Journal of Chromatography A

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1 Journal of Chromatography A, 1518 (2017) Contents lists available at ScienceDirect Journal of Chromatography A j o ur na l ho me page: Solid phase microextraction and gas chromatography coupled to magnetic sector high resolution mass spectrometry for the ultra-trace determination of contaminants in surface water I. Domínguez, F.J. Arrebola, R. Romero-González, A. Nieto-García, J.L. Martínez Vidal, A. Garrido Frenich Analytical Chemistry of Contaminants Research Group, Department of Chemistry and Physics, Andalusian Center for the Assessment and Monitoring of Global Change (CAESCG), University of Almería, Agrifood Campus of International Excellence, ceia3, E Almería, Spain a r t i c l e i n f o Article history: Received 1 February 2017 Received in revised form 17 July 2017 Accepted 20 August 2017 Available online 24 August 2017 Keywords: SPME Magnetic sector Organic pollutants Automated method a b s t r a c t With the aim of monitoring water quality according to the regulations established by the European Union it would be necessary to implement analytical methodologies capable of simultaneously determining a broad range of organic pollutants at ultra-trace levels, allowing for increased sample throughput. In addition, the high number of samples to be analyzed requires a particular focus on setting up fully automated analytical methodologies. In view of that, this study is aimed at the development of a complete automated procedure for the ultra-trace determination of certain pesticides, polycyclic aromatic hydrocarbons (PAHs), brominated diphenyl ethers (BDEs) and polychlorinated biphenyls (PCBs) in surface waters. The proposed method is based on an on-line combination of solid phase microextraction (SPME) and gas chromatography coupled to double-focusing magnetic sector high resolution mass spectrometry (GC HRMS). SPME as well as GC HRMS conditions were optimized to achieve maximum extraction efficiency and sensitivity, which was reinforced by using multiple ion detection (MID) as acquisition mode. Using only 19 ml of water and with minimum sample manipulation, the method allowed for the determination of 53 compounds exhibiting good linearity (R 2 > 0.99), recoveries between 84 and 118% and relative standard deviation (RSD) values <20% for intra-day and inter-day precision. In addition, the method provides quantification limits (LOQs) between ng L 1, lower than the Environmental Quality Standards (EQS) fixed by Directive 2013/39/EC. Finally, the method was successfully applied to determine target contaminants in Almería surface water compartments, detecting dioxin-like PCBs, BDEs and some pesticides Elsevier B.V. All rights reserved. 1. Introduction Organic pollutants are present in the enviroment mainly due to different anthropogenic activities, such as agricultural or industrial chemical production. The combination of their extensive use and physicochemical and toxicological properties make it possible for these compounds to end up in surface water, causing a potential risk for the enviroment and human health. With the aim of controlling and preventing contamination of aquatic ecosystems, the United States Environmental Protection Agency (U.S. EPA) and the European Union (EU) introduced a series of recommend water quality Selected paper from the XVI Scientific Meeting of the Spanish Society of Chromatography and Related Techniques (SECyTA 2016), 2 4 November 2016, Seville, Spain. Corresponding author. address: agarrido@ual.es (A. Garrido Frenich). criteria [1,2]. The Water Framework Directive (WFD) set by the EU, currently Directive 2013/39/EC, includes guidelines to control the pollution of surface water introducing a list of priority substances with their respective environmental quality standards (EQS) [2]. Among other organic contaminants, the list includes certain pesticides, brominated diphenyl ethers (BDEs) and polycyclic aromatic hydrocarbons (PAHs) with EQS values in the range of 0.82 ng L 1 to 130 g L 1. Furthermore, due to their likely presence in environmental waters [3] and their toxicity and persistence, the analysis of polychlorinated biphenyls (PCBs), has to be considered. PCBs is one of the original 12 groups of compounds covered by the Stockholm Convention on persistent organic pollutants (POPs) [4] and are subject to review for possible identification as priority substances. Therefore, in order to evaluate water quality a continuous monitoring of the aforementioned compounds is required. Indeed, the increasingly stringent regulations make it necessary to develop robust, reliable and highly sensitive and selective methods capable / 2017 Elsevier B.V. All rights reserved.

2 16 I. Domínguez et al. / J. Chromatogr. A 1518 (2017) of simultaneously determining a broad range of organic pollutants at ultra-trace levels and thereby obtain a cost- and time-effective monitoring tool. However, multiclass methods are generally difficult to develop since the targeted compounds present different degrees of polarity, solubility, volatility, as well as different pk a values, making their extraction and analysis difficult [5]. In this respect, the majority of methods are focused on specific contaminant classes [6 9] and just a few methodologies have been proposed for the simultaneous determination of organic contaminants in water samples [10 12]. However, to our knowledge, the four groups of contaminants selected in this study, pesticides, PAHs, BDEs and PCBs have only been included in two previously published methods involving GC MS and stir bar sorptive extraction (SBSE) [13] and solid phase extraction (SPE) [14] approaches. On the other hand, most of these organic pollutants have adequately been analyzed by gas chromatography (GC) followed by mass spectrometry (MS) or tandem mass spectrometry (MS/MS), always after an extraction and/or pre-concentration step. Different extraction procedures have been applied to the determination of organic contaminants in environmental water, including the traditional liquid liquid extraction (LLE) [15], SPE [5,12,14] and among others, miniaturized sample preparation techniques such as solid-phase microextraction (SPME) [8,9,16], SBSE [10,13] and liquid-phase microextraction techniques (LPME) [17,18]. Nevertheless, the high and growing number of samples that needs to be analyzed make the complete automation of the analysis, including the extraction procedure, necessary because it would considerably reduce the time employed in sample manipulation and preparation as well as avoid sample contamination and analytes loss. In this regard, SPME is an extraction procedure that can easily be automated merely by using an adequate autosampler [19]. This extraction approach has been applied to the determination of BDEs [20], pesticides [6,8,16,21], PAHs [22,23] and PCBs [24] in environmental samples. However, this approach has not previously been applied to the simultaneous analysis of pesticides, PAHs, BDEs and PCBs. SPME is a great advance in sample preparation for trace analysis because it integrates sampling, extraction, concentration and sample introduction into one simple process [9]. Furthermore, this technique is easy to use, fast and only requires a small sample volume [19]. Nevertheless, the limited volume of SPME fiber coatings results in the limited extraction capacity of SPME fibers, which might result in poorer sensitivity [25]. Consequently, in order to increase method sensitivity and specificity the use of SPME coupled to a GC HRMS concretely a double-focus system (DFS) magnetic sector analyzer is proposed. GC HRMS offers a higher specificity due to its ability to provide millimass (mmu) resolution and a very high level of confidence in the results compared to GC coupled to an electron capture detector (GC-ECD) or to low resolution mass spectrometers (GC-LRMS) [3]. The application of HRMS in the ultra-trace determination of dioxins and furans is well known [26], and it has also been noticed that this system is an important tool for the analysis of pollutants at ultra-trace levels in environmental samples through the results achieved in the determination of PCBs [3,27], organochlorine pesticides (OCPs) [3], BDEs [27 29] and atrazine and their metabolites [30]. In light of all of this, the main objective of this work is to study the analytical capabilities of SPME coupled to HRMS with a DFS analyzer for the simultaneous analysis of organic pollutants in surface waters. SPME and HRMS conditions will be optimized in order to achieve high extraction efficiency and sensitivity of the method. Hereafter, the method will be validated and applied to the analysis of real surface water samples. For the first time, SPME as well as GC HRMS will be applied for the simultaneous determination of pesticides, PAHs, BDEs and PCBs so, through this study, their applicability in this type of analytical strategy will be evaluated. Furthermore, these results constitute a great advance for the development of a sensitive and fully automated methodology capable of monitoring water quality, selecting compounds (pesticides, PAHs and BDEs) listed as priority substances by the EU, as well as PCBs considered as toxic by international organizations [31,32]. 2. Material and methods 2.1. Materials and reagents Certified pesticide standards were purchased from Dr. Ehrenstorfer GmbH (Ausgburg, Germany), Riedel de Haën (Seelze, Germany) and Fluka (Steinheim, Germany). A total of 14 pesticides, all of them listed as priority substances by the EU, were included in the study: pentachlorobenzene, trifluralin, hexachlorobenzene, simazine, atrazine, aldrin, isodrin, dieldrin, endrin, chlorpyrifos, p,p -DDE, o,p -DDT, p,p -DDD and p,p -DDT. Stock standard solutions of each individual compound were prepared in acetone, with concentrations between 200 and 500 mg L 1, and stored at 20 C. A PAH standard mixture (QTM-Standard; 2 mg ml 1 for each compound in dichloromethane) containing 16 US EPA priority PAHs was purchased from Sigma-Aldrich (St. Louis, MO, USA). Naphthalene, anthracene, fluoranthene, benzo[b]fluoranthene, benzo[k]fluoranthene, benzo[a]pyrene, indene[1,2,3-cd]pyrene and benzo[ghi]perylene being the PAHs included in the list of priority substances by the EU were the compounds covered by the study. PCB individual standards were obtained from Dr Ehrenstorfer GmbH. Together with the 12 dioxin-like polychlorinated biphenyls designated as toxic by the World Health Organization (WHO) (PCB77, PCB81, PCB105, PCB114, PCB118, PCB123, PCB126, PCB156, PCB157, PCB167, PCB169 and PCB189) another 14 PCBs congeners, considered of interest to the National Oceanic and Atmospheric Administration (NOAA) of United States, were included in the study (PCB18, PCB28, PCB31, PCB44, PCB52, PCB66, PCB101, PCB128, PCB138, PCB153, PCB170, PCB180, PCB194 and PCB206). Stock standard solutions of each individual compound were prepared in acetone, with concentrations between 10 and 422 mg 1 L, and stored at 20 C. The group of priority substances covered by BDEs is referred to as the sum of the congeners BDE28, BDE47, BDE99, BDE100, BDE153 and BDE154, so all of them were included in the study. They were purchased individually (50 g ml 1 in n-nonane) from LGC Standards (Barcelona, Spain). For each congener, a stock standard solution of 5 mg L 1 was prepared in acetone and stored at 20 C. For correct quantification, different isotopically labelled compounds were used as internal standards (IS). In order to do so, hexachlorobenzene-13c and PCB28-F were purchased from Dr. Ehrenstorfer GmbH, while fluoranthene-d10 was purchased from Supelco (Bellefonte, PA, USA). All analytical standards used had purity of above 97%. For each family of contaminants, multicompound working standard solutions were prepared in acetone at a concentration of 2 mg L 1 of each compound for pesticides, PAHs and PCBs and 0.5 mg L 1 for BDEs. For the IS, a solution containing the three compounds was prepared in acetone at a concentration level of 1 g L 1. All solutions, standard stock and multicompound working solutions, were stored in a freezer at 20 C. Acetone and n-hexane of analytical quality were purchased from Sigma-Aldrich. Milli Q and tap water was used, the latter was employed for method optimization. Perfluorokerosene (PFK) and perfluorotributylamine (FC-43), calibrating agents for the multiple ion detection (MID) acquisition method, were purchased from

3 I. Domínguez et al. / J. Chromatogr. A 1518 (2017) Sigma Aldrich. Due to the high viscosity of PFK, it was necessary to heat to 150 C for 10 min to facilitate its extraction and injection in the equipment SPME procedure Fibers (100 m poly(dimethylsiloxane) (PDMS), 85 m polyacrilate (PA) and 65 m poly (dimethylsiloxane)-divinylbenzene (PDMS-DVB)), extraction vials, septa and sealing caps were supplied by Supelco. Before their use, the fibers were conditioned according to supplier s instructions. SPME procedure was fully automated due to the use of an autosampler (TriPlus autosampler, Thermo Fisher Scientific) equipped with a heater module, an agitator, and an SPME fiber conditioning station. During SPME optimization, principal component analysis (PCA) was applied to the peak area obtained in the evaluated conditions by using the correlation matrix and linear regression through PASW Statistics 18 software (SPSS Inc., Chicago, IL, USA). The 57 compounds, including IS, were the variables and peak areas were the analytical responses used in the multivariate study. For the SPME procedure, 19 ml of unfiltered water sample, 200 L of IS solution and 800 L of acetone were introduced in 20 ml vials. Direct immersion was selected as extraction mode and PA was the fiber used for the analysis of real samples. The extraction procedure was carried out at 75 C for 40 min. Neither ionic strength correction nor ph adjustment was necessary. Desorption of the analytes took place at 280 C for 3 min. The absence of carryover of the fiber after 10 uses was confirmed by analyzing a vial containing 19 ml of milliq water and 1 ml of acetone under the same extraction and desorption conditions. Fiber was useful around uses after which a remarkable carryover was observed Analysis of organic contaminants by GC HRMS Analyses were carried out on a Trace GC Ultra gas chromatograph (Thermo Fisher Scientific, Milan, Italy) fitted with a Thermo TR-DIOXIN-5MS (5% phenyl polysilphenylene-siloxane) GC column (30 m 0.25 mm id 0.1 m film thickness). After extraction in the SPME module of the Triplus autosampler, samples were automatically injected into a split/splitless injector, where desorption of the analytes takes place. The carrier gas was helium ( %) at a constant flow rate of 1 ml min 1. The average carrier gas velocity was cm/s. The GC was coupled to a DFS high-resolution magnetic sector mass spectrometer (Thermo Fisher Scientific, Bremen, Germany) controlled by an Xcalibur data system. The injector temperature was 280 C and the split valve closed for 3 min. After desorption of the analytes, the split flow rate was 50 ml min 1. The column oven program was kept at 70 C for 3.0 min and the temperature was increased up to 180 C at a rate of 11 C min 1, then to 200 C at a rate of 1.5 C min 1 and finally to 295 C at a rate of 6 C min 1, a temperature which was held for 2 min. The total running time was min. MS was performed in positive electron ionization (EI) at 70 ev with an emission current set at 0.92 ma, and the acceleration voltage at 4800 V. High resolution MID mode was operated at a resolving power (10% valley). Multiple gain was fixed at 1576 V, the transfer line and the ionization source were both set at 260 C. The resolution was checked daily, monitoring the reference peak at m/z of PFK. The specific GC HRMS conditions for each compound are included in Table Validation parameters To compensate potential matrix effects, matrix-matched calibration curves were used spiking blank extracts. The blank water samples were collected at the source of the Almanzora river in Sierra de los Filabres (Almería, South of Spain). Before its use five replicates were analyzed which led to confirm the absence of pollutants. Taking into consideration the EQS values set for the contaminants under study, a wide range of concentrations, 14 in total, were analyzed per triplicate in the range of ng L 1. Linearity was considered adequate for all target compounds when obtaining a determination coefficient (R 2 ) higher than Trueness, intra-day (repeatability) and inter-day precision (intermediate precision) were estimated at two validation levels (VL) within the linear range. Concentrations are indicated in Table 2, and one of them corresponded to the EQS value (VL1) when it is applicable. Trueness was evaluated in terms of relative recovery and precision was estimated injecting 5 replicates for each level in the same day (intra-day precision) and on three different days (inter-day precision). Recovery and precision values were considered adequate if they are in the range of % or 20%, respectively. Limits of quantification (LOQs) were estimated as the lowest concentration in which the compound was quantified with a precision lower than 20% and adequate relative recovery can be obtained Water samples Water samples were collected from different surface water compartments from different areas in the Almería province (Spain). Water samples (200 ml) were collected in amber glass bottles, previously washed with n-hexane, acetone and Milli Q water and heated at 250 C for 15 h. After water collection, samples were stored at 4 C and analyzed within 24 h after their collection. 3. Results and discussion 3.1. Optimization of the GC HRMS analysis During method optimization, several analyses were performed injecting individual standards, multicomponent solutions for each group of contaminants as well as mixtures containing all target compounds. The column oven program and the chromatographic column used in this study were previously optimized in our laboratory. These conditions were selected because they allowed for an optimal separation of BDE153 and BDE154 and the twelve toxic PCBs congeners not achieved by other reported conditions [27]. To minimize the carry over effect, the split flow rate was set at 50 ml min 1 and 280 C was the temperature selected for the injector according to SPME desorption requirements. Two ionization energies (45 and 70 ev), in combination with an emission current of 0.92 ma, were applied and a higher sensitivity was obtained when 70 ev was used, so this value was set for the rest of analysis (Fig. S1 in Supplementary Material section). Indeed, for most of the target compounds, peak area values were higher when 70 ev was the applied ionization energy. PCBs and BDEs were the groups of compounds most influenced by this parameter. Indeed, the signal of some of these contaminants, such as PCB189 and BDE154, was increased up to 4 times. These results are in agreement with those obtained by García Bermejo et al. [33], who also observed higher sensitivity of PCBs response when ionization energy was set at 70 ev.

4 18 I. Domínguez et al. / J. Chromatogr. A 1518 (2017) Table 1 GC HRMS parameters of the IS and target pesticides, PAHs, PCBs and BDEs. Compounds Segments RT (min) m/z 1(Q) a m/z 2 Molecular Formula Ion 1 Ion 2 Segment 1 Lock mass Cali mass Naphthalene C 10H 8 C 10H 7 Segment 2 Lock mass Cali mass Pentachlorobenzene C 6HCl 5 C 6H 35 Cl 37 5 Cl Segment 3 Lock mass Cali mass Trifluralin C 11H 11F 3N 3O 4 C 10H 7F 3N 3O 4 Hexachlorobenzene 13C (IS) C 35 6 Cl 6 13 C 35 6 Cl 37 5 Cl Hexachlorobenzene C 35 6 Cl 6 C 35 6 Cl 37 5 Cl Segment 4 Lock mass Cali mass Simazine C 7H 12ClN 5 C 6H 9ClN 5 Atrazine C 7H 11ClN 5 C 8H 14ClN 5 PCB C 12H 35 7 Cl C 12H 37 7 Cl Anthracene C 14H 10 C 14H 2 9 H Segment 5 Lock mass Cali mass PCB 28F (IS) C 12H 7O 35 Cl 3F C 12H 7O 35 Cl 37 2 ClF PCB C 12H 35 7 Cl 3 C 12H 35 7 Cl 37 2 Cl PCB C 12H 35 7 Cl 3 C 12H 35 7 Cl 37 2 Cl Segment 6 Lock mass Cali mass PCB C 12H 35 6 Cl 37 3 Cl C 12H 35 6 Cl 4 Aldrin C 7H 35 2 Cl 5 C 7H 35 2 Cl 37 4 Cl Chlorpyrifos ethyl C 5H 35 2 Cl 3NO C 5H 35 2 Cl 37 2 ClNO PCB C 12H 35 6 Cl 37 3 Cl C 12H 35 6 Cl 4 Isodrin C 7H 35 2 Cl 5 C 7H 35 2 Cl 37 4 Cl Segment 7 Lock mass Cali mass Fluoranthene-d10 (IS) C1 2 6 H 10 C1 6H 2 4 H 6 Fluoranthene C1 6H 10 C16H92H PCB C 12H 35 6 Cl 37 3 Cl C 12H 35 6 Cl 4 PCB C 12H 35 5 Cl 37 4 Cl C 12H 35 5 Cl 37 3 Cl 2 Segment 8 Lock mass Cali mass Dieldrin C 7H 35 2 Cl 5 C 7H 35 2 Cl 37 4 Cl PCB C 12H 35 6 Cl 37 3 Cl C 12H 35 6 Cl 4 p,p -DDE C 14H 35 8 Cl 2 C 14H 35 8 Cl 4 PCB C 12H 35 6 Cl 37 3 Cl C 12H 35 6 Cl 4 Endrin C 7H 2Cl 5 C 10H 5Cl 4 Segment 9 Lock mass Cali mass PCB C 12H 35 5 Cl 37 4 Cl C 12H 35 5 Cl 4 PCB C 12H 35 5 Cl 37 4 Cl C 12H 35 5 Cl 4 BDE C 6H 3O 79 Br 81 Br 81 C 6H 3O 81 Br 2 PCB C 12H 35 5 Cl 37 4 Cl C 12H 35 5 Cl 37 3 Cl 2 o,p -DDT C 13H 9Cl C 13H 37 9 Cl p,p -DDD C 13H 9Cl C 13H 37 9 Cl PCB C 12 H 35 4 Cl 37 3 Cl C 12H 4Cl 4 PCB C 12H 35 5 Cl 37 4 Cl C 12H 35 5 Cl 37 3 Cl 2 Segment 10 Lock mass Cali mass PCB C 12H 35 4 Cl 37 5 Cl C 12H 35 4 Cl 37 4 Cl 2 p,p -DDT C 13H 9Cl 2 C 13H 35 9 Cl 37 Cl PCB C 12H 35 5 Cl 37 4 Cl C 12H 35 5 Cl 37 3 Cl 2 PCB C 12H 35 4 Cl 37 5 Cl C 12H 35 4 Cl 37 4 Cl 2 PCB C 12H 35 4 Cl 37 5 Cl C 12H 35 4 Cl 37 4 Cl 2 PCB C 12H 35 4 Cl 37 5 Cl C 12H 35 4 Cl 37 4 Cl 2 PCB C 12H 35 4 Cl 37 5 Cl C 12H 35 4 Cl 37 4 Cl 2 Segment 11 Lock mass Cali mass PCB C 12H 35 3 Cl 37 6 Cl C 12H 35 3 Cl 37 5 Cl 2 BDE C 12H 6B r4o C 12H 7O 79 Br 81 2 Br 2 PCB C 12H 35 4 Cl 37 5 Cl C 12H 35 4 Cl 37 4 Cl 2 PCB C 12H 35 3 Cl 37 6 Cl C 12H 35 3 Cl 37 5 Cl 2 PCB C 12H 35 3 Cl 37 6 Cl C 12H 35 3 Cl 37 5 Cl 2 PCB C 12H 35 2 Cl 37 6 Cl 2 C 12H 35 2 Cl 37 7 Cl BDE C 12H 5O 79 Br 81 2 Br C 12H 5O 79 Br 81 Br 2 Segment 12 Lock mass Cali mass Benzo[b]fluoranthene C 20H 12 C 20H 2 11 H Benzo[k]fluoranthene C 20H 12 C 20H 2 11 H BDE C 12H 5O 79 Br 81 2 Br C 12H 5O 79 Br 81 Br 2 PCB C 12H 35 Cl 37 7 Cl 2 C 12H 35 Cl 37 8 Cl Benz[a]pyrene C 20H 12 C 20H 2 11 H Segment 13 Lock mass Cali mass BDE C 12H 4O 79 Br 81 2 Br 2 C 12H 4O 79 Br 81 3 Br BDE C 12H 4O 79 Br 81 2 Br 2 C 12H 4O 79 Br 81 3 Br Segment 14 Lock mass Cali mass Indene[1,2,3-cd]pyrene C 22H 12 C 22H 2 11 H Benzo[ghi]perylene C 22H 12 C 22H 2 11 H a Q: Ion used for quantification.

5 I. Domínguez et al. / J. Chromatogr. A 1518 (2017) Table 2 Validation results for the developed method: quantification limits (LOQ), lineal working range, determination coefficient (R 2 ) as well as recovery (R) and precision (RSD) at two different validation levels (VL). Compounds LOQ (ng L 1 ) Lineal Range (ng L 1 ) R 2 VL a (ng L 1 ) Recovery b (%) Interday precision (% RSD) c VL1 VL2 VL1 VL2 VL1 VL2 Pentachlorobenzene* (10) 100(7) Trifluralin* (10) 96(2) 15 5 Hexachlorobenzene* (2) 108(3) 10 5 Simazine* (5) 99(13) 9 14 Atrazine* (2) 115(11) 6 9 Aldrin* (5) 104(4) Isodrin* (12) 96(3) Dieldrin* (4) 104(6) 11 9 Endrin* (4) 102(2) 16 8 Chlorpyrifos* (3) 101(4) p.p -DDE* (3) 95(5) 5 15 o.p -DDT + p.p -DDD* (4) 99(3) 13 5 Naphthalene* (5) 93(4) 11 5 Anthracene* (7) 91(11) Fluoranthene* (2) 105(1) 9 3 Benzo[b + k]fluoranthene* (6) 99(10) Benz[a]pyrene* (5) 99(3) Indene[1,2,3-cd]pyrene (7) 96(5) Benzo[ghi]perylene* (3) 101(3) 8 9 PCB (2) 102(6) 10 7 PCB (9) 102(4) 13 9 PCB (9) 106(3) PCB (8) 100(5) PCB (8) 98(4) 12 5 PCB (12) 108(7) 15 9 PCB (6) 109(10) 7 13 PCB (17) 99(2) 19 7 PCB (6) 100(1) 9 5 PCB (5) 98(10) 8 12 PCB (3) 99(5) 4 7 PCB (7) 100(10) 9 14 PCB (7) 99(4) 10 7 PCB (4) 96(8) 8 9 PCB (10) 97(5) 12 8 PCB (6) 99(1) 8 2 PCB (2) 96(5) 6 9 PCB (5) 104(6) 7 13 PCB (5) 97(7) 7 15 PCB (7) 104(5) 10 6 PCB (16) 105(4) PCB (17) 100(4) 17 9 PCB (9) 105(5) 11 9 PCB (5) 99(2) 13 3 PCB (7) 100(2) 7 8 BDE 28* (5) 101(5) 7 12 BDE 47* (4) 104(6) BDE 99* (6) 103(3) 6 5 BDE 100* (3) 98(6) 9 11 BDE 153* (9) 97(8) BDE 154* (2) 99(5) 9 9 a VL1 coincides with EQS when it is applicable (*). b Relative recovery. Repeatability values (intra-day precision), expressed as%rsd, are given in brackets (n = 5). c n = 3. Under the established conditions, the large majority of the target compounds showed defined and well separated peaks allowing for accurate quantification. However, the chemical and chromatographic behaviors of some compounds led to their coelution, bearing in mind that the responses of the coeluted compounds are similar. Such is the case of the pairs of contaminants, PCB28 and PCB31 and benzo[b]fluoranthene and benzo[k]fluoranthene. In these cases, the compounds were determined in unison. However, it is important to highlight that the EQS established for the coeluted PAHs are given as a sum of the isomers content, consequently the proposed method would be equally adequate Multiple ion detection (MID) method The development of a MID method containing a high number of compounds and consequently a wide range of masses requires a careful planning. However, this detection mode provides considerably high sensitivity. In addition, DFS HRMS benefits from a unique technical feature referred to as the lock-plus-cali mass technique for performing MID analyses, which provided a maximum quantitative precision and certainty in analyte confirmation. For MID data acquisition, the DFS system uses a mass calibration, just before monitoring the target compound intensities, performed in every scan during the analysis. As a consequence, this scan-to-scan mass calibration provides the highest confidence for the acquired analytical data.

6 20 I. Domínguez et al. / J. Chromatogr. A 1518 (2017) As a reference compound, continuously infused from the reference inlet system into the ion source during sample analysis, PFK resulted more convenient than (FC43) because it offered a higher number of suitable compatible masses. Two ions of the reference compound, known as lock and calibration (cali) masses, were used in the MID acquisition windows for scan calibration. As indicated above, due to the high number of target compounds and high mass variability special attention has to be focused on the development of the MID acquisition method. In order to increase the section sensitivity, two ions of each target compound were included in the method. High intensity, selectivity as well as absence of interferences with co-eluting compounds from reference or matrix were the principal criteria for ions selection. However, minimizing the difference between lock and cali masses as much as possible was also taken into consideration. For this reason, the ions selected for PCB18, PCB153 and BDE28 were different than those initially used by Bonilla et al. [27], when PCBs and BDEs were analyzed simultaneously. Ions associated to pesticides and PAHs with lower ion masses, as simazine, atrazine and anthracene in the case of PCB18, and OCPs (p,p -DDT and p,p -DDD) in the case of PCB153 and BDE28, were present in the same section and therefore ion substitution was enforced. Even so, high peak signals were obtained for these compounds. The developed acquisition method is compiled in Table 1 and for better sensitivity it was designed with 14 sections containing a maximum of 8 compounds per section and an acquisition rate of 0.6 s/cycle Quantification of target compounds An important advantage of using GC HRMS is its compatibility with the isotope dilution techniques allowing for a more reliable quantification [28]. Internal standard addition and a plot of the ratios of target analyte/is response against the concentration is used to determine the original concentration of the target analyte in the sample. This led to the compensation of the matrix effects and method irreproducibility issued [25]. For that purpose, the isotopically labeled standards were used for quantitative purposes. Hexachlorobenzene-13C has been used for the quantification of pesticides, PCB28-F in the case of PCBs and BDEs and for PAHs quantification fluoranthene-d10 was the surrogate used Optimization of the SPME procedure Two extraction methods are typically used, direct immersion (DI) and headspace (HS) SPME modes. The last one, HS-SPME is preferred for complex water samples with the aim of protecting fiber coating from damage by high molecular mass and other nonvolatile interferences present in the sample matrix. Both extraction strategies have been applied for the determination of organic contaminants in water samples [19,21]. Nevertheless, DI-SPME is more sensitive than HS-SPME for the studied compounds, and is therefore the generally chosen extraction mode for clean aqueous samples [8], understood as water containing limited dissolved organic carbon (DOC) and suspending sediments. So, DI remains compatible with the selected surface water samples and it was the extraction method used in the present study. SPME was directly performed in an autosampler, as shown in Supplementary Material section (Fig. S2), coupled on line with the GC HRMS system. To ensure faster extraction, the agitation system was turned on and vial movements occurred during the extraction period. SPME conditions were optimized with the help of the SPME protocol published by Pawliszyn s group [25]. Then, different SPME parameters were evaluated and those conditions offering the highest extraction efficiency were selected. For that, 19 ml of spiked Fig. 1. PCA.2D-loading plot, explaining 100% of the variance, achieved in the study of fiber extraction efficiency. Data were obtained from area values achieved by using the different fibers (PA, PDMS and PDMS-DVB) for the different families of target compounds included in the study (pesticides, PAHs, PCBs and BDEs). For that spiked samples were subjected to extraction for 40 min at 60 C. tap water samples (100 ng L 1 ) were subjected to the extraction conditions mentioned below. In order to explore and visualize the achieved results in this part of the study more clearly, and as can be seen in Figs. 1 and 2, we have taken advantage of a multivariate approach, concretely a principal component analysis (PCA). The 54 compounds, including IS, were the variables and area values were the data introduced in the multivariate study. Even so, for a better understanding, if required, individual plots representing the peak area values obtained for the target compounds are included in the supporting information section Fiber selection The efficiency of the extraction process considerably depends on the selectivity of the fiber coating toward the analyte of interest versus other components present in the sample which is mainly influenced by the polarity of the coating. Since the selected compounds exhibit significant differences in their polarity and octanol-water partition coefficients (Log K o/w ), three fiber coatings were evaluated: the non-polar PDMS (100 m), the polar PA (85 m) and the mixed phase PDMS/DVB (65 m). To carry out the experiment, the spiked samples were subjected to extraction for 40 min at 60 C, and the results for each compound are shown in Fig. S3. In Fig. 1 the PCA-two dimensional (PCA-2D) plot obtained from the results achieved by using the three fibers is represented. From the PCA, two components were extracted explaining 100% of the variance. As can be seen in the plot, the first component (PC1), explaining 70% of the variance, differentiates the PA fiber from the other two tested ones. This result can be explained by a higher extraction capacity mainly in the case of most of PCBs and all BDEs included in the study. The second component of the PCA (PC2) explaining 30% of the variance revealed PA and PDMS-DVB exhibited a higher efficiency than PDMS for the extraction of pesticides, PCBs and PAHs. Indeed, with the exception of aldrin, p,p -DDT and its derivates, indene[1,2,3-cd]pyrene and benzo[ghi]perylene higher peak area values were achieved by using these two fibers. On the other hand, PDMS fiber resulted more efficient than PDMS-DVB for the extraction of BDEs even so, as indicated before PA offered better results for the extraction of this family of compounds. Hence, PA and PDMS-DVB fibers have previously been chosen for the extraction of pesticides and PAHs in water samples

7 I. Domínguez et al. / J. Chromatogr. A 1518 (2017) Fig. 2. PCA.2D-loading plots, explaining 98% of the variance, achieved in the evaluation of different extraction conditions. a) Data were obtained from area values achieved for the target compounds when heating the samples in presence of PA fiber at different temperatures (40, 50, 60 and 75 C). b) Data were obtained from area values achieved for the target compounds when heating the samples at 75 C in presence of PA fiber for different periods of time (20, 30, 40, 50 and 60 min). [8,9,11,16,34]. In addition, a similar trend was observed when the three fibers were used for the extraction of the same pesticides as those included in the present study [35]. In conclusion, the PCA-2D plot clearly indicates that PA is the most adequate fiber for the extraction of the four families of compounds under study, so it was the fiber selected to be applied in the multiclass method. In agreement with our results, other authors found that PA fiber has shown the highest extraction efficiency for polar as well as nonpolar compounds [8]. Furthermore, when Endo et al. carried out the comparison between PA and PDMS fibers considering the fiberwater partition coefficients, they concluded that PA fiber exhibited higher extraction capacities for H-bond donor compounds such as pesticides as well as hydrophobic aromatic compounds such as PAHs [36] Extraction conditions The influence of temperature on the peak areas for each compound was investigated setting 40, 50, 60 and 75 C as extraction temperatures with a constant extraction time of 40 min, and the results for each compound are shown in Fig. S4. In the PCA-2D obtained in this case (Fig. 2a), 60 and 75 C are included in the first component (PC1) which explains 86% of the variance. From these results, we can consider that 60 and 75 C are optimal temperatures for the extraction of all the target compounds included in the study with the exception of naphthalene. Increasing the temperature produced an improvement in the extraction efficiency and led to an increase in the analyte diffusion coefficient which allowed for reduction of the equilibrium time. However, the trend was the opposite for naphthalene where the peak area decreased when temperature increased. As a matter of fact, Es-Haghi et al. found that in the case of naphthalene, room temperature is the optimum extraction temperature because it avoids volatilization and transference to the vial headspace [9]. In spite of 60 C resulting as an adequate extraction temperature, 75 C was the temperature selected because it allowed for the highest extraction efficiency for most of the compounds. Once the extraction temperature was defined, different extraction times were tested. In order to do so, samples were exposed at 75 C to the PA fiber for 20, 30, 40, 50 and 60 min (results for each compound is shown in Fig. S5). The PCA-2D plot corresponding to this evaluation is presented in Fig. 2b. The three highest evaluated extraction times, 40, 50 and 60 min are close together in PC1 which explains a 93% of the variance. This is in agreement with no further improvement being observed for most of the compounds when the extraction time was raised from 40 to 60 min indicating that the extraction equilibrium in the SPME process might have been attained. In accordance with these results and in order to minimize the total time for the determination of the contaminants and increasing sample throughput, 40 min was considered as the optimum extraction time under these tested conditions. On the other hand, as it is has been proven that ph has little or no effect in the extraction of the target compounds in water samples [8], ph adjustment was considered unnecessary to carry out. The addition of a soluble salt to increase the ionic strength of the sample or an organic modifier to the sample was also considered. However, taking into account that addition of salts can damage fiber coatings during DI-SPME [25] and can exert a negative influence on extraction efficiency for some compounds, we opted against its use. The use of organic modifiers is recommended in SPME procedures as some authors indicated that analytes loss by absorption problems is avoided through its use [11]. Because a decrease in the extraction yield of PAHs when using methanol has previously been reported [9] and good reproducibility has been achieved when using acetone with the same family of compounds, this last solvent has been chosen as modifier. In this respect, after evaluating the addition of 1, 2.5 and 5% of acetone (avoiding the use of higher amounts), the best results were achieved by using 1 ml of the solvent (5%). The addition of 5% of acetone was detrimental to the extraction of certain pesticides; however, it led to an increase of the extraction efficiency for the rest of the compounds (see Fig. S6 in Supplementary Material section) Desorption time and carryover test Different temperatures in the range of C have been applied for desorption of the organic contaminants. In SPME, the use of the highest possible desorption temperature is recommended, taking into account fiber and analytes thermal stabilities, in order to avoid carry over effect [9]. In this study, the injector temperature was set at 280 C, a temperature compatible with PA fiber, and high enough to desorb the high-molecular-mass compounds which are not desorbed at lower temperatures [9]. In order to reach high sensitivity, different desorption times, 3, 6 and 9 min, were evaluated and we found that an increase of desorption time led to a signal drop (Fig. S7, Supplementary Material section). Indeed, for the large majority of the compounds, the maximum area values were achieved when the fiber was exposed to 280 C for 3 min. In addition, the peak shape was improved when decreasing desorp-

8 22 I. Domínguez et al. / J. Chromatogr. A 1518 (2017) tion time, mainly for PAHs, so 3 min was the time selected to carry out desorption of the analytes. To minimize carry over as well as the introduction in the chromatographic column of interfering compounds from the SPME fiber, a splitless time of 3 min was selected. It was observed that the losses of the desorbed compounds through the split was avoided using this time. At the end of every batch of samples, a blank fiber analysis was carried out in order to check carryover. Finally, a total ion chromatogram of the target compounds at the optimized conditions are shown in Fig. S8 (see Supplementary Material section) Method validation For method validation, special attention has been paid to the maximum allowed concentration (EQS values) established for surface water by the current Directive 2013/39/EC [2] and in the case of BDEs, also the previous one (Directive 2008/105/EC) [35] for being more restrictive. Taking into account the wide range of EQS values for the target compounds a total of 14 concentrations between 0.1 and 1500 ng L 1 were analyzed. The linear working ranges found are summarized in Table 2 and all of them cover the EQS values of the target compounds when it is applicable. In the case of PCBs, for which EQS are still not set up, the linear working range proposed usually contains the lower quantitative concentration levels. Linearity was considered adequate for all target compounds since the determination coefficients obtained are higher in all cases. As an example of this, in supporting information (Fig. S9), the plots showing the linear working range for one analyte of each family of contaminants can be observed. Trueness was estimated as recovery and for this, a total of five blank samples were spiked at two concentration levels in the range of 0.2 and 1000 ng L 1 (Table 2). Since SPME is a non-exhaustive extraction technique relative recovery values are the provided data. The first validation level (VL1) corresponds to the EQS value set up for each target compound and the second one (VL2), in most cases, correspond to a higher concentration. However, when EQS values are in the high level of the linear working range as in the case of simazine, atrazine and some PAHs, VL2 is a lower concentration level than VL1. In the case of BDEs, the EQS value considered for validation was 0.2 ng L 1 according to the previous directive (Directive 2008/105/EC) [37] as appointed before to be more restrictive than the current one. However, it is necessary to highlight that the linear working range found for all BDEs under study also includes the concentration value (14 ng L 1 ) established as maximum concentration EQS in the current Directive [2]. Then, adequate relative recovery values were obtained for the target compounds ranging from 84 to 118% in the first level of validation and % for the second one. Repeatability and reproducibility were expressed in terms of intra-day (n = 5) and inter-day precision (3 days) respectively, and they were evaluated at the same concentration levels used in the recovery studies. The results evidenced good precision of the developed method, since the intra-day and inter-day precisions were < 20%, reaching to obtain intraday precision at values < 10% for a large majority of the target compounds (Table 2), even at the lowest studied concentrations (many of them in the low- g L 1 or ng L 1 levels). In spite of DDT related compounds showing good RSD values, in the case of p,p -DDT having a higher log K o/w, values >20% were obtained for all evaluated concentrations. As a consequence of these results we confirmed that the applied extraction conditions were not satisfactory for this compound. Indeed, from Fig. 2 we can conclude that PDMS fiber should result more effective for its extraction from the water matrix, so the use of this fiber as well as the evaluation of new ones is recommended. The development of a method containing a high number of compounds showing different polarities and logk o/w forced us to establish compromise conditions which can be detrimental for some of them. So, we considered that the method was not appropriate for the quantification of compound p,p -DDT, and further research is being carried out in order to clarify this result. Regarding the determination of LOQs in HRMS, there are some controversial considerations. This validation parameter has usually been obtained by the signal-to-noise ratio (S/N) criteria, defining LOQs as the lowest concentration with a S/N ratio of 10 [5]. However, due to the very low noise generated by the magnetic sector HRMS instrument, a high S/N ratio is obtained. So, it has been considered that this approach could lead to low and uncertain LOQ values [33]. LOQs have also been estimated as 10 times of standard deviations obtained for the lowest level of calibration curves [33]. However, in this study LOQ values have been established as the lowest concentration level in which RSD, determined from the triplicate analysis, was 20% and acceptable recoveries (values ranging from 80 to 120%) can be obtained. Most of the values obtained for this parameter coincided with the lowest value of the linear range established. However, about one quarter of target compounds could be quantified at lower concentrations that those included in the established linear range. As can be seen in Table 2, LOQs values are ranging from ng L 1 and it is important to notice that 87% of the target compounds could be quantified at 5 ng L 1, even 41% at 0.1 ng L 1, which clearly evidenced the high sensitivity of the proposed methodology. Unlike previous results achieved by using SPME (HS mode) coupled with GC MS/MS [11], the two triazine herbicides (simazine and atrazine) could be determined under our experimental conditions. In spite of them exhibiting the highest LOQ values, as well as the rest of target compounds, these contaminants can be quantified at lower levels than the established maximum allowed-eqs concentration. This fact makes us believe that this methodology could be an important tool for the easy and accurate quantification of these compounds and their metabolites in surface water which has been an aim for some time [30]. At this point, it is important to highlight that the combination of SPME with HRMS would allow for the quantification at ultra-trace levels for most target compounds, fulfilling the requirements set by European legislation [2]. The increase of sensitivity by using HRMS has become evident by comparing the previously achieved LOQs when SPME was combined with a GC/MS ion trap mass spectrometer [35]. On the other hand, higher LOQ values were reported by applying SPE extraction procedure, in combination with low resolution mass spectrometry, for the simultaneous determination of any of these pollutants in surface waters [14]. From the comparison of the results achieved for BDEs and PCBs with those obtained with the same HRMS analyzer after a SPE extraction step led us to confirm the method potential since similar or even lower LOQs have been obtained in this study. This is clearly an asset since the proposed method involves the use of a considerably lower sample volume and does not involve tedious sample manipulation such as the traditional extraction procedures do Analysis of real samples The developed method was applied to a total of 24 surface water samples from different environmental compartments (rivers, wells and irrigation channels) from the province of Almería (South East of Spain). A map of Almería province showing the different sampling sites can be found in Supporting Material section (Fig. S10) together with ph and electrical conductivity values corresponding to each of analyzed samples (Table S1).

9 I. Domínguez et al. / J. Chromatogr. A 1518 (2017) Fig. 3. Chromatographic peak and the two ions monitored corresponding to PCB77 found in one real sample at 0.44 ng L 1. Table 3 Organic pollutants found in real surface water samples from Almeria province. Compounds Concentration (ng L 1 ) Sample 1 PCB Sample 2 Endrin 0.62 PCB PCB BDE Sample 3 Hexachlorobenzene 0.69 PCB PCB PCB PCB BDE Contaminants at quantitative concentrations were found in only three samples, all of them related to irrigation systems. In Table 3, the compounds as well as the concentrations are indicated. PCB157 was found in the three positive samples. Apart from this contaminant, sample 2 also contained endrin, PCB138 and BDE47. Four different PCBs could be quantified in sample 3, PCB18 and PCB101 and 2 highly toxic dioxin-like polychlorinated biphenyls, PCB77 (see Fig. 3) and PCB157. Together with these contaminants sample 3 also contained hexachlorobenzene and BDE47. The last 2 contaminants, hexachlorobenzene and BDE47 were found at concentration levels below the maximum allowable concentration-eqs imposed by the applicable directive in the field of water policy (14 ng L 1 ) [2], and higher that the EQS previously established (0.2 ng L 1 ) [37]. These results are in agreement with recent studies in which the presence of PCBs and BDE47 in surface waters from the Almería province has been observed [27,29]. At this point it is important to highlight that application of the optimized method results easy, with minimal sample manipulation, and adequate accuracy offering a broad overview of water quality because it provides information regarding to the contamination of four families of contaminants simultaneously. 4. Conclusions The on-line combination of SPME with GC HRMS provides a highly sensitive analytical and complete automated methodology for the simultaneous determination of 53 organic pollutants including pesticides, PAHs, PCBs and BDEs in surface water samples. SPME procedure diminished to the minimum sample manipulation and its on-line combination with the GC HRMS equipment significantly simplifies the analysis procedure and a higher number of determinations can be carried out increasing sample throughput. SPME and GC HRMS conditions were optimized in order to achieve a high sensitivity and selectivity of the technique. Therefore, the operating MID mode of the magnetic sector analyzer provided excellent sensitivity making the quantification feasible at levels as low as 0.1 ng L 1, the lowest concentration level evaluated. The developed methodology was fully validated showing good linearity, sensitivity and suitable recoveries (84 118%) and precision values (RSD <20%) for 53 organic pollutants. Finally, the multiclass method was applied to different surface waters from the Almería province revealing the absence of PAHs as wells as the presence in trace levels of contaminants in three samples. Hexachlorobenzene, certain PCBs and BDE47 were the compounds quantified in the positive samples. Furthermore, this methodology results reliable, reproducible, and robust so its use could be could be considered for routine analysis. Acknowledgements The authors gratefully acknowledge the Andalusian Regional Government (Regional Ministry of Innovation, Science, and Enterprise) and FEDER for financial support (Project Ref. P-12-FQM 1838). I.D. is also grateful for personal funding through the same Project Reference. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at