Headspace Generation Research Articles

Multiple headspace sampling coupled to a programmed temperature vaporizer – Gas chromatograph-mass spectrometer for the determination of polycyclic aromatic hydrocarbons in water and saliva

Here we describe the development of a multiple headspace sampling methodology coupled to a programmed temperature vaporizer and a gas chromatograph-mass spectrometer (MHS-PTV-GC-MS) for the determination of 13 polycyclic aromatic hydrocarbons (PAHs) which are considered widespread environmental pollutants. Coupling with the PTV in solvent vent mode made it possible to enrich the analytes present in the headspace through multiple extractions and transfers to the injector previous to the chromatographic run. All parameters affecting the headspace generation, extraction, and stepwise transfer to the PTV were optimised. The method was successfully validated using UHQ-water, for thirteen PAHs, with limits of detection (LODs) in the range of 1.0–11 ng L−1. The method was also validated in saliva, with LODs in the range of 1.4–43 ng L−1. Intra- and inter-day repeatability values expressed as relative standard deviation percentage (RSD) were found to be lower or equal to 8.3% and 12.6%, respectively, in water, and 15.2% and 10.0% in saliva. Furthermore, all calibrations presented good linear behaviour (R2 values >0.98) and fitted to the model according to ANOVA model validation. This method was applied to the quantification of PAHs in 14 saliva samples from 11 subjects, both non-smokers and smokers. PAHs were not detected in saliva from non-smokers and light-smokers above the LODs. However, these compounds could be found in saliva samples from heavy smokers taken right after smoking. A study of the same subjects in saliva samples provided one hour later was also conducted to evaluate the concentration change in time.

Development of a methodology based on headspace-gas chromatography-ion mobility spectrometry for the rapid detection and determination of patin fish oil adulterated with palm oil

The present research intends to develop a new method based on headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) for the detection and determination of patin fish oil adulterated with different percentages of palm oil, because it is a cheaper vegetable oil. Five variables that affect headspace generation (incubation time and temperature, amount of sample, injection volume, and pre-heating time) have been optimized by means of a Box Behnken design in combination with Response Surface Methodology. Then, repeatability and intermediate precision have been studied where coefficients of variation lower than 10% were obtained. This new method has been applied to several samples of patin fish oil adulterated with palm oil at 20 different levels (5–50% palm oil content). The results have confirmed the suitability of the HS-GC-IMS for a rapid, easy, and reliable detection and discrimination of adulterated oil samples since a characteristic fingerprint that allows 100% successful discrimination between adulterated and unadulterated patin oil samples was achieved. Finally, a regression model has been developed to determine each sample’s adulteration level with an error lower than 10% and a coefficient of determination greater than 0.95.

Multiple headspace sampling coupled to a programmed temperature vaporizer to improve sensitivity in headspace-gas chromatography. Determination of aldehydes

The improvement of sensitivity in headspace (HS) sampling of not very volatile analytes constitutes a challenge that has usually been approached through coupling with additional techniques. Here we propose a new methodology for increasing sensitivity through a multistep approach. This proof of concept is based on direct coupling of a headspace sampler with a programmed temperature vaporizer (PTV) and a gas chromatograph (GC), with mass spectrometry (MS) detection. Analytes are extracted from the same vial in a stepwise procedure, splitting the headspace generation time of conventional HS into four periods and using the PTV to cryogenically trap the analytes during the successive HS samplings. Solvent vent mode is mandatory in order to retain the analytes, purging the gas solvent at an adequate initial low temperature and flash-heating the PTV liner in a quick ramp (720 °C/min), once the HS samplings are finished. Linear aldehydes, from pentanal to decanal, possible biomarkers of several diseases have been selected as model compounds. This multiple HS method has been compared with conventional HS, and it has been validated in terms of linearity, limits of detection, repeatability, reproducibility and accuracy. The limits of detection (LOD) ranged from 0.004 to 0.159 µg/L. Enrichment factors (EF) in relation to the conventional HS method ranged from 3.0 to 6.7, except for pentanal (EF: 0.8), which is too volatile and polar to be trapped in the PTV with the multiple HS methodology. Similar enrichment factors were obtained in a urine sample.

Gas chromatography-ion mobility spectrometric classification of vegetable oils based on digital image processing

In this paper, a headspace instrument equipped with gas chromatography-ion mobility spectrometry (GC-IMS) was used to classify three kinds of vegetable oils in cooperation with chemometric tools. The procedure contained direct loading of the vegetable oil sample into a vial, headspace generation, and automatic injection of volatile organic components into GC-IMS device. A total of 187 oil samples were detected by GC-IMS, and Otsu’s threshold segmentation and colorized difference methods were adopted to realize automatic peak detection of two-dimensional matrix and comparative visualization for further chemometric pretreatment. Based on the obtained data, principal components analysis showed that 95.77% of sample information could be explained by the first two principal components. Moreover, the oil samples were divided into calibration set (n = 130) and prediction set (n = 57), and the model built by the k-nearest neighbors algorithm showed that the recognition accuracy of calibration set was 100% and the recognition accuracy of prediction set was 98.24%. These results verify that digital image processing methods applied to GC-IMS datasets could preserve chemical information and support qualitative analysis. Thus, GC-IMS technique can be considered a vanguard and reliable tool for recognition of different types of common vegetable oils.

Odour Detection Method of Silk Products Based on Electronic Nose Technology

Silk is a natural animal protein with special odour. Polyester yarns, similar in appearance to silk, are often used in silk production. Electronic nose (e-nose) technology can distinguish different gases by different pattern recognition methods. In this paper, e-nose technology was applied to obtain data sets of silk/polyester yarns with different mixing ratios, and cluster analysis was carried out for silk samples. The experimental results show that the results of e-nose response are related to the headspace, sample quality, and headspace generation time etc.; as the response time increases, the relative standard deviation of each sensor turns to be smaller, and the response value is more stable. There are significant differences in the fluctuations between the ten metal sensors, and different samples have significant effects on the response of sensors No. 2, 7, and. 9. The e-nose sensor has a higher prediction accuracy when identifying different ratios of silk/polyester yarns at the accuracy rate up to 90.286%.

Characterization and Differentiation of Petroleum-Derived Products by E-Nose Fingerprints.

Characterization of petroleum-derived products is an area of continuing importance in environmental science, mainly related to fuel spills. In this study, a non-separative analytical method based on E-Nose (Electronic Nose) is presented as a rapid alternative for the characterization of several different petroleum-derived products including gasoline, diesel, aromatic solvents, and ethanol samples, which were poured onto different surfaces (wood, cork, and cotton). The working conditions about the headspace generation were 145 °C and 10 min. Mass spectroscopic data (45–200 m/z) combined with chemometric tools such as hierarchical cluster analysis (HCA), later principal component analysis (PCA), and finally linear discriminant analysis (LDA) allowed for a full discrimination of the samples. A characteristic fingerprint for each product can be used for discrimination or identification. The E-Nose can be considered as a green technique, and it is rapid and easy to use in routine analysis, thus providing a good alternative to currently used methods.

Urinary volatile fingerprint based on mass spectrometry for the discrimination of patients with lung cancer and controls

Profile signals of urine samples corresponding to patients with lung cancer and controls were obtained using a non-separative methodology. The method is based on the coupling of a headspace sampler, a programed temperature vaporizer and a mass spectrometer (HS-PTV-MS). With only a centrifugation step as prior sample treatment, the samples were subjected to the headspace generation process and the volatiles generated were introduced into the PTV where they were trapped in the Tenax® packed liner while the solvent was purged. Finally, the analytes were introduced directly, without separation, into the mass spectrometer which allows obtaining the fingerprint of the analyzed sample. The mass spectrum corresponding to the mass/charge ratios (m/z) ranging between 35 and 120amu (amu) contains the information related to the composition of the headspace and is used as the analytical signal for the characterization of the samples.Samples of 14 patients with some type of cancer and 24 healthy volunteers were analyzed and the profile signals were subjected to different chemometric techniques, including support vector machines (SVM), linear discriminant analysis (LDA) and partial least squares- discriminant analysis (PLS-DA), with the aim of differentiating the samples of patients with cancer from those of control. Values of 100% were obtained both in sensitivity and specificity in most cases.This methodology has been used previously, as described later, for the analysis of the fingerprint corresponding to saliva samples of patients and controls. However, up to date, the method has not been used in urine samples with the aim of fast discrimination between patients with cancer and controls. The advantages and disadvantages of using urine versus other types of matrices such as saliva are stated.In view of the results obtained in this work, the use of pattern recognition techniques with data corresponding to HS-PTV-MS profile signals is highly suitable as a first screening step to differentiate samples. In addition, it could be applied to a high number of samples in a relatively short period of time due to its high throughput.

Volatile Metabolites of Goat Cheeses Determined by Ion Mobility Spectrometry. Potential Applications in Quality Control

Headspace sampling coupled with multi-capillary column-ion mobility spectrometry (HS-MCC-IMS) has been used for extraction and identification of some volatile metabolites from different types of goat cheese samples. The only manual operation carried out in this method was the introduction of samples into vials; the following steps (headspace generation, injection of the volatiles compounds into MCC and IMS detection) were fully automated. The analysis by MCC-IMS allowed rapid and simple differentiation of goat cheeses made with raw and pasteurized milk. MCC-IMS produced multidimensional ion mobility spectra with different retention times and intensity information different for some individual metabolites. A total of six metabolites were identified in goat cheeses including 1 alcohol (1-hexanol), 1 ketone (2-nonanone), 2 aldehydes (octanal, trans-2-heptanal) and 2 esters (ethyl butanoate and propyl butanoate). Furthermore, the evolution of one targeted metabolite (ethyl butanoate) was monitored through different ripening times (60, 150, 180, 210, 240, 270 days). These preliminary results showed that this volatile compound increased during cheese ageing according to biochemical and microbial dynamic of the matrix, and therefore ethyl butanoate could be a potential marker of ripening time in these kinds of cheese samples. Therefore, the method could be used for quality control purposes in goat cheese producers.

Headspace generation coupled to gas chromatography–mass spectrometry for the automated determination and quantification of endogenous compounds in urine. Aldehydes as possible markers of oxidative stress

A methodology for the determination of five aldehydes in urine has been developed based on the coupling of a headspace generation sampler with a gas chromatography–mass spectrometry system equipped with a programmed temperature vaporizer. This instrumental configuration minimizes sample manipulation and allows the determination of these compounds without the need for a derivatization step so that the methodology is largely shortened and simplified. An experimental design was carried out in order to optimize the headspace sampling. Sample matrix effect was eliminated by means of dilution of urine samples. The calibration models displayed good linearity (0.1–10μg/L) and their validity was checked using ANOVA, and it was observed that they did not exhibit any lack of fit. The LODs obtained ranged between 0.04 and 0.08μg/L and the LOQs between 0.12 and 0.24μg/L. The accuracy of the method was evaluated in terms of apparent recoveries which were between 86 and 120%. The method developed was applied to the analysis of 17 samples of urine from different subjects in order to quantify these endogenous compounds.

Dynamic headspace generation and quantitation of triacetone triperoxide vapor

Two methods for quantitation of triacetone triperoxide (TATP) vapor using a programmable temperature vaporization (PTV) inlet coupled to a gas chromatography/mass spectrometer (GC/MS) have been demonstrated. The dynamic headspace of bulk TATP was mixed with clean humid air to produce a TATP vapor stream. Sampling via a heated transfer line to a PTV inlet with a Tenax-TA™ filled liner allowed for direct injection of the vapor stream to a GC/MS for vapor quantitation. TATP was extracted from the vapor stream and subsequently desorbed from the PTV liner for splitless injection on the GC column. Calibration curves were prepared using solution standards with a standard split/splitless GC inlet for quantitation of the TATP vapor. Alternatively, vapor was sampled onto a Tenax-TA™ sample tube and placed into a thermal desorption system. In this instance, vapor was desorbed from the tube and subsequently trapped on a liquid nitrogen cooled PTV inlet. Calibration curves for this method were prepared from direct liquid injection of standards onto samples tube with the caveat that a vacuum is applied to the tube during deposition to ensure that the volatile TATP penetrates into the tube. Vapor concentration measurements, as determined by either GC/MS analysis or mass gravimetry of the bulk TATP, were statistically indistinguishable. Different approaches to broaden the TATP vapor dynamic range, including diluent air flow, sample chamber temperature, sample vial orifice size, and sample size are discussed. Vapor concentrations between 50 and 5400ngL−1 are reported, with stable vapor generation observed for as long as 60 consecutive hours.

Static headspace gas chromatography–mass spectrometry for the one-step derivatisation and extraction of eleven aldehydes in drinking water

Low-molecular-mass aldehydes (LMMAs) are water disinfection by-products formed by the reaction of ozone and/or chlorine with natural organic matter in water. LMMAs are mutagenic and carcinogenic compounds, which are detected at ng/L levels in water. An analytical method that allows simultaneous derivatisation and extraction of LMMAs in water has been developed using the classical static headspace technique coupled with gas chromatography–mass spectrometry (HS–GC–MS). Important parameters controlling the derivatisation of LMMAs with o-2,3,4,5,6-pentafluorobenzylhydroxylamine, oxime-products extraction and headspace generation were optimised to obtain the highest sensitivity, completing the entire process in 20min. For the first time the derivatisation reaction was carried out at alkaline pH adjusted with sodium hydrogen carbonate which exerts a significant enhancement effect on the derivatisation efficiency of the aldehydes; up to 20-fold with respect to those obtained in weak acid media as recommended by EPA Method 556.1. The addition of 200μL of n-hexane, as a chemical modifier, favoured the volatilisation of oxime-products, increasing the sensitivity of the method. The proposed method allows the achieving of detection limits from 2 to 80ng/L and has excellent precision (RSD average value of 6.4%) and accuracy (recovery ranging from 97% to 99%) for LMMA quantifications in drinking water samples. Finally, the HS–GC–MS method was validated relative to EPA Method 556.1 for the analysis of drinking water samples subjected to several disinfection treatments.

Fast Analytical Methodology Based on Mass Spectrometry for the Determination of Volatile Biomarkers in Saliva

We report a methodology for the rapid determination of biomarkers in saliva. The method is based on direct coupling of a headspace sampler with a mass spectrometer. The saliva samples are subjected to the headspace generation process, and the volatiles generated are introduced directly into the mass spectrometer, thereby obtaining a fingerprint of the sample analyzed. The main advantage of the proposed methodology is that no prior chromatographic separation and no sample manipulation is required. The following model compounds were studied to check the possibilities of the methodology: methyl tert-butyl ether and styrene as biomarkers of exposure and dimethyl disulfide, limonene, and 2-ethyl-1-hexanol as biomarkers of diseases. The method was applied to the determination of biomarkers in 28 saliva samples: 24 of them were from healthy volunteers, and the others were from patients with different types of illness (including different types of cancer). Additionally, a separative analysis by GC/MS was performed for confirmatory purposes, and both methods provided similar results.

Multi-capillary column-ion mobility spectrometry: a potential screening system to differentiate virgin olive oils

The potential of a headspace device coupled to multi-capillary column-ion mobility spectrometry has been studied as a screening system to differentiate virgin olive oils ("lampante," "virgin," and "extra virgin" olive oil). The last two types are virgin olive oil samples of very similar characteristics, which were very difficult to distinguish with the existing analytical method. The procedure involves the direct introduction of the virgin olive oil sample into a vial, headspace generation, and automatic injection of the volatiles into a gas chromatograph-ion mobility spectrometer. The data obtained after the analysis by duplicate of 98 samples of three different categories of virgin olive oils, were preprocessed and submitted to a detailed chemometric treatment to classify the virgin olive oil samples according to their sensory quality. The same virgin olive oil samples were also analyzed by an expert's panel to establish their category and use these data as reference values to check the potential of this new screening system. This comparison confirms the potential of the results presented here. The model was able to classify 97% of virgin olive oil samples in their corresponding group. Finally, the chemometric method was validated obtaining a percentage of prediction of 87%. These results provide promising perspectives for the use of ion mobility spectrometry to differentiate virgin olive oil samples according to their quality instead of using the classical analytical procedure.

Headspace sampling with in situ carbodiimide-mediated derivatization for the determination of ibuprofen in water samples

A method using headspace generation and in situ derivatization with water soluble EDC (1-[3-(dimethylamino)propyl]-3-ethylcarbodiimide) and TFEA (2,2,2-trifluoroethylamine) has been optimized for the determination of ibuprofen (2-(p-isobutylphenyl)propionic acid), one of the most common non-steroid anti-inflammatory drug (NSAIDs) residues in surface and wastewater samples. Derivatization was carried out in the vial of the headspace sampler (HS) in only 15 min, after which instrumental measurements were made with gas chromatography–mass spectrometry (GC–MS). As the injection system, a programmed temperature vaporizer (PTV) in the solvent-vent injection mode is proposed in order to increase the sensitivity of the measurements. The effects of the variables affecting HS generation, the derivatization reaction, and the instrumental PTV conditions were studied. A limit of quantification as low as 32 ng/L was achieved, and repeatability values were below 10%. Accuracy of the method was evaluated using spiked ultrapure water at three concentration levels, obtaining apparent recoveries between 96% and 104%. The proposed method was applied to the quantification of ibuprofen in sea water and urban wastewater samples.

Determination of filbertone in spiked olive oil samples using headspace-programmed temperature vaporization-gas chromatography–mass spectrometry

A sensitive method for the fast analysis of filbertone in spiked olive oil samples is presented. The applicability of a headspace (HS) autosampler in combination with a gas chromatograph (GC) equipped with a programmable temperature vaporizer (PTV) and a mass spectrometric (MS) detector is explored. A modular accelerated column heater (MACH) was used to control the temperature of the capillary gas chromatography column. This module can be heated and cooled very rapidly, shortening total analysis cycle times to a considerable extent. The proposed method does not require any previous analyte extraction, filtration and preconcentration step, as in most methods described to date. Sample preparation is reduced to placing the olive oil sample in the vial. This reduces the analysis time and the experimental errors associated with this step of the analytical process. By using headspace generation, the volatiles of the sample are analysed without interference by the non-volatile matrix, and by using injection in solvent-vent mode at the PTV inlet, most of the compounds that are more volatile than filbertone are purged and the matrix effect is minimised. Use of a liner packed with Tenax-TA allowed the compound of interest to be retained during the venting process. The limits of detection and quantification were as low as 0.27 and 0.83 microg/L, respectively, and precision (measured as the relative standard deviation) was 5.7%. The method was applied to the determination of filbertone in spiked olive oil samples and the results revealed the good accuracy obtained with the method.

Simultaneous liquid–liquid microextraction/methylation for the determination of haloacetic acids in drinking waters by headspace gas chromatography

A novel analytical method that combines simultaneous liquid–liquid microextraction/methylation and headspace gas chromatography–mass spectrometry for the determination of nine haloacetic acids (HAAs) in water was reported. A mechanistic model on the basis of mass transfer with chemical reaction in which methylation of HAAs was accomplished in n-pentane–water (150μl–10ml) two-phase system with a tetrabutylammonium salt as phase transfer catalyst was proposed. Derivatisation with dimethylsulphate was completed in 3min by shaking at room temperature. The methyl ester derivatives and the organic phase were completely volatilised by static headspace technique, being the gaseous phase analysed. Parameters related to the extraction/methylation and headspace generation of HAAs were studied and the results were compared with methyl haloacetate standards to establish the yield of each step. The thermal instability of HAAs, by degradation to their respective halogenated hydrocarbon by decarboxylation, and the possible hydrolysation of the methyl esters were rigorously controlled in the whole process to obtain a reliable and robust method. The proposed method yielded detection limits very low which ranges from 0.02 to 0.4μgl−1 and a relative standard deviation of ca. 7.5%. Finally, the method was validated with the US Environmental Protection Agency (EPA) method 552.2 for the analysis of HAAs in drinking and swimming pool water samples containing concentrations of HAAs that must be higher than 10μgl−1 due to the fact that this method is less sensitive than the proposed one.

Headspace–programmed temperature vaporizer–fast gas chromatography–mass spectrometry coupling for the determination of trihalomethanes in water

A new method based on the use of a headspace autosampler in combination with a GC equipped with a programmable temperature vaporizer (PTV) and an MS detector has been developed for the screening and quantitative determination of trihalomethanes (THMs) in different aqueous matrices. The use of headspace generation to introduce the sample has the advantage that no prior sample treatment is required, thus minimizing the creation of analytical artifacts and the errors associated with this step of the analytical process. The PTV inlet used was packed with Tenax-TA. The injection mode was solvent vent, in which the analytes are retained in the hydrophobic insert packing by cold trapping, while the water vapour is eliminated through the split line. This allows rapid injection of the sample in splitless mode, very low detection limits being achieved without the critical problem of initial sample bandwidth. The capillary column used allowed rapid separations with half-height widths ranging from 1.68 s (chloroform) to 0.66 s (bromoform). The GC run time was 7.3 min. The use of mass spectrometry allows the identification and quantification of the analytes at the low ppt level. The S/N ratio was at least 10-fold higher when the SIM mode was used in data acquisition as compared to the scan mode. The proposed method is extremely sensitive, with detection limits ranging from 0.4 to 2.6 ppt.

Headspace mass spectrometry methodology: application to oil spill identification in soils

In the present work we report the results obtained with a methodology based on direct coupling of a headspace generator to a mass spectrometer for the identification of different types of petroleum crudes in polluted soils. With no prior treatment, the samples are subjected to the headspace generation process and the volatiles generated are introduced directly into the mass spectrometer, thereby obtaining a fingerprint of volatiles in the sample analysed. The mass spectrum corresponding to the mass/charge ratios (m/z) contains the information related to the composition of the headspace and is used as the analytical signal for the characterization of the samples. The signals obtained for the different samples were treated by chemometric techniques to obtain the desired information. The main advantage of the proposed methodology is that no prior chromatographic separation and no sample manipulation are required. The method is rapid, simple and, in view of the results, highly promising for the implementation of a new approach for oil spill identification in soils.

Discrimination of Storage Age for Wheat by E-Nose

An investigation was conducted to evaluate the capacity of an electronic nose (E-nose) to classify wheat based on storage age. The effects of vial volume, headspace generation time, and wheat sample mass were studied, and the optimum experimental procedure was determined using multifactor analysis of variance. The results showed that the headspace generation time and the mass of the wheat sample had an obvious effect on E-nose response; however, the volume of the vial had no significant effect on E-nose response. The optimum parameters are 500 mL vial volume, 1.5 h headspace generation time, and 50 g sample mass. The five wheat groups were discriminated completely by principal component analysis (PCA). However, samples from 2006 and 2005 were overlapped by linear discriminant analysis (LDA). The method of artificial neural network (ANN) was performed, and 85% of the testing set was classified correctly using a back-propagation neural network.

Classification of extra virgin olive oils according to the protected designation of origin, olive variety and geographical origin

A headspace-mass spectrometry (HS-MS) coupling designed for the sensory characterization and classification of extra virgin olive oil on the basis of its protected designation of origin, olive variety and geographical origin is reported. The procedure involves the headspace generation and the direct injection of the homogenized gaseous phase into a mass spectrometer through a transfer line. The results obtained were chemometrically treated to achieve the best model capable of discriminating between the different olive oil categories. For this purpose, several procedures for variables selection, data pretreatments and unsupervised techniques were evaluated. In addition, K-nearest neighbor and soft independent modeling of class analogy algorithms were employed to the classification models building. Taking into account the prediction results obtained (ca. 87% of samples correctly classified and a specificity of ca. 97%), it can be concluded than the HS-MS coupling is, with an adequate chemometric treatment, an appropriate technique for routine control.