Environ. Sci. Technol. 2005, 39, 9244-9252
Use of the Chiral Pharmaceutical Propranolol to Identify Sewage Discharges into Surface Waters LORIEN J. FONO AND DAVID L. SEDLAK* Department of Civil and Environmental Engineering, University of California at Berkeley, Berkeley, California 94720
The discharge of relatively small volumes of untreated sewage is a source of wastewater-derived contaminants in surface waters that is often ignored because it is difficult to discriminate from wastewater effluent. To identify raw sewage discharges, we analyzed the two enantiomers of the popular chiral pharmaceutical, propranolol, after derivitization to convert the enantiomers to diastereomers. The enantiomeric fraction (the ratio of the concentration of one of its isomers to the total concentration) of propranolol in the influent of five wastewater treatment plants was 0.50 ( 0.02, while after secondary treatment it was 0.42 or less. In a laboratory study designed to simulate an activated sludge municipal wastewater treatment system, the enantiomeric fraction of propranolol decreased from 0.5 to 0.43 as the compound underwent biotransformation. In a similar system designed to simulate an effluentdominanted surface water, the enantiomeric fraction of propranolol remained constant as it underwent biotransformation. Analysis of samples from surface waters with known or suspected discharges of untreated sewage contained propranolol with an enantiomeric fraction of approximately 0.50 whereas surface waters with large discharges of wastewater effluent contained propranolol with enantiomeric fractions similar to those observed in wastewater effluent. Measurement of enantiomers of propranolol may be useful in detecting and documenting contaminants related to leaking sewers and combined sewer overflows.
Introduction A variety of contaminants in municipal sewage pose potential risks to human health and aquatic ecosystems (1, 2). For example, pathogens present in untreated sewage have caused widespread outbreaks of gastrointestinal illness (3) while chlorine-disinfected wastewater effluent is believed to be the most important source of the carcinogenic disinfection byproduct N-nitrosodimethylamine (NDMA) and its precursors in locations where water reuse is practiced (4). In surface waters where wastewater effluent accounts for a significant fraction of the overall flow, fish may be impacted by steroid hormones that interfere with development and possibly reproduction (5, 6). A variety of other wastewater-derived chemical contaminants (WWDCs) have also been detected in surface waters (7, 8), but no known risks associated with exposure of humans (9) or aquatic organisms to low concentrations of these compounds have been identified. * Corresponding author phone: (510)643-0256; fax: (510)642-7483; e-mail:
[email protected]. 9244
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Most studies of fate and transport of WWDCs treat wastewater effluent as the sole source of wastewater-derived contaminants in surface waters and use the simplifying assumption that wastewater treatment plant (WWTP) performance is equivalent during wet and dry weather (10, 11). Under these conditions, the concentration of WWDCs in surface waters should be highest in systems where effluent is the main source of water. Although wastewater effluent is undoubtedly an important source of contaminants in many locations, wet weather flows may also contribute WWDCs to surface waters. For example, higher concentrations of some WWDCs have been observed during wet weather than under base flow conditions in a lake in Switzerland (12) and in several U.S. rivers (13, 14). In the U.S., there are approximately 800 cities with a total population of 40 million people that have combined sewers (15). Most of these systems discharge raw sewage into receiving waters during rainfall or snowmelt events through combined sewer overflows (CSOs). Direct discharges of raw sewage also can occur during dry weather through leaking sewers and improperly functioning septic tanks. Although the higher flows in surface waters normally associated with CSOs should dilute WWDCs, CSOs can still be an important source because the concentrations of WWDCs in raw sewage can be up to 1000 times greater than those present in wastewater effluent (12, 16, 17). Furthermore, most WWTPs remove WWDCs less effectively during wet weather events (17). As a result, relatively high concentrations of some WWDCs may be present in surface waters during high-flow conditions. Insight into the relative contribution of treated and untreated sewage to WWDCs in surface waters might be gained by comparing the concentrations of recalcitrant compounds and compounds that are removed efficiently by WWTPs. However, this would not be a very accurate means of quantifying contributions of untreated sewage because concentrations in raw and treated sewage can vary widely over short periods of time (6, 17, 18). Additionally, this type of analysis would be complicated by removal of the labile WWDCs via attenuation in surface waters. An alternative approach for quantifying the relative contribution of raw sewage to surface waters involves the measurement of enantiomers of chiral WWDCs. The chirality of certain pesticides has been used previously by researchers as a means of apportioning their sources (19, 20). The relative concentration of a compound’s enantiomers is often expressed as the enantiomeric fraction (EF), which is defined by eq 1
EF )
[enantiomer 1] [enantiomer 1] + [enantiomer 2]
(1)
Through the use of this approach, the EF of a racemic compound is 0.5 and that of an enantiomerically pure compound is either 1.0 or 0.0. For chiral compounds that undergo enantioselective biodegradation, the EF of a compound will reveal information about its history. For example, a WWDC that undergoes enantioselective biodegradation in a WWTP will have a different EF in WWTP effluent than in raw sewage. This approach, which was suggested by Buser et al. (16) in their study of the enantioselective degradation of ibuprofen, is more useful than analysis of the relative concentrations of different WWDCs because it is not affected by fluctuations in WWDC concentrations in raw sewage or by analytical uncertainty, because the two enantiomers will have the same recovery at each stage of the analytical procedure. 10.1021/es047965t CCC: $30.25
2005 American Chemical Society Published on Web 10/15/2005
TABLE 1. Flow Rates and Biological Treatment Processes Employed by Wastewater Treatment Plants Where Samples Were Collected WWTP
location
flow m3/s (MGDa)
biological treatment processes
26th Ward East Bay Municipal Utilities District Mt. View Sanitary District Riverside Water Quality Control Plant Rapid Infiltration/Extraction (RIX) San Jose/Santa Clara Water Pollution Control Plant Sewerage Agency of Southern Marin
Brooklyn, NY Oakland, CA Martinez, CA Riverside, CA Colton, CA San Jose, CA
3.2 (72) 4.0 (90) 0.80 (18) 1.5 (33) 1.9 (44) 7.3 (167)
activated sludge pure oxygen activated sludgte trickling filter, nitrification biotowerb activated sludge, nitrification/denitrificationb activated sludge, nitrification/denitrificationb activated sludge, biological nutrient removalb
Mill Valley, CA
0.16 (3.6)
activated sludge, biological nutrient removalb
a
Million gallons per day.
b
Tertiary treatment.
In this study we examined the use of propranolol, a chiral pharmaceutical, as a tracer of raw and treated sewage. Propranolol was selected for this purpose because its enantiomers can be separated after derivitization by gas chromatography without an enantioselective stationary phase. Propranolol is a β-blocker that is one of the most common prescription drugs in the United States (21). It has been detected in European surface waters at concentrations up to 590 ng/L and in European and American wastewater effluents at concentrations up to 290 and 1900 ng/L, respectively (17, 22). To assess its utility as a tracer, samples were collected from WWTPs and surface waters where previous research had shown that wastewater effluent or raw sewage are important sources of WWDCs. These measurements were complemented by laboratory studies with microcosms designed to simulate WWTPs and effluentreceiving surface waters.
Experimental Section Materials. Racemic and enantiomerically pure propranolol hydrochloride (99%), metoprolol (99%), N-methyl-N-trifluoroacetamide (MSTFA) hexachlorocyclobenzene (HCB) (99%), and (-)-(R)-methoxy-R-(trifluoromethyl)phenylacetyl chloride ((-)-MTPA-Cl) were obtained from Sigma Aldrich (St. Louis, MO). Analytical grade methanol and isooctane, sodium chloride (NaCl), tryptic soy broth, as well as sodium azide were obtained from Fisher Scientific (Pittsburgh, PA). Distilled water treated with a Barnstead Nanopure II system was used for sample preparation. Sampling Locations. Raw sewage and final effluent samples were collected from seven WWTPs in California and New York (Table 1). At four of the WWTPs, samples were collected at different stages of the treatment train. The wastewater collection system for the 26th Ward WWTP is a combined sewer, and the WWTP has a bypass system for wet weather. This WWTP was sampled during dry weather when the bypass system was not being used and during wet weather when sewage that bypassed secondary treatment comprised 9% of the flow. In addition, sewage was sampled from the wastewater collection system near Bush Creek at Ward Street in Kansas City, MO. All wastewater was collected as grab samples (with the exception of the samples from the San Jose/Santa Clara Water Pollution Control Plant, which were 24-h flow-weighted composites) in 4-L amber glass bottles spiked with 8 g of NaCl to prevent sorption of the analyte onto the sides of the vessel. Grab samples also were collected from four surface waters in 1- or 4-L amber glass bottles spiked with 2 g/L NaCl. Each surface water sampling site is described below. Samples were collected from the Mt. View Sanitary District’s engineered treatment wetland, in Martinez, CA, which was constructed to supply additional treatment to the effluent of the adjacent WWTP. The wetland consists of five
FIGURE 1. Sampling sites in Jamaica Bay, NY. ponds in series connected by weirs and underground pipes. Each pond is between 0.4 and 1.2 m deep and is vegetated around the edges with cattails and bulrushes. Results of a LiCl tracer test indicated that the hydraulic retention time of the wetland is approximately 9 days. Samples were collected at the inlet of the wetland, at a mid-wetland location where the water was determined to have a hydraulic retention time of approximately 5 days relative to the wetland inlet, and at the wetland outlet. Samples were collected upstream and downstream of a storm sewer outfall into Gwynns Falls, Baltimore County, MD. The storm sewer is known to be contaminated by raw sewage from a nearby leaky sanitary sewer. Gwynns Falls otherwise does not receive any wastewater effluent discharges (23). Samples also were collected from Jamaica Bay (Figure 1), which is located on the south shore of western Long Island, NY. During dry weather, the bay receives approximately 12.9 m3/s (290 million gallons per day (MGD)) of secondary effluent. During wet weather, raw sewage and stormwater runoff are discharged into the bay from CSOs. The bay is on average 5 m deep, and the water in the bay has a hydraulic residence time of approximately 35 days (24). Samples were collected from Jamaica Bay off the nearby Canarsie Pier in Brooklyn, NY, 1 and 4 days after a rainfall event. This site is impacted by treated wastewater effluent from the 26th Ward WWTP as well as the CSO outfalls of both this plant and the Coney Island WWTP. A sample also was collected from a lagoon that receives CSO runoff from near the 26th Ward WWTP. The lagoon, which is located adjacent to the 26th Ward WWTP, drains into Jamaica Bay. Finally, samples were collected from the Santa Ana River, which is located in Orange and Riverside Counties, CA (Figure 2). The Santa Ana River flows approximately 160 km from the coastal mountains near Big Bear Lake to the Pacific Ocean. During summer, most of the flow of the river is attributable to twelve WWTPs that discharge into the Santa Ana River and its tributaries (25, 26). The three largest WWTPs that VOL. 39, NO. 23, 2005 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 2. Sampling sites along the Santa Ana River, CA. WWTPs are represented by stars. Letters indicate locations where surface water samples were collected. discharge into the Santa Ana River Basin are Rapid Infiltration/Extraction (RIX), Riverside WQCP, and Chino RPI. Up to 50% of the river’s flow is diverted into the Prado Wetlands, which are located approximately 50 km upstream of the Pacific Ocean. Upstream of the Prado Wetlands, the river is approximately 0.5 m deep and has a sandy bottom whereas downstream of the wetlands the river is confined to a concrete-lined channel as it passes through an urban area. Samples were collected from various reaches of the Santa Ana River on three occasions. During the first two rounds, grab samples were collected from different reaches of the river, and one sample from Chino Creek, which is a tributary to the Santa Ana River, during a period of 12 h. The third round was conducted as part of a synoptic study, following three parcels of water down an 11-km stretch of the Santa Ana River between the RIX facility and the Riverside WQCP. Samples from surface waters and wastewater treatment plants were immediately placed in coolers with ice for transport back to the laboratory, where they were stored at 4 °C. The samples were filtered through 0.45-µm glass-fiber filters within 4 days of sampling. Microcosm Experiments. To simulate the biotransformation of propranolol in a municipal WWTP, five 4-L amber glass bottles were filled with 3.9 L of filtered secondary effluent from the East Bay Municipal Utilities District’s WWTP, collected prior to disinfection. Three of the treatments were amended with 20 mL of freshly collected return activated sludge containing 3000 mg/L suspended solids from the same WWTP. One of the three bottles containing activated sludge was sterilized with 40 mM sodium azide. One of the two treatments that did not receive return activated sludge was sterilized with 10 mM sodium azide. Before the experiment was started, 10 mg/L tryptic soy broth was added to each of the bottles that received return activated sludge. An additional 10 mg/L was added to the two bottles with activated sludge that had not been sterilized on each subsequent day of the experiment. Humidified air was bubbled through each of the bottles through a glass frit at a rate of 150 mL/min. The system was allowed to equilibrate for 24 h prior to addition of 1000 ng/L racemic propranolol. Approximately 500-mL samples were collected daily over a period of 6 days. Although this is longer than the hydraulic retention time, a longer period was needed due to differences between the microbial processes in the batch microcosm and the full-scale system. Before extraction, each sample was fortified with 0.5 µg of racemic metoprolol as an internal standard, which resulted in a concentration of metoprolol at least an order of magnitude higher than that which was already present in the matrix. Suspended solids and pH were monitored over the course of the experiment using standard methods (27). 9246
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To simulate biotransformation of propranolol in surface waters, six 4-L clear Pyrex beakers were filled with water from the Mt. View Wetland that had been strained through a 75-µm sieve. The initial concentration of propranolol in the wetland water was less than 10 ng/L. The beakers were spiked with 1000 ng/L of racemic propranolol and placed in a 15 °C constant-temperature bath, located on the roof of a building on the University of California at Berkeley campus that receives exposure to direct sunlight. Three of the beakers were covered in aluminum foil. One of the beakers covered in foil and one beaker exposed to sunlight were sterilized with 10 mg/L sodium azide. Aliquots with volumes of 200, 300, 400, 500, and 1000 mL were removed for analysis on day 0, 2, 7, 13, and 20, respectively. Before extraction, each of these samples was fortified with 1 µg of metoprolol as an internal standard, which resulted in a concentration of metoprolol at least an order of magnitude higher than that which was already present in the matrix. To maintain constant sunlight exposure conditions, each time a sample of water was removed for analysis, it was replaced with the same volume of strained wetland water that had been stored at 5 °C. Normalized concentrations of propranolol were calculated by accounting for dilution that occurred when water was replaced. Analysis. Samples were subjected to solid-phase extraction prior to derivatization and gas chromatography/tandem mass spectrometry (GC/MS/MS) analysis. Prior to use, cartridges containing 500 mg of Supelclean C18 resin (Supelco, St. Louis, MO) were conditioned with 10 mL of methanol followed by 20 mL of Nanopure water. Aliquots of between 0.5 and 2 L of sample were passed through the cartridges at a rate of 20 mL/min, followed by a rinse with 50 mL of Nanopure water. After extraction, the analytes were eluted from the cartridges with 10 mL of methanol. The eluent was dried overnight in a vacuum oven at 30 °C, redissolved in 2 mL of methanol, transferred to 4-mL screw-cap vials, and blown to dryness under a gentle stream of purified nitrogen. Propranolol and metoproplol were derivitized with MSTFA and (-)-MPTA-Cl using a method adapted from Kim et al. (28). After 50 µL of MSTFA was added to the reaction vials containing the dry samples, they were capped and held at room temperature for 30 min, then placed in a 60 °C oven for 5 min. After the samples cooled, 5 µL of (-)-MPTA-Cl was added to the vials, which were then capped and returned to the 60 °C oven for an additional 5 min. The derivitized samples were diluted with 100, 200, or 250 µL isooctane that contained 500 µg/L HCB as an internal standard to correct for variability in the injection volume. Propranolol and metoprolol derivatives as well as HCB were analyzed by GC/MS/MS (Thermoquest, San Jose, CA). A 30-m, 0.25-mm (i.d.), 0.25-mm (film thickness) MDN-5S column (Supelco, Bellefonte, PA) was used for separation. Splitless injections of 1 µL into an injection port set to 250 °C were used. Helium was used as the carrier gas at 1.0 mL/ min. The programmed temperature run consisted of an initial 1.0-min hold at 100 °C, followed by a 3 °C/min ramp to 300 °C with a 1.0-min hold at the end of the program. Mass spectrometer conditions included electron-impact ionization at 70 eV in a 200 °C ion source with a 300 °C transfer line from the gas chromatograph. Details of the retention times and mass spectrometer conditions are listed in Table 2. The limit of detection of propranolol using this method ranged from 0.1 to 1.0 ng/L depending upon the sample matrix and the instrument response. Spike recoveries of 150 ng/L of propranolol in Nanopure water with 2 g/L NaCl varied from 15% to 90% relative to HCB with a median of 71%. Recoveries were better when using freshly silanized glassware for sample processing. Concentration data were not corrected for recoveries since recoveries varied between samples within each set of samples. Due to these variations in recoveries
TABLE 2. Gas Chromatography/Tandem Mass Spectrometry Analytical Conditions compound
retention time (min)
parent ion (au)
product ion (au)
collision energy (mV)
hexachlorocyclobenzene metoprolol (-)-(S)/(+)-(R) propranolol (-)-(S)/(+)-(R)
23.80 59.5/59.8 61.6/61.9
142, 249, 284 (SIM) 404.0 404.0
189, 105 189, 105
1.0 1.0
FIGURE 3. Derivitization of (R)-(+)-propranolol and (S)-(-)-propranolol by MSTFA and (-)-MPTA-Cl. within each batch of samples, we estimate an uncertainty in the concentration values we report of approximately (30%. The order of elution of the two enantiomers of propranolol from the GC column was determined by comparing the retention times of the sample with that of a standard solution of enantiomerically pure (S)-(-)-propranolol. In this paper, we report the EF of propranolol as the ratio of the concentration of the (R)-(+) enantiomer to the total concentration of propranolol.
Results Chiral Analysis. The derivitization procedure for propranolol presented here was adapted for environmental analysis from a method developed for biomedical applications (28). In this method, the two enantiomers of propranolol were derivatized with a single enantiomer of a chiral compound, (-)-MPTACl, to form diastereomers (Figure 3). The two propranololderivative diastereomers had different physical properties from one another and therefore could be separated with baseline resolution using a common reverse-phase gas chromatographic column (Figure 4). By comparison of the chromatographic retention time of a standard of enantiomerically pure (S)-(-)-propranolol to that of racemic propranolol, it was determined that the first peak to elute from the GC column corresponds to (R)-(+)-propranolol and the second to (S)-(-)-propranolol. Analysis of approximately 20 duplicate samples showed good agreement with a standard deviation for the EF of less than 0.03 whenever the concentration of propranolol was greater than 1 ng/L. The standard deviation of the EF was not correlated with the magnitude of the EF. There also was not a relationship between EF and concentration (Figure 5). Measurements of EF were not affected by sample-to-sample variation in extraction efficiency or derivitization yield. In samples from WWTPs, the chromatogram of derivitized propranolol was accompanied by two peaks with retention times of approximately 1 min longer than propranolol (Figure 6). This second compound did not interfere with the measurement of propranolol in any of the samples. Concentrations of propranolol at the WWTPs varied from 13 to 250 ng/L in the plant influent and from 3 to 160 ng/L after biological treatment (Table 3). In individual plants where
FIGURE 4. Chromatogram of a racemic 600 ng/L standard of propranolol. The peak labeled (1) is (R )-(+)-propranolol; (2) is (S)(-)-propranolol. both the influent and the effluent were sampled, the reduction in the concentration of propranolol varied from 15% to 95% with a median of 77%. Although these removals are imprecise due to the use of grab samples and variation in recoveries, the data agree with previous studies that show that propranolol is partially removed during biological wastewater treatment (17). In each of the wastewater treatment plants surveyed, the propranolol was racemic in the influent (i.e., EF ) 0.49-0.54) but not in the effluent (i.e., EF ) 0.31-0.44). A paired Student’s t-test of the five data sets where both influent and effluent were sampled showed that the EFs were significantly different in the influent and effluent (p < 0.014). The wastewater effluent at the 26th Ward WWTP during dry weather had an EF of 0.42 for propranolol, which was the highest of any of the WWTPs. The high EF was consistent with the apparent poor removal during secondary treatment. During wet weather, when 9% of the effluent sample consisted of raw sewage that bypassed secondary treatment, EF of the effluent increased to 0.44. At the San Jose Water Pollution Control Plant and at Mt. View Sanitary District, samples were taken at intermediate VOL. 39, NO. 23, 2005 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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TABLE 3. Propranolol Concentration and EF Values in WWTPs Sampled concentration (ng/L) location 26th Ward East Bay Municipal Utilities District Kansas City, MOb Mt. View Sanitary District Riverside WQCP RIX San Jose/Santa Clara Water Pollution control plant Sewerage Agency of Southern Marin a
date 04/27/04a 09/13/04 04/06/04 09/13/04 10/02/03 05/30/02 06/08/04 06/08/04 06/26/02 08/08/02 07/11/02
EF
plant influent
post-biological treatment
plant Influent
post-biological treatment
23 13 250
13 11 58 21
0.50 0.50 0.49
0.44 0.42 0.41 0.40
38 58 22
3 10 9 53 3 160
0.50 0.54 0.52
0.33 0.37 0.30 0.33 0.37 0.31
Approximately 9% of effluent bypassed secondary treatment due to wet weather. b Sample collected from sewer line to nearby WWTP.
FIGURE 5. Relationship between EF and concentration in samples taken at WWTPs.
FIGURE 6. Chromatogram of propranolol from Mt. View Wetland inlet. The peak labeled (1) represents the derivative of (R )-(+)propranolol; (2) is the derivative (S)-(-)-propranolol; (3) and (4) are a doublet of unknown identity that consistently shows up in chromatograms of wastewater. In this sample, the total concentration of propranolol is 160 ng/L and EF ) 0.37. stages in the treatment process (Figure 7). In these samples EF decreased after every step of biological treatment and remained unchanged after chemical or physical treatment steps (i.e., filtration, settling, and chlorination). In the microcosms designed to simulate an activated sludge tank, the concentration of propranolol decreased in the two treatments containing live activated sludge but did not change in either of the sterilized treatments or the treatment containing only filtered effluent (Figure 8a). The 9248
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FIGURE 7. Concentration and enantiomeric fraction of propranolol at different steps in the treatment train at (a) Mt. View Sanitary District, Martinez, CA, and (b) San Jose Wastewater pollution control district. For part a, the secondary treatment is a trickling filter and tertiary treatment is nitrification. The final treatment steps are filtration and UV disinfection. For part b, secondary treatment is activated sludge, which is followed by nitrification, filtration, and chlorination. Where duplicate samples were measured, vertical lines indicate the range of values. EF of propranolol decreased from racemic to 0.44 and 0.43 in the two activated sludge treatments after 6 days of incubation (Figure 8b). At the Mt. View Wetland, the concentration of propranolol in the wetland decreased from 230 to 94 ng/L between the wetland inlet and the outlet while the EF remained between 0.32 and 0.39 with no evident trend as the water passed through the wetland (Figure 9). While this decrease in concentration may have been attributable to photolysis or biodegradation, it is also possible that the apparent removal
FIGURE 10. Normalized concentration of propranolol in surface water microcosms and controls.
TABLE 4. Propranolol Concentration and EF Values for Surface Water Samples site
date
concentration (ng/L)
Gwynn’s Falls, MD upstream of outfall 7/27/04
