Advances in pretreatment and analysis methods of aromatic hydrocarbons in soil

Benzene compounds that are prevalent in the soil as organic pollutants mainly include BTEX (benzene, toluene, ethylbenzene, and three xylene isomers) and PAHs (polycyclic aromatic hydrocarbons). These pose a severe threat to many aspects of human health. Therefore, the accurate measurement of BTEX and PAHs concentrations in the soil is of great importance. The samples for analysis of BTEX and PAHs need to be suitable for the various detection methods after pretreatment, which include Soxhlet extraction, ultrasonic extraction, solid-phase microextraction, supercritical extraction, and needle trap. The detection techniques mainly consist of gas chromatography (GC), mass spectrometry (MS), and online sensors, and provide comprehensive information on contaminants in the soil. Their performance is evaluated in terms of sensitivity, selectivity, and recovery. Recently, there has been rapid progress in the pretreatment and analysis methods for the quantitative and qualitative analyses of BTEX and PAHs. Therefore, it is necessary to produce a timely and in-depth review of the emerging pretreatment and analysis methods, which is unfortunately absent from the recent literature. In this work, state-of-art extraction techniques and analytical methods have been summarized for the determination of BTEX and PAHs in soil, with a particular focus on the potential and limitations of the respective methods for different aromatic hydrocarbons. Accordingly, the paper will describe the basic methodological knowledge, as well as the recent advancement of pretreatment and analysis methods for samples containing BTEX and PAHs.

The New Approach to a Pattern Recognition of Volatile Compounds: The Inflammation Markers in Nasal Mucus Swabs from Calves Using the Gas Sensor Array

This paper discusses the application of two approaches (direct and inverse) to the identification of volatile substances by means of a gas sensor array in a headspace over nasal mucus swab samples taken from calves with differing degrees of respiratory damage. We propose a unique method to visualize sensor array data for quality analysis, based on the spectra of cross mass sensitivity parameters. The traditional method, which requires an initial sensor array trained on the vapors of the individual substances (database accumulation)—with their further identification in the analyzed bio-samples through the comparison of the analysis results to the database—has shown unsatisfactory performance. The proposed inverse approach is more informative for the pattern recognition of volatile substances in the headspace of mucus samples. The projection of the calculated parameters of the sensor array for individual substances in the principal component space, acquired while processing the sensor array output from nasal swab samples, has allowed us to divide animals into groups according to the clinical diagnosis of their lung condition (healthy respiratory system, bronchitis, or bronchopneumonia). The substances detected in the gas phase of the nasal swab samples (cyclohexanone, butanone-2,4-methyl-2-pentanone) were correlated with the clinical state of the animals, and were consistent with the reference data on disease markers in exhaled air established for destructive organism processes.