Anal Bioanal Chem (2014) 406:1259–1266 DOI 10.1007/s00216-013-7450-8


Multi-residue analysis of emerging pollutants in sediment using QuEChERS-based extraction followed by LC-MS/MS analysis Alexandra Berlioz-Barbier & Antoine Vauchez & Laure Wiest & Robert Baudot & Emmanuelle Vulliet & Cécile Cren-Olivé

Received: 1 August 2013 / Revised: 7 October 2013 / Accepted: 17 October 2013 / Published online: 21 November 2013 # Springer-Verlag Berlin Heidelberg 2013

Abstract Emerging contaminants are suspected to cause adverse effects in humans and wildlife. Aquatic ecosystems are continuously contaminated by agricultural and industrial sources. To establish a causality relationship between the occurrence of contaminants in the environment and disease, experiments including all environmental matrices must be performed. Consequently, the current analytical tools must be improved. A new multi-residue method for analysing 15 emerging pollutants in sediments based on the Quick, Easy, Cheap, Effective, Rugged and Safe approach is reported. The development of such a multirisque, inter-family method for sediment including pharmaceuticals, pesticides, personal care products and plasticizers is reported for the first time. The procedure involves salting-out liquid–liquid extraction using acetonitrile and clean-up with dispersive solid phase extraction, followed by liquid chromatography coupled with tandem mass spectrometry. The validated analytical procedure exhibited recoveries between 40 and 98 % for every target compound. This methodology facilitated the determination of pollutant contents at nanogram-per-gram concentrations.

Keywords LC-MS/MS . QuEChERS . Multi-residue . Emerging pollutants . Sediment

Published in the special issue Analytical Science in France with guest editors Christian Rolando and Philippe Garrigues. A. Berlioz-Barbier : A. Vauchez : L. Wiest : R. Baudot : E. Vulliet : C. Cren-Olivé (*) Université de Lyon-Institut des Sciences Analytiques, UMR 5280 CNRS-Equipe TRACES, Université Lyon1, ENS-Lyon - 5 rue de la Doua, 69100 Villeurbanne, France e-mail: [email protected]

Introduction Emerging aquatic contaminants are continuously released by agricultural and urban areas. These materials include pharmaceuticals, personal care products, alkyl phenols and plasticisers. Currently, the data are still insufficient to assess the risk these compounds pose on aquatic ecosystems. Therefore, reliable and sensitive analytical methods are needed. Studies describing the environmental concentrations of pesticides or pharmaceuticals are frequently performed using water samples [1–3] but rarely conducted on sediments [4, 5]. Moreover, the described methodologies focus only on the specific analysis for limited chemical families of pollutants [4–6]. Nevertheless, using a multi-residue, inter-family analysis to detect and quantify a wide range of chemical families within a single sample is essential to obtain a global view of aquatic pollution. A typical advantage of the presented analytical procedure is that it has been designed as multi-residue approach. In terms of cost and time, in frontspecific chemical families, using different methodologies is beneficial because they can capture all the chemical information of the sample. To our knowledge, the development of such multi-residue, inter-family method for sediment including pharmaceuticals, pesticides, personal care products and plasticizers has never been proposed. This study sought to develop a rapid, robust and sensitive method for the trace analysis of environmental contaminants in sediment matrices inspired by Quick, Easy, Cheap, Effective, Rugged and Safe (QuEChERS) extraction and followed by LC-MS/MS analysis. This method required limit of quantification in the nanogram-per-gram range. A list of 15 compounds was chosen based on scientific criteria (occurrence and persistence in the environment, as well as bioaccumulation). This list contains mostly pharmaceuticals (carbamazepine (Carba)), tamoxifen (Tamox), triclosan


(Triclo), econazole (Eco), and ketoprofen (Keto)), as well as hormones (norethindrone (Nore), estrone (E1)), pesticides (spinosad (Spin) and pyriproxyfen (Pyri)), synergists (piperonyl butoxide (PipB)), a pesticide metabolite (3,4dichloroaniline (3,4DCA)), alkylphenols (3,5-di-terbutylphenol (3,5DTBP) and 2,6-di-ter-butylphenol (2, 6DTBP)), a UV filter (4-methybenzylidene camphor (4MBC)) and a plasticiser (bisphenol A (BPA)) This paper describes the optimisation of both two steps of the analytical protocol (QuEChERS extraction and LC-MS/ MS analysis) and the validation strategy.

Experimental section Materials and reagents E1, BPA, Pyri, Carba, 3,4DCA, Keto, Triclo, Eco, Tamox, Nore, 3,5DTBP, 2,6DTBP, 4MBC, Methanol (MeOH) (LCMS grade), acetonitrile (ACN) (LC-MS grade), hexane, propan-2-lol (HPLC grade) and formic acid (98 %, LC-MS grade) were purchased from Sigma-Aldrich (Saint-QuentinFallavier, France) with purities greater than 97 %. PipB (92.5 % purity), Spin (98 % purity) and Norethindrone-d 6 (Nore-d 6), Bisphenol A-d 4 (BPA-d 4) were used as injection control, while Carbamazepine-d 10 (Carba-d 10), Tamoxifen-d 5 (Tamo-d 5) and were obtained from Cluzeau (Ste Foy la Grande, France) and Estrone-d 2 (E1-d 2) used as internal standards. Deuterated compounds are generally used as internal standards to compensate the lost during extraction and/or the matrix effect. However, limited internal standards were added because several deuterated standards are not marketed. For the negative mode, E1-d 2 was assigned for each analyte analysed in this mode. For the positive mode, Carba-d 10 was assigned for 3,4DCA, Carba, Eco, Nor, keto and Tamo-d 5 was assigned for Tamo, Spin, 4MBC, Pyri, PipB according to physico-chemical as well as mass spectrometric characteristics. Individual stock solutions were prepared at 200 mg L−1 in MeOH and stored at −23 °C. Working solutions were prepared by diluting an adequate amount of stock solutions. Pure water was obtained from a MilliQ device manufactured by Millipore (Saint-Quentin-en-Yvelines, France). The QuEChERS extract tubes (AOAC and EN methods) were obtained from Agilent Technologies (Massy, France). The acetate buffer contained 1.5 g of NaOAc and 6 g of MgSO4, (pH=4.8), while the citrate buffer contained 1 g of NaOCitrate, 4 g of MgSO4, 1 g of NaCl and 0.5 g of disodium citrate sesquihydrate (pH = 5–5.5). Dispersive SPE PSA (primary and secondary amine exchange containing 900 mg of MgSO4 and 150 mg of PSA) and PSA C18 (containing 900 mg of MgSO4, 150 mg of PSA and 150 mg of C18) were obtained from Carlo Erba-SDS (Val de Reuil, France), while PSA/GCB (containing 900 mg of MgSO4, 150 mg of PSA and

A. Berlioz-Barbier et al.

15 mg of graphitized carbon black) was obtained from Macherey Nagel (Hoerd, France). Sample collection, preparation and extraction The blank matrix sample was composed of sediments collected from the Bourbre River (Bourgoin-Jallieu, France) and was examined to ensure that no contamination with the target compounds had occurred. After freeze-drying and sieving to a 250-μm grain size, the sediments were stored at −20 °C until analysis. Two grams of freeze-dried sediment were weighed into a 50-mL centrifuge tube and 10 mL of water was added. Subsequently, the tube was shaken by hand and vortexed (30 s) before 10 mL ACN and QuEChERS acetate buffer were added. The mixture was immediately shaken manually and subsequently vortexed (30 s). The sample was centrifuged at 5,000 rpm for 5 min. Afterwards, a 6-mL aliquot of the ACN phase was transferred into a previously prepared 15 mL of PSA/GCB tube. Next, this tube was immediately shaken manually, vortexed for 30 s and centrifuged for 5 min at 5, 000 rpm. Finally, 5 mL of the extract was placed in a 10-mL glass centrifuge tube and evaporated at 40 °C under a nitrogen stream. The sample was reconstituted with 500 μL of the ACN solution spiked with 500 ng mL−1 Nore-d 6. Finally, a 100-μL aliquot was diluted ten-fold using 89/11 water/ACN solution for LC-MS/MS analysis. LC-MS/MS analysis An ABSciex API-3200 QTRAP triple quadrupole MS/MS equipped with an electrospray interface (ESI) coupled with an Agilent 1200 LC (binary pump) was used. The chromatographic separation was performed with a Kinetex XDB C18 (50×2.1 mm, 1.7 μm) column from Phenomenex (Le Pecq, France) with an in-line filter (“krudkatcher”) with a porosity of 0.5 μm (Phenomenex). The column oven temperature was 60 °C, the injection volume was 5 μL, and the flow rate was 350 μL min−1. Mobile phase (A) was 0.1 mM ammonium acetate in water, mobile phase (B) was 0.1 % formic acid in water and mobile phase (C) was methanol. In negative mode, the gradient program began at 60 % (A), decreased linearly to 40 % over 5 min and was held for 10 min at 40 % (A). Finally, the concentration ramped up to 100 % (C) within 1 min and was held for 10 min at 100 % (C). In positive mode, the gradient program began at 68 % (B), decreased linearly to 45 % within 3.5 min and was held for 13 min at 45 % (B). Finally, the mobile phase ramped up to 100 % (C) within 1 min and was held for 10 min at 100 % (C). The MS/MS conditions were optimised by directly infusing each compound into the ESI source in both modes. The cone voltages and collision energies for the two MRM were optimised using a continuously flowing standard

Multi-residue analysis of emerging pollutants in sediment


Table 1 Retention time (Rt), MS/MS parameters: quantitation transitions (first lines), precursor and product ions, desclustering potential (DP), collision energy (CE), and transition ratios Mode


Rt (±0.2 min)

Precursor ion (m/z)

Product ion (m/z)

DP (V)


Transition ratio



2.9 4.5

127.0 73.9 194.1 165.1

46 46 36 36

27 63 27 55



161.9 161.9 237.1 237.1


6.4 6.8













209.1 105.1 125.1 127.1 109.1 91.1 72.0 44.1 142.3 98.2 105.1 171.2 96.1 227.2 177.1 119.1

31 31 51 51 46 46 51 51 56 56 36 36 21 21 12 12

17 33 35 37 35 59 45 81 39 83 39 21 21 19 17 45



255.1 255.1 382.9 382.9 299.1 299.1 372.2 372.2 732.3 732.3 255.1 255.1 322.1 322.1 356.2 356.2

Carba-d 10 Tamo-d 5

4.3 8.4

247.1 377.2

204.2 72.1

35 49

22 36


Nore-d 6 BPA

7.4 3.3 5.5







E1-d 2 BPA-d 4

5.5 3.3

114.4 212 133 144.9 142.8 189.1 173.0 35.1 37.0 189.1 173.0 147.1 216

45 −50 −50 −70 −70 −65 −65 −20 −20 −65 −65 −60 −50

35 −28 −34 −48 −66 −38 −56 −28 −22 −32 −56 −50 −27



305.2 227.0 227.0 267.0 267.0 205.1 205.1 286.8 286.8 205.1 205.1 271.1 231


injection (1 mg L−1 in 50/50 (A) and (C) for negative mode or 10 μL min−1 in 50/50 (B) and (C) for positive mode). The first MS/MS transition (MRM 1) was used for quantification and the second one (MRM 2) was selected for confirmation. The maximum tolerance for relative ion intensities using LC-MS/ MS is ±30 %. The source temperature was 600 °C for both negative and positive modes, and the ion spray voltage was −4.5 and 5.5 kV, respectively. The operating pressure of the flowing nitrogen for the nebuliser (GS1) and turbo gases (GS2) were 344.7 and 413.4 kPa for negative and positive mode, respectively. Table 1 presents the parent and fragment


1.9 1.5 7.5 4.3 1.8 3.8 2.5

2.9 1.3 1.0 1.3 – –

ions, as well as the MS/MS conditions, retention times and product ion ratios for each compound. ABSciex Analyst 1.5 software was used. Quantification Matrix-matched calibration was used for quantification. Six calibration points were prepared with concentrations ranging between LOQ to 40×LOQ for each compound and were subsequently injected. For the LC-MS/MS analysis, each compound was characterised using its retention time, two


MRM transitions and the ratio between MRM 1 and MRM 2. In each analytical batch, the instrument's performance was checked using the signal area for Nore-d 6 and BPA-d 4 present in each sample and the injection of quality control samples.

Results and discussion LC-ESI-MS/MS optimisation The ESI-MS/MS parameters were optimised over two steps: direct infusion into the electrospray source followed by flow injection analysis. Directly infusing the samples revealed the optimal detection conditions. Therefore, the MS/MS parameters were optimised to choose the ionisation mode and identify the parent and product ions, as well as select the optimal declustering potential (DP) and collision energy (CE) (Table 1). Both ionisation modes were used to detect every the target compound to display the best selectivity in the transitions and the least amount of noise for the product ion. The ionisation efficiency of a target compound may be increased with mobile phase additives, such as formic acid or ammonium acetate. Five of the 15 selected analytes (BPA, E1, 3,5DTBP, Triclo, 2, 6DTBP) displayed more efficient ionisation in the negative mode when ammonium acetate was used, while the remaining nine compounds (3,4DCA, Carba, Keto, Eco, Nore, Tamo, Spin, 4MBC, Pyri, PipB) demonstrated preferential ionisation in the positive mode when formic acid was added. The operating pressure of the flowing nitrogen for the nebuliser (GS1) and turbo gases (GS2), as well as the source temperature must be optimised for each ionisation mode. GS1 and GS2 were fixed at 344.7 and 413.4 kPa, respectively, for both negative and positive modes. The desolvation of the analytes depends on the source temperature. Therefore, several temperatures (0 to 600 °C) were tested in both modes. For positive mode, all target compounds exhibited the most sensitivity at 600 °C. In negative mode, triclosan did not depend on the desolvation temperature. The response of some analytes (BPA, E1) decreased when the temperature was higher than 400 °C. However, the alkylphenols (3,5DTBP, 2,6DTBP) were not detected when the temperature was below 600 °C. Therefore, the source temperature was set to 600 °C for both modes. This compromise was necessary to detect and analyse every target compound. Optimising the chromatographic conditions during multiresidue analysis is challenging because the target compounds have diverse physico-chemical properties. Moreover, Keto/ 4MBC in ESI+ and 3,5DTBP/2,6DTBP in ESI− get common MRM transition. Therefore, it was necessary to optimise the chromatographic separation of these compounds. In this work, finding the optimal conditions for the class of alkylphenols was the most challenging. These compounds are structural isomers of one another and display the same parent and

A. Berlioz-Barbier et al.

product ions. Moreover, they have similar physico-chemical properties contrary to 4MBC and Keto, so their chromatographic separation requested more stages of development than Keto and 4MBC. The mobile phases, flow and gradient were each varied. For the elution gradient, when MeOH was used as the organic mobile phase, the separation of the alkylphenols increased relative to the separation achieved with ACN. Under both ionisation modes, several aqueous phases were tested, including MilliQ water with formic acid (0.1 %) or acetic acid (0.1 %) additives for the positive ionisation mode and MilliQ water with ammonium acetate (0.1 mM) or ammonium formate (0.1 mM). For the negatively ionised compounds, an elution gradient using aqueous ammonium acetate (0.1 mM) demonstrated the best separation and sensitivity. The addition of ammonium salt increases the signal of most of the target compounds. For the positively ionised compounds, the best separation was obtained using formic acid (0.1 %). Indeed, the addition of 0.1 % of formic acid enhanced the sensitivity by a factor ranging from 1,2 to 2,1 depending on the target compound. Moreover, the separation of Keto, Eco and Nore was improved using water with acid as mobile phase. Optimising the elution gradient led to the following results: the compounds were separated within 20 and 12 min in the positive and negative modes, respectively (Table 1). Finally, the injection solvent was optimised. This solvent influenced the quality of the separation, peak shapes and response factor. For the most polar compounds, which are also eluted first, low resolution was observed when an injection solvent with a high percentage of organic solvent was used. As the elution gradient started began at 60 and 68 % water for the negative and positive ionisation mode, respectively, it became necessary to have at least 60 % water in the injection solution to obtain a good peak shapes. Considering the different responses of the analytes to the solvent composition, a compromise was necessary. Therefore, the samples were reconstituted with a 80/20 water/ACN solution because most of compounds produced their best responses with this composition. Extraction The QuEChERS extraction method is based on a liquid–liquid buffered extraction followed by clean-up using a dispersive SPE. In the first step, an organic solvent extracts the analytes from the matrix and the added buffer facilitates phase separation. To determine the best extraction methodology, two parameters were studied: the buffer and the solvent. To compare each factor, the recoveries were evaluated at 200 ng g−1 using the following equation: Recoveryð%Þ ¼

S ðSpiked before sample preparationÞ  100 S ðSpiked after sample preparationÞ

Multi-residue analysis of emerging pollutants in sediment Fig. 1 Recoveries for 200 ng g−1 of the target compounds obtained using different extraction solvents


140 120

Recovery (%)

100 80 ACN 60

ACN/IPrOH (90:10) ACN/Hexane (90:10)

40 20 0

First, the efficiency obtained using the two buffers recommended in the European [7] and the American [8] standards were compared. Sediments may have different pH depending on their origin. Moreover, the target compounds have different pK a ranged from −0.47 to 10. For all the reasons commented before, original QuEChERS (without citrate or acetate salts), was not considered in initial stage of development. Only acetate or citrate salts were considered in order to buffer sample during the extraction step. The extraction was performed using 10 mL of water and 10 mL of ACN. For most compounds, the acetate buffer generated better recoveries, particularly for alkylphenols and 3,4DCA. Several solvents or mixtures of solvent were also studied: ACN, ACN/IPrOH (90:10), ACN/hexane (90:10). As observed in Fig. 1, the ACNbased methods furnished better recoveries for most compounds. Therefore, the acetate based-method and ACN were chosen to extract the target analytes from sediments. Fig. 2 Recoveries for 200 ng g−1 of the target compounds obtained using different dSPE and without dSPE

Purification Because the matrix was highly complex, a purification step using dispersive SPE (dSPE) was necessary to limit the presence of interfering substances. Matrix effects are commonly reported during the analysis of solid samples because the residual matrix components may cause errors, leading to inaccurate results. This phenomenon either positively or negatively influences the ionisation of the analytes, since matrix compounds can be eluted at the same retention times as the compounds of interest. Matrix effects are dependent on the nature of the matrix and the efficiency of the sample preparation and purification. The purification step eliminates interfering compounds while sparing the target analytes. Consequently, the suitable dSPE can be based on the recoveries of target analytes but also on the matrix effect. In fact, the dSPE may decrease the matrix effect and so improve the quantification limits. To evaluate the matrix effects, blank matrix samples were spiked with a methanol



Recovery (%)









A. Berlioz-Barbier et al. 10

Fig. 3 Matrix effects at 200 ng g−1 of the target compounds obtained using different dSPE and without dSPE


Matrix effect (%)

-10 -20 -30





Without dSPE

-60 -70 -80

solution containing the 15 substances at 200 ng g−1. The obtained signals (S spiked matrix) were compared to the signals from a standard (S solvent) at the same concentration. The matrix effect was determined using the following equation:  Matrix effectð%Þ ¼

 Sspiked matrix −1  100 Ssolvent

Therefore, to evaluate the dSPE's clean-up efficiency, three sorbents were tested: PSA, PSA/C18 and PSA/GCB (graphitized carbon black). The recoveries and matrix effects were calculated for each test and are presented in Figs. 2 and 3, respectively. The PSA and PSA/C18 sorbents allowed good recoveries for most of the target compounds, but they caused the loss of ketoprofen. Therefore, neither the PSA nor the

PSA/C18 sorbents were suitable for the dSPE clean-up because they were not inert toward every analyte. The recoveries obtained with the PSA/GCB were lower than those obtained with PSA and PSA/C18 sorbents but the recovery of ketoprofen was increased two-fold. Additionally, using this sorbent reduced the matrix effect for most of the compounds relative to the PSA or PSA/C18 sorbents. Therefore, PSA/ GCB was chosen for clean-up.

Method validation and method performance Method validation is crucial during chemical analysis to prove the consistency of the developed QuEChERS-LC-MS/MS method using established validation criteria [9]. The criteria to validate the method included the limit of quantification,

Table 2 Method performances (LOQs, linearity, R 2, recovery, intra- and inter-day precision Analytes

3,4DCA Carba Keto Eco Nore Tamo Spin 4MBC Pyri PipB BPA E1 3,5DTBP Triclo 2,6DTBP

LOQ (ng g−1)

4.5 0.5 20 1.5 5 2 1.5 12.8 1.5 3.5 8.5 1.5 2 5.5 8

Linearity (ng g−1)

4.5–180 0.5–20 20–800 1.5–60 5–200 2–80 1.5–60 12.8–512 1.5–60 3.5–140 8.5–340 1.5–60 2–80 5.5–220 8–320


0.991 0.996 0.990 0.994 0.997 0.997 0.994 0.991 0.993 0.997 0.998 0.993 0.983 0.997 0.591

Recovery (±RSD;%)

Intra-day precision(RSD%)

Inter-day precision (RSD%)










80(9) 82(5) 37(7) 77(3) 81(6) 76(3) 80(4) 80(9) 79(10) 90(5) 98(6) 79(7) 94(10) 80(6) 72(16)

81(6) 85(5) 42(9) 79(4) 82(8) 77(5) 86(6) 82(8) 80(9) 92(6) 99(3) 80(9) 90(8) 81(5) 79(12)

84(7) 84(6) 41(8) 80(3) 84(4) 73(3) 82(5) 85(7) 83(8) 94(6) 96(5) 83(4) 88(9) 82(4) 87(10)

3 3 4 7 3 2 1 2 3 5 5 8 5 1 6

4 2 2 2 6 1 1 2 1 1 1 14 1 1 3

2 2 1 1 2 2 5 1 1 1 1 3 1 4 1

12 6 7 10 11 5 3 8 8 15 11 10 11 12 30

9 6 5 7 4 4 4 15 8 26 9 9 10 9 35

7 4 6 7 4 4 7 9 8 18 11 5 14 8 34

Multi-residue analysis of emerging pollutants in sediment

linearity and recovery, as well as inter- and intra-day precision, as indicated by the International Conference on Harmonisation (ICH) [10]. The LOQ were determined using signal-to-noise ratio of 10 [11] and are reported in Table 2. They ranged from 0.5 to 20 ng g−1 and were comparable with the literature values. For hormones, Zhang et al. [12] reported larger LOQs than ours (0.06–0.64 ng g−1). However, Zhang et al. focused on oestrogenic compounds, while a multiresidue method was established in our work. For some compounds, such as carbamazepine and bisphenol A, the LOQs reported in the current study were as low as 0.5 ng g−1, while Salvia et al. [13] reported values varying from 0.018 to 0.94 ng g−1. They achieved better LOQs values because the preconcentration factor was more important in their study than in ours. However, Vasquez-Roig et al. [14] used pressurised liquid extraction (PLE) and liquid chromatography tandem mass spectrometry to determine pharmaceutical contents in soils and sediments and reported values similar to ours; however, our method was less timeconsuming. Moreover, the response of each compound, except for 2,6DTBP and 3,5DTBP, was linear over the entire concentration range; the correlation coefficients (R 2) were higher than 0.99. The acceptability of the linearity data was also evaluated using the statistical Fisher test as described by Araujo et al. [15]. This reliable approach assesses the linearity of calibration functions. Every compound, except for 2, 6DTBP, successfully passed the Fisher test. The linearity of 3,5DTBP presented a correlation coefficient below 0.99 but was still validated by the Fisher test. Consequently, the linearity was validated for every compound except for 2, 6DTBP. The recoveries and RSDs were calculated in triplicate and are presented in Table 2. The recoveries exceeded 50 %, except for ketoprofen (approximately 40 % recovery). However, the RSD for ketoprofen was below 20 %, meaning that the method was still reliable for this compound. This low recovery is due the loss during purification. Indeed, the loss of polar analytes such as Keto, could occur if GCB is used as dSPE. For the oestrogens, the recoveries were concentrationdependent, and comparisons between analyses performed at different concentrations are sometimes difficult. Nevertheless, Zhang et al. reported recoveries between 70 to 90 % at approximately 100 ng g−1 [12] while using PLE; their results are comparable to our recoveries. Finally, for carbamazepine, the recovery obtained by Vasquez-Roig et al. [13] using a PLE extraction on sediment was 86 % at 50 ng g−1. For the intraday precision, good results were obtained (Table 2); the calculated RSDs were below 20 % for every compound. The intra-day precision was below 10 % for many of the investigated compounds. Moreover, for the intermediate precision evaluated at the same levels as reproducibility over 3 days, the RSDs were below 30 % for every compound except for 2,6DTBP (RSD=35 %). The high RSDs for 3, 5DTBP and 2,6DTBP and the non-linearity of the latter


compound might be caused by the degradation of 2,6DTBP that generates 3,5DTBP. This hypothesis was based on a previous study conducted in our laboratory. Indeed, several injections of standard solution containing both alkylphenols were performed in constant time intervals. We noticed a simultaneous decrease of 2,6DTBP signal and an increase of 3,5DTBP. Consequently, 2,6DTBP may degrade to 3,5DTBP. However, to our knowledge, no paper refers this degradation. In fact, both compounds have never been analysed simultaneous in environmental matrices such as sediment. Finally, according to the ICH, the developed QuEChERSLC-MS/MS method was validated for every compound of interest, except for 2,6DTBP. This material should be excluded from the quantification of real samples; only its presence may be checked.

Conclusion This work presents a simple and effective multi-residue procedure to determine the content of emerging pollutants in sediments. This approach uses a simple extraction technique and applies it to a wide range of substances exhibiting various chemical properties. By combining a quick, simple extraction and dSPE cleanup with LC-MS/MS analysis, the obtained method is both selective and sensitive. This procedure enables the determination of target analytes in the nanogramper-gram range. Finally, the multi-residue method was successfully validated according to the criteria in the ICH standard.

References 1. Kasprzyk-Hordern B, Dinsdale R-M, Guwy A-J (2008) The occurrence of pharmaceuticals, personal care products, endocrine disruptors and illicit drugs in surface water in South Wales, UK. Water Res 42(1):3498–3518 2. Conley J-M, Symes S-J, Kindelberger S-A, Richards S-M (2008) Rapid liquid chromatography-tandem mass spectrometry method for the determination of broad pharmaceuticals in surface water. J Chromatogr A 1185:206–2015 3. Varca L-M (2012) Pesticide residues in surface waters of Pagsanjan– Lumban catchment of Laguna de Bay, Philippines. Agric Water Manag 106:35–41 4. Labadie P, Hill E-M (2007) Analysis of estrogens in river sediments by liquid chromatography–electrospray ionization mass spectrometry. Comparison of tandem mass spectrometry and time-of-flight mass spectrometry. J Chromatogr A 1141:174–181 5. Petrovic M, Hernando M-D, Diaz-Cruz M-S, Barcelo D (2005) Liquid chromatography–tandem mass spectrometry for the analysis of pharmaceutical residues in environmental samples: a review. J Chromatogr A 1067:1–14

1266 6. Eiguren Fernández A, Sosa Ferrera Z, Santana Rodríguez J-J (2001) Application of microwave-assisted extraction using micellar media to the determination of polychlorinated biphenyls in marine sediments. Anal Chim Acta 433(2):237–244 7. EN 15662: 2009-01-01- Food of plant origin—determination of pesticide residues using GC-MS and/or LC-MS/MS following acetonitrile extraction/partitioning and clean up by dispersive SPE-QuEChERS method (2009). Austrian Standards institute, Österreichisches Normungsinstitut (ON) Heinestaβe 38, 1020 Wien 8. AOAC Official Method 2007–01. Pesticide residues in food by acetonitrile extraction and partitioning with magnesium sulfate (2007). AOAC International 9. Rambla-Alegre M, Esteve-Romero J, Carda-Broch S (2012) Is it really necessary to validate an analytical method or not? That is the question. J Chromatogr A 1232:101–109 10. ICH (2005) International Conference on Harmonisation of technical requirements for registration of pharmaceuticals for human use. Paper presented at the ICH harmonised tripartite guideline, validation of analytical procedures: text and methodology Q2 (R1). ICH, Geneva

A. Berlioz-Barbier et al. 11. Vial J, Jardy A (1999) Experimental comparison of the different approaches to estimate LOD and LOQ of an HPLC method. Anal Chem 71(14):2672–2677 12. Zhang Z, Rhind SM, Kerr C, Osprey M, Kyle CE (2011) Selective pressurized liquid extraction of estrogenic compounds in soil and analysis by gas chromatography–mass spectrometry. Anal Chim Acta 685(1):29–35 13. Salvia MV, Vulliet E, Wiest L, Baudot R, Cren-Olivé C (2012) Development of multi-residue method using acetonitrile-based extraction followed by liquid chromatography-tandem mass spectrometry for the analysis of steroids and veterinary and human drugs at trace levels in soil. J Chromatogr A 1245: 122–133 14. Vazquez-Roiga P, Segarraa R, Blascoa C, Andreub V, Picóa Y (2010) Determination of pharmaceuticals in soils and sediments by pressurized liquid extraction and liquid chromatography tandem mass spectrometry. J Chromatogr A 1217(16):2471– 2483 15. Araujo P (2009) Key aspects of analytical method validation and linearity evaluation. J Chromatogr B 877(23):2224–2234

MS analysis.

Emerging contaminants are suspected to cause adverse effects in humans and wildlife. Aquatic ecosystems are continuously contaminated by agricultural ...
768KB Sizes 0 Downloads 0 Views