Husam I. S. Kafeenaha,
Rozita Osmanb and
N. K. A. Bakar*a
aDepartment of Chemistry, Faculty of Science, University of Malaya, 50603 Kuala Lumpur, Malaysia. E-mail: kartini@um.edu.my
bFaculty of Applied Sciences, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia
First published on 3rd December 2018
In this work, a new clean-up and pre-concentration method based on disk solid-phase extraction (SPE) was developed to determine multi-class pharmaceutical residues covering a wide range of polarities (logKow values from −0.5 to 5.1) in water systems, prior to ultra-performance liquid chromatographic-tandem mass spectrometry (UPLC-MS/MS) analyses. Electrospray ionisation in positive and negative modes was used for the simultaneous determination of both acidic and basic pharmaceuticals. The performances of disk SPE and cartridge SPE were compared. The targeted pharmaceutical compounds list included bronchodilators, antidiabetic drugs, antihypertensive drugs, a lipid-lowering agent, analgesics, and anti-inflammatory drugs. Based on our results, the disk SPE demonstrated a higher sensitivity and recovery value and less analysis time as compared to the cartridge SPE method. The limits of detection (LOD) for the new method ranged from 0.02–3.2 ng L−1, 0.02–3.1 ng L−1 and 0.02–4.7 ng L−1 for tap, effluent and influent wastewater, respectively. The method's absolute recovery values ranged from 70% to 122% for tap water, 62% to 121% for effluent wastewater and 62% to 121% for influent wastewater, except for metformin in which the absolute recovery value was approximately 48% for all samples. Intra-day precision for tap water, effluent and influent wastewater ranged from 3–12%, 4–9% and 2–8%, respectively. The method developed was applied for the determination of targeted pharmaceuticals in tap, effluent, and influent wastewater from one hospital treatment plant in Malaysia. The results revealed that the highest concentrations of certain pharmaceuticals were up to 49424 ng L−1 (acetaminophen) and 1763 ng L−1 (caffeine) in the influent and effluent wastewater, respectively. The results also showed a variation in the treatment efficiencies for the hospital treatment plant from one compound to another. Nevertheless, the removal efficiencies ranged from 0–99%.
Several SPE formats have been developed in order to suit the different types of samples starting from simple packed disposable syringes to cartridges, disks, SPE pipette tips, 96-well, and 384-well microplates.13 The SPE cartridge is the most popular SPE format in water analyses.14–16 Most of the previous studies used cartridge formats in SPE clean-up, despite a lot of drawbacks when applied in real samples such as the high potential for blockage and the low flow rate (due to the small cross-sectional area in the packing material) that lead to the increase in the analysis time and difficulty handling large volumes of sample.7,17–19 Moreover, the capacity to retain the analytes is low as a result of the large particle size of the packing material in the cartridge. In order to overcome these drawbacks, SPE disk formats have been developed to enhance the extraction performance. SPE disks are made of rigid glass or PTFE fibre material embedded with bonded silica or polymer and the sorbent material. The sorbent particles embedded in the disks are smaller than those in the cartridges (8 μm diameter rather than 40 μm to 60 μm). Smaller disk particle size allows for more interaction between the analytes and the sorbent material. Therefore, the SPE disk is more prone to have efficient trapping of analytes from the water sample, which leads to enhancing the recovery of the methods.18 Furthermore, the short sample path and small particle size in the disk allow the use of greater volume with high flow rates of samples (even the unfiltered samples) and reduce the eluting material amount, which means improving the limit of detection and quantification without increasing the analysis time and at the same time reducing the risk of plugging.17 Several studies have confirmed good recoveries and performance in determining herbicides and pesticides in water by using SPE disks.5,6,20–23
High-performance liquid chromatography-mass spectrometry is one of the most popular instruments in pharmaceutical analysis.24 Studies have been conducted in order to improve the liquid chromatography-mass spectrometry (LC-MS) technology and overcome the limitations.25,26 One of these limitations is the difficulty in running acidic and basic compounds simultaneously, due to the requirements for different ionisation modes for different compounds; acidic compounds require a negative ionisation mode and basic compounds operate in positive ionisation mode. With an increase in switching speed between the negative and positive modes in ESI-LC-MS, a new method that simultaneously employs both the negative and positive electrospray ionisations (ESI) was developed to obtain the maximum amount of information in a short time and with good sensitivity for a wide variety of compounds with different physicochemical properties.27,28
Most of the previous research in pharmaceutical analysis targeted compounds belonging to one or two pharmaceutical classes with similar properties, while only a few studies targeted multi-class pharmaceutical compounds in wastewater. The detection of multi-class pharmaceuticals with different physicochemical properties could reduce the efficiency of the extraction process, thereby reducing the sensitivity of the detection of such compounds as a consequence of different polarities being retained differently on the adsorbent when preparing the sample. The more chemically different the analytes are, the more difficult it is to develop the analytical method with acceptable recovery and sensitivity for their detection in a matrix. Most of the previous research attempted to enhance the extraction efficiency of multi-class pharmaceuticals by testing different adsorbing materials. To the best of the authors' knowledge, none of the previous studies have tried to improve the extraction efficiency of multi-class pharmaceutical residues in water by testing different formats of SPE (cartridges and disk).29–32 No previous study has been carried out for water analysis with this level of sensitivity involving groups of pharmaceuticals with variations in properties such as pKa ranging from 3.7 (perindopril) to 12.4 (metformin) and a wide range of polarities, with logKow ranging from −0.5 to 5.12. This is also the first SPE method used for the detection of metformin in water samples with this level of sensitivity.
In this work, the performances of the disk SPE and cartridge SPE were compared to determine the more efficient SPE format for the clean-up and pre-concentration of 10 multi-class pharmaceuticals with a wide range of polarities from water samples, and thus a sensitive analytical method for the determination of multi-class pharmaceuticals was developed. The properties and classes of the pharmaceutical compounds, including bronchodilators, antidiabetic drugs, antihypertensive drugs, lipid-lowering agents, analgesics and anti-inflammatories are given in Table 1 (ref. 33) and Fig. S1 (ESI†). Ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) utilising triple quadrupole (QQQ) mass spectrometry was employed as a detector. Both positive and negative ionisation modes in electrospray ionisation (ESI) were used simultaneously. The developed method was used investigate the occurrence of these pharmaceuticals in tap water, effluent, and influent wastewater samples, and the efficiency of the removal process in a hospital wastewater treatment plant was assessed.
Compound name | Application origin | MW | logKow | pKa | Molecular formula | Water solubility (at 25 °C) mg L−1 |
---|---|---|---|---|---|---|
a Source (The DrugBank Database).33 | ||||||
Acetaminophen | Analgesics/anti-inflammatories | 151.1 | 0.4 | 9.8 | C8H9NO2 | 1.4 × 104 |
Caffeine | Stimulants/caffeine metabolites | 194.1 | −0.1 | 10.4 | C8H10N4O2 | 2.2 × 104 |
Diclofenac | Analgesics/anti-inflammatories | 296.1 | 4.5 | 4.2 | C14H11Cl2O2 | 2.4 |
Ibuprofen | Analgesics/anti-inflammatories | 206.2 | 3.9 | 4.9 | C13H18O2 | 21.0 |
Mefenamic acid | Analgesic and anti-inflammatories | 241.2 | 5.1 | 4.2, −1.6 | C15H15NO2 | 20.0 |
Metformin | Anti-diabetic | 129.1 | −0.5 | 12.4 | C4H11N5 | 1.1 × 106 |
Nifedipine | Antihypertensive | 346.3 | 2.2 | 5.3, 3.9 | C17H18N2O6 | 0.02 |
Perindopril | Antihypertensive | 368.4 | 2.6 | 3.7, 5.4 | C19H32N2O5 | 1.2 |
Salbutamol | To treat asthma, agonists bronchodilator | 239.3 | 0.4 | 10.3 | C13H21NO3 | 1.4 × 104 |
Simvastatin | Lipid-lowering agent | 418.5 | 4.6 | 14.9, −2.8 | C25H38O5 | 0.01 |
The disks were placed on 47 mm disk holders and the samples were introduced under vacuum at flow rates of 20, 50 and 100 mL min−1 for sewage influent, sewage effluent and tap water, respectively. After sample loading, the disk was washed with 5 mL of 5% methanol in ultrapure water at pH 7. The disk was then dried for about 30 min and subsequently, the analytes were eluted twice with 1 mL of a mixture of ACN:MEOH (1:1 v/v) with 2% formic acid, then twice with 1.5 mL of the mixture of ACN:MEOH (1:1 v/v) with 2% ammonium hydroxide. The extracts were evaporated to near dryness under a vacuum at 50 °C, then reconstituted in 0.5 mL of methanol and diluted to 2 mL using water: methanol (2:1 v/v) at pH 10 (Fig. S12, ESI†). The extracts were stored at −18 °C until analysis.
To determine the best sample pH and the optimum eluent material and additive material, different pH samples and several eluent materials with different additive materials at various concentrations were tested for all the pharmaceuticals together using the described method above on spiked ultrapure water by varying one parameter at a time. The sample pH values were adjusted using 1 M HCl and 1 M NaOH solution, while ammonium hydroxide and formic acid were used as additive materials.
A gradient elution programme was developed. The composition of the mobile phase started with 10% methanol at a flow rate of 0.2 mL min−1 for 1 min. The methanol was elevated from 10 to 80% at a flow rate of 0.2 mL min−1 over the following 5 min, then the methanol was increased to 100% at a flow rate of 0.2 mL min−1 over the next 4 min; this was held for 0.5 min. Finally, the methanol ended with 10% in 1.5 min at a flow rate of 0.25 mL min−1. The system was allowed to equilibrate for 4 min before each injection.
An Agilent 6490 triple-quadrupole mass spectrometer (Agilent Technologies, Singapore) with Agilent Jet Stream system AJS ESI electrospray ionisation was used to detect the analytes. Both positive and negative ionisation modes were operated simultaneously. Capillary voltage was 2 kV and the nebuliser pressure was 45 psi for both modes. Nitrogen gas was used for both dissolution and nebulising gas at a flow rate of 14 L min−1 and temperature of 225 °C, with a dwell time at 0.2 s Table 2.34 In addition, the MassHunter software was used for instrument control, peak detection, and integration. To increase sensitivity, selectivity, and data acquisition, multiple reaction monitoring modes (MRM) were used.
Compound Name | Polarity | Rt | Precursor ion | Product ion 1 | Fragmentation pattern34 | CE | Product ion 2 | Fragmentation pattern34 | CE |
---|---|---|---|---|---|---|---|---|---|
a CE: collision energy, Rt: retention time. | |||||||||
Acetaminophen | Positive | 3.9 | 152.0 | 109.9 | [M–CH3]+ | 13 | 65.1 | [M–CH2CO + H]+ | 33 |
Caffeine | Positive | 4.4 | 195.0 | 138.1 | [M–N2C2H4]+ | 21 | 42.1 | — | 40 |
Diclofenac | Positive | 8.5 | 296.0 | 214.0 | [M–ClCO2]+ | 33 | 215.0 | — | 17 |
Ibuprofen | Negative | 8.1 | 205.1 | 159.0 | [M–H–CO2]+ | 2 | 161.0 | — | 2 |
Mefenamic acid | Positive | 9.6 | 242.2 | 224.2 | [M–H2O]+ | 13 | 209.1 | [M–H2O–CH3]+ | 29 |
Metformin | Positive | 1.4 | 130.1 | 59.9 | [M–C3N2H8]+ | 13 | 71.1 | [M–CN3H4]+ | 21 |
Nifedipine | Positive | 7.3 | 347.1 | 315.1 | — | 1 | 254.2 | — | 13 |
Perindopril | Positive | 6.4 | 369.0 | 172.1 | [M–C10O3NH18] + | 21 | 98.0 | — | 40 |
Salbutamol | Positive | 3.5 | 240.3 | 148.2 | [M + H–(CH3)2C–CH2− (H2O)2]+ | 13 | 222.2 | — | 5 |
Simvastatin | Positive | 8.9 | 419.2 | 199.3 | [M–(CH3)2–COH2]+ | 1 | 285.2 | [M–H2O–C6O2H12]+ | 9 |
Intra-day precision was calculated as the relative standard deviation for five spiked replicates extracted and analysed on the same day, while for inter-day precision, one spiked sample was extracted and analysed on five different days. Intra-day and inter-day precision spiked samples were spiked at 3 different concentration levels (5, 50 and 500 ng L−1 for tap water and 100, 1000 and 9000 ng L−1 for influent wastewater and 50, 500 and 5000 ng L−1 for effluent wastewater). Signal suppression was evaluated by comparing the change in the peak intensity between the sample matrix versus ultrapure water, then calculated by the following equation:
Signal suppression (%) = (1 − (Is − Io)/IMQ) × 100 | (1) |
Compound | LOD (ng L−1) | LOQ (ng L−1) | Intra-day (%) RSD | Inter-day (%) RSD | Recovery (%) | r | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
TW | EF | IN | TW | EF | IN | TW | EF | IN | TW | EF | IN | TW | EF | IN | ||
Acetaminophen | 2.7 | 2.8 | 3.1 | 9.0 | 9.0 | 10.0 | 8 | 8 | 6 | 8 | 13 | 10 | 81 | 79 | 72 | 0.99 |
Caffeine | 0.02 | 0.02 | 0.02 | 0.1 | 0.1 | 0.1 | 4 | 5 | 2 | 7 | 6 | 6 | 102 | 97 | 101 | 0.99 |
Diclofenac | 0.3 | 0.3 | 0.3 | 0.9 | 1.0 | 0.9 | 5 | 5 | 6 | 7 | 9 | 8 | 118 | 111 | 121 | 0.99 |
Ibuprofen | 3.2 | 3.0 | 4.7 | 10.9 | 9.9 | 15.7 | 6 | 8 | 7 | 9 | 8 | 6 | 98 | 107 | 93 | 0.99 |
Mefenamic acid | 0.3 | 0.3 | 0.4 | 0.8 | 0.9 | 1.2 | 3 | 5 | 6 | 6 | 8 | 10 | 122 | 121 | 103 | 0.99 |
Metformin | 0.3 | 0.3 | 0.3 | 0.9 | 0.9 | 0.9 | 9 | 8 | 8 | 13 | 14 | 16 | 48 | 47 | 47 | 0.99 |
Nifedipine | 3.0 | 3.1 | 3.7 | 10 | 10.3 | 12.3 | 12 | 7 | 5 | 14 | 14 | 14 | 76 | 75 | 64 | 0.98 |
Perindopril | 0.3 | 0.3 | 0.3 | 0.9 | 1.0 | 0.9 | 4 | 6 | 6 | 9 | 10 | 11 | 114 | 107 | 117 | 0.99 |
Salbutamol | 0.3 | 0.3 | 0.3 | 1.0 | 1.1 | 1.1 | 6 | 4 | 7 | 10 | 9 | 12 | 70 | 62 | 62 | 0.99 |
Simvastatin | 0.3 | 0.3 | 0.5 | 1.0 | 1.0 | 1.5 | 4 | 9 | 6 | 6 | 11 | 11 | 83 | 81 | 72 | 0.99 |
In this study, the absolute recovery was calculated, which was determined by comparing the peak area ratio of the analyte after extraction with those of non-extracted solutions containing the same concentration of the analyte. This is unlike most of the other studies using relative recovery, which is the percentage amount of pharmaceuticals recovered from the matrix with reference to the extracted internal standard (standard spiked into the same matrix). Absolute recovery can reveal the exact amount analyte lost during the analysis, in contrast to relative recovery which is used to compensate for the loss of the sample analyte without evaluating the real loss.36
The absolute recoveries were obtained by spiking three replicates of each sample matrix at two concentration levels and then the analysis method was applied. Most of the acidic compounds had an absolute recovery that was a much higher value than previously reported,29,30,32,37–40 even though their methods were targeting similar groups of the compound. For metformin, as expected, the recovery was low due to the high polarity of the compound (pKa = 12.4, logKow = −0.5), which led to a high solubility in water and poor solubility in lipids. Thus, it is difficult to extract metformin in an aqueous matrix. However, this study is the first to report a quantitative analytical method for metformin using SPE, which is applicable for wastewaters at this level of sensitivity. For quantification analysis in real samples, an external calibration method was used to calculate the concentration of all the analytes, and since the external calibration method did not compensate for the loss of the analytes during sample preparation and chromatographic analyses, the absolute recoveries were taken into account in the quantitative calculation to compensate for the loss.
Fig. 3 illustrates how the signal suppression in wastewater was reduced when the sample was diluted. By comparing the signal suppression for undiluted and 3-times diluted samples, the efficiency of the technique in eliminating the matrix effect can be observed. Based on our research findings, the signal suppression for diclofenac, ibuprofen and mefenamic acid was reduced within the range of 13 to 2%, 31 to 1%, and 21 to 3%, respectively. For acetaminophen and caffeine, the signal suppression was reduced from approximately 80% to 20%, whereas 50% to 15% reduction was obtained for simvastatin, nifedipine, metformin and salbutamol. Only for perindopril was the signal suppression not affected by the sample dilution. However, the signal suppression for perindopril was very small (less than 5%).
Better recoveries were observed using the disk as compared to the cartridge on the same adsorbing materials (HLB). The results in Table 4 show the recovery increased to more than 50% for five pharmaceuticals when the disk was used. The most notable differences in recovery were for acetaminophen, salbutamol, caffeine, metformin, and perindopril, where the values were doubled for perindopril and caffeine, 15 to 20 times for acetaminophen and salbutamol, and more than 40 times for metformin. The recoveries for diclofenac, mefenamic acid and ibuprofen by disk were close to those obtained with a cartridge in the range of 90 to 120%. The improved recovery is attributed to the disk design. Membranes eliminate the channeling and the small particle size increases the path length, which leads to an increase in the interactions between the analytes and the adsorbing material in the disk. This reduces the risk of analyte loss, which can happen with other packed particle beds, such as the cartridge.
Compound | Recovery (%) | LOD (ng L−1) | LOQ (ng L−1) | Intra-day (%) RSD (100 ng L−1) | Inter-day (%) RSD (100 ng L−1) | Signal suppression (%) | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Disk | Cartridge | Disk | Cartridge | Disk | Cartridge | Disk | Cartridge | Disk | Cartridge | Disk | Cartridge | |
Acetaminophen | 81.0 | 3.3 | 2.7 | 30.8 | 9.0 | 102.0 | 8 | 9 | 8 | 11 | 8 | 26 |
Caffeine | 102 | 54 | 0.02 | 15.9 | 0.1 | 53.0 | 4 | 3 | 7 | 7 | 9 | −26 |
Diclofenac | 118 | 105 | 0.3 | 0.4 | 1.0 | 1.1 | 5 | 4 | 7 | 5 | 6 | −19 |
Ibuprofen | 98 | 95 | 3.3 | 35.1 | 10.9 | 117.0 | 6 | 8 | 9 | 7 | 6 | 23 |
Mefenamic acid | 122 | 110 | 0.3 | 0.4 | 0.9 | 1.2 | 3 | 5 | 6 | 6 | 5 | 12 |
Metformin | 48 | 1 | 0.3 | 145.7 | 0.9 | 485.0 | 9 | 14 | 13 | 16 | 17 | 24 |
Nifedipine | 76 | 34 | 3.0 | 0.4 | 10.0 | 1.3 | 12 | 14 | 14 | 17 | 22 | 16 |
Perindopril | 114 | 65 | 0.3 | 3.4 | 1.0 | 11.4 | 4 | 9 | 9 | 11 | 7 | −5 |
Salbutamol | 70 | 4 | 0.3 | 3.1 | 1.0 | 10.0 | 6 | 8 | 10 | 11 | −9 | −19 |
Simvastatin | 83 | 60 | 0.3 | 3.7 | 1.0 | 12.3 | 4 | 6 | 6 | 7 | 16 | 31 |
By comparing the precision (intra-day and inter-day) of the two methods, we can see the difference between the disk and the cartridge, where the disk was more precise than the cartridge in all the analytes except for diclofenac, mefenamic acid and ibuprofen where it was similar. The disk method produces clean matrices and a concentrated analyte solution that enhances the signal-to-noise ratios, leading to improved the limits of detection and quantitation in LC/MS/MS analysis. LOD and LOQ were lower for the disk method as compared to the cartridge method for most of the pharmaceuticals except for the diclofenac and mefenamic acid, where they were almost similar in both methods. Nifedipine was the only compound that had higher LOD and LOQ in the disk compared to the cartridge.
Our research findings revealed that the disk SPE gave better results in cleaning up and significantly reduced the matrix effect. Table 4 shows the low signal suppression observed when the disk was used for most of the pharmaceuticals when compared to the cartridge. For instance, the matrix effect for influent wastewater with the disk ranged from -9–22%, while it was -26–31% for the cartridge. This difference could be related to the small particle size that made the disk worked as a filter membrane, which produced clean extracts and minimised fine particles potentially reaching the LC/MS/MS. The only disadvantage of using disk SPE in this study is the high price of the disk as compared to the price of the cartridge. On the other hand, using the disk SPE reduced the cost of the solvent and the manpower, which can reduce the analysis cost. The results of using the disk SPE compared favorably with the literature as shown in Table 5.27,29,30,32,37–40
Sample type | Analyte | Analysis method and technique | IDL (pg) | Recovery | LOD (ng L−1) | LOQ (ng L−1) | Intra-day% | Inter-day% | References |
---|---|---|---|---|---|---|---|---|---|
a NR: not reported. | |||||||||
Wastewater/tap water | All the analytes | HLB SPE disk LC-MS/MS (qqq) | 9.7–59 (fg) | 62 to 118 metformin 48 | 0.02–4.73 | 0.1–15.7 | 2–12 | 6–16 | This study disk |
Wastewater/tap water | All the analytes | HLB SPE cartridge LC-MS/MS (qqq) | 9.7–59 (fg) | 1.3–110 | 0.34–145.7 | 1.1–485 | 3–14 | 5–17 | This study cartridge |
Drinking and surface water | Ibuprofen | HLB SPE cartridge 200 mg 6 mL LC-MS/MS (qqq) | 0.5–20 | 61–93 | NR | 0.4–15 | 8–17 | 6–40 | 30 |
Mefenamic acid | |||||||||
Diclofenac | |||||||||
Simvastatin | |||||||||
Wastewater/tap water/river mineral | Ibuprofen | Strata-X 33U | NR | 85 | 30 | NR | 18 | NR | 29 |
Diclofenac | Polymeric reversed phase (200 mg/6 mL) LC-MS/MS (qqq) | 83 | 20 | 14 | |||||
Drinking and surface water | Ibuprofen | HLB SPE cartridge | NR | 174 | 1.0 | 3.8 | 3.5 | NR | 37 |
Diclofenac | 57 | 5.2 | 17.1 | 42 | |||||
Acetaminophen | 139 | 6 | 20 | 7.3 | |||||
Salbutamol | 30 | 0.9 | 3.0 | 4.4 | |||||
Hospital wastewater | Ibuprofen | HLB SPE cartridge | 22 | 111.7 | 31 | 86 | 1.4 | 11.2 | 38 |
Diclofenac | 27 | 113.6 | 30 | 84 | 2.7 | 13.6 | |||
Mefenamic acid | 2 | 100.1 | 4 | 11 | 2.4 | 3.1 | |||
Drinking | Ibuprofen | (Speedisk H2O-Philic DVB, J.T. Baker), GC-MS-SIM | NR | 92.4 | 1.4 | 3.6 | NR | NR | 39 |
Diclofenac | 89.6 | 2.2 | 7.4 | ||||||
Salbutamol | 105.8 | 0.3 | 0.9 | ||||||
Wastewater | Diclofenac | GC-MS SPE-DEX | NR | NR | 0.098 | 0.098 | 0.119 | NR | 32 |
Wastewater | Ibuprofen | Hollow fibre liquid phase microextraction, LC-MS/MS | NR | NR | 16.8 μg L−1 | 55.9 μg L−1 | NR | NR | 40 |
Diclofenac | 7.1 μg L−1 | 23.6 μg L−1 | |||||||
River water | Ibuprofen | OASIS HLB LC-MS/MS | NR | NR | NR | 19 | 5.4 | 27 | |
Diclofenac | 15 | 4.1 | |||||||
Caffeine | 39 | 12 |
All of the targeted pharmaceuticals were detected in the influent and effluent samples in three sampling trips in various concentrations except for nifedipine and perindopril, which were not detected in the third sampling trip. In the influent wastewater, the acetaminophen concentration was very high (above 14000 ng L−1) in all the sessions. Caffeine, simvastatin and metformin were abundant in the influent wastewater where the concentrations were between 1400 to 11000 ng L−1. The mean concentrations of other pharmaceuticals were varied for each compound and for each sampling batch (Table 6). Contrary to the influent, effluent concentration was medium to low for most of the pharmaceuticals, which did not exceed 2000 ng L−1, indicating the efficiency of the removal process. In general, the highest influent concentration of most of the pharmaceuticals was during the second sampling session (May) which ranged from 51.4 ng L−1 (ibuprofen) to 49423.7 ng L−1 (acetaminophen). Different concentrations of all the compounds in the different sampling sessions for the wastewater might reflect the changes in the consumption of these drugs in each month. Fig. S2–S11 in the ESI† show the TIC and MRM chromatograms of a standard mixture, blank, tap water sample, effluent wastewater (EF) sample and influent wastewater sample (IN).
Compounds | Tap water (ng L−1) | Samples 1 | Samples 2 | Samples 3 | ||||||
---|---|---|---|---|---|---|---|---|---|---|
Effluent (ng L−1) | Influent (ng L−1) | Removal percentage (%) | Effluent (ng L−1) | Influent (ng L−1) | Removal percentage (%) | Effluent (ng L−1) | Influent (ng L−1) | Removal percentage (%) | ||
a ND: not detected. | ||||||||||
Acetaminophen | ND | 343 ± 2 | 23736 ± 11 | 98 | 28 ± 1 | 49424 ± 18 | 99 | 330 ± 2 | 14359 ± 6 | 97 |
Caffeine | ND | 1763 ± 8 | 4708 ± 15 | 62 | 1016.9 ± 0.7 | 7440 ± 7 | 86 | 1129 ± 9 | 3629 ± 11 | 68 |
Diclofenac | ND | 164.9 ± 0.9 | 99.5 ± 0.4 | −65 | 54.0 ± 0.6 | 101.0 ± 0.3 | 46 | 109.6 ± 0.6 | 112.4 ± 0.6 | 2 |
Ibuprofen | ND | 261 ± 1 | 270 ± 2 | 3 | 41.8 ± 0.9 | 51 ± 2 | 18 | 202 ± 3 | 438 ± 7 | 53 |
Mefenamic acid | ND | 678 ± 5 | 504 ± 3 | −34 | 89.2 ± 0.9 | 259.2 ± 0.6 | 65 | 468 ± 6 | 518 ± 3 | 9 |
Metformin | ND | 640 ± 3 | 2330 ± 6 | 72 | 1203.0 ± 0.8 | 7695 ± 1 | 84 | 390.4 ± 0.8 | 1421 ± 4 | 72 |
Nifedipine | ND | 26.3 ± 0.4 | 30.9 ± 0.2 | 14 | 33.5 ± 0.2 | 445.2 ± 0.2 | 92 | ND | ND | — |
Perindopril | ND | 112.3 ± 0.8 | 82.2 ± 0.5 | −36 | 81.7 ± 0.5 | 252.1 ± 0.5 | 67 | ND | ND | — |
Salbutamol | ND | 90.1 ± 0.4 | 110.6 ± 0.4 | 18 | 41.7 ± 0.3 | 71.0 ± 0.3 | 41 | 35.3 ± 0.4 | 45.0 ± 0.2 | 21 |
Simvastatin | ND | 132 ± 5 | 5254 ± 12 | 97 | 220 ± 2 | 11809 ± 13 | 98 | 82 ± 2 | 1719 ± 6 | 95 |
Treatment efficiencies for the hospital treatment plant were different from one compound to another, and differed for each sampling session. The removal efficiency was evaluated by calculating the removal percentage during wastewater treatment using the following equation:44
Percentage of removal = (influent − effluent)/influent × 100%). |
Acetaminophen and simvastatin were removed at the rate of 99%. Moderate removal values were observed for caffeine and metformin (70%) for all the sampling seasons. The removal of other pharmaceuticals was in different percentages for each sampling season. Perindopril, diclofenac and mefenamic acid persisted in higher concentrations in effluent wastewater than the concentration measured in influent (untreated) wastewater in the first sampling session. The increased concentration levels of these compounds in the effluent compared to influent has been reported in other studies.38,45–47 This phenomenon could be explained by several theories such as the cleavage of these glucuronide compound conjugates during the treatment processes to release these drug-free forms. Another theory could explain this increase as being due to the formation of transformation products such as epoxy–derivatives and hydroxyls in the influent wastewater, which are not detected by the method used for the original drugs before the treatment, and later breaks down to yield the free form of the drug that can be detected.47 Moreover, these pharmaceuticals could adsorb to some organic matter in the influent, which would lead to a reduction in the free pharmaceuticals detected by the method. Consequently, the organic matter would break down and release the pharmaceuticals into the effluent wastewater after the treatment process.
Footnote |
† Electronic supplementary information (ESI) available. See DOI: 10.1039/c8ra06885b |
This journal is © The Royal Society of Chemistry 2018 |