Pharmaceuticals, Hormones, and

Other Organic Wastewater

Contaminants in U.S. Streams,

1999-2000: A National

Reconnaissance

DANA W. KOLPIN*

U.S. Geological Survey, 400 S. Clinton Street, Box 1230,

Iowa City, Iowa 52244

EDWARD T. FURLONG

U.S. Geological Survey, Box 25046, MS 407,

Denver, Colorado 80225-0046

MICHAEL T. MEYER

U.S. Geological Survey, 4500 SW 40th Avenue,

Ocala, Florida 34474

E. MICHAEL THURMAN

U.S. Geological Survey, 4821 Quail Crest Place,

Lawrence, Kansas 66049

STEVEN D. ZAUGG

U.S. Geological Survey, Box 25046, MS 407,

Denver, Colorado 80225-0046

LARRY B. BARBER

U.S. Geological Survey, 3215 Marine Street,

Boulder, Colorado 80303

HERBERT T. BUXTON

U.S. Geological Survey, 810 Bear Tavern Road,

West Trenton, New Jersey 08628

To provide the first nationwide reconnaissance of the

occurrence of pharmaceuticals, hormones, and other

organic wastewater contaminants (OWCs) in water resources,

the U.S. Geological Survey used five newly developed

analytical methods to measure concentrations of 95 OWCs

in water samples from a network of 139 streams across

30 states during 1999 and 2000. The selection of sampling

sites was biased toward streams susceptible to contamination (i.e. downstream of intense urbanization and livestock

production). OWCs were prevalent during this study,

being found in 80% of the streams sampled. The compounds

detected represent a wide range of residential, industrial,

and agricultural origins and uses with 82 of the 95

OWCs being found during this study. The most frequently

detected compounds were coprostanol (fecal steroid),

cholesterol (plant and animal steroid), N,N-diethyltoluamide

(insect repellant), caffeine (stimulant), triclosan (antimicrobial

disinfectant), tri(2-chloroethyl)phosphate (fire retardant),

and 4-nonylphenol (nonionic detergent metabolite). Measured

concentrations for this study were generally low and

rarely exceeded drinking-water guidelines, drinking-water

health advisories, or aquatic-life criteria. Many compounds,

however, do not have such guidelines established. The

detection of multiple OWCs was common for this study, with

a median of seven and as many as 38 OWCs being

found in a given water sample. Little is known about the

potential interactive effects (such as synergistic or

antagonistic toxicity) that may occur from complex mixtures

of OWCs in the environment. In addition, results of this

study demonstrate the importance of obtaining data on

metabolites to fully understand not only the fate and transport

of OWCs in the hydrologic system but also their ultimate

overall effect on human health and the environment.

Introduction

The continued exponential growth in human population has

created a corresponding increase in the demand for the

Earth’s limited supply of freshwater. Thus, protecting the

integrity of our water resources is one of the most essential

environmental issues of the 21st century. Recent decades

have brought increasing concerns for potential adverse

human and ecological health effects resulting from the

production, use, and disposal of numerous chemicals that

offer improvements in industry, agriculture, medical treatment, and even common household conveniences (1).

Research has shown that many such compounds can enter

the environment, disperse, and persist to a greater extent

than first anticipated. Some compounds, such as pesticides,

are intentionally released in measured applications. Others,

such as industrial byproducts, are released through regulated

and unregulated industrial discharges to water and air

resources. Household chemicals, pharmaceuticals, and other

consumables as well as biogenic hormones are released

directly to the environment after passing through wastewater

treatment processes (via wastewater treatment plants, or

domestic septic systems), which often are not designed to

remove them from the effluent (2). Veterinary pharmaceuticals used in animal feeding operations may be released to

the environment with animal wastes through overflow or

leakage from storage structures or land application (3). As

a result, there are a wide variety of transport pathways for

many different chemicals to enter and persist in environmental waters.

Surprisingly, little is known about the extent of environmental occurrence, transport, and ultimate fate of many

synthetic organic chemicals after their intended use, particularly hormonally active chemicals (4), personal care

products, and pharmaceuticals that are designed to stimulate

a physiological response in humans, plants, and animals (1,

5). One reason for this general lack of data is that, until

recently, there have been few analytical methods capable of

detecting these compounds at low concentrations which

might be expected in the environment (6). Potential concerns

from the environmental presence of these compounds

include abnormal physiological processes and reproductive

impairment (7-12), increased incidences of cancer (13), the

development of antibiotic-resistant bacteria (14-17), and

the potential increased toxicity of chemical mixtures (18).

For many substances, the potential effects on humans and

aquatic ecosystems are not clearly understood (1, 2, 19).

The primary objective of this study is to provide the first

nationwide reconnaissance of the occurrence of a broad suite

of 95 organic wastewater contaminants (OWCs), including

* Corresponding author phone: (319)358-3614; fax: (319)358-3606;

e-mail: dwkolpin@usgs.gov.

Environ. Sci. Technol. 2002, 36, 1202-1211

1202 9 ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 36, NO. 6, 2002 10.1021/es011055j Not subject to U.S. copyright. Publ. 2002 Am. Chem.Soc.

Published on Web 03/13/2002
many compounds of emerging environmental concern, in

streams across the United States. These OWCs are potentially

associated with human, industrial, and agricultural wastewaters and include antibiotics, other prescription drugs,

nonprescription drugs, steroids, reproductive hormones,

personal care products, products of oil use and combustion,

and other extensively used chemicals. The target OWCs were

selected because they are expected to enter the environment

through common wastewater pathways, are used in significant quantities, may have human or environmental health

implications, are representative or potential indicators of

certain classes of compounds or sources, and/or can be

accurately measured in environmental samples using available technologies. Although these 95 OWCs are just a small

subset of compounds being used by society, they represent

a starting point for this investigation examining the transport

of OWCs to water resources of the United States.

This paper describes the analytical results available from

139 streams sampled during 1999-2000 (Figure 1). The results

are intended to determine if OWCs are entering U.S. streams

and to estimate the extent of their co-occurrence in susceptible waters. In addition, this study provides a focal point

for the development and testing of new laboratory methods

for measuring OWCs in environmental samples at trace levels,

an interpretive context for future assessments of OWCs, and

a means for establishing research priorities and future

monitoring strategies. More complete interpretations, including an evaluation of the role of potential sources of

contamination, will follow in subsequent papers.

Site Selection and Sampling

Little data were available on the occurrence of most of the

targeted OWCs in U.S. streams at the onset of this investigation. Therefore, the selection of sampling sites primarily

focused on areas considered susceptible to contamination

from human, industrial, and agricultural wastewater. The

139 stream sites sampled during 1999-2000 (Figure 1)

represent a wide range of geography, hydrogeology, land

use, climate, and basin size. Specific information on the

individual sampling sites is provided elsewhere (20).

All samples were collected by U.S. Geological Survey

personnel using consistent protocols and procedures designed to obtain a sample representative of the streamwaters

using standard depth and width integrating techniques (21).

At each site, a composite water sample was collected from

about 4-6 vertical profiles which was split into appropriate

containers for shipment to the participating laboratories.

For those bottles requiring filtration, water was passed

through a 0.7 μm, baked, glass-fiber filter in the field where

possible, or else filtration was conducted in the laboratory.

Water samples for each chemical analysis were stored in

precleaned-amber, glass bottles and collected in duplicate.

The duplicate samples were used for backup purposes (in

case of breakage of the primary sample) and for laboratory

replicates. Following collection, samples were immediately

chilled and sent to the laboratory. To minimize contamination

of samples, use of personal care items (i.e. insect repellents,

colognes, perfumes), caffeinated products, and tobacco were

discouraged during sample collection and processing.

Each stream site was sampled once during the 1999-

2000 study period. Samples collected in 1999 were analyzed

for a subset of the OWCs based on the watershed land-use

characteristics. Samples collected in 2000 were analyzed for

the complete suite of OWCs. The analytical results for each

stream sample are available elsewhere (20).

Analytical Methods

To determine the environmental extent of 95 OWCs (Table

1) in susceptible streams, five separate analytical methods

were used. Each method was developed independently in

different laboratories, with somewhat different data objectives, such as identifying hormones versus identifying

antibiotics. As a result of these differing objectives, varying

approaches were used in the development of the five

analytical methods. For example, select methods (Methods

1-3 below) used filtered water for solid-phase extraction

(SPE) with liquid chromatography/mass spectrometry positive-ion electrospray (LC/MS-ESI(+)) analysis, while others

(Methods 4 and 5 below) used whole-water continuous

liquid-liquid extraction (CLLE) with capillary gas chromatography/mass spectrometry (GC/MS) analysis.

All methods use selected ion monitoring (SIM) for

improved sensitivity, thus, only the target compounds were

reported with no attempt to report data for nontarget

FIGURE 1. Location of 139 stream sampling sites.

VOL. 36, NO. 6, 2002 / ENVIRONMENTAL SCIENCE & TECHNOLOGY 9 1203
TABLE 1. Summary of Analytical Results of Streams Sampled for 95 Organic Wastewater Contaminantsi

chemical (method) CASRN N

RL

(μg/L)

freq

(%) max(μg/L)

med

(μg/L) use

MCL or

HAL (23)

(μg/L)

lowest LC50 for the

most sensitive

indicator species

(μg/L)/no. of aquatic

studies identified (24)

Veterinary and Human Antibiotics

carbodox (1) 6804-07-5 104 0.10 0 ND ND antibiotic - -/1

chlortetracycline (1) 57-62-5 115 0.05 0 ND ND antibiotic - 88000a/3

chlortetracycline (2) 57-62-5 84 0.10 2.4 0.69 0.42 antibiotic - 88000a/3

ciprofloxacin (1) 85721-33-1 115 0.02 2.6 0.03 0.02 antibiotic - -/0

doxycycline (1) 564-25-0 115 0.1 0 ND ND antibiotic - -/0

enrofloxacin (1) 93106-60-6 115 0.02 0 ND ND antibiotic - 40b/29

erythromycin-H2O (1) 114-07-8 104 0.05 21.5 1.7 0.1 erythromycin

metabolite

- 665000b/35

lincomycin (1) 154-21-2 104 0.05 19.2 0.73 0.06 antibiotic - -/0

norfloxacin (1) 70458-96-7 115 0.02 0.9 0.12 0.12 antibiotic - -/6

oxytetracycline (1) 79-57-2 115 0.1 0 ND ND antibiotic - 102000a/46

oxytetracycline (2) 79-57-2 84 0.10 1.2 0.34 0.34 antibiotic - 102000a/46

roxithromycin (1) 80214-83-1 104 0.03 4.8 0.18 0.05 antibiotic - -/0

sarafloxacin (1) 98105-99-8 115 0.02 0 ND ND antibiotic - -/0

sulfachloropyridazine (2) 80-32-0 84 0.05 0 ND ND antibiotic - -/0

sulfadimethoxine (1) 122-11-2 104 0.05 0 ND ND antibiotic - -/5

sulfadimethoxine (2) 122-11-2 84 0.05 1.2 0.06 0.06 antibiotic - -/5

sulfamerazine (1) 127-79-7 104 0.05 0 ND ND antibiotic - 100000c/17

sulfamerazine (2) 127-79-7 84 0.05 0 ND ND antibiotic - 100000c/17

sulfamethazine (1) 57-68-1 104 0.05 4.8 0.12 0.02 antibiotic - 100000c 17

sulfamethazine (2) 57-68-1 84 0.05 1.2 0.22 0.22 antibiotic - 100000c/17

sulfamethizole (1) 144-82-1 104 0.05 1.0 0.13 0.13 antibiotic - -/0

sulfamethoxazole (1) 723-46-6 104 0.05 12.5 1.9 0.15 antibiotic - -/0

sulfamethoxazole (3) 723-46-6 84 0.023 19.0 0.52 0.066 antibiotic - -/0

sulfathiazole (1) 72-14-0 104 0.10 0 ND ND antibiotic - -/0

sulfathiazole (2) 72-14-0 84 0.05 0 ND ND antibiotic - -/0

tetracycline (1) 60-54-8 115 0.05 0 ND ND antibiotic - 550000b/3

tetracycline (2) 60-54-8 84 0.10 1.2 0.11 0.11 antibiotic - 550000b/3

trimethoprim (1) 738-70-5 104 0.03 12.5 0.71 0.15 antibiotic - 3000c/4

trimethoprim (3) 738-70-5 84 0.014 27.4 0.30 0.013 antibiotic - 3000c/4

tylosin (1) 1401-69-0 104 0.05 13.5 0.28 0.04 antibiotic - -/0

virginiamycin (1) 21411-53-0 104 0.10 0 ND ND antibiotic - -/0

Prescription Drugs

albuterol (salbutamol) (3) 18559-94-9 84 0.029 0 ND ND antiasthmatic - -/0

cimetidine (3) 51481-61-9 84 0.007 9.5 0.58d 0.074d antacid - -/0

codeine (3) 76-57-3 46 0.24 6.5 0.019 0.012 analgesic - -/0

codeine (4) 76-57-3 85 0.1 10.6 1.0d 0.2d analgesic - -/0

dehydronifedipine (3) 67035-22-7 84 0.01 14.3 0.03 0.012 antianginal - -/0

digoxin (3) 20830-75-5 46 0.26 0 NDd NDd cardiac stimulant - 10000000a/24

digoxigenin (3) 1672-46-4 84 0.008 0 ND ND digoxin metabolite - -/0

diltiazem (3) 42399-41-7 84 0.012 13.1 0.049 0.021 antihypertensive - -/0

enalaprilat (3) 76420-72-9 84 0.15 1.2 0.046d 0.046d enalapril maleate

(antihypertensive)

metabolite

- -/0

fluoxetine (3) 54910-89-3 84 0.018 1.2 0.012d 0.012d antidepressant - -/0

gemfibrozil (3) 25812-30-0 84 0.015 3.6 0.79 0.048 antihyperlipidemic - -/0

metformin (3) 657-24-9 84 0.003 4.8 0.15d 0.11d antidiabetic - -/0

paroxetine metabolite (3) - 84 0.26 0 NDd NDd paroxetine

(antidepressant)

metabolite

- -/0

ranitidine (3) 66357-35-5 84 0.01 1.2 0.01d 0.01d antacid - -/0

warfarin (3) 81-81-2 84 0.001 0 ND ND anticoagulant - 16000c/ 33

Nonprescription Drugs

acetaminophen (3) 103-90-2 84 0.009 23.8 10 0.11 antipyretic - 6000a/ 14

caffeine (3) 58-08-2 84 0.014 61.9 6.0 0.081 stimulant - 40000e/ 77

caffeine (4) 58-08-2 85 0.08 70.6 5.7 0.1 stimulant - 40000e/ 77

cotinine (3) 486-56-6 84 0.023 38.1 0.90 0.024 nicotine metabolite - -/0

cotinine (4) 486-56-6 54 0.04 31.5 0.57 0.05 nicotine metabolite - -/0

1,7-dimethylxanthine (3) 611-59-6 84 0.018 28.6 3.1d 0.11d caffeine metabolite - -/0

ibuprofen (3) 15687-27-1 84 0.018 9.5 1.0 0.20 antiinflammatory - -/0

Other Wastewater-Related Compounds

1,4-dichlorobenzene (4) 106-46-7 85 0.03 25.9 4.3 0.09 deodorizer 75 1100c/190

2,6-di-tert-butylphenol (4) 128-39-2 85 0.08 3.5 0.11d 0.06d antioxidant - -/2

2,6-di-tert-butyl-1,4-benzoquinone (4) 719-22-2 85 0.10 9.4 0.46 0.13 antioxidant - -/0

5-methyl-1H-benzotriazole (4) 136-85-6 54 0.10 31.5 2.4 0.39 antiocorrosive - -/0

acetophenone (4) 98-86-2 85 0.15 9.4 0.41 0.15 fragrance - 155000e/21

anthracene (4) 120-12-7 85 0.05 4.7 0.11 0.07 PAH - 5.4e/188

benzo[a]pyrene (4) 50-32-8 85 0.05 9.4 0.24 0.04 PAH 0.2 1.5a/428

3-tert-butyl-4-hydroxy anisole (4) 25013-16-5 85 0.12 2.4 0.2d 0.1d antioxidant - 870c/14

butylated hydroxy toluene (4) 128-37-0 85 0.08 2.4 0.1d 0.1d antioxidant - 1440a/15

bis(2-ethylhexyl) adipate (4) 103-23-1 85 2.0 3.5 10f 3f plasticizer 400 480a/9

bis(2-ethylhexyl) phthalate (4) 117-81-7 85 2.5 10.6 20f 7f plasticizer 6 7500a/309

1204 9 ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 36, NO. 6, 2002
compounds. Target compounds within each method were

selected from the large number of chemical possibilities based

upon usage, toxicity, potential hormonal activity, and

persistence in the environment. Some compounds that fit

the above criteria, however, could not be included (such as

amoxicillin, roxarsone, polybrominated diphenyl ethers)

because they were either incompatible with the corresponding method or reference standards were not available. Positive

identification of a compound required elution within the

expected retention time window. In addition, the sample

spectra and ion abundance ratios were required to match

that of the reference standard compounds. The base-peak

ion was used for quantitation, and, if possible, two qualifier

ions were used for confirmation. After qualitative criteria

were met, compound concentrations were calculated from

5 to 8 point calibration curves (generally from 0.01 to 10.0

μg/L) using internal standard quantitation. Methods 1 and

2 process calibration standards through the extraction

procedure, which generally corrects concentrations for

method losses but not matrix effects. Methods 3-5 do not

TABLE 1. (Continued)

chemical (method) CASRN N

RL

(μg/L)

freq

(%) max(μg/L)

med

(μg/L) use

MCL or

HAL (23)

(μg/L)

lowest LC50 for the

most sensitive

indicator species

(μg/L)/no. of aquatic

studies identified (24)

Other Wastewater-Related Compounds

bisphenol A (4) 80-05-7 85 0.09 41.2 12 0.14 plasticizer - 3600e/26

carbaryl (4) 63-25-2 85 0.06 16.5 0.1d 0.04d insecticide 700 0.4a/1541

cis-chlordane (4) 5103-71-9 85 0.04 4.7 0.1 0.02 insecticide 2 7.4b/28

chlorpyrifos (4) 2921-88-2 85 0.02 15.3 0.31 0.06 insecticide 20 0.1a/1794

diazinon (4) 333-41-5 85 0.03 25.9 0.35 0.07 insecticide 0.6 0.56a/1040

dieldrin (4) 60-57-1 85 0.08 4.7 0.21 0.18 insecticide 0.2 2.6c/1540

diethylphthalate (4) 84-66-2 54 0.25 11.1 0.42 0.2 plasticizer - 12000c/129

ethanol,2-butoxy-phosphate (4) 78-51-3 85 0.2 45.9 6.7 0.51 plasticizer - 10400e/7

fluoranthene (4) 206-44-0 85 0.03 29.4 1.2 0.04 PAH - 74e/216

lindane (4) 58-89-9 85 0.05 5.9 0.11 0.02 insecticide 0.2 30c/1979

methyl parathion (4) 298-00-0 85 0.06 1.2 0.01 0.01 insecticide 2 12a/888

4-methyl phenol (4) 106-44-5 85 0.04 24.7 0.54 0.05 disinfectant - 1400a/74

naphthalene (4) 91-20-3 85 0.02 16.5 0.08 0.02 PAH 20 910c/519

N,N-diethyltoluamide (4) 134-62-3 54 0.04 74.1 1.1 0.06 insect repellant - 71250c/9

4-nonylphenol (4) 251-545-23 85 0.50 50.6 40g 0.8g nonionic detergent

metabolite

- 130e/135

4-nonylphenol monoethoxylate (4) - 85 1.0 45.9 20g 1g nonionic detergent

metabolite

14450a/4

4-nonylphenol diethoxylate (4) - 85 1.1 36.5 9g 1g nonionic detergent

metabolite

- 5500a/6

4-octylphenol monoethoxylate (4) - 85 0.1 43.5 2g 0.2g nonionic detergent

metabolite

- -/0

4-octylphenol diethoxylate (4) - 85 0.2 23.5 1g 0.1g nonionic detergent

metabolite

- -/0

phenanthrene (4) 85-01-8 85 0.06 11.8 0.53 0.04 PAH - 590a/192

phenol (4) 108-95-2 85 0.25 8.2 1.3f 0.7f disinfectant 400 4000c/2085

phthalic anhydride (4) 85-44-9 85 0.25 17.6 1f 0.7f plastic manufacturing - 40400c/5

pyrene (4) 129-00-0 85 0.03 28.2 0.84 0.05 PAH - 90.9a/112

tetrachloroethylene (4) 127-18-4 85 0.03 23.5 0.70d 0.07d solvent, degreaser 5 4680c/147

triclosan (4) 3380-34-5 85 0.05 57.6 2.3 0.14 antimicrobial

disinfectant

- 180e/3

tri(2-chloroethyl) phosphate (4) 115-96-8 85 0.04 57.6 0.54 0.1 fire retardant - 66000b/8

tri(dichlorisopropyl) phosphate (4) 13674-87-8 85 0.1 12.9 0.16 0.1 fire retardant - 3600b/9

triphenyl phosphate (4) 115-86-6 85 0.1 14.1 0.22 0.04 plasticizer - 280c/66

Steroids and Hormones

cis-androsterone (5) 53-41-8 70 0.005 14.3 0.214 0.017 urinary steroid - -/0

cholesterol (4) 57-88-5 85 1.5 55.3 10d 1d plant/animal steroid - -/0

cholesterol (5) 57-88-5 70 0.005 84.3 60h 0.83 plant/animal steroid - -/0

coprostanol (4) 360-68-9 85 0.6 35.3 9.8d 0.70d fecal steroid - -/0

coprostanol (5) 360-68-9 70 0.005 85.7 150h 0.088 fecal steroid - -/0

equilenin (5) 517-09-9 70 0.005 2.8 0.278 0.14 estrogen replacement - -/0

equilin (5) 474-86-2 70 0.005 1.4 0.147 0.147 estrogen replacement - -/0

17r-ethynyl estradiol (5) 57-63-6 70 0.005 15.7 0.831 0.073 ovulation inhibitor - -/22

17r-estradiol (5) 57-91-0 70 0.005 5.7 0.074 0.03 reproductive hormone - -/0

17â-estradiol (4) 50-28-2 85 0.5 10.6 0.2d 0.16d reproductive hormone - -/0

17â-estradiol (5) 50-28-2 70 0.005 10.0 0.093 0.009 reproductive hormone - -/0

estriol (5) 50-27-1 70 0.005 21.4 0.051 0.019 reproductive hormone - -/0

estrone (5) 53-16-7 70 0.005 7.1 0.112 0.027 reproductive hormone - -/11

mestranol (5) 72-33-3 70 0.005 10.0 0.407 0.074 ovulation inhibitor - -/0

19-norethisterone (5) 68-22-4 70 0.005 12.8 0.872 0.048 ovulation inhibitor - -/0

progesterone (5) 57-83-0 70 0.005 4.3 0.199 0.11 reproductive hormone - -/0

stigmastanol (4) 19466-47-8 54 2.0 5.6 4d 2d plant steroid - -/0

testosterone (5) 58-22-0 70 0.005 2.8 0.214 0.116 reproductive hormone - -/4

a Daphnia magna (water flea) - 48 h exposure LC50. b Other species and variable conditions. c Oncorhynchus mykiss (rainbow trout) - 96 h

exposure LC50. d Concentration estimated-average recovery<60%. e Pimephales promelas (fathead minnow)-96 h exposure LC50. f Concentration

estimated - compound routinely detected in laboratory blanks. g Concentration estimated - reference standard prepared from a technical mixture. h Concentration estimated - value greater than highest point on calibration curve. i Compounds suspected of being hormonally active are in bold

(4, 22). CASRN, Chemical Abstracts Service Registry Number; N, number of samples; RL, reporting level; freq, frequency of detection; max,

maximum concentration; med, median detectable concentration; MCL, maximum contaminant level; HAL, health advisory level; LC50, lethal

concentration with 50% mortality; ND, not detected; -, not available; PAH, polycyclic aromatic hydrocarbon.

VOL. 36, NO. 6, 2002 / ENVIRONMENTAL SCIENCE & TECHNOLOGY 9 1205
extract calibration standards, thus the reported concentrations are not corrected for method losses. Reporting levels

(RLs) were determined for each method by either an

evaluation of instrument response, calculation of limit of

detection, or from a previously published procedure (25).

RLs were adjusted based on experience with the compounds

in each method, known interferences, or known recovery

problems.

The following descriptions are intended to provide a brief

overview of the five analytical methods used for this study.

More comprehensive method descriptions are provided

elsewhere (26-28) or will be available in subsequent publications.

Method 1. This method targets 21 antibiotic compounds

(Table 1) in 500-mL filtered water samples using modifications from previously described methods (26, 29). The

antibiotics were extracted and analyzed by tandem SPE and

single quadrapole, LC/MS-ESI(+) using SIM. To prevent the

tetracycline antibiotics from complexing with Ca2+ and Mg2+

ions and residual metals on the SPE cartridges, 0.5 mg of

disodium ethylenediaminetetraacetate (Na2EDTA; C10H14O8-

Na2N2-H2O) was added to each water sample. Sample pH

was adjusted to 3 using concentrated H2SO4. The tandem

SPE included an Oasis Hydrophilic-Lipophilic-Balance

(HLB) cartridge (60 mg) followed by a mixed mode, HLBcation exchange (MCX) cartridge (60 mg) (Waters Inc.,

Milford, MA). The HLB and MCX cartridges were conditioned

with ultrapure H2O, CH3OH, and CH3OH with 5% NH4OH.

The HLB cartridge was attached to the top of the MCX

cartridge, and the sample was passed through the SPE

cartridges using a vacuum extraction manifold. The cartridges

were eluted with CH3OH, and the MCX cartridge was eluted

separately using CH3OH with 5% NH4OH. The eluate was

spiked with 500 ng of 13C6-sulfamethazine (internal standard),

vortexed, and evaporated to 20 μL using N2 and a water bath

of 55° C. Three hundred μL of 20 mM of NH4C2H3OO (pH 5.7)

was added to sample eluate, vortexed, transferred to a glass

chromatography vial, and frozen until analysis. Samples were

extracted as a set of 11 environmental samples, one duplicate

sample, two fortified ultrapure water spikes (check standards),

and two ultrapure water blanks.

Method 2. This method targets eight antibiotic compounds (Table 1) in filtered water samples. Complete details

of this method have been described previously (26). The

antibiotics were extracted and analyzed using SPE and SIM

LC/MS-ESI(+). Samples were prepared for extraction by

adding 13C6-sulfamethazine and meclocycline as surrogate

standards, Na2EDTA, and H2SO4. Target compounds were

extracted using 60-mg HLB cartridges preconditioned with

CH3OH, NHCl, and distilled H2O. Target compounds were

eluted with CH3OH into a test tube containing the internal

standard, simatone. The extracts were then concentrated

under N2 to approximately 50 μL, and mobile phase A (10

mM NH4H2O2 in 90/10 water/CH3OH with 0.3% CH2O2) was

added. The resulting solutions were transferred to amber

autosampler vials to prevent photodegradation of tetracyclines (30). Mobile phase conditions are described in detail

elsewhere (26).

For each compound, the proton adduct of the molecular

ion (M + H)+ and at least one confirming ion were acquired

using LC/MS-ESI(+). All mass spectral conditions are described in detail elsewhere (26). Quantitation was based on

the ratio of the base peak ion (M + H)+ of the analyte to the

base peak of the internal standard. Standard addition was

used for quantitation where each sample was analyzed with

and without the addition of a 0.5 μg/L spike to correct for

suppression of the electrospray signal.

Method 3. This method targets 21 human prescription

and nonprescription drugs and their select metabolites (Table

1) in filtered water samples. Compounds were extracted from

1 L water samples using SPE cartridges that contain 0.5 g of

HLB (flow rate of 15 mL/min). After extraction, the adsorbed

compounds were eluted with CH3OH followed by CH3OH

acidified with C2HCl3O2. The two fractions were reduced

under N2 to near dryness and then combined and brought

to a final volume of 1 mL in 10% C2H3N:90% H2O buffered

with NH4H2O2/CH2O2.

Compounds were separated and measured by highperformance liquid chromatography (HPLC) using a polar

(neutral silanol) reverse-phase octylsilane (C8) HPLC column

(Metasil Basic 3 μm, 150×2.0 mm; Metachem Technologies).

The compounds were eluted with a binary gradient of mobile

phase A (aqueous NH4H2O2/CH2O2 buffer; 10 mM, pH 3.7)

and mobile phase B (100% C2H3N).

Method 4. This method (27, 28) targets 46 OWCs (Table

1) in unfiltered water. One-liter whole-water samples were

extracted using CLLE with CH2Cl2. Distilled solvent was

recycled through a microdroplet dispersing frit to improve

extraction efficiency. Samples were extracted for 3 h at

ambient pH and for an additional 3 h at pH 2. The extract

was concentrated under N2 to 1 mL and analyzed by capillarycolumn GC/MS. Available standards for the 4-nonylphenol

compounds were composed of multiple isomers, and thus,

laboratory standards for these compounds as well as octylphenol ethoxylates were prepared from technical mixtures.

Method 5.This method (28) targets 14 steroid compounds

including several biogenic and synthetic reproductive hormones (Table 1). The CLLE extracts from the previously

analyzed samples of Method 4 were derivatized and reanalyzed. Analysis of steroid and hormone compounds by GC/

MS is enhanced by derivatization to deactivate the hydroxyl

and keto functional groups. The technique used in this study

is the formation of trimethylsilyl (TMS) ethers of the hydroxyl

groups and oximes of the keto groups. Samples were stored

in a silanizing reagent to prevent hydrolysis of the derivatives

back to the free compound. Surrogate standards (d4estradiol

and d7cholesterol) were added to the samples prior to

derivatization to evaluate method performance. After derivatization, the samples were analyzed by GC/MS.

Quality Assurance Protocol. At least one fortified laboratory spike and one laboratory blank was analyzed with each

set of 10-16 environmental samples. Most methods had

surrogate compounds added to samples prior to extraction

to monitor method performance. A summary of recoveries

for target compounds and surrogate compounds in environmental samples (Table 2) indicates the general proficiency

of the methods. The RL (Table 1) is equivalent to the lowest

concentration standard that could be reliably quantitated.

The compound concentrations reported below the RL or the

lowest calibration standard were estimated as indicated in

Figure 2. The concentration of compounds with <60%

recovery, routinely detected in laboratory blanks, or prepared

with technical grade mixtures, was also considered estimated

(Table 1).

The laboratory blanks were used to assess potential sample

contamination. Blank contamination was not subtracted from

environmental results. However, environmental concentrations within twice the values observed in the set blank were

reported as less than the RL.

A field quality assurance protocol was used to determine

the effect, if any, of field equipment and procedures on the

concentrations of OWCs in water samples. Field blanks, made

from laboratory-grade organic free water, were submitted

for about 5% of the sites and analyzed for all of the 95 OWCs.

Field blanks were subject to the same sample processing,

handling, and equipment as the stream samples. To date,

one field blank had a detection of coprostanol and testosterone, one field blank had a detection of naphthalene

and tri(dichlorisopropyl)phosphate, and one field blank had

1206 9 ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 36, NO. 6, 2002
a detection of naphthalene, 4-nonylphenol, phenol, 4-tertoctylphenol monoethoxylate, and ethanol,2-butoxy-phosphate. Most of these detections were near their respective

RLs verifying the general effectiveness of the sampling

protocols used for this study. In addition all field blanks had

low level concentrations of cholesterol being measured using

Method 5 (median concentration ) 0.09 μg/L) documenting

its ubiquitous nature in the environment. Cholesterol

concentrations from 0.005 to 0.18 μg/L obtained through

Method 5 were set to less than the RL.

Compounds that were measured by more than one

analytical method (Table 1; Figure 3) also were used to

evaluate the results for this study. The presence or absence

of these compounds were confirmed in 100% of the determinations for sulfamerazine, and sulfathiazole; 98.8% for

oxytetracycline, sulfadimethoxine, sulfamethazine, and tetracycline; 98.6% for cholesterol and coprostanol; 97.6% for

chlortetracyline; 95.7% for 17â-estradiol; 94.4% for cotinine;

94.0% for trimethoprim; 89.1% for sulfamethoxazole; 86.4%

for codeine; and 83.3% for caffeine. The comparisons for

codeine, caffeine, and cotinine may have been affected by

the differing extractions (SPE versus CLLE) as well as differing

types of sample (filtered versus whole water).

An interlaboratory comparison of Methods 1 and 3 was

conducted using two reagent water blanks and 24 reagent

water spikes prepared at concentrations ranging from 0.5 to

1.1 μg/L for two frequently detected antibiotics (sulfamethoxazole and trimethoprim). The results demonstrated that both

methods are accurately confirming the presence of sulfamethoxazole and trimethoprim in water, with the measured

concentrations being within a factor of 3 or better of the

actual concentrations for these compounds. No false positives

or false negatives occurred for this experiment.

TABLE 2. Summary of Quality Assurance/Quality Control

Results for Target and Surrogate Compoundsb

compound

spike concn

(μg/L)

mean

% recovery % RSD

Method 1

target compounds 1.0 99.0 12.1

Method 2

target compounds 1.0 97.5 12.2

13C6-sulfamethazine 1.0 80.0 20.0

meclocycline 1.0 80.0 20.0

Method 3

target compounds 0.5 85.1 11.6

C13-phenacetin 1.0 96.8 14.0

Method 4

target compounds 1.0 81.0 11.0

d21-BHT 2.0 63.0 25.0

n-nonylphenol 2.0 83.0 20.0

Method 5

target compounds NA NA NA

d4-estradiola 0.047 128.8 42.0

d3-testosteronea 0.051 148.5 47.3

d7-cholesterola 0.053 116.9 55.9

a Surrogate standard added after CCLE extraction but prior to

derivitization. b RSD, relative standard deviation; NA, not currently

available.

FIGURE 2. Measured concentrations for the 30 most frequently detected organic wastewater contaminants. Boxplots show concentration

distribution truncated at the reporting level. Estimated values below the reporting level are shown. Estimated maximum values for

coprostanol and cholesterol obtained from Method 5 (Table 1) are not shown. The analytical method number is provided (in parentheses)

at the end of each compound name. An explanation of a boxplot is provided in Figure 3.

VOL. 36, NO. 6, 2002 / ENVIRONMENTAL SCIENCE & TECHNOLOGY 9 1207
Results and Discussion

One or more OWCs were found in 80% of the 139 streams

sampled for this study. The high overall frequency of detection

for the OWCs is likely influenced by the design of this study,

which placed a focus on stream sites that were generally

considered susceptible to contamination (i.e. downstream

of intense urbanization and livestock production). In addition, select OWCs (such as cholesterol) can also be derived

from nonanthropogenic sources. Furthermore, some of the

OWCs were selected because previous research (28) identified

them as prevalent in the environment. Thus, the results of

this study should not be considered representative of all

streams in the United States. A previous investigation of

streams downstream of German municipal sewage treatment

plants also found a high occurrence of OWCs (31).

A large number of OWCs (82 out of 95) were detected at

least once during this study (Table 1). Only eight antibiotics

and five other prescription drugs were not detected in the

samples analyzed (Table 1). Measured concentrations were

generally low (median detectable concentrations generally

<1 μg/L, Table 1), with few compounds exceeding drinkingwater guidelines, health advisories, or aquatic-life criteria

(Table 1). The concentration of benzo[a]pyrene exceeded its

maximum contaminant level (MCL) of 0.2 μg/L at one site

and bis(2-ethylhexyl)phthalate concentrations exceeded its

MCL of 6.0 μg/L at five sites. In addition, aquatic-life criteria

were exceeded for chlorpyrifos (Table 1) at a single site.

However, many of the 95 OWCs do not have such guidelines

or criteria determined (Table 1). In fact, much is yet to be

known about the potential toxicological effects of many of

the OWCs under investigation (1). For many OWCs, acute

effects to aquatic biota appear limited because of the low

concentrations generally occurring in the environment (24,

32-34). More subtle, chronic effects from low-level environmental exposure to select OWCs appear to be of much

greater concern (1). Such chronic effects have been documented in the literature (34-38). In addition, because

antibiotics are specifically designed to reduce bacterial

populations in animals, even low-level concentrations in the

environment could increase the rate at which pathogenic

bacteria develop resistance to these compounds (15-17,

39).

The 30 most frequently detected compounds represent

a wide variety of uses and origins including residential,

industrial, and agricultural sources (Figure 2, Table 1). Only

about 5% of the concentrations for these compounds

exceeded 1 μg/L. Over 60% of these higher concentrations

were derived from cholesterol and three detergent metabolites (4-nonyphenol, 4-nonylphenol monoethoxylate, and

4-nonylphenol diethoxylate). The frequent detection of

cotinine, 1,7-dimethylxanthine, erythromycin-H2O, and other

OWC metabolites demonstrate the importance of obtaining

data on degradates to fully understand the fate and transport

of OWCs in the hydrologic system. In addition, their presence

suggests that to accurately determine the overall effect on

human and environmental health (such as pathogen resistance and genotoxicity) from OWCs, their degradates should

also be considered. The presence of the parent compound

and/or their select metabolites in water resources has

previously been documented for OWCs (40, 41) as well as

other classes of chemicals such as pesticides (42, 43).

Many of the most frequently detected compounds (Figure

2) were measured in unfiltered samples using Method 4.

Thus, their frequencies of detection may be somewhat higher

because concentrations being measured include both the

dissolved and particulate phases, whereas concentrations

measured by Methods 1-3 include just the dissolved phase.

For example, about 90% of the coprostanol discharged from

FIGURE 3. Comparison of concentrations of select compounds that were measured using two different methods with significantly different

reporting levels. Boxplots show concentration distribution truncated at the reporting level. Estimated values below the reporting level

are shown. Estimated maximum values for chloesterol and coprostanol obtained from Method 5 (Table 1) are not shown. The analytical

method number is provided (in parentheses) at the end of each compound name.

1208 9 ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 36, NO. 6, 2002
sewage effluents has been shown to be associated with

particulate matter (44). Thus, the concentration and frequency of detection for select compounds would likely have

been reduced if sample filtration had taken place.

Variations in RL also influence the frequency of OWC

detection (Figure 2). For example, the detection of 4-nonylphenol would likely have been much greater if an order of

magnitude lower RL (similar to other OWCs) could have been

achieved. The effect of RL on frequencies of detection is more

clearly demonstrated by comparison of concentrations of

select compounds that were measured using multiple

analytical methods (Figure 3). As expected, the frequency of

detection for a given compound was higher with the lower

RL. The only exception being caffeine, where filtration of

Method 3 may have reduced caffeine concentrations compared to that of the unfiltered Method 4. Figures 2 and 3 also

demonstrate the importance of estimated values (45) below

the RL. Clearly the numerous estimated concentrations

illustrate that the current RLs are not low enough to accurately

characterize the total range of OWC concentrations in the

stream samples and that the frequencies of detection for this

study are conservative.

To obtain a broader view of the results for this study, the

95 OWCs were divided into 15 groups based on their general

uses and/or origins. The data show two environmental

determinations: frequency of detection (Figure 4A) and

percent of total measured concentration (Figure 4B) for each

group of compounds. These two views show a vastly different

representation of the data. In relation to frequency of

detection, there were a number of groups that were frequently

detected, with seven of the 15 groups being found in over

60% of the stream samples (Figure 4A). However, three groups

(detergent metabolites, plasticizers, and steroids) contributed

almost 80% of the total measured concentration (Figure 4B).

For those groups of compounds that have received recent

public attentionsnamely antibiotics, nonprescription drugs,

other prescription drugs, and reproductive hormones (1, 2,

10)snonprescription drugs were found with greatest frequency (Figure 4A). Antibiotics, other prescription drugs,

and reproductive hormones were found at relatively similar

frequencies of detection. The greater frequency of detection

for nonprescription drugs may be at least partially derived

from their suspected greater annual use compared to these

other groups of compounds. When toxicity is considered,

measured concentrations of reproductive hormones may

have greater implications for health of aquatic organisms

than measured concentrations of nonprescription drugs.

Previous research has shown that even low-level exposure

(<0.001 μg/L) to select hormones can illicit deleterious effects

in aquatic species (7, 46, 47).

FIGURE 4. Frequency of detection of organic wastewater contaminants by general use category (4A), and percent of total measured

concentration of organic wastewater contaminants by general use category (4B). Number of compounds in each category shown above

bar.

VOL. 36, NO. 6, 2002 / ENVIRONMENTAL SCIENCE & TECHNOLOGY 9 1209
Mixtures of various OWCs were prevalent during this

study, with most (75%) of the streams sampled having more

than one OWC identified. In fact, a median of seven OWCs

were detected in these streams, with as many as 38

compounds found in a given streamwater sample (Figure 5).

Because only a subset of the 95 OWCs were measured at

most sites collected during the first year of study, it is

suspected that the median number of OWCs for this study

is likely underestimated. Although individual compounds

were generally detected at low-levels, total concentrations

of the OWCs commonly exceeded 1 μg/L (Figure 5). In

addition, 33 of the 95 target OWCs are known or suspected

to exhibit at least weak hormonal activity with the potential

to disrupt normal endocrine function (4, 7, 8, 10, 12, 22, 36,

37, 48-50), all of which were detected in at least one stream

sample during this study (Table 1). The maximum total

concentration of hormonally active compounds was 57.3 μg/

L. Aquatic species exposed to estrogenic compounds have

been shown to alter normal hormonal levels (7, 48, 51). Thus,

the results of this study suggest that additional research on

the toxicity of the target compounds should include not only

the individual OWCs but also mixtures of these compounds.

The prevalence of multiple compounds in water resources

has been previously documented for other contaminants

(52, 53). In addition, research has shown that select chemical

combinations can exhibit additive or synergistic toxic effects

(54-56), with even compounds of different modes of action

having interactive toxicological effects (57).

The results of this study document that detectable

quantities of OWCs occur in U.S. streams at the national

scale. This implies that many such compounds survive

wastewater treatment (1, 6, 58) and biodegradation (59).

Future research will be needed to identify those factors (i.e.

high use and chemical persistence) that are most important

in determining the occurrence and concentration of OWCs

in water resources.

Although previous research has also shown that antibiotics

(60), other prescription drugs (1, 2, 19, 61-63), and nonprescription drugs (1, 40, 62, 64) can be present in streams,

this study is the first to examine their occurrence in a wide

variety of hydrogeologic, climatic, and land-use settings

across the United States. Much is yet to be learned pertaining

to the effects (particularly those chronic in nature) on

humans, plants, and animals exposed to low-level concentrations of pharmaceuticals and other OWCs. Furthermore,

little is known about the potential interactive effects (synergistic or antagonistic toxicity) that may occur from complex

mixtures of these compounds in the environment. Finally,

additional research also needs to be focused on those OWCs

not frequently detected in this stream sampling. Select OWCs

may be hydrophobic and thus may be more likely to be

present in stream sediments than in streamwater (65, 66).

For example, the low frequency of detection for the tetracycline (chlortetracycline, doxycycline, oxytetracycline, tetracycline) and quinolone (ciprofloxacin, enrofloxacin, norfloxacin, sarafloxacin) antibiotics is not unexpected given

their apparent affinity for sorption to sediment (66). In

addition, select OWCs may be degrading into new, more

persistent compounds that could be transported into the

environment instead of (or in addition to) their associated

parent compound.

Acknowledgments

The authors wish to acknowledge the USGS scientists and

field technicians who provided essential assistance to this

project by identifying candidate stream sites across the United

States and in collecting and processing stream samples. In

addition, the authors thank Michele Lindsey, Jeff Cahill, and

Greg Brown for their important contributions to developing

the analytical methods being used. The authors also acknowledge Steffanie Keefe for her efforts in compiling the

existing ecotoxicological data, Jessica Hopple for her assistance in generating select figures for this paper, and Kymm

Barnes for her assistance in compiling the water-quality data

for this study. This project was supported by the U.S.

Geological Survey, Toxic Substances Hydrology Program. The

use of trade, firm, or brand names in this paper is for

identification purposes only and does not constitute endorsement by the U.S. Geological Survey.

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ES011055J

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