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Analytica Chimica Acta 587 (2007) 89–96

Headspace–mass spectrometry determination of benzene, tolueneand the mixture of ethylbenzene and xylene isomers in

soil samples using chemometrics

F.A. Esteve-Turrillas, S. Armenta, S. Garrigues, A. Pastor, M. de la Guardia ∗Department of Analytical Chemistry, Universitat de Valencia, Edifici Jeroni Munoz, 50th Dr. Moliner, 46100 Burjassot, Valencia, Spain

Received 5 October 2006; received in revised form 5 January 2007; accepted 15 January 2007Available online 21 January 2007

bstract

A simple and fast method has been developed for the determination of benzene, toluene and the mixture of ethylbenzene and xylene isomersBTEX) in soils. Samples were introduced in 10 mL standard glass vials of a headspace (HS) autosampler together with 150 �L of 2,6,10,14-etramethylpentadecane, heated at 90 ◦C for 10 min and introduced in the mass spectrometer by using a transfer line heated at 250 ◦C as interface.he volatile fraction of samples was directly introduced into the source of the mass spectrometer which was scanned from m/z 75 to 110. A partial

east squares (PLS) multivariate calibration approach based on a classical 33 calibration model was build with mixtures of benzene, toluene and

-xylene in 2,6,10,14-tetramethylpentadecane for BTEX determination. Results obtained for BTEX analysis by HS–MS in different types of soilamples were comparables to those obtained by the reference HS–GC–MS procedure. So, the developed procedure allowed a fast identificationnd prediction of BTEX present in the samples without a prior chromatographic separation.

2007 Elsevier B.V. All rights reserved.

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eywords: Benzene; Toluene; Ethylbenzene; Xylene isomers; Headspace-mass

. Introduction

Volatile organic compounds (VOCs) are chemical productsased on carbon chains or rings, also containing hydrogen withvapour pressure greater than 0.27 kPa at 25 ◦C excludingethane. Measurement of VOCs in different kind of samples

as received significant attention over the past few years becausef direct and indirect impacts of individual VOCs on humanealth and ecosystem. Many VOCs are either known or sus-ected carcinogens and some have toxic effects [1–3]. The 1990S Environmental Protection Agency (EPA) Clean Air Act [4]

ncludes 189 hazardous air pollutants that are mostly VOCs, andt has been evidenced that these compounds also play a criticalole in formation of tropospheric ozone [5,6].

BTEX [benzene, toluene, ethylbenzene and the three xylenesomers (ortho, meta and para)] are a subclass of VOCs withoiling points between 80 and 150 ◦C. Their solubility in water,

∗ Corresponding author. Tel.: +34 963544838; fax: +34 963544838.E-mail address: miguel.delaguardia@uv.es (M. de la Guardia).

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003-2670/$ – see front matter © 2007 Elsevier B.V. All rights reserved.oi:10.1016/j.aca.2007.01.036

trometry; Chemometric analysis

ogether with the chronic toxicity associated with the aromaticing present in their structure, make BTEX display a highollution potential. These aromatic hydrocarbons are widelyistributed in the environment due to natural sources; whichnclude superior plant wax, algae and plankton, and anthro-ogenic sources of hydrocarbons; that comprise domestic andndustrial wastes, biomass and wood burning, incomplete fuelil combustion and urban runoff [7].

Analytical methods of reference for the determination ofTEX residues in environmental samples are based on gashromatography–mass spectrometry (GC–MS), using eithertatic [8] or dynamic [9] headspace (HS) as sample introductionodules. On the other hand, some other techniques like liquid

hromatography [10] or near infrared [11] have been alreadymployed.

In recent years, several novel techniques of sample intro-uction and sample pre-treatment for GC analysis, like

urge-and-trap [12], membrane extraction [13], solid-phaseicroextraction [14] and single-drop microextraction [15]

ave been developed for the determination of BTEX and otherolatile compounds in different samples. On the other hand,

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0 F.A. Esteve-Turrillas et al. / Anal

t has been done a big effort to improve the BTEX extractiony using the accelerated solvent extraction (ASE) in order tochieve an efficient removal of analytes from different matrices16,17] prior to chromatographic analysis.

However, the use of chromatography means long time of anal-sis and, because of that, sample screening methodologies toetect BTEX residues like the combination of headspace andass spectrometry detection have been explored providing a

es/no response in order to reduce the amount of samples toe analyzed [18]. The, HS–MS technique has been successfullypplied in qualitative applications such as the detection of hydro-arbons in environmental matrices [19] and for classification ofhe geographical origin of olive oils [20].

Multivariate calibration is a very useful tool for extract-ng chemical information from instrumental signals. The mostommonly used multivariate methods for chemical analysis areartial least squares (PLS) regression and principal componentegression (PCR), where factors that relate to variation in theesponse measurements are regressed against the properties ofnterest.

= Tq × f

here T is a matrix of latent variables and q contains the regres-ion coefficients for the columns in T. The PLS factors (T) mustodel most of the variation, both in the X- and Y-variable and

lso attain fully adequate predictive ability. Ideally, each factordded to the model would describe variation relevant for predict-ng property values. To find the adequate number of PLS factorso retain in the calibration model there are different methods.ne of the most employed is that which minimizes the predicted

esidual error sum of squares (PRESS) of the model [21].In summary, the relationships between analytical signals and

ata to be determined are developed from the training set andhen applied to the set of unknowns. For unknown samples, theoncentrations of various constituents can often be predictedith a good accuracy.The aim of this study has been the development of a simple

nd quick method capable to identify and to quantify BTEXn soil samples using HS–MS combined with a partial leastquares (PLS) treatment of spectral data obtained, without anyhromatography separation.

. Experimental

.1. Chemicals and reagents

Toluene (99.8%, v/v), benzene (99.7%, v/v), hexane (96%,/v), iso-octane (99.8%, v/v) and petroleum ether (multisol-ent grade) were supplied by Scharlau (Barcelona, Spain) andhe isomers of xylene, ortho, meta and para (99.0%, v/v)nd ethylbenzene (99%, v/v) were provided by Fluka (Buchs,witzerland). 2,6,10,14-Tetramethylpentadecane (98%, v/v)sed to prepare the standard solutions an added to the samples to

ompensate the background was purchased from Sigma–AldrichMadrid, Spain). Methyl tert-buthyl ether (MTBE) (99%, v/v),sed in the evaluation of interferents, was provided by MerckDarmstadt, Germany).

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Chimica Acta 587 (2007) 89–96

Stock standard solutions employed to build the PLS calibra-ion models were prepared in 2,6,10,14-tetramethylpentadecanet a concentration of 5.0 mL L−1 and stored in amber glass-toppered bottles at 4 ◦C. Standard solutions containing BTEXt individual concentration of 5, 25 and 50 �L L−1 ofenzene, toluene and xylene were also prepared in 2,6,10,14-etramethylpentadecane by appropriate dilution of the stocknes. PLS calibration standards were prepared at three differentevels by adding 50 �L of the different dilutions, that corre-ponds to 0.25, 1.25 and 2.5 nL of benzene, toluene and o-xylene,nside glass headspace standard vials.

Spiked samples were prepared by adding 50 �L of each stan-ard solution at 12.5, 25 and 37.5 �L L−1 level, that correspondo 0.25, 0.625 and 1.875 nL of considered compounds, to 1 g ofoil.

Real soil samples were taken from the vicinity of petrol pumptations in the area of Valencia and were directly heated in HSlass vials after adding 150 �L of solvent.

. Apparatus

.1. The extraction–injection module

A static headspace autosampler Thermo Finnigan modelS 2000 (Waltham, MA, USA) equipped with standard glassials of an internal volume of 10 mL (23 mm × 46 mm) wasmployed. Once equilibrium was reached between the matrixnd the gaseous phase, 1 mL vapour sample was injected intohe system.

.2. The transfer line

The transfer line ensures coupling of the extraction–injectionodule to the mass spectrometer. This line must be designed toaintain a high-quality vacuum in the spectrometer source while

llowing rapid transfer of the extracted molecules between thewo modules. A Scharlab fused silica tube of 30 m length withn internal diameter of 0.32 mm was employed. The temperaturef this tube was held at 250 ◦C to prevent condensation of theonsidered compounds.

A Hewlett Packard HP5MS column (Palo Alto, CA, USA)30 m × 0.32 mm i.d., 0.25 �m film thickness) was used tobtain the reference data by chromatography.

.3. The mass spectrometer

A Thermo Finnigan Trace gas chromatograph, equippedith a Thermo Finnigan ion trap mass spectrometer detectorolaris Q was used. Ionization of the molecules introduced

nto the source of the mass detector was carried out by elec-ron ionization at 70 eV and an helium flow of 0.3 mL min−1

as used as damping gas. Data acquisition in full scan mode

as carried out over a mass range of m/z 75–110. The detec-

or temperature was fixed at 250 ◦C. Ion trap tests and massalibration were weekly performed with perfluorotributylaminePFTBA).

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F.A. Esteve-Turrillas et al. / Anal

.4. HS–GC–MS reference procedure

One gram of soil sample was accurately weighted inside10 mL standard glass vial and 150 �L of 2,6,10,14-

etramethylpentadecane were added. After that, the vial wasapped hermetically and heated in the headspace autosamplert 90 ◦C for 10 min with shaking. The syringe temperature waselected at 100 ◦C and 1 mL injection volume was introducednto the system in split mode (1:10), employing a constantow of 1 mL min−1 helium as carrier. The oven temperaturerogram started from 40 ◦C, held for 10 min, increased at aate of 20 ◦C min−1 up to 200 ◦C and finally held for 2 min.he transfer line and source temperature were fixed at 300 and50 ◦C, respectively.

.5. Headspace–mass spectrometry procedure (HS–MS)

Preparation of sample and headspace conditions were kept asor the reference procedure. In order to measure the patterns ofolatile compounds in soil samples without any chromatographyeparation (HS–MS methodology), the column was replaced bysilica tube transfer line and the oven temperature was pro-

rammed to keep a constant temperature of 250 ◦C.

.6. Chemometric analysis

For instrumental, measurement control and data acquisitiont was employed the Xcalibur from Thermo Finnigan (Waltham,

A, USA). Data were exported in excel format and the PLS cali-ration models were developed by means of TurboQuant Analyst.0 software developed by Thermo Nicolet Corp. (Madison, WI,SA).The proposed PLS model was built using 27 standards for

alibration (using a classical 33 design) and it was validatedy means of a set of 10 spiked samples with known amountsf BTEX. As it has been aforementioned, the calibration stan-ards correspond to different mixtures of benzene, toluene and-xylene at three different concentration levels (33). High levelas fixed at 2.5 nL, medium value was evaluated at 1.25 nL and

ow concentration level was fixed at 0.25 nL. Concentration ofhe aforementioned components in spiked samples was predictedmploying the PLS calibration using the information of the masspectra between m/z 75 and 110.

To build and select PLS models, the optimum number of fac-ors was chosen to minimize the PRESS, based on the criterionf Haaland and Thomas [22].

. Results and discussion

.1. MS spectra of BTEX compounds

One nanoliter benzene, toluene, ethylbenzene and eachylene isomer standards were measured by HS–GC–MS, inrder to obtain the retention time and mass spectra of each com-

ound. Mass spectra are shown in Fig. 1 in which it can be seenhe specific ions generated at m/z 77 and 78 for benzene, m/z 91nd 92 for toluene and finally m/z 91 and 106 for ethylbenzenend the three xylenes. Benzene and toluene can be determined

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Chimica Acta 587 (2007) 89–96 91

mploying their characteristic ions. However, ethylbenzene andylenes cannot be differentiated from each other because theyresent the same characteristic ions and only could be quantifiedfter an appropriate separation.

Additionally, in Fig. 1, it can be seen the mass spectra of,6,10,14-tetramethylpentadecane. The specific ions generatedy this molecule at m/z 83–85 and 97–99 do not overlap with theharacteristic ions of the analytes and, thus this compound coulde used as internal reference for the determination of BTEXompounds.

On the other hand, it is clear from Fig. 1 that ethylbenzene andylenes could be determined by MS without any interference ofenzene nor toluene.

.2. HS–GC–MS recording of a BTEX mixture

A conventional chromatographic separation of a mixture ofnL of each one of BTEX compounds, using an HP-5 (5%-henyl)-methylpolysiloxane column and full scan acquisitionode with selected ions at m/z 77, 78, 91, 92 and 106, is shown

n Fig. 2. As it can be seen in the figure, BTEX compoundsre well separated in a run time of 11 min, except meta- andara-xylene that coelute. Thus, five peaks were obtained at 2.4,.1, 7.8, 8.4 and 10.0 min, corresponding to benzene, toluene,thylbenzene, (m,p)-xylenes and o-xylene, respectively.

.3. HS–MS determination of benzene, toluene and-xylene

The main objective of this study was to establish a fast screen-ng procedure based on the decrease of the run time and thencrease of the sample throughput for BTEX determination inoils. So, the chromatography column was changed by a silicampty tube as transfer line, in order to obtain one unresolvedeak and to use the mass spectra of this peak for BTEX quan-ification.

In a first attempt, a silica tube of 5 m length and 0.32 mm.d. was assayed, but the vacuum of the mass spectrometer wasot acceptable, so a longer column of 30 m length and 0.32 mm.d. was used as transfer line and the vacuum problems werevoided.

Using the aforementioned interface, a standard mixture ofnL of benzene, toluene and o-xylene was measured by HS–MS

n full scan mode in a mass range of m/z 75–110. Fig. 3 shows thebtained MS time recording for selected ions of m/z 77, 78, 91,2 and 106. Inset of Fig. 3 shows the corresponding mass spec-rum of this wide peak from 1 to 4 min. Mass spectra obtained asescribed for mixtures of benzene, toluene and o-xylene weresed for multivariate calibration based on partial least squaresPLS) to predict the concentration of these compounds in soilamples.

.4. PLS models for HS–MS determination of benzene,oluene and o-xylene

A classical design of 33 standards for the three analytes con-idered (benzene, toluene and o-xylene), at three concentrationevels was used. Table 1 shows the analytical features of the

92 F.A. Esteve-Turrillas et al. / Analytica Chimica Acta 587 (2007) 89–96

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ig. 1. Mass spectra of benzene, toluene, ethylbenzene, xylene and 2,6,10,14-nL of each one.

LS model developed for the different compounds under study.t has been indicated the number of factors required for predic-ion of each analyte concentration with the minimum predictedesidual error sum of squares (PRESS), the coefficient of deter-

ination, R2 of the calibration model, the root mean square error

f calibration (RMSEC) and the mean absolute validation errors,stablished for ten spiked soil samples previously analyzed byhe reference procedure and not included in the calibration set.

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ethylpentadecane obtained in the full scan mode for an individual amount of

As it can be seen, in the best conditions, using all the infor-ation of the spectral range, without any baseline correction nor

pectra pre-treatment, RMSEC of 12.1, 24.2 and 34.6 and meanelative validation errors of 4.0, 5.4 and 5.9% were obtained for

enzene, toluene and xylene, respectively.

The principal component spectra (PCS) were obtained inrder to explain the contribution of factors on the analysis ofach volatile organic compound (see Fig. 4). On comparing

F.A. Esteve-Turrillas et al. / Analytica Chimica Acta 587 (2007) 89–96 93

Fig. 2. Typical HS–GC–MS chromatogram obtained for a BTEX mixture of 1 nL of each compound measured in full scan mode at m/z 77, 78, 91, 92 and 106selected ions.

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hese signals with spectra in Fig. 1 it can be seen that the mostiscriminant original variables correspond to the m/z ratios 85,7, 78, 91, 92 and 106, which are the major mass fragmentsor the 2,6,10,14-tetramethylpentadecane, used as internal ref-rence, and BTEX compounds, and that the signals are wellodelized with the PCS from 1 to 5 being all other variables

haracteristics of the background noise.On the other hand, the general occurrence of positive and

egative peaks in PLS PC plots is due to the sign of corre-ation between the component to be determined and the PLS

actor. The negative correlation between a PLS factor and annalyte will provide a negative peak at its specific m/z. The load-ngs cannot be interpreted as spectra. Due to the orthogonalityorces, some loadings could have negative values that cannot

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able 1tatistics for the PLS-MS calibration and prediction

egion Baseline Spectra pre-treatment Analyte F

09-76 None None Benzene 4Toluene 4Xylene 5

a The number of factors were chosen in order to obtain the minimum predicted resib R2 is the coefficient of determination of the regression line between predicted andc Root mean square calibration error for a cross-validation.d Mean accuracy error (%) found from the comparison of data obtained for the vali

f each compound. Inset: Mass spectrum obtained for the recording between 1

xist in spectra [21]. Fig. 5 shows the evolution of both, theercentage of explained variance and that of the percentage ofumulative variance for benzene determination as a function ofhe number of PCs, that four components are enough for a good

odelization.Calibration models obtained in different sessions provided

ifferent detector responses in the whole m/z range used and thus,n the following studies the calibration model was establishedrom measurements made in the same session than samples.

There are several circumstances that can introduce variations

n the new spectra that had not been included in the calibra-ion step. The presence of these unmodeled variations in theew data can lead to strongly biased predictions from multivari-te calibration models. The situation arises from changes in the

actorsa R2b RMSECc Mean accuracy errord (nL)

0.9994 12.1 0.040.998 24.2 0.050.996 34.6 0.06

dual error sum of squares.actual values of analyte concentration in the calibration set.

dation set of samples with results obtained by HS–GC–MS.

94 F.A. Esteve-Turrillas et al. / Analytica Chimica Acta 587 (2007) 89–96

Fig. 4. Principal component spectra diagnostic applied to verify the effect oftl(

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Table 2Effect of the use of o-xylene in the calibration set for PLS HS–MS determinationof ethylbenzene, different xylene isomers and a mixture of all of them in thepresence of benzene and toluene

Compound Amount added (nL) %Recovery

o-Xylene 1 101 ± 6m-Xylene 1 102 ± 9p-Xylene 1 101 ± 11Ethylbenzene 1 93 ± 8Mixa 1 99 ± 12

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mcompounds were measured in the presence of 1 nL of both, ben-zene and toluene. Table 2 shows the mean recovery data foundfor the considered compounds in the assayed solutions expressedas o-xylene. As it can be seen, the recovery of the different

he number of factors on the signals of benzene, toluene and o-xylene. Verticalines represent the characteristic m/z for each BTEX compound. Note: BenzeneB), toluene (T), ethylbenzene (E) and xylene (X).

nstrumental response function. These changes can occur whenhe data to be predicted are collected on an instrument differ-

nt from that used to build the model or simply in the samenstrument but in different measurement sessions. Although thepectra may have the same basic shape or profile, the measuredntensity values from two instruments will generally be differ-

ig. 5. Effect of the number of PCs used in the PLS model on the explainedariance and cumulative variance for benzene determination.

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esults are the average of three independent measurements ± the correspondingtandard deviation.a Mix: 0.25 nL of o-xylene, m-xylene, p-xylene and ethylbenzene.

nt, also, in the case of two different sessions, due to changes inhe environment of the instrument or in its response.

A solution to the calibration transfer problem is to applyhemometric techniques to correct for instrumental and envi-onmental differences, thereby making the model transferablend avoiding full recalibration. Various methods for calibrationransfer exist in the literature, and most have been discussed inecent reviews [23,24].

.5. Effect of the use of different xylene isomers in thealibration set

Ethylbenzene and the three xylene isomers present exactlyhe same mass spectra in the m/z range monitored (see Fig. 1).o, it seems impossible to do an individual determination ofll of them by HS–MS without any chromatography separation.ue to this, the effect of the use of o-xylene in the calibration

et to determine the aforementioned compounds as total xyleneas been evaluated.

One nanoliter of ethylbenzene and the different xylene iso-ers and a mixture of 0.25 nL of each one of the aforementioned

able 3ffect of increasing amounts from 0.25 to 25 nL of different interferents on the

ecovery of benzene, toluene and xylene at 1.25 nL level by PLS HS–MS

nterferent Compound %Recovery

etroleum ether Benzene 105 ± 19Toluene 104 ± 24Xylene 107 ± 18

-Hexane Benzene 91 ± 14Toluene 98 ± 19Xylene 106 ± 21

so-Octane Benzene 104 ± 16Toluene 105 ± 9Xylene 96 ± 14

TBEa Benzene 94 ± 13Toluene 94 ± 14Xylene 100 ± 9

a MTBE: methyl tert-buthyl ether.

F.A. Esteve-Turrillas et al. / Analytica Chimica Acta 587 (2007) 89–96 95

Table 4BTEX concentration in soil samples obtained by both, reference HS–GC–MS and HS–MS developed procedures

Sample Soil concentration (nL g−1 ± s, n = 3)

HS–GC–MS HS–MS

Benzene Toluene E. Benzene (m,p)-Xylene o-Xylene E. Benzene +∑

Xylenes Benzene Toluene E. Benzene +∑

Xylenes

1 0.20 ± 0.10 1.5 ± 0.2 1.10 ± 0.08 1.68 ± 0.11 1.31 ± 0.10 4.09 –a 1.5 ± 0.2 4.2 ± 0.32 –a 2.50 ± 0.15 0.91 ± 0.07 –a –a 0.91 –a 2.4 ± 0.3 1.4 ± 0.23 –a 3.1 ± 0.2 –a –a –a –a –a 3.0 ± 0.4 –a

4 –a 1.72 ± 0.11 –a –a –a –a –a 1.5 ± 0.3 –a

5 –a 3.3 ± 0.2 0.20 ± 0.01 0.50 ± 0.03 0.53 ± 0.02 1.23 –a 3.4 ± 0.2 1.4 ± 0.26 –a 0.86 ± 0.10 1.4 ± 0.2 2.1 ± 0.10 1.16 ± 0.12 4.66 –a 0.5 ± 0.2 4.8 ± 0.27 –a –a 0.71 ± 0.08 1.81 ± 0.10 0.62 ± 0.03 3.14 –a –a 2.90 ± 0.108 –a 4.2 ± 0.3 –a –a –a –a –a 4.8 ± 0.3 –a

9 –a –a –a 1.52 ± 0.09 2.2 ± 0.2 3.72 –a –a 3.4 ± 0.41 a a a a a a

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ylenes is around 100%. So, being acceptable, the use of o-ylene in the calibration set for the prediction of ethylbenzene,- and p-xylenes.

.6. Study of interferences

The main contamination sources of BTEX in soils includehe massive use of petroleum and its derivatives, and that ofolvents. So, it was evaluated the interference of hydrocarbonsike petroleum ether, n-hexane or iso-octane together with thatf methyl tert-buthyl ether, a common used additive of gasoline.

In order to assure the accuracy of the developed procedure,t was evaluated the interference of increasing amounts of theonsidered compounds from 0.25 to 25 nL for a fixed amount ofenzene, toluene and xylene of 1.25 nL of each one.

We can notice that whatever the interferent studied and theoncentration of that, the mean recovery values stay around00%, as it can be seen in Table 3. So, the presence of these com-ounds does not interfere on BTEX determination by HS–MS,or interferent/analyte ratios from 0.2 to 20.

.7. Real sample analysis

In a first attempt, 1 g of soil samples taken near petrol sta-ions in the area of Valencia were introduced inside headspaceials and measured by HS–MS, being the obtained results forenzene, toluene and xylene unacceptables.

The main difference between soil samples and standards washe presence of the solvent and, taking into consideration theffect of the solvent in the PLS model which is well explainedy the PC1 (see Fig. 4), it was decided to add 2,6,10,14-etramethylpentadecane to the solid samples.

A 150 �L of solvent added to the soil samples avoided theentioned problem and results found for the PLS HS–MS deter-

ination of toluene and ethylbenzene plus xylenes shown inable 4 indicate the excellent comparability with data found byS–GC–MS. Benzene was detected only in a single sample byC–MS at a level of 0.2 ± 0.1 nL g−1.

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The regression between concentrations found by the recom-ended procedure and those obtained by HS–GC–MS provide

quations CHS–MS = (−0.15 ± 0.15) + (1.08 ± 0.09)CHS–GC–MSith a coefficient of determination R2 = 0.98 (n = 10) andHS–MS = (0.06 ± 0.11) + (1.00 ± 0.03)CHS–GC–MS with a coef-cient of determination R2 = 0.991 (n = 10) for toluene andylenes, respectively. In those equations, the intercept and slopealues were statistically comparables to 0 and 1, respectively,or a probability level of 95% (being texp lower in all caseshan ttheoretical = 1.734 (n = 18)) thus indicating that the devel-ped procedure provides an accuracy comparable with that ofhe chromatography method.

The developed procedure allowed the individual identi-cation and quantification of benzene and toluene and theetermination of the sum of ethylbenzene and xylenes. As itan be seen, benzene was undetected in actual samples, proba-ly as a result of the easy evaporation of this compound, as wells its low concentration in petroleum derivatives (less than 5%,/v). Toluene and xylenes were found in the major part of soilamples analyzed, at concentrations higher than those of othernalytes. These results are consistent with the high concentrationf these compounds in petroleum derivatives (mainly gasoline).

. Conclusions

The present work describes the development of an HS–MSethod for the determination of aromatic hydrocarbons (BTEX)

n soil matrices by using a PLS multivariate calibration approach.onsidering the results, the HS–MS methodology could bepplied for the differentiation and classification of samples, andlso for the quantitative determination of BTEX in soil samples.n fact, benzene, toluene and the mixture of ethylbenzene andylenes could be determined with an excellent accuracy. The dis-dvantage of the need of a multivariate calibration technique forata treatment is compensated by the time saving (no chromatog-

aphy separation step is required). Results are comparables withhose obtained by HS–GC–MS and the sampling throughput isonsiderably improved, from 5 samples per hour by HS–GC–MSo 12 samples per hour by the developed procedure.

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cknowledgements

The authors acknowledge the financial support of the Ministe-io de Educacion y Ciencia (Project CTQ2005-05604, FEDER)nd Direccio General d’Investigacio i Transferencia Tecnologicae la Generalitat Valenciana (Project 017609). F.A. Esteve-urrillas and S. Armenta also acknowledge the V seglesUniversitat de Valencia) and FPU grant (Ministerio de Edu-acion y Ciencia (Ref. AP2002-1874)), respectively.

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[2] C.Y. Chan, L.Y. Chan, X.M. Wang, Y.M. Liu, S.C. Lee, S.C. Zou, G.Y.Sheng, J.M. Fu, Atmos. Environ. 36 (2002) 2039–2047.

[3] K. Na, Y.P. Kim, Atmos. Environ. 35 (2001) 2603–2614.[4] Amendments to 1990 Clean Air Act—List of 189 Hazardous Air Pollutants,

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