Open Access

Ultra high performance liquid chromatography tandem mass spectrometry for rapid analysis of trace organic contaminants in water

  • Tarun Anumol1,
  • Sylvain Merel1,
  • Bradley O Clarke1, 2 and
  • Shane A Snyder1Email author
Chemistry Central Journal20137:104

https://doi.org/10.1186/1752-153X-7-104

Received: 9 April 2013

Accepted: 27 May 2013

Published: 18 June 2013

Abstract

Background

The widespread utilization of organic compounds in modern society and their dispersion through wastewater have resulted in extensive contamination of source and drinking waters. The vast majority of these compounds are not regulated in wastewater outfalls or in drinking water while trace amounts of certain compounds can impact aquatic wildlife. Hence it is prudent to monitor these contaminants in water sources until sufficient toxicological data relevant to humans becomes available. A method was developed for the analysis of 36 trace organic contaminants (TOrCs) including pharmaceuticals, pesticides, steroid hormones (androgens, progestins, and glucocorticoids), personal care products and polyfluorinated compounds (PFCs) using a single solid phase extraction (SPE) technique with ultra-high performance liquid chromatography coupled to tandem mass spectrometry (UHPLC-MS/MS). The method was applied to a variety of water matrices to demonstrate method performance and reliability.

Results

UHPLC-MS/MS in both positive and negative electrospray ionization (ESI) modes was employed to achieve optimum sensitivity while reducing sample analysis time (<20 min) compared with previously published methods. The detection limits for most compounds was lower than 1.0 picogram on the column while reporting limits in water ranged from 0.1 to 15 ng/L based on the extraction of a 1 L sample and concentration to 1 mL. Recoveries in ultrapure water for most compounds were between 90-110%, while recoveries in surface water and wastewater were in the range of 39-121% and 38-141% respectively. The analytical method was successfully applied to analyze samples across several different water matrices including wastewater, groundwater, surface water and drinking water at different stages of the treatment. Among several compounds detected in wastewater, sucralose and TCPP showed the highest concentrations.

Conclusion

The proposed method is sensitive, rapid and robust; hence it can be used to analyze a large variety of trace organic compounds in different water matrixes.

Keywords

Trace organic contaminantPharmaceuticalPersonal-care productGlucocorticoidPFCSolid-phase extractionUltra-high performance liquid chromatographyTandem mass spectrometryWater quality

Background

The environmental occurrence of pharmaceuticals, steroid hormones, pesticides and personal-care products, collectively termed as trace organic contaminants (TOrCs) or contaminants of emerging concern (CECs), has been consistently reported for over a decade [14]. The recalcitrance of certain TOrCs and their ability to pass through conventional drinking water treatment trains has necessitated frequent monitoring of these chemicals [57]. While the effects of many TOrCs on public health remains largely unknown, studies have shown that some of these contaminants can have drastic effects on aquatic organisms at concentrations present in wastewater [8, 9]. In addition, other studies have demonstrated that a combination of TOrCs can have synergistic effects on some organisms [9, 10].

Numerous studies have focused on the analysis of estrogens, both natural and synthetic [1113], but relatively less literature is available on the occurrence and analysis of other endocrine disruptors (glucocorticoids, progestins and androgens) in aquatic environments. Glucocorticoid receptor-active compounds (GRs) are known to control inflammation and infections and hence both natural and synthetic GRs have been used to prevent swelling, asthma and other diseases in humans [14]. This increased use combined with the fact that most GRs are poorly adsorbed in the human body and quickly excreted has led to their recent detection in wastewater and surface waters worldwide [1416]. In this work we expanded the list of steroids typically included for analysis to include an androgen (testosterone), progestins (norethisterone and norgestrel) along with several GRs.

Polyfluorinated compounds (PFCs) are a relatively new sub-class of compounds within the TOrC classification. These compounds are synthetically produced and have a wide-range of applications, including in non-stick cookware, stain-resistant carpets, and surfactants among other things [17]. This frequent usage along with their inherent biological and chemical stability make PFCs persistent in the environment and frequently detected in water [17, 18], biosolids [19] and biological matrices [20]. Consequently, the two most commonly used PFCs (PFOA and PFOS) are on the USEPA’s Contaminant Candidate List 3 [21]. In addition, bioaccumulation properties, potential carcinogenicity and recent reports on toxic effects to animals [22, 23] have led to the voluntary reduction in usage of PFOA and the banning of PFOS in Europe [24]. However, these two compounds are progressively being replaced by shorter chain (C < 7) PFC’s [25], of which far less is known with regards to toxicity and occurrence data. Accordingly, this study set out to include six PFCs with C4-C16 carbon chain length.

Over 82,000 chemicals are registered for industrial use in the US and the number is rapidly increasing [26]. Monitoring each chemical is not feasible; hence the significance of selecting ‘indicator’ compounds that encompass the various classes of TOrCs is critical. Recent studies have sought to identify indicator TOrCs based on their occurrence and attenuation in the environment [27]. This study selected 36 disparate compounds across seven classes of TOrCs for analysis using a single extraction method and short analysis time.

As the number of environmental contaminants monitored continues to increase rapidly, the need for reliable analytical methods offering selectivity, sensitivity and reproducibility also has increased. Over the years, numerous methods relying on a variety of instruments were developed to measure TOrCs. For instance, gas chromatography has been used to analyze volatile compounds and pesticides as well as some polar compounds and steroids using derivatization agents [28, 29]. However, these techniques are time-consuming, labor intensive and limited to the analysis of compounds that are volatile and not thermally-labile.

Liquid chromatography methods have proved more effective in analyzing TOrCs. While methods using UV [30, 31] and fluorescence [32, 33] detectors have been proposed, methods using both single quadrupole [34, 35] and triple quadrupole [36, 37] mass spectrometers have been most common. However, the vast majority of these methods consider only specific classes of pharmaceuticals [38, 39] or compounds with similar polarities and/or use numerous extraction methods that are time-consuming and labor-intensive. Only few methods use a single extraction procedure while still analyzing a wide variety of these compounds [29, 40, 41]. With the introduction of ultra-high performance liquid chromatography (UHPLC), it is now possible to operate at extremely high pressures with much smaller particle sizes which allows for rapid separation of analytes while also improving resolution and sensitivity.

This study aims to provide a simple, rapid, sensitive and robust method for the targeted analysis of 36 compounds (Table 1) representative of several TOrC classes usually considered by water utilities and regulatory agencies. The method includes several different classes of TOrCs including less studied substances like GRs and PFCs. The application of UHPLC allows for a significant reduction in sample runtime while providing good analytical separation compared to previously published methods and also providing very low ng/L detection limits in water. The proposed method includes the addition of 19 stable isotopically labeled compounds to increase accuracy and precision. This method was successfully applied to groundwater, surface water and wastewater matrices.
Table 1

Target compounds with use and class

Compound

Use

Class

Atrazine

Pesticide

Pesticide

Benzophenone

UV Blocker

Personal Care Product

Bisphenol A

Plasticizer

Industrial compound

Caffeine

Stimulant

Personal Care Product

Carbamazepine

Anticonvulsant

Pharmaceutical

N,N-Diethyl-meta-toluamide (DEET)

Insect Repellant

Personal Care Product

Dexamethasone

Anti-Inflammatory

Glucocorticoid

Diclofenac

Anti-arthritic

Pharmaceutical

Diltiazem

Antiarrhythmic

Pharmaceutical

Diphenhydramine

Anti-histamine

Pharmaceutical

Fluoxetine

Anti-Depressant

Pharmaceutical

Gemfibrozil

Anti-Cholesterol

Pharmaceutical

Hydrocortisone (Cortisol)

Anti-inflammatory

Glucocorticoid

Ibuprofen

Analgesic

Pharmaceutical

Meprobamate

Anti-anxiety

Pharmaceutical

Naproxen

Analgesic

Pharmaceutical

Norethisterone

Contraceptive

Progestin

Norgestrel

Contraceptive

Progestin

Perfluoro butanoic acid (PFBA)

Fluorosurfactant

Polyfluorinated Compound

Perfluoro butane sulfonate (PFBS)

Fluorosurfactant

Polyfluorinated Compound

Perfluoro decanoic acid (PFDA)

Fluorosurfactant

Polyfluorinated Compound

Perfluoro hexadecanoic acid (PFHxDA)

Fluorosurfactant

Polyfluorinated Compound

Perfluoro octanoic acid (PFOA)

Fluorosurfactant

Polyfluorinated Compound

Perfluoro octane sulfonate (PFOS)

Fluorosurfactant

Polyfluorinated Compound

Prednisone

Anti-inflammatory

Glucocorticoid

Primidone

Anticonvulsant

Pharmaceutical

Simazine

Herbicide

Pesticide

Sucralose

Artificial Sweetener

Personal Care Product

Sulfamethoxazole

Antibiotic

Pharmaceutical

Tris (2-chloroethyl) phosphate (TCEP)

Flame retardant

Industrial compound

Tris (2-chloropropyl) phosphate (TCPP)

Flame retardant

Industrial compound

Testosterone

Androgen

Androgen

Triamcinolone

Synthetic corticosteroid

Glucocorticoid

Triclocarban

Antibiotic

Personal Care Product

Triclosan

Anti-microbial

Personal Care Product

Trimethoprim

Antibiotic

Pharmaceutical

Experimental

Chemicals and reagents

All standards and reagents used during the study were of the highest purity commercially available (≥97% for all compounds). All native standards were procured from Sigma-Aldrich (St. Louis, MO) except perfluorohexadecanoic acid (PFHxDA) from Matrix Scientific (Columbia, SC); meprobamate from Cerilliant (Round Rock, TX); and triclosan from Alfa Aesar (Ward Hill, MA). Labeled standards were purchased from Cambridge Isotope Laboratories (Andover, MA) except 13C4-PFOA, 13C4-PFOS, 13C2-PFHxA, 13C4-PFBA from Wellington Laboratories (Ontario, Canada); primidone-d5 and 13C6-diclofenac from Toronto Research Chemicals (Ontario, Canada); and gemfibrozil-d6 from C/D/N Isotopes (Quebec, Canada). A working stock of all native standards was prepared at 5 mg/L in pure methanol and diluted as required to obtain the desired concentration of calibration standards. A mix of all isotopically labeled surrogates at 1 mg/L in pure methanol was also prepared and used to spike all samples before extraction. These two solutions were stored in the dark at −20°C and new working stocks were prepared every two months. Both stocks were injected routinely on the mass spectrometer and signal response was monitored for each compound to determine if there was any degradation with time.

All solvents were of the highest purity available and suitable for LC-MS analysis. Methanol (HPLC grade), MTBE (HPLC grade), formic acid (LC/MS grade) and ammonium hydroxide (ACS grade) were obtained from Fisher Scientific (Pittsburgh, PA), while acetonitrile and ultrapure water (both HPLC grade) were obtained from Burdick and Jackson (Muskegon, MI).

Sample collection and preservation

Grab samples were collected from four full-scale water treatment plants across the United States. In addition, multiple samples from two surface waters and a groundwater from Tucson, Arizona were analyzed. Samples (1 L each) were collected in silanized amber glass bottles containing 50 mg of ascorbic acid to quench residual chlorine and 1 g of sodium azide to prevent microbial activity. Samples were sent to the laboratory in coolers containing icepacks and filtered through a 0.7 μm glass filter (Whatman, England) immediately upon arrival. Then, samples were stored in darkness at 4°C and extracted within 14 days. Sample preservation techniques were comparable to those previously published by Vanderford et al. [42].

Solid-phase extraction

All samples were spiked with 19 isotopically labeled surrogate standards at concentrations varying from 50 to 200 ng/L depending on analytical sensitivity and matrix type. Samples were then extracted using an AutoTrace 280 automated SPE system from Dionex (Sunnyvale, CA) using 200 mg hydrophilic-lipophilic balance (HLB) cartridges (Waters Corporation; Millford, MA). Cartridges were first preconditioned with 5 ml of MTBE, followed by 5 ml of methanol and 5 ml of ultrapure water. Samples were then loaded at 15 ml/min onto the cartridges which were subsequently rinsed with ultrapure water and dried under nitrogen flow for 30 min. While 1 L samples were collected, different volumes of sample were extracted based on the matrix. The analytes were then eluted with 5 ml of methanol followed by 5 ml of 10/90 (v/v) methanol/MTBE solution. The eluent was evaporated to less than 500 μl using gentle nitrogen flow and the volume was adjusted to 1 ml by addition of methanol. Final extracts were transferred into 2-mL vials and stored in darkness at 4°C until UHPLC-MS/MS analysis.

Liquid chromatography

Liquid chromatography was performed on 3 μL of sample extract using an Agilent 1290 binary pump (Palo Alto, CA) with metal solvent fittings for all analyses. The Agilent RRHD ZORBAX Eclipse Plus reverse phase C-18 column (2.1×50 mm) with a packing size of 1.8 μm was used to separate analytes in both the negative and positive electrospray ionization (ESI) modes. The column was maintained at a temperature of 30°C for the entire run in both modes.

The mobile phase for ESI positive used two solvents comprising (A) ultrapure water with 0.1% formic acid and (B) acetonitrile with 0.1% formic acid. With a constant flowrate of 400 μl/min, solvent B was held at 5% for 1.5 min. Solvent B then linearly increased to 20% at 3 min, 45% at 4 min, 65% at 6.1, 100% at 7 min and held till 7.45 min. A post-run of 1.45 min was added to allow the column to re-equilibrate before the next analysis. This resulted in a total run-time of 9.90 min for analysis of 23 analytes (Additional file 1: Table S1 and Figure 1).
Figure 1

Extracted ion chromatogram (quantifiers only) of 100 μg/L standard mixture in ESI positive. a) caffeine, b) trimethoprim, c) sucralose, d) primidone e) sulfamethoxazole, f) meprobamate, g) triamcinolone, h) hydrocortisone, i) prednisone, j) simazine, k) carbamazepine, l) fluoxetine m) dexamethasone n) TCEP, o) atrazine, p) testosterone, q) norethisterone, r) TCPP, s) norgestrel, t) benzophenone, u) diphenhydramine, v) diltiazem w) DEET. Qualifier ion and surrogate standard chromatograms have been removed for clarity.

The mobile phase for ESI negative used a dual eluent system comprising (A) 5 mM ammonium acetate in ultrapure water and (B) 10/90 (v/v) water/acetonitrile with 5 mM ammonium acetate. With a constant flowrate of 400 μl/min, solvent B was linearly increased from 20% to 96% at 4.5 min and 100% at 5 min. Solvent B was held at 100% for a further 1.3 min then a post-run of 1.5 min at 20% B was added to allow the column to re-equilibrate before the next analysis. This resulted in a total run-time of 7.8 min for the analysis of 13 analytes (Additional file 1: Table S1 and Figure 2). Sample chromatograms for positive and negative ionization modes at 100 ng/mL are shown in Figures 1 and 2.
Figure 2

Extracted ion chromatogram (quantifier only) of 100 μg/L standard mixture in ESI negative. a) PFBA, b)naproxen, c) PFBS, d) diclofenac, e) Ibuprofen, f) PFOA, g) bisphenolA, h) gemfibrozil, i) PFDA, j) PFOS, k) triclocarban, l) triclosan, m) PFHxDA. Qualifier ion and surrogate standard chromatograms have been removed for clarity.

Mass spectrometry

Mass spectrometry was performed using an Agilent 6460 triple quadrupole mass spectrometer. Optimization was done in two steps: compound-specific and source-dependent. Initially, each compound was prepared from a neat standard at a concentration of 1 μg/ml in pure methanol and injected into the mass spectrometer at a flowrate of 500 μl/min. The first quadrupole was set to scan mode and the most intense precursor ion was selected. This was done both in positive and negative electrospray modes to select the most appropriate ion source for each compound. After the best ion source was chosen, the fragmentor voltage was optimized for each compound in scan mode. After this, the mass spectrometer was run in product ion scan (PI Scan) mode to determine the most abundant product. For this, collision energy (CE) of 20 volts was selected and then adjusted in steps of 10 to find the most abundant products. For most compounds, two transitions; a quantifier (the most abundant product) and a qualifier (the second most abundant product) were selected. Then, the mass spectrometer was set to multiple reaction monitoring (MRM) mode and the CE for each product ion was optimized. This was followed by optimization of the cell accelerator voltage (CAV); however, it was noticed that there was a possibility of cross talk between some compounds especially at low CAVs so this value was only optimized between two and seven. The analyte transitions, optimized parameters and retention times are given in Additional file 1: Table S1.

Once all the compound-specific parameters were optimized, source parameters like gas temperature, flow rate, nozzle voltage, nebulizer and capillary voltage were tuned. While, it was not possible to have optimum source parameters to suit all the compounds, best fit values were used in choosing these parameters. The source-dependent parameters for both positive and negative electrospray ionization modes are detailed in Table 2. Analysis in both ESI modes was performed using a dynamic MRM method with a delta retention time of 0.6 min for ESI positive mode and 0.8 min for ESI negative mode.
Table 2

Mass spectrometer source-dependent parameters

Parameter

ESI Positive

ESI Negative

Gas Temperature (°C)

275

225

Gas Flowrate (L/min)

11

10

Nebulizer (psi)

45

45

Sheath Gas Temperature (°C)

375

350

Sheath Gas Flowrate (L/min)

11

11

Capillary (V)

4000

3600

Nozzle Voltage (V)

0

1500

Delta EMV (V)

400

400

Data analysis and interpretation was carried out with the Agilent MassHunter software (version Rev. B.05.00). Along with monitoring the labeled isotope recoveries and the retention time, the ratio of the two transitions was also noted, which increased the accuracy of detection and reduced the possibility of false positives of the method.

Determination of LOD, LOQ and MRL

The instrumental limit of detection (LOD) and limit of quantification (LOQ) were determined for each compound by injecting standards at 0.02, 0.05, 0.1, 0.5, 1, 2.5, 5, 10 and 25 μg/L on the UHPLC-MS/MS system. The LOD and LOQ were defined as the concentration for which the signal to noise ratio (SNR) was greater than 3 and 10 respectively. The LOD and LOQ of all target analytes are shown in Table 3.
Table 3

LOD, LOQ and MRL of target analytes

Compound

LOD (μg/L)

LOQ (μg/L)

Practical MRL (ng/L)

ESI positive

Caffeine

0.5

1

2.5

Trimethoprim

0.05

0.1

0.1

Sucralose

1

5

10

Triamcinolone

1

2.5

5

Primidone

1

2.5

2.5

Sulfamethoxazole

0.02

.1

.5

Meprobamate

0.1

1

2.5

Diphenylhydramine

0.02

0.1

1

Diltiazem

0.02

0.1

0.5

Hydracortisone

0.5

1

2.5

Prednisone

10

15

20

Simazine

0.1

0.5

1

Fluoxetine

0.02

0.05

0.5

Carbamazepine

0.05

0.1

0.25

Dexamethasone

0.05

0.5

1

TCEP

0.5

1

2.5

Atrazine

0.1

0.5

0.5

DEET

0.05

0.1

2.5*

Testosterone

0.5

1

1

Norethistrone

0.1

0.5

1

TCPP

0.05

1

2.5

Norgestrel

0.5

1

2.5

Benzophenone

0.02

0.5

1

ESI negative

PFOA

0.02

0.5

1

PFDA

0.02

0.5

2.5

Gemfibrozil

0.05

0.5

1

PFOS

0.02

0.05

0.1

Triclocarban

0.1

0.5

1

Triclosan

0.5

2.5

5

PFHxDA

0.02

0.1

0.5

PFBS

0.02

0.05

0.5

PFBA

0.02

0.02

NA

Ibuprofen

5

10

15

Bisphenol A

1

5

15

Naproxen

0.1

1

2.5

Diclofenac

0.1

0.5

2.5

NA Not analyzed; * Adjusted for blank.

The method reporting limit (MRL) was determined by extracting nine samples (1 L each) of ultrapure water fortified with the target analytes at 2–3 times the LOQ (calculated from above) and spiked with isotopically-labeled surrogates. After extraction and analysis, the MRL was calculated by multiplying the standard deviation with the student’s t-test value for n-1 degrees of freedom at 99% confidence levels. The results are shown in Table 3. The method reporting limits determined were similar and in many cases lower than previously published literature [29, 43].

Results and discussion

Chromatography

Optimization of chromatographic conditions was achieved by performing experiments with various mixtures of organic solvents and pH modifying buffers. The best mobile phase was chosen based on peak shape, peak resolution and sensitivity achieved for all compounds. Three different UHPLC reverse phase columns were also tested and the column providing the highest sensitivity for most target analytes was chosen. Details of the three columns tested are provided in Additional file 2: Table S2. Once the column and the mobile phase were selected, the gradients in both modes were optimized to achieve best separation of all target analytes while maintaining a sufficient scan speed and peak width to preserve peak shape allowing accurate integration. In addition, different injection volumes (1, 3, 5 and 10 μl) were also tested and 3 μl was used for all analysis as this gave the highest sensitivity without alteration of peak shape.

Analyte ionization and data analysis

All but one compound were ionized by protonation[(M + H)+] of the uncharged molecule in the ESI positive mode. Sucralose was analyzed with the addition of a sodium adduct [(M + Na)+] as the [(M + H)+] ion was essentially absent during optimization of the compound. In the ESI negative mode, all the compounds analyzed were a result of deprotonation [(M-H)-] of the original neutral molecule.

The quantification of TOrCs in all samples was achieved using a calibration curve with at least nine points and an R2 no lower than 0.990 and typically above 0.995. All concentrations above the calibration range were diluted and re-analyzed. In a few instances, it was not possible to determine the exact concentration of an analyte due to loss of isotope signal because of dilution. In this case, concentration were reported as ‘>’ the highest calibration point. While the MRL for all TOrCs was reported in ultrapure water, this value could be impaired in other water matrices containing natural organic matter that interfere with the ionization of the analytes. To account for this, a separate MRL was determined for each sample. Initially, the lowest calibration point was chosen at or slightly above the MRL determined in ultrapure water. Using the Mass Hunter software, the expected concentrations of the calibration curve were recalculated based on the calibration equation and R2 using a linear regression with 1/X weighting. After comparing the calculated concentrations of all the calibration points with expected concentrations, the lowest calibration point with accuracy between 70-130% was chosen for each analyte. This value was then divided by the isotope recovery obtained for all analytes in each sample to obtain the “true” MRL in that particular sample matrix.

Matrix spike and recoveries

Recoveries for the target analytes after extraction were determined using six replicates in three different water matrices shown in Table 4. Matrix spike levels were chosen as 100 ng/L in ultrapure water and 200 ng/L in surface water and wastewater samples. The spike recoveries were calculated by comparing this known spiking concentration with the concentration determined in unspiked samples by internal standard calibration. For ultrapure water, more than 70% of the compounds had a recovery between 90–110%. Only two compounds (diltiazem and PFHxDA) had a recovery of <70%. The recoveries in the surface water varied from 39–121% while wastewater recoveries ranged from 38–141%. While these ranges seem large, it is important to note that isotopically-labeled surrogate standards were not available for every compound. All compounds with a surrogate standard had corrected recoveries between 73–121% with the exception of diclofenac (64%) in the wastewater spike. In fact, almost all these compounds had recoveries of 85 – 115% further validating the use of isotope dilution to correct for matrix suppression and losses during SPE. The recovery of norgestrel and norethisterone were below 60% in the surface water and wastewater spike samples. Previous studies have shown that these two compounds have poor stability on storage greater than three days and this may have led to loss of analyte in the sample [44]. While every effort was made to extract the samples as soon as possible, extraction times varied between 3–14 days during this study. Spike recoveries for hydrocortisone were found to be 50% and 38% in surface water and wastewater respectively. Similar recoveries (~60%) have been seen in a previous study in wastewater [16]. To obtain better recoveries for all compounds, the use of multiple extraction procedures, and considering compound specific properties would be necessary. It was decided to proceed with this single extraction method that provided good recoveries for the majority of the compounds while allowing for significant savings in time and labor. The precision of the entire method was good as the relative standard deviation (RSD) of the replicates for almost all compounds was less than 10% in both ultrapure and surface water. While larger RSDs were observed for wastewater samples, compounds with surrogate standards were still extremely reproducible. Overall, the use of surrogate standards to correct for loss of target analytes during the extraction and analysis stages proved reliable.
Table 4

Matrix spike recoveries for all target analytes in three different waters

Compounds

Ultrapure water

Surface water

WW effluent

 

Recovery (%)

RSD (%)

Recovery (%)

RSD (%)

Recovery (%)

RSD (%)

ESI positive

Caffeine

106

2.5

95

4.3

100

3.9

Trimethoprim

98

2.1

102

0.9

114

3.2

Sucralose

95

5.4

73

34.1

NA

NA

Primidone

97

2.9

96

1.5

113

10.0

Triamcinolone

101

4.7

48

2.3

106

4.3

Sulfamethoxazole

105

3.3

98

1.7

99

2.1

Meprobamate

97

5

74

1.5

99

8.4

Diphenylhydramine

74

5.4

94

5.4

196

3.8

Diltiazem

67

11.7

NA

NA

NA

NA

Hydracortisone

84

3.7

50

7.3

38

11.3

Prednisone

94

4.1

75

5.4

79

10.0

Simazine

99

3

73

2.0

66

2.6

Carbamezapine

101

2.1

117

1.3

98

25.5

Fluoxetine

89

5.5

97

2.3

99

5.5

Dexamethasone

91

2.7

86

2.2

88

3.4

TCEP

108

3.1

71

4.3

119

8.1

Atrazine

100

2.7

94

1.9

99

2.5

DEET

101

2.7

96

1.6

98

5.5

Testosterone

82

3.3

42

2.4

42

21.6

Norethistrone

79

2.4

39

1.9

54

2.1

TCPP

97

2.4

119

2.9

74

7.1

Norgestrel

82

3.2

57

1.3

55

6.7

Benzophenone

71

15.8

95

6.4

93

26.4

ESI negative

PFBA

95

4.6

NA

NA

NA

NA

Naproxen

95

3.5

89

1.4

80

6.0

PFBS

78

7.1

111

8.0

87

3.6

Diclofenac

103

5.4

96

6.0

64

22.0

Ibuprofen

96

9.2

92

5.7

96

10.8

PFOA

101

2.3

121

6.4

115

7.4

Bisphenol A

91

15.5

97

11.6

87

10.8

Gemfibrozil

104

3.7

93

2.7

111

10.0

PFDA

97

3.6

73

15.3

65

13.4

PFOS

107

2.9

94

9.0

89

9.8

Triclocarban

105

2.8

97

1.5

107

5.0

Triclosan

74

1.1

112

2.8

141

6.7

PFHxDA

46

72.4

56

10.4

66

18.4

NA Not Analyzed.

Matrix suppression

The degree of matrix suppression encountered was analyzed by comparing the instrument response (area count) of the 19 isotopically-labeled standards in the matrix spikes and samples with six instrument blanks spiked at the same concentration. The isotope recovery data in each matrix is presented in Table 5. Fluoxetine d5, PFBA 13C4 and diclofenac 13C6 were the only isotopically-labeled compounds to have <60% recovery in ultrapure water. The degree of suppression for most compounds increased in the wastewater matrix (250 mL) compared to the surface water (1000 mL) and ultrapure water (1000 mL) spikes even though less volume of the sample was extracted. The RSD for all analytes was below 15% and in most cases below 5%.
Table 5

Percent recovery of isotopically labeled standards in different water matrixes (n = 6)

Compound

Ultrapure water (1000 ml)

Surface water (1000 ml)

WWTP effluent (250 ml)

 

Recovery (%)

RSD (%)

Recovery (%)

RSD (%)

Recovery (%)

RSD (%)

Carbamezapine d10

77

4.4

79

2.6

70

4.9

Caffeine 13C3

79

4.7

76

3.2

56

4.5

Trimethoprim d3

67

4.2

66

3.1

41

6.4

Sucralose d6

65

5.9

31

3.3

16

4.0

Primidone d5

81

3.1

71

4.0

74

4.3

Sulfamethoxazole 13C6

80

3.6

30

4.6

28

6.6

Atrazine d5

70

3.1

59

4.1

64

3.9

Fluoxetine d5

40

8.3

35

6.8

40

10.7

DEET d6

60

9.2

70

6.8

75

10.8

PFBA 13C4

15

2.1

13

3.4

10

5.2

Naproxen 13C1d3

87

4.5

94

3.6

75

6.2

Diclofenac 13C6

48

1.5

30

7.5

31

14.5

Ibuprofen d3

86

6.5

103

4.7

90

6.5

PFOA 13C4

90

3.1

115

14.3

104

0.3

Bisphenol A 13C12

92

6.9

70

7.8

83

11.0

Gemfibrozil d6

86

3.1

94

4.6

117

4.9

PFOS 13C4

83

4.2

78

7.7

81

5.7

Triclocarban 13C6

61

7.5

63

3.3

54

5.7

Triclosan d3

122

4.5

81

3.9

68

5.1

Blank analysis

As extremely low levels of analytes are quantified in this method, there was a possibility of contamination through various sources. Potential contamination may arise from presence of trace levels of native compound in the isotopically-labeled standards, presence of contamination in the instrument, and low-level contamination from various external sources. Initially pure methanol was injected in both ESI modes to detect the presence of any background contamination due to the solvent or instrument (Additional file 3: Figure S1 and Additional file 4: Figure S2). The target analytes were not found to be present with the exception of DEET. Next methanol blanks were fortified with the isotopically-labeled standards to determine if native compounds were introduced by the isotopes. No indication of target analyes was found in these blanks with the exception of DEET. The area counts of the DEET chromatograms present in the first two types of blanks was very similar indicating that the DEET detected was in the background and not introduced by the isotopically-labeled standard (Additional file 5: Figure S3). The concentration of DEET in the blanks was estimated using the MRL study calibration curve and subsequently the MRL for DEET was increased five times to prevent reporting of false positives. Finally, a number (n = 6) of ultrapure water samples fortified with labeled isotopes were extracted by SPE and analyzed to ensure the absence of unlabeled compounds through the extraction procedure. Further, routine fortified ultrapure water blanks were analyzed along with the samples to check for any contamination. All blanks tested during the course of the study were below MRLs.

Occurrence in water

To demonstrate the applicability of this method, samples from three WWTPs, a drinking water treatment plant (DWTP), one ground water and two surface waters (Colorado River and Sacramento River) from around the United States were analyzed. Samples from the three wastewater treatment plants were also analyzed at different treatment points to study treatment efficacy. A summary of the treatment trains for each plant is shown in Additional file 6: Table S3. WWTP 1 served a largely urban population (approximately 500,000 people) with both domestic and industrial contribution. WWTP 2 served a considerably smaller population (approximately 17,000) with 73% of the population aged 65 or older (median age of 72 years). WWTP 3 has a capacity of approximately 70 million gallons per day (MGD) and has a predominantly domestic source of wastewater contribution. Thus, the three plants offered significantly different qualities of wastewater to be tested. DWTP 4 is an indirect potable reuse plant that receives treated wastewater effluent as its source water. The occurrence data for all 36 TOrCs at different treatment points in the four plants is shown in Table 6 along with the sample volume extracted.
Table 6

Occurrence of TOrCs in different water matrices

Compound

WWTP 1a

WWTP 1b

WWTP 2

WWTP 3

DWTP 4

 
 

After GF

After AS

Dechlorinated final effluent

After AAS

GMF effluent

After UV

After bar screens

After BNROD

After sand filter

After chlorination

Influent

PostF/S

Post AS

Dechlorinated final effluent

Influent

Post MF

Post RO

Post UV

Sacramento River

Colorado River

Tucson GW

Volume Extracted (ml)

250

500

500

500

500

500

250

250

500

500

250

250

250

500

250

500

1000

1000

1000

1000

1000

Pharmaceuticals

                     

Carbamezapine

260

230

230

270

270

260

580

470

460

400

1620

1760

580

590

180

190

<0.5

<0.5

<0.5

1

<0.5

Diclofenac

96

<15

<15

78

34

<15

830

530

420

14

340

370

280

260

120

70

<8

<8

<8

<8

<8

Diltiazem

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

280

280

130

59

240

140

75

73

<2

<2

<2

Diphenhydramine

1620

1480

1090

280

320

310

25

15

27

<7

<73

<19

<9

<5

470

420

<1

<1

<1

<1

<1

Fluoxetine

160

32

57

41

44

24

79

38

23

34

88

110

89

84

<9

<7

<1

<1

<1

<1

<1

Gemfibrozil

2750

2380

2190

36

38

37

>6000

400

230

190

5550

5300

75

120

680

540

<1

<1

<1

<1

<1

Ibuprofen

>6000

1810

1590

41

41

52

>6000

50

<50

<30

3780

3410

<15

<15

180

120

<15

<15

<15

<15

<15

Meprobamate

1600

650

480

680

670

610

597

421

570

190

690

540

340

280

375

360

<3

<3

<3

3

<3

Naproxen

>6000

550

300

11

10

4

>6000

114

28

6

4740

4170

24

30

970

460

<3

<3

<3

<3

<3

Primidone

200

180

190

170

170

160

1120

620

580

580

370

370

300

300

<20

<8

<4

<4

<4

<4

<3

Sulfamethoxazole

2290

840

1130

1630

1510

990

6080

3910

3010

39

4040

3280

1640

860

590

590

1

1

1

5

<1

Trimethoprim

1110

930

850

130

130

130

1370

30

12

<2

1510

1420

280

200

830

810

<0.5

<0.5

<0.5

1

<0.5

Personal-care Products

Benzophenone

6300

2320

1710

650

380

300

4540

310

310

220

1670

1640

340

250

880

280

150

130

114

15

21

Bisphenol A

640

140

320

<90

<80

<40

350

20

57

36

240

240

30

<25

69

<20

<20

<20

<20

<20

<20

Caffeine

12000

340

490

6

5

15

6000

22

10

<8

13680

11320

12

12

11

10

<3

<3

4

14

<3

DEET

3570

540

630

46

45

44

2250

190

170

160

700

350

110

130

93

220

<3

<3

5

5

3

Sucralose

32000

23000

15000

15600

14400

13500

9000

8170

7570

7950

23000

21000

19000

19000

25000

23000

38

34

47

620

<31

TCEP

780

690

650

380

350

330

550

330

320

260

630

460

400

370

  

<3

<3

<3

<3

<3

TCPP

1650

2900

3040

2970

2760

2380

5670

3870

3410

2910

2000

2040

2080

2050

730

1060

<3

<3

11

9

3

Triclocarban

330

31

42

62

96

38

740

200

68

110

580

520

120

9

50

87

<2

<2

<2

<2

<2

Triclosan

2250

440

162

85

71

28

4640

103

69

15

1790

2000

52

29

<39

<13

<6

<6

<6

<6

<6

Perfluorinated compounds

PFBA

<7

<3

<3

<3

<3

<3

<32

<19

<4

<3

NA

NA

NA

NA

10

9

7

<3

<3

<3

<3

PFBS

17

10

9

13

14

10

24

9

8

5

<5

<4

<3

<3

<3

<2

<1

<1

<1

<1

<1

PFOA

9

7

9

11

45

24

0

46

49

60

<40

<31

<21

<10

<4

<2

<1

<1

<1

<1

<1

PFOS

1080

200

190

5

3

2

460

3

2

4

16

9

10

9

530

290

200

<1

<1

<1

<1

PFDA

<13

<8

<7

<7

<7

<6

<11

<10

<10

<5

<12

<10

<10

<10

<12

<6

<3

<3

<3

<3

<3

PFHxDA

<3

<2

<2

<2

<2

<2

<6

<4

<4

<1

<11

<10

<9

<9

<3

<2

<1

<1

<1

<1

<1

Glucocorticoid

                     

Dexamethasone

19

<14

<10

<22

<14

<10

94

<77

<26

<18

<61

<11

<7

<6

<44

<20

<1

<1

<1

<1

<1

Hydrocortisone

<20

<12

<11

<48

<11

<11

NA

<150

<64

<46

<17

<15

<7

<5

<90

<50

<4

<4

<4

7

<5

Prednisone

<165

<61

20

<61

<59

<28

59

NA

NA

NA

NA

<30

<25

<25

<700

<200

<25

<25

<25

<25

<25

Triamcinolone

<55

<23

<21

<27

<21

<21

24

<14

<12

<7

<61

<54

<26

<12

<200

<80

<7

<7

<7

<7

<6

Pesticides

                     

Atrazine

<10

<9

<2

<2

<2

<2

<20

<3

<2

<2

<3

<2

<2

<1

<19

<6

<1

<1

<1

<1

<1

Simazine

<21

<3

<2

<3

<3

<2

<40

<6

4

3

<6

<4

<2

<2

<38

<12

<2

<2

<2

2

<2

Androgen

                     

Testosterone

14

<2

<2

15

14

<2

15

4

3

<2

<11

<8

<5

<2

9

9

<1

<1

<1

<2

<1

Progestin

                     

Norethistrone

<19

<16

<5

<5

<4

<2

100

6

<5

<5

<30

<7

<3

<2

<18

<7

<3

<3

<3

<3

<3

Norgestrel

93

10

8

18

5

4

19

6

7

3

620

230

<3

<2

110

110

<4

<4

<3

<3

<3

Attached excel file to be placed in main text.

NA Not analyzed.

Sucralose (9000–32000 ng/L) and caffeine (6000–13280 ng/L) were present at the highest concentration in the influent of all WWTPs. All pharmaceuticals analyzed in the influent of the three WWTPs were detected with the exception of diphenhydramine in WWTP 3. Concentrations of diabetes and heart-related pharmaceuticals like gemfibrozil, diclofenac, and primidone were significantly higher in the raw sewage of WWTP 2 (the plant serving the dominantly elderly community) compared to the other two WWTPs. Conversely, industrial compounds like benzophenone, PFOS, DEET, and bisphenol A were found at higher concentrations in WWTP 1, potentially confirming the significant industrial input.

The mean effluent concentrations in all WWTPs of artificial sweetener sucralose (13,860) and flame-retardant TCPP (2595 ng/L) were extremely high compared to the other analyzed TOrCs. Their concentrations remained fairly constant throughout the plant indicating that they may be robust and suitable markers for wastewater influence in drinking water sources. Six pharmaceuticals (carbamazepine, gemfibrozil, meprobamate, naproxen, primidone and sulfamethoxazole) were detected in the effluent of all WWTPs with mean concentrations between 85–755 ng/L. Average concentration of sulfamethoxazole (755 ng/L) and gemfibrozil (634 ng/L) were highest in the WWTP effluent for pharmaceuticals. The GR compounds were present at significantly lower concentrations in the influent and not detected in the final effluent in all three WWTPs. However, these compounds still need to be monitored closely as even trace amounts have been shown to have adverse effects to wildlife [8, 45]. PFOS was the dominant PFC in terms of detection and concentration while the longer chain PFCs (PFDA and PFHxDA) were not detected at any point in all three WWTPs. PFBS was detected in the effluent of two WWTPs (1 and 2) but at concentration <10 ng/L while PFBA was not detected in any of the effluent samples. Norgestrel was the more frequently detected progestin, present in two effluent WWTP samples (WWTP 1 and 2), while norethisterone was never detected in the effluent. The pesticide atrazine was not detected in any of the samples analyzed throughout the study.

To study the treatment efficacy of the WWTPs, samples were collected at different points in the plant. Further, WWTP 1 had water split into two parallel trains after primary treatment: conventional (activated sludge followed by chlorination) and advanced (advanced air activated sludge, granular media filtration and UV disinfection). The biggest factor in removal of TOrCs between the two treatment trains in WWTP 1 was the type of activated sludge (AS) used. The advanced air activated sludge (AAS) process provided significantly lower concentration of most TOrCs as compared to the AS effluent in the conventional train. The sand filter in WWTP 2 did not have much attenuation of TOrCs, similar to previous literature [46]. Compounds like diclofenac, sulfamethoxazole, naproxen, and triclosan were well removed by the free chlorine disinfection step which is consistent with previously published literature [6]. Conversely, compounds such as DEET, TCPP, TCEP and caffeine are known to be recalcitrant at chlorine doses supplied in conventional treatment plants and hence were not well removed in the chlorination step in both treatment plants. The UV disinfection process (in WWTP 1b) was not very effective in attenuation of TOrCs without the addition of hydrogen peroxide. In DWTP 4, very few TOrCs were attenuated by micro-filtration process, which is consistant with previous literature [47]. However, almost no traces of any TOrCs were detected after the reverse osmosis (RO) process. Only six (benzophenone, diltiazem, PFBA, PFOS, sucralose and sulfamethoxazole) of the 36 measured TOrCs were present after RO treatment in DWTP 4. Of these six, only benzophenone and PFOS were present at concentrations >100 ng/L.

Two surface waters from the Colorado River (sampled at Avra Valley, AZ through the CAP canal) and Sacramento River were analyzed using this method. Eleven target compounds were detected in the Colorado River water while seven were seen in the Sacramento River sample. Six of the target analytes (sucralose, meprobamate, caffeine, DEET, TCPP and benzophenone) were common to both waters. Sucralose was present at the highest concentration in the Colorado River samples at 620 ng/L while in the Sacramento River sample it was measured at 47 ng/L. Commercially used compounds like benzophenone and TCPP were detected at higher concentrations in the Sacramento river while all the other analytes detected were higher in the Colorado River sample. The groundwater sample collected from Tucson had trace amounts of DEET and TCPP (<5 ng/L), and benzophenone at 21 ng/L but all other TOrCs were not detected. Although the sampling events were limited, the data generally correlate with previous studies and hence prove the viability of the analytical method.

Conclusion

The analytical method presented above allows for rapid, high-throughput detection and quantitation of up to 36 TOrCs including pharmaceuticals, personal care products and steroid hormones using UHPLC-MS/MS. The use of a single all-inclusive SPE method coupled to UHPLC MS/MS provides significant time and labor savings while achieving reporting limits of low ng/L for all analytes. The method has been applied to a wide-range of aqueous matrices. The authors suggest using routine blank analysis, matrix spike recoveries and isotopically-labeled standards for obtaining most accurate results when analyzing different water matrixes.

Abbreviations

CAV: 

Cell accelerator voltage

CE: 

Collision energy

DEET: 

N,N-Diethyl-meta-toluamide

DWTP: 

Drinking water treatment plant

ESI: 

Electrospray ionization

GC: 

Gas chromatography

GRs: 

Glucocorticoids

LC: 

Liquid chromatography

LOD: 

Limit of detection

LOQ: 

Limit of quantification

MRL: 

Method reporting limit

MS: 

Mass spectrometry

PFBA: 

Perfluoro butyric acid

PFBS: 

Perfluoro butane sulfonate

PFC: 

Polyfluorinated chemical

PFDA: 

Perfluoro decanoic acid

PFHxDA: 

Perfluoro hexadecanoic acid

PFOA: 

Perfluoro octanoic acid

PFOS: 

Perfluoro octane sulfonate

RO: 

Reverse osmosis

SPE: 

Solid-phase extraction

TCEP: 

Tris (2-chloroethyl) phosphate

TCPP: 

Tris (2-chloropropyl) phosphate

TOrC: 

Trace organic contaminant.

Declarations

Acknowledgements

The authors would like to thank the participating utilities particularly Chris Hill from Metro Water for technical assistance in sample collection and transport. We also thank Dr. Armando Durazo, Shimin Wu and Massimiliano Sgroi from the University of Arizona for assistance with solid-phase extraction and sample preparation. The authors are also grateful to Agilent Technologies for providing technical support during method development.

Authors’ Affiliations

(1)
Department of Chemical & Environmental Engineering, University of Arizona
(2)
School of Applied Sciences, RMIT University

References

  1. Kolpin DW, Furlong ET, Meyer MT, Thurman EM, Zaugg SD, Barber LB, Buxton HT: Pharmaceuticals, hormones, and other organic wastewater contaminants in US streams, 1999–2000: a national reconnaissance. Environ Sci Technol. 2002, 36 (6): 1202-1211. 10.1021/es011055j.View ArticleGoogle Scholar
  2. Snyder SA, Westerhoff P, Yoon Y, Sedlak DL: Pharmaceuticals, personal care products, and endocrine disruptors in water: implications for the water industry. Environ Eng Sci. 2003, 20 (5): 449-469. 10.1089/109287503768335931.View ArticleGoogle Scholar
  3. Focazio MJ, Kolpin DW, Barnes KK, Furlong ET, Meyer MT, Zaugg SD, Barber LB, Thurman ME: A national reconnaissance for pharmaceuticals and other organic wastewater contaminants in the United States - II) Untreated drinking water sources. Sci Total Environ. 2008, 402 (2–3): 201-216.View ArticleGoogle Scholar
  4. Benotti MJ, Trenholm RA, Vanderford BJ, Holady JC, Stanford BD, Snyder SA: Pharmaceuticals and endocrine disrupting compounds in US drinking water. Environ Sci Technol. 2009, 43 (3): 597-603. 10.1021/es801845a.View ArticleGoogle Scholar
  5. Snyder S, Westerhoff P, Yoon Y, Vanderford B, Rexing D: Evaluation of conventional and advanced treatment processes to remove endocrine disruptors and pharmaceutically active compounds. Abstr Pap Am Chem Soc. 2004, 228: 184-ENVRGoogle Scholar
  6. Westerhoff P, Yoon Y, Snyder S, Wert E: Fate of endocrine-disruptor, pharmaceutical, and personal care product chemicals during simulated drinking water treatment processes. Environ Sci Technol. 2005, 39 (17): 6649-6663. 10.1021/es0484799.View ArticleGoogle Scholar
  7. Snyder SA, Wert EC, Lei H, Westerhoff P, Yoon Y: Removal of EDCs and Pharmaceuticals in Drinking and Reuse Treatment Processes. 2007, Denver, CO: American Water Works Association Research FoundationGoogle Scholar
  8. Bevans HE, Goodbred SL, Miesner JF, Watkins SA, Gross TS, Denslow ND, Trenton C: Synthetic organic compounds and carp endocrinology and histology, Las Vegas Wash and Las Vegas and Callville Bays of Lake Mead Nevada, 1992 and 1995: U.S. Geological Survey Water-Resources Investigations Report. 1995, 96-4266. 12 accessible at: http://pubs.er.usgs.gov/publication/wri964266,Google Scholar
  9. Daughton CG, Ternes TA: Pharmaceuticals and personal care products in the environment: agents of subtle change?. Environ Health Perspect. 1999, 107: 907-938. 10.1289/ehp.99107s6907.View ArticleGoogle Scholar
  10. Carlsson C, Johansson AK, Alvan G, Bergman K, Kuhler T: Are pharmaceuticals potent environmental pollutants? Part I: environmental risk assessments of selected active pharmaceutical ingredients. Sci Total Environ. 2006, 364 (1–3): 67-87.View ArticleGoogle Scholar
  11. Snyder SA, Villeneuve DL, Snyder EM, Giesy JP: Identification and quantification of estrogen receptor agonists in wastewater effluents. Environ Sci Technol. 2001, 35 (18): 3620-3625. 10.1021/es001254n.View ArticleGoogle Scholar
  12. Stanford BD, Snyder SA, Trenholm RA, Holady JC, Vanderford BJ: Estrogenic activity of US drinking waters: a relative exposure comparison. J Am Water Work Assoc. 2010, 102 (11): 55-65.Google Scholar
  13. Ryu J, Yoon Y, Oh J: Occurrence of endocrine disrupting compounds and pharmaceuticals in 11 WWTPs in Seoul, Korea. KSCE J Civ Eng. 2011, 15 (1): 57-64. 10.1007/s12205-011-0913-6.View ArticleGoogle Scholar
  14. Chang H, Hu JY, Shao B: Occurrence of natural and synthetic glucocorticoids in sewage treatment plants and receiving river waters. Environ Sci Technol. 2007, 41 (10): 3462-3468. 10.1021/es062746o.View ArticleGoogle Scholar
  15. Herrero P, Borrull F, Pocurull E, Marce RM: Determination of glucocorticoids in sewage and river waters by ultra-high performance liquid chromatography-tandem mass spectrometry. J Chromatogr A. 2012, 1224: 19-26.View ArticleGoogle Scholar
  16. Schriks M, van Leerdam JA, van der Linden SC, van der Burg B, van Wezel AP, de Voogt P: High-resolution mass spectrometric identification and quantification of glucocorticoid compounds in various wastewaters in the Netherlands. Environ Sci Technol. 2010, 44 (12): 4766-4774. 10.1021/es100013x.View ArticleGoogle Scholar
  17. Quinones O, Snyder SA: Occurrence of perfluoroalkyl carboxylates and sulfonates in drinking water utilities and related waters from the United States. Environ Sci Technol. 2009, 43 (24): 9089-9095. 10.1021/es9024707.View ArticleGoogle Scholar
  18. Mak YL, Taniyasu S, Yeung LWY, Lu GH, Jin L, Yang YL, Lam PKS, Kannan K, Yamashita N: Perfluorinated compounds in tap water from China and several other countries. Environ Sci Technol. 2009, 43 (13): 4824-4829. 10.1021/es900637a.View ArticleGoogle Scholar
  19. Clarke BO, Smith SR: Review of ‘emerging’ organic contaminants in biosolids and assessment of international research priorities for the agricultural use of biosolids. Environ Int. 2011, 37 (1): 226-247. 10.1016/j.envint.2010.06.004.View ArticleGoogle Scholar
  20. Zhang T, Wu Q, Sun HW, Zhang XZ, Yun SH, Kannan K: Perfluorinated compounds in whole blood samples from infants, children, and adults in China. Environ Sci Technol. 2010, 44 (11): 4341-4347. 10.1021/es1002132.View ArticleGoogle Scholar
  21. Contaminant Candidate List 3. http://water.epa.gov/scitech/drinkingwater/dws/ccl/ccl3.cfm,
  22. Lau C, Butenhoff JL, Rogers JM: The developmental toxicity of perfluoroalkyl acids and their derivatives. Toxicol Appl Pharmacol. 2004, 198 (2): 231-241. 10.1016/j.taap.2003.11.031.View ArticleGoogle Scholar
  23. Lau C, Anitole K, Hodes C, Lai D, Pfahles-Hutchens A, Seed J: Perfluoroalkyl acids: a review of monitoring and toxicological findings. Toxicol Sci. 2007, 99 (2): 366-394. 10.1093/toxsci/kfm128.View ArticleGoogle Scholar
  24. Directive. 2006, http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2006:372:0032:0034:en:PDF, /122/EC of the European Parliament and of the council of 12 December 2006,
  25. Wilhelm M, Bergmann S, Dieter HH: Occurrence of perfluorinated compounds (PFCs) in drinking water of North Rhine-Westphalia, Germany and new approach to assess drinking water contamination by shorter-chained C4-C7 PFCs. Int J Hyg Environ Health. 2010, 213 (3): 224-232. 10.1016/j.ijheh.2010.05.004.View ArticleGoogle Scholar
  26. Hinton TG, Aizawa K: A Layperson’s Primer on Multiple Stressors, Chapter 5. Multiple Stressors: A Challenge for the Future. 2007, 57-69.View ArticleGoogle Scholar
  27. Dickenson ERV, Snyder SA, Sedlak DL, Drewes JE: Indicator compounds for assessment of wastewater effluent contributions to flow and water quality. Water Res. 2011, 45 (3): 1199-1212. 10.1016/j.watres.2010.11.012.View ArticleGoogle Scholar
  28. Ternes TA: Analytical methods for the determination of pharmaceuticals in aqueous environmental samples. Trac-Trends Anal Chem. 2001, 20 (8): 419-434. 10.1016/S0165-9936(01)00078-4.View ArticleGoogle Scholar
  29. Trenholm RA, Vanderford BJ, Drewes JE, Snyder SA: Determination of household chemicals using gas chromatography and liquid chromatography with tandem mass spectrometry. J Chromatogr A. 2008, 1190 (1–2): 253-262.View ArticleGoogle Scholar
  30. Stafiej A, Pyrzynska K, Regan F: Determination of anti-inflammatory drugs and estrogens in water by HPLC with UV detection. J Sep Sci. 2007, 30 (7): 985-991. 10.1002/jssc.200600433.View ArticleGoogle Scholar
  31. Morishima Y, Hirata Y, Jinno K, Fujimoto C: Solid-phase extraction device coupled to a microcolumn liquid chromatograph with a UV detector for determining estrogens in water samples. J Liq Chromatogr Relat Technol. 2005, 28 (20): 3217-3228. 10.1080/10826070500330901.View ArticleGoogle Scholar
  32. Zotou A, Miltiadou N: Sensitive LC determination of ciprofloxacin in pharmaceutical preparations and biological fluids with fluorescence detection. J Pharm Biomed Anal. 2002, 28 (3–4): 559-568.View ArticleGoogle Scholar
  33. Zotou A, Vasiliadou C: A fluorescence-LC method for the determination of sulfonamides in biological fluids with pre-column derivatization. Chromatographia. 2009, 70 (3–4): 389-397.View ArticleGoogle Scholar
  34. Lindsey ME, Meyer M, Thurman EM: Analysis of trace levels of sulfonamide and tetracycline antimicrobials, in groundwater and surface water using solid-phase extraction and liquid chromatography/mass spectrometry. Anal Chem. 2001, 73 (19): 4640-4646. 10.1021/ac010514w.View ArticleGoogle Scholar
  35. La Farre M, Ferrer I, Ginebreda A, Figueras M, Olivella L, Tirapu L, Vilanova M, Barcelo D: Determination of drugs in surface water and wastewater samples by liquid chromatography-mass spectrometry: methods and preliminary results including toxicity studies with Vibrio fischeri. J Chromatogr A. 2001, 938 (1–2): 187-197.View ArticleGoogle Scholar
  36. Bossi R, Vejrup KV, Mogensen BB, Asman WAH: Analysis of polar pesticides in rainwater in Denmark by liquid chromatography-tandem mass spectrometry. J Chromatogr A. 2002, 957 (1): 27-36. 10.1016/S0021-9673(02)00312-6.View ArticleGoogle Scholar
  37. Gros M, Petrovic M, Barcelo D: Development of a multi-residue analytical methodology based on liquid chromatography-tandem mass spectrometry (LC-MS/MS) for screening and trace level determination of pharmaceuticals in surface and wastewaters. Talanta. 2006, 70 (4): 678-690. 10.1016/j.talanta.2006.05.024.View ArticleGoogle Scholar
  38. Ternes T, Bonerz M, Schmidt T: Determination of neutral pharmaceuticals in wastewater and rivers by liquid chromatography-electrospray tandem mass spectrometry. J Chromatogr A. 2001, 938 (1–2): 175-185.View ArticleGoogle Scholar
  39. Tong L, Li P, Wang YX, Zhu KZ: Analysis of veterinary antibiotic residues in swine wastewater and environmental water samples using optimized SPE-LC/MS/MS. Chemosphere. 2009, 74 (8): 1090-1097. 10.1016/j.chemosphere.2008.10.051.View ArticleGoogle Scholar
  40. Vanderford BJ, Pearson RA, Rexing DJ, Snyder SA: Analysis of endocrine disruptors, pharmaceuticals, and personal care products in water using liquid chromatography/tandem mass spectrometry. Anal Chem. 2003, 75 (22): 6265-6274. 10.1021/ac034210g.View ArticleGoogle Scholar
  41. Trenholm RA, Vanderford BJ, Holady JC, Rexing DJ, Snyder SA: Broad range analysis of endocrine disruptors and pharmaceuticals using gas chromatography and liquid chromatography tandem mass spectrometry. Chemosphere. 2006, 65 (11): 1990-1998. 10.1016/j.chemosphere.2006.07.004.View ArticleGoogle Scholar
  42. Vanderford BJ, Mawhinney DB, Trenholm RA, Zeigler-Holady JC, Snyder SA: Assessment of sample preservation techniques for pharmaceuticals, personal care products, and steroids in surface and drinking water. Anal Bioanal Chem. 2011, 399 (6): 2227-2234. 10.1007/s00216-010-4608-5.View ArticleGoogle Scholar
  43. Maldaner L, Jardim I: Determination of some organic contaminants in water samples by solid-phase extraction and liquid chromatography tandem mass spectrometry. Talanta. 2012, 100: 38-44.View ArticleGoogle Scholar
  44. Aboulfadl K, De Potter C, Prevost M, Sauve S: Time-dependent integrity during storage of natural surface water samples for the trace analysis of pharmaceutical products, feminizing hormones and pesticides. Chem Cent J. 2010, 4 (1): 10-10.1186/1752-153X-4-10.View ArticleGoogle Scholar
  45. Sanderson H, Johnson DJ, Reitsma T, Brain RA, Wilson CJ, Solomon KR: Ranking and prioritization of environmental risks of pharmaceuticals in surface waters. Regul Toxicol Pharmacol. 2004, 39 (2): 158-183. 10.1016/j.yrtph.2003.12.006.View ArticleGoogle Scholar
  46. Boleda MR, Galceran MT, Ventura F: Behavior of pharmaceuticals and drugs of abuse in a drinking water treatment plant (DWTP) using combined conventional and ultrafiltration and reverse osmosis (UF/RO) treatments. Environ Pollut. 2011, 159 (6): 1584-1591. 10.1016/j.envpol.2011.02.051.View ArticleGoogle Scholar
  47. Snyder SA, Adham S, Redding AM, Cannon FS, DeCarolis J, Oppenheimer J, Wert EC, Yoon Y: Role of membranes and activated carbon in the removal of endocrine disruptors and pharmaceuticals. Desalination. 2007, 202 (1–3): 156-181.View ArticleGoogle Scholar

Copyright

© Anumol et al.; licensee Chemistry Central Ltd. 2013

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.