Cyclization of N-arylcyclopropanecarboxamides into N-arylpyrrolidin-2-ones under electron ionization and in the condensed phase.

RATIONALE: Mass spectrometry is known as an excellent method to predict the behavior of organic compounds in solution. The behavior of organic compounds in the gas phase inside the ion source of a mass spectrometer allows their intrinsic properties to be defined, avoiding the influence of intermolecular interactions, counter ions and solvent effects. METHODS: Arylpyrrolidin-2-ones were obtained by condensed-phase synthesis from the corresponding N-arylcyclopropanecarboxamides. Electron ionization (EI) with accurate mass measurements by high-resolution time-of-flight mass-spectrometry and quantum chemical calculations were used to understand the behavior of the molecular radical cations of N-arylcyclopropanecarboxamides and N-arylpyrrolidin-2-ones in the ion source of a mass spectrometer. The geometries of the molecules, transition states, and intermediates were fully optimized using DFT-PBE calculations. RESULTS: Fragmentation schemes, ion structures, and possible mechanisms of primary isomerisation were proposed for isomeric N-arylcyclopropanecarboxamides and N-arylpyrrolidin-2-ones. Based on the fragmentation pattern of the N-arylcyclopropanecarboxamides, isomerisation of the original M+• ions into the M+• ions of the N-arylpyrrolidin-2-ones was shown to be only a minor process. In contrast, this cyclization proceeds easily in the condensed phase in the presence of Brønsted acids. CONCLUSIONS: Based on the experimental data and quantum chemical calculations the principal mechanism of decomposition of the molecular ions of N-arylcyclopropanecarboxamides involves their direct fragmentation without any rearrangements. An alternative mechanism is responsible for the isomerisation of a small portion of the higher energy molecular ions into the corresponding N-arylpyrrolidin-2-one ions. Copyright © 2016 John Wiley & Sons, Ltd.

GC-HRMS with Complementary Ionization Techniques for Target and Non-target Screening for Chemical Exposure: Expanding the Insights of the Air Pollution Markers in Moscow Snow.

Environmental exposure assessment is an important step in establishing a list of local priority pollutants and finding the sources of the threats for proposing appropriate protection measures. Exposome targeted and non-targeted analysis as well as suspect screening may be applied to reveal these pollutants. The non-targeted screening is a challenging task and requires the application of the most powerful analytical tools available, assuring wide analytical coverage, sensitivity, identification reliability, and quantitation. Moscow, Russia, is the largest and most rapidly growing European city. That rapid growth is causing changes in the environment which require periodic clarification of the real environmental situation regarding the presence of the classic pollutants and possible new contaminants. Gas chromatography - high resolution time-of-flight mass spectrometry (GC-HR-TOFMS) with electron ionization (EI), positive chemical ionization (PCI), and electron capture negative ionization (ECNI) ion sources were used for the analysis of Moscow snow samples collected in the early spring of 2018 in nine different locations. Collection of snow samples represents an efficient approach for the estimation of long-term air pollution, due to accumulation and preservation of environmental contaminants by snow during winter period. The high separation power of GC, complementary ionization methods, high mass accuracy, and wide mass range of TOFMS allowed for the identification of several hundred organic compounds belonging to the various classes of pollutants, exposure to which could represent a danger to the health of the population. Although quantitative analysis was not a primary aim of the study, targeted analysis revealed that some priority pollutants exceeded the established safe levels. Thus, dibutylphthalate concentration was over 10-fold higher than its safe level (0.001 mg/L), while benz[a]pyrene concentration exceeded Russian maximal permissible concentration value of 5 ng/L in three samples. The large amount of information generated during the combination of targeted and non-targeted analysis and screening samples for suspects makes it feasible to apply the big data analysis to observe the trends and tendencies in the pollution exposome across the city.

Regression algorithm for calculating second-dimension retention indices in comprehensive two-dimensional gas chromatography.

Gas chromatography-mass spectrometry (GC-MS) is one of the most accurate, well developed, and reliable analytical tools for the analysis of volatile and semivolatile compounds. The GC-MS data have been extensively improved by enhancing the separation capacity via comprehensive two-dimensional gas chromatography (GC × GC). The reliability of the identification of the analytes in GC × GC-MS can be notably improved by applying the second-dimension retention index (2I) as additional analytical parameter along with the commonly used first dimension retention index (1I) and mass spectrum. A novel approach for calculating second-dimension retention indices (2I) for semivolatile organic compounds is proposed. It is noteworthy that the standards used in calculations are the same compounds recommended as internal standards by US EPA 8270 Method for analysis of semivolatile organic compounds. The new algorithm takes into account the analyte retention time and its retention temperature at the secondary column, (2tR) and (2TR), respectively. The experimental data collected with different primary oven temperature ramp rates and carrier gas flow rates have shown that the calculated by the proposed approach 2I values remain the same for each evaluated compound, drifting in a very narrow range. The proposed approach was tested using 100 organic compounds from various chemical classes including alkanes, phenols, nitrobenzenes, chlorinated hydrocarbons, anilines, polycyclic aromatic hydrocarbons (PAHs), phthalates, etc. The important advantage of the proposed 2I values for compounds of the same chemical origin (reference standards and analytes) involves applicability of well-known Lee's indices for non-polar phases. Therefore, the proposed approach can be used in targeted and non-targeted analysis of a wide range of organic compounds. The reduced version of the second dimension retention indices provides a valuable mapping of the homologues series of organic compounds, making their detection and identification easy and reliable.

Detection of semi-volatile compounds in cloud waters by GC×GC-TOF-MS. Evidence of phenols and phthalates as priority pollutants.

Although organic species are transported and efficiently transformed in clouds, more than 60% of this organic matter remains unspeciated. Using GCxGC-HRMS technique we were able to detect and identify over 100 semi-volatile compounds in 3 cloud samples collected at the PUY station (puy de Dôme mountain, France) while they were present at low concentrations in a very small sample volume (<25 mL of cloud water). The vast majority (∼90%) of the detected compounds was oxygenated, while the absence of halogenated organic compounds should be specially mentioned. This could reflect both the oxidation processes in the atmosphere (gas and water phase) but also the need of the compounds to be soluble enough to be transferred and dissolved in the cloud droplets. Furans, esters, ketones, amides and pyridines represent the major classes of compounds demonstrating a large variety of potential pollutants. Beside these compounds, priority pollutants from the US EPA list were identified and quantified. We found phenols (phenol, benzyl alcohol, p-cresole, 4-ethylphenol, 3,4-dimethylphenol, 4-nitrophenol) and dialkylphthalates (dimethylphthalate, diethylphthalate, di-n-butylphthalate, bis-(2-ethylhexyl)-phthalate, butylbenzylphthalate, di-n-octyl phthalate). In general, the concentrations of phthalates (from 0.09 to 52 µg L-1) were much higher than those of phenols (from 0.03 to 0.74 µg L-1). To our knowledge phthalates in clouds are described here for the first time. We investigated the variability of phenols and phthalates concentrations with cloud air mass origins (marine vs continental) and seasons (winter vs summer). Although both factors seem to have an influence, it is difficult to deduce general trends; further work should be conducted on large series of cloud samples collected in different geographic areas and at different seasons.

Semi volatile organic compounds in the snow of Russian Arctic islands: Archipelago Novaya Zemlya.

Environmental contamination of the Arctic has widely been used as a worldwide pollution marker. Various classes of organic pollutants such as pesticides, personal care products, PAHs, flame retardants, biomass burning markers, and many others emerging contaminants have been regularly detected in Arctic samples. Although numerous papers have been published reporting data from the Canadian, Danish, and Norwegian Arctic regions, the environmental situation in Russian Arctic remains mostly underreported. Snow analysis is known to be used for monitoring air pollution in the regions with cold climate in both short-term and long-term studies. This paper presents the results of a nontargeted study on the semivolatile organic compounds detected and identified in snow samples collected at the Russian Artic Archipelago Novaya Zemlya in June 2016. Gas chromatography coupled to a high-resolution time-of-flight mass spectrometer enabled the simultaneous detection and quantification of a variety of pollutants including those from the US Environmental Protection Agency (EPA) priority pollutants list, emerging contaminants (plasticizers, flame retardants-only detection), as well as the identification of novel Arctic organic pollutants, (e.g., fatty acid amides and polyoxyalkanes). The possible sources of these novel pollutants are also discussed. GC-HRMS enabled the detection and identification of emerging contaminants and novel organic pollutants in the Arctic, e.g., fatty amides and polyoxyalkanes.

Novel pollutants in the Moscow atmosphere in winter period: Gas chromatography-high resolution time-of-flight mass spectrometry study.

The most common mass spectrometry approach analyzing contamination of the environment deals with targeted analysis, i.e. detection and quantification of the selected (priority) pollutants. However non-targeted analysis is becoming more often the method of choice for environmental chemists. It involves implementation of modern analytical instrumentation allowing for comprehensive detection and identification of the wide variety of compounds of the environmental interest present in the sample, such as pharmaceuticals and their metabolites, musks, nanomaterials, perfluorinated compounds, hormones, disinfection by-products, flame retardants, personal care products, and many others emerging contaminants. The paper presents the results of detection and identification of previously unreported organic compounds in snow samples collected in Moscow in March 2016. The snow analysis allows evaluation of long-term air pollution in the winter period. Gas chromatography coupled to a high resolution time-of-flight mass spectrometer has enabled us with capability to detect and identify such novel analytes as iodinated compounds, polychlorinated anisoles and even Ni-containing organic complex, which are unexpected in environmental samples. Some considerations concerning the possible sources of origin of these compounds in the environment are discussed.