Transport of chemical and microbial compounds from known wastewater discharges: potential for use as indicators of human fecal contamination.
ABSTRACT The quality of drinking and recreational water is currently (2005) determined using indicator bacteria. However, the culture tests used to analyze forthese bacteria require a long time to complete and do not discriminate between human and animal fecal material sources. One complementary approach is to use chemicals found in human wastewater, which would have the advantages of (1) potentially shorter analysis times than the bacterial culture tests and (2) being selected for human-source specificity. At 10 locations, water samples were collected upstream and at two successive points downstream from a wastewaster treatment plant (WWTP); a treated effluent sample was also collected at each WWTP. This sampling plan was used to determine the persistence of a chemically diverse suite of emerging contaminants in streams. Samples were also collected at two reference locations assumed to have minimal human impacts. Of the 110 chemical analytes investigated in this project, 78 were detected at least once. The number of compounds in a given sample ranged from 3 at a reference location to 50 in a WWTP effluent sample. The total analyte load at each location varied from 0.018 microg/L at the reference location to 97.7 microg/L in a separate WWTP effluent sample. Although most of the compound concentrations were in the range of 0.01-1.0 microg/L, in some samples, individual concentrations were in the range of 5-38 microg/L. The concentrations of the majority of the chemicals present in the samples generally followed the expected trend: they were either nonexistent or at trace levels in the upstream samples, had their maximum concentrations in the WWTP effluent samples, and then declined in the two downstream samples. This research suggests that selected chemicals are useful as tracers of human wastewater discharge.
- [Show abstract] [Hide abstract]
ABSTRACT: The occurrence, bioaccumulation and risk assessment of lipophilic pharmaceutically active compounds (LPhACs), such as antibiotics (roxithromycin, erythromycin and ketoconazole), anti-inflammatories (ibuprofen and diclofenac), β-blockers (propranolol), antiepileptics (carbamazepine) and steroid hormones (17α-ethinylestradiol), were investigated in the downstream rivers of sewage treatment plants in Nanjing, China. The results indicate that these LPhACs were widely detected in the surface water and fish samples, with the mean concentrations of the total LPhACs (ΣLPhACs) being in the range of 15.4 and 384.5 ng/L and 3.0 and 128.4 ng/g (wet weight), respectively. The bioaccumulation of the ΣLPhACs in wild fish tissues was generally in the order the liver > brain > gill > muscle. Among the target LPhACs, however, an interspecies difference in tissue distribution was evident for erythromycin. The bioaccumulation factors of LPhACs in the liver and brain, the two major targeted storage sites for toxicants, exhibited an obvious negative correlation with the aquatic concentrations (P < 0.05). Finally, risk quotients posed by pharmaceuticals were assessed by comprehensive and comparative methods for different aquatic organisms (algae, daphnids and fish). The overall relative order of susceptibility was estimated to be algae > daphnids > fish. However, the results indicate that diclofenac, ibuprofen and 17α-ethinylestradiol each posed chronic risks for high trophic level organisms (fish). In all of the risk assessments, erythromycin was found to be the most harmful for the most sensitive algae group. In this work, however, the total BAF and toxicological interactions of pharmaceuticals were not performed due to the lack of metabolite information and combined toxicity data, which represents a major hindrance to the effective risk assessment of pharmaceuticals.Science of The Total Environment 04/2015; 511. · 3.16 Impact Factor
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ABSTRACT: Fecal contamination of source waters is an important issue to the drinking water industry. Improper disposal of animal waste, leaky septic tanks, storm runoff, and wildlife can all be responsible for spreading enteric pathogens into source waters. As a result, methods that can pinpoint fecal pollution sources in natural waters are needed to assist in the development and evaluation of adequate management practices targeting pollution control. In the last decade, several methods have been developed to identify fecal sources, collectively known as microbial source tracking (MST) methods. Early studies focused on the use of methods that rely on generating library dependent databases. More recently library independent PCR-based approaches have become more popular among MST practitioners as they do not rely on the development of large culture-based databases. One potential concern associated with the use of library independent approaches relates to the development of host-specific assays using sequencing information from genes not involved in host-microbial interactions. To address this issue, our research group has applied a novel method called genome fragment enrichment (GFE) to select for genomic regions that differ between different fecal metagenomes. We have shown that the vast majority of the selected fragments are indeed specific to the fecal community in question suggesting that this is an efficient way of enriching for community specific DNA regions. Sequences from the enriched fragments were used to develop host-specific PCR assays. Thus far, we have successfully developed several assays specific to human, cow, and chicken fecal communities. Additionally, several assays are capable of detecting multiple avian species, further suggesting that similar gut environments can select for similar host-specific populations. The latter finding is relevant as it shows that is possible to develop assays targeting multiple species. Signals from metagenomic-based assays were detected in water samples demonstrating their potential as source tracking tools. A brief summary of the history and limitations of current MST tools and the discussion of results with metagenomic markers will be the main topics of this manuscript. The need for a risk assessment tool-box that includes assays targeting indicators, source identifiers and pathogens will also be discussed.Proceedings of the Water Environment Federation. 01/2007; 2007(1):646-661.
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ABSTRACT: Dissipation of veterinary antimicrobials is known to occur during aerated windrow composting of beef cattle manure. However, it is unclear if a similar dissipation occurs during stockpiling. Chlortetracycline, tylosin, and sulfamethazine are three of the most commonly used veterinary antimicrobials in beef cattle production in western Canada. Their dissipation in stockpiled manure was investigated over 140 d during winter in Alberta, Canada. Beef cattle housed in pens were administered 44 mg of chlortetracycline kg-1 feed (dry weight), 44 mg of chlortetracycline + 44 mg sulfamethazine kg-1 feed, 11 mg of tylosin kg-1 feed, or feed without antimicrobials (control). Manure samples were extracted using pressurized liquid extraction, and the extracts were analyzed for chlortetracycline, sulfamethazine, and tylosin by LC-MS-MS. Dissipation of all three antimicrobials in the manure was explained by exponential decay kinetics. Times for 50% dissipation (DT50) were 1.8 Â± 0.1 d for chlortetracycline alone or 6.0 Â± 0.8 d when mixed with sulfamethazine, 20.8 Â± 3.8 d for sulfamethazine, and 4.7 Â± 1.2 d for tylosin. After 77 d, <1% of initial chlortetracycline and <2% of sulfamethazine remained. Tylosin residues were more variable, decreasing to approximately 12% of initial levels after 28 d, with 20% present after 77 d and 13% after 140 d. Temperatures within stockpiles reached maximum values within 6 d of establishment and varied with location (bottom, 62.5Â°C; middle, 63.8Â°C; and top, 42.9Â°C). Antimicrobials in the manure did not inhibit microbial activity, as indicated by temperature and mass losses of carbon (C) and nitrogen (N). The C/N ratio in the manure decreased over the stockpiling period, indicating decomposition of manure to a more stable state. Dissipation of excreted residues with DT50 values 1.8 to 20.8 d showed that stockpiling can be as effective as windrow composting in mitigating the transfer of these three veterinary antimicrobials into the environment during land application of processed manure.Journal of Environmental Quality 05/2014; 43(3):1061-1070. · 2.35 Impact Factor
US Geological Survey
USGS Staff – Published Research
University of Nebraska - LincolnYear
Transport of Chemical and Microbial
Compounds from Known Wastewater
Discharges: Potential for Use as
Indicators of Human Fecal
∗U.S. Environmental Protection Agency
†U.S. Geological Survey
‡U.S. Geological Survey
∗∗U.S. Geological Survey
††U.S. Geological Survey
‡‡U.S. Geological Survey
§U.S. Geological Survey
¶U.S. Environmental Protection Agency
This paper is posted at DigitalCommons@University of Nebraska - Lincoln.
Transport of Chemical and Microbial
Compounds from Known
Wastewater Discharges: Potential
for Use as Indicators of Human
S U S A N T . G L A S S M E Y E R *
U.S. Environmental Protection Agency, Office of Research and
Development, National Exposure Research Laboratory,
26 West Martin Luther King Drive, MS 564,
Cincinnati, Ohio 45268
E D W A R D T . F U R L O N G
U.S. Geological Survey, National Water Quality Laboratory,
P.O. Box 25046, MS 407, Denver Federal Center, Building 95,
Denver, Colorado 80225
D A N A W . K O L P I N
U.S. Geological Survey, 400 S. Clinton Street, Room 269,
Federal Building, Iowa City, Iowa 52244
J E F F E R Y D . C A H I L L ,
S T E V E N D . Z A U G G , A N D
S T E P H E N L . W E R N E R
U.S. Geological Survey, National Water Quality Laboratory,
P.O. Box 25046, MS 407, Denver Federal Center, Building 95,
Denver, Colorado 80225
M I C H A E L T . M E Y E R
U.S. Geological Survey, Organic Geochemistry Research
Laboratory, 4821 Quail Crest Place, Lawrence, Kansas 66049
D A V I D D . K R Y A K
U.S. Environmental Protection Agency, Office of Research and
Development, National Exposure Research Laboratory,
D305-01, Research Triangle Park, North Carolina 27711
The quality of drinking and recreational water is currently
(2005) determined using indicator bacteria. However, the
time to complete and do not discriminate between
approach is to use chemicals found in human wastewater,
which would have the advantages of (1) potentially
shorter analysis times than the bacterial culture tests and
(2) being selected for human-source specificity. At 10
locations, water samples were collected upstream and at
two successive points downstream from a wastewaster
treatment plant (WWTP); a treated effluent sample was also
collected at each WWTP. This sampling plan was used
to determine the persistence of a chemically diverse suite
of emerging contaminants in streams. Samples were
also collected at two reference locations assumed to have
minimal human impacts. Of the 110 chemical analytes
investigated in this project, 78 were detected at least once.
The number of compounds in a given sample ranged
from 3 at a reference location to 50 in a WWTP effluent
sample. The total analyte load at each location varied from
0.018 µg/L at the reference location to 97.7 µg/L in a
separate WWTP effluent sample. Although most of the
compound concentrations were in the range of 0.01-1.0 µg/
L, in some samples, individual concentrations were in
the range of 5-38 µg/L. The concentrations of the majority
of the chemicals present in the samples generally
followed the expected trend: they were either nonexistent
or at trace levels in the upstream samples, had their
maximum concentrations in the WWTP effluent samples,
and then declined in the two downstream samples.
This research suggests that selected chemicals are useful
as tracers of human wastewater discharge.
To protect public health, we need to monitor drinking and
recreational water bodies to ensure that pathogens are not
present. This objective, however, is not a straightforward
task. Because of the large number of potential pathogens,
indicator species are monitored when analyzing water
samples for microorganisms of public health concern. The
fact that some pathogenic organisms cannot be cultured
makes direct analysis impractical. Ideally, indicator species
concentrations so that they will not be difficult to detect;
however, they should not grow and multiply in the aquatic
environment. To provide a conservative level of protection,
and resistant to disinfectant stressors than the pathogens
that they trace and that are easy to detect and identify (1, 2).
to pathogens from anthropogenic waste.
Currently in the United States, the total coliform test is
required for screening drinking water samples for potential
pathogen contamination (3). For recreational water, fecal
coliforms have been the indicator of choice since the late
Protection Agency (USEPA) produced additional guidance
of fecal coliform would provide improved public health
protection because these organisms have shown strong
relations to gastroenteric illnesses during epidemiological
studies (5-7). Methods for these two indicators were
promulgated in 2003 (8, 9).
In their century of use, microbial indicators have been
useful in protecting human health, but their disadvantages
biological assays require 18-48 h for the microorganisms to
grow and be enumerated. In the time that it takes to go from
sample collection to a positive test result, individuals can
water. New microbial techniques, such as polymerase chain
reaction (PCR), may reduce the time required to determine
if pathogens are present, but at this time, these methods are
not sufficiently robust to be practical for widespread imple-
microbial indicators also lack specificity; it is impossible to
use these indicators to discriminate between human or
crucial to public health decision making. For example, if a
watershed that tests positive for a pathogenic indicator
contains a WWTP and a confined animal feeding operation,
determining which operation (if either) is responsible for
* Correspondingauthorphone: 513-569-7526;fax: 513-569-7757;
Environ. Sci. Technol. 2005, 39, 5157-5169
10.1021/es048120k CCC: $30.25
Published on Web 06/11/2005
2005 American Chemical Society VOL. 39, NO. 14, 2005 / ENVIRONMENTAL SCIENCE & TECHNOLOGY95157
the contamination will save the other from making un-
necessary and potentially costly “corrections” to their opera-
Recently, research has begun to determine the ap-
plicability of using chemical indicators of human fecal
contamination to identify human sewage contamination in
water bodies (15-36). Chemical indicator tests have an
advantage over the current microbial tests because the time
required for sample preparation and analysis can be sub-
and visualization of the colonies. Chemical indicators of
human fecal contamination fall into several classes: those
that are produced by humans, those that pass through
humans, and those that are associated with the black water
(sewage-contaminated) waste system.
The fecal sterol coprostanol was first suggested as an
human gut (38). The rate of conversion of cholesterol to
coprostanol is diet-dependent, but North Americans eating
This conversion can be quantified by calculating the co-
prostanol-to-cholesterol ratio; this ratio has been found to
range from 0.3 to greater than 15 in human fecal samples
(39). In herbivores, the primary fecal sterol is 24-ethyl-
cholestanol (38). Because the sterol composition in human
wastes differs from those of other animals, the sterol
composition provides the potential for discriminating be-
tween sources (31, 40, 41). Coprostanol and the other fecal
sterols have been detected in surface-water (16, 24-28, 31,
40, 41) and sediment samples (44).
Other synthetic and natural organic compounds that are
consumed and excreted by humans and domestic animals
can be used to trace fecal sources. The chemical that has
received the most interest as a sewage tracer is caffeine (18,
pharmaceuticals (15, 22, 30, 36, 42, 48-57), also have the
potential to serve as tracers of human waste.
In most of North America, black and gray wastewaters
compounds can also be exploited as indicators. Studies in
England have shown that 16% of the volume of household
waste comes from washing machines (58). The components
of laundry detergents, surfactants (42, 59, 60), fluorescent
whitening agents (23, 26, 61-63), and fragrances such as
musks (17, 35, 52, 64-67), have all been found in aquatic
environments and may be useful as tracers of human waste.
To date, there has been no study that systematically
human wastewater. This paper describes the results of
research by the United States Geological Survey (USGS) and
indicators of human fecal contamination. The results are
intended to determine which wastewater compounds are
commonly found downstream from WWTPs and provide
insight on their environmental persistence, the initial phase
in determining if these compounds are useful chemical
indicators of human fecal contamination. Because organic
chlorination (71), the effluents of WWTPs, rather than their
raw influents, were targeted in this study because we were
interested in behavior following discharge, rather than
reductions during treatment. It should be noted that this
study was designed to explore the correlation between the
that are presumably present within the waste. Traditional
microbial indicator data were collected as part of this study
by using these two complementary data types together.
Site Selection and Sampling. This study focused on 10
WWTPs across the United States (Figure 1). Site selection
was primarily based on the results of previous research
activities (42, 52). Most of the sample sets consisted of one
upstream, one effluent, and two downstream samples (DS1
) sites proximal to WWTP discharge and DS2 ) sites further
FIGURE 1. Sample collection locations. Diamonds indicate wastewaster treatment plants; circles designate the reference locations.
51589ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 39, NO. 14, 2005
of 40 sampling sites: 9 upstream samples (one site had no
upstream sampling point), 11 WWTP effluent samples (one
site had two WWTP discharge points), and 20 downstream
samples. The 10 locations represent a variety of climatic
conditions, populations served, stream sizes, and treatment
practices (Table 1). The distances from the treatment plants
to the upstream and downstream locations vary because of
sampling accessibility. The discharge from the WWTPs
contributed between 10 and 95% of the streamflow at the
DS1 site (Table 1). The samples from the Arizona location
are unique in that the stream is composed entirely of
from the channel immediately downstream from a waste-
water-treatment plant. For all of the data interpretation, the
and no upstream sample.
wastewater. These samples were not included when calcu-
the stream samples, standard width- and depth-integrating
(72). More details on the integrated sampling protocols can
be found in a paper published previously (42). The effluent
sample was collected as a grab sample from the discharge.
Chemical Analysis. The collected water samples were
placed in baked amber glass bottles and shipped on ice for
analysis to the USGS National Water Quality Laboratory in
Lakewood, Colorado and the USGS Organic Geochemistry
in the physicochemical properties of the compounds. For
the majority of the pharmaceuticals, the method consisted
the eluent, and analyzing the final extract using liquid
chromatography/mass spectrometry positive-ion electro-
spray [LC/MS-ESI(+)] (73). Throughout this paper, this
method will be referred to as the “pharmaceutical method”.
For the wastewater compounds, a whole-water sample was
although other classes of compounds (such as pharmaceu-
ticals) are included as analytes. Twenty-five antibiotic
SPE using tandem cartridges, and LC/MS-ESI(+) on a single
quadrapole mass spectrometer (the “antibiotic method”).
Additional details on this method can be found in Kolpin et
al. (42). The target compounds, their methods of analysis,
and their respective reporting levels are listed in Table 2.
Qualitatively identified compound detections for which the
calculated concentrations were less than the reporting level
in the statistical analysis. As in our previous study (42),
so that a more comprehensive and complete data set could
be used to determine the range of potential concentrations
in ambient water samples impacted by wastewater, maxi-
mizing the scientific value of our results (75)
Microbial Analysis. Samples were collected in prester-
Exposure Research Laboratory in Cincinnati, Ohio for
analysis. Three different aliquots (1, 10, and 100 mL) were
analyzed in triplicate by two different USEPA methods: the
modified E. coli method (modified from method 1103.1;
mTEC), and modified enterococci method (method 1600;
MEI). The experimental details for each method were
published previously (76). The median time between col-
8-hour ideal time between collection and analysis because
of the shipping considerations. However, because all of the
samples associated with a WWTP were subject to the same
approximate delay, the results show within-site changes in
microbial populations, and concentrations reported herein
are considered estimates.
Quality Control. Compound concentrations were blank
corrected to zero if the concentrations in the environmental
samples were less than 10 times that measured in the
associated laboratory blanks. In addition, two replicate field
blanks were collected and processed after collection of a
effluent at a site in Arizona. The purpose of these replicate
field blanks was to evaluate the potential for cross-
contamination resulting from sample collection and equip-
ment cleaning procedures.
method. The mean and median concentrations of these
detections were 0.0069 and 0.007 µg/L, respectively. Five
compounds, diltiazem, diphenhydramine, caffeine, met-
formin, and trimethoprim, were detected in both blank
sulfamethoxazole were detected in one of the two replicate
blank samples. These field blank results suggest that under
“worst-case” conditions, field sample collection protocols
and equipment cleaning procedures were sufficient to
minimize cross contamination. Field blank samples were
the same correction level of 10 times the detected concen-
analyzed in duplicate for the 21 compounds in the phar-
maceutical method (73), for a total of 693 (33 × 21) replicate
pair measurements. Of these replicate pairs, 408 had non-
detections in both samples, 55 had a detection in only one
of the samples, and 230 had detections in both samples. In
the detected compound was near or less than the reporting
for acetaminophen to 16.6% for fluoxetine. The overall
median RPD for all samples and all compounds was 10.2%.
This result indicates that the precision of ambient concen-
comparisons between sites.
(74). The reporting levels for these compounds were lower
in the pharmaceutical method, and thus, concentrations
determined by the pharmaceutical method were the values
used in the environmental data analysis. In 22 of the 40
RPD for caffeine between these two methods was 41.6%.
Cotinine was detected by both methods in 13 samples; the
by both methods, or not detected by both methods) in 70%
of the samples. The presence or absence of cotinine was
confirmed in 37.5% of the samples. The considerable RPDs
VOL. 39, NO. 14, 2005 / ENVIRONMENTAL SCIENCE & TECHNOLOGY95159
TABLE 1. Selected Ancillary Information on the Wastewater Treatment Plants Investigated
flow at DS1
419 000U ) 33
A ) 0
ND ) 67
N/AN/A N/A1.40 N/AN/AN/A
320 2782/0secondary chlorineno N/A2330 13 780 N/A1.422.321.21high
Colorado 1 500 000U ) 8
A ) 4
ND ) 88
U ) 7
A ) 16
ND ) 77
U ) 5
A ) 85
ND ) 10
U ) 85
A ) 5
ND ) 10
U ) 5
A ) 84
ND ) 11
40/0 secondarychlorine yes 724214 484 96 5615.974.8115.0 2.07 low
Georgia 800 00015/0secondaryg
UVno 48 753273664 372 26.0 4.5036.232.0normal
Iowa29 7000/0secondary activated
Kansas 115 0001/0secondary activated
UV no457 10671372 0.0250.400.42 0.45normal
Minnesota 90 0004/0secondaryN/Achlorine yes91.4 3051067 3.960.614.58 4.58normal
Nevada625 000 4/0tertiary activated
yes3219 1609 96560.323.72h
65 000U ) 70
A ) 20
ND ) 10
U ) 47
A ) 5
ND ) 48
U ) 3
A ) 84
ND ) 13
0/0secondary no1175 9635840.170.44h
New York10 000 0/0tertiary trickling
chlorineno 1001008050.39 0.044h
0.42 0.71 normal
134 0006/0 tertiarytrickling
chlorine no11 265160964372.830.82 2.552.09low
eDS2) second downstream sample.fN/A ) not available.gWith biological phosphorus removal.hFlows estimated based on volume treated on sample day (MGD × 0.0438 ) m3/s).
51609ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 39, NO. 14, 2005
TABLE 2. Analytical Results of 110 Chemicals Investigated in This Study
butylated hydroxyanisole (BHA)
N,N-diethyl-m-toluamide (DEET) 134-62-3
9-gasoline and diesel fuel component
9-diesel fuel component
9-gasoline and diesel fuel component
8-intermediate in the production of dyes
9-used in cancer research
7-fixative in perfumes and soaps
8-used in manuf of polycarbanate resins
8-wastewater ozonation byproduct
8-used in manuf of dyes and expolosives
10-domestic pest/ termite control
2-nicotine metabolite (H)
8-intermediate in the production of plastics
1A-antibiotic (H, V)
7-fragrance, tobacco addative
9-coal tar and asphalt component
7-fragrance, pesticide inert
1A-antibiotic (H, V)
7-cigarette and household item flavorant
8-soil pathogen, mildew
VOL. 39, NO. 14, 2005 / ENVIRONMENTAL SCIENCE & TECHNOLOGY95161
(LC/MS versus GC/MS). When only the measurements that
were greater than the reporting level of the wastewater
was detected in seven instances by both methods, and the
median RPD decreased to 37.5%. Cotinine was never
of the wastewater method. Confirmation of presence or
absence for both caffeine and cotinine was determined in
97.5% of the samples.
There were also two compounds that were included in
both the pharmaceutical method (73) and the antibiotic
method (42), sulfamethoxazole and trimethoprim. The
of detection by both methods was good. In 20 of the 40
samples, sulfamethoxazole was detected by both methods
and had a median RPD of 17.6%. Twenty-two samples had
detections of trimethoprim by both methods and had a
median RPD of 18.8%. The presence or absence of sul-
famethoxazole was confirmed by these two methods in 75%
of the 40 samples, whereas the presence or absence of
trimethoprim was confirmed in 92.5% of the 40 samples.
The small RPDs between the pharmaceutical and antibiotic
mechanism, and instrumental analyses, with minor differ-
ences in SPE elution solvents and instrumental analysis
conditions. When only the measurements that were greater
than the reporting level of the antibiotic method (0.02 µg/L
the correspondence between the methods showed little to
no improvement. Sulfamethoxazole again was detected in
20 instances by both methods; the median RPD remained
17.6%. The number of simultaneous detections of trime-
slightly to 18.1%. With this more stringent reporting level,
by both methods in 75% of the samples; trimethoprim was
confirmed in 85% of samples.
Results and Discussion
Summary Results for Chemical Samples. Of the 110
chemicals investigated in this study, 78 were found in at
least one sample (Table 2). Not surprisingly, many of these
same chemicals were also detected in a previous national
stream-reconnaissance study of surface-water sites suscep-
tible to wastewater discharge (42). The median number of
(11), WWTP effluent (35), 1st downstream (33), 2nd down-
stream (24), and reference (1.5) (Tables 3 and 4). Among the
TABLE 2 (Continued)
name CAS number
9-fumagant, moth repellant
2-antiinflammatory (H, V)
1A-antibiotic (H, V)
9-manufacture of explosives
9-coal tar and asphalt component
1-antibiotic (H, V)
1A-antibiotic (H, V)
1-antifungal agent and antihelmintic (H, V)
5-antifoaming agent and flame retardant
1-antibiotic (H, V)
aUse classifications: 1, prescription pharmaceutical (registered for H) human, V) veterinary uses in the United States); 2, nonprescription
pharmaceutical (registered for H) human, V) veterinary uses in the United States); 3, plant or animal sterol; 4, detergents and their degradates;
5, flame retardants; 6, household wastewater compounds; 7, flavors and fragrances; 8, industrial wastewater compounds; 9, polycyclic aromatic
were analyzed by GC/MS.bThe concentration unit for the microorganisms is colony forming unit/100 mL (cfu/100 mL).cRL ) reporting level.dND
) not detected.
51629ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 39, NO. 14, 2005
detected compounds, the median concentration detected
was less than 1 µg/L for most compounds; however, seven
compounds had at least one detection greater than 5 µg/L,
and one concentration of 38 µg/L was detected (Table 5).
Not surprisingly, these high concentrations were all derived
from the WWTP effluent samples (Table 5).
When the compounds are divided into categories based
on their type of use, fire retardants and the fecal and plant
2). In general, there were substantial differences in the
frequency of detection within the chemical groups. For
in 92.5% of the environmental samples, but ibuprofen was
never detected (Table 2).
For the two reference locations, three compounds were
detected at low concentrations at the Michigan reference
site, whereas none were detected at the Montana reference
location (Table 4). The relative absence of detected com-
pounds at the reference sites indicates that the target
compounds are not ubiquitous in all streams, and therefore
could potentially serve as chemical indicators of human
Several compounds in this study, ibuprofen, trimetho-
prim, sulfamethoxazole, cabamazepine, cholesterol, copros-
tanol, galaxolide (HHCB), tonalide (AHTN), caffeine, N,N-
been monitored in WWTP effluents and/or waters directly
impacted by human wastewater (15, 17-22, 26, 36, 43). It
should be noted that none of these other studies included
more than 5 of the compounds in the above list, and the
than those measured in the other studies, all of which were
to several factors, such as distinct usage patterns, discrep-
ancies in household water consumption, differences in
treatment regulations and efficiencies, and variations in
Several studies (20, 24, 25, 31, 32) have examined both
cholesterol and coprostanol, so it is possible to calculate
coprostanol-to-cholesterol ratios as an indicator of human
fecal contribution. In this study, the median coprostanol-
to-cholesterol ratios in the upstream, WWTP effluent, DS1,
and DS2 samples were 0, 0.66, 0.55, and 0.48, respectively.
The effluent and downstream coprostanol-to-cholesterol
ratios are similar to that found in human fecal material (39),
making the human contribution of coprostanol from the
WWTP to the streams apparent. In other studies, the range
of upstream ratios was 0.003-0.017 (24, 25), the range of
effluent ratios was 0.50-1.79 (31, 32), and the range of
well with our study.
Summary Results for Microbial Samples. Overall, mi-
in this study, with the two microbial indicators, E. coli and
enterococci, detected in greater than 90% of the samples
found in high densities, with 75% of all of the samples
exceeding the levels recommended for recreational waters
(6, 7) for either E. coli or enterococci (235 and 61 colony
forming units/100 mL (cfu/100 mL), respectively). In 25% of
the samples, high densities (>5000 cfu/100 mL) of E. coli or
enterococci were determined.
were found in both collected reference samples (Michigan:
E. coli, 51.3 cfu/100 mL, enterococci, 40.3 cfu/100 mL;
Montana: E. coli, 56.7 cfu/100 mL, enterococci, 373 cfu/100
mL). This illustrates the lack of specificity of microbial
material from other sources (e.g., livestock, wildlife). Most
of the pathogens that cause illness in humans come from
human hosts; thus, it is useful to know if drinking or
recreational water is contaminated with human or animal
waste, and therefore use indicators are needed that are
specific for human or animal waste. These data suggest that
Instream Analysis. More specific trends in the number
of detections and concentrations can be determined if the
data from each WWTP site are compared with the upstream
(Table 3). The results clearly show the contributions of
WWTPs to water quality, with both the overall frequency of
detection and, in most cases, the total concentration (that
collected upstream from the WWTPs. Previous studies (15,
24, 25) with similar sampling design and target compounds
(e.g., pharmaceuticals and fecal sterols) also documented
the contributions of WWTP effluents to the stream concen-
trations of pharmaceuticals and other wastewater derived
The percent change between the different sample types
was calculated for both the number of compounds and the
Whitney U test. Significant increases (P < 0.050) in the total
number of compounds were found between the upstream
samples and the WWTP, DS1, and DS2 samples (Table 6),
reflecting the contribution of chemical input from the
WWTPs. No statistical differences were identified between
were found between the WWTP and the DS2 sample types
(Table 6). As with the number of compounds, the total
concentration of the upstream sample was significantly
different from the WWTP and DS1 but not significantly
different from the DS2 sample (Table 6). The total concen-
TABLE 3. Number of Compounds and Total Concentration of
Analytes Found at Each Location, Classified by Sample Site
at each sitea(µg/L)
effluent DS1 DS2
aSum of all detections.
TABLE 4. Compounds Detected at the Reference Locations
aNo compounds detected at the Montana location.
VOL. 39, NO. 14, 2005 / ENVIRONMENTAL SCIENCE & TECHNOLOGY95163
trations in the WWTP and DS2 were significantly different,
but the total concentrations in the WWTP and DS1 as well
as the total concentration in the two downstream samples
were not statistically different (Table 6). The trends in both
the number of compounds and the total concentration
(e.g., dilution, degradation, sorption, etc.) act to decrease
chemical concentrations with transport downstream.
only those compounds found in greater than 50% of the
WWTP effluent samples. This reduced the number of
compounds from 110 to 35 (Table 5). Because the reference
in this spatial analysis. Individual compounds exhibited
different incidence patterns and persistence. Of the 35
frequencies in the upstream and WWTP effluent samples,
emphasizing the importance of effluent-point discharges as
of fecal contamination. Among DS2 samples, however, 4 of
these 22 chemical indicators were found in <50% of the
and 8 were found more than 80% of the samples.
A Kruskal-Wallis test, the nonparametric equivalent of
the analysis of variance (ANOVA), was performed to deter-
effluent and the DS2 samples, based on the concentration
of each compound at each of the 10 locations (Table 5). A
change is considered statistically significant if P < 0.050.
Concentrations of 25 of the compounds were found to have
significant increases between the upstream and WWTP
effluent samples; enterococci were shown to decrease
that many compounds present in WWTP effluent are not
found upstream of this source. In comparison, when the
WWTP effluent and the DS1 samples are compared, only
ethyl citrate, galaxolide, and tonalide were found to be
statistically different. The similarity in chemical concentra-
tions between WWTP effluent and proximal downstream
sampling points clearly shows the effect of WWTP effluent
on stream water quality. However, a comparison between
the WWTP effluent and the DS2 sampling sites found 21
compounds to be statistically different. Thus, with further
distances from WWTP discharge, instream processes (e.g.,
dilution, degradation, sorption, etc) are causing decreases
in chemical concentrations. Because the sampling design
for this study did not take into account stream travel times,
TABLE 5. Patterns of Median Concentration and Frequency of Detection for the 35 Most Commonly Detected Chemicals
WWTP DS1DS2UpWWTP DS1DS2Up WWTP DS1 DS2
E. coli (cfu/100 mL)
enterococci (cfu/100 mL)
1277 105.3 713.5 211.5 14 900
<RL 0.150 0.064 0.046
<RL 2.200 2.100 0.770
<RL 0.880 0.760 0.405
<RL 0.200 0.130 0.072
0.040 0.053 0.041 0.050
<RL 0.080 0.079 0.075
0.840 2.000 1.200 0.785
<RL 0.139 0.039 0.018
<RL 1.300 0.720 0.175
0.012 0.024 0.022 0.024
<RL 0.011 0.004 0.005
<RL 0.037 0.011
<RL 0.049 0.016 0.010
<RL 0.078 0.009
0.230 0.180 0.310 0.170
<RL 0.270 0.105 0.082
<RL 0.280 0.140 0.038
<RL 0.180 0.145 0.117
<RL 0.024 0.004
0.710 1.100 1.020 0.570
<RL 0.150 0.081 0.057
<RL 1.000 0.710 0.240
<RL 0.330 0.170 0.180
<RL 0.300 0.210 0.140
<RL 0.180 0.120 0.106
<RL 0.250 0.200 0.110
<RL 0.038 0.014 0.012
<RL 0.072 0.027
78 483.5 174.2 27 3309300
1277 22 670
8170 11 130 89 91
90 100 0.403 0.218 0.503
100 100 0.040 0.078 0.291
400 0.005 0.264 0.003
4050 0.178 0.809 0.969
80 70 0.000 0.062 0.002
70 60 0.002 0.377 0.028
7060 0.006 0.274 0.033
4020 0.082 0.648 0.048
4040 0.001 0.088 0.050
40 40 0.583 0.509 0.509
8070 0.000 0.089 0.021
4010 0.040 0.361 0.023
80 60 0.488 0.943 0.473
100 100 0.006 0.398 0.324
9090 0.013 0.275 0.012
9080 0.021 0.438 0.120
8050 0.010 0.224 0.026
9090 0.057 0.379 0.647
7080 0.002 0.336 0.338
5030 0.051 0.192 0.044
80 70 0.006 0.121 0.022
80 20 0.006 0.091 0.004
8070 0.846 0.859 0.747
100 70 0.000 0.031 0.002
60 50 0.000 0.031 0.000
8080 0.017 0.646 0.416
50 10 0.086 0.970 0.026
4030 0.298 0.594 0.292
70 60 0.062 0.570 0.021
8090 0.003 0.139 0.062
10090 0.000 0.037 0.001
90 70 0.000 0.090 0.013
10080 0.000 0.052 0.015
90 70 0.000 0.180 0.062
7060 0.000 0.245 0.015
70 70 0.019 0.336 0.144
5020 0.011 0.287 0.021
3, plant or animal sterol; 4, detergents and their degradates; 5, flame retardants; 6, household wastewater compounds; 7, flavors and fragrances;
8, industrial wastewater compounds; 9, pesticides.bP values in bold indicate significant difference at the 95% confidence level.cUp ) upstream
51649ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 39, NO. 14, 2005
it was not possible to determine elimination rates for the
Note that two compounds that are consumed daily by
many people, caffeine and cotinine, were found at similar
frequencies in the upstream, WWTP effluent, and down-
may be present further upstream from the sampling sites,
or the inherent stability of the compounds.
(HHCB), tributyl phosphate, and triclosan] were found in
only one upstream sample but in all of the WWTP effluent
samples. The DS2 concentrations of these five compounds
declined at different rates; with frequencies of detection
ranging from 50 to 70%. Thus, these compounds may make
them candidates for chemical indicators of human fecal
As noted by Buser et al. (19), the ratio between the
compound should decrease during wastewater treatment,
In addition, they noted that the ratio should decrease with
increased residence time in a water body. To explore this
trend, the ratio of six compounds was investigated. The six
consisted of two compounds, galaxolide and tonalide, that
were ephemeral (as indicated by significant Kruskal-Wallis
?2P values between the WWTP and DS1 and the WWTP and
DS2; Table 5), two intermediate persistence compounds,
coprostanol and triclosan (as indicated by significant Kruskal-
Wallis ?2P values between the WWTP and DS2), and two
(no significant Kruskal-Wallis ?2P values downstream of
the WWTP). The ratios between the concentrations of the
compounds were calculated in the WWTP effluent and the
downstream samples (Table 7).
When the compounds with similar persistence were
compared to each other, their ratios remained fairly con-
sistent in the WWTP, DS1, and DS2 samples. The ephemeral
and intermediate compounds showed slight downward
trends, suggesting that the compounds in the numerator
(galaxolide and triclosan) were slightly less persistent that
FIGURE 2. Average frequency of detection by compound class. Numbers in parentheses indicate the number of compounds included in
each class. Because of the infrequent detection of antibiotics, they were separated from the rest of the prescription pharmaceuticals.
TABLE 6. Percent Change between the Sample Sites for Both
the Number of Compounds and Total Concentration (µg/L), as
Well as the Mann-Whitney U-test P Values
upstream - WWTP effluent
upstream - DS1
upstream - DS2
WWTP effluent - DS1
WWTP effluent - DS2
DS1 - DS2
TABLE 7. Median Ratios between the Concentrations of
Ephemeral (Galaxolide and Tonalide), Intermediate
(Coprostanol and Triclosan) and Recalcitrant (Carbamazepine
and DEET) Chemicals in the WWTP Effluent, First, and Second
compounds evaluated WWTPDS1 DS2
VOL. 39, NO. 14, 2005 / ENVIRONMENTAL SCIENCE & TECHNOLOGY95165
those in the denominator (tonalide and coprostanol, re-
spectively). The recalcitrant compounds show a slight
in each class behaved similarly, and there was no extremely
to another. Conversely, when the concentrations of the
ephemeral compounds are compared to the intermediate
are compared to the persistent compounds, there is a
dramatic decrease in the ratios when the WWTP, DS1, and
DS2 ratios are compared. The decrease in the ratios reflects
the preferential removal of the less persistent compound in
the numerator. These ratios may not only be a useful tool
in evaluating the composition of compounds in a lake as
compared to the lake’s hydraulic residence time, as Buser et
al. found (19), but also the temporal and spatial distance
from a known source in a stream or riverine system.
of detection for the microbial indicators are listed in Table
5. A trend seen with the microbial indicators was generally
lower densities in the WWTP effluent samples compared to
both the upstream and DS1 and DS2 samples. The recre-
ational water guideline for E. coli of 235 cfu/100 mL (6, 7)
was exceeded in 60% of the upstream samples, 36% of the
and 40% of the second downstream samples. Similarly, the
enterococci guideline of 61 cfu/100 mL (6, 7) was exceeded
in 78% of the upstream samples, 64% of the WWTP effluent
samples, 80% of the first downstream samples, and 70% of
the second downstream samples. The most probable ex-
at the WWTP reduced the concentrations of bacteria in the
WWTP outflow, but the rapid regrowth of the bacteria
downstream, as residual disinfection was consumed or
dispersed, resulted in increased concentrations. Even when
these lowered WWTP effluent concentrations are taken into
account, the microbial indicators do not follow the same
general pattern of the chemicals, that is, low concentrations
upstream, high concentrations at the WWTP, and gradually
decreasing concentrations downstream. The concentration
of the bacteria upstream from the WWTP was often close to,
sample. If blind samples were sent to a laboratory to
determine where a WWTP effluent plume was located (and
thus, where there would be a higher probability of con-
tamination by human pathogens), these results suggest that
with the detections in the locations minimally impacted by
humans in Michigan and Montana, the high densities in the
upstream samples illustrate the limitations of the microbial
Correlation Analysis. To further identify possible cor-
relative relations between the 35 compounds in Table 5, the
data were examined using two different statistical analyses.
package. The data were examined by sample site type. A
relation was determined to be significantly correlated at the
was greater than the critical value of 0.750 for the upstream
sample (degrees of freedom (df) )7), 0.685 for the WWTP
effluent samples (df ) 9), and 0.716 for both of the
downstream samples (df ) 8). Standard water-chemistry
measurements and other physical properties measured at
the time of sample collection (pH, conductivity, water
temperature, turbidity, dissolved oxygen, and streamflow)
properties, water temperature and turbidity, correlated to
the concentration of the compounds; these relations were
In examining the correlations between chemicals, most
of the correlations were between those compounds that
trimethoprim, diltiazem, sulfamethoxazole, dehydronife-
samples. Cholesterol, coprostanol, and sitosterol (the fecal
sterols) were positively correlated with each other in all four
sample-site types. The wastewater (nonpharmaceutical)
compounds were correlated to each other, but chiefly in the
compounds in the upstream samples but not to any other
pharmaceuticals, which would be ingested like caffeine.
Cotinine was similarly correlated to some of the wastewater
but also to the fecal sterols in those samples.
The second type of analysis was a clustering analysis
performed using an algorithm in statistiXL (Kalamunda,
for Excel. For this analysis on a quantitative data set, the
Pearson Correlation, a parametric analysis, was used as the
similarity measure, and the group average was used as the
cluster method. As the dendrogram in Figure 3 shows,
compounds with similar use classifications were frequently
grouped together. For example, the pharmaceuticals trime-
thoprim, sulfamethoxazole, dehydronifedipine, diphenhy-
dramine, diltiazem, and carbamazepine were all grouped
together. The fact that trimethoprim and sulfamethoxazole
were grouped together was particularly interesting because
these two antibiotics often are prescribed in tandem. Other
and sitosterol; caffeine and its metabolite; and the musks
was that acetaminophen grouped with the two microorgan-
isms, E. coli and enterococci, and not the other pharma-
approaches, particularly with a ranked measure, such as the
Pearson correlation, removes the effect of large differences
in concentration range on statistical inference, and may
reflect relations between constituents more accurately.
Utility as Indicators of Human Fecal Contamination.
The results of this work indicate that chemicals, particularly
fecal contamination. For most of these chemicals, there is
an increase in the frequency of detection and concentration
in the WWTP effluent sample as compared to the water
sample collected upstream. In addition, the chemical con-
centrations and occurrences decrease downstream with
distance from the WWTPs. Specifically, the distinct changes
that the concentrations of the wastewater compounds ethyl
citrate, galaxolide, and tonalide undergo between the up-
stream, WWTP effluent, and two downstream sites suggest
that they may be good indicator candidates. Compounds
that are typically only used by humans, such as the
even caffeine, would also be potential indicator candidates.
These compounds are slightly more desirable than the
wastewater compounds as indicators because they are
ingested and would be excreted from the human body. Of
sample sites, has the best potential for use as an indicator
of human fecal material. However, no compound should be
ruled in or out until its presence or concentration has been
caused by contact with the water. This correlation requires
an epidemiological study.
51669ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 39, NO. 14, 2005
This work was assisted by U.S. Geological Survey field
Arizona; Ken Covay, Nevada; Lori Sprague, Colorado; John
Lambing, Montana; Steve Sando, South Dakota; Doug
Schnoebelen, Iowa; Kathy Lee, Minnesota; Sheridan Haack,
Michigan; David Mau, Kansas; Betsy Frick, Georgia; Pat
Phillips, New York; and Paul Stackelberg, New Jersey. The
U.S. Environmental Protection Agency, through its Office of
Research and Development, supported and collaborated in
(DW-14-93940201) with the U.S. Geological Survey. This
paper has been reviewed in accordance with the U.S.
review policies and approved for publication. The use of
trade, product, or firm names in this paper is for descriptive
purposes only and does not imply endorsement by the U.S.
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after the name indicates the use classification described in Table 2.
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Received for review November 29, 2004. Revised manuscript
received April 19, 2005. Accepted May 3, 2005.
VOL. 39, NO. 14, 2005 / ENVIRONMENTAL SCIENCE & TECHNOLOGY95169