Calibration of mass selective detector in non-target analysis of volatile organic compounds in the air

Arh, Gregor; Klasinc̆, L.; Veber, Marjan; Pompe, Matevž

doi:10.1016/j.chroma.2011.01.037

Cited by 11 publications

(5 citation statements)

References 31 publications

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“…In 2011, Arh et al. reported a seven‐parameter quantitative structure–property relationship model to predict experimental RF (to within 20% for most compounds) using selected molecular descriptors for Cryofocuser/GC with ion trap MS applications using a gas working standard (G‐WS).…”

Section: Introductionmentioning

confidence: 99%

Method to predict gas chromatographic response factors for the trace‐level analysis of volatile organic compounds based on the effective carbon number concept

Szulejko

Kim

2013

J of Separation Science

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A procedure has been developed to estimate GC-MS response factors based on the theory of effective carbon number defined as the sum of the carbon number and carbon number equivalent for each selected molecular descriptor (multiplied by its number of occurrences) in each compound's molecular structure. As a means to validate the effective carbon number procedure for GC-MS analysis, a test suite of 19 volatile organic compounds was analyzed by the sorbent-tube thermal desorption method. In the effective carbon number procedure, the carbon number equivalent for each descriptor was determined to yield the optimal linear plots between response factor versus the effective carbon number with the maximum R(2) (>0.975) and the minimum mean absolute error (<5%). Effective carbon number analysis is validated as a potent approach to estimate response factor values for most compounds amenable to the sorbent-tube thermal desorption GC-MS method. Overall, it is concluded that the application of response factor versus effective carbon number relationship can produce fairly reliable prediction with reduced errors relative to other comparable procedures such as the response factor versus the carbon number approach.

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Section: Introductionmentioning

confidence: 99%

Method to predict gas chromatographic response factors for the trace‐level analysis of volatile organic compounds based on the effective carbon number concept

Szulejko

Kim

2013

J of Separation Science

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“…In the case of MS detectors, the theoretical calculation of the RRF values requires a valid hypothesis of the percentage of molecules of each compound that are actually ionized, considering that each ionized fragment that reaches the MS detector's plate yields signals with different intensities that are in turn integrated to form the peak area representing the amount of each analyte. Recently, the software CODESSA was presented with the potential of calculating RRF values of various compounds, nonetheless the experimental calculation of RRFs for MS detectors remains more reliable. In a recently published work, Djokic et al describe the quantification of crude bio‐oil by GC × GC–FID using both standard compounds and theoretical calculation of ECN in order to determine the RRF values for a variety of compounds verifying that the ECN method is reliable for the FID.…”

Section: Comprehensive and Hyphenated Chromatographic Techniquesmentioning

confidence: 99%

Section: Two-dimensional Gas Chromatography (Gc × Gc or 2dgc)mentioning

confidence: 99%

Advanced analytical techniques for bio‐oil characterization

Michailof

Kalogiannis

Sfetsas

et al. 2016

WIREs Energy & Environment

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Bio-oil (pyrolysis oil) is the liquid product of biomass thermochemical conversion. It is a dark, viscous liquid that contains the depolymerization products of hemicellulose, cellulose, and lignin. The physicochemical properties of bio-oils are determined by employing the conventional methods for fuels analysis with proper adaptations. However, the detailed composition of bio-oils in terms of analytes as well as their concentration remains ambiguous and is a challenging task for analytical chemistry. The compounds in the bio-oil range from nonpolar (e.g., hydrocarbons) to highly polar (e.g., phenolics) and from volatile (e.g., organic acids) to nonvolatile (e.g., sugar derivatives), covering a molecular weight (MW) range of about 50-2000 Da. Hence a combination of analytical techniques such as high pressure liquid chromatography, gas chromatography (GC), gel permeation chromatography (GPC), nuclear magnetic resonance spectroscopy (NMR), and Fourier transform infrared spectroscopy (FTIR) are required to determine the bio-oil's composition. Despite the significant breakthroughs of these techniques, they face limitations regarding the sample pretreatment, the incomplete separation and determination of components, and the need of multiple analyses with each method for more complete results. The development of sophisticated, comprehensive, and hyphenated chromatographic and spectrometric techniques such as GC × GC, LC × LC, high-resolution mass spectrometry (HRMS), and 2D-NMR has brought actual advancement in the field of bio-oil analysis. GC × GC and LC × LC have allowed the development of qualitative and quantitative methods for the individual determination of lower MW compounds. However, HRMS and 2D-NMR have facilitated the elucidation of the structure of the higher MW components, offering insight in the effect of pyrolysis conditions on biomass depolymerization and the possibilities for further upgrading of bio-oils.

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“…The greatest challenge in humans and/or the environment assessing risk is to sample as many airborne pollutants as possible that may pose a risk. Several analytical methods for the determination of VOCs in the air exist, which differ mainly by the sampling procedures [ 15 ]. The sampling procedures consist of passive or diffusive sampling, active sampling, the use of canisters and bags, and online sampling [ 16 ].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Coriolis Micro Air Sampling to Detect Volatile and Semi-Volatile Organic Compounds

Courtier

Roig

Cariou³

et al. 2022

Molecules

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There are several analytical procedures available for the monitoring of volatile organic compounds (VOCs) in the air, which differ mainly on sampling procedures. The Coriolis micro air sampler is a tool normally designed for biological air sampling. In this paper, the Coriolis micro bio collector is used to evaluate its ability to sample organic contaminants sampling and detecting them when combined GC-MS. We also compare the use of the Coriolis micro with a standardized sampling method, which is the use of a lung box with a Nalophan® bag. The results show that the Coriolis micro sampling method is suitable for the sampling of organic contaminants. Indeed, the Coriolis micro allows to sample and detect mainly semi-volatile molecules, while the lung box/Nalophan® bags allow to sample more volatile molecules (highly volatile and volatile). These results were confirmed in the controlled air lab with a slight difference with the field. The simultaneous use of the both techniques allow to sample and detect a larger number of molecules with specific physicochemical properties to each sampling technique. In conclusion, the Coriolis micro can sample and detect volatile organic compounds present in air. We have shown that the development of alternative sampling methods and the use of non-target analysis are essential for a more comprehensive risk assessment. Moreover, the use of the Coriolis micro allows the detection of emergent molecules around the Thau lagoon.

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Calibration of mass selective detector in non-target analysis of volatile organic compounds in the air

Cited by 11 publications

References 31 publications

Method to predict gas chromatographic response factors for the trace‐level analysis of volatile organic compounds based on the effective carbon number concept

Method to predict gas chromatographic response factors for the trace‐level analysis of volatile organic compounds based on the effective carbon number concept

Advanced analytical techniques for bio‐oil characterization

Evaluation of Coriolis Micro Air Sampling to Detect Volatile and Semi-Volatile Organic Compounds

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