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Mussels as bioindicators of diclofenac contamination in coastal environments
Environmental Pollution xxx (2017) 1e7
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Mussels as bioindicators of diclofenac contamination in coastal environments* S.C. Cunha a, *, A. Pena b, J.O. Fernandes a a
LAQV-REQUIMTE, Laboratory of Bromatology and Hydrology, Faculty of Pharmacy, University of Porto, Rua Jorge de Viterbo Ferreira 228, 4050-313 Porto, Portugal b LAQV-REQUIMTE, Group of Bromatology, Pharmacognosy and Analytical Sciences, Faculty of Pharmacy, University of Coimbra, Polo III, Azinhaga de Sta Comba, 3000-548 Coimbra, Portugal
a r t i c l e i n f o
a b s t r a c t
Article history: Received 7 January 2017 Received in revised form 27 February 2017 Accepted 27 February 2017 Available online xxx
Diclofenac a nonsteroidal anti-inflammatory drug (NSAID) has been confirmed as an emerging contaminant in the aquatic environment. Toxicology studies have revealed that harmful effects may emerge from diclofenac presence not only for human health, but also for marine organisms, which implies its monitoring. To overcome the demanding challenges of diclofenac quantification in biotic aquatic species, a novel method for the determination of diclofenac in mussels (Mytilus galloprovincialis and Mytilus edulis) and macroalgae (Laminaria digitata) using high performance liquid chromatography coupled to tandem mass spectrometry was developed and validated according to the EC Decision 2002/ 657/EC. Additionally, a study was done about diclofenac contamination in mussels collected from 8 sites along the 1115 miles of coastline in Portugal in 2015. The results suggested that levels in mussels are closely related to the environmental contamination. Therefore, mussels can be a potential bioindicator of diclofenac contamination in the coastal environment. © 2017 Elsevier Ltd. All rights reserved.
Keywords: Diclofenac Macroalgae Mussels Contaminants LC-MS/MS
1. Introduction In the last years, the focus of environmental research has been gradually changing from the conventional “priority pollutants”, such as polychlorinated biphenyls, polycyclic aromatic hydrocarbons, and pesticides, to the so-called “emerging pollutants” (EPs) such as flame retardants, disinfection by-products, pharmaceuticals and personal care products (Sousa, 2013; Geissen et al., 2015). These are chemicals that are not commonly monitored in the environment, but which have the potential to enter into the diverse environmental compartments and cause adverse ecological and human health effects (Geissen et al., 2015). Some EPs as most of the pharmaceutical compounds are not new chemicals but substances that have been present for a long time in the environment and whose presence and significance are only now being elucidated (Norman, 2017).
*
This paper has been recommended for acceptance by Klaus Kummerer. rio de Bromatologia e Hidrologia, Faculdade de * Corresponding author. Laborato cia, Universidade do Porto, Rua Jorge de Viterbo Ferreira 228, 4050-313 Porto, Farma Portugal. E-mail address: [email protected] (S.C. Cunha).
Pharmaceuticals used for the treatment of human or animal illness are commonly excreted via urine and/or faeces, and are thereafter subject to inadequate removal during conventional wastewater treatment. As a result, pharmaceuticals are ubiquitous compounds, often persistent and bioaccumulative in the environment, particular in the aquatic ecosystem (Kot-Wasik et al., 2007). Diclofenac is a non-steroidal anti-inflammatory drug (NSAID), used in the treatment of post-operative pain, rheumatoid arthritis, and the chronic pain regularly associated with cancer, widespread used worldwide. For example, during the year of 2014 about 1 054 952 packages were provided in the National Health Service in Portugal (Infarmed, 2014). Due to its widespread and growing use, it is needed to create sound knowledge about its incidence, levels and fate in the environment, as well as to explain its long-term risks, ecotoxicity and human health impact (Sousa, 2013). Several studies have described physiological and behavioural effects on fish when exposed at environmental or near environmental levels of diclofenac. Cytological changes in rainbow and brown trout tissues (kidney and gills) were found to be induced by exposure to diclofenac in aquatic environments (Schwaiger et al., 2004; Hoeger et al., 2005; Triebskorn et al., 2007). Mehinto et al. (2010) reported that exposure of rainbow trout to diclofenac lead
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Please cite this article in press as: Cunha, S.C., et al., Mussels as bioindicators of diclofenac contamination in coastal environments, Environmental Pollution (2017), http://dx.doi.org/10.1016/j.envpol.2017.02.061
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to tissue damage. Additionally, diclofenac can affect the gene expression in fish (Cuklev et al., 2011). This NSAID has also been associated with the serious reduction of the Gyps vultures in Asia due to renal failure and visceral gout, and ultimately death (Oaks et al., 2004; Taggart et al., 2007). Due to diclofenac direct and indirect toxicity to vertebrates, it has been recently suggested to be added into the list of priority substances in the EU's Water Framework Directive (2013/39/EU). Legislation on maritime water bodies as the Directive 2008/56/EG (European Commission, 2008) (maritime strategy framework directive-MSFD; European Commission, 2008) and the HELCOM (Baltic Marine Environment Protection Commission) (Helcom, 2015) are considering the insertion of some pharmaceuticals in routine monitoring programs, whereas the OSPAR Commission has already recognized clotrimazole as “substance for priority action” and a wider range of pharmaceuticals as “substances of possible concern” (OSPAR, 2013). Assessment of environmental exposure to chemicals can be achieved through the use of indicator species such as algae or bivalves. These biomarker species accumulate pollutants in their tissues from the surrounding environment being therefore important biomonitoring devices. Filter feeders, such as bivalves (clams and mussels) tend to concentrate metals in their gills or other tissues. Mytilus edulis became a species monitored in the United States of America as well as in other countries for changes in levels of water pollution (Phillips and Rainbow, 1993). Seaweeds as Ulva lactuca commonly found at and near effluent discharge points of fish farms have been used as an indicator for the presence of antibiotics (Leston et al., 2015). Laminaria japonica was found to bioaccumulate polycyclic aromatic hydrocarbons from the surrounding medium (Wang and Zhao, 2008). Recently, experimental studies reported that mussels were able to bioconcentrate diclofenac from the water where the mussels were exposed to (Ericson et al., 2010; Mezzelani et al., 2016). McEneff et al. (2014) reported that mussel samples collected from two sites on Irish coastline are able to uptake pharmaceutics such as trimethoprim, carbamazepine and mefenamic acid, although no evidences of diclofenac accumulation were observed. To our knowledge there are a lack of reports on diclofenac in wild mussels along an entire coastal line. The growing interest in diclofenac as an environmental contaminant has catalysed the development of analytical methods able to deal with the trace levels of the compound usually found in the different environmental compartments. Recently, some reviews have been published reporting the state-of-the-art of pharmaceutical environmental analysis (Petrovic et al., 2010; Richardson, 2012). Most of the analytical methods use liquid chromatography coupled to tandem spectrometry (LC-MS/MS) for quantitative analysis of low concentrations of diclofenac. Gas chromatographymass spectrometry (GC-MS) can be also used, although diclofenac residue usually needs to be derivatized before analysis to enhance its volatility. Most methodologies require an extraction procedure usually based on liquid extraction with moderate polar solvents followed by a clean-up step with solid-phase extraction (SPE) prior to LC-MS/MS or GC-MS analysis (Wang and Zhao, 2008; Ericson et al., 2010; Petrovic et al., 2006). Only a few studies have employed QuEChERS method which stands for “quick, easy, cheap, effective, rugged and safe” in pharmaceutical analysis (Cerqueira ~ ez et al., 2015). The advantage of QuEChERS is et al., 2014; Nún that it is a rapid, simple, and accurate method that provides a saving of time and consumables (solvents) over existing methodologies. The aforementioned analytical methods have been applied for the determination of diclofenac in various matrices such as river waters (Johnson et al., 2013), surface waters (Rabiet et al., 2006), €, 2014), wastewaters (Richardson, 2012; Vieno and Sillanp€ aa
seawaters (Loli c et al., 2015), fish (Mehinto et al., 2010; Kallio et al., 2010) and mussels (McEneff et al., 2014), but none directly applied to macroalgae. Taking this into consideration, the aim of present work was to develop a simple and reliable analytical method that not only assures the unequivocal identification and quantification of diclofenac at very low levels, but also allows a common pretreatment process (preservation, extraction and clean-up) for two kind of matrices (mussels and algae) traditionally unwieldy to analyze. Additionally, the developed method was validated according the requirements of the Commission Decision 2002/657/EC for determination of diclofenac in mussels and algae. It was further applied in the analysis of wild mussels samples collected from 8 different sites distributed over Portugal costal, along five different seasons of 2015. 2. Experimental 2.1. Chemicals and reagents Diclofenac sodium salt (99.5% purity) and Internal Standard (IS) diclofenac-acetophenyl ring (13C6, 99.99% purity) sodium salt were acquired from Sigma Aldrich (MO, USA). The solvents acetonitrile (MeCN) and methanol (MeOH), both LC-MS grade, were obtained from VWR (PA, USA). Acetic acid (purity >99%) and formic acid (purity >99%) were both obtained from Merck, (Darmstadt, Germany). The salts ammonium acetate (NH4CH3CO2, 97% purity), ammonium chloride (NH4Cl, 99.8% purity) and ammonium formate (NH4HCO2, 99.99% purity) were obtained from AppliChem Panreac ITW companies (Barcelona Spain), Merck, and Sigma Aldrich, respectively. The sorbents sulfate magnesium (MgSO4) and Z-sep were both obtained from Sigma-Aldrich. Ultrapure water was obtained daily from a “Seradest LFM 20” system (Seral, RansbachBaumbach, Germany). Nitrogen (nitrogen 90, 99.998% purity) was generated in-house with nitrogen generator from Sysadvance (Maia, Portugal). Ultrahigh purity Argon (99.999%) was purchased from Gasin (Maia, Portugal). 2.2. Standard solutions and validation Individual stock standard solutions of diclofenac and 13C6diclofenac (IS) were prepared in MeOH (1 mg/mL). Individual working standard solution of diclofenac at 20 mg/mL and 13C6diclofenac at 10 mg/mL were prepared from the stock solutions by appropriate dilution in MeOH, and stored at - 20 C when not in use. The stability and accuracy of diclofenac in solution were guaranteed using two individual stock solutions, prepared and analyzed on days 0, 30 and 60. The same protocol was used to the standard solutions used in recovery and matrix-matched calibration curves. The method was validated in agreement with internationally recognized principles, such as linearity, recovery, repeatability, sensitivity (limits of detection and quantification), decision limit (CCa), detection capability (CCb), selectivity, and robustness. Validation criteria were adopted from guidelines for residues according to Commission Decision 2002/657/EC [30]. Linearity was studied in mussels and Laminaria digitata samples (free of analytes) spiked at 6 concentration levels, covering a range between 0.5 and 50 ng/g. The relationship between peak area ratios of analyte/IS and concentrations in the investigated concentration range was assessed by the coefficient of determination (R2). Recovery and repeatability were evaluated in simultaneous through the analysis of 6 blank samples spiked, before extraction, at 1, 5 and 20 ng/g with diclofenac only. The internal standard was added to the extracts at the end of the sample preparation with the aim of allowing the estimation of analyte loss during processing.
Please cite this article in press as: Cunha, S.C., et al., Mussels as bioindicators of diclofenac contamination in coastal environments, Environmental Pollution (2017), http://dx.doi.org/10.1016/j.envpol.2017.02.061
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3
The acceptance criterion set for the relative standard deviation (RSD) of the repeatability was 20% at all spiking levels. CCa and CCb were also achieved using blank samples spiked, since there is no allowed limit established for diclofenac. Blank tests were achieved to control potential cross contamination during sampling and storage, or coming from equipment. Thus, as realized in previous works as internal quality control, two solvent injections and two procedural blanks were inserted into each analytical batch made up of ten samples (Cunha and Fernandes, 2013).
and October 2015 (5 sampling campaigns). As presented in Table 1, all specimens were of similar size and satisfied the legal requirements of harvestable size or weight for human consumption. The total number of individual organisms collected from the sampling sites was 1225. Individual biometrics averaged: shell length: 5.01 ± 0.85 cm, shell width: 2.56 ± 0.49 cm and shell height 1.87 ± 0.27 cm. Wet weight (w.w.) ranged between 8.99 ± 3.65 g and 3.27 ± 1.85 g, with and without shell, respectively. Condition index (CI), quantified as the ratio shown in Equation (1) (GonzalezRey and Bebianno, 2013), averaged 32.57 ± 4.09%.
2.3. Site characterization and sample collection
CIð%Þ ¼
Marine mussels M. galloprovincialis and Mytilus edulis were sampled from eight locations along the Portuguese Atlantic coast (Fig. 1), from the coastline, between the parallels presented bellow and the coast, including the intertidal zone and the bathymetry of 70 m; and from a river estuary: L1 Viana coastline area between the parallels 41.86745 N (Minho River) and 41.27064 N (Angeiras River Donda mouth); L2 Matosinhos coastline area between the parallels 41.27064 N and 40.93119 N (Maceda); L3 Aveiro coastline area between the parallels 40.93119 N and 40.44507 N (South Bank of Mira Lagoon); L5 (a, b, c) Peniche/Lisbon coastline area between the parallels 39.45783 N and 38.52222 N ~o); L7 Aljezur St. Vincent coastline area between the (Garalha parallel 37.45167 N (north of the mouth Seixe creek) and the circle defined by the points: (1) 8.9970 W, 37.02270 N (St. Vincent Cape) and (2) 9.12820 W, 36.84378 N (south - south-west of St. Vincent ~o coastline zone between the meridian Cape); L8 Faro Olha 8.12486 W and 7.65535 W meridian (East of Sta Luzia) (IPMA, 2015). Mussels were sampled during one year, between January 2015
In order to reduce the variability effect due to use of organic matrix (Bueno et al., 2014), each composite sample consisted of 25 specimens (edible content) of similar size collected from each sampling site in each campaign. Each pool was grinded, (Retasch Grindomix GM200, Germany), homogenized, and frozen at 80 C in plastic tubes of 40 mL. To conclude, the samples were freezedried for 48 h at 80 C and low pressure (around 0.017 mBar, Telstar Cryodos, Grundy's LaneBristol), homogenized and maintained at 4 C until analysis. Laminaria digitata was randomly collected in a local market in the city of Porto, Portugal.
whole soft tissue wet weightðgÞ 100 whole body weight with shell ðgÞ
(1)
2.4. Optimized sample preparation Sample preparation entailed the following steps: (1) 0.5 g homogenized freeze-dried sample was added with 50 mL IS at 500 ng/ mL (the tubes were vortexed for 1 min to improve the incorporation of IS into the sample and kept in contact for 30 min); (2) 3.5 mL of H2O and 3.5 mL of MeCN with 10% (v/v) formic acid were added
Fig. 1. Location of the sampling sites along the Portuguese coast.
Please cite this article in press as: Cunha, S.C., et al., Mussels as bioindicators of diclofenac contamination in coastal environments, Environmental Pollution (2017), http://dx.doi.org/10.1016/j.envpol.2017.02.061
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Table 1 Mean individual shell biometric and condition index (CI) estimation ± standard deviation for each sampling site along the five sampling campaigns. Location
Length (cm)
Viana do Castelo (L1) Matosinhos (L2) Aveiro (L3) Peniche (L5 a) s (L5 b) Alge Costa Caparica (L5 c) Aljezur (L7) Faro (L8)
4.59 4.73 4.24 4.15 4.70 5.45 5.45 6.73
± ± ± ± ± ± ± ±
0.05 0.09 0.10 0.17 0.15 0.19 0.29 0.14
Width (cm) 2.23 2.32 2.06 2.15 2.56 2.68 2.91 3.54
± ± ± ± ± ± ± ±
0.03 0.06 0.06 0.03 0.07 0.05 0.12 0.06
Height (cm) 1.69 1.76 1.55 1.57 1.92 2.11 2.03 2.31
± ± ± ± ± ± ± ±
0.03 0.07 0.04 0.07 0.13 0.09 0.17 0.08
whole body weight with shell (g)
whole soft tissue wet weight (g)
6.06 ± 0.53 6.48 ± 0.56 5.35 ± 0.65 5.22 ± 0.94 9.85 ± 1.90 12.77 ± 2.44 12.14 ± 3.48 14.09 ± 0.27
1.86 2.59 1.71 1.62 3.21 3.94 5.06 7.17
and the tubes were vortexed for 3 min; (3) 2.5 g of NH4Cl were added and the tubes were mix for 15 min in an automatic shaker and centrifuged at 2700 rcf for 5 min; (4) 1 mL of the MeCN extract was transferred to a d-SPE tube containing 150 mg anh. MgSO4 and 50 mg Z-Sep, vortexed for 1 min, and centrifuged at 2700 rcf for 1 min; (5) 0.5 mL of the extract was transferred for an injection tube and evaporated under a stream of nitrogen; (6) the dry extract was reconstituted with 200 mL of HPLC mobile phase.
2.5. Apparatus and LC-MS/MS conditions A high-performance liquid chromatography (HPLC) system Waters Alliance 2695 (Waters, Milford) was interfaced to a Quattro Micro triple quadrupole mass spectrometer (Waters, Manchester, UK). LC separation was performed using a Kinetex C18 2.6 m particle size analytical column (150 4.6 mm) with pre-column from Phenomenex (Tecnocroma, Portugal), at a flow-rate of 300 mL/min. The column was maintained at 30 C and the auto-sampler was kept at ambient temperature (±25 C). Mobile phase consisted of a mixture of A: MeCN containing 0.1% acetic acid (25%), and B: water at pH 3.5 (adjusted with acetic acid) (75%) in isocratic mode. The sample injection volume was 10 mL and total run time was 14 min. Mass analysis was performed with an ESI source in the negative ion mode (ESI-) for all the analytes because of its higher sensitivity compared with the positive ion mode (ESIþ). Nitrogen was used as the nebuliser gas. The optimum MS parameters were: capillary, 3.00 kV; extractor, 2 V; RF Lens, 0.5 V; Source Temperature, 150 C; Desolvation Temperature, 350 C; Desolvation Gas Flow, 550.0 L/h; Cone Gas Flow, 60.0 L/h; LM Resolution, 13.0; Ion energy, 1.0; Entrance, 1; Exit, 2; Multiplier, 650. The data were collected using the software programme MassLynx4.1. All calculations were based on chromatographic peak area ratios for the multiple reaction monitoring (MRM) precursor-product ion transitions for analyte to the precursor-product ion transition of the internal standard. For each analyte, two transitions were selected for identification, and the corresponding cone voltage and collision energy were optimized for maximum intensity. The optimized MS/ MS parameters for the target compounds are listed in Table 2.
± ± ± ± ± ± ± ±
CI (%)
0.25 0.29 0.20 0.29 0.54 0.83 1.05 1.77
31.15 31.53 40.72 29.42 27.27 32.73 32.17 35.59
± ± ± ± ± ± ± ±
0.48 0.79 0.37 0.37 0.46 0.65 1.67 3.62
3. Results and discussion 3.1. Optimization of HPLC-MS/MS analysis Individual standard solutions of 50 mg/L were prepared in methanol for MS optimization by infusion experiments, being optimized both full-scan mass spectra and MS/MS spectra in order to obtain the maximum number of available transitions for each compound. Negative ion mode was chosen due its best sensitivity and less baseline noise. For diclofenac and IS the two most sensitive Selected Reaction Monitoring (SRM) transitions were selected for each compound: the most abundant was used for quantification (Q) whereas the second one was for confirmation (q) purposes, which is a suitable confirmatory method in accordance with 2002/657/EC (Table 2). Selection of suitable mobile phase plays an important role in the ionization efficiency before the analytes enter the MS/MS system. Mixtures of MeCN/water or MeOH/water acidified or not with acetic or formic acid, and added with a buffer such as ammonium acetate are commonly candidates as the mobile phase in LC analysis. The experimental results showed that, MeCN with 0.1% acetic acid as the organic modifier, combined with water adjusted at pH 3.5 with acetic acid provided the best results. 3.2. Optimization of sample preparation In this study three different alternative versions of the QuEChERS method based on the use of ammonium chloride, ammonium formate or acetate buffers were assessed in order to reduce the matrix effect and enhance extraction recovery for diclofenac in mussels and algae. Among the macroalgae found in Portuguese coastal the Laminaria digitata was chosen due to be more widely and frequently distributed throughout the study period. The optimization was performed using mussel/algae freezedried samples spiked with diclofenac (to achieve a concentration of 1 mg/g) before and after the extraction procedure; the IS 13C6 diclofenac was always added after extraction procedure. Each experiment was evaluated in duplicate in order to calculate the % of the recovery. Initially, acetonitrile mixture composition was adjusted to ensure a high extraction yield of diclofenac together with the reduction as much as possible of the co-extracted substances namely lipids and waxes. Acetonitrile/water mixtures, commonly used in QuEChERS method, have been found to provide significantly higher extraction efficiencies for polar analytes (Cunha
Table 2 LC-MS/MS parameters for analysis of diclofenac and IS (13C6 diclofenac). Analytes
Retention time (min)
Diclofenac Diclofenac
6.81 13
C16
6.83
Precursor ion (Da)
294 [M-H] 296 [(Mþ2)-H] 300 [M-H]
Product ions (Da)
250 [M-H-CO2] 252 [(Mþ2)-H-CO2] 256 [M-H-CO2]
Cone energy (V)
Collision energy (kV)
Dwell time (ms)
16 16 15
12 12 13
0.2 0.2 0.1
Please cite this article in press as: Cunha, S.C., et al., Mussels as bioindicators of diclofenac contamination in coastal environments, Environmental Pollution (2017), http://dx.doi.org/10.1016/j.envpol.2017.02.061
S.C. Cunha et al. / Environmental Pollution xxx (2017) 1e7
lez-Curbelo et al., 2014). Besides, it is and Fernandes, 2013; Gonza relevant the ratio between sample weight and solvent volume employed, since the water present in the sample can modify markedly solubility parameters. Commonly, for samples with less of 80% moisture, sample amount used for analysis need to be reduced and water is added to accomplish more than 80% by volume regarding added MeCN. In this study, 4 mL of water was added to 0.5 g of freeze-dried sample, to promote the efficiency of the extraction solvent. Other crucial parameter to be optimized is the pH of the extraction. Taking into account the pKa of diclofenac (4.15) acidification of acetonitrile with acetic and formic acid at 1%, 5% and 10% were evaluated. Significantly better recoveries were achieved when using 10% (v/v) formic acid in acetonitrile as the extraction solvent (Fig. 2). In original QuEChERs phase separation is usually achieved through the addition of magnesium sulfate combined with sodium chloride or citrate salts. Unfortunately, these salts/ions are nonvolatile and may therefore accumulate in the LC-MS interface. To overcome this limitation, ammonium chloride (NH4Cl), ammonium formate (NH4HCO2) and ammonium acetate (NH4CH3CO2) have been recently tested with success in pesticide residue analysis lez-Curbelo et al., 2014). Thus, in this study 0.5 g of freeze (Gonza dried (containing around 2% of moisture) was added with 4 mL of H20 and 4 mL of 10% formic acid in MeCN plus 3.5 g of NH4Cl or NH4HCO2 or NH4CH3CO2. The lower pH was obtained using the 10% formic acid in MeCN added with NH4Cl (pH 2), NH4HCO2 (pH 3) or NH4CH3CO2 (pH 5). As shown in Fig. 2, the best recovery result was achieved with the mixture of 10% formic acid in MeCN and NH4Cl. One of the greatest drawbacks of LC-MS is usually the perturbation of the signal by co-extracted substances from sample matrix, especially in complex matrices as is the case of mussels and algae. For this reason, the second step of QuEChERS where the extract is cleaned up by using a dispersive solid-phase extraction (dSPE) was performed. A mixture of Z-Sepþ (50 mg), C18 (50 mg) and MgSO4 (150 mg) was evaluated using 1 mL of QuEChERS extract, with the purpose to remove co-extracted substances present in the matrix. C18 sorbent has been widely used to eliminate hydrophobic matrix compounds from various food samples. dSPE Z-Sepþ was also employed to eliminate matrix-related compounds from samples with high fat and/or wax contents (Lehotay et al., 2015). The strategy here adopted proved to be successfully, providing an acceptable recovery for diclofenac in mussels (average of 83%) and algae (average of 79%) concurrently with a significant reduction of co-extractives.
5
3.3. Analytical performance Initially, experiments were conducted to evaluate the matrix effect. Hence, the slopes of the calibration curve of standard solutions were compared with those obtained in matrix-matched standards (standards added to blank samples of mussels and Laminaria digitata). The method showed a slight enhancement of response for diclofenac. Similar effect was verified in previous works for other compounds (Cunha and Fernandes, 2013; Lehotay et al., 2015; Cunha et al., 2015), depending on the chemical characteristics of the analyte itself and the existence of other ionisable substances present in the extract. Therefore, linearity was evaluated using matrix-matched calibration solutions (standards added to blank samples) prepared as described in Section 2. The results obtained demonstrated a good linearity within the tested range, with r2 higher than 0.9967. Recovery results for three levels of concentration (described in Section 2) are presented in Table 3. Overall, recoveries were in the range 69e99%, with some slightly differences between the levels assessed. Precision was assessed in terms of intra-day repeatability as % RSD at three concentration levels through the analysis of six replicated spiked sample extracts. Either in mussels and Laminaria digitata samples, RSD values ranged from 9% to 20%; as expected worse RSD values were obtained from the lowest level (Table 3). Limits of detection (LOD) and quantification (LOQ) of unregulated compounds (without a maximum residue limit-MRL) were determined by estimating the concentration where a signal to noise ratio of three to one and ten to one, respectively, was observed. LOD values of 0.2 ng/g and 0.3 ng/g and LOQ values of 0.5 and 1 ng/g were achieved for mussels and algae, respectively. Because no MRL is established, CCa was evaluated analysing 20 blanks and calculating the signal noise ratio at the time window in which the
Table 3 Average of recovery for 1,5 and 20 mg/kg (%, n ¼ 6), repeatability (%RSD, n ¼ 6), method limit of detection (LOD), limit of quantification (LOQ), decision limit (CCa) and detection capability (CCb). Analyte
Matrices
% Recovery (RSD%) 1 mg/kg
5 mg/kg
20 mg/kg
Diclofenac
Mussel Algae
69 (18) 70 (20)
86 (16) 74 (9)
97 (11) 99 (12)
LOD
LOQ
CCa
CCb
0.2 0.3
0.5 1
0.35 0.5
0.5 0.75
100 90
Mussels
Algae
80
% Recovery
70 60 50 40 30 20 10 0 1% formic acid 1% formic acid 1% formic acid 5% formic acid 5% formic acid 5% formic acid 10% formic acid10% formic acid10% formic acid in MeCN and in MeCN NH4Cl in MeCN and in MeCN and in MeCN NH4Cl in MeCN and in MeCN and in MeCN NH4Cl in MeCN and NH4CH3CO2 NH4HCO2 NH4CH3CO2 NH4HCO2 NH4CH3CO2 NH4HCO2
Fig. 2. Recovery (%) of diclofenac in mussels and algae spiked with 1 mg/g obtained through QuEChERS procedure using MeCN with 1%, 5% and 10% formic acid and different salts such as NH4Cl, NH4HCO2 or NH4CH3CO2 (n ¼ 3).
Please cite this article in press as: Cunha, S.C., et al., Mussels as bioindicators of diclofenac contamination in coastal environments, Environmental Pollution (2017), http://dx.doi.org/10.1016/j.envpol.2017.02.061
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S.C. Cunha et al. / Environmental Pollution xxx (2017) 1e7
analyte was expected and CCb was determined by analysing 20 blanks spiked at CCa (Commission Decision, 2002/657/EC). CCa and CCb achieved for this method ranged from 0.3 to 0.6 ng/g and from 0.5 to 0.75 ng/g for mussels and algae, respectively, being within the requested range (see Table 3). Method selectivity was assessed by analysis of blank samples of each matrix (n ¼ 3) and no interference peaks were observed at the retention time of the diclofenac. Method robustness was assessed by performing minor changes on the main LC parameters: acetic acid concentration of the mobile phase, pH and flow rate. Minor changes in acetic acid concentration (±0.01%) or pH (±0.1%) of the mobile phase did not significantly disturb the separation namely resolution and peak shape. Equal behaviour was verified when flow rate was slightly changed (±0.02 mL/min) no differences in retention time, resolution or peak shape were detected (<10%). Concerning the solutions stability, concentrations of both stock and working standard solutions were stable for 60 days storage at 20 C. 3.4. Occurrence of diclofenac in Portuguese coastal In the present study, diclofenac was for the first time quantified in mussels collected from an extensive geographic area along Portuguese coastal line. Fig. 3 summarises the results obtained in mussels collected in 8 distinct sites during the year of 2015. The results obtained suggest that diclofenac contamination was widespread in wild mussels along the coastal waters of Portugal, being detected in 7 out of 8 sites studied with positive levels ranging from 0.5 to 4.5 mg/kg (dry weight, d.w.). Fig. 4 shows a MRM chros with 2.5 mg/ matogram of a mussel sample collected in July in Alge kg d.w. of diclofenac. The highest concentrations of diclofenac were found in Matosinhos and Costa da Caparica with 4.5 and 4.0 mg/kg d.w., respectively. These results may be induced by the harmful effects of the several anthropogenic activities in these areas known that WWTPs located in the adjacent area discharge their effluents ~es in these points and these beaches are also influenced by Leixo and Lisbon seaport activities. Additionally, Matosinhos and Costa da Caparica sampling points are very close of cities with the highest population density of Portugal namely Porto and Lisbon. As can be seen in Fig. 3 diclofenac levels variation along each sampling point
is somewhat correlated with the population density of the surrounding area. Seasonality of the diclofenac concentration was monitored throughout all the year, from January to October 2015 (Fig. 3). The high occurrence of detection was observed when highest concentrations were reported in July and early October. These results can be related with the increment of population in bathing areas during the summer season. Additionally, this period of the year is associated to a decrease of precipitation; as a result rivers and streams have a reduced renovation capacity, being more negatively affected by human activities as the discharges of WWTPs effluents (Loli c et al., 2015). 3.5. Mussel as potential bioindicator of diclofenac contamination Mussels have been extensively used as sentinels in “Mussel Watch Programme” to describe the current status of aquatic contamination and to detect changes in the environmental quality of estuarine and coastal waters (Li et al., 2016). Nevertheless, they are not used yet as bioindicator for NSAIDs contamination along the coastal waters worldwide. In a recent study along the north Portuguese coast diclofenac was detected in seawaters in concentration ranging between 0.46 ng/L and 241 ng/L (Lolic et al., 2015). Among the NSAIDs and analgesics studied, diclofenac was the only pharmaceutical that showed to present an ecotoxicological risk to fish (Lolic et al., 2015). The results here obtained suggest that diclofenac contamination was prevalent in mussels along all coastal waters of Portugal. On other hand, our results suggest that diclofenac levels found in mussels were strictly connected to the population density and high economic output. In general, these parameters are correlated with the consumption of pharmaceuticals such as diclofenac and congeners. Additionally, widespread diclofenac contamination found in mussels suggests that this species can be a bioindicator of diclofenac contamination in coastal seawaters. However, it will be necessary to extend this type of studies to other coastal areas in order to a further validation of a biomonitoring system using mussels. Primarily, a deep investigation should carry-out to develop standardized methods at international level for the quantification of pharmaceuticals in mussels. Furthermore, it is necessary to search the relation between the diclofenac levels in mussels
5.0 500.0
4.5 4.0
Diclofenac μg/kg
3.0 300.0 2.5 2.0 200.0 1.5 1.0
100.0
Popula on (10x2 persons)
400.0
3.5
0.5 0.0 January March May July October January March May July October January March May July October January March May July October January March May July October January March May July October January March May July October January March May July October
0.0
Viana do Castelo
Matosinhos
Aveiro
Peniche
Algés
Costa da Caparica
Aljezur
Faro
Fig. 3. Average concentration of diclofenac (mg/kg, dw) in mussels collected in 8 distinct sites along the 1115 miles of coastline in Portugal in 2015 (n ¼ 2, error bars) versus the population served by the sampling spots.
Please cite this article in press as: Cunha, S.C., et al., Mussels as bioindicators of diclofenac contamination in coastal environments, Environmental Pollution (2017), http://dx.doi.org/10.1016/j.envpol.2017.02.061
S.C. Cunha et al. / Environmental Pollution xxx (2017) 1e7
7
s with 2.5 mg/kg (dw) of diclofenac and 20 mg/kg of IS. Fig. 4. MRM chromatogram of a mussel sample of Alge
and its living environment. Therefore, mussels can be viewed as potential bioindicator of diclofenac contamination of coastal waters. 4. Conclusions In this study, a modified QuEChERS method was successfully applied for extraction of diclofenac in mussels and algae with good figures of merit and minor matrix effects. The phase separation induced by the addition of ammonium chloride provided to be more efficient than that achieved by using ammonium acetate or ammonium formate, ensuring the effective extraction of diclofenac by the extractive solvent (10% formic acid in MeCN). Dispersive solid-phase extraction with Z-Sepþ, C18 and MgSO4 was used as cleanup procedure, providing effective removal of bulk interferences. The developed method (modified QuEChERS followed by LC-MS/MS) was validated in mussels and algae according the performance criteria established to EU guidelines allowing the determination of diclofenac at trace levels (ng/g, d.w.). Diclofenac contamination in mussels was investigated in 8 sites along 1115 miles of Portuguese coastline along the 2015 year. Diclofenac contamination was widespread in mussels along the coastal waters of Portugal. The levels of diclofenac in mussels tend to be higher in areas of higher population density during the summer period. Mussels can be a potential bioindicator of diclofenac contamination of coastal waters due their large filter-feeding activity. Acknowledgments This work received financial support from project UID/QUI/ 50006/2013 - POCI/01/0145/FEDER/007265 with financial support from FCT/MEC through national funds and co-financed by FEDER, under the Partnership Agreement PT2020. Sara C. Cunha acknowledges FCT for the IF/01616/2015 contract. References mez, E., 2014. Anal. Bueno, M.J.M., Boillot, C., Munaron, D., Fenet, H., Casellas, C., Go Bioanal. Chem. 406, 601e610. Cerqueira, M.B., Guilherme, J.R., Caldas, S.S., Martins, M.L., Zanella, R., Primel, E.G., 2014. Chemosphere 107, 74. Commission Decision (2002/657/EC), 2002. Off. J. Eur. Communities. http://eur-lex. europa.eu/legal-content/EN/TXT/?uri¼CELEX%253A32002D0657 (Accessed in February 2017). €rlin, L., Larsson, D.G.J., 2011. Environ. Cuklev, F., Kristiansson, E., Fick, J., Asker, N., Fo Toxicol. Chem. 30, 2126. Cunha, S.C., Fernandes, J.O., 2013. Food control. 33, 549. Cunha, S.C., Pena, A., Fernandes, J.O., 2015. J. Chromat. A 1414, 10. n, G., Kumblada, L., 2010. Aquat. Toxicol. 99, 223. Ericson, H., Thorse European Commission, 2008. directive 2008/56/EC of the European Parliament and
of the Council of the 17 June 2008 establishing a framework for community action in the field of marine environmental policy (marine strategy framework directive). Eur. Comm. http://eur-lex.europa.eu/LexUriServ/LexUriServ.do? uri¼OJ:L:2008:164:0019:040:EN:PDF0. Geissen, V., Mol, H., Klumpp, E., Umlauf, G., Nadal, M., Ploeg, M.V., Zee, S.E.A.T.M., Ritsema, C.J., 2015. Inter Soil Water Conserv. Res.J. 1358 3, 57. lez-Curbelo, M.A., ndez-Borges, J., RodríguezGonza Lehotay, S.J., Herna 2014. J. Chromatogr.A 1358, 75. Delgado, M.A., Gonzalez-Rey, M., Bebianno, M.J., 2013. Environ. Pollut. 173, 200e209. Helcom, 2015. http://www.helcom.fi/action-areas/waste-water-litter/ pharmaceuticals/basic-facts/ (Accessed in February 2017). €llner, B., Dietrich, D.R., Hitzfeld, B., 2005. Aquat. Toxicol. 75, 53. Hoeger, B., Ko Infarmed, 2014. Estatística do medicamento e produtos de saúde. www.infarmed. pt/ (Accessed in Juy of 2016). ^s Do Mar E Da Atmosfera, I.P. - Despacho N.o IPMA. 2015. “IPMA, Instituto Portugue rio Da República, 2a Se rie 78: 9942e49. 4022/2015.” Dia Johnson, A.C., Dumont, E., Williams, R.J., Oldenkamp, R., Cisowska, I., Sumpter, J.P., 2013. Environ. Sci. Technol. 47, 12297. Kallio, J.M., Lahti, M., Oikai, A., Kronberg, L., 2010. Environ. Sci. Technol. 44, 7213. Kot-Wasik, A., Debska, J., Namiesnik, J., 2007. Trends Anal. Chem. 26, 557. Lehotay, S.J., Sapozhnikova, Y., Han, L., Johnston, J.J., 2015. J. Agric. Food Chem. 63, 10341. ^ Ramos, F., 2015. Environ. Leston, S., Nebot, C., Nunes, M., Cepeda, A., Pardal, M.A., Toxicol. Pharmacol. 3, 77. Li, J., Qu, X., Su, L., Zhang, W., Yang, D., Kolandhasamy, P., Li, D., Shi, H., 2016. Environ. Pollut. 214, 177. Loli c, A., Paíga, P., Santos, L.H., Ramos, S., Correia, M., Delerue-Matos, C., 2015. Sci. Total Environ. 508, 240. McEneff, G., Barron, L., Kelleher, B., Paull, B., Quinn, B., 2014. Sci. Total Environ. 476e477, 317. Mehinto, A.C., Hill, E.M., Tyler, C.R., 2010. Environ. Sci. Technol. 44, 2176. Mezzelani M., Gorbi S., Da Ros Z., Fattorini D., d'Errico G., Milan M., 2016. Norman, 2017. http://www.normandata.eu/ (Accessed in February 2017). ~ ez, M., Borrull, F., Fontanals, N., Pocurull, E., 2015. Anal. Bioanal. Chem. 407, Nún 3841. Oaks, J.L., Gilbert, M., Virani, M.Z., Watson, R.T., Meteyer, C.U., Rideout, B.A., Shivaprasad, H.L., Ahmed, S., Iqbal, C.M.J., Arshad, M., Mahmood, S., Ali, A., Khan, A., 2004. Nature 427, 630. OSPAR, 2013. OSPAR list of chemicals for priority action (revised 2013): reference number 2004-13. Conv. Prot. Mar. Environ. North-East Atl. (OSPAR ). www. ospar.org (Accessed in February 2017). Petrovic, M., Meritxell, G., Barcello, D., 2006. J. Chromatogr. A 1124, 68. , M., de Alda, M.L., Perez, S., Postigo, C., Ko €ck, M., Radjenovic, J., Petrovic, M., Farre Gros, M., Barcelo, D., 2010. J. Chromatorg. A 1217, 4004. Phillips, D.J.H., Rainbow, P.S., 1993. Biomonitoring of Trace Aquatic Contaminants. Elsevier Applied Science, New York, NY. Rabiet, M., Togola, A., Brissaud, F., Seidel, J.-L., Budzinski, H., Elbaz-Poulicher, F., 2006. Environ. Sci. Technol. 40, 5282. Richardson, S.D., 2012. Environmental mass spectrometry: emerging contaminants and current issues. Anal. Chem. 84, 747. Schwaiger, J., Ferling, H., Mallow, U., Wintermayr, H., Negele, R.D., 2004. Aquat. Toxicol. 68, 141. Sousa, A., 2013. Analysis of Pharmaceutical Residues in Wastewaters, Surface and Drinking Waters - Study of the Removal Efficiency through Conventional and Advanced Treatment Processes (Porto). Taggart, M.A., Cuthbert Das, R.D., Sashikumar, C., Pain, D.J., Green, R.E., Feltrer, Y., Shultz, S., Cunningham, A.A., Meharg, A.A., 2007. Environ. Pollut. 147, 60. Triebskorn, R., Casper, H., Scheil, V., Schwaiger, J., 2007. Anal. Bioanal. Chem. 387, 1405. €, M., 2014. Environ. Int. 69, 28. Vieno, N., Sillanp€ aa Wang, X.-.C., Zhao, H.eM., 2008. J. Costal Res. 1056e1061.
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Mussels as bioindicators of diclofenac contamination in coastal environments* S.C. Cunha a, *, A. Pena b, J.O. Fernandes a a
LAQV-REQUIMTE, Laboratory of Bromatology and Hydrology, Faculty of Pharmacy, University of Porto, Rua Jorge de Viterbo Ferreira 228, 4050-313 Porto, Portugal b LAQV-REQUIMTE, Group of Bromatology, Pharmacognosy and Analytical Sciences, Faculty of Pharmacy, University of Coimbra, Polo III, Azinhaga de Sta Comba, 3000-548 Coimbra, Portugal
a r t i c l e i n f o
a b s t r a c t
Article history: Received 7 January 2017 Received in revised form 27 February 2017 Accepted 27 February 2017 Available online xxx
Diclofenac a nonsteroidal anti-inflammatory drug (NSAID) has been confirmed as an emerging contaminant in the aquatic environment. Toxicology studies have revealed that harmful effects may emerge from diclofenac presence not only for human health, but also for marine organisms, which implies its monitoring. To overcome the demanding challenges of diclofenac quantification in biotic aquatic species, a novel method for the determination of diclofenac in mussels (Mytilus galloprovincialis and Mytilus edulis) and macroalgae (Laminaria digitata) using high performance liquid chromatography coupled to tandem mass spectrometry was developed and validated according to the EC Decision 2002/ 657/EC. Additionally, a study was done about diclofenac contamination in mussels collected from 8 sites along the 1115 miles of coastline in Portugal in 2015. The results suggested that levels in mussels are closely related to the environmental contamination. Therefore, mussels can be a potential bioindicator of diclofenac contamination in the coastal environment. © 2017 Elsevier Ltd. All rights reserved.
Keywords: Diclofenac Macroalgae Mussels Contaminants LC-MS/MS
1. Introduction In the last years, the focus of environmental research has been gradually changing from the conventional “priority pollutants”, such as polychlorinated biphenyls, polycyclic aromatic hydrocarbons, and pesticides, to the so-called “emerging pollutants” (EPs) such as flame retardants, disinfection by-products, pharmaceuticals and personal care products (Sousa, 2013; Geissen et al., 2015). These are chemicals that are not commonly monitored in the environment, but which have the potential to enter into the diverse environmental compartments and cause adverse ecological and human health effects (Geissen et al., 2015). Some EPs as most of the pharmaceutical compounds are not new chemicals but substances that have been present for a long time in the environment and whose presence and significance are only now being elucidated (Norman, 2017).
*
This paper has been recommended for acceptance by Klaus Kummerer. rio de Bromatologia e Hidrologia, Faculdade de * Corresponding author. Laborato cia, Universidade do Porto, Rua Jorge de Viterbo Ferreira 228, 4050-313 Porto, Farma Portugal. E-mail address: [email protected] (S.C. Cunha).
Pharmaceuticals used for the treatment of human or animal illness are commonly excreted via urine and/or faeces, and are thereafter subject to inadequate removal during conventional wastewater treatment. As a result, pharmaceuticals are ubiquitous compounds, often persistent and bioaccumulative in the environment, particular in the aquatic ecosystem (Kot-Wasik et al., 2007). Diclofenac is a non-steroidal anti-inflammatory drug (NSAID), used in the treatment of post-operative pain, rheumatoid arthritis, and the chronic pain regularly associated with cancer, widespread used worldwide. For example, during the year of 2014 about 1 054 952 packages were provided in the National Health Service in Portugal (Infarmed, 2014). Due to its widespread and growing use, it is needed to create sound knowledge about its incidence, levels and fate in the environment, as well as to explain its long-term risks, ecotoxicity and human health impact (Sousa, 2013). Several studies have described physiological and behavioural effects on fish when exposed at environmental or near environmental levels of diclofenac. Cytological changes in rainbow and brown trout tissues (kidney and gills) were found to be induced by exposure to diclofenac in aquatic environments (Schwaiger et al., 2004; Hoeger et al., 2005; Triebskorn et al., 2007). Mehinto et al. (2010) reported that exposure of rainbow trout to diclofenac lead
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to tissue damage. Additionally, diclofenac can affect the gene expression in fish (Cuklev et al., 2011). This NSAID has also been associated with the serious reduction of the Gyps vultures in Asia due to renal failure and visceral gout, and ultimately death (Oaks et al., 2004; Taggart et al., 2007). Due to diclofenac direct and indirect toxicity to vertebrates, it has been recently suggested to be added into the list of priority substances in the EU's Water Framework Directive (2013/39/EU). Legislation on maritime water bodies as the Directive 2008/56/EG (European Commission, 2008) (maritime strategy framework directive-MSFD; European Commission, 2008) and the HELCOM (Baltic Marine Environment Protection Commission) (Helcom, 2015) are considering the insertion of some pharmaceuticals in routine monitoring programs, whereas the OSPAR Commission has already recognized clotrimazole as “substance for priority action” and a wider range of pharmaceuticals as “substances of possible concern” (OSPAR, 2013). Assessment of environmental exposure to chemicals can be achieved through the use of indicator species such as algae or bivalves. These biomarker species accumulate pollutants in their tissues from the surrounding environment being therefore important biomonitoring devices. Filter feeders, such as bivalves (clams and mussels) tend to concentrate metals in their gills or other tissues. Mytilus edulis became a species monitored in the United States of America as well as in other countries for changes in levels of water pollution (Phillips and Rainbow, 1993). Seaweeds as Ulva lactuca commonly found at and near effluent discharge points of fish farms have been used as an indicator for the presence of antibiotics (Leston et al., 2015). Laminaria japonica was found to bioaccumulate polycyclic aromatic hydrocarbons from the surrounding medium (Wang and Zhao, 2008). Recently, experimental studies reported that mussels were able to bioconcentrate diclofenac from the water where the mussels were exposed to (Ericson et al., 2010; Mezzelani et al., 2016). McEneff et al. (2014) reported that mussel samples collected from two sites on Irish coastline are able to uptake pharmaceutics such as trimethoprim, carbamazepine and mefenamic acid, although no evidences of diclofenac accumulation were observed. To our knowledge there are a lack of reports on diclofenac in wild mussels along an entire coastal line. The growing interest in diclofenac as an environmental contaminant has catalysed the development of analytical methods able to deal with the trace levels of the compound usually found in the different environmental compartments. Recently, some reviews have been published reporting the state-of-the-art of pharmaceutical environmental analysis (Petrovic et al., 2010; Richardson, 2012). Most of the analytical methods use liquid chromatography coupled to tandem spectrometry (LC-MS/MS) for quantitative analysis of low concentrations of diclofenac. Gas chromatographymass spectrometry (GC-MS) can be also used, although diclofenac residue usually needs to be derivatized before analysis to enhance its volatility. Most methodologies require an extraction procedure usually based on liquid extraction with moderate polar solvents followed by a clean-up step with solid-phase extraction (SPE) prior to LC-MS/MS or GC-MS analysis (Wang and Zhao, 2008; Ericson et al., 2010; Petrovic et al., 2006). Only a few studies have employed QuEChERS method which stands for “quick, easy, cheap, effective, rugged and safe” in pharmaceutical analysis (Cerqueira ~ ez et al., 2015). The advantage of QuEChERS is et al., 2014; Nún that it is a rapid, simple, and accurate method that provides a saving of time and consumables (solvents) over existing methodologies. The aforementioned analytical methods have been applied for the determination of diclofenac in various matrices such as river waters (Johnson et al., 2013), surface waters (Rabiet et al., 2006), €, 2014), wastewaters (Richardson, 2012; Vieno and Sillanp€ aa
seawaters (Loli c et al., 2015), fish (Mehinto et al., 2010; Kallio et al., 2010) and mussels (McEneff et al., 2014), but none directly applied to macroalgae. Taking this into consideration, the aim of present work was to develop a simple and reliable analytical method that not only assures the unequivocal identification and quantification of diclofenac at very low levels, but also allows a common pretreatment process (preservation, extraction and clean-up) for two kind of matrices (mussels and algae) traditionally unwieldy to analyze. Additionally, the developed method was validated according the requirements of the Commission Decision 2002/657/EC for determination of diclofenac in mussels and algae. It was further applied in the analysis of wild mussels samples collected from 8 different sites distributed over Portugal costal, along five different seasons of 2015. 2. Experimental 2.1. Chemicals and reagents Diclofenac sodium salt (99.5% purity) and Internal Standard (IS) diclofenac-acetophenyl ring (13C6, 99.99% purity) sodium salt were acquired from Sigma Aldrich (MO, USA). The solvents acetonitrile (MeCN) and methanol (MeOH), both LC-MS grade, were obtained from VWR (PA, USA). Acetic acid (purity >99%) and formic acid (purity >99%) were both obtained from Merck, (Darmstadt, Germany). The salts ammonium acetate (NH4CH3CO2, 97% purity), ammonium chloride (NH4Cl, 99.8% purity) and ammonium formate (NH4HCO2, 99.99% purity) were obtained from AppliChem Panreac ITW companies (Barcelona Spain), Merck, and Sigma Aldrich, respectively. The sorbents sulfate magnesium (MgSO4) and Z-sep were both obtained from Sigma-Aldrich. Ultrapure water was obtained daily from a “Seradest LFM 20” system (Seral, RansbachBaumbach, Germany). Nitrogen (nitrogen 90, 99.998% purity) was generated in-house with nitrogen generator from Sysadvance (Maia, Portugal). Ultrahigh purity Argon (99.999%) was purchased from Gasin (Maia, Portugal). 2.2. Standard solutions and validation Individual stock standard solutions of diclofenac and 13C6diclofenac (IS) were prepared in MeOH (1 mg/mL). Individual working standard solution of diclofenac at 20 mg/mL and 13C6diclofenac at 10 mg/mL were prepared from the stock solutions by appropriate dilution in MeOH, and stored at - 20 C when not in use. The stability and accuracy of diclofenac in solution were guaranteed using two individual stock solutions, prepared and analyzed on days 0, 30 and 60. The same protocol was used to the standard solutions used in recovery and matrix-matched calibration curves. The method was validated in agreement with internationally recognized principles, such as linearity, recovery, repeatability, sensitivity (limits of detection and quantification), decision limit (CCa), detection capability (CCb), selectivity, and robustness. Validation criteria were adopted from guidelines for residues according to Commission Decision 2002/657/EC [30]. Linearity was studied in mussels and Laminaria digitata samples (free of analytes) spiked at 6 concentration levels, covering a range between 0.5 and 50 ng/g. The relationship between peak area ratios of analyte/IS and concentrations in the investigated concentration range was assessed by the coefficient of determination (R2). Recovery and repeatability were evaluated in simultaneous through the analysis of 6 blank samples spiked, before extraction, at 1, 5 and 20 ng/g with diclofenac only. The internal standard was added to the extracts at the end of the sample preparation with the aim of allowing the estimation of analyte loss during processing.
Please cite this article in press as: Cunha, S.C., et al., Mussels as bioindicators of diclofenac contamination in coastal environments, Environmental Pollution (2017), http://dx.doi.org/10.1016/j.envpol.2017.02.061
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3
The acceptance criterion set for the relative standard deviation (RSD) of the repeatability was 20% at all spiking levels. CCa and CCb were also achieved using blank samples spiked, since there is no allowed limit established for diclofenac. Blank tests were achieved to control potential cross contamination during sampling and storage, or coming from equipment. Thus, as realized in previous works as internal quality control, two solvent injections and two procedural blanks were inserted into each analytical batch made up of ten samples (Cunha and Fernandes, 2013).
and October 2015 (5 sampling campaigns). As presented in Table 1, all specimens were of similar size and satisfied the legal requirements of harvestable size or weight for human consumption. The total number of individual organisms collected from the sampling sites was 1225. Individual biometrics averaged: shell length: 5.01 ± 0.85 cm, shell width: 2.56 ± 0.49 cm and shell height 1.87 ± 0.27 cm. Wet weight (w.w.) ranged between 8.99 ± 3.65 g and 3.27 ± 1.85 g, with and without shell, respectively. Condition index (CI), quantified as the ratio shown in Equation (1) (GonzalezRey and Bebianno, 2013), averaged 32.57 ± 4.09%.
2.3. Site characterization and sample collection
CIð%Þ ¼
Marine mussels M. galloprovincialis and Mytilus edulis were sampled from eight locations along the Portuguese Atlantic coast (Fig. 1), from the coastline, between the parallels presented bellow and the coast, including the intertidal zone and the bathymetry of 70 m; and from a river estuary: L1 Viana coastline area between the parallels 41.86745 N (Minho River) and 41.27064 N (Angeiras River Donda mouth); L2 Matosinhos coastline area between the parallels 41.27064 N and 40.93119 N (Maceda); L3 Aveiro coastline area between the parallels 40.93119 N and 40.44507 N (South Bank of Mira Lagoon); L5 (a, b, c) Peniche/Lisbon coastline area between the parallels 39.45783 N and 38.52222 N ~o); L7 Aljezur St. Vincent coastline area between the (Garalha parallel 37.45167 N (north of the mouth Seixe creek) and the circle defined by the points: (1) 8.9970 W, 37.02270 N (St. Vincent Cape) and (2) 9.12820 W, 36.84378 N (south - south-west of St. Vincent ~o coastline zone between the meridian Cape); L8 Faro Olha 8.12486 W and 7.65535 W meridian (East of Sta Luzia) (IPMA, 2015). Mussels were sampled during one year, between January 2015
In order to reduce the variability effect due to use of organic matrix (Bueno et al., 2014), each composite sample consisted of 25 specimens (edible content) of similar size collected from each sampling site in each campaign. Each pool was grinded, (Retasch Grindomix GM200, Germany), homogenized, and frozen at 80 C in plastic tubes of 40 mL. To conclude, the samples were freezedried for 48 h at 80 C and low pressure (around 0.017 mBar, Telstar Cryodos, Grundy's LaneBristol), homogenized and maintained at 4 C until analysis. Laminaria digitata was randomly collected in a local market in the city of Porto, Portugal.
whole soft tissue wet weightðgÞ 100 whole body weight with shell ðgÞ
(1)
2.4. Optimized sample preparation Sample preparation entailed the following steps: (1) 0.5 g homogenized freeze-dried sample was added with 50 mL IS at 500 ng/ mL (the tubes were vortexed for 1 min to improve the incorporation of IS into the sample and kept in contact for 30 min); (2) 3.5 mL of H2O and 3.5 mL of MeCN with 10% (v/v) formic acid were added
Fig. 1. Location of the sampling sites along the Portuguese coast.
Please cite this article in press as: Cunha, S.C., et al., Mussels as bioindicators of diclofenac contamination in coastal environments, Environmental Pollution (2017), http://dx.doi.org/10.1016/j.envpol.2017.02.061
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Table 1 Mean individual shell biometric and condition index (CI) estimation ± standard deviation for each sampling site along the five sampling campaigns. Location
Length (cm)
Viana do Castelo (L1) Matosinhos (L2) Aveiro (L3) Peniche (L5 a) s (L5 b) Alge Costa Caparica (L5 c) Aljezur (L7) Faro (L8)
4.59 4.73 4.24 4.15 4.70 5.45 5.45 6.73
± ± ± ± ± ± ± ±
0.05 0.09 0.10 0.17 0.15 0.19 0.29 0.14
Width (cm) 2.23 2.32 2.06 2.15 2.56 2.68 2.91 3.54
± ± ± ± ± ± ± ±
0.03 0.06 0.06 0.03 0.07 0.05 0.12 0.06
Height (cm) 1.69 1.76 1.55 1.57 1.92 2.11 2.03 2.31
± ± ± ± ± ± ± ±
0.03 0.07 0.04 0.07 0.13 0.09 0.17 0.08
whole body weight with shell (g)
whole soft tissue wet weight (g)
6.06 ± 0.53 6.48 ± 0.56 5.35 ± 0.65 5.22 ± 0.94 9.85 ± 1.90 12.77 ± 2.44 12.14 ± 3.48 14.09 ± 0.27
1.86 2.59 1.71 1.62 3.21 3.94 5.06 7.17
and the tubes were vortexed for 3 min; (3) 2.5 g of NH4Cl were added and the tubes were mix for 15 min in an automatic shaker and centrifuged at 2700 rcf for 5 min; (4) 1 mL of the MeCN extract was transferred to a d-SPE tube containing 150 mg anh. MgSO4 and 50 mg Z-Sep, vortexed for 1 min, and centrifuged at 2700 rcf for 1 min; (5) 0.5 mL of the extract was transferred for an injection tube and evaporated under a stream of nitrogen; (6) the dry extract was reconstituted with 200 mL of HPLC mobile phase.
2.5. Apparatus and LC-MS/MS conditions A high-performance liquid chromatography (HPLC) system Waters Alliance 2695 (Waters, Milford) was interfaced to a Quattro Micro triple quadrupole mass spectrometer (Waters, Manchester, UK). LC separation was performed using a Kinetex C18 2.6 m particle size analytical column (150 4.6 mm) with pre-column from Phenomenex (Tecnocroma, Portugal), at a flow-rate of 300 mL/min. The column was maintained at 30 C and the auto-sampler was kept at ambient temperature (±25 C). Mobile phase consisted of a mixture of A: MeCN containing 0.1% acetic acid (25%), and B: water at pH 3.5 (adjusted with acetic acid) (75%) in isocratic mode. The sample injection volume was 10 mL and total run time was 14 min. Mass analysis was performed with an ESI source in the negative ion mode (ESI-) for all the analytes because of its higher sensitivity compared with the positive ion mode (ESIþ). Nitrogen was used as the nebuliser gas. The optimum MS parameters were: capillary, 3.00 kV; extractor, 2 V; RF Lens, 0.5 V; Source Temperature, 150 C; Desolvation Temperature, 350 C; Desolvation Gas Flow, 550.0 L/h; Cone Gas Flow, 60.0 L/h; LM Resolution, 13.0; Ion energy, 1.0; Entrance, 1; Exit, 2; Multiplier, 650. The data were collected using the software programme MassLynx4.1. All calculations were based on chromatographic peak area ratios for the multiple reaction monitoring (MRM) precursor-product ion transitions for analyte to the precursor-product ion transition of the internal standard. For each analyte, two transitions were selected for identification, and the corresponding cone voltage and collision energy were optimized for maximum intensity. The optimized MS/ MS parameters for the target compounds are listed in Table 2.
± ± ± ± ± ± ± ±
CI (%)
0.25 0.29 0.20 0.29 0.54 0.83 1.05 1.77
31.15 31.53 40.72 29.42 27.27 32.73 32.17 35.59
± ± ± ± ± ± ± ±
0.48 0.79 0.37 0.37 0.46 0.65 1.67 3.62
3. Results and discussion 3.1. Optimization of HPLC-MS/MS analysis Individual standard solutions of 50 mg/L were prepared in methanol for MS optimization by infusion experiments, being optimized both full-scan mass spectra and MS/MS spectra in order to obtain the maximum number of available transitions for each compound. Negative ion mode was chosen due its best sensitivity and less baseline noise. For diclofenac and IS the two most sensitive Selected Reaction Monitoring (SRM) transitions were selected for each compound: the most abundant was used for quantification (Q) whereas the second one was for confirmation (q) purposes, which is a suitable confirmatory method in accordance with 2002/657/EC (Table 2). Selection of suitable mobile phase plays an important role in the ionization efficiency before the analytes enter the MS/MS system. Mixtures of MeCN/water or MeOH/water acidified or not with acetic or formic acid, and added with a buffer such as ammonium acetate are commonly candidates as the mobile phase in LC analysis. The experimental results showed that, MeCN with 0.1% acetic acid as the organic modifier, combined with water adjusted at pH 3.5 with acetic acid provided the best results. 3.2. Optimization of sample preparation In this study three different alternative versions of the QuEChERS method based on the use of ammonium chloride, ammonium formate or acetate buffers were assessed in order to reduce the matrix effect and enhance extraction recovery for diclofenac in mussels and algae. Among the macroalgae found in Portuguese coastal the Laminaria digitata was chosen due to be more widely and frequently distributed throughout the study period. The optimization was performed using mussel/algae freezedried samples spiked with diclofenac (to achieve a concentration of 1 mg/g) before and after the extraction procedure; the IS 13C6 diclofenac was always added after extraction procedure. Each experiment was evaluated in duplicate in order to calculate the % of the recovery. Initially, acetonitrile mixture composition was adjusted to ensure a high extraction yield of diclofenac together with the reduction as much as possible of the co-extracted substances namely lipids and waxes. Acetonitrile/water mixtures, commonly used in QuEChERS method, have been found to provide significantly higher extraction efficiencies for polar analytes (Cunha
Table 2 LC-MS/MS parameters for analysis of diclofenac and IS (13C6 diclofenac). Analytes
Retention time (min)
Diclofenac Diclofenac
6.81 13
C16
6.83
Precursor ion (Da)
294 [M-H] 296 [(Mþ2)-H] 300 [M-H]
Product ions (Da)
250 [M-H-CO2] 252 [(Mþ2)-H-CO2] 256 [M-H-CO2]
Cone energy (V)
Collision energy (kV)
Dwell time (ms)
16 16 15
12 12 13
0.2 0.2 0.1
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S.C. Cunha et al. / Environmental Pollution xxx (2017) 1e7
lez-Curbelo et al., 2014). Besides, it is and Fernandes, 2013; Gonza relevant the ratio between sample weight and solvent volume employed, since the water present in the sample can modify markedly solubility parameters. Commonly, for samples with less of 80% moisture, sample amount used for analysis need to be reduced and water is added to accomplish more than 80% by volume regarding added MeCN. In this study, 4 mL of water was added to 0.5 g of freeze-dried sample, to promote the efficiency of the extraction solvent. Other crucial parameter to be optimized is the pH of the extraction. Taking into account the pKa of diclofenac (4.15) acidification of acetonitrile with acetic and formic acid at 1%, 5% and 10% were evaluated. Significantly better recoveries were achieved when using 10% (v/v) formic acid in acetonitrile as the extraction solvent (Fig. 2). In original QuEChERs phase separation is usually achieved through the addition of magnesium sulfate combined with sodium chloride or citrate salts. Unfortunately, these salts/ions are nonvolatile and may therefore accumulate in the LC-MS interface. To overcome this limitation, ammonium chloride (NH4Cl), ammonium formate (NH4HCO2) and ammonium acetate (NH4CH3CO2) have been recently tested with success in pesticide residue analysis lez-Curbelo et al., 2014). Thus, in this study 0.5 g of freeze (Gonza dried (containing around 2% of moisture) was added with 4 mL of H20 and 4 mL of 10% formic acid in MeCN plus 3.5 g of NH4Cl or NH4HCO2 or NH4CH3CO2. The lower pH was obtained using the 10% formic acid in MeCN added with NH4Cl (pH 2), NH4HCO2 (pH 3) or NH4CH3CO2 (pH 5). As shown in Fig. 2, the best recovery result was achieved with the mixture of 10% formic acid in MeCN and NH4Cl. One of the greatest drawbacks of LC-MS is usually the perturbation of the signal by co-extracted substances from sample matrix, especially in complex matrices as is the case of mussels and algae. For this reason, the second step of QuEChERS where the extract is cleaned up by using a dispersive solid-phase extraction (dSPE) was performed. A mixture of Z-Sepþ (50 mg), C18 (50 mg) and MgSO4 (150 mg) was evaluated using 1 mL of QuEChERS extract, with the purpose to remove co-extracted substances present in the matrix. C18 sorbent has been widely used to eliminate hydrophobic matrix compounds from various food samples. dSPE Z-Sepþ was also employed to eliminate matrix-related compounds from samples with high fat and/or wax contents (Lehotay et al., 2015). The strategy here adopted proved to be successfully, providing an acceptable recovery for diclofenac in mussels (average of 83%) and algae (average of 79%) concurrently with a significant reduction of co-extractives.
5
3.3. Analytical performance Initially, experiments were conducted to evaluate the matrix effect. Hence, the slopes of the calibration curve of standard solutions were compared with those obtained in matrix-matched standards (standards added to blank samples of mussels and Laminaria digitata). The method showed a slight enhancement of response for diclofenac. Similar effect was verified in previous works for other compounds (Cunha and Fernandes, 2013; Lehotay et al., 2015; Cunha et al., 2015), depending on the chemical characteristics of the analyte itself and the existence of other ionisable substances present in the extract. Therefore, linearity was evaluated using matrix-matched calibration solutions (standards added to blank samples) prepared as described in Section 2. The results obtained demonstrated a good linearity within the tested range, with r2 higher than 0.9967. Recovery results for three levels of concentration (described in Section 2) are presented in Table 3. Overall, recoveries were in the range 69e99%, with some slightly differences between the levels assessed. Precision was assessed in terms of intra-day repeatability as % RSD at three concentration levels through the analysis of six replicated spiked sample extracts. Either in mussels and Laminaria digitata samples, RSD values ranged from 9% to 20%; as expected worse RSD values were obtained from the lowest level (Table 3). Limits of detection (LOD) and quantification (LOQ) of unregulated compounds (without a maximum residue limit-MRL) were determined by estimating the concentration where a signal to noise ratio of three to one and ten to one, respectively, was observed. LOD values of 0.2 ng/g and 0.3 ng/g and LOQ values of 0.5 and 1 ng/g were achieved for mussels and algae, respectively. Because no MRL is established, CCa was evaluated analysing 20 blanks and calculating the signal noise ratio at the time window in which the
Table 3 Average of recovery for 1,5 and 20 mg/kg (%, n ¼ 6), repeatability (%RSD, n ¼ 6), method limit of detection (LOD), limit of quantification (LOQ), decision limit (CCa) and detection capability (CCb). Analyte
Matrices
% Recovery (RSD%) 1 mg/kg
5 mg/kg
20 mg/kg
Diclofenac
Mussel Algae
69 (18) 70 (20)
86 (16) 74 (9)
97 (11) 99 (12)
LOD
LOQ
CCa
CCb
0.2 0.3
0.5 1
0.35 0.5
0.5 0.75
100 90
Mussels
Algae
80
% Recovery
70 60 50 40 30 20 10 0 1% formic acid 1% formic acid 1% formic acid 5% formic acid 5% formic acid 5% formic acid 10% formic acid10% formic acid10% formic acid in MeCN and in MeCN NH4Cl in MeCN and in MeCN and in MeCN NH4Cl in MeCN and in MeCN and in MeCN NH4Cl in MeCN and NH4CH3CO2 NH4HCO2 NH4CH3CO2 NH4HCO2 NH4CH3CO2 NH4HCO2
Fig. 2. Recovery (%) of diclofenac in mussels and algae spiked with 1 mg/g obtained through QuEChERS procedure using MeCN with 1%, 5% and 10% formic acid and different salts such as NH4Cl, NH4HCO2 or NH4CH3CO2 (n ¼ 3).
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S.C. Cunha et al. / Environmental Pollution xxx (2017) 1e7
analyte was expected and CCb was determined by analysing 20 blanks spiked at CCa (Commission Decision, 2002/657/EC). CCa and CCb achieved for this method ranged from 0.3 to 0.6 ng/g and from 0.5 to 0.75 ng/g for mussels and algae, respectively, being within the requested range (see Table 3). Method selectivity was assessed by analysis of blank samples of each matrix (n ¼ 3) and no interference peaks were observed at the retention time of the diclofenac. Method robustness was assessed by performing minor changes on the main LC parameters: acetic acid concentration of the mobile phase, pH and flow rate. Minor changes in acetic acid concentration (±0.01%) or pH (±0.1%) of the mobile phase did not significantly disturb the separation namely resolution and peak shape. Equal behaviour was verified when flow rate was slightly changed (±0.02 mL/min) no differences in retention time, resolution or peak shape were detected (<10%). Concerning the solutions stability, concentrations of both stock and working standard solutions were stable for 60 days storage at 20 C. 3.4. Occurrence of diclofenac in Portuguese coastal In the present study, diclofenac was for the first time quantified in mussels collected from an extensive geographic area along Portuguese coastal line. Fig. 3 summarises the results obtained in mussels collected in 8 distinct sites during the year of 2015. The results obtained suggest that diclofenac contamination was widespread in wild mussels along the coastal waters of Portugal, being detected in 7 out of 8 sites studied with positive levels ranging from 0.5 to 4.5 mg/kg (dry weight, d.w.). Fig. 4 shows a MRM chros with 2.5 mg/ matogram of a mussel sample collected in July in Alge kg d.w. of diclofenac. The highest concentrations of diclofenac were found in Matosinhos and Costa da Caparica with 4.5 and 4.0 mg/kg d.w., respectively. These results may be induced by the harmful effects of the several anthropogenic activities in these areas known that WWTPs located in the adjacent area discharge their effluents ~es in these points and these beaches are also influenced by Leixo and Lisbon seaport activities. Additionally, Matosinhos and Costa da Caparica sampling points are very close of cities with the highest population density of Portugal namely Porto and Lisbon. As can be seen in Fig. 3 diclofenac levels variation along each sampling point
is somewhat correlated with the population density of the surrounding area. Seasonality of the diclofenac concentration was monitored throughout all the year, from January to October 2015 (Fig. 3). The high occurrence of detection was observed when highest concentrations were reported in July and early October. These results can be related with the increment of population in bathing areas during the summer season. Additionally, this period of the year is associated to a decrease of precipitation; as a result rivers and streams have a reduced renovation capacity, being more negatively affected by human activities as the discharges of WWTPs effluents (Loli c et al., 2015). 3.5. Mussel as potential bioindicator of diclofenac contamination Mussels have been extensively used as sentinels in “Mussel Watch Programme” to describe the current status of aquatic contamination and to detect changes in the environmental quality of estuarine and coastal waters (Li et al., 2016). Nevertheless, they are not used yet as bioindicator for NSAIDs contamination along the coastal waters worldwide. In a recent study along the north Portuguese coast diclofenac was detected in seawaters in concentration ranging between 0.46 ng/L and 241 ng/L (Lolic et al., 2015). Among the NSAIDs and analgesics studied, diclofenac was the only pharmaceutical that showed to present an ecotoxicological risk to fish (Lolic et al., 2015). The results here obtained suggest that diclofenac contamination was prevalent in mussels along all coastal waters of Portugal. On other hand, our results suggest that diclofenac levels found in mussels were strictly connected to the population density and high economic output. In general, these parameters are correlated with the consumption of pharmaceuticals such as diclofenac and congeners. Additionally, widespread diclofenac contamination found in mussels suggests that this species can be a bioindicator of diclofenac contamination in coastal seawaters. However, it will be necessary to extend this type of studies to other coastal areas in order to a further validation of a biomonitoring system using mussels. Primarily, a deep investigation should carry-out to develop standardized methods at international level for the quantification of pharmaceuticals in mussels. Furthermore, it is necessary to search the relation between the diclofenac levels in mussels
5.0 500.0
4.5 4.0
Diclofenac μg/kg
3.0 300.0 2.5 2.0 200.0 1.5 1.0
100.0
Popula on (10x2 persons)
400.0
3.5
0.5 0.0 January March May July October January March May July October January March May July October January March May July October January March May July October January March May July October January March May July October January March May July October
0.0
Viana do Castelo
Matosinhos
Aveiro
Peniche
Algés
Costa da Caparica
Aljezur
Faro
Fig. 3. Average concentration of diclofenac (mg/kg, dw) in mussels collected in 8 distinct sites along the 1115 miles of coastline in Portugal in 2015 (n ¼ 2, error bars) versus the population served by the sampling spots.
Please cite this article in press as: Cunha, S.C., et al., Mussels as bioindicators of diclofenac contamination in coastal environments, Environmental Pollution (2017), http://dx.doi.org/10.1016/j.envpol.2017.02.061
S.C. Cunha et al. / Environmental Pollution xxx (2017) 1e7
7
s with 2.5 mg/kg (dw) of diclofenac and 20 mg/kg of IS. Fig. 4. MRM chromatogram of a mussel sample of Alge
and its living environment. Therefore, mussels can be viewed as potential bioindicator of diclofenac contamination of coastal waters. 4. Conclusions In this study, a modified QuEChERS method was successfully applied for extraction of diclofenac in mussels and algae with good figures of merit and minor matrix effects. The phase separation induced by the addition of ammonium chloride provided to be more efficient than that achieved by using ammonium acetate or ammonium formate, ensuring the effective extraction of diclofenac by the extractive solvent (10% formic acid in MeCN). Dispersive solid-phase extraction with Z-Sepþ, C18 and MgSO4 was used as cleanup procedure, providing effective removal of bulk interferences. The developed method (modified QuEChERS followed by LC-MS/MS) was validated in mussels and algae according the performance criteria established to EU guidelines allowing the determination of diclofenac at trace levels (ng/g, d.w.). Diclofenac contamination in mussels was investigated in 8 sites along 1115 miles of Portuguese coastline along the 2015 year. Diclofenac contamination was widespread in mussels along the coastal waters of Portugal. The levels of diclofenac in mussels tend to be higher in areas of higher population density during the summer period. Mussels can be a potential bioindicator of diclofenac contamination of coastal waters due their large filter-feeding activity. Acknowledgments This work received financial support from project UID/QUI/ 50006/2013 - POCI/01/0145/FEDER/007265 with financial support from FCT/MEC through national funds and co-financed by FEDER, under the Partnership Agreement PT2020. Sara C. Cunha acknowledges FCT for the IF/01616/2015 contract. References mez, E., 2014. Anal. Bueno, M.J.M., Boillot, C., Munaron, D., Fenet, H., Casellas, C., Go Bioanal. Chem. 406, 601e610. Cerqueira, M.B., Guilherme, J.R., Caldas, S.S., Martins, M.L., Zanella, R., Primel, E.G., 2014. Chemosphere 107, 74. Commission Decision (2002/657/EC), 2002. Off. J. Eur. Communities. http://eur-lex. europa.eu/legal-content/EN/TXT/?uri¼CELEX%253A32002D0657 (Accessed in February 2017). €rlin, L., Larsson, D.G.J., 2011. Environ. Cuklev, F., Kristiansson, E., Fick, J., Asker, N., Fo Toxicol. Chem. 30, 2126. Cunha, S.C., Fernandes, J.O., 2013. Food control. 33, 549. Cunha, S.C., Pena, A., Fernandes, J.O., 2015. J. Chromat. A 1414, 10. n, G., Kumblada, L., 2010. Aquat. Toxicol. 99, 223. Ericson, H., Thorse European Commission, 2008. directive 2008/56/EC of the European Parliament and
of the Council of the 17 June 2008 establishing a framework for community action in the field of marine environmental policy (marine strategy framework directive). Eur. Comm. http://eur-lex.europa.eu/LexUriServ/LexUriServ.do? uri¼OJ:L:2008:164:0019:040:EN:PDF0. Geissen, V., Mol, H., Klumpp, E., Umlauf, G., Nadal, M., Ploeg, M.V., Zee, S.E.A.T.M., Ritsema, C.J., 2015. Inter Soil Water Conserv. Res.J. 1358 3, 57. lez-Curbelo, M.A., ndez-Borges, J., RodríguezGonza Lehotay, S.J., Herna 2014. J. Chromatogr.A 1358, 75. Delgado, M.A., Gonzalez-Rey, M., Bebianno, M.J., 2013. Environ. Pollut. 173, 200e209. Helcom, 2015. http://www.helcom.fi/action-areas/waste-water-litter/ pharmaceuticals/basic-facts/ (Accessed in February 2017). €llner, B., Dietrich, D.R., Hitzfeld, B., 2005. Aquat. Toxicol. 75, 53. Hoeger, B., Ko Infarmed, 2014. Estatística do medicamento e produtos de saúde. www.infarmed. pt/ (Accessed in Juy of 2016). ^s Do Mar E Da Atmosfera, I.P. - Despacho N.o IPMA. 2015. “IPMA, Instituto Portugue rio Da República, 2a Se rie 78: 9942e49. 4022/2015.” Dia Johnson, A.C., Dumont, E., Williams, R.J., Oldenkamp, R., Cisowska, I., Sumpter, J.P., 2013. Environ. Sci. Technol. 47, 12297. Kallio, J.M., Lahti, M., Oikai, A., Kronberg, L., 2010. Environ. Sci. Technol. 44, 7213. Kot-Wasik, A., Debska, J., Namiesnik, J., 2007. Trends Anal. Chem. 26, 557. Lehotay, S.J., Sapozhnikova, Y., Han, L., Johnston, J.J., 2015. J. Agric. Food Chem. 63, 10341. ^ Ramos, F., 2015. Environ. Leston, S., Nebot, C., Nunes, M., Cepeda, A., Pardal, M.A., Toxicol. Pharmacol. 3, 77. Li, J., Qu, X., Su, L., Zhang, W., Yang, D., Kolandhasamy, P., Li, D., Shi, H., 2016. Environ. Pollut. 214, 177. Loli c, A., Paíga, P., Santos, L.H., Ramos, S., Correia, M., Delerue-Matos, C., 2015. Sci. Total Environ. 508, 240. McEneff, G., Barron, L., Kelleher, B., Paull, B., Quinn, B., 2014. Sci. Total Environ. 476e477, 317. Mehinto, A.C., Hill, E.M., Tyler, C.R., 2010. Environ. Sci. Technol. 44, 2176. Mezzelani M., Gorbi S., Da Ros Z., Fattorini D., d'Errico G., Milan M., 2016. Norman, 2017. http://www.normandata.eu/ (Accessed in February 2017). ~ ez, M., Borrull, F., Fontanals, N., Pocurull, E., 2015. Anal. Bioanal. Chem. 407, Nún 3841. Oaks, J.L., Gilbert, M., Virani, M.Z., Watson, R.T., Meteyer, C.U., Rideout, B.A., Shivaprasad, H.L., Ahmed, S., Iqbal, C.M.J., Arshad, M., Mahmood, S., Ali, A., Khan, A., 2004. Nature 427, 630. OSPAR, 2013. OSPAR list of chemicals for priority action (revised 2013): reference number 2004-13. Conv. Prot. Mar. Environ. North-East Atl. (OSPAR ). www. ospar.org (Accessed in February 2017). Petrovic, M., Meritxell, G., Barcello, D., 2006. J. Chromatogr. A 1124, 68. , M., de Alda, M.L., Perez, S., Postigo, C., Ko €ck, M., Radjenovic, J., Petrovic, M., Farre Gros, M., Barcelo, D., 2010. J. Chromatorg. A 1217, 4004. Phillips, D.J.H., Rainbow, P.S., 1993. Biomonitoring of Trace Aquatic Contaminants. Elsevier Applied Science, New York, NY. Rabiet, M., Togola, A., Brissaud, F., Seidel, J.-L., Budzinski, H., Elbaz-Poulicher, F., 2006. Environ. Sci. Technol. 40, 5282. Richardson, S.D., 2012. Environmental mass spectrometry: emerging contaminants and current issues. Anal. Chem. 84, 747. Schwaiger, J., Ferling, H., Mallow, U., Wintermayr, H., Negele, R.D., 2004. Aquat. Toxicol. 68, 141. Sousa, A., 2013. Analysis of Pharmaceutical Residues in Wastewaters, Surface and Drinking Waters - Study of the Removal Efficiency through Conventional and Advanced Treatment Processes (Porto). Taggart, M.A., Cuthbert Das, R.D., Sashikumar, C., Pain, D.J., Green, R.E., Feltrer, Y., Shultz, S., Cunningham, A.A., Meharg, A.A., 2007. Environ. Pollut. 147, 60. Triebskorn, R., Casper, H., Scheil, V., Schwaiger, J., 2007. Anal. Bioanal. Chem. 387, 1405. €, M., 2014. Environ. Int. 69, 28. Vieno, N., Sillanp€ aa Wang, X.-.C., Zhao, H.eM., 2008. J. Costal Res. 1056e1061.
Please cite this article in press as: Cunha, S.C., et al., Mussels as bioindicators of diclofenac contamination in coastal environments, Environmental Pollution (2017), http://dx.doi.org/10.1016/j.envpol.2017.02.061