Multifactorial optimization approach for the determination of polycyclic aromatic hydrocarbons in river sediments by gas chromatography–quadrupole ion trap selected ion storage mass spectrometry

Multifactorial optimization approach for the determination of polycyclic aromatic hydrocarbons in river sediments by gas chromatography–quadrupole ion trap selected ion storage mass spectrometry

Journal of Chromatography A, 1192 (2008) 273–281 Contents lists available at ScienceDirect Journal of Chromatography A journal homepage: www.elsevie...

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Journal of Chromatography A, 1192 (2008) 273–281

Contents lists available at ScienceDirect

Journal of Chromatography A journal homepage: www.elsevier.com/locate/chroma

Multifactorial optimization approach for the determination of polycyclic aromatic hydrocarbons in river sediments by gas chromatography–quadrupole ion trap selected ion storage mass spectrometry Natalicio Ferreira Leite a , Patricio Peralta-Zamora b , Marco Tadeu Grassi b,∗ a b

Instituto de Tecnologia do Paran´ a (TECPAR), 81350-010 Curitiba, PR, Brazil Departamento de Qu´ımica, Universidade Federal do Paran´ a (UFPR), C.P. 19081, 81531-990 Curitiba, PR, Brazil

a r t i c l e

i n f o

Article history: Received 19 December 2007 Received in revised form 19 March 2008 Accepted 25 March 2008 Available online 28 March 2008 Keywords: Factorial design GC–MS PAHs Trace level analysis Complex matrices

a b s t r a c t A procedure for the determination of very low polycyclic aromatic hydrocarbons (PAHs) concentrations in sediment samples has been developed by gas chromatography–quadrupole ion trap mass spectrometry (GC–QIT MS) after extraction with dichloromethane and purification by using silica gel cleanup. Identification and quantification of analytes were based on the selected ion storage (SIS) strategy using deuterated PAHs as internal standards. In order to search out the main factors affecting the SIS mass spectrometry efficiency, four MS parameters, including target total ion count (TTIC), waveform amplitude (WA), transfer line (XLT) and ion trap temperatures (ITT) were subjected to a complete multifactorial design. The most relevant parameters obtained (TTIC and WA) were optimized by a rotatable and orthogonal composite design. Optimum values for these parameters were selected for the development of the method involving PAH determination in sediment samples. The optimized method exhibited a range of 111–760% higher signal-to-noise (S/N) ratios for PAHs in comparison with the method operated by the default conditions, demonstrating that the multifactorial optimization contributed to substantially improve the sensitivity of the GC–QIT MS determination. The accuracy of the method was verified by analyzing NWRI EC-3 certified reference material (Lake Ontario sediment). The selectivity, sensitivity (limits of quantification were in the range of 0.02–11.0 ng g−1 ), accuracy (recoveries ≥77%) and precision (RSD ≤ 30%) obtained were quite adequate for the determination of very low target PAHs in sediment samples. The established method was then applied to determine 16 PAHs in river sediments from the Metropolitan Region of Curitiba, Brazil. Two selected sediment samples were analyzed, one from the Canguiri River (a slightly urbanized area), and the other from the Iguac¸u River (a heavily urbanized area), illustrating the capabilities of the method to detect PAHs at the threshold concentrations necessary to classify the sediments as well as the status of contamination. © 2008 Elsevier B.V. All rights reserved.

1. Introduction Polycyclic aromatic hydrocarbons (PAHs) comprise a wide class of compounds and hundreds of individual substances that are released to the environment by natural and anthropogenic processes during incomplete combustion or pyrolysis of organic matter [1]. PAHs are ubiquitous environmental contaminants and their presence has been confirmed in a variety of environmental matrices such as ambient air [2–4], food chain organisms [5–7], sediments [8–11], soil [12–14], vegetation [15,16], and waters [11,17] all over the world. Due to their low solubility in water, PAHs are concentrated in bottom sediments and biota where they exert well

∗ Corresponding author. Tel.: +55 41 3361 3176; fax: +55 41 3361 3186. E-mail address: [email protected] (M.T. Grassi). 0021-9673/$ – see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.chroma.2008.03.067

characterized toxic effects (i.e. carcinogenic, mutagenic) [18]. Thus, an assessment of the effects of pollution on life in aquatic environments requires the sources and concentrations of the pollutants to be determined. In this context, bottom sediments are a very useful material for investigation, because they act as a sorption column providing a clear picture of events taking place in the overlying water [19]. Currently, capillary gas chromatography (GC) is the most frequently used analytical technique for the determination of PAHs in environmental samples [20] due to the favorable combination of greater sensitivity and resolution when compared to liquid chromatography (LC). Detection of PAHs in environmental samples following GC separation is most commonly accomplished by use of flame ionization (FID) and MS detectors [21]. However, GC–MS is often more accurate than conventional GC/FID because interference from co-eluting compounds is minimized by the selective nature of

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the detector. Characteristics such as the thermal properties of PAHs, which are particularly amenable to GC contribute to the usefulness of GC–MS techniques for determining these compounds. Another factor that contributes in a similar manner is the electron ionization (EI) due to the projection of large molecular ion peaks or little fragmentation in common MS sources [20]. Three-dimensional quadrupole ion trap MS (QIT MS) has been developed and compared to GC and LC methods, including GC–MS using a linear quadrupole and selected ion monitoring (SIM), and LC/fluorescence detection methods [22]. EI is the most widely used ionization method in QIT MS ion sources for the determination of PAHs, although alternative modes include positive and negative chemical ionization [20,21]. In addition, up-to-date instruments include capabilities such as the tandem-in-time feature, that can be employed to conveniently perform MSn experiments [23], and selected ion storage (SIS), that selectively stores specified target ions, while ejecting those originating in the matrix (the terms select ion monitoring, multiple ion detection (MID) are also in use instead of SIS) [24]. The acquisition strategy adopted in this work was based upon the ion storage capability of the QIT MS due the potential of improved limits of detection for trace quantities in complex matrices, which have been well documented in the literature [24–28]. Unfortunately, the presence of too many ions in the QIT leads to mass misassignment and limited dynamic range as a result of ion–ion interactions shielding the ions from the imposed electrostatic fields (space charging). Nowadays, the ion trap MS instruments automatically control the ionization time in order to maintain the number of ions in the trap at the optimum level. Although this approach usually works, it is nondiscriminating given that ions from every compound entering the QIT are reduced. Thus, the ratio between the number of ions from column bleed or matrix background to the number of ions of the compound of interest is kept constant when the total analytical signal is decreased [26]. Based on this fact, and due to the extreme complexity of the sediment matrices, the instrumental parameters of QIT MS must be thoroughly optimized in order to attain the best sensitivity and selectivity to detect trace quantities of PAHs. Although most of the reported methods have been optimized by using one variable at a time, this approach assumes no interaction between variables, which can lead to biased results. The potential of statistical approaches combining experimental design with multifactorial regression analyses has been mainly illustrated in sample extraction and cleanup methods [12,13,29,30]. Despite the use of QIT MS for the determination of PAHs in biota and sediment samples by the SIS approach [3,27,28], there is no systematic study based on factorial design systems to optimize parameters that affect the performance of the MS. Due to the numerous variables involved throughout the ionization, ion trapping, storage, and detection steps from QIT MS/SIS, and due to the probable interaction effects among these variables, the use of factorial design can be an invaluable alternative for the optimization instead of the univariate methods. Factorial design consists of advanced statistical tools that involve simultaneous combinations of a number of parameters according to a predefined regime and if only two levels of experimental change are considered, the factorial number of experiments required is 2n , where n is the number of variables (factors) to be studied [31]. Taking all the aforementioned aspects into account, the aim of the present study was to establish an overall analytical method, including extraction and cleanup procedures and an optimization of a set of QIT MS/SIS instrument parameters, in order to attain the highest possible sensitivity for the determination of PAHs in river sediments. Particular attention was paid to the optimization of four MS parameters, namely target total ion count (TTIC), wave-

form amplitude (WA), transfer line (XLT) and ion trap temperature (ITT). Thus, a study of these instrumental parameters was carried out with the help of an experimental design strategy, which reduces the experimental work required and allows accounting for possible interactions among factors [31]. The performance of the method was studied, demonstrating that limits of detection in the low ppb levels can be achieved. The established method was then applied to the determination of 16 priority PAHs in sediment samples collected in rivers located at the Metropolitan Region of Curitiba, in Brazil. 2. Experimental 2.1. Materials and reagents A mix of 16 PAHs priority pollutants according to the U.S. Environmental Protection Agency (EPA) (acenaphthene, acenaphthylene, anthracene, benzo[a]anthracene, benzo[a]pyrene, benzo[b]fluoranthene, benzo[g,h,i]perylene, benzo[k] fluoranthene, crysene, dibenzo[a,h]anthracene, fluoranthene, fluorene, indene[1,2,3-cd]pyrene, naphthalene, phenanthrene, and pyrene) at 2 mg mL−1 and a mix of 5 deuterated PAHs ([2 H10 ]acenaphthene, [2 H12 ]crysene, [2 H8 ]naphthalene, [2 H12 ]perylene, and [2 H10 ]phenanthrene) at 4 mg mL−1 were supplied by Ultra Scientific (North Kingstown, RI, USA). Standard stock solutions of 400 ␮g mL−1 of deuterated PAHs (used as internal standard) and 100 ␮g mL−1 of PAHs were prepared in acetone. Working solutions were obtained by appropriate dilution in n-hexane. All solutions were stored in amber colored vials at −20 ◦ C. Anhydrous sodium sulfate, copper powder, and silica gel (0.063–0.200 mm) were supplied by Merck (Darmstadt, Germany), while acetone, cyclohexane, dichloromethane, n-hexane, and pentane were supplied by Mallinckrodt (Paris, KY, USA). Immediately before use, anhydrous sodium sulfate was purified by heating at 400 ◦ C for 4 h; copper powder was activated by treating with dilute hydrochloric acid, rinsed with organic-free reagent water, with acetone and dried under a stream of nitrogen. Silica gel was activated by heating at 135 ◦ C for 16 h. All organic solvents were pesticidefree grade. Helium (purity 99.9999%) was supplied by White Martins (Curitiba, Brazil). Reference material NWRI EC-3 (Lake Ontario sediment) supplied by National Water Research Institute, Environment Canada (Burlington, Canada) was used to study the accuracy. 2.2. Analysis—MS parameter optimization The GC–MS analysis was performed on a Varian CP-3800 gas chromatograph (Walnut Creek, CA, USA) equipped with a Varian Saturn 2000 three-dimensional quadrupole ion trap MS. The target compounds were separated on a 30 m length × 0.25 mm i.d. capillary column coated with a 0.25 ␮m film thickness (diphenyl 5% dimethylsiloxane 95%) stationary phase (Chrompack CP-Sil8). Helium was employed as carrier gas, with a constant column flow of 1.0 mL min−1 . All injections (1 ␮L) were carried out through a universal injector (Varian 1177) in the splitless mode and programmed to return to the split mode after 0.75 min from the beginning of a run, and the samples were introduced using a CP-8400 Varian auto-sampler. Split flow was set at 30 mL min−1 . The GC oven temperature program was: 80 ◦ C for 3 min, 20 ◦ C min−1 to 230 ◦ C, 10 ◦ C min−1 to 300 ◦ C and held for 6.5 min, with a total acquisition program of 24 min. The temperature of the injector was kept constant through all injections at 280 ◦ C. By using these chromatographic conditions it was possible to qualitatively distinguish

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between benzo[a]anthracene/crysene, a pair of isomers that are commonly co-eluted by gas chromatographic systems. The target compounds were identified by GC retention times, comparison with authentic standards, and from their recorded mass spectra with the NIST Mass Spectral Program [32]. The main prominent ion suggested by the NIST Program for each target compound was selected for the MS optimization. These most abundant ions were confirmed through the ion trap mass spectrogram obtained by separated injection of a mixture of 16 target PAHs and a mixture of 5 target deuterated PAHs in the GC–QIT MS operating in full-scan mode. In general, the MS was operated in the EI mode at 70 eV, 10 ␮A for emission current, 100 ␮s for the prescan ionization time, 4.1 V for the axial modulation voltage, and −1950 V for the electron multiplier set. The mass range was scanned from 90 to 300 massto-charge ratio (m/z) at 1 s scan−1 . In order to obtain the best individual SIS conditions, the chromatographic profile was divided in eight periods, each one containing specific parameters for a target analyte or a group of analytes eluting in the period, resulting in no more than a maximum of four ions being monitored at any given time. For the initial SIS experiment, default values for all other operating parameters of the MS system were set. These were 170 ◦ C for the ITT, 200 ◦ C for the XLT, 20,000 counts for the TTIC; 48 m/z for the storage ion level, automatic WA and the values previously described for the full-scan experiment. Once the quality of mass spectrograms obtained by using the aforementioned SIS experiment was confirmed, the following four instrument parameters were simultaneously investigated in a multifactorial experimental design, to optimize the MS/SIS performance: TTIC, WA, XLT and ITT. The TTIC (target total ion count) value establishes how many ions are allowed into the ion trap during the ionization time. While the increase in the TTIC value will amplify peak heights, increasing it too far will result in a loss of mass resolution. This would be observed as mass misassignments and/or incorrect isotope abundance ratios. WA (waveform voltage amplitude) is scaled as a function of the frequency components and storage radio-frequency voltage selected to eject masses above the stored target ions, contributing to a signal-to-noise (S/N) ratio enhancement. XLT (GC–MS transfer line temperature) refers to the temperature applied in the line bridging the distance between the gas chromatograph oven and the ion source to prevent re-adsorption or condensation of eluting components to the end of the column before the ion trap cavity entrance, especially to those less volatile analytes [23]. ITT (ion trap temperature) refers to the temperature applied in the ion trap oven assembly that should be high enough so that the chromatographic performance is not affected. The degree of neutral sample molecule fragmentation is a function of the internal energy of the molecules, which is a function of the energy imparted by the electrons (electron ionization ion source), as well as the ion trap temperature and the axial modulation voltage amplitude. All measurements, in integrated peak area, were carried out using an unpolluted sediment (Canguiri River) organic extract enriched to accomplish a final concentration of 5 ng ␮L−1 for both the PAHs and the deuterated PAHs. 2.3. Sediment sampling and preparation procedures Sediment samples were obtained in the Iguac¸u River system located in the Metropolitan Region of Curitiba in November 2005 using a homemade PVC hand corer (50 mm i.d., 20–25 cm deep). Two river sediment samples were selected to illustrated this study, one from the Canguiri River (latitude 25◦ 32 16.5 S, longitude 49◦ 13 32.5 E), a light-urban area, and another from the Iguac¸u River

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(latitude 25◦ 22 39.5 S, longitude 49◦ 07 11.7 E), a heavy-urban site. Sediment samples stored at −18 ◦ C were thawed at room temperature, transferred to a glass tray and thoroughly mixed. The glass tray was loosely covered with aluminum foil, which was previously perforated, and air-dried for about 5 days under exhaust in a darkened fume hood at about 60% relative humidity and ambient temperature (20–25 ◦ C). Next, each sample was ground in a heavy porcelain mortar and passed through a 149 ␮m sieve. Foreign objects such as sticks, leaves, and rocks were discarded. The samples were then homogenized and stored in a desiccator in the dark at room temperature. The extraction of the PAHs from the sediments was performed according the optimized procedure reported by Wolska [19] and the organic extracts were cleaned up according to U.S. EPA Method 3630C [33]. An aliquot of approximately 10 g of the dried sediment was thoroughly mixed with an equal mass of anhydrous sodium sulfate, transferred to a 250 mL screw cap Erlenmeyer flask, wetted with acetone, spiked with 10 ng of each internal standard and extracted in a shaker apparatus at 120 rpm for 16 h with 50 mL of dichloromethane. The volume of the extract was concentrated in a rota-evaporator to about 5 mL, and the solvent was exchanged by addition of approximately 2 mL of cyclohexane. The volume was reduced again to 2 mL in the same evaporator apparatus. The cleanup of the sample extracts was accomplished by passing them through a chromatographic column (11 mm × 300 mm) which was packed with 0.1 g of activated copper at the bottom to absorb elemental sulfur, 10 g of activated silica gel, and about 2 g of anhydrous sodium sulfate on top to absorb residual water. The extract was cleaned up with 15 mL of pentane and the PAH fraction was recovered with 50 mL of dichloromethane/pentane (2 + 3, v/v) into a Kuderna-Danish concentrator attached to a 5 mL calibrated graduated tube. Then a gentle stream of nitrogen was used to bring the volume of the extract down to 1 mL. The final extract was transferred to an amber vial, sealed and stored at −18 ◦ C until the following analysis. 2.4. Quality assurance and quality control A strict regime of quality control was maintained in the experiment. Deuterated internal standards were used throughout to compensate for losses from sample extraction and workup. For all preparation methods, blank solutions were run parallel to the determinations and their results taken into consideration. Before the onset of the sampling and analysis program, PAH recovery studies were undertaken to demonstrate the suitability of the method. Sediment samples spiked with all 16 PAHs were analyzed with good precision. The reference material NWRI EC-3 was analyzed with good agreement with certified values (Table 6). 3. Results and discussion 3.1. Sample extraction and cleanup method In recognition of the need for effective, robust and reliable sample preparation, we chose a PAH extraction method that was simple, easy and did not use much glassware, by means of the optimized conditions described by Wolska [19]. This method only requires Erlenmeyer flasks and one shaker, items that are commonly found in laboratories, and uses small amounts of reagents when compared to the conventional Soxhlet technique (60 mL compared to a range from 100 to 400 mL). Prior to using GC for the separation of PAHs, sediment extracts were concentrated and cleaned up by use of solid-phase extraction procedures to remove potential interfering polar constituents according to U.S. EPA protocols [33].

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Table 1 Experimental field definition for the complete factorial and central composite designs Parametera

Key

TTIC (counts) WA (V) ITT (◦ C) XLT (◦ C)

A B C D

Low (−)

High (+)

Central point (0)

6,000 8 170 200

34,000 46 220 325

20,000 27 195 263

a TTIC: target total ion count; WA: waveform amplitude; ITT: ion trap temperature; XLT: GC–MS transfer line temperature.

3.2. Optimization of the selected ion storage conditions Four different parameters affecting the PAH selected ion storage efficiency by GC–MS measurement (TTIC, WA, XLT and ITT) from the sediment samples were studied. Table 1 lists the upper, lower and central point values given to each parameter. The compounds belonging to the same period group showed similar behavior during the variation of a parameter and so the compound that shows the most optimum values in each period was chosen to define period optimization. Table 4 shows the final values for each optimized period. 3.3. Complete factorial analysis To evaluate the influence of the main operational parameters on the efficiency of the QIT MS/SIS system a complete 24 factorial design was carried out by using a Statgraphics Plus 5.0 routine (Statgraphics Graphics Corporation, SC, USA). Table 2 shows the experimental design matrix, lists the upper and lower values and the processed response, i.e., average integrated area of three determinations obtained for each run for three selected target compounds that represent the behavior of all studied compounds. The analysis of the results shown in Table 2 produces the main effect and the two-factor interactions Pareto charts (P = 95%) shown in Fig. 1 for three selected target compounds that represented the behavior of all compounds studied. In these charts, bar lengths are proportional to the absolute value of the estimated effect, helping in comparing the relative importance of effects. Pareto charts also show, as a vertical black line, the minimum t-values (at the 95% confidence interval) 2.45. A parameter which offers a value higher than ±t was assumed as significant [31].

3.6. Influence of ion trap temperature Pareto charts (Fig. 1) show that the ion trap temperature was an important factor for four, five and six rings PAHs, with a statistically significant positive effect for benzo[b]fluoranthene /benzo[k]fluoranthene, benzo[a]pyrene, [2 H12 ]perylene, indene [1,2,3-cd]pyrene and dibenzo[a,h]anthracene. The Pareto charts demonstrate a significant effect of the ion trap temperature (labeled as C) for benzo[a]pyrene (Fig. 1-(i)) and indene[1,2,3-cd]pyrene (Fig. 1-(ii)), representing other four, five and six rings PAHs. Additionally, a significant interaction between WA and ITT variables was observed. However, the ITT parameter was fixed at 220 ◦ C, the maximum value recommended by the instrument supplier, in view of the positive effect on the benzo[a]pyrene signal. 3.7. Influence of GC–MS transfer line temperature The GC–MS XLT (Fig. 1, labeled as D) in the range of 200–325 ◦ C did not produce any significant effect in the MS response for the PAH measurements. The insignificance of this factor can be explained by the high thermal stability of PAHs between the high-end chromatographic column and ion trap cavity temperatures in the evaluated range. Due to the low significance given by this parameter, it can be considered as a dummy factor. Taking into account the low significance of the XLT parameter, it was fixed at 280 ◦ C, the chromatographic column temperature programmed in the retention time for the last PAH eluted (benzo[g,h,i]perilene). 3.8. Rotatable and orthogonal central composite design Screening out the parameters ITT and XLT, the remaining factors affecting the SIS efficiency for each ion preparation period were

3.4. Influence of the target total ion count The TTIC (Fig. 1-(i), labeled as A), ranging between 6000 and 34,000 counts, shows an irrelevant effect on the analytical response of all studied substrates, except for benzo[a]pyrene. In this case, a negative effect equal to t was observed. The insignificance of this factor for almost all analytes can be explained by a low concentration of target compounds and relatively low matrix effect of the sample extract resulting in a low ion density in the ion cavity of the mass spectrometer. Despite showing a low influence on the determination of almost all studied compounds, the TTIC factor was selected for the next experimental design step, mainly on account of the effect on the benzo[a]pyrene response. 3.5. Influence of waveform amplitude The results of the factorial design show that WA (Fig. 1-(i) and (ii), labeled as B) was the most important factor, negatively affecting the analytical response. With the exception of anthracene, WA was the only statistically significant factor for all studied PAHs.

Fig. 1. Standardization (P = 95%) main effects Pareto charts for the complete factorial design for the two selected target compounds: A, TTIC—target total ion count (counts); B, WA—waveform amplitude (V); C, ITT—ion trap temperature (◦ C) and D, XLT—GC–MS transfer line temperature (◦ C).

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Table 2 Complete factorial design for the determination of significant variables for the determination of PAHs by GC–QIT MS/SIS Run number

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Selected target compounds (integrated peak area)a

Factors A

B

C

D

Benzo[a]pyrene

− + − + − + − + − + − + − + − +

− − + + − − + + − − + + − − + +

− − − − + + + + − − − − + + + +

− − − − − − − − + + + + + + + +

547 21,662 4,102 8,006 84,991 281,851 136,043 33,191 64,985 7,515 12,882 25,887 147,637 38,519 92,942 39,091

Phenanthrene

Indene[1,2,3-cd]pyrene

240,600 268,758 265,055 129,729 196,516 423,155 321,482 162,756 477,933 131,601 187,124 267,275 266,451 161,879 241,327 201,914

1,216 14,576 8,596 1,161 1,959 278,441 151,031 2,641 13,226 1,276 1,772 4,574 195,831 1,732 83,400 1,466

Factors—A: TTIC (target total ion count), counts; B: WA (waveform amplitude), V; C: ITT (ion trap temperature), ◦ C; D: XLT (GC–MS transfer line temperature), ◦ C. Values: low (−); high (+). a Mean of three determinations. Table 3 Central 22 + star rotatable and orthogonal composite design for the set target total ion count (A) and waveform amplitude (B) for PAHs quantification by GC–QIT MS/SIS Run number

A

B

Selected target compounds (integrated peak area)a

1 2 3 4 5 6 7 8 9

6,000 (−1) 34,000 (+1) 6,000 (−1) 34,000 (+1) 20,000 (0) 201 (−21/2 ) 39,800 (+21/2 ) 20,000 (0) 20,000 (0)

8.0 (−1) 8.0 (−1) 46.0 (+1) 46.0 (+1) 27.0 (0) 27.0 (0) 27.0 (0) 0.1 (−21/2 ) 53.9 (+21/2 )

43,314 57,757 12,596 17,293 66,588 10,710 28,747 61,036 1,132

Benzo[a]pyrene

Phenanthrene

Indene[1,2,3-cd]pyrene

394,756 330,189 177,199 213,605 389,890 268,729 270,604 388,358 46,975

15,433 2,122 1,147 2,237 18,973 17,845 3,242 16,298 954

Factors—A: TTIC (target total ion count), counts; B: WA (waveform amplitude), V. a Mean for three determinations, except run 5 (central point) that represent the mean of 16 determinations.

optimized by a central 22 + star rotatable and orthogonal composite design resulting in nine randomized runs for each ion preparation period. The parameters optimized were TTIC and WA for all studied compounds. Table 1 also summarizes the experimental field definition used for these designs. Table 3 shows the central composite designs together with the response obtained for three selected target compounds (benzo[a]pyrene, phenanthrene and indene[1,2,3cd]pyrene) that represented the behavior of all of them. An evaluation of the estimated response surfaces for TTIC and WA parameters for all eight SIS acquisition periods for PAHs measurement showed the optimum values for each parameter. The response surfaces obtained for TTIC and WA show a similar behavior for each one of the target PAHs and the deuterated PAHs studied. It can be seen from Fig. 2 that the response surfaces for phenanthrene (Fig. 2-(a)), benzo[a]pyrene (Fig. 2-(b)) and indene[1,2,3-cd]pyrene (Fig. 2-(c)) present a strong curvature corresponding to the first half of the WA and the central portion of the TTIC ranges. In general, the integrated area decreased when the WA was higher and when the TTIC values are extreme, both lower and higher. The optimum response was then achieved for the region that comprises the first half of the WA and intermediate TTIC ranges. For the illustrated compounds, 18.5, 14.6 and 18.1 V for WA and 20,100, 21,300 and 17,200 counts for TTIC, respectively, were selected as optimum values (ITMS/SIS periods 5, 8 and 9, respectively). No significant differences were observed for those compounds with distinct number of rings.

Given these findings, we decided to work with the optimum values obtained for the factors that were studied. For each MS/SIS period we selected an analyte that show the best period values to represent that specific period. Optimum conditions for the determination of PAHs by ITMS/SIS, extracted from this experiment, are summarized in Table 4. Deuterated PAHs (internal standards) were not considered in this selection.

Table 4 Optimum parameter values for the determination of PAHs by QIT MS/SIS SIS perioda 2 3 4 5 6 7 8 9

Period time (min) 5.0–7.0 7.0–9.5 9.5–10.0 10.0–11.5 11.5–13.5 13.5–16.0 16.0–19.0 19.0–23.0

WA (V)b 9.5 16.5 19.8 18.5 13.1 10.6 14.6 18.1

TTIC (counts)b 15,700 17,400 17,800 20,100 19,400 9,800 21,300 17,200

a Acquisition SIS periods—1 (not showed): ion source and electron multiplier and naphthalene; 3: acenaphthylene, delay; 2: [2 H8 ]naphthalene 2 [ H10 ]acenaphthene and acenaphthene; 4: fluorene; 5: [2 H10 ]phenanthrene, phenanthrene and anthracene; 6: fluoranthene and pyrene; 7: benzo[a]anthracene, [2 H12 ]crysene and crysene; 8: benzo[b]fluoranthene, benzo[k]fluoranthene, benzo[a]pyrene and [2 H12 ]perylene; 9: indene[1,2,3cd]pyrene, dibenzo[a,h]anthracene and benzo[g,h,i]perylene. b WA: waveform amplitude; TTIC: target total ion count.

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Table 5 Ions selected during QIT MS/SIS analysis of PAHs, retention times, signal-to-noise ratios (S/N) and method quantification limits (MQL) Compounda 2

[ H8 ]Naphthalene Naphthalened Acenaphthylened [2 H10 ]Acenaphthene Acenaphthenee Fluorenee [2 H10 ]Phenanthrene Phenanthrened Anthracenef Fluoranthenef Pyrenef Benzo[a]anthraceneg Cryseneg [2 H12 ]Crysene Benzo[b/k]fluoranthenesg , h Benzo[a]pyreneg [2 H12 ]Perylene Indene[1,2,3-cd]pyrenei Dibenzo[a,h]anthracenei Benzo[g,h,i]perylenei a b c d e f g h i

Retention time (min)

m/zb

S/N for 50 pg ␮L−1

S/N enhancementc (%)

MQL (ng g−1 )

6.6 6.7 8.7 8.9 9.0 9.6 10.7 10.7 10.9 12.6 13.0 15.2 15.3 15.3 17.4 18.0 18.2 20.7 21.0 21.5

136 128, 129, 127 152, 151, 153 162, 160 153, 154, 152 165, 166, 167 188 178, 179, 176 178, 176, 179 202, 101, 203 202, 200, 203 228, 229, 226 228, 229, 226 240 252, 253, 125 252, 253, 125 264 276, 138, 277 278, 139, 279 276, 138, 277

– 225 402 – 419 162 – 288 278 127 94 52 34 – 27 22 – 6 6 6

– 303 111 – 112 120 – 166 165 191 151 487 619 – 328 760 – 433 433 367

– 0.01 0.01 – 0.01 0.01 – 0.02 0.02 0.05 0.04 0.03 0.03 – 0.6 0.7 – 6.0 11.0 8.0

Compounds are listed in sequence of elution. Target ion in italic. S/N ratio enhancement by comparing with the method operated by the default conditions. Internal standard: [2 H8 ]naphthalene. Internal standard: [2 H10 ]acenaphthene. Internal standard: [2 H10 ]phenanthrene. Internal standard: [2 H12 ]crysene. Benzo[b]fluoranthene and benzo[k]fluoranthene: isomer coeluents considered as a solely analyte. Internal standard: [2 H12 ]perylene.

3.9. Features of the method Linearity of the MS detector response is a parameter of utmost importance for quantification purposes. We studied this parameter by constructing an eight-point calibration curve with standard solutions covering concentrations from 0.05 to 5.00 ␮g mL−1 . In these solutions, the concentration of the internal standard was kept constant (10 ␮g mL−1 ). We performed the injections by gradually decreasing the concentration of the analytes under investigation. Moreover the range of concentrations we have used was sufficiently representative for the determination of PAHs in the sample sediments studied. The relative amount (MPAH /MPAH-D ) of each analyte (MPAH ) for the corresponding amount of the internal standard (MPAH-D ) was plotted versus its corresponding relative peak area (SPAH /SPAH-D ). The quality of calibration was assessed by the determination of the correlation coefficient (r2 ) of the linear analytical curves. The r2 values obtained were higher than 0.993 and can be considered as very satisfactory for the purpose of this study. Table 5 shows the internal standard used for each analyte. Also shown are the retention times, target ions, S/N ratios, S/N ratio enhancement and approximate method quantification limits (MQL) for each analyte by using the optimized conditions. The MQL was defined as the target PAH concentration necessary to obtain a signal-to-noise ratio of approximately 10 by the successive dilutions of a standard solution and taking into account the average mass of sediment sample (10 g). The MQL obtained was at concentrations ranging from 0.02 to 0.7 ng g−1 , except for indene[1,2,3-cd]pyrene, dibenzo[a,h]anthracene, and benzo[g,h,i]perylene that showed MQLs 6.0, 8.0 and 11.0 ng g−1 , respectively. A 50 pg ␮L−1 PAH standard solution (with the exception of the internal standards) was submitted to the PAH determination by the optimized method in order to calculate the S/N ratio for each target compound. The obtained results, shown in Table 5, were 225, 402, 419 and 162 for naphthalene, acenaphthylene, acenaphthene and fluo-

rene, respectively, that are the first four eluted compounds. A decrease in S/N ratios was observed for the following compounds in the elution order beginning from 288 for phenanthrene until 6 for the last three eluted analytes (indene[1,2,3-cd]pyrene, dibenzo[a,h]anthracene, and benzo[g,h,i]perylene). In general, the worse performance for the later eluting target compounds is typical for most trace level PAH methods and it is most likely due to chromatographic behavior. Furthermore, the baseline noise increased in the acquisition order, which limits the S/N ratio, probably due to the result of the column bleed. This phenomenon was significantly amplified with the sample measurements due to the matrix effect [26]. For comparison purposes the same 50 pg ␮L−1 PAH standard solution was submitted to the PAH determination by the default QIT MS/SIS method and the calculated S/N ratios for each target compound were compared with the first ones. The optimized method exhibited a range of 111–760% higher S/N ratios for PAHs when compared with the method operated under the default conditions (Table 5), demonstrating that the multifactorial optimization contributed to enrich the sample ions relative to the unwanted matrix ions by ejecting the latter throughout ionization, in order to substantially affect the sensitivity of the MS acquisition. 3.10. Validation of the method The NWRI EC-3 reference material was analyzed in order to assess the accuracy of the developed method (including all steps from extraction, through cleanup to GC–QIT MS/SIS analysis). Extracts from four samples were prepared as described earlier. NWRI EC-3 offers certified contents for 16 PAHs (crysene not shown due to the coelution with the isomer triphenylene that was not analyzed). As shown in Table 6, the results were in agreement with the certified value, according to the t-test for a 95% confidence level. The recoveries of the certified values were in the range of 77–121%, demonstrating a good quantitative agreement and a satisfactory performance of the method.

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Table 6 PAH determination of NWRI EC-3 certified reference material—Lake Ontario sediment (n = 4) PAH Acenaphthene Acenaphthylene Anthracene Benzo[a]anthracene Benzo[a]pyrene Benzo[b/k]fluoranthenesc Benzo[g,h,i]perylene Dibenzo[a,h]anthracene Fluoranthene Fluorene Indene[1,2,3-cd]pyrene Naphthalene Phenanthrene Pyrene a b c

Certified value (SD)a (ng g−1 )

Found value (SD)a (ng g−1 )

b

22 (9) 25b (8) 59b (11) 312 (28) 386 (50) 505b (88)/271b (104) 348b (70) 109b (17) 558 (46) 42b (21) 359b (36) 35b (20) 293 (33) 436 (47)

24 (3) 28 (3) 59 (6) 254 (27) 468 (22) 596 (109) 275 (27) 99 (30) 574 (10) 42 (4) 313 (74) 35 (5) 311 (12) 440 (29)

Average recovery (%) 108 112 100 81 121 77 79 91 103 100 87 101 106 101

SD: standard deviation values (in parenthesis). These values are for information purpose only (not certified). Benzo[b]fluoranthene and benzo[k]fluoranthene: isomer coeluents analytes, quantified as a sole compound.

3.11. Application The final optimized method was then applied in the PAH determination in several river sediment samples from the Metropolitan Region of Curitiba, Brazil. Two sediment samples were selected to illustrate this study, one from Canguiri River and the other

from Iguac¸u River, which the collection points were respectively located upstream and downstream from the city of Curitiba. The obtained results are reported in Table 7 where the mean concentration of each target PAH (n = 4) is given together with the standard deviation values and the total PAH concentrations (sum for 16 compounds). The mean concentration of target PAH ranged from not detected for acenaphthene and naphthalene in the Canguiri River to 466.5 ng g−1 dry weight for dibenzo[a,h]anthracene present in the Iguac¸u River sediment. Fig. 3 shows the comparison between the full-scan EI (Fig. 3a) and the SIS analyses (Fig. 3b) for the Iguac¸u River sediment extract. The GC–QIT MS/SIS reconstructed ion chromatogram (Fig. 3b) is much simpler than the GC–QIT MS full-scan chromatogram (Fig. 3a) because, in each period, only target ions of the PAHs were scanned. A closer look at the chromatograms (total ion chromatogram on top and selected ions chromatogram at the bottom) demonstrates that at these levels, the SIS analysis can better distinguish the target compounds from matrix background when compared to the IE analysis. The high sensitivity and specificity, obtained in this study by means of the QIT MS/SIS technique, along with the high recovery rates of the whole ana-

Table 7 PAH concentrations (ng g−1 dry weight) for two river sediment samples located in the Metropolitan Region of Curitiba, Brazil (n = 4) PAH

Canguiri river sediment mean (SD)a (ng g−1 )

Acenaphthene Acenaphthylene Anthracene Benzo[a]anthracene Crysene Benzo[a]pyrene Benzo[b/k]fluoranthenesb Benzo[g,h,i]perylene Dibenzo[a,h]anthracene Fluoranthene Fluorene Indene[1,2,3-cd]pyrene Naphthalene Phenanthrene Pyrene

nd 0.72 (0.08) 4.9 (0.4) 15.1 (3.2) 8.6 (2.2) 18.7 (4.2) 2.4 (0.9) 22.2 (10.1) 24.9 (5.8) 14.9 (2.6) 12.1 (5.3) 8.2 (1.8) nd 6.2 (0.4) 12.9 (3.6)



PAHs

Fig. 2. Estimated response surfaces from the central composite design for three selected target PAH compounds: TTIC (target total ion count, counts)/WA (waveform amplitude, V).

143

Iguac¸u river sediment mean (SD) (ng g−1 ) 2.9 (0.4) 18.3 (0.4) 12.6 (3.5) 10.1 (1.3) 13.4 (1.7) 34.5 (7.1) 13.6 (4.3) 390.2 (57.9) 466.5 (34.5) 99.2 (11.8) 62.5 (12.3) 164.3 (46.9) 256.7 (31.3) 63.6 (17.3) 104.7 (31.2) 1713

nd (not detected) is assigned for PAHs having concentration lower than the method quantification limit. a SD: standard deviation values (between parenthesis). b Benzo[b]fluoranthene and benzo[k]fluoranthene: isomer coeluents analytes, quantified as a sole compound.

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that the multifactorial optimization contributed to enrich the sample ions relative to the unwanted matrix ions by ejecting the latter throughout ionization, in order to substantially improve the sensitivity of the QIT MS/SIS acquisition mode. Results generated by the optimized method indicate that the selectivity, sensitivity, accuracy and precision obtained were adequate for the determination of very low target PAH concentrations in sediment samples. The obtained results for the analysis of NWRI EC-3 reference material were within the acceptance criteria of the accuracy and precision for organic compounds at trace levels in environmental samples. The method was then applied to evaluate the occurrence of 16 PAHs priority pollutants in river sediment samples from the Metropolitan Region of Curitiba (Brazil) and the complete data of this study will be reported in a future publication. However, the results for two selected sediment samples were reported in this paper, one from a slightly urbanized area (Canguiri River) and other from a heavily urbanized area (Iguac¸u River) illustrating the capabilities of the method in detecting PAHs at the threshold concentrations necessary to classify the sediments as well as the contamination status. Our results are the first, to our best knowledge, to be presented for the application of a factorial design approach to optimize instrumental parameters that affect the QIT MS efficiency in the analysis of PAHs in sediments. Acknowledgements

Fig. 3. Comparison of GC–QIT MS chromatograms for the Iguac¸u River extract. (a) Full-scan (*unknown compound coeluting with compounds 9 and 10); (b) selected ions chromatogram for SIS acquisition with the optimized conditions. Peak identities are: 1, naphthalene; 2, acenaphthylene; 3, acenaphthene; 4, fluorene; 5, phenanthrene; 6, anthracene; 7, fluoranthene; 8, pyrene; 9, benzo[a]anthracene; 10, crysene; 11, benzo[b]fluoranthene; 12, benzo[k]fluoranthene; 13, benzo[a]pyrene; 14, indene[1,2,3-cd]pyrene; 15, dibenzo[a,h]anthracene; 16, benzo[g,h,i]perylene (for ions see Table 5).

lytical method makes it possible to quantify several PAHs at low ppb levels in the sediment samples. This is the case with the Canguiri River that is located in a slightly urbanized area and consequently is a less affected water body. In contrast, the Iguac¸u River is a more polluted environment as a consequence of anthropogenic inputs such as sewage discharges and run-off drainages. In fact, the total PAH concentration obtained in Iguac¸u River sediment was 1713 ng g−1 dry weight, almost 12 times higher than the result for the other river, which was 143 ng g−1 dry weight. These results indicate that the Canguiri and Iguac¸u river sediments can be classified, respectively, as slightly and fairly contaminated [11], confirming that the Iguac¸u River is a much more heavily affected environment. 4. Conclusions This study was developed with the aim to establish an overall analytical method, including extraction and cleanup procedures and an optimization of a set of GC–QIT MS/SIS instrumental parameters, in order to attain the highest possible sensitivity for the determination of 16 PAHs in river sediment samples. The usefulness of a complete multifactorial and central composite experimental strategy was demonstrated to search out the main factors affecting SIS mass spectrometry efficiency and to optimize the significant factors, respectively, allowing the optimization of instrumental parameters. In fact, the optimized method exhibited a range of 111–760% higher S/N ratios for target PAHs when compared to instrument operation under the default conditions, demonstrating

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