounds available that cover the range from

32

lab experiments to field studies. This lack of consistent data hampers a straightforward

33

comparison between observations on these various scales and in systems of different complexity.

34

A holistic assessment of the environmental fate of organic micropollutants needs

35

comprehensive information on the formation of their transformation products (TPs).

36

Transformation is frequently associated with detoxification of pollutants, but persistent and/or

37

toxic products may also be formed. For instance, two polar TPs of the antiviral drug acyclovir

38

were found to significantly reduce the reproduction level of Daphnia magna and to inhibit the

39

growth of green algae.10 Another such example is the increased toxicity to algae reported after


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UV irradiation of surface water containing cephalosporin antibiotics.11 Some TPs may be formed

41

at relatively high yields,9,12 as shown in a study on riverbank filtration where atenolol was almost

42

quantitatively transformed into atenolol acid.9 Furthermore, some TPs may back-transform into

43

the parent compounds (PCs) under certain conditions,13 thereby increasing the exposure to the

44

PC downstream of the point of discharge or initial transformation.14 While the knowledge of the

45

environmental fate of pharmaceuticals and other polar micropollutants is increasing, the fate of

46

their TPs is rarely investigated, despite of a consistently increasing number of studies reporting

47

the environmental occurrence of such TPs.

48

In studies on the fate of polar organic micropollutants in surface water, samples are typically

49

collected using an active method.2,5 It is cost and labor intensive to collect and analyze large

50

numbers of samples. Passive sampling is an alternative approach to determine time-integrated

51

concentrations of such micropollutants in the water phase in a more economic manner. Polar

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organic chemical integrative samplers (POCIS), which are designed to sample hydrophilic

53

organic compounds from the aqueous environment, are one type of the most commonly used

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passive samplers. The POCIS sampler has been successfully applied in many environmental

55

monitoring studies,15-17 but its potential for determining the attenuation of organic

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micropollutants needs further exploration.

57

In the present study, we selected four small- to medium-sized wastewater-receiving rivers in

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Sweden and Germany to simultaneously characterize the fate of both PCs and TPs in situ. The

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rivers cover a wide range of effluent proportion, from as low as 1% of treated wastewater up to

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80% under the conditions studied. We analyzed 20 PCs and 11 TPs. The selection of the PCs

61

was based upon their widespread presence in effluent-receiving aquatic systems all over Europe

62

and America. We have studied the transformation of these compounds in previous laboratory


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experiments12,18 where we identified and investigated the TPs now monitored in this field study.

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The overarching aim of the study was to improve our understanding of how attenuation of

65

organic micropollutants relates to river characteristics by comparing the behavior of the studied

66

PCs among the four rivers. We also investigated to what extent the presence of TPs can be

67

explained by the attenuation of their PCs. An additional aim was to explore the possibilities of

68

using passive sampling to reduce the resources needed for future studies on the fate of organic

69

micropollutants in rivers.

70 71

EXPERIMENTAL METHODS

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Chemicals and Reagents

73 74

Details on all chemicals and reagents are provided as Supporting Information. Study Sites

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Sampling was carried out at four wastewater-impacted rivers: Gründlach (GR; Germany),

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Fyris (FY; Sweden), Rönne (RO; Sweden) and Viskan (VI; Sweden), with varying hydraulic

77

boundary conditions (see Table 1 for details and Figure S1 for maps of the study areas). The

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rivers were selected based on three requirements: 1) continuous discharge of WWTP effluent as

79

the main source of organic micropollutants; 2) a sufficient proportion of WWTP effluent in the

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river to facilitate detection of the studied compounds; and 3) existence of a stretch downstream

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of the WWTP outfall with no major tributaries or additional sources of organic micropollutants.

82

For rivers FY and VI, there is another small WWTP further upstream discharging treated

83

wastewater into the rivers. During the sampling period, electrical conductivity, dissolved oxygen,

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pH, and temperature in surface water were measured every two days at all sites using handheld

85

probes (Hach, Düsseldorf, Germany). Discharge records during the sampling period were


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obtained from a gauging station operated by the local water board (Wasserwirtschaftsamt

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Nürnberg, Germany) for river GR and from the Swedish Water Archive (SVAR) for the three

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Swedish rivers. Details on the general parameters and discharge data are provided as Supporting

89

Information (Figure S2 and Table S2). Total organic carbon (TOC) in river water was measured

90

at all sites using a TOC-VCPH analyzer (Shimadzu, Kyoto, Japan) following the non-purgeable

91

organic carbon (NPOC) protocol. Ultraviolet (UV) absorbance at a wavelength of 254 nm in the

92

river water samples was measured on an Evolution 260 Bio UV-Visible spectrophotometer

93

(Thermo Fisher Scientific, Stockholm, Sweden).

94

Water was sampled over a period of one week at both ends (sites A and B) of a stretch

95

downstream of the WWTP outfall. Site A was located after the complete mixing of the WWTP

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effluent with the river water, which was verified using an established USGS guideline.19 The

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distance between the WWTP outlet and site A was about 500 m for all rivers except for RO, for

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which the distance was 3.5 km because it was impossible to access a site closer to the WWTP

99

effluent that allowed setting up the sampling equipment. Site B was located 6-12 km further

100

downstream of site A yet before the next major source of organic micropollutants into the river

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(e.g., a confluence or effluent from other WWTPs). Sampling at site B started 12 hours later than

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at site A. This time difference was chosen based on pragmatic reasons as the corresponding

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travel times (based on river discharge data) between sites A and B were only available after the

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sampling campaign was terminated.

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Table 1. Characteristics of the Sampling Sites in the Four Studied Rivers Abbreviation River name WWTP (population equivalents) sampling site A coordinates

sampling site B coordinates (distance from site A)

sampling period average discharge (m3 s-1)a temperature (°C)b pHb travel time (d)c

107 108 109 110 111

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GR Gründlach Heroldsberg (12 000) GR_A N 49°31'29.8" E 11°8'4.8" GR_B N 49°31'22.3" E 11°1'27.1" (12 km) 2014/06/14 – 2014/06/22 0.029 ± 0.007 15 ± 0.7 8.0 ± 0.2 2.1

FY Fyris Kungsängsverket (164 200) FY_A N 59°50'32.5" E 17°39'23.8" FY_B N 59°47'14.6" E 17°39'46.4" (7 km) 2014/06/25 – 2014/07/02 2.7 17 ± 1.0 8.1± 0.3 0.6

RO Rönne Klippans (17 000) RO_A N 56°09'47.7" E 13°03'15.4" RO_B N 56°12'26.7" E 12°59'12.1" (6 km) 2014/08/05 – 2014/08/12 5.9 ± 0.6 20 ± 0.6 7.1 ± 0.6 1.0

VI Viskan Gässlösa (80 000) VI_A N 57°42'27.3" E 12°54'55.8" VI_B N 57°39'11.9" E 12°53'27.1" (7 km) 2014/08/23 – 2014/08/30 6.0 ± 0.9 16 ± 1.2 7.0 ± 0.6 1.1

a

For river FY the average discharge data of the month of June from the previous year was used as the gauging station was not operational during the sampling period; bAverage values and standard deviations were calculated from data at sampling sites A and B for the whole sampling period; c Travel time was approximated based on discharge, average stream depth and width, and travel distance.

112 113

Sampling Methods

114

Active Sampling

115

At each river, time-integrated water samples were collected at the two sampling sites with

116

automatic water samplers (model 3700 compact, equipped with a Teflon suction line and a

117

stainless steel inlet filter; Teledyne ISCO, Lincoln, NE) for one week during summer 2014

118

(Table 1). Water (50 mL) was sampled every hour at a depth of approximately 20 cm below the

119

water surface; 24 consecutive samples were combined to one daily composite sample. At the end

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of the sampling period, 150 mL aliquots of these daily samples were combined to give a weekly

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composite sample for each site. As we did not have accurate discharge data at the necessary time

122

resolution for the two sampling sites, flow proportional sampling was not possible. However,


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Figure S2 in the Supporting Information shows that the discharge variation was small for all the

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studied rivers during the sampling period, so the difference between the time- and flow-

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proportional strategies are expected to be minor. During the sampling period, all samples were

126

kept in darkness and the cavity of the sampler was filled with ice. Samples were subsequently

127

stored in 1 L HDPE containers and frozen immediately upon retrieval from the samplers.

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Passive Sampling

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Duplicate POCIS were deployed at each site during the same period as the active samples were

130

collected. The passive samplers were obtained from Environmental Sampling Technologies

131

(EST) Inc. (St. Joseph, MO, USA) and contained 200 mg of Oasis® HLB solid-phase sorbent

132

(Waters Corp., Milford, MA, USA) sandwiched between two sheets of a 0.1 µm pore size

133

polyether sulfone membrane. Upon retrieval, all POCIS were gently cleaned according to the

134

standard operating procedure (EST Laboratories, 2012) before they were tightly wrapped with

135

aluminum foil and stored frozen until analysis.

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Analytical Methods

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Extraction of Water Samples

138

River water samples were extracted by solid phase extraction (SPE). An extraction volume of

139

500 mL was used for the Swedish rivers FY, RO, and VI, while 250 mL was extracted for river

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GR where higher concentrations of micropollutants were expected based on previous work.2 All

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samples were spiked with an internal standard mixture containing 24 isotope-substituted

142

compounds (100 ng of each compound dissolved in methanol). Prior to SPE, the samples were

143

vacuum filtered (glass microfiber filter, particle retention 1.2 µm, VWR, Stockholm, Sweden).

144

The pH of the filtrate was adjusted to 7.0 using sulfuric acid (0.3 M). Oasis® HLB cartridges

145

(500 mg/6 mL) were preconditioned with 5 mL of methanol followed by 5 mL of Milli-Q water


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(pH was adjusted to 7.0 using 1 M sodium hydroxide and 0.3 M sulfuric acid) at a flow rate of 5

147

mL min-1 before the samples were loaded onto the cartridges on a vacuum extraction manifold at

148

a flow rate of approximately 10 mL min-1. The cartridges were subsequently rinsed with 5 mL of

149

Milli-Q water (pH=7.0) and finally dried for 1 h under a nitrogen stream. Afterwards the

150

cartridges were eluted with 3 mL of methanol. The extracts were evaporated close to dryness

151

under a gentle nitrogen stream at 35 ºC and reconstituted with 2 mL of water/acetonitrile (80:20,

152

v/v, 0.1% formic acid). The final extracts were filtered directly into a glass vial using a 0.45 µm

153

PTFE syringe filter. Recoveries of the extraction method for the analytes were measured by

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analyzing spiked (with the target substances at a final concentration of 10 µg L-1) river water

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collected from an additional Swedish river (Tidan).

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Processing of Passive Samplers

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The extraction procedure of POCIS was based on the manufacturer’s standard operating

158

procedure. Briefly, the POCIS was rinsed with deionized water to remove any material adhering

159

to the membrane surfaces. Each sampler was then disassembled and the sorbent material was

160

carefully transferred into a 6 mL cartridge with a polyethylene frit, spiked with a solution of

161

isotope-substituted internal standards (100 ng each), and covered with another polyethylene frit.

162

The cartridge was then rinsed with 5 mL of Milli-Q water to minimize any matrix interference

163

(e.g., salts) and dried under vacuum to remove the excess of water. Elution of the analytes was

164

performed using 25 mL of methanol. The treatment of the eluate was identical to the treatment of

165

the active samples. Two POCIS samplers were analyzed as procedural blanks.

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Analysis

167

All sample extracts were stored at -18 ºC until analysis with ultra-high performance liquid

168

chromatography (ACQUITY UPLC system, Waters) coupled to a triple quadrupole mass


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spectrometer (Xevo TQ-S; Waters) using electrospray ionization. An ACQUITY HSS T3

170

column (100 mm × 2.1 mm, particle diameter 1.8 µm; Waters) was used with a binary mobile

171

phase gradient consisting of A) water/acetonitrile (95:5, v/v) and B) water/acetonitrile (5:95,

172

v/v), both containing 10 mM acetic acid. The injection volume was 5 µL. The gradient

173

separation program is provided as Supporting Information.

174

Twenty PCs and 11 TPs were analyzed. The internal standard method with isotope-substituted

175

standards was used for quantification. Calibration curves were based on 10 standards with the

176

analytes in a concentration range of 0.01-10 µg L-1 and calculated using a weighted (1/x) linear

177

least-squares regression. All extracts were analyzed undiluted and after dilution with

178

water/acetonitrile (80:20, v/v, 0.1% formic acid) by a factor of 20 to ensure that the injected

179

concentrations of all target compounds were within the linear dynamic range of the instrument.

180

A calibration series was measured both before and after every sample sequence. The intra-day

181

variability of the instrument was assessed by analyzing a quality control solution (1.0 µg L-1 of

182

each analyte) prior to each batch of samples. For quality-control purposes, four of the calibration

183

standards and a solvent blank (water/acetonitrile 80:20, v/v, 0.1% formic acid) were measured

184

every eight samples. The method quantification limit (MQL) ranged from 0.04 ng L-1 for most

185

analytes to 4.0 ng L-1 for carboxyibuprofen (details available as Table S3 in the Supporting

186

Information).

187 188

Calculations

189

Concentration changes between sites A and B were calculated indirectly by using

190

concentrations normalized to those of a reference compound. This method was previously

191

demonstrated valid under conditions of relatively constant discharge,2 which were met in this


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study (Figure S2). The method also relies on rather constant compound ratios in the WWTP

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effluent, which is reasonable to assume for the compounds targeted in this study (only

194

micropollutants with regular use pattern, no compounds for which an individual patient could be

195

the single source in a small catchment). We used fluconazole, which was shown to be persistent

196

in previous lab experiments,12 as reference compound to account for dilution by infiltrating

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groundwater or minor tributaries along the stretch. The relative attenuation (Attx) of a compound

198

was calculated using the fluconazole-normalized concentrations. In addition, acesulfame – an

199

artificial sweetener previously used as a benchmark chemical to quantify persistence of polar

200

chemicals in lakes20 – was used to cross-check the persistence of fluconazole. For each river,

201

Attx of a substance along the stretch was calculated by first dividing its concentration at site B by

202

the concentration at site A, then normalizing this ratio by the concentration ratio of fluconazole

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at both sites. A positive value indicates a loss of the compound along the stretch, while a

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negative value indicates a concentration increase. A value of 0 indicates that either the

205

compound is persistent or its attenuation is at a similar rate as its formation. Attx (%) of a

206

compound between site A and B is thus given by:

207

Att x = (1 −

𝐶𝐶x,siteB 𝐶𝐶x,siteA

𝐶𝐶REF,siteB

𝐶𝐶REF,siteA

) × 100%

(1)

208

where Cx,siteA and Cx,siteB are the concentrations (ng L-1) of the substance x at site A and B,

209

respectively, CREF,siteA and CREF,siteB are the concentrations (ng L-1) of the reference compound

210

fluconazole at sites A and B. For calculation purposes, when the concentration of an analyte at

211

site B as below MQL this concentration was set to the respective MQL. This method was chosen

212

as it provides a conservative estimate of the attenuation (i.e., likely underestimates the real

213

attenuation).


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214

To estimate concentrations of pollutants in river water by POCIS, uptake kinetics of the target

215

compounds are necessary. Such calibration data is dependent on specific characteristics

216

(temperature, pH, flow velocity, turbulence etc.) of the sampling site and was not available.

217

However, within the scope of this study the concentrations determined from POCIS are not

218

needed. Instead, we calculated Attx of the analytes in samples from POCIS the same way as for

219

the analytes in samples collected with active sampling, using eq (1). This procedure does not

220

require any calibration of the POCIS, but relies on the assumption that the uptake kinetics of a

221

compound at the two sampling sites are identical, which is reasonable as the river characteristics

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do not change substantially between the two sampling sites in the four rivers.

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For samples from both active and passive sampling, the 95% confidence intervals and p-values

224

for Attx were determined using an ANOVA model with Bonferroni correction after log-

225

transforming the data, meaning that geometric means are used instead of arithmetic means.

226

Quality Assurance

227

None of the analytes was detected in solvent blank samples (water/acetonitrile 80:20, v/v,

228

0.1% formic acid) or procedural blanks. The intra-day coefficient of variation of the instrument

229

was 0). Attx of acesulfame close

292

to 0 was expected due to its known persistence,22 which also confirms that no significant

293

attenuation of the reference compound fluconazole occurred along the studied river stretches and

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thus supports the applicability of fluconazole as reference compound in this study. Although

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biodegradation of carbamazepine has previously been observed in lab experiments12,18 and its TP

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carbamazepine-10,11-epoxide has been detected in various aquatic systems9,25,26 as well as in

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this study, neither attenuation of carbamazepine nor a change of fluconazole-normalized

298

concentrations of its TP was observed. The persistence of carbamazepine in the current study is

299

also supported by a study by Zou et al. (2015) who estimated a transformation half-life of 780-

300

5700 d in a Swedish lake.20

301

Based on an overall assessment of the Attx values of the 14 PCs that were attenuated in at least

302

one river (see Figure S4 for an aggregated view), river GR sticks out as the river with the most

303

efficient micropollutant attenuation. On a per-compound basis, attenuation of each individual

304

compound is also the highest in river GR (Figure 3). The Attx values ranged from about 20% for

305

sulfamethoxazole and tramadol to >80% for acetaminophen, bezafibrate and furosemide (Table

306

S5). Kunkel and Radke (2012) investigated the environmental fate of 10 pharmaceuticals along

307

the same stretch of river GR in the summer of 2010.2 Their dataset and the one generated in this

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study can be considered temporal replicates as both studies were carried out in summer and at


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low river discharge (approximately 0.03-0.04 m3 s-1). For the six compounds attenuated in both

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studies, Attx are in good agreement. For example, Attx of propranolol and sulfamethoxazole was

311

70% and 25% in Kunkel and Radke (2012) and 73% and 18% in this study, respectively (see

312

Table S6). Kunkel and Radke (2012) already concluded that the boundary conditions in river

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GR, e.g., shallow depth, low turbidity, and sandy sediments, make photolysis in the water

314

column and biotransformation in the hyporheic zone relatively efficient. This is also supported

315

by the lowest TOC content and UV absorbance (Table S2) and also the highest global

316

radiation/longest sunshine hours (Figures S3) in GR compared to the other rivers, which further

317

demonstrates that GR provided the most favorable conditions for attenuation of compounds

318

susceptible to photodegradation. In addition, the large proportion of wastewater in river GR may

319

lead to a high abundance of co-emitted wastewater bacteria in the water column or to the

320

establishment of a well-adapted biofilm community at the water/sediment interface, both may be

321

capable of efficiently transforming organic micropollutants.

322

The comparison between the results from the three Swedish rivers is not straightforward

323

(Figure 2). All compounds present as anionic species, except sulfamethoxazole, were attenuated

324

much more efficiently in river FY than in the other rivers, while two of the neutral compounds

325

(acetaminophen, bicalutamide) were not attenuated at all in river FY as compared to Attx of 18-

326

46% in rivers RO and VI. The pattern becomes even more complex when two of the cationic

327

compounds, the beta-blockers metoprolol and propranolol, are taken into account with similar

328

Attx values between 16 and 30 % in rivers FY and RO while no attenuation was observed in river

329

VI. For the third beta-blocker, sotalol, the opposite pattern was observed with no attenuation in

330

FY and RO and 20% in VI. For sotalol, this is most likely attributed to photodegradation as

331

reported previously.2,27 This interpretation is supported by the characteristics of rivers GR and VI


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332

as they both have less shading along the studied stretch compared to the other two rivers, and by

333

the lowest TOC concentration and UV absorbance (Table S2), thus providing better conditions

334

for light penetration into the water column. However, this interpretation is not in line with the

335

Attx pattern of diclofenac, another compound susceptible to photolysis, which had the lowest

336

Attx values in rivers VI and RO. No explanation can be given to resolve this apparent

337

contradiction. The attenuation of hydrochlorothiazide was similar in all the three Swedish rivers

338

but lower than in GR (Attx 36%) by a factor of 1.6-2.0. We conclude that the overall attenuation

339

of hydrochlorothiazide was again favored under the boundary conditions of GR. Previous studies

340

demonstrated that the loss of hydrochlorothiazide in a water-sediment system was attributed to a

341

combination of biotic and abiotic transformation processes such as hydrolysis and

342

photodegradation.7,12,28

343

There is no obvious explanation for the observed lack of a common attenuation pattern in the

344

Swedish rivers. Correlation analysis was performed between the physical-chemical properties of

345

the compounds (pKa and log Dow as shown in Table S1) and the calculated attenuation rates.

346

There is no significant correlation between Attx and any of these properties, meaning that we

347

cannot generalize the attenuation of a compound based on its physical-chemical properties.

348

Based on the anionic compounds, the conclusion would be that biotransformation in river FY is

349

most efficient, while based on the neutral compounds the conclusion would be the opposite. For

350

the cationic beta-blockers, sorption to negatively charged sites in solid matter has been shown a

351

relevant loss process in addition to biotransformation.7,12 Sorption to suspended matter and

352

subsequent significant sedimentation of suspended matter between sites A and B is however

353

unlikely as a loss process, as the overall particle load was apparently low (no sedimentation in


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354

sampling bottles observed) and TOC concentrations at sites A and B (Table S2) were

355

comparable.

356

357 358

Figure 2. Relative attenuation (Attx, %) of parent compounds between site A and B in the four

359

rivers as determined by active sampling (ACES: acesulfame, BEZ: bezafibrate, DIC: diclofenac,

360

FUR: furosemide, GLI: glimepiride, KET: ketoprofen, SUL: sulfamethoxazole, ACET:

361

acetaminophen, BIC: bicalutamide, CAR: carbamazepine, CHL: chlorthalidone, HYD:

362

hydrochlorothiazide, MET: metoprolol, PRO: propranolol, SOT: sotalol, TRA: tramadol). Shown

363

are the 16 out of 19 parent compounds that were detected in at least one river. The compounds

364

are grouped according to their dominant species present at a river water pH of 7.0-8.0. The error

365

bars represent the 95% confidence intervals (relative attenuation is significant if the 95%

366

confidence interval does not include 0). An asterisk indicates that the concentration of a

367

compound was below MQL in the river.

368 369


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Transformation Products

371

Of the 11 TPs analyzed, seven were detected at both site A and B in the four rivers. Their

372

concentrations ranged from 0.29 ng L-1 for α-hydroxymetoprolol in RO to 890 ng L-1 for

373

metoprolol acid in GR (Table S4). Figure 3 shows the Attx values calculated for the TPs. We

374

expected to observe a formation of TPs (i.e., negative Attx values) along with the attenuation of

375

the PCs in a given river system, as was observed in a flume experiment in the laboratory.12

376

However, this expectation was only met for two TPs: 4-chlorobenzoic acid (TP of bezafibrate) in

377

RO and VI, and metoprolol acid (TP of metoprolol) in FY and RO. For all other instances, Attx

378

was ≥0 and the concentrations of all TPs at sampling site A were unexpectedly high.

379

The accumulation of 4-chlorobenzoic acid (RO -103%; VI -97%) indicates an ongoing

380

biotransformation of bezafibrate, which is supported by the attenuation of the PC (Figure 2).

381

However, based on the decrease of bezafibrate concentrations along the stretch (RO: 0.1 ng L-1;

382

VI: 0.3 ng L-1) and the increase of TP concentrations (RO: 23 ng L-1; VI: 5.1 ng L-1; see also

383

Table S4), there seems to be one or more additional compounds transforming into 4-

384

chlorobenzoic acid or there exists another source of this compound between the sampling sites.

385

In contrast to RO and VI, 4-chlorobenzoic acid was attenuated in parallel to bezafibrate in the

386

other two rivers (GR and FY). Metoprolol acid was attenuated in GR (Attx 39%), while it

387

accumulated in FY (Att -8%) and RO (Attx -16%) (Figure 3). Metoprolol acid has an additional

388

parent compound (atenolol);29 as this was not analyzed in this study, a more detailed

389

interpretation of this TP is not possible. Two TPs of hydrochlorothiazide have previously been

390

identified as products formed in a sequence of transformation steps, with chlorothiazide as an

391

intermediate detected at lower levels than 4-amino-6-chloro-1,3-benzenedisulfonamide.12,18 The

392

results of the current study are qualitatively in line with these findings with respect to the lower


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393

concentrations of chlorothiazide (Table S4). In addition, in all rivers the TP carbamazepine-

394

10,11-epoxide was detected at similar concentrations at both sites A and B. Its PC

395

carbamazepine is persistent and therefore no formation of carbamazepine-10,11-epoxide was

396

expected along the stretch. The persistence of the TP is also in line with previous degradation

397

studies in both water and soil.12,30 In general, the majority of the detected TPs were attenuated in

398

river GR, which also is the river where attenuation of the PCs was highest (Figure 2). As argued

399

above, this can be attributed to the boundary conditions in GR that provide an environment

400

favorable for the attenuation of organic micropollutants.

401

While several PCs were substantially attenuated along the distance of 6-12 km between the

402

two sampling sites in the rivers, the concentration increase of the corresponding TPs was less

403

evident (Figure 3). This might be due to short half-lives of the formed TPs preventing their

404

concentrations to build up. Alternatively, the expected increase of TP concentrations might be

405

masked by the rather high concentrations of all of the seven detected TPs already at site A. Since

406

the travel time for the distance between the WWTP and site A was short (

Fate of Pharmaceuticals and Their Transformation Products in Four

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